bluuebunny/crossref_metadata_2025 huggingface dataset:
Genus Apterocuris Jacobson, 1901 (Coleoptera: Chrysomelidae) in the Subfamily Chrysomelinae with Description of a New Species and Remarks on Significance of Preimaginal Characters
Authors: Mikhailov Yuri E.
Published: February 2023

For Apterocuris Jacobson, 1901, formerly considered a monotypic genus endemic to South Siberia, a second congener is described from the Central Sikhote-Alin’ Mountains in the Far East of Russia. Apterocuris brinevi sp. n. differs from A. sibirica Jacobson, 1901 in the rather convex body, shining smooth dorsum, absence of rectangular projecting basilateral angles of elytra, and only two or three distinct striae of elytral punctures. For Apterocuris sibirica, the pupa is first described, imago redescribed, and the revised distribution is mapped. The place of Apterocuris in the tribe Chrysomelini is discussed and its similarity to the genus Sclerophaedon Weise, 1882 considered. Both genera have pupae with two urogomphi that should place them into the subtribe Entomoscelina, but their adults with open anterior coxal cavities do not fit the subtribe diagnosis. Therefore, re-establishment of the subtribe Sclerophaedonina Steinhausen, 1996 is proposed to place the genera Sclerophaedon, Apterocuris, Colaphellus Weise, 1916 and Colaspidema Laporte, 1833. A triple key to the genera of the tribe Chrysomelini based on the combination of larval, pupal and imaginal characters is presented.
A Global Multiscale SPEI Dataset under an Ensemble Approach
Authors: Santini Monia , Noce Sergio , Mancini Marco , Caporaso Luca
Published: February 2023

A new multiscale Standardized Precipitation Evapotranspiration Index (SPEI) dataset is provided for a reference period (1960–1999) and two future time horizons (2040–2079) and (2060–2099). The historical forcing is based on combined climate observations and reanalysis (WATer and global CHange Forcing Dataset), and the future projections are fed by the Fast Track experiment of the Inter-Sectoral Impact Model Intercomparison Project under representative concentration pathways (RCPs) 4.5 and 8.5 and by an additional Earth system model (CMCC-CESM) forced by RCP 8.5. To calculate the potential evapotranspiration (PET) input to the SPEI, the Hargreaves–Samani and Thornthwaite equations were adopted. This ensemble considers uncertainty due to different climate models, development pathways, and input formulations. The SPEI is provided for accumulation periods of potential moisture deficit from 1 to 18 months starting in each month of the year, with a focus on the within-period variability, excluding long-term warming effects on PET. In addition to supporting drought analyses, this dataset is also useful for assessing wetter-than-normal conditions spanning one or more months. The SPEI was calculated using the SPEIbase package.
Hyperammonemic Encephalopathy in a Patient with Pancreatic Neuroendocrine Tumor and Portosystemic Shunt
Authors: Zorgdrager Marcel , Cuperus Frans J. C. , de Haas Robbert J.
Published: February 2023

Hyperammonemia can lead to encephalopathy and may be accompanied by a diagnostic dilemma. Imaging as well as biochemical analyses are the cornerstone for identifying possible underlying causes such as severe liver disease or urea cycle defect. We report a case of a patient that presented with neurological deficits based on hyperammonemia in the presence of a large pancreatic neuroendocrine tumor (PNET) and portosystemic shunts in the liver. Prior cases are rather scarce, and the exact mechanism is not fully understood. The case illustrates the added value of a multimodality imaging approach in patients presenting with hyperammonemia-induced encephalopathy.
In Search of an Efficient and Reliable Deep Learning Model for Identification of COVID-19 Infection from Chest X-ray Images
Authors: Azad Abul Kalam , Mahabub-A-Alahi Mahabub-A-Alahi , Ahmed Imtiaz , Ahmed Mosabber Uddin
Published: February 2023

The virus responsible for COVID-19 is mutating day by day with more infectious characteristics. With the limited healthcare resources and overburdened medical practitioners, it is almost impossible to contain this virus. The automatic identification of this viral infection from chest X-ray (CXR) images is now more demanding as it is a cheaper and less time-consuming diagnosis option. To that cause, we have applied deep learning (DL) approaches for four-class classification of CXR images comprising COVID-19, normal, lung opacity, and viral pneumonia. At first, we extracted features of CXR images by applying a local binary pattern (LBP) and pre-trained convolutional neural network (CNN). Afterwards, we utilized a pattern recognition network (PRN), support vector machine (SVM), decision tree (DT), random forest (RF), and k-nearest neighbors (KNN) classifiers on the extracted features to classify aforementioned four-class CXR images. The performances of the proposed methods have been analyzed rigorously in terms of classification performance and classification speed. Among different methods applied to the four-class test images, the best method achieved classification performances with 97.41% accuracy, 94.94% precision, 94.81% recall, 98.27% specificity, and 94.86% F1 score. The results indicate that the proposed method can offer an efficient and reliable framework for COVID-19 detection from CXR images, which could be immensely conducive to the effective diagnosis of COVID-19-infected patients.
Deep-Learning-Based Automatic Segmentation of Parotid Gland on Computed Tomography Images
Authors: Önder Merve , Evli Cengiz , Türk Ezgi , Kazan Orhan , Bayrakdar İbrahim Şevki , Çelik Özer , Costa Andre Luiz Ferreira , Gomes João Pedro Perez , Ogawa Celso Massahiro , Jagtap Rohan , Orhan Kaan
Published: February 2023

