Search results for: Shreya Pare

Authors: Shreya Srivastava, Sagnik Dey

Abstract:

Aerosol direct radiative forcing (ADRF) refers to the alteration of the Earth's energy balance from the scattering and absorption of solar radiation by aerosol particles. India experiences substantial ADRF due to high aerosol loading from various sources. These aerosols' radiative impact depends on their physical characteristics (such as size, shape, and composition) and atmospheric distribution. Quantifying ADRF is crucial for understanding aerosols’ impact on the regional climate and the Earth's radiative budget. In this study, we have taken radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 22 years (2000-2021) over the Indian subcontinent. Except for a few locations, the short-wave DARF exhibits aerosol cooling at the TOA (values ranging from +2.5 W/m2 to -22.5W/m2). Cooling due to aerosols is more pronounced in the absence of clouds. Being an aerosol hotspot, higher negative ADRF is observed over the Indo-Gangetic Plain (IGP). Aerosol Forcing Efficiency (AFE) shows a decreasing seasonal trend in winter (DJF) over the entire study region while an increasing trend over IGP and western south India during the post-monsoon season (SON) in clear-sky conditions. Analysing atmospheric heating and AOD trends, we found that only the aerosol loading is not governing the change in atmospheric heating but also the aerosol composition and/or their vertical profile. We used a Multi-angle Imaging Spectro-Radiometer (MISR) Level-2 Version 23 aerosol products to look into aerosol composition. MISR incorporates 74 aerosol mixtures in its retrieval algorithm based on size, shape, and absorbing properties. This aerosol mixture information was used for analysing long-term changes in aerosol composition and dominating aerosol species corresponding to the aerosol forcing value. Further, ADRF derived from this method is compared with around 35 studies across India, where a plane parallel Radiative transfer model was used, and the model inputs were taken from the OPAC (Optical Properties of Aerosols and Clouds) utilizing only limited aerosol parameter measurements. The result shows a large overestimation of TOA warming by the latter (i.e., Model-based method).

Keywords: aerosol radiative forcing (ARF), aerosol composition, MISR, CERES, SBDART

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Authors: Shreya Goyal

Abstract:

The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Aishwarya K. V., Shreya Sudesh

Abstract:

Built along the edges of a 11th century CE man-made lake, the city of Bhopal has stood witness to historic layers dating back to Palaeolithic times; early and medieval kingdoms ranging from the Parmaras, Pratiharas to tribal Gonds; the Begum-Nawabs and finally became the Capital of Madhya Pradesh, post-Independence. The lake more popularly called the Upper Lake was created by the King Raja Bhoj from the Parmara dynasty in 1010 AD when he constructed a bund wall across the Kolans river. Atop this bund wall lies the Kamlapati Mahal - which was part of the royal enclosure built in 1702 belonging to the Gond Kingdom. The Mahal is the epicentre of development in the city because it lies in the centre of the axis joining the Old core and New City. Rapid urbanisation descended upon the city once it became the administrative capital of Madhya Pradesh, a newly-formed state of an Independent India. Industrial pockets began being set up and refugees from the Indo-Pakistan separation settled in various regions of the city. To cater to these sudden growth, there was a boom in infrastructure development in the late twentieth century which included precarious decisions made in terms of handling heritage sites causing the destruction of significant parts of the historic fabric. And this practice continues to this day as buffer/ protected zones are breached through exemptions and the absence of robust regulations allow further deterioration of urban heritage. The aim of the research is to systematically study in detail the effect of the urban infrastructure development of the city and its adverse effect on the existing heritage fabric. Through the paper, an attempt to study the parameters involved in preparing the Masterplan of the city and other development projects is done. The research would follow a values-led approach to study the heritage fabric where the significance of the place is assessed based on the values attributed by stakeholders. This approach will involve collection and analysis of site data, assessment of the significance of the site and listing of potential. The study would also attempt to arrive at a solution to deal with urban development along with the protection of the heritage fabric.

