Pathological Evidence Exploration in Deep Retinal Image Diagnosis

Though deep learning has shown successful performance in classifying the label and severity stage of certain disease, most of them give few evidence on how to make prediction. Here, we propose to exploit the interpretability of deep learning application in medical diagnosis. Inspired by Koch's Postulates, a well-known strategy in medical research to identify the property of pathogen, we define a pathological descriptor that can be extracted from the activated neurons of a diabetic retinopathy detector. To visualize the symptom and feature encoded in this descriptor, we propose a GAN based method to synthesize pathological retinal image given the descriptor and a binary vessel segmentation. Besides, with this descriptor, we can arbitrarily manipulate the position and quantity of lesions. As verified by a panel of 5 licensed ophthalmologists, our synthesized images carry the symptoms that are directly related to diabetic retinopathy diagnosis. The panel survey also shows that our generated images is both qualitatively and quantitatively superior to existing methods.Comment: to appear in AAAI (2019). The first two authors contributed equally to the paper. Corresponding Author: Feng L

Protective effect of midazolam against convulsion in neonatal rats via down-regulation of LC3 and Beclin-1 expression

Purpose: To investigate the effect of midazolam on growth of neurocytes in vitro and in neonatal rats. Methods: Neurocyte proliferation and activity of lactate dehydrogenase were assessed by MTT and lactate dehydrogenase assays, respectively. Western blotting was used to determine the effect of midazolam on LC3, Bax, p62 and Beclin-1 protein expressions. Results: The suppression of neurocyte proliferation byconvulsion was alleviated significantly (p < 0.05) by midazolum treatment. Exposure of convulsion model of neurocytes to midazolum suppressed LC3, Bax, p62 and Beclin-1 protein expression. Midazolum exposure of convulsion model of neurocytes suppressed LDH, caspase-3, caspase-8 and caspase-9 activities. The 3-MA (autophagy inhibitor) treatment also significantly (p < 0.05) promoted neurocyte viability after convulsion induction. In convulsion-induced neurocytes, 3-MA exposure suppressed expression of caspase-3/8/9, LC3, Bax, Beclin-1 and p62, while application of midazolum treatment to the rats with convulsion markedly decreased brain water content and neurocyte apoptosis (p < 0.05). Treatment with midazolum inhibited LC3, p62 and Beclin-1 expression in the rat model of convulsion. Conclusion: Midazolum promotes neurocyte proliferation and inhibits edema development via downregulation of autophagy. Therefore, midazolum can potentially be used for the treatment of convulsion, but further studies need to be carried out first. Keywords: Convulsion, Neurocytes, Caspase, Autophagy, Mitochondrial pathwa

Estimation of Fracture Size and Probability Density Function by Setting Scanlines in Rectangular Sampling Window

Rock masses are very important materials in geotechnical engineering. In engineering rock mass, fracture is the relatively weak part of mechanical strength in rock mass and is the most important factor controlling the deformation, damage, and permeability of rock mass. Therefore, investigating fractures is very important for characterizing rock mass. This paper proposed a new approach by using uniformly equidistant orthogonal scanlines. Within the study context, the solution formula of fracture size is derived by establishing the space intersection model of arbitrary fracture and scanline, rectangular window, and a rectangular box with a rectangular window. Then, fractures were randomly generated in a certain size cube and compared with the traditional Kulatilake trace length integral evaluation method. The study results have shown that the proposed method is more reasonable and accurate. Then, this method was applied to an adit of Songta Hydropower Station. Finally, a new fracture diameter probability density estimation method was proposed, the fracture diameter of the normal distribution was verified, and the parameters of the probability density function obtained by the scanlines method were in agreement with the initial set parameters. In summary, the proposed scanlines method can well estimate the mean value of the fracture diameter and the probability density function of the fracture size

Comparison of Machine Learning and Traditional Statistical Methods in Debris Flow Susceptibility Assessment: A Case Study of Changping District, Beijing

