Miracle-dz/UniFAR-FTUs huggingface dataset:
Lossy/lossless coding of bi-level images

Summary form only given. We present improvements to a general type of lossless, lossy, and refinement coding of bi-level images (Martins and Forchhammer, 1996). Loss is introduced by flipping pixels. The pixels are coded using arithmetic coding of conditional probabilities obtained using a template as is known from JBIG and proposed in JBIG-2 (Martins and Forchhammer). Our new state-of-the-art results are obtained using the more general free tree instead of a template. Also we introduce multiple refinement template coding. The lossy algorithm is analogous to the greedy 'rate-distortion'-algorithm of Martins and Forchhammer but is based on the free tree.
Evaluation of partial area under the concentration time curve to estimate midazolam apparent oral clearance for cytochrome P450 3A phenotyping

Abstract Background: Midazolam apparent oral clearance (CLORAL) is used to estimate intestinal and hepatic cytochrome P450 (CYP) 3A activity. A limited sampling approach was performed to access a midazolam partial area under the concentration time curve (AUC) to estimate CLORAL. Methods: Midazolam plasma concentrations from healthy adults were obtained during CYP3A baseline (n=116), inhibition (n=75), and induction or activation (n=66) from seven published studies. Observed CLORAL and partial AUCs of AUC0-2, AUC0-4, AUC0-6, AUC1-2, AUC1-4, AUC2-4, and AUC2-6 were determined by noncompartmental analysis. Subject data were randomly divided into a training set and a validation set. Linear regression equations, derived from partial AUCs, were developed from training set data. Predicted CLORAL was determined from these equations from validation set data. Preset criterion was a coefficient of determination (r2) greater than or equal to 0.9. Bias and precision were evaluated by relative percent mean prediction error (%MPE) and relative percent mean absolute error (%MAE). Results: During CYP3A baseline conditions, all of the evaluated CLORAL equations had unacceptable r2 (range: 0.34–0.86). During CYP3A inhibition, all of the evaluated CLORAL equations had unacceptable %MAE. Acceptable r2, %MPE, and %MAE were observed during CYP3A induction/activation with AUC0-4 (r2=0.99, %MPE=3.9, %MAE=12.5) and AUC1-4 (r2=0.99, %MPE=6%, %MAE=11.1%). The same equations also predicted the extent of CYP3A induction as a lack of equivalence was observed with AUC0-4 and AUC1-4. Conclusions: Midazolam partial AUCs were unable to estimate CYP3A activity during the evaluated baseline and inhibitory conditions. Midazolam CLORAL utilizing a partial AUC0-4 and AUC1-4 was able to estimate CYP3A induction with rifampin and Ginkgo biloba extract.
Molecular diagnostic testing for determination of myeloid lineage in acute leukemias.

Determination of myeloid vs. lymphoid cell lineage in acute leukemias is essential for diagnosis, prognosis, and treatment. However, some leukemic cells are too primitive to be identified based on conventional morphology, cytochemistry, and immunophenotype criteria. The gene for myeloperoxidase (MPO) is central to the lineage designation of myeloid cells and their function. Expression of MPO messenger ribonucleic acid (mRNA) may serve to determine the myeloid lineage of primitive leukemic cells that do not express the final product, MPO. Recently, a procedure has been developed for detection of MPO mRNA in leukemic cells, based on message amplification by reverse transcription-polymerase chain reaction (RT-PCR). Three variant polymerase chain reaction (PCR) methods, developed in view of future diagnostic applications of the RT-PCR procedure are reported: (A) nested PCR, using a second pair of internal primers for reamplification of the first PCR product; (B) multiplex PCR for concomitant amplification of up to seven sequences encompassing all regions of MPO mRNA; (C) adaptation of the standard PCR procedure and the two variant methods for use of cellular material from air-dried unstained or Wright stained smears. These variant procedures developed on the HL-60 cell line make the RT-PCR detection of MPO mRNA easily applicable as a new diagnostic test in acute leukemias and confer the versatility needed in the clinical setting. The advantages of our new procedure for MPO mRNA detection are: high sensitivity and specificity, speed, simplicity, and safety. Myeloid lineage of leukemic blasts can be established, confirmed, or ruled out in 6 to 10 hours, making results available at the time of bone marrow sign-out. (ABSTRACT TRUNCATED AT 250 WORDS)
A Novel Element Detection Method in Audio Sensor Networks

