Non-coding RNAs: Important participants in cardiac fibrosis

Cardiac remodeling is a pathophysiological process activated by diverse cardiac stress, which impairs cardiac function and leads to adverse clinical outcome. This remodeling partly attributes to cardiac fibrosis, which is a result of differentiation of cardiac fibroblasts to myofibroblasts and the production of excessive extracellular matrix within the myocardium. Non-coding RNAs mainly include microRNAs and long non-coding RNAs. These non-coding RNAs have been proved to have a profound impact on biological behaviors of various cardiac cell types and play a pivotal role in the development of cardiac fibrosis. This review aims to summarize the role of microRNAs and long non-coding RNAs in cardiac fibrosis associated with pressure overload, ischemia, diabetes mellitus, aging, atrial fibrillation and heart transplantation, meanwhile shed light on the diagnostic and therapeutic potential of non-coding RNAs for cardiac fibrosis

Reconstructing the earliest known composite-tiled roofs from the Chinese Loess Plateau

The origins of composite tiles, one of the oldest forms of roofing, are still unclear. This study is based on a set of over 5000 clay tile fragments excavated from a single context in the Qiaocun site on the Chinese Loess Plateau, dated to ~ 2400-2200 BCE (Early Longshan Period). By combining morphological measurement statistics, 3D modeling, computer-based simulations, and reference to historical and archaeological records, we reconstruct the earliest known composite-tile roofing techniques and demonstrate that tile production was under a low-level standardization, with manual control forming a key agent during the roofing process. The quantitative study of the composite roof tiles from Qiaocun was then placed in its archaeological context and compared with other sites on the Loess Plateau. It was found that tile-roofed buildings were, by necessity, community projects. Such structures served as nodes in larger social communication networks; additionally, their appearance was linked to intensified social complexity in public affairs during the Longshan Period. The invention of clay tiles was associated with the inception of thick rammed-earth walls which had sufficient strength to serve as load-bearing structures for heavy tiled roofs. The roof tiles excavated from Qiaocun site indicate that the Loess Plateau was a key center for the origin and spread of composite tiles and related roofing and construction methods, suggesting a Longshan-Western Zhou tradition of roofing techniques in East Asia

Minute-Cadence Observations of the LAMOST Fields with the TMTS V. Machine Learning Classification of TMTS Catalogues of Periodic Variable Stars

Periodic variables are always of great scientific interest in astrophysics. Thanks to the rapid advancement of modern large-scale time-domain surveys, the number of reported variable stars has experienced substantial growth for several decades, which significantly deepened our comprehension of stellar structure and binary evolution. The Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) has started to monitor the LAMOST sky areas since 2020, with a cadence of 1 minute. During the period from 2020 to 2022, this survey has resulted in densely sampled light curves for ~ 30,000 variables of the maximum powers in the Lomb-Scargle periodogram above the 5sigma threshold. In this paper, we classified 11,638 variable stars into 6 main types using XGBoost and Random Forest classifiers with accuracies of 98.83% and 98.73%, respectively. Among them, 5301 (45.55%) variables are newly discovered, primarily consisting of Delta Scuti stars, demonstrating the capability of TMTS in searching for short-period variables. We cross-matched the catalogue with Gaia's second Data Release (DR2) and LAMOST's seventh Data Release (DR7) to obtain important physical parameters of the variables. We identified 5504 Delta Scuti stars (including 4876 typical Delta Scuti stars and 628 high-amplitude Delta Scuti stars), 5899 eclipsing binaries (including EA-, EB- and EW-type) and 226 candidates of RS Canum Venaticorum. Leveraging the metal abundance data provided by LAMOST and the Galactic latitude, we discovered 8 candidates of SX Phe stars within the class of "Delta Scuti stars". Moreover, with the help of Gaia color-magnitude diagram, we identified 9 ZZ ceti stars.Comment: 20 pages, 14 figures, accepted to MNRA

A Comprehensive Study of Knowledge Editing for Large Language Models

Large Language Models (LLMs) have shown extraordinary capabilities in understanding and generating text that closely mirrors human communication. However, a primary limitation lies in the significant computational demands during training, arising from their extensive parameterization. This challenge is further intensified by the dynamic nature of the world, necessitating frequent updates to LLMs to correct outdated information or integrate new knowledge, thereby ensuring their continued relevance. Note that many applications demand continual model adjustments post-training to address deficiencies or undesirable behaviors. There is an increasing interest in efficient, lightweight methods for on-the-fly model modifications. To this end, recent years have seen a burgeoning in the techniques of knowledge editing for LLMs, which aim to efficiently modify LLMs' behaviors within specific domains while preserving overall performance across various inputs. In this paper, we first define the knowledge editing problem and then provide a comprehensive review of cutting-edge approaches. Drawing inspiration from educational and cognitive research theories, we propose a unified categorization criterion that classifies knowledge editing methods into three groups: resorting to external knowledge, merging knowledge into the model, and editing intrinsic knowledge. Furthermore, we introduce a new benchmark, KnowEdit, for a comprehensive empirical evaluation of representative knowledge editing approaches. Additionally, we provide an in-depth analysis of knowledge location, which can give a deeper understanding of the knowledge structures inherent within LLMs. Finally, we discuss several potential applications of knowledge editing, outlining its broad and impactful implications.Comment: Ongoing work; 52 pages, 282 citations; benchmark is available at https://huggingface.co/datasets/zjunlp/KnowEdit code is available at https://github.com/zjunlp/EasyEdit paper list is available at https://github.com/zjunlp/KnowledgeEditingPaper

