Fashion, growth and welfare: An evolutionary approach

The task of this paper is to explore the interplay between fashion, consumer lifestyles and economic growth in the context of a world of technological change in which the menu of possibilities that consumers face is constantly changing and tending to increase in length. Our working definition of ‘fashion’ is simple, namely the tendency or behavioural norm of actors to adopt certain types or styles of customs or commodities nearly simultaneously, only to adopt a different type or style of custom or commodity in future periods. The demand spikes associated with fashion may pertain to newly introduced products or to products that have been around for some time; they may also occur in hybrid cases where a seemingly defunct product or genre is given a brief rebirth by being reincarnated in terms of a new technology

2003 Philip C. Jessup International Law Moot Court Competition International Court Of Justice At The Peace Palace The Hague, Netherlands

The Republic of Annolay and the Republic of Reston have submitted the present dispute by Special Agreement to the International Court of Justice pursuant to Articles 36(1) and 40(1) of the Statute of the Court for final resolution

Yb-Doped: YCOB Laser (DIV)

A tunable, solid state laser device with both visible and infrared laser emission is developed with a trivalent ytterbium-doped yttrium calcium oxyborate crystal as the host crystal. The Yb:YCOB crystal generates an infrared fundamental light over a wide bandwidth, from approximately 980 nanometers (nm) to approximately 1100 nm. The bandwidth generated by the Yb:YCOB crystal is approximately 100 nm wide and supports the generation of pulsed infrared light or when self-frequency doubled provides a compact, efficient, source of tunable, visible, blue or green laser light in wavelengths of approximately 490 nm to approximately 550 nm

Self Frequency-doubled Nd-doped YCOB Laser

Neodymium-doped yttrium calcium oxyborate (Nd:YCOB) is the single active gain element for a solid-state laser device capable of achieving both lasing and self-frequency doubling optical effects. A pumping source for optically pumping Nd:YCOB can generate a laser light output of approximately 400 mW at approximately 1060 nm wavelength and a self-frequency doubled output of approximately 60 mW at approximately 530 nm wavelength. Thus, a laser device can be designed that is compact, less expensive and a high-powered source of visible, green laser light

Prevalence and geographical distribution of Papio hamadryas papillomavirus 1 (PhPV1) in Kenyan baboons

Papio hamadryas papillomavirus (PhPV) 1, 2, and 3, are Alphapapillomaviruses that have been detected in Kenyan Olive baboons but the distribution is unknown. Therefore, cervical screening for PhPV1 was performed in baboons from various areas in Kenya using a nested polymerase chain reaction. The prevalence rate was 33%.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135993/1/jmp12247.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135993/2/jmp12247_am.pd

Moxonidine increases uptake of oxidised low-density lipoprotein in cultured vascular smooth muscle cells and inhibits atherosclerosis in apolipoprotein E-deficient mice

This study aimed to investigate the effect of the sympatholytic drug moxonidine on atherosclerosis. The effects of moxonidine on oxidised low-density lipoprotein (LDL) uptake, inflammatory gene expression and cellular migration were investigated in vitro in cultured vascular smooth muscle cells (VSMCs). The effect of moxonidine on atherosclerosis was measured by examining aortic arch Sudan IV staining and quantifying the intima-to-media ratio of the left common carotid artery in apolipoprotein E-deficient (Apo

Predicting malignancy in thyroid nodules: feasibility of a predictive model integrating clinical, biochemical, and ultrasound characteristics

Background: Although the majority of thyroid nodules are benign the process of excluding malignancy is challenging and sometimes involves unnecessary surgical procedures. We explored the development of a predictive model for malignancy in thyroid nodules by integrating a combination of simple demographic, biochemical, and ultrasound characteristics. Methods: Retrospective case-record review. We reviewed records of patients with thyroid nodules referred to our institution from 2004 to 2011 (n = 536; female 84 %, mean age 51 years). All malignancy was proven histologically while benign disease was either confirmed histologically, or on cytology with minimum 36-month observation period. We focused on the following predictors: age, sex, smoking status, thyroid hormones (FT4 and TSH) and nodule characteristics on ultrasound. Variables were included in a multivariate logistic regression and bootstrap analyses were used to confirm results. Results: Independent predictors of malignancy in the fully adjusted model were TSH (OR 1.53, 95 % CI 1.10, 2.12, p = 0.01), male gender (OR 3.45, 95 % CI 1.33, 8.92, p = 0.01), microcalcifications (OR 6.32, 95 % CI 2.82, 14.1, p < 0.001), and irregular nodule margins (OR 5.45, 95 % CI 1.61, 18.6, p = 0.006) Bootstrap analyses strengthened these associations and a parsimonious analysis consisting of these variables and age-group demonstrated an area under the curve of 0.77. A predictive score was sensitive (86.9 %) at low scores and highly specific (94.87 %) at higher scores for distinguishing benign from malignant disease. Conclusions: A predictive model for malignancy using a combination of clinical, biochemical, and radiological characteristics may support clinicians in reducing unnecessary invasive procedures in patients with thyroid nodules

HLAProfiler utilizes k-mer profiles to improve HLA calling accuracy for rare and common alleles in RNA-seq data

BACKGROUND: The human leukocyte antigen (HLA) system is a genomic region involved in regulating the human immune system by encoding cell membrane major histocompatibility complex (MHC) proteins that are responsible for self-recognition. Understanding the variation in this region provides important insights into autoimmune disorders, disease susceptibility, oncological immunotherapy, regenerative medicine, transplant rejection, and toxicogenomics. Traditional approaches to HLA typing are low throughput, target only a few genes, are labor intensive and costly, or require specialized protocols. RNA sequencing promises a relatively inexpensive, high-throughput solution for HLA calling across all genes, with the bonus of complete transcriptome information and widespread availability of historical data. Existing tools have been limited in their ability to accurately and comprehensively call HLA genes from RNA-seq data. RESULTS: We created HLAProfiler ( https://github.com/ExpressionAnalysis/HLAProfiler ), a k-mer profile-based method for HLA calling in RNA-seq data which can identify rare and common HLA alleles with > 99% accuracy at two-field precision in both biological and simulated data. For 68% of novel alleles not present in the reference database, HLAProfiler can correctly identify the two-field precision or exact coding sequence, a significant advance over existing algorithms. CONCLUSIONS: HLAProfiler allows for accurate HLA calls in RNA-seq data, reliably expanding the utility of these data in HLA-related research and enabling advances across a broad range of disciplines. Additionally, by using the observed data to identify potential novel alleles and update partial alleles, HLAProfiler will facilitate further improvements to the existing database of reference HLA alleles. HLAProfiler is available at https://expressionanalysis.github.io/HLAProfiler/

Students’ engagement: empirical investigation into technology acceptance and pre-class activities

The COVID-19 pandemic has led to a significant transformation in the field of education, with a notable shift towards online learning worldwide including higher education institutions. However, one of the major concerns faced by educators is ensuring students’ active participation and engagement in the online learning environment. In maintaining the quality of education and achieve desired learning outcomes, it is crucial to understand the factors that influence students’ engagement. The main objective of this study is to investigate the impact of technology acceptance and pre-class activities on the engagement levels of higher education students in online learning platforms. To conduct the research, a cross-sectional approach was employed, and data was collected from 1,692 students at Sunway College and Sunway University through a Google survey form administered between January and March 2022. The findings of this study reveal a positive and significant correlation between students’ acceptance of technology and their level of engagement in the online learning process. Moreover, the study highlights the empirical significance of pre-class activities in fostering student engagement in online classes. These research findings provide valuable insights for educational institutions, practitioners, and policymakers, enabling them to enhance the effectiveness of online learning initiatives