13 research outputs found
Analysis of issues and trends in the growth of fuel cell firms
Thesis (S.M.M.O.T.)--Massachusetts Institute of Technology, Sloan School of Management, Management of Technology Program, 2003.Includes bibliographical references (leaves 49-50).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Recent scientific progress has shown significant signs that fuel cells will become a tremendous and significant part of distributed energy markets in the future. Fuel Cell technology though first discovered in late 1830s by Sir William Grove, a Welsh judge and scientist only took off when NASA first introduced them in the Gemini space program in 1960s. Technology evolution and the need for a clean energy source for the space program caused the renewed interest in Fuel Cells. A significant amount of progress and numerous investments have been made securing a future for Fuel Cells. The question that remains is not if Fuel Cells will develop into an industry, but when might it evolve and deliver on the promises so intrepidly set forth by researchers, corporations, and investors. The question has been debated many times over in the popular press. For certain, no one is exactly sure what 'when' really means. What this thesis is more interested in is the "how". How will Fuel Cells technology and markets evolve? What factors will determine the industry structure that will influence the development of this industry? How large can we expect this industry to grow? What will be the key drivers for growth? How will different members of this industry facilitate the development of this technology? What form will the industry take? What are some of the current challenges facing the fuel cell manufacturing companies in their growth? This Thesis investigates the formation and growth of Fuel Cell firms in Massachusetts, New York and Connecticut (within 150 miles of Boston) and the current issues facing the upper Management / Founders of these companies. By studying the key factors and developments in these industries different lessons and patterns can be extrapolated which may help answer some of the burning questions surrounding fuel cell industry evolution and where they are on the technology S curve. The basic framework used in this study is taken from the paper written by Gransey to analyze High-tech firms' growth. Eight firms were interviewed using a questionnaire format developed earlier by Prof Elicia Maine to study the materials industry growth. The results of this analysis do indeed conclude that the firms felt that fuel cell is a great product, but it has limitations. It is impossible at this point to beat the grid in cost or reliability with a single piece of equipment- the grid has multiple redundant generating devices and is virtually free. The value of a fuel cell is the ability to have much higher power quality at your location to increase your grid reliability an additional 9 times. It is currently expensive to do this, but no other technology has this capability. Several companies have been formed with lot of optimism and potential for a huge payoff. People are less likely to share ideas in this industry compared to other industries. Secrecy is the norm in this industry and they rely on the patent protection early on and seem to have lot of interactions with the local lawyers for IP filing and protection. Most of the firms did not participate in local industry organizations for the fear of exposing their perceived advantage. Currently fuel cell firms are facing economic challenges due to the downturn in the economy which in turn resulted in the slow down in fuel cell technology research investments. Also as the company grows they are realizing that the market risk is higher than what they have anticipated when they started. This may have an interesting consequence related to the sales and marketing strategy of these companies. Risk is still high, less technology risk than economic and market risk.by Srinivas Chilukuri.S.M.M.O.T
Very late (>5 years) thrombus formation on an atrial septal defect device: a case report
Though percutaneous transcatheter atrial septal defect closure with newer generation occluder devices is a standard treatment at present, these devices have significant long-term risks (>1 year) associated with such as thrombus formation. Here, we present a case of 28 year-old patient presented with few symptoms and had a history of ASD device closure using amplatzer septal occluder device five years back. The patient was found to have a large thrombus (30Ă—33 mm) attached to the device which was managed using anticoagulants and patients was advised for regular echocardiographic follow-up
RareBERT: Transformer Architecture for Rare Disease Patient Identification using Administrative Claims
A rare disease is any disease that affects a very small percentage (1 in 1,500) of population. It is estimated that there are nearly 7,000 rare disease affecting 30 million patients in the U. S. alone. Most of the patients suffering from rare diseases experience multiple misdiagnoses and may never be diagnosed correctly. This is largely driven by the low prevalence of the disease that results in a lack of awareness among healthcare providers. There have been efforts from machine learning researchers to develop predictive models to help diagnose patients using healthcare datasets such as electronic health records and administrative claims. Most recently, transformer models have been applied to predict diseases BEHRT, G-BERT and Med-BERT. However, these have been developed specifically for electronic health records (EHR) and have not been designed to address rare disease challenges such as class imbalance, partial longitudinal data capture, and noisy labels. As a result, they deliver poor performance in predicting rare diseases compared with baselines. Besides, EHR datasets are generally confined to the hospital systems using them and do not capture a wider sample of patients thus limiting the availability of sufficient rare dis-ease patients in the dataset. To address these challenges, we introduced an extension of the BERT model tailored for rare disease diagnosis called RareBERT which has been trained on administrative claims datasets. RareBERT extends Med-BERT by including context embedding and temporal reference embedding. Moreover, we introduced a novel adaptive loss function to handle the class imbal-ance. In this paper, we show our experiments on diagnosing X-Linked Hypophosphatemia (XLH), a genetic rare disease. While RareBERT performs significantly better than the baseline models (79.9% AUPRC versus 30% AUPRC for Med-BERT), owing to the transformer architecture, it also shows its robustness in partial longitudinal data capture caused by poor capture of claims with a drop in performance of only 1.35% AUPRC, compared with 12% for Med-BERT and 33.0% for LSTM and 67.4% for boosting trees based baseline
