bluuebunny/crossref_metadata_2025 huggingface dataset:
An Optimization and Pharmacokinetic Studies of some Thymidine Derivatives
Authors: KAWSAR Sarkar M. A. , HOSSAİN Mohammed Anowar
Published: September 2020

Thymidine is a predecessor of nucleotides that forms DNA and plays a significant role in cell metabolism and as a co-enzyme. Most of the thymidine analogues have remarkable antiviral activity due to structural functions and are globally used as antiviral drugs. Modification of the hydroxyl (-OH) group of thymidine by acylation may causes changes in the property of thymidine which is investigated in this study. Herein, we relate the optimization of thymidine and its acylated analogues applying density functional theory (DFT) with B3LYP/3-21G level theory to demonstrate their thermal, frontier molecular orbital, the density of states (DOS) and molecular electrostatic potential (MEP) properties. Pharmacokinetic parameters are also enumerated to investigate absorption, metabolism, oral toxicity, and carcinogenicity of thymidine and its modified derivatives.
A Mixed-Integer and Asynchronous Level Decomposition with Application to the Stochastic Hydrothermal Unit-Commitment Problem
Authors: Colonetti Bruno , Finardi Erlon Cristian , de Oliveira Welington
Published: September 2020

Independent System Operators (ISOs) worldwide face the ever-increasing challenge of coping with uncertainties, which requires sophisticated algorithms for solving unit-commitment (UC) problems of increasing complexity in less-and-less time. Hence, decomposition methods are appealing options to produce easier-to-handle problems that can hopefully return good solutions at reasonable times. When applied to two-stage stochastic models, decomposition often yields subproblems that are embarrassingly parallel. Synchronous parallel-computing techniques are applied to the decomposable subproblem and frequently result in considerable time savings. However, due to the inherent run-time differences amongst the subproblem’s optimization models, unequal equipment, and communication overheads, synchronous approaches may underuse the computing resources. Consequently, asynchronous computing constitutes a natural enhancement to existing methods. In this work, we propose a novel extension of the asynchronous level decomposition to solve stochastic hydrothermal UC problems with mixed-integer variables in the first stage. In addition, we combine this novel method with an efficient task allocation to yield an innovative algorithm that far outperforms the current state-of-the-art. We provide convergence analysis of our proposal and assess its computational performance on a testbed consisting of 54 problems from a 46-bus system. Results show that our asynchronous algorithm outperforms its synchronous counterpart in terms of wall-clock computing time in 40% of the problems, providing time savings averaging about 45%, while also reducing the standard deviation of running times over the testbed in the order of 25%.
The Development of a European and Mediterranean Chickpea Association Panel (EMCAP)
Authors: Rocchetti Lorenzo , Bellucci Elisa , Cortinovis Gaia , Di Vittori Valerio , Lanzavecchia Giovanna , Frascarelli Giulia , Nanni Laura , Del Gatto Andrea , Pieri Sandro , Mangoni Lorella , Bitocchi Elena , Papa Roberto
Published: September 2020

Association panels represent a useful tool for quantitative trait loci (QTL) mapping and pre-breeding. In this study, we report on the development of a European and Mediterranean chickpea association panel as a useful tool for gene discovery and breeding. Chickpea (Cicer arietinum L.) is one of the most important food legumes worldwide and a key crop in the Mediterranean environments. The selection of genotypes followed criteria aimed to build a set of materials representative of the genetic diversity of chickpea germplasm focusing on the European and Mediterranean environments, which have largely been ignored to date. This tool can help breeders to develop novel varieties adapted to European and Mediterranean agro-ecosystems. Initially, 1931 chickpea accessions were phenotypically evaluated in a field trial in central Italy. From these, an association panel composed by 480 genotypes derived from single-seed descent was identified and phenotypically evaluated. Current and future phenotypic data combined with the genotypic characterization of the association panel will allow to dissect the genetic architecture of important adaptive and quality traits and accelerate breeding. This information can be used to predict phenotypes of unexploited chickpea genetic resources available in genebanks for breeding.
Medium-Term Influence of Organic Fertilization on the Quality and Yield of a Celery Crop
Authors: Navarro Antonio Sánchez , Romero Juan Antonio Sánchez , Sanjuan María del Carmen Salas , Bernardeau María Arantzazu Blanco , Delgado Iniesta María José
Published: September 2020

For some years now, part of society has been demanding the implementation of circular economy models and so the use of organic matter as a source of nutrients is once again taking center stage. In this scenario, the aim of this work was to implement an integrated management model for a farm and to study the influence on a celery crop of organic amendments (animal and vegetable) obtained on the farm, as opposed to inorganic fertilization. This influence was evaluated for the yield and the nutritional, organoleptic, and sanitary quality of the resulting crops. The yield and size of the marketable parts of the celery plants were greater with the inorganic treatment; however, the nutritional and sanitary quality was better in the organic treatments, while the chromatic attributes, as well as the total P and Ca, were not affected by the different fertilization treatments applied. It is therefore concluded that the organic management model is environmentally and economically sustainable.
Amidochelocardin Overcomes Resistance Mechanisms Exerted on Tetracyclines and Natural Chelocardin
Authors: Hennessen Fabienne , Miethke Marcus , Zaburannyi Nestor , Loose Maria , Lukežič Tadeja , Bernecker Steffen , Hüttel Stephan , Jansen Rolf , Schmiedel Judith , Fritzenwanker Moritz , Imirzalioglu Can , Vogel Jörg , Westermann Alexander J. , Hesterkamp Thomas , Stadler Marc , Wagenlehner Florian , Petković Hrvoje , Herrmann Jennifer , Müller Rolf
Published: September 2020

