Much research has focused on physical disorder in urban neighborhoods as evidence that the community does not maintain local norms and spaces. Little attention has been paid to the opposite: indicators of proactive investment in the neighborhood's upkeep. This manuscript presents a methodology that translates a database of approved building permits into an ecometric of investment by community members, establishing basic content, criteria for reliability, and construct validity. A database from Boston, MA contained 150,493 permits spanning 2.5 years, each record including the property to be modified, permit type, and date issued. Investment was operationalized as the proportion of properties in a census block group that underwent an addition or renovation, excluding larger developments involving the demolition or construction of a building. The reliability analysis found that robust measures could be generated every 6 months, and that longitudinal analysis could differentiate between trajectories across neighborhoods. The validity analysis supported two hypotheses: investment was best predicted by homeownership and median income; and maintained an independent relationship with measures of physical disorder despite controlling for demographics, implying that it captures the other end of a spectrum of neighborhood maintenance. Possible uses for the measure in research and policy are discussed.
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http://dx.doi.org/10.1007/s10464-014-9685-8 | DOI Listing |
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFEur J Radiol
January 2025
Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA. Electronic address:
Purpose: To evaluate the feasibility of aortoiliac CT-Angiography (CTA) using dual-source photon-counting detector (PCD)-CT with minimal iodine dose.
Methods: This IRB-approved, single-center prospective study enrolled patients with indications for aortoiliac CTA from December 2022 to March 2023. All scans were performed using a first-generation dual-source PCD-CT.
J Hypertens
November 2024
Faculty of Sport Sciences, Universidad Europea de Madrid.
Objectives: The effects of acute physical exercise in patients with resistant hypertension remain largely unexplored compared with hypertensive patients in general. We assessed the short-term effects of acute moderate-intensity (MICE) and high-intensity interval exercise (HIIE) on the clinic (BP) and 24-h ambulatory blood pressure (ABP) of patients with resistant hypertension.
Methods: Using a crossover randomized controlled design, 10 participants (56 ± 7 years) with resistant hypertension performed three experimental sessions: MICE, HIIE, and control.
J Neurosurg
January 2025
1Department of Neurosurgery, St. Olav's University Hospital, Trondheim, Norway.
Objective: The extent of resection (EOR) and postoperative residual tumor (RT) volume are prognostic factors in glioblastoma. Calculations of EOR and RT rely on accurate tumor segmentations. Raidionics is an open-access software that enables automatic segmentation of preoperative and early postoperative glioblastoma using pretrained deep learning models.
View Article and Find Full Text PDFJCO Precis Oncol
January 2025
Translational Research Support Office, National Cancer Center Hospital East, Chiba, Japan.
Purpose: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mCRC). Identifying optimal biomarkers for treatment decisions remains challenging. This study explores the potential of artificial intelligence (AI) in predicting treatment responses to trastuzumab plus pertuzumab (TP) in patients with -amplified mCRC from the phase II TRIUMPH trial.
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