Spillover Effects of Airdrops: Evidence from Tokenization Platforms

The emergence of tokenization platforms based on blockchain technology has led to the use of free airdrop to replace traditional expensive financial incentives to enhance user engagement. However, critics argue that such incentives may devalue tokens and prompt nonrecipients to panic sell. To investigate the impact of airdrops, we conducted a quasi-experiment on Axie Infinity. Our findings indicate that airdrops significantly enhance engagement among both recipients and nonrecipients. Mechanism analysis shows that cross group spillover effects stems from expectation of another airdrop program and increased market liquidity. While recipients tend to immediately sell tokens and often sell more tokens than received, we did not find evidence of nonrecipients panic selling tokens. Furthermore, we investigated the heterogeneous effects of airdrops. Our work contributes to the ongoing debate of the effectiveness of airdrops and provide insights into the study of tokenization platforms

Lubrication Analysis of Journal Bearings in R410A Rotary Compressor

Understanding the state of lubrication in rotary compressors is of paramount importance for their reliability. This paper refers to an improvement of the lubrication in R410A rotary compressor. The lubricating conditions on the journal bearings can be evaluated by metallic contact that consists of measuring the electrical resistance between lubricated surfaces. The contact resistance can be used to indicate the degree of metal-to-metal contact between the sliding surfaces in the compressor. And some parameters of them are numerically analyzed. It is elucidated from the investigation that when unfavorable condition occurs, the metal contact between the journal and bearings become severe. And lubricating condition on the bearings in the compressor using high viscosity oil is better than that for the compressor using low viscosity

The interaction between copper species and pyrite surfaces in copper cyanide solutions

The adsorption of copper ions and the formation of a copper sulfide phase on pyrite surfaces are of vital importance to alter the surface property of pyrite and determine its fate either to be rejected in the flotation of polymetallic sulfide ores or to be recovered in the flotation of pyritic gold ores. Cyanide and copper may co-exist in the process water with complicated speciation. The objective of this study is to understand the interaction between copper cyanide species and pyrite and clarify the possible adsorption of copper on pyrite surfaces from cyanide-bearing solutions. Surface-enhanced Raman spectroscopy and electrochemical measurements were used to determine the reaction products formed on pyrite surfaces. It was found that Cu(I)-bearing species were incorporated into pyrite, forming a CuS-like sulfide from copper cyanide solutions at a more oxidizing potential, while a Cu2S-like sulfide formed at a more reducing potential. The amount of copper deposited on pyrite was significantly improved at a more reducing potential at which the pyrite surface tended to be FeS-like. In addition, these Cu(I)-sulfides on pyrite surfaces were dissolved by cyanide-bearing species at a high CN/Cu ratio, compromising the total amount of copper uptake

AI/ML for Beam Management in 5G-Advanced

In beamformed wireless cellular systems such as 5G New Radio (NR) networks, beam management (BM) is a crucial operation. In the second phase of 5G NR standardization, known as 5G-Advanced, which is being vigorously promoted, the key component is the use of artificial intelligence (AI) based on machine learning (ML) techniques. AI/ML for BM is selected as a representative use case. This article provides an overview of the AI/ML for BM in 5G-Advanced. The legacy non-AI and prime AI-enabled BM frameworks are first introduced and compared. Then, the main scope of AI/ML for BM is presented, including improving accuracy, reducing overhead and latency. Finally, the key challenges and open issues in the standardization of AI/ML for BM are discussed, especially the design of new protocols for AI-enabled BM. This article provides a guideline for the study of AI/ML-based BM standardization.Comment: 4 figure

Carbon emission abatement quota allocation in Chinese manufacturing industries:An integrated cooperative game data envelopment analysis approach

