Variational Integrators and the Newmark Algorithm for Conservative and Dissipative Mechanical Systems

The purpose of this work is twofold. First, we demonstrate analytically that the classical Newmark family as well as related integration algorithms are variational in the sense of the Veselov formulation of discrete mechanics. Such variational algorithms are well known to be symplectic and momentum preserving and to often have excellent global energy behavior. This analytical result is veried through numerical examples and is believed to be one of the primary reasons that this class of algorithms performs so well. Second, we develop algorithms for mechanical systems with forcing, and in particular, for dissipative systems. In this case, we develop integrators that are based on a discretization of the Lagrange d'Alembert principle as well as on a variational formulation of dissipation. It is demonstrated that these types of structured integrators have good numerical behavior in terms of obtaining the correct amounts by which the energy changes over the integration run

Earth-Abundant Tin Sulfide-Based Photocathodes for Solar Hydrogen Production.

Tin-based chalcogenide semiconductors, though attractive materials for photovoltaics, have to date exhibited poor performance and stability for photoelectrochemical applications. Here, a novel strategy is reported to improve performance and stability of tin monosulfide (SnS) nanoplatelet thin films for H2 production in acidic media without any use of sacrificial reagent. P-type SnS nanoplatelet films are coated with the n-CdS buffer layer and the TiO2 passivation layer to form type II heterojunction photocathodes. These photocathodes with subsequent deposition of Pt nanoparticles generate a photovoltage of 300 mV and a photocurrent density of 2.4 mA cm-2 at 0 V versus reversible hydrogen electrode (RHE) for water splitting under simulated visible-light illumination (λ > 500 nm, Pin = 80 mW cm-2). The incident photon-to-current efficiency at 0 V versus RHE for H2 production reach a maximum of 12.7% at 575 nm with internal quantum efficiency of 13.8%. The faradaic efficiency for hydrogen evolution remains close to unity after 6000 s of illumination, confirming the robustness of the heterojunction for solar H2 production

Mechanical Systems with Symmetry, Variational Principles, and Integration Algorithms

This paper studies variational principles for mechanical systems with symmetry and their applications to integration algorithms. We recall some general features of how to reduce variational principles in the presence of a symmetry group along with general features of integration algorithms for mechanical systems. Then we describe some integration algorithms based directly on variational principles using a discretization technique of Veselov. The general idea for these variational integrators is to directly discretize Hamilton’s principle rather than the equations of motion in a way that preserves the original systems invariants, notably the symplectic form and, via a discrete version of Noether’s theorem, the momentum map. The resulting mechanical integrators are second-order accurate, implicit, symplectic-momentum algorithms. We apply these integrators to the rigid body and the double spherical pendulum to show that the techniques are competitive with existing integrators

Artificial Intelligence-Based Hierarchical Control Design for Current Sharing and Voltage Restoration in DC Microgrid of the More Electric Aircraft

In the conventional droop control method employed in the primary control layer, there is an inherent tradeoff between current-sharing accuracy and voltage regulation. Consequently, to achieve both accurate current sharing and maintain the bus voltage at its nominal value, secondary control schemes are implemented. Nevertheless, a proper design of control parameters of an electrical power system (EPS) is important as it has a huge impact on its stability and dynamic features. To that end, this article proposes a novel artificial intelligent-based design strategy for the optimal design of the power sharing and bus voltage compensation coefficients for the islanded more electric aircraft (MEA) EPS dc microgrid. Through the proposed approach, the bus voltage regulation and dynamic performance of the MEA EPS are improved in different EPS operation conditions when compared with the state-of-the-art methods. Furthermore, the safety and continuous operation of the electrical loads onboard the MEA are guaranteed. The proposed control approach can be conveniently implemented since there is no need for additional controllers and existing communication infrastructure such as power line communication can be utilized. The effectiveness of the proposed approach is validated in both simulations and hardware-in-the-loop experiments

A Low-Complexity Artificial Neural Network-Based Optimal Droop Gain Design Strategy for DC Microgrids Onboard the More Electric Aircraft

