Chinese herbal medicine (CHM), which includes herbal slices and proprietary products, is widely used in China. Shenqi Dihuang (SQDH) is a traditional Chinese medicine (TCM) formula with ingredients that affect tumor growth. Despite recent advances in prognosis, patients with renal cell carcinoma (RCC) cannot currently receive curative treatment. The present study aimed to explore the potential target genes closely associated with SQDH. The gene expression data for SQDH and RCC were obtained from the TCMSP and TCGA databases. The SQDH-based prognostic prediction model reveals a strong correlation between RCC and SQDH. In addition, the immune cell infiltration analysis indicated that SQDH might be associated with the immune response of RCC patients. Based on this, we successfully built the prognostic prediction model using SQDH-related genes. The results demonstrated that CCND1 and NR3C2 are closely associated with the prognosis of RCC patients. Finally, the pathways enrichment analysis revealed that response to oxidative stress, cyclin binding, programmed cell death, and immune response are the most enriched pathways in CCND1. Furthermore, transcription regulator activity, regulation of cell population proliferation, and cyclin binding are closely associated with the NR3C2.

The new mineral, gysinite-(La), with the ideal formula PbLa(CO3)2(OH)⋅H2O, has been discovered in lujavrite from the Saima alkaline complex, Liaoning Province, China. It commonly occurs as subhedral to anhedral, granular and platy crystals of 5 to 50 μm in size, in interstices or enclosed in microcline, aegirine and nepheline. Associated minerals include nepheline, aegirine, microcline, natrolite, eudialyte, lamprophyllite, bastnäsite-(Ce), parasite-(Ce), ancylite-(La), ancylite-(Ce), bobtraillite, britholite-(Ce), thorite, calcite and galena. The crystallisation of gysinite-(La) may be related to the post-magmatic carbonation event. Gysinite-(La) crystals are generally transparent, colourless, or pale yellow, with a vitreous lustre and white streak. It is brittle with an uneven fracture, and the estimated Mohs hardness is 3½ to 4. The calculated density is 5.007 g/cm3. Optically, gysinite-(La) is biaxial (–), α= 1.832(2), β= 1.849(4), γ = 1.862(5) in white light and 2Vmeas = 81.6°. The empirical formula of gysinite-(La) is (La0.93Pb0.61Nd0.23Pr0.14Sr0.04Gd0.02Sm0.01Eu0.01Ca0.01)Σ2(CO3)2(OH)1.34⋅0.66H2O, which is calculated on the basis of general formula (REExM2+2–x)(CO3)2(OH)x⋅(2–x)H2O. The strongest eight lines of its powder X-ray diffraction pattern [d, Å (I, %) (hkl)] are: 5.596 (21) (011), 4.349 (100) (110), 3.732 (68) (111), 2.984 (61) (121), 2.667 (21) (031), 2.363 (48) (131), 2.090 (29) (221) and 2.028 (21) (212). Gysinite-(La) is orthorhombic, in the space group Pmcn, and unit-cell parameters refined from single-crystal X-ray diffraction data are: a = 5.0655(2) Å, b = 8.5990(3) Å, c = 7.3901(4) Å, V = 321.90(2) Å3 and Z = 2. It is a new member of the ancylite group and isostructural with gysinite-(Nd), but with La and Pb dominant in the metal cation sites in the structure.

Fluorsigaiite, ideally Ca2Sr3(PO4)3F, is a new Sr analogue of fluorphosphohedyphane and a new member of the apatite supergroup. It was discovered in lujavrite from the Saima alkaline complex, Liaoning Province, China. Fluorsigaiite commonly occurs as individual prismatic, columnar and platy crystals of 10 to 50 μm in size, associated with microcline, nepheline, aegirine, natrolite, eudialyte, fluorapatite, a fluorstrophite-like mineral, stronadelphite and calcite. Occasionally, crystals of fluorsigaiite form prismatic aggregates in the interstices of lujavrite. Fluorsigaiite is translucent to transparent, colourless to yellowish white with a vitreous lustre and without fluorescence. The estimated Mohs hardness is 5, and the tenacity is brittle with uneven fractures. The calculated density is 3.842 g/cm3. Optically, fluorsigaiite is uniaxial (–) with ω = 1.64(1) and ɛ = 1.63(1) in white light and without dispersion. The mean chemical composition (in wt.%) of fluorsigaiite is Na2O 0.75, CaO 15.17, SrO 44.44, La2O3 3.64, Ce2O3 2.22, Pr2O3 0.19, Nd2O3 0.13, Sm2O3 0.05, Gd2O3 0.23, P2O5 31.87, F 1.91, H2O 0.46, sum 100.26, giving the empirical formula (Sr2.82Ca1.79Na0.16La0.15Ce0.09Pr0.01Nd0.01Gd0.01)Σ5.04P2.97O12[F0.66(OH)0.34]Σ1, which is calculated on the basis of 13 total anions and F+(OH) = 1. The strongest eight lines of its powder X-ray diffraction pattern [d, Å (I, %) (hkl)] are: 3.563 (15) (002), 3.275 (15) (102), 3.144 (19) (120), 2.876 (100) (121), 2.861 (96) (112), 2.772 (27) (300), 1.991 (17) (222) and 1.895 (23) (213). Fluorsigaiite is hexagonal, in the space group P63/m and unit-cell parameters refined from single-crystal X-ray diffraction data are: a = 9.6101(2) Å, c = 7.1311(1) Å, V = 570.35(3) Å3 and Z = 2. It is isostructural with hedyphane-group minerals, and contains different prevailing (species-defining) Ca and Sr cations at the Ca1 and Ca2 sites, respectively. Fluorsigaiite was probably formed from Sr-rich fluids at late-magmatic or hydrothermal stage of the Saima lujavrite.

Echinococcus shiquicus is currently limited to the Qinghai–Tibet plateau, a large mountainous region in China. Although the zoonotic potential remains unknown, progress is being made on the distribution and intermediate host range. In this study, we report E. shiquicus within Gansu and Qinghai provinces in regions located not only around the central areas but also the southeast edge of the plateau and describe their genetic relationship with previous isolates from the plateau. From 1879 plateau pikas examined, 2.39% (95% CI 1.79–3.18) were infected with E. shiquicus. The highest prevalence of 10.26% (4.06–23.58) was recorded in Makehe town, Qinghai province. Overall the prevalence was marginally higher in Qinghai (2.5%, CI 1.82–3.43) than in Gansu (2%, CI 1.02–3.89). The cox1 and nad1 genes demonstrated high and low haplotype and nucleotide diversities, respectively. The median-joining network constructed by the cox1–nad1 gene sequences demonstrated a star-like configuration with a median vector (unsampled haplotype) occupying the centre of the network. No peculiar distinction or common haplotype was observed in isolates originating from the different provinces. The presence of E. shiquicus in regions of the southeast and northeast edges of the Qinghai–Tibet plateau and high genetic variation warrants more investigation into the haplotype distribution and genetic polymorphism by exploring more informative DNA regions of the mitochondrial genome to provide epidemiologically useful insight into the population structure of E. shiquicus across the plateau and its axis.

Cysticercosis caused by the metacestode larval stage of Taenia hydatigena formerly referred to as Cysticercus tenuicollis is a disease of veterinary importance that constitutes a significant threat to livestock production worldwide, especially in endemic regions due to condemnation of visceral organs and mortality rate of infected young animals. While the genetic diversity among parasites is found to be potentially useful in many areas of research including molecular diagnostics, epidemiology and control, that of T. hydatigena across the globe remains poorly understood. In this study, analysis of the mitochondrial DNA (mtDNA) of adult worms and larval stages of T. hydatigena isolated from dogs, sheep and a wild boar in China showed that the population structure consists of two major haplogroups with very high nucleotide substitutions involving synonymous and non-synonymous changes. Compared with other cestodes such as Echinococcus spp., the genetic variation observed between the haplogroups is sufficient for the assignment of major haplotype or genotype division as both groups showed a total of 166 point-mutation differences between the 12 mitochondrial protein-coding gene sequences. Preliminary analysis of a nuclear protein-coding gene (pepck) did not reveal any peculiar changes between both groups which suggests that these variants may only differ in their mitochondrial makeup.

