bluuebunny/crossref_metadata_2025 huggingface dataset:
Physicochemical Composition and Fatty Acid Profile of Goat Kids’ Meat Fed Ground-Corn-Grain Silage Rehydrated with Different Additives
Authors: Diogénes Luciana V. , Edvan Ricardo L. , Medeiros Elisama dos S. , Pereira Filho José M. , de Oliveira Juliana P. F. , Silva Filho Edson C. , Ramos Layse M. G. , de Lucena Kevily H. de O. S. , Araújo Marcos J. , Oliveira Ronaldo L. , Pereira Elzania S. , Bezerra Leilson R.
Published: December 2022

The effects of the replacement of dry ground corn (GC) with corn-grain silage rehydrated with water (RCSwater), cactus pear mucilage (RCSmucilage), and whey (RCSwhey) on the growth, physicochemical composition, and fatty acid profile of goat kids’ meat were investigated. Thirty-two crossbred goat kids (16.4 ± 2.50 kg initial weight) were assigned in a randomized block design with four treatments and eight repetitions. The NDF intake of goat kids fed with RCSmucilage was higher in comparison to RCSwater and RCSwhey (p = 0.0009). The dietary replacement of GC by RCSmucilage increased the final weight (p = 0.033) and meat-cooking losses (p = 0.0001) of kids. The concentrations of oleic (p = 0.046), 11,14-eicosadienoic (p = 0.033), and EPA (p = 0.010) were higher in the meat of kids fed with RCSmucilage and RCSwhey, and the α-linolenic concentration was higher (p = 0.019) for animals feeding with RCSmucilage. Meat from kids fed with RCSwhey presented the lowest ∑SFA and the highest ∑MUFA. In contrast, the ∑PUFA (p < 0.012) was higher for goats fed with RCSwater. The ∑ω3 (p < 0.0001) was higher in animals fed with RCSmucilage and RCSwhey. Desirable fatty acids were higher (p = 0.044) in animals fed with RCSmucilage and RCSwhey, and the atherogenicity (p = 0.044) and thrombogenicity (p < 0.0001) indexes were lower for goats fed the RCSwhey diet. The enzymatic activities of Δ9desaturase (C16) were higher (p = 0.027) in goat kids fed with GC and RCSmucilage, and Δ9desaturase (C18) was higher (p = 0.0497) when goats were fed with RCSmucilage and RCSwhey. Elongase activities were higher (p = 0.045) in goat kids fed with GC and RCSwater. The total replacement of GC by RCSmucilage is recommended in the diet of goat kids due to improvements in the weight gain and proportion of desirable fatty acids in the meat. In addition, RCSmucilage promoted better conservation of the silage at a lower cost when compared to commercial additives.
Measuring Comfort Behaviours in Laying Hens Using Deep-Learning Tools
Authors: Sozzi Marco , Pillan Giulio , Ciarelli Claudia , Marinello Francesco , Pirrone Fabrizio , Bordignon Francesco , Bordignon Alessandro , Xiccato Gerolamo , Trocino Angela
Published: December 2022

Image analysis using machine learning (ML) algorithms could provide a measure of animal welfare by measuring comfort behaviours and undesired behaviours. Using a PLF technique based on images, the present study aimed to test a machine learning tool for measuring the number of hens on the ground and identifying the number of dust-bathing hens in an experimental aviary. In addition, two YOLO (You Only Look Once) models were compared. YOLOv4-tiny needed about 4.26 h to train for 6000 epochs, compared to about 23.2 h for the full models of YOLOv4. In validation, the performance of the two models in terms of precision, recall, harmonic mean of precision and recall, and mean average precision (mAP) did not differ, while the value of frame per second was lower in YOLOv4 compared to the tiny version (31.35 vs. 208.5). The mAP stands at about 94% for the classification of hens on the floor, while the classification of dust-bathing hens was poor (28.2% in the YOLOv4-tiny compared to 31.6% in YOLOv4). In conclusion, ML successfully identified laying hens on the floor, whereas other PLF tools must be tested for the classification of dust-bathing hens.
Licury Cake in Diets for Lactating Goats: Qualitative Aspects of Milk and Cheese
Authors: Ferreira Fernanda G. , Leite Laudí C. , Alba Henry D. R. , Pina Douglas dos S. , Santos Stefanie A. , Tosto Manuela S. L. , de Freitas Júnior José E. , Rodrigues Carlindo S. , Mesquita Bruna M. A. de C. , Carvalho Gleidson G. P. de
Published: December 2022

