Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models

The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture, which we call DeepVess, yielded a segmentation accuracy that was better than both the current state-of-the-art and a trained human annotator, while also being orders of magnitude faster. To explore the effects of aging and Alzheimer's disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer's disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments ($>75\mu m$) in aged animals as compared to young, in both wild type and Alzheimer's disease mouse models.Comment: 34 pages, 9 figure

Soil loss prediction using universal soil loss equation (USLE) simulation model in a mountainous area in Aglasun district, Turkey

Land degradation and soil loss is a global event. Human induced pressures on the natural ecosystems are still in progress as well as conservation efforts. The need for sufficient knowledge and data for decision makers is obvious hence the present study was carried out. The study area, the Alasun district, is in the middle west of Turkey and is characterized by a cold and sub-humid Mediterranean climate. The mountainous area is mostly covered with average low canopy closure of 11 - 40% of different forest species (52% of the study area). Universal soil loss equation (USLE) simulation model was used to predict the soil loss amounts in the study area. The results show that the predicted average soil loss amount is 7.38 (ton/ha/year). The average soil depth is about 35 cm and the soil loss tolerance limit is widely exceeded in the study area

The Two-loop Anomalous Dimension Matrix for Soft Gluon Exchange

The resummation of soft gluon exchange for QCD hard scattering requires a matrix of anomalous dimensions. We compute this matrix directly for arbitrary 2 to n massless processes for the first time at two loops. Using color generator notation, we show that it is proportional to the one-loop matrix. This result reproduces all pole terms in dimensional regularization of the explicit calculations of massless 2 to 2 amplitudes in the literature, and it predicts all poles at next-to-next-to-leading order in any 2 to n process that has been computed at next-to-leading order. The proportionality of the one- and two-loop matrices makes possible the resummation in closed form of the next-to-next-to-leading logarithms and poles in dimensional regularization for the 2 to n processes.Comment: 5 pages, 1 figure, revte

A Material Perspective on Consequence of Deformation Heating During Stamping of DP Steels

Recent studies showed that, during stamping of high strength steels at industrially relevant production rates, local temperature in the blank may rise up to 200°C – 300°C due to deformation heating. Moreover, die temperature may also rise up to 100°C – 150°C for progressive stamping dies. Based on the common assumption that the blank softens as the temperature increases, thermal softening creates a margin in Forming Limit Diagram (FLD) and therefore the FLD determined at room temperature can safely be used for those cases. In this article, the validity of this assumption on DP590 steel is questioned by high temperature tensile tests (RT - 300°C) at various strain rates (10-3 s-1 – 1 s-1). The results indicated a decrease both in uniform and total elongation in 200°C – 300°C range together with several other symptoms of Dynamic Strain Aging (DSA) at all strain rates. Concurrent with the DSA, the simulated FLD confirms the lower formability at high temperature and strain rates. Thus, it is concluded FLD determined at RT may not be valid for the investigated steels

Low/Zero-Carbon Buildings for a Sustainable Future

Fossil fuel-based energy consumption is still dominant in the world today, and there is a consensus on the limited reserves of these energy resources. Therefore, there is a strong stimulation into clean energy technologies to narrow the gap between fossil fuels and renewables. In this respect, several commitments and codes are proposed and adopted for a low energy-consuming world and for desirable environmental conditions. Sectoral energy consumption analyses clearly indicate that buildings are of vital importance in terms of energy consumption figures. From this point of view, buildings have a great potential for decisive and urgent reduction of energy consumption levels and thus greenhouse gas (GHG) emissions. Among the available retrofit solutions, greenery systems (GSs) stand for a reliable, cost-effective and eco-friendly method for remarkablemitigation of energy consumed in buildings. Through the works comparing the thermal regulation performance of uninsulated and green roofs, it is observed that the GS provides 20°C lower surface temperature in operation. Similar to green roofs, vertical greenery systems (VGSs) also reduce energy demand to approximately 25% as a consequence of wind blockage effects in winter. Therefore, within the scope of this chapter, GSs are evaluated for a reliable and effective retrofit solution toward low/zero carbon buildings (L/ZCBs)

Internet of Harvester Nano Things: A Future Prospects

The advancements in nanotechnology, material science, and electrical engineering have shrunk the sizes of electronic devices down to the micro/nanoscale. This brings the opportunity of developing the Internet of Nano Things (IoNT), an extension of the Internet of Things (IoT). With nanodevices, numerous new possibilities emerge in the biomedical, military fields, and industrial products. However, a continuous energy supply is needed for these devices to work. At the micro/nanoscale, batteries cannot supply this demand due to size limitations and the limited energy contained in the batteries. Internet of Harvester Nano Things (IoHNT), a concept of Energy Harvesting (EH), which converts the existing different energy sources, which otherwise would be dissipated to waste, into electrical energy via electrical generators. Sources for EH are abundant, from sunlight, sound, water, and airflow to living organisms. IoHNT methods are significant assets to ensure the proper operation of the IoNT; thus, in this review, we comprehensively investigate the most useful energy sources and IoHNT principles to power the nano/micro-scaled electronic devices with the scope of IoNT. We discuss the IoHNT principles, material selections, challenges, and state-of-the-art applications of each energy source for both in-vivo and in vitro applications. Finally, we present the latest challenges of EH along with future research directions to solve the problems regarding constructing continuous IoNT containing various self-powered nanodevices. Therefore, IoHNT represents a significant shift in nanodevice power supply, leading us towards a future where wireless technology is widespread. Hence, it will motivate researchers to envision and contribute to the advancement of the following power revolution in IoNT, providing unmatched simplicity and efficiency

Stability of Scalar Fields in Warped Extra Dimensions

This work sets up a general theoretical framework to study stability of models with a warped extra dimension where N scalar fields couple minimally to gravity. Our analysis encompasses Randall-Sundrum models with branes and bulk scalars, and general domain-wall models. We derive the Schrodinger equation governing the spin-0 spectrum of perturbations of such a system. This result is specialized to potentials generated using fake supergravity, and we show that models without branes are free of tachyonic modes. Turning to the existence of zero modes, we prove a criterion which relates the number of normalizable zero modes to the parities of the scalar fields. Constructions with definite parity and only odd scalars are shown to be free of zero modes and are hence perturbatively stable. We give two explicit examples of domain-wall models with a soft wall, one which admits a zero mode and one which does not. The latter is an example of a model that stabilizes a compact extra dimension using only bulk scalars and does not require dynamical branes.Comment: 25 pages, 2 figures; v2: minor changes to text, references added, matches published versio

Solitary Fibrous Tumors of Chest: Another Look with the Oncologic Perspective

Solitary fibrous tumors are mesenchymal lesions that arise at a variety of sites, most commonly the pleura. Most patients are asymptomatic at diagnosis, with lesions being detected incidentally. Nevertheless, some patients present due to symptoms from local tumor compression (eg. of the airways and pulmonary parenchyma). Furthermore, radiological methods are not always conclusive in making a diagnosis, and thus, pathological analysis is often required. In the past three decades, immunohistochemical techniques have provided a gold standard in solitary fibrous tumor diagnosis. The signature marker of solitary fibrous tumor is the presence of the NAB2-STAT6 fusion that can be reliably detected with a STAT6 antibody. While solitary fibrous tumors are most often benign, they can be malignant in 10-20% of the cases. Unfortunately, histological parameters are not always predictive of benign vs malignant solitary fibrous tumors. As solitary fibrous tumors are generally regarded as relatively chemoresistant tumors; treatment is often limited to localized treatment modalities. The optimal treatment of solitary fibrous tumors appears to be complete surgical resection for both primary and local recurrent disease. However, in cases of suboptimal resection, large disease burden, or advanced recurrence, a multidisciplinary approach may be preferable. Specifically, radiotherapy for inoperable local disease can provide palliation/shrinkage. Given their sometimes -unpredictable and often- protracted clinical course, long-term follow-up post-resection is recommended

Supervised Nonparametric Image Parcellation

Author Manuscript 2010 August 25. 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part IISegmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing the data alleviates the computational burden at the expense of possibly losing valuable information on inter-subject variability. This paper presents a novel framework for Supervised Nonparametric Image Parcellation (SNIP). SNIP models the intensity and label images as samples of a joint distribution estimated from the training data in a non-parametric fashion. By capitalizing on recently developed fast and robust pairwise image alignment tools, SNIP employs the entire training data to segment a new image via Expectation Maximization. The use of multiple registrations increases robustness to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with manual labels for the white matter, cortex and subcortical structures. SNIP yields better segmentation than state-of-the-art algorithms in multiple regions of interest.NAMIC (NIHNIBIBNAMICU54-EB005149)NAC (NIHNCRRNACP41-RR13218)mBIRN (NIHNCRRmBIRNU24-RR021382)NIH NINDS (Grant R01-NS051826)National Science Foundation (U.S.) (CAREER Grant 0642971)NCRR (P41-RR14075)NCRR (R01 RR16594-01A1)NIBIB (R01 EB001550)NIBIB (R01EB006758)NINDS (R01 NS052585-01)Mind Research InstituteEllison Medical FoundationSingapore. Agency for Science, Technology and Researc