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Computed tomography is widely used to examine internal structures in a non-destructive manner. To obtain high-quality reconstructions, one typically has to acquire a densely sampled trajectory to avoid angular undersampling. However, many scenarios require a sparse-view measurement leading to streak-artifacts if unaccounted for. Current methods do not make full use of the domain-specific information, and hence fail to provide reliable reconstructions for highly undersampled data. We present a novel framework for sparse-view tomography by decoupling the reconstruction into two steps: First, we overcome its ill-posedness using a super-resolution network, SIN, trained on the sparse projections. The intermediate result allows for a closed-form tomographic reconstruction with preserved details and highly reduced streak-artifacts. Second, a refinement network, PRN, trained on the reconstructions reduces any remaining artifacts. We further propose a light-weight variant of the perceptual-loss that enhances domain-specific information, boosting restoration accuracy. Our experiments demonstrate an improvement over current solutions by 4 dB.

The use of computed tomography (CT) imaging has become of increasing interest to academic areas outside of the field of medical imaging and industrial inspection, e.g., to biology and cultural heritage research. The pecularities of these fields, however, sometimes require that objects need to be imaged on-site, e.g., in field-work conditions or in museum collections. Under these circumstances, it is often not possible to use a commercial device and a custom solution is the only viable option. In order to achieve high image quality under adverse conditions, reliable calibration and trajectory reproduction are usually key requirements for any custom CT scanning system. Here, we introduce the construction of a low-cost disassemblable CT scanner that allows calibration even when trajectory reproduction is not possible due to the limitations imposed by the project conditions. Using 3D-printed in-image calibration phantoms, we compute a projection matrix directly from each captured X-ray projection. We describe our method in detail and show successful tomographic reconstructions of several specimen as proof of concept., This paper was originally published at the 6th International Conference on Image Formation in X-Ray Computed Tomography (CTmeeting 2020)

The reconstruction problem of voxels with individual weightings can be modeled a position- and angle- dependent function in the forward-projection. This changes the system matrix and prohibits to use standard filtered backprojection. In this work we first formulate this reconstruction problem in terms of a system matrix and weighting part. We compute the pseudoinverse and show that the solution is rank-deficient and hence very ill posed. This is a fundamental limitation for reconstruction. We then derive an iterative solution and experimentally show its uperiority to any closed-form solution., This paper was originally published at the 6th International Conference on Image Formation in X-Ray Computed Tomography (CTmeeting 2020)

Automated inspection plays an important role in monitoring large-scale photovoltaic power plants. Commonly, electroluminescense measurements are used to identify various types of defects on solar modules but have not been used to determine the power of a module. However, knowledge of the power at maximum power point is important as well, since drops in the power of a single module can affect the performance of an entire string. By now, this is commonly determined by measurements that require to discontact or even dismount the module, rendering a regular inspection of individual modules infeasible. In this work, we bridge the gap between electroluminescense measurements and the power determination of a module. We compile a large dataset of 719 electroluminescense measurementsof modules at various stages of degradation, especially cell cracks and fractures, and the corresponding power at maximum power point. Here,we focus on inactive regions and cracks as the predominant type of defect. We set up a baseline regression model to predict the power from electroluminescense measurements with a mean absolute error of 9.0+/-3.7$W_P$ (4.0+/-8.4%). Then, we show that deep-learning can be used to train a model that performs significantly better (7.3+/-2.7$W_P$ or 3.2+/-6.5%) and propose a variant of class activation maps to obtain the per cell power loss, as predicted by the model. With this work, we aim to open a new research topic. Therefore, we publicly release the dataset, the code and trained models to empower other researchers to compare against our results. Finally, we present a thorough evaluation of certain boundary conditions like the dataset size and an automated preprocessing pipeline for on-site measurements showing multiple modules at once.

