Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing Relationships for System Dynamics Models Supported by Exploratory Data Analysis - A Conceptualizing Approach about the Meeting Diversity in Student Software Projects

Estimating dynamic components in projects involves understanding human factors which are substantial in software development. Communication and collaboration in teams consist of social-driven characteristics with influences on the continuous delivery of software. Efficiently estimated meetings become increasingly important due to budget calculations and shortened release cycles. Experiences of project managers combined with retrospectives on historical data records support a better understanding of team dynamics. But interpreting complex effects is not always trivial, in particular without further analyzes. In several studies, information relationships are investigated through linear correlation measures. Additional analyses for higher correlations are often neglected due to the advanced functional characterization. This leads to statistical gaps with significances for explored data relationships and their functional interpretation. In this paper, we present a systematic identification and visualization of team communication effects and diversities for field study records of 34 student software projects. We combine methodologies from system dynamics with exploratory data analysis to extract and emphasize significant effects. These insights help to sensitize for advanced investigations about the statistical measures of correlation and to interpret sophisticated structures. Furthermore, it reinforces potentials for a team’s communication performances and enables an enhanced understanding about how student teams meet and communicate. Keywords— Team dynamics; exploratory data analysis; data visualization; student software projects
Evaluating Readability on Mobile Devices

The thesis presents findings from five readability studies performed on mobile devices. The dynamic Rapid Serial Visual Presentation (RSVP) format has been enhanced with regard to linguistic adaptation and segmentation as well as eye movement modeling. The novel formats have been evaluated against other common presentation formats including Paging, Scrolling, and Leading in latin-square balanced repeated-measurement studies with 12-16 subjects. Apart from monitoring Reading speed, Comprehension, and Task load (NASA-TLX), Eye movement tracking has been used to learn more about how the text presentation affects reading.The Page format generally offered best readability. Reading on a mobile phone decreased reading speed by 10% compared to reading on a Personal Digital Assistant (PDA), an interesting finding given that the display area of the mobile phone was 50% smaller. Scrolling, the most commonly used presentation format on mobile devices today, proved inferior to both Paging and RSVP. Leading, the most widely known dynamic format, caused very unnatural eye movements for reading. This seems to have increased task load, but not affected reading speed to a similar extent. The RSVP format displaying one word at time was found to reduce eye movements significantly, but contrary to common claims, this resulted in decreased reading speed and increased task load. In the last study, Predictive Text Presentation (PTP) was introduced. The format is based on RSVP and combines linguistic chunking and adaptation with eye movement modeling to achieve a reading experience that can rival traditional text presentation.It is explained why readability on mobile devices is important, how it may be evaluated in an efficient and yet reliable manner, and PTP is pinpointed as the format with greatest potential for improvement. The methodology used in the evaluations and the shortcomings of the studies are discussed. Finally, a hyper-graeco-latin-square experimental design is proposed for future evaluations.
OxMaR: Open Source Free Software for Online Minimization and Randomization for Clinical Trials

Minimization is a valuable method for allocating participants between the control and experimental arms of clinical studies. The use of minimization reduces differences that might arise by chance between the study arms in the distribution of patient characteristics such as gender, ethnicity and age. However, unlike randomization, minimization requires real time assessment of each new participant with respect to the preceding distribution of relevant participant characteristics within the different arms of the study. For multi-site studies, this necessitates centralized computational analysis that is shared between all study locations. Unfortunately, there is no suitable freely available open source or free software that can be used for this purpose. OxMaR was developed to enable researchers in any location to use minimization for patient allocation and to access the minimization algorithm using any device that can connect to the internet such as a desktop computer, tablet or mobile phone. The software is complete in itself and requires no special packages or libraries to be installed. It is simple to set up and run over the internet using online facilities which are very low cost or even free to the user. Importantly, it provides real time information on allocation to the study lead or administrator and generates real time distributed backups with each allocation. OxMaR can readily be modified and customised and can also be used for standard randomization. It has been extensively tested and has been used successfully in a low budget multi-centre study. Hitherto, the logistical difficulties involved in minimization have precluded its use in many small studies and this software should allow more widespread use of minimization which should lead to studies with better matched control and experimental arms. OxMaR should be particularly valuable in low resource settings.
Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis

Motivation: Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how to tailor drug therapies. New methods are required for integrated analyses of a large number of chemical features of drugs against the corresponding genome-wide responses of multiple cell models. Results: In this article, we present the first comprehensive multi-set analysis on how the chemical structure of drugs impacts on genome-wide gene expression across several cancer cell lines [Connectivity Map (CMap) database]. The task is formulated as searching for drug response components across multiple cancers to reveal shared effects of drugs and the chemical features that may be responsible. The components can be computed with an extension of a recent approach called Group Factor Analysis. We identify 11 components that link the structural descriptors of drugs with specific gene expression responses observed in the three cell lines and identify structural groups that may be responsible for the responses. Our method quantitatively outperforms the limited earlier methods on CMap and identifies both the previously reported associations and several interesting novel findings, by taking into account multiple cell lines and advanced 3D structural descriptors. The novel observations include: previously unknown similarities in the effects induced by 15-delta prostaglandin J2 and HSP90 inhibitors, which are linked to the 3D descriptors of the drugs; and the induction by simvastatin of leukemia-specific response, resembling the effects of corticosteroids. Availability and implementation: Source Code implementing the method is available at: http://research.ics. aalto.fi/mi/software/GFAsparse Contact: suleiman.khan@aalto.fi or samuel.kaski@aalto.fi Supplementary Information: Supplementary data are available at Bioinformatics online.
Tropical Aquatic Archaea Show Environment-Specific Community Composition

The Archaea domain is ubiquitously distributed and extremely diverse, however, environmental factors that shape archaeal community structure are not well known. Aquatic environments, including the water column and sediments harbor many new uncultured archaeal species from which metabolic and ecological roles remain elusive. Some environments are especially neglected in terms of archaeal diversity, as is the case of pristine tropical areas. Here we investigate the archaeal composition in marine and freshwater systems from Ilha Grande, a South Atlantic tropical environment. All sampled habitats showed high archaeal diversity. No OTUs were shared between freshwater, marine and mangrove sediment samples, yet these environments are interconnected and geographically close, indicating environment-specific community structuring. Group II Euryarchaeota was the main clade in marine samples, while the new putative phylum Thaumarchaeota and LDS/RCV Euryarchaeota dominated freshwaters. Group III Euryarchaeota , a rare clade, was also retrieved in reasonable abundance in marine samples. The archaeal community from mangrove sediments was composed mainly by members of mesophilic Crenarchaeota and by a distinct clade forming a sister-group to Crenarchaeota and Thaumarchaeota. Our results show strong environment-specific community structuring in tropical aquatic Archaea, as previously seen for Bacteria.
Approximate Methods for Maximum Likelihood Estimation of Multivariate Nonlinear Mixed-Effects Models

Multivariate nonlinear mixed-effects models (MNLMM) have received increasing use due to their flexibility for analyzing multi-outcome longitudinal data following possibly nonlinear profiles. This paper presents and compares five different iterative algorithms for maximum likelihood estimation of the MNLMM. These algorithmic schemes include the penalized nonlinear least squares coupled to the multivariate linear mixed-effects (PNLS-MLME) procedure, Laplacian approximation, the pseudo-data expectation conditional maximization (ECM) algorithm, the Monte Carlo EM algorithm and the importance sampling EM algorithm. When fitting the MNLMM, it is rather difficult to exactly evaluate the observed log-likelihood function in a closed-form expression, because it involves complicated multiple integrals. To address this issue, the corresponding approximations of the observed log-likelihood function under the five algorithms are presented. An expected information matrix of parameters is also provided to calculate the standard errors of model parameters. A comparison of computational performances is investigated through simulation and a real data example from an AIDS clinical study.
Asperger Syndrome in India: Findings from a Case-Series with Respect to Clinical Profile and Comorbidity

Asperger syndrome (AS) is an autism spectrum disorder with a high rate of psychiatric comorbidity. We describe the clinical profile and psychiatric comorbidity in a series of affected individuals referred to an Indian general hospital psychiatry setting. Gilliam Asperger's disorder scale was used to evaluate the clinical characteristics while Mini-International Neuropsychiatric Interview (MINI)-KID and MINI-PLUS were used to assess psychiatric comorbidity. The profile of subjects with AS in our case-series appears similar to that published elsewhere with high rates of psychiatric comorbidity. Mental health professionals should evaluate for psychiatric comorbidity in individuals with autism spectrum disorders.
Influence of opioid-related side effects on disability, mood, and opioid misuse risk among patients with chronic pain in primary care

Background: There is increasing concern among primary care practitioners about the use of opioids for chronic pain, including their adverse effects, but little attention has been given to how reports of side effects from prescription medication can contribute to outcomes among patients with chronic pain. The aim of this study was to investigate the impact of frequently reported side effects on mood, disability, and opioid misuse in patients with chronic pain prescribed opioids within primary care. Methods: Two hundred (N = 200) patients with chronic pain taking opioids for pain were recruited into the study. All patients completed baseline measures and a monthly side effects checklist once a month for 6 months. Patients were divided evenly based on a median split of the number of endorsed side effects over 6 months. The subjects repeated the baseline measures at the end of the study period. Results: Over time, reports of medication side effects tended to decrease, but differences in frequency of reported side effects from baseline to follow-up (6-month time) were not significant, and the order of the frequency of the reported side effects remained similar. Patients who reported significant medication-related adverse effects reported significantly greater activity interference, negative affect, and catastrophizing compared with those with fewer side effects (P < 0.01). In addition, those patients with pain who reported more side effects showed significantly higher scores on opioid misuse risk (P < 0.001). Discussion: This study demonstrates the important role of monitoring medication-related side effects among patients with chronic pain who are prescribed opioid medication for pain within primary care.
Evaluation of adaptive management techniques in NoC-Based MPSoCs

