As humans, we have given our best into critical thinking to improve our lives, bringing us into the age of information and communication technology. We have also devised means and ways to prolong and save human lives from unforeseen circumstances and cut back on response time to emergencies. This perhaps is why life expectancy has improved for people, especially in developed nations. In recent times, we are using technology to improve our healthcare and general wellbeing. So, this is to let you get a glimpse of some high-techs we [humans] have developed, already in the works, or need to establish that can save more lives and further improve our general wellbeing.

This article highlights a revolutionary new approach to offering Ultra-Personalised, Artificial Intelligence-Enabled Healthcare from Cortex Logic which is set to transform the way medical aid schemes, consumers and corporates offering employee benefits as part of their EAP (Employee Assistance Programmes) view their current healthcare offering. The Journey Wellness platform is perfectly timed to coincide with the current global shift in Healthcare, as the focus moves from a disease-management model to one that encourages optimum health and disease-avoidance, targeting younger as well as existing members with a holistic, pro-active offering. Journey Wellness was also recently introduced through the articles "Access To AI-Driven Platforms Can Improve Health And Financial Wellness – Cortex Group" and "This New AI-Enabled, Personalised Healthcare Platform Wants To Revolutionize Wellness & Healthcare In SA" as well as a number of presentations and interviews by Dr Jacques Ludik, Founder and CEO of Cortex Logic and President of the Machine Intelligence Institute of Africa MIIA, who has also recently written a book called'Democratizing Artificial Intelligence to Benefit Everyone'. He says that the Journey Wellness platform will provide more healthcare, to more people, faster. Dr Ludik explained that its AI-enabled, ultra-personalized health wellness platform, called Journey Wellness here in South Africa, provides real-time, relevant, on-demand and proactive guidance, advice, support and recommendations to help optimize a user's wellness whilst ensuring high standards of data privacy and choice. The system makes use of the Cortex AI engine to build a holistic and dynamic 360-degree wellness profile and has an AI-driven personalized wellness coach that provides information and personalized advice, coaching and guidance with respect to healthy eating and diet, exercise and fitness, mental wellness and health with a specific focus on chronic lifestyle diseases.

Much has been made about the rich and inclusive story in this year's edition of the popular Call of Duty video game franchise. That may be, but "Call of Duty: Vanguard," out Friday for PlayStation 5, PS4, Xbox Series X/S, Xbox One and PCs ($59.99-up, You are part of a team of special forces soldiers trying to commandeer a German train buzzing toward Hamburg. You must dodge gunfire from Nazis on both rail lines and German military trucks buzzing between the set of tracks. Your team, led by Sgt.

A Neyman-Scott process is a special case of a Cox process. The latent and observable stochastic processes are both Poisson processes. We consider a deep Neyman-Scott process in this paper, for which the building components of a network are all Poisson processes. We develop an efficient posterior sampling via Markov chain Monte Carlo and use it for likelihood-based inference. Our method opens up room for the inference in sophisticated hierarchical point processes. We show in the experiments that more hidden Poisson processes brings better performance for likelihood fitting and events types prediction. We also compare our method with state-of-the-art models for temporal real-world datasets and demonstrate competitive abilities for both data fitting and prediction, using far fewer parameters.

A modified commercial drone may have been responsible for an attempted attack on a Pennsylvania power substation last year, the first reported case of a drone assault on the U.S.'s energy infrastructure. Authorities believe a DJI Mavic 2 drone with a thick copper wire tethered to it was found in June 2020 was likely intended to disrupt operations'by creating a short circuit to cause damage to transformers or distribution lines,' according to a joint intelligence bulletin from the FBI, Department of Homeland Security, and the National Counterterrorism Center released October 28. If the wire had come into contact with any of the power plant's high-voltage equipment it could have resulted in a short circuit, power failure or even a fire, according to New Scientist. The Drive reported the drone was recovered by authorities from a substation near Hershey, Pennsylvania, about 100 miles from Philadelphia. No groups has claimed responsibility: The device's camera and internal memory card had been removed and identifying labels were removed, in a likely attempt to obscure its origins.

A Canadian startup has made the process of getting a COVID-19 vaccine much easier with a robot that injects a shot directly into the muscle without the use of a needle. Developers of the Cobi robot, designed at the University of Waterloo in Ontario, say the droid has successfully performed the first autonomous robotic intramuscular injection. Cobi relies on a high-pressure jet of serum that passes through an opening in the skin the width of a human hair. Using LiDAR sensors, the same technology employed by autonomous vehicles to map the road, Cobi makes a model of the patient's body and AI-based software determines the optimal site for injection. 'We outfitted Cobi to use a needle-free injection technology and to demonstrate that patients could receive intramuscular injections, such as vaccines, without needles and no involvement from a healthcare professional,' said Tim Lasswell, co-founder and CEO of Cobionix in a statement.

Thirty years ago this month, Europe's most famous mummy was discovered lying face-down in the ice, on the edge of a lake nearly two miles high in the Ötztal Alps bordering Austria and Italy. Naturally preserved by more than 5,000 years of sun, wind, and freezing temperatures, the leathery remains of Ötzi the Iceman quickly became a global sensation, the subject of countless books and documentaries and even a feature film reconstructing his life in Neolithic Europe and his violent death. Today, Ötzi is carefully tended to by researchers at the South Tyrol Museum of Archaeology in Bolzano, Italy, where his wizened body is kept in a custom cold chamber maintained at a constant temperature of –21.2 degrees Fahrenheit. Four or five times a year, his remains are sprayed with sterile water to create an icy, protective exoskeleton that ensures he stays a "wet mummy" (one naturally preserved in a wet rather than dry environment). Go behind the scenes of Ötzi's 2010 autopsy.

Theoretical analyses for graph learning methods often assume a complete observation of the input graph. Such an assumption might not be useful for handling any-size graphs due to the scalability issues in practice. In this work, we develop a theoretical framework for graph classification problems in the partial observation setting (i.e., subgraph samplings). Equipped with insights from graph limit theory, we propose a new graph classification model that works on a randomly sampled subgraph and a novel topology to characterize the representability of the model. Our theoretical framework contributes a theoretical validation of mini-batch learning on graphs and leads to new learning-theoretic results on generalization bounds as well as size-generalizability without assumptions on the input.

An automated feature selection pipeline was developed using several state-of-the-art feature selection techniques to select optimal features for Differentiating Patterns of Care (DPOC). The pipeline included three types of feature selection techniques; Filters, Wrappers and Embedded methods to select the top K features. Five different datasets with binary dependent variables were used and their different top K optimal features selected. The selected features were tested in the existing multi-dimensional subset scanning (MDSS) where the most anomalous subpopulations, most anomalous subsets, propensity scores, and effect of measures were recorded to test their performance. This performance was compared with four similar metrics gained after using all covariates in the dataset in the MDSS pipeline. We found out that despite the different feature selection techniques used, the data distribution is key to note when determining the technique to use.

However, when Dazed tested it using country names, it described the UK and US as "good", France as "nice", and Russia as "a great place to visit", but said Nigeria, Mexico, and Iraq were "dangerous", while Iran was "bad". Clearly, the software – like much artificial intelligence – has a problem with racism. Its creators have addressed this in a post-launch Q&A, writing: "Today's society is unequal and biased. This is a common issue with AI systems, as many scholars have argued, because AI systems are trained on historical or present data and have no way of shaping the future of society, only humans can. What AI systems like Delphi can do, however, is learn about what is currently wrong, socially unacceptable, or biased, and be used in conjunction with other, more problematic, AI systems (to) help avoid that problematic content."