bluuebunny/crossref_metadata_2025 huggingface dataset:
Smoking Cessation Training and Treatment: Options for Cancer Centres
Authors: deRuiter Wayne K. , Barker Megan , Rahimi Alma , Ivanova Anna , Zawertailo Laurie , Melamed Osnat C. , Selby Peter
Published: March 2022

Patients who achieve smoking cessation following a cancer diagnosis can experience an improvement in treatment response and lower morbidity and mortality compared to individuals who continue to smoke. It is therefore imperative for publicly funded cancer centres to provide appropriate training and education for healthcare providers (HCP) and treatment options to support smoking cessation for their patients. However, system-, practitioner-, and patient-level barriers exist that hamper the integration of evidence-based cessation programs within publicly funded cancer centres. The integration of evidence-based smoking cessation counselling and pharmacotherapy into cancer care facilities could have a significant effect on smoking cessation and cancer treatment outcomes. The purpose of this paper is to describe the elements of a learning health system for smoking cessation, implemented and scaled up in community settings that can be adapted for ambulatory cancer clinics. The core elements include appropriate workflows enabled by technology, thereby improving both practitioner and patient experience and effectively removing practitioner-level barriers to program implementation. Integrating the smoking cessation elements of this program from primary care to cancer centres could improve smoking cessation outcomes in patients attending cancer clinics.
Challenges and Adaptations for Providing Smoking Cessation for Patients with Cancer across Canada during the COVID-19 Pandemic
Authors: Warren Graham W. , Silverman Caroline , Halligan Michelle
Published: March 2022

Smoking cessation after a cancer diagnosis can improve health outcomes, but the Coronavirus disease 2019 (COVID-19) pandemic significantly altered healthcare patterns and strained resources, including for smoking cessation support for cancer patients. A Network that included all 13 provinces and territories (jurisdictions) in Canada received funding and coordinated support from a national organization to implement access to smoking cessation support in cancer care between 2016 and 2021, including throughout the COVID-19 pandemic. Descriptive analyses of meetings between the organization and jurisdictions between March of 2020 and August of 2021 demonstrated that all jurisdictions reported disruptions of existing smoking cessation approaches. Common challenges include staff redeployment, inability to deliver support in person, disruptions in travel, and loss of connections with other clinical resources. Common adaptations included budget and workflow adjustments, transition to virtual approaches, partnering with other community resources, and coupling awareness of the harms of smoking and COVID-19. All jurisdictions reported adaptations that maintained or improved access to smoking cessation services. Collectively, data suggest coordinated national efforts to address smoking cessation in cancer care could be crucial to maintaining access during an international healthcare crisis.
Insights into Virus–Prokaryote Relationships in a Subtropical Danshui River Estuary of Northern Taiwan in Summer
Authors: Tsai An-Yi , Gong Gwo-Ching , Mukhanov Vladimir , Chen Patrichka Wei-Yi
Published: March 2022

In spite of the fact that the interactions between environmental parameters and prokaryotic and viral abundance have been explored in various aquatic environments, only a few independent estimates of viral production and decay in the estuarine region have been explored. In this study, data were analyzed for viral and prokaryotic abundance, viral production, and viral decay in a subtropical Danshui estuary in summer 2021. Prokaryotic abundance varied from 2.4 ± 0.6 × 105 to 12 ± 2.3 × 105 cells mL−1, and viral abundance ranged from 2.3 ± 0.9 × 105 to 6.9 ± 1.3 × 105 viruses mL−1 during the study period. Viral abundance was significantly correlated with prokaryotic abundance and chlorophyll a concentration. Furthermore, studies of changes in viral to prokaryotic abundance ratio (VPR) ranged from 0.42 ± 0.11 to 2.0 ± 0.25. Viral decay values were 2.1 ± 0.5 and 2.1 ± 0.3 × 104 virus mL−1h−1, and non-significant differences were observed between the inner estuary and coastal water region. Viral decay almost balanced gross viral production in this study. The dilution experiments revealed non-significant net viral production in July; thus, a lower VPR might be explained in this estuarine environment.
The Impact of Drying Temperature on Basidiospore Size
Authors: Hu Yuwei , Karunarathna Samantha C. , Li Huili , Galappaththi Mahesh C. A. , Zhao Chang-Lin , Kakumyan Pattana , Mortimer Peter E.
Published: March 2022

Fungal taxonomy research, and specifically the study of macro and micro morphological characteristics, requires precise temperature control. This is because variation in temperature can affect macrofungal microstructures. Understanding the appropriate temperature range for drying macrofungal fruitbodies is crucial to ensure consistent reports between studies. In this study, three macrofungal species, viz. Agaricus bisporus, Lentinula edodes, and Pleurotus ostreatus, were selected to compare basidiospore sizes in dried and fresh macrofungal fruitbodies. All three were dehydrated within 24 h of harvesting at five different temperatures: 30 °C, 35 °C, 40 °C, 45 °C, and 50 °C, with dehydration lasting 48 h. We measured a total of 1000 basidiospores at each temperature for each species. A linear regression model was used to monitor the relationship between drying temperature and the length, width, and Q value of the basidiospores. We found that drying temperature was negatively related, while Q value was positively related to basidiospore length and width. Analysis of variance shows significant changes in basidiospore size among different drying temperatures. Our data indicate that the optimal method for drying macrofungal fruitbodies is to use a temperature of 30 °C for 48 h and subsequently preserve the specimens with silica gel. Standardizing drying temperature is crucial for the study of macrofungi as basidiospore size is used as a discriminative taxonomic characteristic in macrofungal identification.
The First Deep-Sea Stylasterid (Hydrozoa, Stylasteridae) of the Red Sea
Authors: Maggioni Davide , Terraneo Tullia I. , Chimienti Giovanni , Marchese Fabio , Pica Daniela , Cairns Stephen D. , Eweida Ameer A. , Rodrigue Mattie , Purkis Sam J. , Benzoni Francesca
Published: March 2022

