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Automated classification and mapping for alluvial geomorphic units:Current approaches and future directions
No full textThis paper critically reviews existing methodologies for classifying alluvial landform units, emphasizing the semantic frameworks and historical evolution of taxonomies that currently underpin identification and mapping efforts. It highlights the inconsistencies and ambiguities inherent in existing classification schemes, underscoring the need for clearer semantic definitions. Subsequently, the paper examines automated and semi-automated approaches, including geomorphometry and Geographic Object-Based Image Analysis (GEOBIA), for analyzing remote sensing imagery, with particular attention to their efficacy within fluvial environments. Recognizing recent advancements in remote sensing and computer vision, especially the increased adoption of taxonomies and ontologies to enable consistent, shareable, reusable, and interoperable geographic data, we advocate the systematic development of domain-specific ontologies for alluvial geomorphic units. We reference internationally accepted standards for ontology creation (ISO/IEC 21838–1:2021) and discuss methodologies for encoding these ontologies into machine-readable schemas suitable for machine learning implementations. From a multidisciplinary perspective, the paper assesses the potential of ontologies and derived knowledge graphs (KGs) to enhance the semantic segmentation of remote sensing imagery. It also explores emerging techniques integrating KGs with large language models (LLMs) and vision-language models (VLMs). Finally, we outline opportunities and considerations for applying and refining Vision Foundation and Language Models to improve object identification and segmentation in remote sensing applications.</p
A pangenome and pantranscriptome of hexaploid oat
Get PDFOat grain is a traditional human food that is rich in dietary fibre and contributes to improved human health . Interest in the crop has surged in recent years owing to its use as the basis for plant-based milk analogues . Oat is an allohexaploid with a large, repeat-rich genome that was shaped by subgenome exchanges over evolutionary timescales . In contrast to many other cereal species, genomic research in oat is still at an early stage, and surveys of structural genome diversity and gene expression variability are scarce. Here we present annotated chromosome-scale sequence assemblies of 33 wild and domesticated oat lines, along with an atlas of gene expression across 6 tissues of different developmental stages in 23 of these lines. We construct an atlas of gene-expression diversity across subgenomes, accessions and tissues. Gene loss in the hexaploid is accompanied by compensatory upregulation of the remaining homeologues, but this process is constrained by subgenome divergence. Chromosomal rearrangements have substantially affected recent oat breeding. A large pericentric inversion associated with early flowering explains distorted segregation on chromosome 7D and a homeologous sequence exchange between chromosomes 2A and 2C in a semi-dwarf mutant has risen to prominence in Australian elite varieties. The oat pangenome will promote the adoption of genomic approaches to understanding the evolution and adaptation of domesticated oats and will accelerate their improvement
Modulated Convolutional Networks
Get PDFWhile the deep convolutional neural network (DCNN) has achieved overwhelming success in various vision tasks, its heavy computational and storage overhead hinders the practical use of resource-constrained devices. Recently, compressing DCNN models has attracted increasing attention, where binarization-based schemes have generated great research popularity due to their high compression rate. In this article, we propose modulated convolutional networks (MCNs) to obtain binarized DCNNs with high performance. We lead a new architecture in MCNs to efficiently fuse the multiple features and achieve a similar performance as the full-precision model. The calculation of MCNs is theoretically reformulated as a discrete optimization problem to build binarized DCNNs, for the first time, which jointly consider the filter loss, center loss, and softmax loss in a unified framework. Our MCNs are generic and can decompose full-precision filters in DCNNs, e.g., conventional DCNNs, VGG, AlexNet, ResNets, or Wide-ResNets, into a compact set of binarized filters which are optimized based on a projection function and a new updated rule during the backpropagation. Moreover, we propose modulation filters (M-Filters) to recover filters from binarized ones, which lead to a specific architecture to calculate the network model. Our proposed MCNs substantially reduce the storage cost of convolutional filters by a factor of 32 with a comparable performance to the full-precision counterparts, achieving much better performance than other state-of-the-art binarized models.</p
The Superstition That Mutilates Children in Africa:Exploring the Scale and Features of Juju-Driven Pedicide in Kenya
