bluuebunny/crossref_metadata_2025 huggingface dataset:
Facile Synthesis of FeCoNiCuIr High Entropy Alloy Nanoparticles for Efficient Oxygen Evolution Electrocatalysis
Authors: Cai Chen , Xin Zongwei , Zhang Xuefan , Cui Jian , Lv Hui , Ren Wanjie , Gao Cunyuan , Cai Bin
Published: September 2022

The lack of an efficient and stable electrocatalyst for oxygen evolution reaction (OER) greatly hinders the development of various electrochemical energy conversion and storage techniques. In this study, we report a facile synthesis of FeCoNiCuIr high-entropy alloy nanoparticles (HEA NPs) by a one-step heat-up method. The involvement of glucose made the NPs grow uniformly and increased the valence of Ir. The resulting FeCoNiCuIr NPs exhibit excellent OER performance in alkaline solution, with a low overpotential of 360 mV to achieve a current density of 10 mA cm−2 at a Tafel slope of as low as 70.1 mV dec−1. In addition, high stability has also been observed, which remained at 94.2% of the current density after 10 h constant electrolysis, with a constant current of 10 mA cm−2. The high electrocatalytic activity and stability are ascribed to the cocktail effect and synergistic effect between the constituent elements. Our work holds the potential to be extended to the design and synthesis of high-performance electrocatalysts.
Dectin-1 as a Potential Inflammatory Biomarker for Metabolic Inflammation in Adipose Tissue of Individuals with Obesity
Authors: Al Madhoun Ashraf , Kochumon Shihab , Al-Rashed Fatema , Sindhu Sardar , Thomas Reeby , Miranda Lavina , Al-Mulla Fahd , Ahmad Rasheed
Published: September 2022

In obesity, macrophage activation and infiltration in adipose tissue (AT) underlie chronic low-grade inflammation-induced insulin resistance. Although dectin-1 is primarily a pathogen recognition receptor and innate immune response modulator, its role in metabolic syndromes remains to be clarified. This study aimed to investigate the dectin-1 gene expression in subcutaneous AT in the context of obesity and associated inflammatory markers. Subcutaneous AT biopsies were collected from 59 nondiabetic (lean/overweight/obese) individuals. AT gene expression levels of dectin-1 and inflammatory markers were determined via real-time reverse transcriptase-quantitative polymerase chain reaction. Dectin-1 protein expression was assessed using immunohistochemistry. Plasma lipid profiles were measured by ELISA. AT dectin-1 transcripts and proteins were significantly elevated in obese as compared to lean individuals. AT dectin-1 transcripts correlated positively with body mass index and fat percentage (r ≥ 0.340, p ≤ 0.017). AT dectin-1 RNA levels correlated positively with clinical parameters, including plasma C-reactive protein and CCL5/RANTES, but negatively with that of adiponectin. The expression of dectin-1 transcripts was associated with that of various proinflammatory cytokines, chemokines, and their cognate receptors (r ≥ 0.300, p ≤ 0.05), but not with anti-inflammatory markers. Dectin-1 and members of the TLR signaling cascade were found to be significantly associated, suggesting an interplay between the two pathways. Dectin-1 expression was correlated with monocyte/macrophage markers, including CD16, CD68, CD86, and CD163, suggesting its monocytes/macrophage association in an adipose inflammatory microenvironment. Dectin-1 expression was independently predicted by CCR5, CCL20, TLR2, and MyD88. In conclusion, dectin-1 may be regarded as an AT biomarker of metabolic inflammation in obesity.
Neutrophil Activated by the Famous and Potent PMA (Phorbol Myristate Acetate)
Authors: Damascena Hylane Luiz , Silveira Wendy Ann Assis , Castro Mariana S. , Fontes Wagner
Published: September 2022

This review will briefly outline the major signaling pathways in PMA-activated neutrophils. PMA is widely used to understand neutrophil pathways and formation of NETs. PMA activates PKC; however, we highlight some isoforms that contribute to specific functions. PKC α, β and δ contribute to ROS production while PKC βII and PKC ζ are involved in cytoskeleton remodeling. Actin polymerization is important for the chemotaxis of neutrophils and its remodeling is connected to ROS balance. We suggest that, although ROS and production of NETs are usually observed together in PMA-activated neutrophils, there might be a regulatory mechanism balancing both. Interestingly, we suggest that serine proteases might determine the PAD4 action. PAD4 could be responsible for the activation of the NF-κB pathway that leads to IL-1β release, triggering the cleavage of gasdermin D by serine proteases such as elastase, leading to pore formation contributing to release of NETs. On the other hand, when serine proteases are inhibited, NETs are formed by citrullination through the PAD4 pathway. This review puts together results from the last 31 years of research on the effects of PMA on the neutrophil and proposes new insights on their interpretation.
Helium Metastable Distributions and Their Effect on the Uniformity of Hydrogenated Amorphous Silicon Depositions in He/SiH4 Capacitively Coupled Plasmas
Authors: Jo Sanghyun , Kang Suik , Lee Kyungjun , Kim Ho Jun
Published: September 2022

