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To investigate the ability of the ratio of blood urea nitrogen (BUN) to serum albumin ratio (BAR) in patients with sepsis in intensive care units (ICUs) to predict the prognosis of short-and long-term death. Data are from the Marketplace for Intensive Care Medical Information IV (MIMIC-IV v2.0) database for patients with sepsis as defined by SEPSIS-3. The primary outcome was 30-day mortality and the secondary outcome was 360-day mortality. Kaplan–Meier (KM) survival curves were plotted to describe differences in BAR mortality in different subgroups and area under the curve (AUC) analysis was performed to compare the predictive value of sequential organ failure assessment (SOFA), BAR, blood urea nitrogen (BUN) and albumin. Multivariate Cox regression models and subgroup analysis were used to determine the correlation between BAR and 30-day mortality and 360-day mortality. A total of 7656 eligible patients were enrolled in the study with a median BAR of 8.0 mg/g, including 3837 in the ≤ 8.0 group and 3819 in the BAR > 8.0 group, with 30-day mortality rates of 19.1% and 38.2% (P < 0.001) and 360-day mortality rates of 31.1% and 55.6% (P < 0.001). Multivariate Cox regression models showed an increased risk of death for 30-day mortality (HR = 1.219, 95% CI 1.095–1.357; P < 0.001) and 360-day mortality (HR = 1.263, 95% CI 1.159–1.376; P < 0.001) in the high BAR group compared to the low BAR group. For the 30-day outcome, the area under the curve (AUC) was 0.661 for BAR and 0.668 for 360-day BAR. In the subgroup analysis, BAR remained an isolated risk factor for patient death. As a clinically inexpensive and readily available parameter, BAR can be a valuable forecaster of prognosis in patients with sepsis in the intensive care unit. [ABSTRACT FROM AUTHOR]

Polymer infiltrated ceramic network (PICN) composites, which combine the flexibility of resin materials with the rigidity of ceramic materials, have become a hot spot for research and development because of their structural and mechanical features that are similar to those of real teeth. In this paper, the porous feldspar ceramic part sintered body is used as the inorganic skeleton to composite with resin, and the preparation processes of porous feldspar ceramic were investigated, including the effects of different sintering temperature and holding time on the pore diameter and porosity of porous feldspar ceramic, and the effects on the properties of resin infiltration ceramic composites. The results show that when the sintering temperature is 750 ℃ and the holding time is 0 min, it has the most suitable porosity and pore size for resin infiltration. The hardness, flexural strength and flexural modulus of PICN composites were 125.5 N/mm2, 162.85 MPa, and 27.01 GPa respectively and the water absorption value and water solubility value are 10.51 μg/mm3 and 2.29 μg/mm3. [ABSTRACT FROM AUTHOR]

Long non-coding metastasis-associated lung adenocarcinoma transcript (lnc-Malat1) emerges as a novel regulator in skeletal muscle development, while its function and the related mechanism is not fully revealed yet. In this study, knockdown of lnc-Malat1 by siRNA significantly inhibited the expression of myoblast marker genes (MyHC , MyoD , and MyoG) and slow muscle fiber marker genes (MyHC I), together with repressed expression of mitochondria-related genes COX5A , ACADM , CPTA1 , FABP3 , and NDUFA1. Overexpression of lnc-Malat1 exerted an opposite effect, promoting myoblast differentiation and slow muscle fiber formation. Dual luciferase reporter assay revealed a direct interaction between lnc-Malat1 and miR-129-5p, and overexpression of lnc-Malat1 significantly inhibited miR-129-5p expression, thereby elevating the expression of Mef2a , miR-129-5p target protein. In addition, enforced expression of lnc-Malat1 restored the inhibitory effect of miR-129-5p on myoblast differentiation and MyHC I expression. Taken together, our results suggest that lnc-Malat1 promotes myoblast differentiation, and maintains the slow muscle fiber phenotype via adsorbing miR-129-5p. [Display omitted] [ABSTRACT FROM AUTHOR]

Here, we present some Reduced Basis (RB) methods for fluid infiltration problems through certain porous media modeled as dual-continuum with localized uncertainties. We apply dimension reduction techniques to construct a reduced order model. In the RB methods, to perform the offline–online computation decomposition, the model inputs need to be affinely dependent on the uncertainties. We develop a Proper Orthogonal Decomposition and Greedy (POD-Greedy) RB method for stochastic dual-continuum models. In the POD-Greedy RB framework, for heterogeneous porous media, we need to solve the stochastic dual-continuum models many times using very fine grid to construct a set of snapshots for building optimal reduced basis. This offline computation may be very expensive. To improve the offline computational efficiency, we further develop a local–global RB method, which integrates the coupled multiscale and multicontinuum approach using Generalized Multiscale Finite Element Method (GMsFEM) to the POD-Greedy RB method. To illustrate the efficiency of the proposed methods, we present two numerical examples for stochastic dual-continuum models. Our numerical results show that both the POD-Greedy RB method and the local–global RB method greatly improve the computation efficiency with high approximation accuracy. [ABSTRACT FROM AUTHOR]

Coupled flow-geomechanics model is needed for investigating the stress change, rock-compaction behavior, and stress-dependent properties in many practical reservoir scenarios. However, the coupled model of large-scale simulation problems usually encounters large matrix system and high computational expenses, where the time stepping is a crucial factor for numerical stability and computational efficiency. Here, we report an adaptive time stepping with the modified local error method to reduce iteration time and improve the computational efficiency for the coupled flow-geomechanics modeling. Firstly, the iterative coupling approach with the fixed-stress method is introduced, where the flow and geomechanics equations are sequentially solved at each time step. Secondly, since updating geomechanics module consumes most of the computing time of the coupled system, the modified local error method is mainly used for geomechanics module to adapt the time step size based on the change of displacement. Finally, a synthetic two-dimensional coupled problem is established to apply the proposed adaptive time stepping approach, where the numerical results including the computational efficiency are compared with the results from regular iteratively coupled method and the fully coupled model. The sensitivity about the local error tolerance on the numerical results is also investigated. The geomechanical responses regarding mechanical loading is validated by comparing with the analytical solution of Terzaghi's consolidation problem. The numerical results of the two-dimensional coupled model show the modified local error method not only yields a higher-order solution for better accuracy, but also significantly reduces the iteration number and computational time. [ABSTRACT FROM AUTHOR]

Compositional simulation is often required for modeling complex oil recovery processes, such as CO 2 enhanced oil recovery ( Chen and Reynolds, 2016; Dai et al., 2014 ). Flash calculation using Equation of State (EOS) is very CPU expensive in compositional simulation. Conventional approaches for initial guess of K-values usually have several levels of limitations. This paper reports our research motivated to provide trustworthy initial guess for flash calculation and further improve flash performance in isothermal processes. Reservoir fluid composition changes are categorized into two different scenarios: (a) slightly varying or constant composition changes in depletion process; and (b) sharp varying composition in gas injection process. Scenario (a) is reasonably parameterized as a compositional space of K-value and vapor mole fraction varied with pressure. Considering the actual simulation of gas injection process, a compositional space is defined via introducing a key pseudo composition as a controlling variable in addition to pressure. Flash calculation is formulated through direct solution of those non-linear equations in phase-split calculation, and solved by combining successive substitution iteration (SSI) and Newton-Raphson (NR) method. Using interpolation from the constructed compositional space, it is found that the initial guess of K-values for flash calculation are always obtained with safeguard. A variety of fluid samples has been applied for testing this new flash technique. The results show that initial guesses of K-values based on Wilson’s correlation results cause much more flash iterations and even failures in some gas injection examples. On the other hand, the proposed method shows significant advantages in reducing the number of flash iterations in all examples. In addition, the SSI procedure in flash can even be bypassed and only NR procedure and a simple Rachford-Rice Equation Preconditioning is sufficient. [ABSTRACT FROM AUTHOR]

