bluuebunny/crossref_metadata_2025 huggingface dataset:
Food Habits and Lifestyle in Hyperphenylalaninemia Patients: Should These Be Monitored?
Authors: Dicintio Annamaria , Paterno Giulia , Carella Rosa , Ortolani Federica , Masciopinto Maristella , De Giovanni Donatella , Tummolo Albina
Published: August 2022

Studies on Hyperphenylalaninemia (HPA) patients are scarce and primarily focused on neurocognitive outcomes compared to PKU patients. In this study, we characterized the food habits and lifestyle of HPA patients compared with healthy peers. We performed a cross-sectional survey of a cohort of 30 patients (13 males, median age/range: 7.9; 2.2–16.7 years) and 28 controls (8 males, median age/range: 7.9; 2.1–16.7 years). Anthropometric parameters, food and nutrient intakes, and level of physical activity were assessed. Food neophobia, eating disorders, and body image perception was investigated by specific tests. Patients showed greater selectivity in the choice of foods than controls, preferring products with lower protein content (p-value: 0.03) and avoiding associating multiple protein and carbohydrate sources. A comparable tendency to distrust new foods emerged without elements suggestive of eating disorders. Patients had higher image dissatisfaction than peers (p-value: 0.01). This group of patients manifested more selective eating habits and worse body image acceptance. A regular evaluation of these aspects in these patients may result in a more effective follow-up of this disorder. More studies are needed to confirm these findings.
Deletion Syndrome 22q11.2: A Systematic Review
Authors: Cortés-Martín Jonathan , Peñuela Nuria López , Sánchez-García Juan Carlos , Montiel-Troya Maria , Díaz-Rodríguez Lourdes , Rodríguez-Blanque Raquel
Published: August 2022

22q11.2 deletion syndrome (DS 22q11.2) is a rare disease of genetic origin, caused by the loss of the q11.2 region of chromosome 22. It affects one in 4000 live newborns, and among the clinical manifestations that can occur in this syndrome are abnormalities in the parathyroid glands (producing calcium deficits), the palate, the heart and the thymus. It is also known as DiGeorge syndrome or velocardiofacial syndrome, among other names, depending on the clinical presentation of each individual. The main objective of the review was to update information on DS 22q11.2 from publications in the scientific literature. The daily activities of these patients are seriously impaired, due to the impact of the clinical manifestations. Interventions can be performed to improve their social, cognitive and emotional skills, thus increasing their ability to perform different daily activities.
Effect of Cucurbit[7]uril on Adsorption of Aniline Derivatives at Quartz
Authors: Wang Kui , Jiang Xiaoming , Hao Chunling , Tao Zhu
Published: August 2022

The adsorption behavior of small molecules at solid–liquid interfaces have become an important research topic in recent years. For example, small molecules of aniline pollutants will adsorb on solid surfaces with a massive discharge of industrial wastewater and are difficult to separate. Therefore, their adsorption and desorption on solid surfaces have become an important scientific problem. In this study, the interactions of cucurbit[7]uril (Q[7]) with 4,4′-diaminodiphenylmethane (MDA) and benzidine (AN) are studied using 1H NMR, UV-Vis spectrometry and fluorescence spectroscopy. The results show that Q[7] forms an inclusion complex with MDA and AN. According to the results of Quartz Crystal Microbalance with Dissipation (QCM-D), MDA adsorbs onto a quartz surface and forms a viscous adsorption layer on it. The AN adsorbs on the quartz surface and forms a rigid adsorption film on it. Q[7] can reduce the adsorption of MDA on the quartz surface and increases the adsorption of AN on it. Through the dynamic adsorption experiments, we find that Q[7] has a desorption effect on MDA molecules adsorbed on the quartz surface. An Atomic Force Microscope (AFM) is used to measure the morphological changes in the adsorption film before and after Q[7] makes contact with the quartz surface, and it proves that Q[7] has a desorption effect on MDA molecules adsorbed on the surface.
Microstructure and Fatigue of EA4T Steel in Laser Cladding Remanufacturing
Authors: Chen Wenjing , Chen Qunyan , Zhang Zhenlin , Tang Sicheng , Cai Qing
Published: August 2022

EA4T steel has been widely used in the manufacture of railway axles. Laser cladding remanufacturing technology has been used to repair railway axles, and the failure behaviors of railway axles has been studied. In this work, a class of original FeCrNiMo alloy layers that contain rare-earth elements was successfully fabricated through a laser cladding technique on EA4T steel substrates. The microstructure and elemental distribution of the cladding layers were analyzed through scanning electron microscopy (SEM), transmission electron microscopy (TEM) and electron probe microanalysis (EPMA). Simultaneously, the microhardness, bond strength and fatigue properties of different samples were determined. The results indicated that the phase composition of the cladding layer was mainly martensite. The grains in the cladding layer were gradually refined with an increase in the distance from the interface, and the chemical composition distribution was more uniform. At the same time, the bonding property of the cladding layer and matrix was good, and the fatigue strength of the sample was improved.
Assessing the Spatiotemporal Relationship between Coastal Habitats and Fish Assemblages at Two Neotropical Estuaries of the Mexican Pacific
Authors: Muro-Torres Victor , Amezcua Felipe , Ramírez-Ortiz Georgina , Flores-de-Santiago Francisco , Amezcua-Linares Felipe , Hernández Yareli
Published: August 2022

