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In this study, the Jaya optimization algorithm is used to address the micro-grid energy management optimization problem using a hybrid PV-wind-microturbine-storage energy system. The main goals of this study are to reduce environmental pollution, increase microturbine operating efficiency, and minimize the cost of power generated. The overall objective of the proposed optimization method employed in the PV-WECS system is to run the PV-WECS systems at full capacity while running the microturbine when the PV-WECS systems are unable to produce all of the required power. The amount of emissions and costs of generated energy are reduced when BESS is used in the microgrid system. Furthermore, it is observed from the results that there is about 61.39% cost saving in the micro-grid operational costs and 38% carbon emissions reductions using the proposed optimization algorithm compared to the other metaheuristic algorithms used in this study. To demonstrate the appropriateness and supremacy of the proposed algorithm over the various optimization techniques for energy management of the proposed micro-grid systems, simulation results from the proposed algorithm are compared with those from other population-based metaheuristic algorithms, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Teaching Learning Based Optimization (TLBO), and Genetic Algorithms (GA). It is clear that the proposed algorithm outperforms and produces better results than the existing metaheuristic optimization techniques. More importantly, it illustrates the viability and efficacy of the proposed JAYA optimization approach in addressing the issue of energy management for large-scale power systems.

This research developed a signal amplification strategy to construct a highly sensitive electrochemiluminescent (ECL) aptasensor by incorporating dysprosium metal-organic framework (Dy-MOF) as a co-reaction accelerator (CRA) in gadolinium (Gd) luminescent complex based ECL system. A new Gd(III) complex GdPc(acac) (Pc = phthalocyanine, acac = acetylacetonate) with semi-sandwich structure was rationally selected as ECL emitter, exhibiting excellent luminescence performance owing to the "antenna effect" from the conjugated macrocyclic ligand. For further improving the sensitivity of the ECL biosensor, Dy-MOF was introduced into the ECL system as CRA. The purposive design and configuration of the Dy-MOF structure accelerated the separation and transport of photogenerated charges, and the nanosheets formed by the composite material provided more active sites, which could not only greatly increased the luminophore loading, but also effectively shorten the transport distance of ions and co-reactants. The constructed biosensor showed superior performance to monitor kanamycin within 0.001 pg/mL-1000 ng/mL and a detection limit down to 0.3 fg/mL (S/N = 3). The current work opened up a skillful strategy to amplify ECL singnal, extending the application field of lanthanide complexes and providing valuable information for the future biosensor design.

Schematic diagram of label-free colorimetric apta-assay based on AuNPs with peroxidase-like amplification.

A dual-mode material with ultraviolet and visible persistent luminescence for multi-mode anti-counterfeiting and information encryption.

The fast development of technology and the popularity and prevalence of social media are constantly changing people's way of living especially their communication patterns. Computer-mediated communication facilitates human contact. Meanwhile, net language becomes widely accepted by computer-mediated communicators. Originating from the text-based form, net language evolves into a multi-modal physical form with a combination of texts, symbols, emojis, pictures and other forms of messages. The multi-modality of net language gives rise to difficulties for hearers or readers of the computer-mediated communication to understand the hidden message due to the ambiguous and polysemic nature of symbols. To clarify hearer's understanding and ensure the smooth conduct of computer-mediated communication, the conceptual blending theory will be useful in processing the multi-modal net language. With a four-space network and three operation mechanism, the emergent meaning will be constructed.

In this work, an aptamer against

Factor analysis is an important way of data mining which can be performed using MATLAB, Python, and so on. We studied the urban competitiveness of Southwest cities in China using factor analysis. Two factors were extracted among 22 original variables. The factor score of cities was obtained using Python and were classified into three categories: Chongqing, Chengdu, Kunming and Guiyang are the first-tier cities; Baoshan, Pu’er, Lincang and Lijiang cities are of the lowest tier; the remaining cities belong to the second tier.

