Materials and Methods: Fifty individual fruit bats were captured using six mists net, from May to July 2017. The nets were set at dusk (1830 h) as bats emerge for foraging and monitored at every 30-min intervals throughout the night until dawn when they returned to the roost. The nets were closed for the day until next night, and captured bats were identified to species levels.
Results: All the captured bats were mega chiropterans, and Cynopterus brachyotis was the highest captured species, representing 40% of the total capture. Shannon-Weiner index is 2.80, and Simpson index is 0.2. Our result suggests that there is a degree of species dominance with low diversity in Lenggong Livestock Breeding Center.
Conclusion: We concluded that fruit bats are indeed, encroaching livestock areas and the species identified could be a potential source of infection to susceptible livestock. Hence, an active surveillance should be embarked on farms that border wildlife sanctuaries.
AIMS: To develop a model to detect the respiratory phases present in the pulmonary acoustic signals and to evaluate the performance of the model in detecting the respiratory phases.
METHODS: Normalised averaged power spectral density for each frame and change in normalised averaged power spectral density between the adjacent frames were fuzzified and fuzzy rules were formulated. The fuzzy inference system (FIS) was developed with both Mamdani and Sugeno methods. To evaluate the performance of both Mamdani and Sugeno methods, correlation coefficient and root mean square error (RMSE) were calculated.
RESULTS: In the correlation coefficient analysis in evaluating the fuzzy model using Mamdani and Sugeno method, the strength of the correlation was found to be r = 0.9892 and r = 0.9964, respectively. The RMSE for Mamdani and Sugeno methods are RMSE = 0.0853 and RMSE = 0.0817, respectively.
CONCLUSION: The correlation coefficient and the RMSE of the proposed fuzzy models in detecting the respiratory phases reveals that Sugeno method performs better compared with the Mamdani method.
METHODS: Observational study conducted on 68 patients (1- 18 yrs.) with physical status of ASA II during methotrexate injection with MAC at the RSUP dr. Sardjito. The depth of anaesthesia was monitored with Observer's Alertness Assessment Sedation Scale (OAAS) every two minutes. Consciousness was defined as OAAS=5, or if there is volunteer movement of patients. The result was analysed and categorised according to age, sex, physical status, Body Mass Index (BMI) and anaesthesia's medication of patients.
RESULTS: Positive consciousness in paediatric patients based on OASS score at 2-minute and 4-minutes was 26.5% and 3.2% respectively, and was rescued by additional propofol 2mg/kg body weight.
CONCLUSION: The incidence of paediatric consciousness in patients during methotrexate injection with Monitored Anaesthesia Care (MAC) in the Sardjito General Hospital is 26.5% (2-minute after induction) and 3.2% (4-minute after induction), and this is considerably high thus needing futher prevention.
OBJECTIVES: The objective of the study is to find a correlation between sonographic measurements of ONSD value with ICP value measured via the gold standard invasive intracranial ICP catheter, and to find the cut-off value of ONSD measurement in predicting raised ICP, along with its sensitivity and specificity value.
METHODS: A prospective observational study was performed using convenience sample of 41 adult neurosurgical patients treated in neurosurgical intensive care unit with invasive intracranial pressure monitoring placed in-situ as part of their clinical care. Portable SonoSite ultrasound machine with 7 MHz linear probe were used to measure optic nerve sheath diameter using the standard technique. Simultaneous ICP readings were obtained directly from the invasive monitoring.
RESULTS: Seventy-five measurements were performed on 41 patients. The non-parametric Spearman correlation test revealed a significant correlation at the 0.01 level between the ICP and ONSD value, with correlation coefficient of 0.820. The receiver operating characteristic curve generated an area under the curve with the value of 0.964, and with standard error of 0.22. From the receiver operating characteristic curve, we found that the ONSD value of 5.205 mm is 95.8% sensitive and 80.4% specific in detecting raised ICP.
CONCLUSIONS: ONSD value of 5.205 is sensitive and specific in detecting raised ICP. Bedside ultrasound measurement of ONSD is readily learned, and is reproducible and reliable in predicting raised ICP. This non-invasive technique can be a useful adjunct to the current invasive intracranial catheter monitoring, and has wide potential clinical applications in district hospitals, emergency departments and intensive care units.
DESIGN: Prospective, non-randomized trial.
SETTING: Naturalistic driving in Malaysia.
PARTICIPANTS: Heavy vehicle drivers in Malaysia were assigned to the Device (n = 25) or Control condition (n = 34).
INTERVENTION: Both conditions were monitored for driving events at work over 4-weeks in Phase 1, and 12-weeks in Phase 2. In Phase 1, the Device condition wore the device operated in the silent mode (i.e., no drowsiness alerts) to examine the accuracy of the device in predicting driving events. In Phase 2, the Device condition wore the device in the active mode to examine if drowsiness alerts from the device influenced the rate of driving events (compared to Phase 1).
MEASUREMENTS: All participants were monitored for harsh braking and harsh acceleration driving events and self-reported sleep duration and sleepiness daily.
RESULTS: There was a significant decrease in the rate of harsh braking events (Rate ratio = 0.48, p