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Shipping in the Eighteenth-Century British Atlantic Slave Trade: A Quantitative Study
No full textThis quantitative study of ships in the eighteenth-century British slave trade shows that nearly half were in the 100–200 ton range while just over a further quarter were between 200 and 300 tons, which lay within the normal range of ocean-going merchant vessels. Thus, large ‘Guinea’ vessels of over 300 tons were less frequently deployed, though some existed. Variations existed in the mean tonnage of vessels trading with different West African regions, with the Bight of Biafra and West-Central Africa attracting larger British slave ships than other regions. The main delivery areas in the Americas for slaves taken on British ships – Virginia, the Carolinas, Barbados and Jamaica – all registered an upward trend in the amount of shipping tonnage in the ‘Guinea’ traffic in the eighteenth century. Though eighteen different rigs can be found among eighteenth-century British slave vessels, six rigs were mainly used and, among them, ships were easily the most common, accounting for almost three-fifths of the vessels in the British slave trade. Though most ships were not specifically constructed as slave ships, some specialist vessels were built as such towards the end of the eighteenth century. Copper sheathing helped to protect the hulls of slave vessels from the American Revolutionary War onwards. Most ships in the British slave trade were between eight and ten years old. More armaments and more crew were found on slave ships in war years than in peacetime. The data analysed here show that the shipping in the British slave trade adapted over time to market demands and that, as the eighteenth century progressed, productivity improved in arming and manning those vessels
Mechanical performance and life cycle assessment of BFRP-reinforced AAC slabs strengthened with basalt macro-fibers
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The data supporting the findings of this study is entirely contained within this paper. All data used for analysis is presented in the main text of this paper. No external or additional data sources were utilised in this study. The data can be accessed upon request from the corresponding author.Steel-reinforced Ordinary Portland Cement (OPC) concrete is the predominant construction material; however, it faces critical challenges, notably steel corrosion and high CO₂ emissions from cement production. Recent research explores corrosion-resistant alternatives to steel and environmentally sustainable substitutes for OPC. Basalt Fiber Reinforced Polymers (BFRP) bars demonstrate promising corrosion resistance, while alkali-activated cements (AACs) offer a lower-emission alternative to OPC. However, reinforced concrete slabs with BFRP bars exhibit lower shear capacity, wider crack widths, and more significant deflections compared to steel-reinforced slabs. Integrating wave-shaped Basalt-Macro fibers (BMFs) into the concrete mix can enhance these properties. This study assesses the structural and environmental viability of combining BFRP reinforcement with AAC. Experimental testing involved investigating the behavior of six BFRP-reinforced AAC slabs with varying BMFs contents (0 %, 1.5 %, and 2 %) compared to a steel-reinforced OPC control slab. The findings revealed that adding the BMFs increased the cracking load, shear capacity, and flexural stiffness of BFRP AAC slabs. Furthermore, a life cycle assessment (LCA) showed that BFRP-reinforced AAC slabs are significantly more sustainable than steel-reinforced OPC concrete, which produces 292 % and 190 % more CO2 emissions than BFRP-reinforced AAC slabs without and with 1.5 % fibers, respectively. This highlights the environmental advantages of using BFRP and AAC in construction
A Dual-Pathway Driver Emotion Classification Network Using Multi-Task Learning Strategy: A Joint Verification
