Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Hepatocellular Carcinoma by Detection of Aberrant Promoter Methylation in Serum DNA

Purpose: Most hepatocellular carcinomas (HCC) are diagnosed at an advanced stage. Hypermethylation of CpG islands in promoter regions is now recognized as an important early event in carcinogenesis and detection of methylated DNA has been suggested as a potential biomarker for early detection of cancer. There are no studies on epigenetic changes in samples from HCC patients before diagnosis. We explored the possible diagnostic value of aberrant promoter hypermethylation of three tumor suppressor genes in serum DNA for early detection of HCC. Experimental Design: Aberrant promoter hypermethylation was investigated in DNA isolated from the serum of 50 HCC patients who provided repeated blood samples before diagnosis and 50 controls enrolled in a cancer screen program in Taiwan. Methylation-specific PCR was used to determine the methylation status of p16, p15, and ras association domain family 1A (RASSF1A). Results: Among cases, aberrant methylation was found in serum DNA 1 to 9 years before clinical HCC diagnosis. RASSF1A had the highest frequency of hypermethylation with 35 (70%) cases having at least one positive sample compared with 22 (44%) for p16 and 12 (22%) for p15. Six subjects were hypermethylation negative for all three genes. For the 50 controls, promoter hypermethylation was found in three and two subjects for RASSF1A and p16, respectively; none had methylation of p15. A receiver operating characteristic curve that included clinical risk factors (age, HBsAg status, anti–hepatitis C virus status, smoking, and alcohol status) and hypermethylation biomarkers gave an overall predictive accuracy of 89% with sensitivity and specificity 84% and 94%, respectively. Conclusions: The analysis of epigenetic changes on RASSF1A, p16, and p15 tumor suppressor genes in serum DNA may be a valuable biomarkers for early detection in populations at high risk of HCC.
Long Short-Term Memory Over Tree Structures

The chain-structured long short-term memory (LSTM) has showed to be effective in a wide range of problems such as speech recognition and machine translation. In this paper, we propose to extend it to tree structures, in which a memory cell can reflect the history memories of multiple child cells or multiple descendant cells in a recursive process. We call the model S-LSTM, which provides a principled way of considering long-distance interaction over hierarchies, e.g., language or image parse structures. We leverage the models for semantic composition to understand the meaning of text, a fundamental problem in natural language understanding, and show that it outperforms a state-of-the-art recursive model by replacing its composition layers with the S-LSTM memory blocks. We also show that utilizing the given structures is helpful in achieving a performance better than that without considering the structures.
Accuracy investigation of an ultra-wideband time domain microwave imaging system

We investigate the measurement accuracy of an ultra-wideband time domain microwave tomography system. A phantom is imaged by means of the system and the reconstructed images are compared to those obtained with an ultra-wideband frequency domain system. The results suggest that the permittivity reconstructions obtained by means of the time domain and the frequency domain systems are very similar to each other, but the conductivity profile reconstructed from time domain measurements presents worse quality than that obtained from frequency domain measurements.
On learning to localize objects with minimal supervision

Learning to localize objects with minimal supervision is an important problem in computer vision, since large fully annotated datasets are extremely costly to obtain. In this paper, we propose a new method that achieves this goal with only image-level labels of whether the objects are present or not. Our approach combines a discriminative submodular cover problem for automatically discovering a set of positive object windows with a smoothed latent SVM formulation. The latter allows us to leverage efficient quasi-Newton optimization techniques. Our experiments demonstrate that the proposed approach provides a 50% relative improvement in mean average precision over the current state-of-the-art on PASCAL VOC 2007 detection.
A Comparison of Machine Measures of Text Document Similarity with Human Judgments

