Semi-implicit relaxed Douglas-Rachford algorithm (sDR) for ptychography
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The effect of chemical exposure on obesity has raised great concerns. Real-world chemical exposure always imposes mixture impacts, however their exposure patterns and the corresponding associations with obesity have not been fully evaluated. To discover obesity-related mixed chemical exposure patterns in the general U.S. population. Sparse Decompositional Regression (SDR), a model adapted from sparse representation learning technique, was developed to identify exposure patterns of chemical mixtures with exclusion (non-targeted model) and inclusion (targeted model) of health outcomes. We assessed the relationships between the identified chemical mixture patterns and obesity-related indexes. We also conducted a comprehensive evaluation of this SDR model by comparing to the existing models, including generalized linear regression model (GLM), principal component analysis (PCA), and Bayesian kernel machine regression (BKMR). Eight core exposure patterns were identified using the non-targeted SDR model. Patterns of high levels of MEP, high levels of naphthalene metabolites (ΣOH-Nap), and a pattern of high exposure levels of MCOP, MCNP, and MCPP were positively associated with obesity. Patterns of high levels of BP3, and a pattern of higher mixed levels of MPB, PPB, and MEP were found to have negative associations. Associations were strengthened using the targeted SDR model. In the single chemical analysis by GLM, BP3, MBP, PPB, MCOP, and MCNP showed significant associations with obesity or body indexes. The SDR model exceeded the performance of PCA in pattern identification. Both SDR and BKMR identified a positive contribution of ΣOH-Nap and MCOP, as well as a negative contribution of BP3 and PPB to obesity. Our study identified five core exposure patterns of chemical mixtures significantly associated with obesity using the newly developed SDR model. The SDR model could open a new avenue for assessing health effects of environmental mixture contaminants.
The ages and sizes of a sex-determination region (SDR) are difficult to determine in non-model species. Due to the lack of recombination and enrichment of repetitive elements in SDRs, the quality of assembly with short sequencing reads is universally low. Unique features present in the SDRs help provide clues about how SDRs are established and how they evolve in the absence of recombination. Several Populus species have been reported with a male heterogametic configuration of sex (XX/XY system) mapped on chromosome 19, but the exact location of the SDR has been inconsistent among species, and thus far, none of these SDRs has been fully assembled in a genomic context. Here we identify the Y-SDR from a Y-linked contig directly from a long-read PacBio assembly of a Populus trichocarpa male individual. We also identified homologous gene sequences in the SDR of P. trichocarpa and the SDR of the W chromosome in Salix purpurea. We show that inverted repeats (IRs) found in the Y-SDR and the W-SDR are lineage-specific. We hypothesize that, although the two IRs are derived from the same orthologous gene within each species, they likely have independent evolutionary histories. Furthermore, the truncated inverted repeats in P. trichocarpa may code for small RNAs that target the homologous gene for RNA-directed DNA methylation. These findings support the hypothesis that diverse sex-determining systems may be achieved through similar evolutionary pathways, thereby providing a possible mechanism to explain the lability of sex-determination systems in plants in general.
Parameter reduction can enable otherwise infeasible design and uncertainty studies with modern computational science models that contain several input parameters. In statistical regression, techniques for sufficient dimension reduction (SDR) use data to reduce the predictor dimension of a regression problem. A computational scientist hoping to use SDR for parameter reduction encounters a problem: a computer prediction is best represented by a deterministic function of the inputs, so data comprised of computer simulation queries fail to satisfy the SDR assumptions. To address this problem, here we interpret SDR methods sliced inverse regression (SIR) and sliced average variance estimation (SAVE) as estimating the directions of a ridge function, which is a composition of a low-dimensional linear transformation with a nonlinear function. Within this interpretation, SIR and SAVE estimate matrices of integrals whose column spaces are contained in the ridge directions’ span; we analyze and numerically verify convergence of these column spaces as the number of computer model queries increases. Moreover, we show example functions that are not ridge functions but whose inverse conditional moment matrices are low-rank. Consequently, the computational scientist should beware when using SIR and SAVE for parameter reduction, since SIR and SAVE may mistakenly suggest that truly important directions are unimportant.