Minute-cadence Observations of the LAMOST Fields with the TMTS: III. Statistic Study of the Flare Stars from the First Two Years

Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) aims to detect fast-evolving transients in the Universe, which has led to the discovery of thousands of short-period variables and eclipsing binaries since 2020. In this paper, we present the observed properties of 125 flare stars identified by the TMTS within the first two years, with an attempt to constrain their eruption physics. As expected, most of these flares were recorded in late-type red stars with $G_{\rm BP}-G_{\rm RP}$ > 2.0 mag, however, the flares associated with bluer stars tend to be on average more energetic and have broader profiles. The peak flux (F_peak) of the flare is found to depend strongly on the equivalent duration (ED) of the energy release, i.e., $F_{{\rm peak}} \propto {\rm ED}^{0.72\pm0.04}$, which is consistent with results derived from the Kepler and Evryscope samples. This relation is likely related to the magnetic loop emission, while -- for the more popular non-thermal electron heating model -- a specific time evolution may be required to generate this relation. We notice that flares produced by hotter stars have a flatter $F_{{\rm peak}} \propto {\rm ED}$ relation compared to that from cooler stars. This is related to the statistical discrepancy in light-curve shape of flare events with different colors. In spectra from LAMOST, we find that flare stars have apparently stronger H alpha emission than inactive stars, especially at the low temperature end, suggesting that chromospheric activity plays an important role in producing flares. On the other hand, the subclass having frequent flares are found to show H alpha emission of similar strength in their spectra to that recorded with only a single flare but similar effective temperature, implying that the chromospheric activity may not be the only trigger for eruptions.Comment: 17 pages, 15 figures, 2 tables, refereed version. For associated data files, see https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/523/219

Rubber Toughened and Nanoparticle Reinforced Epoxy Composites

Epoxy resins have achieved acceptance as adhesives, coatings, and potting compounds, but their main application is as matrix to produce reinforced composites. However, their usefulness in this field still limited due to their brittle nature. Some studies have been done to increase the toughness of epoxy composites, of which the most successful one is the modification of the polymer matrix with a second toughening phase. Resin Transfer Molding (RTM) is one of the most important technologies to manufacture fiber reinforced composites. In the last decade it has experimented new impulse, due to its favorable application to produce large surface composites with good technical properties and at relative low cost. This research work focuses on the development of novel modified epoxy matrices, with enhanced mechanical and thermal properties, suitable to be processed by resin transfer molding technology, to manufacture Glass Fiber Reinforced Composites (GFRC’s) with improved performance in comparison to the commercially available ones. In the first stage of the project, a neat epoxy resin (EP) was modified using two different nano-sized ceramics: silicium dioxide (SiO2) and zirconium dioxide (ZrO2); and micro-sized particles of silicone rubber (SR) as second filler. Series of nanocomposites and hybrid modified epoxy resins were obtained by systematic variation of filler contents. The rheology and curing process of the modified epoxy resins were determined in order to define their aptness to be processed by RTM. The resulting matrices were extensively characterized qualitatively and quantitatively to precise the effect of each filler on the polymer properties. It was shown that the nanoparticles confer better mechanical properties to the epoxy resin, including modulus and toughness. It was possible to improve simultaneously the tensile modulus and toughness of the epoxy matrix in more than 30 % and 50 % respectively, only by using 8 vol.-% nano-SiO2 as filler. A similar performance was obtained by nanocomposites containing zirconia. The epoxy matrix modified with 8 vol.-% ZrO2 recorded tensile modulus and toughness improved up to 36% and 45% respectively regarding EP. On the other hand, the addition of silicone rubber to EP and nanocomposites results in a superior toughness but has a slightly negative effect on modulus and strength. The addition of 3 vol.-% SR to the neat epoxy and nanocomposites increases their toughness between 1.5 and 2.5 fold; but implies also a reduction in their tensile modulus and strength in range 5-10%. Therefore, when the right proportion of nanoceramic and rubber were added to the epoxy resin, hybrid epoxy matrices with fracture toughness 3 fold higher than EP but also with up to 20% improved modulus were obtained. Widespread investigations were carried out to define the structural mechanisms responsible for these improvements. It was stated, that each type of filler induces specific energy dissipating mechanisms during the mechanical loading and fracture processes, which are closely related to their nature, morphology and of course to their bonding with the epoxy matrix. When both nanoceramic and silicone rubber are involved in the epoxy formulation, a superposition of their corresponding energy release mechanisms is generated, which provides the matrix with an unusual properties balance. From the modified matrices glass fiber reinforced RTM-plates were produced. The structure of the obtained composites was microscopically analyzed to determine their impregnation quality. In all cases composites with no structural defects (i.e. voids, delaminations) and good superficial finish were reached. The composites were also properly characterized. As expected the final performance of the GFRCs is strongly determined by the matrix properties. Thus, the enhancement reached by epoxy matrices is translated into better GFRC´s macroscopical properties. Composites with up to 15% enhanced strength and toughness improved up to 50%, were obtained from the modified epoxy matrices

