Future world cancer death rate prediction

Cancer is a worldwide illness that causes significant morbidity and death and imposes an immense cost on global public health. Modelling such a phenomenon is complex because of the non-stationarity and complexity of cancer waves. Apply modern novel statistical methods directly to raw clinical data. To estimate extreme cancer death rate likelihood at any period in any location of interest. Traditional statistical methodologies that deal with temporal observations of multi-regional processes cannot adequately deal with substantial regional dimensionality and cross-correlation of various regional variables. Setting: multicenter, population-based, medical survey data-based biostatistical approach. Due to the non-stationarity and complicated nature of cancer, it is challenging to model such a phenomenon. This paper offers a unique bio-system dependability technique suited for multi-regional environmental and health systems. When monitored over a significant period, it yields a reliable long-term projection of the chance of an exceptional cancer mortality rate. Traditional statistical approaches dealing with temporal observations of multi-regional processes cannot effectively deal with large regional dimensionality and cross-correlation between multiple regional data. The provided approach may be employed in numerous public health applications, depending on their clinical survey data.publishedVersio

Prediction of extreme cargo ship panel stresses by using deconvolution

Extreme value predictions typically originate from certain functional classes of statistical distributions to fit the data and are subsequently extrapolated. This paper describes an alternative method for extrapolation that is based on the intrinsic properties of the data set itself and that does not pre-assume any extrapolation functional class. The proposed novel extrapolation method can be utilized in engineering design. To illustrate this, this study uses two examples to showcase the advantages of the proposed method. The first example used synthetic data from a non-linear Duffing oscillator to illustrate the new method. The second example was an actual container ship sailing between Europe and America and experiencing large deck panel stresses in severe weather. In this example, actual onboard measured data were used in the present study. This example represents a real and physical case that is challenging to model due to the non-stationary and highly non-linear natures of the wave-ship load responses. This is especially so in the case of extreme responses, where the roles of second and higher-order responses tend to be more prominent and have higher contributions. The prediction accuracy of the proposed method was also validated versus the Naess–Gaidai extrapolation method. Finally, this study discusses new methods for generic smoothing of distribution tail irregularities due to underlying scarcity in the data set.publishedVersio

Targeting Integrin-β1 Impedes Cytokine-Induced Osteoclast Differentiation: A Potential Pharmacological Intervention in Pathological Osteolysis

Purpose: To examine whether integrin-β1 is essential for osteoclast differentiation and function and if it can be targeted for pharmacological intervention in pathological osteolysis.Methods: Control and Integrin-β1 knockdown RAW 264.7 cells were treated with receptor activator of nuclear factor kappa-B (RANKL) or TNF-α and evaluated for osteoclast differentiation. Osteoclast differentiation and function were evaluated by marker protein analysis, tartrate-resistant acid phosphatase (TRAP) and resorption assays. Furthermore, downstream molecular signaling analysis was probed using small molecule inhibitors and blocking antibodies, and evaluated by immunoblotting.Results: Integrin-β1 knockdown cells showed reduced osteoclast differentiation following TNF-α treatment while no change was seen after RANKL treatment (p < 0.05). Immunoblot-based molecular signaling analysis showed involvement of MAPK kinase signaling in mediating TNF-α/integrin-β1- induced osteoclastogenesis. Finally, when MAPK kinase inhibitor (2.5 and 5 μM; p < 0.05) and integrin- β1 blocking antibody (2.5 and 5 μg/mL; p < 0.05) was used to specifically attenuate TNF-α induced osteoclastogenesis, no change was observed in RANKL-induced osteoclast formation.Conclusion: The data obtained highlight the role of integrin-β1 in TNF-α-induced osteoclastogenesis, but not in RANKL pathway. Given that, inflammatory cytokine secretions such as TNF-α are progressively implicated in pathological osteolysis, targeting this pathway may attenuate osteolysis in pathological bone tissues.Keywords: Osteoclast differentiation, Integrin-β1, Receptor activator of nuclear factor kappa-B, TNFalpha, Mitogen activated protein kinase, Cytokines, Skeletal diseas

Expression pattern and activity of six glutelin gene promoters in transgenic rice*

The shortage of strong endosperm-specific expression promoters for driving the expression of recombinant protein genes in cereal endosperm is a major limitation in obtaining the required level and pattern of expression. Six promoters of seed storage glutelin genes (GluA-1, GluA-2, GluA-3, GluB-3, GluB-5, and GluC) were isolated from rice (Oryza sativa L.) genomic DNA by PCR. Their spatial and temporal expression patterns and expression potential in stable transgenic rice plants were examined with β-glucuronidase (GUS) used as a reporter gene. All the promoters showed the expected spatial expression within the endosperm. The GluA-1, GluA-2, and GluA-3 promoters directed GUS expression mainly in the outer portion (peripheral region) of the endosperm. The GluB-5 and GluC promoters directed GUS expression in the whole endosperm, with the latter expressed almost evenly throughout the whole endosperm, a feature different from that of other rice glutelin gene promoters. The GluB-3 promoter directed GUS expression solely in aleurone and subaleurone layers. Promoter activities examined during seed maturation showed that the GluC promoter had much higher activity than the other promoters. These promoters are ideal candidates for achieving gene expression for multiple purposes in monocot endosperm but avoid promoter homology-based gene silencing. The GluC promoter did not contain the endosperm specificity-determining motifs GCN4, AACA, and the prolamin-box, which suggests the existence of additional regulatory mechanism in determining endosperm specificity