We present an implementation of the direct one-step (D1S) methodology for shutdown dose rate (SDR) calculations in the OpenMC Monte Carlo particle transport code. In addition to being the first fully open-source D1S implementation, it is also the first to require no ad hoc source code or nuclear data library modifications. The code can seamlessly switch between production of prompt and decay photons based on a user input parameter, and the decay data needed for decay photon generation are made available through a depletion chain file, which is already used for OpenMC’s built-in depletion/activation solver. A set of Python functions significantly eases the burden of computing and applying time correction factors needed to properly account for the time dependence of radionuclide activity. To assess the accuracy of the D1S implementation, SDR calculations have been carried out for three problems: a prism of iron irradiated by 14-MeV neutrons, the ITER port plug computational benchmark, and the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For each of these problems, comparisons were made to calculations using the rigorous two-step (R2S) method. The results on the iron prism problem illustrate how the D1S method achieves superior spatial resolution compared to the R2S method without the need for spatial discretization of the activation regions. The D1S and R2S results for the ITER port plug benchmark agree well with previously reported results in the literature. While the D1S results are 10% to 15% lower than the R2S results, this may be due to stochastic uncertainty and/or spatial discretization in the R2S calculations. On the FNG dose rate benchmark problem, the D1S method produces dose rate estimates that are within 4% of the dose rates predicted using a cell-based R2S workflow. The D1S estimates of the SDR are also in reasonable agreement with the experimental measurements and show the same basic trends that have been observed in previous works. A qualitative analysis of the execution time and uncertainty for the R2S and D1S workflows suggests that the D1S method would attain a higher figure of merit.
We present the first fully open-source capabilities for shutdown dose rate (SDR) calculations of fusion energy facilities based on the Rigorous 2-Step (R2S) methodology. These capabilities have been implemented in the OpenMC Monte Carlo particle transport code, building on its existing capabilities while also leveraging new features that have been added to the code to support SDR calculations, such as decay photon source generation. Each of the individual physics components in the R2S workflow—neutron transport, activation, decay photon source generation, and photon transport—have been verified through code-to-code comparisons with MCNP6.2 and FISPACT-II 4.0. These comparisons generally demonstrate excellent agreement between codes for each of the physics components. The full cell-based R2S workflow was validated by performing a simulation of the first experimental campaign from the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For short cooling times, the dose calculated by OpenMC agrees with the experimental measurements within the stated experimental uncertainties. For longer cooling times, an overprediction of the shutdown dose was observed relative to experiment, which is consistent with previous studies in the literature. Altogether, these features constitute a combination of capabilities in a single, open-source codebase to provide the fusion community with a readily-accessible option for SDR calculations and a platform for rapidly analyzing the performance of fusion technology.
Here we report on an atomic-scale study of trap generation in the initial/intermediate stages of time-dependent dielectric breakdown (TDDB) in high-field stressed (100) Si/SiO2 MOSFETs using two powerful analytical techniques: electrically detected magnetic resonance (EDMR) and near-zero-field magnetoresistance (NZFMR). We find the dominant EDMR-sensitive traps generated throughout the majority of the TDDB process to be silicon dangling bonds at the (100) Si/SiO2 interface (Pb0 and Pb1 centers) for both the spin-dependent recombination (SDR) and trap-assisted tunneling (SDTAT) processes. We find this generation to be linked to both changes in the calculated interface state densities as well as changes in the NZFMR spectra for recombination events at the interface, indicating a redistribution of mobile magnetic nuclei which we conclude could only be due to the redistribution of hydrogen at the interface. Additionally, we observe the generation of traps known as E’ centers in EDMR measurements at lower experimental temperatures via SDR measurements at the interface. Our work strongly suggests the involvement of a rate-limiting step in the tunneling process between the silicon dangling bonds generated at the interface and the ones generated throughout the oxide.
