Can burglary prevention be low-carbon and effective? Investigating the environmental performance of burglary prevention measures

There has been limited study to date on the environmental impacts of crime prevention measures. We address this shortfall by estimating the carbon footprint associated with the most widely used burglary prevention measures: door locks, window locks, burglar alarms, lighting and CCTV cameras. We compare these footprints with a measure of their effectiveness, the security protection factor, allowing us to identify those measures that are both low-carbon and effective in preventing burglary. Window locks are found to be the most effective and low-carbon measure available individually. Combinations of window locks, door locks, external and indoor lightings are also shown to be effective and low-carbon. Burglar alarms and CCTV do not perform as strongly, with low security against burglary and higher carbon footprints. This information can be used to help inform more sustainable choices of burglary prevention within households as well as for crime prevention product design

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Addressing the carbon-crime blind spot: A carbon footprint approach

Governments estimate the social and economic impacts of crime, but its environmental impact is largely unacknowledged. Our study addresses this by estimating the carbon footprint of crime in England and Wales, and identifies the largest sources of emissions. By applying Environmentally-Extended Input-Output Analysis (EE-IOA) derived carbon emission factors to the monetised costs of crime, we estimate that crime committed in 2011 in England and Wales gave rise to over four million tonnes CO2e. Burglary resulted in the largest proportion of the total footprint (30%), due to the carbon associated with replacement of stolen/damaged goods. Emissions arising from criminal justice system services also accounted for a large proportion (21% of all offences; 49% of police recorded offences). Focus on these offences and the carbon efficiency of these services may help reduce the overall emissions that result from crime. However, cutting crime does not automatically result in a net reduction in carbon, as we need to take account of potential rebound effects. As an example, we consider the impact of reducing domestic burglary by 5%. Calculating this is inherently uncertain as it depends on assumptions concerning how money would be spent in the absence of crime. We find that this may result in a rebound effect of between 3% less and 23% more emissions. Despite this uncertainty concerning the carbon savings, our study goes some way towards informing policy makers of the scale of the environmental consequences of crime and thus enables it to be taken into account in policy appraisals

The Relationship between Abdominal Fat Phenotypes and Insulin Resistance in Non-Obese Individuals after Acute Pancreatitis

Both type 2 prediabetes/diabetes (T2DM) and new-onset prediabetes/diabetes after acute pancreatitis (NODAP) are characterized by impaired tissue sensitivity to insulin action. Although the outcomes of NODAP and T2DM are different, it is unknown whether drivers of insulin resistance are different in the two types of diabetes. This study aimed to investigate the associations between abdominal fat phenotypes and indices of insulin sensitivity in non-obese individuals with NODAP, T2DM, and healthy controls. Indices of insulin sensitivity (homeostasis model assessment of insulin sensitivity (HOMA-IS), Raynaud index, triglyceride and glucose (TyG) index, Matsuda index) were calculated in fasting and postprandial states. Fat phenotypes (intra-pancreatic fat, intra-hepatic fat, skeletal muscle fat, visceral fat, and subcutaneous fat) were determined using magnetic resonance imaging and spectroscopy. Linear regression and relative importance analyses were conducted. Age, sex, and glycated hemoglobin A1c were adjusted for. A total of 78 non-obese individuals (26 NODAP, 20 T2DM, and 32 healthy controls) were included. Intra-pancreatic fat was significantly associated with all the indices of insulin sensitivity in the NODAP group, consistently in both the unadjusted and adjusted models. Intra-pancreatic fat was not significantly associated with any index of insulin sensitivity in the T2DM and healthy controls groups. The variance in HOMA-IS was explained the most by intra-pancreatic fat (R2 = 29%) in the NODAP group and by visceral fat (R2 = 21%) in the T2DM group. The variance in the Raynaud index was explained the most by intra-pancreatic fat (R2 = 18%) in the NODAP group and by visceral fat (R2 = 15%) in the T2DM group. The variance in the TyG index was explained the most by visceral fat in both the NODAP group (R2 = 49%) and in the T2DM group (R2 = 25%). The variance in the Matsuda index was explained the most by intra-pancreatic fat (R2 = 48%) in the NODAP group and by visceral fat (R2 = 38%) in the T2DM group. The differing association between intra-pancreatic fat and insulin resistance can be used to differentiate NODAP from T2DM. Insulin resistance in NODAP appears to be predominantly driven by increased intra-pancreatic fat deposition