Miracle-dz/UniFAR-FTUs huggingface dataset:
Food processing: criteria for dietary guidance and public health?

The NOVA food categorisation recommends ‘avoiding processed foods (PF), especially ultra-processed foods (UPF)’ and selecting minimally PF to address obesity and chronic disease. However, NOVA categories are drawn using non-traditional views of food processing with additional criteria including a number of ingredients, added sugars, and additives. Comparison of NOVA's definition and categorisation of PF with codified and published ones shows limited congruence with respect to either definition or food placement into categories. While NOVA studies associate PF with decreased nutrient density, other classifications find nutrient-dense foods at all levels of processing. Analyses of food intake data using NOVA show UPF provide much added sugars. Since added sugars are one criterion for designation as UPF, such a proof demonstrates a tautology. Avoidance of foods deemed as UPF, such as wholegrain/enriched bread and cereals or flavoured milk, may not address obesity but could decrease intakes of folate, calcium and dietary fibre. Consumer understanding and implementation of NOVA have not been tested. Neither have outcomes been compared with vetted patterns, such as Dietary Approaches to Stop Hypertension, which base food selection on food groups and nutrient contribution. NOVA fails to demonstrate the criteria required for dietary guidance: understandability, affordability, workability and practicality. Consumers’ confusion about definitions and food categorisations, inadequate cooking and meal planning skills and scarcity of resources (time, money), may impede adoption and success of NOVA. Research documenting that NOVA can be implemented by consumers and has nutrition and health outcomes equal to vetted patterns is needed.
Use of scenario ensembles for deriving seismic risk

Significance High death tolls from recent earthquakes have highlighted the need to better identify ways to effectively reduce seismic risk. We address this need by developing a new earthquake scenario ensemble approach. We model impacts from multiple different earthquake scenarios, identifying impacts that are common to multiple scenarios. This method allows us to estimate whether particular impacts are specific to certain earthquakes or occur irrespective of the location or magnitude of the next earthquake. Our method provides contingency planners with critical information on the likelihood, and probable scale, of impacts in future earthquakes, especially in situations where robust information on the likelihood of future earthquakes is incomplete, allowing disaster risk-reduction efforts to focus on minimizing such effects and reducing seismic risk. High death tolls from recent earthquakes show that seismic risk remains high globally. While there has been much focus on seismic hazard, large uncertainties associated with exposure and vulnerability have led to more limited analyses of the potential impacts of future earthquakes. We argue that as both exposure and vulnerability are reducible factors of risk, assessing their importance and variability allows for prioritization of the most effective disaster risk-reduction (DRR) actions. We address this through earthquake ensemble modeling, using the example of Nepal. We model fatalities from 90 different scenario earthquakes and establish whether impacts are specific to certain scenario earthquakes or occur irrespective of the scenario. Our results show that for most districts in Nepal impacts are not specific to the particular characteristics of a single earthquake, and that total modeled impacts are skewed toward the minimum estimate. These results suggest that planning for the worst-case scenario in Nepal may place an unnecessarily large burden on the limited resources available for DRR. We also show that the most at-risk districts are predominantly in rural western Nepal, with ∼9.5 million Nepalis inhabiting districts with higher seismic risk than Kathmandu. Our proposed approach provides a holistic consideration of seismic risk for informing contingency planning and allows the relative importance of the reducible components of risk (exposure and vulnerability) to be estimated, highlighting factors that can be targeted most effectively. We propose this approach for informing contingency planning, especially in locations where information on the likelihood of future earthquakes is inadequate.
Text or image?: investigating the effects of instruction type on mid-air gesture making with novice older adults

Unlike traditional interaction methods where the same command (e.g. mouse click) is used for different purposes, mid-air gesture interaction often makes use of different gesture commands for different functions, but first novice users need to learn these commands in order to interact with the system successfully. We describe an empirical study with 25 novice older adults that investigated the effectiveness of 3 "on screen" instruction types for demonstrating how to make mid-air gesture commands. We compared three interface design choices for providing instructions: descriptive (text-based), pictorial (static), and pictorial (animated). Results showed a significant advantage of pictorial instructions (static and animated) over text-based instructions for guiding novice older adults in making mid-air gestures with regards to accuracy, completion time and user preference. Pictorial (animated) was the instruction type leading to the fastest gesture making with 100% accuracy and may be the most suitable choice to support age-friendly gesture learning.
The Salt Content of Lunch Meals Eaten at Danish Worksites

