scholarly journals Effects of demolishing abandoned buildings on firearm violence: a moderation analysis using aerial imagery and deep learning

2021 ◽  
pp. injuryprev-2021-044412
Author(s):  
Jonathan Jay ◽  
Jorrit de Jong ◽  
Marcia P Jimenez ◽  
Quynh Nguyen ◽  
Jason Goldstick
Keyword(s):  
New York ◽  
Deep Learning ◽  
Built Environment ◽  
Aerial Imagery ◽  
Long Term Effects ◽  
Firearm Violence ◽  
Units Of Analysis ◽  
Novel Approach ◽  
Incident Rate

PurposeDemolishing abandoned buildings has been found to reduce nearby firearm violence. However, these effects might vary within cities and across time scales. We aimed to identify potential moderators of the effects of demolitions on firearm violence using a novel approach that combined machine learning and aerial imagery.MethodsOutcomes were annual counts of fatal and non-fatal shootings in Rochester, New York, from 2000 to 2020. Treatment was demolitions conducted from 2009 to 2019. Units of analysis were 152×152 m grid squares. We used a difference-in-differences approach to test effects: (A) the year after each demolition and (B) as demolitions accumulated over time. As moderators, we used a built environment typology generated by extracting information from aerial imagery using convolutional neural networks, a deep learning approach, combined with k-means clustering. We stratified our main models by built environment cluster to test for moderation.ResultsOne demolition was associated with a 14% shootings reduction (incident rate ratio (IRR)=0.86, 95% CI 0.83 to 0.90, p<0.001) the following year. Demolitions were also associated with a long-term, 2% reduction in shootings per year for each cumulative demolition (IRR=0.98, 95% CI 0.95 to 1.00, p=0.02). In the stratified models, densely built areas with higher street connectivity displayed following-year effects, but not long-term effects. Areas with lower density and larger parcels displayed long-term effects but not following-year effects.ConclusionsThe built environment might influence the magnitude and duration of the effects of demolitions on firearm violence. Policymakers may consider complementary programmes to help sustain these effects in high-density areas.

scholarly journals Short-Term Prediction of Demand for Ride-Hailing Services: A Deep Learning Approach

2021 ◽  
Author(s):  
Long Chen ◽  
Piyushimita Vonu Thakuriah ◽  
Konstantinos Ampountolas
Keyword(s):  
New York ◽  
Deep Learning ◽  
Built Environment ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Service Providers ◽  
Road Traffic ◽  
Travel Behaviour ◽  
Demand Prediction ◽  
Research Areas

AbstractAs ride-hailing services become increasingly popular, being able to accurately predict demand for such services can help operators efficiently allocate drivers to customers, and reduce idle time, improve traffic congestion, and enhance the passenger experience. This paper proposes UberNet, a deep learning convolutional neural network for short-time prediction of demand for ride-hailing services. Exploiting traditional time series approaches for this problem is challenging due to strong surges and declines in pickups, as well as spatial concentrations of demand. This leads to pickup patterns that are unevenly distributed over time and space. UberNet employs a multivariate framework that utilises a number of temporal and spatial features that have been found in the literature to explain demand for ride-hailing services. Specifically, the proposed model includes two sub-networks that aim to encode the source series of various features and decode the predicting series, respectively. To assess the performance and effectiveness of UberNet, we use 9 months of Uber pickup data in 2014 and 28 spatial and temporal features from New York City. We use a number of features suggested by the transport operations and travel behaviour research areas as being relevant to passenger demand prediction, e.g., weather, temporal factors, socioeconomic and demographics characteristics, as well as travel-to-work, built environment and social factors such as crime level, within a multivariate framework, that leads to operational and policy insights for multiple communities: the ride-hailing operator, passengers, third-part location-based service providers and revenue opportunities to drivers, and transport operators such as road traffic authorities, and public transport agencies. By comparing the performance of UberNet with several other approaches, we show that the prediction quality of the model is highly competitive. Further, Ubernet’s prediction performance is better when using economic, social and built environment features. This suggests that Ubernet is more naturally suited to including complex motivators of travel behavior in making real-time demand predictions for ride-hailing services.

scholarly journals Long-Term Follow-Up Study of Temporary Tricuspid Valve Detachment as Approach to VSD Repair without Consequent Tricuspid Dysfunction

2016 ◽  
Vol 43 (5) ◽  
pp. 392-396 ◽  
Author(s):  
Gianluca Lucchese ◽  
Lucia Rossetti ◽  
Giuseppe Faggian ◽  
Giovanni B. Luciani
Keyword(s):  
New York ◽  
Tricuspid Valve ◽  
Tricuspid Regurgitation ◽  
Heart Association ◽  
Tricuspid Valve Repair ◽  
Long Term Effects ◽  
A Prospective Study ◽  
Valve Detachment