Differences in fish assemblages’ structures and their relations with environmental variables (due to the variations in sampled seasons, habitats, and zones) were analyzed in two adjacent estuaries on the north Pacific coast of Mexico. Environmental variables and fish catches were registered monthly between August 2018 and October 2020. Multivariate analyses were conducted to define habitats and zones based on their environmental characteristics, and the effect of this variability on fish assemblages’ composition, biomass, and diversity (α and β) was evaluated. A total of 12,008 fish individuals of 143 species were collected using different fishing nets. Multivariate analyses indicated that fish assemblages’ structures were different between zones due to the presence, height, and coverage of distinct mangrove species. Additionally, depth and salinity showed effects on fish assemblages’ diversity (α and β-nestedness), which presented higher values in the ocean and remained similar in the rest of the analyzed zones and habitats. These results and the differences in species replacement (β-turnover) indicate the singularity of fish assemblages at estuaries (even in areas close to the ocean) and the necessity to establish local management strategies for these ecosystems.
Magnetic Resonance Imaging and Spectroscopy Analysis in a Pelizaeus–Merzbacher Disease Rat Model
Authors: Ishikawa Maho , Sawaya Reika , Hirayama Miki , Ueda Junpei , Saito Shigeyoshi
Published: August 2022

Pelizaeus–Merzbacher disease (PMD) is an X-linked recessive disorder of the central nervous system. We performed 7 Tesla magnetic resonance imaging of the brain in Tama rats, a rodent PMD model, and control rats, as well as evaluated the diagnostic values. In the white matter of the Tama rats, the T2 values were prolonged, which is similar to that observed in patients with PMD (60.7 ± 1.8 ms vs. 51.6 ± 1.3 ms, p < 0.0001). The apparent diffusion coefficient values in the white matter of the Tama rats were higher than those of the control rats (0.68 ± 0.03 × 10−3 mm2/s vs. 0.64 ± 0.03 × 10−3 mm2/s, p < 0.05). In proton magnetic resonance spectroscopy, the N-acetylaspartate (6.97 ± 0.12 mM vs. 5.98 ± 0.25 mM, p < 0.01) and N-acetylaspartate + N-acetylaspartylglutamate values of the Tama rats were higher (8.22 ± 0.17 mM vs. 7.14 ± 0.35 mM, p < 0.01) than those of the control rats. The glycerophosphocholine + phosphocholine values of the Tama rats were lower than those of the control rats (1.04 ± 0.09 mM vs. 1.45 ± 0.04 mM, p < 0.001). By using Luxol fast blue staining, we confirmed dysmyelination in the Tama rats. These results are similar to those of patients with PMD and other PMD animal models.
Special Issue “Artificial Intelligence in Oral Health”
Authors: Lee Jae-Hong
Published: August 2022

I thank all authors, reviewers and the editorial staff who contributed to this Special Issue [...]
Correction: Wang et al. Automated 3D Segmentation of the Aorta and Pulmonary Artery on Non-Contrast-Enhanced Chest Computed Tomography Images in Lung Cancer Patients. Diagnostics 2022, 12, 967
Authors: Wang Hao-Jen , Chen Li-Wei , Lee Hsin-Ying , Chung Yu-Jung , Lin Yan-Ting , Lee Yi-Chieh , Chen Yi-Chang , Chen Chung-Ming , Lin Mong-Wei
Published: August 2022

Errors occurred in the standard deviation of the Dice similarity coefficient (DSC) described in the original publication [...]
Is It Possible to Replace Conventional Radiography (CR) with a Dose Neutral Computed Tomography (CT) of the Cervical Spine in Emergency Radiology—An Experimental Cadaver Study
Authors: Deak Zsuzsanna , Brummund Lindis , Kirchhoff Sonja , Körner Markus , Geyer Lucas , Mück Fabian , Scaglione Mariano , Reiser Maximilian , Linsenmaier Ulrich
Published: August 2022

The purpose of this experimental study on recently deceased human cadavers was to investigate whether (I) the radiation exposure of the cervical spine CT can be reduced comparable to a dose level of conventional radiography (CR); and (II) whether and which human body parameters can be predictive for higher dose reduction potential (in this context). Materials and Methods: Seventy serial CT scans of the cervical spine of 10 human cadavers undergoing postmortem virtual autopsy were taken using stepwise decreasing upper limits of the tube current (300 mAs, 150 mAs, 110 mAs, 80 mAs, 60 mAs, 40 mAs, and 20 mAs) at 120 kVp. An additional scan acquired at a fixed tube current of 300 mAs served as a reference. Images were reconstructed with filtered back projection and the upper (C1-4) and lower (C4-7) cervical spine were evaluated by three blinded readers for image quality, regarding diagnostic value and resolution of anatomical structures according to a semiquantitative three-point-scale. Dose values and individual physical parameters were recorded. The relationship of diagnostic IQ, dose reduction level, and patients’ physical parameters were investigated. The high-contrast resolution of the applied CT protocols was tested in an additional phantom study. Results: The IQ of the upper cervical spine was diagnostic at 1.69 ± 0.58 mGy (CTDI) corresponding to 0.20 ± 0.07 mSv (effective dose) in all cadavers. IQ of the lower cervical spine was diagnostic at 4.77 ± 1.86 mGy corresponding to 0.560 ± 0.21 mSv (effective dose) in seven cadavers and at 2.60 ± 0.93 mGy corresponding to 0.31 ± 0.11 mSv in four cadavers. Significant correlation was detected for BMI (0.8366; p = 0.002548) and the anteroposterior (a.p.) chest diameter (0.8363; p = 0.002566), shoulder positioning (0.79799; p = 0.00995), and radiation exposure. Conclusions: Conventional radiography can be replaced with a nearly dose-neutral CT scan of the cervical spine.
Diagnostic Value of Fully Automated Artificial Intelligence Powered Coronary Artery Calcium Scoring from 18F-FDG PET/CT
Authors: Morf Claudia , Sartoretti Thomas , Gennari Antonio G. , Maurer Alexander , Skawran Stephan , Giannopoulos Andreas A. , Sartoretti Elisabeth , Schwyzer Moritz , Curioni-Fontecedro Alessandra , Gebhard Catherine , Buechel Ronny R. , Kaufmann Philipp A. , Huellner Martin W. , Messerli Michael
Published: August 2022

Objectives: The objective of this study was to assess the feasibility and accuracy of a fully automated artificial intelligence (AI) powered coronary artery calcium scoring (CACS) method on ungated CT in oncologic patients undergoing 18F-FDG PET/CT. Methods: A total of 100 oncologic patients examined between 2007 and 2015 were retrospectively included. All patients underwent 18F-FDG PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months. CACS was manually performed on non-contrast ECG-gated CT scans obtained from SPECT-MPI (i.e., reference standard). Additionally, CACS was performed using a cloud-based, user-independent tool (AI-CACS) on ungated CT scans from 18F-FDG-PET/CT examinations. Agatston scores from the manual CACS and AI-CACS were compared. Results: On a per-patient basis, the AI-CACS tool achieved a sensitivity and specificity of 85% and 90% for the detection of CAC. Interscore agreement of CACS between manual CACS and AI-CACS was 0.88 (95% CI: 0.827, 0.918). Interclass agreement of risk categories was 0.8 in weighted Kappa analysis, with a reclassification rate of 44% and an underestimation of one risk category by AI-CACS in 39% of cases. On a per-vessel basis, interscore agreement of CAC scores ranged from 0.716 for the circumflex artery to 0.863 for the left anterior descending artery. Conclusions: Fully automated AI-CACS as performed on non-contrast free-breathing, ungated CT scans from 18F-FDG-PET/CT examinations is feasible and provides an acceptable to good estimation of CAC burden. CAC load on ungated CT is, however, generally underestimated by AI-CACS, which should be taken into account when interpreting imaging findings.
Automated Identification of Multiple Findings on Brain MRI for Improving Scan Acquisition and Interpretation Workflows: A Systematic Review
Authors: Sheng Kaining , Offersen Cecilie Mørck , Middleton Jon , Carlsen Jonathan Frederik , Truelsen Thomas Clement , Pai Akshay , Johansen Jacob , Nielsen Michael Bachmann
Published: August 2022

We conducted a systematic review of the current status of machine learning (ML) algorithms’ ability to identify multiple brain diseases, and we evaluated their applicability for improving existing scan acquisition and interpretation workflows. PubMed Medline, Ovid Embase, Scopus, Web of Science, and IEEE Xplore literature databases were searched for relevant studies published between January 2017 and February 2022. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. The applicability of ML algorithms for successful workflow improvement was qualitatively assessed based on the satisfaction of three clinical requirements. A total of 19 studies were included for qualitative synthesis. The included studies performed classification tasks (n = 12) and segmentation tasks (n = 7). For classification algorithms, the area under the receiver operating characteristic curve (AUC) ranged from 0.765 to 0.997, while accuracy, sensitivity, and specificity ranged from 80% to 100%, 72% to 100%, and 65% to 100%, respectively. For segmentation algorithms, the Dice coefficient ranged from 0.300 to 0.912. No studies satisfied all clinical requirements for successful workflow improvements due to key limitations pertaining to the study’s design, study data, reference standards, and performance reporting. Standardized reporting guidelines tailored for ML in radiology, prospective study designs, and multi-site testing could help alleviate this.
Automatic Acne Object Detection and Acne Severity Grading Using Smartphone Images and Artificial Intelligence
Authors: Huynh Quan Thanh , Nguyen Phuc Hoang , Le Hieu Xuan , Ngo Lua Thi , Trinh Nhu-Thuy , Tran Mai Thi-Thanh , Nguyen Hoan Tam , Vu Nga Thi , Nguyen Anh Tam , Suda Kazuma , Tsuji Kazuhiro , Ishii Tsuyoshi , Ngo Trung Xuan , Ngo Hoan Thanh
Published: August 2022

Skin image analysis using artificial intelligence (AI) has recently attracted significant research interest, particularly for analyzing skin images captured by mobile devices. Acne is one of the most common skin conditions with profound effects in severe cases. In this study, we developed an AI system called AcneDet for automatic acne object detection and acne severity grading using facial images captured by smartphones. AcneDet includes two models for two tasks: (1) a Faster R-CNN-based deep learning model for the detection of acne lesion objects of four types, including blackheads/whiteheads, papules/pustules, nodules/cysts, and acne scars; and (2) a LightGBM machine learning model for grading acne severity using the Investigator’s Global Assessment (IGA) scale. The output of the Faster R-CNN model, i.e., the counts of each acne type, were used as input for the LightGBM model for acne severity grading. A dataset consisting of 1572 labeled facial images captured by both iOS and Android smartphones was used for training. The results show that the Faster R-CNN model achieves a mAP of 0.54 for acne object detection. The mean accuracy of acne severity grading by the LightGBM model is 0.85. With this study, we hope to contribute to the development of artificial intelligent systems to help acne patients better understand their conditions and support doctors in acne diagnosis.
Ultrasound Imaging of the Superficial Fascia in the Upper Limb: Arm and Forearm
Authors: Pirri Carmelo , Pirri Nina , Guidolin Diego , Macchi Veronica , De Caro Raffaele , Stecco Carla
Published: August 2022

The superficial fascia has received much attention in recent years due to its important role of compartmentalizing the subcutaneous tissue. Ultrasound (US) imaging, owing to its high definition, provides the possibility of better visualizing and measuring its thickness. The aim of this study was to measure and compare, with US imaging, the thickness of superficial fascia in the arm and forearm in different regions/levels. An observational study has been performed using US imaging to measure superficial fascia thickness in the anterior and posterior regions at different levels in a sample of 30 healthy volunteers. The results for superficial fascia thickness revealed statistically significant differences (p < 0.0001) in the arm between the anterior and posterior regions; in terms of forearm, some statistically significant differences were found between regions/levels. However, in the posterior region/levels of the arm, the superficial fascia was thicker (0.53 ± 0.10 mm) than in the forearm (0.41 ± 0.10 mm); regarding the anterior regions/levels, the superficial fascia of the arm (0.40 ± 0.10 mm) was not statistically different than the forearm (0.40 ± 0.12 mm). In addition, the intra-rater reliability was good (ICC2,k: 0.88). US helps to visualize and assess the superficial fascia inside the subcutaneous tissue, improving the diagnosis of fascial dysfunction, and one of the Us parameters to reliably assess is the thickness in different regions and levels.
Pre-Service Teachers’ Project-Based Instruction with Mathematics Problem-Solving
Authors: Park Jooyoung
Published: August 2022

Project-Based Instruction (PBI) is prevalent in science classrooms, which focuses on real-world tasks as a vehicle for student learning. PBI can be a fitting instructional approach to enhance student mathematics problem-solving. This case study explored two pre-service secondary mathematics teachers’ PBI with mathematics problem-solving based on their intended and enacted lessons. Data sources were the pre-service teacher (PST)’s lesson plans and video-recorded classroom observations. Results from data analysis report that PSTs employed a wide range of heuristics in their lesson units and spent more time for facilitating student group work than other activities during the instructional time. The findings suggested that project-based design principles may encourage teachers to use problem-solving heuristics, especially for restating problems, using a model or diagram, and making suppositions. Furthermore, scaffolding with problem-solving heuristics can be enacted so that teachers keep students engaging and persevering in problem-solving toward reaching goals.
A Computational Tool for Detection of Soft Tissue Landmarks and Cephalometric Analysis
Authors: Azad Mohammad , Elaiwat Said , Alam Mohammad Khursheed
Published: August 2022

In facial aesthetics, soft tissue landmark recognition and linear and angular measurement play a critical role in treatment planning. Visual identification and judgment by hand are time-consuming and prone to errors. As a result, user-friendly software solutions are required to assist healthcare practitioners in improving treatment planning. Our first goal in this paper is to create a computational tool that may be used to identify and save critical landmarks from patient X-ray pictures. The second goal is to create automated software that can assess the soft tissue facial profiles of patients in both linear and angular directions using the landmarks that have been identified. To boost the contrast, we employ gamma correction and a client-server web-based model to display the input images. Furthermore, we use the client-side to record landmarks in pictures and save the annotated landmarks to the database. The linear and angular measurements from the recorded landmarks are then calculated computationally and displayed to the user. Annotation and validation of 13 soft tissue landmarks were completed. The results reveal that our software accurately locates landmarks with a maximum deviation of 1.5 mm to 5 mm for the majority of landmarks. Furthermore, the linear and angular measurement variances across users are not large, indicating that the procedure is reliable.
A Novel, Blind, Wideband Spectrum Detection under Non-Flat Spectrum and Fading Scenarios
Authors: Shang Peng , Zou Decai , Wang Xue , Chu Ziyue
Published: August 2022

In the field of radio surveillance and cognitive radio, the reception of a signal is usually made in a non-cooperative manner, which means there exists little prior information to detect the signals reliably via a traditional method. At the same time, the prevalent wideband acquisition mode will receive multiple subband signals from homogeneous or heterogeneous systems, leading to deteriorated detection performance under a non-flat spectrum and fading channel. In view of the above concerns, a novel detection algorithm based on the Gaussian hidden Markov model (HMM) is proposed so as to separate the individual sub-band signal from the wideband spectrum accurately in a low signal-to-noise ratio (SNR). The simulated communication signals with spectral fluctuation and multipath fading indicate the superiority and applicability of the proposed algorithm as compared with other detection algorithms. Our algorithm can achieve a 94% detection probability at −10 dB SNR under an additive white Gaussian noise (AWGN) channel and has a nearly ideal receiver operating characteristic (ROC) curve. When faced with a Rayleigh fading channel, it still outperforms other algorithms. The acquired real data also very its practical application with moderate computation complexity and a more stable carrier-frequency estimation.
Evaluating Intelligent Methods for Detecting COVID-19 Fake News on Social Media Platforms
Authors: Alhakami Hosam , Alhakami Wajdi , Baz Abdullah , Faizan Mohd , Khan Mohd Waris , Agrawal Alka
Published: August 2022

