Estimation of Combustion Parameters from Engine Vibrations Based on Discrete Wavelet Transform and Gradient Boosting.

An optimal control of the combustion process of an engine ensures lower emissions and fuel consumption plus high efficiencies. Combustion parameters such as the peak firing pressure (PFP) and the crank angle (CA) corresponding to 50% of mass fraction burned (MFB50) are essential for a closed-loop control strategy. These parameters are based on the measured in-cylinder pressure that is typically gained by intrusive pressure sensors (PSs). These are costly and their durability is uncertain. To overcome these issues, the potential of using a virtual sensor based on the vibration signals acquired by a knock sensor (KS) for control of the combustion process is investigated. The present work introduces a data-driven approach where a signal-processing technique, designated as discrete wavelet transform (DWT), will be used as the preprocessing step for extracting informative features to perform regression tasks of the selected combustion parameters with extreme gradient boosting (XGBoost) regression models. The presented methodology will be applied to data from two different spark-ignited, single cylinder gas engines. Finally, an analysis is obtained where the important features based on the model's decisions are identified.

Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion.

Additive manufacturing, in particular the powder bed fusion of metals using a laser beam, has a wide range of possible technical applications. Especially for safety-critical applications, a quality assurance of the components is indispensable. However, time-consuming and costly quality assurance measures, such as computer tomography, represent a barrier for further industrial spreading. For this reason, alternative methods for process anomaly detection using process monitoring systems have been developed. However, the defect detection quality of current methods is limited, as single monitoring systems only detect specific process anomalies. Therefore, a new methodology to evaluate the data of multiple monitoring systems is derived using sensor data fusion. Focus was placed on the causes and the appearance of defects in different monitoring systems (photodiodes, on- and off-axis high-speed cameras, and thermography). Based on this, indicators representing characteristics of the process were developed to reduce the data. Finally, deterministic models for the data fusion within a monitoring system and between the monitoring systems were developed. The result was a defect detection of up to 92% of the melt track defects. The methodology was thus able to determine process anomalies and to evaluate the suitability of a specific process monitoring system for the defect detection.

Inter-Reader Variability of Volumetric Subsolid Pulmonary Nodule Radiomic Features.

OBJECTIVE: To evaluate the inter-observer consistency for subsolid pulmonary nodule radiomic features. MATERIALS AND METHODS: Subsolid nodules were selected by reviewing radiology reports of CT examinations performed December 1, 2015 to April 1, 2016. Patients with CTs at two time points were included in this study. There were 55 patients with subsolid nodules, of whom 14 had two nodules. Of 69 subsolid nodules, 66 were persistent at the second time point, yielding 135 lesions for segmentation. Two thoracic radiologists and an imaging fellow segmented the lesions using a semi-automated volumetry algorithm (Syngo.via Vb20, Siemens). Coefficient of variation (CV) was used to assess consistency of 91 quantitative measures extracted from the subsolid nodule segmentations, including first and higher order texture features. The accuracy of segmentation was visually graded by an experienced thoracic radiologist. Influencing factors on radiomic feature consistency and segmentation accuracy were assessed using generalized estimating equation analyses and the Exact Mann-Whitney test. RESULTS: Mean patient age was 71 (38-93 years), with 39 women and 16 men. Mean nodule volume was 1.39mL, range .03-48.2mL, for 135 nodules. Several radiomic features showed high inter-reader consistency (CV<5%), including entropy, uniformity, sphericity, and spherical disproportion. Descriptors such as surface area and energy had low consistency across inter-reader segmentations (CV>10%). Nodule percent solid component and attenuation influenced inter-reader variability of some radiomic features. The presence of contrast did not significantly affect the consistency of subsolid nodule radiomic features. Near perfect segmentation, within 5% of actual nodule size, was achieved in 68% of segmentations, and very good segmentation, within 25% of actual nodule size, in 94%. Morphologic features including nodule margin and shape (each p <0.01), and presence of air bronchograms (p = 0.004), bubble lucencies (p = 0.02) and broad pleural contact (p < 0.01) significantly affected the probability of near perfect segmentation. Stroke angle (p = 0.001) and length (p < 0.001) also significantly influenced probability of near perfect segmentation. CONCLUSIONS: The inter-observer consistency of radiomic features for subsolid pulmonary nodules varies, with high consistency for several features, including sphericity, spherical disproportion, and first and higher order entropy, and normalized non-uniformity. Nodule morphology influences the consistency of subsolid nodule radiomic features, and the accuracy of subsolid nodule segmentation.

