Miracle-dz/UniFAR-FTUs huggingface dataset:
ASSESSMENT OF PROBLEMATIC FACEBOOK USE AMONG UNDERGRADUATE STUDENTS IN UPM CORRELATED WITH DEPRESSION, ANXIETY AND STRESS

Introduction: Facebook has emerged as one of the top social networking sites (SNSs) among university students but at the cost of leading to negative implications on psychosocial wellbeing. Psychological factors such as depression, anxiety and stress have been implicated in the development of addictions; however studies that evaluate this are scarce among the Malaysian population. Our objective was to identify problematic Facebook use among undergraduate students in Universiti Putra Malaysia (UPM) and to correlate the psychological factors that influence problematic Facebook use. Methods: A cross sectional study was conducted among 1060 students from various faculties in UPM. Validated Facebook Addiction Test (FAT) and DASS-21 questionnaires were used to collect data. Descriptive analysis was done for demographic data. Pearson correlation and regression analysis were used in the analytical part. Results: Problematic Facebook use was detected among 16.6% of the undergraduate students. Problematic Facebook use was significantly related to the level of depression, anxiety and stress (p<0.05). Multiple regression analysis indicated that younger age, male gender and depression were significant predictors of problematic Facebook use (p<0.05). Conclusion: Problematic Facebook use is significantly related to the level of depression, anxiety and stress. Young male university students are more prone to problematic Facebook use than females. Depression plays an important role in the development of problematic Facebook usage, thus requires careful monitoring of young students for early detection and prevention. Keywords : Internet Addiction, Malaysia, social networking, student psychology, university
Heterogeneity in marginal returns to language training of immigrants

We estimate the effect of language training on subsequent employment and wages of immigrants under essential heterogeneity. The identifying variation is based on regional differences in language training availability that we use to instrument endogenous participation. Estimating marginal treatment effects along the distribution of observables and unobservables that drive individual participation decisions, we find that immigrants with higher gains are more likely to select into language training than immigrants with lower gains. We document up to 15% higher employment rates and 13% wage gains for immigrants with a high desire to participate but the positive returns vanish with increasing resistance to treatment. This pattern of selection on gains correlates with unobserved ability and motivation, promoting investments in education and job-specific skills that yield higher returns when complemented by language capital in the host country.
New Approaches to End-User Training

Over the last couple of decades, there has been tremendous use of information technology in business. Business leaders cite training end-users to use technology as a one of the key challenges of the future. This book explores three contemporary methods in end-user training: e-learning, peer collaboration and collaborative e-learning. Drawing on the two foundational disciplines of Information Systems and Education, this book first summarizes the inconsistencies in existing literature. Next, it outlines a theoretical model that describes the effect of learning methods using the structures embedded in the technology, teams and techniques as well as the important role of faithful appropriation of learning methods on learning outcomes. Finally, drawing on the results of a 2X2 multi-period quasi-experiment, the book outlines detailed guidelines for researchers and practitioners in the area of End-user training as well as anyone else involved in the area of training.
Constructing Spiritual Motherhood in the Democratic Republic of Congo

Drawing on an ethnographic study of Roman Catholic sisters in the Democratic Republic of Congo, I show how women in the Global South draw on religious imagery to redefine cultural ideals of womanhood and family responsibility. By taking the religious vows of chastity, poverty, and obedience, the Congolese sisters I interviewed seemingly betray local expectations regarding women’s responsibility to reproduce and repair the clan. Although sisters’ vows subject them to social ridicule for violating cultural expectations to bear children and support kin, they devise new strategies to negotiate the connection between womanhood and the maternal role of caregiver and nurturer outside of marriage and fertility. In social ministries that affirm their communal, moral, and spiritual ties to others, the sisters realize these cultural ideals through a “spiritual motherhood” that transforms their traditional heteronormative obligations. Framing their decision to live outside accepted kinship structures in religious terms mutes the radicalness of this lifestyle and provides religious legitimation for what would otherwise be considered a selfish choice for a woman acting independent of family well-being. In this context, I demonstrate how doing religion is inseparable from doing gender as Catholic sisters embody alternative ways of being a woman in post-colonial Congolese society through their religious practices.
Narcissism of Volleyball Players in Palestine

The purpose of this study was to investigate narcissism of volleyball players in Palestine. Furthermore, to determine the effect of playing experience, international participation, and player duty variables on the level of narcissism. The sample of the study consisted of 108 volleyball players, from different divisions in Palestine. Emmons’ (1984) inventory consisting of 37 items was used for measuring narcissism. The results revealed that narcissism is prevailing among volleyball players in Palestine, where the percentage of response of total score was 73%. Furthermore, the result revealed significant differences in narcissism due to playing experience, international participation, and player duty variables. Differences were in favor of longer experience, participants in international competition, attackers, wall definders, and prepares.
Exogenous and endogenous models of economic growth

