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Monolayer (ML) molybdenum disulfide (MoS₂) is a novel 2-dimensional (2D) semiconductor whose properties have many applications in devices. Despite its potential, ML MoS₂ is limited in its use due to its degradation under exposure to ambient air. Therefore, studies of possible degradation prevention methods are important. It is well established that air humidity plays a major role in the degradation. In this paper, we investigate the effects of substrate hydrophobicity on the degradation of chemical vapor deposition (CVD) grown ML MoS2. We use optical microscopy, atomic force microscopy (AFM), and Raman mapping to investigate the degradation of ML MoS2 grown on SiO2 and Si3N4 that are hydrophilic and hydrophobic substrates, respectively. Our results show that the degradation of ML MoS₂ on Si3N4 is significantly less than the degradation on SiO2. These results show that using hydrophobic substrates to grow 2D transition metal dichalcogenide ML materials may diminish ambient degradation and enable improved protocols for device manufacturing.
Contrary to popular myth, majority of mentally ill women are mothers with increasing number of them seeking help. Little is known about their own experiences in this regard and the extent to which their needs are met.
To assess the barriers and facilitators in seeking help from mental health care providers in matters of pregnancy and parenting.
The study used qualitative design with social constructivist paradigm. A purposive sample of 30 mothers with severe mental illness was obtained. Data was collected through one-to-one in-depth semi-structured interviews. After verbatim transcription, inductive thematic analysis was used to explore transcripts.
Most women considered motherhood “central” to their lives and almost all of them experienced the burden of the “dual role”. Main barriers in seeking help were stigma, treatment side effects, wrong information and time constraints. Whereas self-advocacy, early engagement, education of women and involvement of the family with service providers were the facilitating factors. The prime expectations of the mothers as identified were early and direct communication, patient audience and basic guidance in regards to child health and parenting issues.
Women who are mothers and also users of mental health services face special challenges in managing the contradictory aspects of their dual identity. Hearing their voices are essential for service provision and ensuring adequate mental health needs. Early and direct intervention along with understanding and addressing critical areas are necessary for proper care of both the mother and child.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
To identify patient and provider characteristics associated with high-volume antibiotic prescribing for children in Tennessee, a state with high antibiotic utilization.
Cross-sectional, retrospective analysis of pediatric (aged <20 years) outpatient antibiotic prescriptions in Tennessee using the 2016 IQVIA Xponent (formerly QuintilesIMS) database.
Patient and provider characteristics, including county of prescription fill, rural versus urban county classification, patient age group, provider type (nurse practitioner, physician assistant, physician, or dentist), physician specialty, and physician years of practice were analyzed.
Tennessee providers wrote 1,940,011 pediatric outpatient antibiotic prescriptions yielding an antibiotic prescribing rate of 1,165 per 1,000 population, 50% higher than the national pediatric antibiotic prescribing rate. Mean antibiotic prescribing rates varied greatly by county (range, 39–2,482 prescriptions per 1,000 population). Physicians wrote the greatest number of antibiotic prescriptions (1,043,030 prescriptions, 54%) of which 56% were written by general pediatricians. Pediatricians graduating from medical school prior to 2000 were significantly more likely than those graduating after 2000 to be high antibiotic prescribers. Overall, 360 providers (1.7% of the 21,798 total providers in this dataset) were responsible for nearly 25% of both overall and broad-spectrum antibiotic prescriptions; 20% of these providers practiced in a single county.
Fewer than 2% of providers account for 25% of pediatric antibiotic prescriptions. High antibiotic prescribing for children in Tennessee is associated with specific patient and provider characteristics that can be used to design stewardship interventions targeted to the highest prescribing providers in specific counties and specialties.
Duck production has the potential to play a major role in agricultural economy. Asian countries alone contribute 84.2% of total duck meat produced in the world. Driven by the demand of processed foods among consumers, the global duck meat market is expected to grow at a steady pace, reaching a value of about $11.23 billion in the coming years. Duck meat has higher muscle fibre content in breast meat compared to chicken, and is considered as red meat. Moreover, due to a higher fat content (13.8%) than chicken and a stronger gamey flavour, duck meat can be less appreciated by the consumer. Development and diversification of ready-to-eat duck meat products is expected to increase consumption levels. Hence, the status of duck meat production, physicochemical properties, processing, including traditional products, and development of novel value-added ready-to-eat products from spent duck meat is discussed in detail to explore its importance as an alternative to chicken.
