A performance degradation model of nitrile butadiene rubber (NBR) O-rings for hydrogen permeation effects under high-pressure.

The integration of molecular chain changes on a microscopic scale to achieve macroscopic performance is crucial in degradation processes concerning O-ring seals. Nonetheless, a comprehensive and compelling mathematical model that can describe molecular chains' material properties and macroscopic material properties simultaneously for O-rings under high-pressure conditions is yet to be established. In this paper, we propose a degradation model based on viscoelasticity and molecular chain statistics for hydrogen permeation. The proposed model aims to establish the relationship between the material molecular chains and macroscopic material properties, with a primary focus on accurately recognizing the performance degradation process of rubber sealing rings. We verify the model's reliability through uniaxial tensile strength experiments and high-pressure hydrogen immersion experiments, respectively. Predictions of the model exhibit favorable conformity with the experimental data concerning the above phenomena. Furthermore, we derive the number of molecular chains and maximum strain of the degradation process. Based on the similarity of the degradation process's descent, it is plausible to speculate that NBR properties' degradation can be characterized by the average number of molecular chains.

Carbon Storage Tanker Lifetime Assessment.

CO2 capture and storage (CCS) is an important strategy to reduce global CO2 emissions. This work presents both cutting-edge carbon storage tanker design, as well as novel reliability method making possible to extract useful information about the lifespan distribution of carbon capture systems from their recorded time history. The method outlined may be applied on more complex sustainable systems that are exposed to environmental stresses throughout the whole period of their planned service life. The latter is of paramount importance at the design stage for complex engineering systems. Novel design for CCS system is discussed and accurate numerical simulation results are used to apply suggested novel reliability methodology. Furthermore, traditional reliability approaches that deal with complex energy systems are not well suited for handling high dimensionality and cross-correlation between various system components of innovative dynamic CO2 storage subsea shuttle tanker. This study has two distinctive key features: the state of art CCS design concept, and the novel general purpose reliability method, recently developed by authors, and particularly suitable for operational safety study of complex energy systems.

Systematically Study the Tensile and Compressive Behaviors of Diamond-like Carbon.

It is important to understand the mechanical properties of diamond-like carbon (DLC) for use not only in frictionand wear-resistant coatings, but also in vibration reduction and damping increase at the layer interfaces. However, the mechanical properties of DLC are influenced by the working temperature and its density, and the applications of DLC as coatings are limited. In this work, we systematically studied the deformation behaviors of DLC under different temperatures and densities using compression and tensile testing of DLC by molecular dynamics (MD) methods. In our simulation results, the values of tensile stress and compressive stress decreased and tensile strain and compressive strain increased as the temperature increased from 300 K to 900 K during both tensile and compressive processes, indicating that the tensile stress and tensile strain depend on the temperature. During the tensile simulation, Young's modulus of DLC models with different densities had a different sensitivity to the increase in temperature, and the DLC model with a high density was more sensitive than that with a low density, which was not seen in the compression process. We conclude that the Csp3-Csp2 transition leads to tensile deformation, while the Csp2-Csp3 transition and relative slip dominate compressive deformation.

Gaidai-Xing reliability method validation for 10-MW floating wind turbines.

In contrast to well-known bivariate statistical approach, which is known to properly forecast extreme response levels for two-dimensional systems, the research validates innovative structural reliability method, which is particularly appropriate for multi-dimensional structural responses. The disadvantage of dealing with large system dimensionality and cross-correlation across multiple dimensions is not a benefit of traditional dependability approaches that deal with time series. Since offshore constructions are built to handle extremely high wind and wave loads, understanding these severe stresses is essential, e.g. wind turbines should be built and operated with the least amount of inconvenience. In the first scenario, the blade root flapwise bending moment is examined, whereas in the second, the tower bottom fore-aft bending moment is examined. The FAST simulation program was utilized to generate the empirical bending moments for this investigation with the load instances activated at under-rated, rated, and above-rated speeds. The novel reliability approach, in contrast to conventional reliability methods, does not call for the study of a multi-dimensional reliability function in the case of numerical simulation. As demonstrated in this work, it is now possible to assess multi-degree-of-freedom nonlinear system failure probability, in the case when only limited system measurements are available.

