Miracle-dz/UniFAR-FTUs huggingface dataset:
Narrative review of the role of gastroenterologist in the diagnosis, treatment and palliation in gastric and gastroesophageal cancer

Esophageal cancer (EC) and gastric cancer (GC) carry a high mortality rate. Unfortunately, a majority of patients are asymptomatic and at the time of diagnosis, the disease may invariably be in its advanced stages with limited curative options. Thus, it is imperative to recognize certain risk factors including gastroesophageal reflux disease (GERD), male gender, pre-existing Barrett’s esophagus, smoking history, obesity, Helicobacter pylori infection, atrophic gastritis among others for both EC and GC, intervene on time with screening and surveillance modalities if indicated and optimize treatment plans. With advances in endoscopic techniques, early neoplastic lesions are increasingly managed by gastroenterologists, offering an alternative to surgery. The gold standard for diagnosis of EC and GC is high definition endoscopy with adequate targeted biopsies. Endoscopic ultrasound (EUS) is a key in the staging of early cancers dictating the pathway for treatment options. We also play a key role in palliation cases with the aim to reduce the symptoms like nausea, vomiting and even when possible, restore oral intake and improve nutrition in both advanced GC and EC. This review article discusses the risk factors, diagnostic and endoscopic treatment modalities of early EC and GC and palliation of advanced cancer where gastroenterologists play a key role.
WHO EMRO | Evaluation of smoking status: comparison of self-reports with exhaled carbon monoxide analysis in university students in the Islamic Republic of Iran

Background: Smoking is considered the leading risk factor for many chronic diseases and deaths worldwide. Thus, it is important to determine the number of smokers before implementing tobacco control initiatives. Due to stigma and deterrent measures, it is impossible to access smokers through a self-report questionnaire. Aims: To compare exhaled carbon monoxide (CO) levels with self-reports among university students in the Islamic Republic of Iran. Methods: This cross-sectional study included a convenience sample of 60 university students recruited in 2016 in Tehran. There were 30 women and 30 men with an average age of 23.1 (15.6) years. They were interviewed using an adaptation of the International Union Against Tuberculosis and Lung Diseases questionnaire and further assessed by breath analysis. Smoking status was compared and then correlated with the resultant CO levels at a cutoff of 6 ppm.
Topology Proceedings 51 (2018) pp. 143-168: General properties of the hyperspace of convergent sequences

Given a Hausdorff space X, the symbol Sc(X) denotes the topological space which results of endowing the set of all infinite convergent sequences in X with the Vietoris topology. This hyperspace was introduced in [5]. In this paper we present answers to some questions posed in that article, namely, we show that if X is either metrizable or second countable, then X is pathwise connected as long as Sc(X) is so, and we exhibit a dendroidX for which Sc(X) is not pathwise connected. Continuing with negative examples, we present a normal (resp. Fréchet-Urysohn) space whose hyperspace of converging sequences is not normal (resp. Fréchet-Urysohn). By proving that the hypothesis X is connected implies that Sc(X) is connected we generalize one of the results from the article mentioned above. Moreover, it is proved here that the reverse implication holds whenever Sc(X) 6= ∅ and similiar results are obtained when we replace connected with locally connected. A section is included where the weight, the character and the density of Sc(X) are compared with the corresponding cardinal functions of X. Then we turn our attention to the study of the topological dimension of the hyperspace of convergent sequences of compact metrizable spaces. Finally, we characterize the continuous functions from Sc(X) to Sc(Y ) which are inducible. 2010 Mathematics Subject Classification. Primary 54A20, 54B; Secondary 54A25, 54C10, 54D05.
Understanding and predicting large-scale hydrological variability in a changing environment

Abstract. In a context of climate, environmental, ecological and socio-economical changes, understanding and predicting the response of hydrological systems on regional to global spatial scales, and on infra-seasonal to multidecadal time-scales, are major topics that must be considered to tackle the challenge of water resource management sustainability. In this context, a number of strongly-linked key issues need to be addressed by the scientific community, including: (i) identifying climate drivers of hydrological variations, (ii) understanding the multi-frequency characteristics of hydroclimate variability, including evolution of extremes (meteorological/hydrological event scale to long-term natural/internal climate- or anthropogenic-driven variations and trends), (iii) assessing the influence of local- to regional-scale basin properties on hydrological system response to climate variability and change, (iv) identifying the evolving contribution of anthropogenic water use in observed hydrological variations. Based on pan-European collaborations, activities of the EURO-FRIEND “Large-scale variations in hydrological characteristics” group aim at generating new findings to improve our understanding of hydrological systems behavior sensu lato (i.e. surface and sub-surface) on large spatial and temporal scales (i.e continental – multidecadal). Through selected examples, this contribution emphasizes recent research developments in characterizing and modeling of climate-hydrology linkages at different temporal and spatial scales, as well as recent insights on climate-hydrology scaling characteristics (i.e. long-term persistence, dependance of processes, of hydrological behaviors, of large-scale climate/hydrology linkages on time-/spatial scales), long-term hydrometeorological reconstructions, and large-scale hydrological model refinement taking into account spatial heterogeneity of watershed physical characteristics.
The Shape of a Gerbil Isocline Measured Using Principles of Optimal Habitat Selection

