Patterns of trait associations in various wheat populations under different growth environments

Five wheat populations were investigated for two years to explore the pattern of trait associations and their contribution to grain yield. The correlation pattern between two traits and their association with grain yield was similar in CIMMYT and Pakistani germplasm. Indian germplasm had different pattern of trait association from those of CIMMYT and Pakistani germplasm. The number of kernels per plant, number of spikes per plant, spike length and spike dry weight were the major yield contributing traits in CIMMYT, Pakistani and ICARDA genotypes. In Indian and miscellaneous genotypes, the number of kernels per plant and number of spikes per plant were the only traits with a positive effect on grain yield. Furthermore, three traits, the number of kernels per plant, the number of spikes per plant and the spike dry weight appeared to have positive effect on grain yield and other major yield traits. Spike density had a negative effect on grain yield in CIMMYT germplasm in dry season. Chlorophyll contents showed no correlation with grain yield in all populations.Key words: Pakistani, CIMMYT, genotypes, wheat, ICARDA, populations

Advanced Particle Swarm Optimization Algorithm with Improved Velocity Update Strategy

© 2018 IEEE. In this paper, advanced particle swarm optimization Algorithm (APSO) with improved velocity updated strategy is presented. The algorithm incorporates an improved velocity update equation so that the particles will reach the optimum point quickly and convergence is much faster than the standard PSO (SPSO) and other improved PSOs in the literature. Five benchmark functions have been selected to evaluate the efficiency of the proposed algorithm. The simulation results demonstrate that the proposed technique has remarkably improved in terms of convergence and solution quality

Profiles of Diabetic Ketoacidosis in Multiethnic Diabetic Population of Malaysia

Purpose: To outline first-time patient profiles of diabetic ketoacidosis (DKA) in the absence of reported incidence and mortality rates of DKA in Malaysian diabetic population.Methods: A retrospective cross-sectional study was designed and all medical records of patients with a discharge note of DKA were reviewed. Admissions from January 2009 to December 2011 were included. Data were analyzed in terms of socio-demographic variables in order to provide incidence and mortality rates. Medical history, as well as physical and biochemical characteristics were analyzed to report epidemiology of DKA patients.Results: Out of a total of 207 admissions for DKA, 132 were selected for the present study. Female (62.9 %), Malay ethnic (47.0 %) and the elderly (45.1 years and above) contributed most to DKA episodes. Type 2 diabetes mellitus (51.1 %) patients were prone to develop DKA. Most patients experienced mild to moderate episode of DKA by the time they sought medical attention. Although, there was no significant relationship between chronic co-morbidity and occurrence of DKA, hypertension (54.5 %), dyslipidemia (43.0 %) and cardiac disorders (35.6 %) were, however, the most frequently observed co-morbidities. Non-adherence (43.2 %), sepsis (31.9 %) and respiratory tract infection (12.2 %) were the most encountered precipitating factors for DKA episode. Mortality rate was as high as 17.6 %.Conclusion: With a higher incidence and mortality rate of DKA in Malaysia, the patterns observed in this study seem to be different from those of developed nations. Further extended studies need to be undertaken to elaborate regional and national patterns of DKA.Keywords: Incidence, Mortality, Diabetic ketoacidosis, Diabetes, Hypertension, Cardiac disorders, Dyslipidemia, Comorbidit

Breeding potential of the basmati rice germplasm under water stress condition

Eight parents were selected on the basis of phenotypic and genotypic screening for the development of F1. All the possible combinations were made between the parents excluding reciprocals in diallel mating design. Data were analyzed by using Hayman graphical approach and Griffing’s approach to study the genetics of the parents and their F1 hybrids. Based on the genetic component analysis, both additive and non-additive components appeared which is important in the inheritance of most of the traits. Both additive and dominance type of gene action were found important in inheritance for different traits under study. Most of the traits showed constant gene action in both environments, but the gene action of some traits was affected by the environment. Morphological traits like plant height, productive tillers per plant and 1000 seed weight showed over dominance type of gene action in both environments (control and drought environments), while seeds per panicle and seed length width ratio showed this type of gene action only in drought conditions. The seeds per panicle and length width ratio showed additive type of gene action with partial dominance only in normal irrigation conditions. From Griffing analysis, genotypes CB-17, CB-32 and Basmati-198 were found to be good general combiners for productive tillers per plant, primary branches per panicle and yield per plant, especially under water stress condition. Also, maximum specific combining ability was found in Basmati-198 × CB-17 for productive tillers per plant, Basmati-198 × CB-42 for primary branches per panicle and CB-32 × CB-14 for yield per plant.Key words: Oryza sativa L., gene action, combining ability, stress, yield traits

High Throughput Screening of a GlaxoSmithKline Protein Kinase Inhibitor Set Identifies an Inhibitor of Human Cytomegalovirus Replication that Prevents CREB and Histone H3 Post-Translational Modification.

