Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthetic Hydrogel Delivery of Growth Factors and Demineralized Bone Matrix for Bone Augmentation

Synthetic Hydrogel Delivery of Growth Factors and Demineralized Bone Matrix for Bone Augmentation By Lucas A. Kinard The overarching objective of this thesis was to investigate synthetic hydrogel delivery of growth factors and demineralized bone matrix (DBM) for bone augmentation. Our motivation rests on observed weaknesses of current clinical approaches to bone augmentation, which synthetic hydrogels hope to overcome based on non-invasive application, contouring, tunability, and drug delivery. First, we investigated the release of bone morphogenetic protein-2 (BMP-2) from gelatin microparticles. Hydrogel composites based on oligo(poly(ethylene glycol) fumarate) (OPF) were prepared to investigate the effect of gelatin amount, gelatin type, and BMP-2 loading phase on release. The most significant factor affecting the release of BMP-2 was the loading phase, whereby gelatin loading reduced the burst release and increased BMP-2 release during later phases. Our results indicated tunability of the physical properties and BMP-2 release kinetics of our hydrogel composites. Second, we developed a rat model for bone augmentation and investigated our BMP-2 delivery system in vivo. Our animal model achieved rigid immobilization of bilateral implants apposed to the parietal bone of the rat. The BMP-2 release profile was varied and compared to the implantation of a material control without BMP-2. The volume of bone augmentation did not vary between groups after 4 weeks largely due to insignificant hydrogel degradation. Altogether, a promising rat model of bone augmentation was established; however, refinement of the hydrogel
CERTH's Participation at the Photo Annotation Task of ImageCLEF 2012

This paper describes the approaches and experimental set- tings of the ve runs submitted by CERTH at the photo annotation task of ImageCLEF 2012. Two dierent approaches were used, the rst using the Laplacian Eigenmaps of an image similarity graph for learning, and the second using a \same class" learning model. Four runs were submit- ted using the rst, and one using the second approach. A multitude of textual and visual features were employed, making use of dierent aggre- gation (BoW, VLAD) and post-processing schemes (WordNet, pLSA). The best performance scores in the test set was achieved by Run 3 (rst approach using all features), which amounted to 0.321 in terms of MiAP and 0.2547 in terms of GMiAP (7th out of 18 compteting teams), and Run 5 which led to an F-ex score of 0.495 (6th out of 18 teams).
Practice of Epidemiology Derivation and Validation of the Denver Human Immunodeficiency Virus (HIV) Risk Score for Targeted HIV Screening

Targeted screening remains an important approach to human immunodeficiency virus (HIV) testing. The authors aimed to derive and validate an instrument to accurately identify patients at risk for HIV infection, using patient data from a metropolitan sexually transmitted disease clinic in Denver, Colorado (1996–2008). With multivariable logistic regression, they developed a risk score from 48 candidate variables using newly identified HIV infection as the outcome. Validation was performed using an independent population from an urban emergency department in Cincinnati, Ohio. The derivation sample included 92,635 patients; 504 (0.54%) were diagnosed with HIV infection. The validation sample included 22,983 patients; 168 (0.73%) were diagnosed with HIV infection. The final score included age, gender, race/ethnicity, sex with a male, vaginal intercourse, receptive anal intercourse, injection drug use, and past HIV testing, and values ranged from 14 to þ81. For persons with scores of <20, 20–29, 30–39, 40–49, and 50, HIV prevalences were 0.31% (95% confidence interval (CI): 0.20, 0.45) (n 1⁄4 27/8,782), 0.41% (95% CI: 0.29, 0.57) (n 1⁄4 36/8,677), 0.99% (95% CI: 0.63, 1.47) (n 1⁄4 24/2,431), 1.59% (95% CI: 1.02, 2.36) (n 1⁄4 24/ 1,505), and 3.59% (95%CI: 2.73, 4.63) (n1⁄4 57/1,588), respectively. The risk score accurately categorizes patients into groups with increasing probabilities of HIV infection.
Distributed program tracing

