Airborne environmental injuries and human health.

The concept that the environment in which we live can have detrimental effects on our health has existed for centuries. Obvious examples of substances that can cause human diseases include infectious agents, poisons, chemicals and other noxious agents, drugs, and physical stimuli such as bright lights and loud sounds. Some less obvious agents can include allergens, nontangible agents such as colorless, odorless gases and aerosolized toxins. In recent decades, humans have developed various new materials and compounds. Additionally, we are now producing known compounds, and even naturally occurring substances, in vastly increased amounts. Many of these substances are generally believed to threaten the health of our environment. However, there is also a considerable amount of hype and exaggeration regarding some of these agents (e.g., mold) that is unsubstantiated. This article extensively reviews the data on a large number of airborne-related illnesses and attempted to place scientific reality in the context of clinical medicine

Rigid Object Tracking Algorithms for Low-Cost AR Devices

Augmented reality (AR) applications rely on robust and efficient methods for tracking. Tracking methods use a computer-internal representation of the object to track, which can be either sparse or dense representations. Sparse representations use only a limited set of feature points to represent an object to track, whereas dense representations almost mimic the shape of an object. While algorithms performed on sparse representations are faster, dense representations can distinguish multiple objects. The research presented in this paper investigates the feasibility of a dense tracking method for rigid object tracking, which incorporates the both object identification and object tracking steps. We adopted a tracking method that has been developed for the Microsoft Kinect to support single object tracking. The paper describes this method and presents the results. We also compared two different methods for mesh reconstruction in this algorithm. Since meshes are more informative when identifying a rigid object, this comparison indicates which algorithm shows the best performance for this task and guides our future research efforts

Review of pyronaridine anti-malarial properties and product characteristics.

Pyronaridine was synthesized in 1970 at the Institute of Chinese Parasitic Disease and has been used in China for over 30 years for the treatment of malaria. Pyronaridine has high potency against Plasmodium falciparum, including chloroquine-resistant strains. Studies in various animal models have shown pyronaridine to be effective against strains resistant to other anti-malarials, including chloroquine. Resistance to pyronaridine appears to emerge slowly and is further retarded when pyronaridine is used in combination with other anti-malarials, in particular, artesunate. Pyronaridine toxicity is generally less than that of chloroquine, though evidence of embryotoxicity in rodents suggests use with caution in pregnancy. Clinical pharmacokinetic data for pyronaridine indicates an elimination T1/2 of 13.2 and 9.6 days, respectively, in adults and children with acute uncomplicated falciparum and vivax malaria in artemisinin-combination therapy. Clinical data for mono or combined pyronaridine therapy show excellent anti-malarial effects against P. falciparum and studies of combination therapy also show promise against Plasmodium vivax. Pyronaridine has been developed as a fixed dose combination therapy, in a 3:1 ratio, with artesunate for the treatment of acute uncomplicated P. falciparum malaria and blood stage P. vivax malaria with the name of Pyramax® and has received Positive Opinion by European Medicines Agency under the Article 58 procedure

Mapping Nearby Terrain in 3D by Use of a Grid of Laser Spots

A proposed optoelectronic system, to be mounted aboard an exploratory robotic vehicle, would be used to generate a three-dimensional (3D) map of nearby terrain and obstacles for purposes of navigating the vehicle across the terrain and avoiding the obstacles. The difference between this system and the other systems would lie in the details of implementation. In this system, the illumination would be provided by a laser. The beam from the laser would pass through a two-dimensional diffraction grating, which would divide the beam into multiple beams propagating in different, fixed, known directions. These beams would form a grid of bright spots on the nearby terrain and obstacles. The centroid of each bright spot in the image would be computed. For each such spot, the combination of (1) the centroid, (2) the known direction of the light beam that produced the spot, and (3) the known baseline would constitute sufficient information for calculating the 3D position of the spot