State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforces a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify native protein termini or those arising from endogenous proteolytic activity (also referred to ‘neo-N-termini’ analysis or ‘N-terminomics’. Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce Fragterminomics, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, (3) visualization of neo-N-termini location, and (4) mapping neo-N-termini to known protein processing features. We illustrate the use of Fragterminomics by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The Fragterminomics approach and example data are available as an R package at https://github.com/MiguelCos/Fragterminomics.

Background: Catheter ablation (CA) and left atrial appendage occlusion (LAAO) are commonly performed minimally invasive procedures for atrial fibrillation. Takotsubo syndrome (TTS), typically induced by severe emotional or physical stressors, is seldom observed as a consequence of these minor surgeries. Methods and Results: We reported a rare case of TTS resulting in significant ST-segment alterations and ventricular tachycardia following a one-stage intervention combining CA and LAAO. Conclusion: This case serves as a reminder that physicians should recognize the risk of iatrogenic TTS in intervention procedures. Timely diagnosis and appropriate supportive therapy can mitigate adverse outcomes and ensure a positive patient prognosis.

Climate warming has triggered shifts in plant distributions, resulting in changes within communities, characterized by an increase in warm-demanding species and a decrease in cold-adapted species - referred to as thermophilization. Researchers conventionally rely on co-occurrence data from vegetation assemblages to examine these community dynamics. Despite the increasing availability of presence-only data in recent decades, their potential has largely remained unexplored due to concerns about their reliability. Our study aimed to determine whether climate-induced changes in community dynamics, as inferred from presence-only data from the Global Biodiversity Information Facility (GBIF), corresponded with those derived from co-occurrence plot data in Norway. To assess the differences between these datasets, we quantified a Community Temperature Index (CTI) from the co-occurrence data set and compared this with CTI obtained from presence-only data. We also examined the temporal trend in CTI (i.e., thermophilization) in both datasets. To do this, we first established a species-temperature relationship based on data before climate warming. In a preliminary analysis, we assessed the performance of this relationship using three datasets: 1) Norwegian co-occurrence data, 2) presence-only data from a broader European region organized into pseudo-plots (potentially capturing more species niches), and 3) a combined dataset merging 1) and 2). The transfer function including both datasets performed best. Subsequently, we compared the CTI for the co-occurrence plots paired up spatially and temporally with presence-only pseudo-plots. The results demonstrated that presence-only data can effectively evaluate species assemblage responses to climate warming, with consistent CTI and thermophilization values in comparison to co-occurrence data. Employing presence-only data for evaluating community responses opens up better spatial and temporal resolution and much more detailed analyses of such responses, our results therefore outline how a large amount of presence-only data can be used to enhance our understanding of community dynamics in a warmer world.

ORCiD: [https://orcid.org/0000-0003-0655-2343] Keywords: Root imaging, root-system architecture (RSA), soybean, 2D-phenotyping & 3D-phenotyping Roots are a major part of plant systems and are essential to obtaining water and nutrients. Despite their importance, roots have not been extensively examined as compared to their aboveground counterparts, due primarily to the difficulties of access and lack of standard methods to quantify root morphology. While there have been several experiments performed under controlled environments, comparatively fewer studies have examined root architectures under field conditions. Here, we apply two imaging techniques to characterize variability in Root System Architecture (RSA) in diverse soybean genotypes under field settings with two contrasting soil conditions. Thus, our objectives are to (1) quantify root system architecture using 2D image techniques (e.g., Winrhizo and Image J) and (2) evaluate a contrasting subset of these samples (n = 30) using a novel 3D phenotyping approach. The research seeks to meet the need for enhanced methods in root system architecture analysis across diverse field conditions potentially leading to more resilient, high-yielding soybean varieties.

A document by Anouk Beniest. Click on the document to view its contents.

