Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Filter Strategy for Theta-Join Query in Distributed Environment

Theta-join query is a very popular application in traditional databases, but due to tremendous computation cost and communication cost in distributed environment, it is not efficiently processed for big data. Current researches focus on processing theta-join by using MapReduce framework, which mainly consider the overheads of load balance in the network, when the data sets become larger, massive intermediate results lead to high communication cost. In this work, we propose a filter method for theta-join to reduce the computation and communication cost in distributed environment, which can effectively improve the theta-join query. We consider both the load balance in the cluster and the memory cost in the parallel framework. We have implemented our method in a popular general-purpose data processing framework, Spark. The experimental results demonstrate that our method can significantly improve the performance of theta-joins comparing the state-of-art solutions.
Role and Impact of Involvement and Enhanced Threat in Resistance

This study examined the relative impact of outcome-relevant (OR), value-relevant (VR), and impression-relevant (IR) involvement on resistance to influence and whether it is possible to enhance elicited threat levels and, if so, to what effect on resistance to counterattitudinal attacks. An experiment was conducted featuring 281 participants. Results indicated that both OR and VR involvement functioned similarly. They both bypassed threat and counterarguing, instead exerting direct impacts on elicited anger, attitude strength, and resistance. There were no statistically significant results for IR involvement. Results concerning standard and enhanced threat revealed that both manipulations functioned similarly: They enhanced elicited threat, boosted the number and strength of cognitive responses to counterarguments, increased elicited anger, enhanced attitude strength, and contributed to resistance. However, the only booster effect for enhanced threat involved greater attitude certainty.
Evaluating the REMO-EKD technique: A technique for the elicitation of software requirements based on EKD organizational models

One of the most common problems regarding software quality is the software's incapability of offering effective and efficient support to business operations. A possible reason for this lack of support is the inconsistency of the requirements related to the business needs. Therefore, strategies that help the identification of requirements based on organizational processes and context are welcomed. This paper reports on our empirical work that aimed at evaluating the REMO-EKD technique. REMO-EKD is a technique that consists on a set of heuristics for the elicitation of software requirements based on organizational models. These heuristics are based on the Enterprise Knowledge Development approach. We discuss the quantitative results of the study and how they can help improving the REMO-EKD technique. Results of the evaluation suggest that our technique supports the extraction of requirements from EKD organizational models, maximizing the number of total requirements found.
Hierarchical clustering analysis for visual-movement response functional MRI data processing

Cognitive experiments involving visual and movement tasks have been intensively studied using functional magnetic resonance imaging (fMRI). A common paradigm of such experiments is that subjects are required to complete different tasks such as visual task or movement task simultaneously. A key problem with these studies is how to identify various cerebral networks, even then all of them were activated and responded to execution of same task. We hypothesized that the differences in spatio-temporal property of various cerebral network and in asymmetry of cerebral networks in bilateral hemispheres allowed us to identify and classify these task-related cerebral networks. In this paper, six datasets from the experiment involving simultaneous bilateral hand movement and classic visual stimulation (i.e. checkerboard stimulation) were analyzed by using hierarchical clustering analysis (HCA) with neighborhood local correlation (NC). The hierarchical result represented that our method can identify and classify various task-related networks. The result of asymmetry on hand moving networks between left hemisphere and right hemisphere also clarified the validity of our method.
Convergence Rates for Greedy Algorithms in Reduced Basis Methods

