This paper presents an experimental overview of linearity metrics using setups based on a PNA-X and a vector signal analyzer to evaluate key performance indicators of a transistor, such as noise power ratio and error vector magnitude, under unequally spaced multi-tone (USMT) and various quadrature amplitude modulation signals. The purpose of this study is to verify the feasibility of characterizing the linearity of transistors and RF power amplifiers on a PNA-X-based measurement bench by exploiting the statistical properties of the previously developed USMT signal, which allows NPR measurement in a single pass. The measurements were performed on an $8 \times 50\,\mu\,\mathrm{m}$ gate GaN transistor from UMS Foundry,operating on-wafer at 29 GHz.

A literature review suggests that the flows past simply connected bodies with aspect ratio close to unity and symmetries aligned with the flow follow a consistent sequence of regimes (steady, periodic, quasiperiodic) as the Reynolds number increases. However, evidence is fragmented, and studies are rarely conducted using comparable numerical or experimental set-ups. This paper investigates the wake dynamics of two canonical bluff bodies with distinct symmetries: a cube (discrete) and a sphere (continuous). Employing three-dimensional (3-D) global linear stability analysis and nonlinear simulations within a unified numerical framework, we identify the bifurcation sequence driving these regime transitions. The sequence: a pitchfork bifurcation breaks spatial symmetry; a Hopf bifurcation introduces temporal periodicity ($St_1$); a Neimark–Sacker bifurcation destabilises the periodic orbit, leading to quasiperiodic dynamics with two incommensurate frequencies ($St_1, St_2$). A Newton–Krylov method computes the unstable steady and periodic base flows without imposing symmetry constraints. Linear stability reveals similarities between the cube and sphere in the spatial structure of the leading eigenvectors and in the eigenvalue trajectories approaching instability. This study provides the first confirmation of a Neimark–Sacker bifurcation to quasiperiodicity in these 3-D wakes, using Floquet stability analysis of computed unstable periodic orbits and their Floquet modes. The quasiperiodic regime is described in space and time by the Floquet modes’ effects on the base flow and a spectrum dominated by the two incommensurate frequencies and tones arising from nonlinear interactions. Although demonstrated for a cube and a sphere, this bifurcation sequence, leading from steady state to quasiperiodic dynamics, suggests broader applicability beyond these geometries.

Spermophagus niger L. is a well-known pest of roselle (Hibiscus sabdariffa L.) seeds in West Africa and responsible of mostly damage. This study first reported the presence of S. niger Motschulsky in kenaf (Hibiscus cannabinus L.) seeds stored. Samples of kenaf seeds collected at four locations in Burkina Faso. In the laboratory, the seeds were incubated until adults’ insects emerged. The emerged insects were first identified morphologically and their biodemographic parameters studied under controlled conditions (32°C ± 0.1, 43% ± 1 r.h.). The results showed that S. niger (Coleoptera: Chrysomelidae) was the only pest encountered on H. cannabinus seeds in storage and was able to complete its development cycle there. Over the course of its life, which lasts an average of 7 days, the female laid around 40 eggs, resulting in 24 individuals dominated by females. The embryonic and total development time were average 5 and 26 days, respectively. Spermophagus niger population doubled in 6 days, with an intrinsic rate of natural increase of 0.105. The finite rate of increase and the generation time averaged 1.11 and 31.86 days, respectively. This study pointed out for the first time that S. niger is able to evolve successfully on H. cannabinus seeds in storage conditions and therefore, could be a serious pest of this important crop. The data from this study could therefore be used as a basis for the post-harvest management of H. cannabinus seeds.

This work experimentally explores the alignment of the vorticity vector and the strain-rate tensor eigenvectors at locations of extreme upscale and downscale energy transfer. We show that the turbulent von Kármán flow displays vorticity–strain alignment behaviour across a large range of Reynolds numbers, which is very similar to previous studies on homogeneous, isotropic turbulence. We observe that this behaviour is amplified for the largest downscale energy transfer events, which tend to be associated with sheet-like geometries. These events are also shown to have characteristics previously associated with high flow field nonlinearity and singularities. In contrast, the largest upscale energy transfer events display very different structures which showcase a strong preference for vortex compression. Notably, in both cases we find that these trends are strengthened as the probed scales approach the Kolmogorov scale. We then show further evidence for the argument that strain self-amplification is the most salient feature in characterising the cascade direction. Finally, we identify possible invariant behaviour for the largest energy transfer events, even at scales near the Kolmogorov scale.

