Kansas State University
  • Manhattan, KS, United States
Recent publications
State estimation is an essential tool for situational awareness and control to ensure safe operation. While current state-of-the-art techniques, such as model-based sparsity-aware state estimators, provide superior performance over conventional approaches, they have poor scalability and require large computational times. These limitations can be overcome by utilizing deep learning models such as deep neural networks (DNNs). However, DNNs are prone to over-fitting and cannot incorporate structural information of networks. Furthermore, current model-based approaches require detailed knowledge of network parameters that may be unavailable in large systems. Therefore, new models with comparable performance are desired that either do not require network parameters or that can work using partial knowledge of these parameters. Recently, graph neural networks (GNNs) have become popular deep learning models that extend neural models to graph structures and incorporate structural information of the networks through graph structures. Therefore, this article proposes GNN-based state estimators by modeling the state estimation problem in distribution systems as node-level prediction problems on their graph representations with state measurement matrices and tensors as input features. Feature scaling and pseudo-measurement generation phases are introduced to enhance their performance. These approaches are evaluated on the IEEE 33, 37-node systems, and an unbalanced three-phase 559-node system. The proposed approaches provide comparable performance to sparsity-aware state estimators while using significantly lower computational times. The GNN-based approaches produce state estimates conforming to the power flow constraints without prior knowledge of the network parameters, thus suggesting that the proposed models can learn the system's underlying physical flows.
Fractured reservoirs are complex and multi‐scale systems composed of matrix and fractures. Accordingly, modeling flow in such geological media has been a great challenge. In this study, we investigated the effect of scale as well as matrix and fracture network characteristics on the effective permeability (keff) in matrix‐fracture systems under fully saturated conditions. We generated fracture networks, embedded within a matrix of permeability of 10⁻¹⁸ m², with fracture lengths followed a truncated power‐law distribution with exponent α = 1.5, 2.0, and 2.5. We set fracture permeability equal to 10⁻¹⁶, 10⁻¹⁴, and 10⁻¹² m² and numerically simulated fluid flow to determine the keff at six fracture densities for 36 fractured reservoirs. Results showed that the effect of α and scale on the keff became more significant as the contrast between matrix and fracture permeabilities increased. We also fit the percolation‐based effective‐medium approximation (P‐EMA) to the simulations and optimized its two parameters critical fracture density and scaling exponent. Results exhibited that both P‐EMA model parameters were scale‐dependent. Through linear regression analysis, we found that the critical fracture density and scaling exponent were highly correlated to other matrix‐fracture system properties and proposed two regression‐based models evaluated using a new six sets of simulations. Comparing the estimated keff values with the simulated ones demonstrated the reliability and predictability of the P‐EMA. The matrix‐fracture systems studied here were finite in size. We also showed that one may extend results to infinitely large reservoirs using the P‐EMA framework.
Palmer amaranth germination and emergence occur throughout the growing season; however, little is known about the impact of late-emerging Palmer amaranth on sorghum, a major crop in Kansas. Field studies were conducted in 2016 and 2017, to measure grain sorghum and late-emerging Palmer amaranth’s response to sorghum population density and nitrogen rate. Treatments comprised weed-free and weedy sorghum as main plots, three sorghum population densities as sub-plots, and three nitrogen rates as sub-sub-plot treatments laid in a randomized complete block design with a split-split-plot arrangement. Weedy sorghum consisted of late-emerging Palmer amaranth only. Weed-free sorghum out-yielded its weedy counterpart by 68 and 45% in 2016 and 2017, respectively. At high sorghum population density (296,400 plants ha-1), applying 112 kg N ha-1 did not improve sorghum grain yield or decrease Palmer amaranth number and height but increased sorghum head number and height, and reduced Palmer amaranth biomass by 65%. Altogether, our findings suggest that while there is an opportunity to maintain grain sorghum yield and achieve some Palmer amaranth control with the integration of high sorghum population density (296,400 plants ha-1) and nitrogen rate (224 kg ha-1) in an irrigated environment, late emerging Palmer amaranth can still cause significant yield reduction (>55%).
