Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of nutrient limitation on cell cycle,toxin content and composition of Alexandrium tamarense CI01

This study optimized the cell synchronized method of Alexandrium tamarense CI01 and investigated the effects of nutrient limitation on cell cycle,toxin content and composition of A.tamarense CI01.The result showed that the synchronization ratio of A.tamarense CI01 cells increased 14% compared to the traditional darkness induced method.Under nutrient limitation conditions,nitrate-limited cells were arrested at G2/M phase while phosphate-limited cells were arrested at G1 phase.Toxin content and composition of A.tamarense CI01 varied significantly at the different cell cycle phases.Nitrate-limitation decreased toxin content while phosphate-limitation increased toxin content compared to the nutrient replete condition.Compared to nutrient replete and phosphate-limitation conditions,the ratio of C1,2 declined from 98% to 90%,and the ratio of GTX2,3 increased from 2% to 10% under nitrate-limitation.Toxin biosynthesis was induced by light and always occurred during a defined time frame within the G1 phase of the cell cycle.Analyzing toxin biosynthesis time and ratios of C1,2 and GTX2,3 toxins in cells,we postulate that GTX2,3 is synthesized firstly and then is transferred to C1,2 in A.tamarense CI01.
Utilization of Multi-Temporal Microwave Remote Sensing Data within a Geostatistical Regionalization Approach for the Derivation of Soil Texture

Land Surface Models (LSM) have become indispensable tools to quantify water and nutrient fluxes in support of land management strategies or the prediction of climate change impacts. However, the utilization of LSM requires soil and vegetation parameters, which are seldom available in high spatial distribution or in an appropriate temporal frequency. As shown in recent studies, the quality of these model input parameters, especially the spatial heterogeneity and temporal variability of soil parameters, has a strong effect on LSM simulations. This paper assesses the potential of microwave remote sensing data for retrieving soil physical properties such as soil texture. Microwave remote sensing is able to penetrate in an imaged media (soil, vegetation), thus being capable of retrieving information beneath such a surface. In this study, airborne remote sensing data acquired at 1.3 GHz and in different polarization is utilized in conjunction with geostatistics to retrieve information about soil texture. The developed approach is validated with in-situ data from different field campaigns carried out over the TERENO test-site “North-Eastern German Lowland Observatorium”. With the proposed approach a high accuracy of the retrieved soil texture with a mean RMSE of 2.42 (Mass-%) could be achieved outperforming classical deterministic and geostatistical approaches.
The toxicity and effects of sublethal doses on detoxifying enzymes of clothianidin to Myzus persicae (Sulzer) (Hemiptera: Aphididae)

In order to clarify the toxicity of clothianidin to Myzus persicae (Sulzer) and the metabolic detoxification mechanisms in the aphid, the toxicity of clothianidin to M. persicae was detected using topical application, leaf dipping and petiole wrapping methods, the synergism of piperoayl butoxide (PBO), triphenyl phosphate (TPP) and diethylmaleate (DEM) to clothianidin was determined, and the influence of sublethal doses of clothianidin on detoxifying enzymes was determined with biochemical method at the doses of LC6, LC15 and LC30. The results showed that the LC50 values through guttate, impregnation and systemic toxicity were 1.891, 2.341 and 1.303 mg/L, respectively. The synergism ratios of PBO and TPP to clothianidin were 2.41 and 1.52, respectively, whereas DEM had no significant synergism to clothianidin. Under the treatment of sublethal doses of clothianidin, the specific activity of AChE was inhibited significantly at 24 h after treatment, and its inhibition rate reached 41.2% at the dose of LC30; the specific activity of CarE, however, increased obviously, and the synergistic ratios at the doses of LC15 and LC30 at 24 h after treatment were 1.29 and 1.36, respectively; and the GST activity was also inhibited significantly with the inhibition rates of 7.9%, 11.9% and 22.7% at the doses of LC6, LC15 and LC30, respectively. These results suggest that clothianidin has high toxicity to M. persicae, and GST and MFO may be the major detoxifying enzymes in metabolizing clothianidin in the aphid.
Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images

