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Abstract Background Regulatory mechanism of ERK1 and ERK2, their mechanisms of action, and how they impact on development, growth, and homeostasis of different organisms have been given much emphasis for long. ERK1 and 2 though are isoforms of ERK mitogen-activated protein kinase but are coded by two different genes MAPK3 and MAPK1 respectively and show differential expressions and interdependency in different cancer cell lines. Our previous investigations substantially stated the effect of ERK1 and ERK2 on different extracellular molecules like MMPs and integrins, responsible for cell growth and differentiation. Here, we aim to study individual roles of ERK1 and ERK2 and their interdependency in progression and invasiveness in various cancer cell lines. Methods Different cancer cell lines namely B16F10 (melanoma), MCF7, and MDAMB231 (breast cancer) for studying this particular question were used. Methodologies like gelatin zymography, immunoprecipitation, Western blotting, cell invasion assay, wound healing assay, siRNA transfection, and double transfection procedures were followed for our study. Results Our findings suggest compensation for ERK2 deficiency by pERK1, clear ERK2 predominance in MCF7 cell line, ERK1-ERK2 interdependency in MDAMB231 cells with regard to compensating each other, and significant role of both ERK1 and ERK2 in modulation of MMP9. Conclusion If summarized, our results prove the contribution of ERK2 in compensating ERK1 loss and vice versa and an evident role of ERK1 in cancer cell invasiveness.

Abstract North Dakota is a transitional semiarid region with annual precipitation in the eastern part of the state of about 50–55 cm, mostly from rainfall. The moisture demand from interseeding cover crops into standing corn (Zea mays) early in the season has been a concern and is likely why most corn growers do not interseed cover crops. Corn grain yield was determined in response to interseeding of cereal rye (Secale cereale) or oat (Avena sativa), radish (Raphanus sativus), and camelina (Camelina sativa) and incremental fertilizer nitrogen (N) application rates for five site‐years in the eastern North Dakota. Fifty‐eight days and 35 days of leaf wetness from dew in 2019 and 2020, respectively, were recorded. Cumulative dew accumulation since cover crop emergence was 5.6 mm and 3.5 mm in 2019 and 2020, respectively. Interseeding and its interactions with fertilizer‐N rate did not influence the grain yield. However, cereal rye produced the most biomass of the cover crop species, but the amount varied with site and growing season conditions. Late October, cereal rye biomass produced was 98.8 kg ha−1 in 2018, 352 kg ha−1 in 2019, and 70.3 kg ha−1 in 2020 at the Gardner site. Interseeding did not reduce grain yield loss compared to control. Outcomes will encourage corn growers to adopt cover crops without any changes in their fertilizer N application.

Abstract Temporary winter flooding is a common practice for enhancing wildlife habitat in the Lower Mississippi River Basin (LMRB) and other migratory waterfowl flyways in North America. This practice also facilitates nutrient retention and reuse of rainwater‐ or drainage‐water. This study examines the consequence of five different water management approaches on soil carbon dioxide (CO2) efflux and corn (Zea mays L.) residue decomposition, from October 11, 2021, through January 31, 2022. Management treatments included (i) control (CT) or no flooding; (ii) passive (P) rainfall capture; (iii) fall (F) pumping of leftover irrigation water; (iv) winter (W) flooding with leftover irrigation water; and (v) fall–winter (FW) flooding. The fall–winter flood field (FW) had reduced daily soil CO2 efflux for 4 out of 12 observations and increased soil pH and residue decomposition compared to the control field. The winter flood field (W) had reduced CO2 efflux on December 8 and January 21, and FW had lower efflux on December 8, December 14, December 21, and January 13, than the control field (CT). Soil temperature was positively associated with soil CO2 efflux in all fields except control. Results are consistent with the hypothesis that flood‐timing and ‐duration had strong connections with soil carbon dynamics in LMRB row croplands during fallow periods.