Get PDFJuju-involved pedicide is becoming a frequent crime in contemporary African communities. Yet, sparse empirical studies on the subject exist. The present study explores the magnitude, motivations, and primary features of this crime in Kenya. An in-depth analysis was conducted of ritual homicide reports publicized in three Kenyan media outlets between 2012 and 2021. Semi-structured interviews were then conducted with five academics and activists to gain additional insights into key aspects of the results of the content analysis. The data support relevant existing literature that the worst victims of juju-driven murders are children of low socio-economic background in rural communities. The study calls for traditional spiritualists and dubious religious leaders to be brought under closer scrutiny.</p
Antimicrobial Peptides in Nematode Secretions:Unveiling Biotechnological Opportunities for Therapeutics and Beyond
Get PDFGastrointestinal (GI) parasitic nematodes threaten food security and affect human health and animal welfare globally. Current anthelmintics for use in humans and livestock are challenged by continuous re-infections and the emergence and spread of multidrug resistance, underscoring an urgent need to identify novel control targets for therapeutic exploitation. Recent evidence has highlighted the occurrence of complex interplay between GI parasitic nematodes of humans and livestock and the resident host gut microbiota. Antimicrobial peptides (AMPs) found within nematode biofluids have emerged as potential effectors of these interactions. This review delves into the occurrence, structure, and function of nematode AMPs, highlighting their potential as targets for drug discovery and development. We argue that an integrated approach combining advanced analytical techniques, scalable production methods, and innovative experimental models is needed to unlock the full potential of nematode AMPs and pave the way for the discovery and development of sustainable parasite control strategies.</p
Life satisfaction around the world:Measurement invariance of the Satisfaction With Life Scale (SWLS) across 65 nations, 40 languages, gender identities, and age groups
Get PDFThe Satisfaction With Life Scale (SWLS) is a widely used self-report measure of subjective well-being, but studies of its measurement invariance across a large number of nations remain limited. Here, we utilised the Body Image in Nature (BINS) dataset–with data collected between 2020 and 2022 –to assess measurement invariance of the SWLS across 65 nations, 40 languages, gender identities, and age groups (N = 56,968). All participants completed the SWLS under largely uniform conditions. Multi-group confirmatory factor analysis indicated that configural and metric invariance was upheld across all nations, languages, gender identities, and age groups, suggesting that the unidimensional SWLS model has universal applicability. Full scalar invariance was achieved across gender identities and age groups. Based on alignment optimisation methods, partial scalar invariance was achieved across all but three national groups and across all languages represented in the BINS. There were large differences in latent SWLS means across nations and languages, but negligible-to-small differences across gender identities and age groups. Across nations, greater life satisfaction was significantly associated with greater financial security and being in a committed relationship or married. The results of this study suggest that the SWLS largely assesses a common unidimensional construct of life satisfaction irrespective of respondent characteristics (i.e., national group, gender identities, and age group) or survey presentation (i.e., survey language). This has important implications for the assessment of life satisfaction across nations and provides information that will be useful for practitioners aiming to promote subjective well-being internationally.</p
Genome-wide association study for dissecting lipid and fatty acid variation in a global collection of pearl millet germplasm
Get PDFPearl millet (Pennisetum glaucum) is a highly nutritious and climate resilient cereal cultivated on marginal lands in Asia and Africa underscoring its importance in global food security. Despite its nutritional value, the lipid and fatty acid variation and their genetic factors in pearl millet remain poorly understood. The Pearl Millet Inbred Germplasm Association Panel (PMiGAP), encompassing global diversity, provides a unique opportunity to explore these traits. This study investigated the variation in lipid and fatty acid composition within the PMiGAP population and applied GWAS to identify candidate genes. The total lipid content ranged from 3.93 % to 9.49 % with fourteen different fatty acids detected in this study. The linoleic acid and oleic acid were the most abundant fatty acids found in the PMiGAP. Palmitic acid varied from 4.35 % to 11.13 %, stearic acid from 0.12 % to 4.63 %, oleic acid from 7.33 % to 64.47 %, linoleic acid from 28.31 % to 85.51 %, and linolenic acid from 0.34 % to 1.69 %. Further, GWAS identified 64 significant marker-trait associations and 52 candidate genes within a 50 kb distance near these associations. The study provided novel insights on the genetic architecture of lipids and fatty acids, and a set of SNPs and candidate genes, which could be exploited in deriving pearl millet varieties through marker assisted breeding.</p
