Effect of Tilt Angle on the Morphology of SiC Epitaxial Films Grown on Vicinal (0001) SiC Substrates

In this study of 4H-SiC and 6H-SiC epitaxial films we found that film morphology was strongly dependent on the tilt angle of the substrate. Large surface steps (up to 25 nm high) due to step bunching were more prevalent at smaller tilt angles. Also, 4H films were more susceptible than 6H to 3C-SiC inclusions during growth. The lateral growth of steps from screw dislocations in low-tilt-angle substrates demonstrated that step bunching on the atomic scale was anisotropic with respect to growth direction for both 4H-SiC and 6H-SiC. A model explaining this behavior is presented. We observed and directly measured the Burgers vector of a 'super' screw dislocation in a 6H-SiC epilayer

A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

While traditional methods for modelling the thermal and electrical behaviour of photovoltaic (PV) modules rely on analytical and empirical techniques, machine learning is gaining interest as a way to reduce the time, expertise, and tools required by designers or experts while maintaining high accuracy and reliability. This research presents a data-driven machine learning tool based on artificial neural networks (ANNs) that can forecast yearly PV electricity directly at the optimal PV inclination angle without geographic restrictions and is valid for a wide range of electrical characteristics of PV modules. Additionally, empirical correlations were developed to easily determine the optimal PV inclination angle worldwide. The ANN algorithm, developed in Matlab, systematically and quantitatively summarizes the behaviour of eight PV modules in 48 worldwide climatic conditions. The algorithm's applicability and robustness were proven by considering two different PV modules in the same 48 locations. Yearly climatic variables and electrical/thermal PV module parameters serve as input training data. The yearly PV electricity is derived using dynamic simulations in the TRNSYS environment, which is a simulation program primarily and extensively used in the fields of renewable energy engineering and building simulation for passive as well as active solar design. Multiple performance metrics validate that the ANN-based machine learning tool demonstrates high reliability and accuracy in the PV energy production forecasting for all weather conditions and PV module characteristics. In particular, by using 20 neurons, the highest value of R-square of 0.9797 and the lowest values of the root mean square error and coefficient of variance of 14.67 kWh and 3.8%, respectively, were obtained in the training phase. This high accuracy was confirmed in the ANN validation phase considering other PV modules. An R-square of 0.9218 and values of the root mean square error and coefficient of variance of 31.95 kWh and 7.8%, respectively, were obtained. The results demonstrate the algorithm's vast potential to enhance the worldwide diffusion and economic growth of solar energy, aligned with the seventh sustainable development goal

BAF(mSWI/SNF) complex regulates mediolateral cortical patterning in the developing forebrain

Early forebrain patterning entails the correct regional designation of the neuroepithelium, and appropriate specification, generation, and distribution of neural cells during brain development. Specific signaling and transcription factors are known to tightly regulate patterning of the dorsal telencephalon to afford proper structural/functional cortical arealization and morphogenesis. Nevertheless, whether and how changes of the chromatin structure link to the transcriptional program(s) that control cortical patterning remains elusive. Here, we report that the BAF chromatin remodeling complex regulates the spatiotemporal patterning of the mouse dorsal telencephalon. To determine whether and how the BAF complex regulates cortical patterning, we conditionally deleted the BAF complex scaffolding subunits BAF155 and BAF170 in the mouse dorsal telencephalic neuroepithelium. Morphological and cellular changes in the BAF mutant forebrain were examined using immunohistochemistry and in situ hybridization. RNA sequencing, Co-immunoprecipitation, and mass spectrometry were used to investigate the molecular basis of BAF complex involvement in forebrain patterning. We found that conditional ablation of BAF complex in the dorsal telencephalon neuroepithelium caused expansion of the cortical hem and medial cortex beyond their developmental boundaries. Consequently, the hippocampal primordium is not specified, the mediolateral cortical patterning is compromised, and the cortical identity is disturbed in the absence of BAF complex. The BAF complex was found to interact with the cortical hem suppressor LHX2. The BAF complex suppresses cortical hem fate to permit proper forebrain patterning. We provide evidence that BAF complex modulates mediolateral cortical patterning possibly by interacting with the transcription factor LHX2 to drive the LHX2-dependent transcriptional program essential for dorsal telencephalon patterning. Our data suggest a putative mechanistic synergy between BAF chromatin remodeling complex and LHX2 in regulating forebrain patterning and ontogeny