Monitoring levels of sodium (salt) in meals consumed out-of-home is needed to support effective implementation of salt-reduction strategies. The objective of the study was to examine lunch salt intake at 15 worksite canteens and to compare with results from a comparable study conducted 10 years before. A duplicate-portion-technique with subsequent chemical analysis was used to quantify 240 customers’ lunch salt intake. Estimated mean salt intake was 2.6 g/meal (95% Cl: 2.2 to 3.0 g/meal) and 0.78 g/100 g (95% Cl: 0.69 to 0.88 g/100 g). Salt intake measured both as g per meal and per 100 g was found to be significantly higher for male compared with female participants (+0.10 g/100 g, 95% Cl: +0.02 to +0.17 g/100 g, p = 0.011). Compared with the study conducted 10 years before, there was a significantly lower estimated salt intake of 0.5 g/meal (95% CI: −0.8 to −0.2 g/meal, p = 0.001), suggesting a possible reduction in canteen lunch salt intake during a 10-year period. Still, 40% of the meals exceeded the Nordic Keyhole label requirements of maximum 0.8 g salt per 100 g for ready meals. A further reduction of salt intake is warranted to comply with salt reduction targets.
An open corpus for the computational research of arab-andalusian music

In the medieval Islamic territories of the Iberian Peninsula known as Al-Andalus a unique style of music was formed combining local practices with Arab sensibilities. After the fall of the last Andalusian kingdom, this classical repertoire has been preserved to the present in North African countries. The idiosyncrasies of this repertoire, which combines musical traits from Western and Eastern Mediterranean traditions in orchestral and choral settings, as well as instrumental and vocal solos, deserves an in depth musicological study, that can benefit from computational tools for corpus-driven research. On the other hand, the characteristics of this music poses interesting challenges to MIR methods and therefore offer new research opportunities to this field. To address these topics, we present here the first complete release of the corpus for the research of the Moroccan tradition of Arab-Andalusian music built in the framework of the CompMusic project. The corpus comprises three data collections, namely audio recordings, music scores and lyrics, as well as related annotations and metadata. We also present a series of Jupyter Notebooks for browsing and retrieving data from the corpus. Both the corpus and notebooks are completely open to the research community.
Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers

Objective: In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in a cohort of train drivers. Approach: Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20). Main results: Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores. Significance: Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.
Physical Activity Earlier in Life Is Inversely Associated With Insulin Resistance Among Adults in Japan

Background It is known that physical activity affects glucose metabolism. However, there have been no reports on the influence of physical activity earlier in life on subsequent glucose metabolism. Therefore, we analyzed the influence of physical activity in earlier decades of life on insulin resistance in middle aged and older residents in Japan. Methods The subjects were 6,883 residents of Okazaki City between the ages of 40 and 79 years who underwent physical examinations at the Okazaki City Medical Association Public Health Center from April 2007 through August 2011. They gave informed consent for participation in the study. Data on individual characteristics were collected via a questionnaire and from the health examination records. Fasting blood glucose and insulin levels were used to calculate the homeostatic model assessment of insulin resistance (HOMA-IR). HOMA-IR >1.6 was considered to indicate insulin resistance for the purpose of logistic regression models. Results The study sample included 3,683 men and 3,200 women for whom complete information was available. For those who exercised regularly throughout their teens to their 30s–40s, the odds ratio for having insulin resistance was 0.75 (95% confidence interval [CI], 0.58–0.96) for men and 0.76 (95% CI, 0.58–0.99) for women after adjusting for other variables, including age, body mass index, and present physical activity. A linear trend was also observed in both men and women. Conclusions Subjects who have exercised regularly in the early decades of life are less likely to have insulin resistance later in life.
Neural basis of location-specific pupil luminance modulation

Significance The pupil regulates the amount of light entering the eyes to optimize visual sensitivity and sharpness. The visual system selects objects of interest for future fixation, and pupil size can be adjusted for object luminance before fixation. This study demonstrates that the intermediate layers of the superior colliculus (SC), a phylogenetically conserved structure for controlling eye movements and spatial attention, coordinates this predictive pupil response. By manipulating intermediate SC (SCi) excitability via microstimulation and lidocaine microinjection, we show that, although global luminance remained unchanged, pupil size was modulated by local luminance at the next fixated location. These results highlight a causal role of the SCi to prepare the pupil for local luminance conditions at the saccadic goal. Spatial attention enables us to focus visual processing toward specific locations or stimuli before the next fixation. Recent evidence has suggested that local luminance at the spatial locus of attention or saccade preparation influences pupil size independent of global luminance levels. However, it remains to be determined which neural pathways produce this location-specific modulation of pupil size. The intermediate layers of the midbrain superior colliculus (SC) form part of the network of brain areas involved in spatial attention and modulation of pupil size. Here, we demonstrated that pupil size was altered according to local luminance level at the spatial location corresponding to a microstimulated location in the intermediate SC (SCi) map of monkeys. Moreover, local SCi inactivation through injection of lidocaine reversed this local luminance modulation. Our findings reveal a causal role of the SCi in preparing pupil size for local luminance conditions at the next saccadic goal.
Using Deep Learning Model for Network Scanning Detection