The three-dimensional structure of nucleons (protons and neutrons) is embedded in so-called generalized parton distributions, which are accessible from deeply virtual Compton scattering. In this process, a high energy electron is scattered off a nucleon by exchanging a virtual photon. Then, a highly-energetic real photon is emitted from one of the quarks inside the nucleon, which carries information on the quark's transverse position and longitudinal momentum. By measuring the cross-section of deeply virtual Compton scattering, Compton form factors related to the generalized parton distributions can be extracted. Here, we report the observation of unpolarized deeply virtual Compton scattering off a deuterium target. From the measured photon-electroproduction cross-sections, we have extracted the cross-section of a quasi-free neutron and a coherent deuteron. Due to the approximate isospin symmetry of quantum chromodynamics, we can determine the contributions from the different quark flavours to the helicity-conserved Compton form factors by combining our measurements with previous ones probing the proton's internal structure. These results advance our understanding of the description of the nucleon structure, which is important to solve the proton spin puzzle.

Machine learning is bringing a paradigm shift to healthcare by changing the process of disease diagnosis and prognosis in clinics and hospitals. This development equips doctors and medical staff with tools to evaluate their hypotheses and hence make more precise decisions. Although most current research in the literature seeks to develop techniques and methods for predicting one particular clinical outcome, this approach is far from the reality of clinical decision making in which you have to consider several factors simultaneously. In addition, it is difficult to follow the recent progress concretely as there is a lack of consistency in benchmark datasets and task definitions in the field of Genomics. To address the aforementioned issues, we provide a clinical Meta-Dataset derived from the publicly available data hub called The Cancer Genome Atlas Program (TCGA) that contains 174 tasks. We believe those tasks could be good proxy tasks to develop methods which can work on a few samples of gene expression data. Also, learning to predict multiple clinical variables using gene-expression data is an important task due to the variety of phenotypes in clinical problems and lack of samples for some of the rare variables. The defined tasks cover a wide range of clinical problems including predicting tumor tissue site, white cell count, histological type, family history of cancer, gender, and many others which we explain later in the paper. Each task represents an independent dataset. We use regression and neural network baselines for all the tasks using only 150 samples and compare their performance., 5 Pages, Submitted to MLCB 2019

The constant introduction of standardized benchmarks in the literature has helped accelerating the recent advances in meta-learning research. They offer a way to get a fair comparison between different algorithms, and the wide range of datasets available allows full control over the complexity of this evaluation. However, for a large majority of code available online, the data pipeline is often specific to one dataset, and testing on another dataset requires significant rework. We introduce Torchmeta, a library built on top of PyTorch that enables seamless and consistent evaluation of meta-learning algorithms on multiple datasets, by providing data-loaders for most of the standard benchmarks in few-shot classification and regression, with a new meta-dataset abstraction. It also features some extensions for PyTorch to simplify the development of models compatible with meta-learning algorithms. The code is available here: https://github.com/tristandeleu/pytorch-meta

We describe an approach for incorporating prior knowledge into machine learning algorithms. We aim at applications in physics and signal processing in which we know that certain operations must be embedded into the algorithm. Any operation that allows computation of a gradient or sub-gradient towards its inputs is suited for our framework. We derive a maximal error bound for deep nets that demonstrates that inclusion of prior knowledge results in its reduction. Furthermore, we also show experimentally that known operators reduce the number of free parameters. We apply this approach to various tasks ranging from CT image reconstruction over vessel segmentation to the derivation of previously unknown imaging algorithms. As such the concept is widely applicable for many researchers in physics, imaging, and signal processing. We assume that our analysis will support further investigation of known operators in other fields of physics, imaging, and signal processing., Paper conditionally accepted in Nature Machine Intelligence