The reassessment of known but neglected natural compounds is a vital strategy for providing novel lead structures urgently needed to overcome antimicrobial resistance. Scaffolds with resistance-breaking properties represent the most promising candidates for a successful translation into future therapeutics. Our study focuses on chelocardin, a member of the atypical tetracyclines, and its bioengineered derivative amidochelocardin, both showing broad-spectrum antibacterial activity within the ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) panel. Further lead development of chelocardins requires extensive biological and chemical profiling to achieve favorable pharmaceutical properties and efficacy. This study shows that both molecules possess resistance-breaking properties enabling the escape from most common tetracycline resistance mechanisms. Further, we show that these compounds are potent candidates for treatment of urinary tract infections due to their in vitro activity against a large panel of multidrug-resistant uropathogenic clinical isolates. In addition, the mechanism of resistance to natural chelocardin was identified as relying on efflux processes, both in the chelocardin producer Amycolatopsis sulphurea and in the pathogen Klebsiella pneumoniae. Resistance development in Klebsiella led primarily to mutations in ramR, causing increased expression of the acrAB-tolC efflux pump. Most importantly, amidochelocardin overcomes this resistance mechanism, revealing not only the improved activity profile but also superior resistance-breaking properties of this novel antibacterial compound.
Use of Spectroscopic Techniques to Monitor Changes in Food Quality during Application of Natural Preservatives: A Review
Authors: Hassoun Abdo , Carpena Maria , Prieto Miguel A. , Simal-Gandara Jesus , Özogul Fatih , Özogul Yeşim , Çoban Özlem Emir , Guðjónsdóttir María , Barba Francisco J. , Marti-Quijal Francisco J. , Jambrak Anet Režek , Maltar-Strmečki Nadica , Kljusurić Jasenka Gajdoš , Regenstein Joe M.
Published: September 2020

Consumer demand for food of high quality has driven research for alternative methods of food preservation on the one hand, and the development of new and rapid quality assessment techniques on the other hand. Recently, there has been a growing need and interest in healthier food products, which has led to an increased interest in natural preservatives, such as essential oils, plant extracts, and edible films and coatings. Several studies have shown the potential of using biopreservation, natural antimicrobials, and antioxidant agents in place of other processing and preservation techniques (e.g., thermal and non-thermal treatments, freezing, or synthetic chemicals). Changes in food quality induced by the application of natural preservatives have been commonly evaluated using a range of traditional methods, including microbiology, sensory, and physicochemical measurements. Several spectroscopic techniques have been proposed as promising alternatives to the traditional time-consuming and destructive methods. This review will provide an overview of recent studies and highlight the potential of spectroscopic techniques to evaluate quality changes in food products following the application of natural preservatives.
Chlorella sorokiniana Dietary Supplementation Increases Antioxidant Capacities and Reduces ROS Release in Mitochondria of Hyperthyroid Rat Liver
Authors: Napolitano Gaetana , Fasciolo Gianluca , Salbitani Giovanna , Venditti Paola
Published: September 2020

The ability of aerobic organisms to cope with the attack of radicals and other reactive oxygen species improves by feeding on foods containing antioxidants. Microalgae contain many molecules showing in vitro antioxidant capacity, and their food consumption can protect cells from oxidative insults. We evaluated the capacity of dietary supplementation with 1% dried Chlorella sorokiniana strain 211/8k, an alga rich in glutathione, α-tocopherol, and carotenoids, to counteract an oxidative attack in vivo. We used the hyperthyroid rat as a model of oxidative stress, in which the increase in metabolic capacities is associated with an increase in the release of mitochondrial reactive oxygen species (ROS) and the susceptibility to oxidative insult. Chlorella sorokiniana supplementation prevents the increases in oxidative stress markers and basal oxygen consumption in hyperthyroid rat livers. It also mitigates the thyroid hormone-induced increase in maximal aerobic capacities, the mitochondrial ROS release, and the susceptibility to oxidative stress. Finally, alga influences the thyroid hormone-induced changes in the factors involved in mitochondrial biogenesis peroxisomal proliferator-activated receptor-γ coactivator (PGC1-1) and nuclear respiratory factor 2 (NRF-2). Our results suggest that Chlorella sorokiniana dietary supplementation has beneficial effects in counteracting oxidative stress and that it works primarily by preserving mitochondrial function. Thus, it can be useful in preventing dysfunctions in which mitochondrial oxidative damage and ROS production play a putative role.
The Transcriptomic Response of the Murine Thyroid Gland to Iodide Overload and the Role of the Nrf2 Antioxidant System
Authors: Chartoumpekis Dionysios V. , Ziros Panos G. , Georgakopoulos-Soares Ilias , Smith Adam A. T. , Marques Ana Claudia , Ibberson Mark , A. Kopp Peter , Habeos Ioannis , Trougakos Ioannis P. , Khoo Nicholas K. H. , Sykiotis Gerasimos P.
Published: September 2020

