Traditional optimal power flow (OPF) ensures power systems are operated safely at minimum cost. Recent disasters have highlighted that a focus on minimizing cost can result in a fragile system, such ...as the immense economic loss and adverse societal impacts after the 2021 Texas Winter Storm. Resilience objectives must also be considered to guide power system operation through unexpected non-ideal conditions. The long-term survivability of ecosystems against various unexpected catastrophes has been quantified by ecologists using the metric <inline-formula><tex-math notation="LaTeX">\mathit{R_{ECO}}</tex-math></inline-formula>. The metric depends on a system's network structure and energy flows, enabling its application to power systems to investigate the impact of a bio-inspired power system to address resilience needs. This paper formulates an ecological robustness oriented OPF (<inline-formula><tex-math notation="LaTeX">R_{ECO}</tex-math></inline-formula> OPF) problem to optimize power systems for reliability and survivability under unexpected contingencies. Six power system cases, ranging from 24- to 500-buses are optimized, comparing the reliability and cost of the <inline-formula><tex-math notation="LaTeX">{R_{ECO}}</tex-math></inline-formula> OPF with an economics-driven OPF and a security-constrained OPF (SCOPF). The results show the ecologically-inspired method is able to improve the reliability of the power systems with fewer violations and unsolved scenarios during unexpected disturbances. The results also support the potential to use <inline-formula><tex-math notation="LaTeX">{R_{ECO}}</tex-math></inline-formula> to control power flow distribution for improved survivability and resilience.
Bacteria contain an immense untapped trove of novel secondary metabolites in the form of 'silent' biosynthetic gene clusters (BGCs). These can be identified bioinformatically but are not expressed ...under normal laboratory growth conditions. Methods to access their products would dramatically expand the pool of bioactive compounds. We report a universal high-throughput method for activating silent BGCs in diverse microorganisms. Our approach relies on elicitor screening to induce the secondary metabolome of a given strain and imaging mass spectrometry to visualize the resulting metabolomes in response to ~500 conditions. Because it does not require challenging genetic, cloning, or culturing procedures, this method can be used with both sequenced and unsequenced bacteria. We demonstrate the power of the approach by applying it to diverse bacteria and report the discovery of nine cryptic metabolites with potentially therapeutic bioactivities, including a new glycopeptide chemotype with potent inhibitory activity against a pathogenic virus.
Light-driven water oxidation is a fundamental reaction in the biosphere. The Mn4Ca cluster of photosystem II cycles through five redox states termed S0–S4, after which oxygen is evolved. Critically, ...the timing of O–O bond formation within the Kok cycle remains unknown. By combining recent crystallographic, spectroscopic, and DFT results, we demonstrate an atomistic S3 state model with the possibility of a low barrier to O–O bond formation prior to the final oxidation step. Furthermore, the associated one electron oxidized S4 state does not provide more advantages in terms of spin alignment or the energy of O–O bond formation. We propose that a high energy peroxide isoform of the S3 state can preferentially be oxidized by Tyr z ox in the course of final electron transfer leading to O2 evolution. Such a mechanism may explain the peculiar kinetic behavior of O2 evolution as well as serve as an evolutionary adaptation to avoid release of the harmful peroxides.
False alerts due to misconfigured or compromised intrusion detection systems (IDS) in industrial control system (ICS) networks can lead to severe economic and operational damage. However, research ...using deep learning to reduce false alerts often requires the physical and cyber sensor data to be trustworthy. Implicit trust is a major problem for artificial intelligence or machine learning (AI/ML) in cyber-physical system (CPS) security, because when these solutions are most urgently needed is also when they are most at risk (e.g., during an attack). To address this, the Inter-Domain Evidence theoretic Approach for Inference (IDEA-I) is proposed that reframes the detection problem as how to make good decisions given uncertainty. Specifically, an evidence theoretic approach leveraging Dempster-Shafer (DS) combination rules and their variants is proposed for reducing false alerts. A multi-hypothesis mass function model is designed that leverages probability scores obtained from supervised-learning classifiers. Using this model, a location-cum-domain-based fusion framework is proposed to evaluate the detector's performance using disjunctive, conjunctive, and cautious conjunctive rules. The approach is demonstrated in a cyber-physical power system testbed, and the classifiers are trained with datasets from Man-In-The-Middle attack emulation in a large-scale synthetic electric grid. For evaluating the performance, we consider plausibility, belief, pignistic, and general Bayesian theorem-based metrics as decision functions. To improve the performance, a multi-objective-based genetic algorithm is proposed for feature selection considering the decision metrics as the fitness function. Finally, we present a software application to evaluate the DS fusion approaches with different parameters and architectures.
