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Medical education has drastically transformed during the COVID-19 pandemic. Measures such as adopting telemedicine visits, minimizing the number of trainees on service, discontinuing external rotations, and converting in-person to online didactics have been broadly and swiftly implemented. While these innovations have promoted greater interconnectivity amongst institutions and made continuing medical education possible, international exchange programs in medical education are still largely disrupted. In response to the changing guidelines and restrictions necessitated by the COVID-19 pandemic, the authors used Kern’s six-step approach to design and implement a virtual curriculum to replace the in-person activities of the 2020–2021 Neurology Peru-Rochester exchange program (NeuroPro). Twenty-seven trainees participated in this virtual adaptation. The average daily attendance was ≥85% and the program was rated 9/10 on average in a feedback survey (63% response rate). The median percentage of correct answers during the pre-test was 64% and it increased to 79% during the post-test (P = 0.003). Virtual adaptation of international exchange programs in medical education is feasible to safely continue international collaborative efforts to promote symbiotic building of local expertise and cross-cultural exchange during the ongoing COVID-19 pandemic and beyond.

Abstract Background The generation of new eggplant (Solanum melongena L.) cultivars with drought tolerance is a main challenge in the current context of climate change. In this study, the eight parents (seven of S. melongena and one of the wild relative S. incanum L.) of the first eggplant MAGIC (Multiparent Advanced Generation Intercrossing) population, together with four F1 hybrids amongst them, five S5 MAGIC recombinant inbred lines selected for their genetic diversity, and one commercial hybrid were evaluated in young plant stage under water stress conditions (30% field capacity; FC) and control conditions (100% FC). After a 21-day treatment period, growth and biomass traits, photosynthetic pigments, oxidative stress markers, antioxidant compounds, and proline content were evaluated. Results Significant effects (p

Titanium dioxide nanotubes (TNTs) have been extensively researched for their enhanced biomedical characteristics, including biocompatibility, cell apposition, and growth morphology. However, there is a significant concern in metallic medical devices owing to micro-movements between implants and bone in aggressive environments due to wear and corrosion synergies, leading to adverse body responses and implant failure. In this study, TNTs on Commercially Pure titanium (C.P. Ti) with three different thickness layers were grown to correlate their corrosion and wear behavior. Initially amorphous after anodization, TNTs underwent annealing at 450 °C for 2 h to transform the distorted, into a crystalline structure. The characterization included X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray (EDX), X-ray Photoelectron Spectroscopy (XPS), and contact profilometry. Potentiodynamic polarization (PD) and tribocorrosion tests were conducted in Simulated Body Fluid Electrolyte (SBF). SEM micrographs showed TNT thickness layers of 314, 691, and 5280 nm, and X-ray Diffraction showed anatase transformation post-annealing. Results confirmed a significant influence of TNT thickness layers on corrosion and tribocorrosion properties, with higher current density obtained from PD for thicker TNTs layers, associated with surface fluorine content. During tribocorrosion, annealed samples demonstrated lower corrosion tendency, potential drop, and coefficient of friction. Morphology of worn surfaces and volumetric wear rate varied with TNT thickness layer and thermal treatment.

Dog breeds are grouped based on scientific agreement, whether for traditional reasons or specific tasks during their domestication. Discrepancies may occur between public views of breed behaviour and actual evidence. This research aims to investigate differences in five behavioural traits (aggression towards people, aggression towards animals, fearfulness, responsiveness to training, and activity/excitability) by using the Dog Personality Questionnaire (DPQ) across six conventional groups/clusters of dog breeds (herding, hunting, guarding, companion dogs, potentially aggressive breeds, and mixed-breed dogs) and to assess hypotheses derived from common public presumptions. A cohort of 1309 dog owners sourced through diverse online platforms took part in the study. Contrary to stereotypes, the findings indicate that breeds labelled as “potentially aggressive” display lower levels of aggression compared to guarding breeds (χ2 (5) = 3.657, p = 0.041) and mixed-breeds (χ2 (5) = 3.870, p = 0.002). Additionally, mixed-breed dogs exhibited the highest levels of fearfulness among the six conventional clusters. In terms of aggression and gender, males demonstrated higher aggression levels towards both humans and animals compared to females (p = 0.001). These results challenge established assumptions and emphasise the necessity of evidence-based methodologies in the assessment of canine behaviour.