Risk of second malignancy after modern conformal and proton beam radiotherapy-Minimizing risks, improving survivorshipInstructions to authors and other literary works of fiction
Amide proton transfer imaging-arterial spin labeling mismatch: a new imaging biomarker for pilocytic astrocytoma
Abstract We describe the potential utility of Amide Proton Transfer weighted (APTw) Magnetic Resonance Imaging and arterial spin labeling (ASL) in characterizing pilocytic astrocytoma (PA), a type of brain tumor that can be challenging to accurately diagnose and treat. The study included 50 patients with solid or predominantly solid intra-cranial and intra-axial tumors, with 25 patients diagnosed with PA and 25 patients diagnosed with other types of tumors. The study found that the APTw imaging-arterial spin labeling (ASL) mismatch is a new imaging biomarker that could be used to differentiate PA from other types of tumors with a high degree of sensitivity and specificity. The results suggest that APTw imaging and ASL may be useful in characterizing PA, potentially improving diagnosis and treatment planning for this type of brain tumor
COVID-19-related stigma towards doctors in India: an online cross-sectional study
Background: The coronavirus disease 2019 (COVID-19) pandemic has led to worry and panic in the minds of people all over the world. Consequently, doctors and other frontline healthcare workers have become a target of stigma in the society. In spite of the Indian government appreciating doctors and healthcare workers with gestures, such as an aerial floral salute and asking the citizens to maintain a positive attitude toward doctors, several people are looking down at doctors as probable virus carriers and treating them as a potential threat to the general public. Aims: To assess stigma and discrimination faced by doctors during the COVID-19 pandemic and their psychological wellbeing. Materials and methodology: A cross-sectional study was conducted on doctors, with convenience sampling technique used to collect data. The study tools were presented in Google forms, and the link was circulated by an exponential non-discriminative snowballing method through doctors’ WhatsApp groups across several states of the country. The study tools included participant information sheet, informed consent form, sociodemographic proforma, a self-designed questionnaire related to stigma and discrimination, and the World Health Organization (Five) Well-Being Index (WHO-5). Results: Three hundred and fifty-six (69.94%) out of 509 doctors reported that they had experienced stigma from the society and their families. 95.5% doctors reported that they are proud of their profession despite experiencing stigma. 58.2% doctors reported that they have received appreciation from the society for their work. 5.6% doctors reported that stigma had a serious impact on their wellbeing. Conclusion: The study results show that majority of doctors are facing stigma and discrimination. Addressing stigma and discrimination faced by doctors and other frontline healthcare workers is significant in fighting this pandemic
Proton therapy and oral mucositis in oral & oropharyngeal cancers: outcomes, dosimetric and NTCP benefit
Abstract Introduction Radiation-induced oral mucositis (RIOM), is a common, debilitating, acute side effect of radiotherapy for oral cavity (OC) and oropharyngeal (OPx) cancers; technical innovations for reducing it are seldom discussed. Intensity-modulated-proton-therapy (IMPT) has been reported extensively for treating OPx cancers, and less frequently for OC cancers. We aim to quantify the reduction in the likelihood of RIOM in treating these 2 subsites with IMPT compared to Helical Tomotherapy. Material and methods We report acute toxicities and early outcomes of 22 consecutive patients with OC and OPx cancers treated with IMPT, and compare the dosimetry and normal tissue complication probability (NTCP) of ≥ grade 3 mucositis for IMPT and HT. Results Twenty two patients, 77% males, 41% elderly and 73% OC subsite, were reviewed. With comparable target coverage, IMPT significantly reduced the mean dose and D32, D39, D45, and D50, for both the oral mucosa (OM) and spared oral mucosa (sOM). With IMPT, there was a 7% absolute and 16.5% relative reduction in NTCP for grade 3 mucositis for OM, compared to HT. IMPT further reduced NTCP for sOM, and the benefit was maintained in OC, OPx subsites and elderly subgroup. Acute toxicities, grade III dermatitis and mucositis, were noted in 50% and 45.5% patients, respectively, while 22.7% patients had grade 3 dysphagia. Compared with published data, the hospital admission rate, median weight loss, feeding tube insertion, unplanned treatment gaps were lower with IMPT. At a median follow-up of 15 months, 81.8% were alive; 72.7%, alive without disease and 9%, alive with disease. Conclusion The dosimetric benefit of IMPT translates into NTCP reduction for grade 3 mucositis compared to Helical Tomotherapy for OPx and OC cancers and encourages the use of IMPT in their management
Standard Operating Procedure (SOP) for mould room practices and simulation of head neck cancer patients undergoing proton therapy
Head Neck cancer patients treated with modern proton therapy need special attention during mould room procedures. In addition to usual mould room practices, patients undergoing Intensity Modulated Proton Therapy (IMPT) require attention to the special characteristics of protons viz., sensitivity to beam path and its alteration, sharp dose fall off and end of range. In this article, we discuss the Standard Operating Procedure (SOP) for HNC immobilization and simulation for IMPT, developed and practiced at our centre. The SOP details each step during the immobilization and simulation process, with nuances specific to IMPT