723 research outputs found
Local Defects in colloidal quantum dot thin films measured via spatially resolved multi-modal optoelectronic spectroscopy.
The morphology, chemical composition, and electronic uniformity of thin-film solution-processed optoelectronics are believed to greatly affect device performance. Although scanning probe microscopies can address variations on the micrometer scale, the field of view is still limited to well under the typical device area, as well as the size of extrinsic defects introduced during fabrication. Herein, a micrometer-resolution 2D characterization method with millimeter-scale field of view is demonstrated, which simultaneously collects photoluminescence spectra, photocurrent transients, and photovoltage transients. This high-resolution morphology mapping is used to quantify the distribution and strength of the local optoelectronic property variations in colloidal quantum dot solar cells due to film defects, physical damage, and contaminants across nearly the entire test device area, and the extent to which these variations account for overall performance losses. It is found that macroscopic defects have effects that are confined to their localized areas, rarely prove fatal for device performance, and are largely not responsible for device shunting. Moreover, quantitative analysis based on statistical partitioning methods of such data is used to show how defect identification can be automated while identifying variations in underlying properties such as mobilities and recombination strengths and the mechanisms by which they govern device behavior.DMR-1807342 - National Science Foundation; Hopkins Extreme Materials InstituteAccepted manuscrip
Too attached to speak up? It depends: How supervisor–subordinate guanxi and perceived job control influence upward constructive voice
In general, reciprocal supervisor–subordinate relationships (high leader–member exchange relationships) provide a supportive context for employees to speak up. In China however, supervisor–subordinate relationships or guanxi are characterized by affective characteristics and hierarchical characteristics which may respectively facilitate and inhibit employee voice. We draw on Guanxi Theory to develop a model of differential effects of two dimensions of supervisor–subordinate guanxi (affective attachment to the supervisor and deference to the supervisor) on voice. Results of a multi-source, lagged field study demonstrated that the affective attachment to the supervisor dimension of guanxi facilitated and the deference to supervisor dimension of guanxi inhibited voice, when employees experienced low job control. We discuss ways these findings extend our understanding of the nature of supervisor–subordinate relationships, guanxi, and their impact on voice
Enhancing Social Media Marketing with A Brand Post Management Process
In recent years, enterprises are increasingly using social media to enhance the marketing effects about their brands and services. As such, brand pages on social media sites with brand posts placed are commonly used for effecting desired marketing features such as advertisement of services and assistance of customers. Therefore, it has become an important objective for enterprises to enhance the effects of their brand pages via sufficient management mechanisms. For this purpose, we present in this paper a management process that focuses on the organization, execution, and control of brand posts to enhance their marketing effects
NASA ROVER, Tackling Citizen Science With Grand Challenges and Everyday Problems
ROVER is the Citizen Science arm of the NASA Clouds and the Earth's Radiant Energy System (CERES) Students' Cloud Observations On-Line (S'COOL) Project. Since 2007, participants around the world have been making and reporting ground truth observations of clouds to assist in the validation of the NASA CERES satellite instrument. NASA scientists are very interested in learning how clouds affect our atmosphere, weather, and climate (relating to climate change). It is the clouds, in part, that affect the overall temperature and energy balance of the Earth. The more we know about clouds, the more we will know about our Earth as a system and citizen scientists are an important piece of that puzzle! As a ROVER cloud observer, all participants follow simple online tutorials to collect data on cloud type, height, cover and related conditions. Observations are sent to NASA to be matched to similar information obtained from satellites and sent back to participants for comparison and analysis. The supporting ROVER website houses a searchable database archiving all participant reports and matching satellite data. By involving Citizen Scientists in cloud observations and reporting we can gain a valuable set of data that would have been previously unavailable to science teams due to funding, manpower, and resource limitations or would have taken an unreasonable amount of time to collect. Reports from a wide range of Citizen Scientist locations are helpful to assess the satellite data under different conditions. With nothing more than their eyes and an internet connection participants provide a different perspective and analysis of clouds, adding to a more complete picture of what's happening in the atmosphere in which we live
Comparative Assessment on Static O-D Synthesis
Recognizing the benefits of data and the information it provides to travel demand is pertinent to network planning and design. Technological advances have led the ability to produce large quantities and types of data and as a result, many origin-destination (O-D) estimation techniques have been developed to accommodate this data. In contrast to the abundant choices on data types, data quantity and estimation procedures, there lacks a common framework to assess these methods. Without consistency in a baseline foundation, the performances of the methodologies can vary greatly based on each individual assumption.
This research addresses the need for techniques to be tested on a common framework by establishing a baseline condition for static O-D estimation through a synthetic Vissim model of the Sioux Falls network as a case study area. The model is used to generate a master dataset, representing the ground-truth, and a subset of the master dataset, emulating the data collected from real world technologies. The subset of data is used as the input for the O-D estimation techniques where the input is varied to evaluate the effects of different levels of coverage/penetration of each data type on estimation results. A total of five estimation techniques developed by Cascetta and Postorino (2001), Castillo et al. (2008b), Parry and Hazelton (2012), Feng et al. (2015) and X. Yang et al. (2017) are tested with three data types (link counts, partial traces, and full traces) and two traffic
assignment conditions (all-or-nothing and user equilibrium).
