bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Simulation of Dynamic Response and Evaluation of Flexural Damage of RC Columns under Horizontal Impact Load
Authors: Hu Bin , Cai Jian , Ye Jiabin
Published: November 2021

By using the ABAQUS finite element (FE) model, which has been verified by experiments, the deformation and internal force changes of RC columns during the impact process are investigated, and a parametric analysis is conducted under different impact kinetic energies Ek. According to the development path of the bottom bending moment-column top displacement curve under impact, the member is in a slight damage state when the curve rebounds before reaching the peak and in a moderate or severe damage state when the curve exceeds the peak, in which case the specific damage state of the member needs to be determined by examining whether there is a secondary descending stage in the curve. Accordingly, a qualitative method for evaluating the bending failure of RC column members under impact is obtained. In addition, the damage state of RC columns under impact can also be quantitatively evaluated by the ratio of the equivalent static load Feq and the ultimate static load-bearing capacity Fsu.
Machine Learning Models of COVID-19 Cases in the United States: A Study of Initial Lockdown and Reopen Regimes
Authors: Kamis Arnold , Ding Yudan , Qu Zhenzhen , Zhang Chenchen
Published: November 2021

The purpose of this paper is to model the cases of COVID-19 in the United States from 13 March 2020 to 31 May 2020. Our novel contribution is that we have obtained highly accurate models focused on two different regimes, lockdown and reopen, modeling each regime separately. The predictor variables include aggregated individual movement as well as state population density, health rank, climate temperature, and political color. We apply a variety of machine learning methods to each regime: Multiple Regression, Ridge Regression, Elastic Net Regression, Generalized Additive Model, Gradient Boosted Machine, Regression Tree, Neural Network, and Random Forest. We discover that Gradient Boosted Machines are the most accurate in both regimes. The best models achieve a variance explained of 95.2% in the lockdown regime and 99.2% in the reopen regime. We describe the influence of the predictor variables as they change from regime to regime. Notably, we identify individual person movement, as tracked by GPS data, to be an important predictor variable. We conclude that government lockdowns are an extremely important de-densification strategy. Implications and questions for future research are discussed.
Application of Various YOLO Models for Computer Vision-Based Real-Time Pothole Detection
Authors: Park Sung-Sik , Tran Van-Than , Lee Dong-Eun
Published: November 2021

Pothole repair is one of the paramount tasks in road maintenance. Effective road surface monitoring is an ongoing challenge to the management agency. The current pothole detection, which is conducted image processing with a manual operation, is labour-intensive and time-consuming. Computer vision offers a mean to automate its visual inspection process using digital imaging, hence, identifying potholes from a series of images. The goal of this study is to apply different YOLO models for pothole detection. Three state-of-the-art object detection frameworks (i.e., YOLOv4, YOLOv4-tiny, and YOLOv5s) are experimented to measure their performance involved in real-time responsiveness and detection accuracy using the image set. The image set is identified by running the deep convolutional neural network (CNN) on several deep learning pothole detectors. After collecting a set of 665 images in 720 × 720 pixels resolution that captures various types of potholes on different road surface conditions, the set is divided into training, testing, and validation subsets. A mean average precision at 50% Intersection-over-Union threshold (mAP_0.5) is used to measure the performance of models. The study result shows that the mAP_0.5 of YOLOv4, YOLOv4-tiny, and YOLOv5s are 77.7%, 78.7%, and 74.8%, respectively. It confirms that the YOLOv4-tiny is the best fit model for pothole detection.
Long Distance Moving Vehicle Tracking with a Multirotor Based on IMM-Directional Track Association
Authors: Yeom Seokwon
Published: November 2021

The multirotor has the capability to capture distant objects. Because the computing resources of the multirotor are limited, efficiency is an important factor to consider. In this paper, multiple target tracking with a multirotor at a long distance (~400 m) is addressed; the interacting multiple model (IMM) estimator combined with the directional track-to-track association (abbreviated as track association) is proposed. The previous work of the Kalman estimator with the track association approach is extended to the IMM estimator with the directional track association. The IMM estimator can handle multiple targets with various maneuvers. The track association scheme is modified in consideration of the direction of the target movement. The overall system is composed of moving object detection for measurement generation and multiple target tracking for state estimation. The moving object detection consists of frame-to-frame subtraction of three-color layers and thresholding, morphological operation, and false alarm removing based on the object size and shape properties. The centroid of the detected object is input into the next tracking stage. The track is initialized using the difference between two nearest points measured in consecutive frames. The measurement nearest to the state prediction is used to update the state of the target for measurement-to-track association. The directional track association tests both the hypothesis and the maximum deviation between the displacement and directions of two tracks followed by track selection, fusion, and termination. In the experiment, a multirotor flying at an altitude of 400 m captured 55 moving vehicles around a highway interchange for about 20 s. The tracking performance is evaluated for the IMMs using constant velocity (CV) and constant acceleration (CA) motion models. The IMM-CA with the directional track association scheme outperforms other methods with an average total track life of 91.7% and an average mean track life of 84.2%.
Heuristics for a Two-Stage Assembly-Type Flow Shop with Limited Waiting Time Constraints
Authors: Han Jun-Hee , Lee Ju-Yong
Published: November 2021

