Miracle-dz/UniFAR-FTUs huggingface dataset:
CMU-Informedia at TREC 2019 Incident Streams Track

We describe CMU-Informedia’s models for the TREC 2019 Incident Streams track. The goal of this track is classifying event/incident related tweets by High-level Information Types such as ‘SearchAndRescue’, ‘InformationWanted’ and so on. Each tweet should be assigned as many categories as are appropriate. What’s more, this track requires predicting the Importance Scores, which is converted from the Importance Labels including ‘Critical’, ‘High’, ‘Medium’, ‘Low’ and ‘Ir-relevant’. For predicting the information types, we use feature extractors to extract features including meta-information, user entity, and textual embed-dings, and then we build an information type predictor on those features. For predicting the importance scores, we build an importance score predictor which combines the scores derived from the predicted information types and the scores produced by a regression model. Evaluation results show that our models perform well on all metrics, and different models perform particularly well on different aspects.
Hybrid Method for Detection of Brain Tumor Using Fuzzy C-Mean Clustering and Discrete Curve let Transform

In this paper, a straightforward algorithm for detecting the array and form of tumor in mind MRI Images is explain. Algorithm in preprocessing phase wiener filter since The purpose of all this is to reduce the amount of noise and the like in the image as compared to the estimate of the image without noise and using in second stage (feature extraction) three steps :the first step is Curve let Transform going to pass on original image. The purpose of it can provide sparse expression for both edge portions and smooth portions on the image simultaneously then apply second step is Fuzzy C-Mean Cluster on original image. In which the data point here can be assigned to each cluster center because of this point that may belong to more _than one cluster center, and this is the opposite of k-mean where the data point should belong only_ to the cluster_ center, and here one is assigned to the membership information point for every cluster center The data point will fit in to more than one cluster center. Finally step apply fuzzed wave let for two output image of Fuzzy C-Mean Cluster and Curve let Transform. Finally fused by inverse wavelet for merge two methods to detection the tumor in brain
Logistic Regression is Still Alive and Effective: The 3 rd YouTube 8M Challenge Solution of the IVUL-KAUST team

In this report, we present our solution for the 3 rd YouTube-8M Video Understanding Challenge for a task of temporal localization of topics within a video. Our team achieves the 9 th place in the Public Leaderboard and the 11 th place in the Private Leaderboard with a difference of 4 . 5 × 10 − 4 from the 10 th gold medal winner. Overall, we train 20 different models independently and use their ensemble to predict segment scores. Along with a video clas-siﬁer, we generate ﬁnal scores for each segment. We use one-loss or two-loss training strategies for different models to make full use of video-level annotations and segment-level annotations. Furthermore, we adopt a teacher-student model and deep clustering to generate pseudo-labels to increase the amount of fully-annotated data.
Does it Pay to Know More in Games of Incomplete Information?

The paper investigates experimentally the effect of information about the payoff matrix on the players’ welfare attainments in repeated 2x2 games of incomplete information. Controlling for both the amount of information available to the players and the behavioral model of the opponent allows for distinct treatments of performance of informed and uninformed subjects. The main findings are as follows: (a) the informed player need not benefit from his informational advantage while the uninformed player need not be worse off; (b) asymmetric information can be used as an equilibrium selection device in games with a multiple of such; (c) asymmetric scenarios do not improve much in terms of welfare over the symmetric incomplete information baseline; (d) uninformed subjects can easily be exploited by a purposeful opponent; and in general, (e) subjects tend to perform worse than simplistic benchmark strategies.
A Novel Bayesian Filter for RSS-Based Device-Free Localization and Tracking

