bluuebunny/crossref_metadata_2025 huggingface dataset:
The Medical Triazole Voriconazole Can Select for Tandem Repeat Variations in Azole-Resistant Aspergillus Fumigatus Harboring TR34/L98H Via Asexual Reproduction
Authors: Zhang Jianhua , Zoll Jan , Engel Tobias , van den Heuvel Joost , Verweij Paul E. , Debets Alfons J. M.
Published: November 2020

Azole-resistant Aspergillus fumigatus isolates recovered at high frequency from patients, harbor mutations that are associated with variation of promoter length in the cyp51A gene. Following the discovery of the TR34/L98H genotype, new variations in tandem repeat (TR) length and number of repeats were identified, as well as additional single nucleotide polymorphisms (SNPs) in the cyp51A gene, indicating that the diversity of resistance mutations in A. fumigatus is likely to continue to increase. Investigating the development routes of TR variants is critical to be able to design preventive interventions. In this study, we tested the potential effects of azole exposure on the selection of TR variations, while allowing haploid A. fumigatus to undergo asexual reproduction. Through experimental evolution involving voriconazole (VOR) exposure, an isolate harboring TR343/L98H evolved from a clinical TR34/L98H ancestor isolate, confirmed by whole genome sequencing. TR343/L98H was associated with increased cyp51A expression and high VOR and posaconazole MICs, although additional acquired SNPs could also have contributed to the highly azole-resistant phenotype. Exposure to medical azoles was found to select for TR343, thus supporting the possibility of in-host selection of TR34 variants.
Imaging Biomarkers of Tumour Proliferation and Invasion for Personalised Lung Cancer Therapy
Authors: Marcu Loredana G.
Published: November 2020

Personalised treatment in oncology has seen great developments over the last decade, due to both technological advances and more in-depth knowledge of radiobiological processes occurring in tumours. Lung cancer therapy is no exception, as new molecular targets have been identified to further increase treatment specificity and sensitivity. Yet, tumour resistance to treatment is still one of the main reasons for treatment failure. This is due to a number of factors, among which tumour proliferation, the presence of cancer stem cells and the metastatic potential of the primary tumour are key features that require better controlling to further improve cancer management in general, and lung cancer treatment in particular. Imaging biomarkers play a key role in the identification of biological particularities within tumours and therefore are an important component of treatment personalisation in radiotherapy. Imaging techniques such as PET, SPECT, MRI that employ tumour-specific biomarkers already play a critical role in patient stratification towards individualized treatment. The aim of the current paper is to describe the radiobiological challenges of lung cancer treatment in relation to the latest imaging biomarkers that can aid in the identification of hostile cellular features for further treatment adaptation and tailoring to the individual patient’s needs.
The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey
Authors: Zadeh Shirazi Amin , Fornaciari Eric , McDonnell Mark D. , Yaghoobi Mahdi , Cevallos Yesenia , Tello-Oquendo Luis , Inca Deysi , Gomez Guillermo A.
Published: November 2020

In recent years, improved deep learning techniques have been applied to biomedical image processing for the classification and segmentation of different tumors based on magnetic resonance imaging (MRI) and histopathological imaging (H&E) clinical information. Deep Convolutional Neural Networks (DCNNs) architectures include tens to hundreds of processing layers that can extract multiple levels of features in image-based data, which would be otherwise very difficult and time-consuming to be recognized and extracted by experts for classification of tumors into different tumor types, as well as segmentation of tumor images. This article summarizes the latest studies of deep learning techniques applied to three different kinds of brain cancer medical images (histology, magnetic resonance, and computed tomography) and highlights current challenges in the field for the broader applicability of DCNN in personalized brain cancer care by focusing on two main applications of DCNNs: classification and segmentation of brain cancer tumors images.
Ageing Society and SARS-CoV-2 Mortality: Does the Healthcare Absorptive Capacity Matter?
Authors: Farzanegan Mohammad
Published: November 2020

This study examines the effect of the elderly population on SARS-CoV-2 Disease (COVID-19) mortality for a sample of 146 countries. It shows that the elderly population is robustly associated with higher COVID-19 mortality. This effect, however, decreases significantly in countries with higher health care absorptive capacity. The results are robust to control for a set of economic, institutional and regional variables.
Effect of Vegetation Removal on Soil Erosion and Bank Stability in Agricultural Drainage Ditches
Authors: Aviles Daniel , Wesström Ingrid , Joel Abraham
Published: November 2020

Maintenance of agricultural drainage ditches can be difficult to optimize if farmers have no guidelines on where to target their maintenance efforts. A main concern is whether ditch banks will experience soil erosion or mass movement (failure). In order to help identify sites that are more likely to experience soil erosion and/or mass movement, soil susceptibility to detachment was assessed in this study using a cohesive strength meter (CSM) and measurements of shear strength in unsaturated direct shear tests. The results showed that soil roots play an important role in stabilizing ditch banks against mass movement and in reducing the rate of soil detachment. A positive stabilizing effect was detected by CSM and confirmed by shear strength measurements. The conclusion is that native vegetation should be maintained on ditch banks, instead of being removed during maintenance work as is currently the case.
Asymmetrical Complexity in Languages Due to L2 Effects: Unserdeutsch and Beyond
Authors: Lindenfelser Siegwalt
Published: November 2020

