bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial Challenge in Acute Care Surgery
Authors: Schena Carlo Alberto , de’Angelis Gian Luigi , Carra Maria Clotilde , Bianchi Giorgio , de’Angelis Nicola
Published: September 2022

The burden of infections in acute care surgery (ACS) is huge. Surgical emergencies alone account for three million admissions per year in the United States (US) with estimated financial costs of USD 28 billion per year. Acute care facilities and ACS patients represent boost sanctuaries for the emergence, development and transmission of infections and multi-resistant organisms. According to the World Health Organization, healthcare-associated infections affected around 4 million cases in Europe and 1.7 million in the US alone in 2011 with 39,000 and 99,000 directly attributable deaths, respectively. In this scenario, antimicrobial resistance arose as a public-health emergency that worsens patients’ morbidity and mortality and increases healthcare costs. The optimal patient care requires the application of comprehensive evidence-based policies and strategies aiming at minimizing the impact of healthcare associated infections and antimicrobial resistance, while optimizing the treatment of intra-abdominal infections. The present review provides a snapshot of two hot topics, such as antimicrobial resistance and systemic inflammatory response, and three milestones of infection management, such as source control, infection prevention, and control and antimicrobial stewardship.
In Silico Study for Algerian Essential Oils as Antimicrobial Agents against Multidrug-Resistant Bacteria Isolated from Pus Samples
Authors: Aouf Abdelhakim , Bouaouina Sarah , Abdelgawad Mohamed A. , Abourehab Mohammed A. S. , Farouk Amr
Published: September 2022

In the context of the globally growing problem of resistance to most used antibacterial agents, essential oils offer promising solutions against multidrug-resistant (MDR) bacterial pathogens. The present study aimed to evaluate the prevalence, etiology, and antibiotic-resistance profiles of bacteria responsible for pyogenic infections in Regional Military University Hospital of Constantine. Disc diffusion and broth microdilution (MIC) methods were used to evaluate the antimicrobial activity of essential oils from five Algerian aromatic plants growing wild in the north of Algeria—Salvia officinalis (Sage), Thymus vulgaris (Thyme), Mentha pulegium L. (Mentha), Rosmarinus officinalis (Rosemary), and Pelargonium roseum (Geranium)—against reference and MDR strains. During three months of the prospective study, 112 isolates out of 431 pus samples were identified. Staphylococcus aureus was the most predominant species (25%), followed by Klebsiella pneumoniae (21.42%), Pseudomonas aeruginosa (21%), and Escherichia coli (17.95%). Among pus isolates, 65 were MDR (58.03%). The radial streak-line assay showed that R. officinalis and M. pulegium L. had weak activity against the tested strains, whereas P. roseum showed no activity at all. Meanwhile, T. vulgaris was the most potent, with an inhibition zone of 12–26 mm and an MIC value ranging between 0.25 and 1.25%, followed by S. officinalis with an inhibition zone of 8–12 mm and an MIC value ranging between 0.62 and 2.5%. Generally, A. baumannii and S. aureus ATCC6538P were the most sensitive strains, whereas P. aeruginosa ATCC27853 was the most resistant strain to the oils. Gas chromatography–mass spectrometry analysis of chemical composition revealed the presence of borneol (76.42%) and thymol (17.69%) as predominant in thyme, whereas camphor (36.92%) and α- thujone (34.91%) were the major volatiles in sage. The in-silico study revealed that sesquiterpenes and thymol had the highest binding free energies against the vital enzymes involved in biosynthesis and repair of cell walls, proteins, and nucleic acids compared to monoterpenes. The results demonstrated that T. vulgaris and S. officinalis are ideal candidates for developing future potentially active remedies against MDR strains.
Bioactive Compounds, Nutritional Quality and Antioxidant Capacity of the Red-Fleshed Kirkwood Navel and Ruby Valencia Oranges
Authors: Zacarías-García Jaime , Pérez-Través Laura , Gil José-Vicente , Rodrigo María-Jesús , Zacarías Lorenzo
Published: September 2022

Kirkwood Navel and Ruby Valencia are two spontaneous bud-mutations of the ordinary Washington Navel and Valencia late oranges characterized by the red coloration of their flesh. The purpose of this study was to analyze the physiological features, internal fruit quality, contents of relevant bioactive compounds and antioxidant capacity in the pulps of the red-fleshed fruits compared with the ordinary oranges during late development and maturation. In general, the content of sugars, organic acids, vitamin C, tocopherols, total phenolics and flavonoids, the hydrophilic antioxidant capacity and their changes during maturation were similar in the red-fleshed oranges and in the corresponding blond oranges. However, the mature Ruby fruits contained lower concentrations of sugars, malic and succinic acid and higher levels of citric acid than the ordinary Valencia. The major difference between the pulps of the Kirkwood and Ruby oranges and those of the ordinary oranges was the higher lipophilic antioxidant capacity and SOAC (singlet oxygen absorption capacity) of the former. Together, the high and unique content and composition of carotenoids in Kirkwood and Ruby may contribute to an enhanced antioxidant capacity without any detrimental effects on other fruit-quality attributes, making these varieties good sources of phytochemicals for the fresh-fruit and juice-processing citrus industries.
Bioinspired Lipase Immobilized Membrane for Improving Hesperidin Lipophilization
Authors: Ming Shanxiu , Li Shuyi , Chen Zhe , Chen Xujun , Wang Feifei , Deng Shaonan , Marszałek Krystian , Zhu Zhenzhou , Zhang Wenxiang , Barba Francisco J.
Published: September 2022