The Stylasteridae, commonly known as lace corals, is a family of colonial calcifying hydrozoans mostly inhabiting deep waters. Stylasterids show a cosmopolitan distribution but, in some areas, they are characterized by low species diversity, such as in the Red Sea, where only a shallow-water species has been reported so far. With this work, we provide the first evidence of a deep-sea stylasterid inhabiting the NEOM region in the northern Saudi Arabian Red Sea, at depths ranging between 166 and 492 m. Morphological examinations revealed that this species was previously unknown and belonging to the genus Stylaster. We, therefore, describe Stylaster tritoni sp. nov., representing the first record of the genus in the Red Sea. Lastly, the phylogenetic position of the species within the Stylasteridae was evaluated, revealing a close relationship with shallow-water Indo-Pacific and Western Atlantic Stylaster species and confirming the polyphyletic nature of the genus Stylaster.
Radiomic Detection of Malignancy within Thyroid Nodules Using Ultrasonography—A Systematic Review and Meta-Analysis
Authors: Cleere Eoin F. , Davey Matthew G. , O’Neill Shane , Corbett Mel , O’Donnell John P , Hacking Sean , Keogh Ivan J. , Lowery Aoife J. , Kerin Michael J.
Published: March 2022

Background: Despite investigation, 95% of thyroid nodules are ultimately benign. Radiomics is a field that uses radiological features to inform individualized patient care. We aimed to evaluate the diagnostic utility of radiomics in classifying undetermined thyroid nodules into benign and malignant using ultrasonography (US). Methods: A diagnostic test accuracy systematic review and meta-analysis was performed in accordance with PRISMA guidelines. Sensitivity, specificity, and area under curve (AUC) delineating benign and malignant lesions were recorded. Results: Seventy-five studies including 26,373 patients and 46,175 thyroid nodules met inclusion criteria. Males accounted for 24.6% of patients, while 75.4% of patients were female. Radiomics provided a pooled sensitivity of 0.87 (95% CI: 0.86–0.87) and a pooled specificity of 0.84 (95% CI: 0.84–0.85) for characterizing benign and malignant lesions. Using convolutional neural network (CNN) methods, pooled sensitivity was 0.85 (95% CI: 0.84–0.86) and pooled specificity was 0.82 (95% CI: 0.82–0.83); significantly lower than studies using non-CNN: sensitivity 0.90 (95% CI: 0.89–0.90) and specificity 0.88 (95% CI: 0.87–0.89) (p < 0.05). The diagnostic ability of radiologists and radiomics were comparable for both sensitivity (OR 0.98) and specificity (OR 0.95). Conclusions: Radiomic analysis using US provides a reproducible, reliable evaluation of undetermined thyroid nodules when compared to current best practice.
The ETS Homologous Factor (EHF) Represents a Useful Immunohistochemical Marker for Predicting Prostate Cancer Metastasis
Authors: Scimeca Manuel , Montanaro Manuela , Bonfiglio Rita , Anemona Lucia , Agrò Enrico Finazzi , Asimakopoulos Anastasios D. , Bei Roberto , Manzari Vittorio , Urbano Nicoletta , Giacobbi Erica , Servadei Francesca , Bonanno Elena , Schillaci Orazio , Mauriello Alessandro
Published: March 2022

The main aim of this study was to investigate the risk of prostate cancer metastasis formation associated with the expression of ETS homologous factor (EHF) in a cohort of bioptic samples. To this end, the expression of EHF was evaluated in a cohort of 152 prostate biopsies including primary prostate cancers that developed metastatic lesions, primary prostate cancers that did not develop metastasis, and benign lesions. Data here reported EHF as a candidate immunohistochemical prognostic biomarker for prostate cancer metastasis formation regardless of the Gleason scoring system. Indeed, our data clearly show that primary lesions with EHF positive cells ≥40% had a great risk of developing metastasis within five years from the first diagnosis. Patients with these lesions had about a 40-fold increased risk of developing metastasis as compared with patients with prostate lesions characterized by a percentage of EHF positive cells ≤30%. In conclusion, the immunohistochemical evaluation of EHF could significantly improve the management of prostate cancer patients by optimizing the diagnostic and therapeutic health procedures and, more important, ameliorating the patient’s quality of life.
Early Markers in Resistant Schizophrenia: Effect of the First Antipsychotic Drug
Authors: Panov Georgi Panov
Published: March 2022