This study investigates, numerically, the spatial distribution of metastable helium (He*) in He/SiH4 capacitively coupled plasma (CCP) for the purpose of optimizing plasma density distributions. As a first step, we presented the results of a two-dimensional fluid model of He discharges, followed by those of He/SiH4 discharges to deposit hydrogenated amorphous silicon films, to investigate which factor dominates the coating uniformity. We retained our CCPs in the 300 mm wafer reactor used by the semiconductor industry in the recent past. Selected parameters, such as a sidewall gap (radial distance between the electrode edge and the sidewall), electrical condition of the sidewall, and position of the powered electrode, were considered. In addition, by increasing the gas pressure while varying the sidewall condition, we observed modification of the plasma distributions and, thus, the deposition rate profiles. According to the results, the shift in He* distributions was mainly due to the reduction in the electron mean free path under conditions of gas pressure higher than 100 Pa, as well as local perturbations in the ambipolar electric field due to the finite electrode structure. Small additions of SiH4 largely changed the He* density profile in the midplane of the discharge due to He* quenching. Furthermore, we found that the wide sidewall gap did not improve deposition uniformity against the expectation. This was because the excitation and ionization rate profiles were enhanced and localized only near the bottom electrode edge.
Increasing the Life Span of Tools Applied in Cheese Cutting Machines via Appropriate Micro-Blasting
Authors: Skordaris Georgios , Vogiatzis Konstantinos , Kakalis Leonidas , Mirisidis Ioannis , Paralidou Vasiliki , Paralidou Soultana
Published: September 2022

The potential to increase the life span of tools applied in cheese cutting machines is of great importance, considering their cost and the risk of fragmented metallic parts of the tool being inserted into the cheese. Such tools are commonly manufactured using stainless steel 405 and are subjected to dynamic loads during their operation, leading to fatigue failure. An efficient method to improve the fatigue properties of such tools is the application of micro-blasting. In this work, for the first time, an experimental–analytical methodology was developed for determining optimum micro-blasting conditions and ascertaining a preventive replacement of the tool before its extensive fracture. This methodology is based on the construction of a pneumatic system for the precise cutting of cheese and simultaneous force measurements. Additionally, the entire cheese-cutting process is simulated by appropriate FEA modeling. According to the attained results, micro-blasting on steel tools significantly improves the resistance against dynamic loads, whilst the number of impacts that a tool can withstand until fatigue fracture is more than three times larger. Via the developed methodology, a preventive replacement of the tool can be conducted, avoiding the risk of a sudden tool failure. The proposed methodology can be applied to different tool geometries and materials.
Oxide Nanostructured Coating for Power Lines with Anti-Icing Effect
Authors: Blinov Andrey Vladimirovcih , Kostyukov Dmitry Aleksandrovich , Yasnaya Maria Anatolevna , Zvada Pavel Aleksandrovich , Arefeva Lyudmila Pavlovna , Varavka Valery Nikolaevich , Zvezdilin Roman Aleksandrovich , Kravtsov Alexander Aleksandrovich , Maglakelidze David Guramievich , Golik Alexey Borisovich , Gvozdenko Alexey Alekseevich , Lazareva Natalia Viatcheslavovna , Kushch Elena Nikolaevna , Goncharov Vadim Nikolaevich , Kolodkin Maxim Andreevich , Shariati Mohammad Ali , Nagdalian Andrey Ashotovich
Published: September 2022

This paper presents the results of the development of a technology to obtain a nanostructured coating for the protection of overhead wires and the possibility of their application in the electric power industry. The paper provides an analysis of available data on methods of combating ice in different countries, ways to protect the surface of metals from environmental influences, and new materials used for protection. We studied the possibility of using a protective nanostructured coating to protect overhead wires. A technology for obtaining a protective nanostructured coating based on silicon oxide and methods for applying it to the wire of overhead lines are proposed. The analysis of the elemental composition and surface morphology of overhead line wires with protective coating is carried out by scanning electron microscopy. The influence of the nanostructured coating on the high-frequency signal bandwidth and wire resistance using a PCIe-6351 data acquisition board, equipped with a BNC-2120 terminal module generating a frequency signal were determined using the National Instruments LabVIEW software package. The subject of the study was a 110 kV overhead power line with a protective coating developed in this work. By analyzing the calculation, we obtained the operating requirements of the developed nanostructured coating. As a result, we developed a protective coating satisfying the working conditions and investigated its properties. In the final phase of the experiment, we tested the electrical characteristics of overhead wires with the developed protective coating.
Requirements of Scintillation Crystals with the Development of PET Scanners
Authors: Yu Xin , Zhang Xi , Zhang Heng , Peng Hao , Ren Qiushi , Xu Jianfeng , Peng Qiyu , Xie Siwei
Published: September 2022

Positron emission tomography (PET) is widely used in the diagnosis of tumors, cardiovascular system diseases, and neurological diseases. Scintillation crystals are an important part of PET scanners; they can convert γ photons into fluorescent photons to obtain their energy, time, and position information. Currently, an important research goal in PET is to find scintillation crystals with better performance. In this work, the principle of scintillation crystals is introduced, and the properties and requirements of scintillation crystals in different PET scanners are analyzed. At present, Lu2(1−x)Y2xSiO5 (LYSO) is the scintillation crystal with the best comprehensive properties. LaBr3 performs even better regarding the timing characteristics and light output; however, LaBr3 has not been used in any PET scanner because of its deliquescence. Detectors made of Gd3(Ga, Al)5O12 (GAGG) exhibit a high depth of interaction (DOI) resolution and have considerable application potential. The application fields of PET are constantly expanding, and its future development aims to achieve high spatial resolution and high sensitivity, which require scintillation crystals with better performance.
Simulation of Microstructure Evolution in Mg Alloys by Phase-Field Methods: A Review
Authors: Wang Yongbiao , Zhang Yang , Liu Xintian , Wang Jiaxin , Xie Xinyuan , Jiang Junjie , Liu Jianxiu , Liu Hong , Wu Yujuan , Dong Shuai , Peng Liming
Published: September 2022

Microstructure is one of the vital factors that determine the mechanical properties of magnesium (Mg) alloys. However, traditional microstructure characterization methods hardly satisfy the needs of tracking the morphological evolution of Mg alloys. With the rapid development of computer simulation, using the phase-field method to simulate the evolution of microstructures in Mg alloys has become the new norm. This article provides a review of the applications of the phase-field method in Mg alloys. First, classic phase-field models and the derived multi-phase and polycrystalline phase-field models are reviewed, then a review of the twin and solid-state phase transition phase-field models was undertaken, and the research progress of phase-field simulation in the solidification, recrystallization, and solid-state phase transformation of Mg alloys, were gradually introduced. In addition, unresolved problems of phase-field simulation were summarized, and the possible direction of future studies on phase-field simulation in Mg alloys field were discussed.
Evaluation of a Navigated 3D Ultrasound Integration for Brain Tumor Surgery: First Results of an Ongoing Prospective Study
Authors: Aleo Danilo , Elshaer Ziad , Pfnür Andreas , Schuler Patrick J. , Fontanella Marco Maria , Wirtz Christian Rainer , Pala Andrej , Coburger Jan
Published: September 2022

The aim of the study was to assess the quality, accuracy and benefit of navigated 2D and 3D ultrasound for intra-axial tumor surgery in a prospective study. Patients intended for gross total resection were consecutively enrolled. Intraoperatively, a 2D and 3D iUS-based resection was performed. During surgery, the image quality, clinical benefit and navigation accuracy were recorded based on a standardized protocol using Likert’s scales. A total of 16 consecutive patients were included. Mean ratings of image quality in 2D iUS were significantly higher than in 3D iUS (p < 0.001). There was no relevant decrease in rating during the surgery in 2D and 3D iUS (p > 0.46). The benefit was rated 2.2 in 2D iUS and 2.6 in 3D iUS (p = 0.08). The benefit remained stable in 2D, while there was a slight decrease in the benefit in 3D after complete tumor resection (p = 0.09). The accuracy was similar in both (mean 2.2 p = 0.88). Seven patients had a small tumor remnant in intraoperative MRT (mean 0.98 cm3) that was not appreciated with iUS. Crucially, 3D iUS allows for an accurate intraoperative update of imaging with slightly lower image quality than 2D iUS. Our preliminary data suggest that the benefit and accuracy of 2D and 3D iUS navigation do not undergo significant variations during tumor resection.
Predator-Induced Nocturnal Benthic Emergence: Field and Experimental Evidence for an Unknown Behavioral Escape Mechanism along the Coral Reef–Seagrass Interface
Authors: Blackmon Derrick C. , Valentine John F.
Published: September 2022

Previously, using plankton tows, and emergence and settlement traps, we documented persistent widespread nocturnal emergence, and planktonic redistribution, of benthic macroinvertebrates along the coral reef–seagrass interface at two geographically separated locations. We also documented that emergence intensity varies with distance from the reef, leading us to hypothesize that the spatial pattern of emergence is determined by the foraging patterns of nocturnally active, bottom-feeding, mid-level consumers (mainly grunts). In this second study, we coupled those previously published data with nocturnal fish surveys concurrently conducted along belt transects placed at the same locations as the emergence trap collections, and a controlled laboratory experiment, to test this hypothesis. The results of these analyses find that variability in the density of nocturnally active, bottom-feeding fish is strongly positively correlated with emergence intensity, regardless of site or season. Results from the laboratory experiments show that nocturnal invertebrate emergence is significantly higher in the presence of one bottom-feeding fish (the blue-striped grunt Haemulon sciurus) than in microcosms that do not contain this predator. Overall, this study shows that such processes may explain how benthic prey can avoid capture by nocturnally active, bottom-feeding predators and persist in the predator-rich seagrass habitats that surround coral reefs in the Florida Keys National Marine Sanctuary. This study also points out the need to consider nocturnal processes when studying seagrass biodiversity in a predator-rich environment.
Variations in Fish Community Structure at the Lagoon of Yongshu Reef, South China Sea between 1999 and 2016–2019
Authors: Dai Xuejiao , Li Yuanjie , Cai Yancong , Gong Yuyan , Zhang Jun , Chen Zuozhi
Published: September 2022

