bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of Road Surfaces Based on CNN Architecture and Tire Acoustical Signals
Authors: Yoo Jinhwan , Lee Chang-Hun , Jea Hae-Min , Lee Sang-Kwon , Yoon Youngsam , Lee Jaehun , Yum Kiho , Hwang Seoung-Uk
Published: September 2022

This paper presents a novel work for classification of road surfaces using deep learning method-based convolutional neural network (CNN) architecture. With the development of advanced driver assistance system (ADAS) and autonomous driving technologies, the need for research on vehicle state recognition has increased. However, research on road surface classification has not yet been conducted. If road surface classification and recognition are possible, the control system can make a more robust decision by validating the information from other sensors. Therefore, road surface classification is essential. To achieve this, tire-pavement interaction noise (TPIN) is adopted as a data source for road surface classification. Accelerometers and vision sensors have been used in conventional approaches. The disadvantage of acceleration signals is that they can only represent the surface profile properties and are masked by the resonance characteristics of the car structure. An image signal can be easily contaminated by factors such as illumination, obstacles, and blurring while driving. However, the TPIN signal reflects the surface profile properties of the road and its texture properties. The TPIN signal is also robust compared to those in which the image signal is affected. The measured TPIN signal is converted into a 2-dimensional image through time–frequency analysis. Converted images were used together with a CNN architecture to examine the feasibility of the road surface classification system.
Multigranularity Syntax Guidance with Graph Structure for Machine Reading Comprehension
Authors: Xu Chuanyun , Liu Zixu , Li Gang , Zhu Changpeng , Zhang Yang
Published: September 2022

In recent years, pre-trained language models, represented by the bidirectional encoder representations from transformers (BERT) model, have achieved remarkable success in machine reading comprehension (MRC). However, limited by the structure of BERT-based MRC models (for example, restrictions on word count), such models cannot effectively integrate significant features, such as syntax relations, semantic connections, and long-distance semantics between sentences, leading to the inability of the available models to better understand the intrinsic connections between text and questions to be answered based on it. In this paper, a multi-granularity syntax guidance (MgSG) module that consists of a “graph with dependence” module and a “graph with entity” module is proposed. MgSG selects both sentence and word granularities to guide the text model to decipher the text. In particular, syntactic constraints are used to guide the text model while exploiting the global nature of graph neural networks to enhance the model’s ability to construct long-range semantics. Simultaneously, named entities play an important role in text and answers and focusing on entities can improve the model’s understanding of the text’s major idea. Ultimately, fusing multiple embedding representations to form a representation yields the semantics of the context and the questions. Experiments demonstrate that the performance of the proposed method on the Stanford Question Answering Dataset is better when compared with the traditional BERT baseline model. The experimental results illustrate that our proposed “MgSG” module effectively utilizes the graph structure to learn the internal features of sentences, solve the problem of long-distance semantics, while effectively improving the performance of PrLM in machine reading comprehension.
Stick-Slip Phenomena and Acoustic Emission in the Hertzian Linear Contact
Authors: Babici Laura Mariana , Tudor Andrei , Romeu Jordi
Published: September 2022

AE detection and analysis usually requires a specific, costly platform due to its particular burst nature and high-frequency content. This experimental study investigates the relationship between low-demand acoustic emission parameters (AE) and the occurrence of stick–slip (SS) at the Hertzian linear contact. Hence, the correlation of basic AE characteristics (amplitude, energy, and evolution in time) with stick–slip characteristics (static and kinetic friction coefficients, amplitude, energy, and evolution in time) is pursued. Tribological tests were conducted on cylinder–plane specimens under dry friction conditions with different loads at different low driving speeds and Hertzian contact pressures at a constant stiffness. The AE, normal, and friction forces were recorded simultaneously on the experimental stand. At the cylinder–plane interface, the jumps specific to the stick–slip phenomenon (friction coefficient—COF) were followed after a few milliseconds by AE jump peaks. The results of the experiments show that the amplitude and energy generated by AE were sensitive to the occurrence of the stick–slip phenomenon, while the AE and COF energies in the stick and slip phases had the same law of variation based on the driving velocities. The results show that the amplitude and energy of the sampled low-frequency AE signals were enough to detect the friction in SS and demonstrate the potential of AE as a tool for detecting and monitoring the tribological behaviour of SS at the linear Hertzian contact.
An Improved Algorithm of Drift Compensation for Olfactory Sensors
Authors: Lu Siyu , Guo Jialiang , Liu Shan , Yang Bo , Liu Mingzhe , Yin Lirong , Zheng Wenfeng
Published: September 2022

This research mainly studies the semi-supervised learning algorithm of different domain data in machine olfaction, also known as sensor drift compensation algorithm. Usually for this kind of problem, it is difficult to obtain better recognition results by directly using the semi-supervised learning algorithm. For this reason, we propose a domain transformation semi-supervised weighted kernel extreme learning machine (DTSWKELM) algorithm, which converts the data through the domain and uses SWKELM algorithmic classification to transform the semi-supervised classification problem of different domain data into a semi-supervised classification problem of the same domain data.
X-ray Phase Contrast Imaging from Synchrotron to Conventional Sources: A Review of the Existing Techniques for Biological Applications
Authors: Quenot Laurene , Bohic Sylvain , Brun Emmanuel
Published: September 2022