Influence of breathing state on the accuracy of automated patient positioning in thoracic CT using a 3D camera for body contour detection.

OBJECTIVE: To assess the influence of breathing state on the accuracy of a 3D camera for body contour detection and patient positioning in thoracic CT. MATERIALS AND METHODS: Patients who underwent CT of the thorax with both an inspiratory and expiratory scan were prospectively included for analysis of differences in the ideal table height at different breathing states. For a subgroup, an ideal table height suggestion based on 3D camera images at both breathing states was available to assess their influence on patient positioning accuracy. Ideal patient positioning was defined as the table height at which the scanner isocenter coincides with the patient's isocenter. RESULTS: The mean (SD) difference of the ideal table height between the inspiratory and the expiratory breathing state among the 64 included patients was 10.6 mm (4.5) (p < 0.05). The mean (SD) positioning accuracy, i.e., absolute deviation from the ideal table height, within the subgroup (n = 43) was 4.6 mm (7.0) for inspiratory scans and 7.1 mm (7.7) for expiratory scans (p < 0.05) when using corresponding 3D camera images. The mean (SD) accuracy was 14.7 mm (7.4) (p < 0.05) when using inspiratory camera images on expiratory scans; vice versa, the accuracy was 3.1 mm (9.5) (p < 0.05). CONCLUSION: A 3D camera allows for accurate and precise patient positioning if the camera image and the subsequent CT scan are acquired in the same breathing state. It is recommended to perform an expiratory planning image when acquiring a thoracic CT scan in both the inspiratory and expiratory breathing state. KEY POINTS: • A 3D camera for body contour detection allows for accurate and precise patient positioning if the camera image and the subsequent CT scan are acquired in the same breathing state. • It is recommended to perform an expiratory planning image when acquiring a thoracic CT scan in both the inspiratory and expiratory breathing state.

Genauigkeit und Reproduzierbarkeit eines Software-Prototypen zur halbautomatischen computergestützten Volumetrie der soliden und subsoliden Komponenten von teilsoliden Lungenrundherden.

PURPOSE: To test the accuracy and reproducibility of a software prototype for semi-automated computer-aided volumetry (CAV) of part-solid pulmonary nodules (PSN) with separate segmentation of the solid part. MATERIALS AND METHODS: 66 PSNs were retrospectively identified in 34 thin-slice unenhanced chest CTs of 19 patients. CAV was performed by two medical students. Manual volumetry (MV) was carried out by two radiology residents. The reference standard was determined by an experienced radiologist in consensus with one of the residents. Visual assessment of CAV accuracy was performed. Measurement variability between CAV/MV and the reference standard as a measure of accuracy, CAV inter- and intra-rater variability as well as CAV intrascan variability between two recontruction kernels was determined via the Bland-Altman method and intraclass correlation coefficients (ICC). RESULTS: Subjectively assessed accuracy of CAV/MV was 77 %/79 %-80 % for the solid part and 67 %/73 %-76 % for the entire nodule. Measurement variability between CAV and the reference standard ranged from -151-117 % for the solid part and -106-54 % for the entire nodule. Interrater variability was -16-16 % for the solid part (ICC 0.998) and -102-65 % for the entire nodule (ICC 0.880). Intra-rater variability was -70-49 % for the solid part (ICC 0.992) and -111-31 % for the entire nodule (ICC 0.929). Intrascan variability between the smooth and the sharp reconstruction kernel was -45-39 % for the solid part and -21-46 % for the entire nodule. CONCLUSION: Although the software prototype delivered satisfactory results when segmentation is evaluated subjectively, quantitative statistical analysis revealed room for improvement especially regarding the segmentation accuracy of the solid part and the reproducibility of measurements of the nodule's subsolid margins. KEY POINTS: · Assessed visually CAV delivers similar accuracy compared to manual volumetry. · Accuracy of CAV was higher for the entire nodule. · Reproducibility was better for the solid part. · Variability between the kernels was higher for the solid part.

