Entire Pool Research Articles

Causal Inference Over a Subpopulation: The Effect of Malaria Vaccine in Women During Pregnancy.

Preventing malaria during pregnancy is of critical importance, yet there are no approved malaria vaccines for pregnant women due to lack of efficacy results within this population. Conducting a randomized trial in pregnant women throughout the entire duration of pregnancy is impractical. Instead, a randomized trial was conducted among women of childbearing potential (WOCBP), and some participants became pregnant during the 2-year study. We explore a statistical method for estimating vaccine effect within the target subpopulation-women who can naturally become pregnant, namely, women who can become pregnant under a placebo condition-within the causal inference framework. Two vaccine effect estimators are employed to effectively utilize baseline characteristics and account for the fact that certain baseline characteristics were only available from pregnant participants. The first estimator considers all participants but can only utilize baseline variables collected from the entire participant pool. In contrast, the second estimator, which includes only pregnant participants, utilizes all available baseline information. Both estimators are evaluated numerically through simulation studies and applied to the WOCBP trial to assess vaccine effect against pregnancy malaria.

The NF-κB Factor Relish maintains blood progenitor homeostasis in the developing Drosophila lymph gland.

Post-larval hematopoiesis in Drosophila largely depends upon the stockpile of progenitors present in the blood-forming organ/lymph gland of the larvae. During larval stages, the lymph gland progenitors gradually accumulate reactive oxygen species (ROS), which is essential to prime them for differentiation. Studies have shown that ROS triggers the activation of JNK (c-Jun Kinase), which upregulates fatty acid oxidation (FAO) to facilitate progenitor differentiation. Intriguingly, despite having ROS, the entire progenitor pool does not differentiate simultaneously in the late larval stages. Using expression analyses, genetic manipulation and pharmacological approaches, we found that the Drosophila NF-κB transcription factor Relish (Rel) shields the progenitor pool from the metabolic pathway that inducts them into the differentiation program by curtailing the activation of JNK. Although ROS serves as the metabolic signal for progenitor differentiation, the input from ROS is monitored by the developmental signal TAK1, which is regulated by Relish. This developmental circuit ensures that the stockpile of ROS-primed progenitors is not exhausted entirely. Our study sheds light on how, during development, integrating NF-κB-like factors with metabolic pathways seem crucial to regulating cell fate transition during development.

Effect of Chromosomal Localization of NGS-Based Markers on Their Applicability for Analyzing Genetic Variation and Population Structure of Hexaploid Triticale.

This study aimed to determine whether using DNA-based markers assigned to individual chromosomes would detect the genetic structures of 446 winter triticale forms originating from two breeding companies more effectively than using the entire pool of markers. After filtering for quality control parameters, 6380 codominant single nucleotide polymorphisms (SNPs) markers and 17,490 dominant diversity array technology (silicoDArT) markers were considered for analysis. The mean polymorphic information content (PIC) values varied depending on the chromosomes and ranged from 0.30 (2R) to 0.43 (7A) for the SNPs and from 0.28 (2A) to 0.35 (6R) for the silicoDArTs. The highest correlation of genetic distance (GD) matrices based on SNP markers was observed among the 5B-5R (0.642), 5B-7B (0.626), and 5A-5R (0.605) chromosomes. When silicoDArTs were used for the analysis, the strongest correlations were found between 5B-5R (0.732) and 2B-5B (0.718). A Bayesian analysis showed that SNPs (total marker pool) allowed for the identification of a more complex structure (K = 4, ΔK = 2460.2) than the analysis based on silicoDArTs (K = 2, ΔK = 128). Triticale lines formed into groups, ranging from two (most of the chromosomes) to four (7A) groups depending on the analyzed chromosome when SNP markers were used for analysis. Linkage disequilibrium (LD) varied among individual chromosomes, ranging from 0.031 for 1A to 0.228 for 7R.

The Spectrum of Renal "TFEopathies": Flipping the mTOR Switch in Renal Tumorigenesis.