Crop evapotranspiration (ETC) water demands are critical decision support information for the sustainable use of water resources for optimum crop productivity. When measurements of ETC at all locations are not feasible, the prediction of ETC and crop growth from weather and soil–water–crop management data using state-of-the-science cropping system simulations is a viable alternative. This study compared soybean (Glycine max (L.) Merr.) ETC quantified using the eddy covariance (EC) method against simulations from two models, (i) the CSM-CROPGRO-soybean module within the Decision Support System for Agroecology Transfer (DSSAT) and (ii) CSM-CROPGRO-soybean module within the Root Zone Water Quality Model v2.0 (RZWQM) for a grower’s field in the Mississippi Delta, USA, during 2017, 2018, and 2019 growing seasons. The measured soybean grain yields during the three seasons, respectively, were 4979 kg ha−1, 5157 kg ha−1, and 5665 kg ha−1. The DSSAT and RZWQM simulated yields deviated from the measured yields by −10.8% and 15.4% in 2017, −24.0% and 1.56% in 2018, and −6.22%, and 9.98% in 2019. Simulated daily ETC values were less than EC estimates by 0.33 mm, 0.29 mm, and 0.23 mm for DSSAT and 0.05 mm, 0.42 mm, and 0.24 mm for RZWQM, respectively, for the three seasons. EC-quantified seasonal values of ETC were 584 mm, 532 mm, and 566 mm, respectively, for three seasons. Similarly, simulated seasonal ETC values were less than EC estimates by 40 mm, 31 mm, and 16 mm by DSSAT, and 7 mm, 46 mm, and 29 mm by RZWQM. The results obtained demonstrated that accuracy in the prediction of ETC varied among models and growing seasons. When the magnitude of errors in daily ETC simulations does not deter its applications in tactical irrigation water management decisions, a higher degree of agreement between measured and simulated ETC values at a seasonal scale is more promising for strategical irrigation water management planning decision support. Further improvement of the models for more accurate simulations of daily ETC can help in more confident applications of these models for tactical crop-water management applications.

There has been tremendous interest in the development and deployment of Signal Processing and Machine Learning algorithms for almost all areas of instrumentation and measurement systems, starting from power systems, transportation, biomedical and healthcare, industrial measurements and automation, robotics and mechatronics, smart infrastructure, and facility management to aerospace and navigation. Their combination, signal processing and machine learning, is expected to dominate the next decade industrial developments. In order to embed the “intelligence” into the measurement, signal processing has been one of the ubiquitous techniques for quite some time. Machine learning methods make these intelligent methods “experienced.” Because machine learning has been around in recent years, signal processing software–hardware systems equipped with machine learning are relatively mature. In this Special Section, a call for paper included (but were not limited to) the following areas.

Abstract Among many other ecosystem services, cover crops have potential to protect soil and nutrient loss from erosion. However, cover crop residues can alter nitrogen (N) dynamics and affect fertilizer N availability. Response of sugarbeet (Beta vulgaris L.) yield and quality were studied for two fall‐seeded cover crops, winter wheat (Triticum aestivum L.) and cereal rye (Secale cereale L.), and three fertilizer N treatments (fall and spring applications of 100% of recommended N, and 50% split in between fall and spring), in the Red River Valley of Minnesota. Cover crop species and fertilizer N application time significantly influenced sugarbeet canopy reflectance, soil inorganic N, and cover crop biomass production; however, they did not affect root yield and sugar concentration. Sugarbeet grown without a cover crop had higher normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE) than sugarbeet grown after fall‐seeded rye. Fall N application had higher NDVI and NDRE than spring N application for most of the growing season. Cereal rye produced 15% higher biomass than winter wheat. Adoption of rye as a cover crop in sugarbeet might be possible without any adverse effect on sugarbeet production.

Optimizing irrigation water use efficiency (WUE) is critical to reduce the dependency of irrigated cotton (Gossypium spp.) production on depleting aquifers. Cropping system models can integrate and synthesize data collected through experiments in the past and simulate management changes for enhancing WUE in agriculture. This study evaluated the simulation of cotton growth and evapotranspiration (ET) in a grower’s field using the CSM-CROPGRO-cotton module within the Decision Support System for Agrotechnology Transfer (DSSAT) and APSIM (Agricultural Production Systems simulator)-OzCot during 2017–2018 growing seasons. Crop ET was quantified using the eddy covariance (EC) method. Data collected in 2017 was used in calibrating the models and in 2018 validating. Over two cropping seasons, the simulated seedling emergence, flowering, and maturity dates were varied less than a week from measured for both models. Simulated leaf area index (LAI) varied from measured with the relative root mean squared errors (RRMSE) ranging between 20.6% to 38.7%. Daily ET deviated from EC estimates with root mean square errors (RMSEs) of 1.90 mm and 2.03 mm (RRMSEs of 63.1% and 54.8%) for the DSSAT and 1.95 mm and 2.17 mm (RRMSEs of 64.7% and 58.8%) for APSIM, during 2017 and 2018, respectively. Model performance varied with growing seasons, indicating improving ET simulation processes and long-term calibrations and validations are necessary for adapting the models for decision support in optimizing WUE in cotton cropping systems.

