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The interest in the value relevance of marketing investments has given rise to numerous studies on the marketing-finance interface. This study integrates extant research findings and establishes empirical generalizations on marketing's impact on firm value. Specifically, the authors conduct a meta-analysis of prior econometric elasticity estimates of the stock market impact of marketing actions and marketing assets. Analyses based on 488 elasticities drawn from 83 studies reveal a mean elasticity of .04 for advertising expenditure variables and of .54 for marketing asset variables. Among marketing assets, customer-related assets show a higher mean elasticity of .72, compared with .33 for brand-related assets. Further analyses show that advertising elasticities are lower in more concentrated industries and that marketing asset elasticities are higher during recession times. Researchers should also be aware that characteristics of the research design (e.g., the type of firm value metric used, the omission of control variables, or not accounting for endogeneity) may affect the estimation results.

Passive leg raising (PLR) reliably predicts fluid responsiveness but requires a real-time cardiac index (CI) measurement or the presence of an invasive arterial line to achieve this effect. The plethysmographic variability index (PVI), an automatic measurement of the respiratory variation of the perfusion index, is non-invasive and continuously displayed on the pulse oximeter device. We tested whether PLR-induced changes in PVI (ΔPVIPLR) could accurately predict fluid responsiveness in mechanically ventilated patients with acute circulatory failure. This was a secondary analysis of an observational prospective study. We included 29 mechanically ventilated patients with acute circulatory failure in this study. We measured PVI (Radical-7 device; Masimo Corp., Irvine, CA) and CI (Echocardiography) before and during a PLR test and before and after volume expansion of 500 mL of crystalloid solution. A volume expansion-induced increase in CI of >15% defined fluid responsiveness. To investigate whether ΔPVIPLR can predict fluid responsiveness, we determined areas under the receiver operating characteristic curves (AUROCs) and gray zones for ΔPVIPLR. Of the 29 patients, 27 (93.1%) received norepinephrine. The median tidal volume was 7.0 [IQR: 6.6–7.6] mL/kg ideal body weight. Nineteen patients (65.5%) were classified as fluid responders (increase in CI > 15% after volume expansion). Relative ΔPVIPLR accurately predicted fluid responsiveness with an AUROC of 0.89 (95%CI: 0.72–0.98, p < 0.001). A decrease in PVI ≤ −24.1% induced by PLR detected fluid responsiveness with a sensitivity of 95% (95%CI: 74–100%) and a specificity of 80% (95%CI: 44–97%). Gray zone was acceptable, including 13.8% of patients. The correlations between the relative ΔPVIPLR and changes in CI induced by PLR and by volume expansion were significant (r = −0.58, p < 0.001, and r = −0.65, p < 0.001; respectively). In sedated and mechanically ventilated ICU patients with acute circulatory failure, PLR-induced changes in PVI accurately predict fluid responsiveness with an acceptable gray zone. ClinicalTrials.govNCT03225378. •PVI is not reliable to predict fluid responsiveness in patients mechanically ventilated with low tidal volume•The changes in PVI induced by PLR reliably predict fluid responsiveness in mechanically ventilated patients receiving norepinephrine•The accuracy of the changes in PVI induced by PLR was the same as the changes in CI or PPV after PLR in predicting fluid responsiveness

This study quantitatively estimates the spatial distribution of anthropogenic methane sources in the United States by combining comprehensive atmospheric methane observations, extensive spatial datasets, and a high-resolution atmospheric transport model. Results show that current inventories from the US Environmental Protection Agency (EPA) and the Emissions Database for Global Atmospheric Research underestimate methane emissions nationally by a factor of ∼1.5 and ∼1.7, respectively. Our study indicates that emissions due to ruminants and manure are up to twice the magnitude of existing inventories. In addition, the discrepancy in methane source estimates is particularly pronounced in the south-central United States, where we find total emissions are ∼2.7 times greater than in most inventories and account for 24 ± 3% of national emissions. The spatial patterns of our emission fluxes and observed methane–propane correlations indicate that fossil fuel extraction and refining are major contributors (45 ± 13%) in the south-central United States. This result suggests that regional methane emissions due to fossil fuel extraction and processing could be 4.9 ± 2.6 times larger than in EDGAR, the most comprehensive global methane inventory. These results cast doubt on the US EPA’s recent decision to downscale its estimate of national natural gas emissions by 25–30%. Overall, we conclude that methane emissions associated with both the animal husbandry and fossil fuel industries have larger greenhouse gas impacts than indicated by existing inventories.

