bluuebunny/crossref_metadata_2025 huggingface dataset:
Inferring Whole-Organism Metabolic Rate From Red Blood Cells in Birds
Authors: Malkoc Kasja , Casagrande Stefania , Hau Michaela
Published: July 2021

Metabolic rate is a key ecological variable that quantifies the energy expenditure needed to fuel almost all biological processes in an organism. Metabolic rates are typically measured at the whole-organism level (woMR) with protocols that can elicit stress responses due to handling and confinement, potentially biasing resulting data. Improved, non-stressful methodology would be especially valuable for measures of field metabolic rate, which quantifies the energy expenditure of free-living individuals. Recently, techniques to measure cellular metabolic rate (cMR) in mitochondria of blood cells have become available, suggesting that blood-based cMR can be a proxy of organismal aerobic performance. Aerobic metabolism actually takes place in the mitochondria. Quantifying cMR from blood samples offers several advantages such as direct estimates of metabolism and minimized disturbance of individuals. To our knowledge, the hypothesis that blood-based cMR correlates with woMR has not yet been directly tested. We measured cMR in red blood cells of captive great tits (Parus major), first during their morning activity period and second after subjecting them to a 2.5 h day-time respirometry protocol to quantify woMR. We predicted cMR to decrease as individuals transitioned from an active to a resting state. In the two blood samples we also assessed circulating corticosterone concentrations to determine the perceived disturbance of individuals. From respirometry traces we extracted initial and final woMR measures to test for a predicted positive correlation with cMR measures, while accounting for corticosterone concentrations. Indeed, cMR declined from the first to the second measurement. Furthermore, woMR and cMR were positively related in individuals that had relatively low corticosterone concentrations and displayed little locomotor activity throughout respirometry. By contrast, woMR and cMR covaried negatively in birds that increased corticosterone concentrations and activity levels substantially. Our results show that red blood cell cMR represents a proxy for woMR when birds do not display signs of stress, i.e., either before increases in hormonal or behavioral parameters have occurred or after they have abated. This method represents a valuable tool for obtaining metabolic data repeatedly and in free-living individuals. Our findings also highlight the importance of accounting for individual stress responses when measuring metabolic rate at any level.
Impact of the Stress Status of Employees on the Enterprise Technology Management Cost Through Matter-Element Analysis Under Psychological Health Education
Authors: Zhang Ximeng , Han Fanshen , Gao Ming , Liu Lu , Wang Xiaping
Published: July 2021

In this study, in order to analyze the stress sources and stress-coping strategies of employees in construction enterprises, to explore the influencing factors of enterprise technical management cost, and to offer suggestions for mental health education of employees, 372 employees of Shandong Construction Engineering Group Co., Ltd. were selected for a questionnaire survey. The influences of stress sources and stress-coping strategies on the mental health of employees were compared, based on different demographic variables. The evaluation model was constructed using the matter-element analysis to rank the factors influencing the enterprise technology management cost. The results showed that the stress value of work characteristics was the highest (4.26 ± 0.511), followed by the organizational structure and atmosphere (4.15 ± 0.382); stress-coping strategies at the individual level (1.84 ± 0.315) scored higher than that at the organizational level (1.67 ± 0.248) (P< 0.05). Notable differences were observed in balance between work and family between males and females (P< 0.05); in work characteristics, role orientation, personal relationship, and balance between work and family between subjects of different ages (P< 0.05); in work characteristics, and balance between work and family between the married and the unmarried (P< 0.05); and in role stress and work characteristics between subjects in different positions (P< 0.05). The evaluation results revealed that the factors influencing the technology management cost of enterprises included price index, development cost, fixed investment proportion, power equipment rate, mechanical artificial intelligence, labor cost, rate of technical equipment, the output value, informatization of technology management, and national policy. In conclusion, the two major sources of stress for employees in Luoyang Construction Engineering Group Co., Ltd. were as follows: (1) work characteristics and (2) organizational structure and atmosphere. Besides, many employees adopted the stress-coping strategies at the individual level, and enterprises needed to strengthen the psychological health education for employees at the organizational level. In practice, the enterprise needed to add importance to the development of mechanical artificial intelligence, informatization of technology management, and national policy.
The Effects of COVID-19 Risk Perception on Travel Intention: Evidence From Chinese Travelers
Authors: Meng Yue , Khan Asif , Bibi Sughra , Wu Haoyue , Lee Yao , Chen Wenkuan
Published: July 2021

This study attempts to assess the relationship between risk perception, risk knowledge, and travel intentions of Chinese leisure travelers during the COVID-19 pandemic in the framework of social contagion and risk communication theories by analyzing a sample of 1,209 travelers through structural equation modeling (SEM) and path analysis. We used the process macro of Hayes to analyze the moderation effects of age, gender, and education between risk perception, media and interpersonal communication, and risk knowledge. It was found that travelers were more concerned about self-efficacy than severity. Risk perception of travelers predicts the information-seeking process of tourists. This process helps travelers to accumulate risk information that influences their travel intentions. Travelers give more importance to interpersonal (contagion) communication in making a traveling decision. Demographic factors influence traveling decision-making; women travelers were found to be more risk resilient than men. Young travelers seek information at low- and old travelers at high-risk levels. Marketing implications also provided.
The Effect of Cerebral Small Vessel Disease on the Subtypes of Mild Cognitive Impairment
Authors: Li Xudong , Shen Miaoxin , Jin Yi , Jia Shuhong , Zhou Zhi , Han Ziling , Zhang Xiangfei , Tong Xiaopeng , Jiao Jinsong
Published: July 2021

