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At least 163 records · Page 9

Modeling the Influenza A NP-vRNA-Polymerase Complex in Atomic Detail

Seasonal flu is an acute respiratory disease that exacts a massive toll on human populations, healthcare systems and economies. The disease is caused by an enveloped Influenza virus containing eight ribonucleoprotein (RNP) complexes. Each RNP incorporates multiple copies of nucleoprotein (NP), a fragment of the viral genome (vRNA), and a viral RNA-dependent RNA polymerase (POL), and is responsible for packaging the viral genome and performing critical functions including replication and transcription. A complete model of an Influenza RNP in atomic detail can elucidate the structural basis for viral genome functions, and identify potential targets for viral therapeutics. In this work we construct a model of a complete Influenza A RNP complex in atomic detail using multiple sources of structural and sequence information and a series of homology-modeling techniques, including a motif-matching fragment assembly method. Our final model provides a rationale for experimentally-observed changes to viral polymerase activity in numerous mutational assays. Further, our model reveals specific interactions between the three primary structural components of the RNP, including potential targets for blocking POL-binding to the NP-vRNA complex. The methods developed in this work open the possibility of elucidating other functionally-relevant atomic-scale interactions in additional RNP structures and other biomolecular complexes.

59 BASIC BIOLOGICAL SCIENCES↗

A Systematic Approach to Developing Sustainable Post-Disaster Shelters in the Southern Region of the United States

This study aims to propose a sustainable shelter design involving energy savings, less environmental impact, and rapid construction. The structural design of the shelter is based on 3D-printing technology. Sustainability assessments, including life cycle analysis (LCA), life cycle energy assessment (LCEA), and energy justice of the designed shelter, were conducted to prove the sustainable shelter design. The outcomes of this study for several scenarios will not only allow decision-makers to design permanent shelters with maximized utilization of limited resources but also help local communities strengthen their ability to recover with minimal outside assistance post-disaster. Furthermore, residents can utilize the sustainable shelter to maintain critical functions, including business continuity and local business in emergencies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Secure Cryptographic Key Management System (CKMS) Considerations for Smart Grid Devices

In this paper, we examine some unique challenges associated with key management in the Smart Grid and concomitant research initiatives: 1) effectively model security requirements and their implementations, and 2) manage keys and key distribution for very large scale deployments such as Smart Meters over a long period of performance. This will set the stage to: 3) develop innovative, low cost methods to protect keying material, and 4) provide high assurance authentication services. We will present our perspective on key management and will discuss some key issues within the life cycle of a cryptographic key designed to achieve the following: 1) control systems designed, installed, operated, and maintained to survive an intentional cyber assault with no loss of critical function, and 2) widespread implementation of methods for secure communication between remote access devices and control centers that are scalable and cost-effective to deploy.

99 GENERAL AND MISCELLANEOUS↗

Voltage Regulator Chip: Power Supplies on a Chip

ADEPT Project: CPES at Virginia Tech is finding ways to save real estate on a computer's motherboard that could be used for other critical functions. Every computer processor today contains a voltage regulator that automatically maintains a constant level of electricity entering the device. These regulators contain bulky components and take up about 30% of a computer's motherboard. CPES at Virginia Tech is developing a voltage regulator that uses semiconductors made of gallium nitride on silicon (GaN-on-Si) and high-frequency soft magnetic material. These materials are integrated on a small, 3D chip that can handle the same amount of power as traditional voltage regulators at 1/10 the size and with improved efficiency. The small size also frees up to 90% of the motherboard space occupied by current voltage regulators.

ADEPT↗

LCMSNet v. 3.0

LCMSnet communicates with, controls and orchestrates devices for high pressure liquid chromatography. In developing cutting edge chromatographic methods it was apparent that components from different manufacturers were required. Autosamplers, valves, and pumps all had to be controlled and configured to run unattended and in the highest throughput possible. The power of LCMSnet is the ability so build methods in a simple step by step fashion and then the software uses a scheduling algorithm to run the devices as efficiently as possible without crashing critical functions. This latest iteration of the software allows for modeling of the valves and incorporates logic that will report if a fluid path is undesirable. LCMSnet has reduced method development time from days to minutes and allows the ability to check configurations before any valves or pumps are connected.

Source record↗

Audits and Energy Efficiency in Support of Resilience

Presentation provides an overview of how facility energy and water efficiency audits can provide resilience benefits, how NREL's REopt Lite web tool optimizes the economic and resilience benefits of distributed energy resources, and how FEMP's Technical Resilience Navigator assesses risk to a site's critical functions and prioritizes solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synchronous High-frequency Distributed Readout For Edge Processing At The Fermilab Main Injector And Recycler

The Main Injector (MI) was commissioned using data acquisition systems developed for the Fermilab Main Ring in the 1980s. New VME-based instrumentation was commissioned in 2006 for beam loss monitors (BLM)[2], which provided a more systematic study of the machine and improved displays of routine operation. However, current projects are demanding more data and at a faster rate from this aging hardware. One such project, Real-time Edge AI for Distributed Systems (READS), requires the high-frequency, low-latency collection of synchronized BLM readings from around the approximately two-mile accelerator complex. Significant work has been done to develop new hardware to monitor the VME backplane and broadcast BLM measurements over Ethernet, while not disrupting the existing operations critical functions of the BLM system. This paper will detail the design, implementation, and testing of this parallel data pathway.

43 PARTICLE ACCELERATORS↗

Data-driven cyber attack detection and mitigation for decentralized wide-area protection and control in smart grids

Modern power systems have already evolved into complicated cyber physical systems (CPS), often referred to as smart grids, due to the continuous expansion of the electrical infrastructure, the augmentation of the number of heterogeneous system components and players, and the consequential application of a diversity of information and telecommunication technologies to facilitate the Wide Area Monitoring, Protection and Control (WAMPAC) of the day-to-day power system operation. Because of the reliance on cyber technologies, WAMPAC, among other critical functions, is prone to various malicious cyber attacks. Successful cyber attacks, especially those sabotage the operation of Bulk Electric System (BES), can cause great financial losses and social panics. Application of conventional IT security solutions is indispensable, but it often turns out to be insufficient to mitigate sophisticated attacks that deploy zero-day vulnerabilities or social engineering tactics. To further improve the resilience of the operation of smart grids when facing cyber attacks, it is desirable to make the WAMPAC functions per se capable of detecting various anomalies automatically, carrying out adaptive activity adjustments in time and thus staying unimpaired even under attack. Most of the existing research efforts attempt to achieve this by adding novel functional modules, such as model-based anomaly detectors, to the legacy centralized WAMPAC functions. In contrast, this dissertation investigates the application of data-driven algorithms in cyber attack detection and mitigation within a decentralized architecture aiming at improving the situational awareness and self-adaptiveness of WAMPAC. First part of the research focuses on the decentralization of System Integrity Protection Scheme (SIPS) with Multi-Agent System (MAS), within which the data-driven anomaly detection and optimal adaptive load shedding are further explored. An algorithm named as Support Vector Machine embedded Layered Decision Tree (SVMLDT) is proposed for the anomaly detection, which provides satisfactory detection accuracy as well as decision-making interpretability. The adaptive load shedding is carried out by every agent individually with dynamic programming. The load shedding relies on the load profile propagation among peer agents and the attack adaptiveness is accomplished by maintaining the historical mean of load shedding proportion. Load shedding only takes place after the consensus pertaining to the anomaly detection is achieved among all interconnected agents and it serves the purpose of mitigating certain cyber attacks. The attack resilience of the decentralized SIPS is evaluated using IEEE 39 bus model. It is shown that, unlike the traditional centralized SIPS, the proposed solution is able to carry out the remedial actions under most Denial of Service (DoS) attacks. The second part investigates the clustering based anomalous behavior detection and peer-assisted mitigation for power system generation control. To reduce the dimensionality of the data, three metrics are designed to interpret the behavior conformity of generator within the same balancing area. Semi-supervised K-means clustering and a density sensitive clustering algorithm based on Hierarchical DBSCAN (HDBSCAN) are both applied in clustering in the 3D feature space. Aiming to mitigate the cyber attacks targeting the generation control commands, a peer-assisted strategy is proposed. When the control commands from control center is detected as anomalous, i.e. either missing or the payload of which have been manipulated, the generating unit utilizes the peer data to infer and estimate a new generation adjustment value as replacement. Linear regression is utilized to obtain the relation of control values received by different generating units, Moving Target Defense (MTD) is adopted during the peer selection and 1-dimensional clustering is performed with the inferred control values, which are followed by the final control value estimation. The mitigation strategy proposed requires that generating units can communicate with each other in a peer-to-peer manner. Evaluation results suggest the efficacy of the proposed solution in counteracting data availability and data integrity attacks targeting the generation controls. However, the strategy stays effective only if less than half of the generating units are compromised and it is not able to mitigate cyber attacks targeting the measurements involved in the generation control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FPGA Architectures for Distributed ML Systems for Real-time Beam Loss De-blending

