bluuebunny/crossref_metadata_2025 huggingface dataset:
Prophylactic Feeding of Clostridium butyricum and Saccharomyces cerevisiae Were Advantageous in Resisting the Adverse Effects of Heat Stress on Rumen Fermentation and Growth Performance in Goats
Authors: Xue Ligang , Wang Dan , Zhang Fangyu , Cai Liyuan
Published: September 2022

This study aimed to investigate the effect of the prophylactic feeding of Clostridium butyricum (CB), Saccharomyces cerevisiae (SC), and their mixture before the onset of heat stress on the rumen fermentation and growth performance of goats, and subsequently, on heat stress status. Forty-eight male Macheng Black × Boer crossed goats (22.25 ± 4.26 kg) were divided into four groups—the control group (fed the basal diet), and the CB (0.05% CB added to the basal diet), SC (0.60% SC added to the basal diet), and Mix (0.05% CB and 0.60% SC added to the basal diet) groups—and fed for fourteen days. Then, these goats were kept in a heat stress environment (with a temperature–humidity index of 87.04) for fourteen days. Then, the parameters of rumen fermentation and growth performance were measured. The results showed that the pH values, the activities of cellulolytic enzymes (avicelase, CMCaes, cellobiase, and xylanase), and the concentrations of ammonia-N, total volatile fatty acid, acetic acid, propionic acid, and butyric acid were significantly increased (p < 0.05) in the rumens of the CB, SC, and Mix groups compared to those of the control group. Moreover, the average daily gain and the digestibility of dry matter, neutral detergent fiber, and acid detergent fiber were significantly increased (p < 0.05) in the CB, SC, and Mix groups compared to those of the control group. These results suggest that these two probiotics and their mixture effectively alleviate the adverse effects of heat stress on rumen fermentation and growth performance via prophylactic feeding.
The World of Organoids: Gastrointestinal Disease Modelling in the Age of 3R and One Health with Specific Relevance to Dogs and Cats
Authors: Csukovich Georg , Pratscher Barbara , Burgener Iwan Anton
Published: September 2022

One Health describes the importance of considering humans, animals, and the environment in health research. One Health and the 3R concept, i.e., the replacement, reduction, and refinement of animal experimentation, shape today’s research more and more. The development of organoids from many different organs and animals led to the development of highly sophisticated model systems trying to replace animal experiments. Organoids may be used for disease modelling in various ways elucidating the manifold host–pathogen interactions. This review provides an overview of disease modelling approaches using organoids of different kinds with a special focus on animal organoids and gastrointestinal diseases. We also provide an outlook on how the research field of organoids might develop in the coming years and what opportunities organoids hold for in-depth disease modelling and therapeutic interventions.
Assessment of Hematologic and Biochemical Parameters for Healthy Commercial Pigs in China
Authors: Zhang Shuo , Yu Bo , Liu Qing , Zhang Yongjin , Zhu Mengjin , Shi Liangyu , Chen Hongbo
Published: September 2022

Hematologic and biochemical data are useful for indicating disease diagnosis and growth performance in swine. However, the assessment of these parameters in healthy commercial pigs is rare in China. Thus, blood samples were collected from 107 nursery pigs and 87 sows and were analyzed for 25 hematologic and 14 biochemical variables. After the rejection of the outliers and the detection of the data distribution, the correlations between the blood parameters were analyzed and the hematologic/biochemical RIs were preliminarily established using the 95% percentile RI. Correlation analysis showed that albumin was the hub parameter among the blood parameters investigated, and genes overlapping with key correlated variables were discovered. Most of the hematologic and biochemical parameters were significantly different between nursery pigs and sows. The 95% RIs of white blood cells and red blood cells were 7.18–24.52 × 109/L and 5.62–7.84 × 1012/L, respectively, for nursery pigs, but 9.34–23.84 × 109/L and 4.98–8.29 × 1012/L for sows. The 95% RIs of total protein and albumin were 43.16–61.23 g/dL and 19.35–37.86 g/dL, respectively, for nursery pigs, but 64.96–88.68 g/dL and 31.91–43.28 g/dL for sows. In conclusion, our study highlights the variability in blood parameters between nursery pigs and sows and provides fundamental data for the health monitoring of commercial pigs in China.
Uncovering the Fecal Bacterial Communities of Sympatric Sika Deer (Cervus nippon) and Wapiti (Cervus canadensis)
Authors: Yan Jiakuo , Wu Xiaoyang , Wang Xibao , Shang Yongquan , Zhang Honghai
Published: September 2022