Despite growing evidence that associations between autonomic nervous system (ANS) responsivity and psychopathic traits vary across stress tasks only a single study has systematically assessed cross-task differences in associations. To advance this limited literature the current study randomized subjects into either a noise blast (countdown) task or a social stressor speech task. Analyses estimated associations between ANS (heart rate, skin conductance) and measures of psychopathic traits (Self-Report Psychopathy Scale-III, Inventory of Callous-Unemotional traits, Levenson Self-Report Psychopathy Scale, Sensation Seeking Scale – Form V). Results indicated that associations between ANS activity and psychopathic traits varied across stress task, ANS measure, and psychopathy measure. Associations that were consistent across analyses included a negative association between heart rate reactivity to the countdown task and SRP total scores, and a negative association between skin conductance reactivity to the social stressor speech task the interpersonal manipulation scale in the SRP. In addition, there was a negative association between resting skin conductance and SSS-V total scores.

The residual stress resulting from welding was commonly disregarded in traditional fatigue life evaluation. This reduced the accuracy of life prediction and increased the challenges associated with optimizing the fatigue life of the shear wave seismic vibrator baseplate. This work introduced a modified fatigue life prediction model that considered the interaction between welding residual stress and load stress, based on the S-N curve. The study revealed the impact of welding process parameters on residual stress. A mathematical correlation was established between welding residual stress, welding speed and interlayer temperature. We developed a fatigue life optimization model by leveraging the local sensitivity method. The NSGA-II algorithm was ultimately employed to obtain the Pareto solution set. We determined the optimal fatigue life parameters using a combination of entropy weighting and TOPSIS. The optimized results showed a remarkable 17.72% improvement of fatigue life, the optimization method was proved to be accurate and efficient.

The steam reforming of hydrocarbon fuels for the production of synthesis gas or hydrogen is a well-established technology. A common process is steam-reforming, where a suitable reforming catalyst facilitates the reaction between the hydrocarbon feed and steam to generate carbon monoxide and hydrogen. This study relates to a thermochemical process for producing hydrogen by the catalytic endothermic reaction of methanol with steam in a thermally integrated microchannel reforming reactor. Computational fluid dynamics simulations are conducted to better understand the consumption, generation, and exchange of thermal energy between endothermic and exothermic processes in the reactor. The effects of wall heat conduction properties and channel dimensions on heat transfer characteristics and reactor performance are investigated. Thermodynamic analysis is performed based on specific enthalpy to better understand the evolution of thermal energy in the reactor. Design recommendations are made to improve thermal performance for the reactor. The results indicate that the peak reaction heat flux increases with the channel dimensions while maintaining the flow rates. Reaction heat flux profiles are considerably affected by channel dimensions. The thermal conductivity of the channel walls is fundamentally important. Materials with high thermal conductivity are preferred for the channel walls. Thermally conductive ceramics and metals are well-suited. Wall materials with poor heat conduction properties degrade the reactor performance. The change in specific enthalpy is positive for the exothermic reaction and negative for the endothermic reaction. The change in specific sensible enthalpy is always positive.Keywords: Efficiencies; Performances; Enthalpy; Hydrocarbons; Conductivities; Hydrogen

Beetle hindwings have the unique advantages of lightweight and high strength, which play a key role in flight. In this study, the beetle hindwings were cut along the chordal direction, then the first groove microstructure of different vein cross sections was investigated using the 3D microscope system and LSCM. It was found that the position of the first groove relative to the entire chordal cross-section of the wing gradually moves backwards, which has an effect on the flying aerodynamic behaviors of the beetle. Next, three corrugated airfoils (CA models) learned from the microscopy imaging of ladybird beetle hindwing were designed. Then aerodynamic behaviors were calculated by ANSYS Fluent software, it was confirmed that the position of the first groove microstructure affects the aerodynamic performance of the airfoil. For further study the influence of corrugated structural and motion parameters on the aerodynamic, 2D ‘simplified’ airfoil models with triangular corrugations (TWA models) were developed and studied.