The study was carried out to evaluate the effects of licury cake (LC) inclusion in diets for lactating goats on milk chemical composition and fatty acid profile, and physicochemical composition and sensory attributes of Minas Frescal cheese. Twelve lactating goats were used (eight Saanen and four Anglo Nubian goats, with 35 ± 5 days in lactation and average body weight of 37.93 ± 9.22 kg), distributed in a triplicate 4 × 4 Latin Square design. The increasing levels of LC studied were: 0, 67, 133 and 200 g/kg of dry matter (DM). The analyses were adjusted using orthogonal polynomial contrasts, in which the probability level of 5% was considered. For sensory attributes, principal component analysis was performed. The LC inclusion promoted the reduction in moisture (p = 0.013) and mineral matter (p < 0.001) content in cheese. The ether extract content in cheese showed a quadratic effect (p = 0.021). Lauric acid showed a linear (p = 0.002) increasing effect, and myristic (p < 0.001) and rumenic (p = 0.018) acids showed quadratic effects. The sensory attributes analysis in cheese indicated that the inclusion of 133 and 200 g/kg of LC improve its texture. Flavor was improved with the inclusion of 67 and 133 g/kg. The inclusion of up to 133 g/kg of LC in the diet of lactating goats is recommended because it promotes improvements in flavor and texture of Minas Frescal cheese.
Genomic Characterization of KPC-31 and OXA-181 Klebsiella pneumoniae Resistant to New Generation of β-Lactam/β-Lactamase Inhibitor Combinations
Authors: Muresu Narcisa , Del Rio Arcadia , Fox Valeria , Scutari Rossana , Alteri Claudia , Are Bianca Maria , Terragni Pierpaolo , Sechi Illari , Sotgiu Giovanni , Piana Andrea
Published: December 2022

Background: Carbapenem resistant Klebsiella pneumoniae (cr-Kp) causes serious infections associated with a high mortality rate. The clinical efficacy of ceftazidime/avibactam (CZA), meropenem/vaborbactam (M/V), and imipenem/relebactam (I/R) against cr-Kp is challenged by the emergence of resistant strains, making the investigation and monitoring of the main resistance mechanisms crucial. In this study, we reported the genome characterization of a Klebsiella pneumoniae strain isolated from a critically ill patient and characterized by a multidrug resistant (MDR) profile, including resistance to CZA, M/V, and I/R. Methods: An antimicrobial susceptibility test (AST) was performed by an automated system and E-test and results were interpreted following the EUCAST guidelines. Genomic DNA was extracted using a genomic DNA extraction kit and it was sequenced using the Illumina Nova Seq 6000 platform. Final assembly was manually curated and carefully verified for detection of antimicrobial resistance genes, porins modifications, and virulence factors. Results: The K. pneumoniae isolate belonged to sequence type ST512 and harbored 23 resistance genes, conferring resistance to all antibiotic classes, including blaKPC-31 and blaOXA-181, leading to carbapenems resistance. The truncation of OmpK35 and mutation OmpK36GD were also observed. Conclusions: The genomic characterization demonstrated the high resistant profile of new cr-Kp coharboring class A and D carbapenemases. The presence of KPC-31, as well as the detection of OXA-181 and porin modifications, further limit the therapeutic options, including the novel combinations of β-lactam/β-lactamase inhibitor antibiotics in patients with severe pneumonia caused by cr-Kp.
Pre-Referral Microbiology in Long Bone Infection: What Can It Tell Us?
Authors: Hotchen Andrew J. , Corrigan Ruth A. , Dudareva Maria , Bernard Andrew , Ferguson Jamie , Atkins Bridget L. , McNally Martin
Published: December 2022

Background: It remains unclear how accurately patients’ previous microbiology correlates with that ascertained from deep sampling in long bone infection. This study assessed the quality of microbiology referral information and compared it to the gold standard of intra-operative deep tissue sampling. Methods: All patients referred to a single specialist centre within the UK between January 2019 and March 2020 who received surgery for long bone infection were eligible for inclusion. Data on microbiological testing that was performed prior to referral was collected prospectively at the time of clinic appointment and prior to surgery. Pre-referral microbiology was compared to microbiology from deep tissue samples taken during surgery. Results: 141 patients met the diagnostic criteria for long bone infection and were included for analysis. Of these, 72 patients had microbiological information available at referral from 88 samples, obtained from either sinus swab (n = 40), previous surgical sampling (n = 25), biopsy (n = 19) or blood cultures (n = 4). In 65.9% of samples, pre-referral microbiology was deemed to be a non-match when compared to intra-operative samples. Factors that increased risk of a non-match included presence of a sinus (odd’s ratio (OR) 11.3 [95% CI 2.84–56.6], p = 0.001), increased duration of time from sampling (OR 2.29, [95% CI 1.23–5.90], p = 0.030) and results from prior surgical sampling (OR 23.0 [95% CI 2.80–525.6], p = 0.011). Furthermore, previous surgical debridement gave an increased risk of multi-, extensively or pan-resistant isolates cultured from intra-operative sampling (OR 3.6 [95% CI 1.5–8.7], p < 0.01). Conclusions: We have demonstrated that presence of a sinus, a long time from the sample being taken and results from prior surgical sampling are more likely to give inaccurate representation of current microbiology. Importantly, in cases with previous debridement surgery, there was an increased risk of multi drug resistant isolates which should be planned for in future treatments.
Baicalein Attenuates Brain Iron Accumulation through Protecting Aconitase 1 from Oxidative Stress in Rotenone-Induced Parkinson’s Disease in Rats
Authors: Liu Run-Zhe , Zhang Sen , Zhang Wen , Zhao Xiao-Yue , Du Guan-Hua
Published: December 2022

