Fabrication of Air Cavity Structures Using DRIE for Acoustic Signal Confinement in FBAR Devices by Raju Patel, Manoj Singh Adhikari, Deepak Bansal, Tanmoy Majumder

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PATHOMORPHOLOGICAL CHANGES IN THE VESSELS OF THE HEART AND THE LUNGS IN PNEUMOCONIOSIS by Надежда Николаевна Михайлова, Олег Иванович Бондарев, Мария Сергеевна Бугаева

“…In the conditions of the prolonged exposure to coal-rock dust on the body in the vessels of the heart and the lungs we observed the formation of similar pathological changes in the form of endotheliosis, hypertrophy of the medial layer, thickening of the wall, perivascular fibrosis. …”
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Inorganic carbon assimilation by planktonic community in Santos Basin, Southwestern Atlantic Ocean by Deborah S. Kutner, Jeff S. Bowman, Flávia M. P. Saldanha-Corrêa, Mateus G. Chuqui, Pedro M. Tura, Daniel L. Moreira, Frederico P. Brandini, Camila N. Signori

“…Rates were analyzed using statistical tests to verify spatial differences between groups of samples and generalized linear models to identify correlations with environmental variables (temperature, salinity, density, mixed layer depth, dissolved oxygen, nitrite, nitrate, silicate, phosphate, turbidity, CDOM, and phycoerythrin and chlorophyll-a concentrations). …”
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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

“…The selected features are used to train a multi-layer perceptron (MLP) neural network and further processed using a long short-term (LSTM) memory network in order to classify tumors as malignant or benign. …”
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Key technology of fine description of complex fault block reservoir and its application by LI Guoyong

“…Six key technologies have been gradually formed, including small layer division and fine correlation of complex fault block reservoirs, low-order fault identification, comprehensive characterization of delta reservoirs, formation and main controlling factors of dominant permeability channels in the process of water injection development, three-dimensional geological modeling of complex fault block reservoirs, and quantitative characterization and distribution of remaining oil, which are applied to five typical blocks, including two types of reservoir genesis of fan delta and braided river delta, and two types of physical properties of medium permeability and low permeability. …”
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Analysis of the Effect of Precipitation Type on Flow Simulation in Talar and Khoramabad Watershed by Mohammad Golshan, Abdollah Pirneia, Payam Ebrahimi, Abazar Esmali Ouri

“…Using a model with integrity and high performance to simulate the hydrological process in deferent watersheds is very important. …”
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Sustainable Material Cutting Optimization Using Deep Q-Networks: A Reinforcement Learning Approach for Resource Efficiency by Chen Linxuan

“…The GNN model is embedded with Graph Convolutional Networks (GCN) layers, while the DRL model is structured with Deep Q-network (DQN). …”
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Palynofacies and Sporomorph EcoGroups-based paleoecology implications for the Dalichai Formation, Andariyeh, central Alborz by Firoozeh Hashemi Yazdi, Neda Bashiri, fereshteh sajjadi

“…In addition, The Sporomorph Ecogroup Model (SEG model) of Abbink et al. (2001, 2004a) was applied to the Dalichai Formation. …”
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3D Simulations Demonstrate Propagating Thermohaline Convection for Polluted White Dwarfs by Imogen G. Cresswell, Adrian E. Fraser, Evan B. Bauer, Evan H. Anders, Benjamin P. Brown

“…It has been argued that this instability cannot be treated as a continuous mixing process and thus should not be considered in these models. …”
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Mechanism Analysis of an Abrupt Torrential Rain Event under Weak Synoptic Forcing by Mingjuan LI, Damei GUO, Dian FENG, Kuifeng ZHAO, Jiahuimin LIU, Liwei QU

“…On July 18， 2021， abrupt rainstorms， torrential rain and local torrential rain occurred in areas of northeastern Xi'an and southern Weinan.The global numerical model and multiple Meso-scale numerical models failed to predict this torrential rain process.Based on data of aerological sounding， surface observation， ERA5 reanalysis， TBB data of FY-2G satellite， lidar wind vector data of Lintong station， radar data of Jinghe station， and microwave radiometer data， circulation patterns， environmental conditions and Meso-scale convective system evolution are investigated in this paper to enhance the understanding of mechanisms of this type of torrential rain and improve its predicting accuracy.Results show that the abrupt torrential rain process occurred under the forcing of a weak synoptic system， on the edge of the continental high at 500 hPa.There were no shear lines， warm advections and high-speed wind transporting water vapor at 700 hPa and 850 hPa， and neither cold front nor warm front on surface.Before the torrential rain process， on environmental fields， vertical wind shear was weak from 0 to 6 km on T-lnP chart， and 0 ℃-level was high， which was conducive to formation of deep warm clouds.A light rain appeared on surface， increasing atmospheric humidity near ground and lowering atmospheric lifting condensation level and lower cloud base， which was favorable for developing Meso-scale convective systems and improving precipitating efficiency.On radar wind profile map and wind lidar map， the low-level easterly wind was increased to 6~10 m·s-1， transferring abundant water vapor and energy to the rainstorm area， giving the atmosphere a certain amount of convective available potential energy（CAPE）.Satellite image， ERA5 reanalysis data and microwave radiometer data show a weak ascent was found in the middle and low levels which produced a deep wet layer and a large value of total atmospheric precipitable water.TBB data indicates that quasi-stationary isolated Meso-β-scale convective systems caused the abrupt torrential rain.On radar composite reflectivity factor map， the heavy rainfall was induced by a Meso-γ-scale and Meso-β-scale convective cell or a Meso-β-scale convective system.The Meso-γ-scale convective cell developed near Lishan Mountain with loose structure and organization.The maximum center of reflectivity factor demonstrates a consistently vertical structure from top to bottom with a low centroid， showing characteristics of highly efficient warm cloud precipitation.The abrupt torrential rain was caused by convections triggered by interaction of the ground convergence line induced by weak cold air on surface， topographic uplift of the Lishan Mountain and funneling effect of Bahe Valley collectively.The initial heavy rainfall formed a cold pool， then， the outflow of the cold pool generated new convergence lines around， triggering new convective systems.The Meso-β-scale convective system on the northeast side of the Jinghe River propagated backwards and moved slowly southwestwards.In the Meso-β-scale convective system， multiple new Meso-γ-scale convective cells developed and created a “train effect” over Jinghe River， resulting in this torrential rain process.For prediction under the forcing of weak synoptic systems， it is necessary to strengthen the understanding of its formation mechanism and the use of new observation data， pay close attention to the influence of early weak precipitation on near-surface humidification and lifting condensation level， water vapor and unstable energy transport to rainstorm areas by increased low-level wind， and the triggering effect of weak cold air on the ground and terrain， combined with maximum values predicted by a number of Meso-scale numerical models， comprehensively consider the possibility of abrupt torrential rain.…”
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Early diagenesis in anoxic sediments of the Gulf of Gdańsk (southern Baltic Sea): Implications for porewater chemistry and benthic flux of carbonate alkalinity by Katarzyna Łukawska-Matuszewska, Maciej Dwornik