Lipophilization is a promising way to improve the bioavailability of flavonoids. However, the traditional enzymatic esterification methods are time-consuming, and present low yields and purity. Herein, a novel membrane-based lipophilization technology—bioinspired lipase immobilized membranes (BLIMs), including CAL-B@PES, CAL-B@PDA/PES and GA/CAL-B@PDA/PES— were fabricated to improve the antioxidant flavanone glycoside hesperidin lipophilization. Via reverse filtration, PDA coating and GA crosslinking, Candida antarctica lipase B (CAL-B) was stably immobilized on membrane to fabricate BLIMs. Among the three BLIMs, GA/CAL-B@PDA/PES had the greatest enzyme activity and enzyme loading, the strongest tolerance of changes in external environmental conditions (temperatures, pH, heating time, storage time and numbers of cycles) and the highest hesperidin esterification efficiency. Moreover, the optimal operating condition for GA/CAL-B@PDA/PES fabrication was the CAL-B concentration of 0.36 mg/mL, operation pressure of 2 bar, GA concentration of 5% and crosslinking time of 1 h. Afterwards, the hesperidin esterification process did not affect the micromorphology of BLIM, but clearly improved the BLIM permeability and esterified product efficiency. The present study reveals the fabrication mechanism of BLIMs and offers insights into the optimizing strategy that governs the membrane-based lipophilization technology process.
Glucose Starvation-Caused Oxidative Stress Induces Inflammation and Autophagy in Human Gingival Fibroblasts
Authors: Li Runbo , Kato Hirohito , Taguchi Yoichiro , Deng Xin , Minagawa Emika , Nakata Takaya , Umeda Makoto
Published: September 2022

Gingival tissue experiences an environment of nutrient shortage, such as low glucose conditions, after periodontal surgery. Our previous studies found that this low glucose condition inhibits normal gingival cell functions. However, the mechanism by which this glucose-deficient environment causes cellular damage to human gingival fibroblasts (HGnFs) remains unclear. This study aimed to investigate the biological effects of ROS induction on HGnFs under low glucose conditions. ROS levels and cellular anti-ROS ability of HGnFs under different glucose concentrations were evaluated by measuring ROS formation and the expression of superoxide dismutase and heme oxygenase 1. Changes in cellular viability were investigated using 5-bromo-2′-deoxyuridine assay and cell survival detection, and the cellular damage was evaluated by the expression of inflammatory cytokines and changes in the expression of autophagy-related protein. ROS formation was then blocked using N-acetyl-L-cysteine (NAC), and the effects of ROS on HGnFs under low glucose conditions were investigated. Low glucose conditions induced ROS accumulation, reduced cellular activity, and induced inflammation and autophagy. After NAC application, the anti-ROS capacity increased, cellular activity improved, and inflammation and autophagy were controlled. This can be effectively controlled by the application of antioxidants such as NAC.
Development of an In Vitro Model of SARS-CoV-Induced Acute Lung Injury for Studying New Therapeutic Approaches
Authors: Shevtsova Yulia A. , Goryunov Kirill V. , Babenko Valentina A. , Pevzner Irina B. , Vtorushina Valentina V. , Inviyaeva Evgeniya V. , Krechetova Lyubov V. , Zorova Ljubava D. , Plotnikov Egor Y. , Zorov Dmitry B. , Sukhikh Gennady T. , Silachev Denis N.
Published: September 2022

One of the causes of death of patients infected by SARS-CoV-2 is the induced respiratory failure caused by excessive activation of the immune system, the so-called “cytokine storm”, leading to damage to lung tissue. In vitro models reproducing various stages of the disease can be used to explore the pathogenetic mechanisms and therapeutic approaches to treating the consequences of a cytokine storm. We have developed an in vitro test system for simulating damage to the pulmonary epithelium as a result of the development of a hyperinflammatory reaction based on the co-cultivation of pulmonary epithelial cells (A549 cells) and human peripheral blood mononuclear cells (PBMC) primed with lipopolysaccharide (LPS). In this model, after 24 h of co-cultivation, a sharp decrease in the rate of proliferation of A549 cells associated with the intrinsic development of oxidative stress and, ultimately, with the induction of PANoptotic death were observed. There was a significant increase in the concentration of 40 cytokines/chemokines in a conditioned medium, including TNF-α, IFN-α, IL-6, and IL-1a, which corresponded to the cytokine profile in patients with severe manifestation of COVID-19. In order to verify the model, the analysis of the anti-inflammatory effects of well-known substances (dexamethasone, LPS from Rhodobacter sphaeroides (LPS-RS), polymyxin B), as well as multipotent mesenchymal stem cells (MSC) and MSC-derived extracellular vesicles (EVs) was carried out. Dexamethasone and polymyxin B restored the proliferative activity of A549 cells and reduced the concentration of proinflammatory cytokines. MSC demonstrated an ambivalent effect through stimulated production of both pro-inflammatory cytokines and growth factors that regenerate lung tissue. LPS-RS and EVs showed no significant effect. The developed test system can be used to study molecular and cellular pathological processes and to evaluate the effectiveness of various therapeutic approaches for the correction of hyperinflammatory response in COVID-19 patients.
Phytochemical Profile, In Vitro Bioactivity Evaluation, In Silico Molecular Docking and ADMET Study of Essential Oils of Three Vitex Species Grown in Tarai Region of Uttarakhand
Authors: Karakoti Himani , Mahawer Sonu Kumar , Tewari Monika , Kumar Ravendra , Prakash Om , de Oliveira Mozaniel Santana , Rawat Dharmendra Singh
Published: September 2022

