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Leaf day respiration (Rd) strongly influences carbon-use efficiencies of whole plants and the global terrestrial biosphere. It has long been thought that Rd is slower than respiration in the dark at a given temperature, but measuring Rd by gas exchange remains a challenge because leaves in the light are also photosynthesizing. The Kok method and the Laisk method are widely used to estimate Rd. We highlight theoretical limitations of these popular methods, and recent progress toward their improvement by using additional information from chlorophyll fluorescence and by accounting for the photosynthetic reassimilation of respired CO2. The latest evidence for daytime CO2 and energy release from the oxidative pentose phosphate pathway in chloroplasts appears to be important to understanding Rd.

Item does not contain fulltext, BACKGROUND: Drug repurposing could provide novel treatment options for Duchenne muscular dystrophy. Because tamoxifen-an oestrogen receptor regulator-reduced signs of muscular pathology in a Duchenne muscular dystrophy mouse model, we aimed to assess the safety and efficacy of tamoxifen in humans as an adjunct to corticosteroid therapy over a period of 48 weeks. METHODS: We did a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial at 12 study centres in seven European countries. We enrolled ambulant boys aged 6·5-12·0 years with a genetically confirmed diagnosis of Duchenne muscular dystrophy and who were on stable corticosteroid treatment for more than 6 months. Exclusion criteria included ophthalmological disorders, including cataracts, and haematological disorders. We randomly assigned (1:1) participants using an online randomisation tool to either 20 mg tamoxifen orally per day or matched placebo, stratified by centre and corticosteroid intake. Participants, caregivers, and clinical investigators were masked to treatment assignments. Tamoxifen was taken in addition to standard care with corticosteroids, and participants attended study visits for examinations every 12 weeks. The primary efficacy outcome was the change from baseline to week 48 in scores on the D1 domain of the Motor Function Measure in the intention-to-treat population (defined as all patients who fulfilled the inclusion criteria and began treatment). This study is registered with ClinicalTrials.gov (NCT03354039) and is completed. FINDINGS: Between May 24, 2018, and Oct 14, 2020, 95 boys were screened for inclusion, and 82 met inclusion criteria and were initially enrolled into the study. Three boys were excluded after initial screening due to cataract diagnosis or revoked consent directly after screening, but before randomisation. A further boy assigned to the placebo group did not begin treatment. Therefore, 40 individuals assigned tamoxifen and 38 allocated placebo were inc

We have measured the cross section of the $^{83}$Rb(p,$\gamma)^{84}$Sr radiative capture reaction in inverse kinematics using a radioactive beam of $^{83}$Rb at incident energies of 2.4 and $2.7 A$ MeV. Prior to the radioactive beam measurement, the $^{84}$Kr(p,$\gamma)^{85}$Rb radiative capture reaction was measured in inverse kinematics using a stable beam of $^{84}$Kr at an incident energy of $2.7 A$ MeV. The effective relative kinetic energies of these measurements lie within the relevant energy window for the $\gamma$ process in supernovae. The central values of the measured partial cross sections of both reactions were found to be $0.17-0.42$ times the predictions of statistical model calculations. Assuming the predicted cross section at other energies is reduced by the same factor leads to a slightly higher calculated abundance of the $p$ nucleus $^{84}$Sr, caused by the reduced rate of the $^{84}$Sr($\gamma$,p)$^{83}$Rb reaction derived from the present measurement., Comment: 11 pages, 11 figures. arXiv admin note: text overlap with arXiv:2109.06775

Background Arthrogryposis multiplex congenita (AMC) is characterised by congenital joint contractures in two or more body areas. AMC exhibits wide phenotypic and genetic heterogeneity. Our goals were to improve the genetic diagnosis rates of AMC, to evaluate the added value of whole exome sequencing (WES) compared with targeted exome sequencing (TES) and to identify new genes in 315 unrelated undiagnosed AMC families. Methods Several genomic approaches were used including genetic mapping of disease loci in multiplex or consanguineous families, TES then WES. Sanger sequencing was performed to identify or validate variants. Results We achieved disease gene identification in 52.7% of AMC index patients including nine recently identified genes (CNTNAP1, MAGEL2, ADGRG6, ADCY6, GLDN, LGI4, LMOD3, UNC50 and SCN1A). Moreover, we identified pathogenic variants in ASXL3 and STAC3 expanding the phenotypes associated with these genes. The most frequent cause of AMC was a primary involvement of skeletal muscle (40%) followed by brain (22%). The most frequent mode of inheritance is autosomal recessive (66.3% of patients). In sporadic patients born to non-consanguineous parents (n=60), de novo dominant autosomal or X linked variants were observed in 30 of them (50%). Conclusion New genes recently identified in AMC represent 21% of causing genes in our cohort. A high proportion of de novo variants were observed indicating that this mechanism plays a prominent part in this developmental disease. Our data showed the added value of WES when compared with TES due to the larger clinical spectrum of some disease genes than initially described and the identification of novel genes.