This study investigates a two-stage assembly-type flow shop with limited waiting time constraints for minimizing the makespan. The first stage consists of m machines fabricating m types of components, whereas the second stage has a single machine to assemble the components into the final product. In the flow shop, the assembly operations in the second stage should start within the limited waiting times after those components complete in the first stage. For this problem, a mixed-integer programming formulation is provided, and this formulation is used to find an optimal solution using a commercial optimization solver CPLEX. As this problem is proved to be NP-hard, various heuristic algorithms (priority rule-based list scheduling, constructive heuristic, and metaheuristic) are proposed to solve a large-scale problem within a short computation time. To evaluate the proposed algorithms, a series of computational experiments, including the calibration of the metaheuristics, were performed on randomly generated problem instances, and the results showed outperformance of the proposed iterated greedy algorithm and simulated annealing algorithm in small- and large-sized problems, respectively.
K-Means-Based Nature-Inspired Metaheuristic Algorithms for Automatic Data Clustering Problems: Recent Advances and Future Directions
Authors: Ikotun Abiodun M. , Almutari Mubarak S. , Ezugwu Absalom E.
Published: November 2021

K-means clustering algorithm is a partitional clustering algorithm that has been used widely in many applications for traditional clustering due to its simplicity and low computational complexity. This clustering technique depends on the user specification of the number of clusters generated from the dataset, which affects the clustering results. Moreover, random initialization of cluster centers results in its local minimal convergence. Automatic clustering is a recent approach to clustering where the specification of cluster number is not required. In automatic clustering, natural clusters existing in datasets are identified without any background information of the data objects. Nature-inspired metaheuristic optimization algorithms have been deployed in recent times to overcome the challenges of the traditional clustering algorithm in handling automatic data clustering. Some nature-inspired metaheuristics algorithms have been hybridized with the traditional K-means algorithm to boost its performance and capability to handle automatic data clustering problems. This study aims to identify, retrieve, summarize, and analyze recently proposed studies related to the improvements of the K-means clustering algorithm with nature-inspired optimization techniques. A quest approach for article selection was adopted, which led to the identification and selection of 147 related studies from different reputable academic avenues and databases. More so, the analysis revealed that although the K-means algorithm has been well researched in the literature, its superiority over several well-established state-of-the-art clustering algorithms in terms of speed, accessibility, simplicity of use, and applicability to solve clustering problems with unlabeled and nonlinearly separable datasets has been clearly observed in the study. The current study also evaluated and discussed some of the well-known weaknesses of the K-means clustering algorithm, for which the existing improvement methods were conceptualized. It is noteworthy to mention that the current systematic review and analysis of existing literature on K-means enhancement approaches presents possible perspectives in the clustering analysis research domain and serves as a comprehensive source of information regarding the K-means algorithm and its variants for the research community.
Comparative Study of Different Types of Waterproofing Screeds with a Focus on Cohesion with Selected Building Materials after the Freeze-Thaw Exposure
Authors: Nývlt Michal , Pazderka Jiří , Reiterman Pavel
Published: November 2021

The aim of the research was focused on the functionality of three types of waterproofing screeds from the perspective of their use in building structures. Bitumen, polymer, silicate (mineral) were studied in terms of their cohesion with the substrate and their sealing ability, used in combination with different building materials—ceramics, concrete, lime-sand bricks and marl stone, the permeability properties of which were taken into consideration, too. The cohesion was also studied after the freeze-thaw exposure to take into account the aspects of durability. During the experimental program, the basic waterproofing ability of all types of tested screeds applied on building materials was confirmed. Comparing the overall tested screeds, despite the best adhesion of the polymer-based screed, this material exhibited the lowest durability after the freeze-thaw exposure. The bitumen and silicate (mineral) screed attained similar values of adhesion to the studied base materials. However, they differ in their ability to withstand freeze-thaw cycles over time. The modified water permeability test on model masonry specimens was performed. No leakage of water during the test was monitored for the specimens with all types of applied screeds over time, and, in addition, water had not penetrated through the bricks, nor through the joints. The waterproofing effect of the screed is not affected by the joints in masonry.
Ground-Penetrating Radar Prospections to Image the Inner Structure of Coastal Dunes at Sites Characterized by Erosion and Accretion (Northern Tuscany, Italy)
Authors: Ribolini Adriano , Bertoni Duccio , Bini Monica , Sarti Giovanni
Published: November 2021

