Easy Fabrication of Performant SWCNT-Si Photodetector

We propose a simple method to fabricate a photodetector based on the carbon nanotube/silicon nitride/silicon (CNT/Si3N4/Si) heterojunction. The device is obtained by depositing a freestanding single-wall carbon nanotube (SWCNT) film on a silicon substrate using a dry transfer technique. The SWCNT/Si3N4/Si heterojunction is formed without the thermal stress of chemical vapor deposition used for the growth of CNTs in other approaches. The CNT film works as a transparent charge collecting electrode and guarantees a uniform photocurrent across the sensitive area of the device. The obtained photodetector shows a great photocurrent that increases linearly with the incident light intensity and grows with the increasing wavelength in the visible range. The external quantum efficiency is independent of the light intensity and increases with the wavelength, reaching 65% at 640 nm.

Effect of Cascade Surface Roughness on Boundary Layer Flow Under Variable Conditions

Under the influence of many factors, the surface roughness of the cascade will change during turbomachinery operation, which will affect the boundary layer flow of the cascade. In this article, the effects of cascade surface roughness on boundary layer flow under variable conditions are analyzed by experiments and numerical simulation. The results show that with the increase of roughness, the total pressure loss coefficient of the cascade decreases first and then increases. The larger the Reynolds number is, the greater the total pressure loss coefficient is, and the sensitive area of loss change is changed. In the sensitive area, the roughness has a greater influence on cascade loss. There are separation bubbles at the suction front edge of smooth cascades. With the increase of roughness, the degree of turbulence increases, and the transition process is accelerated. When the roughness is between 74 and 150 μm, the separation bubble disappears and the separation loss decreases. In conclusion, the aerodynamic loss of the cascade increases with the increase of roughness, and the cascade efficiency decreases. However, roughness can restrain the flow separation and reduce the separation loss. The two have gone through a process of one and the other. When the roughness is 74 μm, the displacement thickness, momentum thickness, and shape factor at the back of the cascade are the minimum.

Simulation, Precursor Analysis and Targeted Observation Sensitive Area Identification for Two Types of ENSO using ENSO-MC v1.0

The global impact of an El Niño-Southern Oscillation (ENSO) event can differ greatly depending on whether it is an Eastern-Pacific-type (EP-type) event or a Central-Pacific-type (CP-type) event. Reliable predictions of the two types of ENSO are therefore of critical importance. Here we construct a deep neural network with multichannel structure for ENSO (named ENSO-MC) to simulate the spatial evolution of sea surface temperature (SST) anomalies for the two types of events. We select SST, heat content, and wind stress (i.e., three key ingredients of Bjerknes feedback) to represent coupled ocean-atmosphere dynamics that underpins ENSO, achieving skillful forecasts for the spatial patterns of SST anomalies out to one year ahead. Furthermore, it is of great significance to analyze the precursors of EP-type or CP-type events and identify targeted observation sensitive area for the understanding and prediction of ENSO. Precursors analysis is to determine what type of initial perturbations will develop into EP-type or CP-type events. Sensitive area identification is to determine the regions where initial states tend to have greatest impacts on evolution of ENSO. We use saliency map method to investigate the subsurface precursors and identify the sensitive areas of ENSO. The results show that there are pronounced signals in the equatorial subsurface before EP events, while the precursory signals of CP events are located in the North Pacific. It indicates that the subtropical precursors seem to favor the generation of the CP-type El Niño and the EP-type El Niño is more related to the tropical thermocline dynamics. And the saliency maps show that the sensitive areas of the surface and the subsurface are located in the equatorial central Pacific and the equatorial western Pacific, respectively. The sensitivity experiments imply that additional observations in the identified sensitive areas can improve forecasting skills. Our results of precursors and sensitive areas are consistent with the previous theories of ENSO, demonstrating the potential usage and advantages of the ENSO-MC model in improving the simulation, understanding and observations of two ENSO types.