Owing to climate change and anthropogenic stressors, the abundance and diversity of reef fishes have globally decreased. However, we know little about the long-term change in reef fishes in the South China Sea (SCS). To reveal the response of reef fishes to these threats in the SCS, based on the fish specimens at Yongshu Reef lagoon collected in 1999 and 2016–2019, this study investigated variations in fish composition and community structure. Additionally, we inferred the changes in the coral cover of Yongshu Reef based on the change of the coral cover of near Meiji Reef in the SCS, sea surface temperature (SST) in Yongshu Reef, and total annual catch of Epinephelinae from China in the SCS. We found that compared with 1999, the number of dominant species in 2016–2019 decreased. The relative dominance of the first dominant species increased from 24.46 in 1999 to 39.44 in 2016–2019. Indices of catch per unit effort, species diversity and richness declined from 1999 to 2016–2019. Community pattern changed with some species with a higher trophic level (3.7–4.5) decreased, while those with lower trophic level (2.2–4.1) increased greatly. Some species with high economic value and important ecological functions decreased or disappeared locally. Correlation analysis indicated that declining coral cover, increasing fishing and rising SST were clearly associated with changes in fish community structure at Yongshu Reef. We speculated that declining coral cover and increasing fishing had a direct impact on the degradation of fish communities at Yongshu Reef lagoon, but increasing SST had an indirect impact on that. To conserve coral reef fish, it is recommended to take rigorous measures for improving habitat and protecting resource.
Computer-Assisted Differentiation between Colon-Mesocolon and Retroperitoneum Using Hyperspectral Imaging (HSI) Technology
Authors: Okamoto Nariaki , Rodríguez-Luna María Rita , Bencteux Valentin , Al-Taher Mahdi , Cinelli Lorenzo , Felli Eric , Urade Takeshi , Nkusi Richard , Mutter Didier , Marescaux Jacques , Hostettler Alexandre , Collins Toby , Diana Michele
Published: September 2022

Complete mesocolic excision (CME), which involves the adequate resection of the tumor-bearing colonic segment with “en bloc” removal of its mesocolon along embryological fascial planes is associated with superior oncological outcomes. However, CME presents a higher complication rate compared to non-CME resections due to a higher risk of vascular injury. Hyperspectral imaging (HSI) is a contrast-free optical imaging technology, which facilitates the quantitative imaging of physiological tissue parameters and the visualization of anatomical structures. This study evaluates the accuracy of HSI combined with deep learning (DL) to differentiate the colon and its mesenteric tissue from retroperitoneal tissue. In an animal study including 20 pig models, intraoperative hyperspectral images of the sigmoid colon, sigmoid mesentery, and retroperitoneum were recorded. A convolutional neural network (CNN) was trained to distinguish the two tissue classes using HSI data, validated with a leave-one-out cross-validation process. The overall recognition sensitivity of the tissues to be preserved (retroperitoneum) and the tissues to be resected (colon and mesentery) was 79.0 ± 21.0% and 86.0 ± 16.0%, respectively. Automatic classification based on HSI and CNNs is a promising tool to automatically, non-invasively, and objectively differentiate the colon and its mesentery from retroperitoneal tissue.
Sequential Ultrasound Assessment of Peri-Articular Soft Tissue in Adhesive Capsulitis of the Shoulder: Correlations with Clinical Impairments—Sequential Ultrasound in Adhesive Capsulitis
Authors: Lee Byung Chan , Yeo Seung Mi , Do Jong Geol , Hwang Ji Hye
Published: September 2022

Recently, ultrasound measurements of the shoulder such as thickening of the rotator interval (RI) and the axillary recess (AR) are suggested as specific indicators of adhesive capsulitis. Herein, we evaluated the sequential changes in ultrasound parameters and clinical impairments and the correlation between the two in the case of adhesive capsulitis through a prospective observational study of 56 patients with adhesive capsulitis. Clinical assessments and ultrasound parameters, including the thicknesses of the RI and AR, were surveyed at baseline and after 1, 3, and 6 months. In 56 patients with adhesive capsulitis, the thickness of the AR significantly decreased at each follow-up evaluation, but the thickness of the RI showed a significant decrease only between the baseline and 1-month evaluation. In repeated analyses of correlation, the thickness of the AR was strongly correlated with all clinical impairments except the pain at rest and range of internal rotation in the affected shoulder. The thickness of AR was correlated with clinical impairments in patients with adhesive capsulitis during the 6 months follow up and could be useful as a surrogate marker in patients with adhesive capsulitis.
An Asymmetric Contrastive Loss for Handling Imbalanced Datasets
Authors: Vito Valentino , Stefanus Lim Yohanes
Published: September 2022

Contrastive learning is a representation learning method performed by contrasting a sample to other similar samples so that they are brought closely together, forming clusters in the feature space. The learning process is typically conducted using a two-stage training architecture, and it utilizes the contrastive loss (CL) for its feature learning. Contrastive learning has been shown to be quite successful in handling imbalanced datasets, in which some classes are overrepresented while some others are underrepresented. However, previous studies have not specifically modified CL for imbalanced datasets. In this work, we introduce an asymmetric version of CL, referred to as ACL, in order to directly address the problem of class imbalance. In addition, we propose the asymmetric focal contrastive loss (AFCL) as a further generalization of both ACL and focal contrastive loss (FCL). The results on the imbalanced FMNIST and ISIC 2018 datasets show that the AFCL is capable of outperforming the CL and FCL in terms of both weighted and unweighted classification accuracies.
Interdependent Autonomous Human–Machine Systems: The Complementarity of Fitness, Vulnerability and Evolution
Authors: Lawless William F.
Published: September 2022