This study examines asymmetries between so-called inherent and contextual categories in relation to the morphological complexity of the nominal and verbal inflectional domain of languages. The observations are traced back to the influence of adult L2 learning in scenarios of intense language contact. A method for a simple comparison of the amount of inherent versus contextual categories is proposed and applied to the German-based creole language Unserdeutsch (Rabaul Creole German) in comparison to its lexifier language. The same procedure will be applied to two further language pairs. The grammatical systems of Unserdeutsch and other contact languages display a noticeable asymmetry regarding their structural complexity. Analysing different kinds of evidence, the explanatory key factor seems to be the role of (adult) L2 acquisition in the history of a language, whereby languages with periods of widespread L2 acquisition tend to lose contextual features. This impression is reinforced by general tendencies in pidgin and creole languages. Beyond that, there seems to be a tendency for inherent categories to be more strongly associated with the verb, while contextual categories seem to be more strongly associated with the noun. This leads to an asymmetry in categorical complexity between the noun phrase and the verb phrase in languages that experienced periods of intense L2 learning.
A Phonetic Account of Spanish-English Bilinguals’ Divergence with Agreement
Authors: Colantoni Laura , Martínez Ruth , Mazzaro Natalia , Pérez-Leroux Ana T. , Rinaldi Natalia
Published: November 2020

Does bilingual language influence in the domain of phonetics impact the morphosyntactic domain? Spanish gender is encoded by word-final, unstressed vowels (/a e o/), which may diphthongize in word-boundary vowel sequences. English neutralizes unstressed final vowels and separates across-word vocalic sequences. The realization of gender vowels as schwa, due to cross-linguistic influence, may remain undetected if not directly analyzed. To explore the potential over-reporting of gender accuracy, we conducted parallel phonetic and morphosyntactic analyses of read and semi-spontaneous speech produced by 11 Monolingual speakers and 13 Early and 13 Late Spanish-English bilinguals. F1 and F2 values were extracted at five points for all word-final unstressed vowels and vowel sequences. All determiner phrases (DPs) from narratives were coded for morphological and contextual parameters. Early bilinguals exhibited clear patterns of vowel centralization and higher rates of hiatuses than the other groups. However, the morphological analysis yielded very few errors. A follow-up integrated analysis revealed that /a and o/ were realized as centralized vowels, particularly with [+Animate] nouns. We propose that bilinguals’ schwa-like realizations can be over-interpreted as target Spanish vowels. Such variable vowel realization may be a factor in the vulnerability to attrition in gender marking in Spanish as a heritage language.
Macrobiont: Cradle for the Origin of Life and Creation of a Biosphere
Authors: Clark Benton C. , Kolb Vera M.
Published: November 2020

Although the cellular microorganism is the fundamental unit of biology, the origin of life (OoL) itself is unlikely to have occurred in a microscale environment. The macrobiont (MB) is the macro-scale setting where life originated. Guided by the methodologies of Systems Analysis, we focus on subaerial ponds of scale 3 to 300 m diameter. Within such ponds, there can be substantial heterogeneity, on the vertical, horizontal, and temporal scales, which enable multi-pot prebiotic chemical evolution. Pond size-sensitivities for several figures of merit are mathematically formulated, leading to the expectation that the optimum pond size for the OoL is intermediate, but biased toward smaller sizes. Sensitivities include relative access to nutrients, energy sources, and catalysts, as sourced from geological, atmospheric, hydrospheric, and astronomical contributors. Foreshores, especially with mudcracks, are identified as a favorable component for the success of the macrobiont. To bridge the gap between inanimate matter and a planetary-scale biosphere, five stages of evolution within the macrobiont are hypothesized: prebiotic chemistry → molecular replicator → protocell → macrobiont cell → colonizer cell. Comparison of ponds with other macrobionts, including hydrothermal and meteorite settings, allows a conclusion that more than one possible macrobiont locale could enable an OoL.
Competitive Adsorption of Ionic Liquids Versus Friction Modifier and Anti-Wear Additive at Solid/Lubricant Interface—Speciation with Vibrational Sum Frequency Generation Spectroscopy
Authors: Ngo Dien , He Xin , Luo Huimin , Qu Jun , Kim Seong H.
Published: November 2020

A modern lubricant contains various additives with different functionalities and the interactions or reactions between these additives could induce synergistic or antagonistic effects in tribological performance. In this study, sum frequency generation (SFG) spectroscopy was used to investigate competitive adsorption of lubricant additives at a solid/base oil interface. A silica substrate was used as a model solid surface. The lubricant additives studied here included two oil-soluble ionic liquids (ILs, [N888H][DEHP] and [P8888][DEHP]), an antiwear additive (secondary ZDDP), an organic friction modifier (OFM), and a dispersant (PIBSI). Our results showed that for mixtures of ZDDP and IL in a base oil (PAO4), the silica surface is dominated by the IL molecules. In the cases of base oils containing OFM and IL, the silica/lubricant interface is dominated by OFM over [N888H][DEHP], while it is preferentially occupied by [P8888][DEHP] over OFM. The presence of PIBSI in the mixture of PAO4 and IL leads to the formation of a mixed surface layer at the silica surface with PIBSI as a major component. The SFG results in this investigation provide fundamental insights that are helpful to design the formulation of new lubricant additives of desired properties.
Embedded NiTi Wires for Improved Dynamic Thermomechanical Performance of Silicone Elastomers
Authors: Çakmak Umut , Graz Ingrid , Moser Richard , Fischlschweiger Michael , Major Zoltán
Published: November 2020