Received signal strength based device-free localization applications utilize a model that relates the measurements to position of the wireless sensors and person, and the underlying inverse problem is solved either using an imaging method or a nonlinear Bayesian filter. In this paper, it is shown that the Bayesian filters nearly reach the posterior Cramér-Rao bound and they are superior with respect to imaging approaches in terms of localization accuracy because the measurements are directly related to position of the person. However, Bayesian filters are known to suffer from divergence issues and in this paper, the problem is addressed by introducing a novel Bayesian filter. The developed filter augments the measurement model of a Bayesian filter with position estimates from an imaging approach. This bounds the filter's measurement residuals by the position errors of the imaging approach and as an outcome, the developed filter has robustness of an imaging method and tracking accuracy of a Bayesian filter. The filter is demonstrated to achieve a localization error of <inline-formula><tex-math notation="LaTeX">$0.11 \text{ m}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>0</mml:mn><mml:mo>. </mml:mo><mml:mn>11</mml:mn><mml:mspace width="4.pt"/><mml:mtext>m</mml:mtext></mml:mrow></mml:math><inline-graphic xlink:href="kaltiokallio-ieq1-2953474.gif"/></alternatives></inline-formula> in a <inline-formula><tex-math notation="LaTeX">$75 \; \text{m}^2$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>75</mml:mn><mml:mspace width="0.277778em"/><mml:msup><mml:mtext>m</mml:mtext><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:math><inline-graphic xlink:href="kaltiokallio-ieq2-2953474.gif"/></alternatives></inline-formula> open indoor deployment and an error of <inline-formula><tex-math notation="LaTeX">$0.29 \text{ m}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>0</mml:mn><mml:mo>. </mml:mo><mml:mn>29</mml:mn><mml:mspace width="4.pt"/><mml:mtext>m</mml:mtext></mml:mrow></mml:math><inline-graphic xlink:href="kaltiokallio-ieq3-2953474.gif"/></alternatives></inline-formula> in a <inline-formula><tex-math notation="LaTeX">$82 \; \text{m}^2$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>82</mml:mn><mml:mspace width="0.277778em"/><mml:msup><mml:mtext>m</mml:mtext><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:math><inline-graphic xlink:href="kaltiokallio-ieq4-2953474.gif"/></alternatives></inline-formula> apartment experiment, decreasing the localization error by 30-48 percent with respect to a state-of-the-art imaging method.
The nodular adrenal.

Nodules commonly occur in the human adrenal gland. They are best regarded as part of the ageing process, produced in response to adrenal vascular changes. Nodules exhibit a wide diversity of size and distribution and are seen not only in subjects with normal adrenal function but also in patients with hypercorticalism (Cushing's and Conn's syndromes). In these disorders, the nodules appear to be a consequence of the diseases, rather than being aetiological.
REVIEW: The Role of Vitamin D and Calcium in Type 2 Diabetes. A Systematic Review and Meta-Analysis

Context: Altered vitamin D and calcium homeostasis may play a role in the development of type 2 diabetes mellitus (type 2 DM). Evidence Acquisition and Analyses: MEDLINE review was con- ducted through January 2007 for observational studies and clinical trials in adults with outcomes related to glucose homeostasis. When data were available to combine, meta-analyses were performed, and summary odds ratios (OR) are presented. Evidence Synthesis: Observational studies show a relatively con- sistent association between low vitamin D status, calcium or dairy intake, and prevalent type 2 DM or metabolic syndrome [OR (95% confidence interval): type 2 DM prevalence, 0.36 (0.16–0.80) among nonblacks for highest vs . lowest 25-hydroxyvitamin D; metabolic syn- drome prevalence, 0.71 (0.57–0.89) for highest vs . lowest dairy in-take]. There are also inverse associations with incident type 2 DM or metabolic syndrome [OR (95% confidence interval): type 2 DM inci- dence, 0.82 (0.72–0.93) for highest vs . lowest combined vitamin D and calcium intake; 0.86 (0.79–0.93) for highest vs . lowest dairy intake]. Evidence from trials with vitamin D and/or calcium supplementation suggests that combined vitamin D and calcium supplementation may have a role in the prevention of type 2 DM only in populations at high risk ( i . e . glucose intolerance). The available evidence is limited be- cause most observational studies are cross-sectional and did not adjust for important confounders, whereas intervention studies were short in duration, included few subjects, used a variety of formulations of vitamin D and calcium, or did post hoc analyses. Conclusions : Vitamin D and calcium insufficiency may negatively influence glycemia, whereas combined supplementation with both nutrientsmaybebeneficialinoptimizingglucosemetabolism. ( JClin Endocrinol Metab 92: 2017–2029, 2007) drome , insulin resistance , homa , homeostasis model assessment , (cid:1) -cell function , insulin secretion , vitamin D , calcium , dairy , milk been reported in cross-sectional studies (18–23, 39, 40). Some (19, 40), but not all (23), observational studies have shown an inverse association between vitamin D or calcium status and insulin resistance. Results from randomized trials on the effect of vitamin D and/or calcium supplementation on insulin resistance show either no effect (23, 41–45) or improvement (46–48) of insulin action with supplementation.
Dynamically Evolving, Large-scale

Sensor nets have many undisputed ﬁelds of application. A paradigm of communication is the use of one control channel in the MAC layer. We challenge this paradigm for nodes with very restricted hardware resources. In our model nodes support the use of different channels and use clock synchronisation. We present a simple probabilistic synchronised channel utilisation scheme for wireless communication. The main features are its simplicity, robustness against radio interference, the high throughput caused by less interfering signals, and predictable energy consumption. For this, the channel selection is based on a carefully chosen probability distribution maximising the expected number of successfully delivered packets up to a constant factor. Combined with a standard synchronisation scheme it provides a novel energy-efﬁcient, robust, and fast message delivery service for sensor networks where data gathering is not available due to memory restrictions.
THERMO – HYDROMECHANICAL COMPRESSION OF FAST GROWING POPLAR FROM SHORT TERM PLANTATION

