Analysis of training programmes and education schemes for skills development on marine transport

The more important and global role the marine transportation has taken nowadays suggests that a larger number of skilled workforce are currently in demand. New technologies and efficient information management create an opportunity for better service, more reliable operation and profit. This paper mainly analyses the current situation with skills development and education schemes for marine transportation in different countries. Statistical data from sample countries was collected and compared through different management levels, education forms and job groups. The conclusions of the paper show that the available training schemes and education programmes for skills development on marine transport are unsatisfactory in the countries under study. For the marine industry to ensure a steady growth in a long run, improvements in the current skills development schemes supported by the deployment and implementation of advanced technology in the future are needed

Experimental and theoretical evidence for molecular forces driving surface segregation in photonic colloidal assemblies

Surface segregation in binary colloidal mixtures offers a simple way to control both surface and bulk properties without affecting their bulk composition. Here, we combine experiments and coarse-grained molecular dynamics (CG-MD) simulations to delineate the effects of particle chemistry and size on surface segregation in photonic colloidal assemblies from binary mixtures of melanin and silica particles of size ratio (Dlarge/Dsmall) ranging from 1.0 to similar to 2.2. We find that melanin and/or smaller particles segregate at the surface of micrometer-sized colloidal assemblies (supraballs) prepared by an emulsion process. Conversely, no such surface segregation occurs in films prepared by evaporative assembly. CG-MD simulations explain the experimental observations by showing that particles with the larger contact angle (melanin) are enriched at the supraball surface regardless of the relative strength of particle-interface interactions, a result with implications for the broad understanding and design of colloidal particle assemblies

META-SELD: Meta-Learning for Fast Adaptation to the new environment in Sound Event Localization and Detection

For learning-based sound event localization and detection (SELD) methods, different acoustic environments in the training and test sets may result in large performance differences in the validation and evaluation stages. Different environments, such as different sizes of rooms, different reverberation times, and different background noise, may be reasons for a learning-based system to fail. On the other hand, acquiring annotated spatial sound event samples, which include onset and offset time stamps, class types of sound events, and direction-of-arrival (DOA) of sound sources is very expensive. In addition, deploying a SELD system in a new environment often poses challenges due to time-consuming training and fine-tuning processes. To address these issues, we propose Meta-SELD, which applies meta-learning methods to achieve fast adaptation to new environments. More specifically, based on Model Agnostic Meta-Learning (MAML), the proposed Meta-SELD aims to find good meta-initialized parameters to adapt to new environments with only a small number of samples and parameter updating iterations. We can then quickly adapt the meta-trained SELD model to unseen environments. Our experiments compare fine-tuning methods from pre-trained SELD models with our Meta-SELD on the Sony-TAU Realistic Spatial Soundscapes 2023 (STARSSS23) dataset. The evaluation results demonstrate the effectiveness of Meta-SELD when adapting to new environments.Comment: Submitted to DCASE 2023 Worksho

Morphology and Molecular Analysis of Moesziomyces antarcticus Isolated From the Blood Samples of a Chinese Patient

Objective: To identify the pathogen causing fungemia in a Chinese patient and describe its morphological and molecular characterizes.Methods: Samples of central and peripheral venous blood were collected for blood culture. Morphology and drug sensitivities of the isolated yeast-like fungus were analyzed. rDNA sequencing and molecular phylogenetic analysis of the isolated strains were performed using DNAMAN and MEGA software.Results: A strain of yeast-like fungi was repeatedly isolated from blood samples of a Chinese patient. The isolates grew well on sabouraud medium broth plate. The colonies were smooth and round at 28°C, and were of rough surface and irregular shape at 35°C. Molecular phylogenetic trees constructed based on the internal transcribed spacer (ITS) and D1/D2 domains of 28S rDNA gene demonstrated the isolated yeast-like fungus was Moesziomyces antarcticus. Drug susceptibility test showed that this isolated M. antarcticus was resistant or had relatively low susceptibility to flucytosine, fluconazole, voriconazole, and itraconazole, and only sensitive to amphotericin.Conclusion: This study provided more information for the molecular and morphology characteristics of M. antarcticus and reviewed the species information of Moesziomyces associated with human infections, which will contribute to the identification and diagnosis of Moesziomyces infections

Bioinspired bright noniridescent photonic melanin supraballs

Structural colors enable the creation of a spectrumof nonfading colors without pigments, potentially replacing toxic metal oxides and conjugated organic pigments. However, significant challenges remain to achieve the contrast needed for a complete gamut of colors and a scalable process for industrial application. We demonstrate a feasible solution for producing structural colors inspired by bird feathers. We have designed core-shell nanoparticles using high-refractive index (RI) (similar to 1.74) melanin cores and low-RI (similar to 1.45) silica shells. The design of these nanoparticles was guided by finite-difference time-domain simulations. These nanoparticles were self-assembled using a one-pot reverse emulsion process, which resulted in bright and noniridescent supraballs. With the combination of only two ingredients, synthetic melanin and silica, we can generate a full spectrum of colors. These supraballs could be directly added to paints, plastics, and coatings and also used as ultraviolet-resistant inks or cosmetics

Structural Color Production in Melanin-based Disordered Colloidal Nanoparticle Assemblies in Spherical Confinement

