Community environment, cognitive impairment and dementia in later life: results from the Cognitive Function and Ageing Study

Background: Few studies have investigated the impact of the community environment, as distinct from area deprivation, on cognition in later life. This study explores cross-sectional associations between cognitive impairment and dementia and environmental features at the community level in older people. Method: The postcodes of the 2424 participants in the year-10 interview of the Cognitive Function and Ageing Study in England were mapped into small area level geographical units (Lower-layer Super Output Areas) and linked to environmental data in government statistics. Multilevel logistic regression was conducted to investigate associations between cognitive impairment (defined as MMSE3 in GMS-AGECAT) and community level measurements including area deprivation, natural environment, land use mix and crime. Sensitivity analyses tested the impact of people moving residence within the last two years. Results: Higher levels of area deprivation and crime were not significantly associated with cognitive impairment and dementia after accounting for individual level factors. Living in areas with high land use mix was significantly associated with a nearly 60% reduced odds of dementia (OR: 0.4; 95% CI: 0.2, 0.8) after adjusting for individual level factors and area deprivation, but there was no linear trend for cognitive impairment. Increased odds of dementia (OR: 2.2, 95% CI: 1.2, 4.2) and cognitive impairment (OR: 1.4, 95% CI: 1.0, 2.0) were found in the highest quartile of natural environment availability. Findings were robust to exclusion of the recently relocated. Conclusion: Features of land use have complex associations with cognitive impairment and dementia. Further investigations should focus on environmental influences on cognition to inform health and social policies

Community environment, cognitive impairment and dementia in later life: results from the Cognitive Function and Ageing Study

Background: Few studies have investigated the impact of the community environment, as distinct from area deprivation, on cognition in later life. This study explores cross-sectional associations between cognitive impairment and dementia and environmental features at the community level in older people. Method: The postcodes of the 2424 participants in the year-10 interview of the Cognitive Function and Ageing Study in England were mapped into small area level geographical units (Lower-layer Super Output Areas) and linked to environmental data in government statistics. Multilevel logistic regression was conducted to investigate associations between cognitive impairment (defined as MMSE3 in GMS-AGECAT) and community level measurements including area deprivation, natural environment, land use mix and crime. Sensitivity analyses tested the impact of people moving residence within the last two years. Results: Higher levels of area deprivation and crime were not significantly associated with cognitive impairment and dementia after accounting for individual level factors. Living in areas with high land use mix was significantly associated with a nearly 60% reduced odds of dementia (OR: 0.4; 95% CI: 0.2, 0.8) after adjusting for individual level factors and area deprivation, but there was no linear trend for cognitive impairment. Increased odds of dementia (OR: 2.2, 95% CI: 1.2, 4.2) and cognitive impairment (OR: 1.4, 95% CI: 1.0, 2.0) were found in the highest quartile of natural environment availability. Findings were robust to exclusion of the recently relocated. Conclusion: Features of land use have complex associations with cognitive impairment and dementia. Further investigations should focus on environmental influences on cognition to inform health and social policies

Distance measures in gravitational-wave astrophysics and cosmology

We present quantities which characterize the sensitivity of gravitational-wave observatories to sources at cosmological distances. In particular, we introduce and generalize the horizon, range, response, and reach distances. These quantities incorporate a number of important effects, including cosmologically well-defined distances and volumes, cosmological redshift, cosmological time dilation, and rate density evolution. In addition, these quantities incorporate unique aspects of gravitational wave detectors, such as the variable sky sensitivity of the detectors and the scaling of the sensitivity with inverse distance. An online calculator (https://users.rcc.uchicago.edu/~dholz/gwc/) and python notebook (https://github.com/hsinyuc/distancetool) to determine GW distances are available. We provide answers to the question: "How far can gravitational-wave detectors hear?

Toward Robust Manufacturing Scheduling: Stochastic Job-Shop Scheduling

Manufacturing plays a significant role in promoting economic development, production, exports, and job creation, which ultimately contribute to improving the quality of life. The presence of manufacturing defects is, however, inevitable leading to products being discarded, i.e. scrapped. In some cases, defective products can be repaired through rework. Scrap and rework cause a longer completion time, which can contribute to the order being shipped late. In addition, complex manufacturing scheduling becomes much more challenging when the above uncertainties are present. Motivated by the presence of uncertainties as well as combinatorial complexity, this paper addresses the challenge illustrated through a case study of stochastic job-shop scheduling problems arising within low-volume high-variety manufacturing. To ensure on-time delivery, high-quality solutions are required, and near-optimal solutions must be obtained within strict time constraints to ensure smooth operations on the job-shop floor. To efficiently solve the stochastic job-shop scheduling (JSS) problem, a recently-developed Surrogate "Level-Based" Lagrangian Relaxation is used to reduce computational effort while efficiently exploiting the geometric convergence potential inherent to Polyak's step-sizing formula thereby leading to fast convergence. Numerical testing demonstrates that the new method is more than two orders of magnitude faster as compared to commercial solvers

Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music

To model the periodicity of beats, state-of-the-art beat tracking systems use "post-processing trackers" (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for music with a steady tempo. For expressive classical music, however, these assumptions can be too rigid. With two large datasets of Western classical piano music, namely the Aligned Scores and Performances (ASAP) dataset and a dataset of Chopin's Mazurkas (Maz-5), we report on experiments showing the failure of existing PPTs to cope with local tempo changes, thus calling for new methods. In this paper, we propose a new local periodicity-based PPT, called predominant local pulse-based dynamic programming (PLPDP) tracking, that allows for more flexible tempo transitions. Specifically, the new PPT incorporates a method called "predominant local pulses" (PLP) in combination with a dynamic programming (DP) component to jointly consider the locally detected periodicity and beat activation strength at each time instant. Accordingly, PLPDP accounts for the local periodicity, rather than relying on a global tempo assumption. Compared to existing PPTs, PLPDP particularly enhances the recall values at the cost of a lower precision, resulting in an overall improvement of F1-score for beat tracking in ASAP (from 0.473 to 0.493) and Maz-5 (from 0.595 to 0.838).Comment: Accepted to IEEE/ACM Transactions on Audio, Speech, and Language Processing (July 2023

O-GlcNAc modification blocks the aggregation and toxicity of the protein α-synuclein associated with Parkinson's disease.

Several aggregation-prone proteins associated with neurodegenerative diseases can be modified by O-linked N-acetyl-glucosamine (O-GlcNAc) in vivo. One of these proteins, α-synuclein, is a toxic aggregating protein associated with synucleinopathies, including Parkinson's disease. However, the effect of O-GlcNAcylation on α-synuclein is not clear. Here, we use synthetic protein chemistry to generate both unmodified α-synuclein and α-synuclein bearing a site-specific O-GlcNAc modification at the physiologically relevant threonine residue 72. We show that this single modification has a notable and substoichiometric inhibitory effect on α-synuclein aggregation, while not affecting the membrane binding or bending properties of α-synuclein. O-GlcNAcylation is also shown to affect the phosphorylation of α-synuclein in vitro and block the toxicity of α-synuclein that was exogenously added to cells in culture. These results suggest that increasing O-GlcNAcylation may slow the progression of synucleinopathies and further support a general function for O-GlcNAc in preventing protein aggregation