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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.

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.

This study primarily focuses on green machining, which refers to the environmentally friendly machining of parts without compromising the environment and human health. Green machining, an innovative approach in the manufacturing industry, aims to reduce the environmental impact and promote sustainable practices throughout the machining process. Green machining involves the utilization of methods such as machining, dry machining, high-performance cutting, hybrid machining, and high-speed cutting, along with environmentally friendly lubrication practices. The objective of this research is to investigate the effects of machining Ti6Al4V alloys, a widely used lightweight metal in the aerospace industry known for its challenging machinability. The study specifically examines cutting force, surface roughness, and tool wear under various cutting parameters and tribological conditions. The use of a new lubrication/cooling method was investigated in order to minimize the effects of traditional cutting fluids used in the machining of difficult materials, which may cause environmental and human health. This way, sustainable green production compatible with the environment has been realized today, where global warming and carbon emissions are rapidly increasing. In addition, it was observed that the factor determining the cutting force was the depth of cut and the feed rate was the most significant factor affecting the surface roughness. [ABSTRACT FROM AUTHOR]

Bu çalışmada sıcak iş takım çeliklerinden Dievar derece çeliği üzerinde çeşitli matkaplar ile delik delme esnasında meydana gelen eksenel kuvvetler, kesme momentleri, yüzey pürüzlülükleri, ölçü tamlığı ve dairesellikten sapma değerleri araştırılmıştır. Deneyler dik işleme tezgâhında soğutma sıvısı ile Ø16 mm çaplarında kaplamasız karbür matkap ve kendinden raybalı TiAlN kaplamalı matkap kullanılarak yapılmıştır. Deneylerde ilerleme hızı 0,16 mm/dev, kesme hızı ise 36, 40, 44, 48 m/dak hızları kullanılmıştır. Çıkan sonuçlar doğrusal regresyon metodu ile modellenmiş ve polinom regresyon eğrisi eşitliği anlamlılık değerleri mukayese edilmiştir. Aynı zamanda varyans analizi yapılarak kesme hızı ve matkap tipinin eksenel ilerleme kuvveti, kesme momenti, yüzey pürüzlülüğü ölçü tamlığı ve dairesellikten sapma değeri sonuçları üzerine etkileri incelenmiştir.

Bu çalışmada sıcak iş takım çeliklerinden Dievar derece çeliği üzerinde çeşitli matkaplar ile delik delme esnasında meydana gelen eksenel kuvvetler, kesme momentleri, yüzey pürüzlülükleri, ölçü tamlığı ve dairesellikten sapma değerleri araştırılmıştır. Deneyler dik işleme tezgâhında soğutma sıvısı ile Ø16 mm çaplarında kaplamasız karbür matkap ve kendinden raybalı TiAlN kaplamalı matkap kullanılarak yapılmıştır. Deneylerde ilerleme hızı 0,16 mm/dev, kesme hızı ise 36, 40, 44, 48 m/dak hızları kullanılmıştır. Çıkan sonuçlar doğrusal regresyon metodu ile modellenmiş ve polinom regresyon eğrisi eşitliği anlamlılık değerleri mukayese edilmiştir. Aynı zamanda varyans analizi yapılarak kesme hızı ve matkap tipinin eksenel ilerleme kuvveti, kesme momenti, yüzey pürüzlülüğü ölçü tamlığı ve dairesellikten sapma değeri sonuçları üzerine etkileri incelenmiştir.

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. [ABSTRACT FROM AUTHOR]

Background: It is important that nursing students who will be at the forefront of providing health services and be key personnel in the development of public health practices have sufficient knowledge of COVID‐19 and related appropriate practices surrounding the outbreak. Thus, it is necessary to update the nursing curriculum for the changing needs in nursing education in urgent public health problems such as epidemics. Aims: This study aims to determine the knowledge and practices of nursing students about the COVID‐19 pandemic. Methods: This study was conducted with 304 nursing students. The study data were collected using online tools consisting of a personal information form and the COVID‐19 Knowledge and Practice Questionnaire. Results: Participants had good levels of knowledge and practices regarding the COVID‐19 outbreak. The students' total mean knowledge score regarding COVID‐19 was 28.95 ± 4.46 and their total mean practice score was 5.85 ± 1.03. Conclusions: It is very important that all nurse candidates, who will soon play an active role in the pandemic, have the correct knowledge and practices to prevent its spread. Therefore, the current curriculum for nurses, whom we can describe as the backbone of public health, should be equipped and enriched with evidence to support them during major events such as the COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

Using a combination of continuum modeling, atomistic simulations, and numerical optimization, we estimate the flexural rigidity of a graphene sheet. We consider a rectangular sheet that is initially parallel to a rigid substrate. The sheet interacts with the substrate by van der Waals forces and deflects in response to loading on a pair of opposite edges. To estimate the flexural rigidity, we model the graphene sheet as a continuum and numerically solve an appropriate differential equation for the transverse deflection. This solution depends on the flexural rigidity. We then use an optimization procedure to find the value of the flexural rigidity that minimizes the difference between the numerical solutions and the deflections predicted by atomistic simulations. This procedure predicts a flexural rigidity of 0.26 nN nm=1.62 eV.