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.

Suppression of hepatocellular carcinoma by Ulva lactuca ulvan via gut microbiota and metabolite interactions.

INTRODUCTION: Ulva lactuca polysaccharide (ULP) is green algae extract with numerous biological activities, including anticoagulant, anti-inflammatory, and antiviral effects. However, the inhibitory ability of ULP in the development of hepatocellular carcinoma warrants further studies. OBJECTIVES: To elucidate the anti-tumor mechanism of ULP action and evaluate its regulatory effect on gut microbiota and metabolism in H22 hepatocellular carcinoma tumor-bearing mice. METHODS: An H22 tumor-bearing mouse model was established by subcutaneously injecting H22 hepatoma cells. The gut microbiota composition in cecal feces was assessed and subjected to untargeted metabolomic sequencing. The antitumor activity of ULP was verified further by western blot, RT-qPCR, and reactive oxygen species (ROS) assays. RESULTS: Administration of ULP alleviated tumor growth by modulating the compositions of the gut microbial communities (Tenericutes, Agathobacter, Ruminiclostridium, Parabacteroides, Lactobacillus, and Holdemania) and metabolites (docosahexaenoic acid, uric acid, N-Oleoyl Dopamine, and L-Kynurenine). Mechanistically, ULP promoted ROS production by inhibiting the protein levels of JNK, c-JUN, PI3K, Akt, and Bcl-6, thereby delaying the growth of HepG2 cells. CONCLUSION: ULP attenuates tumor growth in H22 tumor-bearing mice by modulating gut microbial composition and metabolism. ULP inhibits tumor growth mainly by promoting ROS generation.

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.

Improving extreme offshore wind speed prediction by using deconvolution.

This study proposes an innovative method for predicting extreme values in offshore engineering. This includes and is not limited to environmental loads due to offshore wind and waves and related structural reliability issues. Traditional extreme value predictions are frequently constructed using certain statistical distribution functional classes. The proposed method differs from this as it does not assume any extrapolation-specific functional class and is based on the data set's intrinsic qualities. To demonstrate the method's effectiveness, two wind speed data sets were analysed and the forecast accuracy of the suggested technique has been compared to the Naess-Gaidai extrapolation method. The original batch of data consisted of simulated wind speeds. The second data related to wind speed was recorded at an offshore Norwegian meteorological station.

Synthesis of RGO/Cu@ FeAl2O4 Composites and Its Applications in Electromagnetic Microwave Absorption Coatings.

In order to satisfy the requirements of wide frequency bands, the lightweight and strong absorption for the electromagnetic wave absorbing materials, a uniform mixture of FeAl2O4 with RGO/Cu (reduction graphene oxide, RGO) was obtained by the mechanical mixing method, and composite coating was obtained by plasma spraying. The addition of RGO/Cu into FeAl2O4 is conducive to improve the dielectric properties and the impedance matching performance of spinel. When the RGO/Cu composite powders are doped by 10 wt.%, the reflection loss at 15 GHz is -16 dB and the absorption bandwidth is 2 GHz, indicating that the composite material has potential application value in the field of high-frequency wave absorption. The research on the electromagnetic wave absorption mechanism shows that its superior wave absorption performance is determined by the synergistic effect of multiple loss mechanisms such as interfacial polarization, dipole relaxation, natural resonance, exchange resonance, and eddy current loss.

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.

Effect of Nd Element of Mg-Nd Binary Alloy on the Corrosion Resistance in Sulfate-Reducing Bacteria Solution.

In this paper, the corrosion resistances of Mg-Nd binary alloys with various contents of the neodymium (Nd) element in sulfate-reducing bacteria (SRB) were studied. In the SRB medium, the results of weight loss experiments showed that the increase in the Mg12Nd phase in the alloy increased the galvanic corrosion and the corrosion rate. However, when the continuous network distribution of the second phase formed, the corrosion resistance of the alloy improved. The biofilm was formed by the adhesion of the SRB. Meanwhile, the protection from the corrosion improved due to the corrosion products, which prevent the penetration of corrosive ions. On the other hand, the products of biological metabolism accelerated the corrosion of the matrix.