Thin sheets of bean curd (TSBC), a favorite food in China, is mostly vacuum packed to maintain the shelf life. However, the vacuum packing processing will cause adhesion between sheets, which is difficult to peel. To solve this problem, a rapid dehydration technique for the TSBC using cold plasma was developed. The surface structure and physicochemical properties of the TSBC treated by cold plasma were evaluated. The results indicated that water contact angle increased from 0° to 66.37° and 66.94°, and adhesion between sheets decreased from 2.81 g. sec to 0.01 g.sec. It was due to the removal of the bulk-phase water from the TSBC. And scanning electron microscopy showed the formation of a dense structure on the TSBC surface. Moreover, surface structure determination revealed that the cold plasma etching led to the depolymerization of protein and the exposure of hydrophobic points without any effect on the primary structure. • TSBC treated by cold plasma formed a dense surface structure, reducing the adhesion between sheets. • The etching effects of cold plasma led to the depolymerization of protein of TSBC. • More hydrophobic groups of protein in TSBC were exposed, improving the surface hydrophobicity. [ABSTRACT FROM AUTHOR]

Because of its high theoretical specific capacity, lithium-sulfur batteries are regarded as one of the most promising secondary batteries. However, there are still a series of problems, which seriously affect the commercial application of lithium-sulfur batteries. Therefore, a magnetic porous carbon material was developed in this work for the modification of lithium-sulfur battery separators, which may reduce the shuttle effect of polysulfides and increase its electrochemical performances. The solvothermal preparation of Ni-Zn bimetallic MOF precursors was followed by a high-temperature carbonization in nitrogen environment to sublimate Zn ions and produce porous structures, achieving Ni@C(Zn) composite. In order to improve the electrochemical performances of lithium-sulfur batteries, the Ni@C(Zn) composite was coated on one side of the polyethylene (PE) separator. Ni@C(Zn) composite displays good physisorption and chemisorption properties, and it can also operate as a secondary current collector to promote the usage of active materials as well as inhibiting shuttle effect of polysulfides. By using Ni@C(Zn) coated PE separator, the initial discharge specific capacity of lithium sulfur battery is as high as 1278.6 mAh g−1 at a current density of 0.05 C when the S cathode is loaded with 3 mg cm−2 active materials. Furthermore, the discharge specific capacity in the first cycle at 0.5 C is 749.4 mAh g−1, which remains at 461 mAh g−1 after 500 long cycles, and the capacity retention rate is as high as 61.5%. Even when the S loading is as high as 5 mg cm−2, it can still experience a stable cycle of 100 cycles at 0.2 C. • Ni@C(Zn) composite was derived by bimetallic Ni-Zn MOFs. • Ni@C(Zn) composite was used as separator modification layer of lithium sulfur battery. • larger specific surface area and higher porosity can better block the shuttle of polysulfides. • Ni@C(Zn) composites have good catalytic effect which can promote the redox conversion of polysulfides. [ABSTRACT FROM AUTHOR]

Because of its high theoretical specific capacity, lithium-sulfur batteries are regarded as one of the most promising secondary batteries. However, there are still a series of problems, which seriously affect the commercial application of lithium-sulfur batteries. Therefore, a magnetic porous carbon material was developed in this work for the modification of lithium-sulfur battery separators, which may reduce the shuttle effect of polysulfides and increase its electrochemical performances. The solvothermal preparation of Ni-Zn bimetallic MOF precursors was followed by a high-temperature carbonization in nitrogen environment to sublimate Zn ions and produce porous structures, achieving Ni@C(Zn) composite. In order to improve the electrochemical performances of lithium-sulfur batteries, the Ni@C(Zn) composite was coated on one side of the polyethylene (PE) separator. Ni@C(Zn) composite displays good physisorption and chemisorption properties, and it can also operate as a secondary current collector to promote the usage of active materials as well as inhibiting shuttle effect of polysulfides. By using Ni@C(Zn) coated PE separator, the initial discharge specific capacity of lithium sulfur battery is as high as 1278.6 mAh g−1 at a current density of 0.05 C when the S cathode is loaded with 3 mg cm−2 active materials. Furthermore, the discharge specific capacity in the first cycle at 0.5 C is 749.4 mAh g−1, which remains at 461 mAh g−1 after 500 long cycles, and the capacity retention rate is as high as 61.5%. Even when the S loading is as high as 5 mg cm−2, it can still experience a stable cycle of 100 cycles at 0.2 C. • Ni@C(Zn) composite was derived by bimetallic Ni-Zn MOFs. • Ni@C(Zn) composite was used as separator modification layer of lithium sulfur battery. • larger specific surface area and higher porosity can better block the shuttle of polysulfides. • Ni@C(Zn) composites have good catalytic effect which can promote the redox conversion of polysulfides. [ABSTRACT FROM AUTHOR]

As a result of the low concentration of avian influenza viruses in samples for routine screening, the separation and concentration of these viruses are vital for their sensitive detection. We present a novel three-dimensional printed magnetophoretic system for the continuous flow separation of the viruses using aptamer-modified magnetic nanoparticles, a magnetophoretic chip, a magnetic field, and a fluidic controller. The magnetic field was designed based on finite element magnetic simulation and developed using neodymium magnets with a maximum intensity of 0.65 T and a gradient of 32 T/m for dragging the nanoparticle-virus complexes. The magnetophoretic chip was designed by SOLIDWORKS and fabricated by a three-dimensional printer with a magnetophoretic channel for the continuous flow separation of the viruses using phosphate-buffered saline as carrier flow. The fluidic controller was developed using a microcontroller and peristaltic pumps to inject the carrier flow and the viruses. The trajectory of the virus-nanoparticle complexes was simulated using COMSOL for optimization of the carrier flow and the magnetic field, respectively. The results showed that the H5N1 viruses could be captured, separated, and concentrated using the proposed magnetophoretic system with the separation efficiency up to 88% in a continuous flow separation time of 2 min for a sample volume of 200 μL. [ABSTRACT FROM AUTHOR]

Conventional compositional simulators are usually difficult to interpret the different gas oil ratio (GOR) from tight oil reservoirs, and this also indicates an unreliable prediction of ultimate hydrocarbon recovery. We realize that there are two issues related to the compositional simulation of production in tight oil reservoirs. Firstly, tight oil reservoirs typically exhibit extremely small matrix pore size in the order of nanometers, so the capillary pressure between vapor and liquid phases is considerable such that the PVT of the confined fluid deviates from that of the bulk fluid with capillary pressure ignored. Secondly, during depletion process, rock compaction causes pore space reduction and brings remarkable changes in rock properties. In this work we implement rigorous confined fluid phase behavior calculation depending on capillary pressure and rock compaction in a fully compositional simulator. Capillary pressure in matrix nanopores is calculated by Leverett J-function. Further, the impact of capillarity on phase equilibrium is taken into account through modifying the stability test and two-phase flash calculation. Dynamic rock compaction is considered in the simulator via rock compaction tables, such that fluid mobility decreases with permeability reduction and capillary effect is simultaneously coupled. The unique implementation in the simulator captures the dynamic behavior of rock and fluid properties in tight oil reservoirs. Typical suppression of bubble point pressure and reduction of oil viscosity and density is observed from our simulation results. Reservoir-scale simulation results show that this model resolves the problem of the inconsistent GOR in tight oil production and greatly facilitates the history matching process. The enhanced compositional simulation will ultimately improve our understanding of tight oil reservoirs and provide better guidance for recovery prediction. [ABSTRACT FROM AUTHOR]

We unify the diffusion and seepage process for nonlinear gas transport in multiscale porous media via a proposed new general transport equation. A coherent theoretical derivation indicates the wall-molecule and molecule-molecule collisions drive the Knudsen and collective diffusive fluxes, and constitute the system pressure across the porous media. A new terminology, nominal diffusion coefficient can summarize Knudsen and collective diffusion coefficients. Physical and numerical experiments show the support of the new formulation and provide approaches to obtain the diffusion coefficient and permeability simultaneously. This work has important implication for natural gas extraction and greenhouse gases sequestration in geological formations. [ABSTRACT FROM AUTHOR]

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on penelope and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: penelope was first translated from fortran to c++ and the result was confirmed to produce equivalent results to the original code. The c++ code was then adapted to cuda in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gpenelope highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gpenelope as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gpenelope. Ultimately, gpenelope was applied toward independent validation of patient doses calculated by MRIdian's kmc. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread fortran implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gpenelope with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of penelope. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems. [ABSTRACT FROM AUTHOR]

The state of the art of modeling fluid flow in shale reservoirs is dominated by dual-porosity models which divide the reservoirs into matrix blocks that significantly contribute to fluid storage and fracture networks which principally control flow capacity. However, recent extensive microscopic studies reveal that there exist massive micro- and nano-pore systems in shale matrices. Because of this, the actual flow mechanisms in shale reservoirs are considerably more complex than can be simulated by the conventional dual-porosity models and Darcy's law. Therefore, a model capturing multiple pore scales and flow can provide a better understanding of the complex flow mechanisms occurring in these reservoirs. This paper presents a micro-scale multiple-porosity model for fluid flow in shale reservoirs by capturing the dynamics occurring in three porosity systems: inorganic matter, organic matter (mainly kerogen), and natural fractures. Inorganic and organic portions of shale matrix are treated as sub-blocks with different attributes, such as wettability and pore structures. In kerogen, gas desorption and diffusion are the dominant physics. Since the flow regimes are sensitive to pore size, the effects of nano-pores and micro-pores in kerogen are incorporated into the simulator. The multiple-porosity model is built upon a unique tool for simulating general multiple-porosity systems in which several porosity systems may be tied to each other through arbitrary connectivities. This new model allows us to better understand complex flow mechanisms and eventually is extended into the reservoir scale through upscaling techniques. Sensitivity studies on the contributions of the different flow mechanisms and kerogen properties give some insight as to their importance. Results also include a comparison of the conventional dual-porosity treatment and show that significant differences in fluid distributions and dynamics are obtained with the improved multiple-porosity simulation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to report the first preliminary study of the recently introduced combinatorial multilevel (CML) method for solver preconditioning in large-scale reservoir simulation with coupled geomechanics. The CML method is a variant of the popular algebraic multigrid (AMG) method yet with essential differences. The basic idea of this new approach is to construct a hierarchy of matrices using the discrete geometry of the graph, based on support theory for preconditioners. In this way, the CML method combines the merits of both geometric and algebraic multigrid methods. The resulting hybrid approach not only provides a simpler and faster setup phase compared to AMG, but the method can be proven to exhibit strong convergence guarantees for arbitrary symmetric diagonally dominant matrices. In addition, the underlying theoretical soundness of the CML method contrasts to the heuristic AMG approach, which often can show slow convergence for difficult problems. This new approach is implemented in a reservoir simulator for both pressure and poroelastic displacement preconditioners in the multistage preconditioning technique. We present results based on several known benchmark problems and provide a comparison of performance and complexity with the widespread preconditioning schemes used in large-scale reservoir simulation. An adaptation of CML for non-symmetric matrices is shown to exhibit excellent convergence properties for realistic cases. [ABSTRACT FROM AUTHOR]

Herein, two-ligand nickel-based MOF (JUC-85Ni) have been prepared by choosing high N-containing and S-containing ligand. On this basis of the research, the NiS 2 nanoparticles dispersed N and S co-doped carbon materials (NiS 2 @NSC) are fabricated through the sulfidation of JUC-85Ni precursors with thioacetamide (TAA). The rationally designed NiS 2 @NSC catalysts are conducted a test for catalytically reducing 4-nitrophenol (4-NP) to environment friendly 4-aminophenol (4-AP) under NaBH 4 alkaline condition. The superior features endows the catalyst with outstanding catalytic activity and recycling performance, and support it great potential for wastewater treatment. The N, S -codoped carbon-coated NiS 2 nanoparticle composites (NiS 2 @NSC) are accurately synthesized by using two-ligand MOF as precursors through sulfidation with thioacetamide. Synergetic effect endow NiS 2 @NSC with excellent catalytic activity and stability for 4-nitrophenol reduction. [Display omitted] • The NiS 2 nanoparticles dispersed N, S co-doped carbon nanocomposites are rationally synthesized. • Synergetic effect endows catalyst with unusual catalytic activity in 4-NP reduction. • The proposal catalytic mechanism for NiS 2 @NSC is proposed in detail. • The high stability stems from the thin carbon around NiS 2 nanoparticles. [ABSTRACT FROM AUTHOR]

• Ni-MOF derived Ni-C composites are used as separator coating layer of Li-S battery. • The influence of different morphology Ni-C composites are compared. • Ni nanodots are proved to have catalytic effect on the conversion of polysulfides. In order to solve the problems caused by the low conductivity of sulfur and the shuttle effect of polysulfides in lithium-sulfur battery (LSB), we conducted a series of studies and successfully prepared Ni-C composite materials employing Ni-MOF as the precursor, which were used as coating materials for the separator of LSB. Two kinds of ligands, terephthalic acid and trimesic acid were used to react with nickel nitrate to obtain Ni-MOF precursors and their carbonized products were named as Ni-C(B) and Ni-C(T) respectively. Ni-MOF precursors with different morphologies were obtained by different ligands, the precursor of Ni-C(B) is the petal-like layered microspheres and the morphology maintained after calcination, the precursor of Ni-C(T) has the structure of drug flake and agglomerates into a massive structure during the reaction. Because of the uniform distribution of nickel particles and the advantages in morphology and specific surface area, the performance of batteries equipped with Ni-C(B) modified separator is better than that of Ni-C(T) sample. Through a series of electrochemical performance tests, the results are consistent with our expectations. When the sulfur area density in positive electrode is 3 mg cm−2, the highest discharge capacity of the battery using Ni-C(B) coated separator is 1413.7 mAh g−1 at 0.05C, 1169.7 mAh g−1 at 0.1C and 997.3 mAh g−1 at 0.3C. Furthermore, the initial discharge capacity is 926 mAh g−1 at 0.5 C and can retain a capacity of 600 mAh g−1 after 300 cycles. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is a chronic infectious disease which remains a main cause of death worldwide, and arises more and more concerns in recent years. CytochromeP450 (CYP450) is involved in the metabolism of many exogenous and endogenous compounds, and its polymorphism is associated with many diseases. The objective of our study was to explore the relationship between CYP450 polymorphisms and TB susceptibility in Northwest Chinese Han population. 506 TB patients and 506 controls were recruited for our study, and their DNA were extracted. Six single nucleotide polymorphisms (SNPs) were selected for genotype. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated to evaluate the correlation between SNPs and TB risk. The genotype "TA" of CYP2C8 rs2275620 was related to an increased risk of TB in the co-dominant model (OR = 1.33, 95%CI =1.00–1.76, p = 0.049). In females, CYP2E1 rs2070672 was related to an increased TB susceptibility (co-dominant: OR = 1.62, 95%CI = 1.04–2.52, p = 0.032; dominant: OR = 1.66, 95%CI = 1.08–2.56, p = 0.020; additive: OR = 1.60, 95%CI = 1.08–2.36, p = 0.018), and CYP2E1 rs2515641 was also associated with an increased risk of TB (co-dominant: OR = 1.90, 95%CI = 1.19–3.04, p = 0.007; dominant: OR = 1.94, 95%CI = 1.23–3.05, p = 0.004; additive: OR = 1.80, 95%CI = 1.20–2.71, p = 0.005) in women. But there was no statistical significance between haplotypes and TB risk (p > 0.05). Our research showed CYP2C8 and CYP2E1 polymorphisms are associated with an increased risk of TB in Northwest Chinese Han population, which may provide a crucial help on defining new therapeutic strategies for chemoprevention. • A case-control study explored the relationship between CYP2C8 and CYP2E1 polymorphisms with TB risk in Northwest Chinese Han population. • Genotype "TA" of CYP2C8 rs2275620 is related to an increased risk of TB. • In females, CYP2E1 rs2070672 and rs2515641 are associated with an increased risk of TB. [ABSTRACT FROM AUTHOR]

The incidence of thyroid nodules is increasing year by year. Accurate determination of benign and malignant nodules is an important basis for formulating treatment plans. Ultrasonography is the most widely used methodology in the diagnosis of benign and malignant nodules, but diagnosis by doctors is highly subjective, and the rates of missed diagnosis and misdiagnosis are high. To improve the accuracy of clinical diagnosis, this paper proposes a new diagnostic model based on deep learning. The diagnostic model adopts the diagnostic strategy of localization-classification. First, the distribution laws of the nodule size and nodule aspect ratio are obtained through data statistics, a multiscale localization network structure is a priori designed, and the nodule aspect ratio is obtained from the positioning results. Then, uncropped ultrasound images and nodule area image are correspondingly input into a two-way classification network, and an improved attention mechanism is used to enhance the feature extraction performance. Finally, the deep features, the shallow features, and the nodule aspect ratio are fused, and a fully connected layer is used to complete the classification of benign and malignant nodules. The experimental dataset consists of 4021 ultrasound images, where each image has been labeled under the guidance of doctors, and the ratio of the training set, validation set, and test set sizes is close to 3:1:1. The experimental results show that the accuracy of the multiscale localization network reaches 93.74%, and that the accuracy, specificity, and sensitivity of the classification network reach 86.34%, 81.29%, and 90.48%, respectively. Compared with the champion model of the TNSCUI 2020 classification competition, the accuracy rate is 1.52 points higher. Therefore, the network model proposed in this paper can effectively diagnose benign and malignant thyroid nodules. [ABSTRACT FROM AUTHOR]

Abstract: Desulfurization of JP-5 jet fuel (1172ppmw S) was investigated by π-complexation adsorption with AgNO3 supported on mesoporous silica SBA-15 and MCM-41. The average pore sizes of AgNO3/SBA-15 and AgNO3/MCM-41 were 48.8 and 19.1Å, respectively. The results of JP-5 desulfurization showed that significant sulfur breakthrough occurred at ∼10.0 and ∼15.0mL/g by AgNO3/SBA-15 and AgNO3/MCM-41, respectively, at a space velocity of 1.25h−1. The spent AgNO3/MCM-41 was regenerated by a simple process (heating in air at 200°C) and ∼50% of the sulfur capacity was recovered after the first cycle. Molecular orbital calculations show that Cu+ (as that in CuY zeolite) formed stronger π-complexation bonding with the thiophenic compounds than Ag+ (in AgNO3), as evidenced by experimental heats of adsorption. However, pore diffusion limitation of the large sulfur molecules (alkylated benzothiophenes) became an important factor for desulfurization of high sulfur jet fuels such that the AgNO3-supported mesoporous sorbents yielded substantially better results than Cu(I)Y, although Cu(I)Y was better for a model fuel that contained only small sulfur molecules. Among all sorbents that have been investigated, the AgNO3/MCM-41 sorbent showed the best desulfurization performance for high sulfur jet fuels. [Copyright &y& Elsevier]

Abstract: The catalytic activities of Fe/Beta (i.e., by incipient wetness impregnation) zeolite catalysts with various Fe loadings were investigated for the selective catalytic reduction (SCR) of nitric oxide by ammonia. Their stabilities and deactivation behavior were studied via hydrothermal aging and hydrocarbon coking. The results showed that NO conversion over 2.5 wt% Fe/Beta catalyst could reach 97.0% in the temperature range of 300–500°C at a high space velocity (1.9×105 h−1). The Fe/Beta catalyst showed stability up to a hydrothermal aging temperature of 750°C. XRD results showed that the structure of Fe/Beta was altered by hydrothermal aging over 750°C, with significant de-alumination as well as a decrease of lattice constants at 900°C. The catalysts after deactivation by the presence of propylene could be fully regenerated by burning off the coke in the reactants over 450°C or in air at 550°C. It was found that the deposition of carbon species on Fe/Beta decreased its activity for forming NO2 as evidenced by FTIR. XPS results showed that the introduction of C3H6 in the reactants resulted in partial reduction of Fe2+ thereby decreased the activity of Fe/Beta for NO SCR. [Copyright &y& Elsevier]

Abstract: A new bridge-building technique was used for facilitating H spillover on metal doped adsorbents for hydrogen storage at room temperature. By preadsorbing of CH4 on Pt/AX-21 (superactivated carbon), the adsorbed amount of hydrogen increased by ∼100% at 1 atm and 25 °C, attributed to the adsorbed CH4 serving as bridges for spillover. We conclude that the Benson–Boudart method can provide a good assessment for the dispersion of metals supported on Al2O3 (and zeolites). For carbon and SiO2 supports, even with pure H2, spillover leads to overestimates of dispersion, and any small amounts of gaseous impurities could lead to much greater overestimates. [Copyright &y& Elsevier]

Desulfurization of a JP-5 light fraction (841ppmw S) for fuel cell applications was achieved by -complexation adsorption with CuCl and supported on the MCM-41 and SBA-15 mesoporous materials. CuCl/MCM-41, , CuCl/SBA-15 and sorbents were prepared with spontaneous monolayer dispersion of metal halides onto surfaces of supports. These sorbents were characterized with XRD, physical adsorption and CO chemisorption. The results showed that the mesoporous structures remained in the supported sorbents. Desulfurization of JP-5 light fraction with these sorbents was investigated at room temperature. showed by far the highest capacity of selective sulfur adsorption among all known sorbents, and the significant breakthrough occurred at about 50.0ml/g for desulfurization of JP-5 light fraction. The total sulfur content of JP-5 light fraction can be reduced from 841ppmw S to below 50.0ppmw S. The spent was regenerated by purge with benzene at 70°C, and the regenerated was tested again for the desulfurization. The results showed that about 44% and 48% of the sulfur capacity were recovered at breakthrough and saturation, respectively. [Copyright &y& Elsevier]

Microtubule-based kinesin motor proteins are crucial for intracellular transport, but their hyperactivation can be detrimental for cellular functions. This study investigated the impact of a constitutively active ciliary kinesin mutant, OSM-3CA, on sensory cilia in C. elegans. Surprisingly, we found that OSM-3CA was absent from cilia but underwent disposal through membrane abscission at the tips of aberrant neurites. Neighboring glial cells engulf and eliminate the released OSM-3CA, a process that depends on the engulfment receptor CED-1. Through genetic suppressor screens, we identified intragenic mutations in the OSM-3CA motor domain and mutations inhibiting the ciliary kinase DYF-5, both of which restored normal cilia in OSM-3CA-expressing animals. We showed that conformational changes in OSM-3CA prevent its entry into cilia, and OSM-3CA disposal requires its hyperactivity. Finally, we provide evidence that neurons also dispose of hyperactive kinesin-1 resulting from a clinic variant associated with amyotrophic lateral sclerosis, suggesting a widespread mechanism for regulating hyperactive kinesins. Synopsis: Hyperactivation of kinesins has been linked to neurodegenerative conditions. This study shows that a hyperactive version of OSM-3, a member of kinesin-2 superfamily that drives anterograde intraflagellar transport in C. elegans, is expelled from neurons for degradation in glial cells. Hyperactive OSM-3CA kinesin is absent from cilia and forms dynamic puncta within the neurites of sensory neurons. OSM-3CA puncta are ejected from sensory neurons and engulfed by neighboring cephalic sheath glia cells in a manner dependent of the phagocytic receptor CED-1. Mutations that reduce OSM-3CA activity or increase its microtubule binding protect OSM-3CA and restore normal cilia. ALS-linked hyperactive kinesin-1 is also expelled from neurons when ectopically expressed in C. elegans. Phagocytic receptor CED-1 enables glial uptake and subsequent degradation of hyperactive kinesins in C. elegans. [ABSTRACT FROM AUTHOR]

Water content plays a crucial role in the retrogradation of rice starch. The relationship between the water content of rice starch gels and their structural changes during retrogradation is studied. The results indicate that the gels have three distinct types of water: structural constitution water, starch intermolecular bound water, and free water. The rate of retrogradation increases as the water content increases. Nevertheless, when the water content is lower (1:1) or higher (1:6) than optimal, the starch molecules show limited aggregation and recrystallization, which retards the rate of retrogradation. With the aggregation and recrystallization of starch and the inward contraction of the gel structure, the mobility of water is restricted, and the binding of water to the starch is enhanced. With the sustained contraction of the gel structure, the water‐holding capacity of the gel is weakened. By analyzing the experimental results, water distribution, transformation, and migration in rice starch during retrogradation are delineated. These findings provide a theoretical basis for controlling the retrogradation of rice starch and improving product quality. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) is the most important food crop in the world, with significant acreage and production across the globe. However, it is affected by low temperatures throughout its growth process, especially during germination. Therefore, it is important to identify more QTLs or genes associated with germination under low-temperature conditions. For the QTL analysis of traits related to low-temperature germination, we used a high-res genetic map of 213 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, which had 6618 bin markers. We detected 28 QTLs of eight phenotypic characteristics associated with low-temperature germination, while they explained the phenotypic contribution rate of 5.4 ~ 13.34%. Additionally, 14 overlapping QTLs produced six QTL clusters on every chromosome, except for 8 and 10. RNA-Seq found six genes related to low-temperature tolerance in these QTLs, while qRT-PCR analysis demonstrated that the expression trends of the Zm00001d045568 gene in the LT_BvsLT_M group and the CK_BvsCK_M group were highly significantly different at all four-time points (P < 0.01), and encoded the RING zinc finger protein. It was located on qRTL9-2 and qRSVI9-1 and is related to the total length and simple vitality index. These results provided potential candidate genes for further gene cloning and improving the low-temperature tolerance of maize. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, has led to the rapid development of Coronavirus disease 2019 (COVID-19) pandemic. COVID-19 represents a fatal disease with a great global public health importance. This study aims to develop a three-parameter Weibull mathematical model using continuous functions to represent discrete COVID-19 data. Subsequently, the model was applied to quantitatively analyze the characteristics for the mortality of COVID-19, including the age, sex, the length of symptom time to hospitalization time (SH), hospitalization date to death time (HD) and symptom time to death time time (SD) and others. A three-parameter mathematical model was developed by combining the reported cases in the Data Repository from the Center for Systems Science and Engineering at Johns Hopkins University and applied to estimate and analyze the characteristics for mortality of COVID-19. We found that the scale parameters of males and females were 5.85 and 5.45, respectively. Probability density functions in both males and females were negative skewness. 5% of male patients died under the age of 43.28 (44.37 for females), 50% died under 69.55 (73.25 for females), and 95% died under 86.59 (92.78 for females). The peak age of male death was 67.45 years, while that of female death was 71.10 years. The peak and median values of SH, HD and SD in male death were correspondingly 1.17, 5.18 and 10.30 days, and 4.29, 11.36 and 16.33 days, while those in female death were 1.19, 5.80 and 12.08 days, and 4.60, 12.44 and 17.67 days, respectively. The peak age of probability density in male and female deaths was 69.55 and 73.25 years, while the high point age of their mortality risk was 77.51 and 81.73 years, respectively. The mathematical model can fit and simulate the impact of various factors on IFR. From the simulation results of the model, we can intuitively find the IFR, peak age, average age and other information of each age. In terms of time factors, the mortality rate of the most susceptible population is not the highest, and the distribution of male patients is different from the distribution of females. This means that Self-protection and self-recovery in females against SARS-CoV-2 virus might be better than those of males. Males were more likely to be infected, more likely to be admitted to the ICU and more likely to die of COVID-19. Moreover, the infection fatality ration (IFR) of COVID-19 population was intrinsically linked to the infection age. Public health measures to protect vulnerable sex and age groups might be a simple and effective way to reduce IFR. [ABSTRACT FROM AUTHOR]

The buds of I Z. striolatum i were collected in August of 2019 from Guizhou Province of P. R. China and were authenticated by Dr. Daopeng Tan (Pharmacognosy), an associate professor of Zunyi Medical University. In the present study, our further chemical investigation into the constituents of the buds of I Z. striolatum, i nine compounds were isolated and identified previously from this plant. The EtOAc extract (60 g) was subjected to a series of chromatographic methods, such as column chromatography using silica gel (200-300 or 300-400 mesh) and Sephadex LH-20, and yielded compounds B 1-9 b . The buds of I Z. striolatum i contain abundant protein, polysaccharides, amino acids, and trace elements, and serve as a delicious vegetable with high nutritional value [[3]]. [Extracted from the article]

Total factor productivity (TFP) is a sustainable driver of economic growth, and TFP-driven growth is of great importance for a knowledge- and technology-intensive industry. However, there is a massive gap between theoretical research and practical observations on the role that TFP has played in driving construction growth since the global financial crisis. The understanding of this TFP role may shake and even change the traditional notion that the Chinese construction industry is a typical labor-intensive industry. To fulfill this gap, this paper presents an analysis on the driving effects of growth drivers in the industry. From the perspective of neoclassical growth theory, the Solow residual approach is applied to perform this analysis, where the growth drivers are decomposed into TFP, labor and capital. The data are collected from the China Statistical Yearbook on Construction and China Statistical Yearbook for the period of 2008–2016. Interestingly, the results indicate that during the surveyed period, the average driving effects of TFP, labor and capital were 45.08%, 39.95% and 14.97%, respectively. TFP was the first and foremost growth driver, but its driving effect has been facing a rigorous challenge from labor-driven effect. From an evolutionary perspective, the growth mostly driven by TFP occurred over 4 years (2008/09, 2011/12, 2012/13 and 2013/14), which accounted for 50% of the whole study period; the growth mainly driven by labor occurred in only 3 years (2009/10, 2014/15 and 2015/16). Given this situation, the Chinese construction industry can no longer be considered a labor-intensive industry; instead, it is believed to be moving from a labor-intensive industry to a knowledge- and technology-intensive industry. • TFP-driven growth is of great importance for a knowledge- and technology-intensive industry. • The Chinese construction industry has long been regarded as a typical labor-intensive industry. • The average driving effect of TFP during the period 2008-2016 was much larger than that of labor. • The Chinese construction industry is thus considered to be moving towards a knowledge- and technology-intensive industry. [ABSTRACT FROM AUTHOR]

