bluuebunny/crossref_metadata_2025 huggingface dataset:
A Bizarre Cause of Acute Appendicitis in a Pediatric Patient: An Ingested Tooth
Authors: Pogorelić Zenon , Čohadžić Tin
Published: January 2023

(1) Background: Among all possible causes, foreign bodies are the rarest cause of appendicitis in the pediatric population. In the majority of cases, ingested foreign bodies pass through the gastrointestinal tract without causing symptoms. However, those foreign bodies that pass through the lumen of the vermiform appendix cannot re-enter the colon and may cause acute appendicitis. So far, various foreign bodies have been described to enter the appendix and cause acute appendicitis, such as seeds, needles, toothpicks, plant material, or even hair. Tooth or dental implants as a cause of acute appendicitis have been described in only a few cases. To our knowledge, this is the first described case of the tooth causing acute appendicitis in the pediatric population. (2) Case presentation: A 14-year-old male patient presented to the emergency department complaining of pain in the right lower quadrant of the abdomen and vomiting that persisted for approximately 24 h. Until then, the patient was healthy and had no concomitant diseases. Physical examination revealed guarding and tenderness in the right lower abdominal quadrant. The white blood cell count was 17.1 × 109/L with a neutrophil count of 91.1% and a C-reactive protein of 39.3 mg/dL. Ultrasonography of the abdomen revealed a thickened, inflamed appendix with a diameter of 11 mm and free periappendicular fluid. A 9 × 6 mm foreign body at the base of the appendix was visualized. The patient was diagnosed with acute appendicitis, and an emergency laparoscopic appendectomy was performed on the same day. Intraoperatively, gangrenous appendicitis was noted and removed without complications. Upon examination of the removed specimen, it was determined that the patient’s appendicitis had been caused by an ingested tooth. As it later turned out, the patient had broken a lateral incisor while playing sports the day before admission without knowing that he had swallowed it. The patient recovered well and was discharged the day after surgery. (3) Conclusion: Although an extremely rare event, acute appendicitis can be caused by a swallowed tooth. This case highlights the importance of a thorough history in pediatric patients who present to the emergency department with suspected acute appendicitis to determine if there is a precipitating event that may have caused acute appendicitis.
Skeletal Muscle Measurements in Pediatric Hematology and Oncology: Essential Components to a Comprehensive Assessment
Authors: Rock Kelly , Addison Odessa , Gray Vicki L. , Henshaw Robert M. , Ward Christopher , Marchese Victoria
Published: January 2023

Children with hematologic and oncologic health conditions are at risk of impaired skeletal muscle strength, size, and neuromuscular activation that may limit gross motor performance. A comprehensive assessment of neuromuscular function of these children is essential to identify the trajectory of changes in skeletal muscle and to prescribe therapeutic exercise and monitor its impact. Therefore, this review aims to (a) define fundamental properties of skeletal muscle; (b) highlight methods to quantify muscle strength, size, and neuromuscular activation; (c) describe mechanisms that contribute to muscle strength and gross motor performance in children; (d) recommend clinical assessment measures; and (e) illustrate comprehensive muscle assessment in children using examples of sickle cell disease and musculoskeletal sarcoma.
Simulation of 1500 °C Thermal Shock for Novel Structural Thermal/Environmental Barrier Coatings System
Authors: Li Kaibin , Wang Weize , Yang Ting , Liu Yangguang
Published: January 2023

In recent years, with the development of SiC composites in aero-engine hot-end components, environmental barrier coatings (EBCs) have received extensive attention. Moreover, in order to elevate the service temperature, it is a developing trend to apply thermal barrier coatings (TBCs) with low thermal conductivity on EBCs coating system to form thermal/environmental barrier coatings (T/EBCs). However, the combination of high coefficient of thermal expansion (CTE) of TBCs with low CTE of EBCs often leads to premature failure due to excessive thermal expansion mismatch stress. However, a novel structural thermal barrier coating with embedded micro-agglomerated particles (EMAP TBC) by using atmospheric plasma spraying (APS) process has brought hope to solve this problem due to its low elastic modulus. Therefore, in this study, an innovative EMAP Gd2Zr2O7 T/EBCs coating system (EMAP Gd2Zr2O7/Yb2Si2O7/Si) under 1500 °C flame thermal shock was simulated and systematically studied on the SiC substrate. The results showed that the EMAP Gd2Zr2O7 T/EBCs coating system has much lower thermal stress than the conventional Gd2Zr2O7/Yb2Si2O7/Si T/EBCs coating system. Furthermore, when the thickness of each layer of the EMAP Gd2Zr2O7 T/EBCs coating system varies, to meet the thermal insulation requirements of Yb2Si2O7 layer and reduce the thermal shock stress, the thickness of the EMAP Gd2Zr2O7 layer is recommend being about 100 μm. Meanwhile, the thicknesses of Yb2Si2O7 and Si layers can be set as large as needed. In addition, with the increase in Yb2SiO5 doping content in the Yb2Si2O7 intermediate layer, the EMAP Gd2Zr2O7 T/EBCs coating system suffers a greater risk of spalling failure due to the increase in thermal stress.
The Resistance to Wear and Thermal Cracking of Laser Surface Engineered P20 Steel
Authors: Zhao Kangpei , Yan Guanghua , Li Jinhong , Guo Wenwu , Gu Jianfeng , Li Chuanwei
Published: January 2023