Background: Thyroid follicular cells have physiologically high levels of reactive oxygen species because oxidation of iodide is essential for the iodination of thyroglobulin (Tg) during thyroid hormone synthesis. Thyroid follicles (the functional units of the thyroid) also utilize incompletely understood autoregulatory mechanisms to defend against exposure to excess iodide. To date, no transcriptomic studies have investigated these phenomena in vivo. Nuclear erythroid factor 2 like 2 (Nrf2 or Nfe2l2) is a transcription factor that regulates the expression of numerous antioxidant and other cytoprotective genes. We showed previously that the Nrf2 pathway regulates the antioxidant defense of follicular cells, as well as Tg transcription and Tg iodination. We, thus, hypothesized that Nrf2 might be involved in the transcriptional response to iodide overload. Methods: C57BL6/J wild-type (WT) or Nrf2 knockout (KO) male mice were administered regular water or water supplemented with 0.05% sodium iodide for seven days. RNA from their thyroids was prepared for next-generation RNA sequencing (RNA-Seq). Gene expression changes were assessed and pathway analyses were performed on the sets of differentially expressed genes. Results: Analysis of differentially expressed messenger RNAs (mRNAs) indicated that iodide overload upregulates inflammatory-, immune-, fibrosis- and oxidative stress-related pathways, including the Nrf2 pathway. Nrf2 KO mice showed a more pronounced inflammatory–autoimmune transcriptional response to iodide than WT mice. Compared to previously published datasets, the response patterns observed in WT mice had strong similarities with the patterns typical of Graves’ disease and papillary thyroid carcinoma (PTC). Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) also responded to iodide overload, with the latter targeting mRNAs that participate mainly in inflammation pathways. Conclusions: Iodide overload induces the Nrf2 cytoprotective response and upregulates inflammatory, immune, and fibrosis pathways similar to autoimmune hyperthyroidism (Graves’ disease) and PTC.
Deep Neural Network and Long Short-Term Memory for Electric Power Load Forecasting
Authors: Son Namrye , Yang Seunghak , Na Jeongseung
Published: September 2020

Forecasting domestic and foreign power demand is crucial for planning the operation and expansion of facilities. Power demand patterns are very complex owing to energy market deregulation. Therefore, developing an appropriate power forecasting model for an electrical grid is challenging. In particular, when consumers use power irregularly, the utility cannot accurately predict short- and long-term power consumption. Utilities that experience short- and long-term power demands cannot operate power supplies reliably; in worst-case scenarios, blackouts occur. Therefore, the utility must predict the power demands by analyzing the customers’ power consumption patterns for power supply stabilization. For this, a medium- and long-term power forecasting is proposed. The electricity demand forecast was divided into medium-term and long-term load forecast for customers with different power consumption patterns. Among various deep learning methods, deep neural networks (DNNs) and long short-term memory (LSTM) were employed for the time series prediction. The DNN and LSTM performances were compared to verify the proposed model. The two models were tested, and the results were examined with the accuracies of the six most commonly used evaluation measures in the medium- and long-term electric power load forecasting. The DNN outperformed the LSTM, regardless of the customer’s power pattern.
Establishing Correlations between Breast Tumor Response to Radio-Immunotherapy and Radiomics from Multi-Parametric Imaging: An Animal Study
Authors: Ahmad Anis , Totiger Tulasigeri M. , Benaduce Ana Paula , Marples Brian , Mihaylov Ivaylo Bodganov
Published: September 2020

Triple-negative breast cancer (TNBC), which is a type of invasive breast cancer, is characterized by severe disease progression, poor prognosis, high recurrence rate, and short survival. We sought to gain new insight into TNBC by applying computed tomography (CT) and magnetic resonance (MR) quantitative imaging (radiomics) approaches to predict the outcome of radio-immunotherapy treatments in a syngeneic subcutaneous murine breast tumor model. Five Athymic Nude mice were implanted with breast cancer cell lines (4T1) tumors on the right flank. The animals were CT- and MRI-imaged, tumors were contoured, and radiomics features were extracted. All animals were treated with radiotherapy (RT), followed by the administration of PD1 inhibitor. Approximately 10 days later, the animals were sacrificed, tumor volumes were measured, and histopathology evaluation was performed through Ki-67 staining. Linear regression modeling between radiomics and Ki-67 results was performed to establish a correlation between quantitative imaging and post-treatment histochemistry. There was no correlation between tumor volumes and Ki-67 values. Multiple CT- and MRI-derived features, however, correlated with histopathology with correlation coefficients greater than 0.8. MRI imaging helps in tumor delineation as well as an additional orthogonal imaging modality for quantitative imaging purposes. This is the first investigation correlating simultaneously CT- and MRI-derived radiomics to histopathology outcomes of combined radio-immunotherapy treatments in a preclinical setting applied to treatment naïve tumors. The findings indicate that imaging can guide discrimination between responding and non-responding tumors for the combined RT and ImT treatment regimen in TNBC.
Recognition of Hand Gesture Sequences by Accelerometers and Gyroscopes
Authors: Chu Yen-Cheng , Jhang Yun-Jie , Tai Tsung-Ming , Hwang Wen-Jyi
Published: September 2020