There have been no culturally validated measures to screen for depression in Madagascar. In 2022–2023, we conducted qualitative studies in the Bay of Ranobe area in southwestern Madagascar to understand local mental health syndromes specific to this region. We found that the 8-item Patient Health Questionnaire (PHQ-8) shares symptoms with the general distress-like, depressive-like and grief-like syndromes elicited locally. We adapted the PHQ-8 to align with the unique symptoms found in the region that were missing from the measure. We administered the adapted PHQ-8 to 809 participants aged 16 and above. We found that the one-factor (Depression) model (root mean square error of approximation [RMSEA] = 0.046, standardized root mean square residual [SRMR] = 0.053, Comparative Fit Index [CFI] = 0.993 and Tucker–Lewis Index [TLI] = 0.991) had a better fit to our data than the two-factor (Cognitive–Affective and Somatic) model (RMSEA = 0.047, SRMR = 0.052, CFI = 0.994 and TLI = 0.990). The one-factor (Depression) model demonstrated good internal consistency (MacDonald’s omega coefficient $ {\omega}_0 $ = 0.81 and ordinal alpha $ {\alpha}_0 $ = 0.87). We conducted a multigroup confirmatory factor analysis to establish measurement invariance (MI) across four groups (sex, ethnicity, level of education and age group) and found that all levels of MI were achieved across groups. Our research provides a validated method to assess the probable prevalence of current depression in southwestern Madagascar.

This work is a numerical study of a transitional shock wave boundary layer interaction (SWBLI). The main goal is to improve our understanding of the well-known low-frequency SWBLI unsteadiness and especially the suspected role of triadic interactions in the underlying physical mechanism. To this end, a direct numerical simulation is performed using a high-order finite-volume scheme equipped with a suitable shock capturing procedure. The resulting database is then extensively post-processed in order to extract the main dynamical features of the interaction zone dynamics (involved characteristic frequencies, characteristics of the vortical structures, etc.). The dynamical organisation and space–time evolution of the flow at dominant frequencies are then further characterised by mean of an spectral proper orthogonal decomposition analysis. In order to study the role of triadic interactions occurring in the interaction region, a bispectral mode decomposition analysis is applied to the database. It allows us to extract the significant triadic interactions, their location and the resulting physical spatial modes. Strong triadic interactions are detected in the downstream part of the separation bubble whose role on the low-frequency unsteadiness is characterised. All the results of the various analyses are then discussed and integrated to formulate a possible mechanism fuelling low-frequency SWBLI unsteadiness.

Objectives/Goals: Transmission-blocking vaccines hold promise for malaria elimination by reducing community transmission. But a major challenge that limits the development of efficacious vaccines is the vast parasite’s genetic diversity. This work aims to assess the genetic diversity of the Pfs25 vaccine candidate in complex infections across African countries. Methods/Study Population: We employed next-generation amplicon deep sequencing to identify nonsynonymous single nucleotide polymorphisms (SNPs) in 194 Plasmodium falciparum samples from four endemic African countries: Senegal, Tanzania, Ghana, and Burkina Faso. The individuals aged between 1 and 74 years, but most of them ranged from 1 to 19 years, and all presented symptomatic P. falciparum infection. The genome amplicon sequencing was analyzed using Geneious software and P. falciparum 3D7 as a reference. The SPNs were called with a minimum coverage of 500bp, and for this work, we used a very sensitive threshold of 1% variant frequency to determine the frequency of SNPs. The identified SNPs were threaded to the crystal structure of the Pfs25 protein, which allowed us to predict the impact of the novel SNP in the protein or antibody binding. Results/Anticipated Results: We identified 26 SNPs including 24 novel variants, and assessed their population prevalence and variant frequency in complex infections. Notably, five variants were detected in multiple samples (L63V, V143I, S39G, L63P, and E59G), while the remaining 21 were rare variants found in individual samples. Analysis of country-specific prevalence showed varying proportions of mutant alleles, with Ghana exhibiting the highest prevalence (44.6%), followed by Tanzania (12%), Senegal (11.8%), and Burkina Faso (2.7%). Moreover, we categorized SNPs based on their frequency, identifying dominant variants (>25%), and rare variants (Discussion/Significance of Impact: We identified additional SNPs in the Pfs25 gene beyond those previously reported. However, the majority of these newly discovered display low variant frequency and population prevalence. Further research exploring the functional implications of these variations will be important to elucidate their role in malaria transmission.

