Population Ecology of Northern Bobwhite (\u3ci\u3eColinus virginianus\u3c/i\u3e) on a Reclaimed Surface Mine

Direct linkages between habitat management and northern bobwhite (Colinus virginianus) survival are not well documented; therefore, we implemented an experiment to evaluate those responses. We conducted our experiment on a reclaimed surface mine, a novel landscape where conditions were considered sub-optimal for bobwhite. Nonetheless, these areas have great potential for contributing to bobwhite conservation. Our objectives were to determine if habitat management could improve (1) seasonal and (2) nest survival, how (3) multi-scale habitat contributed to seasonal and nest survival, and (4) conduct life stage simulation analyses (LSA) to determine which vital rates were affecting population growth rate. Research was conducted on Peabody Wildlife Management Area in western Kentucky. Two units of the site (Sinclair and Ken, 1471 and 1853 ha, respectively) served as replicates and were each randomly divided into a treatment (disking, burning, herbicide application) and control. Treatments were applied October 2009 - September 2013. We detected evidence that treatments may have improved summer survival (Part II). However, we found no evidence that treatments had an impact on nest survival (Part III). Among habitat covariates, litter depth (β [beta] = -0.387, CI = -0.5809, -0.1930) was the most influential covariate on survival (Part II). Pooled seasonal survival rates differed between winter (S = 0.281, SE = 0.022) and summer (S = 0.148, SE = 0.015). Nest survival (0.352 ± 0.037, 23-day period) was low compared to other studies and was not related to habitat (Part III). Instead, nest age (β = 0.641, CI = 0.372-0.911) and nest initiation date (β = 0.022, 95% CI = 0.001-0.043) influenced (positive) nest survival. Our LSA revealed that clutch size (r2[coefficient of determination] = 0.384), followed by hatching success (r² = 0.207), and nest survival (r² = 0.141)explained most variation in λ [lambda] (Part IV). Total fecundity explained 94% of the variation in λ.It appears that summer survival and elements of fecundity may be limiting factors on our site. Additional experiments across a wider range of habitat conditions may be required to determine management intensity and duration thresholds required to elicit greater changes in survival for bobwhite populations

Randomised crossover trial of rate feedback and force during chest compressions for paediatric cardiopulmonary resuscitation

Objective: To determine the effect of visual feedback on rate of chest compressions, secondarily relating the forces used. / Design: Randomised crossover trial. / Setting: Tertiary teaching hospital. / Subjects: Fifty trained hospital staff. / Interventions: A thin sensor-mat placed over the manikin's chest measured rate and force. Rescuers applied compressions to the same paediatric manikin for two sessions. During one session they received visual feedback comparing their real-time rate with published guidelines. / Outcome measures: Primary: compression rate. Secondary: compression and residual forces. / Results: Rate of chest compressions (compressions per minute (compressions per minute; cpm)) varied widely (mean (SD) 111 (13), range 89–168), with a fourfold difference in variation during session 1 between those receiving and not receiving feedback (108 (5) vs 120 (20)). The interaction of session by feedback order was highly significant, indicating that this difference in mean rate between sessions was 14 cpm less (95% CI −22 to −5, p=0.002) in those given feedback first compared with those given it second. Compression force (N) varied widely (mean (SD) 306 (94); range 142–769). Those receiving feedback second (as opposed to first) used significantly lower force (adjusted mean difference −80 (95% CI −128 to −32), p=0.002). Mean residual force (18 N, SD 12, range 0–49) was unaffected by the intervention. / Conclusions: While visual feedback restricted excessive compression rates to within the prescribed range, applied force remained widely variable. The forces required may differ with growth, but such variation treating one manikin is alarming. Feedback technologies additionally measuring force (effort) could help to standardise and define effective treatments throughout childhood

Defining the Newborn Blood Spot Screening Reference Interval for TSH: Impact of Ethnicity

