Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of Remote Sensing in Precision Agriculture: A Review

Agriculture provides for the most basic needs of humankind: food and fiber. The introduction of new farming techniques in the past century (e.g., during the Green Revolution) has helped agriculture keep pace with growing demands for food and other agricultural products. However, further increases in food demand, a growing population, and rising income levels are likely to put additional strain on natural resources. With growing recognition of the negative impacts of agriculture on the environment, new techniques and approaches should be able to meet future food demands while maintaining or reducing the environmental footprint of agriculture. Emerging technologies, such as geospatial technologies, Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI), could be utilized to make informed management decisions aimed to increase crop production. Precision agriculture (PA) entails the application of a suite of such technologies to optimize agricultural inputs to increase agricultural production and reduce input losses. Use of remote sensing technologies for PA has increased rapidly during the past few decades. The unprecedented availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing in many PA applications, including crop monitoring, irrigation management, nutrient application, disease and pest management, and yield prediction. In this paper, we provide an overview of remote sensing systems, techniques, and vegetation indices along with their recent (2015–2020) applications in PA. Remote-sensing-based PA technologies such as variable fertilizer rate application technology in Green Seeker and Crop Circle have already been incorporated in commercial agriculture. Use of unmanned aerial vehicles (UAVs) has increased tremendously during the last decade due to their cost-effectiveness and flexibility in obtaining the high-resolution (cm-scale) images needed for PA applications. At the same time, the availability of a large amount of satellite data has prompted researchers to explore advanced data storage and processing techniques such as cloud computing and machine learning. Given the complexity of image processing and the amount of technical knowledge and expertise needed, it is critical to explore and develop a simple yet reliable workflow for the real-time application of remote sensing in PA. Development of accurate yet easy to use, user-friendly systems is likely to result in broader adoption of remote sensing technologies in commercial and non-commercial PA applications.
The Experiment Study of Kaiyuqingre's Prescription on the Expression of Sterol Regulatory Element Binding Protein-1c and Fatty Acid Synthase in Peritoneal Adipose Tissue of Spontaneous Type 2 Diabetes Mellitus Rats(OLETF rats)

Objective:To observe the effect of Kaiyuqingre's Prescription on the protein and mRNA expression of sterol regulatory element binding protein-1c and fatty acid synthase in peritoneal adipose tissue of spontaneous Type 2 Diabetes Mellitus rats(OLETF rats). Methods:A control study was carried out between the OLETF rats and LETO rats,and all OLETF rats were divided into three groups randomly:Model group,Metformin group and Kaiyuqingre's Prescription group.Immunohistochemical method and real-time flourescent quantitative polymerase chain reaction(PCR)technology were used to detect the expression of sterol regulatory element binding protein-1c and fatty acid synthase in adipose tissue from the protein and gene levels in each group.Results: The sterol regulatory element binding protein-1c and fatty acid synthase protein and mRNA expression in rats' adipose tissue:Contrast to Modal group,the Kaiyuqingre's Prescription group is significantly lower.Conclusion:Kaiyuqingre's Prescription has a role of reducing the expression of protein and mRNA of sterol regulatory element binding protein-1c and fatty acid synthase in adipose tissue of spontaneous Type 2 Diabetes Mellitus rats.
Introducing an Improved GRACE Global Point-Mass Solution - A Case Study in Antarctica

In the so-called point-mass modeling, surface densities are represented by point masses, providing only an approximated solution of the surface integral for the gravitational potential. Here, we propose a refinement for the point-mass modeling based on Taylor series expansion in which the zeroth-order approximation is equivalent to the point-mass solution. Simulations show that adding higher-order terms neglected in the point-mass modeling reduces the error of inverted mass changes of up to 90% on global and Antarctica scales. The method provides an alternative to the processing of the Level-2 data from the Gravity Recovery and Climate Experiment (GRACE) mission. While the evaluation of the surface densities based on improved point-mass modeling using ITSG-Grace2018 Level-2 data as observations reveals noise level of approximately 5.77 mm, this figure is 5.02, 6.05, and 5.81 mm for Center for Space Research (CSR), Goddard Space Flight Center (GSFC), and Jet Propulsion Laboratory (JPL) mascon solutions, respectively. Statistical tests demonstrate that the four solutions are not significant different (95% confidence) over Antarctica Ice Sheet (AIS), despite the slight differences seen in the noises. Therefore, the estimated noise level for the four solutions indicates the quality of GRACE mass changes over AIS. Overall, AIS shows a mass loss of −7.58 mm/year during 2003–2015 based on the improved point-mass solution, which agrees with the values derived from mascon solutions.
A Novel Coarse-to-Fine Method of Ship Detection in Optical Remote Sensing Images Based on a Deep Residual Dense Network