The objective of this study is to present novel neural network (NN) algorithms and systems for sensor-based hand gesture recognition. The algorithms are able to classify accurately a sequence of hand gestures from the sensory data produced by accelerometers and gyroscopes. They are the extensions from the PairNet, which is a Convolutional Neural Network (CNN) capable of carrying out simple pairing operations with low computational complexities. Three different types of feedforward NNs, termed Residual PairNet, PairNet with Inception, and Residual PairNet with Inception are proposed for the extension. They are the PairNet operating in conjunction with short-cut connections and/or inception modules for achieving high classification accuracy and low computation complexity. A prototype system based on smart phones for remote control of home appliances has been implemented for the performance evaluation. Experimental results reveal that the PairNet has superior classification accuracy over its basic CNN and Recurrent NN (RNN) counterparts. Furthermore, the Residual PairNet, PairNet with Inception, and Residual PairNet with Inception are able to further improve classification hit rate and/or reduce recognition time for hand gesture recognition.
Trends in the Characterization of the Proximal Humerus in Biomechanical Studies: A Review
Authors: Castro-Franco Angel D. , Mendoza-Muñoz Ismael , González-Ángeles Álvaro , Cruz-Sotelo Samantha E. , Castañeda Ana Maria , Siqueiros-Hernández Miriam
Published: September 2020

Proximal humerus fractures are becoming more common due to the aging of the population, and more related scientific research is also emerging. Biomechanical studies attempt to optimize treatments, taking into consideration the factors involved, to obtain the best possible treatment scenario. To achieve this, the use of finite element analysis (FEA) is necessary, to experiment with situations that are difficult to replicate, and which are sometimes unethical. Furthermore, low costs and time requirements make FEA the perfect choice for biomechanical studies. Part of the complete process of an FEA involves three-dimensional (3D) bone modeling, mechanical properties assignment, and meshing the bone model to be analyzed. Due to the lack of standardization for bone modeling, properties assignment, and the meshing processes, this article aims to review the most widely used techniques to model the proximal humerus bone, according to its anatomy, for FEA. This study also seeks to understand the knowledge and bias behind mechanical properties assignment for bone, and the similarities/differences in mesh properties used in previous FEA studies of the proximal humerus. The best ways to achieve these processes, according to the evidence, will be analyzed and discussed, seeking to obtain the most accurate results for FEA simulations.
Karl Fischer Water Titration—Principal Component Analysis Approach on Bread Products
Authors: Popescu Gabriela , Radulov Isidora , Iordănescu Olimpia A. , Orboi Manuela D. , Rădulescu Laura , Drugă Mărioara , Bujancă Gabriel S. , David Ioan , Hădărugă Daniel I. , (Banciu) Christine A. Lucan , Hădărugă Nicoleta G. , Riviş Mircea
Published: September 2020

(1) Background: The water content and the way of bonding in the food matrices, including bread, can be easily and simply evaluated by Karl Fischer titration (KFT). The goal was to identify the main KFT parameters that influence the similarity/dissimilarity of commercial bread products, using multivariate statistical analysis. (2) Methods: Various commercial bread samples were analyzed by volumetric KFT and the water content, parameters from titration process and KFT kinetics were used as input for principal component analysis (PCA). (3) Results: The KFT water content was in the range of 35.1–44.2% for core samples and 19.4–22.9% for shell samples. The storage and transportation conditions consistently influence the water content of bread. The type of water molecules can be evaluated by means of KFT water reaction rates. The mean water reaction rates up to 2 min are consistently higher for bread core samples, which indicates a high fraction of “surface” water. PCA reveals the similarity of core samples and various bread types, as well as dissimilarity between bread parts, mainly based on KFT kinetic parameters. (4) Conclusions: KFT kinetics can be a useful tool for a rapid and simple differentiations between various types of bread products.
Drill Bit Deformations in Rotary Drilling Systems under Large-Amplitude Stick-Slip Vibrations
Authors: Kessai Idir , Benammar Samir , Doghmane Mohamed Zinelabidine , Tee Kong Fah
Published: September 2020

In oil and gas industry, rotary drilling systems are used for energy exploration and productions. These types of systems are composed of two main parts: mechanical and electrical parts. The electrical part is represented by rotating motor called top drive; however, the mechanical part of the system is composed of tool string with many pipes, at the bottom end of these pipes the bit is attached to cut the rock during their contact. Since the bit is in a direct contact with rock characteristic variations, it can be under risk for heavy damage. The latter is principally caused by the fact that the rock–bit interaction term is highly nonlinear and unpredictable. In literature, many mathematical models have been proposed for rock–bit interaction, but they do not reflect the dynamic of the bit under vibrations since torsional and axial vibrations are strongly coupled and synchronized with it. In industrial development, the design of drill bit has faced many improvements in order to overcome these vibrations and mitigate unpredictable phenomena. Even though, the practical use of these drill bits confirmed that there are still many failures and damages for the new designs; moreover, bits’ virtual life become shorter than before. The objective of this study is to analyze the drill bit deformations caused by the stick-slip vibration phenomenon which is characterized by high-frequency high-amplitude in rotary drilling systems. The obtained results were validated through a case study of MWD (measurement while drilling) data of well located in a Southern Algerian oil field.
Contact-Free Optical Assessment of Changes in the Chest Wall Perfusion after Coronary Artery Bypass Grafting by Imaging Photoplethysmography
Authors: Kukel Imre , Trumpp Alexander , Plötze Katrin , Rost Antje , Zaunseder Sebastian , Matschke Klaus , Rasche Stefan
Published: September 2020

