bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Fitness Cost, Stability, and Conjugation Frequencies of tet(X4)-Positive Plasmids in Chicken and Pig Escherichia coli
Authors: Liu Ziyi , Zhang Huiru , Xiao Xia , Liu Yuan , Li Ruichao , Wang Zhiqiang
Published: November 2022

The large-scale epidemic of the tet(X4) gene in the livestock and poultry industry is threatening public health; however, there is still a lack of comparative studies on tet(X4)-bearing plasmids in chicken and pig Escherichia coli. To evaluate the prevalence trend of tet(X4)-bearing plasmids and the factors influencing their persistence in the livestock and poultry industry, we examined the fitness cost, stability under tetracyclines pressure, and conjugation frequencies at various temperatures of six tet(X4)-bearing plasmids in four representative pig E. coli isolates and chicken E. coli isolates. Compared with pig E. coli, the plasmid in chicken E. coli showed lower fitness cost, and stronger ability to promote bacterial biofilm formation and motility. Meanwhile, the presence of tetracycline may favor the stability of tet(X4)-bearing plasmids, which was more common in chicken E. coli. Furthermore, the optimal temperature for IncX1 tet(X4)-bearing plasmid conjugation was 42 °C, and its conjugation frequency in chicken E. coli was higher than that in pig E. coli, whereas the optimal temperature for IncFII tet(X4)-bearing plasmid conjugation was 37 °C and it performed better in pig E. coli, suggesting the predominant plasmid types circulating in chicken E. coli and pig E. coli may be distinct. Collectively, although tet(X4) currently appears to be more prevalent in pig E. coli, this is probably independent of the fitness cost caused by tet(X4)-plasmids. To curb the future spread of the tet(X4) gene, reduced tetracyclines usage and tailored interventions should be applied in different breeding industries.
Defining Exposure Predictors of Meropenem That Are Associated with Improved Survival for Severe Bacterial Infection: A Preclinical PK/PD Study in Sepsis Rat Model
Authors: Wang Yan , Liu Lanyu , Wu Qiping , Yin Qiufen , Xie Feifan
Published: November 2022

Background: The pharmacokinetic/pharmacodynamic (PK/PD) index of carbapenems that best correlates with in vivo antimicrobial activity is percent time of dosing interval in which free drug concentration remains above MIC (%fT > MIC), while the magnitudes of the PK/PD index of carbapenems remains undefined in critically ill sepsis patients. Methods: A sepsis rat model was first developed by comparing the survival outcomes after intraperitoneal injection of different inoculum size (1–10 × 107 CFU) of Pseudomonas aeruginosa ATCC9027 (MIC = 0.125 mg/L) in neutropenic rats. The PK characteristics of the model drug meropenem in the developed sepsis rat model was then evaluated, and PK modeling and simulation was applied to design meropenem dosing regimens attaining various PD targets (40%fT > MIC, 100%fT > MIC, and 100%fT > 4 × MIC). The microbiological response and survival outcomes for different meropenem treatment regimens were investigated in the rat sepsis model (n = 12 for each group). Results: The optimal inoculum for the rat sepsis model was 1 × 107 CFU of Pseudomonas aeruginosa ATCC9027. A one-compartment model with first-order absorption best described the PK of meropenem in sepsis rats. Pronounced survival prolongation and lower hazard risk were observed in the treatment groups of 50 or 75 mg/kg/q2.4h (100%fT > MIC) and 75 mg/kg/q2h (100%fT > 4 × MIC) compared to the 75 mg/kg/q6h (40%fT > MIC) group, while meropenem groups with PD targets of 100%fT > MIC and 100%fT > 4 × MIC showed comparable survival curves. Microbiological response for different PD targets is inconclusive due to irregular bacterial counts in blood samples. Conclusions: The PD target of 40%fT > MIC is suboptimal for sepsis rats, and the aggressive 100%fT > 4 × MIC target does not provide a survival benefit against the target of 100%fT > MIC.
Empirical Antibiotic Therapy for Gram-Negative Bacilli Ventilator-Associated Pneumonia: Observational Study and Pharmacodynamic Assessment
Authors: Pajot Olivier , Lakhal Karim , Lambert Jérome , Gros Antoine , Bruel Cédric , Boulain Thierry , Garot Denis , Das Vincent , Timsit Jean François , Cerf Charles , Souweine Bertrand , Chaffaut Cendrine , Mentec Hervé , Zahar Jean Ralph , Mira Jean Paul , Jullien Vincent
Published: November 2022

