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• The precipitation evolution behaviors and mechanical properties of an Al-Cu-Li-Mg alloy under T3- and T4-aged tempers were firstly studied in detail. • The precipitation sequences of different aged samples during natural aging were determined by using HADDF-STEM. • The intrinsic mechanism of the suppressed nucleation and growth of GPI zones, and the inhibition of δ′/GPI zones/δ′ complex precipitates precipitation in the T3 samples was revealed. • The fundmental reasons for the significantly distinct aging-hardening behaviors between T3- and T4-aged samples were clarifed. The precipitation evolution and mechanical properties of a commercial Al-Cu-Li-Mg alloy in natural aging (NA) tempers (T3 and T4) were investigated in detail. It was demonstrated that GPI zones were the predominant precipitate throughout the NA process. In the T3-aged sample, the precipitation sequence was determined: supersaturated solid solution (SSSS) → atom clusters → GPI zones, whereas in the T4-aged sample, it was SSSS → atom clusters → GPI zones → GPI zones + δ′/GPI zones/δ′. For samples without NA, the strength of the T3 sample was 76.0 MPa higher than that in the T4 sample, which was attributed to the pre-deformation-introduced dislocations. During the early stage of NA, GPI zone nucleation was substantially restricted in the T3 sample, resulting in a much lower number density of GPI zones. It retarded the aging response and strength improvement, consequently narrowing the strength difference between T3 and T4 samples. As the NA process progressed, the average diameter of GPI zones in the T4 sample increased to approximately 4.5 nm, accompanied by the formation of δ′/GPI zones/δ′ composite precipitate. However, GPI zone growth and δ′/GPI zones/δ′ composite precipitate formation were significantly inhibited in the T3 sample, as evidenced by its much smaller average diameter of approximately 2.1 nm and the absence of composite precipitates. It inhibited the strength improvement of the T3 sample. Therefore, after a long period (5 months) of NA, the strength of the T4 sample was about 13.0 MPa higher than that of the T3 samples, instead. [Display omitted] [ABSTRACT FROM AUTHOR]

Byline: Yan. Zhang, Fenghua. Lu, Nannan. Cai, Lanjing. Tang, Yao. Zhou, Yalin. Li, Kai. Liu, Wengang. Song, Li. Kang, Hao. He Objective: This study aimed to map the antitumor immunity [...]

Surrogate-assisted evolutionary algorithm (SAEA) prevails in the optimization of computationally expensive problems. However, existing SAEAs confront low efficiency in the resolution of high-dimensional problems characterized by multiple local optima and multivariate coupling. To this end, this paper offers a dual-drive collaboration surrogate-assisted evolutionary algorithm (DDCSAEA) by coupling feature reduction and reconstruction, which coordinates two unsupervised feature learning techniques, i.e., principal component analysis and autoencoder, in tandem. DDCSAEA creates a low-dimensional solution space by downscaling the target high-dimensional space via principal component analysis and collects promising candidates in the reduced space by collaborating a surrogate-assisted evolutionary sampling with differential mutation. An autoencoder is used to perform the feature reconstruction on the collected candidates for infill-sampling in the target high-dimensional space to sequentially refine the neighborhood landscapes of the optimal solution. Experimental results reveal that DDCSAEA has stronger convergence performance and optimization efficiency against eight state-of-the-art SAEAs on high-dimensional benchmark problems within 200 dimensions.

In this article, we propose a new frequency-limited Riemannian geometric-nonlinear conjugate gradient model order reduction (MOR) method with the modified Armijo step-size control to solve the frequency-limited $\mathcal {H}_{2}$ optimal MOR problem of linear port-Hamiltonian systems. This problem is formulated as a Riemannian optimization problem on the product of several manifolds. Based on the geometric properties of the product manifold, the Riemannian gradient of the cost function is derived. Further, by scaling the vector transport of the product manifold, we design a new Riemannian spectral conjugate gradient direction, which is always descent for the cost function and is independent of the line search used and the convexity of the cost function. Meanwhile, a new modified Armijo step-size control strategy is presented. The resulting reduced system can preserve the port-Hamiltonian structure and the passivity of the original system. Two numerical examples are simulated to demonstrate the efficiency of the proposed method.

Federated learning (FL) represents a promising distributed machine learning paradigm for resolving data isolation due to data privacy concerns. Nevertheless, most vanilla FL algorithms, which depend on a server, encounter the problem of reliability and a high communication burden in real cases. Decentralized federated learning (DFL) that does not follow the star topology faces the challenges of weight divergence and inferior communication efficiency. In this paper, a novel DFL framework called federated incremental subgradient-proximal (FedISP) is proposed that utilizes the incremental method to perform model updates to alleviate weight divergence. In our setup, multiple clients are distributed in a ring topology and communicate in a cyclic manner, which significantly mitigates the communication load. A convergence guarantee is given under the convex condition to demonstrate the impact of the learning rate on our algorithms, which further improves the performance of FedISP. Extensive experiments on benchmark datasets validate the effectiveness of the proposed approach in both independent and identically distributed (IID) and non-IID settings while illustrating the advantages of the FedISP algorithm in achieving model consensus and saving communication costs.

In this letter, the back-end of line (BEOL) compatible H0.5Z0.5O2/ZrO2/H0.5Z0.5O2 stack was designed for enhancing both the ferroelectricity and reliability under low-voltage operation. Compared to the conventional H0.5Z0.5O2(HZO) film, the HZO/ZrO2/HZO stack exhibits superior remnant polarization ( $2{P}_{\text {r}}{)}$ of $39.6~\mu \text{C}$ /cm2 and $53.8~\mu \text{C}$ /cm2 under 2 MV/cm and 4 MV/cm, respectively. By integrating ZrO2 middle layer (ML) into HZO films, robust reliability was achieved, including a large breakdown electric field of 2.73 MV/cm in 10-year time-dependent dielectric breakdown (TDDB) lifetime, as well as excellent endurance characteristic with a $2{P}_{\text {r}}$ of $38.04~\mu \text{C}$ /cm2 after ${4}.{34}\times {10} ^{{9}}$ cycles at 2 MV/cm and no breakdown after ${6}\times {10} ^{{10}}$ fatigue cycles at 1.5 MV/cm. It is believed that ZrO2 ML could introduce additional strain at a low annealing temperature below 350 °C and improve the proportion of the ferroelectric phase in the HZO/ZrO2/HZO stack. The HZO/ZrO2/HZO stack with low-voltage operation shows the great potential for BEOL-compatible non-volatile memory applications.

