824 resultados para early detection


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Wireless access is expected to play a crucial role in the future of the Internet. The demands of the wireless environment are not always compatible with the assumptions that were made on the era of the wired links. At the same time, new services that take advantage of the advances in many areas of technology are invented. These services include delivery of mass media like television and radio, Internet phone calls, and video conferencing. The network must be able to deliver these services with acceptable performance and quality to the end user. This thesis presents an experimental study to measure the performance of bulk data TCP transfers, streaming audio flows, and HTTP transfers which compete the limited bandwidth of the GPRS/UMTS-like wireless link. The wireless link characteristics are modeled with a wireless network emulator. We analyze how different competing workload types behave with regular TPC and how the active queue management, the Differentiated services (DiffServ), and a combination of TCP enhancements affect the performance and the quality of service. We test on four link types including an error-free link and the links with different Automatic Repeat reQuest (ARQ) persistency. The analysis consists of comparing the resulting performance in different configurations based on defined metrics. We observed that DiffServ and Random Early Detection (RED) with Explicit Congestion Notification (ECN) are useful, and in some conditions necessary, for quality of service and fairness because a long queuing delay and congestion related packet losses cause problems without DiffServ and RED. However, we observed situations, where there is still room for significant improvements if the link-level is aware of the quality of service. Only very error-prone link diminishes the benefits to nil. The combination of TCP enhancements improves performance. These include initial window of four, Control Block Interdependence (CBI) and Forward RTO recovery (F-RTO). The initial window of four helps a later starting TCP flow to start faster but generates congestion under some conditions. CBI prevents slow-start overshoot and balances slow start in the presence of error drops, and F-RTO reduces unnecessary retransmissions successfully.

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Background Skin temperature assessment is a promising modality for early detection of diabetic foot problems, but its diagnostic value has not been studied. Our aims were to investigate the diagnostic value of different cutoff skin temperature values for detecting diabetes-related foot complications such as ulceration, infection, and Charcot foot and to determine urgency of treatment in case of diagnosed infection or a red-hot swollen foot. Materials and Methods The plantar foot surfaces of 54 patients with diabetes visiting the outpatient foot clinic were imaged with an infrared camera. Nine patients had complications requiring immediate treatment, 25 patients had complications requiring non-immediate treatment, and 20 patients had no complications requiring treatment. Average pixel temperature was calculated for six predefined spots and for the whole foot. We calculated the area under the receiver operating characteristic curve for different cutoff skin temperature values using clinical assessment as reference and defined the sensitivity and specificity for the most optimal cutoff temperature value. Mean temperature difference between feet was analyzed using the Kruskal–Wallis tests. Results The most optimal cutoff skin temperature value for detection of diabetes-related foot complications was a 2.2°C difference between contralateral spots (sensitivity, 76%; specificity, 40%). The most optimal cutoff skin temperature value for determining urgency of treatment was a 1.35°C difference between the mean temperature of the left and right foot (sensitivity, 89%; specificity, 78%). Conclusions Detection of diabetes-related foot complications based on local skin temperature assessment is hindered by low diagnostic values. Mean temperature difference between two feet may be an adequate marker for determining urgency of treatment.

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Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

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We propose a self-regularized pseudo-time marching strategy for ill-posed, nonlinear inverse problems involving recovery of system parameters given partial and noisy measurements of system response. While various regularized Newton methods are popularly employed to solve these problems, resulting solutions are known to sensitively depend upon the noise intensity in the data and on regularization parameters, an optimal choice for which remains a tricky issue. Through limited numerical experiments on a couple of parameter re-construction problems, one involving the identification of a truss bridge and the other related to imaging soft-tissue organs for early detection of cancer, we demonstrate the superior features of the pseudo-time marching schemes.

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RAPADILINO syndrome is an autosomally resessively inherited condition that belongs to a group of rare syndromes more common in Finland than in other parts of the world. RAPADILINO is characterized by pre- and postnatal growth retardation, radial ray defects, diarrhoea of unknown aetiology during chilhood, a facial resemblance with other patients and normal intelligence. In Finland, 15 patients with this condition have been found which compares with only five patients in other parts of the world. We found RECQL4 gene mutations in RAPADILINO patients and proved this syndrome to be allelic with a subgroup of Rothmund-Thomson syndrome (RTS). Later we found RECQL4 mutations in patients with Baller-Gerold syndrome (BGS). These three syndromes share clinical findings and differential diagnostics rely on poikiloderma and craniosynostosis not seen in RAPADILINO syndrome. We found five different mutations in the Finnish RAPADILINO patients. The g.2545delT mutation is the founder mutation in the Finnish population as all the patients are either homozygotes or compound heterozygotes for it. This mutation leads to the inframe skipping of exon seven from mRNA. The protein encoded by this mutant mRNA lacks the nuclear retention signal and thus leads to the mislocalization of the mutant protein. The genotype-phenotype correlation is not straightforward but it seems that RAPADILINO could be due to alteration in protein function and truncating mutations in both alleles are more common among RTS patients. RTS patients with RECQL4 mutations have an elevated risk for osteosarcoma, but their risk to develop other types of malignancies is not increased.Two Finnish RAPADILINO patients have been diagnosed with osteosarcoma, but in addition to this we have found an excess of lymphoma cases among the Finnish RAPADILINO patients. This difference between cancer types could be due to different mutations found in these syndromes. The mutation screening of the patients will help to differentiate patients who have RECQL4 mutations and thus the elevated cancer risk. Patients will benefit from the follow up since early detection of malignancies is important for the treatment.

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Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under a single service class and multiple queues, and present a multi-layered pricing scheme. We propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. The pricing policy used depends on a weighted average queue length at each node. This helps in reducing frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using our scheme over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our approach exhibits a throughput improvement in the range of 34 to 69 percent in all cases studied (over all routes) over the above scheme.

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An HIV outbreak among Finnish injecting drug users (IDUs) occurred in 1998. By the end of 2005, 282 IDUs were in-fected, most of them by recombinant virus CRF01_AE of HIV. After a rapid spread, the outbreak subsided, and the prevalence of HIV among IDUs remained low (<2%). The purpose of the study was to describe the outbreak in order to recognise factors that have influenced the spread and restriction of the outbreak, and thus to find tools for HIV preven-tion. Data on Finnish IDUs newly diagnosed HIV-positive between 1998 and 2005 was collected through interviews and patient documents. Study I compared markers of disease progression between 93 Finnish IDUs and 63 Dutch IDUs. In study II, geographical spread of the HIV outbreak was examined and compared with the spatial distribution of employed males. In study III, risk behaviour data from interviews of 89 HIV-positive and 207 HIV-negative IDUs was linked, and prevalence and risk factors for unprotected sex were evaluated. In study IV, data on 238 newly diagnosed IDUs was combined with data on 675 sexually transmitted HIV cases, and risk factors for late HIV diagnosis (CD4 cell count <200/µL, or AIDS at HIV diagnosis) were analysed. Finnish IDUs infected with CRF01_AE exhibited higher viral loads than did Amsterdam IDUs infected with subtype B, but there was no difference in CD4 development. The Finnish IDU outbreak spread and was restricted socially in a marginalised IDU population and geographically in areas characterised by low proportions of employed males. Up to 40% of the cases in the two clusters outside the city centre had no contact with the centre, where needle exchange services were available since 1997. Up to 63% of HIV-positive and 80% of HIV-negative sexually active IDUs reported inconsistent condom use, which was associated with steady relationships and recent inpatient addiction care. Com-pared to other transmission groups, HIV-positive IDUs were diagnosed earlier in their infection. The proportion of late diagnosed HIV cases in all transmission groups was 23%, but was only 6% among IDUs diagnosed during the first four years of the epidemic. The high viral load in early HIV infection may have contributed to the rapid spread of recombinant virus in the Finnish outbreak. The outbreak was restricted to a marginalised IDU population, and limited spatially to local pockets of pov-erty. To prevent HIV among IDUs, these pockets should be recognised and reached early through outreach work and the distribution of needle exchange and other prevention activities. To prevent the sexual transmission of HIV among IDUs, prevention programmes should be combined with addiction care services and targeted at every IDU. The early detection of the outbreak and early implementation of needle exchange programmes likely played a crucial role in re-versing the IDU outbreak.

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Although prevention and early detection of the disease greatly improved over the past few years, lung cancer remains the leading cause of cancer deaths. In order to be able to treat a larger population, we are in urgent need for novel treatments. While it is known that DNA repair genes play a major role in the oncogenic transformation, they also represent a weakness of cancers that constitute a therapeutic opportunity. To identify novel DNA repair genes implicated in Lung cancers, we conducted an in silico investigation to identify genes co-regulated with two DNA repair factors, BRCA2 and hSSB1. This approach allowed for the identification of EXOSC4, a component of the RNA Exosome machinery, as a potential factor involved in the maintenance of genome stability and that is deregulated in lung cancer.

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This paper describes how a Hospital Social Work Department's Emergency Team has attempted to provide a crisis and out-of-hours service to its Emergency Department. Through a staffing commitment to extensive evening and weekend cover, the Emergency Team's social worker is able to provide an immediate intervention and assessment service to problems. This has resulted in early detection and treatment of the non-medical aspects of a patient's problem and appropriate referral to other agencies for longer-term follow-up.

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The overall performance of random early detection (RED) routers in the Internet is determined by the settings of their associated parameters. The non-availability of a functional relationship between the RED performance and its parameters makes it difficult to implement optimization techniques directly in order to optimize the RED parameters. In this paper, we formulate a generic optimization framework using a stochastically bounded delay metric to dynamically adapt the RED parameters. The constrained optimization problem thus formulated is solved using traditional nonlinear programming techniques. Here, we implement the barrier and penalty function approaches, respectively. We adopt a second-order nonlinear optimization framework and propose a novel four-timescale stochastic approximation algorithm to estimate the gradient and Hessian of the barrier and penalty objectives and update the RED parameters. A convergence analysis of the proposed algorithm is briefly sketched. We perform simulations to evaluate the performance of our algorithm with both barrier and penalty objectives and compare these with RED and a variant of it in the literature. We observe an improvement in performance using our proposed algorithm over RED, and the above variant of it.

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Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under a single service class and multiple queues, and present a multi-layered pricing scheme. We propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. The pricing policy used depends on a weighted average queue length at each node. This helps in reducing frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using our scheme over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our approach exhibits a throughput improvement in the range of 34 to 69 percent in all cases studied (over all routes) over the above scheme.

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Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes with multiple queues and multiple grades of service. We present a closed-loop multi-layered pricing scheme and propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. This is different from most adaptive pricing schemes in the literature that do not obtain a closed-loop state dependent pricing policy. The method that we propose finds optimal price levels that are functions of the queue lengths at individual queues. Further, we also propose a variant of the above scheme that assigns prices to incoming packets at each node according to a weighted average queue length at that node. This is done to reduce frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using both of our schemes over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our first scheme exhibits a throughput improvement in the range of 67-82% among all routes over the above scheme. (C) 2011 Elsevier B.V. All rights reserved.

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Oxidative stress due to excessive accumulation of reactive oxygen or nitrogen species in the brain as seen in certain neurodegenerative diseases can have deleterious effects on neurons. Hydrogen peroxide, endogenously generated in neurons under normal physiological conditions, can produce an excess of hydroxyl radical via a Fenton mediated mechanism. This may induce acute oxidative injury if not scavenged or removed effectively by antioxidants. There are several biochemical assay methods to estimate oxidative injury in cells; however, they do not provide information on the biochemical changes as the cells get damaged progressively under oxidative stress. Raman microspectroscopy offers the possibility of real time monitoring of the chemical composition of live cells undergoing oxidative stress under physiological conditions. In the present study, a hippocampal neuron coculture was used to observe the acute impact of hydroxyl radicals generated by hydrogen peroxide in the presence of Fe2+ (Fenton reaction). Raman peaks related to nucleic acids (725, 782, 1092, 1320, 1340, 1420, and 1576 cm(-1)) showed time-dependent changes over the experimental period (60 mm), indicating the breakdown of the phosphodiester backbone as well as nuclear bases. Interestingly, ascorbic acid (a potent antioxidant) when cotreated with Fenton reactants showed protection of cells as inferred from the Raman spectra, presumably by scavenging hydroxyl radicals. Little or no change in the Raman spectra was observed for untreated control cells and for cells exposed to Fe2+ only, H2O2 only, and ascorbate only. A live dead assay study also supported the current observations. Hence, Raman microspectroscopy has the potential to be an excellent noninvasive tool for early detection of oxidative stress that is seen in neurodegenerative diseases.

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Reuse is at the heart of major improvements in productivity and quality in Software Engineering. Both Model Driven Engineering (MDE) and Software Product Line Engineering (SPLE) are software development paradigms that promote reuse. Specifically, they promote systematic reuse and a departure from craftsmanship towards an industrialization of the software development process. MDE and SPLE have established their benefits separately. Their combination, here called Model Driven Product Line Engineering (MDPLE), gathers together the advantages of both. Nevertheless, this blending requires MDE to be recasted in SPLE terms. This has implications on both the core assets and the software development process. The challenges are twofold: (i) models become central core assets from which products are obtained and (ii) the software development process needs to cater for the changes that SPLE and MDE introduce. This dissertation proposes a solution to the first challenge following a feature oriented approach, with an emphasis on reuse and early detection of inconsistencies. The second part is dedicated to assembly processes, a clear example of the complexity MDPLE introduces in software development processes. This work advocates for a new discipline inside the general software development process, i.e., the Assembly Plan Management, which raises the abstraction level and increases reuse in such processes. Different case studies illustrate the presented ideas.