Miracle-dz/UniFAR-FTUs huggingface dataset:
Nutrient Budget and Biogeochemical Dynamics in Sansha Bay, China: A Coastal Bay Affected by Intensive Mariculture

This study examines the spatiotemporal distribution of dissolved and particulate nutrients in Sansha Bay, a coastal bay characterized by complex hydrodynamics (monsoon‐driven river inputs and alongshore coastal waters), and intensive mariculture. However, nutrient stoichiometry and underlying biological responses in this ecosystem remain unclear. High nutrient (39.6–87.5 μmol L−1 dissolved inorganic nitrogen (DIN), 1.79–3.77 μmol L−1 dissolved inorganic phosphorus (DIP)) in winter suggested entrainment of the nutrient‐enriched China Coastal Current superimposed with mariculture inputs; lower nutrient concentrations (9.6–47.1 μmol L−1 DIN, 0.31–1.57 μmol L−1 DIP) in summer, and high Chlorophyll a (0.8–17.0 mg m−3) and dissolved oxygen (4.48–8.78 mg L−1), were driven by the exchange of nutrient‐poor coastal waters and enhanced biological consumption. Using the Land‐Ocean Interaction Coastal Zone (LOICZ) mass balance model, field observations of nutrient sources/sinks allowed construction of a robust nutrient budget, in which Δ indicated non‐conservative dissolved nutrient fluxes. In both winter and summer, the external DIN and DIP additions ratio ΔDIN:ΔDIP was ∼21.8–20.4:1, while Si(OH)4 addition/removal occurred seasonally. Potential N biogeochemical processes were also explored. Using a three end‐member mixing model, nutrient biogeochemistry (regeneration/uptake, denoted by δ) within the aquaculture ecosystem was estimated separately from complex physical mixing effects. In winter, nutrient regeneration dominated (δDIN:δDIP ∼20:1; δSi(OH)4:δDIN <1:2), likely due to remineralization of particles (phytoplankton with a 16:1 Redfield ratio and/or fish feed/feces with a non‐Redfield ratio). In contrast, nutrient consumption dominated in summer (δDIN:δDIP ∼13.5:1; δSi(OH)4:δDIN ∼2.4:1). Results of this study are relevant to other coastal bays affected by intensive aquaculture, riverine inputs and coastal waters.
Principios inmediatos y elementos minerales en hongos comestibles

Se han analizado 20 especies de hongos comestibles en los que se ha determinado humedad cenizas proteina bruta fibra bruta grasa hidratos de carbono cenizas insolubles en clh y valor calorico. Entre los elementos minerales: Na, K, Ca, Dg, Ca, Fe, Zn y Mn.
ETV5 overexpression promotes progression of esophageal squamous cell carcinoma by upregulating SKA1 and TRPV2

Esophageal squamous cell carcinoma (ESCC) is notorious for the rapid progression especially early tumor metastasis due to the unclear mechanism. Recently, ETV5 attracts much attention for its potential role as an oncogenic transcription factor involved in multiple cancers. However, no one reported the mechanism behind the association between ETV5 expression and esophageal squamous cell carcinoma progression. In this study, we found that ETV5 was upregulated in ESCC both from online database and our ESCC tissues and ETV5 was associated with tumor staging and prognosis. Knockdown of ETV5 or its downstream genes SKA1 and TRPV2 significantly suppress ESCC cells migration and invasion, respectively. Additionally, in vivo study showed knockdown of ETV5 inhibited tumor metastasis. Further experiments unveiled ETV5 could transcriptionally upregulate the expression of SKA1 and TRPV2 and further activate MMPs in ESCC progression. In conclusion, ETV5 was associated with ESCC tumor staging and ESCC prognosis clinically. ETV5 promoted metastasis of ESCC by activating MMPs through augmenting the transcription of SKA1 and TRPV2. ETV5 was likely to be a novel oncogene and therapeutic target in ESCC.
Oxidative stability of crude extract of red variety rice bran from Minahasa, North Sulawesi on lipid-based food products

