Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital filters in adaptive time-stepping

Adaptive time-stepping based on linear digital control theory has several advantages: the algorithms can be analyzed in terms of stability and adaptivity, and they can be designed to produce smoother stepsize sequences resulting in significantly improved regularity and computational stability. Here, we extend this approach by viewing the closed-loop transfer map Hϕ : logϕ ↦ log h as a digital filter, processing the signal logϕ (the principal error function) in the frequency domain, in order to produce a smooth stepsize sequence log h. The theory covers all previously considered control structures and offers new possibilities to construct stepsize selection algorithms in the asymptotic stepsize-error regime. Without incurring extra computational costs, the controllers can be designed for special purposes such as higher order of adaptivity (for smooth ODE problems) or a stronger ability to suppress high-frequency error components (nonsmooth problems, stochastic ODEs). Simulations verify the controllers' ability to produce stepsize sequences resulting in improved regularity and computational stability.
Minimal Repetition Dynamic Checkpointing Algorithm for Unsteady Adjoint Calculation

Adjoint equations of differential equations have seen widespread applications in optimization, inverse problems, and uncertainty quantification. A major challenge in solving adjoint equations for time dependent systems has been the need to use the solution of the original system in the adjoint calculation and the associated memory requirement. In applications where storing the entire solution history is impractical, checkpointing methods have frequently been used. However, traditional checkpointing algorithms such as revolve require a priori knowledge of the number of time steps, making these methods incompatible with adaptive time stepping. We propose a dynamic checkpointing algorithm applicable when the number of time steps is a priori unknown. Our algorithm maintains a specified number of checkpoints on the fly as time integration proceeds for an arbitrary number of time steps. The resulting checkpoints at any snapshot during the time integration have the optimal repetition number. The efficiency of our algorithm is demonstrated both analytically and experimentally in solving adjoint equations. This algorithm also has significant advantage in automatic differentiation when the length of execution is variable.
Round-trip privacy with nfsv4

With the advent of NFS version 4, NFS security is more important than ever. This is because a main goal of the NFSv4 protocol is suitability for use on the Internet, whereas previous versions were used mainly on private networks. To address these security concerns, the NFSv4 protocol utilizes the RPCSEC GSS protocol and allows clients and servers to negotiate security at mount-time. However, this provides privacy only while data is traveling over the wire. We believe that file servers accessible over the Internet should contain only encrypted data. We present a round-trip privacy scheme for NFSv4, where clients encrypt file data for write requests, and decrypt the data for read requests. The data stored by the server on behalf of the clients is encrypted. This helps ensure privacy if the server or storage is stolen or compromised. As the NFSv4 protocol was designed with extensibility, it is the ideal place to add roundtrip privacy. In addition to providing a higher level of security than only over-the-wire encryption, our technique is more efficient, as the server is relieved from performing encryption and decryption. We developed a prototype of our round-trip privacy scheme. In our performance evaluation, we saw throughput increases of up to 24%, as well as good scalability.
Ultrasonography of Median Nerve and Electrophysiologic Severity in Carpal Tunnel Syndrome

Objective To investigate the correlation of the ultrasonographic wrist-to-forearm median nerve area ratio (WFR) and cross sectional area of median nerve at the wrist (CSA-W) to the electrophysiologic severity in patients with carpal tunnel syndrome (CTS). Method One hundred and ten wrists electrophysiologically graded as mild, moderate, and severe CTS and 38 healthy controls underwent ultrasonography of median nerve at the distal wrist crease and mid-forearm. WFR and CSA-W were analyzed according to the severity of CTS. Results WFR was 1.12±0.14, 1.91±0.33, 2.27±0.47 and 3.02±0.97 and the CSAs-W was 7.23±1.67 mm2, 13.51±3.72 mm2, 14.67±2.93 mm2, and 18.74±6.01 mm2 in controls, mild (n=28), moderate (n=46), and severe (n=36) CTS, respectively. CSA-W displayed significant differences between the control and the mild CTS, moderate CTS and severe CTS groups. However, there was no significant difference between mild CTS and moderate CTS groups. WFR revealed significant difference between all groups. The sensitivity and specificity of the WFR in grading the severity of CTS were higher than those of the CSA-W. Conclusion Ultrasonography is a useful complementary tool for the evaluation of CTS. Both WFR and CSA-W are highly correlated with severity grade of CTS. However, WFR is superior to CSA-W for diagnosis and grading of the severity of CTS.
Performance Analysis of an Integrated GPS / Inertial Attitude Determination System