The palynology and distribution of the trichomes, on the aerial parts and anatomy of Plectranthus scutellarioides from Udalguri district of Assam were studied in order to understand the significance of these features in systematics. The present work on Plectranthus scutellarioides thus provides an empirical basis for the identification of the species. Micromorphological features such as epidermal cell, stomata and trichomes were also studied under both light microscope and scanning electron microscope. The main types of trichomes - peltate, glandular and non-glandular were observed in leaves. Different features of pollen were observed and recorded. Photographs and Micrographs were also provided. All the observations were done under Light microscope and Scanning Electron Microscopy (SEM). The research provides the first detailed descriptions of floral micromorphological and palynological characteristics for Plectranthus scutellarioides, contributing to the empirical identification of the species. The findings offer valuable insights into the structure, size, and shape of stomata, as well as trichome diversity and pollen characteristics

Novel chemical, electrical, and mechanical properties absent in other materials have been discovered in carbon nanotubes. Pristine carbon nanotubes are inert to most chemicals and need to be grafted with surface functional groups to increase their chemical reactivity and add new properties. The increasing popularity of carbon nanotubes has created a demand for greater scientific understanding of the characteristics of thermal transport in nanostructured materials. However, the effects of impurities, misalignments, and structure factors on the thermal conductivity of carbon nanotube films and fibers are still poorly understood. Carbon nanotube films and fibers were produced, and the parallel thermal conductance technique was employed to determine the thermal conductivity. The effects of carbon nanotube structure, purity, and alignment on the thermal conductivity of carbon films and fibers were investigated to understand the characteristics of thermal transport in the nanostructured material. The importance of bulk density and cross-sectional area was determined experimentally. The results indicated that single-walled carbon nanotube films and fibers generally have high thermal conductivity. The presence of non-carbonaceous impurities degrades the thermal performance due to the low degree of bundle contact. The prepared carbon nanotube films and fibers are very efficient at conducting heat. The structure, purity, and alignment of carbon nanotubes play a fundamentally important role in determining the heat conduction properties of carbon films and fibers. The thermal conductivity may present power law dependence with temperature. The specific thermal conductivity decreases with increasing bulk density. The specific thermal conductivity of carbon nanotube fibers is significantly higher than that of carbon nanotube films due to the increased degree of bundle alignment. At room temperature, a maximum specific thermal conductivity is obtained but Umklapp scattering occurs.Keywords: Thermal properties; Preparation; Carbon films; Carbon fibers; Characterization; Thermal conductivity

This paper is concerned with the stability analysis of the static output-feedback polynomial fuzzy-model-based (SOF PFMB) control systems through designing a novel membership grade integration (MGI) approach. The nonconvex problems of the SOF PFMB control systems are convexificated into the convex conditions by introducing block diagonal positive-definite Lyapunov matrix and nonsingular transformation matrix. We proposed a new approximated membership functions, i.e. Lagrange Membership Functions (LMFs) method, which can be introduced into the stabilization process to relieve the stability conservativeness results. The LMFs are general representations of piecewise-linear membership functions (PLMFs), which makes the number of stability conditions not limited by the number of sample points. In a fixed subdomain, arbitrary sample points can be employed by the LMFs method and achieve higher approximation capability by increasing more sample points, so that membership grades can be incorporated into the system analysis. Furthermore, a novel MGI approach including the information of premise variables and LMFs are proposed, which can make the stability conditions more relaxed. Finally, a simulation example is given to show the merits of the developed techniques.

Herbarium specimens are increasingly being used as sources of information to understand the ecology and evolution of plants and their associated microbes. Most studies have used specimens as a source of genetic material using culture independent approaches. We demonstrate that herbarium specimens can also be used to culture nodule-associated bacteria, opening the possibility of using specimens to understand plant-microbe interactions at new spatiotemporal scales. We used historic and contemporary nodules of a common legume, Medicago lupulina, to create a culture collection. We were able to recover historic bacteria in 15 genera from three specimens (collected in 1950, 2004, and 2015). This work is the first of its kind to isolate historic bacteria from herbarium specimens. Future work should include inoculating plants with historic strains to see if they produce nodules and if they affect plant phenotype and fitness. Although we were unable to recover any Ensifer, the main symbiont of Medicago lupulina, we recovered some other potential nodulating species, as well as many putative growth-promoting bacteria.