Background: Schizophrenia is a mental illness with a multifactorial etiology and clinical presentation. Treatment is mainly with antipsychotic drugs. Despite the increasing number of antipsychotic drugs, there has been no significant change in the percentage of resistant cases. These data gave us reason to look for a link between the effect of the first individually selected antipsychotic drug and the established resistance to therapy. Method: An assessment has been made of 105 patients with chronic schizophrenia with consecutive psychotic episodes. The choice of antipsychotic has been made on the basis of clinical features, history of efficacy of previously used neuroleptics, anthropometric features, as well as somatic comorbidities. Accidental use of benzodiazepines in anxiety conditions as well as correctors in indications for extrapyramidal problems have been reported. Assessment was made based on clinical observation as well as on changes in PANSS score. Results: Of the 105 observed patients, the effectiveness of the first antipsychotic effect was found in 46.7% of patients. Follow-up of patients for a period of 12 weeks revealed that 45 (42.8%) of them had resistant schizophrenia, while the remaining 60 (57.2%) achieved clinical remission and initial functional recovery. The effect of the first antipsychotic drug was established in 9 (20%) of the patients with resistant schizophrenia and in 40 (66.57%) of the patients in clinical remission. Conclusion: The evaluation of the first antipsychotic medication is significant for the prognosis of patients with schizophrenia. Its lack of effectiveness indicates a high probability of resistance and can be a good indicator of earlier change and a possible search for more “aggressive” measures to prevent future resistance and possible disability.
Three-Dimensional Echocardiography Assessment of Right Ventricular Volumes and Function: Technological Perspective and Clinical Application
Authors: Ahmad Ashfaq , Li He , Zhang Yanting , Liu Juanjuan , Gao Ying , Qian Mingzhu , Lin Yixia , Yi Luyang , Zhang Li , Li Yuman , Xie Mingxing
Published: March 2022

Right ventricular (RV) function has important prognostic value in a variety of cardiovascular diseases. Due to complex anatomy and mode of contractility, conventional two-dimensional echocardiography does not provide sufficient and accurate RV function assessment. Currently, three-dimensional echocardiography (3DE) allows for an excellent and reproducible assessment of RV function owing to overcoming these limitations of traditional echocardiography. This review focused on 3DE and discussed the following points: (i) acquisition of RV dataset for 3DE images, (ii) reliability, feasibility, and reproducibility of RV volumes and function measured by 3DE with different modalities, (iii) the clinical application of 3DE for RV function quantification.
Sex-Specific Differences in Cardiovascular Risk, Risk Factors and Risk Management in the Peripheral Arterial Disease Population
Authors: Pouncey Anna Louise , Woodward Mark
Published: March 2022

Cardiovascular disease (CVD) is the leading cause of mortality in women worldwide but has been primarily recognised as a man’s disease. The major components of CVD are ischaemic heart disease (IHD), stroke and peripheral arterial disease (PAD). Compared with IHD or stroke, individuals with PAD are at significantly greater risk of major cardiovascular events. Despite this, they are less likely to receive preventative treatment than those with IHD. Women are at least as affected by PAD as men, but major sex-specific knowledge gaps exist in the understanding of relevant CVD risk factors and efficacy of treatment. This prompted the American Heart Association to issue a “call to action” for PAD in women, in 2012. Despite this, PAD and CVD risk in women continues to be under-recognised, leading to a loss of opportunity to moderate and prevent CVD morbidity. This review outlines current evidence regarding cardiovascular risk in women and men with PAD, the relative significance of traditional and non-traditional risk factors and sex differences in cardiovascular risk management.
A Low Sampling Rate Receiver Design for Multi-Antenna Multi-User OFDM Systems
Authors: Ou Zeliang , Liu Xiaofeng , Yang Hongwen
Published: March 2022

The future 6G mobile communication network will support an unprecedented amount of Internet of Things (IoT) devices, which will boost the demand for low cost terminals under the principle of green communication. One of the critical issues for low cost terminals is the sampling rate of analog-to-digital converters (ADCs) at the receivers. A high sampling rate of the ADC gives rise to a high energy consumption and high hardware cost for the terminal. In the conventional multi-user OFDM systems, all users have to sample the received signal with a sampling rate that is larger than or equal to the Nyquist rate, despite only a small fraction of the bandwidth (number of subcarriers) is allocated to each user. This paper proposes a low sampling rate receiver design for multi-antenna multi-user OFDM systems. With the aid of zero-forcing precoding, the sampling rate of the receiver can be reduced to 1/K of the Nyquist rate, where K is the number of users. The simulation results show that with a significant reduction in sampling rate, performance loss is insignificant and acceptable in terms of bit error rate, mutual information and peak-to-average power ratio.
Thermodynamic Irreversibility Analysis of Dual-Skin Chest-Freezer
Authors: Matsuda Vinicius Akyo , Gardenghi Álvaro Roberto , Tibiriçá Cristiano Bigonha , Cabezas-Gómez Luben
Published: March 2022