The unique physical, mechanical, chemical, optical, and electronic properties of hexagonal boron nitride (hBN) make it a promising two‐dimensional material for electronic, optoelectronic, nanophotonic, and quantum devices. Here we report on the changes in hBN's properties induced by isotopic purification in both boron and nitrogen. Previous studies on isotopically pure hBN have focused on purifying the boron isotope concentration in hBN from its natural concentration (approximately 20 at% ¹⁰ B, 80 at% ¹¹ B) while using naturally abundant nitrogen (99.6 at% ¹⁴ N, 0.4 at% ¹⁵ N), i.e., almost pure ¹⁴ N. In this study, we extend the class of isotopically‐purified hBN crystals to ¹⁵ N. Crystals in the four configurations, namely h ¹⁰ B ¹⁴ N, h ¹¹ B ¹⁴ N, h ¹⁰ B ¹⁵ N, and h ¹¹ B ¹⁵ N, were grown by the metal flux method using boron and nitrogen single isotope (>99%) enriched sources, with nickel plus chromium as the solvent. In‐depth Raman and photoluminescence spectroscopies demonstrate the high quality of the monoisotopic hBN crystals with vibrational and optical properties of the ¹⁵ N‐purified crystals at the state of the art of currently available ¹⁴ N‐purified hBN. The growth of high‐quality h ¹⁰ B ¹⁴ N, h ¹¹ B ¹⁴ N, h ¹⁰ B ¹⁵ N, and h ¹¹ B ¹⁵ N opens exciting perspectives for thermal conductivity control in heat management, as well as for advanced functionalities in quantum technologies. This article is protected by copyright. All rights reserved
Evidence supports the potential application of polyphenols as agents against obesity. Pomegranate is one of the fruits that possess a high content of polyphenols. This systematic review and meta-analysis of randomized controlled trials (RCTs) sought to evaluate the effects of pomegranate consumption on obesity indices, including body mass index (BMI), body weight, waist circumference (WC), fat mass (FM), body fat percentage (BFP), and fat-free mass (FFM) in adults. Relevant RCTs were obtained by searching databases, including PubMed, SCOPUS, and Web of Science, up to May 2023. Heterogeneity tests of the included trials were performed using the I2 statistic. Random effects models were assessed based on the heterogeneity tests, and pooled data were determined as the weighted mean difference with a 95% confidence interval. Pooled analysis of 28 trials revealed that pomegranate consumption led to a significant reduction in body weight (WMD: −1.97, 95% CI: −2.91, −1.03, p < .05), and a significant decrease in BMI (WMD: −0.48, 95% CI: −0.76, −0.20, p < .05) in comparison with the control group. However, there were no significant effects on WC, FM, FFM, and BFP in comparison with the control group. Pomegranate consumption may yield a beneficial effect on body weight and BMI in adults. However, there were no significant effects on WC, FM, FFM, and BFP, by pomegranate consumption. Also, pomegranate consumption can reduce body weight, BMI, WC, and BFP in obese adults. Long-term trials with different doses of pomegranate are needed.
