Evaluating spring wheat cultivars for drought tolerance through yield and physiological parameters at booting and anthesis

Progress in wheat yields under drought conditions is rather a difficult task to achieve. The experiment was conducted in factorial design with 16 spring wheat cultivars grown under two irrigation regimes, non-stress and water-stress imposed at boot and anthesis growth stages. Water-stress significantly influenced the physiological and yield traits in both the growth stages, yet the reductions in most traits were pronounced at anthesis than at boot. Stomatal conductance, relative water content, leaf area (LA), seeds/spike, 1000-grain weight and grain yield/plant were the best drought tolerant indicators. On the basis of physiological and yield traits, the cultivars Moomal, Bhitai, TD-1, and Abadgar proved to be the best performing in water-stress conditions. Stomatal conductance, RWC% and LA were significantly and positively correlated with grain yield/plant. These results suggest that the stomatal conductance, relative water content and leaf area are the most important traits that should be considered while developing drought tolerant wheat genotypes.Keywords: Water stress, boot and anthesis, yield and physiological traits, wheat genotype

Evaluation of different strategies for induction of chilling tolerance in spring maize using moringa leaf extracts

Spring maize is highly sensitive to low temperatures during the early development of seedlings and to high temperatures during its reproductive stage. Different strategies are being used to minimize the adverse effects of temperature extremes. Therefore, a field experiment was conducted to enhance the performance of spring hybrid maize by seed priming (3% MLE) and transplanting 20 and 30-day-old seedlings. Seed priming with moringa leaf extract (MLE) significantly enhanced stand establishment in both direct sowing and in transplanting, as indicated by the higher emergence percentage, emergence index, and lower time taken to start of emergence and mean emergence time. Minimum days from sowing to tasseling and silking were found in MLE primed 20-day-old seedlings grown in a nursery. However, all the agronomic parameters increased considerably with MLE priming of 20-day-old seedlings. Thus, MLE priming reduced chilling damage by improving stand establishment, whereas transplanting 20-day-old seedlings further enhanced the agronomic traits, yield, and quality of maize. However, the performance of maize plants from 30-day-old transplanted seedling and direct sowing was substandard

Evaluating the potential effect of seed priming techniques in improving germination and root shoot length of maize seed

The present research was conducted under laboratory conditions. The purpose of research was to investigate the potential of priming with press mud, peat moss, sand, gunny bags, compost, farm yard manure and moringa leaf extract (MLE) on seedling growth and germination capacity of maize seed. Untreated or non-primed seeds were used as a control treatment. Priming treatments improved germination capacity, stand establishment and seedling vigor, compared with control. Priming with moringa leaf extract enhance germination and seedling vigor of maize seed, compared with the control and other seed primed treatments. In moringa leaf extract primed seeds, root and shoot growth was improved. Overall, moringa leaf extract primed maize seeds performed better than all other treatments and it could be related by seedling vigor enhancement and lowering the mean germination time, due to imbibition of higher quantity of water and earlier enzymatic activity. The results propose that moringa leaf extract priming treatment had the potential to enhance germination, stand establishment and early growth of maize seeds

CrowdHEALTH: Holistic Health Records and Big Data Analytics for Health Policy Making and Personalized Health.

Today's rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. The aim of the presented approach, namely CrowdHEALTH, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs are transformed into HHRs clusters capturing the clinical, social and human context of population segments and as a result collective knowledge for different factors. The proposed approach also seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders, as well as to policy makers towards a "health in all policies" approach. Cross-domain co-creation of policies is feasible through a rich toolkit, being provided on top of the DaaS, incorporating mechanisms for causal and risk analysis, and for the compilation of predictions

The CrowdHEALTH project and the Hollistic Health Records: Collective Wisdom Driving Public Health Policies.

