Forward Intensity Model Monitoring Using Multivariate Exponential Weighted Moving Average Scheme

We propose a parameter monitoring method for the forward intensity model – the default probability prediction model of the Credit Research Initiative (CRI). We review the relative statistical process control scheme in the field of engineering. Based on this, we propose a new Multivariate Exponential Weighted Moving Average (MEWMA) scheme to monitor the forward intensity model monthly. This new chart might be applied to identify and diagnose the out-of-control (OC) parameters in real time as the data updating, which reduces the cost of recalculating all parameters and improve the operational and calculational efficiency of the default prediction models in practical application

Proposing a New Research Framework for Loan Allocation Strategies in P2P Lending

One of the frontier Web 2.0 applications is online peer-to-peer (P2P) lending marketplace, where individual lenders and borrowers can virtually meet for loan transactions. From a lender’s perspective, she not only wants to lower investment risk but also to gain as much return as possible. However, P2P lenders possess the inherent problem of information asymmetry that they don’t really know if a borrower has capability to pay the loan or is truthfully willing to pay it in due time, leading them to a disadvantaged situation when making the decision of lending money to the borrower. This study intends to consider the loan allocation as an optimization research problem using the research framework based upon modern portfolio theory with the aim of helping lenders achieve the two goals of gaining high return and lowering risk at the same time. The expected results of this research are twofold: 1) compared to a logistic regression based credit scoring method, we expect to make more profits for lenders with risk level unchanged, and 2) compared to a linear regression based profit scoring method, we expect to lower risk without lowering return. Our proposed new model could offer insights into how individual lenders can optimize their loan allocation strategies when considering return and risk simultaneously

Screening and simulation of offshore CO2-EOR and storage:A case study for the HZ21-1 oilfield in the Pearl River Mouth Basin, Northern South China Sea

CO2-enhanced oil recovery (CO2-EOR) and storage is currently the most effective and economic technology for reducing CO2 emissions from burning fossil fuels in large scale. This paper is the first effort of proposing a modelling assessment of CO2-EOR and storage in the HZ2-1 oilfield in the Pearl River Mouth Basin in northern South China Sea offshore Guangdong Province. We attempt to couple the multi-parameter dimensionless quick screening model and reservoir compositional simulation for optimization of site screen and injection simulation. Through the quick screening, the reservoirs are ranked by FOR dimensionless recovery R-D, and by CO2 storage in pore volume SCO2. Our results indicate that SCO2 is highly pressure dependent and not directly related to R-D. Of these reservoirs, CO2-EOR and storage potential of the M10 was estimated through a compositional simulation as a case study based on a 3D geological model. Nine scenarios of CO2 injection operations have been simulated for 20 years with different well patterns and injection pressures. The simulation results represent an obvious improvement in oil production by CO2 flooding over No - CO2 production. The best operation for M10 is miscible CO2 flooding, which led to the higher recovery factors of 52%(similar to)58% and CO 2 stored masses of 8.1 x 10(6 similar to)10.8 x 10(6)t The optimum operation for CO2 injection should be set well pattern in region of injector I1 and high injection pressure for miscible flooding. In a whole, the HZ21-1 field can be used as a candidate geological site for GDCCUS project. We are fully aware of the limitation in the primary modelling including reservoir and fluid properties and production history matching, and regard this study as a general and hypothetic proposal

The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets

BackgroundMethamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients.MethodFecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features.ResultsMUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes. Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria. The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients.ConclusionIn conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings

Mannose-modified erythrocyte membrane-encapsulated chitovanic nanoparticles as a DNA vaccine carrier against reticuloendothelial tissue hyperplasia virus

IntroductionThe erythrocyte membranes used in nanovaccines include high membrane stability, long circulation life, adaptability and extremely good bio compatibility. Nanoparticles encapsulated by erythrocyte membranes are widely used as ideal drug delivery vehicles because of their high drug loading, long circulation time, and excellent biocompatibility. The mannose modification of delivery materials can help target mannose receptors (MRs) to deliver antigens to antigen-presenting cells (APCs).MethodsIn this study, the antigen gene gp90 of avian reticuloendotheliosis virus (REV) was encapsulated with carboxymethyl chitosan (CS) to obtain CSgp90 nanoparticles, which were coated with mannose-modied fowl erythrocyte membranes to yield CS-gp90@M-M nanoparticles. The physicochemical characterization and immune response of the CS-gp90@M-M nanoparticles were investigated in vitro and in vivo.ResultsCS-gp90@M-M nanoparticles were rapidly phagocytized in vitro by macrophages to induce the production of cytokines and nitric oxide. In vivo, CS-gp90@M-M nanoparticles increased cytokine levels, the CD4+/8+ ratio, REV-specific antibodies in the peripheral blood of chicks, and the mRNA levels of immune-related genes in the spleen and bursa of immunized chicks. CS-gp90@M-M nanoparticles could be targeted to lymphoid organs to prolong the retention time of the nanoparticles at the injection site and lymphatic organs, leading to a strong, sustained immune response. Moreover, the CS-gp90@M-M nano-vaccine showed a lasting immunoprotective effect and improved the body weight of chicks after the challenge.ConclusionOverall, CS-gp90@M-M nanoparticles can be used in vaccine designs as an effective delivery carrier with immune response-enhancing effects

machine learning model for MUD diagnosis

The code for machine learning in the maniscript "Identification of patients with methamphetamine use disorder : machine learning models based on gut microbial characteristics.

