Small-Size Humanoid Soccer Robot Design for FIRA HuroSot

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Measuring temporal change in alpha diversity : a framework integrating taxonomic, phylogenetic and functional diversity and the iNEXT.3D standardization

Funding: This work is jointly supported by the Natural Environment Research Council, UK (NE/T004487/1 for AM and MD) and the Taiwan Ministry of Science and Technology under Contracts NERC-MOST 108-2923-M-007-003 (for AC and CC). AM and MD also acknowledge support from the Leverhulme Trust (RPG-2019-401).1. Biodiversity is a multifaceted concept covering different levels of organisation from genes to ecosystems. Biodiversity has at least three dimensions: (i) Taxonomic diversity (TD): a measure that is sensitive to the number and abundances of species. (ii) Phylogenetic diversity (PD): a measure that incorporates not only species abundances but also species evolutionary histories. (iii) Functional diversity (FD): a measure that considers not only species abundances but also species? traits. 2. We integrate the three dimensions of diversity under a unified framework of Hill numbers and their generalizations. Our TD quantifies the effective number of equally-abundant species, PD quantifies the effective total branch length, mean-PD (PD divided by tree depth) quantifies the effective number of equally-divergent lineages, and FD quantifies the effective number of equally-distinct virtual functional groups (or functional ?species?). Thus, TD, mean-PD and FD are all in the same units of species/lineage equivalents and can be meaningfully compared. 3. Like species richness, empirical TD, PD and FD based on sampling data, depend on sampling effort and sample completeness. For TD (Hill numbers), the iNEXT (interpolation and extrapolation) standardization was developed for standardizing sample size or sample completeness (as measured by sample coverage, the fraction of individuals that belong to the observed species) to make objective comparisons across studies. This paper extends the iNEXT method to the iNEXT.3D standardization to encompass all three dimensions of diversity via sample-size- and sample-coverage-based rarefaction and extrapolation under the unified framework. The asymptotic diversity estimates (i.e., sample size tends to infinity and sample coverage tends to unity) are also derived. In addition to individual-based abundance data, the proposed iNEXT.3D standardization is adapted to deal with incidence-based occurrence data. 4. We apply the integrative framework and the proposed iNEXT.3D standardization to measure temporal alpha-diversity changes for estuarine fish assemblage data spanning four decades. The influence of environmental drivers on diversity change are also assessed. Our analysis informs a mechanistic interpretation of biodiversity change in the three dimensions of diversity. The accompanying freeware, iNEXT.3D, developed during this project, facilitates all computation and graphics.PostprintPeer reviewe

Screening for fear of cancer recurrence : instrument validation and current status in early stage lung cancer patients

Background Fear of cancer recurrence (FCR) is one of the most distressing concerns for cancer patients. A psychometrically validated brief scale is urgently needed for use in busy clinical oncology settings. This study aimed to (1) develop and validate the 7-item fear of cancer recurrence scale Chinese version (FCR7-C), and (2) explore the severity of FCR in post-operative early-stage lung cancer patients in Taiwan. Methods Early-stage lung cancer patients were recruited from a medical center in Taiwan. The FCR7-C was evaluated for content and construct validity and internal consistency reliability. Construct validity of FCR7-C was determined by the empirically supported correlation and confirmatory factor analysis (CFA). Results A total of 160 subjects were recruited. The FCR7-C was shown to have satisfactory content validity and internal consistency reliability (Cronbach's α = 0.9). The uni-dimensional structure was confirmed by CFA that showed a good fit for the model. The FCR7-C score correlates positively with the degree of most of the physical symptoms, anxiety, and depression, but correlates negatively with patient age, performance status, and quality of life. We found that 81.9% of patients reported at least some FCR, with a mean FCR severity of 15.18 (SD = 7.78). Conclusion FCR7-C is a brief screening tool with good psychometrics. Patients with early-stage lung cancer still revealed mild to moderate level of FCR. Applying the FCR7-C for to screen cancer patients’ distress and further develop personalized psychological interventions would be strongly suggested.Publisher PDFPeer reviewe

Rarefaction and extrapolation with beta diversity under a framework of Hill numbers : the iNEXT.beta3D standardization