The aims of our study are: i) to explore whether plasma levels of BDNF/GDNF are valuable in the diagnosis of first-episode depression; ii) to discuss whether there is an association between peripheral plasma levels of BDNF/GDNF and patients' depression severity and cognitive dysfunction; iii) to explore the association between plasma levels of BDNF/GDNF and the effectiveness of antidepressant treatment.Ninety patients with first-episode unmedicated MDD and healthy controls were recruited. MDD patients were treated with antidepressant medication for 8 weeks. Patients were assessed for clinical symptoms using HDRS-17 and HAMA-14. Social and neurocognitive functioning of all subjects was assessed at baseline using the Functional Assessment Test Short Form (FAST) and the MATRICS Consensus Cognitive Battery (MCCB). At the same time, peripheral venous blood was drawn from all subjects for BDNF/GDNF peripheral plasma level analysis at baseline and after 8 weeks of treatment.The baseline BDNF/GDNF levels in MDD patients were significantly lower than that in healthy controls. The area under ROC curve (AUC) of baseline plasma BDNF and GDNF levels predicting MDD was 0.776 (95 % CI: 0.705-0.846, p 0.001) and 0.864 (95 % CI: 0.808-0.920, p 0.001), respectively. The baseline GDNF level (beta = 0.425, p = 0.001), the autonomy score of FAST (beta = -0.247, p = 0.037) and BACS-SC score of MCCB (beta = 0.323, p = 0.039) were predictors of HDRS-17 reduction rate after 8 weeks' antidepressant treatment.A longer follow-up period than 8 weeks may make the results more convincing, and the sample size of this study is still insufficient.The decreased plasma levels of BDNF and GDNF are strong indicators for predicting the occurrence of MDD. This preliminary finding highlighted the value of GDNF plasma concentrations in the diagnosis of MDD and the prognosis of antidepressant treatment.

Programmed death ligand 1 (PD-L1) is widely known as an immune checkpoint, and immunotherapy through the inhibition of checkpoint molecules has become an important component in the successful treatment of tumours via programmed death 1 (PD-1)/PD-L1 signalling pathways. However, its biological functions and expression profile in colorectal cancer (CRC) are elusive. We previously found that PD-L1 can bind to PD-L1 and cause cell detachment. However, the detailed molecular mechanisms of how PD-L1 binds to PD-L1 and how it transmits signals to the cell remain unclear. In this study, we disclosed that PD-L1 expression was dramatically upregulated in CRC compared to normal tissues. Ectopic expression of PD-L1 inhibits cell adhesive capacity and promotes cell migration in CRC cell lines, while silencing PD-L1 had the opposite effects and suppressed invasion and proliferation. Mechanistically, PD-L1 was found to promote epithelial-mesenchymal transition (EMT) through the ERK signalling molecule pathway and interacted with the 1-86 aa fragment of KRAS to transduce signals. Collectively, our study demonstrated the role of PD-L1 after binding to PD-L1 in CRC, thereby providing a new theoretical basis for further improving immunotherapy with anti-PD-L1 antibodies.

Science and technology are advancing at a breakneck pace. Only individuals with strong mathematical skills and knowledge will be able to adapt to social development and progress. However, advanced mathematics education is often neglected in vocational universities. Student and conceptual factors are invariably to blame. Therefore, it is urgent to improve the teaching quality of advanced mathematics in vocational universities. In improving the teaching quality, it is necessary to change the teaching mode, advocate interest in learning, emphasize on the cultivation of students’ skills during teaching, implement stratified teaching, lay emphasis on mathematical models, and strengthen the evaluation and assessment of students.

Bombyx mori nucleopolyhedrovirus (BmNPV) is a serious threat to sericulture. Nevertheless, no effective control strategy is currently available. The innate immunity of silkworm is critical in the antiviral process. Exploring its molecular mechanism provides theoretical support for the prevention and treatment of BmNPV. Insect hormone receptors play an essential role in regulating host immunity. We found a correlation between Bombyx mori ecdysone receptor B1 (BmEcR-B1) and BmNPV infection, whereas the underlying mechanism remains unclear. In this study, the expression patterns and sequence characteristics of BmEcR-B1 and its isoform, BmEcR-A, were initially analyzed. BmEcR-B1 was found to be more critical than BmEcR-A in silkworm development and responses to BmNPV. Moreover, RNAi and an overexpression in BmN cells showed BmEcR-B1 had antiviral effects in the presence of 20-hydroxyecdysone (20E); Otherwise, it had no antiviral activity. Furthermore, BmEcR-B1 was required for 20E-induced apoptosis, which significantly suppressed virus infection. Finally, feeding 20E had no significant negative impacts on larval growth and the cocoon shell, suggesting the regulation of this pathway has practical value in controlling BmNPV in sericulture. The findings of this study provide important theoretical support for understanding the mechanism of the silkworm innate immune system in response to BmNPV infection.