A central problem in the information sciences involves measuring the semantic similarity between text documents. Although this is fundamentally a cognitive modeling problem, existing methods have not been assessed in terms of their ability to emulate human judgments of similarity. To address this problem, we conducted a controlled psychological experiment that collected repeated similarity measures for each pair of documents in a small corpus of short news documents. We then considered the ability of a variety of established methods using word-based, n-gram and Latent Semantic Analysis (LSA) approaches to model these human judgments. Our most important finding is that none of the methods we examined produced good correlations with the human judgments. The best performed LSA model produced correlations of about 0.6. The best performed word-based and n-gram models achieved correlations closer to 0.5. Many of the variations we considered showed almost no ∗Correspondence should be addressed to: Michael D. Lee, Department of Psychology, University of Adelaide, SA 5005, AUSTRALIA. Telephone: +61 8 8303 6096, Facsimile: +61 8 8303 3770, E-mail: michael.lee@adelaide.edu. au, URL: http://www.psychology. adelaide.edu. au/members/staff/michaellee/homepage
Defective Differentiation of Myeloid and Plasmacytoid Dendritic Cells in Advanced Cancer Patients is not Normalized by Tyrosine Kinase Inhibition of the Vascular Endothelial Growth Factor Receptor

Tumor-derived vascular endothelial growth factor (VEGF) has previously been identified as a causative factor in the disturbed differentiation of myeloid dendritic cells (DC) in advanced cancer patients. Here, we investigated the potential of vascular endothelial growth factor receptor (VEGFR) tyrosine kinase (TK) inhibition to overcome this defective DC differentiation. To this end, peripheral blood DC (PBDC) precursor and subset frequencies were measured in 13 patients with advanced cancer before and after treatment with AZD2171, a TK inhibitor (TKI) of VEGFR, coadministered with gefitinib, and an epidermal growth factor receptor (EGFR) TKI. Of note, not only myeloid DC but also plasmacytoid DC frequencies were significantly reduced in the blood of the cancer patients prior to treatment, as compared to healthy controls. Moreover, besides an accumulated population of immature myeloid cells (ImC), a population of myeloid suppressor cells (MSC) was significantly increased. Upon systemic VEGFR TK inhibition, DC frequencies did not increase, whereas the rate of circulating MSC showed a slight, but not significant, decrease. In conclusion, TK inhibition of VEGFR with AZD2171 does not restore the defective PBDC differentiation observed in advanced cancer patients.
Eclipsing binaries in extrasolar planet transit surveys: the case of SuperWASP

Extrasolar planet transit surveys will also detect eclipsing binaries. Using a comprehensive binary population synthesis scheme, we investigate the statistical properties of a sample of eclipsing binaries that is detectable by an idealized extrasolar planet transit survey with specifications broadly similar to those of the Wide Angle Search for Planets (SuperWASP) project. In this idealized survey, the total number of detectable single stars in the Galactic disc is of the order of 106-107, while, for a flat initial mass ratio distribution, the total number of detectable eclipsing binaries is of the order of 104-105. The majority of the population of detectable single stars is made up of main-sequence stars (~60 per cent), horizontal-branch stars (~20 per cent), and giant-branch stars (~10 per cent). The largest contributions to the population of detectable eclipsing binaries stem from detached double main-sequence star binaries (~60 per cent), detached giant-branch main-sequence star binaries (~20 per cent), and detached horizontal-branch main-sequence star binaries (~10 per cent). White dwarf main-sequence star binaries make up approximately 0.3 per cent of the sample. The ratio of the number of eclipsing binaries to the number of single stars detectable by the idealized SuperWASP survey varies by less than a factor of 2.5 across the sky, and decreases with increasing Galactic latitude. It is found to be largest in the direction of the Galactic longitude l=-7 b 5 and the Galactic latitude b=-22 b 5. We also show that the fractions of systems in different subgroups of eclipsing binaries are sensitive to the adopted initial mass ratio or initial secondary mass distribution, which is one of the poorest constrained input parameters in present-day binary population synthesis calculations. This suggests that once statistically meaningful results from transit surveys are available, they will be able to significantly improve the predictive power of population synthesis studies of interacting binaries and related objects.
Reply to Leland B . Yeager on " Mises and Hayek on Calculation and Knowledge "