Separating dissolved silver from nanoparticulate silver is the key: Improved cloud-point-extraction hyphenated to single particle ICP-MS for comprehensive analysis of silver-based nanoparticles in real environmental samples down to single-digit nm particle sizes.

Investigating silver-based nanoparticles (Ag-b-NPs) in environmental samples is challenging with current analytical techniques, owing to their low concentrations (ng L-1) in the presence of high quantities of dissolved Ag(I) species. sp-ICP-MS is a promising technique able to simultaneously determine the concentration and particle sizes of Ag-b-NPs even at concentrations of several ng L-1. However, sp-ICP-MS suffers from the coexistence of dissolved analyte species causing high background signals. These background signals cover particle signals and therefore limit the size detection limit (SDL) in sp-ICP-MS. Ag-b-NPs in environmental samples exhibit diameters of < 20 nm, whereas the current sp-ICP-MS approaches barely reach an SDL as low as 20 nm. Using a surfactant-mediated sample pre-treatment (improved cloud point extraction, iCPE), we were able to separate Ag-b-NPs in aqueous samples from dissolved Ag(I) species and enrich the NPs in the extract. By hyphenating iCPE to sp-ICP-MS, we were able to reach SDL values as low as 4.5 nm, thus paving the way for the successful monitoring of Ag-b-NPs in the environment.

Automated patient positioning in CT using a 3D camera for body contour detection: accuracy in pediatric patients.

OBJECTIVE: To assess the accuracy of a 3D camera for body contour detection in pediatric patient positioning in CT compared with routine manual positioning by radiographers. METHODS AND MATERIALS: One hundred and ninety-one patients, with and without fixation aid, which underwent CT of the head, thorax, and/or abdomen on a scanner with manual table height selection and with table height suggestion by a 3D camera were retrospectively included. The ideal table height was defined as the position at which the scanner isocenter coincides with the patient's isocenter. Table heights suggested by the camera and selected by the radiographer were compared with the ideal height. RESULTS: For pediatric patients without fixation aid like a baby cradle or vacuum cushion and positioned by radiographers, the median (interquartile range) absolute table height deviation in mm was 10.2 (16.8) for abdomen, 16.4 (16.6) for head, 4.1 (5.1) for thorax-abdomen, and 9.7 (9.7) for thorax CT scans. The deviation was less for the 3D camera: 3.1 (4.7) for abdomen, 3.9 (6.3) for head, 2.2 (4.3) for thorax-abdomen, and 4.8 (6.7) for thorax CT scans (p < 0.05 for all body parts combined). CONCLUSION: A 3D camera for body contour detection allows for automated and more accurate pediatric patient positioning than manual positioning done by radiographers, resulting in overall significantly smaller deviations from the ideal table height. The 3D camera may be also useful in the positioning of patients with fixation aid; however, evaluation of possible improvements in positioning accuracy was limited by the small sample size. KEY POINTS: • A 3D camera for body contour detection allows for automated and accurate pediatric patient positioning in CT. • A 3D camera outperformed radiographers in positioning pediatric patients without a fixation aid in CT. • Positioning of pediatric patients with fixation aid was feasible using the 3D camera, but no definite conclusions were drawn regarding the positioning accuracy due to the small sample size.

Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. / Personalisierte Computertomografie ­ automatisierte Abschätzung von Größe und Gewicht durch Simulation eines digitalen Zwillings mit einer 3D-Kamera und künstlicher Intelligenz.

PURPOSE: The aim of this study was to develop an algorithm for automated estimation of patient height and weight during computed tomography (CT) and to evaluate its accuracy in everyday clinical practice. MATERIALS AND METHODS: Depth images of 200 patients were recorded with a 3D camera mounted above the patient table of a CT scanner. Reference values were obtained using a calibrated scale and a measuring tape to train a machine learning algorithm that fits a patient avatar into the recorded patient surface data. The resulting algorithm was prospectively used on 101 patients in clinical practice and the results were compared to the reference values and to estimates by the patient himself, the radiographer and the radiologist. The body mass index was calculated from the collected values for each patient using the WHO formula. A tolerance level of 5 kg was defined in order to evaluate the impact on weight-dependent contrast agent dosage in abdominal CT. RESULTS: Differences between values for height, weight and BMI were non-significant over all assessments (p > 0.83). The most accurate values for weight were obtained from the patient information (R²â€Š= 0.99) followed by the automated estimation via 3D camera (R²â€Š= 0.89). Estimates by medical staff were considerably less precise (radiologist: R²â€Š= 0.78, radiographer: R²â€Š= 0.77). A body-weight dependent dosage of contrast agent using the automated estimations matched the dosage using the reference measurements in 65 % of the cases. The dosage based on the medical staff estimates would have matched in 49 % of the cases. CONCLUSION: Automated estimation of height and weight using a digital twin model from 3D camera acquisitions provide a high precision for protocol design in computer tomography. KEY POINTS: · Machine learning can calculate patient-avatars from 3D camera acquisitions.. · Height and weight of the digital twins are comparable to real measurements of the patients.. · Estimations by medical staff are less precise.. · The values can be used for calculation of contrast agent dosage.. CITATION FORMAT: · Geissler F, Heiß R, Kopp M et al. Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. Fortschr Röntgenstr 2021; 193: 437 - 445.

Looking at Silver-Based Nanoparticles in Environmental Water Samples: Repetitive Cloud Point Extraction Bridges Gaps in Electron Microscopy for Naturally Occurring Nanoparticles.

The growing use of silver-based nanoparticles (Ag-b-NPs) in everyday products goes hand in hand with their release into the environment, resulting in ng L-1 traces in natural water bodies. In order to assess their fate, possible transformations and ecotoxicology-essential information to proper risk assessment-particle size, shape, and chemical composition have to be determined. Transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (TEM-EDX) is a powerful tool for determining these particle characteristics, but it requires high particle concentrations in order to produce statistically reliable results. In this study, we will present the extraction of Ag-b-NPs at environmentally relevant concentrations down to 5 ng L-1 from artificial as well as environmental water samples via cloud point extraction on a repetitive basis. The combination with an on-grid centrifugation technique ensures an efficient concentration and deposition of the extracted particles onto the TEM grid for subsequent TEM-EDX measurements. Furthermore, electron microscopy investigations were supplemented by single particle inductively coupled plasma mass spectrometry (sp-ICP-MS) measurements. Ag-b-NPs were successfully visualized and characterized at environmentally relevant concentrations of 5 ng L-1 with TEM-EDX and sp-ICP-MS measurements. Their size, shape, and chemical composition were not affected by the sample preparation.

What happens to silver-based nanoparticles if they meet seawater?