Potassium (K) fertilization is a crucial component of sweet potato (Ipomoea batatas L.) production. The basis for K fertilizer recommendations in sweet potato production varies greatly and relies on studies conducted in the late 1950s–1970s. Changes in agronomic practices and increasing costs emphasize the need to revisit fertilizer recommendations. A field experiment was conducted to investigate the impact of seven different K fertilizer (K2O) application rates on sweet potato storage root yield, tissue K concentration, and economic implications in Mississippi. Incremental applications of K fertilizer did not influence sweet potato yield at any grade. Leaf tissue K concentration exhibited a quadratic trend in response to K fertilizer rate, with maximum leaf and root K content achieved at 269 and 404 kg·ha−1 K2O, respectively. Both the predicted K application rate for maximum yield and maximum profitability were the same, at 174 kg·ha−1 K2O. Accordingly, comparable sweet potato yields were achieved while applying substantially less fertilizer than the recommended rate. Further research is warranted to examine the impacts of only potassium fertilizer applications on soil characteristics and temporal trends in sweet potato potassium uptake, as well as refine fertilization recommendations for sweet potato production.

Core Ideas Enhanced efficiency fertilizers significantly reduced cumulative N2O emission compared with urea. Volatilization loss was lower with determinate than indeterminate cultivar. SuperU application lead to higher soil N after harvest. Environmentally Smart N can be a potential alternative to urea to increase N use efficiency. Fertilizer‐N can be lost through ammonia (NH3) volatilization, nitrous oxide (N2O) emission, and nitrate (NO3−) leaching. Field studies were conducted in 2015 and 2016 at Inkster, ND, to evaluate the effectiveness of enhanced efficiency fertilizers (EEFs) in reducing N losses over urea alone in an irrigated potato (Solanum tuberosum L.) production system. Research and fertilizer‐N recommendation for potato were mostly restricted to Russet Burbank; it is critical to understand N dynamics of newly released cultivars. Two EEFs (SuperU and Environmentally Smart Nitrogen [ESN]) at a rate of 280 kg N ha−1, urea at a rate of 225 kg and 280 kg N ha−1, and Growers’ standard (10–34–0 and urea and urea ammonium nitrate in split) at a rate of 280 kg N ha−1 were applied as N treatments in three russet potato cultivars (Russet Burbank, Dakota Trailblazer, and ND8068‐5 Russ). Urea at 280 kg N ha−1 had the highest NH3 volatilization and was significantly higher than SuperU and ESN for Russet Burbank and Trailblazer for both years. Both EEFs reduced N2O emission compared with urea in both years, but SuperU was more efficient than ESN. Residual NO3–N was highest with SuperU both years. Residual soil NO3–N concentration of 120 cm depth with ND8068‐5 Russ were significantly higher compared with Russet Burbank in both growing seasons. Application of EEFs might have the potential to reduce N losses under irrigated late‐planted russet potatoes.

Soil temperature plays an important role in organic matter decomposition, thus likely to affect ammonia and gaseous emission from land application of manure. An incubation experiment was conducted to quantify ammonia and greenhouse gas (GHG) (N2O, CO2 and CH4) emissions from manure and urea applied at 215 kg N ha−1 to Fargo-Ryan silty clay soil. Soil (250 g) amended with solid beef manure (SM), straw-bedded solid beef manure (BM), urea only (UO), and control (CT) were incubated at 5, 10, 15, and 25 °C for 31 days at constant 60% water holding capacity (WHC). The cumulative GHGs and NH3 emission generally increased with temperature and highest emission observed at 25 °C. Across temperature levels, 0.11–1.3% and 0.1–0.7% of the total N was lost as N2O and NH3, respectively. Cumulative CO2 emission from manure was higher than UO and CT at all temperatures (P

Abstract Excessive applications of fertilizer N in corn (Zea mays L.) has profound environmental and economic consequences. Corn grain yield, N losses, N2O denitrification, NH3 volatilization, and soil water NO3 concentration at 60‐cm depth were collected for eight corn fields in the Red River Valley of North Dakota. Relationships of soil and management factors with cumulative N2O and NH3 losses were studied. Grain yield varied from 3.58 to 5.66 Mg ha–1. Cumulative NH3 and N2O losses were ranged between 1.0–2.4 kg ha–1 and 24.7–150 g N2O‐N ha–1, respectively. Soil organic matter (SOM; r = .94, p = .001), clay (r = .94, p = .001), and initial inorganic N (0–60 cm) content (r = .83, p = .01) had a positive relationship with cumulative N2O losses. Cumulative NH3 had a negative relationship with soil pH (r2 = .63, p = .01). Results indicate that soil properties such as, SOM, clay concentration, and initial profile N had a control over N losses.