Background: Strong evidence suggests a correlation between pharmacodynamics (PD) index and antibiotic efficacy while dose adjustment should be considered in critically ill patients due to modified pharmacokinetic (PK) parameters and/or higher minimum inhibitory concentrations (MICs). This study aimed to assess pharmacodynamic (PD) target attainment considering both antibiotics serum concentrations and measured MICs in these patients. Method: A multicentric prospective open-label trial conducted in 11 French ICUs involved patients with Gram-negative bacilli (GNB) ventilator-associated pneumonia (VAP) confirmed by quantitative cultures. Results: We included 117 patients. Causative GNBs were P. aeruginosa (40%), Enterobacter spp. (23%), E. coli (20%), and Klebsiella spp. (16%). Hence, 117 (100%) patients received β-lactams, 65 (58%) aminoglycosides, and two (1.5%) fluoroquinolones. For β-lactams, 83% of the patients achieved a Cmin/MIC > 1 and 70% had a Cmin/MIC > 4. In the case of high creatinine clearance (CrCL > 100 mL/min/1.73 m2), 70.4% of the patients achieved a Cmin/MIC ratio > 1 versus 91% otherwise (p = 0.041), and 52% achieved a Cmin/MIC ratio > 4 versus 81% (p = 0.018). For aminoglycosides, 94% of the patients had a Cmax/MIC ratio > 8. Neither β-lactams nor aminoglycosides PK/PD parameters were associated clinical outcomes, but our data suggest a correlation between β-lactams Cmin/MIC and microbiological success. Conclusion: In our ICU patients treated for GNB VAP, using recommended antibiotic dosage led in most cases to PK/PD targets attainment for aminoglycosides and β-lactams. High creatinine clearance should encourage clinicians to focus on PK/PD issues.
Defining the S-Glutathionylation Proteome by Biochemical and Mass Spectrometric Approaches
Authors: Li Xiaolu , Zhang Tong , Day Nicholas J. , Feng Song , Gaffrey Matthew J. , Qian Wei-Jun
Published: November 2022

Protein S-glutathionylation (SSG) is a reversible post-translational modification (PTM) featuring the conjugation of glutathione to a protein cysteine thiol. SSG can alter protein structure, activity, subcellular localization, and interaction with small molecules and other proteins. Thus, it plays a critical role in redox signaling and regulation in various physiological activities and pathological events. In this review, we summarize current biochemical and analytical approaches for characterizing SSG at both the proteome level and at individual protein levels. To illustrate the mechanism underlying SSG-mediated redox regulation, we highlight recent examples of functional and structural consequences of SSG modifications. Finally, we discuss the analytical challenges in characterizing SSG and the thiol PTM landscape, future directions for understanding of the role of SSG in redox signaling and regulation and its interplay with other PTMs, and the potential role of computational approaches to accelerate functional discovery.
Selenium and Redox Enzyme Activity in Pregnant Women Exposed to Methylmercury
Authors: Branco Vasco , Carvalho Luís , Barboza Cássia , Mendes Eduarda , Cavaco Afonso , Carvalho Cristina
Published: November 2022

Selenium (Se) is a micronutrient with essential physiological functions achieved through the production of selenoproteins. Adequate Se intake has health benefits and reduces mercury (Hg) toxicity, which is important due to its neurotoxicity. This study determined the Se status and redox enzyme, including selenoproteins’, activity in pregnant women highly exposed to Hg (between 1 to 54 µg Hg/L blood) via fish consumption. A cross-sectional study enrolling 513 women between the first and third trimester of pregnancy from Madeira, Portugal was conducted, encompassing collection of blood and plasma samples. Samples were analyzed for total Se and Hg levels in whole blood and plasma, and plasma activity of redox-active proteins, such as glutathione peroxidase (GPx), thioredoxin reductase (TrxR) and thioredoxin (Trx). Enzyme activities were related to Se and Hg levels in blood. Se levels in whole blood (65.0 ± 13.1 µg/L) indicated this population had a sub-optimal Se status, which translated to low plasma GPx activity (69.7 ± 28.4 U/L). The activity of TrxR (12.3 ± 5.60 ng/mL) was not affected by the low Se levels. On the other hand, the decrease in Trx activity with an increase in Hg might be a good indicator to prevent fetal susceptibility.
Association of Polyphenols Consumption with Risk for Gestational Diabetes Mellitus and Preeclampsia: A Systematic Review and Meta-Analysis
Authors: Jorquera Gonzalo , Fornes Romina , Cruz Gonzalo , Thomas-Valdés Samanta
Published: November 2022

Gestational Diabetes Mellitus (GDM) and preeclampsia (PE) affects 6–25% of pregnancies and are characterized by an imbalance in natural prooxidant/antioxidant mechanisms. Due to their antioxidant and anti-inflammatory properties, polyphenols consumption during the pregnancy might exert positive effects by preventing GDM and PE development. However, this association remains inconclusive. This systematic review and metanalysis is aimed to analyze the association between polyphenol-rich food consumption during pregnancy and the risk of GDM and PE. A systematic search in MEDLINE, EMBASE, and Web of Science (Clarivate Analytics, London, United Kingdom) for articles dated between 1 January 1980 and July 2022 was undertaken to identify randomized controlled trials and observational studies evaluating polyphenol-rich food consumption and the risk of GDM and PE. The Newcastle-Ottawa Scale was used to evaluate the quality of these included studies. Twelve studies were included, of which eight articles evaluated GDM and four studied PE. A total of 3785 women presented with GDM (2.33%). No association between polyphenol consumption and GDM was found (ES = 0.85, 95% CI 0.71–1.01). When total polyphenol intake was considered, a lower likelihood to develop GDM was noted (ES = 0.78, 95% CI 0.69–0.89). Furthermore, polyphenol consumption was not associated with PE development (ES = 0.90, 95% CI 0.57–1.41). In conclusion, for both outcomes, pooled analyses showed no association with polyphenol-rich food consumption during pregnancy. Therefore, association of polyphenol intake with a decreased risk of GDM and PE remains inconclusive.
Glymphatic Dysfunction Induced Oxidative Stress and Neuro-Inflammation in Major Depression Disorders
Authors: Gu Simeng , Li Yumeng , Jiang Yao , Huang Jason H. , Wang Fushun
Published: November 2022

