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While structural realism has already been employed in physics or biology, its application as a meta-theory contextualising and relating various scientific findings on consciousness is new indeed. Out of the two variants ontic structural realism (OSR) and epistemic structural realism (ESR), the latter can be considered more suitable for the study of consciousness and its associated neurophysiological phenomena because it removes the pressure of the still unanswered 'What is consciousness?' ontological question and allows us to concentrate instead on the 'What can we know about consciousness?' epistemological question.The popularity of senior-friendly food has been increasing as the world enters the age of an aging society. It is required that senior-friendly food products are processed with the new concept of processing techniques that do not destroy the nutritional and sensory values. Ohmic heating can be an alternative to conventional heating methods for processing senior-friendly food with retaining excellent taste and quality because of less destruction of nutrients in the food. In this study, the ohmic-vacuum combination heating system was developed to process a multiphase type of senior-friendly food. Changes in physical and electrical properties of senior-friendly model foods were investigated depending on the experimental conditions such as vacuum pressure intensity and vacuum pretreatment time. Numerical simulations based on the experimental conditions were performed using COMSOL multiphysics. The ohmic-vacuum combination heating method with agitation reduced the heating time of the model food, and non-uniform temperature distribution in model food was successfully resolved due to the effect of vacuum and agitation. Furthermore, the difference was found in the hardness of solid particles depending on the vacuum treatment time and intensity after the heating treatment. The ohmic-vacuum combination heating system appeared effective when applying for the senior-friendly foods in multiphase form. The simulation results matched reasonably well with the experimental data, and the data predicted through simulation could save the cost and time of experimentation.Zeolite Y is one of the earliest known and most widely used synthetic zeolites. Many experimental investigations verify the valuable ion exchange capability of this zeolite. In this study, we assessed the effects of ion exchange on its vibrational spectra. We applied classical lattice dynamics methods for IR and Raman intensity calculations. Computed spectra of optimized zeolite Y structures with different cations were compared with experimental data. The spectra obtained in this study are in agreement with previous experimental and computational studies on zeolites from the faujasite group.Growth hormone (GH) is secreted by the pituitary gland, and in addition to its classical functions of regulating height, protein synthesis, tissue growth, and cell proliferation, GH exerts profound effects on metabolism. In this regard, GH stimulates lipolysis in white adipose tissue and antagonizes insulin's effects on glycemic control. During the last decade, a wide distribution of GH-responsive neurons were identified in numerous brain areas, especially in hypothalamic nuclei, that control metabolism. The specific role of GH action in different neuronal populations is now starting to be uncovered, and so far, it indicates that the brain is an important target of GH for the regulation of food intake, energy expenditure, and glycemia and neuroendocrine changes, particularly in response to different forms of metabolic stress such as glucoprivation, food restriction, and physical exercise. The objective of the present review is to summarize the current knowledge about the potential role of GH action in the brain for the regulation of different metabolic aspects. The findings gathered here allow us to suggest that GH represents a hormonal factor that conveys homeostatic information to the brain to produce metabolic adjustments in order to promote energy homeostasis.Increase of inbreeding and loss of genetic diversity have large impact on farm animal genetic resources. Therefore, the aims of the present study were to analyse measures of genetic diversity as well as recent and ancestral inbreeding using pedigree data of the German Brown population, and to identify causes for loss of genetic diversity. PY-60 activator The reference population included 922,333 German Brown animals born from 1990 to 2014. Pedigree depth and completeness reached an average number of complete equivalent generations of 6.24. Estimated effective population size for the German Brown reference population was about 112 with a declining trend from 141 to 95 for the birth years. Individual inbreeding coefficients increased from 0.013 to 0.036. Effective number of founders, ancestors and founder genomes of 63.6, 36.23 and 20.34 indicated unequal contributions to the reference population. Thirteen ancestors explained 50% of the genetic diversity. Higher breed proportions of US Brown Swiss were associated with higher levels of individual inbreeding. Ancestral inbreeding coefficients, which are indicative for exposure of ancestors to identical-by-descent alleles, increased with birth years but recent individual inbreeding was higher than ancestral inbreeding. Given the increase of inbreeding and decline of effective population size, measures to decrease rate of inbreeding and increase effective population size through employment of a larger number of sires are advisable.The targeted local delivery of anticancer therapeutics