bluuebunny/crossref_metadata_2025 huggingface dataset:
Hernia mesh infection treatment following the repair of abdominal wall hernias: A single-center experience
Authors: He Linxiang , Wang Xuehu , Fan Gaoxiang , Zhao Yu
Published: October 2022

Introduction

The mesh-based repair of abdominal wall hernias is a commonly employed approach as it is easy to implement and associated with low rates of hernia recurrence. However, the occurrence of hernia mesh infections following such repair can be extremely serious, and no clinical consensus regarding the optimal treatment of such infections has been established. This study was thus developed to review the management of hernia mesh infection cases treated at our center, summarizing the demographic and clinical characteristics of affected patients and summarizing our associated therapeutic experiences.

Methods

Data pertaining to 64 cases of hernia mesh infections treated at our center were retrospectively reviewed. Data were obtained from patient medical records, including general situation, hernia type, prior hernia repair approaches, type of mesh, and postoperative condition. Other reviewed outcomes include bacteriological and imaging findings, as well as treatment outcomes. In cases where conservative management was not successful, the approach to mesh removal (laparoscopic vs. open) was made based on the primary surgical approach and the type of material used for the repair.

Results

In total, 42 patients underwent primary open inguinal hernioplasty (including plug repair, preperitoneal mesh repair, and Lichtenstein repair), while 11 patients underwent laparoscopic repair (9 transabdominal preperitoneal, TAPP and 2 totally extraperitoneal,TEP), and 11 patients with incisional hernias underwent the intraperitoneal onlay mesh (IPOM) procedure. Six patients exhibited mesh erosion of the internal organs. Of these patients, 38 underwent mesh removal via open debridement, while 9 underwent laparoscopic exploration and open debridement, and 1 underwent laparoscopic mesh removal. No patients exhibited serious postoperative sequelae, serious complications, or mortality after the treatment of mesh infections.One patient experienced postoperative infection recurrence following partial mesh removal, with the appearance of a small fistula. Hernias recurred in 2 patients following mesh removal, and 1 patient underwent repair via laparoscopic IPOM.

Conclusions

While conservative treatment can cure early mesh infections, there is nonetheless a risk that these infections will recur. In view of the variety of surgical intervention of abdominal wall hernias at present,treatment of mesh infection should be individualized. Our findings suggest that hernias repaired via the placement of mesh in the preperitoneal space can more readily contribute to internal organ erosion and late-onset infections, with open debridement often being unable to completely remove the mesh without causing collateral damage. Laparoscopic exploration is an effective and minimally invasive approach to detecting internal organ involvement and removing the infected hernia mesh from affected patients.
Interpretive review: Semiochemicals in domestic pigs and dogs
Authors: McGlone John J. , Archer Courtney , Henderson Madelyn
Published: October 2022

This interpretive review includes discussion of the available scientific literature with interpretations by the authors. The broad field of semiochemicals can be confusing to scientists and consumers. This review attempts to summarize the known scientific studies for pig and dog semiochemicals while at the same time attempting to refine our use of terminology. The specific objectives of this interpretive review are to summarize and interpret much of the key scientific literature (but not the lay literature) on semiochemicals in pigs and dogs to include (1) definitions of semiochemicals and related molecules including pheromones, (2) to briefly summarize olfactory organs, and (3) and to examine the scientific literature for semiochemical mechanisms and applications in dogs and pigs (two domesticated species with known olfactory acuity). Dogs and pigs have olfactory features that are similar in that they both lack certain olfactory organs (Grueneberg ganglion and Septal Organ) and they have a small vomeronasal organ (VNO) without some major receptors that are found in other species. The primary olfactory organs for both pigs and dogs are the main olfactory epithelium and perhaps the trigeminal nerve. Several examples of pheromones activating the brain via the MOE or Trigeminal nerve rather than the VNO challenge the concept that the VNO is the site of pheromone sensing. We believe it is not appropriate to label something a pheromone when evidence is not available to show that it is a pheromone. We offer definitions for the terms semiochemicals, pheromones, interomones and others and then determine if the evidence is sufficient to call certain semiochemicals a pheromone. Here we review mixed, largely negative, scientific reports of the efficacy of some products labeled as “pheromones” that are more appropriately called semiochemicals. Interomones can have a more powerful effect on dog behavior and physiology than semiochemicals marketed as pheromones. Because marketing of semiochemicals is far ahead of the science, bringing some logic and uniformity to the field will benefit animals and hopefully cause less consumer confusion. Semiochemicals have the potential to offer powerful solutions to behavioral problems using more naturally occurring molecules.
Study on the Hydraulic and Energy Loss Characteristics of the Agricultural Pumping Station Caused by Hydraulic Structures
Authors: Jiao Weixuan , Li Zhishuang , Cheng Li , Wang Yuqi , Zhang Bowen
Published: October 2022

