Search

Background: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. Results: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. Conclusion: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs. [ABSTRACT FROM AUTHOR]

Background: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. Results: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. Conclusion: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs. [ABSTRACT FROM AUTHOR]

Background: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. Results: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. Conclusion: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs. [ABSTRACT FROM AUTHOR]

In India, agricultural production is a crucial factor for economic growth. However, plants can be attacked by diseases that range from mild to severe, leading to their destruction. Therefore, it is essential to detect plant diseases at an early stage to prevent such damage. To address this issue, we propose a Hybrid Xception transfer learning with crossover optimized kernel extreme learning machine (HXTL-COKELM) method for identifying healthy and diseased plant leaves. The proposed approach preprocesses and extracts image features using transfer learning with the Xception model to improve computation accuracy before classification. Additionally, we developed a crossover-based tasmanian devil-optimized kernel extreme learning machine model to optimize the KELM's parameters using the TDO algorithm. We collected a dataset with 43,466 images of plant leaves from healthy and diseased plants to train, test, and validate the CNN model. Finally, we evaluated the system's efficacy using performance metrics such as accuracy, recall, specificity, F1-score, and kappa static value. Our experimental findings show that the proposed HXTL-COKELM method achieves a 98.9% accuracy rate, outperforming existing methods. The HXTL-COKELM model also exhibits superior overall performance. Thus, the proposed HXTL-COKELM model can effectively detect plant leaf diseases. [ABSTRACT FROM AUTHOR]

Scour is a natural phenomenon in alluvial streams around hydraulic structures due to the removal of bed material and often leads to their failure. Scour due to jets are the most prevalent form of scour seen downstream of hydraulic structures. This paper presents a detailed review of scour processes with respect to the effect of various parameters on scour under different jet conditions. Different aspects of the scour hole characteristics under various applications of jets have been reviewed, which include (1) scour process; (2) the effect of parameters such as impinging height, jet impact angle, aeration, size of sediment particle, and sediment gradation; (3) flow characteristics within the scour hole; and (4) temporal variation and time taken to reach an asymptotic state of scour depth. Moreover, the experimental findings of various researchers on the development of the scour profile geometry and their applicability to large-scale conditions have been summarized. [ABSTRACT FROM AUTHOR]

In this article, we prove the infinitude of the non‐trivial zeroes of Koecher–Maass series associated to a Siegel cusp form of weight k$k$ and degree 2 on the critical line. [ABSTRACT FROM AUTHOR]

The main problem that healthcare workers face in many hospitals is how long it takes patients to receive services. This tendency is becoming more prevalent, posing a threat to healthcare services. The repercussions of keeping people in a long line for medical care can result in a variety of issues, including death. The many server queuing models were utilized to examine the government hospital's service efficiency in this study. Over two weeks, primary data was collected at the hospital using observation and questionnaire methods to find the queuing model that minimizes patient waiting time. The findings revealed that most of the patients were dissatisfied with the hospital's queue management tactics. [ABSTRACT FROM AUTHOR]

Considering the pivotal role of interfaces in controlling the performance of organic electronic devices, implications of metal/organic interfacial quality in a Schottky barrier diode (SBD) are investigated. The nature of metal/organic interfaces and the thin film quality of regioregular poly (3-hexylthiophene) based SBDs fabricated in different device architectures are investigated using experimental and theoretical modeling. The importance of oxidized aluminum nanostructures as an interlayer at the Schottky interface for the dramatic enhancement of the rectification ratio (>106 at ±5 V) has been demonstrated, which is attributed to suppressed leakage current due to the oxide layer and the formation of a charge double layer. Furthermore, electrical performances of all the SBDs were modeled in terms of an underlying particular phenomenon solely or with the combination of multiple physical phenomena. The combined modeling equation used in this work fits well for the different device architectures, which validates its generality in order to extract the device parameters. [ABSTRACT FROM AUTHOR]

The "Horizontal Y" shaped queuing model in which there is bulk infinite arrival of patients, but available M services are limited. The discrete flow of patients in the system is reduced in continuous flow and a diffusion equation is used. In terms of means and variances of inter-arrival time distribution, this process of the number of patients and the number of servers is used, imposing reflecting boundaries. The inspiration for this analysis came from Aradhye and Kallurkar [2], and Armony [3], who explained that hospitals are complex systems whose problems can be resolved utilizing queuing theory. The present paper deals with a double-ended queue in which patients wait in a queue for services. The discrete distribution equations for queue size with various cases have been derived. Finally, the expected length of the queue, i.e., LC and the expected finite server, i.e., LS have been derived. [ABSTRACT FROM AUTHOR]

Given that a stationary Gaussian process is above a high threshold, the length of time it spends before going below that threshold is studied. The asymptotic order is determined by the smoothness of the sample paths, which in turn is a function of the tails of the spectral measure. Two disjoint regimes are studied – one in which the second spectral moment is finite and the other in which the tails of the spectral measure are regularly varying and the second moment is infinite. [ABSTRACT FROM AUTHOR]

The present study evaluates the accuracy of SNAP-Sentinel-2 Prototype Processor (SL2P) derived Leaf Area Index (LAI) and proposes a new simple method to generate new datasets of LAI through data fusion. Rigorous optimization of the data fusion approaches (Kalman filter and Linear weighted) were performed for the generation of new LAI products over the complex hilly terrain of the Himalayan region. The results showed a good correlation (r = 0.79) and low error (RMSE = 1.63) between SNAP-derived (at 20 m) and ground-observed LAI. A lower correlation was obtained between the ground observed LAI data and the corresponding global LAI products for the Moderate Resolution Imaging Spectroradiometer (MODIS) (r = 0.1, RMSE = 1.19), Copernicus Global Land Service (CGLS) (r = 0.1, RMSE = 0.61) and the Visible Infrared Imaging Radiometer Suite (VIIRS) (r = 0.04, RMSE = 1.25). Notably, after implementing the data fusion, both SNAP-derived LAI and Global LAI products exhibited much-improved performance statistics with ground observed data sets. [ABSTRACT FROM AUTHOR]

