Accurate Representation Research Articles

Light attenuation parameterization in a highly turbid mega estuary and its impact on the coastal planktonic ecosystem

Light is essential for phytoplankton photosynthesis and many other biogeochemical processes in the aquatic system. However, light regimes vary greatly in the estuaries and coasts due to the optical complexity of the Case-2 waters. In this study, observed vertical profiles of photosynthetically active radiation (PAR; 400-700 nm) in a highly turbid mega estuary, the Changjiang (Yangtze River) Estuary, are used to quantify the effects of sedimentary and biogeochemical components on PAR attenuation in the water column and associated ecological impacts. The in-situ data suggest suspended sediment plays the most crucial role in light diffuse attenuation coefficient (Kd) distribution, followed by salinity (i.e., an index for colored dissolved organic matter) and phytoplankton chlorophyll-a. A new parameterization of Kd, based on suspended sediment, chlorophyll-a concentration, and salinity, is fitted using multiple linear regression. The previous and new Kd parameterizations are further applied to a coupled hydrodynamics-sediment-ecosystem model to simulate spring phytoplankton blooms. Comparative model runs reveal that the new Kd parameterization resulted in a better representation of the spring bloom patterns in magnitude, horizontal distribution, and vertical thickness of the high chlorophyll-a band offshore the turbidity maximum zone during the spring bloom. In summary, accurate representations of underwater light fields in the optically complex Case-2 water are critical in understanding biophysical processes that control planktonic ecosystem dynamics in the estuaries and coastal seas.

Machine learning for air quality index (AQI) forecasting: shallow learning or deep learning?

In this study, several machine learning (ML) models consisting of shallow learning (SL) models (e.g., random forest (RF), K-nearest neighbor (KNN), weighted K-nearest neighbor (WKNN), support vector machine (SVM), artificial neural network (ANN), and deep learning (DL) models (e.g., long short-term memory (LSTM), gated recurrent unit (GRU), recurrent neural network (RNN), and convolutional neural network (CNN)) have been employed for predicting air pollution and its classification. The models were selected based on factors such as prediction accuracy, model generalization, model complexity, and training time. Our study focuses on analyzing and predicting the air quality index (AQI) using daily PM10 concentration as natural pollutants and nine meteorological parameters from March 2013 to February 2022 in Zabol. We also utilized the information gain (IG) method for feature selection. Several measures including accuracy, F1 score, precision, recall, and the area under the curve (AUC), are computed to assess model performance. This study demonstrates the efficacy of DL models, particularly CNN, in predicting the AQI with remarkable accuracy. Our findings reveal that all models effectively classify air quality levels, with an AUC of 0.95 for the good class in both DL and ANN models, significantly outperforming SL models. The AUC values for the hazardous and moderate classes of DL models were also impressive, at 0.90 and 0.83, respectively, underscoring their effectiveness in critical classifications. In terms of performance, CNN achieved an accuracy of 0.60, leading the models, while RF followed closely at 0.58. RNN, GRU, ANN, and SVM each reached an accuracy of 0.57, demonstrating a competitive edge. LSTM and WKNN recorded an accuracy of 0.55, and KNN was slightly lower at 0.53. These results highlight the superior capabilities of DL models in addressing complex air quality classifications, providing invaluable insights for policymakers. By leveraging these advanced techniques, stakeholders can implement more effective strategies to combat air pollution and safeguard public health. It is worth noting that irregular monitoring of air quality data may affect the robustness of our predictions, highlighting the need for more consistent data collection to ensure an accurate representation of pollution levels.

Insights into the aetiology and temporal trends in cardiac mortality in the young: a 21-year review of national and registry data in the united kingdom