As a basic agricultural parameter in the formation, transformation, and consumption of surface water resources, soil moisture has a very important influence on the vegetation growth, agricultural production, and healthy operation of regional ecosystems. The Aksu river basin is a typical semi-arid agricultural area which seasonally suffers from water shortage. Due to the lack of knowledge on soil moisture change, the water management and decision-making processes have been a difficult issue for local government. Therefore, soil moisture monitoring by remote sensing became a reasonable way to schedule crop irrigation and evaluate the irrigation efficiency. Compared to in situ measurements, the use of remote sensing for the monitoring of soil water content is convenient and can be repetitively applied over a large area. To verify the applicability of the typical drought index to the rapid acquisition of soil moisture in arid and semi-arid regions, this study simulated, compared, and validated the effectiveness of soil moisture inversion. GF-1 WFV images, Landsat 8 OLI images, and the measured soil moisture data were used to determine the Perpendicular Drought Index (PDI), the Modified Perpendicular Drought Index (MPDI), and the Vegetation Adjusted Perpendicular Drought Index (VAPDI). First, the determination coefficients of the correlation analyses on the PDI, MPDI, VAPDI, and measured soil moisture in the 0–10, 10–20, and 20–30 cm depth layers based on the GF-1 WFV and Landsat 8 OLI images were good. Notably, in the 0–10 cm depth layers, the average determination coefficient was 0.68; all models met the accuracy requirements of soil moisture inversion. Both indicated that the drought indices based on the Near Infrared (NIR)-Red spectral space derived from the optical remote sensing images are more sensitive to soil moisture near the surface layer; however, the accuracy of retrieving the soil moisture in deep layers was slightly lower in the study area. Second, in areas of vegetation coverage, MPDI and VAPDI had a higher inversion accuracy than PDI. To a certain extent, they overcame the influence of mixed pixels on the soil moisture spectral information. VAPDI modified by Perpendicular Vegetation Index (PVI) was not susceptible to vegetation saturation and, thus, had a higher inversion accuracy, which makes it performs better than MPDI’s in vegetated areas. Third, the spatial heterogeneity of the soil moisture retrieved by the GF-1 WFV and Landsat 8 OLI image were similar. However, the GF-1 WFV images were more sensitive to changes in the soil moisture, which reflected the actual soil moisture level covered by different vegetation. These results provide a practical reference for the dynamic monitoring of surface soil moisture, obtaining agricultural information and agricultural condition parameters in arid and semi-arid regions.
A new objective function for RPL routing protocol in IoT to increase network lifetime

Internet of Things (IoT) uses Routing Protocol of Low Power and Lossy Networks (RPL) for routing task with an Objective Function (OF) which determines next hop of nodes with calculation of path cost. However, energy imbalance between nodes is considered as one of the main problems in RPL and causes increasing in energy consumption. In this paper, we design a new OF called Time OF (T-OF) to achieve balance between energy of the nodes to improve network lifetime. A new varying weighted combination of energy, Expected Transmission Count (ETX) and Number of Children and Siblings (NOCS) metrics is used. The proposed T-OF has been compared to Minimum Rank with Hysteresis Objective Function (MRHOF), Objective Function Zero (OF0), and Energy Objective Function (EN-OF). Experimental results show that the proposed OF improves network lifetime and energy balancing significantly owing to lower delay, 11.35 seconds and Packet Delivery Ratio (PDR) of 95%.
Underwater 3D Rigid Object Tracking and 6-DOF Estimation: A Case Study of Giant Steel Pipe Scale Model Underwater Installation