Automatic ship detection in optical remote sensing images is of great significance due to its broad applications in maritime security and fishery control. Most ship detection algorithms utilize a single-band image to design low-level and hand-crafted features, which are easily influenced by interference like clouds and strong waves and not robust for large-scale variation of ships. In this paper, we propose a novel coarse-to-fine ship detection method based on discrete wavelet transform (DWT) and a deep residual dense network (DRDN) to address these problems. First, multi-spectral images are adopted for sea-land segmentation, and an enhanced DWT is employed to quickly extract ship candidate regions with missing alarms as low as possible. Second, panchromatic images with clear spatial details are used for ship classification. Specifically, we propose the local residual dense block (LRDB) to fully extract semantic feature via local residual connection and densely connected convolutional layers. DRDN mainly consists of four LRDBs and is designed to further remove false alarms. Furthermore, we exploit the multiclass classification strategy, which can overcome the large intra-class difference of targets and identify ships of different sizes. Extensive experiments demonstrate that the proposed method has high robustness in complex image backgrounds and achieves higher detection accuracy than other state-of-the-art methods.
3D Reconstruction of a Complex Grid Structure Combining UAS Images and Deep Learning

The latest advances in technical characteristics of unmanned aerial systems (UAS) and their onboard sensors opened the way for smart flying vehicles exploiting new application areas and allowing to perform missions seemed to be impossible before. One of these complicated tasks is the 3D reconstruction and monitoring of large-size, complex, grid-like structures as radio or television towers. Although image-based 3D survey contains a lot of visual and geometrical information useful for making preliminary conclusions on construction health, standard photogrammetric processing fails to perform dense and robust 3D reconstruction of complex large-size mesh structures. The main problem of such objects is repeated and self-occlusive similar elements resulting in false feature matching. This paper presents a method developed for an accurate Multi-View Stereo (MVS) dense 3D reconstruction of the Shukhov Radio Tower in Moscow (Russia) based on UAS photogrammetric survey. A key element for the successful image-based 3D reconstruction is the developed WireNetV2 neural network model for robust automatic semantic segmentation of wire structures. The proposed neural network provides high matching quality due to an accurate masking of the tower elements. The main contributions of the paper are: (1) a deep learning WireNetV2 convolutional neural network model that outperforms the state-of-the-art results of semantic segmentation on a dataset containing images of grid structures of complicated topology with repeated elements, holes, self-occlusions, thus providing robust grid structure masking and, as a result, accurate 3D reconstruction, (2) an advanced image-based pipeline aided by a neural network for the accurate 3D reconstruction of the large-size and complex grid structured, evaluated on UAS imagery of Shukhov radio tower in Moscow.
The role of wild goose (Anser) populations of Russia and the Tibet Plateau in the spread of the avian influenza virus