The mammalian target of Rapamycin complex 1 (mTORC1) is a serine/threonine kinase that couples nutrient and growth factor signaling to the cellular control of metabolism and plays a fundamental role in aberrant proliferation in cancer. mTORC1 has previously been considered an "on/off" switch, capable of phosphorylating the entire pool of its substrates when activated. However, recent studies have indicated that mTORC1 may be active toward its canonical substrates, eukaryotic translation initiation factor 4E-binding protein 1 (4EBP1) and S6 kinase (S6K), involved in mRNA translation and protein synthesis, and inactive toward TFEB and TFE3, transcription factors involved in the regulation of lysosome biogenesis, in several pathological contexts. Among these conditions are Birt-Hogg-Dubé syndrome (BHD) and, recently, tuberous sclerosis complex (TSC). Furthermore, increased TFEB and TFE3 nuclear localization in these syndromes, and in translocation renal cell carcinomas (tRCC), drives mTORC1 activity toward the canonical substrates, through the transcriptional activation of the Rag GTPases, thereby positioning TFEB and TFE3 upstream of mTORC1 activity toward 4EBP1 and S6K. The expanding importance of TFEB and TFE3 in the pathogenesis of these renal diseases warrants a novel clinical grouping that we term "TFEopathies." Currently, there are no therapeutic options directly targeting TFEB and TFE3, which represents a challenging and critically required avenue for cancer research.

Hazard Identification and Risk Assessment for Sustainable Shipyard Floating Dock Operations: An Integrated Spherical Fuzzy Analytical Hierarchy Process and Fuzzy CoCoSo Approach

Background: This study investigated the process of selecting sustainable safety protocols for floating dock operations in shipyards by identifying potential workplace risks in emergency situations. Thirteen occupational hazards for shipyard floating dock operations were identified through a literature review and expert discussions. Methods: We incorporated four risk elements (consequence: C, frequency: F, probability: P, and number of people at risk: NP) from the Fine–Kinney and Hazard Rating Number System (HRNS) approaches as the risk assessment criteria. We obtained the importance weights of the risk assessment criteria via the Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) and extended the Combined Compromise Solution (CoCoSo) method within the fuzzy framework to prioritize occupational hazards. This study demonstrated the practicality and efficiency of the proposed emergency risk assessment model for shipyard floating dock operations through a case example of occupational risk assessment. Results: The analysis results show that H4 is the occupational hazard with the highest priority, with a score of 3.553. H4 represents the hazard associated with insufficient access to the entire pool area. The second and third most important hazards are the inability of cranes to move freely in and out of the berthing dock and the inability to dispatch emergency teams. These hazards, denoted H1 and H12, follow closely behind with scores of 3.391 and 3.344, respectively. H10 is deemed the least concerning hazard, with a score of 1.802. Conclusions: Professionals can handle complex and uncertain risk assessment data more flexibly using the proposed system, which excels in accurately organizing occupational hazards.

Numerical evaluation of interwire angle influence on molten pool fluid dynamics and weld defects in tandem NG-GMAW of 5083 aluminum alloy

The impact of interwire angle on the fluid dynamics and weld defects in tandem NG-GMAW of 5083 AlMg alloy was investigated through experimental and simulation methods. The rotating coordinate system was employed to model the inclined arc and arc interaction, while a pulsed Gaussian distribution arc model was adopted to consider factors such as arc heat, arc pressure and drag force. Experimental results demonstrate that different interwire angles lead to different weld formation and varying levels of porosity and pore distribution. A sound weld bead with no formation defect and low porosity was achieved when the interwire angle was set at 10°. Simulation results illustrate the relationship between weld formation, bubble escape and molten pool fluid dynamics under diverse interwire angles. As the interwire angle increases, the weld surface becomes concave. At the interwire angle of 0°, the weld bead surface appears leveled and porosity tends to occur near the sidewalls due to roundabout flows in that region. At an interwire angle of 14°, roundabout flows converge at the central longitudinal section, resulting in significant porosity in this area. However, when the interwire angle is set at 10°, backward flows driven by two arcs suppresses roundabout flow throughout the entire molten pool, leading to a lower percentage of porosity area.

Computational identification of ultra-conserved elements in the human genome: a hypothesis on homologous DNA pairing.