Keywords: heritage management, infrastructure development, urban conservation, urban heritage

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Authors: Stephan Boehm, Julia Engel, Judith Eisser

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During the last decade communication in the Internet transformed from a broadcast to a conversational model by supporting more interactive features, enabling user generated content and introducing social media networks. Another important trend with a significant impact on electronic commerce is a massive usage shift from desktop to mobile devices. However, a presentation of product- or service-related information accumulated on websites, micro pages or portals often remains the pivot and focal point of a customer journey. A more recent change of user behavior –especially in younger user groups and in Asia– is going along with the increasing adoption of messaging applications supporting almost real-time but asynchronous communication on mobile devices. Mobile apps of this type cannot only provide an alternative for traditional one-to-one communication on mobile devices like voice calls or short messaging service. Moreover, they can be used in mobile commerce as a new marketing and sales channel, e.g., for product promotions and direct marketing activities. This requires a new way of customer interaction compared to traditional mobile commerce activities and functionalities provided based on mobile web-sites. One option better aligned to the customer interaction in mes-saging apps are so-called chatbots. Chatbots are conversational programs or dialog systems simulating a text or voice based human interaction. They can be introduced in mobile messaging and social media apps by using rule- or artificial intelligence-based imple-mentations. In this context, a comparative analysis is conducted to examine the impact of using traditional websites or chatbots for promoting a product in an impulse purchase situation. The aim of this study is to measure the impact on the customers’ user experi-ence and emotions. The study is based on a random sample of about 60 smartphone users in the group of 20 to 30-year-olds. Participants are randomly assigned into two groups and participate in a traditional website or innovative chatbot based mobile com-merce scenario. The chatbot-based scenario is implemented by using a Wizard-of-Oz experimental approach for reasons of sim-plicity and to allow for more flexibility when simulating simple rule-based and more advanced artificial intelligence-based chatbot setups. A specific set of metrics is defined to measure and com-pare the user experience in both scenarios. It can be assumed, that users get more emotionally involved when interacting with a system simulating human communication behavior instead of browsing a mobile commerce website. For this reason, innovative face-tracking and analysis technology is used to derive feedback on the emotional status of the study participants while interacting with the website or the chatbot. This study is a work in progress. The results will provide first insights on the effects of chatbot usage on user experiences and emotions in mobile commerce environments. Based on the study findings basic requirements for a user-centered design and implementation of chatbot solutions for mobile com-merce can be derived. Moreover, first indications on situations where chatbots might be favorable in comparison to the usage of traditional website based mobile commerce can be identified.

Keywords: chatbots, emotions, mobile commerce, user experience, Wizard-of-Oz prototyping

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Authors: Shreya Saxena

Abstract:

Background: Choledocholithiasis is a common complication of gallstone disease. Risk scoring systems exist to guide the need for further imaging or endoscopy in managing choledocholithiasis. We completed an audit to review the American Society for Gastrointestinal Endoscopy (ASGE) scoring system for prediction and management of choledocholithiasis against the current practice at a tertiary hospital to assess its utility in resource optimisation. We have now conducted a cost focused sub-analysis on patients categorized high-risk for choledocholithiasis according to the guidelines to determine any associated cost benefits. Method: Data collection from our prior audit was used to retrospectively identify thirteen patients considered high-risk for choledocholithiasis. Their ongoing management was mapped against the guidelines. Individual costs for the key investigations were obtained from our hospital financial data. Total cost for the different management pathways identified in clinical practice were calculated and compared against predicted costs associated with recommendations in the guidelines. We excluded the cost of laparoscopic cholecystectomy and considered a set figure for per day hospital admission related expenses. Results: Based on our previous audit data, we identified a77% positive predictive value for the ASGE risk stratification tool to determine patients at high-risk of choledocholithiasis. 47% (6/13) had an magnetic resonance cholangiopancreatography (MRCP) prior to endoscopic retrograde cholangiopancreatography (ERCP), whilst 53% (7/13) went straight for ERCP. The average length of stay in the hospital was 7 days, with an additional day and cost of £328.00 (£117 for ERCP) for patients awaiting an MRCP prior to ERCP. Per day hospital admission was valued at £838.69. When calculating total cost, we assumed all patients had admission bloods and ultrasound done as the gold standard. In doing an MRCP prior to ERCP, there was a 130% increase in cost incurred (£580.04 vs £252.04) per patient. When also considering hospital admission and the average length of stay, it was an additional £1166.69 per patient. We then calculated the exact costs incurred by the department, over a three-month period, for all patients, for key investigations or procedures done in the management of choledocholithiasis. This was compared to an estimate cost derived from the recommended pathways in the ASGE guidelines. Overall, 81% (£2048.45) saving was associated with following the guidelines compared to clinical practice. Conclusion: MRCP is the most expensive test associated with the diagnosis and management of choledocholithiasis. The ASGE guidelines recommend endoscopy without an MRCP in patients stratified as high-risk for choledocholithiasis. Our audit that focused on assessing the utility of the ASGE risk scoring system showed it to be relatively reliable for identifying high-risk patients. Our cost analysis has shown significant cost savings per patient and when considering the average length of stay associated with direct endoscopy rather than an additional MRCP. Part of this is also because of an increased average length of stay associated with waiting for an MRCP. The above data supports the ASGE guidelines for the management of high-risk for choledocholithiasis patients from a cost perspective. The only caveat is our small data set that may impact the validity of our average length of hospital stay figures and hence total cost calculations.