The result of this research highlights the uniqueness of each network situation and highlights the outcomes of each approach. The wealth of data does not directly equal better information for every methodology. The insights that each data type provides each estimation technique reveals different results. The findings of this research demonstrate and supports that an established testbed framework supports and enhances future O-D estimation scenarios as it pertains to general O-D estimation and extensions of existing techniques
Derivation and validation of a set of miRNA predictors of month-3 moderate-severe pain following trauma exposure using the AURORA cohort
Pain development is common following a traumatic experience. Moderate-severe pain is defined as any severity response of 4 or higher on a 0-10 Numeric Pain Rating Scale for overall body pain and can negatively affect an individual’s quality of life as well as bodily functions. The aim of this thesis is to use data from the Advancing Understanding of RecOvery afteR traumA (AURORA) Study to develop machine learning classification models to accurately classify if a patient will develop month-3 moderate-severe pain following trauma exposure. After data cleaning, imputation, and preprocessing, there were a total of 271 observations and 157 miRNA features. The data were partitioned into a 70:30 train test ratio to exclusively derive the models on the training data and exclusively validate the models on the test data. Data handling, model building, and data analysis were all done in R. I created the logistic regression, least absolute shrinkage and selection operator (LASSO) logistic regression, naïve Bayes, random forest, and polynomial support vector machine (SVM) models using the stats, glmnnet, e1071, randomForest, and e1071 packages, respectively. Of the 5 models created, polynomial SVM had the best external accuracy and F1 score at 0.5909 with a 95% confidence interval (CI) of (0.4809, 0.6946) and 0.7313, respectively. On the other hand, naïve Bayes overall had the worst external accuracy and F1 score at 0.4886 with a 95% CI of (0.3805, 0.5975) and 0.5455, respectively. Logistic regression had the best external AUC score of 0.5313, followed closely by random forest (AUC = 0.5260) and polynomial SVM (AUC = 0.5209). The performance rates of my models were worse compared with others found in the literature that were used to classify pain following trauma exposure. Improvements to the model building process is needed for better classification of individuals at risk of developing moderate-severe pain following trauma exposure in the early stages when presented to the emergency department.Bachelor of Science in Public Healt
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Dynamics of Charged Colloids in Nonpolar Solvents
Charging is typically not expected in nonpolar environments due to a high electrostatic barrier to charge dissociation. Nevertheless, charge effects are observed in such environments upon the addition of surfactants, which aggregate to form charge-stabilizing reverse micelles. Surfactants facilitate the charging and electrostatic stabilization of particles dispersed in nonpolar solvents. Suspensions of charged particles in nonpolar solvents are found in a variety of applications, such as electrophoretic displays, in which charged pigment particles are arranged with an external electric field to form an image. The ability to precisely control the locations and trajectories of the particles using an electric field is essential. However, the behavior of charged particles in a nonpolar solvent in response to an electric field is not fully understood. To investigate the behavior of charged particles in nonpolar solvents, we fabricate a novel microfluidic device that allows us to apply an electric field across a particle suspension and directly visualize the particles as they move across a channel. We image the particles, analyze the particle dynamics, and explore the relationship between the dynamics and the electrical properties of the suspension. We find that the presence of reverse micelles has a significant effect on particle motion. In a constant applied electric field, the particles initially move, but then unexpectedly slow down and stop. This behavior is due to screening of the applied field by the accumulation of charged reverse micelles at the channel walls. Consequently, the internal electric field within the channel decays exponentially. The decay time constant is dependent on the electrical conductivity of the suspension and the size of the channel. We model this behavior as an equivalent RC circuit. We also explore the behavior of charged particles in applied fields that are large enough to transport the particles completely across the channel. We find that the transport of particles is governed by a fingering instability. Furthermore, repeated switches of the direction of the field results in the localization of particles into a well-defined, periodic pattern. The wavelength of this pattern is dependent on the frequency of the applied field.Physic
Adjuvant Migraine Medications in the Treatment of Sudden Sensorineural Hearing Loss.
Objectives/hypothesisTo examine the hearing outcomes of patients with sudden sensorineural hearing loss (SSNHL) treated with oral and intratympanic (IT) steroid only or a combination of steroid and migraine treatment. Our hypothesis was that adjuvant migraine medications may improve outcomes in SSNHL.MethodsA retrospective chart review at a tertiary otology center was conducted to identify patients with SSNHL who received oral steroid and IT dexamethasone injection(s) with or without migraine medications (a combination of nortriptyline and topiramate).ResultsA total of 47 patients received oral steroid and IT dexamethasone injection(s) only, and 46 patients received oral steroid and IT dexamethasone injection(s) as well as migraine lifestyle changes plus a combination of nortriptyline and topiramate. There were no significant differences in demographics and baseline audiometric data between the two groups. Both groups demonstrated improvements in pure tone average (PTA) and hearing thresholds at 250 Hz and 8000 Hz posttreatment. However, compared to steroid-only group, the adjuvant migraine medications group had significantly greater improvements in hearing thresholds at the lower frequencies (250 Hz, 500 Hz, 1000 Hz). Patients in the latter cohort also had greater improvement in PTA (P = .01) and received fewer IT injections (P = .04) PTA improvement of ≥ 10 dB was observed in 36 patients (78%) in the adjuvant migraine medications group and 22 patients (46%) in the control group (P < .001).ConclusionIn multimodal treatment of SSNHL, supplementing oral and IT steroid with migraine medications may result in greater improvements in lower frequency hearing thresholds and PTA. Furthermore, adjuvant migraine treatment can lead to decrease in number of IT injections, thus reducing procedure-related risks and complications.Level of evidence3 Laryngoscope, 131:E283-E288, 2021
Analysis of geologic parameters on recirculating well technology, using 3-D numerical modeling : Massachusetts Military Reservation, Cape Cod
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1997.by Tina L. Lin.M.Eng
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