This study aims to develop an algorithm for the automatic segmentation of the parotid gland on CT images of the head and neck using U-Net architecture and to evaluate the model’s performance. In this retrospective study, a total of 30 anonymized CT volumes of the head and neck were sliced into 931 axial images of the parotid glands. Ground truth labeling was performed with the CranioCatch Annotation Tool (CranioCatch, Eskisehir, Turkey) by two oral and maxillofacial radiologists. The images were resized to 512 × 512 and split into training (80%), validation (10%), and testing (10%) subgroups. A deep convolutional neural network model was developed using U-net architecture. The automatic segmentation performance was evaluated in terms of the F1-score, precision, sensitivity, and the Area Under Curve (AUC) statistics. The threshold for a successful segmentation was determined by the intersection of over 50% of the pixels with the ground truth. The F1-score, precision, and sensitivity of the AI model in segmenting the parotid glands in the axial CT slices were found to be 1. The AUC value was 0.96. This study has shown that it is possible to use AI models based on deep learning to automatically segment the parotid gland on axial CT images.
The Role of Color Doppler Imaging in the Diagnosis of Glaucoma: A Review of the Literature
Authors: Banou Lamprini , Dastiridou Anna , Giannoukas Athanasios , Kouvelos Georgios , Baros Christos , Androudi Sofia
Published: February 2023

Glaucoma is a progressive optic neuropathy and one of the leading causes of irreversible blindness worldwide. Elevated intraocular pressure (IOP) is the major risk factor for the onset and progression of glaucoma. In addition to elevated IOP, impaired intraocular blood flow is also considered to be involved in the pathogenesis of glaucoma. Various techniques have been used to assess ocular blood flow (OBF), including Color Doppler Imaging (CDI), a technique used in ophthalmology in recent decades. This article reviews the role of CDI in both the diagnosis and effective monitoring of glaucoma progression, presenting the protocol for imaging and its advantages, as well as the limitations of its use. Moreover, it analyzes the pathophysiology of glaucoma, focusing on vascular theory and its role in the onset and progression of the disease.
Anti-Toothbreaker: A Novel Low-Budget Device Enabling Contactless Dental Protection and a Forbidden Technique during Direct Laryngoscopy for Endotracheal Intubation
Authors: Razaeian Sam , Liebich Helena Kristin
Published: February 2023

Background: Iatrogenic dental injury is the most common complication of conventional laryngoscopy during orotracheal intubation. The main cause is unintended pressure and leverage forces from the hard metal blade of the laryngoscope. The aim of this pilot study was to introduce and test a novel, reusable low-budget device not only providing contactless dental protection during direct laryngoscopy for endotracheal intubation, but also enabling, in contrast to established tooth protectors, active levering with conventional laryngoscopes for easier visualization of the glottis. Methods: A constructed prototype for intrahospital usage was evaluated by seven participants on a simulation manikin for airway management. Endotracheal intubation was performed with and without the device using a conventional Macintosh laryngoscope (blade size 4) and a 7.5 mm endotracheal tube (Teleflex Medical GmbH, Fellbach, Germany). Necessary time and success of first pass were determined. Degree of visualization of the glottis with and without the device was stated by the participants according to the Cormack and Lehane (CL) classification system and the Percentage of Glottic Opening (POGO) scoring system. In addition, subjective physical effort, feeling of safety regarding successful intubation, and risk for dental injury were queried on a numeric scale between 1 and 10. Results: All participants except one stated that the intubation procedure was easier with usage of the device than without it. On average, this was subjectively perceived as being approximately 42% (range, 15–65%) easier. In addition, time to first pass success, as well as degree of glottis visualization, subjective physical effort, and feeling of safety regarding risk for dental injury, were clearly better with usage of the device. Concerning feeling of safety regarding successful intubation, there was only a minor advantage. No difference in first pass success rate and number of total attempts could be observed. Conclusion: The Anti-Toothbreaker is a novel, reusable low-budget device which might not only provide contactless dental protection during direct laryngoscopy for endotracheal intubation, but also enables, in contrast to established tooth protectors, active levering with conventional laryngoscopes for easier visualization of the glottis. Future human cadaveric studies are needed to investigate whether these advantages also prove themselves there.
Retinal Blood Vessel Analysis Using Optical Coherence Tomography (OCT) in Multiple Sclerosis
Authors: Young Nicholas , Zivadinov Robert , Dwyer Michael G. , Bergsland Niels , Weinstock-Guttman Bianca , Jakimovski Dejan
Published: February 2023