Thermal-Infrared Spectral Feature Analysis and Spectral Identification of Monzonite Using Feature-Oriented Principal Component Analysis

Rock spectral analysis is an important research field in hyperspectral remote sensing information processing. Compared with the spectra in the short-wave infrared and visible–near-infrared regions, the emittance spectrum of rocks in the thermal infrared (TIR) region is highly significant for identifying some major rock-forming minerals, including feldspar, biotite, pyroxene and hornblende. Even for the same rock type, slight differences in mineral composition generally result in varying spectral signatures, undoubtedly increasing the difficulty in discriminating rock types on the Earth’s surface via TIR spectroscopy. In this study, amounts of monzonite samples from different regions were collected in the central part of Hunan Province, China, and emission spectra at 8–14 μm were measured using a portable thermal infrared spectrometer. The experimental result illustrates 13 remarkable feature positions for all the monzonite samples from different geological environments. Furthermore, by combining the extracted features with the principal component analysis (PCA) method, feature-oriented PCA was applied to establish a model for identifying monzonite accurately and quickly without performing spectral library matching and spectral deconvolution. This study provides an important method for rock type identification in the TIR region that is helpful for the rock spectral analysis, geological mapping and pixel unmixing of remote sensing images

Ecological risk assessment of landscape in arid area watersheds under ecological water conveyance: A case study of Taitema Lake

The Taitema Lake Basin serves as an ecological barrier in the south of the Tarim Basin, connecting with the Qiemo, Ruoqiang, and Milan oases, collectively preventing the expansion and merging of the desert, specifically inhibiting the convergence of the Taklamakan Desert and Lop Nur. In recent years, with changes in the natural environment and an increase in water usage, the downstream flow of the Tarim River has decreased, leading to the gradual drying up of Taitema Lake and exacerbating desertification, resulting in frequent sandstorms. Subsequently, under the influence of ecological water transfer projects, Taitema Lake has gradually recovered, and the ecological environment has improved. This study focuses on Taitema Lake and its nearby regions, constructing the Regional Landscape Ecological Risk Index (ERI) to assess landscape ecological risks before and after ecological engineering and determine ecological benefits. The results indicate that the EWC (Ecological Water Conveyance) project effectively supplements water in the intermediate and lower courses of the Tarim River and the terminal lakes, significantly bolstering ecological conditions in the lake basin and reducing risks. However, the current EWC project is relatively extensive, and the water reaching the Tarim River and Taitema Lake depends entirely on the surplus water from upstream production and daily life. Additionally, the distribution of downstream water depends entirely on natural topography, leading to uneven spatiotemporal distribution of water resources and significant evaporation losses. Rational hydraulic engineering measures should be taken to re-plan the distribution of rivers and lakes, achieving the maximum ecological benefits of the EWC project

An Enhanced Information Retrieval Method Based on Ontology for Bridge Inspection

Bridge management systems (BMSs) are widely used to assist an inspector in performing element-level bridge inspection. Retrieving and determining target elements to be inspected becomes an important factor in the efficiency of bridge inspection. This paper presents an enhanced information retrieval (IR) method based on ontology to predict the target elements. The novelty of this method is that an improved seven-step method based on automatic mapping technology is proposed to construct a new bridge inspection ontology (BIontology), which provides a knowledge base for the present IR method. A further novelty is that a new software architecture is designed for integrating ontology, and a promising prototype system based on the software architecture is developed to realize the present IR method using SPARQL query. In addition, a novel prediction algorithm based on the present IR method is proposed to automatically recommend the target elements. A case study of ontology construction is performed to demonstrate that the improved seven-step method can accelerate the construction of the BIontology compared with the manual method. A case study of bridge inspection is implemented to verify that the proposed algorithm outperforms an existing method, thereby validating the effectiveness of the present IR method