Abstract Background An accurate representation of the incidence and aetiology of cardiac and sudden cardiac death (SCD) is vital for healthcare policymakers to effectively allocate resources for preventative strategies. Purpose We aimed to report on the incidence and causes of cardiac and SCD among individuals under 35-years-old in England and Wales for 21 years (2001-2021), with a focus on identifying any temporal trends. Methods Annual mortality data from the Office for National Statistics (ONS) pertaining to cardiovascular (CV) and possible CV deaths in individuals under 35-years-old were analyzed using International Classification of Diseases-10 codes. Deaths were categorized into four-classes: A1- definitive cardiac deaths without identifiable structural heart disease (consistent with sudden arrhythmic death syndrome, SADS); A2- definitive cardiac deaths with identified structural heart disease; A3- definitive cardiac deaths with indeterminate cause; and B- potential cardiac deaths. Incidence rates were computed based on annual ONS census data. Additionally, insights were gleaned from the Cardiac Risk in the Young Centre for Cardiac Pathology (CRYCCP) nationwide registry. Results The mean annual number of definitive cardiac deaths (classes A1+A2+A3) was 414 (SD 27.4), resulting in an incidence of young cardiac and SCD of 1.68/100,000 individuals/year. Ischaemic heart disease (28.4%), cardiomyopathies (25.9%), and SADS (21.8%) were the most prevalent cardiac conditions. Cardiomyopathies and SADS related mortality peaked in the 10-to-19 age group, while ischaemic heart disease peaked in the 30-to-35 age group. A mean of 573 (SD 76.6) possible cardiac deaths (class B) occurred, these primarily included ill-defined causes (33.5%), epilepsy (32.4%), sudden infant death syndrome (24.2%), and drowning (7%). Definitive and possible cardiac deaths showed a male preponderance (male to female ratios: 2.3:1 and 1.6:1, respectively). A declining trend in cardiac mortality was observed with a 1.3% (95%CI: 1.0%-1.7%) incidence rate reduction/year (p<0.001). This was associated with a 2.5% annual incidence rate reduction for deaths attributed to structural heart disease (p<0.001), but an 8.5% annual incidence rate increase for deaths attributed to SADS (p<0.001). These trends corelated with increasing numbers of deaths referred to the CRYCCP where an expert cardiac pathologist diagnosed SADS in over 52% of cases. Conclusions Over 21 years in England and Wales, national datasets suggest the incidence of young cardiac and SCD is 1.68/100,000/year, with a small but appreciable declining mortality trend. The rise in SADS rates and contemporaneous decline in deaths attributed to structural heart disease may signify increased awareness and accessibility to expert cardiac pathologists. Ensuring accurate mortality coding is crucial for thoroughly assessing first-degree family members in cases of suspected inherited cardiac conditions.

3D modelling-based left atrium geometry analysis to predict atrial fibrillation in patients with cryptogenic stroke

Abstract Introduction Atrial fibrillation (AF) is a high prevalence condition associated with high morbidity and mortality. Its early diagnosis allows to initiate several prophylactic treatments that have proved to improve its prognosis. 3D modeling techniques allow to design accurate representations of cardiac cavities from diverse source images. Purpose We evaluated the association between new geometrical measurements obtained by 3D echocardiographic models of the left atrium (LA) and the presence of underlying paroxysmal AF in patients with cryptogenic stroke (CS). Methods 3D LA volumes from a sample of consecutive patients aged ≥60 years old and admitted to our Stroke Unit with the diagnosis of CS from April 2019 to November 2020 were analyzed. 15 days ECG monitoring was performed after discharge to detect underlying paroxysmal AF. All 3D echo volumes were analyzed by a 3D modeling open-source application. From this analysis several LA geometry parameters were obtained: sphericity, elongation, flatness, major axis length, minor axis length, maximum 2D diameter (max2Ddiam) and surface-volume ratio (S/V). Functional atrial parameters (3D left atrial ejection fraction, LAEF) were also determined. Results 36 patients were analyzed. Mean age was 78 ± 7 years old. 19% were diabetic, 58% had high blood pressure and 14% of patients had history of ischemic cardiomyopathy. Mean body-mass index was 26. These baseline characteristics were equally distributed between groups. Baseline proBNP was significantly higher in patients developing atrial fibrillation (949 vs 275 pg/mL; p= 0,014.). Maximum 2D diameter (max2Ddiam) and Surface-volume ratio (S/V) were the best predictors of AF (AUC of ROC curves: 0.69; 0.49 – 0.88 and 0.63; 0.42 – 0.84, respectively). An optimal cut-off point of 39 mm was selected for max2Ddiam and of 0.20 for S/V. These values were included in a multivariate model adjusted by baseline proBNP. A Max2Ddiam <39 mm and a S/V ≥0.20 were both significantly associated with the presence of paroxysmal AF (OR 6.96; p= 0.048 and OR 12.22; p = 0.043, respectively). Conclusions New geometrical atrial parameters can be obtained from echo 3D models and might be able to predict AF in patients with CS. Further analysis and larger samples are required to better understand these findings.TableFigure

