Farm forests, seasonal hunger, and biomass poverty: Evidence of induced intensification from panel data in the Ethiopian Highlands.

Seasonal hunger is the most common food insecurity experience for millions of small dryland farmers. This study tests the relationships between food insecurity, farm forests, and biomass poverty using a longitudinal dataset from the Amhara region of Ethiopia. These data form part of the Ethiopia Socioeconomic Survey, which collected panel data over three survey rounds from 530 households between 2011 and 2016. This dataset represents a collection of unique socioeconomic, wellbeing, and micro-land use measures, including farm forests. Hierarchical mixed effect regression models assessed the relationship between food insecurity and farm forests as well as the conditional effects of biomass poverty among the poorest farmers and women-headed households. Over a six-year study period, farmers reported increased stress from smaller land holdings, higher prices, and climate-related shocks. A clear trend towards spontaneous dispersed afforestation is observed by both researchers and satellite remote sensing. Model results indicate, dedicating approximately 10% of farm area to forest reduces months of food insecurity by half. The greatest reductions in food insecurity from farm forests are reported by ultra-poor and crop residue-burning households, suggesting that biomass poverty may be a major constraint to resilient food security on these farms. This research provides novel quantitative evidence of induced intensification and food security impacts of farm management preserving and building stores of biomass value as green assets. The results reported here have important implications for nature-based solutions as a major strategy to achieve sustainable development in some contexts.

The Impact of Lateral Ventricular Opening in the Resection of Newly Diagnosed High-Grade Gliomas: A Single Center Experience.

Given the importance of maximizing resection for prognosis in patients with HGG and the potential risks associated with ventricle opening, this study aimed to assess the actual increase in post-surgical complications related to lateral ventricle opening and its influence on OS and PFS. A retrospective study was conducted on newly diagnosed HGG, dividing the patients into two groups according to whether the lateral ventricle was opened (69 patients) or not opened (311 patients). PFS, OS, subependymal dissemination, distant parenchymal recurrences, the development of hydrocephalus and CSF leak were considered outcome measures. A cohort of 380 patients (154 females (40.5%) and 226 males (59.5%)) was involved in the study (median age 61 years). The PFS averaged 10.9 months (±13.3 SD), and OS averaged 16.6 months (± 16.3 SD). Among complications, subependymal dissemination was registered in 15 cases (3.9%), multifocal and multicentric progression in 56 cases (14.7%), leptomeningeal dissemination in 12 (3.2%) and hydrocephalus in 8 (2.1%). These occurrences could not be clearly justified by ventricular opening. The act of opening the lateral ventricles itself does not carry an elevated risk of dissemination, hydrocephalus or cerebrospinal fluid (CSF) leak. Therefore, if necessary, it should be pursued to achieve radical removal of the disease.

Unraveling spatial patterns of COVID-19 in Italy: Global forces and local economic drivers.

This article investigates the spatial patterns of coronavirus disease 2019 (COVID-19) infection in Italy and its determinants from March 9 to June 15, 2020, a time interval covering the so-called first wave of COVID pandemics in Europe. The results, based on negative binomial regressions and linear spatial models, confirm the importance of multiple factors that positively correlate with the number of recorded cases. Economic forces, including urban agglomeration, industrial districts, concentration of large companies (both before and after the beginning of the 'lockdown') and a north-south gradient, are the most significant predictors of the strength of COVID-19 infection. These effects are statistically more robust in the spatial models than in the aspatial ones. We interpretate our results in the light of pitfalls related to data reliability, and we discuss policy implications and possible avenues for future research.