Imaging photoplethysmography (iPPG) is a contact-free monitoring of the cutaneous blood volume pulse by RGB (red-green-blue) cameras. It detects vital parameters from skin areas and is associated to cutaneous perfusion. This study investigated the use of iPPG to quantify changes in cutaneous perfusion after major surgery. Patients undergoing coronary artery bypass grafting (CABG) were scanned before surgery and in three follow-up measurements. Using an industrial-grade RGB camera and usual indoor lighting, a contact-free imaging plethysmogram from the chest was obtained. Changes of the iPPG signal strength were evaluated in view of both the operation itself as well as the unilateral preparation of the internal thoracic artery (ITA) for coronary artery grafting, which is the main blood source of the chest wall. iPPG signal strength globally decreased after surgery and recovered partially during the follow up measurements. The ITA preparation led to a deeper decrease and an attenuated recovery of the iPPG signal strength compared to the other side of the chest wall. These results comply with the expected changes of cutaneous perfusion after CABG using an ITA graft. iPPG can be used to assess cutaneous perfusion and its global changes after major surgery as well as its local changes after specific surgical procedures.
A Parallel Particle Swarm Optimisation for Selecting Optimal Virtual Machine on Cloud Environment
Authors: Abdelaziz Ahmed , Anastasiadou Maria , Castelli Mauro
Published: September 2020

Cloud computing has a significant role in healthcare services, especially in medical applications. In cloud computing, the best choice of virtual machines (Virtual_Ms) has an essential role in the quality improvement of cloud computing by minimising the execution time of medical queries from stakeholders and maximising utilisation of medicinal resources. Besides, the best choice of Virtual_Ms assists the stakeholders to reduce the total execution time of medical requests through turnaround time and maximise CPU utilisation and waiting time. For that, this paper introduces an optimisation model for medical applications using two distinct intelligent algorithms: genetic algorithm (GA) and parallel particle swarm optimisation (PPSO). In addition, a set of experiments was conducted to provide a competitive study between those two algorithms regarding the execution time, the data processing speed, and the system efficiency. The PPSO algorithm was implemented using the MATLAB tool. The results showed that the PPSO algorithm gives accurate outcomes better than the GA in terms of the execution time of medical queries and efficiency by 3.02% and 37.7%, respectively. Also, the PPSO algorithm has been implemented on the CloudSim package. The results displayed that the PPSO algorithm gives accurate outcomes better than default CloudSim in terms of final implementation time of medicinal queries by 33.3%. Finally, the proposed model outperformed the state-of-the-art methods in the literature review by a range from 13% to 67%.
Increasing Hypopnea in Sleep Breathing Disturbance Improves Postoperative Oxygen Saturation in Patients with Very Severe Obstructive Sleep Apnea
Authors: Huang Ethan I. , Huang Shu-Yi , Lin Yu-Ching , Lin Chieh-Mo , Lin Chin-Kuo , Huang Ying-Chih , Su Jian-An
Published: September 2020

In patients of very severe obstructive sleep apnea (OSA) with confined framework, reducing volume is difficult to achieve a postoperative apnea-hypopnea index (AHI) qualifying the classical surgical success. However, a higher AHI with a larger part of hypopneas may have similar or even less severity of oxygen (O2) desaturation, compared to a lower index mostly made of apneas. Here, in 27 consecutive enrolled patients, we show that besides the improvement of mean AHI, the multilevel surgery increased hypopnea in AHI from 29.1% to 77.3%, and improves postoperative O2 saturation by reducing desaturation frequency (mean desaturation index decreased from 62.5 to 24.4 events/h) and level (mean oxyhemoglobin saturation of pulse oximetry (SpO2) desaturation cut down from 10.0 to 5.8%). The mean SpO2 improved from 92.3% to 94.7%, and the improvement was positively related to the proportion increase of hypopnea/AHI. The results suggest that the non-framework surgery could help patients with very severe OSA whose AHIs are ≥60 events/h in terms of improving postoperative O2 saturation. Due to the improvement also presented in those not qualified as classical surgical success, further studies are needed to clarify the connection between O2 desaturation and various consequences to reconsider defining a surgical success.
Multi-Scale Probabilistic Analysis for the Mechanical Properties of Plain Weave Carbon/Epoxy Composites Using the Homogenization Technique
Authors: Jin Ji-Won , Jeon Byung-Wook , Choi Chan-Woong , Kang Ki-Weon
Published: September 2020

