Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamics on potential energy surfaces with a conical intersection: Adiabatic, intermediate, and diabatic behavior

The nuclear dynamics on potential energy surfaces which are strongly vibronically coupled through a conical intersection is investigated by exact (numerical) integration of the time‐dependent Schrodinger equation. Results for realistic model systems including three nuclear degrees of freedom are presented: C2H+4, pyrazine and NO2. It was found previously for C2H+4 that the wave packet moves after an initial decay mainly on the lower adiabatic surface. This observation could be confirmed also for pyrazine and NO2. By varying the coupling strength λ also other types of behavior could be identified. A transition from adiabatic via intermediate to a diabatic nature of the system dynamics is found upon decreasing λ. Population of diabatic and adiabatic states in the long time limit are calculated by classical phase‐space statistics. Analytic relations between the population of the diabatic states and the dynamical observables, coordinates and momenta, are derived. They allow for a deeper understanding of their.
Synergy between Satellite Altimetry and Optical Water Quality Data towards Improved Estimation of Lakes Ecological Status

European countries are obligated to monitor and estimate ecological status of lakes under European Union Water Framework Directive (2000/60/EC) for sustainable lakes’ ecosystems in the future. In large and shallow lakes, physical, chemical, and biological water quality parameters are influenced by the high natural variability of water level, exceeding anthropogenic variability, and causing large uncertainty to the assessment of ecological status. Correction of metric values used for the assessment of ecological status for the effect of natural water level fluctuation reduces the signal-to-noise ratio in data and decreases the uncertainty of the status estimate. Here we have explored the potential to create synergy between optical and altimetry data for more accurate estimation of ecological status class of lakes. We have combined data from Sentinel-3 Synthetic Aperture Radar Altimeter and Cryosat-2 SAR Interferometric Radar Altimeter to derive water level estimations in order to apply corrections for chlorophyll a, phytoplankton biomass, and Secchi disc depth estimations from Sentinel-3 Ocean and Land Color Instrument data. Long-term in situ data was used to develop the methodology for the correction of water quality data for the effects of water level applicable on the satellite data. The study shows suitability and potential to combine optical and altimetry data to support in situ measurements and thereby support lake monitoring and management. Combination of two different types of satellite data from the continuous Copernicus program will advance the monitoring of lakes and improves the estimation of ecological status under European Union Water Framework Directive.
Multi-Scale Attentive Aggregation for LiDAR Point Cloud Segmentation

Semantic segmentation of LiDAR point clouds has implications in self-driving, robots, and augmented reality, among others. In this paper, we propose a Multi-Scale Attentive Aggregation Network (MSAAN) to achieve the global consistency of point cloud feature representation and super segmentation performance. First, upon a baseline encoder-decoder architecture for point cloud segmentation, namely, RandLA-Net, an attentive skip connection was proposed to replace the commonly used concatenation to balance the encoder and decoder features of the same scales. Second, a channel attentive enhancement module was introduced to the local attention enhancement module to boost the local feature discriminability and aggregate the local channel structure information. Third, we developed a multi-scale feature aggregation method to capture the global structure of a point cloud from both the encoder and the decoder. The experimental results reported that our MSAAN significantly outperformed state-of-the-art methods, i.e., at least 15.3% mIoU improvement for scene-2 of CSPC dataset, 5.2% for scene-5 of CSPC dataset, and 6.6% for Toronto3D dataset.
Density and relative permittivity of (pyridine + 2-methoxyethanol, 2-ethoxyethanol, 2-propoxyethanol, and 2-butoxyethanol) binary mixtures at 298.15 K

The densities and relative permittivities of binary mixtures of pyridine with 2-methoxyethanol, 2-ethoxyethanol, 2-propoxyethanol and 2-butoxyethanol have been measured as a function of composition, at T = 298.15 K. From the experimental data the excess molar volume (VE) and the deviation in the relative permittivity (Δε) from a mole fraction average have been calculated. The results are discussed in terms of intermolecular interactions and structure of studied binary mixtures.
Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil

The lack of measurement of precipitation in large areas using fine-resolution data is a limitation in water management, particularly in developing countries. However, Version 6 of the Integrated Multi-satellitE Retrievals for GPM (IMERG) has provided a new source of precipitation information with high spatial and temporal resolution. In this study, the performance of the GPM products (Final run) in the state of Paraná, located in the southern region of Brazil, from June 2000 to December 2018 was evaluated. The daily and monthly products of IMERG were compared to the gauge data spatially distributed across the study area. Quantitative and qualitative metrics were used to analyze the performance of IMERG products to detect precipitation events and anomalies. In general, the products performed positively in the estimation of monthly rainfall events, both in volume and spatial distribution, and demonstrated limited performance for daily events and anomalies, mainly in mountainous regions (coast and southwest). This may be related to the orographic rainfall in these regions, associating the intensity of the rain, and the topography. IMERG products can be considered as a source of precipitation data, especially on a monthly scale. Product calibrations are suggested for use on a daily scale and for time-series analysis.
Tuning chirality in the self-assembly of rod-like viruses by chemical surface modifications

