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Put the methyl to the metal: hydrogenolysis of metal–carbon bonds offers controlled access to low-valent early metal complexes.
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Reconstituted cell-free protein synthesis systems such as the Protein synthesis Using Recombinant Elements (PURE) system give high-throughput and controlled access to in vitro protein synthesis. Here we show that compared with the commercial S30 crude extract based RTS 100 E. coli HY system, the PURE system has less mRNA degradation and produces up to ~6-fold full-length proteins. However the majority of polypeptides PURE produces are partially translated or inactive since the signal from firefly luciferase (Fluc) translated in PURE is only ~2/3 rd of that measured using the RTS 100 E. coli HY S30 system. Both of the 2 batch systems suffer from low ribosome recycling efficiency when translating proteins from 82 k D to 224 k D . A systematic fed-batch analysis of PURE shows replenishment of 6 small molecule substrates individually or in combination before energy depletion increased Fluc protein yield by ~1.5 to ~2-fold, while creatine phosphate and magnesium have synergistic effects when added to the PURE system. Additionally, while adding EF-P to PURE reduced full-length protein translated, it increased the fraction of functional protein and reduced partially translated protein probably by slowing down the translation process. Finally, ArfA, rather than YaeJ or PrfH, helped reduce ribosome stalling when translating Fluc and improved system productivity in a template-dependent fashion.
Novel measurements and modeling of runaway electron (RE) dynamics in DIII-D have resolved experimental discrepancies and validated predictions for ITER, improving confidence that RE avoidance and mitigation can be predictably achieved. Considering RE formation, first experimental assessments of the RE seed current demonstrates that present hot-tail theories are not yet accurate and require improved treatment of the pellet dynamics. Novel measurements of kinetic instabilities in the MHz-range have been made in the RE formation phase, with the intensity of these modes correlated with previously unexplained empirical thresholds for RE generation. Controlled RE dissipation experiments in quiescent regimes have validated RE distribution function dependencies on collisional and synchrotron damping, both in terms of distribution function shape and dissipation rates. Measurements of RE bremsstrahlung and synchrotron emission are now used in tandem to resolve energy and pitch-angle effects. A resolution to long-standing dissipation anomalies in the quiescent regime is offered by taking into account kinetic instability effects on RE phase-space dynamics. Kinetic instabilities in the 100–200 MHz range are directly observed, though modeling finds the largest dissipation arises from GHz range instabilities that are beyond the reach of existing diagnostics. Kinetic instabilities are also observed in the mature post-disruption RE plateau phase, so long as the collisional damping rate is reduced with low-Z injection. Experiments with high-Z injection find that the dissipation rate saturates with injection quantity, likely due to neutral diffusion rates being slower than vertical instability rates in DIII-D. Considering the final loss, a 0D model for first-wall Joule heating is found to be in agreement with experiment, and controlled access to RE equilibria with edge safety factor of two identifies novel dynamics brought about by large-scale kink instabilities. These dynamics are typified by fast (tens of microseconds) RE loss rates without RE beam regeneration. The above measurements and comparison with theory represent significant advances in the understanding of RE dynamics and indicate possible new opportunities for RE avoidance or mitigation via kinetic instabilities.
Abstract Tuberculosis, caused by Mycobacterium tuberculosis, responsible for ∼1.5 million fatalities in 2018, is the deadliest infectious disease. Global spread of multidrug resistant strains is a public health threat, requiring new treatments. Aminoacyl-tRNA synthetases are plausible candidates as potential drug targets, because they play an essential role in translating the DNA code into protein sequence by attaching a specific amino acid to their cognate tRNAs. We report structures of M. tuberculosis Phe-tRNA synthetase complexed with an unmodified tRNAPhe transcript and either L-Phe or a nonhydrolyzable phenylalanine adenylate analog. High-resolution models reveal details of two modes of tRNA interaction with the enzyme: an initial recognition via indirect readout of anticodon stem-loop and aminoacylation ready state involving interactions of the 3′ end of tRNAPhe with the adenylate site. For the first time, we observe the protein gate controlling access to the active site and detailed geometry of the acyl donor and tRNA acceptor consistent with accepted mechanism. We biochemically validated the inhibitory potency of the adenylate analog and provide the most complete view of the Phe-tRNA synthetase/tRNAPhe system to date. The presented topography of amino adenylate-binding and editing sites at different stages of tRNA binding to the enzyme provide insights for the rational design of anti-tuberculosis drugs.
Here, we develop a proposal to realize a widely tunable and clean quantum phase transition in bilayer graphene between two paradigmatic fractionalized phases of matter: the Moore-Read fractional quantum Hall state and the composite Fermi liquid metal. This transition can be realized at total fillings $\textit{ν}$ = ±3 + 1/2 and the critical point can be controllably accessed by tuning either the interlayer electric bias or the perpendicular magnetic field values over a wide range of parameters. We study the transition numerically within a model that contains all leading single particle corrections to the band structure of bilayer graphene and includes the fluctuations between the $\textit{n}$ = 0 and $\textit{n}$ = 1 cyclotron orbitals of its zeroth Landau level to delineate the most favorable region of parameters to experimentally access this unconventional critical point. We also find evidence for a new anisotropic gapless phase stabilized near the level crossing of $\textit{n}$ = 0/1 orbits.
Data Lakehouse is a new paradigm in data architectures that embodies and integrates already established concepts for the systematic management of disparate, large-scale data – a data lake for heterogeneous data management, use of open standards for high-performance querying, and systematic maintenance of the data "freshness". In addition to being a new concept, the data lakehouse is also still a conceptual construct. Many projects that use the lakehouse require maturing, empirical studies, and specific implementations. In this paper, we present our implementation of the data lakehouse concept in a biomedical research and health data analytics domain, and we discuss the implementation of some unique and novel features such as support for specialized access controls in support of HIPAA regulation and IRB protocols, and support for the FAIR standard.
Here, this paper studies the problem of distributed beam scheduling for 5G millimeter-Wave (mm-Wave) cellular networks where base stations (BSs) belonging to different operators share the same spectrum without centralized coordination among them. Our goal is to design efficient distributed scheduling algorithms to maximize the network utility, which is a function of the achieved throughput by the user equipment (UEs), subject to the average and instantaneous power consumption constraints of the BSs. We propose a Media Access Control (MAC) and a power allocation/adaptation mechanism utilizing the Lyapunov stochastic optimization framework and non-cooperative games. In particular, we first decompose the original utility maximization problem into two sub-optimization problems for each time frame, which are a convex optimization problem and a non-convex optimization problem, respectively. By formulating the distributed scheduling problem as a non-cooperative game where each BS is a player attempting to optimize its own utility, we provide a distributed solution to the non-convex sub-optimization problem via finding the Nash Equilibrium (NE) of the game whose weights are determined optimally by the Lyapunov optimization framework. Finally, we conduct simulation under various network settings to show the effectiveness of the proposed game-based beam scheduling algorithm in comparison to that of several reference schemes.
Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.
The Visualizer dashboard provides grid operator highly-trusted alarming environment for an ongoing or potential cyber-attack based on system anomalies and network-based verification. Once anomalies are detected by the IDS tool (HIDES, NREL SWR-19-65), this platform stores the signatures or alert logs that are generated by the intrusion detector, lays out the detailed summary of the possible alerts, and maps these attacks with high-level scenarios. These scenarios are later combined to define a final event using a decision tree approach and a final report is generated out of this tool for further forensic analysis. It also supports authentication and authorization to support roles-based access control (RBAC) for users and a group of people.
The Chemical Asset Tracker, CAT, is a web-based (browser) application for tracking chemical inventories. The application records information about stored chemicals from user input (via the keyboard, barcode readers, or mobile device) and stores that information into a database. A tiered user login controls access to functions in the application. A user interface is provided that allows users to search the database and update data in the database. SAND2019-7525 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
This code is the complete software and firmware components supporting DTC model radios H2 and BluSDR6. This software package contains all the hardware boot up code/config files(BSP), user space Linux code (Web, Network, MAC (media access control) & drivers), the field programable gate array HDL (hardware description language) code and the build environment to compile and organize these components together to work in the aforementioned radios. Additional details of these components are as follows: • Hardware support components o Board support package and configuration files o uBoot • Linux Components: o The web components include the user interface for setup, configuration, and status components of the system. o Vulture code configures the radio’s IP network, configures radio parameters and runs the MAC layer of the radio. • The Field Programmable Gate Array HDL contains hardware drivers, interface logic to go between the software to the physical layer and the radio hardware as well as the logic for the physical layer of the radio. • Build environment includes compilers and config files that compile and organize all the other components to be able to be run on the radios.
Research data infrastructure such as storage must now accommodate new requirements resulting from trends in research data management that require researchers to store their data for the long term and make it available to other researchers. We propose Data Depot, a system and service that provides capabilities for shared space within a group, shared applications, flexible access patterns and ease of transfer at Purdue University. We evaluate Depot as a solution for storing and sharing multiterabytes of data produced in the long tail of science with a use case in soundscape ecology studies from the Human- Environment Modeling and Analysis Laboratory. We observe that with the capabilities enabled by Data Depot, researchers can easily deploy fine-grained data access control, manage data transfer and sharing, as well as integrate their workflows into a High Performance Computing environment.
The Advanced Synchrophasor Protocol Project had two main objectives: To develop, document, and demonstrate a new standard communications protocol (that became named the Streaming Telemetry Transport Protocol, or STTP) to overcome the issues being encountered in large-scale synchrophasor data system deployments using existing protocols – specifically with issues of scalability, data loss, bandwidth utilization, data access control, transport security options, and cost of configuration management, and to work with standards bodies to put STTP on a track for consideration as a standard protocol.
Researchers from Sandia National Laboratories (Sandia) and the University of Texas at Austin (UT) conducted this study to explore the effectiveness of commercial artificial neural network (ANN) software to improve insider threat detection and mitigation (ITDM). This study hypothesized that ANNs could be "trainee to learn patterns of organizational behaviors, detect off-normal (or anomalous) deviations from these patterns, and alert when certain types, frequencies, or quantities of deviations emerge. The ReconaSense ANN system was installed at UT's Nuclear Engineering Teaching Laboratory (NETL) and collected 13,653 access control data points and 694 intrusion sensor data points over a three-month period. Preliminary analysis of this baseline data demonstrated regularized patterns of life in the facility, and that off-normal behaviors are detectable under certain situations -- even for a facility with anticipated highly non-routine, operational behaviors. Completion of this pilot study demonstrated how the ReconaSense ANN could be used to identify expected operational patterns and detect unexpected anomalous behaviors in support of a data-analytic approach to ITDM. While additional studies are needed to fully understand and characterize this system, the results of this initial study are overall very promising for demonstrating a new framework for ITDM utilizing ANNs and data analysis techniques.
This report demonstrates the impact of blockchain technology underlying a transactive energy system and articulates details and principle components of each of five stages in a transactive energy system. This report depicts the engineering requirements of a sample market system, blockchain features, and the relationship between those requirements and features (Section 2.2). Clear value propositions of blockchain features for transactive energy systems are: identity management, security of data, resiliency, decentralization and smart contract trustworthiness, performance, integrity in a trustless environment and access control. Due to the immutability afforded by blockchain architecture, increased data fidelity could potentially help detect targeted cyber-attacks and increase resiliency of grid integration. A distributed system can be more fault tolerant and enable transactive energy by supporting machine-to-machine transactions that can be integrated directly into complex grid operations without the need of trust in a third party. Energy auctions, and potentially registration processes, can be carried out according to transparent rules implemented as smart contracts (Section 4.0). In this current experiment, we ran a use-case/table-top exercise that imitated a real-time 5-min double auction market. The objective of this demonstration is to investigate the applicability of blockchain with transactive energy systems (Section 3.0).
Currently, the solar industry is operating with little application-specific guidance on how to protect and defend their systems from cyberattacks. This 3-year Department of Energy (DOE) Solar Energy Technologies Office-funded project helped advance the distributed energy resource (DER) cybersecurity state-of-the-art by (a) bolstering industry awareness of cybersecurity concepts, risks, and solutions through a webinar series and (b) developing recommendations for DER cybersecurity standards to improve the security performance of DER products and networks. Drafting DER standards is a lengthy, consensus-based process requiring effective leadership and stakeholder participation. This project was designed to reduce standard and guide writing times by creating well-researched recommendations that could act as a starting place for national and international standards development organizations. Working within the SunSpec/Sandia DER Cybersecurity Workgroup, the team produced guidance for DER cybersecurity certification, communication protocol standards, network architecture s, access control, and patching. The team also led subgroups within the IEEE P 1547.3 Guide for Cybersecurity of Distributed Energy Resources Interconnected with Electric Power Systems committee and pushed a draft to ballot in October 2021.
The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.