Miracle-dz/UniFAR-FTUs huggingface dataset:
23 2 Designing an Outcomes Research Study

A health outcomes research study design is a plan for executing the study. At a minimum, the design depicts the groups studied; for example, treatment and control group, instances of the treatment and the timing, and frequency of health outcomes measures. The design provides a high-level overview of the health outcomes study and insights into the plan for analysis. Finally, the design should specify whether the individuals studied are randomly assigned to either receive the treatment of interest or no treatment , also referred to as a control group. Control over treatment assignment through randomization is the basis for distinguishing two types of outcomes studies: experiments and quasi-experiments. Random assignment of subjects is central to controlling for extraneous differences between groups, but it does not guarantee comparability ; it simply asserts that any differences are due to chance. Without randomization of study participants, the outcomes researcher runs the risk of individuals with particular characteristics having a higher probability of being included in the study or one of the study groups. These differences can arise from patient self-selection or from clinician decisions about who should get treatment. Selection bias or self-selection has the potential to confound the treatment-outcome relationship, thereby biasing results. Some of these differences can be measured and controlled for in the analysis , but others may remain unmeasured and uncorrected. Overall, selection bias may be the greatest threat to the validity of health outcomes research studies.
Finite-time stabilization of nonlinear impulsive dynamical systems

Finite-time stability involves dynamical systems whose trajectories converge to an equilibrium state in finite time. For continuous-time dynamical systems finite-time convergence implies nonuniqueness of system solutions in reverse time, and hence, such systems possess non-Lipschitzian dynamics. For impulsive dynamical systems, however, it may be possible to reset the system states to an equilibrium state achieving finite-time convergence without requiring non-Lipschitzian system dynamics. In this paper, we develop sufficient conditions for finite-time stability of impulsive dynamical systems involving both scalar and vector Lyapunov functions. Furthermore, we design hybrid finite-time stabilizing controllers for impulsive dynamical systems that are robust against full modeling uncertainty. Finally, we present a numerical example for finite-time stabilization of large-scale impulsive dynamical systems.
Current State of Data

This report is a compendium of results uncovered in CS 851, spring semester 2002. Our goal is to provide direction to other graduate students who want to explore the fascinating eld of \data mining". Be aware that this represents the topics and the papers that we found most interesting. We made no attempt to be either \fair" or to be \comprehensive" as in a Computing Reviews article. Instead we tried to pick just one or two references in each of our interest areas that were both relatively recent and, in our opinion, worth reading. Their bibliographies can direct a reader to other sources.
Simulation of the Adaptive Multivariate Exploration for Routes Guidance

Nowadays, Navigation systems have become very popular and necessary for travelers from all around the world. Navigation systems give travelers all the information they need and guide them quickly and comfortably to get to the destination. Pre-trip planning regarding road and traffic conditions can enhance driver's knowledge of the situation in road networks and can assist in drivers' decisions concerning routes and departure times. Many factors such as the route density, traffic volume, departure time, destination, workday, working time, holiday period, tournaments and events are important to find the best route under the criterion. In this paper presented two new models with the purpose of recommending travelers the best route to destination. These two models are the multivariate class exploration and route guidance models. The multivariate class exploration model analyzes the network-flow patterns in order to investigate some important factors such as demand conditions, compliance with information, speed and variance of travel-time and calculate a travel-time reduction. A route guidance model was used to find efficient routes (minimizing travel time) for traveling. This paper conducted experiments on a real-world dataset collected from the OpenStreetMap. The accuracy of the proposed model's predictions was determined. The results show that the predictions given by the models are accurate and can be used in real-life situations.
MICRO-ELECTROHYDRODYNAMIC PUMP BY DIELECTRIC FLUID: IMPROVEMENT FOR PERFORMANCE OF PRESSURE USING CYLINDRICAL ELECTRODES

