bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of suprathermal electrons on electron-acoustic instabilities
Authors: Guo Ran
Published: November 2022

We study the electron-acoustic instabilities in plasmas with two kappa-distributed electrons and stationary ions. The instabilities are driven by the relative drift between two electron components. The suprathermal effects of different species on growth rates and instability thresholds are analyzed and compared by numerical calculations. The present study reveals that the suprathermal electrons with slow most probable speed play more important roles than the suprathermal ones with fast most probable speed. The former significantly reduces the instabilities and raises the instability thresholds. The parameters used in this study are inspired from the observations in Earth’s magnetopause.
Interventions After First Post-Transplant Cutaneous Squamous Cell Carcinoma: A Proposed Decision Framework
Authors: Bottomley Matthew J. , Massey Paul R. , Thuraisingham Raj , Doyle Alden , Rao Swati , Bibee Kristin P. , Bouwes Bavinck Jan Nico , Jambusaria-Pahlajani Anokhi , Harwood Catherine A.
Published: November 2022

Cutaneous squamous cell carcinoma (CSCC) is a major cause of morbidity and mortality after organ transplant. Many patients subsequently develop multiple CSCC following a first CSCC, and the risk of metastasis and death is significantly increased compared to the general population. Post-transplant CSCC represents a disease at the interface of dermatology and transplant medicine. Both systemic chemoprevention and modulation of immunosuppression are frequently employed in patients with multiple CSCC, yet there is little consensus on their use after first CSCC to reduce risk of subsequent tumors. While relatively few controlled trials have been undertaken, extrapolation of observational data suggests the most effective interventions may be at the time of first CSCC. We review the need for intervention after a first post-transplant CSCC and evidence for use of various approaches as secondary prevention, before discussing barriers preventing engagement with this approach and finally highlight areas for future research. Close collaboration between specialties to ensure prompt deployment of these interventions after a first CSCC may improve patient outcomes.
Robust Stabilization of Underactuated Two-Wheeled Balancing Vehicles on Uncertain Terrains with Nonlinear-Model-Based Disturbance Compensation
Authors: Kim Yongkuk , Kwon SangJoo
Published: November 2022

Two-wheeled inverted pendulum (TWIP) vehicles are prone to lose their mobility and postural stability owing to their inherently unstable and underactuated dynamic characteristics, specifically when they encounter abruptly changed slopes or ground friction. Overcoming such environmental disturbances is essential to realize an agile TWIP-based mobile platform. In this paper, we suggest a disturbance compensation method that is compatible with unmanned TWIP systems in terms of the nonlinear-model-based disturbance observer, where the underactuated dynamic model is transformed to a fully actuated form by regarding the gravitational moment of the inverted pendulum as a supplementary pseudo-actuator to counteract the pitch-directional disturbances. Consequently, it enables us to intuitively determine the disturbance compensation input of the two wheels and the pitch reference input accommodating to uncertain terrains in real time. Through simulation and experimental results, the effectiveness of the proposed method is validated.
Numerical Comparison of Contact Force Models in the Discrete Element Method
Authors: Li Ziwen , Zeng Xiangyuan , Wen Tongge , Zhang Yonglong
Published: November 2022

The discrete element method (DEM) is usually applied in analyzing the scientifical origin/evolution of the asteroids and the landing/sampling of the regolith. In order to manage the contact between the non-spherical granules, the Polygonal Contact Model (PCM) has been introduced into the DEM method. This paper applies four different contact force models in the newly-proposed DEM algorithm to analyze their difference and implication. The four contact force models include one linear model and three nonlinear models derived from the complete Mindlin–Deresiewicz equations. By considering the macroscopical results and calculation efficiency, the single-collision and multiple-collision cases are analyzed by comparing the four contact models. Specifically, the restitution coefficient, the angular velocity, the rebound angle, and the kinetic energy are applied as indicators for the single collision. The multiple-collision case is studied under the Brazil nut effect with ellipsoidal granules. Additionally, the softening feasibility is also discussed by decreasing the Young’s modulus of the material, mainly analyzing the outgoing results and the calculation efficiency.
Designing an Interactively Cognitive Humanoid Field-Phenotyping Robot for In-Field Rice Tiller Counting
Authors: Huang Yixiang , Xia Pengcheng , Gong Liang , Chen Binhao , Li Yanming , Liu Chengliang
Published: November 2022

Field phenotyping is a crucial process in crop breeding, and traditional manual phenotyping is labor-intensive and time-consuming. Therefore, many automatic high-throughput phenotyping platforms (HTPPs) have been studied. However, existing automatic phenotyping methods encounter occlusion problems in fields. This paper presents a new in-field interactive cognition phenotyping paradigm. An active interactive cognition method is proposed to remove occlusion and overlap for better detectable quasi-structured environment construction with a field phenotyping robot. First, a humanoid robot equipped with image acquiring sensory devices is designed to contain an intuitive remote control for field phenotyping manipulations. Second, a bio-inspired solution is introduced to allow the phenotyping robot to mimic the manual phenotyping operations. In this way, automatic high-throughput phenotyping of the full growth period is realized and a large volume of tiller counting data is availed. Third, an attentional residual network (AtResNet) is proposed for rice tiller number recognition. The in-field experiment shows that the proposed method achieves approximately 95% recognition accuracy with the interactive cognition phenotyping platform. This paper opens new possibilities to solve the common technical problems of occlusion and observation pose in field phenotyping.
Insect Detection in Sticky Trap Images of Tomato Crops Using Machine Learning
Authors: Domingues Tiago , Brandão Tomás , Ribeiro Ricardo , Ferreira João C.
Published: November 2022

