Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary intake of pregnant women attending a rural primary health centre in Dakshina Kannada district in Karnataka state in India

Nutrition and health status of pregnant women is important both for quality of their lives and for survival and healthy development of their children. 40 pregnant women with gestational age of 12 weeks or more attending an ante-natal clinic in a rural Primary Health Centre in Dakshina Kannada District in Karnataka state in India participated in this cross-sectional study. Dietary intake was assessed using 24 hours recall method. Haemoglobin level was estimated by acid haematin method and WHO Criteria for anaemia was applied. Among the 40 antenatal women assessed 23(58%) consumed diets deficient in calories by more than 10% of RDA. 14(60.9%) of these 23 respondents who consumed inadequate diet lived in nuclear families, 21(91.3%) had education below intermediate level and 9(39.1%) were unskilled workers and 10(43.4%) were house wives. 36(90%) of the respondents were anaemic. 30(75%) of the respondents had awareness about the Anganwadi Nutrition Programme for pregnant women. Keywords: Dietary intake, Pregnant Women, rural, primary health centre
Protocol Assessment Adherence for Depression Among Community-Dwelling and Inpatient Older Adults

Many older adults are under diagnosed and undertreated for depression by healthcare professionals (Brown, Bruce, McAvay, Raue, Lachs, & Nassisi, 2003). Depression is very prevalent in all older adults and, during times of war, veterans are at increased risk for development of some type of mental disorder (Allen & Annells, 2009). Cully, Khan, Peterson, and Zimmer (2008) indicate that almost one in 10 veterans are affected by depression. This study aimed to fill some of the gaps that exist in literature regarding depression screening and adherence to protocols for older adults. This retrospective study looked at impatient versus outpatient PHQ-2 scores to examine adherence to depression assessment protocols compare results over time. Limited data made it impossible to draw conclusions or support the research questions. Unexpected findings are discussed.
Two decades of mesoscale phenomena on either side of the Strait of Gibraltar ; Dos décadas de fenómenos de mesoescala a uno y otro lado del estrecho de Gibraltar

Mesoscale circulation patterns in the adjacent basins of the Strait of Gibraltar were investigated by means of altimetry data. In the Gulf of Cádiz, the pattern is relatively stable with two gyres: a cyclonic gyre close to the southern Iberian coast and an anticyclonic one on the western side of the Strait of Gibraltar. Both structures are located in the right place to convey the surface circulation towards the Strait and feed the Atlantic inflow. In the Alboran Sea, our results confirm that the western anticyclonic gyre is the most stable feature observed, while the eastern cyclonic gyre is subject to great variability. The mesoscale structures fluctuate at seasonal and interannual frequencies, but they may also undergo great changes in a very short time scale. A simple correlation analysis suggests that changes in the upstream Gulf of Cádiz basin may be transmitted through the Strait of Gibraltar to the Alboran Sea with a time delay of around one week.
D’Eath, R. (2012) Repeated locomotion scoring of a sow herd to measure lameness: consistency over time, the effect of sow

9 Investigating variability of scores between different observers, between animals and over time aids the 10 design of valid sampling methodologies for measuring animal welfare. Locomotion scores (0 to 5 scale) 11 were collected from i) 154 sows in one herd, using 3 to 5 (mean ± s.d. = 3.95 ± 0.65) observers each 12 time, and scoring sows on up to 10 (mean ± s.d. = 4.8 ± 2.7) occasions over a 19 month period, and ii) for 13 123 of these sows, locomotion scoring also took place prior to farrowing and at weaning. 14 The distribution of scores was highly skewed towards low scores (0: 84.8%, 1: 9.5%, 2: 4.0%, 3+: 1.7%). 15 Sows showed moderate consistency in their scores over time (W=0.496, p<0.001), and later parity sows 16 had higher scores (χ1 = 3.98, p = 0.049), but there was no effect of stage in the reproductive cycle (days 17 pregnant, pre-farrowing, post-weaning). This suggests that infrequent visits to a farm (e.g. annual) might 18 give a fair picture of the extent of lameness if a representative range of parities was sampled, although a 19 larger study of more farms would be required to investigate this. 20 The three different types of agreement between observers (absolute differences, matching and 21 association) were assessed as follows: i) Analysis of absolute differences between observers showed 22 that the farm manager scored lower than researchers/technicians (S = 102.6, p < 0.001). ii) Exact 23 matching approaches suggested fair (κ = 0.443) or good (PABAK = 0.692) agreement. Agreement was 24 poorest for mild gait abnormalities (score 1 “stiff”), and agreement improved if scores were combined 25 into ‘sound’ (0-1) and ‘lame’ (2-5) categories (κ = 0.653). iii) Measures of association suggested 26 moderate agreement (Kendall’s W = 0.692, p<0.001). Inter-observer reliability improved over time until 27 the 5th scoring event. To improve inter-observer agreement, observer training/practice and the use of 28 fewer categories are recommended, and inter-observer agreement should be checked regularly. 29
Effects on contiguous anatomical structures by disarticulation of the pterygo‐palato‐maxillary suture without the Le Fort I component

