75 resultados para SEGMENTS


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PURPOSE: The pig eye is similar to the human eye in terms of anatomy, vasculature, and photoreceptor distribution, and therefore provides an attractive animal model for research into retinal disease. The purpose of this study was to characterize retinal histology in the developing and mature pig retina using antibodies to well established retinal cell markers commonly used in rodents.

METHODS: Eyes were enucleated from fetuses in the 9th week of gestation, 1 week old piglets and 6 months old adult animals. Eyeglobes were fixed and cryosectioned. A panel of antibodies to well established retinal markers was employed for immunohistochemistry. Fluorescently labeled secondary antibodies were used for signal detection, and images were acquired by confocal microscopy. Mouse retina at postnatal day (P) 5 was used as a reference for this study to compare progression of histogenesis. Most of the primary antibodies have previously been used on mouse tissue.

RESULTS: Most of the studied markers were detected in midgestation pig retina, and the majority had a similar distribution in pig as in P5 mouse retina. However, rhodopsin immunolabeling was detected in pig retina at midgestation but not in P5 mouse retina. Contrary to findings in all rodents, horizontal cells were Islet1-positive and cones were calbindin-immunoreactive in pig retina, as has also been shown for the primate retina. Recoverin and rhodopsin immunolabeling revealed an increase in the length of photoreceptor segments in 6 months, compared to 1 week old animals.

CONCLUSIONS: Comparison with the published data on human retina revealed similar marker distribution and histogenesis progression in the pig and human retina, supporting the pig as a valuable animal model for studies on retinal disease and repair. Furthermore, this study provides information about the dynamics of retinal histogenesis in the pig and validates a panel of antibodies that reliably detects developing and mature retinal cell phenotypes in the pig retina.

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The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

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Purpose. To investigate the robustness of single vocal cord intensity modulated radiation therapy (IMRT) treatment plans for set-up errors, respiration, and deformation. Material and methods. Four-dimensional computed tomography (4D-CT) scans of 10 early glottic carcinoma patients, previously treated with conventional techniques, were used in this simulation study. For each patient a pre-treatment 4D-CT was used for IMRT planning, generating a reference dose distribution. Prescribed PTV dose was 66 Gy. The impact of systematic set-up errors was simulated by applying shifts of ± 2 mm to the planning CT scans, followed by dose re-calculation with original beam segments, MUs, etc. Effects of respiration and deformation were determined utilizing extreme inhale and exhale CT scans, and repeat scans acquired after 22 Gy, 44 Gy, and 66 Gy, respectively. All doses were calculated using Monte Carlo dose simulations. Results. Considering all investigated geometrical perturbations, reductions in the clinical target volume (CTV) V95%, D98%, D2%, and generalized equivalent uniform dose (gEUD) were limited to 1.2 ± 2.2%, 2.4 ± 2.9%, 0.2 ± 1.8%, and 0.6 ± 1.1 Gy, respectively. The near minimum dose, D98%, was always higher than 89%, and gEUD always remained higher than 66 Gy. Planned contra-lateral (CL) vocal cord DMean, gEUD, and V40 Gy were 38.2 ± 6.0 Gy, 43.4 ± 5.6 Gy, and 42.7 ± 14.9%. With perturbations these values changed by -0.1 ± 4.3 Gy, 0.1 ± 4.0 Gy, and -1.0 ± 9.6%, respectively. Conclusions. On average, CTV dose reductions due to geometrical perturbations were very low, and sparing of the CL vocal cord was maintained. In a few observations (6 of 103 simulated situations), the near-minimum CTV-dose was around 90%, requiring attention in deciding on a future clinical protocol. 

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Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading that incorporates these and additional subprocesses, simultaneously discovering their fMRI signatures. Our model predicts the fMRI activity associated with reading arbitrary text passages, well enough to distinguish which of two story segments is being read with 74% accuracy. This approach is the first to simultaneously track diverse reading subprocesses during complex story processing and predict the detailed neural representation of diverse story features, ranging from visual word properties to the mention of different story characters and different actions they perform. We construct brain representation maps that replicate many results from a wide range of classical studies that focus each on one aspect of language processing and offer new insights on which type of information is processed by different areas involved in language processing. Additionally, this approach is promising for studying individual differences: it can be used to create single subject maps that may potentially be used to measure reading comprehension and diagnose reading disorders.