This paper presents the improvements for the performance of a micro-electrohydrodynamic (EHD) pump and the fundamental model theory based on unipolar charge conduction. The EHD pump was fabricated with thin stainless wires which are the diameter of 0.3mm. An electrode pair consisted of one emitter electrode and two collector electrodes. The distance between the emitter and the collector electrode in an electrode pair had a 0.2mm. Static pressure tests have been performed with a dielectric fluid. In order to increase the pressure performance, the electrode pair was increased from one to five at the distance between the electrode pairs, 2.0mm. As a result, it is found that the increase of the electrode pairs improve the pressure performance. The EHD pump produces a static pressure about 700 Pa with five electrode pairs using Dibutyl Sebacate. Both experimental and theoretical pressure results show a liner relationship. This linear relationship confirmed the unipolar conduction concept theoretically.
Information Scent and Web Navigation: Theory, Models, and Automated Usability Evaluation

Within a more Information Foraging Theory, we have developed a rational analysis of Web use, which has shaped a cognitive model of Web navigation called SNIF-ACT. An automated and practical method for initializing the model with requisite knowledge of information scent was developed based on Pointwise Mutual Information (PMI) computations from a local document corpus with a Web back-off. An automated Web usability tool called Bloodhound was developed that implements an algorithm that approximates the operation of the cognitive model. We report on succesful empirical tests of the SNIF-ACT cognitive mode, the PMI method, and Bloodhound.
Free Energy of Electric Double Layer. Effect of Ion Size.

An expression for the free energy of an electric double layer is derived. A method of undetermined multipliers is applied within a simple statistical mechanical approach. The electrostatic interactions are described by the mean electrostatic field while the finite size of particles, constituting the electrolyte solution, is considered by the excluded volume effect. The particles in the solution are distributed over a lattice with an adjustable constant. The free energy is derived for any composition of ions and any ion valency allowing the mean electrostatic field to vanish far from the charged plane.
Bridging the Gaps in Bringing in the Bystander: An Intersectional Approach to Campus-Based Sexual Violence Prevention

This paper draws upon pilot-test data from an intersectional approach to a sexual violence prevention program on university campuses. While many programs have been created to address the sexual violence epidemic, many focus heavily on white, heterosexual, and cisgender scenarios. This research utilizes the Bringing in the Bystander® workshop, a community-based prevention initiative focused on preventing sexual violence through inspiring students to intervene in pro-social ways. In this analysis, the program maintained the same pedagogical structure, but contained a wider variety of narratives designed to include stories and scenarios about contexts relevant to the experiences of LGBTQ+ and racialized students. A pilot test was conducted using a pre-and post-test design. The researchers tested for: knowledge about sexual violence, (including an intersectional understanding of the issue), efficacy for intervening, and attitudes such as empathy and rape myth acceptance. Changes were present from preto postworkshop for readiness to change, empathy for survivors, and perceptions of intervention capabilities for intersectional bystander scenarios. Results suggest that diversifying content leads to desirable outcomes for students.
Innocent Strategies are Sheaves over Plays - Deterministic, Non-deterministic and Probabilistic Innocence

Although the HO/N games are fully abstract for PCF, the traditional notion of innocence (which underpins these games) is not satisfactory for such language features as non-determinism and probabilistic branching, in that there are stateless terms that are not innocent. Based on a category of P-visible plays with a notion of embedding as morphisms, we propose a natural generalisation by viewing innocent strategies as sheaves over (a site of) plays, echoing a slogan of Hirschowitz and Pous. Our approach gives rise to fully complete game models in each of the three cases of deterministic, nondeterministic and probabilistic branching. To our knowledge, in the second and third cases, ours are the first such factorisation-free constructions.
Dynamical Torque in CoxFe3–xO4 Nanocube Thin Films Characterized by Femtosecond Magneto-Optics: A π-Shift Control of the Magnetization Precession