The conflicting reports of fractures following Le Fort I osteotomies may reflect the different types of specimens and techniques used. One report suggested that fractures could be avoided with proper placement of a newly designed osteotome. The results of a linear growth study tend to dispute that contention as it showed that interdigitating osseous bridges connect the components of the pterygo‐palato‐maxillary complex and fractures would occur with any attempted separation. The purpose of this radiographic and anatomic investigation was to review the suture patterns of this complex on dry adult skulls and to use cadaver specimens to determine the effects of separation of the pterygo‐palato‐maxillary articulations on the concomitant bones.
Measurement of exclusive Y photoproduction in pPb collisions at sNN = 5.02 TeV

A measurement of exclusive photoproduction of Y(1S), Y(2S) and Y(3S) mesons, in their μ+μ− decay modes, in ultraperipheral pPb collisions at a center-of-mass energy per nucleon pair of 5.02 TeV is presented. The measurement is based on data collected by the CMS experiment corresponding to an integrated luminosity of 32.6 nb−1. The Y(1S) photoproduction cross section is measured, over the rapidity range |y| < 2.2, as a function of the photon-proton center-of-mass energy, Wγp, in the range 91 < Wγp < 826 GeV. The differential cross section dσ/d|t|, where |t| ≈ pT is the squared transverse momentum of the Y(nS) mesons is measured in the range 0.01 < |t| < 1 GeV2. The results are compared to other measurements and to theoretical predictions.
The Effect of Viewing a Landscape on Physiological Health of Elderly Women

Abstract A quasi-experiment was undertaken to measure physiological characteristics of elderly women as they viewed different landscapes. Blood pressure and heart rate were monitored as elderly women living in a retirement centre viewed a natural landscape, a built landscape, and a control room with no view to the outside. Other characteristics of the individuals and the settings that have been shown to affect blood pressure and heart rate were controlled. The results indicated that, in all cases, viewing the natural landscape resulted in lower systolic and diastolic blood pressures and lower heart rates than those measured in the control room. Viewing the built landscape also had the general effect of lowering blood pressures and heart rates, but the effect was less consistent and the magnitude was smaller than that caused by the natural landscape. Lowering of blood pressure and heart rate have both been shown to be positively correlated with increased health and well-being, indicating the benefit of sim.
Iodine deficiency in pregnancy and in women of reproductive age in Erzurum, Turkey

Aim: Iodine deficiency (ID) is an important public health problem and the most common cause of preventable mental retardation. The aims of this study were to determine the urinary iodine concentration (UIC) of pregnant women living in Erzurum, to assess the ID rate, and to find out whether iodine supplementation is necessary in pregnancy. Materials and methods: Spot urine was obtained from pregnant and nonpregnant women with no functional or organic thyroid disease. The UIC was studied using the Sandell-Kolthoff method. Results: The median UIC values of pregnant women in the first, second, and third trimesters and of the nonpregnant women were 126.0, 134.6, 132.7, and 137.3 µg/L, respectively. The total ID rate was 72.6% and 18.0% in the pregnant and the nonpregnant women, respectively. Conclusion: The ID rate in pregnancy was found to be high in Erzurum. ID rates were highest in the first trimester, when fetal neurodevelopment is most affected. ID is still a serious problem in Erzurum despite mandatory salt iodization. However, the fact that the deficiency is mild to moderate is promising as regards the potential response to iodine supplementation in pregnant women.
Ju l 2 01 3 Analysis of the radiative Λ b → Λ γ transition in SM and scenarios with one or two universal extra dimensions

We investigate the radiative process of the Λb → Λγ in the standard model as well as models with one or two compact universal extra dimensions. Using the form factors entered to the low energy matrix elements, calculated via light cone QCD in full theory, we calculate the total decay width and branching ratio of this decay channel. We compare the results of the extra dimensional models with those of the standard model on the considered physical quantities and look for the deviations of the results from the standard model predictions at different values of the compactification scale (1/R). PACS number(s): 12.60. -i, 13.30. -a, 13.30. Ce, 14.20. Mr e-mail: kazizi@dogus.edu. tr e-mail: sehban@istanbul.edu. tr e-mail: a.t. olgun@gmail.com e-mail: z.tavukoglu@gmail.com
Effect of Aloe Vera (Aloe barbadensis) and Clove (Syzigium aromaticum) Supplementation on Immune Status, Haematological and Serum Biochemical Parameters in Japanese Quails

