Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the perceived logic of care by vaccine-hesitant and vaccine-refusing parents: A qualitative study in Australia

In terms of public health, childhood vaccination programs have benefits that far outweigh risks. However, some parents decide not to vaccinate their children. This paper explores the ways in which such parents talked about the perceived risks and benefits incurred by vaccinating (or not vaccinating) their children. Between 2013–2016 we undertook 29 in-depth interviews with non-vaccinating and/or ‘vaccine hesitant’ parents in Australia. Interviews were conducted in an open and non-judgmental manner, akin to empathic neutrality. Interviews focused on parents talking about the factors that shaped their decisions not to (or partially) vaccinate their children. All interviews were transcribed and analysed using both inductive and deductive processes. The main themes focus on parental perceptions of: 1. their capacity to reason; 2. their rejection of Western medical epistemology; and 3. their participation in labour intensive parenting practices (which we term salutogenic parenting). Parents engaged in an ongoing search for information about how best to parent their children (capacity to reason), which for many led to questioning/distrust of traditional scientific knowledge (rejection of Western medical epistemology). Salutogenic parenting spontaneously arose in interviews, whereby parents practised health promoting activities which they saw as boosting the natural immunity of their children and protecting them from illness (reducing or negating the perceived need for vaccinations). Salutogenic parenting practices included breastfeeding, eating organic and/or home-grown food, cooking from scratch to reduce preservative consumption and reducing exposure to toxins. We interpret our data as a ‘logic of care’, which is seen by parents as internally consistent, logically inter-related and inter-dependent. Whilst not necessarily sharing the parents’ reasoning, we argue that an understanding of their attitudes towards health and well-being is imperative for any efforts to engage with their vaccine refusal at a policy level.
Leaf morphological and physiological adaptations of a deciduous oak (Quercus faginea Lam.) to the Mediterranean climate: a comparison with a closely related temperate species (Quercus robur L.).

'White oaks'--one of the main groups of the genus Quercus L. --are represented in western Eurasia by the 'roburoid oaks', a deciduous and closely related genetic group that should have an Arcto-Tertiary origin under temperate-nemoral climates. Nowadays, roburoid oak species such as Quercus robur L. are still present in these temperate climates in Europe, but others are also present in southern Europe under Mediterranean-type climates, such as Quercus faginea Lam. We hypothesize the existence of a coordinated functional response at the whole-shoot scale in Q. faginea under Mediterranean conditions to adapt to more xeric habitats. The results reveal a clear morphological and physiological segregation between Q. robur and Q. faginea, which constitute two very contrasting functional types in response to climate dryness. The most outstanding divergence between the two species is the reduction in transpiring area in Q. faginea, which is the main trait imposed by the water deficit in Mediterranean-type climates. The reduction in leaf area ratio in Q. faginea should have a negative effect on carbon gain that is partially counteracted by a higher inherent photosynthetic ability of Q. faginea when compared with Q. robur, as a consequence of higher mesophyll conductance, higher maximum velocity of carboxylation and much higher stomatal conductance (gs). The extremely high gs of Q. faginea counteracts the expected reduction in gs imposed by the stomatal sensitivity to vapor pressure deficit, allowing this species to diminish water losses maintaining high net CO2 assimilation values along the vegetative period under nonlimiting soil water potential values. In conclusion, the present study demonstrates that Q. faginea can be regarded as an example of adaptation of a deciduous oak to Mediterranean-type climates.
Augmenting Performance of SMT Models by Deploying Fine Tokenization of the Text and Part-of-Speech Tag

This paper presents our study of exploiting the languages’ word class information augmented with some rule-based processing for phrase-based Statistical Machine Translation (SMT). In statistical machine translation, estimating word-to-word alignment probabilities for the translation model can be difficult due to the problem of sparse data: most words in a given corpus occur at most a handful of times. With a highly inflected language such as Oromo, this problem can be particularly severe. In addition, there is variant nature or use of different symbols for ‘hudhaa’ (the diacritical marker) in Oromo language which intrudes another severe data sparsity problem. In this work, we show that using fine tokenization of words considering intra-word behavior of words consisting hudhaa, and POS tag to modify the Oromo input and see how it improves Oromo-English machine translation system. The models were trained on a very small parallel corpus of data set (usually unacceptable for normal SMT system) and also the quality of the parallel corpus both in translation and spelling errors were not so good. Yet, our final system achieves a BLEU score of 2.88, as compared to 2.56 for the baseline system.
Is there a link between availability of food and beverage establishments and BMI in Mexican adults?

