Four years of multi-modal odometry and mapping on the rail vehicles

Precise, seamless, and efficient train localization as well as long-term railway environment monitoring is the essential property towards reliability, availability, maintainability, and safety (RAMS) engineering for railroad systems. Simultaneous localization and mapping (SLAM) is right at the core of solving the two problems concurrently. In this end, we propose a high-performance and versatile multi-modal framework in this paper, targeted for the odometry and mapping task for various rail vehicles. Our system is built atop an inertial-centric state estimator that tightly couples light detection and ranging (LiDAR), visual, optionally satellite navigation and map-based localization information with the convenience and extendibility of loosely coupled methods. The inertial sensors IMU and wheel encoder are treated as the primary sensor, which achieves the observations from subsystems to constrain the accelerometer and gyroscope biases. Compared to point-only LiDAR-inertial methods, our approach leverages more geometry information by introducing both track plane and electric power pillars into state estimation. The Visual-inertial subsystem also utilizes the environmental structure information by employing both lines and points. Besides, the method is capable of handling sensor failures by automatic reconfiguration bypassing failure modules. Our proposed method has been extensively tested in the long-during railway environments over four years, including general-speed, high-speed and metro, both passenger and freight traffic are investigated. Further, we aim to share, in an open way, the experience, problems, and successes of our group with the robotics community so that those that work in such environments can avoid these errors. In this view, we open source some of the datasets to benefit the research community

The future of coastal and estuarine modeling: Findings from a workshop

This paper summarizes the findings of a workshop convened in the United States in 2018 to discuss methods in coastal and estuarine modeling and to propose key areas of research and development needed to improve their accuracy and reliability. The focus of this paper is on physical processes, and we provide an overview of the current state-of-the-art based on presentations and discussions at the meeting, which revolved around the four primary themes of parameterizations, numerical methods, in-situ and remote-sensing measurements,and high-performance computing. A primary outcome of the workshop was agreement on the need to reduce subjectivity and improve reproducibility in modeling of physical processes in the coastal ocean. Reduction of subjectivity can be accomplished through development of standards for benchmarks, grid generation, and validation, and reproducibility can be improved through development of standards for input/output, coupling and model nesting, and reporting. Subjectivity can also be reduced through more engagement with the applied mathematics and computer science communities to develop methods for robust parameter estimation anduncertainty quantification. Such engagement could be encouraged through more collaboration between thef orward and inverse modeling communities and integration of more applied math and computer science into oceanography curricula. Another outcome of the workshop was agreement on the need to develop high-resolution models that scale on advanced HPC systems to resolve, rather than parameterize, processes with horizontal scales that range between the depth and the internal Rossby deformation scale. Unsurprisingly,more research is needed on parameterizations of processes at scales smaller than the depth, includingparameterizations for drag (including bottom roughness, bedforms, vegetation and corals), wave breaking, and air–sea interactions under strong wind conditions. Other topics that require significantly more work to better parameterize include nearshore wave modeling, sediment transport modeling, and morphodynamics. Finally, it was agreed that coastal models should be considered as key infrastructure needed to support research, just like laboratory facilities, field instrumentation, and research vessels. This will require a shift in the way proposals related to coastal ocean modeling are reviewed and funded

Synthesis of Carbon Onion and Its Application as a Porous Carrier for Amorphous Drug Delivery

Given the great potential of porous carrier-based drug delivery for stabilising the amorphous form of drugs and enhancing dissolution profiles, this work is focussed on the synthesis and application of carbon onion or onion-like carbon (OLC) as a porous carrier for oral amorphous drug delivery, using paracetamol (PA) and ibuprofen (IBU) as model drugs. Annealing of nanodiamonds at 1100 °C produced OLC with a diamond core that exhibited low cytotoxicity on Caco-2 cells. Solution adsorption followed by centrifugation was used for drug loading and results indicated that the initial concentration of drug in the loading solution needs to be kept below 11.5% PA and 20.7% IBU to achieve complete amorphous loading. Also, no chemical interactions between the drug and OLC could be detected, indicating the safety of loading into OLC without changing the chemical nature of the drug. Drug release was complete in the presence of sodium dodecyl sulphate (SDS) and was faster compared to the pure crystalline drug, indicating the potential of OLC as an amorphous drug carrier

The Effect of the Antimicrobial Peptide Plectasin on the Growth Performance, Intestinal Health, and Immune Function of Yellow-Feathered Chickens