Probabilistic analyses of carbon fabric composites were conducted using the Monte Carlo simulation based on a homogenization technique to evaluate the mechanical properties of composites and their stochastic nature. First, the homogenization analysis was performed for a micro-level structure, which fiber and matrix are combined. The effective properties obtained from this analysis were compared with the results from the rule of mixture theory to verify the homogenization analysis. And, tensile tests were conducted to clearly evaluate the result and the reliability was verified by comparing the results of the tensile tests and homogenization analysis. In addition, the Monte Carlo simulation was performed based on homogenization analyses to consider the uncertainties of the micro-level structure combined of fiber and matrix. Next, the results of this simulation were applied to the macro-level structure combined of the tow and matrix to perform the Monte Carlo simulation based on the homogenization technique. Finally, the sensitivity analysis was conducted to identify the effect of constituents of the carbon plain weave composite and the linear correlation of the micro- and macro-level structures combined of the fiber/matrix and tow/matrix, respectively. The findings of this study verified that the effective properties of the plain weave carbon/epoxy composite and their uncertainties depended on the properties of the carbon fiber and epoxy, which are the basic constituents of plain weave carbon/epoxy composites.
Targeting Receptors on Cancer Cells with Protein Toxins
Authors: Antignani Antonella , Ho Eric Chun Hei , Bilotta Maria Teresa , Qiu Rong , Sarnvosky Robert , FitzGerald David J.
Published: September 2020

Cancer cells frequently upregulate surface receptors that promote growth and survival. These receptors constitute valid targets for intervention. One strategy involves the delivery of toxic payloads with the goal of killing those cancer cells with high receptor levels. Delivery can be accomplished by attaching a toxic payload to either a receptor-binding antibody or a receptor-binding ligand. Generally, the cell-binding domain of the toxin is replaced with a ligand or antibody that dictates a new binding specificity. The advantage of this “immunotoxin” approach lies in the potency of these chimeric molecules for killing cancer cells. However, receptor expression on normal tissue represents a significant obstacle to therapeutic intervention.
Automatic Quantification of Cardiomyocyte Dimensions and Connexin 43 Lateralization in Fluorescence Images
Authors: Oliver-Gelabert Antoni , García-Mendívil Laura , Vallejo-Gil José María , Fresneda-Roldán Pedro Carlos , Andelová Katarína , Fañanás-Mastral Javier , Vázquez-Sancho Manuel , Matamala-Adell Marta , Sorribas-Berjón Fernando , Ballester-Cuenca Carlos , Tribulova Narcisa , Ordovás Laura , Raúl Diez Emiliano , Pueyo Esther
Published: September 2020

Cardiomyocytes’ geometry and connexin 43 (CX43) amount and distribution are structural features that play a pivotal role in electrical conduction. Their quantitative assessment is of high interest in the study of arrhythmias, but it is usually hampered by the lack of automatic tools. In this work, we propose a software algorithm (Myocyte Automatic Retrieval and Tissue Analyzer, MARTA) to automatically detect myocytes from fluorescent microscopy images of cardiac tissue, measure their morphological features and evaluate the expression of CX43 and its degree of lateralization. The proposed software is based on the generation of cell masks, contouring of individual cells, enclosing of cells in minimum area rectangles and splitting of these rectangles into end-to-end and middle compartments to estimate CX43 lateral-to-total ratio. Application to human ventricular tissue images shows that mean differences between automatic and manual methods in terms of cardiomyocyte length and width are below 4 μm. The percentage of lateral CX43 also agrees between automatic and manual evaluation, with the interquartile range approximately covering from 3% to 30% in both cases. MARTA is not limited by fiber orientation and has an optimized speed by using contour filtering, which makes it run hundreds of times faster than a trained expert. Developed for CX43 studies in the left ventricle, MARTA is a flexible tool applicable to morphometric and lateralization studies of other markers in any heart chamber or even skeletal muscle. This open-access software is available online.
Effect of SiC on Microstructure, Phase Evolution, and Mechanical Properties of Spark-Plasma-Sintered High-Entropy Ceramic Composite
Authors: Zhang Hanzhu , Akhtar Farid
Published: September 2020

Ultra-high temperature ceramic composites have been widely investigated due to their improved sinterability and superior mechanical properties compared to monolithic ceramics. In this work, high-entropy boron-carbide ceramic/SiC composites with different SiC content were synthesized from multicomponent carbides HfC, Mo2C, TaC, TiC, B4C, and SiC in spark plasma sintering (SPS) from 1600 °C to 2000 °C. It was found that the SiC addition tailors the phase formation and mechanical properties of the high-entropy ceramic (HEC) composites. The microhardness and fracture toughness of the HEC composites sintered at 2000 °C were improved from 20.3 GPa and 3.14 MPa·m1/2 to 26.9 GPa and 5.95 MPa·m1/2, with increasing SiC content from HEC-(SiC)0 (0 vol. %) to HEC-(SiC)3.0 (37 vol. %). The addition of SiC (37 vol. %) to the carbide precursors resulted in the formation of two high-entropy ceramic phases with two different crystal structures, face-centered cubic (FCC) structure, and hexagonal structure. The volume fraction ratio between the hexagonal and FCC high-entropy phases increased from 0.36 to 0.76 when SiC volume fraction was increased in the composites from HEC-(SiC)0 to HEC-(SiC)3.0, suggesting the stabilization of the hexagonal high-entropy phase over the FCC phase with SiC addition.
Real-World Insights in Thailand on Usage Satisfaction and Perceived Efficacy of Dexpanthenol in Nappy Care
Authors: Tan Sheryl S.L. , Peltier Erwan
Published: September 2020

