bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of Heating Methods and Xylose to Increase Rumen Undegradable Protein of Alternative Protein Sources: 2) Cottonseed Meal
Authors: Molosse Vitor L. , Pereira David A. B. , Rigon Fernanda , Loregian Kalista E. , Magnani Elaine , Marcondes Marcos I. , Branco Renata H. , Benedeti Pedro D. B. , Paula Eduardo M.
Published: December 2022

The ruminal kinetics of protein sources may be changed by heat and sugar treatments. Thus, these processing methods may be used as alternatives to increase beef-cattle diets’ rumen undegradable protein (RUP). We aimed to evaluate the effects of processing cottonseed meals with autoclave, conventional, and microwave ovens, with and without using xylose, on the ruminal kinetics degradation parameters and intestinal digestibility (ID). In situ studies were conducted, and each sample was incubated in the rumen to determine dry matter (DM) and crude protein (CP) rumen degradation kinetics. In vitro studies were also conducted to evaluate ID. The control treatment had a greater soluble fraction for DM and CP than processed cottonseed meals (p < 0.05). The addition of xylose decreased both DM and CP water-soluble fractions (fraction A) of cottonseed meal heated in a conventional oven (p < 0.05). Compared to the control, we observed a decrease in effective degradability and increased RUP for all processed methods (p < 0.05). Furthermore, conventional and microwave ovens showed greater ID than the control. Moreover, xylose-treated groups heated in the autoclave and conventional ovens had greater ID than xylose-untreated cottonseed meal. Under these experimental conditions, cottonseed RUP was increased by the evaluated processing methods.
Does Stocking Density Affect Growth Performance and Hematological Parameters of Juvenile Olive Flounder Paralichthys olivaceus in a Recirculating Aquaculture System?
Authors: Seo Junhyuk , Park Jeonghwan
Published: December 2022

Olive flounder Paralichthys olivaceus is a representative culture species in South Korea. Recirculating aquaculture systems (RASs) have received increased attention because they can provide sustainable and environmentally friendly productivity. However, to maintain economic sustainability, the system generally requires high productivity, achieved through a high stocking density, which compromises animal welfare. The reduction in growth based on the stocking density may be due to the social hierarchy resulting from the growth suppression of subordinate individuals. Species, size, culture systems, and other management regimes can affect the social hierarchy. Therefore, a more practical approach must be taken to adjust the stocking density for a particular fish species and fish size in a specific culture system. This study investigated the effect of stocking density on juvenile olive flounder in an RAS. Juvenile olive flounder (61.0 ± 0.3 g) were initially stocked at 3.29, 4.84, 7.14, and 8.56 kg/m2 (T1, T2, T3, and T4, respectively). After 8 weeks, growth performance, in terms of feed conversion, specific growth rate, and daily feed intake rate, was measured. In addition, the blood levels of insulin-like growth factor (IGF-1), growth hormone, glucose, glutamic oxaloacetic transaminase, and glutamic pyruvic transaminase and the whole-body composition were evaluated as stress indicators. Growth performance increased as stocking density increased, but fish at the highest stocking density showed signs of growth reduction toward the end of the experiment. In addition, as stocking density increased, IGF-1 decreased, and cortisol increased. The whole-body protein level was significantly lower in T4 compared with the other treatments. Olive flounder seemed to tolerate a stocking density up to 20.16 kg/m2. Based on the growth performance, hematological response, and whole-body composition results in the present study, a final stocking density of 20 kg/m2 (from the initial stocking density of 4.84–7.14 kg/m2) may be desirable for juvenile olive flounder in an RAS for fish weighing ~60–180 g.
A Descriptive Study on the Carcass, Muscle, and Offal Yields of the Plains Zebra (Equus quagga) Harvested in Two Seasons
Authors: Myburgh Angelique , Lambrechts Helet , Hoffman Louwrens Christiaan
Published: December 2022

This study presents descriptive data on the meat and offal production of Plains zebras harvested in the winter (n = 8) and summer (n = 12) seasons, at different respective locations in the Western Cape Province of South Africa. The cold dressing percentages were numerically higher for the winter (58.0 ± 0.60%) than for the summer-harvested animals (56.60 ± 0.70%). Heavier internal offal yields were reported for the winter-harvested group (70.76 ± 21.8 kg) compared to the summer-harvested animals (66.13 ± 3.78 kg). As harvest season had no influence, pooled data of the percentage contribution of each muscle to cold carcass weight indicated that the Longissimus et lumborum (3.5 ± 0.18%), semimembranosus (1.6 ± 0.04%), biceps femoris (2.7 ± 0.05%) and semitendinosus (0.9 ± 0.02%) muscles differed significantly in their respective contributions to cold carcass weight. No significant differences were recorded between the contribution of the infraspinatus (0.6 ± 0.02%), supraspinatus (0.4 ± 0.03%) and psoas major (0.6 ± 0.02%) muscles. Carcass and muscle yields, as well as low-cost protein offal yields from this study indicate that the Plains zebra has the potential to be used and distributed as an alternative protein source.
Binding of Equine Seminal Lactoferrin/Superoxide Dismutase (SOD-3) Complex Is Biased towards Dead Spermatozoa
Authors: Alghamdi Abdorrahman S. , Fedorka Carleigh E. , Scoggin Kirsten E. , Esteller-Vico Alejandro , Beatty Kaylin , Davolli Gabriel , Ball Barry A. , Troedsson Mats H. T.
Published: December 2022

