V496 Scuti: An Fe II nova with dust shell accompanied by CO emission

We present near-infrared and optical observations of the nova V496 Scuti 2009 covering various phases - pre-maximum, early decline and nebular - during the first 10 months of its discovery followed by limited observations in early part of 2011 April. The spectra follow the evolution of the nova when the lines had strong P Cygni profiles to a phase dominated by prominent emission lines. The notable feature of the near-IR spectra in the early decline phase is the rare presence of first overtone bands of carbon monoxide in emission. Later about 150 days after the peak brightness the IR spectra show clear dust formation in the expanding ejecta. Dust formation in V496 Sct is consistent with the presence of lines of elements with low ionization potentials like Na and Mg in the early spectra and the detection of CO bands in emission. The light curve shows a slow rise to the maximum and a slow decline indicating a prolonged mass loss. This is corroborated by the strengthening of P Cygni profiles during the first 30 days. In the spectra taken close to the optical maximum brightness, the broad and single absorption component seen at the time of discovery is replaced by two sharper components. During the early decline phase two sharp dips that show increasing outflow velocities are seen in the P Cygni absorption components of Fe II and H I lines. The spectra in 2010 March showed the onset of the nebular phase. Several emission lines display saddle-like profiles during the nebular phase. In the nebular stage the observed fluxes of [O III] and H-beta lines are used to estimate the electron number densities and the mass of the ejecta. The optical spectra show that the nova evolved in the P_fe A_o spectral sequence. The physical conditions in the ejecta are estimated. The absolute magnitude and the distance to the nova are estimated to be M_V = -7.0 +/- 0.2 and d = 2.9 +/- 0.3 kpc respectively.Comment: 14 pages, 9 figures and 6 Tables, Accepted for Publication in MNRA

The Evolution of Mentorship Capacity Development in Low- and Middle-Income Countries: Case Studies from Peru, Kenya, India, and Mozambique.

Following the Fogarty International Center-supported "Mentoring the Mentors" workshops in South America, Africa, and Asia, approaches and guidelines for mentorship at institutions within these low- and middle-income country (LMIC) contexts, appropriate for the respective regional resources and culture, were implemented. Through the presentation of case studies from these three geographic regions, this article illustrates the institutional mentorship infrastructure before the workshop and the identified gaps used to implement strategies to build mentorship capacity at the Universidad Peruana Cayetano Heredia (Peru), Kenya Medical Research Institute (Kenya), Saint John's Research Institute (India), and Eduardo Mondlane University (Mozambique). These case studies illustrate three findings: first, that mentorship programs in LMICs have made uneven progress, and institutions with existing programs have exhibited greater advancement to their mentoring capacity than institutions without formal programs before the workshops. Second, mentoring needs assessments help garner the support of institutional leadership and create local ownership. Third, developing a culture of mentorship that includes group mentoring activities at LMIC institutions can help overcome the shortage of trained mentors. Regardless of the stage of mentoring programs, LMIC institutions can work toward developing sustainable, culturally effective mentorship models that further the partnership of early career scientists and global health

Force trace characteristics in anterior cruciate ligament deficient and uninjured knees during a maximal isometric task

Anterior cruciate ligament (ACL) deficiency has been shown to alter the muscle function of the leg. This study aimed to investigate differences in force trace characteristics of a maximal isometric task between ACL deficient and uninjured knees. Six ACL injured and uninjured participants completed maximal adduction, extension, and flexion isometric contractions. Peak, mean, standard deviation (SD), coefficient of variance (CV), frequency and signal regularity were calculated for all trials. Mean flexion force was larger in the ACL intact (0.91 N/kg) compared to their deficient (0.67 N/kg; p<0.05) knee. SD, CV and frequency composition of the extension trial differed between limbs in the uninjured (p<0.05). Analysis of variability, frequency and regularity of a signal may provide information on the function of the knee

Are providers prepared for genomic medicine: interpretation of Direct-to-Consumer genetic testing (DTC-GT) results and genetic self-efficacy by medical professionals

Background: Precision medicine is set to deliver a rich new data set of genomic information. However, the number of certified specialists in the United States is small, with only 4244 genetic counselors and 1302 clinical geneticists. We conducted a national survey of 264 medical professionals to evaluate how they interpret genetic test results, determine their confidence and self-efficacy of interpreting genetic test results with patients, and capture their opinions and experiences with direct-to-consumer genetic tests (DTC-GT). Methods: Participants were grouped into two categories, genetic specialists (genetic counselors and clinical geneticists) and medical providers (primary care, internists, physicians assistants, advanced nurse practitioners, etc.). The survey (full instrument can be found in the Additional file 1) presented three genetic test report scenarios for interpretation: a genetic risk for diabetes, genomic sequencing for symptoms report implicating a potential HMN7B: distal hereditary motor neuropathy VIIB diagnosis, and a statin-induced myopathy risk. Participants were also asked about their opinions on DTC-GT results and rank their own perceived level of preparedness to review genetic test results with patients. Results: The rates of correctly interpreting results were relatively high (74.4% for the providers compared to the specialist’s 83.4%) and age, prior genetic test consultation experience, and level of trust assigned to the reports were associated with higher correct interpretation rates. The self-selected efficacy and the level of preparedness to consult on a patient’s genetic results were higher for the specialists than the provider group. Conclusion: Specialists remain the best group to assist patients with DTC-GT, however, primary care providers may still provide accurate interpretation of test results when specialists are unavailable

