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Recently, nanoporous graphene has attracted great interest in the scientific community. It possesses nano-sized holes; thus, it has a highly accessible surface area for lithium adsorption for energy storage applications. Defective graphene has been extensively studied. However, the lithium adsorption mechanism of nanoporous graphene is not clearly understood yet. Here, we present theoretical investigations on the lithium-ion adsorption mechanism in nanoporous graphene. We perform ab initio electronic structure calculations based on density functional theory. Lithium adsorption in a graphene nanopore is studied and adsorption sites are determined. We also study different lithium-ion distributions in graphene nanopores to determine the best lithium–nanoporous graphene structures for lithium-ion batteries. We show that lithium ions can be adsorbed in a graphene nanopore, even in a single layer of graphene. It is also shown that adding more nanopores to multilayer nanoporous graphene can result in higher Li storage capacity for new-generation lithium-ion batteries.

The molecular transport and quantum tunneling of H2 and H2O molecules through nanoporous graphene is studied using computational modeling and first-principles density functional theory. It is demonstrated that molecules with sufficiently high kinetic energies can tunnel through nanopores. It is also demonstrated that molecules can be trapped in front of a nanopore or behind it. These investigations help us learn the behavior of molecules in and around the nanopores of graphene. They also help us learn the fundamentals of molecular tunneling. We believe nanoporous graphene can play important roles for gas separation and nanofiltration.

Automated design and build processes can rapidly accelerate work in synthetic biology and metabolic engineering. Here the authors present Galaxy-SynBioCAD, a toolshed for synthetic biology, metabolic engineering, and industrial biotechnology that they use to build and execute Galaxy scientific workflows from pathway design to strain engineering through the automated generation of scripts driving robotic workstations.

Recently, nanoporous graphene has attracted great interest in the scientific community. It possesses nano-sized holes; thus, it has a highly accessible surface area for lithium adsorption for energy storage applications. Defective graphene has been extensively studied. However, the lithium adsorption mechanism of nanoporous graphene is not clearly understood yet. Here, we present theoretical investigations on the lithium-ion adsorption mechanism in nanoporous graphene. We perform ab initio electronic structure calculations based on density functional theory. Lithium adsorption in a graphene nanopore is studied and adsorption sites are determined. We also study different lithium-ion distributions in graphene nanopores to determine the best lithium–nanoporous graphene structures for lithium-ion batteries. We show that lithium ions can be adsorbed in a graphene nanopore, even in a single layer of graphene. It is also shown that adding more nanopores to multilayer nanoporous graphene can result in higher Li storage capacity for new-generation lithium-ion batteries. [ABSTRACT FROM AUTHOR]

The molecular transport and quantum tunneling of H2 and H2O molecules through nanoporous graphene is studied using computational modeling and first-principles density functional theory. It is demonstrated that molecules with sufficiently high kinetic energies can tunnel through nanopores. It is also demonstrated that molecules can be trapped in front of a nanopore or behind it. These investigations help us learn the behavior of molecules in and around the nanopores of graphene. They also help us learn the fundamentals of molecular tunneling. We believe nanoporous graphene can play important roles for gas separation and nanofiltration. [ABSTRACT FROM AUTHOR]

Amaç: Gebelerdeki vitamin takviyesi obstetrik sonuçlar açısından önemlidir. Beslenme alışkanlıkları et ağırlıklı olan ve bol güneşli ilimizdeki gebelerin ulusal kılavuzlarda önerilen takviyelere olan gerçek ihtiyacı bilinmemektedir. Bu yüzden çalışmamızda, ilimizdeki gebelerin hemoglobin, ferritin, B12, folat ve D vitamini seviyeleri ve desteğe olan ihtiyaçları araştırıldı.Gereç ve Yöntem: Haziran 2018 ve Aralık 2018 tarihleri arasında kadın doğum polikliniğine başvuran 17845 gebenin verisi incelendi. Hastalardan takviye ilaç kullanmayan ve birinci trimesterde hemoglobin, ferritin, B12, folat ve D vitamini istenen 200 gebe çalışmaya dahil edildi. Gebelerin demografik özellikleri tanımlayıcı istatistiksel yöntemlerle belirlendi. Çalışma grubumuzdaki gebeler iki doğum arasındaki süreye göre ve hemoglobin, ferritin, B12, folat ve D vitamini konsantrasyonlarının seviyelerine göre gruplandırılarak sonuçları incelendi.Bulgular: Hastaların hemogram, ferritin, vitamin B12 ve folat konsantrasyonları normal sınırlarda iken, çalışmaya dahil edilen tüm gebelerde bir önceki gebeliği ile mevcut gebeliği arasındaki süre dikkate alınmadan D vitamini düzeyleri ciddi düşük 20 ng/mL’nin altında bulundu. İlaveten yaşı 26’nın altında olan gebelerde B12 seviyeleri anlamlı olarak daha düşüktü. Sonuç: D Vitamini eksikliği ilimizde sık görülen bir sağlık sorunudur ve güneşli günlerin yaygın olduğu bölgemizde yaşayan gebeler için gizli bir risk faktörüdür. İlaveten nöral tüp defekti etiyolojisinde rol oynadığından özellikle daha genç hasta grubunda B12 vitamini takviyesi, hayvansal temelli diyetin yaygın olduğu yerlerde bile prekonsepsiyonel olarak değerlendirilmelidir