The advent of Internet-based technology has made daily life much easy than earlier days. The exponential rise in the popularity of social media platforms has not only connected people from faraway places, but has also increased communication among humans. However, in several instances, social media platforms have also been utilized for unethical and criminal activities. The propagation of fake news on social media during the ongoing COVID-19 pandemic has deteriorated the mental and physical health of people. Therefore, to control the flow of fake news regarding the novel coronavirus, several studies have been undertaken to automatically detect the fake news about COVID-19 using various intelligent techniques. However, different studies have shown different results on the performance of the predicting models. In this paper, we have evaluated several machine learning and deep learning models for the automatic detection of fake news regarding COVID-19. The experiments were carried out on two publicly available datasets, and the results were assessed using several evaluation metrics. The traditional machine learning models produced better results than the deep learning models in predicting fake news.
Chinese Spam Detection Using a Hybrid BiGRU-CNN Network with Joint Textual and Phonetic Embedding
Authors: Yao Jinliang , Wang Chenrui , Hu Chuang , Huang Xiaoxi
Published: August 2022

The proliferation of spam in China has a negative impact on internet users’ experiences online. Existing methods for detecting spam are primarily based on machine learning. However, it has been discovered that these methods are susceptible to adversarial textual spam that has frequently been imperceptibly modified by spammers. Spammers continually modify their strategies to circumvent spam detection systems. Text with Chinese homophonic substitution may be easily understood by users according to its context. Currently, spammers widely use homophonic substitution to break down spam identification systems on the internet. To address these issues, we propose a Bidirectional Gated Recurrent Unit (BiGRU)–Text Convolutional Neural Network (TextCNN) hybrid model with joint embedding for detecting Chinese spam. Our model effectively uses phonetic information and combines the advantages of parameter sharing from TextCNN with long-term memory from BiGRU. The experimental results on real-world datasets show that our model resists homophone noise to some extent and outperforms mainstream deep learning models. We also demonstrate the generality of joint textual and phonetic embedding, which is applicable to other deep learning networks in Chinese spam detection tasks.
Understanding and Controlling Band Alignment at the Metal/Germanium Interface for Future Electric Devices
Authors: Nishimura Tomonori
Published: August 2022

Germanium (Ge) is a promising semiconductor as an alternative channel material to enhance performance in scaled silicon (Si) field-effect transistor (FET) devices. The gate stack of Ge FETs has been much improved based on extensive research thus far, demonstrating that the performance of Ge FETs is much superior to that of Si FETs in terms of the on-state current. However, to suppress the performance degradation due to parasitic contact resistance at the metal/Ge interface in advanced nodes, the reduction of the Schottky barrier height (SBH) at the metal/Ge interface is indispensable, yet the SBH at the common metal/Ge interface is difficult to control by the work function of metal due to strong Fermi level pinning (FLP) close to the valence band edge of Ge. However, the strong FLP could be alleviated by an ultrathin interface layer or a low free-electron-density metal, which makes it possible to lower the SBH for the conduction band edge of Ge to less than 0.3 eV. The FLP alleviation is reasonably understandable by weakening the intrinsic metal-induced gap states at the metal/Ge interface and might be a key solution for designing scaled Ge n-FETs.
A Flexible Semantic Ontological Model Framework and Its Application to Robotic Navigation in Large Dynamic Environments
Authors: Joo Sunghyeon , Bae Sanghyeon , Choi Junhyeon , Park Hyunjin , Lee Sangwook , You Sujeong , Uhm Taeyoung , Moon Jiyoun , Kuc Taeyong
Published: August 2022

Advanced research in robotics has allowed robots to navigate diverse environments autonomously. However, conducting complex tasks while handling unpredictable circumstances is still challenging for robots. The robots should plan the task by understanding the working environments beyond metric information and need countermeasures against various situations. In this paper, we propose a semantic navigation framework based on a Triplet Ontological Semantic Model (TOSM) to manage various conditions affecting the execution of tasks. The framework allows robots with different kinematics to perform tasks in indoor and outdoor environments. We define the TOSM-based semantic knowledge and generate a semantic map for the domains. The robots execute tasks according to their characteristics by converting inferred knowledge to Planning Domain Definition Language (PDDL). Additionally, to make the framework sustainable, we determine a policy of maintaining the map and re-planning when in unexpected situations. The various experiments on four different kinds of robots and four scenarios validate the scalability and reliability of the proposed framework.
A Novel MPPT Algorithm for Photovoltaic Systems Based on Improved Sliding Mode Control
Authors: Zhang Yan , Wang Ya-Jun , Yu Jia-Qi
Published: August 2022