Thousands of prolonged sequences of human ultra-conserved non-coding elements (UCNEs) share only one common feature: peculiarities in the unique composition of their dinucleotides. Here we investigate whether the numerous weak signals emanating from these dinucleotide arrangements can be used for computational identification of UCNEs within the human genome. For this purpose, we analyzed 4272 UCNE sequences, encompassing 1 393 448 nucleotides, alongside equally sized control samples of randomly selected human genomic sequences. Our research identified nine different features of dinucleotide arrangements that enable differentiation of UCNEs from the rest of the genome. We employed these nine features, implementing three Machine Learning techniques - Support Vector Machine, Random Forest, and Artificial Neural Networks - to classify UCNEs, achieving an accuracy rate of 82-84%, with specific conditions allowing for over 90% accuracy. Notably, the strongest feature for UCNE identification was the frequency ratio between GpC dinucleotides and the sum of GpG and CpC dinucleotides. Additionally, we investigated the entire pool of 31 046 SNPs located within UCNEs for their representation in the ClinVar database, which catalogs human SNPs with known phenotypic effects. The presence of UCNE-associated SNPs in ClinVar aligns with the expectation of a random distribution, emphasizing the enigmatic nature of UCNE phenotypic manifestation.

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. The highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

Enhancing deadwood reporting for forest ecosystems: Bridge equations to convert deadwood measured at any diameter threshold to reference diameters

National as well as international requirements have led to an increased need to quantify deadwood stocks in forest ecosystems given their important role not only in terms of carbon storage and regulation of the carbon cycle but also as biodiversity refugia. However, differences in definitions and field monitoring as well as gaps in existing data on deadwood mean that comparisons among countries and retrospective analyses are difficult. In this research, we propose two potential approaches to solve the most common gaps in forest deadwood monitoring. First, we develop bridging functions capable of converting deadwood measurements with a specific reference diameter to 7.5 cm (minimum diameter value in Spain) and 10.0 cm (the most common minimum value for international statistics) diameters for the main forest types while also addressing the effect of raising the minimum measurable size on the quantification of deadwood. Furthermore, we aim to calculate the ratios between the amount of standing deadwood, the most common indicator monitored in National Forest Inventories, and the entire deadwood pool as a proxy for estimating complete deadwood stocks when data are not available. For this objective, we use information obtained from the Spanish National Forest Inventory, linear models and 10-fold cross-validation. We estimate the percentage of deadwood omitted when the minimum deadwood size is increased for the main eight forest types in Spain as well as for the entire country, using two different approaches. The ratio between the amount of standing deadwood and the entire deadwood pool ranged between 0.14 and 0.45 depending on the forest type. The lowest values of this ratio were found in Open woodlands and the largest in Mediterranean conifers. The validation statistics (R2 ranging from 0.82 in Evergreen broadleaves to 0.97 in Macaronesian broadleaves) indicate that the bridging functions we propose are robust and accurate. However, the ratios between the amount of standing deadwood and the entire deadwood pool performed poorer (R2 ranging from 0.26 in Macaronesian conifers to 0.65 in Macaronesian broadleaves) and led to an overestimation of the total stocks. Our results are of value not only for the purposes of comparison and harmonization but also for the implementation of new forest monitoring systems.

NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing

BackgroundCurrent approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation.ResultsWe cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed.ConclusionsOur work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.

Delineating the evolutionary pathway to multidrug-resistant outbreaks of a Mycobacterium tuberculosis L4.1.2.1/Haarlem sublineage

