Puckettmichelsen5094

This large-scale proposed system was used to test different amounts of LOs for various science fields. The results show that the developed system can be efficiently used to create visually enhanced content for digital use.The taxonomic resolution of palynological identification is determined by morphological criteria that are used to define pollen types. Different levels of taxonomic resolution are reached in palynology, depending on several factors such as the analyst's expertise, the palynological school, the aim of the study, the preservation of the pollen grains, the reference collections and the microscope facilities. Previous research has suggested that attaining pollen records with high taxonomic resolution is important to reconstruct correctly past land use and human impact. This is in turn central to disentangling past human activities from other drivers of long-term vegetation dynamics such as natural disturbance or climate variability. In this study, we assess the impact of taxonomic resolution on the indicative capacity of anthropogenic pollen types. To achieve this, we attribute the pollen types of sixteen sedimentary records, located along a latitudinal gradient spanning from Switzerland to Italy, to three levels of taxonomic resolution previously proposed at the European scale. Our results show that higher taxonomic resolution improves the identification of human impact by enhancing the indicative power of important pollen indicators widely used in the research field. Our results may contribute to the improvement of palynological reconstructions of land use and human impact by identifying key pollen types whose determination requires particular attention.

The online version contains supplementary material available at 10.1007/s00334-021-00838-x.

The online version contains supplementary material available at 10.1007/s00334-021-00838-x.This paper describes an engineering design methodology, called conceptual design for assembly (CDFA) in the context of aircraft development, to assess aircraft systems' installation during conceptual phase, in relation to industrial performance objectives. The methodology is based on a given framework (hierarchical structure) which includes a set of attributes, collected in recognized domains that characterize the aircraft systems installation. The framework of the CDFA methodology enables to analyze product architectures at different levels of granularity, splitting the global analysis into sub-problems (problem discretization) with the aim to help architects and designers to identify product architecture weaknesses in terms of fit for assembly performances. The CDFA methodology was applied on a complex system (the nose-fuselage of a commercial aircraft) presenting a high number of criticalities both for the product and its assembly operations. Results identified the architectural components leading to the less efficient assembly operations and the rationales enabling to elaborate alternative architectures for an improved product industrial efficiency.This paper investigates the simplification of programming for non-technical university students. Typical simplification strategies are outlined, and according to our findings CT courses for non-technical students typically address learners from different faculties, providing generic and basic knowledge, not specifically related to their major. In this study, we propose instead a hermeneutic approach to simplify programming, in which we aim at clarifying the problem-solving aspect of programming, addressing computational problems that are specific to their studies and leveraging on learners' preunderstanding of the digital media they have experienced as users. The practical counterpart of our theoretical approach is a minimalistic Python multimedia library, called Medialib, that we designed to enable university students with a non-technical profile to create visual media and games with short and readable code. We discuss the use of Medialib in two empirical case studies a collaboration with the university of Kyushu in Fukuoka, Japan, and a coding module for Media Studies students at the University of Southern Denmark. Furthermore, we use Notional Machines to attempt a comparison of the simplicity of learning tools for programming, and to ground our claim that Medialib is "simpler" for learners than other popular approaches. The main contribution is a hermeneutic approach to the simplification of programming for specific contexts that combines the hermeneutic spiral and notional machines. The approach is supported by a tool, the Medialib library; the two case studies provide examples of how the approach and tool can be deployed in beginners in CT courses.EM waves are extremely powerful when it comes to propagation of information during communication. There is no alternative to EM waves in such applications. However, the use of EM waves or antennas in general has not been explored fully as sensors for measuring the change in physical environment. GANT61 in vivo This particular aspect has been exploited and the present work focuses on the application of antennas into the domain of classification. We propose accurate human activity classification (HAC) using on body miniaturized antennas. A simple patch antenna has been designed in order to be employed on human body for HAC. The antenna has been tested with respect to its Specific Absorption Ratio (SAR) values in order to make it body-mountable. The antenna has been fabricated and tested on human body while performing daily activities. The reflection co-efficient of antennas is a function of human motion activities and this principle is exploited to achieve the desired results. To explore different approaches, a miniaturized circularly polarized antenna is then designed and tested. The results of the two antennas are then compared. Dynamic Time Warping (DTW) algorithm has been used for the analysis of the Reflection co-efficient of the antenna. Excellent activity classification performance has been obtained using both the antennas, the miniaturized antenna giving better results.Hancornia speciosa Gomes is a fruit and medicinal tree species native to South America, which in Brazil is considered of potential economic value and priority for research and development. We present a map of the state-of-art, including articles, patents, and molecular data of the species to identify perspectives for future research. The annual scientific production, intellectual, social, and conceptual structure were evaluated, along with the number of patent deposits, components of the plant used, countries of deposit, international classification and assignees, and the accessibility of available molecular data. Brazil has the most significant publications (306) between 1992 and 2020. Technological products (29) have been developed from different tissues of the plant. Most of the articles and patents were developed by researchers from public universities from different regions of Brazil. The molecular data are sequences of nucleotides (164) and proteins (236) of the chloroplast genome and are described to identify the species as DNA barcodes and proteins involved in photosynthesis. The compilation and report of scientific, technological, and molecular information in the present review allowed the identification of new perspectives of research to be developed based on the gaps in knowledge regarding the species and perspectives for the definition of future research.

