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Insecticide resistance evolution is becoming increasingly problematic globally. With chemical insecticides, attempts to combat resistance involves developing compounds with novel modes of action, or increasing rates to overcome partial resistance. While pests can develop resistance to pathogens used as biopesticides, these “pesticides” can be subjected to evolutionary selection pressure as well and may be able to adapt countermeasures to overcome pest resistance. Here, we consider two scenarios: 1) a single trait governs an arms race between pest and parasite, and 2) an epidemiological scenario where each, pathogen transmission and virulence, are governed by host and pathogen traits. Considering the single-trait parasite attack scenario, the evolving parasite is able to overcome resistance in the pest population and effectively suppress host population abundance. In this case, overcoming biopesticide resistance may be possible from parasite evolution to resistant hosts. In contrast, when transmission and abundance are allowed to vary independently in an epidemiological model, different pathogen traits promote different types of resistance development in the host – more contagious pathogens promote pathogen-tolerant (low mortality susceptibility) hosts, while less contagious pathogens promote pathogen-resistant (low transmission susceptibility) hosts. Pathogen-tolerant hosts are particularly detrimental to control programs, because they can quickly outcompete wild types by promoting infection in wild type populations. Furthermore, because evolution of pathogen-tolerance in pests can benefit pathogens through increasing infection prevalence, we do not expect pathogen evolution to improve control. Thus, the keys to biopesticide management depend on the virulence-transmission trade-off and whether hosts evolve to better prevent or survive infection.

With diverse genetic backgrounds, soybean landraces are valuable resource for breeding programs. Herein, we apply multi-omic approaches to extensively characterize the molecular basis of drought tolerance in the soybean landrace LX. Initial screens established that LX performed better with PEG6000 treatment than control cultivars. LX germinated better than William 82 under drought conditions and accumulated more anthocyanin and flavonoids. Untargeted mass spectrometry in combination with transcriptomic analyses revealed the chemical diversity and genetic basis underlying the overall performance of LX landrace. Under control and drought conditions, significant differences in the expression of a suite of secondary metabolism genes, particularly those involved in the general phenylpropanoid pathway and flavonoid but not lignin biosynthesis, were seen in LX and William 82. The expression of these genes correlated with the corresponding metabolites in LX plants. Further correlation analysis between metabolites and transcripts identified pathway structural genes and transcription factors likely are responsible for the LX agronomic traits. The activities of some key biosynthetic genes or regulators were confirmed through heterologous expression in transgenic Arabidopsis and hairy root transformation in soybean. We propose a regulatory mechanism based on flavonoid secondary metabolism and adaptive traits of this landrace which could be of relevance to cultivated soybean.

Summary ERECTA PANICLE 3 (EP3) and ORYZA SATIVA F‐BOX KELCH 1 (OsFBK1) proteins share 57% and 54% sequence identity with the Arabidopsis F‐box protein HAWAIIAN SKIRT (HWS). Previously we showed that EP3 is a functional orthologue of HWS. Here we demonstrate that OsFBK1 is another functional orthologue of HWS and show the complexity of interaction between EP3 and OsFBK1 genes at different developmental stages of the plant. qRT‐PCR expression analyses and studies of EP3‐GFP and OsFBK1‐RFP promoter reporter lines demonstrate that although EP3 and OsFBK1 expression can be detected in the same tissues some cells exclusively express EP3 or OsFBK1 whilst others co‐express both genes. Loss, reduction or gain‐of‐function lines for EP3 and OsFBK1, show that EP3 and OsFBK1 affect plant architecture, organ size, floral organ number and size, floral morphology, pollen viability, grain size and weight. We have identified the putative orthologue genes of the rice microRNA pathway for ORYZA SATIVA DAWDLE (OsDDL) and ORYZA SATIVA SERRATE (OsSE), and demonstrated that EP3 and OsFBK1 affect their transcript levels as well as those of CROWN ROOT DEFECT 1/ORYZA SATIVA Exportin‐5 HASTY (CRD1/OsHST), ORYZA SATIVA DICER‐LIKE 1 (OsDCL) and ORYZA SATIVA WEAVY LEAF1 (OsWAF1). We show that EP3 affects OsPri‐MIR164, OsNAM1 and OsNAC1 transcript levels. OsNAC1 transcripts are modified by OsFBK1, suggesting two independent regulatory pathways, one via EP3 and OsMIR164 and the other via OsFBK1. Our data propose that EP3 and OsFBK1 conjointly play similar roles in rice to how HWS does in Arabidopsis.

