Developing and assessing a new web-based tapping test for measuring distal movement in Parkinson’s disease: a Distal Finger Tapping test

Disability in Parkinson’s disease (PD) is measured by standardised scales including the MDS-UPDRS, which are subject to high inter and intra-rater variability and fail to capture subtle motor impairment. The BRadykinesia Akinesia INcoordination (BRAIN) test is a validated keyboard tapping test, evaluating proximal upper-limb motor impairment. Here, a new Distal Finger Tapping (DFT) test was developed to assess distal upper-limb function. Kinetic parameters of the test include kinesia score (KS20, key taps over 20 s), akinesia time (AT20, mean dwell-time on each key) and incoordination score (IS20, variance of travelling time between key taps). To develop and evaluate a new keyboard-tapping test for objective and remote distal motor function in PD patients. The DFT and BRAIN tests were assessed in 55 PD patients and 65 controls. Test scores were compared between groups and correlated with the MDS-UPDRS-III finger tapping sub-scores. Nine additional PD patients were recruited for monitoring motor fluctuations. All three parameters discriminated effectively between PD patients and controls, with KS20 performing best, yielding 79% sensitivity for 85% specificity; area under the receiver operating characteristic curve (AUC) = 0.90. A combination of DFT and BRAIN tests improved discrimination (AUC = 0.95). Among three parameters, KS20 showed a moderate correlation with the MDS-UPDRS finger-tapping sub-score (Pearson’s r = − 0.40, p = 0.002). Further, the DFT test detected subtle changes in motor fluctuation states which were not reflected clearly by the MDS-UPDRS-III finger tapping sub-scores. The DFT test is an online tool for assessing distal movements in PD, with future scope for longitudinal monitoring of motor complications.

PERSPECTIVES FOR A WIND ASSISTED SHIP PROPULSION

For three different wind propulsion technologies, the energy saving potential of sea going cargo vessels are discussed: a kite, a Flettner rotor and a Dynarig-sail. The energy saving potential can be increased significantly if the route can be optimized when using a wind assisted ship propulsion. The increase of travelling time due to a route adoption is within the frame of the commonly accepted uncertainty in supply chains and can be limited or adjusted in the route optimization software as a parameter. The calculated saving potential depends on several parameters: the considered wind propulsion system, the route, the kind of ship (bulker, multipurpose carrier, tanker), as well as the ship speed and the weather. The cost-effectiveness of the installation of a wind propulsion system strongly depends on the fuel price, the ship speed and the international policy concerning the ship emissions.

Assessing The Public Health Benefits of Parkrun By Modelling Performance And Participation At Events In Scotland

Background: parkrun is a hugely successful public health initiative that encourages inactive people to exercise. The parkrun results database is likely to contain a wealth of potentially important public health information on the fitness benefits and participation patterns of parkrun, yet this resource has been ignored. The aim was to identify patterns in performance and attendance of participants at parkrun events in Scotland to enhance the future health benefits of parkrun through widening participation particularly by identifying features of events that overcome barriers to women taking part.Study design: The study conducted linear and binomial mixed models of age-graded performance, sex ratio and age of participants at parkrun events held in Scotland. Predictor variables were age, sex, parkrun ID number, number of runs, elevation gain, surface type and travelling time to the next nearest parkrun event. The data were generated from parkrun results pages for 56 events in Scotland. Results: There was a decline in the mean performance of participants at events, however individual performances improved over time. The sex ratio was male biased but the proportion of female participants has been increasing. Events in the most remote parts of Scotland had the lowest age graded performance scores and the highest proportion of female participants with the remotest events exhibiting a female bias in participation. Events on slower surfaces had a higher proportion of female participants.Conclusion: This study reports that parkrun events are becoming more inclusive with new participants being increasingly unfit women. In remoter parts of Scotland the traditional male bias in participation in sport has actually become a slight female bias revealing parkrun has seemingly overcome traditional barriers to female participation in sport. Events with slower surfaces had more female participants. Prioritising the creation of events at more remote locations and on slower surfaces could increase inclusivity and widen participation further. These findings could also help general practitioners prescribe those events that are most likely to benefit new participants making the parkrun practice initiative more effective. For example, women might be encouraged to attend traditionally slower events than men.

Effective Routing in Vehicular Adhoc Network (VANET) using an Bio-inspired Algorithm: Enhanced Deep Reinforcement Learning (EDRL) for Secure Wireless Communication

For improving the performance of city wide-ranging lane networks through the optimized control signal, we proposed a framework in Vehicular Adhoc Network (VANET). Node which reduces the traffic efficiency drastically is identified as critical node, with the help of defined framework. Tripartite graph is used for identifying critical node through vehicle trajectory in the over-all viewpoint. Enhanced Deep Reinforcement Learning (EDRL) method is introduced to control the traffic signal and gives appropriate decision for routing the data from Road Side Unit (RSU) to intermediate or destination node. Various experiments were done with proposed model and the result shows considerable efficiency in delay and travelling time of the node in VANET.

Vocal communication in wild chimpanzees: a call rate study

Background Patterns of vocal communication have implications for species conservation: a change in calling behaviour can, for instance, reflect a disturbed habitat. More importantly, call rate is a parameter that allows conservation planners to convert call density into animal density, when detecting calls with a passive acoustic monitoring system (PAM). Methods We investigated chimpanzee (Pan troglodytes schweinfurthii) call rate during the late dry season in the Issa Valley, western Tanzania by conducting focal follows. We examined the socio-ecological factors that influence call production rate of savanna woodland chimpanzees. Results We found that sex, proportion of time spent in a vegetation type, proportion of time spent travelling, time of the day, party size and swollen parous female presence had a significant effect on the call rate. Call rate differed among the different demographic classes with subadult and adult males vocalising twice as often as the subadult and adult females and three times as often as the juveniles. Applications The use of PAM and recent statistical developments to estimate animal density is promising but relies on our knowing individual call rate, often not available for many species. With the improvement in automatic call detection, we anticipate that PAM will increasingly be broadly applied to primates but also across taxa, for conservation.