The isoclines of Gerbillus allenbyi competing with G. pyramidum are negatively sloped and at least approximately parallel. They are not linear, however; they are steeper over both low and high G. pyramidum densities and only very slightly negative at intermediate densities. This nonlinearity agrees with the predictions of the theory of optimal density—dependent habitat selection in a two—species, shared—preference system, the system that obtains here. The isocline field was measured by a new method based on the single—species habitat selection theory of Fretwell. The species whose isoclines are being measured (the target species) is given a chance to equilibrate its per capita reproductive rate across a fence that separates two densities of its competitors. Equilibration requires that the target species distribute its density unequally on the two side of the fence. The general features of the method may be useful in other animal studies where densities can be experimentally manipulated.
Effect of phase feeding on performance and economy of production of heavy broiler chickens

A high –low – high phase feeding was used to determine the performance and economy of producing heavy broilers (Roasters of 12 weeks of age). One hundred and twenty (120) finisher broiler chickens were selected after brooding and allotted to four experimental units. The feeding trial comprised; a starter phase (0-4 weeks), a grower phase (4-8 weeks) and a finisher phase (8-12 weeks) on broiler finisher rations of varying crude protein levels which represented the treatments. The treatments include; T1 (Control) no restriction – commercial finisher ration 4-12 weeks after brooding. T2 (Four weeks restriction after brooding and 18%crude protein dietre-feeding 8-12 weeks). T3 (Four weeks restriction after brooding and 19% crude protein dietre-feeding (8-12) weeks. T4(Four weeks restriction after brooding and 20% crude protein diet re-feeding 8-12 weeks). Each treatment was replicated three times in a completely randomized design. T2 on 18% CP re-feeding had significant (p 0.05) from the control. Feed intake was significantly (p<0.05) higher for all the restricted groups than the control. Mortality was zero percent for the nutrient restricted groups and 4% for the control. Cost of feed per kilogram weight gain was about 25% higher for the control than the nutrient restricted groups. Extending the growing period of the broiler using a high-low-high phasing of nutrient intake resulted in the production of heavy broilers (roasters) that achieved identical body weight with the control at twelve weeks of age, with lower cost of feed per kilogram gain than the control. Key words: Heavy broilers, Roasters, Phasing of nutrient intake, Body weight.
Seasonal Distribution of PCDDs/PCDFs in the Small urban Reservoirs

Man-made reservoirs constructed on running waters, where a decrease in flow velocity and an increase in flocculent settling occurs, create perfect conditions for the deposition of allohtonic matter and adsorbed pollutants, such as toxic polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). The results obtained from the research on a cascade of five small reservoirs located along an urban river (Lodz, Poland) showed significantly lower concentrations of PCDDs/PCDFs in the spring season in the first three reservoirs; whereas the other two demonstrated an opposite tendency with the lower values observed during the autumn. Also, analysis of the seasonal variations of the TEQ concentrations showed lower values in the reservoirs located at the beginning of the cascade (I, II and III) in spring, while in the lower ponds (IV and V) lesser values were observed during autumn. The winter and spring snow and ice melting, and the accelerated run-off washing out organic and mineral matter with the associated micropollutants accumulated during this period, were recognized as the main reasons for such seasonal distribution of PCDDs/ PCDFs. Intensive rains occurring during the autumn, especially after dry summers, may be in turn responsible for the raised total PCDDs/PCDFs and TEQ concentrations during the autumn sampling period. Furthermore, the discharges of polluted stormwater and illegal domestic sewage through the stormwater outlets located along the river boosted the reservoirs sediments in the PCDDs/PCDFs.
EFFECTS OF MOTHERâ€™S LITERACY ON CHILD HEALTH ASSESSED BY PERSONAL HYGIENE, NUTRITIONAL AND VACCINATION STATUS