Aconitase 1 (ACO1) links oxidative stress and iron accumulation in Parkinson’s disease (PD). ACO1 loses its aconitase activity and turns into iron regulatory protein 1 (IRP1) upon oxidative stress. IRP1 plays an important role in the accumulation of intracellular iron. Baicalein is a flavonoid isolated from the roots of Scutellaria baicalensis. The present results show that baicalein could bind to ACO1 and protect its isoform from the oxidative stress induced by reactive oxygen species (ROS) and reactive nitrogen species (RNS). Furthermore, baicalein promoted aconitase activity and inhibited IRP1 activation in rotenone-induced PD models. Additionally, baicalein decreased the hydroxyl radicals generated by iron. In conclusion, baicalein attenuated iron accumulation and iron-induced oxidative stress in the brain of PD rats by protecting ACO1.
Metabolic Fate of Orally Ingested Proanthocyanidins through the Digestive Tract
Authors: Niwano Yoshimi , Kohzaki Hidetsugu , Shirato Midori , Shishido Shunichi , Nakamura Keisuke
Published: December 2022

Proanthocyanidins (PACs), which are oligomers or polymers of flavan-3ols with potent antioxidative activity, are well known to exert a variety of beneficial health effects. Nonetheless, their bioaccessibility and bioavailability have been poorly assessed. In this review, we focused on the metabolic fate of PACs through the digestive tract. When oligomeric and polymeric PACs are orally ingested, a large portion of the PACs reach the colon, where a small portion is subjected to microbial degradation to phenolic acids and valerolactones, despite the possibility that slight depolymerization of PACs occurs in the stomach and small intestine. Valerolactones, as microbiota-generated catabolites of PACs, may contribute to some of the health benefits of orally ingested PACs. The remaining portion interacts with gut microbiota, resulting in improved microbial diversity and, thereby, contributing to improved health. For instance, an increased amount of beneficial gut bacteria (e.g., Akkermansia muciniphila and butyrate-producing bacteria) could ameliorate host metabolic functions, and a lowered ratio of Firmicutes/Bacteroidetes at the phylum level could mitigate obesity-related metabolic disorders.
Credit Card-Not-Present Fraud Detection and Prevention Using Big Data Analytics Algorithms
Authors: Razaque Abdul , Frej Mohamed Ben Haj , Bektemyssova Gulnara , Amsaad Fathi , Almiani Muder , Alotaibi Aziz , Jhanjhi N. Z. , Amanzholova Saule , Alshammari Majid
Published: December 2022

Currently, fraud detection is employed in numerous domains, including banking, finance, insurance, government organizations, law enforcement, and so on. The amount of fraud attempts has recently grown significantly, making fraud detection critical when it comes to protecting your personal information or sensitive data. There are several forms of fraud issues, such as stolen credit cards, forged checks, deceptive accounting practices, card-not-present fraud (CNP), and so on. This article introduces the credit card-not-present fraud detection and prevention (CCFDP) method for dealing with CNP fraud utilizing big data analytics. In order to deal with suspicious behavior, the proposed CCFDP includes two steps: the fraud detection Process (FDP) and the fraud prevention process (FPP). The FDP examines the system to detect harmful behavior, after which the FPP assists in preventing malicious activity. Five cutting-edge methods are used in the FDP step: random undersampling (RU), t-distributed stochastic neighbor embedding (t-SNE), principal component analysis (PCA), singular value decomposition (SVD), and logistic regression learning (LRL). For conducting experiments, the FDP needs to balance the dataset. In order to overcome this issue, Random Undersampling is used. Furthermore, in order to better data presentation, FDP must lower the dimensionality characteristics. This procedure employs the t-SNE, PCA, and SVD algorithms, resulting in a speedier data training process and improved accuracy. The logistic regression learning (LRL) model is used by the FPP to evaluate the success and failure probability of CNP fraud. Python is used to implement the suggested CCFDP mechanism. We validate the efficacy of the hypothesized CCFDP mechanism based on the testing results.
Blockchain and Smart Contracts to Secure Property Transactions in Smart Cities
Authors: Uchani Gutierrez Omar Cliff , Xu Guangxia
Published: December 2022

Cities have been growing at an impressive rate, and with the advancement of technology and digitization, new ways have been proposed to provide cities with a certain level of autonomy and intelligence so that they can self-regulate tasks that currently take a lot of time for both citizens and authorities, and which also have a negative impact on the environment. We have recently experienced one of the most abrupt changes in history as a result of the COVID-19 pandemic, where millions of people, businesses, schools, companies, governments, etc., have had to modify their ways of working, in addition to dealing with many other changes in the present moment, the most important of which is the transition to electronic transactions. This is a chance to progress toward smart city transformation and the implementation of models that assist citizens in their ordinary activities. One of the most common activities is the purchase of real estate. In this study, we propose a model to make the purchase and sale of real estate more equitable and fairer, and not just based on the amount of money. A smart home should be able to identify who its current owner is by functioning as an IoT badge, and, after the subject’s identity has been verified, it should be granted full access to all services, or else it should be blocked and/or alerted to the authorities. The use of smart contracts in a blockchain to transfer ownership of a smart home that includes, as inputs, those interested in acquiring a specific house and, as outputs, a person who chose the system based on the requirements previously established by the government of the Smart City. As a result, susceptibility to fraud or interference by a third person is reduced, and an individual’s security of living in a smart home, and therefore, in a smart city, is strengthened.
Recent Trends on Domestic, Agricultural and Industrial Wastewaters Treatment Using Microalgae Biorefinery System
Authors: El Bakraoui Houria , Slaoui Miloudia , Mabrouki Jamal , Hmouni Driss , Laroche Céline
Published: December 2022