Magnetic Resonance Fingerprinting (MRF) is an efficient quantitative MRI technique that can extract important tissue and system parameters such as T1, T2, B0, and B1 from a single scan. This property also makes it attractive for retrospectively synthesizing contrast-weighted images. In general, contrast-weighted images like T1-weighted, T2-weighted, etc., can be synthesized directly from parameter maps through spin-dynamics simulation (i.e., Bloch or Extended Phase Graph models). However, these approaches often exhibit artifacts due to imperfections in the mapping, the sequence modeling, and the data acquisition. Here we propose a supervised learning-based method that directly synthesizes contrast-weighted images from the MRF data without going through the quantitative mapping and spin-dynamics simulation. To implement our direct contrast synthesis (DCS) method, we deploy a conditional Generative Adversarial Network (GAN) framework and propose a multi-branch U-Net as the generator. The input MRF data are used to directly synthesize T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) images through supervised training on paired MRF and target spin echo-based contrast-weighted scans. In-vivo experiments demonstrate excellent image quality compared to simulation-based contrast synthesis and previous DCS methods, both visually as well as by quantitative metrics. We also demonstrate cases where our trained model is able to mitigate in-flow and spiral off-resonance artifacts that are typically seen in MRF reconstructions and thus more faithfully represent conventional spin echo-based contrast-weighted images., Comment: 19 pages, 8 figures

Background: LAMA2-related muscular dystrophy (LAMA2-RD) encompasses a group of recessive muscular dystrophies caused by mutations in the LAMA2 gene, which codes for the alpha-2 chain of laminin-211 (merosin). Diagnosis is straightforward in the classic congenital presentation with no ambulation and complete merosin deficiency in muscle biopsy, but is far more difficult in milder ambulant individuals with partial merosin deficiency. Objective: To investigate the diagnostic utility of muscle imaging in LAMA2-RD using whole-body magnetic resonance imaging (WBMRI). Results: 27 patients (2–62 years, 21–80% with acquisition of walking ability and 6 never ambulant) were included in an international collaborative study. All carried two pathogenic mutations, mostly private missense changes. An intronic variant (c.909 + 7A > G) was identified in all the Chilean cases. Three patients (two ambulant) showed intellectual disability, epilepsy, and brain structural abnormalities. WBMRI T1w sequences or T2 fat-saturated images (Dixon) revealed abnormal muscle fat replacement predominantly in subscapularis, lumbar paraspinals, gluteus minimus and medius, posterior thigh (adductor magnus, biceps femoris, hamstrings) and soleus. This involvement pattern was consistent for both ambulant and non-ambulant patients. The degree of replacement was predominantly correlated to the disease duration, rather than to the onset or the clinical severity. A “COL6-like sandwich sign” was observed in several muscles in ambulant adults, but different involvement of subscapularis, gluteus minimus, and medius changes allowed distinguishing LAMA2-RD from collagenopathies. The thigh muscles seem to be the best ones to assess disease progression. Conclusion: WBMRI in LAMA2-RD shows a homogeneous pattern of brain and muscle imaging, representing a supportive diagnostic tool.

Franklin R Amthor, Christianne E Strang Department of Psychology, The University of Alabama at Birmingham, Birmingham, AL, 35294, USACorrespondence: Franklin R AmthorDepartment of Psychology, The University of Alabama at Birmingham, 1300 University Blvd, Birmingham, AL, 35294-1170, USATel/Fax +1 205 934-2694Email amthorfr@uab.eduPurpose: Transcranial alternating current stimulation (tACS) is a stimulation protocol used for learning enhancement and mitigation of cognitive dysfunction. Correlated firing has been postulated to be a meta-code that links neuronal spike responses associated with a single entity and may be an important component of high-level cognitive functions. Thus, changes in the covariance firing structure of CNS neurons such as retinal ganglion cells are one potential mechanism by which tACS can exert its effects.Materials and Methods: We used microelectrode arrays to record light-evoked spike responses of 24 retinal ganglion cells in 7 rabbit eyecup preparations and analyzed the covariance between 30 pairs of neighboring retinal ganglion cells before, during, and after 10-minute application of alternating currents of 1 microampere at 10 or 20 Hz.Results: tACS stimulation significantly changed the covariance structure of correlated firing in 60% of simultaneously recorded retinal ganglion cells. Application of tACS in the retinal preparation increased cross-covariance in 26% of cell pairs, an effect usually associated with increased light-evoked ganglion cell firing. tACS associated decreases in cross-covariance occurred in 37% of cell pairs. Increased covariance was more common in response to the first, 10-minute application of tACS in isolated retina preparation. Changes in covariance were rare after repeated stimulation, and more likely to result in decreased covariance.Conclusion: Retinal ganglion cell correlated firing is modulated by 1 microampere tACS currents showing that electrical stimulation can significantly and persistently change the st

