Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety and immunogenicity of a bivalent cytomegalovirus DNA vaccine in healthy adult subjects.

BACKGROUND VCL-CB01, a candidate cytomegalovirus (CMV) DNA vaccine that contains plasmids encoding CMV phosphoprotein 65 (pp65) and glycoprotein B (gB) to induce cellular and humoral immune responses and that is formulated with poloxamer CRL1005 and benzalkonium chloride to enhance immune responses, was evaluated in a phase 1 clinical trial. METHODS VCL-CB01 was evaluated in 44 healthy adult subjects (22 CMV seronegative and 22 CMV seropositive) 18-43 years old. Thirty-two subjects received 1- or 5-mg doses of vaccine on a 0-, 2-, and 8-week schedule, and 12 subjects received 5-mg doses of vaccine on a 0-, 3-, 7-, and 28-day schedule. RESULTS Overall, the vaccine was well tolerated, with no serious adverse events. Local reactions included mild to moderate injection site pain and tenderness, induration, and erythema. Systemic reactions included mild to moderate malaise and myalgia. All reactions resolved without sequelae. Through week 16 of the study, immunogenicity, as measured by enzyme-linked immunosorbant assay and/or ex vivo interferon (IFN)-gamma enzyme-linked immunospot assay, was documented in 45.5% of CMV-seronegative subjects and in 25.0% of CMV-seropositive subjects who received the full vaccine series, and 68.1% of CMV-seronegative subjects had memory IFN-gamma T cell responses at week 32. CONCLUSION The safety and immunogenicity data from this trial support further evaluation of VCL-CB01.
Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties

Non-accidental properties (NAPs) correspond to image properties that are invariant to changes in viewpoint (e.g., straight vs. curved contours) and are distinguished from metric properties (MPs) that can change continuously with in-depth object rotation (e.g., aspect ratio, degree of curvature, etc.). Behavioral and electrophysiological studies of shape processing have demonstrated greater sensitivity to differences in NAPs than in MPs. However, previous work has shown that such sensitivity is lacking in multiple-views models of object recognition such as Hmax. These models typically assume that object processing is based on populations of view-tuned neurons with distributed symmetrical bell-shaped tuning that are modulated at least as much by differences in MPs as in NAPs. Here, we test the hypothesis that unsupervised learning of invariances to object transformations may increase the sensitivity to differences in NAPs vs. MPs in Hmax. We collected a database of video sequences with objects slowly rotating in-depth in an attempt to mimic sequences viewed during object manipulation by young children during early developmental stages. We show that unsupervised learning yields shape-tuning in higher stages with greater sensitivity to differences in NAPs vs. MPs in agreement with monkey IT data. Together, these results suggest that greater NAP sensitivity may arise from experiencing different in-depth rotations of objects.
Human Management of a Hierarchical System for the Control of Multiple Mobile Robots ( Dissertation Proposal ) MS-CIS-95-17 GRASP Lab 392

We have developed a hierarchy of human supervisory mediation levels into a robotic system. The purpose of this work was to create a semi-autonomous system which should enable completion of all feasible tasks. We propose the mediation hierarchy permits increased interaction between the human supervisor and all levels of a robotic system. This interaction permits the supervisor to maintain the system in a stable state. We have incorporated these hierarchical levels into MASC, a Multiple Agent Supervisory Control system. MASC provides the human supervisor with a three dimensional graphical human-machine interface. Our current test bed is the University of Pennsylvania's General Robotics and Active Sensory Perception (GRASP) Laboratory's multiagent system. This system includes two mobile observation robots and two mobile manipulatory agents. We designed human factors experiments to test the MASC system's usability as well as the mediation hierarchy theory. Novice users were recruited to participate in the experiments which included three different tasks: the single agent, the two agent and the four agent tasks. This thesis reviews the design of the experiments, analysis of the experimental results and a discussion of the results. The results are discussed in three perspectives, the MASC interface, the mediation hierarchy and the multiagent's system. In general, we found novice users were capable of executing the assigned tasks. We also substantiated the higher level interactions as well as the need for the lower level interactions of the mediation hierarchy. This thesis also presents a detailed review of all related research, as well as the contributions and future directions of this research.
Urinary marker for oxidative stress in kidneys in cisplatin-induced acute renal failure in rats.