The pumping station is an important part of the agricultural irrigation and drainage system. The sump is one of the common water inlet types of agricultural pumping stations. In the sump, to facilitate the installation and maintenance of equipment, some hydraulic structures, such as pump beams, maintenance platforms and chest walls, are added to the sump. At present, the impact of hydraulic structures in the sump on the hydraulic performance of the pump device is not clear, so this paper focused on the impact of hydraulic structures on the hydraulic characteristics and entropy generation characteristics of the pump device by using numerical simulation methods. The results showed that the installation of hydraulic structures in the sump has the greatest impact on the efficiency of the pump device. The efficiency coefficient increased after adding a pump beam in the sump and decreased by about 2% after adding a maintenance platform and a water retaining chest wall. Results also showed that the installation of hydraulic structures in the sump will lead to uneven distribution of entropy generation in the sump, especially in the vicinity of the hydraulic structures. The installation of the maintenance platform and chest wall will lead to the increase of the total entropy generation in the sump, which also means that the hydraulic loss in the sump will increase accordingly. Hence, in addition to the pump beam, other structures should be avoided in the sump.
Effect of Chestnut Tannins and Vitamin E Supplementation to Linseed Oil-Enriched Diets on Growth Performance, Meat Quality, and Intestinal Morphology of Broiler Chickens
Authors: Perić Lidija , Žikić Dragan , Stojčić Mirjana Đukić , Tomović Vladimir , Leskovec Jakob , Levart Alenka , Salobir Janez , Kanački Zdenko , Rezar Vida
Published: October 2022

The objective of this study was to establish the effects of chestnut tannin extract or vitamin E added to linseed oil-enriched diets on growth performance, meat quality, and intestinal morphology of broiler chickens. A total of 240 day-old Ross 308 male broiler chicks were included in trial. 5% of cold-pressed linseed oil was included in finisher diets (21–40 days), and three feeding treatments with four replicates were formed: finisher without additives; finisher + 200 IU vitamin E/kg; finisher + 500 mg/kg of chestnut wood tannin extract. No significant influence of treatments was established on body weight or feed conversion ratio. A negative effect on feed intake (p < 0.05) was found in the vitamin E group. The addition of vitamin E increased the dressing percentage (p < 0.05) and increased the breast meat yield (p < 0.01) compared to the control group. No significant effects were found on the water holding capacity or pH of breast meat. The highest level of AST (p < 0.01) and ALT (p < 0.05) was recorded in vitamin E group. The addition of chestnut tannin extract in feed increased villus height, villus height: crypt depth ratio, and villus area compared to the other two groups (p < 0.05). It can be concluded that vitamin E supplementation improves carcass percentage and breast meat yield, while chestnut tannins improve the intestinal morphology of broiler chickens when added to oil-enriched diets.
Application of Bioelectrical Impedance Analysis (BIA) to Assess Carcass Composition and Nutrient Retention in Rabbits from 25 to 77 Days of Age
Authors: Saiz del Barrio Alejandro , García-Ruiz Ana Isabel , Fuentes-Pila Joaquín , Nicodemus Nuria
Published: October 2022

The aim of this study was to assess and validate, using independent data, the prediction equations obtained to estimate in vivo carcass composition using bioelectrical impedance analysis (BIA) to determine the nutrient retention and overall energy and nitrogen retention efficiencies of growing rabbits. Seventy-five rabbits grouped into five different ages (25, 35, 49, 63 and 77 days) were used in the study. A four-terminal body-composition analyzer was applied to obtain resistance (Rs, Ω) and reactance (Xc, Ω) values. All the animals were stunned and bled at each selected age, and the chilled carcasses were analyzed to determine water, fat, crude protein (CP), ash and gross energy (GE). Multiple linear regression analysis was conducted to determine the equations, using body weight, length and impedance data as independent variables. The coefficients of determination (R2) to estimate the content of water, protein, fat and ash in grams, and energy in Mega Jules(MJ), were: 0.99, 0.99, 0.95, 0.96 and 0.98, respectively, and the relative mean prediction errors (RMPE) were: 4.20, 5.48, 21.9, 9.10 and 6.77%, respectively. Carcass yield (%) estimation had values of 0.50 and 10.0 for R2 and RMPE, respectively. When water content was expressed as a percentage, the R2 and RMPE were 0.79 and 1.62%, respectively. When the protein, fat and ash were expressed as a percentage of dry matter (%DM) and the energy content as kJ/100 g DM, the R2 values were 0.68, 0.76, 0.66 and 0.82, respectively, and the RMPEs were 3.22, 10.5, 5.82 and 2.54%, respectively. Energy Retention Efficiency was 20.4 ± 7.29%, 21.0 ± 4.18% and 20.8 ± 2.79% from 35 to 49, from 49 to 63 and from 35 to 63 d, respectively. Nitrogen Retention Efficiency was 46.9 ± 11.7%, 34.5 ± 7.32% and 39.1 ± 3.23% for the same periods. Energy was retained in body tissues for growth with an efficiency of approximately 52.5%, and the energy efficiency for protein and fat retention was 33.3 and 69.9%, respectively. This work shows that BIA is a non-invasive and good method to estimate in vivo carcass composition and to determine the nutrient retention of growing rabbits from 25 to 77 days of age.
Untargeted Metabolomics Used to Describe the Chemical Composition, Antioxidant and Antimicrobial Effects of Extracts from Pleurotus spp. Mycelium Grown in Different Culture Media
Authors: Flores Giancarlo Angeles , Girometta Carolina Elena , Cusumano Gaia , Angelini Paola , Tirillini Bruno , Ianni Federica , Blasi Francesca , Cossignani Lina , Pellegrino Roberto Maria , Emiliani Carla , Venanzoni Roberto , Venturella Giuseppe , Colasuonno Pasqualina , Cirlincione Fortunato , Gargano Maria Letizia , Zengin Gokhan , Acquaviva Alessandra , Di Simone Simonetta Cristina , Orlando Giustino , Menghini Luigi , Ferrante Claudio
Published: October 2022

