Heterogeneity in Subnational Mortality in The Context of The COVID-19 Pandemic: The Case of Belgian Districts

Background: The COVID-19 pandemic has caused major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shock at the sub-national level, rigorously accounting for the different sources of uncertainty.Methods: Using death registration data from Belgium, we first assess the change in the heterogeneity of subnational standardized mortality ratios in 2020, when compared to previous years. We then measure the shock of the pandemic using district-level values of life expectancy, comparing the observed and projected districts life expectancy, accounting for all sources of uncertainty (related to the life-table construction at district level and to the projection methods at country and district level). The Bayesian modelling approach makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.Results: The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial, with some districts barely showing any impact whereas the Bruxelles-Capital and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in mortality levels ' heterogeneity at a subnational level in comparison to past years measured by both the standardized mortality ratios and the life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.Conclusion: Developing sub-national mortality estimates with their uncertainty is key to understanding why certain areas have been hard hit in comparison to others.

Measuring habitat quality for waterbirds: a review

Quantifying habitat quality is dependent on measuring a site’s relative contribution to population growth rate. This is challenging for studies of waterbirds, whose high mobility can decouple demographic rates from local habitat conditions and make sustained monitoring of individuals near-impossible. To overcome these challenges, biologists have used many direct and indirect proxies of waterbird habitat quality. However, consensus on what methods are most appropriate for a given scenario is lacking. We undertook a structured literature review of the methods used to quantify waterbird habitat quality, and provide a synthesis of the context-dependent strengths and limitations of those methods. Our structured search of the Web of Science database returned a sample of 398 studies, upon which our review was based. The reviewed studies assessed habitat quality by either measuring habitat attributes (e.g., food abundance, water quality, vegetation structure), or measuring attributes of the waterbirds themselves (e.g., demographic parameters, body condition, behaviour, distribution). Measuring habitat attributes, although they are only indirectly related to demographic rates, has the advantage of being unaffected by waterbird behavioural stochasticity. Conversely, waterbird-derived measures (e.g., body condition, peck rates) may be more directly related to demographic rates than habitat variables, but may be subject to greater stochastic variation (e.g., behavioural change due to presence of conspecifics). Therefore, caution is needed to ensure that the measured variable does influence waterbird demographic rates. This assumption was usually based on ecological theory rather than empirical evidence. Our review highlighted that there is no single best, universally applicable method to quantify waterbird habitat quality. Individual project specifics (e.g., time frame, spatial scale, funding) will influence the choice of variables measured. Where possible, practitioners should measure variables most directly related to demographic rates. Generally, measuring multiple variables yields a better chance of accurately capturing the relationship between habitat characteristics and demographic rates.

Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata

Simple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise.

Noise in a metabolic pathway leads to persister formation in Mycobacterium tuberculosis

Tuberculosis is difficult to treat due to dormant cells in hypoxic granulomas, and stochastically-formed persisters tolerant of antibiotics. Bactericidal antibiotics kill by corrupting their energy-dependent targets. We reasoned that noise in the expression of an energy-generating component will produce rare persister cells. In sorted low ATP M. tuberculosis grown on acetate there is considerable cell-to-cell variation in the level of mRNA coding for AckA, the acetate kinase. Quenching the noise by overexpressing ackA sharply decreases persisters, showing that it acts as the main persister gene under these conditions. This demonstrates that a low energy mechanism is responsible for the formation of M. tuberculosis persisters and suggests that the mechanism of their antibiotic tolerance is similar to that of dormant cells in a granuloma. Entrance into a low energy state driven by stochastic variation in expression of energy-producing enzymes is likely a general mechanism by which bacteria produce persisters.

High-Speed Imaging Reveals the Bimodal Nature of Dense Core Vesicle Exocytosis and Jet Flow through the Fusion Pore

During exocytosis, the fusion of secretory vesicle with plasma membrane forms a pore that regulates release of neurotransmitter and peptide. Osmotic forces contribute to exocytosis but release through the pore is thought to occur by diffusion. Heterogeneity of fusion pore behavior has also suggested stochastic variation in a common exocytic mechanism, implying a lack of biological control. Imaging at millisecond resolution to observe the first events in exocytosis, we find that fusion pore duration is bimodal rather than stochastic. Loss of calcium sensor synaptotagmin 7 increases the proportion of slow events without changing the intrinsic properties of either class, indicating the potential for independent regulation. In addition, dual imaging shows a delay in the entry of external dye relative to release that indicates discharge at high velocity rather than strictly by diffusion.

Influence of climate change on the energy performance assessment of NZEB houses

The Energy Performance of Buildings (EPB) regulations aim to reduce primary energy use and carbon dioxide emissions of buildings, which are the result of creating a comfortable and healthy indoor environment. In this study, the influence of climate change on the regulatory EPB calculation results is analysed for the Flanders region in Belgium. The results of the analysis may be used by authorities to better define nearly zero energy building (NZEB) requirements today. Meteonorm has been used to simulate future climate change based on IPCC scenarios and urban heat island effect. These future climates have been implemented in a Revit-and Excel-based tool that calculates the stochastic variation of energy performance for six different dwelling typologies, based on the semi-steady state energy use calculation method applied in the regional rating method. Four different packages of measures to achieve NZEB performance (thermal insulation, energy efficient ventilation, renewable energy technologies,…) have been considered. The results for primary energy use, overheating indicator and net energy use for heating and cooling have been analysed. As may be expected, climate change is found to lead to an increase in overheating risk, an increase in cooling energy use, and a decrease in heating energy use in the analysed dwellings. Since in most cases the decrease in heating energy use outweighs the increase in cooling energy use, the total primary energy use decreases in most cases for the 2050 future climate.