In this study we aimed to gain insights into dune formation and evolution from select coastal tracts of Northern Tuscany by inspecting their internal sedimentary architecture with Ground-Penetrating Radar (GPR) analysis. Erosion, equilibrium and accretion characterize the selected coastal tracts, and this analysis remarks on some GPR features consistently associated with specific coastal evolution states. A standard sequence of data processing made it possible to trace several radar surfaces and reflectors in the GPR profile, eventually interpreted in terms of depositional processes and erosive events. The stable or currently accreting coastal sectors show radar features compatible with a general beach progradation process, punctuated by berm formation in the general context of a positive sedimentary budget. Additionally, the radar facies distribution locally supports a mechanism of dune nucleation on an abandoned berm. Conversely, the GPR profile of the coastal sector today affected by erosion shows how a negative sedimentary budget inhibited coastal progradation and favored destructive events. These events interacted also with the active dunes, as demonstrated by the overlapping of wave run-up and aeolian radar facies. GPR prospections were effective at delineating the recent/ongoing coastal sedimentary budget by identifying radar features linked to construction/destruction phenomena in the backshore, and to dune nucleation/evolution.
Anticancer Effects of Seaweed-Derived Bioactive Compounds
Authors: Lee Heesu , Selvaraj Baskar , Lee Jae Wook
Published: November 2021

Cancer remains a major life-threatening disease worldwide. The development of anticancer drugs using natural products obtained from marine organisms has been proposed as an alternative approach. Seaweeds are the mainstay of marine ecosystems; therefore, they are highly enriched with diverse bioactive compounds. In the past decade, a vast number of natural compounds, such as polysaccharides, polyphenols, carotenoids, and terpenoids, have been isolated from seaweeds. Seaweeds have bioactive compounds that show cytotoxicity in various cancer cell lines. These compounds prevent tumor growth by inducing apoptotic cell death and arrest growth by interfering with different kinases and cell cycle pathways. This review discussed the anticancer properties of various bioactive compounds isolated from different types of seaweeds and their therapeutic potential against cancers.
Long Short-Term Memory Network-Based Metaheuristic for Effective Electric Energy Consumption Prediction
Authors: Hora Simran Kaur , Poongodan Rachana , de Prado Rocío Pérez , Wozniak Marcin , Divakarachari Parameshachari Bidare
Published: November 2021

The Electric Energy Consumption Prediction (EECP) is a complex and important process in an intelligent energy management system and its importance has been increasing rapidly due to technological developments and human population growth. A reliable and accurate model for EECP is considered a key factor for an appropriate energy management policy. In recent periods, many artificial intelligence-based models have been developed to perform different simulation functions, engineering techniques, and optimal energy forecasting in order to predict future energy demands on the basis of historical data. In this article, a new metaheuristic based on a Long Short-Term Memory (LSTM) network model is proposed for an effective EECP. After collecting data sequences from the Individual Household Electric Power Consumption (IHEPC) dataset and Appliances Load Prediction (AEP) dataset, data refinement is accomplished using min-max and standard transformation methods. Then, the LSTM network with Butterfly Optimization Algorithm (BOA) is developed for EECP. In this article, the BOA is used to select optimal hyperparametric values which precisely describe the EEC patterns and discover the time series dynamics in the energy domain. This extensive experiment conducted on the IHEPC and AEP datasets shows that the proposed model obtains a minimum error rate relative to the existing models.
Estimating CPT Parameters at Unsampled Locations Based on Kriging Interpolation Method
Authors: Liu Jinhao , Liu Jinming , Li Zhongwei , Hou Xiaoyu , Dai Guoliang
Published: November 2021

The cone penetrometer test (CPT) has been widely used in geotechnical investigations. However, how to use the limited CPT data to reasonably predict the soil parameters of the unsampled regions remains a challenge. In the present study, we adopted the Kriging method to obtain the CPT data of an unsampled location in Adelaide, South Australia, based on the collected CPT data from six soundings around this location. Interpolation results showed that the trend of the estimated parameters is consistent with the trend of parameters of the surrounding points. From the Kriging interpolation result, we further carried out axial bearing capacity calculation of a precast concrete pile using the CPT-based direct method to verify the reliability of the method. The calculated bearing capacity of the pile is 99.6 kN which is very close to the true value of 102.8 kN. Our results demonstrated the effectiveness of the Kriging method in considering the soil spatial variability and predicting soil parameters, which is quite suitable for the application in engineering practice.
Profile Design of the Grooved Die and Rolling Force Prediction in the Cold Pilger Rolling Process
Authors: Lee Sang-Kon , Lee Kyung-Hun
Published: November 2021

The objective of this study was to design the die groove profile and predict the rolling force produced when employing the variable curvature rolls and mandrel for manufacturing seamless pipes using the cold pilger rolling process. The parameters of the key process design were the diameter of the initial tube and final product, as well as the feed amount, reduction area, principal deformation zone, and roller radius. The rolling forces during the pilger rolling process were theoretically calculated to enable their prediction, and the characteristics of the cold pilger rolling process were identified. The calculated values were in close agreement with the experimental data. The die groove design is important in the prediction process because the dimensional accuracy of the tubes and the life of the dies are highly dependent on this design. The presented design method can be successfully applied to fulfill this objective. The tube shape and adequate tolerance can be attained by using the proposed design method. The mechanical properties of the pipe are evaluated by calculating the Q factor.
Numerical Modelling of a Floating Wind Turbine Semi-Submersible Platform
Authors: Galera-Calero Lander , Blanco Jesús María , Iglesias Gregorio
Published: November 2021

