bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a Low-Cost Open-Source Platform for Smart Irrigation Systems
Authors: Puig Francisco , Rodríguez Díaz Juan Antonio , Soriano María Auxiliadora
Published: November 2022

Nowadays, smart irrigation is becoming an essential goal in agriculture, where water and energy are increasingly limited resources. Its importance will grow in the coming years in the agricultural sector where the optimal use of resources and environmental sustainability are becoming more important every day. However, implementing smart irrigation is not an easy task for most farmers since it is based on knowledge of the different processes and factors that determine the crop water requirements. Thanks to technological developments, it is possible to design new tools such as sensors or platforms that can be connected to soil-water-plant-atmosphere models to assist in the optimization and automation of irrigation. In this work, a low-cost, open-source IoT system for smart irrigation has been developed that can be easily integrated with other platforms and supports a large number of sensors. The platform uses the FIWARE framework together with customized components and can be deployed using edge computing and/or cloud computing systems. To improve decision-making, the platform integrates an irrigation model that calculates soil water balance and wet bulb dimensions to determine the best irrigation strategy for drip irrigation systems. In addition, an energy efficient open-source datalogger has been designed. The datalogger supports a wide range of communications and is compatible with analog sensors, SDI-12 and RS-485 protocols. The IoT system has been deployed on an olive farm and has been in operation for one irrigation season. Based on the results obtained, advantages of using these technologies over traditional methods are discussed.
Extracellular Vesicles from Animal Milk: Great Potentialities and Critical Issues
Authors: Mecocci Samanta , Trabalza-Marinucci Massimo , Cappelli Katia
Published: November 2022

Other than representing the main source of nutrition for newborn mammals, milk delivers a sophisticated signaling system from mother to child that promotes postnatal health. The bioactive components transferred through the milk intake are important for the development of the newborn immune system and include oligosaccharides, lactoferrin, lysozyme, α-La, and immunoglobulins. In the last 15 years, a pivotal role in this mother-to-child exchange has been attributed to extracellular vesicles (EVs). EVs are micro- and nanosized structures enclosed in a phospholipidic double-layer membrane that are produced by all cell types and released in the extracellular environment, reaching both close and distant cells. EVs mediate the intercellular cross-talk from the producing to the receiving cell through the transfer of molecules contained within them such as proteins, antigens, lipids, metabolites, RNAs, and DNA fragments. The complex cargo can induce a wide range of functional modulations in the recipient cell (i.e., anti-inflammatory, immunomodulating, angiogenetic, and pro-regenerative modulations) depending on the type of producing cells and the stimuli that these cells receive. EVs can be recovered from every biological fluid, including blood, urine, bronchoalveolar lavage fluid, saliva, bile, and milk, which is one of the most promising scalable vesicle sources. This review aimed to present the state-of-the-art of animal-milk-derived EV (mEV) studies due to the exponential growth of this field. A focus on the beneficial potentialities for human health and the issues of studying vesicles from milk, particularly for the analytical methodologies applied, is reported.
Natural Mycoplasma Infection Reduces Expression of Pro-Inflammatory Cytokines in Response to Ovine Footrot Pathogens
Authors: Blanchard Adam M. , Baumbach Christina-Marie , Michler Jule K. , Pickwell Natalie D. , Staley Ceri E. , Franklin Jemma M. , Wattegedera Sean R. , Entrican Gary , Tötemeyer Sabine
Published: November 2022

Ovine footrot is a complex multifactorial infectious disease, causing lameness in sheep with major welfare and economic consequences. Dichelobacter nodosus is the main causative bacterium; however, footrot is a polymicrobial disease with Fusobacterium necrophorum, Mycoplasma fermentans and Porphyromonas asaccharolytica also associated. There is limited understanding of the host response involved. The proinflammatory mediators, interleukin (IL)-1β and C-X-C Motif Chemokine Ligand 8 (CXCL8), have been shown to play a role in the early response to D. nodosus in dermal fibroblasts and interdigital skin explant models. To further understand the response of ovine skin to bacterial stimulation, and to build an understanding of the role of the cytokines and chemokines identified, primary ovine interdigital fibroblasts and keratinocytes were isolated, cultured and stimulated. The expression of mRNA and protein release of CXCL8 and IL-1β were measured after stimulation with LPS, D. nodosus or F. necrophorum, which resulted in increased transcript levels of IL-1β and CXCL8 in the M. fermentans-free cells. However, only an increase in the CXCL8 protein release was observed. No IL-1β protein release was detected, despite increases in IL-1β mRNA, suggesting the signal for intracellular pre-IL-1β processing may be lacking when culturing primary cells in isolation. The keratinocytes and fibroblasts naturally infected with M. fermentans showed little response to the LPS, a range of D. nodosus preparations or heat-inactivated F. necrophorum. Primary single cell culture models complement ex vivo organ culture models to study different aspects of the host response to D. nodosus. The ovine keratinocytes and fibroblasts infected with M. fermentans had a reduced response to the experimental bacterial stimulation. However, in the case of footrot where Mycoplasma spp. are associated with diseased feet, this natural infection gives important insights into the impact of multiple pathogens on the host response.
Characterisation of Non-Carbapenemase-Producing Carbapenem-Resistant Klebsiella pneumoniae Based on Their Clinical and Molecular Profile in Malaysia
Authors: Lee Yee Qing , Sri La Sri Ponnampalavanar Sasheela , Chong Chun Wie , Karunakaran Rina , Vellasamy Kumutha Malar , Abdul Jabar Kartini , Kong Zhi Xian , Lau Min Yi , Teh Cindy Shuan Ju
Published: November 2022

