Miracle-dz/UniFAR-FTUs huggingface dataset:
Ajuste de equações alométricas para Araucaria angustifolia (Bert.) O. Ktze. utilizando análise de componentes principais conjuntamente com análise de regressão

The main objective of the present research was to select variables for fitting alometric equations in order to estimate stem fresh weight (sfw), needles fresh weight (nfw) and branches fresh weight (BFW), through Principal Components Analysis, for native and planted Araucaria angustifolia trees, in the southern regions of Parana State, Brazil. Data from 15 trees of several ages (29 to 33 years) being evaluated the following variables: dbh (diameter at breast height), h (total height) hc (commercial height), sfw, nfw and bfw. As independent variables (x) they were used dbh, dbh2, log(dbh), ht, dbh2ht, log(h), hc, dbh2hc and log(hc) and as dependent variables sfw, nfw, bfw. Once data were computed for all variable combinations, a correlation matrix was generated by Excel 2000 and Principal Components Analysis was made by Statgraphics 5.0. The study leaded to the conclusion that the use of Principal Components Analysis together with Regression Analysis showed a great potential for fitting alometric equations for Araucaria angustifolia, as well as for other wood species. A greater number of tree measurements for biomass variables is advisable, to improve the fitting of biomass equations for Araucaria angustifolia
Fundamentals of environmental engineering

The field of environmental engineering is rapidly emerging into a mainstream engineering discipline. For a long time, environmental engineering has suffered from the lack of a well-defined identity. At times, the problems faced by environmental engineers require knowledge in many engineering fields, including chemical, civil, sanitary, and mechanical engineering. Increased demand for undergraduate training in environmental engineering has led to growth in the number of undergraduate programs offered. Fundamentals of Environmental Engineering provides an introductory approach that focuses on the basics of this growing field. This informative reference provides an introduction to environmental pollutants, basic engineering principles, dimensional analysis, physical chemistry, mass, and energy and component balances. It also explains the applications of these ideas to the understanding of key problems in air, water, and soil pollution.
An evaluation of high-resolution multisatellite rainfall products over the Indian monsoon region

To date, more than half a dozen merged rainfall data sets are available to the research community. These data sets use different approaches for rainfall retrieval and combine different satellites or/and ground-based rainfall observations. However, these data sets appear to differ among themselves and deviate from in situ observations at regional and seasonal scales. Hence, it is becoming difficult to choose a suitable data set from these products for regional rainfall analyses. In the present study, four independently developed multisatellite high-resolution precipitation products (HRPPs), namely Climate Prediction Center Morphing (CMORPH) version 1.0, Naval Research Laboratory (NRL)–blended, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA)–3B42 version 7 are compared with quality-controlled gridded rain gauge data over India developed by the India Meteorological Department (IMD). A preliminary analysis is carried out for a 6 year period from 2004 to 2009 at daily scale for the summer monsoon season of June to September. Comparison of all-India seasonal (June to September) mean rainfall with rain gauge data shows a considerable underestimation by all HRPPs, although the underestimation is comparatively less for TMPA. Moreover, all the HRPPs are able to capture the important characteristic features of the summer monsoon rainfall such as intra-seasonal (active/break spells) and inter-annual (excess/deficient) variabilities reasonably well. Regional differences between observed rainfall and the HRPPs are also analysed. Results suggest that TMPA is comparatively closer to the ground-truth, possibly due to the incorporation of rain gauge observations. Furthermore, all the HRPPs show high probability of detection, low false alarm ratio, and high threat score in detection of rainfall events over most parts of India. It is also observed that all these HRPPs have certain issues in rainfall detection over the rain-shadow region of southeast peninsular India, semi-arid northwest parts of India, and hilly northern parts. Hence, results of the 6 year analysis over a region with a dense network of surface observations of rainfall suggest that the TMPA merged rainfall product is better than the other HRPPs due to (1) lower underestimation of rainfall, (2) higher correlation and lower root-mean-square error (RMSE), and (3) better performance over the west coast. Therefore, TMPA can be used with confidence as compared to other HRPPs for monsoon studies, particularly over the Indian land region with a considerable rain gauge network. This study also clarifies the fact that the merged satellite rainfall products with sufficient ground-truths can be the ideal product for monsoon and hydrological studies.
Ultra-thin transition metal di-chalcogenides (TMDCs) as radiation-resistant photovoltaic materials for space