This study describes the settling velocity phenomenon and deals with the methods for its estimation. The accuracy of three previously proposed settling velocity equations is also checked in this study. After graphical and statistical analysis, the authors proposed generalized reduced gradient (GRG) and hybrid generalized reduced gradient–genetic algorithm (hybrid GRG-GA) approaches for the estimation of settling velocity. Hybrid GRG-GA-based settling velocity approach showed more precise results than GRG approach. In addition, hybrid GRG-GA and GRG approaches were compared with previously proposed equations using 226 data points. The graphical and statistical analysis shows that the hybrid GRG-GA and GRG approaches give better agreement with observed data points as compared to previously proposed equations. Application of hybrid GRG-GA reduces the sum of square of error in fall velocity by over 70% and 30% on an average as compared to previous equations during training and testing, respectively. This study highlights that the hybrid GRG-GA approach could be efficiently used for calculating the settling velocity. [ABSTRACT FROM AUTHOR]

Globally, smart cities, infrastructure, and transportation have led to a rise in vehicle numbers, resulting in an increasing number of problems. This includes problems such as air pollution, noise pollution, high energy consumption, and people's health. A viable solution to these problems is carpooling, which involves sharing vehicles between people going to the same location. As carpooling solutions become more popular, they need to be implemented efficiently. Data analytics can help people make informed decisions when selecting a ride (Car or Bus). We applied machine learning algorithms to select the desired ride (Car or Bus) and used feature ranking algorithms to identify the foremost traits for selecting the desired ride. Based on the performance evaluation metric, 11 classifiers were used for the experiment. In terms of selecting the desired ride, Random Forest performs best. Using ten-fold cross-validation, we obtained a sensitivity of 87.4%, a specificity of 73.7%, an accuracy of 81.0%, a sensitivity of 90.8%, a specificity of 77.6%, and an accuracy of 84.7% using leave-one-out cross-validation. To identify the most favorable characteristics of the Ride (Car or Bus), the recursive elimination of features algorithm was applied. By identifying the factors contributing to users' experience, the service providers will be able to rectify those factors to increase business. It has been determined that the weather can make or break the user experience. This model will be used to quantify and map intrinsic and extrinsic sentiments of the people and their interactions with locality, socio-economic conditions, climate, and environment. [ABSTRACT FROM AUTHOR]

Interband information overlapping enhances redundancy in hyperspectral data. This makes identification of application-specific optimal bands essential for obtaining accurate information about foliar traits. The current study investigated the performance of three novel Band Selection (BS) algorithms (i.e. the Chi-squared-statistics based attribute evaluator (CSS), the Recursive elimination of features-based attribute evaluator (REF) and the Correlation-based attribute subset evaluator (CBS)) in identifying the spectral bands of Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) from visible and Near Infrared (NIR) regions that are sensitive to variation in Chlorophyll Content (CC). Identified bands were employed to formulate Hyperspectral Indices (HIs) by incorporating combinations of Blue, Green, Red, and NIR regions. CC models were built by establishing a linear fit between ground CC and HIs. For all the three BS algorithms, optimum bands varied for visible and NIR regions. REF-HI (NIR,R), REF-HI(NIR,R + G), CSS-HI(NIR,R) and CSS-HI(NIR,R + G) had the best correlation with CC. HI(NIR,R) is identified as the best HI and REF the best BS algorithm for retrieving CC. [ABSTRACT FROM AUTHOR]

Flood is the most common natural hazard that causing unprecedented loss of life and property in the world. In recent years, flood damage has increased due to human intervention and land use and climate changes. The purpose of this study is to predict flood susceptibility in Tafresh watershed in Markazi Province, Iran based on K-nearest neighbor (KNN), Extremely Gradient Boosting (XGB) machine learning models and evaluate the performance of hybrid genetic algorithm (GA) optimization method and XGB model. For this purpose, 14 independent variables affecting flood susceptibility were prepared, also, 227 flood locations were identified as independent variables based on available information and field survey. In order to evaluate the efficiency of the models, receiver operating characteristic (ROC) parameters were used. Evaluating the efficiency of the models based on the AUCs of testing dataset showed the higher efficiency of the GA-XGB hybrid model in modeling flood susceptibility in the Tafresh watershed is compared to KNN and XGB models, and the AUC in KNN, XGB, and GA-XGB models are 0.82, 0.85, and 0.87, respectively. So using the genetic algorithm as an optimizer for determining the best parameters in the XGB model increases efficiency in this model. The results of determining the relative importance of independent variables in flood susceptibility modeling showed that the independent variables considered in each model have different effects. Distance from road and distance from river in all three models had significant importance in modeling flood hazard in the Tafresh watershed. The optimization method in this study can be used as a powerful method in other spatial modeling studies. The results of this study also support management programs to reduce flood risks in the study area. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut" published in BMC Plant Biology. The authors identified minor typographical errors in the original article and provided the corrected versions. The errors were related to the description of the composition of groundnut oil and the function of the fatty acid desaturase enzyme. The corrected article has been published to address these errors. The publisher, Springer Nature, remains neutral and does not take any position on jurisdictional claims or institutional affiliations. [Extracted from the article]

In this article, we have considered the problem of first sign change of Fourier coefficients of a primitive cusp form at a sparse sequence, where elements of the sparse sequence can be written as a sum of two squares. Following the methods of Kohnen–Sengupta, we give an effective upper bound on elements of such a sparse sequence to have first sign change. [ABSTRACT FROM AUTHOR]

