Assessment of radio frequency exposures in schools, homes, and public places in Belgium

Characterization of exposure from emerging radio frequency (RF) technologies in areas where children are present is important. Exposure to RF electromagnetic fields (EMF) was assessed in three "sensitive" microenvironments; namely, schools, homes, and public places located in urban environments and compared to exposure in offices. In situ assessment was conducted by performing spatial broadband and accurate narrowband measurements, providing 6-min averaged electric-field strengths. A distinction between internal (transmitters that are located indoors) and external (outdoor sources from broadcasting and telecommunication) sources was made. Ninety-four percent of the broadband measurements were below 1 V m(-1). The average and maximal total electric-field values in schools, homes, and public places were 0.2 and 3.2 V m(-1) (WiFi), 0.1 and 1.1 V m(-1) (telecommunication), and 0.6 and 2.4 V m(-1) (telecommunication), respectively, while for offices, average and maximal exposure were 0.9 and 3.3 V m(-1) (telecommunication), satisfying the ICNIRP reference levels. In the schools considered, the highest maximal and average field values were due to internal signals (WiFi). In the homes, public places, and offices considered, the highestmaximal and average field values originated from telecommunication signals. Lowest exposures were obtained in homes. Internal sources contributed on average more indoors (31.2%) than outdoors (2.3%), while the average contributions of external sources (broadcast and telecommunication sources) were higher outdoors (97.7%) than at indoor positions (68.8%). FM, GSM, and UMTS dominate the total downlink exposure in the outdoor measurements. In indoor measurements, FM, GSM, and WiFi dominate the total exposure. The average contribution of the emerging technology LTE was only 0.6%

In-situ RF exposure in schools, houses, and public places

C

Data Analysis for Solar Energy Generation in a University Microgrid

This paper presents a data acquisition process for solar energy generation and then analyzes the dynamics of its data stream, mainly employing open software solutions such as Python, MySQL, and R. For the sequence of hourly power generations during the period from January 2016 to March 2017, a variety of queries are issued to obtain the number of valid reports as well as the average, maximum, and total amount of electricity generation in 7 solar panels. The query result on all-time, monthly, and daily basis has found that the panel-by panel difference is not so significant in a university-scale microgrid, the maximum gap being 7.1% even in the exceptional case. In addition, for the time series of daily energy generations, we develop a neural network-based trace and prediction model. Due to the time lagging effect in forecasting, the average prediction error for the next hours or days reaches 27.6%. The data stream is still being accumulated and the accuracy will be enhanced by more intensive machine learning

Dynamic changes in hippocampal diffusion and kurtosis metrics following experimental mTBI correlate with glial reactivity

Diffusion magnetic resonance imaging biomarkers can provide quantifiable information of the brain tissue after a mild traumatic brain injury (mTBI). However, the commonly applied diffusion tensor imaging (DTI) model is not very specific to changes in the underlying cellular structures. To overcome these limitations, other diffusion models have recently emerged to provide a more complete view on the damage profile following TBI. In this study, we investigated longitudinal changes in advanced diffusion metrics following experimental mTBI, utilising three different diffusion models in a rat model of mTBI, including DTI, diffusion kurtosis imaging and a white matter model. Moreover, we investigated the association between the diffusion metrics with histological markers, including glial fibrillary acidic protein (GFAP), neurofilaments and synaptophysin in order to investigate specificity. Our results revealed significant decreases in mean diffusivity in the hippocampus and radial diffusivity and radial extra axonal diffusivity (RadEAD) in the cingulum one week post injury. Furthermore, correlation analysis showed that increased values of fractional anisotropy one day post injury in the hippocampus was highly correlated with GFAP reactivity three months post injury. Additionally, we observed a positive correlation between GFAP on one hand and the kurtosis parameters in the hippocampus on the other hand three months post injury. This result indicated that prolonged glial activation three months post injury is related to higher kurtosis values at later time points. In conclusion, our findings point out to the possible role of kurtosis metrics as well as metrics from the white matter model as prognostic biomarker to monitor prolonged glial reactivity and inflammatory responses after a mTBI not only at early timepoints but also several months after injury. Keywords: Mild traumatic brain injury, Diffusion magnetic resonance imaging, DTI, DKI, White matter mode

A study on Manukan Island

No Abstrac

Current challenges faced by the lodging operators in Sabah and Labuan

In the recent three years, the lodging industry in Sabah and Labuan has undergone rapid development with an estimated increase of more than 50 per cent in room inventory. Coincidentally, most of the up-market lodging properties in Sabah were completed in the period of the economic downturn in East Asia in general and Malaysia, in particular. The purpose of our research is to study the possible forces which shaped the lodging industry and the major challenges faced by the lodging operators in Sabah and Labuan. This research is also to highlight the intensity of the identified challenges according to the different categories of lodging properties. A comparison will be made between the challenges encountered by the lodging operators in Sabah and Labuan and other countries. For the purpose of this research,the lodging properties are divided into three broad categories; the budget accommodations; the one, two and three-star hotels and the four and five-star hotels. Our research findings indicated that the current economic situation, the intensity of rivalry between the lodging operators, the increased in operation costs especially in cleaning chemicals, food and beverages, the reduction in consumer spending and the lack of skilled human resources are the major forces which challenge the lodging industry. In the early 1990s, countries like the United States of America faced similar severe competition. Before the currency and stock market crisis in East Asia, Hong Kong and Thailand encountered the lack of skilled manpower owing to their robust expansion in the hotel industry