Microbial symbiotic associations may be beneficial, neutral, or harmful to the host. Symbionts exploit the host space and nutrition or use hosts as carriers to spread to other environments. In order to investigate the fecal bacterial communities of wild sika deer (Cervus nippon) and wapiti (Cervus canadensis), this study aimed to sequence and explore the composition of, and similarity between, the fecal microbiota of sika deer and wapiti using high-throughput sequencing. The composition and relative abundance of fecal microbiota, alpha diversity, and differences in beta diversity between the two species were analyzed. We found that no pathogenic bacteria were present in large quantities in the hosts. The dominant bacterial phyla found in the two deer species were similar and included Firmicutes, Bacteroidetes, Proteobacteria, and Spirochaetes. Moreover, the deer also shared similar dominant genera, including the Rikenellaceae RC9 gut group, Ruminococcaceae_UCG-010, Ruminococcaceae_UCG-005, and Bacteroides. These results demonstrate that the sika deer and wapiti share a similar fecal microbiotal structure, probably due to their common diet and living environment, but there was some evidence of a difference at the species level. These analyses provide new insights into the health status of deer populations outside protected environments and offer a scientific framework for monitoring the health conditions of sika deer and wapiti.
Microbiological Characterization of Cutibacterium acnes Strains Isolated from Prosthetic Joint Infections
Authors: Salar-Vidal Llanos , Aguilera-Correa John Jairo , Brüggemann Holger , Achermann Yvonne , Esteban Jaime
Published: September 2022

Aims: This study aimed to characterize 79 Cutibacterium acnes strains isolated from prosthetic joint infections (PJIs) originated from eight European hospitals. Methods: Isolates were phylotyped according to the single-locus sequence typing (SLST) scheme. We evaluated the ability of the biofilm formation of C. acnes strains isolated from PJIs and 84 isolates recovered from healthy skin. Antibiotic susceptibility testing of planktonic and biofilm cells of PJI isolates and skin isolates was performed. Results: Most of the isolates from PJIs belonged to the SLST class H/phylotype IB (34.2%), followed by class D/phylotype IA1 (21.5%), class A/phylotype IA1 (18.9%), and class K/phylotype II (13.9%). All tested isolates were biofilm producers; no difference in biofilm formation was observed between the healthy skin group and the PJI group of strains. Planktonic and sessile cells of C. acnes remained highly susceptible to a broad spectrum of antibiotics, including beta-lactams, clindamycin, fluoroquinolones, linezolid, rifampin, and vancomycin. The minimal inhibitory concentrations (MICs) for planktonic and biofilm states coincided in most cases. However, the minimal biofilm eradication concentration (MBEC) was high for all antimicrobial drugs tested (>32 mg/L), except for rifampin (2 mg/L). Conclusions: C. acnes strains isolated from healthy skin were able to produce biofilm to the same extent as isolates recovered from PJIs. All C. acnes strains in planktonic and sessile states were susceptible to most antibiotics commonly used for PJI treatment, although rifampin was the only antimicrobial agent able to eradicate C. acnes embedded in biofilm.
Enrofloxacin and Sulfamethoxazole Sorption on Carbonized Leonardite: Kinetics, Isotherms, Influential Effects, and Antibacterial Activity toward S. aureus ATCC 25923
Authors: Chokejaroenrat Chanat , Sakulthaew Chainarong , Satchasataporn Khomson , Snow Daniel D. , Ali Tarik E. , Assiri Mohammed A. , Watcharenwong Apichon , Imman Saksit , Suriyachai Nopparat , Kreetachat Torpong
Published: September 2022

Excessive antibiotic use in veterinary applications has resulted in water contamination and potentially poses a serious threat to aquatic environments and human health. The objective of the current study was to quantify carbonized leonardite (cLND) adsorption capabilities to remove sulfamethoxazole (SMX)- and enrofloxacin (ENR)-contaminated water and to determine the microbial activity of ENR residuals on cLND following adsorption. The cLND samples prepared at 450 °C and 850 °C (cLND450 and cLND550, respectively) were evaluated for structural and physical characteristics and adsorption capabilities based on adsorption kinetics and isotherm studies. The low pyrolysis temperature of cLND resulted in a heterogeneous surface that was abundant in both hydrophobic and hydrophilic functional groups. SMX and ENR adsorption were best described using a pseudo-second-order rate expression. The SMX and ENR adsorption equilibrium data on cLND450 and cLND550 revealed their better compliance with a Langmuir isotherm than with four other models based on 2.3-fold higher values of qmENR than qmSMX. Under the presence of the environmental interference, the electrostatic interaction was the main contributing factor to the adsorption capability. Microbial activity experiments based on the growth of Staphylococcus aureus ATCC 25923 revealed that cLND could successfully adsorb and subsequently retain the adsorbed antibiotic on the cLND surface. This study demonstrated the potential of cLND550 as a suitable low-cost adsorbent for the highly efficient removal of antibiotics from water.
Prolongation of Fate of Bacteriophages In Vivo by Polylactic-Co-Glycolic-Acid/Alginate-Composite Encapsulation
Authors: Kim Sang-Guen , Giri Sib Sankar , Jo Su-Jin , Kang Jeong-Woo , Lee Sung-Bin , Jung Won-Joon , Lee Young-Min , Kim Hee-Jin , Kim Ji-Hyung , Park Se-Chang
Published: September 2022

