Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Cellular Senescence in the Gastrointestinal Mucosa

Cellular senescence is a biologically irreversible state of cell-growth arrest that occurs following either a replicative or an oncogenic stimulus. This phenomenon occurs as a response to the presence of premalignant cells and appears to be an important anticancer mechanism that keeps these transformed cells at bay. Many exogenous and endogenous triggers for senescence have been recognized to act via genomic or epigenomic pathways. The most common stimulus for senescence is progressive loss of telomeric DNA, which results in the loss of chromosomal stability and eventual unregulated growth and malignancy. Senescence is activated through an interaction between the p16 and p53 tumor-suppressor genes. Senescent cells can be identified in vitro because they express senescence-associated β-galactosidase, a marker of increased lysosomal activity. Cellular senescence plays an integral role in the prevention and development of both benign and malignant gastrointestinal diseases. The senescence cascade and the cell-cycle checkpoints that dictate the progression and maintenance of senescence are important in all types of gastrointestinal cancers, including pancreatic, liver, gastric, colon, and esophageal cancers. Understanding the pathogenic mechanisms involved in cellular senescence is important for the development of agents targeted toward the treatment of gastrointestinal tumors.
’ s repository of research publications and other research outputs Identifying Important Life Events from Twitter Using Semantic and Syntactic Patterns Conference Item How to

Identifying global events from social media has been the focus of much research in recent years. However, the identification of personal life events poses new requirements and challenges that have received relatively little research attention. In this paper we explore a new approach for life event identification, where we expand social media posts into both semantic, and syntactic networks of content. Frequent graph patterns are mined from these networks and used as features to enrich life-event classifiers. Results show that our approach significantly outperforms the best performing baseline in accuracy (by 4.48% points) and F-measure (by 4.54% points) when used to identify five major life events identified from the psychology literature: Getting Married, Having Children, Death of a Parent, Starting School, and Falling in Love. In addition, our results show that, while semantic graphs are effective at discriminating the theme of the post (e.g. the topic of marriage), syntactic graphs help identify whether the post describes a personal event (e.g. someone getting married).
The influence of information overload and problematic Internet use on adults' wellbeing

We are living in an information age, where the overabundance of information can result in stressful conditions for information users, such as information overload. This might lead to internet addiction or problematic internet use, because the internet is the most used information source and can be addictive or misused due to its evolving and endless content and activities. An individual can face difficulties in understanding an issue or making a decision because of the presence of too much information, like the flow of instant messages, text messages, phone calls, emails, social network notifications, advertisements, as well as non-cyber based information sources. This flood of information we are being exposed to can result in negative consequences for individual wellbeing. This mixed methods study investigated the impact of information overload and internet addiction on adults’ psychological wellbeing, work performance and academic attainment. Five empirical studies were used to measure the influence of information overload and internet addiction on wellbeing through a holistic approach. These studies also controlled possible factors that could influence or interfere with the wellbeing process. The results revealed interesting findings: The influence of information overload and internet addiction on university students’ predicted negative wellbeing, and the cultural differences between Kuwait and UK sample were not significant. However, the influence of information overload and internet addiction was significantly different between students and workers. The impact of different internet uses on workers were also significantly different than students. The diary study revealed significant differences between problematic internet users and non-problematic internet users’ wellbeing scores, although hours spent on the internet and internet activities were similar. The thesis provides a comprehensive approach to understanding the influence of information overload and internet addiction on adults’ wellbeing, which can provide intervention plans and solutions in universities and workplaces.
Carer experiences of services for adults with intellectual disabilities and Co-morbid mental ill health or challenging behaviour

ABSTRACT The aim of this study was to examine carer experiences with mental health services for individuals with dual disabilities in Australia. This qualitative study involved semi-structured interviews with nine parents with an adult offspring with an intellectual disability in 2016. Parents who had received a mental health service for their offspring within the past two years in Australia with adequate spoken English were included. Parents were asked four open ended questions relating to their experiences of mental health services for their offspring. Findings revealed parents reported more negative experiences with mental health services perceived to hold limited expertise in dual disabilities. They also reported difficulties in accessing appropriate services and highlighted the importance of collaboration and adjustments to suit individual needs of their child. The findings are discussed in terms of the implications for service provision and training for practitioners working with families with intellectual disabilities. Acknowledging the important role of carers as key informants and partners in treatment decision making is highlighted as necessary aligning services with best practice standards.
Factors Affecting the Internet Game Addiction Risk of Elementary School Students in Multicultural Families

Objectives: This study aims to determine that the general characteristics, self-esteem, parent-child relationships, and school life adjustment differ between the Internet game addiction risk group and the non-addiction group, and identify the factors affecting the risk of Internet game addiction. Methods: Data were collected from 24 January to 17 April 2013. A total of 209 subjects were analyzed in the 4th, 5th, 6th grade of elementary school students of multicultural families in Gwangju and Jeollanam-do Province, South Korea. Results: There was a statistically significant difference in self-esteem, parent-child relationship, and school life adjustment between the Internet game addiction risk group and the non-addiction group. The factors affecting Internet game addiction risk to elementary school students in multicultural families were gender, foreign mother’s country, school life adjust ment in order. Conclusions: It is necessary to consider cultural sensitivity in developing Internet game addiction risk prevention program, and to grasp the Internet game addiction targeting multicultural elementary school students.
Short-term changes in quitting-related cognitions and behaviours after the implementation of plain packaging with larger health warnings: findings from a national cohort study with Australian adult smokers

Background Plain packaging (PP) with larger graphic health warnings (GHWs) was implemented in Australia in late 2012. This study examined effects of these packaging changes on short-term changes in quitting-related cognitions and behaviours. Methods We used a series of cohorts of Australian adult cigarette smokers originally sourced from a nationally representative cross-sectional tracking survey, followed up approximately 1 month after their baseline interview (n(weighted)=5441). Logistic regression analyses compared changes in seven quitting-related outcomes over this 1-month follow-up period for the cohorts surveyed before PP, over the period of transition to PP, and during the first year of PP, adjusting for baseline levels of the outcome and covariates. Results Compared to the referent group of smokers who completed their follow-up survey pre-PP, those who were followed-up in the early transition period showed significantly greater increases in rates of stopping themselves from smoking (OR=1.51, 95% CI (1.08 to 2.10)) and higher quit attempt rates (OR=1.43, 95% CI (1.00 to 2.03)), those followed-up in the late transition period showed greater increases in intentions to quit (OR=1.42, 95% CI (1.06 to 1.92)) and pack concealment (OR=1.55, 95% CI (1.05 to 2.31)), and those followed-up in the first year of PP showed higher levels of pack concealment (OR=1.65, 95% CI (1.01 to 2.72)), more premature stubbing out of cigarettes (OR=1.55, 95% CI (1.01 to 2.36)), and higher quit attempt rates (OR=1.52, 95% CI (1.01 to 2.30)). Conclusions These findings provide some of the strongest evidence to date that implementation of PP with larger GHWs was associated with increased rates of quitting cognitions, microindicators of concern and quit attempts among adult cigarette smokers.
Enhancing Prudential Standards in Financial Regulations

The financial crisis has generated fundamental reforms in the financial regulatory system in the U.S. and internationally. Much of this reform was in direct response to the weaknesses revealed in the pre-crisis system. The new “macroprudential” approach to financial regulations focuses on risks arising in financial markets broadly as well as the potential impact on the financial system that may arise from financial distress at systemically important financial institutions. Systemic risk is the key factor in financial stability, but our current understanding of systemic risk is rather limited. While the goal of using regulation to maintain financial stability is clear, it is not obvious how to design an effective regulatory framework that achieves the financial stability objective while also promoting financial innovations. This article discusses academic research and expert opinions on this vital subject of financial stability and regulatory reforms. Specifically, among other issues, it discusses the impact of increasing public disclosure of supervisory information, effectiveness of bank stress testing as a tool to enhance financial stability, whether the financial crisis was caused by TBTF, and whether the DFA resolution regime would be effective in achieving financial stability and ending TBTF.
An automatic non-native speaker recognition system

Identification of non-native personnel is a critical piece of information for making crucial on-the-spot decisions for security purposes. Identification of a non-native speaker is often readily apparent in normal conversation with a native speaker through speech content and accent. Such identification which requires familiarity with language nuances may not be possible for a non-native interrogator or intelligence analyst or when conversing or listening through a machine language translator. Developing an automatic system to identify speakers as native or non-native, as well as their native language, including dialect, within input audio streams, is the major goal of this project. Such a system may be used alone or with other downstream applications such as machine language translation systems. In this paper we present four approaches to identify native and non-native speakers as a binary recognition problem. The approaches can be further categorized into phonetic-based approaches and non-phonetic-based approaches. These approaches were tested on two separate databases, including text-dependent read speech and text-independent spontaneous speech. The results show that our system is competitive in comparison with other published, state-of-the-art non-native speaker recognition systems. Key metrics for automated non-native recognition systems include: 1) positive identification rates, 2) false alarm/identification rates, and 3) length of captured speech sample required to reach a decision.
The subjective well-being of homeworkers across life domains

