Economic assessment of pulse crop rotations in western Canada

Non-Peer ReviewedPulse crops have become essential to farming practices in the Northern Great Plains, but little has been studied how rotation systems with different crop mixes affect the economic returns. Initiated in 2010, a four-year crop rotation study was repeated at Swift Current, Saskatchewan, and Brooks, Alberta to identify effective crop rotation length and frequency of pulses in a rotation and to evaluate the economic returns for individual crop and for the entire crop rotations in western Canada. Rotation systems that included one or two lentil crops in the 4-year sequence lead to greater and consistent revenue gains at all sites. Wheat monoculture resulted in the lowest net return due to higher cost and lower product prices compared with other crops in the rotation

Real-time Profiling of Solid-State Nanopores During Solution-Phase Nanofabrication

We describe a method for simply characterizing the size and shape of a nanopore during solution-based fabrication and surface modification, using only low-overhead approaches native to conventional nanopore measurements. Solution-based nanopore fabrication methods are democratizing nanopore science by supplanting the traditional use of charged-particle microscopes for fabrication, but nanopore profiling has customarily depended on microscopic examination. Our approach exploits the dependence of nanopore conductance in solution on nanopore size, shape, and surface chemistry in order to characterize nanopores. Measurements of the changing nanopore conductance during formation by etching or deposition can be analyzed using our method to characterize the nascent nanopore size and shape—beyond the typical cylindrical approximation—in real-time. Our approach thus accords with ongoing efforts to broaden the accessibility of 3 nanopore science from fabrication through use: it is compatible with conventional instrumentation and offers straightforward nanoscale characterization of the core tool of the field

Conductance-Based Profiling of Nanopores: Accommodating Fabrication Irregularities

Solid-state nanopores are nanoscale channels through otherwise impermeable membranes. Single molecules or particles can be passed through electrolyte-filled nanopores by, e.g. electrophoresis, and then detected through the resulting physical displacement of ions within the nanopore. Nanopore size, shape, and surface chemistry must be carefully controlled, and on extremely challengingwork, confirmed the suitability of the basic conductance equation using the results of a time-dependent experimental conductance measurement during nanopore fabrication by Yanagi et al., and then deliberately relaxed the model constraints to allow for (1) the presence of defects; and (2) the formation of two small pores instead of one larger one. Our simulations demonstrated that the time-dependent conductance formalism supports the detection and characterization of defects, as well as the determination of pore number, but with implementation performance depending on the measurement context and results. In some cases, the ability to discriminate numerically between the correct and incorrect nanopore profiles was slight, but with accompanying differences in candidate nanopore dimensions that could yield to post-fabrication conductance profiling, or be used as convenient uncertainty bounds. Time-dependent nanopore conductance thus offers insight into nanopore structure and function, even in the presence of fabrication defects

THE ANALYSIS OF DISPOSITION EFFECTAND PRICE REVERSAL TAKING UNOBSERVABLE FACTORS INTO CONSIDERATION: WITH SPECIAL REFERENCE TO THE SRI LANKAN STOCK MARKET

Disposition Effect, which has been popularized and well documented as one of the various explanations for the persistence of momentum in the returns of the stocks over various time horizons was first documented by Shefrin and Statman (1985). Accordingly, the disposition effect refers to the tendency of investors to realize their profits too early and reluctance to realize their losses that arise out of changes in stock prices. The downward pressure on the prices of winner stocks due to higher growth in trading volume could lead to a price reversal, which ultimately results in losers outperforming winners for a specific time. This price reversal tendency could be influenced by many factors of which some are observable and, some, unobservable. Consideration of observable factors while disregarding those unobservable variables may result in producing biased and counterintuitive estimates by cross sectional and time series analyses. Based on the studies by Cressy and Farag (2009, 2010) this study examines by using Fixed Effects Model which takes unobservable factors into consideration, whether past losers outperform past winners. Using daily data from the Sri Lankan stock market, a sample of 20 stocks that faced a drastic 1 day price change was taken to examine price reversals. Even though cross section and pooled regression results yield insignificant results, fixed effects model strongly supports price reversals of the winning and losing stocks. These results suggest that the unobservable time specific together with firm specific factors play a major role in explaining price reversals in the Sri Lankan stock market