This work focuses on comparing results of flood susceptibility modelling in the part of Middle Ganga Plain, Ganga foreland basin. Following inclusivity rule, 12 major flood explanatory factors including a new one, geomorphology, have been utilized. Out of 1000 randomly generated flood-points from 2008 Landsat 5 TM image derived flood polygon, 70% have been utilized for the training purpose of Shannon's entropy (SE) model and 30% for area under receiver operating characteristic (AUROC) method of validation of both, SE and frequency ratio (FR), models. Result from FR shows that the contributions of specific classes of different explanatory factors to flooding susceptibility vary whereas the SE model suggests that geomorphology is the most contributing factor. The AUROC curve for SE (0.90) was better than that for FR (0.85). Hence, the SE model predicts flood-susceptible areas more accurately than the multivariate statistical model FR in the study area. [ABSTRACT FROM AUTHOR]

The scouring process near spur dikes could jeopardize the stability of riverbanks. Thus, accurate estimation of the maximum scour depth near spur dikes is crucial in river engineering. However, due to the complexity of the scour phenomenon around these structures, it has been a challenge to accurately estimate the maximum scour depth. Few efforts have been made to develop a machine learning (ML) approach for such a purpose. In this study, two novel multilayer stacked generalization frameworks are developed to model the scour depth near a spur dike in a uniform sediment condition. Stacked tree-based frameworks consist of three standalone ML approaches, including multivariate adaptive regression spline, multigene genetic programming, and kernel extreme learning machine as the first layer and the boosting regression tree (BRT) and bagging regression tree (BGT) as meta learners. A total of 186 data points were collected from previous experimental studies, and 32 flume experiments were further conducted under clear water conditions at the Indian Institute of Technology (IIT) Roorkee Laboratory in this study. The performances of the models were assessed using various statistical metrics [e.g., correlation coefficient (R), root-mean-square error (RMSE), and mean absolute percentage error (MAPE)], graphical criteria, and some existing empirical equations. The modeling results demonstrated that the stacked BRT and BGT frameworks were superior to all the standalone ML approaches (R=0.9786 , RMSE=0.1654 , and MAPE=11.68 for BRT; and R=0.9742 , RMSE=0.1831 , and MAPE =11.29 for BGT). This finding was also confirmed by a comparison between the empirical correlations and the artificial intelligence models. In addition, the sensitivity analysis proved that the mean sediment size ratio (L/d50) was the most influential variable in estimating the scour depth near spur dikes. [ABSTRACT FROM AUTHOR]

In this article, we have considered the problem of first sign change of Fourier coefficients of a primitive cusp form at a sparse sequence, where elements of the sparse sequence can be written as a sum of two squares. Following the methods of Kohnen–Sengupta, we give an effective upper bound on elements of such a sparse sequence to have first sign change. [ABSTRACT FROM AUTHOR]

Shimura defined a family of maps from the space of modular forms of half-integral weight to the space of modular forms of integral weight. Selberg in his unpublished work found explicitly this correspondence (the first Shimura map 𝒮 1 ) for the class of forms which are products of a Hecke eigenform of level one and a Jacobi theta function. Later, Cipra generalized the work of Selberg to the case where Jacobi theta functions are replaced by the theta functions associated to Dirichlet character of prime power moduli, and the level one Hecke eigenforms are replaced by newforms of arbitrary level. Hansen and Naqvi generalized Cipra's work (on the image of a class of modular forms under the first Shimura map 𝒮 1 ) to cover theta functions associated to Dirichlet characters of arbitrary moduli. In this paper, we show that the earlier results can be modified to get similar results for the t th Shimura lifts 𝒮 t , for any positive square-free integer t. [ABSTRACT FROM AUTHOR]

Dietary restriction (DR) extends healthy lifespan in diverse species. Age and nutrient- related changes in the abundance of microRNAs (miRNAs) and their processing factors have been linked to organismal longevity. However, the mechanisms by which they modulate lifespan and the tissue-specific role of miRNA-mediated networks in DR-dependent enhancement of lifespan remains largely unexplored. We show that two neuronally enriched and highly conserved microRNAs, miR-125 and let-7 mediate the DR response in Drosophila melanogaster. Functional characterization of miR-125 demonstrates its role in neurons while its target chinmo acts both in neurons and the fat body to modulate fat metabolism and longevity. Proteomic analysis revealed that Chinmo exerts its DR effects by regulating the expression of FATP, CG2017, CG9577, CG17554, CG5009, CG8778, CG9527, and FASN1. Our findings identify miR-125 as a conserved effector of the DR pathway and open the avenue for this small RNA molecule and its downstream effectors to be considered as potential drug candidates for the treatment of late-onset diseases and biomarkers for healthy aging in humans. [ABSTRACT FROM AUTHOR]

Plant bioregulators (PBRs) represent low-cost chemicals for boosting plant defense, especially under stress conditions. In the present study, redox based PBRs such as thiourea (TU; a non-physiological thiol-based ROS scavenger) and hydrogen peroxide (H2O2; a prevalent biological ROS) were assessed for their ability to mitigate NaCl stress in rice variety IR 64. Despite their contrasting redox chemistry, TU or H2O2 supplementation under NaCl [NaCl + TU (NT) or NaCl + H2O2 (NH)] generated a reducing redox environment in planta, which improved the plant growth compared with those of NaCl alone treatment. This was concomitant with better K+ retention and upregulated expression of NaCl defense related genes including HAK21, LEA1, TSPO and EN20 in both NT and NH treated seedlings. Under field conditions, foliar applications of TU and H2O2, at vegetative growth, pre-flowering and grain filling stages, increased growth and yield attributes under both control and NaCl stress conditions. Principal component analysis revealed glutathione reductase dependent reduced ROS accumulation in source (flag leaves) and sucrose synthase mediated sucrose catabolism in sink (developing inflorescence), as the key variables associated with NT and NH mediated effects, respectively. In addition, photosystem-II efficiency, K+ retention and source-sink relationship were also improved in TU and H2O2 treated plants. Taken together, our study highlights that reducing redox environment acts as a central regulator of plant's tolerance responses to salt stress. In addition, TU and H2O2 are proposed as potential redox-based PBRs for boosting rice productivity under the realistic field conditions. [ABSTRACT FROM AUTHOR]

