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An award-winning makeup artist showcases an array of eye makeup looks for all occasions and presents easy-to-follow instructions to design the perfect look for every age, situation, shape, and color of eyes. -- Source other than Library of Congress.

Background During the early phase of the COVID-19 pandemic, antibiotic usage among COVID-19 patients was noted to be high in many countries. The objective of this study was to determine the prevalence of antibiotic usage and factors affecting antibiotic usage among COVID-19 patients during the early phase of the COVID-19 pandemic in Malaysia. Methods This was a cross-sectional study that involved reviewing medical records of COVID-19 Malaysian patients aged 12 and above who were diagnosed with COVID-19 and received treatment in 18 COVID-19 hospitals from February to April 2020. A minimum sample of 375 patients was required. A binary logistic regression analysis was performed to determine factors associated with antibiotic usage. Variables with p  < 0.05 were considered statistically significant. Results A total of 4043 cases were included for analysis. The majority of the patients (87.6%) were non-smokers, male (65.0%), and had at least one comorbidity (37.0%). The median age was 35 years (IQR: 38). The prevalence of antibiotic usage was 17.1%, with 5.5% of them being prescribed with two or more types of antibiotics. The most frequent antibiotics prescribed were amoxicillin/clavulanic acid (37.8%), ceftriaxone (12.3%), piperacillin/tazobactam (13.3%), azithromycin (8.3%), and meropenem (7.0%). Male patients (adjusted OR 1.53), who had a comorbidity (adjusted OR 1.36), associated with more severe stage of COVID-19 (adjusted OR 6.50–37.06), out-of-normal range inflammatory blood parameters for neutrophils, lymphocytes, and C-reactive protein (adjusted OR 2.04–3.93), corticosteroid use (adjusted OR 3.05), and ICU/HDU admission (adjusted OR 2.73) had higher odds of antibiotic use. Conclusions The prevalence of antibiotic usage in the early phase of the COVID-19 pandemic was low, with amoxicillin/clavulanic acid as the most common antibiotic of choice. The study showed that clinicians rationalized antibiotic usage based on clinical assessment, supported by relevant laboratory parameters.

This study evaluated the effects of oregano essential oil (OEO)-meditated intestinal microbiota and immunity on growth, amino acid composition, and Aeromonas salmonicida resistance in rainbow trout. A total of 480 fish were allocated to four feeding treatments: dietary supplementation with 2.0 mL OEO/kg (group L), 4.0 mL OEO/kg (group M), 8.0 mL OEO/kg (group H), and no supplementation as control group (CK group). The results indicated that dietary OEO had a positive impact on the growth performance and pathogen resistance of rainbow trout, with higher amino acid deposition in the muscle and, in particular, a significant enrichment in amino acid pathways was observed. The use of OEO led to an increase in abundance of Proteobacteria and decrease in abundance of Firmicutes in intestinal microbiota. Moreover, the abundance of taxa containing beneficial bacteria such as Streptococcus lutetiensis , Oscillospirales , and Methylobacterium - Methylorubrum increased, while the abundance of taxa containing potential pathogens such as Mycoplasma , Morganellaceae , and Paenalcaligenes decreased in OEO treatment groups. In addition, transcriptome analysis showed that a number of immune-related genes such as TLR3 , MyD88 , IRF7 , and TRAF2 were up-regulated, while il-6 , il-21 , and il-34 were down-regulated. Thus, OEO intervention contributed to the amino acid deposition and resistance to A. salmonicida infection in rainbow trout by mediating the link between fish immunity and intestinal microbiota function.

Reducing recidivism for drug offenders has been a challenge in Singapore since the late 1990s, when there was a spike in reentry into the system. In the year 2000, resources were invested in rehabilitation and reintegration programs to bring a reduction to the recidivism rate, but the interventions have been unsatisfactory in preventing relapse and reincarceration. This study’s purpose was to describe and interpret the lived experience of male ex-addicts who were in prison in Singapore and how they made sense of their motivation to stay drug free after their incarceration. Motivation is an important predictor of reduction and abstinence outcomes for illicit substances, and self-determination theory provided a broad framework for the study. Eight participants were selected to share their lived experiences and meaning-making processes to remain motivated to stay off drugs. Interpretative phenomenological analysis was employed and interviews were conducted in which the participants answered semistructured questions. The findings revealed that (a) addicts’ core issues hinder recovery, (b) negative peer influence exists among inmates, (c) addiction might not be absolutely a chronic disease, (d) triggering events may be a good catalyst for permanent change, (e) there was a preference for quality of life over addiction, (f) there was growth in motivation, and (g) spirituality and religion are essential for successful abstinence. The study supported the recommendation to implement further segregation within prison clusters and to implement counseling that includes the resolution of underlying core issues. This study may lead to positive social change by supporting efforts to reduce the recidivism rate, thereby making the society in Singapore safer, and increasing the local workforce.

You've got to love a premier who's prepared to jump into his Speedos at 7.30 one sunny but chilly morning at Wylie's Baths, Coogee, and pose for a photograph. His lower lip trembling with cold, every now and then he'd ask to do a few laps to warm up. Finally, after a good 25 minutes or so, his minders rescued him from our clutches and the numbing chill of being submerged to his chest in an unheated pool at that hour of the day - but not before we got a terrific series of pictures befitting your choice for Sydney's Man of the Year.

MaxEnt is a program for modelling species distributions from presence-only species records. This paper is written for ecologists and describes the MaxEnt model from a statistical perspective, making explicit links between the structure of the model, decisions required in producing a modelled distribution, and knowledge about the species and the data that might affect those decisions. To begin we discuss the characteristics of presence-only data, highlighting implications for modelling distributions. We particularly focus on the problems of sample bias and lack of information on species prevalence. The keystone of the paper is a new statistical explanation of MaxEnt which shows that the model minimizes the relative entropy between two probability densities (one estimated from the presence data and one, from the landscape) defined in covariate space. For many users, this viewpoint is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts. We then step through a detailed explanation of MaxEnt describing key components (e.g. covariates and features, and definition of the landscape extent), the mechanics of model fitting (e.g. feature selection, constraints and regularization) and outputs. Using case studies for a Banksia species native to south-west Australia and a riverine fish, we fit models and interpret them, exploring why certain choices affect the result and what this means. The fish example illustrates use of the model with vector data for linear river segments rather than raster (gridded) data. Appropriate treatments for survey bias, unprojected data, locally restricted species, and predicting to environments outside the range of the training data are demonstrated, and new capabilities discussed. Online appendices include additional details of the model and the mathematical links between previous explanations and this one, example code and data, and further information on the case studies.

To describe the use of artificial intelligence (AI)-enabled dark nudges by leading global food and beverage companies to influence consumer behaviour. The five most recent annual reports (ranging from 2014-2018 or 2015-2019, depending on the company) and websites from 12 of the leading companies in the global food and beverage industry were reviewed to identify uses of AI and emerging technologies to influence consumer behaviour. Uses of AI and emerging technologies were categorised according to the Typology of Interventions in Proximal Physical Micro-Environments (TIPPME) framework, a tool for categorising and describing nudge-type behaviour change interventions (which has also previously been used to describe dark nudge-type approaches used by the alcohol industry). Not applicable. 12 leading companies in the global food and beverage industry. Text was extracted from 56 documents from 11 companies. AI-enabled dark nudges used by food and beverage companies included those that altered products and objects' availability (e.g., social listening to inform product development), position (e.g., decision technology and facial recognition to manipulate the position of products on menu boards), functionality (e.g., decision technology to prompt further purchases based on current selections) and presentation (e.g., augmented or virtual reality to deliver engaging and immersive marketing). Public health practitioners and policymakers must understand and engage with these technologies and tactics if they are to counter industry promotion of products harmful to health, particularly as investment by the industry in AI and other emerging technologies suggests their use will continue to grow.

The oil palm fruit ‘mantled’ abnormality is a somaclonal variant that markedly reduces yield; here, a genome-wide DNA methylation analysis finds that hypomethylation of a single Karma family retrotransposon embedded in a homeotic gene intron is common to all mantled clones and is associated with aberrant splicing and termination of the gene transcript, and that loss of methylation predicts a loss of oil palm yield. How Bad Karma epiallele can ruin oil palm oil crops A flower and fruit abnormality known as 'mantled' can develop in some agricultural oil palm cultivars derived from tissue culture and the resulting mantled palms can become unproductive. Mantling is widely regarded as an epigenetic trait, but has not been fully explained. Meilina Ong-Abdullah et al . have undertaken a genome-wide, unbiased, DNA methylation analysis to look for loci epigenetically associated with the mantled phenotype. They find that hypomethylation of a single Karma family retrotransposon embedded in the intron of a homeotic gene is common to all mantled clones and associated with aberrant splicing and termination of the gene transcript. Loss of methylation — dubbed the Bad Karma epiallele — predicts a loss of oil palm yield and this property should enable screening for higher-performing clones at the plantlet stage. Somaclonal variation arises in plants and animals when differentiated somatic cells are induced into a pluripotent state, but the resulting clones differ from each other and from their parents. In agriculture, somaclonal variation has hindered the micropropagation of elite hybrids and genetically modified crops, but the mechanism responsible remains unknown 1 . The oil palm fruit ‘mantled’ abnormality is a somaclonal variant arising from tissue culture that drastically reduces yield, and has largely halted efforts to clone elite hybrids for oil production 2 , 3 , 4 . Widely regarded as an epigenetic phenomenon 5 , ‘mantling’ has defied explanation, but here we identify the MANTLED locus using epigenome-wide association studies of the African oil palm Elaeis guineensis . DNA hypomethylation of a LINE retrotransposon related to rice Karma , in the intron of the homeotic gene DEFICIENS , is common to all mantled clones and is associated with alternative splicing and premature termination. Dense methylation near the Karma splice site (termed the Good Karma epiallele) predicts normal fruit set, whereas hypomethylation (the Bad Karma epiallele) predicts homeotic transformation, parthenocarpy and marked loss of yield. Loss of Karma methylation and of small RNA in tissue culture contributes to the origin of mantled, while restoration in spontaneous revertants accounts for non-Mendelian inheritance. The ability to predict and cull mantling at the plantlet stage will facilitate the introduction of higher performing clones and optimize environmentally sensitive land resources.