We observed pediatric S. aureus hospitalizations decreased 36% from 26.3 to 16.8 infections per 1,000 admissions from 2009 to 2016, with methicillin-resistant S. aureus (MRSA) decreasing by 52% and methicillin-susceptible S. aureus decreasing by 17%, among 39 pediatric hospitals. Similar decreases were observed for days of therapy of anti-MRSA antibiotics.
OBJECTIVES/SPECIFIC AIMS: The objective of this study is to use machine Learning techniques to generate maps of epithelium and lumen density in MRI space. METHODS/STUDY POPULATION: Methods: We prospectively recruited 39 patients undergoing prostatectomy for this institutional review board (IRB) approved study. Patients underwent MP-MRI before prostatectomy on a 3T field strength MRI scanner (General Electric, Waukesha, WI, USA) using an endorectal coil. MP-MRI included field-of-view optimized and constrained undistorted single shot (FOCUS) diffusion weighted imaging with 10 b-values (b=0, 10, 25, 50, 80, 100, 200, 500, 1000, and 2000), dynamic contrast enhanced imaging, and T2-weighted imaging. T2 weighted images were intensity normalized and apparent diffusion coefficient maps were calculated. The dynamic contrast enhanced data was used to calculate the percent change in signal intensity before and after contrast injection. All images were aligned to the T2 weighted image. Robotic prostatectomy was performed 2 weeks after image acquisition. Prostate samples were sliced using a 3D printed slicing jig matching the slice profile of the T2 weighted image. Whole mount samples at 10 μm thickness were taken, hematoxylin and eosin stained, digitized, and annotated by a board certified pathologist. A total of 210 slides were included in this study. Lumen and epithelium were automatically segmented using a custom algorithm written in MATLAB. The algorithm was validated by comparing manual to automatic segmentation on 18 samples. Slides were aligned with the T2 weighted image using a nonlinear control point warping technique. Lumen and epithelium density and the expert annotation were subsequently transformed into MRI space. Co-registration was validated by applying a known warp to tumor masks noted by the pathologist and control point warping the whole mount slide to match the transform. Overlap was measured using a DICE coefficient. A learning curve was generated to determine the optimal number of patients to train the algorithm on. A PLS algorithm was trained on 150 random permutations of patients incrementing from 1 to 29 patients. Slides were stratified such that all slides from a single patient were in the same cohort. Three cohorts were generated, with tumor burden balanced across all cohort. A PLS algorithm was trained on 2 independent training sets (cohorts 1 and 2) and applied to cohort 3. The input vector consisted of MRI values and the target variable was lumen and epithelium density. The algorithm was trained lesion-wise. Trained PiCT models were applied to the test cohort voxel-wise to generate 2 new image contrasts. Mean lesion values were compared between high grade, low grade, and healthy tissue using an ANOVA. An ROC analysis was performed lesion-wise on the test set. RESULTS/ANTICIPATED RESULTS: Results: The segmentation accuracy validation revealed R=0.99 and R=0.72 (p<0.001) for lumen and epithelium, respectively. The co-registration accuracy revealed a 94.5% overlap. The learning curve stabilized at 10 patients with a root mean square error of 0.14, thus the size of the 2 independent training cohorts was set to 10, leaving 19 for the test cohort. DISCUSSION/SIGNIFICANCE OF IMPACT: We present a technique for combining radiology and pathology with machine learning for generating predictive cytological topography (PiCT) maps of cellularity and lumen density prostate. The voxel-wise approach to mapping cellular features generates 2 new interpretable image contrasts, which can potentially increase confidence in diagnosis or guide biopsy and radiation treatment.
Introduction: Electrocardiographic (ECG) rhythms are used during resuscitation (ACLS) to guide resuscitation, and often to determine futility. Survival rates to hospital discharge have been reported to be higher for patients with PEA than asystole in out-of-hospital cardiac arrest. This study examines how well the initial ECG cardiac rhythm represents actual cardiac activity as determined by point of care ultrasound (PoCUS). Methods: A database review was completed for patients arriving to a tertiary ED in asystole or PEA arrest, from 2010 to 2014. Patients under 19y or with a previous DNR were excluded. Patients were grouped into those with cardiac activity (PEA) and asystole on ECG; as well as whether cardiac activity was seen on PoCUS during the arrest. Data was analyzed for visualized cardiac activity on PoCUS. Results: 186 patients met the study criteria. Those with asystole on ECG were more likely to have no cardiac activity than those with PEA (Odds 7.21 for initial PoCUS; 5.45 for any PoCUS). The sensitivity of ECG rhythm was 80.49% and 82.12%, specificity was 77.91% and 54.28%, positive predictive value was 94.28% and 88.57%, and negative predictive value was 30.43% and 41.30% for cardiac activity on initial PoCUS and on any PoCUS respectively. The positive and negative likelihood ratios for ECG were 3.47 and 0.25 for activity on initial PoCUS. The positive and negative likelihood ratios for activity on any PoCUS were 1.78 and 0.33. Conclusion: Our results suggest that although most patients with asystole on ECG demonstrate no cardiac activity, a small number actually had activity on PoCUS. This supports the use of PoCUS during cardiac arrest, in addition to ECG, to identify patients with ongoing mechanical cardiac activity.