Major Depression disorder (MDD) is a potentially life-threatening mental illness, however, many patients have a poor response to current treatments. Recent studies have suggested that stress- or trauma-induced oxidative stress and inflammation could be important factors involved in the development of MDD, but the mechanisms remain unclear. We showed that the glymphatic system is a recently discovered structure in the brain that may be involved in the clearance of large molecular and cell debris in extracellular space. In addition, the glymphatic system can help with the removal of reactive oxygen species (ROS) and cytokines such as IL-1β and HIF-1α. Glymphatic impairment can lead to ROS accumulation in the microenvironment, inducing cellular injury signaling and activating NLRP3 in microglia to induce inflammation and, thus, many brain diseases, including psychiatric disorders. Therefore, trauma-induced glymphatic impairment could induce oxidative stress and inflammation, and thus MDD. This paper will review recent advances with regard to stress-induced glymphatic system impairment and ROS-mediated inflammation in MDD.
Impact of N-Acetyl Cysteine (NAC) on Tuberculosis (TB) Patients—A Systematic Review
Authors: Mapamba Daniel Adon , Sauli Elingarami , Mrema Lucy , Lalashowi Julieth , Magombola David , Buza Joram , Olomi Willyhelmina , Wallis Robert S. , Ntinginya Nyanda Elias
Published: November 2022

Sustained TB infection overproduces reactive oxygen species (ROS) as a host defense mechanism. Research shows ROS is destructive to lung tissue. Glutathione (GSH) neutralizes ROS, although it is consumed. NAC is a precursor of GSH synthesis, and administering an appropriate dose of NAC to patients with respiratory conditions may enhance lung recovery and replenish GSH. The present review searched for articles reporting on the effects of NAC in TB treatment from 1960 to 31 May 2022. The PICO search strategy was used in Google Scholar, PubMed, SciFinder, and Wiley online library databases. The COVIDENCE tool was used to delete inappropriate content. We eventually discovered five clinical trials, one case report, seven reviews, in vitro research, and four experimental animal studies from the twenty-four accepted articles. The use of NAC resulted in increased GSH levels, decreased treatment time, and was safe with minimal adverse events. However, the evidence is currently insufficient to estimate the overall effects of NAC, thus the study warrants more NAC clinical trials to demonstrate its effects in TB treatment.
Study on Permeability Stress-Sensitivity in Seepage-Geomechanical Coupling of Fractured Deep Tight Sandstone Gas Reservoirs
Authors: Song Jiecheng , Liu Jianjun , Song Rui , Song Yujia
Published: November 2022

Accurately predicting the characteristics and influencing factors of permeability stress-sensitivity contributes to improving gas production in gas reservoirs. In this paper, the effects of effective stress on the permeability of fractured deep tight sandstone reservoirs were studied by laboratory tests. With the experimental results, a coupled seepage-geomechanical model for fractured deep tight sandstone gas reservoirs was constructed. The influences of pore pressure and geo-stress on permeability characteristics and gas production were studied by numerical simulation. The results indicate: (1) When the effective stress increases from 0 to 65 MPa, the permeability of the natural sample with fractures decreases by 81.28%, and the permeability of the intact core sample decreases by 54.67%. (2) When the pore pressure decreases from 120 to 85 MPa, the three-dimensional effective stress increases. The largest increase of the effective stress was along the vertical direction, which increased by 11~19 MPa. In addition, the permeability of the fractured zone and the intact rock along the vertical direction decreased by about 40% and 16%, respectively. (3) The mean square error between the historical gas production results and the results by simulation was 2.22 when considering the permeability stress-sensitivity, and 4.01 without considering the permeability stress-sensitivity. The proposed coupled seepage-geomechanical model with permeability stress-sensitivity proved to be more accurate in historical gas production comparison and prediction. This study provides a reliable optimization scheme for the development of fractured deep tight sandstone gas reservoirs.
Semantic Decomposition and Anomaly Detection of Tympanic Membrane Endoscopic Images
Authors: Song Dahye , Song In Sik , Kim Jaeyoung , Choi June , Lee Yeonjoon
Published: November 2022