ObjectivesWe sought to capture the evolutionary itinerary of the Mycobacterium tuberculosis L4.1.2.1/Haarlem sublineage in northern Tunisia, where it caused a major multidrug-resistant (MDR) tuberculosis outbreak in a context strictly negative for HIV infection. MethodsWe combined whole genome sequencing and Bayesian approaches using a representative collection of drug-susceptible and drug-resistant L4.1.2.1/Haarlem clinical strains (n = 121) recovered from the outbreak region over 16 years. ResultsIn the absence of drug resistance, the L4.1.2.1/Haarlem sublineage showed a propensity for rapid transmission as witnessed by the high clustering (44.6%) and recent transmission rates (25%), as well as the reduced mean distance between genome pairs. The entire pool of L4.1.2.1/Haarlem MDR strains was found to be linked to either the aforementioned major outbreak (68 individuals, 2001-2016) or to a minor, newly uncovered outbreak (six cases, 2001-2011). Strikingly, the two outbreaks descended independently from a common ancestor that can be dated back to 1886. ConclusionsOur data point to the intrinsic propensity for rapid transmission of the M. tuberculosis L4.1.2.1/Haarlem sublineage in northern Tunisia, linking the overall MDR tuberculosis epidemic to a single ancestor. These findings bring out the important role of the bacillus’ genetic background in the emergence of successful MDR M. tuberculosis clones.

Retrospective Analysis of Tuberculosis Epidemiology in Okara, Pakistan

Tuberculosis, commonly called T.B., is a persistent bacterial illness attributed to Mycobacterium tuberculosis. Tuberculosis (T.B.) is a prevalent infectious disease that results in millions of deaths each year, particularly in low-income countries. A retrospective study was conducted between December 1, 2022, and April 30, 2023. Sputum smear microscopy was performed on all individuals suspected of having the T.B. condition. Out of the entire pool of 711 cases under suspicion, 227 cases, which accounts for 31.93% of the total, were confirmed positive for Tuberculosis. The male population is more susceptible to T.B. infection than their female counterparts, with a distribution of 59.47% and 40.53%, respectively. The age group of 30-44 years exhibited the highest rate of pulmonary tuberculosis cases at 24.67%, whereas the age group of 60-74 years recorded the highest percentage of cases at 25.56%. Based on our research, it was determined that the incidence of Tuberculosis exhibited a statistically significant increase within the overall populace of Okara District. The objective of the present study was to examine the Prevalence of Tuberculosis (T.B.) infection and raise awareness among the population regarding T.B. infection in the Okara district of Punjab, Pakistan. Effective disease control and elimination require appropriate management, diagnosis, treatment, and public consciousness.

Regioisomerism vs Conformation: Impact of Molecular Design on the Emission Pathway in Organic Light-Emitting Device Emitters.

Despite the design and proposal of several new structural motifs as thermally activated delayed fluorescent (TADF) emitters for organic light-emitting device (OLED) applications, the nature of their interaction with the host matrix in the emissive layer of the device and their influence on observed photophysical outputs remain unclear. To address this issue, we present, for the first time, the use of up to four regioisomers bearing a donor-acceptor-donor electronic structure based on the desymmetrized naphthalene benzimidazole scaffold, equipped with various electron-donating units and possessing distinguished conformational lability. Quantum chemical calculations allow us to identify the most favorable conformations adopted by the electron-rich groups across the entire pool of regioisomers. These conformations were then compared with conformational changes caused by the interaction of the emitter with the Zeonex and 4,4'-bis(N-carbazolyl)-1,1'-biphenyl (CBP) matrices, and the correlation with observed photophysics was monitored by UV-vis absorption and steady-state photoluminescence spectra, combined with time-resolved spectroscopic techniques. Importantly, a CBP matrix was found to have a significant impact on the conformational change of regioisomers, leading to unique TADF emission mechanisms that encompass dual emission and inversion of the singlet-triplet excited-state energies and result in the enhancement of TADF efficiency. As a proof of concept, regioisomers with optimal donor positions were utilized to fabricate an OLED, revealing, with the best-performing dye, an external quantum emission of 11.6%, accompanied by remarkable luminance (28,000 cd/m2). These observations lay the groundwork for a better understanding of the role of the host matrix. In the long term, this new knowledge can lead to predicting the influence of the host matrix and adopting the structure of the emitter in a way that allows the development of highly efficient and efficient OLEDs.

Unsupervised Fusion Feature Matching for Data Bias in Uncertainty Active Learning.