The extraordinary properties of shape memory NiTi alloy are combined with the inherent viscoelastic behavior of a silicon elastomer. NiTi wires are incorporated in a silicon elastomer matrix. Benefits include features as electrical/thermal conductivity, reinforcement along with enhanced damping performance and flexibility. To gain more insight of this composite, a comprehensive dynamic thermomechanical analysis is performed and the temperature- as well as frequency-dependent storage modulus and the mechanical loss factor are obtained. The analyses are realized for the composite and single components. Moreover, the models to express the examined properties and their temperature along with the frequency dependencies are also presented.
Formation of Self-Assembled Anticorrosion Films on Different Metals
Authors: Telegdi Judit
Published: November 2020

The review will first discuss shortly the phenomenon of corrosion and enroll some general possibilities to decrease the rate of this deterioration. The stress will be laid upon the presentation of anticorrosive self-assembled molecular (SAM) layers as well as on the preparation technology that is a simple technique, does not need any special device, and can be applied on different solids (metals or non-metals) alone or in combination. The paper groups the chemicals (mainly amphiphiles) that can develop nanolayers on different pure or oxidized metal surfaces. The history of the self-assembled molecular layer will be discussed from the beginning of the first application up to now. Not only the conditions of the nanofilm preparation as well as their characterization will be discussed, but the methods that can evaluate the corrosion-inhibiting efficiency of the SAM layers under a corrosive environment will be demonstrated as well.
The Significance of Coherent Transformation on Grain Refinement and Consequent Enhancement in Toughness
Authors: Li Xiucheng , Zhao Jingxiao , Dong Lili , Misra R. Devesh Kumar , Wang Xuemin , Wang Xuelin , Shang Chengjia
Published: November 2020

Coherent transformation is considered to be an effective approach to refine the microstructure and enhance toughness of structural steels. However, there are gaps in the knowledge on the key aspects of microstructure that govern toughness. In this regard, a low alloyed experimental steel with lean chemistry was subjected to a simple heat treatment involving austenitization at different temperatures, followed by quenching and tempering to obtain bainitic microstructures with different boundary composition. The microstructure of the four experimental steels was characterized by electron backscattered diffraction and mechanical properties were determined. The study indicated that the density of high angle grain boundaries does not adequately reflect the change of ductile-to-brittle transition temperatures (DBTT) of the experimental steels. Thus, we propose here a new mechanism on reducing DBTT from the perspective of misorientation of boundary, which takes into consideration these aspects in defining DBTT. One is inhibition effect on cleavage fracture by boundaries with high {100}-plane misorientation angles, and the other is ductility improvement by boundaries with high {110}-plane misorientation angles. Furthermore, the contribution of prior austenite grain boundary, packet boundary, block boundary, and sub-block boundary on toughness is also analyzed.
Fracture of Thin-Walled Polyoxymethylene Bulk Specimens in Modes I and III
Authors: Schrader Peer , Gosch Anja , Berer Michael , Marzi Stephan
Published: November 2020

Thin-walled polymeric components are used in many applications. Hence, knowledge about their fracture behavior in bulk is beneficial in practice. Within this study, the double cantilever beam (DCB) and out-of-plane double cantilever beam (ODCB) tests are enhanced to enable the testing of such bulk specimens in mode I and mode III on the basis of the J-integral. This paper then presents and discusses the experimental results following the investigation of a semicrystalline polymer (polyoxymethylen) under quasi-static load conditions. From the experiments, fracture energies of similar magnitude in both mode I and mode III were determined. In mode III, pop-in fracture was observed. Furthermore, the fracture surfaces were investigated regarding the mode I and mode III dominant crack growth mechanisms, based on the morphology of the tested material. For specimens tested in mode I, no signs of plastic deformation were observed, and the fracture surface appears flat. In mode III, some samples display a twisted fracture surface (twisting angle close to 45°), which indicates local mode I crack growth. A transfer of the presented methodology to other (more ductile) polymeric materials is deemed possible without further restrictions. In addition, the presented setup potentially enables an investigation of polymeric bulk specimens in mixed mode I+III.
Systematic Review on the Creep of Fiber-Reinforced Concrete
Authors: Tošić Nikola , Aidarov Stanislav , de la Fuente Albert
Published: November 2020