Sperm-neutrophil binding is an important facet of breeding and significantly impacts fertility. While a specific seminal plasma protein has been found to reduce this binding and improve fertility (CRISP-3), additional molecule(s) appear to promote binding between defective sperm and neutrophils. Recent work has suggested one of these proteins is lactoferrin (LF), an 80 kDa iron-binding protein found throughout the body, but the purity of the protein was not confirmed. It is unknown if LF binds to sperm selectively based on viability, and if receptors for LF are located on equine sperm. To evaluate this, we attempted to purify equine seminal LF from five stallions (n = 5), biotinylate LF, and evaluate potential binding site(s) on spermatozoa. LF was consistently associated with superoxide dismutase (SOD-3), and all attempts to separate the two proteins were unsuccessful. Flow cytometric and microscopic analyses were used to compare LF/SOD-3 binding to viable and nonviable spermatozoa. Additionally, various methods of biotinylation were assessed to optimize this methodology. Biotinylation of seminal plasma protein was an effective and efficient method to study seminal plasma protein properties, and the binding site for LF/SOD-3 was found to be broadly localized to the entire sperm cell surface as well as selective towards nonviable/defective sperm. Although we were not able to determine if the binding to equine spermatozoa was through LF or SOD-3, we can conclude that equine seminal LF is tightly bound to SOD-3 and this protein complex binds selectively to nonviable spermatozoa, possibly to mark them for elimination by neutrophil phagocytosis.
Sperm Cryopreservation as a Tool for Amphibian Conservation: Production of F2 Generation Offspring from Cryo-Produced F1 Progeny
Authors: Lampert Shaina S. , Burger Isabella J. , Julien Allison R. , Gillis Amanda B. , Kouba Andrew J. , Barber Diane , Kouba Carrie K.
Published: December 2022

Sperm cryopreservation and biobanking are emerging as tools for supporting genetic management of small and threatened populations in amphibian conservation programs. However, there is little to no evidence demonstrating reproductive maturity and viability of offspring generated with cryopreserved sperm, potentially limiting widespread integration of these technologies. The purpose of this report is to demonstrate that amphibian sperm can be cryopreserved and thawed to successfully produce individuals of an F1 generation that can reach adulthood and reproductive maturity, to generating viable gametes and an F2 generation. Species-specific exogenous hormones were administered to both F0 and F1 adults to stimulate spermiation and oviposition in the eastern tiger salamander (Ambystoma tigrinum), dusky gopher frog (Lithobates sevosa), and Puerto Rican crested toad (Peltophryne lemur). Sperm cells collected non-lethally from F0 adults were cryopreserved, thawed, and used for in vitro fertilization (IVF) to produce F1 offspring. Individuals of the F1 generation are shown to reach adulthood, express viable gametes, and produce offspring through facilitated breeding, or IVF. The production of amphibian F2 generations shown here demonstrates that amphibian sperm collected non-lethally can be banked and used to generate reproductively viable animals of subsequent generations, thus maintaining valuable genetic linages and diversity in threatened amphibian species. The incredible value that cryopreservation of sperm has for long-term genetic management aids in the sustainability of both in situ and ex situ conservation efforts for this taxon.
Development of 3D-Printed Collagen Scaffolds with In-Situ Synthesis of Silver Nanoparticles
Authors: Municoy Sofia , Antezana Pablo Edmundo , Bellino Martín Gonzalo , Desimone Martín Federico
Published: December 2022

UV-irradiation method has grown as an alternative approach to in situ synthetize silver nanoparticles (AgNPs) for avoiding the use of toxic reducing agents. In this work, an antimicrobial material by in situ synthesizing AgNPs within 3D-printed collagen-based scaffolds (Col-Ag) was developed. By modifying the concentration of AgNO3 (0.05 and 0.1 M) and UV irradiation time (2 h, 4 h, and 6 h), the morphology and size of the in situ prepared AgNPs could be controlled. As a result, star-like silver particles of around 23 ± 4 μm and spherical AgNPs of 220 ± 42 nm were obtained for Ag 0.05 M, while for Ag 0.1 M cubic particles from 0.3 to 1.0 μm and round silver precipitates of 3.0 ± 0.4 μm were formed in the surface of the scaffolds at different UV irradiation times. However, inside the material AgNPs of 10–28 nm were obtained. The DSC thermal analysis showed that a higher concentration of Ag stabilizes the 3D-printed collagen-based scaffolds, while a longer UV irradiation interval produces a decrease in the denaturation temperature of collagen. The enzymatic degradation assay also revealed that the in situ formed AgNPs act as stabilizing and reinforcement agent which also improve the swelling capacity of collagen-based material. Finally, antimicrobial activity of Col-Ag was studied, showing high bactericidal efficiency against Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria. These results showed that the UV irradiation method was really attractive to modulate the size and shape of in situ synthesized AgNPs to develop antimicrobial 3D-printed collagen scaffolds with different thermal, swelling and degradation properties.
Structure–Activity Relationship Studies of Substitutions of Cationic Amino Acid Residues on Antimicrobial Peptides
Authors: Takada Mayu , Ito Takahito , Kurashima Megumi , Matsunaga Natsumi , Demizu Yosuke , Misawa Takashi
Published: December 2022