Abstract The Salicaceae family is of growing interest in the study of dioecy in plants because the sex determination region (SDR) has been shown to be highly dynamic, with differing locations and heterogametic systems between species. Without the ability to transform and regenerate Salix in tissue culture, previous studies investigating the mechanisms regulating sex in the genus Salix have been limited to genome resequencing and differential gene expression, which are mostly descriptive in nature, and functional validation of candidate sex determination genes has not yet been conducted. Here, we used Arabidopsis to functionally characterize a suite of previously identified candidate genes involved in sex determination and sex dimorphism in the bioenergy shrub willow Salix purpurea . Six candidate master regulator genes for sex determination were heterologously expressed in Arabidopsis, followed by floral proteome analysis. In addition, 11 transcription factors with predicted roles in mediating sex dimorphism downstream of the SDR were tested using DAP‐Seq in both male and female S. purpurea DNA. The results of this study provide further evidence to support models for the roles of ARR17 and GATA15 as master regulator genes of sex determination in S. purpurea , contributing to a regulatory system that is notably different from that of its sister genus Populus . Evidence was also obtained for the roles of two transcription factors, an AP2 / ERF family gene and a homeodomain‐like transcription factor, in downstream regulation of sex dimorphism.
Adsorption is an important phenomenon in surface chemistry, especially for nano-porous shales. In the shale gas-in-place, adsorbed gas could contribute up to 85%. However, adsorption is hard to quantitatively characterize due to different adsorption mechanisms, patterns, surfaces, and pore sizes. Moreover, key thermodynamic parameters, such as the enthalpy of adsorption, are challenging to determine due to uncertainties in adsorbed gas densities used in constructing absolute isotherms. In this paper, we revisit the Brunauer, Emmett, and Teller (BET) model, analytically simplify Ono-Kondo (OK) models for subsurface shales, and compare commonly used mono- and multilayer adsorption models (e.g., Langmuir, supercritical Dubinin-Radushkevich (SDR), supercritical BET (SBET), and simplified OK (OKs) models) with recently proposed pressure-dependent adsorption densities to develop a practical and reliable methodology that can be used in the supercritical state, typical for subsurface black shale conditions.Three independent data sets were used for nitrogen and methane adsorption isotherms at different temperatures. Furthermore, we demonstrate that adsorption predicted by the SDR model is comparable or lower than that predicted by the SBET model, but higher than the amounts predicted by Langmuir and OK models. The nitrogen BET method tends to underestimate the accessible SSA for methane. Measurement of isosteric heat of adsorption is suggested instead of the experimental fitting method, due to the significant difference between the calculated results by two commonly used methods. Experimental fitting and simulation methods are also briefly reviewed to guide future research on shale gas adsorption.
The mesh-based Rigorous-Two-Step (R2S) method has been widely used in the accurate estimation of the shutdown dose rate (SDR) of fusion systems. Several mesh-based R2S code has been implemented based on Monte Carlo particle transport code MCNP5 or DAG-MCNP5 and inventory calculation code such as FISPACT-II, ALARA or ACAB. Recently, the OpenMC, a community-developed Monte Carlo particle transport code, implemented the photon particle transport capability, which enables OpenMC to be used in R2S. In this paper, PyNE R2S is extended with the support of DAG-OpenMC, i.e., OpenMC with DAGMC. Modifications that allow PyNE to read the flux result in the state point file of OpenMC has been implemented to PyNE R2S workflow. A custom source routine of OpenMC that reads the photon source file from PyNE R2S and sampling photon particle in OpenMC photon transport has been implemented in OpenMC. With these modifications, PyNE R2S is now capable of performing R2S calculations with both DAG-MCNP5 and DAG-OpenMC. The ITER FNG dose rate benchmark problem has been used to validate the code. The FNG neutron source has been modified for neutron transport with DAG-OpenMC. The shutdown dose rate of 19 cooling times has been calculated and compared with the experimental data and the computational results of other R2S codes. The results of PyNE R2S with DAG-OpenMC show satisfactory agreement with the experimental data and other computational results. Therefore, we consider PyNE R2S with DAG-OpenMC is a reliable code to calculate the SDR of fusion systems.