With concern growing over antibiotics resistance, the use of bacteriophages to combat resistant bacteria has been suggested as an alternative strategy with which to enable the selective control of targeted pathogens. One major challenge that restrains the therapeutic application of bacteriophages as antibacterial agents is their short lifespan, which limits their antibacterial effect in vivo. Here, we developed a polylactic-co-glycolic acid (PLGA)/alginate-composite microsphere for increasing the lifespan of bacteriophages in vivo. The alginate matrix in PLGA microspheres encapsulated the bacteriophages and protected them against destabilization by an organic solvent. Encapsulated bacteriophages were detected in the tissue for 28 days post-administration, while the bacteriophages administered without advanced encapsulation survived in vivo for only 3–5 days. The bacteriophages with extended fate showed prophylaxis against the bacterial pathogens for 28 days post-administration. This enhanced prophylaxis is presumed to have originated from the diminished immune response against these encapsulated bacteriophages because of their controlled release. Collectively, composite encapsulation has prophylactic potential against bacterial pathogens that threaten food safety and public health.
The Feed Additive Potassium Diformate Prevents Salmonella enterica Serovar Pullorum Infection and Affects Intestinal Flora in Chickens
Authors: Sun Yufan , Yu Panyuan , Cheng Yiluo , Liu Jiahui , Chen Xiabing , Zhang Tengfei , Gao Ting , Zhou Rui , Li Lu
Published: September 2022

Extensive studies have shown that potassium diformate (KDF), an antibiotic substitute used as a feed additive, improves animal growth performance, although there is less direct evidence of its preventive effect on bacterial infections and its influence on the intestinal flora of animals. In this study, the inhibition effect of KDF on Salmonella enterica serovar Pullorum, an important enteric pathogen causing pullorum disease, was investigated in vitro and on a chicken infection model. The effect of KDF on the diversities and structures of chicken duodenal and cecum flora were also investigated using 16S rRNA gene sequencing. The results showed that addition of 0.5% KDF in feed or 0.1% KDF in drinking water significantly reduced the bacterial loads and the degree of pathological changes in the cecum, improved digestion and reduced the pH of the gastrointestinal tract of chickens infected with S. pullorum. KDF also significantly modified the diversity and abundance of intestinal microflorae in chickens. In particular, it promoted the colonization of several probiotics, such as Bacteroides, Blautia, Ruminococcus_torques_group and Faecalibacteriumm, which are involved in maintenance of the intestinal barrier, modulation of inflammation, energy supply for intestinal cells and pathogen resistance. These results enrich the theoretical basis for the clinical application of KDF in chickens.
Homocysteine and Inflammatory Cytokines in the Clinical Assessment of Infection in Venous Leg Ulcers
Authors: Cavallo Ilaria , Lesnoni La Parola Ilaria , Sivori Francesca , Toma Luigi , Koudriavtseva Tatiana , Sperduti Isabella , Kovacs Daniela , D’Agosto Giovanna , Trento Elisabetta , Cameli Norma , Mussi Anna , Latini Alessandra , Morrone Aldo , Pimpinelli Fulvia , Di Domenico Enea Gino
Published: September 2022

Inflammation and biofilm-associated infection are common in chronic venous leg ulcers (VU), causing deep pain and delayed healing. Albeit important, clinical markers and laboratory parameters for identifying and monitoring persistent VU infections are limited. This study analyzed 101 patients with infected (IVU) and noninfected VUs (NVU). Clinical data were collected in both groups. The serum homocysteine (Hcys) and inflammatory cytokines from the wound fluid were measured. In addition, microbial identification, antibiotic susceptibility, and biofilm production were examined. IVU were 56 (55.4%) while NVU were 45 (44.5%). IVUs showed a significant increase in the wound’s size and depth compared to NVUs. In addition, significantly higher levels of interleukin (IL)-6, IL-10, IL17A, and tumor necrosis factor-alpha (TNF-α) were found in patients with IVUs compared to those with NVUs. Notably, hyperhomocysteinemia (HHcy) was significantly more common in patients with IVUs than NVUs. A total of 89 different pathogens were identified from 56 IVUs. Gram-negative bacteria were 51.7%, while the Gram-positives were 48.3%. At the species level, Staphylococcus aureus was the most common isolate (43.8%), followed by Pseudomonas aeruginosa (18.0%). Multidrug-resistant organisms (MDROs) accounted for 25.8% of the total isolates. Strong biofilm producers (SBPs) (70.8%) were significantly more abundant than weak biofilm producers (WBP) (29.2%) in IVUs. SBPs were present in 97.7% of the IVUs as single or multispecies infections. Specifically, SBPs were 94.9% for S. aureus, 87.5% for P. aeruginosa, and 28.6% for Escherichia coli. In IVU, the tissue microenvironment and biofilm production can support chronic microbial persistence and a most severe clinical outcome even in the presence of an intense immune response, as shown by the high levels of inflammatory molecules. The measurement of local cytokines in combination with systemic homocysteine may offer a novel set of biomarkers for the clinical assessment of IVUs caused by biofilm-producing bacteria.
New Properties of a Well-Known Antioxidant: Pleiotropic Effects of Human Lactoferrin in Mice Exposed to Gamma Irradiation in a Sublethal Dose
Authors: Kopaeva Marina Yu. , Alchinova Irina B. , Cherepov Anton B. , Demorzhi Marina S. , Nesterenko Mikhail V. , Zarayskaya Irina Yu. , Karganov Mikhail Yu.
Published: September 2022