The relationship between language proficiency and word-problem solving has been extensively studied in the last three decades with one main finding: language proficiency is directly proportional to word-problem solving scores. Researchers have focused on language accommodations to standardized tests to level the playing field for nonnative speakers. Interestingly, several meta-analyses on language accommodation have noted that there are no significant effects on scores. At the same time, most research has reported significance and not effect sizes, which does not allow to establish comparisons between studies. Therefore, the purpose of this meta-analyses was to study the effect size of studies conducted in the US and the rest of the world to provide a new population effect size and identify possible moderator variables that have not been considered before. The main findings were that the differences in scores between native speakers and nonnative speakers (g=.360) were less pronounced than previously reported (g=.604). The participants’ age and the language of instruction and testing moderated a small percentage of the effect size, which leads to the need to include specific information about the participants to provide a clearer picture of this relationship and eventually provide language accommodations that have significant effects on scores.

This research paper presents a data-based energy management method for a vessel that predicts the upcoming load demands based on data from weather information and its automated tracking system. The vessel is powered by a hybrid propulsion system consisting of a high-temperature fuel cell system to cover the base load and a battery system to compensate for the fuel cell’s limited dynamic response capability to load fluctuations. The developed energy management method predicts the load demand of the next time steps by analyzing physical relationships utilizing operational and positional data of a real vessel. This allows a steadier operation of the fuel cell and reduces stress factors leading to accelerated aging and increasing the resource efficiency of the propulsion system. Since large ships record tracking data of their cruise and no a priori training is required to adjust the energy management, the proposed method can be implemented with small additional computational effort. The functionality of the energy management method was verified using data from a real ship and records of the water currents in the North Sea. The accuracy of the load prediction is 2.7% and the attenuation of the fuel cell’s power output could be increased by approximately 32%.

The intensification of climatic changes, mainly natural geophysical hazards like hurricanes, are of great interest to the South Texas region. Scientists and engineers must protect essential resources from coastal threats, such as storm surge. This study presents the development process and improvements of a hydrodynamic finite element model that covers the South Texas coast, specifically the Lower Laguna Madre, for the aid of local emergency management teams. Four historical tropical cyclone landfalls are evaluated and used as a means of verification of the hydrodynamic model simulation results. The parameters used to improve the accuracy of the model are the tidal harmonic constituents and the surface roughness coefficient, or manning’s n value. A total of four different scenarios that use a variety of tidal constituent combinations and nodal attribute files were developed to identify the best case. Statistical evaluation, such as regression analysis, normalized root mean square error, and scatter index, was used to determine the significance of each hydrodynamic computational storm surge result with observed historical water surface elevations. In an effort to improving all models locally, using seven tidal constituents combinations along with a surface roughness nodal attribute grid that assigns values with respect to bathymetric data improves the accuracy of the storm surge model and should, therefore, be implemented for future hydrodynamic studies in the South Texas region.

Asteraceae is one of the families with a large number of ornamental plants. Climate change imposes the need to select species that are more tolerant to changing environmental conditions, especially drought. In this study, we compared the performance under water stress of six species belonging to different tribes of Asteraceae with different geographical origins. Young plants obtained after seed germination were subjected to intermediate water stress (irrigation with half the water amount used in control treatments) and severe water stress (no irrigation at all) for one month. Growth variables and biochemical stress markers were determined to assess the effects on the plants of the stress treatments. Multivariate analysis tools were used to rank species according to their tolerance. Three species were relatively more susceptible to water stress, Callistephus chinensis, Xerochrysum bracteatum, and Calendula officinalis, whereas Leucanthemum vulgare, Glebionis carinata, and Ageratum houstonianum were more tolerant. Our study indicated that the last two species, which are registered as invasive in some geographic areas, possess a larger phenotypic plasticity. Principal component analysis (PCA) combined with canonical variation analysis (CVA) proved optimal statistical methods for analysing species of diverse origins and belonging to different genera of a large family, such as the Asteraceae.

