Assessing the performance of the Asian/Pacific islander identification algorithm to infer Hmong ethnicity from electronic health records in California.

OBJECTIVE:This study assesses the performance of the North American Association of Central Cancer Registries Asian/Pacific Islander Identification Algorithm (NAPIIA) to infer Hmong ethnicity. DESIGN AND SETTING:Analyses of electronic health records (EHRs) from 1 January 2011 to 1 October 2015. The NAPIIA was applied to the EHR data, and self-reported Hmong ethnicity from a questionnaire was used as the gold standard. Sensitivity, specificity, positive (PPV) and negative predictive values (NPVs) were calculated comparing the source data ethnicity inferred by the algorithm with the self-reported ethnicity from the questionnaire. PARTICIPANTS:EHRs indicating Hmong, Chinese, Vietnamese and Korean ethnicity who met the original study inclusion criteria were analysed. RESULTS:The NAPIIA had a sensitivity of 78%, a specificity of 99.9%, a PPV of 96% and an NPV of 99%. The prevalence of Hmong population in the sample was 3.9%. CONCLUSION:The high sensitivity of the NAPIIA indicates its effectiveness in detecting Hmong ethnicity. The applicability of the NAPIIA to a multitude of Asian subgroups can advance Asian health disparity research by enabling researchers to disaggregate Asian data and unmask health challenges of different Asian subgroups

Pengaruh Suplementasi Saccharomyces Cerevisiae sebagai Probiotik dalam Ransum Berbasis Pakan Lokal terhadap Performans dan Kecernaan Nutrisi pada Babi Lokal Fase Starter

The long term purposes of the study are to change the mind and the custom of pigs farmers from using restaurant or household wastes to using local feeds enriched with yeast (Saccharomyces cerevisiae). The short term or special purpose of the study are to find out the cheaper alternative feeds for pigs and information of using yeast to improve feeds quality and pigs productivity. The study with those purposes was carried out off farm by supplementing yeast into low quality pig feeds (crude protein/CP ≤ 16%) of local weaned pigs composed of: corn meal, rice brand, soybean/tofu extract and unused fish meal. 12 local weaned pigs were fed 4 treatment diets based on block design of 4 treatments with 3 blocks design procedure. The 4 treatment feeds were formulated as : R0 (commercial diet/551); R1 (basal feed + 2% yeast of daily requirement); R2 (basal feed + 4% yeast of daily requirement); and R3 (basal feed + 6% yeast of daily requirement). Feed intake, daily weight gain, feeds conversion efficiency, protein, and crude fibre digestibility were studied in the study. Statistical analysis showed that the effect of the treatments is not significant (P>0.05) on all variables studied. Supplementation yeast of 6% is the best treatment performing the highest result of most variable studied. The conclusion drawn is that supplementing yeast up to 6% could improve performance of weaned pigs fed low quality feed and perform the similar result with feeding commercial feed (551). It is suggested to use yeast up to 6% in the diet and further research including widen range and high level of yeast supplementation could be done

Multispectral pattern recognition reveals a diversity of clinical signs in intermediate age-related macular degeneration

PURPOSE. To develop a proof-of-concept, computational method for the quantification and classification of fundus images in intermediate age-related macular degeneration (AMD). METHODS. Multispectral, unsupervised pattern recognition was applied to 184 fundus images from 10 normal and 36 intermediate AMD eyes. The imaging results of preprocessed, grayscale images from three modalities (infrared, green, and fundus autofluorescence scanning laser ophthalmoscopy) were automatically classified into various clusters sharing a common spectral signature, using a k-means clustering algorithm. Class separability was calculated by using transformed divergence (DT). The classification results for large drusen, pigmentary abnormalities, and areas unaffected by AMD were compared against three expert observers for concordance, and to calculate sensitivity and specificity. RESULTS. Multispectral, unsupervised pattern recognition successfully identified a finite number of AMD-specific, statistically separable signatures in eyes with intermediate AMD. By using a correct classification criterion of >83% for identical clusters and a total of 1693 expert annotations, the sensitivity and specificity of multispectral pattern recognition for the detection of AMD lesions was 74% and 98%, respectively. Large drusen and pigmentary abnormalities were correctly classified in 75% and 68% of instances, respectively. CONCLUSIONS. We describe herein a novel approach for the classification of multispectral images in intermediate AMD. Automated classification of intermediate AMD, using multispectral pattern recognition, has moderate sensitivity and high specificity, when compared against clinical experts. The methods described may have a future role in AMD screening or monitoring

Linear and Deep Neural Network-based Receivers for Massive MIMO Systems with One-Bit ADCs

The use of one-bit analog-to-digital converters (ADCs) is a practical solution for reducing cost and power consumption in massive Multiple-Input-Multiple-Output (MIMO) systems. However, the distortion caused by one-bit ADCs makes the data detection task much more challenging. In this paper, we propose a two-stage detection method for massive MIMO systems with one-bit ADCs. In the first stage, we propose several linear receivers based on the Bussgang decomposition, that show significant performance gain over existing linear receivers. Next, we reformulate the maximum-likelihood (ML) detection problem to address its non-robustness. Based on the reformulated ML detection problem, we propose a model-driven deep neural network-based (DNN-based) receiver, whose performance is comparable with an existing support vector machine-based receiver, albeit with a much lower computational complexity. A nearest-neighbor search method is then proposed for the second stage to refine the first stage solution. Unlike existing search methods that typically perform the search over a large candidate set, the proposed search method generates a limited number of most likely candidates and thus limits the search complexity. Numerical results confirm the low complexity, efficiency, and robustness of the proposed two-stage detection method.Comment: 12 pages, 10 figure

Emerging role of iron oxide nanoparticles in the diagnostic imaging of pancreatic cancer: a systematic review

Background/Aims: Pancreatic cancer is the fourth most common cause of cancer associated death worldwide with a five year survival rate less than 5%. The poor prognosis is mainly due to late presentation in 80% of patients and its drug resistant nature. Most diagnoses are made using contrast-enhanced computed-tomography (CT) or magnetic-resonance-imaging (MRI) which have a limited sensitivity between 76-86%. Iron oxide nanoparticles are increasingly used in the diagnostic imaging of pancreatic cancer, due their ability to selectively target tumour cells thereby increasing image resolution. The aim of this study is to identify studies investigating the use of iron oxide nanoparticles in the diagnostic imaging of pancreatic cancer. Methods: A systematic review was performed using PubMed for records up to 2015. Search terms used included "iron oxide nanoparticles", "pancreatic cancer" and "imaging". Results: A total of 16 studies were identified evaluating the use of iron oxide nanoparticles in the imaging of pancreatic cancer in-vitro and in in-vivo animal models. Eight of the studies evaluated the use of superparamagnetic-iron-oxide-nanoparticles (SPION), they showed SPION significantly decrease the T2 and T2* relaxation times of tumour tissue, providing a high sensitivity for MRI. Similar results were seen in eight studies that investigated the use of iron oxide nanoparticles conjugated to other molecules including gelatin, survivin, chemokine-receptor-4, silica-gold, endothelial-growth-factor-receptor, urokinase-receptor activator, Clostridium and a sonic-hedgehog target. Conclusion: Iron oxide nanoparticles in the form of SPION or conjugates are biocompatible and effective at targeting tumour cells and significantly attenuate MRI signals in T2-weighted images of pancreatic cancers from a range of cell lines

DNN-based Detectors for Massive MIMO Systems with Low-Resolution ADCs

Low-resolution analog-to-digital converters (ADCs) have been considered as a practical and promising solution for reducing cost and power consumption in massive Multiple-Input-Multiple-Output (MIMO) systems. Unfortunately, low-resolution ADCs significantly distort the received signals, and thus make data detection much more challenging. In this paper, we develop a new deep neural network (DNN) framework for efficient and low-complexity data detection in low-resolution massive MIMO systems. Based on reformulated maximum likelihood detection problems, we propose two model-driven DNN-based detectors, namely OBMNet and FBMNet, for one-bit and few-bit massive MIMO systems, respectively. The proposed OBMNet and FBMNet detectors have unique and simple structures designed for low-resolution MIMO receivers and thus can be efficiently trained and implemented. Numerical results also show that OBMNet and FBMNet significantly outperform existing detection methods.Comment: 6 pages, 8 figures, submitted for publication. arXiv admin note: text overlap with arXiv:2008.0375

Genetic and phylogenetic analysis of ten Gobiidae species in China based on amplified fragment length polymorphism (AFLP) analysis

To study the genetic and phylogenetic relationship of gobioid fishes in China, the representatives of 10 gobioid fishes from 2 subfamilies in China were examined by amplified fragment length polymorphism (AFLP) analysis. We established 220 AFLP bands for 45 individuals from the 10 species, and the percentage of polymorphic bands was 100%. The percentage of polymorphic loci within species ranged from 3.61 to 58.56%. Chaeturichthys stigmatias showed the greatest percentage of polymorphic loci (58.56%), the highest Nei’s genetic diversity (0.2421 ± 0.2190) and Shannon’s information index (0.3506 ± 0.3092), while Pterogobius zacalles showed the lowest percentage polymorphic loci (3.61%), the lowest Nei’s genetic diversity (0.0150 ± 0.0778) and lowest Shannon’s information index (0.0219 ± 0.1136). The topology of UPGMA tree showed that the individuals from the same species clustered together and the 10 species formed two major clades. One clade consisted Cryptocentrus filifer, P. zacalles, Tridentiger trigonocephalus, Chaeturichthys hexanema, C. stigmatias, Acanthogobius flavimanus and Synechogobius ommaturus, and the other clade consisted Odontamblyopus rubicundus, Trypauchen vagina and Ctenotrypauchen microcephalus. The results agreed with the traditional taxonomy of the morphological characters. AFLP fingerprints were successfully used to study the phylogenetic relationship of the gobioid fishes and it identified species origins of morphologically similar taxa.Key words: Phylogenetic, amplified fragment length polymorphism (AFLP), gobiidae, Amblyopinae, gobiinae

Going Out or Staying In: How the COVID-19 Pandemic has Influenced College Students’ Drinking and Socializing

People’s daily social activities have been altered during the pandemic since they carry risk for contracting COVID-19. Prior to the pandemic, drinking socially has been the highlight of many college students’ lives. This study explores how COVID-19 has impacted college students’ drinking and social activities. We examined samples from a large, southern, public university both prior (N=65, Mean age=22.15, SD=2.03, 78.87% female) and during COVID-19 (N=47, Mean age=22.42, SD=1.64, 75.47% female). Students filled out an alcohol-related Timeline Followback measure (TLFB), in which they recalled their drinking over the past 30 days using anchor events inputted into a calendar. The events were qualitatively coded and assigned a COVID-19-risk behavior (CRB) score based on the Texas Medical Association’s 9- point scale. Activities now known to contain risk for COVID-19 contraction were classified as follows: Moderate CRB (ranked 5-6; e.g., visiting friends), Moderate-High CRB (ranked 7; e.g., attending a party), and High CRB (ranked 8-9; e.g., going to a bar). Results revealed that students who engaged in CRBs that were ranked 5 and above were more likely to report greater number of drinks on one occasion in the past 30 days (e.g., peak drinks) and more drinks over the entire month (e.g., total monthly drinks). Although total alcohol consumption (e.g., peak drinks and total monthly drinks) remained unchanged, and students were less likely to partake in the highest ranked CRBs (e.g., ranked 8-9) during the pandemic, those who were participating in the highest ranked CRBs (e.g., ranked 8-9) may have been more likely to contract or spread COVID-19. Keywords: college students, COVID-19 risk behaviors, alcohol consumptio

Telehealth technology: Potentials, challenges and research directions for developing countries

Telehealth has been developed and successfully applied in clinical practices, gained a strong interest and demonstrated its usefulness for medical diagnosis, treatments and rehabilitation worldwide. The advent of high speed communication technology and complex signal processing techniques, and recent advancements in cloud and cognitive computing, has created a new wave of opportunities for delivering remote healthcare applications and services, where the cost-effective diagnosis and treatment solutions as well as healthcare services are important and need to be deployed widely. Nevertheless, there is still a significant challenge in fully adopting this technology due to asymmetry among the healthcare centers, hospitals and the user-ends, especially in developing countries. This paper provides an overview of the telehealth, then to addresses the possible telehealth technologies and applications that could be applied to improve the healthcare service performance, with the focus on the developing countries. The incorporation of different technologies in telehealth including, Internet of Things (IoT), cloud and cognitive computing, medical image processing and effective encoding is introduced and discussed. Finally, the possible research directions, challenges for the efficient telehealth, and potential research and technology collaborations are outlined