Antimicrobial peptides (AMPs) have received considerable attention as next-generation drugs for infectious diseases. Amphipathicity and the formation of a stabilized secondary structure are required to exert their antimicrobial activity by insertion into the microbial membrane, resulting in lysis of the bacteria. We previously reported the development of a novel antimicrobial peptide, 17KKV, based on the Magainin 2 sequence. The peptide was obtained by increasing the amphipathicity due to the replacement of amino acid residues. Moreover, we studied the structural development of 17KKV and revealed that the secondary structural control of 17KKV by the introduction of non-proteinogenic amino acids such as α,α-disubstituted amino acids or side-chain stapling enhanced its antimicrobial activity. Among them, peptide 1, which contains 2-aminobutyric acid residues in the 17KKV sequence, showed potent antimicrobial activity against multidrug-resistant Pseudomonus aeruginosa (MDRP) without significant hemolytic activity against human red blood cells. However, the effects of cationic amino acid substitutions on secondary structures and antimicrobial activity remain unclear. In this study, we designed and synthesized a series of peptide 1 by the replacement of Lys residues with several types of cationic amino acids and evaluated their secondary structures, antimicrobial activity, hemolytic activity, and resistance against digestive enzymes.
Evaluation of Antimicrobial Resistance of Different Phylogroups of Escherichia coli Isolates from Feces of Breeding and Laying Hens
Authors: Pais Sandra , Costa Mariana , Barata Ana Rita , Rodrigues Lígia , Afonso Isabel M. , Almeida Gonçalo
Published: December 2022

Animal and food sources are seen as a potential transmission pathway of multi-drug resistance (MDR) micro-organisms to humans. Escherichia. coli is frequently used as an indicator of fecal contamination in the food industry and known as a reservoir of antimicrobial resistance genes (ARGs). Microbial contamination as a major outcome for the poultry and egg industry and is a serious public health problem. In the present study we performed the quantification of β-glucoronidase positive E. coli in 60 fecal samples of breeding and laying hens collected in Portugal in 2019. Phylogenetic and pathotypic characterization, antimicrobial susceptibility, and detection of resistant extended-spectrum β-lactamase (ESBL) genes were assessed. The phylogenetic and pathogenic characterization and detection of ESBL genes were assessed by real-time PCR and antimicrobial susceptibility was evaluated using the disk diffusion method. Overall, E. coli quantification was 6.03 log CFU/g in breeding hens and 6.02 log CFU/g in laying hens. The most frequent phylogroups were B1. None of the isolates was classified as diarrheagenic E. coli (DEC). In total, 57% of the isolates showed MDR and 3.8% were positive for ESBL. Our study highlights that consumers may be exposed to MDR E. coli, presenting a major hazard to food safety and a risk to public health.
Effects of In Vitro Digestion on the Antioxidant Activity of Three Phenolic Extracts from Olive Mill Wastewaters
Authors: Mercatante Dario , Ansorena Diana , Taticchi Agnese , Astiasarán Iciar , Servili Maurizio , Rodriguez-Estrada Maria Teresa
Published: December 2022

The aim of this study was to assess the impact of in vitro digestion on the antioxidant activity of three extracts rich in phenols (two purified organic extracts (A20, A21) and one powdered extract stabilized with maltodextrins (SP)) obtained from olive mill wastewaters (OMWW). The content and composition of phenols and antioxidant activity was determined before and after in vitro digestion. The phenol content of the A20 and A21 samples were higher (>75%) than that of the SP sample before in vitro digestion. After the entire in vitro digestion, 89.3, 76.9, and 50% loss of phenols was found in A20, A21 and SP, respectively. ABTS•+ and ORAC values decreased during in vitro digestion of A20 and A21 samples, while they remained almost constant in SP. IC50 increased during digestion of A20 and A21, evidencing a loss of antioxidant capacity after the intestinal phase; an opposite IC50 trend was noted in SP, confirming the protective role of maltodextrins. For these reasons, SP represents a promising formulation to be used in the food field.
Extract of Wheatgrass and Aronia Mixture Ameliorates Atopic Dermatitis-Related Symptoms by Suppressing Inflammatory Response and Oxidative Stress In Vitro and In Vivo
Authors: Lee Ji-Hyun , Lim Ji-Ye , Jeon Yong-Deok , Yun Dae-Ho , Lee Young-Mi , Kim Dae-Ki
Published: December 2022

Atopic dermatitis is regulated by the production of pro-inflammatory cytokines and chemokines via the nuclear factor kappa B or mitogen-activated protein kinase signaling pathways, as well as, the release of oxidative stress-related factors via the NF-E2 p45-related factor 2 signaling pathway. Both wheatgrass (Triticum aestivum L., TA) and aronia (Aronia melanocarpa, AR) are known for their anti-inflammatory and antioxidant properties, however, the anti-inflammatory and antioxidant effects of TA and AR (TAAR) mixture extract have not been elucidated in an atopic dermatitis model. In this study, we assessed the inhibitory effects and underlying molecular mechanism of TAAR extract against lipopolysaccharide-induced inflammation and tumor necrosis factor-α/interferon-γ-induced inflammation and oxidative stress in vitro. We also investigated the alleviating effect of TAAR extract on DNCB-induced atopic dermatitis-like skin lesions in mice in vivo. We found that TAAR extract treatment inhibited inflammatory mediators in both RAW 264.7 cells and HaCaT cells, and increased the expression of oxidative stress defense enzymes in HaCaT cells. Furthermore, treatment of the DNCB-induced mouse model with TAAR extract ameliorated the overall symptoms of atopic dermatitis. Therefore, TAAR extract as a novel natural therapeutic agent may be used for the treatment of atopic dermatitis.
Generating Digital Twins for Path-Planning of Autonomous Robots and Drones Using Constrained Homotopic Shrinking for 2D and 3D Environment Modeling
Authors: Denk Martin , Bickel Sebastian , Steck Patrick , Götz Stefan , Völkl Harald , Wartzack Sandro
Published: December 2022