Both magmatic and tectonic processes contribute to the formation of volcanic continental margins. Such margins are thought to undergo extension across a narrow zone of lithospheric thinning (~100 km). New observations based on existing and reprocessed data from the Eastern North American Margin contradict this hypothesis. With ~64,000 km of 2-D seismic data tied to 40 wells combined with published refraction, deep reflection, receiver function, and onshore drilling efforts, we quantified along-strike variations in the distribution of rift structures, magmatism, crustal thickness, and early post-rift sedimentation under the shelf of Baltimore Canyon Trough (BCT), Long Island Platform, and Georges Bank Basin (GBB). Results indicate that BCT is narrow (80–120 km) with a sharp basement hinge and few rift basins. The seaward dipping reflectors (SDR) there extend ~50 km seaward of the hinge line. In contrast, the GBB is wide (~200 km), has many syn-rift structures, and the SDR there extend ~200 km seaward of the hinge line. Early post-rift depocenters at the GBB coincide with thinner crust suggesting “uniform” thinning of the entire lithosphere. Models for the formation of volcanic margins do not explain the wide structure of the GBB. We argue that crustal thinning of the BCT was closely associated with late syn-rift magmatism, whereas the broad thinning of the GBB segment predated magmatism. Correlation of these variations to crustal terranes of different compositions suggests that the inherited rheology determined the premagmatic response of the lithosphere to extension.
Sex chromosomes have evolved hundreds of times across the flowering plant tree of life; their recent origins in some members of this clade can shed light on the early consequences of suppressed recombination, a crucial step in sex chromosome evolution. Amborella trichopoda, the sole species of a lineage that is sister to all other extant flowering plants, is dioecious with a young ZW sex determination system. Here we present a haplotype-resolved genome assembly, including highly contiguous assemblies of the Z and W chromosomes. We identify a ~3-megabase sex-determination region (SDR) captured in two strata that includes a ~300-kilobase inversion that is enriched with repetitive sequences and contains a homologue of the Arabidopsis METHYLTHIOADENOSINE NUCLEOSIDASE (MTN1-2) genes, which are known to be involved in fertility. However, the remainder of the SDR does not show patterns typically found in non-recombining SDRs, such as repeat accumulation and gene loss. These findings are consistent with the hypothesis that dioecy is derived in Amborella and the sex chromosome pair has not significantly degenerated.
Sphingobium sp. strain SYK-6 is an efficient aromatic catabolic bacterium that can consume all four stereoisomers of 1,2-diguaiacylpropane-1,3-diol (DGPD), which is a ring-opened β-1-type dimer. Recently, LdpA-mediated catabolism of erythro-DGPD was reported in SYK-6, but the catabolic pathway for threo-DGPD was as yet unknown. Here, in this study, we elucidated the catabolism of threo-DGPD, which proceeds through conversion to erythro-DGPD. When threo-DGPD was incubated with SYK-6, the Cα hydroxy groups of threo-DGPD (DGPD I and II) were initially oxidized to produce the Cα carbonyl form (DGPD-keto I and II). This initial oxidation step is catalyzed by Cα-dehydrogenases, which belong to the short-chain dehydrogenase/reductase (SDR) family and are involved in the catabolism of β-O-4-type dimers. Analysis of seven candidate genes revealed that NAD + -dependent LigD and LigL are mainly involved in the conversion of DGPD I and II, respectively. Next, we found that DGPD-keto I and II were reduced to erythro-DGPD (DGPD III and IV) in the presence of NADPH. Genes involved in this reduction were sought from Cα-dehydrogenase and ldpA-neighboring SDR genes. The gene products of SLG_12690 (ldpC) and SLG_12640 (ldpB) catalyzed the NADPH-dependent conversion of DGPD-keto I to DGPD III and DGPD-keto II to DGPD IV, respectively. Mutational analysis further indicated that ldpC and ldpB are predominantly involved in the reduction of DGPD-keto. Together, these results demonstrate that SYK-6 harbors a comprehensive catabolic enzyme system to utilize all four β-1-type stereoisomers through successive oxidation and reduction reactions of the Cα hydroxy group of threo-DGPD with a net stereoinversion using multiple dehydrogenases.
This software adds a data handling module to the GNU Radio (GR) software defined radio (SDR) framework as well as some general-purpose function blocks (filters, metadata control, etc). This software is useful for processing bursty RF transmissions with GR, and serves as a base for applying SDR signal processing techniques to a whole burst of data at a time, as opposed to streaming data which GR.
