Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effectiveness of Sponsorship of the F1 Singapore Grand Prix: Recall and Recognition

This article examines the effectiveness of sport sponsorship at the 2014 F1 Singapore Grand Prix, particularly by testing recall and recognition of brands on cars, driver's clothing and venue. Data was gathered from 120 undergraduate students who were asked to watch a 30-second video first and complete the questionnaires. The multivariate analysis of variance revealed that cars and driver's clothing were found to be more effective locations for brand awareness. There was significant differences in both recall (I”M = 1.28, p < .05 and I”M = 0.80, p < .05, respectively) and recognition (I”M = 2.15, p < .05 and I”M = 1.47, p < .05, respectively). These findings help present or potential sponsors review the benefits and costs associated with this channel of sponsorship and maximise their sponsorship investments on F1 teams or the Singapore Grand Prix in the future.
SPIRE-SST: An Automatic Web-based Self-learning Tool for Syllable Stress Tutoring (SST) to the Second Language Learners

Correct stress placement on the syllables in a word or word groups is important in the spoken communication. Thus, incorrect syllable stress, typically made by second language (L2) learners, could result in miscommunication. In this demo, we present SPIRE-SST tool that tutors to learn correct stress patterns in a self-learning manner. Thus, the proposed tool could also beneﬁt the learners without any access to the effective training methods. For this, we design a front-end containing self-explanatory instructions that can be easily followed by the user. Using the front-end, learners can submit their audio to the back-end and can view the corresponding feedback from the back-end. In the back-end, we divide the entire audio from the learner into syllable segments and detect each syllable as stressed or un-stressed. Using these stress markings, we compute a score representing the stress quality in comparison with the ground-truth stress markings and send it to the front-end as a feedback. We also send a set of three features by comparing the audio from the expert and learner as the feedback, which we assume to be useful for correcting the pronunciation errors.
A Multiphysics Biventricular Cardiac Model: Simulations With a Left-Ventricular Assist Device

Computational models have become essential in predicting medical device efficacy prior to clinical studies. To investigate the performance of a left-ventricular assist device (LVAD), a fully-coupled cardiac fluid-electromechanics finite element model was developed, incorporating electrical activation, passive and active myocardial mechanics, as well as blood hemodynamics solved simultaneously in an idealized biventricular geometry. Electrical activation was initiated using a simplified Purkinje network with one-way coupling to the surrounding myocardium. Phenomenological action potential and excitation-contraction equations were adapted to trigger myocardial contraction. Action potential propagation was formulated within a material frame to emulate gap junction-controlled propagation, such that the activation sequence was independent of myocardial deformation. Passive cardiac mechanics were governed by a transverse isotropic hyperelastic constitutive formulation. Blood velocity and pressure were determined by the incompressible Navier-Stokes formulations with a closed-loop Windkessel circuit governing the circulatory load. To investigate heart-LVAD interaction, we reduced the left ventricular (LV) contraction stress to mimic a failing heart, and inserted a LVAD cannula at the LV apex with continuous flow governing the outflow rate. A proportional controller was implemented to determine the pump motor voltage whilst maintaining pump motor speed. Following LVAD insertion, the model revealed a change in the LV pressure-volume loop shape from rectangular to triangular. At higher pump speeds, aortic ejection ceased and the LV decompressed to smaller end diastolic volumes. After multiple cycles, the LV cavity gradually collapsed along with a drop in pump motor current. The model was therefore able to predict ventricular collapse, indicating its utility for future development of control algorithms and pre-clinical testing of LVADs to avoid LV collapse in recipients.
Circuits and Expressions over Finite Semirings

The computational complexity of the circuit and expression evaluation problem for finite semirings is considered, where semirings are not assumed to have an additive or a multiplicative identity. The following dichotomy is shown: If a finite semiring is such that (i) the multiplicative semigroup is solvable and (ii) it does not contain a subsemiring with an additive identity 0 and a multiplicative identity 1 ≠ 0, then the circuit evaluation problem is in DET ⊆ NC2, and the expression evaluation problem for the semiring is in TC0. For all other finite semirings, the circuit evaluation problem is P-complete and the expression evaluation problem is NC1-complete. As an application, we determine the complexity of intersection non-emptiness problems for given context-free grammars (regular expressions) with a fixed regular language.
Synthetic circuits reveal how mechanisms of gene regulatory networks constrain evolution

Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe—a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.
Daily Consumption of Chocolate Rich in Flavonoids Decreases Cellular Genotoxicity and Improves Biochemical Parameters of Lipid and Glucose Metabolism