CONTEXT: There is variability in the congenital hypothyroidism (CH) newborn screening TSH cutoff across the United Kingdom. OBJECTIVE: To determine the influences of year, gender, and ethnicity on screening variability and examine whether there is an optimal operational TSH cutoff. DESIGN AND SETTING: Single center, retrospective population study using blood spot TSH cards received by the Great Ormond Street Hospital Screening Laboratory between 2006 and 2012. PATIENTS: A total of 824 588 newborn screening blood spot TSH cards. INTERVENTION: Blood spot TSH results were recorded with demographic data including the Ethnic Category Code. MAIN OUTCOME MEASURES: The proportions of samples exceeding different TSH cutoffs, ranked by ethnicity. RESULTS: The proportion of samples exceeding the TSH cutoff increased over time, with the cutoff at 4 mU/L, but not at 6 mU/L. There was a consistent trend with ethnicity, irrespective of cutoff, with the odds ratio of exceeding the TSH cutoff lowest (∼1.0) in White babies, higher in Pakistani and Bangladeshi (>2.0), and highest in Chinese (>3.5). CONCLUSIONS: The blood spot TSH screening data demonstrate a clear ranking according to ethnicity for differences in mean TSH. This suggests that there may be ethnic differences in thyroid physiology. Ethnic diversity within populations needs to be considered when establishing and interpreting screening TSH cutoffs

Particle Sensor Using Solidly Mounted Resonators

This paper describes the development of a novel particle sensing system employing zinc oxide based solidly mounted resonator (SMR) devices for the detection of airborne fine particles (i.e., PM2.5 and PM10). The system operates in a dual configuration in which two SMR devices are driven by Colpitts-type oscillators in a differential mode. Particles are detected by the frequency shift caused by the mass of particles present on one resonator with while the other acts as a reference channel. Experimental validation of the system was performed inside an environmental chamber using a dust generator with the particles of known size and concentration. A sensor sensitivity of 4.6 Hz per μg/m3 was demonstrated for the SMRs resonating at a frequency of 970 MHz. Our results demonstrate that the SMR-based system has the potential to be implemented in CMOS technology as a low-cost, miniature smart particle detector for the real-time monitoring of airborne particles

Learning dispositif and emotional attachment:a preliminary international investigation

This research investigated the significance of learning dispositif (LD) and emotional attachment (EA) on perceived learning success (LS) across a diaspora of Western, Russian, Asian, Middle Eastern and Chinese student cohorts. Foucault’s LD captures the disparate socio-cultural contexts, institutional milieus and more or less didactic teaching styles that moderate learning. EA is a multi-dimensional notion involving affective bonds that emerged in child psychology and spread to marketing and other fields. The sequential explanatory research reviewed the learning and EA literatures and generated an LD–EA framework to structure the quantitative phase of its mixed investigations. In 2017 and 2018, the research collected 150 responses and used a range of statistical techniques for quantitative analysis. It found that LS varied significantly across cohorts, intimating that dispositifs influence learning. Nonparametric analysis suggested that EA also influenced learning, but regressions were inconclusive. Exploratory techniques hint at a dynamic mix of emotional or cognitive motivations during the student learning journey, involving structural breaks in student/instructor relationships. Cluster analysis identified distinct student groupings, linked to years of learning. Separately, qualitative analysis of open-ended survey questions and expert interviews intimates that frequent teacher interactions can increase EA. The synthesis of quantitative with qualitative results and pedagogical reflection suggests that LD and EA both influence learning in a complex, dynamic system. The key constituents for EA are Affection, Connection, Social Presence (SP), Teaching Presence (TP) and Flow but student emotional engagement is conditioned by the socio-cultural milieu (LD) and associated factors like relationships and trust. Unlike in the Community of Learning framework, in the EA framework Cognitive Presence (CP) is an outcome of the interaction between these EA constituents, associated factors and the socio-cultural milieu. Finally, whilst awareness of culture and emotions is a useful pedagogical consideration, learning mainstays remain inclusive educational systems that identify student needs and support well-designed programmes. Within these, scaffolded modules should include a variety of engaging learning activities with non-threatening formative and trustworthy summative feedback. We acknowledge some statistical study limitations, but its tentative findings make a useful preliminary contribution

