Miracle-dz/UniFAR-FTUs huggingface dataset:
Transport properties of pancreatic cancer describe gemcitabine delivery and response.

BACKGROUND The therapeutic resistance of pancreatic ductal adenocarcinoma (PDAC) is partly ascribed to ineffective delivery of chemotherapy to cancer cells. We hypothesized that physical properties at vascular, extracellular, and cellular scales influence delivery of and response to gemcitabine-based therapy. METHODS We developed a method to measure mass transport properties during routine contrast-enhanced CT scans of individual human PDAC tumors. Additionally, we evaluated gemcitabine infusion during PDAC resection in 12 patients, measuring gemcitabine incorporation into tumor DNA and correlating its uptake with human equilibrative nucleoside transporter (hENT1) levels, stromal reaction, and CT-derived mass transport properties. We also studied associations between CT-derived transport properties and clinical outcomes in patients who received preoperative gemcitabine-based chemoradiotherapy for resectable PDAC. RESULTS Transport modeling of 176 CT scans illustrated striking differences in transport properties between normal pancreas and tumor, with a wide array of enhancement profiles. Reflecting the interpatient differences in contrast enhancement, resected tumors exhibited dramatic differences in gemcitabine DNA incorporation, despite similar intravascular pharmacokinetics. Gemcitabine incorporation into tumor DNA was inversely related to CT-derived transport parameters and PDAC stromal score, after accounting for hENT1 levels. Moreover, stromal score directly correlated with CT-derived parameters. Among 110 patients who received preoperative gemcitabine-based chemoradiotherapy, CT-derived parameters correlated with pathological response and survival. CONCLUSION Gemcitabine incorporation into tumor DNA is highly variable and correlates with multiscale transport properties that can be derived from routine CT scans. Furthermore, pretherapy CT-derived properties correlate with clinically relevant endpoints. TRIAL REGISTRATION Clinicaltrials.gov NCT01276613. FUNDING Lustgarten Foundation (989161), Department of Defense (W81XWH-09-1-0212), NIH (U54CA151668, KCA088084).
Evolutionary history of the critically endangered Cozumel dwarf carnivores inferred from mitochondrial DNA analyses

The pygmy raccoon Procyon pygmaeus and dwarf coati Nasua nelsoni, both endemic to Cozumel Island, Mexico, are two of the most endangered carnivores in the world, and their persistence requires active management. However, the taxonomic status of these populations remains unclear. Therefore we investigated mitochondrial DNA variation using the control region to examine the genetic uniqueness and evolutionary history of these taxa. Using strict phylogenetic criteria, species-level uniqueness of the Cozumel taxa was difficult to discern based solely on haplotype groupings and identification of unique alleles. However, population genetic approaches indicate significant population differentiation between Cozumel and mainland populations and we suggest that these taxa should be treated as distinct management units from their mainland conspecifics. Coalescent analysis indicated that the pygmy raccoon diverged from the mainland about 3050–200 111 years before present (ybp) and the Cozumel coati 1263–82 896 ybp; dates that can be further constrained by incorporating knownage subfossil specimens from Cozumel as well as the geological history of the island. Thus, although it is likely that the island taxa colonized Cozumel before the Mayan peoples populated the island, we are unable to definitively reject the hypothesis that colonization by these taxa was not human facilitated.
Automatic verification of safety and liveness for XScale-like processor models using WEB refinements

We show how to automatically verify that complex XScale-like pipelined machine models satisfy the same safety and liveness properties as their corresponding instruction set architecture models, by using the notion of well-founded equivalence bisimulation (WEB) refinement. Automation is achieved by reducing the WEB-refinement proof obligation to a formula in the logic of counter arithmetic with lambda expressions and uninterpreted functions (CLU). We use the tool UCLID to transform the resulting CLU formula into a Boolean formula, which is then checked with a SAT solver. The models we verify include features such as out of order completion, precise exceptions, branch prediction, and interrupts. We use two types of refinement maps. In one, flushing is used to map pipelined machine states to instruction set architecture states; in the other, we use the commitment approach, which is the dual of flushing, since partially completed instructions are invalidated. We present experimental results for all the machines modelled, including verification times. For our application, we found that the time spent proving liveness accounts for about 5% of the over-all verification time.
The internal representation of head orientation differs for conscious perception and balance control

