Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Interactions between the Macro-Environment, Development Thinking and Group Behaviour

This paper explores the hypothesis that groups' behaviour is greatly influenced by the societal environment in which they operate. It does so by looking at societal norms over three eras in developing countries, and the ways in which these affected behaviour at a micro-level as evidenced by the health sector. In the Colonial (and neo-colonial) era macro-norms were hierarchical and based on power relationships; in the post-world war two era, the dominant norms combined power and control with a more cooperative rhetoric; while in the post-1980 era, macro-norms have leaned heavily towards markets and monetary incentives as a way of organising behaviour. It is shown that micro-behaviour in the health sector largely reflects these macro-norms, with the organisation and incentives of health institutions following the sort of incentive system favoured at a macro-level, although in each era, exceptions can be observed, and many organisations combine different elements of behaviour. It is noted that in the most recent era, excessive reliance on monetary incentives is tending to undermine trust and cooperation, and that this may endanger the efficiency as well as the equity of outcomes since trust and cooperation are generally important ingredients of both efficiency and equity.
A Novel Approach For Noise Estimation And Removal From An Image Through PCA

Visual information transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmission is often corrupted with noise. In this paper, we want to remove noise from a singly image. We divide the image into segment and estimate noise through Principal component analysis (PCA). We proposed a model for this effect, and use it to estimate noise standard deviation in noisy image. We want to remove noise through PCA. It is provide the efficiency for estimate and removal of noise.
The Effects of Nudges on Students’ Use of the Diagnostic Assessment and Achievement of College Skills

The purpose of this study is to examine the effects of nudges on online college students’ use of the Diagnostic Assessment and Achievement of College Skills (DAACS), a suite of free, online assessments, feedback, and resources designed to optimize student success in college. The results indicate that the nudges had an effect on students’ completion of the DAACS and on accessing the feedback. The effectiveness varied by type of nudge and the order in which a series of nudges was sent. Simply sending the nudges did not have a direct effect on academic outcomes, but students who responded to one series of nudges were more successful than those who did not.
Practice of Epidemiology New Approaches to Estimating National Rates of Invasive Pneumococcal Disease

National infectious disease incidence rates are often estimated by standardizing locally derived rates using national-level age and race distributions. Data on other factors potentially associated with incidence are often not available in the form of patient-level covariates. Including characteristics of patients’ area of residence may improve the accuracy of national estimates. The authors used data from the Centers for Disease Control and Prevention’s Active Bacterial Core Surveillance program (2004–2005), adjusted for census-based variables, to estimate the national incidence of invasive pneumococcal disease (IPD). The authors tested Poisson and negative binomial models in a cross-validation procedure to select variables best predicting the incidence of IPD in each county. Including census-level information on race and educational attainment improved the fit of both Poisson and negative binomial models beyond that achieved by adjusting for other census variables or by adjusting for an individual’s race and age alone. The Poisson model with census-based predictors led to a national estimate of IPD of 16.0 cases per 100,000 persons as compared with 13.5 per 100,000 persons using an individual’s age and race alone. Accuracy of, and confidence intervals for, these estimates can only be determined by obtaining data from other randomly selected US counties. However, incorporating census-derived characteristics should be considered when estimating national incidence of IPD and other diseases.
Classification Based on Distributional Representations of Words

Short texts usually encounter the problem of data sparseness, as they do not provide sufficient term co-occurrence information. In this paper, we show how to mitigate the problem in short text classification through word embeddings. We assume that a short text document is a specific sample of one distribution in a Gaussian-Bayesian framework. Furthermore, a fast clustering algorithm is utilized to expand and enrich the context of short text in embedding space. This approach is compared with those based on the classical bag-of-words approaches and neural network based methods. Experimental results validate the effectiveness of the proposed method. key words: short text classification, word embedding, gaussian model
Model-Free Evaluation of Directional Predictability in Foreign Exchange Markets

We examine directional predictability in foreign exchange markets using a model-free statistical evaluation procedure. Based on a sample of foreign exchange spot rates and futures prices in six major currencies, we document strong evidence that the directions of foreign exchange returns are predictable not only by the past history of foreign exchange returns, but also the past history of interest rate differentials, suggesting that the latter can be a useful predictor of the directions of future foreign exchange rates. This evidence becomes stronger when the direction of larger changes is considered. We further document that despite the weak conditional mean dynamics of foreign exchange returns, directional predictability can be explained by strong dependence derived from higher-order conditional moments such as the volatility, skewness and kurtosis of past foreign exchange returns. Moreover, the conditional mean dynamics of interest rate differentials contributes significantly to directional predictability. We also examine the co-movements between two foreign exchange rates, particularly the co-movements of joint large changes. There exists strong evidence that the directions of joint changes are predictable using past foreign exchange returns and interest rate differentials. Furthermore, both individual currency returns and interest rate differentials are also useful in predicting the directions of joint changes. Several sources can explain this directional predictability of joint changes, including the level and volatility of underlying currency returns. Copyright © 2007 John Wiley & Sons, Ltd.
Explorer Extending dependencies with conditions for data cleaning