In recent years, the incidence of atherosclerotic cardiovascular disease, obesity, and diabetes has increased largely worldwide. In the present work, we evaluated the genoprotective effect of the consumption of flavonoids-rich chocolate on 84 young volunteers. Biochemical indicators related to the prevention and treatment of cardiovascular risk and metabolic syndrome were also determined. A randomized, placebo-controlled, double-blind study was performed in the Autonomous University of Baja California. The treatments comprised the daily consumption of either 2 g of dark chocolate containing 70% cocoa, or 2 g of milk chocolate, for 6 months. The total amount of phenolic compounds and flavonoids was determined in both types of chocolate. Anthropometrical and Biochemical parameters were recorded prior to and after the study. The evaluation of the genotoxicity in buccal epithelial cells was performed throughout the duration of the study. Flavonoids from cocoa in dark chocolate significantly prevented DNA damage, and improved the nucleus integrity of cells. This effect could be related to the antioxidant capacity of the dark chocolate that decreased cellular stress. Biochemical parameters (total cholesterol, triglycerides, and LDL-cholesterol level in blood) and anthropometrical parameters (waist circumference) were improved after six months of daily intake of 2 g of dark chocolate with a 70% of cocoa.
Exploring Machine Reading Comprehension with Explicit Knowledge

To apply general knowledge to machine reading comprehension (MRC), we propose an innovative MRC approach, which consists of a WordNet-based data enrichment method and an MRC model named as Knowledge Aided Reader (KAR). The data enrichment method uses the semantic relations of WordNet to extract semantic level inter-word connections from each passage-question pair in the MRC dataset, and allows us to control the amount of the extraction results by setting a hyper-parameter. KAR uses the extraction results of the data enrichment method as explicit knowledge to assist the prediction of answer spans. According to the experimental results, the single model of KAR achieves an Exact Match (EM) of $72.4$ and an F1 Score of $81.1$ on the development set of SQuAD, and more importantly, by applying different settings in the data enrichment method to change the amount of the extraction results, there is a $2\%$ variation in the resulting performance of KAR, which implies that the explicit knowledge provided by the data enrichment method plays an effective role in the training of KAR.
Significance Level of a Big Data Query by Exploiting Business Processes and Strategies

Querying data is one of the most frequent activities in business organisations. The tasks involving queries for big data collection, extraction and analysis have never been easy, because to obtain the high quality responses, the expected outcome from these tasks need to be more accurate and highly relevant to a business organisation. The emergence of big data era has further complicated the task. The enormous volume of data from diverse sources and the variety of queries impose a big challenge on business organisations on how to extract deep insight from big data within acceptable time. Determining significance levels of queries based on their relevance to business organisations is able to deal with such challenge. To address this issue, up to our knowledge, there exists only one approach in the literature to calculate the significance level of a query. However, in this approach, only business processes are considered by manually selecting weights for core and non-core business processes. As the significance level of a query must express the importance of that query to a business organisation, it has to be calculated based on the consideration of business strategic direction, which requires the consideration of both business processes and strategies. This paper proposes an approach for the first time where the significance level of a query is determined by exploiting process contributions and strategy priorities. The results produced by our proposed approach using a business case study show the queries that are associated with more important business processes and higher priority strategies have higher significance levels. This vindicates the application of the significance level in a query to dynamically scale the semantic information use in capturing the appropriate level of deep insight and relevant information required for a business organisation.
The Golden Activity of Lysinibacillus sphaericus: New Insights on Gold Accumulation and Possible Nanoparticles Biosynthesis

Power struggles surrounding the increasing economic development of gold mining give rise to severe environmental and social problems. Two new strains of Lysinibacillus sphaericus were isolated from an area of active alluvial gold mining exploitation at El Bagre, Antioquia. The absorption capacity of these strains and some of the L. sphaericus Microbiological Research Center (CIMIC) collection (CBAM5, OT4b.31, III(3)7) were evaluated by spectrophotometry according to a calibration gold curve of HAuCl4− with concentrations between 0 µg/mL and 100 µg/mL. Bioassays with living biomass were carried out with an initial gold concentration of 60 µg/mL. Their sorption capacity was evident, reaching percentages of gold removal between 25% and 85% in the first 2 h and 75% to 95% after 48 h. Biosynthesis of possible gold nanoparticles (AuNPs) in assays with living biomass was also observed. Metal sorption was evaluated using scanning electron microscopy and energy-dispersive X-ray spectroscopy (EDS) analysis. The sorption and fabrication capacity exhibited by the evaluated strains of L. sphaericus converts this microorganism into a potential alternative for biomining processes, especially those related to gold extraction.
Analyzing the Terminal Protein Differences of Adenovirus serotype 2(Ad2) and Human Herpes virus-4(HHV-4) by Using Support Vector Machine