Objectives: Cerebral small vessel disease (CSVD) is the most common vascular cause of dementia, and mild cognitive impairment (MCI) is an intermediate state between dementia and normal cognitive aging. The present study investigated the main imaging features of CSVD on different MCI subtypes in memory clinics.

Methods: A total of 236 patients with MCI and 85 healthy controls were included. One hundred nine amnestic MCI-multiple domains (amMCI), 38 amnestic MCI-single domain (asMCI), 36 non-amnestic MCI-multiple domains (namMCI), and 53 non-amnestic MCI-single domain (nasMCI) patients were diagnosed. All participants were evaluated with the cognitive assessments and imaging features including white matter hyperintensity (WMH), enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and cerebral atrophy according to a standard procedure.

Results: The patients with amMCI, namMCI, and nasMCI had more high-grade basal ganglia EPVS compared with healthy controls, while the percentages of high-grade basal ganglia EPVS in the patients with amMCI were also more than those in patients with asMCI, namMCI, and nasMCI. There were more high-grade centrum semiovale EPVS in patients with amMCI in comparison with all other groups. The patients with amMCI and namMCI had more percentages of severe deep and periventricular WMH and deep CMBs compared with healthy controls. All MCI groups had higher scores of the medial temporal lobe atrophy than healthy controls, whereas the scores of the amMCI group were also higher than those of the namMCI and nasMCI groups.

Conclusions: There were varied neuroimaging features of CSVD including cerebral atrophy in different MCI groups, which meant that vascular mechanism contributed to the prodromal stage of dementia.
Space and Control in Soccer
Authors: Martens Florian , Dick Uwe , Brefeld Ulf
Published: July 2021

In many team sports, the ability to control and generate space in dangerous areas on the pitch is crucial for the success of a team. This holds, in particular, for soccer. In this study, we revisit ideas from Fernandez and Bornn (2018) who introduced interesting space-related quantities including pitch control (PC) and pitch value. We identify influence of the player on the pitch with the movements of the player and turn their concepts into data-driven quantities that give rise to a variety of different applications. Furthermore, we devise a novel space generation measure to visualize the strategies of the team and player. We provide empirical evidence for the usefulness of our contribution and showcase our approach in the context of game analyses.
ArCAR: A Novel Deep Learning Computer-Aided Recognition for Character-Level Arabic Text Representation and Recognition
Authors: Muaad Abdullah Y. , Jayappa Hanumanthappa , Al-antari Mugahed A. , Lee Sungyoung
Published: July 2021

Arabic text classification is a process to simultaneously categorize the different contextual Arabic contents into a proper category. In this paper, a novel deep learning Arabic text computer-aided recognition (ArCAR) is proposed to represent and recognize Arabic text at the character level. The input Arabic text is quantized in the form of 1D vectors for each Arabic character to represent a 2D array for the ArCAR system. The ArCAR system is validated over 5-fold cross-validation tests for two applications: Arabic text document classification and Arabic sentiment analysis. For document classification, the ArCAR system achieves the best performance using the Alarabiya-balance dataset in terms of overall accuracy, recall, precision, and F1-score by 97.76%, 94.08%, 94.16%, and 94.09%, respectively. Meanwhile, the ArCAR performs well for Arabic sentiment analysis, achieving the best performance using the hotel Arabic reviews dataset (HARD) balance dataset in terms of overall accuracy and F1-score by 93.58% and 93.23%, respectively. The proposed ArCAR seems to provide a practical solution for accurate Arabic text representation, understanding, and classification.
Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
Authors: Abu-Khalaf Nawaf
Published: July 2021

An electronic nose (EN), which is a kind of chemical sensors, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.
The GASA Gene Family in Cacao (Theobroma cacao, Malvaceae): Genome Wide Identification and Expression Analysis
Authors: Abdullah  , Faraji Sahar , Mehmood Furrukh , Malik Hafiz Muhammad Talha , Ahmed Ibrar , Heidari Parviz , Poczai Peter
Published: July 2021