Urolithin A (UroA), a dietary phytochemical, is produced by gut bacteria from fruits rich in natural polyphenols ellagitannins (ETs). The efficiency of ETs metabolism to UroA in humans depends on gut microbiota. UroA has shown a variety of pharmacological activities. In this study we investigated the effects of UroA on atherosclerotic lesion development and stability. Apolipoprotein E-deficient (ApoE−/−) mice were fed a high-fat and high-cholesterol diet for 3 months to establish atherosclerosis model. Meanwhile the mice were administered UroA (50 mg·kg−1·d−1, i.g.). We showed that UroA administration significantly decreased diet-induced atherosclerotic lesions in brachiocephalic arteries, macrophage content in plaques, expression of endothelial adhesion molecules, intraplaque hemorrhage and size of necrotic core, while increased the expression of smooth muscle actin and the thickness of fibrous cap, implying features of plaque stabilization. The underlying mechanisms were elucidated using TNF-α-stimulated human endothelial cells. Pretreatment with UroA (10, 25, 50 μM) dose-dependently inhibited TNF-α-induced endothelial cell activation and monocyte adhesion. However, the anti-inflammatory effects of UroA in TNF-α-stimulated human umbilical vein endothelial cells (HUVECs) were independent of NF-κB p65 pathway. We conducted RNA-sequencing profiling analysis to identify the differential expression of genes (DEGs) associated with vascular function, inflammatory responses, cell adhesion and thrombosis in UroA-pretreated HUVECs. Human disease enrichment analysis revealed that the DEGs were significantly correlated with cardiovascular diseases. We demonstrated that UroA pretreatment mitigated endothelial inflammation by promoting NO production and decreasing YAP/TAZ protein expression and TEAD transcriptional activity in TNF-α-stimulated HUVECs. On the other hand, we found that UroA administration modulated the transcription and cleavage of lipogenic transcription factors SREBP1/2 in the liver to ameliorate cholesterol metabolism in ApoE−/−mice. This study provides an experimental basis for new dietary therapeutic option to prevent atherosclerosis.

Graphical Abstract:

Existing class imbalance learning paradigms focus on lifting the importance of minority instance, aiming to improve the model in terms of certain evaluation metrics (e.g., AUC and $F_{1}$F1-measure). One drawback of these methods is that they lack enough transparency, hence, cannot be fully trusted in vital domains. To this end, this paper deal with the class imbalance learning task with counterfactual instances. Given an instance and a classifier, a counterfactual is a fake instance which, while having smallest distance to the original instance, is classified as a different class by the classifier. Therefore, the most important features for a classifier can be identified by inspecting the difference between an instance and its counterfactual. To utilize counterfactuals, a novel Explainable Generative Adversarial Network (EXGAN) is proposed. EXGAN has a unique “two generators versus multiple discriminators” architecture where the generators are used to generate effective counterfactuals and discriminators are trained for the class imbalance learning task. In addition to the architecture, an innovative ensemble loss function ensuring each discriminator complementing each other is designed to overcome the class imbalance issue. Extensive experiments prove that the counterfactuals generated by EXGAN can be used to produce effective local explanation and provide significant better class imbalance learning ability than existing competitors.

The artificial bee colony algorithm (ABC) struggles in handling complex optimization problems with high dimensions in light of its search operators’ strong exploration and weak exploitation properties. To tackle this situation, in this study, we propose a bi-preference linkage-driven ABC algorithm with multi-operator fusion, named BPLABC. BPLABC couples a preference-free stochastic search operator with a global best-guided search operator in the employed bee phase to maintain the population diversity while enhancing the population quality. During the onlooker bee phase, a tailored bi-type elite-guided exploitation mechanism is employed to regulate the exploitation intensity of the promising elite nectar sources selected via a new roulette selection probability calculation paradigm. To discourage the onlooker bees from slipping into local traps, after the scout bee phase, an auxiliary adversarial search operator is assembled to tug certain promising elite solutions away from the present pseudo-global best solution. To illustrate the effectiveness and efficiency of BPLABC, two sets of test suits consisting of 23 benchmark problems, 30 complex CEC2014 functions, and two real-world problems are picked for testing. Experimental results showed that BPLABC can achieve superior or equivalent performance to several representative ABC variants on the majority of the tested problems.

This study reported the fabrication of Ni50 and Ni50-WC coatings while employing the laser cladding manufacture (LCM) technique. The surface and cross-sectional morphologies, microhardness, phase structure, corrosion, and wear resistances of the coatings were measured using a scanning electron microscope (SEM), stereoscopic microscope, X-ray diffractometer (XRD), microhardness tester, electrochemical workstation, and friction and wear tester. These results illustrated the emergence of γ-(Ni, Fe), WC, W2C, M23C6, M7C3, and Ni3Fe phases in Ni50–10WC and Ni50–20WC coatings. Besides, W and C contents were higher in Ni50–20WC coating than that in Ni50–10WC coating. The average microhardness of the Ni50–10WC and Ni50–20WC coatings was 655.2 HV and 817.9 HV, respectively, which tripled or quadrupled the substrates' average microhardness. Among all coatings, Ni50 had the lowest corrosion potential value of −0.83 V, indicating poor anti-corrosion efficiency. Ni50–10WC and Ni50–20WC coatings had wear depths of approximately 13.1 μm and 8.3 μm, respectively indicating the outstanding wear resistance of all coatings. Furthermore, the Ni50–20WC coating exhibited the lowest average friction coefficient (0.41) of all coatings because of its fine and compact structure.

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest forms of human malignancy that currently lacks approved targeted therapeutics. Accumulating evidence suggests that SOX2 overexpression is a key driving factor for ESCC and various squamous cell carcinoma. Here, through screening a small-molecule kinase inhibitor library, we identified GSK3β as a kinase that is critically required for robust SOX2 expression in ESCC cells. GSK3β did not promote SOX2 transcriptionally but was required for SOX2 protein stability. We demonstrated that GSK3β interacts with and phosphorylates SOX2 at residue S251, which blocks SOX2 from ubiquitination and proteasome-dependent degradation instigated by ubiquitin E3 ligase CUL4ADET1-COP1. Pharmacological inhibition or knockdown of GSK3β by RNA interference selectively impaired SOX2-positive ESCC cell proliferation, cancer stemness, and tumor growth in mouse xenograft model, suggesting that GSK3β promotes ESCC tumorigenesis primarily by driving SOX2 overexpression. GSK3β was found to be frequently overexpressed in clinical esophageal tumors, and there was a positive correlation between GSK3β and SOX2 protein levels. Notably, we found that SOX2 enhanced GSK3β expression transcriptionally, suggesting the existence of a vicious cycle that drives a coordinated GSK3β and SOX2 overexpression in ESCC cells. Finally, we demonstrated in tumor xenograft model that GSK3β inhibitor AR-A014418 was effective in suppressing SOX2-positive ESCC tumor progression and inhibited tumor progression cooperatively with chemotherapeutic agent carboplatin. In conclusion, we uncovered a novel role for GSK3β in driving SOX2 overexpression and tumorigenesis and provided evidence that targeting GSK3β may hold promise for the treatment of recalcitrant ESCCs.

