Post-script-Retail forecasting: Research and practice.

This note updates the 2019 review article "Retail forecasting: Research and practice" in the context of the COVID-19 pandemic and the substantial new research on machine-learning algorithms, when applied to retail. It offers new conclusions and challenges for both research and practice in retail demand forecasting.

The practicality of Malaysia dengue outbreak forecasting model as an early warning system.

Dengue is a harmful tropical disease that causes death to many people. Currently, the dengue vaccine development is still at an early stage, and only intervention methods exist after dengue cases increase. Thus, previously, two scientific experimental field studies were conducted in producing a dengue outbreak forecasting model as an early warning system. Successfully, an Autoregressive Distributed Lag (ADL) Model was developed using three factors: the epidemiological, entomological, and environmental with an accuracy of 85%; but a higher percentage is required in minimizing the error for the model to be useful. Hence, this study aimed to develop a practical and cost-effective dengue outbreak forecasting model with at least 90% accuracy to be embedded in an early warning computer system using the Internet of Things (IoT) approach. Eighty-one weeks of time series data of the three factors were used in six forecasting models, which were Autoregressive Distributed Lag (ADL), Hierarchical Forecasting (Bottom-up and Optimal combination) and three Machine Learning methods: (Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest). Five error measures were used to evaluate the consistency performance of the models in order to ensure model performance. The findings indicated Random Forest outperformed the other models with an accuracy of 95% when including all three factors. But practically, collecting mosquito related data (the entomological factor) was very costly and time consuming. Thus, it was removed from the model, and the accuracy dropped to 92% but still high enough to be of practical use, i.e., beyond 90%. However, the practical ground operationalization of the early warning system also requires several rain gauges to be located at the dengue hot spots due to localized rainfall. Hence, further analysis was conducted in determining the location of the rain gauges. This has led to the recommendation that the rain gauges should be located about 3-4 km apart at the dengue hot spots to ensure the accuracy of the rainfall data to be included in the dengue outbreak forecasting model so that it can be embedded in the early warning system. Therefore, this early warning system can save lives, and prevention is better than cure.

Hereditary nephritis mimicking immune complex-mediated glomerulonephritis.

The defining ultrastructural features of hereditary nephritis are "basket weave" lamellation or thinning of glomerular basement membranes. Electron-dense deposits are not seen and immunofluorescence (IF) is generally negative. In this study, we report 5 cases of hereditary nephritis in which substantial amounts of glomerular electron-dense deposits were identified on electron microscopy, with corresponding positive IF staining in 4 cases, suggesting immune complex-mediated glomerulonephritis. However, no case had histological evidence of glomerular endocapillary or extracapillary proliferation or leukocyte infiltration typical of active glomerulonephritis. Four cases were diagnosed at outside institutions simply as forms of glomerulonephritis without considering the possibility of hereditary nephritis and were sent for consultation in contemplation of possible immunosuppressive therapy. All patients had negative serologies and no known underlying infectious or autoimmune disease; 4 patients had family history of hematuria or renal disease. The glomerular electron-dense deposits were predominantly mesangial (4 cases) and intramembranous (4 cases), as well as subepithelial (2 cases) or subendothelial (1 case). Corresponding IF positivity for immune reactants was identified in 4 cases, and IgG was the predominant immunoglobulin deposited. A characteristic feature was the tendency for deposits to form between the complex layers of glomerular basement membrane material, favoring a process of nonspecific entrapment of immune reactants within the thickened, lamellated basement membrane. In all cases, a diagnosis of hereditary nephritis was confirmed by demonstration of the characteristic loss of immunoreactivity for the alpha5 subunit of collagen IV (4 cases) or Goodpasture's antigen (1 case) in renal or epidermal basement membranes. These cases expand the spectrum of unusual pathological findings in hereditary nephritis and emphasize the potential for hereditary nephritis to mimic immune complex glomerulonephritis.