Oracle Counterpoint: Relationships between On-chain and Off-chain Market Data

We investigate the theoretical and empirical relationships between activity in on-chain markets and pricing in off-chain cryptocurrency markets (e.g., ETH/USD prices). The motivation is to develop methods for proxying off-chain market data using data and computation that is in principle verifiable on-chain and could provide an alternative approach to blockchain price oracles. We explore relationships in PoW mining, PoS validation, block space markets, network decentralization, usage and monetary velocity, and on-chain liquidity pools and AMMs. We select key features from these markets, which we analyze through graphical models, mutual information, and ensemble machine learning models to explore the degree to which off-chain pricing information can be recovered entirely on-chain. We find that a large amount of pricing information is contained in on-chain data, but that it is generally hard to recover precise prices except on short time scales of retraining the model. We discuss how even a noisy trustless data source such as this can be helpful toward minimizing trust requirements of oracle designs

Rethinking Multi-Modal Alignment in Video Question Answering from Feature and Sample Perspectives

Reasoning about causal and temporal event relations in videos is a new destination of Video Question Answering (VideoQA).The major stumbling block to achieve this purpose is the semantic gap between language and video since they are at different levels of abstraction. Existing efforts mainly focus on designing sophisticated architectures while utilizing frame- or object-level visual representations. In this paper, we reconsider the multi-modal alignment problem in VideoQA from feature and sample perspectives to achieve better performance. From the view of feature,we break down the video into trajectories and first leverage trajectory feature in VideoQA to enhance the alignment between two modalities. Moreover, we adopt a heterogeneous graph architecture and design a hierarchical framework to align both trajectory-level and frame-level visual feature with language feature. In addition, we found that VideoQA models are largely dependent on language priors and always neglect visual-language interactions. Thus, two effective yet portable training augmentation strategies are designed to strengthen the cross-modal correspondence ability of our model from the view of sample. Extensive results show that our method outperforms all the state-of-the-art models on the challenging NExT-QA benchmark, which demonstrates the effectiveness of the proposed method

Deep Clustering: A Comprehensive Survey

Cluster analysis plays an indispensable role in machine learning and data mining. Learning a good data representation is crucial for clustering algorithms. Recently, deep clustering, which can learn clustering-friendly representations using deep neural networks, has been broadly applied in a wide range of clustering tasks. Existing surveys for deep clustering mainly focus on the single-view fields and the network architectures, ignoring the complex application scenarios of clustering. To address this issue, in this paper we provide a comprehensive survey for deep clustering in views of data sources. With different data sources and initial conditions, we systematically distinguish the clustering methods in terms of methodology, prior knowledge, and architecture. Concretely, deep clustering methods are introduced according to four categories, i.e., traditional single-view deep clustering, semi-supervised deep clustering, deep multi-view clustering, and deep transfer clustering. Finally, we discuss the open challenges and potential future opportunities in different fields of deep clustering

Improvement of the Magnetic Properties of Nanocrystalline Nd 12.3

Nd12.3−xDyxFe81.7Zr0.8Nb0.8Cu0.4B6.0  (x=0–2.5) ribbons have been prepared by melt-spun at 30 m/s and subsequent annealing. The influence of addition of Dy on the crystallization behavior, magnetic properties, and microstructure were investigated. Differential scanning calorimeter (DSC) and X-ray diffraction (XRD) revealed a single-phase material. Microstructure studies using transmission electron microscopy (TEM) had shown a significant microstructure refinement with Dy addition. Wohlfarth’s analysis showed that the exchange coupling interactions increased first with Dy content x increasing, reached the maximum value at x=0.5, and then slightly decreased with x further increasing. Optimal magnetic properties with Jr=1.09 T, Hci=1048 kA/m, and BHmax=169.5 kJ/m3 are achieved by annealing the melt-spun ribbons with x=0.5 at% at 700°C for 10 min

Targeting PELP1 Attenuates Angiogenesis and Enhances Chemotherapy Efficiency in Colorectal Cancer

SIMPLE SUMMARY: Excessive angiogenesis is a distinct feature of colorectal cancer (CRC) and plays a pivotal role in tumor development and metastasis. Therefore, it is essential to clarify the underlying mechanism of angiogenesis. In this study, we found that the level of proline-, glutamic acid, and leucine-rich protein 1 (PELP1) was positively correlated with microvessel density (MVD). In vitro and in vivo assays further showed PELP1 regulated angiogenesis via the Signal transducer and activator of transcription 3 (STAT3)/Vascular endothelial growth factor (VEGFA). Notably, we found that inhibition of PELP1 enhanced the efficacy of chemotherapy due to vascular normalization. Thus, targeting of PELP1 may be a potentially therapeutic strategy for CRC. ABSTRACT: Abnormal angiogenesis is one of the important hallmarks of colorectal cancer as well as other solid tumors. Optimally, anti-angiogenesis therapy could restrain malignant angiogenesis to control tumor expansion. PELP1 is as a scaffolding oncogenic protein in a variety of cancer types, but its involvement in angiogenesis is unknown. In this study, PELP1 was found to be abnormally upregulated and highly coincidental with increased MVD in CRC. Further, treatment with conditioned medium (CM) from PELP1 knockdown CRC cells remarkably arrested the function of human umbilical vein endothelial cells (HUVECs) compared to those treated with CM from wildtype cells. Mechanistically, the STAT3/VEGFA axis was found to mediate PELP1-induced angiogenetic phenotypes of HUVECs. Moreover, suppression of PELP1 reduced tumor growth and angiogenesis in vivo accompanied by inactivation of STAT3/VEGFA pathway. Notably, in vivo, PELP1 suppression could enhance the efficacy of chemotherapy, which is caused by the normalization of vessels. Collectively, our findings provide a preclinical proof of concept that targeting PELP1 to decrease STAT3/VEGFA-mediated angiogenesis and improve responses to chemotherapy due to normalization of vessels. Given the newly defined contribution to angiogenesis of PELP1, targeting PELP1 may be a potentially ideal therapeutic strategy for CRC as well as other solid tumors