Self-adaptation capability is as a key feature to meet runtime application requirements in dynamic systems such as NoC-Based MPSoCs. This paper presents an evaluation of adaptive management techniques combined with task monitoring, which are able to change at runtime the communication priority, the tasks scheduling priority and execute task migration. The monitoring is designed based on application profiling. The obtained results in terms execution time, latency and jitter, demonstrate the feasibility of such approach and the ability to support real-time applications.
Primary care groups: Improving the quality of care through clinical governance.

This is the third in a series of five articles The UK government has set a challenging agenda for monitoring and improving the quality of health care. It is based on a series of national standards and guidelines, a strategy for quality improvement termed “clinical governance,” and a framework for monitoring the quality of care in and performance of NHS organisations (box). Clinical governance is “a framework through which NHS organisations are accountable for continually improving the quality of their services, safeguarding high standards by creating an environment in which excellence in clinical care will flourish. ”1 To be successful this strategy requires effective leadership by clinicians who have responsibility for improving quality; it must engage the doctors and nurses who provide care on a daily basis; and it must have commitment and support from managers within the NHS. #### Summary points Primary care groups and trusts are responsible for implementing clinical governance, including monitoring and improving the quality of care In their first two years they have concentrated on educating and supporting health professionals and encouraging shared learning Information about the quality of care provided in general practice is being shared between practices and with the public, often in a form that permits practices to be identified Many groups and trusts are offering incentives to practices to promote improvements in the quality of care Sanctions and disciplinary action are rarely used when dealing with poor performance Limited resources and the pace of change are potential obstacles to future success in improving the quality of care #### Goals of quality improvement strategies in the NHS National service frameworks, National Institute for Clinical Excellence —set standards, develop guidelines Clinical governance —deliver care, improve quality National performance framework, annual appraisal of doctors, Commission for Health Improvement, national surveys of patients —monitor quality and performance Primary care groups and trusts are responsible for implementing clinical …
Title : Adenovirus-mediated transfer of siRNA against survivin enhances the radiosensitivity of human non-small cell lung cancer cells

1. Division of Pulmonary and Critical Care Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan 2. Department of Respiratory Care, College of Medicine, Chang Gung University, Taoyuan, Taiwan 3. Graduate Institute of Animal Science, College of Agriculture, National Chiayi University, Chiayi, Taiwan 4. Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan 5. Department of Radiation Oncology, Chang Gung Memorial Hospital, Chiayi, Taiwan.
Pathways to mental health in young adulthood and beyond: The long-term effects of childhood experiences expressed through self-esteem

ii Acknowledgments iii Table of Contents iv List of Tables viii List of Figures ix List of Appendices x Chapter 1 1 1 Introduction 1 Chapter 2 3 2 Background and literature review 3 2.1 Stress process in Cumulative Advantage/Disadvantage perspective 4 2.1. 1 Path dependent processes 4 2.1. 2 Duration dependent processes 5 2.1. 3 Joint Stressors Processes 5 2.2 The role of linked lives in the stress process paradigm 6 2.2.1 Linked lives as a primary source of stressors: shared context and interaction 6 2.2.2 Linked lives as a secondary source of stressors: stress proliferation between family members 8 2.2.3 Linked lives as a source of stress mediator: support 8 2.3 Coping and the stress process paradigm: Taking agency into consideration . 11 2.3.1 Coping by changing the stressful situation 12 2.3.2 Coping by managing the meaning of stressful situation 12 2.3. 3 Coping by dealing with the stress symptoms 13 2.4 Applying agency as coping throughout life course 14 v 2.4. 1 Agency in the social causation and selection process 14 2.4. 2 The buffering effect of agency 16 2.4. 3 Agency and coping efforts 17 2.4. 4 The long-term effect of agency 18 2.4. 5 Agency as subject to change in structural constraints 20 2.4. 6 Intertwined structure and agency throughout the life course 21 2.4. 7 Agency in linked lives: a potential interactive process 22 2.5 Conceptual model and research questions 24 Chapter 3 29 3 Data and Variables 29 3.1 Data 29 3.2 Variables 31 3.2.1 Stress outcomes: Focal Child’s depressed affect in early adulthood . 31 3.2.2 Early stress exposure: Focal Child’s exposure to economic strain in adolescence 33 3.2.3 Early stress exposure: Focal Child’s experience of family instability before 18 33 3.2.4 Social statuses and stress exposure in young adulthood: Focal Child’s personal income status 34 3.2.5 Social statuses and stress exposure in young adulthood: Focal Child’s educational attainment 34 3.2. 6 Social statuses and stress exposure in young adulthood: Focal Child’s relationship status 35 3.2. 7 Social statuses and stress exposure in young adulthood: Focal Child’s parenthood status 35 3.2. 8 Coping resource: Focal Child’s self-esteem in adolescence and young adulthood 35 3.2. 9 Perceived support in adolescence and young adulthood: support from parents/parental figures 36
THE EFFECTS OF QOS LEVEL DEGRADATION COST ON PROVIDER SELECTION AND TASK ALLOCATION MODEL IN TELECOMMUNICATION NETWORKS