Background F-box proteins are substrate-recognition components of the Skp1-Rbx1-Cul1-F-box protein (SCF) ubiquitin ligases. By selectively targeting the key regulatory proteins or enzymes for ubiquitination and 26S proteasome mediated degradation, F-box proteins play diverse roles in plant growth/development and in the responses of plants to both environmental and endogenous signals. Studies of F-box proteins from the model plant Arabidopsis and from many additional plant species have demonstrated that they belong to a super gene family, and function across almost all aspects of the plant life cycle. However, systematic exploration of F-box family genes in the important fiber crop cotton (Gossypium hirsutum) has not been previously performed. The genome-wide analysis of the cotton F-box gene family is now possible thanks to the completion of several cotton genome sequencing projects. Results In current study, we first conducted a genome-wide investigation of cotton F-box family genes by reference to the published F-box protein sequences from other plant species. 592 F-box protein encoding genes were identified in the Gossypium hirsutume acc.TM-1 genome and, subsequently, we were able to present their gene structures, chromosomal locations, syntenic relationships with their parent species. In addition, duplication modes analysis showed that cotton F-box genes were distributed to 26 chromosomes, with the maximum number of genes being detected on chromosome 5. Although the WGD (whole-genome duplication) mode seems play a dominant role during cotton F-box gene expansion process, other duplication modes including TD (tandem duplication), PD (proximal duplication), and TRD (transposed duplication) also contribute significantly to the evolutionary expansion of cotton F-box genes. Collectively, these bioinformatic analysis suggest possible evolutionary forces underlying F-box gene diversification. Additionally, we also conducted analyses of gene ontology, and expression profiles in silico, allowing identification of F-box gene members potentially involved in hormone signal transduction. Conclusion The results of this study provide first insights into the Gossypium hirsutum F-box gene family, which lays the foundation for future studies of functionality, particularly those involving F-box protein family members that play a role in hormone signal transduction.

Presented is an algorithm based on dynamic mode decomposition (DMD) for acceleration of the power method (PM). The power method is a simple technique for determining the dominant eigenmode of an operator $\mathbf{A}$, and variants of the power method are widely used in reactor analysis. Dynamic mode decomposition is an algorithm for decomposing a time-series of spatially-dependent data and producing an explicit-in-time reconstruction for that data. By viewing successive power-method iterates as snapshots of a time-varying system tending toward a steady state, DMD can be used to predict that steady state using (a sometime surprisingly small) $n$ iterates. The process of generating snapshots with the power method and extrapolating forward with DMD can be repeated. The resulting restarted, DMD-accelerated power method (or DMD-PM($n$)) was applied to the two-dimensional IAEA diffusion benchmark and compared to the unaccelerated power method and Arnoldi's method. Results indicate that DMD-PM($n$) can reduce the number of power iterations required by approximately a factor of 5. However, Arnoldi's method always outperformed DMD-PM($n$) for an equivalent number of matrix-vector products $\mathbf{Av}$. In other words, DMD-PM($n$) cannot compete with leading eigensolvers if one is not limited to snapshots produced by the power method. Contrarily, DMD-PM($n$) can be readily applied as a post process to existing power-method applications for which Arnoldi and similar methods are not directly applicable. A slight variation of the method was also found to produce reasonable approximations to the first and second harmonics without substantially affecting convergence of the dominant mode., 5 figures

Dynamic Mode Decomposition (DMD) was used to produce surrogates for the evolution of spatially-varying nuclide compositions in a TRIGA reactor. First, the method was explored by applying it to a single fuel element in which the data used was produced from the Polaris sequence in SCALE-6.2. Then the method was applied to a full core for which the data used to produce the surrogate was generated from a two-dimensional TRITON/NEWT model of a 78-element TRIGA core depleted over six full-power years. The surrogates have explicit time dependence and exhibited high accuracy for major nuclides in the problem studied. Then the analysis was extended to explore the propagation of time-dependent uncertainties in isotopic composition. The fuel element case showed potential where the full core generalization results revealed that the surrogates eigenpairs are sensitive to the perturbations in the data and hence failed to capture the whole space. Suggestions to address these difficulties were presented in the conclusion section.