Dynamic program analysis techniques depend on accurate program traces. Program instrumentation is commonly used to collect these traces, which causes overhead to the program execution. Various techniques have addressed this problem by minimizing the number of probes/witnesses used to collect traces. In this paper, we present a novel distributed trace collection framework wherein, a program is executed multiple times with the same input for different sets of witnesses. The partial traces such obtained are then merged to create the whole program trace. Such divide-and-conquer strategy enables parallel collection of partial traces, thereby reducing the total time of collection. The problem is particularly challenging as arbitrary distribution of witnesses cannot guarantee correct formation of traces. We provide and prove a necessary and sufficient condition for distributing the witnesses which ensures correct formation of trace. Moreover, we describe witness distribution strategies that are suitable for parallel collection. We use the framework to collect traces of field SAP-ABAP programs using breakpoints as witnesses as instrumentation cannot be performed due to practical constraints. To optimize such collection, we extend Ball-Larus' optimal edge-based profiling algorithm to an optimal node-based algorithm. We demonstrate the effectiveness of the framework for collecting traces of SAP-ABAP programs.
Continued involvement in software development: motivational factors

Software practitioner motivation has been recognised as a key factor in system quality, yet much of what we know about practitioner motivation is based on research conducted decades ago. In this paper, we present the analysis of data collected from 23 current practitioners at a workshop on motivation. This is the third in a series of workshops, each aimed at investigating the motivational factors in current software practice. We found that people factors are those most often cited, which reinforces the findings from the two previous workshops. This has implications for motivational programmes in software organisations, and indicates the need for further empirical research in the area.
Testing Decision Rules for Categorizing Species’ Extinction Risk to Help Develop Quantitative Listing Criteria for the U.S. Endangered Species Act

Lack of guidance for interpreting the definitions of endangered and threatened in the U.S. Endangered Species Act (ESA) has resulted in case‐by‐case decision making leaving the process vulnerable to being considered arbitrary or capricious. Adopting quantitative decision rules would remedy this but requires the agency to specify the relative urgency concerning extinction events over time, cutoff risk values corresponding to different levels of protection, and the importance given to different types of listing errors. We tested the performance of 3 sets of decision rules that use alternative functions for weighting the relative urgency of future extinction events: a threshold rule set, which uses a decision rule of x% probability of extinction over y years; a concave rule set, where the relative importance of future extinction events declines exponentially over time; and a shoulder rule set that uses a sigmoid shape function, where relative importance declines slowly at first and then more rapidly. We obtained decision cutoffs by interviewing several biologists and then emulated the listing process with simulations that covered a range of extinction risks typical of ESA listing decisions. We evaluated performance of the decision rules under different data quantities and qualities on the basis of the relative importance of misclassification errors. Although there was little difference between the performance of alternative decision rules for correct listings, the distribution of misclassifications differed depending on the function used. Misclassifications for the threshold and concave listing criteria resulted in more overprotection errors, particularly as uncertainty increased, whereas errors for the shoulder listing criteria were more symmetrical. We developed and tested the framework for quantitative decision rules for listing species under the U.S. ESA. If policy values can be agreed on, use of this framework would improve the implementation of the ESA by increasing transparency and consistency.
Response of Salt Marsh Ponds to Eutropication

