Broad Spectrum Algae Compounds Against Viruses

The pharmaceutical industry is currently trying to develop new bioactive compounds to inactivate both enveloped and non-enveloped viruses for therapeutic purposes. Consequently, microalgal and macroalgal bioactive compounds are being explored by pharmaceutical, as well as biotechnology and food industries. In this review, we show how compounds produced by algae include important candidates for viral control applications. We discuss their mechanisms of action and activity against enveloped and non-enveloped viruses, including those causing infections by enteric, parenteral, and respiratory routes. Indeed, algal products have potential in human and animal medicine.

Evolutionary vs. imitation learning for neuromorphic control at the edge

Neuromorphic computing offers the opportunity to implement extremely low power artificial intelligence at the edge. Control applications, such as autonomous vehicles and robotics, are also of great interest for neuromorphic systems at the edge. It is not clear, however, what the best neuromorphic training approaches are for control applications at the edge. In this work, we implement and compare the performance of evolutionary optimization and imitation learning approaches on an autonomous race car control task using an edge neuromorphic implementation. We show that the evolutionary approaches tend to achieve better performing smaller network sizes that are well-suited to edge deployment, but they also take significantly longer to train. We also describe a workflow to allow for future algorithmic comparisons for neuromorphic hardware on control applications at the edge.

Application of Healthy and Safe Internet in Controlling Negative Internet Impacts for Students at MI Darussa'adah, South Jakarta.

The use of gadgets today has become a major requirement for everyone. In the present, many children are using gadget since childhood especially to watch videos on youtube, play online games, and search for learning materials through the help of the internet.This can be a good step so that children easily adapt to technological developments. But on the other hand, parents must worry if children play gadgets too often and access things that are not age-appropriate, which is not necessarily suitable for their age. It is important for parents to monitor the use of gadgets in children. The role of parents and teachers in dealing with this situation, they must have the ability to monitor and control the use of the internet by parental control applications. It is able to select, limit, and supervise what applications can be accessed by children and adolescents so they can still use gadgets as a learning and entertainment medium without having to be addicted and poisoned by negative content.

Identification of a Spatio-Temporal Temperature Model for Laser Metal Deposition

Laser-based additive manufacturing enables the production of complex geometries viaayer-wise cladding. Laser metal deposition (LMD) uses a scanningaser source to fuse in situ deposited metal powderayer byayer. However, due to the excessive number of influential factors in the physical transformation of the metal powder and the highly dynamic temperature fields caused by the melt pool dynamics and phase transitions, the quality and repeatability of parts built by this process is still challenging. In order to analyze and/or predict the spatially varying and time dependent thermal behavior in LMD, extensive work has been done to develop predictive models usually by using finite element method (FEM). From a control-oriented perspective, simulations based on these models are computationally too expensive and are thus not suitable for real-time control applications. In this contribution, a spatio-temporal input–output model based on the heat equation is proposed. In contrast to other works, the parameters of the model are directly estimated from measurements of the LMD process acquired with an infrared (IR) camera during processing specimens using AISI 316 L stainless steel. In order to deal with noisy data, system identification techniques are used taking different disturbing noise into account. By doing so, spatio-temporal models are developed, enabling the prediction of the thermal behavior by means of the radiance measured by the IR camera in the range of the considered processing parameters. Furthermore, in the considered modeling framework, the computational effort for thermal prediction is reduced compared to FEM, thus enabling the use in real-time control applications.