Fiber-reinforced concrete (FRC) is increasingly used in structural applications owing to its benefits in terms of toughness, durability, ductility, construction cost and time. However, research on the creep behavior of FRC has not kept pace with other areas such as short-term properties. Therefore, this study aims to present a comprehensive and critical review of literature on the creep properties and behavior of FRC with recommendations for future research. A transparent literature search and filtering methodology were used to identify studies regarding creep on the single fiber level, FRC material level, and level of structural behavior of FRC members. Both experimental and theoretical research are analyzed. The results of the review show that, at the single fiber level, pull-out creep should be considered for steel fiber-reinforced concrete, whereas fiber creep can be a governing design parameter in the case of polymeric fiber reinforced concrete subjected to permanent tensile stresses incompatible with the mechanical time-dependent performance of the fiber. On the material level of FRC, a wide variety of test parameters still hinders the formulation of comprehensive constitutive models that allow proper consideration of the creep in the design of FRC elements. Although significant research remains to be carried out, the experience gained so far confirms that both steel and polymeric fibers can be used as concrete reinforcement provided certain limitations in terms of structural applications are imposed. Finally, by providing recommendations for future research, this study aims to contribute to code development and industry uptake of structural FRC applications.
The Microstructure and Mechanical Properties of Dual-Spot Laser Welded-Brazed Ti/Al Butt Joints with Different Groove Shapes
Authors: Li Peng , Lei Zhenglong , Zhang Xinrui , Cai Enze , Chen Yanbin
Published: November 2020

Laser welding-brazing was performed to join Ti and Al together. The dual-spot laser beam mode was selected as the heat source in this study. Ti-6Al-4V and 6061-T6 Al alloys were selected as the experimental materials. Al-12Si welding wire was selected as the filler material. The effect of groove shape on the weld appearance, microstructure, temperature field, and mechanical performance of Ti/Al welded-brazed butt joints was investigated. The interfacial intermetallic compound (IMC) layer at the Ti/Weld brazing interface was inhomogeneous in joints with I-shaped and Y-shaped grooves. In Ti/Al joints with V-shaped grooves, the homogeneity of temperature field and IMC layer was improved, and the maximum thickness difference of IMC layer was only 0.20 μm. Nano-sized granular Ti7Al5Si12, Ti5Si3, and Ti(Al,Si)3 constituted the IMCs. The tensile strength of Ti/Al joints with V-shaped grooves was the highest at 187 MPa. The fracture mode transformed from brittle fractures located in the IMC layer to ductile fractures located in the Al base metal, which could be attributed to the improvement of the IMC layer at the brazing interface.
Insights into Nature of Magnetization Plateaus of a Nickel Complex [Ni4(μ-CO3)2(aetpy)8](ClO4)4 from a Spin-1 Heisenberg Diamond Cluster
Authors: Karl’ová Katarína , Strečka Jozef , Haniš Jozef , Hagiwara Masayuki
Published: November 2020

Magnetic and magnetocaloric properties of a spin-1 Heisenberg diamond cluster with two different coupling constants are investigated with the help of an exact diagonalization based on the Kambe’s method, which employs a local conservation of composite spins formed by spin-1 entities located in opposite corners of a diamond spin cluster. It is shown that the spin-1 Heisenberg diamond cluster exhibits several intriguing quantum ground states, which are manifested in low-temperature magnetization curves as intermediate plateaus at 1/4, 1/2, and 3/4 of the saturation magnetization. In addition, the spin-1 Heisenberg diamond cluster may also exhibit an enhanced magnetocaloric effect, which may be relevant for a low-temperature refrigeration achieved through the adiabatic demagnetization. It is evidenced that the spin-1 Heisenberg diamond cluster with the antiferromagnetic coupling constants J1/kB = 41.4 K and J2/kB = 9.2 K satisfactorily reproduces a low-temperature magnetization curve recorded for the tetranuclear nickel complex [Ni4(μ-CO3)2(aetpy)8](ClO4)4 (aetpy = 2-aminoethyl-pyridine) including a size and position of intermediate plateaus detected at 1/2 and 3/4 of the saturation magnetization. A microscopic nature of fractional magnetization plateaus observed experimentally is clarified and interpreted in terms of valence-bond crystal with either a single or double valence bond. It is suggested that this frustrated magnetic molecule can provide a prospective cryogenic coolant with the maximal isothermal entropy change −ΔSM=10.6 J·K−1·kg−1 in a temperature range below 2.3 K.
Automated Maintenance Data Classification Using Recurrent Neural Network: Enhancement by Spotted Hyena-Based Whale Optimization
Authors: Abidi Mustufa Haider , Umer Usama , Mohammed Muneer Khan , Aboudaif Mohamed K. , Alkhalefah Hisham
Published: November 2020

Data classification has been considered extensively in different fields, such as machine learning, artificial intelligence, pattern recognition, and data mining, and the expansion of classification has yielded immense achievements. The automatic classification of maintenance data has been investigated over the past few decades owing to its usefulness in construction and facility management. To utilize automated data classification in the maintenance field, a data classification model is implemented in this study based on the analysis of different mechanical maintenance data. The developed model involves four main steps: (a) data acquisition, (b) feature extraction, (c) feature selection, and (d) classification. During data acquisition, four types of dataset are collected from the benchmark Google datasets. The attributes of each dataset are further processed for classification. Principal component analysis and first-order and second-order statistical features are computed during the feature extraction process. To reduce the dimensions of the features for error-free classification, feature selection was performed. The hybridization of two algorithms, the Whale Optimization Algorithm (WOA) and Spotted Hyena Optimization (SHO), tends to produce a new algorithm—i.e., a Spotted Hyena-based Whale Optimization Algorithm (SH-WOA), which is adopted for performing feature selection. The selected features are subjected to a deep learning algorithm called Recurrent Neural Network (RNN). To enhance the efficiency of conventional RNNs, the number of hidden neurons in an RNN is optimized using the developed SH-WOA. Finally, the efficacy of the proposed model is verified utilizing the entire dataset. Experimental results show that the developed model can effectively solve uncertain data classification, which minimizes the execution time and enhances efficiency.
Impact of Heat Generation on Magneto-Nanofluid Free Convection Flow about Sphere in the Plume Region
Authors: Khan Anwar , Ashraf Muhammad , Rashad Ahmed M. , Nabwey Hossam A.
Published: November 2020