We examined the response of New England salt marsh ponds to nutrient loading via flooding tidal water as part of a larger, long-term whole ecosystem manipulation. Nitrate and phosphate concentration were added directly to two tidal creek in concentrations approximately 15x ambient for ~150 d during the growing season and 30x ambient for 3 d during the study period. During the summer, when fertilization was occurring, we measured a time series of nitrate and ammonium concentrations, water column algal content, the numerical abundance of benthic micro-algae, and the numerical abundance of protists. Additionally we measured benthic algae biomass, floating algae mat percent cover, and R. maritima percent cover. During the fall, sediment cores were collected and incubated in the lab where we obtained measurements of ammonium and nitrate fluxes, gross primary production, and bacterial production before and after the addition of nutrient (70 uM nitrate and 4uM phosphate). Our results indicate that gross nitrate processing in salt marsh ponds occurs at comparable rates to the rest of the marsh ecosystem. Additionally, our results indicate that primary producers in the ponds are limited by light and/or top-down grazer controls. Despite relatively high rate of production, are responsible for, at most, half of the initial processing of nitrate entering the ponds through flooding tidal water.
Planning for Human-Robot Interaction Using Time-State Aggregated POMDPs

In order to interact successfully in social situations, a robot must be able to observe others’ actions and base its own behavior on its beliefs about their intentions. Many interactions take place in dynamic environments, and the outcomes of people’s or the robot’s actions may be time-dependent. In this paper, such interactions are modeled as a POMDP with a time index as part of the state, resulting in a fully Markov model with a potentially very large state space. The complexity of finding even an approximate solution often limits POMDP’s practical applicability for large problems. This difficulty is addressed through the development of an algorithm for aggregating states in POMDPs with a time-indexed state space. States that represent the same physical configuration of the environment at different times are chosen to be combined using reward-based metrics, preserving the structure of the original model while producing a smaller model that is faster to solve. We demonstrate that solving the aggregated model produces a policy with performance comparable to the policy from the original model. The example domains used are a simulated elevator-riding task and a simulated driving task based on data collected from human drivers.
Comparison of simulation-based and measurement-based RF shimming for whole-body MRI at 7 Tesla

(1.9 m, 85 kg): a) Simulation-based shim, FLASH sequence, transverse plane, b) corresponding simulated B1 distribution. c) Measured shim, FLASH sequence, transverse plane, d) measured absolute flip angle distribution. Fig. 1: RF shimming for cardiac MRI: female volunteer (1.65 m, 70 kg). a) Relative B1 maps (pulse triggered) of individual transmit channels used for calculating the measured shim. Short-axis, cine FLASH, transverse plane: b) measured shim, c) simulation-based shim. a)
Sparse binary zero-sum games

Solving zero-sum matrix games is polynomial, because it boils down to linear programming. The approximate solving is sublinear by randomized algorithms on machines with random access memory. Algorithms working separately and independently on columns and rows have been proposed, with the same performance; these versions are compliant with matrix games with stochastic reward. (Flory and Teytaud, 2011) has proposed a new version, empirically performing better on sparse problems, i.e. cases in which the Nash equilibrium has small support. In this paper, we propose a variant, similar to their work, also dedicated to sparse problems, with provably better bounds than existing methods. We then experiment the method on a card game.
Deep Context: A Neural Language Model for Large-scale Networked Documents

We propose a scalable neural language model that leverages the links between documents to learn the deep context of documents. Our model, Deep Context Vector, takes advantage of distributed representations to exploit the word order in document sentences, as well as the semantic connections among linked documents in a document network. We evaluate our model on large-scale data collections that include Wikipedia pages, and scientific and legal citations networks. We demonstrate its effectiveness and efficiency on document classification and link prediction tasks.
An essential role for hGle1 nucleocytoplasmic shuttling in mRNA export

