Unsteady RANS and IDDES studies on a telescopic crescent-shaped wingsail

Over the years, several research projects have evaluated different concepts for wind-assisted propulsion, generally concluding that it can lead to significant fuel savings. The time-averaged propulsive performance of a single rigid wingsail has been analysed in previous studies. However, the unsteady characteristics of the external loads which may induce structural vibration are also important to be considered. In this study, full-scale simulations, with both unsteady RANS and IDDES methods, are performed to analyze the flow field. The paper\u27s analysis includes flow separation and vortex shedding, the development and dissipation of wake vortices, and the lift reduction due to tip vortices. It also studies the telescopic function of the wingsail by analyzing sails with different heights and wind conditions. The paper concludes that the unsteady RANS and IDDES simulations make similar predictions for time-averaged loads but disagree on the unsteady characteristics. The IDDES simulations indicate more complex vortex-shedding phenomena

Regulation of the proteostasis network by the neuronal system

The protein homeostasis (proteostasis) network is a nexus of molecular mechanisms that act in concert to maintain the integrity of the proteome and ensure proper cellular and organismal functionality. Early in life the proteostasis network efficiently preserves the functionality of the proteome, however, as the organism ages, or due to mutations or environmental insults, subsets of inherently unstable proteins misfold and form insoluble aggregates that accrue within the cell. These aberrant protein aggregates jeopardize cellular viability and, in some cases, underlie the development of devastating illnesses. Hence, the accumulation of protein aggregates activates different nodes of the proteostasis network that refold aberrantly folded polypeptides, or direct them for degradation. The proteostasis network apparently functions within the cell, however, a myriad of studies indicate that this nexus of mechanisms is regulated at the organismal level by signaling pathways. It was also discovered that the proteostasis network differentially responds to dissimilar proteotoxic insults by tailoring its response according to the specific challenge that cells encounter. In this mini-review, we delineate the proteostasis-regulating neuronal mechanisms, describe the indications that the proteostasis network differentially responds to distinct proteotoxic challenges, and highlight possible future clinical prospects of these insights

Propulsive performance of a rigid wingsail with crescent-shaped profiles

Wind-assisted ship propulsion is considered an effective method for reducing greenhouse gas emissions. This paper presents numerical analyses of the aerodynamics of a single rigid wingsail conducted using the unsteady Reynolds-averaged Navier–Stokes (uRANS) equations. The wingsail is designed with a new sectional profile: a crescent-shaped foil. This new profile and the classical NACA 0015 profile were compared. Simulations were performed in two and three dimensions, with a focus on key physical quantities such as the external loads on the wingsail, the flow field, and the propulsive performance. It is concluded that the wingsail with the crescent-shaped section has higher propulsion efficiency than the NACA 0015. However, stronger flow separation was detected for the crescent-shaped section. As the separation deteriorates, the flow unsteadiness, challenges the strength and stability of the wingsail structure. The three-dimensional simulations of both profiles, particularly NACA 0015, show that the tip vortices induced from the side edge of the wingsail account for substantial negative effects on the propulsion performance. A case study revealed that installing a wingsail with a crescent-shaped profile reduced fuel consumption by 9% compared with no wingsail

Reducing carbon emissions in the architectural design process via transformer with cross-attention mechanism

IntroductionThe construction industry is one of the world’s largest carbon emitters, accounting for around 40% of total emissions. Therefore, reducing carbon emissions from the construction sector is critical to global climate change mitigation. However, traditional architectural design methods have some limitations, such as difficulty in considering complex interaction relationships and a large amount of architectural data, so machine learning can assist architectural design in improving design efficiency and reducing carbon emissions.MethodsThis study aims to reduce carbon emissions in the architectural design by using a Transformer with a cross-attention mechanism model. We aim to use machine learning methods to generate optimized building designs that reduce carbon emissions during their use and construction. We train the model on the building design dataset and its associated carbon emissions dataset and use a cross-attention mechanism to let the model focus on different aspects of the building design to achieve the desired outcome. We also use predictive modelling to predict energy consumption and carbon emissions to help architects make more sustainable decisions.Results and discussionExperimental results demonstrate that our model can generate optimized building designs to reduce carbon emissions during their use and construction. Our model can also predict a building’s energy consumption and carbon emissions, helping architects make more sustainable decisions. Using Transformers with cross-attention mechanism models to reduce carbon emissions in the building design process can contribute to climate change mitigation. This approach could help architects better account for carbon emissions and energy consumption and produce more sustainable building designs. In addition, the method can also guide future building design and decision-making by predicting building energy consumption and carbon emissions

Exploring Format Consistency for Instruction Tuning

Instruction tuning has emerged as a promising approach to enhancing large language models in following human instructions. It is shown that increasing the diversity and number of instructions in the training data can consistently enhance generalization performance, which facilitates a recent endeavor to collect various instructions and integrate existing instruction tuning datasets into larger collections. However, different users have their unique ways of expressing instructions, and there often exist variations across different datasets in the instruction styles and formats, i.e., format inconsistency. In this work, we study how format inconsistency may impact the performance of instruction tuning. We propose a framework called "Unified Instruction Tuning" (UIT), which calls OpenAI APIs for automatic format transfer among different instruction tuning datasets. We show that UIT successfully improves the generalization performance on unseen instructions, which highlights the importance of format consistency for instruction tuning. To make the UIT framework more practical, we further propose a novel perplexity-based denoising method to reduce the noise of automatic format transfer. We also train a smaller offline model that achieves comparable format transfer capability than OpenAI APIs to reduce costs in practice