We studied the effects of human lactoferrin (hLf), a multifunctional protein from the transferrin family, on integral (survival, lifespan during the experiment, body weight, behavior, subfractional compositions of blood serum) and systemic (hemoglobin level, leukocyte number, differential leukocyte count, histological structure of the liver and spleen) parameters of the body in mice after acute gamma irradiation in a sublethal dose. The experiments were performed on male C57BL/6 mice. The mice in the experimental groups were exposed to whole-body gamma radiation in a dose of 7.5 Gy from a 60Co source. Immediately after irradiation and 24 h after it, some animals received an intraperitoneal injection of hLf (4 mg/mouse). Single or repeated administration of hLf had a positive pleiotropic effect on irradiated animals: animal survival increased from 28% to 78%, and the mean life expectancy during the experiment (30 days) increased from 16 to 26 days. A compensatory effect of hLf on radiation-induced body weight loss, changes in homeostasis parameters, and a protective effect on the structural organization of the spleen were demonstrated. These data indicate that Lf has potential as a means of early therapy after radiation exposure.
Kinematic Determinants of the Swimming Push Start in Competitive Swimmers
Authors: Trinidad Alfonso , Navandar Archit , Navarro Enrique , Veiga Santiago
Published: September 2022

(1) Background: The aim of the present research is to describe the kinematic characteristics of push start in competitive swimmers and to examine the role of the push start sub-phases on the overall start performance. (2) Methods: Seventy-four swimmers (33 males and 41 females) of national and international level performed one 25 m trial at maximum velocity with a push start at butterfly, backstroke and/or front-crawl techniques and were filmed with two sequential underwater cameras during the glide, leg kicking, transition and surface swimming phases. (3) Results: Backstroke starts showed greater emersion distances but slower times to 10 m than the remaining strokes. Distances and average velocities in each of the start sub-phases predicted the overall push start performance (times to 10 m) on the butterfly (R2: 0.50) and backstroke (R2: 0.58) strokes, with the velocity of the leg kicking phase having a statistical effect on both regression analysis and the glide and transition phases in backstroke. (4) Conclusions: Push starts performed in a dorsal body position seemed to present kinematic differences with ventral techniques and a greater technical complexity with all glide, leg kicking and transition sub-phases meaningfully impacting the overall push start performance. This should be considered when executing the daily training repetitions with swimmers in water.
Microwave Assisted Preparation of Barium Doped Titania (Ba/TiO2) as Photoanode in Dye Sensitized Solar Cells
Authors: Ahmad Awais , Khan Safia , Khan Mariam , Luque Rafael , Jalalah Mohammed , Alsaiari Mabkhoot A.
Published: September 2022

Pure TiO2 and barium (0.5 wt%) doped TiO2 (Ba/TiO2) nanostructures have been synthesized via facile microwave irradiation method. The pure anatase phase of synthesized photoactive material was confirmed by X-ray diffraction. Ba doping in the TiO2 host structure influenced the optical band gap as confirmed by UV-visible spectroscopy. The optical band gap increased from 3.21 eV for the TiO2 to 3.26 eV for Ba/TiO2. Morphological analysis of synthesized TiO2 and Ba/TiO2 was conducted using scanning electron microscopy. Energy dispersive X-ray spectroscopy confirmed the formation of Ba/TiO2 and no impurities were observed. Electrochemical impedance spectroscopy showed that the charge transfer resistance increased for Ba/TiO2, which reduced dark current creation in a dye-sensitized solar cell. The highest power conversion efficiency (3.24%) was achieved for Ba/TiO2 photoanode compared to 2.1% for a pure TiO2 photoanode-based device.
Path-Guided Finite-Time Formation Control of Nonholonomic Mobile Robots Based on an Extended State Observer
Authors: Fan Yanyan , Jin Zhenlin , Luo Xiaoyuan , Li Shaobao , Guo Baosu
Published: September 2022

In this paper, we study the finite-time formation control problem of uncertain nonholonomic mobile robots following a parameterized path. A path-guided formation control scheme based on an extended state observer is proposed. To compensate for unmeasured velocities and disturbances simultaneously, a third-order fast finite-time extended state observer (FFTESO) is proposed. Then, a distributed formation control solution is developed to achieve the kinematic and dynamic system coordination control of the nonholonomic mobile robots. For the kinematic system control, a path-parameter-updating law is developed for a virtual leader, and the desired linear velocity and heading angle are developed for the mobile robots. For the kinetic control, an anti-disturbance control protocol is designed based on the estimated signals. The salient features of the proposed algorithms lie in that the estimations of disturbances and unmeasured velocities are achieved against the system’s nonholonomic constraints, and the path following the control and cooperative control is synthesized together for path-guided formation, which reduces the complexity of the controller design. Finally, simulation studies are conducted to demonstrate the effectiveness of the proposed algorithm.
Designing a Hybrid Equipment-Failure Diagnosis Mechanism under Mixed-Type Data with Limited Failure Samples
Authors: Chen Cheng-Hui , Tsung Chen-Kun , Yu Shyr-Shen
Published: September 2022

The rarity of equipment failures results in a high level of imbalance between failure data and normal operation data, which makes the effective classification and prediction of such data difficult. Furthermore, many failure data are dominated by mixed data, which makes the model unable to adapt to this type of failure problem. Second, the replacement cycle of production equipment increases the difficulty of collecting failure data. In this paper, an equipment failure diagnosis method is proposed to solve the problem of poor prediction accuracy due to limited data. In this method, the synthetic minority oversampling technique is combined with a conditional tabular generative adversarial network. The proposed method can be used to predict limited data with a mixture of numerical and categorical data. Experimental results indicate that the proposed method can improve 6.45% compared to other similar methods when equipment failure data account for less than 1% of the total data.
The Dynamic Image Analysis of Retaining Wall Crack Detection and Gap Hazard Evaluation Method with Deep Learning
Authors: Mo Dong-Han , Wu Yi-Ching , Lin Chern-Sheng
Published: September 2022