As climate change, biodiversity loss, and biological invaders are all on the rise, the significance of conservation and pest management initiatives cannot be stressed. Insect traps are frequently used in projects to discover and monitor insect populations, assign management and conservation strategies, and assess the effectiveness of treatment. This paper assesses the application of YOLOv5 for detecting insects in yellow sticky traps using images collected from insect traps in Portuguese tomato plantations, acquired under open field conditions. Furthermore, a sliding window approach was used to minimize insect detection duplicates in a non-complex way. This article also contributes to event forecasting in agriculture fields, such as diseases and pests outbreak, by obtaining insect-related metrics that can be further analyzed and combined with other data extracted from the crop fields, contributing to smart farming and precision agriculture. The proposed method achieved good results when compared to related works, reaching 94.4% for mAP_0.5, with a precision and recall of 88% and 91%, respectively, using YOLOv5x.
Model and Method of Fault Signal Diagnosis for Blockage and Slippage of Rice Threshing Drum
Authors: Hao Shuaihua , Tang Zhong , Guo Songbao , Ding Zhao , Su Zhan
Published: November 2022

Rice threshing drum of combine harvester is difficult to monitor and repair the abnormal state in time. When slippage or blockage occurs in the threshing drum, the working efficiency of the threshing drum will reduce seriously, such as the threshing efficiency will decline seriously, and then cleaning performance of combine harvester will decline. In order to reveal the vibration characteristics of rice threshing drum under different working conditions and the vibration response state of the drum bearing undergoing different faults occur, the vibration system model of the threshing drum is established in this paper. With the help of the vibration test bench of the multi-stage threshing drum, the vibration signal test of the slippage and blockage of the threshing drum under the belt drive mode is carried out. The results show that the Z direction signal has a vibration peak at the low frequency (25 Hz) when the threshing drum is blocked, the maximum vibration displacement is about 0.55 mm; the Z direction signal signal peak is concentrated at 50 Hz when a slip fault occurs, and the maximum vibration displacement is about 0.184 mm, the fitting effect between frequency and mathematical model is good. The results of this paper reveal the vibration characteristics of the threshing drum under different abnormal working conditions, at the same time provide a theoretical basis for the fault diagnosis of the threshing drum of the combine harvester.
Hydrogeochemical Studies to Assess the Suitability of Groundwater for Drinking and Irrigation Purposes: The Upper East Region of Ghana Case Study
Authors: Obiri-Nyarko Franklin , Asugre Stephen Junior , Asare Sandra Vincentia , Duah Anthony Appiah , Karikari Anthony Yaw , Kwiatkowska-Malina Jolanta , Malina Grzegorz
Published: November 2022

Groundwater is increasingly being used to help meet the Sustainable Development Goals (SDGs) 2 and 6 in many parts of the world, including Ghana. Against this background, hydrogeochemical and multivariate statistical studies were conducted to determine the physicochemical characteristics and suitability of groundwater in some agrarian communities in the Upper East Region of Ghana for drinking and irrigational farming. Additional analyses were also performed to identify potential health risks associated with the groundwater use and to better understand the hydrogeochemical processes controlling groundwater evolution for its effective management. The results showed that the groundwater is typically fresh; moderate to very hard in character; undersaturated with calcite, dolomite, halite, and gypsum; and supersaturated with quartz and amorphous silica. The physicochemical characteristics of the groundwater are controlled by both anthropogenic and natural activities/processes, such as fertilizer application, irrigation return flows, rock weathering, and forward/reverse cation exchange. The total dissolved solids (TDS) (165–524 mg/L), electrical conductivity (EC) (275–873 μS/cm), sodium percentage (Na%; 9.05–17.74%), magnesium ratios (MR) (29.25–53.3%), permeability index (PI) (36.6–74.6%), and sodium adsorption ratio (SAR) (0.20–0.51) point to the possibility of using the groundwater for irrigation, however, with some salinity control. The water quality and health risk analysis also revealed that the groundwater can be used for drinking; however, the high concentrations of fluoride, which can cause noncarcinogenic health issues such as dental and skeletal fluorosis in both adults and children, must be reduced to the WHO required level of 1.5 mg/L.
A Hydraulic Evapotranspiration Multisensor
Authors: Kypris Dedalos , Nikolaou Georgios , Evangellides Eustathios , Neocleous Damianos
Published: November 2022