Background: Both greater retinal neurodegenerative pathology and greater cardiovascular burden are seen in people with multiple sclerosis (pwMS). Studies also describe multiple extracranial and intracranial vascular changes in pwMS. However, there have been few studies examining the neuroretinal vasculature in MS. Our aim is to determine differences in retinal vasculature between pwMS and healthy controls (HCs) and to determine the relationship between retinal nerve fiber layer (RNFL) thickness and retinal vasculature characteristics. Methods: A total of 167 pwMS and 48 HCs were scanned using optical coherence tomography (OCT). Earlier OCT scans were available for 101 pwMS and 35 HCs for an additional longitudinal analysis. Segmentation of retinal vasculature was performed in a blinded manner in MATLAB’s optical coherence tomography segmentation and evaluation GUI (OCTSEG) software. Results: PwMS has fewer retinal blood vessels when compared to HCs (35.1 vs. 36.8, p = 0.017). Over the 5.4 year follow up, and when compared to HCs, pwMS has a significant decrease in number of retinal vessels (average loss of −3.7 p = 0.007). Moreover, the total vessel diameter in pwMS does not change when compared to the increase in vessel diameter in the HCs (0.06 vs. 0.3, p = 0.017). Only in pwMS is there an association between lower RNFL thickness and fewer retinal vessel number and smaller diameter (r = 0.191, p = 0.018 and r = 0.216, p = 0.007). Conclusions: Over 5 years, pwMS exhibit significant retinal vascular changes that are related to greater atrophy of the retinal layers.
The Role of PET/CT in Breast Cancer
Authors: Hadebe Bawinile , Harry Lerwine , Ebrahim Tasmeera , Pillay Venesen , Vorster Mariza
Published: February 2023

Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer worldwide, with an estimated 2.3 million new cases (11.7%), followed by lung cancer (11.4%) The current literature and the National Comprehensive Cancer Network (NCCN) guidelines state that 18F-FDG PET/CT is not routine for early diagnosis of breast cancer, and rather PET/CT scanning should be performed for patients with stage III disease or when conventional staging studies yield non-diagnostic or suspicious results because this modality has been shown to upstage patients compared to conventional imaging and thus has an impact on disease management and prognosis. Furthermore, with the growing interest in precision therapy in breast cancer, numerous novel radiopharmaceuticals have been developed that target tumor biology and have the potential to non-invasively guide the most appropriate targeted therapy. This review discusses the role of 18F-FDG PET and other PET tracers beyond FDG in breast cancer imaging.
Safeguarding UAV Networks against Active Eavesdropping: An Elevation Angle-Distance Trade-Off for Secrecy Enhancement
Authors: Shen Aijia , Luo Junsong , Ning Jin , Li Yilian , Wang Zibin , Duo Bin
Published: February 2023

Because of their low expense and ease of rapid deployment, unmanned aerial vehicles (UAVs) are frequently applied in wireless networks. Although the wireless channel is able to broadcast, legitimate communications between UAVs and ground nodes are incredibly susceptible to severe security threats, such as malicious jamming and eavesdropping. Compared with the traditional line-of-sight channel (LC) model, the probabilistic LC (PrLC) model can better describe the practical channel conditions of UAV-to-ground transmission in city areas. Therefore, this paper considers the UAV-enabled networks under the PrLC model in complex city environments. Specifically, when the UAV transmits classified messages to legitimate ground nodes, multiple active eavesdroppers simultaneously eavesdrop on the transmitted confidential information to interfere with the signal and limit the legal transmission. We jointly optimize the communication connection, the three-dimensional (3D) UAV trajectory, and the transmit power of the UAV to increase the average secrecy rate for the worst condition. Because the problem is non-convex, the best solution is formidable to get, this paper designs an iterative algorithm and use the successive convex approximation (SCA) technique to solve it. Compared to other benchmarks, our proposed algorithm, as demonstrated by numerical results, can effectively balance the elevation angle-distance trade-off to improve secrecy rate performance.
On the Kaniadakis Distributions Applied in Statistical Physics and Natural Sciences
Authors: Wada Tatsuaki , Scarfone Antonio Maria
Published: February 2023

Constitutive relations are fundamental and essential to characterize physical systems. By utilizing the κ-deformed functions, some constitutive relations are generalized. We here show some applications of the Kaniadakis distributions, based on the inverse hyperbolic sine function, to some topics belonging to the realm of statistical physics and natural science.
PBQ-Enhanced QUIC: QUIC with Deep Reinforcement Learning Congestion Control Mechanism
Authors: Zhang Zhifei , Li Shuo , Ge Yiyang , Xiong Ge , Zhang Yu , Xiong Ke
Published: February 2023

Currently, the most widely used protocol for the transportation layer of computer networks for reliable transportation is the Transmission Control Protocol (TCP). However, TCP has some problems such as high handshake delay, head-of-line (HOL) blocking, and so on. To solve these problems, Google proposed the Quick User Datagram Protocol Internet Connection (QUIC) protocol, which supports 0-1 round-trip time (RTT) handshake, a congestion control algorithm configuration in user mode. So far, the QUIC protocol has been integrated with traditional congestion control algorithms, which are not efficient in numerous scenarios. To solve this problem, we propose an efficient congestion control mechanism on the basis of deep reinforcement learning (DRL), i.e., proximal bandwidth-delay quick optimization (PBQ) for QUIC, which combines traditional bottleneck bandwidth and round-trip propagation time (BBR) with proximal policy optimization (PPO). In PBQ, the PPO agent outputs the congestion window (CWnd) and improves itself according to network state, and the BBR specifies the pacing rate of the client. Then, we apply the presented PBQ to QUIC and form a new version of QUIC, i.e., PBQ-enhanced QUIC. The experimental results show that the proposed PBQ-enhanced QUIC achieves much better performance in both throughput and RTT than existing popular versions of QUIC, such as QUIC with Cubic and QUIC with BBR.
Artificial Intelligence and Machine Learning in Grid Connected Wind Turbine Control Systems: A Comprehensive Review
Authors: Farrar Nathan Oaks , Ali Mohd Hasan , Dasgupta Dipankar
Published: February 2023