This experiment has the meaning for effective classification between Adenovirus serotype 2 and Human Herpes Virus-4 by discovering the Kernel Function which has low error rate using Support Vector Machine. Analyzing the differences would state the potential of developing medical remedy for Herpesvirus which has no vaccine of virus-specific therapy.
Vesicle sub‐pool organization at inner hair cell ribbon synapses

The afferent inner hair cell synapse harbors the synaptic ribbon, which ensures a constant vesicle supply. Synaptic vesicles (SVs) are arranged in morphologically discernable pools, linked via filaments to the ribbon or the presynaptic membrane. We propose that filaments play a major role in SV resupply and exocytosis at the ribbon. Using advanced electron microscopy, we demonstrate that SVs are organized in sub‐pools defined by the filament number per vesicle and its connections. Upon stimulation, SVs increasingly linked to other vesicles and to the ribbon, whereas single‐tethered SVs dominated at the membrane. Mutant mice for the hair cell protein otoferlin (pachanga, OtofPga/Pga) are profoundly deaf with reduced sustained release, serving as a model to investigate the SV replenishment at IHCs. Upon stimulation, multiple‐tethered and docked vesicles (rarely observed in wild‐type) accumulated at OtofPga/Pga active zones due to an impairment downstream of docking. Conclusively, vesicles are organized in sub‐pools at ribbon‐type active zones by filaments to support vesicle supply, transport, and finally release.
5-Hydroxymethylfurfural (HMF) Production from Real Biomasses

The present paper reviews recent advances on the direct synthesis of 5-hydroxymethylfurfural (HMF) from different kinds of raw biomasses. In particular, in the paper HMF production from: (i) edible biomasses; (ii) non-edible lignocellulosic biomasses; (iii) food wastes (FW) have been reviewed. The different processes and catalytic systems have been reviewed and their merits, demerits and requirements for commercialisation outlined.
Impact of Dysphagia Assessment and Management on Risk of Stroke-Associated Pneumonia: A Systematic Review

Background: Patients with dysphagia are at an increased risk of stroke-associated pneumonia. There is wide variation in the way patients are screened and assessed during the acute phase. The aim of this review was to identify the methods of assessment and management in acute stroke that influence the risk of stroke-associated pneumonia. Studies of stroke patients that reported dysphagia screening, assessment or management and occurrence of pneumonia during acute phase stroke were screened for inclusion after electronic searches of multiple databases from inception to November 2016. The primary outcome was association with stroke-associated pneumonia. Summary: Twelve studies of 87,824 patients were included. The type of dysphagia screening protocol varied widely across and within studies. There was limited information on what comprised a specialist swallow assessment and alternative feeding was the only management strategy, which was reported for association with stroke-associated pneumonia. Use of a formal screening protocol and early dysphagia screening (EDS) and assessment by a speech and language pathologist (SLP) were associated with a reduced risk of stroke-associated pneumonia. There was marked heterogeneity between the included studies, which precluded meta-analysis. Key Messages: There is variation in the assessment and management of dysphagia in acute stroke. There is increasing evidence that EDS and specialist swallow assessment by an SLP may reduce the odds of stroke-associated pneumonia. There is the potential for other factors to influence the incidence of stroke-associated pneumonia during the acute phase.
Physics-Informed Kriging: A Physics-Informed Gaussian Process Regression Method for Data-Model Convergence

In this work, we propose a new Gaussian process regression (GPR) method: physics-informed Kriging (PhIK). In the standard data-driven Kriging, the unknown function of interest is usually treated as a Gaussian process with assumed stationary covariance with hyperparameters estimated from data. In PhIK, we compute the mean and covariance function from realizations of available stochastic models, e.g., from realizations of governing stochastic partial differential equations solutions. Such a constructed Gaussian process generally is non-stationary, and does not assume a specific form of the covariance function. Our approach avoids the costly optimization step in data-driven GPR methods to identify the hyperparameters. More importantly, we prove that the physical constraints in the form of a deterministic linear operator are guaranteed in the resulting prediction. We also provide an error estimate in preserving the physical constraints when errors are included in the stochastic model realizations. To reduce the computational cost of obtaining stochastic model realizations, we propose a multilevel Monte Carlo estimate of the mean and covariance functions. Further, we present an active learning algorithm that guides the selection of additional observation locations. The efficiency and accuracy of PhIK are demonstrated for reconstructing a partially known modified Branin function and learning a conservative tracer distribution from sparse concentration measurements.
The Association of Built Environment and Physical Activity in Older Adults: Using a Citywide Public Housing Scheme to Reduce Residential Self-Selection Bias