This study reports the microstructure and surface properties of P20 steel processed by laser surface engineering (involving surface hardening and melting), which are carried out using a fiber laser with the maximum power of 2 kW. Ultrafine martensite laths with high boundary density are formed both in the laser surface hardened layer and in the melted layer. This dramatically improves the surface hardness of the P20 steel. However, the laser surface melted layer exhibits a relatively lower hardness than the laser surface hardened layer. It can be attributed to the remarkable autotempering effect and the vaporization of alloy elements in the melted layer. The wear resistance and thermal cracking resistance of the samples treated by laser surface engineering show a significant improvement compared with the as received material. The surface hardened layer exhibits superior wear and thermal cracking resistance due to its relatively high surface hardness and plastic deformation resistance, which can effectively suppress the formation of cracks during wear and thermal cracking tests.
Effect of Sigma Phases on Moderate-Temperature Tensile Properties of Z3CN20.09M CASS Used for Primary Coolant Pipe of Nuclear Power Plant
Authors: Wang Yongqiang , Hu Chaojun , Li Na , Lin Suhua , Ge Zhangqi , Zheng Chengsi
Published: January 2023

The effect of sigma phases on the moderate-temperature tensile properties of Z3CN20.09M casting austenite stainless steel was investigated by means of isothermal treatment, scanning electron microscopy, transmission electron microscopy, instrumented nanoindentation, tensile testing, and finite element simulation. The results show that the yield strength and ultimate tensile strength of aged specimens tensile tested at moderate temperature increase remarkably with an increasing sigma phase, while the elongation at break decreased. The strain-hardening rate of aged specimens with sigma phases is higher than that of unaged specimens without sigma phases at a certain low-strain range. However, the value of the strain-hardening rate of aged specimens is lower than that of unaged specimens when the strain exceeds a certain value. The effect of the sigma phase on the tensile properties at moderate temperature is also more significant. This can be attributed to the many high-energy σ/γ2 and α/σ/γ2 incoherent phase boundaries caused by the precipitation of sigma phases. On the one hand, these boundaries hinder the movement of dislocations and subsequently accumulate dislocations to some extent, so strength is enhanced and the strain-hardening rate is improved. On the other hand, microcracks at these interfaces initiate and propagate more easily when the strain exceeds a certain value. Thus, the elongation value and the strain-hardening rate decrease.
Diagnosis and Control of Brown Leaf Spot of Kiwi (Actinidia deliciosa) Using Biochar-Zinc Oxide Nanocomposite (MB-ZnO) as a Non-Toxic Bio-Fungicides
Authors: Kamal Asif , Ali Musrat , Farraj Dunia A. Al , Al-Zaidi Enshad M. , Khizar Maria , Aljaaidi Reem Amer , Elshikh Mohmed S. , Munis Muhammad Farooq Hussain
Published: January 2023

Kiwi is one of the best natural sources of vitamin C and has wide applications. During October–November 2021, small brown spots were examined on the Kiwi leaves. The diseased leaf samples were collected and placed on potato dextrose agar nutrient media for diagnosis. Morphological, anatomical, and molecular studies revealed this disease-causing agent to be Rhizopus oryzae. Molecular characterizations of the isolated pathogen were performed by using actin translation elongation factor (EF-1α) and ribosomal deoxyribose nucleotide inter transcribed sequence (rDNA ITS ITS1/ITS4) and elongation factors (EFl-F/EFl-R) primers. A BLAST study of the resultant ITS1/ITS4 sequence showed > 99% resemblance with R. oryzae (MT603964.1), while the EF-1α sequence revealed 100% similarity with translation elongation factor-1α gene of R. oryzae (MK510718.1). The obtained ITS1/ITS4 sequence was submitted to NCBI (MW603842.1). Koch’s postulates established the pathogenicity of isolated R. oryzae and proved it to be the brown spot pathogen of Kiwi. For the environmentally-friendly management of Kiwi leaf spot, maize biochar-Zinc Oxide (MB-ZnO) nanocomposite was used. The prepared nanocomposite was characterized by Fourier transform infrared (FTIR) spectroscopy, thermo gravitational analysis (TGA), X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), and energy dispersive X-ray (EDX) analysis. After successful preparation, MB-ZnO was assessed for its possible antifungal potential against R. oryzae. MB-ZnO displayed substantial growth inhibition, and the highest growth inhibition (79%) was observed at a 19 mg/mL dose rate of nanoparticles. These excellent findings propose that Ball-milled synthesis is a fast, economical, and environmentally friendly method for nanocomposite in the near future. The nanocomposite is used as a nominal substitute for chemical fungicides.
Mind the Gaps: Taxonomic, Geographic and Temporal Data of Marine Invertebrate Databases from Mozambique and São Tomé and Príncipe
Authors: Bento Marta , Niza Henrique , Cartaxana Alexandra , Bandeira Salomão , Paula José , Correia Alexandra Marçal
Published: January 2023

