Quantitative and temporal measurement of dynamic autophagy rates

Autophagy is a multistep degradative process that is essential for maintaining cellular homeostasis. Systematically quantifying flux through this pathway is critical for gaining fundamental insights and effectively modulating this process that is dysregulated during many diseases. Established methods to quantify flux use steady state measurements, which provide limited information about the perturbation and the cellular response. We present a theoretical and experimental framework to measure autophagic steps in the form of rates under non-steady state conditions. We use this approach to measure temporal responses to rapamycin and wortmannin treatments, two commonly used autophagy modulators. We quantified changes in autophagy rates in as little as 10 minutes, which can establish direct mechanisms for autophagy perturbation before feedback begins. We identified concentration-dependent effects of rapamycin on the initial and temporal progression of autophagy rates. We also found variable recovery time from wortmannin’s inhibition of autophagy, which is further accelerated by rapamycin. In summary, this new approach enables the quantification of autophagy flux with high sensitivity and temporal resolution and facilitates a comprehensive understanding of this process.

An approach to adhesive bond characterisation using guided acoustic waves in multi-layered plates

An approach for the non-destructive characterisation of adhesive bonds using guided ultrasonic waves is presented. Pulsed laser radiation is used to thermoacoustically excite broadband ultrasonic waves in a multi-layered sample, consisting of a metal plate adhesively joined to a polymeric layer using synthetic resin. The resulting signals are received by a purpose-built piezoelectric transducer. Varying the distance between excitation and detection yields spatio-temporal measurement data, from which the dispersive properties of the propagating waves can be inferred using a two-dimensional Fourier transform, assuming the plates to act as coupled waveguides. Coupled multi-layered waveguides show an effect referred to as mode repulsion, where the distance between certain modes in the frequency-wavenumber domain is assumed to be a measure of coupling strength. Measurements at different stages of curing of the adhesive layer are performed and evaluated. A comparison of the results shows changes in the dispersive properties, namely an increased modal bandwidth for the fully cured sample as well as an increased modal distance.

Temporal Measurement Invariance of the Financially Focused Self-Concept Construct

Persons maintaining a financially focused self-concept view financial success as a core aspect of their respective self-concepts. We examined whether measurement properties of the financially focused self-concept scale (FFS) are invariant over time. A sample of predominantly older community members who gamble (N = 147) completed the 4-item FFS and Problem Gambling Severity Index (PGSI) twice, approximately four weeks apart. FFS had strong temporal measurement invariance and moderate-to-high temporal stability. FFS and PGSI were also positively associated within and across waves. These findings indicate that people who score higher in financial focus report more gambling problems concurrently and over time.

Designing and interpreting 4D tumour spheroid experiments

Tumour spheroid experiments are routinely used to study cancer progression and treatment. Various and inconsistent experimental designs are used, leading to challenges in interpretation and reproducibility. Using multiple experimental designs, live-dead cell staining, and real-time cell cycle imaging, we measure necrotic and proliferation-inhibited regions in over 1000 4D tumour spheroids (3D space plus cell cycle status). By intentionally varying the initial spheroid size and temporal sampling frequencies across multiple cell lines, we collect an abundance of measurements of internal spheroid structure. These data are difficult to compare and interpret. However, using an objective mathematical modelling framework and statistical identifiability analysis we quantitatively compare experimental designs and identify design choices that produce reliable biological insight. Measurements of internal spheroid structure provide the most insight, whereas varying initial spheroid size and temporal measurement frequency is less important. Our general framework applies to spheroids grown in different conditions and with different cell types.

Urgent Decision Making: Resolving Visuomotor Interactions at High Temporal Resolution

Measuring when exactly perceptual decisions are made is crucial for defining how the activation of specific neurons contributes to behavior. However, in traditional, nonurgent visuomotor tasks, the uncertainty of this temporal measurement is very large. This is a problem not only for delimiting the capacity of perception, but also for correctly interpreting the functional roles ascribed to choice-related neuronal responses. In this article, we review psychophysical, neurophysiological, and modeling work based on urgent visuomotor tasks in which this temporal uncertainty can be effectively overcome. The cornerstone of this work is a novel behavioral metric that describes the evolution of the subject's perceptual judgment moment by moment, allowing us to resolve numerous perceptual events that unfold within a few tens of milliseconds. In this framework, the neural distinction between perceptual evaluation and motor selection processes becomes particularly clear, as the conclusion of one is not contingent on that of the other. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Spatial and Temporal Measurement of the Interaction between the County Economy and Rural Transformation in Xinjiang, China