With the recent development of deep learning, the supervised learning method has been widely applied in otolaryngology. However, its application in real-world clinical settings is difficult because of the inapplicability outside the learning area of the model and difficulty in data collection due to privacy concerns. To solve these limitations, we studied anomaly detection, the task of identifying sample data that do not match the overall data distribution with the Variational Autoencoder (VAE), an unsupervised learning model. However, the VAE makes it difficult to learn complex data, such as tympanic membrane endoscopic images. Accordingly, we preprocess tympanic membrane images using Adaptive Histogram Equalization (AHE) and Canny edge detection for effective anomaly detection. We then had the VAE learn preprocessed data for only normal tympanic membranes and VAE was used to calculate an abnormality score for those differences between the distribution of the normal and abnormal tympanic membrane images. The abnormality score was applied to the K-nearest Neighbor (K-NN) algorithm to classify normal and abnormal tympanic membranes. As a result, we were obtained a total of 1232 normal and abnormal eardrum images, classified with an accuracy of 94.5% using an algorithm that applied only normal tympanic membrane images. Consequently, we propose that unsupervised-learning-based anomaly detection of the tympanic membrane can solve the limitations of existing supervised learning methods.
Dynamic Voltage Regulation and Unbalance Compensation in a Low-Voltage Distribution Network Using Energy Storage System
Authors: Rafał Krzysztof , Biskupski Jacek , Bykuć Sebastian , Chaja Patryk
Published: November 2022

Modern distribution grids may suffer problems of voltage distortion, especially along radial low-voltage feeders with a high penetration of intermittent, unbalanced and distorted loads and generation sources. It is a challenge to develop an effective voltage-regulation method using a straightforward implementation. This paper proposes a novel method for local voltage control and balancing using a shunt-connected energy storage system. The compensation principles are explained, and a complete controller design is proposed. The algorithm is designed to be implemented in power electronic converters that provide the interface between the storage and the grid. The original contribution is the development of a low-level control method, which includes voltage balancing and a method to minimize the compensator current and is to be implemented in power electronic converters that provide the interface between the storage and the grid. The calculation of active and reactive compensator currents is explained with relation to the estimated grid impedance. The efficacy of the designed controller is verified by laboratory experiments. It is shown that voltage regulation using the proposed method is achieved with less apparent power compared to a system where only reactive power is used. The controller presents a very good dynamic response to rapid voltage variations, such as unbalanced voltage dips. The applicability and constraints of the method are discussed with respect to the present state of the art in low-voltage-grid voltage regulation.
The Speed of Pathogen Eradication May Prevent the Early Development of Cartilage Destruction: Case Series of Long-Term Follow-Up of Septic Arthritis (SA) after Anterior Cruciate Ligament Reconstruction (ACL-R) and Literature Review
Authors: Waszczykowski Michał , Fabiś-Strobin Anna , Korczyc-Stępnicka Agnieszka , Małecki Krzysztof , Białecki Jerzy , Bartosz Paweł , Fabiś Jarosław
Published: November 2022

Late diagnosis and treatment of septic arthritis (SA) after anterior cruciate ligament reconstruction (ACL-R) can lead to graft and cartilage damage. Pathogen eradication time may be the key to preventing the development of osteoarthritis. The purpose of this study was to evaluate the effect of the proposed management of SA after ACL-R on knee function, pathogen eradication time and knee cartilage status on MRI. Five patients with acute knee SA after ACL-R were included in this study. All five patients underwent knee arthroscopic debridement with lavage and flow drainage with physiological saline with vancomycin. All five patients underwent clinical assessment, isokinetic examinations and MRI quantitative cartilage thickness evaluation at two follow-up points: at a mean of 10.9 years and at a mean of 18.1 years. Slight statistical differences in cartilage thickness on the medial femoral condyle were observed between the SA and control groups (2.077 mm and 2.237 mm, respectively; p = 0.021). There were no significant differences in cartilage thickness between the first and last follow-ups in the SA knees. The proposed treatment could lead to a faster eradication of infection, and thus protect against the early development of osteoarthritis. The quadriceps peak torque deficit may persist afterwards at a mean of 18.1 years follow-up.
Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring for Head and Neck Radiation Therapy
Authors: Ng Curtise K. C. , Leung Vincent W. S. , Hung Rico H. M.
Published: November 2022

Various commercial auto-contouring solutions have emerged over past few years to address labor-intensiveness, and inter- and intra-operator variabilities issues of traditional manual anatomy contouring for head and neck (H&N) radiation therapy (RT). The purpose of this study is to compare the clinical performances between RaySearch Laboratories deep learning (DL) and atlas-based auto-contouring tools for organs at risk (OARs) segmentation in the H&N RT with the manual contouring as reference. Forty-five H&N computed tomography datasets were used for the DL and atlas-based auto-contouring tools to contour 16 OARs and time required for the segmentation was measured. Dice similarity coefficient (DSC), Hausdorff distance (HD) and HD 95th-percentile (HD95) were used to evaluate geometric accuracy of OARs contoured by the DL and atlas-based auto-contouring tools. Paired sample t-test was employed to compare the mean DSC, HD, HD95, and contouring time values of the two groups. The DL auto-contouring approach achieved more consistent performance in OARs segmentation than its atlas-based approach, resulting in statistically significant time reduction of the whole segmentation process by 40% (p < 0.001). The DL auto-contouring had statistically significantly higher mean DSC and lower HD and HD95 values (p < 0.001–0.009) for 10 out of 16 OARs. This study proves that the RaySearch Laboratories DL auto-contouring tool has significantly better clinical performances than its atlas-based approach.
High-Resolution Through-the-Wall Radar Imaging with Exploitation of Target Structure
Authors: Xu Chendong , Wu Qisong
Published: November 2022

