Identifying the orbital angular momentum of light based on atomic ensembles

We propose a scheme to distinguish the orbital angular momentum state of the Laguerre-Gaussian (LG) beam based on the electromagnetically induced transparency modulated by a microwave field in atomic ensembles. We show that the transverse phase variation of a probe beam with the LG mode can be mapped into the spatial intensity distribution due to the change of atomic coherence caused by the microwave. The proposal may provide a useful tool for studying higher-dimensional quantum information based on atomic ensembles.Comment: 4 pages, 4 figure

Benchmark data set and method for depth estimation from light field images

Convolutional neural networks (CNNs) have performed extremely well for many image analysis tasks. However, supervised training of deep CNN architectures requires huge amounts of labeled data, which is unavailable for light field images. In this paper, we leverage on synthetic light field images and propose a two-stream CNN network that learns to estimate the disparities of multiple correlated neighborhood pixels from their epipolar plane images (EPIs). Since the EPIs are unrelated except at their intersection, a two-stream network is proposed to learn convolution weights individually for the EPIs and then combine the outputs of the two streams for disparity estimation. The CNN estimated disparity map is then refined using the central RGB light field image as a prior in a variational technique. We also propose a new real world data set comprising light field images of 19 objects captured with the Lytro Illum camera in outdoor scenes and their corresponding 3D pointclouds, as ground truth, captured with the 3dMD scanner. This data set will be made public to allow more precise 3D pointcloud level comparison of algorithms in the future which is currently not possible. Experiments on the synthetic and real world data sets show that our algorithm outperforms existing state of the art for depth estimation from light field images

Effect of CO2 Stress Pretreatment and Electron Beam Irradiation on the Quality of NFC Apple Juice

The single processing technology is difficult to meet the multiple requirements of the NFC juice, such as maintaining the nutrition and flavor, reducing browning and sterilization. In order to explore the combined effect of stress pretreatment and sterilization technologies on NFC fruit juice, 50% CO2 stress pretreatment was used before apple juice squeezed to study the influence of different stress intensity on sensory quality and nutritional quality of apple juice. The effects of electron beam irradiation and pasteurization on sensory and nutritional quality and bacteriologic effect of apple juice were also studied. The results showed that: 50% CO2 stress pretreatment could significantly increase the total phenolic content, antioxidant activity and VC content of the NFC apple juice (P<0.05). Stored for 48 h, the total phenolic content and total antioxidant capacity of the 60 min stressed apple juice group were 118.7% and 104% of the control, respectively. Moreover, the CO2 stress treatment significantly decreased the browning degree of NFC juice (P<0.05). Compared with the control and pasteurized groups, the browning degree of 2 kGy irradiation group and 4 kGy irradiation group were significantly lower (P<0.05), the total phenolic content and aroma were also better maintained, among which the 4 kGy irradiation was more effective. In the same time, compared with the control group, the 2 kGy and 4 kGy electron beam irradiation groups had a significant antibacterial effect (P<0.05), which all met the requirements of the national standards. 50% CO2 stress pre-treatment combined with 4 kGy electron beam irradiation sterilization can be used as a new NFC apple juice processing technique

Solution Growth and Thermal Treatment of Crystals Lead to Two New Forms of 2-((2,6-Dimethylphenyl)Amino)Benzoic Acid

We report the discovery of two new forms (II and III) of a potential non-steroidal anti-inflammatory and thyroid drug, 2-((2,6-dimethylphenyl)amino)benzoic acid (HDMPA) through solution growth and thermal treatment of crystals. Form II has been discovered through crystal growth in a variety of solvents, and characterized by single-crystal X-ray diffraction, powder X-ray diffraction (PXRD), FT-IR, and Raman spectroscopy. Form II converts into form III upon thermal treatment, as indicated by the phase behavior study of form II with differential scanning calorimetry (DSC). Form III has been characterized by IR, Raman and PXRD. Conformational flexibility of the molecule seems to lead to the polymorphism of the system. A conformational scan shows the conformational minima correspond to the conformers in the polymorphs. Lattice energy calculations show energies of −48.14 and −50.31 kcal mol−1 for forms I and II, providing information on the relative stability for each form. Hirshfeld analysis revealed that intermolecular interactions such as C⋯C, H⋯H, C⋯H, and H⋯O contribute to the stability of the crystal forms

Architecture engineering of carbonaceous anodes for high‐rate potassium‐ion batteries

The limited lithium resource in earth's crust has stimulated the pursuit of alternative energy storage technologies to lithium‐ion battery. Potassium‐ion batteries (KIBs) are regarded as a kind of promising candidate for large‐scale energy storage owing to the high abundance and low cost of potassium resources. Nevertheless, further development and wide application of KIBs are still challenged by several obstacles, one of which is their fast capacity deterioration at high rates. A considerable amount of effort has recently been devoted to address this problem by developing advanced carbonaceous anode materials with diverse structures and morphologies. This review presents and highlights how the architecture engineering of carbonaceous anode materials gives rise to high‐rate performances for KIBs, and also the beneficial conceptions are consciously extracted from the recent progress. Particularly, basic insights into the recent engineering strategies, structural innovation, and the related advances of carbonaceous anodes for high‐rate KIBs are under specific concerns. Based on the achievements attained so far, a perspective on the foregoing, and proposed possible directions, and avenues for designing high‐rate anodes, are presented finally

LLM-Mini-CEX: Automatic Evaluation of Large Language Model for Diagnostic Conversation

There is an increasing interest in developing LLMs for medical diagnosis to improve diagnosis efficiency. Despite their alluring technological potential, there is no unified and comprehensive evaluation criterion, leading to the inability to evaluate the quality and potential risks of medical LLMs, further hindering the application of LLMs in medical treatment scenarios. Besides, current evaluations heavily rely on labor-intensive interactions with LLMs to obtain diagnostic dialogues and human evaluation on the quality of diagnosis dialogue. To tackle the lack of unified and comprehensive evaluation criterion, we first initially establish an evaluation criterion, termed LLM-specific Mini-CEX to assess the diagnostic capabilities of LLMs effectively, based on original Mini-CEX. To address the labor-intensive interaction problem, we develop a patient simulator to engage in automatic conversations with LLMs, and utilize ChatGPT for evaluating diagnosis dialogues automatically. Experimental results show that the LLM-specific Mini-CEX is adequate and necessary to evaluate medical diagnosis dialogue. Besides, ChatGPT can replace manual evaluation on the metrics of humanistic qualities and provides reproducible and automated comparisons between different LLMs