In this paper, we derive a neural network architecture based on an analytical formulation of the parallel-to-fan beam conversion problem following the concept of precision learning. The network allows to learn the unknown operators in this conversion in a data-driven manner avoiding interpolation and potential loss of resolution. Integration of known operators results in a small number of trainable parameters that can be estimated from synthetic data only. The concept is evaluated in the context of Hybrid MRI/X-ray imaging where transformation of the parallel-beam MRI projections to fan-beam X-ray projections is required. The proposed method is compared to a traditional rebinning method. The results demonstrate that the proposed method is superior to ray-by-ray interpolation and is able to deliver sharper images using the same amount of parallel-beam input projections which is crucial for interventional applications. We believe that this approach forms a basis for further work uniting deep learning, signal processing, physics, and traditional pattern recognition., Inproceedings GCPR 2018

The potential benefit of hybrid X-ray and MR imaging in the interventional environment is large due to the combination of fast imaging with high contrast variety. However, a vast amount of existing image enhancement methods requires the image information of both modalities to be present in the same domain. To unlock this potential, we present a solution to image-to-image translation from MR projections to corresponding X-ray projection images. The approach is based on a state-of-the-art image generator network that is modified to fit the specific application. Furthermore, we propose the inclusion of a gradient map in the loss function to allow the network to emphasize high-frequency details in image generation. Our approach is capable of creating X-ray projection images with natural appearance. Additionally, our extensions show clear improvement compared to the baseline method., Comment: In proceedings of SPIE Medical Imaging 2019

In this paper, we reformulate the conventional 2-D Frangi vesselness measure into a pre-weighted neural network ("Frangi-Net"), and illustrate that the Frangi-Net is equivalent to the original Frangi filter. Furthermore, we show that, as a neural network, Frangi-Net is trainable. We evaluate the proposed method on a set of 45 high resolution fundus images. After fine-tuning, we observe both qualitative and quantitative improvements in the segmentation quality compared to the original Frangi measure, with an increase up to $17\%$ in F1 score.

Hybrid imaging promises large potential in medical imaging applications. To fully utilize the possibilities of corresponding information from different modalities, the information must be transferable between the domains. In radiation therapy planning, existing methods make use of reconstructed 3D magnetic resonance imaging data to synthesize corresponding X-ray attenuation maps. In contrast, for fluoroscopic procedures only line integral data, i.e., 2D projection images, are present. The question arises which approaches could potentially be used for this MR to X-ray projection image-to-image translation. We examine three network architectures and two loss-functions regarding their suitability as generator networks for this task. All generators proved to yield suitable results for this task. A cascaded refinement network paired with a perceptual-loss function achieved the best qualitative results in our evaluation. The perceptual-loss showed to be able to preserve most of the high-frequency details in the projection images and, thus, is recommended for the underlying task and similar problems., In Proceedings of the 5th International Conference on Image Formation in X-ray Computed Tomography

In this paper, we present substantial evidence that a deep neural network will intrinsically learn the appropriate way to discretize the ideal continuous reconstruction filter. Currently, the Ram-Lak filter or heuristic filters which impose different noise assumptions are used for filtered back-projection. All of these, however, inhibit a fully data-driven reconstruction deep learning approach. In addition, the heuristic filters are not chosen in an optimal sense. To tackle this issue, we propose a formulation to directly learn the reconstruction filter. The filter is initialized with the ideal Ramp filter as a strong pre-training and learned in frequency domain. We compare the learned filter with the Ram-Lak and the Ramp filter on a numerical phantom as well as on a real CT dataset. The results show that the network properly discretizes the continuous Ramp filter and converges towards the Ram-Lak solution. In our view these observations are interesting to gain a better understanding of deep learning techniques and traditional analytic techniques such as Wiener filtering and discretization theory. Furthermore, this will allow fully trainable data-driven reconstruction deep learning approaches., Accepted at The Fifth International Conference on Image Formation in X-Ray Computed Tomography

We establish sharp long time asymptotic behaviour for a family of entropies to defective Fokker-Planck equations and show that, much like defective finite dimensional ODEs, their decay rate is an exponential multiplied by a polynomial in time. The novelty of our study lies in the amalgamation of spectral theory and a quantitative non-symmetric hypercontractivity result, as opposed to the usual approach of the entropy method.