Recenze - LANGFORD, Rosemary Teele. Company Directors’ Duties and Conflicts of Interest Oxford: Oxford University Press, 2019, 465 s. ISBN 978-0-19-881366-8.

Cloud Functions are a trend in cloud computing in which developers are allowed to install code in a Function-as-a-Service (FaaS) platform able to manage provisioning, execution, monitoring and automatic scaling. The underlying infrastructure in FaaS platforms is hidden from the developers and designers and, since the inuence of the infrastructure is unknown, this makes it di_cult to apply software performance engineering approaches on cloud functions, which could lead to wrong or inaccurate performance estimations. In this study, we explore the use of component-based modeling and simulation in order to generate performance estimations of an exemplar cloud function which was exercised using a variety of workloads. A cloud function was both implemented and instrumented to record performance datain a log _le, associated with its invocations; using the log _le as an input, we extracted a performance model in a Palladio Component Model format suitable for running simulations to validate whether the generated model could explain the runtime behavior of the function. Using this approach and further tunings in the model, we were able to validate that the simulations could explain more than 95% of the function's behavior and that component-based modeling and simulation can be considered a serious option when trying to explain the behavior of a cloud function.

The titanium nitride (Ti2N) films have good mechanical properties, such as high hardness and chemical stability, giving Ti2N good resistance to wear and corrosion. The properties of films deposited by PVD techniques are determined by their structure, microstructure, composition, and morphology that depend on the deposition parameters, such as substrate temperature, vacuum pressure, and the distance between the target and the substrate. The influence of these parameters has been studied individually. This work studied the structure, morphology, composition, and electrochemical behavior of Ti/Ti2N films deposited by RF-magnetron sputtering on carbon steel, such as a function of the power of the RF source, substrate temperature, and the target to substrate distance and the Ar/N2 ratio. The film structure was analyzed by X-ray diffraction (XRD), the morphology of cross-section by SEM, the semi-quantitative composition by EDS, and the electrochemical properties was studied by open circuit potential, potentiodynamic polarization, and electrochemical impedance spectroscopy techniques. The films showed two phases of Ti and Ti2N. The SEM-EDS exhibited a morphology according to the Stranski–Krastanov or layer-plus-island growth model. The substrate temperature of 450 °C strongly influences the electrochemical properties.

Recenze publikace - DURAČINSKÁ, Jana. Povinnosť lojality (fiduciárne povinnosti) spoločníkov kapitálových spoločností Bratislava: Wolters Kluwer, 2020, 160 s. ISBN 978-80-571-0223-6.

El rendimiento es un importante atributo de calidad de un sistema de software. La Ingeniería de rendimiento del software comprende las actividades de análisis, diseño, construcción, medición y validación, que atienden los requerimientos de rendimiento a lo largo del proceso de desarrollo de software. En los sistemas de software que utilizan comunicación basada en mensajes, el rendimiento depende en gran medida del middleware orientado a mensajes (Message-Oriented Middleware – MOM). Los arquitectos de software necesitan considerar su organización, configuración y uso para predecir el comportamiento de un sistema que use tal plataforma. La inclusión de un MOM en una arquitectura de software requiere conocer el impacto de la mensajería y de la infraestructura utilizada. Omitir la influencia del MOM llevaría a la generación de predicciones erróneas. En este artículo se explora tal influencia, mediante el modelado y la simulación basados en componentes, utilizando el enfoque Palladio Component Model – PCM. En particular, una aplicación modelada en PCM fue adaptada para incluir comunicación basada en mensajes. Las simulaciones sobre el modelo, mediciones sistemáticas y pruebas de carga sobre la aplicación permitieron determinar cómo cambios introducidos en el modelo influyen en las predicciones del comportamiento de la aplicación en cuanto a rendimiento y confiabilidad. Fue posible identificar un cuello de botella que impacta negativamente el rendimiento y la confiabilidad del sistema original. La introducción de MOM mejoró la confiabilidad del sistema, a expensas del rendimiento. La simulación del rendimiento basado en componentes reveló diferencias significativas respecto de los experimentos basados en pruebas de carga y mediciones.