F U L L P A P E R Oxidative stability of crude extract of red variety rice bran from Minahasa, North Sulawesi on lipid-based food products Moko, E.M. , Ngangi, J. and Rahardiyan, D. Biology Department, Mathematics and Natural Sciences Faculty, Manado State University, Tondano, 95619 Indonesia Agribusiness Department, Faculty of Agricultural, De La Salle Catholic University, Manado, 95000, Indonesia
Building Footprint Generation by Integrating U-Net with Deepened Space Module

In this paper, we propose a novel and practical convolutional neural network method for building footprint generation in remote sensing images, in order to deal with the problem that the detailed information and geometric structure of ground objects in high-resolution images become more abundant, which leads to a large increase in the calculation amount. So we introduce a deepened space module, which can ignore the channels with weak target features and emphasize the effective features. It is embedded in each splicing layer in the upsampling process of U-net to achieve the effect of feature selection. By means of clipping and data enhancement, we carry out iterative training and model optimization learning on Inria aerial image label dataset, and realize the automatic generation of building footprint. Compared with FCN8s, Unet, SegNet, PSPNet, Deeplabv3 + and GLNet, experimental results show that the method we use to generate building footprint is more accurate, and in IoU, mPA, PA three indicators are better than the comparison algorithms.
Effect of Hot Band on Texture Evolution and Plastic Anisotropy in Aluminium Alloys

This contribution presents the evolution of crystallographic texture during thermomechanical processing of Al alloys. It is shown that the nature of crystallographic changes involved in deformation and recrystallization is strongly affected by the variety of initial (pre-rolling) state of a given metallic system. Four hot rolled Al strips of identical chemical composition and different textures were subjected to further thermomechanical processing with equal technological characteristics. Although the pre-rolling textures were first destroyed by the deformation, while annealing accounted for further qualitative and quantitative crystallographic changes in the investigated polycrystalline systems, it seems that there is still a great influence of the hot band texture on the texture dependent properties. Various qualitative and quantitative texture characteristics of annealed sheets ensured diverse Lanford value curves, which is a direct consequence of the crystallographic features developed in the hot bands. The Cube-dominated hot band ensured a strong V-shaped profile after cold rolling and subsequent recrystallization, whereas it was shown that a weak pre-rolling texture is more advantageous in terms of both normal and planar anisotropy.
Raman Spectroscopy Follows Time-Dependent Changes in T Lymphocytes Isolated from Spleen of Endotoxemic Mice

T lymphocytes (T cells) are highly specialized members of the adaptive immune system and hold the key to the understanding the hosts’ response toward invading pathogen or pathogen-associated molecular patterns such as LPS. In this study, noninvasive Raman spectroscopy is presented as a label-free method to follow LPS-induced changes in splenic T cells during acute and postacute inflammatory phases (1, 4, 10, and 30 d) with a special focus on CD4+ and CD8+ T cells of endotoxemic C57BL/6 mice. Raman spectral analysis reveals highest chemical differences between CD4+ and CD8+ T cells originating from the control and LPS-treated mice during acute inflammation, and the differences are visible up to 10 d after the LPS insult. In the postacute phase, CD4+ and CD8+ T cells from treated and untreated mice could not be differentiated anymore, suggesting that T cells largely regained their original status. In sum, the biological information obtained from Raman spectra agrees with immunological readouts demonstrating that Raman spectroscopy is a well-suited, label-free method for following splenic T cell activation in systemic inflammation from acute to postacute phases. The method can also be applied to directly study tissue sections as is demonstrated for spleen tissue one day after LPS insult.
Progressive Spatio-Temporal Feature Extraction Model For Gait Recognition