Non-carbapenemase-producing carbapenem-resistant Klebsiella pneumoniae (NC-CRKP) confers carbapenem resistance through a combination of chromosomal mutations and acquired non-carbapenemase resistance mechanisms. In this study, we aimed to evaluate the clinical and molecular profiles of NC-CRKP isolated from patients in a tertiary teaching hospital in Malaysia from January 2013 to October 2019. During the study period, 54 NC-CRKP-infected/colonised patients’ isolates were obtained. Clinical parameters were assessed in 52 patients. The all-cause in-hospital mortality rate among NC-CRKP patients was 46.2% (24/52). Twenty-three (44.2%) patients were infected, while others were colonised. Based on the Charlson Comorbidity Index (CCI) score, 92.3% (48/52) of the infected/colonised patients had a score of ≥ 1. Resistance genes found among the 54 NC-CRKP isolates were blaTEM, blaSHV, blaCTX-M, blaOXA, and blaDHA. Porin loss was detected in 25/54 (46.3%) strains. None of the isolated strains conferred carbapenem resistance through the efflux pumps system. In conclusion, only 25/54 (46.3%) NC-CRKP conferred carbapenem resistance through a combination of porin loss and the acquisition of non-carbapenemase resistance mechanisms. The carbapenem resistance mechanisms for the remaining strains (53.7%) should be further investigated as rapid identification and distinction of the NC-CRKP mechanisms enable optimal treatment and infection control efforts.
Correction: Wang et al. Diverse Metabolites and Pharmacological Effects from the Basidiomycetes Inonotus hispidus. Antibiotics 2022, 11, 1097
Authors: Wang Zhen-xin , Feng Xi-long , Liu Chengwei , Gao Jin-ming , Qi Jianzhao
Published: November 2022

In the original publication, there were publisher errors in the names of authors Zhen-xin Wang, Xi-long Feng and Jin-ming Gao and affiliation (1) of the first, second, fourth and fifth authors (name of the Key Laboratory and city) [...]
Potent Anti-Inflammatory Effects of a Helix-to-Helix Peptide against Pseudomonas aeruginosa Endotoxin-Mediated Sepsis
Authors: Son Hyosuk , Park Seong-Cheol , Kim Young-Min , Lee Jong-Kook , Park Soyoung , Guk Taeuk , Yoon A-Mi , Lim Hye Song , Jang Mi-Kyeong , Lee Jung Ro
Published: November 2022

Although considerable scientific research data is available for sepsis and cytokine storm syndrome, there is a need to develop new treatments or drugs for sepsis management. Antimicrobial peptides (AMPs) possess anti-bacterial and anti-inflammatory activity, neutralizing toxins such as lipopolysaccharides (LPS, endotoxin). Most AMPs have been designed as a substitute for conventional antibiotics, which kill drug-resistant pathogens. The present study aimed to determine the anti-inflammatory potential of 10 designed XIW (X: lysine, arginine, or glutamic acid) α-helical peptides in macrophages and a mouse model in the presence of LPS. Among them, WIKE-14, a peptide with a helix-to-helix structure, having the 12th amino acid substituted with glutamic acid, suppressed pro-inflammatory cytokines in RAW 264.7 macrophages. This reaction was mediated by the inhibition of the binding between LPS and macrophages. In addition, the WIKE-14 peptide exhibited a potent anti-inflammatory activity in mice ears and lungs inflamed using LPS. Thus, our results may provide useful insights for the development of anti-sepsis agents via the sequence and structure information of the WIKE-14 peptide.
Evaluation of Healthcare Students’ Knowledge on Antibiotic Use, Antimicrobial Resistance and Antimicrobial Stewardship Programs and Associated Factors in a Tertiary University in Ghana: Findings and Implications
Authors: Sefah Israel Abebrese , Akwaboah Emmanuel , Sarkodie Emmanuel , Godman Brian , Meyer Johanna Caterina
Published: November 2022

Antimicrobial resistance (AMR) is a major public health problem globally, and Ghana is no exception. Good knowledge regarding antibiotic use, AMR, and the concept of antimicrobial stewardship (AMS) is critical among healthcare students to curb rising AMR rates in the future. Consequently, a need to ascertain this. A cross-sectional survey was undertaken among fifth-year pharmacy, medical students and fourth (final)-year nursing and physician assistantship students at the University of Health and Allied Sciences in Ghana to assess their knowledge on antibiotic use, AMR and AMS using a web-based self-administered structured questionnaire. Descriptive statistics, Fishers’ exact test, and multiple logistic regression analyses were performed. A total of 160 healthcare students were interviewed, of which 56.3% (n = 90) were male and 58.8% (n = 94) were in their fourth year of study. Good knowledge of antibiotic use, AMR, and AMS was associated with the study course (p = 0.001) and the number of years of study (p < 0.001). Overall, there were differences in the level of knowledge of antibiotics among the different healthcare students and their years of study. Efforts must now be made to enhance the curricula to ensure an improved and uniform transfer of knowledge of antibiotics, AMR, and AMS among the different healthcare students to sustain the fight against AMR in Ghana given growing concerns.
Reduced Fitness and Elevated Oxidative Stress in the Marine Copepod Tigriopus japonicus Exposed to the Toxic Dinoflagellate Karenia mikimotoi
Authors: Chen Hongju , Wang Jing , Zhuang Yunyun , Yu Wenzhuo , Liu Guangxing
Published: November 2022