Christianne E Strang, Franklin R Amthor Department of Psychology, The University of Alabama at Birmingham, Birmingham, AL, 35294-1170, USACorrespondence: Franklin R AmthorDepartment of Psychology, The University of Alabama at Birmingham, Birmingham, AL, 35294-1170, USA, Tel +1 205 934-2694, Fax +1 205 975-6110, Email amthorfr@uab.eduPurpose: Transcranial alternating current stimulation (tACS) is used as a brain stimulation mechanism to enhance learning, ameliorate some psychiatric disorders, and modify behavior. This study assessed the effects of near threshold tACS-like currents on Off-center and On-Off retinal ganglion cell responsiveness in the rabbit retina eyecup preparation as a model for central nervous system effects.Materials and Methods: We made extracellular recordings in the isolated rabbit eyecup preparation using single electrodes and microelectrode arrays to measure light-evoked spike responses in different classes of Off-center and On-Off retinal ganglion cells before, during, and after brief applications of alternating currents of 1– 2 microamperes, at frequencies of 10, 20, 30, and 40 Hz.Results: tACS application sculpted the light-evoked response profiles without directly driving spiking activity of the 20 Off-center and On-Off ganglion cells we recorded from. During tACS application, Off responses were significantly enhanced for 6 cells and significantly suppressed for 14 cells, but after tACS application, Off responses were significantly enhanced for 7 cells and suppressed for 12 cells. The Off responses of the remaining two cells returned to baseline. On responses were less affected during and after tACS.Conclusion: tACS sculpts Off-center and On-Off retinal ganglion cell responsiveness. The dissimilarity of effects in different cells within the same class and the differential effects on the On and Off components of the light response within the same cell are consistent with the hypothesis that tACS acts at threshold on amacrine cells

During the light-dependent reaction of photosynthesis green plants couple photoinduced cascades of redox reactions with transmembrane proton translocations to generate reducing equivalents and chemical energy in the form of NADPH (nicotinamide adenine dinucleotide phosphate) and ATP (adenosine triphosphate), respectively. We mimic these basic processes by combining molecular ruthenium polypyridine-based photocatalysts and inverted vesicles derived from Escherichia coli. Upon irradiation with visible light, the interplay of photocatalytic nicotinamide reduction and enzymatic membrane-located respiration leads to the simultaneous formation of two biologically active cofactors, NADH (nicotinamide adenine dinucleotide) and ATP, respectively. This inorganic-biologic hybrid system thus emulates the cofactor delivering function of an active chloroplast.

In der lichtabhängigen Reaktion der Photosynthese koppeln grüne Pflanzen photoinduzierte Kaskaden von Redoxreaktionen mit transmembranen Protonentransfers um Reduktionsäquivalente und chemische Energie in Form von NADPH (Nikotinamidadenindinukleotidphosphat) und ATP (Adenosintriphosphat) zu erzeugen. Wir imitieren diese grundlegenden Prozesse durch Kombination von molekularen Rutheniumpolypyridinkomplexen und invertierten Vesikeln, die aus Escherichia coli gewonnen werden. Bei Bestrahlung mit sichtbarem Licht führt das Zusammenspiel von photokatalytischer Nikotinamidreduktion und enzymatischer, membranlokalisierter Atmung zur gleichzeitigen Bildung der beiden biologisch aktiven Cofaktoren NADH (Nikotinamidadenindinukleotid) und ATP. Dieses anorganisch-biologische Hybridsystem ahmt daher die Cofaktor-bereitstellende Funktion eines aktiven Chloroplasten nach.

Franklin R Amthor, Christianne E Strang Department of Psychology, The University of Alabama at Birmingham, Birmingham, AL, 35294-1170, USACorrespondence: Franklin R AmthorDepartment of Psychology, The University of Alabama at Birmingham, 1300 University Blvd, Birmingham, AL, 35294-1170, USATel +1 (205) 934-2694Email amthorfr@uab.eduPurpose: Electrical stimulation of the human central nervous system via surface electrodes has been used for both learning enhancement and the amelioration of neurodegenerative or psychiatric disorders. However, data are sparse on how such electrical stimulation affects neural circuits at the cellular level. This study assessed the effects of tACS-like currents at 10 Hz on On-center retinal ganglion cell responsiveness, using the rabbit retina eyecup preparation as a model for central nervous system effects.Methods: We made extracellular recordings of light-evoked spike responses in different classes of On-center retinal ganglion cells before, during and after brief applications of 1 microampere alternating currents using single electrodes and microelectrode arrays.Results: tACS-like currents (tACS) of 1 microampere produced effects on On-center ganglion cell response profiles immediately after initiation or cessation of tACS, without driving phase-locked firing in the absence of light stimuli. tACS affected the initial transient responses to light stimulation for all cells, sustained response components (if any) more strongly for sustained cells, and the center-surround balance more strongly for transient cells.Conclusion: tACS sculpted light-evoked responses that lasted for one or more hours after cessation of current without, itself, directly inducing significant firing changes. Functionally, tACS effects could result in effects on contrast thresholds for both broad classes of cells, but because tACs differentially affects the center-surround balance of transient On-center cells, there may be greater effects on the spatial resolution a

Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary. A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint. The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity. The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm, ImPhys/Medical Imaging, ImPhys/Computational Imaging

Purpose To develop an efficient algorithm for multi‐component analysis of magnetic resonance fingerprinting (MRF) data without making a priori assumptions about the exact number of tissues or their relaxation properties. Methods Different tissues or components within a voxel are potentially separable in MRF because of their distinct signal evolutions. The observed signal evolution in each voxel can be described as a linear combination of the signals for each component with a non‐negative weight. An assumption that only a small number of components are present in the measured field of view is usually imposed in the interpretation of multi‐component data. In this work, a joint sparsity constraint is introduced to utilize this additional prior knowledge in the multi‐component analysis of MRF data. A new algorithm combining joint sparsity and non‐negativity constraints is proposed and compared to state‐of‐the‐art multi‐component MRF approaches in simulations and brain MRF scans of 11 healthy volunteers. Results Simulations and in vivo measurements show reduced noise in the estimated tissue fraction maps compared to previously proposed methods. Applying the proposed algorithm to the brain data resulted in 4 or 5 components, which could be attributed to different brain structures, consistent with previous multi‐component MRF publications. Conclusions The proposed algorithm is faster than previously proposed methods for multi‐component MRF and the simulations suggest improved accuracy and precision of the estimated weights. The results are easier to interpret compared to voxel‐wise methods, which combined with the improved speed is an important step toward clinical evaluation of multi‐component MRF., ImPhys/Quantitative Imaging

Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary. A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint. The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity. The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm, ImPhys/Medical Imaging, ImPhys/Computational Imaging

Purpose To develop an efficient algorithm for multi‐component analysis of magnetic resonance fingerprinting (MRF) data without making a priori assumptions about the exact number of tissues or their relaxation properties. Methods Different tissues or components within a voxel are potentially separable in MRF because of their distinct signal evolutions. The observed signal evolution in each voxel can be described as a linear combination of the signals for each component with a non‐negative weight. An assumption that only a small number of components are present in the measured field of view is usually imposed in the interpretation of multi‐component data. In this work, a joint sparsity constraint is introduced to utilize this additional prior knowledge in the multi‐component analysis of MRF data. A new algorithm combining joint sparsity and non‐negativity constraints is proposed and compared to state‐of‐the‐art multi‐component MRF approaches in simulations and brain MRF scans of 11 healthy volunteers. Results Simulations and in vivo measurements show reduced noise in the estimated tissue fraction maps compared to previously proposed methods. Applying the proposed algorithm to the brain data resulted in 4 or 5 components, which could be attributed to different brain structures, consistent with previous multi‐component MRF publications. Conclusions The proposed algorithm is faster than previously proposed methods for multi‐component MRF and the simulations suggest improved accuracy and precision of the estimated weights. The results are easier to interpret compared to voxel‐wise methods, which combined with the improved speed is an important step toward clinical evaluation of multi‐component MRF., ImPhys/Quantitative Imaging

We introduce blueprint separable convolutions (BSConv) as highly efficient building blocks for CNNs. They are motivated by quantitative analyses of kernel properties from trained models, which show the dominance of correlations along the depth axis. Based on our findings, we formulate a theoretical foundation from which we derive efficient implementations using only standard layers. Moreover, our approach provides a thorough theoretical derivation, interpretation, and justification for the application of depthwise separable convolutions (DSCs) in general, which have become the basis of many modern network architectures. Ultimately, we reveal that DSC-based architectures such as MobileNets implicitly rely on cross-kernel correlations, while our BSConv formulation is based on intra-kernel correlations and thus allows for a more efficient separation of regular convolutions. Extensive experiments on large-scale and fine-grained classification datasets show that BSConvs clearly and consistently improve MobileNets and other DSC-based architectures without introducing any further complexity. For fine-grained datasets, we achieve an improvement of up to 13.7 percentage points. In addition, if used as drop-in replacement for standard architectures such as ResNets, BSConv variants also outperform their vanilla counterparts by up to 9.5 percentage points on ImageNet. Code and models are available under https://github.com/zeiss-microscopy/BSConv., Comment: Published at CVPR 2020. Code and models are available under https://github.com/zeiss-microscopy/BSConv