This study uses machine vision combined with drones to detect cracks in retaining walls in mountaineering areas or forest roads. Using the drone’s pre-collected images of retaining walls, the gaps in the wall are obtained as the target for sample data. Deep learning is carried out with neural network architecture. After repeated training of the module, the characteristic conditions of the crack are extracted from the image to be tested. Then, the various characteristics of the gap feature are extracted through image conversion, and the factors are analyzed to evaluate the danger degree of the gap. This study proposes a series of gap danger factor equations for the gap to analyze the safety of the detected gap image so that the system can judge the image information collected by the drone to assist the user in evaluating the safety of the gap. At present, deep learning modules and gap hazard evaluation methods are used to make suggestions on gaps. The expansion of the database has effectively improved the efficiency of gap identification. The detection process is about 20–25 frames per second, and the processing time is about 0.04 s. During the capture process, there will still be a few misjudgments and improper circle selections. The misjudgment rate is between 2.1% and 2.6%.
Effect of Non-Metallic Inclusions on the Fatigue Strength Coefficient of High-Purity Constructional Steel Heated in Industrial Conditions
Authors: Lipiński Tomasz
Published: September 2022

Steel fatigue strength testing is a process that requires large amounts of time, resources and appropriate equipment. The industry seeks to replace cumbersome destructive testing with non-destructive testing. Coefficients were developed that allow the comparison of the parameters of material properties. One such factor is the fatigue strength coefficient, which allows the estimate of fatigue strength using the known hardness of a given material. The fatigue strength factor should be developed for conditions that are as close to the industrial conditions as possible. It should take into account not only the expected properties of the material and the technological process but also its imperfections, e.g., the share of non-metallic inclusions and the steel microstructure. This paper presents the results of research on the influence of non-metallic inclusions on the fatigue strength coefficient of structural steel subjected to rotary bending. The tests were carried out in seven heats obtained in a 140-ton electric furnace under industrial conditions. The steel was desulfurized and refined with argon. The paper presents the bending fatigue strength of hardened and tempered steel at temperatures from 200 °C to 600 °C as a function of the relative volume of inclusions. The non-metallic inclusions occurring in steel were determined qualitatively and quantitatively. The derived fatigue strength coefficient, k, for different tempering temperatures makes it possible to estimate the fatigue strength of the analyzed steel as a function of its hardness for various microstructures represented by the respective tempering temperatures.
The Feasibility of Shadowed Image Restoration Using the Synthetic Aperture Focusing Technique
Authors: Huang Kuo-Yuan , Chang Chih-Hsiung , Chang Young-Fo , Liu Jia-Wei , Chang Jer-Wei
Published: September 2022

The phenomenon of acoustic shadowing on ultrasonography is characterized by an echo signal void behind structures that strongly absorb or reflect ultrasonic energy. In medical ultrasonography, once the ultrasound energy is shielded, acoustic shadowing makes it difficult to create an image, leading to misinterpretations and obscure diagnoses. Hence, instead of dealing with the defocused problem encountered in an ultrasound scan (US), this current research focuses on revealing the existence of an acoustically shadowed target (or a potential lesion) using a well-known restoration algorithm, i.e., the synthetic aperture focusing technique (SAFT). To demonstrate the effects of an acoustic shadow on an ultrasound scan (US), a forward model study is carried out. In laboratory manipulations, a purposely designed physical model is created and then scanned using B-mode and pitch/catch arrangements to carry out shadowed and shadow-free scans in a water tank. Thereafter, making use of a delay-and-sum (DAS) operation, the echo signals are processed by the synthetic aperture focusing technique (SAFT) to perform image restoration. The results of the restoration process show that the SAFT algorithm performs well with respect to directional shadowing. Once the target or lesion is positioned in a total anechoic zone, or even in a multi-channel scan, it will fail.
Effect of Onboard Training for Improvement of Navigation Skill under the Simulated Navigation Environment for Maritime Autonomous Surface Ship Operation Training
Authors: Hwang Hyoseon , Hwang Taemin , Youn Ik-Hyun
Published: September 2022

As the technology of the maritime autonomous surface ship (MASS) systems has geared toward autonomy, the importance of human operations in the shore control center (SCC) has gained in significance. Accordingly, the effects of the training method, including the traditional and new remote operator training methods have to be investigated in terms of MASS navigation safety. Therefore, this study conducted a comparative analysis to prove the effect of onboard training. The findings include the execution of a simulated navigation experiment, the extraction of rudder steering-related features, selection of significant features, and comparative analysis with network graph visualization. The separate results obtained from the “untrained” group and “trained” group were exhibited as the purpose of research for the effect of onboard training on navigation skills. Then, the authors interpreted the difference in each group allusively in accordance with features considering actual navigation and compared groups using descriptive statistics. Consequently, this study emphasized the importance of proving the effect of training before the new training technologies are used to train MASS remote operators in the future.
An Accelerated Degradation Durability Evaluation Model for the Turbine Impeller of a Turbine Based on a Genetic Algorithms Back-Propagation Neural Network
Authors: Yi Xiaojian , Wang Zhezhe , Liu Shulin , Hou Xinrong , Tang Qing
Published: September 2022