False data injection attacks (FDIA) are a main category of cyber-attacks threatening the security of power systems. Contrary to the detection of these attacks, less attention has been paid to ...identifying the attacked units of the grid. To this end, this work jointly studies detecting and localizing the stealth FDIA in power grids. Exploiting the inherent graph topology of power systems as well as the spatial correlations of measurement data, this paper proposes an approach based on the graph neural network (GNN) to identify the presence and location of the FDIA. The proposed approach leverages the auto-regressive moving average (ARMA) type graph filters (GFs) which can better adapt to sharp changes in the spectral domain due to their rational type filter composition compared to the polynomial type GFs such as Chebyshev. To the best of our knowledge, this is the first work based on GNN that automatically detects and localizes FDIA in power systems. Extensive simulations and visualizations show that the proposed approach outperforms the available methods in both detection and localization of FDIA for different IEEE test systems. Thus, the targeted areas can be identified and preventive actions can be taken before the attack impacts the grid.
Power systems are critical infrastructure for reliable and secure electric energy delivery. Incidents are increasing, as unexpected multiple hazards ranging from natural disasters to cyberattacks ...threaten the security and functionality of society. Inspired by resilient ecosystems, this article presents a resilient network design approach with an ecological robustness (RECO)-oriented optimization to improve power systems' ability to maintain a secure operating state throughout unknown hazards. The approach uses RECO, a surprisal -based metric that captures key features of an ecosystem's resilient structure, as an objective to strategically design the electrical network. The approach enables solvability and practicality by introducing a stochastic-based candidate branch creation algorithm and a Taylor series expansion for relaxation of the RECO formulation. Finally, studies are conducted on the RECO-oriented approach using the IEEE 24 Bus RTS and the ACTIVSg200 systems. Results demonstrate improvement of the system's reliability under multiple hazards, network properties of robust structure and equally distributed power flows, and survivability against cascading failures. From the analysis, we observe that a more redundant network structure with equally distributed power flows benefits its resilience.
Many retinal dystrophies result in photoreceptor loss, but the inner retinal neurons can survive, making them potentially amenable to emerging optogenetic therapies. Here, we show that ectopically ...expressed human rod opsin, driven by either a non-selective or ON-bipolar cell-specific promoter, can function outside native photoreceptors and restore visual function in a mouse model of advanced retinal degeneration. Electrophysiological recordings from retinal explants and the visual thalamus revealed changes in firing (increases and decreases) induced by simple light pulses, luminance increases, and naturalistic movies in treated mice. These responses could be elicited at light intensities within the physiological range and substantially below those required by other optogenetic strategies. Mice with rod opsin expression driven by the ON-bipolar specific promoter displayed behavioral responses to increases in luminance, flicker, coarse spatial patterns, and elements of a natural movie at levels of contrast and illuminance (≈50–100 lux) typical of natural indoor environments. These data reveal that virally mediated ectopic expression of human rod opsin can restore vision under natural viewing conditions and at moderate light intensities. Given the inherent advantages in employing a human protein, the simplicity of this intervention, and the quality of vision restored, we suggest that rod opsin merits consideration as an optogenetic actuator for treating patients with advanced retinal degeneration.
