Effect of skin surface stimulation on acupoints for phonotraumatic injuries

From a recent large-scaled randomized controlled trial, it was found that genuine acupuncture was not significantly different from the placebo, or skin surface stimulation, in improving the vocal functions of dysphonic subjects with benign vocal pathologies. This randomized, double-blind, placebo-controlled study investigated the effects of skin surface stimulation on acupoints for treating phonotraumatic injuries. Four female subjects were randomly assigned to either a treatment group or a placebo group. Subjects in the treatment group received skin surface stimulation on voice-related acupoints Hegu (Li4), Lieque (Lu7), Lianquan (CV23), Renying (St9) and Zhaohai (Ki6), whereas subjects in the placebo group received skin surface stimulation on non-voice related acupoints Tianchuang (SI16), Neiguan (PC6), Zhongzhu (SJ3) and Shangqiu (SP5). All subjects completed 12 sessions within a 6-week timeframe. Outcome measures included aerodynamic measures, the voice range profile, and self-perceived voice-related quality of life by subjects. Limited by a small sample size, significant changes over time were not found in both groups from pre-treatment to post-treatment and 14 days post-treatment. There were no conclusive results regarding whether skin surface stimulation on acupoints is an effective treatment for improving the vocal functions and quality of life in patients with phonotraumatic injuries.published_or_final_versionSpeech and Hearing SciencesBachelorBachelor of Science in Speech and Hearing Science

Assessing the predictive ability of the Suicide Crisis Inventory for near-term suicidal behavior using machine learning approaches

OBJECTIVE: This study explores the prediction of near-term suicidal behavior using machine learning (ML) analyses of the Suicide Crisis Inventory (SCI), which measures the Suicide Crisis Syndrome, a presuicidal mental state. METHODS: SCI data were collected from high-risk psychiatric inpatients (N = 591) grouped based on their short-term suicidal behavior, that is, those who attempted suicide between intake and 1-month follow-up dates (N = 20) and those who did not (N = 571). Data were analyzed using three predictive algorithms (logistic regression, random forest, and gradient boosting) and three sampling approaches (split sample, Synthetic minority oversampling technique, and enhanced bootstrap). RESULTS: The enhanced bootstrap approach considerably outperformed the other sampling approaches, with random forest (98.0% precision; 33.9% recall; 71.0% Area under the precision-recall curve [AUPRC]; and 87.8% Area under the receiver operating characteristic [AUROC]) and gradient boosting (94.0% precision; 48.9% recall; 70.5% AUPRC; and 89.4% AUROC) algorithms performing best in predicting positive cases of near-term suicidal behavior using this dataset. CONCLUSIONS: ML can be useful in analyzing data from psychometric scales, such as the SCI, and for predicting near-term suicidal behavior. However, in cases such as the current analysis where the data are highly imbalanced, the optimal method of measuring performance must be carefully considered and selected

Estimates of Power Plant NOx Emissions and Lifetimes from OMI NO2 Satellite Retrievals

Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons

Effects of Handling Real Objects and Self-Avatar Fidelity on Cognitive Task Performance and Sense of Presence in Virtual Environments

Immersive virtual environments (VEs) provide participants with computer-generated environments filled with virtual objects to assist in learning, training, and practicing dangerous and/or expensive tasks. But does having every object being virtual inhibit the interactivity and effectiveness for certain tasks? Further, does the visual fidelity of the virtual objects affect performance? If participants spent most of their time and cognitive load on learning and adapting to interacting with a purely virtual system, this could reduce the overall effectiveness of a VE. We conducted a study that investigated how handling real objects and self-avatar visual fidelity affects performance on a spatial cognitive manual task. We compared participants' performance of a block arrangement task in both a real-space environment and several virtual and hybrid environments. The results showed that manipulating real objects in a VE brings task performance closer to that of real space, compared to manipulating virtual objects

The Observed Response of Ozone Monitoring Instrument (OMI) NO2 Columns to NOx Emission Controls on Power Plants in the United States: 2005-2011

We show that Aura Ozone Monitoring Instrument (OMI) nitrogen dioxide (NO2) tropospheric column data may be used to assess changes of the emissions of nitrogen oxides (NOx) from power plants in the United States, though careful interpretation of the data is necessary. There is a clear response for OMI NO2 data to NOx emission reductions from power plants associated with the implementation of mandated emission control devices (ECDs) over the OMI record (2005e2011). This response is scalar for all intents and purposes, whether the reduction is rapid or incremental over several years. However, it is variable among the power plants, even for those with the greatest absolute decrease in emissions. We document the primary causes of this variability, presenting case examples for specific power plants