The anaphase promoting complex impacts repair choice by protecting ubiquitin signalling at DNA damage sites

Double-strand breaks (DSBs) are repaired through two major pathways, homology-directed recombination (HDR) and non-homologous end joining (NHEJ). While HDR can only occur in S/G2, NHEJ can happen in all cell cycle phases (except mitosis). How then is the repair choice made in S/G2 cells? Here we provide evidence demonstrating that APCCdh1 plays a critical role in choosing the repair pathways in S/G2 cells. Our results suggest that the default for all DSBs is to recruit 53BP1 and RIF1. BRCA1 is blocked from being recruited to broken ends because its recruitment signal, K63-linked poly-ubiquitin chains on histones, is actively destroyed by the deubiquitinating enzyme USP1. We show that the removal of USP1 depends on APCCdh1 and requires Chk1 activation known to be catalysed by ssDNA-RPA-ATR signalling at the ends designated for HDR, linking the status of end processing to RIF1 or BRCA1 recruitment.We thank S.-Y. Lin (MD Anderson Cancer Center) for cell lines; J. Rosen (Baylor College of Medicine) for reagents; H. Masai (Tokyo Metropolitan Institute of Medical Science) for U2OS-Fucci cell line; D. Durocher (University of Toronto) for HeLa-Fucci cell line; E. Citterio (Netherlands Cancer Institute) for GFP-USP3 construct; M.S.Y. Huen (The University of Hong Kong) for RNF168 antibody. This work was performed with facilities and instruments in the Imaging Core of National Center for Protein Science (Beijing), the Cytometry and Cell Sorting Core at Baylor College of Medicine with funding from the NIH (P30 AI036211, P30 CA125123 and S10 RR024574), the Integrated Microscopy Core at Baylor College of Medicine with funding from the NIH (HD007495, DK56338 and CA125123), and the John S. Dunn Gulf Coast Consortium for Chemical Genomics. We also thank other members of the Zhang lab for helpful discussion and support. This work was supported in part by an international collaboration grant (# 2013DFB30210) and a 973 Project grant (# 2013CB910300) from Chinese Minister of Science and Technology, in part by a Chinese National Natural Science Foundation grant (# 81171920), in part by a grant from The Committee of Science and Technology of Beijing Municipality, China (# Z141100000214015), and in part by NIH grants CA116097 and CA122623 to P.Z. J.J. is supported by grants from National Institutes of Health (R01GM102529) and the Welch Foundation (AU-1711). S.H. is supported by grants (# 81272488 and 81472795) from Chinese National Natural Science Foundation. Y.Z. is supported by grants from the National Natural Scientific Foundation of China (No. 81430055), Programs for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R13).S

Guest editorial : Dynamic analysis, control, and situation awareness of power systems with high penetrations of power electronic converters

In recent decades, global power grids have evolved with a rapid and extensive development of power electronic converters (PEC), including renewable energy systems (RES), high-voltage DC (HVDC) transmission, flexible AC transmission system (FACTS), energy storages, and microgrids. The distinct characteristics of power electronic devices traditional synchronous generators, especially their rapid control speed, wide-band performance and lack of inertia response and spinning reserve, are altering grid dynamics, and inducing new stability challenges. Continuation of such trends could further exacerbate the risk to the stability of power grids because of factors such as low inertias, lack of spinning reserve to quickly nullify active power mismatch between demand and supply. Therefore, scientific investigations on novel dynamic modelling and stability analysis methods, data-driven monitoring and situation awareness on grid inertia-power-frequency evolution, grid dynamic frequency forecast methodologies in consideration of novel PEC control schemes, and advanced PEC grid integration control schemes to minimise frequency management risks become increasingly crucial for the secured operations of power systems with high PEC penetrations. In this Special Issue, namely ‘Dynamic Analysis, Control, and Situation Awareness of Power Systems with High Penetrations of Power Electronic Converters’, we have presented eight original papers of sufficient quality and innovation. The 10 eventually accepted papers can be clustered into three two categories, namely novel control design, stability and fault analysis

Molecular Cloning, Expression Profiling, and Marker Validation of the Chicken Myoz3 Gene

Myozenin3 (Myoz3) has been reported to bind multiple Z-disc proteins and hence play a key role in signal transduction and muscle fiber type differentiation. The purpose of current study is to better understand the basic characteristics of Myoz3. Firstly, we cloned the ORF (open reading frame) of the Myoz3 gene. AA (amino acid) sequence analysis revealed that the Myoz3 gene encodes a 26 kDa protein which have 97% identities with that of turkey. Expression profiling showed that Myoz3 mRNA is mainly expressed in leg muscle and breast muscle. Furthermore, we investigated Myoz3 gene polymorphisms in two broiler breeds, the Yellow Bantam (YB) and the Avian. Five SNPs (single nucleotide polymorphisms) were identified in the YB breed and 3 were identified in the Avian breed. Genotypes and haplotype were constructed and their associations with carcass traits were analyzed. In the YB breed, c.516 C>T had a strong effect on both shank bone length and the * value of breast muscle, and the H1H3 diplotype had the highest FC compared to other diplotypes. The markers identified in this study may serve as useful targets for the marker-assisted selection (MAS) of growth and meat quality traits in chickens