One of the best ways to share and disseminate biodiversity information is through the digitization of data and making it available via online databases. The rapid growth of publicly available biodiversity data is not without problems which may decrease the utility of online databases. In this study we analyze taxonomic, geographic and temporal data gaps, and bias related to existing data on selected marine invertebrate occurrences along the coastline of two African countries, Mozambique and São Tomé and Príncipe. The final marine invertebrate dataset comprises of 19.910 occurrences, but 32% of the original dataset occurrences were excluded due to data gaps. Most marine invertebrates in Mozambique were collected in seagrasses, whereas in São Tomé and Príncipe they were mostly collected offshore. The dataset has a temporal coverage from 1816 to 2019, with most occurrences collected in the last two decades. This study provides baseline information relevant to a better understanding of marine invertebrate biodiversity data gaps and bias in these habitats along the coasts of these countries. The information can be further applied to complete marine invertebrate data gaps contributing to design informed sampling strategies and advancing refined datasets that can be used in management and conservation plans in both countries.
Giant Gallbladder Tumor, Unusual Cancer—Case Report and Short Review of Literature
Authors: Constantin Adrian , Achim Florin , Turcu Tudor , Birceanu Adelina , Evsei Anca , Socea Bogdan , Predescu Dragos
Published: January 2023

Background: Giant gallbladder is an uncommon condition that can result from a benign pathology and rarely presents with malignancy. Intracholecystic papillary–tubular neoplasm (ICPN) is a relatively new entity first described by V. Adsay in 2012 and included in the World Health Classification of Digestive System Tumours in 2019. Intracholecystic papillary-tubular neoplasm is a preinvasive lesion with an incidence of around 1% that may present as four histologic subtypes—biliary, gastric, intestinal, or oncocytic—of which the biliary subtype has the highest risk of associated invasive cancer. Although invasive carcinoma is present in about 50% of cases of ICPN, these patients have a significantly better prognosis than those with usual gallbladder cancer, suggesting that the entities may have distinct biological signatures. Case report: A 77-year-old female presented to the hospital with progressive swelling in the right hemiabdomen, a loss of appetite, and weight loss. MRI highlighted a giant abdominal tumor located in the right hypochondrium and right abdominal flank with liver invasion (segment V). Preoperatively, a gallbladder 25 × 17 cm in size was noted, and the patient underwent radical cholecystectomy. It was surprising to find such a giant malignant gallbladder tumor, diagnosed as invasive poorly cohesive carcinoma associated with ICPN. Discussion: A megacholecyst is a rare discovery. Although most often found in benign pathologies, giant gallbladder cancer can be considered. The neoplastic features and the loco-regional extension of the tumor must be evaluated by imaging scans. Few cases of giant benign gallbladder have been reported in the literature; however, this appeared to be the largest resectable gallbladder carcinoma reported to date according to the literature. Conclusion: The stage of gallbladder neoplasia is not correlated with the size of the gallbladder. Regardless of tumor size, the prognosis seems to be directly related to the stage, morphology, and resectability.
Spectral Similarity Measures for In Vivo Human Tissue Discrimination Based on Hyperspectral Imaging
Authors: Pathak Priya , Chalopin Claire , Zick Laura , Köhler Hannes , Pfahl Annekatrin , Rayes Nada , Gockel Ines , Neumuth Thomas , Melzer Andreas , Jansen-Winkeln Boris , Maktabi Marianne
Published: January 2023

Problem: Similarity measures are widely used as an approved method for spectral discrimination or identification with their applications in different areas of scientific research. Even though a range of works have been presented, only a few showed slightly promising results for human tissue, and these were mostly focused on pathological and non-pathological tissue classification. Methods: In this work, several spectral similarity measures on hyperspectral (HS) images of in vivo human tissue were evaluated for tissue discrimination purposes. Moreover, we introduced two new hybrid spectral measures, called SID-JM-TAN(SAM) and SID-JM-TAN(SCA). We analyzed spectral signatures obtained from 13 different human tissue types and two different materials (gauze, instruments), collected from HS images of 100 patients during surgeries. Results: The quantitative results showed the reliable performance of the different similarity measures and the proposed hybrid measures for tissue discrimination purposes. The latter produced higher discrimination values, up to 6.7 times more than the classical spectral similarity measures. Moreover, an application of the similarity measures was presented to support the annotations of the HS images. We showed that the automatic checking of tissue-annotated thyroid and colon tissues was successful in 73% and 60% of the total spectra, respectively. The hybrid measures showed the highest performance. Furthermore, the automatic labeling of wrongly annotated tissues was similar for all measures, with an accuracy of up to 90%. Conclusion: In future work, the proposed spectral similarity measures will be integrated with tools to support physicians in annotations and tissue labeling of HS images.
Upstaging and Downstaging in Gliomas—Clinical Implications for the Fifth Edition of the World Health Organization Classification of Tumors of the Central Nervous System
Authors: Trifănescu Oana Gabriela , Trifănescu Raluca Alexandra , Mitrică Radu , Mitrea Dan , Ciornei Ana , Georgescu Mihai , Butnariu Ioana , Galeș Laurenția Nicoleta , Șerbănescu Luiza , Anghel Rodica Maricela , Păun Mihai-Andrei
Published: January 2023