Ball burnishing routine permits through a simple, fast and economical manner to obtain free chip on the manufactured parts. It generates a superior surface finish by rotating a ball tool against a workpiece. The burnishing process is commonly developed in industry in order to improve the surface quality, which is a critical issue in the manufacturing sector. An experimental study were carried out to determine the best surface quality for magnesium alloy subjected to different medium. Burnishing of magnesium alloy was performed varying four different mediums and combining different burnishing parameters. To design the experiment were used the classical Taguchi method through which were developed the L16 orthogonal array. This strategy allowed to detect the driving parameters that generate the best surface roughness value by computing the signal-to-noise ratio. The driving parameters values for this study are 400 N (force), 0.05 mm/min (feed rate), three number of passes and boron oil as medium. The results are paramount important for designing heavy parts used in transportation vehicles such as automobiles, airplanes, high-speed trains etc.

Solid-state argyrodite electrolytes are promising candidate materials to produce safe all-solid-state lithium batteries (ASSLBs) due to their high ionic conductivity. These batteries can be used to power electric vehicles and portable consumer electronics which need high power density. Atomic-scale modeling with ab initio calculations became an invaluable tool to better understand the intrinsic properties and stability of these materials. It is also used to create new structures to tailor their properties. This review article presents some of the recent theoretical investigations based on atomic-scale modeling to study argyrodite electrolytes for ASSLBs. A comparison of the effectiveness of argyrodite materials used for ASSLBs and the underlying advantages and disadvantages of the argyrodite materials are also presented in this article.

Copyright of Turkiye Klinikleri Journal of Nursing Sciences is the property of Turkiye Klinikleri and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The artificial neural network method (ANN) is widely used in both modeling and optimization of manufacturing processes. Determination of optimum processing parameters plays a key role as far as both cost and time are concerned within the manufacturing sector. The burnishing process is simple, easy and cost-effective, and thus it is more common to replace other surface finishing processes in the manufacturing sector. This study investigates the effect of burnishing parameters such as the number of passes, burnishing force, burnishing speed and feed rate on the surface roughness and microhardness of an AZ91D magnesium alloy using different artificial neural network models (i.e. the function fitting neural network (FITNET), generalized regression neural network (GRNN), cascade-forward neural network (CFNN) and feed-forward neural network (FFNN). A total of 1440 different estimates were made by means of ANN methods using different parameters. The best average performance results for surface roughness and microhardness are obtained by the FITNET model (i.e. mean square error (MSE): 0.00060608, mean absolute error (MAE): 0.01556013, multiple correlation coefficient (R): 0.99944545), using the Bayesian regularization process (trainbr)). The FITNET model is followed by the FFNN (i.e. MAE: 0.01707086, MSE: 0.00072907, R: 0.99932069) and CFNN (i.e. MAE: 0.01759166, MSE: 0.00080154, R: 0.99924845) models with very small differences, respectively. The GRNN model has noted worse estimation results (i.e. MSE: 0.00198232, MAE: 0.02973829, R: 0.99900783) as compared with the other models. As a result, MSE, MAE and R values show that it is possible to predict the surface roughness and microhardness results of the burnishing process with high accuracy using ANN models.

In this paper, we describe the stepwise development of a cell-free protein synthesis (CFPS) platform derived from cultured Chinese hamster ovary (CHO) cells. We provide a retrospective summary of the design challenges we faced, and the optimized methods developed for the cultivation of cells and the preparation of translationally active lysates. To overcome low yields, we developed procedures to supplement two accessory proteins, GADD34 and K3L, into the reaction to prevent deactivation of the translational machinery by phosphorylation. We compared different strategies for implementing these accessory proteins including two variants of the GADD34 protein to understand the potential trade-offs between yield and ease of implementation. Addition of the accessory proteins increased yield of turbo Green Fluorescent Protein (tGFP) by up to 100-fold depending on which workflow was used. Using our optimized protocols as a guideline, users can successfully develop their own functional CHO CFPS system, allowing for broader application of mammalian CFPS.

Copyright of Turkiye Klinikleri Journal of Nursing Sciences is the property of Turkiye Klinikleri and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)