Introduction: The decision as to whether to end resuscitation for pre-hospital cardiac arrest (CA) patients in the field or in the emergency department (ED) is commonly made based upon standard criteria. We studied the reliability of several easily determined criteria as predictors of resuscitation outcomes in a population of adults in CA transported to the ED. Methods: A retrospective database and chart analysis was completed for patients arriving to a tertiary ED in cardiac arrest, between 2010 and 2014. Patients were excluded if aged under 19. Multiple data were abstracted from charts using a standardized form. Regression analysis was used to compare criteria that predicted return of spontaneous circulation (ROSC) and survival to hospital admission (SHA). Results: 264 patients met the study inclusion criteria. Logistic regression was used to identify predictors of ROSC and SHA. The criteria that emerged as significant predictors for ROSC included; longer ED resuscitation time (Odds ratio 1.11 (1.06- 1.18)), witnessed arrest (Odds ratio 9.43 (2.58- 53.0)) and having an initial cardiac rhythm of Pulseless Electrical Activity (Odds Ratio 3.23 (1.07-9.811)) over Asystole. Receiving point of care ultrasound (PoCUS; Odds ratio 0.22 (0.07-0.69)); and having an initial cardiac rhythm of Pulseless Electrical Activity (Odds Ratio 4.10 (1.43-11.88)) were the significant predictors for SHA. Longer times for ED resuscitation was close to reaching significance for predicting SHA Conclusion: Our results suggest that both fixed and adaptable factors, including increasing resuscitation time, and PoCUS use in the ED were important independent predictors of successful resuscitation. Several commonly used criteria were unreliable predictors.
The coronal field typically reorganizes itself to attain a force-free field configuration. We have evaluated the power law index of the energy distribution f(E) = f0E−α by using a model of relaxation incorporating different profile functions of winding number distribution f(w) based on braided topologies. We study the radio signatures that occur in the solar corona using the radio data obtained from the Gauribidanur Radio Observatory (IIA) and extract the power law index by using the Statistic-sensitive nonlinear iterative peak clipping (SNIP) algorithm. We see that the power law index obtained from the model is in good agreement with the calculated value from the radio data observation.
The properties of the acoustic modes are sensitive to magnetic activity. The unprecedented long-term Kepler photometry, thus, allows stellar magnetic cycles to be studied through asteroseismology. We search for signatures of magnetic cycles in the seismic data of Kepler solar-type stars. We find evidence for periodic variations in the acoustic properties of about half of the 87 analysed stars. In these proceedings, we highlight the results obtained for two such stars, namely KIC 8006161 and KIC 5184732.
The Solar Mean Magnetic Field (SMMF) is generally defined as the disc-averaged line-of-sight (LOS) magnetic field on the sun. The role of the active regions and the large-scale magnetic field structures (also called the background) has been debated over the past few decades to understand whether the origin of the SMMF is either due to the active regions or the background. We, in this paper have investigated contribution of sunspots, plages, networks and the background towards the variability of the SMMF using the datasets from the SDO-AIA & HMI, and found that 89% of the SMMF is due to the background whereas the remaining 11% originates from the active regions and the networks.
Sunspots are the most obvious and high contrast observable feature of solar magnetic activity in the photosphere. The morphological and kinematic behavior of sunspots on the solar surface need to be studied over a long time period to understand solar magnetic activity. For this, it is important to understand the long term emergence patterns, and developments, decay of the sunspots on the solar surface over many cycles. The long time sequence of the Kodaikanal white-light images provide a consistent data set for this study. The digitized images were calibrated for relative plate density and aligned in such a way that the solar north is in upward direction. A sunspot detection technique was used to identify the sunspots on the digitized images. In addition to describing the calibration procedure and availability of the data, we here present results on the sunspot, umbral and penumbral area measurements and their variation with time.
