Alzheimer’s Disease: A Decreased Cerebral Blood Flow to Critical Intraneuronal Elements is the Cause

Normally, an adequate cerebral blood flow arrives at individual cerebral neurons in which the blood flow augments activity of intraneuronal mitochondria, which is the source of intraneuronal ATP, the energy source of cerebral neurons. With a decrease in cerebral blood flow that can occur as a function of normal aging phenomena, less blood results in decreased mitochondria, decreased ATP, and a decrease in neuronal activity, which can eventually lead to Alzheimer’s disease. It has been found that placement of the omentum directly on an Alzheimer’s disease brain can lead to improved cognitive function.

A DNAmCULTURE Epigenetic Fingerprint Recapitulates Physiological Aging

Aging elicits dramatic changes to DNA methylation (DNAm), however the causes and consequences of such alterations to the epigenome remain unclear. The utility of biomarkers of aging based on DNAm patterns would be greatly enhanced if in vitro models existed that recapitulated physiological phenotypes such that modulation could garnish mechanistic insights. Using DNAm from serially passaged mouse embryonic fibroblasts, we developed a marker of culture aging and asked if culture phenotypes, like exhaustive replication, are epigenetically analogous to physiological aging. Our measure, termed DNAmCULTURE, accurately estimated passage number and was shown to strongly increase with age when examined in multiple tissues. Furthermore, we observed epigenetic alterations indicative of early cultured cells in animals undergoing caloric restriction and in lung and kidney fibroblasts re-programmed to iPSCs. This study identifies culture-derived alterations to the methylome as physiologically relevant and implicates culture aging as an important feature in known epigenetic aging phenomena.

Accelerated Battery Lifetime Simulations Using Adaptive Inter-Cycle Extrapolation Algorithm

We propose algorithms to speed up physics-based battery lifetime simulations by one to two orders of magnitude compared to the state-of-the-art. First, we propose a reformulation of the Single Particle Model with side reactions to remove algebraic equations and hence reduce stiffness, with 3x speed-up in simulation time (intra-cycle reformulation). Second, we introduce an algorithm that makes use of the difference between the `fast' timescale of battery cycling and the `slow' timescale of battery degradation by adaptively selecting and simulating representative cycles, skipping other cycles, and hence requires fewer cycle simulations to simulate the entire lifetime (adaptive inter-cycle extrapolation). This algorithm is demonstrated with a specific degradation mechanism but can be applied to various models of aging phenomena. In the particular case study considered, simulations of the entire lifetime are performed in under 5 seconds. This opens the possibility for much faster and more accurate model development, testing, and comparison with experimental data.

Accelerated battery lifetime simulations using adaptive inter-cycle extrapolation algorithm

We propose algorithms to speed up physics-based battery lifetime simulations by one to two orders of magnitude compared to the state-of-the-art. First, we propose a reformulation of the Single Particle Model with side reactions to remove algebraic equations and hence reduce stiffness, with 3x speed-up in simulation time (intra-cycle reformulation). Second, we introduce an algorithm that makes use of the difference between the `fast' timescale of battery cycling and the `slow' timescale of battery degradation by adaptively selecting and simulating representative cycles, skipping other cycles, and hence requires fewer cycle simulations to simulate the entire lifetime (adaptive inter-cycle extrapolation). This algorithm is demonstrated with a specific degradation mechanism but can be applied to various models of aging phenomena. In the particular case study considered, simulations of the entire lifetime are performed in under 5 seconds. This opens the possibility for much faster and more accurate model development, testing, and comparison with experimental data.

Work Hardening of Heat-Treated AlSi10Mg Alloy Manufactured by Single and Double Laser Selective Laser Melting: Effects of Layer Thickness and Hatch Spacing

The present study analyzed the microstructure and the mechanical properties of AlSi10Mg SLMed bars (10 × 10 × 300 mm) and billets (10 × 100 × 300 mm) before and after the direct aging at 200 °C for 4 h and the T6 heat treatment. The discussed results are compared to those obtained by the AlSi10Mg samples manufactured with the same geometry but using different process parameters (layer thickness higher than 40 μm and a hatch spacing lower than 100 μm) and also through the Quality Index (QI). These work conditions allow the obtaining of a microstructural variation and different tensile properties in as-built top samples. In both batches, the cycle time was 45 h and together with the preheated build platform at 150 °C, induced an increase of UTS (Ultimate Tensile Strength) and yield strength on the bottom rather than the top samples due to the aging phenomena. Upon completion of the direct aging heat treatment, the effects induced by the platform were cancelled, keeping a full cellular microstructure that characterized the as-built SLMed (Selective Laser Melted) samples. Moreover, the Considère criterion and the work hardening analysis showed that the failure occurs after the necking formation in some of the T6 heat-treated samples. In this last case, the Si eutectic network globularized into Si particles, causing a decrease of UTS (from around 400 MPa to 290 MPa) in favour of an increase of ductility up to 15% and reaching a QI in the range 400 ÷ 450 MPa. These values place these samples between the high-quality aluminium cast alloy and T6 heat-treated ones.

Challenges in Membrane Process for Gas Separation from Natural Gas

Membrane technology is cost effective solution for CO2 removal from natural gas. However, there is challenges during its application depending on the polymer material characteristic. Understanding on the polymer fundamental and transport properties, will enable proper design of pre-treatment and operating conditions that suits its capability envelope. Diffusivity selective membrane favors high pressure and high temperature conditions and vice versa for solubility selective polymer. On top of that, the robustness and durability of the resultant membrane, need to be evaluated with multicomponent mixture to understand the effect of competitive sorption, plasticization and aging phenomena that will seriously impacting the membrane performance during its application.

Research on Testing Method of Oil Characteristic Based on Quartz Tuning Fork Sensor

There is increasing demand for the on-board diagnosis of lubricating oils. In this research, we consider various sensor principles for on-board diagnosis of the thermal aging of engine oils. One of the parameters investigated is the viscosity of the lubricating oil, which can be efficiently measured using a microacoustic sensor. Compared with conventional viscometers, these sensors probe a different rheological domain, which needs to be considered in the interpretation of measurement results. This specific behavior is examined by systematically investigating engine oils, with and without additive packages, that were subjected to a defined artificial aging process. This paper presents design strategies for the algorithm developed and applied for direct on-board diagnosis of engine oil conditions with a fluid property sensor; this enables prediction of remaining oil life and optimization of oil change intervals, thereby minimizing the likelihood of dramatic engine failure and reducing maintenance costs. After a general description of the principles of sensor measurement, different engine oil contaminants, aging phenomena, and associated sensor detection and measurement capabilities are discussed.