Reflected Backward Stochastic Differential Equations Driven by L\'{e}vy Process

In this paper, we deal with a class of reflected backward stochastic differential equations associated to the subdifferential operator of a lower semi-continuous convex function driven by Teugels martingales associated with L\'{e}vy process. We obtain the existence and uniqueness of solutions to these equations by means of the penalization method. As its application, we give a probabilistic interpretation for the solutions of a class of partial differential-integral inclusions.Comment: 14 page

An M2e-based multiple antigenic peptide vaccine protects mice from lethal challenge with divergent H5N1 influenza viruses

<p>Abstract</p> <p>Background</p> <p>A growing concern has raised regarding the pandemic potential of the highly pathogenic avian influenza (HPAI) H5N1 viruses. Consequently, there is an urgent need to develop an effective and safe vaccine against the divergent H5N1 influenza viruses. In the present study, we designed a tetra-branched multiple antigenic peptide (MAP)-based vaccine, designated M2e-MAP, which contains the sequence overlapping the highly conserved extracellular domain of matrix protein 2 (M2e) of a HPAI H5N1 virus, and investigated its immune responses and cross-protection against different clades of H5N1 viruses.</p> <p>Results</p> <p>Our results showed that M2e-MAP vaccine induced strong M2e-specific IgG antibody responses following 3-dose immunization of mice with M2e-MAP in the presence of Freunds' or aluminium (alum) adjuvant. M2e-MAP vaccination limited viral replication and attenuated histopathological damage in the challenged mouse lungs. The M2e-MAP-based vaccine protected immunized mice against both clade1: VN/1194 and clade2.3.4: SZ/406H H5N1 virus challenge, being able to counteract weight lost and elevate survival rate following lethal challenge of H5N1 viruses.</p> <p>Conclusions</p> <p>These results suggest that M2e-MAP presenting M2e of H5N1 virus has a great potential to be developed into an effective subunit vaccine for the prevention of infection by a broad spectrum of HPAI H5N1 viruses.</p

A Recombinant Vaccine of H5N1 HA1 Fused with Foldon and Human IgG Fc Induced Complete Cross-Clade Protection against Divergent H5N1 Viruses

Development of effective vaccines to prevent influenza, particularly highly pathogenic avian influenza (HPAI) caused by influenza A virus (IAV) subtype H5N1, is a challenging goal. In this study, we designed and constructed two recombinant influenza vaccine candidates by fusing hemagglutinin 1 (HA1) fragment of A/Anhui/1/2005(H5N1) to either Fc of human IgG (HA1-Fc) or foldon plus Fc (HA1-Fdc), and evaluated their immune responses and cross-protection against divergent strains of H5N1 virus. Results showed that these two recombinant vaccines induced strong immune responses in the vaccinated mice, which specifically reacted with HA1 proteins and an inactivated heterologous H5N1 virus. Both proteins were able to cross-neutralize infections by one homologous strain (clade 2.3) and four heterologous strains belonging to clades 0, 1, and 2.2 of H5N1 pseudoviruses as well as three heterologous strains (clades 0, 1, and 2.3.4) of H5N1 live virus. Importantly, immunization with these two vaccine candidates, especially HA1-Fdc, provided complete cross-clade protection against high-dose lethal challenge of different strains of H5N1 virus covering clade 0, 1, and 2.3.4 in the tested mouse model. This study suggests that the recombinant fusion proteins, particularly HA1-Fdc, could be developed into an efficacious universal H5N1 influenza vaccine, providing cross-protection against infections by divergent strains of highly pathogenic H5N1 virus

Analysis of Aspergillus niger isolated from ancient palm leaf manuscripts and its deterioration mechanisms

Abstract Palm leaf manuscripts (PLMs), venerable historical artefacts containing Buddhist scriptures, history, mathematics and literature, which are carried by palm leaves (Corypha umbraculifera) and are highly susceptible to microbial degradation during prolonged storage. This degradation results in significant alterations to both the appearance and material properties of PLMs, but the precise mechanism underlying this deterioration remains a mystery. To this end, the present study focused on ancient PLMs from Xishuangbanna Dai Autonomous Prefecture in Yunnan Province, China. The objective of present study was to isolate, culture and identify the microorganisms typically found in these manuscripts and to use them to biodegrade the carriers of PLMs. Detailed observations of the biodegradation behavior of these microorganisms on the carriers of PLMs were carried out, together with characterizations of the hierarchical structure and mechanical properties of the leaf fiber cell walls. This comprehensive analysis provided insights into the deterioration mechanisms of the carriers of PLMs. The study revealed the presence of the common fungus Aspergillus niger on ancient PLMs. Aspergillus niger can secrete cellulase, lipase, and acidic substances after colonizing on the carriers of PLMs. These substances sequentially damage the carrier's epidermal cells, mesophyll cells, and leaf fibers, leading to the separation of different tissue structures. At the molecular level, the lipids on the surface of the leaves were degraded initially, and sequential depolymerization of hemicellulose, amorphous cellulose, and crystalline cellulose occurred. Additionally, this study firstly applied nanoindentation technology in the research of PLMs. The mechanical properties of the cell walls underwent notable alterations due to the modifications in chemical and crystalline structure of the carriers of PLMs upon the biodegradation of Aspergillus niger. Specifically, the hardness and elastic modulus of leaf fiber cell walls showed an initial increasing and then decreasing trend, consistent with the trend of cellulose crystallinity, which also provided a new reference for assessing the degree of deterioration of PLMs

