Miracle-dz/UniFAR-FTUs huggingface dataset:
An investigation of dietary patterns in UK adults as a method for developing a brief diet quality

Background Dietary patterns analyses reduce detailed dietary intake data to underlying patterns, derived empirically or based on a priori knowledge. Brief tools to assess diet quality are needed for dietary surveillance and research in the UK. This study explores dietary patterns in UK adults as a method for developing such a tool. Methods Data analyses were conducted in National Diet and Nutrition Survey (NDNS) data (n=2083). Dietary patterns were derived through Principal Component Analysis. Associations with socio-demographic characteristics, lifestyle factors, nutrient intake and biomarkers were explored. A nutrient-based diet quality score (NDQS) was developed based on a priori knowledge and validated against nutrient biomarkers. NDNS respondents were scored against the NDQS. Backwards elimination regression identified variables independently predictive of the NDQS. Confirmatory analysis compared the indicator variables generated from empirically and theoretically driven methods as predictors of the NDQS. Regressions identified the most parsimonious model predictive of the NDQS. Results Four dietary patterns, explaining13.4% of the sample variance, were labelled according to the foods characterising them: ‘fruit, vegetables and oily fish’ (FVOF), ‘snacks, fast food and fizzy drinks’ (SFFFD), ‘sugary foods and dairy (SFD)’ and ‘meat, potatoes and beer (MPB)’. FVOF was positively associated with being female, non-white, older, a non-smoker and a higher NDQS score. SFFFD was the inverse. The NDQS was positively associated with biomarkers of vitamins C, D, B6, total carotenoids and age and negatively with urinary sodium, being white and smoking. Both methods generated models predictive of diet quality (adjusted R2 = 0.29-0.31, 0.33 respectively). A tool with 5 items, fruit, vegetables, wholemeal bread, sugary drinks and coated chicken/turkey, was predictive of diet quality (adjusted R2 = 0.26). Conclusion Diet quality is an important measure for informing public health policy. This study found dietary patterns analyses to be useful methods for developing a brief, diet quality assessment tool.
Genetic identification of blue rockfish (Sebastes mystinus) and deacon rockfish (S. diaconus) to enable life history analyses for stock assessment: suppl. table 1

7 Department of Ocean Sciences University of California, Santa Cruz 1156 High Street Santa Cruz, California 95064 Abstract—To better inform stock assessment and management decisions, we used multiple approaches for estimating and comparing speciesspecific characteristics of the spatiotemporal composition of catch and life history traits of blue rockfish (Sebastes mys­ tinus) and deacon rockfish (S. diaconus). We confirmed the specieslevel distinction of blue rockfish and deacon rockfish by using the results of genetic identification of individual fish from fin tissue samples and otoliths. Those results reveal the systematic relationships of these species with other rockfish species and enabled an evaluation of differences in distribution and life history (growth) between the 2 species in different management areas. Our evaluation of population structure found no significant differentiation within deacon rockfish and slight differentiation in blue rockfish that may not be biologically significant. Along the U.S. Pacific coast, deacon rockfish accounted for the majority of individuals sampled north of Monterey Bay, California, whereas blue rockfish were the more frequently observed species in waters of Monterey Bay and southern California. Modest but significant differences in growth parameters between the 2 species were observed by species, sex, and state (California or Oregon). The multidisciplinary nature of this study and the techniques and protocols we established provide a model for future research on and assessment of species complexes.
Identifying appropriate interruption-handling strategies during healthcare care processes

ABSTRACT Interruptions are a salient component of healthcare care work. While there is a significant amount of literature studying interruptions in inpatient care, most of it focuses on retrospectively assessing their frequency and impact on processes. Strategies to address interruptions often do not completely eliminate them. There is a need to identify strategies that can be proactively used by practitioners to address the interruptions they face during care. This article describes an analysis of the potential effects of interruptions at different stages of a primary task (patient assessment). An Interruption-Failure Modes and Effects Analysis (I-FMEA), where interruption-related failure modes are evaluated in terms of risk, worker efficiency, and patient satisfaction, is proposed. This approach helps to identify interruptions that could be postponed (i.e., representing relatively low-risk, average impact on patient satisfaction, and average added work). It also helps to identify higher-risk tasks that should always be finished before addressing any interruption. The strategies identified in this research depend on the specific primary task, type of interruption, and performance metric to optimize. The proposed approach can be used to identify general recommendations when the provider lacks experience. It can be adapted to analyze other primary tasks and their associated interruptions.
Coded Caching With User Grouping Over Wireless Channels