The performance of an integrated GPS/inertial attitude determination system is investigated using a linear covariance analysis. The principles of GPS interferometry are reviewed, and the major error sources of both interferometers and gyroscopes are discussed and modeled. A new figure of merit, Attitude Dilution of Precision (ADOP), is defined for two possible GPS attitude determination methods, namely single difference and double difference interferometry. Based on this figure of merit, a satellite selection scheme is proposed. The performance of the integrated GPS/inertial attitude determination system is determined using a linear covariance analysis. Based on this analysis, it is concluded that the baseline errors (i.e., knowledge of the GPS interferometer baseline relative to the vehicle coordinate system) are the limiting factor in system performance. By reducing baseline errors, it should be possible to use lower quality gyroscopes without significantly reducing performance. For the cases considered, single difference interferometry is only marginally better than double difference interferometry. Finally, the performance of the system is found to be relatively insensitive to the satellite selection technique. Thesis Supervisor: Professor Steven R. Hall Title: Associate Professor, Department of Aeronautics and Astronautics Technical Supervisor: Kevin B. Mahar Title: Senior Member Technical Staff, C. S. Draper Laboratory, Inc. Technical Supervisor: Kenneth M. Spratlin Title: Senior Member Technical Staff, C. S. Draper Laboratory, Inc.
A Dirichlet Process Mixture Model for Spherical Data

Since the geodesic between any two points is the shortest path on the manifold between the two of them, we know that p has to lie on the geodesic. On the unit sphere we can describe the location on the geodesic as a rotation about the axis defined by the cross product of the two vectors 〈x〉a and 〈x〉b by an angle θa, which we define such that the location of 〈x〉a on the geodesic has θa = 0. This implies that the location of 〈x〉b on the geodesic has angle θb = arccos(〈x〉a 〈x〉b). With this intuition we can reformulate the optimization problem in terms of angles on the geodesic as:
Visualization in the Einstein Year 2005: a case study on explanatory and illustrative visualization of relativity and astrophysics

In this application paper, we report on over fifteen years of experience with relativistic and astrophysical visualization, which has been culminating in a substantial engagement for visualization in the Einstein Year 2005 - the 100/sup th/ anniversary of Einstein's publications on special relativity, the photoelectric effect, and Brownian motion. This paper focuses on explanatory and illustrative visualizations used to communicate aspects of the difficult theories of special and general relativity, their geometric structure, and of the related fields of cosmology and astrophysics. We discuss visualization strategies, motivated by physics education and didactics of mathematics, and describe what kind of visualization methods have proven to be useful for different types of media, such as still images in popular-science magazines, film contributions to TV shows, oral presentations, or interactive museum installations. Although our visualization tools build upon existing methods and implementations, these techniques have been improved by several novel technical contributions like image-based special relativistic rendering on GPUs, an extension of general relativistic ray tracing to manifolds described by multiple charts, GPU-based interactive visualization of gravitational light deflection, as well as planetary terrain rendering. The usefulness and effectiveness of our visualizations are demonstrated by reporting on experiences with, and feedback from, recipients of visualizations and collaborators.
Modeling Credit Risk for Smes: Evidence from the Us Market

AbstractConsidering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord, we develop a distress prediction model specifically for the SME sector and to analyze its effectiveness compared to a generic corporate model. The behavior of financial measures for SMEs is analyzed and the most significant variables in predicting the entities' credit worthiness are selected in order to construct a default prediction model. Using a logit regression technique on a panel of over 2,000 US firms (with sales less than $65 million) over the period 1994–2002, we develop a one-year default prediction model. This model has an out of sample prediction power which is almost 30 percent higher than a generic corporate model. An associated objective is to observe our model's ability to lower bank capital requirements considering the new Basel Capital Accord's rules for SMEs.
Case-Control Study Examining the Association between Selective Serotonin Reuptake Inhibitors Use and Hepatocellular Carcinoma

Objectives: The purpose of the study was to assess the relationship between selective serotonin reuptake inhibitors use and hepatocellular carcinoma in Taiwan. Methods: Using the database of the Taiwan National Health Insurance Program, we conducted a case-control study to identify 4901 subjects aged 20 years and more with newly diagnosed hepatocellular carcinoma in 2000–2013 as the cases. We randomly selected 19604 subjects aged 20 years and more without hepatocellular carcinoma as the controls. Both cases and controls were matched with sex and age. Ever use of selective serotonin reuptake inhibitors was defined as a subject who had at least a prescription for selective serotonin reuptake inhibitors before index date. Never use was defined as a subject who never had a prescription for selective serotonin reuptake inhibitors before index date. The odds ratio (OR) and 95% confidence interval (CI) for hepatocellular carcinoma associated with selective serotonin reuptake inhibitors use was estimated by the multivariable logistic regression model. Results: Among subjects with any one of the comorbid conditions associated with hepatocellular carcinoma, the adjusted OR of hepatocellular carcinoma was 0.89 (95% CI 0.75, 1.06) for subjects with ever use of selective serotonin reuptake inhibitors, comparing with never use. Conclusion: The findings indicate that among subjects with any one of the comorbid conditions associated with hepatocellular carcinoma, no significant association can be detected between selective serotonin reuptake inhibitors use and hepatocellular carcinoma.
Gene delivery into malignant cells in vivo by a conjugated adenovirus/DNA complex.