Eimeria species occurrence varies between geographic regions and poultry production systems and may influence parasite genetic diversity

Coccidiosis is one of the biggest challenges faced by the global poultry industry. Recent studies have highlighted the ubiquitous distribution of all Eimeria species which can cause this disease in chickens, but intriguingly revealed a regional divide in genetic diversity and population structure for at least one species, Eimeria tenella. The drivers associated with such distinct geographic variation are unclear, but may impact on the occurrence and extent of resistance to anticoccidial drugs and future subunit vaccines. India is one of the largest poultry producers in the world and includes a transition between E. tenella populations defined by high and low genetic diversity. The aim of this study was to identify risk factors associated with the prevalence of Eimeria species defined by high and low pathogenicity in northern and southern states of India, and seek to understand factors which vary between the regions as possible drivers for differential genetic variation. Faecal samples and data relating to farm characteristics and management were collected from 107 farms from northern India and 133 farms from southern India. Faecal samples were analysed using microscopy and PCR to identify Eimeria occurrence. Multiple correspondence analysis was applied to transform correlated putative risk factors into a smaller number of synthetic uncorrelated factors. Hierarchical cluster analysis was used to identify poultry farm typologies, revealing three distinct clusters in the studied regions. The association between clusters and presence of Eimeria species was assessed by logistic regression. The study found that large-scale broiler farms in the north were at greatest risk of harbouring any Eimeria species and a larger proportion of such farms were positive for E. necatrix, the most pathogenic species. Comparison revealed a more even distribution for E. tenella across production systems in south India, but with a lower overall occurrence. Such a polarised region- and system-specific distribution may contribute to the different levels of genetic diversity observed previously in India and may influence parasite population structure across much of Asia and Africa. The findings of the study can be used to prioritise target farms to launch and optimise appropriate anticoccidial strategies for long-term control

The associations of everyday and major discrimination exposure with violence and poor mental health outcomes during the COVID-19 pandemic

Research on discrimination and risks for violence and mental health issues under the pandemic is notably absent. We examined the relative effects of perceived everyday discrimination (e.g., poorer service, disrespectful treatment in a typical week) and major experiences of race-based discrimination (e.g., racial/ethnic discrimination in housing or employment at any point in the lifetime) on experiences of violence and the PHQ-4 assessment of symptoms of depression and anxiety under the pandemic. We analyzed state-representative cross-sectional survey data from California adults (N = 2114) collected in March 2021. We conducted multivariate regression models adjusting for age, race/ethnicity, gender, sexual identity, income, and disability. One in four Californians (26.1%) experienced everyday discrimination in public spaces, due most often to race/ethnicity and gender. We found that everyday discrimination was significantly associated with past year physical violence (single form Adjusted Odds Ratio [AOR] 5.0, 95% CI 2.5–10.3; multiple forms AOR 2.6, 95% CI 1.1–5.8), past year sexual violence (multiple forms AOR 2.5, 95% CI 1.4–4.4), and mental health symptoms (e.g., severe symptoms, multiple forms AOR 3.3, 95% CI 1.6–6.7). Major experiences of race-based discrimination (reported by 10.0% of Californians) were associated with past year sexual violence (AOR 2.0, 95% CI 1.1–3.8) and severe mental health symptoms (AOR 2.7, 95% CI 1.2–6.2). Non-race-based major discrimination (reported by 23.9% of Californians) was also associated with violence and mental health outcomes Everyday discrimination, more than major experiences of discrimination, was associated with higher risk for violence and poor mental health outcomes during the pandemic. Non-race-based forms of major discrimination independently were also associated with these negative outcomes. Findings indicate that efforts to reduce and ultimately eliminate discrimination should be a focus of public health and COVID-19 rebuilding efforts

On Correlated Knowledge Distillation for Monitoring Human Pose with Radios

In this work, we propose and develop a simple experimental testbed to study the feasibility of a novel idea by coupling radio frequency (RF) sensing technology with Correlated Knowledge Distillation (CKD) theory towards designing lightweight, near real-time and precise human pose monitoring systems. The proposed CKD framework transfers and fuses pose knowledge from a robust "Teacher" model to a parameterized "Student" model, which can be a promising technique for obtaining accurate yet lightweight pose estimates. To assure its efficacy, we implemented CKD for distilling logits in our integrated Software Defined Radio (SDR)-based experimental setup and investigated the RF-visual signal correlation. Our CKD-RF sensing technique is characterized by two modes -- a camera-fed Teacher Class Network (e.g., images, videos) with an SDR-fed Student Class Network (e.g., RF signals). Specifically, our CKD model trains a dual multi-branch teacher and student network by distilling and fusing knowledge bases. The resulting CKD models are then subsequently used to identify the multimodal correlation and teach the student branch in reverse. Instead of simply aggregating their learnings, CKD training comprised multiple parallel transformations with the two domains, i.e., visual images and RF signals. Once trained, our CKD model can efficiently preserve privacy and utilize the multimodal correlated logits from the two different neural networks for estimating poses without using visual signals/video frames (by using only the RF signals)