Background: In Pakistan, literacy means â€˜the ability to read and writeâ€™. Motherâ€™s education is a stronger determinant of child survivorship. This study was carried out in order to determine the impact of motherâ€™s literacy on child health in terms of personal hygiene of child, nutritional status and vaccination status, and to compare the child health status of literate and non-literate mothers. Methods: It was a cross-sectional study carried out in Paediatric Unit, Ayub Teaching Hospital, Abbottabad, from Dec 2015 to Aug 2016. Data was collected using non probability sampling and analysed on SPSS-21. Frequencies and percentages were calculated for categorical variables like gender, residence, education, immunization and hygiene status, and MeanÂ±SD were calculated for quantitative variables like age. Results: Among total 160 children, mothers of 48 (30%) children were completely uneducated. Nutrition status showed that 89 (55.6%) were of normal height for age while rest of them were having stunting of mild to severe categories. Immunization of 135 (84.4%) of the children was done as per their age. Regarding hygiene, clothing of 129 (80.6%) was clean, nails of 95 (59.4%) children were properly clean and trimmed, while hair hygiene of 119 (74.4%) children and dental hygiene of 109 (68.12%) children was well maintained. Majority of those whose immunization, nutrition, and hygiene status was maintained had educated mothers. Conclusion: Maternal literacy has a direct effect on the overall child health with respect to personal hygiene, nutritional and vaccination status. Pak J Physiol 2017;13(1):22â€“5
High-Dimensional Model-Assisted Inference for Local Average Treatment Effects With Instrumental Variables

Abstract Consider the problem of estimating the local average treatment effect with an instrument variable, where the instrument unconfoundedness holds after adjusting for a set of measured covariates. Several unknown functions of the covariates need to be estimated through regression models, such as instrument propensity score and treatment and outcome regression models. We develop a computationally tractable method in high-dimensional settings where the numbers of regression terms are close to or larger than the sample size. Our method exploits regularized calibrated estimation for estimating coefficients in these regression models, and then employs a doubly robust point estimator for the treatment parameter. We provide rigorous theoretical analysis to show that the resulting Wald confidence intervals are valid for the treatment parameter under suitable sparsity conditions if the instrument propensity score model is correctly specified, but the treatment and outcome regression models may be misspecified. In this sense, our confidence intervals are instrument propensity score model based, and treatment and outcome regression models assisted. For existing high-dimensional methods, valid confidence intervals are obtained for the treatment parameter if all three models are correctly specified. We evaluate the proposed method via extensive simulation studies and an empirical application to estimate the returns to education. The methods are implemented in the R package RCAL.
Learning Realistic Patterns from Unrealistic Stimuli: Generalization and Data Anonymization

Good training data is a prerequisite to develop useful ML applications. However, in many domains existing data sets cannot be shared due to privacy regulations (e.g., from medical studies). This work investigates a simple yet unconventional approach for anonymized data synthesis to enable third parties to benefit from such private data. We explore the feasibility of learning implicitly from unrealistic, task-relevant stimuli, which are synthesized by exciting the neurons of a trained deep neural network (DNN). As such, neuronal excitation serves as a pseudo-generative model. The stimuli data is used to train new classification models. Furthermore, we extend this framework to inhibit representations that are associated with specific individuals. We use sleep monitoring data from both an open and a large closed clinical study and evaluate whether (1) end-users can create and successfully use customized classification models for sleep apnea detection, and (2) the identity of participants in the study is protected. Extensive comparative empirical investigation shows that different algorithms trained on the stimuli are able generalize successfully on the same task as the original model. However, architectural and algorithmic similarity between new and original models play an important role in performance. For similar architectures, the performance is close to that of using the true data (e.g., Accuracy difference of 0.56\%, Kappa coefficient difference of 0.03-0.04). Further experiments show that the stimuli can to a large extent successfully anonymize participants of the clinical studies.
Adversarial Consistent Learning on Partial Domain Adaptation of PlantCLEF 2020 Challenge

Domain adaptation is one of the most crucial techniques to mitigate the domain shift problem, which exists when transferring knowledge from an abundant labeled sourced domain to a target domain with few or no labels. Partial domain adaptation addresses the scenario when target categories are only a subset of source categories. In this paper, to enable the efficient representation of cross-domain plant images, we first extract deep features from pre-trained models and then develop adversarial consistent learning ($ACL$) in a unified deep architecture for partial domain adaptation. It consists of source domain classification loss, adversarial learning loss, and feature consistency loss. Adversarial learning loss can maintain domain-invariant features between the source and target domains. Moreover, feature consistency loss can preserve the fine-grained feature transition between two domains. We also find the shared categories of two domains via down-weighting the irrelevant categories in the source domain. Experimental results demonstrate that training features from NASNetLarge model with proposed $ACL$ architecture yields promising results on the PlantCLEF 2020 Challenge.
Detecting the Figure Rotation of Dark Matter Halos with Tidal Streams

