Averaging in Cosmology

In this paper we discuss the effect of local inhomogeneities on the global expansion of nearly FLRW universes, in a perturbative setting. We derive a generic linearized averaging operation for metric perturbations from basic assumptions, and we explicify the issue of gauge invariance. We derive a gauge invariant expression for the back-reaction of density inhomogeneities on the global expansion of perturbed FLRW spacetimes, in terms of observable quantities, and we calculate the effect quantitatively. Since we do not adopt a comoving gauge, our result incorporates the back-reaction on the metric due to scalar velocity and vorticity perturbations. The results are compared with the results by other authors in this field.Comment: 24 pages, Latex, accepted for publication in Phys. Rev.

Elevated levels of interleukin-12/23p40 may serve as a potential indicator of dysfunctional heart rate variability in type 2 diabetes

BACKGROUND: Systemic inflammatory processes plausibly contribute to the development of cardiovascular complications, causing increased morbidity and mortality in type 2 diabetes. Circulating inflammatory markers, i.e., interleukin (IL)-6 and tumour necrosis factor-α, are associated with neurocardiac measures. We examined a broad panel of various inflammatory and inflammation-related serum markers to obtain more detailed insight into the possible neuro-immune interaction between cardiovascular regulation and systemic level of inflammation. METHODS: Serum samples from 100 participants with type 2 diabetes were analysed. Heart rate variability, cardiovascular autonomic reflex tests, and cardiac vagal tone tests were performed based on electrocardiographic readings. Data regarding covariates (demographic-, diabetes-, and cardiovascular risk factors) were registered. RESULTS: Increased serum levels of IL-12/IL-23p40 (p  < 0.01) and intercellular adhesion molecule (ICAM)-1 (p  < 0.007) were associated with diminished heart rate variability measures. After all adjustments, the associations between IL-12/23p40, SDANN and VLF persisted (p  = 0.001). Additionally, serum levels of vascular endothelial growth factor (VEGF)-C were associated with response to standing (p  = 0.005). DISCUSSION: The few but robust associations between neurocardiac regulation and serum markers found in this study suggest systemic changes in proinflammatory, endothelial, and lymphatic function, which collectively impacts the systemic cardiovascular function. Our results warrant further exploration of IL-12/IL-23p40, ICAM-1, and VEGF-C as possible cardiovascular biomarkers in T2D that may support future decisions regarding treatment strategies for improved patient care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-021-01437-w

A biophysical model of prokaryotic diversity in geothermal hot springs

Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms

Estimating the functional form for the density dependence from life history data

Two contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dynamics, population density, and environmental covariates are investigated. In this paper, we develop an approach to combine these methods and apply it to detailed data from Soay sheep (Ovis aries). We examine how density dependence and climate contribute to fluctuations in population size via age- and sex-specific demographic rates, and how fluctuations in demographic structure influence population dynamics. Density dependence contributes most, followed by climatic variation, age structure fluctuations and interactions between density and climate. We then simplify the density-dependent, stochastic, age-structured demographic model and derive a new phenomenological time series which captures the dynamics better than previously selected functions. The simple method we develop has potential to provide substantial insight into the relative contributions of population and individual-level processes to the dynamics of populations in stochastic environments

Особливості управлінння персоналом в сучасних організаціях

Головним ресурсом підприємства є люди. Саме від персоналу залежить якість продукції, рівень обслуговування, загальний ріст і розвиток компанії. Система управління персоналом підприємства представляє собою сукупність прийомів, методів, управлінських дій спрямованих на організації роботи з персоналом. При формуванні системи управління персоналом організації необхідно враховувати такі моменти: організація є відкритою системою і на її діяльність впливають фактори зовнішнього середовища, такі, як ринкова кон’юнктура, ринок праці, правові норми, потреби споживачів, конкуренти; внутрішнє середовище організації характеризується такими складовими, як: місія організації, ціль діяльності, задачі, люди, організаційна структура та корпоративна культура; результат діяльності організації залежить від кваліфікації, досвіду, компетенцій персоналу організації; конкурентоздатність організації залежить не лише від конкурентоздатності продукції чи послуг, а і від конкурентоздатності персоналу організації