SOX2 is highly expressed and controls tumor initiation and cancer stem cell function in various squamous cell carcinomas including esophageal squamous cancer. However, the molecular mechanism leading to SOX2 overexpression in cancer is incompletely understood. Here, we identified CHIP, a chaperone-associated ubiquitin E3 ligase, as a novel negative regulator of SOX2 protein stability and tumorigenic activity in esophageal squamous carcinoma cells. We showed that CHIP interacted with SOX2 primarily via chaperone HSP70, together they catalyzed SOX2 ubiquitination and degradation via proteasome. In contrast, HSP90 promoted SOX2 stability and inhibition of HSP90 activity induced SOX2 ubiquitination and degradation. Notably, unlike the case in normal esophageal tissues where CHIP was detected in both the cytoplasm and nucleus, CHIP in clinical esophageal tumor specimens was predominantly localized in the cytoplasm. Consistent with this observation, we observed increased expression of exportin-1/CRM-1 in clinical esophageal tumor specimens. We further demonstrated that CHIP catalyzed SOX2 ubiquitination and degradation primarily in the nuclear compartment. Taken together, our study has identified CHIP as a key suppressor of SOX2 protein stability and tumorigenic activity and revealed CHIP nuclear exclusion as a potential mechanism for aberrant SOX2 overexpression in esophageal cancer. Our study also suggests HSP90 inhibitors as potential therapeutic agents for SOX2-positive cancers.

Two-dimensional (2D) crystal-to-crystal transition is an important method in crystal engineering because of its ability to directly create diverse crystal materials from one crystal. However, steering a 2D single-layer crystal-to-crystal transition on surfaces with high chemo- and stereoselectivity under ultra-high vacuum conditions is a great challenge because the transition is a complex dynamic process. Here, we report a highly chemoselective 2D crystal transition from radialene to cumulene with retention of stereoselectivity on Ag(111) via retro-[2 + 1] cycloaddition of three-membered carbon rings and directly visualize the transition process involving a stepwise epitaxial growth mechanism by the combination of scanning tunneling microscopy and non-contact atomic force microscopy. Using progression annealing, we found that isocyanides on Ag(111) at a low annealing temperature underwent sequential [1 + 1 + 1] cycloaddition and enantioselective molecular recognition based on C–H···Cl hydrogen bonding interactions to form 2D triaza[3]radialene crystals. In contrast, a higher annealing temperature induced the transformation of triaza[3]radialenes to generate trans-diaza[3]cumulenes, which were further assembled into 2D cumulene-based crystals through twofold N–Ag–N coordination and C–H···Cl hydrogen bonding interactions. By combining the observed distinct transient intermediates and density functional theory calculations, we demonstrate that the retro-[2 + 1] cycloaddition reaction proceeds via the ring opening of a three-membered carbon ring, sequential dechlorination/hydrogen passivation, and deisocyanation. Our findings provide new insights into the growth mechanism and dynamics of 2D crystals and have implications for controllable crystal engineering.

The Coronavirus Disease 2019 (COVID-19) pandemic has become a leading societal concern. eHealth literacy is important in the prevention and control of this pandemic. The purpose of this study is to identify eHealth literacy of Chinese residents about the COVID-19 pandemic and factors influencing eHealth literacy. A total of 15 694 individuals clicked on the link to the questionnaire, and 15 000 agreed to participate and completed the questionnaire for a response rate of 95.58%. Descriptive statistics, χ2test, and logistic regression analysis were conducted to analyze participants' level of eHealth literacy about COVID-19 and its influencing factors. The results showed 52.2% of participants had relatively lower eHealth literacy regarding COVID-19 (eHealth literacy score ≤ 48). The scores of the information judgment dimension (3.09 ± 0.71) and information utilization dimension (3.18 ± 0.67) of the eHealth literacy scale were relatively lower. The logistics regression showed that sex, age, education level, level of uncertainty, having people around the respondent diagnosed with COVID-19, relationship with family, and relationship with others were associated to eHealth literacy (χ2= 969.135, P< .001). The public's eHealth literacy about COVID-19 needs to be improved, especially the ability to judge and utilize online information. Close collaboration among global health agencies, governments, healthcare institutions, and media is needed to provide reliable online information to the public. Interventions to improve eHealth literacy should take into account and accentuate the importance of sex, age, educational background, level of uncertainty, exposure to disease, and social support.

The emergence of quantum magnetism in nanographenes provides ample opportunities to fabricate purely organic devices for spintronics and quantum information. Although heteroatom doping is a viable way to engineer the electronic properties of nanographenes, the synthesis of doped nanographenes with collective quantum magnetism remains elusive. Here, a set of nitrogen-doped nanographenes (N-NGs) with atomic precision are fabricated on Au(111) through a combination of imidazole [2+2+2]-cyclotrimerization and cyclodehydrogenation reactions. High-resolution scanning probe microscopy measurements reveal the presence of collective quantum magnetism for nanographenes with three radicals, with spectroscopic features which cannot be captured by mean-field density functional theory calculations but can be well reproduced by Heisenberg spin model calculations. In addition, the mechanism of magnetic exchange interaction of N-NGs has been revealed and compared with their counterparts with pure hydrocarbons. Our findings demonstrate the bottom-up synthesis of atomically precise N-NGs which can be utilized to fabricate low-dimensional extended graphene nanostructures for realizing ordered quantum phases.

Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a class highly imbalanced problem. Traditional unsupervised anomaly detectors are suboptimal while supervised models can easily make biased predictions towards normal data. In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). EAL-GAN is a conditional GAN having a unique one generator versus multiple discriminators architecture where anomaly detection is implemented by an auxiliary classifier of the discriminator. In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is designed to overcome the class imbalanced problem, and an active learning algorithm is introduced to significantly reduce the cost of labeling real-world data. We present extensive experimental results to demonstrate that the new anomaly detector consistently outperforms a variety of SOTA methods by significant margins.