Audio element detection in wireless sensor networks (WSNs) has great significance in our lives (e.g., in detecting traffic jam and accident, gun shots and explosion, and hurricane). It is particularly useful when video cameras cannot be used effectively (e.g., in darkness, with a wide range to cover); audio sensors are also much cheaper. However, most previous works on audio element detection require a large number of training examples to obtain satisfactory results. This becomes even more infeasible for audio sensors in WSNs where small energy consumption is required. In this paper, we propose a novel approach to solve this difficult problem. We first break down audio clips into a collection of simple “audio elements,” and train these audio elements offline using statistical learning. Then, we train a weighted association graph using the trained audio element models online. This greatly reduces the amount of online training without sacrificing accuracy. We deploy our approach in an audio sensor network for traffic monitoring and venue monitoring to evaluate its performance. The experiments demonstrate that our proposed method achieves better results compared to the state-of-the-art methods while using smaller online training sets.
Revealing pentimenti: the hidden history in a painting

Art conservators often explore X-ray images of paintings to help find pentimenti, the artist's revisions hidden beneath the painting's visible first surfaces. X-ray interpretation is difficult due to artifacts in the image, superimposed features from all paint layers, and because image intensity depends on both the paint layer thickness and each pigment's opacity. We present a robust user-guided method to suppress clutter, find visually significant differences between X-ray images and color photographs, and visualize them together. These tools allow domain experts as well as museum visitors to explore the artist's creative decisions that led to a masterpiece.
Uncovering the dispersion history, adaptive evolution and selection of wheat in China

Summary Wheat was introduced to China approximately 4500 years ago, where it adapted over a span of time to various environments in agro‐ecological growing zones. We investigated 717 Chinese and 14 Iranian/Turkish geographically diverse, locally adapted wheat landraces with 27 933 DArTseq (for 717 landraces) and 312 831 Wheat660K (for a subset of 285 landraces) markers. This study highlights the adaptive evolutionary history of wheat cultivation in China. Environmental stresses and independent selection efforts have resulted in considerable genome‐wide divergence at the population level in Chinese wheat landraces. In total, 148 regions of the wheat genome show signs of selection in at least one geographic area. Our data show adaptive events across geographic areas, from the xeric northwest to the mesic south, along and among homoeologous chromosomes, with fewer variations in the D genome than in the A and B genomes. Multiple variations in interdependent functional genes such as regulatory and metabolic genes controlling germination and flowering time were characterized, showing clear allelic frequency changes corresponding to the dispersion of wheat in China. Population structure and selection data reveal that Chinese wheat spread from the northwestern Caspian Sea region to South China, adapting during its agricultural trajectory to increasingly mesic and warm climatic areas.
Brain Areas Involved in the Retrieval of Updated Memories : The Long-Term Effects

When we learn something new, we have to update our memory. The new information is stored together with the old and by doing this some of the old information might destroyed. The questions I wanted to answer were what brain areas are activated by the retrieval of symbols associated with either a sound or a face and if any residual activation would be found for the old associations (when association was changed during training) even though it had been 18 months since the last study was conducted. 11 participants were included, 5 females, 6 males between the ages of 23-29 (mean 24.67). Data was collected using fMRI. In an earlier study (Stiernstedt, 2009) participants had studied a symbol-sound or symbol-face combination. After two, of a total of five days, half of the symbol associations changed (faces to sounds and vice verse). The same symbols and associations were used here. The results showed activation in fusiform gyrus for faces and primary and secondary auditory cortex for sounds, residual activation was found in secondary visual cortex for faces and secondary auditory cortex for sounds. This implicates that the same areas involved with encoding the information is also involved in retrieving it and that the old information is not deleted but still accessible.
An elitist evolutionary algorithm for automatically generating test data

The development of an effective and efficient method for generating test data is an extremely challenging process which directly impacts the time that could be spent on activities relevant to software testing. Therefore, various researches related to this area have been carried out. Among the techniques for automatically generating test data, we highlight the use of metaheuristics, a promising area called Search-Based Software Testing (SBST). Thus, this article proposes the use of an Elitist Genetic Algorithm (GA) as a tool for generation and selection of test data applied in Mutation Testing for different benchmarks. The results indicate a good performance of the algorithm used in the benchmarks.
Aggregation in Confidence-Based Concept Discovery for Multi-Relational Data Mining

Multi-relational data mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. Several relational knowledge discovery systems have been developed employing various search strategies, heuristics, language pattern limitations and hypothesis evaluation criteria, in order to cope with intractably large search space and to be able to generate high-quality patterns. In this work, we describe a method for generating and using aggregate predicates in an ILP-based concept discovery system and compare its performance in terms of quality of concept discovery with other multi-relational learning systems using aggregation.
How Many Small Cells Can be Turned Off via Vertical Offloading Under a Separation Architecture?