Filamentous viruses of similar molecular and subunitary structure can form either a liquid crystalline nematic phase or a chiral nematic – also called cholesteric – phase, which is an elegant example of how self-organization of nanorods, with otherwise similar properties, can be affected by only subtle differences of surface properties and of the arrangement of the constituent subunits. In this work, we studied the influence of viral surface properties on the self-assembly of rod-like fd virus suspensions into the chiral nematic phase. For this purpose, the filamentous fd virus has been subjected to various chemical modifications on its capsid proteins: several organic molecules of different sizes and structures, including two popular fluorescent dyes (fluorescein and rhodamine), were coupled to the surface amino groups of the virus. The resulting chemically modified viruses still form a cholesteric phase in an aqueous suspension, but with a lower helicity compared to suspensions made of wild-type fd viruses. The degree of unwinding of the helical periodicity (or cholesteric pitch) depends on the structure of the labeled molecules. In addition, the chemically modified viruses exhibit a well-defined first order phase transition between the isotropic liquid and the liquid-crystalline state. Besides these modifications targeting the amino groups, the surface carboxyl groups were coupled with amino compounds so that the surface charge of fd viruses was reversed from negative to positive. The resulting particles can only form a nematic phase without any macroscopic helicity. These results suggest that inter-particle interactions, together with the intrinsic chirality of the virus, play an important role in the origin of the helical twist in the cholesteric phase.
Red neuronal convolucional de baja latencia para la estimación de profundidad monocular

Resumen. La estimación de profundidad monocular se ha convertido recientemente en una de las técnicas emergentes y de creciente interés para la obtención de la estructura espacial de una escena. En gran parte, los recientes avances en el área de aprendizaje profundo han permitido obtener resultados prometedores en esta línea de investigación. No obstante, los métodos del estado del arte se caracterizan por utilizar redes neuronales convolucionales muy complejas cuya etapa de inferencia no puede llevarse a cabo en tiempo real en sistemas con recursos computacionales limitados. Desde esta perspectiva, pocos trabajos se han propuesto para la estimación de profundidad monocular mediante arquitecturas de baja latencia. En el presente trabajo, se propone una arquitectura de red neuronal convolucional basada en el extractor de características ShuffleNet V2. Los resultados obtenidos en el conjunto de datos NYU Depth V2 muestran que la arquitectura propuesta es capaz de reducir el tiempo de inferencia en un 37.5% con respecto a métodos relacionados del estado del arte.
Influence of variety, maturity, processing, and storage on the phenolic composition of pear juice

HPLC separation with diode array detection was used to examine the influence of processing and storage on the phenolic composition of pear juice. As it is common commercial practice to process pear juice from both hard green and soft fruit, the influence of maturity was included. The effect of SO 2 addition was studied because of its effectiveness as an inhibitor of PPO and possible improvement in product quality. Comparison of total phenolics determinations by HPLC and colorimetric assay was also done
Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification

Robust and reliable classification of sea ice types in synthetic aperture radar (SAR) images is needed for various operational and environmental applications. Previous studies have investigated the class-dependent decrease in SAR backscatter intensity with incident angle (IA); others have shown the potential of textural information to improve automated image classification. In this work, we investigate the inclusion of Sentinel-1 (S1) texture features into a Bayesian classifier that accounts for linear per-class variation of its features with IA. We use the S1 extra-wide swath (EW) product in ground-range detected format at medium resolution (GRDM), and we compute seven grey level co-occurrence matrix (GLCM) texture features from the HH and the HV backscatter intensity in the linear and logarithmic domain. While GLCM texture features obtained in the linear domain vary significantly with IA, the features computed from the logarithmic intensity do not depend on IA or reveal only a weak, approximately linear dependency. They can therefore be directly included in the IA-sensitive classifier that assumes a linear variation. The different number of looks in the first sub-swath (EW1) of the product causes a distinct offset in texture at the sub-swath boundary between EW1 and the second sub-swath (EW2). This offset must be considered when using texture in classification; we demonstrate a manual correction for the example of GLCM contrast. Based on the Jeffries–Matusita distance between class histograms, we perform a separability analysis for 57 different GLCM parameter settings. We select a suitable combination of features for the ice classes in our data set and classify several test images using a combination of intensity and texture features. We compare the results to a classifier using only intensity. Particular improvements are achieved for the generalized separation of ice and water, as well as the classification of young ice and multi-year ice.
UMA ABORDAGEM DA EXTENSÃO UNIVERSITÁRIA NA MELHORIA DA QUALIDADE DO LEITE NA CADEIA PRODUTIVA DO MUNICÍPIO DE BARBOSA FERRAZ (PARANÁ)