Due to the poor tracking performance and significant chattering of traditional sliding mode control in the maximum power point tracking (MPPT) algorithm, a novel MPPT algorithm based on sliding mode control for photovoltaic systems is proposed in this paper. The sliding mode control structure and new sliding mode surface of the multi-power reaching law are designed with the boost converter as the carrier of the photovoltaic system, and the sigmoid function is proposed to replace the symbolic function and saturation function in the power reaching law to improve the reaching rate and control quality of the traditional sliding mode control. Furthermore, the Liapunov function is employed to analyze the accessibility, existence and stability of the improved sliding mode control. Simulation results under dynamic and partial shading conditions show that compared with exponential sliding mode and constant speed sliding mode, the improved sliding mode control strategy can quickly track the maximum power point of photovoltaic systems under various atmospheric conditions. The proposed MPPT algorithm has stronger robustness and universality. Additionally, the efficiency of the proposed algorithm is improved by 2.3% and 5.6% as compared to the exponential sliding model control algorithm and constant velocity sliding model control algorithm. In addition, the experimental platform is constructed to further validate the feasibility and effectiveness of the proposed algorithm.
Improving Fuel Properties and Hydrocarbon Content from Residual Fat Pyrolysis Vapors over Activated Red Mud Pellets in Two-Stage Reactor: Optimization of Reaction Time and Catalyst Content
Authors: Ferreira Caio , Bernar Lucas , de Freitas Costa Augusto , da Silva Ribeiro Haroldo , Santos Marcelo , Moraes Nathalia , Costa Yasmin , Baia Ana , Mendonça Neyson , da Mota Sílvio , da Costa Assunção Fernanda , de Castro Douglas , Quaresma Carlos , Duvoisin Sergio , Borges Luiz , Machado Nélio
Published: August 2022

Catalytic upgrading of vapors from pyrolysis of triglycerides materials is a promising approach to achieve better conversions of hydrocarbons and production of liquid biofuels. Catalytic cracking often shows incomplete conversion due to distillation of initial reaction products and the addition of a second catalytic reactor, whereas pyrolytic vapors are made in contact to a solid catalyst was applied to improve the physical-chemical properties and quality of bio-oil. This work investigated the effect of catalyst content and reaction time by catalytic upgrading from pyrolysis vapors of residual fat at 450 °C and 1.0 atmosphere, on the yields of reaction products, physicochemical properties (density, kinematic viscosity, refractive index, and acid value), and chemical composition of organic liquid products (OLP), over a catalyst fixed bed reactor, in semi pilot scale. Pellets of red mud chemically activated with 1.0 M HCl were used as catalysts. The thermal catalytic cracking of residual fat show OLP yields from 54.4 to 84.88 (wt.%), aqueous phase yields between 2.21 and 2.80 (wt.%), solid phase yields (coke) between 1.30 and 8.60 (wt.%), and gas yields from 11.61 to 34.22 (wt.%). The yields of OLP increases with catalyst content while those of aqueous, gaseous and solid phase decreases. For all experiments, the density, kinematic viscosity, and acid value of OLP decreases with reaction time. The GC-MS of liquid reaction products identified the presence of hydrocarbons and oxygenates. In addition, the hydrocarbon content in OLP increases with reaction time, while those of oxygenates decrease, reaching concentrations of hydrocarbons up to 95.35% (area.). The best results for the physicochemical properties and the maximum hydrocarbon content in OLP were obtained at 450 °C and 1.0 atmosphere, using a catalyst fixed bed reactor, with 5.0% (wt.) red mud pellets activated with 1.0 M HCl as catalyst.
Design and Research on DC Electric Leakage Protection Circuit Breaker
Authors: Hou Lei , Chen Dezhi , Li Tongfei , Zhao Ming , Ren Huaibo
Published: August 2022

In recent years, DC power supply and distribution technology plays an increasingly significant role in power supply and distribution systems with a low loss and large power supply radius. However, the corresponding DC distribution network protection electric devices cannot satisfy the needs of the existing DC power supply and distribution network. Based on this, in this article, an intelligent/energy-efficient DC leakage protection circuit breaker based on two-phase magnetic nanomaterials and detection and control technology is proposed. Firstly, the core of an intelligent/energy-efficient DCCB is composed of two-phase magnetic nanomaterials, and the mathematical modeling process, preparation and processing method of two-phase magnetic nanomaterials are given. Secondly, the DC leakage detection technology is studied by fluxgate technology, and the design process of magnetic rings, winding and detection circuit is given. Thirdly, the simulation and experiment results of the detection system and actuator are given by the simulation and experiment of an intelligent/energy-efficient DCCB to verify the correctness of the proposed scheme.
Effect of Spar Design Optimization on the Mass and Cost of a Large-Scale Composite Wind Turbine Blade
Authors: Hayat Khazar , Siddique Shafaqat , Sultan Tipu , Ali Hafiz T. , Aloufi Fahed A. , Halawani Riyadh F.
Published: August 2022

Mass and cost tradeoffs by deploying three optimized spars, made of all-glass, hybrid and all-carbon composites, applied to a publicly available large-scale composite blade of 100 m in length for a 13.2 MW wind turbine, are explored. The blade mass and cost minimizations are calculated for two design load cases, generating the worst aerodynamic loads for parked and rotating rotor blades, while meeting the stiffness, strength, stability and resonance design requirements, as recommended by the wind turbine standards. The optimization cases are formulated as a single-objective, multi-constraint optimization problem, while taking into account the manufacturability of hybrid spars in particular, and it is solved using a genetic algorithm method. The blade mass lowers in the range of 8.1–13.3%, 18.5–20.7% and 25.7–26.4% for the optimized all-glass, hybrid and all-carbon spars, respectively, while the cost decreases for the optimized all-glass spars only. The cost increases in a range of 1.2–13.6% and 24.5–31.5% when the optimized hybrid and all-carbon spars are used. Further, the hybrid spar optimization using the blade mass and cost objective functions, as well as the effects of spar optimization on the blade’s structural performance in terms of tip deflection, strength, buckling resistance and first natural frequency, are discussed.
Quantitative Seismic Interpretation of Reservoir Parameters and Elastic Anisotropy Based on Rock Physics Model and Neural Network Framework in the Shale Oil Reservoir of the Qianjiang Formation, Jianghan Basin, China
Authors: Guo Zhiqi , Zhang Tao , Liu Cai , Liu Xiwu , Liu Yuwei
Published: August 2022