In Europe, organic food must comply with specific regulations which do not include nutritional criteria. The ability of organic food to meet the nutritional needs of children is not assessed. This narrative review discusses the nutritional composition (macronutrients, micronutrients) of organic food compared with conventional products and its clinical relevance with a paediatric focus, as well as the health impact of these differences and of contaminants which interfere with metabolism. Other potential differences, particularly regarding the direct/indirect exposure to other contaminants in conventional food, are not addressed in this review. The composition of some organic food may differ from conventional food. Protein content was lower in cereals and eggs. A lower n-6:n-3 polyunsaturated fat (PUFA) ratio was observed in milk, meat and eggs. Long-chain PUFA and vitamin E may be higher in milk, meat and fish, as well as some minerals and antioxidants (phenolic compounds, vitamin C) in fruits, vegetables and starchy food and carotenoids in fruits and vegetables. Epidemiological studies suggest an association between organic diets and lower prevalence of childhood obesity, type 2 diabetes and metabolic syndrome, whereas the protective effect on allergy and cancer is controversial. Some organic food may be of greater nutritional interest for children’s diet than conventional food. Standardised studies comparing food composition and diet in children are needed. Considering the lower toxicologic risk and the sustainability of organic food, the Committee on Nutrition encourages the use of organic food, provided that such food is affordable, alongside specific baby food which is subject to strict specific European Union regulations.

Laser systems based on coherent beam combination (CBC) that rely on tiled pupil architecture intrinsically carry digital capabilities independently applicable to all three essential characteristics of a laser pulse: amplitude, phase and polarization. Those capabilities allow the far-field energy distribution to be flexibly tailored in real time. Operation in the femtosecond regime at high repetition rates gives access to a wide range of applications requiring both high peak and average powers. We address the task of independent peak versus average power adjustment needed for applications seeking to decouple nonlinear phenomena associated with GW peak power from the thermal load inherent to kW average power operation. The technical solutions proposed are presented in the framework of the Ecole Polytechnique XCAN CBC laser platform (61 independent channels) with an emphasis on thermal management measures implemented to ensure its nominal operation.

The measurement of latent traits and investigation of relations between these and a potentially large set of explaining variables is typical in psychology, economics, and the social sciences. Corresponding analysis often relies on surveyed data from large-scale studies involving hierarchical structures and missing values in the set of considered covariates. This paper proposes a Bayesian estimation approach based on the device of data augmentation that addresses the handling of missing values in multilevel latent regression models. Population heterogeneity is modeled via multiple groups enriched with random intercepts. Bayesian estimation is implemented in terms of a Markov chain Monte Carlo sampling approach. To handle missing values, the sampling scheme is augmented to incorporate sampling from the full conditional distributions of missing values. We suggest to model the full conditional distributions of missing values in terms of non-parametric classification and regression trees. This offers the possibility to consider information from latent quantities functioning as sufficient statistics. A simulation study reveals that this Bayesian approach provides valid inference and outperforms complete cases analysis and multiple imputation in terms of statistical efficiency and computation time involved. An empirical illustration using data on mathematical competencies demonstrates the usefulness of the suggested approach.

This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained convolutional neural networks to custom data. The manuscript demonstrates several deepImageJ capabilities, particularly in deploying complex pipelines, three-dimensional (3D) image analysis, and processing large images. A key development is the integration of the Java Deep Learning Library, expanding deepImageJ’s compatibility with various deep learning (DL) frameworks, including TensorFlow, PyTorch, and ONNX. This allows for running multiple engines within a single Fiji/ImageJ instance, streamlining complex bioimage analysis workflows. The manuscript details three case studies to demonstrate these capabilities. The first case study explores integrated image-to-image translation followed by nuclei segmentation. The second case study focuses on 3D nuclei segmentation. The third case study showcases large image volume segmentation and compatibility with the BioImage Model Zoo. These use cases underscore deepImageJ’s versatility and power to make advanced DLmore accessible and efficient for bioimage analysis. The new developments within deepImageJ seek to provide a more flexible and enriched user-friendly framework to enable next-generation image processing in life science.

This article investigates the promise of Insurtech to expand the frontier of the insurance market to include vulnerable populations around the world. It contributes to current debates on the proliferation of new technologies for financial inclusion as embedded in contemporary forms of platform-based capitalism. We argue that Insurtech’s promises fall short of expectations because of the contradiction between the principles of platform scalability and insurance risk pooling. Such contradictions lead Insurtech platforms to unpool risk rather than provide innovative technologies to pool it. This ultimately limits the expansion of markets for inclusive insurance as Insurtech platforms struggle to scale up the market through their supposedly disruptive technology. Our analysis draws on a range of regulatory reports, complemented by in-depth interviews with Insurtech executive officers. The article offers insights into the contradictory principles currently driving the digital inclusive insurance market, as well as the limits to the ongoing global expansion of platform capitalism.