Moisture and Temperature do have a considerate impact on wood properties. High temperatures and moisture content soften the wooden structure and allow to compress and to form wood without harming the inner structure. During compression, the structure stores deformation that later can be regained. The elasticity is enhanced proportional to the amount of compression. In wood machining, the material is no longer considered to be a solid body, but a cellular solid. This is will change the prospect on treating wood considerably. Forming perpendicular to the grain will add to milling and sawing and enhance the possibilities of treating timber for constructive purpose. To utilize the deformation, compressing must be done in a different way than when compression is done to enhance the material properties. To establish the densification method, temperature, moisture content and compression speed must be fitted to this purpose. Small, clear samples are compressed varying the parameter mentioned and are being evaluated according to the defined purposes. Measuring the stress strain relationship during the densification process, studying the spring back and analyzing the densification distribution within the cross section enables to evaluate the process parameters.
Study of Emotional Intelligence among Psychiatric Mental Health Nurses in Eastern Province, Saudi Arabia

Background: Mental health nurses worked at a highly stressful environment which created by multiple factors including demanding work-load, spending long hours of nursing duties, shortage of nursing workforce, interpersonal communication with patients who have for instance hallucination and aggression. Those factors may lead to burnout of psychiatric mental health nurses. Emotional Intelligence has been discovered to be an essential element in nursing practice generally and psychiatric nursing practice more specifically. Aim: The aim of this study is to investigate the level of emotional intelligence of psychiatric mental health nurses at two different hospitals in Eastern Province, Saudi Arabia. Method: This study used descriptive cross-sectional design. Data was collected from 121 psychiatric mental health nurses through the use of Schutte Self-Report Emotional Intelligence Test (SSEIT). Data were analyzed through the use of SPSS program version 25. Result: Majority of the psychiatric mental health nurses have a high level of EI (69.4%), 28.1% of nurses have moderate level , and only 2.5% have low level of EI. In addition, there was a positive correlation between level of EI and nurse's job position and assigned department. Conclusion: As the study shows significant correlation between level of EI of psychiatric mental health nurses and their job position and assigned department, a number of recommendation were proposed. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 11-12-2019 Date of Acceptance: 26-12-2019 -------------------------------------------------------------------------------------------------------------------------------------
Pre-lacteal feeding practices and its predominant factors among mothers’ of infants in Damanhour

Background: Although there are many health programs applied for promoting skin to skin and early initiation of breastfeeding, pre-lacteal feeding (PLF) is still considered one of the barrier of optimal breastfeeding practices and risk of neonatal disease and fatality rate. PLF is considered one of the profound nutritional mismanagement in health care setting of child in the first 1000 days of his life especially in developing countries as in Egypt. Early initiation of breastfeeding continues to remain low in Egypt and the practices of introducing pre-lacteal feed is still prevalent. There are many factors affecting the pre-lacteal feeding practices in Egyptian society as the advice by elder family members (mother in low) or relatives and to calm baby of excessive crying immediately after birth, baby sucking problem and mother illness. Therefore the aim of this study was to explore pre-lacteal feeding practices and its predominant factors among mothers infants’ in Damanhour. Methods: Descriptive, cross-sectional study was conducted from February to April 2019 in 6 Damanhour family health center and units. 300 mothers of children aged less than one years were conveniently recruited by equal allocation sampling technique and the data were collected by using interview based structured questionnaire. Descriptive statistics, binary and multivariable logistic regression analysis were used to identify the related factors associated with pre-lacteal feeding practices among studied mothers. Results: The prevalence of pre-lacteal feeding among the studied sample was nearly 60%. Moreover, the most common type of pre-lacteal feeding introduced, was infant formula, followed by herbal tea and plain water 57.9%, 25% and 13.1% respectively. The main purposes of PLF introduction was, the delayed of milk let down, insufficient breast milk and to calm / soothing or feed hungry baby and or advised of physician or nurses. Mothers’ age, gravidity, mode and place of delivery and lack of breastfeeding counselling were associated with prelacteal feeding practices and were statistically significant positive predictors of it. Conclusion & Recommendation: Pre-lacteal feeding is commonly practiced in studied sample in Damanhour. Mothers less than 20 years, had the first baby, had cesarean section and did not get breastfeeding counseling were statistically significant positive correlation of pre-lacteal feeding practice. Therefore, counselling emphasizing on importance of skin to skin and early initiation of breastfeeding and rooming in is essential in prevention of pre -lacteal feeding practices through antenatal period and availability and publicity of concepts of breastfeeding support group and sustainability of The Baby-friendly Hospital Initiative (BFHI) should be highlighted and reinforced by the governmental authority in all maternity private and governmental hospitals.
Compounding as a Near Universal Phenomenon with Special Reference to Standard Arabic Nominal Compounding Abdul-Hafeed

