Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisit of Logistic Regression : Efficient Optimization and Kernel Extensions

Logistic regression (LR) is widely applied as a powerful classification method in various fields, and a variety of optimization methods have been developed. To cope with large-scale problems, an efficient optimization method for LR is required in terms of computational cost and memory usage. In this paper, we propose an efficient optimization method using non-linear conjugate gradient (CG) descent. In each CG iteration, the proposed method employs the optimized step size without exhaustive line search, which significantly reduces the number of iterations, making the whole optimization process fast. In addition, on the basis of such CG-based optimization scheme, a novel optimization method for kernel logistic regression (KLR) is proposed. Unlike the ordinary KLR methods, the proposed method optimizes the kernel-based classifier, which is naturally formulated as the linear combination of sample kernel functions, directly in the reproducing kernel Hilbert space (RKHS), not the linear coefficients. Subsequently, we also propose the multiple-kernel logistic regression (MKLR) along with the optimization of KLR. The MKLR effectively combines the multiple types of kernels with optimizing the weights for the kernels in the framework of the logistic regression. These proposed methods are all based on CG-based optimization and matrix-matrix computation which is easily parallelized such as by using multi-thread programming. In the experimental results on multi-class classifications using various datasets, the proposed methods exhibit favorable performances in terms of classification accuracies and computation times.
Optical spectroscopy of X‐Mega targets in the Carina nebula – VII. On the multiplicity of Tr 16‐112, HD 93343 and HD 93250★

We present the results of a spectroscopic monitoring campaign devoted to three O-type stars in the Carina nebula. We derive the full SB2 orbital solution of the binary system Tr 16112, an exceptional dissymmetrical system consisting of an O5.5-6 V((f + ? p)) primary and a B2 V-III secondary. We also report on low-amplitude brightness variations in Tr 16-112 that are likely due to the ellipsoidal shape of the O5.5-6 primary revolving in an eccentric orbit around the system’s centre of mass. We detect for the first time a clear SB2 binary signature in the spectrum of HD 93343 (O8 + O8), although our data are not sufficient to establish an orbital solution. This system also displays low amplitude photometric modulations. On the other hand, no indication of multiplicity is found in the optical spectra of HD 93250. Finally, we discuss the general properties of multiple massive stars in the Carina OB1 association.
A Reconfigurable Multi-Byte Regular-Expression Matching Architecture for Signature-Based Intrusion Detection

String/regular-expression matching is widely used in different applications. Our work is concerned with high-throughput regular-expression matching in the context of intrusion detection systems as it is the most computationally intensive part of the operation. The results, however, should be equally applicable to other domains that require fast regular-expression matching. The major contribution of this paper is a reconfigurable architecture that performs regular-expression matching on a multi-byte per clock cycle basis. We are able to explore the system performance for different byte-processing rates - from 4 to 64 - by automating the VHDL-generation process and implementing the resulting circuits on a general- purpose FPGA. Theoretical expressions for resource usage (cost) as a function of byte-rate and pattern-length are also presented.
Delaunay Mesh Generation

Written by authors at the forefront of modern algorithms research, Delaunay Mesh Generation demonstrates the power and versatility of Delaunay meshers in tackling complex geometric domains ranging from polyhedra with internal boundaries to piecewise smooth surfaces. Covering both volume and surface meshes, the authors fully explain how and why these meshing algorithms work. The book is one of the first to integrate a vast amount of cutting-edge material on Delaunay triangulations. It begins with introducing the problem of mesh generation and describing algorithms for constructing Delaunay triangulations. The authors then present algorithms for generating high-quality meshes in polygonal and polyhedral domains. They also illustrate how to use restricted Delaunay triangulations to extend the algorithms to surfaces with ridges and patches and volumes with smooth surfaces. For researchers and graduate students, the book offers a rigorous theoretical analysis of mesh generation methods. It provides the necessary mathematical foundations and core theoretical results upon which researchers can build even better algorithms in the future. For engineers, the book shows how the algorithms work well in practice. It explains how to effectively implement them in the design and programming of mesh generation software.
A Hint in the Right Direction: Interactive Synthesis with Partial Dynamic Specifications

Most programs contain conceptually simple statements that are difficult to write. We propose a new methodology that allows programmers to give partial dynamic specifications of the results of statements in a particular program state, and which uses them to synthesize candidate statements. Building on previous work, these specifications can consist of information about the type or value of a desired expression or can be arbitrary predicates relating the input and output states. We implemented our methodology in a tool named CodeHint and ran a user study where we found that programmers used it when given the choice.
Genome-wide analysis of 3′-untranslated regions supports the existence of post-transcriptional regulons controlling gene expression in trypanosomes