As a new biometric feature, gait brings new possibilities for personal recognition. At present, gait recognition methods mainly extract appearance features, but seldom use temporal information, such as the method based on gait energy images (GEI) to fuse gait sequence into one image. In order to mine the motion patterns contained in gait sequences, this paper proposes a model that can gradually fuse temporal features while extracting spatial features to achieve the spatiotemporal feature extraction: 1) the model mines temporal information by passing partial channels of feature maps and fusing features of adjacent frames; 2) the model adapts the part-based method to split feature map into several parts, which can refine the spatial features. Extensive experiments on the challenging datasets CASIA-B demonstrate the superiority and effectiveness of our proposed model.
Strategies of Deep Learning for Tomographic Reconstruction

In this article, we introduce three different strategies of tomographic reconstruction based on deep learning. These algorithms are model-based learning for iterative optimization. We discuss the basic principles of developing these algorithms. The performance of them is analyzed and evaluated both on theory and simulation reconstruction. We developed open-source software to run these algorithms in the same framework. From the simulation results, all these deep learning algorithms showed improvements in reconstruction quality and accuracy where the strategy based on Generative Adversarial Networks showed the advantage especially.
Environmental Drivers and Network Structure of Hylid Anurans in Floating Meadows From Amazonian Oxbow Lakes

Despite the increasing amount of knowledge available regarding the ecological interactions between species, the dynamics of anurans in aquatic environments are little explored and understood. In this way, our work aims to assess which factors influence the composition and the ecological interactions of hylid anurans in oxbow lakes in the middle Purus River, Amazonas. We sampled three lakes with high, medium and low levels of connectivity twice, once during the flood and then in drought hydrological regimes. Variations in the hylid anuran assemblages and ecological interactions were tested as function of environmental niche, food resources, level of connectivity and hydrological regime. The availability of environmental resources and the availability of food resources were the best factors that explain the distribution of hylid anurans, which were also highly dependent on the variations between the hydrological regimes. The interactions between anurans, macroinvertebrates and macrophytes showed a modular and specialized structure, which varied according to the connectivity and hydrological regime of the lakes. Connectance showed an increasing trend from high to low connectivity lakes, suggesting that anurans had low trophic and environmental specialization in lakes with low connectivity. Hylids found in the lake of medium connectivity had higher values of trophic specialization and modularity. Our results illustrate the role of river-lake connectivity and annual hydrological cycle to maintain the aquatic biota and their interactions, and highlight the importance of floating meadows for the maintenance of biodiversity in floodplains.
A testbed for geomagnetic data assimilation

Geomagnetic data assimilation merges past and present-day observations of the Earth’s magnetic field with numerical geodynamo models and the results are used to initialize forecasts. We present a new ‘proxy model’ that can be used to test, or rapidly prototype, numerical techniques for geomagnetic data assimilation. The basic idea for constructing a proxy is to capture the conceptual difficulties one encounters when assimilating observations into high-resolution, 3-D geodynamo simulations, but at a much lower computational cost. The framework of using proxy models as ‘gate-keepers’ for numerical methods that could/should be considered for more extensive testing on operational models has proven useful in numerical weather prediction, where advances in data assimilation and, hence, improved forecast skill, are at least in part enabled by the common use of a wide range of proxy models. We also present a large set of systematic data assimilation experiments with the proxy to reveal the importance of localization and inflation in geomagnetic data assimilation.
Effect of irrigation regimes using saline water on faba bean (Vicia faba L.) yield and water productivity in an arid environment *

A 2‐year study was conducted to assess the effects of irrigation regimes using saline water on soil salinization, yield, water productivity, and net income of faba bean (Vicia faba L.) under actual farming conditions in arid regions of Tunisia. Faba bean (cvs. Luz de Otono and local) was grown on a sandy soil and drip‐irrigated with water having an electrical conductivity of 6 dS m−1. Two deficit irrigation (DI70 and DI40) and one full irrigation (FI) strategy consisting of applications of 40%, 70%, and 100% of crop evapotranspiration (ETc), respectively, were compared to the traditional farmers' irrigation method (FM) in which 16 mm irrigation were applied every 5 days from planting till harvest. Results showed that the lowest soil salinity values at harvest were observed under FI treatment, while the highest were obtained with DI40 and the FM. The maximum values of faba bean yields were obtained under FI and the lowest with the FM. No significant reduction in yields was observed with the DI70 treatment compared to FI, while DI40 and the FM significantly decreased the fresh pod yields. Using 12%–20% more irrigation water than FI treatment, the FM did not improve soil salinity but resulted in a significant yield reduction compared to FI. Total water productivity values varied between 4.9 (FM) and 14 kg m−3 (DI40) across different years and treatments. Compared to the FM, which applies fixed amounts with the same frequency, the FI strategy, which adapts the irrigation amounts to the actual crop water requirements, was more productive and provided a significant advantage in terms of yield and net income. Under limited availability of irrigation water, adoption of the DI70 treatment was found to be a good alternative as it allowed 30% water saving and was subject to limited negative effects on soil salinity, yield, and net income.
Deep Video Compression for Interframe Coding