This paper investigates the effectiveness of four different airfoil collars (b c 1 , b c 2 , b c 3 , and b c 4 ) in reducing scour around the bridge pier. A total of 69 experiments are conducted under two threshold velocities with two pier diameters of 0.05 and 0.06 m and four airfoil collars placed at four locations from the uniform sediment bed. This study investigates the scour hole profiles and their depth, effect of flow intensity, collar diameter, and location on scour depth, and computes the protection efficiencies. The results show that the collar effectively reduces the scour depth. When the collar is located at bed level (i.e., y = 0, where y is water depth from the bed), y /4, y /2, and 3 y /4 above the bed level, the protection efficacies are found to be ranging between the percentages 65–100%, 40–53%, 23–38%, and 8–29% for b c 1 , b c 2 , b c 3 , and b c 4 , respectively. An empirical relationship is proposed for variation of scour depth with respect to time. Statistical sensitivity analyses are performed and found that the most and least sensitive parameters are h / y and T c , where h and T c are the collar's location from the water surface and dimensionless time, respectively. • This paper investigates the effectiveness of four different airfoil collars (b c 1 , b c 2 , b c 3 , and b c 4 ) in reducing scour around the bridge pier. • This study investigates the scour hole profiles and their depth, effect of flow intensity, collar diameter, and location on scour depth, and computes the protection efficiencies. The results show that the collar effectively reduces the scour depth. • When the collar is located at bed level (i.e., y = 0, where y is water depth from the bed), y /4, y /2, and 3 y /4 above the bed level, the protection efficacies are found to be ranging between the percentages 65–100%, 40–53%, 23–38%, and 8–29% for b c 1 , b c 2 , b c 3 , and b c 4 , respectively. • Empirical relationships are proposed for maximum scour depth and variation in scour depth with time. • Statistical sensitivity analyses are performed and found that the most and least sensitive parameters are h / y and T c , where h and T c are the collar's location from the water surface and dimensionless time, respectively. [ABSTRACT FROM AUTHOR]

Background: Anti-EGFR-based therapies have limited success in HNSCC patients. Predictive biomarkers are greatly needed to identify the patients likely to be benefited from these targeted therapies. Here, we present the prognostic and predictive association of biomarkers in HPV-negative locally advanced (LA) HNSCC patients.Methods: Treatment-naive tumour tissue samples of 404 patients, a subset of randomised Phase 3 trial comparing cisplatin radiation (CRT) versus nimotuzumab plus cisplatin radiation (NCRT) were analysed to evaluate the expression of HIF1α, EGFR and pEGFR by immunohistochemistry and EGFR gene copy change by FISH. Progression-free survival (PFS), locoregional control (LRC) and overall survival (OS) were estimated by Kaplan-Meier method. Hazard ratios were estimated by Cox proportional hazard models.Results: Baseline characteristics of the patients were balanced between two treatment groups (CRT vs NCRT) and were representative of the trial cohort. The median follow-up was of 39.13 months. Low HIF1α was associated with better PFS [HR (95% CI) = 0.62 (0.42-0.93)], LRC [HR (95% CI) = 0.56 (0.37-0.86)] and OS [HR (95% CI) = 0.63 (0.43-0.93)] in the CRT group. Multivariable analysis revealed HIF1α as an independent negative prognostic biomarker. For patients with high HIF1α, NCRT significantly improved the outcomes [PFS:HR (95% CI) = 0.55 (0.37-0.82), LRC:HR (95% CI) = 0.55 (0.36-0.85) and OS:HR (95% CI) = 0.54 (0.36-0.81)] compared to CRT. While in patients with low HIF1α, no difference in the clinical outcomes was observed between treatments. Interaction test suggested a predictive value of HIF1α for OS (P = 0.008).Conclusions: High HIF1α expression is a predictor of poor clinical response to CRT in HPV-negative LA-HNSCC patients. These patients with high HIF1α significantly benefited with the addition of nimotuzumab to CRT.Clinical Trial Registration: Registered with the Clinical Trial Registry of India (Trial registration identifier-CTRI/2014/09/004980). [ABSTRACT FROM AUTHOR]

Key message: Comparative assessment identified naïve interaction model, and naïve and informed interaction GS models suitable for achieving higher prediction accuracy in groundnut keeping in mind the high genotype × environment interaction for complex traits. Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K 'Axiom_Arachis' SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400–0.600) were obtained for pods/plant, shelling %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut. [ABSTRACT FROM AUTHOR]

Sugarcane (Saccharum officinarum) is a globally cultivated cash crop whose yield is negatively affected by soil salinity. In this study, we investigated the molecular basis of inducible salt tolerance in M4209, a sugarcane mutant line generated through radiation-induced mutagenesis. Under salt-contaminated field conditions, M4209 exhibited 32% higher cane yield as compared with its salt-sensitive parent, Co86032. In pot experiments, post-sprouting phenotyping indicated that M4209 had significantly greater leaf biomass compared with Co86032 under treatment with 50 mM and 200 mM NaCl. This was concomitant with M4209 having 1.9-fold and 1.6-fold higher K+/Na+ ratios, and 4-fold and 40-fold higher glutathione reductase activities in 50 mM and 200 mM NaCl, respectively, which suggested that it had better ionic and redox homeostasis than Co86032. Transcriptome profiling using RNA-seq indicated an extensive reprograming of stress-responsive modules associated with photosynthesis, transmembrane transport, and metabolic processes in M4209 under 50 mM NaCl stress. Using ranking analysis, we identified Phenylalanine Ammonia Lyase (PAL), Acyl-Transferase Like (ATL), and Salt-Activated Transcriptional Activator (SATA) as the genes most associated with salt tolerance in M4209. M4209 also exhibited photosynthetic rates that were 3–4-fold higher than those of Co86032 under NaCl stress conditions. Our results highlight the significance of transcriptional reprogramming coupled with improved photosynthetic efficiency in determining salt tolerance in sugarcane. [ABSTRACT FROM AUTHOR]

