Economic risk assessment of future debris flows by machine learning method

The economic analysis presented thus far serves to map risk levels in various catchments, offering effective guidance and scientific support for decision makers. By quantifying potential risks, decision makers can gain a better understanding of future challenges, enabling them to prioritize actions and optimize resource allocation in high-risk zones. This approach facilitates long-term urban planning, policy development, and the formulation of adaptation strategies to effectively reduce and manage identified risks. Moreover, the preparedness and emergency response system would be implemented accordingly. Despite these strengths, some limitations persist, suggesting room for improvement in the proposed methodology’s performance. The database of debris-flow occurrences needs further enrichment to refine the volume prediction model. Another potential area for enhancement lies in augmenting the physical vulnerability assessment with new data, considering additional building characteristics such as shape and the number of windows. Nevertheless, all these limitations cannot alter the fact that the proposed ML-based method represents a new tool for generating a map of economic risk caused by future debris-flow events. It also signifies a practical method to deliver accurate and reliable warnings to local residents about the risks posed by debris flows

Development of Polysorbate 80/Phospholipid mixed micellar formation for docetaxel and assessment of its in vivo distribution in animal models

Docetaxel (DTX) is a very important member of taxoid family. Despite several alternative delivery systems reported recently, DTX formulated by Polysorbate 80 and alcohol (Taxotere®) is still the most frequent administration in clinical practice. In this study, we incorporated DTX into Polysorbate 80/Phospholipid mixed micelles and compared its structural characteristics, pharmacokinetics, biodistribution, and blood compatibility with its conventional counterparts. Results showed that the mixed micelles loaded DTX possessed a mean size of approximately 13 nm with narrow size distribution and a rod-like micelle shape. In the pharmacokinetics assessment, there was no significant difference between the two preparations (P > 0.05), which demonstrated that the DTX in the two preparations may share a similar pharmacokinetic process. However, the Polysorbate 80/Phospholipid mixed micelles can increase the drug residence amount of DTX in kidney, spleen, ovary and uterus, heart, and liver. The blood compatibility assessment study revealed that the mixed micelles were safe for intravenous injection. In conclusion, Polysorbate 80/Phospholipid mixed micelle is safe, can improve the tumor therapeutic effects of DTX in the chosen organs, and may be a potential alternative dosage form for clinical intravenous administration of DTX

Neurexin and neuroligins jointly regulate synaptic degeneration at the Drosophila neuromuscular junction based on TEM studies

The Drosophila larval neuromuscular junction (NMJ) is a well-known model system and is often used to study synapse development. Here, we show synaptic degeneration at NMJ boutons, primarily based on transmission electron microscopy (TEM) studies. When degeneration starts, the subsynaptic reticulum (SSR) swells, retracts and folds inward, and the residual SSR then degenerates into a disordered, thin or linear membrane. The axon terminal begins to degenerate from the central region, and the T-bar detaches from the presynaptic membrane with clustered synaptic vesicles to accelerate large-scale degeneration. There are two degeneration modes for clear synaptic vesicles. In the first mode, synaptic vesicles without actin filaments degenerate on the membrane with ultrafine spots and collapse and disperse to form an irregular profile with dark ultrafine particles. In the second mode, clear synaptic vesicles with actin filaments degenerate into dense synaptic vesicles, form irregular dark clumps without a membrane, and collapse and disperse to form an irregular profile with dark ultrafine particles. Last, all residual membranes in NMJ boutons degenerate into a linear shape, and all the residual elements in axon terminals degenerate and eventually form a cluster of dark ultrafine particles. Swelling and retraction of the SSR occurs prior to degradation of the axon terminal, which degenerates faster and with more intensity than the SSR. NMJ bouton degeneration occurs under normal physiological conditions but is accelerated in Drosophila neurexin (dnrx) dnrx273, Drosophila neuroligin (dnlg) dnlg1 and dnlg4 mutants and dnrx83;dnlg3 and dnlg2;dnlg3 double mutants, which suggests that both neurexin and neuroligins play a vital role in preventing synaptic degeneration

