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Policies that attempt to balance timber production with non-market values that forests provide are common across the United States. Such is the case in northern Maine, USA, where management of critical areas of mature softwood-dominated forest are regulated through the State’s primary wildlife management agency. We use a case study approach with qualitative and quantitative analyses to understand the persistent difficulties encountered by both forest and wildlife managers when implementing this policy. Interviews with foresters and wildlife biologists established the management parameters, and simulated management scenarios compared forest management outcomes with respect to both financial and wildlife habitat provision goals. The model results indicated that there are opportunities for comparable revenues within regulated habitat areas as without, although the returns varied due to legacy of previous management and species composition. More importantly, the interviews revealed that differing habitat metrics used by foresters and biologists are a barrier to communication and management planning, and thus also a barrier to effective policy implementation. We close with thoughts on the applicability of both the methods and results to other situations where an understanding of multiple-use forest policy implementation is desired.

Antimicrobial resistance is a global challenge requiring reliable surveillance data collection and use. Prior studies on resistance in Zambia depended on laboratory methods with limited standardization. Since 2015, the University Teaching Hospital (UTH) microbiology laboratory has used the Vitek 2 Compact (bioMerieux, Inc., Marcy-l’Étoile, France) for standardized identification and susceptibility testing. We conducted a cross-sectional study of 2019 bacterial isolates collected from July 2015 to April 2017 to identify bacterial causes of infections, their susceptibility to commonly used antibiotics at UTH, and develop hospital antibiograms with a multidisciplinary team using World Health Organization guidance. We found high levels of antibiotic resistance among Gram negative bacteria. Escherichia coli and Klebsiella pneumoniae were highly resistant to all antibiotics except amikacin and carbapenems. E. coli had susceptibilities of 42.4% to amoxicillin/clavulanic acid, 41.4% to ceftriaxone, 40.2% to ciprofloxacin, and 10.4% to trimethoprim/sulfamethoxazole (TMP/SMX). K. pneumoniae had susceptibilities of 20.7% to amoxicillin/clavulanic acid, 15.6% to ceftriaxone, 48.5% to ciprofloxacin, and 12.3% to TMP/SMX. The high resistance to 3rd generation cephalosporins indicates high rates of beta-lactamase production. This is information that clinicians need to inform clinical decision making and choice of empiric antibiotics and that UTH requires to inform antimicrobial stewardship such as improvements in antibiotic use.

Information plane analysis, describing the mutual information between the input and a hidden layer and between a hidden layer and the target over time, has recently been proposed to analyze the training of neural networks. Since the activations of a hidden layer are typically continuous-valued, this mutual information cannot be computed analytically and must thus be estimated, resulting in apparently inconsistent or even contradicting results in the literature. The goal of this paper is to demonstrate how information plane analysis can still be a valuable tool for analyzing neural network training. To this end, we complement the prevailing binning estimator for mutual information with a geometric interpretation. With this geometric interpretation in mind, we evaluate the impact of regularization and interpret phenomena such as underfitting and overfitting. In addition, we investigate neural network learning in the presence of noisy data and noisy labels.

Abstract Measurements of inclusive spectra and mean multiplicities of $$\pi ^\pm $$ π± , K$$^\pm $$ ± , p and $${\bar{\text {p}}}$$ p¯ produced in inelastic p + p interactions at incident projectile momenta of 20, 31, 40, 80 and 158 $$\text{ GeV }/c$$ GeV/c ($$\sqrt{s} = $$ s= 6.3, 7.7, 8.8, 12.3 and 17.3 $$\text{ GeV }$$ GeV , respectively) were performed at the CERN Super Proton Synchrotron using the large acceptance NA61/SHINE hadron spectrometer. Spectra are presented as function of rapidity and transverse momentum and are compared to predictions of current models. The measurements serve as the baseline in the NA61/SHINE study of the properties of the onset of deconfinement and search for the critical point of strongly interacting matter.

Abstract We present measurements of $$\rho ^0$$ ρ 0 , $$\omega $$ ω and K $$^{*0}$$ ∗ 0 spectra in $$\pi ^{-} + $$ π - + C production interactions at 158 $$\text{ GeV }{/}\text{ c }$$ GeV / c and $$\rho ^0$$ ρ 0 spectra at 350 $$\text{ GeV }{/}\text{ c }$$ GeV / c using the NA61/SHINE spectrometer at the CERN SPS. Spectra are presented as a function of the Feynman’s variable $$x_\text {F}$$ x F in the range $$0< x_\text {F} < 1$$ 0 < x F < 1 and $$0< x_\text {F} < 0.5$$ 0 < x F < 0.5 for 158 and 350 $$\text{ GeV }{/}\text{ c }$$ GeV / c respectively. Furthermore, we show comparisons with previous measurements and predictions of several hadronic interaction models. These measurements are essential for a better understanding of hadronic shower development and for improving the modeling of cosmic ray air showers.