The prevalence of nappy rash or napkin dermatitis in Thailand infants aged 1–24 months is 36.1%. Dexpanthenol-containing nappy creams are clinical validated and effective in treating napkin dermatitis. This study explores the real-world usage satisfaction and perceived effectiveness of a 5% Dexpanthenol-containing product as a preventive strategy for napkin dermatitis. Respondents were mothers with babies between 6–12 months of age, who purchased and used a 5% Dexpanthenol-containing product (Bepanthen® Ointment) in the past one month. An online study collected respondents’ satisfaction with the product and its benefits and properties. A total of 300 respondents (52% frequent users and 48% as-needed users) completed the study. Over 90% of respondents reported that their babies experienced less nappy-related discomfort, crying, fidgeting and sleep disruption after applying the nappy care product. Almost all respondents (96%) were satisfied with the product. Notably, frequent users of the product reported higher rates of satisfaction than as-needed users (62% vs. 43%; p < 0.05). This high level of satisfaction was associated with the moisturizing properties and long-lasting skin protection provided by the dexpanthenol-containing product. Our findings from a real-world setting further validate the use of dexpanthenol-containing products as a preventive strategy for napkin dermatitis in Thai infants.
Recent and Rapid Radiation of the Highly Endangered Harlequin Frogs (Atelopus) into Central America Inferred from Mitochondrial DNA Sequences
Authors: Ramírez Juan , Jaramillo César , Lindquist Erik , Crawford Andrew , Ibáñez Roberto
Published: September 2020

Populations of amphibians are experiencing severe declines worldwide. One group with the most catastrophic declines is the Neotropical genus Atelopus (Anura: Bufonidae). Many species of Atelopus have not been seen for decades and all eight Central American species are considered “Critically Endangered”, three of them very likely extinct. Nonetheless, the taxonomy, phylogeny, and biogeographic history of Central American Atelopus are still poorly known. In this study, the phylogenetic relationships among seven of the eight described species in Central America were inferred based on mitochondrial DNA sequences from 103 individuals, including decades-old museum samples and two likely extinct species, plus ten South American species. Among Central American samples, we discovered two candidate species that should be incorporated into conservation programs. Phylogenetic inference revealed a ladderized topology, placing species geographically furthest from South America more nested in the tree. Model-based ancestral area estimation supported either one or two colonization events from South America. Relaxed-clock analysis of divergence times indicated that Atelopus colonized Central America prior to 4 million years ago (Ma), supporting a slightly older than traditional date for the closure of the Isthmus. This study highlights the invaluable role of museum collections in documenting past biodiversity, and these results could guide future conservation efforts. An abstract in Spanish (Resumen) is available as supplementary material.
Leonardo da Vinci’s Contributions from a Design Perspective
Authors: Cerveró-Meliá Ernesto , Capuz-Rizo Salvador F. , Ferrer-Gisbert Pablo
Published: September 2020

The figure of Leonardo da Vinci has been extensively studied. In fact, the Leonardiana Library brings together tens of thousands of titles on Leonardo and his work. During the second half of the 20th century, various treaties were published focusing on Leonardo’s activity as an engineer, and more recently, an increasing number of scientific articles that focus on certain aspects of the prolific work of the genius such as construction, mechanics, strength of materials, etc. have been published. This article analyses the main contributions of the Tuscan genius in the field of design focusing on his processes for generating new solutions, his developments regarding graphic representation techniques, his improvements in plotting and measuring instruments, and how some of his devices were implemented and continue to maintain their usefulness.
An Approach for Route Optimization in Applications of Precision Agriculture Using UAVs
Authors: Srivastava Kshitij , Pandey Prem Chandra , Sharma Jyoti K.
Published: September 2020

This research paper focuses on providing an algorithm by which (Unmanned Aerial Vehicles) UAVs can be used to provide optimal routes for agricultural applications such as, fertilizers and pesticide spray, in crop fields. To utilize a minimum amount of inputs and complete the task without a revisit, one needs to employ optimized routes and optimal points of delivering the inputs required in precision agriculture (PA). First, stressed regions are identified using VegNet (Vegetative Network) software. Then, methods are applied for obtaining optimal routes and points for the spraying of inputs with an autonomous UAV for PA. This paper reports a unique and innovative technique to calculate the optimum location of spray points required for a particular stressed region. In this technique, the stressed regions are divided into many circular divisions with its center being a spray point of the stressed region. These circular divisions would ensure a more effective dispersion of the spray. Then an optimal path is found out which connects all the stressed regions and their spray points. The paper also describes the use of methods and algorithms including travelling salesman problem (TSP)-based route planning and a Voronoi diagram which allows applying precision agriculture techniques.
Machine Learning for Modeling the Singular Multi-Pantograph Equations
Authors: Mosavi Amirhosein , Shokri Manouchehr , Mansor Zulkefli , Qasem Sultan Noman , Band Shahab S. , Mohammadzadeh Ardashir
Published: September 2020