The F-box domain containing protein is one of the super protein families in Eukaryotic cells including yeast, plant and mammals. For example, the model plant Arabidopsis and Medicago genomes contain nearly 700 and 1000 F-box protein encoding genes respectively which are the two largest gene families in the plant kingdom. Excluding the N-terminal signature, the approximately 40–50 conserved amino acid F-box motif and their C-terminal protein-protein interaction domains define the different F-box protein subfamilies. Most of the F-box proteins studied so far can interact with SKP proteins, together with Cullin and Rbx1 to form the SCF complexes which are the classic and most well studied E3 ubiquitin ligase complexes. Through the F-box protein C-terminal domains, the SCF complexes confer the specificity of selective protein ubiquitination and subsequent degradation by the 26S proteasome, and this process is routinely termed as the ubiquitin-protease pathway（UPP）. UPP-mediated protein degradation is one of the key regulatory mechanisms for protein stability，and is the major protein degradation pathway for the majority of the intracellular proteins. Since the first plant F-box gene, UFO (Unusual Floral Organs) was isolated in 1995, a collection of about 20 plant F-box genes have been identified and functionally characterized. Proteins encoded by plant F-box genes have been revealed to be functionally diverse and play a variety of roles in developmental processes including: plant hormonal signal transduction, floral development, secondary metabolism, senescence, circadian rhythms and responses to both biotic and abiotic stresses. In recent years，with the rapid improvements of new genome sequencing technologies, hundreds of F-box genes from every sequenced plant species have been identified. Comparing with the large number of F-box genes identified so far, only a handful of them have been studied in detail and the functional characterization of the majority of F-box gene families remains unknown. This review summarizes our current understanding of plant F-box proteins, including their classification and the pathways that they regulate, and seeks to lay the foundation for a systematical investigation of F-box genes in plants.

This work describes the theoretical and experimental performances of four alternatives to the original Hornyak Button-type device that was used in the construction of the Transient Reactor Test (TREAT) Facility hodoscope. The alternatives considered differ in geometry, construction and detection materials to improve performance while decreasing some of the negative aspects of the original device. A Geant4 model of the original Hornyak Button was developed as a benchmark to validate the physics modeled, which agreed well with the reported values. The four alternatives considered were (1) a homogenized ZnS:Ag/PMMA rectangular bar outfitted with silicon photomultipliers (SiPMs), (2) a layered ZnS:Ag/PMMA rectangular bar detector also outfitted with SiPMs, (3) a microstructured neutron detector (MSND) backfilled with hydrogenous material and (4) a pressurized, organic gaseous scintillator. In two scintillation devices, SiPMs were considered as a replacement for photomultiplier tubes for greater light collection. These alternatives were considered as they each had the potential to provide better signal-to-noise ratios, reduce Cerenkov light production, increase detection efficiency, and/or improve neutron-to-gamma discrimination. At comparable lengths, the layered design has been experimentally determined to yield an efficiency of 1.3% (the Hornyak button exhibits 0.4%), while studies on the performances of the other detectors are still underway.

Presented is the numerical study of fast-sensitive, actinide and hydrogenous microstructured semiconductor neutron detectors (MSNDs) for the hodoscope at the Transient REActor Test facility (TREAT) using Geant4 and MCNP6. Neutron converters considered were 237Np, 235U, natural uranium, and 232Th for actinide MSNDs and paraffin wax for hydrogenous MSNDs (H-MSNDs). Paraffin wax was found to have a larger fission-spectrum-weighted macroscopic cross section (0.32 cm −1) than the actinide materials (the best being 0.067 cm −1 for 237 Np). However, actinide reactants were found to allow higher lower-level discriminator (LLD) settings due to the large energy of fission fragments. Actinide MSNDs filled with 235U, natural uranium, and 232Th were evaluated in Geant4 using the fission fragment generator. With the LLD set to 5 MeV, the intrinsic neutron-detection efficiency of the 235U-filled MSNDs was 1.2% for a 2-cm device length and saturated at 2.6% for lengths beyond 14 cm, where 20- μ m trench and 10- μ m wall widths were assumed. The deposited energy in 235U predicted by Geant4 differed from the MCNP6-predicted value by about −0.7%. With the LLD set to 300 keV, Geant4 and MCNP6 predicted an efficiency of about 10% for a 2-cm long H-MSND with 20- μ m trench and 10- μ m wall widths and an efficiency of about 26% for a detector length of 20 cm. For a LLD set to achieve a signal-to-noise (S/N) ratio of 100 when including gamma-ray noise, the best-case, Geant4-predicted efficiencies were 2.5% and 9.6% for 2-cm and 20-cm long devices with 60- μ m trench and 40- μ m wall widths.

