Research on Consumers\u27 Buying Behavior in the Context of Helping Farmers Live”: Based on the Dual Role of Economic Rationality and Normative Rationality

As the digital economy has become an important driving force for a new round of global industrial change, live ecommerce has become a new outlet, and the agriculture assisted live broadcasting has emerged. This paper combs the existing literature and combines the characteristics of agriculture assisted live broadcasting to get a theoretical research model of consumers\u27 purchasing behavior in the context of assisted farmer direct broadcast . Using questionnaire survey method to collect data for empirical analysis, the research found that consumers’ perceived risk negatively affects purchase intention; efficacy positively affects purchase intention; consumer purchase intention positively affects purchase behavior; consumer perceived value and social norms have no significant effect on purchase intention. Finally, this article makes suggestions for businesses and relevant departments of the live broadcast industry

Impact of Corporate Social Responsibility on Consumers\u27 Purchase Behavior in the E-commerce Environment

The development of the Internet has promoted the prosperity of e-commerce, and has a great impact on today\u27s consumers\u27 consumption concepts. For e-commerce platform, this is not only an opportunity, but also a challenge. If we gain advantages in the fierce competition environment, it will become the leader in the e-commerce environment. Corporate social responsibility has a significant impact on the operation and development of enterprises. With the increasing attention of society to corporate social responsibility, social responsibility is gradually becoming an important factor in determining the value of enterprises, which is also the case for e-commerce platforms. In order to provide a new way for the development of e-commerce platform, this paper analyzes the impact of corporate social responsibility on consumer purchasing behavior, and discusses the significance of corporate social responsibility on e-commerce platform

Rethinking pulmonary toxicity in advanced non-small cell lung cancer in the era of combining anti-PD-1/PD-L1 therapy with thoracic radiotherapy.

The combination of programmed cell death 1/programmed cell death ligand 1 blockade and thoracic radiotherapy has become the new standard of care in the treatment of locally advanced non-small-cell lung cancer. The information regarding the pulmonary safety of such therapy remains limited to mostly retrospective studies and case reports with a small portion of data from prospective clinical trials. By analyzing the underlying mechanisms of interactions between radiation and immunotherapy from preclinical data and summarizing safety data from relevant clinical studies with pulmonary toxicity, we believe that longer and rigorous follow-up is warranted, to determine if the combination of such modalities is appropriate for patients without risking undue toxicity

MEV Makes Everyone Happy under Greedy Sequencing Rule

Trading through decentralized exchanges (DEXs) has become crucial in today's blockchain ecosystem, enabling users to swap tokens efficiently and automatically. However, the capacity of miners to strategically order transactions has led to exploitative practices (e.g., front-running attacks, sandwich attacks) and gain substantial Maximal Extractable Value (MEV) for their own advantage. To mitigate such manipulation, Ferreira and Parkes recently proposed a greedy sequencing rule such that the execution price of transactions in a block moves back and forth around the starting price. Utilizing this sequencing rule makes it impossible for miners to conduct sandwich attacks, consequently mitigating the MEV problem. However, no sequencing rule can prevent miners from obtaining risk-free profits. This paper systemically studies the computation of a miner's optimal strategy for maximizing MEV under the greedy sequencing rule, where the utility of miners is measured by the overall value of their token holdings. Our results unveil a dichotomy between the no trading fee scenario, which can be optimally strategized in polynomial time, and the scenario with a constant fraction of trading fee, where finding the optimal strategy is proven NP-hard. The latter represents a significant challenge for miners seeking optimal MEV. Following the computation results, we further show a remarkable phenomenon: Miner's optimal MEV also benefits users. Precisely, in the scenarios without trading fees, when miners adopt the optimal strategy given by our algorithm, all users' transactions will be executed, and each user will receive equivalent or surpass profits compared to their expectations. This outcome provides further support for the study and design of sequencing rules in decentralized exchanges.Comment: 14 Pages, ACM CCS Workshop on Decentralized Finance and Security (DeFi'23

The epidermal growth factor receptor (EGFR) is proteolytically modified by the Matriptase–Prostasin serine protease cascade in cultured epithelial cells