Pleurotus species isolated in vitro were studied to determine the effect of different media on their production of secondary metabolites, antimicrobial, and antioxidant activity. The different metabolites among Pleurotus samples covered a total of 58 pathways. Comparisons were made between the metabolic profiles of Pleurotus spp. mycelia grown in two substrates: Potato-dextrose-agar-PDA, used as control (S1), and PDA enriched with 0.5 % of wheat straw (S2). The main finding was that the metabolic pathways are strongly influenced by the chemical composition of the growth substrate. The antibacterial effects were particularly evident against Escherichia coli, whereas Arthroderma curreyi (CCF 5207) and Trichophyton rubrum (CCF 4933) were the dermatophytes more sensitive to the mushroom extracts. The present study supports more in-depth investigations, aimed at evaluating the influence of growth substrate on Pleurotus spp. antimicrobial and antioxidant properties.
Identification and Characterization of Genes Related to Ampicillin Antibiotic Resistance in Zymomonas mobilis
Authors: Geng Binan , Huang Xingyu , Wu Yalun , He Qiaoning , Yang Shihui
Published: October 2022

Antibiotics can inhibit or kill microorganisms, while microorganisms have evolved antibiotic resistance strategies to survive antibiotics. Zymomonas mobilis is an ideal industrial microbial chassis and can tolerate multiple antibiotics. However, the mechanisms of antibiotic resistance and genes associated with antibiotic resistance have not been fully analyzed and characterized. In this study, we investigated genes associated with antibiotic resistance using bioinformatic approaches and examined genes associated with ampicillin resistance using CRISPR/Cas12a−based genome−editing technology. Six ampicillin−resistant genes (ZMO0103, ZMO0893, ZMO1094, ZMO1650, ZMO1866, and ZMO1967) were identified, and five mutant strains ZM4∆0103, ZM4∆0893, ZM4∆1094, ZM4∆1650, and ZM4∆1866 were constructed. Additionally, a four−gene mutant ZM4∆ARs was constructed by knocking out ZMO0103, ZMO0893, ZMO1094, and ZMO1650 continuously. Cell growth, morphology, and transformation efficiency of mutant strains were examined. Our results show that the cell growth of ZM4∆0103 and ZM4∆ARs was significantly inhibited with 150 μg/mL ampicillin, and cells changed to a long filament shape from a short rod shape. Moreover, the transformation efficiencies of ZM4∆0103 and ZM4∆ARs were decreased. Our results indicate that ZMO0103 is the key to ampicillin resistance in Z. mobilis, and other ampicillin−resistant genes may have a synergetic effect with it. In summary, this study identified and characterized genes related to ampicillin resistance in Z. mobilis and laid a foundation for further study of other antibiotic resistance mechanisms.
The Enzymatic Antioxidants Activities Changes in Water Plants Tissues Exposed to Chlorpyrifos Stress
Authors: Sobiecka Elżbieta , Mroczkowska Milena , Olejnik Tomasz P.
Published: October 2022

Water pollution is an immense environmental problem, and plant protection products are part of it. The organophosphorus insecticides, chlorpyrifos as an example, were used for years, and their high concentration could negatively influence ecosystems. Some of the plants, such as macrophytes, were exposed to a variety of stress factors. To live on, the macrophytes developed an efficient antioxidative system consisting of enzymatic and non-enzymatic antioxidants. The remediation process of polluted water ecosystems caused by plant protection products in our climate zone can be intensified if it is provided by autochthonic macrophytes. The results of our studies are part of the research that allows optimizing the phytoremediation process without irreversible effect on investigated species. The influence of various concentrations of chlorpyrifos on the enzymatic system in Canadian waterweed (Elodea canadensis Michx.), needle spikerush (Eleocharis acicularis L.), and water mint (Mentha aquatica L.) were studied. The differences in values of guaiacol peroxidase (GPX) and glutathione S-transferase (GST) activities were determined in leaves and roots. Research indicated an increase in both enzyme activities in plants exposed to toxic compounds. The highest concentration of chlorpyrifos affected the highest activities of enzymes. The water mint roots responded with the highest value of glutathione S-transferase activity during cultivation in polluted environment. It was therefore concluded that an aqueous plant exposed to the toxic insecticide created a defensive mechanism by enzymatic antioxidant systems that correlated to the pollutant concentration and plant species.
Numerical Prediction of Internal Flows in He/LOx Seals for Liquid Rocket Engine Cryogenic Turbopumps
Authors: Maritano Lorenzo , Marin Francesco Maria , Bertani Cristina , Pastrone Dario , Angelucci Maddalena , Caggiano Giuseppe
Published: October 2022