Blooms of the toxic dinoflagellate Karenia mikimotoi cause devastation to marine life, including declines of fitness and population recruitment. However, little is known about the effects of them on benthic copepods. Here, we assessed the acute and chronic effects of K. mikimotoi on the marine benthic copepod Tigriopus japonicus. Results showed that adult females maintained high survival (>85%) throughout 14-d incubation, but time-dependent reduction of survival was detected in the highest K. mikimotoi concentration, and nauplii and copepodites were more vulnerable compared to adults. Ingestion of K. mikimotoi depressed the grazing of copepods but significantly induced the generation of reactive oxygen species (ROS), total antioxidant capacity, activities of antioxidant enzymes (superoxide dismutase, catalase, and glutathione peroxidase), and acetylcholinesterase. Under sublethal concentrations for two generations, K. mikimotoi reduced the fitness of copepods by prolonging development time and decreasing successful development rate, egg production, and the number of clutches. Our findings suggest that the bloom of K. mikimotoi may threaten copepod population recruitment, and its adverse effects are associated with oxidative stress.
Myeloperoxidase: Regulation of Neutrophil Function and Target for Therapy
Authors: Rizo-Téllez Salma A. , Sekheri Meriem , Filep János G.
Published: November 2022

Neutrophils, the most abundant white blood cells in humans, are critical for host defense against invading pathogens. Equipped with an array of antimicrobial molecules, neutrophils can eradicate bacteria and clear debris. Among the microbicide proteins is the heme protein myeloperoxidase (MPO), stored in the azurophilic granules, and catalyzes the formation of the chlorinating oxidant HOCl and other oxidants (HOSCN and HOBr). MPO is generally associated with killing trapped bacteria and inflicting collateral tissue damage to the host. However, the characterization of non-enzymatic functions of MPO suggests additional roles for this protein. Indeed, evolving evidence indicates that MPO can directly modulate the function and fate of neutrophils, thereby shaping immunity. These actions include MPO orchestration of neutrophil trafficking, activation, phagocytosis, lifespan, formation of extracellular traps, and MPO-triggered autoimmunity. This review scrutinizes the multifaceted roles of MPO in immunity, focusing on neutrophil-mediated host defense, tissue damage, repair, and autoimmunity. We also discuss novel therapeutic approaches to target MPO activity, expression, or MPO signaling for the treatment of inflammatory and autoimmune diseases.
GIS-Based Cluster and Suitability Analysis of Crop Residues: A Case Study in Yangon Region, Myanmar
Authors: Min Htoo Tin , Yabar Helmut , Mizunoya Takeshi
Published: November 2022

In the study of biomass assessment, geospatial modeling-based analysis becomes crucial for the sustainable management of agriculture. Currently, there is no integrated sustainability assessment of the geographic information system (GIS) cluster or suitability analysis for the feedstock of crop residues. In order to fill this research gap and support the strategy of bioenergy formulation with the circular economy concept in agriculture residues in Myanmar, this study aims to assess the energy generation potential and site locations of treatment facilities for crop residue, utilizing the integrated assessment of GIS cluster and suitability modeling. The cluster analysis identifies the rice straw as the highest feedstock of crop residues and township-based high/low clusters. In addition, the electricity generation potential is estimated at 279.14 MW for different clusters of rice straw. Moreover, the suitability analysis in the study uses the conceptual model of variables for constraints and factors with the analytical hierarchy process (AHP) technique to evaluate the weights. The suitability analysis found high suitability areas of 14,603 hectares for treatment facilities within the high/low cluster of feedstock for rice straw. The multicriteria and GIS integrated assessment model adopted in this research can support the decision-makers in developing spatial-based strategic planning for bioenergy promotion which will support sustainable farming practices in Myanmar. Additionally, the proposed model is adaptable in study areas with similar feedstock.
Technology and Management Applied in Construction Engineering Projects
Authors: Szóstak Mariusz , Konior Jarosław , Sawicki Marek
Published: November 2022

The current Special Issue is a digest of 13 published articles that referred to the following scientific and professional areas: construction project management and quality management in construction engineering and supervision; cost discount and the financial control of construction projects; multi-criteria feasibility studies of investment enterprises; the qualitative and quantitative research of engineering buildings by probabilistic and fuzzy sets approach; multidiscipline expertise investigations of buildings that significantly differ in structure and use.
Local-Moment-Driven Robust Reversible Data Hiding
Authors: Singh Yash Veer , Khan Shadab , Shukla Santosh Kumar , Jung Ki-Hyun
Published: November 2022