A novel statistical method for long-term coronavirus modelling

Background: Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Methods: Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. Results: This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces. Conclusions: The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.publishedVersio

The Two Phase Transitions of Hydrophobically End-Capped Poly(N-isopropylacrylamide)s in Water

High-sensitivity differential scanning calorimetry (HS-DSC) thermograms of aqueous poly(N-isopropylacrylamide) (PNIPAM) solutions present a sharp unimodal endotherm that signals the heat-induced dehydration/collapse of the PNIPAM chain. Similarly, alpha,omega-di-n-octadecyl-PNIPAM (C18-PN-C18) aqueous solutions exhibit a unimodal endotherm. In contrast, aqueous solutions of alpha,omega-hydrophobically modified PNIPAMs with polycyclic terminal groups, such as pyrenylbutyl (Py-PN-Py), adamantylethyl (Ad-PN-Ad), and azopyridine- (C12-PN-AzPy) moieties, exhibit bimodal thermograms. The origin of the two transitions was probed using microcalorimetry measurements, turbidity tests, variable temperature H-1 NMR (VT-NMR) spectroscopy, and 2-dimensional NOESY experiments with solutions of polymers of molar mass (M-n) from 5 to 20 kDa and polymer concentrations of 0.1 to 3.0 mg/mL. The analysis outcome led us to conclude that the difference of the thermograms reflects the distinct self-assembly structures of the polymers. C18-PN-C18 assembles in water in the form of flower micelles held together by a core of tightly packed n-C18 chains. In contrast, polymers end-tagged with azopyridine, pyrenylbutyl, or adamantylethyl form a loose core that allows chain ends to escape from the micelles, to reinsert in them, or to dangle in surrounding water. The predominant low temperature (T-1) endotherm, which is insensitive to polymer concentration, corresponds to the dehydration/collapse of PNIPAM chains within the micelles, while the higher temperature (T-2) endotherm is attributed to the dehydration of dangling chains and intermicellar bridges. This study of the two phase transitions of telechelic PNIPAM homopolymer highlights the rich variety of morphologies attainable via responsive hydrophobically modified aqueous polymers and may open the way to a variety of practical applications.Peer reviewe

Novel methods for reliability study of multi-dimensional non-linear dynamic systems

This research presents two unique techniques for engineering system reliability analysis of multi-dimensional non-linear dynamic structures. First, the structural reliability technique works best for multi-dimensional structural responses that have been either numerically simulated or measured over a long enough length to produce an ergodic time series. Second, a novel extreme value prediction method that can be used in various engineering applications is proposed. In contrast to those currently used in engineering reliability methodologies, the novel method is easy to use, and even a limited amount of data can still be used to obtain robust system failure estimates. As demonstrated in this work, proposed methods also provide accurate confidence bands for system failure levels in the case of real-life measured structural response. Additionally, traditional reliability approaches that deal with time series do not have the benefit of being able to handle a system's high dimensionality and cross-correlation across several dimensions readily. Container ship that experiences significant deck panel pressures and high roll angles when travelling in bad weather was selected as the example for this study. The main concern for ship transportation is the potential loss of cargo owing to violent movements. Simulating such a situation is difficult since waves and ship motions are non-stationary and complicatedly non-linear. Extreme movements greatly enhance the role of nonlinearities, activating effects of second and higher order. Furthermore, laboratory testing may also be called into doubt due to the scale and the choice of the sea state. Therefore, data collected from actual ships during difficult weather journeys offer a unique perspective on the statistics of ship movements. This work aims to benchmark state-of-the-art methods, making it possible to extract necessary information about the extreme response from available on-board measured time histories. Both suggested methods can be used in combination, making them attractive and ready to use for engineers. Methods proposed in this paper open up possibilities to predict simply yet efficiently system failure probability for non-linear multi-dimensional dynamic structure.publishedVersio

Improving extreme anchor tension prediction of a 10-MW floating semi-submersible type wind turbine, using highly correlated surge motion record

Extreme value prediction of the load-effect responses of complex offshore structures such as the floating wind turbine (FWT) is crucial in ultimate limit state (ULS) design. This paper considers two cases to understand the feasibility of the bivariate correction on the extreme load and motion responses of a 10-MW semi-submersible type FWT. The empirical anchor tension force and surge motion used in this study are obtained from the FAST simulation tool (developed by the National Renewable Energy Laboratory) with the load cases stimulated at under-rated, rated and above rated speeds. Then, the bivariate correction method is applied to model FWT extreme response for a 5-years return period prediction with a 95% confidence interval (CI), based on just 2 min short response record. The proposed methodology permits accurate correction of the bivariate extreme value in case of, for example, corrupted measurement sensor data. Based on the proposed novel method’s performance, it is concluded that the bivariate correction method can offer better robust and precise bivariate predictions of coupled surge motion and anchor tension of the FWT.publishedVersio

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.publishedVersio