I n this article on "Mises and Hayek on Calculation and Knowledge ," Leland Yeager argues against the view recently propounded by Murray Rothbard, Jeffrey Herbener, and myself that calculation and knowledge constitute separate and distinct problems of economic organization and that Ludwig von Mises attributed the impossibility of socialism exclusively to its inability to solve the former problem. In rebuttal, Yeager alleges that calculation, as this term is used by Salerno, Rothbard, and Herbener (henceforward, SRH) refers narrowly to a trivial arithmetic operation and that it is, therefore, preposterous and a violation of a putative principle of hermeneutics, i.e., "a heuristic principle of textual interpretation," to identify, as SRH do, calculation in this sense as the crux of Mises's critique of socialist central planning. Yeager seeks to buttress his hermeneutical case by arguing that if the knowledge problem is solved, i.e., if the central planners are miraculously endowed with knowledge of all previously discovered production functions currently used or potentially useful, in addition to exhaustive and minutely detailed information regarding the quantities, qualities, and locations of existing resources and the global set of consumer value scales (comprehensively defined to include leisure and time preferences as well as preferences for the various types of labor), then all that remains to be done to effect a rational or "Pareto optimal" allocation of resources is to address a relatively tractable problem in linear programming that can be *Joseph T.Salerno is associate professor of economics a t the Lubin School of Business a t Pace University. like to thank two anonymous referees for many thoughtful suggestions on stylistic and substantive matters that contributed significantly to improving this article.
Norges Teknisk-naturvitenskapelige Universitet Residuals and Functional Form in Accelerated Life Regression Models Residuals and Functional Form in Accelerated Life Regression Models

We study residuals of parametric accelerated failure time (AFT) models for censored data, with the main aim of inferring the correct functional form of possibly misspecified covariates. We demonstrate the use of the methods by a simulated example and by applications to two reliability data sets. We also consider briefly a corresponding approach for parametric proportional hazards models.
Time-varying autoregressive parameter estimation of cauchy processes by particle filters

In this work, a new method is proposed in order to sequentially estimate the time-varying parameters of a Cauchy distributed process. For this purpose, particle filters, which are used in non-Gaussian and nonlinear Bayesian applications, are utilised. The proposed method forms a basis for the possible future applications of the α-stable distributions with timevarying autoregressive coefficients, since it is the first general method that can be used for the estimation of such coefficients without using any restrictions on the parameters. The method is tested both for abruptly and slowly changing autoregressive parameters and observed to be performing very well.
Conformational Ordering of Biomolecules in the Gas Phase: Nitrogen Collision Cross Sections Measured on a Prototype High Resolution Drift Tube Ion Mobility-Mass Spectrometer

Ion mobility-mass spectrometry measurements which describe the gas-phase scaling of molecular size and mass are of both fundamental and pragmatic utility. Fundamentally, such measurements expand our understanding of intrinsic intramolecular folding forces in the absence of solvent. Practically, reproducible transport properties, such as gas-phase collision cross-section (CCS), are analytically useful metrics for identification and characterization purposes. Here, we report 594 CCS values obtained in nitrogen drift gas on an electrostatic drift tube ion mobility-mass spectrometry (IM-MS) instrument. The instrument platform is a newly developed prototype incorporating a uniform-field drift tube bracketed by electrodynamic ion funnels and coupled to a high resolution quadrupole time-of-flight mass spectrometer. The CCS values reported here are of high experimental precision (±0.5% or better) and represent four chemically distinct classes of molecules (quaternary ammonium salts, lipids, peptides, and carbohydrates), which enables structural comparisons to be made between molecules of different chemical compositions for the rapid “omni-omic” characterization of complex biological samples. Comparisons made between helium and nitrogen-derived CCS measurements demonstrate that nitrogen CCS values are systematically larger than helium values; however, general separation trends between chemical classes are retained regardless of the drift gas. These results underscore that, for the highest CCS accuracy, care must be exercised when utilizing helium-derived CCS values to calibrate measurements obtained in nitrogen, as is the common practice in the field.
An Efficient Provable Data Possession Scheme with Data Dynamics

