Miracle-dz/UniFAR-FTUs huggingface dataset:
Frailty in Older American Indians: The Native Elder Care Study

Introduction: Frailty is often described as a reduction in energy reserves, especially with respect to physical ability and endurance, and it has not been examined in American Indians. The goals of this study were to estimate the prevalence of frailty and identify its correlates in a sample of American Indians. Methods: We examined data from 411 community-dwelling American Indians aged ≥55 years. Frailty was measured with weight loss, exhaustion, low energy expenditure, slowness, and weakness characteristics. Results: Slightly over 44% of participants were classified as pre-frail and 2.9% as frail. Significant correlates of a combined pre-frail and frail status identified in the fully adjusted analyses were younger age, female gender, lower levels of education, increased number of chronic medical conditions, and increased number of activities of daily living limitations. Marital status, chronic pain, and social support were not associated with pre-frail/frail status. Conclusions: Our findings point to specific areas in need of further research, including use of frailty measures that also capture psychosocial components and examining constructs of physical resilience. Targeting those with multiple chronic medical conditions may be an important area in which to intervene, with the goal of reducing risk factors and preventing frailty onset.
Tinnitus and suicide: An unresolved relation

Tinnitus is an auditory phantom sensation which can be a devastating condition for the affected person causing annoyance and discomfort. It may be associated with psychiatric conditions. Patients with highly annoying tinnitus and different comorbidities may have a higher risk of expressing suicidal behaviour and ideation. We aimed to review available reports on the prevalence of suicide and suicidal behaviour with tinnitus patients in order to collate current concepts and to identify possible alarming signs and risk factors. A comprehensive search for appropriate studies listed in PubMed, Ovid and Cochrane databases was conducted using appropriate keyword combinations. We identified 22 publications including original articles, case reports and reviews of which 10 fit our stringent search criteria. Most importantly, from the present studies it appears not feasible to univocally conclude on the co-incidence of tinnitus and suicide. This is due to methodological differences in these approaches, complex interrelations between tinnitus and other psychiatric comorbidities and confounding factors such as the inclusion of patients suffering from post-traumatic stress disorder. More concerted actions involving different medical disciplines are needed to reflect the ethiological heterogeneity of tinnitus and suicide or suicidal behaviour to test for a relationship.
Individual and Contextual Factors of Nulliparas’ Levels of Depression, Anxiety and Fear of Childbirth in the Last Trimester of Pregnancy: Intimate Partner Attachment a Key Factor?

Abstract Background Depression, anxiety and fear of childbirth have numerous consequences for women and their developing offspring. Insecure attachment in close adult relationships is considered to be a risk factor for depressive symptoms. This study aims to gain further insight into the risk factors for depressive and anxiety symptoms in nulliparous women during the third trimester of pregnancy regarding the main contextual relations, with an emphasis on partner attachment. Methods A group of 325 nulliparas in the third trimester of pregnancy was enrolled in a childbirth preparation program. The following instruments were applied: Experiences in Close Relationships-Revised, the Edinburgh Depression Scale, the Zung Anxiety Scale, and a questionnaire regarding fear of childbirth. Three separate multiple linear regression models were built to explore the associations between demographic, social and attachment variables and mental health functioning. Results Highly educated nulliparas and those with a higher level of co-workers’ emotional support experienced a lower level of anxiety when other predictors in the model were held constant. Of all the predictors in the model, only attachment anxiety and co-workers’ support were statistically significantly associated with the level of depression. Attachment anxiety was significantly associated with all three mental health indicators (level of depression, anxiety and fear of childbirth). Conclusions The results suggest that intimate attachment anxiety could be a key contextual factor for mood and anxiety mental health functioning during the third trimester of pregnancy, accessible to change. Our results could facilitate the formulation of interventions for reducing antenatal depressive symptoms.
A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency

Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time-space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency. Based on the train diagram, we constructed a symmetric time-space network for the first time by considering the transition of the railcar state. On this basis, an improved A* algorithm based on the railcar flow route was proposed to generate feasible path sets and a dynamic railcar flow distribution model was built to simulate the railcar flow distribution process in an emergency. In our numerical studies, these output results of our proposed model can be used to control traffic congestion.
When online is off: Public communications following the February 2011 Christchurch, NZ, earthquake