The performance of traditional Hornyak buttons and two proposed variants for fast-neutron hodoscope applications was evaluated using Geant4. The Hornyak button is a ZnS(Ag)-based device previously deployed at the Idaho National Laboratory’s TRansient REActor Test Facility (better known as TREAT) for monitoring fast neutrons emitted during pulsing of fissile fuel samples. Past use of these devices relied on pulse-shape discrimination to reduce the significant levels of background Cherenkov radiation. Proposed are two simple designs that reduce the overall light guide mass (here, polymethyl methacrylate or PMMA), employ silicon photomultipliers (SiPMs), and can be operated using pulse-height discrimination alone to eliminate background noise to acceptable levels. Geant4 was first used to model a traditional Hornyak button, and for assumed, hodoscope-like conditions, an intrinsic efficiency of 0.35% for mono-directional fission neutrons was predicted. The predicted efficiency is in reasonably good agreement with experimental data from the literature and, hence, served to validate the physics models and approximations employed. Geant4 models were then developed to optimize the materials and geometries of two alternatives to the Hornyak button, one based on a homogeneous mixture of ZnS(Ag) and PMMA, and one based on alternating layers of ZnS(Ag) and PMMA oriented perpendicular to the incident neutron beam. For the same radiation environment, optimized, 5-cm long (along the beam path) devices of the homogeneous and layered designs were predicted to have efficiencies of approximately 1.3% and 3.3%, respectively. For longer devices, i.e., lengths larger than 25 cm, these efficiencies were shown to peak at approximately 2.2% and 5.9%, respectively. Moreover, both designs were shown to discriminate Cherenkov noise intrinsically by using an appropriate pulse-height discriminator level, i.e., pulse-shape discrimination is not needed for these devices.

Presented here is an application of POD-Galerkin projection to develop a reduced-order-model (ROM) that approximates the solution of the multi-group, time-dependent, diffusion equation with a lower computational cost. Such reduced models are often sought in the context of parametric studies and uncertainty quantification, which require successive evaluation of the full-order model (FOM). To construct the ROM efficiently, greedy sampling was used to generate a reduced subspace that represents the entire parameter (here, cross-sections) domain. By using this subspace, the ROM is expected to yield accurate predictions when used in place of the FOM for uncertainty quantification conducted, e.g., with direct Monte-Carlo sampling. The TWIGL benchmark was used here for illustration. A ROM constructed with a POD basis of rank 10 was able to reproduce the core power with a maximum RMS error on the order of 10–6, and for the precursors concentration it was 10–9. Moreover, the statistical moments obtained from the ROM were in good agreement with those of the full-order-model. The mean relative error of the power sample mean prediction was about 4 ×10–6 for both the ramp and the step perturbations. In terms of the computational efficiency, the ROM time, including the projection, is approximately four-times faster than the full-order-model.

The impact of spatial discretization on reactivity biases in TRIGA fuel models was analyzed. In particular, unit-cell analyses in 2-D and 3-D were performed using Serpent to understand how spatial discretization affects the accuracy with which the effects of material evolution and temperature feedback are resolved. For temperature-dependent cases, a simple, single-channel model was employed. Analysis of 2-D models showed that essentially no radial discretization resolution is needed to eliminate biases (i.e., to reduce biases to the level of stochastic uncertainties) due to material evolution but that more than eight, equal-area, radial regions are needed to resolve temperature-feedback effects. Analysis of 3-D models showed that at least seven, equal-volume, axial regions may be required to resolve material evolution with temperature feedback leading to insignificant additional bias. Because of memory constraints, a full-core model with radially- and axially-resolved fuel elements may be impractical, especially for production-level analyses. Consequently, an “effective Doppler temperature” was determined empirically as a function of the radially-averaged temperature and may be used for future, full-core analyses.

Advancements in nuclear reactor core modeling and computational capability have encouraged further development of in-core neutron sensors. Micro-Pocket Fission Detectors (MPFDs) have been fabricated and tested previously, but successful testing of these prior detectors was limited to single-node operation with specialized designs. Described in this work is a modular, four-node MPFD array fabricated and tested at Kansas State University (KSU). The four sensor nodes were equally spaced to span the length of the fuel-region of the KSU TRIGA Mk. II research nuclear reactor core. The encapsulated array was filled with argon gas, serving as an ionization medium in the small cavities of the MPFDs. The unified design improved device ruggedness and simplified construction over previous designs. A 0.315-in. (8-mm) penetration in the upper grid plate of the KSU TRIGA Mk. II research nuclear reactor was used to deploy the array between fuel elements in the core. The MPFD array was coupled to an electronic support system which has been developed to support pulse-mode operation. Neutron-induced pulses were observed on all four sensor channels. Stable device operation was confirmed by testing under steady-state reactor conditions. Each of the four sensors in the array responded to changes in reactor power between 10 kWth and full power (750 kWth). Reactor power transients were observed in real-time including positive transients with periods of 5, 15, and 30 s. Finally, manual reactor power oscillations were observed in real-time.