Evaluating face gender cues in virtual humans within and beyond the gender binary

Introduction: Virtual human work regarding gender is widely based on binary gender despite recent understandings of gender extending beyond female and male. Additionally, gender stereotypes and biases may be present in virtual human design.Methods: This study evaluates how face gender cues are implemented in virtual humans by conducting an exploratory study where an undergraduate computing population (n = 67) designed three virtual human faces—female, male, and nonbinary.Results: Results showed that face gender cues were implemented in stereotypical ways to represent binary genders (female and male virtual humans). For nonbinary gender virtual humans, stereotypical face gender cues were expressed inconsistently (sometimes feminine, sometimes masculine), and conflicting gender cues (pairs of cues that signal opposing binary gender) occurred frequently. Finally, results revealed that not all face gender cues are leveraged equally to express gender.Discussion: Implications of these findings and future directions for inclusive and representative gender expression in virtual humans are discussed

The Influence of Health Care Professional Characteristics on Pain Management Decisions

Objective Evidence suggests that patient characteristics such as sex, race, and age influence the pain management decisions of health care providers. Although this signifies that patient demographics may be important determinants of health care decisions, pain-related care also may be impacted by the personal characteristics of the health care practitioner. However, the extent to which health care provider characteristics affect pain management decisions is unclear, underscoring the need for further research in this area. Methods A total of 154 health care providers (77 physicians, 77 dentists) viewed video vignettes of virtual human (VH) patients varying in sex, race, and age. Practitioners provided computerized ratings of VH patients’ pain intensity and unpleasantness, and also reported their willingness to prescribe non-opioid and opioid analgesics for each patient. Practitioner sex, race, age, and duration of professional experience were included as predictors to determine their impact on pain management decisions. Results When assessing and treating pain, practitioner sex, race, age, and duration of experience were all significantly associated with pain management decisions. Further, the role of these characteristics differed across VH patient sex, race, and age. Conclusions These findings suggest that pain assessment and treatment decisions may be impacted by the health care providers’ demographic characteristics, effects which may contribute to pain management disparities. Future research is warranted to determine whether findings replicate in other health care disciplines and medical conditions, and identify other practitioner characteristics (e.g., culture) that may affect pain management decisions

Outcomes of multimodal therapy in a large series of patients with anaplastic thyroid cancer

Background The role of radiotherapy (RT) in the treatment of patients with anaplastic thyroid cancer (ATC) for local tumor control is critical because mortality often is secondary to complications of tumor volume rather than metastatic disease. Herein, the authors report the long-term outcomes of RT for patients with ATC. Methods A total of 104 patients with histologically confirmed ATC were identified who presented to the study institution between 1984 and 2017 and who received curative-intent or postoperative RT. Locoregional progression-free survival (LPFS), overall survival (OS), and distant metastasis-free survival were assessed. Results The median age of the patients was 63.5 years. The median follow-up was 5.9 months (interquartile range, 2.7-17.0 months) for the entire cohort and 10.6 months (interquartile range, 5.3-40.0 months) for surviving patients. Thirty-one patients (29.8%) had metastatic disease prior to the initiation of RT. Concurrent chemoradiation was administered in 99 patients (95.2%) and 53 patients (51.0%) received trimodal therapy. Systemic therapy included doxorubicin (73.7%), paclitaxel with or without pazopanib (24.3%), and other systemic agents (2.0%). The 1-year OS and LPFS rates were 34.4% and 74.4%, respectively. On multivariate analysis, RT >= 60 Gy was associated with improved LPFS (hazard ratio [HR], 0.135; P = .001) and improved OS (HR, 0.487; P = .004), and trimodal therapy was associated with improved LPFS (HR, 0.060; P = .017). The most commonly observed acute grade 3 adverse events included dermatitis (20%) and mucositis (13%), with no grade 4 subacute or late adverse events noted (adverse events were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events [version 4.0]). Conclusions RT appears to demonstrate a dose-dependent, persistent LPFS and OS benefit in patients with locally advanced ATC with an acceptable toxicity profile. Aggressive RT should be strongly considered for the treatment of patients with ATC as part of a trimodal treatment approach

Molecular Differentiation of Mycobacterium tuberculosis Strains without IS6110 Insertions

By using standard restriction fragment length polymorphism, 6 zero-copy IS6110 Mycobacterium tuberculosis isolates were identified from 1,180 Maryland isolates as part of the National Tuberculosis Genotyping Surveillance Network Project. By using various genotyping methods, we demonstrated that this zero band cluster can be differentiated into six genotypes