Robust Optimization Design of Bolt-Shotcrete Support Structure in Tunnel

The uncertainty of rock and soil parameters is one of the key problems to limit the stability of tunnel support structure. Based on this, a robust optimization design method is proposed to reduce the sensitivity of support system to the uncertainty of rock and soil parameters. By defining the design parameters, noise factors and system response, a robust design system for bolt-shotcrete support structure is established. The non-dominant solutions of system robustness and support cost consist of the Pareto Front, then an knee point recognition method is designed to further filter all non-dominant solutions and determine the only optimal solution. The robust optimization design of the bolt-shotcrete support structure is carried out with a tunnel as the engineering background. The results show that the method can not only improve the stability and adaptability of the supporting structure, but also reduce the economic cost to the greatest extent, which provides a reference for the optimization design of other geotechnical engineering supporting structures

4-Amino-3,5-dichloro­benzene­sulfonamide

In the title compound, C6H6Cl2N2O2S, the O atoms of the sulfonamide group lie on one side of the benzene ring and the amino group lies on the opposite side. An inter­molecular N—H⋯Cl inter­action occurs. In the crystal, adjacent mol­ecules are linked by N—H⋯O hydrogen bonds, forming a three-dimensional structure with supporting π–π stacking inter­actions [centroid–centroid distance = 3.7903 (12) Å]. A short Cl⋯Cl contact [3.3177 (10) Å] also occurs

Sesquiterpenes from the marine red alga Laurencia composita.

Four new chamigrane derivatives, laurecomin A (1). laurecomin B (2), laurecomin C (3), and laurecomin D (4), one new naturally occurring sesquiterpene, 2,10-dibromo-3-chloro-7-chamigren-9-ol acetate (5), and three known halogenated structures, deoxyprepacifenol (6), 1-bromoselin-4(14),11-diene (7), and 9-bromoselin-4(14).11-diene (8), were isolated from the marine red alga Laurencia cornposita collected from Pingtan Island, China. The structures of these compounds were unambiguously established by 1D, 2D NMR and mass spectroscopic techniques. The bioassay results showed that 2 was active against both brine shrimp and fungus Colletotrichum lagenarium. (C) 2012 Elsevier B.V. All rights reserved.Four new chamigrane derivatives, laurecomin A (1). laurecomin B (2), laurecomin C (3), and laurecomin D (4), one new naturally occurring sesquiterpene, 2,10-dibromo-3-chloro-7-chamigren-9-ol acetate (5), and three known halogenated structures, deoxyprepacifenol (6), 1-bromoselin-4(14),11-diene (7), and 9-bromoselin-4(14).11-diene (8), were isolated from the marine red alga Laurencia cornposita collected from Pingtan Island, China. The structures of these compounds were unambiguously established by 1D, 2D NMR and mass spectroscopic techniques. The bioassay results showed that 2 was active against both brine shrimp and fungus Colletotrichum lagenarium. (C) 2012 Elsevier B.V. All rights reserved

Bis[4-(2-hydroxy­benzyl­ideneamino)benzoato-κO]tetrakis­(methanol-κO)manganese(II)

In the title mononuclear complex, [Mn(C14H10NO3)2(CH3OH)4], the MnII atom, lying on an inversion centre, exhibits a distorted octa­hedral geometry, defined by two O atoms from two monodentate ligands and four O atoms from four methanol mol­ecules. The crystal structure involves intra­molecular O—H⋯N and O—H⋯O and inter­molecular O—H⋯O hydrogen bonds

[μ-N,N,N′,N′-Tetra­kis(diphenyl­phosphino­meth­yl)benzene-1,4-diamine-κ4 P,P′:P′′,P′′′]bis­[bis­(nitrato-κO)palladium(II)]

The asymmetric unit of the title complex, [Pd2(NO3)4(C58H52N2P4)], contains one half-mol­ecule, in which the central benzene ring is located on a crystallographic centre of inversion. The Pd atom has a distorted square-planar coordination consisting of two P and two O atoms. In the crystal structure, inter­molecular C—H⋯O inter­actions link the mol­ecules into chains, and π–π contacts between the phenyl rings [centroid–centroid distance = 3.928 (3) Å] may further stabilize the structure

Integrated application of uniform design and least-squares support vector machines to transfection optimization

<p>Abstract</p> <p>Background</p> <p>Transfection in mammalian cells based on liposome presents great challenge for biological professionals. To protect themselves from exogenous insults, mammalian cells tend to manifest poor transfection efficiency. In order to gain high efficiency, we have to optimize several conditions of transfection, such as amount of liposome, amount of plasmid, and cell density at transfection. However, this process may be time-consuming and energy-consuming. Fortunately, several mathematical methods, developed in the past decades, may facilitate the resolution of this issue. This study investigates the possibility of optimizing transfection efficiency by using a method referred to as least-squares support vector machine, which requires only a few experiments and maintains fairly high accuracy.</p> <p>Results</p> <p>A protocol consists of 15 experiments was performed according to the principle of uniform design. In this protocol, amount of liposome, amount of plasmid, and the number of seeded cells 24 h before transfection were set as independent variables and transfection efficiency was set as dependent variable. A model was deduced from independent variables and their respective dependent variable. Another protocol made up by 10 experiments was performed to test the accuracy of the model. The model manifested a high accuracy. Compared to traditional method, the integrated application of uniform design and least-squares support vector machine greatly reduced the number of required experiments. What's more, higher transfection efficiency was achieved.</p> <p>Conclusion</p> <p>The integrated application of uniform design and least-squares support vector machine is a simple technique for obtaining high transfection efficiency. Using this novel method, the number of required experiments would be greatly cut down while higher efficiency would be gained. Least-squares support vector machine may be applicable to many other problems that need to be optimized.</p

Follow-up care delivery in community-based hypertension and type 2 diabetes management: a multi-centre, survey study among rural primary care physicians in China

Abstract Background Follow-up care is crucial but challenging for disease management particularly in rural areas with limited healthcare resources and clinical capacity, yet few studies have been conducted from the perspective of rural primary care physicians (PCPs). We assessed the frequency of follow-up care delivered by rural PCPs for hypertension and type 2 diabetes – the two most common long-term conditions. Methods We conducted a multi-centre, self-administered survey study built upon existing general practice course programmes for rural PCPs in four provinces. Information on follow-up care delivery were collected from rural PCPs attending centralised in-class teaching sessions using a set of close-ended, multiple choice questions. Binary logistic regression analysis was performed to examine physician-level factors associated with non-attainment of the target frequency of follow-up care for hypertension and type 2 diabetes, respectively. The final sample consisted of rural PCPs from 52 township-level regions. The Complex Samples module was used in the statistical analysis to account for the multistage sample design. Results The overall response rate was 91.4%. Around one fifth of PCPs in rural practices did not achieve the target frequency of follow-up care delivery (18.7% for hypertension; 21.6% for type 2 diabetes). Higher education level of physicians, increased volume of daily patients seen, and no provision of home visits were risk factors for non-attainment of the target frequency of follow-up care for both conditions. Moreover, village physicians with less working experiences tended to have less frequent follow-up care delivery in type 2 diabetes management. Conclusions Efforts that are solely devoted to enhancing rural physicians’ education may not directly translate into strong motivation and active commitment to service provision given the possible existence of clinical inertia and workload-related factors. Risk factors identified for target non-attainment in the follow-up care delivery may provide areas for capacity building programmes in rural primary care practice