For the science of autonomous human–machine systems, traditional causal-time interpretations of reality in known contexts are sufficient for rational decisions and actions to be taken, but not for uncertain or dynamic contexts, nor for building the best teams. First, unlike game theory where the contexts are constructed for players, or machine learning where contexts must be stable, when facing uncertainty or conflict, a rational process is insufficient for decisions or actions to be taken; second, as supported by the literature, rational explanations cannot disaggregate human–machine teams. In the first case, interdependent humans facing uncertainty spontaneously engage in debate over complementary tradeoffs in a search for the best path forward, characterized by maximum entropy production (MEP); however, in the second case, signified by a reduction in structural entropy production (SEP), interdependent team structures make it rationally impossible to discern what creates better teams. In our review of evidence for SEP–MEP complementarity for teams, we found that structural redundancy for top global oil producers, replicated for top global militaries, impedes interdependence and promotes corruption. Next, using UN data for Middle Eastern North African nations plus Israel, we found that a nation’s structure of education is significantly associated with MEP by the number of patents it produces; this conflicts with our earlier finding that a U.S. Air Force education in air combat maneuvering was not associated with the best performance in air combat, but air combat flight training was. These last two results exemplify that SEP–MEP interactions by the team’s best members are made by orthogonal contributions. We extend our theory to find that competition between teams hinges on vulnerability, a complementary excess of SEP and reduced MEP, which generalizes to autonomous human–machine systems.
Does Social Investment Influence Poverty and Economic Growth in South Africa: A Cointegration Analysis?
Authors: Ogujiuba Kanayo , Mngometulu Ntombifuthi
Published: September 2022

Despite having a middle-income status, many South African households are either already in or are about to fall into poverty. The income and wealth distribution in South Africa is among the most uneven in the world, and many households lack even the most basic access to healthcare, clean energy, and clean water. Although it has increased government spending, South Africa’s government has made significant steps to combat poverty and inequality and encourage economic growth. Understanding the connection between social investment, poverty, inequality, and economic growth is, therefore, necessary to comprehend the ambiguity that currently prevails. In order to analyze the effects of social investment on poverty and economic growth in South Africa between 1990 and 2020, this paper uses the cointegration technique. The cointegration estimates indicate that there is no correlation between social investment, poverty, inequality, and economic development. According to study findings, South Africa’s macroeconomic policies, which seem to be more urban-focused, need to be modified and redirected into inclusive policies with strict constraints to assure their implementation. The transformation of rural and township life will be aided by this plan.
Fuel Cell Voltage Regulation Using Dynamic Integral Sliding Mode Control
Authors: Yasin Amina , Yasin Abdul Rehman , Saqib Muhammad Bilal , Zia Saba , Riaz Mudassar , Nazir Robina , Abdalla Ridab Adlan Elamin , Bajwa Shaherbano
Published: September 2022

Fuel cells guarantee ecological ways of electricity production by promising zero emissions. Proton exchange membrane fuel cells (PEMFCs) are considered one of the safest methods, with a low operating temperature and maximum conversion efficiency. In order to harness the full potential of PEMFC, it is imperative to ensure the membrane’s safety through appropriate control strategies. However, most of the strategies focus on fuel economy along with viable fuel cell life, but they do not assure constant output voltage characteristics. A comprehensive design to regulate and boost the output voltages of PEMFC under varying load conditions is addressed with dynamic integral sliding mode control (DISMC) by combining the properties of both the dynamic and integral SMC. The proposed system outperforms in robustness against parametric uncertainties and eliminates the reaching phase along with assured stability. A hardware test rig consisting of a portable PEMFC is connected to the power converter using the proposed technique that regulates voltage for varying loads and power conditions. The results are compared with a proportional integral (PI) based system. Both simulation and hardware results are provided to validate the proposed technique. The experimental results show improvements of 35.4%, 34% and 50% in the rise time, settling time and robustness, respectively.
Design and Implementation of Real-Time Image Acquisition Chip Based on Triple-Hybrid Encryption System
Authors: Li Jiakun , Luo Yixuan , Wang Fei , Gao Wei
Published: September 2022

With the improved hardware storage capabilities and the rapid development of artificial intelligence image recognition technology, information is becoming image-oriented. Increasingly sensitive image data needs to be processed. When facing a large amount of real-time sensitive image data encryption and decryption, ensuring both the speed and the security is an urgent demand. This paper proposes an original triple-hybrid encryption system for a real-time sensitive image acquisition chip. This encryption system optimizes the symmetric encryption algorithm AES, asymmetric encryption algorithm ECC, and chip authentication algorithm PUF in pursuit of security, calculation speed, and to ensure that it is lightweight. The three optimized algorithms are further mixed and reused on the circuit level, to ensure mutual protection while making full use of their advantages. Apart from sensitive image protection at the algorithm level, the image chip itself is also protected by an innovative PUF chip authentication method that prevents it from being tampered with and copied. Triple-hybrid encryption system hardware implementation achieves a frequency of 132.5 MHz under the Virtex-5 FPGA with an area of 2834 Slices; with Virtex-7 FPGA, it reaches a frequency of 137.6 MHz with an area of 2716 Slices. The system is also implemented on SMIC 40 nm ASIC, and the clock frequency reaches 480 MHz and the area is 94,812.4 μm2. In terms of computing speed, the peak image encryption speed is 6.15 Gb/s, which meets the real-time image encryption requirement. In terms of hardware resource usage, AES reduced the hardware area by 60.1% compared with the results in other literature, ECC reduced the hardware area by 43.4%, and the PUF hardware area decreased exponentially with the increase in information entropy. The implementation of the three algorithms is reasonable and cost-effective, and the mixture of algorithms does not increase the required capacity of the hardware resource. The triple-hybrid encryption system cooperates with the image acquisition subsystem, storage subsystem, and asynchronous clock subsystem through software control to realize a complete triple-hybrid encryption SoC chip solution, and was successfully taped-out under the SMIC 40 nm process with all constraints passed and a total area of 10.59 mm2.
Used Car Price Prediction Based on the Iterative Framework of XGBoost+LightGBM
Authors: Cui Baoyang , Ye Zhonglin , Zhao Haixing , Renqing Zhuome , Meng Lei , Yang Yanlin
Published: September 2022