COVID-19 Shock and the Time-Varying Volatility Spillovers Among the Energy and Precious Metals Markets: Evidence From A DCC-GARCH-CONNECTEDNESS Approach

The outbreak of the COVID-19 epidemic intensified the volatility of commodity markets (the energy and precious metals markets), which created a significant negative impact on the volatility spillovers among these markets. It may also have triggered a new volatility risk contagion. In this paper, we introduce the DCC-GARCH-CONNECTEDNESS approach to explore the volatility spillover level and multi-level spillover structure characteristics among the commodity markets before and during the COVID-19 epidemic in order to clarify the new volatility risk contagion patterns across the markets. The results implied several conclusions. (i) The COVID-19 epidemic has significantly improved the total volatility spillover level of the energy and precious metals markets and has enhanced the risk connectivity among the markets. (ii) The COVID-19 epidemic has amplified the volatility of the crude oil market, making it the main volatility spillover market, namely the source of volatility risk contagion. (iii) The COVID-19 epidemic outbreak enhanced the external risk absorption capacity of the natural gas and silver markets, and the absorption level of the external volatility spillover improved significantly. Furthermore, the risk absorption capacity of the gold market weakened, while the gold market has remained the endpoint of external volatility risk during the epidemic and has acted as a risk stabilizer. (iv) The volatility spillover among markets has clear time-varying characteristics and a positive connectedness with the severity of the COVID-19 epidemic. As the severity of the COVID-19 epidemic increases, the volatility risk connectivity among the markets rapidly increases

Design and optimization of an advanced time-of-flight neutron spectrometer for deuterium plasmas of the large helical device

A time-of-flight neutron spectrometer based on the Time-Of-Flight Enhanced Diagnostic (TOFED) concept has been designed and is under development for the Large Helical Device (LHD). It will be the first advanced neutron spectrometer to measure the 2.45 MeV D–D neutrons (DDNs) from helical/stellarator plasmas. The main mission of the new TOFED is to study the supra-thermal deuterons generated from the auxiliary heating systems in helical plasmas by measuring the time-of-flight spectra of DDN. It will also measure the triton burnup neutrons (TBNs) from the d+t reactions, unlike the original TOFED in the EAST tokamak. Its capability of diagnosing the TBN ratios is evaluated in this work. This new TOFED is expected to be installed in the basement under the LHD hall and shares the collimator with one channel of the vertical neutron camera to define its line of sight. The distance from its primary scintillators to the equatorial plane of LHD plasmas is about 15.5 m. Based on Monte Carlo simulation by a GEANT4 model, the resolution of the DDN energy spectra is 6.6%. When projected onto the neutron rates that are typically obtained in LHD deuterium plasmas (an order of 1015 n/s with neutral beam injection), we expect to obtain the DDN and TBN counting rates of about 2.5 · 105 counts/s and 250 counts/s, respectively. This will allow us to analyze the DDN time-of-flight spectra on time scales of 0.1 s and diagnose the TBN emission rates in several seconds with one instrument, for the first time in helical/stellarator plasmas

Improved design of transient power sharing strategy for AES multi-gensets in response to high power load mutation

The Medium Voltage Direct Current (MVDC) Integrated Power System (IPS) represents the developing trend of marine ship power. It facilitates the provision of high quality energy for weaponry, however, high power load switching will have a severe impact on power system as well as on gas turbine gensets, which is a critical problem needs to be solved urgently. In this paper, based on the traditional IPS hierarchical control strategy, an improved design method of transient power sharing is proposed for multi-gensets operation. Firstly, by analyzing the transient fluctuation process of voltage and speed, the law of system energy coupling transfer is illustrated and a strategy of equalizing torque impact is proposed. Then, a set of speed compensation factors is introduced to achieve the equalization of transient speed regulation (TSR). Finally, the effectiveness of the proposed improved control strategy is verified by MATLAB/Simulink simulation. Compared to before the improvement, the gensets operate away from the limiting boundary of bearing torque impact and speed deviation, and the bus voltage stability is also enhanced