Online retailers are increasingly adding buy-online and pick-up-in-store (BOPS) modes to order fulfilment. In this paper, we study a system of BOPS by developing a stochastic Nash equilibrium model with incentive compatibility constraints, where the online retailer seeks optimal online sale prices and an optimal delivery schedule in an order cycle, and the offline retailer pursues a maximal rate of sharing the profit owing to the consignment from the online retailer. By an expectation method and optimality conditions, the equilibrium model is first transformed into a system of constrained nonlinear equations. Then, by a case study and sensitivity analysis, the model is validated and the following practical insights are revealed. (I) Our method can reliably provide an equilibrium strategy for the online and offline retailers under BOPS mode, including the optimal online selling price, the optimal delivery schedule, the optimal inventory and the optimal allocation of profits. (II) Different model parameters, such as operational cost, price sensitivity coefficient, cross-sale factor, opportunity loss ratio and loss ratio of unsold goods, generate distinct impacts on the equilibrium solution and the profits of the BOPS system. (III) Optimization of the delivery schedule can generate greater consumer surplus, and makes the offline retailer share less sale profit from the online retailer, even if the total profit of the BOPS system becomes higher. (IV) Inventory subsidy is an indispensable factor to improve the applicability of the game model in BOPS mode.

We propose a new adaptive and composite Barzilai–Borwein (BB) step size by integrating the advantages of such existing step sizes. Particularly, the proposed step size is an optimal weighted mean of two classical BB step sizes and the weights are updated at each iteration in accordance with the quality of the classical BB step sizes. Combined with the steepest descent direction, the adaptive and composite BB step size is incorporated into the development of an algorithm such that it is efficient to solve large-scale optimization problems. We prove that the developed algorithm is globally convergent and it R-linearly converges when applied to solve strictly convex quadratic minimization problems. Compared with the state-of-the-art algorithms available in the literature, the proposed step size is more efficient in solving ill-posed or large-scale benchmark test problems.

Numerous efforts have been devoted to the derivation of equations describing the kinematics of finite-size spherical particles in arbitrary fluid flows. These approaches rely on asymptotic arguments to obtain a description of the particle motion in terms of a slow manifold. Here we present a novel approach that results in kinematic models with unprecedented accuracy compared with traditional methods. We apply a recently developed machine learning framework that relies on (i) an imperfect model, obtained through analytical arguments, and (ii) a long short-term memory recurrent neural network. The latter learns the mismatch between the analytical model and the exact velocity of the finite-size particle as a function of the fluid velocity that the particle has encountered along its trajectory. We show that training the model for one flow is sufficient to generate accurate predictions for any other arbitrary flow field. In particular, using as an exact model for trajectories of spherical particles, the Maxey–Riley equation, we first train the proposed machine learning framework using trajectories from a cellular flow. We are then able to accurately reproduce the trajectories of particles having the same inertial parameters for completely different fluid flows: the von Kármán vortex street as well as a two-dimensional turbulent fluid flow. For the second example we also demonstrate that the machine learned kinematic model successfully captures the spectrum of the particle velocity, as well as the extreme event statistics. The proposed scheme paves the way for machine learning kinematic models for bubbles and aerosols using high-fidelity DNS simulations and experiments.

The following paper investigates the prevalence and characteristics of asymptomatic norovirus infection in the population living around oyster farm sites. Two consecutive surveys were conducted from January 2014 to December 2014 and 4549 stool samples were screened during the same time period. The total asymptomatic infection rate was 4.04% (184/4549). Norovirus infection rate was 5.20% in oyster farming population which was significantly higher compared with non-farming population where the infection rate was 3.65% (χ2 = 5.49, P < 0.05). A total of 184 NoV positive samples were identified by real time-quantitative polymerase chain reaction (RT-qPCR) and semi-nested RT-PCR and 136 sequences were obtained. The sequences were clustered into 14 genotypes. GI strains were clustered into six genotypes, including GI.2, GI.3, GI.5, GI.6, GI.8 and GI.9; while GII strains were clustered into GII.2, GII.3, GII.4, GII.5, GII.6, GII.8 and GII.13. GI.9 and GII.17 were the predominant and most prevalent genotypes, respectively. The GII.17 genotype replaced GII.4 becoming the dominant genotype in the oyster farming area in 2014. To sum up, long-term monitoring of asymptomatic infection is crucial for the detection of new variant strains and for identifying outbreaks during the early stage.