This article proposes a new droop control design method based on a “reversed data training” of artificial neural network (ANN). Conventionally, after data collection, the ANN is used for forward mapping the control variables (inputs) and system response (outputs). After training, the ANN model can be used for optimal control design for each specific system performance requirement either through curve fittings or other optimization methods. In our proposed method, however, a reversed data training process is used. The ANN uses system responses as its inputs and control variables as outputs. By doing so, the ANN can identify the requested control variables directly for a given system performance request. In the example aircraft DC microgrid, multiple generation systems feed a common DC bus with droop control implemented. During the data-generating process, different droop coefficient combinations are used, and the resulting power sharing ratios are stored as outputs. However, the ANN is data reversely trained with power sharing ratios as inputs and droop coefficients being the outputs. Through this example, we have shown that the proposed approach is straightforward and effective to derive the optimal droop gains based on desired power sharing requests. The proposed approach is tested in both simulation and experiment

Preserving Differential Privacy in Convolutional Deep Belief Networks

The remarkable development of deep learning in medicine and healthcare domain presents obvious privacy issues, when deep neural networks are built on users' personal and highly sensitive data, e.g., clinical records, user profiles, biomedical images, etc. However, only a few scientific studies on preserving privacy in deep learning have been conducted. In this paper, we focus on developing a private convolutional deep belief network (pCDBN), which essentially is a convolutional deep belief network (CDBN) under differential privacy. Our main idea of enforcing epsilon-differential privacy is to leverage the functional mechanism to perturb the energy-based objective functions of traditional CDBNs, rather than their results. One key contribution of this work is that we propose the use of Chebyshev expansion to derive the approximate polynomial representation of objective functions. Our theoretical analysis shows that we can further derive the sensitivity and error bounds of the approximate polynomial representation. As a result, preserving differential privacy in CDBNs is feasible. We applied our model in a health social network, i.e., YesiWell data, and in a handwriting digit dataset, i.e., MNIST data, for human behavior prediction, human behavior classification, and handwriting digit recognition tasks. Theoretical analysis and rigorous experimental evaluations show that the pCDBN is highly effective. It significantly outperforms existing solutions

Expression and trans-specific polymorphism of self-incompatibility RNases in Coffea (Rubiaceae)

Self-incompatibility (SI) is widespread in the angiosperms, but identifying the biochemical components of SI mechanisms has proven to be difficult in most lineages. Coffea (coffee; Rubiaceae) is a genus of old-world tropical understory trees in which the vast majority of diploid species utilize a mechanism of gametophytic self-incompatibility (GSI). The S-RNase GSI system was one of the first SI mechanisms to be biochemically characterized, and likely represents the ancestral Eudicot condition as evidenced by its functional characterization in both asterid (Solanaceae, Plantaginaceae) and rosid (Rosaceae) lineages. The S-RNase GSI mechanism employs the activity of class III RNase T2 proteins to terminate the growth of "self" pollen tubes. Here, we investigate the mechanism of Coffea GSI and specifically examine the potential for homology to S-RNase GSI by sequencing class III RNase T2 genes in populations of 14 African and Madagascan Coffea species and the closely related self-compatible species Psilanthus ebracteolatus. Phylogenetic analyses of these sequences aligned to a diverse sample of plant RNase T2 genes show that the Coffea genome contains at least three class III RNase T2 genes. Patterns of tissue-specific gene expression identify one of these RNase T2 genes as the putative Coffea S-RNase gene. We show that populations of SI Coffea are remarkably polymorphic for putative S-RNase alleles, and exhibit a persistent pattern of trans-specific polymorphism characteristic of all S-RNase genes previously isolated from GSI Eudicot lineages. We thus conclude that Coffea GSI is most likely homologous to the classic Eudicot S-RNase system, which was retained since the divergence of the Rubiaceae lineage from an ancient SI Eudicot ancestor, nearly 90 million years ago.United States National Science Foundation [0849186]; Society of Systematic Biologists; American Society of Plant Taxonomists; Duke University Graduate Schoolinfo:eu-repo/semantics/publishedVersio