In eukaryotic cells, a group of messenger ribonucleic acids (mRNAs) encoding functionally interrelated proteins together with the trans-acting factors that coordinately modulate their expression is termed a post-transcriptional regulon, due to their partial analogy to a prokaryotic polycistron. This mRNA clustering is organized by sequence-specific RNA-binding proteins (RBPs) that bind cis-regulatory elements in the noncoding regions of genes, and mediates the synchronized control of their fate. These recognition motifs are often characterized by conserved sequences and/or RNA structures, and it is likely that various classes of cis-elements remain undiscovered. Current evidence suggests that RNA regulons govern gene expression in trypanosomes, unicellular parasites which mainly use post-transcriptional mechanisms to control protein synthesis. In this study, we used motif discovery tools to test whether groups of functionally related trypanosomatid genes contain a common cis-regulatory element. We obtained conserved structured RNA motifs statistically enriched in the noncoding region of 38 out of 53 groups of metabolically related transcripts in comparison with a random control. These motifs have a hairpin loop structure, a preferred sense orientation and are located in close proximity to the open reading frames. We found that 15 out of these 38 groups represent unique motifs in which most 3′-UTR signature elements were group-specific. Two extensively studied Trypanosoma cruzi RBPs, TcUBP1 and TcRBP3 were found associated with a few candidate RNA regulons. Interestingly, 13 motifs showed a strong correlation with clusters of developmentally co-expressed genes and six RNA elements were enriched in gene clusters affected after hyperosmotic stress. Here we report a systematic genome-wide in silico screen to search for novel RNA-binding sites in transcripts, and describe an organized network of several coordinately regulated cohorts of mRNAs in T. cruzi. Moreover, we found that structured RNA elements are also conserved in other human pathogens. These results support a model of regulation of gene expression by multiple post-transcriptional regulons in trypanosomes.
Learning stable, regularised latent models of neural population dynamics

Ongoing advances in experimental technique are making commonplace simultaneous recordings of the activity of tens to hundreds of cortical neurons at high temporal resolution. Latent population models, including Gaussian-process factor analysis and hidden linear dynamical system (LDS) models, have proven effective at capturing the statistical structure of such data sets. They can be estimated efficiently, yield useful visualisations of population activity, and are also integral building-blocks of decoding algorithms for brain-machine interfaces (BMI). One practical challenge, particularly to LDS models, is that when parameters are learned using realistic volumes of data the resulting models often fail to reflect the true temporal continuity of the dynamics; and indeed may describe a biologically-implausible unstable population dynamic that is, it may predict neural activity that grows without bound. We propose a method for learning LDS models based on expectation maximisation that constrains parameters to yield stable systems and at the same time promotes capture of temporal structure by appropriate regularisation. We show that when only little training data is available our method yields LDS parameter estimates which provide a substantially better statistical description of the data than alternatives, whilst guaranteeing stable dynamics. We demonstrate our methods using both synthetic data and extracellular multi-electrode recordings from motor cortex.
Powder Pattern Decomposition with the Aid of Preferred Orientation - Use of the Whole Debye-Scherrer Ring

Method of the decomposition of overlapping reflections in a powder pattern with the aid of preferred orientation is tested on magnetically aligned samples using the effect of easy magnetization direction in hexagonal SmCo5 and TbCo5. Complete Debye-Scherrer rings, measured with an image plate detector, are integrated in different radial directions. The texture aided powder pattern decomposition results in correct values of structure amplitudes
On the Statistical Independence in the Context of the Rössler Map

The paper mainly focuses on the statistical dependence/independence relationship existing in the Rössler map and on the possibility to sample the chaotic system to obtain experimental data complying with the i.i. d. model (data coming out from independent and identically distributed random variables). The overall investigation relies on Smirnov tests on two experimental data sets, a Monte Carlo analysis and an original independence test applicable to all kinds of continuous random variables, normal or not, even of unknown statistical law.
Interactive graphics for plastic surgery: a task-level analysis and implementation

We have implemented a system for Computer-Aided Plastic Surgery. Planning plastic surgery procedures is complex because the surgeon needs to stretch and reshape the patient’s skin to replace missing tissue while minimizing distortion of the surrounding tissue. Traditional planning techniques rely on the surgeon’s experience to select among a myriad of possible procedure designs. While mathematica1 techniques for predicting the outcome of surgery have been proposed in the past, these are not in widespread use by surgeons because they require the surgeon to perform manual constructions and geometric calculations. Our system makes the analysis process easier by allowing the surgeon to draw the surgical plan directly on a 3D model of the patient. An automatic mesh generator is used to convert that drawing into a well-formulated problem for finite element analysis.
A hybrid method towards automated nipple detection in 3D breast ultrasound images