Christianne E Strang, Mary Katherine Ray, Mary M Boggiano, Franklin R Amthor Department of Psychology, The University of Alabama at Birmingham, Birmingham, AL, USA Purpose: Transcranial direct current stimulation (tDCS) has been studied in humans for its effects on enhancement of learning, amelioration of psychiatric disorders, and modification of other behaviors for over 50 years. Typical treatments involve injecting 2 mA current through scalp electrodes for 20 minutes, sometimes repeated weekly for two to five sessions. Little is known about the direct effects of tDCS at the neural circuit or the cellular level. This study assessed the effects of tDCS-like currents on the central nervous system by recording effects on retinal ganglion cell responsiveness using the rabbit retina eyecup preparation. Materials and methods: We examined changes in firing to On and Off light stimuli during and after brief applications of a range of currents and polarity and in different classes of ganglion cells. Results: The responses of Sustained cells were consistently suppressed during the first round of current application, but responses could be enhanced after subsequent rounds of stimulation. The observed first round suppression was independent of current polarity, amplitude, or number of trials. However, the light responses of Transient cells were more likely to be enhanced by negative currents and unaffected or suppressed by first round positive currents. Short-duration currents, that is, minutes, as low as 2.5 µA produced a remarkable persistency of firing changes, for up to 1.5 hours, after cessation of current. Conclusion: The results are consistent with postulated tDCS alteration of central nervous system function, which outlast the tDCS session and provide evidence for the isolated retina as a useful model to understand tDCS actions at the neuronal level. Keywords: tDCS mechanisms, CNS, in vitro model, neural coding, neuromodulation

The approachable, comprehensive guide to neurobiology Neurobiology rolls the anatomy, physiology, and pathology of the nervous system into one complex area of study. Neurobiology For Dummies breaks down the specifics of the topic in a fun, easy-to-understand manner. The book is perfect for students in a variety of scientific fields ranging from neuroscience and biology to pharmacology, health science, and more. With a complete overview of the molecular and cellular mechanisms of the nervous system, this complete resource makes short work of the ins and outs of neurobiology so you can understand the details quickly. Dive into this fascinating guide to an even more fascinating subject, which takes a step-by-step approach that naturally builds an understanding of how the nervous system ties into the very essence of human beings, and what that means for those working and studying in the field of neuroscience. The book includes a complete introduction to the subject of neurobiology. Gives you an overview of the human nervous system, along with a discussion of how it's similar to that of other animals Discusses various neurological disorders, such as strokes, Alzheimer's disease, Parkinson's disease, and schizophrenia Leads you through a point-by-point approach to describe the science of perception, including how we think, learn, and remember Neurobiology For Dummies is your key to mastering this complex topic, and will propel you to a greater understanding that can form the basis of your academic and career success.

Security-critical system requirements are increasingly enforced through mandatory access control systems. These systems are controlled by security policies, highly sensitive system components, which emphasizes the paramount importance of formally verified security properties regarding policy correctness. For the class of safety-properties, addressing potential dynamic right proliferation, a number of known and tested formal analysis methods and tools already exist. Unfortunately, these methods need to be redesigned from scratch for each particular policy from a broad range of different application domains. In this paper, we seek to mitigate this problem by proposing a uniform formal framework, tailorable to a safety analysis algorithm for a specific application domain. We present a practical workflow, guided by model-based knowledge, that is capable of producing a meaningful formal safety definition along with an algorithm to heuristically analyze that safety. Our method is demonstrated based on security policies for the SELinux operating system. Keywords: Security engineering, security policies, access control systems, access control models, safety, heuristic analysis, SELinux.

X-ray bursts are thermonuclear flashes on the surface of accreting neutron stars and reliable burst models are needed to interpret observations in terms of properties of the neutron star and the binary system. We investigate the dependence of X-ray burst models on uncertainties in (p,$\gamma$), ($\alpha$,$\gamma$), and ($\alpha$,p) nuclear reaction rates using fully self-consistent burst models that account for the feedbacks between changes in nuclear energy generation and changes in astrophysical conditions. A two-step approach first identified sensitive nuclear reaction rates in a single-zone model with ignition conditions chosen to match calculations with a state-of-the-art 1D multi-zone model based on the {\Kepler} stellar evolution code. All relevant reaction rates on neutron deficient isotopes up to mass 106 were individually varied by a factor of 100 up and down. Calculations of the 84 highest impact reaction rate changes were then repeated in the 1D multi-zone model. We find a number of uncertain reaction rates that affect predictions of light curves and burst ashes significantly. The results provide insights into the nuclear processes that shape X-ray burst observables and guidance for future nuclear physics work to reduce nuclear uncertainties in X-ray burst models., Comment: 24 pages, 13 figures, 4 tables, submitted