We report the first longitudinal-transverse separation of the deeply virtual exclusive π^{0} electroproduction cross section off the neutron and coherent deuteron. The corresponding four structure functions dσ_{L}/dt, dσ_{T}/dt, dσ_{LT}/dt, and dσ_{TT}/dt are extracted as a function of the momentum transfer to the recoil system at Q^{2}=1.75 GeV^{2} and x_{B}=0.36. The ed→edπ^{0} cross sections are found compatible with the small values expected from theoretical models. The en→enπ^{0} cross sections show a dominance from the response to transversely polarized photons, and are in good agreement with calculations based on the transversity generalized parton distributions of the nucleon. By combining these results with previous measurements of π^{0} electroproduction off the proton, we present a flavor decomposition of the u and d quark contributions to the cross section.

Generating agricultural innovations has traditionally been attributed to research organizations. The farmer���s own potential for the development of innovative solutions has largely been neglected. Our experience with Farmer Innovation Contests in Ghana shows that farmers can be a promising source for locally adapted innovations which may be suitable for rapid and costeffective dissemination.

Program obfuscation is increasingly popular among malware creators. Objectively comparing different malware detection approaches with respect to their resilience against obfuscation is challenging. To the best of our knowledge, there is no common empirical framework for evaluating the resilience of malware detection approaches w.r.t. behavior obfuscation. We propose and implement such a framework that obfuscates the observable behavior of malware binaries. To assess the framework's utility, we use it to obfuscate known malware binaries and then investigate the impact on detection effectiveness of different $n$-gram based detection approaches. We find that the obfuscation transformations employed by our framework significantly affect the precision of such detection approaches. Several $n$-gram-based approaches can hence be concluded not to be resilient against this simple kind of obfuscation.

We report the first measurement of the target single-spin asymmetry, A(y), in quasielastic scattering from the inclusive reaction (3)He(↑)(e,e') on a (3)He gas target polarized normal to the lepton scattering plane. Assuming time-reversal invariance, this asymmetry is strictly zero for one-photon exchange. A nonzero A(y) can arise from the interference between the one- and two-photon exchange processes which is sensitive to the details of the substructure of the nucleon. An experiment recently completed at Jefferson Lab yielded asymmetries with high statistical precision at Q(2)=0.13, 0.46, and 0.97 GeV(2). These measurements demonstrate, for the first time, that the (3)He asymmetry is clearly nonzero and negative at the 4σ-9σ level. Using measured proton-to-(3)He cross-section ratios and the effective polarization approximation, neutron asymmetries of -(1-3)% were obtained. The neutron asymmetry at high Q(2) is related to moments of the generalized parton distributions (GPDs). Our measured neutron asymmetry at Q(2)=0.97 GeV(2) agrees well with a prediction based on two-photon exchange using a GPD model and thus provides a new, independent constraint on these distributions.

Double-spin asymmetries and absolute cross sections were measured at large Bjorken x (0.25≤x≤0.90), in both the deep-inelastic and resonance regions, by scattering longitudinally polarized electrons at beam energies of 4.7 and 5.9 GeV from a transversely and longitudinally polarized (3)He target. In this dedicated experiment, the spin structure function g(2)((3)He) was determined with precision at large x, and the neutron twist-3 matrix element d(2)(n) was measured at ⟨Q(2)⟩ of 3.21 and 4.32 GeV(2)/c(2), with an absolute precision of about 10(-5). Our results are found to be in agreement with lattice QCD calculations and resolve the disagreement found with previous data at ⟨Q(2)⟩=5 GeV(2)/c(2). Combining d(2)(n) and a newly extracted twist-4 matrix element f(2)(n), the average neutron color electric and magnetic forces were extracted and found to be of opposite sign and about 30 MeV/fm in magnitude.

