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Additional file 1. Survey instrument

Additional file 2. Holm’s correction for the p-values

Additional file 3. Full list of estimates

Objective The study aims to analyze the effectiveness of bevacizumab in addressing the complications associated with gynecological cancers and evaluates effective treatments for various gynecological cancers. Methods The study follows a systematic review approach that has been implemented to analyze the qualitative published data from previous studies. Studies related with the trials of angiogenesis and bevacizumab were selected in the review. Results In general, the management of gynecological cancers include chemotherapy, surgery and radiation therapy. Results suggest bevacizumab as an effective treatment modality for cervical and several other cancers. Overall, bevacizumab showed promising results in improving the overall survival rate of gynecological cancer patients through the combination of bevacizumab with other chemotherapeutic agents. Conclusion Bevacizumab possess less documented adverse effects when compared to other chemotherapeutic agents. The manifestation and severity of adverse effects reported varied according to the chemotherapeutic agent(s) that were used with bevacizumab in combination therapy. Overall, bevacizumab effectively improved the survival rate in patients with several gynaecological cancers.

Additional file 1. Questions in the baseline and end-of-study survey that were developed by authors.

Thermal comfort is a very important factor in many people’s lives; when people do not feel comfortable, their focus, productivity and performance are affected. In our research, we investigate how to help students achieve optimal comfort by predicting their comfort levels. We collected data on 5 students, and then utilised the k-nearest neighbour machine learning algorithm, in conjunction with tenfold cross-validation, to generate models of student comfort in the classroom. The features utilised are air temperature, air velocity, air relative humidity, body temperature and heart rate. In our experiments, we seek to learn if acceptable individual models may be derived, and more importantly, if combined models can help increase predictive accuracy. Our work suggests that combined models are applicable only when used to augment datasets that are applied to a subject with a more complex thermal comfort model.