A digital twin describes the virtual representation of a real process. This twin is constantly updated with real data and can thus control and adapt the real model. Designing suitable digital twins for path planning of autonomous robots or drones is often challenging due to the large number of different dynamic environments and multi-task and agent systems. However, common path algorithms are often limited to two tasks and to finding shortest paths. In real applications, not only a short path but also the width of the passage with a path as centered as possible are crucial, since robotic systems are not ideal and require recalibration frequently. In this work, so-called homotopic shrinking is used to generate the digital twin, which can be used to extract all possible path proposals including their passage widths for 2D and 3D environments and multiple tasks and robots. The erosion of the environment is controlled by constraints such that the task stations, the robot or drone positions, and the topology of the environment are considered. Such a deterministic path algorithm can flexibly respond to changing environmental conditions and consider multiple tasks simultaneously for path generation. A distinctive feature of these paths is the central orientation to the non-passable areas, which can have significant benefits for worker and patient safety. The method is tested on 2D and 3D maps with different tasks, obstacles, and multiple robots. For example, the robust generation of the digital twin for a maze and also the dynamic adaptation in case of sudden changes in the environment is covered. This variety of use cases and the comparison with alternative methods result in significant advantages, such as high robustness, consideration of multiple targets, and high safety distances to obstacles and areas that cannot be traversed. Finally, it was shown that the environment for the digital twin can be reduced to reasonable paths by constrained shrinking, both for real 2D maps and for complex virtual 2D and 3D maps.
Vision-Guided Object Recognition and 6D Pose Estimation System Based on Deep Neural Network for Unmanned Aerial Vehicles towards Intelligent Logistics
Authors: Luo Sijin , Liang Yu , Luo Zhehao , Liang Guoyuan , Wang Can , Wu Xinyu
Published: December 2022

Unmanned aerial vehicle (UAV) express delivery is facing a period of rapid development and continues to promote the aviation logistics industry due to its advantages of elevated delivery efficiency and low labor costs. Automatic detection, localization, and estimation of 6D poses of targets in dynamic environments are key prerequisites for UAV intelligent logistics. In this study, we proposed a novel vision system based on deep neural networks to locate targets and estimate their 6D pose parameters from 2D color images and 3D point clouds captured by an RGB-D sensor mounted on a UAV. The workflow of this system can be summarized as follows: detect the targets and locate them, separate the object region from the background using a segmentation network, and estimate the 6D pose parameters from a regression network. The proposed system provides a solid foundation for various complex operations for UAVs. To better verify the performance of the proposed system, we built a small dataset called SIAT comprising some household staff. Comparative experiments with several state-of-the-art networks on the YCB-Video dataset and SIAT dataset verified the effectiveness, robustness, and superior performance of the proposed method, indicating its promising applications in UAV-based delivery tasks.
Deep Learning Models Applied to Prediction of 5G Technology Adoption
Authors: Zamzami Ikhlas Fuad
Published: December 2022

The issue addressed by this research study is the public’s scepticism about the benefits of adopting 5G technology. Some have even gone so far as to say that the technology can be harmful to people, while others are still looking for reassurance. This is why it is crucial to comprehend the primary factors that will affect the spread of 5G networks. The method used for this heavily relies on a deep learning algorithm. Channel metrics, context metrics, cell metrics, and throughput data are the conceptualized variables that will serve as the primary indicators for determining the adoption of 5G technology. Three deep learning models—deep reinforcement (DR), long-short term memory (LSTM), and a convolutional neural network (CNN)—were applied. The results show that the DR model and the CNN model are the most effective at predicting the elements that would affect 5G adoption. Despite the fact that LSTM models appear to have a high degree of accuracy, the quality of the data they output is quite poor. However, this is the case even when the models appear to be rather accurate. The logical inferences drawn from these findings show that the DR model and the CNN model’s applicability to the problem of predicting the rate at which 5G will be adopted can be put into practice with a high degree of accuracy. The novelty of this study is in its emphasis on using channel metrics, context metrics, cell metrics, and throughput data to focus on predictions for the development of 5G networks themselves and on the generation of the elements that determine the adoption of 5G. Previous efforts in the literature failed to establish methods for adopting 5G technology related to the criteria considered in this study; hence, this research fills a gap.
Effect of Human Hair Fibers on the Performance of Concrete Incorporating High Dosage of Silica Fume
Authors: Akbar Muhammad , Umar Tariq , Hussain Zahoor , Pan Huali , Ou Guoqiang
Published: December 2022