In clinical work-up of breast cancer, nipple position is an important marker to locate lesions. Moreover, it serves as an effective landmark to register a 3D automated breast ultrasound (ABUS) images to other imaging modalities, e.g., X-ray mammography, tomosynthesis or magnetic resonance imaging (MRI). However, the presence of speckle noises caused by the interference waves and variant imaging directions poses challenges to automatically identify nipple positions. In this work, a hybrid fully automatic method to detect nipple positions in ABUS images is presented. The method extends the multi-scale Laplacian-based method that we proposed previously, by integrating a specially designed Hessian-based method to locate the shadow area beneath the nipple and areola. Subsequently, the likelihood maps of nipple positions generated by both methods are combined to build a joint-likelihood map, where the final nipple position is extracted. To validate the efficiency and robustness, the extended hybrid method was tested on 926 ABUS images, resulting in a distance error of 7.08±10.96 mm (mean±standard deviation).
Gaugino mediated supersymmetry breaking

We consider supersymmetric theories where the standard-model quark and lepton fields are localized on a `3-brane' in extra dimensions, while the gauge and Higgs fields propagate in the bulk. If supersymmetry is broken on another 3-brane, supersymmetry breaking is communicated to gauge and Higgs fields by direct higher-dimension interactions, and to quark and lepton fields via standard-model loops. We show that this gives rise to a realistic and predictive model for supersymmetry breaking. The size of the extra dimensions is required to be of order 10-100 times larger than fundamental scale (e.g. the string scale). The spectrum is similar to (but distinguishable from) the predictions of `no-scale' models. Flavor-changing neutral currents are naturally suppressed. The μ term can be generated by the Giudice-Masiero mechanism. The supersymmetric CP problem is naturally solved if CP violation occurs only on the observable sector 3-brane. These are the simplest models in the literature that solve all supersymmetric naturalness problems.
Automating Cognitive Model Improvement by A * Search and Logistic Regression

A good cognitive model is important to the effectiveness to an intelligent tutor. In this paper we present a method of combining the A* search algorithm and logistic regression to automate the improvement of a cognitive model by 1) automatically generating different models by mutating learning factors in a base model 2) integrating logistical regression to evaluate different models 3)selecting the best model through a depth-first search algorithm.
Image Segmentation Based on Fast Normalized Cut

In this paper, we propose a fast image segmentation method based on normalized cut. This method apply sim- ple linear iterative clustering super-pixel algorithm to obtain super-pixel regions, and then use affinity propagation cluster- ing to extract the representative pixels in each super-pixel regions, Finally, we apply normalized cut to obtain segmenta- tion results. At the end of the paper, Numerical experiments are presented to demonstrate the effectiveness of our pro- posed method.
Compensatory changes in the hippocampus of somatostatin knockout mice: upregulation of somatostatin receptor 2 and its function in the control of bursting activity and synaptic transmission

Somatostatin‐14 (SRIF) co‐localizes with γ‐aminobutyric acid (GABA) in the hippocampus and regulates neuronal excitability. A role of SRIF in the control of seizures has been proposed, although its exact contribution requires some clarification. In particular, SRIF knockout (KO) mice do not exhibit spontaneous seizures, indicating that compensatory changes may occur in KO. In the KO hippocampus, we examined whether specific SRIF receptors and/or the cognate peptide cortistatin‐14 (CST) compensate for the absence of SRIF. We found increased levels of both sst2 receptors (sst2) and CST, and we explored the functional consequences of sst2 compensation on bursting activity and synaptic responses in hippocampal slices. Bursting was decreased by SRIF in wild‐type (WT) mice, but it was not affected by either CST or sst2 agonist and antagonist. sst4 agonist increased bursting frequency in either WT or KO. In WT, but not in KO, its effects were blocked by agonizing or antagonizing sst2, suggesting that sst2 and sst4 are functionally coupled in the WT hippocampus. Bursting was reduced in KO as compared with WT and was increased upon application of sst2 antagonist, while SRIF, CST and sst2 agonist had no effect. At the synaptic level, we observed that in WT, SRIF decreased excitatory postsynaptic potentials which were, in contrast, increased by sst2 antagonist in KO. We conclude that sst2 compensates for SRIF absence and that its upregulation is responsible for reduced bursting and decreased excitatory transmission in KO mice. We suggest that a critical density of sst2 is needed to control hippocampal activity.
Bloom filter based routing for content-based publish/subscribe

Achieving expressive and efficient content-based routing in publish/subscribe systems is a difficult problem. Traditional approaches prove to be either inefficient or severely limited in their expressiveness and flexibility. We present a novel routing method, based on Bloom filters, which shows high efficiency while simultaneously preserving the flexibility of content-based schemes. The resulting implementation is a fast, flexible and fully decoupled content-based publish/subscribe system.
MFD: Mutual feature description for image matching