The gibberellic acid-stimulated Arabidopsis (GASA/GAST) gene family is widely distributed in plants and involved in various physiological and biological processes. These genes also provide resistance to abiotic and biotic stresses, including antimicrobial, antiviral, and antifungal. We are interested in characterizing the GASA gene family and determining its role in various physiological and biological process in Theobroma cacao. Here, we report 17 tcGASA genes distributed on six chromosomes in T. cacao. The gene structure, promoter region, protein structure and biochemical properties, expression, and phylogenetics of all tcGASAs were analyzed. Phylogenetic analyses divided tcGASA proteins into five groups. Among 17 tcGASA genes, nine segmentally duplicating genes were identified which formed four pairs and cluster together in phylogenetic tree. Differential expression analyses revealed that most of the tcGASA genes showed elevated expression in the seeds (cacao food), implying their role in seed development. The differential expression of tcGASAs was recorded between the tolerant and susceptible cultivars of cacao, which indicating their possible role as fungal resistant. Our findings provide new insight into the function, evolution, and regulatory system of the GASA family genes in T.cacao and may suggest new target genes for development of fungi-resistant cacao varieties in breeding programs.
Activity Budget Comparisons Using Long-Term Observations of a Group of Bottlenose Dolphins (Tursiops truncatus) under Human Care: Implications for Animal Welfare
Authors: Huettner Tim , Dollhaeupl Sandra , Simon Ralph , Baumgartner Katrin , von Fersen Lorenzo
Published: July 2021

Zoos and aquaria must provide optimal husbandry conditions and the highest welfare standards for their animals. How the welfare state of an animal or a group of animals can be precisely assessed is currently under debate, and new approaches are necessary to reliably evaluate changes in welfare. One particular measure that is easily applicable is behavioral observations. However, for dolphins and other cetaceans under human care, reliable behavior-based measures are rare. Using long-term observations of a group of bottlenose dolphins, we investigate how their activity budgets and different behaviors changed over time and are impacted by construction noise. Additionally, we investigate whether behavioral differences are also reflected in changes in the dolphins’ performance during daily training sessions. Our results show that construction noise significantly alters the dolphins’ behavior. Play behavior decreases during construction periods; most importantly, the frequency of fast swimming activities significantly increased, and at the same time, a decrease in training performance is found. Additionally, inter- and intraindividual behavioral differences are attributed to factors, such as age or weaning. Significant changes in a dolphin’s activity budget can also pose potential welfare concerns. Thus, this study highlights the importance of regularly assessing and analyzing the behavior of dolphins under human care. Behavioral observations are essential welfare indicators and can—when complemented with other measures, such as assessment of training performance—provide zoo staff with important information about each individual’s state of welfare.
Robust Three-Dimensional (3D) Expansion of Bovine Intestinal Organoids: An In Vitro Model as a Potential Alternative to an In Vivo System
Authors: Lee Bo-Ram , Yang Hyeon , Lee Sang-In , Haq Inamul , Ock Sun-A , Wi Hayeon , Lee Hwi-Cheul , Lee Poongyeon , Yoo Jae-Gyu
Published: July 2021

Intestinal organoids offer great promise for disease-modelling-based host–pathogen interactions and nutritional research for feed efficiency measurement in livestock and regenerative medicine for therapeutic purposes. However, very limited studies are available on the functional characterisation and three-dimensional (3D) expansion of adult stem cells in livestock species compared to other species. Intestinal crypts derived from intestinal organoids under a 3D culture system from the small intestine in adult bovine were successfully established and characterised for functionality testing, including the cellular potentials and genetic properties based on immunohistochemistry, immunocytochemistry, epithelial barrier permeability assay, QuantSeq 3′ mRNA-Seq. data and quantitative reverse transcription-polymerase chain reaction. Intestinal organoids were long-term cultivated over several passages of culture without loss of the recapitulating capacity of crypts, and they had the specific expression of several specific markers involved in intestinal stem cells, intestinal epithelium, and nutrient absorption. In addition, they showed the key functionality with regard to a high permeability for compounds of up to FITC-dextran 4 kDa, while FITC-dextran 40 kDa failed to enter the organoid lumen and revealed that the genetic properties of bovine intestinal organoids were highly similar to those of in vivo. Collectively, these results provide a reliable method for efficient isolation of intestinal crypts from the small intestine and robust 3D expansion of intestinal organoids in adult bovine and demonstrate the in vitro 3D organoids mimics the in vivo tissue topology and functionality. Finally, intestinal organoids are potential alternatives to in vivo systems and will be facilitated as the practical model to replace animal experiments for various purposes in the fields of animal biotechnology.
Antimicrobial Activity of Calcium Silicate-Based Dental Materials: A Literature Review
Authors: Janini Ana Cristina Padilha , Bombarda Gabriela Fernanda , Pelepenko Lauter Eston , Marciano Marina Angélica
Published: July 2021

Endodontic biomaterials have significantly improved dental treatment techniques in several aspects now that they can be used for vital pulp treatments, as temporary intracanal medication, in definitive fillings, in apical surgeries, and for regenerative procedures. Calcium silicate-based cement is a class of dental material that is used in endodontics in direct contact with the dental structures, connective tissue, and bone. Because the material interacts with biological tissues and stimulates biomineralization processes, its properties are of major importance. The main challenge in endodontic treatments is the elimination of biofilms that are present in the root canal system anatomical complexities, as it remains even after chemical-mechanical preparation and disinfection procedures. Thus, an additional challenge for these biomaterials is to exert antimicrobial activity while maintaining their biological properties in parallel. This article reviews the literature for studies considering the antimicrobial properties of calcium silicate-based dental biomaterials used in endodontic practice. Considering the reviewed studies, it can be affirmed that the reduced antimicrobial effect exhibited by calcium silicate-based endodontic materials clearly emphasizes that all clinical procedures prior to their use must be carefully performed. Future studies for the evaluation of these materials, and especially newly proposed materials, under poly-microbial biofilms associated with endodontic diseases will be necessary.
Vibration Error Correction for the FOGs-Based Measurement in a Drilling System Using an Extended Kalman Filter
Authors: Wang Lu , Hu Yuanbiao , Wang Tao , Liu Baolin
Published: July 2021