Transition metal di-chalcogenides (TMDCs) have strong potential for ultra -thin electronic and photonic applications because of their range of electronic and optical properties, 2D layered structure, and tunability of properties by dopants and hybrid alloys. TMDCs have high atomic masses compared to commonly used semiconductors, which makes them resistant to damage by high energy particles in space. We have studied the fundamental electronic and optical properties of various tungsten-based TMDCs by Density Functional Theory (DFT) calculations. We then developed a solar cell model composed of heavier TMDCs with photon management features to design high-performing photovoltaic devices which are ultra-thin, lightweight, with significantly enhanced resistance to radiation-induced damage. Here, we model electro-optic properties and photovoltaic performance of various combinations of tungsten-based TMDCs containing sulfur, selenium and tellurium. Device simulations conducted using the AM0 space solar spectrum yield high efficiencies above 17% for the tungsten-based devices. The non-ionizing energy loss (NIEL) due to high energy protons for tungsten-based TMDCs are much lower than common photovoltaic semiconductors, such as silicon, resulting in significantly reduced displacement damage doses (DDD) from space radiation. Our results show that TMDCs have great potential for implementation in radiation-resistant electronic and photonic technologies in the space environment.
Efficient 3D Object Detection Based on Pseudo-LiDAR Representation

3D object detection is a critical task in the field of robotics and autonomous driving. Although recent light detection and ranging (LiDAR)-based 3D object detection techniques have been well-studied and achieve high detection accuracy, the cost of the LiDAR sensor itself proposes a high premium for its practical implementation. Recently introduced Pseudo-LiDAR based methods that utilize image data to detect 3D information show great prospects for their high cost-effectiveness. However, existing Pseudo-LiDAR methods tend to be intensive computations for the adaption of complex stereo matching algorithms, and therefore can not meet the real-time requirement. To tackle this issue, we propose a lightweight Pseudo-LiDAR 3D detection system that achieves both high accuracy and high responsiveness. Specifically, we adopt a highly efficient depth estimator with Binary Neural Networks (BNNs) to exploit timely depth prediction. To mitigate the accuracy degradation issue caused by the quantization of the BNNs, we introduce several promoting schemes into the depth estimation procedure, including continuous depth approximation, geometric constraints of virtual planes, and training scope restriction, to enhance its performance. Moreover, we further provide an in-depth analysis to the architecture of 3D detector orienting to the Pseudo-LiDAR task and develop effective modules to gain solid accuracy improvement while maintaining low runtime demand. Experiments on the KITTI benchmark and online leaderboard show that our system can conduct the 3D detection within a mere 36 ms, while simultaneously achieving competitive results when compared to the state-of-the-art algorithms.
Infrared spectroscopy analysis determining secondary structure change in albumin by cerium oxide nanoparticles

Cerium oxide (CeO2) nanoparticles are expected to have applications in the biomedical field because of their antioxidative properties. Inorganic nanoparticles interact with proteins at the nanoparticle surface and change their conformation when administered; however, the principle underlying this interaction is still unclear. This study aimed to investigate the secondary structural changes occurring in bovine serum albumin (BSA) mixed with CeO2 nanoparticles having different surface modifications using Fourier transform infrared spectroscopy. CeO2 nanoparticles (diameter: 240 nm) were synthesized from an aqueous cerium (III) nitrate solution using a homogeneous precipitation method. The surfaces of the nanoparticles were modified by the catechol compounds dopamine and 3,4-dihydroxyhydrocinnamic acid (DHCA). In the presence of these CeO2 nanoparticles (0.11–0.43 mg/mL), β-sheet formation of BSA (30 mg/mL) was promoted especially on the amine-modified (positively charged) nanoparticles. The local concentration of BSA on the surface of the positively charged nanoparticles may have resulted in structural changes due to electrostatic and other interactions with BSA. Further investigations of the interaction mechanism between nanoparticles and proteins are expected to lead to the safe biomedical applications of inorganic nanoparticles.
A review of few-shot network traffic classification based on deep learning