Job Market Signaling of Relative Position, or Becker Married to Spence

This paper considers a matching model of the labor market where workers, who have private information on their quality, signal to firms that also differ in quality. Signals allow assortative matching in which the highest-quality workers send the highest signals and are hired by the best firms. Matching is considered both when wages are rigid (nontransferable utility) and when they are fully flexible (transferable utility). In both cases, equilibrium strategies and payoffs depend on the distributions of worker and firm types. This is in contrast to separating equilibria of the standard model, which do not respond to changes in supply or demand. With sticky wages, despite incomplete information, equilibrium investment in education by low-ability workers can be inefficiently low, and this distortion can become worse in a more competitive environment. In contrast, with flexible wages, greater competition improves efficiency

Unique chemical reactivity of His-21 of CRM-197, a mutated diphtheria toxin

AbstractCRM-197 is a mutated diphtheria toxin (63 000 Da) widely used as a carrier protein of conjugated vaccines. Among the 14 histidines of CRM-197, His-21 was found to be modified selectively with iodoacetamide based reagents. This finding suggests a simplified method for the preparation of conjugate vaccines crosslinked to CRM-197. A bifunctional iodoacetamide, N,N′-(2-hydroxy-1,3-propanediyl)-bis-[2-iodoacetamide] (I-CH2-CONH-CH2-CH(OH)-CH2-NHCO-CH2-I) (HPBIA), was synthesized and allowed to react with CRM-197. In the alkaline buffer of pH 8.0–8.4, HPBIA was shown to react and intra-bridge His-21 and Lys-24 of CRM-197 sequentially. At lower pH (7.1–7.5) in the phosphate buffer, the reactivity of Lys-24 toward HPBIA was suppressed drastically. Under these conditions, His-21 could be specifically labeled with HPBIA. Initial experiments have demonstrated that HPBIA modified CRM-197 is able to crosslink to a cysteine-containing peptide. These results offer a potential route for improving the homogeneity of CRM-197 based protein-peptide as well as protein-polysaccharide conjugates

Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI

BACKGROUND: Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. We apply this strategy to train a deep learning (DL) model to classify the anatomical position of CMR images. This allows the automated removal of slices that do not contain the left ventricular (LV) myocardium. METHODS: Anonymised LV short-axis slices from 300 random scans (3,552 individual images) were extracted. Each image's anatomical position relative to the LV was labelled using two different strategies performed for 5 hours each: (I) 'one-image-at-a-time': each image labelled according to its position: 'too basal', 'LV', or 'too apical' individually by one of three experts; and (II) 'multiple-image-ranking': three independent experts ordered slices according to their relative position from 'most-basal' to 'most apical' in batches of eight until each image had been viewed at least 3 times. Two convolutional neural networks were trained for a three-way classification task (each model using data from one labelling strategy). The models' performance was evaluated by accuracy, F1-score, and area under the receiver operating characteristics curve (ROC AUC). RESULTS: After excluding images with artefact, 3,323 images were labelled by both strategies. The model trained using labels from the 'multiple-image-ranking strategy' performed better than the model using the 'one-image-at-a-time' labelling strategy (accuracy 86% vs. 72%, P=0.02; F1-score 0.86 vs. 0.75; ROC AUC 0.95 vs. 0.86). For expert clinicians performing this task manually the intra-observer variability was low (Cohen's κ=0.90), but the inter-observer variability was higher (Cohen's κ=0.77). CONCLUSIONS: We present proof of concept that, given the same clinician labelling effort, comparing multiple images side-by-side using a 'multiple-image-ranking' strategy achieves ground truth labels for DL more accurately than by classifying images individually. We demonstrate a potential clinical application: the automatic removal of unrequired CMR images. This leads to increased efficiency by focussing human and machine attention on images which are needed to answer clinical questions