High-Permeability Wood with Microwave Remodeling Structure

This paper presents the development of a microwave puffed wood (MPW) with novel and unique structural features in its internal structure that are based on natural wood (NW). The focus of the research was on the comprehensive visualization of the structural characteristics of MPW from the macroscopic to the microscopic scale followed by an exploration of its impregnation capabilities. The results showed that the volume of MPW increased by about 9% compared to NW due to the presence of a large number of cracked cavities. The CT images indicated that there was a significant difference between the macroscopic cracks produced by microwave processing and the natural cracks in the wood. The mercury intrusion test results showed that macro-pores increased while the micro-pores decreased in the MPW compared to in the NW. The MPW showed good fluid permeability and liquid absorption performance. The phenolic resin penetration rate of the MPW was about 20 times that of the NW, and the material absorption was more than 2 times that of the NW. The crack space enabled the MPW to serve as a fluid transportation and a storage warehouse. MPW is a super container based on natural materials. It has broad potential in more fields, such as in wood composite materials

Pretreatment thrombocytosis as a significant prognostic factor in malignant mesothelioma: a meta-analysis

The current meta-analysis analyzed the prognostic impact of elevated platelet count before the treatment of malignant mesothelioma (MM). We performed a search for articles published up to April 15, 2016 in PubMed, MEDLINE, EMBASE, and Web of Science, which evaluated elevated platelet count and survival outcome of MM. STATA version 12 was used for statistical analysis. The pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) were combined to calculate overall effects. The assessment of heterogeneity was tested by the Cochran Q and I2 statistics. The sensitivity and meta-regression analyses were performed to explore the origin of heterogeneity. We analyzed 18 eligible studies (3602 patients) that evaluated the correlation between pretreatment platelet count and overall survival (OS). Elevated platelet count was a prognostic factor of poor OS, with a pooled HR of 1.56 (95% CI = 1.36–1.77). However, significant heterogeneity was observed in the included studies (I2 = 86.0%, p < 0.001). Sensitivity and meta-regression analyses were performed to trace the origin of heterogeneity. Only the variable type (multivariable or univariate model) was traced as the origin of heterogeneity. Hence, we conducted a subgroup analysis of variable type. The HR was 1.66 (95% CI = 1.41–1.91) in the multivariable group and no significant heterogeneity was observed (I2 = 0.0%, p = 0.476). In conclusion, high pretreatment platelet count resulted in poor OS in MM. Therefore, platelet count could be an adequate and useful factor of prognosis for MM

Microstructural and Micromechanical Characterization of Modified Urea-Formaldehyde Resin Penetration into Wood

Characterization of the adhesive penetration behavior in wood is highly desired for optimizing the manufacturing processes and product properties. In this study, modified urea-formaldehyde (UF) adhesive was used to prepare glued laminated timber (Cryptomeria fortunei Hooibrenk). The depth of gross penetration was measured by fluorescence microscopy (FM), which showed the UF passed through 1.5 to 3.5 earlywood tracheids (with an average penetration depth of 88.95 ± 27.49 μm) or 0.5 to 4.0 latewood tracheids (with an average penetration depth of 36.39 ± 15.14 μm). In addition, the distribution of cell wall penetration was observed clearly by confocal laser scanning microscopy (CLSM). The adhesive was found to diffuse into the cell walls of surface tissues embedded in the UF. To verify the results from CLSM, the mechanical properties of cell walls with and without adhesive penetration were measured through nanoindentation (NI). The reduced elastic modulus of exposed cell walls (18.10 GPa) was roughly equal to that of fully filled cell walls (17.68 GPa) but significantly greater than that of reference ones (15.71 GPa). The hardness showed a similar variation trend for these three types of cell walls. Combining the three techniques, both the microstructure and micromechanics of the adhesive penetration behavior can be quantitatively identified in a complementary manner

Asymmetric dark current in double-barrier quantum well infrared photodetectors

Asymmetric dark current and photocurrent versus voltage characteristic in the Double Barrier Quantum Wells (DBQWs) photovoltaic infrared photodetector has been studied. A model based on asymmetric potential barriers was proposed. The asymmetric potential thick barrier, which due to the Si dopant segregation during growth makes a major contribution to the asymmetrical I-V characteristic, calculations based on our model agree well with experimental results. This work also confirms the potential use of this DBQWs for infrared photodetector with large responsivity and little dark current under negative bias

A Neighborhood Rough Sets-Based Attribute Reduction Method Using Lebesgue and Entropy Measures

For continuous numerical data sets, neighborhood rough sets-based attribute reduction is an important step for improving classification performance. However, most of the traditional reduction algorithms can only handle finite sets, and yield low accuracy and high cardinality. In this paper, a novel attribute reduction method using Lebesgue and entropy measures in neighborhood rough sets is proposed, which has the ability of dealing with continuous numerical data whilst maintaining the original classification information. First, Fisher score method is employed to eliminate irrelevant attributes to significantly reduce computation complexity for high-dimensional data sets. Then, Lebesgue measure is introduced into neighborhood rough sets to investigate uncertainty measure. In order to analyze the uncertainty and noisy of neighborhood decision systems well, based on Lebesgue and entropy measures, some neighborhood entropy-based uncertainty measures are presented, and by combining algebra view with information view in neighborhood rough sets, a neighborhood roughness joint entropy is developed in neighborhood decision systems. Moreover, some of their properties are derived and the relationships are established, which help to understand the essence of knowledge and the uncertainty of neighborhood decision systems. Finally, a heuristic attribute reduction algorithm is designed to improve the classification performance of large-scale complex data. The experimental results under an instance and several public data sets show that the proposed method is very effective for selecting the most relevant attributes with high classification accuracy