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When cyanobacterial phytoplankton form harmful cyanobacterial blooms (HCBs), the toxins they produce threaten freshwater ecosystems. Hydrogen peroxide is often used to control HCBs, but it is broadly toxic and dangerous to handle. Previously, we demonstrated that glucose addition to lake water could suppress the abundance of cyanobacteria. In this study, glucose was compared to hydrogen peroxide for the treatment of cyanobacterial phytoplankton communities. The six-week study was conducted in the large mesocosms facility at Grand Valley State University’s Annis Water Resources Institute in Michigan. To 1000 L of Muskegon Lake water, glucose was added at either 150 mg or 30 mg glucose/L. Hydrogen peroxide was added at 3 mg/L to two 1000 L mesocosms. And two mesocosms were left untreated as controls. Triplicate 100 mL samples were collected weekly from each mesocosm, which were then filtered and frozen at −80 °C for 16S rRNA amplicon sequencing. The 16S rRNA amplicon sequencing results revealed that hydrogen peroxide treatment quickly reduced the relative abundance of the cyanobacteria compared to the control mesocosms, but the cyanobacteria population returned over the course of the 6-week study. On the other hand, both glucose concentrations caused a rapid proliferation of multiple low abundance proteobacterial and bacteroidotal taxa resulting in notable increases in taxonomic richness over the duration of the study and reducing the relative abundance of cyanobacteria. Although hydrogen peroxide quickly suppressed the cyanobacteria, the population later returned to near starting levels. The glucose suppressed the cyanobacterial phytoplankton apparently by promoting competitive heterotrophic bacteria.

Strategies for mitigating the impacts of cyberattacks on control systems using a control-oriented perspective have become of greater interest in recent years. Our group has contributed to this trend by developing several methods for detecting cyberattacks on process sensors, actuators, or both sensors and actuators simultaneously using an advanced optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC). However, each technique comes with benefits and limitations, both with respect to one another and with respect to traditional information technology and computer science-type approaches to cybersecurity. An important question to ask, therefore, is what the goal should be of the development of new control-based techniques for handling cyberattacks on control systems, and how we will be able to benchmark these as “successful” compared to other techniques to drive development or signal when the research in this direction has reached maturity. In this paper, we propose that the goal of research in control system cybersecurity for next-generation manufacturing should be the development of a security architecture that provides flexibility and safety with lowest cost, and seek to clarify this concept by re-analyzing some of the security techniques from our prior work in such a context. We also show how new methods can be developed and analyzed within this “minimum security architecture” context by proposing a technique which we term “directed randomization” that may require less sensors to be secured in a system than some of our prior methods, potentially adding flexibility to the system while still maintaining security. Directed randomization seeks to utilize the existence of two possible stabilizing inputs at every sampling time to attempt to create a challenge for an attacker for setting up an arbitrary sensor attack policy without being detected within a finite number of sampling periods. We discuss benefits and limitations of this technique with respect to our prior cybersecurity strategies and also with respect to extended versions of these prior concepts, such as image-based control and distributed control, to provide further insights into the minimum security concept.

Background The high prevalence of mental distress among university students is gaining academic, policy and public attention. As the volume of research into student mental health increases, it is important to involve students to ensure that the evidence produced can translate into meaningful improvements. Aims For the first time, we consult UK students about their research priorities on student mental health. Method This priority setting exercise involved current UK university students who were asked to submit three research questions relating to student mental health. Responses were aggregated into themes through content analysis and considered in the context of existing research. Students were involved throughout the project, including inception, design, recruitment, analysis and dissemination. Results UK university students (N = 385) submitted 991 questions, categorised into seven themes: epidemiology, causes and risk factors, academic factors and work–life balance, sense of belonging, intervention and services, mental health literacy and consequences. Across themes, respondents highlighted the importance of understanding the experience of minority groups. Conclusions Students are interested in understanding the causes and consequences of poor mental health at university, across academic and social domains. They would like to improve staff and students’ knowledge about mental health, and have access to evidence-based support. Future research should take a broad lens to evaluate interventions; considering how services are designed and delivered, and investigating institutional and behavioural barriers to accessibility, including how this varies across different groups within the student population.