We tested perceived head‐on‐feet orientation and the direction of vestibular‐evoked balance responses in passively and actively held head‐turned postures. The direction of vestibular‐evoked balance responses was not aligned with perceived head‐on‐feet orientation while maintaining prolonged passively held head‐turned postures. Furthermore, static visual cues of head‐on‐feet orientation did not update the estimate of head posture for the balance controller. A prolonged actively held head‐turned posture did not elicit a rotation in the direction of the vestibular‐evoked balance response despite a significant rotation in perceived angular head posture. It is proposed that conscious perception of head posture and the transformation of vestibular signals for standing balance relying on this head posture are not dependent on the same internal representation. Rather, the balance system may operate under its own sensorimotor principles, which are partly independent from perception.
A Density Functional Tight Binding Study of Acetic Acid Adsorption on Crystalline and Amorphous Surfaces of Titania

We present a comparative density functional tight binding study of an organic molecule attachment to TiO2 via a carboxylic group, with the example of acetic acid. For the first time, binding to low-energy surfaces of crystalline anatase (101), rutile (110) and (B)-TiO2 (001), as well as to the surface of amorphous (a-) TiO2 is compared with the same computational setup. On all surfaces, bidentate configurations are identified as providing the strongest adsorption energy, Eads = −1.93, −2.49 and −1.09 eV for anatase, rutile and (B)-TiO2, respectively. For monodentate configurations, the strongest Eads = −1.06, −1.11 and −0.86 eV for anatase, rutile and (B)-TiO2, respectively. Multiple monodentate and bidentate configurations are identified on a-TiO2 with a distribution of adsorption energies and with the lowest energy configuration having stronger bonding than that of the crystalline counterparts, with Eads up to −4.92 eV for bidentate and −1.83 eV for monodentate adsorption. Amorphous TiO2 can therefore be used to achieve strong anchoring of organic molecules, such as dyes, that bind via a -COOH group. While the presence of the surface leads to a contraction of the band gap vs. the bulk, molecular adsorption caused no appreciable effect on the band structure around the gap in any of the systems.
Sparse Multivariate Regression With Covariance Estimation

We propose a procedure for constructing a sparse estimator of a multivariate regression coefficient matrix that accounts for correlation of the response variables. This method, which we call multivariate regression with covariance estimation (MRCE), involves penalized likelihood with simultaneous estimation of the regression coefficients and the covariance structure. An efficient optimization algorithm and a fast approximation are developed for computing MRCE. Using simulation studies, we show that the proposed method outperforms relevant competitors when the responses are highly correlated. We also apply the new method to a finance example on predicting asset returns. An R-package containing this dataset and code for computing MRCE and its approximation are available online.
Modified particle swarm optimizers and their application to robust design and structural optimization

Many scientific, engineering and economic problems involve optimization. In reaction to that, numerous optimization algorithms have been proposed. Particle Swarm Optimization (PSO) is a new paradigm of Swarm Intelligence which is inspired by concepts from 'Social Psychology' and 'Artificial Life'. Essentially, PSO proposes that the co-operation of individuals promotes the evolution of the swarm. In terms of optimization, the hope would be to enhance the swarm's ability to search on a global scale so as to determine the global optimum in a fitness landscape. It has been empirically shown to perform well with regard to many different kinds of optimization problems. PSO is particularly a preferable candidate to solve highly nonlinear, non-convex and even discontinuous problems. The main ambition of this thesis is to propose two enhanced versions of PSO (Modified Guaranteed Convergence PSO (MGCPSO) and Modified Lbest based PSO (LPSO)) and to extend them to different areas of application. MGCPSO is an extension of the Gbest based version of PSO and exhibits balanced performance between accuracy and efficiency in empirical numerical tests. It is applied to robust design with metamodel as well as structural sizing optimization in this work. In order to improve the efficiency of computing with regard to robust design, a mixed Fortran-Matlab program is developed as well as its corresponding parallel pattern. It obtains satisfying results for both optimization problems. On the other hand, LPSO constitutes an enhanced Lbest based version of PSO whereby two LPSOs with two and three neighbour links are tested by means of the empirical benchmark test. Both demonstrate excellent global searching ability. For this reason, this algorithm is extended to problems of truss topological design. This type of optimization problems can be characterised as large-scale and non-convex. LPSO is very well suited to this particular field of optimization. Indeed, it achieves solutions that challenge the best ones ever found. Finally, MGCPSO is successfully applied to a structural sizing optimization problem.
Breast cancer detection using cartesian genetic programming evolved artificial neural networks