The Accelerator Real-time Edge AI for Distributed Systems (READS) project’s goal is to create a Artificial Intelligence (AI) system for real-time beam loss de-blending within the accelerator enclosure, which houses two accelerators: the Main Injector (MI) and the Recycler Ring (RR). In periods of joint operation, when both machines contain high intensity beam, radioactive beam losses from MI and RR overlap on the enclosure’s beam loss monitoring Beam Loss Monitor (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financialand experimental cost. The ML system will automatically disentangle each machine’s contributions to those measured losses, while not disrupting the existing operations-critical functions of the BLM system. This paper will focus on the evolution of the architectures, which provided the high-frequency, low-latency collection of synchronized data streams to make real-time inferences. The ML models, used for learning both local and global machine signatures and producing high quality inferences based on raw BLM loss measurements, will only be discussed at a high-level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Noncoding deletions reveal a gene that is critical for intestinal function

Large-scale genome sequencing is poised to provide a substantial increase in the rate of discovery of disease-associated mutations, but the functional interpretation of such mutations remains challenging. Here we show that deletions of a sequence on human chromosome 16 that we term the intestine-critical region (ICR) cause intractable congenital diarrhoea in infants. Reporter assays in transgenic mice show that the ICR contains a regulatory sequence that activates transcription during the development of the gastrointestinal system. Targeted deletion of the ICR in mice caused symptoms that recapitulated the human condition. We report transcriptome analysis revealed that an unannotated open reading frame (Percc1) flanks the regulatory sequence, and the expression of this gene was lost in the developing gut of mice that lacked the ICR. Percc1-knockout mice displayed phenotypes similar to those observed upon ICR deletion in mice and patients, whereas an ICR-driven Percc1 transgene was sufficient to rescue the phenotypes found in mice that lacked the ICR. Together, our results identify a gene that is critical for intestinal function and underscore the need for targeted in vivo studies to interpret the growing number of clinical genetic findings that do not affect known protein-coding genes.

59 BASIC BIOLOGICAL SCIENCES↗

Mapping the current–current correlation function near a quantum critical point

The current–current correlation function is a useful concept in the theory of electron transport in homogeneous solids. The finite-temperature conductivity tensor as well as Anderson’s localization length can be computed entirely from this correlation function. Based on the critical behavior of these two physical quantities near the plateau–insulator or plateau–plateau transitions in the integer quantum Hall effect, we derive an asymptotic formula for the current–current correlation function, which enables us to make several theoretical predictions about its generic behavior. For the disordered Hofstadter model, we employ numerical simulations to map the current–current correlation function, obtain its asymptotic form near a critical point and confirm the theoretical predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Critical Two-Point Function for Long-Range O(n) Models Below the Upper Critical Dimension

We consider the n-component |φ|{sup 4} lattice spin model (n≥1) and the weakly self-avoiding walk (n=0) on ℤ{sup d}, in dimensions d=1,2,3. We study long-range models based on the fractional Laplacian, with spin-spin interactions or walk step probabilities decaying with distance r as r{sup −(d+α)} with α∈(0,2). The upper critical dimension is d{sub c}=2α. For ε>0, and α=(1/2)(d+ε), the dimension d=d{sub c}−ε is below the upper critical dimension. For small ε, weak coupling, and all integers n≥0, we prove that the two-point function at the critical point decays with distance as r{sup −(d−α)}. This “sticking” of the critical exponent at its mean-field value was first predicted in the physics literature in 1972. Our proof is based on a rigorous renormalisation group method. The treatment of observables differs from that used in recent work on the nearest-neighbour 4-dimensional case, via our use of a cluster expansion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Meeting Report: Towards a Critical Assessment of Functional Annotation Experiment (CAFAE) for bacterial genome annotation

It is widely recognized that, with the advent of very high throughput, short read, and highly parallelized sequencing technologies, the generation of new DNA sequences from microbes, plants, metagenomes is outpacing the ability to assign functions to (“annotate”) all this data. To begin to try to address this, on May 18 and 19, 2010, a team of roughly fifty people met to define and scope the possibility of a first Critical Assessment of Functional Annotation Experiment (CAFAE) for bacterial genome annotation in Crystal City, Virginia. Due to the fundamental importance of genomic data to its mission, the Department of Energy (DOE) BER program hosted this workshop, funding the attendance of all invitees. The workshop was coorganized by Dan Drell and Susan Gregurick (DOE), Owen White and Nikos Kyripides.