For spintronic devices excited by a sudden magnetic or optical perturbation, the torque acting on the magnetization plays a key role in its precession and damping. However, the torque itself can be a dynamical quantity via the time-dependent anisotropies of the system. A challenging problem for applications is then to disentangle the relative importance of various sources of anisotropies in the dynamical torque, such as the dipolar field, the crystal structure or the shape of the particular interacting magnetic nanostructures. Here, we take advantage of a range of colloidal cobalt ferrite nanocubes assembled in 2D thin films under controlled magnetic fields to demonstrate that the phase, ϕPrec, of the precession carries a strong signature of the dynamical anisotropies. Performing femtosecond magneto-optics, we show that ϕPrec displays a π-shift for a particular angle θH of an external static magnetic field, H. θH is controlled with the cobalt concentration, the laser intensity, as well as the interparticle interactions. Importantly, it is shown that the shape anisotropy, which strongly departs from those of equivalent bulk thin films or individual noninteracting nanoparticles, reveals the essential role played by the interparticle collective effects. This work shows the reliability of a noninvasive optical approach to characterize the dynamical torque in high density magnetic recording media made of organized and interacting nanoparticles.
Text mining in radiology reports

Text mining is a popular research topic with application areas ranging from security to media and marketing. More specifically, text mining has been applied in biomedical area for the categorization of radiology reports, which is a challenging problem due to their free-text and unstructured format. State-of-the-art in radiology report mining has mostly focused on English text, while studies on Turkish reports are scarce. Accordingly, in this work we propose to employ text mining for categorization of Turkish radiology reports. We automatically remove header and footer of the reports, apply frequency analysis on the remaining report text, and perform categorization of reports to anatomical regions using pre-selected keywords. The accuracy of the proposed solution is measured as 84.3% over a 66-report test set.
Towards Multi-Component Analysis of Gas Turbines by CFD: Integration of RANS and LES Flow Solvers

The numerical prediction of the entire aero-thermal o w through an entire gas turbine is currently limited by its high computational costs. The approach presented here intends to use several specialized o w solvers based on the Reynolds-averaged Navier-Stokes equations (RANS) as well as Large Eddy Simulations (LES) running simultaneously and exchanging information at the interfaces. This study documents the development of the interface and proves its accuracy and efcienc y on simple testcases. Compressor computation currently underway
Global Regulation of Nucleotide Biosynthetic Genes by c-Myc

Background The c-Myc transcription factor is a master regulator and integrates cell proliferation, cell growth and metabolism through activating thousands of target genes. Our identification of direct c-Myc target genes by chromatin immunoprecipitation (ChIP) coupled with pair-end ditag sequencing analysis (ChIP-PET) revealed that nucleotide metabolic genes are enriched among c-Myc targets, but the role of Myc in regulating nucleotide metabolic genes has not been comprehensively delineated. Methodology/Principal Findings Here, we report that the majority of genes in human purine and pyrimidine biosynthesis pathway were induced and directly bound by c-Myc in the P493-6 human Burkitt's lymphoma model cell line. The majority of these genes were also responsive to the ligand-activated Myc-estrogen receptor fusion protein, Myc-ER, in a Myc null rat fibroblast cell line, HO.15 MYC-ER. Furthermore, these targets are also responsive to Myc activation in transgenic mouse livers in vivo. To determine the functional significance of c-Myc regulation of nucleotide metabolism, we sought to determine the effect of loss of function of direct Myc targets inosine monophosphate dehydrogenases (IMPDH1 and IMPDH2) on c-Myc-induced cell growth and proliferation. In this regard, we used a specific IMPDH inhibitor mycophenolic acid (MPA) and found that MPA dramatically inhibits c-Myc-induced P493-6 cell proliferation through S-phase arrest and apoptosis. Conclusions/Significance Taken together, these results demonstrate the direct induction of nucleotide metabolic genes by c-Myc in multiple systems. Our finding of an S-phase arrest in cells with diminished IMPDH activity suggests that nucleotide pool balance is essential for c-Myc's orchestration of DNA replication, such that uncoupling of these two processes create DNA replication stress and apoptosis.
What is Your Selfie Worth? A Field Study on Individuals' Valuation of Personal Data