FSH3D: 3D Representation via Fibonacci Spherical Harmonics

AbstractSpherical harmonics are a favorable technique for 3D representation, employing a frequency‐based approach through the spherical harmonic transform (SHT). Typically, SHT is performed using equiangular sampling grids. However, these grids are non‐uniform on spherical surfaces and exhibit local anisotropy, a common limitation in existing spherical harmonic decomposition methods. This paper proposes a 3D representation method using Fibonacci Spherical Harmonics (FSH3D). We introduce a spherical Fibonacci grid (SFG), which is more uniform than equiangular grids for SHT in the frequency domain. Our method employs analytical weights for SHT on SFG, effectively assigning sampling errors to spherical harmonic degrees higher than the recovered band‐limited function. This provides a novel solution for spherical harmonic transformation on non‐equiangular grids. The key advantages of our FSH3D method include: 1) With the same number of sampling points, SFG captures more features without bias compared to equiangular grids; 2) The root mean square error of 32‐degree spherical harmonic coefficients is reduced by approximately 34.6% for SFG compared to equiangular grids; and 3) FSH3D offers more stable frequency domain representations, especially for rotating functions. FSH3D enhances the stability of frequency domain representations under rotational transformations. Its application in 3D shape reconstruction and 3D shape classification results in more accurate and robust representations. Our code is publicly available at https://github.com/Miraclelzk/Fibonacci-Spherical-Harmonics.

ADDON FOR BLENDER3D. AUTOMATION OF THE OBJECT TEXTURING PROCESS

Abstract. Today, the use of 3D visualization technologies is one of the key directions in the field of information technologies. The 3D direction has become extremely popular in many fields, such as architecture, interior design, game industry, medicine, automotive and other fields. This method opens up new opportunities for perception and interpretation of information, adding it to a three-dimensional virtual space. The topic of the research work is the creation of a software module (addon) for the Blender3D program, which will provide the user with a library of ready-made materials, divided by categories. This addon has similar functionality to Substance Painter and Quixel Mixer, the main functions of which are to create and adjust materials and textures for imported ready-made 3D models. The addon has its own name "QuickShader" and will provide the user with 8 shaders and 35 PBR materials. Throughout the development of the project, the Waterfall life cycle model was used, stability and a clear structure were put first, which helped to efficiently work through each step of creating an addon for the Blender program. In the conclusion to the scientific work, it can also be noted that the development of a software addon for Blender3D, which includes a library of shader operators and PBR materials, will greatly facilitate the work of users when assigning textures to objects on the scene. A library of shader operators makes it easy to implement and customize shaders for light, glass, and some metals, giving you more control over the visual aspect of the scene. PBR materials provide realism due to the accurate representation of physical properties using Physically Based Rendering technologies. This addon gives users the ability to interact more effectively with procedural materials, providing a quick means to create realistic renders. This module automates the creation of materials by providing a list of prepared shaders and textures that can be applied to scene objects. The user will be provided with a set of ready-made shaders (glass, light material, metals) and PBR materials (wood, fabric, metals, and others), which can be applied with one button on the module panel.

Nonlocal Nernst-Planck-Poisson System for Modeling Electrochemical Corrosion in Biodegradable Magnesium Implants