Data scarcity is a significant obstacle to both flood simulation and flood risk analysis. This study used an Integrated Flood Modeling System (IFMS) to setup a 1D-2D coupled hydrodynamic model in order to simulate the flood inundation process in the Anning River Basin (ARB) in Sichuan Province under design flood scenarios with various return periods (5-year, 10-year, 20-year, 50-year, 100-year). Owing to the lack of available long-term time series data, we used the design flood flow of a hydrological station, design standard of levee engineering, and historical flooding events in order to validate the model. Then, the comprehensive risk degree ( R-value) method was used to elucidate the flood risk levels. Finally, we drew a flood risk map of the ARB and analyzed its flood risk. The statistical analysis produced the following findings: About 147.5 km 2 of the total inundation areas in the ARB are inundated at an extremely high-risk level, and the inundation rate reached 75.18%. Among the key towns present, the percentage of extremely high-risk areas was greater than 80%. In terms of settlement flooding, the extremely high risk level had 184 inundation spots, which was much higher than the other risk categories. These results indicate that the risk of flooding in ARB is high. This study used hydrodynamic models with limited measured data in order to simulate flood inundation and assess the risk of riverine flooding. This study can serve as a reference for flood studies in similar rivers that lack measured hydrological data.

Knowledge of the Soil Water Retention Function (SWRF) is important for irrigation management, soil water modelling and quantification of soil phys- ical health. However, determining the SWRF is laborious, requiring spe- cialized skills and equipment. Multi-depth soil moisture data is routinely measured and collected by Australian farmers to guide irrigation man- agement. This data provides an extraordinary opportunity to better un- derstand and characterize the hydraulic properties of agricultural soils if a means of inversely determining the SWRF from daily multi-depth soil moisture data existed. While the SWRF has been solved using the soil water program HYDRUS-1D to inversely determine the van Genuchten- Mualem (VGM) parameters from inflow/outflow type experiments, its im- plementation in real-world, multi-layer soils is rare. This study evaluated the ability of the HYDRUS-1D model to determine the VGM parameters from daily soil moisture and weather data obtained at two Tasmanian field sites. The experiments were conducted as four separate 100-day periods from two sites for three soil depths, including five different optimized pa- rameter sets, and three different initial parameter value sources with each of six variants, producing 420 inverse modelling tests. The quality of these tests was assessed according to five criteria: (i) modelling robustness, (ii) simulation accuracy, (iii) prediction accuracy, (iv) parameter uniqueness, and (v) estimation stability. Overall, 322 of 420 simulations failed due to non-convergence. The accuracy of the successfully completed simulations was poor, with an average R 2 value of 0.460 and an average RMSE value of 0.066 between the simulated and measured soil moisture. The prediction accuracy of the completed predictions of VGM parameters was less than 30%. Furthermore, predicted VGM parameters showed nonuniqueness and stability below 50%.

Background:To avoid unplanned, rapid repeat pregnancies, it is recommended that women use effective contraception from day 21 postpartum. This study presents a novel method for displaying postnatal contraception use over time, analysing data from highly health-literate women. Methods:This is a secondary analysis of a cross-sectional study which compared postnatal contraception use in women over 30 who had successful IVF to those who conceived without fertility treatment. This analysis uses a subset of data: 177 doctors who had conceived spontaneously. Their postnatal contraception use over time is presented using a Sankey plot. Chi-squared or Fisher's exact tests were used to compare contraception efficacy by socio-demographics and experience of contraception counselling. Qualitative data on quality of counselling were analysed using thematic analysis. Results:Contraception-efficacy was associated with timing of initiation (p<0.001); 92.3% of sexually-active participants initiating contraception before three weeks postpartum used effective or very effective methods. Overall, only 11.6% (17/146) of sexually-active participants used a very effective method as first contraception. Only contraception counselling at the place of birth was associated with initiation of effective or very effective contraception (p=0.041). Analysis of qualitative data on quality of counselling generated three themes: information provision, multi-disciplinary working, and need for self-advocacy. Conclusions:Use of effective postnatal contraception was low, despite a highly health-literate population. However, the high proportion of women choosing effective contraception before three weeks postpartum indicates acceptability where available. The Sankey plot is an effective visual that could be used to monitor and evaluate postnatal contraception services and interventions.