Studies on intelligent robotic manipulation systems have typically focused on the programming efficiency, adaptive control of robotic arms, motion planning of robotic arms, and action diversity of grippers. In this study, a decision tree and visual recognition incorporate into a robotic arm to help it learn complex tasks. This study employed a task tree for the automatic planning of complex tasks, in which a decision-making model was used to generate complex task sets from a pre-built motion dataset in real-time performance. Moreover, the model can analyze the rationality of model steps, introduce new tasks, and perform object analysis. This work applies a support vector machine to identify the state of an object. The model selects a suitable gripper with a rapid gripper switch process by considering the characteristics of the targeting object. This study demonstrated the effectiveness of the proposed approach with suitable intelligence through the assembly task.

Underwater image processing has been shown to exhibit significant potential for exploring underwater environments. It has been applied to a wide variety of fields, such as underwater terrain scanning and autonomous underwater vehicles (AUVs)-driven applications, such as image-based underwater object detection. However, underwater images often suffer from degeneration due to attenuation, color distortion, and noise from artificial lighting sources as well as the effects of possibly low-end optical imaging devices. Thus, object detection performance would be degraded accordingly. To tackle this problem, in this article, a lightweight deep underwater object detection network is proposed. The key is to present a deep model for jointly learning color conversion and object detection for underwater images. The image color conversion module aims at transforming color images to the corresponding grayscale images to solve the problem of underwater color absorption to enhance the object detection performance with lower computational complexity. The presented experimental results with our implementation on the Raspberry pi platform have justified the effectiveness of the proposed lightweight jointly learning model for underwater object detection compared with the state-of-the-art approaches.

Class imbalance is a prevalent phenomenon in various real-world applications and it presents significant challenges to model learning, including deep learning. In this work, we embed ensemble learning into the deep convolutional neural networks (CNNs) to tackle the class-imbalanced learning problem. An ensemble of auxiliary classifiers branching out from various hidden layers of a CNN is trained together with the CNN in an end-to-end manner. To that end, we designed a new loss function that can rectify the bias toward the majority classes by forcing the CNN’s hidden layers and its associated auxiliary classifiers to focus on the samples that have been misclassified by previous layers, thus enabling subsequent layers to develop diverse behavior and fix the errors of previous layers in a batch-wise manner. A unique feature of the new method is that the ensemble of auxiliary classifiers can work together with the main CNN to form a more powerful combined classifier, or can be removed after finished training the CNN and thus only acting the role of assisting class imbalance learning of the CNN to enhance the neural network’s capability in dealing with class-imbalanced data. Comprehensive experiments are conducted on four benchmark data sets of increasing complexity (CIFAR-10, CIFAR-100, iNaturalist, and CelebA) and the results demonstrate significant performance improvements over the state-of-the-art deep imbalance learning methods.

The liver responds to an increase in blood glucose levels in the postprandial state by uptake of glucose and conversion to glycogen. Liver glycogen synthase (GYS2), a key enzyme in glyeogen synthesis, is controlled by a complex interplay between the allosteric activator glucose-6-phosphate (G6P) and reversible phosphorylation through glycogen synthase kinase-3 and the glycogen-associated form of protein phosphatase 1. Here, we initially performed mutagenesis analysis and identified a key residue ([Arg.sup.582) required for activation of GYS2 by G6P. We then used GYS2 [Arg.sup.582] Ala knockin (+/R582A) mice in which G6Pmediated GYS2 activation had been profoundly hnpaired (60-70%), while sparing regulation through reversible phosphorylation. R582A mutant-expressing hepatocytes showed significantly reduced glycogen synthesis with glucose and insulin or glucokinase activator, which resulted in channeling glucose/G6P toward glycolysis and lipid synthesis. [GYS2.sup.+/R582A] mice were modestly glucose intolerant and displayed significantly reduced glycogen accumulation with feeding or glucose load in vivo. These data show that G6P-mediated activation of GYS2 plays a key role in controlling glycogen synthesis and hepatic glucose-G6P flux control and thus whole-body glucose homeostasis., The liver plays a central role in maintaining blood glucose homeostasis by uptake of glucose in the postprandial state and conversion to glycogen and triglyceride and by production of glucose [...]

•Isoalantolactone (IALT) exhibits cytotoxic effects on aggressive cholangiocarcinoma (CCA) cells.•IALT induces apoptosis and modulates Yes-associated protein (YAP) signaling in SNU478 cells.•The study confirms the involvement of the Hippo pathway through LATS1/LATS2 knockout cells.•IALT suppresses cell growth, migration, and influences YAP-TEAD activity in CCA.

•A total of 9433 PLHIV taking antiretroviral therapy were selected from 63 facilities in Ethiopia.•There is high HIV-RTI resistance (77.8%) among people failing first-line treatment.•Prior HAART exposure and disclosure status were predictors for HIV drug resistance.•Bedridden and immunosuppressed were independent clinical predictors for HIV drug resistance.•The program shall consider drugs targeting protease and integrase.

The endogenous hormone relaxin increases vascular reactivity and angiogenesis. We demonstrate that acute relaxin infusion in lean C57BL/6J mice enhances skeletal muscle perfusion and augments muscle glucose uptake during a hyperinsulinemic-euglycemic clamp. However, an acute effect was absent in mice fed a high-fat (HF) diet for 13 weeks. In contrast, mice fed an HF diet for 13 weeks and continuously treated with relaxin for the final 3 weeks of the diet exhibited decreased fasting blood glucose. Insulin-stimulated whole-body glucose disappearance and percent suppression of hepatic glucose production are corrected by chronic relaxin. The increase in peripheral glucose utilization is a result of augmented in vivo skeletal muscle glucose uptake. Relaxin intervention improves endothelial-dependent vascular reactivity and induces a two-fold proliferation in skeletal muscle capillarity. The metabolic effects of the treatment are not attributed to changes in myocellular insulin signaling. Relaxin intervention reverses the accumulation of collagen HI in the liver and collagen HI and collagen IV in the heart; this is induced by HF feeding. These studies show the potential of relaxin in the treatment of diet-induced insulin resistance and vascular dysfunction. Relaxin provides a novel therapeutic approach targeting the extramyocellular barriers to insulin action, which are critical to the pathogenesis of insulin resistance., Insulin resistance precedes the development of type 2 diabetes, and it is associated with cardiovascular disease. Recent evidence suggests that muscle insulin resistance coincides with extramyocellular adaptations, including extracellular matrix [...]