Wild birds of the orders Anseriformes and Charadriiformes represent a natural reservoir of low pathogenic avian influenza (LPAI) viruses (family Orthomyxoviridae). Wild geese (order Anseriformes) relating to waterfowls undertake extensive migration flights reaching thousands of kilometers. Isolation of the avian influenza virus (AIV) from wild geese is quite low or absent. The aims of this study are to monitor the AIV in different wild goose species, nesting on Russian territory and the Tibet Plateau and to analyze the derived data for the purpose of determining the role of these wild bird species in spreading pathogens. In our study 3245 samples from nine wild goose species in nine regions of Russia and on the territory of the Tibet Plateau (the Xizang Autonomous Region) were tested and no AIV were detected. Our study shows the non-essential role of wild geese in the spread of the AIV over long distances and reaches the conclusion that geese are probably not natural reservoirs for the primary viruses. However, further inquiry of AIV in wild goose populations is required. Studies of wild geese and AIV ecology will allow us to obtain more information about pathogen-host relationships and to make arrangements for the maintenance of wild goose populations.
COMPARISON OF THE PREDOMINANT BACTERIAL COMMUNITY STRUCTURE IN THE GASTROINTESTINAL WALL BETWEEN LUTJANUS SEBAE AND EPHIPPUS ORBIS BASED ON 16S rDNA PCR-DGGE FINGERPRINT

The comparison of the predominant bacterial community structure in the gastrointestinal walls between Lutjanus sebae(Cuvier,1816) and Ephippus orbis(Bloch,1787) based on 16S rDNA PCR-DGGE fingerprint using a culture-independent method was conducted in the paper.The results showed that abundant bacterium were planted in the gastrointestinal walls of both marine finfish species,the similarity was above 50% in the community structures in the gastrointestinal walls with the highest similarity of 67% in the bacterial composition between the intestinal wall of Lutjanus sebae and that of Ephippus orbis,and the walls of the stomach and the intestinal in one fish shared the same most predominant bacteria species,which might reflect the same aquaculture environment and the diet fed for both finfish species.However,the difference of the richness and relative abundance in the bacterium of the gastrointestinal walls in both finfish species was also observed from the DGGE fingerprint with the results of richer bacterium of the gastrointestinal wall in Ephippus orbis compared to that in Lutjanus sebae,which might due to the different natural living habits.The first time of the establishment and comparison of the 16S rDNA-DGGE fingerprint in the gastrointestinal wall of marine finfish in present study do help to elucidate the microflora structure in the gastrointestinal wall of marine finfish.
Microsatellite DNA analysis of genetic diversity and the phylogenetic relationships of four breed varieties of Carassius sp.

The genetic diversity and the phylogenetic relationships of four breed varieties of C.auratus cuvieri,C.auratus red var,C.auratus auratus and C.auratus auratus var. Pengze were studied by using microsaterllite technology and nine pairs of microsatellite DNA primers. The results showed that the average heterozygosity of the four breed varieties of Carassius sp. ranged between 0.607 and 0.720, which was 0.720 for C.auratus cuvieri,0.650 for C.auratus red var. , 0.630 for C.auratus auratus var.Pengze, and 0.610 for C.auratus auratu. The average polymorphism information contents ranged from 0.530 to 0.650, with 0.650 for C.auratus cuvieri, 0.590 for C.auratus red var, 0.550 for C.auratus auratus var.Pengze,and 0.530 for C.auratus auratus. Thus, C.auratus cuvieri had the highest genetic diversity,but C.auratus auratus had the lowest among the four Carassius sp. breed varieties. The genetic similarity index between C.auratus auratus and C.auratus cuvieri was the lowest ((0.714)) among the four breed varieties of Carassius sp. , and their genetic distance was the highest (0.286), which indicated that the phylogenetic relationship between these two breed varieties was quite far. On the other side,the genetic similarity index between C.auratus cuvieri and C.auratus red var was the highest (0.812), and their genetic distance was the lowest (0.188), which indicated a near phylogenetic relationship between C.auratus cuvieri and C.auratus red var. Cluster's analysis showed that the phylogenetic relationship of C.auratus cuvieri and C.auratus red var was quite near,as well as C.auratus auratus and C.auratus auratus var.Pengze was relatively near. It's very important to study the genetic diversity of Carassius sp. on its quality protection and hereditary bases modification.
A primary study on effec of VAM fungi to strawberry and Verticillium wilt