The focus of this thesis is the examination of cross-country and time series data to distinguish between specific classes of exogenous and endogenous models of economic growth. Chapter 1 describes the broad trends in the data, emphasising the wide variation in growth rates, both cross-country and over time. Chapter 2 investigates the theoretical models of growth, focusing on the differences between exogenous and endogenous specifications. Chapter 3 surveys the empirical literature relating to cross-country estimates of growth. Four related issues are addressed, namely convergence, human capital, physical capital, and the role of government policy. It is argued that this evidence is insufficient to differentiate between exogenous and endogenous models of growth. Chapter 4 presents new time series evidence, based on data in Maddison (1993) for 8 industrialised countries. Specifically, it examines the properties of output series to test between stochastic variants of Solow's (1956) neoclassical, exogenous growth model, and Rebelo's (1991) constant returns, endogenous model of economic growth. Chapter 5 presents the conclusions of this thesis.
Did somebody say populism? Towards a renewal and reorientation of populism studies

ABSTRACT Responding to the recent explosion in scholarly analysis of populism, this paper offers a conceptual mapping and critique of the dominant schools of thought within the burgeoning field of populism studies. In the first half of the paper we suggest that two broad conceptions of populism – one associated with Cas Mudde, the other with Ernesto Laclau – have come to dominate the field. Yet neither of these approaches, we argue, are able to satisfactorily capture the specificity of contemporary forms of radical politics. Thus, the second part of the paper examines possible responses to this conceptual impasse. On the one hand, we recommend a move towards more theoretically and sociologically enriched accounts of populism, by drawing on the insights and concepts of political sociology, political theory and cultural studies. On the other, drawing on recent work by Benjamin De Cleen, Jason Glynos and Aurelien Mondon, we suggest a partial reorientation of populism towards thinking about populism as a signifier (rather than as a concept). In so doing, we conclude with a call for greater sensitivity to, and awareness of, the role that discourses about populism (including scholarly discourses) play in sustaining existing relations of power and ideology.
Global Innovation and Knowledge Diffusion

We develop a Ricardian model of trade where countries innovate ideas that diffuse globally. Our key result provides necessary and sufficient conditions for innovation and diffusion to generate max-stable Fréchet productivity, linking generalized extreme value expenditure to knowledge flows. Innovation makes a country technologically distinct, reducing its substitutability with other countries. In contrast, diffusion generates technological similarity, increasing head-to-head competition and substitutability. In an innovation-only model where countries do not share ideas, productivities are independent across countries and expenditure is CES. Consequently, departures from CES reveal diffusion patterns. (JEL F11, O31, O33, O41)
Abstractive text summarization with attention-based mechanism

In the age of information, the huge amount of data that is produced every day will remain unuseful for humans unless making it available with new tools and technologies. Abstractive Text Summarization tries to get the most essential content of a text corpus and compress is to a shorter text while keeping its meaning and maintaining its semantic and grammatical correctness. Neural architectures are becoming dominant in the Abstractive Text Summarization. The use of deep learning architectures in natural language processing entered a new era after the appearance of the sequence to sequence models in the recent decade. These models are basically founded on a couple of recurrent neural networks that connect the input and output data in an encoder-decoder architecture. Better results were possible by adding the Attention Mechanism to the RNN layers. Many works have shown the competitive performance of these new architectures in Machine Translation (ML). The recently proposed model which is called Transformer uses only the attention mechanism. It has surpassed the previous state of the art models in translation tasks. In this work, we want to experiment this new model, the Transformer, for abstractive text summarization. We will discuss its advantages and shortcomings in comparison with the available models.
Exploring Patterns of Sustainability Stimuli of Project Managers

Sustainable project management is becoming important and the sustainability concepts of people, the planet and profit needs to be incorporated into any type of project. This article focuses on the behavior of the project manager per se and the stimuli patterns that motivate them to adhere to sustainable project management. Three stimuli patterns are used i.e., intrinsically motivated, pragmatic and task driven. To determine which of these patterns influence a project manager, a quantitative pair-wise comparison was used. Twelve statements were used in a pair-wise comparison resulting in a combination of 66 questions. A sample of 101 project managers was analyzed to determine the stimuli patterns. The results indicate that the most prevalent stimulus pattern is the intrinsically motivated pattern with the other two patterns equally important. The results are consistent across gender, age and types of projects as well as industries. It can be concluded that for this study, project managers incorporate sustainability because they feel that it is something they should do. The motivation to consider sustainability is dominated by their behavioral beliefs and the characteristics of the project, or the opinion of others, do not play a large role. This research contributes to the larger body of knowledge with regards to sustainable project management and specifically to the human behavior of project managers. This research addresses the gap that currently exists in current literature where the focus is on the product’s sustainability and sustainable processes.
The effect of limb preference on braking strategy and knee joint mechanics during pivoting in female soccer players