Wir betrachten die Sturm-Liouville Differentialgleichung mit ma��wertigen Koeffizienten und f��hren die Weyl m-Funktion f��r selbstadjungierte Realisierungen ein. Weiters betrachten wir den Spezialfall der eindimensionalen Schr��dinger Operatoren mit ma��wertigen Potentialen. F��r diesen Fall entwickeln wir eine verbesserte Absch��tzung der Hochenergieasymptotik f��r die Weyl m-Funktion., We consider the Sturm-Liouville differential expression with measure-valued coefficients and introduce the Weyl m-function for self-adjoint realizations. We further look at the special case of one-dimensional Schr��dinger operators with measure-valued potentials. For this case we develop an improved estimate for the high energy asymptotics of the Weyl m-function.

We present a precise measurement of double-polarization asymmetries in the ^{3}He[over →](e[over →],e^{'}d) reaction. This particular process is a uniquely sensitive probe of hadron dynamics in ^{3}He and the structure of the underlying electromagnetic currents. The measurements have been performed in and around quasielastic kinematics at Q^{2}=0.25(GeV/c)^{2} for missing momenta up to 270 MeV/c. The asymmetries are in fair agreement with the state-of-the-art calculations in terms of their functional dependencies on p_{m} and ω, but are systematically offset. Beyond the region of the quasielastic peak, the discrepancies become even more pronounced. Thus, our measurements have been able to reveal deficiencies in the most sophisticated calculations of the three-body nuclear system, and indicate that further refinement in the treatment of their two-and/or three-body dynamics is required.

We derive an asymptotic expansion for the Weyl function of a one-dimensional Schr��dinger operator which generalizes the classical formula by Atkinson. Moreover, we show that the asymptotic formula can also be interpreted in the sense of distributions., 10 pages

We report the first measurement of the parity-violating asymmetry A_PV in the elastic scattering of polarized electrons from 208Pb. A_PV is sensitive to the radius of the neutron distribution (Rn). The result A_PV = 0.656 \pm 0.060 (stat) \pm 0.014 (syst) ppm corresponds to a difference between the radii of the neutron and proton distributions Rn - Rp = 0.33 +0.16 -0.18 fm and provides the first electroweak observation of the neutron skin which is expected in a heavy, neutron-rich nucleus., Comment: 6 pages, 1 figure

The dynamics of the movement of gas is discussed for two-chambered polarized He-3 target cells of the sort that have been used successfully for many electron scattering experiments. A detailed analysis is presented showing that diffusion is a limiting factor in target performance, particularly as these targets are run at increasingly high luminosities. Measurements are presented on a new prototype polarized He-3 target cell in which the movement of gas is due largely to convection instead of diffusion. NMR tagging techniques have been used to visualize the gas flow, showing velocities along a cylindrically-shaped target of between 5-80 cm/min. The new target design addresses one of the principle obstacles to running polarized He-3 targets at substantially higher luminosities while simultaneously providing new flexibility in target geometry., Comment: First revision: 14 pages, 9 figures, submitted to Phys. Rev. C. We have shortened our discussion of the limitations inherent in various historical He-3 targets, and we have added a discussion exploring the optimal performance that can be expected from a suitably modified target based on diffusion-based mixing. A reference (Jones et. al.) was added. The results we present have not changed

The electric form factor of the neutron was determined from studies of the reaction ${}^{3}\stackrel{\ensuremath{\rightarrow}}{\mathrm{He}}(\stackrel{\ensuremath{\rightarrow}}{e},{e}^{\ensuremath{'}}n)pp$ in quasielastic kinematics in Hall A at Jefferson Lab. Longitudinally polarized electrons were scattered off a polarized target in which the nuclear polarization was oriented perpendicular to the momentum transfer. The scattered electrons were detected in a magnetic spectrometer in coincidence with neutrons that were registered in a large-solid-angle detector. More than doubling the ${Q}^{2}$ range over which it is known, we find ${G}_{E}^{n}=0.0236\ifmmode\pm\else\textpm\fi{}0.0017(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.0026(\mathrm{syst})$, $0.0208\ifmmode\pm\else\textpm\fi{}0.0024\ifmmode\pm\else\textpm\fi{}0.0019$, and $0.0147\ifmmode\pm\else\textpm\fi{}0.0020\ifmmode\pm\else\textpm\fi{}0.0014$ for ${Q}^{2}=1.72$, 2.48, and $3.41\text{ }\text{ }{\mathrm{GeV}}^{2}$, respectively.