中国和葡萄牙关于农业和自然的谚语的比较研究

Dissertação de mestrado em Português Língua Não Materna (PLNM) - Português Língua Estrangeira (PLE) e Língua Segunda (PL2)Como género especial de criação oral popular, os provérbios refletem a relação entre a língua e a cultura. Como um ramo subordinado do provérbio, o provérbio agrícola é o resumo da experiência dos agricultores no processo de produção de trabalho desde tempos antigos, que não só desempenha um papel orientador na produção agrícola, como também orienta a vida quotidiana dos agricultores. Ao mesmo tempo, os agricultores devem compreender as regras da natureza, e realizar o trabalho agrícola segundo as regras, que são abundantes em provérbios sobre a agricultura e a natureza. Estes provérbios resumem as regras da existência de vários animais e plantas na natureza, e também as experiências no processo de trabalho da sociedade humana. Através da aná lise e comparação detalhada destes provérbios pode não só compreender as características deste tipo de provérbios, mas também descobrir as semelhanças e diferenças entre os provérbios portugueses e chineses, e as diferenças entre chineses e portugueses no trabalho agrícola e forma de viver, crenças religiosas, ambiente cultural e ainda noutras vertentes. E no ensino de português língua não materna, espera-se que este trabalho ajude os aprendentes chineses a compreenderem e dominarem estes provérbios e a poderem utilizá-los em atividades letivos para o ensino da língua.As a special genre of popular oral creation, proverbs reflect the relationship between language and culture. As a subordinate branch of proverb, agricultural proverb is the summary of farmers' experience in the process of work production since ancient times, which not only plays a guiding role in agricultural production, but also guides farmers' daily life. At the same time, farmers should understand the rules of nature, and carry out agricultural work according to the rules, which are abundant in proverbs about agriculture and nature. These proverbs summarize the rules of the existence of various animals and plants in nature, and also the experiences in the working process of human society. Through the detailed analysis and comparison of these proverbs, you can not only understand the characteristics of these proverbs, but also discover the similarities and differences between Portuguese and Chinese proverbs, and the differences between Chinese and Portuguese in agricultural work and way of life, religious beliefs, cultural environment and other aspects. And in the teaching of Portuguese as a non-native language, it is hoped that this work will help Chinese learners to understand and master these proverbs and be able to use them in teaching activities for language learning.谚语作为民间口头创作的一种特殊体裁，反映了语言与文化之间的关系。 作为谚语的一个分支，农业谚语是自古以来农民在劳动生产过程中的经验总结， 它不仅对农业生产起着指导作用，而且对农民的日常生活起着指导作用。同时， 农民要了解自然界的规律，按照规律开展农业劳动，就存在着大量有关农业和 自然的谚语。这些谚语总结了自然界中各种动物和植物的生存法则，也总结了 人类社会生产工作过程中的经验。 通过对这些谚语的详细分析和比较，不仅可以了解这些谚语的特点，还可 以发现葡萄牙语和汉语谚语的异同，以及中葡两国在农业劳动和生活方式、宗 教信仰、文化环境等方面的差异。而对于葡萄牙语作为非母语的教学，希望这 项工作能帮助中国学习者理解和掌握这些谚语，并能在教学活动中使用这些谚 语进行语言的教学

A precipitation downscaling framework for regional warning of debris flow in mountainous areas

A timely warning system for debris-flow mitigation in mountainous areas is vital to decrease casualties. However, the lack of rainfall monitoring stations and coarse resolution of satellite-based observations pose challenges for developing such a debris-flow warning model in data-scarce areas. To offer an effective method for the generation of precipitation with fine resolution, a machine learning (ML) based approach is proposed to establish the relationship between precipitation and regional environmental factors (REVs), including normalized difference vegetation index (NDVI), digital elevation model (DEM), geolocations (longitude and latitude) and land surface temperature (LST). This approach enables the downscaling of 3B42 TRMM precipitation data, providing fine temporal and spatial resolution precipitation data. We use PERSIANN-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR) data to calibrate the downscaled results using geographical differential analysis (GDA) before applying them in a case study in the Gyirong Zangbo Basin. After that, we calculate the rainfall thresholds of effective antecedent rainfall (Pe) - intraday rainfall (Po) based on the calibrated precipitation and integrate them into a susceptibility map to develop a debris-flow warning model. The results show that: (1) this ML-based approach can effectively achieve the downscaling of TRMM data; (2) calibrated TRMM data outperforms the original TRMM and downscaled TRMM data, reducing deviations by 55% and 57%; (3) the integrated model, incorporating rainfall thresholds, outperforms a single susceptibility map in providing debris-flow warnings. The developed warning model can offer dynamic warnings for debris flows that may have been missed by the original warning system at a regional scale

Thermodynamic Analysis of Supercritical CO2 Power Cycle with Fluidized Bed Coal Combustion

Closed supercritical carbon dioxide (S-CO2) Brayton cycle is a promising alternative to steam Rankine cycle due to higher cycle efficiency at equivalent turbine inlet conditions, which has been explored to apply to nuclear, solar power, waste heat recovery, and coal-fired power plant. This study establishes 300MW S-CO2 power system based on modified recompression Brayton cycle integrated with coal-fired circulating fluidized bed (CFB) boiler. The influences of two stages split flow on system performance have been investigated in detail. In addition, thermodynamic analysis of critical operating parameters has been carried out, including terminal temperature difference, turbine inlet pressure/temperature, reheat stages, and parameters as well as compressor inlet pressure/temperature. The results show that rational distribution of split ratio to the recompressor (SR1) achieves maximal cycle efficiency where heat capacities of both sides in the low temperature recuperator (LTR) realize an excellent matching. The optimal SR1 decreases in the approximately linear proportion to high pressure turbine (HPT) inlet pressure due to gradually narrowing specific heat differences in the LTR. Secondary split ratio to the economizer of CFB boiler (SR2) can recover moderate flue gas heat caused by narrow temperature range and improve boiler efficiency. Smaller terminal temperature difference corresponds to higher efficiency and brings about larger cost and pressure drops of the recuperators, which probably decrease efficiency conversely. Single reheat improves cycle efficiency by 1.5% under the condition of 600°C/600°C/25Mpa while efficiency improvement for double reheat is less obvious compared to steam Rankine cycle largely due to much lower pressure ratio. Reheat pressure and main compressor (MC) inlet pressure have corresponding optimal values. HPT and low pressure turbine (LPT) inlet temperature both have positive influences on system performance