Active learning (AL) aims to sample the most valuable data for model improvement from the unlabeled pool. Traditional works, especially uncertainty-based methods, are prone to suffer from a data bias issue, which means that selected data cannot cover the entire unlabeled pool well. Although there have been lots of literature works focusing on this issue recently, they mainly benefit from the huge additional training costs and the artificially designed complex loss. The latter causes these methods to be redesigned when facing new models or tasks, which is very time-consuming and laborious. This article proposes a feature-matching-based uncertainty that resamples selected uncertainty data by feature matching, thus removing similar data to alleviate the data bias issue. To ensure that our proposed method does not introduce a lot of additional costs, we specially design a unsupervised fusion feature matching (UFFM), which does not require any training in our novel AL framework. Besides, we also redesign several classic uncertainty methods to be applied to more complex visual tasks. We conduct rigorous experiments on lots of standard benchmark datasets to validate our work. The experimental results show that our UFFM is better than the similar unsupervised feature matching technologies, and our proposed uncertainty calculation method outperforms random sampling, classic uncertainty approaches, and recent state-of-the-art (SOTA) uncertainty approaches.

Prevalence of Moderate to Severe Depressive Symptoms among Adults in the UAE: A Cross-sectional Study

Objective:: The objectives of the study were to assess the prevalence of moderate to severe depressive symptoms among adults aged 18 years or older, assess the relationship between the severity of depression and selected socio-demographic, psycho-social, lifestyle, and health-related factors, and identify the determinants of moderate-to-severe depressive symptoms in the adult population of 18 years and older in the United Arab Emirates (UAE). Methods:: This was a cross-sectional study conducted in the United Arab Emirates that targeted residents above 18 years of age. A research questionnaire was developed and approved by three specialists in the field, along with the Patient Health Questionnaire-9 (PHQ9). The Chi-square test was used to assess the association between variables, and multiple logistic regression analysis was used to find the predictive risk factors for moderate to severe depressive symptoms. Results:: The study encompassed a group of 562 participants, achieving a response rate of 97.33%. Initially, a Google Form was distributed electronically to the entire participant pool; however, 15 individuals declined to participate, resulting in a final sample size of 547 (n). Amongst the variables that showed significant prevalence of moderate to severe depressive symptoms were age (P <0.001), sex (P <0.001), marital status (P <0.001), occupation classification (P <0.001), religiosity (P <0.001), education level (P <0.001), job stress (P <0.001), domicile and residence (P <0.001), responsibility towards family (P <0.001), post-traumatic stress disorder (PTSD) (P <0.001), consumption of alcohol (P <0.001), coronavirus disease pandemic (P <0.001), employment status (P = 0.002), family size (P = 0.001), and smoking (P = 0.004). Amongst the variables, the subgroups that showed significant predictive factors of moderate to severe depressive symptoms were the ages between 18 and 25 years old (P = 0.01), the female gender (P <0.001), and low levels of religiosity (P <0.001). Conclusion:: The prevalence of moderate-to-severe depressive symptoms was 48% (n=260). In our study on the prevalence of depression, we have investigated several predictive factors, including age, gender, religiosity, and a history of prior depression diagnosis. While numerous factors contribute to depression, additional research is imperative to identify and validate additional predictive factors.

Cost Analysis of High-Signal Approach in Otolaryngology-Head and Neck Surgery Residency.

The objective of this study is to analyze a high-signal approach for otolaryngology-head and neck surgery (OHNS) residency applicants and calculate cost savings for programs and applicants. Data from both the 2022-2024 Electronic Residency Application Service (ERAS) and a data model were used to demonstrate cost savings with a high-signal approach. Modeled data assumed that the number of applications per applicant would be equal to the number of signals allowed. Predicted and real-world cost savings across the five other specialties participating in a high-signal approach were calculated. ERAS data cost savings for the entire OHNS applicant pool amounted to $365,950. In the modeled data, cost savings amounted to $825,921. When extrapolated to include all five high-signal specialties, total cost savings amounted to $2,570,464 (ERAS data) and $6,359,478 (modeled data). Otolaryngology programs were predicted to experience significant time savings, resulting in cost savings of $437,883 and $1,113,342 for ERAS data and modeled data, respectively. The study highlights the advantages of a high-signal approach, including financial advantages or increased time for programs to engage in holistic review and diversify the pool of interview candidates. Cost savings in this study were shown to be significant when extrapolated across all specialties using a high-signal approach. Further research is needed to optimize the signaling system and confirm the favorable interview distribution and equity data from the low-signal OHNS experience with a high-signal approach. N/A Laryngoscope, 134:2684-2688, 2024.