AbstractThis paper provides a comprehensive derivation and application of the nonlocal Nernst-Planck-Poisson (NNPP) system for accurate modeling of electrochemical corrosion with a focus on the biodegradation of magnesium-based implant materials under physiological conditions. The NNPP system extends and generalizes the peridynamic bi-material corrosion model by considering the transport of multiple ionic species due to electromigration. As in the peridynamic corrosion model, the NNPP system naturally accounts for moving boundaries due to the electrochemical dissolution of solid metallic materials in a liquid electrolyte as part of the dissolution process. In addition, we use the concept of a diffusive corrosion layer, which serves as an interface for constitutive corrosion modeling and provides an accurate representation of the kinetics with respect to the corrosion system under consideration. Through the NNPP model, we propose a corrosion modeling approach that incorporates diffusion, electromigration and reaction conditions in a single nonlocal framework. The validity of the NNPP-based corrosion model is illustrated by numerical simulations, including a one-dimensional example of pencil electrode corrosion and a three-dimensional simulation of a Mg-10Gd alloy bone implant screw decomposing in simulated body fluid. The numerical simulations correctly reproduce the corrosion patterns in agreement with macroscopic experimental corrosion data. Using numerical models of corrosion based on the NNPP system, a nonlocal approach to corrosion analysis is proposed, which reduces the gap between experimental observations and computational predictions, particularly in the development of biodegradable implant materials.

Single-photon 3D imaging of room-scale scenes through scattering media

Light detection and ranging (LiDAR) utilizes eye-safe laser beams to perceive the world in three-dimensional (3D) detail, offering machines and computers with an accurate representation of their surroundings. This technology is widely employed in metrology, environmental monitoring, archaeology, and robotics. However, the presence of scattering media in the optical path, such as fog, dust, or translucent plates, will cause light scattering and occlude direct observation of the scene. To address scattering distortions, conventional methods require the prior knowledge of the scattering media or the target location, limiting their applicability outside the laboratory. Leveraging single-photon sensitivity and time-gated technology, single photon LiDAR emerges as a promising solution for active scattering imaging. In this study, we construct a single-photon LiDAR prototype and demonstrate its capability to perform 3D imaging of a room-scale (1.1 m × 1.1 m × 4 m) hidden scene behind a ground glass diffuser located approximately 50 meters away from the imaging system. Incorporating phase function to construct the forward model and considering the system-induced temporal broadening, our method is capable of producing reliable results behind various scattering layers. The results indicate potential applications such as remote non-invasive testing and detection in challenging scenarios.

Improved Empirical Backgrounds for JWST NIRISS Image/Wide-field Slitless Spectroscopy Data Reduction

The Near Infrared Imager and Slitless Spectrograph (NIRISS) on the James Webb Space Telescope (JWST) is a versatile instrument for collecting imaging and wide-field slitless spectroscopy (WFSS) data for surveys of galaxy clusters, emission-line galaxies, stellar populations, and more. Dispersed zodiacal light imprints distinct structures on space-based near-infrared imaging and WFSS observations, necessitating careful subtraction during JWST NIRISS data reduction. As of 2024 September 24 NIRISS WFSS calibration backgrounds introduce significant spatially dependent artifacts, up to 5% of the overall background level, which can severely affect data quality and following astronomical analysis. Notably, there are no existing backgrounds for NIRISS imaging data, which also show systematic artifacts, such as the “light saber” effect. In this work, we present improved empirical JWST NIRISS imaging and WFSS backgrounds derived from all available public data in the F115W, F150W, and F200W filters. We demonstrate that our empirical backgrounds provide a more accurate representation of the background structure in NIRISS imaging and WFSS data than existing reference files, mitigating the impact of spatially dependent artifacts. Our empirical backgrounds are publicly available and can be used to improve the quality of JWST NIRISS imaging and WFSS data reduction.

Climate change is intensifying rainfall erosivity and soil erosion in West Africa

Soil erosion is a critical environmental challenge with significant implications for agriculture, water quality, and ecosystem stability. Understanding its dynamics is essential for sustainable environmental management and societal welfare. Here, we analyze rainfall erosivity and erosion patterns across West Africa (WAF) during the historical (1982–2014), near future (2028–2060), and far future (2068–2100) periods under Shared Socioeconomic Pathways (SSPs 370 and 585). Using bias-corrected-downscaled (BCD) climate models validated against reference data, we ensure an accurate representation of rainfall—a key driver of erosivity (R-factor) and soil erosion. We compare Renard's approach and the Modified Fournier Index (MFI) to calculate the R-factor and note a strong correlation. However, Renard's method shows slightly lower accuracy in Sierra Leone, Guinea, and The Gambia, likely due to its inability to capture high-intensity, short-duration rainfall events. In contrast, the MFI, utilizing continuous rain gauge data, proves more reliable for these regions. We also attribute fluctuations in erosivity, such as those seen during the 2003 West Africa floods, to synoptic weather patterns influenced by multiple climate processes.Furthermore, our analysis reveals regions where future soil erosion could exceed 20 t/ha/yr due to climate change. Under the SSP 370 scenario, soil erosion in WAF is projected to rise by 14.84 % in the near future and 18.65 % in the far future, increasing further under SSP 585 to 19.86 % and 23.49 %, respectively. The most severe increases are expected in Benin and Nigeria, with Nigeria potentially facing a 66.41 % rise in erosion by the far future under SSP 585. These findings highlight the region's exposure to intensified climatic conditions and underscore the urgent need for targeted soil management and climate adaptation strategies to mitigate erosion's ecological and socioeconomic impacts.