This work in progress investigates the communication issues encountered and the strategies used by local government to communicate electronically with disaster affected individuals in the immediate aftermath of the February 2011 earthquake in Christchurch, NZ. It also provides a preliminary examination of the effects of information access on individual perceptions of community resiliency. We draw from a variety of data sources, including field research, interviews, and focus groups with local community members. Ongoing survey research will be integrated into future papers and presentations. This research provides insight into online crisis communications and the effectiveness of strategies to communicate with members of the public in a post-disaster environment when there is limited access to information via electronic channels.
The value of different media types to support command and control situation awareness

We investigated the value of different media types (Photo, Video, Audio) to support the situational awareness of a Command and Control (C2) officer monitoring three simultaneous military operations. Twenty-one Polish soldiers individually monitored the real-time battlefield information collected by three (virtual, scripted) platoons. Twice during the monitoring task a series of Situation Awareness (SA) probes were presented (Endsley, 1995). At the end of the task, participants were also given a series of meta-SA probes and preference questions. We found that Video supported Level 2 SA (comprehension) better than the other two media types. We also found that participants preferred to receive information in the Photos and Audio clips than in Video. We conclude that if the goal of the C2 team is to better understand the global situation, then providing the persons-in-the-field with video cameras is a valid solution. However, we obtained no evidence to suggest that such an approach supports the ability to predict what may occur in the future (Level 3 SA).
Symmetric Networks with Geometric Constraints as Models of Visual Illusions

Multistable illusions occur when the visual system interprets the same image in two different ways. We model illusions using dynamic systems based on Wilson networks, which detect combinations of levels of attributes of the image. In most examples presented here, the network has symmetry, which is vital to the analysis of the dynamics. We assume that the visual system has previously learned that certain combinations are geometrically consistent or inconsistent, and model this knowledge by adding suitable excitatory and inhibitory connections between attribute levels. We first discuss 4-node networks for the Necker cube and the rabbit/duck illusion. The main results analyze a more elaborate model for the Necker cube, a 16-node Wilson network whose nodes represent alternative orientations of specific segments of the image. Symmetric Hopf bifurcation is used to show that a small list of natural local geometric consistency conditions leads to alternation between two global percepts: cubes in two different orientations. The model also predicts brief transitional states in which the percept involves impossible rectangles analogous to the Penrose triangle. A tristable illusion generalizing the Necker cube is modelled in a similar manner.
A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network

In the era of big data, data-driven methods mainly based on deep learning have been widely used in the field of intelligent fault diagnosis. Traditional neural networks tend to be more subjective when classifying fault time-frequency graphs, such as pooling layer, and ignore the location relationship of features. The newly proposed neural network named capsules network takes into account the size and location of the image. Inspired by this, capsules network combined with the Xception module (XCN) is applied in intelligent fault diagnosis, so as to improve the classification accuracy of intelligent fault diagnosis. Firstly, the fault time-frequency graphs are obtained by wavelet time-frequency analysis. Then the time-frequency graphs data which are adjusted the pixel size are input into XCN for training. In order to accelerate the learning rate, the parameters which have bigger change are punished by cost function in the process of training. After the operation of dynamic routing, the length of the capsule is used to classify the types of faults and get the classification of loss. Then the longest capsule is used to reconstruct fault time-frequency graphs which are used to measure the reconstruction of loss. In order to determine the convergence condition, the three losses are combined through the weight coefficient. Finally, the proposed model and the traditional methods are, respectively, trained and tested under laboratory conditions and actual wind turbine gearbox conditions to verify the classification ability and reliable ability.
Requirements engineering for business workflow systems : a scenario-based approach

Workflow implementations require a deep understanding of business and human cooperation. Several approaches have been proposed to address this need for understanding, but largely in a descriptive way. Attempts to use them in software development have had mixed results. The work reported here proposes that these approaches can be used in a generative way, as part of the requirement engineering process, by (a) extending requirements engineering modelling techniques with underlying cooperation properties, (b) integrating these techniques through the use of a derivation modelling approach, and (c) providing pragmatic heuristics and guidelines that support the real-world requirements engineering practitioner to ensure a high probability of success for the business workflow system to be developed. This thesis develops and evaluates a derivation modelling approach that is based on scenario modelling. It supports clear and structured views of cooperation properties, and allows the derivation of articulation protocols from business workflow models in a scenario-driven manner. This enables requirements engineering to define how the expectations of the cooperative situation are to be fulfilled by the system to be built - a statement of requirements for business workflow systems that reflects the richness of these systems, but also acts as a feasible starting point for development. The work is evaluated through a real-world case study of business workflow management. The main contribution of this work is a demonstration that the above problems in modelling requirements for business workflow systems can be addressed by scenario-based derivation modelling approach. The method transforms models through a series of properties involving cooperation, which can be addressed by using what are effectively extensions of current requirements engineering methods.
FROM PERSON DESCRIPTIONS TO INTERVIEWING METHODS: WHAT CAN BE DONE TO IMPROVE CHILD WITNESSES' TESTIMONIES?