In addition to producing bioenergy and molecules with high added value, microalgae have been recognized as an efficient microorganism for wastewater treatment. However, a major obstacle preventing its widespread use is the high energy cost of pretreatment, cultivation and downstream processes. Different types of wastewaters have been tested as culture mediums for microalgal biorefinery system. This review gives a summary of the most used microalgae strains for wastewater treatment, as well as information on the physical and chemical characteristics of domestic, agricultural, and industrial wastewaters. It also discusses wastewater pretreatment techniques, nutrient uptake and removal, biomass production and biomolecules productivities. There is also discussion on how microalgae remove contaminants from wastewater. Additionally, the problems and restrictions of microalgae-based wastewater treatment are explored, and recommendations are made for additional study and advancement. This literature review demonstrates that microalgae monoculture systems have proven to be beneficial as an innovative wastewater treatment technology, due to its high efficiencies in pollutant removals and biomolecule production; however, the upstream and downstream treatment pose a limit to industrialize the process. Until now, there has been no conventional design of the wastewater treatment process using microalgae in the biorefinery system, which constitutes a huge gap to assess a real life cycle assessment (LCA) and techno economic analysis (TEA).
An Improved Method to Obtain Fish Weight Using Machine Learning and NIR Camera with Haar Cascade Classifier
Authors: Lopez-Tejeida Samuel , Soto-Zarazua Genaro Martin , Toledano-Ayala Manuel , Contreras-Medina Luis Miguel , Rivas-Araiza Edgar Alejandro , Flores-Aguilar Priscila Sarai
Published: December 2022

The calculation of weight and mass in aquaculture systems is of great importance, since with this task, it is decided when to harvest; generally, the above is manipulating the body manually, which causes stress in the fish body. Said stress can be maintained in the fish body for several hours. To solve this problem an improved method was implemented using artificial intelligence, near-infrared spectroscopy camera, Haar classifiers, and a mathematical model. Hardware and software were designed to get a photograph of the fish in its environment in real conditions. This work aimed to obtain fish weight and fish length in real conditions to avoid the manipulation of fish with hands for the process mentioned, avoiding fish stress, and reducing the time for these tasks. With the implemented hardware and software adding an infrared light and pass band filter for the camera successfully, the fish was detected automatically, and the fish weight and length were calculated moreover the future weight was estimated.
Numerical Identification of Material Model Parameters of UHPFRC Slab under Blast Loading
Authors: Dubec Branislav , Maňas Pavel , Štoller Jiří , Zezulová Eva , Dvořák Petr , Hejmal Zdeněk
Published: December 2022

The reliability of numerical simulations of the structural response of nonhomogeneous materials to high velocity loadings is highly dependent on the used material model and parameters. For nonhomogeneous materials, such as fibres, reinforced concrete is widely used for the Winfrith model, but the question of appropriate material parameters for Ultra-High Performance Fibre Reinforcement Concrete (UHPFRC) under high velocity loadings is still open. The article deals with possible method of inverse identification of material parameters of a UHPFRC slab under blast loading for a Winfrith material model. Possible application is in the field of numerical simulation of protective or critical infrastructure response to blast loading. Experimental measurement of the time–deflection curve through laser scanning using the triangulation method gave us input data for an inverse identification phase conducted in Optislang software. Obtained material parameters from a given range are optimized for blast loading and their Pearson’s correlation coefficient provides us information about their significance for simulation.
Thermal Response in Two Models of Socks with Different 3-D Weave Separations
Authors: Sánchez-Rodríguez Raquel , Gómez-Martín Beatriz , Escamilla-Martínez Elena , Morán-Cortés Juan Francisco , Martínez-Nova Alfonso
Published: December 2022

Socks with the same three-dimensional plantar design but with different compositions in the separation of their weaves could have different thermoregulatory effects. The objective of this study was therefore to evaluate the temperatures on the sole of the foot after a 10-km run using two models of socks with different weave separations. In a sample of 20 individuals (14 men and 6 women), plantar temperatures were analyzed using a Flir E60bx® (Flir Systems) thermographic camera before and after a run of 10 km wearing two models of socks that had different separations between the fabric weaves (5 mm versus 3 mm). After the post-exercise thermographic analysis, the participants responded to a Likert-type survey to evaluate the physiological characteristics of the two models of socks. There was a significant increase of temperature (+4 °C, p < 0.001) after the 10-km run with both models of sock. However, the temperature under the 1st metatarsal head was higher with the AWC 2.1 model than with the AWC 1 (33.6 ± 2.0 °C vs. 33.2 ± 2.1 °C, p = 0.014). No significant differences were found in the scores on the physiological characteristics comfort survey (p > 0.05 in all cases). The two models presented similar thermoregulatory effects on the soles of the feet, although the model with the narrowest weave separation generated greater temperatures (+0.4 °C) under the first metatarsal head.
Effect of the Geometric Configuration of the Disc Cutter on the Cutting Behaviour in Tunneling
Authors: Duan Yixin , Yuan Dajun , Wu Jun , Deng Xiaojie , Wu Bing , Sun Zhangang
Published: December 2022