An exclusively mechanical stand-alone automatic device, self-adjusting to weather changes for controlled irrigation, that operates only on the energy of piped water, without electricity, is the described low-cost “Hydraulic Evapotranspiration Multisensor-HEM”. It is composed of an Evaporation Pan with water left to evaporate, a Floater with a Magnet floating in this water, a Hydraulic Device managing a Hydraulic Water Valve having means to adjust irrigation frequency, and a system that returns water to said Pan, through an Adjustable Dripper, to replace that lost by evaporation. During the Evaporation Phase, gradually the water level is lowered to a predetermined level, at which the floating Magnet acts on said Hydraulic Device to start irrigation. Water from the irrigation line is returned to the Evaporation Pan at the proper for the irrigation time rate. When the lost water is replaced irrigation is terminated and the system resets. On installation Irrigation Frequency and Irrigation Time are set with two graduated screws, for normal weather and the conditions of the particular plantation. HEM responding to weather changes modifies the irrigation schedule set, either by shortening, at a high evaporation rate, the time interval between consecutive irrigation cycles to protect plantations from water deficit stress or extending this time interval at a low evaporation rate to save water. Assessing the performance of HEM, by taking the estimations of evapotranspiration from the Penman–Monteith method shows high accuracy in the studied site. Considering the advantages of the product against the programmable irrigation controller devices, HEM provides optimum irrigation control in field crops and makes it a powerful “green tool” to be used in Mediterranean greenhouses.
Relationship between the Dynamics of Gross Composition, Free Fatty Acids and Biogenic Amines, and Microbial Shifts during the Ripening of Raw Ewe Milk-Derived Idiazabal Cheese
Authors: Santamarina-García Gorka , Amores Gustavo , López de Armentia Emma , Hernández Igor , Virto Mailo
Published: November 2022

This study reports for the first time the relationship between bacterial succession, characterized by high-throughput sequencing (sequencing of V3–V4 16S rRNA regions), and the evolution of gross composition, free fatty acids (FFAs) and biogenic amines (BAs) during cheese ripening. Specifically, Idiazabal PDO cheese, a raw ewe milk-derived semi-hard o hard cheese, was analysed. Altogether, 8 gross parameters were monitored (pH, dry matter, protein, fat, Ca, Mg, P and NaCl) and 21 FFAs and 8 BAs were detected. The ripening time influenced the concentration of most physico-chemical parameters, whereas the producer mainly affected the gross composition and FFAs. Through an O2PLS approach, the non-starter lactic acid bacteria Lactobacillus, Enterococcus and Streptococcus were reported as positively related to the evolution of gross composition and FFAs release, while only Lactobacillus was positively related to BAs production. Several environmental or non-desirable bacteria showed negative correlations, which could indicate the negative impact of gross composition on their growth, the antimicrobial effect of FFAs and/or the metabolic use of FFAs by these genera, and their ability to degrade BAs. Nonetheless, Obesumbacterium and Chromohalobacter were positively associated with the synthesis of FFAs and BAs, respectively. This research work provides novel information that may contribute to the understanding of possible functional relationships between bacterial communities and the evolution of several cheese quality and safety parameters.
Environmental Niche Modelling Predicts a Contraction in the Potential Distribution of Two Boreal Owl Species under Different Climate Scenarios
Authors: Cerman Kristina , Rajković Draženko , Topić Biljana , Topić Goran , Shurulinkov Peter , Mihelič Tomaž , Delgado Juan D.
Published: November 2022

Studying current and future geographic distribution is essential for conserving endangered species such as the Boreal Owl and Eurasian Pygmy Owl. The main aim of this study was to determine the potential distribution of both species in the Balkan Peninsula by using spatial distribution models (SDMs) in MaxEnt. We used data from field surveys, the scientific and grey literature, and an online database. We considered the current time and two future periods, 2041–2060 and 2061–2080. For future periods, we included different climate scenarios (SSP 126, 245, 370, and 585) in studying the potential geographic distribution of both species. We identified two types of potential future refugia for species: in situ and ex situ. Our study shows the highly suitable area for the Boreal Owl increased during the 2041–2060 period compared with the current area in all scenarios, except in SSP 585. However, during the 2061–2080 period, the highly suitable areas contracted. For the Eurasian Pygmy Owl, highly suitable areas decreased during 2041–2060, but during the 2061–2080 period, it was larger than the current area. Our study is of importance for conservation and preserving areas of potential distribution and refugia for Boreal and Eurasian Pygmy Owls in the face of climate change.
Implications of Salinity and Acidic Environments on Fitness and Oxidative Stress Parameters in Early Developing Seahorses Hippocampus reidi
Authors: Carneiro Mario D. D. , García-Mesa Sergio , Sampaio Luis A. , Planas Miquel
Published: November 2022