Referred to as the new oil, undoubtedly personal data is a valuable resource for organizations. Contrary, it is still blurred, to what extent individuals value their data even though, in a digitized world, users are requested to exchange their data for adequate services. Former research on individuals’ valuation of personal data result in scattered, partly contradictious values, depending on the data type, context, and the measurement method. In this study, we aimed to facilitate the valuation for individuals by applying a new and promising measurement methodology: the participants of our field experiment had the chance to sell their selfies in a name-your-own-price auction with repeated bidding and feedback loops. As a result, 39% of our participants were willing to donate or sell their selfies with a median of 5€. Additionally, bidding clusters were identified. Implications for research on the valuation of personal data in terms of privacy are discussed.
Casualty Modeling for Real-Time Medical Training

We present a model for simulating casualties in virtual environments for real-time medical training. It allows a user to choose diagnostic and therapeutic actions to carry out on a simulated casualty who will manifest appropriate physiological, behavioral, and physical responses. Currently, the user or a stealth instructor can specify one or more injuries that the casualty has sustained. The model responds by continuously determining the state of the casualty, responding appropriately to medical assessment and treatment procedures. So far, we have modeled four medical conditions and over 20 procedures. The model has been designed to handle the addition of other injuries and medical procedures.
Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events

In nowadays social networks, a huge volume of content containing rich information, such as reviews, ratings, microblogs, etc., is being generated, consumed and diffused by users all the time. Given the temporal information, we can obtain the event cascade which indicates the time sequence of the arrival of information to users. Many models have been proposed to explain how information diffuses. However, most existing models cannot give a clear explanation why every specific event happens in the event cascade. Such explanation is essential for us to have a deeper understanding of information diffusion as well as a better prediction of future event cascade. In order to uncover the mechanism of the happening of social events, we analyze the rating event data crawled from Douban.com, a Chinese social network, from year 2006 to 2011. We distinguish three factors: social, external and intrinsic influence which can explain the emergence of every specific event. Then we use the mixed Poisson process to model event cascade generated by different factors respectively and integrate different Poisson processes with shared parameters. The proposed model, called Combinational Mixed Poisson Process (CMPP) model, can explain not only how information diffuses in social networks, but also why a specific event happens. This model can help us to understand information diffusion from both macroscopic and microscopic perspectives. We develop an efficient Classification EM algorithm to infer the model parameters. The explanatory and predictive power of the proposed model has been demonstrated by the experiments on large real data sets.
Germination responses to temperature and water potential in Jatropha curcas seeds: a hydrotime model explains the difference between dormancy expression and dormancy induction at different incubation temperatures.

BACKGROUND AND AIMS Jatropha curcas is a drought-resistant tree whose seeds are a good source of oil that can be used for producing biodiesel. A successful crop establishment depends on a rapid and uniform germination of the seed. In this work we aimed to characterize the responses of J. curcas seeds to temperature and water availability, using thermal time and hydrotime analysis, METHODS Thermal and hydrotime analysis was performed on germination data obtained from the incubation of seeds at different temperatures and at different water potentials. KEY RESULTS Base and optimum temperatures were 14·4 and 30 °C, respectively. Approximately 20 % of the seed population displayed absolute dormancy and part of it displayed relative dormancy which was progressively expressed in further fractions when incubation temperatures departed from 25 °C. The thermal time model, but not the hydrotime model, failed to describe adequately final germination percentages at temperatures other than 25 °C. The hydrotime constant, θ(H), was reduced when the incubation temperature was increased up to 30 °C, the base water potential for 50 % germination,Ψ(b(50)), was less negative at 20 and 30 °C than at 25 °C, indicating either expression or induction of dormancy. At 20 °C this less negative Ψ(b(50)) explained satisfactorily the germination curves obtained at all water potentials, while at 30 °C it had to be corrected towards even less negative values to match observed curves at water potentials below 0. Hence, Ψ(b(50)) appeared to have been further displaced to less negative values as exposure to 30 °C was prolonged by osmoticum. These results suggest expression of dormancy at 20 °C and induction of secondary dormancy above 25 °C. This was confirmed by an experiment showing that inhibition of germination imposed by temperatures higher than 30 °C, but not that imposed at 20 °C, is a permanent effect. CONCLUSIONS This study revealed (a) the extremely narrow thermal range within which dormancy problems (either through expression or induction of dormancy) may not be encountered; and (b) the high sensitivity displayed by these seeds to water shortage. In addition, this work is the first one in which temperature effects on dormancy expression could be discriminated from those on dormancy induction using a hydrotime analysis.
Optimal approximation algorithm of virtual machine placement for data latency minimization in cloud systems