A typical learning-based video compression scheme consists of motion coding and residual coding. In this paper, our deep video compression features a motion predictor and refinement networks for interframe coding. To save the bits for transmitting motion information, our scheme performs local motion prediction and sends only the differential motion vectors to the decoder. In the residual coding, we couple the residual decoder with the refine-net to reduce residual signal bits. The experiments show that our work can produce a very competitive coding performance compared to the other learning-based predictive video codecs.
Influence of Spatial Resolution for Vegetation Indices' Extraction Using Visible Bands from Unmanned Aerial Vehicles' Orthomosaics Datasets

The consolidation of unmanned aerial vehicle (UAV) photogrammetric techniques for campaigns with high and medium observation scales has triggered the development of new application areas. Most of these vehicles are equipped with common visible-band sensors capable of mapping areas of interest at various spatial resolutions. It is often necessary to identify vegetated areas for masking purposes during the postprocessing phase, excluding them for the digital elevation models (DEMs) generation or change detection purposes. However, vegetation can be extracted using sensors capable of capturing the near-infrared part of the spectrum, which cannot be recorded by visible (RGB) cameras. In this study, after reviewing different visible-band vegetation indices in various environments using different UAV technology, the influence of the spatial resolution of orthomosaics generated by photogrammetric processes in the vegetation extraction was examined. The triangular greenness index (TGI) index provided a high level of separability between vegetation and nonvegetation areas for all case studies in any spatial resolution. The efficiency of the indices remained fundamentally linked to the context of the scenario under investigation, and the correlation between spatial resolution and index incisiveness was found to be more complex than might be trivially assumed.
The benefits of an asymmetric tri-stable energy harvester in low-frequency rotational motion

This letter investigates the benefits of an asymmetric tri-stable energy harvester in low-frequency rotational motion. A theoretical model framework is presented, which considers the effect of the rotational motion, to describe the dynamic characteristics and output voltage of the harvester. More importantly, the asymmetric tri-stable energy harvester is experimentally verified to be better than the symmetric one under various rotational speeds. The former exhibits a wide working rotational speed range of 140–460 rpm. The weight component of tip mass produces a periodic harmonic exciting force due to rotational motion, which can be designed to enhance energy harvesting.
Greening of regional industrial paths and the role of sectoral characteristics: A study of the maritime and petroleum sectors in an Arctic region

Recent studies on regional industrial path development call for new perspectives and studies of how a region’s endogenous and exogenous processes (e.g. networks, capital, knowledge) influence its industries, and more recently, the greening of those industries. To this end, recent research has focused on increasing our understanding of the roles of firm and non-firm agency and multi-scalar dynamics (e.g. value chains, national and global regulations). However, the literature has naturally tended to focus more on territorial dynamics (e.g. agglomerations, clusters, regional innovation systems) than on the role of sectoral characteristics to explain regional industrial path development and regional industry greening. To address this, we have developed a framework built on the sectoral innovation systems literature to provide a better explanation of the role of sectoral characteristics in regional industrial path development. We argue herein that the greening of regional industrial paths can be strongly influenced by sectoral characteristics (e.g. standards, markets, technological solutions, laws, regulations), and not merely by territorial characteristics. Our theory-based argument is practically exemplified by an investigation of how a new green technology, onshore power supply, has influenced the greening of two industries (i.e. maritime and petroleum) in the rural Arctic region of northern Norway.
3d Point Cloud Completion Using Stacked Auto-Encoder For Structure Preservation

