Tag: pubmed

Work. 2023 Nov 18. doi: 10.3233/WOR-230179. Online ahead of print.

ABSTRACT

BACKGROUND: Numerous systems for detecting driver drowsiness have been developed; however, these systems have not yet been widely used in real-time.

OBJECTIVE: The purpose of this study was to investigate at the feasibility of detecting alert and drowsy states in drivers using an integration of features from respiratory signals, vehicle lateral position, and reaction time and out-of-vehicle ways of data collection in order to improve the system’s performance and applicability in the real world.

METHODS: Data was collected from 25 healthy volunteers in a driving simulator-based study. Their respiratory activity was recorded using a wearable belt and their reaction time and vehicle lateral position were measured using tests developed on the driving simulator. To induce drowsiness, a monotonous driving environment was used. Different time domain features have been extracted from respiratory signals and combined with the reaction time and lateral position of the vehicle for modeling. The observer of rating drowsiness (ORD) scale was used to label the driver’s actual states. The t-tests and Man-Whitney test was used to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features then combined to investigate the improvement in performance using the Multilayer Perceptron (MLP), the Support Vector Machines (SVMs), the Decision Trees (DTs), and the Long Short Term Memory (LSTM) classifiers. The models were implemented in Python library 3.6.

RESULTS: The experimental results illustrate that the support vector machine classifier achieved accuracy of 88%, precision of 85%, recall of 83%, and F1 score of 84% using selected features.

CONCLUSION: These results indicate the possibility of very accurate detection of driver drowsiness and a viable solution for a practical driver drowsiness system based on combined measurement using less-intrusive and out-of-vehicle recording methods.

PMID:38007634 | DOI:10.3233/WOR-230179

J Aging Soc Policy. 2023 Nov 26:1-16. doi: 10.1080/08959420.2023.2284575. Online ahead of print.

ABSTRACT

There is growing recognition that older persons, both male and female, may experience sexual assault. One clearly identified gap in the body of scientific literature is examination of the criminal justice response for older adults who have been sexually assaulted. This retrospective age-group comparative data analysis examines publicly available population and police statistics for 2018 to describe rates (per 100,000) of reported sexual assault across adult age categories (young adult, n = 748; adult, n = 1,478; middle age, n = 290; older adult, n = 58) and compare (using Chi-square bivariate analysis) the criminal justice response to sexual assault for these adult age categories in New Zealand (NZ). Sexual assault was perpetrated against victims across all age and sex groups examined. The rate of reported sexual assault against older adults was significantly lower after the age of 65 years (7.90 per 100,000) compared to younger adults aged 20-64 years (87.57 per 100,000). Across age categories no difference was found in the proportion of cases proceeded to court action. This study raises awareness of the topic of sexual assault perpetrated against older persons and shows that a substantial number of older adults experience sexual assault in cases that do not result in court action. It points to the need for policy-makers to consider the reporting of sexual assaults against older persons to justice services.

PMID:38007620 | DOI:10.1080/08959420.2023.2284575

Sci Rep. 2023 Nov 25;13(1):20728. doi: 10.1038/s41598-023-48005-8.

ABSTRACT

In the last decade, several studies aimed at dissecting the genetic architecture of local small ruminant breeds to discover which variations are involved in the process of adaptation to environmental conditions, a topic that has acquired priority due to climate change. Considering that traditional breeds are a reservoir of such important genetic variation, improving the current knowledge about their genetic diversity and origin is the first step forward in designing sound conservation guidelines. The genetic composition of North-Western European archetypical goat breeds is still poorly exploited. In this study we aimed to fill this gap investigating goat breeds across Ireland and Scandinavia, including also some other potential continental sources of introgression. The PCA and Admixture analyses suggest a well-defined cluster that includes Norwegian and Swedish breeds, while the crossbred Danish landrace is far apart, and there appears to be a close relationship between the Irish and Saanen goats. In addition, both graph representation of historical relationships among populations and f4-ratio statistics suggest a certain degree of gene flow between the Norse and Atlantic landraces. Furthermore, we identify signs of ancient admixture events of Scandinavian origin in the Irish and in the Icelandic goats. The time when these migrations, and consequently the introgression, of Scandinavian-like alleles occurred, can be traced back to the Viking colonisation of these two isles during the Viking Age (793-1066 CE). The demographic analysis indicates a complicated history of these traditional breeds with signatures of bottleneck, inbreeding and crossbreeding with the improved breeds. Despite these recent demographic changes and the historical genetic background shaped by centuries of human-mediated gene flow, most of them maintained their genetic identity, becoming an irreplaceable genetic resource as well as a cultural heritage.