The electric form factor of the neutron was determined from studies of the reaction 3He(e,e'n)pp in quasielastic kinematics in Hall A at Jefferson Lab. Longitudinally polarized electrons were scattered off a polarized target in which the nuclear polarization was oriented perpendicular to the momentum transfer. The scattered electrons were detected in a magnetic spectrometer in coincidence with neutrons that were registered in a large-solid-angle detector. More than doubling the Q2 range over which it is known, we find G(E)(n)=0.0236±0.0017(stat)±0.0026(syst), 0.0208±0.0024±0.0019, and 0.0147±0.0020±0.0014 for Q(2)=1.72, 2.48, and 3.41 GeV2, respectively.

Following the first experiment on three-body photodisintegration of polarized $^3$He utilizing circularly polarized photons from High Intensity Gamma Source (HI$\gamma$S) at Duke Free Electron Laser Laboratory (DFELL), a new high-pressure polarized $^3$He target cell made of pyrex glass coated with a thin layer of sol-gel doped with aluminum nitrate nonahydrate has been built in order to reduce the photon beam induced background. The target is based on the technique of spin-exchange optical pumping of hybrid rubidium and potassium and the highest polarization achieved is $\sim$62% determined from both NMR-AFP and EPR polarimetry. The $X$ parameter is estimated to be $\sim0.06$ and the performance of the target is in good agreement with theoretical predictions. We also present beam test results from this new target cell and the comparison with the GE180 $^3$He target cell used previously at HI$\gamma$S. This is the first time that sol-gel coating technique has been used in a polarized $^3$He target for nuclear physics experiments., Comment: 8 pages, 3 figures

We report new measurements of the parity-violating asymmetry A(PV) in elastic scattering of 3 GeV electrons off hydrogen and 4He targets withtheta(lab)approximately 6.0 degrees . The 4He result is A(PV)=(+6.40+/-0.23(stat)+/-0.12(syst))x10(-6). The hydrogen result is A(PV)=(-1.58+/-0.12(stat)+/-0.04(syst))x10(-6). These results significantly improve constraints on the electric and magnetic strange form factors G(E)(s) and G(M)(s). We extract G(E)(s)=0.002+/-0.014+/-0.007 atQ(2)=0.077 GeV2, and G(E)(s)+0.09G(M)(s)=0.007+/-0.011+/-0.006 atQ(2)=0.109 GeV2, providing new limits on the role of strange quarks in the nucleon charge and magnetization distributions.

We report a measurement of the parity-violating asymmetry in fixed target electron-electron (Moller) scattering: A_PV = -175 +/- 30 (stat.) +/- 20 (syst.) parts per billion. This first direct observation of parity nonconservation in Moller scattering leads to a measurement of the electron's weak charge at low energy Q^e_W = -0.053 +/- 0.011. This is consistent with the Standard Model expectation at the current level of precision: sin^2\theta_W(M_Z)_MSbar = 0.2293 +/- 0.0024 (stat.) +/- 0.0016 (syst.) +/- 0.0006 (theory)., Comment: Version 3 is the same as version 2. These versions contain minor text changes from referee comments and a change in the extracted value of Q^e_W and sin^2\theta_W due to a change in the theoretical calculation of the bremsstrahulung correction (ref. 16)

High-purity sol-gel solutions have been developed to coat the interior surface of glass vessels used for polarizing 3He by spin-exchange optical pumping. Such cells have been shown to exhibit 3He longitudinal lifetimes 2'1 in excess of 350 hours'. T h e sol-gel technique was designed to minimize spin-relaxation due to wall collisions so that only dipole-dipole interactions between colliding 3He atoms dominate in the relaxation process. Until now, sol-gel technology had not been applied to high pressure 3He gas targets used in nuclear scattering experiments. A description of the sol-gel technique and recent developments on its integration into the production of 3He targets will be presented.

