Lawn Buddy

Grass lawns are a common hallmark of the American home. In 2019, a survey from the National Association of Landscape Professionals found that 81% of all Americans owned a lawn [1]. Mowing is a time consuming and costly chore that is part of maintaining a grass lawn. The manual labor in mowing a lawn can exceed 40 hours per year [2]. People commonly incur weekly costs on mowing services to save time. Traditional gas powered mowers are physically demanding and use engines that need routine maintenance. They operate loudly enough that users should be wearing hearing protection and the noise commonly disturbs neighbors. Air pollution from gas emissions are also a concern for both the user and for the environment. An electric autonomous mower utilizes rechargeable batteries for power. Without a gas-engine, it is significantly quieter and requires little maintenance. No user is necessary to push the mower and there are no gas emissions. The mower returns to a docking station for charging its self-contained battery and leaves to mow as scheduled by the user. Collision avoidance and object detection are part of the mower’s completely autonomous navigation. These features allow the user to spend their time freely after the initial setup. Additional functionality such as blade mowing patterns and routine check-up reminders can be controlled through a wireless remote interface

Social media marketing strategy: definition, conceptualization, taxonomy, validation, and future agenda

Although social media use is gaining increasing importance as a component of firms’ portfolio of strategies, scant research has systematically consolidated and extended knowledge on social media marketing strategies (SMMSs). To fill this research gap, we first define SMMS, using social media and marketing strategy dimensions. This is followed by a conceptualization of the developmental process of SMMSs, which comprises four major components, namely drivers, inputs, throughputs, and outputs. Next, we propose a taxonomy that classifies SMMSs into four types according to their strategic maturity level: social commerce strategy, social content strategy, social monitoring strategy, and social CRM strategy. We subsequently validate this taxonomy of SMMSs using information derived from prior empirical studies, as well with data collected from in-depth interviews and a quantitive survey among social media marketing managers. Finally, we suggest fruitful directions for future research based on input received from scholars specializing in the field

Temporal changes in the epidemiology, management, and outcome from acute respiratory distress syndrome in European intensive care units: a comparison of two large cohorts

Background: Mortality rates for patients with ARDS remain high. We assessed temporal changes in the epidemiology and management of ARDS patients requiring invasive mechanical ventilation in European ICUs. We also investigated the association between ventilatory settings and outcome in these patients. Methods: This was a post hoc analysis of two cohorts of adult ICU patients admitted between May 1–15, 2002 (SOAP study, n = 3147), and May 8–18, 2012 (ICON audit, n = 4601 admitted to ICUs in the same 24 countries as the SOAP study). ARDS was defined retrospectively using the Berlin definitions. Values of tidal volume, PEEP, plateau pressure, and FiO2 corresponding to the most abnormal value of arterial PO2 were recorded prospectively every 24 h. In both studies, patients were followed for outcome until death, hospital discharge or for 60 days. Results: The frequency of ARDS requiring mechanical ventilation during the ICU stay was similar in SOAP and ICON (327[10.4%] vs. 494[10.7%], p = 0.793). The diagnosis of ARDS was established at a median of 3 (IQ: 1–7) days after admission in SOAP and 2 (1–6) days in ICON. Within 24 h of diagnosis, ARDS was mild in 244 (29.7%), moderate in 388 (47.3%), and severe in 189 (23.0%) patients. In patients with ARDS, tidal volumes were lower in the later (ICON) than in the earlier (SOAP) cohort. Plateau and driving pressures were also lower in ICON than in SOAP. ICU (134[41.1%] vs 179[36.9%]) and hospital (151[46.2%] vs 212[44.4%]) mortality rates in patients with ARDS were similar in SOAP and ICON. High plateau pressure (> 29 cmH2O) and driving pressure (> 14 cmH2O) on the first day of mechanical ventilation but not tidal volume (> 8 ml/kg predicted body weight [PBW]) were independently associated with a higher risk of in-hospital death. Conclusion: The frequency of and outcome from ARDS remained relatively stable between 2002 and 2012. Plateau pressure > 29 cmH2O and driving pressure > 14 cmH2O on the first day of mechanical ventilation but not tidal volume > 8 ml/kg PBW were independently associated with a higher risk of death. These data highlight the continued burden of ARDS and provide hypothesis-generating data for the design of future studies

Smartphone imaging repository: a novel method for creating a CT image bank

Abstract Background Imaging repositories are commonly attached to ongoing clinical trials, but capturing, transmitting, and storing images can be complicated and labor-intensive. Typical methods include outdated technologies such as compact discs. Electronic file transfer is becoming more common, but even this requires hours of staff time on dedicated computers in the radiology department. Methods We describe and test an image capture method using smartphone camera video-derived images of brain computed tomography (CT) scans of traumatic intracranial hemorrhage. The deidentified videos are emailed or uploaded from the emergency department for central adjudication. We selected eight scans, mild moderate, and severe subdural and multicompartmental hematomas and mild and moderate intraparenchymal hematomas. Ten users acquired data using seven different smartphones. We measured the time in seconds it took to capture and send the files. The primary outcomes were hematoma volume measured by ABC/2, Marshall scale, midline shift measurement, image quality by a contrast-to-noise ratio (CNR), and time to capture. A radiologist and an imaging scientist applied the ABC/2 method and calculated the Marshall scale and midline shift on the data acquired on different smartphones and the PACS in a randomized order. We calculate the intraclass correlation coefficient (ICC). We measured image quality by calculating the contrast-to-noise ratio (CNR). We report summary statistics on time to capture in the smartphone group without a comparator. Results ICC for lesion volume, midline shift, and Marshall score were 0.973 (95% CI 0.931, 0.994), 0.998 (95% CI: 0.996, 0.999), and 0.973 (0.931, 0.994), respectively. Lesion conspicuity was not different among the image types via assessment of CNR using the Friedman test, $${\lambda }^{2}$$ λ 2 of 24.8, P =  < .001, with a small Kendall’s W effect size (0.591). Mean (standard deviation) time to capture and email the video was 60.1 (24.3) s. Conclusions Typical smartphones may produce video image quality high enough for use in a clinical trial imaging repository. Video capture and transfer takes only seconds, and hematoma volumes, Marshall scales, and image quality measured on the videos did not differ significantly from those calculated on the PACS