Non-Global Privacy Protection Facing Sensitive Areas in Face Images

Face images, as an information carrier, are naturally weak in privacy. If they are collected and analyzed by malicious third parties, personal privacy will leak, and many other unmeasurable losses will occur. Differential privacy protection of face images is mainly being studied under non-interactive frameworks. However, the ε-effect impacts the entire image under these frameworks. Besides, the noise influence is uniform across the protected image, during the realization of the Laplace mechanism. The differential privacy of face images under interactive mechanisms can protect the privacy of different areas to different degrees, but the total error is still constrained by the image size. To solve the problem, this paper proposes a non-global privacy protection method for sensitive areas in face images, known as differential privacy of landmark positioning (DPLP). The proposed algorithm is realized as follows: Firstly, the active shape model (ASM) algorithm was adopted to position the area of each face landmark. If the landmark overlaps a subgraph of the original image, then the subgraph would be taken as a sensitive area. Then, the sensitive area was treated as the seed for regional growth, following the fusion similarity measurement mechanism (FSMM). In our method, the privacy budget is only allocated to the seed; whether any other insensitive area would be protected depends on whether the area exists in a growing region. In addition, when a subgraph meets the criterion for merging with multiple seeds, the most reasonable seed to be merged would be selected by the exponential mechanism. Experimental results show that the DPLP algorithm satisfies ε-differential privacy, its total error does not change with image size, and the noisy image remains highly available.

Measurements and analysis of different front-end configurations for monolithic SiGe BiCMOS pixel detectors for HEP applications

This paper presents a small-area monolithic pixel detector ASIC designed in 130 nm SiGe BiCMOS technology for the upgrade of the pre-shower detector of the FASER experiment at CERN. The purpose of this prototype is to study the integration of fast front-end electronics inside the sensitive area of the pixels and to identify the configuration that could satisfy at best the specifications of the experiment. Self-induced noise, instabilities and cross-talk were minimised to cope with the several challenges associated to the integration of pre-amplifiers and discriminators inside the pixels. The methodology used in the characterisation and the design choices will also be described. Two of the variants studied here will be implemented in the pre-production ASIC of the FASER experiment pre-shower for further tests.

Nuclear Weapons Law

This book examines the law relating to the possession, threat or use of nuclear weapons. By addressing in logical sequence the law regarding sovereignty, the threat or use of force, the conduct of nuclear hostilities, neutrality, weapons law and war crimes, the book illustrates the topics that an effective national command, control and communications system for nuclear weapons must address. Guidance is given on intractable issues, such as the responsibilities of remote submarine commanders. The continuing relevance of the ICJ's Nuclear Advisory Opinion is assessed, and the prospects for the Treaty on the Prohibition of Nuclear Weapons are discussed. The book has been written in an accessible style so that it will be equally useful to lawyers and practitioners, including relevant commanders, politicians, policy staffs and academics. The objective is to state the law accurately and to explain its implications and provide practical guidance in this most sensitive area.

Vehicle Lane-Changes Trajectory Prediction Model Considering External Parameters

The ability to predict the motion of vehicles is essential for autonomous vehicles. Aiming at the problem that existing models cannot make full use of the external parameters including the outline of vehicles and the lane, we proposed a model to use the external parameters thoroughly when predicting the trajectory in the straight-line and non-free flow state. Meanwhile, dynamic sensitive area is proposed to filter out inconsequential surrounding vehicles. The historical trajectory of the vehicles and their external parameters are used as inputs. A shared Long Short-Term Memory (LSTM) cell is proposed to encode the explicit states obtained by mapping historical trajectory and external parameters. The hidden states of vehicles obtained from the last step are used to extract latent driving intent. Then, a convolution layer is designed to fuse hidden states to feed into the next prediction circle and a decoder is used to decode the hidden states of the vehicles to predict trajectory. The experiment result shows that the dynamic sensitive area can shorten the training time to 75.86% of the state-of-the-art work. Compared with other models, the accuracy of our model is improved by 23.7%. Meanwhile, the model's ability of anti-interference of external parameters is also improved.