Iron deficiency chlorosis is an important abiotic stress affecting groundnut production worldwide in calcareous and alkaline soils with a pH of 7.5–8.5. To identify genomic regions controlling iron deficiency chlorosis resistance in groundnut, the recombinant inbred line population from the cross TAG 24 × ICGV 86031 was evaluated for associated traits like visual chlorosis rating and SPAD chlorophyll meter reading across three crop growth stages for two consecutive years. Thirty‐two QTLs were identified for visual chlorosis rating (3.9%–31.8% phenotypic variance explained [PVE]) and SPAD chlorophyll meter reading [3.8%–11% PVE] across three stages over 2 years. This is the first report of identification of QTLs for iron deficiency chlorosis resistance‐associated traits in groundnut. Three major QTLs (>10% PVE) were identified at severe stage, while majority of other QTLs were having small effects. Interestingly, two major QTLs for visual chlorosis rating at 60 days (2013) and 90 days (2014) were located at same position on LG AhXIII. The identified QTLs/markers after validation across diverse genetic material could be used in genomics‐assisted breeding. [ABSTRACT FROM AUTHOR]

Key message: Groundnut has entered now in post-genome era enriched with optimum genomic and genetic resources to facilitate faster trait dissection, gene discovery and accelerated genetic improvement for developing climate-smart varieties. Cultivated groundnut or peanut (Arachis hypogaea), an allopolyploid oilseed crop with a large and complex genome, is one of the most nutritious food. This crop is grown in more than 100 countries, and the low productivity has remained the biggest challenge in the semiarid tropics. Recently, the groundnut research community has witnessed fast progress and achieved several key milestones in genomics research including genome sequence assemblies of wild diploid progenitors, wild tetraploid and both the subspecies of cultivated tetraploids, resequencing of diverse germplasm lines, genome-wide transcriptome atlas and cost-effective high and low-density genotyping assays. These genomic resources have enabled high-resolution trait mapping by using germplasm diversity panels and multi-parent genetic populations leading to precise gene discovery and diagnostic marker development. Furthermore, development and deployment of diagnostic markers have facilitated screening early generation populations as well as marker-assisted backcrossing breeding leading to development and commercialization of some molecular breeding products in groundnut. Several new genomics applications/technologies such as genomic selection, speed breeding, mid-density genotyping assay and genome editing are in pipeline. The integration of these new technologies hold great promise for developing climate-smart, high yielding and more nutritious groundnut varieties in the post-genome era. [ABSTRACT FROM AUTHOR]

Key message: Two novel and adjacent genomics and candidate genes for bacterial wilt resistance were identified on chromosome B02 in peanut variety Zhonghua 6 using both traditional QTL mapping and QTL-seq methods. Peanut (Arachis hypogaea) is an important oilseed crop worldwide. Utilization of genetic resistance is the most economic and effective approach to control bacterial wilt, one of the most devastating plant diseases, in peanut production. To accelerate the genetic improvement of bacterial wilt resistance (BWR) in peanut breeding programs, quantitative trait locus (QTL) mapping has been conducted for two resistant varieties. In this context, we deployed linkage mapping as well as sequencing-based mapping approach, QTL-seq, to identify genomic regions and candidate genes for BWR in another highly resistant variety Zhonghua 6. The recombination inbred line population (268 progenies) from the cross Xuhua 13 × Zhonghua 6 was used in BWR evaluation across five environments. QTL mapping using both SSR- and SNP-based genetic maps identified a stable QTL (qBWRB02-1) on chromosome B02 with 37.79–78.86% phenotypic variation explained (PVE) across five environments. The QTL-seq facilitated further dissection of qBWRB02-1 into two adjacent genomic regions, qBWRB02-1-1 (2.81–4.24 Mb) and qBWRB02-1-2 (6.54–8.75 Mb). Mapping of newly developed Kompetitive allele-specific PCR (KASP) markers on the genetic map confirmed their stable expressions across five environments. The effects of qBWRB02-1-1 (49.43–68.86% PVE) were much higher than qBWRB02-1-2 (3.96–6.48% PVE) and other previously reported QTLs. Nineteen putative candidate genes affected by 49 non-synonymous SNPs were identified for qBWRB02-1-1, and ten of them were predicted to code for disease resistance proteins. The major and stable QTL qBWRB02-1-1 and validated KASP markers could be deployed in genomics-assisted breeding (GAB) to develop improved peanut varieties with enhanced BWR. [ABSTRACT FROM AUTHOR]

In this article, we investigate the sign changes of the sequence of coefficients at sum of two squares where the coefficients are the Fourier coefficients of the normalized Hecke eigen cusp form for the full modular group. We provide the quantitative result for the number of sign changes of the sequence in a small interval. [ABSTRACT FROM AUTHOR]

Summary: Bacterial wilt, caused by Ralstonia solanacearum, is a devastating disease affecting over 350 plant species. A few peanut cultivars were found to possess stable and durable bacterial wilt resistance (BWR). Genomics‐assisted breeding can accelerate the process of developing resistant cultivars by using diagnostic markers. Here, we deployed sequencing‐based trait mapping approach, QTL‐seq, to discover genomic regions, candidate genes and diagnostic markers for BWR in a recombination inbred line population (195 progenies) of peanut. The QTL‐seq analysis identified one candidate genomic region on chromosome B02 significantly associated with BWR. Mapping of newly developed single nucleotide polymorphism (SNP) markers narrowed down the region to 2.07 Mb and confirmed its major effects and stable expressions across three environments. This candidate genomic region had 49 nonsynonymous SNPs affecting 19 putative candidate genes including seven putative resistance genes (R‐genes). Two diagnostic markers were successfully validated in diverse breeding lines and cultivars and could be deployed in genomics‐assisted breeding of varieties with enhanced BWR. [ABSTRACT FROM AUTHOR]

