A photocatalytic rotating disc reactor with TiO<font size=-1>₂</font> nanowire arrays deposited for industrial watewater treatment

published_or_final_versio

The human initiator is a distinct and abundant element that is precisely positioned in focused core promoters.

DNA sequence signals in the core promoter, such as the initiator (Inr), direct transcription initiation by RNA polymerase II. Here we show that the human Inr has the consensus of BBCA+1BW at focused promoters in which transcription initiates at a single site or a narrow cluster of sites. The analysis of 7678 focused transcription start sites revealed 40% with a perfect match to the Inr and 16% with a single mismatch outside of the CA+1 core. TATA-like sequences are underrepresented in Inr promoters. This consensus is a key component of the DNA sequence rules that specify transcription initiation in humans

Performance assessment of a programmable five degrees-of-freedom motion platform for quality assurance of motion management techniques in radiotherapy.

Inter-fraction and intra-fraction motion management methods are increasingly applied clinically and require the development of advanced motion platforms to facilitate testing and quality assurance program development. The aim of this study was to assess the performance of a 5 degrees-of-freedom (DoF) programmable motion platform HexaMotion (ScandiDos, Uppsala, Sweden) towards clinically observed tumor motion range, velocity, acceleration and the accuracy requirements of SABR prescribed in AAPM Task Group 142. Performance specifications for the motion platform were derived from literature regarding the motion characteristics of prostate and lung tumor targets required for real time motion management. The performance of the programmable motion platform was evaluated against (1) maximum range, velocity and acceleration (5 DoF), (2) static position accuracy (5 DoF) and (3) dynamic position accuracy using patient-derived prostate and lung tumor motion traces (3 DoF). Translational motion accuracy was compared against electromagnetic transponder measurements. Rotation was benchmarked with a digital inclinometer. The static accuracy and reproducibility for translation and rotation was <0.1 mm or <0.1°, respectively. The accuracy of reproducing dynamic patient motion was <0.3 mm. The motion platform’s range met the need to reproduce clinically relevant translation and rotation ranges and its accuracy met the TG 142 requirements for SABR. The range, velocity and acceleration of the motion platform are sufficient to reproduce lung and prostate tumor motion for motion management. Programmable motion platforms are valuable tools in the investigation, quality assurance and commissioning of motion management systems in radiation oncology

The effects of different fatigue levels on brain–behavior relationships in driving

© 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. Background: In the past decade, fatigue has been regarded as one of the main factors impairing task performance and increasing behavioral lapses during driving, even leading to fatal car crashes. Although previous studies have explored the impact of acute fatigue through electroencephalography (EEG) signals, it is still unclear how different fatigue levels affect brain–behavior relationships. Methods: A longitudinal study was performed to investigate the brain dynamics and behavioral changes in individuals under different fatigue levels by a sustained attention task. This study used questionnaires in combination with actigraphy, a noninvasive means of monitoring human physiological activity cycles, to conduct longitudinal assessment and tracking of the objective and subjective fatigue levels of recruited participants. In this study, degrees of effectiveness score (fatigue rating) are divided into three levels (normal, reduced, and high risk) by the SAFTE fatigue model. Results: Results showed that those objective and subjective indicators were negatively correlated to behavioral performance. In addition, increased response times were accompanied by increased alpha and theta power in most brain regions, especially the posterior regions. In particular, the theta and alpha power dramatically increased in the high-fatigue (high-risk) group. Additionally, the alpha power of the occipital regions showed an inverted U-shaped change. Conclusion: Our results help to explain the inconsistent findings among existing studies, which considered the effects of only acute fatigue on driving performance while ignoring different levels of resident fatigue, and potentially lead to practical and precise biomathematical models to better predict the performance of human operators

Performance assessment of a programmable five degrees-of-freedom motion platform for quality assurance of motion management techniques in radiotherapy.

Inter-fraction and intra-fraction motion management methods are increasingly applied clinically and require the development of advanced motion platforms to facilitate testing and quality assurance program development. The aim of this study was to assess the performance of a 5 degrees-of-freedom (DoF) programmable motion platform HexaMotion (ScandiDos, Uppsala, Sweden) towards clinically observed tumor motion range, velocity, acceleration and the accuracy requirements of SABR prescribed in AAPM Task Group 142. Performance specifications for the motion platform were derived from literature regarding the motion characteristics of prostate and lung tumor targets required for real time motion management. The performance of the programmable motion platform was evaluated against (1) maximum range, velocity and acceleration (5 DoF), (2) static position accuracy (5 DoF) and (3) dynamic position accuracy using patient-derived prostate and lung tumor motion traces (3 DoF). Translational motion accuracy was compared against electromagnetic transponder measurements. Rotation was benchmarked with a digital inclinometer. The static accuracy and reproducibility for translation and rotation was <0.1 mm or <0.1°, respectively. The accuracy of reproducing dynamic patient motion was <0.3 mm. The motion platform’s range met the need to reproduce clinically relevant translation and rotation ranges and its accuracy met the TG 142 requirements for SABR. The range, velocity and acceleration of the motion platform are sufficient to reproduce lung and prostate tumor motion for motion management. Programmable motion platforms are valuable tools in the investigation, quality assurance and commissioning of motion management systems in radiation oncology

Learning Shape Priors for Single-View 3D Completion and Reconstruction

The problem of single-view 3D shape completion or reconstruction is challenging, because among the many possible shapes that explain an observation, most are implausible and do not correspond to natural objects. Recent research in the field has tackled this problem by exploiting the expressiveness of deep convolutional networks. In fact, there is another level of ambiguity that is often overlooked: among plausible shapes, there are still multiple shapes that fit the 2D image equally well; i.e., the ground truth shape is non-deterministic given a single-view input. Existing fully supervised approaches fail to address this issue, and often produce blurry mean shapes with smooth surfaces but no fine details. In this paper, we propose ShapeHD, pushing the limit of single-view shape completion and reconstruction by integrating deep generative models with adversarially learned shape priors. The learned priors serve as a regularizer, penalizing the model only if its output is unrealistic, not if it deviates from the ground truth. Our design thus overcomes both levels of ambiguity aforementioned. Experiments demonstrate that ShapeHD outperforms state of the art by a large margin in both shape completion and shape reconstruction on multiple real datasets.Comment: ECCV 2018. The first two authors contributed equally to this work. Project page: http://shapehd.csail.mit.edu

Quality assurance for the clinical implementation of kilovoltage intrafraction monitoring for prostate cancer VMAT.

PURPOSE: Kilovoltage intrafraction monitoring (KIM) is a real-time 3D tumor monitoring system for cancer radiotherapy. KIM uses the commonly available gantry-mounted x-ray imager as input, making this method potentially more widely available than dedicated real-time 3D tumor monitoring systems. KIM is being piloted in a clinical trial for prostate cancer patients treated with VMAT (NCT01742403). The purpose of this work was to develop clinical process and quality assurance (QA) practices for the clinical implementation of KIM. METHODS: Informed by and adapting existing guideline documents from other real-time monitoring systems, KIM-specific QA practices were developed. The following five KIM-specific QA tests were included: (1) static localization accuracy, (2) dynamic localization accuracy, (3) treatment interruption accuracy, (4) latency measurement, and (5) clinical conditions accuracy. Tests (1)-(4) were performed using KIM to measure static and representative patient-derived prostate motion trajectories using a 3D programmable motion stage supporting an anthropomorphic phantom with implanted gold markers to represent the clinical treatment scenario. The threshold for system tolerable latency is <1 s. The tolerances for all other tests are that both the mean and standard deviation of the difference between the programmed trajectory and the measured data are <1 mm. The (5) clinical conditions accuracy test compared the KIM measured positions with those measured by kV/megavoltage (MV) triangulation from five treatment fractions acquired in a previous pilot study. RESULTS: For the (1) static localization, (2) dynamic localization, and (3) treatment interruption accuracy tests, the mean and standard deviation of the difference are <1.0 mm. (4) The measured latency is 350 ms. (5) For the tests with previously acquired patient data, the mean and standard deviation of the difference between KIM and kV/MV triangulation are <1.0 mm. CONCLUSIONS: Clinical process and QA practices for the safe clinical implementation of KIM, a novel real-time monitoring system using commonly available equipment, have been developed and implemented for prostate cancer VMAT

Identification of Individual Glandular Regions Using LCWT and Machine Learning Techniques

A new approach for the segmentation of gland units in histological images is proposed with the aim of contributing to the improvement of the prostate cancer diagnosis. Clustering methods on several colour spaces are applied to each sample in order to generate a binary mask of the different tissue components. From the mask of lumen candidates, the Locally Constrained Watershed Transform (LCWT) is applied as a novel gland segmentation technique never before used in this type of images. 500 random gland candidates, both benign and pathological, are selected to evaluate the LCWT technique providing results of Dice coefficient of 0.85. Several shape and textural descriptors in combination with contextual features and a fractal analysis are applied, in a novel way, on different colour spaces achieving a total of 297 features to discern between artefacts and true glands. The most relevant features are then selected by an exhaustive statistical analysis in terms of independence between variables and dependence with the class. 3.200 artefacts, 3.195 benign glands and 3.000 pathological glands are obtained, from a data set of 1468 images at 10x magnification. A careful strategy of data partition is implemented to robustly address the classification problem between artefacts and glands. Both linear and non-linear approaches are considered using machine learning techniques based on Support Vector Machines (SVM) and feedforward neural networks achieving values of sensitivity, specificity and accuracy of 0.92, 0.97 and 0.95, respectivelyThis work has been funded by the Ministry of Economy, Industry and Competitiveness under the SICAP project (DPI2016-77869-C2-1-R). The work of Adri´an Colomer has been supported by the Spanish FPI Grant BES-2014-067889. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this researchGarcía-Pardo, JG.; Colomer, A.; Naranjo Ornedo, V.; Peñaranda, F.; Sales, MÁ. (2018). Identification of Individual Glandular Regions Using LCWT and Machine Learning Techniques. En Intelligent Data Engineering and Automated Learning – IDEAL 2018. Springer. 642-650. https://doi.org/10.1007/978-3-030-03493-1_67S642650Gleason, D.F.: Histologic grading and clinical staging of prostatic carcinoma. In: Urologic Pathology (1977)Naik, S., Doyle, S., Feldman, M., Tomaszewski, J., Madabhushi, A.: Gland segmentation and computerized gleason grading of prostate histology by integrating low-, high-level and domain specific information. In: MIAAB Workshop, pp. 1–8 (2007)Nguyen, K., Sabata, B., Jain, A.K.: Prostate cancer grading: gland segmentation and structural features. Pattern Recogn. Lett. 33(7), 951–961 (2012)Kwak, J.T., Hewitt, S.M.: Multiview boosting digital pathology analysis of prostate cancer. Comput. Methods Programs Biomed. 142, 91–99 (2017)Ren, J., Sadimin, E., Foran, D.J., Qi, X.: Computer aided analysis of prostate histopathology images to support a refined gleason grading system. In: SPIE Medical Imaging, International Society for Optics and Photonics, p. 101331V (2017)Soille, P.: Morphological Image Analysis: Principles and Applications. Springer, Berlin (2013)Nguyen, K., Sarkar, A., Jain, A.K.: Structure and context in prostatic gland segmentation and classification. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012. LNCS, vol. 7510, pp. 115–123. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33415-3_15Beare, R.: A locally constrained watershed transform. IEEE Trans. Pattern Anal. Mach. Intell. 28(7), 1063–1074 (2006)Gertych, A., et al.: Machine learning approaches to analyze histological images of tissues from radical prostatectomies. Comput. Med. Imaging Graph. 46, 197–208 (2015)Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)Guo, Z., Zhang, L., Zhang, D.: A completed modeling of local binary pattern operator for texture classification. IEEE Trans. Image Process. 19(6), 1657–1663 (2010)Huang, P., Lee, C.: Automatic classification for pathological prostate images based on fractal analysis. IEEE Trans. Med. Imaging 28(7), 1037–1050 (2009)Ruifrok, A.C., Johnston, D.A., et al.: Quantification of histochemical staining by color deconvolution. Anal. Quant. Cytol. Histol. 23(4), 291–299 (2001

Forward-backward Asymmetry and Branching Ratio of B \rar K_1 \ell^+ \ell^- Transition in Supersymmetric Models

The mass eigen states $K_1(1270)$ and $K_1(1400)$ are mixture of the strange members of two axial-vector SU(3) octet, $^3P_1(K_1^A)$ and $^1P_1(K_1^B)$. Taking into account this mixture, the forward-backward asymmetry and branching ratio of B \rar K_1(1270,1400) \ell^+ \ell^- transitions are studied in the framework of different supersymmetric models. It is found that the results have considerable deviation from the standard model predictions. Any measurement of these physical observables and their comparison with the results obtained in this paper can give useful information about the nature of interactions beyond the standard model.Comment: 14 pages, 4 figure