Durability evaluation plays an important role in product operation and maintenance during the design stage. In order to ensure a long life, high reliability, and short development cycle, an accelerated degradation durability evaluation model for the turbine impeller of a turbine based on a genetic algorithms back-propagation neural network is established. Based on the proposed model, we discuss two types of practical problems. One is the matching problem of the component strengthening test and whole machine system test. The other is the design problem of two kinds of bench tests. All in all, this work not only proposes a durability evaluation model to effectively solve the current turbine durability evaluation problems, but it also provides a feasible research idea for similar problems.
Context-Aware Complex Human Activity Recognition Using Hybrid Deep Learning Models
Authors: Omolaja Adebola , Otebolaku Abayomi , Alfoudi Ali
Published: September 2022

Smart devices, such as smartphones, smartwatches, etc., are examples of promising platforms for automatic recognition of human activities. However, it is difficult to accurately monitor complex human activities on these platforms due to interclass pattern similarities, which occur when different human activities exhibit similar signal patterns or characteristics. Current smartphone-based recognition systems depend on traditional sensors, such as accelerometers and gyroscopes, which are built-in in these devices. Therefore, apart from using information from the traditional sensors, these systems lack the contextual information to support automatic activity recognition. In this article, we explore environmental contexts, such as illumination (light conditions) and noise level, to support sensory data obtained from the traditional sensors using a hybrid of Convolutional Neural Network and Long Short-Term Memory (CNN–LSTM) learning models. The models performed sensor fusion by augmenting low-level sensor signals with rich contextual data to improve the models’ recognition accuracy and generalization. Two sets of experiments were performed to validate the proposed solution. The first set of experiments used triaxial inertial sensing signals to train baseline models, while the second set of experiments combined the inertial signals with contextual information from environmental sensors. The obtained results demonstrate that contextual information, such as environmental noise level and light conditions using hybrid deep learning models, achieved better recognition accuracy than the traditional baseline activity recognition models without contextual information.
Recent Developments on the Synthesis of Nanocomposite Materials via Ball Milling Approach for Energy Storage Applications
Authors: Joy Josny , Krishnamoorthy Anand , Tanna Ashish , Kamathe Vishal , Nagar Rupali , Srinivasan Sesha
Published: September 2022

This review is focused on the topical developments in the synthesis of nanocomposites using the simplest top-down approach, mechanochemical milling, and the related aspects of the interfacial interactions. Milling constraints include time duration of milling, ball size, the ball-to-sample content proportion, rotation speed, and energy that took part in a vital part of the structure–property relationships and composite interactions. Milled nanocomposites are being used in different structural applications for their higher performance rate and throughput. The synthesis of different nanocomposites and the effect of various parameters on the mill-ability of nanocomposites are discussed. Moreover, some of the major advancements in the energy sector are discussed in the latter part of the review.
Practical Experience in the Application of Energy Roofs, Ground Heat Storages, and Active Thermal Protection on Experimental Buildings
Authors: Kalús Daniel , Koudelková Daniela , Mučková Veronika , Sokol Martin , Kurčová Mária , Janík Peter
Published: September 2022

Research Area: Building components with integrated energy-active elements (BCEAE) are generally referred to as combined building-energy systems (CBES). Aim: Research on the application of energy (solar) roofs (ESR), ground heat storage (GHS), active thermal protection (ATP), and their cooperation in different modes of operation of energy systems with an emphasis on the use of renewable energy sources (RES) and waste heat. Methodology: The analysis and synthesis of the state of the art in the field, the inductive and analogical form of the creation of an innovative method of operation of combined building-energy systems, the development of an innovative solution of the envelope panel with integrated energy-active elements, the synthesis of the knowledge obtained from the scientific analysis and the transformation of the data into the design and implementation of the prototype of the prefabricated house IDA I and the experimental house EB2020. Results: The theoretical analysis of building structures with active thermal protection results in the determination of their energy potential and functionality, e.g., thermal barrier, heating/cooling, heat storage, etc. New technical solutions for envelopes with controlled heat transfer were proposed based on the implementation of experimental buildings. Conclusions: The novelty of our research lies in the design of different variants of the way of operation of energy systems using RES and in upgrading building envelope panels with integrated energy-active elements.
The High-Precision Detection Method for Insulators’ Self-Explosion Defect Based on the Unmanned Aerial Vehicle with Improved Lightweight ECA-YOLOX-Tiny Model
Authors: Ru Chengyin , Zhang Shihai , Qu Chongnian , Zhang Zimiao
Published: September 2022