Since the seminal work of Roentgen, X-ray imaging mainly uses the same physical phenomenon: the absorption of light by matter. Thanks to third-generation synchrotrons that provide a high flux of quasi-coherent X-rays, we have seen in recent years new imaging concepts such as phase contrast or dark-field imaging that were later adapted to conventional X-ray sources. These innovative imaging techniques are particularly suitable for visualizing soft matter, such as biological tissues. After a brief introduction to the physical foundations of these two techniques, we present the different experimental set-ups that are now available to produce such contrasts: propagation, analyzer-based, grating interferometry and non-interferometric methods, such as coded aperture and modulation techniques. We present a comprehensive review of their principles; associated data processing; and finally, their requirements for their transfer outside of synchrotrons. In conclusion, gratings interferometry, coded aperture and modulation techniques seem to be the best candidates for the widespread use of phase contrast and dark-field imaging on low-cost X-ray sources.
A Glimpse into Photodetachment Spectra of Giant and Nested Fullerene Anions
Authors: Dolmatov Valeriy K. , Manson Steven T.
Published: September 2022

We focus on the study of the photodetachment of bare, i.e., single-cage (CN)− as well as nested (multi-cage) (CN@CM@…)− singly charged fullerene anions. We calculate the attached electron’s wavefunctions, energies, oscillator strengths and photodetachment cross sections of the C60−, C240−, C540−, (C60@C240)−, (C60@C540)−, (C240@C540)− and (C60@C240@C540)− fullerene anions, where the attached electron is captured into the ground s-state by the resultant external field provided by all fullerene cages in the anion. The goal is to gain insight into the changes in behavior ofphotodetachment of this valence electron as a function of the different geometries and potentials of the various underlying fullerenes or nested fullerenes (fullerene onions) both due to their increasing size and due to “stuffing” of a larger bare fullerene with smaller fullerenes. To meet this goal, we opt for a simple semi-empirical approximation to this problem: we approximate each individual fullerene cage by a rigid potential sphere of a certain inner radius, thickness and potential depth, as in numerous other model studies performed to date. The results reveal a number of rather significant differences in the wavefunctions, oscillator strengths and photodetachment cross sections among these fullerene anions, some of which are completely counter-intuitive. The results obtained can serve as a “zeroth-order-touchstone” for future studies of single-cage and nested fullerene anions by more rigorous theories and/or experiments to build upon this work to assess the importance of interactions omitted in the present study.
Molecular Tools and Their Applications in Developing Salt-Tolerant Soybean (Glycine max L.) Cultivars
Authors: Rasheed Adnan , Raza Ali , Jie Hongdong , Mahmood Athar , Ma Yushen , Zhao Long , Xing Hucheng , Li Linlin , Hassan Muhammad Umair , Qari Sameer H. , Jie Yucheng
Published: September 2022

Abiotic stresses are one of the significant threats to soybean (Glycine max L.) growth and yields worldwide. Soybean has a crucial role in the global food supply chain and food security and contributes the main protein share compared to other crops. Hence, there is a vast scientific saddle on soybean researchers to develop tolerant genotypes to meet the growing need of food for the huge population. A large portion of cultivated land is damaged by salinity stress, and the situation worsens yearly. In past years, many attempts have increased soybean resilience to salinity stress. Different molecular techniques such as quantitative trait loci mapping (QTL), genetic engineering, transcriptome, transcription factor analysis (TFs), CRISPR/Cas9, as well as other conventional methods are used for the breeding of salt-tolerant cultivars of soybean to safeguard its yield under changing environments. These powerful genetic tools ensure sustainable soybean yields, preserving genetic variability for future use. Only a few reports about a detailed overview of soybean salinity tolerance have been published. Therefore, this review focuses on a detailed overview of several molecular techniques for soybean salinity tolerance and draws a future research direction. Thus, the updated review will provide complete guidelines for researchers working on the genetic mechanism of salinity tolerance in soybean.
Targeting Capabilities of Native and Bioengineered Extracellular Vesicles for Drug Delivery
Authors: Frolova Liubov , Li Isaac
Published: September 2022

Extracellular vesicles (EVs) are highly promising as drug delivery vehicles due to their nanoscale size, stability and biocompatibility. EVs possess natural targeting abilities and are known to traverse long distances to reach their target cells. This long-range organotropism and the ability to penetrate hard-to-reach tissues, including the brain, have sparked interest in using EVs for the targeted delivery of pharmaceuticals. In addition, EVs can be readily harvested from an individual’s biofluids, making them especially suitable for personalized medicine applications. However, the targeting abilities of unmodified EVs have proven to be insufficient for clinical applications. Multiple attempts have been made to bioengineer EVs to fine-tune their on-target binding. Here, we summarize the current state of knowledge on the natural targeting abilities of native EVs. We also critically discuss the strategies to functionalize EV surfaces for superior long-distance targeting of specific tissues and cells. Finally, we review the challenges in achieving specific on-target binding of EV nanocarriers.
The Implications of Sports Biomechanics Studies on the Research and Development of Running Shoes: A Systematic Review
Authors: Lin Shuangshuang , Song Yang , Cen Xuanzhen , Bálint Kovács , Fekete Gusztáv , Sun Dong
Published: September 2022

Although various sports footwear demonstrated marked changes in running biomechanical variables, few studies have yielded definitive findings on the underlying mechanisms of shoe constructions affecting running-related performance and injuries. Therefore, this study focused on examining the effect of basic shoe constructions on running biomechanics and assessing the current state of sports shoe production in terms of injury and efficiency. Relevant literature was searched on five databases using Boolean logic operation and then screened by eligibility criteria. A total of 1260 related articles were retrieved in this review, and 41 articles that met the requirements were finally included, mainly covering the influence of midsole, longitudinal bending stiffness, heel-toe drop, shoe mass, heel flare, and heel stabilizer on running-related performance and injuries. The results of this review study were: (1) The functional positioning of running shoe design and the target groups tend to influence running performance and injury risk; (2) Thickness of 15–20 mm, hardness of Asker C50-C55 of the midsole, the design of the medial or lateral heel flares of 15°, the curved carbon plate, and the 3D printed heel cup may be beneficial to optimize performance and reduce running-related injuries; (3) The update of research and development concepts in sports biomechanics may further contribute to the development of running shoes; (4) Footwear design and optimization should also consider the influences of runners’ strike patterns.
The Acute and Short-Term Inhalation of Carbon Nanofiber in Sprague-Dawley Rats
Authors: Jo Mi Seong , Kim Boo Wook , Kim Young Hun , Kim Jin Kwon , Kim Hoi Pin , Shin Jae Hoon , Lee Gun Ho , Ahn Kangho , Gulumian Mary , Yu Il Je
Published: September 2022

The inhalation toxicity of carbon nanofibers (CNFs) is not clearly known due to relatively few related studies reported. An acute inhalation study and short-term inhalation study (5 days) were therefore conducted using Sprague-Dawley rats. In the acute inhalation study, the rats were grouped and exposed to a fresh air control or to low (0.238 ± 0.197), moderate (1.935 ± 0.159), or high (24.696 ± 6.336 mg/m3) CNF concentrations for 6 h and thereafter sacrificed at 14 days. For the short-term inhalation study, the rats were grouped and exposed to a fresh air control or low (0.593 ± 0.019), moderate (2.487 ± 0.213), or high (10.345 ± 0.541 mg/m3) CNF concentrations for 6 h/day for 5 days and sacrificed at 1, 3, and 21 days post-exposure. No mortality was observed in the acute inhalation study. Thus, the CNF LC50 was higher than 25 mg/m3. No significant body or organ weight changes were noted during the 5 days short-term inhalation study or during the post-exposure period. No significant effects of toxicological importance were observed in the hematological, blood biochemical, and coagulation tests. In addition, the bronchoalveolar lavage (BAL) fluid cell differential counts and BAL inflammatory markers showed no CNF-exposure-relevant changes. The histopathological examination also found no CNF-exposure-relevant histopathological lesions. Thus, neither acute nor 5 days inhalation exposure to CNFs induced any noticeable toxicological responses.
Does the c.-14C>T Mutation in the IFITM5 Gene Provide Identical Phenotypes for Osteogenesis Imperfecta Type V? Data from Russia and a Literature Review
Authors: Tyurin Anton , Merkuryeva Elena , Zaripova Aliya , Markova Tatyana , Nagornova Tatyana , Dantsev Ilya , Nadyrshina Dina , Zakharova Ekaterina , Khusainova Rita
Published: September 2022

Osteogenesis imperfecta (OI) is a large group of genetically heterogeneous diseases resulting from decreased bone density and an abnormal microarchitecture, which are clinically manifested by abnormal bone fractures. A distinctive clinical feature of this group of diseases is the presence of spontaneous fractures and skeletal deformities. However, the clinical manifestations of different types of OI are characterized by marked polymorphism with variable severity of skeletal and extra-skeletal features. Previous studies have shown that a mutation (c.-14C>T) in the IFITM5 gene is responsible for autosomal dominant OI type V. However, the mutation has a variable expression pattern and marked clinical heterogeneity. In this study, a clinical and genetic analysis of 12 cases with molecularly confirmed OI type V from 12 unrelated families was performed. Significant clinical heterogeneity of the disease with the same molecular defect was detected. In six subjects (50%), there were no classic signs of OI type V (formation of a hyperplastic bone callus, calcification of the interosseous membrane and dislocation of the radial head). In all cases, the mutation occurred de novo.
C. elegans as a Powerful Tool for Cancer Screening
Authors: di Luccio Eric , Morishita Masayo , Hirotsu Takaaki
Published: September 2022