As grid-connected wind farms become more common in the modern power system, the question of how to maximize wind power generation while limiting downtime has been a common issue for researchers around the world. Due to the complexity of wind turbine systems and the difficulty to predict varying wind speeds, artificial intelligence (AI) and machine learning (ML) algorithms have become key components when developing controllers and control schemes. Although, in recent years, several review papers on these topics have been published, there are no comprehensive review papers that pertain to both AI and ML in wind turbine control systems available in the literature, especially with respect to the most recently published control techniques. To overcome the drawbacks of the existing literature, an in-depth overview of ML and AI in wind turbine systems is presented in this paper. This paper analyzes the following reviews: (i) why optimizing wind farm power generation is important; (ii) the challenges associated with designing an efficient control scheme for wind farms; (iii) a breakdown of the different types of AI and ML algorithms used in wind farm controllers and control schemes; (iv) AI and ML for wind speed prediction; (v) AI and ML for wind power prediction; (vi) AI and ML for mechanical component monitoring and fault detection; and (vii) AI and ML for electrical fault prevention and detection. This paper will offer researchers and engineers in the wind energy generation field a comprehensive review of the application of AI and ML in the control methodology of offshore and onshore wind farms so that more efficient and robust control schemes can be designed for future wind turbine controllers.
Sustainable Production of Biodiesel from Novel Non-Edible Oil Seeds (Descurainia sophia L.) via Green Nano CeO2 Catalyst
Authors: Akhtar Maryam Tanveer , Ahmad Mushtaq , Ramadan Mohamed Fawzy , Makhkamov Trobjon , Yuldashev Akramjon , Mamarakhimov Oybek , Munir Mamoona , Asma Maliha , Zafar Muhammad , Majeed Salman
Published: February 2023

The current study focuses on the synthesis of Cerium oxide (CeO2) nanocatalyst via Tragacanth Gum (TG) using the wet impregnation method and its application for sustainable biodiesel production from a novel, non-edible Descurainia sophia (L.) Webb ex Prantl seed oil. The D. sophia seed oil has higher oil content (36 wt%) and free fatty acid (FFA) value (0.6 mg KOH/g). Innovative analytical methods, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), transmission electron microscopy (TEM), thermogravimetric analysis (TGA), and Fourier transform infrared spectroscopy, were used to characterize the newly synthesized, environmentally friendly, and recyclable CeO2-TG phytonanocatalyst (FT-IR). The results show that the CeO2-TG phytonanocatalyst was 22 nm in diameter with a spherical shape outer morphology, while the inner structure was hexagonal. Due to low FFA content, the D. sophia seed oil was pretreated and transesterified via a single step. Using varying parameters, the optimized process variables were determined via Response Surface Methodology (RSM). The optimum process values were 8:1 methanol to oil molar ratio, 0.3 wt% catalyst concentration, 90 °C temperature, and reaction time of 210 min with 98% biodiesel yield. The recently created phytonanocatalyst was reliable and effective, with three times reusability in the transesterification reaction. Thin layer chromatography (TLC), FT-IR, gas chromatography–mass spectroscopy (GCMS), and Nuclear magnetic resonance (NMR) analyses were used to characterize the synthesized biodiesel. Physico-chemical properties of D. sophia biodiesel, i.e., Kinematic viscosity (4.23 mm2/s), density (0.800 kg/m3), pour point (−7 °C), cloud point (−12 °C), and flash point (73.5 °C) agree well with international biodiesel standards (ASTM-6751, 951), (EU-14214), and China (GB/T 20828) standards. The results show that the synthesized nanocatalyst demonstrated remarkable stability, indicating a bright future for industrial biodiesel production from low-cost feedstock.
A Comparative-Analysis-Based Multi-Criteria Assessment of On/Off-Grid-Connected Renewable Energy Systems: A Case Study
Authors: Falama Ruben Zieba , Dumbrava Virgil , Saidi Abdelaziz Salah , Houdji Etienne Tchoffo , Salah Chokri Ben , Doka Serge Yamigno
Published: February 2023

Different configurations of on/off-grid-connected hybrid renewable energy systems (HRESs) are analyzed and compared in the present research study for optimal decision making in Sub-Saharan Africa, facing the problems of electricity deficit. A multi-criteria analysis is performed for this purpose using MATLAB software for simulation. The obtained results show that the levelized cost of energy (LCOE) corresponding to 0% power supply deficit probability (PSDP) is 0.0819 USD/kWh, 0.0925 USD/kWh, 0.3979 USD/kWh, 0.3251 USD/kWh, 0.1754 USD/kWh, 0.1641 USD/kWh, 0.5385 USD/kWh, and 1.4515 USD/kWh, respectively, for the Grid-PV/Wind/Battery, Grid-PV/Battery, Grid-Wind/Battery, Grid-Wind, PV/Wind/Battery, PV/Battery, Wind/Battery, and stand-alone Wind systems. The CO2 emissions are 14,888.4 kgCO2/year, 16,916.6 kgCO2/year, 13,139.7 kgCO2/year, 6430.4 kgCO2/year, 11,439 kgCO2/year, 14,892.5 kgCO2/year, 10,252.6 kgCO2/year, and 1621.5 kgCO2/year, respectively, for the aforementioned systems. It is found that the Grid-connected PV/Wind/Battery is the most cost-effective system leading to a grid energy cost reduction of 30.89%. Hybridization of different renewable energy sources (RESs) could significantly improve the electricity cost and reduce the CO2 emissions. However, this improvement and this reduction depend on the used RES and the system configuration. On-grid-connected HRESs are more cost-effective than off-grid-connected HRES. The least polluting energy system is the stand-alone Wind system, which allows a reduction in the grid CO2 emissions by 93.66%. The sensitivity analysis has proven that the long-term investment, the decrease in the battery cost, and the decrease in the discount rate could lead to the reduction in the LCOE.
Performance Assessment of Coupled Concentrated Photovoltaic-Thermal and Vacuum Membrane Distillation (CPVT-VMD) System for Water Desalination
Authors: Santana Juan Pablo , Rivera-Solorio Carlos I. , Chew Jia Wei , Tan Yong Zen , Gijón-Rivera Miguel , Acosta-Pazmiño Iván
Published: February 2023