Abstract Objective To study the association between density of stores (food and beverage stores, stores selling only fruits and vegetables, and supermarkets) and the BMI of adults aged ≥20 years in Mexico. Design A cross-sectional study was performed. Individual data came from the 2012 National Health and Nutrition Survey, while information on stores was taken from the National Institute of Geography and Statistics’ National Statistics Directory of Economic Units. A weighted least-squares model was estimated to test the association between density of stores and BMI of adults adjusting for sex, age, education, presence of hypertension, diabetes or both, household assets index and marginality index at the municipality level. Setting Mexico. Results An additional 1 sd in the density of fruit and vegetable stores was associated with a reduction of 0·24 (95 % CI −0·37, −0·12) kg/m2 in BMI when the densities of the other stores were at their mean values. For food and beverage store density, a difference of 1 sd was associated with an increase of 0·50 (95 % CI 0·33, 0·67) kg/m2 in BMI, while for supermarkets the corresponding association was a reduction of 0·48 (95 % CI −1·52, 0·56) kg/m2 in BMI. Conclusions In places with a higher density of stores that offer unhealthy foods, the BMI of adults tends to be higher.
Neural Nets Can Learn Function Type Signatures From Binaries

Function type signatures are important for binary analysis, but they are not available in COTS binaries. In this paper, we present a new system called E KLAVYA which trains a recurrent neural network to recover function type signatures from disassembled binary code. E KLAVYA assumes no knowledge of the target instruction set semantics to make such inference. More importantly, E KLAVYA results are “explicable”: we ﬁnd by analyzing its model that it auto-learns relationships between instructions, compiler conventions, stack frame setup instructions, use-before-write patterns, and operations relevant to identifying types directly from binaries. In our evaluation on Linux binaries compiled with clang and gcc , for two different architectures (x86 and x64), E KLAVYA exhibits accuracy of around 84% and 81% for function argument count and type recovery tasks respectively. E KLAVYA generalizes well across the compilers tested on two different instruction sets with various optimization levels, without any specialized prior knowledge of the instruction set, compiler or optimization level.
Subjective memory complaints in the elderly: a sign of cognitive impairment?

OBJECTIVES: Cognitive impairment in the elderly is frequently overlooked by general practitioners. The use of subjective memory complaints as a sign of cognitive impairment by the general practice is controversial. METHODS: Elderly individuals (N = 248) were asked whether they had memory complaints and underwent a cognitive impairment screening. Subjects classified as exhibiting “probable cognitive impairment” underwent a complete cognitive evaluation, and the final diagnoses were established by expert consensus. RESULTS: A total of 147 patients presented with subjective memory complaints, and 43 were further classified as demented or “cognitively impaired not demented”. Subjective memory complaints presented a sensitivity of 100% and a negative predictive value of 100%. CONCLUSION: Subjective memory complaints are an indicator for cognitive impairment screening.
Diverse Kir Expression Contributes to Distinct Bimodal Distribution of Resting Potentials and Vasotone Responses of Arterioles

The resting membrane potential (RP) of vascular smooth muscle cells (VSMCs) is a major determinant of cytosolic calcium concentration and vascular tone. The heterogeneity of RPs and its underlying mechanism among different vascular beds remain poorly understood. We compared the RPs and vasomotion properties between the guinea pig spiral modiolar artery (SMA), brain arterioles (BA) and mesenteric arteries (MA). We found: 1) RPs showed a robust bimodal distribution peaked at -76 and -40 mV evenly in the SMA, unevenly at -77 and -51 mV in the BA and ~-71 and -52 mV in the MA. Ba2+ 0.1 mM eliminated their high RP peaks ~-75 mV. 2) Cells with low RP (~-45 mV) hyperpolarized in response to 10 mM extracellular K+, while cells with a high RP depolarized, and cells with intermediate RP (~-58 mV) displayed an initial hyperpolarization followed by prolonged depolarization. Moderate high K+ typically induced dilation, constriction and a dilation followed by constriction in the SMA, MA and BA, respectively. 3) Boltzmann-fit analysis of the Ba2+-sensitive inward rectifier K+ (Kir) whole-cell current showed that the maximum Kir conductance density significantly differed among the vessels, and the half-activation voltage was significantly more negative in the MA. 4) Corresponding to the whole-cell data, computational modeling simulated the three RP distribution patterns and the dynamics of RP changes obtained experimentally, including the regenerative swift shifts between the two RP levels after reaching a threshold. 5) Molecular works revealed strong Kir2.1 and Kir2.2 transcripts and Kir2.1 immunolabeling in all 3 vessels, while Kir2.3 and Kir2.4 transcript levels varied. We conclude that a dense expression of functional Kir2.X channels underlies the more negative RPs in endothelial cells and a subset of VSMC in these arterioles, and the heterogeneous Kir function is primarily responsible for the distinct bimodal RPs among these arterioles. The fast Kir-based regenerative shifts between two RP states could form a critical mechanism for conduction/spread of vasomotion along the arteriole axis.
KCa channels and epoxyeicosatrienoic acids: major contributors to thermal hyperaemia in human skin

