Peer-to-Peer File Sharing WebApp: Enhancing Data Security and Privacy through Peer-to-Peer File Transfer in a Web Application

Peer-to-peer (P2P) networking has emerged as a promising technology that enables distributed systems to operate in a decentralized manner. P2P networks are based on a model where each node in the network can act as both a client and a server, thereby enabling data and resource sharing without relying on centralized servers. The P2P model has gained considerable attention in recent years due to its potential to provide a scalable, fault-tolerant, and resilient architecture for various applications such as file sharing, content distribution, and social networks.In recent years, researchers have also proposed hybrid architectures that combine the benefits of both structured and unstructured P2P networks. For example, the Distributed Hash Table (DHT) is a popular hybrid architecture that provides efficient lookup and search algorithms while maintaining the flexibility and adaptability of the unstructured network.To demonstrate the feasibility of P2P systems, several prototypes have been developed, such as the BitTorrent file-sharing protocol and the Skype voice-over-IP (VoIP) service. These prototypes have demonstrated the potential of P2P systems for large-scale applications and have paved the way for the development of new P2P-based systems

Hypothermia for moderate or severe neonatal encephalopathy in low-income and middle-income countries (HELIX): a randomised controlled trial in India, Sri Lanka, and Bangladesh

Background: Although therapeutic hypothermia reduces death or disability after neonatal encephalopathy in high-income countries, its safety and efficacy in low-income and middle-income countries is unclear. We aimed to examine whether therapeutic hypothermia alongside optimal supportive intensive care reduces death or moderate or severe disability after neonatal encephalopathy in south Asia. Methods: We did a multicountry open-label, randomised controlled trial in seven tertiary neonatal intensive care units in India, Sri Lanka, and Bangladesh. We enrolled infants born at or after 36 weeks of gestation with moderate or severe neonatal encephalopathy and a need for continued resuscitation at 5 min of age or an Apgar score of less than 6 at 5 min of age (for babies born in a hospital), or both, or an absence of crying by 5 min of age (for babies born at home). Using a web-based randomisation system, we allocated infants into a group receiving whole body hypothermia (33·5°C) for 72 h using a servo-controlled cooling device, or to usual care (control group), within 6 h of birth. All recruiting sites had facilities for invasive ventilation, cardiovascular support, and access to 3 Tesla MRI scanners and spectroscopy. Masking of the intervention was not possible, but those involved in the magnetic resonance biomarker analysis and neurodevelopmental outcome assessments were masked to the allocation. The primary outcome was a combined endpoint of death or moderate or severe disability at 18–22 months, assessed by the Bayley Scales of Infant and Toddler Development (third edition) and a detailed neurological examination. Analysis was by intention to treat. This trial is registered with ClinicalTrials.gov, NCT02387385. Findings: We screened 2296 infants between Aug 15, 2015, and Feb 15, 2019, of whom 576 infants were eligible for inclusion. After exclusions, we recruited 408 eligible infants and we assigned 202 to the hypothermia group and 206 to the control group. Primary outcome data were available for 195 (97%) of the 202 infants in the hypothermia group and 199 (97%) of the 206 control group infants. 98 (50%) infants in the hypothermia group and 94 (47%) infants in the control group died or had a moderate or severe disability (risk ratio 1·06; 95% CI 0·87–1·30; p=0·55). 84 infants (42%) in the hypothermia group and 63 (31%; p=0·022) infants in the control group died, of whom 72 (36%) and 49 (24%; p=0·0087) died during neonatal hospitalisation. Five serious adverse events were reported: three in the hypothermia group (one hospital readmission relating to pneumonia, one septic arthritis, and one suspected venous thrombosis), and two in the control group (one related to desaturations during MRI and other because of endotracheal tube displacement during transport for MRI). No adverse events were considered causally related to the study intervention. Interpretation: Therapeutic hypothermia did not reduce the combined outcome of death or disability at 18 months after neonatal encephalopathy in low-income and middle-income countries, but significantly increased death alone. Therapeutic hypothermia should not be offered as treatment for neonatal encephalopathy in low-income and middle-income countries, even when tertiary neonatal intensive care facilities are available. Funding: National Institute for Health Research, Garfield Weston Foundation, and Bill & Melinda Gates Foundation. Translations: For the Hindi, Malayalam, Telugu, Kannada, Singhalese, Tamil, Marathi and Bangla translations of the abstract see Supplementary Materials section

Brain Controlled Car using Deep Neural Network

Brain Computer Interface (BCI) isthe modern technology which uses the brainneural activity to control the machines,robots, etc. This paper focuses on processingof the signals received from theElectroencephalography (EEG) headset intodirections using Artificial Neural Network.The main aim is to control a car usingNeurosky Mindwave Mobile headset. Thegoal is to help people suffering fromdisabilities and motion syndrome. The EEGheadset is placed on the head of the user andsignals like Alpha1, Alpha2, attention level,meditation level, blink and raw signals arerecorded. The pre-processed signal and feedforwardArtificial Neural Network are usedfor classification. ANN is developed in 3layers: input, hidden and output. The sixsignals received from Neurosky Mindwaveheadset is given as input to ANN. This willidentify the direction of the car to moveforward, backward, left, right or stop

Cloud computing adoption in the government sector in Brazil: an exploratory study with recommendations from IT Managers

Cloud Computing constitutes an alternative for organizations that want to op-timize the use of computing resources and rationalize costs with IT infrastructure. How-ever, the adoption and implementation in the government sector pose several challenges, regarding IT control, data protection in the Internet, efficient use of computing resources and cost rationalization. Within the government sector, the lack of knowledge about is-sues involving adoption and migration to cloud computing may negatively impact IT.This study aims to identifythe factors influencing the adoption of cloud computing in the government sector in Brazil. We carried out the study interviewing IT professionalsthat successfully migrated to the cloud with three organizations, two large and public univer-sities and one data processing agency. Using the approach Value-Focused Thinking, we analyzed the data collected from the interviews.Our Findings revealed a set of twenty-one recommendationsto take into account when implementing cloud computing in the government sector, such asusing a pilot project, training,andconsulting, amongothers. These recommendations are useful to guide the IT decision makers in the process of cloud computing adoptionand implementationas an efficient and reliable approachin the government sectorFCT –Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/201