Numerical simulations were carried out to assess the technical and economic feasibility of a solar water desalination system that has a novel hybrid Concentrating Photovoltaic Thermal (CPVT) collector coupled with a Vacuum Membrane Distillation (VMD) process. A special characteristic of this CPVT is its triangular receiver with PV cells facing the reflecting surface. This type of receiver has the advantage of generating more electricity with less PV surface area and great potential to be used to hybridize conventional parabolic thermal collectors. TRNSYS was employed to analyze the annual performance of the CPVT-VMD system evaluating parameters such as solar fraction, specific permeate production and specific energy production for different coastal cities. In the dynamic simulations, local annual weather data and specific information about the characteristics and operating conditions of a real CPVT collector and a VMD module were considered. From the parametric analysis the optimal surface area of collectors and the input temperature of the VDM module were determined. A maximum specific permeate of 218.410 m 3/m2VMD for Acapulco, MX, and a minimum of 170.365 m 3/m2VMD for Singapore, SG, were achieved for the proposed CPVT-VMD system of four solar collectors with an operating set temperature of 55 °C. An economic profit was found after 7 years for Acapulco city, which showed great potential to use solar energy from hybrid CPVT collectors for a VMD process to provide freshwater in coastal cities.
Developing an Appropriate Energy Trading Algorithm and Techno-Economic Analysis between Peer-to-Peer within a Partly Independent Microgrid
Authors: Muntasir Fahim , Chapagain Anusheel , Maharjan Kishan , Baig Mirza Jabbar Aziz , Jamil Mohsin , Khan Ashraf Ali
Published: February 2023

The intimidating surge in the procurement of Distributed Energy Resources (DER) has increased the number of prosumers, creating a new possibility of local energy trading across the community. This project aims to formulate the peer-to-peer energy (P2P) sharing model to encourage the DERs to share surplus energy among the consumers. An effective pricing method is developed based on the supply-demand ratio (SDR) with the importance of self-optimization, which allows the prosumers to maximize their energy sharing and profits. To implement this pricing method, a simplified dynamic matchmaking algorithm has been deployed to introduce the Outstanding Prosumer to interact with existing consumers to increase the efficiency and profitability of the trade network. Consumers also benefit from this model, as they can pick the most economical energy supplier instead of relying on the utility grid. The prosumer with high excess energy and the consumer with the highest energy demand will be prioritized to maintain the SDR ratio to one or greater than one. Here, all the above-stated features of the peer-to-peer energy trading have been demonstrated with some calculations to back up some tangible results. Finally, a case study is simulated among the residents of Dhaka, Bangladesh, to demonstrate how peers can profit from participating in trading at a given time. Comparing the results with and without P2P trading, there has been a 17.54% reduction in an electric bill on a typical day of July, and a 49.53% reduction in the interaction with the grid.
Electric Vehicle Supply Chain Management: A Bibliometric and Systematic Review
Authors: Soares Laene Oliveira , Reis Augusto da Cunha , Vieira Pedro Senna , Hernández-Callejo Luis , Boloy Ronney Arismel Mancebo
Published: February 2023

With the advancement of electric mobility, critical materials that are used in the batteries and electronic equipment of electric vehicles tend to become scarce. This work aims to analyse the state-of-art of the electric vehicle supply chain through bibliometric and systematic reviews, using quantitative and qualitative indicators, to find critical points that represent risks to the supply chain and that should be focused on and to identify trends for further studies. The bibliometric review was carried out with the support of the Bibliometrix software. The systematic review was performed using the PRISMA method. The bibliometric analysis showed the importance of the costs associated with electric vehicles, as well as trends in studies related to sustainability and transparency in the supply chain. Although risk management in the supply chain appears to be relatively little studied when considering the authors’ keyword analysis, the systematic review showed that this process was the most studied topic. Even so, raw materials supply appeared as the topic most focused on, followed by an environmental impact assessment and cost analysis. There were also studies aiming to achieve competitiveness and analyse ecologically correct practices. The battery was the most studied component, but other components must be analysed in search of greater competitiveness in relation to conventional vehicles.
Impact of Digital Industrialization on the Energy Industry Supply Chain: Evidence from the Natural Gas Industry in China
Authors: Peng Jiachao , Chen Hanfei , Jia Lei , Fu Shuke , Tian Jiali
Published: February 2023