Aiming at the application of the overhead transmission line insulator patrol inspection requirements based on the unmanned aerial vehicle (UAV), a lightweight ECA-YOLOX-Tiny model is proposed by embedding the efficient channel attention (ECA) module into the lightweight YOLOX-Tiny model. Some measures of data augmentation, input image resolution improvement and adaptive cosine annealing learning rate are used to improve the target detection accuracy. The data of the standard China power line insulator dataset (CPLID) are used to train and verify the model. Through a longitudinal comparison before and after the model improved, and a cross-sectional comparison with other similar models, the advantages of the proposed model are verified in terms of multi-target identification for normal insulators, localization for small target defect areas, and the parameters required for calculation. Finally, the comparative analysis between the proposed ECA-YOLOX-Tiny model and YOLOV4-Tiny model is given by introducing the visualization method of class activation mapping (CAM). The comparative results show that the ECA-YOLOX-Tiny model is more accurate in locating the self-explosion areas of defective insulators, and has a higher response rate for decision areas and some special backgrounds, such as the overlapping small target insulators, the insulators obscured by tower poles, or the insulators with high-similarity backgrounds.
Therapeutic Potential of Interactive Audiovisual 360-Degree Virtual Reality Environments for Anxiety Reduction—A Case Study with an Abstract Art Application
Authors: Jyskä Ilmari , Puura Kaija , Turunen Markku
Published: September 2022

The increasing contrast between limited resources and growing demand in psychiatric care for anxiety disorders has caused an urgent need to find new cost-effective methods for treatment. This article studies the therapeutic potential of interactive audiovisual abstract art in a 360-degree virtual reality environment as a method for reducing anxiety and inducing relaxation. The study consists of experimental research of a virtual reality relaxation application called Binaural Odyssey. This research was conducted with 13 research participants between June and August 2021, and it uses a within-subjects design. Digital questionnaires, structured interviews, Heart Rate Variability (HRV) data, and the researcher’s observations during the research situation were used to gather research data. Results of the study suggest that this method can produce positive mental health effects for the users, such as reduced anxiety and tension, as well as increased relaxation levels and mental resources. Binaural Odyssey is a promising prototype of this method, but it lacks parity regarding application contents and clear therapeutic goals and, therefore, cannot be recommended for treatment purposes. However, further development with mental health professionals could pave the way for a new functional treatment method for reducing and controlling anxiety and tension.
A Linked Data Application for Harmonizing Heterogeneous Biomedical Information
Authors: Capuano Nicola , Foggia Pasquale , Greco Luca , Ritrovato Pierluigi
Published: September 2022

In the biomedical field, there is an ever-increasing number of large, fragmented, and isolated data sources stored in databases and ontologies that use heterogeneous formats and poorly integrated schemes. Researchers and healthcare professionals find it extremely difficult to master this huge amount of data and extract relevant information. In this work, we propose a linked data approach, based on multilayer networks and semantic Web standards, capable of integrating and harmonizing several biomedical datasets with different schemas and semi-structured data through a multi-model database providing polyglot persistence. The domain chosen concerns the analysis and aggregation of available data on neuroendocrine neoplasms (NENs), a relatively rare type of neoplasm. Integrated information includes twelve public datasets available in heterogeneous schemas and formats including RDF, CSV, TSV, SQL, OWL, and OBO. The proposed integrated model consists of six interconnected layers representing, respectively, information on the disease, the related phenotypic alterations, the affected genes, the related biological processes, molecular functions, the involved human tissues, and drugs and compounds that show documented interactions with them. The defined scheme extends an existing three-layer model covering a subset of the mentioned aspects. A client–server application was also developed to browse and search for information on the integrated model. The main challenges of this work concern the complexity of the biomedical domain, the syntactic and semantic heterogeneity of the datasets, and the organization of the integrated model. Unlike related works, multilayer networks have been adopted to organize the model in a manageable and stratified structure, without the need to change the original datasets but by transforming their data “on the fly” to respond to user requests.
Evolution and Controlling Factors of the Reef and Carbonate Platform in Wan’an Basin, South China Sea
Authors: Yang Zhen , Zhang Guangxue , Liu Songfeng , Du Xuebin , Wang Lifei , Yan Wei , Huang Lei
Published: September 2022

In this study, high-resolution seismic profiles and well data provided a good opportunity for better understanding the reefs and carbonate platforms in the Wan’an Basin, southwest of the South China Sea, and also provided valuable information for the oil–gas exploration in the reef reservoirs. Four evolutional phases, including the initial phase, the prosperous phase, the recession phase and the submerged phase, of the reefs and carbonate platforms are proposed according to our data. In the Early Miocene, a few small, isolated carbonate platforms initiated in the center of the basin. In the Middle Miocene, they flourished and mainly formed around the Northern Uplift and Central Uplift, with two belts of carbonate platforms in the western area and eastern area that were mainly platform-edge reefs, massive reefs and a few point reefs. In the Late Miocene, the carbonate platforms began to retreat towards the high topographic position because of the rising of sea level. Meanwhile, the numbers and styles of reefs increased to include platform-edge reefs, massive reefs, atoll reefs and point reefs. Since the Pliocene, most of the carbonate platforms have been covered by detrital materials from terrestrial sources. Crustal tectonic activity provides favorable topography for reef growth and the distribution of platforms, and eustasy controlled the vertical growth and lateral migration of reefs. Since the Late Miocene, the rapidly crustal tectonic subsidence and the rising of relative sea level may lead to the drowning of the carbonate platform.
A Novel Approach to Detect COVID-19: Enhanced Deep Learning Models with Convolutional Neural Networks
Authors: Ramadhan Awf A. , Baykara Muhammet
Published: September 2022