Safety analysis was conducted for the KSU TRIGA Mark-II reactor to assess the safety impact of loading enriched fuel in the reactor core. This analysis was performed using a representative single channel conservative model in the best estimate thermal-hydraulic code RELAP5/MOD3.3. However the effects of epistemic uncertainties on the safety calculations and sensitivity of the model towards these uncertainties can play a critical role in decision-making. One of the major uncertainties in the input parameters for RELAP model can be in the axial power peaking factors attributed to uncertainties in burnup estimates. The uncertainty propagation through different models and sensitivity analysis were studied with the help of established tools such as MCNP and RELAP5/MOD3.3. The results of these sensitivity studies due to uncertainties in the burnup values were compared with the sensitivity to uncertainties within the thermal-hydraulic model.

Micro-Pocket Fission Detectors (MPFDs) are under development for in-core neutron flux measurements at the Transient REActor Test facility (TREAT) and in other experiments at Idaho National Laboratory (INL). The sensitivity of MPFDs to the energy dependent neutron flux at TREAT has been determined for 0.0300-μm thick active material coatings of 242 Pu, 232 Th, natural uranium, and 93% enriched 235 U. Self-shielding effects in the active material of the MPFD was also confirmed to be negligible. Finally, fission fragment energy deposition was found to be in conformance with previously reported results.

Presented is an application of the Karhunen–Loeve Transform (KLT) for treatment of the energy variable in response matrix methods to a 44-group version of the 2-D C5G7 benchmark problem. Response matrix methods are based on the partitioning of global domains into independent nodes linked via boundary conditions approximated by truncated expansions of the phase space in orthogonal bases. Here, the KLT was used to produce basis sets appropriate for the energy variable based on “snapshots.” The method of snapshots employs small, representative problems to provide input spectra with which the KLT produces an orthogonal basis for the application. For this study, several computationally small models were defined, and the success of the corresponding basis was compared to the reference (full-multigroup) solution. The best performing basis sets were generated using information from both the scalar flux and the partial current, and typically included information from each unique material (e.g., a UO2 pin cell) in the application problem and junctions between such materials (e.g., a UO2 adjacent to a MOX pin cell). In general, the KLT performed better than the standard discrete Legendre Polynomials (DLPs) as well as “modified” DLPs with proper snapshot selection. The largest errors were found at the material junctions, precisely where spectral gradients are greatest.

Porous media incorporating highly neutron-sensitive materials are of interest for use in the development of neutron detectors. Previous studies have shown experimentally the feasibility of 6 LiF-saturated, multi-layered detectors; however, the random geometry of porous materials has limited the effectiveness of simulation efforts. The results of scatterless neutron transport and subsequent charged reaction product ion energy deposition are reported here using a novel Monte Carlo method and compared to results obtained by MCNP6. This new Dynamic Path Generation (DPG) Monte Carlo method was developed in order to overcome the complexities of modeling a random porous geometry in MCNP6. The DPG method is then applied to determine the optimal coating thickness for 10 B 4 C-coated reticulated vitreous-carbon (RVC) foams. The optimal coating thickness for 4.1275 cm-thick 10 B 4 C-coated reticulated vitreous carbon foams with porosities of 5, 10, 20, 30, 45, and 80 pores per inch (PPI) were determined for ionizing gas pressures of 1.0 and 2.8 atm. A simulated, maximum, intrinsic thermal-neutron detection efficiency of 62.8±0.25% was predicted for an 80 PPI RVC foam with a 0.2 µm thick coating of 10 B 4 C, for a lower level discriminator setting of 75 keV and an argon pressure of 2.8 atm.

International audience; The Arabidopsis thaliana F-box gene HAWAIIAN SKIRT (HWS) affects organ growth and the timing of floral organ abscission. The loss-of-function hws-1 mutant exhibits fused sepals and increased organ size. To understand the molecular mechanisms of HWS during plant development, we mutagenized hws-1 seeds with ethylmethylsulphonate (EMS) and screened for mutations suppressing hws-1 associated phenotypes. We isolated the shs1/ hws-1 (suppressor of hws-1) mutant in which hws-1 sepal fusion phenotype was suppressed. The shs1/hws-1 mutant carries a G -> A nucleotide substitution in the MIR164 binding site of CUP-SHAPED COTYLEDON 1 (CUC1) mRNA. CUC1 and CUP-SHAPED COTYLEDON 2 (CUC2) transcript levels were altered in shs1, renamed cuc1-1D, and in hws-1 mutant. Genetic interaction analyses using single, double and triple mutants of cuc1-1D, cuc2-1D (a CUC2 mutant similar to cuc1-1D), and hws-1, demonstrate that HWS, CUC1 and CUC2 act together to control floral organ number. Loss of function of HWS is associated with larger petal size due to alterations in cell proliferation and mitotic growth, a role shared with the CUC1 gene.