Convex Obstacles from Travelling Times

We consider situations where rays are reflected according to geometrical optics by a set of unknown obstacles. The aim is to recover information about the obstacles from the travelling-time data of the reflected rays using geometrical methods and observations of singularities. Suppose that, for a disjoint union of finitely many strictly convex smooth obstacles in the Euclidean plane, no Euclidean line meets more than two of them. We then give a construction for complete recovery of the obstacles from the travelling times of reflected rays.

GIS Mapping Evaluation of Stroke Service Areas in Bangkok Using Emergency Medical Services

Stroke is a major cause of death in Thailand. It requires a specific time period of 4.5 h from onset to treatment to increase recovery rates, and therefore, it can be categorized as a time-sensitive disease. The objective of this research is to identify whether the service areas of the main existing Emergency Medical Services (EMS) prehospital stroke practices cover all areas in Bangkok. This is determined by using GIS mapping. After verifying the current EMS delivery models, comparisons are drawn to find the travelling time of each model. The conditioning factors for GIS mapping were collected and verified, including the traffic speed and duration spent in each mode of the prehospital stroke process. After inputting all of the data into GIS, the service areas were visualized to show the area serviced in each delivery model. The results also show the different hospital groups, including the service areas for (1) non-network hospitals and (2) hospitals with stroke networks. Suggestions for re-networking and adding more hospitals to the existing networks were also identified using GIS. Regularly updating the service area with up-to-date data in GIS is key to improving stroke service areas.

FACTORS CONTRIBUTING TO DELAYED AMBULANCE RESPONSE TIME USING AMBULANCE VEHICLE LOCATOR AND GLOBAL INTEGRATING SYSTEM (AVL- GIS) AT HOSPITAL UNIVERSITI SAINS MALAYSIA

This study aims to determine ambulance response time in KubangKerian district, Kelantan, Malaysia using Ambulance Vehicle Locator and Global Integrating System (AVL-GIS) device and the factors associated with delayed response time. This was a 6-months prospective, cross-sectional study conducted at Emergency and Trauma Department, Hospital Universiti Sains Malaysia (HUSM) in Kubang Kerian, Kelantan, Malaysia. The possible factors identified to have caused delayed ambulance response time from previous literature were included in this study. All prehospital cases from September 2017 until February 2018 attended to by AVL- GIS installed ambulances were included in this study. Data were obtained from the standardized prehospital Proforma forms and extracted from AVL-GIS using iGPS software. Simple and multiple logistic regression tests were used to determine the factors associated to delayed response time. From 505 cases, 75% found to be delayed case meanwhile 25% is non delayed case as defined in study protocol. Further analysis on delayed cases show that call duration, caller type, traffic condition, travelling time and team allocation time were associated with delayed ambulance response time. Evaluation of each component contributing to delayed ambulance response time is needed for intervention to improve prehospital care in the future.

Traffic Congestion Prediction using Deep Reinforcement Learning in Vehicular Ad-Hoc Networks (VANETS)

In recent years, a new wireless network called vehicular ad-hoc network (VANET), has become a popular research topic. VANET allows communication among vehicles and with roadside units by providing information to each other, such as vehicle velocity, location and direction. In general, when many vehicles likely to use the common route to proceed to the same destination, it can lead to a congested route that should be avoided. It may be better if vehicles are able to predict accurately the traffic congestion and then avoid it. Therefore, in this work, the deep reinforcement learning in VANET to enhance the ability to predict traffic congestion on the roads is proposed. Furthermore, different types of neural networks namely Convolutional Neural Network (CNN), Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) are investigated and compared in this deep reinforcement learning model to discover the most effective one. Our proposed method is tested by simulation. The traffic scenarios are created using traffic simulator called Simulation of Urban Mobility (SUMO) before integrating with deep reinforcement learning model. The simulation procedures, as well as the programming used, are described in detail. The performance of our proposed method is evaluated using two metrics; the average travelling time delay and average waiting time delay of vehicles. According to the simulation results, the average travelling time delay and average waiting time delay are gradually improved over the multiple runs, since our proposed method receives feedback from the environment. In addition, the results without and with three different deep learning algorithms, i.e., CNN, MLP and LSTM are compared. It is obvious that the deep reinforcement learning model works effectively when traffic density is neither too high nor too low. In addition, it can be concluded that the effective algorithms for traffic congestion prediction models in descending order are MLP, CNN, and LSTM, respectively.

Teleworking in the Field of Financial Audit in the Context Generated by the COVID-19 Pandemic

In the sensitive socio-economic context generated by the COVID-19 pandemic, teleworking was, in many fields, a way to continue the activity while complying to the measures imposed by law in order to fight the spread of the new Coronavirus. On the one hand, teleworking offers flexibility in setting the work schedule, eliminates travelling time to and from the worksite and allows to attract competent employees from all over the world, by means of digitalisation. On the other hand, working from home is a challenge. The time required to transfer the activity in the virtual space, and the additional training necessary for the use of innovative information technologies can reduce efficiency and affect the work-life balance. This paper focuses on the audit profession, which had to rethink remote auditing so as to comply with the restrictive measures, but at the same time to avoid affecting the quality of audit missions. The questionnaire distributed among professional practitioners, members of the CFAR, helped us identify the perception of Romanian financial auditors on the variables influencing the efficiency of the audit work carried out in the “new normal” and the extent to which teleworking could become a practice in future financial audit missions.