PMID:38007600 | DOI:10.1038/s41598-023-48005-8

Int J Obes (Lond). 2023 Nov 25. doi: 10.1038/s41366-023-01412-3. Online ahead of print.

ABSTRACT

INTRODUCTION: Obesity is associated with alterations in cardiac structure and haemodynamics leading to cardiovascular mortality and morbidity. Culminating evidence suggests improvement of cardiac structure and function following bariatric surgery.

OBJECTIVE: To evaluate the effect of bariatric surgery on cardiac structure and function in patients before and after bariatric surgery.

METHODS: Systematic review and meta-analysis of studies reporting pre- and postoperative cardiac structure and function parameters on cardiac imaging in patients undergoing bariatric surgery.

RESULTS: Eighty studies of 3332 patients were included. Bariatric surgery is associated with a statistically significant improvement in cardiac geometry and function including a decrease of 12.2% (95% CI 0.096-0.149; p < 0.001) in left ventricular (LV) mass index, an increase of 0.155 (95% CI 0.106-0.205; p < 0.001) in E/A ratio, a decrease of 2.012 mm (95% CI 1.356-2.699; p < 0.001) in left atrial diameter, a decrease of 1.16 mm (95% CI 0.62-1.69; p < 0.001) in LV diastolic dimension, and an increase of 1.636% (95% CI 0.706-2.566; p < 0.001) in LV ejection fraction after surgery.

CONCLUSION: Bariatric surgery led to reverse remodelling and improvement in cardiac geometry and function driven by metabolic and haemodynamic factors.

PMID:38007595 | DOI:10.1038/s41366-023-01412-3

Sci Rep. 2023 Nov 25;13(1):20731. doi: 10.1038/s41598-023-47949-1.

ABSTRACT

While the direct effects of the pandemic are well documented, less is known about the indirect ones, including changes in healthcare provision or human behavior. This paper aims to study the impact of indirect consequences on mortality, focusing on two leading causes (cardiovascular diseases, COVID-19) and places of death in Czechia, during the COVID-19 pandemic, one of the most severely affected European countries. The analysis was performed using data from the Czech Statistical Office and the Institute of Health Information and Statistics. The study compares annual mortality changes during three time periods: pre-pandemic (2018-2019), pandemic beginning and peaking (2020-2021), and pandemic fading (2022). Pandemic years were covered by the WHO public health emergency of international concern. Abridged life tables were computed, and Pollard’s decomposition was used to calculate the contributions of causes and places of death on annual differences in life expectancy. Seasonal decomposition of monthly time series revealed an increase in cardiovascular mortality at home or in social care facilities corresponding to limitations in healthcare. While COVID-19 had a systemic negative effect on life expectancy during the pandemic, the impact of cardiovascular mortality according to place of death changed over time. This study contributes to the evidence base of systemic risks during health crises and emergency response.

PMID:38007583 | DOI:10.1038/s41598-023-47949-1

Sci Rep. 2023 Nov 25;13(1):20740. doi: 10.1038/s41598-023-48104-6.

ABSTRACT

A balanced ecosystem with coexisting constituent species is often perturbed by different natural events that persist only for a finite duration of time. What becomes important is whether, in the aftermath, the ecosystem recovers its balance or not. Here we study the fate of an ecosystem by monitoring the dynamics of a particular species that encounters a sudden increase in death rate. For exploration of the fate of the species, we use Monte-Carlo simulation on a three-species cyclic rock-paper-scissor model. The density of the affected (by perturbation) species is found to drop exponentially immediately after the pulse is applied. In spite of showing this exponential decay as a short-time behavior, there exists a region in parameter space where this species surprisingly remains as a single survivor, wiping out the other two which had not been directly affected by the perturbation. Numerical simulations using stochastic differential equations of the species give consistency to our results.

PMID:38007582 | DOI:10.1038/s41598-023-48104-6

Nat Commun. 2023 Nov 25;14(1):7739. doi: 10.1038/s41467-023-43120-6.

ABSTRACT

Spatial transcriptomics (ST) technologies generate multiple data types from biological samples, namely gene expression, physical distance between data points, and/or tissue morphology. Here we developed three computational-statistical algorithms that integrate all three data types to advance understanding of cellular processes. First, we present a spatial graph-based method, pseudo-time-space (PSTS), to model and uncover relationships between transcriptional states of cells across tissues undergoing dynamic change (e.g. neurodevelopment, brain injury and/or microglia activation, and cancer progression). We further developed a spatially-constrained two-level permutation (SCTP) test to study cell-cell interaction, finding highly interactive tissue regions across thousands of ligand-receptor pairs with markedly reduced false discovery rates. Finally, we present a spatial graph-based imputation method with neural network (stSME), to correct for technical noise/dropout and increase ST data coverage. Together, the algorithms that we developed, implemented in the comprehensive and fast stLearn software, allow for robust interrogation of biological processes within healthy and diseased tissues.