We have analyzed the data on yearly mean international sunspot number (RZ) during the period 1610 – 2015 and orbital positions (ecliptic longitudes) of the giant planets in each 10-day interval during the period 1600 – 2099. We determined mean absolute difference (
) of the orbital positions of the giant planets in each interval. We find that there exits a good correlation between cycle amplitude (RM, i.e. the maximum value of RZ) and the value of
at cycle maximum, suggesting that on longer time scales low/high solar activity associated with less/large spread in orbital positions of the giant planets (i.e. with a low/high value of
A number of complex systems arising in diverse disciplines may have certain quantitative features that are surprisingly similar which are classified under the paradigm of “universality”. The non-extensive Tsallis stastical mechanics and Lévy flight patterns provide a novel basis for analyzing non-equilibrium complex systems that may exhibit long-range correlations. The present work studies the scope of employing non-extensive Gutenberg-Richter (G-R) type law for the magnitude distribution of energy of solar wind, in order to investigate the existence of a universal behavior as well as to compute the relations of degree of non-extensivity and Lévy statistics in solar wind turbulence with heliographic distance during different solar cycles.
We study 30 solar flare events associated with coronal mass ejections (CMEs) that produced geomagnetic storms as measured in Dst index. Our study reveals that the magnitude of Dst index is significantly associated with maximum solar wind speed, peak of Bz component of the IMF and the product of peak Bz and solar wind speed (minimum and maximum). From our investigations, it can be inferred that CMEs travel with higher speed in the beginning and their speed reduces as they reach L1 location.
Both direct observations and reconstructions from various datasets, suggest that conditions were radically different during the Maunder Minimum (MM) than during the space era. Using an MHD model, we develop a set of feasible solutions to infer the properties of the solar wind during this interval. Additionally, we use these results to drive a global magnetospheric model. Finally, using the 2008/2009 solar minimum as an upper limit for MM conditions, we use results from the International Reference Ionosphere (ILI) model to speculate on the state of the ionosphere. The results describe interplanetary, magnetospheric, and ionospheric conditions that were substantially different than today. For example: (1) the solar wind density and magnetic field strength were an order of magnitude lower; (2) the Earth’s magnetopause and shock standoff distances were a factor of two larger; and (3) the maximum electron density in the ionosphere was substantially lower.
Here we report our recent prediction of the solar cycle 25 based on a newly developed scheme, which is used to investigate the predictability of the solar cycle over one cycle. The scheme is a combination of the empirical properties of solar cycles and a surface flux transport model to get the possible axial dipole moment evolution at a few years before cycle minimum, by which to get the subsequent cycle strength based on the correlation between the axial dipole moment at cycle minimum and the subsequent cycle strength. We apply this scheme to predict the large-scale field evolution since 2018 onwards. The results show that the northern polar field will keep on increasing, while the southern polar field almost keeps flat by the end of cycle 24. This leads to the cycle 25 strength of 125 ± 32, which is about 10% stronger than cycle 24 according to the mean value.
Our understanding of stellar dynamos has largely been driven by the phenomena we have observed of our own Sun. Yet, as we amass longer-term datasets for an increasing number of stars, it is clear that there is a wide variety of stellar behavior. Here we briefly review observed trends that place key constraints on the fundamental dynamo operation of solar-type stars to fully convective M dwarfs, including: starspot and sunspot patterns, various magnetism-rotation correlations, and mean field flows such as differential rotation and meridional circulation. We also comment on the current insight that simulations of dynamo action and flux emergence lend to our working knowledge of stellar dynamo theory. While the growing landscape of both observations and simulations of stellar magnetic activity work in tandem to decipher dynamo action, there are still many puzzles that we have yet to fully understand.
Coronal Mass Ejections (CMEs) contribute to the perturbation of solar wind in the heliosphere. Thus, depending on the different phases of the solar cycle and the rate of CME occurrence, contribution of CMEs to solar wind parameters near the Earth changes. In the present study, we examine the long term occurrence rate of CMEs, their speeds, angular widths and masses. We attempt to find correlation between near sun parameters of the CMEs with near the Earth measurements. Importantly, we attempt to find what fraction of the averaged solar wind mass near the Earth is provided by the CMEs during different phases of the solar cycles.
Full disk magnetic field measurements of the photosphere and chromosphere have been performed at National Solar Observatory (NSO), USA for many decades. Here we briefly describe recent upgrades made to this synoptic observing program. In particular, we present the full Stokes polarimetry observations made using the chromospheric Ca II 854.2 nm spectral line. These new observations have the potential to probe vector nature of magnetic field in the chromosphere above the active regions and provide improved estimates of magnetic free-energy, which is released during flares and coronal mass ejections (CMEs). We emphasize that these observations could improve estimates of polar fields, as compared to photospheric observations, due to magnetic field expansion in higher layers and perspective effect near the polar regions. The global coronal potential field models and solar wind speed estimates depend critically on polar field measurements.