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This is a processed molecular dataset from this https://doi.ccs.ornl.gov/ui/doi/348 adding up to 50M molecules for the training and 486K molecules for the validation. Instructions on how to use/run/train this dataset can be found here: https://code.ornl.gov/candle/mlmol
Understanding and mitigating decoherence is a key challenge for quantum science and technology. The main source of decoherence for solid-state spin systems is the uncontrolled spin bath environment. Here, we demonstrate quantum control of a mesoscopic spin bath in diamond at room temperature that is composed of electron spins of substitutional nitrogen impurities. The resulting spin bath dynamics are probed using a single nitrogen-vacancy (NV) centre electron spin as a magnetic field sensor. We exploit the spin bath control to dynamically suppress dephasing of the NV spin by the spin bath. Furthermore, by combining spin bath control with dynamical decoupling, we directly measure the coherence and temporal correlations of different groups of bath spins. These results uncover a new arena for fundamental studies on decoherence and enable novel avenues for spin-based magnetometry and quantum information processing.
It is known that the gut microbiome of a healthy person affects the process of COVID-19 after getting infected with SARS-CoV-2 virus. It is also believed that colchicine can alleviate the severity of COVID-19. Current investigations aimed to evaluate the associations between the baseline gut microbiota composition of healthy and Familial Mediterranean fever (FMF) - carrier Armenian men populations, and the severity of the COVID-19 disease after their infection with the SARS-CoV-2. The study has a purpose of answering three core questions: i. Do the characteristics of gut microbiome of Armenians affect the course of COVID-19 severity? ii. How does the COVID-19 disease course on go for FMF patients who have been taking colchicine as a medication over the years after getting infected with SARS-CoV-2? iii. Is there an initial gut micribiota structure pattern for non-FMF and FMF patients in the cases when COVID-19 appears in mild form? The gut microbiota composition in non-FMF and FMF patients before the first infection (mild and moderate course of COVID-19) was considered. COVID-19 was diagnosed by SARS-CoV-2 nucleic acid RT-PCR in nasopharyngeal swab and/or sputum. The number of patients with male FMF with mild COVID-19 was approximately two times higher than that of non-FMF male subjects with COVID-19. In addition, an association of COVID-19 disease severity with the baseline gut Prevotella, Clostridium hiranonis, Eubacterium biforme, Veillonellaceae, Coprococcus, and Blautia diversities in the non-FMF and FMF populations were revealed by us, which can be used as risk/prognostic factor for the severity of COVID-19.
Wastewater testing can be used to monitor SARS-CoV-2 infections in communities. Data from PCR-based wastewater testing are usually available to public health authorities within 5–7 days after excreta and other body fluids enter the sewer. While PCR-based methods can accurately detect and quantify SARS-CoV-2, sequencing-based methods are usually required to distinguish between variants, delaying the results and adding cost to the process. We developed and assessed a novel, customizable digital PCR (dPCR)-based genotyping method for SARS-CoV-2 variant detection in wastewater, which is more cost-effective, faster, and more accessible than sequencing. This approach was applied to more than 1,400 wastewater samples
Regeneration energy and recyclability are important parameters that dictate the viability of a CO 2 direct air capture (DAC) process. In this study, differential scanning calorimetry (DSC) is used in conjunction with thermogravimetric analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR) to evaluate the regeneration energy required for CO 2 -loaded 3 M aqueous potassium sarcosinate (K-SAR) solvent and crystalline methyl-glyoxal-bisiminoguanidine (MGBIG) sorbent. Based on calorimetric measurements, for aqueous K-SAR, the sensible heat amounts to 1.5 GJ/tCO 2 and the enthalpy of desorption is estimated at 3.68 GJ/tCO 2 . The total energy of regeneration will also include the enthalpy of solvent vaporization, which will depend on the thermodynamic conditions and the level of regeneration. For MGBIG, the total regeneration energy required was measured at approximately 7.0 GJ/tCO 2 . Further, FTIR measurements were used to observe CO 2 and H 2 O release during the thermal regeneration process. For K-SAR, CO 2 release is seen to take place at temperatures greater than 80 °C and, for MGBIG, the CO 2 release takes place at temperatures greater than 100 °C. The moderate temperatures required for K-SAR and MGBIG regenerations compared to other DAC solvents/sorbents suggest that low-cost sources of heat, such as geothermal heat, could potentially be used for regeneration to drive down the cost of direct air capture.