A comparative study of volatiles, antioxidant activity, phytotoxic activity, as well as in silico molecular docking and ADMET study, was conducted for essential oils from three Vitex species, viz., V. agnus-castus, V. negundo, and V. trifolia. Essential oils (OEs) extracted by hydrodistillation were subjected to compositional analysis using GC-MS. A total number of 37, 45, and 43 components were identified in V. agnus-castus, V. negundo, and V. trifolia, respectively. The antioxidant activity of EOs, assessed using different radical-scavenging (DPPH, H2O2 and NO), reducing power, and metal chelating assays, were found to be significant as compared with those of the standards. The phytotoxic potential of the EOs was performed in the receptor species Raphanusraphanistrum (wild radish) and the EOs showed different levels of intensity of seed germination inhibition and root and shoot length inhibition. The molecular docking study was conducted to screen the antioxidant and phytotoxic activity of the major and potent compounds against human protein target, peroxiredoxin 5, and 4-hydroxyphenylpyruvate dioxygenase protein (HPPD). Results showed good binding affinities and attributed the strongest inhibitory activity to 13-epi-manoyl oxide for both the target proteins.
Date Seed: Rich Source of Antioxidant Phenolics Obtained by Hydrothermal Treatments
Authors: Mrabet Abdessalem , Jiménez-Araujo Ana , Fernández-Prior África , Bermúdez-Oria Alejandra , Fernández-Bolaños Juan , Sindic Marianne , Rodríguez-Gutiérrez Guillermo
Published: September 2022

The growing interest in natural compounds is helping to improve the management of agro-industrial by-products such as the date seed as sources of such compounds. In this work, the application of a hydrothermal treatment at 160 and 180 °C for 60 min was studied to achieve the solubilization of its phenolic components and sugars in order to obtain biologically active extracts. The percentage of phenols and total sugars in the final extracts were very similar, at 45 and 25% for the 160 and 180 °C treatments, respectively. The treatment at a higher temperature allowed greater solubilization of other components. The antioxidant activity was measured as free-radical scavenging capacity. For the DPPH• method, expressed as EC50, the results were 0.34 and 0.37 mg/L, the TEAC values for the ABTS• method were 6.61 and 3.28 mg/g dried extract, and the values obtained by the ORAC method were 12.82 and 9.91 mmol Trolox/g dried extract, for 160 and 180 °C, respectively. All these values are higher than those of other plant extracts and extracts obtained using the whole date. Therefore, the date seed is a very important source of phenols, and through thermal and chromatographic processes, it is possible to obtain extracts with high antioxidant activity.
Biogenic Selenium Nanoparticles and Their Anticancer Effects Pertaining to Probiotic Bacteria—A Review
Authors: Ullah Asad , Mu Jing , Wang Fenghuan , Chan Malik Wajid Hussain , Yin Xian , Liao Yonghong , Mirani Zulfiqar Ali , Sebt-e-Hassan Syed , Aslam Sadar , Naveed Muhammad , Khan Muhammad Naseem , Khatoon Zakia , Kazmi Mohib Reza
Published: September 2022

Selenium nanoparticles (SeNPs) can be produced by biogenic, physical, and chemical processes. The physical and chemical processes have hazardous effects. However, biogenic synthesis (by microorganisms) is an eco-friendly and economical technique that is non-toxic to human and animal health. The mechanism for biogenic SeNPs from microorganisms is still not well understood. Over the past two decades, extensive research has been conducted on the nutritional and therapeutic applications of biogenic SeNPs. The research revealed that biogenic SeNPs are considered novel competitors in the pharmaceutical and food industries, as they have been shown to be virtually non-toxic when used in medical practice and as dietary supplements and release only trace amounts of Se ions when ingested. Various pathogenic and probiotic/nonpathogenic bacteria are used for the biogenic synthesis of SeNPs. However, in the case of biosynthesis by pathogenic bacteria, extraction and purification techniques are required for further useful applications of these biogenic SeNPs. This review focuses on the applications of SeNPs (derived from probiotic/nonpathogenic organisms) as promising anticancer agents. This review describes that SeNPs derived from probiotic/nonpathogenic organisms are considered safe for human consumption. These biogenic SeNPs reduce oxidative stress in the human body and have also been shown to be effective against breast, prostate, lung, liver, and colon cancers. This review provides helpful information on the safe use of biogenic SeNPs and their economic importance for dietary and therapeutic purposes, especially as anticancer agents.
Improved Bioavailability and Bioaccessibility of Lutein and Isoflavones in Cultured Cells In Vitro through Interaction with Ginger, Curcuma and Black Pepper Extracts
Authors: Blank-Landeshammer Bernhard , Klanert Gerald , Mitter Lisa , Turisser Sophia , Nusser Nicolas , König Alice , Iken Marcus , Weghuber Julian
Published: September 2022