We study coded caching over non-ergodic fading channels. As the multicast capacity of a broadcast channel is restricted by the user experiencing the worst channel conditions, we formulate an optimization problem to minimize the transmission time by grouping users based on their channel conditions, and transmit coded messages according to the worst channel conditions in the group, as opposed to the worst among all. We develop two algorithms to determine the user groups: a locally optimal iterative algorithm and a numerically more efficient solution through a shortest path problem, and we illustrate the effectiveness of developed solutions via numerical examples.
The complete chloroplast genome sequence of Knema elegans (Myristicaceae)

Abstract Knema elegans is a member of Myristicaceae. The K. elegans chloroplast genome is found to be 155,691 bp in length and has a base composition of A (30.02%), G (19.31%), C (19.89%), and T (30.78%). The genome contained two short inverted repeat (IRa and IRb) regions (48,122 bp) which were separated by a large single-copy (LSC) region (86,883 bp) and a small single-copy (SSC) region (20,686 bp). The chloroplast genome has 85 protein-coding genes, 27 transfer RNA (tRNA) genes, and 8 ribosomal RNA (rRNA) genes. Further, complete chloroplast sequence of K. elegans was aligned together with two species of Myristicaceae and five basal angiosperms species for which the complete chloroplast sequence have been reported. This complete chloroplast genome will provide valuable information for the development of DNA markers for future species resource development and phylogenetic analysis of K. elegans.
Antioxidative Effect and First Evidence of Synergistic Antimicrobial Effects of Ficus carica (L.) Leaf Essential Oil with Conventional Antibiotics

Abstract Ficus carica is one of the oldest and earliest cultivated fruits in the world. To our knowledge, little information is available on the antimicrobial and antioxidant activities of F. carica leaf essential oil (EO). Also, the potential synergistic interaction of this EO with standard antibiotics against multidrug resistant bacteria and clinically pathogenic yeasts has not been investigated. The characterization of the EO with GC/MS analyses led to identification of 35 components, representing 98.1 % of the total oil, with ficusin (32.8 %), caryophyllene oxide (9.0 %), bergapten (6.1 %) as major constituents. Regarding the antioxidant property, F. carica leaf EO showed moderate activity, as measured by DPPH free radical scavenging (1.45 ± 0.05 mg/mL), β-carotene/linoleic acid (1.56 ± 0.09 mg/mL) and reducing power assays (1.92 ± 0.13 mg/mL). The antimicrobial tests showed that EO presented higher activity against all tested microorganisms with MIC values ranging from 4.75 mg/mL to 38 mg/mL. The combination between conventional antibiotics and EO showed a high synergistic effect, especially against the Gram-positive bacteria, with FICI values ranged from 0.312 to 0.750. Interestingly, F. carica leaf oil has strongly reduced the known antibiotic MICs by 1 to 16-fold.
Radiative Transfer Modeling of EC 53: An Episodically Accreting Class I Young Stellar Object

In the episodic accretion scenario, a large fraction of the protostellar mass accretes during repeated and large bursts of accretion. Since outbursts on protostars are typically identified at specific wavelengths, interpreting these outbursts requires converting this change in flux to a change in total luminosity. The Class I young stellar object EC 53 in the Serpens Main cloud has undergone repeated increases in brightness at 850 μm that are likely caused by bursts of accretion. In this study, we perform two- and three-dimensional continuum radiative transfer modeling to quantify the internal luminosity rise in EC 53 that corresponds to the factor of ∼1.5 enhancement in flux at 850 μm. We model the spectral energy distribution and radial intensity profile in both the quiescent and outburst phases. The internal luminosity in the outburst phase is ∼3.3 times brighter than the luminosity in the quiescent phase. The radial intensity profile analysis demonstrates that the detected submillimeter flux variation of EC 53 comes from the heated envelope by the accretion burst. We also find that the role of external heating of the EC 53 envelope by the interstellar radiation field is insignificant.
Who Cares For The Carers? The Impacts Of Immigrant Elderly Care Workers On The Female Labour Supply

We analyse how the availability of immigrant workers in the elderly care sector affects the labour force participation of Italian females aged between 45 and 65. We estimate a selection bias correction model and exploit an IV strategy based on the role of migration networks in determining the geographical distribution of immigrants over time. Our main findings show that the local availability of foreignâ€“born caregivers has a positive impact on the number of hours worked by Italian women, especially those with highâ€“educational levels and living in the Northern regions. The effect on participation rates are instead positive and significant only for lowâ€“educated women and for women living in Central Italy.
A Case Report of Patient with Guillain-Barre Syndrome Complaining of Fatigue and Tingling Improved by Korean Medicine Treatment

Objectives: This case report presents improvement of fatigue and tingling symptoms in a patient with Guillain-Barre syndrome (GBS) after receiving Korean medical treatment. Methods: The patient was treated for 35days with the herbal medicine Hyangsayangwi-tang-gamibang and acupuncture. The effects of treatments were measured with fatigue severity scale (FSS) and numeric rating scale (NRS). Results: The clinical symptoms of the GBS patient were improved considerably after Korean medicine treatment. Conclusions: The herbal medicine Hyangsayangyi-tang-gaimibang and acupuncture could be effective for treatment of symptoms of fatigue and tingling in patients with GBS, but more studies are needed to confirm the present results.
The Relationship Among Attributional Style, Mentalization, and Five Anxiety Phenotypes in School-Age Children

ABSTRACT Literature has shown the importance of social cognition for emotional wellness. However, to our knowledge, few studies so far investigated the relationship between social cognition and anxiety in childhood. No study systematically examined social cognition in relation to specific domains of anxiety. By a correlational design and multivariate models, we explored in a sample of 337 children the association between five anxiety phenotypes and two social cognition domains (Mentalization/Attributional style). After controlling for depressive symptoms, we found that a good performance in the mentalization task was predicted by high levels of generalized anxiety and low levels of separation anxiety. Moreover, positive attributions for good events were predicted by low levels of social anxiety. The present findings remark the importance of rehabilitating social cognition skills in children with social/separation anxiety and depressive symptoms.
A new measure of the ‘democratic peace’: what country feeling thermometer data can teach us about the drivers of American and Western European foreign policy

ABSTRACT While the existence of a ‘Democratic Peace’ (DP) is widely accepted, the various DP theories that seek to explain why democracies rarely fight one another are highly contested. A ‘commercial/capitalist peace’ counterargument maintains that the relationship between democratic politics and peace is spurious: the actual driver is greater trade among democracies. Meanwhile, Realists counter that it is alliances among democratic states, not their democratic nature, that causes peace among them. This research note utilizes novel country feeling thermometer data to explore the debate’s micro-foundations: the underlying drivers of international amity and enmity among democratic citizens in the US, UK, France, and Germany. Utilizing Freedom House and other quantitative measures of freedom, trade, military strength, and racial and cultural difference, it pits the micro-foundations of the DP against its rivals to explain attitude formation among a group of Western democratic publics. Given the resurgence of authoritarianism around the world today, a better understanding of the role of regime type in shaping public opinion – and subsequently war and peace – is urgently needed.
Financial Inclusion, Financial Stability and Sustainability in the Banking Sector: The Case of Indonesia

Purpose: The purpose of the present study is to analyze the effect of financial inclusion on sustainable economic growth for Indonesian banking companies, and to investigate the effect of financial inclusion on sustainable economic growth through financial system stability. Design/Methodology/Approach: This research is a quantitative study using secondary data taken from annual financial statements of banking companies listed on the Indonesia Stock Exchange (BEI) over the period 2010-2017. Findings: The results show that (a) the financial inclusion does not affect sustainable economic growth in Indonesian banking companies, and (b) the financial system stability mediates the effect of financial inclusion on sustainable economic growth in Indonesian banking companies. Practical Implications: This study provides deeper insight into the factors that drive financial inclusion and an increase in market share and financial performance of banks. With conditions of inclusion that are still low in Indonesia while the number of banks is increasing, it is necessary to have strong financial system stability. By understanding the matrix in financial inclusion, managers are well-positioned to understand the strategies needed to promote financial inclusion so that market share increases. Likewise, the results of the present study are probable to be an input for other stakeholders for their consideration in decision making. Originality/Value: Empirical research that explores the effects of financial inclusion, and sustainable economic growth in Indonesia is still very limited. According to our knowledge, no one has examined the use of financial system stability as mediation as it is used in this study.
Determination of the type of Erythemato-Squamous Disease using Intelligent classifier

In this paper the differential diagnosis of erythemato-squamous diseases using intelligent classifier is discussed. The differential diagnosis of erythemato-squamous diseases is an intricate problem in dermatology. The given samples when trained, nearly 98 % classification accuracy is achieved with Artificial Neural Network (ANN) classifier. Generalized Feed Forward Neural Network (FFNN) can solve the multivariable classification problem of determination of skin disease. ANN approach is studied to determine the type of Erythemato-Squamous Disease, which all share the clinical features of erythema and scaling, with very little differences. The diseases are classified into six classes, namely psoriasis, seboreic dermatitis, lichen planus, pityriasis rosea, chronic dermatitis, and pityriasis rubra pilaris. Keywords: classification, FFNN, RBF, erythemato-squamous disease
Brand Loyalty in a Bertrand-Type Oligopoly Setting

It appears that in today’s brand-proliferating, constantly market-segmenting and technologically evolving global economy, consumer perceptions affect an entire industry in which brand loyalty is possible such as the extremely hot and rapidly developing global smartphone industry. In a brand-loyalty-prone industry, what are the implications of brand loyalty in terms of, among others, industry price, sales and profit? I propose a market structure in which each firm’s profit depends on sales of a brand realized in a captive market segment as well as on sales of the same brand realized in a non-captive market segment; ignoring costs of production and assuming that all firms simultaneously enter into the two market segments and that price discrimination of the 3rd degree is not possible, I employ a Bertrand-type duopoly structure and then aggregate over n firms. Counterintuitively, industry price, quantity and profit all rise with entry. The findings are primarily due to the assumed entry condition (that each entrant enters into two market segments one of which is a monopoly) and secondarily to the inability of the sellers to price discriminate. I conclude that experience-type data in the smartphone industry can be considered as somewhat supportive of the proposed structure and the derived theoretical results.
Simulating isolated populations to identify emerging genetic structure in the absence of selection

Conservation efforts are often informed by measures of genetic structure within or between isolated populations. We have established a simulation approach to investigate how isolated or captive populations can display misleading (i.e recently acquired) genetic structure as a result of genetic drift. We utilized a combination of softwares to generate isolated population genetic datasets that allow interrogation of emerging genetic structure under a range of conditions. We have developed a new statistic, S, to describe the extent of differentiation due to genetic drift between two isolated populations within the clustering software, STRUCTURE. A novel method to infer the effects of genetic drift on structure among isolated populations Graphical Abstract SPECIFICATIONS TABLE
Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization

The technological developments in wind energy field have reduced the investment and the operation costs. For this reason, wind farms have become more popular around the world. Increasing the share of wind energy in the market has led to the need for secure, inexpensive, and effective monitoring and control approaches. In the present work, various monitoring and control tools, which are cheap and easy to implement in wind farms using existing system data are proposed. The primary purpose of this study is to offer a new methodology, i.e. an artificial neural network (ANN) design with a novel training algorithm called Antrain ANN, in order to explore the early fault detection in a wind turbine. Our case problem is the fault detection for a wind turbine. For this issue, we used real data consisting of 873 samples with 12 inputs and one output. The models used in the work try to forecast fault occurrence before 10 minutes it happens. The proposed Antrain ANN algorithm is compared with Quick Propagation, Conjugate Gradient Descent, Quasi-Newton, Limited Memory Quasi-Newton, Online Backpropagation, and Batch Back Propagation algorithms, respectively. The results have shown that the proposed novel approach has better results in the correct classification rates than other algorithms except the Quasi-Newton and Limited Memory Quasi-Newton ones.
Engaging Professional Sports to Reduce Bullying: An Evaluation of the Boston vs. Bullies Program

ABSTRACT We evaluated the effectiveness of Boston vs. Bullies, a short-term, free, bullying prevention program that uses celebrity athletes to present content. Fifth-grade students in 10 schools were randomized to either complete the Boston vs. Bullies intervention (n = 388), or to a wait-list control group (n = 266). Pre- and post-surveys assessed knowledge, attitudes, and behaviors related to bullying. Students completing Boston vs. Bullies reported greater improvement in knowledge of bullying, assertiveness, perceptions of adult responsiveness, and bystander responsibility. They also reported decreased acceptance of aggression and peer victimization. However, when statistical models introduced robust standard errors to account for school clustering, some associations attenuated, suggesting that program effectiveness is somewhat variable across schools. Further, among youth in the intervention group, greater improvement was associated with student-reported engagement and facilitator-reported adherence to program components. Results suggest that Boston vs. Bullies can contribute to improving bullying, but some program outcomes may be influenced by school context.
Why Do Cognitive Prompts Hurt Learning in Older Adults?

The purposes of the present investigation were to attempt to replicate the negative effects for learning prompts in older adults reported by Cavanagh, Kraiger and Peters (2016), determine if the impact of learning prompts depends on type of prompt, and investigate the two possible explanations of the negative impact of prompts &#8211; increased cognitive load and higher negative affect. Learning prompts refer to short text inserted into training content to encourage trainees to rehearse new content or engage in meta&#8208;cognitive activity. Although learning prompts generally lead to greater learning in training, Cavanagh et al. reported a negative impact for prompts on measures of recall and transfer. Using similar training materials and learning outcome measures, we conducted two studies using both elaboration and meta&#8208;cognitive prompts in online training. In the first, older adults (N&#160;=&#160;194) between 55 and 70&#160;years and younger adults (N&#160;=&#160;218) were randomly assigned to either a meta&#8208;cognitive, elaboration or no prompts (control) condition. Older adults learned less and reported greater mental effort than younger learners, but these effects were not moderated by prompt condition. In the second, N&#160;=&#160;57 older adults were randomly assigned to the same three prompts conditions listed above. Older adults learned less with prompts than without, but there were no differences between conditions in mental effort or negative affect. In sum, we found negative effects for learning prompts in older adults in two studies, but found no evidence to suggest that these effects were due to either increased cognitive load or greater negative affect.