Increased deposition of specific extracellular matrix (ECM) components is a characteristic of insulin-resistant skeletal muscle. Hyaluronan (HA) is a major constituent of the ECM. The hypotheses that 1) HA content is increased in the ECM of insulin-resistant skeletal muscle and 2) reduction of HA in the muscle ECM by long-acting pegylated human recombinant PH20 hyaluronidase (PEGPH20) reverses high-fat (HF) diet-induced muscle insulin resistance were tested. We show that muscle HA was increased in HF diet-induced obese (DIO) mice and that treatment of PEGPH20, which dose-dependently reduced HA in muscle ECM, decreased fat mass, adipocyte size, and hepatic and muscle insulin resistance in DIO mice at 10 mg/kg. Reduced muscle insulin resistance was associated with increased insulin signaling, muscle vascularization, and percent cardiac output to muscle rather than insulin sensitization of muscle per se. Dose-response studies revealed that PEGPH20 dose-dependently increased insulin sensitivity in DIO mice with a minimally effective dose of 0.01 mg/kg. PEGPH20 at doses of 0.1 and 1 mg/kg reduced muscle HA to levels seen in chow-fed mice, decreased fat mass, and increased muscle glucose uptake. These findings suggest that ECM HA is a target for treatment of insulin resistance., The extracellular matrix (ECM) is important to cellular functions (1,2). An increase in specific components that comprise the matrix and the basement membrane is a characteristic of metabolic disorders including [...]

OBJECTIVE--The hypothesis that high-fat (HF) feeding causes skeletal muscle extracellular matrix (ECM) remodeling in C57BL/6J mice and that this remodeling contributes to diet-induced muscle insulin resistance (IR) through the collagen receptor integrin [α.sub.2]][β.sub.1] was tested. RESEARCH DESIGN AND METHODS--The association between IR and ECM remodeling was studied in mice fed chow or HF diet. Specific genetic and pharmacological murine models were used to study effects of HF feeding on ECM in the absence of IR. The role of ECM-integrin interaction in IR was studied using hyperinsulinemic-euglycemic clamps on integrin [α.sub.2][β.sub.1]-null ([itga2.sup.-/-] ), integrin ([α.sub.1][β.sub.1]-null ([itga1.sup.-/-]), and wild-type littermate mice fed chow or HF. Integrin [α.sub.2][β.sub.1] and integrin [α.sub.1][β.sub.1] signaling pathways have opposing actions. RESULTS--HF-fed mice had IR and increased muscle collagen (Col) III and ColIV protein; the former was associated with increased transcript, whereas the latter was associated with reduced matrix metalloproteinase 9 activity. Rescue of muscle IR by genetic muscle-specific mitochondria-targeted catalase overexpression or by the phosphodiesterase 5a inhibitor, sildenafil, reversed HF feeding effects on ECM remodeling and increased muscle vascularity. Collagen remained elevated in HF-fed [itga2.sup.-/-]-mice. Nevertheless, muscle insulin action and vascularity were increased. Muscle IR in HF-fed [itga1.sup.-/-] mice was unchanged. Insulin sensitivity in chow-fed [itgal.sup.-/-] and [itga2.sup.-/-] mice was not different from wild-type littermates. CONCLUSIONS--ECM collagen expansion is tightly associated with muscle IR. Studies with [itga2.sup.-/-] mice provide mechanistic insight for this association by showing that the link between muscle IR and increased collagen can be uncoupled by the absence of collagen-integrin [α.sub.2][β.sub.1] interaction. Diabetes 60:416-426, 2011, The inflammatory response associated with insulin resistance may have extensive effects on extracellular matrix (ECM) remodeling and endothelial cell function. ECM adaptations that accompany insulin resistance in muscle are of [...]

In this paper, we discuss the structure-preserving H 2 optimal model order reduction (MOR) problem of integral-differential systems based on the projection technique. Different from the common idea, we take a new way to deal with this minimization problem and for the first time reduce the integral-differential systems on the product of two Stiefel manifolds. The cost function is viewed as a function whose parameters are a pair of projection matrices with different dimensions, and then the H 2 optimal MOR problem is reformulated as the minimization problem of the product of two Stiefel manifolds. We extend the Riemannian geometry of the single Stiefel manifold to the product manifold and the Riemannian gradient of the cost function is derived using the orthogonal projection of the product manifold. Further, we design a Riemannian conjugate gradient scheme on the product manifold, and propose a structure-preserving Riemannian conjugate gradient algorithm. The resulting search direction is a descent direction of the cost function. Besides, we show that our algorithm is globally convergent and has the potential application to second-order systems. Finally, numerical examples demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

A major challenge in modern rice production is to achieve the dual goals of high yield and good quality with low environmental costs. This study was designed to determine whether optimized nitrogen (N) fertilization could fulfill these multiple goals. In two-year experiments, two high yielding ‘super’ rice cultivars were grown with different N fertilization management regimes, including zero N input, local farmers’ practice (LFP) with heavy N inputs, and optimized N fertilization (ONF). In ONF, by reducing N input, increasing planting density, and optimizing the ratio of urea application at different stages, N use efficiency and the physicochemical and textural properties of milled rice were improved at higher yield levels. Compared with LFP, yield and partial factor productivity of applied N (PFP) under ONF were increased (on average) by 1.70 and 13.06%, respectively. ONF increased starch and amylose content, and significantly decreased protein content. The contents of the short chains of A chain (degree of polymerization (DP) 6–12) and B1 chain (DP 13–25) of amylopectin were significantly increased under ONF, which resulted in a decrease in the stability of rice starch crystals. ONF increased viscosity values and improved the thermodynamic properties of starch, which resulted in better eating and cooking quality of the rice. Thus, ONF could substantially compensate the negative effects caused by N fertilizer and achieve the multiple goals of higher grain quality and nitrogen use efficiency (NUE) at high yield levels. These results will be useful for applications of high quality rice production at high yield levels.