A study was conducted on 120 Japanese quails to study the effect of Aloe vera and clove on serum biochemical, haematological and immunological parameters. The experiment lasted for 35 days in which Japanese quails were randomly divided into four treatment groups, each group having three replications consisting of ten birds each. All the birds (starter and finisher) were fed according to requirements. The birds in control group (T1) were given no supplement whereas in treatments T2, T3 and T4, birds were supplemented with Aloe vera leaf powder, clove and mixture of both (powdered form) at 0.5, 0.5 and 0.25+0.25% of feed, respectively. Haemoglobin concentration, packed cell volume, total erythrocyte count and total leucocyte count, serum protein, albumin, globulin, albumin-globulin ratio, glucose, triglycerides were not affected by Aloe vera and clove supplementation. Immune response as revealed by delayed type of hypersensitivity (measurement of skin thickness) and serum immunoglobulin were improved in all the three supplemented groups. It could be concluded that Aloe vera and clove supplementation through feed improved immune status of Japanese quails without affecting haematological and serum biochemical parameters.
ToyArchitecture: Unsupervised Learning of Interpretable Models of the World

Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are usually uncomputable, incompatible with theories of biological intelligence, or lack practical implementations. The goal of this work is to combine the main advantages of the two: to follow a big picture view, while providing a particular theory and its implementation. In contrast with purely theoretical approaches, the resulting architecture should be usable in realistic settings, but also form the core of a framework containing all the basic mechanisms, into which it should be easier to integrate additional required functionality. In this paper, we present a novel, purposely simple, and interpretable hierarchical architecture which combines multiple different mechanisms into one system: unsupervised learning of a model of the world, learning the influence of one's own actions on the world, model-based reinforcement learning, hierarchical planning and plan execution, and symbolic/sub-symbolic integration in general. The learned model is stored in the form of hierarchical representations with the following properties: 1) they are increasingly more abstract, but can retain details when needed, and 2) they are easy to manipulate in their local and symbolic-like form, thus also allowing one to observe the learning process at each level of abstraction. On all levels of the system, the representation of the data can be interpreted in both a symbolic and a sub-symbolic manner. This enables the architecture to learn efficiently using sub-symbolic methods and to employ symbolic inference.
Nonparametric identification of hidden Markov models

Nonparametric identification of finite-state hidden Markov models (HMMs) is investigated. We obtain identification of the parameters as well as the order of the Markov chain in the class of HMMs which have full-rank, ergodic transition probability matrices and for which the state-dependent distributions are all distinct. We also show how our result implies that the asymptotic contrast for ML-estimation, the Kullback-Leibler distance of the HMM, identifies the true parameter vector uniquely, thus paving the way for nonparametric maximum likelihood estimation in HMMs.
Bayesian forecasting of electoral outcomes with new parties' competition

This paper proposed a methodology to forecast electoral outcomes using the result of the combination of a fundamental model and a model-based aggregation of polls. We propose a Bayesian hierarchical structure for the fundamental model that synthesises data at the provincial, regional and national level. We use a Bayesian strategy to combine the fundamental model with the information coming for recent polls. This model can naturally be updated every time new information, for instance a new poll, becomes available. This methodology is well suited to deal with increasingly frequent situations in which new political parties enter an electoral competition, although our approach is general enough to accommodate any other electoral situation. We illustrate the advantages of our method using the 2015 Spanish Congressional Election in which two new parties ended up receiving 30\% of the votes. We compare the predictive performance of our model versus alternative models. In general the predictions of our model outperform the alternative specifications, including hybrid models that combine fundamental and polls models. Our predictions are, in relative terms, particularly accurate in predicting the seats obtained by each political party.
Robust Factor Models with Explanatory Proxies

We provide an econometric analysis for the factor models when the latent factors can be explained partially by several observed explanatory proxies. In financial factor models for instance, the unknown factors can be reasonably well predicted by a few observable proxies, such as the Fama-French factors. In diffusion index forecasts, identified factors are strongly related to several directly measurable economic variables such as consumption-wealth variable, financial ratios, and term spread. To incorporate the explanatory power of these observed characteristics, we propose a new two-step estimation procedure: (i) regress the data onto the observables, and (ii) take the principal components of the fitted data to estimate the loadings and factors. The proposed estimator is robust to possibly heavy-tailed distributions, which are encountered by many macroeconomic and financial time series. With those proxies, the factors can be estimated accurately even if the cross-sectional dimension is mild. Empirically, we apply the model to forecast US bond risk premia, and find that the observed macroeconomic characteristics contain strong explanatory powers of the factors. The gain of forecast is more substantial when these characteristics are incorporated to estimate the common factors than directly used for forecasts. JEL Classification: C38, C53, C58
Proxy Discrimination∗ in Data-Driven Systems Theory and Experiments with Machine Learnt Programs

