Classification of Porcine Cranial Fracture Patterns Using a Fracture Printing Interface,,

Distinguishing between accidental and abusive head trauma in children can be difficult, as there is a lack of baseline data for pediatric cranial fracture patterns. A porcine head model has recently been developed and utilized in a series of studies to investigate the effects of impact energy level, surface type, and constraint condition on cranial fracture patterns. In the current study, an automated pattern recognition method, or a fracture printing interface (FPI), was developed to classify cranial fracture patterns that were associated with different impact scenarios documented in previous experiments. The FPI accurately predicted the energy level when the impact surface type was rigid. Additionally, the FPI was exceedingly successful in determining fractures caused by skulls being dropped with a high‐level energy (97% accuracy). The FPI, currently developed on the porcine data, may in the future be transformed to the task of cranial fracture pattern classification for human infant skulls.     

Estimation of stature from foot and shoe measurements by multiplication factors: A revised attempt

Estimation of stature from foot and shoe measurements using multiplication factors is well known. It is a simple method and it is used very frequently as a ready reckoner in forensic anthropology. However the individual error is quite large. In the present work an attempt has been made to evolve revised multiplication factors to reduce this error so that this method (multiplication factor) can be used more effectively with smaller error.     

Government as Catalyst: Can It Work Again with Wireless Internet Access?

As the Internet becomes an indispensable component of the global economy, Internet access is an increasingly important prerequisite to exploiting social, economic and educational opportunities. Municipal wireless networks (MWNs), which are wireless Internet access networks created with active local leadership and involvement, are seen as a potential solution. In this case study we describe the development of the Philadelphia MWN including goals, stakeholder expectations, policy, applications, technology, management models, funding, and implementation. The case provides insights on how communities can act as catalysts and use information technology to promote social and economic change. We found that MWNs involve competing private and public sector stakeholders, and it is important to clearly identify the main application of the MWN. We also found that focusing on the digital divide affords both opportunities and risks, and there are powerful external forces that impact MWNs and the underlying technology.     

Effect of testing and social distancing measures on COVID-19 deaths in India: Role of pre-existing socio-economic factors

We examine the effect of testing and social distancing measures on the severity of COVID19 across Indian states during the 68th day nationwide lockdown period. We also explore whether pre-existing socio-economic factors such as quality of health care and the ability to practice social distancing influences the effect of these policy measures across states. Using daily level data between April 1 and May 31 for 18 of the major states, we find that both testing and social distancing have a negative effect on COVID-19 fatalities in India. Further, testing is more helpful in reducing CFR for states with lower per capita health expenditure and weaker medical infrastructure. This highlights how ramping up testing can aid states that have a weak health care system through the detection of infection, contact tracing and isolation. In contrast, social distancing measures are more effective in states that are less populous and have lesser people dwelling in single-room houses. Our results confirm the role of pre-existing institutional factors in shaping the effect of policy actions on health outcomes.