Overfitting occurs when one tries to train a large model on small amount of data. Regularizing a neural network using prior knowledge remains a topic of research as it is not concluded how much prior information can be given to the neural network. In this paper, a novel algorithm is introduced which uses regularization to train a neural network without increasing the dataset. A trivial prior information of a class label is supplied to the model while training. Laplace noise is introduced to the intermediate layer for more generalization. The results show significant improvement in accuracy on the standard datasets for a simple Convolutional Neural Network (CNN). While the proposed method outperforms previous regularization techniques like dropout and batch normalization, it can also be applied with them for further improvement in the performance. On the variants of MNIST, proposed algorithm achieved an average 48% increment in the test accuracy. [ABSTRACT FROM AUTHOR]

Natural algal bloom consists of promising algal species which could be a feasible option for the source of bulk biomass and biodiesel production. It has been found in five natural fresh water algal blooms (Uttar Pradesh, India), containing high nitrogen (N) (4.6 ± 0.32 mg/L) and phosphorus (P) (4.12 ± 0.29 mg/L) concentration during spring (23.9–25.9 °C) and summer season (32.0–35.0 °C). Among the isolated algae from naturally occurring bloom, Chlorella sorokiniana MKP01 exhibited highest biomass (1.02 ± 0.02 g/L) and lipid content (174.1 ± 9.6 mg/L) in untreated tap water and urea/single super phosphate (SSP) in the ratio (2:1). The biodiesel quality was assessed and found to be with the Indian and international standards. Algal bloom was artificially developed in the open pond containing 10,000 l tap water supplemented with Urea/SSP (2:1) for a consistent supply of bulk biomass, yielded 8 kg of total biomass and lipid 1.3 kg. [ABSTRACT FROM AUTHOR]

Summary: Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non‐synonymous effects or in UTRs were identified in these regions for SP. Cost‐effective KASP (Kompetitive Allele‐Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties. [ABSTRACT FROM AUTHOR]

Ploidy difference between wild Arachis species and cultivated genotypes hinder transfer of useful alleles for agronomically important traits. To overcome this genetic barrier, two synthetic tetraploids, viz., ISATGR 1212 (A. duranensis ICG 8123 × A. ipaensis ICG 8206) and ISATGR 265-5A (A. kempff-mercadoi ICG 8164 × A. hoehnei ICG 8190), were used to generate two advanced backcross (AB) populations. The AB-populations, namely, AB-pop1 (ICGV 91114 × ISATGR 1212) and AB-pop2, (ICGV 87846 × ISATGR 265-5A) were genotyped with DArT and SSR markers. Genetic maps were constructed for AB-pop1 and AB-pop2 populations with 258 loci (1415.7 cM map length and map density of 5.5 cM/loci) and 1043 loci (1500.8 cM map length with map density of 1.4 cM/loci), respectively. Genetic analysis identified large number of wild segments in the population and provided a good source of diversity in these populations. Phenotyping of these two populations identified several introgression lines with good agronomic, oil quality, and disease resistance traits. Quantitative trait locus (QTL) analysis showed that the wild genomic segments contributed favourable alleles for foliar disease resistance while cultivated genomic segments mostly contributed favourable alleles for oil quality and yield component traits. These populations, after achieving higher stability, will be useful resource for genetic mapping and QTL discovery for wild species segments in addition to using population progenies in breeding program for diversifying the gene pool of cultivated groundnut. [ABSTRACT FROM AUTHOR]

Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and technologies. For instance, next-generation sequencing technologies have facilitated availability of genome sequence assemblies, re-sequencing of several hundred lines, development of HapMaps, high-density genetic maps, a range of marker genotyping platforms and identification of markers associated with a number of agronomic traits in these legume crops. Although marker-assisted backcrossing and marker-assisted selection approaches have been used to develop superior lines in several cases, it is the need of the hour for continuous population improvement after every breeding cycle to accelerate genetic gain in the breeding programs. In this context, we propose a sequence-based breeding approach which includes use of independent or combination of parental selection, enhancing genetic diversity of breeding programs, forward breeding for early generation selection, and genomic selection using sequencing/genotyping technologies. Also, adoption of speed breeding technology by generating 4–6 generations per year will be contributing to accelerate genetic gain. While we see a huge potential of the sequence-based breeding to revolutionize crop improvement programs in these legumes, we anticipate several challenges especially associated with high-quality and precise phenotyping at affordable costs, data analysis and management related to improving breeding operation efficiency. Finally, integration of improved seed systems and better agronomic packages with the development of improved varieties by using sequence-based breeding will ensure higher genetic gains in farmers' fields. [ABSTRACT FROM AUTHOR]

Abstract Given two pure representations of the absolute Galois group of an ℓ -adic number field with coefficients in Q ‾ p (with ℓ ≠ p), we show that the Frobenius-semisimplifications of the associated Weil–Deligne representations are twists of each other by an integral power of a certain unramified character if they have equal normalized traces. This is an analogue of a recent result of Patankar and Rajan in the context of local Galois representations. [ABSTRACT FROM AUTHOR]