Current viral delivery systems suffer from disadvantages that may limit the rate at which therapeutic gene expressing constructs can be tested both in vitro and in vivo. In this study, our focus was to develop a simple gene delivery system for the rapid and reproducible testing of therapeutic genes in cancer cells both in vitro and in vivo. We report here that a delivery system based on using a conjugated adenovirus in complex from with a DNA plasmid can be used for not only delivering genes in vitro but also for efficient and reproducible delivery in vivo. Replication defective adenoviral particles were chemically modified by covalent attachment of poly-L-lysine (PLL) to the viral capsid, allowing for direct interaction with DNA. The adenovirus/PLL conjugate (Adv/PLL) was used to deliver the plasmid pCMV/beta-gal to several different cancer cell lines (i.e., lung, cervical) in vitro and resulted in transduction efficiencies as high as 52% as determined by histochemical staining. On direct intralesional injection of the Adv/PLL/DNA complex into subcutaneous tumors, transduction efficiencies greater than 35% could also be achieved. As a result, this system provides a simple method for delivering and testing therapeutic genes in cells both in vitro and in vivo, prior to the further development of gene therapy vectors for both malignant and benign disease.
Nuclear actin: to polymerize or not to polymerize

The form and function of actin in the nucleus have been enigmatic for over 30 years. Recently actin has been assigned numerous functional roles in the nucleus, but its form remains a mystery. The intricate relationship between actin form and function in the cytoplasm implies that understanding the structural properties of nuclear actin is elementary to fully understanding its function. In this issue, McDonald et al. (p. 541) use fluorescence recovery after photobleaching (FRAP) to tackle the question of whether nuclear actin exists as monomers or polymers.
Autoantibody Approach for Serum-Based Detection of Head and Neck Cancer

Currently, no effective tool exists for screening or early diagnosis of head and neck squamous cell carcinoma (HNSCC). Here, we describe an approach for cancer detection based on analysis of patterns of serum immunoreactivity against a panel of biomarkers selected using microarray-based serologic profiling and specialized bioinformatics. We biopanned phage display libraries derived from three different HNSCC tissues to generate 5,133 selectively cloned tumor antigens. Based on their differential immunoreactivity on protein microarrays against serum immunoglobulins from 39 cancer and 41 control patients, we reduced the number of clones to 1,021. The performance of a neural network model (Multilayer Perceptron) for cancer classification on a data set of 80 HNSCC and 78 control samples was assessed using 10-fold cross-validation repeated 100 times. A panel of 130 clones was found to be adequate for building a classifier with sufficient sensitivity and specificity. Using these 130 markers on a completely new and independent set of 80 samples, an accuracy of 84.9% with sensitivity of 79.8% and specificity of 90.1% was achieved. Similar performance was achieved by reshuffling of the data set and by using other classification models. The performance of this classification approach represents a significant improvement over current diagnostic accuracy (sensitivity of 37% to 46% and specificity of 24%) in the primary care setting. The results shown here are promising and show the potential use of this approach toward eventual development of diagnostic assay with sufficient sensitivity and specificity suitable for detection of early-stage HNSCC in high-risk populations. (Cancer Epidemiol Biomarkers Prev 2007;16(11):2396–405)
Linux vs. Windows in the Middle Kingdom: A Strategic Valuation Model for Platform Competition

This paper examines factors at work when an established standard competes with an open-source offering. Although the argument is often framed along price or technical features, these aspects may describe only a portion of the consumer’s adoption calculus. Modeling the consumer’s technology platform adoption decision is critical to developing market preservation for incumbents and market invasion strategies by rivals. This paper proposes a theory grounded, quantitative model for technology adoption in the presence of network effects, switching costs, and software piracy. We apply the model as a strategy development and market analysis tool to the context of the Linux market in China. A series of strategies for the new rival, as well as strategies for the incumbent, are presented. Findings from this study suggest approaches not only for the context at hand, but also for other scenarios where open-source, network effects, software piracy, and extreme income variances exist.
A session management method of Augmented Video Services in Access Grid