Capillary filling with wall corrugations] Capillary filling in microchannels with wall corrugations: A comparative study of the Concus-Finn criterion by continuum, kinetic and atomistic approaches

We study the impact of wall corrugations in microchannels on the process of capillary filling by means of three broadly used methods - Computational Fluid Dynamics (CFD), Lattice-Boltzmann Equations (LBE) and Molecular Dynamics (MD). The numerical results of these approaches are compared and tested against the Concus-Finn (CF) criterion, which predicts pinning of the contact line at rectangular ridges perpendicular to flow for contact angles theta > 45. While for theta = 30, theta = 40 (no flow) and theta = 60 (flow) all methods are found to produce data consistent with the CF criterion, at theta = 50 the numerical experiments provide different results. Whilst pinning of the liquid front is observed both in the LB and CFD simulations, MD simulations show that molecular fluctuations allow front propagation even above the critical value predicted by the deterministic CF criterion, thereby introducing a sensitivity to the obstacle heigth.Comment: 25 pages, 8 figures, Langmuir in pres

Thermal modelling of gas generation and retention in the Jurassic organic-rich intervals in the Darquain field, Abadan Plain, SW Iran

The petroleum system with Jurassic source rocks is an important part of the hydrocarbons discovered in the Middle East. Limited studies have been done on the Jurassic intervals in the 26,500 km2 Abadan Plain in south-west Iran, mainly due to the deep burial and a limited number of wells that reach the basal Jurassic successions. The goal of this study was to evaluate the Jurassic organic-rich intervals and shale gas play in the Darquain field using organic geochemistry, organic petrography, biomarker analysis, and basin modelling methods. This study showed that organic-rich zones present in the Jurassic intervals of Darquain field could be sources of conventional and unconventional gas reserves. The organic matter content of samples from the organic-rich zones corresponds to medium-to-high-sulphur kerogen Type II-S marine origin. The biomarker characteristics of organic-rich zones indicate carbonate source rocks that contain marine organic matter. The biomarker results also suggest a marine environment with reducing conditions for the source rocks. The constructed thermal model for four pseudo-wells indicates that, in the kitchen area of the Jurassic gas reserve, methane has been generated in the Sargelu and Neyriz source rocks from Early Cretaceous to recent times and the transformation ratio of organic matter is more than 97%. These organic-rich zones with high initial total organic carbon (TOC) are in the gas maturity stage [1.5–2.2% vitrinite reflectance in oil (Ro)] and could be good unconventional gas reserves and gas source rocks. The model also indicates that there is a huge quantity of retained gas within the Jurassic organic-rich intervals

FIB patterning of stainless steel for the development of nano-structured stent surfaces for cardiovascular applications

Stent implantation is a percutaneous interventional procedure that mitigates vessel stenosis, providing mechanical support within the artery and as such a very valuable tool in the fight against coronary artery disease. However, stenting causes physical damage to the arterial wall. It is well accepted that a valuable route to reduce in-stent re-stenosis can be based on promoting cell response to nano-structured stainless steel (SS) surfaces such as by patterning nano-pits in SS. In this regard patterning by focused ion beam (FIB) milling offers several advantages for flexible prototyping. On the other hand FIB patterning of polycrystalline metals is greatly influenced by channelling effects and redeposition. Correlative microscopy methods present an opportunity to study such effects comprehensively and derive structure–property understanding that is important for developing improved patterning. In this chapter we present a FIB patterning protocol for nano-structuring features (concaves) ordered in rectangular arrays on pre-polished 316L stainless steel surfaces. An investigation based on correlative microscopy approach of the size, shape and depth of the developed arrays in relation to the crystal orientation of the underlying SS domains is presented. The correlative microscopy protocol is based on cross-correlation of top-view scanning electron microscopy, electron backscattering diffraction, atomic force microscopy and cross-sectional (serial) sectioning. Various FIB tests were performed, aiming at improved productivity by preserving nano-size accuracy of the patterned process. The optimal FIB patterning conditions for achieving reasonably high throughput (patterned rate of about 0.03 mm2/h) and nano-size accuracy in dimensions and shapes of the features are discussed as well

