Real Exchange Rate Fluctuations and the Dynamics of Retail Trade Industries on the U.S.-Canada Border

Consumers living near the U.S.-Canada border can shift their expenditures between the two countries, so real exchange rate fluctuations can act as demand shocks to border areas' retail trade industries. Using annual county-level data, we estimate the effects of real exchange rates on the number of establishments and their average payroll in border counties for four retail industries. In three of the four industries we consider, the number of operating establishments responds either contemporaneously or with a lag of one year to real exchange rate movements. For these industries, the response of retailers' average size is less pronounced. The rapid response of net entry is inconsistent with any model of persistent deviations from purchasing power parity that depends on retailers' costs of changing nominal prices.

Real exchange rates and retail trade on the U.S.-Canada border

Foreign exchange rates ; Retail trade

Real exchange rate fluctuations and the dynamics of retail trade industries on the U.S.-Canada border

Consumers living near the U.S.-Canada border can shift their expenditures between the two countries, so real exchange rate fluctuations can act as demand shocks to border areas' retailers. Using annual county-level data, we estimate the effects of real exchange rates on the number of establishments and their average employment in border counties for four retail industries. In three of the four industries we consider, the number of operating establishments responds either contemporaneously or with a lag of one year, so long-run changes in net entry in fact occur quickly enough to matter for short-run fluctuations.Foreign exchange rates ; Retail trade

Public Facilities Department LEND Program

This project provides background information on an affordable housing development project sponsored by Caritas, a not-for-profit organization located in Boston (MA). (Library-derived description)Lapham, M. R. (1989). P F D Lend Program. Retrieved from http://academicarchive.snhu.eduMaster of Science (M.S.)School of Community Economic Developmen

Contracting Agile Developments for Mission Critical Systems in the Public Sector

Although Agile is a well established software development paradigm, major concerns arise when it comes to contracting issues between a software consumer and a software producer. How to contractualize the Agile production of software, especially for security & mission critical organizations, which typically outsource software projects, has been a major concern since the beginning of the \u201cAgile Era.\u201d In literature, little has been done, from a foundational point of view regarding the formalization of such contracts. Indeed, when the development is outsourced, the management of the contractual life is non\u2013trivial. This happens because the interests of the two parties are typically not aligned. In these situations, software houses strive for the minimization of the effort, while the customer commonly expects high quality artifacts. This structural asymmetry can hardly be overcome with traditional \u201cWaterfall\u201d contracts. In this work, we propose a foundational approach to the Law & Economics of Agile contracts. Moreover, we explore the key elements of the Italian procurement law and outline a suitable solution to merge some basic legal constraints with Agile requirements. Finally, a case study is presented, describing how Agile contracting has been concretely implemented in the Italian Defense Acquisition Process. This work is intended to be a framework for Agile contracts for the Italian public sector of critical systems, according to the new contractual law (Codice degli Appalti)

Observer agreement for small bowel ultrasound in Crohn's disease: results from the METRIC trial

PURPOSE: To prospectively evaluate interobserver agreement for small bowel ultrasound (SBUS) in newly diagnosed and relapsing Crohn's disease. METHODS: A subset of patients recruited to a prospective trial comparing the diagnostic accuracy of MR enterography and SBUS underwent a second SBUS performed by one of a pool of six practitioners, who recorded the presence, activity and location of small bowel and colonic disease. Detailed segmental mural and extra-mural observations were also scored. Interobserver variability was expressed as percentage agreement with a construct reference standard, split by patient cohort, grouping disease as present or absent. Prevalence adjusted bias adjusted kappa (PABAK), and simple percentage agreement between practitioners, irrespective of the reference standard, were calculated. RESULTS: Thirty-eight patients (11 new diagnosis, 27 relapse) were recruited from two sites. Overall percentage agreement for small bowel disease presence against the consensus reference was 82% (52-95% (95%CI)), kappa coefficient (κ) 0.64, (substantial agreement) for new diagnosis and 81%, κ 0.63 (substantial agreement) for the relapsing cohort. Agreement for colonic disease presence was 64%, κ 0.27 (fair agreement) in new diagnosis and 78%,κ 0.56 (moderate agreement) in the relapsing cohort. Simple agreement between practitioners was 84% and 87% for small bowel and colonic disease presence respectively. Practitioners agreed on small bowel disease activity in 24/27 (89%) where both identified disease. Kappa agreement for detailed mural observations ranged from κ 0.00 to 1.00. CONCLUSION: There is substantial practitioner agreement for small bowel disease presence in newly diagnosed and relapsing CD patients, supporting wider dissemination of enteric US

