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With the development of Internet of Things (IoT) technology,its application scenarios have exploded recently,and such applications are generally delay-sensitive and resource-constrained.It is a focused issue in the way of offloading the real-time tasks under the condition of limited resource.Besides,it is a NP-hard combinatorial optimization problem to allocate limited computational resources for the real-time tasks.To solve this problem,this paper proposes a real-time resource management algorithm based on Lyapunov optimization,aiming at stabilizing the virtual queues while optimizing the total power consumption and total utility.Firstly,the optimization model for the total power consumption and weighted total utility is proposed under the constraint of computation and communication resources.This model contains of two virtual buffer queues,and tasks are unloaded in a device-to-device (D2D) scheduling model.Then,an optimization algorithm is proposed based on Lyapunov optimization to decompose the joint long-term average sum energy consumption and sum utility optimization problem into a series of real-time optimization problems.To solve these problems,a greedy-based matching algorithm is proposed.Experimental results demonstrate that the performance of the proposed algorithm is 8.6% better than the best result of random method and can approximate the exhaustive attack method under different connection degrees.

Silver (Ag) nanocrystals are appealing due to their excellent antimicrobial properties. Synthesis of harmless Ag nanocrystals by low toxic reagents remains significant. Herein, an environmentally benign solvothermal process was applied to synthesize Ag nanocrystals in ethylene glycol (EG) dissolving silver nitrate and sodium oleate. Silver ions were reduced by EG to zero-valent Ag atoms that underwent nucleation and growth to form oleate-stabilized Ag nanocrystals. Multiple experimental parameters including the reaction time, temperature, concentration of Ag precursor, and the molar ratio of sodium oleate and silver nitrate were investigated to probe their effects on morphological structures and surface plasmon resonance (SPR) properties of resulting Ag nanocrystals. Results from UV–Vis absorption spectra and TEM images show that structural and SPR features of Ag nanocrystals are extremely sensitive to the reaction temperature as well as the molar ratio of sodium oleate and silver nitrate. Especially, two absorption bands appeared. The short wavelength (~ 450 nm) represents the characteristic SPR of Ag nanospheres. While, the plasmon absorption at long wavelength (500–700 nm depending on reaction conditions) indicates the anisotropic or heterogeneous structures of Ag nanocrystals that maybe pave their potential applications in asymmetric catalysis, selective growth of coating materials, nanomedicine and optoelectronics. [ABSTRACT FROM AUTHOR]

Due to the difficulty in self-degradation of waste polyethylene terephthalate (PET) products, in order to solve the environmental problems and energy resource waste caused by PET, it is necessary to explore effective recovery methods for the treatment of waste PET products. For the chemical recovery process, the chemical recovery and reuse methods of waste PET were introduced from the aspects of alkaline hydrolysis, neutral hydrolysis, acidic hydrolysis, methanol alcoholysis, ethylene glycol alcoholysis, and ammonia/amine hydrolysis, and various chemical depolymerization methods were compared. The studies show that chemical recovery can obtain the initial raw material of PET, maintain the quality of PET products, and recycle and upgrade PET waste to add value to chemicals. Improving the recycling rate of waste PET products and converting them into renewable green resources is one of the effective measures to promote the clean and low-carbon transformation of energy. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to explore the shared and specific signalling pathways involved in diabetic retinopathy (DR), diabetic peripheral neuropathy (DPN) and diabetic nephropathy (DN). Methods: Differentially expressed mRNAs and lncRNAs were identified by high-throughput sequencing. Subsequently, functional enrichment analysis, protein-protein interaction (PPI) analysis and lncRNAs-mRNAs networks were conducted to determine the pathogenic mechanisms underlying DR, DPN and DN. Results: Twenty-six biological pathways were shared among DR, DPN and DN groups compared to the type 2 diabetes mellitus (T2DM) group without complications, and most of the shared pathways and core proteins were involved in immune and inflammatory responses of microvascular damage. Cytokine‒cytokine receptor interactions and chemokine signalling pathway were the most significant and specific pathways for DR, and the lncRNA‒mRNA regulatory networks affected DR by targeting these pathways. Sphingolipid metabolism and neuroactive ligand-receptor pathways were found to be specific for the pathogenesis of DPN. Moreover, multiple amino acid metabolic pathways were involved in the occurrence and progression of DN. Conclusions: Diabetic retinopathy, DPN and DN exhibited commonality and heterogeneity simultaneously. The shared pathologic mechanisms underlying these diabetic complications are involved in diabetic microvascular damage via immune and inflammatory pathways. Our findings predict several biomarkers and therapeutic targets for these diabetic complications. [ABSTRACT FROM AUTHOR]

Objective. We aim to evaluate the clinical effect of combined topical 20% autologous serum eye drops (ASEs) along with silicone–hydrogel soft contact lenses (SCLs) in the treatment of chemical burn-induced bilateral corneal persistent epithelial defects (PEDs) and to review the literature of related studies. Methods. From January 1, 2017, to December 31, 2019, we conducted a retrospective chart review of 8 patients with chemical burn-induced bilateral corneal PEDs who were unsuccessfully treated with conventional medical therapy and were then treated with combined topical 20% (v/v) ASEs and silicone–hydrogel CLs. The clinical effects and effectiveness of the combined treatment were evaluated. Results. The bilateral corneal PEDs healed in all sixteen eyes of the eight patients within 2 weeks. The patients did not report any discomfort associated with the combined treatment. Improved ocular comfort/visual acuity and decreased conjunctival injection correlated with healing. No recurrent corneal epithelial breakdown was noted during the 3-month posttreatment follow-up. Conclusions. The combined treatment of silicone–hydrogel CLs and ASEs can help to stabilize the ocular surface and successfully treat chemical burn-induced bilateral corneal PEDs. It may be considered as an alternative treatment method for patients with bilateral chemical burn-induced corneal PEDs with potential corneal melting. [ABSTRACT FROM AUTHOR]