To further improve the energy efficiency of heterogeneous networks, a separation architecture called hyper-cellular network (HCN) has been proposed, which decouples the control signaling and data transmission functions. Specifically, the control coverage is guaranteed by macro base stations (MBSs), whereas small cells (SCs) are only utilized for data transmission. Under HCN, SCs can be dynamically turned off when traffic load decreases for energy saving. A fundamental problem then arises: how many SCs can be turned off as traffic varies? In this paper, we address this problem in a theoretical way, where two sleeping schemes (i.e., random and repulsive schemes) with vertical inter-layer offloading are considered. Analytical results indicate the following facts: 1) under the random scheme where SCs are turned off with certain probability, the expected ratio of sleeping SCs is inversely proportional to the traffic load of SC-layer and decreases linearly with the traffic load of MBS-layer; 2) the repulsive scheme, which only turns off the SCs close to MBSs, is less sensitive to the traffic variations; and 3) deploying denser MBSs enables turning off more SCs, which may help to improve network energy-efficiency. Numerical results show that about 50% SCs can be turned off on average under the predefined daily traffic profiles, and 10% more SCs can be further turned off with inter-layer channel borrowing.
Total variation superiorization schemes in proton computed tomography image reconstruction.

PURPOSE Iterative projection reconstruction algorithms are currently the preferred reconstruction method in proton computed tomography (pCT). However, due to inconsistencies in the measured data arising from proton energy straggling and multiple Coulomb scattering, the noise in the reconstructed image increases with successive iterations. In the current work, the authors investigated the use of total variation superiorization (TVS) schemes that can be applied as an algorithmic add-on to perturbation-resilient iterative projection algorithms for pCT image reconstruction. METHODS The block-iterative diagonally relaxed orthogonal projections (DROP) algorithm was used for reconstructing GEANT4 Monte Carlo simulated pCT data sets. Two TVS schemes added on to DROP were investigated; the first carried out the superiorization steps once per cycle and the second once per block. Simplifications of these schemes, involving the elimination of the computationally expensive feasibility proximity checking step of the TVS framework, were also investigated. The modulation transfer function and contrast discrimination function were used to quantify spatial and density resolution, respectively. RESULTS With both TVS schemes, superior spatial and density resolution was achieved compared to the standard DROP algorithm. Eliminating the feasibility proximity check improved the image quality, in particular image noise, in the once-per-block superiorization, while also halving image reconstruction time. Overall, the greatest image quality was observed when carrying out the superiorization once per block and eliminating the feasibility proximity check. CONCLUSIONS The low-contrast imaging made possible with TVS holds a promise for its incorporation into future pCT studies.
[Protein expression profilings of polycystic ovary syndrome].

OBJECTIVE To screen out serum protein profiling of polycystic ovary syndrome(PCOS) by surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) for discovering the discriminatory proteins. METHODS Thirty one women with PCOS and thirty healthy women were detected by Weak Cation Exchange(WCX2)chip. ProteinChip reader and Biomarker Wizard software from Ciphergen Inc were combined with a bioinformatics method (support vector machines, SVM ) to analyze protein fingerprinting. RESULTS There were 4 proteins which were obviously different between the PCOS group and the control. Three of them were up-regulated, and one down-regulated. To set up a analysis model by SVM using the 4 proteins could successfully distinguish between PCOS and the normal control. The corresponding sensitivity, specificity and positive predict value were 86.7%, 83.3%, 87.2%, respectively. CONCLUSION Using ProteinChip technology can screen out serum discriminatory proteins quickly and efficiently. Combined with SVM, an optimal fingerprinting model has been set up, which can easily predict PCOS. In disease state of PCOS, there are significant variations which consist of four proteins. To investigate those four discriminatory proteins, especially the protein m/z 6 628 may be of benefit to pathogenic study and the development of biomarkers for PCOS.
Using Queue Time Predictions for Processor

When a malleable job is submitted to a space-sharing parallel computer, it must choose often whether to begin execution on a small, available cluster, or wait in queue for more processors to become available. To make this decision, it must predict how long it will have to wait for the larger cluster. We propose statistical techniques for predicting these queue times, and develop an allocation strategy that uses these predictions. We present a workload model based on the environment we have observed at the San Diego Supercomputer Center, and use this model to drive simulations of various allocation strategies. We conclude that prediction-based allocation not only improves the average turnaround time for the jobs; it also improves the utilization of the system as a whole.
Quantifying economic ! uctuations