Get PDFNegative emotion (e.g., anger, fear) may influence normal driver behavior, resulting in serious traffic accidents. Thus, developing an automatic driver emotion classification method is necessary and urgent. Most of the existing methods are performed in realistic indoor environment and always lack effective utilization of heterogeneous information, resulting in low accuracy and reliability. In this paper, a novel dual-pathway driver emotion classification network using multi-task learning strategy is proposed. To illustrate the design of the proposed driver emotion classification network, three modules are constructed: 1) visual-facial data processing module; 2) driving behavioral data processing module; 3) fusion output module. Meanwhile, considering the influence of emotional states on driving behavior, a comprehensive analysis is conducted to distinguish the positive, neutral, and negative influence on driving behavior. Furthermore, a joint verification in both realistic indoor environment (i.e., laboratory simulation on the PPB-Emo dataset) and real-world outdoor scenario is performed. The experimental results illustrate that the proposed network exhibits superior performance in terms of classification accuracy and response time, achieving good balance between classification accuracy and running speed in internet of things scenarios.10.13039/501100012279-Zhejiang Provincial Xinmiao Talents Program (Grant Number: 2024R407C065);
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62206062);
Ministry of Science and Technology - Yangtze River Delta Science and Technology Innovation Program (Grant Number: YDZX20233100004028);
the Postdoctoral Fellowship Program of CPSF (Grant Number: GZB20230356);
10.13039/501100002858-China Postdoctoral Science Foundation (Grant Number: 2024M751676 and 2024T170463)
The Association Between Metabolic Syndrome and the Risk of Endometrial Cancer in Pre- and Post-Menopausal Women: A UK Biobank Study
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Data can be made available upon requests made via the UK Biobank.Supplementary Materials are available online at: https://www.mdpi.com/2077-0383/14/3/751#app1-jcm-14-00751 .Background: Metabolic syndrome (MetS) is a syndrome that comprises central obesity, increased serum triglyceride (TG) levels, decreased serum HDL cholesterol (HDL) levels, raised blood pressure (BP), and impaired glucose regulation, including prediabetic and diabetic glycaemic levels. Recently, the association with endometrial cancer (EC) has been described but it is unclear if the risk associated with MetS is higher than the individual effect of obesity alone. This study investigates the association between MetS components and differing MetS definitions on EC risk and compares the risk of MetS with the risk posed by obesity alone. It also analyses how MetS affects the risk of EC development in the pre- and post-menopausal subgroups. Methods: A prospective cohort study was undertaken using data from the UK biobank. Multivariable Cox proportional risk models with the time to diagnosis (years) were used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of MetS and its components on the risk of EC. A subgroup analysis was also undertaken for pre- and post-menopausal participants. Kaplan–Meier (KM) was undertaken to assess the difference in the risk of EC development in differing BMI classes, and in pre- and post-menopausal subgroups. Results: A total of 177,005 females from the UK biobank were included in this study. Of those participants who developed EC (n = 1454), waist circumference > 80 cm, BMI > 30 kg/m2, hypertension > 130/80 mmHg, hyperlipidaemia and diabetes (HbA1C > 48 mmol/L were significant predictors of EC development, with waist circumference being the strongest predictor (HR = 2.21; 95% CI: 1.98–2.47, p < 0.001). Comparing the pre- and post-menopausal subgroup, hypertriglyceridaemia and diabetes were the strongest predictors of EC in the pre-menopausal subgroup (HR = 1.53; 95% CI: 1.18–1.99 and HR = 1.51; 95% CI: 1.08–2.12, p < 0.05, respectively). Raised waist circumference was not a significant independent predictor in the pre-menopausal subgroup. A KM curve analysis showed a clear distinction between those with and without MetS in the pre-menopausal group, suggesting a benefit of testing for MetS components in pre-menopausal women with obesity. Conclusions: Components of MetS, both independently and in combination, significantly increase the risk of EC. Screening those with obesity for MetS in their pre-menopausal years may help to identify those at the highest risk.The funding to access the UK Biobank data was supported by the Brunel University London BRIEF AWARDS 2020/21 awarded to Raha Pazoki
Hydration behaviors, workability, and strength variations in direct aqueous carbonation (DAC) of Portland cement paste