Membrane-mediated dimerization potentiates PIP5K lipid kinase activity

The phosphatidylinositol 4-phosphate 5-kinase (PIP5K) family of lipid modifying enzymes generate the majority of phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) lipids found at the plasma membrane in eukaryotic cells. PI(4,5)P2 lipids serve a critical role in regulating receptor activation, ion channel gating, endocytosis, and actin nucleation. Here we describe how PIP5K activity is regulated by cooperative binding to PI(4,5)P2 lipids and membrane-mediated dimerization of the kinase domain. In contrast to constitutively dimeric phosphatidylinositol 5-phosphate 4-kinase (PIP4K, type II PIPK), solution PIP5K exists in a weak monomer-dimer equilibrium. PIP5K monomers can associate with PI(4,5)P2 containing membranes and dimerize in a protein density dependent manner. Although dispensable for PI(4,5)P2 binding and lipid kinase activity, dimerization enhances the catalytic efficiency of PIP5K through a mechanism consistent with allosteric regulation. Additionally, dimerization amplifies stochastic variation in the kinase reaction velocity and strengthens effects such as the recently described stochastic geometry sensing. Overall, the mechanism of PIP5K membrane binding creates a broad dynamic range of lipid kinase activities that are coupled to the density of PI(4,5)P2 and membrane bound kinase.

On randomly changing conformity bias in cultural transmission

Humans and nonhuman animals display conformist as well as anticonformist biases in cultural transmission. Whereas many previous mathematical models have incorporated constant conformity coefficients, empirical research suggests that the extent of (anti)conformity in populations can change over time. We incorporate stochastic time-varying conformity coefficients into a widely used conformity model, which assumes a fixed number n of “role models” sampled by each individual. We also allow the number of role models to vary over time (nt). Under anticonformity, nonconvergence can occur in deterministic and stochastic models with different parameter values. Even if strong anticonformity may occur, if conformity or random copying (i.e., neither conformity nor anticonformity) is expected, there is convergence to one of the three equilibria seen in previous deterministic models of conformity. Moreover, this result is robust to stochastic variation in nt. However, dynamic properties of these equilibria may be different from those in deterministic models. For example, with random conformity coefficients, all equilibria can be stochastically locally stable simultaneously. Finally, we study the effect of randomly changing weak selection. Allowing the level of conformity, the number of role models, and selection to vary stochastically may produce a more realistic representation of the wide range of group-level properties that can emerge under (anti)conformist biases. This promises to make interpretation of the effect of conformity on differences between populations, for example those connected by migration, rather difficult. Future research incorporating finite population sizes and migration would contribute added realism to these models.

Energy-induced resonance synchronization in neural circuits

Biological neurons can be approached by using some functional neural circuits, and the biophysical mechanism for signal processing can be explained. Chemical stimulus can adjust the intracellular and extracellular ions concentration, and thus the channel current can be regulated to trigger appropriate firing modes in the neural activities. A physical stimulus often injects kinds of energy, and the energy can be encoded in the components for generating a certain channel current. The energy driving on the cell can be effective to enhance the pumping of ions and mode transition is induced. Based on a simple neural circuit exposed to the external magnetic field, the mode selection is investigated to explore the biophysical mechanism of energy absorption by applying periodic, and stochastic magnetic fields, respectively. The external field energy is encoded in the induction coil of the neural circuit, and the channel current is induced. Two identical neural circuits are exposed to the same magnetic field and the synchronization approach is investigated without synapse coupling. It is found that two neurons in periodic firings can be synchronized under the same periodic or noise-like magnetic field even applying different initials, while intermittent phase lock is induced between two chaotic neurons. Stochastic variation in the external magnetic field can induce noisy induced electromotive force (IEF) and the firing mode is regulated effectively. When both noisy IEF and periodic stimulus are applied, synchronization stability between periodic neurons with initials diversity is enhanced while synchronization approach between chaotic neurons becomes difficult. In addition, the Hamilton energy in each neuron can keep pace with another neuron when complete synchronization is stabilized within a finite transient period. These results provide new insights to know the energy encoding mechanism in neural circuits and neurons exposed to external magnetic field.

Design of DC/DC Boost Converter for Photovoltaic Systems Applications

Renewable energy sources are growing rapidly and becoming an essential part of the national electricity system. The photovoltaic (PV) system is considered an appropriate option due to its advantages over traditional fossil energy sources. However, this energy source is affected by the stochastic variation of irradiance parameters and environment temperature, etc. Therefore, improving the efficiency of this PV system is always an interesting topic to scientists and many researches. This paper focuses on studying and designing DC/DC boost converter with integrated the Maximum Power Point Tracking (MPPT) algorithm using a hybrid method. The method of finding the maximum power point is developed based on many modern algorithms. Design equipment is analyzed, evaluated and gave positive results with high performance.