Samples with 40% vol. of pores and a pore size distribution between 100 and 500 µm were produced by powder metallurgy from Ti6Al4V alloy powders. Sintering was performed at 1300 °C during one hour in an inert Argon atmosphere in a vertical dilatometer. The compressive strength and the porosity of these samples was investigated before and after compression tests through X-ray microtomography. The values of the elastic modulus (8GPa) and yield strength (80MPa) are within the range of those used in bone implants. Porosity leads to greater deformation whereas fracture of compacts occurs perpendicularly to the applied load. It was determined that the origin of the failure is generated by rupture of interparticle necks and, large pores enhance the propagation of cracks.

Basic knowledge about the factors and mechanisms affecting the performance of solar cells and their identification is essential when thinking of future improvements to the device. Within this paper, we investigated the current transport mechanism in GaAsN p-i-n solar cells grown with atmospheric pressure metal organic vapour phase epitaxy (AP-MOVPE). We examined the electro-optical and structural properties of a GaAsN solar cell epitaxial structure and correlated the results with temperature-dependent current-voltage measurements and deep level transient spectroscopy findings. The analysis of J-V-T measurements carried out in a wide temperature range allows for the determination of the dominant current transport mechanism in a GaAsN-based solar cell device and assign it a nitrogen interstitial defect, the presence of which was confirmed by DLTFS investigation.

Genomic analysis of the kelp fly Fucellia costalis (Family Anthomyiidae) from Asilomar beach, Pacific Grove, California, resulted in the assembly of its complete mitogenome. The mitogenome is 16,175 bp in length, A + T biased (78.1%), contains 37 genes, a large 1356 bp control region, and has a high-level of gene synteny to other Muscoidea. Phylogenetic analysis of F. costalis fully resolves it in a clade with two members of the Anthomyiidae, Delia platura (8.2% pairwise genetic distance) and D. antiqua (9.2% distance), in a sister position to Scathophaga stercoraria (7.8% distance) from the Scathophagidae. The phylogenetic position and genetic distances of F. costalis support the continued recognition of the subfamily Fucellinae. This identification and data extends the distributional range of F. costalis northward from California to Vancouver Island, Canada.

Genomic analysis of the marine alga Corallina chilensis from Tomales Bay, California, USA, resulted in the assembly of its complete mitogenome (GenBank accession number MK598844) and plastid genome (GenBank MK598845). The mitogenome is 25,895 bp in length and contains 50 genes. The plastid genome is 178,350 bp and contains 233 genes. The organellar genomes share a high-level of gene synteny to other Corallinales. Comparison of rbcL and cox1 gene sequences of C. chilensis from Tomales Bay reveals it is identical to three specimens from British Columbia, Canada and very similar to a specimen of C. chilensis from southern California. These genetic data confirm that C. chilensis is distributed in Pacific North America.

Experimental work on the synthesis of the CoSb2O6 oxide and its CO2 sensing properties is presented here. The oxide was synthesized by a microwave-assisted colloidal method in presence of ethylenediamine after calcination at 600 °C. This CoSb2O6 oxide crystallized in a tetragonal structure with cell parameters and Å, and space group P42/mnm. To prove its physical, chemical and sensing properties, the oxide was subjected to a series of tests: Raman spectroscopy, Scanning Electron Microscopy (SEM) and impedance (Z) measurements. Microstructures, like columns, bars and hollow hemispheres, were observed. For the CO2 sensing test, a thick film of CoSb2O6 was used, measuring the impedance variations on the presence of air/CO2 flows (0.100 sccm/0.100 sccm) using AC (alternating current) signals in the frequency-range 0.1–100 kHz and low relative temperatures (250 and 300 °C). The CO2 sensing results were quite good.