Temporary tricuspid valve detachment improves the operative view of certain congenital ventricular septal defects (VSDs), but its long-term effects on tricuspid valve function are still debated.From 2002 through 2012, we performed a prospective study of 68 children (mean age, 1.28 ± 1.01 yr) who underwent transatrial closure of VSDs following temporary tricuspid valve detachment. Sixty patients had conoventricular and 8 had mid-muscular VSDs. All were in sinus rhythm. Seventeen patients had systemic pulmonary artery pressures. Preoperative echocardiograms showed trivial-to-mild tricuspid regurgitation in 62 patients and tricuspid dysplasia with severe regurgitation in 6 patients. Patients were clinically and echocardiographically monitored at 30 postoperative days, 3 months, 6 months, every 6 months thereafter for the first 2 years, and then once a year.No in-hospital or late death was observed at the median follow-up evaluation of 5.9 years. Mean intensive care unit and hospital stays were 1.6 ± 1.1 and 7.3 ± 2.7 days, respectively. Residual small VSDs occurred in 3 patients, and temporary atrioventricular block in one. After VSD repair, 62 patients (91%) had trivial or mild tricuspid regurgitation, and 6 moderate. Five of these last had severe tricuspid regurgitation preoperatively and had undergone additional tricuspid valve repair during the procedure. The grade of residual tricuspid regurgitation remained stable postoperatively, and no tricuspid stenosis was documented. All patients were in New York Heart Association class I at follow-up.Temporary tricuspid valve detachment is a simple and useful method for a complete visualization of certain VSDs without incurring substantial tricuspid dysfunction.

scholarly journals Ice and Forest Health

2000 ◽  
Vol 17 (1) ◽  
pp. 16-19 ◽  
Author(s):  
William H. Smith
Keyword(s):  
New York ◽  
New Hampshire ◽  
Forest Health ◽  
Ice Storm ◽  
Health It ◽  
Long Term Effects ◽  
Research Opportunities ◽  
Short And Long Term ◽  
State Region

Abstract In January 1998, a major ice storm damaged millions of urban and rural forest acres in the states of Maine, New Hampshire, Vermont, and New York. A total of 37 counties across the four-state region were designated Federal disaster areas. This article evaluates the storm's influence on general northeastern forest health. It presents a diagnosis of the damage, a prognosis of short- and long-term effects, and a prescription for management and research opportunities. North. J. Appl. For. 17(1)16-19.

Deterrence or Brutalization

1980 ◽  
Vol 26 (4) ◽  
pp. 453-484 ◽  
Author(s):  
William J. Bowers ◽  
Glenn L. Pierce
Keyword(s):  
New York ◽  
Capital Punishment ◽  
Time Trends ◽  
Human Life ◽  
New York State ◽  
Long Term Effects ◽  
Short Term ◽  
Mass Murders ◽  
Effects Of War

In this study, we find that in New York State over the period 1907-63 there were, on the average, two additional homicides in the month after an execution. Controls for time trends, seasonality, the effects of war, and adjustments for autocorrelation tend to confirm this finding. Such a "brutalizing" effect of executions is consistent with research on violent events such as publicized suicides, mass murders, and assassinations; with previous studies of the long-term effects of the availability and use of capital punishment; and with a small number of investigations of the short-term impact of executions in the days, weeks, and months that fol low. This suggests that the message of executions is one of "lethal ven geance" more than deterrence. The resulting sacrifice of human life chal lenges the constitutionality of capital punishment.

“Invasión Del 80/¡Yo Vine Del Mariel!”

2020 ◽  
pp. 279-322
Author(s):  
Benjamin Lapidus
Keyword(s):  
United States ◽  
New York ◽  
New York City ◽  
York City ◽  
Puerto Ricans ◽  
Dance Music ◽  
Long Term Effects ◽  
Music Scenes ◽  
Insight Into

This chapter discusses the immediate musical impact of the 1980 Mariel Boatlift by examining some of the dancers and musicians who arrived in New York City at that time: Orlando “Puntilla” Ríos, Manuel Martínez Olivera “El llanero solitario” (The Lone Ranger), Roberto Borrell, Rita Macías, Xiomara Rodríguez, Félix “Pupy” Insua, Pedro Domech, Daniel Ponce, Fernando Lavoy, Gerardo “Taboada” Fernández, Gabriel “Chinchilita” Machado, and many others. The chapter highlights the musical activities of these people and other musicians and its long-term effects on the folkloric and Latin popular dance music scenes in New York and the greater United States, not only in the performance realm but in many cases also as teachers for subsequent generations of Cuban and non-Cuban musicians, particularly Puerto Ricans in New York City. This group of artists who arrived during El Mariel would also serve as important points of connection for the next major wave of newly arriving musicians and dancers in the early 1990s, known as the balseros (raft people). Ultimately, the chapter provides an analysis of and insight into this overlooked era of Cuban musical history in New York and how it would impact Latin music in New York and elsewhere.

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