This paper extends the view of homeworking as a type of flexible working by employees in organisations aimed at improving work–life balance and job satisfaction, to a type of work that encapsulates significant changes of work towards increased self-employment and casual work, high proportions of which are performed in people’s homes. Such changes to work represent a reconfiguration of the spatial separation and relationship between place of work and place of residence. Through homeworking, this paper studies how changing geographies of work and workplaces impact on workers’ life satisfaction overall and across various aspects of their lives. Using a large representative longitudinal dataset for the United Kingdom, findings reveal that workers’ satisfaction with their job, income and leisure time is significantly shaped by homeworking and that the employment status (employee versus self-employed) and gender are important elements for understanding how homeworking is related to subjective well-being. Homeworking is positively related with leisure time satisfaction of men and women. Job satisfaction advances of homeworking are only observed for employees, but not the self-employed. Men’s income satisfaction is decreased when they work as self-employed without employees in their homes. Future policies and research concerning workers’ subjective well-being need to pay attention to the continued trend towards individualised work in people’s own homes.
Choice of Fluids in Severe Septic Patients - A Cost-effectiveness Analysis Informed by Recent Clinical Trials

Fluid resuscitation with colloids is an established second line therapy for septic patients. Evidence of relative efficacy outcomes is tempered by considerations of the relative costs of the individual fluids. An assessment of recent large clinical trials was performed, resulting in a ranking in the efficacy of these therapies. Probabilities for mortality and the need for renal replacement therapy (RRT) were derived and used to inform a decision analysis model comparing the effect of crystalloid, albumin and hydroxyethyl starch solutions in severe septic patients followed from hospital admission to 90 days in intensive care. The US payer perspective was used. Model inputs for costs and efficacy were derived from the peer-reviewed literature, assuming that that all fluid preparations are bio-equivalent within each class of these therapies. Probabilities for mortality and the need for renal replacement therapy (RRT) data were synthesized using a Bayesian meta-analysis. Relative to crystalloid therapy, 0.21 life years were gained with albumin and 0.85 life years were lost with hydroxyethyl starch. One-way sensitivity analysis showed that the model’s outcomes were sensitive to the cost of RRT but not to the costs of the actual fluids or any other costs. We conclude that albumin may be the most cost-effective treatment in these patients when the total medical costs and iatrogenic morbidities involved in treating sepsis with fluids are considered. These results should assist and inform decision making in the choice of these drugs.
Efficient Optimization Algorithms for Learning Abstract Efficient Optimization Algorithms for Learning

Efficient Optimization Algorithms for Learning Ruslan Salakhutdinov Master’s Degree Graduate Department of Computer Science University of Toronto 2003 Many problems in machine learning and pattern recognition ultimately reduce to the optimization of a scalar valued function. A variety of general techniques exist for optimizing such objective functions. We study the general class of bound optimization algorithms – including Expectation-Maximization, Iterative Scaling, Non-negative Matrix Factorization, Concave-Convex Procedure – and their relationship to direct optimization algorithms such as gradient-based methods for parameter learning. We also provide a theoretical analysis of the convergence properties of bound optimization algorithms and identify analytic conditions under which these optimizers exhibit quasi-Newton behavior, and conditions under which they possess poor, first-order convergence. Motivated by these analyses, we interpret and analyze their convergence properties and provide some recipes for preprocessing input to these algorithms to yield faster convergence behavior. Our presented analysis also allows us to design several algorithms for practical optimization, that possess superior convergence over standard existing methods.
Physiologically structured models - from versatile technique to ecological theory