To identify new compounds with anti-human cytomegalovirus (HCMV) activity and new anti-HCMV targets, we developed a high throughput strategy to screen a GlaxoSmithKline (GSK) Published Kinase Inhibitor Set (PKIS). This collection contains a range of extensively characterized compounds grouped into chemical families (chemotypes). From our screen we identified compounds within chemotypes that impede HCMV replication and identified kinase proteins associated with inhibition of HCMV replication that are potential novel anti-HCMV targets. We focused our study on a top "hit" in our screen, SB-734117, which we found inhibits productive replication of several HCMV strains. Kinase selectivity data indicated that SB-734117 exhibits polypharmacology and is an inhibitor of several proteins from the AGC and CMCG kinase groups. Using western blotting we found that SB-734711 inhibited accumulation of HCMV immediate-early proteins, phosphorylation of cellular proteins involved in immediate-early protein production (CREB and histone H3) and histone H3 lysine 36 trimethylation (H3K36me3). Therefore, we identify SB-734117 as a novel anti-HCMV compound and find that inhibition of AGC and CMCG kinase proteins during productive HCMV replication is associated with inhibition of viral protein production and prevents post-translational modification of cellular factors associated with viral protein production

MBE growth of cubic AlxIn1-xN and AlxGayIn1-x-yN lattice matched to GaN

Ternary and quaternary cubic c-AlxIn1-xN/GaN and c-AlxGayIn1-x-y/GaN heterostructures lattice-matched to c-GaN on freestanding 3C-SiC substrates were grown by plasma-assisted molecular beam epitaxy. The c-AlxGayIn1-x-y alloy permits the independent control of band gap and lattice parameter. The ternary and quaternary films were grown at 620 C. Different alloy compositions were obtained by varying the Al and Ga fluxes. The alloy composition was measured by Energy Dispersive X-ray Spectroscopy (EDX) and Rutherford Backscattering Spectrometry (RBS). X-ray reciprocal space map of asymmetric (-1-13) reflex were used to measure the lattice parameters and to verify the lattice match between the alloy and the c-GaN buffer.Comment: 4 pages including 4 figure

Sensitivity and Specificity of Cystatin C in Detecting Early Renal Impairment in Hypertensive Pregnancies

Purpose: To determine the cutoff point of cystatin C for the detection of renal impairment in hypertensive pregnancies.Methods: A cross-sectional study was conducted in an antenatal clinic and ward at Hospital Universiti Sains Malaysia, Kelantan, Malaysia from January 2009 until January 2010. Sixty four pregnant patients beginning at 2nd trimester, aged of 16 to 55 years and hypertensive, including gestational hypertension, chronic hypertension with superimposed preeclampsia, preeclampsia and unclassified hypertension, were included in the study. Consenting patients were required to provide 5 ml of blood and 24-h urine. Serum and reagent, N Latex cystatin C, were equilibrated at room temperature and measured by particle-enhanced nephelometric immunoassay (PENIA) using a BN II Dade Behring Nephelometer SystemResults: The mean age of the patients was 37.06 ±4.32 (range: 24 to 46 years). A majority (64.1 %) of the patients were in the second trimester of pregnancy and delivered in the gestational period of 38 - 40 weeks (54.7 %). The number of patients in chronic kidney disease (CKD) stages I, II, III, IV and V were 25 (39.1 %), 18 (28.1 %), 18 (28.1 %), 2 (3.1 %) and 1 (1.6 %), respectively. The mean systolic blood pressure was 149.59 ± 18.79 mm Hg, and diastolic blood pressure 91.53 ± 10.33 mm Hg. The cutoff point in detecting renal impairment using cystatin C was > 0.74 with 84.6 % sensitivity and 86.7 % specificity for second trimester and > 0.81 with sensitivity of 76.9 % and specificity of 60.0 % in detecting renal impairment for third trimester.Conclusion: The cutoff point in detecting renal impairment for second trimester is better than for third trimester since it maximizes the value of sensitivity and specificity.Keywords: Cystatin C, Sensitivity, Specificity, Renal impairment, Hypertension; Pregnanc