A detailed study is undertaken of the computational modelling of a sub-platform for floating offshore wind using the software Star-CCM+ with the application of the RANS approach. First, a mathematical introduction to the governing equations is carried out. Then, the computational grid is defined, and the grid-independence of the solution is verified. A time-dependent study is performed with the selected time-step. Finally, two examples of 3D decay tests in heave of the sub-platform without and with moorings are presented, accompanied by a damping factor study, with the aim of providing a better understanding of the hydrodynamic damping of the platform. Throughout the process, three degrees of freedom (DoFs) are locked due to the limitations imposed by the use of a symmetry plane; this implementation allowed us to reduce the computational cost of each simulation by 50%. Therefore, three DoFs (heave, surge and pitch) are considered. The coupling study, adding a mooring system in the decay tests and the regular wave tests, shows good agreement between the experimental and computational results. The first half-period of the simulations presents a greater discrepancy due to the fact that the damping of the platform is lower in the computational simulation. However, this does not imply that the hydrodynamic damping is underestimated but may be directly related to the lock of various DoFs associated with the hydrodynamic damping.
Automated Detection of Gastric Cancer by Retrospective Endoscopic Image Dataset Using U-Net R-CNN
Authors: Teramoto Atsushi , Shibata Tomoyuki , Yamada Hyuga , Hirooka Yoshiki , Saito Kuniaki , Fujita Hiroshi
Published: November 2021

Upper gastrointestinal endoscopy is widely performed to detect early gastric cancers. As an automated detection method for early gastric cancer from endoscopic images, a method involving an object detection model, which is a deep learning technique, was proposed. However, there were challenges regarding the reduction in false positives in the detected results. In this study, we proposed a novel object detection model, U-Net R-CNN, based on a semantic segmentation technique that extracts target objects by performing a local analysis of the images. U-Net was introduced as a semantic segmentation method to detect early candidates for gastric cancer. These candidates were classified as gastric cancer cases or false positives based on box classification using a convolutional neural network. In the experiments, the detection performance was evaluated via the 5-fold cross-validation method using 1208 images of healthy subjects and 533 images of gastric cancer patients. When DenseNet169 was used as the convolutional neural network for box classification, the detection sensitivity and the number of false positives evaluated on a lesion basis were 98% and 0.01 per image, respectively, which improved the detection performance compared to the previous method. These results indicate that the proposed method will be useful for the automated detection of early gastric cancer from endoscopic images.
Durability and Safety Performance of Pavements with Added Photocatalysts
Authors: Jimenez-Relinque Eva , Grande Maria , Rubiano Francisco , Castellote Marta
Published: November 2021

The use of photocatalysts to enhance the performance of construction materials with large surfaces exposed to sunlight has become an increasingly common practice in recent decades. Although construction material durability is of crucial importance and is extensively studied when incorporating new additions, very few studies have specifically addressed the effects when adding photocatalysts. This paper discusses the effect of TiO2-based photocatalysts on pavement durability (porosity, time of transmission of ultrasonic pulses, freeze-thaw resistance and capillary water absorption) and safety (slip resistance and roughness) by comparison of commercial photocatalytic materials of different families and twin materials without the photocatalyst added. The analysis covers concrete tile pavements and porous asphalt treated with photocatalysts in the form of sprayed emulsions, slurry admixtures or built-in during casting. The findings show that changes in the properties of a construction material induced by photocatalytic functionality depend primarily on the porous structure of the matrix and the properties of the resulting photocatalytic surface.
Comparison of the Physicochemical Properties of Chitin Extracted from Cicada orni Sloughs Harvested in Three Different Years and Characterization of the Resulting Chitosan
Authors: Poerio Aurelia , Girardet Thomas , Petit Chloé , Fleutot Solenne , Jehl Jean-Philippe , Arab-Tehrany Elmira , Mano João F. , Cleymand Franck
Published: November 2021