offers an alternative to systemic chemotherapy for oral cancers not amenable to surgical excision. However, epithelial barrier function can pose a challenge to their passive topical delivery. The charged, deformable liposomes-"iontosomes"-described here are able to overcome the buccal mucosal barrier via a combination of the electrical potential gradient imposed by iontophoresis and their shape-deforming characteristics. Two chemotherapeutic agents with very different physicochemical properties, cisplatin (CDDP) and docetaxel (DTX), were co-encapsulated in cationic iontosomes comprising 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and Lipoid-S75. The entrapment of CDDP was improved by formulating it in anionic reverse micelles of dipalmitoyl-sn-glycero-3-phospho-rac-glycerol sodium (DPPG) prior to loading in the iontosomes. Cryo-TEM imaging clearly demonstrated the iontosomes' electroresponsive shape-deformable properties. The in vitro transport study side effects.Mono(ADP-ribose) transferases and mono(ADP-ribosyl)ating sirtuins use NAD+ to perform the mono(ADP-ribosyl)ation, a simple form of post-translational modification of proteins and, in some cases, of nucleic acids. The availability of NAD+ is a limiting step and an essential requisite for NAD+ consuming enzymes. The synthesis and degradation of NAD+, as well as the transport of its key intermediates among cell compartments, play a vital role in the maintenance of optimal NAD+ levels, which are essential for the regulation of NAD+-utilizing enzymes. In this review, we provide an overview of the current knowledge of NAD+ metabolism, highlighting the functional liaison with mono(ADP-ribosyl)ating enzymes, such as the well-known ARTD10 (also named PARP10), SIRT6, and SIRT7. To this aim, we discuss the link of these enzymes with NAD+ metabolism and chronic diseases, such as cancer, degenerative disorders and aging.Graph convolutional networks (GCNs) have brought considerable improvement to the skeleton-based action recognition task. Existing GCN-based methods usually use the fixed spatial graph size among all the layers. It severely affects the model's abilities to exploit the global and semantic discriminative information due to the limits of receptive fields. Furthermore, the fixed graph size would cause many redundancies in the representation of actions, which is inefficient for the model. The redundancies could also hinder the model from focusing on beneficial features. To address those issues, we proposed a plug-and-play channel adaptive merging module (CAMM) specific for the human skeleton graph, which can merge the vertices from the same part of the skeleton graph adaptively and efficiently. The merge weights are different across the channels, so every channel has its flexibility to integrate the joints. Then, we build a novel shallow graph convolutional network (SGCN) based on the module, which achieves state-of-the-art performance with less computational cost. Experimental results on NTU-RGB+D and Kinetics-Skeleton illustrates the superiority of our methods.The structural and strength analysis of the materials used to construct an important engine element such as the turbine is of great significance, at both the design stage and during tests and training relating to emergency situations. This paper presents the results of a study on the chemical composition, morphology, and phased structure of the metallic construction material used to produce the blades of the high- and low-pressure turbines of the RD-33 jet engine, which is the propulsion unit of the MiG-29 aircraft. On the basis of an analysis of the chemical composition and phased structure, the data obtained from tests of the blade material allowed the grade of the alloy used to construct the tested elements of the jet engine turbine to be determined. The structural stability of the material was found to be lower in comparison with the engine operating conditions, which was shown by a clear decrease in the resistance properties of the blade material. The results obtained may be used as a basis for analyzing the life span of an object or a selection of material replacements, which may enable the production of the analyzed engine element.Label-free optical biosensors, such as surface plasmon resonance, are sensitive and well-established for the characterization of molecular interactions. Yet, these sensors require stabilization and constant conditions even with the use of reference channels. In this paper, we use tools from signal processing to show why these sensors are so cross-sensitive and how to overcome their drawbacks. In particular, we conceptualize the spatial affinity lock-in as a universal design principle for sensitive molecular sensors even in the complete absence of stabilization. The spatial affinity lock-in is analogous to the well-established time-domain lock-in. Instead of a time-domain signal, it modulates the binding signal at a high spatial frequency to separate it from the low spatial frequency environmental noise in Fourier space. In addition, direct sampling of the locked-in sensor's response in Fourier space enabled by diffraction has advantages over sampling in real space as done by surface plasmon resonance sensors using the distributed reference principle. This paper and part II hint at the potential of spatially locked-in diffractometric biosensors to surpass state-of-the-art temperature-stabilized refractometric biosensors. Even simple, miniaturized and non-stabilized sensors might achieve the performance of bulky lab instruments. This may enable new applications in label-free analysis of molecular binding and point-of-care diagnostics.