As a common geological hazard, debris flow is widely distributed around the world. Meanwhile, due to the influence of many factors such as geology, geomorphology and climate, the occurrence frequency and main inducing factors are different in different places. Therefore, the evaluation of debris flow sensitivity can provide a very important theoretical basis for disaster prevention and control. In this research, 43 debris flow gullies in Changping District, Beijing were cataloged and studied through field surveys and the 3S technology (GIS (Geography Information Systems), GPS (Global Positioning Systems), RS (Remote Sensing)). Eleven factors, including elevation, slope, plane curvature, profile curvature, roundness, geomorphic information entropy, TWI, SPI, TCI, NDVI and rainfall, were selected to establish a comprehensive evaluation index system. The watershed unit is directly related to the development and activities of debris flow, which can fully reflect the geomorphic and geological environment of debris flow. Therefore, the watershed unit was selected as the basic mapping unit to establish four evaluation models, namely ACA–PCA–FR (Analytic Hierarchy Process–Principal Component Analysis–Frequency Ratio), FR (Frequency Ratio), SVM (Support Vector Machines) and LR (Logistic Regression). In other words, this research evaluates debris flow susceptibility by comparingit with two traditional weight methods (ACA–PCA–FR and FR) and two machine learning methods (SVM and LR). The results show that the SVM evaluation model is superior to the other three models, and thevalueofthe area under the receiver-operating characteristic curve (AUC) is 0.889 from the receiver operating characteristic curve (ROC). It verifies that the SVM model has strong adaptability to small sample data. The study was divided into five regions, which were very low, low, moderate, high and very high, accounting for 22.31%, 25.04%, 17.66%, 18.85% and 16.14% of the total study area, respectively, by SVM model. The results obtained in this researchagree with the actual survey results, and can provide theoretical help for disaster prevention and reduction projects

The morphology of tourism : planning for impact in tourist destinations

xiii, 204 p. ; 22 cm

Comparison of Machine Learning and Traditional Statistical Methods in Debris Flow Susceptibility Assessment: A Case Study of Changping District, Beijing

As a common geological hazard, debris flow is widely distributed around the world. Meanwhile, due to the influence of many factors such as geology, geomorphology and climate, the occurrence frequency and main inducing factors are different in different places. Therefore, the evaluation of debris flow sensitivity can provide a very important theoretical basis for disaster prevention and control. In this research, 43 debris flow gullies in Changping District, Beijing were cataloged and studied through field surveys and the 3S technology (GIS (Geography Information Systems), GPS (Global Positioning Systems), RS (Remote Sensing)). Eleven factors, including elevation, slope, plane curvature, profile curvature, roundness, geomorphic information entropy, TWI, SPI, TCI, NDVI and rainfall, were selected to establish a comprehensive evaluation index system. The watershed unit is directly related to the development and activities of debris flow, which can fully reflect the geomorphic and geological environment of debris flow. Therefore, the watershed unit was selected as the basic mapping unit to establish four evaluation models, namely ACA–PCA–FR (Analytic Hierarchy Process–Principal Component Analysis–Frequency Ratio), FR (Frequency Ratio), SVM (Support Vector Machines) and LR (Logistic Regression). In other words, this research evaluates debris flow susceptibility by comparingit with two traditional weight methods (ACA–PCA–FR and FR) and two machine learning methods (SVM and LR). The results show that the SVM evaluation model is superior to the other three models, and thevalueofthe area under the receiver-operating characteristic curve (AUC) is 0.889 from the receiver operating characteristic curve (ROC). It verifies that the SVM model has strong adaptability to small sample data. The study was divided into five regions, which were very low, low, moderate, high and very high, accounting for 22.31%, 25.04%, 17.66%, 18.85% and 16.14% of the total study area, respectively, by SVM model. The results obtained in this researchagree with the actual survey results, and can provide theoretical help for disaster prevention and reduction projects

Sequence Analysis of Ancient River Blocking Events in SE Tibetan Plateau Using Multidisciplinary Approaches

The temporary or permanent river blocking event caused by mass movement usually occurs on steep terrain. With the increase of mountain population and land use pressure and the construction of water conservancy and hydropower projects, river blocking events have gradually attracted people’s attention and understanding. The area in this study is affected by strong tectonic activity in the Jinsha River suture zone and the rapid uplift of the Tibetan Plateau. In the past 6000 years, there have been at least five obvious river blocking events in the reach. The number and density are very rare. Combining field investigation, indoor interpretation, laboratory tests, optically stimulated luminescence (OSL) dating, SBAS-InSAR and previous studies, multidisciplinary approaches are used to systematically summarize the analysis methods and further the understanding of one river blocking event and multiple river blocking events from different perspectives. Especially in multiple river blocking events, we can get the wrong results if interaction is not considered. Through this study, the general method of analyzing the river blocking event and the problems that should be paid attention to in sampling are given, and relatively reliable historical results of river blocking events are obtained. This method has applicability to the identification and analysis of river blocking events and age determination of dams with multiple river blockages