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The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.This study investigates the mechanisms behind direct aqueous carbonation in concrete manufacturing, focusing on its effects on workability and strength. Through an analysis of cement paste under varying water-to-cement ratios (0.5, 0.55, and 0.6) and CO2 additive amount (0%, 0.1%, and 1%), the results demonstrate that early carbonation accelerates the setting process. Higher CO2 additive amounts and lower w/c ratios further reduce setting time and fluidity, also increase free water consumption, which negatively affects the pore structure and compressive strength. However, as the transformation of amorphous calcium carbonate to calcite, enhancing hydration during curing and ultimately improving the final compressive strength. This study elucidates the various effects of CO2 addition to cement paste on fresh and hardened paste during the direct aqueous carbonation process, shedding light on how it influences hydration, workability, and strength, contributing to sustainable concrete production.This work was financially supported by the “Pioneer” R&D Program of Zhejiang (2022C03003), Horizon 2021(CSTO2NE) (101086302) and Ningbo Public Welfare Science and Technology Plan Project (Grant No.2023056)
A revision of sponges from the Faringdon Sponge Gravel Member and Atherfield Clay Formation, Lower Greensand Group of England
Get PDFSupplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0016787824000725?via%3Dihub#s0045 .Sponges of the Lower Greensand Group (LGS) are well preserved and occur in sediments of a sandy matrix. Abundant in the Faringdon Sponge Gravel Member (FSG), these sponges, mostly Calcareans, are found in Oxfordshire, with notable preservation at Little Coxwell quarries. This study provides descriptions of common species following the updated Porifera classification and recent sponge taxonomy research, illustrated with specimens from the Natural History Museum, London (NHM), British Geological Survey (BGS), and Natural History Museum Basel (NMB) collections. The following taxa are recorded and described: 1) Calcareans: Barroisia anastomosans (Parkinson, 1822), Barroisia clavata (Keeping, 1883), Barroisia irregularis (Hinde, 1884), Dehukia crassa (de Fromentel, 1861), [Elasmoierea] faringdonensis (Mantell, 1854), [Elasmoierea] mantelli (Hinde, 1884), Peronidella gillieroni (de Loriol, 1869), Peronidella prolifera (Hinde, 1884), Peronidella ramosa (Roemer, 1839), Oculospongia dilatate (Roemer, 1864), Tremospongia pulvinaria (Goldfuss, 1826), Raphidonema contortum (Hinde, 1884), Raphidonema porcatum (Sharpe, 1854), Raphidonema farringdonensis (Sharpe, 1854), Raphidonema macropora (Sharpe, 1854), Raphidonema pustulatum (Hinde, 1884), Endostoma foraminosa (Goldfuss, 1826); and 2) Hexactinellids: Lonsda contortuplicata (Lonsdale, 1849). Key findings include the identification of Tethyan biogeographic affinities and ecological adaptations that highlight the role of these sponges in early reef-like systems. By refining species descriptions and linking them to broader Cretaceous ecosystems, this work enhances understanding of sponge biodiversity, evolutionary strategies, and their contributions to carbonate platform development during periods of environmental change.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors
IoT-based cloud monitoring system for building fires
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The dataset used in this paper is available at request.This paper presents an IoT (Internet of Things) based smart building fire cloud monitoring system to enhance fire safety in smart buildings. It integrates low-cost sensors and real-time video surveillance for real-time environmental data collection. Data are uploaded to the cloud for remote monitoring via a custom web interface. The system features an artificial neural network model that reduces computational complexity and response time, achieving >95% accuracy in fire prediction. It assists in planning evacuation routes based on fire location, enhancing safety and efficiency. Laboratory and field tests confirm reliable performance, and the novel system will find applications in smart fire detection and prevention.This research received no external funding
Habitat complexity reduces feeding strength of freshwater predators