Melanin is a ubiquitous natural pigment that exhibits broadband absorption and high refractive index. Despite its widespread use in structural color production, how the absorbing material, melanin, affects the generated color is unknown. Using a combined molecular dynamics and finite-difference time-domain computational approach, this paper investigates structural color generation in one-component melanin nanoparticle-based supra-assemblies (called supraballs) as well as binary mixtures of melanin and silica (non-absorbing) nanoparticle-based supraballs. Experimentally produced one-component melanin and one-component silica supraballs, with thoroughly characterized primary particle characteristics using neutron scattering, produce reflectance profiles similar to the computational analogues, confirming that the computational approach correctly simulates both absorption and multiple scattering from the self-assembled nanoparticles. These combined approaches demonstrate that melanin's broadband absorption increases the primary reflectance peak wavelength, increases saturation, and decreases lightness factor. In addition, the dispersity of nanoparticle size more strongly influences the optical properties of supraballs than packing fraction, as evidenced by production of a larger range of colors when size dispersity is varied versus packing fraction. For binary melanin and silica supraballs, the chemistry-based stratification allows for more diverse color generation and finer saturation tuning than does the degree of mixing/demixing between the two chemistries.Comment: 40 pages, Figure

Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-based Supraballs using Combined Experimental and Simulation Techniques

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. Here, we use a computational approach to first reconstruct the nanoparticles' assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.Comment: 14 pages, 3 figures, 1 ToC figur

Salivary and fecal microbiota: potential new biomarkers for early screening of colorectal polyps

ObjectiveGut microbiota plays an important role in colorectal cancer (CRC) pathogenesis through microbes and their metabolites, while oral pathogens are the major components of CRC-associated microbes. Multiple studies have identified gut and fecal microbiome-derived biomarkers for precursors lesions of CRC detection. However, few studies have used salivary samples to predict colorectal polyps. Therefore, in order to find new noninvasive colorectal polyp biomarkers, we searched into the differences in fecal and salivary microbiota between patients with colorectal polyps and healthy controls.MethodsIn this case–control study, we collected salivary and fecal samples from 33 patients with colorectal polyps (CP) and 22 healthy controls (HC) between May 2021 and November 2022. All samples were sequenced using full-length 16S rRNA sequencing and compared with the Nucleotide Sequence Database. The salivary and fecal microbiota signature of colorectal polyps was established by alpha and beta diversity, Linear discriminant analysis Effect Size (LEfSe) and random forest model analysis. In addition, the possibility of microbiota in identifying colorectal polyps was assessed by Receiver Operating Characteristic Curve (ROC).ResultsIn comparison to the HC group, the CP group’s microbial diversity increased in saliva and decreased in feces (p < 0.05), but there was no significantly difference in microbiota richness (p > 0.05). The principal coordinate analysis revealed significant differences in β-diversity of salivary and fecal microbiota between the CP and HC groups. Moreover, LEfSe analysis at the species level identified Porphyromonas gingivalis, Fusobacterium nucleatum, Leptotrichia wadei, Prevotella intermedia, and Megasphaera micronuciformis as the major contributors to the salivary microbiota, and Ruminococcus gnavus, Bacteroides ovatus, Parabacteroides distasonis, Citrobacter freundii, and Clostridium symbiosum to the fecal microbiota of patients with polyps. Salivary and fecal bacterial biomarkers showed Area Under ROC Curve of 0.8167 and 0.8051, respectively, which determined the potential of diagnostic markers in distinguishing patients with colorectal polyps from controls, and it increased to 0.8217 when salivary and fecal biomarkers were combined.ConclusionThe composition and diversity of the salivary and fecal microbiota were significantly different in colorectal polyp patients compared to healthy controls, with an increased abundance of harmful bacteria and a decreased abundance of beneficial bacteria. A promising non-invasive tool for the detection of colorectal polyps can be provided by potential biomarkers based on the microbiota of the saliva and feces

Mechanism of Structural Colors in Binary Mixtures of Nanoparticle-based Supraballs

Inspired by structural colors in avian species, various synthetic strategies have been developed to produce non-iridescent, saturated colors using nanoparticle assemblies. Mixtures of nanoparticles varying in particle chemistry (or complex refractive indices) and particle size have additional emergent properties that impact the color produced. For such complex multi-component systems, an understanding of assembled structure along with a robust optical modeling tool can empower scientists to perform intensive structure-color relationship studies and fabricate designer materials with tailored color. Here, we demonstrate how we can reconstruct the assembled structure from small-angle scattering measurements using the computational reverse-engineering analysis for scattering experiments (CREASE) method and then use the reconstructed structure in finite-difference time-domain (FDTD) calculations to predict color. We successfully, quantitatively predict experimentally observed color in mixtures containing strongly absorbing melanin nanoparticles and demonstrate the influence of a single layer of segregated nanoparticles on color produced. The versatile computational approach presented in this work is useful for engineering synthetic materials with desired colors without laborious trial and error experiments.Comment: 23 Pages, 5 Figures, 1 ToC Figur

Ferret and Pig Models of Cystic Fibrosis: Prospects and Promise for Gene Therapy

Large animal models of genetic diseases are rapidly becoming integral to biomedical research as technologies to manipulate the mammalian genome improve. The creation of cystic fibrosis (CF) ferrets and pigs is an example of such progress in animal modeling, with the disease phenotypes in the ferret and pig models more reflective of human CF disease than mouse models. The ferret and pig CF models also provide unique opportunities to develop and assess the effectiveness of gene and cell therapies to treat affected organs. In this review, we examine the organ disease phenotypes in these new CF models and the opportunities to test gene therapies at various stages of disease progression in affected organs. We then discuss the progress in developing recombinant replication-defective adenoviral, adeno-associated viral, and lentiviral vectors to target genes to the lung and pancreas in ferrets and pigs, the two most affected organs in CF. Through this review, we hope to convey the potential of these new animal models for developing CF gene and cell therapies