Regular cancer screening is critical for early cancer detection. Cancer screening tends to be burdensome, invasive, and expensive, especially for a comprehensive multi-organ check. Improving the rate and effectiveness of routine cancer screenings remain a challenge in health care. Multi-cancer early detection (MCED) is an exciting concept and a potentially effective solution for addressing current issues with routine cancer screening. In recent years, several technologies have matured for MCED, such as identifying cell-free tumor DNA in blood or using organisms such as Caenorhabditis elegans as a tool for early cancer detection. In Japan, N-NOSE is a commercially available multi-cancer detection test based on the chemotaxis of C. elegans using a urine sample showing 87.5% sensitivity and 90.2% specificity. In this review, we focus on using C. elegans as a powerful biosensor for universal cancer screening. We review N-NOSE clinical research results, spotlighting it as an effective primary cancer screening test.
Ruthenium and Nickel Molybdate-Decorated 2D Porous Graphitic Carbon Nitrides for Highly Sensitive Cardiac Troponin Biosensor
Authors: Khushaim Walaa , Mani Veerappan , Peramaiya Karthik , Huang Kuo-Wei , Salama Khaled Nabil
Published: September 2022

Two-dimensional (2D) layered materials functionalized with monometallic or bimetallic dopants are excellent materials to fabricate clinically useful biosensors. Herein, we report the synthesis of ruthenium nanoparticles (RuNPs) and nickel molybdate nanorods (NiMoO4 NRs) functionalized porous graphitic carbon nitrides (PCN) for the fabrication of sensitive and selective biosensors for cardiac troponin I (cTn-I). A wet chemical synthesis route was designed to synthesize PCN-RuNPs and PCN-NiMoO4 NRs. Morphological, elemental, spectroscopic, and electrochemical investigations confirmed the successful formation of these materials. PCN-RuNPs and PCN-NiMoO4 NRs interfaces showed significantly enhanced electrochemically active surface areas, abundant sites for immobilizing bioreceptors, porosity, and excellent aptamer capturing capacity. Both PCN-RuNPs and PCN-NiMoO4 NRs materials were used to develop cTn-I sensitive biosensors, which showed a working range of 0.1–10,000 ng/mL and LODs of 70.0 pg/mL and 50.0 pg/mL, respectively. In addition, the biosensors were highly selective and practically applicable. The functionalized 2D PCN materials are thus potential candidates to develop biosensors for detecting acute myocardial infractions.
Productivity Prediction and Analysis Method of Large Trailing Suction Hopper Dredger Based on Construction Big Data
Authors: Cheng Tao , Lu Qiaorong , Kang Hengrui , Fan Ziyuan , Bai Shuo
Published: September 2022

Trailing suction hopper dredgers (TSHD) are the most widely used type of dredgers in dredging engineering construction. Accurate and efficient productivity prediction of dredgers is of great significance for controlling dredging costs and optimizing dredging operations. Based on machine learning and artificial intelligence, this paper proposes a feature selection method based on the Lasso-Maximum Information Coefficient (MIC), uses methods such as Savitzky-Golay (S-G) filtering for data preprocessing, and then selects different models for prediction. To avoid the limitations of a single model, we assign weights according to the predicted goodness of fit of each model and obtain a weight combination model (WCM) with better generalization performance. By comparing multiple error metrics, we find that the optimization effect is obvious. The method effectively predicts the construction productivity of the TSHD and can provide meaningful guidance for the construction control of the TSHD, which has important engineering significance.
Bioinformatics and Functional Analysis of a New Nuclear Localization Sequence of the Influenza A Virus Nucleoprotein
Authors: Nguyen Nhan L. T. , Panté Nelly
Published: September 2022

Influenza viruses deliver their genome into the nucleus of infected cells for replication. This process is mediated by the viral nucleoprotein (NP), which contains two nuclear localization sequences (NLSs): NLS1 at the N-terminus and a recently identified NLS2 (212GRKTR216). Through mutagenesis and functional studies, we demonstrated that NP must have both NLSs for an efficient nuclear import. As with other NLSs, there may be variations in the basic residues of NLS2 in different strains of the virus, which may affect the nuclear import of the viral genome. Although all NLS2 variants fused to the GFP mediated nuclear import of GFP, bioinformatics showed that 98.8% of reported NP sequences contained either the wild-type sequence 212GRKTR216 or 212GRRTR216. Bioinformatics analyses used to study the presence of NLS2 variants in other viral and nuclear proteins resulted in very low hits, with only 0.4% of human nuclear proteins containing putative NLS2. From these, we studied the nucleolar protein 14 (NOP14) and found that NLS2 does not play a role in the nuclear import of this protein but in its nucleolar localization. We also discovered a functional NLS at the C-terminus of NOP14. Our findings indicate that NLS2 is a highly conserved influenza A NP sequence.
Timing of Blood Sample Processing Affects the Transcriptomic and Epigenomic Profiles in CD4+ T-cells of Atopic Subjects
Authors: Alhamdan Fahd , Laubhahn Kristina , Happle Christine , Habener Anika , Jirmo Adan C. , Thölken Clemens , Conca Raffaele , Chung Ho-Ryun , Hansen Gesine , Potaczek Daniel P. , Schaub Bianca , Grychtol Ruth , Garn Holger
Published: September 2022