The goal of the study was to test the effects of an antibiotic substitute, plectasin, on the growth performance, immune function, intestinal morphology and structure, intestinal microflora, ileal mucosal layer construction and tight junctions, ileal immune-related cytokines, and blood biochemical indices of yellow-feathered chickens. A total of 1,500 one-day-old yellow-feathered chicks were randomly divided into four dietary treatment groups with five replicates in each group and 75 yellow-feathered chicks in each replication, as follows: basal diet (group A); basal diet supplemented with 10 mg enramycin/kg of diet (group B), basal diet supplemented with 100 mg plectasin/kg of diet (group C), and basal diet supplemented with 200 mg plectasin/kg of diet (group D). It was found that the dietary antimicrobial peptide plectasin could improve the ADG and had better F/G for the overall period of 1–63 days. Dietary plectasin can enhance H9N2 avian influenza virus (AIV) and Newcastle disease virus (NDV) antibody levels of yellow-feathered chickens at 21, and 35 days of age. Dietary plectasin can enhance the intestine structure, inhibit Escherichia coli and proinflammatory cytokines in the ileum, and ameliorate the blood biochemical indices of yellow-feathered chickens at 21 days of age. This study indicates that the antimicrobial peptide plectasin has beneficial effects on the growth performance, intestinal health and immune function of yellow-feathered chickens

ACHIKO-M Database for high myopia analysis and its evaluation

Myopia is the leading public health concern with high prevalence in developed countries. In this paper, we present the ACHIKO-M fundus image database with both myopic and emmetropic cases for high myopia study. The database contains 705 myopic subjects and 151 normal subjects with both left eye and right eye images for each subject. In addition, various clinical data is also available, allowing correlation study of different risk factors. We evaluated two state-of-the-art automated myopia detection algorithms on this database to show how it can be used. Both methods achieve more than 90% accuracy for myopia diagnosis. We will also discuss how ACHIKO-M can be a good database for both scientific and clinical research of myopia

Climate Extremes Dominating Seasonal and Interannual Variations in Carbon Export from the Mississippi River Basinariations in Carbon Export from the Mississippi River Basin

Knowledge about the annual and seasonal patterns of organic and inorganic carbon (C) exports from the major rivers of the world to the coastal ocean is essential for our understanding and potential management of the global C budget so as to limit anthropogenic modification of global climate. Unfortunately our predictive understanding of what controls the timing, magnitude, and quality of C export is still rudimentary. Here we use a process-based coupled hydrologic/ecosystem biogeochemistry model (the Dynamic Land Ecosystem Model) to examine how climate variability and extreme events, changing land use, and atmospheric chemistry have affected the annual and seasonal patterns of C exports from the Mississippi River basin to the Gulf of Mexico. Our process-based simulations estimate that the average annual exports of dissolved organic C (DOC), particulate organic C (POC), and dissolved inorganic C (DIC) in the 2000s were 2.6 ± 0.4 Tg C yr−1, 3.4 ± 0.3 Tg C yr−1, and 18.8 ± 3.4 Tg C yr−1, respectively. Although land use change was the most important agent of change in C export over the past century, climate variability and extreme events (such as flooding and drought) were primarily responsible for seasonal and interannual variations in C export from the basin. The maximum seasonal export of DIC occurred in summer while for DOC and POC the maximum occurred in winter. Relative to the 10 year average (2001–2010), our modeling analysis indicates that the years of maximal and minimal C export cooccurred with wet and dry years (2008: 32% above average and 2006: 32% below average). Given Intergovernmental Panel on Climate Change-predicted changes in climate variability and the severity of rain events and droughts of wet and dry years for the remainder of the 21st century, our modeling results suggest major changes in the riverine link between the terrestrial and oceanic realms, which are likely to have a major impact on C delivery to the coastal ocean

Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations

Due to growing throughput and shrinking cost, massively parallel sequencing is rapidly becoming an attractive alternative to microarrays for the genome-wide study of gene expression and copy number alterations in primary tumors. The sequencing of transcripts (RNA-Seq) should offer several advantages over microarray-based methods, including the ability to detect somatic mutations and accurately measure allele-specific expression. To investigate these advantages we have applied a novel, strand-specific RNA-Seq method to tumors and matched normal tissue from three patients with oral squamous cell carcinomas. Additionally, to better understand the genomic determinants of the gene expression changes observed, we have sequenced the tumor and normal genomes of one of these patients. We demonstrate here that our RNA-Seq method accurately measures allelic imbalance and that measurement on the genome-wide scale yields novel insights into cancer etiology. As expected, the set of genes differentially expressed in the tumors is enriched for cell adhesion and differentiation functions, but, unexpectedly, the set of allelically imbalanced genes is also enriched for these same cancer-related functions. By comparing the transcriptomic perturbations observed in one patient to his underlying normal and tumor genomes, we find that allelic imbalance in the tumor is associated with copy number mutations and that copy number mutations are, in turn, strongly associated with changes in transcript abundance. These results support a model in which allele-specific deletions and duplications drive allele-specific changes in gene expression in the developing tumor