AbstractProstasin is expressed at the apical surface of normal epithelial cells and suppresses in vitro invasion of cancer cells. Prostasin re-expression in the PC-3 prostate carcinoma cells down-regulated the epidermal growth factor receptor (EGFR) protein expression and EGF-induced phosphorylation of the extracellular signal-regulated kinases (Erk1/2). We report here that prostasin and its activating enzyme matriptase are capable of inducing proteolytic cleavages in the EGFR extracellular domain (ECD) when co-expressed in the FT-293 cells, generating two amino-terminally truncated fragments EGFR135 and EGFR110, at 135 and 110 kDa. Prostasin's role in EGFR cleavage is dependent on the serine active-site but not the GPI-anchor. The modifications of EGFR were confirmed to be on the primary structure by deglycosylation. EGFR135 and EGFR110 are not responsive to EGF stimulation, indicating loss of the ligand-binding domains. EGFR110 is constitutively phosphorylated and in its presence Erk1/2 phosphorylation is increased in the absence of EGF. The protease-induced EGFR cleavages are not dependent on EGFR phosphorylation. The EGFR ECD proteolytic modification by matriptase–prostasin is also observed in the BEAS-2B normal lung epithelial cells, the BPH-1 benign prostate hyperplasia and the MDA-MB-231 breast cancer cell lines; and represents a novel mechanism for epithelial cells to modulate EGF-EGFR signaling

Characterizing CDK8/19 Inhibitors through a NFκB-Dependent Cell-Based Assay

Cell-based assays for CDK8/19 inhibition are not easily defined, since there are no known cellular functions unique to these kinases. To solve this problem, we generated derivatives of 293 cells with CRISPR knockout of one or both of CDK8 and CDK19. Double knockout (dKO) of CDK8 and CDK19 together (but not individually) decreased the induction of transcription by NFκB (a CDK8/19-potentiated transcription factor) and abrogated the effect of CDK8/19 inhibitors on such induction. We generated wild type (WT) and dKO cell lines expressing luciferase from an NFκB-dependent promoter. Inhibitors selective for CDK8/19 over other CDKs decreased TNFα-induced luciferase expression in WT cells by ~80% with no effect on luciferase induction in dKO cells. In contrast, non-selective CDK inhibitors flavopiridol and dinaciclib and a CDK7/12/13 inhibitor THZ1 (but not CDK4/6 inhibitor palbociclib) suppressed luciferase induction in both WT and dKO cells, indicating a distinct role for other CDKs in the NFκB pathway. We used this assay to characterize a series of thienopyridines with in vitro bone anabolic activity, one of which was identified as a selective CDK8/19 inhibitor. Thienopyridines inhibited luciferase induction in the WT but not dKO cells and their IC50 values in the WT reporter assay showed near-perfect correlation (R2 = 0.98) with their reported activities in a bone anabolic activity assay, confirming that the latter function is mediated by CDK8/19 and validating our assay as a robust and quantitative method for CDK8/19 inhibition

Decentralized Funding of Public Goods in Blockchain System:Leveraging Expert Advice

Public goods projects, such as open-source technology, are essential for the blockchain ecosystem's growth. However, funding these projects effectively remains a critical issue within the ecosystem. Currently, the funding protocols for blockchain public goods lack professionalism and fail to learn from past experiences. To address this challenge, our research introduces a human oracle protocol involving public goods projects, experts, and funders. In our approach, funders contribute investments to a funding pool, while experts offer investment advice based on their expertise in public goods projects. The oracle's decisions on funding support are influenced by the reputations of the experts. Experts earn or lose reputation based on how well their project implementations align with their advice, with successful investments leading to higher reputations. Our oracle is designed to adapt to changing circumstances, such as experts exiting or entering the decision-making process. We also introduce a regret bound to gauge the oracle's effectiveness. Theoretically, we establish an upper regret bound for both static and dynamic models and demonstrate its closeness to an asymptotically equal lower bound. Empirically, we implement our protocol on a test chain and show that our oracle's investment decisions closely mirror optimal investments in hindsight

Decentralized Funding of Public Goods in Blockchain System:Leveraging Expert Advice

Public goods projects, such as open-source technology, are essential for the blockchain ecosystem's growth. However, funding these projects effectively remains a critical issue within the ecosystem. Currently, the funding protocols for blockchain public goods lack professionalism and fail to learn from past experiences. To address this challenge, our research introduces a human oracle protocol involving public goods projects, experts, and funders. In our approach, funders contribute investments to a funding pool, while experts offer investment advice based on their expertise in public goods projects. The oracle's decisions on funding support are influenced by the reputations of the experts. Experts earn or lose reputation based on how well their project implementations align with their advice, with successful investments leading to higher reputations. Our oracle is designed to adapt to changing circumstances, such as experts exiting or entering the decision-making process. We also introduce a regret bound to gauge the oracle's effectiveness. Theoretically, we establish an upper regret bound for both static and dynamic models and demonstrate its closeness to an asymptotically equal lower bound. Empirically, we implement our protocol on a test chain and show that our oracle's investment decisions closely mirror optimal investments in hindsight