Gle1 is required for mRNA export in yeast and human cells. Here, we report that two human Gle1 (hGle1) isoforms are expressed in HeLa cells (hGle1A and B). The two encoded proteins are identical except for their COOH-terminal regions. hGle1A ends with a unique four–amino acid segment, whereas hGle1B has a COOH-terminal 43–amino acid span. Only hGle1B, the more abundant isoform, localizes to the nuclear envelope (NE) and pore complex. To test whether hGle1 is a dynamic shuttling transport factor, we microinjected HeLa cells with recombinant hGle1 and conducted photobleaching studies of live HeLa cells expressing EGFP–hGle1. Both strategies show that hGle1 shuttles between the nucleus and cytoplasm. An internal 39–amino acid domain is necessary and sufficient for mediating nucleocytoplasmic transport. Using a cell-permeable peptide strategy, we document a role for hGle1 shuttling in mRNA export. An hGle1 shuttling domain (SD) peptide impairs the export of both total poly(A)+ RNA and the specific dihydrofolate reductase mRNA. Coincidentally, SD peptide–treated cells show decreased endogenous hGle1 localization at the NE and reduced nucleocytoplasmic shuttling of microinjected, recombinant hGle1. These findings pinpoint the first functional motif in hGle1 and link hGle1 to the dynamic mRNA export mechanism.
Symbolic reachability analysis for parameterized administrative role based access control

Role based access control (RBAC) is a widely used access control paradigm. In large organizations, the RBAC policy is managed by multiple administrators. An administrative role based access control (ARBAC) policy specifies how each administrator may change the RBAC policy. It is often difficult to fully understand the effect of an ARBAC policy by simple inspection, because sequences of changes by different administrators may interact in unexpected ways. ARBAC policy analysis algorithms can help by answering questions, such as user-role reachability, which asks whether a given user can be assigned to given roles by given administrators. Allowing roles and permissions to have parameters significantly enhances the scalability, flexibility, and expressiveness of ARBAC policies. This paper defines PARBAC, which extends the classic ARBAC97 model to support parameters, and presents an analysis algorithm for PARBAC. To the best of our knowledge, this is the first analysis algorithm specifically for parameterized ARBAC policies. We evaluate its efficiency by analyzing its parameterized complexity and benchmarking it on case studies and synthetic policies.
Testing web applications focusing on their specialties

Nowadays, Web applications are very prevalent around the world, and it becomes more and more important to ensure their qualities by testing. However, due to the special characters of Web applications, traditional testing methods are not suitable for Web testing in many aspects. So based on the related work by now, this paper presents our research work in such areas as the Web application modeling, the test case generation, the detailed testing methods and techniques, the testing executing process, and the testing measurements. And based on the rules of software engineering, these processes are the necessary parts of the whole testing. Our methods focus on such specialties as numerous users, distributed structures, dynamic and interactive functions of Web applications and the improvements for the testing efficiency.
Solving mixed 0-1programs by a lift-and-project method

We propose a procedure to sequentially tighten the linear programming relaxation of a mixed O-l program by generating lift-and-project cutting planes. The cuts are found through the solution of a linear program that has at most twice the size of the current LP relaxation. We report our computational experience when using our cuts as part of a cutting plane algorithm, as well as in the context of a branch-and-cut procedure.
Process Evaluation of a Positive Youth Development Program in Hong Kong Based on Different Cohorts

There are only a few process evaluation studies on positive youth development programs, particularly in the Chinese context. This study aims to examine the quality of implementation of a positive youth development program (the Project P.A.T.H.S.: Positive Adolescent Training through Holistic Social Programmes) and investigate the relationships among program adherence, process factors, implementation quality, and perceived program success. Process evaluation of 97 classroom-based teaching units was conducted in 62 schools from 2005 to 2009. Findings based on different cohorts generally showed that there were high overall program adherence and implementation quality. Program adherence and implementation process were highly correlated with quality and success of the program. Multiple regression analyses further showed that both implementation process and program adherence are significant predictors of program quality and success. Theoretical and practical implications of the findings are discussed.
Distance measurements as a probe of cosmic acceleration