This manuscript is a brief summary of a talk designed to address the question of whether two of the pillars of the "eld of phase transitions and critical phenomena—scale invariance and universality—can be useful in guiding research on interpreting empirical data on economic ! uctuations. Using this conceptual framework as a guide, we empirically quantify the relation between trading activity—measured by the number of transactions N—and the price change G(t) for a given stock, over a time interval [t; t + #t]. We relate the time-dependent standard deviation of price changes—volatility—to two microscopic quantities: the number of transactions N (t) in #t and the variance W (t) of the price changes for all transactions in #t. We "nd that the long-ranged volatility correlations are largely due to those of N . We then argue that the tail-exponent of the distribution of N is insu$cient to account for the tail-exponent of P{G¿x}. Since N and W display only weak inter-dependency, our results show that the fat tails of the distribution P{G¿x} arises from W . Finally, we review recent work on quantifying collective behavior among stocks by applying the conceptual framework of random matrix theory (RMT). RMT makes predictions for “universal” properties that do not depend on the interactions between the elements comprising the system, and deviations from RMT provide clues regarding system-speci"c properties. We compare the statistics of the cross-correlation matrix C—whose elements Cij are the correlation coe$cients of price ! uctuations of stock i and j—against a random matrix having the same symmetry properties. It is found that RMT methods can distinguish random and non-random parts of C. The non-random part of C which deviates from RMT results, provides information regarding genuine collective behavior among stocks. We also discuss results that are reminiscent of phase transitions in spin systems, where the divergent behavior of the response function at the critical point (zero magnetic "eld) leads to large ! uctuations, and we discuss a curious “symmetry breaking”, a feature qualitatively identical to the behavior of the probability density of the magnetization for "xed values of the inverse temperature. c © 2001 Elsevier Science B.V. All rights reserved. ∗Corresponding author. Tel. : +1-617-353-2617; fax: +1-617-353-3783. E-mail address: hes@bu.edu (H.E. Stanley). 0378-4371/01/$ see front matter c © 2001 Elsevier Science B.V. All rights reserved. PII: S 0378 -4371(01)00504 -0 H.E. Stanley et al. / Physica A 302 (2001) 126–137 127
Analyses of Instance-Based Learning Algorithms

This paper presents PAC-learning analyses for instance-based learning algorithms for both symbolic and numeric-prediction tasks. The algorithms analyzed employ a variant of the k-nearest neighbor pattern classifier. The main results of these analyses are that the IB1 instance-based learning algorithm can learn, using a polynomial number of instances, a wide range of symbolic concepts and numeric functions. In. addition, we show that a bound on the degree of difficulty of predicting symbolic values may be obtained by considering the size of the boundary of the target concept, and a bound on the degree of difficulty in predicting numeric values may be obtained by considering the maximum absolute value of the slope between instances in the instance space. Moreover, the number of training instances required by IB1 is polynomial in these parameters. The implications of these results for the practical application of instance-based learning algorithms are discussed.
Generative and Discriminative Methods for Online Adaptation in SMT

In an online learning protocol, immediate feedback about each example is used to refine the next prediction. We apply this protocol to statistical machine translation for computer-assisted translation and compare generative and discriminative approaches for online adaptation. We develop our methods on reference translations and test on feedback gathered from professional translators. Experimental results show that improvements of straightforward adaptations of translation and language model are greater than those achieved by discriminative re-ranking. However, the improvements add up to 4 BLEU points over a baseline static model.
Ternary Content Addressable Memory Types And Matchline Schemes

Ternary Content Addressable Memory (TCAM) used in many application like network routers and packet classification. To reduce the power consumption of matchlines, the matchline partitioning scheme is used. Matchline is partitioned into NOR and NAND type matchline. If NAND (NOR) type TCAM cell is used then NAND (NOR) type matchline is used. NOR type TCAM has feature of high speed and high compare power. NAND type TCAM has low speed and low compare power. The NAND and NOR type matchlines are combined to form the pai-sigma matchlines. In pai segment the NAND type cells are connected in parallel to form the NAND type matchline. In sigma segment NOR type cells are connected in series to form the NOR type matchline. When compare operation is performed all NAND type matchlines are activated because switching power is low. Based on the match result of the NAND matchlines the NOR matchlines are activated because of high speed. The matchline incurs the problem of short circuit current due to mismatch and match result of NAND and NOR matchlines. NAND type matchline exist the problem of charge sharing when the search result of the NAND line is mismatches. This proposed TCAM has less compare (search) power compared to the NAND/NOR type TCAM cell. Key Words: Content Addressable Memories (CAM), Ternary CAM (TCAM), NAND TCAM, NOR TCAM, Matchline Power (MP), Ripple Precharge (RP), Internet Protocol (IP), Classless Inter-Domain Routing (CIDR), Match Line (ML).
A new version of the two-dimensional Lax-Friedrichs scheme

We develop a new two-dimensional version of the Lax-Friedrichs scheme, which corresponds exactly to a transport projection method. The scheme we obtain in this way is different from the one derived by averaging the one-dimensional scheme in the two directions as usually done. The LaxFriedrichs scheme is known to be a very stable scheme with much diffusion. However, this diffusion can be easily reduced by using corrected fluxes, without altering the total-variation estimates. The accuracy of this corrected scheme is of order two except near a local extrema. The numerical results computed by using this corrected scheme are similar to the ones obtained by using the Godunov scheme with corrected fluxes but require less CPU time. Convergence towards the entropy solution is proved, and some extensions to systems of conservation laws or three-dimensional models are discussed. Some numerical experiments are reported.