Este trabalho teve como principais objetivos difundir praticas de higiene e avaliar a sua eficacia na reducao da contaminacao microbiologica do leite. Efetuou-se mapeamento da linha de processamento do leite pasteurizado para identificar os principais pontos de contaminacao e elimina-los com a adocao de Boas Praticas de Fabricacao. Realizou-se levantamento de dados nas propriedades produtoras de leite e no estabelecimento processador, mediante listas de verificacao. Ministrou-se treinamento nas propriedades rurais com enfase nas Boas Praticas de Producao, seguido da coleta de amostras de leite cru e de esfregaco da superficie das maos dos ordenhadores e dos latoes para determinacoes microbiologicas, antes e apos a implantacao de praticas de higiene. No estabelecimento processador foram coletadas 5 amostras de leite em diferentes pontos da linha de processamento e 1 pacote de leite pasteurizado tipo C. Os resultados mostraram que dos 9 itens relacionados a higiene diagnosticados nas 17 propriedades rurais, 5 (55%) apresentaram nao conformidade com as normas. As amostras coletadas apos a implantacao das praticas de higiene apresentaram reducao da elevada carga microbiana verificada anteriormente. Dos 142 itens avaliados pela lista de verificacao aplicada no estabelecimento processador, 38% apresentaram conformidade. A provavel origem da contaminacao localizou-se apos a saida do tanque isotermico. Comprovou-se a eficacia da adocao das Boas Praticas de Producao na reducao da contaminacao microbiologica do leite cru, bem como a necessidade de adequacao do estabelecimento processador as normas de Boas Praticas de Fabricacao.
Distance learning during the early stages of the COVID-19 pandemic: Examining K-12 students' and parents' experiences and perspectives

This study examines K-12 students and parents in the United States' experiences and challenges during the sudden shift to distance learning during the spring of 2020 The study also aims to analyze what can be done to better educate students in the case of continued distance learning during the COVID-19 crisis and during future emergencies The study was conducted with an online survey of K-12 students and parents in the United States, and both qualitative and quantitative data was collected However, the results should be interpreted with caution, as it was a smaller study that is not a representative sample of the population The study results show that a variety of strategies were utilized to teach students online, and that from the perspective of the participants both successful and unsuccessful methods were utilized
A Mechanistic Approach for Modeling Soil Development Using Remotely Sensed Data Collected from Invaded Coasts

The invasion of the exotic species Spartina alterniflora (S. alterniflora) has profoundly influenced coastal soil development in China. Accurate assessment and monitoring of invasion-driven development in coastal soils requires the development of reliable methods to support the sustainable governance of coastal ecosystems. A space-for-time substitution method and a stratified random sampling strategy were utilized in this study to obtain soil data from 15 sites at three depth intervals (0–30, 30–60 and 60–100 cm) to obtain a total of 45 soil samples. We developed a mechanistic approach to model soil development using Sentinel-1 data. Here, soil development was represented by a comprehensive soil index, the soil quality index (SQI), which was calculated from key physical and chemical soil properties. In the structural equation model (SEM), soil, vegetation and remote-sensing data were initially assumed to be related to each other based on prior knowledge and were constructed from their corresponding observed variables. The results of the correlation analysis showed that there was a significant correlation between the invasion processes and SQI values, especially in the topsoil of the upper 30 cm. The final SEM model showed that the invasion process had great direct and positive effects on SQI in the upper 60 cm depth soil; however, vegetation (represented by a vegetation index) had a negative influence on SQI in the topmost layer. We found that Sentinel-1 data explained the large variation in the interacting ecosystem of the invasion, vegetation, and soils, with R2 values ranging between 0.45 and 0.96. The results of model performance evaluation demonstrated the efficacy of the proposed model in predicting SQI, with a ratio of performance to deviation (RPD) of 1.44 in the upper 60 cm. Our findings highlight the potential of Sentinel-1 data in monitoring the pace of soil development in constructed S. alterniflora marshes.
A Response of Snow Cover to the Climate in the Northwest Himalaya (NWH) Using Satellite Products