Water acidification affects aquatic species, both in natural environmental conditions and in ex situ rearing production systems. The chronic effects of acidic conditions (pH 6.5 vs. pH 8.0) in seahorses (Hippocampus spp.) are not well known, especially when coupled with salinity interaction. This study investigated the implications of pH on the growth and oxidative stress in the seahorse Hippocampus reidi (Ginsburg, 1933), one of the most important seahorse species in the ornamental trade. Two trials were carried out in juveniles (0–21 and 21–50 DAR—days after the male’s pouch release) reared under acid (6.5) and control (8.0) pH, both in brackish water (BW—salinity 11) and seawater (SW—salinity 33). In the first trial (0–21 DAR), there was no effect of pH on the growth of seahorses reared in SW, but the survival rate was higher for juveniles raised in SW at pH 6.5. However, the growth and survival of juveniles reared in BW were impaired at pH 6.5. Compared to SW conditions, the levels of superoxide dismutase and DT-diaphorase, as well as the oxidative stress index, increased for juveniles reared in BW. In the second trial, seahorse juveniles were reared in SW at pH 8.0, and subsequently kept for four weeks (from 21 to 50 DAR) at pH 6.5 and 8.0. The final survival rates and condition index were similar in both treatments. However, the growth under acidic conditions was higher than at pH 8.0. In conclusion, this study highlights that survival, growth, and oxidative status condition was enhanced in seahorse juveniles reared in SW under acidic conditions (pH = 6.5). The concurrent conditions of acidic pH (6.5) and BW should be avoided due to harmful effects on the fitness and development of seahorse juveniles.
Impact of Lower Airway Inflammation on Fitness Parameters in Standardbred Racehorses
Authors: Lo Feudo Chiara Maria , Stucchi Luca , Conturba Bianca , Stancari Giovanni , Ferrucci Francesco
Published: November 2022

Mild–moderate equine asthma (MEA) is a common respiratory disorder among racehorses, characterized by lower airway inflammation. Although it is generally agreed that MEA causes poor performance, contrasting results have been reported about the effects of tracheal mucus and the leukocyte populations of the bronchoalveolar lavage (BAL) on performance. This study aims to investigate the associations between airway inflammation and fitness parameters measured during an incremental treadmill test on Standardbred racehorses. For this purpose, the clinical records of 116 Standardbreds subjected to a diagnostic protocol for poor performance were retrospectively reviewed. Parametric and nonparametric statistics were used to evaluate the relationships between endoscopic scores, BAL cytological results, and fitness parameters. Moreover, horses were divided into MEA and non-MEA groups and into neutrophilic, eosinophilic–mastocytic, and mixed MEA groups; fitness parameters were compared between groups. Neutrophils percentages were inversely correlated with the speed at a heart rate of 200 bpm, the speed and heart rate at a plasma lactate concentration of 4 mmol/L (VLa4 and HRLa4), and the maximal speed, while they were positively correlated with higher lactate concentrations. Moreover, significant differences were detected between different MEA subtypes concerning VLa4, HRLa4, and lactate concentrations. These results suggest that airway neutrophilic inflammation impairs athletic capacity in Standardbreds.
Demographic Analysis of Shortfin Mako Shark (Isurus oxyrinchus) in the South Pacific Ocean
Authors: Huynh Hoang Huy , Hung Chun-Yi , Tsai Wen-Pei
Published: November 2022

The shortfin mako shark (Isurus oxyrinchus) demonstrates low productivity and is thus relatively sensitive to fishing. Natural mortality (M) and fishing mortality (F) data are critical to determine their population dynamics. However, catch and fishing effort data are unavailable for this species in the South Pacific Ocean, making stock assessments difficult. Demographic quantitative methods aid in analyzing species with limited data availability. We used a two-sex stage-structured matrix population model to examine the demographic stock status of mako sharks. However, data-limited models to determine fishery management strategies have limitations. We performed Monte Carlo simulations to evaluate the effects of uncertainty on the estimated mako shark population growth rate. Under unfished conditions, the simulations demonstrated that the mako sharks showed a higher finite population growth rate in the 2-year reproductive cycle compared to the 3-year reproductive cycle. Protecting immature mako sharks led to a higher population growth rate than protecting mature mako sharks. According to the sex-specific data, protecting immature male and female sharks led to a higher population growth rate than protecting mature male and female sharks. In conclusion, sex-specific management measures can facilitate the sustainable mako shark conservation and management.
Post Mortem Study on the Effects of Routine Handling and Manipulation of Laboratory Mice
Authors: Assenmacher Charles-Antoine , Lanza Matthew , Tarrant James C , Gardiner Kristin L , Blankemeyer Eric , Radaelli Enrico
Published: November 2022

Routine handling and manipulation of laboratory mice are integral components of most preclinical studies. Any type of handling and manipulation may cause stress and result in physical harm to mice, potentially leading to unintended consequences of experimental outcomes. Nevertheless, the pathological effects of these interventions are poorly documented and assumed to have a negligible effect on experimental variables. In that context, we provide a comprehensive post mortem overview of the main pathological changes associated with routine interventions (i.e., restraint, blood drawing, and intraperitoneal injections) of laboratory mice with an emphasis on presumed traumatic osteoarticular lesions. A total of 1000 mice from various studies were included, with 864 animals being heavily manipulated and 136 being handled for routine husbandry procedures only. The most common lesions observed were associated with blood collection or intraperitoneal injections, as well as a series of traumatic osteoarticular lesions likely resulting from restraint. Osteoarticular lesions were found in 62 animals (61 heavily manipulated; 1 unmanipulated) with rib fractures and avulsion of the dens of the axis being over-represented. Histopathology and micro-CT confirmed the traumatic nature of the rib fractures. While these lesions might be unavoidable if mice are manipulated according to the current standards, intentional training of research personnel on appropriate mouse handling and restraint techniques could help reduce their frequency and the impact on animal wellbeing as well as study reproducibility.
Deep Learning and Antibiotic Resistance
Authors: Popa Stefan Lucian , Pop Cristina , Dita Miruna Oana , Brata Vlad Dumitru , Bolchis Roxana , Czako Zoltan , Saadani Mohamed Mehdi , Ismaiel Abdulrahman , Dumitrascu Dinu Iuliu , Grad Simona , David Liliana , Cismaru Gabriel , Padureanu Alexandru Marius
Published: November 2022

Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless all known antibiotics in the fight against bacterial infections. Although bacterial resistance appeared before any human life form, this process has accelerated in the past years. Important causes of AR in modern times could be the over-prescription of antibiotics, the presence of faulty infection-prevention strategies, pollution in overcrowded areas, or the use of antibiotics in agriculture and farming, together with a decreased interest from the pharmaceutical industry in researching and testing new antibiotics. The last cause is primarily due to the high costs of developing antibiotics. The aim of the present review is to highlight the techniques that are being developed for the identification of new antibiotics to assist this lengthy process, using artificial intelligence (AI). AI can shorten the preclinical phase by rapidly generating many substances based on algorithms created by machine learning (ML) through techniques such as neural networks (NN) or deep learning (DL). Recently, a text mining system that incorporates DL algorithms was used to help and speed up the data curation process. Moreover, new and old methods are being used to identify new antibiotics, such as the combination of quantitative structure-activity relationship (QSAR) methods with ML or Raman spectroscopy and MALDI-TOF MS combined with NN, offering faster and easier interpretation of results. Thus, AI techniques are important additional tools for researchers and clinicians in the race for new methods of overcoming bacterial resistance.
An Overview of Repurposed Drugs for Potential COVID-19 Treatment
Authors: Govender Kamini , Chuturgoon Anil
Published: November 2022

The COVID-19 pandemic caused by SARS-CoV-2 has placed severe constraints on healthcare systems around the globe. The SARS-CoV-2 virus has caused upheaval in the healthcare and economic sectors worldwide. On the 20th of May 2020, the World Health Organisation declared COVID-19 a global pandemic due to the unprecedented number of cases reported around the globe. As of the 4th of November 2022, there were 637,117,429 coronavirus cases reported globally by Worldometer stats, with 6,602,572 related deaths. In South Africa, there were approximately 4,029,496 coronavirus cases and 102,311 associated deaths. As such, there is a need for efficacious therapeutic regimes. There has been a paucity of knowledge encompassing the use of effective and specific antiviral drug therapies for treating COVID-19 since the outbreak. In this review, we provide valuable insights into the repurposing of current drugs for COVID-19. Drug repurposing provides a suitable option for the discovery of efficacious drugs for COVID-19, thereby decreasing the costs and turnaround times of drug development strategies. This review provides an overview of ten drugs, including antimalarial, antiparasitic, anti-inflammatory, nucleoside analogue, monoclonal-antibody drugs, that were repurposed for the potential treatment of COVID-19.
Dietary Supplementation of Silybum marianum Seeds Improved Growth Performance and Upregulated Associated Gene Expression of Muscovy Ducklings (Cairina moschata)
Authors: El-Garhy Osama , Soudy Fathia A. , Alharbi Yousef M. , Alshanbari Fahad A. , Almujaydil Mona S. , Alhomaid Raghad M. , Ahmed-Farid Omar A. , Mohamed Shereen A. , El-Garhy Hoda A. S. , Barakat Hassan , EL Nagar Ayman G.
Published: November 2022

The effect of feeding on diets supplemented with Silybum marianum L. dry seeds (SMS) on growth performance, mortality percentage, biochemical parameters, the expression profile of related genes, and genotoxic effect in Muscovy ducklings was evaluated during a brooding period of 4 weeks. Two hundred and forty one-day-old Muscovy ducks were randomly assigned to four treatment groups (60 ducklings/group), the first group fed on basal diet with no additives (control), and the second (4 g kg−1), third (8 g kg−1), and fourth (12 g kg−1) groups fed the basal diet supplemented with 0, 4, 8, and 12 g kg−1 diet SMS, respectively. A substantial improvement in live body weight (LBW), body weight gain (BWG), and growth rate (GR), and a decrease in feed conversion ratios (FCR) and mortality rate were shown in ducks fed a diet supplemented with either 8 g kg−1 or 12 g kg−1 SMS compared to the other groups. Relevant improvements in liver function, oxidative stress markers, purinergic cell energy, and brain appetite were recorded on ducklings fed diets supplemented with SMS. Moreover, diets which included 8 or 12 g kg−1 SMS positively upregulated the expression of growth hormone gene (GH) and antioxidant genes (SOD1, SOD2, and CAT). These results are consistent with the increase in liver activity SOD and CAT enzymes, resulting in less DNA fragmentation. Consequently, all the aforementioned improvements in biochemical parameters and gene expression profiling may explain the superiority of the treated ducklings compared with the control group. Conclusively, the SMS could be used as a natural feed additive to promote health status and improve the growth performance of small grower ducks during the brooding period.
Modularization Method to Reuse Medical Knowledge Graphs
Authors: Bravo Maricela , González-Villarreal Darinel , Reyes-Ortiz José A. , Sánchez-Martínez Leonardo D.
Published: November 2022