In this paper, a local-moment-driven robust reversible data hiding (LM-RRDH) scheme is proposed, which can provide security to hidden messages against unintentional modifications. The proposed LM-RRDH decomposes an image into LSB and MSB planes and then embeds the secret information into the MSB image so that intrusion by unintentional modifications can be avoided. In addition, the proposed scheme utilizes the prevalent correlation among the pixels on the MSB plane for optimal embedding. In the proposed scheme, a cover image is partitioned into sub-blocks at first, and pixel groups in the sub-block are formed according to local moment and moment-of-moment so that similar-intensity pixels can be grouped into the same group. Next, the secret data is embedded into the pixels of each group by selecting a pairwise embedding strategy adaptively which is based on the number of pixels in each group. As a result, the proposed LM-RRDH can limit the distortion while providing a decent embedding capacity. Further, a protection against non-malicious attacks such as Joint Photographic Experts Group (JPEG) compression is also provided. The experimental results show that the proposed scheme provides a superior quality to the previous works while providing a comparable embedding capacity.
Evaluation of Microleakage of a New Bioactive Material for Restoration of Posterior Teeth: An In Vitro Radioactive Model
Authors: Neves Pedro , Pires Salomé , Marto Carlos Miguel , Amaro Inês , Coelho Ana , Sousa José , Ferreira Manuel Marques , Botelho Maria Filomena , Carrilho Eunice , Abrantes Ana Margarida , Paula Anabela Baptista
Published: November 2022

Hybrid bioactive composite resins combine the benefits of glass ionomer cements with composite resins. Its self-adhesiveness is achieved through functional polyacrylic acids and carboxylic groups, hybridizing the smear layer and establishing ionic interactions between calcium and dentin. These materials are defined as having good aesthetics, moisture tolerance, durability, simplicity in technique and handling and are able to maintain a low microfiltration rate while releasing calcium, phosphate and fluorine. The aim of the present study was to evaluate microleakage in restorations using Surefill One™ bioactive resin. The null hypothesis is that this type of resin does not obtain a lower microleakage rate when compared to other materials. An in vitro study was carried out using thirty-six premolars and molars extracted for orthodontic reasons. Identical preparations were thus performed in all of them (Class V with 4 mm mesio-distal, 3 mm occluso-gingival and 3 mm in depth) and divided into different experimental groups: one positive control, one negative control and two tests with bioactive composite resin and conventional composite resin (Surefill One™ and Spectra™ ST HV, respectively). Through quantitative techniques using nuclear medicine, it was possible to evaluate microleakage through the use of a radioactive isotope, technetium. Radioactivity emitted by the specimens was detected by a gamma camera. The different groups were compared using the Kruskal–Wallis test and the Games–Howell test for multiple comparisons. The results of the experimental study point to statistically significant differences between the test groups (p = 0.002) with increased microleakage in the bioactive composite resin group. Based on the present microleakage study, it was possible to conclude that the bioactive composite resin (Surefill One™) does not reduce the microleakage rate when compared to a conventional nanohybrid composite resin (Spectra™ ST HV). However, Surefill One™ can be used in temporary restorations, primary teeth and in cases of tissue remineralization, thus avoiding more invasive procedures.
A Many-Objective Marine Predators Algorithm for Solving Many-Objective Optimal Power Flow Problem
Authors: Khunkitti Sirote , Siritaratiwat Apirat , Premrudeepreechacharn Suttichai
Published: November 2022

Since the increases in electricity demand, environmental awareness, and power reliability requirements, solutions of single-objective optimal power flow (OPF) and multi-objective OPF (MOOPF) (two or three objectives) problems are inadequate for modern power system management and operation. Solutions to the many-objective OPF (more than three objectives) problems are necessary to meet modern power-system requirements, and an efficient optimization algorithm is needed to solve the problems. This paper presents a many-objective marine predators algorithm (MaMPA) for solving single-objective OPF (SOOPF), multi-objective OPF (MOOPF), and many-objective OPF (MaOPF) problems as this algorithm has been widely used to solve other different problems with many successes, except for MaOPF problems. The marine predators algorithm (MPA) itself cannot solve multi- or many-objective optimization problems, so the non-dominated sorting, crowding mechanism, and leader mechanism are applied to the MPA in this work. The considered objective functions include cost, emission, transmission loss, and voltage stability index (VSI), and the IEEE 30- and 118-bus systems are tested to evaluate the algorithm performance. The results of the SOOPF problem provided by MaMPA are found to be better than various algorithms in the literature where the provided cost of MaMPA is more than that of the compared algorithms for more than 1000 USD/h in the IEEE 118-bus system. The statistical results of MaMPA are investigated and express very high consistency with a very low standard deviation. The Pareto fronts and best-compromised solutions generated by MaMPA for MOOPF and MaOPF problems are compared with various algorithms based on the hypervolume indicator and show superiority over the compared algorithms, especially in the large system. The best-compromised solution of MaMPA for the MaOPF problem is found to be greater than the compared algorithms around 4.30 to 85.23% for the considered objectives in the IEEE 118-bus system.
Temperature Prediction of Chinese Cities Based on GCN-BiLSTM
Authors: Miao Lizhi , Yu Dingyu , Pang Yueyong , Zhai Yuehao
Published: November 2022