Keywords: cost-analysis, choledocholithiasis, risk stratification tool, general surgery

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Authors: Shreya Saxena, Felix Miller-Molloy, Phillipa Bowen, Greg Fellows, Elizabeth Bowen

Abstract:

Background: Complex fluid balance abnormalities are well-established post-neurosurgery and traumatic brain injury (TBI). The triple-phase response requires fluid management strategies reactive to urine output and sodium homeostasis as patients shift between Diabetes Insipidus (DI) and Syndrome of Inappropriate ADH (SIADH). It was observed, at a tertiary paediatric center, a relatively high prevalence of the above complications within a cohort of paediatric post-neurosurgical and TBI patients. An audit of the clinical practice against set institutional guidelines was undertaken and analyzed to understand why this was occurring. Based on those results, new guidelines were developed with structured educational packages for the specialist teams involved. This was then reaudited, and the findings were compared. Methods: Two independent audits were conducted across two time periods, pre and post guideline change. Primary data was collected retrospectively, including both qualitative and quantitative data sets from the CQUIN neurosurgical database and electronic medical records. All paediatric patients post posterior fossa (PFT) or supratentorial surgery or with a TBI were included. A literature review of evidence-based practice, initial audit data, and stakeholder feedback was used to develop new clinical guidelines and nursing standard operation procedures. Compliance against these newly developed guidelines was re-assessed and a thematic, trend-based analysis of the two sets of results was conducted. Results: Audit-1 January2017-June2018, n=80; Audit-2 January2020-June2021, n=30 (reduced operative capacity due to COVID-19 pandemic). Overall, improvements in the monitoring of both fluid balance and electrolyte trends were demonstrated; 51% vs. 77% and 78% vs. 94%, respectively. The number of clear fluid management plans documented postoperatively also increased (odds ratio of 4), leading to earlier recognition and management of evolving fluid-balance abnormalities. The local paediatric endocrine team was involved in the care of all complex cases and notified sooner for those considered to be developing DI or SIADH (14% to 35%). However, significant Na fluctuations (>12mmol in 24 hours) remained similar – 5 vs six patients – found to be due to complex pituitary hypothalamic pathology – and the recommended adaptive fluid management strategy was still not always used. Qualitative data regarding useability and understanding of fluid-balance abnormalities and the revised guidelines were obtained from health professionals via surveys and discussion in the specialist teams providing care. The feedback highlighted the new guidelines provided a more consistent approach to the post-operative care of these patients and was a better platform for communication amongst the different specialist teams involved. The potential limitation to our study would be the small sample size on which to conduct formal analyses; however, this reflects the population that we were investigating, which we cannot control. Conclusion: The revised clinical guidelines, based on audited data, evidence-based literature review and stakeholder consultations, have demonstrated an improvement in understanding of the neuro-endocrine complications that are possible, as well as increased compliance to post-operative monitoring of fluid balance and electrolytes in this cohort of patients. Emphasis has been placed on preventative rather than treatment of DI and SIADH. Consequently, this has positively impacted patient safety for the center and highlighted the importance of educational awareness and multi-disciplinary team working.

Keywords: post-operative, fluid-balance management, neuro-endocrine complications, paediatric

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