To better address the problem of the low prediction accuracy of used car prices under a large number of features and big data and improve the accuracy of existing deep learning models, an iterative framework combining XGBoost and LightGBM is proposed in this paper. First, the relevant data processing is carried out for the initial recognition features. Then, by training the deep residual network, the predicted results are fused with the original features as new features. Finally, the new feature group is input into the iteration framework for training, the iteration is stopped, and the results are output when the performance reaches the highest value. These experimental results show that the combination of the deep residual network and iterative framework has a better prediction accuracy than the random forest and deep residual network. At the same time, by combining the existing mainstream methods with the iterative framework, it is verified that the iterative framework proposed in this paper can be applied to other models and greatly improve the prediction performance of other models.
Experimental Diagnosis of Broken Rotor Bar Faults in Induction Motors at Low Slip via Hilbert Envelope and Optimized Subtractive Clustering Adaptive Neuro-Fuzzy Inference System
Authors: Chehaidia Seif Eddine , Cherif Hakima , Alraddadi Musfer , Mosaad Mohamed Ibrahim , Bouchelaghem Abdelaziz Mahmoud
Published: September 2022

Knowledge of the distinctive frequencies and amplitudes of broken rotor bar (BRB) faults in the induction motor (IM) is essential for most fault diagnosis methods. Fast Fourier transform (FFT) is widely applied to diagnose the faults within BRBs. However, this method does not provide satisfactory results if it is applied directly to the stator current signal at low slip because a high-resolution spectrum is required to separate the different components of the frequency. To address this problem, this paper proposes an efficient method based on a Hilbert fast Fourier transform (HFFT) approach, which is used to extract the envelope from the stator current using the Hilbert transform (HT) at low slip. Then, the stator current envelope is analyzed using the fast Fourier transform (FFT) to obtain the amplitude and frequency of the particular harmonic. These data were recently collected and selected as BRB fault features and were employed as adaptive neuro-fuzzy inference system (ANFIS) inputs for BRB fault autodiagnosis and classification. To identify the BRB defect by determining the number of broken bars in the rotor, two ANFIS models are proposed: ANFIS grid partitioning (ANFIS-GP) and ANFIS-subtractive clustering (ANFIS-SC). To validate the effectiveness of the proposed method, three different motors were used during experiments under various loads; the first was with one broken bar, the second was with two adjacent broken bars, and the third was a healthy motor. The obtained results confirmed the effectiveness and the robustness of the proposed method, which is based on the combination of HFFT-ANFIS-SC to diagnose the BRB faults and quantify the number of broken bars under different load conditions (under low and high slip) precisely with minimal errors (this method had an MSE of 10-14 and 10-7 for the RMSE) compared to the method based on the combination of HFFT-ANFIS-GP.
Modeling of Fuel Cells Characteristics in Relation to Real Driving Conditions of FCHEV Vehicles
Authors: Pielecha Ireneusz
Published: September 2022

Fuel cells are one of the zero-emission elements of modern automotive drive systems. This article presents theoretical identification of the component parameters of indicators for the fuel cell operating conditions. Activation, ohmic, and mass transport losses were identified. Current–voltage characteristics were provided along with an analysis of typical cell losses. The actual performance characteristics of fuel cells were analyzed for Toyota Mirai I and II generation vehicles. The fuel cells operating conditions were derived and analyzed in the context of real driving conditions. Therefore, urban, rural, and motorway conditions were used. The vehicles were equipped with PEM fuel cells supplying power equal to 114 kW (1st gen.) or 128 kW (2nd gen.). The average fuel cell stack power values depend on the driving conditions: urban (about 10 kW), rural (20 kW) and motorway (about 30–40 kW) driving modes. The different power ratings of fuel cells combined with different battery generations resulted in a variation in the cells operating conditions. Analyses conducted in various traffic conditions indicated the possibility of determining losses related to the fuel cells. The analysis of fuel cell losses shows the greatest values for activation losses when the cells are under high load (for both generations)—i.e., in motorway driving conditions. The voltage of resistive losses reached its maximum in urban driving conditions when the load on the fuel cells was small.
Dual-Zone Gas Flow Characteristics for Gas Drainage Considering Anomalous Diffusion
Authors: Wang Xiangyu , Zhou Hongwei , Zhang Lei , Hou Wei , Cheng Jianchao
Published: September 2022

