Controlling Your Own Story Using a Digital Identity Solution: Creation Of Economic Identity for Financial Inclusion and Protection

An economic identity that we take for granted in many developed countries is often elusive for large segments of the population who are at risks or under political oppression. These segments are often physically located in geographical jurisdiction that are politically unstable and are not connected to conventional banking infrastructure and have little means to access or afford financial services that some of us take for granted. Therefore, in this research proposal, we posit that the starting point of activating one’s digital identity and the subsequent creation of an economy identity is the proper management of the elements of their life stories associated with their identity. We are thus interested in exploring the design principles underlying a digital identity solution (DIS) built on a decentralized blockchain that would bestow upon the individual the affordances to curate, manage, and formulate their life stories through the mechanisms of the narrative persuasion theory for an optimal economic identity

IMRT QA using machine learning: A multi-institutional validation.

PurposeTo validate a machine learning approach to Virtual intensity-modulated radiation therapy (IMRT) quality assurance (QA) for accurately predicting gamma passing rates using different measurement approaches at different institutions.MethodsA Virtual IMRT QA framework was previously developed using a machine learning algorithm based on 498 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3 mm with 10% threshold at Institution 1. An independent set of 139 IMRT measurements from a different institution, Institution 2, with QA data based on portal dosimetry using the same gamma index, was used to test the mathematical framework. Only pixels with ≥10% of the maximum calibrated units (CU) or dose were included in the comparison. Plans were characterized by 90 different complexity metrics. A weighted poison regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input.ResultsThe methodology predicted passing rates within 3% accuracy for all composite plans measured using diode-array detectors at Institution 1, and within 3.5% for 120 of 139 plans using portal dosimetry measurements performed on a per-beam basis at Institution 2. The remaining measurements (19) had large areas of low CU, where portal dosimetry has a larger disagreement with the calculated dose and as such, the failure was expected. These beams need further modeling in the treatment planning system to correct the under-response in low-dose regions. Important features selected by Lasso to predict gamma passing rates were as follows: complete irradiated area outline (CIAO), jaw position, fraction of MLC leafs with gaps smaller than 20 or 5 mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted average irregularity factor, and duty cycle.ConclusionsWe have demonstrated that Virtual IMRT QA can predict passing rates using different measurement techniques and across multiple institutions. Prediction of QA passing rates can have profound implications on the current IMRT process

Missouri 3,500-cow dairy business plan

"A financial model of an integrated modern dairy system: Rotary parlor; Sand bedded, tunnel ventilated; freestall housing; Passive sand and manure separation; Irrigated forage production""This dairy farm business plan demonstrates one path forward for the next generation of Missouri's dairy farmers. This path involves producing milk in Missouri with a 3,500-cow single site dairy, a capital and labor efficient scale. This dairy plan gives Missouri dairy producers a vision of a new scale and style of dairying common in growing dairy regions. This report is designed to guide planning a completely new dairy. The dairy model uses next generation confinement housing solutions: freestalls with sand bedding and tunnel ventilation to improve cow comfort and cooling. A 72-cow rotary parlor is used to milk the herd three times per day. This model serves as a complete business template for starting a new greenfield dairy. Capital investments, operating costs, production plans, rations, forage systems, housing systems and manure systems are designed as integrated systems. Currently operating dairies seldom start a greenfield dairy by designing a completely new dairy system. However, this strategy can be an option for a group of crop and dairy farmers jointly planning to transition to the next generation of dairying by pooling resources and forming a new entity. This template can also be helpful for existing dairy producers evolving on-site in their current facilities as they examine various technologies for the dairy's expansion path. This model uses a systems approach to integrate cropland planning, irrigated forage production, specific rations tied to production, comprehensive nutrient management, labor-efficient facilities and modern cow housing solutions. This integrated system reduces obstacles to higher milk production at scale. These production practices and management techniques, along with the economic analysis, can be applied to other herd sizes. Dairy producers can use these plans to establish production goals and to evaluate how the various performance measures influence their financial statement. Financial statements show how various components of the dairy operation impact the cash flow, the income statement and the five-year budget. A comparison of key system components and financial indicators for the dairy model can be found in Exhibit A1. This model represents a dairy using 100% equity financing with no debt. Although unrealistic, this simplifying assumption allows lenders to quickly analyze the free cash flow to determine how much debt the operation could service."--IntroductionAuthors of this report: Joe Horner (State Specialist, Agricultural Business and Policy, MU Extension), Ryan Milhollin (State Specialist, Agricultural Business and Policy, MU Extension), Joseph Zulovich (Assistant Professor, Agricultural Systems Management, MU Extension), Teng Lim (Professor, Agricultural Systems Management, MU Extension)New 11/2

Missouri robotic dairy business plans

"Financial models of integrated modern dairy systems: 150-, 300- and 600-cow herds; Robotic milking systems; Sand bedded, tunnel ventilated freestall housing; Passive sand and manure separation; Irrigated forage production""This dairy farm business plan demonstrates one path forward for the next generation of Missouri's dairy farmers. This path involves labor-saving robotic milking systems and next generation confinement housing solutions that improve cow comfort and cooling and remove barriers to higher milk production. Three model dairy herd sizes (150-, 300- and 600-cow units) are modeled here to fit differences in farm equity levels and available land resources. Each plan uses an integrated systems approach combining capital investments, operating costs, production plans, rations, forage systems, housing systems and manure systems. Each model serves as a complete template for starting a new greenfield dairy. Currently operating dairies seldom start a greenfield dairy by designing a completely new dairy system. However, this strategy can be an option for dairy farms transitioning to the next generation – especially if milking and housing facilities are functionally obsolete, fully depreciated and poorly located for expansion. This report is designed to guide such farms in planning a completely new dairy. The templates in this report are also helpful for existing dairy producers evolving on-site in their current facilities as they examine possible technologies to use in a dairy's expansion path. Each economic model evaluates profitability and cash flow potential for each different herd size. This can inform a dairy's production goals and allow producers to evaluate how various investment and performance levels impact financial measures. Financial statements show how various components of the dairy operation impact the operation's cash flow, income statement and the five-year budget. Fitting these financial statements together captures the dairy's business potential. A comparison of key system components and financial indicators for each model is found in Exhibit A1. Each model assumes the dairy uses 100% equity financing, with no debt. Although unrealistic, this simplifying assumption allows lenders to quickly analyze the free cash flow to determine how much debt the operation could service."--IntroductionAuthors of this report: Joe Horner (State Specialist, Agricultural Business and Policy, MU Extension), Ryan Milhollin (State Specialist, Agricultural Business and Policy, MU Extension), Joseph Zulovich (Assistant Professor, Agricultural Systems Management, MU Extension), Teng Lim (Professor, Agricultural Systems Management, MU Extension)New 11/20Includes bibliographical reference

Overnight Risk Model: A Unique Capability

We present a novel risk measurement model capable of capturing overnight risk i.e. the risk encountered between the closing time of the previous day and the opening time of the next day. The risk model captures both the overnight risk and also the intraday risk. Statistical models of intraday asset returns must separate the market opening period from the remainder of the day as these follow statistical laws with different properties. Here we present results showing our two models for these two distinct periods

Missouri 400-cow dairy and 600-cow dairy business plans

"Financial models of integrated modern dairy systems: Parallel parlor; Sand bedded, tunnel ventilated; freestall housing; Passive sand and manure separation; Irrigated forage production""This dairy farm business plan is intended to demonstrate one pathway for the next generation of Missouri's dairy farmers. This path involves next generation confinement housing solutions that can improve cow comfort and cooling while removing barriers to higher milk production. Two dairy herd sizes (400- and 690-cow units) are modeled here to fit differences in farm equity levels and available land resources. Each plan uses an integrated systems approach to combine capital investments, operating costs, production plans, rations, forage systems, housing systems and manure systems. Each model serves as a complete template for starting a new greenfield dairy. Currently operating dairies seldom start a greenfield dairy by designing a completely new dairy system. However, this strategy can be an option for dairy farms transitioning to the next generation – especially if milking and housing facilities are functionally obsolete, fully depreciated and poorly located for expansion. This report is designed to guide such farms in planning a completely new dairy. The templates in this report are also helpful for existing dairy producers evolving on-site in their current facilities as they examine possible technologies to use in a dairy's expansion path. Each economic model evaluates profitability and cash flow potential for each different herd size. This can inform a dairy's production goals and allow producers to evaluate how various investment and performance levels impact financial measures. Financial statements show how various components of the dairy operation impact the operation's cash flow, income statement and the five-year budget. Fitting these financial statements together captures the dairy's business potential. A comparison of key system components and financial indicators for each model is found in Exhibit A1. Each model assumes the dairy uses 100% equity financing, with no debt. Although unrealistic, this simplifying assumption allows lenders to quickly analyze the free cash flow to determine how much debt the operation could service."--First page.Authors of this report: Joe Horner (State Specialist, Agricultural Business and Policy, MU Extension), Ryan Milhollin (State Specialist, Agricultural Business and Policy, MU Extension), Joseph Zulovich (Assistant Professor, Agricultural Systems Management, MU Extension), Teng Lim (Professor, Agricultural Systems Management, MU Extension)New 11/2