A major recent development in observational cosmology has been an accurate measurement of the luminosity distance–redshift relation out to redshifts z=0.8 from Type Ia supernova standard candles. The results have been argued as evidence for cosmic acceleration. It is well known that this assertion depends on the assumption that we know the equation of state for all mass–energy other than normal pressureless matter; popular models are based either on the cosmological constant or on the more general quintessence formulation. However, this assertion also depends on a number of other assumptions, implicit in the derivation of the standard cosmological field equations: large-scale isotropy and homogeneity, the flatness of the Universe, and the validity of general relativity on cosmological scales (where it has not been tested). A detailed examination of the effects of these assumptions on the interplay between the luminosity distance–redshift relation and the acceleration of the Universe is not possible unless one can define the precise nature of the failure of any particular assumption. However a simple quantitative investigation is possible and reveals a number of considerations about the relative importance of the different assumptions. In this paper we present such an investigation. We find that the relationship between the distant-redshift relation and the sign of the deceleration parameter is fairly robust and is unaffected if only one of the assumptions that we investigate is invalid so long as the deceleration parameter is not close to zero (it would not be close to zero in the currently favoured ΩΛ=1−Ωmatter=0.7 or 0.8 Universe, for example). Failures of two or more assumptions in concordance may have stronger effects.
An Extended General Location Model for Causal Inferences from Data Subject to Noncompliance and Missing Values

Summary Noncompliance is a common problem in experiments involving randomized assignment of treatments, and standard analyses based on intention‐to‐treat or treatment received have limitations. An attractive alternative is to estimate the Complier‐Average Causal Effect (CACE), which is the average treatment effect for the subpopulation of subjects who would comply under either treatment ( Angrist, Imbens, and Rubin, 1996 , Journal of American Statistical Association91, 444–472). We propose an extended general location model to estimate the CACE from data with noncompliance and missing data in the outcome and in baseline covariates. Models for both continuous and categorical outcomes and ignorable and latent ignorable ( Frangakis and Rubin, 1999 , Biometrika86, 365–379) missing‐data mechanisms are developed. Inferences for the models are based on the EM algorithm and Bayesian MCMC methods. We present results from simulations that investigate sensitivity to model assumptions and the influence of missing‐data mechanism. We also apply the method to the data from a job search intervention for unemployed workers.
Code Size Aware Compilation for Real-Time Applications

Statically constructed plan of execution (POE) and aggressive instruction level parallelism (ILP) exploitation make EPIC/VLIW processors appropriate for high performance real-time systems. On the one hand, the compiler controlled POE makes the worst-case execution-time (WCET) analysis more accurate as run-time variations are minimized. On the other hand, the compiler can leverage ILP optimizations and instruction scheduling to explicitly reduce the WCET of real-time tasks, which in turn improves the system level schedulability. The ILP optimizations, however, could result in excessive static code size increase if they are not performed carefully, which incurs additional system cost and potential performance degradation due to the affected I-cache performance. In this paper, we propose a low complexity, systematic way to selective perform the code size related ILP optimizations including if-conversion, loop unrolling, and tail duplication, so that the WCET is significantly reduced at the cost of minor static code size increase. We also show that the coupled instruction scheduling algorithm, treegion scheduling, suits the real-time systems well due to its capability to optimize multiple control paths simultaneously.
A computational study of a host‐guest complex

The geometry and energetics of a complex involving pyrazine and an acridine diacid cleft‐like host designed by Rebek were investigated at several levels of theory. Molecular mechanics (using the Tripos and CHARMm force fields), semiempirical quantum chemical approaches (with the AM1 and PM3 methods), and an ab initio quantum chemical method (RHF/STO‐3G) were used in the complete relaxation of the complex. The geometry of the complex optimized by the RHF/STO‐3G method is in excellent agreement with a published X‐ray structure; upon superposition, the rms deviation between the corresponding cleft heavy atoms is only 0.17 Å and the pyrazine molecules are superimposable. In addition, ab initio quantum chemical techniques were used to study the complex when the cleft is modeled by a pair of acetic acid molecules. All the calculations presented herein support a two‐point interaction mechanism. The similarities found in the results for the full complex and the truncated model are consistent with a purely structural role for the acridine linker of the host. © 1997 John Wiley & Sons, Ltd.