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.

Definition of Atomic-Scale Contact: What Dominates the Atomic-Scale Friction Behaviors?

The definition of atomic-scale contact is a very ambiguous issue owing to the discrete atomic arrangement, which hinders the development of contact theory and nano-tribological techniques. In this work, we studied the atomic-scale contact area and their correlations with friction force based on three distinct contact definitions (interatomic distance, force, and interfacial chemical bonds) by performing large-scale atomistic simulations on a typical ball-on-disk contact model. In the simulations, the measured contact areas defined by interatomic distance, force, and interfacial chemical bonds (referred as to Adist, Aforce, and Abond, respectively) are not equivalent at all, while we interestingly clarify that only Adist is consistent with the one calculated by continuum Hertz contact mechanics, and moreover, only Abond is proportional to the friction force indicating that Abond is the dominant one for determining materials' frictional behaviors. The above fundamental insights into the atomic-scale contact problems are useful to deeply understand the origins of tribological phenomena and contribute to the further prediction of atomic-scale friction.

Structure-immunomodulatory activity relationships of dietary polysaccharides.

Polysaccharides are usually composed of more than ten monosaccharide units, which are connected by linear or branched glycosidic bonds. The immunomodulatory effect of natural polysaccharides is one of the most important bioactive function. In this review, molecular weight, monosaccharide (including galactose, mannose, rhamnogalacturonan-I arabinogalactan and uronic acid), functional groups (namely sulfate, selenium, and acetyl groups), types of glycoside bond connection (including ß-1,3-D-glucosyl, α-1,4-D-glucosyl, ß-1,4-D-glucosyl, α-1,6-D-glucosyl, ß-1,4-D-mannosyl, and ß-1,4-D-Xylopyranosyl), conformation and the branching degrees are systematically identified as their contribution to the immunostimulatory activity of polysaccharides. At present, studies on the structure-activity relationships of polysaccharides are limited due to their low purity and high heterogeneity. However, it is an important step in providing useful guidance for dietary supplements with polysaccharides. The chemical structures and the process of immune responses induced are necessary to be discussed. Polysaccharides may bind with the cell surface receptors to modulate immune responses. This review mainly discusses the structure-activity relationship of dietary polysaccharides.

Sea Cucumber Detection Algorithm Based on Deep Learning.

The traditional single-shot multiBox detector (SSD) for the recognition process in sea cucumbers has problems, such as an insufficient expression of features, heavy computation, and difficulty in application to embedded platforms. To solve these problems, we proposed an improved algorithm for sea cucumber detection based on the traditional SSD algorithm. MobileNetv1 is selected as the backbone of the SSD algorithm. We increase the feature receptive field by receptive field block (RFB) to increase feature details and location information of small targets. Combined with the attention mechanism, features at different depths are strengthened and irrelevant features are suppressed. The experimental results show that the improved algorithm has better performance than the traditional SSD algorithm. The average precision of the improved algorithm is increased by 5.1%. The improved algorithm is also more robust. Compared with YOLOv4 and the Faster R-CNN algorithm, the performance of this algorithm on the P-R curve is better, indicating that the performance of this algorithm is better. Thus, the improved algorithm can stably detect sea cucumbers in real time and provide reliable feedback information.

Plasmodium infection suppresses colon cancer growth by inhibiting proliferation and promoting apoptosis associated with disrupting mitochondrial biogenesis and mitophagy in mice.