Optimal pre-analytical conditions for blood sample processing and isolation of selected cell populations for subsequent transcriptomic and epigenomic studies are required to obtain robust and reproducible results. This pilot study was conducted to investigate the potential effects of timing of CD4+ T-cell processing from peripheral blood of atopic and non-atopic adults on their transcriptomic and epigenetic profiles. Two heparinized blood samples were drawn from each of three atopic and three healthy individuals. For each individual, CD4+ T-cells were isolated from the first blood sample within 2 h (immediate) or from the second blood sample after 24 h storage (delayed). RNA sequencing (RNA-Seq) and histone H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-Seq) analyses were performed. A multiplicity of genes was shown to be differentially expressed in immediately processed CD4+ T-cells from atopic versus healthy subjects. These differences disappeared when comparing delayed processed cells due to a drastic change in expression levels of atopy-related genes in delayed processed CD4+ T-cells from atopic donors. This finding was further validated on the epigenomic level by examining H3K27 acetylation profiles. In contrast, transcriptomic and epigenomic profiles of blood CD4+ T-cells of healthy donors remained rather unaffected. Taken together, for successful transcriptomics and epigenomics studies, detailed standard operation procedures developed on the basis of samples from both healthy and disease conditions are implicitly recommended.
Copper-Induced Fluorescence Quenching in a Bis[2-(2′-hydroxyphenyl)benzoxazole]pyridinium Derivative for Quantification of Cu2+ in Solution
Authors: Rajapakshe Buddhima U. , Li Yonghao , Corbin Brian , Wijesinghe Kaveesha J. , Pang Yi , Abeywickrama Chathura S.
Published: September 2022

Accurate determination of Cu2+ in solution is crucial for preventing several disease conditions. Spectroscopy-based techniques for metal ion detection are promising methods due to their excellent sensitivity and rapid response time. In this work, we are reporting a newly synthesized 2-(2′-Hydroxyphenyl) benzoxazole-based compound, probe 2, by incorporating a vinyl pyridinium segment into the bis(HBO) 4 system. Probe 2 exhibited excellent specificity toward Cu2+ in solution. The ratiometric absorbance (λ440/λ370) and the quenching of fluorescence at λem ≈585 nm exhibited an excellent linear correlation. The formation of the 2-Cu complex can be utilized as a highly sensitive spectroscopic method for the detection of Cu2+ in solution with a detection limit of 0.15 µM. In addition, Cu2+-induced fluorescence quenching in probe 2 occurs mainly via a static quenching mechanism by forming a 2-Cu complex, and the stability constant for the 2-Cu complex was calculated based on spectroscopic measurements.
A Ratiometric Fluorescence Probe of Dopamine-Functionalized Carbon Nanodots for Hypochlorite Detection
Authors: Qi Wenjing , Chen Lei , Du Chengpei , Wang Yi
Published: September 2022

A dopamine-functionalized carbon nanodot (C-dots) ratiometric fluorescence probe for hypochlorite (ClO−) detection is reported. Fluorescent C-dots with maximal emission at 420 nm are synthesized via the hydrothermal synthesis of 3-hydroxyphenylboric acid at 160 °C for 8 h. After modified with dopamine for 5 min, the obtained dopamine-functionalized C-dots exhibit two maximal fluorescence emissions at 420 nm and 460 nm. Fluorescent intensity at 460 nm gets quenched with the addition of ClO− and fluorescent intensity at 420 nm is almost unaffected. Therefore dopamine-functionalized C-dots can be used as ratiometric fluorescence probe for highly sensitive detection of ClO−. The ratio of fluorescent intensity at 460 nm and 420 nm (I460nm/I420nm) has a linear relationship with the concentration of ClO− from 2 μM to 60 μM and limit of detection (LOD) of 0.6 μM. It shows high selectivity for the detection of ClO− toward other anions (SO42−, Cl−, NO3−, S2−, CO32−), metal ions (Mg2+, Ba2+, Ag+, Fe3+, Ca2+, Na+, Cr6+, Cr3+, Hg+), or other substances such as H2O2, glutamate, cysteine, and citric acid. When it is utilized in ClO− detection in tap water, the average recoveries are from 95.7% to 103.2% with the relative standard deviations (RSDs) lower than 5%.
Lactoferrin as Possible Treatment for Chronic Gastrointestinal Symptoms in Children with Long COVID: Case Series and Literature Review
Authors: Morello Rosa , De Rose Cristina , Cardinali Sara , Valentini Piero , Buonsenso Danilo
Published: September 2022

Long COVID is an emergent, heterogeneous, and multisystemic condition with an increasingly important impact also on the pediatric population. Among long COVID symptoms, patients can experience chronic gastrointestinal symptoms such as abdominal pain, constipation, diarrhea, vomiting, nausea, and dysphagia. Although there is no standard, agreed, and optimal diagnostic approach or treatment of long COVID in children, recently compounds containing multiple micronutrients and lactoferrin have been proposed as a possible treatment strategy, due to the long-standing experience gained from other gastrointestinal conditions. In particular, lactoferrin is a pleiotropic glycoprotein with antioxidant, anti-inflammatory, antithrombotic, and immunomodulatory activities. Moreover, it seems to have several physiological functions to protect the gastrointestinal tract. In this regard, we described the resolution of symptoms after the start of therapy with high doses of oral lactoferrin in two patients referred to our post-COVID pediatric unit due to chronic gastrointestinal symptoms after SARS-CoV-2 infection.
COVID-19 History Increases the Anxiety of Mothers with Children in Intensive Care during the Pandemic in Turkey
Authors: Yildiz Eren , Koc Apaydin Zuhal , Alay Berna , Dincer Zübeyde , Cigri Emrah
Published: September 2022