Abstract The most common formsof S fertilizers in the northern Great Plains are ammonium sulfate (AS), ammonium thiosulfate (ATS), and elemental S (ES). Among these, AS is preferred over the others because of its readily available SO42– form, and it can be blended with other dry fertilizer granules, but SO42– is prone to leaching. Recently, fertilizer industries introduced micronized (

Abstract Selection of dry bean (Phaseolus vulgaris L.) cultivars based on their symbiotic nitrogen fixation (SNF) could reduce the fertilizer N requirement. The nifH gene in the bacterial symbiont facilitates the organic N assimilation by N‐assimilatory enzymes, nitrate reductase (NR), and glutamine synthetase (GS). Fertilizer‐N recommendation of legumes could be adjusted with the relative potential of bacterial nifH gene expression. We hypothesized that quantification of bacterial and plant marker gene expression could predict the amount of total N‐assimilation. We studied the expression dynamics of dry bean NR and GS along with the Rhizobium phaseoli nifH gene in four dry bean commercial cultivars La Paz, Lariat, Windbreaker, and ND‐307 at the third trifoliate (V3) and late flowering (R2) stages using quantitative reverse transcription polymerase chain reaction. Association between gene expression and the amount of SNF using 15N stable isotope dilution was determined. At V3 stage, Lariat had a highest nifH expression, followed by ND‐307, La Paz, and Windbreaker. At R2 stage, ND‐307 had the highest nifH expression followed by Windbreaker, La Paz, and Lariat. At R2 stage, the nifH gene expression was upregulated, whereas NR and GS gene expressions were downregulated compared with the V3 stage, indicating dry bean might be benefitted from late‐season N application. Thus, cultivar dependent nifH, NR, and GS gene expression varied depending on the growth stage. The amount of SNF was significantly correlated (r2 = 0.82) with the relative normalized nifH gene expression in experimental cultivars, validating this molecular assay as a tool to screen SNF potential of dry bean cultivars.

Purpose: Role of no-tillage (NT) in soil conservation has been already established but its influence on soil organic carbon (SOC) is still under debate. Materials and methods: Three paired sites, with NT and chisel-plow (CT) fields adjacent to each other were selected for this study. Fields were under the same tillage practices for more than 20 years. Fields were sampled up to 90 cm depth to determine SOC and different C pools based on soil CO2 flux during 86 d of incubation. Results and conclusion: Significant differences in SOC and its pools were limited within the surface 0–15 cm depth only. Profile SOC did not vary between NT and CT. Tillage had a significant influence on soil C pools but the effect was not consistent across sites.

Manure and inorganic fertilizer help to meet crop nitrogen demand by supplementing soil nitrogen (N). However, excessive N losses reduce soil fertility and crop yield and can impair water and air quality. The objectives of the research were to compare different forms of fall-applied N for (1) the change in soil nitrate (NO3-N) over the growing season and (2) the aerial ammonia (NH3) and nitrous oxide (N2O) fluxes during the fall and early growing season. Treatments included solid beef cattle manure with bedding (BM), solid beef cattle manure only (SM), urea (UO), and no fertilizer (NF). The two-year plot-scale study took place in Brookings County, South Dakota, under rain-fed conditions in a silty clay loam. Manure and urea were applied at equal plant-available N rates of 130 and 184 kg·N·ha−1 in Y1 and Y2, respectively, according to the South Dakota nutrient management planning process. The average total (i.e., 0–0.60 m soil depth) soil NO3-N for Y1 (83 kg·ha−1) was significantly higher than Y2 (67 kg·ha−1), whereas surface (i.e., 0–0.15 m soil depth) soil NO3-N was not significantly different between years. The average surface soil NO3-N (33.5 kg·ha−1) and total soil NO3-N (105.0 kg·ha−1) for UO were significantly higher than the remaining treatments (P

In recent years, extensive research jobs have been developed on the definition, measurement and analyzing of poverty. Poverty is a multidimensional phenomenon, thus a number of challenges appears measuring it. The fuzzy set theoretic approach has been used to measure the poverty and to classify the difference between poor and non-poor households. This paper aims at proposing a new methodology to measure the poverty index in fuzzy environment via a two-step membership function. The concept of one poverty line is chalked out first and then a general method is developed to split the poverty index. Linguistic variables are used for the attributes to find the membership values of the households against the attributes and to grade the attributes. The effectiveness and usefulness of the proposed method is numerically illustrated through a case study for rural household people living in remote rural areas of India.

The editorial boards of the IEEE Electron Device Letters (EDL), IEEE Journal of the Electron Devices Society (J-EDS), and the IEEE Transactions on Electron Device (T-ED) have taken note of a substantial increase in device-oriented manuscripts focused on a variety of "emerging technologies" and, as such, do not fall into traditional subject categories utilized by our journals. Examples include novel nanoelectronic devices based on various "low-dimensional" material systems such as graphene sheets, nanoribbons, carbon nanotubes, transition metal dichalcogenides, and topological insulators, etc. In recognition of this important trend, and to best serve the global electron devices community, we announce the introduction of an "Emerging Technologies and Devices" category within EDL, J-EDS, and T-ED. We recognize that a category with a title of "emerging" by definition represents a dynamic situation (today's emerging device may well become tomorrow’s mainstream device), but it is a terminology easily understood by practitioners in the field. This category will cover the physics, modeling, and operation of such low-dimensional devices, as well as the fabrication techniques needed to construct them.