Agile Product Line Engineering (APLE), a relatively new approach combining the two successful methods of Agile Software Development (ASD) and Software Product Lines (SPLs), makes product lines more responsive to ever-changing customer needs or market changes. However, SPLs often fail to keep up with market demand due to high coordination costs, slow development processes, and long release cycles in the case of frequent changes in business requirements; in agile software projects, the lack of a unified specification for describing requirements leads to high coordination costs and inconvenient requirement management. Some studies in the literature have proposed optimized approaches to integrate ASD and SPLs, but they still have not covered all aspects of APLE’s characteristics, and software resource reuse is rarely considered in these approaches during product line development. In view of this, we propose a collaborative framework of agile product line engineering for software resource reuse, namely ScrumOntoSPL. The ScrumOntoSPL approach efficiently merges ASD and SPL based on the agile method Scrum, SPL architecture, and ontology technology. In ScrumOntoSPL, uniform requirement specification is constructed by utilizing ontology, and the Matching Requirement with Component (MRC) process is designed to match product new requirements and software resources stored in a resource pool. In addition, we evaluated the proposed framework and approach with CMMI. In the end, a case study of a software development tool called IMC-Tool based on ScrumOntoSPL for a universal Instrument Microcontroller Chip (IMC) is discussed. The IMC-Tool case illustrates that the ScrumOntoSPL has the advantages of dynamically managing demand changes, enhancing software resource reuse, reducing coordination costs, and reducing time to market.

Supplementary Materials and Figure Legends 1-2 from Inhibition of Growth and Metastasis of Human Hepatocellular Carcinoma by Antisense Oligonucleotide Targeting Signal Transducer and Activator of Transcription 3

Purpose: Hepatocellular carcinoma (HCC) is an aggressive malignancy and is a devastating clinical complication of chronic liver disease. Therapeutic options are limited mainly because the genetic and biochemical understanding of this disease remains fragmented. We intended to study the role of signal transducer and activator of transcription 3 (STAT3) aberrant signaling in HCC malignancy, and the therapeutic potential of inhibition of STAT3 expression for HCC.Experimental Design: A 2′-O-methoxyethylribose–modified phosphorothioate antisense oligonucleotide (ASO) was used to knock down STAT3 expression in different human HCC cell lines, including the highly metastatic HCCLM3 derived from orthotopic implantation and subsequent lung metastasis in athymic mice. The effects of STAT3 ASO treatment on HCC cells, metastasis, and animal survival following HCCLM3 orthotopic implantation were evaluated.Results: Specific suppression of phosphorylated STAT3 reduced its DNA-binding activity, inhibited the expression of vascular endothelial growth factor, survivin, matrix metalloproteinases 2 and 9, reduced cell proliferation and migratory potential, induced apoptosis in vitro, and inhibited intradermal angiogenesis and s.c. tumorigenesis upon injection in mice. In mice bearing orthotopically implanted HCCLM3, STAT3 inhibition following therapeutic treatment with STAT3 ASO reduced circulating vascular endothelial growth factor and basic fibroblast growth factor, decreased intratumor CD34-positive microvessel density, intrahepatic and intraperitoneal transmission, and lung metastasis. HCC tumor volume and weight were reduced and the survival time of mice bearing orthotopically xenografted HCC was approximately doubled in STAT3 ASO–treated mice (P < 0.05).Conclusions: Constitutively activated STAT3 is essential for the growth, survival, and metastasis of HCC, suggesting that STAT3-targeted therapy may have utility for HCC.

Supplementary Figures 1-2 from Inhibition of Growth and Metastasis of Human Hepatocellular Carcinoma by Antisense Oligonucleotide Targeting Signal Transducer and Activator of Transcription 3

In recent years, the tourism industry in traditional villages has been developing rapidly due to the national call to vigorously advocate for and promote traditional culture, but there are plenty of problems and challenges facing the protection and development of traditional villages. The GPS action tracking method was adopted in this study to investigate the trajectory of tourists in typical traditional villages of Huizhou and to screen out different spatial sites with different characteristics based on the kernel density analysis. Thereby, people’s behavior in different spatial sites were analyzed in depth using the method of behavior observation, and ultimately, the relevance between the spatial environment of traditional villages, the characteristics of tourists’ actions, and their staying preferences were discussed, and hence an improvement strategy of spatial optimization was put forward accordingly. The research shows that, in Huizhou traditional villages, different scales and forms of space will affect tourists’ tour paths; the unreasonable distribution of commercial formats leads to the uneven distribution of village vitality; and traditional elements and landscape facilities are more likely to cause tourists to demonstrate a variety of behaviors. These findings provide (1) a basis for further understanding the spatial characteristics of traditional villages in Huizhou; (2) a basis for the spatial optimization of traditional villages; and (3) a new research perspective and feasible technical route for the protection, renewal, and sustainable development of traditional villages in other regions.