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A novel monolithic zirconia restoration fabricated by additive 3-dimensional (3D) gel deposition, named as self-glazed zirconia (SGZ), has recently been developed. SGZ crowns exhibit reliable mechanical properties and esthetic appearance, but their adaptation and uniformity are unclear. The purpose of this in vitro study was to compare the adaptation and uniformity of monolithic zirconia crowns fabricated by additive 3D gel deposition with that of milled zirconia and lithium disilicate crowns. Ten identical resin abutments were made based on the scanning data of an extracted and prepared human mandibular first molar. Three types of monolithic crowns were then fabricated by using 2 different processes: 3D gel deposition zirconia (SGZ), milled zirconia (ZZ), and milled lithium disilicate (EMX) (n=10) through a completely digital workflow. The nondestructive direct-view technique and replica technique were used to measure the marginal and internal discrepancy values individually. The uniformity index was calculated to describe the uniformity of the internal space. The results were analyzed by using 1-way ANOVA and Kruskal-Wallis statistical tests (α=.05). The marginal discrepancy of EMX exhibited the highest values among the 3 groups (P =.001). The 2 types of zirconia crowns had comparable marginal discrepancy values (P >.05). The internal discrepancy values of SGZ were significantly lower than those of EMX at the occlusal region and of ZZ at all measured locations (P <.05). All 3 types of monolithic crowns showed comparable good uniformity (P =.056). The marginal and internal adaptations of novel monolithic zirconia crowns were within clinical requirements. Compared with the zirconia and lithium disilicate crowns fabricated by subtractive milling, monolithic zirconia crowns fabricated by additive 3D gel deposition had comparable uniformity and better internal adaptation. [ABSTRACT FROM AUTHOR]

A transient mathematical model is developed based on the distributed-parameter method by dividing the heat transfer regions of the secondary side of the once-through steam generator into single-phase preheating region, subcooled boiling region, nucleate boiling region, liquid deficient region (also known as post-dryout region) and single-phase superheating region in present work. And then it is used to simulate dryout phenomenon and transient heat transfer of the once-through steam generator. The results show that the developed mathematical model and method can be used to reasonably predict dryout phenomenon and transient heat transfer performance at different loads of the once-through steam generator. The heat transfer coefficient of the secondary side decreases sharply when dryout occurs, correspondingly the wall temperature shows a soaring trend and the maximum rising amplitude within present operating range is about 23 °C. The reduction of inlet enthalpy and mass flow rate of the primary side of the once-through steam generator both lead to a reduction of the outlet steam superheat and a downstream movement of the dryout point. The steam at the outlet cannot reach the superheating condition when the inlet enthalpy of the primary side decreases by 5%. The decrease of the inlet enthalpy of the secondary side within current range has little effect on the overall heat transfer performance, while the decrease of the mass flow rate of the secondary side leads to the upstream displacement of the dryout point and a rising outlet steam temperature. [ABSTRACT FROM AUTHOR]

Abstract: This study was designed to identify poultry feces-specific marker(s) within sequences of Faecalibacterium 16S rDNA for detecting poultry fecal pollution in water. Bioinformatics tools were used in the comparative analysis of 7,458 sequences of Faecalibacterium 16S rDNA, reportedly associated with various poultry (chicken and turkey) and animal species. One intervening sequence (IVS) within between the hypervariable region 1 and the conserved region 2, designated as IVS-p, was found to be unique to poultry feces. Based on this sequence, a PCR assay (PCR-p) was developed. The PCR-p produced an amplicon of 132 bp only in the test when fecal or wastewater samples from poultry were used, but not when using fecal or wastewater samples from other sources. The non-poultry sources included feces of beef or dairy cattle, dog, horse, human, domestic or wild geese, seagull, sheep, swine, and wild turkey. These data indicate that IVS-p may prove to be a useful genetic marker for the specific identification of poultry fecal pollution in environmental waterways. Furthermore, results of data mining and PCR assay indicate that the IVS-p may have a broad geographic distribution. This report represents initial evidence of the potential utility of ribosomal intervening sequences as genetic markers for tracking host sources of fecal pollution in waterways. [Copyright &y& Elsevier]

Abstract: Rotating counterflow twin premixed flames of methane–air were numerically simulated with detailed chemistry based on a similarity solution to explore the leanest extinction limit without preheating and to elucidate the mechanism of “ultra-lean” combustion. We focused on high rotation rate cases in which unrealistic backflow from infinity is allowed to occur since ultra-lean combustion was found to be realized in such a situation. It was found that the reaction zone is in the backflow zone, where the flame’s apparent burning velocity is negative, and that the flame zone width is much smaller than that of a 1-D planar premixed flame due to an inversion of the convexity directions of the profiles of temperature and main species concentrations. The decrease of the flame width seems to make the flame less extinguishable. The equivalence ratio of the leanest flame obtained neglecting radiative heat loss is 0.32, while that obtained with an optically thin radiation model is 0.42, which is still much leaner than the ratio of 0.49 for a 1-D planar premixed flame generated using the same radiation model. [Copyright &y& Elsevier]