Radioresistance of prostate cancer (PCa) is a major factor leading to local failure of radiotherapy. STAT3 is an oncogenic protein that was recently found to be activated in PCa tumors. This study aimed to investigate the radiosensitization effect of targeting STAT3 in PCa tumors. Here, the radiosensitization effect of STAT3 blockade was investigated by clonogenic assay, flow cytometry and western blot analysis in human PCa cells in vitroand in vivo. We demonstrated that STAT3 blockade with a STAT3 inhibitor or siRNA increased the radiosensitivity of PCa cells and that radiation together with STAT3 blockade induced more apoptosis and double-strand breaks (DSBs) than radiation alone in LNCaP cells. In addition, radiation induced STAT3 activation and survivin expression in PCa cells, which was inhibited by STAT3 blockade. Transfection with survivin cDNA attenuated the radiosensitization effect of STAT3 blockade. These effects were further confirmed by in vivostudies, which showed that the STAT3 inhibitor enhanced the treatment efficacy of radiation on LNCaP xenografts with decreased STAT3 activation and survivin expression.These findings suggest that STAT3 blockade radiosensitizes PCa cells through regulation of survivin. Thus, our study has revealed STAT3 as a potential sensitizer for irradiation in PCa cells. Its clinical application as an adjuvant in radiotherapy of PCa should be explored in the future.

The interaction mechanism between sodium arsenate and fayalite-type copper slag at 1200 °C was investigated through XRD, XPS, HRTEM, TCLP and other technical means and methods. The results indicated that the proportions of sodium arsenate in the slag and flue gas phases were approximately 30% and 70%, respectively. The addition of sodium arsenate depolymerized the fayalite structure and changed it from a crystalline state to an amorphous state. The fayalite structural changes indicated that the [AsO4] tetrahedron in sodium arsenate combined with the [SiO4] tetrahedron and [FeO4] tetrahedron through bridging oxygen to form a silicate glass structure. The TCLP test results of the samples before and after the high temperature reaction of fayalite and sodium arsenate showed that after high temperature reaction, fayalite could effectively reduce the leaching toxicity of sodium arsenate, reducing the leaching concentration of arsenic from 3025.52 to 12.8 mg /L before and after reaction, respectively.

In recent years, numerous incidents of information leakage have not only violated the privacy of users but also been a key issue hindering the development of cloud computing. How to guarantee the confidentiality of shared data while protecting the privacy of users has become a hot topic of research. In this article, we propose a decentralized attribute-based access control mechanism. Compared with the existing well-known schemes, the proposed scheme enhances private security and the confidentiality of shared data. An anonymous key extraction protocol is introduced to help users prove their identities with zero knowledge and help the authorities to generate legitimate private keys without knowing the users global identifiers and specific attributes. We also eliminate linear relationships among the keys appearing in the previous reported works, which makes unauthorized users unable to combine their private keys to generate a legal secret key or combine their respective decryption results to recover the plaintext message. Performance and security analyses show that the new work is secure against collusion attacks, thus protecting users’ privacy and security. Besides, the security of the proposed scheme is reduced to the q-PBDHE assumption in the standard model.

Molecular adsorption conformations and arrangement configurations on surfaces are important structural aspects of surface stereochemistry, but their roles in steering the structures of metal–organic networks (MONs) remain vague and unexplored. In this study, we constructed MONs by the coordination self-assembly of isocyanides on Cu(111) and Ag(111) surfaces and demonstrated that the MON structures can be steered by surface stereochemistry, including the adsorption conformations of the isocyanide molecules and the arrangement configurations of the coordination nodes and subunits. The coordination self-assembly of 1,4-phenylene diisocyanobenzene afforded a honeycomb MON consisting of 3-fold (isocyano)3–Cu motifs on a Cu(111) surface. In contrast, geometrically different chevron-shaped 1,3-phenylene diisocyanobenzene (m-DICB) failed to generate a MON, which is ascribable to its standing conformation on the Cu(111) surface. However, m-DICB was adsorbed in a flat conformation on a Ag(111) surface, which has a larger lattice constant than a Cu(111) surface, and smoothly underwent coordination self-assembly to form a MON consisting of (isocyano)3–Ag motifs. Interestingly, only C3–Ag nodes with heterotactic configurations could grow into larger subunits; those subunits with heterotactic configurations further grew into Sierpiński triangle fractals (up to fourth order), while subunits with homotactic configurations afforded a triangular MON.

In this article, we propose two new iterative algorithms to solve the frequency-limited Riemannian optimization model order reduction problems of linear and bilinear systems. Different from the existing Riemannian optimization methods, we design a new Riemannian conjugate gradient scheme based on the Riemannian geometry notions on a product manifold, and then generate a new search direction. Theoretical analysis shows that the resulting search direction is always descent with depending neither on the line search used, nor on the convexity of the cost function. The proposed algorithms are also suitable for generating reduced systems over a frequency interval in bandpass form. Finally, two numerical examples are simulated to demonstrate the efficiency of our algorithms. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is a rare malignant tumor that has predominantly affected children and adolescents in the past 50 years. The genomes of OS tumors exhibit a high degree of complexity, which leads to the great challenge of target identification for anti-OS. To date, no efficient therapeutic target for the treatment of OS has been validated in clinical practice. In our previous drug hunting for the treatment of OS by phenotypic screening, we found that thiazolone derivate (R)-8iwas an effective and selective inhibitor against OS in MNNG/HOS cells and in vivo. However, the mechanism of action and specific molecular targets of (R)-8iremain unclear. In this study, we design and synthesize the photo-cross-linking probes based on the lead compound (R)-8iand identify DDX5 as a potential target protein using an activity-based protein profiling strategy. Further experiments including Western blot, shRNA knockdown experiments, cell colony formation, wound healing assays, and cellular thermal shift assays support that (R)-8ibinds to DDX5 and induces its degradation, which affect cell proliferation and migration through the PI3K-AKT-mTOR signaling pathway. The research shows that DDX5 is a potential therapeutic target for the treatment of OS.

The role of hydrogen in the transition to carbon-neutral energy systems will be influenced by key factors such as carbon neutrality pathways, hydrogen production technology costs, and hydrogen transportation costs. Existing studies have not comprehensively analyzed and compared the impact of these key factors on the development of hydrogen supply and demand under China's carbon neutrality pathways. This study uses the Global Change Assessment Model (GCAM) with an upgraded hydrogen module to evaluate the development potential of China's hydrogen industry, considering various carbon neutrality pathways as well as hydrogen production and transportation costs. The findings indicate that, by 2050, hydrogen could account for 8%‒14% of final energy, averting 1.0‒1.7 Bt of carbon emissions annually at an average mitigation cost of 85‒183$ t−1CO2. The total hydrogen production is projected to reach 75‒135 Mt, with 34%‒56% from renewable energy electrolysis and about 15%‒29% from fossil fuel-based CCS. On a sectoral level, by 2050, the hydrogen demand in the industrial and transportation sectors is expected to reach 37‒63 Mt and 30‒42 Mt, with a potential reduction of about 0.6‒0.9 BtCO2and 0.5‒0.6 BtCO2. The share of hydrogen in the final energy of the steel and chemical sectors is estimated to be 9%‒19% and 17%‒25%, collectively accounting for 36%‒42% of total hydrogen demand and 46%‒50% of total emission reduction potential. Realizing hydrogen’s emission reduction potential relies on the rapid development of hydrogen production, transportation, and utilization technologies. Firstly, the development of on-site electrolysis for hydrogen production and early deployment of industrial hydrogen applications should be prioritized to stimulate overall growth of hydrogen industry and cost reduction. Secondly, vigorous development of renewable energy electrolysis and hydrogen end-use technologies like fuel cells should be pursued, along with the demonstration and promotion of hydrogen transportation technologies. Lastly, further advancement of carbon market mechanisms is essential to support the widespread adoption of hydrogen technologies.