This study aimed to examine the mental status of mothers whose children were hospitalized during the COVID-19 pandemic, especially in places where risk factors are higher such as pediatric intensive care units, and to contribute to the development of psychological health policies, especially for these high-risk groups in epidemic situations. Method: This descriptive cross-sectional study was conducted between January 2021 and July 2021. The population of the study was mothers whose children were hospitalized in the pediatric intensive care unit during the study period. Data collection was carried out via a face-to-face interview method by experienced nurses working in pediatric clinics using a sociodemographic data form, the Beck Anxiety Inventory, the Beck Depression Inventory, the Fear of COVID-19 Inventory, and the Coronavirus Anxiety Inventory. Results: The median age of the participants was 33 (min: 21, max: 50). The Beck Anxiety score was affected by the child’s diagnosis, location, and history of COVID-19 (* P = 0.011, ** P = 0.018, and *** P = 0.002, respectively). Similarly, the Beck Depression score was affected by the child’s diagnosis and history of COVID-19 in a relative (* P = 0.034 and ** P = 0.037, respectively). The Coronavirus Anxiety score was affected by a history of COVID-19 in a relative and work status (* P = 0.040 and ** P = 0.005, respectively), while the Fear of COVID-19 score was not significantly affected by any variable. In a logistic regression model, previous COVID-19 experience was independently associated with anxiety; a history of COVID-19 increased the risk of developing anxiety by approximately 15 times (odds ratio: 14.915, 95% CI: 2.075–107.192). Conclusion: When children of mothers with a history of COVID-19 are hospitalized, special attention should be given to their mothers concerning psychological support and assistance.
Theoretical Study of the Friction Coefficient in the M-B Model
Authors: Cao Hongjun , Zhu Min , Li Biao , Lu Xiaohan , Li Haiyan , Guo Ming , Wu Fei , Xu Zijian
Published: September 2022

In order to study the influencing factors of friction coefficient in an M-B model, based on the basic model of fractal theory, the distribution function and probability distribution density of the micro-convex body truncation area are derived by using mathematical and statistical means, and a new model of critical truncation area and friction coefficient in fractal surface contact process are proposed. Considering the differences between the actual contact area and the truncated area during plastic deformation of the micro-convex body, a correction factor is introduced. Focusing on the mechanism of the elastic-plastic transition phase, and finally a friction coefficient model based on the fractal dimension, the normal force and correction factor is derived. Finally, the friction coefficient of fractal surface is simulated and verified by taking nickel as an example, and it is proved that the new model is correct in predicting the change trend of friction coefficient in the M-B model.
Naphthenic Acids Aggregation: The Role of Salinity
Authors: Cunha Renato D. , Ferreira Livia J. , Orestes Ednilsom , Coutinho-Neto Mauricio D. , de Almeida James M. , Carvalho Rogério M. , Maciel Cleiton D. , Curutchet Carles , Homem-de-Mello Paula
Published: September 2022

Naphthenic Acids (NA) are important oil extraction subproducts. These chemical species are one of the leading causes of marine pollution and duct corrosion. For this reason, understanding the behavior of NAs in different saline conditions is one of the challenges in the oil industry. In this work, we simulated several naphthenic acid species and their mixtures, employing density functional theory calculations with the MST-IEFPCM continuum solvation model, to obtain the octanol–water partition coefficients, together with microsecond classical molecular dynamics. The latter consisted of pure water, low-salinity, and high-salinity environment simulations, to assess the stability of NAs aggregates and their sizes. The quantum calculations have shown that the longer chain acids are more hydrophobic, and the classical simulations corroborated: that the longer the chain, the higher the order of the aggregate. In addition, we observed that larger aggregates are stable at higher salinities for all the studied NAs. This can be one factor in the observed low-salinity-enhanced oil recovery, which is a complex phenomenon. The simulations also show that stabilizing the aggregates induced by the salinity involves a direct interplay of Na+ cations with the carboxylic groups of the NAs inside the aggregates. In some cases, the ion/NA organization forms a membrane-like circular structural arrangement, especially for longer chain NAs.
Solution of Extended Multi-Objective Portfolio Selection Problem in Uncertain Environment Using Weighted Tchebycheff Method
Authors: Kumar Pavan
Published: September 2022

In this paper, a mathematical model for an extended multi-objective portfolio selection (EMOPS) problem is explored with liquidity considered as another objective function besides the risk and return. The model is mathematically formulated in an uncertain environment. The concerned uncertainty is dealt with by employing the fuzzy numbers in the risk matrix and return. While the fuzzy EMOPS model is converted into the corresponding deterministic case based on the α—level sets of the fuzzy numbers, a weighted Tchebycheff method is implemented by defining relative weights and ideal targets. The merit of the suggested method is the applicability in many real-world situations. At the end, some numerical illustration is exhibited for the utility of the suggested EMOPS problem. Finally, it is concluded that the suggested method is simple to learn and to implement in real-life situations for the decision maker.
Unambiguous Identification of Crystal Plasticity Parameters from Spherical Indentation
Authors: Frydrych Karol , Papanikolaou Stefanos
Published: September 2022