The reduced basis method was introduced for the accurate online evaluation of solutions to a parameter dependent family of elliptic PDEs. Abstractly, it can be viewed as determining a “good” n-dimensional space $\mathcal{H}_n$ to be used in approximating the elements of a compact set $\mathcal{F}$ in a Hilbert space $\mathcal{H}$. One by now popular computational approach is to find $\mathcal{H}_n$ through a greedy strategy. It is natural to compare the approximation performance of the $\mathcal{H}_n$ generated by this strategy with that of the Kolmogorov widths $d_n(\mathcal{F})$ since the latter gives the smallest error that can be achieved by subspaces of fixed dimension n. The first such comparisons, given in [A. Buffa et al., ESAIM Math. Model. Numer. Anal. , 2011, to appear], show that the approximation error, $\sigma_n(\mathcal{F}):=\mathrm{dist}(\mathcal{F},\mathcal{H}_n)$, obtained by the greedy strategy satisfies $\sigma_n(\mathcal{F})\leq Cn2^nd_n(\mathcal{F})$. In this paper, various improvemen.
Discontinuation and non-publication of surgical randomised controlled trials: observational study

Objective To determine the rate of early discontinuation and non-publication of randomised controlled trials involving patients undergoing surgery. Design Cross sectional observational study of registered and published trials. Setting Randomised controlled trials of interventions in patients undergoing a surgical procedure. Data sources The ClinicalTrials.gov database was searched for interventional trials registered between January 2008 and December 2009 using the keyword “surgery”. Recruitment status was extracted from the ClinicalTrials.gov database. A systematic search for studies published in peer reviewed journals was performed; if they were not found, results posted on the ClinicalTrials.gov results database were sought. Email queries were sent to trial investigators of discontinued and unpublished completed trials if no reason for the respective status was disclosed. Main outcome measures Trial discontinuation before completion and non-publication after completion. Logistic regression was used to determine the effect of funding source on publication status, with adjustment for intervention type and trial size. Results Of 818 registered trials found using the keyword “surgery”, 395 met the inclusion criteria. Of these, 21% (81/395) were discontinued early, most commonly owing to poor recruitment (44%, 36/81). The remaining 314 (79%) trials proceeded to completion, with a publication rate of 66% (208/314) at a median time of 4.9 (interquartile range 4.0-6.0) years from study completion to publication search. A further 6% (20/314) of studies presented results on ClinicalTrials.gov without a corresponding peer reviewed publication. Industry funding did not affect the rate of discontinuation (adjusted odds ratio 0.91, 95% confidence interval 0.54 to 1.55) but was associated with a lower odds of publication for completed trials (0.43, 0.26 to 0.72). Investigators’ email addresses for trials with an uncertain fate were identified for 71.4% (10/14) of discontinued trials and 83% (101/122) of unpublished studies. Only 43% (6/14) and 20% (25/122) replies were received. Email responses for completed trials indicated 11 trials in press, five published studies (four in non-indexed peer reviewed journals), and nine trials remaining unpublished. Conclusions One in five surgical randomised controlled trials are discontinued early, one in three completed trials remain unpublished, and investigators of unpublished studies are frequently not contactable. This represents a waste of research resources and raises ethical concerns regarding hidden clinical data and futile participation by patients with its attendant risks. To promote future efficiency and transparency, changes are proposed to research governance frameworks to overcome these concerns.
F LEXIBLE D ECISCION T REES FOR G RAPHEME B ASED S PEECH R ECOGNITION

: Over the last decades research in the ﬁeld of automatic speech recognition (ASR) has seen enormous progress. Speech recognition systems are now deployed in real world applications, such as commercial software systems on PCs or Workstations, embedded in consumer devices such as cell phones or car navigation systems, or as part of specialized appliances. With this increasing economic relevance it has become more and more important to be able to rapidly extend speech recognition systems by new words, or to port them to new, previously unseen languages or domains. Hereby the speed and cost of development are of great importance.
Dynamic Reconfigurable Task Schedule Support towards a Reflective Middleware for Sensor Network

Sensor networks are being applied in several emerging sophisticated applications due to the use of powerful and high-quality sensor nodes, such as radars and visible light cameras. However, these nodes need additional features to optimally benefit from heterogeneous modern computing platforms. Therefore, reconfigurable computing is a potential paradigm for those scenarios as it can provide flexibility to explore the computational resources on that kind of high performance computing system. This paper presents a reconfigurable sensor node allocation support, based on application requirements, provided by a middleware focused on heterogeneous sensor networks. In order to address this concern, an aspect-orientation paradigm and intelligent agents approach is proposed followed by an UAV case study.
Total Serum Cholesterol and Cancer Incidence in the Metabolic Syndrome and Cancer Project (Me-Can)