We present an extension of vendor-managed inventory (VMI) problems by considering advertising and pricing policies. Unlike the results available in the literature, the demand is supposed to depend on the retail price and advertising investment policies of the manufacturer and retailers, and is a random variable. Thus, the constructed optimization model for VMI supply chain management is a stochastic bi-level programming problem, where the manufacturer is the upper level decision-maker and the retailers are the lower-level ones. By the expectation method, we first convert the stochastic model into a deterministic mathematical program with complementarity constraints (MPCC). Then, using the partially smoothing technique, the MPCC is transformed into a series of standard smooth optimization subproblems. An algorithm based on gradient information is developed to solve the original model. A sensitivity analysis has been employed to reveal the managerial implications of the constructed model and algorithm: (1) the market parameters of the model generate significant effects on the decision-making of the manufacturer and the retailers, (2) in the VMI mode, much attention should be paid to the holding and shortage costs in the decision-making.

As a new business form, the buy-online and pick-up-in-store (BOPS) mode allows consumers to pay for goods online and pick them up in a physical store. In this paper, an equilibrium model is constructed to formulate an optimal decision-making problem for online and offline retailers under the BOPS mode, where the online retailer determines the retail price of the goods and the consignment quantity in a physical store, while the offline retailer chooses the revenue share of profit by a consignment contract. Different to the existing models, the cost of overstocking and loss of understocking are incorporated into the profit function of the online retailer due to the randomness of demand. For the objective function of the offline retailer, the cross-sale quantity generated by the BOPS mode is taken into account. Then the game between the online and offline retailers is expressed as a stochastic Nash equilibrium model. Based on the analytic properties of the model, necessary conditions for the equilibrium solution are obtained. A case study and sensitivity analysis are employed to reveal the managerial implications of the model, which can provide a number of valuable suggestions on optimizing the strategies for the online and offline retailers under the BOPS mode.

We propose a locally smoothing method for some mathematical programs with complementarity constraints, which only incurs a local perturbation on these constraints. For the approximate problem obtained from the smoothing method, we show that the Mangasarian–Fromovitz constraints qualification holds under certain conditions. We also analyse the convergence behaviour of the smoothing method, and present some sufficient conditions such that an accumulation point of a sequence of stationary points for the approximate problems is a C-stationary point, an M-stationary point or a strongly stationary point. Numerical experiments are employed to test the performance of the algorithm developed. The results obtained demonstrate that our algorithm is much more promising than the similar ones in the literature.

The high repetition rate 10 J/10 ns Yb:YAG laser system and its key techniques are reported. The amplifiers in this system have a multi-pass V-shape structure and the heat in the amplifiers is removed by means of laminar water flow. In the main amplifier, the laser is four-pass, and an approximately 8.5 J/1 Hz/10 ns output is achieved in the primary test. The far-field of the output beam is approximately 10 times the diffraction limit. Because of the higher levels of amplified spontaneous emission (ASE) in the main amplifier, the output energy is lower than expected. At the end we discuss some measures that can improve the properties of the laser system.

We propose a modified projected Polak–Ribière–Polyak (PRP) conjugate gradient method, where a modified conjugacy condition and a method which generates sufficient descent directions are incorporated into the construction of a suitable conjugacy parameter. It is shown that the proposed method is a modification of the PRP method and generates sufficient descent directions at each iteration. With an Armijo-type line search, the theory of global convergence is established under two weak assumptions. Numerical experiments are employed to test the efficiency of the algorithm in solving some benchmark test problems available in the literature. The numerical results obtained indicate that the algorithm outperforms an existing similar algorithm in requiring fewer function evaluations and fewer iterations to find optimal solutions with the same tolerance.

Hierarchical and hollow SnS2 nanostructures as precursors were fabricated via a surfactant-assisted assembly process using sodium dodecyl sulfate as soft templates. The as-prepared SnS2 nanostructures were further oxidized to form porous SnO2 conversion for investigating their gas-sensing properties in drug-precursor detection. On the basis of a series of time- and ratio-dependent reactions, a formation mechanism of the special nanostructures and factors influencing morphology and structure were determined. Gas-sensing measurements revealed that the porous and hierarchical SnO2 hollow nanostructures were sensitive to drug precursors, indicating promising applications in environmental monitoring and public safety investigation. In addition, we found that the assembled SnO2 nanomaterials possessed significantly enhanced gas-sensing properties compared with unassembled SnO2 with a solid interior.