ABSTRACT Purpose: The purpose of this study was to explore whether limb preference influences braking strategy and knee joint mechanics during a 180° pivot task in female soccer players. Methods: Three-dimensional motion analyses of pivoting on the preferred and non-preferred kicking limbs were performed using 10 Qualisys ‘Oqus 7ʹ infrared cameras (240 Hz). Ground reaction forces (GRF) were collected from two AMTI force platforms (1200 Hz) embedded into the running track to examine penultimate (PEN) and final (FC) contact. Results: Both preferred and non-preferred limbs involved greater hip (ES = 2.85–3.81) and knee joint flexion angles (ES = 5.74–5.78) and peak vertical GRFs (ES = 0.87–1.61), but lower average vertical (ES = 2.55–3.01) and horizontal GRFs (ES = 3.05–3.67) during the PEN compared to the FC. Knee abduction angles were very likely greater (ES = 0.61) when turning off the non-preferred limb compared to the preferred limb. Conclusion: These findings may help us question the role of limb preference during pivoting, yet knee abduction angles and moments should be monitored with caution in female soccer players. Thus, it remains inconclusive the role limb preference plays in change of direction biomechanics for performance and risk of injury.
Performance Analysis of Big Data Tools

The limitation in traditional Database Management Systems to process and analysis the growing data from various sources has led to emergence of Big Data. A lot of tools have been developed under Hadoop architecture to utilize the powerful functionality provide by Hadoop. In this paper, we have evaluated the performance of Big Data tools, Pig and Hive. We have shown that Hive is 2.82 faster than Pig with respect to data size ranging from one hundred thousand to one million rows. Moreover, Hive achieved 3.95 faster performance over Pig when more complex query is performed. However, the learning curve of Pig is higher than Hive, but the last required preparing the data warehouse before starting processing them.
In search of institutional complementarities: Comparative Capitalism and economic policy reform

ABSTRACT The Comparative Capitalism research programme has become the dominant institutional approach with regard to the study of advanced economies. Still, very few scholars use it to develop proposals for economic policy reform. The introductory paper to the special issue discusses how this can be changed. It highlights the considerable institutional differences between contemporary models of capitalism. Moreover, it demonstrates how core Comparative Capitalism notions such as “institutional complementarities” can be used for designing policies. However, it also points to recent developments in Comparative Capitalism research that replace the traditional Varieties of Capitalism preoccupation with micro-economic equilibria through the heterodox macro-economic preference for the balancing out of Growth Models
Defining and targeting combination immunotherapies in mouse models of cancer

Checkpoint blockade has achieved long-lasting anti-tumour responses, unfortunately this is limited to a fraction of patients, highlighting the need for more effective therapies. This thesis focuses on the rational proposal and design of new cancer immunotherapies through: (1) proposing a novel immunomodulatory-target for cancer-immunotherapy, Inducible T-cell co-stimulator (ICOS), and studying its efficacy in murine models of cancer; and (2) the description of the immune tumour-microenvironment (TME) of mouse models of lung cancer, to propose strategies that promote increased immunogenicity and tumour rejection. In models of melanoma, the absence of ICOS/ICOSL pathway in ICOS-/- mice, impaired the efficacy of anti-CTLA-4 (Cytotoxic T-lymphocyte antigen-4) therapy. Additionally, patients that received ipilimumab (anti-CTLA-4) monoclonal antibody (mAb) had an increase in the frequency of ICOS+ T-cells. We hypothesised that an agonistic non-depleting anti-ICOS mAb will promote the function of activated T-cells in the TME. Here we show that an agonistic anti-ICOS mAb, with either mIgG1 (non-depleting) or mIgG2a (depleting) isotype, does not promote survival, either as a monotherapy or in combination with other antibody therapies. We also showed that both anti-ICOS isotypes eliminated T-cells in the TME and that anti-ICOS mIgG1 T-cell elimination was Fc-engagement independent. These results were replicated using mice expressing human Fcγ receptors (FcγRs) and anti-ICOS mAb with human (h)IgGs, demonstrating that anti-cancer therapy with anti-ICOS mAbs should be carefully evaluated before use in clinical trials. To design and test new combination therapies, we described the immune-TME of mouse models of lung cancer. Currently, lung cancer has the highest mortality among cancers, with immunotherapy-benefit limited to some patients. Here we described the TME of two mouse models of lung cancer: KPB6.F1 and CMT-167. We did not find significant differences in the TME of the KPB6.F1 model after radiotherapy and chemotherapy. To promote immunogenicity, combination therapy with anti-CD25 mAb and anti-4-1BB mAb was evaluated in both the KPB6.F1 and CMT-167 models. Anti-4-1BB promoted proliferation, granzyme B production and expression of activation markers on effector CD4+ and CD8+ T-cells. Whilst this combination reduced the tumour-burden of the CMT-167 model, no differences were observed in the KPB6.F1 model, suggesting intrinsic differences between them. Further work describing the differential response of both models to specific therapies could provide important information regarding resistant tumours in patients, together with strategies to overcome those resistances. The work presented in this thesis describes variations in the immune-TME following different therapies, suggesting that further investigation is crucial for understanding the biology of the mechanism of action of cancer immunotherapies and to improve their efficacy.
Effects of surface compliance on the dynamic response and strains sustained by a player’s helmeted head during ice hockey impacts