X-ray bursts are thermonuclear flashes on the surface of accreting neutron stars and reliable burst models are needed to interpret observations in terms of properties of the neutron star and the binary system. We investigate the dependence of X-ray burst models on uncertainties in (p,$\gamma$), ($\alpha$,$\gamma$), and ($\alpha$,p) nuclear reaction rates using fully self-consistent burst models that account for the feedbacks between changes in nuclear energy generation and changes in astrophysical conditions. A two-step approach first identified sensitive nuclear reaction rates in a single-zone model with ignition conditions chosen to match calculations with a state-of-the-art 1D multi-zone model based on the {\Kepler} stellar evolution code. All relevant reaction rates on neutron deficient isotopes up to mass 106 were individually varied by a factor of 100 up and down. Calculations of the 84 highest impact reaction rate changes were then repeated in the 1D multi-zone model. We find a number of uncertain reaction rates that affect predictions of light curves and burst ashes significantly. The results provide insights into the nuclear processes that shape X-ray burst observables and guidance for future nuclear physics work to reduce nuclear uncertainties in X-ray burst models., Comment: 24 pages, 13 figures, 4 tables, submitted

We propose Impatient Deep Neural Networks (DNNs) which deal with dynamic time budgets during application. They allow for individual budgets given a priori for each test example and for anytime prediction, i.e., a possible interruption at multiple stages during inference while still providing output estimates. Our approach can therefore tackle the computational costs and energy demands of DNNs in an adaptive manner, a property essential for real-time applications. Our Impatient DNNs are based on a new general framework of learning dynamic budget predictors using risk minimization, which can be applied to current DNN architectures by adding early prediction and additional loss layers. A key aspect of our method is that all of the intermediate predictors are learned jointly. In experiments, we evaluate our approach for different budget distributions, architectures, and datasets. Our results show a significant gain in expected accuracy compared to common baselines., Comment: British Machine Vision Conference (BMVC) 2016

Nine ecosystem process models were used to predict CO2 and water vapor exchanges by a 150-year-old black spruce forest in central Canada during 1994–1996 to evaluate and improve the models. Three models had hourly time steps, five had daily time steps, and one had monthly time steps. Model input included site ecosystem characteristics and meteorology. Model predictions were compared to eddy covariance (EC) measurements of whole-ecosystem CO2 exchange and evapotranspiration, to chamber measurements of nighttime moss-surface CO2 release, and to ground-based estimates of annual gross primary production, net primary production, net ecosystem production (NEP), plant respiration, and decomposition. Model-model differences were apparent for all variables. Model-measurement agreement was good in some cases but poor in others. Modeled annual NEP ranged from −11 g C m−2 (weak CO2 source) to 85 g C m−2 (moderate CO2 sink). The models generally predicted greater annual CO2 sink activity than measured by EC, a discrepancy consistent with the fact that model parameterizations represented the more productive fraction of the EC tower “footprint.” At hourly to monthly timescales, predictions bracketed EC measurements so median predictions were similar to measurements, but there were quantitatively important model-measurement discrepancies found for all models at subannual timescales. For these models and input data, hourly time steps (and greater complexity) compared to daily time steps tended to improve model-measurement agreement for daily scale CO2 exchange and evapotranspiration (as judged by root-mean-squared error). Model time step and complexity played only small roles in monthly to annual predictions.

Nine ecosystem process models were used to predict CO2 and water vapor exchanges by a 150-year-old black spruce forest in central Canada during 1994–1996 to evaluate and improve the models. Three models had hourly time steps, five had daily time steps, and one had monthly time steps. Model input included site ecosystem characteristics and meteorology. Model predictions were compared to eddy covariance (EC) measurements of whole-ecosystem CO2 exchange and evapotranspiration, to chamber measurements of nighttime moss-surface CO2 release, and to ground-based estimates of annual gross primary production, net primary production, net ecosystem production (NEP), plant respiration, and decomposition. Model-model differences were apparent for all variables. Model-measurement agreement was good in some cases but poor in others. Modeled annual NEP ranged from −11 g C m−2 (weak CO2 source) to 85 g C m−2 (moderate CO2 sink). The models generally predicted greater annual CO2 sink activity than measured by EC, a discrepancy consistent with the fact that model parameterizations represented the more productive fraction of the EC tower “footprint.” At hourly to monthly timescales, predictions bracketed EC measurements so median predictions were similar to measurements, but there were quantitatively important model-measurement discrepancies found for all models at subannual timescales. For these models and input data, hourly time steps (and greater complexity) compared to daily time steps tended to improve model-measurement agreement for daily scale CO2 exchange and evapotranspiration (as judged by root-mean-squared error). Model time step and complexity played only small roles in monthly to annual predictions.

The possibility of investigating macroscopic coherent quantum states in polariton condensates and of engineering polariton landscapes in semiconductors has triggered interest in using polaritonic systems to simulate complex many-body phenomena. However, advanced experiments require superior trapping techniques that allow for the engineering of periodic and arbitrary potentials with strong on-site localization, clean condensate formation, and nearest-neighbor coupling. Here we establish a technology that meets these demands and enables strong, potentially tunable trapping without affecting the favorable polariton characteristics. The traps are based on a locally elongated microcavity which can be formed by standard lithography. We observe polariton condensation with non-resonant pumping in single traps and photonic crystal square lattice arrays. In the latter structures, we observe pronounced energy bands, complete band gaps, and spontaneous condensation at the M-point of the Brillouin zone.