Ateniese et al proposed an efficient Provable Data Possession scheme which uses only hash and symmetric-key cryptographic functions, but it cannot support block insertion. To achieve full data dynamics, a SN-BN table which maps the logical indices of blocks to their physical ones is introduced. The SN (Serial Number) is used to determine which blocks are included in tags, while the corresponding BN (Block Number) is used to retrieve the actual data blocks. Therefore, the remaining tags need not to be recomputed with new blocks while a block is inserted. Therefore, it can support full data dynamics including block modification, deletion, insertion and appending. Because of its high efficiency and full dynamics, our scheme is very suitable for applications in which some resource-constrained clients are used to check the data possession and the data needs to be updated after being outsourced.
Self-Tuning of the PID Controller for a Digital Excitation Control System

This paper proposes an indirect method for self-tuning of the proportional, integral, and derivative (PID) controller gains. Some of the modern voltage regulator systems are utilizing PID control for stabilization. Based on given excitation system parameters, several PID tuning approaches are reported. Since in general, these parameters are not available during commissioning, specifically the machine time constants, this lack of information causes a considerable time delay and cost of fuel usage for commissioning the automatic voltage regulator (AVR). To reduce the commissioning time and cost, the excitation system parameters are automatically identified and the PID gains are calculated using well-developed algorithms. Recursive least-square (RLS) with linearization via feedback is proposed to identify the system parameters. The performance of the proposed method is evaluated with several generator sets. With self-tuned PID gains, commissioning is accomplished very quickly with excellent performance results.
The Meta Distribution of the SIR in Poisson Bipolar and Cellular Networks

The calculation of the SIR distribution at the typical receiver (or, equivalently, the success probability of transmissions over the typical link) in Poisson bipolar and cellular networks with Rayleigh fading is relatively straightforward, but it only provides limited information on the success probabilities of the individual links. This paper focuses on the meta distribution of the SIR, which is the distribution of the conditional success probability Ps given the point process, and provides bounds, an exact analytical expression, and a simple approximation for it. The meta distribution provides fine-grained information on the SIR and answers questions such as “What fraction of users in a Poisson cellular network achieve 90% link reliability if the required SIR is 5 dB? ” Interestingly, in the bipolar model, if the transmit probability p is reduced while increasing the network density λ such that the density of concurrent transmitters λp stays constant as p → 0, Ps degenerates to a constant, i.e., all links have exactly the same success probability in the limit, which is the one of the typical link. In contrast, in the cellular case, if the interfering base stations are active independently with probability p, the variance of Ps approaches a non-zero constant when p is reduced to 0 while keeping the mean success probability constant.
Effects of Cu/Zn Superoxide Dismutase (sod1) Genotype and Genetic Background on Growth, Reproduction and Defense in Biomphalaria glabrata

Resistance of the snail Biomphalaria glabrata to the trematode Schistosoma mansoni is correlated with allelic variation at copper-zinc superoxide dismutase (sod1). We tested whether there is a fitness cost associated with carrying the most resistant allele in three outbred laboratory populations of snails. These three populations were derived from the same base population, but differed in average resistance. Under controlled laboratory conditions we found no cost of carrying the most resistant allele in terms of fecundity, and a possible advantage in terms of growth and mortality. These results suggest that it might be possible to drive resistant alleles of sod1 into natural populations of the snail vector for the purpose of controlling transmission of S. mansoni. However, we did observe a strong effect of genetic background on the association between sod1 genotype and resistance. sod1 genotype explained substantial variance in resistance among individuals in the most resistant genetic background, but had little effect in the least resistant genetic background. Thus, epistatic interactions with other loci may be as important a consideration as costs of resistance in the use of sod1 for vector manipulation.
Control of vehicle vibration using the combined compliant actuator and suspension system