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Purpose: We have shown previously that macrophages/microglia accumulate in the subretinal space and express CD68 and Arginase-1 in the aging eye. Subretinal macrophages are in close contact with retinal pigment epithelial (RPE) cells. We hypothesize that RPE cells may play an important role in regulating macrophage/microglial phenotype and function. The aim of this study was to investigate the effect of RPE cells on the phenotype and function of bone marrow–derived macrophages (BM-DMs).
Methods: BM-DM from C57BL/6J mice were cultured in DMEM supplemented with 20%L929 cell supernatant for 5 days. The phenotype of BM-DMs was confirmed by flow cytometry as CD11b+F4/80+. Primary RPE cells were cultured from C57BL/6J mice and confirmed by RPE65 and cytokeratin staining. BMDMs were co-cultured with different types of RPE cells (healthy, oxidized, and apoptotic RPE) and then isolated from the co-culture system for phenotypic and functional assays.
Results: Co-culture of BM-DMs with RPE cells results in a time-dependent down-regulation of MHC-II expression and the generation of CD11b+F4/80+Ly6G+ myeloid-derived suppressor cells (MDSC). qRT-PCR analysis showed that RPE-induced MDSCs expressed high levels of IL-6, IL-1β, and Arginase-1, but lower levels of IL-12p40 and TNF-a compared to naïve BM-DMs. The expression levels of iNOS, TGF-β and Ym1 did not differ 207 between naive BMDMs and RPE-induced MDSCs. Furthermore, functional studies showed that these cells had reduced phagocytic activity and lower ability to stimulate T cell activation and proliferation. When RPE cells were pre-treated with oxidized photoreceptor outer segments before co-culturing with BMDMs, the expression of IL-1β and IL-6 in BMDMs was increased whereas the expression of Arginase-1 was decreased. 
Conclusion: Our results suggest that healthy RPE cells can convert BMDMs into myeloid-derived suppressor cells under in vitro culture conditions, RPE-induced myeloid-derived suppressor cells are CD11b+F4/80+Ly6G+MHCIIlowIL6+IL1b+Arg-1+. The ability of RPE cells is reduced when suffering from oxidative insults.

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Relatively few measurements of the solar phase function of cometary nuclei exist, despite the importance of this parameter in determining accurate sizes and its use in modeling surface properties. We make use of robotic telescopes and servicemode observing to monitor cometary nuclei over months at a time, combining intensive observations at a single epoch with regular short light-curve segments to efficiently account for brightness changes due to both nucleus rotation and changing solar phase angle. We present our latest results on comets 8P/Tuttle, 14P/Wolf, 67P/Churyumov- Gerasimenko and 110P/Hartley 3.

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Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

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Purpose: Although L-type Ca2+ channels are known to play a key role in the myogenic reactivity of retinal arterial vessels, the involvement of other types of voltage-gated Ca2+ channels in this process remains unknown. In the present study we have investigated the contribution of T-type Ca2+ channels to myogenic signalling in arterioles of the rat retinal microcirculation.

Methods: Confocal immunolabelling of wholemount preparations was used to investigate the localisation of CaV3.1-3 channels in retinal arteriolar smooth muscle cells. T-type currents and the contribution of T-type channels to myogenic signalling were assessed by whole-cell patch-clamp recording and pressure myography of isolated retinal arteriole segments.

Results: Strong immunolabelling for CaV3.1 was observed on the plasma membrane of retinal arteriolar smooth muscle cells. In contrast, no expression of CaV3.2 or CaV3.3 could be detected in retinal arterioles, although these channels were present on glial cell end feet surrounding the vessels and retinal ganglion cells, respectively. TTA-A2 sensitive T-type currents were recorded in retinal arteriolar myocytes with biophysical properties distinct from those of the L-type currents present in these cells. Inhibition of T-type channels using TTA-A2 or ML-218 dilated isolated, myogenically active, retinal arterioles.

Conclusions: CaV3.1 T-type Ca2+ channels are functionally expressed on arteriolar smooth muscle cells of retinal arterioles and play an important role in myogenic signalling in these vessels. The work has important implications concerning our understanding of the mechanisms controlling blood flow autoregulation in the retina and its disruption during ocular disease.

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Purpose: Cataract surgery increases the risk of developing diabetic retinopathy (DR) and accelerates the progression of pre-existing DR. Recent evidence suggests that cataract surgery elicits retinal pro-inflammatory gene expression, although the underlying pathogenic mechanisms remain ill-defined. In this study, we investigated the effect of capsulotomy on visual function, retinal immune cell activation and photoreceptor stress in the Ins2Akita mice, a mouse model of Type-1 diabetes. Methods: Male heterozygous Ins2Akita mice (2 months of hyperglycemia) and C57BL/6J age-matched siblings were used in this study. An incision (1mm) was made in the peripheral cornea and Capsulotomy was performed in the anterior lens capsule of the right eye. Control mice received corneal incision without capsulotomy in the right eye. The unoperated left eyes were used as internal controls. Forty days following surgery, retinal function was assessed by electroretinography (ERG). Neuronal retinal damage and microglial activation were assessed by imunohistochemistry. Results: The Ins2Akita mice receiving capsulotomy presented lower scotopic a-wave, b-wave and oscillatory potentials amplitudes compared to other experimental groups. Fundus images, SD-OCT and H&E staining did not show significant changes between different groups. Immunostaining of Iba-1 and CD68 revealed exacerbated microglial activation and giant cell immune cell infiltration in eyes receiving capsulotomy in Ins2Akita mice. This was accompanied by a disruption of cone photoreceptor outer segments and abnormal rhodopsin expression at the outer nuclear layer. Conclusions: Our results suggest that capsulotomy induces retinal microglial activation and worsens retinal neuropathy in diabetic eyes.

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This paper presents a new approach to speech enhancement from single-channel measurements involving both noise and channel distortion (i.e., convolutional noise), and demonstrates its applications for robust speech recognition and for improving noisy speech quality. The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise for speech estimation. Third, we present an iterative algorithm which updates the noise and channel estimates of the corpus data model. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.

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This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement. Index Terms: corpus-based speech model, longest matching segment, speech enhancement, speech recognition

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Textbook introducing the fundamentals of aircraft performance using industry standards and examples: bridging the gap between academia and industry
•Provides an extensive and detailed treatment of all segments of mission profile and overall aircraft performance
•Considers operating costs, safety, environmental and related systems issues
•Includes worked examples relating to current aircraft (Learjet 45, Tucano Turboprop Trainer, Advanced Jet Trainer and Airbus A320 types of aircraft)
•Suitable as a textbook for aircraft performance courses

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Standard identification systems usually ensure that biopsy material is correctly associated with a given patient. Sometimes, as when a tumor is unexpectedly found, the provenance (proof of origin) of a tissue sample may be questioned; the tissue may have been mislabelled or contaminated with tissue from another patient. Techniques used to confirm tissue provenance include comparing either tissue markers of gender or ABO blood groups; however, these methods have weak confirmatory power. Recently, the use of DNA-based polymerase chain reaction (PCR) techniques has been reported. Paired, formalin-fixed, paraffin-embedded, 10 microns tissue sections were selected from 17 patients, 8 of whom had carcinoma, either by dividing a biopsy section, using sequential biopsies, or sequential biopsy and autopsy tissue. The resulting 36 samples were coded before analysis. In two additional cases, 1-mm fragments of tumor from one patient were included in the tissue block of benign tissue from another patient, the tumor fragments were identified on hematoxylin-and-eosin-stained sections, separately scraped off the glass slide, and analyzed. Tissue from two clinical cases, one of suspected mislabelling and one with a suspected carry-over of malignant tissue were also investigated. Short tandem repeat sequences (STR) or microsatellites, are 2-5 base pair repeats that vary in their repeat number between individuals. This variation (polymorphism) can be assessed using a PCR. A panel of markers of 3 STRs; ACPP, INT 2, and CYP 19 (on chromosomes 3, 11, and 15, respectively) were used. DNA was isolated from the samples after xylene deparaffinization and proteinase digestion, and was then amplified in a radioactive PCR using primers selected to give a product size ranging from 136-178 bases. Amplified products were electrophoresed on denaturing polyacrylamide gels, dried, and autoradiographed. DNA segments were successfully extracted from all samples but one, which was fixed in Bouin's fluid. By comparing allele sizes from the panel, all tissue pairs (other than the Bouin's pair) were successfully matched, the 1-mm tumor fragments were correctly assigned, and the two clinical problems were solved. STRs are highly informative and robust markers, well suited to PCR of small portions of tissue sections, and are an effective method to confirm the provenance of benign and malignant biopsy and autopsy material.

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We consider the problem of segmenting text documents that have a
two-part structure such as a problem part and a solution part. Documents
of this genre include incident reports that typically involve
description of events relating to a problem followed by those pertaining
to the solution that was tried. Segmenting such documents
into the component two parts would render them usable in knowledge
reuse frameworks such as Case-Based Reasoning. This segmentation
problem presents a hard case for traditional text segmentation
due to the lexical inter-relatedness of the segments. We develop
a two-part segmentation technique that can harness a corpus
of similar documents to model the behavior of the two segments
and their inter-relatedness using language models and translation
models respectively. In particular, we use separate language models
for the problem and solution segment types, whereas the interrelatedness
between segment types is modeled using an IBM Model
1 translation model. We model documents as being generated starting
from the problem part that comprises of words sampled from
the problem language model, followed by the solution part whose
words are sampled either from the solution language model or from
a translation model conditioned on the words already chosen in the
problem part. We show, through an extensive set of experiments on
real-world data, that our approach outperforms the state-of-the-art
text segmentation algorithms in the accuracy of segmentation, and
that such improved accuracy translates well to improved usability
in Case-based Reasoning systems. We also analyze the robustness
of our technique to varying amounts and types of noise and empirically
illustrate that our technique is quite noise tolerant, and
degrades gracefully with increasing amounts of noise

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This chapter argues that there is a gap between symbolic exclusion from the national community when it comes to the inclusion of new German citizens of Turkish or Kurdish background, and a broad claim to be a cosmopolitan society, at large. While focusing on narratives of minority key political activists in Berlin, and analysing individual stories on the background of contemporary populist xenophobic debates and hate crime of the 1990s, the chapter illustrates both, individual success and vulnerability due to institutionalised forms of anti- Muslim and anti-Turks segments in Germany.