Identification of elastic and plastic properties of materials from indentation tests received considerable attention in the open literature. However, unambiguous and automatic determination of parameters in the case of the crystal plasticity (CP) model is still an unsolved problem. In this paper, we investigate the possibility to unambiguously identify the CP parameters from spherical indentation tests using finite element method simulations combined with evolutionary algorithm (EA). To this aim, we check the efficiency and accuracy of EA while fitting either load–penetration curves, surface topographies, or both at the same time. By fitting the results against simulation data with known parameters, we can verify the accuracy of each parameter independently. We conclude that the best option is to fit both load–penetration curve and surface topography at the same time. To understand why a given fitting scheme leads to correct values for some parameters and incorrect values for others, a sensitivity analysis was performed.
CD47 Expression Predicts Unfavorable Prognosis in Clear Cell Renal Cell Carcinoma after Curative Resection
Authors: Park Hosub , Jee Seungyun , Bang Seongsik , Son Hwangkyu , Cha Hyebin , Myung Jaekyung , Sim Jongmin , Kim Yeseul , Paik Seungsam , Kim Hyunsung
Published: September 2022

The role of CD47 expression as a ‘do not eat me’ signal that inhibits phagocytosis of tumor cells by macrophages is well established. Immune checkpoint therapy that targets CD47 has been successful in preclinical trials and is currently undergoing clinical investigation for various human malignancies. Here, the clinicopathological correlation with CD47 expression in clear cell renal cell carcinoma (ccRCC) was explored. CD47 expression was evaluated by immunohistochemical staining in tissue microarray sections of 235 ccRCC tissues. CD47 expression was observed in 28 (11.9%) of 235 ccRCC tissues and was significantly associated with higher WHO/ISUP grade (p = 0.001), frequent lymphovascular invasion (p = 0.036), frequent renal vein thrombus (p = 0.018), frequent sinus fat invasion (p = 0.004), frequent sarcomatous change (p = 0.001), higher pT stage (p = 0.002), higher pN stage (p = 0.002), higher pM stage (p < 0.001), and advanced American Joint Committee on Cancer stage (p = 0.002). In the survival analyses, positive CD47 expression was associated with cancer-specific survival (p = 0.003). However, positive CD47 expression was not associated with recurrence-free survival. In conclusion, CD47 expression was associated with adverse clinicopathological parameters and cancer-specific survival in patients with ccRCC.
Advances in Chip-Based Quantum Key Distribution
Authors: Liu Qiang , Huang Yinming , Du Yongqiang , Zhao Zhengeng , Geng Minming , Zhang Zhenrong , Wei Kejin
Published: September 2022

Quantum key distribution (QKD), guaranteed by the principles of quantum mechanics, is one of the most promising solutions for the future of secure communication. Integrated quantum photonics provides a stable, compact, and robust platform for the implementation of complex photonic circuits amenable to mass manufacture, and also allows for the generation, detection, and processing of quantum states of light at a growing system’s scale, functionality, and complexity. Integrated quantum photonics provides a compelling technology for the integration of QKD systems. In this review, we summarize the advances in integrated QKD systems, including integrated photon sources, detectors, and encoding and decoding components for QKD implements. Complete demonstrations of various QKD schemes based on integrated photonic chips are also discussed.
Radiation-Tolerant Electronics
Authors: Leroux Paul
Published: September 2022

When thinking of radiation-tolerant electronics, many readers will think of space [...]
Benchmarking Real-Time Control Platforms Using a Matlab/Simulink Coder with Applications in the Control of DC/AC Switched Power Converters
Authors: Vasquez-Plaza Jesus , Lopez-Chavarro Andres , Sanabria-Torres Enrique , Patarroyo-Montenegro Juan , Andrade Fabio
Published: September 2022

In the control of DC/AC switched power converters (SPC), one of the most important aspects to be considered is the selection of the real-time control platform. The real-time control platform must be able to meet the high performance efficiency and regulation requirements of the DC/AC SPC, as these typically operate at switching frequencies in the order of kHz to MHz. For this reason, the hardware characteristics of the ADC and PWM, and the processing capacity of the real-time control platform are of vital importance when implementing advanced digital controllers that maintain voltage and current levels within regulatory standards. In this context, we aimed to perform a comparative study of the computation times of different real-time control platforms when implementing different control strategies for DC/AC switched power converters. We also analyzed the impact of the real-time control platforms on the THD of the voltages generated by the DC/AC switched power converters. With the help of this paper, researchers and developers will have criteria to select which real-time control platform to use in real-time control for DC/AC SPC applications.
Breakdown Pressure Prediction of Tight Sandstone Horizontal Wells Based on the Mechanism Model and Multiple Linear Regression Model
Authors: Yang Huohai , Xie Binghong , Liu Xuanyu , Chu Xiangshu , Ruan Jingxin , Luo Yanxu , Yue Jie
Published: September 2022