The MapReduce/Hadoop architecture has become very important and effective in cloud systems because many data-intensive applications are usually required to process big data. In such environments, big data is partitioned and stored over several data nodes; thus, the total completion time of a task would be delayed if the maximum access latency among all pairs of a data node and its assigned computation node is not bounded. Moreover, the computation nodes usually need to communicate with each other for aggregating the computation results; therefore, the maximum access latency among all pairs of assigned computation nodes also needs to be bounded. In the literature, it has been proved that the placement problem of computation nodes (virtual machines) to minimize the maximum access latency among all pairs of a data node and its assigned computation node and among all pairs of assigned computation nodes does not admit any approximation algorithm with a factor smaller than two, whereas no approximation algorithms have been proposed so far. In this paper, we first propose a 3-approximation algorithm for resolving the problem. Subsequently, we close the gap by proposing a 2-approximation algorithm, that is, an optimal approximation algorithm, for resolving the problem in the price of higher time complexity. Finally, we conduct simulations for evaluating the performance of our algorithms.
Cs674/info630: Advanced Language Technologies, Fall 2007, Lecture by Lillian Lee Lecture 16 Guide: an Introduction to Empirical Evaluations of Clickthrough Data

Recall that by following the analysis of [1] and combining the mixture of 2-Poisson model with the Robertson-Spärck Jones scoring function [2] we obtained the following scoring formula for a document d with the term frequency vector d: score q (d) = j: q[j]>0 d[j]>0
AN OPTIMIZATION APPROACH TO AUTOMATIC GENERIC DOCUMENT SUMMARIZATION

In this paper, we have presented an optimization approach to document summarization. The potential of optimization based document summarization models has not been well explored to date. This is partially the difficulty to formulate the criteria used for objective assessment. We modeled document summarization as the linear and nonlinear optimization problems. These models generally attempt simultaneously to balance coverage and diversity in the summary. To solve the optimization problem we developed a novel particle swarm optimization (PSO) algorithm. Experiments showed our linear and nonlinear models produce very competitive results, which significantly outperform the NIST baselines in both years. More important, although linear and nonlinear models are comparable to the top three systems S24, S15, and S12 in the DUC2006, they are even superior to the best participating system in the DUC2005.
Sapientia: the Ontology of Multi-dimensional Research Assessment

This paper proposes an Ontology-Based Data Management (OBDM) approach to a multi-dimensional research assessment. It is shown that an OBDM approach is able to take into account the recent trends in quantitative studies of Science, Technology and Innovation, including computerization of bibliometrics, multidimensionality of research assessment, altmetrics, and, more generally, the generation of new indicators with higher granularity and cross-referencing specificities according to increasingly demanding policy needs. The main features of Sapientia are presented, the Ontology of Multi-dimensional Research Assessment, developed within a project funded by the University of Rome La Sapienza. Illustrative examples are given of its usefulness for the specification of well known as well as recently developed indicators of research assessment.