Intestinal absorption is intrinsically low for lipophilic micronutrients and phytochemicals. Plant extracts acting as bioavailability enhancers can complement for this deficiency by modulation of both, physicochemical and biochemical parameters, in the absorption process. However, these interactions often are limited to specific conditions and the mechanisms and potential synergisms are poorly understood. In this work, we used a human intestinal cell line to characterize the impact of extracts from C. longa (curcuma), Z. officinale (ginger) and P.nigrum (black pepper) on uptake and transport rates of the xanthophylls lutein and zeaxanthin as well as soy isoflavones measured by HPLC-DAD. We found a significant increase in the uptake of lutein in the presence of curcuma extract and enhanced isoflavone transport rates mediated by curcuma and ginger extracts. Combinations of the plant extracts did not lead to any additional increase in uptake or transport rates. By investigation of mixed micelle incorporation efficiency, we could dismiss changes in bioaccessibility as a potential enhancing mechanism in our experimental setup. We further conducted a rhodamine 123 efflux assay and discovered inhibition of P-glycoproteins by the ginger and black pepper extracts, highlighting a plausible route of action leading to increased isoflavone bioavailability.
Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review
Authors: Ali Abdulalem , Abd Razak Shukor , Othman Siti Hajar , Eisa Taiseer Abdalla Elfadil , Al-Dhaqm Arafat , Nasser Maged , Elhassan Tusneem , Elshafie Hashim , Saif Abdu
Published: September 2022

Financial fraud, considered as deceptive tactics for gaining financial benefits, has recently become a widespread menace in companies and organizations. Conventional techniques such as manual verifications and inspections are imprecise, costly, and time consuming for identifying such fraudulent activities. With the advent of artificial intelligence, machine-learning-based approaches can be used intelligently to detect fraudulent transactions by analyzing a large number of financial data. Therefore, this paper attempts to present a systematic literature review (SLR) that systematically reviews and synthesizes the existing literature on machine learning (ML)-based fraud detection. Particularly, the review employed the Kitchenham approach, which uses well-defined protocols to extract and synthesize the relevant articles; it then report the obtained results. Based on the specified search strategies from popular electronic database libraries, several studies have been gathered. After inclusion/exclusion criteria, 93 articles were chosen, synthesized, and analyzed. The review summarizes popular ML techniques used for fraud detection, the most popular fraud type, and evaluation metrics. The reviewed articles showed that support vector machine (SVM) and artificial neural network (ANN) are popular ML algorithms used for fraud detection, and credit card fraud is the most popular fraud type addressed using ML techniques. The paper finally presents main issues, gaps, and limitations in financial fraud detection areas and suggests possible areas for future research.
Calculation of Nonlimit Active Earth Pressure against Rigid Retaining Wall Rotating about Base
Authors: Wang Zeyue , Liu Xinxi , Wang Weiwei
Published: September 2022

A retaining wall with sandy fill was considered as the research object in order to study the nonlimiting active earth pressure under the rotation about the base (RB mode). Rankine’s and Coulomb’s earth pressure theories are no longer applicable to the above conditions (RB mode and nonlimiting active earth pressure). In order to improve the traditional earth pressure calculation methods (Rankine and Coulomb), a calculation method using curvilinear thin layer elements is presented with overall considerations of wall displacement, soil arching effect, and friction angle exertion coefficient to deduce the nonlimit active earth pressure under RB. Additionally, the calculation results were in good agreement with model test data (from Fang and Smita). Moreover, a parametric analysis was carried out. It was revealed that the developed value of the shear strength decreased with the depth, and the active earth pressure distribution curve was linear and nonlinear in the upper and lower halves, respectively.
Research on a Fault Diagnosis Method of an A-Class Thermal Insulation Panel Production Line Based on Multi-Sensor Data Fusion
Authors: Wang Yong , Guo Xiaoqiang , Liu Xinhua , Liu Xiaowen
Published: September 2022

To detect the running state of an A-class thermal insulation board production line in real time, conveniently and accurately, a fault diagnosis method based on multi-sensor data fusion was proposed. The proposed algorithm integrates the ideas of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and Attention Mechanism, and combines a Dilated Convolution Module (DCM) with LSTM to recognize complex signals of multiple sensors. By introducing an attention mechanism, the recognition performance of the network was improved. Finally, the real-time status information of the production line was obtained by integrating attention weight. Experimental results show that for the custom multi-sensor dataset of A-class insulation board production line, the proposed CNN-LSTM fault diagnosis method achieved 98.97% accuracy. Compared with other popular algorithms, the performance of the proposed CNN-LSTM model performed excellently in each evaluation index is better.
Genetic Mechanism of Uranium Concentration in Ferruginous Sandstone of the Wajid Group in Southern Saudi Arabia
Authors: He Feng , Xing Zuochang , Li Xide , Zhang Zilong , Jia Cui
Published: September 2022