Exciton-polariton lasers are operated in the strong light matter coupling regime. They promise low threshold operation since population inversion is not inherently necessary. Hence they are of great interest for next generation coherent light sources.

CO2 diffusion from substomatal intercellular cavities to sites of carboxylation in chloroplasts (mesophyll conductance; gm) limits photosynthetic rate and influences leaf intrinsic water-use efficiency (A/gsw). We investigated genotypic variability of gm

Polariton lasing under electrical pumping is observed in a GaAs multi-quantum-well microcavity diode. Lasing in the strong-coupling regime is unambiguously evidenced by detection of Zeeman-split emission in an external magnetic field as a result of the polaritons' excitonic content.

1The rate of CO2 assimilation by plants is directly influenced by the concentration of CO2 in the atmosphere, ca. As an environmental variable, ca also has a unique global and historic significance. Although relatively stable and uniform in the short term, global ca has varied substantially on the timescale of thousands to millions of years, and currently is increasing at seemingly an unprecedented rate. This may exert profound impacts on both climate and plant function. Here we utilise extensive datasets and models to develop an integrated, multi-scale assessment of the impact of changing ca on plant carbon dioxide uptake and water use. We find that, overall, the sensitivity of plants to rising or falling ca is qualitatively similar across all scales considered. It is characterised by an adaptive feedback response that tends to maintain 1 - ci/ca, the relative gradient for CO2 diffusion into the leaf, relatively constant. This is achieved through predictable adjustments to stomatal anatomy and chloroplast biochemistry. Importantly, the long-term response to changing ca can be described by simple equations rooted in the formulation of more commonly studied short-term responses.

The location of electron capture heat sources in the crust of accreting neutron stars depends on the masses of extremely neutron-rich nuclei. We present first results from a new implementation of the time-of-flight technique to measure nuclear masses of rare isotopes at the National Superconducting Cyclotron Laboratory. The masses of 16 neutron-rich nuclei in the scandium -- nickel range were determined simultaneously, improving the accuracy compared to previous data in 12 cases. The masses of $^{61}${V}, $^{63}${Cr}, $^{66}${Mn}, and $^{74}${Ni} were measured for the first time with mass excesses of $-30.510(890)$ MeV, $-35.280(650)$ MeV, $-36.900(790)$ MeV, and $-49.210(990)$ MeV, respectively. With the measurement of the $^{66}$Mn mass, the locations of the two dominant electron capture heat sources in the outer crust of accreting neutron stars that exhibit superbursts are now experimentally constrained. We find that the location of the $^{66}$Fe$\rightarrow^{66}$Mn electron capture transition occurs significantly closer to the surface than previously assumed because our new experimental Q-value is 2.1 MeV (2.6$\sigma$) smaller than predicted by the FRDM mass model., Comment: 4 pages, 3 figures

The location of electron capture heat sources in the crust of accreting neutron stars depends on the masses of extremely neutron-rich nuclei. We present first results from a new implementation of the time-of-flight technique to measure nuclear masses of rare isotopes at the National Superconducting Cyclotron Laboratory. The masses of 16 neutron-rich nuclei in the scandium -- nickel range were determined simultaneously, improving the accuracy compared to previous data in 12 cases. The masses of $^{61}${V}, $^{63}${Cr}, $^{66}${Mn}, and $^{74}${Ni} were measured for the first time with mass excesses of $-30.510(890)$ MeV, $-35.280(650)$ MeV, $-36.900(790)$ MeV, and $-49.210(990)$ MeV, respectively. With the measurement of the $^{66}$Mn mass, the locations of the two dominant electron capture heat sources in the outer crust of accreting neutron stars that exhibit superbursts are now experimentally constrained. We find that the location of the $^{66}$Fe$\rightarrow^{66}$Mn electron capture transition occurs significantly closer to the surface than previously assumed because our new experimental Q-value is 2.1 MeV (2.6$\sigma$) smaller than predicted by the FRDM mass model., Comment: 4 pages, 3 figures