Cryogenic turbopumps are used in high-performance, lightweight liquid rocket engines for space applications. The development of bearings and shaft seals for cryogenic turbopumps requires detailed characterization of the internal flow, taking into account the effects of boiling and multi-component two-phase flow. Here, a flow network solver was developed to analyse the secondary flow circuit of a cryogenic turbopump where the propellant is mixed with high-temperature helium after bearing cooling. The network solver is based on an extension of a classic 1D homogeneous model, originally developed for a pure substance, to the case of two-phase multi-component flow. The solver is capable of predicting pressures, temperatures, flow rates, and species concentrations in a complex two-phase flow in the presence of non-condensable gases. The unsteady mass, momentum, and energy conservation equations are implemented in conjunction with the thermodynamic equations of state using a general-purpose finite volume formulation, where the pressure drop and the heat transfer are calculated using correlations. The numerical tool was validated by comparing its predictions with experimental data obtained during tests on the secondary circuit of an oxygen turbopump developed at Avio S.p.A. A number of engine operating conditions were considered (inlet helium temperature in the range of 250–280 K, helium/liquid oxygen drain in the range of 165–230 K). The predicted temperature values showed good agreement with the experimental data in most conditions.
Reflectance Transformation Imaging Visual Saliency: Local and Global Approaches for Visual Inspection of Engineered Surfaces
Authors: Nurit Marvin , Le Goïc Gaëtan , Maniglier Stéphane , Jochum Pierre , Mansouri Alamin
Published: October 2022

Reflectance Transformation Imaging (RTI) is a non-contact technique which consists in acquiring a set of multi-light images by varying the direction of the illumination source on a scene or a surface. This technique provides access to a wide variety of local surface attributes which describe the angular reflectance of surfaces as well as their local microgeometry (stereo photometric approach). In the context of the inspection of the visual quality of surfaces, an essential issue is to be able to estimate the local visual saliency of the inspected surfaces from the often-voluminous acquired RTI data in order to quantitatively evaluate the local appearance properties of a surface. In this work, a multi-scale and multi-level methodology is proposed and the approach is extended to allow for the global comparison of different surface roughnesses in terms of their visual properties. The methodology is applied on different industrial surfaces, and the results show that the visual saliency maps thus obtained allow an objective quantitative evaluation of the local and global visual properties on the inspected surfaces.
The Effects of Functional Ankle Taping on Postural Stability in Elite Judo Players
Authors: Kwon Moonseok , Lee Seongyeol , Lee Jaewoo , Lee Ayoon , Lee Hyokeun
Published: October 2022

The purpose of this study was to investigate the effect of ankle taping intervention on postural stability in elite Judo players. A total of twenty-two elite Judo players participated in this study. For biomechanical evaluation of postural stability, all participants performed postural standing tasks including narrow, normal, and wide stance conditions with both taping and non-taping conditions, respectively. Ground reaction forces and the center of pressure (COP) were obtained from the force plate. COP data for 30-s duration were analyzed to assess postural stability by measuring 95% confidence ellipse sway area (COPSWAY), COP velocity (COPVEL), and approximate entropy (ApEn). Significant differences were found in COPSWAY (p = 0.025) and COPVEL (p = 0.041) in the narrow stance, but no differences in normal and wide stances were observed between taping and non-taping conditions. For ApEn in the anteroposterior (AP) direction, significant differences were identified in normal (p = 0.026) and wide (p = 0.014) stances, but in the mediolateral direction there were no significant differences in all stances between taping and non-taping conditions. This study suggests that ankle taping that is purported to increase ankle stability may ironically negatively affect posture maintenance in Judo players. Our study suggests that the purpose of ankle taping should be reconsidered and associated individual objective data should be first analyzed before tape application.
Sound Localization Framework for Construction Site Monitoring
Authors: Kim In-Chie , Kim Yi-Je , Chin Sang-Yoon
Published: October 2022

This study developed a construction sound localization framework (CSLF) using the time delay of the arrival technique and the generalized cross-correlation phase transform. Based on the spatial characteristics of construction sites, this study identified sound-source locations at construction sites to overcome the limitations of existing sensor-based localization methods. Verification tests were performed on the CSLF in both interior and exterior environments. The interior tests showed that the average error was less than 0.5 m for each axis; which is 0.26, 0.27, and 0.36 m for the x-, y-, and z-axes, respectively. The exterior tests conducted at an actual construction site showed average x-, y-, and z-axis errors of 0.19, 0.21, and 0.24 m, respectively. These results show that the CSLF can effectively identify sound locations at construction sites within an arm’s length. Furthermore, CSLF is applicable on the sound data categorization-related research. The system can categorize an accidental or abnormal sound and locate the sound source for safety management at the construction site. It can also be utilized to monitor construction productivity by categorizing and locating the machinery-related sound sources.
Recent Advances in Applied Microbiology and Food Sciences
Authors: Kieliszek Marek , Kowalczewski Przemysław Łukasz
Published: October 2022