Fabry Disease in Latin America: Data from the Fabry Registry

The purpose of these analyses was to characterize demographic and baseline clinical characteristics of Latin American patients with Fabry disease compared to that of patients in the rest of the world. Observational data reported to the Fabry Registry were obtained from untreated patients or prior to treatment with enzyme replacement therapy. As of October 1, 2010, 3,752 patients were enrolled in the Fabry Registry worldwide, including 333 patients within Latin America. Latin American patients tended to be younger than Fabry Registry patients enrolled in the rest of the world: mean current age 35.5 years versus 39.2 years for men (p < 0.05 by t-test), mean age 37.8 years versus 43.6 years for women (p < 0.05 by t-test). A smaller percentage of Latin American patients have received enzyme replacement therapy, compared to patients in the rest of the world: 67% versus 80% for men, and 19% versus 39% of women, respectively. Thirty-one percent of men and 22% of women in Latin America reported experiencing a significant cardiovascular, renal, or cerebrovascular event, at a mean age of 35 ± 12.6 years in men and 44 ± 12.3 years in women. Cardiovascular events were the most common type of initial clinical event among men and women in Latin America. The medical community in Latin America should be aware of Fabry disease as a possible cause of renal or cardiac dysfunction. Increased awareness will facilitate prompt diagnosis and initiation of treatment

Soil pH effects on the interactions between dissolved zinc, non-nano- and nano-ZnO with soil bacterial communities

Zinc oxide nanoparticles (ZnO NPs) are used in an array of products and processes, ranging from personal care products to antifouling paints, textiles, food additives, antibacterial agents and environmental remediation processes. Soils are an environment likely to be exposed to manmade nanoparticles due to the practice of applying sewage sludge as a fertiliser or as an organic soil improver. However, understanding on the interactions between soil properties, nanoparticles and the organisms that live within soil is lacking, especially with regards to soil bacterial communities. We studied the effects of nanoparticulate, non-nanoparticulate and ionic zinc (in the form of zinc chloride) on the composition of bacterial communities in soil with a modified pH range (from pH 4.5 to pH 7.2). We observed strong pH dependent effects on the interaction between bacterial communities and all forms of zinc, with the largest changes in bacterial community composition occurring in soils with low and medium pH levels (pH 4.8 and 5.9). The high pH soil (pH 7.2) was less susceptible to the effects of zinc exposure. At the highest doses of zinc (2500 mg/kg dw soil) both nano and non-nano particulate zinc applications elicited a similar response in the soil bacterial community, and this differed significantly to the ionic zinc salt treatment. The results highlight the importance of considering soil pH in nanotoxicology studies, although further work is needed to determine the exact mechanisms controlling the toxicity and fate and interactions of nanoparticles with soil microbial communities

Osteoprotegerin in Exosome-Like Vesicles from Human Cultured Tubular Cells and Urine

Urinary exosomes have been proposed as potential diagnostic tools. TNF superfamily cytokines and receptors may be present in exosomes and are expressed by proximal tubular cells. We have now studied the expression of selected TNF superfamily proteins in exosome-like vesicles from cultured human proximal tubular cells and human urine and have identified additional proteins in these vesicles by LC-MS/MS proteomics. Human proximal tubular cells constitutively released exosome-like vesicles that did not contain the TNF superfamily cytokines TRAIL or TWEAK. However, exosome-like vesicles contained osteoprotegerin (OPG), a TNF receptor superfamily protein, as assessed by Western blot, ELISA or selected reaction monitoring by nLC-(QQQ)MS/MS. Twenty-one additional proteins were identified in tubular cell exosomelike vesicles, including one (vitamin D binding protein) that had not been previously reported in exosome-like vesicles. Twelve were extracellular matrix proteins, including the basement membrane proteins type IV collagen, nidogen-1, agrin and fibulin-1. Urine from chronic kidney disease patients contained a higher amount of exosomal protein and exosomal OPG than urine from healthy volunteers. Specifically OPG was increased in autosomal dominant polycystic kidney disease urinary exosome-like vesicles and expressed by cystic epithelium in vivo. In conclusion, OPG is present in exosome-like vesicles secreted by proximal tubular epithelial cells and isolated from Chronic Kidney Disease urine.This work was supported by grants from the Instituto de Salud Carlos III (ISCIIIRETIC REDINREN RD06/0016, RD12/0021, PI11/01854, PI10/00072 PI09/ 00641 and PS09/00447); Comunidad de Madrid (Fibroteam S2010/BMD-2321, S2010/BMD-2378); Sociedad Española de NefrologÍa; European Network (HEALTH F2-2008-200647); DIALOK European project LSHB-CT-2007-036644; Fundacion Lilly and IRSIN/FRIAT to JE; Programa Intensificación Actividad Investigadora (ISCIII/ Agencia Laín-Entralgo/CM) to AO; Instituto de Salud Carlos III (FIS PI11/01401, CP09/00229); and Fundación Conchita Rábago de Jiménez DÍaz to GAL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscrip