Numerical study of turbulent fluid flow and heat transfer in lateral perforated extended surfaces

Numerical study has been performed in this study to investigate the turbulent convection heat transfer on a rectangular plate mounted over a flat surface. Thermal and fluid dynamic performances of extended surfaces having various types of lateral perforations with square, circular, triangular and hexagonal cross sections are investigated. RANS (Reynolds averaged Navier–Stokes) based modified k–ω turbulence model is used to calculate the fluid flow and heat transfer parameters. Numerical results are compared with the results of previously published experimental data and obtained results are in reasonable agreement. Flow and heat transfer parameters are presented for Reynolds numbers from 2000 to 5000 based on the fin thickness.

An analysis of DNA methylation in human adipose tissue reveals differential modification of obesity genes before and after gastric bypass and weight loss

Background Environmental factors can influence obesity by epigenetic mechanisms. Adipose tissue plays a key role in obesity-related metabolic dysfunction, and gastric bypass provides a model to investigate obesity and weight loss in humans. Results Here, we investigate DNA methylation in adipose tissue from obese women before and after gastric bypass and significant weight loss. In total, 485,577 CpG sites were profiled in matched, before and after weight loss, subcutaneous and omental adipose tissue. A paired analysis revealed significant differential methylation in omental and subcutaneous adipose tissue. A greater proportion of CpGs are hypermethylated before weight loss and increased methylation is observed in the 3′ untranslated region and gene bodies relative to promoter regions. Differential methylation is found within genes associated with obesity, epigenetic regulation and development, such as CETP, FOXP2, HDAC4, DNMT3B, KCNQ1 and HOX clusters. We identify robust correlations between changes in methylation and clinical trait, including associations between fasting glucose and HDAC4, SLC37A3 and DENND1C in subcutaneous adipose. Genes investigated with differential promoter methylation all show significantly different levels of mRNA before and after gastric bypass. Conclusions This is the first study reporting global DNA methylation profiling of adipose tissue before and after gastric bypass and associated weight loss. It provides a strong basis for future work and offers additional evidence for the role of DNA methylation of adipose tissue in obesity.

Kallikrein 4 (hK4) and prostate-specific antigen (PSA) are associated with the loss of E-cadherin and an epithelial-mesenchymal transition (EMT)-like effect in prostate cancer cells

Prostate-specific antigen (PSA) and the related kallikrein family of serine proteases are current or emerging biomarkers for prostate cancer detection and progression. Kallikrein 4 (KLK4/hK4) is of particular interest, as KLK4 mRNA has been shown to be elevated in prostate cancer. In this study, we now show that the comparative expression of hK4 protein in prostate cancer tissues, compared with benign glands, is greater than that of PSA and kallikrein 2 (KLK2/hK2), suggesting that hK4 may play an important functional role in prostate cancer progression in addition to its biomarker potential. To examine the roles that hK4, as well as PSA and hK2, play in processes associated with progression, these kallikreins were separately transfected into the PC-3 prostate cancer cell line, and the consequence of their stable transfection was investigated. PC-3 cells expressing hK4 had a decreased growth rate, but no changes in cell proliferation were observed in the cells expressing PSA or hK2. hK4 and PSA, but not hK2, induced a 2.4-fold and 1.7-fold respective increase, in cellular migration, but not invasion, through Matrigel, a synthetic extracellular matrix. We hypothesised that this increase in motility displayed by the hK4 and PSA-expressing PC-3 cells may be related to the observed change in structure in these cells from a typical rounded epithelial-like cell to a spindle-shaped, more mesenchymal-like cell, with compromised adhesion to the culture surface. Thus, the expression of E-cadherin and vimentin, both associated with an epithelial-mesenchymal transition (EMT), was investigated. E-cadherin protein was lost and mRNA levels were significantly decreased in PC-3 cells expressing hK4 and PSA (10-fold and 7-fold respectively), suggesting transcriptional repression of E-cadherin, while the expression of vimentin was increased in these cells. The loss of E-cadherin and associated increase in vimentin are indicative of EMT and provides compelling evidence that hK4, in particular, and PSA have a functional role in the progression of prostate cancer through their promotion of tumour cell migration.

A comparison between conductive and infrared devices for measuring mean skin temperature at rest, during exercise in the heat, and recovery

Purpose: Skin temperature assessment has historically been undertaken with conductive devices affixed to the skin. With the development of technology, infrared devices are increasingly utilised in the measurement of skin temperature. Therefore, our purpose was to evaluate the agreement between four skin temperature devices at rest, during exercise in the heat, and recovery. Methods: Mean skin temperature (T̅sk) was assessed in thirty healthy males during 30 min rest (24.0± 1.2°C, 56 ± 8%), 30 min cycle in the heat (38.0 ± 0.5°C, 41 ± 2%), and 45 min recovery(24.0 ± 1.3°C, 56 ± 9%). T̅sk was assessed at four sites using two conductive devices(thermistors, iButtons) and two infrared devices (infrared thermometer, infrared camera). Results: Bland–Altman plots demonstrated mean bias ± limits of agreement between the thermistors and iButtons as follows (rest, exercise, recovery): -0.01 ± 0.04, 0.26 ± 0.85, -0.37 ± 0.98°C; thermistors and infrared thermometer: 0.34 ± 0.44, -0.44 ± 1.23, -1.04 ± 1.75°C; thermistors and infrared camera (rest, recovery): 0.83 ± 0.77, 1.88 ± 1.87°C. Pairwise comparisons of T̅sk found significant differences (p < 0.05) between thermistors and both infrared devices during resting conditions, and significant differences between the thermistors and all other devices tested during exercise in the heat and recovery. Conclusions: These results indicate poor agreement between conductive and infrared devices at rest, during exercise in the heat, and subsequent recovery. Infrared devices may not be suitable for monitoring T̅sk in the presence of, or following, metabolic and environmental induced heat stress.

Tensor reduction for user profiling in personalized recommender systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhoodbased collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.

Latent class analysis reveals distinct subgroups of patients based on symptom occurrence and demographic and clinical characteristics

Context Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report ten unrelieved and co-occurring symptoms. Objectives To determine if subgroups of oncology outpatients receiving active treatment (n=582) could be identified based on their distinct experience with thirteen commonly occurring symptoms; to determine whether these subgroups differed on select demographic, and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. Methods Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis (LCA) was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale (MSAS). Results Four distinct latent classes were identified (i.e., All Low (28.0%), Moderate Physical and Lower Psych (26.3%), Moderate Physical and Higher Psych (25.4%), All High (20.3%)). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the All High class had the worst QOL scores. Conclusion Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients are risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.

Sensorineural hearing loss after treatment for head and neck cancer : a review of the literature

Background Definitive cisplatin-based is increasingly delivered as the treatment of choice for patients with head and neck cancer. Sensorineural hearing loss is a significant long term side effect of cisplatin-based chemoradiation and is associated with potential major quality of life issues for patients. Purpose The purpose of this manuscript was to review the mechanism behind sensorineural hearing loss in patients treated with cisplatin-based chemoradiation, including incidence, the contributions of radiotherapy and cisplatin to sensorineural hearing loss and the impact of the toxicity on patient quality of life. Methods Database searches were conducted through PubMed (National Centre for Biotechnology Information) and OvidSP Medline via the Queensland University of Technology Library website. General article searches were conducted through the online search engine Google Scholar. Articles were excluded if the full-text was unavailable, they were not in English or if they were published prior to 1990. Keywords included hearing loss, ototoxicity, cancer, quality of life, cisplatin and radiotherapy. Results/Discussion The total number of journal articles accessed was 290. Due to exclusion criteria, 129 articles were deemed appropriated for review. Findings indicated that sensorineural hearing loss is a significant, long term complication for patients treated with cisplatin-based chemoradiation. Current literature recognises the ototoxic effects of cisplatin and cranial irradiation as separate entities, however the impact of combined modality therapy on sensorineural hearing loss is seldom reported. Multiple risk factors for hearing loss are described, however there are contradictory opinions on incidence and severity and the exact radiation dose threshold responsible for inducing hearing loss in patients receiving combined modality therapy. Sensorineural hearing loss creates a subset of complexities for patients with head and neck cancer and that these patients face significant quality of life impairment. Conclusion The literature review identified that sensorineural hearing loss is a major quality of life issue for patients treated with cisplatin-based chemoradiation for head and neck cancer. Further investigation evaluating the contribution of cisplatin-based chemoradiation to sensorineural hearing loss and the subsequent effect on patient quality of life is warranted.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Extinction risk in cloud forest fragments under climate change and habitat loss

Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.

Efficient minimax strategies for square loss games

We consider online prediction problems where the loss between the prediction and the outcome is measured by the squared Euclidean distance and its generalization, the squared Mahalanobis distance. We derive the minimax solutions for the case where the prediction and action spaces are the simplex (this setup is sometimes called the Brier game) and the \ell_2 ball (this setup is related to Gaussian density estimation). We show that in both cases the value of each sub-game is a quadratic function of a simple statistic of the state, with coefficients that can be efficiently computed using an explicit recurrence relation. The resulting deterministic minimax strategy and randomized maximin strategy are linear functions of the statistic.