During the creation and integration of a health care system based on medical knowledge graphs, it is necessary to review and select the vocabularies and definitions that best fit the information requirements of the system being developed. This implies the reuse of medical knowledge graphs; however, full importation of knowledge graphs is not a tractable solution in terms of memory requirements. In this paper, we present a modularization-based method for knowledge graph reuse. A case study of graph reuse is presented by transforming the original model into a lighter one.
Effective Dereverberation with a Lower Complexity at Presence of the Noise
Authors: Tan Fengqi , Bao Changchun , Zhou Jing
Published: November 2022

Adaptive beamforming and deconvolution techniques have shown effectiveness for reducing noise and reverberation. The minimum variance distortionless response (MVDR) beamformer is the most widely used for adaptive beamforming, whereas multichannel linear prediction (MCLP) is an excellent approach for the deconvolution. How to solve the problem where the noise and reverberation occur together is a challenging task. In this paper, the MVDR beamformer and MCLP are effectively combined for noise reduction and dereverberation. Especially, the MCLP coefficients are estimated by the Kalman filter and the MVDR filter based on the complex Gaussian mixture model (CGMM) is used to enhance the speech corrupted by the reverberation with the noise and to estimate the power spectral density (PSD) of the target speech required by the Kalman filter, respectively. The final enhanced speech is obtained by the Kalman filter. Furthermore, a complexity reduction method with respect to the Kalman filter is also proposed based on the Kronecker product. Compared to two advanced algorithms, the integrated sidelobe cancellation and linear prediction (ISCLP) method and the weighted prediction error (WPE) method, which are very effective for removing reverberation, the proposed algorithm shows better performance and lower complexity.
Investigation and Design of the Transonic Laminar Flow Characteristics in a Laminar Aircraft
Authors: Niu Xiaotian , Li Jie
Published: November 2022

Reducing drag is critical to aircraft design. In recent years, laminar technology has become one of the most important feasible technologies for civil aircraft drag reduction design under many design constraints. However, various factors have a certain impact on the laminar flow characteristics in the state of transonic flight. Therefore, it is necessary to deeply understand the specific effects of various flight parameters on the characteristics of laminar flow. In this paper, a parameter sensitivity analysis for a central experimental wing in a special layout aircraft was carried out to investigate its transonic laminar characteristics. Then, the airfoil of the central experimental wing of the aircraft was designed for real flight. The RANS (Reynold-averaged Navier–Stokes) method combined with the γ−Reθ transition model based on local variables was used. The computational approach was validated by the wind tunnel tests and analyzed by the grid independence analysis. The sensitivity mainly focuses on the transition location and the length of the laminar flow zone of the central experiment under different boundary conditions. The transonic transition was affected by a variety of interacting factors that include FSTI (free stream turbulence intensity), pressure gradient, Re (Reynolds number), Ma (Mach number) and α (angle of attack, degree). The essence of the transition is the disruption of flow stability caused by the increase in flow entropy. Among these factors, FSTI directly affects global flow stability, and the pressure gradient affects local flow stability. Ma and α can indirectly affect the flow stability by changing the pressure gradient. Re can control the boundary layer properties to change the flow stability, whereas its effect is easily determined by the pressure gradient. Finally, the improved design of the airfoil with the central experimental wing was conducted. The design of weak shock wave and aerodynamic load on the rear part of the airfoil can improve the aerodynamic characteristics (CL, lift coefficient, increases by 0.28) of the airfoil, which can reduce the load burden on the outboard wing without affecting the laminar flow characteristics of the airfoil. In the next step, cross-flow instability will be considered.
Gamification in Engineering Education: The Use of Classcraft Platform to Improve Motivation and Academic Performance
Authors: Parody Luisa , Santos Jenifer , Trujillo-Cayado Luis Alfonso , Ceballos Manuel
Published: November 2022

Pedagogical innovation involving information and communications technology (ICT) may offer teachers the opportunity to create engaging learning environments in engineering courses. In this paper, we present a gamification teaching experience whose primary objective is to improve motivation, and we obtained results for students of a mathematics course during their first year at university. For this case study, we used Classcraft®, which is a role-playing game supported by a digital platform and a mobile application that has been developed to answer teachers’ classroom management needs. We hypothesized that using this application as ICT could enhance learning and promote the development of the four “super skills” (or the Four C’s): critical thinking, communication, collaboration, and creativity. In order to explore the educational effectiveness of the methodology, a comparison between a gamification group of students and a control group was carried out. Our results showed that the mean mark obtained by the control group students was lower than that obtained by the gamification group students. In addition, the Nemenyi test showed that the Four C’s were improved thanks to the Classcraft® activities and group project. Overall, course participants positively evaluated the use of the gamification platform.
Streptococcus mutans Associated with Endo-Periodontal Lesions in Intact Teeth
Authors: Buonavoglia Alessio , Trotta Adriana , Camero Michele , Cordisco Marco , Dimuccio Michela Maria , Corrente Marialaura
Published: November 2022