Background: Kidney cancer is the predominant form of malignancy of the kidney and accounts for approximately 3%–4% of all cancers. Renal cell cancer (RCC) represents more than 85% of kidney cancer. It has been reported that genetic factors may predispose individuals to RCC. This study evaluated the association between Acylphosphatase 2 (ACYP2) gene polymorphisms and RCC risk in the Han Chinese population. Methods: Twelve single‐nucleotide polymorphisms (SNPs) in ACYP2 were genotyped using the Agena MassARRAY platform from 293 RCC patients and 495 controls. The Chi‐squared test, genetic models, haplotype, and stratification analyses were used to evaluate the association between SNPs and the risk of RCC. The relative risk was estimated using the odds ratio (OR) and 95% confidence interval (CI). Results: We observed that the rs6713088 allele G (OR = 1.26, 95% CI: 1.03–1.53, p = .023) and rs843711 allele T (OR = 1.29, 95% CI: 1.06–1.57, p = .010) were associated with increased RCC risk. Genetic model analyses found that rs843711 was significantly associated with an increased RCC risk under the recessive model and log‐additive model after adjusting for age and gender. Haplotype analysis showed that the haplotype "TTCTCGCC" (OR = 0.67, 95% CI: 0.48–0.94, p = .021) was associated with a decreased risk of RCC in the Han Chinese population. Stratification analysis also found that rs6713088 and rs843711 were significantly associated with increased RCC risk. Conclusion: In summary, the results suggested that ACYP2 polymorphisms could be used as a genetic marker for RCC. Additional functional and association studies are required to validate our results. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) is a significant worldwide health problem, and is caused by Mycobacteria tuberculosis. Recent studies have suggested that FOXO3 plays vital roles in the risk of immune–related infectious diseases such as TB. Methods and Results: The present study aimed to evaluate FOXO3 genetic variants and TB risk. We recruited 510 TB patients and 508 healthy controls in this study. All subjects were genotyped with the Agena MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression adjusted for age and gender. Our result revealed that rs3800229 T/G and rs4946935 G/A genotypes significantly increased the risk of TB (OR = 1.34, 95% CI = 1.04–1.74, p = 0.026; OR = 1.34, 95% CI = 1.03–1.73, p = 0.029, respectively). In stratified analysis according to gender and age, we observed that rs3800229 T/G and rs4946935 G/A genotypes were associated with an increase the risk of TB among males and age ≤41 years, respectively (OR = 1.47, 95% CI = 1.06–2.04, p = 0.022 and OR = 1.45, 95% CI = 1.05–2.02, p = 0.025). Conclusions: Our study showed that rs3800229 and rs4946935 in FOXO3 were associated with a risk of TB in the Chinese population. [ABSTRACT FROM AUTHOR]

Ventricular septal defect (VSD) is the most common congenital heart malformation in children. This study aimed to investigate potential pathogenic genes associated with Tibetan familial VSD. Whole genomic DNA was extracted from eight Tibetan children with VSD and their healthy parents (a total of 16 individuals). Whole-exome sequencing was performed using the Illumina HiSeq platform. After filtration, detection, and annotation, single nucleotide variations and insertion-deletion markers were examined. Comparative evaluations using the Sorting Intolerant from Tolerant, PolyPhen V2, Mutation Taster, and Combined Annotation Dependent Depletion databases were conducted to predict harmful mutant genes associated with the etiology of Tibetan familial VSD. A total of six missense mutations in genetic disease-causing genes associated with the development of Tibetan familial VSD were identified: activin A receptor type II-like 1 (c.652 C > T: p.R218 W), ATPase cation transporting 13A2 (c.1363 C > T: p.R455 W), endoplasmic reticulum aminopeptidase 1 (c.481 G > A: p.G161 R), MRI1 (c.629 G > A: p.R210Q), tumor necrosis factor receptor-associated protein 1 (c.224 G > A: p.R75H), and FBN2 (c.2260 G > A: p.G754S). The Human Gene Mutation Database confirmed activin A receptor type II-like 1, MRI1 , and tumor necrosis factor receptor-associated protein 1 as pathogenic mutations, while FBN2 was classified as a probable pathogenic mutation. This novel study directly screens genetic variations associated with Tibetan familial VSD using whole-exome sequencing, providing new insights into the pathogenesis of VSD. [ABSTRACT FROM AUTHOR]

Renewable and carbon free energy relates to the sustainable development of human beings while hydrogen production by renewables and hydrogen underground storage ensure the stable and economic renewable energy supply. A hybrid energy system combining hydrogen production by offshore wind power with hydrogen storage in depleted oil reservoirs was constructed along with a mathematical model where the Weibull distribution, Wind turbine power function, Faraday's law, continuity equation, Darcy's law, state equation of real gas, Net Present Value (NPV) and the concept of leveling were adopted to clarify the system characteristics. For the case of a depleted oil field in the Bohai Bay, China, the annual hydrogen production, annual levelized cost of hydrogen and payback period are 2.62 × 106 m³, CNY 34.6/kgH 2 and 7 years, respectively. Sensitivity analysis found that the wind speed impacted significantly on system NPV and LCOH, followed by hydrogen price and stratum pressure. • A novel hybrid energy system for hydrogen production and storage was built. • The hydrogen was produced by offshore wind while stored in the depleted reservoir. • The H 2 production and CO 2 reduction were 2.6 × 106 m³ and 6.9 × 105 kg annually. • The system NPV and payback period were CNY 1.1 × 108 and 7 years. • Wind speed, H 2 price and stratum static pressure impacted the most on system NPV. [ABSTRACT FROM AUTHOR]

One of the most common urological diseases is benign prostatic hyperplasia (BPH), with a high prevalence in the middle-aged and elderly male population. Patient's mental and physical health is affected significantly by this condition, causing them considerable discomfort. During the development of BPH, a synergistic effect occurs in response to inflammation, oxidative stress, and apoptosis induced by the activation of macrophages. The nuclear factor erythroid2-related factor 2 (Nrf2) signaling pathway can mediate macrophage activation and inhibit prostate hyperplasia by suppressing pro-inflammatory factors, anti-oxidative stress disorder, and initiating apoptosis. The purpose of this study was to review the mechanism of action of Nrf2 signaling pathway-mediated macrophage activation on the immune microenvironment of BPH and to summarize the Chinese medicine based on Nrf2 to provide an overview of BPH treatment options. • This article reviews the Nrf 2 signaling -mediated macrophage activation mechanism on the BPH immune microenvironment. • The Nrf 2 signaling mediates macrophage activation and inhibits BPH by inhibiting pro-inflammatory factors. • The Nrf 2 signaling mediates macrophage activation and inhibits BPH by inhibiting oxidative stress disorders. • The Nrf 2 signaling mediates macrophage activation and inhibits BPH by initiating apoptosis. • The traditional Chinese medicine based on Nrf 2 were summarized to provide ideas for the BPH treatment. [ABSTRACT FROM AUTHOR]

Intramuscular fat content is an important factor that determines meat quality in pigs. In recent years, epigenetic regulation has increasingly studied the physiological model of intramuscular fat. Although long noncoding RNAs (lncRNAs) play essential roles in various biological processes, their role in intramuscular fat deposition in pigs remains largely unknown. In this study, intramuscular preadipocytes in the longissimus dorsi and semitendinosus of Large White pigs were isolated and induced into adipogenic differentiation in vitro. High-throughput RNA-seq was carried out to estimate the expression of lncRNAs at 0, 2 and 8 days post-differentiation. At this stage, 2135 lncRNAs were identified. KEGG analysis showed that the differentially expressed lncRNAs were common in pathways involved with adipogenesis and lipid metabolism. lnc_000368 was found to gradually increase during the adipogenic process. Reverse-transcription quantitative polymerase chain reaction and a western blot revealed that the knockdown of lnc_000368 significantly repressed the expression of adipogenic genes and lipolytic genes. As a result, lipid accumulation in porcine intramuscular adipocytes was impaired by the silencing of lnc_000368. Overall, our study identified a genome-wide lncRNA profile related to porcine intramuscular fat deposition, and the results suggest that lnc_000368 is a potential target gene that might be targeted in pig breeding in the future. [ABSTRACT FROM AUTHOR]