Advancing equine genomics: the development of a high density Axiom_Ashwa SNP chip for Indian horses and ponies.

The unique horse and pony breeds of India are declining at an alarming rate. These horses have been integral to the Indian culture and customs for centuries and represent a valuable genetic resource. It is imperative to harness the potential of this equine genetic resource that urgently needs conservation. The study highlights the design and development of a high density SNP array, the Axiom_Ashwa to aid in the genetic analysis and conservation efforts for Indian horse and pony breeds. With 613,950 SNPs, this chip offers extensive genome coverage having an average inter-marker distance of 4kb. The Axiom_Ashwa has been validated on a larger set of diverse indigenous samples as well as Thoroughbreds, demonstrating a high call rate of 99.4% and robustness for genotyping indigenous breeds. Linkage disequilibrium (LD) analysis showed higher average LD in Indian breeds compared to exotic breeds, suggesting a limited effective population size and recent bottlenecks. Phylogenetic and population stratification analyses using PCA and DAPC clearly distinguished horses, ponies and Thoroughbreds, confirming the efficacy of the Axiom_Ashwa chip. These findings underscore the urgent need for conservation efforts for Indian horse breeds, which have experienced significant drop in population size. The Axiom_Ashwa SNP chip offers advantages such as cost-effectiveness and high throughput, providing a more accurate genetic representation of Indian horses.

Can satellite products monitor solar brightening in Europe?

Satellite products provide the best way to monitor the solar radiation reaching the Earth’s surface on a global scale. However, their capability to monitor solar radiation trends needs to be constantly evaluated. This depends on their temporal stability and the accurate representation of all processes driving solar radiation. This study evaluates these aspects by comparing and cross-comparing different solar radiation products (ERA5, CAMS-RAD 4.6, SARAH-3, CLARA-A3, CERES-EBAF 4.2) against in-situ measurements over Europe.All products show a moderate positive bias over Europe but strong differences in their root mean squared deviation (RMSD) related to their different cloud transmittance models. Geostationary-based products (SARAH-3, CAMS-RAD 4.6) provide the smallest RMSD closely followed by CLARA-A3, whereas ERA5 shows a large RMSD due to random errors in cloud transmittance.All products show an increase in surface solar radiation, or brightening, over the last 40 years over Europe, but the magnitude of the trends and their spatiotemporal variability differ between products. Despite finding temporal inhomogeneities in some products, the different trends are mostly due to different aerosol modeling approaches implemented by each product. Both SARAH-3 (+2.3 W/m2/decade, 2001–22) and CERES-EBAF 4.2 (+2.2 W/m2/decade, 2001–22) provide the most consistent trends compared to in-situ data, showing that after stabilizing in the late 2000s, brightening is particularly recovering in Western Europe. In-situ measurements show a reduction of aerosol optical depth from 2001 to 2022 that has been accentuated in the last 10 years, particularly in Western Europe. This would be consistent with the hypothesis that brightening recovery is driven by an aerosol reduction, though other analyses suggest that clouds also play a role in this recovery. More work is needed to understand the contribution of aerosols to solar radiation trends and the exact aerosol effects represented by each solar radiation product.