Recently an increasing number of studies have been conducted in psychology and law. This paper reviews more closely relevant research concerning child witnesses. Several factors which may affect witness test imonies are covered, including theoretical issues regarding person descriptions such as verbal and visual processing, and charac- teristics influencing these processes. Also, archival and empirical studies of person descriptions and characteristics of witnesses are reviewed. Finally, the outcomes of different methods which were intended to increase the quality and quantity of children's person descriptions (but have had limited success) are overviewed such as the standard model for comparison. In order to achieve the best balance between quantity and quality in children's accounts, it is recommended that interviewers learn to use structured methods such as the NICHD protocol or the cognitive interview.
Deep Hierarchical Multi-label Classification of Chest X-ray Images

Chest X-rays (CXRs) are a crucial and extraordinarily common diagnostic tool, leading to heavy research for Computer-Aided Diagnosis (CAD) solutions. However, both high classification accuracy and meaningful model predictions that respect and incorporate clinical taxonomies are crucial for CAD usability. To this end, we present a deep Hierarchical Multi-Label Classification (HMLC) approach for CXR CAD. Different than other hierarchical systems, we show that first training the network to model conditional probability directly and then refining it with unconditional probabilities is key in boosting performance. In addition, we also formulate a numerically stable cross-entropy loss function for unconditional probabilities that provides concrete performance improvements. To the best of our knowledge, we are the first to apply HMLC to medical imaging CAD. We extensively evaluate our approach on detecting 14 abnormality labels from the PLCO dataset, which comprises 198,000 manually annotated CXRs. We report a mean Area Under the Curve (AUC) of 0.887, the highest yet reported for this dataset. These performance improvements, combined with the inherent usefulness of taxonomic predictions, indicate that our approach represents a useful step forward for CXR CAD.
Structural Properties of Vicsek-like Deterministic Multifractals

Deterministic nano-fractal structures have recently emerged, displaying huge potential for the fabrication of complex materials with predefined physical properties and functionalities. Exploiting the structural properties of fractals, such as symmetry and self-similarity, could greatly extend the applicability of such materials. Analyses of small-angle scattering (SAS) curves from deterministic fractal models with a single scaling factor have allowed the obtaining of valuable fractal properties but they are insufficient to describe non-uniform structures with rich scaling properties such as fractals with multiple scaling factors. To extract additional information about this class of fractal structures we performed an analysis of multifractal spectra and SAS intensity of a representative fractal model with two scaling factors—termed Vicsek-like fractal. We observed that the box-counting fractal dimension in multifractal spectra coincide with the scattering exponent of SAS curves in mass-fractal regions. Our analyses further revealed transitions from heterogeneous to homogeneous structures accompanied by changes from short to long-range mass-fractal regions. These transitions are explained in terms of the relative values of the scaling factors.
Modeling Overlapped Mutual Funds' Portfolios: A Bipartite Network Approach

This paper studies the topology of the Chilean mutual fund industry using networks methods. With the physical positions of the local equity portfolios managed during 2003.01-2017.4, we analyze their connectivity structure in both the mutual funds’ bipartite network and their one-mode projection. We estimate network measures to examine the potential effects on the topology arising from changes in the industrial environment and changes in the mutual funds’ investment strategies in their overlapped portfolios. Our main results show that changes in the bipartite network and its one-mode projection are correlated with variables related to funds’ investment strategies and with industry-specific variables. In consequence, these elements are a new potential of disturbance in the financial network conformed by stocks and mutual funds. We contribute to the existing literature, improving the understanding of the aggregate behavior of a financial sector which despite its economic importance has attracted little attention from a systemic risk perspective.
Maternal predictors of low birth weights: Audit of data of delivery room register at a Tertiary Health Center of Sub-Himalayan Region