In 2021, the 5th edition of the WHO Classification of Tumors of the Central Nervous System (WHO-CNS5) was published as the sixth volume of the international standard for brain and spinal cord tumor classification. The most remarkable practical change in the current classification involves grading gliomas according to molecular characterization. IDH mutant (10%) and IDH wild-type tumors (90%) are two different entities that possess unique biological features and various clinical outcomes regarding treatment response and overall survival. This article presents two comparative cases that highlight the clinical importance of these new classification standards. The first clinical case aimed to provide a comprehensive argument for determining the IDH status in tumors initially appearing as low-grade astrocytoma upon histologic examination, thus underlining the importance of the WHO-CNS5. The second case showed the implications of the histologic overdiagnosis of glioblastoma using the previous classification system with a treatment span of 7 years that proceeded through full-dose re-irradiation up to metronomic therapy. The new WHO-CNS5 classification significantly impacted complex neurooncological cases, thus changing the initial approach to a more precise therapeutic management.
Characteristic Chest Computed Tomography Findings for Birt–Hogg–Dube Syndrome Indicating Requirement for Genetic Evaluation
Authors: Choi Yong Jun , Park Chul Hwan , Park Hye Jung , Shin Jae Min , Kim Tae Hoon , Lee Kyung-A , Moon Duk Hwan , Lee Sungsoo , Lee Sang Eun , Byun Min Kwang
Published: January 2023

Background: Chest computed tomography (CT) findings are important for identifying Birt–Hogg–Dube (BHD) syndrome. However, the predictive power of classical criteria for chest CT findings is weak. Here, we aimed to identify more specific chest CT findings necessitating genetic examination for FLCN gene mutations. Methods: From June 2016 to December 2017, we prospectively enrolled 21 patients with multiple bilateral and basally located lung cysts on chest CT with no other apparent cause, including cases with and without spontaneous primary pneumothorax. All enrolled patients underwent FLCN mutation testing for diagnosis confirmation. Results: BHD was diagnosed in 10 of 21 enrolled patients (47.6%). There were no differences in clinical features between the BHD and non-BHD groups. Maximal cyst diameter was significantly greater in the BHD group (mean ± standard deviation; 4.1 ± 1.1 cm) than in the non-BHD group (1.6 ± 0.9 cm; p < 0.001). Diversity in cyst size was observed in 100.0% of BHD cases and 18.2% of non-BHD cases (p = 0.001). Morphological diversity was observed in 100.0% of BHD cases and 54.6% of non-BHD cases (p = 0.054). Areas under the receiver operating characteristic curves for predicting FLCN gene mutations were 0.955 and 0.909 for maximal cyst diameter and diversity in size, respectively. The optimal cut-off value for maximal diameter FLCN mutations prediction was 2.1 cm (sensitivity: 99%; specificity: 82%). Conclusions: Reliable chest CT features suggesting the need for FLCN gene mutations screening include variations in cyst size and the presence of cysts > 2.1 cm in diameter, predominantly occurring in the bilateral basal lungs.
Diagnostic Algorithm for Surgical Management of Limbal Stem Cell Deficiency
Authors: Malyugin Boris , Kalinnikova Svetlana , Isabekov Ruslan , Ostrovskiy Dmitriy , Knyazer Boris , Gerasimov Maxim
Published: January 2023

Background: Limbal stem cell deficiency (LCSD) presents several challenges. Currently, there is no clearly defined systematic approach to LSCD diagnosis that may guide surgical tactics. Methods: The medical records of 34 patients with LSCD were analyzed. Diagnostic modalities included standard (visometry, tonometry, visual field testing, slit-lamp biomicroscopy with corneal fluorescein staining, Schirmer test 1, ultrasonography) and advanced ophthalmic examination methods such as anterior segment optical coherence tomography, in vivo confocal microscopy, impression cytology, and enzyme-linked immunoassay. Results: Standard ophthalmological examination was sufficient to establish the diagnosis of LSCD in 20 (58.8%) cases, whereas advanced evaluation was needed in 14 (41.2%) cases. Depending on the results, patients with unilateral LSCD were scheduled to undergo glueless simple limbal epithelial transplantation (G-SLET) or simultaneous G-SLET and lamellar keratoplasty. Patients with bilateral LSCD with normal or increased corneal thickness were enrolled in the paralimbal oral mucosa epithelium transplantation (pLOMET) clinical trial. Conclusions: Based on the diagnostic and surgical data analyzed, the key points in LSCD diagnosis were identified, helping to guide the surgeon in selecting the appropriate surgical procedure. Finally, we proposed a novel step-by-step diagnostic algorithm and original surgical guidelines for the treatment of patients with LSCD.
Monitoring the Calibration of In-Office 3D Printers
Authors: Mukherjee Esha , Malone Luke , Tackett Edward , Gunaratnam Bakeerathan , Grant Gerald
Published: January 2023