We employed several algorithms with high efficacy to analyze the public transcriptomic data, aiming to identify key transcription factors (TFs) that regulate regeneration in Arabidopsis thaliana. Initially, we utilized CollaborativeNet, also known as TF-Cluster, to construct a collaborative network of all TFs, which was subsequently decomposed into many subnetworks using the Triple-Link and Compound Spring Embedder (CoSE) algorithms. Functional analysis of these subnetworks led to the identification of nine subnetworks closely associated with regeneration. We further applied principal component analysis and gene ontology (GO) enrichment analysis to reduce the subnetworks from nine to three, namely subnetworks 1, 12, and 17. Searching for TF-binding sites in the promoters of the co-expressed and co-regulated (CCGs) genes of all TFs in these three subnetworks and Triple-Gene Mutual Interaction analysis of TFs in these three subnetworks with the CCGs involved in regeneration enabled us to rank the TFs in each subnetwork. Finally, six potential candidate TFs-WOX9A, LEC2, PGA37, WIP5, PEI1, and AIL1 from subnetwork 1-were identified, and their roles in somatic embryogenesis (GO:0010262) and regeneration (GO:0031099) were discussed, so were the TFs in Subnetwork 12 and 17 associated with regeneration. The TFs identified were also assessed using the CIS-BP database and Expression Atlas. Our analyses suggest some novel TFs that may have regulatory roles in regeneration and embryogenesis and provide valuable data and insights into the regulatory mechanisms related to regeneration. The tools and the procedures used here are instrumental for analyzing high-throughput transcriptomic data and advancing our understanding of the regulation of various biological processes of interest.
Background Anal sac adenocarcinoma (ASACA) in dogs is a malignant perianal tumour that often metastasizes to the iliosacral lymph nodes. Additionally, this tumour can be associated with hypercalcemia of malignancy. To date, no study has looked at the association between increased blood calcium levels and suspected or confirmed lymph node metastasis as a primary objective. Objective The objective of this study was to determine if increased total serum calcium level is associated with iliosacral lymph node metastasis in dogs diagnosed with ASACA. Methods Medical records of a single referral hospital were searched to identify dogs examined between 2011 and 2021 that had a diagnosis of ASACA via cytology or histopathology. Only dogs that had serum total calcium recorded and abdominal ultrasound were included in the study. All images were reviewed by a board‐certified radiologist blinded to any patient identifiers. Results Of the 58 dogs, 33% (19/58) had total hypercalcaemia, and of these, 68% had confirmed or suspected iliosacral lymph node metastasis. Total hypercalcaemia was significantly associated with confirmed or suspected iliosacral lymph node metastasis ( p < 0.01). However, 46% (11/24) of dogs with confirmed or suspected iliosacral lymph node metastasis were normocalcaemic. Conclusions Based on these results, it is suggested that while the presence of total hypercalcaemia may increase the likelihood of concurrent lymph node metastasis, total hypercalcaemia alone cannot be used as a screening tool for lymph node metastasis. Dogs diagnosed with ASACA should undergo full staging regardless of total serum calcium values.
The electronic and nuclear dynamics inside molecules are essential for chemical reactions, where different pathways typically unfold on ultrafast timescales. Extreme ultraviolet (XUV) light pulses generated by free-electron lasers (FELs) allow atomic-site and electronic-state selectivity, triggering specific molecular dynamics while providing femtosecond resolution. Yet, time-resolved experiments are either blind to neutral fragments or limited by the spectral bandwidth of FEL pulses. Here, we combine a broadband XUV probe pulse from high-order harmonic generation with an FEL pump pulse to observe dissociation pathways leading to fragments in different quantum states. We temporally resolve the dissociation of a specific O 2 ⁺ state into two competing channels by measuring the resonances of ionic and neutral fragments. This scheme can be applied to investigate convoluted dynamics in larger molecules relevant to diverse science fields.