BJOG-23-0396The Choice

We conducted a feasibility study to evaluate micronutrients and body mass index. Fat soluble vitamins A, D, E and trace elements copper (Cu), selenium (Se) and zinc (Zn) levels were evaluated. Weight, height, body mass index (BMI) and Z-scores were recorded. Side effects or specific adverse events were documented. No patients had a Z score for height, weight, or BMI of <2SD or >2SD. Ninety percent of patients had one or more micronutrient levels below normal. These results suggest that micro-nutrient abnormalities are common despite no obvious evidence of malnutrition. Side effects of chemotherapy may be exacerbated by micronutrient depletion.

[Background] EQ-5D instruments (HRQOL), incuding the three-level (Y-3L) and five-level (Y-5L) child-friendly versions (EQ-5D-Y) are widely employed for assessing health-related quality of life. However, their effectiveness in children with asthma remains understudied. This study aimed to assess their performance in pediatric asthma patients and their caregivers. [Methods] Dyads of asthmatic patients (n=76, aged 8-16.7) and caregivers completed Y-5L and Y-3L, respectively, at two visits. Test-retest reliability and patient-caregiver agreement were assessed via intraclass correlation coefficient (ICC). Known-groups validity was assessed by comparing scores across varying asthma control levels. Responsiveness was assessed in children showing improved overall health and asthma control. [Results] ICCs for test-retest reliability ranged from 0.744 to 0.898 (self-complete) and 0.525 to 0.767 (proxy), indicating satisfactory reliability. As expected, overall scores for both EQ-5D-Y versions were higher (better HRQOL) in well-/partially-controlled asthma patients. Standardized effect sizes ranged from 0.19 to 1.00 (self-complete), 0.39 to 0.83 (proxy), and 0.26 to 1.40 (EQ VAS) in improved patients. Patient-caregiver agreement ranged from moderate to good. [Conclusion] Both self-complete and proxy EQ-5D-Y versions appeared to be suitable for assessing HRQOL in pediatric asthma patients, with the self-complete version being more preferable. Further investigation on the responsiveness of EQ-5D-Y is warranted.

This paper presents an empirical analysis of using deep learning features with an Extreme Learning Machine (ELM) for automatic modulation classification in wireless communication. The study utilizes advanced pre-deep learning models like VGG 16, Resnet 50, and Inception V3 to extract features, which are then fed to an ELM for classification. The ELM’s performance is enhanced by the moth flame optimization method (MFOP-ELM). To measure the efficacy of the proposed model, it is tested on two standard datasets - RADIOML2016.10A and RADIOML 2018.01A. The paper also compares the proposed model with other classifiers such as SVM, K-NN, and BPNN. Results show that the proposed model using Inception V3 features with the MFOP-ELM classifier outperforms other state-of-the-art models.

Echolocating bats use and adapt ultrasound pulses that vary in several parameters, one of them being the pulse’s source level, which is a measure of the emitted sound amplitude. This is a vital ecological parameter as it directly impacts the maximum distance over which bats can perceive targets in their environment, most importantly their prey. Different habitats present different sensing challenges for echolocation systems, and the quality and content of information derived from echolocation pulses reflect these environmental challenges. As such, echolocation pulses within or between species may vary from one habitat to the next due to variable selection pressure, resulting in local adaptation. Habitat is, therefore, a key component in shaping the evolution of echolocation. The Acoustic Adaptation Hypothesis (AAH) proposes that acoustic properties of the environment influence sound propagation and therefore the evolution of echolocation pulses. Here, we tested the AAH using multiple microphone arrays to measure the source levels of echolocation pulses of 14 bat species in bat assemblages across sites in six biomes in South Africa. Contrary to the AAH, our results revealed that bats in the same assemblage used different echolocation pulse source levels, frequencies, and duration resulting in different detection distances, which differ among bat assemblages occupying different sites. Furthermore, detection distance was species-specific and remained similar within species between assemblages; suggesting that species is a better predictor of detection distances compared to habitat as indicated by Miniopterus natalensis across all seven sites. KEYWORDS: adaptation, bat assemblages, detection distances, microphone arrays, selection pressure, source levels

A key goal in ecology is to develop more effective ways to understand species’ distributions in order to facilitate both their study and conservation. Many species distribution modeling analyses have been performed to date, using either structured survey data or unstructured citizen science data; these two pools of data have tradeoffs in terms of data density, spatiotemporal coverage, and accuracy. Recent studies have shown that combining structured and unstructured survey data can greatly improve the accuracy of species distribution models for birds, but most of this work has focused on north temperate bird species and uses bird atlas data that is much more common in the temperate zone than elsewhere. We sought to adapt a data pooling approach from the literature on north temperate bird biology to create distribution models for a selection of secretive suboscine bird species that occur in a highly diverse region of the southwestern Amazon.

Defect engineering and metal decoration onto 2-D materials have gained major attention as a means of creating viable hydrogen storage materials. This Density Functional Theory (DFT) based study presents lithium decorated single vacancy (SV) and Stone-Wales (SW) defective silicene as a viable media for storing hydrogen via physisorption. Introducing defects increases the Li adatom’s binding energy from -2.36 eV in pristine silicene to -3.44 eV and -2.73 eV in SV and SW silicene, respectively, thus preventing Li adatom clustering. The presence of defects and Li adatom further aid hydrogen adsorption onto the substrates with binding energies present in the US-DOE set range of -0.2 to -0.7 eV/H 2 with the highest binding energy measured to be -0.389 eV/H 2. It was seen that both the Li-decorated defective systems were able to effectively store multiple H 2 molecules up to 28 H 2 with the highest gravimetric density being 5.97 wt %. The projected density of state plots indicates a combined overlap of the Li (p) and Li (s) orbitals with the H (s) orbital leading to enhanced H 2 binding energies. Molecular dynamic simulations conducted at 300 K confirm the stability of the Li adatom as well as the adsorbed H 2 molecules at room temperature, establishing the viability of these systems as effective, high gravimetric density, physisorption-based hydrogen storage media.

Objective: To better understand underlying factors of peripartum mortality we assessed variations in mortality by Robson 10-group classification. Design: Cross-sectional study. Setting: Prospectively collected perinatal e-registry data from 16 hospitals in Benin, Malawi, Tanzania and Uganda. Population: All women aged 13-49 who gave birth to a live or stillborn baby >1000g between July 2021 and December 2022. Methods: We compared peripartum mortality risk by Robson group and calculated proportional contributions to mortality. We assessed interactions between mortality and Caesarean sections using multivariable logistic regression and post-estimations margins. Main Outcome Measures: Peripartum mortality, defined as intrapartum stillbirths and very early (≤24 hours after birth) neonatal deaths. Results: We included 80 663 babies born to 78 085 women, of which 1 706 were intrapartum stillbirths and 617 very early neonatal deaths. Peripartum mortality was 5.2% (Benin), 1.6% (Malawi), 1.1% (Tanzania), and 3.7% (Uganda). The largest contributor to intrapartum stillbirths (27.8%) and very early neonatal deaths (23.3%) was Robson group 3 (multipara with cephalic term singleton in spontaneous labour) followed by group 10 (preterm birth). Intrapartum stillbirth risk in breech presentation (groups 6 and 7) was 5.1% in nullipara and 11.1% in multipara. A Caesarean section halved the odds of peripartum mortality in breech presentation in primipara (0.46; 95% CI 0.22-0.95). Conclusions: Our findings indicate a high share of peripartum mortality in lower obstetric risk groups and high mortality in breech deliveries and preterm births. This underscores the need to intensify actions to improve labour management.