Compounding has received little attention in linguistic typology and, in particular, in studies on linguistic universals. This paper seeks to study compounding as a universal process with special reference to Arabic nominal compounding. It aims to point out whether compounding is a universal process in light of Standard Arabic nominal compounding. It attempts to extrapolate universal tendencies in compounding with respect to the following features of compounding: the identity of compounding, classification of compounds, headedness of the compounds in the world's languages, relationships between the constituents of compounds, and universality of compounding. It proposes lines of empirical research and methodological suggestions towards the study of universals in compounding. The focus of the study is on nominal compounds consisting of two lexemes.
Visceral Interaction

This paper introduces visceral interaction, which we believe complements the vision of creating more natural and intuitive interfaces. We re-emphasise the importance of the detailed physical aspects of devices and the way in which these can recruit our natural human abilities. We describe a study that highlights this in physical manipulation so long as devices possess key features of physicality - in this case the ‘natural inverse’ property. The device, a Cubicle, controls a media application, but the mapping between the device and its effects were deliberately manipulated. Despite a lack of understanding of the mappings, the participants were able to react appropriately to feedback and successfully complete tasks, and moreover enjoy the experience. We attribute this to the fact that the device preserves key properties of visceral interaction that allow a momentary tacit mapping. We hope that this understanding of physical interaction will help improve future human-centred interaction.
The Functions of Emoticons and Pictograms in Instant Messengers

Human communication has been evolving for thousands of years and technological progress is continuously expanding the range of media that people use for exchanging information and talking to friends. One medium of communication which has become more popular over the years is the Instant Messenger in its various forms. WhatsApp is one of the most popular Instant Messengers. It offers multimodal functionalities that can be used to compensate for the lack of actual human contact and even beyond, for more complex purposes. This paper comprises three parts. Starting from a media-linguistic perspective, it provides insights into In-stant Messengers as such and Whats-App as the prominent example in this context. On the basis of this information, central assumptions on the function of emoticons in computer-mediated communication are reviewed. Afterwards, based on general observations and a corpus of WhatsApp conversations, the significance of emoti-cons and pictograms is discussed in order to arrive at the conclusion that WhatsApp emoticons and pictograms by far exceed the compensatory functions once ascribed to them.
ON THE SYNTACTIC LICENSING OF LOCATIVE EXPRESSIONS IN JAPANESE*

Since Vendler (1967) classified verbs into four semantic types, that is, states, activities, accomplishments and achievements, two major streams of theorizing this classification have been proposed. In one stream, Hale and Keyser (1993), Levin and Rappaport Hovav (1995), Rappaport Hovav and Levin (1998), and Kageyama (1996) propose that different verb meanings should be represented on their lexical semantic representations, a ‘submodule’ of the language faculty, with the basic assumption that the linguistically relevant information is projected from the lexicon, by a set of linking rules. In the other stream, the linguists of the minimalist syntax persuasion, including Mateu and Rigau (2002), Zubizarreta and Oh (2007), and Ramchand (2008), have explored a view of the architecture of grammar whereby the lexicon is eliminated as a module with its own special primitives and modes of combination, and argued for a syntactic representation of these basic classifications of verb meaning. Among them, Ramchand (2008) proposes to replace the lexical conceptual structure (LCS), as in (1a,b), by a purely syntactic representation, as in (2a,b), where InitP is the causing/initiating projection, ProcP is the process projection, and ResP is the result projection:
A Systematic Review of Deep Learning Methods Applied to Ocular Images

Artificial intelligence is having an important effect on different areas of medicine, and ophthalmology has not been the exception. In particular, deep learning methods have been applied successfully to the detection of clinical signs and the classification of ocular diseases. This represents a great potential to increase the number of people correctly diagnosed. In ophthalmology, deep learning methods have primarily been applied to eye fundus images and optical coherence tomography. On the one hand, these methods have achieved an outstanding performance in the detection of ocular diseases such as: diabetic retinopathy, glaucoma, diabetic macular degeneration and age-related macular degeneration. On the other hand, several worldwide challenges have shared big eye imaging datasets with segmentation of part of the eyes, clinical signs and the ocular diagnostic performed by experts. In addition, these methods are breaking the stigma of black-box models, with the delivering of interpretable clinically information. This review provides an overview of the state-of-the-art deep learning methods used in ophthalmic images, databases and potential challenges for ocular diagnosis