Introduction: With the expansion of available Information and Communication Technology (ICT) services, a plethora of data sources provide structured and unstructured data used to detect certain health conditions or indicators of disease. Data is spread across various settings, stored and managed in different systems. Due to the lack of technology interoperability and the large amounts of health-related data, data exploitation has not reached its full potential yet. Aim: The aim of the CrowdHEALTH approach, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants defining health status by using big data management mechanisms. Methods: HHRs are transformed into HHRs clusters capturing the clinical, social and human context with the aim to benefit from the collective knowledge. The presented approach integrates big data technologies, providing Data as a Service (DaaS) to healthcare professionals and policy makers towards a "health in all policies" approach. A toolkit, on top of the DaaS, providing mechanisms for causal and risk analysis, and for the compilation of predictions is developed. Results: CrowdHEALTH platform is based on three main pillars: Data & structures, Health analytics, and Policies. Conclusions: A holistic approach for capturing all health determinants in the proposed HHRs, while creating clusters of them to exploit collective knowledge with the aim of the provision of insight for different population segments according to different factors (e.g. location, occupation, medication status, emerging risks, etc) was presented. The aforementioned approach is under evaluation through different scenarios with heterogeneous data from multiple sources

Detection of autoantibodies against reactive oxygen species modified glutamic acid decarboxylase-65 in type 1 diabetes associated complications

<p>Abstract</p> <p>Background</p> <p>Autoantibodies against glutamate decarboxylase-65 (GAD₆₅Abs) are thought to be a major immunological tool involved in pathogenic autoimmunity development in various diseases. GAD₆₅Abs are a sensitive and specific marker for type 1 diabetes (T1D). These autoantibodies can also be found in 6-10% of patients classified with type 2 diabetes (T2D), as well as in 1-2% of the healthy population. The latter individuals are at low risk of developing T1D because the prevalence rate of GAD₆₅Abs is only about 0.3%. It has, therefore, been suggested that the antibody binding to GAD₆₅in these three different GAD₆₅Ab-positive phenotypes differ with respect to epitope specificity. The specificity of reactive oxygen species modified GAD₆₅(ROS-GAD₆₅) is already well established in the T1D. However, its association in secondary complications of T1D has not yet been ascertained. Hence this study focuses on identification of autoantibodies against ROS-GAD₆₅(ROS-GAD₆₅Abs) and quantitative assays in T1D associated complications.</p> <p>Results</p> <p>From the cohort of samples, serum autoantibodies from T1D retinopathic and nephropathic patients showed high recognition of ROS-GAD₆₅as compared to native GAD₆₅(N-GAD₆₅). Uncomplicated T1D subjects also exhibited reactivity towards ROS-GAD₆₅. However, this was found to be less as compared to the binding recorded from complicated subjects. These results were further proven by competitive ELISA estimations. The apparent association constants (AAC) indicate greater affinity of IgG from retinopathic T1D patients (1.90 × 10^-6M) followed by nephropathic (1.81 × 10^-6M) and uncomplicated (3.11 × 10^-7M) T1D patients for ROS-GAD₆₅compared to N-GAD₆₅.</p> <p>Conclusion</p> <p>Increased oxidative stress and blood glucose levels with extended duration of disease in complicated T1D could be responsible for the gradual formation and/or exposing cryptic epitopes on GAD₆₅that induce increased production of ROS-GAD₆₅Abs. Hence regulation of ROS-GAD₆₅Abs could offer novel tools for analysing and possibly treating T1D complications.</p

Benchmarking LHC background particle simulation with the CMS triple-GEM detector

In 2018, a system of large-size triple-GEM demonstrator chambers was installed in the CMS experiment at CERN\u27s Large Hadron Collider (LHC). The demonstrator\u27s design mimicks that of the final detector, installed for Run-3. A successful Monte Carlo (MC) simulation of the collision-induced background hit rate in this system in proton-proton collisions at 13 TeV is presented. The MC predictions are compared to CMS measurements recorded at an instantaneous luminosity of 1.5 ×10$^{34}$ cm$^{-2}$ s$^{-1}$. The simulation framework uses a combination of the FLUKA and GEANT4 packages. FLUKA simulates the radiation environment around the GE1/1 chambers. The particle flux by FLUKA covers energy spectra ranging from 10$^{-11}$ to 10$^{4}$ MeV for neutrons, 10$^{-3}$ to 10$^{4}$ MeV for γ\u27s, 10$^{-2}$ to 10$^{4}$ MeV for e$^{±}$, and 10$^{-1}$ to 10$^{4}$ MeV for charged hadrons. GEANT4 provides an estimate of the detector response (sensitivity) based on an accurate description of the detector geometry, the material composition, and the interaction of particles with the detector layers. The detector hit rate, as obtained from the simulation using FLUKA and GEANT4, is estimated as a function of the perpendicular distance from the beam line and agrees with data within the assigned uncertainties in the range 13.7-14.5%. This simulation framework can be used to obtain a reliable estimate of the background rates expected at the High Luminosity LHC