The dark matter halos that surround Milky Way–like galaxies in cosmological simulations are, to first order, triaxial. Nearly 30 yr ago it was predicted that such triaxial dark matter halos should exhibit steady figure rotation or tumbling motions for durations of several gigayears. The angular frequency of figure rotation predicted by cosmological simulations is described by a log-normal distribution of pattern speed Ω p with a median value 0.15 h km s−1 kpc−1 (∼0.15 h rad Gyr−1 ∼ 9° h Gyr−1) and a width of 0.83h km s−1 kpc−1. These pattern speeds are so small that they have generally been considered both unimportant and undetectable. In this work we show that even extremely slow figure rotation can significantly alter the structure of extended stellar streams produced by the tidal disruption of satellites in the Milky Way halo. We simulate the behavior of a Sagittarius-like polar tidal stream in triaxial dark matter halos with different shapes, when the halos are rotated about the three principal axes. For pattern speeds typical of cosmological halos, we demonstrate, for the first time, that a Sagittarius-like tidal stream would be altered to a degree that is detectable even with current observations. This discovery will potentially allow for a future measurement of figure rotation of the Milky Way’s dark matter halo, perhaps enabling the first evidence of this relatively unexplored prediction of cold dark matter.
SOCIAL BEHAVIOR OF THE TUATARA, SPHENODON PUNCTATUS

The social behavior of tuatara, Sphenodon punctatus, was studied in a natural population on Stephens Island, New Zealand, from January to March, 1987-1989. Study sites were located in both wooded (bush) and open (paddock) habitats. Nocturnal observations were enhanced by using night-vision equipment and elevated viewing platforms. Individuals were identified by idiosyncratic differences in crest morphology. At the peak of courtship activity (late January to the end of February), the behaviors of territorial males were observed and their responses to visual stimuli were tested in the field. Visual stimuli were found to be of significance. A radio-controlled, life-sized tuatara model revealed the importance of nuchal and dorsal crests and female head- nodding in the initiation of male courtship and mating behaviors and territorial defense.
Will it Unblend?

Natural language processing systems often struggle with out-of-vocabulary (OOV) terms, which do not appear in training data. Blends, such as “innoventor”, are one particularly challenging class of OOV, as they are formed by fusing together two or more bases that relate to the intended meaning in unpredictable manners and degrees. In this work, we run experiments on a novel dataset of English OOV blends to quantify the difficulty of interpreting the meanings of blends by large-scale contextual language models such as BERT. We first show that BERT’s processing of these blends does not fully access the component meanings, leaving their contextual representations semantically impoverished. We find this is mostly due to the loss of characters resulting from blend formation. Then, we assess how easily different models can recognize the structure and recover the origin of blends, and find that context-aware embedding systems outperform character-level and context-free embeddings, although their results are still far from satisfactory.
Casimir and Casimir-Polder Forces in Graphene Systems: Quantum Field Theoretical Description and Thermodynamics

We review recent results on the low-temperature behaviors of the Casimir-Polder and Casimir free energy an entropy for a polarizable atom interacting with a graphene sheet and for two graphene sheets, respectively. These results are discussed in the wide context of problems arising in the Lifshitz theory of van der Waals and Casimir forces when it is applied to metallic and dielectric bodies. After a brief treatment of different approaches to theoretical description of the electromagnetic response of graphene, we concentrate on the derivation of response function in the framework of thermal quantum field theory in the Matsubara formulation using the polarization tensor in (2 + 1)-dimensional space—time. The asymptotic expressions for the Casimir-Polder and Casimir free energy and entropy at low temperature, obtained with the polarization tensor, are presented for a pristine graphene as well as for graphene sheets possessing some nonzero energy gap Δ and chemical potential μ under different relationships between the values of Δ and μ. Along with reviewing the results obtained in the literature, we present some new findings concerning the case μ≠0, Δ=0. The conclusion is made that the Lifshitz theory of the Casimir and Casimir-Polder forces in graphene systems using the quantum field theoretical description of a pristine graphene, as well as real graphene sheets with Δ>2μ or Δ<2μ, is consistent with the requirements of thermodynamics. The case of graphene with Δ=2μ≠0 leads to an entropic anomaly, but is argued to be physically unrealistic. The way to a resolution of thermodynamic problems in the Lifshitz theory based on the results obtained for graphene is discussed.
A Review of Visual Odometry Methods and Its Applications for Autonomous Driving

The research into autonomous driving applications has observed an increase in computer vision-based approaches in recent years. In attempts to develop exclusive vision-based systems, visual odometry is often considered as a key element to achieve motion estimation and self-localisation, in place of wheel odometry or inertial measurements. This paper presents a recent review to methods that are pertinent to visual odometry with an emphasis on autonomous driving. This review covers visual odometry in their monocular, stereoscopic and visual-inertial form, individually presenting them with analyses related to their applications. Discussions are drawn to outline the problems faced in the current state of research, and to summarise the works reviewed. This paper concludes with future work suggestions to aid prospective developments in visual odometry.