"/>

外国黄片网站黄色片一级视屏|国产视频-日美不卡在线视频|看欧美1级1级1级生活片儿|青青草人人插青青操干日AV|青青操在线免费观看av|一级成年国产中文字幕av一|美女黄黄视频骚货网站在线观看|欧美一级做一级a做片|少妇高潮一区二区三区99|丁香五月蜜桃久久久亚洲精品成人

Australian invention able to help crack down on illegal drug trade
Source: Xinhua   2018-06-08 09:59:25

CANBERRA, June 8 (Xinhua) -- Australian scientists have helped develop a system that can detect chemicals in minuscule quantities and potentially help law authorities curtail illegal drug trade.

The system, devised by a team that included academics from the Canberra-based Australian National University (ANU), can be developed into a portable drug-testing kits to help authorities crack down on drugs.

ANU scientist Professor Dragomir Neshev, a co-author of the research published in Science, said on Friday the invention measured infrared signatures of organic molecules and translated them into barcodes, which could be used to identify specific drugs.

Infrared spectroscopy detects whether a given molecule is present in a sample by seeing whether the sample absorbs light rays at the molecule's signature frequencies.

Professor Neshev, from the ANU Research School of Physics and Engineering, said on Friday, "We think our invention could be developed into a commercial drug-testing prototype within just a few years."

"It can detect and recognise drugs in extremely small quantities which are released when the body metabolises drugs, providing a new technology for police to mobile-drug test motorists or suspected drug traffickers in a simple and non-invasive way," he said.

Co-researcher Dr Mingkai Liu said such a device can be used also for medical diagnosis and to make the benefits of prescribed medications for patients on expensive therapeutic treatments.

"Our invention consists of an engineered surface with hundreds of tiny pixels," Dr Liu said. "Each pixel senses the molecular absorption at a specific frequency, generating a distinct barcode for every molecule that the surface touches."

These barcodes can be analyzed and classified using advanced pattern recognition and machine learning such as artificial neural networks.

Editor: Xiang Bo
Related News
Xinhuanet

Australian invention able to help crack down on illegal drug trade

Source: Xinhua 2018-06-08 09:59:25
[Editor: huaxia]

CANBERRA, June 8 (Xinhua) -- Australian scientists have helped develop a system that can detect chemicals in minuscule quantities and potentially help law authorities curtail illegal drug trade.

The system, devised by a team that included academics from the Canberra-based Australian National University (ANU), can be developed into a portable drug-testing kits to help authorities crack down on drugs.

ANU scientist Professor Dragomir Neshev, a co-author of the research published in Science, said on Friday the invention measured infrared signatures of organic molecules and translated them into barcodes, which could be used to identify specific drugs.

Infrared spectroscopy detects whether a given molecule is present in a sample by seeing whether the sample absorbs light rays at the molecule's signature frequencies.

Professor Neshev, from the ANU Research School of Physics and Engineering, said on Friday, "We think our invention could be developed into a commercial drug-testing prototype within just a few years."

"It can detect and recognise drugs in extremely small quantities which are released when the body metabolises drugs, providing a new technology for police to mobile-drug test motorists or suspected drug traffickers in a simple and non-invasive way," he said.

Co-researcher Dr Mingkai Liu said such a device can be used also for medical diagnosis and to make the benefits of prescribed medications for patients on expensive therapeutic treatments.

"Our invention consists of an engineered surface with hundreds of tiny pixels," Dr Liu said. "Each pixel senses the molecular absorption at a specific frequency, generating a distinct barcode for every molecule that the surface touches."

These barcodes can be analyzed and classified using advanced pattern recognition and machine learning such as artificial neural networks.

[Editor: huaxia]
010020070750000000000000011100001372391791