Successful Features of Crowdfunding Campaigns: An Analysis of Requests for Coronavirus Food Relief

Crowdfunding is an emerging industry in the past decades, which proliferates and has attracted an enormous population from the public to be involved in various funding projects in multiple fields such as business entrepreneurship, healthcare, and fintech. Meanwhile, charitable crowdfunding platforms such as GoFundMe, Indiegogo, and Kickstarter have allowed internet users to provide help and donation to the fundraisers directly. As the year 2020 is surrounded by the COVID-19 global pandemic spreading out the world, the topic of coronavirus relief has surged. Thus, it is worthy of evaluating the crowdfunding campaign\u27s effectiveness during the coronavirus context by making a connection between fundraising activities and coronavirus relief. This paper aims to investigate the effects of various factors affecting a donation-based crowdfunding campaign for coronavirus relief of food donation in the United States and determine the significant factors affecting the campaign\u27s success rate. To achieve this research purpose, secondary data were extensively collected from the crowdfunding platform GoFundMe for regression analysis. The sample data was derived from crowdfunding campaigns launched from March 1st, 2020, to May 31st, 2020. During this period, the United States was severely affected by the COVID-19 pandemic with an exponentially surged number of confirmed cases. This paper derives the independent variables that have been examined from previous studies and further applies in the coronavirus context to identify whether these factors are significant influencers to the success of crowdfunding campaigns for coronavirus relief of food donation. The factors being examined include target funding amount, the existence of spelling mistakes, the presence of pictures, video, social network sites, project updates, comments between fundraisers and backers, and links to external websites. That the significant factors contributing to a successful funding project are similar, as identified in previous reward-based and equity crowdfunding studies. On the other hand, several independent variables\u27 effectiveness varied between the normal scenario and the coronavirus context, as such variables demonstrate a much compelling role to attract donors for the coronavirus relief activations. The analysis is valuable and worthy of different viewpoints. First, understanding the donor\u27s motivation and the success features of funding projects is valuable for fundraisers to have a strategic mindset for decision-making criteria when initiating funding projects to attract more donors and the amount of money. Second, because of the lack of literature focusing on examining the success features for donation-based crowdfunding campaigns, this study fills the gap and further focus on the crowdfunding activations in the context of coronavirus food relief in the US. Therefore, this study provides significant insight to understand the dynamics of the donation-based crowdfunding campaign and provides a recommendation to develop coronavirus relief more efficiently

Spectrally narrowed edge emission from leaky waveguide modes in organic light-emitting diodes

A dramatic spectral line narrowing of the edge emission at room temperature from tris(quinolinolate) Al (Alq3), N,N′-diphenyl-N,N′-bis(1-naphthylphenyl)-1,1′-biphenyl-4,4′-diamine (NPD), 4,4′-bis(2,2′-diphenyl-vinyl)-,1′-biphenyl (DPVBi), and some guest-host small molecular organic light-emitting diodes(OLEDs), fabricated on indium tin oxide (ITO)-coated glass, is described. In all but the DPVBi OLEDs, the narrowed emission band emerges above a threshold thickness of the emitting layer, and narrows down to a full width at half maximum of only 5–10 nm. The results demonstrate that this narrowed emission is due to irregular waveguide modes that leak from the ITO to the glass substrate at a grazing angle. While measurements of variable stripe length l devices exhibit an apparent weak optical gain 0≤g≤1.86 cm−1, there is no observable threshold current or bias associated with this spectral narrowing. In addition, in the phosphorescent guest-host OLEDs, there is no decrease in the emission decay time of the narrowed edge emission relative to the broad surface emission. It is suspected that the apparent weak optical gain is due to misalignment of the axis of the waveguided mode and the axis of the collection lens of the probe. However, it is not clear if such a misalignment can account for all the effects of the observed evolution of the edge-emission spectra with l

Spectrally narrowed edge emission from organic light-emitting diodes

A dramatic spectrally narrowed edge emission (SNEE) from small molecular organic light-emitting diodes at room temperature, with a full width at half maximum of 5–10nm, is described. The results show that this emission is due to irregular waveguide modes that leak from the indium tin oxide anode to the glass substrate at a grazing angle. Measurements of variable stripe length devices exhibit an apparent weak optical gain, but there is no observable threshold bias associated with this SNEE. Hence this apparent “optical gain” is suspected to result from misalignment of the propagating leaky waveguide mode and the collecting optics

an software vulnerability number prediction model based on micro-parameters

全球每年因为软件漏洞造成的损失十分巨大,而软件漏洞分析方法的缺陷使得漏洞本身难以被发现,因此大家开始对漏洞数量进行预测,预测软件的漏洞数量对信息安全评估有着重要的意义.目前主要的估算方法是漏洞密度的方法,但此方法仅是宏观范围内估算,并不能反映漏洞软件本身的性质.提出从软件的微观角度进行软件漏洞数量的估算通过提取软件典型微观参数,从而发现软件漏洞数量与其微观参数的联系,相比漏洞密度的预测方法具有相当的优势.软件微观漏洞模型在提出漏洞继承假设的基础上,认为软件的漏洞数量与它的某些微观参数之间存在线性关系,并给出了根据软件微观参数以及其历史版本漏洞数据预测软件漏洞数量的方法.通过对7款软件进行验证,证明了软件微观漏洞模型在预测软件漏洞数量时的有效性与准确性.As the cost caused by software vulnerabilities keeps increasing, people pay more and more attention to the researches on the vulnerability. Although discovering vulnerability is difficult because of the defect of vulnerability analysis, to predict the number of vulnerabilities is very useful in some domain, such as information security assessment. At present, the main methods to estimate the density of the vulnerabilities focus on the macro level, but they can not reflect the essential of vulnerability. A prediction model based on micro-parameter is proposed to predict the number of vulnerability with the micro-parameters of software, and it extracts the typical micro-parameters from some software series for the purpose of discovering the relationship between the vulnerability number and micro-parameters. With the hypothesis of vulnerability inheriting, the prediction model abstracts the micro-parameters from software and tries to find a linear relationship between the vulnerability number and some micro-parameters. This model also gives a method to predict the vulnerability number of software with its micro-parameters and the vulnerability number of its previous versions. This method is verified with 7 software series, and the results show the prediction model is effective

Synthesis and Promotion of the Osteoblast Proliferation Effect of Morroniside Derivatives

Sambucus williamsii Hance has been used in fractures for thousands of years, but research on its active components, such as morroniside, until now had not been carried out. In this study, morroniside was taken as the leading compound, and fourteen derivatives were synthesized. The promotion of osteoblast proliferation effect of the derivatives was evaluated on MC3T3-E1 cells. Five derivatives (2, 3, 4, 5, and 14) showed a good proliferation effect on MC3T3-E1 cells, and their promoted expression effects on OC (Osteocalcin) and ALP (Alkaline phosphatase) in MC3T3-E1 cells were measured. Compound 3 was shown to have the strongest proliferation effect (EC50 = 14.78 ± 1.17 μg/mL) and to significantly promote the expression of OC and ALP