BACKGROUND Establishment of non-invasive urinary biomarkers for the prediction of acute renal failure (ARF) is important. We evaluated whether urinary oxidative stress markers reflect intrarenal oxidative stress in cisplatin (CDDP)-induced ARF, and whether these markers can be used for the prediction of future ARF. METHODS Urinary malondialdehyde (MDA) and 8-hydroxy-2'-deoxyguanosine (8-OHdG) were measured up to day 14 post-CDDP (6 mg/kg) injection in rats. MDA and 8-OHdG expressions were examined in kidneys. RESULTS CDDP induced an increase in serum creatinine (Scr), blood urea nitrogen (BUN), and tubular damage at day 5, increased urinary MDA excretion and MDA expression in kidneys at day 1 (but returned to basal values by day 3), increased urinary excretion of 8-OHdG at day 5 till day 14 (though the number of 8-OHdG-positive tubular cells increased at day 5 and then gradually decreased). Urinary MDA levels at day 1 correlated significantly with Scr (rho = 0.721, P < 0.01) and tubular damage score (rho = 0.840, P < 0.01) at day 5. CONCLUSION Our findings demonstrated divergent changes of urinary oxidative stress markers in CDDP-induced ARF, and suggested that urinary MDA may be a useful marker for the prediction of the development of CDDP-induced ARF.
A Particle PHD Filter with Improved Resampling Design for Multiple Target Tracking

Multi-target tracking is a complex problem including time-varying number of targets and their states in the presence of data association uncertainty and clutter. In this article, we develop a novel implementation of Sequential Monte Carlo filter with a new improved partial resampling strategy in random finite sets framework. This algorithm provides an approach to increase diversity of particles and keep accuracy of filtering performance. Simulation results verify that for the MTT problems, the proposed algorithm could achieve better performance than the standard particle PHD filter.
RASSF1A and the rs2073498 Cancer Associated SNP

RASSF1A is one of the most frequently inactivated tumor suppressors yet identified in human cancer. It is pro-apoptotic and appears to function as a scaffolding protein that interacts with a variety of other tumor suppressors to modulate their function. It can also complex with the Ras oncoprotein and may serve to integrate pro-growth and pro-death signaling pathways. A SNP has been identified that is present in approximately 29% of European populations [rs2073498, A(133)S]. Several studies have now presented evidence that this SNP is associated with an enhanced risk of developing breast cancer. We have used a proteomics based approach to identify multiple differences in the pattern of protein/protein interactions mediated by the wild type compared to the SNP variant protein. We have also identified a significant difference in biological activity between wild type and SNP variant protein. However, we have found only a very modest association of the SNP with breast cancer predisposition.
EEG-based decoding of error-related brain activity in a real-world driving task

Objectives. Recent studies have started to explore the implementation of brain–computer interfaces (BCI) as part of driving assistant systems. The current study presents an EEG-based BCI that decodes error-related brain activity. Such information can be used, e.g., to predict driver’s intended turning direction before reaching road intersections. Approach. We executed experiments in a car simulator (N = 22) and a real car (N = 8). While subject was driving, a directional cue was shown before reaching an intersection, and we classified the presence or not of an error-related potentials from EEG to infer whether the cued direction coincided with the subject’s intention. In this protocol, the directional cue can correspond to an estimation of the driving direction provided by a driving assistance system. We analyzed ERPs elicited during normal driving and evaluated the classification performance in both offline and online tests. Results. An average classification accuracy of 0.698 ± 0.065 was obtained in offline experiments in the car simulator, while tests in the real car yielded a performance of 0.682 ± 0.059. The results were significantly higher than chance level for all cases. Online experiments led to equivalent performances in both simulated and real car driving experiments. These results support the feasibility of decoding these signals to help estimating whether the driver’s intention coincides with the advice provided by the driving assistant in a real car. Significance. The study demonstrates a BCI system in real-world driving, extending the work from previous simulated studies. As far as we know, this is the first online study in real car decoding driver’s error-related brain activity. Given the encouraging results, the paradigm could be further improved by using more sophisticated machine learning approaches and possibly be combined with applications in intelligent vehicles.
Implementing visual cervical cancer screening in Senegal: a cross-sectional study of risk factors and prevalence highlighting service utilization barriers