The Chinese government announced to cut its carbon emissions intensity by 60%–65% from its 2005 level. To realize the national abatement commitment, a rational allocation into its subunits (i.e. industries, provinces) is eagerly needed. Centralized allocation models can maximize the overall interests, but might cause implementation difficulty and fierce resistance from individual subunits. Based on this observation, this article will address the carbon emission abatement quota allocation problem from decentralized perspective, taking the competitive and cooperative relationships simultaneously into account. To this end, this article develops an integrated cooperative game data envelopment analysis (DEA) approach. We first investigate the relative efficiency evaluation by taking flexible carbon emission abatement allocation plans into account, and then define a super-additive characteristic function for developing a cooperative game among units. To calculate the nucleolus-based allocation plan, a practical computation procedure is developed based on the constraint generation mechanism. Further, we present a two-layer way to allocate the CO2 abatement quota into different sub-industries and further different provinces in Chinese manufacturing industries. The empirical results show that five sub-industries (Processing of petroleum, coking and processing of nuclear fuel; Smelting and pressing of ferrous metals; Manufacture of non-metallic mineral products; Manufacture of raw chemical materials and chemical product; Smelting and pressing of non-ferrous metals) and two provinces (Guangdong and Shandong) will be allocated more than 10% of the total national carbon emission abatement quota

Complete genome sequence of human astrovirus genotype 6

<p>Abstract</p> <p>Background</p> <p>Human astroviruses (HAstVs) are one of the important causes of acute gastroenteritis in children. Currently, eight HAstV genotypes have been identified and all but two (HAstV-6 and HAstV-7) have been fully sequenced. We here sequenced and analyzed the complete genome of a HAstV-6 strain (192-BJ07), which was identified in Beijing, China.</p> <p>Results</p> <p>The genome of 192-BJ07 consists of 6745 nucleotides. The 192-BJ07 strain displays a 77.2-78.0% nucleotide sequence identity with other HAstV genotypes and exhibits amino acid sequence identities of 86.5-87.4%, 94.2-95.1%, and 65.5-74.8% in the ORF1a, ORF1b, and ORF2 regions, respectively. Homological analysis of ORF2 shows that 192-BJ07 is 96.3% identical to the documented HAstV-6 strain. Further, phylogenetic analysis indicates that different genomic regions are likely undergoing different evolutionary and selective pressures. No recombination event was observed in HAstV-6 in this study.</p> <p>Conclusion</p> <p>The completely sequenced and characterized genome of HAstV-6 (192-BJ07) provides further insight into the genetics of astroviruses and aids in the surveillance and control of HAstV gastroenteritis.</p

Potential immune evasion of the severe acute respiratory syndrome coronavirus 2 Omicron variants

Coronavirus disease 2019 (COVID-19), which is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a global pandemic. The Omicron variant (B.1.1.529) was first discovered in November 2021 in specimens collected from Botswana, South Africa. Omicron has become the dominant variant worldwide, and several sublineages or subvariants have been identified recently. Compared to those of other mutants, the Omicron variant has the most highly expressed amino acid mutations, with almost 60 mutations throughout the genome, most of which are in the spike (S) protein, especially in the receptor-binding domain (RBD). These mutations increase the binding affinity of Omicron variants for the ACE2 receptor, and Omicron variants may also lead to immune escape. Despite causing milder symptoms, epidemiological evidence suggests that Omicron variants have exceptionally higher transmissibility, higher rates of reinfection and greater spread than the prototype strain as well as other preceding variants. Additionally, overwhelming amounts of data suggest that the levels of specific neutralization antibodies against Omicron variants decrease in most vaccinated populations, although CD4+ and CD8+ T-cell responses are maintained. Therefore, the mechanisms underlying Omicron variant evasion are still unclear. In this review, we surveyed the current epidemic status and potential immune escape mechanisms of Omicron variants. Especially, we focused on the potential roles of viral epitope mutations, antigenic drift, hybrid immunity, and “original antigenic sin” in mediating immune evasion. These insights might supply more valuable concise information for us to understand the spreading of Omicron variants