In this study, a new approach to basis of intelligent systems and machine learning algorithms is introduced for solving singular multi-pantograph differential equations (SMDEs). For the first time, a type-2 fuzzy logic based approach is formulated to find an approximated solution. The rules of the suggested type-2 fuzzy logic system (T2-FLS) are optimized by the square root cubature Kalman filter (SCKF) such that the proposed fineness function to be minimized. Furthermore, the stability and boundedness of the estimation error is proved by novel approach on basis of Lyapunov theorem. The accuracy and robustness of the suggested algorithm is verified by several statistical examinations. It is shown that the suggested method results in an accurate solution with rapid convergence and a lower computational cost.
A Comparison of the General Knowledge and Skills Displayed by Students Participating in International Geopolitical Competitions
Authors: Wilczyński Piotr L.
Published: September 2020

Three years ago, the Polish Geopolitical Society began an initiative focused on students, PHD candidates and interested academic societies, who wished to co-operate in popularizing the subject area of geopolitics. This initiative sought to serve as a forum for such groups and individuals to compete with other interested colleagues and groups from around the world. During the process, students strive to prove their level of professional knowledge, while their teachers assist them in preparing for their best presentations. All participants then meet during the final stages of the competition in order to exchange their experiences. This, in turn, benefits the development of general approaches and methods of study regarding the discipline of geopolitics. The question addressed in this paper then, is how such international competitions can improve the overall skills and knowledge of the subject area at hand among those participating. The importance of this question is underscored by various initiatives undertaken that attempt to measure the quality of higher education. The research presented in this article, then, is based upon interviews with both participants and organizing committee members, which attempt to gauge the experiences and results achieved during such competitions. The results show both the positive and negative aspects of organizing such gatherings. Most certainly, one could draw the conclusion that such events are the most attractive to the most ambitious of students and teachers, who consider education a privilege and as a process, which continues throughout one’s lifetime. Adversely, for those who place education in the same category as a material good, to be bought and sold, such competitions have little appeal especially when focused upon a narrow field of study.
ACSiamRPN: Adaptive Context Sampling for Visual Object Tracking
Authors: Qin Xiaofei , Zhang Yipeng , Chang Hang , Lu Hao , Zhang Xuedian
Published: September 2020

In visual object tracking fields, the Siamese network tracker, based on the region proposal network (SiamRPN), has achieved promising tracking effects, both in speed and accuracy. However, it did not consider the relationship and differences between the long-range context information of various objects. In this paper, we add a global context block (GC block), which is lightweight and can effectively model long-range dependency, to the Siamese network part of SiamRPN so that the object tracker can better understand the tracking scene. At the same time, we propose a novel convolution module, called a cropping-inside selective kernel block (CiSK block), based on selective kernel convolution (SK convolution, a module proposed in selective kernel networks) and use it in the region proposal network (RPN) part of SiamRPN, which can adaptively adjust the size of the receptive field for different types of objects. We make two improvements to SK convolution in the CiSK block. The first improvement is that in the fusion step of SK convolution, we use both global average pooling (GAP) and global maximum pooling (GMP) to enhance global information embedding. The second improvement is that after the selection step of SK convolution, we crop out the outermost pixels of features to reduce the impact of padding operations. The experiment results show that on the OTB100 benchmark, we achieved an accuracy of 0.857 and a success rate of 0.643. On the VOT2016 and VOT2019 benchmarks, we achieved expected average overlap (EAO) scores of 0.394 and 0.240, respectively.
Evaluating the Factors Affecting QoE of 360-Degree Videos and Cybersickness Levels Predictions in Virtual Reality
Authors: Shahid Anwar Muhammad , Wang Jing , Ahmad Sadique , Ullah Asad , Khan Wahab , Fei Zesong
Published: September 2020

360-degree Virtual Reality (VR) videos have already taken up viewers’ attention by storm. Despite the immense attractiveness and hype, VR conveys a loathsome side effect called “cybersickness” that often creates significant discomfort to the viewers. It is of great importance to evaluate the factors that induce cybersickness symptoms and its deterioration on the end user’s Quality-of-Experience (QoE) when visualizing 360-degree videos in VR. This manuscript’s intent is to subjectively investigate factors of high priority that affect a user’s QoE in terms of perceptual quality, presence, and cybersickness. The content type (fast, medium, and slow), the effect of camera motion (fixed, horizontal, and vertical), and the number of moving targets (none, single, and multiple) in a video can be the factors that may affect the QoE. The significant effect of such factors on end-user QoE under various stalling events (none, single, and multiple) is evaluated in a subjective experiment. The results from subjective experiments show a notable impact of these factors on end-user QoE. Finally, to label the viewing safety concern in VR, we propose a neural network-based QoE prediction method that can predict the degree of cybersickness influenced by 360-degree videos under various stalling events in VR. The performance accuracy of the proposed method is then compared against well-known Machine Learning (ML) algorithms and existing QoE prediction models. The proposed method achieved a 90% prediction accuracy rate and performed well against existing models and other ML methods.