Follicle selection in chicken refers to the process of selecting a follicle to enter hierarchy from a cohort of small yellow follicles (SY) with a diameter of 6 to 8 mm. The follicle being selected will develop rapidly and ovulate. Follicle selection is a key stage affecting chicken egg-laying performance. Our previous study showed that the phosphorylation level of lysine (K)-specific demethylase 1A (LSD1) at serine 54 (LSD1Ser54p) was significantly increased in F6 follicles compared to prehierarchal SY follicles, but its function was unclear. Here, the mechanism of this modification, the effect of LSD1Ser54p dephosphorylation on gene expression profile of chicken hierarchal granulosa cells and the function of fibroblast growth factor 9 (FGF9) that is regulated by LSD1Ser54p were further investigated. The modification of LSD1Ser54p was predicted to be mediated by cyclin-dependent kinase 5 (CDK5) and glycogen synthase kinase 3 (GSK3). Treatment of chicken hierarchal granulosa cells with CDK5 inhibitor significantly decreased LSD1Ser54p level (P< 0.05) and LSD1Ser54p interacted with CDK5, suggesting that, in the granulosa cells of chicken hierarchal follicles, LSD1Ser54p modification was carried out by CDK5. When the LSD1Ser54p level decreased in the granulosa cells of chicken hierarchal follicles, both the mRNA expression of FGF9and α-actinin 2 (ACTN2) and the H3K4me2 level in their promoter regions significantly increased (P< 0.05), indicating that this phosphorylation modification enhanced the demethylation activity of LSD1. Moreover, in chicken hierarchal granulosa cells, overexpression of chicken FGF9stimulated their proliferation and increased the mRNA expression of hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroid delta-isomerase 1 (Hsd3b) and steroidogenic acute regulatory protein (StAR). This study collectively revealed that phosphorylation of LSD1 at serine 54 by CDK5 enhanced its demethylation activity in chicken ovarian granulosa cells and regulated genes including FGF9that is engaged in chicken follicle selection.

The present study explored the effects of miR-152-mediated targeting of suppressor of cytokine signaling 3 (SOCS3) on hepatic insulin resistance (HIR) in mice with gestational diabetes mellitus (GDM). Healthy SPF C57BL/6J mice were selected to establish a GDM model.

The superior properties of metal organic frameworks (MOF) can provide great opportunities for merging functional nanoparticles to construct smart and versatile cancer theranostic agents. In this study, on the basis of non-mesoporous nanoparticles (molybdenum disulfide, MoS2), the structure of the MOF shell layer with an adjustable structure can be constructed through the natural coordination interaction between polydopamine (PDA) and iron ion, and the tumor cell target ligand was modified on the surface of the nanocomposite after loading the anticancer drug doxorubicin hydrochloride (DOX) to form a multifunctional cancer theranostics nanoplatform (DOX@MoS2-PMA). Benefiting from the excellent properties of MoS2and MOF, the favorable photothermal properties and pH/near-infrared (NIR) laser-triggered DOX release behavior of composite nanoparticles were demonstrated. Its well-defined nanostructure, adequate colloidal stability, and satisfactory biocompatibility were further evidenced. Furthermore, the selective tumor cell targeting ability of DOX@MoS2-PMA can improve the cellular uptake efficacy and the photothermal-chemotherapy combination therapy can significantly enhance the killing effect on cancer cells both in vitroand in vivo. In addition, fluorescence imaging results show that nanoparticles can efficiently accumulate inside tumors. The photoacoustic (PA) and magnetic resonance (MR) imaging capabilities derived from different components of nanoparticles can perform better imaging effects. To the best of our knowledge, this is the first attempt to merge the performance of MoS2with MOF for PA/MR dual-modality imaging-guided photothermal-chemotherapy combination therapy. Our work presented herein proves that MOF can be combined with non-mesoporous nanoparticles and exhibits excellent performance, thus opening a new avenue for endowing non-mesoporous nanoparticles with an efficient drug loading capacity and practical applications of MOFs in nanomedicine.

Surrogate models are commonly used to reduce the number of required expensive fitness evaluations in optimizing computationally expensive problems. Although many competitive surrogate-assisted evolutionary algorithms have been proposed, it remains a challenging issue to develop an effective model management strategy to address problems with different landscape features under a limited computational budget. This paper adopts a coarse-to-fine evaluation scheme basing on two surrogate models, i.e., a coarse Gaussian process and a fine radial basis function, for assisting a differential evolution algorithm to solve computationally expensive optimization problems. The coarse Gaussian process model is meant to capture the general contour of the fitness landscape to estimate the fitness and its degree of uncertainty. A surrogate-assisted environmental selection strategy is then developed according to the non-dominance relationship between approximated fitness and estimated uncertainty. Meanwhile, the fine radial basis function model aims to learn the details of the local fitness landscape to refine the approximation quality of the new parent population and find the local optima for real-evaluations. The performance and scalability of the proposed method are extensively evaluated on two sets of widely used benchmark problems. Experimental results show that the proposed method can outperform several state-of-the-art algorithms within a limited computational budget.