A fast learning neuro-evolutionary technique that evolves Artificial Neural Networks using Cartesian Genetic Programming (CGPANN) is used to detect the presence of breast cancer. Features from breast mass are extracted using fine needle aspiration (FNA) and are applied to the CGPANN for diagnosis of breast cancer. FNA data is obtained from the Wisconsin Diagnostic Breast Cancer website and is used for training and testing the network. The developed system produces fast and accurate results when compared to contemporary work done in the field. The error of the model comes out to be as low as 1% for Type-I (classifying benign sample falsely as malignant) and 0.5% for Type-II (classifying malignant sample falsely as benign).
Reduction in the Incidence of Type 2 Diabetes With the Mediterranean Diet

OBJECTIVE To test the effects of two Mediterranean diet (MedDiet) interventions versus a low-fat diet on incidence of diabetes. RESEARCH DESIGN AND METHODS This was a three-arm randomized trial in 418 nondiabetic subjects aged 55–80 years recruited in one center (PREDIMED-Reus, northeastern Spain) of the Prevención con Dieta Mediterránea [PREDIMED] study, a large nutrition intervention trial for primary cardiovascular prevention in individuals at high cardiovascular risk. Participants were randomly assigned to education on a low-fat diet (control group) or to one of two MedDiets, supplemented with either free virgin olive oil (1 liter/week) or nuts (30 g/day). Diets were ad libitum, and no advice on physical activity was given. The main outcome was diabetes incidence diagnosed by the 2009 American Diabetes Association criteria. RESULTS After a median follow-up of 4.0 years, diabetes incidence was 10.1% (95% CI 5.1–15.1), 11.0% (5.9–16.1), and 17.9% (11.4–24.4) in the MedDiet with olive oil group, the MedDiet with nuts group, and the control group, respectively. Multivariable adjusted hazard ratios of diabetes were 0.49 (0.25–0.97) and 0.48 (0.24–0.96) in the MedDiet supplemented with olive oil and nuts groups, respectively, compared with the control group. When the two MedDiet groups were pooled and compared with the control group, diabetes incidence was reduced by 52% (27–86). In all study arms, increased adherence to the MedDiet was inversely associated with diabetes incidence. Diabetes risk reduction occurred in the absence of significant changes in body weight or physical activity. CONCLUSIONS MedDiets without calorie restriction seem to be effective in the prevention of diabetes in subjects at high cardiovascular risk.
Carbohydrate structure of vesicular stomatitis virus glycoprotein.