Most desktop 3D printers lack features that allow manual calibration of printer parameters. It is crucial to assess the accuracy of printing to minimize the margin of error and variance between each print. Therefore, this study aimed to develop a method for monitoring the calibration of in-office 3D printers. A calibration coupon was designed to have a tolerance and dimensions that define nominal geometry and allow the measurement of variances occurring in X–Y axes and curvature. Ten printing cycles were run on two stereolithography (SLA) 3D printers with two different resins. Additionally, the coupons were positioned in five positions on the build platform to assess errors caused by differences in positioning. Measurements were made on the X and Y axes. No statistical difference was noted between the coupons being printed in different positions on the build platform and between the two resins at both X and Y axes of measurement (p > 0.05). Desktop 3D printers currently lack a standardized calibration protocol, which provides a closed loop for design and manufacturing of printed parts. The coupon in this study will allow monitoring the calibration of desktop 3D printers to ensure high-quality printing.
Implications of Spectral Interlacing for Quantum Graphs
Authors: Lu Junjie , Hofmann Tobias , Kuhl Ulrich , Stöckmann Hans-Jürgen
Published: January 2023

Quantum graphs are ideally suited to studying the spectral statistics of chaotic systems. Depending on the boundary conditions at the vertices, there are Neumann and Dirichlet graphs. The latter ones correspond to totally disassembled graphs with a spectrum being the superposition of the spectra of the individual bonds. According to the interlacing theorem, Neumann and Dirichlet eigenvalues on average alternate as a function of the wave number, with the consequence that the Neumann spectral statistics deviate from random matrix predictions. There is, e.g., a strict upper bound for the spacing of neighboring Neumann eigenvalues given by the number of bonds (in units of the mean level spacing). Here, we present analytic expressions for level spacing distribution and number variance for ensemble averaged spectra of Dirichlet graphs in dependence of the bond number, and compare them with numerical results. For a number of small Neumann graphs, numerical results for the same quantities are shown, and their deviations from random matrix predictions are discussed.
Classification of Kinematic and Electromyographic Signals Associated with Pathological Tremor Using Machine and Deep Learning
Authors: Pascual-Valdunciel Alejandro , Lopo-Martínez Víctor , Beltrán-Carrero Alberto J. , Sendra-Arranz Rafael , González-Sánchez Miguel , Pérez-Sánchez Javier Ricardo , Grandas Francisco , Farina Dario , Pons José L. , Oliveira Barroso Filipe , Gutiérrez Álvaro
Published: January 2023

Peripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion–extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f1 score. The LSTM models achieved 0.98 f1 scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps.
The Use of Digital Resources in Teaching during the Pandemic: What Type of Learning Have They Promoted?
Authors: Cabellos Beatriz , Pérez Echeverría M. Puy , Pozo Juan Ignacio
Published: January 2023

The COVID-19 pandemic induced an accelerated transition to digital teaching in all countries. We ask ourselves whether this massive use of digital resources promoted student–centred, dialogical, and multimodal teaching, as shown in some experimental studies, or whether, on the contrary, these resources were used only as a substitute for the teacher’s voice, maintaining content-centred teaching. We analysed 269 activities carried out during the lockdown by teachers in Spain through the System of Analysis of Teaching Activities. This analysis system considered the resources used and the learning they promoted within activities. In general, the activities were content-centred independently of the resource used. However, in a few cases, activities were student–centred. The greatest systematic difference between the two types of activities was related to who managed these resources. Only when the student managed the digital resources were the activities student-centred. Conversely, when the tasks were content-centred, teachers managed the resources. These results indicate the need to achieve proven ICT integration in education, which in turn requires a boost in teacher training aimed at both familiarising teachers with the use of digital resources and, above all, promoting a change in teachers’ conceptions about their use.
Improvement of Retinal Vessel Segmentation Method Based on U-Net
Authors: Wang Ning , Li Kefeng , Zhang Guangyuan , Zhu Zhenfang , Wang Peng
Published: January 2023

Retinal vessel segmentation remains a challenging task because the morphology of the retinal vessels reflects the health of a person, which is essential for clinical diagnosis. Therefore, achieving accurate segmentation of the retinal vessel shape can determine the patient’s physical condition in a timely manner and can prevent blindness in patients. Since the traditional retinal vascular segmentation method is manually operated, this can be time-consuming and laborious. With the development of convolutional neural networks, U-shaped networks (U-Nets) and variants show good performance in image segmentation. However, U-Net is prone to feature loss due to the operation of the encoder convolution layer and also causes the problem of mismatch in the processing of contextual information features caused by the skip connection part. Therefore, we propose an improvement of the retinal vessel segmentation method based on U-Net to segment retinal vessels accurately. In order to extract more features from encoder features, we replace the convolutional layer with ResNest network structure in feature extraction, which aims to enhance image feature extraction. In addition, a Depthwise FCA Block (DFB) module is proposed to deal with the mismatched processing of local contextual features by skip connections. Combined with the two public datasets on retinal vessel segmentation, namely DRIVE and CHASE_DB1, and comparing our method with a larger number of networks, the experimental results confirmed the effectiveness of the proposed method. Our method is better than most segmentation networks, demonstrating the method’s significant clinical value.
ML-Based Traffic Classification in an SDN-Enabled Cloud Environment
Authors: Belkadi Omayma , Vulpe Alexandru , Laaziz Yassin , Halunga Simona
Published: January 2023