Thin Polymer Brush Decouples Biomaterial's Micro-/Nano-Topology and Stem Cell Adhesion

Surface morphology and chemistry of polymers used as biomaterials, such as tissue engineering scaffolds, have a strong influence on the adhesion and behavior of human mesenchymal stem cells. Here we studied semicrystalline poly(ε-caprolactone) (PCL) substrate scaffolds, which exhibited a variation of surface morphologies and roughness originating from different spherulitic superstructures. Different substrates were obtained by varying the parameters of the thermal processing, i.e. crystallization conditions. The cells attached to these polymer substrates adopted different morphologies responding to variations in spherulite density and size. In order to decouple substrate topology effects on the cells, sub-100 nm bio-adhesive polymer brush coatings of oligo(ethylene glycol) methacrylates were grafted from PCL and functionalized with fibronectin. On surfaces featuring different surface textures, dense and sub-100 nm thick brush coatings determined the response of cells, irrespective to the underlying topology. Thus, polymer brushes decouple substrate micro-/nano-topology and the adhesion of stem cells

Benzo[a]pyrene, Aflatoxine B1 and Acetaldehyde Mutational Patterns in TP53 Gene Using a Functional Assay: Relevance to Human Cancer Aetiology

Mutations in the TP53 gene are the most common alterations in human tumours. TP53 mutational patterns have sometimes been linked to carcinogen exposure. In hepatocellular carcinoma, a specific G>T transversion on codon 249 is classically described as a fingerprint of aflatoxin B1 exposure. Likewise G>T transversions in codons 157 and 158 have been related to tobacco exposure in human lung cancers. However, controversies remain about the interpretation of TP53 mutational pattern in tumours as the fingerprint of genotoxin exposure. By using a functional assay, the Functional Analysis of Separated Alleles in Yeast (FASAY), the present study depicts the mutational pattern of TP53 in normal human fibroblasts after in vitro exposure to well-known carcinogens: benzo[a]pyrene, aflatoxin B1 and acetaldehyde. These in vitro patterns of mutations were then compared to those found in human tumours by using the IARC database of TP53 mutations. The results show that the TP53 mutational patterns found in human tumours can be only partly ascribed to genotoxin exposure. A complex interplay between the functional impact of the mutations on p53 phenotype and the cancer natural history may affect these patterns. However, our results strongly support that genotoxins exposure plays a major role in the aetiology of the considered cancers

The Importance of Escherichia coli O157: H7 in Foodborn Infection

Abstract: Enterohemorrhagic Escherichia coli O157: H7 is one of the most important causes of bloody diarrhea. This bacterium is able to make bloody diarrhea or Hemorrhagic Colitis (HC) through verotoxin or shigatoxin production, and in acute forms it may lead to Hemolytic Uremic Syndrome (HUS) or Thrombotic Thrombocytopenic Purpurea (TTP). Contamination with E. coli O157:H7 usually happens after consumption of animal products especially undercooked meats. The most important reservoir of this bacterium is beef and consumption of undercooked ground beef, especially in children younger than 10 years old, is the most common reason of food infection by this bacterium. Two important biochemical characteristics for detection of E. coli O157: H7 are lack of sorbitol fermentation and absence of glucuronidase. In order to control food infection with this bacterium, foods must be cooked thoroughly until reaching the temperature of at least 68.3°C, in the center. Keywords: Enterohemorrhagic Escherichia coli, Food contamination, Hemorrhogic Colitis, Hemolytic Uremic Syndrome, Thrombotic Thrombocytopenic Purpure