Chitin and its derivative chitosan are among the most used polysaccharides for biomedical and pharmaceutical applications. Most of the commercially available chitin is obtained from seafood wastes. However, the interest in alternative renewable sources of chitin and chitosan, such as insects, is growing. When new sources are identified, their stability over time has to be evaluated to allow for their commercialization. The aim of this study is to compare the physicochemical properties of chitin extracted from Cicada orni sloughs harvested in three different years (2017, 2019 and 2020) in order to assess the stability of the source and the repeatability of the extraction process. Chitin and its derivative chitosan were characterized by simple techniques such as Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). Results suggest that the physicochemical properties of the extracted chitin varied from year to year, and that these differences are not due to the extraction process, but rather to intrinsic differences within the source. We showed that these differences could already be detected by analyzing the raw material (i.e., cicada sloughs) using the above-mentioned simple methods. The chitosan obtained from deacetylation of chitin had a low degree of deacetylation (66.2±1.6%). This low degree of deacetylation can be attributed to the deacetylation process, which is probably not appropriate for this source of chitin.
Color in Selected Artistic Glass Compositions by Tomasz Urbanowicz as an Element of Intervention in Historic Buildings and Contemporary Architecture
Authors: Gronostajska Barbara Ewa , Urbanowicz Konrad
Published: November 2021

Colored glass in the form of stained-glass windows has been used to decorate buildings for over a thousand years. Due to various late-twentieth-century technological achievements, this material allows for a broad spectrum of design solutions. Glass can be used both in contemporary and historical buildings. This paper presents an analysis of the work of Tomasz Urbanowicz, an artist who works with glass, and its objective is to present not only the body of work of this artist but also the means of using colored glass in creating new values in architecture. The work is based on a study of the literature that covers the contemporary application of colored glass, on-site analysis of projects, and a series of interviews with the artist before, during, and after project completion, as well as the authors’ personal experience in the matter. One of the main research methods used was an analysis of the artist’s stance, as to him, the very process of pursuing creative inspiration is a fundamental procedure. Glassworks by Urbanowicz were displayed at the EXPO 2000 in Hanover (Germany), the EXPO 2005 in Aichi (Japan), and the EXPO 2008 in Saragossa (Spain). The United Earth glass sphere has been decorating the agora of the European Parliament building in Strasbourg (France) since 2004. In the paper, the artist’s projects are presented in two groups: The first includes solutions that employ monochromatic color schemes, whereas in the second, color has been used to create a strong contrast. The analysis presented includes interventions in historical buildings under heritage conservation, but also compositions from architectural glass in newly built buildings and that reference place-based history. Both the initial vision and the final effect of the glass architectural compositions are site-specific. The analysis of these differences and how the artist works allowed us to formulate a scheme of how he operates. Urbanowicz’s glass interventions affect the quality of the spaces they create and highlight their existing or expected features. The influence of the works can either play a primary and dominant role in relation with the surrounding space or be a secondary and delicate addition. Applied color may have different functions, from highlighting specific aspects of a building to introducing symbolic or direct reference. In many projects, color works as a source of a building interior’s atmosphere. The artistic interventions in historic spaces emphasize their features without disrupting pre-existing authenticity, whereas contemporary projects with no historic reference offer a wide variety of color applications that focus on the function and form of architecture, landscape, or surroundings.
Quadratic Lyapunov Functions for Stability of the Generalized Proportional Fractional Differential Equations with Applications to Neural Networks
Authors: Almeida Ricardo , Agarwal Ravi P. , Hristova Snezhana , O’Regan Donal
Published: November 2021

A fractional model of the Hopfield neural network is considered in the case of the application of the generalized proportional Caputo fractional derivative. The stability analysis of this model is used to show the reliability of the processed information. An equilibrium is defined, which is generally not a constant (different than the case of ordinary derivatives and Caputo-type fractional derivatives). We define the exponential stability and the Mittag–Leffler stability of the equilibrium. For this, we extend the second method of Lyapunov in the fractional-order case and establish a useful inequality for the generalized proportional Caputo fractional derivative of the quadratic Lyapunov function. Several sufficient conditions are presented to guarantee these types of stability. Finally, two numerical examples are presented to illustrate the effectiveness of our theoretical results.
Dynamics of an Impulsive Stochastic Predator–Prey System with the Beddington–DeAngelis Functional Response
Authors: Shao Yuanfu
Published: November 2021

Taking impulsive effects into account, an impulsive stochastic predator–prey system with the Beddington–DeAngelis functional response is proposed in this paper. First, the impulsive system is transformed into an equivalent system without pulses. Then, by constructing suitable functionals and applying the extreme-value theory of quadratic functions, sufficient conditions on the existence of periodic Markovian processes are provided. The uniform continuity and global attractivity of solutions are also investigated. Additionally, we investigate the extinction and permanence in the mean of all species with the help of comparison methods and inequality techniques. Sufficient conditions on the existence and ergodicity of the stationary distribution of solutions for the autonomous and non-impulsive case are given. Finally, numerical simulations are performed to illustrate the main results.
A Point-Matching Method of Moment with Sparse Bayesian Learning Applied and Evaluated in Dynamic Lung Electrical Impedance Tomography
Authors: Dimas Christos , Alimisis Vassilis , Uzunoglu Nikolaos , Sotiriadis Paul P.
Published: November 2021