Deep learning for real-time multi-class segmentation of artefacts in lung ultrasound

Lung ultrasound (LUS) has emerged as a safe and cost-effective modality for assessing lung health, particularly during the COVID-19 pandemic. However, interpreting LUS images remains challenging due to its reliance on artefacts, leading to operator variability and limiting its practical uptake. To address this, we propose a deep learning pipeline for multi-class segmentation of objects (ribs, pleural line) and artefacts (A-lines, B-lines, B-line confluence) in ultrasound images of a lung training phantom. Lightweight models achieved a mean Dice Similarity Coefficient (DSC) of 0.74, requiring fewer than 500 training images. Applying this method in real-time, at up to 33.4 frames per second in inference, allows enhanced visualisation of these features in LUS images. This could be useful in providing LUS training and helping to address the skill gap. Moreover, the segmentation masks obtained from this model enable the development of explainable measures of disease severity, which have the potential to assist in the triage and management of patients. We suggest one such semi-quantitative measure called the B-line Artefact Score, which is related to the percentage of an intercostal space occupied by B-lines and in turn may be associated with the severity of a number of lung conditions. Moreover, we show how transfer learning could be used to train models for small datasets of clinical LUS images, identifying pathologies such as simple pleural effusions and lung consolidation with DSC values of 0.48 and 0.32 respectively. Finally, we demonstrate how such DL models could be translated into clinical practice, implementing the phantom model alongside a portable point-of-care ultrasound system, facilitating bedside assessment and improving the accessibility of LUS

Bubble-size distributions produced by wall injection of air into flowing freshwater, saltwater and surfactant solutions

As air is injected into a flowing liquid, the resultant bubble characteristics depend on the properties of the injector, near-wall flow, and flowing liquid. Previous research has shown that near-wall bubbles can significantly reduce skin-friction drag. Air was injected into the turbulent boundary layer on a test section wall of a water tunnel containing various concentrations of salt and surfactant (Triton-X-100, Union Carbide). Photographic records show that the mean bubble diameter decreased monotonically with increasing salt and surfactant concentrations. Here, 33 ppt saltwater bubbles had one quarter, and 20 ppm Triton-X-100 bubbles had one half of the mean diameter of freshwater bubbles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47073/1/348_2004_Article_850.pd

Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set

BACKGROUND: A multi-cancer early detection (MCED) test used to complement existing screening could increase the number of cancers detected through population screening, potentially improving clinical outcomes. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was a prospective, case-controlled, observational study and demonstrated that a blood-based MCED test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin (CSO) with high accuracy. The objective of this third and final CCGA substudy was to validate an MCED test version further refined for use as a screening tool. PATIENTS AND METHODS: This pre-specified substudy included 4077 participants in an independent validation set (cancer: n = 2823; non-cancer: n = 1254, non-cancer status confirmed at year-one follow-up). Specificity, sensitivity, and CSO prediction accuracy were measured. RESULTS: Specificity for cancer signal detection was 99.5% [95% confidence interval (CI): 99.0% to 99.8%]. Overall sensitivity for cancer signal detection was 51.5% (49.6% to 53.3%); sensitivity increased with stage [stage I: 16.8% (14.5% to 19.5%), stage II: 40.4% (36.8% to 44.1%), stage III: 77.0% (73.4% to 80.3%), stage IV: 90.1% (87.5% to 92.2%)]. Stage I-III sensitivity was 67.6% (64.4% to 70.6%) in 12 pre-specified cancers that account for approximately two-thirds of annual USA cancer deaths and was 40.7% (38.7% to 42.9%) in all cancers. Cancer signals were detected across >50 cancer types. Overall accuracy of CSO prediction in true positives was 88.7% (87.0% to 90.2%). CONCLUSION: In this pre-specified, large-scale, clinical validation substudy, the MCED test demonstrated high specificity and accuracy of CSO prediction and detected cancer signals across a wide diversity of cancers. These results support the feasibility of this blood-based MCED test as a complement to existing single-cancer screening tests. CLINICAL TRIAL NUMBER: NCT02889978