Changes are taking place on many fronts, including socio-demographic changes, economic changes, and technological progress [...]
Digital Transformation of Production Planning and Control in Manufacturing SMEs-The Mold Shop Case
Authors: Alexopoulos Kosmas , Nikolakis Nikolaos , Xanthakis Evangelos
Published: October 2022

This work describes an approach for the Digital Transformation (DT) of a manufacturing SME in the mold production industry. The phases for changing from manual and non-adding value labor-intensive practices to digital and smart manufacturing configurations are described. Initially, the needs of the SME are presented in terms of improving the planning and monitoring capabilities. Following the requirements analysis, a set of digital functionalities are proposed and mapped to the specific needs. The digital solution presented includes technologies such as the Internet of Things, data management, intelligent production planning and web technologies. The industrial pilot case has showed how the use of open-source off-the-shelf technology, integrated with the facility’s legacy systems can reduce daily production management tasks and ease the burden of planning and monitoring. The engineers and management team of the SME have acquired first-hand experience on the benefits digitalization of process can bring to the organization that is valuable for proceeding with the DT of the organization.
Fully Automated Electronic Cleansing Using CycleGAN in Computed Tomography Colonography
Authors: Isobe Yoshitaka , Teramoto Atsushi , Morita Fujio , Saito Kuniaki , Fujita Hiroshi
Published: October 2022

In computed tomography colonography (CTC), an electric cleansing technique is used to mix barium with residual fluid, and colon residue is removed by image processing. However, a nonhomogenous mixture of barium and residue may not be properly removed. We developed an electronic cleansing method using CycleGAN, a deep learning technique, to assist diagnosis in CTC. In this method, an original computed tomography (CT) image taken during a CTC examination and a manually cleansed image in which the barium area was manually removed from the original CT image were prepared and converted to an image in which the barium was removed from the original CT image using CycleGAN. In the experiment, the electric cleansing images obtained using the conventional method were compared with those obtained using the proposed method. The average barium cleansing rates obtained by the conventional and proposed methods were 72.3% and 96.3%, respectively. A visual evaluation of the images showed that it was possible to remove only barium without removing the intestinal tract. Furthermore, the extraction of colorectal polyps and early stage cancerous lesions in the colon was performed as in the conventional method. These results indicate that the proposed method using CycleGAN may be useful for accurately visualizing the colon without barium.
Investigation of the Pressure Coefficients Correlation Field for Low-Rise Building Roofs
Authors: Rizzo Fabio , Sepe Vincenzo , Sabbà Maria Francesca
Published: October 2022

The use of hyperbolic paraboloid roofing (HPRs) is increasingly common in contemporary architecture, especially for buildings with large spans, making use of tensile structures or light shells. These structures are very sensitive to wind loads because of their light weight. In particular, they tend to oscillate under wind action, generating complex pressure distributions and cable instability. Therefore, for this shape structure, the investigation of wind-pressure coefficients correlations plays a relevant role in the design of structural elements. Therefore, based on wind tunnel tests, this paper investigates the behavior of four rectangular low-rise building models with HPR when immersed in a turbulent boundary layer flow. The test results were synthesized in correlation maps of the pressure coefficients. The results were evaluated as functions of different model heights and curvatures, and considering three different angles of wind incidence (0°, 45°, and 90°).
Application of Semantic Analysis and LSTM-GRU in Developing a Personalized Course Recommendation System
Authors: Premalatha Mariappan , Viswanathan Vadivel , Čepová Lenka
Published: October 2022

The selection of elective courses based on an individual’s domain interest is a challenging and critical activity for students at the start of their curriculum. Effective and proper recommendation may result in building a strong expertise in the domain of interest, which in turn improves the outcomes of the students getting better placements, and enrolling into higher studies of their interest, etc. In this paper, an effective course recommendation system is proposed to help the students in facilitating proper course selection based on an individual’s domain interest. To achieve this, the core courses in the curriculum are mapped with the predefined domain suggested by the domain experts. These core course contents mapped with the domain are trained semantically using deep learning models to classify the elective courses into domains, and the same are recommended based on the student’s domain expertise. The recommendation is validated by analyzing the number of elective course credits completed and the grades scored by a student who utilized the elective course recommendation system, with the grades scored by the student who was subjected to the assessment without elective course recommendations. It was also observed that after the recommendation, the students have registered for a greater number of credits for elective courses on their domain of expertise, which in-turn enables them to have a better learning experience and improved course completion probability.
Application of Convolutional Neural Network to Defect Diagnosis of Drill Bits
Authors: Yu Yongchao , Liu Qi , Han Boon Siew , Zhou Wei
Published: October 2022