“…According to recent modeling studies, anaerobic processes in sediments are an important internal source of alkalinity in the Baltic Sea. …”
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Progress in research on the effects of environmental factors on natural forest regeneration by Jiabo Liu

“…Light strongly influences processes such as photosynthetic efficiency, biomass allocation and photoinhibition in tree growth. …”
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Risk management of emergency situations caused by flooding of built‐up mountain areas by E. V. Arefyeva, I. Yu. Oltyan, Yu. I. Prus

“…In such territories, the watered soil preserves the cultural layer, which determines the need for flexible regulation of the groundwater regime. …”
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Multi-Variable Transformer-Based Meta-Learning for Few-Shot Fault Diagnosis of Large-Scale Systems by Weiyang Li, Yixin Nie, Fan Yang

“…To enable the Transformer model to simultaneously receive continuous and state inputs, we introduced feature layers before the encoder to better integrate the characteristics of both continuous and state variables. …”
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Multimodal data deep learning method for predicting symptomatic pneumonitis caused by lung cancer radiotherapy combined with immunotherapy by Mingyu Yang, Jianli Ma, Chengcheng Zhang, Liming Zhang, Jianyu Xu, Shilong Liu, Jian Li, Jiabin Han, Songliu Hu

“…This process was repeated five times, and the results from these iterations were aggregated to compute the average values of performance metrics, thereby assessing the overall performance and stability of the model.ResultsThe multimodal fusion model developed in this research, which incorporated depth image characteristics, radiomics properties, and clinical data, demonstrated an AUC of 0.922 (95% CI: 0.902-0.945, P value < 0.001). …”
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Marine organic aerosol at Mace Head: effects from phytoplankton and source region variability by E. Chevassus, K. N. Fossum, D. Ceburnis, L. Lei, C. Lin, C. Lin, W. Xu, W. Xu, C. O'Dowd, J. Ovadnevaite

“…Four OA factors were deconvolved by the source apportionment model. The analysis revealed primary marine organic aerosol (PMOA) as the predominant submicron OA at Mace Head during summertime, accounting for 42 % of the total resolved mass. …”
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Physical-Abstract Bidirectional-Guided Learning for High-Resolution Radar Target Recognition by Yuying Zhu, Yinan Zhao, Zhaoting Liu, Meilin He

“…The core innovation lies in modeling this process as a bidirectional integration, enabling simultaneous parameter estimations of scattering center based physical models and mapping abstract representation to local scattering structures of targets. …”
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Improving vertical detail in simulated temperature and humidity data using machine learning by Joana D. da Silva Rodrigues, Cyril J. Morcrette

“…There are however atmospheric phenomena that occur on scales smaller than the thickness of those model layers. The formation of low‐level clouds due to temperature inversions is an example. …”
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Random Finite Element Analysis and Random Factor response Mechanism for Geocell-reinforced Soil Retaining Walls by ZHANG Bingbing, SONG Fei

“…Finally, the global sensitivity analysis method was adopted, focusing on revealing the influence laws of key parameters (<italic>K</italic>, <italic>n</italic>, <italic>φ</italic>₀ and <italic>P</italic>_Mt), their coefficients of variation and spatial fluctuation ranges on the deformation characteristics of the retaining wall, and quantitatively analyzing the mapping relationship between each parameter and the deformation response of the structure.Results and Discussions　Through the in-depth analysis of the random field parameters of foundation soil, backfill soil and geocell-reinforced retaining wall, it is revealed that the soil parameters have significant layering characteristics and the trend of change with depth, which is highly consistent with the layering distribution characteristics of the soil in the actual project, and verifies the reliability of the constructed random field model. …”
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Conceptualizing mental health stigma in organizational settings: a sociolinguistic perspective by Jasper Zhao Zhen Wu, Olga Zayts-Spence, Zoë Fortune

“…Specifically, the model maps the complex discursive processes of mental health stigmatization through workplace discursive practices. …”
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