The main aim of the current study is to analyze the physical phenomenon of free convection nanofluids heat transfer along a sphere and fluid eruption through boundary layer into a plume region above the surface of the sphere. In the current study, the effect of heat generation with the inclusion of an applied magnetic field by considering nanofluids is incorporated. The dimensioned form of formulated equations of the said phenomenon is transformed into the non-dimensional form, and then solved numerically. The developed finite difference method along with the Thomas algorithm has been utilized to approximate the given equations. The numerical simulation is carried out for the different physical parameters involved, such as magnetic field parameter, Prandtl number, thermophoresis parameter, heat generation parameter, Schmidt number, and Brownian motion parameter. Later, the quantities, such as velocity, temperature, and mass distribution, are plotted under the impacts of different values of different controlling parameters to ascertain how these quantities are affected by these pertinent parameters. Moreover, the obtained results are displayed graphically as well in tabular form. The novelty of present work is that we first secure results around different points of a sphere and then the effects of all parameters are captured above the sphere in the plume.
Modeling and Performance Improvement of Direct Power Control of Doubly-Fed Induction Generator Based Wind Turbine through Second-Order Sliding Mode Control Approach
Authors: Mazen Alhato Mohammed , Bouallègue Soufiene , Rezk Hegazy
Published: November 2020

A second-order sliding mode (SOSM)-based direct power control (DPC) of a doubly-fed induction generator (DFIG) is introduced in this research paper. Firstly, the DFIG output powers are regulated with the developed SOSM controller-based DPC scheme. The Super Twisting Algorithm (STA) has been used to reduce the chattering phenomenon. The proposed strategy is a combination of the Lyapunov theory and metaheuristics algorithms, which has been considered to identify the optimal gains of the STA-SOSM controllers. The Lyapunov function method is employed to define the stability regions of the controller parameters. On the other hand, the metaheuristics algorithms are mainly employed to select the fine controllers’ parameters from the predefined ranges. A Thermal Exchange Optimization (TEO) method is used to compute the optimal gain parameters. To prove the superiority of the proposed TEO, its obtained results have been compared with those obtained by other algorithms, including particle swarm optimization, genetic algorithm, water cycle algorithm, grasshopper optimization algorithm and harmony search algorithm. Moreover, the results of the introduced TEO-based SOSM controller have been also compared with the Proportional-Integral (PI)-based vector control and the conventional sliding mode control-based DPC. Moreover, an empirical comparison is carried out to investigate the indication of every metaheuristics method by employing Friedman’s rank and Bonferroni tests. The main findings indicate the effectiveness of STA-SOSM control for system stability and power quality improvement. The ripples in the active and reactive powers are minimized and the harmonics’ distortions of stator and rotor currents are improved. Besides, the STA-SOSM controller shows a superior performance of control in terms of chattering phenomenon elimination.
Constrained Mixed-Variable Design Optimization Based on Particle Swarm Optimizer with a Diversity Classifier for Cyclically Neighboring Subpopulations
Authors: Kim Tae-Hyoung , Cho Minhaeng , Shin Sangwoo
Published: November 2020

In this research, an easy-to-use particle swarm optimizer (PSO) for solving constrained engineering design problems involving mixed-integer-discrete-continuous (MIDC) variables that adopt two kinds of diversity-enhancing mechanisms to achieve superior reliability and validity was developed. As an initial diversity-boosting tool, the local neighborhood topology of each particle is set up such that information exchange is restricted to a limited number of consecutively numbered particles. This topological mechanism forces each particle to move in the search space while interacting only with its neighboring subpopulation. The second diversity-enhancing task is to ensure that the exploration behavior of each particle in the search space is governed such that it follows the diversity classifier decision applied to its subpopulation. This diversity classification iteratively adjusts the three-phase velocity-related mechanism of each particle such that it approaches or retreats from its previous best position/the current best position among the subpopulation. In summary, this PSO tool not only introduces the social interaction of the particle within its cyclically neighboring subpopulation but also exploits the three-phase velocity behavior law governed by the distributed diversity measures categorized for each neighboring subpopulation. This scheme has superior reliability, as well as high practicality for engineering optimization problems involving MIDC variables, which are handled by the widely adopted straightforward rounding-off technique used in most swarm-inspired metaheuristic search technologies.
Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem
Authors: Mahrach Mohammed , Miranda Gara , León Coromoto , Segredo Eduardo
Published: November 2020

One of the main components of most modern Multi-Objective Evolutionary Algorithms (MOEAs) is to maintain a proper diversity within a population in order to avoid the premature convergence problem. Due to this implicit feature that most MOEAs share, their application for Single-Objective Optimization (SO) might be helpful, and provides a promising field of research. Some common approaches to this topic are based on adding extra—and generally artificial—objectives to the problem formulation. However, when applying MOEAs to implicit Multi-Objective Optimization Problems (MOPs), it is not common to analyze how effective said approaches are in relation to optimizing each objective separately. In this paper, we present a comparative study between MOEAs and Single-Objective Evolutionary Algorithms (SOEAs) when optimizing every objective in a MOP, considering here the bi-objective case. For the study, we focus on two well-known and widely studied optimization problems: the Knapsack Problem (KNP) and the Travelling Salesman Problem (TSP). The experimental study considers three MOEAs and two SOEAs. Each SOEA is applied independently for each optimization objective, such that the optimized values obtained for each objective can be compared to the multi-objective solutions achieved by the MOEAs. MOEAs, however, allow optimizing two objectives at once, since the resulting Pareto fronts can be used to analyze the endpoints, i.e., the point optimizing objective 1 and the point optimizing objective 2. The experimental results show that, although MOEAs have to deal with several objectives simultaneously, they can compete with SOEAs, especially when dealing with strongly correlated or large instances.
Nandrolone Decanoate: Use, Abuse and Side Effects
Authors: Patanè Federico Giuseppe , Liberto Aldo , Maria Maglitto Andreana Nicoletta , Malandrino Pasquale , Esposito Massimiliano , Amico Francesco , Cocimano Giuseppe , Rosi Giuseppe Li , Condorelli Dario , Nunno Nunzio Di , Montana Angelo
Published: November 2020

Background and Objectives: Androgens play a significant role in the development of male reproductive organs. The clinical use of synthetic testosterone derivatives, such as nandrolone, is focused on maximizing the anabolic effects and minimizing the androgenic ones. Class II anabolic androgenic steroids (AAS), including nandrolone, are rapidly becoming a widespread group of drugs used both clinically and illicitly. The illicit use of AAS is diffused among adolescent and bodybuilders because of their anabolic proprieties and their capacity to increase tolerance to exercise. This systematic review aims to focus on side effects related to illicit AAS abuse, evaluating the scientific literature in order to underline the most frequent side effects on AAS abusers’ bodies. Materials and Methods: A systematic review of the scientific literature was performed using the PubMed database and the keywords “nandrolone decanoate”. The inclusion criteria for articles or abstracts were English language and the presence of the following words: “abuse” or “adverse effects”. After applying the exclusion and inclusion criteria, from a total of 766 articles, only 148 were considered eligible for the study. Results: The most reported adverse effects (found in more than 5% of the studies) were endocrine effects (18 studies, 42%), such as virilization, gynecomastia, hormonal disorders, dyslipidemia, genital alterations, and infertility; cardiovascular dysfunctions (six studies, 14%) such as vascular damage, coagulation disorders, and arteriosus hypertension; skin disorders (five studies, 12%) such as pricking, acne, and skin spots; psychiatric and mood disorders (four studies, 9%) such as aggressiveness, sleep disorders and anxiety; musculoskeletal disorders (two studies, 5%), excretory disorders (two studies, 5%), and gastrointestinal disorders (two studies, 5%). Conclusions: Based on the result of our study, the most common adverse effects secondary to the abuse of nandrolone decanoate (ND) involve the endocrine, cardiovascular, skin, and psychiatric systems. These data could prove useful to healthcare professionals in both sports and clinical settings.
Treatment of Olive Mill Wastewater through Integrated Pressure-Driven Membrane Processes
Authors: Bottino Aldo , Capannelli Gustavo , Comite Antonio , Costa Camilla , Firpo Raffaella , Jezowska Anna , Pagliero Marcello
Published: November 2020

The disposal of wastewater resulting from olive oil production (olive mill wastewater, OMW) is a major issue for olive oil producers. This wastewater is among the most polluting due to the very high concentration of organic substances and the presence of hardly degradable phenolic compounds. The systems proposed for OMW treatment are essentially based either on conventional chemical-physical, biological and thermal processes, or on membrane processes. With respect to conventional methods, membrane processes allow to separate different species without the use of chemicals or heat. This work deals with the use of the integrated pressure-driven membrane processes for the treatment of OMW. They consist of a first stage (microfiltration, MF) in which a porous multichannel ceramic membrane retains suspended materials and produces a clarified permeate for a second stage (reverse osmosis, RO), in order to separate (and concentrate) dissolved substances from water. Laboratory scale experiments with different small flat sheet RO membranes were first carried out in order to select the most appropriate one for the successive bench scale tests with a spiral wound module having a large membrane surface. The aim of this test was to concentrate the dissolved substances and to produce water with low salinity, chemical oxygen demand (COD), and reduced phytotoxicity due to a low content of phenolic compounds. The trend of the permeate flux and membrane retention as a function of the volume concentration ratio was investigated. The influence of OMW origin and its aging on the membrane performance was also studied.
The Mini Blast Furnace Process: An Efficient Reactor for Green Pig Iron Production Using Charcoal and Hydrogen-Rich Gas: A Study of Cases
Authors: Adilson de Castro Jose , Medeiros Giulio Antunes de , Oliveira Elizabeth Mendes de , de Campos Marcos Flavio , Nogami Hiroshi
Published: November 2020

The mini blast furnace process is an efficient route to produce pig iron based on the burden with granulated charcoal. New, improved technologies have recently been introduced in the mini blast furnace process, such as pulverized charcoal and gas injections, new burden materials, and peripheral devices that improve the overall process efficiency. In this paper, we revise the new injection possibilities and discuss new aspects for further developments. The analysis is carried out with a comprehensive multiphase multicomponent mathematical model using mass, momentum, and energy conservation principles coupled with the rate equations for chemical reactions, multiphase momentum, and heat exchanges. We analyze new technological possibilities for the enhancement of this process as follows: (i) a base case of pulverized charcoal injection with industrial data comparison; (ii) a set of scenarios with raceway injections, combining pulverized charcoal with hydrogen-rich fuel gas, replacing granular charcoal in the burden; (iii) a set of scenarios with hydrogen-rich gas injection at the shaft level, replacing reducing gas in the granular zone of the reactor; and the possible combination of both methodologies. The simulated scenarios showed that a considerable decrease in granular charcoal consumption in the burden materials could be replaced by combining a pulverized charcoal injection of 150 kg/tHM and increasing rich gas injections and oxygen enrichment values, decreasing the specific blast injection and granular charcoal. The productivity of the mini blast furnace process was increased for all scenarios compared with the reference case. We review the aspects of these operational conditions and present an outlook for improvements on the process efficiency.
TiAl-Based Materials by In Situ Selective Laser Melting of Ti/Al Reactive Composites
Authors: Nepapushev Andrey , Moskovskikh Dmitry , Vorotilo Ksenia , Rogachev Alexander
Published: November 2020

Additive manufacturing (AM) of refractory materials requires either a high laser power or the use of various easily melting binders. In this work, we propose an alternative—the use of spherical reactive Ti/Al composite particles, obtained by preliminary high-energy ball milling. These powders were used to produce high-temperature TiAl-based materials during the selective laser melting (SLM) process. When laser heating is applied, mechanically activated composite particles readily react with the release of a considerable amount of heat and transform into corresponding intermetallic compounds. The combustion can be initiated at relatively low temperatures, and the exothermic effect prevents the sharp cooling of as-sintered tracks. This approach allows one to produce dense intermetallic materials with a homogeneous structure in one step via SLM and eliminates the need for powerful lasers, binders, or additional post-processing and heat treatments.
Islet Health, Hormone Secretion, and Insulin Responsivity with Low-Carbohydrate Feeding in Diabetes
Authors: Locatelli Cassandra A. A. , Mulvihill Erin E.
Published: November 2020

Exploring new avenues to control daily fluctuations in glycemia has been a central theme for diabetes research since the Diabetes Control and Complications Trial (DCCT). Carbohydrate restriction has re-emerged as a means to control type 2 diabetes mellitus (T2DM), becoming increasingly popular and supported by national diabetes associations in Canada, Australia, the USA, and Europe. This approval comes from many positive outcomes on HbA1c in human studies; yet mechanisms underlying their success have not been fully elucidated. In this review, we discuss the preclinical and clinical studies investigating the role of carbohydrate restriction and physiological elevations in ketone bodies directly on pancreatic islet health, islet hormone secretion, and insulin sensitivity. Included studies have clearly outlined diet compositions, including a diet with 30% or less of calories from carbohydrates.
Bessel Beam: Significance and Applications—A Progressive Review
Authors: Khonina Svetlana Nikolaevna , Kazanskiy Nikolay Lvovich , Karpeev Sergey Vladimirovich , Butt Muhammad Ali
Published: November 2020

Diffraction is a phenomenon related to the wave nature of light and arises when a propagating wave comes across an obstacle. Consequently, the wave can be transformed in amplitude or phase and diffraction occurs. Those parts of the wavefront avoiding an obstacle form a diffraction pattern after interfering with each other. In this review paper, we have discussed the topic of non-diffractive beams, explicitly Bessel beams. Such beams provide some resistance to diffraction and hence are hypothetically a phenomenal alternate to Gaussian beams in several circumstances. Several outstanding applications are coined to Bessel beams and have been employed in commercial applications. We have discussed several hot applications based on these magnificent beams such as optical trapping, material processing, free-space long-distance self-healing beams, optical coherence tomography, superresolution, sharp focusing, polarization transformation, increased depth of focus, birefringence detection based on astigmatic transformed BB and encryption in optical communication. According to our knowledge, each topic presented in this review is justifiably explained.
A Low Spring Constant Piezoresistive Microcantilever for Biological Reagent Detection
Authors: Tian Yuan , Zhao Rui , Liu Yi , Yu Xiaomei
Published: November 2020

