Electrical and magnetic properties of antiferromagnetic semiconductor MnSi2N4 monolayer

Two-dimensional antiferromagnetic semiconductors have triggered significant attention due to their unique physical properties and broad application. Based on first-principles calculations, a novel two-dimensional (2D) antiferromagnetic material MnSi2N4 monolayer is predicted. The calculation results show that the two-dimensional MnSi2N4 prefers an antiferromagnetic state with a small band gap of 0.26 eV. MnSi2N4 has strong antiferromagnetic coupling which can be effectively tuned under strain. Interestingly, the MnSi2N4 monolayer exhibits a half-metallic ferromagnetic properties under an external magnetic field, in which the spin-up electronic state displays a metallic property, while the spin-down electronic state exhibits a semiconducting characteristic. Therefore, 100% spin polarization can be achieved. Two-dimensional MnSi2N4 monolayer has potential application in the field of high-density information storage and spintronic devices

Absence of nematic instability in the kagome metal CsV3_3Sb5_5

Ever since the discovery of the charge density wave (CDW) transition in the kagome metal CsV$_3$Sb$_5$, the nature of its symmetry breaking is under intense debate. While evidence suggests that the rotational symmetry is already broken at the CDW transition temperature ($T_{\rm CDW}$), an additional electronic nematic instability well below $T_{\rm CDW}$ was reported based on the diverging elastoresistivity coefficient in the anisotropic channel ($m_{E_{2g}}$). Verifying the existence of a nematic transition below $T_{\rm CDW}$ is not only critical for establishing the correct description of the CDW order parameter, but also important for understanding the low-temperature superconductivity. Here, we report elastoresistivity measurements of CsV$_3$Sb$_5$ using three different techniques probing both isotropic and anisotropic symmetry channels. Contrary to previous reports, we find the anisotropic elastoresistivity coefficient $m_{E_{2g}}$ is temperature-independent except for a step jump at $T_{\rm CDW}$. The absence of nematic fluctuations is further substantiated by measurements of the elastocaloric effect, which show no enhancement associated with nematic susceptibility. On the other hand, the symmetric elastoresistivity coefficient $m_{A_{1g}}$ increases below $T_{\rm CDW}$, reaching a peak value of 90 at $T^* = 20$ K. Our results strongly indicate that the phase transition at $T^*$ is not nematic in nature and the previously reported diverging elastoresistivity is due to the contamination from the $A_{1g}$ channel

Diverse Applications of Nanomedicine

The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic. \ua9 2017 American Chemical Society

The Shift from State Partnerships to Technological Solutions: Comparing Two Generations of Chinese NGOs

This article uses an organizational approach to compare and contrast first- and second-generation Chinese NGOs

Differentially Private Fingerprinting for Location Trajectories

Location-based services have brought significant convenience to people in their daily lives. Services like navigation, food delivery, and carpooling frequently ask for location data from users. On the other side, researchers and businesses are eager to acquire those data (that is collected by location-based service providers) for various purposes. However, directly releasing those data causes privacy concerns since location data contain users' sensitive information, e.g., regular moving patterns and favorite spots. To solve this, we propose a system that protects users' location data under differential privacy and prevents unauthorized redistribution at the same time. Observing high amount of noise introduced to achieve differential privacy, we implement a novel post-processing scheme to regain data utility. In addition, we also propose a novel fingerprinting scheme as a part of the post-processing (to detect unauthorized redistribution of data). Our proposed fingerprinting scheme considers correlations in location datasets and collusions among multiple parties, which makes it hard for the attackers to infer the fingerprinting codes and avoid accusation. Using the experiments on a real-life location dataset, we show that our system achieves high fingerprint robustness against state-of-the-art attacks. We also show the integrated fingerprinting scheme increases data utility for differentially private datasets, which is beneficial for data analyzers in data mining