In this work, a transient analysis of a dual-skin chest-freezer refrigeration system, operating with R290, is studied numerically with the purpose of performing the characterization of the system through the second law of thermodynamics. A mathematical model which accounts for refrigerant mass distribution inside the system is used. In addition, this work addresses the calculation of entropy generation and exergy destruction for characterizing the system performance during its operations. In order to validate the model, a comparison with measured experimental data is performed for both pull-down and on-off operations. The characterization of the system through the second law of thermodynamics is conducted using two different methods. One consists of a direct calculation of the entropy generation rate and the second one in the calculation of exergy destruction rate. The equivalence of these two methods is used as an indicative of the “correctness” of the performed calculations. The model results agree near 97% with the experimental data used in the comparisons. Entropy generation and exergy destruction results along time for the whole system and in its individual components are characterized with the second law. These results are very useful for improving refrigeration system design.
Numerical Analysis and Comparison of Four Stabilized Finite Element Methods for the Steady Micropolar Equations
Authors: Liu Jingnan , Liu Demin
Published: March 2022

In this paper, four stabilized methods based on the lowest equal-order finite element pair for the steady micropolar Navier–Stokes equations (MNSE) are presented, which are penalty, regular, multiscale enrichment, and local Gauss integration methods. A priori properties, existence, uniqueness, stability, and error estimation based on Fem approximation of all the methods are proven for the physical variables. Finally, some numerical examples are displayed to show the numerical characteristics of these methods.
A Compression-Based Multiple Subword Segmentation for Neural Machine Translation
Authors: Nonaka Keita , Yamanouchi Kazutaka , I Tomohiro , Okita Tsuyoshi , Shimada Kazutaka , Sakamoto Hiroshi
Published: March 2022

In this study, we propose a simple and effective preprocessing method for subword segmentation based on a data compression algorithm. Compression-based subword segmentation has recently attracted significant attention as a preprocessing method for training data in neural machine translation. Among them, BPE/BPE-dropout is one of the fastest and most effective methods compared to conventional approaches; however, compression-based approaches have a drawback in that generating multiple segmentations is difficult due to the determinism. To overcome this difficulty, we focus on a stochastic string algorithm, called locally consistent parsing (LCP), that has been applied to achieve optimum compression. Employing the stochastic parsing mechanism of LCP, we propose LCP-dropout for multiple subword segmentation that improves BPE/BPE-dropout, and we show that it outperforms various baselines in learning from especially small training data.
Run-Time Adaptive In-Kernel BPF/XDP Solution for 5G UPF
Authors: Navarro do Amaral Thiago A. , Rosa Raphael V. , Moura David F. Cruz , Esteve Rothenberg Christian
Published: March 2022

Flexibility is considered a key feature of 5G softwarization to deliver a timely response to changes in network requirements that may be caused by traffic variation, user mobility, dynamic network function chains, slice lifecycle management operations, among others. In this article, we evolve the upf-bpf1 open-source project by proposing a new design to improve its flexibility by reducing the run-time adaptation time. The project proposes an in-kernel solution based on BPF and eXpress Data Path (XDP) for 5G User Plane Function (UPF) implementations. The Just-In-Time (JIT) compilation may have a huge impact on the adaptation time due to the in-kernel verification of the BPF programs at run-time. Our results show latency improvements of around 95% to inject the BPF program into the Linux kernel. Furthermore, the solution keeps the same functionalities and delivers a packet processing performance of around 10–11 Mpps using 6 cores with almost 70% of the CPU utilization in downlink/uplink directions.
Design and Control of Ultra-High-Speed Sensorless Drive with Two-Input Power Source for Portable Consumer Electronics
Authors: Lee Dong-Geun , Kim Rae-Young
Published: March 2022

The convenience and usability of portable consumer electronics that require a motor, such as vacuum cleaners and hair dryers, will be greatly improved if both ac and dc two-input power sources can be used. The dc input power is mostly composed of a dc battery, and single-phase voltage is used as ac input power. A converter system capable of converting ac and dc voltage with control technology is required to supply the voltage for motor driving to apply both ac and dc input to the product. Because a limited number of batteries are used to decrease the weight and size of portable products, a system such as a dc converter is necessary to supply the voltage required to operate the motor and to keep the voltage fluctuation according to the usage time constant. When ac power is used in the product, a voltage drop system that can step down the ac voltage to supply voltage to the dc link is necessary to supply the voltage required to operate the motor to the dc-link. In addition, it is important to reduce the size of the system through ultra-high-speed motor operation by increasing the rotation speed because portable consumer electronics that include a motor drive should be light and portable. This paper proposed a system that can supply a stable dc-link voltage required for ultra-high-speed motor control by applying a phase control method to the ac input side and a dc boost converter to the dc input side. Furthermore, the 1-shunt sensorless method was applied to the inverter for ultra-high-speed motor design and ultra-high-speed motor control system that contributes to product miniaturization and material cost reduction, experimental verification. The ultra-high-speed motor driving evaluation under ac and dc input power conditions and the conversion to dc power input when ac power interrupt occurs were performed to more stably verify the system according to the input power change.
Lightweight Challenge-Response Authentication in SDN-Based UAVs Using Elliptic Curve Cryptography
Authors: Usman Muhammad , Amin Rashid , Aldabbas Hamza , Alouffi Bader
Published: March 2022