Objective To investigate the association between total serum cholesterol (TSC) and cancer incidence in the Metabolic syndrome and Cancer project (Me-Can). Methods Me-Can consists of seven cohorts from Norway, Austria, and Sweden including 289,273 male and 288,057 female participants prospectively followed up for cancer incidence (n = 38,978) with a mean follow-up of 11.7 years. Cox regression models with age as the underlying time metric were used to estimate hazard ratios (HR) and their 95% confidence intervals (CI) for quintiles of cholesterol levels and per 1 mmol/l, adjusting for age at first measurement, body mass index (BMI), and smoking status. Estimates were corrected for regression dilution bias. Furthermore, we performed lag time analyses, excluding different times of follow-up, in order to check for reverse causation. Results In men, compared with the 1st quintile, TSC concentrations in the 5th quintile were borderline significantly associated with decreasing risk of total cancer (HR = 0.94; 95%CI: 0.88, 1.00). Significant inverse associations were observed for cancers of the liver/intrahepatic bile duct (HR = 0.14; 95%CI: 0.07, 0.29), pancreas cancer (HR = 0.52, 95% CI: 0.33, 0.81), non-melanoma of skin (HR = 0.67; 95%CI: 0.46, 0.95), and cancers of the lymph−/hematopoietic tissue (HR = 0.68, 95%CI: 0.54, 0.87). In women, hazard ratios for the 5th quintile were associated with decreasing risk of total cancer (HR = 0.86, 95%CI: 0.79, 0.93) and for cancers of the gallbladder (HR = 0.23, 95%CI: 0.08, 0.62), breast (HR = 0.70, 95%CI: 0.61, 0.81), melanoma of skin (HR = 0.61, 95%CI: 0.42, 0.88), and cancers of the lymph−/hematopoietic tissue (HR = 0.61, 95%CI: 0.44, 0.83). Conclusion TSC was negatively associated with risk of cancer overall in females and risk of cancer at several sites in both males and females. In lag time analyses some associations persisted, suggesting that for these cancer sites reverse causation did not apply.
Observation operators for the direct assimilation of TRMM microwave imager retrieved soil moisture

Each soil moisture data set is characterized by its specific mean value, variability, and dynamical range. For the assimilation of soil moisture observations into numerical models observation operators have to be developed, which reduce systematic differences. In this study, cumulative distribution function (CDF) matching is used to derive observation operators for TRMM Microwave Imager (TMI) derived soil moisture for the southern US, modeled soil moisture fields from the European Centre for Medium‐Range Weather Forecasts (ECMWF), and model output from the Variable Infiltration Capacity model (VIC). It is found that the transferability of these observation operators in space and time strongly depends on the geographical region. In the Central US, where the assimilation of soil moisture is most promising, the observation operator exhibits little variability in time. The temporal variability in the observation operator can result in substantial differences between the modeled field and the observation. In Numerical Weather Prediction (NWP) applications, where the model tends to be updated on a regular basis, dynamic observation operators will be necessary to assimilate soil moisture. For climate studies or re‐analysis projects long time series are required to define an observation operator, which correctly reproduces interannual variability.
Coupling VIC with GCM models to predict climate change impact in the Hanjiang basin, China.