Data cleaning aims to effectively detect and repair errors and inconsistencies in real life data. The increasing costs and risks of dirty data highlight the need for data cleaning techniques. This paper provides an overview of recent advances in data cleaning, based on conditional dependencies, an extension of functional and inclusion dependencies for characterizing the consistency of relational data.
Simultaneous Survey of Water and Class I Methanol Masers toward Red MSX Sources

We report simultaneous single-dish surveys of 22 GHz H2O and 44 and 95 GHz class I CH3OH masers toward 299 Red Midcourse Space Experiment Sources in the protostellar stage. The detection rates are 45% at 22 GHz, 28% at 44 GHz, and 23% at 95 GHz. There are 15, 53, and 51 new discoveries at 22, 44, and 95 GHz, respectively. We detect high-velocity (>30 km s−1) features in 27 H2O maser sources. The 95 GHz maser emission is detected only in 44 GHz maser sources. The two transitions show strong correlations in the peak velocity, peak flux density, and isotropic maser luminosity, indicating that they are likely generated in the same sites by the same mechanisms. The 44 GHz masers have much narrower distributions than 22 GHz masers in the relative peak velocity and velocity range, while 6.7 GHz class II CH3OH masers have distributions intermediate between the two. The maser luminosity significantly correlates with the parental clump mass, while it correlates well with the bolometric luminosity of the central protostar only when data of the low-mass regime from the literature are added. Comparison with the results of previous maser surveys toward massive star-forming regions suggests that the detection rates of 22 and 44 GHz masers tend to increase as the central objects evolve. This is contrary to the trends found in low- and intermediate-mass star-forming regions. Thus, the occurrence of both masers might depend on the surrounding environments as well as on the evolution of the central object.
The extinction of the dinosaurs

Non‐avian dinosaurs went extinct 66 million years ago, geologically coincident with the impact of a large bolide (comet or asteroid) during an interval of massive volcanic eruptions and changes in temperature and sea level. There has long been fervent debate about how these events affected dinosaurs. We review a wealth of new data accumulated over the past two decades, provide updated and novel analyses of long‐term dinosaur diversity trends during the latest Cretaceous, and discuss an emerging consensus on the extinction's tempo and causes. Little support exists for a global, long‐term decline across non‐avian dinosaur diversity prior to their extinction at the end of the Cretaceous. However, restructuring of latest Cretaceous dinosaur faunas in North America led to reduced diversity of large‐bodied herbivores, perhaps making communities more susceptible to cascading extinctions. The abruptness of the dinosaur extinction suggests a key role for the bolide impact, although the coarseness of the fossil record makes testing the effects of Deccan volcanism difficult.
Business nets : classification and management mechanisms

This paper focuses on the type and management of intentionally created business networks called nets. Nets are extensively being used to achieve a variety of benefits over those of a single firm or market transaction. We propose that the effective management of different types of business net is dependent on their underlying value creation logic. Based on notion a value creation framework of three generic net types “current business nets”, “business renewal nets”, and “emerging new business nets” – is suggested. We argue that they pose widely different conditions and requirements for net management. The management mechanisms of these basic net types are then identified and discussed. We contend that the proposed contingency framework captures the complexity and variety of the expanding strategic business nets in a more valid way than the extant classifications of network organizations. The paper contributes the emerging theory of network management.
Importance Weighted Hierarchical Variational Inference

Variational Inference is a powerful tool in the Bayesian modeling toolkit, however, its effectiveness is determined by the expressivity of the utilized variational distributions in terms of their ability to match the true posterior distribution. In turn, the expressivity of the variational family is largely limited by the requirement of having a tractable density function. To overcome this roadblock, we introduce a new family of variational upper bounds on a marginal log density in the case of hierarchical models (also known as latent variable models). We then give an upper bound on the Kullback-Leibler divergence and derive a family of increasingly tighter variational lower bounds on the otherwise intractable standard evidence lower bound for hierarchical variational distributions, enabling the use of more expressive approximate posteriors. We show that previously known methods, such as Hierarchical Variational Models, Semi-Implicit Variational Inference and Doubly Semi-Implicit Variational Inference can be seen as special cases of the proposed approach, and empirically demonstrate superior performance of the proposed method in a set of experiments.
Utilization of Date-pits in Transformer Oil Chemical Regeneration