Accurately predicting the breakdown pressure in horizontal sections is essential when designing and optimizing fracturing jobs for horizontal wells in tight gas reservoirs. Taking the Sulige block in the Ordos Basin as an example, for different completion methods combined with indoor rock experience data and well data, a new method for predicting breakdown pressure based on a linear regression model is proposed. Based on the Hossain horizontal well stress field model, this paper established a calculation model of breakdown pressure under different completion methods by using experimental and well data. The average error between the calculation results and the actual breakdown pressure at the initiation point is 3.67%. A Pearson correlation analysis was conducted for eight sensitive factors of horizontal well stress, which showed that the maximum horizontal principal stress, minimum horizontal principal stress, tensile strength, and elastic modulus had strong linear correlations with breakdown pressure. In this study, multiple linear regression was used to establish the prediction model of breakdown pressure under different completion conditions, and the calculation method of the prediction model was optimized. The model was verified using the relevant data for four horizontal wells. The average relative error between the prediction model and the actual breakdown pressure was 4.33–6.30%, indicating that the breakdown pressure obtained by the new prediction model was similar to the actual conditions. Thus, the prediction model is reasonable and reliable.
Effect of Nano-MgO Doping in XLPE on Charge Transport and Electric Field Distribution in Composite Insulation of HVDC Cable Joint
Authors: Wang Yani , Zhang Shuai , Sun Yuanyuan , Yang Xingwu , Liu Chun
Published: September 2022

The space charge characteristics of cross-linked polyethylene (XLPE) can be improved to some extent by doping the appropriate amount of nano-MgO. In this study, in order to explore the influence of nano-MgO on the space charge and electric field distributions of the composite insulation of high voltage direct current (HVDC) cable joints, the effect of nano-MgO concentration on the depth and density of the deep traps in MgO/XLPE was first analyzed. On this basis, the charge transport simulation model of a 320 kV HVDC cable joint was established with MgO/XLPE as the cable insulation, and the space charge and electric field distributions of the cable joint under different temperature conditions were simulated. It was found that the radial charge distribution in the joint shows different trends with the change of nano-MgO concentration. There is a significant difference in the charge density on both sides of the (MgO/XLPE)/EPDM interface, and the difference first decreased and then increased with the increase of concentration. When the nano-MgO concentration was 0.5 wt%, the number of charges in the radial direction is the fewest, and the maximum value is only 0.42 C/m−3. The radial electric field changed abruptly at the (MgO/XLPE)/EPDM interface, and it was homogenized to a certain extent with time. It was found that the highest electric field of the interface is at the root of the stress cone, which is the weakest point of the joint insulation. When the nano-MgO concentration was 0.5 wt%, the electric field at the root of the stress cone was found to be the lowest, with a value of 13.38 kV/mm. A comprehensive comparison shows that the joint can maintain better insulation when the concentration is 0.5 wt% compared to other concentrations. The results can provide a basis for further improving the insulation properties of HVDC cable joints through nano doping technology.
Static Concentrator Photovoltaics Module for Electric Vehicle Applications Based on Compound Parabolic Concentrator
Authors: Vu Hoang , Vu Ngoc Hai , Shin Seoyong
Published: September 2022

Electric vehicles (EVs) and photovoltaics (PVs) are new technologies that will play an important role in the transportation industry over the next decade. Using solar panels on the roofs of cars is one of the simplest ways to reduce fuel costs and increase the mobility of electric vehicles. Solar electric cars can be charged anywhere under the Sun without additional infrastructure, but the problem is the size of the solar panel is limited on the roof and the electricity conversion efficiency of the panel is only 15% to 20%. This means they will not provide significant electricity to EVs. An effective way to increase efficiency is to utilize multi-junction solar cells with concentrator photovoltaic (CPV) technology. The challenge is that the moving sun-tracking mechanism will reduce the stability of the vehicle structure. To solve this issue, in this research, we present a static concentrator photovoltaic system for electric vehicles. This structure is more stable and simpler than CPV systems using sun-tracking mechanisms and thus suitable for car roof application. The CPV system includes solid compound parabolic concentrators (CPCs), three-junction solar cells, and a crystalline Si cell panel. This structure allows for the manufacture of a static CPV with a geometrical concentration ratio of 4× for three-junction cells. The simulation results showed that the module can achieve 25% annual efficiency. Moreover, it can be flexible to meet the requirements of car roof application.
Teaching Energy Economics in the GCC: A Synergistic Approach between Engineering and Economics
Authors: Zhou Yishu , Smith Joseph D. , Gelles Greg
Published: September 2022

Issues related to safe and abundant energy production have been prominent in recent years. This is particularly true when society considers how to increase the quality of life by providing low-cost energy to citizens. A significant concern of the Gulf Cooperation Council (GCC) relates to the environmental effects of energy production and energy use associated with climate change. Efforts to reduce fossil fuel use and increase the use of renewable energy, together with the price volatility of fossil fuels, have seriously impacted the economics of many oil-producing countries, particularly the Gulf States, which has led to efforts to make their economies more diverse and less dependent on oil production. In this article, we introduce a multidisciplinary energy economics course developed at the Missouri University of Science and Technology that can be easily adopted by GCC universities to enhance future generations’ understanding of energy challenges.