To develop new fetal weight prediction models using automated fractional limb volume (FLV). A prospective multicenter study measured fetal biometry within 4 to 7 days of delivery. Three‐dimensional data acquisition included the automated FLV that was based on 50% of the humerus diaphysis (fractional arm volume [AVol]) or 50% of the femur diaphysis (fractional thigh volume [TVol]) length. A regression analysis provided population sample–specific coefficients to develop 4 weight estimation models. Estimated and actual birth weights (BWs) were compared for the mean percent difference ± standard deviation of the percent differences. Systematic errors were analyzed by the Student ttest, and random errors were compared by the Pitman test. A total of 328 pregnancies were scanned before delivery (BW range, 825–5470 g). Only 71.3% to 72.6% of weight estimations were within 10% of actual BW using original published models by Hadlock et al (Am J Obstet Gynecol1985; 151:333–337) and INTERGROWTH‐21st (Ultrasound Obstet Gynecol2017; 49:478–486). All predictions were accurate by using sample‐specific model coefficients to minimize bias in making these comparisons (Hadlock, 0.4% ± 8.7%; INTERGROWTH‐21st, 0.5% ± 10.0%; AVol, 0.3% ± 7.4%; and TVol, 0.3% ± 8.0%). Both AVol‐ and TVol‐based models improved the percentage of correctly classified BW ±10% in 83.2% and 83.9% of cases, respectively, compared to the INTERGROWTH‐21st model (73.8%; P< .01). For BW of less than 2500 g, all models slightly overestimated BW (+2.0% to +3.1%). For BW of greater than 4000 g, AVol (–2.4% ± 6.5%) and TVol (–2.3% ± 6.9%) models) had weight predictions with small systematic errors that were not different from zero (P> .05). For these larger fetuses, both AVol and TVol models correctly classified BW (±10%) in 83.3% and 87.5% of cases compared to the others (Hadlock, 79.2%; INTERGROWTH‐21st, 70.8%) although these differences did not reach statistical significance. In this cohort, the inclusion of automated FLV measurements with conventional 2‐dimensional biometry was generally associated with improved weight predictions.

MoS2nanomaterial with the micro-pompon structure was synthesized by a surfactant-assisted hydrothermal method. The morphologies and structures of as-prepared MoS2micro-pompon were investigated by adding different types of surfactants such as cetyltrimethyl ammonium bromide (CTAB), sodium dodecylbenzene sulphonate (SDBS), and polyvinyl pyrrolidone (PVP). The results indicated that the morphology of MoS2could be controlled and changed effectively by the cationic surfactant of CTAB. A reasonable growth mechanism for hollow structured MoS2micro-pompon by hydrothermal processes was proposed. Further, photocatalytic degradation properties of MoS2micro-pompon under visible light were evaluated by degradation of common organic dyes, which include rhodamine B (RhB), congo red, methyl orange, and methylene blue. The results indicated that MoS2micro-pompon owned the highly selective catalytic ability to RhB with degradation efficiency of 95% in 60 min and 68% in 30 min. With the additive of the surfactant, the MoS2-CTAB sample exhibited an enhanced ability of photocatalytic activity where degradation efficiency was improved to 92% in 30 min. The method employed in this work could be expanded to fabricate other sulfides with the controllable morphology and structure to further regulate the photocatalytic performance.

Supplementation of surface-active additives during enzymatic saccharification of biomass helps to increase the activity of cellulase and thus reduces the enzyme dosage in the bioconversion processes. To evaluate the boost effect of additives on enzymatic hydrolysis, five different water-soluble polymers were studied in this work, including poly(vinyl alcohol) (PVA), poly(vinyl pyrrolidone) (PVP), poly(ethylene glycol) (PEG), cationic polyacrylamide (C-PAM), and polyethyleneimine (PEI). Lignin-containing substrates and lignin-free substrates were used in enzymatic hydrolysis tests. It was found that an addition of 10 mg polymer/g-substrate leads to up to a 25.4% increase in glucan hydrolysis and a 13.2% increase in xylan hydrolysis depending on the type of the substrate and polymer. Glucan digestibility achieved from low enzyme loading of 5 FPU/g-glucan with the polymer is comparable to that from 15 FPU/g-glucan enzyme loading. Reducing the amount of the enzyme required could make biomass conversion more cost-effective. Significantly higher yields were obtained with nonionic polymers (PVP, PVA, and PEG) compared with ionic polymers (PEI and C-PAM) for all substrates.

Polymer Janus particles (PJPs) have been extensively investigated due to their intriguing features which cannot be achieved in traditional counterparts. Chiral polymer particles also have constituted a unique research area in polymer science. However, how to construct PJPs derived from chiral polymers, especially chiral helical polymers, still remains a significant academic challenge. This contribution reports the first success in preparing optically active PJPs constructed by chiral helical substituted polyacetylene via emulsion polymerization combined with solvent evaporation to induce phase separation. In emulsion polymerization systems, polymethyl methacrylate worked as a template and separated from polyacetylene domains in the course of acetylenic monomers’ polymerization and evaporation of the solvent, by which optically active PJPs were formed. The major influencing factors were explored to elucidate their effects on the formation and morphology of PJPs. Mushroom- and bowl-like PJPs were obtained. Scanning electron microscopy (SEM) images ascertain nonspherical morphologies of the obtained PJPs. Circular dichroism and UV–vis absorption spectra demonstrate their optical activity, which originated in the predominantly one-handed helical polyacetylene chains constructing the PJPs. A formation mechanism was then proposed for understanding this unprecedented type of PJPs.

The online social networks have greatly transformed the way that people interact with each other, and have salient impact on our lives. However, there exist common security challenges and limitations in attracting users' activities due to the centralised structure of current online social networks. We exploit the blockchain technology to design a new photo-sharing social network, in which users' social behaviours are stored in the blockchain. Blockchain technology allows the authenticity and credibility of data to be improved and precludes data tampering. To improve efficiency, we design a new blockchain consensus algorithm to support fast and frequent transactions. Moreover, a new incentive model is designed to quantify the contribution of user in a more accurate and trustworthy way, thereafter, reward the user with financial incentives, as well as enable the user to easily control and claim the ownership of every photos they share to the network.

Two homogenized as-cast magnesium (Mg)–1 wt% manganese (Mn) alloys containing 1·0 and 4·0 wt% alloying yttrium (Y) were processed at an extrusion ratio of 17:1 at 400°C using a ram speed of 0·3 mm/s. The effect of yttrium additions on the microstructure and mechanical properties of the extruded alloy was analyzed and compared. The average grain size of the extruded Mg–1Mn–4Y (MW14) alloy was much smaller than that of the extruded Mg–1Mn–1Y (MW11) alloy. In addition, the tensile strength of the MW14 alloy was higher than that of the MW11 alloy at the investigated temperature ranging form RT to 200°C, although the former exhibited a lower elongation to failure. The fracture surface of the MW14 alloy exhibited the cleavage fracture mode. Conversely, a dimple was observed in the MW11 alloy which the significant differences in performance between the two alloys are attributed to their Y contents.