The layered insulator hexagonal boron nitride (hBN) is a critical substrate that brings out the exceptional intrinsic properties of two‐dimensional (2D) materials such as graphene and transition metal dichalcogenides (TMDs). In this work, we demonstrate how hBN slabs tuned to the correct thickness act as optical waveguides, enabling direct optical coupling of light emission from encapsulated layers into waveguide modes. We integrate two types of TMD monolayers (MoSe 2 and WSe 2 ) within hBN‐based waveguides and demonstrate direct coupling of photoluminescence emitted by in‐plane and out‐of‐plane transition dipoles (bright and dark excitons) to slab waveguide modes. Fourier plane imaging of waveguided photoluminescence from MoSe 2 demonstrates that dry etched hBN edges are an effective out‐coupler of waveguided light without the need for oil‐immersion optics. Gated photoluminescence of WSe 2 demonstrates the ability of hBN waveguides to collect light emitted by out‐of‐plane dark excitons and trions. In‐depth numerical simulations explore the parameters of dipole placement and total slab thickness, elucidating the critical design parameters and serving as a guide for novel devices implementing hBN slab waveguides that broaden the 2D material toolkit. Our results provide a direct route for waveguide‐based interrogation of layered materials, as well as a way to integrate layered materials into future photonic devices at arbitrary positions whilst maintaining their intrinsic properties. This article is protected by copyright. All rights reserved
This research revisits the perennial policy concern that operating subsidies hamper transit efficiency. We argue that the relationship between subsidies and efficiency can be better understood at the regional level and propose improved metrics related to transit efficiency. To begin, we focus on the impact of subsidies on transitsheds rather than transit operators to recast subsidy as a per resident metric, and we average vehicle load in the transitshed as our efficiency metric. Comparing these measures, we discover a surprising trend – transit efficiency is strongly and positively correlated with per resident operating subsidy. To explore this relationship further, we decompose per resident subsidy into federal and non-federal components and generate several new measures to improve modeling of transit efficiency at the transitshed level—subsidy revenue ratio, vehicle ratio, and guideway mile ratio (the latter two of which are scaled by “effective” population). We then apply a linear regression with these new measures on four years of data across the fifteen most populous transitsheds in the United States. Results suggest that operating subsidies promote transit efficiency (with federal subsidies being roughly three times as effective as non-federal subsidies) as long as the subsidies do not unduly outpace revenues. Results also suggest that the vehicle ratio is negatively associated with transit efficiency while the guideway mile ratio is positively associated. These findings offer support for operating subsidies that are reasonably offset by revenues and for targeting capital investments towards fixed guideway infrastructure rather than towards expanding fleet size.
Pork branding is a common tool used to differentiate products based on quality to assist consumers in making purchasing decisions. Most pork processers have premium pork programs with different parameters related to color, mar-bling, and other quality factors, though many differences in specific criteria exist among programs. The objective of this study was to assess differences in pork quality and the associated eating experience of different premium and commodity pork loin programs available in the retail market. Loins (n=30/brand) from 7 branded (PRE A, B, C, D, and E) and commodity (COM A and B) programs were acquired and fabricated at 14–15 d post-box date into 2.54-cm chops for visual color, marbling, pH, intramuscular fat, drip loss, purge loss, shear force, and trained sensory panels. Overall, few differences were found among products for most of the quality traits evaluated. One commodity brand, COM B, had higher (P<0.05) loin L* values and chop L* values and had lower chop a* values, visual color scores, pH, and drip loss than other treatments, but it did not differ (P>0.05) in initial juiciness, sustained juiciness, or any tenderness measurement. The only quality measurement that was associated with changes in eating experience was shear force value, with the PRE C product having the highest (P<0.05) Warner-Brazler shear force and slice shear force values and the associated lowest (P<0.05) myofibrillar tenderness and overall tenderness ratings in the sensory panels. There were no differences (P>0.05) among any treatment for initial juiciness, sustained juiciness, and pork flavor intensity. The results from this study indicate that the range of pork quality differences sold domestically among the evaluated premium and commodity programs is minimal and does not result in associated differences in eating experience.