We report on a novel architecture for robust mode-locked femtosecond fiber lasers using a nonlinear optical loop mirror with all polarization-maintaining fibers. Due to a nonreciprocal phase shift, the loop mirror can be operated in a compact and efficient reflection mode, offering the possibility to reach high repetition rates and easy implementation of tuning elements. In particular, longitudinal mode spacing and carrier-envelope offset frequency may be controlled in order to operate the laser as an optical frequency comb. We demonstrate femtosecond pulse generation at three different wavelengths (1030, 1565, and 2050 nm) using Ytterbium, Erbium, and co-doped Thulium–Holmium as gain media, respectively. Robust operation is achieved for a wide range of parameters, including repetition rates from 10 to 250 MHz.

NASA's Orbiting Carbon Observatories (OCO‐2 and OCO‐3) provide measurements of column‐averaged carbon dioxide concentrations (XCO2) with sufficient spatial resolution and precision to constrain bottom‐up estimates of CO2 fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO2 fluxes in the South Coast Air Basin (SoCAB) which surrounds Los Angeles, and in the San Francisco Bay Area Air Basin (SFBA). We study 2020 to understand the impact of the COVID‐19 lockdowns and an active wildfire season. Our results indicated that a 50% (30%) reduction in CO2 emissions relative to 2015 during the COVID‐19 lockdown period was consistent with OCO measurements for SFBA (SoCAB). We find that posterior wildfire emissions differed significantly from the prior at the scale of individual wildfires, though with large uncertainties, and that wildfire emissions in SFBA are significant, attributing 72% of the region's CO2 emissions during August 2020 to wildfires. Plain Language Summary Satellites can measure variations in carbon dioxide concentrations over urban areas. These measurements can be combined with models of the atmosphere to validate estimates of carbon dioxide emissions. We use this approach to better understand emissions in and around San Francisco and Los Angeles, the two major cities in California. We study the year 2020 to see how emissions changed in response to COVID‐19 lockdowns and to observe emissions from wildfires. The satellite measurements combined with the atmospheric model provide us with updated emission estimates that more closely match the measurements and provide greater certainty than our initial estimate of emissions. We also observe reduced emissions during lockdowns in both cities, updated emissions at the scale of individual wildfires, and large emissions from wildfires during peak wildfire season in the San Francisco Bay Area. Key Points Satellite measurements can be used to validate emission inventories of CO2 within urban areas of California Changes in CO2 emissions due to COVID‐19 lockdowns and wildfires in 2020 are captured by satellites During August 2020, wildfires were responsible for 72% of CO2 emissions in the Bay Area

This article focuses on the measurement of the overall importance of brands for consumer decision making—that is, brand relevance in category, or BRiC—across multiple categories and countries. Although brand equity measures for specific brands have attracted a large body of literature, the questions of how important brands are within an entire product category and the extent to which BRiC differs across categories and countries have been neglected. The authors introduce the concept of BRiC (a category-level measure, not a brand-level measure). They develop a conceptual framework to measure BRiC and the drivers of BRiC, test the framework empirically with a sample of more than 5700 consumers, and show how the construct varies across 20 product categories and five countries (France, Japan, Spain, the United Kingdom, and the United States). The results suggest a high validity of the proposed BRiC measure and show substantial differences between categories and countries. A replication study two-and-a-half years later confirms the psychometric properties of the suggested scale and shows remarkable stability of the findings. The findings have important implications for the management of brand investments.

Background Hemorrhagic events remain a major concern in patients under extracorporeal membrane oxygenation (ECMO) support. We tested the association between anticoagulation levels and hemorrhagic events under ECMO using anti-Xa activity monitoring. Methods We performed a retrospective multicenter cohort study in three ECMO centers. All adult patients treated with veno-venous (VV)- or veno-arterial (VA)-ECMO in 6 intensive care units between September 2017 and August 2019 were included. Anti-Xa activities were collected until a hemorrhagic event in the bleeding group and for the duration of ECMO in the non-bleeding group. All dosages were averaged to obtain means of anti-Xa activity for each patient, and patients were compared according to the occurrence or not of bleeding. Results Among 367 patients assessed for eligibility, 121 were included. Thirty-five (29%) presented a hemorrhagic complication. In univariate analysis, anti-Xa activities were significantly higher in the bleeding group than in the non-bleeding group, both for the mean anti-Xa activity (0.38 [0.29–0.67] vs 0.33 [0.22–0.42] IU/mL; p  = 0.01) and the maximal anti-Xa activity (0.83 [0.47–1.46] vs 0.66 [0.36–0.91] IU/mL; p  = 0.05). In the Cox proportional hazard model, mean anti-Xa activity was associated with bleeding ( p  = 0.0001). By Kaplan–Meier analysis with the cutoff value at 0.46 IU/mL obtained by ROC curve analysis, the probability of survival under ECMO without bleeding was significantly lower when mean anti-Xa was > 0.46 IU/mL ( p  = 0.0006). Conclusion In critically ill patients under ECMO, mean anti-Xa activity was an independent risk factor for hemorrhagic complications. Anticoagulation targets could be revised downward in both VV- and VA-ECMO.