The resistance to strawberry Verticillium wilt caused by Verticillium dahliae was studied after the symbiosis between strawberry and Glomus mosseae and Glomus versiforme. The results showed both the G.mosseae and G.versiforme have obvious control resistance to strawberry Verticillium wilt. Comparing with the control, the disease index(DI) of the treatment inoculated with G.mosseae and of the treatment with G.versiforme were reduced by 39.4 and 34.7 respectively, the control effection is 66.22% and 58.32% respectively. In addition, the two VAM fungi showed obvious effection of promoting growth. The plant height, diameter of stem, length of root, fresh weight of shoot of both treatments inoculated with G.mosseae and G.versiforme were significantly higher than that of the control.
Differing influences of resource availability on the demographics and habitat selection of wildebeest compared with impala

Abstract: Although what drives the abundance and habitat selection of ungulates is a long-standing question, coherent datasets investigating the influences of rainfall, competition and fire on ungulates are unusual. Over 4 y we carried out extensive monthly road transects in Ithala Game Reserve, South Africa, to determine the demographics and habitat occupancy of the region's prevalent grazer (wildebeest) and mixed-feeder (impala). Habitat occupancy was determined using a GIS-based approach. We obtained 8742 sighting records, encompassing 8400 wildebeest and 10071 impala. Annual rainfall did not significantly correlate with population sizes of either species. Fecundity of wildebeest, but not of impala, showed a significant positive relationship with rainfall specifically over the perinatal period (November–December), whilst no significant relationships were found for either species between fecundity and rainfall over the previous year, 2 y, rut (February–April) or height of the dry season (June–August). Impala unexpectedly favoured browse habitats to grassland year round, probably consequent on competition for grass with wildebeest. Dry-season grass flushes attracted both wildebeest and impala. The study emphasized how rainfall, competition and fire regimes may affect differently grazers compared with mixed-feeders.
Relações entre parâmetros culturais e resposta espectral de cafezais

Para a utilizacao eficiente de dados de sensoriamento remoto visando a obtencao de informacoes relativas ao parque cafeeiro nacional, e necessario o conhecimento dos efeitos interativos entre estes dados e as variaveis biofisicas dessa cultura. Objetivando estudar as relacoes entre variaveis biofisicas de cafezais e sua resposta espectral, foram coletadas, em campo, quase simultaneamente a passagem do satelite, variaveis biofisicas para 145 talhoes. Das imagens TM/Landsat-5 foram obtidos os dados de reflectância para as bandas 1 a 5 e 7, referentes a cada talhao. Foi analisada, inicialmente, a correlacao entre os parâmetros culturais e, em seguida, a correlacao entre parâmetros culturais e reflectância. Apesar da complexidade inerente a cultura, observaram-se correlacoes significativas, como, por exemplo, entre percentagem de cobertura do terreno por arvores e colheita, e ano de poda e altura. Os parâmetros culturais referentes as caracteristicas biofisicas da planta foram mais bem correlacionados com a reflectância do que os parâmetros relativos ao substrato ou os parâmetros geomorfologicos do terreno.
Effects of Different Soil Moisture Conditions on Photosynthetic Characteristics and Effective Content of Saponin of Paris polyphylla

Using pot experiment of soil water stress, the photosynthetic characteristics and effective content of the endangered Paris polyphylla with the treatments of different soil moisture conditions(5.78%–21.32%) were studied, which could provide basis for water management in artif icial cultivating. Results showed with the intensif ication of water stress, the chlorophyll content, maximum net photosynthetic rate and light saturation point decreased gradually, while the light compensation point and dark respiration rate increased. The total saponin content in rootstalk fi rst increased and then decreased with the decreasing of soil water content, and the saponin content was the highest(11.95%) when the soil moisture content was 12.44%. It meant that water stress was not conductive to the photosynthesis of Paris polyphylla, but moderate drought conditions could increase the content of saponin. So we can maintain certain moisture at the vegetative growth stage of Paris polyphylla, while in the later period we can make appropriate drought treatment to increase the content of saponin.
FLRT proteins act as guidance cues for migrating cortical interneurons

