The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII): First Flight

The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII) is an 8-meter far-infrared (30-100 m) double-Fourier Michelson interferometer designed to fly on a high altitude scientific balloon. The project began in 2011, and the payload was declared ready for flight in September 2016. Due to bad weather, the first flight was postponed until June 2017; BETTII was successfully launched on June 8, 2017 for an engineering flight. Over the course of the one night flight, BETTII acquired a large amount of technical data that we are using to characterize the payload. Unfortunately, the flight ended with an anomaly that resulted in destruction of the payload. In this paper, we will discuss the path to BETTII flight, the results of the first flight, and some of the plans for the future

The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII): towards the first flight

The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII) is a balloon-borne, far-infrared direct detection interferometer with a baseline of 8 m and two collectors of 50 cm. It is designed to study galactic clustered star formation by providing spatially-resolved spectroscopy of nearby star clusters. It is being assembled and tested at NASA Goddard Space Flight Center for a first flight in Fall 2016. We report on recent progress concerning the pointing control system and discuss the overall status of the project as it gets ready forits commissioning flight

RADIOLOGICAL AND PATHOLOGICAL EVALUATION OF TRICHILEMMAL CYSTS OF THE SCALP

BACKGROUND Trichilemmal cysts or pilar tumours are slow growing scalp lesion commonly found in elderly women. These slow growing lesions may cause morbidity and even mortality. Recurrence of the lesions after local excision is common. These trichilemmal cyst usually indolent with benign nature or may transform to proliferating trichilemmal cyst or Proliferating Pilar Tumour (PPT) or may show malignant transformation. The aim of the study is to study the radiological and pathological evaluation of trichilemmal cysts of scalp. MATERIALS AND METHODS A hospital-based cross-sectional retrospective study was conducted. The study group comprised of 20 patients presenting to the Departments of Radiodiagnosis, Radiotherapy, General Surgery, Plastic Surgery and Dermatology in a tertiary care hospital from July 2015 to August 2017. All patients were initially evaluated clinically followed by cross-sectional imaging modality like Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). RESULTS In 20 patients, a total of 51 trichilemmal cysts were evaluated where 46 (90.2%) were benign trichilemmal cysts and 5 (9.8%) showed malignant transformation. The mean age of presentation was 47.9 yrs. ± 1.5 (SD) with male:female ratio of 1:3.The mean duration of presence of trichilemmal cyst was 5.9 yrs. ± 3.2 (SD). Out of 5 malignant trichilemmal cysts 3 patients (15%) showed bony calvarial erosion and 2 patients (10%) showed intracranial extensions. Statistical significance with ‘p’ value of 0.003 was noted between the size of largest dimension of trichilemmal cyst and their histopathology without any statistical significance between duration of swelling and their histopathology. CONCLUSION Even though, the trichilemmal cysts of scalp are denoted as benign lesion, as they usually shows recurrence and its affinity to become locally aggressive and turn into malignancy is there. Hence, clinical, radiological and pathological correlation isnecessary to decreased morbidity or even mortality from these scalp lesions

Multi-reward reinforcement learning based development of inter-atomic potential models for silica

Abstract Silica is an abundant and technologically attractive material. Due to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics, the development of accurate models to predict the structure, energetics and properties of silica polymorphs remain challenging. Current models for silica range from computationally efficient Buckingham formalisms (BKS, CHIK, Soules) to reactive (ReaxFF) and more recent machine-learned potentials that are flexible but computationally costly. Here, we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning (RL) using an experimental training dataset. Our model concurrently captures the structure, energetics, density, equation of state, and elastic constants of quartz (equilibrium) as well as 20 other metastable silica polymorphs. We also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous properties. We demonstrate ways to improve model flexibility and introduce a flexible formalism, machine-learned ML-BKS, that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential (GAP) in capturing the experimental structure and properties of silica polymorphs and amorphous silica