Traffic classification plays an essential role in network security and management; therefore, studying traffic in emerging technologies can be useful in many ways. It can lead to troubleshooting problems, prioritizing specific traffic to provide better performance, detecting anomalies at an early stage, etc. In this work, we aim to propose an efficient machine learning method for traffic classification in an SDN/cloud platform. Traffic classification in SDN allows the management of flows by taking the application’s requirements into consideration, which leads to improved QoS. After our tests were implemented in a cloud/SDN environment, the method that we proposed showed that the supervised algorithms used (Naive Bayes, SVM (SMO), Random Forest, C4.5 (J48)) gave promising results of up to 97% when using the studied features and over 95% when using the generated features.
Development of a Wideband Slotted Antenna Array with Low Profile and Low Sidelobe
Authors: Yuan Haoyun , Li Jinkai , Zhao Zhibo , Wang Zeyu , Lodi Matteo , Gugliandolo Giovanni , Donato Nicola , Crupi Giovanni , Si Liming , Bao Xiue
Published: January 2023

In this paper, a novel multi-layered waveguide-fed slotted cavity antenna array operating in the K-band (i.e., 18–27 GHz) is presented. The antenna is composed of 64 (8 × 8) groups of 2 × 2 subarrays with low profile, and fed by a 1–64 ways waveguide corporate-feed-network. In order to obtain a low sidelobe level (SLL), the Chebyshev power distribution is introduced into the feeding network to accurately taper the power distribution among the subarrays. To realize the amplitude-tapering network, a simple T-junction, which can provide equal phase but unequal power, is used. The antenna array is analyzed and validated by using the finite element method (FEM). Simulation results demonstrate that the proposed antenna array can achieve a broad bandwidth of 21.9%, and a good gain as 29.1 dBi. Additionally, the first SLL can be as small as −28.3 dB and −20 dB in the E-plane and the H-plane, respectively. The overall size of the slotted cavity antenna array is 169.6 × 169.6 × 7.23 mm3.
Vehicle Classification Using Deep Feature Fusion and Genetic Algorithms
Authors: Alghamdi Ahmed S. , Saeed Ammar , Kamran Muhammad , Mursi Khalid T. , Almukadi Wafa Sulaiman
Published: January 2023

Vehicle classification is a challenging task in the area of image processing. It involves the classification of various vehicles based on their color, model, and make. A distinctive variety of vehicles belonging to various model categories have been developed in the automobile industry, which has made it necessary to establish a compact system that can classify vehicles within a complex model group. A well-established vehicle classification system has applications in security, vehicle monitoring in traffic cameras, route analysis in autonomous vehicles, and traffic control systems. In this paper, a hybrid model based on the integration of a pre-trained Convolutional Neural Network (CNN) and an evolutionary feature selection model is proposed for vehicle classification. The proposed model performs classification of eight different vehicle categories including sports cars, luxury cars and hybrid power-house SUVs. The used in this work is derived from Stanford car dataset that contains almost 196 cars and vehicle classes. After performing appropriate data preparation and preprocessing steps, feature learning and extraction is carried out using pre-trained VGG16 first that learns and extracts deep features from the set of input images. These features are then taken out of the last fully connected layer of VGG16, and feature optimization phase is carried out using evolution-based nature-inspired optimization model Genetic Algorithm (GA). The classification is performed using numerous SVM kernels where Cubic SVM achieves an accuracy of 99.7% and outperforms other kernels as well as excels in terns of performance as compared to the existing works.
Design Challenges in Hydrogen-Fueled Rotary Engine—A Review
Authors: Johar Tehseen , Hsieh Chiu-Fan
Published: January 2023

The rotary engine (RE) is a potential power plant for unmanned aerial vehicles (UAVs) and automobiles because of its structural and design merits. However, it has some serious drawbacks, such as frequent maintenance requirements and excessive fuel consumption. This review paper presents the current status of hydrogen-fueled rotary engine (HRE) technology and identifies the existing research and development gaps in combustion efficiency and performance of this engine that might benefit transportation sector. Focusing primarily on the research from past ten years, the crucial challenges encountered in hydrogen-powered rotary engines have been reviewed in terms of knock, hydrocarbon (HC) emissions, and seal leakages. The paper identifies the recent advances in design concepts and production approaches used in hydrogen-fueled rotary engines such as geometric models of trochoid profiles, port configurations, fuel utilization systems, and currently available computational fluid dynamics (CFD) tools. This review article is an attempt to collect and organize literature on existing design methods up to date and provide recommendations for further improvements in RE technology.
Insight into the Effect of Natural Fracture Density in a Shale Reservoir on Hydraulic Fracture Propagation: Physical Model Testing
Authors: Wu Jihuan , Li Xuguang , Wang Yu
Published: January 2023

Here, laboratory tests were conducted to examine the effects of natural fracture density (NFD) on the propagation of hydraulic fracture (HF), HF and natural fracture (NF) interaction, and the formation of the stimulated reservoir volume (SRV). Laboratory methods were proposed to prepare samples with dense, medium and spare discrete orthogonal fracture networks. After conducting a true triaxial hydraulic fracturing experiment on the synthetic blocks, the experimental results were analyzed by qualitative failure morphology descriptions, and the quantitative analysis used two proposed new indices. On the pump pressure profiles, it reflected the non-linear interactions between HFs and NFs well. For rock blocks with a dense DFN density, pump pressure curves present fluctuation shape and the degree of interaction between HF and NF is strong; however, for model blocks with a sparse DFN density, the pump pressure curves present a sudden drop shape. In addition, different propagation behaviors of NFs—offset, divert, branch, and cross NF—can be observed from the fractured model blocks. By using a proposed index of “P-SRV”, the relationship between NFD and the fracturing effectiveness was further confirmed. Furthermore, the most striking finding is that mixed mode I–II and I–III fracture types can be formed in the naturally fractured model blocks. The experimental results are beneficial for grasping the influential mechanism of NFD on the propagation of HF and for developing more accurate and full 3D-coupled simulation models for unconventional oil and gas development.
Advances in the Development of New Heat Transfer Fluids Based on Nanofluids
Authors: Colangelo Gianpiero , Milanese Marco , Starace Giuseppe , de Risi Arturo
Published: January 2023