It is quite challenging for through-the-wall radar imaging (TWRI) to achieve high-resolution ghost-free imaging with limited measurements in an indoor multipath scenario. In this paper, a novel high-resolution TWRI algorithm with the exploitation of the target clustered structure in a hierarchical Bayesian framework is proposed. More specifically, an extended spike-and-slab clustered prior is imposed to statistically encourage the cluster formations in both downrange and crossrange domains of the target region, and a generative model of the proposed approach is provided. Then, a Markov Chain Monte Carol (MCMC) sampler is used to implement the posterior inference. Compared to other state-of-the-art algorithms, the proposed nonparametric Bayesian algorithm can preserve underlying target clustered properties and effectively suppress these isolated spurious scatterers without any prior information on targets themselves, such as sizes, shapes, and numbers.
Utilizing Alike Neighbor Influenced Similarity Metric for Efficient Prediction in Collaborative Filter-Approach-Based Recommendation System
Authors: Singh Raushan Kumar , Singh Pradeep Kumar , Singh Juginder Pal , Singh Akhilesh Kumar , Dhanasekaran Seshathiri
Published: November 2022

The most popular method collaborative filter approach is primarily used to handle the information overloading problem in E-Commerce. Traditionally, collaborative filtering uses ratings of similar users for predicting the target item. Similarity calculation in the sparse dataset greatly influences the predicted rating, as less count of co-rated items may degrade the performance of the collaborative filtering. However, consideration of item features to find the nearest neighbor can be a more judicious approach to increase the proportion of similar users. In this study, we offer a new paradigm for raising the rating prediction accuracy in collaborative filtering. The proposed framework uses rated items of the similar feature of the ’most’ similar individuals, instead of using the wisdom of the crowd. The reliability of the proposed framework is evaluated on the static MovieLens datasets and the experimental results corroborate our anticipations.
An Experimental Analysis of Drift Detection Methods on Multi-Class Imbalanced Data Streams
Authors: Palli Abdul Sattar , Jaafar Jafreezal , Gomes Heitor Murilo , Hashmani Manzoor Ahmed , Gilal Abdul Rehman
Published: November 2022

The performance of machine learning models diminishes while predicting the Remaining Useful Life (RUL) of the equipment or fault prediction due to the issue of concept drift. This issue is aggravated when the problem setting comprises multi-class imbalanced data. The existing drift detection methods are designed to detect certain drifts in specific scenarios. For example, the drift detector designed for binary class data may not produce satisfactory results for applications that generate multi-class data. Similarly, the drift detection method designed for the detection of sudden drift may struggle with detecting incremental drift. Therefore, in this experimental investigation, we seek to investigate the performance of the existing drift detection methods on multi-class imbalanced data streams with different drift types. For this reason, this study simulated the streams with various forms of concept drift and the multi-class imbalance problem to test the existing drift detection methods. The findings of current study will aid in the selection of drift detection methods for use in developing solutions for real-time industrial applications that encounter similar issues. The results revealed that among the compared methods, DDM produced the best average F1 score. The results also indicate that the multi-class imbalance causes the false alarm rate to increase for most of the drift detection methods.
Inverse Analysis of Structural Damage Based on the Modal Kinetic and Strain Energies with the Novel Oppositional Unified Particle Swarm Gradient-Based Optimizer
Authors: Alkayem Nizar Faisal , Shen Lei , Al-hababi Tareq , Qian Xiangdong , Cao Maosen
Published: November 2022

Structural damage inspection is a key structural engineering technique that strives for ensuring structural safety. In this regard, one of the major intelligent approaches is the inverse analysis of structural damage using evolutionary computation. By considering the recent advances in this field, an efficient hybrid objective function that combines the global modal kinetic and modal strain energies is introduced. The newly developed objective function aims to extract maximum dynamic information from the structure and overcome noisy conditions. Moreover, the original methods are usually vulnerable to the associated high multimodality and uncertainty of the inverse problem. Therefore, the oppositional learning (OL) for population initialization and convergence acceleration is first adopted. Thereafter, the unified particle swarm algorithm (UPSO) mechanism is combined with another newly developed algorithm, the gradient-based optimizer (GBO). The new algorithm, called the oppositional unified particle swarm gradient-based optimizer (OL-UPSGBO), with the convergence acceleration feature of (OL), enhances balanced exploration-exploitation of UPSO, and the local escaping operator of GBO is designed to specifically deal with the complex inverse analysis of structural damage problems. To authenticate the performance of the OL-UPSGBO, the complex benchmark set of CEC 2017 is adopted to compare the OL-UPSGBO with several original metaheuristics. Furthermore, the developed approach for structural damage identification is tested using several damage scenarios in a multi-story frame structure. Results show that the developed approach shows superior performance and robust behavior when tackling the inverse analysis of structural damage.
Influence of Complex Load on the Strength and Reliability of Offshore Derrick by Using APDL and Python
Authors: Tan Zhengbo , Chen Hao , Wan Fu , Liao Feilong , Gao Yuan , Cai Can
Published: November 2022