A massive periodontal destruction can affect the root canal (RC) system and potentially expose the pulpo-dentinal complex to opportunistic bacteria. Streptococcus mutans is a major pathogen of human caries and periodontal diseases, and its virulence mostly resides in the ability to adhere to collagen and form biofilms, due to collagen-binding proteins (CBPs) Cnm and Cbm. Seventeen patients affected by severe endo-periodontal lesions without caries and/or exposure of pulpal tissue were subjected to tooth extraction and samples for microbiological investigation were collected from the root surface (RS) and RC. The collected swabs were cultivated and subjected to the quantitative real-time PCR (qPCR) for the detection of S. mutans and to the PCR for the cnm/cbm genes investigation, followed by next-generation sequencing (NGS). S. mutans DNA was detected in 12/17 (70.5%) RS samples and in 8/17 (47.0%) RC samples. In the CBPs screening of positive samples, the cnm gene was detected in 4/12 (33.3%) RS and in 1/8 (12.5%) RC samples, whilst all the samples tested negative for the cbm gene. The presence of the cnm gene could enhance the local virulence of the pathogens. Therefore, S. mutans have to be included as potential periodontopathogen bacterium in severe or refractory forms of periodontal diseases.
Development of an Ontology-Based Solution to Reduce the Spread of Viruses
Authors: Saba Djamel , Hadidi Abdelkader , Cheikhrouhou Omar , Hamdi Monia , Hamam Habib
Published: November 2022

With the sudden emergence of many dangerous viruses in recent years and with their rapid transmission and danger to individuals, most countries have adopted several strategies, such as closure and social distancing, to control the spread of the virus in the population. In parallel with all these precautions, scientific laboratories are working on developing the appropriate vaccine, which in many cases takes many years. Until then, it is necessary to resort to many solutions, including solutions that rely on information technologies and artificial intelligence (AI). In this context, this paper proposes a new solution based on the ontology and rules of intelligent reasoning. Initially, the virus environment is analyzed, followed by the extraction and editing of the main elements of the ontology using the “Protégé” software. In the last step, the proposed solution is tested, by choosing the city of Adrar in southwestern Algeria, which was particularly affected by COVID-19. Three scenarios were shown for different cases. The efficiency of the proposed solution was confirmed through the instructions it provides in the event of symptoms appearing in a person. In addition, this solution helps the competent authorities know the location and extent of the epidemic by informing the local communities.
An Interactive System Based on the IASP91 Earth Model for Earthquake Data Processing
Authors: Gao Wenqi , Wang Youxue , Yu Songping
Published: November 2022

System software for interactive human–computer data processing based on the IASP91 Earth model was designed. An interactive data processing system for visualizing earthquake data was designed and implemented via the Intel Fortran platform. The system reads and processes broadband seismic data acquired by field stations, mainly including the reading and import of raw data, pre-processing, identification of seismic phases and inter-correlation traveltimes picking. In the data processing step, shortcomings have been improved and functions have been gradually refined and enhanced, making it easier and faster to process data. It has already processed more than 1000 large seismic events received by the station from 2013 to 2018. The practical application shows that the human–computer interaction system is easy to operate, accurate, fast and flexible, and is an effective tool for processing seismic data.
An Intelligent Healthcare System for Residential Aged Care during the COVID-19 Pandemic
Authors: Chou Hsien-Ming , Pi Shih-Ming , Cho Tsai-Lun
Published: November 2022

There are many healthcare possibilities for the elderly, such as hospitals, nursing homes, and home-based care. However, in times of COVID-19, most home-based elderly people did not have sufficient supplies or healthcare as usual. Fulfilling their desire for an independent lifestyle while protecting them from falls, sudden illness, or accidents is difficult. This study represents a smart system for coping with this problem in public healthcare. The existing methods for residential aged care (RAC), such as fall detection, focus on personal profiles and physical symptoms records or use a collaborative filtering method to notify caregivers or family members that the elderly person may be at a high level of risk. However, these methods have many limitations in times of COVID-19, including insufficient risk factors, problems gathering information from mobile sensors, and issues with handling human variability. This study proposes a new method for RAC in times of COVID-19 called the Intelligent Healthcare Agent System (IHAS), which, unlike the old system, incorporates context information, such as indoor and outdoor (IO), standing and lying (SL), and resting and moving (RM). IHAS integrates diverse mobile sensor data and utilizes artificial intelligence (AI) technologies into the research model and learning-oriented prototype system that can manage human variability. Ultimately, this study’s findings should contribute to the existing research and industrial applications of RAC, as well as offer new avenues of study in future research.
Clustering-Based Channel Allocation Method for Mitigating Inter-WBAN Interference
Authors: Song Woojin , Park Jaesung
Published: November 2022