This paper introduces a piezoresistive microcantilever with a low spring constant. The microcantilever was fabricated with titanium (Ti) as the piezoresistor, a low spring constant polyimide (PI) layer, and a thin silicon oxide (SiO2) layer as the top and bottom passive layers, respectively. Excellent mechanical performances with the spring constant of 0.02128 N/m and the deflection sensitivity (∆V/V)/∆z of 1.03 × 10−7 nm−1 were obtained. The output voltage fluctuation of a Wheatstone bridge, which consists of four piezoresistive microcantilevers, is less than 3 μV@3 V in a phosphate buffered saline (PBS) environment. A microcantilever aptasensor was then developed through functionalizing the microcantilevers with a ricin aptamer probe, and detections on ricin with concentrations of 10, 20, 50 and 100 ng/mL were successfully realized. A good specificity was also confirmed by using bovine serum albumin (BSA) as a blank control. The experiment results show that the Ti and PI-based microcantilever has great prospects for ultrasensitive biochemical molecule detections with high reliability and specificity.
Assessing the Risk of Occurrence of Bluetongue in Senegal
Authors: Gahn Marie Cicille Ba , Niakh Fallou , Ciss Mamadou , Seck Ismaila , Lo Modou Moustapha , Fall Assane Gueye , Biteye Biram , Fall Moussa , Ndiaye Mbengué , Ba Aminata , Seck Momar Talla , Sall Baba , Lo Mbargou , Faye Coumba , Squarzoni-Diaw Cécile , Ka Alioune , Amevoin Yves , Apolloni Andrea
Published: November 2020

Bluetongue is a non-contagious viral disease affecting small ruminants and cattle that can cause severe economic losses in the livestock sector. The virus is transmitted by certain species of the genus Culicoides and consequently, understanding their distribution is essential to enable the identification of high-risk transmission areas. In this work we use bioclimatic and environmental variables to predict vector abundance, and estimate spatial variations in the basic reproductive ratio  R0. The resulting estimates were combined with livestock mobility and serological data to assess the risk of Bluetongue outbreaks in Senegal. The results show an increasing abundance of C. imicola, C. oxystoma, C. enderleini, and C. miombo from north to south. R0 < 1 for most areas of Senegal, whilst southern (Casamance) and southeastern (Kedougou and part of Tambacounda) agro-pastoral areas have the highest risk of outbreak (R0 = 2.7 and 2.9, respectively). The next higher risk areas are in the Senegal River Valley (R0 = 1.07), and the Atlantic coast zones. Seroprevalence rates, shown by cELISA, weren’t positively correlated with outbreak probability. Future works should include follow-up studies of competent vector abundancies and serological surveys based on the results of the risk analysis conducted here to optimize the national epidemiological surveillance system.
Highly Sensitive and Rapid Quantitative Detection of Plasmodium falciparum Using an Image Cytometer
Authors: Hashimoto Muneaki , Yokota Kazumichi , Kajimoto Kazuaki , Matsumoto Musashi , Tatsumi Atsuro , Nakajima Yoshihiro , Mita Toshihiro , Minakawa Noboru , Oka Hiroaki , Kataoka Masatoshi
Published: November 2020

The gold standard for malaria diagnosis is microscopic examination of blood films by expert microscopists. It is important to detect submicroscopic and asymptomatic Plasmodium infections in people, therefore the development of highly sensitive devices for diagnosing malaria is required. In the present study, we investigated whether an imaging cytometer was useful for the highly sensitive quantitative detection of parasites. Whole blood samples were prepared from uninfected individuals spiked with Plasmodium falciparum-infected erythrocytes. Thereafter, erythrocytes were purified using a push column comprising of a syringe filter unit with SiO2-nanofiber filters. After adding the erythrocytes, stained with nuclear stain, to a six-well plate, quantitative detection of the parasites was performed using an image cytometer, CQ1. Imaging of 2.6 × 106 erythrocytes was completed in 3 min, and the limit of detection indicated parasitemia of 0.00010% (≈5 parasites/μL of blood). In addition to rapid, highly sensitive, and quantitative detection, the ease of application and economic costs, image cytometry could be efficiently applied to diagnose submicroscopic parasites in infected people from endemic countries.
Quantitative Microbial Risk Assessment Based on Whole Genome Sequencing Data: Case of Listeria monocytogenes
Authors: Njage Patrick Murigu Kamau , Leekitcharoenphon Pimlapas , Hansen Lisbeth Truelstrup , Hendriksen Rene S. , Faes Christel , Aerts Marc , Hald Tine
Published: November 2020

The application of high-throughput DNA sequencing technologies (WGS) data remain an increasingly discussed but vastly unexplored resource in the public health domain of quantitative microbial risk assessment (QMRA). This is due to challenges including high dimensionality of WGS data and heterogeneity of microbial growth phenotype data. This study provides an innovative approach for modeling the impact of population heterogeneity in microbial phenotypic stress response and integrates this into predictive models inputting a high-dimensional WGS data for increased precision exposure assessment using an example of Listeria monocytogenes. Finite mixture models were used to distinguish the number of sub-populations for each of the stress phenotypes, acid, cold, salt and desiccation. Machine learning predictive models were selected from six algorithms by inputting WGS data to predict the sub-population membership of new strains with unknown stress response data. An example QMRA was conducted for cultured milk products using the strains of unknown stress phenotype to illustrate the significance of the findings of this study. Increased resistance to stress conditions leads to increased growth, the likelihood of higher exposure and probability of illness. Neglecting within-species genetic and phenotypic heterogeneity in microbial stress response may over or underestimate microbial exposure and eventual risk during QMRA.