Gas drainage in deep coal seam is a critical issue ensuring the safety of mining and an important measure to obtain gas as a kind of clean available energy. In order to get a better understanding of gas flow and diffusion for gas drainage in deep coal seams, a dual-zone gas flow model, including the drainage damage zone (DDZ) and the non-damaged zone (NDZ), are characterized by different permeability models and anomalous diffusion models to analyze the influence of damage induced by drilling boreholes on gas flow. The permeability model and anomalous diffusion model are verified with experiment and field data. A series of finite-element numerical simulations based on developed models are carried out, indicating that, compared with normal diffusion model, the anomalous diffusion is more accurate and appropriate to field test data. The coal fracture permeability increases rapidly with the distance decreasing from the borehole, and the area of DDZ is increasing significantly with the extraction time. Moreover, with the increasing of fractional derivative order, the diffusion model transforms the anomalous diffusion to the normal gradually, and the decay of gas pressure is aggravated. The higher value of non-uniform coefficient results in the larger increment of fracture permeability. The permeability–damage coefficient increase makes the increment of fracture permeability bigger.
Review of Medium-Voltage Switchgear Fault Detection in a Condition-Based Monitoring System by Using Deep Learning
Authors: Alsumaidaee Yaseen , Yaw Chong , Koh Siaw , Tiong Sieh , Chen Chai , Ali Kharudin
Published: September 2022

In power energy distribution networks, switchgear is considered critical equipment. This is because the act of monitoring the operation and condition of switchgear, as well as performing the required corrective maintenance on any potentially problematic equipment, is critical. A single event may harm thousands of customers over time and pose a significant risk to operational staff. Many considerations must be put in place before using outages to switch down the system since they may raise maintenance costs and disrupt the power supply to users. As a result, proper interpretation of switchgear status evaluations is critical for the early identification of possible faults. Existing ultrasound condition-based monitoring (CBM) diagnostic testing techniques require the tester to manually interpret test data. This study aims to review the status of the recent development of CBM techniques with faults in switchgear. The current trend in electrification will be toward the safety and sustainability of power grid assets, which involves an evaluation of the electrical systems’ and components’ health and grids for medium-voltage distribution. This work provides a current state-of-the-art evaluation of deep learning (DL)-based smart diagnostics that were used to identify partial discharges and localize them. DL techniques are discussed and categorized, with special attention given to those sophisticated in the last five years. The key features of each method, such as fundamental approach and accuracy, are outlined and compared in depth. The benefits and drawbacks of various DL algorithms are also examined. The technological constraints that hinder sophisticated PD diagnostics from being implemented in companies are also recognized. Lastly, various remedies are suggested, as well as future research prospects.
Day-Ahead Optimal Scheduling of Integrated Energy System Based on Type-II Fuzzy Interval Chance-Constrained Programming
Authors: Sun Xinyu , Wu Hao , Guo Siqi , Zheng Lingwei
Published: September 2022

Renewable energy sources (RES) generation has huge environmental and social benefits, as a clean energy source with great potential. However, the difference in the uncertainty characteristics of RES and electric–thermal loads poses a significant challenge to the optimal schedule of an integrated energy system (IES). Therefore, for the different characteristics of the multiple uncertainties of IES, this paper proposes a type-II fuzzy interval chance-constrained programming (T2FICCP)-based optimization model to solve the above problem. In this model, type-II fuzzy sets are used to describe the uncertainty of RES in an IES, and interval numbers are used to describe the load uncertainty, thus constructing a T2FICCP-based IES day-ahead economic scheduling model. The model was resolved with a hybrid algorithm based on interval linear programming and T2FICCP. The simulations are conducted for a total of 20 randomly selected days to obtain the advance operation plan of each unit and the operation cost of the system. The research results show that the T2FICCP optimization model has less dependence on RES output power and load forecasting error, so can effectively improve the economy of IES, while ensuring the safe and stable operation of the system.
An Experimental Approach to Energy and Exergy Analyses of a Hybrid PV/T System with Simultaneous Water and Air Cooling
Authors: Mourshed Monjur , Masuk Nahid Imtiaz , Nguyen Huy Quoc , Shabani Bahman
Published: September 2022

In this paper, the effects of simultaneous air and water cooling on the energy performances of a single-pass hybrid PV/T system are experimentally investigated. Both air and water are used as coolants and are tested at four different mass flow rates, ranging from 0.0014 to 0.0026 kg/s. It is found that the overall efficiency of the PV/T system is dependent on the solar intensity and mass flow rate of coolants. Maximum PV/T system efficiency is found to be 62.2% for a simultaneous flow of water and air at a 0.0026 kg/s flow rate, which is 35.5% higher than the efficiency found at 0.0014 kg/s coolant flow rate. Maximum thermal energy outputs are 85.8 and 211.84 W/m2 while using air- and water-based coolants, respectively. Exergy analysis of the developed system indicates that exergy efficiency increased by up to two times by introducing simultaneous air and water cooling in this PV/T system.
Fractal Analysis and Classification of Pore Structures of High-Rank Coal in Qinshui Basin, China
Authors: Zhao Difei , Guo Yinghai , Wang Geoff , Guan Xin , Zhou Xueqing , Liu Jing
Published: September 2022