Fiber-optic gyroscopes (FOGs)-based Measurement While Drilling system (MWD) is a newly developed instrument to survey the borehole trajectory continuously and in real time. However, because of the strong vibration while drilling, the measurement accuracy of FOG-based MWD deteriorates. It is urgent to improve the measurement accuracy while drilling. Therefore, this paper proposes an innovative scheme for the vibration error of the FOG-based MWD. Firstly, the nonlinear error models for the FOGs and ACCs are established. Secondly, a 36-order Extended Kalman Filter (EKF) combined with a calibration method based on 24-position is designed to identify the coefficients in the error model. Moreover, in order to obtain a higher accurate error model, an iterative calibration method has been suggested to suppress calibration residuals. Finally, vibration experiments simulating the drilling vibration in the laboratory is implemented. Compared to the original data, compensated the linear error items, the error of 3D borehole trajectory can only be reduced by a ratio from 10% to 34%. While compensating for the nonlinear error items of the FOG-based MWD, the error of 3D borehole trajectory can be reduced by a ratio from 44.13% to 97.22%. In conclusion, compensation of the nonlinear error of FOG-based MWD could improve the trajectory survey accuracy under vibration.
Automatic Boundary Extraction for Photovoltaic Plants Using the Deep Learning U-Net Model
Authors: Pérez-González Andrés , Jaramillo-Duque Álvaro , Cano-Quintero Juan Bernardo
Published: July 2021

Nowadays, the world is in a transition towards renewable energy solar being one of the most promising sources used today. However, Solar Photovoltaic (PV) systems present great challenges for their proper performance such as dirt and environmental conditions that may reduce the output energy of the PV plants. For this reason, inspection and periodic maintenance are essential to extend useful life. The use of unmanned aerial vehicles (UAV) for inspection and maintenance of PV plants favor a timely diagnosis. UAV path planning algorithm over a PV facility is required to better perform this task. Therefore, it is necessary to explore how to extract the boundary of PV facilities with some techniques. This research work focuses on an automatic boundary extraction method of PV plants from imagery using a deep neural network model with a U-net structure. The results obtained were evaluated by comparing them with other reported works. Additionally, to achieve the boundary extraction processes, the standard metrics Intersection over Union (IoU) and the Dice Coefficient (DC) were considered to make a better conclusion among all methods. The experimental results evaluated on the Amir dataset show that the proposed approach can significantly improve the boundary and segmentation performance in the test stage up to 90.42% and 91.42% as calculated by IoU and DC metrics, respectively. Furthermore, the training period was faster. Consequently, it is envisaged that the proposed U-Net model will be an advantage in remote sensing image segmentation.
Dynamic Analysis Method for Fault Propagation Behaviour of Machining Centres
Authors: Mu Liming , Zhang Yingzhi , Liu Jintong , Zhai Fenli , Song Jie
Published: July 2021

Fault propagation behaviour analysis is the basis of fault diagnosis and health maintenance. Traditional fault propagation studies are mostly based on a priori knowledge of a causality model combined with rule-based reasoning, disregarding the limitations of experience and the dynamic characteristics of the system that cause deviations in the identification of critical fault sources. Thus, this paper proposes a dynamic analysis method for fault propagation behaviour of machining centres that combines fault propagation mechanisms with model structure characteristics. This paper uses the design structure matrix (DSM) to establish the fault propagation hierarchy structure model. Considering the correlation of fault time, the fault probability function of a component is obtained and the fault influence degree of nodes are calculated. By introducing the Copula and Coupling degree functions, the fault influence degree of the edges between the same level and different levels are calculated, respectively. This paper constructs a fault propagation intensity model by integrating the edge betweenness and uses it as an index to analyze real-time fault propagation behaviour. Finally, a certain type of machining centre is taken as an example for specific application. This study can provide as a reference for the fault maintenance and reliability growth of a machining centre.
Identifying and Characterizing the Propagation Scale of COVID-19 Situational Information on Twitter: A Hybrid Text Analytic Approach
Authors: Wahid Junaid , Shi Lei , Gao Yufei , Yang Bei , Tao Yongcai , Wei Lin , Hussain Shabir
Published: July 2021