Machine learnt systems inherit biases against protected classes, historically disparaged groups, from training data. Usually, these biases are not explicit, they rely on subtle correlations discovered by training algorithms, and are therefore difficult to detect. We formalize a notion of proxy discrimination in data-driven systems, a class of properties indicative of bias, as the presence of protected class correlates that have causal influence on the system’s output. We evaluate an implementation on a corpus of social datasets, demonstrating how to validate systems against these properties and to repair violations where they occur.
Global smoothness for the Euler-Weil-Petersson equation

Abstract. In this paper we prove that all initially-smooth solutions of the Euler-Weil-Petersson equation, which describes geodesics on the universal Teichmüller space under the Weil-Petersson metric, will remain smooth for all time. This extends the work of Escher-Kolev for strong Riemannian metrics to the borderline case of H metrics. In addition we show that all initially-smooth solutions of the Wunsch equation, which describes geodesics on the universal Teichmüller curve under the Velling-Kirillov metric, must blow up in finite time due to wave breaking, extending work of Castro-Córdoba and Bauer-Kolev-Preston. Finally we illustrate these phenomena in terms of conformal maps of the unit disc, using the conformal welding representation of circle diffeomorphisms which is natural in Teichmüller theory.
0 A pr 2 00 9 Constraints on charged Higgs bosons from D ± s → μ ± ν and D ± s → τ ± ν

The decays D s → μνμ and D s → τντ have traditionally been used to measure the D s meson decay constant fDs . Recent measurements at CLEO-c and the B factories suggest a branching ratio for both decays somewhat higher than the Standard Model prediction using fDs from unquenched lattice calculations. The charged Higgs boson (H) in the Two Higgs Doublet Model (Type II) would also mediate these decays, but any sizeable contribution from H can only suppress the branching ratios and consequently is now slightly disfavoured. It is shown that constraints on the parameters tan β and mH± from such decays can be competitive with and complementary to analogous constraints derived from the leptonic meson decays B → τντ and K → μνμ, especially if lattice calculations eventually prefer fDs < 250 MeV.
SAW interdigitated transducers as topological mechanical metamaterial

A lattice model is developed to describe the mechanical displacement of and current through each electrode of a surface acoustic wave (SAW) interdigitated tranducer (IDT). Each electrode of an IDT is treated as a mass connected mechanically to its neighbors with a spring and electrically with a capacitor. Simulations for the electrical admittance of a typical SAW IDT are performed and compared with the results of an accurate finite element method simulation. The utility of this lattice model is demonstrated by simulating the admittance of an IDT structure known as a hiccup resonator, which has a mode in the center of the band gap. It is shown here that this mode is a topologically protected edge state described by the 1D Su-Schrieffer-Heeger (SSH) model. Hiccup resonators have been used in commercial products for decades, and as such it may considered the first mass-produced topological mechanical metamaterial.
Fine-Grained Visual Recognition with Batch Confusion Norm

We introduce a regularization concept based on the proposed Batch Confusion Norm (BCN) to address Fine-Grained Visual Classification (FGVC). The FGVC problem is notably characterized by its two intriguing properties, significant inter-class similarity and intra-class variations, which cause learning an effective FGVC classifier a challenging task. Inspired by the use of pairwise confusion energy as a regularization mechanism, we develop the BCN technique to improve the FGVC learning by imposing class prediction confusion on each training batch, and consequently alleviate the possible overfitting due to exploring image feature of fine details. In addition, our method is implemented with an attention gated CNN model, boosted by the incorporation of Atrous Spatial Pyramid Pooling (ASPP) to extract discriminative features and proper attentions. To demonstrate the usefulness of our method, we report state-of-the-art results on several benchmark FGVC datasets, along with comprehensive ablation comparisons.
FAB: A Robust Facial Landmark Detection Framework for Motion-Blurred Videos

Recently, facial landmark detection algorithms have achieved remarkable performance on static images. However, these algorithms are neither accurate nor stable in motion-blurred videos. The missing of structure information makes it difficult for state-of-the-art facial landmark detection algorithms to yield good results. In this paper, we propose a framework named FAB that takes advantage of structure consistency in the temporal dimension for facial landmark detection in motion-blurred videos. A structure predictor is proposed to predict the missing face structural information temporally, which serves as a geometry prior. This allows our framework to work as a virtuous circle. On one hand, the geometry prior helps our structure-aware deblurring network generates high quality deblurred images which lead to better landmark detection results. On the other hand, better landmark detection results help structure predictor generate better geometry prior for the next frame. Moreover, it is a flexible video-based framework that can incorporate any static image-based methods to provide a performance boost on video datasets. Extensive experiments on Blurred-300VW, the proposed Real-world Motion Blur (RWMB) datasets and 300VW demonstrate the superior performance to the state-of-the-art methods. Datasets and model will be publicly available at \href{https://github.com/KeqiangSun/FAB}{https://github.com/KeqiangSun/FAB}.