The global economy is moving into a new era characterized by digital and green development. To examine the impact of digital industrialization development on the energy supply chain, in relation to the sustainable development of China’s energy security, we discuss the nonlinear impact and transmission mechanism of digital industrialization on the supply chain of the energy industry using a panel threshold regression model based on sample data on the development of the provincial natural gas industry in China from 2006 to 2020. We found that there are multiple threshold effects of digital industrialization level development on energy supply chain length, and the results are statistically significant, i.e., digital industrialization development positively contributes to natural gas supply chain length after digital industrialization is raised to or crosses the critical threshold. Meanwhile, the heterogeneity analysis results show that there are differences in the impact of digital industrialization on the energy supply chain from sub-sectors, regional development differences, and different development periods. Therefore, we provide some factual support and experience for achieving the construction goal of “Digital China” and accelerating the digital reform of the energy supply chain as well as transforming and upgrading the economic structure.
Recent Approaches to Achieve High Temperature Operation of Nafion Membranes
Authors: Xu Guoxiao , Dong Xinwei , Xue Bin , Huang Jianyou , Wu Junli , Cai Weiwei
Published: February 2023

A proton exchange membrane fuel cell (PEMFC), as an efficient energy conversion device, has many advantages, such as high energy conversion efficiency and environmentally friendly zero emissions, and is expected to have great potential for addressing the uneven distribution of global green energy. As a core component, the performance of the proton exchange membrane (PEM) directly affects the overall output of the fuel cell system. At present, Nafion membranes with good, comprehensive properties are the most widely used commercial proton exchange membrane materials. However, Nafion membranes demonstrate a great inadaptability with an increase in operating temperatures, such as a rapid decay in proton conductivity. Therefore, enhancing the overall performance of Nafion membranes under high temperatures and low relative humidity (RH) has become an urgent problem. Although many efforts have been made to solve this problem, it is difficult to find the balance point between high-temperature conductivity and overall stability for researchers. In this paper, we summarize the recent approaches to improving the operating temperature of Nafion membranes from the following two perspectives: (1) using different materials for the modification of Nafion membranes, and (2) applying different modification methods to the Nafion membranes. Based on the structural and functional characteristics of Nafion, the non-destructive targeted filling of fillers and the efficient synergy of the two-phase region are two vital research directions for the preparation of high-performance composite membranes.
Simulations for Planning of Liquid Hydrogen Spill Test
Authors: Mangala Gitushi Kevin , Blaylock Myra , Hecht Ethan S.
Published: February 2023

In order to better understand the complex pooling and vaporization of a liquid hydrogen spill, Sandia National Laboratories is conducting a highly instrumented, controlled experiment inside their Shock Tube Facility. Simulations were run before the experiment to help with the planning of experimental conditions, including sensor placement and cross wind velocity. This paper describes the modeling used in this planning process and its main conclusions. Sierra Suite’s Fuego, an in-house computational fluid dynamics code, was used to simulate a RANS model of a liquid hydrogen spill with five crosswind velocities: 0.45, 0.89, 1.34, 1.79, and 2.24 m/s. Two pool sizes were considered: a diameter of 0.85 m and a diameter of 1.7. A grid resolution study was completed on the smaller pool size with a 1.34 m/s crosswind. A comparison of the length and height of the plume of flammable hydrogen vaporizing from the pool shows that the plume becomes longer and remains closer to the ground with increasing wind speed. The plume reaches the top of the facility only in the 0.45 m/s case. From these results, we concluded that it will be best for the spacing and location of the concentration sensors to be reconfigured for each wind speed during the experiment.
The Effects of Rising Energy Prices on Inflation in Croatia
Authors: Keček Damira
Published: February 2023

The estimation of the price change effects caused by the impact of external shocks on the national economy is extremely important. The aim of this paper is to estimate the effect of the increasing global energy prices on the stability of the Croatian economy. The effects of the increase in energy prices are compared with other exogenous shocks, i.e., with the effects of the increasing gross wages and salaries and the increasing prices of imported goods and services. The impact of the changes in the prices of primary inputs on the trends in the economic sector prices was quantified using the input–output price model. The intensity of the transmission of the change in price of a primary input to other sectors through intersectoral dependence was analyzed. The results of the analysis indicate that the Croatian economy is extremely sensitive to energy price shocks. The estimated effects of increases in the prices of certain primary inputs, especially energy, on various economic sectors and on the overall economy are particularly significant when considering situations in which Croatia adopts the EUR, and when the price increases could affect the stability and successful completion of that process.
Possibility Study in CO2 Free Hydrogen Production Using Dodecane (C12H26) from Plasma Reaction
Authors: Park Dong Kyoo , Kim Ji-Hyeon , Kim Hyo-Sik , Kim Jin-Ho , Ryu Jae-Hong
Published: February 2023

Turquoise hydrogen refers to hydrogen produced through a fossil-fuel-based process in which carbon is separated into solid carbon and no carbon dioxide is produced. In this study, dodecane was selected as a simulated oil for waste plastic pyrolysis recovery oil, and the turquoise hydrogen production characteristics through the thermal cracking reaction using an arc plasma torch were investigated. The plasma was stably discharged at 2 to 4 kW. Hydrogen in the produced gas was analyzed through an online IR gas analyzer, and hydrocarbons from C1 to C5 were analyzed through GC-FID. As a result of the experiment, the hydrogen yield tended to increase as the plasma power increased, and a maximum of 11.5% based on mass was obtained. On the other hand, carbon oxides such as CO and CO2 were not generated. Along with hydrogen, the valuable by-products of this process are solid carbon and gaseous hydrocarbons. The solid carbon yields also increased up to 66% as the plasma power increased. On the other hand, the yield of gaseous hydrocarbons showed an opposite trend to that of hydrogen and carbon and consisted mainly of C2 series (average content of 77%) and olefins (average fraction of 0.67). Consequently, it can be considered that the plasma thermal cracking is a promising technology for the CO2-free hydrogen production, as well as solid carbon and C2-olefin.
Advancements in Offshore Vertical Axis Wind Turbines
Authors: Micallef Daniel
Published: February 2023

