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Funding and service provision are fundamental tenets of nonprofit organizations in Singapore. The advent of the COVID-19 pandemic has challenged the resilience of the nonprofit sector and beckoned the government to respond with digitalization programs that blend into the innovative capacity of the nonprofit sector. Consequently, digitalization has produced different versions of innovation that have helped tide nonprofits over this difficult time, in which crowdfunding has played an important role. In this article, we use two case studies to examine how nonprofits approach and situate crowdfunding in Singapore against the backdrop of the pandemic. One organization utilizes crowdfunding as the core of their fundraising model and views it as an essential part of their operation. During the pandemic, they even used this crowdfunding model to reach marginalized communities that tend not to be the target beneficiaries of the registered nonprofit organizations in Singapore. The other organization finds itself innovating within existing fundraising mechanisms, though it has experimented with crowdfunding. We argue that this case represents the strategy that most nonprofits are using during the pandemic by developing new and existing digital programs to attract potential donors. At the core of our argument, crowdfunding has the potential to expand the type of services and reach communities that tend to be overlooked or forgotten by present nonprofit structures in Singapore. By doing so, crowdfunding provides an outlet for these groups to voice their issues.

The main purpose of the present study is to apply three classification models, namely, the index of entropy (IOE) model, the logistic regression (LR) model, and the support vector machine (SVM) model by radial basis function (RBF), to produce landslide susceptibility maps for the Fugu County of Shaanxi Province, China. Firstly, landslide locations were extracted from field investigation and aerial photographs, and a total of 194 landslide polygons were transformed into points to produce a landslide inventory map. Secondly, the landslide points were randomly split into two groups (70/30) for training and validation purposes, respectively. Then, 10 landslide explanatory variables, such as slope aspect, slope angle, altitude, lithology, mean annual precipitation, distance to roads, distance to rivers, distance to faults, land use, and normalized difference vegetation index (NDVI), were selected and the potential multicollinearity problems between these factors were detected by the Pearson Correlation Coefficient (PCC), the variance inflation factor (VIF), and tolerance (TOL). Subsequently, the landslide susceptibility maps for the study region were obtained using the IOE model, the LR–IOE, and the SVM–IOE model. Finally, the performance of these three models was verified and compared using the receiver operating characteristics (ROC) curve. The success rate results showed that the LR–IOE model has the highest accuracy (90.11%), followed by the IOE model (87.43%) and the SVM–IOE model (86.53%). Similarly, the AUC values also showed that the prediction accuracy expresses a similar result, with the LR–IOE model having the highest accuracy (81.84%), followed by the IOE model (76.86%) and the SVM–IOE model (76.61%). Thus, the landslide susceptibility map (LSM) for the study region can provide an effective reference for the Fugu County government to properly address land planning and mitigate landslide risk.

INTRODUCTION: High-risk human papilloma virus (HPV)-associated cervical cancer is the fourth most common cancer in women worldwide. Current treatments of high-grade squamous intraepithelial lesion (HSIL) of the cervix are based on invasive surgical interventions, compromising cervical competence and functionality. APRICITY is a multicentre, prospective, double-blind, randomised controlled phase 3 study further evaluating the efficacy and safety of Cevira, an integrated drug-delivery and light-delivery device for hexaminolevulinate photodynamic therapy, which shows promise as a novel, non-invasive outpatient therapy for women with HSIL. METHODS AND ANALYSIS: Patients with biopsy-confirmed HSIL histology are invited to participate in the study planned to be conducted at 47 sites in China and 25 sites in Ukraine, Russia and the European Union. The aim is to include at least 384 patients, which will be randomised to either Cevira or placebo group (2:1). All patients will be assessed 3 months after first treatment and a second treatment will be administered in patients who are HPV positive or have at least low-grade squamous intraepithelial lesion. Primary endpoint is the proportion of the responders 6 months after first treatment. Secondary efficacy and safety endpoints will be assessed at 6 months, and data for secondary performance endpoints of the Cevira device will be collected at 3 months and 6 months, in case second treatment was administered. All patients in the Cevira group will be enrolled in an open, long-term extension study for 6 months to collect additional efficacy and safety data (study extension endpoints). ETHICS AND DISSEMINATION: The study was approved by the ethics committee of the Peking Union Medical College Hospital and Hannover Medical University, Germany. Findings will be disseminated through peer review publications and conference presentations. TRIAL REGISTRATION NUMBER: NCT04484415; clinicaltrials.gov.