Unmanned aerial vehicles (UAVs) (also known as drones) are aircraft that do not require the presence of a human pilot to fly. UAVs can be controlled remotely by a human operator or autonomously by onboard computer systems. UAVs have many military uses, including battlefield surveillance, effective target tracking and engagement in air-to-ground warfare, and situational awareness in challenging circumstances. They also offer a distinct advantage in various applications such as forest fire monitoring and surveillance. Surveillance systems are developed using advanced technologies in the modern era of communications and networks. As a result, UAVs require enhancements to control and manage systems efficiently. Network security is a critical concern with respect to UAVs due to the risk of surveillance information theft and physical misuse. Although several new tools have been introduced to secure networks, attackers can use more advanced methods to get into a UAV network and create problems that pose an organizational threat to the entire system. Security mechanisms also reduce the performance of systems because some restrictive measures prevent users from accessing specific resources, but a few techniques and tools have overcome the problem of performance reduction in various scenarios. There are many types of attacks, i.e., denial of service attacks (DOS), distributed denial of service attacks (DDOS), address resolution protocol (ARP) spoofing, sniffing, etc., that make it challenging to maintain a UAV network. This research paper proposes a lightweight challenge-response authentication that can overcome the previously mentioned problems. As security is provided by utilizing a minimum number of bits in memory, this technique offers the same security features while using fewer network resources, low computing resources, and low power consumption.
Dynamic Task Allocation of Multiple UAVs Based on Improved A-QCDPSO
Authors: Zhang Jiandong , Chen Yuyang , Yang Qiming , Lu Yi , Shi Guoqing , Wang Shuo , Hu Jinwen
Published: March 2022

With the rapid changes in the battlefield situation, the requirement of time for UAV groups to deal with complex tasks is getting higher, which puts forward higher requirements for the dynamic allocation of the UAV group. However, most of the existing methods focus on task pre-allocation, and the research on dynamic task allocation technology during task execution is not sufficient. Aiming at the high real-time requirement of the multi-UAV collaborative dynamic task allocation problem, this paper introduces the market auction mechanism to design a discrete particle swarm algorithm based on particle quality clustering by a hybrid architecture. The particle subpopulations are dynamically divided based on particle quality, which changes the topology of the algorithm. The market auction mechanism is introduced during particle initialization and task coordination to build high-quality particles. The algorithm is verified by constructing two emergencies of UAV sudden failure and a new emergency task.
A Survey of Network-Based Hardware Accelerators
Authors: Skliarova Iouliia
Published: March 2022

Many practical data-processing algorithms fail to execute efficiently on general-purpose CPUs (Central Processing Units) due to the sequential matter of their operations and memory bandwidth limitations. To achieve desired performance levels, reconfigurable (FPGA (Field-Programmable Gate Array)-based) hardware accelerators are frequently explored that permit the processing units’ architectures to be better adapted to the specific problem/algorithm requirements. In particular, network-based data-processing algorithms are very well suited to implementation in reconfigurable hardware because several data-independent operations can easily and naturally be executed in parallel over as many processing blocks as actually required and technically possible. GPUs (Graphics Processing Units) have also demonstrated good results in this area but they tend to use significantly more power than FPGA, which could be a limiting factor in embedded applications. Moreover, GPUs employ a Single Instruction, Multiple Threads (SIMT) execution model and are therefore optimized to SIMD (Single Instruction, Multiple Data) operations, while in FPGAs fully custom datapaths can be built, eliminating much of the control overhead. This review paper aims to analyze, compare, and discuss different approaches to implementing network-based hardware accelerators in FPGA and programmable SoC (Systems-on-Chip). The performed analysis and the derived recommendations would be useful to hardware designers of future network-based hardware accelerators.
TCSA: A Traffic Congestion Situation Assessment Scheme Based on Multi-Index Fuzzy Comprehensive Evaluation in 5G-IoV
Authors: Liu Li , Lian Minjie , Lu Caiwu , Zhang Sai , Liu Ruimin , Xiong Neal
Published: March 2022

The traffic congestion situation is an important reference indicator for the orderly control and management of traffic systems. As intelligent transport systems (ITS) become increasingly popular, the challenge of realizing real-time traffic congestion situation assessments (TCSAs) in the post-traffic era is particularly important. In this study, we propose a TCSA scheme for multi-metric fuzzy integrated evaluation based on three predicted vehicle traffic parameters for the 5G Internet of Vehicles (5G-IoV) environment, which is dedicated to accelerating the development of ITS. Firstly, the scheme uses dynamic multi-model adaptive exponential smoothing (DMMAES), which can calculate the optimal smoothing coefficients and weight of each model based on historical prediction errors to predict the average speed and traffic volume and then calculate the predicted traffic speed, traffic flow density, and road saturation of the three traffic congestion indicators. Secondly, the predicted values of the three traffic congestion indicators are used as fuzzy comprehensive evaluation, taking into account the vagueness of the traffic congestion levels, the uncertainty of the indicators, and the conflict among the indicators, using a trapezoidal affiliation function to determine the degree of affiliation of each indicator through the adaptive CRITIC method to determine the weights. Finally, the predicted traffic congestion situations are classified into five levels. The effectiveness of the scheme was verified by the measured data of Yanta North Road in Xi’an. The results showed that the traffic congestion level predicted by TCSA was basically consistent with the actual situation and had a high prediction accuracy.
Recommending Reforming Trip to a Group of Users
Authors: Abbas Rizwan , Amran Gehad Abdullah , Alsanad Ahmed , Ma Shengjun , Almisned Faisal Abdulaziz , Huang Jianfeng , Al Bakhrani Ali Ahmed , Ahmed Almesbahi Belal , Alzahrani Ahmed Ibrahim
Published: March 2022