Historical and future trends in emergency pituitary referrals: a machine learning analysis

Purpose: Acute pituitary referrals to neurosurgical services frequently necessitate emergency care. Yet, a detailed characterisation of pituitary emergency referral patterns, including how they may change prospectively is lacking. This study aims to evaluate historical and current pituitary referral patterns and utilise state-of-the-art machine learning tools to predict future service use. Methods: A data-driven analysis was performed using all available electronic neurosurgical referrals (2014–2021) to the busiest U.K. pituitary centre. Pituitary referrals were characterised and volumes were predicted using an auto-regressive moving average model with a preceding seasonal and trend decomposition using Loess step (STL-ARIMA), compared against a Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) algorithm, Prophet and two standard baseline forecasting models. Median absolute, and median percentage error scoring metrics with cross-validation were employed to evaluate algorithm performance. Results: 462 of 36,224 emergency referrals were included (referring centres = 48; mean patient age = 56.7 years, female:male = 0.49:0.51). Emergency medicine and endocrinology accounted for the majority of referrals (67%). The most common presentations were headache (47%) and visual field deficits (32%). Lesions mainly comprised tumours or haemorrhage (85%) and involved the pituitary gland or fossa (70%). The STL-ARIMA pipeline outperformed CNN-LSTM, Prophet and baseline algorithms across scoring metrics, with standard accuracy being achieved for yearly predictions. Referral volumes significantly increased from the start of data collection with future projected increases (p < 0.001) and did not significantly reduce during the COVID-19 pandemic. Conclusion: This work is the first to employ large-scale data and machine learning to describe and predict acute pituitary referral volumes, estimate future service demands, explore the impact of system stressors (e.g. COVID pandemic), and highlight areas for service improvement

Analysis of Restrained Composite Perforated Beams during Fire Using a Hybrid Simulation Approach

This paper is concerned with the behavior of restrained perforated beams acting compositely with a profiled slab during a fire. These members are increasingly popular in the construction of long-span floor systems because they provide a structurally and materially efficient design solution and provide space for placement of building services. However, their response during a fire has received little attention from the research community until recently. In the current work, a hybrid simulation-type numerical approach is adopted using a combination of the OpenSEES, ABAQUS, and OpenFresco software. The accuracy of the model is validated using available fire test data whereby the temperatures measured during the experiments are directly applied in the numerical model at various locations. The effect of axial and rotational restraint due to the connections between the beams and columns is also investigated following validation of the model. Furthermore, the hybrid simulation approach is employed to study a number of salient parameters, including load ratios, material grade, and the location of the openings. The variation in axial force during the fire is also examined. Various failure modes were observed during the analysis, including flexural and shear failure, failure of the web-post, concrete crushing, and also a Vierendeel mechanism. The fire resistance of the analyzed beams is compared with the values obtained from the most common design codes. Because of the consideration of restraint forces, which are not included in the design codes, the resistances predicted by the finite-element simulations were more favorable. It was found that the location of the openings along the span and also the boundary conditions had a considerable effect on the time-displacement behavior, axial reactions, and web-post buckling behavior, as well as the fire performance of the perforated beam

Health Impacts Model

This report presents the draft outline of the CORFU Health Impacts Model. The model consists of assessing the risk to human health in four steps: Hazard identification Hazard characterisation (or dose-response assessment) Exposure assessment Risk characterisation The health impacts model has four components. The first of these is the risk to human life component, and adapts a model developed in the FLOODsite project to estimate the number of deaths and injuries that could be caused by flooding. The next component relates to waterborne diseases and illnesses that can be assessed by means of a Quantitative Microbial Risk Assessment. Thirdly, the model takes account of other diseases (such as those transmitted by vectors) and suggests the use of relative risk information to estimate the impact of this disease. A similar approach is suggested to consider the mental health impacts of flooding. Finally, the report describes how the health risks could be characterised using the Disability Adjusted Life Year (DALY).The work described in this publication was supported by the European Community’s Seventh Framework Programme through the grant to the budget of CORFU Collaborative Research on Flood Resilience in Urban Areas, Contract 244047