The influence of high-rank coal’s pore characteristics on the physical properties, gas-bearing properties, and exploitation of coal reservoirs is becoming more and more prominent. How to establish the classification to describe the pore networks combining quantitative and qualitative characteristics has emerged as a major problem, which may offer a scientific foundation to deepen the understanding of this issue. In this research, the structure and fractal characteristics of reservoir pores were determined after analyzing 20 high-rank coal samples from Xinjing Coal Mine in the Qinshui Basin with the application of the high-pressure mercury intrusion method (HPMI) and argon ion polishing–field emission scanning electron microscopy (AIP–FESEM). The results show that the tested coal samples were bipolar distributed, with transitional pores and micropores dominating the pore volume, followed by macropores. The Menger sponge fractal models manifested two or three distinct straight-line segments with demarcation points of 65 nm and 1000 nm. A natural classification with three major pore types of diffusion pores (D-pores), seepage pores (S-pores), and pico pores (P-pores), demarcated by pore size intervals of 65 nm and 1 nm and seven sub-types, was established to relate pores to pore networks based on these fractal characteristics and the kinetic characteristics of methane molecules. This classification scheme can characterize the relationship between pore types and the corresponding major occurrence and transport mechanisms of the gas. In addition, P-pores and D-pores are predominately nanoscale OM pores with three major genetic types of organic constituent interparticle pores (5–200 nm), metamorphic pores (<5 nm), and intermorphic pores (<5 nm). S-pores are more complex in origin and shape features, and the major types include outgas pores, plant tissue residual pores, mineral-related pores, and microfractures. The mean radius (Pa), total pore volume (Vt), apparent porosity (Φ), and volume ratio of macro- and mesopores were positively correlated with the fractal dimension D1 of S-pores (>65 nm). Since fractal analysis is a more comprehensive characterization of reservoir structure and quantitatively reflects the pore structure, undulating state, and roughness of the inner surface, fractal parameters can be used as an important index to describe the pore structure characteristics of high-rank coal reservoirs.
Foliar Application of Selenium Reduces Cadmium Accumulation in Walnut Seedlings
Authors: Wang Bingwen , Zhang Dangquan , Wang Wenfeng , Song Yukun , Lu Mengfei , Ding Shen
Published: September 2022

Cadmium (Cd) and selenium (Se) could jointly affect plant growth. To investigate the affect of Se on the Cd accumulation in Juglans regia and the physiological mechanism by which Se regulates Cd-induced oxidative stress, in this study, the effects of different foliar application doses of Se (0 (Se0), 20 (Se20), and 200 (Se200) μM) on J. regia (variety Xinfeng) seedlings under Cd stress (5 mM) were determined. The results show that exogenous application of Se (Se20 and Se200) increased walnut biomass compared with Se0 under Cd stress. Under Cd stress, exogenous application of 20 μM Se increased the catalase (CAT), peroxidase (POD), and ascorbate oxidase (AAO) activities in walnut roots and the CAT and AAO activities in walnut leaves, and exogenous application of 200 μM Se increased the CAT, POD, and AAO activities in walnut roots. Furthermore, under Cd stress, exogenous application of 20 and 200 μM Se both decreased the contents of superoxide (O2•−), hydrogen peroxide (H2O2), and malondialdehyde (MDA) in walnut roots and the content of MDA in walnut leaves. Moreover, application of 20 and 200 μM Se both reduced the accumulation of Cd in the root, wood, bark, and leaves of walnuts, and application of 200 μM Se enhanced Se concentration in the root, wood, bark, and leaves. Overall, exogenous application of Se, especially 200 μM Se, could reduce Cd accumulation and enhance CAT, POD, and AAO activities in Cd-stressed walnut roots, thus alleviating Cd stress. This study provides technical guidance for reducing the effects of Cd stress on walnut growth.
Performance of Iron(II)-Sulphate-Treated Norway Spruce and Siberian Larch in Laboratory and Outdoor Tests
Authors: Lesar Boštjan , Humar Miha
Published: September 2022

Wood in outdoor applications is exposed to various environmental factors that cause weathering. Weathering is important, primarily from an aesthetic standpoint and predominantly in wooden claddings. However, not all parts of claddings are equally exposed to weathering. Sections exposed to UV radiation and moisture discolour faster than less exposed sections, such as wood under roof overhangs. Architects and owners seek a uniform appearance in buildings. To achieve fast and uniform greying, a surface treatment with iron(II) sulphate can be used. Such a treatment results in an appearance that is similar to that resulting from natural greying. However, iron compounds do not exert a biocidal effect; therefore, it is desirable to upgrade iron(II) sulphate aqueous solution with boric acid and quarterly ammonium compounds. To this end, spruce and larch samples were treated with varying concentrations of iron(II) sulphate and biocides. After treatment, the inherent durability, water performance and resistance dose (DRd) were determined according to the Meyer-Veltrup model. The samples were also exposed outdoor conditions. During exposure, colour changes and iron leaching were monitored. The results show that the addition of biocides does not affect the rate of colour change and the final colour, which is similar to natural greying after 36 weeks of outdoor exposure. The addition of biocides exerted a positive effect on the durability of treated wood, despite the low retention of preservative solutions. The water behaviour of the treated wood had little effect on the resistance dose, with a more considerable influence on inherent durability. The addition of biocides can increase the resistance dose up to 2.4 (Fe5B0.2Q0.2). On all spruce and larch samples treated with iron(II) sulphate and exposed to outdoor conditions, the colour change in the first week was roughly comparable to the final state. However, 40% of the iron had leached from the surface after only one week of exposure.