Uranium anomalies were discovered in ferruginous sandstone in the Khusayyayn Formation of the Wajid Group in southern Saudi Arabia. Based on field surveys, ground radiometric surveys, and chemical analysis, this paper summarizes the characteristics of the lithology and lithofacies of the ferruginous sandstone and analyzes the genetic mechanism of uranium concentration in ferruginous sandstone. Ferric iron basically exists in the form of Fe2O3 in ferruginous sandstone, with an average content of 28.95 wt.%. The formation period of the ferruginous sandstone occurred during the early synsedimentary and later diagenesis stages from the Carboniferous to the Devonian. The uranium anomaly is hosted in thin-bedded and lenticular ferruginous sandstone, with a uranium content ranging from 50 to 766 ppm. The average U-Ra equilibrium coefficient of ferruginous sandstone was 1.00, indicating that the uranium was weakly reformed after the uranium concentration. Ferric ions are closely related to uranium mineralization. The initial concentration of the uranium occurred during the deposition of the ferruginous sandstone. Most of the uranium was adsorbed by a ferric colloidal solution, and part of it was reduced by Fe2+, organic carbon, and sulfur in the uranium preconcentrated stage during the deposition of ferruginous sandstone. The uranium ore was superimposed, transformed, and concentrated due to the change in the pH environment in the early Neogene.
Design of the System for the Analysis of Disinfection in Automated Guided Vehicle Utilisation
Authors: Mozol Štefan , Krajčovič Martin , Dulina Ľuboslav , Mozolová Lucia , Oravec Matúš
Published: September 2022

The article’s main goal is to describe the system design for the analysis of disinfection automated guided vehicle (AGV) utilisation so that the AGV’s optimal number can be determined. The simulation was used as the system’s main tool, allowing a relatively objective approach to imitate real system behaviour. With the proposed system, it is possible to determine the utilisation of AGVs and the number of necessary AGVs that carry out disinfection of the premises through the superstructure platforms. In the simulation model, two main modes of disinfection of ground AGV were tested. A regular circuit is carried out at specific intervals as well as a dynamic evaluation of the area and its possible contamination. When the area reaches a certain threshold, the instruction to disinfect the area is triggered. Experiments were carried out for a different number of AGVs, with the possible restriction of entry in the presence of the patient, and for a combination of specialised AGVs. Based on the results, we can conclude that the use of only surface-disinfecting AGVs is limited by the movement of patients and does not bring the same results as the use of a combination of surface- and air-disinfecting specialised AGVs.
Complementary in Time and Space: Optimization on Cost and Performance with Multiple Resources Usage by Server Consolidation in Cloud Data Center
Authors: Li Huixi , Shen Yongluo , Xi Huidan , Xiao Yinhao
Published: September 2022

The recent COVID-19 pandemic has accelerated the use of cloud computing. The surge in the number of users presents cloud service providers with severe challenges in managing computing resources. Guaranteeing the QoS of multiple users while reducing the operating cost of the cloud data center (CDC) is a major problem that needs to be solved urgently. To solve this problem, this paper establishes a cost model based on multiple computing resources in CDC, which comprehensively considers the hosts’ energy cost, virtual machine (VM) migration cost, and SLAV penalty cost. To minimize this cost, we design the following solution. We employ a convolutional autoencoder-based filter to preprocess the VM historical workload and use an attention-based RNN method to predict the computing resource usage of the VMs in future periods. Based on the predicted results, we trigger VM migration before the host enters an overloaded state to reduce the occurrence of SLAV. A heuristic algorithm based on the complementary use of multiple resources in space and time is proposed to solve the placement problem. Simulations driven by the VM real workload dataset validate the effectiveness of our proposed method. Compared with the existing methods, our proposed method reduces the energy consumption of the hosts and SLAV and reduces the total cost by 26.1~39.3%.
Root Cause Failure Analysis of Deep-Groove Ball Bearing Used in a Governor
Authors: Hou Xueqin , Liu Yujian , Li Tianyu , Liu Changkui , Zhang Zheng , Tao Chunhu
Published: September 2022

Premature failure of a deep-groove ball bearing used in an aeroengine governor took place during service. In this paper, the failure mode and root cause of the bearing were studied by macroscopic and microscopic examination, metallographic analysis, hardness test, calculations of contact stress and L10 life, flatness measurement and comparative experiment. The results show that the failure modes of the inner ring raceway and steel balls are contact fatigue spalling, the failure modes of the outer ring raceway are wear and contact fatigue spalling, and the failure mode of the cage is fatigue fracture. The root cause and direct cause of the bearing failure were the unqualified machining process of the spring end face and the high unbalanced axial load, respectively. The unqualified machining process induced high points of the spring end face, which caused misalignment of the outer ring and inner ring and thereby resulted in the high unbalanced axial load. The characteristic damages induced by high axial load were climbing with the morphology of metal extrusion and accumulation at the border of the raceway for the inner and outer ring, and multiple fatigue fractures with the characteristic of multi origins for the cage. The unqualified machining process can be prevented by adopting the refined grinding process and adding detection requirements of flatness.
Improved Calculation Method for Siphon Drainage with Extended Horizontal Sections
Authors: Zhang Yingqiu , Shang Yuequan , Sun Hongyue
Published: September 2022