The global energy and environmental crises are the most urgent issues confronting humanity in the coming years [...]
Band Engineering of Photocatalytic BiVO4 with Modified Vanadium States via Potassium Chloride Addition during Hydro-Thermal Synthesis and Post-Annealing
Authors: Meng Sopheak , Ogawa Takaya , Ishihara Keiichi N. , Okumura Hideyuki
Published: January 2023

The monoclinic BiVO4 in a powder state was prepared via a hydrothermal method, with the addition of KCl as a structure-directing agent. The as-prepared sample was calcined at different temperatures (400–600 °C), either in the air or in Ar gas. It is found that, though the morphology and crystal structure mostly remain unchanged, the bandgap properties are modified during calcination. A detailed analysis of the surface chemical states and optical absorption properties reveals the involvement of tetravalent vanadium ions and oxygen vacancies as the cause of the band modification. The bandgap properties are to be found tunable via changing the calcination condition, as well as the KCl concentration in the precursor. The photocatalytic properties of BiVO4 samples are greatly enhanced with the addition of KCl in the precursor, but degraded by post-annealing, where the residual Cl in the calcined sample may act as an inhibitor. The enhanced photoactivity is explained in terms of favorable faceting, bandgap modification, and heterojunction of BiVO4/BiOCl.
Models for Battery Health Assessment: A Comparative Evaluation
Authors: Vasta Ester , Scimone Tommaso , Nobile Giovanni , Eberhardt Otto , Dugo Daniele , De Benedetti Massimiliano Maurizio , Lanuzza Luigi , Scarcella Giuseppe , Patanè Luca , Arena Paolo , Cacciato Mario
Published: January 2023

Considering the importance of lithium-ion (Li-ion) batteries and the attention that the study of their degradation deserves, this work provides a review of the most important battery state of health (SOH) estimation methods. The different approaches proposed in the literature were analyzed, highlighting theoretical aspects, strengths, weaknesses and performance indices. In particular, three main categories were identified: experimental methods that include electrochemical impedance spectroscopy (EIS) and incremental capacity analysis (ICA), model-based methods that exploit equivalent electric circuit models (ECMs) and aging models (AMs) and, finally, data-driven approaches ranging from neural networks (NNs) to support vector regression (SVR). This work aims to depict a complete picture of the available techniques for SOH estimation, comparing the results obtained for different engineering applications.
Assessment of the Performance of Phasor-Based and Transients-Based Faulted Phase Identification Techniques in the Presence of Inverter Interfaced Resources
Authors: Kariyawasam Sachintha , Wijekoon Jagannath , Rajapakse Athula
Published: January 2023

Faulted phase identification is one of the segments of conventional system protection that is severely vulnerable in the presence of inverter-based resources (IBR) such as Type IV wind and solar PV power plants. The work presented in this paper investigates the effect of IBRs on the conventional phasor-based faulted phase identification methods widely implemented in contemporary commercial protection relays using theoretical analysis and simulation results. Moreover, this premise is further validated by testing commercial line protection relays using hardware-in-the-loop simulations. This paper also evaluates the applicability of recently proposed transients/incremental quantities-based techniques to overcome the deficiencies of conventional methods to correctly identify the faulted phase in systems with IBRs through real-time and control hardware-in-the-loop simulations. Comparisons with commercial relays show that transient/incremental quantities-based methods are more suitable for systems with a high penetration of IBRs.
Identification of Karst Cavities from 2D Seismic Wave Impedance Images Based on Gradient-Boosting Decision Trees Algorithms (GBDT): Case of Ordovician Fracture-Vuggy Carbonate Reservoir, Tahe Oilfield, Tarim Basin, China
Authors: Kouassi Allou Koffi Franck , Pan Lin , Wang Xiao , Wang Zhangheng , Mulashani Alvin K. , James Faulo , Shaame Mbarouk , Hussain Altaf , Hussain Hadi , Nyakilla Edwin E.
Published: January 2023