The Zengwen desilting tunnel project installed an Elephant Trunk Steel Pipe (ETSP) at the bottom of the reservoir that is designed to connect the new bypass tunnel and reach downward to the sediment surface. Since ETSP is huge and its underwater installation is an unprecedented construction method, there are several uncertainties in its dynamic motion changes during installation. To assure construction safety, a 1:20 ETSP scale model was built to simulate the underwater installation procedure, and its six-degrees-of-freedom (6-DOF) motion parameters were monitored by offline underwater 3D rigid object tracking and photogrammetry. Three cameras were used to form a multicamera system, and several auxiliary devices—such as waterproof housing, tripods, and a waterproof LED—were adopted to protect the cameras and to obtain clear images in the underwater environment. However, since it is difficult for the divers to position the camera and ensure the camera field of view overlap, each camera can only observe the head, middle, and tail parts of ETSP, respectively, leading to a small overlap area among all images. Therefore, it is not possible to perform a traditional method via multiple images forward intersection, where the camera’s positions and orientations have to be calibrated and fixed in advance. Instead, by tracking the 3D coordinates of ETSP and obtaining the camera orientation information via space resection, we propose a multicamera coordinate transformation and adopted a single-camera relative orientation transformation to calculate the 6-DOF motion parameters. The offline procedure is to first acquire the 3D coordinates of ETSP by taking multiposition images with a precalibrated camera in the air and then use the 3D coordinates as control points to perform the space resection of the calibrated underwater cameras. Finally, we calculated the 6-DOF of ETSP by using the camera orientation information through both multi- and single-camera approaches. In this study, we show the results of camera calibration in the air and underwater environment, present the 6-DOF motion parameters of ETSP underwater installation and the reconstructed 4D animation, and compare the differences between the multi- and single-camera approaches.
Visual Tracking of Deformable Objects with RGB-D Camera. (Suivi visuel d'objets déformables avec une caméra RGB-D)

Tracking soft objects using visual information has immense applications in the field of robotics, computer graphics and automation. In this thesis, we propose multiple new approaches for tracking both rigid and non-rigid objects using a RGB-D camera. There are four main contributions of this thesis. The first contribution is a rigid object tracking method which utilizes depth and photometry based errors for tracking complex shapes using their coarse, 3D template. The second contribution is a non-rigid object tracking method which uses co-rotational FEM to track deforming objects by regulating the virtual forces acting on the surface of a physics based model of the object. The third contribution is a deformation tracking approach which minimizes a combination of geometric and photometric error while utilizing co-rotation FEM as the deformation model. The fourth contribution involves estimating the elasticity properties of a deforming object while tracking their deformation using RGB-D camera. Once the elasticity parameters have been estimated, the same methodology can be re-utilized for tracking contact forces on the surface of deforming objects.
Fusarium Wilt of Radish Detection Using RGB and Near Infrared Images from Unmanned Aerial Vehicles

The radish is a delicious, healthy vegetable and an important ingredient to many side dishes and main recipes. However, climate change, pollinator decline, and especially Fusarium wilt cause a significant reduction in the cultivation area and the quality of the radish yield. Previous studies on plant disease identification have relied heavily on extracting features manually from images, which is time-consuming and inefficient. In addition to Red-Green-Blue (RGB) images, the development of near-infrared (NIR) sensors has enabled a more effective way to monitor the diseases and evaluate plant health based on multispectral imagery. Thus, this study compares two distinct approaches in detecting radish wilt using RGB images and NIR images taken by unmanned aerial vehicles (UAV). The main research contributions include (1) a high-resolution RGB and NIR radish field dataset captured by drone from low to high altitudes, which can serve several research purposes; (2) implementation of a superpixel segmentation method to segment captured radish field images into separated segments; (3) a customized deep learning-based radish identification framework for the extracted segmented images, which achieved remarkable performance in terms of accuracy and robustness with the highest accuracy of 96%; (4) the proposal for a disease severity analysis that can detect different stages of the wilt disease; (5) showing that the approach based on NIR images is more straightforward and effective in detecting wilt disease than the learning approach based on the RGB dataset.
Incorporating Deep Features into GEOBIA Paradigm for Remote Sensing Imagery Classification: A Patch-Based Approach