During the recent pandemic of COVID-19, an increasing amount of information has been propagated on social media. This situational information is valuable for public authorities. Therefore, this study characterized the propagation scale of situational information types by harnessing the power of natural language processing techniques and machine learning algorithms. We observed that the length of the post has a positive correlation with type 1 information (announcements), and negative words were mostly used in type 5 information (criticizing the government), whereas anxiety-related words have a negative effect on the amount of retweeted type 0 (precautions) and type 2 (donations) information. This type of research study not only contributes to the situational information literature by comprehensively defining categories but also provides data-oriented practical insights into information so that management authorities can formulate response strategies after the pandemic. Our approach is one of its kind and combines Twitter content features, user features and LIWC linguistic features with machine learning algorithms to analyze the propagation scale of situational information, and it achieved 77% accuracy with SVM while classifying the information categories.
A Predictive Model of Chlorophyll a in Western Lake Erie Based on Artificial Neural Network
Authors: Wang Qi , Wang Song
Published: July 2021

The reoccurrence of algal blooms in western Lake Erie (WLE) since the mid-1990s, under increased system stress from climate change and excessive nutrients, has shown the need for developing management tools to predict water quality. In this study, process-based model GLM-AED (General Lake Model-Aquatic Ecosystem Dynamics) and statistical model ANN (artificial neural network) were developed with meteorological forcing derived from surface buoys, airports, and land-based stations and historical monitoring nutrients, to predict water quality in WLE from 2002 to 2015. GLM-AED was calibrated with observed water temperature and chlorophyll a (Chl-a) from 2002 to 2015. For ANN, during the training period (2002–2010), the inputs included meteorological forcing and nutrient concentrations, and the target was Chl-a simulated by calibrated GLM-AED due to the lack of continuously daily measured Chl-a concentrations. During the testing period (2011–2015), the predicted Chl-a concentrations were compared with the observations. The results showed that the ANN model has higher accuracy with lower Chl-a RMSE and MAE values than GLM-AED during 2011 and 2015. Lastly, we applied the established ANN model to predict the future 10-year water quality of WLE, which showed that the probability of adverse health effects would be moderate, so more intense water resources management should be implemented.
Determinants of Reactive Agility in Tests with Different Demands on Sensory and Motor Components in Handball Players
Authors: Horníková Henrieta , Jeleň Michal , Zemková Erika
Published: July 2021

This study investigates the relationship between reactive agility and reaction speed, sprint speed, and muscle strength and their contribution to Y-shaped agility test and reactive agility test (RAT) performance in handball players. Seven handball players performed a Y-shaped agility test and RAT, simple and choice-based reaction time test, reaction test to fast and slow generated visual stimuli, 5 m and 20 m sprint tests, a 505 Agility test, a squat jump, a countermovement jump, and a drop jump. The results reveal a significant relationship between the times for the Y-shaped agility test and the 20 m sprint (r = 0.777, p = 0.040, R = 0.604), as well as the time for the 505 Agility test (r = 0.770, p = 0.043, R2 = 0.593), and RSI (r = −0.755, p = 0.050, R2 = 0.570); however, no relationship was found with parameters pertaining to reaction speed. RAT performance did not significantly correlate with RSI, time in the 505 Agility test, squat jump height, time in the 20 m sprint, and reaction time to fast generated visual stimuli, although large effect sizes were found (r > 0.5). It seems that the contribution of sensory and motor components depends on the structure of the agility test. While the Y-shaped agility test is mainly determined by sprinting, the change of direction speed, and reactive strength, there is the tendency for the reactive agility test to be determined by strength, speed, and visual reaction time.
Torque Reduction of a Reconfigurable Spherical Parallel Mechanism Based on Craniotomy Experimental Data
Authors: Essomba Terence , Sandoval Juan , Laribi Med Amine , Wu Chieh-Tsai , Breque Cyril , Zeghloul Saïd , Richer Jean-pierre
Published: July 2021

This paper deals with a robotic manipulator dedicated to craniotomy with a remote center of motion based on a Spherical Parallel Manipulator (SPM) architecture. The SPM is proposed to handle the drilling tool through the requested craniotomy Degrees of Freedom (DoF) with two rotations. The proposed architecture allows one degree of redundancy according to the total DoF. Thus, a first contribution of this work focuses on the experimental analysis of craniotomy surgery tasks. Secondly, its behavior is improved, taking advantage of the redundancy of the SPM using the spinning motion as a reconfiguration variable. The spinning angle modulation allows the reconfigurable manipulator to minimize its motor torques. A series of motion capture and force experimentations is performed for the analysis of the kinematic and force interaction characterizing Burr hole craniotomy procedures. Experimentations were carried out by a neurosurgeon on a human cadaver, ensuring highly realistic conditions.
Monitoring the Impact of the Large Building Investments on the Neighborhood
Authors: Łupieżowiec Marian
Published: July 2021

The article presents the concept of monitoring buildings and infrastructure elements located near large construction investments (the construction of high-rise buildings of the Oak Terraces housing estate in Katowice and the construction of a tunnel under the roundabout in Katowice along the intercity express road DTŚ). The impacts include deep excavation, lowering of the groundwater level over a large area, and dynamic influences related to the use of impact methods of soil improvement. The presented monitoring includes observation of the groundwater level with the use of piezometers, geodetic measurements of settlement and inclinations, as well as the measurement of vibration amplitudes generated during the works involving shocks and vibrations. It was also important to observe the development of cracks on the basis of a previously made inventory of damage. The results of the monitoring allow corrections to be made in the technology of works (e.g., reduction of vibration amplitudes, application of additional protections at excavations, etc.) or the use additional safety measures. Currently, there are also monitoring systems used during the operation of completed facilities.
Applying Force Plate Technology to Inform Human Performance Programming in Tactical Populations
Authors: Merrigan Justin J. , Stone Jason D. , Martin Joel R. , Hornsby William Guy , Galster Scott M. , Hagen Joshua A.
Published: July 2021