The establishment of functional neuronal connectivity starts during development and depends on neuronal migration and the correct positioning of newborn neurons which integrate into specific layers of the cortex. The fibronectin and leucine-rich family of transmembrane proteins (FLRT) have evolved as new regulators of several aspects during nervous system development, including neuronal migration. This work is focused on the study of in vivo FLRTs involvement in the tangential migration of interneurons. For this, we have analyzed nervous system specific knockout animals for FLRT2 and FLRT3, single mutants as well as the double mutants The simultaneous suppression of FLRT2 and FLRT3, resulted in the appearance of several defects related to interneuron migration. Finally, was addressed the intracellular mechanisms involved in FLRT function and was assessed the relationship between FLRT3 and the Rho GTPase Rnd3. The results suggest a possible functional interaction between FLRTs and Rnds in the central nervous system.
A Qualitative Study on Trust Perception in IoT Mobile Applications

The Internet of Things (IoT) is a paradigm where devices, equipped with sensing and data processing capabilities, can communicate with each other seamlessly. In this context, the smartphone, considered as the ultimate IoT device, plays a key-role in this environment. These appliances that initially had limited functionality, nowadays are charged with a full set of sensors and capabilities. Service Providers and development companies encourage their community to take advantage of these embedded hardware components through the creation and deployment of mobile applications and thus, offering new services and enhancing user experience. However, to do so, this kind of applications gathers personal data from direct or indirect interaction, most of the times without awareness from the user.We performed a qualitative study by conducting semi-structure interviews with participants from different backgrounds, in order to understand user’s perception regarding trust in IoT Mobile Applications. With a grounded theory analysis, we concluded that not only people should be recognized as the central entity of any system that seeks the collection of their personal data, but also that trust in IoT technology depends on who controls and has access to it. We believe these results contribute for further application development, concerning the construction of new privacy models and user experience.
Model Driven Engineering for Performance Testing in Mobile Applications

Advancements in mobile computing are constantly being seen and its use is steadily growing in several areas. In addition, new heterogeneous devices are increasingly emerging, which requires a significant effort for software development process. Among development steps, there is the software test, which is performed to assure efficiency and effectiveness of the developed application. Despite the existence of several tools aimed at automating tests, there is a lack in the literature on mobile device performance testing approaches during application development process. In this paper, an approach is proposed based on Model Driven Engineering (MDE), for performance test cases generation in application units aimed at mobile devices using Android operating system. In order to accomplish this goal, an MDE-based framework, a methodology, metamodels, transformation definitions and an illustrative example are presented. A test case was created to improve understanding of the proposed approach.
A Circularly Polarized Patch Antenna Array

In this paper, a two-layer circularly polarized (CP) patch antenna array operating at X-band is presented. The proposed CP antenna element is composed of a corner-truncated rectangular radiating patch at the lower PCB and an air-coupled parasitic corner-truncated rectangular patch at the higher PCB. 3-dB axial ratio (AR) bandwidth and impedance bandwidth have been enhanced simultaneously by adding the parasitic patch. A 4×4 array is designed based on the proposed antenna element. Simulated results show that the proposed CP antenna array is suitable for the X-band radar communication applications.
Analysis of Smartphone Sensor Bias from an Activity Recognition Experiment in the Wild

A multitude of sensor models is being embedded in a variety of smartphone brands. Notably, the accelerometer sensor has been widely used to recognize a variety of human-induced activities leading to the growth of human activity recognition (HAR) research. However, diversities in sensor models create heterogeneity in the data which could result in inaccurate recognition accuracies. Existing empirical work handling a diverse set of mobile devices do not pay attention to this issue. In this paper, we report on the bias observed across 13 different accelerometer models spanning 26 different phones. A continuous sensing application was deployed on all phones over a period of 45 days to empirically assess students’ behavioral patterns (physical activity patterns). Sensor bias analysis revealed One Plus 6, Poco F1 to have the lowest bias and Samsung S4 the largest bias. Except for Samsung S4(11%), Honor 7(6%) and Nexus 5(6%), all other phones showed less than 3% avg deviation from the actual value which was 9.8m/s2. Using the bias ranges observed, we classify the entire unlabeled data with accuracy close to 98%. We believe our results will provide a baseline information before using the phones for continuous sensing applications in general and human activity monitoring in particular.