The traditional Transformer model primarily employs a self-attention mechanism to capture global feature relationships, potentially overlooking local relationships within sequences and thus affecting the modeling capability of local features. For Support Vector Machine (SVM), it often requires the joint use of feature selection algorithms or model optimization methods to achieve maximum classification accuracy. Addressing the issues in both models, this paper introduces a novel network framework, CTSF, specifically designed for Industrial Internet intrusion detection. CTSF effectively addresses the limitations of traditional Transformers in extracting local features while compensating for the weaknesses of SVM. The framework comprises a pre-training component and a decision-making component. The pre-training section consists of both CNN and an enhanced Transformer, designed to capture both local and global features from input data while reducing data feature dimensions. The improved Transformer simultaneously decreases certain training parameters within CTSF, making it more suitable for the Industrial Internet environment. The classification section is composed of SVM, which receives initial classification data from the pre-training phase and determines the optimal decision boundary. The proposed framework is evaluated on an imbalanced subset of the X-IIOTID dataset, which represent Industrial Internet data. Experimental results demonstrate that with SVM using both "linear" and "rbf" kernel functions, CTSF achieves an overall accuracy of 0.98875 and effectively discriminates minor classes, showcasing the superiority of this framework. [ABSTRACT FROM AUTHOR]

In this paper, a trench-assisted large-mode-field-area multi-core fiber with an air-hole structure composed of 21 conventional fiber cores and 16 air holes is proposed, and it can realize dual-mode transmission. By adjusting the structural parameters, the effective mode field area of fundamental mode can be up to 1916.042 µm2 at 1550 nm. In addition, the fiber has good bending characteristics by adding a trench with a lower refractive index than the cladding. When the bending radius is 1.4 cm, the bending loss is low to 2.96 × 10–3 dB/m. This fiber is of great significance for the design of bending insensitive fiber. [ABSTRACT FROM AUTHOR]

Ion-complementary self-assembling peptides have potential in delivering hydrophobic drugs. This study involved two self-assembling peptides, RADA16-I and RVDV16-I, of which RVDV16-I was a novel self-assembling peptide with different hydrophobic side chains designed from RADA16-I. The purpose of this study was to observe the interaction between different self-assembling peptides and emodin through fluorescence spectrophotometry, CD, SEM and AFM; to construct a preliminary suspension in-situ hydrogel delivery system for emodin with the self-assembling peptides; and to investigate the drug-loading and drug-releasing properties of the self-assembling peptides on emodin. The results showed that both peptides can interact with emodin and the interaction was dominated by hydrophobic interaction. The aqueous solutions of both self-assembling peptides can form relatively stable suspensions with emodin under mechanical stirring, and the suspension can form in-situ hydrogel under physiological condition. In vitro release of emodin from the hydrogels showed a manner of sustained release to some extent. Cell viability studies showed inherent proliferation inhibiting effects of emodin on tumor cells was maintained or enhanced through the in-situ hydrogels. The self-assembling peptides RADA16-I and RVDV16-I had showed promising drug-loading and drug-releasing performance for hydrophobic drugs. It is reasonable to exploit self-assembling peptides as drug carriers for their great potential to improve delivery of hydrophobic drugs. [ABSTRACT FROM AUTHOR]

The production evaluation of high-temperature and high-pressure gas condensate remains unsatisfactory in terms of precision due to the inadequate knowledge of viscosity variation and dynamic relative permeability. Here, we first conduct phase behavior experiments to clarify the mechanisms of viscosity variation followed by core flooding experiments to reveal the dynamic relative permeability. The viscosity variation responses in different regimes to pressure and temperature increases. Besides, the carbon number of the gas condensate exhibits three influencing scenarios on viscosity variation at different pressure and temperature conditions. Moreover, the variation of relative permeability is limited within 5% as temperature decreases together with pressure decreases, but the decline rate of pressure is expected to be higher than that of temperatures. We then theoretically model the production of the gas condensate reservoir by integrating the viscosity variation and dynamic relative permeability mechanisms obtained from the experiments. Modeling results well fit the field data. We adopt the model to analyze and elucidate the effects of temperature, pressure and fracture size on water flooding recovery of ultra-deep gas condensate reservoirs. We figure out that at high temperature, the gas condensate recovery can be enhanced by a rapid pressure decline which can further accelerate the oil thinning and gas condensate production. A high gas condensate production is obtained in the early stage at high pressure, but the oil with high viscosity consumes vast amounts of reservoir energy, leading to a rapid pressure drop in the early development stage. This work pioneers in revealing the interactive mechanisms of viscosity variation and dynamic permeability of ultra-deep reservoir during water flooding development, and brings insights into more adequate gas condensate recovery evaluation. [ABSTRACT FROM AUTHOR]

It is very important to utilize hydraulic fracturing for unconventional reservoir development. Accurate prediction of effective stimulated reservoir volume (SRV) after fracturing facilitates production evaluation. However, the traditional methods to predict SRV are time consuming and the precision cannot fully meet the requirements. To overcome the shortcomings, a new approach was presented using deep learning which includes four procedures. Firstly, the datasets were collected by numerical simulation considering non-Darcy flow characteristics. Additionally, the Branched Deep Neural Network model (B-DNN) was established after data fusion through adding a branch neural network. Then the optimal hyperparameters were obtained after adjusting to satisfy model accuracy and reliability. Finally, the prediction results of B-DNN and convolutional neural network (CNN) and recurrent neural network (RNN) were compared. The results show that the model with Softplus activation function, four hidden layers, and 250 neurons in each layer would have the best calculation results. The proposed model has good agreement with actual field data which can reach 97%. Furthermore, compared with the CNN and RNN models, it is shown that the B-DNN model has considerable prediction accuracy and is less time-consuming. This deep learning model provides new insight for production evaluation in the fractured tight oil reservoir. [ABSTRACT FROM AUTHOR]

A Multiscale Locally Conservative Galerkin (MsLCG) method is proposed to accurately simulate multiphase flow in heterogeneous and fractured porous media. MsLCG employs a coarse partition of the fine grids and multiscale basis function for mapping the fine-scale information to the coarse-scale unknowns. Different from standard Multiscale Finite Element Method (MsFEM), the main improvement of our MsLCG is to use the property of local conservation at steady state conditions to define a numerical flux at element boundaries. MsLCG provides a way to extend standard MsFEM to handle challenging multiphase flow problems in heterogeneous and fractured porous media. MsLCG preserves all the advantages of the standard MsFEM while it provides explicitly conservative fluxes through each element. We present a number of representative numerical examples to demonstrate that our method is efficient and accurate for simulating multiphase flow through heterogeneous and fractured porous media. [ABSTRACT FROM AUTHOR]