The online version contains supplementary material available at 10.1007/s10722-021-01319-w.

The online version contains supplementary material available at 10.1007/s10722-021-01319-w.Schurz (2019, ch. 4) argues that probabilistic accounts of induction fail. In particular, he criticises probabilistic accounts of induction that appeal to direct inference principles, including subjective Bayesian approaches (e.g., Howson 2000) and objective Bayesian approaches (see, e.g., Williamson 2017). In this paper, I argue that Schurz' preferred direct inference principle, namely Reichenbach's Principle of the Narrowest Reference Class, faces formidable problems in a standard probabilistic setting. Furthermore, the main alternative direct inference principle, Lewis' Principal Principle, is also hard to reconcile with standard probabilism. So, I argue, standard probabilistic approaches cannot appeal to direct inference to explicate the logic of induction. However, I go on to defend a non-standard objective Bayesian account of induction I argue that this approach can both accommodate direct inference and provide a viable account of the logic of induction. I then defend this account against Schurz' criticisms.Mn-doped I(II)-III-VI NCs (e.g., Mn-doped AgZnInS/ZnS NCs) possessing low-energy excitation, high brightness and long fluorescence lifetimes have been desired for time-gated fluorescence biosensing/imaging. In this type of NCs, their optical properties are significantly affected by the microscopic interactions between Mn and Mn and between Mn and host NC, the compositions of NCs, and the defects in NCs. On the other hand, it is known that Zn etching to core I(II)-III-VI NCs in NC synthesis can significantly enhance the NC brightness because Zn can exchange surface atoms (e.g., Ag and In) in NCs to minimize NC surface-defects. But for Mn-doped I(II)-III-VI NCs, Zn etching could etch out not only surface-atoms of host NCs (e.g., Ag and In) but also Mn in NCs. As a result, it could significantly affect the NC compositions and the microscopic interactions between Mn and Mn as well as between Mn and host NC, and thus the optical properties of NCs (like lifetime and absorption/emission spectra). Therefore, it is neere further measured/analyzed and the possible fluorescence mechanisms were discussed.The role of cloud services in the data-intensive industry is indispensable. Cision recently reported that the cloud market would grow to 55 billion USD, with an active contribution of the cloud to healthcare around 2025. Inspired by the report, cloud vendors expand their market and the quality of services to seek growth globally. The rapid growth of the cloud sector in the healthcare industry imposes a challenge making a rational choice of a cloud vendor (CV) out of a diverse set of vendors. Typically, the healthcare industry 4.0 sees the issue as a large-scale group decision-making problem. Previous studies on a CV selection face certain challenges, such as (i) a lack of the ability to handle multiple users' views, as well as experts'/users' complex linguistic views; (ii) the confidence level associated with a view is not considered; (iii) the transformation of multiple users' views into holistic data is lacking; and (iv) the systematic prioritization of CVs with minimum human intervention is a crucial task. Motivated by these challenges and circumventing them, a new big data-driven decision model is put forward in this paper. Initially, the data in the form of complex expressions are collected from multiple cloud users and are further transformed into a holistic decision matrix by adopting probabilistic linguistic information (PLI). PLI represents complex linguistic expressions along with the associated confidence levels. Later, a holistic decision matrix is formed with the missing values imputed by proposing an imputation algorithm. Furthermore, the criteria weights are determined by using a newly proposed mathematical model and partial information. Finally, the evaluation based on the distance from average solution (EDAS) approach is extended to PLI for the rational ranking of CVs. A real-time example of a CV selection for a healthcare center in India is exemplified so as to demonstrate the usefulness of the model, and the comparison reveals the merits and limitations of the model.