A VEHICLE-MOUNTED INSECT TRAP

1979 ◽  
Vol 111 (7) ◽  
pp. 851-854 ◽  
Author(s):  
D. R. Barnard
Keyword(s):  

AbstractA vehicle-mounted trap for collecting airborne insects is described. Air enters at 1.9 m wide × 0.7 m high funnel and escapes through 12.5 mesh/cm nylon netting; insects are concentrated and directed into a removable receiving bag. The trap is durable, inexpensive, simple to construct and install, and can be transported in a station wagon or pickup truck.

1994 ◽  
Vol 12 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Michael R. Baye ◽  
Dan Kovenock
Keyword(s):  

CJEM ◽  
2015 ◽  
Vol 17 (5) ◽  
pp. 569-570
Author(s):  
Christopher Sampson

A 16-year-old male presented to the emergency department following a single-truck motor vehicle collision. The patient was the driver of an older model pickup truck that he lost control of while driving and went off of the road. He was restrained with a lap belt only, given the age of the vehicle. His only complaint at the presenting hospital was left-sided neck pain and hoarseness.


Structures ◽  
2022 ◽  
Vol 36 ◽  
pp. 482-492
Author(s):  
Karim Aliakbari ◽  
Reza Masoudi Nejad ◽  
Tohid Akbarpour Mamaghani ◽  
Pooya Pouryamout ◽  
Hossein Rahimi Asiabaraki

2018 ◽  
Vol 2 (1) ◽  
pp. 51-58 ◽  
Author(s):  
Shasta Claire Henry ◽  
Peter B. McQuillan ◽  
James B. Kirkpatrick

The Southernmost region of Australia, the island of Tasmania, is also the most mountainous, with large areas of rugged alpine environments. This entomological frontier offers a distinct suite of insects for study including many endemic taxa. However, harsh weather, remote locations and rough terrain represent an environment too extreme for many existing insect trap designs. We report here on the design and efficacy of a new Alpine Malaise Trap (AMT), which can be readily hybridised with several other common insect trapping techniques. Advantages of the design include its light weight and portability, low cost, robustness, rapid deployment and long autonomous sampling period. The AMT was field tested in the Tasmanian highlands (AUST) in 2017. A total of 16 orders were collected. As expected, samples are dominated by Diptera. However, the trap also collected a range of flightless taxa including endemic and apterous species, Apteropanorpatasmanica – closest relative of the boreal, snow scorpionflies (Boreidae). Combined and compared with other trap types the Alpine Malaise Traps captured less specimens but of a greater diversity than passive sticky traps, while drop traps captured less specimens but a greater diversity than AMT. The statistical potential of the catch is discussed.


2021 ◽  
Author(s):  
Francis Fish ◽  
Bert Bras

Abstract Advanced Driver Assistance Systems (ADAS) have become increasingly common in vehicles in the last decade. The majority of studies has focused on smaller vehicles with gross vehicle weight rating (GVWR) under 5,000lbs, predominantly sedans, for their ADAS evaluations. While it is sensible to use this style of vehicle because it is ubiquitous worldwide for a typical vehicle body style, these studies neglect full-size light-duty pickup trucks (FSLDPTs), GVWR 5,000 – 10,000lbs, which are abundant on the roads in the United States, 18% of vehicles. The increase in mass, higher center of gravity, and utilitarianism of the vehicles allows for unique conditions for studying the effects of ADAS. This work determines the best and worst location to be hit in a full-size light-duty pickup truck based on data for the industry sales leader in this class of vehicles. The objective is to use these results for future designs of ADAS technologies and their placement on the FSLDPT. While these methods could be applied to any vehicle, the FSLDPT sales leader will be investigated as it represents about 9% of registered vehicles in the United States. The results will be optimized with respect to cost in terms of initial up-front purchasing cost and post-accident vehicle repair cost.


2019 ◽  
Vol 20 (sup2) ◽  
pp. S165-S168 ◽  
Author(s):  
Mary Pat McKay ◽  
Kristin Poland ◽  
Donald Karol ◽  
Rafael Marshall ◽  
Ronald Kaminski

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