Background The main aim of the study whether changes in central venous-to-arterial CO 2 difference (ΔP(v–a)CO 2 ) and central venous oxygen saturation (ΔScvO 2 ) induced by volume expansion (VE) are reliable parameters to define fluid responsiveness (FR) in sedated and mechanically ventilated septic patients. We also sought to determine whether the degree of FR was related to baseline ScvO 2 and P(v–a)CO 2 levels. Methods This was a post-hoc analysis of a multicenter prospective study. We included 205 mechanically ventilated patients with acute circulatory failure. Cardiac index (CI), P(v–a)CO 2 , ScvO 2 , and other hemodynamic variables were measured before and after VE. A VE-induced increase in CI > 15% defined fluid responders. Areas under the receiver operating characteristic curves (AUCs) and the gray zones were determined for ΔP(v–a)CO 2 and ΔScvO 2 . Results One hundred fifteen patients (56.1%) were classified as fluid responders. The AUCs for ΔP(v–a)CO 2 and ΔScvO 2 to define FR were 0.831 (95% CI 0.772–0.880) ( p  < 0.001) and 0.801 (95% CI 0.739–0.853) ( p  < 0.001), respectively. ΔP(v–a)CO 2  ≤ 2.1 mmHg and ΔScvO 2  ≥ 3.4% after VE allowed the categorization between responders and non-responders with positive predictive values of 90% and 86% and negative predictive values of 58% and 64%, respectively. The gray zones for ΔP(v–a)CO 2 (− 2 to 0 mmHg) and ΔScvO 2 (− 1 to 5%) included 22% and 40.5% of patients, respectively. ΔP(v–a)CO 2 and ΔScvO 2 were independently associated with FR in multivariable analysis. No significant relationships were found between pre-infusion ScvO 2 and P(v–a)CO 2 levels and FR. Conclusion In mechanically critically ill patients, ΔP(v–a)CO 2 and ΔScvO 2 are reliable parameters to define FR and can be used in the absence of CI measurement. The response to VE was independent of baseline ScvO 2 and P(v–a)CO 2 levels. Clinical trial registration The study was registered in the ClinicalTrials.gov registry: NCT03225378, date: July 20, 2017.

Climate models show that particles formed by nucleation can affect cloud cover and, therefore, the earth's radiation budget. Measurements worldwide show that nucleation rates in the atmospheric boundary layer are positively correlated with concentrations of sulfuric acid vapor. However, current nucleation theories do not correctly predict either the observed nucleation rates or their functional dependence on sulfuric acid concentrations. This paper develops an alternative approach for modeling nucleation rates, based on a sequence of acid-base reactions. The model uses empirical estimates of sulfuric acid evaporation rates obtained from new measurements of neutral molecular clusters. The model predicts that nucleation rates equal the sulfuric acid vapor collision rate times a prefactor that is less than unity and that depends on the concentrations of basic gaseous compounds and preexisting particles. Predicted nucleation rates and their dependence on sulfuric acid vapor concentrations are in reasonable agreement with measurements from Mexico City and Atlanta.

BackgroundThe use of artificial intelligence (AI) in psychiatry holds promise for diagnosis, therapy, and the categorization of mental disorders. At the same time, it raises significant theoretical and ethical concerns. The debate appears polarized, with proponents and critics seemingly irreconcilably opposed. On the one hand, AI is heralded as a transformative force poised to revolutionize psychiatric research and practice. On the other hand, it is depicted as a harbinger of dehumanization. To better understand this dichotomy, it is essential to identify and critically examine the underlying arguments. To what extent does the use of AI challenge the theoretical assumptions of psychiatric diagnostics? What implications does it have for patient care, and how does it influence the professional self-concept of psychiatrists?MethodsTo explore these questions, we conducted 15 semi-structured interviews with experts from psychiatry, computer science, and philosophy. The findings were analyzed using a structuring qualitative content analysis.ResultsThe analysis focuses on the significance of AI for psychiatric diagnosis and care, as well as on its implications for the identity of psychiatry. We identified different lines of argument suggesting that expert views on AI in psychiatry hinge on the types of data considered relevant and on whether core human capacities in diagnosis and treatment are viewed as replicable by AI.ConclusionsThe results provide a mapping of diverse perspectives, offering a basis for more detailed analysis of theoretical and ethical issues of AI in psychiatry, as well as for the adaptation of psychiatric education.