Public health system sustainability assessment by Gaidai hypersurface approach.

BACKGROUND: to determine extreme cardiovascular and cancer diseases deathrate risks at any time in any region of interest. DESIGN: Apply modern novel statistical methods to raw clinical surveillance data. METHODS: multi-centre, population-based, medical survey data-based bio statistical approach. For this study, cardiovascular and cancer diseases annual recorded deaths numbers in all 195 world countries have been selected, constituting 390D (390-dimensional) biosystem. It is challenging to model such phenomena. RESULTS: this paper describes a novel bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient timelapse. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the advantage of dealing efficiently with extensive regional dimensionality. The suggested methodology coped with this challenge well. CONCLUSIONS: the suggested methodology may be used in various public health applications, based on raw clinical survey data.

COVID-19 spatio-temporal forecast in England.

The 2019 novel coronavirus disease (COVID-19, SARS-CoV-2) being contagious illness with allegedly high potential for global transmission, low potential for morbidity and fatality, and certain impact on global public health. This study describes a novel bio-system reliability spatio-temporal approach, that is especially appropriate for multi-regional environmental, biological and health systems and that, when observed for a sufficient amount of time, produces a reliable long-term forecast of the likelihood of an outbreak of a highly pathogenic virus. Conventional statistical approaches do not have the benefit of effectively handling large regional dimensionality and cross-correlation between various regional observations. These methods deal with temporal observations of multi-regional phenomena. The most afflicted districts of England's COVID-19 daily counts of reported patients were used for this investigation. In order to extract the essential data from dynamically observed patient numbers while taking into consideration pertinent geographical mapping, this study utilized recently developed bio-reliability methodology. With the use of the spatio-temporal approach described in this study, future epidemic outbreak risks for multi-regional public health systems may be predicted with sufficient accuracy.

Floating wind turbines structural details fatigue life assessment.

Fatigue damage prediction is essential for safety of contemporary offshore energy industrial projects, like offshore wind turbines, that are to be designed for sufficiently long operational period of time, with minimal operational disruptions. Offshore structures being designed to withstand environmental loadings due to winds and waves. Due to accumulated fatigue damage, offshore wind floating turbines may develop material cracks in their critical locations sooner than expected. Dataset needed for an accurate assessment of fatigue damage may be produced by either extensive numerical modeling, or direct measurements. However, in reality, temporal length of the underlying dataset being typically too short to provide an accurate calculation of direct fatigue damage and fatigue life. Hence, the objective of this work is to contribute to the development of novel fatigue assessment methods, making better use of limited underlying dataset. In this study, in-situ environmental conditions were incorporated to assess offshore FWT tower base stresses; then structural cumulative fatigue damage has been assessed. Novel deconvolution extrapolation method has been introduced in this study, and it was shown to be able to accurately predict long-term fatigue damage. The latter technique was validated, using artificially reduced dataset, and resulted in fatigue damage that was shown to be close to the damage, calculated from the full original underlying dataset. Recommended method has been shown to utilize available dataset much more efficiently, compared to direct fatigue estimation. Accurate fatigue assessment of offshore wind turbine structural characteristics is essential for structural reliability, design, and operational safety.

Meta-Structure Hull Design with Periodic Layered Phononic Crystals Theory for Wide-Band Low-Frequency Sound Insolation.

The hulls of marine vehicles are generally very effective at attenuating airborne acoustic noise generated by their powertrains. However, conventional hull designs are generally not very effective at attenuating wide-band low-frequency noise. Meta-structure concepts offer an opportunity for the design of laminated hull structures tailored to address this concern. This research proposes a novel meta-structure laminar hull concept using periodic layered Phononic crystals to optimize the sound insolation performance on the air-solid side of the hull structure. The acoustic transmission performance is evaluated using the transfer matrix, the acoustic transmittance, and the tunneling frequencies. The theoretical and numerical models for a proposed thin solid-air sandwiched meta-structure hull indicate ultra-low transmission within a 50-to-800 Hz frequency band and with two predicted sharp tunneling peaks. The corresponding 3D-printed sample experimentally validates the tunneling peaks at 189 Hz and 538 Hz, with 0.38 and 0.56 transmission magnitudes, respectively, with the frequency band between those values showing wide-band mitigation. The simplicity of this meta-structure design provides a convenient way to achieve acoustic band filtering of low frequencies for marine engineering equipment and, accordingly, an effective technique for low-frequency acoustic mitigation.

Oil tanker under ice loadings.

As a result of global warming, the area of the polar pack ice is diminishing, making merchant travel more practical. Even if Arctic ice thickness reduced in the summer, fractured ice is still presenting operational risks to the future navigation. The intricate process of ship-ice interaction includes stochastic ice loading on the vessel hull. In order to properly construct a vessel, the severe bow forces that arise must be accurately anticipated using statistical extrapolation techniques. This study examines the severe bow forces that an oil tanker encounters when sailing in the Arctic Ocean. Two stages are taken in the analysis. Then, using the FEM program ANSYS/LS-DYNA, the oil tanker bow force distribution is estimated. Second, in order to estimate the bow force levels connected with extended return periods, the average conditional exceedance rate approach is used to anticipate severe bow forces. The vessel's itinerary was planned to take advantage of the weaker ice. As a result, the Arctic Ocean passage took a meandering route rather than a linear one. As a result, the ship route data that was investigated was inaccurate with regard to the ice thickness data encountered by a vessel yet skewed with regard to the ice thickness distribution in the region. This research intends to demonstrate the effective application of an exact reliability approach to an oil tanker with severe bow forces on a particular route.