The disc cutter is a key tool in shield machines that come into direct contact with rock while participating in the removal of rock. Therefore, the reasonable design of the geometric configuration of disc cutters greatly determines the tunnelling efficiency of the shield machine. In this paper, the factors influencing the rock-breaking behaviour of disc cutters are studied. Firstly, to ensure the accuracy of the rock-breaking simulation, the parameters of the Holmquist–Johnson–Cook model of the diorite in the Jinan area were determined. Secondly, using ANSYS/LS-DYNA to simulate the rock-breaking process, the influence of the geometric configuration, including blade width and blade fillet, on rock-breaking behaviour was analysed. The results show that with increasing depth of penetration, the contact force increases approximately linearly. The contact force and the rock-breaking influence range gradually decrease with increasing number of blade fillets. In addition, with increasing number of blade fillets, the shape of the influence range gradually transitions from an approximate circle to a trapezoid, and finally to a triangle. With increasing blade width, the contact force and the rock-breaking influence range both increase, but the shape of the influence range remains largely unchanged as a trapezoid. On the basis of these research results, this paper gives some suggestions for the selection and configuration of disc cutters in different strata, which can give some guidance for practical engineering.
Hydroxyapatite Growth on Activated Carbon Surface for Methylene Blue Adsorption: Effect of Oxidation Time and CaSiO3 Addition on Hydrothermal Incubation
Authors: Moreno-Santos Anastasio , Rios-Hurtado Jorge Carlos , Flores-Villaseñor Sergio Enrique , Esmeralda-Gomez Alma Graciela , Guevara-Chavez Juanita Yazmin , Lara-Castillo Fatima Pamela , Escalante-Ibarra Griselda Berenice
Published: December 2022

Many adsorbent materials are now commercially available; however, studies have focused on modifying them to enhance their properties. In this study, an activated carbon (AC) and hydroxyapatite (HAp) composite was synthesized by the immersion of ACs in a simulated body fluid solution, varying the AC oxidation degree along with the addition of CaSiO3. The resulting composites were characterized by ash %, X-ray fluorescence (XRF), Fourier-transformed infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and point of zero charge (PZC). The characterization results indicated that the addition of CaSiO3 and the oxygenated functional groups in the AC surface are key factors for HAp growth. The composites were tested on methylene blue (MB) adsorption as a potential application for the synthesized materials. Adsorption isotherms were modeled with Langmuir and Freundlich isotherms, and the composites were fitted to a Langmuir model with the highest qmax value of 9.82. The kinetic results indicated that for the pseudo-second-order model, the composites fitted, with a contact time of 180 min to remove a 95.61% average of the MB. The results indicate that composite materials can be an efficient adsorbent for the removal of MB from aqueous solutions at low concentrations since the material with the highest amount of HAp growth removed 99.8% of the MB in 180 min.
The Analysis of the Loading and the Strength of the FLAT RACK Removable Module with Viscoelastic Bonds in the Fittings
Authors: Panchenko Sergii , Gerlici Juraj , Vatulia Glib , Lovska Alyona , Pavliuchenkov Mykhailo , Kravchenko Kateryna
Published: December 2022

The article presents the results of the strength calculation of the FLAT RACK removable module design using the finite element method. The FLAT RACK removable module provides higher efficiency of freight transportation. The special features of the removable module are its components made of rectangular tubes and its fittings with viscoelastic bonds. The parameters of the profile for such a removable module are determined through the maximum resistance moments of its components. The research includes mathematical modelling of the dynamic loading on the removable module placed on a flat wagon during a shunting impact. The accelerations to the removable module are also determined. The results are confirmed by computer modelling of the dynamic loading on the removable module. It is found that the strength of the removable module is provided. The research conducted may be used by those who are concerned about designing advanced module-type rail vehicle structures and enhancing their operational efficiency.
Use of Neural Networks and Computer Vision for Spill and Waste Detection in Port Waters: An Application in the Port of Palma (MaJorca, Spain)
Authors: Morell Mariano , Portau Pedro , Perelló Antoni , Espino Manuel , Grifoll Manel , Garau Carlos
Published: December 2022

Water quality and pollution is the main environmental concern for ports and adjacent coastal waters. Therefore, the development of Port Environmental Management systems often relies on water pollution monitoring. Computer vision is a powerful and versatile tool for an exhaustive and systematic monitoring task. An investigation has been conducted at the Port of Palma de Mallorca (Spain) to assess the feasibility and evaluate the main opportunities and difficulties of the implementation of water pollution monitoring based on computer vision. Experiments on surface slicks and marine litter identification based on random image sets have been conducted. The reliability and development requirements of the method have been evaluated, concluding that computer vision is suitable for these monitoring tasks. Several computer vision techniques based on convolutional neural networks were assessed, finding that Image Classification is the most adequate for marine pollution monitoring tasks due to its high accuracy rates and low training requirements. Image set size for initial training and the possibility to improve accuracy through retraining with increased image sets were considered due to the difficulty in obtaining port spill images. Thus, we have found that progressive implementation can not only offer functional monitoring systems in a shorter time frame but also reduce the total development cost for a system with the same accuracy level.
Experimental and Empirical Studies to Evaluate Liquefaction Resistance of Partially Saturated Sands
Authors: Zeybek Abdülhakim
Published: December 2022

Partially saturated sands with occluded gas bubbles may occur naturally in the field or can be created artificially as a way of mitigating liquefaction effects. This study aimed to investigate the main parameters that influence the liquefaction resistance of partially saturated sands containing occluded gas bubbles. It also adopted a simplified approach and proposed empirical relationships that linked the liquefaction-resistance ratio to the bulk modulus, maximum volumetric strain, and excess pore-pressure ratio. Considering these objectives, a total of 60 stress-controlled dynamic triaxial tests were conducted. Nearly/fully saturated and partially saturated sand specimens prepared using sodium percarbonate were subjected to undrained cyclic loading with a loading frequency of 0.1 Hz. The loosely or densely packed sand specimens at different degrees of saturation (79–100%) were examined under different initial effective confining stresses (25–100 kPa) and back pressures (100–400 kPa). The analysis of the test results indicated that the liquefaction resistance of the partially saturated sands constantly increased as the degree of saturation decreased, and this effect was more prominent under higher initial effective confining stresses and lower back pressures. The adopted method satisfactorily captured this trend and showed reasonable matches between the empirical predictions and experimentally observed results from this study and previous research.
Combining Standard Artificial Intelligence Models, Pre-Processing Techniques, and Post-Processing Methods to Improve the Accuracy of Monthly Runoff Predictions in Karst-Area Watersheds
Authors: Mo Chongxun , Jiang Changhao , Lei Xingbi , Lai Shufeng , Deng Yun , Cen Weiyan , Sun Guikai , Xing Zhenxiang
Published: December 2022

The complex and unique topography of karst regions highlights the weaknesses of traditional hydrological models which fail to fully generalize them. The successive proposals of standard artificial intelligence (AI) models, pre-processing techniques, and post-processing methods have provided new opportunities to enhance the accuracy of runoff prediction in karst areas. In this study, first, the BP neural network model and the Elman neural network model were used for runoff prediction. Then, the performance of four coupled models—formed by combining two AI pre-processing techniques, Empirical Modal Decomposition (EMD) and Ensemble Empirical Modal Decomposition (EEMD), with the previously mentioned AI models—was investigated. Finally, the accuracy of triple-coupled models, formed by applying the post-processing method of quantile mapping (QM) to the previous coupled models, was estimated. The Nash–Sutcliffe efficiency (NSE), the mean absolute percentage error (MAPE), the root mean square error (RMSE), and the peak percentage of threshold statistics (PPTS) were selected to evaluate and analyze the forecasting results of the above models. The results demonstrated that the BP model had the best prediction effect of the standard AI models, the coupled forecasting models had better prediction accuracy than the standard AI models, and the triple-coupled QM–EMD–Elman model had the best forecasting effect with an NSE value of 0.73, MAPE value of 0.75, RMSE value of 34.60, and PPTS value of 2.36.
Reliability Assessment of Steel-Lined and Prestressed FRC Slabs against Projectile Impact
Authors: Siddiqui Nadeem , Abbas Husain , Almusallam Tarek , Li Q. M. , Al-Salloum Yousef
Published: December 2022

A simulation-based probabilistic method is proposed for assessing the reliability of steel-lined and prestressed fiber-reinforced concrete (PFRC) slabs against the impact loads. The impact testing of several prestressed and non-prestressed FRC slabs of 800 × 800 × 100 mm in size was carried out. The experimental program involved projectile impact testing of prestressed and non-prestressed FRC slabs using a gas gun. Three parameters were varied for testing of slabs under the projectile impact, viz., a quantity of steel fibers in the concrete, steel lining on the backside of the slab, and the prestressing level. The probability-based reliability analysis of all the tested specimens was then performed to highlight the influence of steel lining, steel fibers, and prestress in enhancing the safety of RC (reinforced concrete) slabs against projectile impacts. Projectile impact velocity exceeding the slab’s ballistic limit was assumed to lead to the failure of the PFRC slab, i.e., the perforation failure of the slab. Study results indicate that when no steel fiber was present, slab reliability was low. Adding fibers to slabs increases slabs’ reliability significantly. Specimens with the highest steel fiber content (1.2%) showed the greatest increase in reliability. The steel lining on the back face makes the slab’s reliability almost doubled in comparison with those without lining. Additionally, steel lining makes the PFRC slabs as reliable as desired. It was further noticed that the prestressing helps in enhancing the slab safety against projectile impacts. Even a minimal amount of prestressing makes a noticeable improvement in the reliability of PFRC slabs.
OFDM Emitter Identification Method Based on Data Augmentation and Contrastive Learning
Authors: Yu Jiaqi , Yuan Ye , Zhang Qian , Zhang Wei , Fan Ziyu , Jin Fusheng
Published: December 2022

Deep learning technology has been widely applied in emitter identification. With the deepening research, the problem of emitter identification under the few-shots condition has become a frontier research direction. As a special communication signal, OFDM (Orthogonal Frequency Division Multiplexing) signal is of high complexity so emitter identification technology under OFDM is extremely challenging. In this paper, an emitter identification method based on contrastive learning and residual network is proposed. First, according to the particularity of OFDM, we adjust the structure of ResNet and propose a targeted data preprocessing method. Then, some data augmentation strategies are designed to construct positive samples. We conduct self-supervised pretraining to distinguish features of positive and negative samples in hidden space. Based on the pretrained feature extractor, the classifier is no longer trained from scratch. Extensive experiments have validated the effectiveness of our proposed methods.
Modeling and Characteristic Analysis of Combined Beam Tri-Stable Piezoelectric Energy Harvesting System Considering Gravity
Authors: Zhang Xuhui , Xu Hengtao , Pan Jianan , Chen Xiaoyu , Zhu Fulin , Guo Yan , Tian Hao , Cheng Yujun
Published: December 2022