Most transcriptomic studies of SARS-CoV-2 infection have focused on differentially expressed genes, which do not necessarily reveal the genes mediating the transcriptomic changes. In contrast, exploiting curated biological network, our PathExt tool identifies central genes from the differentially active paths mediating global transcriptomic response. Here we apply PathExt to multiple cell line infection models of SARS-CoV-2 and other viruses, as well as to COVID-19 patient-derived PBMCs. The central genes mediating SARS-CoV-2 response in cell lines were uniquely enriched for ATP metabolic process, G1/S transition, leukocyte activation and migration. In contrast, PBMC response reveals dysregulated cell-cycle processes. In PBMC, the most frequently central genes are associated with COVID-19 severity. Importantly, relative to differential genes, PathExt-identified genes show greater concordance with several benchmark anti-COVID-19 target gene sets. We propose six novel anti-SARS-CoV-2 targets ADCY2, ADSL, OCRL, TIAM1, PBK, and BUB1, and potential drugs targeting these genes, such as Bemcentinib, Phthalocyanine, and Conivaptan.
The urgent search for drugs to combat SARS-CoV-2 has included the use of supercomputers. The use of general-purpose graphical processing units (GPUs), massive parallelism, and new software for high-performance computing (HPC) has allowed researchers to search the vast chemical space of potential drugs faster than ever before. We developed a new drug discovery pipeline using the Summit supercomputer at Oak Ridge National Laboratory to help pioneer this effort, with new platforms that incorporate GPU-accelerated simulation and allow for the virtual screening of billions of potential drug compounds in days compared to weeks or months for their ability to inhibit SARS-COV-2 proteins. Here, this effort will accelerate the process of developing drugs to combat the current COVID-19 pandemic and other diseases.
The current severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) pandemic has highlighted the need for personal protective equipment, specifically filtering facepiece respirators like N95 masks. While it is common knowledge that polypropylene (PP) is the industry standard material for filtration media, trial and error is often required to identify suitable commercial precursors for filtration media production. This work aims to identify differences between several commercial grades of PP and demonstrate the development of N95 filtration media with the intent that the industry partners can pivot and help address N95 shortages. Three commercial grades of high melt flow index PP were melt blown at Oak Ridge National Laboratory and broadly characterized by several methods including differential scanning calorimetry (DSC), X-ray diffraction (XRD), and neutron scattering. Despite the apparent similarities (high melt flow and isotacticity) between PP feedstocks, the application of corona charging and charge enhancing additives improve each material to widely varying degrees. From the analysis performed here, the most differentiating factor appears to be related to crystallization of the polymer and the resulting electret formation. Materials with higher crystallization onset temperatures, slower crystallization rates, and larger number of crystallites form a stronger electret and are more effective at filtration.
Protecting the dynamics of coupled quantum systems from decoherence by the environment is a key challenge for solid-state quantum information processing. An idle quantum bit (qubit) can be efficiently insulated from the outside world by dynamical decoupling, as has recently been demonstrated for individual solid-state qubits. However, protecting qubit coherence during a multi-qubit gate is a non-trivial problem in general, the decoupling disrupts the interqubit dynamics and hence conflicts with gate operation. This problem is particularly salient for hybrid systems, in which different types of qubit evolve and decohere at very different rates. Here we present the integration of dynamical decoupling into quantum gates for a standard hybrid system, the electron-nuclear spin register. Our design harnesses the internal resonance in the coupled-spin system to resolve the conflict between gate operation and decoupling. We experimentally demonstrate these gates using a two-qubit register in diamond operating at room temperature. Quantum tomography reveals that the qubits involved in the gate operation are protected as accurately as idle qubits. We also perform Grover's quantum search algorithm, and achieve fidelities of more than 90% even though the algorithm run-time exceeds the electron spin dephasing time by two orders of magnitude. Our results directly allow decoherence-protected interface gates between different types of solid-state qubit. Ultimately, quantum gates with integrated decoupling may reach the accuracy threshold for fault-tolerant quantum information processing with solid-state devices.
Verification of arms control treaties may require information barriers to protect sensitive data acquired during the verification process. These information barriers are commonly implemented in software, but must store and operate on data that are vulnerable to attack and tampering. Here, we present a new Secure Measurement Unit based on a modified pipeline SAR ADC architecture. The idea is to move the information barrier back into the digitization process so that prohibited data is never created. A prototype 65nm CMOS Secure Measurement Unit (SMU) was tested using U-235, U-238, Co-60, Cs-137 and Am-241 sources. Here, the prototype accurately digitized allowable signals while being immune to side-channel attacks on signals within preset forbidden regions.
Sandia provided technical assistance to RingIR to test and evaluate of the RingIR molecular detector. The detector can identify gas phase species using molecular fingerprinting and has potential application for SARS-CoV-2 detection in near real time. As part of the development process Sandia will utilize the biological aerosol test bed deployed at the Aerosol Complex to evaluate the penetration of MS2 bacteriophage aerosol through the RingIR system. The objective of this project is to provide experimentally derived measurements of the RingIR molecular detector penetration efficiency, including external exhaust filter for mitigation of exhaust aerosol and operation using MS2 bacteriophage as a biological surrogate to the SARS-CoV-2 virus.