• An equilibrium constants database established according to minimizing Gibbs energy. • Development of a combustion products equilibrium model by the constants database instead of fitting functions. • Model accuracy greatly improved compared with that of fitting functions. • Analysis of temperature, O 2 concentration, fuel types, etc., on the equilibrium mole fraction of combustion products. As international concern that regards N O x emissions from the shipping industry increases, it is challenging and urgent to reduce ships' N O x emissions. According to the extended Zeldovich, the determination of the equilibrium concentration of combustion products is crucial for the prediction of N O formation in internal combustion engines. In the present work, an equilibrium constants database of related chemical reactions is established based on the theory that the total Gibbs energy reaches its minimum when a reaction achieves equilibrium. Afterward, a combustion product equilibrium model with twelve species considered is established based on the equilibrium constants database. The accuracy of the model is significantly improved compared with the commonly used ones which calculate the equilibrium constants through fitting function. The errors of the model are within 2% compared with STANJAN which is widely used for chemical equilibrium analysis. The model results are comparable to STANJAN. Afterward, the effects of the temperature, pressure, fuel–air equivalence ratio, O 2 concentration, N 2 concentration, A r concentration and fuel type on the equilibrium mole fractions of the combustion products are investigated. The equilibrium concentration of combustion products is significantly affected by the temperature, O 2 concentration and fuel–air equivalence ratio, but slightly influenced by the pressure and A r concentration. The existence of O and N in the fuel slightly reduces the N O equilibrium mole fraction of the combustion products at the same temperature, pressure and fuel–air equivalence ratio. However, the ratio of molar carbon hydrogen in the fuel and the existence of O and N in the fuel have a significant impact on the C O 2 mole fraction of the combustion products. [ABSTRACT FROM AUTHOR]

• Machine learning algorithms are used to define experimental boundary conditions and facilitate micropattern optimization. • Integrating classification and regression models in the learning loops, we improve the accuracy of model predictions. • Through active learning, we accelerate the optimization process of fabricating micropatterns with the least experiments. • The optimal micropattern has a diameter range of 27-470 nm, much wider than the widest diameter range ever reported. • The optimal gradient micropattern further shows superior performance in high-throughput screening for biomedical use. [Display omitted] Micropatterning has been widely applied in electronics, biomaterials engineering, and microfluidics studies. A key challenge in using bipolar electrochemistry for fabricating titanium dioxide (TiO 2) nanotube micropatterns (TNMs) with desired properties is to balance interrelated experimental parameters and define experimental boundary conditions. For example, it is challenging to determine the anodization voltage boundary as high anodization voltage with certain conditions might induce titanium foils rupture. Here, we utilize active learning to facilitate the optimization process of fabricating TNMs with a wide dimension range within one sample using bipolar electrochemistry. Starting with a small dataset, the decision tree model differentiates normal data from abnormal data (i.e., titanium foils ruptured), which helps define the experimental boundaries. Then gradient boosted regression tree (GBRT) model analyzes the data and provides predictions and directions for optimizing TNMs. Then predictions are verified by experiments, and new results update the training dataset for the next learning loop. Results show that ML algorithms well define the experimental boundary conditions. And only within several iterations, we obtained the optimal TNMs with a diameter range of 27–470 nm, expanding the gradient to the largest extend without tedious experiments. Those results indicate that machine learning algorithms are effective in accelerating materials manufacture and optimization. Further silver nanoparticle doping demonstrates that large-scale TNMs are effective platforms for high-throughput screening. [ABSTRACT FROM AUTHOR]

• PINK1/Parkin-mediated mitophagy is involved in APAP-induced acute liver injury. • NF-kB and NLRP3 inflammasome signaling pathway are activated by APAP overdose. • Enhancement of mitophagy by RAPA suppresses NLRP3 inflammasome signaling and alleviate the liver injury. • Blockage of autophagic flux by CQ aggravates APAP-induced NLRP3 inflammasome signaling. Mitochondrial dysfunction was considered as a critical event involved in acetaminophen (APAP)-induced acute liver injury. Mitophagy is a type of autophagy responsible for the selective removal of damaged mitochondria. However, the exact role and possible mechanism of mitophagy in APAP-induced hepatotoxicity remains largely unknown. In this study, C57/BL6 mice were used to establish a model of acute liver injury via intraperitoneal (i.p.) injection with different doses of APAP. Furthermore, autophagy intervention experiments were achieved by the administration of rapamycin (RAPA) or chloroquine (CQ) one hour prior to dosing 300 mg/kg APAP. The activity of serum enzymes and pathological changes of APAP-treated mice were evaluated, and the critical molecules in mitophagy and NLRP3 inflammasome pathway were determined by electron microscopy, immunoblot, immunofluorescence and real-time PCR. The results demonstrated that APAP overdose resulted in an activation of PINK1/Parkin-mediated mitophagy in mice liver. Moreover, the expression of the critical molecules in NF-kB and NLRP3 inflammasome signaling pathway were markedly increased by APAP. Our further investigation found that pretreatment with RAPA protected against APAP-induced hepatoxicity in mice. Notably, RAPA significantly inhibited the activation of NF-kB and NLRP3 inflammasome and the production of IL-1β in APAP-treated mice. By contrast, pretreatment with CQ further enhanced NLRP3 inflammasome signaling pathway. Taken together, these results indicated that activation of PINK1/Parkin-mediated mitophagy protects against APAP-induced acute liver injury in mice through inhibiting inflammasome activation. Therefore, mitophagy may represent a promising therapeutic target for APAP-induced liver injury. [ABSTRACT FROM AUTHOR]