Diamond based materials and nanostructures for advanced functional applications

This doctoral thesis is dedicated to the multidisciplinary exploration of the diverse applications of diamonds, harnessing their exceptional physical and chemical properties. Diamonds, characterized by their unique attributes, exhibit immense potential across various scientific domains and industrial sectors. The research in this thesis commenced with an extensive investigation into diamond growth technique s, with a primary focus on chemical vapor deposition (CVD). Through this method, we succeeded in expanding the spectrum of synthesized diamonds, both in terms of quality and size, thereby opening up new avenues for their utilization across a myriad of appl ications. The outcomes of this research have significantly broadened the applicability of diamonds in diverse fields such as electronics, optics, thermal management, life sciences, and materials science. Subsequently, our attention turned towards the devel opment of marine antibacterial properties. By scrutinizing the nanostructures present on diamond surfaces, we embarked on an exploration of their potential deployment in nanoelectronics devices, biomedicine, and material processing. This research is primar ily geared towards enhancing the antibacterial attributes of diamonds, thereby catering to the stringent demands of biomedical applications. Our efforts are directed at mitigating infection risks, preserving the sterility of medical equipment, averting cro ss contamination, and ushering in the era of highly sensitive biosensors and diagnostic tools.Furthermore, we have delved into the realm of diamond thermoelectric properties. Despite diamonds' inherent high thermal conductivity, which historically posed c hallenges for their use in thermoelectric applications, we have endeavored to enhance their thermoelectric performance through innovative physical modification methodologies. Leveraging the unique material characteristics of diamonds, we have unlocked thei r potential for extended longevity and stability in comparison to other thermoelectric materials. This achievement translates into reduced maintenance requirements, lower replacement frequencies, and ultimately, cost savings. Moreover, diamonds' steadfast stability equips them to maintain peak performance even in the harshest of environments, such as aerospace and energy conversion systems. In summation, this doctoral thesis undertakes a comprehensive exploration of diamonds' attributes, encompassing growth methodologies, marine antibacterial applications, and thermoelectric properties. Our research not only augments the scientific understanding of diamonds but also fosters innovation and paves the way for their diverse applications across several sectors.</p

Enhancement of the thermoelectric performance of (BiSb)2Te3 films by single target sputtering

In this study, (BiSb) 2Te3 films were deposited onto a glass substrate at 300 °C using radio frequency (RF) sputtering at various growth conditions. The effects of RF power, chamber gas pressure, and annealing temperature on the thermoelectric properties of the deposited films were investigated. An increase in the annealing temperature was found to enhance both the deposition rate and grain size. After optimizing the growth conditions and applying further annealing treatment, thin films grown at higher RF power exhibited higher electrical conductivity, attributable to an increase in carrier concentration. Additionally, films grown under 37.5 W RF power demonstrated an enhancement in the Seebeck coefficient, leading to a maximum power factor. The deposition chamber's base pressure was 10−6 mbar, and the optimal thermoelectric performance was achieved in the film grown under 0.04 mbar Ar+ partial pressure

A Cloud-Free, Satellite-Derived, Sea Surface Temperature Analysis for the West Florida Shelf

Clouds are problematic in using Advanced Very High Resolution Radiometer (AVHRR) imagery for describing sea surface temperature (SST). The Tropical Rainfall Measuring Mission Microwave Imager (TMI) observes SST through clouds, providing daily, 1/4° maps under all weather conditions excepting rain. A TMI limitation, however, is coarse resolution. Optimal interpolation (OI) is used to generate a cloud-free, 5-km, daily SST analysis for the West Florida Shelf (WFS) by merging the high-resolution (cloud-covered) AVHRR with the coarse-resolution (cloud-free) TMI SST products. Comparisons with in-situ data show good agreements. Given large spatial gradients by coastal ocean processes, this regional analysis has advantage over the global, weekly, 1° Reynolds SST. A 5-year (1998-2002) OI SST analysis is diagnosed using Empirical Orthogonal Functions. The first two modes represent annual cycles, one by surface heat flux and another by shelf circulation dynamics