Real-time characterization of irradiation facilities improves the utilization of the core capabilities of test nuclear reactors. The ability to observe how the local neutron flux (level and spectrum) changes as control elements and experiments change will fundamentally transform our understanding of the underlying physical phenomena that govern the operation of present and advanced nuclear reactors, ultimately providing valuable information for the nuclear energy industry. The objective of this research was to demonstrate how advanced sensors could be used to significantly reduce the time and cost of experiments, improve our understanding of experimental environments, and enable verification and validation of simulation and modeling methods. This was accomplished by designing and fabricating a dedicated real-time instrument test train for the Advanced Test Reactor Critical (ATR-C) facility. The first year of this project focused on the design and modeling of real-time axial neutron flux monitors, leveraging proven technologies pioneered at the Idaho National Laboratory, to characterize the transient that occurs in the Small-B positions at the Advanced Test Reactor and the Advanced Test Reactor Critical Facility. We found that the flux amplitude in those positions can fluctuate as much as 380% depending on the outer shim control cylinder position. The engineering design of the test fixture and flux monitor instrumentation was the objective of the 2nd project year. New capabilities were established to electrodeposit enriched uranium for fission chamber development at the Idaho National Laboratory and trials were begun to characterize the process. The final year included the fabrication of the test fixture and instruments for Advanced Test Reactor Critical Facility. The fabrication process was delayed by supply chain and personal availability caused by the COVID-19 pandemic. However, we were still able to deliver this unique capability to Advanced Test Reactor Critical Facility that will enable future instrument testing and scientific experiments.
Different protein sources create distinct textures in plant‐based meat due to differences in their hydration properties when exposed to different time, temperature, and shear regimes, which in turn depend upon their solubility, protein structure, and specific amino acids. This research aimed to identify these differences and manipulate them to reach a desired texture utilizing simple and reproducible analytical methods to characterize protein properties as either cold or heat swelling. Protein functionality was determined through least gelation concentration (LGC), water absorption index (WAI), and rapid visco analysis (RVA). Cold swelling or CS proteins (pea protein isolate, soy protein isolate, Arcon S soy protein concentrate) were characterized by an LGC < 14% and/ or WAI > 4.0 g/g, while LGC > 16% and/ or WAI < 4.0 g/g indicates proteins with heat swelling or HS properties (Arcon F soy protein concentrate, wheat gluten, and fava protein concentrate). An RVA peak time of around or less than 3 min (<75°C peak temperature) indicated CS properties while greater than 3.5 min (>80°C peak temperature) was considered HS. Protein mixes or treatments comprising mainly of different combinations and ratios of CS proteins were hypothesized to create a softer textured vegetable protein product or texturized vegetable protein (TVP) and those based on HS proteins a firmer TVP. Bulk density was higher for HS treatments (274–287 g/L) than for CS treatments (160–223 g/L). CS treatments exhibited a microstructure that was porous, while HS showed a dense, laminar microstructure. Texture profile analysis showed that CS treatments seemed to show a lower hardness (1154–1595 g) than the HS treatments (1893–2231 g). Practical Application Controlling texture can be a valuable tool when producing a plant‐based meat product. Different applications have various texture requirements. For example, a plant‐based fish stick would require a softer texture than a hamburger or chicken nugget. By increasing the knowledge of how protein functionality affects meat analogue texture, the time needed to produce new products with novel textures can be reduced. Money could also be saved by being able to quickly replace ingredients with a more affordable or accessible protein with similar swelling abilities to preserve product quality.
Using the metaphor of a publication “pipeline,” this article offers practical tips for early-career scholars to take their ideas from concept to publication. Too often, conference presentations do not continue to publication, limiting the potential for dissemination of research work throughout the field and impeding professional scholarly growth. Here, experienced scholars share what they have found helpful to maximize publication productivity.
The fungal pathogen, Magnaporthe oryzae Triticum pathotype, causing wheat blast disease was first identified in South America and recently spread across continents to South Asia and Africa. Here, we studied the genetic relationship among isolates found on the three continents. Magnaporthe oryzae strains closely related to a South American field isolate B71 were found to have caused the wheat blast outbreaks in South Asia and Africa. Genomic variation among isolates from the three continents was examined using an improved B71 reference genome and whole‐genome sequences. We found strong evidence to support that the outbreaks in Bangladesh and Zambia were caused by the introductions of genetically separated isolates, although they were all close to B71 and, therefore, collectively referred to as the B71 branch. In addition, B71 branch strains carried at least one supernumerary mini‐chromosome. Genome assembly of a Zambian strain revealed that its mini‐chromosome was similar to the B71 mini‐chromosome but with a high level of structural variation. Our findings show that while core genomes of the multiple introductions are highly similar, the mini‐chromosomes have undergone marked diversification. The maintenance of the mini‐chromosome and rapid genomic changes suggest the mini‐chromosomes may serve important virulence or niche adaptation roles under diverse environmental conditions.
High night air temperature (HNT) stress negatively impacts both rice (Oryza sativa L) yield and grain quality and has been extensively investigated because of the significant yield loss observed (10%) for every increase in air temperature (1°C). Most of the rice HNT studies have been conducted under greenhouse conditions, with limited information on field-level responses for the major rice sub-populations. This is due to a lack of a field-based phenotyping infrastructure that can accommodate a diverse set of accessions representing the wider germplasm and impose growth stage-specific stress. In this study,we built six high-tunnel greenhouses and screened 310 rice accessions from the Rice Diversity Panel 1 (RDP1) and 10 commercial hybrid cultivars in a replicated design. Each greenhouse had heating and a cyber–physical system that sensed ambient air temperature and automatically increased night air temperature to about 4°C relative to ambient temperature in the field for two cropping seasons. The system successfully imposed HNT stress of 4.0 and 3.94°C as recorded by Raspberry Pi sensors for 2 weeks in 2019 and 2020, respectively. HOBO sensors (Onset Computer Corporation) recorded a 2.9 and 2.07°C temperature differential of ambient air between control and heated greenhouses in 2019 and 2020, respectively. These greenhouses were able to withstand constant flooding, heavy rains, strong winds (140 mph), and thunderstorms. Selected US rice cultivars showed an average of 24% and 15% yield reduction under HNT during the 2019 and 2020 cropping seasons, respectively. Our study highlights the potential of this computer-based infrastructure for accurate implementation of HNT or other abiotic stresses under field-growing conditions.
African animal trypanosomiasis (AAT) is one of the major constraints to animal health and production in sub-Saharan Africa. To inform AAT control in Uganda and help advance along the progressive control pathway (PCP), we characterized AAT prevalence among eight host species in Uganda and explored factors that influence the prevalence variation between studies. We retrieved AAT prevalence publications (n = 2232) for Uganda (1980–2022) from five life sciences databases, focusing on studies specifying AAT detection methods, sample size, and the number of trypanosome-positive animals. Following PRISMA guidelines, we included 56 publications, and evaluated publication bias by the Luis Furuya-Kanamori (LFK) index. National AAT prevalence under DNA diagnostic methods for cattle, sheep and goats was 22.15%, 8.51% and 13.88%, respectively. Under DNA diagnostic methods, T. vivax was the most common Trypanosoma sp. in cattle (6.15%, 95% CI: 2.91–10.45) while T. brucei was most common among small ruminants (goats: 8.78%, 95% CI: 1.90–19.88, and sheep: 8.23%, 95% CI: 4.74–12.50, respectively). Northern and Eastern regions accounted for the highest AAT prevalence. Despite the limitations of this study (i.e., quality of reviewed studies, underrepresentation of districts/regions), we provide insights that could be used for better control of AAT in Uganda and identify knowledge gaps that need to be addressed to support the progressive control of AAT at country level and other regional endemic countries with similar AAT eco-epidemiology.
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7,240 members
Ho Leung Ng
  • Department of Biochemistry and Molecular Biophysics
George A Milliken
  • Department of Statistics
Scott Deloach
  • Department of Computer Science
Ryszard Jankowiak
  • Department of Chemistry
Douglas Jardine
  • Department of Plant Pathology
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