At present, deep learning has achieved excellent performance in the field of network traffic classification. However, deep learning relies on massive data-driven classification models. When the data set is small, it is usually hindered. In order to solve this problem, few-shot network traffic classification technology based on deep learning has been gradually studied. In this paper, we conducted a comprehensive survey to fully understand the few-shot traffic classification techniques. We first define the few-shot traffic classification problem. Based on how to solve the contradiction between the few-shot data set and the large number of parameters to be trained in the model, we classify the current few-shot traffic classification method based on deep learning from two perspectives: (1) Data augmentation method, which uses the method of expanding the data set to enhance the supervision experience. In this paper, the methods based on data enhancement are divided into two categories based on GAN and feature transformation. (2) Model-based methods. Model-based methods are divided into three categories: transfer learning, metric learning and meta-learning. And discuss the advantages and disadvantages of each classification method. Finally, the results are summarized and the future development direction of few-shot network traffic classification technology based on deep learning is prospected.
3D Numerical Investigation of Distorted Scale in Hydraulic Physical Model Experiments

Abstract In some physical model experiments, it is necessary to use distorted models. It is difficult, however, to build in an optimal degree of distortion into the models to ensure a closer degree of similarity between the model and the prototype. Three-dimensional (3D) numerical simulation is used in this paper to model experiments with a straight channel under different distorted scales. The calculated results of stream-wise, lateral and vertical velocities and sediment concentration along the vertical direction are shown by comparing the deviations of the velocities and sediment concentration between the distorted model and a normal one. Generally the discrepancy between the distorted model and the normal in stream-wise velocity is acceptable, while in vertical and transverse directions, the velocity shows differences. Concerning sediment concentration and channel bed deformation, the effect of the distorted scale is mainly related to two different similarity criteria. The similarity ratio between the turbulence diffusion velocity and gravity settling velocity can reproduce better results of sediment concentration along the vertical direction. The better bed deformation results come, however, from the similarity ratio between the averaged flow velocity and gravity settling velocity.
The Influence of TiO2 Nanoparticles Morphologies on the Performance of Lithium-Ion Batteries

Anode materials based on the TiO2 nanoparticles of different morphologies were prepared using the hydrothermal method and characterized by various techniques, such as X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and N2 absorption. The TiO2 nanoparticles prepared were used as anode materials for lithium-ion batteries (LIBs), and their electrochemical properties were tested using discharging/charging measurements. The results showed that the initial morphology of the nanoparticles plays a minor role in battery performance after the first few cycles and that better capacity was achieved for TiO2 nanobelt morphology. The sharp drop in the specific capacity of LIB during their first cycles is examined by considering changes in the morphology of TiO2 particles and their porosity properties in terms of size and connectivity. The performance of TiO2 anode materials has also been assessed by considering their phase.
Ophiolites as faithful records of the oxygen isotope ratio of ancient seawater: the Solund-Stavfjord Ophiolite Complex as a Late Ordovician example

Abstract Fragments of the Ordovician sea floor preserved in the Solund-Stavfjord Ophiolite Complex in Western Norway serve as proxies for the δ18O of Ordovician seawater. The pillow basalt sections at Oldra and Strand are both enriched in 18O, recording their alteration by seawater at low temperature on the sea floor. In contrast, the sheeted dykes and gabbros generally are depleted of 18O, reflecting the modal proportion of secondary, low-18O chlorite and epidote formed from seawater at high temperature. These isotopic contrasts simply reflect the high water to rock ratio of sea-floor alteration and the temperature dependence of the 18O partitioning between minerals and water. Superposition of high-δ18O pillows on low-δ18O dykes and gabbros is a necessary consequence of alteration at both low and high temperatures by a fluid near 0‰ and is easily recognized in well-preserved ophiolites. Also, the δ18O of seawater can be independently calculated from 18O fractionations among secondary minerals. Older, dismembered and highly metamorphosed segments of the oceanic crust may still retain the original seawater imprint because their subsequent obduction and metamorphism was relatively closed to external fluids. Suites of diamond-bearing nodules from kimberlites still have contrasting high- and low-δ18O eclogites, proving that even subduction into the mantle is not sufficient to erase the seawater fingerprint. Inspection of the sea-floor, ophiolite and eclogite data reveals no secular trend in δ18O, indicating that the δ18O of seawater has not changed with geological age. Because the δ18O of seawater itself is fixed by sea-floor-seawater exchange, the constancy of δ18O of seawater implies that the scale and style of sea-floor-seawater interactions has not changed over time.
Capabilities and limitations of detailed hillslope hydrological modelling

Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated–saturated soil moisture flow, macropore flow), problems of small-scale variability, a general scarcity of detailed soil data, incomplete process parametrization and problems with the interdependent linkage of several hillslopes and channel–hillslope interactions. Copyright © 1999 John Wiley & Sons, Ltd.
Computational Approaches to Toll-Like Receptor 4 Modulation