Background: Birth weight is an indicator of social and economic development of any country. It predicts the status of women of country and the resources invested in them so that they deliver healthy child. The proportion of low birth weight (LBW) has reduced in India in the past few decades; however, we have still a long way to go. Objective: We aimed to conduct an audit of retrospective data from the records of labor room of a Tertiary Care Center of Dr. Rajendra Prasad Government Medical College, Kangra at Tanda, Himachal Pradesh. Methodology: A retrospective data mining of records of the labor room wards (delivery rooms) was conducted from January to June 2016 at Tertiary Care Center of Dr. Rajendra Prasad Government Medical College, Kangra at Tanda, Himachal Pradesh. LBW was our outcome of interest. Results: Out of the total 3738 deliveries conducted, 1251 (33.46%) of babies born were LBW, and there were 100 intrauterine deaths and 12 stillbirths with a total of 112 (2.9%) deaths. Age, height of mother, backward caste, history of pregnancy-induced hypertension, preterm delivery, one living child of mother, multiple fetuses, and cesarean section in current pregnancy were significant predictors after controlling for confounders. Conclusion: The higher proportion of LBW in tertiary center as compared to state-level data shows that secondary prevention in the form of early identification of high-risk cases, and timely referral to higher centers is functioning well in this part of the country. However, the community-based primary prevention efforts are still given a low preference.
Consequence of long-standing auditory neuropathy spectrum disorder on voice

Introduction: Individuals with auditory neuropathy spectrum disorder (ANSD) are known to have temporal processing deficits and poor speech perception abilities. The distorted auditory perception, if long-standing, may influence speech production abilities. The present study was undertaken to probe into the voice characteristics of individuals with long-standing ANSD, on a perceptual scale. The study used standard groups comparison research design. Materials and Methods: The study involved 11 individuals with acquired long-standing ANSD and 20 age-matched individuals (10 males and 10 females) with normal-hearing sensitivity. The recorded reading samples of the participants were presented randomly to nine speech-language pathologists who were blindfolded to the purpose of the study. The analysis was done using the Consensus Auditory-Perceptual Evaluation of Voice which provides a 100-mm Visual Analog Scale (VAS). Descriptive statistics and Pearson's correlations were carried out. Results: The results obtained revealed that individuals with long-standing ANSD present with deviant voice characteristics in terms of rough voice, breathiness, strain, high pitch, and reduced loudness. These deviations in voice could be attributed to defective auditory feedback secondary to hearing loss. Furthermore, a significant correlation was found to exist between the duration of hearing loss and the severity of deviant voice in these individuals. Conclusions: The findings suggest that voice is deviant in individuals with long-standing ANSD. This finding necessitates early identification and rehabilitation in individuals with long-standing AD to avoid negative influence on other domains of communication such as speech production.
A novel class of neural networks with quadratic junctions

The authors discuss the architecture and training properties of a multilayer feedforward neural network class that uses quadratic junctions in a neural architecture that uses effectively the backpropagation learning algorithm given by P.J. Werbos (1989). Both the architecture of the quadratic junctions and the backpropagation were adopted so as to endow the networks with appealing training properties (under supervision) and acceptable generalizations. Complexity and learning aspects of this class are examined and compared with traditional networks that use linear junctions. <<ETX>>
Awareness of asthma and its management in primary school teachers in Eastern Province

Introduction: Asthma is one of the most common chronic respiratory disease affecting young children. It is estimated that 14% of the world's children have had asthmatic symptoms, according to the International Study of Asthma and Allergies in Childhood (ISAAC). Schools represent “home” for most children as they spend about a third of their waking hours in school each weekday. Also, schools are significant sources of exposure to asthma-triggering allergens. Therefore, school personnel, including teachers, face all the issues of asthma management that the family meets at home. The aim of this study is to assess the levels of knowledge about asthma and its management among primary school teachers in Eastern Province; Saudi Arabia. Methods: 396 primary school teachers answered an electronic questionnaire about asthma. This questionnaire contained different questions which assessed teacher's knowledge about symptoms of asthma, and its management. Also, the survey can determine the teacher's attitude and practice regarding asthmatic students. Results: Overall, 59.6% of teachers had a high level of asthma knowledge as they were able to answer ≥75% of the knowledge questions correctly. Teachers' level of asthma knowledge was not significantly associated with age, but significantly associated with years of teaching experience, educational level and contact with an asthmatic individual. Most of the respondents were at a high level of awareness concerning asthma symptoms, triggering and treatment (73.2%, 60.9%, 60.7%), respectively, while only 19.4% had high knowledge level about sport and asthma. Conclusions: The primary school teachers are not well informed about asthma and its management. Future educational efforts should seek to provide teachers with accurate information about asthma with particular concern for sport and asthma. This will have a significant impact on the management of this chronic respiratory disorder.