With the quick evolution of mobile apps and trip guidance technologies, a trip recommender that recommends sequential points of interest (POIs) to travelers has emerged and recently received popularity. Compared to other outing recommenders, which suggest the following single POI, our proposed trip proposal research centers around the POI sequence proposal. An advanced sequence of the POI recommendation system named Recommending Reforming Trip (RRT) is presented, recommending a dynamic sequence of POIs to a group of users. It displays the information progression in a verifiable direction, and the output produced is the arrangement of POIs to be expected for a group of users. A successful plan is executed depending upon the deep neural network (DNN) to take care of this sequence-to-sequence problem. From start to finish of the work process, RRT can permit the input to change over time by smoothly recommending a dynamic sequence of POIs. Moreover, two advanced new estimations, adjusted precision (AP) and sequence-mindful precision (SMP), are introduced to analyze the recommended precision of a sequence of POIs. It considers the POIs’ consistency and also meets the sequence of order. We evaluate our algorithm using users’ travel histories extracted from a Weeplaces dataset. We argue that our algorithm outperforms various benchmarks by satisfying user interests in the trips.
Control of the Solar Radiation Reception Rate (SRRR) Using a Novel Poly-Tilted Segmented Panel (PTSP) in the Region of Makkah, Saudi Arabia
Authors: Alqurashi Faris , Nciri Rached , Alghamdi Abdulrahman , Ali Chaouki , Nasri Faouzi
Published: March 2022

This work deals with controlling the solar radiation reception rate (SRRR) (ratio of the incident solar radiation on tilted panel to the global incident solar radiation). Controlling the SRRR will permit the amount of the received solar energy on solar panels to be adjusted. This SRRR control is very useful for several technological applications such as solar thermal and photovoltaic technologies in extremely sunny regions around the world, such as the case of Makkah, Saudi Arabia. Thus, the sustainability of the cities and villages, located in such regions, is promoted. A novel design proposing a poly-tilted segmented panel (PTSP) is proposed as an original techno-logical solution enabling the control of the SRRR. Design technical details are clearly explained. The proposed design presents a cheap, simple and effective alternative to conventional sun tracking systems. The SRRR on the proposed PTSP is mathematically modeled. The influence of the combinations “number of segment/tilt angles” on the SRRR is assessed for the most significant days in the year: equinox, summer solstice and winter solstice. A specific “document-aided design”, showing the SRRR level reached by each specific combination “num-ber of segment/tilt angles”, is provided. Based on these documents, the adequate combination “number of segment/tilt angles” is easily determined by knowing the desired SRRR level. The SRRR level is determined based on the global incident solar radiation and the desired level of the incident so-lar radiation on the tilted panel. Results are properly presented, discussed and interpreted for each segment/tilt angles combination.
Advancements in Hydropower Design and Operation for Present and Future Electrical Demand
Authors: Cimbala John , Lewis Bryan
Published: March 2022

With the current infrastructure, meeting the ever-growing demand for electrical energy across the globe is becoming increasingly difficult [...]
Power Flow Optimization and Economic Analysis Based on High Voltage Phase Shifting Transformer
Authors: Yu Mengze , Yuan Jiaxin , Li Zuohong , Li Feng , Yang Xinyi , Zhang Weizhe , Xu Shunkai , Mei Jiajun
Published: March 2022

With the development of power systems, the power flow problem of transmission line is becoming more and more prominent. This paper presents a power flow regulation method based on phase shifting transformer (PST). Firstly, the working principle and performance of PST are analyzed. Then, the simulation model of BPA multi node system is established. PST access reduces the line imbalance to less than 8%. On this basis, considering the influence of saturation effect and leakage reactance, a PST suitable for 220 kV power grid is designed. Three different working conditions are simulated by PSCAD software. Under normal working conditions and N-1 conditions, PST can increase the transmission limit of the ring network section by more than 20%. When a short-circuit fault occurs, PST can also suppress the fault current. For 220 kV practical projects, unified power flow controller (UPFC) has faster response speed and stronger performance, but PST is more economical and reliable, and the equipment cost is 49.86% lower than that of UPFC. The power flow regulation method based on PST has good steady-state effect. It can improve the utilization efficiency of power grid assets and optimize the power flow distribution in a short time and at low cost.
Advance Energy Harvesting Technologies
Authors: Zhu Dibin
Published: March 2022

Energy harvesting is the conversion of unused or wasted energy in the ambient environment into useful electrical energy [...]
Correlations for Convective Laminar Heat Transfer of Carreau Fluid in Straight Tube Flow
Authors: Kim Sun Kyoung
Published: March 2022