The emergence of the vibration energy harvesting system makes it possible for wireless monitoring nodes in coal mines to realize self-power supply. In order to reveal the influence of gravity effect on the response characteristics of the combined beam tri-stable piezoelectric energy harvesting system (CTEHS), the system’s nonlinear magnetism is calculated according to the principle of point magnetic charge dipole, and the system’s nonlinear resilience is obtained through experimental measurements and nonlinear fitting methods. Based on the Lagrange equation, the system’s electromechanical coupling motion model considering gravity is established. The system’s motion equation is solved numerically based on the Runge–Kutta algorithm, and the effects of the end magnet mass and the initial vibration point on the bifurcation behavior, potential energy, and system output performance are investigated by emulation and experiment. The research shows that the magnet’s gravity effect causes a change in the stable equilibrium position and the system’s motion state and also causes the system to generate additional gravitational potential energy, which leads to a potential asymmetric well of the system. Under the consideration of magnet gravity, the appropriate end magnet mass and initial vibration point can not only reduce the system’s requirements for external excitation strength but also effectively improve the system’s response and output. This research provides a new theoretical basis for the optimal design of the tri-stable piezoelectric energy harvesting system.
Influence of the Texture Configuration of Heating Surfaces Created by Laser Irradiation on the Ignition and Combustion Characteristics of Liquid Fuels
Authors: Orlova Evgeniya , Glushkov Dmitriy , Abedtazehabadi Akram , Belyaev Saveliy , Feoktistov Dmitriy
Published: December 2022

The main characteristics of ignition and combustion of fuel droplets (organic coal-water fuel, oil emulsion, and oil in the usual state) placed on the heated surfaces of structural steel (DIN standard grade X16CrNi25-20) were experimentally determined under conditions corresponding to the start-up and nominal operation of power-generating equipment. It was shown that due to the application of texture on the steel surfaces, it is possible to change the ignition and combustion characteristics of fuel droplets. A graphic-analytical method was developed to predict the dimensions of textures in the form of microchannels using laser technology for processing metal surfaces. It was found that the texture configuration in the form of microchannels formed by nanosecond laser radiation on steel surfaces makes it possible to significantly increase the surface resistance to adhesion of combustion products of liquid and slurry fuels.
A Wireless EEG System for Neurofeedback Training
Authors: Totev Tsvetalin , Taskov Tihomir , Dushanova Juliana
Published: December 2022

This paper presents a mobile, easy-to-maintain wireless electroencephalograph (EEG) system designed for work with children in a school environment. This EEG data acquisition platform is a small-sized, battery-powered system with a high sampling rate that is scalable to different channel numbers. The system was validated in a study of live z-score neurofeedback training for quantitative EEG (zNF-qEEG) for typical-reading children and those with developmental dyslexia (DD). This system reads and controls real-time neurofeedback (zNF) signals, synchronizing visual stimuli (low spatial frequency (LSF) illusions) with the alpha/theta (z-α/θ) score neural oscillations. The NF sessions were applied during discrimination of LSF illusions with different contrasts. Visual feedback was provided with color cues to remodulate neural activity in children with DD and their cognitive abilities. The combined zNF-qEEG and training with different visual magnocellular and parvocellular tasks (VTs) compensated for the deficits in the temporal areas affecting the occipitotemporal pathway more in the left-hemispheric ventral brain areas of the post-training children with dyslexia in the low-contrast LSF illusion and dorsal dysfunction in the high-contrast LSF illusion. The better α/θ scores for postD in the temporoparietal and middle occipital regions can be associated with an improvement in special frequency processing, while the better scores in the precentral and parietal cortices were due to an advancement in the temporal processing of the illusion. The improvements in the reading speeds were twice as high after 4 months of qEEG z-NF-VT training, with three times fewer omitted words and errors.
The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges
Authors: Zinno Raffaele , Haghshenas Sina Shaffiee , Guido Giuseppe , Rashvand Kaveh , Vitale Alessandro , Sarhadi Ali
Published: December 2022

The challenges of urban administration are growing, as the population, automobiles, and cities rise. Making cities smarter is thus one of the most effective solutions to urban issues. A key feature of the “smart cities” of today is that they use cutting-edge technology in their infrastructure and services. With strategic planning, the smart city utilizes its resources in the most efficient manner. With reduced expenses and enhanced infrastructure, smart cities provide their residents with more and better services. One of these important urban services that can be very helpful in managing cities is structural health monitoring (SHM). By combining leading new technologies like the Internet of Things (IoT) with structural health monitoring, important urban infrastructure can last longer and work better. A thorough examination of recent advances in SHM for infrastructure is thus warranted. Bridges are one of the most important parts of a city’s infrastructure, and their building, development, and proper maintenance are some of the most important aspects of managing a city. The main goal of this study is to look at how artificial intelligence (AI) and some technologies, like drone technology and 3D printers, could be used to improve the current state of the art in SHM systems for bridges, including conceptual frameworks, benefits and problems, and existing methods. An outline of the role AI and other technologies will play in SHM systems of bridges in the future was provided in this study. Some novel technology-aided research opportunities are also highlighted, explained, and discussed.
Antioxidant and Antimicrobial Properties of Selected Phytogenics for Sustainable Poultry Production
Authors: Mnisi Caven M. , Mlambo Victor , Gila Akho , Matabane Allen N. , Mthiyane Doctor M. N. , Kumanda Cebisa , Manyeula Freddy , Gajana Christian S.
Published: December 2022

