"Enhancing Perinatal Outcomes In Gestational Diabetes Mellitus: A Midwifery Facilitator Based Approach"

Introduction: Gestational diabetes mellitus, or GDM, is a metabolic disorder that affects both expectant mothers and their developing fetuses. It increases the chance of several pregnancy and delivery complications. Babies born to women with gestational diabetes mellitus (GDM) are at risk for perinatal death, fetal macrosomia, low blood sugar, birth trauma, and congenital malformations. This paper explores the possibility of enhancing perinatal outcomes in GDM by applying a midwifery facilitator-based approach. Objectives: This study's primary objective is to assess the impact of a midwife facilitator-based approach on the management of gestational diabetes mellitus (GDM) and its associated complications in expectant mothers and their babies. Our objective is to create a midwifery facilitator approach model that provides recommendations for clinical practice. Methods: A prospective cohort study involving 111 mothers compared standard care with care led by midwives. The intervention group was chosen based on their preferences, and they received full support, which included education, lifestyle modifications, and assistance for mothers. A certified diabetes educator led the classes, which covered a variety of subjects like multiple pregnancies, chronic illnesses, and absences. Group 1 comprised 62 mothers who attended classes and follow-ups, while 49 mothers in Group 2 did not attend any of them. Consistency and low turnover were assured. Results: The Midwifery Facilitator-Based Approach, which considers psychological, emotional, and physical factors, fully manages GDM. Strict diabetes management, nutritional counseling, promoting a healthy diet, and aiding in stress reduction are all made possible by these midwives. They empower mothers with GDM to take care of themselves and allow informed decision-making, potentially improving perinatal outcomes and the general well-being of GDM-affected families. Conclusion: A promising strategy for improving perinatal outcomes in GDM is the facilitator-based approach used by midwives. It offers a treatment plan that is holistic in nature, taking into account the relationships between various aspects of health. By integrating midwifery into GDM management, we can enhance mothers' empowerment and comprehension, which will ultimately benefit moms and their infants

Evaluation of CERES-Wheat and CropSyst models for water-nitrogen interactions in wheat crop

Crop simulation models can provide an alternative, less time-consuming and inexpensive means of determining the optimum crop N and irrigation requirements under varied soil and climatic conditions. In this context, two dynamic mechanistic models (CERES (Crop Environment REsource Synthesis)-Wheat and CropSyst (Cropping Systems Simulation Model)) were validated for predicting growth and yield of wheat (Triticum aestivum L) under different nitrogen and water management conditions. Their potential as N and water management tool was evaluated for New Delhi representing semi-arid irrigated ecosystems in the Indo-Gangetic Plains. The field experiment was carried out on a silty clay loam soil at the Research Farm of the Indian Agricultural Research Institute, New Delhi, India during 2000-2001 to collect the input data for the calibration and validation of both the models on wheat crop (variety HD 2687). The models were evaluated for three water regimes [I4 (4 irrigations within the growing season), I3 (3 irrigations within the growing season) and I2 (2 irrigations within the growing season)] and five N treatments (N0, N60, N90, N120 and N150). Both the models were calibrated using data obtained from the treatments receiving maximum nitrogen and irrigations, i.e., N150 and I4 treatments. The models were then validated against other water and nitrogen treatments. For performance evaluation, in addition to coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and Wilmot's index of agreement (IoA) were estimated. Both CERES-Wheat and CropSyst provided very satisfactory estimates for the emergence, flowering and physiological maturity dates. For CERES-Wheat overall prediction (pooled result of the three water regimes) of grain yield was satisfactory with significant R2 values (0.88). The model, however, under estimated the biomass under all water regimes and N levels except for N0 level, under which biomass was overpredicted. CropSyst predicted yield and biomass of wheat more closely than CERES-Wheat. The combined RMSE for the three water regimes between predicted and observed grain yield was 0.36 mg ha-1 for CropSyst as compared to 0.63 mg ha-1 for CERES-Wheat. Similarly, RMSE between observed and predicted biomass by CropSyst was 1.27 mg ha-1 as compared to 1.94 mg ha-1 between observed and predicted biomass by CERES-Wheat. Wilmot's index of agreement (IoA) also indicated that CropSyst model is more appropriate than CERES-Wheat in predicting growth and yield of wheat under different N and irrigation application situations in this study.

Monitoring cotton crop condition through synergy of optical and radar remote sensing

Synergistic use of Optical and Microwave remotely sensed data for cotton condition based on biophysical traits, indices from ground measurements and satellite derived reflectance were assessed. Regression models derived for estimating LAI, biomass and VWC using ground based indices were applied to satellite products. LAI, biomass and VWC of cotton with optical VIs as input (R2= 0.42, 0.51 and 0.52) respectively were estimated. Correlation between RVI and plant height, crop age and VWC were found between 0.4 and 0.6. Fresh biomass from RVI ranged 100 –4000 gm−2, dry biomass from NDVI ranged 50–950 gm−2 and VWC 65–85%. Correlation between VIs and RVI was found to be non- significant. A multiple linear regression model using NDVI vs. LSWI and RVI were developed to assess LAI, biomass and VWC. The model predicted LAI with R2 of 0.5 but failed to estimate biomass and VWC

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Not AvailableA field experiment was conducted in 2015 to study the land surface energy fluxes from tropical lowland rice paddy in eastern India with an objective to determine the mass, momentum, and energy exchange rates between rice paddies and the atmosphere. All the land surface energy fluxesweremeasured by eddy covariance (EC) system(make Campbell Scientific) in dry season (DS, 1–125 Julian days), dry fallow (DF, 126–181 Julian days), wet season (WS, 182–324 Julian days), and wet fallow (WF, 325–365 Julian days). The rice was cultivated in dry season (January–May) and wet season (July–November) in low wet lands and the ground is kept fallow during the remainder of the year. Results showed that albedo varied from 0.09 to 0.24 and showed positive value from morning 6:00 h until evening 18:00 h. Mean soil temperature (Tg) was highest in DF, while the skin temperature (Ts) was highest in WS. Average Bowen ratio (B) ranged from 0.21 to 0.64 and large variation in B was observed during the fallow periods as compared to the cropping seasons. The magnitude of aerodynamic, canopy, and climatological resistances increased with the progress of cropping season and their magnitudes decreased during the end of both cropping seasons and found minimum during the fallow periods. At a constant vapor pressure deficit (VPD) at 0.16, 0.18, 0.15, and 0.43 kPa, latent heat flux (LE) initially increased, but later it tended to level off with an increase in VPD. The actual evapotranspiration (ETa) during both the cropping seasons was higher than the fallow period. This study can be used as a source of default values for many land surface energy fluxes which are required in various meteorological or air-quality models for rice paddies. A larger imbalance of energy was observed during the wet season as the energy is stored and perhaps advected in the fresh water.Not Availabl