Firms acquire network capacity from multiple suppliers which offer different Quality of Service (QoS) levels. After acquisition, day-to-day operations such as video conferencing, voice over IP and data applications are allocated between these acquired capacities by considering QoS requirement of each operation. In optimal allocation scheme, it is generally assumed each operation has to be placed into resource that provides equal or higher QoS Level. Conversely, in this study it is showed that former allocation strategy may lead to suboptimal solutions depending upon penalty cost policy to charge degradation in QoS requirements. We model a cost minimization problem which includes three cost components namely capacity acquisition, opportunity and penalty due to loss in QoS.
Cell Cycle , Cell Death , and Senescence Inactivation of Heat Shock Factor Hsf 4 Induces Cellular Senescence and Suppresses Tumorigenesis In Vivo

Studies suggest that Hsf4 expression correlates with its role in cell growth and differentiation. However, the role of Hsf4 in tumorigenesis in vivo remains unexplored. In this article, we provide evidence that absence of the Hsf4 gene suppresses evolution of spontaneous tumors arising in p53orArf-deficientmice. Furthermore, deletion of hsf4 alters the tumor spectrum by significantly inhibiting development of lymphomas that are normally observed in the majority of mice lacking p53 or Arf tumor suppressor genes. Using mouse embryo fibroblasts deficient in the hsf4 gene, we have found that these cells exhibit reduced proliferation that is associated with induction of senescence and senescence-associated b-galactosidase (SA-b-gal). Cellular senescence in hsf4-deficient cells is associated with the increased expression of the cyclin-dependent kinase inhibitors, p21 and p27 proteins. Consistent with the cellular senescence observed in vitro, specific normal tissues of hsf4 / mice and tumors that arose in mice deficient in both hsf4 and p53 genes exhibit increased SA-b-gal activity and elevated levels of p27 compared with wild-type mice. These results suggest that hsf4 deletion-induced senescence is also present in vivo. Our results therefore indicate that Hsf4 is involved in modulation of cellular senescence, which can be exploited during cancer therapy.Mol Cancer Res; 1–12. 2012 AACR.
Predicting the quality of service of wireless LANs using neural networks

Wireless Local Area Networks (WLANs) are particularly difficult to manage due to the highly dynamic nature of the traffic, caused by variations on the number of users, their locations and the type applications they use. In this paper, we propose a new modeling approach, based on neural networks, that is able to predict the Quality of Service (QoS) of WLANs based on the characterization of an operational scenario. From measurements of the inbound and outbound traffic at each Access Point (AP) and of the QoS perceived at each Cell, the model estimates the QoS when the number of users grows. The model does not require the knowledge of the exact network characteristics, since it is only based on measurements carried out at the APs. This modeling approach can be of great help in the planning and management of WLANs. Several realistic network scenarios were defined in order to test the validity of the model. The results show that the model can achieve excellent performance, since the QoS prediction is accurate even when there are significant changes in the number of users.
Exact Statistical Methods for Data Analysis

provide highly technical, but readable, reviews on nonlinear optimization and on eigenvalues and singular value decomposition in the context of linear estimation. This book contains considerable information on the concept of statistical learning theory and various applications that relate to characterizing the dependencies in collected data. However, some may  nd its presentation dif cult to follow, partly because of the complex issues being presented, and as a result will need to review the material carefully several times to really understand what is being presented. The authors seem to be aware of this because they admit in the book’s introduction that this book “is not an easy read. ”
Fast Distributed Agreement

We describe a Byzantine Agreement algorithm, with early stopping, for systems with arbitrary process failures. The algorithm presented is simpler and more efficient than those previously known. It was derived using a broadcast primitive that provides properties of message authentication and thus restricts the disruptive behavior of faulty processes. This primitive is a general tool for deriving fault-tolerant algorithms in the presence of arbitrary failures.