An accurate fuel consumption model is essential for optimising ship operations. This study examined the impact of main engine data on the precision of ship fuel consumption models. When compared to models constructed without engine data, models utilising engine data can decrease prediction errors by 18.49%–31.25%. However, since speed and trim optimisation tasks necessitate control variables which are not available before the voyage, they cannot be employed as inputs to the fuel consumption model developed for the optimisation task. The first approach involves a two-stage process, while the second entails incorporating an auxiliary branch into a deep neural network. In the experimental findings of the second strategy, the mean absolute error was 0.001139, signifying a 20.9% reduction in fuel consumption model error compared to not utilising the main engine data. These strategies present novel methods for establishing precise fuel consumption models in ship operation optimisation research. • The impact of engine data on the accuracy of the fuel consumption model was analysed. • Engine data were utilised in the fuel consumption model built for optimisation tasks. • Adding a branch structure to the deep neural network to fit the engine data. [ABSTRACT FROM AUTHOR]

Abstract: Acute pancreatitis is a common disease, which is divided into mild pancreatitis and severe pancreatitis. For the latter, a systemic inflammatory response may occur and lead to distant organ damage and the development of multiple organ dysfunction syndrome (MODS), which accounts for significant morbidity and mortality in humans. Chemokines and their receptors are being believed to play a pivotal role in the pathogenesis of acute pancreatitis. Chemokine receptor CXCR3 is reported to be involved in acute tissue injury, for example acute lung injury induced by cigarette smoking, but its role in acute pancreatitis is not yet known. In this study, two animal models of acute pancreatitis (cerulein- and arginine-induced pancreatitis) were applied in CXCR3−/− mice and wild-type mice, in order to explore the role of CXCR3 in acute pancreatitis. Serum amylase, lipase and histological observations revealed that CXCR3 knockout did not affect the severity of acute pancreatitis. However, edema and inflammatory cell infiltrate in the lung tissue were attenuated in CXCR3−/− mice when acute pancreatitis was induced. In conclusion, chemokine receptor CXCR3 is not involved in acute pancreatic injury, but has a connection with acute pancreatitis-associated lung injury. Acute pulmonary injury is attenuated in CXCR3 knockout mice in experimental acute pancreatitis. [Copyright &y& Elsevier]

The performance of continuously reversed polarization induced by non-collinear conical magnetic structures was investigated in Y-type BaSrCo 2 Fe 11 AlO 22 ceramics. The electrical polarization induced by the non-collinear magnetic structures was categorized as reversible polarization and bound polarization. When the range of a circulating magnetic field H ≥ ±1.5 kOe, the P – H loops reached a saturated state and the saturated polarization increased linearly as the circulating magnetic field increased, which was ascribed to the bound polarization. During the continuous magnetic field cycle, a portion of the reversible polarization transformed into bound polarization and only the poling process can achieve inverse transformation. Therefore, the polarization attenuated exponentially as the number of the H cycles increased. [ABSTRACT FROM AUTHOR]

Mathematical and simulation models of the nonlinear speed optimization under the influence of irregular winds and waves are established for a 48000DWT oil tanker. The objective functions are minimum fuel consumption of the main engine and maximum operating cost reduction. The influence of winds and waves on fuel consumption, the maximum operating cost reduction under different market conditions, and speed of single voyage for a given route are studied using the verified speed optimization model. The fuel saving rate of 1.07% by speed optimization compared with that at the punctual constant speed. Therefore, the speed optimization can reduce significantly the fuel consumption. In the five different market conditions, the single voyage cost reduction is as much as $85,865, compared with that at the punctual constant speed. The proposed model can be used to significantly improve a ship's operating economy and provide decision support for shipping companies. [ABSTRACT FROM AUTHOR]

The effect of high concentration of hydrogen on the segregation of radiation-induced segregation (RIS) in AL-6XN stainless steels has been investigated by transmission electron microscopy (TEM) with energy-dispersive X-ray spectroscopy. Specimens were irradiated with 100 keV H 2 + ions from 1 dpa to 5 dpa at 380 °C to investigated the dose dependence of grain boundary RIS. A specimen was irradiated to 5 dpa at 290 °C to study the effect of irradiation temperature. The trends of Cr depletion and Ni enrichment with irradiation dose is similar to that of other austenitic steels reported in the literatures, but the higher concentration of hydrogen made the RIS profile wider. An abnormal phenomenon that the degree of RIS increased with decreasing irradiation temperature was found, indicating that with the retention of hydrogen in the steels, temperature dependence of RIS is dominated by the quantity of retained hydrogen, rather than by thermal segregation processes. [ABSTRACT FROM AUTHOR]