Drilling, one of the most used machining processes, has wide application in different industrial fields. Monitoring the system health and operation status of the drilling process is essential for maintaining production efficiency. In this study, a convolutional neural network (CNN), a deep-learning method, is applied to the defect diagnosis of drill bits. Four drill bits with different health conditions were used to drill holes in an aluminum block, and a vibration sensor collected the signals. Vibration spectrograms generated using short-time Fourier transform were applied to a 2D CNN algorithm, and they were then reconstructed into a 1D data set and applied to a 1D CNN algorithm. The input data size was reduced significantly compared to the raw vibration data after the data-reconstruction process. As a result, the 2D CNN process shows a diagnostic accuracy of 97.33%. On the other hand, the 1D CNN provides a diagnostic accuracy of 96.6%, but it only requires 2/3 of the computational time required by the 2D CNN.
Research on the Tunnel Boring Machine Selection Decision-Making Model Based on the Fuzzy Evaluation Method
Authors: Tan Zhongsheng , Lai Haixiang , Li Zonglin , Zhou Zhenliang , Jiao Yifeng , Li Fengyuan , Wang Liming
Published: October 2022

When the tunnel boring machine (TBM) construction method is used to build tunnels, if the type of TBM is not appropriate, problems, such as low construction efficiency and increased construction cost, will easily occur. Therefore, it is necessary to build a TBM selection decision-making model to guide TBM selection. In this paper, seven evaluation indexes are selected according to engineering experience and expert suggestions, and the quantitative standards of each index are unified. The modified analytic hierarchy process (MAHP) method is used to determine the weight of each evaluation index. The technique for order preference by similarity to an ideal solution (TOPSIS) method is adopted as the decision-making method of TBM selection. Finally, a TBM selection decision-making model is proposed based on the above methods. In order to verify the reliability of the TBM selection decision-making model proposed in this paper, we selected three projects for case verification and compared them with the previous TBM selection methods. The results show that the decision-making results of the method proposed in this paper are good. Additionally, the method proposed in this paper is more comprehensive and accurate than the previous methods. The model proposed in this paper can provide better suggestions for TBM selection in the project planning stage.
Generalizable Underwater Acoustic Target Recognition Using Feature Extraction Module of Neural Network
Authors: Li Daihui , Liu Feng , Shen Tongsheng , Chen Liang , Yang Xiaodan , Zhao Dexin
Published: October 2022

The underwater acoustic target signal is affected by factors such as the underwater environment and the ship’s working conditions, causing the generalization of the recognition model is essential. This study is devoted to improving the generalization of recognition models, proposing a feature extraction module based on neural network and time-frequency analysis, and validating the feasibility of the model-based transfer learning method. A network-based filter based on one-dimensional convolution is built according to the calculation mode of the finite impulse response filter. An attention-based model is constructed using the convolution network components and full-connection components. The attention-based network utilizes convolution components to perform the Fourier transform and feeds back the optimization gradient of a specific task to the network-based filter. The network-based filter is designed to filter the observed signal for adaptive perception, and the attention-based model is constructed to extract the time-frequency features of the signal. In addition, model-based transfer learning is utilized to further improve the model’s performance. Experiments show that the model can perceive the frequency domain features of underwater acoustic targets, and the proposed method demonstrates competitive performance in various classification tasks on real data, especially those requiring high generalizability.
Traffic Light Detection and Recognition Method Based on YOLOv5s and AlexNet
Authors: Niu Chuanxi , Li Kexin
Published: October 2022

Traffic light detection and recognition technology are of great importance for the development of driverless systems and vehicle-assisted driving systems. Since the target detection algorithm has the problems of lower detection accuracy and fewer detection types, this paper adopts the idea of first detection and then classification and proposes a method based on YOLOv5s target detection and AlexNet image classification to detect and identify traffic lights. The method first detects the traffic light area using YOLOv5s, then extracts the area and performs image processing operations, and finally feeds the processed image to AlexNet for recognition judgment. With this method, the shortcomings of the single-target detection algorithm in terms of low recognition rate for small-target detection can be avoided. Since the homemade dataset contains more low-light images, the dataset is optimized using the ZeroDCE low-light enhancement algorithm, and the performance of the network model trained after optimization of the dataset can reach 99.46% AP (average precision), which is 0.07% higher than that before optimization, and the average accuracy on the traffic light recognition dataset can reach 87.75%. The experimental results show that the method has a high accuracy rate and can realize the recognition of many types of traffic lights, which can meet the requirements of traffic light detection on actual roads.
Entropy Optimization in MHD Nanofluid Flow over an Exponential Stretching Sheet
Authors: Sibanda Precious , Almakki Mohammed , Mburu Zachariah , Mondal Hiranmoy
Published: October 2022

We numerically investigate mixed convective heat and mass transport in incompressible nanofluid flow through an exponentially stretching sheet with temperature-dependent viscosity. The fluid flow equations are transformed to a system of non-linear ordinary differential equations using appropriate similarity transformations and solved numerically by using the multi-domain bivariate spectral quasi-linearization technique. The fast convergence of the method is shown by demonstrating that the error is exponentially small for a finite number of iterations. The significance and impact of different fluid parameters are presented and explained. For engineering relevance, the entropy generation number has been calculated for different fluid parameter values.
Analysis of TihxOy Films Produced by Physical Vapor Deposition Method
Authors: Urbonavicius Marius , Tuckute Simona , Karazhanov Smagul , Lelis Martynas
Published: October 2022