In the past few years, the journal Energies received various original research manuscripts on offshore vertical axis wind turbines (VAWTs) [...]
Renewable Energy Potential Estimation Using Climatic-Weather-Forecasting Machine Learning Algorithms
Authors: Maduabuchi Chika , Nsude Chinedu , Eneh Chibuoke , Eke Emmanuel , Okoli Kingsley , Okpara Emmanuel , Idogho Christian , Waya Bryan , Harsito Catur
Published: February 2023

The major challenge facing renewable energy systems in Nigeria is the lack of appropriate, affordable, and available meteorological stations that can accurately provide present and future trends in weather data and solar PV performance. It is crucial to find a solution to this because information on present and future solar PV performance is important to renewable energy investors so that they can assess the potential of renewable energy systems in various locations across the country. Although Nigerian weather provides favorable weather conditions for clean power generation, there is little penetration of renewable energy systems in the region, since over 95% of the power is fossil-fuel-generated. This is because there has been no detailed report showing the potential of clean power generation systems due to the dysfunctional meteorological stations in the country. This paper sought to fill this knowledge gap by providing a machine-learning-inspired forecasting of environmental weather parameters that can be used by manufacturing companies in evaluating the profitability of siting renewable energy systems in the region. Crucial weather parameters such as daily air temperature, relative humidity, atmospheric pressure, wind speed, and rainfall were obtained from NASA for a period of 19 years (viz. 2004–2022), resulting in the collection of 6664 high-resolution data points. These data were used to build diverse regressive neural networks with varying hyperparameters to find the best network arrangement. In summary, a low mean-squared error of 7 × 10−3 and high regression correlations of 96% were obtained during the training.
A Review on Optimal Energy Management in Commercial Buildings
Authors: Hossain Jahangir , Kadir Aida. F. A. , Hanafi Ainain. N. , Shareef Hussain , Khatib Tamer , Baharin Kyairul. A. , Sulaima Mohamad. F.
Published: February 2023

The rising cost and demand for energy have prompted the need to devise innovative methods for energy monitoring, control, and conservation. In addition, statistics show that 20% of energy losses are due to the mismanagement of energy. Therefore, the utilization of energy management can make a substantial contribution to reducing the unnecessary usage of energy consumption. In line with that, the intelligent control and optimization of energy management systems integrated with renewable energy resources and energy storage systems are required to increase building energy efficiency while considering the reduction in the cost of energy bills, dependability of the grid, and mitigating carbon emissions. Even though a variety of optimization and control tactics are being utilized to reduce energy consumption in buildings nowadays, several issues remain unsolved. Therefore, this paper presents a critical review of energy management in commercial buildings and a comparative discussion to improve building energy efficiency using both active and passive solutions, which could lead to net-zero energy buildings. This work also explores different optimum energy management controller objectives and constraints concerning user comfort, energy policy, data privacy, and security. In addition, the review depicts prospective future trends and issues for developing an effective building energy management system, which may play an unavoidable part in fulfilling the United Nations Sustainable Development Goals.
Plastome Phylogeny and Taxonomy of Cinnamomum guizhouense (Lauraceae)
Authors: Yang Zhi , Ferguson David Kay , Yang Yong
Published: February 2023

Taxonomy of the genus Cinnamomum Schaeff. (Lauraceae) is difficult because of parallel evolution of morphology. Recent phylogenomic and taxonomic studies have clarified the problem and subdivided the Asian Cinnamomum into two genera, i.e., Camphora Fabr. and Cinnamomum sensu stricto. Here we sequenced and characterized the plastome of a recently described species Cinnamomum guizhouense C.Y. Deng, Zhi Yang et Y. Yang, performed a phylogenomic analysis, and also conducted a comparative analysis. The plastome of Cinnamomum guizhouense is 152,739 bp long and quadri-parted with a pair of inverted repeat regions (IR: 20,132 bp) divided by a small single copy region (SSC: 18,852 bp) and a large single copy region (LSC: 93,623 bp). The plastome possesses a total of 128 genes including 82 protein-coding genes, 36 tRNA genes, and eight rRNA genes, which is similar to most published plastomes of the core Lauraceae group. The plastome of Cinnamomum guizhouense displays higher similarity to Camphora than Cinnamomum. Our phylogenomic result suggests that Cinnamomum guizhouense belongs to the Camphora clade. As a result, we propose a new combination, i.e. Camphora guizhouensis (C.Y. Deng, Zhi Yang et Y. Yang) Zhi Yang et Y.Yang, comb. nov.
Adhesive-and Metal-Free Assembly Techniques for Prefabricated Multi-Layer Engineered Wood Products: A Review on Wooden Connectors
Authors: Han Lei , Kutnar Andreja , Sandak Jakub , Šušteršič Iztok , Sandberg Dick
Published: February 2023

