Method Development and Validation for Simultaneous Estimation of Benidipine Hydrochloride and Metoprolol Succinate in Tablet

Present work focusing in developing and validating a new high performance liquid chromatography method for estimation of Metoprolol Succinate and Benidipine Hydrochloride in their combine tablet dosage form. The method was performed on Shimadzu LC-20AT instrument using C18 (250 mm x 4.6 mm, 5 µm) Hypersil BDS Column and Potassium Dihydrogen Phosphate Buffer (pH 4.0): Methanol (65: 35% v/v) as mobile phase at ambient temperature. Detection was carried out at 269 nm. Concentration range 4-12 µg/ml for Benidipine Hydrochloride and 25-75 µg/ml for Metoprolol Succinate . The Percentage recovery of Benidipine Hydrochloride and Metoprrolol succinate was found to be 99.59% and 99.39 respectively. Correlation coefficient for Metoprolol succinate and Benidipine Hydrochloride was found 0.9995 and 0.9997 respectively. The Rt values for Metoprolol succinate and Benidipine Hydrochloride were found to be 3.4 and 5.9 min respectively. The method was validated according to the guidelines of International Conference on Harmonisation (ICH) and was successfully employed in the estimation of commercial formulations. Keywords:  Metoprolol Succinate, Benidipine Hydrochoride, HPLC, Mobile Phase

GrASPE: Graph based Multimodal Fusion for Robot Navigation in Unstructured Outdoor Environments

We present a novel trajectory traversability estimation and planning algorithm for robot navigation in complex outdoor environments. We incorporate multimodal sensory inputs from an RGB camera, 3D LiDAR, and robot's odometry sensor to train a prediction model to estimate candidate trajectories' success probabilities based on partially reliable multi-modal sensor observations. We encode high-dimensional multi-modal sensory inputs to low-dimensional feature vectors using encoder networks and represent them as a connected graph to train an attention-based Graph Neural Network (GNN) model to predict trajectory success probabilities. We further analyze the image and point cloud data separately to quantify sensor reliability to augment the weights of the feature graph representation used in our GNN. During runtime, our model utilizes multi-sensor inputs to predict the success probabilities of the trajectories generated by a local planner to avoid potential collisions and failures. Our algorithm demonstrates robust predictions when one or more sensor modalities are unreliable or unavailable in complex outdoor environments. We evaluate our algorithm's navigation performance using a Spot robot in real-world outdoor environments

UHF Ground Station for Satellite Communications: The Design, Build, Test, and Lessons Learned

The Olin Satellite + Spectrum Technology and Policy (OSSTP) Group was founded at Olin College of Engineering to explore real-world, project-based learning with apprenticeship-styled educational experiences in satellite communications. In 2019, OSSTP was awarded the National Science Foundation (NSF) Cubesat Ideas Lab Grant for the Space Weather Atmospheric Reconfigurable Multiscale Experiment (SWARM-EX) mission in collaboration with five other institutions (CU Boulder, Georgia Tech, Stanford, Western Michigan, and University of Southern Alabama) to develop and launch three CubeSats. This mission aims to serve as a pathfinder demonstration of swarm operations at separation distances of 1-1000 km using differential drag and onboard propulsion. SWARM-Ex will also showcase key technologies and address scientific questions related to the evolution of equatorial ionization (EIA) and equatorial thermospheric anomaly (ETA by including a FIPEX neutral Oxygen sensor and a Langmuir Probe1. As part of the SWARM-Ex project, a team of Olin undergraduates, along with Prof. Lohmeyer, have designed, built, and tested an Ultra High Frequency (UHF) Ground Station to support small satellite telemetry and command operations between 435 - 470 MHz. This station will first serve as an integral component of the SWARM-Ex communications network, enabling students to assist with downlinking science data for the mission and uplinking control sequences. The station will support small satellite missions of different universities and interference research in the future. This paper documents the overall design, including a breakdown of the transmit and receive chains and the tracking mechanisms, interfaces, testing, and lessons learned. The goal of this paper is to document the build of the Olin ground station to aid in the buildout of other university ground stations

High prevalence of alpha thalassemia in the tribal community of the western part of India! Reality or myth? Can simple hematology parameters; MCV and MCH act as screening tools at birth?