Temperature is an important part of meteorological factors, which are affected by local and surrounding meteorological factors. Aiming at the problems of significant prediction error and insufficient extraction of spatial features in current temperature prediction research, this research proposes a temperature prediction model based on the Graph Convolutional Network (GCN) and Bidirectional Long Short-Term Memory (BiLSTM) and studies the influence of temperature time-series characteristics, urban spatial location, and other meteorological factors on temperature change in the study area. In this research, multi-meteorological influencing factors and temperature time-series characteristics are used instead of single time-series temperature as influencing factors to improve the time dimension of the input data through time-sliding windows. Meanwhile, considering the influence of meteorological factors in the surrounding area on the temperature change in the study area, we use GCN to extract the urban geospatial location features. The experimental results demonstrate that our model outperforms other models and has the smallest root mean squared error (RMSE) and mean absolute error (MAE) in the following 14-day and multi-region temperature forecasts. It has higher accuracy in areas with stable temperature fluctuations and small temperature differences than in baseline models.
Numerical Study on the Flow Past Three Cylinders in Equilateral-Triangular Arrangement at Re = 3 × 106
Authors: Zhang Mohan , Yin Bo , Guo Dilong , Ji Zhanling , Yang Guowei
Published: November 2022

One of the most common systems in engineering problems is the multi-column system in the form of an equilateral-triangular arrangement. This study used three-dimensional numerical simulations to investigate the flow around three cylinders in this arrangement at the super-critical Reynolds number Re=3×106, concentrating on the influence on the spacing ratio (L/D) among cylinders. The instantaneous vortex structures, Strouhal numbers, fluid force coefficients, and pressure distributions are analyzed thoroughly. The present study demonstrated that fluid dynamics is sensitive to L/D, by which five different flow patterns are classified, namely single bluff body flow (L/D≤1.1), deflected gap flow (1.2≤L/D≤1.4), anti-phase flow (1.5≤L/D≤2.3), in-phase flow (2.5≤L/D<3.5), and co-shedding flow (L/D≥3.5). Critical bounds are identified by significant transitions in the flow structure, discontinuous drop and jump of St, and force coefficients.
Adaptive Dynamic Search for Multi-Task Learning
Authors: Kim Eunwoo
Published: November 2022

Multi-task learning (MTL) is a learning strategy for solving multiple tasks simultaneously while exploiting commonalities and differences between tasks for improved learning efficiency and prediction performance. Despite its potential, there remain several major challenges to be addressed. First of all, the task performance degrades when the number of tasks to solve increases or the tasks are less related. In addition, finding the prediction model for each task is typically laborious and can be suboptimal. This nature of manually designing the architecture further aggravates the problem when it comes to solving multiple tasks under different computational budgets. In this work, we propose a novel MTL approach to address these issues. The proposed method learns to search in a finely modularized base network dynamically and to discover an optimal prediction model for each instance of a task on the fly while taking the computational costs of the discovered models into account. We evaluate our learning framework on a diverse set of MTL scenarios comprising standard benchmark datasets. We achieve significant improvements in performance for all tested cases compared with existing MTL alternatives.
The Train-Bridge Coupled Vibration Analysis of a Long-Span Prestressed Concrete Continuous Beam Bridge under Creep Deformation Effect
Authors: Luo Hao , Xu Chuyi , Gan Xianbei , Liu Mougang , Guo Xiangrong , Guo Hui
Published: November 2022

The track smoothness of high-speed railroads is severely limited to ensure train performance. The concrete continuous girder bridge is deformed to influence the smoothness of the bridge decks and track caused by creep bulge. There is a need to research the impact of beam creep on the dynamical response of bridge and train operation safety. This paper used Midas software to calculate the long-term deformation of large-span prestressed concrete continuous beam bridges under concrete creep and shrinkage. The train-bridge coupled system was established by adopting self-programming software. Thereafter, the large-term deformation results of the main girder are considered as track irregularity input into the vibration equation of the train-bridge system. The safety of the train operation was evaluated by calculating the dynamic response of the bridge and analyzing the criteria of train running safety. It was shown that the indicators of the large-span bridge are within the allowable code values under all working conditions. The bridge deformation under creep has an impact on the displacement and acceleration response of the bridge when a high-speed train passes through. There is no noticeable impact of creep deformation on the operational performance of trains. Nevertheless, the criteria for assessing the safety of trains’ operation, such as derailment factor, wheel load differences, lateral wheel forces, and vehicle acceleration, have been increased.
Sloshing of Liquid in a Cylindrical Tank with Multiple Baffles and Considering Soil-Structure Interaction
Authors: Sun Ying , Zhou Ding , Wang Jiadong , Gu Zhenyuan , Qian Wangping
Published: November 2022