Branching Burreed (<i>Sparganium androcladum</i> (Engelmann) Morong; Typhaceae) rediscovered in Ontario, but conservation status unclear

We report three new records of Branching Burreed (Sparganium androcladum), which has not been seen in Ontario in several decades. This species is understudied and has been confused with other taxa, primarily American Burreed (Sparganium americanum). It is not known when it was last collected in the province, and its conservation status is unclear. Specimens identified as Branching Burreed are few and do not fully clarify the situation; of the 14 putative S. androcladum specimens we examined, five are too immature to verify confidently, and at least seven are misidentified. Previous specimen-based maps are probably not accurate representations of Branching Burreed’s provincial distribution, but it is likely more widespread than records indicate. We provide a description of our new records and notes on identification to provide a basis for additional study of this plant.

The influence of spider news on online information-seeking.

Fear of spiders is a widespread condition often disproportionate to the actual danger spiders pose to humans. Likely rooted in evolutionary history, fear of spiders might also have a cultural component. Recent studies have shown that a significant fraction of spider-related media reports are misleading and sensationalistic. Information-seeking behaviours serve as common coping mechanisms for our fears and anxieties, yet the link between spider-related news stories and such behaviors remains unexplored.We hypothesize that media reports foster concern about spiders, resulting in an increased awareness of spiders and health issues associated with them. We extracted 1486 reports in English from a public database providing a content-analysis of spider-related online traditional media reports published between 2010-2020. We examined whether the volume of spider-related queries in Google Trends, Wikipedia, and iNaturalist increased in the week following the publication of each news story.Sensationalistic news stories were associated with a small, significant increase in search volumes, compared to non-sensationalistic ones. The search volume for "brown recluse" (Loxosceles reclusa), which are potentially dangerous spiders, was higher after the publication date of news related to human-spider encounters. There was a significant positive relationship between the number of spider-related news stories published in a given month and the traffic on target spider-related Wikipedia pages, especially so for the page on brown recluse spiders.Our results suggest that traditional media have a detectable impact on the behaviour of the general public towards spiders, supporting the hypothesis that the fear of spiders is perpetuated by culture. Additionally, our findings indicate that information-seeking behaviour is a common response to learn about spiders and potentially fact-check spurious claims found in sensationalised news. By recognizing the role of media in shaping attitudes towards spiders and acknowledging the benefits of accurate representation, we can lay the foundation for a more informed and harmonious relationship between humans and spiders.

Punishment or reward? Environmental information disclosure in Chinese listed companies based on evolutionary game systems

AbstractIn February 2022, the Chinese government implemented a mandatory environmental information disclosure policy for publicly traded corporations. To assess the factors influencing environmental information disclosure, we developed a tripartite evolutionary game system model based on strategic interactions between the government, enterprises and the public. Afterwards, we conducted a simulation to examine the systemic interaction equilibrium among the parties involved. Additionally, we assessed critical factor changes in decision‐making for three stakeholders: initial strategy selection, related policy subsidies, regulatory penalties and public incentives. Incorporating Gaussian white noise into the evolutionary game model enhances the realism of simulations, allowing for a more accurate representation of how random disturbances affect decision‐making among the government, the public and enterprises. The study reveals that the active participation of the public in information disclosure activities has a certain degree of substitution effect on the government's choice to regulate high‐quality information disclosure by enterprises actively. The penalty mechanism is more effective than the subsidy mechanism. The public's decision‐making process is susceptible to the direct economic benefits that enterprises can gain from disclosing low‐quality environmental information.

A numerical study of double flow focusing micro-jets

Purpose Double flow-focusing nozzles (DFFNs) form a coaxial flow of primary liquid with micro-crystalline samples, surrounded by secondary liquid and focusing gas. This paper aims to develop an experimentally validated numerical model and assess the performance of micro-jets from a DFFN as a function of various operating parameters for the water–ethanol–helium system, revealing the jet's stability, diameter, length and velocity. Design/methodology/approach The physical model is formulated in the mixture-continuum formulation, which includes coupled mass, momentum and species transport equations. The model is numerically formulated within the finite volume method–volume of fluid approach and implemented in OpenFOAM to allow for a non-linear variation of the fluid's material properties as a function of the mixture concentration. The numerical results are compared with the experimental data. Findings A sensitivity study of jets with Reynolds numbers between 12 and 60, Weber numbers between 4 and 120 and capillary numbers between 0.2 and 2.0 was performed. It was observed that jet diameters and lengths get larger with increased primary and secondary fluid flow rates. Increasing gas flow rates produces thinner, shorter and faster jets. Previously considered pre-mixed and linear mixing models substantially differ from the accurate representation of the water–ethanol mixing dynamics in DFFNs. The authors demonstrated that Jouyban–Acree mixing model fits the experimental data much better. Originality/value The mixing of primary and secondary liquids in the jet produced by DFFN is numerically modelled for the first time. This study provides novel insights into mixing dynamics in such micro-jets, which can be used to improve the design of DFFNs.