The novel coronavirus (COVID-19) is a contagious viral disease that has rapidly spread worldwide since December 2019, causing the disruption of life and heavy economic losses. Since the beginning of the virus outbreak, a polymerase chain reaction has been used to detect the virus. However, since it is an expensive and slow method, artificial intelligence researchers have attempted to develop quick, inexpensive alternative methods of diagnosis to help doctors identify positive cases. Therefore, researchers are starting to incorporate chest X-ray scans (CXRs), an easy and inexpensive examination method. This study used an approach that uses image cropping methods and a deep learning technique (updated VGG16 model) to classify three public datasets. This study had four main steps. First, the data were split into training and testing sets (70% and 30%, respectively). Second, in the image processing step, each image was cropped to show only the chest area. The images were then resized to 150 × 150. The third step was to build an updated VGG16 convolutional neural network (VGG16-CNN) model using multiple classifications (three classes: COVID-19, normal, and pneumonia) and binary classification (COVID-19 and normal). The fourth step was to evaluate the model’s performance using accuracy, sensitivity, and specificity. This study obtained 97.50% accuracy for multiple classifications and 99.76% for binary classification. The study also got the best COVID-19 classification accuracy (99%) for both models. It can be considered that the scientific contribution of this research is summarized as: the VGG16 model was reduced from approximately 138 million parameters to around 40 million parameters. Further, it was tested on three different datasets and proved highly efficient in performance.
Development Trend of Electronic Nose Technology in Closed Cabins Gas Detection: A Review
Authors: Tan Lidong , Feng Zhaohui , Zheng Hongli , Yao Zongwei , Weng Xiaohui , Wang Fangrong , Chang Zhiyong
Published: September 2022

Gas detection in enclosed cabins is a challenging concern in the industry to ensure the safety of cabin operations and personnel driving. There has been a growing development in the detection of safety in enclosed cabin operations based on volatile organic compounds, which have unique characteristics. The air pollution in closed cabins seriously affects the driver’s health, and the accuracy of the detection directly affects the operation safety of the cabin. However, until today, gas detection in enclosed cabins has relied on traditional methods that are expensive and time-consuming, and it cannot be detected in real time. This paper focuses on the potential and capability of electronic nose applications for gas detection in enclosed cabins. Since the electronic nose is a good substitute for the closed cabin, people’s attention to it has increased greatly. The characteristics of hazardous gas and warning gas in closed cabins are also discussed. In addition, this paper provides important insights into the challenges and future trends of the electronic nose, a low-cost, high-precision, and fast detection method, in more applications in closed compartments.
Fast Airfoil Selection Methodology for Small Unmanned Aerial Vehicles
Authors: Kapoulas Ioannis K. , C. Statharas J. C. , Hatziefremidis Antonios , Baldoukas A. K.
Published: September 2022

The purpose of this study is to fill the gap that exists when applying the airfoil selection methodology according to the textbooks that appear in the above featured application section, in the low Reynolds number segment, by providing useful data. Data acquisition software was XFLR5. The major result is the construction of a prototype maximum lift coefficient versus ideal lift coefficient diagram, or (Clmax−Cli) diagram, composed exclusively of low Reynolds number airfoils. In addition, the necessary supplementary airfoil characteristics’ tables are provided, for conducting fast airfoil selection for Small Unmanned Aerial Vehicles (SUAVs). As a conclusion by implementing the proposed methodology, the SUAV designer is disengaged from the time-consuming process of the construction of similar Clmax−Cli diagrams and supplementary characteristic tables and the airfoil selection-processing time can be greatly shortened, because the main work of the process is reflected by the current findings. To express the time gain in a percentage manner, authors estimate that 85% of engineering time will be economized in the overall airfoil selection procedure if the current findings are used, due to the fact that no new airfoil simulations are required. Finally, candidate SUAV designers are encouraged to expand the airfoil database, according to the proposed methodology.
Deep Reinforcement Learning Approach for Material Scheduling Considering High-Dimensional Environment of Hybrid Flow-Shop Problem
Authors: Gil Chang-Bae , Lee Jee-Hyong
Published: September 2022

Manufacturing sites encounter various scheduling problems, which must be dealt with to efficiently manufacture products and reduce costs. With the development of smart factory technology, many elements at manufacturing sites have become unmanned and more complex. Moreover, owing to the mixing of several processes in one production line, the need for efficient scheduling of materials has emerged. The aim of this study is to solve the material scheduling problem of many machines in a hybrid flow-shop environment using deep reinforcement learning. Most previous work has ignored some conditions, which were critical for solving practical problems. Such critical conditions make the scheduling more complex and difficult to solve. They expand the size of the state and large action space and make learning in an environment with many machines problematic. In this study, a reinforcement learning approach was developed considering practical factors such as the processing time and material transfer to solve realistic manufacturing scheduling problems. Additionally, a method to simplify the high-dimensional environmental space at manufacturing sites for efficient learning was established to solve the problem of learning in a high-dimensional space. Through experiments, we showed that our approach could optimally schedule material scheduling in multi-process lines, which contributes to realistic manufacturing intelligence.