In general, SIFT has been proven to be the most robust local feature descriptor. However, it was designed mainly for gray-level images. Many Objects cannot be distinguished if their color contents are ignored. In addition, SIFT greatly depend on the main orientation assignment, and about one third of orientations are assigned with a big error. Thus many corresponding points are mismatched. This paper addresses these two problems and proposes a local feature descriptor with color and geometric invariance. In this method, the image is transformed into the Gaussian color space to construct the color invariant variable for detecting key points. And then the computation of canonical orientation of key point in the feature descriptor is substituted by the relative gradient direction around the candidate key points which reduces the accumulated orientation error. The pixel gradient and orientation around the extracted key points are computed to build the local gradient orientation histogram to describe the features. The results on the Amsterdam Library of Object Images dataset and 3D objects have shown that the proposed descriptor is better than SIFT and CSIFT.
Treebanks Gone Bad: Generating a Treebank of Ungrammatical English

This paper describes how a treebank of ungrammatical sentences can be created from a treebank of well-formed sentences. The treebank creation procedure involves the automatic introduction of frequently occurring grammatical errors into the sentences in an existing treebank, and the minimal transformation of the analyses in the treebank so that they describe the newly created ill-formed sentences. Such a treebank can be used to test how well a parser is able to ignore grammatical errors in texts (as people can), and can be used to induce a grammar capable of analysing such sentences. This paper also demonstrates the first of these uses.
Calendar Effects in Chinese Stock Market

Our paper examines calendar effects in Chinese stock market, particularly monthly and daily effects. Using individual stock returns, we observe the change of the calendar effect over time. In Shanghai and Shenzhen, the yearend effect was strong in 1991 – but disappeared later. As the Chinese year-end is in February, the highest returns can be achieved in March and April. Studying daily effects, we found that Fridays are profitable. Chinese investors are “amateur speculator” who often embezzles business fund for private trading; thus, these funds are used for short-term speculations before they are paid back prior to weekends. c © 2005 Peking University Press
The role of ambient lighting in circadian disc shedding in the rod outer segment of the rat retina.

Rats raised from birth on a 7 A.M.:7 P.M. light cycle exhibited a circadian burst of shedding 1 1/2 hr after the scheduled onset of light. This rhythmic event persisted even after the animals had been placed in total darkness for up to 2 weeks. When animals were placed in constant light (LL) for more than 24 hr, the shedding peak was abolished. A period of darkness of at least 2 hr, ending at the normal time for light onset, was necessary for the production of a shedding burst. When animals were placed in altered lighting cycles, the shedding rhythm shifted accordingly, although the speed of this shift was greatest with large advances in the light cycle and slowest with small delays in the light cycle. Animals exposed to LL and then returned to the dark exhibited the original shedding rhythm, a phenomenon not affected when the optic nerves were severed. A shedding peak could be induced at a noncircadian time by exposing the animals to more than 20 hr of LL followed by 2 hr of darkness and 1 1/2 hr of light, although the magnitude of the shedding was related to the circadian time.
Maternal low-protein diet during mouse pre-implantation development induces vascular dysfunction and altered renin–angiotensin-system homeostasis in the offspring

Environmental perturbations during early mammalian development can affect aspects of offspring growth and cardiovascular health. We have demonstrated previously that maternal gestational dietary protein restriction in mice significantly elevated adult offspring systolic blood pressure. Therefore, the present study investigates the key mechanisms of blood pressure regulation in these mice. Following mating, female MF-1 mice were assigned to either a normal-protein diet (NPD; 18 % casein) or an isocaloric low-protein diet throughout gestation (LPD; 9 % casein), or fed the LPD exclusively during the pre-implantation period (3·5 d) before returning to the NPD for the remainder of gestation (Emb-LPD). All offspring received standard chow. At 22 weeks, isolated mesenteric arteries from LPD and Emb-LPD males displayed significantly attenuated vasodilatation to isoprenaline (P = 0·04 and P = 0·025, respectively), when compared with NPD arteries. At 28 weeks, stereological analysis of glomerular number in female left kidneys revealed no significant difference between the groups. Real-time RT-PCR analysis of type 1a angiotensin II receptor, Na+/K+ ATPase transporter subunits and glucocorticoid receptor expression in male and female left kidneys revealed no significant differences between the groups. LPD females displayed elevated serum angiotensin-converting enzyme (ACE) activity (P = 0·044), whilst Emb-LPD males had elevated lung ACE activity (P = 0·001), when compared with NPD offspring. These data demonstrate that elevated offspring systolic blood pressure following maternal gestational protein undernutrition is associated with impaired arterial vasodilatation in male offspring, elevated serum and lung ACE activity in female and male offspring, respectively, but kidney glomerular number in females and kidney gene expression in male and female offspring appear unaffected.