High Accuracy Protein Identification: Fusion of solid-state nanopore sensing and machine learning

Proteins are arguably the most important class of biomarkers for health diagnostic purposes. Label-free solid-state nanopore sensing is a versatile technique for sensing and analysing biomolecules such as proteins at single-molecule level. While molecular-level information on size, shape, and charge of proteins can be assessed by nanopores, the identification of proteins with comparable sizes remains a challenge. Here, we present methods that combine solid-state nanopore sensing with machine learning to address this challenge. We assess the translocations of four similarly sized proteins using amplifiers with bandwidths (BWs) of 100 kHz (sampling rate=200 ksps) and 10 MHz (sampling rate=40 Msps), the highest bandwidth reported for protein sensing, using nanopores fabricated in <10 nm thick silicon nitride membranes. F-values of up to 65.9% and 83.2% (without clustering of the protein signals) were achieved with 100 kHz and 10 MHz BW instruments, respectively, for identification of the four proteins. The accuracy of protein identification was significantly improved by grouping the signals into several clusters depending on the event features, resulting in F-value and specificity reaching as high as 88.7% and 96.4%, respectively, for combinations of four proteins. The combined improvement in sensor signals through the use of high bandwidth instruments, advanced clustering, machine learning, and other advanced data analysis methods allows identification of proteins with high accuracy

Dissecting the Economic Impact of Soybean Diseases in the United States over Two Decades

Soybean (Glycine max L. Merrill) is an economically important commodity for United States agriculture. Nonetheless, the profitability of soybean production has been negatively impacted by soybean diseases. The economic impacts of 23 common soybean diseases were estimated in 28 soybean-producing states in the U.S., from 1996 to 2016 (the entire data set consisted of 13,524 data points). Estimated losses were investigated using a variety of statistical approaches. The main effects of state, year, pre- and post-discovery of soybean rust, region, and zones based on yield, harvest area, and production, were significant on “total economic loss” as a function of diseases. Across states and years, the soybean cyst nematode, charcoal rot, and seedling diseases were the most economically damaging diseases while soybean rust, bacterial blight, and southern blight were the least economically damaging. A significantly greater mean loss (51%) was observed in states/years after the discovery of soybean rust (2004 to 2016) compared to the pre-discovery (1996 to 2003). From 1996 to 2016, the total estimated economic loss due to soybean diseases in the U.S. was $95.48 billion, with$80.89 billion and $14.59 billion accounting for the northern and southern U.S. losses, respectively. Over the entire time period, the average annual economic loss due to soybean diseases in the U.S. reached nearly$4.55 billion, with approximately 85% of the losses occurring in the northern U.S. Low yield/harvest/production zones had significantly lower mean economic losses due to diseases in comparison to high yield/harvest/production zones. This observation was further bolstered by the observed positive linear correlation of mean soybean yield loss (in each state, due to all diseases considered in this study, across 21 years) with the mean state wide soybean production (MT), mean soybean yield (kg ha-1), and mean soybean harvest area (ha). Results of this investigation provide useful insights into how research, policy, and educational efforts should be prioritized in soybean disease management

Hybrid Multipixel Array X-Ray Detectors for Real-Time Direct Detection of Hard X-Rays

X-ray detectors currently employed in dosimetry suffer from a number of drawbacks including the inability to conform to curved surfaces and being limited to smaller dimensions due to available crystal sizes. In this study, a hybrid X-ray detector (HXD) has been developed which offers real-time response with added advantages of being highly sensitive over a broad energy range, mechanically flexible, relatively inexpensive, and able to be fabricated over large areas on the desired surface. The detector comprises an organic matrix embedded with high-atomic-number inorganic nanoparticles which increase the radiation attenuation and within the device allows for simultaneous transfer of electrons and holes. The HXD delivers a peak response of 14 nA cm −2 , which corresponds to a sensitivity of 30.8 μC Gy −1 cm −2 , under the exposure of 6-MV hard X-rays generated by a medical linear accelerator. The angular dependence of the HXD has been studied, which offers a maximum variation of 26% in the posterior versus lateral beam directions. The flexible HXD can be conformed to the human body shape and is expected to eliminate variations due to source-to-skin distance with reduced physical evaluation complexities