• The increased blood flow associated with local heating of the skin is ∼60% dependent on nitric oxide. The remaining ∼40% is unknown. • Endothelial‐derived hyperpolarizing factors (EDHFs), a class of vasodilators, are known to contribute to increases in blood flow in other vascular beds. • In the present study, we showed the drug tetraethylammonium (which blocks the channels involved in EDHF‐mediated vasodilatation), when given in combination with nitric oxide synthase inhibition, blocked the majority of hyperaemia to local heat, indicating that EDHFs are responsible for the majority of the remaining ∼40% of hyperaemia. • We also showed that about half of the EDHF‐component is attributed to a specific type of EDHF, epoxyeicosatrienoic acid (EET), as evidenced using the cytochrome P450 inhibitor sulfaphenazole. • These findings help further our understanding of the mechanisms behind cutaneous thermal hyperaemia.
Effect of age on semen parameters in infertile men after varicocelectomy

Background The effectiveness of varicocelectomy in restoration of fertility and improvement of semen parameters is still controversial. The purpose of this study was to determine the effect of age on semen parameters following varicocelectomy in a group of infertile men. Methods Improvements in sperm count, morphology, and motility were studied in 67 infertile patients 4–10 months after varicocelectomy. Results The mean age of the patients was 30.48 ± 7.49 years. Significant improvements in total sperm count, percentage normal morphology, and motility were noted in all age groups (P < 0.05). Patients aged <25 years demonstrated the greatest increase in sperm counts, normal morphology, and motility following varicocelectomy. There was a significant negative correlation between age and sperm count, sperm morphology, and sperm motility (P < 0.05). Conclusion The effect of age on improvement in sperm parameters after varicocelectomy is inconsistent with some reports in the literature, and could be attributable to the duration of infertility prior to surgery; in the long term, varicoceles are known to have deleterious effects on testis biology.
Cross-Covariance Functions for Multivariate Geostatistics

Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Mat\'{e}rn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems.
Attracting Early Stage Investors: Evidence from a Randomized Field Experiment

This paper uses a randomized field experiment to identify which start-up characteristics are most important to investors in early stage firms. The experiment randomizes investors’ information sets of fund-raising start-ups. The average investor responds strongly to information about the founding team, but not to firm traction or existing lead investors. In contrast, inexperienced investors respond to all information categories. Our results suggest that information about human assets is causally important for the funding of early stage firms, and hence, for entrepreneurial success.
A Note on dual superconformal symmetry of the N=4 super Yang-Mills S-matrix

We present a supersymmetric recursion relation for tree-level scattering amplitudes in N=4 super Yang-Mills. Using this recursion relation, we prove that the tree-level S matrix of the maximally supersymmetric theory is covariant under dual superconformal transformations. We further analyze the consequences that the transformation properties of the trees under this symmetry have on those of the loops. In particular, we show that the coefficients of the expansion of generic one-loop amplitudes in a basis of pseudoconformally invariant scalar box functions transform covariantly under dual superconformal symmetry, and in exactly the same way as the corresponding tree-level amplitudes.
Distributed Area Coverage by Connected Set Cover Partitioning in Wireless Sensor Networks

Assuming a random uniform distribution of n sensor nodes over a virtual grid, this paper addresses the problem of finding the maximum number of connected set covers each ensuring 100% coverage of the query region. The connected sets remain active one after another in a round robin fashion such that if there are P such set covers, it can enhance the network lifetime P-fold. From graph-theoretic point of view, a centralized O(n3) heuristic is proposed here to maximize P. Next, for large self-organized sensor networks, a distributed algorithm is developed. The proposed algorithm is to be executed just once, during the initialization of the network. In case of failure, a distributed recovery algorithm is executed to rearrange the partitions. Simulation studies show that the performance of the proposed distributed algorithm is comparable with that of the centralized algorithm in terms of number of partitions. Also, comparison with earlier works shows significant improvement in terms of number of partitions, message complexity and network lifetime.
Development and characterization study of silk filament reinforced chitosan biocomposite

ABSTRACT The present work aims to explore the use of a silk filament (SF) as a reinforced material in chitosan matrix to develop low-cost biocomposite using the solution casting technique. The biocomposites were assessed for their physiochemical, mechanical, as well as thermal properties. Fourier-transform infrared study confirmed the chemical interaction between SF and chitosan matrix in biocomposite samples. The morphology of SF in the matrix was discovered by scanning electron microscopy analysis and bundle formation of individual filaments was observed due to the adhesive effect of chitosan solution. The prepared composites with higher loading showed improved mechanical properties. X-ray diffraction study showed increased crystallinity of the biocomposite when compared with the chitosan film (CF). The thermal properties of the biocomposites improved due to the presence of SF.
Artificial Immune System-based algorithm for vehicle routing problem with time window constraint for the delivery of agri-fresh produce