Sustainable development in structural materials is currently getting attention all around the world. Solid waste, building and demolition waste, natural resources, and their reuse are the most obvious strategies for achieving sustainability in the construction industry. Solid waste human hair fiber (HHF) with a diameter of 70 µm and a length of 30–40 mm is used as a fiber, having a dosage of 0%, 1%, 1.5%, 2%, 3%, 4%, and 5%, while silica fume (SF) with a dosage of 0%, 5%, 10%, 15%, 20%, 25%, and 30% is used as a cement substitute. A drop of 50 mm to 75 mm slump was witnessed for the water–cement ratio used in the M20 mix design of concrete. The concrete’s mechanical properties, such as compressive, split tensile, and flexural strength, were determined after 28 days of water curing. The concept of the response surface methodology (RSM) for optimizing human hair fiber concrete (HHFC) and SF substitution was used, which was validated by the polynomial work expectation. The model is statistically significant when the fluctuation of the analysis of variance (ANOVA) is analyzed using a p-value with a significance level of 0.05. The test results showed that the use of 2% human hair as fiber and 15% SF as a cementitious additive or cement replacement considerably improved the strength of concrete. The compressive, flexural, and split tensile strengths of HHFC improved by 14%, 8%, and 7%, respectively, which shows the significance of human hair and the partial replacement of cement with SF. Moreover, SEM analysis was carried out to study the microstructure of the concrete matrix.
Training Artificial Intelligence Algorithms with Automatically Labelled UAV Data from Physics-Based Simulation Software
Authors: Boone Jonathan , Goodin Christopher , Dabbiru Lalitha , Hudson Christopher , Cagle Lucas , Carruth Daniel
Published: December 2022

Machine-learning (ML) requires human-labeled “truth” data to train and test. Acquiring and labeling this data can often be the most time-consuming and expensive part of developing trained models of convolutional neural networks (CNN). In this work, we show that an automated workflow using automatically labeled synthetic data can be used to drastically reduce the time and effort required to train a machine learning algorithm for detecting buildings in aerial imagery acquired with low-flying unmanned aerial vehicles. The MSU Autonomous Vehicle Simulator (MAVS) was used in this work, and the process for integrating MAVS into an automated workflow is presented in this work, along with results for building detection with real and simulated images.
Static Compressive Properties of Polypropylene Fiber Foam Concrete with Concave Hexagonal Unit Cell
Authors: Yin Zhiqiang , Shao Zhenguo , Qi Chao , Wu Haoyuan , Wang Jianen , Gao Lulu
Published: December 2022

For the purpose of studying the influence of fiber on the negative Poisson’s ratio effect of foam concrete, a concave hexagonal unit cell structure of polypropylene fiber foam concrete was proposed. The effects of different fiber volume contents on the structural mechanical parameters, Poisson’s ratio, and energy absorption capacity of the unit cells were studied by static compression of concave hexagonal unit cells and cube specimens. The results show that the compressive strength of foam concrete is reduced by adding polypropylene fiber, and the peak stress of concave hexagonal unit cells decreases less rapidly than that of cube specimens. The proper amount of polypropylene fiber can enhance the deformation ability of the unit cells in foam concrete, and the Poisson’s ratio of the unit cells in foam concrete with 1.5% fiber content is the lowest. In the process of failure of concave hexagonal unit cells, the failure phenomenon is mainly concentrated on the concave surfaces on both sides, and the cracks are distributed in the form of “upper left and lower right” or “lower left and upper right”. When the content of polypropylene fiber is 0.5%, the total energy absorbed by the concave hexagonal cells in the compression deformation process increases by 12.98%.
Prefetching Method for Low-Latency Web AR in the WMN Edge Server
Authors: Choi Seyun , Hong Sukjun , Kim Hoijun , Lee Seunghyun , Kwon Soonchul
Published: December 2022

Recently, low-latency services for large-capacity data have been studied given the development of edge servers and wireless mesh networks. The 3D data provided for augmented reality (AR) services have a larger capacity than general 2D data. In the conventional WebAR method, a variety of data such as HTML, JavaScript, and service data are downloaded when they are first connected. The method employed to fetch all AR data when the client connects for the first time causes initial latency. In this study, we proposed a prefetching method for low-latency AR services. Markov model-based prediction via the partial matching (PPM) algorithm was applied for the proposed method. Prefetched AR data were predicted during AR services. An experiment was conducted at the Nowon Career Center for Youth and Future in Seoul, Republic of Korea from 1 June 2022 to 31 August 2022, and a total of 350 access data points were collected over three months; the prefetching method reduced the average total latency of the client by 81.5% compared to the conventional method.
An Aeromagnetic Compensation Algorithm Based on Radial Basis Function Artificial Neural Network
Authors: Zhou Shuai , Yang Changcheng , Su Zhenning , Yu Ping , Jiao Jian
Published: December 2022