Bystromite (MgSb2O6) nanorods were prepared using a colloidal method in the presence of ethylenediamine, after a calcination step at 800 °C in static air. From X-ray powder diffraction analyses, a trirutile-type structure with lattice parameters a = 4.64 Å and c = 9.25 Å and space group P42/mnm was identified. Using scanning electron microscopy (SEM), microrods with sizes from 0.2 to 1.6 μm were observed. Transmission electron microscopy (TEM) analyses revealed that the nanorods had a length of ~86 nm and a diameter ~23.8 nm. The gas-sensing properties of these nanostructures were tested using pellets elaborated with powders of the MgSb2O6 oxide (calcined at 800 °C) at temperatures 23, 150, 200, 250 and 300 °C. The pellets were exposed to different concentrations of carbon monoxide (CO) and propane (C3H8) at these temperatures. The results showed that the MgSb2O6 nanorods possess excellent stability and high sensitivity in these atmospheres.

Abstract Background Ethylene production and signalling play an important role in somatic embryogenesis, especially for species that are recalcitrant in in vitro culture. The AP2/ERF superfamily has been identified and classified in Hevea brasiliensis. This superfamily includes the ERFs involved in response to ethylene. The relative transcript abundance of ethylene biosynthesis genes and of AP2/ERF genes was analysed during somatic embryogenesis for callus lines with different regeneration potential, in order to identify genes regulated during that process. Results The analysis of relative transcript abundance was carried out by real-time RT-PCR for 142 genes. The transcripts of ERFs from group I, VII and VIII were abundant at all stages of the somatic embryogenesis process. Forty genetic expression markers for callus regeneration capacity were identified. Fourteen markers were found for proliferating calli and 35 markers for calli at the end of the embryogenesis induction phase. Sixteen markers discriminated between normal and abnormal embryos and, lastly, there were 36 markers of conversion into plantlets. A phylogenetic analysis comparing the sequences of the AP2 domains of Hevea and Arabidopsis genes enabled us to predict the function of 13 expression marker genes. Conclusions This first characterization of the AP2/ERF superfamily in Hevea revealed dramatic regulation of the expression of AP2/ERF genes during the somatic embryogenesis process. The gene expression markers of proliferating callus capacity to regenerate plants by somatic embryogenesis should make it possible to predict callus lines suitable to be used for multiplication. Further functional characterization of these markers opens up prospects for discovering specific AP2/ERF functions in the Hevea species for which somatic embryogenesis is difficult.

Abstract Background In crop production systems, genetic markers are increasingly used to distinguish individuals within a larger population based on their genetic make-up. Supervised approaches cannot be applied directly to genotyping data due to the specific nature of those data which are neither continuous, nor nominal, nor ordinal but only partially ordered. Therefore, a strategy is needed to encode the polymorphism between samples such that known supervised approaches can be applied. Moreover, finding a minimal set of molecular markers that have optimal ability to discriminate, for example, between given groups of varieties, is important as the genotyping process can be costly in terms of laboratory consumables, labor, and time. This feature selection problem also needs special care due to the specific nature of the data used. Results An approach encoding SSR polymorphisms in a positive definite kernel is presented, which then allows the usage of any kernel supervised method. The polymorphism between the samples is encoded through the Nei-Li genetic distance, which is shown to define a positive definite kernel between the genotyped samples. Additionally, a greedy feature selection algorithm for selecting SSR marker kits is presented to build economical and efficient prediction models for discrimination. The algorithm is a filter method and outperforms other filter methods adapted to this setting. When combined with kernel linear discriminant analysis or kernel principal component analysis followed by linear discriminant analysis, the approach leads to very satisfactory prediction models. Conclusions The main advantage of the approach is to benefit from a flexible way to encode polymorphisms in a kernel and when combined with a feature selection algorithm resulting in a few specific markers, it leads to accurate and economical identification models based on SSR genotyping.