In this paper, we propose a channel assignment method that can mitigate the inter-WBAN interference when the density of WBANs is high. To achieve the goal, we group the coexisting WBANs into a set of clusters by using the Louvain algorithm and allocate different channels to the WBANs in the same cluster by using a graph coloring method. By increasing the distance between the WBANs using the same channel, our method reduces the inter-WBAN interference. As a result, compared with the conventional centralized channel allocation method, our method increases the average data rate of a WBAN more than twice even when the number of coexisting WBANs is larger than the number of available channels. Compared with a distributed method involving an iterative process, our method reduces the channel decision time by 94.6%. Furthermore, since our method self-configures the algorithm parameters dynamically according to the topology changes, it can be used without human intervention even when the topology changes.
A DDoS Detection and Prevention System for IoT Devices and Its Application to Smart Home Environment
Authors: Al-Begain Khalid , Khan Murad , Alothman Basil , Joumaa Chibli , Alrashed Ebrahim
Published: November 2022

The Internet of Things (IoT) has become an integral part of our daily life as it is growing in many fields, such as engineering, e-health, smart homes, smart buildings, agriculture, weather forecasting, etc. However, the growing number of IoT devices and their weak configuration raise many security challenges such as designing protocols to protect these devices from various types of attacks such as using them as bots for DDoS attacks on target servers. In order to protect IoT devices from enslavement as bots in a home environment, we develop a lightweight security model consisting of various security countermeasures. The working mechanism of the proposed security model is presented in a two-part experimental scenario. Firstly, we describe the working mechanism of how an attacker infects an IoT device and then spreads the infection to the entire network. Secondly, we propose a set of mechanisms consisting of filtration, detection of abnormal traffic generated from IoT devices, screening, and publishing the abnormal traffic patterns to the rest of the home routers on the network. We tested the proposed scheme by infecting an IoT device with malicious code. The infected device then infects the rest of the IoT devices in its network and launches a DDoS attack by receiving attack-triggering commands from the botmaster. Finally, the proposed detection mechanism is used to detect the abnormal traffic and block the connection of infected devices in the network. The results reveal that the proposed system blocks abnormal traffic if the packets from an IoT device exceeded a threshold of 50 packets. Similarly, the network packet statistics show that, in the event of an unwanted situation, the detection mechanism runs smoothly and avoids any possible delays in the network.
Towards an Automatic Test Generation Method for Systems of Systems Based on Fault Injection and Model-Based Systems Engineering
Authors: Tian Yingchun , Jing Delin
Published: November 2022

The emergence and development of systems of systems (SoSs) have expanded the complexity and adaptability of systems engineering. Due to the heterogeneity of its constituent systems, designing and analyzing an SoS faces enormous challenges. Therefore, the verification of an SoS is important in its design phase. However, related methods and techniques are still in the preliminary research state, mainly for requirements verification and system verification, and a lack of efforts in design verification for SoSs. Aiming to provide the ability to detect hazardous states at the design phase, we worked on a novel method for automatically generating test cases for model verification in SoSs. Considering the characteristics of SoSs, the method adopts fault injection and model-based system engineering as the foundations to extend the automated generation capability of test cases. This paper proposes an automatic test generation (ATG) method for an SoS based on fault injection and model-based systems engineering (MBSE). It is meant to generate test cases that can be used to check the effectiveness of fault detection or identification in SoSs and for the effective testing of their constituent systems (CSs). This paper discusses scenario generation and ATG in linear temporal logic and designs an algorithm to generate traces as test suites, taking into account the constraints of the models. By establishing a concept alignment example (CAE) as the experimental use case, three test scenarios are generated automatically, showing that the use of the proposed ATG method provides a reasonable hazardous detection capability for verification in SoS design. The main contributions of the paper are (1) the description of the proposed two-phase ATG approach with fault-centric modeling activities and generation-related activities; (2) the explanation of the designed ATG algorithm at both high and low levels; and (3) the discussion of the experiment in an emergency response CAE with three generated test scenarios.
Modern Techniques for Flavonoid Extraction—To Optimize or Not to Optimize?
Authors: Jurinjak Tušek Ana , Šamec Dunja , Šalić Anita
Published: November 2022

Flavonoids, specialized metabolites found in plants, have a number of beneficial properties and are important for maintaining good health. Efficient extraction methods are required to extract the most bioactive compounds from plant material. Modern techniques are replacing conventional methods of flavonoids extraction in order to reduce energy and solvent consumption, increase extraction efficiency, and satisfy growing market demand as well as environmental legislation. The extraction of bioactive molecules compounds is affected by a number of variables. To determine the conditions that ensure the highest extraction yield, it is advisable to analyze the interactions between the above in parallel. In this work, an overview of the advantages and performance of modern methods (microwave-assisted extraction, ultrasound-assisted extraction, pressurized liquids-assisted extraction, and supercritical fluids extraction) for the extraction of flavonoids is presented. This work also presents the application of extraction process optimization and extraction kinetics for flavonoid extraction, using different types of experimental designs for different flavonoid sources and different extraction methods. The general conclusion of all the studies listed is that an experimental design combined with RSM modeling reduces the number of experiments that should be performed to achieve maximum extraction yield.