In recent years, new and devastating cyber attacks amplify the need for robust cybersecurity practices. Preventing novel cyber attacks requires the invention of Intrusion Detection Systems (IDSs), which can identify previously unseen attacks. Many researchers have attempted to produce anomaly - based IDSs, however they are not yet able to detect malicious network traffic consistently enough to warrant implementation in real networks. Obviously, it remains a challenge for the security community to produce IDSs that are suitable for implementation in the real world. In this paper, we propose a new approach using a Deep Belief Network with a combination of supervised and unsupervised machine learning methods for port scanning attacks detection - the task of probing enterprise networks or Internet wide services, searching for vulnerabilities or ways to infiltrate IT assets. Our proposed approach will be tested with network security datasets and compared with previously existing methods.
Comparative Genomics of Degradative Novosphingobium Strains With Special Reference to Microcystin-Degrading Novosphingobium sp. THN1

Bacteria in genus Novosphingobium associated with biodegradation of substrates are prevalent in environments such as lakes, soil, sea, wood and sediments. To better understand the characteristics linked to their wide distribution and metabolic versatility, we report the whole genome sequence of Novosphingobium sp. THN1, a microcystin-degrading strain previously isolated by Jiang et al. (2011) from cyanobacteria-blooming water samples from Lake Taihu, China. We performed a genomic comparison analysis of Novosphingobium sp. THN1 with 21 other degradative Novosphingobium strains downloaded from GenBank. Phylogenetic trees were constructed using 16S rRNA genes, core genes, protein-coding sequences, and average nucleotide identity of whole genomes. Orthologous protein analysis showed that the 22 genomes contained 674 core genes and each strain contained a high proportion of distributed genes that are shared by a subset of strains. Inspection of their genomic plasticity revealed a high number of insertion sequence elements and genomic islands that were distributed on both chromosomes and plasmids. We also compared the predicted functional profiles of the Novosphingobium protein-coding genes. The flexible genes and all protein-coding genes produced the same heatmap clusters. The COG annotations were used to generate a dendrogram correlated with the compounds degraded. Furthermore, the metabolic profiles predicted from KEGG pathways showed that the majority of genes involved in central carbon metabolism, nitrogen, phosphate, sulfate metabolism, energy metabolism and cell mobility (above 62.5%) are located on chromosomes. Whereas, a great many of genes involved in degradation pathways (21–50%) are located on plasmids. The abundance and distribution of aromatics-degradative mono- and dioxygenases varied among 22 Novosphingoibum strains. Comparative analysis of the microcystin-degrading mlr gene cluster provided evidence for horizontal acquisition of this cluster. The Novosphingobium sp. THN1 genome sequence contained all the functional genes crucial for microcystin degradation and the mlr gene cluster shared high sequence similarity (≥85%) with the sequences of other microcystin-degrading genera isolated from cyanobacteria-blooming water. Our results indicate that Novosphingobium species have high genomic and functional plasticity, rearranging their genomes according to environment variations and shaping their metabolic profiles by the substrates they are exposed to, to better adapt to their environments.
Formamide Adsorption at the Amorphous Silica Surface: A Combined Experimental and Computational Approach

Mineral surfaces have been demonstrated to play a central role in prebiotic reactions, which are understood to be at the basis of the origin of life. Among the various molecules proposed as precursors for these reactions, one of the most interesting is formamide. Formamide has been shown to be a pluripotent molecule, generating a wide distribution of relevant prebiotic products. In particular, the outcomes of its reactivity are strongly related to the presence of mineral phases acting as catalysts toward specific reaction pathways. While the mineral–products relationship has been deeply studied for a large pool of materials, the fundamental description of formamide reactivity over mineral surfaces at a microscopic level is missing in the literature. In particular, a key step of formamide chemistry at surfaces is adsorption on available interaction sites. This report aims to investigate the adsorption of formamide over a well-defined amorphous silica, chosen as a model mineral surface. An experimental IR investigation of formamide adsorption was carried out and its outcomes were interpreted on the basis of first principles simulation of the process, adopting a realistic model of amorphous silica.
OptMDFpathway: Identification of metabolic pathways with maximal thermodynamic driving force and its application for analyzing the endogenous CO2 fixation potential of Escherichia coli

Constraint-based modeling techniques have become a standard tool for the in silico analysis of metabolic networks. To further improve their accuracy, recent methodological developments focused on integration of thermodynamic information in metabolic models to assess the feasibility of flux distributions by thermodynamic driving forces. Here we present OptMDFpathway, a method that extends the recently proposed framework of Max-min Driving Force (MDF) for thermodynamic pathway analysis. Given a metabolic network model, OptMDFpathway identifies both the optimal MDF for a desired phenotypic behavior as well as the respective pathway itself that supports the optimal driving force. OptMDFpathway is formulated as a mixed-integer linear program and is applicable to genome-scale metabolic networks. As an important theoretical result, we also show that there exists always at least one elementary mode in the network that reaches the maximal MDF. We employed our new approach to systematically identify all substrate-product combinations in Escherichia coli where product synthesis allows for concomitant net CO2 assimilation via thermodynamically feasible pathways. Although biomass synthesis cannot be coupled to net CO2 fixation in E. coli we found that as many as 145 of the 949 cytosolic carbon metabolites contained in the genome-scale model iJO1366 enable net CO2 incorporation along thermodynamically feasible pathways with glycerol as substrate and 34 with glucose. The most promising products in terms of carbon assimilation yield and thermodynamic driving forces are orotate, aspartate and the C4-metabolites of the tricarboxylic acid cycle. We also identified thermodynamic bottlenecks frequently limiting the maximal driving force of the CO2-fixing pathways. Our results indicate that heterotrophic organisms like E. coli hold a possibly underestimated potential for CO2 assimilation which may complement existing biotechnological approaches for capturing CO2. Furthermore, we envision that the developed OptMDFpathway approach can be used for many other applications within the framework of constrained-based modeling and for rational design of metabolic networks.
Mosquitoes and the Lymphatic Filarial Parasites: Research Trends and Budding Roadmaps to Future Disease Eradication

The mosquito-borne lymphatic filariasis (LF) is a parasitic, neglected tropical disease that imposes an unbearable human scourge. Despite the unprecedented efforts in mass drug administration (MDA) and morbidity management, achieving the global LF elimination slated for the year 2020 has been thwarted by limited MDA coverage and ineffectiveness in the chemotherapeutic intervention. Moreover, successful and sustainable elimination of mosquito-vectored diseases is often encumbered by reintroduction and resurgence emanating from human residual or new infections being widely disseminated by the vectors even when chemotherapy proves effective, but especially in the absence of effective vaccines. This created impetus for strengthening the current defective mosquito control approach, and profound research in vector–pathogen systems and vector biology has been pushing the boundaries of ideas towards developing refined vector-harnessed control strategies. Eventual implementation of these emerging concepts will offer a synergistic approach that will not only accelerate LF elimination, but also augurs well for its future eradication. This brief review focuses on advances in mosquito–filaria research and considers the emerging prospects for future eradication of LF.
Factors Associated with Obesity Prevention Efforts Among the Senior High School Students in Makassar City

The aim of this study to determine factors associated with obesity prevention efforts among the senior high school students in Makassar city. The study type was an observational cross-sectional study. The population of this study were all students of class X at six senior high schools in Makassar city. The samples sizes were 318 students by proportional random sampling. The result found relationship between parent education level (p= 0.000), heredity (p=0.037), benefits perceived (p=0.000), barriers perceived (p=0.000), knowledge (p=0.000), parental support (p=0.000), peer support (p=0.005) and media support (p= 0.000) with obesity prevention on the senior high school students in Makassar city.
Lexical Bias In Essay Level Prediction

Automatically predicting the level of non-native English speakers given their written essays is an interesting machine learning problem. In this work I present the system "balikasg" that achieved the state-of-the-art performance in the CAp 2018 data science challenge among 14 systems. I detail the feature extraction, feature engineering and model selection steps and I evaluate how these decisions impact the system's performance. The paper concludes with remarks for future work.
On k-abelian Equivalence and Generalized Lagrange Spectra

We study the set of $k$-abelian critical exponents of all Sturmian words. It has been proven that in the case $k = 1$ this set coincides with the Lagrange spectrum. Thus the sets obtained when $k > 1$ can be viewed as generalized Lagrange spectra. We characterize these generalized spectra in terms of the usual Lagrange spectrum and prove that when $k > 1$ the spectrum is a dense non-closed set. This is in contrast with the case $k = 1$, where the spectrum is a closed set containing a discrete part and a half-line. We describe explicitly the least accumulation points of the generalized spectra. Our geometric approach allows the study of $k$-abelian powers in Sturmian words by means of continued fractions.