Previous studies have documented numerous health benefits of conducting regular physical activity among older adults. The built environment is believed to be a key factor that can hinder or facilitate daily physical activity, such as walking and exercising. However, most empirical studies focusing on environment-physical activity associations exhibited residential self-selection bias with cross-sectional research design, engendering doubts about the impact of built environment on physical activity. To reduce this bias, we assessed physical activity behaviors of 720 Hong Kong older adults (≥65 years) residing in 24 public housing estates. The Hong Kong public housing scheme currently provides affordable rental flats for 2.1 million people or approximate 30% of total population. The applicants were allocated to one of 179 housing estates largely by family size and flat availability. Built environment characteristics were measured following the ‘5Ds’ principle: (street network) design, (land-use) diversity, density, distance to transit, and destination accessibility. Multilevel mixed models were used to explore the associations between the built environment and the different domains of physical activity (transportation walking, recreational walking, and recreational moderate-to-vigorous physical activity (MVPA) while controlling for potential estate-level socioeconomic and individual confounders. We found that transportation walking was positively associated with the number of bus stops and the presence of Mass Transit Railway (MTR) stations. Recreational MVPA was positively related to the number of recreational facilities. However, land-use mix was negatively related to transportation walking, recreational walking, and recreational MVPA. The findings of this study support a threshold effect in the environment-physical activity associations. Furthermore, large-scale public housing schemes involving random or semi-random residence assignment in many cities may provide opportunities to explore built environments and physical activity behavior, with the potential to overcome residential self-selection bias.
BLAG: Bandit On Large Action Set Graph

Information diffusion in social networks facilitates rapid and large-scale propagation of content. However, spontaneous diffusion behavior could also lead to the cascading of sensitive information, which is neglected in prior arts. In this paper, we present the first look into adaptive diffusion of sensitive information, which we aim to prevent from widely spreading without incurring much information loss. We undertake the investigation in networks with partially known topology, meaning that some users' ability of forwarding information is unknown. Formulating the problem into a bandit model, we propose BLAG (Bandit on Large Action set Graph), which adaptively diffuses sensitive information towards users with weak forwarding ability that is learnt from tentative transmissions and corresponding feedbacks. BLAG enjoys a low complexity of O(n), and is provably more efficient in the sense of half regret bound compared with prior learning method. Experiments on synthetic and three real datasets further demonstrate the superiority of BLAG in terms of adaptive diffusion of sensitive information over several baselines, with at least 40 percent less information loss, at least 10 times of learning efficiency given limited learning rounds and significantly postponed cascading of sensitive information.
Voxel-Mirrored Homotopic Connectivity of Resting-State Functional Magnetic Resonance Imaging in Blepharospasm

Objective: Several networks in human brain are involved in the development of blepharospasm. However, the underlying mechanisms for this disease are poorly understood. A voxel-mirrored homotopic connectivity (VMHC) method was used to quantify the changes in functional connectivity between two hemispheres of the brain in patients with blepharospasm. Methods: Twenty-four patients with blepharospasm and 24 healthy controls matched by age, sex, and education were recruited. The VMHC method was employed to analyze the fMRI data. The support vector machine (SVM) method was utilized to examine whether these abnormalities could be applied to distinguish the patients from the controls. Results: Compared with healthy controls, patients with blepharospasm showed significantly high VMHC in the inferior temporal gyrus, interior frontal gyrus, posterior cingulate cortex, and postcentral gyrus. No significant correlation was found between abnormal VMHC values and clinical variables. SVM analysis showed a combination of increased VMHC values in two brain areas with high sensitivities and specificities (83.33 and 91.67% in the combined inferior frontal gyrus and posterior cingulate cortex; and 83.33 and 87.50% in the combined inferior temporal gyrus and postcentral gyrus). Conclusion: Enhanced homotopic coordination in the brain regions associated with sensory integration networks and default-mode network may be underlying the pathophysiology of blepharospasm. This phenomenon may serve as potential image markers to distinguish patients with blepharospasm from healthy controls.