Personalized Alpha-Motoneuron Pool Models Driven by Neural Data Encode the Mechanisms Controlling Rate of Force Development.

The central nervous system employs distinct motor control strategies depending on task demands. Accordingly, the activity of alpha-motoneuron (MN) pools innervating skeletal muscle fibers is modulated based on muscle force and rate of force development (RFD). In human subjects, biophysical MN models enable inferring in vivo the neural processes (e.g., synaptic input, activity of the entire MN pool, etc.) underlying this modulation, which are otherwise challenging to measure experimentally. Due to unique neurophysiological characteristics of individuals, personalizing these models is essential to study motor control in humans. Therefore, this work studied the mechanisms involved in the modulation of RFD using person-specific MN pool models driven by in vivo common synaptic input estimates (i.e., derived from surface high-density electromyography). Specifically, we assessed how in vivo MN activity changed across RFD and muscle force. This included modulation of recruitment and rate coding in the complete MN pool, as well as model-based estimates of excitatory synaptic gains ( ∆ IF). We found RFD-specific changes in MN activity associated to changes in ∆ IF. Moreover, we showed that MN pool models driven by RFD-specific ∆ IFs reproduced in vivo MN firing features and associated force profiles at different RFDs. Altogether, this work represents a step towards modelling the mechanisms of force generation in humans and creating person-specific models of the spinal circuitry. This will open a window for studying in vivo human neuromechanics and motor restoring interventions.

Phosphorus release from rewetted agricultural peat soils varies strongly in dependence of the phosphorus resorption capacity

Rewetting of drained agricultural lowland peat soils is followed by the risk of increased phosphorus (P) release to downstream systems, thereby challenging their restoration as nutrient sinks for years to decades. While extensive knowledge is available on P mobilization under anaerobic conditions caused by reductive (Fe(III))-oxide dissolution, the net P release to the aqueous phase (PSol) is only poorly understood due to unknown significance of P re-sorption to aluminum (Al) oxides and non-reduced Fe(III)-oxides. We therefore hypothesize that PSol is a function of the sorption capacity and P saturation of Al-oxides and non-reduced Fe(III)-oxides. A comprehensive set of 47 Danish topsoil and subsoil samples from agricultural lowlands were incubated for up to 148 days in the laboratory under anoxic and water-saturated conditions at room temperature. Oxalate-extractable Fe, Al and P (Feox, Alox and Pox) varied by three orders of magnitude, with Feox ranging between 1.8 and 1590 mmol kg−1; Alox and Pox also showed high variation with maximum contents of 883 and 153 mmol kg−1, respectively. Bicarbonate-dithionite generally extracted 2 times less Fe, Al and P (FeBD, AlBD, PBD) than oxalate. Oxalate extraction data were used to calculate the degree of P saturation (DPS) and P sorption capacity (PSC). The extent of Fe(III)-oxide reduction measured as 0.1 M HCl extractable Fe(II)HCl was well described by first-order kinetics with rate constants ranging between 0.01 and 0.3 d-1.The estimated maximum Fe(II)HCl produced (Fe(II)max) ranged between 3 and 1490 mmol Fe(II) kg−1, with Feox corresponding to Fe(II)max values very closely. For most soils almost full dissolution of the entire Feox pool was achieved within 21 days of incubation. PSol concentrations, measured in the soil solution extract, ranged between 0.05 and 5.05 mg L-1, increasing with incubation time for most of the soils. While PSol was not correlated with FeBD:PBD and Feox:Pox, DPS, total P (PT) or total Fe (FeT):PT ratio, the investigations revealed a strong reciprocal relationship between the residual sorption capacity (RSC) of the soils, i.e., PSC subtracted the Fe(III)-oxides reduced, and the PSol/Pox ratio. Moreover, the results showed low or lack of P release to the aqueous phase, even for the soil samples where all Feox pools were reduced, if the RSC of the soil was above 100 mmol kg−1. This highlights the importance of redox-stable Al-oxides to capture mobilized P from rewetted lowland peat soils.