Objective: Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy, and its pathogenesis is still unclear. Studies have shown that circular RNAs (circRNAs) can regulate blood glucose levels by targeting mRNAs, but the role of circRNAs in GDM is still unknown. Therefore, a joint microarray analysis of circRNAs and their target mRNAs in GDM patients and healthy pregnant women was carried out. Methods: In this study, microarray analyses of mRNA and circRNA in 6 GDM patients and 6 healthy controls were conducted to identify the differentially expressed mRNA and circRNA in GDM patients, and some of the discovered mRNAs and circRNAs were further validated in additional 56 samples by quantitative realtime PCR (qRT-PCR) and droplet digital PCR (ddPCR). Results: Gene ontology and pathway analyses showed that the differentially expressed genes were significantly enriched in T cell immune-related pathways. Cross matching of the differentially expressed mRNAs and circRNAs in the top 10 KEGG pathways identified 4 genes (CBLB , ITPR3 , NFKBIA , and ICAM1) and 4 corresponding circRNAs (circ-CBLB, circ-ITPR3, circ-NFKBIA, and circ-ICAM1), and these candidates were subsequently verified in larger samples. These differentially expressed circRNAs and their linear transcript mRNAs were all related to the T cell receptor signaling pathway, and PCR results confirmed the initial microarray results. Moreover, circRNA/miRNA/mRNA interactions and circRNA-binding proteins were predicted, and circ-CBLB, circ-ITPR3, and circ-ICAM1 may serve as GDM-related miRNA sponges and regulate the expression of CBLB, ITPR3, NFKBIA, and ICAM1 in cellular immune pathways. Conclusion: Upregulation of T cell receptor signaling pathway components may represent the major pathological mechanism underlying GDM, thus providing a potential approach for the prevention and treatment of GDM. [ABSTRACT FROM AUTHOR]

Brake wear gives 16%–55% by mass to total non-exhaust traffic related PM10 emissions in urban environments. While engines have become cleaner in the past decades, few improvements were made to lower non-exhaust emission until recently. Researchers have developed several experimental methods over the past years to assess brake emissions. However, observations tend to differ from a method to another with respect to many disciplines, ranging from particle system characterization to brake cycles, and it remains difficult to compare results of different research groups. It is so crucial to get a consensus on the standard experimental method. The following article lists limits which influence measurements and has to be taken into account when comparing works from different laboratories. This article also discusses how to design tests to get a relevant braking particle system characterization. [ABSTRACT FROM AUTHOR]

One of the central goals in molecular evolutionary biology is to determine the sources of variation in the rate of sequence evolution among proteins. Gene expression level is widely accepted as the primary determinant of protein evolutionary rate, because it scales with the extent of selective constraints imposed on a protein, leading to the well-known negative correlation between expression level and protein evolutionary rate (the E–R anticorrelation). Selective constraints have been hypothesized to entail the maintenance of protein function, the avoidance of cytotoxicity caused by protein misfolding or nonspecific protein–protein interactions, or both. However, empirical tests evaluating the relative importance of these hypotheses remain scarce, likely due to the nontrivial difficulties in distinguishing the effect of a deleterious mutation on a protein's function versus its cytotoxicity. We realized that examining the sequence evolution of viral proteins could overcome this hurdle. It is because purifying selection against mutations in a viral protein that result in cytotoxicity per se is likely relaxed, whereas purifying selection against mutations that impair viral protein function persists. Multiple analyses of SARS-CoV-2 and nine other virus species revealed a complete absence of any E–R anticorrelation. As a control, the E–R anticorrelation does exist in human endogenous retroviruses where purifying selection against cytotoxicity is present. Taken together, these observations do not support the maintenance of protein function as the main constraint on protein sequence evolution in cellular organisms. [ABSTRACT FROM AUTHOR]

Private entrepreneurs and government organizations widely adopt Facebook fan pages as an online social platform to communicate with the public. Posting on the platform to attract people's comments and shares is an effective way to increase public engagement. Moreover, the comment functions allow users who have read the posts to express their thoughts. Hence, it also enables us to understand the users' emotional feelings regarding that post by analyzing the comments. The goal of this study is to investigate the public image of organizations by exploring the content on fan pages. In order to efficiently analyze the enormous amount of public opinion data generated from social media, we propose a Bi-directional Long Short-Term Memory (BiLSTM) that can model detailed sentiment information hidden in those words. It first forecasts the sentiment information in terms of Valence and Arousal (VA) values of the smallest unit in a text, and later fuses this into a deep learning model to further analyze the sentiment of the whole text. Experiments show that our model can achieve state-of-the-art performance in terms of predicting the VA values of words. Additionally, combining VA with a BiLSTM model results in a boost of the performance for social media text sentiment analysis. Our method can assist governments or other organizations to improve their effectiveness in social media operations through the understanding of public opinions on related issues. [ABSTRACT FROM AUTHOR]

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