In an offshore operational environment, complex loads such as the hook load, stand load and wind load play a crucial role in the structural strength and reliability of the offshore derrick. Previous studies have mainly focused on the effect of a specific load on the strength of the derrick by using commercial software. Therefore, the influencing mechanism of each complex load on the strength and reliability of the offshore derrick is urgently necessary to explore. Not only is the strength numerical model of the JJ315/45-K typical derrick established and conducted via APDL (ANSYS Parametric Design Language), but also the stress–strength reliability simulation is explored and plotted using Python code and APDL. Furthermore, the influence and contribution of each load to the strength and reliability is determined. With the increase in hook load, the positions of maximum reliability risk appear in section II-1. With the increase in stand load or back wind load, the positions of maximum reliability risk appear in the bottom section. In addition, with the decrease in the columns’ height, the stress proportion of the hook load decreases by 73.5%, the stress proportion of the stand load increases by 22.6%, and the stress proportion of the back wind load changes slightly. When the wind speed is less than 20 m/s, the hook load mainly affects the minimum reliability index of the derrick. Moreover, when the wind speed is more than 20 m/s, the back wind load mainly affects the minimum reliability index of the derrick. This study provides a thorough explanation of the strength distribution law and the reliability of derricks under complex loads.
Decision-Refillable-Based Two-Material-View Fuzzy Classification for Personal Thermal Comfort
Authors: Xu Zhaofei , Lu Weidong , Hu Zhenyu , Zhou Ta , Zhou Yi , Yan Wei , Jiang Feifei
Published: November 2022

The personal thermal comfort model is used to design and control the thermal environment and predict the thermal comfort responses of individuals rather than reflect the average response of the population. Previous individual thermal comfort models were mainly focused on a single material environment. However, the channels for individual thermal comfort were various in real life. Therefore, a new personal thermal comfort evaluation method is constructed by means of a reliable decision-based fuzzy classification model from two views. In this study, a two-view thermal comfort fuzzy classification model was constructed using the interpretable zero-order Takagi–Sugeno–Kang (TSK) fuzzy classifier as the basic training subblock, and it is the first time an optimized machine learning algorithm to study the interpretable thermal comfort model is used. The relevant information (including basic information, sampling conditions, physiological parameters, physical environment, environmental perception, and self-assessment parameters) was obtained from 157 subjects in experimental chambers with two different materials. This proposed method has the following features: (1) The training samples in the input layer contain the feature data under experimental conditions with two different materials. The training models constructed from the training samples under these two conditions complement and restrict each other and improve the accuracy of the whole model training. (2) In the rule layer of the training unit, interpretable fuzzy rules are designed to solve the existing layers with the design of short rules. The output of the intermediate layer of the fuzzy classifier and the fuzzy rules are difficult to explain, which is problematic. (3) Better decision-making knowledge information is obtained in both the rule layer of the single-view training model and in the two-view fusion model. In addition, the feature mapping space is generated according to the degree of contribution of the decision-making information from the two single training views, which not only preserves the feature information of the source training samples to a large extent but also improves the training accuracy of the model and enhances the generalization performance of the training model. Experimental results indicated that TMV-TSK-FC has better classification performance and generalization performance than several related state-of-the-art non-fuzzy classifiers applied in this study. Significantly, compared with the single view fuzzy classifier, the training accuracies and testing accuracies of TMV-TSK-FC are improved by 3–11% and 2–9%, respectively. In addition, the experimental results also showed good semantic interpretability of TMV-TSK-FC.
Research on the Performance of an End-to-End Intelligent Receiver with Reduced Transmitter Data
Authors: Wang Mingbo , Wang Anyi , Zhang Yuzhi , Chai Jing
Published: November 2022

A large amount of data transmission is one of the challenges faced by communication systems. In this paper, we revisit the intelligent receiver consisting of a neural network, and we find that the intelligent receiver can reduce the data at the transmitting end while improving the decoding accuracy. Specifically, we first construct a smart receiver model, and then design two ways to reduce the data at the transmitter side, namely, end-of-transmitter data trimming and equal-interval data trimming, to investigate the decoding performance of the receiver under the different trimming methods. The simulation results show that the receiver still has an accurate decoding performance with a small amount of trimming at the end of the transmitter data, while the decoding performance of the smart receiver is better than that of the conventional receiver with complete data when the data is trimmed at equal intervals. Moreover, the receiver with equally-spaced data cropping has a lower BER when the data at the transmitter side is reduced by the same data length. This paper provides a new solution to reduce the amount of data at the transmitter side.
Acoustic Shooting and Bounce Ray Method for Calculating Echoes of Complex Underwater Targets
Authors: Zhao Gang , Zheng Wei , Sun Naiwei , Shen Shen , Wu Xianyun
Published: November 2022

The acoustic scattering characteristics of a target are of great significance to the design of underwater acoustic detection systems. With the improvement in underwater weapon detection ability, the precision and accuracy of underwater target echo characteristic simulations are required to be higher and higher. The traditional underwater target simulation based on bright spot can no longer meet the needs of an underwater acoustic detection system for targeting fine feature recognition. This paper proposes a calculation using the fine complex underwater target echo bounce beam line method, in addition to the establishment of a bandwidth signal time domain calculation model and the integral dimension reduction to accelerate the algorithm on the basis of thorough target subspace division, combined with the geometrical acoustics method (GA) and physical acoustics (PA) for the pipeline space beam propagation tracking and aperture sound field to solve and realize the acoustic scattering characteristic calculation of a complex underwater target. Finally, the proposed method was verified by the Benchmark standard submarine. The accuracy and computational efficiency of the PA acceleration method are given, and the integrity of the target information calculated by the method is verified by acoustic ISAR imaging analysis. The simulation results show that the pipeline method of bouncing an acoustic beam is suitable for the simulation of complex underwater, target-wide band fine echoes.
Key Properties for the Toxicity Classification of Chemicals: A Comparison of the REACH Regulation and Scientific Studies Trends
Authors: Garralaga Mª Pilar , Lomba Laura , Zuriaga Estefanía , Santander Sonia , Giner Beatriz
Published: November 2022