Abstract This paper addresses the problem of delivering continuously deteriorating agri-fresh produce from a wholesaler to a number of retailers, within specific time windows. The prime objective is to decide the routes in such a way that the overall cost incurred in transportation, deterioration and penalty is minimised. To model these conflicting objectives a mathematical modelling approach is proposed. The Vehicle Routing Problem with Time Windows (VRPTW) is a Non-deterministic Polynomial-time hard (NP-hard) problem, without considering the business constraints, and becomes computationally prohibitive with the increase in number of retailers. To solve the VRPTW within feasible time limits, Artificial Immune System (AIS)-based solution methodology is proposed. The algorithm is tested on real-life instances generated from Azadpur wholesale market, New Delhi (India). An experiment is performed on the same problems with other algorithms, such as Genetic Algorithm (GA) and Simulated Annealing (SA), to compare the effectiveness and efficiency of the proposed approach. It is found from the quality of solution and rate of convergence that AIS performed better compared to the other applied approaches.
The Awareness of Cloud Computing: A Case Study of South African SMEs

—South African SMEs are faced with several challenges which negatively affect their growth and sustainability, such as marketing factors, financial issues, management skills and lack of investment in Information and Communication technology (ICT). The evolution of ICT solutions such as cloud computing, have the potential to counter some of the challenges that SMEs are facing. However, most technologies are not adopted due to lacking knowledge and perceptions on their potentials and value. Therefore this paper investigates the awareness of cloud computing within SMEs in South Africa. In addition, the paper identifies SMEs perceptions on cloud computing as an alternative ICT solution. The study adopted qualitative research approach, where case study research designs was used consisting of three SMEs organisation. The data was collected through interviews, expert reviews, literature and questionnaires, where a total of 19 participants were used. The findings reveals a lacking levels of cloud computing awareness, thus limited knowledge on cloud computing benefits and services. This paper concludes that the lacking awareness and understanding of cloud computing is the main cause of slow cloud computing adoption amongst SMEs in South Africa. The paper concludes by recommending methods which can be used to increase SMEs awareness of cloud computing.
Metal Abundances of KISS Galaxies. II. Nebular Abundances of 12 Low-Luminosity Emission-Line Galaxies

We present follow-up spectra of 39 emission-line galaxies (ELGs) from the KPNO International Spectroscopic Survey (KISS). Many targets were selected as potentially low-metallicity systems based on their absolute B magnitudes and the metallicity-luminosity relation. The spectra, obtained with the Lick 3 m telescope, cover the full optical region from [O II] λλ3726, 3729 to beyond [S II] λλ6717, 6731 and include measurement of [O III] λ4363 in 12 objects. The spectra are presented and tables of the strong line ratios are given. For 12 high signal-to-noise ratio spectra, we determine abundance ratios of oxygen, nitrogen, neon, sulfur, and argon. We find these galaxies to be metal deficient with three systems approaching O/H of 1/25th solar. We compare the abundance results from the temperature-based Te method to the results from the strong-line p3 method of Pilyguin.
Assessing the effects of narrative, pictorial, and graphical information about global population growth on risk perceptions and support for mitigation and prevention strategies

The human population is forecast to increase by 3-4 billion people during this century and many scientists have expressed concerns that this could increase the likelihood of certain adverse events (e.g., climate change, resource shortages). Recent research shows that these concerns are mirrored in public risk perceptions and that these perceptions correlate with a willingness to adopt mitigation behaviors (e.g., reduce resource consumption) and preventative actions (e.g., support actions to limit growth). However, little research has assessed the factors that influence risk perceptions of global population growth (GPG). To contribute to this important goal, this paper presents three studies that examined how risk perceptions of GPG might be influenced by textual-visual representations (like those in media and internet articles) of the potential effects of GPG. Study 1 found that a textual-narrative which highlighted the potential negative (cf. positive) consequences of GPG led to higher perceived risk and greater willingness to adopt mitigation behaviors, but not to support preventative actions. Notably, the influence of the narratives on perceived risk was largely moderated by the participant’s prior knowledge and perceptions of GPG. Contrary to expectations, Studies 2 and 3 revealed, respectively, that photographs depicting GPG-related imagery and graphs depicting GPG rates had no significant effect on the perceived risk of GPG or the willingness to embrace mitigation or preventative actions. However, Study 3 found that individuals with higher ‘graph literacy’ perceived GPG as a higher risk and were more willing to adopt mitigation behaviors and support preventative actions.