Evaluating Hunting Success of Pen-Reared and Wild Northern Bobwhite in a Reclaimed Kentucky Mineland

Northern bobwhites (Colinus virginianus) have experienced severe population declines across their distribution. In order to address population declines and to continue providing hunting opportunities, multi-state efforts have been undertaken to stabilize and restore bobwhite populations. Ongoing efforts using the National Bobwhite Conservation Initiative’s quail focus area approach have so far demonstrated success throughout Kentucky. However, population increases in the Peabody Bobwhite Focal Area, in western Kentucky, have not been correlated to increases in perceived hunter success. Consequently, some sportsmen question the effectiveness of focal area conservation. In response to hunter concerns, we tested dog hunting ability with wild and pen-reared bobwhites. We also measured evasive behaviors of wild bobwhite using radiotelemetry. During the 2013–2014 and 2014–2015 hunting seasons we conducted 114 dog trials. Dogs detected bobwhite during 46 of 59 (78.0%) pen-reared trials and 16 of 55 (29.1%) wild bird trials. When dogs did not detect wild quail, birds ran away 64.1% of the time and remained motionless 20.5% of the time. Using an information-theoretic approach, we determined that bird type (wild vs. pen-reared) had a significant effect on bird detection, with dogs 8.62 times more likely to detect pen-reared birds than wild birds. We recommend that hunters be informed about differences in dog detection rates between pen-reared and wild bobwhite so that public support needed for wild bobwhite restoration can persist

Temperature Assessment on a Reclaimed Surface Mine During Northern Bobwhite Breeding Season: Considerations for Habitat Management

Ground-level air temperatures were assessed within 4 distinct habitat areas on a managed reclaimed surface mine at Peabody Wildlife Management Area, Kentucky, 26 June–17 July 2015, during the northern bobwhite (Colinus virginianus) brood season. Habitat consisted of disked and nondisked areas of native grass and an invasive species, sericea lespedeza (Lespedeza cuneata). Disked areas offered more open space for bobwhite mobility and experienced higher average temperatures than nondisked sites. Although statistically significant, differences in air temperature between disked and nondisked areas were likely too small to have practical implications for bobwhite habitat management in Kentucky under current climatic conditions. This will likely change in the future as the regional climate warms and periods of excessive heat are more likely to occur. Consequently, managers may want to consider microclimate when making management decisions

The Palermo (Sicily) seismic cluster of September 2002 in the seismotectonic framework of the Tyrrhenian Sea-Sicily border area

The northern coast of Sicily and its offshore area represent a hinge zone between a sector of the Tyrrhenian Basin, characterized by the strongest crustal thinning, and the sector of the Sicilian belt which has emerged. This hinge zone is part of a wider W-E trending right-lateral shear zone, which has been affecting the Maghrebian Chain units since the Pliocene. Seismological and structural data have been used to evaluate the seismotectonic behavior of the area investigated here. Seismological analysis was performed on a data set of about 2100 seismic events which occurred between January 1988 and October 2002 in the Southern Tyrrhenian Sea. This paper focuses in particular on a set of data relating to the period from 6th September 2002, including both the main shock and about 540 aftershocks of the Palermo seismic sequence. The distribution of the hypocenters revealed the presence of two main seismogenic zones. The events of the easternmost zone may be related to the Ionian lithospheric slab diving beneath the Calabrian Arc. The seismicity associated with the westernmost zone is closely clustered around a sub-horizontal regression plane contained within the thinned Southern Tyrrhenian crust, hence suggesting that this seismogenic zone is strictly connected to the deformation field active within the hinge zone. On the basis of both structural and seismological data, the brittle deformation pattern is characterized by high-angle faults, mainly represented by transcurrent synthetic right-lateral and antithetic left-lateral systems, producing both restraining/uplifting and releasing/subsiding zones which accommodate strains developing in response to the current stress field (characterized by a maximum axis trending NW-SE) which has been active in the area since the Pliocene. The cluster of the seismic sequence which started with the 6th September 2002's main shock is located within the hinge zone. The distribution of the hypocenters relative to this sequence emphasizes the presence of a high-angle NE-SW-oriented deformation belt within which several shear surfaces are considered to be found sub-parallel to that established for the main shock. The kinematics of all these structures is consistent with a compressive right-lateral focal mechanism

The flux qubit revisited to enhance coherence and reproducibility

The scalable application of quantum information science will stand on reproducible and controllable high-coherence quantum bits (qubits). Here, we revisit the design and fabrication of the superconducting flux qubit, achieving a planar device with broad-frequency tunability, strong anharmonicity, high reproducibility and relaxation times in excess of 40 μs at its flux-insensitive point. Qubit relaxation times T₁ across 22 qubits are consistently matched with a single model involving resonator loss, ohmic charge noise and 1/f-flux noise, a noise source previously considered primarily in the context of dephasing. We furthermore demonstrate that qubit dephasing at the flux-insensitive point is dominated by residual thermal-photons in the readout resonator. The resulting photon shot noise is mitigated using a dynamical decoupling protocol, resulting in T₂≈85 μs, approximately the 2T₁ limit. In addition to realizing an improved flux qubit, our results uniquely identify photon shot noise as limiting T₂ in contemporary qubits based on transverse qubit–resonator interaction