Silver based nanoparticles (Ag-b-NPs) in the environment are of current concern as they may pose risks to human and environmental health, even at low concentration levels. It is widely known that Ag-b-NPs, once released from products containing these particles for antimicrobial reasons, can pass through wastewater treatment plants to some extent. These particles are transported via running waterways and eventually reach the sea. However, the fate of environmentally relevant ng L-1 traces of Ag-b-NPs in seawater has not yet been sufficiently studied. Analytical techniques capable of determining these ultratraces of Ag-b-NPs in seawater are scarce and struggle furthermore with the high chloride content in highly saline matrices, such as seawater. In this study, we extracted Ag-b-NPs from matrices with varying salinity via cloud point extraction (CPE) and determined concentration and size of Ag-b-NPs in extracts with single particle inductively coupled plasma mass spectrometry (sp-ICP-MS). Applying this extraction and measurement technique, we were able to investigate the fate of Ag-b-NPs with different coatings (citrate and the predominant coatings in nature, silver sulfide and silver chloride) in matrices with increasing salinity and real seawater. All types of Ag-b-NPs were dissolved in all matrices almost independently of the chemical composition of the nanoparticles (NPs), whereas dissolution rates increased with increasing salinity due to the formation of soluble Ag(I) species and - in the presence of chloride - AgClx1-x (x > 1) complexes. After an incubation time of not more than 72 h, Ag-b-NPs were dissolved almost completely. During the dissolution process, NP shrinkage could be clearly observed by sp-ICP-MS. Supplementary electron microscopy measurements revealed that the sulfur content in silver sulfide nanoparticles (Ag2S-NPs) increased during the dissolution process. Finally, we were able to investigate the dissolution process of real Ag-b-NPs in wastewater after increasing the salinity to seawater levels.

Copper Drinking Water Pipes as a Previously Undocumented Source of Silver-Based Nanoparticles.

Wastewater streams are widely known to release silver-based nanoparticles (Ag-b-NPs) into the environment with a plethora of unknown consequences. Until recently, studies have commonly associated Ag-b-NP sources with products that contain these NPs for antimicrobial reasons, such as fabrics, cosmetics, and medical products. However, our study reveals that there is a thus far completely undocumented source of Ag-b-NPs: copper drinking water pipes. We applied cloud point extraction hyphenated to electrothermal atomic absorption spectrometry or single-particle inductively coupled plasma mass spectrometry to analyze the concentration and perform size-selective quantification of Ag-b-NPs in tap water passing through copper pipes. Up to 83 ng of total silver and 25 ng of Ag-b-NPs were present in tap water samples per liter, which resulted in an NP proportion of approximately 30% of total silver. In total, 96% of the measurable particle sizes ranged from 10 to 36 nm. Additionally, 53 µg of copper was released per liter tap water on average. The measurements included tap water from different sampling days and from four different buildings with varying ages, whereas Ag-b-NPs could be detected in the tap water of two buildings. Silver traces in the copper pipe material of 27.5 ± 4.4 µg g-1 were found to be responsible for the release of nanoparticulate silver into the tap water.

Mixed precious-group metal-organic frameworks: a case study of the HKUST-1 analogue [RuxRh3-x(BTC)2].

This work presents the first full series of mixed precious-group metal-organic frameworks (MPG-MOFs) using ruthenium and rhodium. The obtained crystalline, highly porous and thermally robust materials were characterized by means of powder X-ray diffraction, N2/CO2 sorption isotherms, thermogravimetry, spectroscopy methods (IR, Raman, UV/VIS-, NMR and XPS) and as well by high resolution transmission electron microscopy (HR-TEM) with elemental mapping (HAADF-EDS). Additionally, the assignment of spectroscopic data is supported by computational (time dependent)-density functional theory methods. The materials turned out to consist of homogeneously dispersed Ru2 and Rh2 paddlewheel units being linked by benzenetricarboxylate (BTC) to yield a framework that is isoreticular to [Cu3(BTC)2] (HKUST-1, Hong Kong University of Science and Technology). However, acetate (OAc) is incorporated as an intrinsic component which compensates for missing BTC-linker defects and some Cl is coordinated to the Ru centre at an apical position. The exact empirical formula of the MPG-MOFs is derived as [RuxRh3-x(BTC)2-a(OAc)b(Cl)c].

Sampling and pre-treatment effects on the quantification of (nano)silver and selected trace elements in surface water - Application in a Dutch case study.