Quantitative estimates of reservoir parameters and elastic anisotropy using seismic methods is essential for characterizing shale oil reservoirs. Rock physics models were established to quantify elastic anisotropy associated with clay properties, laminated microstructures, and bedding fractures at different scales in shale. The inversion schemes based on the built rock physics models were proposed to estimate reservoir parameters and elastic anisotropy using well log data. Based on the back propagation neural network framework, the obtained rock physical inversion results were used to establish the nonlinear models between elastic properties and reservoir parameters and elastic anisotropy of shale. The established correlations were applied for quantitative seismic interpretation, converting seismic inversion results to the reservoir parameters and elastic anisotropy to characterize the shale oil reservoir comprehensively. The predicted elastic anisotropy of the shale matrix reflects the lamination degree and the mechanical properties of the shale, which is critical for the effective implementation of hydraulic fracturing. The calculated elastic anisotropy of the shale provides more accurate models for seismic modeling and inversion. The obtained bedding fracture parameters provide insights into reservoir permeability. Therefore, the proposed method provides valuable information for identifying favorable oil zones in the study area.
Multi-Port Multi-Directional Converter with Multi-Mode Operation and Leakage Energy Recycling for Green Energy Processing
Authors: Shen Chih-Lung , Chen Li-Zhong , Chen Guan-Yu , Yang Ching-Ming
Published: August 2022

In this article, a novel multi-port multi-directional converter (MPMDC) is proposed. Even though the power stage of the MPMDC belongs to a single-stage structure, it can control power flow direction handily among ports and achieve converter operation in up to five modes. The MPMDC has the feature of galvanic isolation and can obtain a high voltage conversion ratio even under the adoption of only one inductor and one transformer. The leakage energy of the transform can be recycled to improve overall efficiency. Once the MPMDC is applied to deal with renewable energy, battery, and bus energy, the advantage of multi-directional control of power flow can advance an energy storage system to perfectly function power conditioning feature. In addition to the discussion of converter operation, voltage gain, voltage stress, current stress, and inductance design are analyzed theoretically. Comparisons with some of the latest similar converters are also carried out. A 200-W prototype is built and measured. According to the practical results, it is verified that the hardware measurements meet the theoretical derivations and the MPMDC is validated. The maximum efficiency of the converter is up to 94%.
Air-Side Nusselt Numbers and Friction Factor’s Individual Correlations of Finned Heat Exchangers
Authors: Marcinkowski Mateusz , Taler Dawid , Taler Jan , Węglarz Katarzyna
Published: August 2022

Currently, when designing finned heat exchangers (FHE), the average value of the entire heat transfer coefficient (HTC) is considered. However, each row of the heat exchanger (HEX) has different hydraulic-thermal characteristics. The novelty of this research is to present the differentiation of the individual air-side Nusselt number and Darcy-Weisbach friction factor correlations in each row of FHE using CFD modelling. FHE has four-rows, circular tubes, and continuous fins with a staggered tube arrangement. Relationships for the Nusselt number and D-W friction factor derived for the entire exchanger based on CFD modelling were compared with those available in the literature, determined using experimental data. The maximum relative differences between the Nusselt number for a four-row FHE determined experimentally and by CFD modelling are in the range from 22% for a Reynolds number based on a tube outside diameter of 1000 to 30% for a Reynolds number of 13,000. The maximum relative differences between the D-W friction factor for a four-row FHE determined experimentally and by CFD modelling are in the range of 50% for a Reynolds number based on a tube outer diameter of 1000 to 10% for a Reynolds number of 13,000. The CFD modelling performed shows that in the range of Reynolds numbers based on hydraulic diameters from 150 to 1400, the Nusselt number for the first row in a four-row FHE is about 22% to 15% higher than the average Nusselt number for the entire exchanger. In the range of Reynolds number changes based on hydraulic diameter from 2800 to 6000, the Nusselt numbers on the first and second rows of tubes are close to each other. Correlations of Nusselt numbers and D-W friction factors derived for individual tube rows can be used in the design of plate-fin and tube heat exchangers used in equipment such as air-source heat pumps, automotive radiators, air-conditioning systems, and in air hot-liquid coolers. In particular, the correlations can be used to select the optimum number of tube rows in the exchanger.
Experimental Study on the Distribution Characteristics of CO2 in Methane Hydrate-Bearing Sediment during CH4/CO2 Replacement
Authors: Sun Jianye , Hao Xiluo , Li Chengfeng , Wu Nengyou , Chen Qiang , Liu Changling , Li Yanlong , Meng Qingguo , Huang Li , Bu Qingtao
Published: August 2022