3D point cloud completion problem deals with completing the shape from partial points. The problem finds its application in many vision-related applications. Here, structure plays an important role. Most of the existing approaches either do not consider structural information or consider structure at the decoder only. For maintaining the structure, it is also necessary to maintain the position of the available 3D points. However, most of the approaches lack the aspect of maintaining the available structural position. In this paper, we propose to employ stacked auto-encoder in conjunction a with shared Multi-Layer Perceptron (MLP). MLP converts each 3D point into a feature vector and the stacked auto-encoder helps in maintaining the available structural position of the input points. Further, it explores the redundancy present in the feature vector. It aids to incorporate coarse to fine scale information that further helps in better shape representation. The embedded feature is finally decoded by a structural preserving decoder. Both the encoding and the decoding operations of our method take care of preserving the structure of the available shape information. The experimental results demonstrate the structure preserving capability of our network as compared to the state-of-the-art methods.
Development of a Liposomal Dosage Form for a New Somatostatin Analogue

A new pentapeptide analogue of somatostatin was synthesized and preliminary studies demonstrated that this analogue possessed antitumor activity on transplanted solid tumors of mice. Due the analogue’s insolubility in water, a liposomal formulation was attempted to increase bioavailability of the drug, to administer intravenously and to improve selectivity towards the tumor cells. This study employed the somatostatin analogue, egg lecithin, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethyleneglycol)-2000, cholesterol and sucrose. Model compositions of the somatostatin analogue liposomal dosage form were prepared using the lipid film rehydration method. All samples obtained were characterized by measuring size of liposomes, pH of the liposomal dispersion, and assay of somatostatin analogue incorporated in the liposomal bilayer. Efficiency of the formulation was investigated on models of breast adenocarcinoma Ca-755. During experimental development of the somatostatin analogue liposomal formulation, an optimal composition was established, which included egg lecithin and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethyleneglycol)-2000 in the 72/1 molar ratio. Influence of extrusion on the quality of liposomal preparations was studied. It was shown that to reach an optimal liposome size of about 150 nm, 7 extrusion cycles were necessary. In addition, while assessing the stability of the somatostatin analogue liposomal dispersion during storage it was found that somatostatin analogue was extremely unstable in liquid form, thus, to produce a stable formulation, lyophilization became necessary. The liposomal formulation when tested on transplanted tumors in mice, more than 60 % tumor growth inhibition was observed at 5 mg/kg dose and more than 80 % tumor growth inhibition at 20 mg/kg dose. These findings indicated that further efforts are required to improve this liposomal formulation to develop the somatostatin analogue in to a potential antitumor drug.
Risk assessment of water inrushes from bed separations in Cretaceous strata corresponding to different excavation lengths during mining in the Ordos Basin

Abstract Evaluation of the risk of bed-separation water inrush (BWI) hazards in Cretaceous strata is required for safe mining in the Ordos Basin, China. In this paper, three coal mines in the Ordos Basin were selected for detailed evaluation of the water inrush risk. The multifactor superposition method and stress balance arch theory were used to obtain the water inrush risk in the mines from bed separations at different excavation lengths. First, the related BWI factors were analyzed, and the BWI risk index at any coordinate point in the study area was calculated using multifactor superposition. The weights of relevant factors were obtained using the entropy weight method. Then, based on stress arch theory, the overall BWI risk index in the bed-separation zone corresponding to any excavation length was calculated. Finally, the boundary values between different risk levels were obtained by comparing the overall risk in the mining area with and without BWIs. With the help of these boundary values, the overall BWI risk in bed-separation zones corresponding to any excavation length in some mining areas was evaluated. The evaluation results were verified in practice, which demonstrated the scientific basis for and practicality of this BWI risk assessment method.