The use of antibiotic growth promoters (AGP) in poultry production not only promotes the emergence of pathogenic multi-drug resistant bacteria, but it also compromises product quality, threatens animal and human health, and pollutes the environment. However, the complete withdrawal of AGP without alternatives could result in uncontrollable disease outbreaks that would jeopardize large-scale poultry intensification. Thus, the use of phytogenic products as potential alternatives to in-feed AGP has attracted worldwide research interest. These phytogenic products contain numerous biologically active substances with antioxidant and antimicrobial activities that can enhance poultry health, growth performance, and meat quality characteristics. In addition, the incorporation of phytogenic products as feed additives in poultry diets could result in the production of high-quality, drug-free, and organic poultry products that are safe for human consumption. Thus, this review examines the current evidence on the antioxidant and antimicrobial properties of a selection of phytogenic products, their effects on nutrient utilization, and physiological and meat quality parameters in poultry. The paper also reviews the factors that could limit the utilization of phytogenic products in poultry nutrition and proposes solutions that can deliver efficient and sustainable poultry production systems for global food and nutrition security.
Comparative Analysis of Grapevine Epiphytic Microbiomes among Different Varieties, Tissues, and Developmental Stages in the Same Terroir
Authors: Awad Murad , Giannopoulos Georgios , Mylona Photini V. , Polidoros Alexios N.
Published: December 2022

There is limited knowledge about the relationships of epiphytic microbiomes associated with the phyllosphere of different Vitis vinifera cultivars in the same vineyard and terroir. To address this research gap, we investigated the microbiome compositionof 36 grapevine genotypes grown in the same vineyard in different plant sections during the growing season. Using high-throughput NGS-based metagenomic analysis targeting the ITS2 and the V4 regions of the 16S ribosomal gene of fungal and bacterial communities, respectively, weassessed the impact of grapevine genotypes on microbial assemblages in various parts of the phyllosphere. The results indicated that different phyllosphere tissues display high microbial diversity regardless of the cultivars’ identity and use. The selected three phyllosphere parts representing three distinct phenological stages, namely bark and bud, berry set, and fruit harvest, had almost a similar number of fungal OTUs, while a difference was recorded for the bacterial species. The fruit harvest stage hosted the highest number of bacterial OTUs, whereas the bark and bud stage contained the lower. Bacterial dominant phyla were Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes, and the genera were Gluconacetobacter, Erwinia, Gluconobacter, Zymobacter, Buchnera, Pseudomonas, Pantoea, Hymenobacter, Pedobacter, Frigoribacterium, Sphingomonas, and Massilia. For fungi, the dominant phyla were Ascomycota and Basidiomycota, and the genera were Aureobasidium, Cladosporium, Alternaria, Aspergillus, Davidiella, Phoma, Epicoccum, Rhodosporidium, Glomerella, Botryosphaeria, Metschnikowia, Issatchenkia, and Lewia. Both the genotype of the cultivar and the phenological stage appeared to considerably impact the shape of microbial diversity and structure within the same terroir. Taken together, these results indicate that microbiome analysis could be proved to be an important molecular fingerprint of cultivars and provide an efficient management tool for the traceability of wine and grape end products. Moreover, the unique identity of cultivars’ microbial signatures highlights the need for further development of precision management to support viticulture sustainability in the face of climate change.
Increasing the Oxidative Stability of the Wafer Lipid Fraction with Fruit Extract during Storage
Authors: Bełkowska Liliana , Muzolf-Panek Małgorzata , Islam Mahbuba , Tomaszewska-Gras Jolanta
Published: December 2022

Confectionary products are increasingly popular among consumers. However, since they usually have a long shelf life (about 12 months), their oxidative stability during long-term storage becomes a significant issue. Thus, the aim of this study was to investigate the effect of addition of commercially available fruit extract on the oxidative stability of lipid fraction, extracted from wafers sheets stored 13 months at 18 °C. For this purpose, the oxidation induction times (OIT) were determined by using isothermal differential scanning calorimetry (DSC). Conjugated diene content (CD) and 2,2-diphenyl-1-pikrylhydrazyl (DPPH) antioxidant activity were also monitored. All results obtained showed that the fruit extract addition slowed down effectively the peroxidation process of lipid fraction of wafer sheets. The rate of OIT and CD changes during the first six months of storage were about two times lower for the sample with the extract (LWE) than for the control (LWS). The DPPH antioxidant activity of LWE was higher than for the LWS sample until the 8th month of storage. It was stated that fruit extract effectively enhanced the oxidative stability of lipid fraction of wafers up until the 10th month of storage. After this period, CD values increased significantly for LWS and LWE samples, while at the same time there were no significant differences in OIT and DPPH values between both samples (p > 0.05).