Aeromagnetic exploration is a magnetic exploration method that detects changes of the earth’s magnetic field by loading a magnetometer on an aircraft. With the miniaturization of magnetometers and the development of unmanned aerial vehicles (UAV) technology, UAV aeromagnetic surveying plays an increasingly important role in mineral exploration and other fields due to its advantages of low cost and safety. However, in the process of aeromagnetic measurement data, due to the ferromagnetic material of the aircraft itself and the change of flight direction and attitude, magnetic field interference will occur and affect the measurement of the geomagnetic field by the magnetometer. The work of aeromagnetic compensation is to compensate for this part of the magnetic interference and improve the magnetic measurement accuracy of the magnetometer. This paper focused on the problems of UAV aeromagnetic survey data processing and improved the accuracy of UAV based aeromagnetic data measurement. Based on the Tolles–Lawson model, a numerical simulation experiment of magnetic interference of UAV-based aeromagnetic data was carried out, and a radial basis function (RBF) artificial neural network (ANN) algorithm was proposed for the first time to compensate the aeromagnetic data. Compared with classical backpropagation (BP) ANN, the test results of the synthetic data and real measured magnetic data showed that the RBF-ANN has higher compensation accuracy and stronger generalization ability.
How Different Load Carriage Scenarios Impact the Gait in Police Officers
Authors: Kasović Mario , Bilobrk Mate , Sladin Damir , Štefan Andro , Štefan Lovro
Published: December 2022

The main purpose of this study was to examine the effects on gait of carrying different standardized police loads. In this cross-sectional study, we randomly recruited 30 special police officers. Spatiotemporal and kinetic gait changes were evaluated by using the Zebris FDM pressure platform, when load carriage ranged from 5 to 45 kg. Heavier loading conditions significantly increased ground reaction forces and plantar pressures for both feet beneath the forefoot, midfoot, and hindfoot regions of the foot. However, as load increased there were no significant changes in spatiotemporal gait parameters. This study shows that heavier loads carried by special police officers significantly increase ground reaction forces and plantar pressures under different foot regions. Thus, special interventions aiming to lower kinetic gait parameters throughout a different ergonomics and design of standardized equipment should be considered.
Model Predictive Control of Quadruped Robot Based on Reinforcement Learning
Authors: Zhang Zhitong , Chang Xu , Ma Hongxu , An Honglei , Lang Lin
Published: December 2022

For the locomotion control of a legged robot, both model predictive control (MPC) and reinforcement learning (RL) demonstrate powerful capabilities. MPC transfers the high-level task to the lower-level joint control based on the understanding of the robot and environment, model-free RL learns how to work through trial and error, and has the ability to evolve based on historical data. In this work, we proposed a novel framework to integrate the advantages of MPC and RL, we learned a policy for automatically choosing parameters for MPC. Unlike the end-to-end RL applications for control, our method does not need massive sampling data for training. Compared with the fixed parameters MPC, the learned MPC exhibits better locomotion performance and stability. The presented framework provides a new choice for improving the performance of traditional control.
E-Eye Solution for the Discrimination of Common and Niche Celery Ecotypes
Authors: Biancolillo Alessandra , Foschi Martina , D’Archivio Angelo Antonio
Published: December 2022

Celery (Apium graveolens L.) is a well- known plant and at the basis of the culinary tradition of different populations. In Italy, several celery ecotypes, presenting unique peculiarities, are grown by small local producers, and they need to be characterized, in order to be protected and safeguarded. The present work aims at developing a fast and non-destructive method for the discrimination of a common celery (the "Elne" celery) from a typical celery of Abruzzo (Central Italy). The proposed strategy is based on the use of an e-eye tool which allows the collection of images used to infer colorgrams. Initially, a principal component analysis model was used to investigate the trends and outliers in the data. Then, the classification between the common celery (Elne class) and celery from Torricella Peligna (Torricella class) was achieved by a discriminant analysis, conducted by sequential preprocessing through orthogonalization (SPORT) and sequential and orthogonalized covariance selection (SO-CovSel) and by a class-modelling method called soft independent modelling of class analogies (SIMCAs). Among these, the highest accuracy was provided by the strategies, based on the discriminant classifiers, both of which provided a total accuracy of 82% in the external validation.
Comparison of the Gill Microbiome of Retail Oysters from Two Geographical Locations Exhibited Distinct Microbial Signatures: A Pilot Study for Potential Future Applications for Monitoring Authenticity of Their Origins
Authors: Singh Prashant , Williams David , Velez Frank J. , Nagpal Ravinder
Published: December 2022

The oyster industry is a significant component of United States aquaculture and is vulnerable to various food frauds. In addition to species substitution, mislabeling of oyster geographical origin is performed for economic gains. The geographical origin misrepresentations are performed to claim a famed region of origin known for its unique flavor profile. DNA barcoding is the gold standard method for identifying seafood species but has limited resolution to the species level. This pilot study was conducted to characterize and compare the oyster gill microbiome as an alternative approach for tracking oysters’ origin. Commercially available raw east coast oysters (Crassostrea virginica) from two distinct geographical locations were purchased. Genomic DNA isolated from the gills was processed for microbiome analysis. The data revealed distinct microbiome signatures among the two sample sets. Oysters from Louisiana showed the presence of eighteen unique bacterial genera, whereas Maryland oysters showed a higher abundance of twelve genera. Findings from this study demonstrate the applicability of microbiome analysis as an emerging alternative approach for identifying geographical origin misrepresentations.
WRF Physics Ensemble Performance Evaluation over Continental and Coastal Regions in Germany
Authors: Stergiou Ioannis , Tagaris Efthimios , Sotiropoulou Rafaella-Eleni P.
Published: December 2022