High quality transformer oil is required to increase the reliability and the life time of the transformer. This oil carries information about the operating condition of the transformer. Therefore, the transformer oil properties should be monitored in order to give early warnings and maintain the transformers efficiency. When the oil quality is decreased, it should be either changed or regenerated. Transformer oil regeneration was carried out using adsorption on Activated Carbon (AC) produced from waste date-pits. After adsorption, drop in density, viscosity, neutralization index and metallic contents were observed, whereas adsorption resulted in an increase in interfacial tension. The properties of the regenerated oil after adsorption was found to approach the acceptable standards, which clearly demonstrate the potential of using locally made AC from waste date-pits as an adsorption agent for transformer oil regeneration.
What Lurks in the martian Rocks and Soil? Investigations of Sulfates, Phosphates, and Perchlorates. Gypsum in modern Kamchatka volcanic hot springs and the Lower Cambrian black shale: Applied to the microbial-mediated precipitation of sulfates on Mars

Abstract Gypsum is a mineral that commonly precipitates in hydrothermal environments. This study reports the electron microscopic analyses of gypsum morphologies and crystal sizes found in hot springs on the Kamchatka Peninsula, Russia, and compares these analyses with gypsum morphologies of hydrothermal genesis found in Lower Cambrian black shale. In sediments of the Kamchatka hot springs, we observed prismatic, prismatic pseudo-hexagonal, fibrous, tubular, lenticular and twinned gypsum crystals, with crystal sizes ranging from <200 nm to >200 μm. The coexistence of diverse crystal habits of gypsum implies a constant interaction between hot spring geochemistry and the metabolisms of the microbial community. The crystallization of Ca- and Ba-sulfates in the black shale of the Lower Cambrian, which shows similar but less varied morphology, was influenced by post-depositional hydrothermal fluids. The partial replacement of pyrite by sulfates in a situation coexisting with rich biomass deposits and animal fossils indicates limited modification of the sedimentary records by biological materials. If the gypsum precipitated on Mars underwent similar interactions between microbial communities and their geochemical environments, the resulting crystal habits could be preserved even better than those on Earth due to the weak geodynamics prevailing on Mars throughout its evolutionary history.
Studying Facial Expression Recognition and Imitation Ability of Children with Autism Spectrum Disorder in Interaction with a Social Robot

Children with Autism Spectrum Disorder (ASD) experience limited abilities in recognizing non-verbal elements of social interactions such as facial expressions [1]. They also show deficiencies in imitating facial expressions in social situations. In this Master thesis, we focus on studying the ability of children with ASD in recognizing facial expressions and imitating the expressions using a rear-projected expressive humanoid robot, called Ryan. Recent studies show that social robots such as Ryan have great potential for autism therapy. We designed and developed three studies, first to evaluate the ability of children with ASD in recognizing facial expressions that are presented to them with different methods (i.e. robot versus video), and second to determine the effect of various methods on the facial expression imitation performance of children with ASD using Reinforcement Learning (RL). In the first study, we compared the facial expression recognition ability of children with ASD with Typically Developing (TD) children using Ryan. Overall, the results did not show a significant difference between the performance of the ASD and groups in expression recognition. The study revealed the significant effect of increasing the expression intensity level on the expression recognition accuracy. iii The study also revealed both groups perform significantly worse in recognizing fear and disgust expressions. The second study focused on the effect of context on the facial expression recognition ability of children with ASD compared to their TD peers. The result of this study showed a higher general performance of TD children compared to the ASD group. Within the TD group, fear and in the ASD group sadness were recognized with the lowest accuracy compared to the average accuracy of other expressions. The result of this study did not show any difference between groups; however, we found that there is a significant effect of different background categories in both groups. It means, we found a significant higher recognition accuracy for the negative backgrounds compared to positive backgrounds in 20% intensity for the fear and sadness expressions. In the third study, we designed an active learning method using RL algorithm to identify and adapt based on the individual differences in expression imitation in response to different conditions. We implemented the RL to first, identify the effective imitation method based on individual’s performance and preference; and second, to make an online adaptation and adjustment based on the effective method for each individual. The result of this study showed that the active learning method could successfully identify and adjust the session based on participant’s strength and preference. The results also showed that each participant responded differently to each method in general and for each expression.
Interpreting Performance in Research on Independent Entrepreneurship