This work isjointly supported by the Natural Environment Research Council, UK and the Taiwan Ministry of Science and Technology under Contracts NERC-MOST 108-2923-M-007-003 and NE/T004487/1. AEM also acknowledges the Leverhulme Trust (RPG-2019-402). Support for the establishment and monitoring of permanent plots in Costa Rican forests was provided by grants from the Andrew W. Mellon Foundation, the US National Science Foundation (NSF DEB-0424767, NSF DEB-0639393 and NSF DEB-1147429), US NASA Terrestrial Ecology Program, and the University of Connecticut Research Foundation. MD is supported by a Leverhulme Trust Research Centre - the Leverhulme Centre for Anthropocene Biodiversity (RC-2018-021). L.F.S.M. was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) grant 307984/2022-2.Based on sampling data, we propose a rigorous standardization method to measure and compare beta diversity across datasets. Here beta diversity, which quantifies the extent of among-assemblage differentiation, relies on Whittaker's original multiplicative decomposition scheme, but we use Hill numbers for any diversity order q ≥ 0. Richness-based beta diversity (q = 0) quantifies the extent of species identity shift, whereas abundance-based (q > 0) beta diversity also quantifies the extent of difference among assemblages in species abundance. We adopt and define the assumptions of a statistical sampling model as the foundation for our approach, treating sampling data as a representative sample taken from an assemblage. The approach makes a clear distinction between the theoretical assemblage level (unknown properties/parameters of the assemblage) and the sampling data level (empirical/observed statistics computed from data). At the assemblage level, beta diversity for N assemblages reflects the interacting effect of the species abundance distribution and spatial/temporal aggregation of individuals in the assemblage. Under independent sampling, observed beta (= gamma/alpha) diversity depends not only on among-assemblage differentiation but also on sampling effort/completeness, which in turn induces dependence of beta on alpha and gamma diversity. How to remove the dependence of richness-based beta diversity on its gamma component (species pool) has been intensely debated. Our approach is to standardize gamma and alpha based on sample coverage (an objective measure of sample completeness). For a single assemblage, the iNEXT method was developed, through interpolation (rarefaction) and extrapolation with Hill numbers, to standardize samples by sampling effort/completeness. Here we adapt the iNEXT standardization to alpha and gamma diversity, that is, alpha and gamma diversity are both assessed at the same level of sample coverage, to formulate standardized, coverage-based beta diversity. This extension of iNEXT to beta diversity required the development of novel concepts and theories, including a formal proof and simulation-based demonstration that the resulting standardized beta diversity removes the dependence of beta diversity on both gamma and alpha values, and thus reflects the pure among-assemblage differentiation. The proposed standardization is illustrated with spatial, temporal, and spatiotemporal datasets, while the freeware iNEXT.beta3D facilitates all computations and graphics.Publisher PDFPeer reviewe

Hill-Chao numbers allow decomposing gamma multifunctionality into alpha and beta components

Biodiversity-ecosystem functioning (BEF) research has provided strong evidence and mechanistic underpinnings to support positive effects of biodiversity on ecosystem functioning, from single to multiple functions. This research has provided knowledge gained mainly at the local alpha scale (i.e. within ecosystems), but the increasing homogenization of landscapes in the Anthropocene has raised the potential that declining biodiversity at the beta (across ecosystems) and gamma scales is likely to also impact ecosystem functioning. Drawing on biodiversity theory, we propose a new statistical framework based on Hill-Chao numbers. The framework allows decomposition of multifunctionality at gamma scales into alpha and beta components, a critical but hitherto missing tool in BEF research; it also allows weighting of individual ecosystem functions. Through the proposed decomposition, new BEF results for beta and gamma scales are discovered. Our novel approach is applicable across ecosystems and connects local- and landscape-scale BEF assessments from experiments to natural settings

The Modified Shields Classification and 12 Families with Defined DSPP Mutations

Mutations in Dentin Sialophosphoprotein (DSPP) are known to cause, in order of increasing severity, dentin dysplasia type-II (DD-II), dentinogenesis imperfecta type-II (DGI-II), and dentinogenesis imperfecta type-III (DGI-III). DSPP mutations fall into two groups: a 5′-group that affects protein targeting and a 3′-group that shifts translation into the −1 reading frame. Using whole-exome sequence (WES) analyses and Single Molecule Real-Time (SMRT) sequencing, we identified disease-causing DSPP mutations in 12 families. Three of the mutations are novel: c.53T>C/p.(Val18Ala); c.3461delG/p.(Ser1154Metfs*160); and c.3700delA/p.(Ser1234Alafs*80). We propose genetic analysis start with WES analysis of proband DNA to identify mutations in COL1A1 and COL1A2 causing dominant forms of osteogenesis imperfecta, 5′-DSPP mutations, and 3′-DSPP frameshifts near the margins of the DSPP repeat region, and SMRT sequencing when the disease-causing mutation is not identified. After reviewing the literature and incorporating new information showing distinct differences in the cell pathology observed between knockin mice with 5′-Dspp or 3′-Dspp mutations, we propose a modified Shields Classification based upon the causative mutation rather than phenotypic severity such that patients identified with 5′-DSPP defects be diagnosed as DGI-III, while those with 3′-DSPP defects be diagnosed as DGI-II

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO