TB87: Delivery Costs per Package on Wholesale Milk Routes: A Comparison of Two Methods of Cost Allocation

This study of milk delivery operations was undertaken to develop labor relatives for different packages and to compare unit costs of delivery computed by using these relatives. A principal issue was whether variable direct labor was a better measure than total direct labor for allocating costs to various packages. Delivery operations on milk routes were timed to determine the amount of labor used in performing various functions in serving wholesale customers. This route information and the financial information on dealer delivery operations comprised the data base for the analyses.https://digitalcommons.library.umaine.edu/aes_techbulletin/1116/thumbnail.jp

B742: Improving the Incomes of Small Farm Families in Coastal Maine

Two basic objectives were formulated for this study: 1) To determine the physical, human and financial resources, as well as the source of income from farm and non-farm outlets available to small farm families living in coastal Maine; and, 2) To develop optimal organizations of existing small farm and family labor resources in order to maximize the incomes of these farm families.https://digitalcommons.library.umaine.edu/aes_bulletin/1097/thumbnail.jp

Justifying Public Decisions in Arctic Oil and Gas Development: American and Russian Approaches

Government resource decisions in the Arctic typically involve complex issues; multiple criteria are used to choose among alternatives. This complexity is even greater with petroleum development because of concerns about national energy security, environmental impacts, and economic development. Two decision-aiding techniques may help decision makers clarify their decisions to themselves, the stakeholders, and the general public. The Russian qualitative technique seeks to reduce the number of criteria and find alternative options that may be better than the initial ones. The Western quantitative technique seeks to measure the decision maker's judgement about the utility and certainty of each option. These techniques are applied to two case studies: a decision about gas pipeline routing on the Yamal Peninsula, Russia, and a tool for evaluating applications for development permits on the North Slope of Alaska. The qualitative method is easier to use and may be the best model for people who use numbers infrequently or want to make a claim based on rights. The quantitative method did well at preserving detail and incorporating uncertainty. Both approaches helped to reduce the apparent complexity of the decisions.Les décisions gouvernementales concernant les ressources dans l'Arctique mettent le plus souvent en jeu des questions complexes; un grand nombre de critères sont utilisés en vue de choisir parmi différentes options. Cette complexité s'accroît dans le cas de l'exploitation pétrolière en raison des problèmes entourant la sécurité nationale de l'énergie, les retombées environnementales et le développement économique. Deux techniques d'aide à la décision peuvent inciter les décideurs à clarifier leurs décisions pour eux-mêmes, pour les parties intéressées et pour le grand public. La technique qualitative russe cherche à réduire le nombre de critères et à trouver des solutions de rechange qui pourraient être meilleures que les mesures initiales. La technique quantitative occidentale cherche à mesurer le jugement du décideur sur l'utilité et la certitude de chaque option. Ces techniques sont appliquées à deux études de cas: une décision concernant le tracé d'un gazoduc dans la presqu'île de Iamal en Russie, et un outil permettant d'évaluer les demandes de permis d'exploitation sur le versant Nord de l'Alaska. La méthode qualitative est plus facile à utiliser et peut être le meilleur modèle pour des individus qui n'ont pas l'habitude des chiffres ou qui veulent établir une revendication fondée sur des droits. La méthode quantitative réussit bien à préserver le détail et à intégrer l'incertitude. Les deux approches aidaient à réduire la complexité apparente des décisions

Justifying Public Decisions in Arctic Oil and Gas Development: American and Russian Approaches

Government resource decisions in the Arctic typically involve complex issues; multiple criteria are used to choose among alternatives. This complexity is even greater with petroleum development because of concerns about national energy security, environmental impacts, and economic development. Two decision-aiding techniques may help decision makers clarify their decisions to themselves, the stakeholders, and the general public. The Russian qualitative technique seeks to reduce the number of criteria and find alternative options that may be better than the initial ones. The Western quantitative technique seeks to measure the decision maker* s judgement about the utility and certainty of each option. These techniques are applied to two case studies: a decision about gas pipeline routing on the Yamal Peninsula, Russia, and a tool for evaluating applications for development permits on the North Slope of Alaska. The qualitative method is easier to use and may be the best model for people who use numbers infrequently or want to make a claim based on rights. The quantitative method did well at preserving detail and incorporating uncertainty. Both approaches helped to reduce the apparent complexity of the decisions

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Outmigration and gender balance in Greenland

Research on Alaska has established a pattern of disproportionate outmigration by young adult females from Native villages and towns. Consequently, smaller villages tend to have more young adult Native men than women; the reverse holds true in Alaskan cities. Such migration reflects gender differences in opportunities and also in perceptions regarding the relative attractions of life in small and larger communities. For this article, we replicate parts of the Alaskan research using demographic data on Greenland. A broadly similar pattern of female outmigration emerges, of equal or greater scale. We also find differences in the details, however, corresponding to unique aspects of Greenland\u27s communities, policies, and recent history

Outmigration and gender balance in Greenland

t. Research on Alaska has established a pattern of disproportionate outmigration by young adult females from Native villages and towns. Consequently, smaller villages tend to have more young adult Native men than women; the reverse holds true in Alaskan cities. Such migration reflects gender differences in opportunities and also in perceptions regarding the relative attractions of life in small and larger communities. For this article, we replicate parts of the Alaskan research using demographic data on Greenland. A broadly similar pattern of female outmigration emerges, of equal or greater scale. We also find differences in the details, however, corresponding to unique aspects of Greenland\u27s communities, policies, and recent h