A novel wideband dynamic directional indoor channel model based on a Markov process

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Physicochemical and sensory analyses of high fibre bread incorporated with corncob powder

The primary objectives of the present work were to produce corncob powder (CCP) from corncobs and incorporate the CCP into bread formulation in order to develop high fibre bread, and to investigate the physicochemical and sensory properties of the produced high fibre bread (HFB). The corncobs were collected and washed before they underwent the grinding and drying processes. The obtained CCP was incorporated into the bread formulation in three different proportions (5, 10 and 20%) to partially substitute bread flour in the formulation. All three bread samples and the control (0% CCP in the formulation) were analysed to obtain their physicochemical and sensory properties. The incorporation of CCP significantly affected the texture, colour and volume attributes of the produced breads. Increasing the content of CCP in the formulation was found to be responsible for firmer, smaller and darker bread loaves as compared to the composite bread samples. The bread formulation incorporated with 10% CCP had the highest mean scores (7.00) of overall acceptability among all the other formulations, and it was comparable to the commercial breads in the current market

Incidence and outcomes of delayed presentation and surgery in peritoneal surface malignancies

BackgroundPeritoneal surface malignancies (PSM) present insidiously and often pose diagnostic challenges. There is a paucity of literature quantifying the frequency and extent of therapeutic delays in PSM and its impact on oncological outcomes.MethodsA review of a prospectively maintained registry of PSM patients undergoing Cytoreductive Surgery and Hyperthermic Intra-peritoneal Chemotherapy (CRS-HIPEC) was conducted. Causes for treatment delays were identified. We evaluate the impact of delayed presentation and treatment delays on oncological outcomes using Cox proportional hazards models.Results319 patients underwent CRS-HIPEC over a 6-years duration. 58 patients were eventually included in this study. Mean duration between symptom onset and CRS-HIPEC was 186.0 ± 37.1 days (range 18-1494 days) and mean duration of between patient-reported symptom onset and initial presentation was 56.7 ± 16.8 days. Delayed presentation (> 60 days between symptom onset and presentation) was seen in 20.7% (n=12) of patients and 50.0% (n=29) experienced a significant treatment delay of > 90 days between 1st presentation and CRS-HIPEC. Common causes for treatment delays were healthcare provider-related i.e. delayed or inappropriate referrals (43.1%) and delayed presentation to care (31.0%). Delayed presentation was a significantly associated with poorer disease free survival (DFS) (HR 4.67, 95% CI 1.11-19.69, p=0.036).ConclusionDelayed presentation and treatment delays are common and may have an impact on oncological outcomes. There is an urgent need to improve patient education and streamline healthcare delivery processes in the management of PSM

A genetic algorithm for management of coding resources in VANET

This project aims to improve the throughput, energy consumption and overhead of vehicular ad hoc network (VANET) by optimising the network coding (NC) using Genetic Algorithm (GA). VANET shows a promising technology as it could enhance the traffic efficiency and promote traffic safety on the road systems. The conventional store-and-forward transmission protocol used in the intermediate node(s) simply stores the received packet and then send at a later time to the destination. However, the rapid changing in VANET topology has made the conventional store-and-forward approach inefficient to meet the throughput and reliability demand posed by VANET. Hence, NC is proposed to perform additional functions on the packet in the source or intermediate node(s). However, the chances to perform NC in wireless network is highly unlikely if the packet is not transmit to the potential NC node. Therefore, GA based network routing (GANeR) is embedded into network to search for shortest path from the source to the destination. It showed that the developed GANER in this work provides a better route with coding opportunities and reduces energy consumption in the network. The total energy consumed by GANER is 5.6% fewer than NC in wireless network transmission and forwarding structure (COPE)

HYBRID SIMULATION NETWORK FOR VEHICULAR AD HOC NETWORK (VANET)

Intelligent Transportation Systems (ITS) plays a vital role in providing different means of traffic management and enables users to be better informed of traffic condition, promoting safer, coordinated and efficient use of transport network. Vehicular Ad Hoc Network (VANET) shows promising reliability and validity in ITS. But, it poses challenges to researchers in designing protocol specifically for VANET as the deployment of VANET in real world will incur high cost. Therefore, simulation and non-physical testbed implementation have been widely adopted by the VANET research community in the development and assessment of the new or improved system and protocol of VANET. This paper presents a viable simulation platform for network development. Besides, a code cast or better known as network coding, a data packet transmission method has been developed and introduced into VANET protocol using the presented platform to assess and determine the potential of the introduced simulation platform

Engine fault diagnosis using probabilistic neural network

Engine failure is one of the major factors caused vehicle breakdown. In the current practice, the engine faults are diagnosed manually by mechanics and the accuracy is highly relied on their experience. Therefore, this study would like to explore the feasibility of implementing auto fault diagnosis using Probabilistic Neural Network (PNN). A benchmarked engine fault model is developed and simulated in Maltab. The proposed algorithm is designed to detect 9 common engine faults based on the information extracted from exhaust gas, such as hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), carbon dioxide (CO2) and dioxygen (O2). The proposed PNN is trained using the collected engine fault data from experiment and the probability density of PNN is determined based on the Parzen window estimation method. Bayes decision rule is implemented for classifying the types of the engine faults. The simulated results show that the proposed algorithm has faster diagnosis speed, higher accuracy and consistent. The algorithm takes 0.038 s in diagnosing the fault and the average accuracy is 98.3 %

