Trunk sway in mildly disabled multiple sclerosis patients with and without balance impairment

Multiple sclerosis (MS) causes a broad range of neurological symptoms. Most common is poor balance control. However, knowledge of deficient balance control in mildly affected MS patients who are complaining of balance impairment but have normal clinical balance tests (CBT) is limited. This knowledge might provide insights into the normal and pathophysiological mechanisms underlying stance and gait. We analysed differences in trunk sway between mildly disabled MS patients with and without subjective balance impairment (SBI), all with normal CBT. The sway was measured for a battery of stance and gait balance tests (static and dynamic posturography) and compared to that of age- and sex-matched healthy subjects. Eight of 21 patients (38%) with an Expanded Disability Status Scale of 1.0-3.0 complained of SBI during daily activities. For standing on both legs with eyes closed on a normal and on a foam surface, patients in the no SBI group showed significant differences in the range of trunk roll (lateral) sway angle and velocity, compared to normal persons. Patients in the SBI group had significantly greater lateral sway than the no SBI group, and sway was also greater than normal in the pitch (anterior-posterior) direction. Sway for one-legged stance on foam was also greater in the SBI group compared to the no SBI and normal groups. We found a specific laterally directed impairment of balance in all patients, consistent with a deficit in proprioceptive processing, which was greater in the SBI group than in the no SBI group. This finding most likely explains the subjective symptoms of imbalance in patients with MS with normal CBT.

UAVNet: A Mobile Wireless Mesh Network Using Unmanned Aerial Vehicles

We developed UAVNet, a framework for the autonomous deployment of a flying Wireless Mesh Network using small quadrocopter-based Unmanned Aerial Vehicles (UAVs). The flying wireless mesh nodes are automatically interconnected to each other and building an IEEE 802.11s wireless mesh network. The implemented UAVNet prototype is able to autonomously interconnect two end systems by setting up an airborne relay, consisting of one or several flying wireless mesh nodes. The developed software includes basic functionality to control the UAVs and to setup, deploy, manage, and monitor a wireless mesh network. Our evaluations have shown that UAVNet can significantly improve network performance.

Role of milk and meat products as vehicles for antibiotic-resistant bacteria

This subject is reviewed under the following headings: Microbial contamination of raw meat and raw milk; Antibiotic resistance of food-borne pathogens; Antibiotic resistance of commensal and potentially pathogenic bacteria as a new threat in food microbiology; Antibiotic-resistant staphylococci in fermented meat and [in] milk products; Antibiotic-resistant Enterococcus sp. in fermented meat and [in] milk products; Enterococci in farm animals and meat; Enterococci in fermented food; Molecular characterization of resistance of food-borne enterococci; and Further ecological and epidemiological considerations of resistant live bacteria in food. It is concluded that further research is needed, particularly into the possible transfer of the resistance of bacteria consumed in meat or milk products to the indigenous bacteria of the human consumer.

The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides

The application of pesticides and fertilizers in agricultural areas is of crucial importance for crop yields. The use of aircrafts is becoming increasingly common in carrying out this task mainly because of their speed and effectiveness in the spraying operation. However, some factors may reduce the yield, or even cause damage (e.g., crop areas not covered in the spraying process, overlapping spraying of crop areas, applying pesticides on the outer edge of the crop). Weather conditions, such as the intensity and direction of the wind while spraying, add further complexity to the problem of maintaining control. In this paper, we describe an architecture to address the problem of self-adjustment of the UAV routes when spraying chemicals in a crop field. We propose and evaluate an algorithm to adjust the UAV route to changes in wind intensity and direction. The algorithm to adapt the path runs in the UAV and its input is the feedback obtained from the wireless sensor network (WSN) deployed in the crop field. Moreover, we evaluate the impact of the number of communication messages between the UAV and the WSN. The results show that the use of the feedback information from the sensors to make adjustments to the routes could significantly reduce the waste of pesticides and fertilizers.