A matter of space and perspective – Cyclists’, car drivers’, and pedestrians’ assumptions about subjective safety in shared traffic situations

Subjective safety has been considered a key factor for a successful promotion of cycling. As of yet, subjective safety and the factors affecting it have been studied almost exclusively from the cyclists’ perspective. However, subjective safety is largely determined by the interaction of cyclists with other road users. We thus argue that it is crucial to assess the subjective safety different road user groups associate with shared road situations, because street designs that increase the subjective safety of one group may have negative impacts on the subjective safety of another group. For this purpose, we conducted a large-scale, web-based survey presenting computer-generated 2D images showing various traffic situations. The entire pool of images included 1,900 variations and combinations of road designs. About 21,500 individual participants provided about 460,000 estimates with regard to the safety they associated with travelling at the shown location from the perspective of cyclists, car drivers, or pedestrians. Our analysis with generalized mixed models focused on three base scenarios and the comparison of the different perspectives: Side streets were perceived as unsafe by both cyclists and car drivers. A prominent designation as a cycling boulevard had highly positive effects, especially for cyclists. On main streets, cyclists and car drivers rated mixed traffic without cycling infrastructure as very unsafe, and situations with cyclists travelling on protected bike lanes as very safe. Whereas car drivers rated all types of cycling lanes as safe, this did not generally apply to cyclists. In particular, narrow cycling lanes adjacent to parked cars felt unsafe for cyclists. We hypothesize that this discrepancy has a self-reinforcing mechanism: Research on risk-taking suggests that the low risk perception of car drivers leads to more risky behavior (e.g. overtaking cyclists with higher speed and less lateral clearance), which in turn decreases the subjective safety of cyclists. We found an inverted pattern for sidewalks, where cyclists felt mostly safe, and the more vulnerable pedestrians did not (especially if there was no clear indication of lanes for both groups). Taken together, our research sheds light on an as-of-yet rather under-researched issue: the perception of a traffic situation may vary significantly depending on the perspective and transportation mode of a road user. More specifically, our findings suggest that the subjective safety of vulnerable road users in a traffic situation can be negatively affected by the perception of this situation by the less vulnerable road users. We present recommendations about road designs that feel safe for all road user groups.

Multi-physics multi-scale simulation of microstructure evolution in entire welds of 2219-T6 aluminum alloy: An MPF-LBM study

The microstructure of fusion welds significantly affects its mechanical properties. Existing studies on the dynamic evolution of welding molten pools have exposed great limitations in considering the flow field and the solid motion of free dendrites. In this paper, a multi-physics multi-scale coupling simulation of thermal-mass-flow was conducted to study the solidification behavior during the welding of 2219-T6 aluminum alloy. The developed multi-phase field lattice Boltzmann model realized the direct full coupling of phase, temperature, solute, solid motion, and flow fields. It is also combined with a continuous nucleation model to simulate heterogeneous nucleation and columnar-to-equiaxed transition (CET), and a transient growth-condition model to simulate the movement and solidification of the entire molten pool. The model and simulation results were verified by welding experiments, electron back-scattered diffraction, and scanning electron microscopy tests. Good agreements are achieved in terms of grain structure, dendrite morphology, and grain size. The undercooling field, fluid flow, solid motion, dendrite morphology, solute distribution, and quantitative parameters during the whole solidification process were analyzed in detail to reveal the true evolution of thousands of dendrites in fusion welds. The results show that solute convection caused by fluid flow significantly affects the dendrite morphology. The solid motion of equiaxed dendrites squeezes the solute enrichment layer and forms a solute hysteresis transport effect. A band of equiaxed dendrites gathers in front of the columnar dendrites and blocks their growth, forming a mechanical blockade mechanism of the CET process. The equiaxed dendrites dominated the subsequent solidification after CET is complete, and the final microstructure consists of brief-growth columnar dendrites and dense equiaxed dendrites. The top tangential flow causes a band of equiaxed dendrites with large gaps in the upper weld, which was presumed to be the source of surface cracks in welds with high residual stress.