The performance of the often young and independent businesses studies in entrepreneurship research is not only difficult to assess (Brush & Vanderwerf, 1992) and hard to predict (Cooper, 1995), but also a challenge to interpret. Is discontinuation a sign of failure, and always a worse outcome than continuation of the business? Is growth a sure sign of success and always a better outcome than stability? Based on empirical insights from several large research studies this paper will argue that greater care ought to be taken in the selection and interpretation of the dependent variable in entrepreneurship research. It will be argues that discontinuation of some incumbent firms is a necessary part of 'creative destruction' (Schumpeter, 1934) and that termination of a start-up effort may be the best outcome of an essentially sound experiment. If a venture idea is inherently non-viable it is better to learn that earlier rather than later and to minimize the losses rather than continuing dreaming perhaps because the founders shun any 'acid test' for as long as possible. As regards growth, empirical results demonstrate that many firm founders do embrace growth as a goal. Moreover, firms that embark on a growth trajectory starting from a situation of low profitability rarely became profitable as a result of their expansion. Instead they often become low performing firms in terms of growth and profits in subsequent periods. Implications for entrepreneurs, policy-makers and researchers are discussed.
Engagement with Mental Health Screening on Mobile Devices: Results from an Antenatal Feasibility Study

Perinatal depression (PND) affects up to 15% of women within the United Kingdom and has a lasting impact on a woman's quality of life, birth outcomes and her child's development. Suicide is the leading cause of maternal mortality. However, it is estimated that at least 50% of PND cases go undiagnosed. This paper presents the results of the first feasibility study to examine the potential of mobile devices to engage women in antenatal mental health screening. Using a mobile application, 254 women attending 14 National Health Service midwifery clinics provided 2,280 momentary and retrospective reports of their wellbeing over a 9-month period. Women spoke positively of the experience, installing and engaging with this technology regardless of age, education, wellbeing, number of children, marital or employment status, or past diagnosis of depression. 39 women reported a risk of depression, self-harm or suicide; two-thirds of whom were not identified by screening in-clinic.
Engaging Students With a Chatbot-Based Academic Advising System

Abstract Advising systems automate aspects of academic advising. Traditionally, advising systems focused on specialized tasks such as course selection. Recently, chatbot-based advising systems have emerged as they emulate scenario-based advising. Nevertheless, the design of most chatbot-based advising systems is not user-centric, potentially causing a lack of adoption. Further, there is a lack of studies reporting findings of usability evaluation of chatbot-based advising systems. In response, we contribute a chatbot-based academic advising system, MyAdvisor, that helps students with prescriptive academic inquiries. The system is based on real advising scenarios and designed with usability principles. The results show that students learn the system fast and find it helpful. This work contributes (1) scenario-based functional requirements and usability requirements of the chatbot-based advising system, (2) the application of usability heuristics in the design of the system, and (3) findings of empirically evaluating the system usability.
Evaluating the Financial Performance Through ‘Consumer Centric Decision’ Approach in Pharmaceutical Companies of Bangladesh: A Business Planning Perspective

Pharmaceuticals agglomerations consistently use their brand image and versatile product portfolios to consolidate their position in the financial sector, which is evident in their continuous profit making and expansion in market share. This paper explores the short-term and long-term investment attractiveness through ‘consumer centric decision’ approach in two selected pharmaceutical companies, Renata Limited and Orion Pharma Limited, of Bangladesh over the last three years’ period. This research adopts a systematic approach which primarily addresses the various concerns of investors to illustrate the decision-making process of the existing and future investors. Using primarily domestic transaction data, this study explores how the leading pharmaceuticals companies of Bangladesh effectively use the wide array of drug portfolios mix with appropriate branding techniques to increase their financial profit and market share simultaneously. Both SWOT analysis and Porters Five Forces Model explore the business analysis of Renata Limited in compare to Orion Pharma Limited that provides a conclusion regarding investors’ decision to invest in Renata Limited. Considering the financial analysis, Renata’s financial liquidity is not very satisfactory and could have been improved further if management is prudent on financial strategy settings. Findings of the business analysis indicate that Renata Limited would be a good investment choice for existing and prospective shareholders based on its opportunities for long term and short term growth and further expansion in developing the market. The results suggest that even lower liquidity coupled with higher interest borrowings can be balanced by posing positive picture to the public shareholders by returning the positive dividend to them.