Patterns and Association of Pediatrics Head Injury Due to Fall in Accordance to Height

Background and Purpose: The authors conducted a study to describe the patterns and association of fall related head injuries in pediatric population and also to compare it with the western world.Methods: We performed a retrospective analysis of all patients less than 15 years of age treated for fall – related trauma between June, 2009 and September, 2011. Falls were classified as low (12 feet) and high level (more than12 feet).Results: Eight hundred and sixty cases were identified with a mortality rate of 6.7%. A fall of greater than 12 feet (high – level fall) was associated with a higher mortality rate than low – level falls 52 (5.7% Compared with 5 (1.0%), respectively). Two Hundred and twenty eight patients had sustained a skull fracture (150 children had a depressed skull fracture) and 80 patients had basal skull fracture, 46 patients had suffered a cerebral contusion, 25 subarachnoid hemorrhage, 42 subdural hematoma, and 82 had an epidural / extradural hematoma. One hundred twenty patients required surgery for traumatic injuries of these, 80 underwent craniotomy for evacuation of a blood clot. Height was not predictive of the Glasgow Coma Scale (GCS) score. In all 15 deaths resulting from a low – level fall there was an admission GCS score of 4/15, and abnormal findings were demonstrated on computerized tomography scanning. Death from high – level falls was attributable to either intracranial injuries (50%) or severe extra-cranial injuries (50%). Intracranial injury is the major source of fall – related death in children and, unlike extra-cranial insults, brain injuries are sustained with equal frequency from low – and high – level falls in this population. Height was not predictive of the Glasgow Coma Scale (GCS) score. In all 15 deaths resulting from a low – level fall there was an admission GCS score of 4/15, and abnormal findings were demon-strated on computerized tomography scanning.Conclusion: The GCS scores obtained in patients who sustained a Low – level fall were a poor predictor of intracranial bleeding. In 47% of these patients with intracranial bleeding an Emergency room GCS score of 13 to 15 was determined. A high GCS score does not therefore; eliminate the need for performing head CT scanning, even after the patient suffers a low level fall. We found a high percentage of intracranial bleeding/cranial frac-tures in patients falling from low height. Physicians should obtain a brain CT scan in pediatric fall victims. A proper trauma protocol should be followed and made in accordance of our need and standards

Qualitative Assessment of the Pharmacist’s Role in Punjab, Pakistan: Medical Practitioners’ Views

Purpose: To assess the perception of Pakistani doctors regarding pharmacist’s role in Punjab Pakistan.Methods: A qualitative approach was used to assess the perception of doctors regarding pharmacist’s role in the study setting. A total of 12 doctors were interviewed using a semi- structured interview guide. The study was conducted for a period of 3 months in the Pakistani cities of Islamabad and Lahore, from July to September 2011. Doctors were informed regarding the aim, objective and nature of the study.Results: All the interviews were transcribed verbatim and thematically analyzed for their content. Thematic content analysis yielded four major themes: 1) Availability of pharmacist in Pakistan’s healthcare setting. 2) Willingness to collaborate with pharmacist. 3) Separation of prescribing from dispensing. 4) Difference in academic levels of doctors and pharmacist.Conclusion: Doctors are receptive to an expanded role for pharmacists, also regard them as drug information experts, but their expectations fall short of the quality of clinically-focused pharmacy services that pharmacists are actually rendering.Keywords: Doctors’ expectation, Pharmacist, Clinical pharmacy services, Qualitative study, Prescribin

Dynamic Hand Gesture Recognition Using 3D-CNN and LSTM Networks

Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video stream. Many researchers have been working on vision-based gesture recognition due to its various applications. This paper proposes a deep learning architecture based on the combination of a 3D Convolutional Neural Network (3D-CNN) and a Long Short-Term Memory (LSTM) network. The proposed architecture extracts spatial-temporal information from video sequences input while avoiding extensive computation. The 3D-CNN is used for the extraction of spectral and spatial features which are then given to the LSTM network through which classification is carried out. The proposed model is a light-weight architecture with only 3.7 million training parameters. The model has been evaluated on 15 classes from the 20BN-jester dataset available publicly. The model was trained on 2000 video-clips per class which were separated into 80% training and 20% validation sets. An accuracy of 99% and 97% was achieved on training and testing data, respectively. We further show that the combination of 3D-CNN with LSTM gives superior results as compared to MobileNetv2 + LSTM

Formal Modeling and Improvement in the Random Path Routing Network Scheme Using Colored Petri Nets

Wireless sensor networks (WSNs) have been applied in networking devices, and a new problem has emerged called source-location privacy (SLP) in critical security systems. In wireless sensor networks, hiding the location of the source node from the hackers is known as SLP. The WSNs have limited battery capacity and low computational ability. Many state-of-the-art protocols have been proposed to address the SLP problems and other problems such as limited battery capacity and low computational power. One of the popular protocols is random path routing (RPR), and in random path routing, the system keeps sending the message randomly along all the possible paths from a source node to a sink node irrespective of the path’s distance. The problem arises when the system keeps sending a message via the longest route, resulting because of high battery usage and computational costs. This research paper presents a novel networking model referred to as calculated random path routing (CRPR). CRPR first calculates the top three shortest paths, and then randomly sends a token to any of the top three shortest calculated paths, ensuring the optimal tradeoff between computational cost and SLP. The proposed methodology includes the formal modeling of the CRPR in Colored Petri Nets. We have validated and verified the CRPR, and the results depict the optimal tradeoff

Formal Modeling and Improvement in the Random Path Routing Network Scheme Using Colored Petri Nets

Wireless sensor networks (WSNs) have been applied in networking devices, and a new problem has emerged called source-location privacy (SLP) in critical security systems. In wireless sensor networks, hiding the location of the source node from the hackers is known as SLP. The WSNs have limited battery capacity and low computational ability. Many state-of-the-art protocols have been proposed to address the SLP problems and other problems such as limited battery capacity and low computational power. One of the popular protocols is random path routing (RPR), and in random path routing, the system keeps sending the message randomly along all the possible paths from a source node to a sink node irrespective of the path’s distance. The problem arises when the system keeps sending a message via the longest route, resulting because of high battery usage and computational costs. This research paper presents a novel networking model referred to as calculated random path routing (CRPR). CRPR first calculates the top three shortest paths, and then randomly sends a token to any of the top three shortest calculated paths, ensuring the optimal tradeoff between computational cost and SLP. The proposed methodology includes the formal modeling of the CRPR in Colored Petri Nets. We have validated and verified the CRPR, and the results depict the optimal tradeoff