Background Senegal ranks 15th in the world in incidence of cervical cancer, the number one cause of cancer mortality among women in this country. The estimated participation rate for cervical cancer screening throughout Senegal is very low (6.9% of women 18–69 years old), especially in rural areas and among older age groups (only 1.9% of women above the age of 40 years). There are no reliable estimates of the prevalence of cervical dysplasia or risk factors for cervical dysplasia specific to rural Senegal. The goals of this study were to estimate the prevalence of cervical dysplasia in a rural region using visual inspection of the cervix with acetic acid (VIA) and to assess risk factors for cervical cancer control. Patients and methods We conducted a cross-sectional study in which we randomly selected 38 villages across the Kédougou region using a three-stage clustering process. Between October 2013 and March 2014, we collected VIA screening results for women aged 30–50 years and cervical cancer risk factors linked to the screening result. Results We screened 509 women; 5.6% of the estimated target population (9,041) in the region. The point prevalence of cervical dysplasia (positive VIA test) was 2.10% (95% confidence interval [CI]: 0.99–3.21). Moreover, 287 women completed the cervical cancer risk factor survey (56.4% response rate) and only 38% stated awareness of cervical cancer; 75.9% of the screened women were less than 40 years of age. Conclusion The overall prevalence of dysplasia in this sample was lower than anticipated. Despite both overall awareness and screening uptake being less than expected, our study highlights the need to address challenges in future prevalence estimates. Principally, we identified that the highest-risk women are the ones least likely to seek screening services, thus illustrating a need to fully understand demand-side barriers to accessing health services in this population. Targeted efforts to educate and motivate older women to seek screenings are needed to sustain an effective cervical cancer screening program.
Improving Simulation-Based Algorithms for Fitting ERGMs

Markov chain Monte Carlo methods can be used to approximate the intractable normalizing constants that arise in likelihood calculations for many exponential-family random graph models for networks. However, in practice, the resulting approximations degrade as parameter values move away from the value used to define the Markov chain, even in cases where the chain produces perfectly efficient samples. We introduce a new approximation method along with a novel method of moving toward a maximum likelihood estimator (MLE) from an arbitrary starting parameter value in a series of steps based on alternating between the canonical exponential-family parameterization and the mean-value parameterization. This technique enables us to find an approximate MLE in many cases where this was previously not possible. We illustrate these methods on a model for a transcriptional regulation network for E. coli, an example where previous attempts to approximate an MLE had failed, and a model for a well-known social network dataset involving friendships among workers in a tailor shop. These methods are implemented in the publicly available ergm package for R, and computer code to duplicate the results of this article is included in the online supplementary materials.
Stochastic Spot/Volatility Correlation in Stochastic Volatility Models and Barrier Option Pricing

Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local volatility/stochastic volatility mixture model, where the mixture parameter tunes that covariance. This paper defines an alternate model where the spot/volatility correlation is a separate mean-reverting stochastic variable which is itself correlated with spot. We also develop an efficient approximation for barrier option and one touch pricing in the model based on semi-static vega replication and compare it with Monte Carlo pricing. The approximation works well in markets where the risk neutral drift is modest.
Automatic Region Tracking for MR Glomerular Filtration Rate Analysis

Contrast-enhanced dynamic magnetic resonance imaging (MRI) acquisition is a common method to retrieve functional information from organs in the human body. Applied to the kidney, the observation of the signal evolution in the cortex of a MR-series gives access to the renal perfusion and filtration. The glomerular filtration rate (GFR) is in particular the most useful quantitative index of renal function. Since the rapid bolus passage hampers the use of gated sequences, fast sequences have to be employed to enable a data acquisition while free-breathing. As a result, the acquired data contains motion artifacts caused by the respiratory cycle, spontaneous movements and drifts which limit quantitative analysis of the data. Although these problems can in principle be addressed with motion correction algorithms applied in a post processing step, additional challenges arise from the fact that image amplitude changes not only due to motion but also due to the contrast change during bolus passage. This study proposes a 2D region tracking method for retrospective motion correction without sacrificing temporal resolution which addresses the latter point by a preparative learning phase.
Leveraging the Structure of the Semantic Web to Enhance Information Retrieval for Proteomics