Given the background of urbanization and rural revitalization in the new era, it is important to explore the synergy between regional macroeconomics and rural transformation, as a balanced and coordinated urban–rural relationship must be built to promote regional sustainable development and rural revitalization. This paper used the spatial econometric model to study the spatiotemporal synergy and interaction between Xinjiang’s county economy and rural transformation from 2007 to 2017. The conclusions were as follows. A clear spatial difference exists between the county economy and the rural transformation level, and regional bulk agricultural products lack competitiveness. The synergy between the county economy and rural transformation is weak, as the county economy is lagging while rural transformation progresses without collaboration, indicating different types of non-equivalence. The county economy has a stronger spatial dependence on rural transformation and insufficient spillover, a stagnating effect, mainly negative driving effects, and unstable interaction effects; while the unstable changes in rural transformation affect the county economy. The urbanization rate, urban wage level, rural employment structure, and planting area per capita were the main influencing factors. It is necessary to deepen rural transformation, consolidate and enhance its stability, cultivate regional growth poles, promote overall development, and promote regional coordination.

Exploring the Relationship between Preprocessing and Hyperparameter Tuning for Vibration-Based Machine Fault Diagnosis Using CNNs

This paper demonstrates the differences between popular transformation-based input representations for vibration-based machine fault diagnosis. This paper highlights the dependency of different input representations on hyperparameter selection with the results of training different configurations of classical convolutional neural networks (CNNs) with three common benchmarking datasets. Raw temporal measurement, Fourier spectrum, envelope spectrum, and spectrogram input types are individually used to train CNNs. Many configurations of CNNs are trained, with variable input sizes, convolutional kernel sizes and stride. The results show that each input type favors different combinations of hyperparameters, and that each of the datasets studied yield different performance characteristics. The input sizes are found to be the most significant determiner of whether overfitting will occur. It is demonstrated that CNNs trained with spectrograms are less dependent on hyperparameter optimization over all three datasets. This paper demonstrates the wide range of performance achieved by CNNs when preprocessing method and hyperparameters are varied as well as their complex interaction, providing researchers with useful background information and a starting place for further optimization.

Economic and Mathematical Modelling of the Effectiveness of the National System for Combatting Cyber Fraud and Legalisation of Criminal Proceeds Based on Survival Analysis Methods

In modern world, the digitalisation of financial relations, the development of innovative technologies, and the emergence and use of cryptocurrencies for payments lead to an increase in the number of cyber frauds in the financial sector and their intellectualisation, increasing the illegal outflow of funds abroad. Ineffective decisions and inaction in counteracting these threats lead to large-scale negative consequences of both financial and social nature. The purpose of this study is to implement economic and mathematical modelling of the effectiveness of the national system for combatting cyber fraud and legalisation of criminal proceeds, which is based on the use of survival analysis methods. The study provides a bibliometric analysis of publications on the effectiveness of cyber fraud and combatting the legalisation of illegal funds, by building a bibliometric map of keywords, using VOSviewer software. This allowed identifying 7 clusters of basic categories of cyber fraud analysis, and changes in the vectors of research scientists showed a visual map of the contextual-temporal measurement of research into the effectiveness of cyber fraud in the publications of the Scopus database. The paper examines the effectiveness of the national system for combatting cyber fraud and money laundering based on survival tables. As a result of the study, the effectiveness of the national system for combatting cyber fraud and money laundering was analysed based on the Kaplan-Meier method. The study identified the dependences of the effectiveness of the national system for combatting cyber fraud and legalisation of criminal proceeds on the time interval after the discovery of violations. The practical value of applying the developed model is to form an analytical basis for further management decisions by the National Bank of Ukraine, the State Financial Monitoring Service, and the Security Service of Ukraine in terms of the effectiveness of the national system to combat cyber fraud and legalisation of criminal proceeds and the need to adjust it