In this study, the liquid sloshing in a cylindrical tank considering soil–structure interaction and undergoing horizontal excitation is investigated analytically. Multiple rigid annular baffles are positioned on the rigid wall to mitigate the liquid sloshing. Firstly, combined with the subdomain partition method for sloshing, the complex liquid domain is partitioned into simple subdomains with the single condition for boundary. Based on continuity conditions of velocity and pressure as well as the linear sloshing equation for free surface, the exact solution for convective velocity potential is derived with high accuracy. By yielding the similar hydrodynamic shear and moment as those of the original system, a mechanical model is developed to describe continuous sloshing, and parameters of the model are given in detail. Then, by means of the least squares approach, the Chebyshev polynomials are utilized to fit impedances for the circular surface foundation. A lumped parameter model is employed to represent influences of soil on the superstructure. Finally, by using the substructure method, a coupling model of the soil–tank system is developed to simplify the dynamic analysis. Comparison investigations are carried out to verify the effectiveness of the model. Detailed sloshing characteristics and dynamic responses of sloshing are analyzed with regard to different baffle sizes and positions as well as soil parameters, respectively. The novelty of the present study is that an equivalent analytical model for the soil–foundation–tank–liquid system with multiple baffles is firstly obtained and it allows the dynamic behaviors of the coupling system to be investigated with high computation efficiency and acceptable accuracy.
Developing an Electrical System toward the Prevention of Heat Ventilation Air Conditioning Contamination
Authors: Han Sang Kuy , Kim Young Wook , Koo Bon-Sang , Choi Hae Won , Lee Soonbum
Published: November 2022

Biofilms comprise diverse bacteria and fungi with slime material, especially in humid conditions. The surface of the heat ventilation and air conditioning (HVAC) system, especially at the evaporator, is in high moisture conditions due to the compression and relaxation of refrigerant. Biofilms comprise electrically polarized molecules, which include polysaccharide, DNA, liposome, and diverse amino acids. Thus, when an electric field is applied to biofilms, the field creates an electrostatic force that enhances the destruction of biofilms and results in detachment from the surface. The principles are known as the bioelectric effect. A new bioelectric (BE) technology has been developed that is focused on the optimization of electrical energy for biofilm removal, and its efficacy has been previously demonstrated. In this work, a prototype of the BE device for HVAC application has been fabricated and tested. Escherichia coli (E. coli) biofilms were utilized as a standard model of biofilm on the HVAC evaporator. The results demonstrate that when the BE technology was applied for one hour, approximately 81.8% of total biofilm was removed. Furthermore, live cells in biofilms were reduced by approximately 71.4% under the BE device, compared to non-treated biofilms.
Dynamic Heat Transfer Calculation for Ground-Coupled Floor in Emergency Temporary Housing
Authors: Ding Pei , Li Jin , Xiang Mingli , Cheng Zhu , Long Enshen
Published: November 2022

Generally, ground-coupled floor heat transfer is supposed as annual periodic, which is reasonable for conventional buildings. However, for emergency housing with a short life cycle, the influence of initial soil temperature needs to be considered. In a previous study, the Wiener–Hopf technique was introduced to solve the two-dimensional transient heat transfer equation with mixed Dirichlet and Robin boundary conditions. Based on that, an analytical solution of the dynamic heat transfer equation with initial soil temperature conditions was obtained. Since the solution was in the form of a double integral, its numerical evaluation method was also analyzed to improve computational efficiency. The accuracy and efficiency of the solution were validated by the finite volume method. Then, the effects of initial soil temperatures in different seasons, soil heat conductivities, and floor insulation on ground-coupled heat transfer were discussed. Results showed significant temperature differences between the current solution and the annual periodic solutions (long-time solutions), especially in hot and cold climates. Moreover, the larger the thermal capacity of the soil, the bigger temperature differences occurred. Therefore, this study is expected to provide a theoretical foundation for the indoor environment prediction and optimization design of emergency temporary housing.
Configuration Design and Gait Planning of a Six-Bar Tensegrity Robot
Authors: Hao Siqi , Liu Ruiwei , Lin Xuntao , Li Chenxiao , Guo Hongwei , Ye Zhiwen , Wang Chunlong
Published: November 2022

Due to their high kinematic characteristics, six-bar tensegrities have great potential application value in the field of robotics, especially in the field of deep space exploration robots. In this paper, an ultralight six-bar tensegrity robot is designed, and a gait planning method for continuous motion is proposed. First, the equilibrium matrix of the tensegrity structure is constructed, and singular value decomposition (SVD) is performed to find the node coordinates and internal forces of the tensegrity structure. Two representative examples regarding tensegrity structures are presented to demonstrate the capability of the proposed method in the initial selfstress design that satisfies the stability of tensegrities. Furthermore, both the principal rolling analysis and gait planning are also addressed based on the offset of the center of gravity. A six-bar tensegrity robot prototype is developed, and the obstacle avoidance experiment is completed. Finally, the results show that the six-bar tensegrity robot has good kinematic performance. Moreover, this robot is expected to play a key role in future planetary exploration.
RIS-Assisted High-Speed Communications with Time-Varying Distance-Dependent Rician Channels
Authors: Wang Ke , Lam Chan-Tong , Ng Benjamin K.
Published: November 2022