CH4/CO2 replacement is of great significance for the exploitation of natural gas hydrate resources and CO2 storage. The feasibility of this method relies on our understanding of the CH4/CO2 replacement efficiency and mechanism. In this study, CH4/CO2 replacement experiments were carried out to study the distribution characteristics of CH4 and CO2 in hydrate-bearing sediments during and after replacement. Similar to previously reported data, our experiments also implied that the CH4/CO2 replacement process could be divided into two stages: fast reaction and slow reaction, representing CH4/CO2 replacement in the hydrate-gas interface and bidirectional CH4/CO2 diffusion caused replacement, respectively. After replacement, the CO2 content gradually decreased, and the methane content gradually increased with the increase of sediment depth. Higher replacement percentage can be achieved with higher replacement temperature and lower initial saturation of methane hydrate. Based on the calculation of CO2 consumption amounts, it was found that the replacement mainly took place in the fast reaction stage while the formation of CO2 hydrate by gaseous CO2 and water almost runs through the whole experimental process. Thus, the pore scale CH4/CO2 replacement process in sediments can be summarized in the following steps: CO2 injection, CO2 diffusing into sedimentary layer, occurrence of CH4/CO2 replacement and CO2 hydrate formation, wrapping of methane hydrate by mixed CH4-CO2 hydrate, continuous CO2 hydrate formation, and almost stagnant CH4/CO2 replacement.
Impact of Courtyard Concept on Energy Efficiency and Home Privacy in Saudi Arabia
Authors: Abuhussain Mohammed Awad , Al-Tamimi Nedhal , Alotaibi Badr S. , Singh Manoj Kumar , Kumar Sanjay , Elnaklah Rana
Published: August 2022

The aim of this research is to develop an architectural style commensurate with the requirements of residential buildings in the hot and dry climate of Najran. The courtyard concept is one of the most important passive design strategies most in tune with the desert climate. The courtyard concept also meets the sociocultural requirements of the region. The success of this strategy can be verified by selecting a typical residential unit (villa) and assessing its indoor environmental conditions and energy performance. The villa can then be redesigned with the same functional and spatial determinants while creating a courtyard at the heart of the new villa configuration. To determine the level of improvement resulting from the proposed solution, the energy consumption per square meter is measured, and the results are compared with the DesignBuilder simulation program. The results indicate that with the proposed design focused mainly on the courtyard and some passive design strategies, the total energy consumption is reduced by 32.80% compared to the base case. The research concludes with a set of recommendations related to opportunities to improve the quality of the indoor environment and reduce cooling energy demand, in addition to achieving privacy for occupants and meeting the sociocultural requirements in the context of preserving Islamic values.
Enabling Co-Innovation for a Successful Digital Transformation in Wind Energy Using a New Digital Ecosystem and a Fault Detection Case Study
Authors: Barber Sarah , Lima Luiz Andre Moyses , Sakagami Yoshiaki , Quick Julian , Latiffianti Effi , Liu Yichao , Ferrari Riccardo , Letzgus Simon , Zhang Xujie , Hammer Florian
Published: August 2022

In the next decade, further digitalisation of the entire wind energy project lifecycle is expected to be a major driver for reducing project costs and risks. In this paper, a literature review on the challenges related to implementation of digitalisation in the wind energy industry is first carried out, showing that there is a strong need for new solutions that enable co-innovation within and between organisations. Therefore, a new collaboration method based on a digital ecosystem is developed and demonstrated. The method is centred around specific “challenges”, which are defined by “challenge providers” within a topical “space” and made available to participants via a digital platform. The data required in order to solve a particular “challenge” are provided by the “challenge providers” under the confidentiality conditions they specify. The method is demonstrated via a case study, the EDP Wind Turbine Fault Detection Challenge. Six submitted solutions using diverse approaches are evaluated. Two of the solutions perform significantly better than EDP’s existing solution in terms of Total Prediction Costs (saving up to €120,000). The digital ecosystem is found to be a promising solution for enabling co-innovation in wind energy in general, providing a number of tangible benefits for both challenge and solution providers.
Emissions Released by Forest Fuel in the Daxing’an Mountains, China
Authors: Zhang Heng , Li Hui , Liu Xinyuan , Ma Yunjia , Zhou Qing , Sa Rula , Zhang Qiuliang
Published: August 2022

The large amounts of emissions released by forest fires have a significant impact on the atmospheric environment, ecosystems, and human health. Revealing the main components of emissions released by forest fuel under different combustion states is of great importance to evaluate the impact of forest fires on the ecological environment. Here, a self-designed biomass combustion system was used to simulate the combustion of different parts (i.e., branch, trunk, and bark) of five tree species and branches, and three layers of surface dead fuel (i.e., litter layer, semi-humus layer, and humus layer) of three shrub species, in the Daxing’an Mountains, Inner Mongolia. The emission characteristics of the main gas pollutants (i.e., CO, CO2, HC, and NOx) and PM2.5 released under the two combustion states of smoldering and flaming, along with the correlation ratio among emission factors, were measured. The results show that the average amounts of emissions released by different trees and the three layers of surface dead fuel from a smoldering state are higher than those from the flaming state, while shrub combustion shows the opposite. The emissions released by trees, shrubs, and surface dead fuel from the flaming state are ordered from high to low as follows: CO2 > CO > HC > NOx > PM2.5; and from the smoldering state as CO2 > CO > HC > PM2.5 > NOx, indicating that the primary emissions under both conditions are mainly due to CO2, CO, and HC, while the emissions of NOx and PM2.5 are dependent on the combustion state—flaming promotes the emission of NOx, while smoldering promotes the emission of PM2.5. The average emissions of PM2.5 from the branches, bark, and trunks of Quercus mongolica are significantly higher than those of the other four tree species in the smoldering state, and the emissions of PM2.5 from the five tree species are ordered as follows: bark > branch > trunk. This study will help to further understand the impact of forest fires on the atmospheric environment and ecosystems in Northern China.