Assembling mountains through food:Typical cheese and politics of mountainness in the Italian Alps
Get PDFThe role of typical products in rural regions has sparked scholarly debate, with a great variety of approaches and perspectives employed to investigate agri-food goods with unique territorial characteristics. This paper delves into the complexities surrounding the identification and codification of such products, particularly focusing on the cheese industry within mountain regions. Through the assemblage theory, it explores the multifaceted elements contributing to the production of typical cheese, including geographical indications, local practices and knowledge. Using Castelmagno cheese as a case study, the research investigates the intricate dynamics of its recognition and production, shedding light on important issues such re-localization, economic strategies, and conflicts within the local community. By defining and analyzing the politics of mountainness inherent in the designation of typical products, this study uncovers the diverse perspectives and negotiations shaping rural economies and landscapes. The research elucidates the intricate relationship between the qualification of Castelmagno cheese as a typical product and the relational fabrication of the mountain, both as a tangible geographical entity and as a conceptual construct. Through qualitative methods such as interviews, observations, and literature analysis, it provides insights into the interplay between food production, cultural heritage, and the negotiation of territorial identities in mountainous regions, thus proposing an unconventional understanding of the relationships between food-making and place-making.</p
Same data, different analysts:Variation in effect sizes due to analytical decisions in ecology and evolutionary biology
Get PDFAlthough variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small "many analyst" study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.</p
Green tea with rhubarb root reduces plasma lipids while preserving gut microbial stability in a healthy human cohort
Get PDFBackground/Objectives: Cardiovascular diseases remain a leading cause of mortality and morbidity, and dyslipidaemia is one of the major risk factors. The widespread use of herbs and medicinal plants in traditional medicine has garnered increasing recognition as a valuable resource for increasing wellness and reducing the onset of disease. Several epidemiologic and clinical studies have shown that altering blood lipid profiles and maintaining gut homeostasis may protect against cardiovascular diseases. Methods: A randomised, active-controlled parallel human clinical trial (n = 52) with three herbal tea infusions (green (Camellia sinensis) tea with rhubarb root, green tea with senna, and active control green tea) daily for 21 days in a free-living healthy adult cohort was conducted to assess the potential for health benefits in terms of plasma lipids and gut health. Paired plasma samples were analysed using Afinion lipid panels (total cholesterol, LDL (low-density lipoprotein) cholesterol, HDL (high-density lipoprotein) cholesterol, triglycerides, and non-HDL cholesterol) and paired stool samples were analysed using 16S rRNA amplicon sequencing to determine bacterial diversity within the gut microbiome. Results: Among participants providing fasting blood samples before and after the intervention (n = 47), consumption of herbal rhubarb root tea and green tea significantly lowered total cholesterol, LDL-cholesterol, and non-HDL cholesterol (p < 0.05) in plasma after 21 days of daily consumption when compared with concentrations before the intervention. No significant change was observed in the senna tea group. In participants providing stool samples (n = 48), no significant differences in overall microbial composition were observed between pre- and post-intervention, even at the genus level. While no significant changes in overall microbial composition were observed, specific bacterial genera, such as Dorea spp., showed correlations with LDL cholesterol concentrations, suggesting potential microbiota-mediated effects of tea consumption. Diet and BMI was maintained in each of the three groups before and after the trial. Conclusions: It was found that drinking a cup of rhubarb root herbal or green tea infusion for 21 days produced beneficial effects on lipid profiles and maintained gut eubiosis without observable adverse effects in a healthy human cohort. More studies are needed to fully understand the effects of rhubarb root and green tea in fatty acid metabolism and gut microbial composition