The energy loss of ions in plasma is a challenging issue in inertial confinement fusion and many theoretical models exist on ion-stopping power. Here, the authors use laser-generated plasma probed by accelerator-produced ions in experiments to discriminate various ion stopping models near the Bragg peak.

The radio technique is a promising method for detection of cosmic-ray air showers of energies around 100PeV and higher with an array of radio antennas. Since the amplitude of the radio signal can be measured absolutely and increases with the shower energy, radio measurements can be used to determine the air-shower energy on an absolute scale. We show that calibrated measurements of radio detectors operated in coincidence with host experiments measuring air showers based on other techniques can be used for comparing the energy scales of these host experiments. Using two approaches, first via direct amplitude measurements, and second via comparison of measurements with air shower simulations, we compare the energy scales of the air-shower experiments Tunka-133 and KASCADE-Grande, using their radio extensions, Tunka-Rex and LOPES, respectively. Due to the consistent amplitude calibration for Tunka-Rex and LOPES achieved by using the same reference source, this comparison reaches an accuracy of approximately 10% – limited by some shortcomings of LOPES, which was a prototype experiment for the digital radio technique for air showers. In particular we show that the energy scales of cosmic-ray measurements by the independently calibrated experiments KASCADE-Grande and Tunka-133 are consistent with each other on this level. Keywords: Cosmic rays, Radio detection, LOPES, Tunka-Rex, Tunka-133, KASCADE-Grande

Cancer stem cells (CSCs) are proposed to be the cells that initiate tumorigenesis and maintain tumor development due to their self-renewal and multipotency properties. CSCs have been identified in many cancer types and are thought to be responsible for treatment resistance, metastasis, and recurrence. As such, targeting CSCs specifically should result in durable cancer treatment. One potential option for targeting CSCs is by manipulation of the renin-angiotensin system (RAS) and pathways that converge on the RAS with numerous inexpensive medications currently in common clinical use. In addition to its crucial role in cardiovascular and body fluid homeostasis, the RAS is vital for stem cell maintenance and differentiation and plays a role in tumorigenesis and cancer prevention, suggesting that these roles may converge and result in modulation of CSC function by the RAS. In support of this, components of the RAS have been shown to be expressed in many cancer types and have been more recently localized to the CSCs in some tumors. Given these roles of the RAS in tumor development, clinical trials using RAS inhibitors either singly or in combination with other therapies are underway in different cancer types. This review outlines the roles of the RAS, with respect to CSCs, and suggests that the presence of components of the RAS in CSCs could offer an avenue for therapeutic targeting using RAS modulators. Due to the nature of the RAS and its crosstalk with numerous other signaling pathways, a systems approach using traditional RAS inhibitors in combination with inhibitors of bypass loops of the RAS and other signaling pathways that converge on the RAS may offer a novel therapeutic approach to cancer treatment.

Proper axonal growth and guidance is essential for neuron differentiation and development. Abnormal neuronal development due to genetic or epigenetic influences can contribute to neurological and mental disorders such as Down syndrome, Rett syndrome, and autism. Identification of the molecular targets that promote proper neuronal growth and differentiation may restore structural and functional neuroplasticity, thus improving functional performance in neurodevelopmental disorders. Using differentiated human neuronal progenitor cells (NPCs) derived from induced pluripotent stem cells (iPSCs), the present study demonstrates that during early stage differentiation of human NPCs, neuron-targeted overexpression constitutively active Rac1 (Rac1CA) and constitutively active Cdc42 (Cdc42CA) enhance expression of P-Cav-1, T-Cav-1, and P-cofilin and increases axonal growth. Similarly, neuron-targeted over-expression of Cav-1 (termed SynCav1) increases axonal development by increasing both axon length and volume. Moreover, inhibition of Cav-1(Y14A) phosphorylation blunts Rac1/Cdc42-mediated both axonal growth and differentiation of human NPCs and SynCav1(Y14A)-treated NPCs exhibited blunted axonal growth. These results suggest that: (1) SynCav1-mediated dendritic and axonal growth in human NPCs is dependent upon P-Cav-1, (2) P-Cav-1 is necessary for proper axonal growth during early stages of neuronal differentiation, and (3) Rac1/Cdc42CA-mediated neuronal growth is in part dependent upon P-Cav-1. In conclusion, Cav-1 phosphorylation is essential for human neuronal axonal growth during early stages of neuronal differentiation.