To determine the lipid content and fatty acid (FA) composition of breast milk from fifty-two lactating women between ninth and twelfth lactation weeks in rural North China. The mothers were questioned on their dietary habits. Total milk lipids extracts were transmethylated and analysed using GLC to determine FA contents. The mean lipid content was 40·21 (sd 1·43) g/l. SFA constituted 35·92 % of the total FA. Medium-chain and long-chain SFA presented levels of 10·91 and 25·01 %, respectively. MUFA and PUFA constituted 32·59 and 19·97 % of the total FA, respectively. Oleic, linoleic and α-linolenic acid (ALA) presented contents of 31·26, 17·73 and 1·03 %, respectively. Arachidonic acid had a content of 0·30 %, while DHA content was 0·19 %. Not any form of trans FA were found in human milk samples. A maternal diet transition is proceeding in China. Further investigation on the analysis of human milk FA composition is needed to upgrade the human milk database in China.

In this paper, we consider a linear program with only equality constraints but containing interval and random coefficients. We first address the linear program with interval coefficients, and establish some structural properties of this linear program. On this basis, a solution method is proposed. We then move on to consider the linear program with random coefficients. Using the chance constraint approach and a new approach, the satisfaction degree approach, we obtain the two respective deterministic equivalent formulations. Then the results and the numerical solution methods obtained for these two linear models are applied to the original linear problem which contains both interval and random coefficients. By way of illustration, we consider a practical problem, where the optimal mixing proportions need to be determined for the mix slurry in the production process of aluminium with sintering. This gives rise to a linear program with interval and random coefficients. Its deterministic equivalent formulations are presented. Preliminary numerical examples show that the proposed models and the solution methods are promising.

The dynamic interaction of a shockwave (modelled as a pressure pulse) with an initially spherically oscillating bubble is investigated. Upon the shockwave impact, the bubble deforms non-spherically and the flow field surrounding the bubble is determined with potential flow theory using the boundary-element method (BEM). The primary advantage of this method is its computational efficiency. The simulation process is repeated until the two opposite sides of the bubble surface collide with each other (i.e. the formation of a jet along the shockwave propagation direction). The collapse time of the bubble, its shape and the velocity of the jet are calculated. Moreover, the impact pressure is estimated based on water-hammer pressure theory. The Kelvin impulse, kinetic energy and bubble displacement (all at the moment of jet impact) are also determined. Overall, the simulated results compare favourably with experimental observations of lithotripter shockwave interaction with single bubbles (using laser-induced bubbles at various oscillation stages). The simulations confirm the experimental observation that the most intense collapse, with the highest jet velocity and impact pressure, occurs for bubbles with intermediate size during the contraction phase when the collapse time of the bubble is approximately equal to the compressive pulse duration of the shock wave. Under this condition, the maximum amount of energy of the incident shockwave is transferred to the collapsing bubble. Further, the effect of the bubble contents (ideal gas with different initial pressures) and the initial conditions of the bubble (initially oscillating vs. non-oscillating) on the dynamics of the shockwave-bubble interaction are discussed.

Bovine mastitis caused by Streptococcus agalactiae is mainly subclinical and therefore can be diagnosed only in the laboratory. A nested polymerase chain reaction (PCR)-based method for specific, sensitive and rapid detection of S. agalactiae in raw milk was developed. The general streptococci primers, which anneal to conserved areas within the 16S rRNA subunit gene, were used as positive controls. The specificity of S. agalactiae primers is based on various areas within conserved areas of the 16S rRNA genes of S. agalactiae. Results have indicated that the method enables the detection of 1 CFU/ml of S. agalactiae in raw milk after enrichment, followed by DNA extraction using a rapid and simple procedure developed for this purpose, and specific PCR reaction. The method developed can be used efficiently in the early infectious status investigation of S. agalactiae in the dairy herd and in prevention and control of S. agalactiae spread in a herd.

Three-dimensional temperature (T)–pressure (P)–composition (X) phase diagrams of binary carbon-hydrogen (C–H) and carbon-oxygen (C–O) systems for activated low pressure diamond growth have been calculated. Based on an approximation of linear combination between C–H and C–O systems, a projective ternary carbonhydrogen-oxygen (C–H–O) phase diagram has also been obtained. There is always a diamond growth region in each of these phase diagrams. Once a supply of external activating energy stops, the diamond growth region will not exist. Nearly all of the reliable experimental data reported in the literature drop into the possible diamond growth region of the calculated projective ternary C–H–O phase diagram under the conditions of 0.01–100 kPa and above 700 K.