Correlations for the Nusselt number for the fully-developed laminar flow of Carreau fluids through circular pipe subject to a uniform heat flux have been sought. Based on the mathematical expression, the Nusselt number could be obtained by numerical integration. To evaluate the Nusselt number for many conditions, an efficient integration method has been proposed. Using the obtained Nusselt number for different material constants and flow conditions, an improved correlation method has been proposed. The proposed correlation could reduce the maximum error from 3% to 0.9%.
Spectral Kurtosis Based Methodology for the Identification of Stationary Load Signatures in Electrical Signals from a Sustainable Building
Authors: Romero-Ramirez Luis A. , Elvira-Ortiz David A. , Romero-Troncoso Rene de J. , Osornio-Rios Roque A. , Zorita-Lamadrid Angel L. , Gonzalez-Gonzalez Sergio L. , Morinigo-Sotelo Daniel
Published: March 2022

The increasing use of nonlinear loads in the power grid introduces some unwanted effects, such as harmonic and interharmonic contamination. Since the existence of spectral contamination causes waveform distortion that may be harmful to the loads that are connected to the grid, it is important to identify the frequency components that are related to specific loads in order to determine how relevant their contribution is to the waveform distortion levels. Due to the diversity of frequency components that are merged in an electrical signal, it is a challenging task to discriminate the relevant frequencies from those that are not. Therefore, it is necessary to develop techniques that allow performing this selection in an efficient way. This paper proposes the use of spectral kurtosis for the identification of stationary frequency components in electrical signals along the day in a sustainable building. Then, the behavior of the identified frequencies is analyzed to determine which of the loads connected to the grid are introducing them. Experimentation is performed in a sustainable building where, besides the loads associated with the normal operation of the building, there are several power electronics equipment that is used for the electric generation process from renewable sources. Results prove that using the proposed methodology it is possible to detect the behavior of specific loads, such as office equipment and air conditioning.
Effects of Polyoxymethylene Dimethyl Ethers Addition in Diesel on Real Driving Emission and Fuel Consumption Characteristics of a CHINA VI Heavy-Duty Vehicle
Authors: Gu Haoming , Liu Shenghua , Wei Yanju , Liu Xibin , Zhu Xiaodong , Li Zheyang
Published: March 2022

Polyoxymethylene dimethyl ethers (PODE), as the most potential oxygenated alternative fuel for diesel engines, is widely investigated. Considering the importance of research on real driving emissions (RDE) and the few studies focus on the emission characteristics of the PODE/diesel blended fuels under real driving conditions, a portable emission measurement system (PEMS) was applied to measure the RDE of a heavy-duty tractor fueled with diesel or PODE/diesel blends. The tests were carried out in accordance with the relevant regulations of the CHINA VI emission standards. The second-by-second data from PEMS and the OBD system were utilized to construct engine transient operating maps. The results indicated that the addition of PODE can still decrease CO and PN emissions significantly under real driving conditions, although the low load conditions are still the areas of high brake specific CO and brake specific PN emissions. The NOx emissions, however, were not reduced as the results of the steady-state experiment of the same model of the engine. Fuel mass consumption raised when PODE was added, while the overall brake thermal efficiency improved, especially for the blending ratio of 30%, up to 40.3%, which is higher than 38.4% of pure diesel operation.
A Type-2 Fuzzy Controller to Enable the EFR Service from a Battery Energy Storage System
Authors: Cantillo-Luna Sergio , Moreno-Chuquen Ricardo , Gonzalez-Longatt Francisco , Chamorro Harold R.
Published: March 2022

The increased use of distributed energy resources, especially electrical energy storage systems (EESS), has led to greater flexibility and complexity in power grids, which has led to new challenges in the operation of these systems, with particular emphasis on frequency regulation. To this end, the transmission system operator in Great Britain has designed a control scheme known as Enhanced Frequency Response (EFR) that is especially attractive for its implementation in EESS. This paper proposes a Type-2 fuzzy control system that enables the provision of EFR service from a battery energy storage system in order to improve the state-of-charge (SoC) management while providing EFR service from operating scenarios during working and off-duty days. The performance of the proposed controller is compared with a conventional FLC and PID controllers with similar features. The results showed that in all scenarios, but especially under large frequency deviations, the proposed controller presents a better SoC management in comparison without neglecting the EFR service provision.
Optimal Calibration of an Adaptive and Predictive Energy Management Strategy for Fuel Cell Electric Trucks
Authors: Ferrara Alessandro , Zendegan Saeid , Koegeler Hans-Michael , Gopi Sajin , Huber Martin , Pell Johannes , Hametner Christoph
Published: March 2022

Energy management strategies have a significant impact on the hydrogen economy of fuel cell trucks and the lifetime of battery and fuel cell systems. This contribution presents the design and optimal calibration of an energy management strategy that is adaptive to the battery and ambient temperatures. Indeed, fuel cell trucks face critical operating conditions due to high ambient temperatures or high loads on long uphill roads. However, the presented adaptive energy management strategy shifts the electric loads to the fuel cell system to limit the battery usage, avoiding accelerated degradation due to battery temperature peaks without hindering the hydrogen economy. The strategy design and calibration involves a multi-objective optimization of performance indicators related to hydrogen consumption, fuel cell degradation, battery thermal state, equivalent charge/discharge cycles, and charge control. This work uses AVL CAMEO to systematically vary the adaptive curve parameters to explore the trade-off between the key performance indicators. The calibration considers real-world driving cycles of road freight vehicles, including measured speed, road elevation, and variable vehicle mass. Moreover, the energy management design is robust because the performance indicators are evaluated over 8935 km, covering an extensive range of real-world driving scenarios. Eventually, the adaptive and predictive energy management strategy proposed in this work can meet all the performance targets thanks to the optimal calibration, and it is particularly effective in avoiding battery temperature peaks.
A Study on the Modeling Method of Cage Slip and Its Effects on the Vibration Response of Rolling-Element Bearing
Authors: Luo Ya , Tu Wenbing , Fan Chunyu , Zhang Lu , Zhang Yudong , Yu Wennian
Published: March 2022