The fast and accurate creation of land use/land cover maps from very-high-resolution (VHR) remote sensing imagery is crucial for urban planning and environmental monitoring. Geographic object-based image analysis methods (GEOBIA) provide an effective solution using image objects instead of individual pixels in VHR remote sensing imagery analysis. Simultaneously, convolutional neural networks (CNN) have been widely used in the image processing field because of their powerful feature extraction capabilities. This study presents a patch-based strategy for integrating deep features into GEOBIA for VHR remote sensing imagery classification. To extract deep features from irregular image objects through CNN, a patch-based approach is proposed for representing image objects and learning patch-based deep features, and a deep features aggregation method is proposed for aggregating patch-based deep features into object-based deep features. Finally, both object and deep features are integrated into a GEOBIA paradigm for classifying image objects. We explored the influences of segmentation scales and patch sizes in our method and explored the effectiveness of deep and object features in classification. Moreover, we performed 5-fold stratified cross validations 50 times to explore the uncertainty of our method. Additionally, we explored the importance of deep feature aggregation, and we evaluated our method by comparing it with three state-of-the-art methods in a Beijing dataset and Zurich dataset. The results indicate that smaller segmentation scales were more conducive to VHR remote sensing imagery classification, and it was not appropriate to select too large or too small patches as the patch size should be determined by imagery and its resolution. Moreover, we found that deep features are more effective than object features, while object features still matter for image classification, and deep feature aggregation is a critical step in our method. Finally, our method can achieve the highest overall accuracies compared with the state-of-the-art methods, and the overall accuracies are 91.21% for the Beijing dataset and 99.05% for the Zurich dataset.
Refining the Joint 3D Processing of Terrestrial and UAV Images Using Quality Measures

The paper presents an efficient photogrammetric workflow to improve the 3D reconstruction of scenes surveyed by integrating terrestrial and Unmanned Aerial Vehicle (UAV) images. In the last years, the integration of this kind of images has shown clear advantages for the complete and detailed 3D representation of large and complex scenarios. Nevertheless, their photogrammetric integration often raises several issues in the image orientation and dense 3D reconstruction processes. Noisy and erroneous 3D reconstructions are the typical result of inaccurate orientation results. In this work, we propose an automatic filtering procedure which works at the sparse point cloud level and takes advantage of photogrammetric quality features. The filtering step removes low-quality 3D tie points before refining the image orientation in a new adjustment and generating the final dense point cloud. Our method generalizes to many datasets, as it employs statistical analyses of quality feature distributions to identify suitable filtering thresholds. Reported results show the effectiveness and reliability of the method verified using both internal and external quality checks, as well as visual qualitative comparisons. We made the filtering tool publicly available on GitHub.
Theory and evidence in cognitive neuropsychology: A "radical" response to Robertson, Knight, Rafal, and Shimamura (1993).

L. C. Robertson, R. T. Knight, R. Rafal, and A. P. Shimamura (1993) have presented a variety of arguments in opposition to a view of cognitive neuropsychological research put forth by so-called «radical» cognitive neuropsychologists. In this reply, I suggest that Robertson et al. (1993) failed to offer an effective response to «radical» criticisms of group-study methods, because the rationale they propose for patient-group studies rests on untenable assumptions. I further suggest that Robertson et al.'s (1993) objections to single-patient studies are without foundation and reflect an impoverished view of cognitive neuropsychology. Finally, I argue that single-patient studies are necessary in research aimed at exploring brain-cognition relationships as well as in research concerned with characterizing normal cognitive mechanisms
Comparison of Antibacter Effect of Tilmicosin with Tylosin on some Commonly Pathogenic Bacteria of Domestic Animals

The comparative activity against 20 commonly pathogenic bacteria of tilmicosin and tylosin was carried out with double dilution method in tubes.The results showed that tilmicosin has the similar antibacter activity with tylosin.They inhibited efficiently Gram-positive bacteria.For some Gram-negative bacteria,they inhibited efficiently Pasteurella aviseptica,Erysipelothrix rhusiopathiae,Actinobacillus pleuropneumoniae and Mycoplasma gallisepticum.But some other Gram-negative bacteria were less-susceptible or drug-fast.Some pathogenic bacteria such as Salmonella dysenteriae gallinarum,Salmonella typhimurium,Klebsiella pneumoniae were more susceptible to tilmicosin than to tylosin.As a whole,common pathogeny were more sensitive to tilmicosin than tylosin.
Effects of Deuterium-Depleted Water and Liquor on Lipid Metabolism in Rat Models of Hyperlipidemia