Triple-GEM discharge probability studies at CHARM: Simulations and experimental results

The CMS muon system in the region with 2.03<|η|<2.82 is characterized by a very harsh radiation environment which can generate hit rates up to 144 kHz/cm$^{2}$ and an integrated charge of 8 C/cm$^{2}$ over ten years of operation. In order to increase the detector performance and acceptance for physics events including muons, a new muon station (ME0) has been proposed for installation in that region. The technology proposed is Triple—Gas Electron Multiplier (Triple-GEM), which has already been qualified for the operation in the CMS muon system. However, an additional set of studies focused on the discharge probability is necessary for the ME0 station, because of the large radiation environment mentioned above. A test was carried out in 2017 at the Cern High energy AcceleRator Mixed (CHARM) facility, with the aim of giving an estimation of the discharge probability of Triple-GEM detectors in a very intense radiation field environment, similar to the one of the CMS muon system. A dedicated standalone Geant4 simulation was performed simultaneously, to evaluate the behavior expected in the detector exposed to the CHARM field. The geometry of the detector has been carefully reproduced, as well as the background field present in the facility. This paper presents the results obtained from the Geant4 simulation, in terms of sensitivity of the detector to the CHARM environment, together with the analysis of the energy deposited in the gaps and of the processes developed inside the detector. The discharge probability test performed at CHARM will be presented, with a complete discussion of the results obtained, which turn out to be consistent with measurements performed by other groups

Impact of magnetic field on the stability of the CMS GE1/1 GEM detector operation

The Gas Electron Multiplier (GEM) detectors of the GE1/1 station of the CMS experiment have been operated in the CMS magnetic field for the first time on the 7$^{th}$ of October 2021. During the magnetic field ramps, several discharge phenomena were observed, leading to instability in the GEM High Voltage (HV) power system. In order to reproduce the behavior, it was decided to conduct a dedicated test at the CERN North Area with the Goliath magnet, using four GE1/1 spare chambers. The test consisted in studying the characteristics of discharge events that occurred in different detector configurations and external conditions. Multiple magnetic field ramps were performed in sequence: patterns in the evolution of the discharge rates were observed with these data. The goal of this test is the understanding of the experimental conditions inducing discharges and short circuits in a GEM foil. The results of this test lead to the development of procedure for the optimal operation and performance of GEM detectors in the CMS experiment during the magnet ramps. Another important result is the estimation of the probability of short circuit generation, at 68 % confidence level, p$_{short}$$^{HV}$ $^{OFF}$ = 0.42$^{-0.35+0.94}$% with detector HV OFF and p$_{short}$$^{HV}$ $^{OFF}$ < 0.49% with the HV ON. These numbers are specific for the detectors used during this test, but they provide a first quantitative indication on the phenomenon, and a point of comparison for future studies adopting the same procedure

Modeling the triple-GEM detector response to background particles for the CMS Experiment

An estimate of environmental background hit rate on triple-GEM chambers is performed using Monte Carlo (MC) simulation and compared to data taken by test chambers installed in the CMS experiment (GE1/1) during Run-2 at the Large Hadron Collider (LHC). The hit rate is measured using data collected with proton-proton collisions at 13 TeV and a luminosity of 1.5$\times10^{34}$ cm$^{-2}$ s$^{-1}$. The simulation framework uses a combination of the FLUKA and Geant4 packages to obtain the hit rate. FLUKA provides the radiation environment around the GE1/1 chambers, which is comprised of the particle flux with momentum direction and energy spectra ranging from $10^{-11}$ to $10^{4}$ MeV for neutrons, $10^{-3}$ to $10^{4}$ MeV for $\gamma$'s, $10^{-2}$ to $10^{4}$ MeV for $e^{\pm}$, and $10^{-1}$ to $10^{4}$ MeV for charged hadrons. Geant4 provides an estimate of detector response (sensitivity) based on an accurate description of detector geometry, material composition and interaction of particles with the various detector layers. The MC simulated hit rate is estimated as a function of the perpendicular distance from the beam line and agrees with data within the assigned uncertainties of 10-14.5%. This simulation framework can be used to obtain a reliable estimate of background rates expected at the High Luminosity LHC.Comment: 16 pages, 9 figures, 6 table