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Sinking marine particles drive the biological pump that naturally sequesters carbon from the atmosphere. Despite their small size, the compartmentalized nature of particles promotes intense localized metabolic activity by their bacterial colonizers. Yet the mechanisms promoting the onset of denitrification, a metabolism that arises once oxygen is limiting, remain to be established. Here we show experimentally that slow sinking aggregates composed of marine diatoms—important primary producers for global carbon export—support active denitrification even among bulk oxygenated water typically thought to exclude anaerobic metabolisms. Denitrification occurs at anoxic microsites distributed throughout a particle and within microns of a particle’s boundary, and fluorescence-reporting bacteria show nitrite can be released into the water column due to segregated dissimilatory reduction of nitrate and nitrite. Examining intact and broken diatoms as organic sources, we show slowly leaking cells promote more bacterial growth, allow particles to have lower oxygen, and generally support greater denitrification.

 

Mechatronics for Technologists and Technicians was recognized as an occupation by the U.S. Department of Labor in 2019 and was given the code 49-2094.00. In 2022 the occupation was migrated to the code 17-3024.00 and titled "Electro-Mechanical and Mechatronics Technologists and Technicians". Several organizations offer certifications in the mechatronics occupation that we list here. The major challenge that faces mechatronics education is the decline in the job market that is projected to stand at -2 % over the next decade for holders of bachelor’s or lower degrees. This is attributed to the post-pandemic remote work trend and the hard-hit manufacturing industry during the pandemic. This decline is coupled with an aggressive growth in the job market for holders of graduate degrees (standing at over 11% growth) due to the growing demand in research and innovation and engineering training. 

In this work we investigate the effectiveness of two train-the-trainer workshops on intelligent industrial robotics. The two workshops, which took place in summer 2021 in Tennessee and Alabama, were the first of a series of six workshops. A total of 32 persons applied to the two summer workshops from 10 states, of whom 15 attended and successfully completed the workshops. Evaluation results show that the participants’ knowledge on industrial robotics significantly improved after the workshops, and the vast majority indicated that the training will be used in their home institutions. The major challenge faced during the workshops was the spread of the delta variant of CoVid-19 at the time the workshops were scheduled to take place, and the wide diversity of the educational background of participants. 

In this paper we present recent advances, current and future market trends in industrial robotics. Artificial Intelligence has evolved as the main feature to characterize Industry 4.0, Next-generation robotics utilize this feature to perform tasks collaboratively, as opposed to the currently deployed industrial robots, which were designed mainly for automation, isolated in cages, and highly-controlled environments. Current data show that China takes the lead in the industrial robotics market with 48% of the top-ten market in 2019. The electronics sector took the lead in robot-deployment in East Asia, and is continuously increasing in deploying industrial robotics in other parts of the world. Studies on the challenges associated with this technology, show that the main concern is the lack of trained labor to handle the technologies in next generation industrial robotics. 

A low-cost remote supervisory control capability is added to a packaging process, in which a low-voltage signal is used to communicate between a distant HMI control panel and a PLC network using the AC power line as a communication medium. The network is a star-topology and uses a Mater-slave protocol. Remote Supervisory control is achieved using a user-defined toolbox of control functions. In this system, a Programmable Logic Controller (PLC) is used to control a process and interface with the operator through a Human Machine Interface (HMI) Panel. A star topology ethernet network is used to connect the PLCs and the HMI panel. 

In this paper we demonstrate two applications of a low-cost remote supervisory control and data acquisition system in two models. The first model is demonstrated with a Profibus-DP protocol based system in which a master Programmable Logic Controller (PLC) unit with control inputs and display outputs controls the speed and monitors the overload condition of a DC motor that is connected to a slave PLC in real time. In the upgraded model, a Profinet protocol is used to connect PLCs, and a power-line communication link is used to remotely connect the control HMI to the network. In both models, remote Supervisory control is achieved using user-defined control functions that act altogether as a block-oriented function library or toolbox. High levels of performance are achieved in real time control and data acquisition in both models.