Structure of the archaeal Cascade subunit Csa5 : Relating the small subunits of CRISPR effector complexes

This work was funded by a grant from the Biotechnology and Biological Sciences Research Council (BBSRC) (REF: BB/G011400/1) to M.F.W. and J.H.N. and a BBSRC-funded studentship to J.R.The Cascade complex for CRISPR-mediated antiviral immunity uses CRISPR RNA (crRNA) to target invading DNA species from mobile elements such as viruses, leading to their destruction. The core of the Cascade effector complex consists of the Cas5 and Cas7 subunits, which are widely conserved in prokaryotes. Cas7 binds crRNA and forms the helical backbone of Cascade. Many archaea encode a version of the Cascade complex (denoted Type I-A) that includes a Csa5 (or small) subunit, which interacts weakly with the core proteins. Here, we report the crystal structure of the Csa5 protein from Sulfolobus solfataricus. Csa5 comprises a conserved α-helical domain with a small insertion consisting of a weakly conserved β-strand domain. In the crystal, the Csa5 monomers have multimerized into infinite helical threads. At each interface is a strictly conserved intersubunit salt bridge, deletion of which disrupts multimerization. Structural analysis indicates a shared evolutionary history among the small subunits of the CRISPR effector complexes. The same α-helical domain is found in the C-terminal domain of Cse2 (from Type I-E Cascade), while the N-terminal domain of Cse2 is found in Cmr5 of the CMR (Type III-B) effector complex. As Cmr5 shares no match with Csa5, two possibilities present themselves: selective domain loss from an ancestral Cse2 to create two new subfamilies or domain fusion of two separate families to create a new Cse2 family. A definitive answer awaits structural studies of further small subunits from other CRISPR effector complexes.Publisher PDFPeer reviewe

Quick assessment to ascertain technical rational well spacing density in artificial water flooding oilfield

Optimization of technical rational well spacing density (TRWSD) is a crucial part of the study of oilfield development. However, the methods widely used previously have some disadvantages as followings: (1) Some quoted theories and formulas for algorithms are intractable. (2) Some are incompatible with the reality as they assumed too many conditions which are more ideal. (3) The influence factors considered by other algorithms are not comprehensive and irrational. (4) In applications, the applicable conditions are ignored by some algorithms. Aiming at the problems above, this paper has built a quick estimation model of TRWSD and proposed a new optimizing method of TRWSD, based on the comprehensive investigation of pressure distribution and the theoretical model of rational ratio of oil to water wells (RROWW) in artificial water flooding oilfield. Verification by reservoir numerical simulation model and actual data of the field implementation shows that the TRWSD model is reliable, and practical. It is revealed from the studies that the injection-production pressure system factors are the main ones to control TRWSD except water cut, such as the oil-bearing area of producing geological reserves, liquid productivity index, injection-production ratio and number of injection-production wells, and so on. And compared with the previous ones, the TRWSD method comprehensively takes into account such the factors as injection-production unbalance, density difference between oil and water, volume factor, start-up pressure gradient of injection wells, start-up pressure gradient of production wells and so on. Hereinafter, the new model can be applied for the calculation of the TRWSD and related parameters at any injection-production development stages, reservoir types and reservoir pressure distributions in artificial water flooding oilfield, all of which means that the new method has a strong promising adaptabilities and prospects in the water flooding oilfield with close well spacings or during high water cut stage

DEC-205 receptor-mediated long-circling nanoliposome as an antigen and Eucommia ulmoides polysaccharide delivery system enhances the immune response via facilitating dendritic cells maturation

DEC-205 receptor-mediated dendritic cells (DC) targeting nanoliposomes is a promising delivery system in eliciting an immune response against pathogens. When this delivery system carries both antigen and immunomodulator, it can effectively regulate the DC function as well as the initial T cell response. To maximize the desired therapeutic effects of Eucommia ulmoides Oliv. polysaccharides (EUPS), and induce an efficient humoral and cellular immune response against an antigen, we encapsulated the OVA and EUPS in long-circling nanoliposomes and conjugated it with anti-DEC-205 receptor antibody to obtain a DEC-205-targeted nanoliposomes (anti-DEC-205-EUPS-OVA-LPSM). The physicochemical properties and immune-modulating effects were investigated in vitro and in vivo by a series of the experiment to evaluate the targeting efficiency of anti-DEC-205-EUPS-OVA-LPSM. In vitro, anti-DEC-205-EUPS-OVA-LPSM (160 μg mL−1) could enhance DCs proliferation and increase their phagocytic efficiency. In vivo anti-DEC-205-EUPS-OVA-LPSM remarkably promoted the OVA-specific IgG and IgG isotypes levels, enhanced the splenocyte proliferation, and induced the NK cell and CTL cytotoxicity. Besides, the anti-DEC-205-EUPS-OVA-LPSM enhanced the maturation of DCs. These findings suggest that the DEC-205 receptor antibody-conjugated EUPS nanoliposome can act as an efficient antigen delivery system to enhance the cellular and humoral immune response by promoting DC maturation. This indicates that the anti-DEC-205-EUPS-OVA-LPSM has significant potential as an immune-enhancing agent and antigen delivery system