A ubiquitous feature of natural communities is the variation in size that can be observed between organisms, a variation that to a substantial degree is intraspecific. Size variation within species by necessity implies that ecological interactions vary both in intensity and type over the life cycle of an individual. Physiologically structured population models (PSPMs) constitute a modelling approach especially designed to analyse these size-dependent interactions as they explicitly link individual level processes such as consumption and growth to population dynamics. We discuss two cases where PSPMs have been used to analyse the dynamics of size-structured populations. In the first case, a model of a size-structured consumer population feeding on a non-structured prey was successful in predicting both qualitative (mechanisms) and quantitative (individual growth, survival, cycle amplitude) aspects of the population dynamics of a planktivorous fish population. We conclude that single generation cycles as a result of intercohort competition is a general outcome of size-structured consumer–resource interactions. In the second case, involving both cohort competition and cannibalism, we show that PSPMs may predict double asymptotic growth trajectories with individuals ending up as giants. These growth trajectories, which have also been observed in field data, could not be predicted from individual level information, but are emergent properties of the population feedback on individual processes. In contrast to the size-structured consumer–resource model, the dynamics in this case cannot be reduced to simpler lumped stage-based models, but can only be analysed within the domain of PSPMs. Parameter values used in PSPMs adhere to the individual level and are derived independently from the system at focus, whereas model predictions involve both population level processes and individual level processes under conditions of population feedback. This leads to an increased ability to test model predictions but also to a larger set of variables that is predicted at both the individual and population level. The results turn out to be relatively robust to specific model assumptions and thus render a higher degree of generality than purely individual-based models. At the same time, PSPMs offer a much higher degree of realism, precision and testing ability than lumped stage-based or non-structured models. The results of our analyses so far suggest that also in more complex species configurations only a limited set of mechanisms determines the dynamics of PSPMs. We therefore conclude that there is a high potential for developing an individual-based, size-dependent community theory using PSPMs.
Rectifying transformations that minimize resampling effects

Image rectification is the process of warping a pair of stereo images in order to align the epipolar lines with the scan-lines of the images. Once a pair of images is rectified, stereo matching can be implemented in an efficient manner. Given the epipolar geometry, it is straightforward to define a rectifying transformation, however, many transformations will lead to unwanted image distortions. In this paper, we present a novel method for stereo rectification that determines the transformation that minimizes the effects of resampling that can impede stereo matching. The effects we seek to minimize are the loss of pixels due to under-sampling and the creation of new pixels due to over-sampling. To minimize these effects we parameterize the family of rectification transformations and solve for the one that minimizes the change in local area integrated over the area of the images.
Rules of thumb in life-cycle savings models

We analyze life-cycle savings decisions when households use simple heuristics, or rules of thumb, rather than solve the underlying intertemporal optimization problem. The decision rules we explore are a simple Keynesian rule where consumption follows income; a simple consumption rule where only a fraction of positive income shocks is saved; a rule that corresponds to the permanent income hypothesis; and two rules that have been found in experimental studies. Using these rules, we simulate life-cycle savings decisions numerically and compute the utility losses relative to the backwards solution of the intertemporal optimization problem. Our central finding is that the utility losses induced by rule-of-thumb behavior are relatively low. We conclude that behaving optimally, in the sense of solving an intertemporal optimization model, is not only costly, it is also not much better than using simple heuristics. Our results might also explain why optimization models typically fit the main features of empirical data quite well although optimizing behavior itself is frequently rejected.
An evaluation of internship program by using Kirkpatrick evaluation model

This study was aimed at evaluating an internship program using Kirkpatrick’s evaluation program. The subjects of the study were students of batch 2015 and instructors. Slovin formula was used to calculate the sample. A questionnaire and teaching assessment sheet were used as instruments for collecting data. This study used content validity and exploratory factor analysis as the validity of the test. Reliability was estimated by Cronbach’s Alpha. The results of this study showed that (1) in facility, the level of satisfaction was in the ‘very satisfactory’ category (77.01%); (2) in instructor, the level of satisfaction was in the ‘very satisfactory’ category (82.76%); (3) in schedule, the level of satisfaction was in the ‘satisfactory’ category (50.57%); (4) in material, the level of satisfaction was in the ‘very satisfactory’ category (89.66%); and (5) in students’ teaching abilities. The improvement was in the ‘very satisfactory’ category.
An Exploratory Study of the Role of Values in Microeconomic Decision-Making and the Implications for Organizations and Leaders

This research is designed to test the role reflecting on and sharing values plays in our individual decision-making schemas in a group. The research is based on evidence from the literature that values play a role in economic decision-making, can be formed and utilized either consciously or unconsciously, and impact microeconomic decision-making and ethics in organizations. The study found that when decision considerations were reframed in a values context the decision-making process became more quasi-rational, but the decisions participants made were as good or better than they were before values were introduced. In some cases decision-makers became less interested in personal considerations after decisions were framed in a values context. This is an important finding because traditional models of economic decision-making assume the decisionmaking process is always rational and decision-makers are always self-interested. There may also be some relationship between utilizing values and improved ethical decisionmaking for women within small groups with relatively strong relationships in a community.