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The datasets analyzed for this study can be found on GitHub (https://github.com/b-c-r/CRITTERdata), where we also provide the code (https://github.com/b-c-r/CRITTERcode) and statistical methods (https://github.com/b-c-r/CRITTERstatistics) for the analysis. Citable versions can be found on Zenodo (https://doi.org/10.5281/zenodo.15348769, https://doi.org/10.5281/zenodo.15346225 and https://doi.org/10.5281/zenodo.15348995).The physical structure of an environment potentially influences feeding interactions among organisms, for instance, by providing refuge for prey. We examined how habitat complexity affects the functional feeding response of an ambush predator (damselfly larvae Ischnura elegans) and a pursuit predator (backswimmer Notonecta glauca) feeding on the isopod Asellus aquaticus. We ran experiments in aquatic microcosms with an increasing number of structural elements (0, 2, or 3 rings of plastic plants in different spatial configurations), resulting in five habitat complexity levels. Across these levels, predators were presented with different prey densities to determine the functional response pattern. The experimental design and analysis allowed us to test for effects of structure presence, amount, and complexity level on functional response in one pass, without confounding predictors. Across all complexity levels, the feeding for both predators was best described by a type II functional response model, and habitat drove feeding strength. Regarding the latter, the predators showed different responses to the complexity treatments. The overall feeding rate of I. elegans was mainly explained by the absence versus presence of structure. Yet, in the case of N. glauca, feeding rate was strongly dependent on habitat complexity with the predator showing a unique maximum feeding rate (i.e., the inverse of the handling time) for each complexity level and a decreasing attack rate with increasing amount of habitat. On average, prey consumption by both predators was reduced when complex structures were present, compared to the ‘no habitat structure’ environment (e.g., consumption more than halved for some treatments). Our findings demonstrate that habitat complexity dampens feeding rates and therefore plays a key role in the stability of freshwater ecosystems.M.A. was funded by the Investigo Program funded by the NextGenerationEU initiative, L.F. was funded by a grant from the Spanish Ministry of Education and Culture, I.G. was funded by the Spanish Ministry of Science, Innovation and Universities (TED2021-129966B-C31) and the University of the Basque Country (POSTUPV24/47). B.C.R. gratefully acknowledges the funding from the German Science Foundation (DFG) to the Research Unit DynaSym (FOR 5726). J.R. was supported by a Royal Society of London Starting Grant
Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies
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• Summary statistics are available from Figshare through the following link https://pgc.unc.edu/for-researchers/download-results/ (https://doi.org/10.6084/m9.figshare.27061255). These data are publicly
available as of the date of publication.
• Individual data are made available following an approved application to the PGC Data Access Committee (https://pgc.unc.edu/for-researchers/data-access-committee/). These data are available as of the date of publication.
• Available summary statistics, including 23andMe data, require an approved application to 23andMe here: https://research.23andme.com/dataset-access/. These data are available as of the date of publication.
• Summary statistics for the Genetic Association Information Network (GAIN), NeuroGenetics Research Consortium (NGRC), Gene Environment Association Studies Initiative (GENEVA, Melanoma Study), and other studies are available from The Database of Genotypes and Phenotypes (dbGaP: https://dbgap.ncbi.nlm.nih.gov/). These data are available as of the date of publication. Instructions on how to access dbGap data are available here: https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/.
• Additional deposited reference dataset availability is here: Haplotype Reference Consortium (European Genome-Phenome Archive, https://ega-archive.org), GTEx v8 (GTEx Portal, https://gtexportal.org), Human Brain Cell Atlas (CELL×GENE Discover, https://cellxgene.cziscience.com/), eQTLGen (https://www.eqtlgen.org), MetaBrain (https://www.metabrain.nl), Brain pQTL (AD Knowledge Portal, https://adknowledgeportal.synapse.org), and SynGO (https://syngoportal.org/).
• Additional quality control information, gene-based association summary statistics in fastBAT (including figures), Hi-C, genetic correlation results, full drug target enrichment findings, single-cell enrichment figures, and PGS plots are also available for download from Figshare through the following link: https://pgc.unc.edu/for-researchers/download-results/ (https://doi.org/10.6084/m9.figshare.27089614). See STAR Methods for a key resources table. These data are publicly available as of the date of publication.