A Smooth Support Vector Machine (SSVM) is proposed for statistical downscaling of daily precipitation and temperature from GCM output. The Variable Infiltration Capacity (VIC) distributed hydrological model with a 9 x 9 km 2 grid resolution is established and calibrated in the Hanjiang basin of China. Validation results show that SSVM can approximate observed precipitation and temperature data reasonably well, and the VIC model can simulate the runoff hydrograph with high model efficiency and low relative error. By applying the SSVM model, the trends of precipitation and temperature projected from CGCM2 under the A2 and B2 scenarios will decrease in the 2020s, and increase in the 2080s. However, in the 2050s, the precipitation will decrease under the A2 scenario and there will be no significant changes under the B2 scenario, but the temperature will be not obviously change under either scenario. Under both scenarios, the impact analysis of runoff made with the downscaled precipitation and temperature time series as input to the VIC distributed model, resulted in a decreasing trend for the 2020s and 2050s, and an overall increasing trend for the 2080s.
Massively parallel CUDA simulations of cardiac and embryonic MRI on a cloud-based cluster

Embryonic and cardiovascular Magnetic Resonance Imaging (MRI) in both clinic and research environments is confronted by challenges like motion, flow and low resolution. MRI simulations can be used as a valuable tool against these challenges but they are characterized by high computational intensity. In this study we implemented cardiac and embryonic MR simulations on a cloud-based cluster. For this purpose, an anatomical model of a human embryo was split over a variable number of computer nodes on the cloud. Simulation of a Gradient-Echo pulse sequence was performed and the partial results were aggregated in a central node to produce the simulated MR image, following the MapReduce paradigm. The measured execution times and speedups demonstrated the benefits of this cloud-based approach.
THE ROLE OF TCF7L2 IN THE GENERATION OF OLIGODENDROCYTES DURING DEVELOPMENT

I certify that this student has met the requirements for format contained in the University format manual, and that this project is suitable for shelving in the Library and credit is to be awarded for the project. One of the major obstacles to myelin repair in multiple sclerosis is the failure of endogenous oligodendrocyte progenitor cells (OPCs) to differentiate into mature oligodendrocytes (OLs). Transcription factor 7-like 2 (TCF7l2), also known as TCF4, is a transcriptional effector that mediates canonical Wnt/β-catenin signaling in Wnt-responsive cells. The role of TCF7l2 in the generation of OPCs from neural stem cells (NSCs) is unknown, although canonical Wnt/β-catenin signaling has been shown to inhibit NSCs from generating OPCs. To study the role of TCF7l2 in OPC differentiation, we conditionally ablated TCF7l2 in Olig2+ cells and Cnpase+ cells (neural stem cells and OPCs) in the developing mouse spinal cord. We analyzed embryonic spinal cord tissues for changes in the OPC population and found decreased OPCs in TCF7l2 knockout mice. We also investigated whether TCF7l2 exerts its effects in OLs in a Wnt-independent manner during neural development using the Wnt reporter mouse strain BAT-lacZ. Our vi data show that TCF7l2 deletion does not affect Wnt/β-catenin signaling, indicating that TCF7l2's effects in OPC generation is Wnt-independent. Contrary to previous findings, our data show that TCF7l2 in fact promotes oligodendrogenesis, and that it does so independent of the Wnt/β-catenin pathway. _______________________ Date vii ACKNOWLEDGEMENTS I would first like to thank David Pleasure for his invaluable mentorship and guidance. I consider myself lucky to have had the chance to learn from you. I would also like to thank Fuzheng Guo for the many opportunities he has given me to grow as a scientist. Thank you, Fuzheng, for challenging me to think critically and for encouraging me to have confidence in myself.
Maximum profit mining and its application in software development

While most software defects (i.e., bugs) are corrected and tested as part of the lengthy software development cycle, enterprise software vendors often have to release software products before all reported defects are corrected, due to deadlines and limited resources. A small number of these defects will be escalated by customers and they must be resolved immediately by the software vendors at a very high cost. In this paper, we develop an Escalation Prediction (EP) system that mines historic defect report data and predict the escalation risk of the defects for maximum net profit. More specifically, we first describe a simple and general framework to convert the maximum net profit problem to cost-sensitive learning. We then apply and compare several well-known cost-sensitive learning approaches for EP. Our experiments suggest that the cost-sensitive decision tree is the best method for producing the highest positive net profit and comprehensible results. The EP system has been deployed successfully in the product group of an enterprise software vendor.
Epidemic thresholds in real networks