Corrections to photocount distributions due to dead-time effects are evaluated by the use of a new pulse-pileup model incorporating a paralyzable portion and nonparalyzable component in sequence. In the simple model, the two dead times are regarded as nonvarying. A more complete mode is presented in the Appendix, which incorporates dead times that are themselves random variables.

— Reaction center (RC) complexes isolated from the photosynthetic bacterium Rhodopseudomonas sphaeroides R-26 were dried as a film onto platinum and semiconductor (SnO2) electrodes. The light-induced primary charge separation which occurs across the biological complex couples electrically with the SnO2 but not with the metal electrode on the time scale of observation. As the working electrode in a two-electrode photoelectrochemical cell, RC-coated SnO2 generated photovoltages as high as 80 mV and photocurrents as high as 0.5µA·cm2 when exposed to light of λ >600nm. The number of quinone molecules per RC strongly influences the photovoltage and photocurrent observed. Photo-effects generated by RC electrodes persist after several days of storage; however, the kinetics and polarity of the effects are subject to change. The potential use of RC electrodes lies more as a new probe of photosynthetic electron transport rather than as a solar energy conversion device because modification to the RCs and their environment affect the electrical properties of the cell. An energy-level model is proposed to explain how the photoelectrochemical cell functions.

A rapid purification procedure has been developed for the isolation of reaction centers From Rhodopseudomonas sphaeroides strain R-26. The procedure takes about 7 h and results in yields of 60–75%. The ratio of the optical absorbances at 280 and 800 nm is between 1.4 and 1.5, and preparations can be made with either one or two quinones per reaction center. EPR spectra show a sharp g 1.83 signal for the ubisemiquinone. The substitution of lauryl maltoside for lauryldimethylamine oxide suppresses reaction-center degradation in solution.

Oriel's new diode array radiometer consists of a flat focal plane spectrograph and a diode array detector, interfaced to a standard XT or AT type computer. The spectrograph has interchangeable gratings, and can be set for almost any wavelength range from 180 to 1100 nm. The diode array detector is thermally stabilized to 0.1°C, and can acquire an entire spectrum in only 5 milliseconds, it can take a sequence of scans, and can follow the time course of an optical change. The results can be graphically displayed in absolute energy units verses wavelength or time. Radiometric capability is achieved by using an NIST traceable light source to calibrate the system in situ for the wavelength region of interest. This takes into account front end fiber optic guides, optical filters, and spectrograph efficiency. Extensive software semi-automates this process, providing automatic calibration of the radiometer against the output energy curve of the source. The radiometer can exactly quantify exposure levels of UV-A and UV-B radiation. This is more accurate than the approximate values derived using optical filters. The system can also simulate other types of detectors defined by the user, and the data can be presented in a variety of photometric units. The diode array detector is 25 mm long and can be used for linear radiometric imaging when used with bandpass filters. A camera and assortment of lenses may be used in conjunction with the diode array detector for telephoto, wide-angle, or micro imaging.

Measurements were made of energy-dependent quenching of atebrin fluorescence in membrane particles prepared from Escherichia coli grown anaerobically with glycerol as carbon source in the presence of either nitrate or fumarate. It is concluded that this technique can be used to study the functional organization of the anaerobic proton-translocating electron-transport chains that use nitrate or fumarate as terminal electron acceptor.

A horizontal rotor can be used as an alternative to the common vertical chopper for light‐beam modulation. The horizontal rotor is more compact than the vertical type and the modulation duty cycle is variable. This kind of chopper is well suited to the alternate modulation of two light beams. A well‐designed chopper should be able to function as either a vertical or horizontal light modulator.