Motivation: Proteomics researchers need to be able to quickly retrieve relevant information from the web and the biomedical literature. To improve information retrieval, we leverage the structure of the semantic web, developing an approach for joining it with the largely opposing paradigm of unsupervised web search. Results: Our approach uses a Resource-Description-Framework (RDF) graph that interrelates documents through their associated biological identifiers (e.g., protein ID). A search begins with a simple query term (UniProt identifier), which is expanded with terms extracted from documents in the RDF graph surrounding the query (''the subgraph''). We re-rank documents in the full corpus (e.g. all PubMed) by their cosine-similarity scores against a composite word-weight vector created from the subgraph. This vector is a weighted sum of individual word-weight vectors for documents at each node of the subgraph, taking into account the types of relationships between the central query identifier and the nodes connected to it. The computation also uses inverse document frequency (IDF) in a novel way to rescale the local word frequencies in the query's subgraph relative to that in other subgraphs. Applying our procedure to PubMed, we optimize weights for various relationships in the subgraph and benchmark overall performance in detail. Using a subgraph containing family relationships (from PFAM) results in a significant improvement in accuracy (as compared to not considering the subgraph in the search) when assessed against known relationships in the yeast literature. Moreover, we achieve this accuracy using only relatively simple and computationally efficient methods.
Age-related changes in seminal polymorphonuclear elastase in men with asymptomatic inflammation of the genital tract.

AIM To investigate age-related inflammatory events in the male genital tract. METHODS In a total of 4265 randomly collected patients attending the andrological outpatient clinic of the Center for Dermatology and Andrology, University of Giessen, Germany, ejaculate volume, pH-value, sperm concentration, total and progressive sperm motility, concentration of polymorphonuclear (PMN) elastase, number of peroxidase-positive cells and fructose were measured and correlated with patient's age. RESULTS While ejaculate volume, motility and fructose all correlated negatively with age, sperm concentration, PMN elastase and the pH-value showed a positive correlation. The prevalence of male genital tract inflammation (as defined by PMN elastase > 250 ng/mL) and its severity increased significantly. PMN elastase did not correlate with sperm motility. Fructose as a marker of seminal vesicle function showed a significant negative relationship with the PMN elastase levels, the number of peroxidase-positive cells and sperm motility. CONCLUSION The significant increases of PMN-elastase levels as marker of male genital tract inflammation in older men appear to be indicative of age-related changes in local immunoregulatory mechanisms. Because there is no association of PMN elastase with sperm motility, a direct inhibitory effect of this enzyme can be excluded.
Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.
PLD growth and PFM study of self-poled, mono-crystalline PZT thin films

In this work we report the growth of high quality, fully epitaxial, mono-crystalline Pb (Zr0.5T0.5)O3 thin films with step flow growth mode by PLD. For the first time the study of self-polarization in doped mono-crystalline PZT thin films using PFM is presented. The direction of self-polarization in pure PZT on SRO is upwards whereas that of Fe dopes PZT is downwards. The behavior is explained by trapped oxygen vacancies at the film-electrode interface as well as lead vacancies gradient in the bulk.
Monte Carlo) Resampling Technique in Validity Testing and Reliability Testing

paper describes the use of resampling technique in validity testing and reliability testing that are widely used in order to make the measurement tool in the field of psychology and education research. Resampling technique is the technique of resampling sample with replacement or without replacement. Resampling technique can be used to determine whether the item is valid or not by using the percentile confidence interval. The same technique can also be used to determine the significance of reliability coefficients in order to obtain a reliable measurement tool. This technique can also be used to obtain a higher reliability coefficient by reducing the sample size or by reducing the number of items used in the calculation. In this paper, the technique/method is described in the mini-data and case studies using real data that has 40 items and 48 respondents.
Intellectual capital and firm performance of US multinational firms

The resource‐based view of the firm maintains that firms achieve a sustainable comparative advantage and earn superior profits by owning or controlling tangible as well as intangible strategic assets. The stakeholder view recommends that a better measure of financial performance than accounting profit is the total wealth created or net value added. Accordingly, this study examines the relationship between a return on total assets based on net value added (a la stakeholder view) and the specific intangible asset of intellectual capital to test the resource‐based view of the firm. The results, using a sample of US multinational firms, are statistically significant in support of both the resource‐based and stakeholder views.
Can Stock Price Fundamentals Properly Be Captured? Using Markov Switching in Heteroskedasticity Models to Test Identification Schemes

Structural identification schemes are of essential importance to vector autoregressive (VAR) analysis. This paper tests a commonly used structural parameter identification scheme to assess whether it can properly capture fundamental and non-fundamental shocks to stock prices. In particular, five related structural models, which are widely used in the literature on assessing stock price determinants are considered. They are either specified in vector error correction (VEC) or in VAR form. Restrictions on the long-run effects matrix are used to identify the structural parameters. These identifying restrictions are tested by means of a Markov switching in heteroskedasticity model. It is found that for two of the five models considered, the long-run identification scheme appropriately classifies shocks as being either fundamental or non-fundamental. A series of robustness tests are performed, which largely confirm the initial findings.