In the last half century, the improvements in quality of life owing to the development of the chemical industry are indisputable. However, despite global improvements, there has also been a large increase in pollution at the environmental level and this has caused relevant harmful risks not only to wildlife and the environment but also to human health. In response, governments have begun to regulate and control chemicals to prevent environmental pollution. At the European level, REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals) was created with the aim to protect human/animal health and the environment from chemicals. Additionally, this regulation shows the main experimental tests that are needed to classify a chemical from a physicochemical and toxicological point of view. The main objective of this study is to compare the tests or experiments stipulated by the European REACH regulation with the studies carried out by the scientific community. To obtain this comparison, an exhaustive bibliographic review was carried out, analyzing the physicochemical properties and the (eco)toxicological information established by the European REACH regulation and scientific articles published in the Web of Science (WOS) database. The results obtained indicate that, although there are many authors who conducted tests indicated by the regulation, there are others whose essays or studies are not in line with the regulation; this may be because, on many occasions, the purpose of the information to be obtained is quite different.
Recent Progress in On-Chip Erbium-Based Light Sources
Authors: Wang Bo , Zhou Peiqi , Wang Xingjun
Published: November 2022

In recent years, silicon photonics has achieved great success in optical communication area. More and more on-chip optoelectronic devices have been realized and commercialized on silicon photonics platform, such as silicon-based modulators, filters and detectors. However, on-chip light sources are still not achieved because that silicon is an indirect bandgap material. To solve this problem, the rare earth element erbium (Er) is considered, which emits light covering 1.5 μm to 1.6 μm and has been widely used in fiber amplifiers. Compared to Er-doped fiber amplifiers (EDFA), the Er ion concentration needs to be more than two orders higher for on-chip Er-based light sources due to the compact size integration requirements. Therefore, the choice of the host material is crucially important. In this paper, we review the recent progress in on-chip Er-based light sources and the advantages and disadvantages of different host materials are compared and analyzed. Finally, the existing challenges and development directions of the on-chip Er-based light sources are discussed.
Special Issue: “The Planning and Scheduling of Manufacturing Systems”
Authors: Renna Paolo
Published: November 2022

The “Fourth Industrial Revolution” (alternatively known as “Industry 4 [...]
Numerical Investigation on Thermal Performance of Duplex Nanocoolant Jets in Drilling of Ti-6Al-4V Alloy
Authors: Mohan R. , Shrikhande Shardul , Joshi Vedant , Harish R.
Published: November 2022

In the current industry, coolants are widely used in numerous operations for the purpose of cooling and heat transfer. These operations include all kinds of heat sinks for electronic devices and manufacturing processes such as milling, drilling, turning, and CNC machining. The thermophysical properties of coolants play a vital role in determining the effectiveness of heat transfer and help prevent the components from wear and tear caused by extremely high temperatures. The computational domain consists of a drill bit and rectangular workpiece, and hybrid nanocoolants are sprayed from duplex nozzles. The nanocoolant heat transfer and flow characteristics of the drill bit–workpiece interface were analysed using the large eddy simulation (LES) turbulence model. The workpiece is made of Ti-6Al-4V alloy maintained at a temperature of 1073.15 K. The coolant used is a mineral oil into which different nanoparticles of Al2O3, TiO2, Cu, MWCNT, and SWCNT are dispersed by varying the volume concentration. The variations in temperature, Nusselt number, and wall heat transfer coefficient, with respect to the volume fraction of nanoparticles and the Reynolds number, were investigated. It was concluded that Cu–Al2O3 nanoparticles dispersed in mineral oil depicted the most favourable heat transfer.
Recognizing Teachers’ Hand Gestures for Effective Non-Verbal Interaction
Authors: Peng Zhenlong , Yang Zhidan , Xiahou Jianbing , Xie Tao
Published: November 2022

Hand gesturing is one of the most useful non-verbal behaviors in the classroom, and can help students activate multi-sensory channels to complement teachers’ verbal behaviors and ultimately enhance teaching effectiveness. The existing mainstream detection algorithms that can be used to recognize hand gestures suffered from low recognition accuracy under complex backgrounds and different backlight conditions. This study proposes an improved hand gesture recognition framework based on key point statistical transformation features. The proposed framework can effectively reduce the sensitivity of images to background and light conditions. We extracted key points of the image and establish a weak classifier to enhance the anti-interference ability of the algorithm in the case of noise and partial occlusion. Then, we used a deep convolutional neural network model with multi-scale feature fusion to recognize teachers’ hand gestures. A series of experiments were conducted on different human gesture datasets to verify the performance of the proposed framework. The results show that the framework proposed in this study has better detection and recognition rates compared to the you only look once (YOLO) algorithm, YOLOv3, and other counterpart algorithms. The proposed framework not only achieved 98.43%, measured by F1 score, for human gesture images in low-light conditions, but also has good robustness in complex lighting environments. We used the proposed framework to recognize teacher gestures in a case classroom setting, and found that the proposed framework outperformed YOLO and YOLOv3 algorithms on small gesture images with respect to recognition performance and robustness.
Nonsurgical Correction of Anterior Crossbite with Extra-Radicular Miniscrews—A Case Report
Authors: Park Jae Hyun , Liaw Johnny Joung-Lin
Published: November 2022