Insulin resistance, intramyocellular lipid content, and plasma adiponectin in patients with type 1 diabetes

Insulin resistance is a key pathogenic factor of type 2 diabetes (T2DM); in contrast, in type 1 diabetes (T1DM) it is considered a secondary alteration. Increased intramyocellular lipid (IMCL) content accumulation and reduced plasma adiponectin were suggested to be pathogenic events of insulin resistance in T2DM. This study was designed to assess whether IMCL content and plasma adiponectin were also associated with the severity of insulin resistance in T1DM. We studied 18 patients with T1DM, 7 older and overweight/obese patients with T2DM, and 15 nondiabetic, insulin-resistant offspring of T2DM parents (OFF) and 15 healthy individuals (NOR) as appropriate control groups matched for anthropometric features with T1DM patients by means of the euglycemic hyperinsulinemic clamp combined with the infusion of [6,6-2H2]glucose and 1H magnetic resonance spectroscopy of the calf muscles. T1DM and T2DM patients showed reduced insulin-stimulated glucose metabolic clearance rate (MCR: 5.1 +/- 0.6 and 3.2 +/- 0.8 ml x kg(-1) min(-1)) similar to OFF (5.3 +/- 0.4 ml x kg(-1) x min(-1)) compared with NOR (8.5 +/- 0.5 ml x kg(-1) min(-1), P < 0.001). Soleus IMCL content was increased in T1DM (112 +/- 15 AU), T2DM (108 +/- 10 AU) and OFF (82 +/- 13 AU) compared with NOR (52 +/- 7 AU, P < 0.05) and the result was inversely proportional to the MCR (R2 = 0.27, P < 0.001); an association between IMCL content and Hb A1c was found only in T1DM (R2 = 0.57, P < 0.001). Fasting plasma adiponectin was reduced in T2DM (7 +/- 1 microg/ml, P = 0.01) and OFF (11 +/- 1 microg/ml, P = 0.03) but not in T1DM (25 +/- 6 microg/ml), whose plasma level was increased with respect to both OFF (P = 0.03) and NOR (16 +/- 2 microg/ml, P = 0.05). In conclusion, in T1DM, T2DM, and OFF, IMCL content was associated with insulin resistance, demonstrating that IMCL accretion is a marker of insulin resistance common to both primary genetically determined and secondary metabolic (chronic hyperglycemia) alterations. The increased adiponectin levels in insulin-resistant patients with T1DM, in contrast to the reduced levels found in patients with T2DM and in OFF, demonstrated that the relationship of adiponectin to insulin resistance in humans is still unclear

Mathematical modelling for antibiotic resistance control policy: do we know enough?

Background: Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base. Main text: One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy. Conclusions: We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research

Demonstration of tunable three-body interactions between superconducting qubits

Nonpairwise multi-qubit interactions present a useful resource for quantum information processors. Their implementation would facilitate more efficient quantum simulations of molecules and combinatorial optimization problems, and they could simplify error suppression and error correction schemes. Here we present a superconducting circuit architecture in which a coupling module mediates 2-local and 3-local interactions between three flux qubits by design. The system Hamiltonian is estimated via multi-qubit pulse sequences that implement Ramsey-type interferometry between all neighboring excitation manifolds in the system. The 3-local interaction is coherently tunable over several MHz via the coupler flux biases and can be turned off, which is important for applications in quantum annealing, analog quantum simulation, and gate-model quantum computation.Comment: 14 pages, 11 figure

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

Background: The previous COVID-19 lung diagnosis system lacks both scientific validation and the role of explainable artificial intelligence (AI) for understanding lesion localization. This study presents a cloud-based explainable AI, the “COVLIAS 2.0-cXAI” system using four kinds of class activation maps (CAM) models. Methodology: Our cohort consisted of ~6000 CT slices from two sources (Croatia, 80 COVID-19 patients and Italy, 15 control patients). COVLIAS 2.0-cXAI design consisted of three stages: (i) automated lung segmentation using hybrid deep learning ResNet-UNet model by automatic adjustment of Hounsfield units, hyperparameter optimization, and parallel and distributed training, (ii) classification using three kinds of DenseNet (DN) models (DN-121, DN-169, DN-201), and (iii) validation using four kinds of CAM visualization techniques: gradient-weighted class activation mapping (Grad-CAM), Grad-CAM++, score-weighted CAM (Score-CAM), and FasterScore-CAM. The COVLIAS 2.0-cXAI was validated by three trained senior radiologists for its stability and reliability. The Friedman test was also performed on the scores of the three radiologists. Results: The ResNet-UNet segmentation model resulted in dice similarity of 0.96, Jaccard index of 0.93, a correlation coefficient of 0.99, with a figure-of-merit of 95.99%, while the classifier accuracies for the three DN nets (DN-121, DN-169, and DN-201) were 98%, 98%, and 99% with a loss of ~0.003, ~0.0025, and ~0.002 using 50 epochs, respectively. The mean AUC for all three DN models was 0.99 (p &lt; 0.0001). The COVLIAS 2.0-cXAI showed 80% scans for mean alignment index (MAI) between heatmaps and gold standard, a score of four out of five, establishing the system for clinical settings. Conclusions: The COVLIAS 2.0-cXAI successfully showed a cloud-based explainable AI system for lesion localization in lung CT scans