Background: The majority of adult tribal subjects in the western part of India, show microcytic hypochromic red cells, and borderline anemia with a normal iron profile, suggesting a high prevalence of thalassemia in this population. Methods: The current study was designed to perform qualitative (to screen for Hb Bart’s) and quantitative (to estimate percentage of Hb Bart’s) hemoglobin electrophoresis with modification of the method, to evaluate the prevalence of α thalassemia and to determine gene frequency of α+ thal gene. Furthermore, the present study also aimed to evaluate common hematology parameters like MCV and MCH as screening tools to suspect α thalassemia at birth. Results: Based on hemoglobin electrophoresis, the prevalence of α thalassemia in all its forms was found to be 66.66%. The estimated gene frequency for α+ thal was found to be 0.7453 and based on that, the extrapolated prevalence of α thalassemia was 93.52% (55.55% homozygous and 37.97% heterozygous). MCV<100 fl and MCH<31 pg were found to be reliable screening tools to predict α thalassemia at birth in full-term uncomplicated pregnancy. Conclusions: Tribal community in the western part of India bears a very high prevalence of α thalassemia, it’s a reality and not a myth. Simple hematological parameters like MCV (<100 fl) and MCH (<31 pg) measured at birth can prove to be cost-effective surrogate markers for α thalassemia. Large scale study using confirmatory genetic analysis is required to validate the findings.

Effect of percutaneous balloon mitral valvuloplasty on left ventricular function in rheumatic mitral stenosis

Objective: Patients with rheumatic mitral stenosis, despite having normal left ventricular ejection fraction (LV EF), have ventricular dysfunction in the form of impaired longitudinal excursion. Tissue Doppler velocity is a useful indicator for assessment of long-axis ventricular shortening and lengthening. The aim of our study was to evaluate the effect of percutaneous balloon mitral valvuloplasty (PBMV) on LV function in rheumatic MS and to study echocardiographic parameters with M-Mode and Tissue Doppler Imaging pre PBMV, post PBMV and on follow-up to determine predictors of LV function. Methods: We analysed 52 patients with severe mitral stenosis with normal LV EF, who underwent PBMV at our institute. Baseline parameters of LV function were compared with immediate post PBMV and at three months follow up. Results: The mean age of the patients was 33.73 (10.87) years with female preponderance. The mean mitral valve area before PBMV was 0.92 (0.13) cm2 which increased to 1.65 (0.21) cm2 after PBMV and at 3 month it was 1.61 (0.23) cm2 (p0.05). Mitral valve E’ was 8.71 (1.54) cm/s which increased to 10.13 (1.68) cm/s post PBMV and at 3 month it was 10.83 (1.34) cm/s (p<0.001).. Mitral annular systolic velocity (MASV), before PBMV was 7.90 (0.96) cm/s which increased to 9.31 (1.68) cm/s after PBMV and at 3 month it was 10.13 (0.96) cm/s (p<0.001). Myocardial performance index (MPI) before PBMV was 0.54 (0.48) which decreased post PBMV to 0.47 (0.06) and at 3 month it was 0.38 (0.04) (p=0.01). Pre PBMV MPI value <0.48 predicted improvement in LV function (sensitivity: 81%, specificity: 58.1%). Conclusion: Thus, PBMV leads to improvement in LV function in patients with severe MS with normal LV EF

Amalgame: Cosmological Constraints from the First Combined Photometric Supernova Sample

Future constraints of cosmological parameters from Type Ia supernovae (SNe Ia) will depend on the use of photometric samples, those samples without spectroscopic measurements of the SNe Ia. There is a growing number of analyses that show that photometric samples can be utilised for precision cosmological studies with minimal systematic uncertainties. To investigate this claim, we perform the first analysis that combines two separate photometric samples, SDSS and Pan-STARRS, without including a low-redshift anchor. We evaluate the consistency of the cosmological parameters from these two samples and find they are consistent with each other to under $1\sigma$. From the combined sample, named Amalgame, we measure $\Omega_M = 0.328 \pm 0.024$ with SN alone in a flat $\Lambda$CDM model, and $\Omega_M = 0.330 \pm 0.018$ and $w = -1.016^{+0.055}_{-0.058}$ when combining with a Planck data prior and a flat $w$CDM model. These results are consistent with constraints from the Pantheon+ analysis of only spectroscopically confirmed SNe Ia, and show that there are no significant impediments to analyses of purely photometric samples of SNe Ia.Comment: Submitting to MNRAS; comments welcom