Hypsometry is widely used for inferring tectonic effects and erosion status of landscapes. Tectonics, structural inhomogeneity, lithologic differences, and climatic variations lead to topographic undulations discerned into discrepancies in the values. Hypsometric index (and curve), indicative of frequency distribution of proportional elevation with the respective proportional area, is used as a tool to describe characteristics of landscape morphology, lithological variability, and degree of fluvial dissection. Many workers have used to infer comparison of rates of erosion with tectonic uplift rates. However, there are many other factors reported to influence topographic undulations other than tectonics which lead to a variety of hypsometries. Morphotectonic index, hypsometric integral, calculated using digital elevation models (DEMs) in GIS environment has been widely used for inferring tectonic effects, status of erosion, and structural controls. The present study is conducted in the North Koel River basin. This river rises in the Ranchi plateau and joins the Son River a few miles north-west of Haidarnagar, is the right bank tributary of the Son River. Along its entire course of flow, North Koel river (260 km) flows through plateau region mostly formed of metamorphic rocks. Hence, structural control seems to be the primary control on the landscape evolution of this subbasin. In this study, hypsometric integral (and curve) has been calculated for third order and upper order streams to look whether this morphotectonic index shows any sign of tectonic, structural, or lithologic control on the landscape evolution in the North Koel River basin. [ABSTRACT FROM AUTHOR]

The experimental results of time average velocity components measured around circular pier models during transient scour stage using acoustic Doppler velocimeter are shown for flow pattern and turbulence characteristics. Totally, four experiments were performed under clear water scour conditions in a model of gravel bed stream. Four circular pier models of diameter 6.6, 8.4, 11.5, and 13.5 cm were used for this study. Detailed controlled measurements on velocity components, and turbulence intensities near the pier and in scour hole at 0° and 180° plane are shown. Flow structure around a pier model in the presence of a scoured region was compared with the flow structure similarly noticed around all pier model runs by utilizing the observations taken at 0° and 180° plane from flow axis. Size of the primary vortex at 0° plane with largest diameter pier model in place (R4 run) is found to be maximum and was approximately 61% larger than that for smallest diameter pier model in place (R1 run). The time-averaged velocity components of turbulence intensities plots at 0° and 180° planes are also presented around each pier. [ABSTRACT FROM AUTHOR]

An effective approach for tuning the electronic characteristics of polymer-based organic field-effect transistors (OFETs) consisted of poly(3-hexylthiophene) (P3HT) doped with 7,7,8,8-tetracyanoquinodimethane (TCNQ) and depleting layer formed by aluminum (Al) coating is being reported. Doping of P3HT was employed to accumulate and tune the carrier concentration while implementation of depletion layer led to reduce the channel conductance. It has been demonstrated that on-currents in the OFETs were enhanced with the extent of TCNQ doping from 0% to 20% in the P3HT. Upon introduction of an ultra-thin Al led to the formation of depletion region resulting in to further decrease in the off-state current along with the improvement in the subthreshold characteristics. These two procedures provide counter-effects in terms of the on-state characteristics by doping and the off-state characteristics by depletion, which promotes switching performance in OFETs indicating the potentiality of doping technology for organic electronics. [ABSTRACT FROM AUTHOR]

An effort was made in the present study to identify the main effect and epistatic quantitative trait locus (QTL) for the morphological and yield-related traits in peanut. A recombinant inbred line (RIL) population derived from TAG 24 × GPBD 4 was phenotyped in seven environments at two locations. QTL analysis with available genetic map identified 62 main-effect QTLs (M-QTLs) for ten morphological and yield-related traits with the phenotypic variance explained (PVE) of 3.84-15.06%. Six major QTLs (PVE > 10%) were detected for PLHT, PPP, YPP, and SLNG. Stable M-QTLs appearing in at least two environments were detected for PLHT, LLN, YPP, YKGH, and HSW. Five M-QTLs governed two traits each, and 16 genomic regions showed co-localization of two to four M-QTLs. Intriguingly, a major QTL reported to be linked to rust resistance showed pleiotropic effect for yield-attributing traits like YPP (15.06%, PVE) and SLNG (13.40%, PVE). Of the 24 epistatic interactions identified across the traits, five interactions involved six M-QTLs. Three interactions were additive × additive and remaining two involved QTL × environment (QE) interactions. Only one major M-QTL governing PLHT showed epistatic interaction. Overall, this study identified the major M-QTLs for the important productivity traits and also described the lack of epistatic interactions for majority of them so that they can be conveniently employed in peanut breeding. [ABSTRACT FROM AUTHOR]

Rust and late leaf spot ( LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing ( WGRS)-based approach referred as ' QTL-seq' was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms ( SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population ( TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications. [ABSTRACT FROM AUTHOR]

• Plant disease detection and diagnosing measures become a major concern in agriculture field. • Proposed HRF-MCSVM accurately classifies the diseases and rapidly improves the quality. • So avoid such destruction, plant diseases should be detected at the initial stage. • Proposed HRF-MCSVM method is compared with a few existing techniques to determine its efficiency. In recent times, plant disease detection and diagnosing measures become a major concern in the agriculture field. Earlier identification of plant disease aids the farmers to take precautionary measures thereby preventing the spread of disease to other parts of plants. Based on the severity of the diseases, the plant may undergo an attack from mild to complete destruction. So, to avoid such destruction, plant diseases should be detected at the initial stage. Therefore, this paper proposes a novel hybrid random forest Multiclass SVM (HRF-MCSVM) design for plant foliar disease detection. To improve the computation accuracy, the image features are preprocessed and segmented using Spatial Fuzzy C-Means prior to the classification process. The Plant Village dataset used consists of a total of 54,303 healthy and diseased leaf images. Finally, the performance metrics like accuracy, F-measure, specificity, sensitivity, and recall value were evaluated to determine the effectiveness of the system. The proposed HRF-MCSVM method is compared with a few existing techniques to determine its efficiency. [ABSTRACT FROM AUTHOR]