Toll-like receptor 4 (TLR4), along with its accessory protein myeloid differentiation factor 2 (MD-2), builds a heterodimeric complex that specifically recognizes lipopolysaccharides (LPS), which are present on the cell wall of Gram-negative bacteria, activating the innate immune response. Some TLR4 modulators are undergoing preclinical and clinical evaluation for the treatment of sepsis, inflammatory diseases, cancer and rheumatoid arthritis. Since the relatively recent elucidation of the X-ray crystallographic structure of the extracellular domain of TLR4, research around this fascinating receptor has risen to a new level, and thus, new perspectives have been opened. In particular, diverse computational techniques have been applied to decipher some of the basis at the atomic level regarding the mechanism of functioning and the ligand recognition processes involving the TLR4/MD-2 system at the atomic level. This review summarizes the reported molecular modeling and computational studies that have recently provided insights into the mechanism regulating the activation/inactivation of the TLR4/MD-2 system receptor and the key interactions modulating the molecular recognition process by agonist and antagonist ligands. These studies have contributed to the design and the discovery of novel small molecules with promising activity as TLR4 modulators.
Habitat suitability index models: field sparrow

Abstract : Habitat preferences of the field sparrow (Spizella pusilla) are described in this report, which is one of a series of Habitat Suitability Index (HSI) models. A review and synthesis of the literature is followed by the development of a habitat model for the field sparrow throughout its breeding range in the United States. HSI models are designed to be used in conjunction with Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service.
Study on Community Detection Method for Morning and Evening Peak Shared Bicycle Trips in Urban Areas: A Case Study of Six Districts in Beijing

Examining the clustering characteristics and fluctuations within urban areas during peak hours through the lens of bike-sharing is of utmost importance in the optimization of bike-sharing systems and urban transportation planning. This investigation adopts the principles of urban spatial interaction network construction and employs streets as the fundamental units of analysis to model bike-sharing activities during morning and evening peak hours within Beijing’s six central districts. Subsequent to this, a comprehensive analysis of the network’s structural attributes was carried out. A Walktrap method, rooted in modularity analysis, was introduced to discern and scrutinize the clustering patterns and characteristics of communities within the network across different temporal intervals. Empirical findings reveal a predominant usage pattern of shared bicycles for short-distance travel during both morning and evening peak hours. Notably, distinctive community structures manifest during these periods, characterized by two large communities and multiple smaller ones during the morning peak, while the evening peak showcases a single large community alongside several medium-sized and smaller ones. Moreover, the extended interaction radius points to an expanded geographic range of interactions among streets. These findings bear significant implications for the management of urban transportation, bike-sharing enterprises, and urban residents, proffering valuable insights for the optimization of bike-sharing schemes and transportation strategies. These research findings not only contribute to enhancing urban transportation planning and bike-sharing systems but also provide robust guidance for advancing more efficient and sustainable urban transportation solutions, thereby fostering the sustainable development of cities.
Crustal extension along a rooted system of imbricate low-angle faults: Colorado River extensional corridor, California and Arizona

Summary The upper 10 to 15 km of crystalline crust in the 100-km-wide Colorado River extensional corridor of mid-Tertiary age underwent extension along an imbricate system of gently dipping normal faults. Detachment faults cut gently down-section eastward in the direction of tectonic transport from a headwall breakaway, best expressed in the Old Woman Mountains, California. Successively higher and more distal allochthons are displaced farther from the headwall, some as much as tens of kilometres. The basal fault(s) cut initially to depths of 10 to 15 km, the palaeothickness of a tilted allochthonous slab of basement rocks above the Chemehuevi-Whipple Mountains detachment fault(s). Hanging wall blocks tilt consistently toward the headwall as shown by dips of capping Tertiary strata and of originally horizontal Proterozoic diabase dykes. Block tilts and the degree of extension increase northeastward across much of the corridor. The faults are interpreted as rooting under the unbroken Hualapai Mountains and Colorado Plateau on the down-dip side of the corridor in Arizona. Slip on faults at all exposed levels of the crust was unidirectional, and totals an estimated 50 km. These data and inferences support the concept that the crust in California moved out from under Arizona along a rooted, normal-slip shear system. Brittle thinning above the sole faults affected the entire upper crust, and in places wholly removed it along the central part of the corridor. Upwarp exposed metamorphic core complexes in footwall domes.