Force plate assessments, such as countermovement jumps and isometric mid-thigh pulls, examine performances (e.g., jump height, force, power) and movement strategies (e.g., asymmetries, durations), and are best suited to characterize and monitor physical capabilities, not predict injuries. To begin applying force plate technologies, users must first; (1) develop a data management plan to visualize and capture data over time; (2) select appropriate force plates for their scenario; (3) design appropriate testing protocols to ensure valid and reliable data. Force plate assessments may be added to existing testing, serve as separate testing batteries for annual profile testing to compare individuals and understand initial physical capabilities, or for more frequent testing (i.e., monthly or weekly) to monitor training-related adaptations or neuromuscular fatigue. Although these assessments inform evidence-based program designs, human performance practitioners must understand the considerations for conducting appropriate force plate testing, as well as proper visualizations and management of force plate data. Thus, the aim of this review is to provide evidence-based practices for utilizing force plates in tactical populations (e.g., military, firefighters, police). This includes best practices to implement testing for performance profiling, training adaptations, and monitoring neuromuscular fatigue and force asymmetries. Of note, due to the large amount of force-time metrics to choose from, this article provides general examples of important metrics to monitor and training recommendations based on changes to these force-time metrics, followed by specific examples in three case studies.
Instance Segmentation of Microscopic Foraminifera
Authors: Johansen Thomas Haugland , Sørensen Steffen Aagaard , Møllersen Kajsa , Godtliebsen Fred
Published: July 2021

Foraminifera are single-celled marine organisms that construct shells that remain as fossils in the marine sediments. Classifying and counting these fossils are important in paleo-oceanographic and -climatological research. However, the identification and counting process has been performed manually since the 1800s and is laborious and time-consuming. In this work, we present a deep learning-based instance segmentation model for classifying, detecting, and segmenting microscopic foraminifera. Our model is based on the Mask R-CNN architecture, using model weight parameters that have learned on the COCO detection dataset. We use a fine-tuning approach to adapt the parameters on a novel object detection dataset of more than 7000 microscopic foraminifera and sediment grains. The model achieves a (COCO-style) average precision of 0.78 on the classification and detection task, and 0.80 on the segmentation task. When the model is evaluated without challenging sediment grain images, the average precision for both tasks increases to 0.84 and 0.86, respectively. Prediction results are analyzed both quantitatively and qualitatively and discussed. Based on our findings we propose several directions for future work and conclude that our proposed model is an important step towards automating the identification and counting of microscopic foraminifera.
A Voxel-Based Assessment of Noise Properties in Computed Tomography Imaging with the ASiR-V and ASiR Iterative Reconstruction Algorithms
Authors: Barca Patrizio , Marfisi Daniela , Marzi Chiara , Cozza Sabino , Diciotti Stefano , Traino Antonio Claudio , Giannelli Marco
Published: July 2021

Given the inherent characteristics of nonlinearity and nonstationarity of iterative reconstruction algorithms in computed tomography (CT) imaging, this study aimed to perform, for the first time, a voxel-based characterization of noise properties in CT imaging with the ASiR-V and ASiR algorithms as compared with conventional filtered back projection (FBP). Multiple repeated scans of the Catphan-504 phantom were carried out. CT images were reconstructed using FBP and ASiR/ASiR-V with different blending levels of reconstruction (20%, 40%, 60%, 80%, 100%). Noise maps and their nonuniformity index (NUI) were obtained according to the approach proposed by the report of AAPM TG-233. For the homogeneous CTP486 module, ASiR-V/ASiR allowed a noise reduction of up to 63.7%/52.9% relative to FBP. While the noise reduction values of ASiR-V-/ASiR-reconstructed images ranged up to 33.8%/39.9% and 31.2%/35.5% for air and Teflon contrast objects, respectively, these values were approximately 60%/50% for other contrast objects (PMP, LDPE, polystyrene, acrylic, Delrin). Moreover, for all contrast objects but air and Teflon, ASiR-V showed a greater noise reduction potential than ASiR when the blending level was ≥40%. While noise maps of the homogenous CTP486 module showed only a slight spatial variation of noise (NUI < 5.2%) for all reconstruction algorithms, the NUI values of iterative-reconstructed images of the nonhomogeneous CTP404 module increased nonlinearly with blending level and were 19%/15% and 6.7% for pure ASiR-V/ASiR and FBP, respectively. Overall, these results confirm the potential of ASiR-V and ASiR in reducing noise as compared with conventional FBP, suggesting, however, that the use of pure ASiR-V or ASiR might be suboptimal for specific clinical applications.
Epidemiological and Molecular Characterization of Blastocystis Infection in Children Attending Daycare Centers in Medellín, Colombia
Authors: Osorio-Pulgarin Maria I. , Higuera Adriana , Beltran-Álzate Juan C. , Sánchez-Jiménez Miryan , Ramírez Juan David
Published: July 2021