This is the Final Report for the DOE Phase II SBIR project “A Robust Wireless Communication System for Harsh Environments Including Nuclear Facilities.” The topics covered herein include technical progress made, progress against the planned milestones and deliverables, project outcomes, and a discussion on future expectations of deployment and impacts of the results of this work. In brief, all planned work for the project was successfully completed, on or ahead of schedule and on budget. The major accomplishment was the successful development of new sensor/communications systems with wideband (WB)/ultra-wideband (UWB) communications based on the software-defined-radio (SDR) technology to improve sensing and control in nuclear power plants and then a broad range of similar sensing applications. The impacts of these disciplines/focuses of this SBIR include: A new multi-frequency SDR-based architecture with WB/UWB communications integrated with sensors was developed, utilizing 310 MHz, 450 MHz, 915 MHz, and 5 GHz frequencies; Secure communications using Advanced Encryption Standard (AES) algorithm; Sensing possibilities not effectively addressed by previous technologies was addressed; and, The newly developed wireless sensor communications system can adapt its communications parameters to its operational environment for optimal performance. The performance of this system has been evaluated by systematic laboratory and field testing. The field testing was conducted at Massachusetts Institute of Technology (MIT)’s Nuclear Test Reactor, and the McClellan Nuclear center at the University of California Davis (UC Davis), as well as at Oak Ridge National Laboratory (ORNL). The success in this project resulted in DSI being awarded “The DOE’s 2018 SBIR/STTR Small Business of the Year”. This technology has attracted interest from The Rolls Royce company with ongoing discussions under NDA for potential strategic partnership between DSI and Rolls Royce in providing wireless sensor communications in nuclear facilities. Furthermore, the success of this project has attracted significant interest from the United Nations International Atomic Agency (IAEA) in Vienna, Austria, as well as other DOE and DOD offices. Currently, per request from IAEA, DOE’s office of International Safeguards has funded DSI to develop a WB/UWB wireless communication system for real-time transmission of images from IAEA’s safeguards cameras in various nuclear facilities. DSI also has received a Phase II and Phase II.5 SBIR awards from ARMY and NAVY for wireless communications capability for various DOD aircraft.
Syntrophus aciditrophicus strain SB is a model syntroph that degrades benzoate and alicyclic acids. Here, the structure of a putative 3-hydroxypimelyl-CoA dehydrogenase from S. aciditrophicus strain SB (SaHcd1) was resolved at 1.78 Å resolution. SaHcd1 contains sequence motifs and structural features that belong to the short-chain dehydrogenase/reductase (SDR) family of NADPH-dependent oxidoreductases. SaHcd1 is proposed to concomitantly reduce NAD + or NADP + to NADH or NADPH, respectively, while converting 3-hydroxypimelyl-CoA to 3-oxopimeyl-CoA. Further enzymatic studies are needed to confirm the function of SaHcd1.
Here, we utilize electrically detected magnetic resonance (EDMR) measurements to compare high-field stressed, and gamma irradiated Si/SiO 2 metal–oxide–silicon (MOS) structures. We utilize spin-dependent recombination (SDR) EDMR detected using the Fitzgerald and Grove dc I-V approach to compare the effects of high-field electrical stressing and gamma irradiation on defect formation at and near the Si/SiO 2 interface. As anticipated, both greatly increase the concentration of P b centers (silicon dangling bonds at the interface) densities. The irradiation also generated a significant increase in the dc I-V EDMR response of E' centers (oxygen vacancies in the SiO 2 films), whereas the generation of an E' EDMR response in high-field stressing is much weaker than in the gamma irradiation case. These results likely suggest a difference in their physical distribution resulting from radiation damage and high electric field stressing.
Recent advancements in radio frequency (RF) sensing technology can be attributed to the development of the Internet of Things (IoT), healthcare, RF-identification, and communication applications. RF sensing is a multidisciplinary research field that requires expertise in computing, electronics, and electromagnetics to cover all system features, including protocol development, antenna design, sensor integration, algorithm formulation, interconnection, data, and analytics. The overarching aim of this work is to present detailed information about RF technologies and their innovations and application diversity from the novel work carried out at CSI Lab1, together in one platform with an extensive survey. This study presents state-of-the art applications and RF sensing that include W-Fi, radar, and SDR and RFID-based sensing. A comprehensive survey and study of the advantages and limitations of each non-contact technology is discussed. Additionally, open research gaps have been identified as well. Decades of knowledge and experience have been put to use to meet new challenges and demands. The development and study of RF systems, IoT, RFID sensing, and research and deployment activities, are briefly discussed. The emerging research projects with industry, institutional research centers, and academic studies are also addressed. Finally, an outline of identified potential future research areas is provided, emphasizing opportunities and challenges.