Detection and quantification of trace elements in aqueous samples is crucial in terms of environmental monitoring and risk assessment for (heavy) metals in the environment. Silver (Ag) in its nanoparticulate form is commonly used as antimicrobial additive in consumer products and pharmaceuticals. Since released dissolved Ag species act as the actual antimicrobial agent, Ag nanomaterials are supposed to pose risks to the environment by a release of dissolved species. Unfortunately, no standard protocols exist yet to gain reliable information about the presence and distribution of nanomaterials in the environment. Therefore, we present an interlaboratory collaboration involving three laboratories to quantify silver, silver based nanoparticles (Ag-b-NPs) and a wide range of relevant trace elements after different sample pre-treatments for profiling surface water of a Dutch channel. Besides quantification of the elements, different sample pretreatments like acidification, with or without filtration, and their effect on the measurable elemental content were studied. Total Ag and Ag-b-NPs were quantified at lower ng L-1 range in the channel water whereas reasonable differences depending on the pre-treatment were identified; Ba, As, Pb, Co, Cr, Cu, Ni and Zn were detected at µg L-1 range and Na, K, Mg, Ca and Fe at mg L-1 range. Significant sample pre-treatment effects were observed for the elements Cr, Cu, Fe, Pb and Zn, which is very likely due to the existence of particulate species. Measured concentrations were well comparable among the three laboratories underpinning method validity and correctness allowing for a comprehensive, reliable risk assessment for nanomaterials in the environment.

A User Interface for Optimizing Radiologist Engagement in Image Data Curation for Artificial Intelligence.

PURPOSE: To delineate image data curation needs and describe a locally designed graphical user interface (GUI) to aid radiologists in image annotation for artificial intelligence (AI) applications in medical imaging. MATERIALS AND METHODS: GUI components support image analysis toolboxes, picture archiving and communication system integration, third-party applications, processing of scripting languages, and integration of deep learning libraries. For clinical AI applications, GUI components included two-dimensional segmentation and classification; three-dimensional segmentation and quantification; and three-dimensional segmentation, quantification, and classification. To assess radiologist engagement and performance efficiency associated with GUI-related capabilities, image annotation rate (studies per day) and speed (minutes per case) were evaluated in two clinical scenarios of varying complexity: hip fracture detection and coronary atherosclerotic plaque demarcation and stenosis grading. RESULTS: For hip fracture, 1050 radiographs were annotated over 7 days (150 studies per day; median speed: 10 seconds per study [interquartile range, 3-21 seconds per study]). A total of 294 coronary CT angiographic studies with 1843 arteries and branches were annotated for atherosclerotic plaque over 23 days (15.2 studies [80.1 vessels] per day; median speed: 6.08 minutes per study [interquartile range, 2.8-10.6 minutes per study] and 73 seconds per vessel [interquartile range, 20.9-155 seconds per vessel]). CONCLUSION: GUI-component compatibility with common image analysis tools facilitates radiologist engagement in image data curation, including image annotation, supporting AI application development and evolution for medical imaging. When complemented by other GUI elements, a continuous integrated workflow supporting formation of an agile deep neural network life cycle results.Supplemental material is available for this article.© RSNA, 2019.

Re-evaluation of stability and toxicity of silver sulfide nanoparticle in environmental water: Oxidative dissolution by manganese oxide.

Stability of silver sulfide nanoparticle (Ag2S-NP) in the environment has recently drawn considerable attention since it is associated with environmental risk. Although the overestimated stability of Ag2S-NP in aqueous solution has already been recognized, studies on transformation of Ag2S-NP in environmental water are still very scarce. Here we reported that Ag2S-NP could undergo dissolution by manganese(IV) oxide (MnO2), an important naturally occurring oxidant in the environment, even in environmental water, although the dissolved silver would probably be adsorbed onto the particles (>0.45 µm) in environmental water, mitigating the measurable levels of dissolved silver. The extent and rate of Ag2S-NP dissolution rose with the increasing concentration of MnO2. In addition, environmental factors including natural organic matter, inorganic salts and organic acids could accelerate the Ag2S-NP dissolution by MnO2, wherein an increase in dissolution extent was also observed. We further documented that Ag2S-NP dissolution by MnO2 was highly dependent on O2 and it was an oxidative dissolution, with the production of SO42-. Finally, dissolution of Ag2S-NP by MnO2 affected zebra fish (Danio rerio) embryo viability, showing significant reduction in embryo survival and hatching rates, compared to embryos exposed to Ag2S-NP, MnO2 or dissolved manganese alone. These findings would further shed light on the stability of Ag2S-NP in the natural environment - essential for comprehensive nano risk assessment.

Precise and Automatic Patient Positioning in Computed Tomography: Avatar Modeling of the Patient Surface Using a 3-Dimensional Camera.

OBJECTIVES: The aim of this study was to evaluate the accuracy of a 3-dimensional (3D) camera algorithm for automatic and individualized patient positioning based on body surface detection and to compare the results of the 3D camera with manual positioning performed by technologists in routinely obtained chest and abdomen computed tomography (CT) examinations. MATERIALS AND METHODS: This study included data of 120 patients undergoing clinically indicated chest (n = 68) and abdomen (n = 52) CT. Fifty-two of the patients were scanned with CT using a table height manually selected by technologists; 68 patients were automatically positioned with the 3D camera, which is based on patient-specific body surface and contour detection. The ground truth table height (TGT) was defined as the table height that aligns the axial center of the patient's body region in the CT scanner isocenter. Off-centering was defined as the difference between the ground truth table height (TGT) and the actual table position used in all CT examinations. The t test was performed to determine significant differences in the vertical offset between automatic and manual positioning. The χ test was used to check whether there was a relationship between patient size and the magnitude of off-centering. RESULTS: We found a significant improvement in patient centering (offset 5 ± 3 mm) when using the automatic positioning algorithm with the 3D camera compared with manual positioning (offset 19 ± 10 mm) performed by technologists (P < 0.005). Automatic patient positioning based on the 3D camera reduced the average offset in vertical table position from 19 mm to 7 mm for chest and from 18 mm to 4 mm for abdomen CT. The absolute maximal offset was 39 mm and 43 mm for chest and abdomen CT, respectively, when patients were positioned manually, whereas with automatic positioning using the 3D camera the offset never exceeded 15 mm. In chest CT performed with manual patient positioning, we found a significant correlation between vertical offset greater than 20 mm and patient size (body mass index, >26 kg/m, P < 0.001). In contrast, no such relationship was found for abdomen CT (P = 0.38). CONCLUSIONS: Automatic individualized patient positioning using a 3D camera allows for accurate patient centering as compared with manual positioning, which improves radiation dose utilization.

New insights into the formation of silver-based nanoparticles under natural and semi-natural conditions.

For the first time, the natural formation of silver-based nanoparticles (Ag-b-NPs) was studied in field investigations of two pre-alpine lakes in Germany that contain geogenic silver traces in the sub-ng L-1 range. Light-sensitive microorganisms most likely accumulate and transport these silver traces from deeper water layers to the surface. At the surface of the eutrophic lake, approximately 40% of total silver (5.7 ng L-1) consisted of Ag-b-NPs, whereas in the oligotrophic lake with similar enrichment of silver species, no Ag-b-NPs were detected. Additional lab experiments with nature-related Ag(I) concentrations in the lower-ng L-1 range and natural organic matter with total organic carbon values of ≤5 mg L-1 revealed that, contrary to common interpretation in the literature, Ag-b-NPs are also or even preferably formed in the dark. Particle size increases gradually with increasing reaction time, showing that Ostwald ripening occurs even at such low particle concentrations. When sulfide ions are present, smaller Ag-b-NPs with a narrower size distribution are formed.

Upregulation of the aging related LMNA splice variant progerin in dilated cardiomyopathy.

BACKGROUND: Mutations in the LMNA gene are a common cause (6-8%) of dilated cardiomyopathy (DCM) leading to heart failure, a growing health care problem worldwide. The premature aging disease Hutchinson-Gilford syndrome (HGPS) is also caused by defined mutations in the LMNA gene resulting in activation of a cryptic splice donor site leading to a defective truncated prelamin A protein called progerin. Low levels of progerin are expressed in healthy individuals associated with ageing. Here, we aimed to address the role of progerin in dilated cardiomyopathy. METHODS AND RESULTS: mRNA expression of progerin was analyzed in heart tissue of DCM (n = 15) and non-failing hearts (n = 10) as control and in blood samples from patients with DCM (n = 56) and healthy controls (n = 10). Sequencing confirmed the expression of progerin mRNA in the human heart. Progerin mRNA levels derived from DCM hearts were significantly upregulated compared to controls (1.27 ± 0.42 vs. 0.81 ± 0.24; p = 0.005). In contrast, progerin mRNA levels in whole blood cells were not significantly different in DCM patients compared to controls. Linear regression analyses revealed that progerin mRNA in the heart is significantly negatively correlated to ejection fraction (r = -0.567, p = 0.003) and positively correlated to left ventricular enddiastolic diameter (r = 0.551, p = 0.004) but not with age of the heart per se. Progerin mRNA levels were not influenced by inflammation in DCM hearts. Immunohistochemistry and Immunofluorescence analysis confirmed increased expression of progerin protein in cell nuclei of DCM hearts associated with increased TUNEL+ apoptotic cells. CONCLUSION: Our data suggest that progerin is upregulated in human DCM hearts and strongly correlates with left ventricular remodeling. Progerin might be involved in progression of heart failure and myocardial aging.

Formation of iron oxide nanoparticles for the photooxidation of water: Alteration of finite size effects from ferrihydrite to hematite.

Iron oxide nanoparticles represent a promising low-cost environmentally-friendly material for multiple applications. Especially hematite (α-Fe2O3) nanoparticles demonstrate great possibilities in energy storage and photoelectrochemistry. A hydrothermal one-pot synthesis can be used to synthesise hematite nanoparticles. Here, the particle formation, nucleation and growth of iron oxide nanoparticles using a FeCl3 precursor over time is monitored. The formation of 6-line ferrihydrite seeds of 2-8 nm which grow with reaction time and form clusters followed by a phase transition to ~15 nm hematite particles can be observed with ex situ X-ray diffraction (XRD), transmission electron microscopy (TEM), Raman and UV/Vis spectroscopy. These particles grow with reaction time leading to 40 nm particles after 6 hours. The changes in plasmon and electron transition patterns, observed upon particle transition and growth lead to the possibility of tuning the photoelectrochemical properties. Catalytic activity of the hematite nanoparticles can be proven with visible light irradiation and the use of silver nitrate as scavenger material. The generation of elementary silver is dependent on the particle size of iron oxide nanoparticles while only slight changes can be observed in the oxygen generation. Low-cost nanoscale hematite, offers a range of future applications for artificial photosynthesis.

Band Transport and Trapping in Didodecyl[1]benzothieno[3,2-b][1]benzothiophene Probed by Terahertz Spectroscopy.

Terahertz electromodulation spectroscopy provides insight into the material-inherent transport properties of charge carriers in organic semiconductors. Experiments on didodecyl[1]benzothieno[3,2-b][1]benzothiophene (C12-BTBT-C12) devices yield for holes an intraband mobility of 9 cm2 V-1 s-1. The short duration of the THz pulses advances the understanding of the hole transport on the molecular scale. The efficient screening of Coulomb potentials leads to a collective response of the hole gas to external fields, which can be well described by the Drude model. Bias stress of the devices generates deep traps that capture mobile holes. Although the resulting polarization across the device hinders the injection of mobile holes, the hole mobilities are not affected.