Dynamic lung imaging is a major application of Electrical Impedance Tomography (EIT) due to EIT’s exceptional temporal resolution, low cost and absence of radiation. EIT however lacks in spatial resolution and the image reconstruction is very sensitive to mismatches between the actual object’s and the reconstruction domain’s geometries, as well as to the signal noise. The non-linear nature of the reconstruction problem may also be a concern, since the lungs’ significant conductivity changes due to inhalation and exhalation. In this paper, a recently introduced method of moment is combined with a sparse Bayesian learning approach to address the non-linearity issue, provide robustness to the reconstruction problem and reduce image artefacts. To evaluate the proposed methodology, we construct three CT-based time-variant 3D thoracic structures including the basic thoracic tissues and considering 5 different breath states from end-expiration to end-inspiration. The Graz consensus reconstruction algorithm for EIT (GREIT), the correlation coefficient (CC), the root mean square error (RMSE) and the full-reference (FR) metrics are applied for the image quality assessment. Qualitative and quantitative comparison with traditional and more advanced reconstruction techniques reveals that the proposed method shows improved performance in the majority of cases and metrics. Finally, the approach is applied to single-breath online in-vivo data to qualitatively verify its applicability.
Co-Existence of Free-Living Amoebae and Potential Human Pathogenic Bacteria Isolated from Rural Household Water Storage Containers
Authors: Potgieter Natasha , van der Loo Clarissa , Barnard Tobias George
Published: November 2021

This study investigated the co-existence of potential human pathogenic bacteria and free-living amoebae in samples collected from stored water in rural households in South Africa using borehole water as a primary water source. Over a period of 5 months, a total of 398 stored water and 392 biofilm samples were collected and assessed. Free-living amoebae were identified microscopically in 92.0% of the water samples and 89.8% of the biofilm samples. A further molecular identification using 18S rRNA sequencing identified Vermamoeba vermiformis, Entamoeba spp., Stenamoeba spp., Flamella spp., and Acanthamoeba spp. including Acanthamoeba genotype T4, which is known to be potentially harmful to humans. Targeted potential pathogenic bacteria were isolated from the water samples using standard culture methods and identified using 16S rRNA sequencing. Mycobacterium spp., Pseudomonas spp., Enterobacter spp., and other emerging opportunistic pathogens such as Stenotrophomonas maltophilia were identified. The results showed the importance of further studies to assess the health risk of free-living amoebae and potential human pathogenic bacteria to people living in rural communities who have no other option than to store water in their homes due to water shortages.
Standard Non-Personalized Electric Field Modeling of Twenty Typical tDCS Electrode Configurations via the Computational Finite Element Method: Contributions and Limitations of Two Different Approaches
Authors: Molero-Chamizo Andrés , Nitsche Michael A. , Gutiérrez Lérida Carolina , Salas Sánchez Ángeles , Martín Riquel Raquel , Andújar Barroso Rafael Tomás , Alameda Bailén José Ramón , García Palomeque Jesús Carlos , Rivera-Urbina Guadalupe Nathzidy
Published: November 2021

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation procedure to modulate cortical excitability and related brain functions. tDCS can effectively alter multiple brain functions in healthy humans and is suggested as a therapeutic tool in several neurological and psychiatric diseases. However, variability of results is an important limitation of this method. This variability may be due to multiple factors, including age, head and brain anatomy (including skull, skin, CSF and meninges), cognitive reserve and baseline performance level, specific task demands, as well as comorbidities in clinical settings. Different electrode montages are a further source of variability between tDCS studies. A procedure to estimate the electric field generated by specific tDCS electrode configurations, which can be helpful to adapt stimulation protocols, is the computational finite element method. This approach is useful to provide a priori modeling of the current spread and electric field intensity that will be generated according to the implemented electrode montage. Here, we present standard, non-personalized model-based electric field simulations for motor, dorsolateral prefrontal, and posterior parietal cortex stimulation according to twenty typical tDCS electrode configurations using two different current flow modeling software packages. The resulting simulated maximum intensity of the electric field, focality, and current spread were similar, but not identical, between models. The advantages and limitations of both mathematical simulations of the electric field are presented and discussed systematically, including aspects that, at present, prevent more widespread application of respective simulation approaches in the field of non-invasive brain stimulation.
Torkildsen’s Ventriculocisternostomy First Applications: The Anthropological Evidence of a Young Slavic Soldier Who Died in the Torre Tresca Concentration Camp (Bari, Italy) in 1946
Authors: Sablone Sara , Gallieni Massimo , Leggio Alessia , Cazzato Gerardo , Puzo Pasquale , Santoro Valeria , Introna Francesco , De Donno Antonio
Published: November 2021