Slope siphon drainage is a convenient and efficient above-ground drainage method that is free of manual power and can effectively maintain the stability of potential landslides and prevent the loss of life and property. The complex engineering topography inevitably requires the use of siphon drains with a total length of more than 150 m and a horizontal section length of more than 80 m, which significantly increases the difficulty of calculating the drainage capacity and thus affects the actual utilization of the project. The traditional siphon flow rate equation does not apply to long-pipe siphon conditions, especially when the lift is close to the limit, and there are significant errors in the calculation results, for which we propose a new calculation method. The proposed method considers both air release and flow-pattern classification. Thirty-six sets of experiments were conducted to validate our proposed calculation method. The results showed that our method not only calculated the siphon flow velocity well but also predicted the main flow pattern in the siphon in the experiment well. Furthermore, the equation for calculating the siphon flow velocity was extended to the siphon operation mode with long horizontal sections.
Effect of Wind Direction and Velocity on PV Panels Cooling with Perforated Heat Sinks
Authors: Hudișteanu Sebastian Valeriu , Țurcanu Florin Emilian , Cherecheș Nelu-Cristian , Popovici Cătălin-George , Verdeș Marina , Ancaș Diana-Ana , Hudișteanu Iuliana
Published: September 2022

The numerical modeling of the effect of wind direction and velocity over the air cooling of PV panels with heat sinks is realized. During the study, a random PV panel with typical characteristics was analyzed for three different wind directions—towards its back, towards its front and from the side. The analysis was realized on a fixed PV panel, oriented to the south, with an inclination of 45 degrees from the horizontal position. The accuracy of the numerical simulation was achieved by comparison with the experimental studies presented in the literature and by comparing the NOCT conditions. The numerical study is focused on different types of heat sinks attached to a typical PV panel. The fins were distributed both horizontally and vertically. A challenging task consisted in simulation of the real wind conditions around the PV panel by taking into account the entire air domain. The simulations were realized for air velocity vair from 1 m/s to 5 m/s, solar radiation of G = 1000 W/m2 and ambient temperature tair = 35 °C. The output parameters analyzed were the average temperature of PV panels and their power production. Although the lowest temperatures were achieved for the back wind, the cooling effect was more intense for the side wind. The other direction studied also determined the cooling of PV panels. The passive cooling solutions analyzed introduced a rise of maximum power production between 1.85% and 7.71% above the base case, depending on the wind direction and velocity.
Potential of Computer-Aided Engineering in the Design of Ground-Improvement Technologies
Authors: Shakya Sudip , Inazumi Shinya , Nontananandh Supakij
Published: September 2022

The progress status of jet-grouting construction during the construction phase is difficult to verify and even after the completion of construction, it can be verified only by empirical methods. This study attempted to recreate a realistic simulation result of the middle-pressure jet-grouting method by establishing a computer-aided engineering (CAE) system from the planning/design stage of the ground model and verifying the validity of the construction process after the model was analyzed by the moving particle semi-implicit (MPS) method. The governing parameters for the ground were determined by the MPS simulation of the unconfined compression test. The construction simulation was analyzed and the results were validated by visual confirmation of the related phenomena, such as the soil-improved body formation and mud discharge. To verify the accuracy of the mud discharge phenomenon, three different probe regions were set above the model ground and the amount of mud discharge generated in each region was computed before drawing an overall conclusion of the study. A soil-improvement body of approximately 0.38 m3 was observed to have formed at the end of the study and the highest mud discharge particle number measured, for instance, was 896. This study is expected to serve as a guideline for further studies on simulation-based research.
MreNet: A Vision Transformer Network for Estimating Room Layouts from a Single RGB Panorama
Authors: Xu Bing , Sun Yaohui , Meng Xiangxu , Liu Zhihan , Li Wei
Published: September 2022

The major problem with 3D room layout reconstruction is estimating the 3D room layout from a single panoramic image. In practice, the boundaries between indoor objects are difficult to define, for example, the boundary position of a sofa and a table, and the boundary position of a picture frame and a wall. We propose MreNet, a novel neural network architecture for predicting 3D room layout, which outperforms previous state-of-the-art approaches. It can efficiently model the overall layout of indoor rooms through a global receptive field and sparse attention mechanism, while prior works tended to use CNNs to gradually increase the receptive field. Furthermore, the proposed feature connection mechanism can solve the problem of the gradient disappearing in the process of training, and feature maps of different granularity can be obtained in different layers. Experiments on both cuboid-shaped and general Manhattan layouts show that the proposed work outperforms recent algorithms in prediction accuracy.
MCA-YOLOV5-Light: A Faster, Stronger and Lighter Algorithm for Helmet-Wearing Detection
Authors: Sun Cheng , Zhang Shiwen , Qu Peiqi , Wu Xingjin , Feng Peng , Tao Zhanya , Zhang Jin , Wang Ying
Published: September 2022