Optimization of signalized traffic network using swarm intelligence

Traffic lights are the signaling devices located at a road intersection for granting right-of-way movement to road users. Thus, optimization of traffic signalization is essential to improve road service as it is the cost-effective way. Commonly, the signal optimization aims to minimize the average travel delay by manipulating the green signal timing. Besides to optimize the signal timing, the local intersection controller needs to collaborate with neighboring intersection controllers for minimizing the average delay for whole network as the congestion will be propagated to the downstream intersection. However, the current fixed-time signal controller is inadequate to manage the high growing demands of traffic as it is tuned offline using the nominal traffic flow data. Thus, this work aims to explore the potential of using Particle Swarm Optimization (PSO) to optimize the traffic signal timing for the traffic network. The proposed algorithm is texted using a benchmarked 1x2 traffic model and its performances are compared with the classical Genetic Algorithm (GA). The simulated results show the proposed PSO has improved the performances in minimizing average travel delay by 3.94 %

Genomic expression and single-nucleotide polymorphism profiling discriminates chromophobe renal cell carcinoma and oncocytoma

<p>Abstract</p> <p>Background</p> <p>Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma are two distinct but closely related entities with strong morphologic and genetic similarities. While chRCC is a malignant tumor, oncocytoma is usually regarded as a benign entity. The overlapping characteristics are best explained by a common cellular origin, and the biologic differences between chRCC and oncocytoma are therefore of considerable interest in terms of carcinogenesis, diagnosis and clinical management. Previous studies have been relatively limited in terms of examining the differences between oncocytoma and chromophobe RCC.</p> <p>Methods</p> <p>Gene expression profiling using the Affymetrix HGU133Plus2 platform was applied on chRCC (n = 15) and oncocytoma specimens (n = 15). Supervised analysis was applied to identify a discriminatory gene signature, as well as differentially expressed genes. High throughput single-nucleotide polymorphism (SNP) genotyping was performed on independent samples (n = 14) using Affymetrix GeneChip Mapping 100 K arrays to assess correlation between expression and gene copy number. Immunohistochemical validation was performed in an independent set of tumors.</p> <p>Results</p> <p>A novel 14 probe-set signature was developed to classify the tumors internally with 93% accuracy, and this was successfully validated on an external data-set with 94% accuracy. Pathway analysis highlighted clinically relevant dysregulated pathways of c-erbB2 and mammalian target of rapamycin (mTOR) signaling in chRCC, but no significant differences in p-AKT or extracellular HER2 expression was identified on immunohistochemistry. Loss of chromosome 1p, reflected in both cytogenetic and expression analysis, is common to both entities, implying this may be an early event in histogenesis. Multiple regional areas of cytogenetic alterations and corresponding expression biases differentiating the two entities were identified. Parafibromin, aquaporin 6, and synaptogyrin 3 were novel immunohistochemical markers effectively discriminating the two pathologic entities.</p> <p>Conclusions</p> <p>Gene expression profiles, high-throughput SNP genotyping, and pathway analysis effectively distinguish chRCC from oncocytoma. We have generated a novel transcript predictor that is able to discriminate between the two entities accurately, and which has been validated both in an internal and an independent data-set, implying generalizability. A cytogenetic alteration, loss of chromosome 1p, common to renal oncocytoma and chRCC has been identified, providing the opportunities for identifying novel tumor suppressor genes and we have identified a series of immunohistochemical markers that are clinically useful in discriminating chRCC and oncocytoma.</p

Efficacy and tolerability of vardenafil in Asian men with erectile dysfunction

10.1111/j.1745-7262.2008.00388.xAsian Journal of Andrology103495-50

Dynamics of multiple resistance mechanisms in plasma DNA during EGFR-targeted therapies in non-small cell lung cancer.

Tumour heterogeneity leads to the development of multiple resistance mechanisms during targeted therapies. Identifying the dominant driver(s) is critical for treatment decision. We studied the relative dynamics of multiple oncogenic drivers in longitudinal plasma of 50 EGFR-mutant non-small-cell lung cancer patients receiving gefitinib and hydroxychloroquine. We performed digital PCR and targeted sequencing on samples from all patients and shallow whole-genome sequencing on samples from three patients who underwent histological transformation to small-cell lung cancer. In 43 patients with known EGFR mutations from tumour, we identified them accurately in plasma of 41 patients (95%, 41/43). We also found additional mutations, including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%) and PTEN (4/50, 8%). Patients with both TP53 and EGFR mutations before treatment had worse overall survival than those with only EGFR Patients who progressed without T790M had worse PFS during TKI continuation and developed alternative alterations, including small-cell lung cancer-associated copy number changes and TP53 mutations, that tracked subsequent treatment responses. Longitudinal plasma analysis can help identify dominant resistance mechanisms, including non-druggable genetic information that may guide clinical management.We would like to acknowledge the support of The University of Cambridge, Cancer Research UK (grant numbers A11906, A20240) (to N.R.), the European Research Council under the European Union's Seventh Framework Programme (FP/2007- 2013) / ERC Grant Agreement n. 337905 (to N.R.), and Hutchison Whampoa Limited (to N.R.