The Himalayan region is one of the most crucial mountain systems across the globe, which has significant importance in terms of the largest depository of snow and glaciers for fresh water supply, river runoff, hydropower, rich biodiversity, climate, and many more socioeconomic developments. This region directly or indirectly affects millions of lives and their livelihoods but has been considered one of the most climatically sensitive parts of the world. This study investigates the spatiotemporal variation in maximum extent of snow cover area (SCA) and its response to temperature, precipitation, and elevation over the northwest Himalaya (NWH) during 2000–2019. The analysis uses Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra 8-day composite snow Cover product (MOD10A2), MODIS/Terra/V6 daily land surface temperature product (MOD11A1), Climate Hazards Infrared Precipitation with Station data (CHIRPS) precipitation product, and Shuttle Radar Topography Mission (SRTM) DEM product for the investigation. Modified Mann-Kendall (mMK) test and Spearman’s correlation methods were employed to examine the trends and the interrelationships between SCA and climatic parameters. Results indicate a significant increasing trend in annual mean SCA (663.88 km2/year) between 2000 and 2019. The seasonal and monthly analyses were also carried out for the study region. The Zone-wise analysis showed that the lower Himalaya (184.5 km2/year) and the middle Himalaya (232.1 km2/year) revealed significant increasing mean annual SCA trends. In contrast, the upper Himalaya showed no trend during the study period over the NWH region. Statistically significant negative correlation (−0.81) was observed between annual SCA and temperature, whereas a nonsignificant positive correlation (0.47) existed between annual SCA and precipitation in the past 20 years. It was also noticed that the SCA variability over the past 20 years has mainly been driven by temperature, whereas the influence of precipitation has been limited. A decline in average annual temperature (−0.039 °C/year) and a rise in precipitation (24.56 mm/year) was detected over the region. The results indicate that climate plays a vital role in controlling the SCA over the NWH region. The maximum and minimum snow cover frequency (SCF) was observed during the winter (74.42%) and monsoon (46.01%) season, respectively, while the average SCF was recorded to be 59.11% during the study period. Of the SCA, 54.81% had a SCF above 60% and could be considered as the perennial snow. The elevation-based analysis showed that 84% of the upper Himalaya (UH) experienced perennial snow, while the seasonal snow mostly dominated over the lower Himalaya (LH) and the middle Himalaya (MH).
Effect of Incorporation of Mint on Texture, Colour and Sensory Parameters of Biscuits

In recent years, there has been a general trend towards replacing the use of synthetic antioxidant by natural antioxidant, derived from various plants, spices and oil seeds, in processed food. The present study deals in the use of mint (Mentha spicta L) as a source of natural antioxidant in different forms viz, powder, extract, and pure menthol for its application in biscuits. Formulation of mint component was designed based on preliminary studies using various parameters such as instrumental assessment for texture and color measurement and sensory evaluation. The selected levels were as follows 1% mint powder (MNT-P), 500 mg mint extract (MNT-E), and 100 ppm pure menthol (MNT-M) for incorporation in biscuits. The biscuits with different mint forms were packed in unit pouches of metallized polyester/poly laminate and stored at room temperature for five months. The texture value of biscuits with mint powder (MNT-P) received higher scores, comparable with the control (CNT) and BHA (BNT) biscuit indicating their crisp nature. However, color measurement (ΔE) values in MNT-P biscuits were higher followed by MNT-E biscuit due to their green color, whereas the values of MNT-M biscuit were comparable with the CNT and BHA biscuit indicating MNT-M did not impart any change in the color of the biscuit. The sensory scores of MNT-M were higher (P ≤ 0.05) than MNT‐P and MNT-E biscuits. MNT-P variation received significantly higher (P ≤ 0.05) scores in terms of texture, taste and mouth feel. The results indicate that MNT-P biscuits were highly acceptable compared to MNT-E and MNT-M biscuits.
Synthesis and electrochemistry of monoclinic Li(MnxFe1−x)BO3: a combined experimental and computational study

The lithium-ion battery is the most advanced energy storage system that has conquered the portable electronics market, but it has been considered unsuitable for large-scale applications such as plug-in hybrid vehicles due to cost, safety, and calendar life issues. Research in materials science is approaching a possible solution to these problems by the combination of abundant Fe as a redox center and covalent (PO4)3−oxyanion units with fixed oxygen, leading to the use of LiFePO4 with olivine-type structure as a cathode material. A high level of stability, safety, significant cost reduction, and huge power generation are now on the verge of being guaranteed. Replacing the (PO4)3− anion to smaller and lighter (BO3)3−, namely LiMBO3 (M = transition metal) compounds, could possibly increase the theoretical capacity by approximately >1.3 times; however, such systems have not been thoroughly investigated to date. Here we present the successful solid state synthesis of a complete solid solution of Li(MnxFe1−x)BO3 with monoclinic structure and the optimization processes to maximize its performance as a lithium battery cathode. Details of the intrinsic electrode properties, including the phase stability issues as well as degradation mode, are demonstrated, followed by systematic investigation of the reaction mechanisms by ex situX-ray diffraction, Mossbauer spectroscopy, X-ray absorption spectroscopy, and ab initio calculations.