For decades, partially oxidized hydrides were commonly considered as undesirably contaminated phases and were avoided by scientists. Nevertheless, more recently, it was realized that in some hydrides and oxides, partial substitution of dissimilar H− and O2− anions allows one to obtain unique optical and electrical properties that might have appealing applications in commercial products. It was determined that specific properties of so called oxyhydride materials strongly depend on the used synthesis methods; therefore, there is a great interest in exploring various variants of oxyhydride formation. In the current study, TiHxOy films were deposited by a reactive magnetron sputtering process in Ar-O2-H2 gas mixtures. Color, transparency and crystal phase composition of the films coherently reacted to the Ar:O2:H2 gas ratio. Namely, the rise in partial hydrogen pressure promoted the formation of anatase phase TiO2 structure and darkening of the films. Interestingly, this had only minimal impact on the band gap values, but had a relatively strong negative effect on the photocatalytic activity of the films. The unaccustomed results stressed the difference between the partially reduced TiO2 with a significant amount of oxygen vacancies and synthesized TiHxOy films where some O2− ions are implicitly substituted by H− ions.
Structural Characterization and Cardioprotective Effect of Water-Soluble Polysaccharides Extracted from Clematis flammula
Authors: Baaziz Intissar , Ghazouani Lakhdar , Rjeibi Ilhem , Feriani Anouar , Mnafgui Kais , Mufti Afoua , Traikia Mounir , Le Cerf Didier , Michaud Philippe , Pierre Guillaume , Cherif Slim
Published: October 2022

Clematis flammula is widely used for its pharmacological properties in Tunisia. This work aimed to explore, in a rat model, the cardiopreventive capacity of polysaccharides extracted from C. flammula (CFPS) after a myocardial injury caused by isoproterenol. Structural analyses suggested that the average molecular weight of CFPS was 1.82 × 105 g/mol, being mainly composed of glucuronide (41.53%), galacturonic acid (19.06%), arabinose (16.10%), galactose (6.15%), glucose (5.49%), and rhamnose (3.55%). Fourier transform–infrared spectroscopy and nuclear magnetic resonance spectroscopy experiments showed that CFPS was rich with carbohydrates containing pectic materials with glycosidic bonds. In addition, results show that pretreatment with CFPS (150 mg/kg) could improve the electrocardiogram pattern by decreasing the elevated ST segment and ameliorating the relative heart weights and the biochemical profile content (creatine phosphokinase-MB, lactate dehydrogenase, and cardiac troponin I). Furthermore, pretreatment with CFPS reduced the amount of malondialdehyde and restored the genotoxicity induced by isoproterenol. The histopathological study revealed that CFPS pretreatment diminished the level of cardiac tissue injury. Based on these data, CFPS presents a broad biological effect as a cardioprotective and can be used for the exploration of novel natural products for the treatment of cardiac disease.
A Hybrid Framework Using PCA, EMD and LSTM Methods for Stock Market Price Prediction with Sentiment Analysis
Authors: Srijiranon Krittakom , Lertratanakham Yoskorn , Tanantong Tanatorn
Published: October 2022

The aim of investors is to obtain the maximum return when buying or selling stocks in the market. However, stock price shows non-linearity and non-stationarity and is difficult to accurately predict. To address this issue, a hybrid prediction model was formulated combining principal component analysis (PCA), empirical mode decomposition (EMD) and long short-term memory (LSTM) called PCA-EMD-LSTM to predict one step ahead of the closing price of the stock market in Thailand. In this research, news sentiment analysis was also applied to improve the performance of the proposed framework, based on financial and economic news using FinBERT. Experiments with stock market price in Thailand collected from 2018–2022 were examined and various statistical indicators were used as evaluation criteria. The obtained results showed that the proposed framework yielded the best performance compared to baseline methods for predicting stock market price. In addition, an adoption of news sentiment analysis can help to enhance performance of the original LSTM model.
Prediction of Venous Thrombosis Chinese Electronic Medical Records Based on Deep Learning and Rule Reasoning
Authors: Chen Jiawei , Yang Jianhua , He Jianfeng
Published: October 2022

Aiming at the problems of heavy workload of medical staff in the process of venous thrombosis prevention and treatment, error evaluation, missed evaluation, and inconsistent evaluation, we propose a joint extraction model of Chinese electronic medical records based on deep learning. The approach was to first construct the handshake annotation, then use bidirectional encoder representations from transformers (BERT) as the word vector embedding, then use the bidirectional long short-term memory network (BiLSTM) to extract the contextual features, and then integrate the contextual information into the process of normalizing the word vector. Experiments show that our proposed method achieves 93.3% and 94.3% of entity and relation F1 on the constructed electronic medical record dataset, which effectively improves the effect of medical information extraction. At the same time, the venous thromboembolism (VTE) risk factors extracted from the electronic medical record were used to judge the risk factors of venous thrombosis by means of rule reasoning. Compared with the assessment of clinicians on the Wells and Geneva scales, the accuracy rates of 84.7% and 86.1% were obtained.
Robustness Analysis on Graph Neural Networks Model for Event Detection
Authors: Wei Hui , Zhu Hanqing , Wu Jibing , Xiao Kaiming , Huang Hongbin
Published: October 2022