Increasing size and strength of skeletal muscle represents a promising therapeutic strategy for muscular disorders. One possible new tool is Myostatin (Mstn) because it plays a crucial role in regulating skeletal muscle mass. The first goal of our work was to determine whether Mstn inhibition could prevent muscle atrophy in catabolic states. As glucocorticoids play a major role in most muscle atrophy models, we assessed whether muscle atrophy caused by glucocorticoids in excess could be prevented by Mstn inhibition. This hypothesis was suggested by the fact that glucocorticoids increase muscle Mstn expression and that Mstn muscle overexpression is sufficient to cause muscle atrophy. Our work showed that deletion of Mstn gene protects skeletal muscle from glucocorticoid-induced atrophy, partially through inhibition of proteolysis. The identification of Mstn binding proteins able to inhibit Mstn activity has led to potential new approaches for postdevelopmental muscle mass enhancement. These Mstn binding proteins include Follistatin (FS) which shows a potent Mstn-inhibiting activity. The increase in muscle mass observed in transgenic mice overexpressing FS in muscle is even significantly larger than that observed in Mstn KO mice, suggesting that other ligands could contribute to the muscle hypertrophic effect of FS. The mechanisms involved in the FS effect are however relatively unknown. The second aim of this thesis was to investigate the contribution of satellite cells to the FS-induced muscle hypertrophy and to assess whether other FS ligands could act similarly to Mstn in controlling muscle growth. Our study showed that FS overexpression induces skeletal muscle hypertrophy via satellite cell activation and probably increased protein synthesis. Furthermore, our results indicate that FS-induced hypertrophy results not only from Mstn but also from Act inhibition. These observations therefore suggest that, besides Mstn, Act is a crucial player in the regulation of mus, (SBIM 3) -- UCL, 2009

Details on the generation of multiple quasimonoenergetic electron bunches in the self-modulated laser wakefield acceleration SMLWFA regime are presented. This type of laser-plasma interaction can result in pronounced longitudinal laser pulse fragmentation, dependent on plasma density and laser intensity. It is shown by experiments and particle-in-cell simulations that these laser pulse fragments can be powerful enough to trigger nonlinear plasma wave breaking, injection, and acceleration of electrons to quasimonoenergetic energies. With high plasma densities, selfmodulation is promoted, and the advantages of SMLWFA such as especially high accelerating fields and short electron bunches (<5 fs) can be harvested. In addition, more than one quasimonoenergetic electron bunch can be created, with a temporal spacing between each bunch of only few tens of femtoseconds, again governed by plasma density.

scaling (optimizing) of conventional techniques novel techniques: dielectric wall accelerators new concepts: laser plasma acceleration and local beam guiding systems

The rapid progress in the field of laser particle acceleration has stimulated a debate about the promising perspectives of laser based ion beam sources. For a long time, the beams produced exhibited quasi-thermal spectra. Recent proof-of-principle experiments demonstrated that ion beams with narrow energy distribution can be generated from special target geometries. However, the achieved spectra were strongly limited in terms of monochromacity and reproducibility. We show that microstructured targets can be used to reliably produce protons with monoenergetic spectra above 2 MeV with less than 10% energy spread. Detailed investigations of the effects of laser ablation on the target resulted in a significant improvement of the reproducibility. Based on statistical analysis, we derive a scaling law between proton peak position and laser energy, underlining the suitability of this method for future applications. Both the quality of the spectra and the scaling law are well reproduced by numerical simulations.

First steps have been taken in a more comprehensive study of the dependence of observables in Type I X-ray bursts on uncertain (p,gamma) reaction rates along the rp-process path. We use the multizone hydrodynamics code KEPLER which implicitly couples a full nuclear reaction network of more than 1000 isotopes, as needed, to follow structure and evolution of the X-ray burst layer and its ashes. This allows us to incorporate the full rp-process network, including all relevant nuclear reactions, and individually study changes in the X-ray burst light curves when modifying selected key nuclear reaction rates. In this work we considered all possible proton captures to nuclei with 10 < Z < 28 and N <= Z. When varying individual reaction rates within a symmetric full width uncertainty of a factor of 10000, early results for some rates show changes in the burst light curve as large as 10 percent of peak luminosity. This is very large compared to the current sensitivity of X-ray observations. More precise reaction rates are therefore needed to test current X-ray burst models, particularly of the burst rise, with observational data and to constrain astrophysical parameters., Comment: 6 pages, 2 figures, Nuclei in the Cosmos IX - poster 068

We suggest an experiment to observe vacuum birefringence induced by intense laser fields. A high-intensity laser pulse is focused to ultra-relativistic intensity and polarizes the vacuum which then acts like a birefringent medium. The latter is probed by a linearly polarized x-ray pulse. We calculate the resulting ellipticity signal within strong-field QED assuming Gaussian beams. The laser technology required for detecting the signal will be available within the next three years., Comment: 4 pages, 4 figures

Highly collimated, quasimonoenergetic multi-MeV electron bunches were generated by the interaction of tightly focused, 80-fs laser pulses in a high-pressure gas jet. These monoenergetic bunches are characteristic of wakefield acceleration in the highly nonlinear wave breaking regime, which was previously thought to be accessible only by much shorter laser pulses in thinner plasmas. In our experiment, the initially long laser pulse was modified in underdense plasma to match the necessary conditions. This picture is confirmed by semianalytical scaling laws and 3D particle-in-cell simulations. Our results show that laser-plasma interaction can drive itself towards this type of laser wakefield acceleration even if the initial laser and plasma parameters are outside the required regime.