• Project code is available from https://github.com/psychiatric-genomics-consortium/mdd-wave3-meta.STAR★Methods are available online at: https://www.cell.com/cell/fulltext/S0092-8674(24)01415-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867424014156%3Fshowall%3Dtrue#sec-9 .Supplemental information is available online at: https://www.cell.com/cell/fulltext/S0092-8674(24)01415-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867424014156%3Fshowall%3Dtrue#app-1 .Consortia members are listed online at: https://www.sciencedirect.com/science/article/pii/S0092867424014156#sec5 .In a genome-wide association study (GWAS) meta-analysis of 688,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries across diverse and admixed ancestries, we identify 697 associations at 635 loci, 293 of which are novel. Using fine-mapping and functional tools, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. A neural cell-type enrichment analysis utilizing single-cell data implicates excitatory, inhibitory, and medium spiny neurons and the involvement of amygdala neurons in both mouse and human single-cell analyses. The associations are enriched for antidepressant targets and provide potential repurposing opportunities. Polygenic scores trained using European or multi-ancestry data predicted MD status across all ancestries, explaining up to 5.8% of MD liability variance in Europeans. These findings advance our global understanding of MD and reveal biological targets that may be used to target and develop pharmacotherapies addressing the unmet need for effective treatment.This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award no. 1IK2BX005058 and I01CX001849. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. Major funding for the PGC is from the US National Institutes of Health (MH124873 and MH124871). Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org/) hosted by SURFsara. The iPSYCH team acknowledges funding from the Lundbeck Foundation (grants R102-A9118 and R155-2014-1724), the Stanley Medical Research Institute, the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and the GenomeDK HPC facility. This research has been conducted using the UK Biobank Resource (application 4844) and data from dbGaP (accession phs000021, phs000196, and phs000187) and including data from the Molecular Genetics of Schizophrenia Collaboration (Pablo Gejman, Northwestern University), the NINDS CIDR:NGRC Parkinson’s Disease Study, and the SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation (supported by the FNIH GAIN study, CA093459, CA097007, ES011740, and CA133996). Individual study funding and other acknowledgments are provided in the supplementary study information (Methods S1). This paper represents independent research partly funded by the NIHR Maudsley Biomedical Research Centre and Maudsley NHS Foundation Trust and King’s College London, and the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The current work was also supported by the Wellcome Trust (220857/Z/20/Z) and the European Union under the Horizon 2020 research and innovation programme (no. 847776 and 948561)
Emerging roles of the cancerous inhibitor of protein phosphatase 2A (CIP2A) in ovarian cancer
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The datasets generated and/or analysed during the current study are available upon reasonable request. Researchers interested in accessing the data can contact the corresponding authors. Data on DEGs is provided within the supplementary information files.Supplementary Information: The online version contains supplementary material available at https://link.springer.com/article/10.1038/s41598-025-05013-0#Sec19 .AF and SS should be considered as joint first authors.Ovarian cancer (OvCa) is the sixth most common gynaecological cancer in the UK, accounting for over 200,000 deaths worldwide. Cancerous Inhibitor of Phosphatase 2 A (CIP2A) is an oncoprotein and an endogenous inhibitor of PP2A. CIP2A is a key regulator for cellular processes (e.g. proliferation, DNA damage) and is involved in the progression of many malignancies. In this study we provide a comprehensive overview of its role in OvCa making use of in silico tools, clinical samples and in vitro models. CIP2A is overexpressed in OvCa patients, with metastatic patients having significantly higher expression when compared to patients with malignant and benign ovarian tumours. High CIP2A expression reduces both overall-and progression-free survival, whereas an R530T mutation is predicted to cause structural destabilisation of the CIP2A dimer. We also provide evidence for microRNA (miRNA) and mRNA target interactions with CIP2A. Finally, we have studied the effects of CIP2A inhibition in an in vitro BRCA2 model compared to BRCA2 wild-type OvCa cells, using RNA-sequencing. Gene enrichment pointed towards changes p53 pathway, protein metabolism, transporter activity, DNA replication, and cell cycle. Our data provide a novel insight into the role of CIP2A in OvCa and the potential of drug repurposing for therapeutic interventions
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