The carbohydrate structure of the membrane glycoprotein of vesicular stomatitis virus (New Jersey serotype) has been determined on material purified from virions grown in spinner cultures of BHKzl cells in the presence of [3H]glucosamine. The intact 3H-glycoprotein contains 6 residues of N-acetyl-n-neuraminic acid, 6 of D-galactose, 6 of D-mannose, 2 of L-fucose, and 10 of N-acetyl-n-glucosamine. Neither D-ghCOSe nor Nacetyl-D-galactosamine was detected. The carbohydrate was not susceptible to fl elimination, and glycopeptides were obtained that yielded 1 mol of aspartic acid/m01 of glycopeptide after acid hydrolysis, both of which indicate that the sugar is linked to the amide nitrogen of asparagine in the glycoprotein. Hydrazinolysis of the glycoprotein yielded a single major oligosaccharide that, after re-N-acetylation, contained 3 residues of N-acetylneuraminic acid, 3 of galactose, 3 of maxmose, 1 of fucose, and 6 of N-acetylglucosamine, suggesting that the glycoprotein contains two identical oligosaccharide chains. The linkages in the hydrazinolysis oligosaccharide were established by methylation analysis. The oligosaccharide was fragmented by partial acid hydrolysis and was specifically depolymerized at de-N-acetylated glucosamine residues by nitrous acid dean&nation, the fragments obtained at each step were purified, and their carbohydrate compositions were determined. A glycopeptide fraction, obtained by digestion of the glycoprotein with trypsin and pronase, was separated on the basis of amino acid differences into two components with identical sugar compositions that are assumed to represent units from the two different sites of glycosylation in the protein. The glycopeptides were subjected to sequential exoglycosidase digestion with a-D-neuraminidase, P-D-galactosidase, F-D-hexosaminidase, a-D-mannosidase, fi-n-mannosidase, and a-Mucosidase. After removal of the N-acetylneuraminic acid, the galactose, and part of the Nacetylglucosamine, the glycopeptides were cleaved with an endo-N-acetyl-/3-D-glucosaminidase. All fragments were reisolated after each digestion step and analyzed for carbohydrate composition or for linkages by methylation analysis. The glycoprotein, glycopeptides, and hydrazinolysis oligosaccharide were oxidized with periodate and subjected to Smith degradation, and the compositions and linkages of the products were determined. The results establish that the glycoprotein contains two identical carbohydrate chains that are composed of three outer chain units, a mannose-rich
Improving Nurses' Peripheral Intravenous Catheter Insertion Knowledge, Confidence, and Skills Using a Simulation-Based Blended Learning Program

Introduction Peripheral intravenous catheter (PIVC) insertion is one of the most common invasive procedures performed in a hospital, but most nurses receive little formal training in this area. Blended PIVC insertion training programs that incorporate deliberate simulated practice have the potential to improve clinical practice and patient care. Methods The study was a randomized, wait-list control group with crossover using nurses on three medical/surgical units. Baseline PIVC knowledge, confidence, and skills assessments were completed for both groups. The intervention group then received a 2-hour PIVC online course, followed by an 8-hour live training course using a synergistic mix of three simulation tools. Both groups were then reassessed. After crossover, the wait-list group received the same intervention and both groups were reassessed. Results At baseline, both groups were similar for knowledge, confidence, and skills. Compared with the wait-list group, the intervention group had significantly higher scores for knowledge, confidence, and skills upon completing the training program. After crossover, the wait-list group had similarly higher scores for knowledge, confidence, and skills than the intervention group. Between the immediate preintervention and postintervention periods, the intervention group improved scores for knowledge by 31%, skills by 24%, and decreased confidence by 0.5%, whereas the wait-list group improved scores for knowledge by 28%, confidence by 16%, and skills by 15%. Conclusions Results demonstrate significant improvements in nurses' knowledge, confidence, and skills with the use of a simulation-based blended learning program for PIVC insertion. Transferability of these findings from a simulated environment into clinical practice should be further explored.
Moment-based Uniform Deviation Bounds for k-means and Friends

Suppose $k$ centers are fit to $m$ points by heuristically minimizing the $k$-means cost; what is the corresponding fit over the source distribution? This question is resolved here for distributions with $p\geq 4$ bounded moments; in particular, the difference between the sample cost and distribution cost decays with $m$ and $p$ as $m^{\min\{-1/4, -1/2+2/p\}}$. The essential technical contribution is a mechanism to uniformly control deviations in the face of unbounded parameter sets, cost functions, and source distributions. To further demonstrate this mechanism, a soft clustering variant of $k$-means cost is also considered, namely the log likelihood of a Gaussian mixture, subject to the constraint that all covariance matrices have bounded spectrum. Lastly, a rate with refined constants is provided for $k$-means instances possessing some cluster structure.
Testing the BIAS Map Model: The Positive Effects of Perceiving Weakness and Harmony in Powerful Out-Groups

ABSTRACT Two experimental studies were used to test predictions derived from the BIAS map model. While the first experiment manipulated the perception of power in the out-group (the USA), the second manipulated the perceived harmony of the relationships between this out-group and the participants' own national group. The results confirmed the hypotheses derived from the model. The manipulation of power affected the perception of competence, thus affecting emotions and behavioral dispositions towards out-group members. The manipulation of perceived harmony of intergroup interests had a similar effect, but was not mediated by changes in the attribution of competence, but of warmth. Attitudes did not play a significant role in the prediction of emotions and behavioral intentions.
Newton's method with a model trust region modification