This paper deals with the development of a vehicle vibration control system by integrating a compliant actuator in the existing vehicle suspension system. The compliant actuator is attached to the vehicle body and consists of a servo-motor, a compliant element and a pinion-rack set. A vehicle ride model is developed for the vibration control performance analysis, combining the vehicle suspension system with the compliant actuator model. The investigation results show that the compliant actuator can provide beneficial passive and active vibration control characteristics, particularly at the low frequency region around the vehicle body resonance. The operational bandwidth of the compliant actuator can be adjusted according to the selected compliant stiffness and it has the benefits of protecting the actuator against potential shocks received during vehicle ride. These benefits offer an attractive alternative for the actuator used in vehicle suspension system, compared to the conventional rigid actuator. The active vibration control results using an output feedback control demonstrate the effectiveness of the proposed system in reducing the vehicle body acceleration at important low frequencies.
Papier-Mache: toolkit support for tangible input

Tangible user interfaces (TUIs) augment the physical world by integrating digital information with everyday physical objects. Currently, building these UIs requires "getting down and dirty" with input technologies such as computer vision. Consequently, only a small cadre of technology experts can currently build these UIs. Based on a literature review and structured interviews with nine TUI researchers, we created Papier-Mâché, a toolkit for building tangible interfaces using computer vision, electronic tags, and barcodes. Papier-Mache introduces a high-level event model for working with these technologies that facilitates technology portability. For example, an application can be prototyped with computer vision and deployed with RFID. We present an evaluation of our toolkit with six class projects and a user study with seven programmers, finding the input abstractions, technology portability, and monitoring window to be highly effective.
Possible X-Ray Diagnostic for Jet/Disk Dominance in Type 1 AGNs

Using Rossi X-Ray Timing Explorer Seyfert 1 and 1.2 data spanning 9 years, we study correlations between X-ray spectral features. The sample consists of 350 time-resolved spectra from 12 Seyfert 1 and 1.2 galaxies. Each spectrum is fitted to a model with an intrinsic power-law X-ray spectrum produced close to the central black hole that is reprocessed and absorbed by material around the black hole. To test the robustness of our results, we performed Monte Carlo simulations of the spectral sample. We find a complex relationship between the iron line equivalent width (EW) and the underlying power-law index (Γ). The data reveal a correlation between Γ and EW, which turns over at Γ ≲ 2, but finds a weak anticorrelation for steeper photon indices. We propose that this relationship is driven by dilution of a disk spectrum (which includes the narrow iron line) by a beamed jet component and hence could be used as a diagnostic of jet dominance. In addition, our sample shows a strong correlation between R and Γ, but we find that it is likely the result of modeling degeneracies. We also see the X-ray Baldwin effect (an anticorrelation between the 2-10 keV X-ray luminosity and EW) for the sample as a whole, but not for the individual galaxies and galaxy types.
Pattern classification for finding facial growth abnormalities

Cephalometric analysis of lateral radiographs of the head is an important diagnosis tool in orthodontics. Based on actually locating precise landmarks, it is a tedious, long-lasting and error prone mission. The objective of this work is to calculate the SNA angle, SNB angle and ANB angle between the landmarks to identify the input and output parameters pertaining to skeletal abnormalities. By doing so the patients data for training and testing the back propagation neural network (BPNN), generalized regression neural network (GRNN), support vector machine (SVM) and extreme learning machine (ELM) classifiers by nine fold cross substantiation. The presentation of skeletal is originated out using the BPNN, GRNN, SVM and ELM models. This will be useful to identify whether the patient is normal or abnormal (need for treatment). This will categorize situation of the diverse patients with severity of abnormalities in skeletal.