The precise characterization of geological bodies in fracture-vuggy carbonates is challenging due to their high complexity and heterogeneous distribution. This study aims to present the hybrid of Visual Geometry Group 16 (VGG-16) pre-trained by Gradient-Boosting Decision Tree (GBDT) models as a novel approach for predicting and generating karst cavities with high accuracy on various scales based on uncertainty assessment from a small dataset. Seismic wave impedance images were used as input data. Their manual interpretation was used to build GBDT classifiers for Light Gradient-Boosting Machine (LightGBM) and Unbiased Boosting with Categorical Features (CatBoost) for predicting the karst cavities and unconformities. The results show that the LightGBM was the best GBDT classifier, which performed excellently in karst cavity interpretation, giving an F1-score between 0.87 and 0.94 and a micro-G-Mean ranging from 0.92 to 0.96. Furthermore, the LightGBM performed better in cave prediction than Linear Regression (LR) and Multilayer Perceptron (MLP). The prediction of karst cavities according to the LightGBM model was performed well according to the uncertainty quantification. Therefore, the hybrid VGG16 and GBDT algorithms can be implemented as an improved approach for efficiently identifying geological features within similar reservoirs worldwide.
Numerical Investigation on Mechanism of Swirling Flow of the Prefilming Air-Blast Fuel Injector
Authors: Cao Cheng , Gao Yaping , Wang Shaolin , Liu Fuqiang , Liu Cunxi , Mu Yong , Mei Deqing , Xu Gang
Published: January 2023

Prefilming air-blast atomizers are widely used in modern gas turbine combustors. Due to insufficient awareness of the coupling mechanism of multi-stage swirling flow in gas turbines, there is a lack of effective methods for flow field optimization in combustor. In this study, the effect of some critical parameters on the flow field of a prefilming air-blast atomizer was analyzed with CFD. The parameters include the angle and number of the first swirler blades, the angle of the second swirler blades and the angle of sleeve. Furthermore, the coupling mechanism of two-stage swirling airflows of prefilming air-blast atomizer was discussed. Moreover, the influence of the interaction between two-stage counter swirling airflows on the characteristics of flow field was explained. The results show that with the increase in SNi, the axial length of the primary recirculation zone decreased, while the radial width increased. The starting position of primary recirculation zone (PRZ) moves forward with the increase in SNo. Reducing the sleeve angle β helps to form the primary recirculation zone. The results indicate that it is the transition of tangential velocity of airflow to radial velocity that promotes the formation of the PRZ. These results provide theoretical support for optimization of the flow field in swirl combustor.
Analysis Behavior of Openings on Full-Size Cross-Laminated Timber (CLT) Frame Shear Walls Tested Monotonically
Authors: Dungani Rudi , Sulistyono  , Karliati Tati , Suhaya Yoyo , Malik Jamaludin , Alpian  , Supriyati Wahyu
Published: January 2023

Walls, as components of the lateral-force-resisting system of a building, are defined as shear walls. This study aims to determine the behavior of shear wall panel cross-laminated-timber-based mangium wood (Acacia mangium Willd) (CLT-mangium) in earthquake-resistant prefabricated houses. The earthquake performance of CLT mangium frame shear walls panels has been studied using monotonic tests. The shear walls were constructed using CLT-mangium measuring 2400 mm × 1200 mm × 68 mm with various design patterns (straight sheathing, diagonal sheathing/45°, windowed shear wall with diagonal pattern and a door shear wall with a diagonal pattern). Shear wall testing was carried out using a racking test, and seismic force calculations were obtained using static equivalent earthquake analysis. CLT-mangium sheathing installed horizontally (straight sheathing) is relatively weak compared to the diagonal sheathing, but it is easier and more flexible to manufacture. The diagonal sheathing type is stronger and stiffer because it has triangulation properties, such as truss properties, but is more complicated to manufacture (less flexible). The type A design is suitable for low-intensity zones (2), and types B, D, E1 and E2 are suitable for moderate-intensity zones (3, 4), and type C is suitable for severe-intensity zones (5).
Sex-Related Ecophysiological Responses of Hippophae rhamnoide Saplings to Simulate Sand Burial Treatment in Desertification Areas
Authors: Chen Juan , Lin Yuhu , Fang Ling , Li Jinfang , Han Suju , Li Yudong , Li Yan
Published: January 2023

(1) Background: In recent years, Hippophae rhamnoides has been used extensively to prevent desertification in China due to its nitrogen (N) fixation and sand stabilization abilities. However, as a dioecious species, few studies have focused on the sexual dimorphism of H. rhamnoides in response to sand burial, which frequently presents in desertification areas. (2) Methods: In this paper, we explored the ecophysiological responses of female and male saplings of H. rhamnoides under unburied treatment (control) and different sand burial depths (denoted as T33, T67, T90 and T133, corresponding to sand burial depths of 33, 67, 90 and 133 percent of the mean initial height of the saplings, respectively). (3) Results: Compared with unburied controls, the T33 treatment significantly promoted biomass accumulation and photosynthetic capacity, whereas T67 and T90 treatments inhibited biomass and physiological parameters of the two sexes. Deeper sand burial treatments, i.e., T90 and T133, significantly decreased the survival rates of the two sexes. Furthermore, the sex-specific responses of the two sexes of H. rhamnoides were affected by different depths of sand burial. Males had higher levels of stem starch and root sucrose and exhibited a larger increase in root nodule biomass under the T33 treatment, indicating better carbohydrate utilization and N fixation, whereas females showed lower total biomass and fewer root nodules, as well as more inhibition of photosynthetic and chlorophyll fluorescence parameters, water potential and root carbohydrates, indicating more negative effects on females than males under the T67 treatment. (4) Conclusions: We conclude that sex-related response and adaptation to sand burial depths may potentially affect the colonization, sex ratio and ecological function of the two sexes of H. rhamnoides in desertification areas.