A modified Newton method for unconstrained minimization is presented and analyzed. The modification is based upon the model trust region approach. This report contains a thorough analysis of the locally constrained quadratic minimizations that arise as subproblems in the modified Newton iteration. Several promising alternatives are presented for solving these subproblems in ways that overcome certain theoretical difficulties exposed by this analysis. Very strong convergence results are presented concerning the minimization algorithm. In particular, the explicit use of second order information is justified by demonstrating that the iterates converge to a point which satisfies the second order necessary conditions for minimization. With the exception of very pathological cases this occurs whenever the algorithm is applied to problems with continuous second partial derivatives.
MICROCONTROLLER BASED SYSTEM-ON-CHIPS

Except where reference is made to the work of others, the work described in this thesis is my own or was done in collaboration with my advisory committee. This thesis does not include proprietary or classified information. Permission is granted to Auburn University to make copies of this thesis at its discretion, upon the request of individuals or institutions and at their expense. System-on-Chip (SoC) implementations typically incorporate embedded Field Programmable Gate Array (FPGA) cores to take advantage of the programmable logic and routing resources provided by FPGAs. Testing the FPGA core typically requires numerous configuration downloads to completely test the various modes of operation of the programmable logic resources and the size of each configuration download file is large due to large amount of programmable resources. However, the ability to perform dynamic partial reconfiguration of the FPGA core from embedded processor core opens new opportunities for testing the FPGA using Built-In Self-Test (BIST). This thesis discusses the implementation of BIST for FPGA cores using partial dynamic reconfiguration from the embedded processor. As a result, all external configuration downloads are eliminated and replaced by one single processor program that programs vi the FPGA core for BIST, executes the BIST sequence, retrieves the BIST results, and executes diagnostic procedures to locate and identify faults detected by the BIST. Total testing time is improved by as much as a factor of 45 and a configuration memory storage requirement by as much as a factor of 83 by using dynamic partial reconfiguration compared to the traditional approach that requires BIST configuration downloads for every mode of operation of the programmable logic resources in the FPGA core of the Atmel AT94K series SoCs. vii ACKNOWLEDGMENTS I am greatly indebted to Dr. Charles E. Stroud for his guidance and support during this study. He helped me becoming a better engineer not only with his technical assistance, but also with his moral support. Also, I would like to express sincere appreciation to my fellow research colleagues Srinivas, Jonathan, Sudheer, Sachin and Adam for their advice, concern and friendship. I reserve special thanks to Jinsung who has given so much of her time for the completion of this thesis. Additional appreciation is extended to my committee members Dr. Victor Nelson and Dr. Thaddeus Roppel for their critical reading of the thesis and their helpful suggestions. Finally, I would like to express my deepest gratitude to my parents, …
Brucella abortus induces intracellular retention of MHC‐I molecules in human macrophages down‐modulating cytotoxic CD8+ T cell responses

Brucella abortus elicits a vigorous Th1 immune response which activates cytotoxic T lymphocytes. However, B. abortus persists in its hosts in the presence of CD8+ T cells, establishing a chronic infection. Here, we report that B. abortus infection of human monocytes/macrophages inhibited the IFN‐γ‐induced MHC‐I cell surface expression. This phenomenon was dependent on metabolically active viable bacteria. MHC‐I down‐modulation correlated with the development of diminished CD8+ cytotoxic T cell response as evidenced by the reduced expression of the activation marker CD107a on CD8+ T lymphocytes and a diminished percentage of IFN‐γ‐producing CD8+ T cells. Inhibition of MHC‐I expression was not due to changes in protein synthesis. Rather, we observed that upon B. abortus infection MHC‐I molecules were retained within the Golgi apparatus. Overall, these results describe a novel mechanism based on the intracellular sequestration of MHC‐I molecules whereby B. abortus would avoid CD8+ cytotoxic T cell responses, evading their immunological surveillance.