Offshore tethered platform springing response statistics.

This paper demonstrates the validity of the Naess-Gadai method for extrapolating extreme value statistics of second-order Volterra series processes through application on a representative model of a deep water small size tension leg platform (TLP), with specific focus on wave sum frequency effects affecting restrained modes: heave, roll and pitch. The wave loading was estimated from a second order diffraction code WAMIT, and the stochastic TLP structural response in a random sea state was calculated exactly using Volterra series representation of the TLP corner vertical displacement, chosen as a response process. Although the wave loading was assumed to be a second order (non-linear) process, the dynamic system was modelled as a linear damped mass-spring system. Next, the mean up-crossing rate based extrapolation method (Naess-Gaidai method) was applied to calculate response levels at low probability levels. Since exact solution was available via Volterra series representation, both predictions were compared in this study, namely the exact Volterra and the approximate one. The latter gave a consistent way to estimate efficiency and accuracy of Naess-Gaidai extrapolation method. Therefore the main goal of this study was to validate Naess-Gaidai extrapolation method by available analytical-based exact solution. Moreover, this paper highlights limitations of mean up-crossing rate based extrapolation methods for the case of narrow band effects, such as clustering, typically included in the springing type of response.

Novel methods for wind speeds prediction across multiple locations.

This article provides two unique methodologies that may be coupled to study the dependability of multidimensional nonlinear dynamic systems. First, the structural reliability approach is well suited for multidimensional environmental and structural reactions and is either measured or numerically simulated over sufficient time, yielding lengthy ergodic time series. Second, a unique approach to predicting extreme values has technical and environmental implications. In the event of measurable environmental loads, it is also feasible to calculate the probability of system failure, as shown in this research. In addition, traditional probability approaches for time series cannot cope effectively with the system's high dimensionality and cross-correlation across dimensions. It is common knowledge that wind speeds represent a complex, nonlinear, multidimensional, and cross-correlated dynamic environmental system that is always difficult to analyze. Additionally, global warming is a significant element influencing ocean waves throughout time. This section aims to demonstrate the efficacy of the previously mentioned technique by applying a novel method to the Norwegian offshore data set for the greatest daily wind cast speeds in the vicinity of the Landvik wind station. This study aims to evaluate the state-of-the-art approach for extracting essential information about the extreme reaction from observed time histories. The approach provided in this research enables the simple and efficient prediction of failure probability for the whole nonlinear multidimensional dynamic system.

MicroRNA-378 inhibits cell growth and enhances L-OHP-induced apoptosis in human colorectal cancer.

MicroRNAs (miRNAs) are small noncoding RNAs that participate in a variety of biological processes, and dysregulation of miRNAs is widely associated with cancer development and progression. MiR-378 is frequently downregulated in colorectal cancer (CRC) and colorectal cell lines; however, it has high serum levels. Bioinformatics analysis further deduced that CDC40 is a potential target of miR-378, and luciferase reporter assays confirmed the direct regulation of CDC40 by miR-378. CDC40 plays a key role in cell cycle progression through G1/S and G2/M and pre-mRNA splicing. Subsequently, we determined that miR-378 inhibits cell growth and the G1/S transition in CRC cells and that these effects were CDC40-dependent. Finally, miR-378 increased cell apoptosis induced by the chemotherapeutic drug L-OHP. Our data highlight the potential application of miR-378 as a tumor suppressor for CRC therapy and overcoming chemoresistance, and it may also be a potential tumor marker for CRC prognosis.

B7-H1 and B7-H4 expression in colorectal carcinoma: correlation with tumor FOXP3(+) regulatory T-cell infiltration.

B7-H1 and B7-H4 are newly discovered members of the B7-CD28 family. They can inhibit T cell activation and proliferation and regulate T cell immune response negatively. Both B7-H1 and B7-H4 are expressed in many tumors and are classified as co-inhibitors of cell-mediated immunity. FOXP3(+) regulatory T cells (Tregs) play an important role in the maintenance of tumor immunity tolerance. However, the implication of B7-H1 and B7-H4 expression and their interaction with Tregs infiltration in colorectal cancer are unknown. The present study aimed to determine the expression of B7-H1 and B7-H4 as well as Tregs infiltration in colorectal cancer and to explore the clinical and pathological implication of suppressor immune cells and molecules. Frozen sections and immunohistochemical assay were undertaken to assess B7-H1, B7-H4 expression and Tregs infiltration in fresh specimens collected from 56 patients with colorectal carcinoma. The results showed that expression of B7-H1 and B7-H4 in colorectal carcinoma tissues was significantly higher than in adjacent normal mucosa (P<0.001). B7-H1 expression was positively correlated to the infiltration depth, lymph node metastasis and advanced Duke's stage (P<0.05, P<0.05 and P<0.05, respectively), whereas B7-H4 expression was positively related to the infiltration depth and lymph node metastasis (P<0.01 and P<0.05, respectively). Furthermore, Tregs infiltration was more frequent in tumor tissue than in adjacent normal mucosa and was associated with poor differentiation and positive lymph node metastasis (P<0.01, and P<0.01, respectively). The statistical analysis indicated a significant correlation between Tregs infiltration and B7-H1 or B7-H4 expression respectively. These results suggest that over-expression of B7-H1 and B7-H4 has stronger prognostic significance and promote tumor tolerance, and they might contribute to Tregs development in the colorectal carcinoma tolerogenic milieu.