Reconfigurable intelligent surface (RIS) has been envisioned as one of the promising solutions for enhancing signal transmissions in high-speed communications (HSC). In this paper, we present a time-varying channel model with distance-dependent Rician factors for the RIS-assisted HSC. Our model not only contains Rayleigh components and Doppler shift (DS) terms but also distance-dependent Rician factors, for characterizing time-varying features. In particular, we show that when the vehicle is far from the base station and the RIS, the channel contains only Rayleigh fading. However, when they are close enough, the channel can be considered as a light-of-sight channel. Based on the proposed model, it is proven that using RIS phase shift optimization, the DS of the cascaded links can be aligned with the DS of the direct link; and if the direct link is blocked, the DS can be removed entirely. Furthermore, we derive the closed-form expressions for the ergodic spectral efficiency and the outage probability of the proposed system. Besides, it is observed that the deployment strategy also affects the system performance. Simulation results validate all analyses.
Improved Belgian AI Algorithm for Dynamic Management in Action Role-Playing Games
Authors: Mi Qingwei , Gao Tianhan
Published: November 2022

Artificial intelligence in games is one of the most challenging tasks in academia and industry. In action role-playing games, how to manage combat effectively is a key issue related to game development and the player’s experience. The Belgian artificial intelligence (BAI) algorithm is a classic but limited method that is widely used for combat management between the player and enemies. To address the poor adaptability of BAI, this paper proposes an improved Belgian artificial intelligence (IBAI) algorithm with dynamic difficulty adjustment (DDA) and implements two systems separately based on BAI and IBAI in Unreal Engine 4. Advantages on 12 parameters—10.086 mean total score greater, and 0.079 standard deviation smaller—demonstrate that the system based on IBAI has higher adaptability and a better player experience by comparing the two systems in different situations and inviting players to participate in gameplay experiences and questionnaires. The robust dynamic management mechanism of IBAI can help game designers and developers achieve the combat system of action role-playing games more efficiently, thus, shortening the development cycle and improving the player retention rate.
A Study on the Efficiency in the Energy Harvesting Device Using Resonance of Pendulum
Authors: Kim Hyunsu , Lee Sangwoo
Published: November 2022

Recently, increased public interest in pollution caused by fossil fuels has prompted studies on various renewable energy sources. As it is important to ensure power generation efficiency in energy harvesting, research in this area continues. Therefore, this paper presents the results of a numerical analysis to calculate the efficiency of an energy harvesting generator that uses pendulum resonance. The Lagrange equation was used to derive the numerical model of the pendulum, which in turn was used to derive the angle of power generation and time required to reach this angle. The power generation efficiency was derived by calculating the input and output work using the power generation angle and time obtained from the numerical model. In addition, the effect of design variables, such as the mass of the pendulum, the length of the pendulum, and angle at which power generation starts, on the efficiency is considered by presenting an efficiency map. The efficiency map presented in this study is expected to be an important reference for designing highly efficient energy harvesting devices using pendulum resonance.
Stability of MSW Landfill Slopes Reinforced with Geogrids
Authors: Keskin Mehmet Salih , Kezer Sedat
Published: November 2022

Slope stability is one of the main problems encountered in MSW (municipality solid waste) landfill designs. Slope stability calculations become difficult due to the heterogeneous structure of MSW landfills and leachate, and therefore, slope geometries are formed by choosing low slope angles for safe designs. This causes less waste to be stored on site. This study presents slope stability analyses of MSW landfills. Numerical analyses were performed using finite element and limit equilibrium methods. The stability behavior of landfill slopes was analyzed for both unreinforced and geogrid-reinforced conditions in order to investigate the effects of shear strength parameters, the unit weight of soil waste, and material model parameters. It has been seen that the stability of landfill slopes can be increased significantly using geogrid materials. When the optimum geogrid parameters obtained from the numerical analysis results are used, it has been observed that the safety factor of the slope can be increased by up to approximately two times. Slopes in landfills reinforced with geogrid reinforcements can be formed steeper, allowing more solid waste to be stored. Considering the high initial investment cost of MSW landfills, it has been concluded that storing more solid waste with the use of geogrids will provide significant economic gains. Based on the results, the optimum values of geogrid parameters were determined and suggested for maximum reinforcing effects in MSW landfill slopes.
Study on Size Optimization of a Protective Coal Pillar under a Double-Key Stratum Structure
Authors: Zhang Daming , Zhao Hui , Li Gang
Published: November 2022

Because of the problem that the size of a coal pillar is difficult to determine and it is easy to waste coal resources, taking the Sangou Xindu coal industry as the engineering background, this paper examined the roof cutting and pressure relief technology of small coal pillar gob-side entry driving by means of theoretical analysis, laboratory experiments, and numerical simulation. Through theoretical calculations, the coal pillar width should not be less than 7.15 m without cutting the top. According to the theory of key strata, there are two key strata in the overlying strata on the working face, namely the main key strata and the subkey strata. Through numerical simulation, the stress evolution characteristics of the coal at the side of the goaf under the double-key stratum roof cutting structure are studied. When the roof is not cut, the roof cutting height is 6 m and 12 m and the width of the lateral stress reduction zone in the goaf is 4 m, 8 m, and 10.5 m, respectively. Therefore, the cutting top height is determined to be 12 m and the hydraulic fracturing cutting plan is designed. After cutting the top of the main key stratum, the size of the coal pillar is optimized. Three schemes of coal pillar sizes of 6 m, 5 m, and 4 m are designed for simulation and the analysis shows that it is most reasonable to keep a 5 m wide coal pillar. After field application, the deformation of the surrounding rock in the roadway is within a controllable range and the roadway use is good.
Identification of Content-Adaptive Image Steganography Using Convolutional Neural Network Guided by High-Pass Kernel
Authors: Agarwal Saurabh , Jung Ki-Hyun
Published: November 2022