Background: The present study aims to perform an epidemiological and molecular characterization of Blastocystis infection in a child population attending daycare centers of Medellín, Colombia. Methods: A total of 265 children aged 0–5 years were enrolled in five children’s centers in urban sectors of Medellín, northwestern Colombia. Stool samples were taken to identify intestinal parasites by direct examination, Ritchie–Frick concentration, and molecular identification of Blastocystis by conventional PCR and subtype (ST) identification by PCR barcoding with subsequent phylogenetic reconstruction. Kappa index was calculated to evaluate the agreement between microscopy and PCR for the diagnosis of Blastocystis. Results: The prevalence of intestinal protozoa was 36.6% (97/265), with Blastocystis as the most frequent parasitic protozoan at 15.8% (42/265), followed by Giardia intestinalis at 15.5% (41/265) and Endolimax nana at 15.1% (40/265). The prevalence of Blastocystis by PCR was 53.2% (141/265), the subtypes identified were ST3 at 30.5% (18/59), ST2 at 23.7% (14/59), ST1 at 20.3% (12/59), and with less frequency, ST4 at 5.1% (3/59), ST6 at 1.7% (1/59) and ST16 at 15.3% (9/59) allele 162. Conclusion: This study provides the first genetic characterization of Blastocystis subtypes circulating in a population of Medellín, Colombia, and also updates the epidemiology of Blastocystis subtypes in the world with the first identification of ST16 in humans.
Identification of the Active Ingredient and Beneficial Effects of Vitex rotundifolia Fruits on Menopausal Symptoms in Ovariectomized Rats
Authors: Lee Ji Hwan , Lee Sullim , Nguyen Quynh Nhu , Phung Hung Manh , Shin Myoung-Sook , Kim Jae-Yong , Choi Hyukjae , Shim Sang Hee , Kang Ki Sung
Published: July 2021

Estrogen replacement therapy is a treatment to relieve the symptoms of menopause. Many studies suggest that natural bioactive ingredients from plants resemble estrogen in structure and biological functions and can relieve symptoms of menopause. The fruit of V. rotundifolia, called “Man HyungJa” in Korean, is a traditional medicine used to treat headache, migraine, eye pain, neuralgia, and premenstrual syndrome in Korea and China. The aim of the present study was to confirm that V. rotundifolia fruit extract (VFE) exerts biological functions similar to those of estrogen in menopausal syndrome. We investigated its in vitro effects on MCF-7 cells and in vivo estrogen-like effects on weight gain and uterine contraction in ovariectomized rats. Using the polar extract, the active constituents of VFE (artemetin, vitexicarpin, hesperidin, luteolin, vitexin, and vanillic acid) with estrogen-like activity were identified in MCF-7 cells. In animal experiments, the efficacy of VFE in ameliorating body weight gain was similar to that of estrogen, as evidenced from improvements in uterine atrophy. Vitexin and vitexicarpin are suggested as the active constituents of V. rotundifolia fruits.
Epithelial Protein Lost in Neoplasm, EPLIN, the Cellular and Molecular Prospects in Cancers
Authors: Zeng Jianyuan , Jiang Wen G. , Sanders Andrew J.
Published: July 2021

Epithelial Protein Lost In Neoplasm (EPLIN), also known as LIMA1 (LIM Domain And Actin Binding 1), was first discovered as a protein differentially expressed in normal and cancerous cell lines. It is now known to be key to the progression and metastasis of certain solid tumours. Despite a slow pace in understanding the biological role in cells and body systems, as well as its clinical implications in the early years since its discovery, recent years have witnessed a rapid progress in understanding the mechanisms of this protein in cells, diseases and indeed the body. EPLIN has drawn more attention over the past few years with its roles expanding from cell migration and cytoskeletal dynamics, to cell cycle, gene regulation, angiogenesis/lymphangiogenesis and lipid metabolism. This concise review summarises and discusses the recent progress in understanding EPLIN in biological processes and its implications in cancer.
Comparison on Well-Being, Engagement and Perceived School Climate in Secondary School Students with Learning Difficulties and Specific Learning Disorders: An Exploratory Study
Authors: Lombardi Elisabetta , Traficante Daniela , Bettoni Roberta , Offredi Ilaria , Vernice Mirta , Sarti Daniela
Published: July 2021

Reading and writing skills influence the social status of students, exerting effects not only on learning, but also on wellbeing. This study aimed to assess the impact of diagnosis of specific learning disorder on well-being in secondary-school students, comparing students with a diagnosis of specific learning disorder (SLD-group), students showing learning difficulties without diagnosis (LD-group) and students without learning difficulties (control-group). Students were tested with neuropsychological screening tests in order to identify learning difficulties and were further assessed by means of psychological and school well-being questionnaires. The results show that LD group perceive themselves as having a low sense of mastery and autonomy, less interest and engagement in daily activities and low peer social support than their schoolmates. This result highlights, for the LD group, a low well-being experience, which is not observed in the SLD and control groups. On the contrary, SLD group students do not differ from control group students in any dimensions except for the perceived parents’ support and involvement in school life, in which the SLD group show the highest scores. This work underlines the importance of having a diagnosis as it seems to work as a protective factor for both the psychological and school well-being of the student.
Targeting Metastatic Colorectal Cancer with Immune Oncological Therapies
Authors: Galbraith Norman J. , Wood Colin , Steele Colin W.
Published: July 2021

Metastatic colorectal cancer carries poor prognosis, and current therapeutic regimes convey limited improvements in survival and high rates of detrimental side effects in patients that may not stand to benefit. Immunotherapy has revolutionised cancer treatment by restoring antitumoural mechanisms. However, the efficacy in metastatic colorectal cancer, is limited. A literature search was performed using Pubmed (Medline), Web of Knowledge, and Embase. Search terms included combinations of immunotherapy and metastatic colorectal cancer, primarily focusing on clinical trials in humans. Analysis of these studies included status of MMR/MSS, presence of combination strategies, and disease control rate and median overall survival. Evidence shows that immune checkpoint inhibitors, such as anti-PD1 and anti-PD-L1, show efficacy in less than 10% of patients with microsatellite stable, MMR proficient colorectal cancer. In the small subset of patients with microsatellite unstable, MMR deficient cancers, response rates were 40–50%. Combination strategies with immunotherapy are under investigation but have not yet restored antitumoural mechanisms to permit durable disease regression. Immunotherapy provides the potential to offer additional strategies to established chemotherapeutic regimes in metastatic colorectal cancer. Further research needs to establish which adjuncts to immune checkpoint inhibition can unpick resistance, and better predict which patients are likely to respond to individualised therapies to not just improve response rates but to temper unwarranted side effects.
Photocatalytic Treatment of Wastewater Containing Simultaneous Organic and Inorganic Pollution: Competition and Operating Parameters Effects
Authors: Azzaz Ahmed Amine , Jellali Salah , Hamed Nasser Ben Harharah , El Jery Atef , Khezami Lotfi , Assadi Aymen Amine , Amrane Abdeltif
Published: July 2021

In the present study, methylene blue (MB) removal from aqueous solutions via the photocatalytic process using TiO2 as a catalyst in the presence of external ultra-violet light (UV) was investigated. The results of adsorption in the absence of UV radiation showed that adsorption reached an equilibrium state at 60 min. The experimental kinetic data were found to be well fitted by the pseudo-second-order model. Furthermore, the isotherm study suggested that dye uptake by TiO2 is a chemisorption process with a maximum retention capacity of 34.0 mg/g. The photodegradation of MB was then assessed under various experimental conditions. The related data showed that dye mineralization decreased when dye concentrations were increased and was favored at high pH values and low salt concentrations. The simultaneous presence of organic and inorganic pollution (Zinc) was also evaluated. The effect of the molar ratio Zn2+/MB+ in the solution at different pH values and NaCl concentrations was also monitored. The corresponding experimental results showed that at low values of Zn2+ in the solution (30 mg/L), the kinetic of the MB removal became faster until reaching an optimum at Zn2+/MB+ concentrations of 60/60 mg/L; it then slowed down for higher concentrations. The solutions’ carbon contents were measured during the degradation process and showed total mineralization after about 5 h for the optimal Zn2+/MB+ condition.
Induced Pluripotent Stem Cell-Derived Neural Precursors Improve Memory, Synaptic and Pathological Abnormalities in a Mouse Model of Alzheimer’s Disease
Authors: Armijo Enrique , Edwards George , Flores Andrea , Vera Jorge , Shahnawaz Mohammad , Moda Fabio , Gonzalez Cesar , Sanhueza Magdalena , Soto Claudio
Published: July 2021

Alzheimer’s disease (AD) is the most common type of dementia in the elderly population. The disease is characterized by progressive memory loss, cerebral atrophy, extensive neuronal loss, synaptic alterations, brain inflammation, extracellular accumulation of amyloid-β (Aβ) plaques, and intracellular accumulation of hyper-phosphorylated tau (p-tau) protein. Many recent clinical trials have failed to show therapeutic benefit, likely because at the time in which patients exhibit clinical symptoms the brain is irreversibly damaged. In recent years, induced pluripotent stem cells (iPSCs) have been suggested as a promising cell therapy to recover brain functionality in neurodegenerative diseases such as AD. To evaluate the potential benefits of iPSCs on AD progression, we stereotaxically injected mouse iPSC-derived neural precursors (iPSC-NPCs) into the hippocampus of aged triple transgenic (3xTg-AD) mice harboring extensive pathological abnormalities typical of AD. Interestingly, iPSC-NPCs transplanted mice showed improved memory, synaptic plasticity, and reduced AD brain pathology, including a reduction of amyloid and tangles deposits. Our findings suggest that iPSC-NPCs might be a useful therapy that could produce benefit at the advanced clinical and pathological stages of AD.