Engineered wood products (EWPs) are being increasingly used as construction materials. EWPs are currently being made using synthetic adhesives or metal fasteners, which lead to poor recyclability and reusability. Therefore, this review paper focused on emerging adhesive- and metal-free assembling techniques including wood dowels, rotary-dowel welding, wooden nails, and dovetail joining as alternative ways of making prefabricated EWPs. This will contribute towards green construction and optimising the building process to minimise its negative impact on the environment and its inhabitants, while maximising the positive aspects of the finished structure. The respective advantages and shortcomings will be compared with those of equivalent EWPs. In general, the dowel-laminated timber (DLT) provides sufficient load-bearing capacity and even better ductility than EWPs of equivalent size, but its relatively low stiffness under a bending load limits its application as a structural element. Optimised manufacturing parameters such as dowel species, dowel spacing, dowel diameter, dowel insertion angle, dowel shape, etc. could be studied to improve the stiffness. The improved mechanical properties and tight fitting due to set-recovery of densified wood support its use as sustainable alternatives to hardwood dowels in DLT to overcome problems such as the loosening of connections over time and dimensional instability. The rotary welding technology could also enhance the strength and long-term performance of dowel-type joints, but its poor water resistance needs further investigation. The main obstacles to implementing DLT products in the market are missing technical information and design guidelines based on national codes.
In the Northeasternmost Stands in Europe, Beech Shows Similar Wind Resistance to Birch
Authors: Krišāns Oskars , Matisons Roberts , Jansone Līga , Īstenais Nauris , Kāpostiņš Rolands , Šēnhofa Silva , Jansons Āris
Published: February 2023

The ongoing shifts in natural vegetation zones predict the expansion of European beech (Fagus sylvatica L.) into the Eastern Baltic region, suggesting it will become a potential alternative to birch (Betula pendula Roth. and Betula pubescens Ehrh.) in forest regeneration. For a successful application of alternative forest regeneration material, an evaluation of susceptibility to natural disturbances (e.g., wind) is necessary for reliable projections of timber yield in the long term. This study compared the loading resistance of beech growing in the northeasternmost stands in Europe to local birch by applying the static tree-pulling test. Relationships between dimensions of aboveground parts and resistance against intrinsic wood damages (primary failure) and fatal (secondary) failure were similar between species. However, birch, which is more drought sensitive compared to beech, is suggested to have a higher susceptibility to post-storm legacy effects, supporting beech as a potential alternative to birch in terms of wind resistance.
Nutshell Physicochemical Characteristics of Different Hazel Cultivars and Their Defensive Activity toward Curculio nucum (Coleoptera: Curculionidae)
Authors: Li Xingpeng , Xiu Dongying , Huang Jinbin , Yu Bo , Jia Shuxia , Song Liwen
Published: February 2023

Hazel (Corylus avellana) is easily attacked by Curculio nucum L. To better understand the physiological mechanisms underlying the different resistance of cultivars to C. nucum, we determined the insect-resistant compounds, plant hormones contents, and enzyme activities in the nutshells of three hazel cultivars (DW, B21, and MZ) before (preexisting defense) and after (induced defense) C. nucum chewing. The findings demonstrated that the resistance of three hazel cultivars to C. nucum differed significantly (p < 0.05): the damage rate of MZ with 17.57% was highest, followed by DW (11.23%), and then B21 (7.15%). The contents of insect-resistant compounds (total terpenoid, tannin, total phenol, flavonoids, cellulose, and lignin) varied with hazel cultivars, both before and after C. nucum chewing, except for cellulose and lignin before induction. The level of plant hormones and defense enzyme activities of hazelnut enhanced due to C. nucum induction. Pearson correlation results revealed that the hazelnut damage rate was significantly negatively correlated with jasmonic acid (JA) (R2 = 0.812), SOD (R2 = 0.671), salicylic acid (SA) (R2 = 0.878), and terpenoids (R2 = 0.774), and significantly positively correlated with flavonoids (R2 = 0.696), celluloses (R2 = 0.501), POD (R2 = 0.758), and abscisic acid (ABA) (R2 = 0.978). The hazelnut defense to C. nucum was negatively related to cellulose contents, and not to lignin contents, but was significantly positively related to the ratio of cellulose-to-lignin (R2 = 0.703). Our results suggested that the hazel against C. nucum attack responded by improving plant hormones contents and enzyme activities in the nutshells. A particular cellulose-to-lignin ratio provides the most effective physical structural defense properties in the nutshells.
Development and Experimental Study of Mobile Fire Smoke Decontamination System
Authors: Yuan Hongyong , Zhou Yang , Zhou Fan , Huang Lida , Chen Tao
Published: February 2023

Fire smoke decontamination equipment, such as fire-fighting robots and smoke exhaust robots, is mainly used in long and narrow spaces such as underground garages. In several recent decades, the study of fire smoke spread in narrow spaces and fire smoke decontamination equipment stimulated the interests of many researchers. However, present equipment cannot eliminate insoluble toxic gases such as CO and may decrease the height of the smoke layer, causing great difficulty to rescue. In this study, a novel mobile fire smoke decontamination process and system are proposed. The experimental study and theoretical prediction of the system are conducted. The results show that the developed equipment is able to eliminate fire smoke particles and CO, cool the space, and improve the visibility of the fire site. The developed equipment can reduce the space temperature to below 60 °C, reduce the CO concentration to below 145 ppm, and enhance the visibility to more than 50 m in the rectangular tunnel after operating for 30 min under 4 MW fire condition.