Methodological approaches in 16S sequencing of female reproductive tract in fertility patients: a review.

The female genital tract microbiome has become a particular area of interest in improving assisted reproductive technology (ART) outcomes with the emergence of next-generation sequencing (NGS) technology. However, NGS assessment of microbiomes currently lacks uniformity and poses significant challenges for accurate and precise bacterial population representation. As multiple NGS platforms and assays have been developed in recent years for microbiome investigation-including the advent of long-read sequencing technologies-this work aimed to identify current trends and practices undertaken in female genital tract microbiome investigations. Areas like sample collection and transport, DNA extraction, 16S amplification vs. metagenomics, NGS library preparation, and bioinformatic analysis demonstrated a detrimental lack of uniformity. The lack of uniformity present is a significant limitation characterised by gap discrepancies in generation and interpretation of results. Minimal consistency was observed in primer design, DNA extraction techniques, sample transport, and bioinformatic analyses. With third-generation sequencing technology highlighted as a promising tool in microbiota-based research via full-length 16S rRNA sequencing, there is a desperate need for future studies to investigate and optimise methodological approaches of the genital tract microbiome to ensure better uniformity of methods and results interpretation to improve clinical impact.

A Systematic Review Toward a Comprehensive Framework for Measuring Non-chronological Age

As populations age globally, there is a need to refine the understanding of aging beyond simply chronological age. Therefore, this study used the PRISMA framework to synthesize literature on alternative aging metrics beyond chronological age. We analyzed articles from 6 databases (SCOPUS, PsychINFO, Web of Science, CINAHL, Engineering Village, and PubMed) and selected 18 articles that explored factors that lead to older adults’ individual differences. Findings indicated the necessity of a consistent terminology that better describes one’s cognitive and physical functioning, such as “non-chronological age.” Also, the review found that daily cognitive, physical, and social activities may result in different non-chronological ages. A comprehensive tool to measure non-chronological age and thereby provide a more accurate representation of aging that incorporates these critical factors is needed. The findings may contribute to the development of theories in non-chronological age.

Integrating different fidelity models for process optimization: A case of equilibrium and rate-based extractive distillation using ionic liquids

We integrate equilibrium and rate-based models to formulate a hybrid optimization scheme for designing an ionic liquid-based extractive distillation process for mixed-refrigerant separation. The equilibrium model assumes vapor–liquid equilibrium at each stage but challenges arise with low-volatility, high-viscosity solvents, which drive the system away from equilibrium. The rate-based approach considers mass and heat transfer rates, giving more accurate representation. We compare the two models for separating R-410A, an azeotropic mixture of R-32 and R-125, using [EMIM][SCN] ionic liquid as entrainer. Analyzing over 4300 simulations with various dimensionality reduction and topological analysis techniques, we find that predictions from the two models exhibit similar trends, but the overestimation in equilibrium-based purities sometimes leads to infeasible process designs. The proposed optimization algorithm thus combines the strengths of the two models to locate feasible and optimal designs.

An Operational Assessment of Team Cognition for Long-Distance Space Missions

Long-duration and long-distance space missions create a complicated context for collaboration. The combination of environmental and psychosocial factors will negatively impact individual and team cognition, potentially jeopardizing mission success. To provide a richer understanding of the issues surrounding team cognition for future space exploration missions, this paper describes an operational assessment to identify the key team cognition factors most likely to affect problem solving. Semi-structured interviews were conducted to elicit team cognitive and associated factors relevant to long-duration spaceflight missions. Ten NASA employees (e.g., astronauts, mission controllers) were interviewed to provide a more complete and accurate representation of individual and team cognitive demands. Our goal was to explicate critical cognitive processes associated with team effectiveness in space missions and provide guidance on technology and training collaborative problem solving for space missions.