Protrusion can occur after correction of the anterior crossbite in Class III malocclusions. Four-premolar extractions might be indicated if the patients asked for a profile reduction. Two similar Class III anterior crossbite cases illustrate how the skeletal anchorage can prevent protrusion after anterior crossbite correction and the need for four- premolar extractions, as in the first case. The use of extra-radicular miniscrews at the infrazygomatic crest and buccal shelf are recommended for whole arch distalization of the maxillary and mandibular arches to reduce protrusion after anterior crossbite correction. It is an effective and efficient treatment alternative to extraction therapy for the protrusion after anterior crossbite correction. Long-term follow-up records show encouraging results supporting this paradigm shift in anterior crossbite correction with extra-radicular miniscrews.
Voice Simulation: The Next Generation
Authors: Titze Ingo R. , Lucero Jorge C.
Published: November 2022

Simulation of the acoustics and biomechanics of sound production in humans and animals began half a century ago. The three major components are the mechanics of tissue under self-sustained oscillation, the transport of air from the lungs to the lips, and the propagation of sound in the airways. Both low-dimensional and high-dimensional computer models have successfully predicted control of pitch, loudness, spectral content, vowel production, and many other features of speaking and singing. However, the problems of computational efficiency, validity, and accuracy have not been adequately addressed. Low-dimensional models are often more revealing of nonlinear phenomena in coupled oscillators, but the simplifying assumptions are not always validated. High-dimensional models can provide more accuracy, but interpretations of results are sometimes clouded by computational redundancy and uncertainty of parameters. The next generation will likely combine pre-calculations and machine learning with abbreviated critical calculations.
One-Step Microcrystalline Glass Preparation Using Smelting Slag from Waste Automobile Three-Way Catalysts through Iron Collection
Authors: Zhu Xiaoping , Huo Yingda , Zhao Ruiming , Wu Hao , Li Fubao , Sun Shuchen , Liu Chuan
Published: November 2022

The smelting slag obtained through iron collection from waste automobile three-way catalysts was used as a raw material to prepare microcrystalline glass through a one-step crystallization heat treatment. The phase composition and microstructure of the prepared glass were analyzed through X-ray diffraction and scanning electron microscopy–energy dispersive X-ray spectroscopy, respectively. Single-factor experiments were conducted to investigate the effects of crystallization temperature from 900 to 950 °C and crystallization time from 0.5 to 4 h on the physical and chemical properties of the microcrystalline glass. The results indicated that the optimum crystallization temperature and time for preparing microcrystalline glass with glass smelting slag through the proposed one-step crystallization heat treatment process were 950 °C and 3 h, respectively. Under these experimental conditions, the number of crystalline phases of the microcrystalline glass was high, the grains were mainly spherical and columnar particles, the sample structure was dense, and the best results were obtained: the density was 2.72 g/cm3, the water absorption was 1.55%, the porosity was 4.2%, the Vickers hardness was 618 HV, the acid resistance was 2.6%, and the alkali resistance was 0.04%. In addition, the results of the toxicity characteristic leaching procedure indicated that the leaching concentrations of heavy metals such as Zn, Cr, and Pb in the microcrystalline glass were lower than those in the base glass and were considerably lower than the acceptable limits. The microcrystalline glass obtained from final smelting slag through heat treatment can enhance the stabilization of harmful elements. The findings of this study can be applied to the treatment of bulk solid waste.
Predicting the Frequency of Marine Accidents by Navigators’ Watch Duty Time in South Korea Using LSTM
Authors: Choi Jungyeon
Published: November 2022

Despite the development of advanced technology, marine accidents have not decreased. To prevent marine accidents, it is necessary to predict accidents in advance. With the recent development of artificial intelligence (AI), AI technologies such as deep learning have been applied to create and analyze predictive models in various fields. The purpose of this study is to develop a model for predicting the frequency of marine accidents using a long-short term memory (LSTM) network. In this study, a prediction model was developed using marine accidents from 1981 to 2019, and the proposed model was evaluated by predicting the accidents in 2020. As a result, we found that marine accidents mainly occurred during the third officer’s duty time, representing that the accidents are highly related to the navigator’s experience. In addition, the proposed LSTM model performed reliably to predict the frequency of marine accidents with a small mean absolute percentage error (best MAPE: 0.059) that outperformed a traditional statistical method (i.e, ARIMA). This study could help us build LSTM structures for marine accident prediction and could be used as primary data to prevent the accidents by predicting the number of marine accidents by the navigator’s watch duty time.