WRF is used to simulate eight extreme precipitation events that occurred over the regions of Schleswig–Holstein and Baden–Wurttemberg in Germany. The events were chosen from the German Weather Service (DWD) catalog and exceeded the DWD’s warning level 3 (i.e., rainfall > 40 mm/h). A two-way nesting approach is used with 9 and 3 km spatial resolutions. Initial and boundary conditions are obtained from the ERA5 dataset at 0.25° × 0.25°. To model each event, thirty different parameterization configurations were used, accounting for all possible combinations of five microphysics (MP), three cumulus (CU), and two planetary boundary layer (PBL) parameterization methods, yielding a total of 240 simulations. TOPSIS multicriteria analysis technique is employed to determine the performance skill of each setup and rank them, using six categorical and five statistical metrics. Resolution increase from 9 to 3 km did not improve forecasting accuracy temporally or in intensity. According to TOPSIS ranking, when treating each event individually, the ideal parameterizations combination is spatiotemporally dependent, with certain members ranking higher. When all events are considered, the Morrison double-moment MP–Grell–Freitas CU–YSU PBL combination works best with a frequency of occurrence in the top five performing scenarios of 30%, 47.5%, and 57.5% respectively.
Atmospheric Deposition of Lead and Cadmium in a Central European Country over the Last Three Decades
Authors: Hůnová Iva , Kurfürst Pavel , Schreiberová Markéta , Vlasáková Leona , Škáchová Hana
Published: December 2022

Lead (Pb) and cadmium (Cd) levels in ambient air were explored due to their toxicity and deleterious environmental effects. The aim of this study was to assess the time tendencies and spatial changes in Pb and Cd atmospheric deposition in a Central European country with a long history of ambient air pollution. We used measured data on precipitation chemistry and ambient air pollutant concentrations in the Czech Republic (CR) obtained within a nation-wide monitoring network. Our analysis is based on spatial patterns of annual wet-only and dry deposition fluxes constructed for 1996–2021. The results indicated that both Pb and Cd deposition over the CR during the last three decades decreased substantially, about 10 times, the absolute values for Cd being one order of magnitude lower than those for Pb. The wet-only deposition pathway dominated over the dry deposition pathway. This trend reflects the heavy metal (HM) emission reductions in the CR and neighboring countries and is in line with decreasing trends in ambient air HM concentrations in Europe. The spatial patterns showed that the northern industrial portions of the CR were loaded more as compared to the southern parts, and that the extension of affected regions has recently decreased substantially.
Application of the Methodology of Multi-Valued Logic Trees with Weighting Factors in the Optimization of a Proportional Valve
Authors: Deptuła Adam , Stosiak Michał , Cieślicki Rafał , Karpenko Mykola , Urbanowicz Kamil , Skačkauskas Paulius , Deptuła Anna Małgorzata
Published: December 2022

Hydraulic valves are used to determine the set values of hydraulic quantities (flow rate, pressure, or pressure difference) in a hydraulic system or its part. This is achieved through the appropriate throttling of the stream flowing through the valve, which is automatically set by the operator (e.g., opening the throttle valve). The procedures for determining its static and dynamic properties were described using the example of modeling a two-stage proportional relief valve. Subsequently, the importance of the design and operational parameters was determined using multi-valued logic trees. Modeling began with the determination of equations describing the flow and movement of moving parts in a valve. Based on the equations, a numerical model was then created, e.g., in the Matlab/Simulink environment (R2020b). The static characteristics were obtained as the result of a model analysis of slow changes in the flow rate through the valve. Various coefficients of logical products have not been taken into account in the separable and common minimization processes of multi-valued logic equation systems in any available literature. The results of the model tests can be used to optimize several types of hydraulic valve constructions.
A Nonlinear System of Differential Equations in Supercritical Flow Spread Problem and Its Solution Technique
Authors: Evtushenko Sergej
Published: December 2022

A nonlinear system of differential equations in the problem of free flowing of supercritical flow is considered and a method of its solution is proposed. The analytical method is based on the introduction of the velocity hodograph plane and the obtaining of analytical solutions for the system of partial differential equations. It is pointed out that apart from being purely analytical, the potential flow model has a great practical demand due to its use as a base for the further research of the flow resistance forces. The proposed model can be developed by taking into account flow resistance and gradient, the bottom of the diverting channel flow. The theoretical results are complemented by numerical experiments and compared with experimental data.
Building Bridges: Unifying Design and Development Aspects for Advancing Non-Aqueous Redox-Flow Batteries
Authors: Kortekaas Luuk , Fricke Sebastian , Korshunov Aleksandr , Cekic-Laskovic Isidora , Winter Martin , Grünebaum Mariano
Published: December 2022

Renewable energy sources have been a topic of ever-increasing interest, not least due to escalating environmental changes. The significant rise of research into energy harvesting and storage over the years has yielded a plethora of approaches and methodologies, and associated reviews of individual aspects thereof. Here, we aim at highlighting a rather new avenue within the field of batteries, the (noaqueous) all-organic redox-flow battery, albeit seeking to provide a comprehensive and wide-ranging overview of the subject matter that covers all associated aspects. This way, subject matter on a historical perspective, general types of redox-flow cells, electrolyte design and function, flow kinetics, and cell design are housed within one work, providing perspective on the all-organic redox-flow battery in a broader sense.
Deep Learning for Detecting COVID-19 Using Medical Images
Authors: Liu Jia , Qi Jing , Chen Wei , Wu Yi , Nian Yongjian
Published: December 2022