In hockey, players experience different compliances during impacts to the head, from stiff ice to compliant collisions against other players. The objective of this study was to examine the effect of striking compliance in ice hockey impacts and its influence on dynamic response and brain tissue strain. Three striking caps of low, medium, and high compliances were used to impact a helmeted 50th-percentile Hybrid III headform. The headform was impacted at five locations at three velocities, representative of collision scenarios in hockey. The dependent variables, peak resultant linear and rotational acceleration as well as maximum principal strain were analyzed using a multivariate analysis of variance to determine significant differences between the compliances. The results indicated a significant effect of compliance on the responses of the headform. As expected, low-impact compliance resulted in higher linear and rotational accelerations when compared to the medium and high compliance conditions. However, while the linear and rotational acceleration responses of the medium and high compliance conditions would indicate a low chance of brain injury, the maximum principal strain magnitudes indicated a high likelihood of concussion. Medium- and high-impact compliances are a factor that has not been considered when designing and testing helmet technology in sport, with current methods reflective of low compliance surfaces, that is, those with high stiffness and rigidity. The results of this study demonstrate that an impact compliance is an important factor in producing brain injury and should be considered when certifying helmets through standard testing to mitigate the risk of brain injury.
Review and Modeling of Crystal Growth of Atropisomers from Solutions

In this paper, theories on anisotropic crystal growth and crystallization of atropisomers are reviewed and a model for anisotropic crystal growth from solution containing slow inter-converting conformers is presented. The model applies to systems with growth-dominated crystallization from solutions and assumes that only one conformation participates in the solute integration step and is present in the crystal lattice. Other conformers, defined as the wrong conformers, must convert to the right conformer before they can assemble to the crystal lattice. The model presents a simple implicit method for evaluating the growth inhibition effect by the wrong conformers. The crystal growth model applies to anisotropic growth in two main directions, namely a slow-growing face and a fast-growing face and requires the knowledge of solute crystal face integration coefficients in both directions. A parameter estimation algorithm was derived to extract those coefficients from data about temporal concentration and crystal size during crystallization and was designed to have a short run time, while providing a high-resolution estimation. The model predicts a size-dependent growth rate and simulations indicated that for a given seed size and solvent system and for an isothermal anti-solvent addition crystallization, the seed loading and the supersaturation at seeding are the main factors impacting the final aspect ratio. The model predicts a decrease of the growth inhibition effect by the wrong conformer with increasing temperature, likely due to faster equilibration between conformers and/or a decrease of the population of the wrong conformer, if of low energy, at elevated temperatures. Finally, the model predicts that solute surface integration becomes the rate-limiting mechanism for high solute integration activation energies, resulting in no impact of the WC on the overall crystal growth process.
Building Rich Recommender Systems by Modeling Visual, Sequential, and Relational Signals

Author(s): He, Ruining | Advisor(s): McAuley, Julian | Abstract: Modeling and predicting user behavior in recommender systems are challenging as there are various types of signals at play. Traditional item recommendation algorithms mainly focus on modeling signals that indicate users’ preferences, e.g. purchases, clicks, ratings. Despite their success, they typically ignore other signals that are also important for the recommendation task, e.g. visual signals for understanding users’ finer-grained preferences toward appearances of items, sequential signals for exploiting the recommendation context, or relational signals encoding the complex and useful relationships amongst items.Modeling these signals is non-trivial because it requires one to tackle not only ‘standard’ recommender systems challenges such as dealing with large, sparse, and long-tailed datasets, but also new challenges from dealing with the signals themselves, such as the need to model content in terms of its visual appearance, highly subjective sequential behavior, and the heterogeneous ‘relatedness’ amongst items.In this dissertation, we tackle these challenges by building novel models that are scalable, accurate, and intuitive. Empirical results on a wide spectrum of large, real-world datasets indicate that our methods can not only quantitatively improve recommendation accuracy, but also enrich the system’s ability to understand visual interactions (e.g. visual preferences and fashion trends), context (e.g. the impact of recent actions on the future), and complicated relationships amongst items (e.g. complementary or substitutable).