In the present study, device geometry having top contact bottom gated poly(2,5-bis(3-tetradecylthiophen-2yl)thieno(3,2-b)thiophene) (PBTTT) based polymer thin film transistor (PTFT) is reported to measure the changes in electrical responses with the exposure to various concentrations of ammonia vapor at room temperature. PTFT is preferred over other electronic devices due to its multi-parameter characteristics to explore gas sensing capabilities. A facile floating–film transfer method (FTM) is used to prepare an active layer of PTFT by forming optimized thin layer of PBTTT film having a thickness of ∼25 nm. Exposure to various concentrations of ammonia vapor, device parameters like I/O characteristics, mobility, threshold voltage, and trap density are found to change significantly. As PTFT is exposed to 100 ppm ammonia vapor a 70% reduction in mobility is observed whereas threshold voltage shifted to more negative from −17.62 V to −23.64 V. Better sensing capabilities with a detection limit of 0.33 ppm, fast response and recovery of exposed ammonia vapor are observed, when PTFT is operated in sub-threshold regime rather than the cut-off or saturated regime. All the electrical characterizations for the sensing purpose are carried out in ambient but in a closed chamber. Device shows enormous potential for ammonia sensing for real and environmental applications. [ABSTRACT FROM AUTHOR]

Peanut (Arachis hypogaea L.) is an important self-pollinating tetraploid (AABB, 2n = 4x = 40) legume grown for the high-quality edible oil and easily digestible protein in its seeds. Enormous genetic variability is present in the genus Arachis containing 79 wild species and cultivated peanut. Wild species offer significant variability, particularly for biotic and abiotic stresses, and can be used to develop cultivars with enhanced levels of resistance to key stresses. However, utilization of these species requires use of ploidy manipulations, bridge crosses, and embryo or ovule rescue. For efficient use of diploid wild species from section Arachis, several synthetics (amphidiploids and autotetraploids) have been developed using A- and B-genome accessions with high levels of resistance to multiple stresses. These synthetics are used in crossing programs with cultigens to develop prebreeding populations and introgression lines (ILs) with high frequency of useful genes and alleles into good agronomic backgrounds. Evaluation of two such populations derived from ICGV 91114 x ISATGR 121250 (a synthetic derived from A. duranensis Krapov. & W.C. Greg. x A. ipaensis Krapov. & W.C. Greg.) and ICGV 87846 x ISATGR 265-5 (A. kempf-mercadoi W.C. Greg. & C.E. Simpson x A. hoehnei Krapov. & W.C. Greg.) resulted in the identification of ILs with high levels of late leaf spot (LLS) and rust resistance and significant genetic variability for morphoagronomic traits. Genotyping of these ILs with markers linked to rust and LLS resistance provided evidence that introgression of possible novel alleles and resistance sources from different wild species other than the commonly used A. cardenasii Krapov. & W.C. Greg. will be beneficial for peanut improvement. [ABSTRACT FROM AUTHOR]

Dynamic casting of floating-film and transferring method for preparing oriented multilayer films of conjugated polymers is reported. This method is based on dynamic casting of a floating-film on liquid substrate to obtain oriented thin-film followed by its transfer on a desired solid substrate. The uniqueness in this method lies in the isolation of casting and coating procedures of oriented films, which enables us to fabricate the oriented multilayer with minimum interlayer interference. It provides a key-technology to build up the organic multi-layered architecture while preserving oriented morphologies. Several types of multilayer films have been prepared and investigated in detail in terms of their film characteristics. The layer-by-layer coating of oriented films demonstrated by this method is found to be a unique feature which overcomes cumbersome procedures in the conventional orientation methods. The coating procedure demonstrated in this study provides a facile methodology to construct anisotropic architectures. [ABSTRACT FROM AUTHOR]

Considering the advantages of floating film transfer method (FTM), we have investigated the optical and electronic characteristics of PBTTT-C14 thin-films prepared by the static and the dynamic casting on liquid substrate. It has been demonstrated that judicious selection of solvents during FTM switches the casting mode from the static casting (S-FTM) using high boiling point solvent to the dynamic casting (D-FTM) from low boiling point solvent. Although both of the methods provide the edge-on oriented structure of PBTTT-C14 by XRD, the structural and the optical analyses reveal relatively extended π-conjugation length in parallel D-FTM film as compared to that of S-FTM. A high field-effect mobility (μ) of 0.11 cm 2 /V.s was exhibited by OFETs fabricated by parallel D-FTM film even without any high temperature post-annealing up to the liquid crystalline phase transition. This observed value of μ for parallel D-FTM is 4.7 and 12.8 times higher than the isotropic S-FTM and the perpendicular D-FTM films, respectively. [ABSTRACT FROM AUTHOR]

Recent changes to immigration selection policies favor skilled workers with prior work experience in the immigrant host country. Using unique administrative tax data for Canada, we estimate earnings equations to quantify the difference in earnings of immigrants with prior Canadian experience (prefilers) and those without prior experience (non-prefilers). We find that, relative to non-prefilers, entry earnings are higher for prefilers and, for male immigrants, this earnings advantage persists for at least 20 years after arrival. We show that the primary source of the higher entry earnings of prefilers is a higher return to foreign experience. In addition, the prefiler earnings advantage is largest for university graduates and the return to foreign experience is higher for prefilers from Western countries than those from the rest of the world. Our findings suggest that a move towards an immigrant selection system which uses previous host-country work experience as a criterion will improve the labor market performance of immigrants. [ABSTRACT FROM AUTHOR]

Let (S,ω) be a weighted abelian semigroup, let Mω(S) be the semigroup of ω-bounded multipliers of S, and let A be a strictly convex commutative Banach algebra with identity. It is shown that T is an onto isometric multiplier of ℓ¹(S, ω, A) if and only if there exists an invertible σ ∈ Mω(S), a unitary point a ∈ A, and a k > 0 such that T(f) = ka ∑x∈S f(x)δσ(x) for each f = ∑x∈S f(x)δx ∈ ℓ¹(S, ω, A). It is also shown that an isomorphism from ℓ¹(S1, ω1, A) onto ℓ¹(S2, ω2, B) induces an isomorphism from M(ℓ¹(S1, ω1, A)), the set of all multipliers of ℓ¹(S1, ω1, A), onto M(ℓ¹(S2, ω2, B)). [ABSTRACT FROM AUTHOR]