Rolling-element bearings play vital roles in the dynamic vibration performance of the whole machinery. Hence, accurate modeling and assessment of the rolling-element bearing are beneficial for the well understanding of the vibration response of rolling-element bearing. However, cage slip is usually ignored in the traditional rolling-element bearing modeling methods, which has a direct influence on the rotating speed and friction force of the rolling elements. To settle the modeling problem of rolling-element bearing with cage slip, in this study, a nonlinear dynamic model with multiple degrees of freedom of the roller bearing is established. The cage slip, the motion of each roller, nonlinear contact, damping, and friction are taken into consideration. With the proposed method, a nonlinear traction model is presented to describe the friction forces induced by cage slip. Furthermore, both the friction force acting on rolling elements and the effects of cage slip on the vibration response are investigated based on the established model. Some comparisons between the proposed modeling method with cage slip and the classical method without cage slip are made. The results show that the friction force applied to the balls increases with the cage slip, friction coefficient, rotational speed, and radial load. A slight cage slip could be beneficial for reducing the vibration energy of rolling-element bearing; however, it will result in more friction loss and impact components.
Optimization of Well Control during Gas Flooding Using the Deep-LSTM-Based Proxy Model: A Case Study in the Baoshaceng Reservoir, Tarim, China
Authors: Feng Qihong , Wu Kuankuan , Zhang Jiyuan , Wang Sen , Zhang Xianmin , Zhou Daiyu , Zhao An
Published: March 2022

Gas flooding has proven to be a promising method of enhanced oil recovery (EOR) for mature water-flooding reservoirs. The determination of optimal well control parameters is an essential step for proper and economic development of underground hydrocarbon resources using gas injection. Generally, the optimization of well control parameters in gas flooding requires the use of compositional numerical simulation for forecasting the production dynamics, which is computationally expensive and time-consuming. This paper proposes the use of a deep long-short-term memory neural network (Deep-LSTM) as a proxy model for a compositional numerical simulator in order to accelerate the optimization speed. The Deep-LSTM model was integrated with the classical covariance matrix adaptive evolutionary (CMA-ES) algorithm to conduct well injection and production optimization in gas flooding. The proposed method was applied in the Baoshaceng reservoir of the Tarim oilfield, and shows comparable accuracy (with an error of less than 3%) but significantly improved efficiency (reduced computational duration of ~90%) against the conventional numerical simulation method.
Short Text Classification for Faults Information of Secondary Equipment Based on Convolutional Neural Networks
Authors: Liu Jiufu , Ma Hongzhong , Xie Xiaolei , Cheng Jun
Published: March 2022

As the construction of smart grids is in full swing, the number of secondary equipment is also increasing, resulting in an explosive growth of power big data, which is related to the safe and stable operation of power systems. During the operation of the secondary equipment, a large amount of short text data of faults and defects are accumulated, and they are often manually recorded by transportation inspection personnel to complete the classification of defects. Therefore, an automatic text classification based on convolutional neural networks (CNN) is proposed in this paper. Firstly, the topic model is used to mine the global features. At the same time, the word2vec word vector model is used to mine the contextual semantic features of words. Then, the improved LDA topic word vector and word2vec word vector are combined to absorb their respective advantages and utilizations. Finally, the validity and accuracy of the model is verified using actual operational data from the northwest power grid as case study.
Distribution Locational Marginal Price Based Transactive Energy Management in Distribution Systems with Smart Prosumers—A Multi-Agent Approach
Authors: Amanbek Yerasyl , Kalakova Aidana , Zhakiyeva Svetlana , Kayisli Korhan , Zhakiyev Nurkhat , Friedrich Daniel
Published: March 2022

This work proposes a distribution locational marginal price (DLMP)-based transactive energy (TE) framework for distribution systems with enthusiastic or smart prosumers. The framework uses a multi-agent system (MAS) as the basis on which the proposed TE model, i.e., distribution locational marginal price (DLMP) based TE management system (DTEMS), is implemented. DTEMS uses a novel metric known as the nodal earning component, which is determined by the optimal power flow (OPF) based smart auction mechanism, to schedule the TE transactions optimally among the stakeholders by alleviating the congestion in the distribution system. Based on the individual contributions to the congestion relief, DTEMS ranks the prosumers and loads as most valuable players (MVP) and assigns the energy trading price according to the category of the player. The effectiveness of the proposed TE model is verified by simulating the proposed DTEMS for a modified 33 bus radial distribution system fed with various plug-able energy resources, prosumers, and microgrids.