Variational cross-validation of slow dynamical modes in molecular kinetics

Markov state models (MSMs) are a widely used method for approximating the eigenspectrum of the molecular dynamics propagator, yielding insight into the long-timescale statistical kinetics and slow dynamical modes of biomolecular systems. However, the lack of a unified theoretical framework for choosing between alternative models has hampered progress, especially for non-experts applying these methods to novel biological systems. Here, we consider cross-validation with a new objective function for estimators of these slow dynamical modes, a generalized matrix Rayleigh quotient (GMRQ), which measures the ability of a rank-$m$ projection operator to capture the slow subspace of the system. It is shown that a variational theorem bounds the GMRQ from above by the sum of the first $m$ eigenvalues of the system's propagator, but that this bound can be violated when the requisite matrix elements are estimated subject to statistical uncertainty. This overfitting can be detected and avoided through cross-validation. These result make it possible to construct Markov state models for protein dynamics in a way that appropriately captures the tradeoff between systematic and statistical errors

Towards a digitised process-wheel for historic building repair and maintenance projects in Scotland

Purpose – With the increasing demand for high quality economical and sustainable historic building Repair and Maintenance (R&M) allied with the perennial problem of skills shortages (PM-project management and on-site practice) investment in new technologies becomes paramount for modernising training and practice. Yet, the historic R&M industry, in-particular Small–Medium sized Enterprises (SMEs) have yet to benefit from digital technologies (such as laser scanning, virtual reality (VR) and cloud-computing) which have the potential to enhance performance and productivity. Design/methodology/approach – A qualitative participatory action research approach was adopted. One demonstration project (Project A) exhibiting critical disrepair, showcasing the piloting of a five phased digitised ‘process-wheel’ intended to provide a common framework for facilitating collaboration of project stakeholders thereby aiding successful project delivery is reported. Five semi-structured interviews were conducted with industry employers to facilitate the process-wheel concept development. Findings – Implementing only Phase 1 of the digitised ‘process-wheel’ (e-Condition surveying incorporating laser scanning) resulted in an estimated 25-30% cost and time savings) when compared to conventional methods. The accrued benefits are two-fold: (1) provide a structured standardised data capturing approach that is shared in a common project repository amongst relevant stakeholders; (2) inform the application of digital technologies to attain efficiencies across various phases of the process-wheel. Originality/value – This paper has provided original and valuable information on the benefits of modernising R&M practice, highlighting the importance of continued investment in innovative processes and new technologies for historic building R&M to enhance existing practice and in form current training provision. Future work will focus on further piloting and validation of the process-wheel in its entirety on selected demonstration projects with a view of supporting the industry to digitise its workflows and going-fully digital to realise optimum process efficiencies

Accelerated forgetting in healthy older samples: Implications for methodology, future ageing studies, and early identification of risk of dementia

Accelerated long-term forgetting (ALF) has been reported in healthy older individuals, and is a possible early marker for risk of developing Alzheimer’s disease (AD). The Verbal Associative Learning & Memory Test (VALMT; McGibbon & Jansari, 2013) addresses methodological weaknesses in existing clinical tests and has detected ALF in epilepsy within an hour. We used VALMT to investigate learning and forgetting in healthy older participants. Older (60-69yrs) and Younger (19-31yrs) participants were compared. Using VALMT, unrelated word-pairs were learnt to criterion, then cued-recall tested at delays of 5, 30 and 55 minutes. Unique pairs were tested at each delay. Subjective memory complaints data was gathered, and the Wechsler Memory Scale Logical Memory test (WMS-LM; a standard clinical measure) was administered. VALMT identified a significant difference in delayed recall between Younger and Older groups by 55 minutes (d = 1.32). While ‘fast-learning’ Older participants scored similarly to Younger participants, ‘slow-learning’ Older participants were impaired at all delays. Forgetting rates suggested degradation of memory starts during early synaptic consolidation rather than later system-level consolidation. Increased subjective memory complaints were associated with reduced VALMT scores. By contrast, WMS-LM failed to identify significant differences between any groups, and did not correlate with memory complaints. We conclude VALMT may be better able than WMS-LM to identify subtle impairments in healthy older adults within a single clinical visit, and VALMT results better reflect subjective experience. Older slow-learners forget faster and report more subjective memory complaints, which may indicate a group at risk of developing AD

Monitoring SARS-CoV-2 in Wastewater During New York City\u27s Second Wave of COVID-19: Sewershed-level Trends and Relationships to Publicly Available Clinical Testing Data

New York City\u27s wastewater monitoring program tracked trends in sewershed-level SARS-CoV-2 loads starting in the fall of 2020, just before the start of the city\u27s second wave of the COVID-19 outbreak. During a five-month study period, from November 8, 2020 to April 11, 2021, viral loads in influent wastewater from each of New York City\u27s 14 wastewater treatment plants were measured and compared to new laboratory-confirmed COVID-19 cases for the populations in each corresponding sewershed, estimated from publicly available clinical testing data. We found significant positive correlations between viral loads in wastewater and new COVID-19 cases. The strength of the correlations varied depending on the sewershed, with Spearman\u27s rank correlation coefficients ranging between 0.38 and 0.81 (mean = 0.55). Based on a linear regression analysis of a combined data set for New York City, we found that a 1 log10 change in the SARS-CoV-2 viral load in wastewater corresponded to a 0.6 log10 change in the number of new laboratory-confirmed COVID-19 cases per day in a sewershed. An estimated minimum detectable case rate between 2–8 cases per day/100 000 people was associated with the method limit of detection in wastewater. This work offers a preliminary assessment of the relationship between wastewater monitoring data and clinical testing data in New York City. While routine monitoring and method optimization continue, information on the development of New York City\u27s wastewater monitoring program may provide insights for similar wastewater-based epidemiology efforts in the future