Tunable Photoresponse in a Two-Dimensional Superconducting Heterostructure

The photo-induced superconducting phase transition is widely used in probing the physical properties of correlated electronic systems and to realize broadband photodetection with extremely high responsivity. However, such photoresponse is usually insensitive to electrostatic doping due to the high carrier density of the superconductor, restricting its applications in tunable optoelectronic devices. In this work, we demonstrate the gate voltage modulation to the photoresponsivity in a two-dimensional NbSe2-graphene heterojunction. The superconducting critical current of the NbSe2 relies on the gate-dependent hot carrier generation in graphene via the Joule heating effect, leading to the observed shift of both the magnitude and peak position of the photoresponsivity spectra as the gate voltage changes. This heating effect is further confirmed by the temperature and laser-power-dependent characterization of the photoresponse. In addition, we investigate the spatially-resolved photocurrent, finding that the superconductivity is inhomogeneous across the junction area. Our results provide a new platform for designing tunable superconducting photodetector and indicate that the photoresponse could be a powerful tool in studying the local electronic properties and phase transitions in low-dimensional superconducting systems

Inhibition of TRPC6 Signal Pathway Alleviates Podocyte Injury Induced by TGF-β1

Background/Aims: Transforming growth factor beta 1 (TGF-β1) plays a critical role in the pathogenesis of glomerulosclerosis. The purpose of this study was to examine the effects of inhibition of transient receptor potential cation channel C6 (TRPC6) on podocyte injury induced by TGF-β1 via nephrin and desmin mechanisms. Methods: A rat model of nephropathy was first induced by intravenous injections of adriamycin to determine TRPC6 signal pathway engaged in glomerulosclerosis in vivo. Conditionally immortalized podocytes were cultured in vitro and they were divided into four groups: control; TGF-β1 treatment; TGF-β1 with TRPC6 knockdown and TGF-β1 without TRPC6 knockdown. Real time RT-PCR and Western blot analysis were employed to determine the mRNA and protein of expression of nephrin, desmin and caspase-9, respectively. Flow cytometry was used to examine the apoptotic rate of podocytes and DAPI fluorescent staining was used to determine apoptotic morphology. Results: In vivo experiment, adriamycin significantly upregulated the protein expression of TGF-β1, TRPC6, desmin and caspase-9, and decreased nephrin. Consistent with the latter results, in vitro experiment mRNA and protein expression of desmin and caspase-9 was increased in cultured TGF-β1-treated podocytes, whereas nephrin was declined as compared with the control group. Importantly, TRPC6 knockdown significantly attenuated the upregulated desmin and caspase-9, and alleviated impairment of nephrin induced by TGF-β1. Moreover, typical morphologic features were presented in apoptotic podocytes. The number of apoptotic podocytes was increased after exposure to TGF-β1 and this was alleviated after TRPC6 knockdown. TRPC6 knockdown also decreased an apoptosis rate of TGF-β1-treated podocytes. Note that negative TRPC6 transfection control failed to alter an increase of the apoptosis rate in TGF-β1-treated podocytes. Conclusions: TGF-β1 induced by glomerulosclerosis impairs the protein expression of nephrin and amplifies the protein expression of desmin and caspase -9 via TRPC6 signal pathway. Inhibition of TRPC6 alleviates these changes in podocytes-treated with TGF-β1 and attenuated apoptosis of podocytes. Our data suggest that TRPC6 signal plays an important role in mediating TGF-β1-induced podocyte injury via nephrin, desmin and caspase-9. Results of the current study also indicate that blocking TRPC6 signal pathway has a protective effect on podocyte injury. Targeting one or more of these signaling molecules may present new opportunities for treatment and management of podocyte injury observed in glomerulosclerosis