Ferromagnetic InMnAs on InAs Prepared by Ion Implantation and Pulsed Laser Annealing

Ferromagnetic InMnAs has been prepared by Mn ion implantation and pulsed laser annealing. The InMnAs layer reveals a saturated magnetization of 2.6 mu_B/Mn at 5 K and a perpendicular magnetic anisotropy. The Curie temperature is determined to be 46 K, which is higher than those in previous reports with similar Mn concentrations. Ferromagnetism is further evidenced by the large magnetic circular dichroism.Comment: 9 pages, 3 figure

The relationships between silver price, gold price and U.S. dollar index before and after the subprime crisis

1 online resource (v, 53 leaves) : ill.Includes abstract.Includes bibliographical references (leaves 50-53).This paper analyzes the relationship betweensilver price, gold price and U.S. dollar index and its change before and after the U.S. subprime mortgage crisis,especially focusing on the dynamics of silver price. The data used covers a period from January 2, 1986 to January 31, 2012. The methodology in this study includes cointegrated VAR model and Granger causality test. The findings show that there is a cointegration relationship between the three variables and silver price is unidirectionally Granger caused by the other two variables before the subprime crisis but such relationship has weakened after the subprime crisis

Open Science Practices are on the Rise: The State of Social Science (3S) Survey

Has there been meaningful movement toward open sci-ence practices within the social sciences in recent years? Discussions about changes in practices such as posting data and pre-registering analyses have been marked by controversy—including controversy over the extent to which change has taken place. This study, based on the State of Social Science (3S) Survey, provides the first com-prehensive assessment of awareness of, attitudes towards, perceived norms regarding, and adoption of open science practices within a broadly representative sample of scholars from four major social science disciplines: economics, political science, psychology, and so-ciology. We observe a steep increase in adoption: as of 2017, over 80% of scholars had used at least one such practice, rising from one quarter a decade earlier. Attitudes toward research transpar-ency are on average similar between older and younger scholars, but the pace of change di˙ers by field and methodology. According with theories of normal science and scientific change, the timing of increases in adoption coincides with technological innovations and institutional policies. Patterns are consistent with most scholars underestimating the trend toward open science in their discipline

Measuring the boundary gapless state and criticality via disorder operator

The disorder operator is often designed to reveal the conformal field theory (CFT) information in the quantum many-body system. By using large-scale quantum Monte Carlo simulation, we study the scaling behavior of disorder operator on the boundary in the two-dimensional Heisenberg model on the square-octagon lattice with gapless topological edge state. In the Affleck-Kennedy-Lieb-Tasaki (AKLT) phase, the disorder operator is shown to hold the perimeter scaling with a logarithmic term associated with the Luttinger Liquid parameter K. This effective Luttinger Liquid parameter K reflects the low energy physics and CFT for (1+1)d boundary. At bulk critical point, the effective K is suppressed but keep finite value, indicating the coupling between the gapless edge state and bulk fluctuation. The logarithmic term numerically capture this coupling picture, which reveals the (1+1)d SU(2)_1 CFT and (2+1)d O(3) CFT at boundary criticality. Our work paves a new way to study the exotic boundary state and boundary criticality.Comment: 8 Pages,7 figure

Innate Immune Cells: A Potential and Promising Cell Population for Treating Osteosarcoma

Advanced, recurrent, or metastasized osteosarcomas remain challenging to cure or even alleviate. Therefore, the development of novel therapeutic strategies is urgently needed. Cancer immunotherapy has greatly improved in recent years, with options including adoptive cellular therapy, vaccination, and checkpoint inhibitors. As such, immunotherapy is becoming a potential strategy for the treatment of osteosarcoma. Innate immunocytes, the first line of defense in the immune system and the bridge to adaptive immunity, are one of the vital effector cell subpopulations in cancer immunotherapy. Innate immune cell-based therapy has shown potent antitumor activity against hematologic malignancies and some solid tumors, including osteosarcoma. Importantly, some immune checkpoints are expressed on both innate and adaptive immune cells, modulating their functions in tumor immunity. Therefore, blocking or activating immune checkpoint-mediated downstream signaling pathways can improve the therapeutic effects of innate immune cell-based therapy. In this review, we summarize the current status and future prospects of innate immune cell-based therapy for the treatment of osteosarcoma, with a focus on the potential synergistic effects of combination therapy involving innate immunotherapy and immune checkpoint inhibitors/oncolytic viruses

The heme-p53 interaction: Linking iron metabolism to p53 signaling and tumorigenesis

Recently, we reported that heme binds to tumor suppressor p53 protein (TP53, best known as p53) and promotes its nuclear export and cytosolic degradation, whereas iron chelation stabilizes p53 protein and suppresses tumors in a p53-dependent manner. This not only provides mechanistic insights into tumorigenesis associated with iron excess, but also helps guide the administration of chemotherapy based on iron deprivation in the clinic

Is Underwater Image Enhancement All Object Detectors Need?

Underwater object detection is a crucial and challenging problem in marine engineering and aquatic robot. The difficulty is partly because of the degradation of underwater images caused by light selective absorption and scattering. Intuitively, enhancing underwater images can benefit high-level applications like underwater object detection. However, it is still unclear whether all object detectors need underwater image enhancement as pre-processing. We therefore pose the questions "Does underwater image enhancement really improve underwater object detection?" and "How does underwater image enhancement contribute to underwater object detection?". With these two questions, we conduct extensive studies. Specifically, we use 18 state-of-the-art underwater image enhancement algorithms, covering traditional, CNN-based, and GAN-based algorithms, to pre-process underwater object detection data. Then, we retrain 7 popular deep learning-based object detectors using the corresponding results enhanced by different algorithms, obtaining 126 underwater object detection models. Coupled with 7 object detection models retrained using raw underwater images, we employ these 133 models to comprehensively analyze the effect of underwater image enhancement on underwater object detection. We expect this study can provide sufficient exploration to answer the aforementioned questions and draw more attention of the community to the joint problem of underwater image enhancement and underwater object detection. The pre-trained models and results are publicly available and will be regularly updated. Project page: https://github.com/BIGWangYuDong/lqit/tree/main/configs/detection/uw_enhancement_affect_detection.Comment: 17 pages, 9 figure

Against The Achilles' Heel: A Survey on Red Teaming for Generative Models

Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safety issues as various vulnerabilities are exposed. Faced with the problem, the field of red teaming is experiencing fast-paced growth, which highlights the need for a comprehensive organization covering the entire pipeline and addressing emerging topics for the community. Our extensive survey, which examines over 120 papers, introduces a taxonomy of fine-grained attack strategies grounded in the inherent capabilities of language models. Additionally, we have developed the searcher framework that unifies various automatic red teaming approaches. Moreover, our survey covers novel areas including multimodal attacks and defenses, risks around multilingual models, overkill of harmless queries, and safety of downstream applications. We hope this survey can provide a systematic perspective on the field and unlock new areas of research