Determining the genetic rearrangement and domestication footprints in Gossypium hirsutum cultivars and primitive race genotypes are essential for effective gene conservation efforts and the development of advanced breeding molecular markers for marker-assisted breeding. In this study, 94 accessions representing the 7 primitive races of G hirsutum , along with 9 G hirsutum and 12 Gossypium barbadense cultivated accessions were evaluated. The genotyping-by-sequencing (GBS) approach was employed and 146 558 single nucleotide polymorphisms (SNP) were generated. Distinct SNP signatures were identified through the combination of selection scans and association analyses. Phylogenetic analyses were also conducted, and we concluded that the Latifolium, Richmondi, and Marie-Galante race accessions were more genetically related to the G hirsutum cultivars and tend to cluster together. Fifty-four outlier SNP loci were identified by selection-scan analysis, and 3 SNPs were located in genes related to the processes of plant responding to stress conditions and confirmed through further genome-wide signals of marker-phenotype association analysis, which indicate a clear selection signature for such trait. These results identified useful candidate gene locus for cotton breeding programs.

A series of experiments are reported which serve as milestones in the development of the MPFD technology. Each test involved reactor pulsing, a controlled power excursion that results from rapid removal of control rods. During a reactor pulse, the power level increases by several orders of magnitude in a fraction of a second resulting from prompt-critical neutron generation in the core. Preliminary reactor pulse testing was conducted at the Kansas State University TRIGA Mk. II nuclear reactor (KSU). The MPFD was used to track reactor pulses of $2.77 and $2.50 worth of reactivity insertion with measured Full Widths at Half Maximum (FWHM) of 13.2 and 16.1 ms compared to theoretical FWHM of 12.2 and 14.4 ms using the Fuchs-Nordheim Model. At the University of Wisconsin Madison Nuclear Reactor (UWNR), a set of 7 detectors, each with 4 independent chambers was deployed as part of the NEUP–NEAMS collaboration between UWNR and KSU. Nine of the time-synchronized chambers were able to track six reactor pulses to provide a spatial map of neutron flux. Finally, a two-chamber MPFD was deployed inside the Idaho National Laboratory Transient Reactor Test Facility (TREAT) reactor core and successfully monitored the power excursion of a 15 GW reactor pulse with an estimated neutron flux of ~1018 n/cm2/s. These preliminary tests highlight the multi-faceted capability of the MPFD as an instrument in different research and power reactors.

The Micro-Layered Fast-Neutron Detector (MLFD) is a proton-recoil fast-neutron scintillator that uses lucite as the hydrogen-rich neutron converter and silver-doped zinc sulfide (ZnS:Ag) as the inorganic scintillator medium. The MLFD is constructed by placing alternative layers of neutron converter and scintillation medium in order to maximize its light collection. A 43-mm long MLFD has previously shown a high detection efficiency of 9.2% for a bare 252Cf source, and exhibits acceptable gamma-ray suppression with pulse height discrimination. Pulse-shape discrimination of neutrons and gamma-rays yielded a figure-of-merit of 4.56. Modeling in Geant4 has shown that lengthening the MLFDs up to 200 mm can further increase the neutron detection efficiency. These results indicate that the MLFD can potentially be used in applications such as active and passive interrogation, and Special Nuclear Material (SNM) searches. However, the light collection device used thus far has been photomultiplier tubes (PMTs), which prove to be infeasible at longer lengths of the MLFD. To construct a compact hand-held neutron detection system, the PMTs would require to be replaced with silicon photomultipliers (SiPMs). Thus, this paper reports the performance of the MLFD coupled to SiPMs when irradiated with neutrons and gamma-rays. The results show that the MLFD-SiPM system is highly insensitive to gamma-rays (pulses not discernible from electronic noise), and simply setting a threshold to reject electronic noise is sufficient to register only neutron events. This indicates that the MLFD-SiPM system would be a compact, highly efficient fast-neutron detector in a gamma-ray environment.

This paper provides a case study and lessons learned through the roll-out of the U.S. National Institute of Standards and Technology and U.S. Department of Energy Green Button electricity, natural gas, and water data-access initiative: to make readily available energy and water consumption data for consumers and third-party companies assisting mutual customers of utilities while protecting the security and privacy of the data. Energy and water usage data are important for smart cities in addition to individual consumers. Smart-city solutions rely heavily on the availability of such data to provide situational awareness as well as to inform control, actuation, and decision-making processes. However, the data need to be protected both for security and integrity. This paper presents a case study using the Green Button standard and the steps taken to ensure data security and privacy while enabling access to those consumption data by the consumer and third parties. Data security and privacy were achieved through use of the Green Button standard and subsequent implementation by the Green Button Alliance of a compliance-testing program. Considerations and solutions were needed for data in transit, data at rest, and the authorization mechanisms for allowing unregulated third-party companies to interface directly to utilities on behalf of the consumer while ensuring the consumer maintains complete control of what is to be shared and the ability to revoke that sharing at any time. The lessons learned from this approach could be applicable to other smart-city data.

An improved computational model of the University of Wisconsin Nuclear Reactor (UWNR) was developed to support the benchmark evaluation of recent data acquired during an experimental campaign conducted at UWNR. Previous efforts led to a scripted UWNR model for automated generation of MCNP6 and Serpent inputs. This capability was extended to SCALE/KENO. All three tools were used to evaluate a variety of zero-power, fresh-critical configurations, and the results agreed well. The MCNP6 model was extended to support shuffling the core configuration, which allows the modeling of burnup for evaluation of depleted critical configurations. The MCNP6 model successfully predicts core reactivity over time, after accounting for the initial reactivity bias. The inclusion of SCALE/KENO input generation enables sensitivity and uncertainty analyses using the TSUNAMI and Sampler modules of SCALE. A preliminary uncertainty analysis was performed with TSUNAMI for nuclear data uncertainties while direct perturbation calculations were performed using MCNP6 for geometry and material uncertainties, which helped to identify model parameters with the largest effect on the eigenvalue. A transient UWNR transport Model in Mammoth/Rattlesnake is under development to simulate the transient experiments. The existing MCNP6 and Serpent models are used to provide the CAD file for meshing and homogenized cross-sections. In conclusion, the evaluation of UWNR benchmark data provides increased confidence in various states of the UWNR computational model and will provide a unique model for use by other analysts.

Until recently, reactor transient problems were exclusively solved by approximate deterministic methods. The increase in available computing power made it feasible to approach the transient analyses with time-dependent Monte Carlo methods. These methods offer the first-principle solution to the space-time evolution of reactor power by explicitly tracking prompt neutrons, precursors of delayed neutrons and delayed neutrons in time and space. Nevertheless, a very significant computing cost is associated with such methods. The general benefits of the Monte Carlo approach may be retained at a reduced computing cost by applying a hybrid stochastic-deterministic computing scheme. Among such schemes are those based on the fission matrix and the response matrix formalisms. These schemes aim at estimating a variant of the Greens function during a Monte Carlo transport calculation, which is later used to formulate a deterministic approach to solving a space-time dependent problem. In this contribution, we provide an overview of the time-dependent response matrix method, which describes a system by a set of response functions. We have recently suggested an approach where the functions are determined during a Monte Carlo criticality calculation and are then used to deterministically solve the space-time behaviour of the system. Here, we compare the time-dependent response matrix solution with the transient fission matrix and the time-dependent Monte Carlo solutions for a control rod movement problem in a mini-core reactor geometry. The response matrix formalism results in a set of loosely connected equations which offers favourable scaling properties compared to the methods based on the fission matrix formalism.

There is growing interest in the development of transient, multiphysics models for nuclear reactors and analysis of uncertainties in those models. Reduced-order models (ROMs) provide a computationally cheaper alternative to compute uncertainties. However, the application of ROMs to transient systems remains a challenging task. Here, a 1-D, twogroup, time-dependent, diffusion model was used to explore the potential of three different ROMs: the intrusive POD-Galerkin and DMD-Galerkin methods and the purely datadriven DMD. For the problem studied, POD-Galerkin exhibited by far the best accuracy and was selected for further application to uncertainty propagation. Perturbations were introduced to the initial condition and to the cross-section data. A greedy-POD sampling procedure was used to construct a reduced space that captured much of the variation in the uncertain these parameters. Results indicate that relatively few samples of the uncertain parameters are needed to produce a basis for POD-Galerkin that leads to distributions of the quantities of interest that match well with those obtained from the full-order model using brute-force, forward sampling.

A nonlinear reactivity model with thermal-hydraulic feedback is presented for analysis of PWR fuel with various cladding materials. The simplified, batch-wise neutronic model requires batch reactivities and migration areas as predetermined functions of burnup, temperature (fuel and coolant), and any design parameters having neutronic significance (e.g., enrichment or cladding composition). Here, such functions are found by using symbolic regression, a unique approach that finds both a functional form and any model coefficients simultaneously. Core thermal-hydraulics are modeled using single-channel, axially-averaged values. The models were implemented in an open-source, Python-based tool, used here to the analyze fuel with Zr-based cladding having outer, protective layers of either FeCrAl or SiC, two materials proposed for use in next-generation, accident-tolerant fuel.

Neutron sensors capable of real-time measurement of neutrons in high-flux environments are necessary for tests aimed at demonstrating the performance of experimental nuclear reactor fuels and materials in material test reactors (MTRs). In-core Micro-Pocket Fission Detectors (MPFDs) have been studied at Kansas State University for many years. Previous MPFD prototypes were successfully built and tested with promising results. Efforts are now underway to develop advanced MPFDs with radiation-resistant, high-temperature materials capable of withstanding irradiation test conditions in high performance material and test reactors. Stackable MPFDs have been designed, built, and successfully demonstrated as in-core neutron sensors. Advances in the electrodeposition and measurement of neutron reactive material, along with refinements to composition optimization simulations, have enhanced the capabilities of contemporary MPFDs.

Understanding digital supports for early learning is paramount for school readiness and later mathematics learning. We present results from a randomized control trial evaluating a digital app (Measure Up!) and a parent companion app (Super Vision) designed to teach children measurement concepts, a skill that many teachers do not feel comfortable teaching. Ninety-nine 4- and 5-year-old children were randomly assigned to one of three conditions: Measure Up!, Super Vision + Measure Up!, or a control game. Analyses revealed a statistically significant effect of being in the treatment group (Measure Up! or Measure Up! + Super Vision) on children's posttest scores (about two additional questions correct), controlling for the pretest and demographic characteristics (gender, SES). In particular, gains were made for children's understanding of pan balances. There was no significant difference between the two treatment groups. Results suggest that apps can be designed to help children learn important mathematics skills; however, more research needs to be done to understand how parent supports can be better designed. Implications for evaluation and design of game-based learning tools are discussed.

The Micro-Layered Fast-Neutron Detector (MLFD) is a proton-recoil scintillation detector constituting microscale alternating layers of hydrogenous medium and ZnS:Ag. The device employs a peripheral photon detection for maximizing light collection while minimizing gamma-ray background. The layered configuration offers several novel advantages inherently by design, e.g., it overcomes the light-opacity limitation of polycrystalline ZnS, recoil protons have a high probability of reacting with the scintillation grains in their forward-directional path, the design and photomultiplier orientation eliminates the need for extraneous light guides, and minimizes Ĉerenkov generation and collection. The most striking ability of the MLFD is that its efficiency can be scaled higher by simply adding layers and increasing the length, up to 20 cm. Presently, a 40-mm MLFD has an intrinsic detection efficiency of 9.2% for bare 252Cf. Described is a comparison between experimental results and a theoretical model, the respective performances of which differ in high energy regions. The differences in the two models suggest that epoxy in the MLFD contributes to an increased count rate in higher channels.

In 2015, the Corporation for Public Broadcasting (CPB) and Public Broadcasting Service (PBS) were awarded a five-year grant as part of the Ready To Learn Television Grant Program, a school readiness and educational media initiative funded by the US Department of Education and Congress. In collaboration with UCLA’s National Center for Research on Evaluation, Standards, and Student Testing (CRESST), PBS KIDS has created the PBS KIDS Learning Analytics Platform to collect, store, and support the analysis of data gathered as children engage with media such as playing games and watching videos. The authors of this chapter are a blended interdisciplinary team from PBS KIDS and UCLA CRESST that represent content, product, technology, science, education, and data analysis expertise. The authors present evidence that gameplay can relate meaningfully to children's performance on standardized test items related to numbers and counting concepts. They use gameplay data to help identify the specific interactions that promote learning involving measurement concepts.

Abscission is a developmental process with important implications for agricultural practices. Ethylene has long been considered as a key regulator of the abscission process. The existence of an ethylene-independent abscission pathway, controlled by the complex of INFLORESCENCE DEFICIENT IN ABSCISSION (IDA) peptide and the HAESA (HAE) and HAESA-like2 (HSL2) kinases, has been proposed, based mainly on observations that organ abscission in ethylene-insensitive mutants was delayed but not inhibited. A recent review on plant organ abscission signaling highlighted the IDA-HAE-HSL2 components as the regulators of organ abscission, while the role of auxin and ethylene in this process was hardly addressed. After a careful analysis of the relevant abscission literature, we propose that the IDA-HAE-HSL2 pathway is essential for the final stages of organ abscission, while ethylene plays a major role in its initiation and progression. We discuss the view that the IDA-HAE-HSL2 pathway is ethylene independent, and present recent evidence showing that ethylene activates the IDA-HAE-HSL2 complex. We conclude that the ability of an organ to abscise is tightly linked to cell turgidity in the abscission zone, and suggest that lack of cell turgidity might contribute to the failure of floral organ abscission in the ida mutants.