Synthetic β‐Cyclodextrin Dimers for Squaraine Binding: Effect of Host Architecture on Photophysical Properties, Aggregate Formation and Chemical Reactivity

Reported herein is the synthesis and application of three novel β‐cyclodextrin dimer hosts for the complexation of near infrared (NIR) squaraine dyes in aqueous solution. A series of eight different N‐substituted N‐methyl anilino squaraine dyes with variable terminal groups are investigated, with an optimal n‐hexyl‐substituted squaraine guest demonstrating binding constants orders of magnitude higher than the other squaraine–host combinations and comparable to literature‐reported systems. Moreover, hydrophobic complexation of the squaraine dyes with the β‐cyclodextrin dimer hosts causes drastic changes in the squaraine\u27s photophysical properties, propensity for aggregation and susceptibility to hydrolytic decay

High Operating Temperature Barrier Infrared Detector with Tailorable Cutoff Wavelength

A barrier infrared detector with absorber materials having selectable cutoff wavelengths and its method of manufacture is described. A GaInAsSb absorber layer may be grown on a GaSb substrate layer formed by mixing GaSb and InAsSb by an absorber mixing ratio. A GaAlAsSb barrier layer may then be grown on the barrier layer formed by mixing GaSb and AlSbAs by a barrier mixing ratio. The absorber mixing ratio may be selected to adjust a band gap of the absorber layer and thereby determine a cutoff wavelength for the barrier infrared detector. The absorber mixing ratio may vary along an absorber layer growth direction. Various contact layer architectures may be used. In addition, a top contact layer may be isolated into an array of elements electrically isolated as individual functional detectors that may be used in a detector array, imaging array, or focal plane array

Modeling the Relationship Between Estimated Fungicide Use and Disease-Associated Yield Losses of Soybean in the United States I: Foliar Fungicides vs Foliar Diseases

Fungicide use in the United States to manage soybean diseases has increased in recent years. The ability of fungicides to reduce disease-associated yield losses varies greatly depending on multiple factors. Nonetheless, historical data are useful to understand the broad sense and long-term trends related to fungicide use practices. In the current study, the relationship between estimated soybean yield losses due to selected foliar diseases and foliar fungicide use was investigated using annual data from 28 soybean growing states over the period of 2005 to 2015. For national and regional (southern and northern United States) scale data, mixed effects modeling was performed considering fungicide use as a fixed and state and year as random factors to generate generalized R2 values for marginal (R2GLMM(m); contains only fixed effects) and conditional (R2GLMM(c); contains fixed and random effects) models. Similar analyses were performed considering soybean production data to see how fungicide use affected production. Analyses at both national and regional scales showed that R2GLMM(m) values were significantly smaller compared to R2GLMM(c) values. The large difference between R2 values for conditional and marginal models indicated that the variation of yield loss as well as production were predominantly explained by the state and year rather than the fungicide use, revealing the general lack of fit between fungicide use and yield loss/production at national and regional scales. Therefore, regression models were fitted across states and years to examine their importance in combination with fungicide use on yield loss or yield. In the majority of cases, the relationship was nonsignificant. However, the relationship between soybean yield and fungicide use was significant and positive for majority of the years in the study. Results suggest that foliar fungicides conferred yield benefits in most of the years in the study. Furthermore, the year-dependent usefulness of foliar fungicides in mitigating soybean yield losses suggested the possible influence of temporally fluctuating abiotic factors on the effectiveness of foliar fungicides and/or target disease occurrence and associated loss magnitudes