It is an essential measure for workers to wear safety helmets when entering the construction site to prevent head injuries caused by object collision and falling. This paper proposes a lightweight algorithm for helmet-wearing detection based on YOLOV5, which is faster and more robust for helmet detection in natural construction scenarios. In this paper, the MCA attention mechanism is embedded in the backbone network to help the network extract more productive information, reduce the missed detection rate of small helmet objects and improve detection accuracy. In order to ensure the safety of workers in construction, it is necessary to detect whether the construction workers are wearing safety helmets in real-time to achieve monitoring on-site. A channel pruning strategy is proposed on the MCA-YOLOv5 algorithm to compress it, realizing the optimal large-scale model into ultrasmall models for real-time detection on embedded or mobile devices. The experimental results on the public data set show that the model parameter volume is reduced by 87.2%, and the detection speed is increased by 53.5%, even though the MCA-YOLOv5-light reduces the mAP slightly.
Data Processing Method of Mine Wind Speed Monitoring Based on an Improved Fuzzy C-Means Clustering Algorithm
Authors: Zhang Wei , Li Yucheng , Li Junqiao
Published: September 2022

Analyzing and processing mine wind speed monitoring data is the key to realizing intelligent ventilation and real-time calculation of the ventilation network. According to the characteristics of the artificial regulation of a mine ventilation system, a local regression fuzzy C clustering algorithm is proposed in this paper, which combines local outlier processing with global air volume state analysis. Firstly, the algorithm uses the robust local weighted regression principle to analyze and preprocess the data locally, determines the risk degree of the abnormal data according to the identified times of outliers, determines the clustering number according to the clustering validity function, and analyzes the global air volume fluctuation according to the clustering results. The results show that most outliers are identified in data preprocessing. Still, the processing of dense outliers is weak, related to the window width setting and weighting multiple. The number of clusters can represent the fluctuation of the ventilation state and the pre-processed cluster centers are 4.4% lower than the original data because most of the outliers are higher than the average data. According to the law of air volume balance, the clustering results can pave the way for the global deduction of mine wind speed. There is an implicit relationship between data preprocessing and the clustering process, and when intensive outliers are not eliminated, they may be identified as separate clusters. The research of this paper points out the direction of mine wind speed data analysis, which can provide a theoretical basis for intelligent mine ventilation and real-time calculation of the ventilation network.
A Novel Radial Artery P-S Curve Model Based on Radial Vibration of Vascular Wall
Authors: Wang Guotai , Geng Xingguang , Kang Xiaoxiao , Zhang Yitao , Zhang Jun , Zhang Haiying
Published: September 2022

In pulse wave analysis, the changing curve of pulse wave strength with continuous increasing pressure, that is, the P-S (pressure-strength) curve, contains abundant human physiological information, but there is no accurate model to describe the formation mechanism of the curve. Therefore, this paper proposes a modeling method of the radial artery P-S curve based on the radial vibration of the vascular wall. The modeling method includes three parts. Firstly, based on hemodynamics, we proposed the blood motion equation in the pulsation process of healthy people. Secondly, the motion equation of the vascular wall based on the fluid–structure interaction between blood motion and vascular wall was established. Finally, according to the elastic theory of the vascular wall, the relationship between pulse strength and extravascular pressure of blood vessels was found. To verify the accuracy and applicability of the model, this paper simulated the changes in the vascular wall stress and the intravascular pressure with the extravascular pressure during the process of vascular deformation. In addition, 69 healthy volunteers were selected to participate in this study. Based on the gradient compression, the pulse strength envelope under the continuous pressure sequence of the radial artery, namely the pulse P-S curve, was extracted. We also analyzed the relationship between the individual P-S curve difference and BMI. The results show that the actual human body data collection and analysis results are consistent with the theoretical model established in this paper, which indicates that the model can provide a novel idea for the evaluation of the state of the human body.
A Hybrid Golden Jackal Optimization and Golden Sine Algorithm with Dynamic Lens-Imaging Learning for Global Optimization Problems
Authors: Yuan Panliang , Zhang Taihua , Yao Liguo , Lu Yao , Zhuang Weibin
Published: September 2022

Golden jackal optimization (GJO) is an effective metaheuristic algorithm that imitates the cooperative hunting behavior of the golden jackal. However, since the update of the prey’s position often depends on the male golden jackal and there is insufficient diversity of golden jackals in some cases, it is prone to falling into a local optimal optimum. In order to address these drawbacks of GJO, this paper proposes an improved algorithm, called a hybrid GJO and golden sine (S) algorithm (Gold-SA) with dynamic lens-imaging (L) learning (LSGJO). First, this paper proposes novel dual golden spiral update rules inspired by Gold-SA. These rules give GJO the ability to think like a human (Gold-SA), making the golden jackal more intelligent in the process of preying, and improving the ability and efficiency of optimization. Second, a novel nonlinear dynamic decreasing scaling factor is introduced into the lens-imaging learning operator to maintain the population diversity. The performance of LSGJO is verified through 23 classical benchmark functions and 3 complex design problems in real scenarios. The experimental results show that LSGJO converges faster and more accurately than 11 state-of-the-art optimization algorithms, the global and local search ability has improved significantly, and the proposed algorithm has shown superior performance in solving constrained problems.
The Effect of Confined Granular Soil on Embedded PZT Patches Using FFT and Digital Static Cone Penetrometer (DSCP)
Authors: Kumari Nisha , Trivedi Ashutosh
Published: September 2022