PMID:38007580 | DOI:10.1038/s41467-023-43120-6

Sci Rep. 2023 Nov 25;13(1):20718. doi: 10.1038/s41598-023-47803-4.

ABSTRACT

Microplastics (MPs) as an emerging pollutant can affect aquatic organisms through physical ingestion, chemical problems and possible creation of biological layers on their surfaces in the environment. One of the significant ways for MPs to enter the aquatic environment is through the effluent discharge of wastewater treatment plants (WWTPs). In this study, first, the concentration and characteristics of MPs in secondary wastewater effluent, and the influential variables related to the coagulation process, for MPs removal were identified using systematic reviews of previous studies. Then, the most proper MPs characterization and coagulation variables were chosen by experts’ opinions using a fuzzy Delphi method. Therefore, the experiment tested in conditions close to the full-scale wastewater treatments. Finally, in the laboratory removal of MPs by coagulation of polyamide (PA), polystyrene (PS), and polyethylene (PE), < 125 and 300-600 μm in size, was tested by a jar test applying Al₂(SO₄)₃ in doses of 5 to 100 mg/L plus 15 mg/L polyacrylamide as a coagulant aid. Using R and Excel software, the results were analyzed statistically. It was concluded that the maximum and minimum removal efficiency was 74.7 and 1.39% for small PA and large PE, respectively. Smaller MPs were found to have higher removal efficiency. The MPs type PA achieved greater removal efficiency than PS, while PE had the least removal efficiency.

PMID:38007565 | DOI:10.1038/s41598-023-47803-4

Sci Rep. 2023 Nov 25;13(1):20763. doi: 10.1038/s41598-023-47327-x.

ABSTRACT

When nanoparticles are dispersed and stabilized in a base-fluid, the resulting nanofluid undergoes considerable changes in its thermophysical properties, which can have a substantial influence on the performance of nanofluid-flow systems. With such necessity and importance, developing a set of mathematical correlations to identify these properties in various conditions can greatly eliminate costly and time-consuming experimental tests. Hence, the current study aims to develop innovative correlations for estimating the specific heat capacity of mono-nanofluids. The accurate estimation of this crucial property can result in the development of more efficient and effective thermal systems, such as heat exchangers, solar collectors, microchannel cooling systems, etc. In this regard, four powerful soft-computing techniques were considered, including Generalized Reduced Gradient (GRG), Genetic Programming (GP), Gene Expression Programming (GEP), and Group Method of Data Handling (GMDH). These techniques were implemented on 2084 experimental data-points, corresponding to ten different kinds of nanoparticles and six different kinds of base-fluids, collected from previous research sources. Eventually, four distinct correlations with high accuracy were provided, and their outputs were compared to three correlations that had previously been published by other researchers. These novel correlations are applicable to various oxide-based mono-nanofluids for a broad range of independent variable values. The superiority of newly developed correlations was proven through various statistical and graphical error analyses. The GMDH-based correlation revealed the best performance with an Average Absolute Percent Relative Error (AAPRE) of 2.4163% and a Coefficient of Determination (R²) of 0.9743. At last, a leverage statistical approach was employed to identify the GMDH technique’s application domain and outlier data, and also, a sensitivity analysis was carried out to clarify the degree of dependence between input and output variables.

PMID:38007563 | DOI:10.1038/s41598-023-47327-x

Nat Commun. 2023 Nov 25;14(1):7738. doi: 10.1038/s41467-023-43551-1.

ABSTRACT

Bottom-up grown nanomaterials play an integral role in the development of quantum technologies but are often challenging to characterise on large scales. Here, we harness selective area growth of semiconductor nanowires to demonstrate large-scale integrated circuits and characterisation of large numbers of quantum devices. The circuit consisted of 512 quantum devices embedded within multiplexer/demultiplexer pairs, incorporating thousands of interconnected selective area growth nanowires operating under deep cryogenic conditions. Multiplexers enable a range of new strategies in quantum device research and scaling by increasing the device count while limiting the number of connections between room-temperature control electronics and the cryogenic samples. As an example of this potential we perform a statistical characterization of large arrays of identical quantum dots thus establishing the feasibility of applying cross-bar gating strategies for efficient scaling of future selective area growth quantum circuits. More broadly, the ability to systematically characterise large numbers of devices provides new levels of statistical certainty to materials/device development.

PMID:38007553 | DOI:10.1038/s41467-023-43551-1