The Access Grid (AG) is an important component of grid, and it can provide immersive, interactive and collaborative access to grid applications. Augmented Video Services (AVS) in AG build shared Augmented Reality environment to extend the service functionality of AG. It merges the real video scene of AG and 3D geometric model of grid services' results to allow users' manipulating the model collaboratively in the real video scene. Due to the differences between the augmented video stream and the pure video stream which AG commonly supports, the existed session management of the default video services has not been applicable to augmented video session. This paper addresses the problem of augmented video stream sharing in AG session, and presents a session management method of AVS and techniques of session addition, deletion and modification based on this method. After presenting this technique, this paper describes its use in a prototype AG application, and results show that this method can properly solve the management problem of augmented video session and correctly share the augmented video stream among AG users.
Lipopeptides as main ingredients for inhibition of fungal phytopathogens by Bacillus subtilis/amyloliquefaciens

Some isolates of the Bacillus subtilis/amyloliquefaciens species are known for their plant protective activity against fungal phytopathogens. It is notably due to their genetic potential to form an impressive array of antibiotics including non‐ribosomal lipopeptides (LPs). In the work presented here, we wanted to gain further insights into the relative role of these LPs in the global antifungal activity of B. subtilis/amyloliquefaciens. To that end, a comparative study was conducted involving multiple strains that were tested against four different phytopathogens. We combined various approaches to further exemplify that secretion of those LPs is a crucial trait in direct pathogen ward off and this can actually be generalized to all members of these species. Our data illustrate that for each LP family, the fungitoxic activity varies in function of the target species and that the production of iturins and fengycins is modulated by the presence of pathogens. Our data on the relative involvement of these LPs in the biocontrol activity and modulation of their production are discussed in the context of natural conditions in the rhizosphere.
Effect of Acute Sympathectomy on Responses to Angiotensin and Norepinephrine

The vasopressor response to angiotensin administered intra-arterially to the perfused hindquarters of the dog was reduced significantly after acute sympathectomy. Responses to norepinephrine and tyramine remained unchanged. Similar results were obtained following gangliouic blockade with hexamethonium and cervical spinal transection. After the response to augiotensin was reduced following sympathectomy, the cut lumbar sympathetic nerves were stimulated electrically. During the period of stimulation, an increase in the vasoconstrictor effect to angiotensin was obtained, but complete restoration to the control magnitude was not seen consistently. Possible mechanisms for the reduction in the response to angiotensin following sympathectomy are discussed. The present evidence suggests that the tonic discharge of normally functioning sympathetic nerves is capable of facilitating the response to angiotensin and that sympathectomy results in an abolition of this effect.
A gentle introduction to quantile regression for ecologists

Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable (y) distribution and the measured predictive factors (X). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogen.
Universes collide: combining immunotherapy with targeted therapy for cancer.

UNLABELLED There have been significant advances in the past several years with regard to targeted therapy and immunotherapy for cancer. This is highlighted in melanoma, where treatment with targeted therapy (against the BRAF oncoprotein) results in responses in the majority of patients, although the duration of response is limited. In contrast, treatment with immunotherapy results in a lower response rate, but one that tends to be more durable. Insights about mechanisms of response and potential synergy between these treatment strategies for melanoma are a focus of this review, with opportunities to extend these insights to the treatment of other cancers. SIGNIFICANCE Two major advances in melanoma have occurred concurrently and involve treatment with targeted therapy and immune checkpoint blockade. However, each of these approaches has limitations with regard to overall response rates or duration of response. To address this, investigators have proposed combining these strategies, and this concept is being tested empirically in clinical trials. There is a scientific rationale supporting the combination of targeted therapy and immunotherapy, and these concepts are discussed herein.
Face Recognition using Eigenface

Face Recognition using Eigenface Yogesh Tayal, Pramod Kumar Pandey, D. B. V. Singh Department of Electrical and Instrumentation Engineering Institute of Technology & Management Gwalior M.P. _____________________________________________________________________________________________ AbstractTo recognize an image from a database is typical task due to the image of a face changes with facial expression, age, viewpoint, illumination conditions, noise etc. With the help of Facial expression we can read the emotion, intention etc these are the most powerful, natural, and immediate means for human beings to communicate. Facial expression carries crucial information about the mental, emotional and even physical states of the conversation. This paper proposes an Eigen based face recognition algorithm for recognize an image from the database. Eigen face has proven to be a useful and robust cue for face recognition, localization and tracking. KeywordsFace Recognition, Eigenface, Eigen-values, Pose Invariance and Illumination Invariance. _____________________________________________________________________________________________