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Since the COVID-19 Pandemic began, there have been several efforts to create new technology to mitigate the impact of the COVID-19 Pandemic around the world. One of those efforts is to design a new task force, robots, to deal with fundamental goals such as public safety, clinical care, and continuity of work. However, those characteristics need new products based on features that create them more innovatively and creatively. Those products could be designed using the S4 concept (sensing, smart, sustainable, and social features) presented as a concept able to create a new generation of products. This paper presents a low-cost robot, Robocov, designed as a rapid response against the COVID-19 Pandemic at Tecnologico de Monterrey, Mexico, with implementations of artificial intelligence and the S4 concept for the design. Robocov can achieve numerous tasks using the S4 concept that provides flexibility in hardware and software. Thus, Robocov can impact positivity public safety, clinical care, continuity of work, quality of life, laboratory and supply chain automation, and non-hospital care. The mechanical structure and software development allow Robocov to complete support tasks effectively so Robocov can be integrated as a technological tool for achieving the new normality’s required conditions according to government regulations. Besides, the reconfiguration of the robot for moving from one task (robot for disinfecting) to another one (robot for detecting face masks) is an easy endeavor that only one operator could do. Robocov is a teleoperated system that transmits information by cameras and an ultrasonic sensor to the operator. In addition, pre-recorded paths can be executed autonomously. In terms of communication channels, Robocov includes a speaker and microphone. Moreover, a machine learning algorithm for detecting face masks and social distance is incorporated using a pre-trained model for the classification process. One of the most important contributions of this paper is to show how a reconfigurable robot can be designed under the S3 concept and integrate AI methodologies. Besides, it is important that this paper does not show specific details about each subsystem in the robot. 

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Blind and sighted persons can now share and visualize the same piece of data using tactile graphics that glow in ambient light. 

Mononuclear non-heme iron enzymes are a large class of enzymes catalyzing a wide-range of reactions. In this work, we report that a non-heme iron enzyme in Methyloversatilis thermotolerans , OvoA Mtht, has two different activities, as a thiol oxygenase and a sulfoxide synthase. When cysteine is presented as the only substrate, OvoA Mtht is a thiol oxygenase. In the presence of both histidine and cysteine as substrates, OvoA Mtht catalyzes the oxidative coupling between histidine and cysteine (a sulfoxide synthase). Additionally, we demonstrate that both substrates and the active site iron's secondary coordination shell residues exert exquisite control over the dual activities of OvoA Mtht (sulfoxide synthase vs. thiol oxygenase activities). OvoA Mtht is an excellent system for future detailed mechanistic investigation on how metal ligands and secondary coordination shell residues fine-tune the iron-center electronic properties to achieve different reactivities. 

Handheld models help students visualize three-dimensional (3D) objects, especially students with blindness who use large 3D models to visualize imagery by hand. The mouth has finer tactile sensors than hand, which could improve visualization using microscopic models that are portable, inexpensive, and disposable. The mouth remains unused in tactile learning. Here, we created bite-size 3D models of protein molecules from “gummy bear” gelatin or nontoxic resin. Models were made as small as rice grain and could be coded with flavor and packaged like candy. Mouth, hands, and eyesight were tested at identifying specific structures. Students recognized structures by mouth at 85.59% accuracy, similar to recognition by eyesight using computer animation. Recall accuracy of structures was higher by mouth than hand for 40.91% of students, equal for 31.82%, and lower for 27.27%. The convenient use of entire packs of tiny, cheap, portable models can make 3D imagery more accessible to students.