BACKGROUND: Colon cancer is a common gastrointestinal tumor with a poor prognosis, and thus new therapeutic strategies are urgently needed. The antitumor effect of Plasmodium infection has been reported in some murine models, but it is not clear whether it has an anti-colon cancer effect. In this study, we investigated the anti-colon cancer effect of Plasmodium infection and its related mechanisms using a mouse model of colon cancer. METHODS: An experimental model was established by intraperitoneal injection of Plasmodium yoelii 17XNL-infected erythrocytes into mice with colon cancer. The size of tumors was observed dynamically in mice, and the expression of Ki67 detected by immunohistochemistry was used to analyze tumor cell proliferation. Apoptosis was assessed by terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling (TUNEL) staining, and the expression of apoptosis-related proteins including Bax, Bcl-2, caspase-9, and cleaved caspase-3 was detected by western blot and immunohistochemistry, respectively. Transmission electron microscopy (TEM) was used to observe the ultrastructural change in colon cancer cells, and the expression of mitochondrial biogenesis correlative central protein, PGC-1α, and mitophagy relevant crucial proteins, PINK1/Parkin, were detected by western blot. RESULTS: We found that Plasmodium infection reduced the weight and size of tumors and decreased the expression of Ki67 in colon cancer-bearing mice. Furthermore, Plasmodium infection promoted mitochondria-mediated apoptosis in colon cancer cells, as evidenced by the increased proportion of TUNEL-positive cells, the upregulated expression of Bax, caspase-9, and cleaved caspase-3 proteins, and the downregulated expression of Bcl-2 protein. In colon cancer cells, we found destroyed cell nuclei, swollen mitochondria, missing cristae, and a decreased number of autolysosomes. In addition, Plasmodium infection disturbed mitochondrial biogenesis and mitophagy through the reduced expression of PGC-1α, PINK1, and Parkin proteins in colon cancer cells. CONCLUSIONS: Plasmodium infection can play an anti-colon cancer role in mice by inhibiting proliferation and promoting mitochondria-mediated apoptosis in colon cancer cells, which may relate to mitochondrial biogenesis and mitophagy.

Enantioselective Organocatalytic Three-Component Vinylogous Michael/Aldol Tandem Reaction among 3-Alkylidene oxindoles, Methyleneindolinones, and Aldehydes.

We reported a one-pot enantioselective three-component vinylogous Michael/aldol tandem reaction of prochiral 3-alkylidene oxindoles with methyleneindolinones and aldehydes using bifunctional organocatalysts. A variety of enantioenriched 3,3-disubstituted oxindoles 3 and spirolactones 4 were generated in moderate yields (up to 78%) with high stereoselectivities (up to >20:1 dr, >99% ee). Intriguingly, we observed that the aldol reaction with paraformaldehyde generates 3,3-disubstituted oxindoles 3 bearing a hydroxymethyl group, while the reaction with aliphatic aldehydes generates spirolactones 4.

Gaidai reliability 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.

Self-assembled lanthanide-based helixes: synthetic control of the helical handedness by chirality of the ligand.

The control of the self-assembly of lanthanide helical chain and their helical handedness have been investigated for the first time. Δ- and Λ-form lanthanide chain complexes were obtained by introducing thiazolidine ligands that were synthesised from L- and D-cysteine, respectively, and shared the same formula: [Ln2(L)3(H2O)5]∞·3H2O (Ln: Sm and Eu) (L: 2-(2-hydroxy-3,5-dinitrophenyl)thiazolidine-4-carboxylic acid). The crystallographic, circular dichroism, and luminescence properties of these novel lanthanide chain complexes were studied.

Temperature Gradient Control of the Solid Oxide Fuel Cell under Variable Load.

Nowadays, the temperature gradient is considered as one of the most important parameters which impact the performance of the solid oxide fuel cell (SOFC). In this paper, a control strategy based on an input-output feedback linearization technology is derived for controlling the maximum temperature gradient within the anode fuel flow channel at the desired value. For the controller design, the temperature dynamic model is proposed and simplified to a control-oriented multi-input and multioutput nonlinear dynamic model. Then, this paper presents an input-output feedback linearization controller to realize the control objective by adjusting the cathode input air flow. Finally, the simulation results are given to demonstrate the accuracy of the proposed model in reflecting the temperature dynamic characteristics. Moreover, the compound controller is added for simulation as a comparison, which shows that the proposed controller is equipped with better effectiveness and efficiency in the presence of external disturbances.