Human skeletal remains are considered as real biological archives of each subject’s life. Generally, traumas, wounds, surgical interventions, and many human pathologies suffered in life leave identifiable marks on the skeleton, and their correct interpretation is possible only through a meticulous anthropological investigation of skeletal remains. The study here presented concerns the analysis of a young Slavic soldier’s skeleton who died, after his imprisonment, in the concentration camp of Torre Tresca (Bari, Italy), during the Second World War (1946). In particular, the skull exhibited signs of surgical activity on the posterior cranial fossa and the parieto-occipital bones. They could be attributed to surgical procedures performed at different times, showing various degrees of bone edge remodeling. Overall, it was possible to correlate the surgical outcomes highlighted on the skull to the Torkildsen’s ventriculocisternostomy (VCS), the first clinically successful shunt for cerebrospinal fluid (CSF) diversion in hydrocephalus, which gained widespread use in the 1940s. For this reason, the skeleton we examined represents a rare, precious, and historical testimony of an emerging and revolutionary neurosurgical technique, which differed from other operations for treating hydrocephalus before the Second World War and was internationally recognized as an efficient procedure before the introduction of extracranial shunts.
Characterization of a MOB1 Homolog in the Apicomplexan Parasite Toxoplasma gondii
Authors: Delgado Inês L. S. , Tavares Alexandra , Francisco Samuel , Santos Dulce , Coelho João , Basto Afonso P. , Zúquete Sara , Müller Joachim , Hemphill Andrew , Meissner Markus , Soares Helena , Leitão Alexandre , Nolasco Sofia
Published: November 2021

Monopolar spindle One Binder1 (MOB1) proteins are conserved components of the tumor-suppressing Hippo pathway, regulating cellular processes such as cytokinesis. Apicomplexan parasites present a life cycle that relies on the parasites’ ability to differentiate between stages and regulate their proliferation; thus, Hippo signaling pathways could play an important role in the regulation of the apicomplexan life cycle. Here, we report the identification of one MOB1 protein in the apicomplexan Toxoplasma gondii. To characterize the function of MOB1, we generated gain-of-function transgenic lines with a ligand-controlled destabilization domain, and loss-of-function clonal lines obtained through CRISPR/Cas9 technology. Contrary to what has been characterized in other eukaryotes, MOB1 is not essential for cytokinesis in T. gondii. However, this picture is complex since we found MOB1 localized between the newly individualized daughter nuclei at the end of mitosis. Moreover, we detected a significant delay in the replication of overexpressing tachyzoites, contrasting with increased replication rates in knockout tachyzoites. Finally, using the proximity-biotinylation method, BioID, we identified novel members of the MOB1 interactome, a probable consequence of the observed lack of conservation of some key amino acid residues. Altogether, the results point to a complex evolutionary history of MOB1 roles in apicomplexans, sharing properties with other eukaryotes but also with divergent features, possibly associated with their complex life cycle.
Blood Performance: A New Formula for Fish Growth and Health
Authors: Esmaeili Noah
Published: November 2021

Monitoring fish health in a repeatable and accurate manner can contribute to the profitability and sustainability of aquaculture. Haematological and blood biochemistry parameters have been powerful tools and becoming increasingly common in aquaculture studies. Fish growth is closely related to its health status. A fish with a higher growth rate is more likely to be a healthy one. Any change in the physiological status of the fish, from pollution to nutritional stress, can cause changes in the blood parameters. Various aquaculture studies have measured the following components: red blood cells, white blood cells, haemoglobin, haematocrit, and total protein. However, because these parameters do not always follow the same trend across experimental fish, it is difficult to draw a firm conclusion about which parameter should be considered. Therefore, Blood Performance (BP) as a new formula is introduced, which is a more reliable indicator. This formula is simple and sums up the natural logarithm of the five above-mentioned parameters. More than 90 published peer-reviewed articles that measured these five parameters in the last six years confirmed the reliability and validity of this formula. Regardless of which supplements were added to the diets, the fish with a higher growth rate had higher BP as well. In addition, in 44 studies out of 53 articles, there was a significant positive correlation between specific growth rate and BP. Under different stressful situations, from pollution to thermal stress, the fish under stress had a lower BP than the control. Fish meal and fish oil replacement studies were further evidence for this formula and showed that adding excessive alternative proteins decreased growth along with BP. In conclusion, BP can be a reliable indicator of fish health and growth when it is compared between groups in the same experiment or farm. Although there was a positive correlation between specific growth rate and BP, comparing BP between experiments is not recommended. Standardising the haematological assays can improve the reliability and accuracy of BP across experiments.
Differential Effects of Normoxic versus Hypoxic Derived Breast Cancer Paracrine Factors on Brain Endothelial Cells
Authors: Rado Mariam , Flepisi Brian , Fisher David
Published: November 2021