A hybrid machine-learning model to map glacier-related debris flow susceptibility along Gyirong Zangbo watershed under the changing climate

Gyirong serves as an important channel to Chine-Nepal Economic Corridor, which is also the only land route for China-Nepal trade since the 2015 earthquake. However, the Gyirong corridor suffers from glacier-related debris flow from every April to September because of the complex topographic features and the changing climate. Therefore, a susceptibility map in response to precipitation and temperature change is timely, not only to ensure the safe operation of this corridor, but also to provide decision-makers a guidance for hazard mitigation and environmental remediation. Conventional method is difficult to consider and link the meteorological factors (e.g. temperature and precipitation), topographies, ecological, geological conditions all together to produce the susceptibility map, as such, machine learning is utilised to conduct the analysis. Logistic Regression (LR) and Support Vector Machine (SVM) were firstly applied to evaluate their efficiency and effectiveness of the performance of producing the susceptibility map. In order to improve the fitting and prediction accuracy (ACC), genetic algorithm - support vector machine (GA-SVM) and certainty factor - genetic algorithm - support vector machine (CF-GA-SVM) were conducted based on the initial analysis results of receiver operating characteristics curve (ROC) and ACC. Through the analysis, it can be seen that over 61% of the study areas have a high susceptibility to debris flow, requiring an intensive attention from the local government. To further optimise the computational time, when dealing with small amounts of sample data, SVM is more efficient than LR, but CF-GA-SVM can achieve the highest AUC (Area Under Curve) and ACC values, 0.945 and 0.800, respectively. Overall, CF-GA-SVM model presents a relatively high robustness according to sensitivity analysis

Exhaust Gas Temperature Prediction of Aero-Engine via Enhanced Scale-Aware Efficient Transformer

This research introduces the Enhanced Scale-Aware efficient Transformer (ESAE-Transformer), a novel and advanced model dedicated to predicting Exhaust Gas Temperature (EGT). The ESAE-Transformer merges the Multi-Head ProbSparse Attention mechanism with the established Transformer architecture, significantly optimizing computational efficiency and effectively discerning key temporal patterns. The incorporation of the Multi-Scale Feature Aggregation Module (MSFAM) further refines 2 s input and output timeframe. A detailed investigation into the feature dimensionality was undertaken, leading to an optimized configuration of the model, thereby improving its overall performance. The efficacy of the ESAE-Transformer was rigorously evaluated through an exhaustive ablation study, focusing on the contribution of each constituent module. The findings showcase a mean absolute prediction error of 3.47∘R, demonstrating strong alignment with real-world environmental scenarios and confirming the model’s accuracy and relevance. The ESAE-Transformer not only excels in predictive accuracy but also sheds light on the underlying physical processes, thus enhancing its practical application in real-world settings. The model stands out as a robust tool for critical parameter prediction in aero-engine systems, paving the way for future advancements in engine prognostics and diagnostics

Roles of TiO2 buffer layer for preparation of high performance VO2 thin films with Monoclinic polymorph

Vanadium dioxide (VO2) thin films with pure Monoclinic phase could be transformed from B-phase by inserting TiO2 buffer layers on transparent amorphous glass substrates at the low temperature of 400 °C. This crystalline transformation might be ascribed to oxygen-deficient environment induced by the TiO2 buffer layer and the template effect of TiO2 layer for M-VO2 phase. The simplicity in phase regulation of the present method and the superior optical and electrical properties of the films may allow its wide applications in thermo-opto-electro sensing devices. Keywords: Vanadium dioxide, TiO2 buffer layers, Photoelectric propertie

Excellent near-infrared transmission of Zr-based thin film metallic glasses

Zr50Cu50, Zr47Cu44Al9, Zr46.3Cu43.4Al8.3Nb2 and Zr41.2Ti13.8Cu17.5Ni5Be22.5 thin film metallic glasses (TFMGs) were prepared by pulsed laser deposition (PLD) on glass substrates at room temperature. The effect of thickness on the electrical and optical properties of the Zr-based TFMGs was investigated. It was found that the resistivity of the Zr-based TFMGs basically decreased as the thickness varied from 10 nm to 40 nm. Interestingly, while the transmittance in the visible region decreased significantly with the increase of thickness, the transmittance in the near-infrared range still remained at a high level of larger than 80%. Through the characterization of electrical properties, the high transmittance of the Zr-based TFMGs in the near-infrared range was attributed to their rather low carrier concentration. Our findings provided the possibility for TFMGs to be used as transparent electrodes in the field of near infrared sensors and solar cells. Keywords: Thin film metallic glass, Zr-based alloys, Transmittance, Near infrare