To elucidate the coupling effects of temperature and ratio of steam to carbon on the methane steam reforming process, the characterizations of methane steam reforming at different temperature and ratio of steam to carbon in term of distribution of H 2 and CO, and the elementary reaction rate were investigated. Meanwhile, the formation mechanisms of H 2 and CO via sensitivity analysis and reaction path analysis were obtained. The results showed that the coupling effects of temperature and ratio of steam to carbon on the methane steam reforming were higher than that of individual factor. The effects of temperature on the methane steam reforming were higher than that of the ratio of steam to carbon. The adsorption and desorption reaction of CH 4 on the surface of Ni-based catalyst had the most obvious effect on the sensitivity of H 2 , CH 4 and CO. Besides, the effects of adsorption and desorption reaction of H 2 O on the sensitivity of H 2 were higher than that of CH 4 and CO. Hydrogen was generated by the desorption reaction of H(s) in the adsorbed state and from three generating paths: a) CH 4 (s) dissociated directly or reacted with O(s) to form H(s); b) The dissociation reaction of H 2 O(s) produced H(s); c) OH(s) dissociated directly or reacted with C(s) to form H(s). Carbon monoxide was generated from single path: CH 4 (s)→CH 3 (s)→CH 2 (s)→CH(s)→C(s)→CO(s)→CO(g). • The coupling effects of temperature and the ratio of steam to carbon on methane steam reforming mechanism were investigated. • The hydrogen and carbon monoxide reaction path route was obtained. • The methane conducted a direct decomposition reaction on the surface of catalyst which showed as following: CH 4 (s)→CH 3 (s)→CH 2 (s)→CH(s)→C(s). [ABSTRACT FROM AUTHOR]

Camptothecin (CPT) is an important natural product targeting to Topoisomerase I (Topo I). Despite the high antitumor activity, this compound cannot enter clinical trial owing to its high toxicity and low bio‐availability. In this project, the ring‐closing metathesis (RCM) synthesis strategy was employed to introduce spirocycle functional group in the 5‐position of CPT. Thus, in the catalysis of Grubbs II catalyst, 5,5‐diallylcamptothecin underwent RCM reaction to give 5‐spirocycle CPT compound in 73% yield. [ABSTRACT FROM AUTHOR]

Earthquake forecasting is the process of forecasting the time, location, and magnitude of an earthquake, hoping to gain some time to prepare to reduce the disasters caused by earthquakes. In this paper, the possible relationship between the maximum electron density, the corresponding critical frequency, and the occurrence of earthquakes is explored by means of radio occultation data based on mechanism analysis and actual earthquake-nearby data. A new disturbance frequency index is proposed in this paper as a novel method to help forecast earthquakes. Forecasting of the location and timing of earthquakes is based on the connection between proven new frequency distributions and earthquakes. The effectiveness of this index is verified by backtracking observation around the 2022 Ya'an earthquake. Using this index, occultation data can forecast the occurrence of earthquakes five days ahead of detection, which can help break the bottleneck in earthquake forecasting. [ABSTRACT FROM AUTHOR]

Ethyl 2-methylcyclopent-2-ene-1-carboxylate (3) is an important building block in the synthesis of some natural products. In this paper, 2GGC was used for the RCM reaction to prepare this scaffold instead of reported 1GGC. This scaffold (3) was obtained in a moderate yield and its structure was determined by 1H NMR and 13C NMR. A contra-ring closing metathesis mechanism was also put forward to explain the formation of the product. [ABSTRACT FROM AUTHOR]

Shale gas reservoir is comprised of highly heterogeneous porosity systems including hydraulic/secondary fractures, inorganic and organic matrix. Multiple non-Darcy flow mechanisms in the shale matrix further bring challenges for modeling. In this paper, we developed a framework combining a multi-physics compositional simulator with Multi-Porosity Modeling preprocessor for gas storage and transport in shale. A Triple-Porosity Model is used to characterize the three porosity systems in shale gas reservoirs. In the fracture porosity the heterogeneous impact of secondary fractures distribution on matrix-to-fracture fluid transfer is revealed by shape factor distribution. They are upscaled with superior accuracy from a detailed Discrete Fracture Network Model (DFN) sector model, where orthogonal hydraulic fractures are explicitly discretized. With the occurrence of nano-pores in shale matrix, the interaction between pore-wall and gas molecules is considered via Knudsen diffusion and gas slippage. Gas adsorption on the pore-wall of organic matrix is modeled by extended Langmuir isotherm. The inter-porosity and intra-porosity connectivities in the Triple-Porosity Model are flexibly controlled by arbitrary connections. Our results show that gas production in the Triple-Porosity Model with shape factor upscaled from DFN exhibits different production performance from models with uniform shape factor distribution. The deviations are caused by the dominance of different regions at different production periods. Connection topology in the shale gas reservoir is also comprehensively assessed. We demonstrate that the intra-porosity connections in the inorganic and organic matrix have negligible impact on the global gas flux, while the inter-porosity connections have different levels of importance for the gas production. Moreover, different combinations of flow and storage mechanisms are investigated. We show that Langmuir desorption maintains reservoir pressure, but gas slippage and Knudsen diffusion accelerate the pressure drop. Both mechanisms contribute to improve the gas production and the consideration of them simultaneously improve gas production most. [ABSTRACT FROM AUTHOR]

The natural buckwheat flour exhibits poor processing behaviour due to its conservative structure and the lack of gluten protein, thereby limiting its use in the food industry. The replacement of chemical modification with sustainable, environmentally friendly steam treatment is, currently, technically feasible and promising for most chemical modification methods. The data showed that the steam-treated buckwheat flour degree of gelatinization increased to 99.3 g/100 g, and water absorption increased to 3.93 g/100 g. Also, particle size of the samples in the trial group was significantly larger compared to the control group. Scanning electron microscopy and infrared tests showed that not only did the steam treatment disrupt the granular structure of the buckwheat flour, but its proximity crystalline ordering structure Importantly, rheological behaviour tests showed that the steam-treated buckwheat gel exhibited a better viscoelasticity. Consequently, steam-treated pre-gelatinized buckwheat flour readily forms a tight network structure and provided important information for potential processing applications. [ABSTRACT FROM AUTHOR]

Intervertebral disc degeneration (IDD) is the leading cause of lower back pain, which is one of the primary factors that lead to disability and pose a serious economic burden. The key pathological processes involved are extracellular matrix degradation, autophagy, apoptosis, and inflammation of nucleus pulposus cells. Non-coding RNAs (ncRNAs), including microRNAs, long ncRNAs and circular RNAs, are key regulators of the aforementioned processes. ncRNAs are differentially expressed in tissues of the intervertebral disc between healthy individuals and patients and participate in the pathological progression of IDD via a complex pattern of gene regulation. However, the regulatory mechanisms of ncRNAs in IDD remain unclear. The present review summarizes the latest insights into the regulatory role of ncRNAs in IDD and sheds light on potentially novel therapeutic strategies for IDD that may be implemented in the future. [ABSTRACT FROM AUTHOR]

Steam reforming (SR) of pure butanol and a specific mixture (butanol/acetone/ethanol = 6/3/1, mass ratio) assumed as a model of bio-butanol raw mixture have been researched over mesoporous MgO supported Ni catalysts with various particle size (3.6–8.8 nm). The catalysts were characterized by N 2 adsorption, H 2 -TPR, XRD, XPS and TEM. The volcano-like curves were observed when the H 2 yield and H 2 selectivity were plotted as a function of the nickel particle size in butanol steam reforming (BSR) and acetone–butanol–ethanol steam reforming (ABESR) reactions. Prepared mesoporous Ni 0.12 /MgO catalysts exhibited the highest catalytic performance in two model reaction systems. Surprisingly, the Ni particle size effects in BSR developed difference with counterpart in ABESR. Specifically, the catalytic performance of mesoporous Ni 0.20 /MgO even outperform that of mesoporous Ni 0.08 /MgO catalyst with respect to lower by-products selectivity and higher hydrogen yield in ABESR compared to BSR results. [ABSTRACT FROM AUTHOR]