Background: The blood-brain barrier (BBB) is a central nervous system protective barrier formed primarily of endothelial cells that regulate the entry of substances and cells from entering the brain. However, the BBB integrity is disrupted in disease, including cancer, allowing toxic substances, molecules, and circulating cells to enter the brain. This study aimed to determine the mitochondrial changes in brain endothelial cells co-cultured with cancer cells. Method: Brain endothelial cells (bEnd.3) were co-cultivated with various concentrations of breast cancer (MCF7) conditioned media (CM) generated under normoxic (21% O2) and hypoxic conditions (5% O2). The mitochondrial activities (including; dehydrogenases activity, mitochondrial membrane potential (ΔΨm), and ATP generation) were measured using Polarstar Omega B.M.G-Plate reader. Trans-endothelial electrical resistance (TEER) was evaluated using the EVOM system, followed by quantifying gene expression of the endothelial tight junction (ETJs) using qPCR. Results: bEnd.3 cells had reduced cell viability after 72 h and 96 h exposure to MCF7CM under hypoxic and normoxic conditions. The ΔΨm in bEnd.3 cells were hyperpolarized after exposure to the hypoxic MCF7CM (p < 0.0001). However, the normoxic MCF7CM did not significantly affect the state of ΔΨm in bEnd.3 cells. ATP levels in bEnd.3 co-cultured with hypoxic and normoxic MCF7CM was significantly reduced (p < 0.05). The changes in brain endothelial mitochondrial activity were associated with a decrease in TEER of bEnd.3 monolayer co-cultured with MCF7CM under hypoxia (p = 0.001) and normoxia (p < 0.05). The bEnd.3 cells exposed to MCF7CM significantly increased the gene expression level of ETJs (p < 0.05). Conclusions: MCF7CM modulate mitochondrial activity in brain endothelial cells, affecting the brain endothelial barrier function.
In Silico Characterization and Virtual Screening of GntR/HutC Family Transcriptional Regulator MoyR: A Potential Monooxygenase Regulator in Mycobacterium tuberculosis
Authors: Abeywickrama Thanusha Dhananji , Perera Inoka Chinthana
Published: November 2021

Mycobacterium tuberculosis is a well-known pathogen due to the emergence of drug resistance associated with it, where transcriptional regulators play a key role in infection, colonization and persistence. The genome of M. tuberculosis encodes many transcriptional regulators, and here we report an in-depth in silico characterization of a GntR regulator: MoyR, a possible monooxygenase regulator. Homology modelling provided a reliable structure for MoyR, showing homology with a HutC regulator DasR from Streptomyces coelicolor. In silico physicochemical analysis revealed that MoyR is a cytoplasmic protein with higher thermal stability and higher pI. Four highly probable binding pockets were determined in MoyR and the druggability was higher in the orthosteric binding site consisting of three conserved critical residues: TYR179, ARG223 and GLU234. Two highly conserved leucine residues were identified in the effector-binding region of MoyR and other HutC homologues, suggesting that these two residues can be crucial for structure stability and oligomerization. Virtual screening of drug leads resulted in four drug-like compounds with greater affinity to MoyR with potential inhibitory effects for MoyR. Our findings support that this regulator protein can be valuable as a therapeutic target that can be used for developing drug leads.
Vegetation and Environmental Changes on Contaminated Soil Formed on Waste from an Historic Zn-Pb Ore-Washing Plant
Authors: Rahmonov Oimahmad , Cabała Jerzy , Krzysztofik Robert
Published: November 2021

Post-mining waste from Zn-Pb ore exploitation undergoes processes of spontaneous succession and changes in soil chemical composition. The Zakawie area was industrially transformed by historical mining activity, ore enrichment, and the metallurgical processing of Zn-Pb ore. The subject of the study was to analyse the rate of vegetation succession (from 1999 to 2019), soil chemistry, and the relationships between them in an anthropogenic habitat with high concentrations of potentially toxic metals. Ecological and geochemical studies were carried out in an area contaminated with waste from a disused Zn-Pb ore-washing plant. Between 1999 and 2019, the transformation of grassland and meadow vegetation into scrub and forest–grassland communities was observed. This transformation led to a decrease in the area of Molinietum caeruleae meadow (from 25.8% in 1999 to 10.7% in 2019), whose place was taken by Prunus spinosa and Rhamnus cathartica. The community of xerothermic limestone grasslands completely disappeared, being replaced in favour of the Diantho-Armerietum and Prunus spinosa community. In this period, the share of lifeforms of plants and species composition (46 and 60, respectively) also changed. The Shannon and Simpson biodiversity index reached high values in the second investigation period, and it was 0.893 and 0.86, respectively. The anthrosols had a high content of Zn—85,360 mg kg−1, Pb—28,300 mg kg−1, Cd—340 mg kg−1, and As—1200 mg kg−1. Carbonates, clay minerals, and fe-oxides are predominant in the mineral composition of the rhizosphere; the metal-bearing phases are stable; and hardly soluble minerals include smithsonite, cerussite, monheimite, hemimorphite, and oxides of Fe and Fe-Mn. Mineralisation/crust processes formed on the epidermis, and their influences on root development were found. Scanning electron microscopy and energy-dispersive X-ray spectroscopy studies on rhizosphere soil components provide information on the type of minerals and their susceptibility to heavy metals release. The identification of some biotic and mineral structures in rhizospheres can be an interesting source of information on pedogenic processes identified in back-scattered electron images.