Digital images are very popular and commonly used for hiding crucial data. In a few instances, image steganography is misused for communicating with improper data. In this paper, a robust deep neural network is proposed for the identification of content-adaptive image steganography schemes. Multiple novel strategies are applied to improve detection performance. Two non-trainable convolutional layers is used to guide the proposed CNN with fixed kernels. Thirty-one kernels are used in both non-trainable layers, of which thirty are high-pass kernels and one is the neutral kernel. The layer-specific learning rate is applied for each layer. ReLU with customized thresholding is applied to achieve better performance. In the proposed method, image down-sampling is not performed; only the global average pooling layer is considered in the last part of the network. The experimental results are verified on BOWS2 and BOSSBase image sets. Content-adaptive steganography schemes, such as HILL, Mi-POD, S-UNIWARD, and WOW, are considered for generating the stego images with different payloads. In experimental analysis, the proposed scheme is compared with some of the latest schemes, where the proposed scheme outperforms other state-of-the-art techniques in the most cases.
Laboratory Experimental Study on Polymer Flooding in High-Temperature and High-Salinity Heavy Oil Reservoir
Authors: Zhang Fujian , Jiang Youwei , Liu Pengcheng , Wang Bojun , Sun Shuaishuai , Hua Daode , Zhao Jiu
Published: November 2022

Polyacrylamide (HPAM) and other traditional polymers have poor temperature resistance and salinity tolerance and do not meet the needs of high-temperature and high-salinity reservoirs. In this study, a new temperature-resistant and salinity-tolerant polymer QJ75-39 was synthesized using acrylamide (AM) as a hydrophilic monomer, 1-acrylamide-2-methylpropanesulfonic acid (AMPS) and N-vinylpyrrolidone (NVP) as functional monomers and DS-16 as a hydrophobic monomer. Through laboratory experiments, the properties (temperature resistance, salinity tolerance and aging stability), polymer injection and core displacement effect of the polymer were studied. The experimental results showed that the new polymer could meet the needs of polymer flooding technology in high-temperature and high-salinity reservoirs. Experiments showed that the polymer had a temperature resistance of 95 °C and a salinity tolerance of 1.66 × 105 mg/L. When the temperature was 95 °C and the TDS was 55,376.8 mg/L, the viscosity of the polymer was 31.3 mPa s, and the viscosity remained above 30 mPa·s after aging for 60 days. The polymer had good injectivity between 300 and 600 mD, and the injection pressure could reach equilibrium quickly. The oil recovery effectively increased with the grsowth in the amount of injected polymer. When the injection amount was 0.5 PV, the enhanced oil recovery was 20.65%. This study is of great significance for the application and popularization of polymer flooding technology in high-temperature and high-salinity reservoirs.
AI Approaches in Computer-Aided Diagnosis and Recognition of Neoplastic Changes in MRI Brain Images
Authors: Kluk Jakub , Ogiela Marek R.
Published: November 2022

Advanced diagnosis systems provide doctors with an abundance of high-quality data, which allows for diagnosing dangerous diseases, such as brain cancers. Unfortunately, humans flooded with such plentiful information might overlook tumor symptoms. Hence, diagnostical devices are becoming more commonly combined with software systems, enhancing the decisioning process. This work picks up the subject of designing a neural network based system that allows for automatic brain tumor diagnosis from MRI images and points out important areas. The application intends to speed up the diagnosis and lower the risk of slipping up on a neoplastic lesion. The study based on two types of neural networks, Convolutional Neural Networks and Vision Transformers, aimed to assess the capabilities of the innovative ViT and its possible future evolution compared with well-known CNNs. The research reveals a tumor recognition rate as high as 90% with both architectures, while the Vision Transformer turned out to be easier to train and provided more detailed decision reasoning. The results show that computer-aided diagnosis and ViTs might be a significant part of modern medicine development in IoT and healthcare systems.
A Cost-Effective Triplet Lens Design with Chromatic Aberration Correction Based on Optimization Algorithm and Illustration Method
Authors: Sun Wen-Shing , Tien Chuen-Lin , Liang Siao-Suang , Lin Jhe-Syuan
Published: November 2022

This paper proposes an optimization algorithm combined with an illustration method to select the three best glass materials for the design of a thickened triplet lens and a correction of the paraxial chromatic aberrations. In the thin lens thickening process, chromatic aberration arises from the deviation between the real and paraxial chromatic aberrations. To solve this problem, we propose an optimization algorithm and illustration method, which are integrated into a thickened triplet lens design. We optimize the eight thickened triplet lens groups to obtain the longitudinal chromatic aberration curve for the best group in the visible light range from 0.4861 μm to 0.6563 μm. The chromatic aberration curve area is 3.33 × 10−7 (μm × mm) for the longitudinal chromatic aberration and 2.11 × 10−5 (μm × mm) for the lateral chromatic aberration. Finally, the chromatic aberration of the thicken triplet lens is close to that of the thin triplet lens design, and the proposed method can obtain a good optical performance.