How will a virus propagate in a real network? How long does it take to disinfect a network given particular values of infection rate and virus death rate? What is the single best node to immunize? Answering these questions is essential for devising network-wide strategies to counter viruses. In addition, viral propagation is very similar in principle to the spread of rumors, information, and “fads,” implying that the solutions for viral propagation would also offer insights into these other problem settings. We answer these questions by developing a nonlinear dynamical system (NLDS) that accurately models viral propagation in any arbitrary network, including real and synthesized network graphs. We propose a general epidemic threshold condition for the NLDS system: we prove that the epidemic threshold for a network is exactly the inverse of the largest eigenvalue of its adjacency matrix. Finally, we show that below the epidemic threshold, infections die out at an exponential rate. Our epidemic threshold model subsumes many known thresholds for special-case graphs (e.g., Erdös--Rényi, BA powerlaw, homogeneous). We demonstrate the predictive power of our model with extensive experiments on real and synthesized graphs, and show that our threshold condition holds for arbitrary graphs. Finally, we show how to utilize our threshold condition for practical uses: It can dictate which nodes to immunize; it can assess the effects of a throttling policy; it can help us design network topologies so that they are more resistant to viruses.
A Hybrid Music Recommendation System by M-LSA

In this paper, a hybrid music recommendation system is proposed, which combines collaborative filtering and content-base recommendation. Neither of these two parts can make full use of all the information. Our method integrates both user rating and music content information using an expansion method of LSA (Latent Semantic Analysis) called M-LSA. We use a text representation for music content information, which is obtained by K-means Clustering or HMM method. Experiments on the data of 300 popular songs show that the proposed approach achieves satisfactory results.
EMERGING OPPORTUNITIES AND RISKS IN MASSIVELY MULTIPLAYER ONLINE ROLE PLAYING GAMES

Massively Multiplayer Online Role Playing Games (MMORPG’s) are highly immersive environments which promote and sustain hyper personal interaction amongst players. This body of work aimed to identify, compare and draw conclusions from existing and ongoing research on player behaviour, motivations, addiction, data disclosure and the potential for harm in MMORPGs. Two quantitative survey based studies and a series of semi structured interviews formed the evidence base for the research findings. The first quantitative study consisted of European participants (n=357) and the second of Singaporean participants (n=188). In addition the European study encompassed qualitative findings from semi structured interviews. Player behaviour was measured using Bolino and Turnley’s (2003) Impression Management (IM) Scale adapted to fit the context of online gaming. An adapted Basic Psychological Needs scale from Deci and Ryan’s (2000) Self Determination Theory (SDT) was used to measure the degree to which online gaming fulfils the basic psychological needs of the participant gamer. Addiction was measured using the Game Addiction Scale (GAS) developed by Lemmens et. al. (2009) and data disclosure was measured and scored based on the number of data types previously disclosed within MMORPG environments. Participants exhibited varying levels of addiction and over half were found to be high level disclosers of personal and sensitive data, making them potentially more vulnerable to exploitation and predation. Hours of game play was found to
The effects of stress states in the brain

The objective of this study is to assess the interaction between brain activity for cognitive and emotional processing and stress states in the healthy adults. The brain activities of thirty-three healthy adults divided into stress and non-stress groups according to their stress responses were assessed during emotional audio-visual stimuli using functional magnetic resonance imaging (fMRI). The results showed that a significant correlation was found between the profile of mood states (POMS) subscale scores for Fatigue and the right inferior parietal gyrus in the Relaxed stimuli (r=−0.359), and POMS subscale scores for Depression-Defection and the right inferior parietal gyrus in the Unpleasant stimuli (r=−0.371). These results suggest that the beginnings of stress states, especially the depression or fatigue states, represent deficits in the attention process.