Aim To investigate the effects of deuterium-depleted water(DDW) and liquor on lipid metabolism,blood coagulation and fibrinolysis activity in experimental hyperlipidemic rats. Methods Normal control and hyperlipidemia model groups were designed.Experimental hyperlipidemia rats were administration of liquor [(0.01 L/(kg·d)] or deuterium-depleted water for 90 d.The levels of plasma triglyceride(TG),total cholesterol(TC),high-density lipoprotein(HDL),and low-density lipoprotein(LDL)were determined,and prothrombin time(PT),activated partial thromboplastin time(APTT),tissue plasminogen activator(t-PA)activity,and plasminogen activator inhibitor-l(PAI-1) activity were measured.The pathological examination of the aorta structure and liver tissue was performed. Results Compared with model group,HDL and t-PA significantly increased(P0.05) and PAI-1 significantly decreased(P0.05)in DDW group. LDL and PAI-1 significantly decreased(P0.05) and PT and t-PA significantly increased(P0.05) in low-dose liquor group.Further,TC,HDL,and PT and t-PA in high-dose liquor group significantly increased(P0.05). The TC,HDL,LDL,and PT and t-PA significantly increased(P0.05) and TG and PAI-1 significantly decreased(P0.05) in high-dose liquor with DDW group.The TC,TG,and t-PA significantly increased(P0.05) and APTT and PAI-1 significantly decreased(P0.05) in low-dose liquor with DDW group. Conclusions Blood clotting system and fibrinolysis system in the experimental hyperlipidemic rats were improved by DDW and liquor,respectively.The combined effects of liquor and DDW on these 2 systems in hyperlipidemic rats were similar to those of liquor.
Modulations by cAMP and cGMP of the high-voltage activated Ca~(2+) channels in the central neurons of the cotton bollworm, Helicoverpa armigera

The effects of cAMP and cGMP on the high-voltage activated (HVA) Ca~(2+) channels in the central neurons isolated from the 3rd instar larvae of the cotton bollworm(Helicoverpa armigera) were studied using the whole-cell patch clamp techinque. With barium as current carrier, the currents of Ca~(2+) channels were recorded by blocking Na~(2+) and K~(+) currents. Extracellular application of 0.1 mmol/L forskolin, a stimulator of adenylyl cyclase (AC), had no effect on the peak amplitude of Ba~(2+) currents. In contrast, 1 mmol/L cGMP in the the intracellular solution suppressed the current amplitude significantly and the inhibition was time-and dose-dependent. The results suggest that the activities of HVA Ca~(2+) channels in the cotton bollworm may not be affected by the elevated cAMP, but can be inhibited by the increased cGMP.
Breeding and utilization of Ning RS-1 resistance to sclerotinia stem rot in rapeseed (B.napus L.)

The present paper reported the procedure of breeding for Ning RS-1 which has a medium resistance to sclerotinia stem rot and its utilization in rapeseed genetics and breeding. Ning RS-1 was bred by the complex-crosses between B.napus varieties (Junnong No.1, 3-67, Midas and Wesroona), B.oleracea and B.campestris variety (Guanxian divided-leaf). The resistance of Ning RS-1 might come from B.oleracea and the B.napus variety Junnong No.1. The relative resistant effect RRA and RRB in field disease nursery was 57.4% and 55.7%, respectively, so the resistant type of Ning RS-1 reached medium resistance (MR). In disease inoculation nursery, the resistant type was low resistance (LR). Ning RS-1 had been used as a parent to breed some new double low rapeseed lines and hybrids, which performed well in various yield test trials. Ning RS-1 had also been used in the studies of the inheritance of resistance to sclerotinia stem rot and the molecular markers of resistant genes. 