•Ectopic human rod opsin restores visual functions in advanced retinal degeneration•Rod opsin has greater sensitivity than current optogenetic strategies•Rod opsin-treated animals respond to spatial stimuli, flicker, and natural scenes•As a human protein ordinarily found in retinal tissue, barriers to clinic are minimized
Cehajic-Kapetanovic at al. show that ectopically expressed human rod opsin restores vision in a mouse model of advanced retinal degeneration. The quality of the restored vision compares favorably, especially in terms of sensitivity, with alternative approaches, and using a native human protein reduces barriers to future clinical trials.
Many sex differences in brain and behavior are programmed during development by gonadal hormones, but the cellular mechanisms are incompletely understood. We found that immune-system-derived mast ...cells are a primary target for the masculinizing hormone estradiol and that mast cells are in turn primary mediators of brain sexual differentiation. Newborn male rats had greater numbers and more activated mast cells in the preoptic area (POA), a brain region essential for male copulatory behavior, than female littermates during the critical period for sexual differentiation. Inhibiting mast cells with a stabilizing agent blunted the masculinization of both POA neuronal and microglial morphology and adult sex behavior, whereas activating mast cells in females, even though fewer in number, induced masculinization. Treatment of newborn females with a masculinizing dose of estradiol increased mast cell number and induced mast cells to release histamine, which then stimulated microglia to release prostaglandins and thereby induced male-typical synaptic patterning. These findings identify a novel non-neuronal origin of brain sex differences and resulting motivated behaviors.
We found that immune-system-derived mast cells are a primary target for the masculinizing hormone estradiol and that mast cells are in turn primary mediators of brain sexual differentiation. These findings identify a novel non-neuronal origin of brain sex differences and resulting motivated behaviors.
Marine microbes exhibit seasonal cycles in community composition, yet the key drivers of these patterns and microbial population fidelity to specific environmental conditions remain to be determined. ...To begin addressing these questions, we characterized microbial dynamics weekly for 3 years at a temperate, coastal site with dramatic environmental seasonality. This high-resolution time series reveals that changes in microbial community composition are not continuous; over the duration of the time series, the community instead resolves into distinct summer and winter profiles with rapid spring and fall transitions between these states. Here, we show that these community shifts involve switching between closely related strains that exhibit either summer or winter preferences. Moreover, taxa repeat this process annually in both this and another temperate coastal time series, suggesting that this phenomenon may be widespread in marine ecosystems. To address potential biogeochemical impacts of these community changes, PICRUSt-based metagenomes predict seasonality in transporters, photosynthetic proteins, peptidases and carbohydrate metabolic pathways in spite of closely related summer- and winter-associated taxa. Thus, even small temperature shifts, such as those predicted by climate change models, could affect both the structure and function of marine ecosystems.
The use of core outcome sets (COS) ensures that researchers measure and report those outcomes that are most likely to be relevant to users of their research. Several hundred COS projects have been ...systematically identified to date, but there has been no formal quality assessment of these studies. The Core Outcome Set-STAndards for Development (COS-STAD) project aimed to identify minimum standards for the design of a COS study agreed upon by an international group, while other specific guidance exists for the final reporting of COS development studies (Core Outcome Set-STAndards for Reporting COS-STAR).
An international group of experienced COS developers, methodologists, journal editors, potential users of COS (clinical trialists, systematic reviewers, and clinical guideline developers), and patient representatives produced the COS-STAD recommendations to help improve the quality of COS development and support the assessment of whether a COS had been developed using a reasonable approach. An open survey of experts generated an initial list of items, which was refined by a 2-round Delphi survey involving nearly 250 participants representing key stakeholder groups. Participants assigned importance ratings for each item using a 1-9 scale. Consensus that an item should be included in the set of minimum standards was defined as at least 70% of the voting participants from each stakeholder group providing a score between 7 and 9. The Delphi survey was followed by a consensus discussion with the study management group representing multiple stakeholder groups. COS-STAD contains 11 minimum standards that are the minimum design recommendations for all COS development projects. The recommendations focus on 3 key domains: the scope, the stakeholders, and the consensus process.
The COS-STAD project has established 11 minimum standards to be followed by COS developers when planning their projects and by users when deciding whether a COS has been developed using reasonable methods.
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