Lognormal Properties of SGR 1806-20 and Implications for Other SGR Sources

The time interval between successive bursts from SGR 1806-20 and the intensity of these bursts are both consistent with lognormal distributions. Monte Carlo simulations of lognormal burst models with a range of distribution parameters have been investigated. The main conclusions are that while most sources like SGR 1806-20 should be detected in a time interval of 25 years, sources with means about 100 times longer have a probability of about 5\% of being detected in the same interval. A new breed of experiments that operate for long periods are required to search for sources with mean recurrence intervals much longer than SGR 1806-20.Comment: 4 pages, latex with seperate file containing 2 uuencoded, gzip'ed, tarred, .eps figures. Replaced with file that does not use kluwer.sty to allow automatic postscript generation. To appear in proceedings of ESLAB 2

Arctic air pollution: Challenges and opportunities for the next decade

The Arctic is a sentinel of global change. This region is influenced by multiple physical and socio-economic drivers and feedbacks, impacting both the natural and human environment. Air pollution is one such driver that impacts Arctic climate change, ecosystems and health but significant uncertainties still surround quantification of these effects. Arctic air pollution includes harmful trace gases (e.g. tropospheric ozone) and particles (e.g. black carbon, sulphate) and toxic substances (e.g. polycyclic aromatic hydrocarbons) that can be transported to the Arctic from emission sources located far outside the region, or emitted within the Arctic from activities including shipping, power production, and other industrial activities. This paper qualitatively summarizes the complex science issues motivating the creation of a new international initiative, PACES (air Pollution in the Arctic: Climate, Environment and Societies). Approaches for coordinated, international and interdisciplinary research on this topic are described with the goal to improve predictive capability via new understanding about sources, processes, feedbacks and impacts of Arctic air pollution. Overarching research actions are outlined, in which we describe our recommendations for 1) the development of trans-disciplinary approaches combining social and economic research with investigation of the chemical and physical aspects of Arctic air pollution; 2) increasing the quality and quantity of observations in the Arctic using long-term monitoring and intensive field studies, both at the surface and throughout the troposphere; and 3) developing improved predictive capability across a range of spatial and temporal scales

Aggregation Prediction in Therapeutic Protein Formulations for Excipient Design

Computational Infrastructure & Informatics Poster SessionA major concern in the development therapeutic protein formulations is protein aggregation. Proteins can interact to form bound groups of protein molecules or aggregates. Aggregates in protein formulations reduce effectiveness and can lead to severe immune responses in patients. Excipients are additive molecules that are not therapeutically active, but can increase the stability of protein formulations. An ideal excipient binds with aggregation prone regions on the protein to limit interaction of that region with another protein molecule. The goal of this project is to predict aggregation prone regions and design excipients to interact with these regions. Several tools exist to predict which regions on a protein will be most likely to initiate aggregation. Aggrescan (http://bioinf.uab.es/aggrescan/) and SAP (Spatial Aggregation Potential) were used to predict aggregation prone regions on proteins and the results were compared. Aggrescan uses experimental data to assign each amino acid an aggregation propensity score. An aggregation prone region is identified by a sequence of amino acids with high propensities. The three-dimensional structure is not used in the aggregation prediction. SAP uses molecular simulation to determine regions that are hydrophobic and solvent accessible. Each residue is scored and the results are mapped to the three-dimensional protein structure. A successful prediction tool must use parameters that correlate with aggregation potential for a folded protein. The aggregation prone regions predicted by Aggrescan and SAP were compared to experimental data on protein aggregation. Proteins with a high number of predicted regions or large predicted regions were found to have higher experimental percent aggregation. With the regions identified, molecular simulations were performed for protein-excipient systems. A protein and small molecule docking algorithm was used to determine which regions of the protein certain excipients interacted with. Trehalose, poly(vinylpyrrolidone), and guanadine hydrochloride were used. For an excipient to successfully stabilize a protein and prevent aggregation, the excipient should interact with the aggregation prone regions predicted by Aggrescan and SAP. The predicted regions were compared to the regions where the excipient docks in the molecular simulation. The simulation results were compared to experimental data on the percent aggregation observed in several protein-excipient formulations. The excipients that were found to interact with the predicted aggregation prone regions in simulations should also experimentally prohibit aggregation, leading to lower percent aggregation. Hydrogen-deuterium swapping along with FTIR analysis will be performed experimentally to determine exposed regions on the protein. Proteins with a high number of exposed regions are less stable. The exposed regions will be compared to the aggregation prone regions predicted by Aggrescan and SAP