This paper presents the effect of confined granular fill on the efficiency of embedded PZT (Lead Zirconate Titanate) patches. The experiments are carried out to capture the dynamic response of confined granular fill and voltage output. The dynamic response of the system is analysed using the fast Fourier transformation (FFT) of vibration and digital static cone penetrometer (DSCP) test at various excitation frequencies. The peak pick method is used to determine the damping loss factor and natural frequency. The efficiency of voltage generation of embedded PZT patches is influenced by the depth of embedment, excitation frequency, location, and engineering properties of the confined granular fill. The results show that the influence of vibration frequency and placement of PZT on the output voltage should be considered. The thickness and engineering properties of granular soil affect the efficiency of voltage output. This study emphasizes the utility of PZT patches in the subgrade and structural health monitoring of various geotechnical structures.
Pedestrians’ Microscopic Walking Dynamics in Single-File Movement: The Influence of Gender
Authors: Dias Charitha , Abdullah Muhammad , Ahmed Dawood , Subaih Rudina
Published: September 2022

Demographics of individuals could largely influence their behaviors and interactions with surrounding pedestrians. This study investigates the influence of pedestrians’ gender on microscopic walking dynamics of single-file movements using the trajectory data collected from a controlled experiment conducted under different density levels. Instantaneous acceleration (with a time lag that varied from 0.12 s to 0.68 s) versus relative speed between the subject pedestrian and the pedestrian in front of him/her plots displayed significant correlations, which is analogous to the car following behavior, indicating that the relative speed is a key determinant of pedestrians’ acceleration behavior. Time-delayed instantaneous accelerations and decelerations of pedestrians were modeled as functions of relative speed and spacing that are used in microscopic behavior models and gender using multiple linear regression. The outcomes revealed that in addition to relative speed, gender has a significant influence on instantaneous acceleration and deceleration for all density levels. Spacing displayed significant influence on acceleration and deceleration only for several density levels, and that influence was not as strong as relative speed. Males were likely to accelerate more and decelerate more compared to females for all density levels. The findings of this study provide important insights into gender dependence on microscopic walking dynamics. Furthermore, the results emphasize the importance of considering gender influence in microscopic behavior models.
Quantitative Comparison of Tree Ensemble Learning Methods for Perfume Identification Using a Portable Electronic Nose
Authors: Cao Mengli , Ling Xingwei
Published: September 2022

Perfume identification (PI) based on an electronic nose (EN) can be used for exposing counterfeit perfumes more time-efficiently and cost-effectively than using gas chromatography and mass spectrometry instruments. During the past five years, decision-tree-based ensemble learning methods, also called tree ensemble learning methods, have demonstrated excellent performance when solving multi-class classification problems. However, the performance of tree ensemble learning methods for the EN-based PI problem remains uncertain. In this paper, four well-known tree ensemble learning classification methods, random forest (RF), stagewise additive modeling using a multi-class exponential loss function (SAMME), gradient-boosting decision tree (GBDT), and extreme gradient boosting (XGBoost), were implemented for PI using our self-designed EN. For fair comparison, all the tested classification methods used as input the same feature data extracted using principal component analysis. Moreover, two benchmark methods, neural network and support vector machine, were also tested with the same experimental setup. The quantitative results of experiments undertaken demonstrated that the mean PI accuracy achieved by XGBoost was up to 97.5%, and that XGBoost outperformed other tested methods in terms of accuracy mean and variance based on our self-designed EN.
Cobrançosa Table Olives: Characterization of Processing Method and Lactic Acid Bacteria Profile throughout Spontaneous Fermentation
Authors: Reis Patrícia J. M. , Tavares Tânia G. , Rocha Joana M. , Malcata Francisco Xavier , Macedo Angela C.
Published: September 2022

Our major goal was the physicochemical, biochemical and microbiological characterization of Cobrançosa table olives, as support for the eventual granting of a PDO status. Seven producers were accordingly sampled throughout eleven months. Brines were analyzed for pH, salinity, acidity, and organic and phenolic compounds. Yeasts and Latic Acid Bacteria (LAB) were enumerated, and the dominant strains duly identified. Despite process variabilities, two stages appear to be shared by all manufacturers: sweetening—the renewal of water to remove bitter compounds; and salting—gradual addition of salt to brine for preservation. Yeasts dominated during sweetening, but LAB tended to be similar in viable counts (7 log CFU/mL) by the end of salting. Lactiplantibacillus (Lpb.) pentosus, Lpb. paraplantarum, Pediococcus parvulus, and Oenococcus kitaharae were the most abundant LAB found, together with an average pH of 4.1 and 6–9% for salt content. All organic acids exhibited an inverted parabolic evolution, with maxima of 3450 mg/L for lactic and 4000 mg/L for succinic by 3 months, and 2750 mg/L for acetic and 2950 mg/L for citric by 4 months. Oleuropein levels were affected by the frequency of brine renewal but decreased from 1350 to 700 mg/L, with hydroxityrosol and tyrosol increasing from 10 to 2000 mg/L and 2 to 550 mg/L, respectively, within 11 months.