59 BASIC BIOLOGICAL SCIENCES↗

High-order cumulants and correlation functions near the critical point from molecular dynamics

We present a systematic investigation of particle-number fluctuations in the crossover region near the critical end point of a first-order phase transition using molecular dynamics simulations of the classical Lennard-Jones fluid. We extend our prior studies to third- and fourth-order cumulants in both coordinate- and momentum-space acceptances and integrated correlation functions (factorial cumulants). We find that, even near the critical point, non-Gaussian cumulants equilibrate on timescales comparable to those of the second-order cumulants, but show stronger finite-size effects. The presence of interactions and of the critical point leads to strong deviations of the cumulants from the ideal-gas baseline in coordinate space; these deviations are expected to persist in momentum space in the presence of collective expansion. In particular, the kurtosis becomes strongly negative, κσ 2 ≪ − 1 , on the crossover side of the critical point. However, this signal is significantly diluted once an efficiency cut used to distinguish protons from baryons is applied, leading to |κσ 2 | ≲ 1 even in the presence of the critical point. We discuss our results in the context of ongoing measurements of proton-number cumulants in heavy-ion collisions in RHIC-BES-II.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Feasibility of critical infrastructure protection using network functions for programmable and decoupled ICS policy enforcement over WAN

Industrial control systems (ICS) represent a major component of our critical infrastructure. With the increasing need for more control and monitoring of such systems, ICS have seen an increase in connectivity to wide area networks (WAN) exposing aging equipment to rapidly evolving cybersecurity threats. Furthermore, the ICS data requires a reliability measure from the networks for critical functions for infrastructure monitoring and control. Especially when remote plant sites are involved such as pipelines, energy distribution networks, and transportation, WAN transport impairments most often provide a best effort delivery with no strict reliability guarantees. Network functions can provide a vendor agnostic, programmable critical infrastructure protection with a single maintenance, policy determination, and reliability assurance surface. A network function (NF) can be utilized for policy enforcement over the communication between remote entities and the main control office. This paper presents the research on transparent integration with existing ICS without disrupting communications, resulting in minimal downtime while decoupling the fast paced evolution of defensive security measures from the upgrade cycle of expensive long term hardware. We report our measurements on the resource requirements and overhead in the network for successful NF insertion under a wide variety of network impairments (network packet delay, reordering, and loss). Our paired NF implementation provides a policy enforcement platform extensible to cover myriad cybersecurity-related communication goals, including packet signing for verification, encryption for data privacy, packet filtering and data diode operation (i.e. protecting against eavesdropping, packet injection, and denial-of-service). Furthermore, bundling communication specifications into packet flows allows for tunability in applying policies as coarse- or fine-grained as the needs of the operator. We report on network function resource requirements in the form of required queue depth and network utilization overhead to inform the decision making against hardware cost constraints.

42 ENGINEERING↗

Critical review of functionalized silica sorbent strategies for selective extraction of rare earth elements from acid mine drainage

We report the ubiquitous and growing global reliance on rare earth elements (REEs) for modern technology and the need for reliable domestic sources underscore the rising trend in REE-related research. Adsorption-based methods for REE recovery from liquid waste sources are well-positioned to compete with those of solvent extraction, both because of their expected lower negative environmental impact and simpler process operations. Functionalized silica represents a rising category of low cost and stable sorbents for heavy metal and REE recovery. These materials have collectively achieved high capacity and/or high selective removal of REEs from ideal solutions and synthetic or real coal wastewater and other leachate source. These sorbents are competitive with conventional materials, such as ion exchange resins, activated carbon; and novel polymeric materials like ion-imprinted particles and metal organic frameworks (MOFs). This critical review first presents a data mining analysis for rare earth element recovery publications indexed in Web of science, highlighting changes in REE recovery research foci and confirming the sharply growing interest in functionalized silica sorbents. A detailed examination of sorbent formulation and operation strategies to selectively separate heavy (HREE), middle (MREE), and light (LREE) REEs from the aqueous sources is presented. Selectivity values for sorbents were largely calculated from available figure data and gauged the success of the associated strategies, primarily: (1) silane-grafted ligands, (2) impregnated ligands, and (3) bottom-up ligand/silica hybrids. These were often accompanied by successful co-strategies, especially bite angle control, site saturation, and selective REE elution. Recognizing the need to remove competing fouling metals to achieve purified REE “baskets,” we highlight techniques for eliminating these species from acid mine drainage (AMD) and suggest a novel adsorption-based process for purified REE extraction that could be adapted to different water systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