The AG-4000 detector can identify gas phase species using molecular fingerprinting and has potential application for SARS-CoV-2 detection in near real time. As part of the development process Sandia will utilize the biological aerosol test bed deployed at the Aerosol Complex to evaluate the penetration of MS2 bacteriophage aerosol through the Ring IR system. The objective of this project is to provide experimentally derived measurements of the RingIR AG-4000 penetration efficiency, including external exhaust filter for mitigation of exhaust aerosol and operation using MS2 bacteriophage as a biological surrogate to the SARS-CoV-2 virus.
Single Image SICD-Based Automatic Object Processing (SIS-AOP) is an automatic object identification tool for SAR imagery. It ingests a SAR image in standard SICD format, and it will run a suite of algorithms to cue possible vehicle detections, cull those detections and then ultimately label them either as detections only or possible expound to give a class-level ID or a vehicle-type ID. The SIS-AOP results are given in an XML (Extensible Markup Language) output format. This document defines the elements in the SISAOPR XML output format.
Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer to true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.
The relation between amino acid (AA) sequence and biologically active conformation controls the process of polypeptide chains folding into three-dimensional (3d) protein structures. The recent achievements in the resolution achieved in cryo-electron microscopy coupled with improvements in computational methodologies have accelerated the analysis of structures and properties of proteins. However, the detailed interaction between AAs has not been fully elucidated. Herein, we present a de novo method to evaluate inter-amino acid interactions based on the concept of accurately evaluating the amino acid bond pairs (AABP). The results obtained enabled the identification of complex 3d long-range interconnected AA interacting network in proteins. The method is applied to the receptor binding domain (RBD) of the SARS-CoV-2 spike protein. We show that although nearest-neighbor AAs in the primary sequence have large AABP, other nonlocal AAs make substantial contribution to AABP with significant participation of both covalent and hydrogen bonding. Detailed analysis of AABP in RBD reveals the pivotal role they play in sequence conservation with profound implications on residue mutations and for therapeutic drug design. This approach could be easily applied to many other proteins of biomedical interest in life sciences.
The COVID-19 disease caused by the SARS-CoV-2 coronavirus has become a pandemic health crisis. An attractive target for antiviral inhibitors is the main protease 3CL Mpro due to its essential role in processing the polyproteins translated from viral RNA. Here we report the room temperature X-ray structure of unliganded SARS-CoV-2 3CL Mpro, revealing the ligand-free structure of the active site and the conformation of the catalytic site cavity at near-physiological temperature. Comparison with previously reported low-temperature ligand-free and inhibitor-bound structures suggest that the room temperature structure may provide more relevant information at physiological temperatures for aiding in molecular docking studies.
We present a detailed survey here on the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is unstable due to the underlying geology that is formed by alternate and variable strata of highly soluble materials such as gypsum, anhydrite, marl and limestone. We present the first comprehensive multi-sensor cumulative deformation map for the dam generated from space-based synthetic aperture radar (SAR) measurements from the Italian constellation COSMO-SkyMed and the European Sentinel-1a satellite. We compared 2014-2016 data to an historic dataset spanning 2004-2010 acquired with the Envisat ASAR sensor. We found that deformation was rapid during 2004-2010, slowed down in 2012-2014, and restarted in August 2014 when grouting operations stopped due to the temporary capture of the dam by the self proclaimed Islamic State in Iraq and Syria (ISIS). We took advantage of the availability of data from multiple SAR satellites to infer the deformation at the dam in great spatial and temporal detail and shed new light on the processes of the ongoing destabilization. This study highlights how new constellations of SAR sensors together with the availability of historical datasets are leading to important advances in deformation monitoring of small scale geologic and manmade features.
SARS-CoV-2 poses an ongoing threat to human health as variants continue to emerge. Several effective vaccines are available, but a diminishing number of Americans receive the updated vaccines (only 22% received the 2023 update). Public hesitancy towards vaccines and common occurrence of “breakthrough” infections (i.e., infections of vaccinated individuals) highlight the need for alternative methods to reduce viral transmission. SARS-CoV-2 enters cells by fusing its envelope with the target cell membrane in a process mediated by the viral spike protein, S. The S protein operates via a Class I fusion mechanism in which fusion between the viral envelope and host cell membrane is mediated by structural rearrangements of the S trimer. We previously reported lipopeptides derived from the C-terminal heptad repeat (HRC) domain of SARS-CoV-2 S that potently inhibit fusion by SARS-CoV-2, both in vitro and in vivo. These lipopeptides bear an attached cholesterol unit to anchor them in the membrane. Here, to improve prospects for experimental development and future clinical utility, we employed structure-guided design to incorporate charged residues at specific sites in the peptide to enhance aqueous solubility. This effort resulted in two new, potent lipopeptide inhibitors.