The global spread of COVID-19 (also known as SARS-CoV-2) is a major international public health crisis [...]
Principal Component and Structural Element Analysis Provide Insights into the Evolutionary Divergence of Conotoxins
Authors: Kikuchi Akira Kio V. , Tayo Lemmuel L.
Published: December 2022

Predatory cone snails (Conus) developed a sophisticated neuropharmacological mechanism to capture prey, escape against other predators, and deter competitors. Their venom’s remarkable specificity for various ion channels and receptors is an evolutionary feat attributable to the venom’s variety of peptide components (conotoxins). However, what caused conotoxin divergence remains unclear and may be related to the role of prey shift. Principal component analysis revealed clustering events within diet subgroups indicating peptide sequence similarity patterns based on the prey they subdue. Molecular analyses using multiple sequence alignment and structural element analysis were conducted to observe the events at the molecular level that caused the subgrouping. Three distinct subgroups were identified. Results showed homologous regions and conserved residues within diet subgroups but divergent between other groups. We specified that these structural elements caused subgrouping in alpha conotoxins that may play a role in function specificity. In each diet subgroup, amino acid character, length of intervening amino acids between cysteine residues, and polypeptide length influenced subgrouping. This study provides molecular insights into the role of prey shift, specifically diet preference, in conotoxin divergence.
Analyzing Predominant Bacterial Species and Potential Short-Chain Fatty Acid-Associated Metabolic Routes in Human Gut Microbiome Using Integrative Metagenomics
Authors: Kingkaw Amornthep , Raethong Nachon , Patumcharoenpol Preecha , Suratannon Narissara , Nakphaichit Massalin , Keawsompong Suttipun , Roytrakul Sittiruk , Vongsangnak Wanwipa
Published: December 2022

Gut microbiome plays an essential role in host health, and there is interest in utilizing diet to modulate the composition and function of microbial communities. Copra meal hydrolysate (CMH) is commonly used as a natural additive to enhance health. However, the gut microbiome is largely unknown at species level and is associated with metabolic routes involving short-chain fatty acids (SCFAs). In this study, we aimed to analyze, using integrative metagenomics, the predominant species and metabolic routes involved in SCFAs production in the human gut microbiome after treatment with CMH. The effect of CMH treatment on the Thai gut microbiome was demonstrated using 16S rRNA genes with whole-metagenome shotgun (WMGS) sequencing technology. Accordingly, these results revealed that CMH has potentially beneficial effects on the gut microbiome. Twelve predominant bacterial species, as well as their potential metabolic routes, were involved in cooperative microbiome networks under sugar utilization (e.g., glucose, mannose, or xylose) and energy supply (e.g., NADH and ATP) in relation to SCFAs biosynthesis. These findings suggest that CMH may be used as a potential prebiotic diet for modulating and maintaining the gut microbiome. To our knowledge, this is the first study to reveal the predominant bacterial species and metabolic routes in the Thai gut microbiome after treatment with potential prebiotics.
Burden, Outcome, and Comorbidities of Extrahepatic Manifestations in Hepatitis C Virus Infection
Authors: Songtanin Busara , Nugent Kenneth
Published: December 2022

Hepatitis C virus (HCV) is a significant cause of chronic liver diseases worldwide and is associated with negative consequences, including cirrhosis, hepatic decompensation, hepatocellular carcinoma, and increased risk of mortality. In addition to liver-related morbidities, HCV is also associated with several extrahepatic manifestations, including mixed cryoglobulinemia, diabetes mellitus, cardiocerebrovascular disease, lymphoma, and autoimmune diseases. These non-liver-related complications of HCV increase the complexity of this disease and can contribute to the economic burden, morbidity, quality of life, and mortality throughout the world. Therefore, understanding how this virus can contribute to each extrahepatic manifestation is worth investigating. Currently, the advancement of HCV treatment with the advent of direct-acting anti-viral agents (DAAs) has led to a high cure rate as a result of sustained virologic response and tremendously reduced the burden of extrahepatic complications. However, HCV-associated extrahepatic manifestations remain a relevant concern, and this review aims to give an updated highlight of the prevalence, risk factors, associated burdens, and treatment options for these conditions.
Noncoding RNAs in Vascular Cell Biology and Restenosis
Authors: Efovi Denis , Xiao Qingzhong
Published: December 2022

In-stent restenosis (ISR), characterised by ≥50% re-narrowing of the target vessel, is a common complication following stent implantation and remains a significant challenge to the long-term success of angioplasty procedures. Considering the global burden of cardiovascular diseases, improving angioplasty patient outcomes remains a key priority. Noncoding RNAs (ncRNAs) including microRNA (miRNA), long noncoding RNA (lncRNA) and circular RNA (circRNA) have been extensively implicated in vascular cell biology and ISR through multiple, both distinct and overlapping, mechanisms. Vascular smooth muscle cells, endothelial cells and macrophages constitute the main cell types involved in the multifactorial pathophysiology of ISR. The identification of critical regulators exemplified by ncRNAs in all these cell types and processes makes them an exciting therapeutic target in the field of restenosis. In this review, we will comprehensively explore the potential functions and underlying molecular mechanisms of ncRNAs in vascular cell biology in the context of restenosis, with an in-depth focus on vascular cell dysfunction during restenosis development and progression. We will also discuss the diagnostic biomarker and therapeutic target potential of ncRNAs in ISR. Finally, we will discuss the current shortcomings, challenges, and perspectives toward the clinical application of ncRNAs.