Event Detection (ED), which aims to identify trigger words from the given text and classify them into corresponding event types, is an important task in Natural Language Processing (NLP); it contributes to several downstream tasks and is beneficial for many real-world applications. Most of the current SOTA (state-of-the-art) models for ED are based on Graph Neural Networks (GNN). However, a few studies focus on the issue of GNN-based ED models’ robustness towards text adversarial attacks, which is a challenge in practical applications of EDs that needs to be solved urgently. In this paper, we first propose a robustness analysis framework for an ED model. Using this framework, we can evaluate the robustness of the ED model with various adversarial data. To improve the robustness of the GNN-based ED model, we propose a new multi-order distance representation method and an edge representation update method based on attention weights, then design an innovative model named A-MDL-EEGCN. Extensive experiments illustrate that the proposed model can achieve better performance than other models both on original data and various adversarial data. The comprehensive robustness analysis according to experimental results in this paper brings new insights into the evaluation and design of a robust ED model.
Comparison of Patients with Reduced and Mildly Reduced Left Ventricular Ejection Fraction: Intermediate Data from the FAR NHL Registry
Authors: Trčková Alžběta , Špinarová Lenka , Špinar Jindřich , Pařenica Jiří , Málek Filip , Špinarová Monika , Ludka Ondřej , Krejčí Jan , Jarkovský Jiří , Benešová Klára , Lábr Karel
Published: October 2022

Introduction: We present the results of a study by the Pharmacology and NeuroHumoral Activation Registry (FAR NHL), which collects data on patients with chronic heart failure. The register contains 1088 patients from three workplaces in the Czech Republic which specialize in the care of patients with heart failure. Objectives: The aim was to obtain a comparison of pharmacotherapy and the incidence of comorbidities in patients with reduced ejection fraction (HFrEF) versus patients with mid-range (or newly mildly reduced) ejection fraction (HFmrEF). Methods: Patients with a baseline left ventricular ejection fraction below 50% were included and divided into HFrEF with EF below 40% and HFmrEF with EF 40–49%, according to the 2016 ESC Guidelines. In addition to the clinical condition, we also monitored laboratory parameters, comorbidities and pharmacotherapy in the patients. Results: Patients with HFrEF versus HFmrEF are more likely to be male (p < 0.008), younger (p < 0.001), have lower systolic blood pressure and are less likely to have ischemic etiology of heart failure (p < 0.001). There were no differences between the groups in the proportion of comorbidities: hypertension, diabetes mellitus, dyslipidemia, ischemic lower limb disease or chronic obstructive pulmonary disease. There were no differences in the proportion of smokers and non-smokers between the groups. Patients with HFrEF have a higher class of New York Heart Association (NYHA), a level of N-terminal fraction of natriuretic peptide B (NT-proBNP), and a higher level of urea and uric acid. They are more often treated with loop diuretics or mineral corticosteroid receptor (MRA) blockers and less often with thiazides (p < 0.001), and also have a worse two-year prognosis. Conclusion: Compared to patients with HFmrEF, patients with HFrEF have more severe heart failure, more pronounced neurohumoral activation and a worse prognosis. They do not differ in the presence of comorbidities.
Autonomous Short-Term Traffic Flow Prediction Using Pelican Optimization with Hybrid Deep Belief Network in Smart Cities
Authors: Mohammed Gouse Pasha , Alasmari Naif , Alsolai Hadeel , Alotaibi Saud S. , Alotaibi Najm , Mohsen Heba
Published: October 2022

Accurate and timely traffic flow prediction not just allows traffic controllers to evade traffic congestion and guarantee standard traffic functioning, it even assists travelers to take advantage of planning ahead of schedule and modifying travel routes promptly. Therefore, short-term traffic flow prediction utilizing artificial intelligence (AI) techniques has received significant attention in smart cities. This manuscript introduces an autonomous short-term traffic flow prediction using optimal hybrid deep belief network (AST2FP-OHDBN) model. The presented AST2FP-OHDBN model majorly focuses on high-precision traffic prediction in the process of making near future prediction of smart city environments. The presented AST2FP-OHDBN model initially normalizes the traffic data using min–max normalization. In addition, the HDBN model is employed for forecasting the traffic flow in the near future, and makes use of DBN with an adaptive learning step approach to enhance the convergence rate. To enhance the predictive accuracy of the DBN model, the pelican optimization algorithm (POA) is exploited as a hyperparameter optimizer, which in turn enhances the overall efficiency of the traffic flow prediction process. For assuring the enhanced predictive outcomes of the AST2FP-OHDBN algorithm, a wide-ranging experimental analysis can be executed. The experimental values reported the promising performance of the AST2FP-OHDBN method over recent state-of-the-art DL models with minimal average mean-square error of 17.19132 and root-mean-square error of 22.6634.