Introduction: We assessed awareness of pre-exposure prophylaxis (PrEP) among HIV-negative Black and Latinx persons living in the Philadelphia Metropolitan Statistical Area. Methods: Using chi-square and Wilcoxon rank-sum tests, we analyzed data from the 2016 heterosexual cycle of the National HIV Behavioral Surveillance system to assess how sociodemographic factors, health care utilization, and risk behaviors affected PrEP awareness. Results: Participants (n = 472) were predominately Black, non-Hispanic (88.1%) with a median age of 41.5 years. Most participants reported having a usual source of medical care (92.1%) and seeing a medical provider within 12 months (87.0%). However, PrEP awareness was low in this sample (4.9%) and was lower among those who had a medical visit compared with those who had not ( P < .01). Conclusion: Current Centers for Disease Control and Prevention clinical guidelines suggest that providers counsel high-risk patients about PrEP. Our data suggest that this is not happening with people of color in Philadelphia. Interventions targeting medical providers working with HIV-risk people of color may be appropriate.

An overview of the multi-messenger capabilities of the Pierre Auger Observatory is presented. The techniques and performance of searching for Ultra-High Energy neutrinos, photons and neutrons are described. Some of the most relevant results are reviewed, such as stringent upper bounds that were placed to a flux of diffuse cosmogenic neutrinos and photons, bounds placed on neutrinos emitted from compact binary mergers that were detected by LIGO and Virgo during their first and second observing runs, as well as searches for high energy photons and neutrons from the Galactic center that constrain the properties of the putative Galactic PeVatron, observed by the H.E.S.S. collaboration. The observation of directional correlations between ultra-high energy cosmic rays and either high energy astrophysical neutrinos or specific source populations, weighted by their electromagnetic radiation, are also discussed. They constitute additional multi-messenger approaches aimed at identifying the sources of high energy cosmic rays.

We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an invaluable tool in the different treatment stages of diseases. Especially medical image segmentation plays a vital role, since segmentation is often the initial step in an image analysis pipeline. Since deep neural networks have made a large impact on the field of image processing in the past years, we use two different deep learning architectures to segment the urinary bladder. Both of these architectures are based on pre-trained classification networks that are adapted to perform semantic segmentation. Since deep neural networks require a large amount of training data, specifically images and corresponding ground truth labels, we furthermore propose a method to generate such a suitable training data set from Positron Emission Tomography/Computed Tomography image data. This is done by applying thresholding to the Positron Emission Tomography data for obtaining a ground truth and by utilizing data augmentation to enlarge the dataset. In this study, we discuss the influence of data augmentation on the segmentation results, and compare and evaluate the proposed architectures in terms of qualitative and quantitative segmentation performance. The results presented in this study allow concluding that deep neural networks can be considered a promising approach to segment the urinary bladder in CT images.

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.

We report a first measurement for ultrahigh energy cosmic rays of the correlation between the depth of shower maximum and the signal in the water Cherenkov stations of air-showers registered simultaneously by the fluorescence and the surface detectors of the Pierre Auger Observatory. Such a correlation measurement is a unique feature of a hybrid air-shower observatory with sensitivity to both the electromagnetic and muonic components. It allows an accurate determination of the spread of primary masses in the cosmic-ray flux. Up till now, constraints on the spread of primary masses have been dominated by systematic uncertainties. The present correlation measurement is not affected by systematics in the measurement of the depth of shower maximum or the signal in the water Cherenkov stations. The analysis relies on general characteristics of air showers and is thus robust also with respect to uncertainties in hadronic event generators. The observed correlation in the energy range around the ‘ankle’ at lg⁡(E/eV)=18.5–19.0 differs significantly from expectations for pure primary cosmic-ray compositions. A light composition made up of proton and helium only is equally inconsistent with observations. The data are explained well by a mixed composition including nuclei with mass A>4. Scenarios such as the proton dip model, with almost pure compositions, are thus disfavored as the sole explanation of the ultrahigh-energy cosmic-ray flux at Earth. Keywords: Pierre Auger Observatory, Cosmic rays, Mass composition, Ankle

Step-by-step, time-consuming scanning of the sample is still the state-of-the-art in imaging Raman spectroscopy. Even for a few 100 image points the measurement time may add up to minutes or hours. A radical decrease in measurement time can be achieved by applying multiplex spectrographs coupled to imaging fiber bundles that are successfully used in astronomy. For optimal use of the scarce and expensive observation time at astronomical observatories, special high-performance spectrograph systems were developed. They are designed for recording thousands of spatially resolved spectra of a two-dimensional image field within one single exposure. Transferring this technology to imaging Raman spectroscopy allows a considerably faster acquisition of chemical maps. Currently, an imaging field of up to 1 cm2 can be investigated. For porcine skin the required measurement time is less than 1 min. For this reason, this technique is of particular interest for medical diagnostics, e.g., the identification of potentially cancerous abnormalities of skin tissue.

Shock synthesis of diamond and even harder carbon polymorphs from graphite is of great interest for science and technology. Here, the authors present unprecedented in situmeasurements of the structural changes, showing ultrafast formation of diamond and, at higher pressures, evidence for a pure lonsdaleite structure.