Miracle-dz/UniFAR-FTUs huggingface dataset:
Barcodes: The persistent topology of data

This article surveys recent work of Carlsson and collaborators on applications of computational algebraic topology to problems of feature detection and shape recognition in high-dimensional data. The primary mathematical tool considered is a homology theory for point-cloud data sets — persistent homology — and a novel representation of this algebraic characterization — barcodes. We sketch an application of these techniques to the classification of natural images. 1. The shape of data When a topologist is asked, “How do you visualize a four-dimensional object? ” the appropriate response is a Socratic rejoinder: “How do you visualize a threedimensional object? ” We do not see in three spatial dimensions directly, but rather via sequences of planar projections integrated in a manner that is sensed if not comprehended. We spend a significant portion of our first year of life learning how to infer three-dimensional spatial data from paired planar projections. Years of practice have tuned a remarkable ability to extract global structure from representations in a strictly lower dimension. The inference of global structure occurs on much finer scales as well, with regards to converting discrete data into continuous images. Dot-matrix printers, scrolling LED tickers, televisions, and computer displays all communicate images via arrays of discrete points which are integrated into coherent, global objects. This also is a skill we have practiced from childhood. No adult does a dot-to-dot puzzle with anything approaching anticipation. 1.1. Topological data analysis. Problems of data analysis share many features with these two fundamental integration tasks: (1) how does one infer high dimensional structure from low dimensional representations; and (2) how does one assemble discrete points into global structure. The principal themes of this survey of the work of Carlsson, de Silva, Edelsbrunner, Harer, Zomorodian, and others are the following: (1) It is beneficial to replace a set of data points with a family of simplicial complexes, indexed by a proximity parameter. This converts the data set into global topological objects. (2) It is beneficial to view these topological complexes through the lens of algebraic topology — specifically, via a novel theory of persistent homology adapted to parameterized families. (3) It is beneficial to encode the persistent homology of a data set in the form of a parameterized version of a Betti number: a barcode. The author gratefully acknowledges the support of DARPA # HR0011-07-1-0002. The work reviewed in this article is funded by the DARPA program TDA: Topological Data Analysis.
NanoMatrix3D® technology in development of nanofibrouse scaffolds: Biomedical evaluation

Nanofiber based materials present unique properties favourable in many biomedical applications and electrospinning technics is the most common for their production due to its capability to produce fibrous materials with their structure and fiber diameters similar to those of extracellular matrix. In this research we evaluated in-vitro degradation, tissue responce and general toxicity of nanofibrose PLA and PCL 3D scaffolds produced by conventional method of electrospinning and using NanoMatrix3D® technology. There were no significant difference in mass loss between conventional and NM3D® electrospun scaffolds both during the static and dynamic degradation test, but dynamic condition significant facilitate degradation rate, that mimic in-vivo non-enzymatic hydrolysis. PCL and PLA scaffolds made by conventional method have shown toxic effect during the in-vivo tests due to residual chloroform that released with material degradation. NM3D® method allows clean scaffolds from residual solutions that makes it non-toxic and biocompatible. Subcutaneous, intramuscular and intraperitoneal implantation of PCL and PLA NM3D® electrospun nanofibrous scaffolds show their appropriate cell conductive properties, tissue and vessels formation in all sites. Thus, NM3D® PCL and PLA nanofibrouse electrospun scaffolds could be used in the field of tissue engineering, surgery, wound healing, drug delivery etc. due to their unique properties, non-toxicity and biocompatibility.
Current Sensor Fault-Tolerant Control for Direct Torque Control of Induction Motor Drive Using Flux-Linkage Observer

This paper proposes a novel fault-tolerant control (FTC) scheme for direct torque control of induction motor (IM) drives against the line current sensor failures. Three major steps involved in the proposed FTC scheme are the detection of sensor fault, isolation of the same, and finally, the reconfiguration by proper estimation. Third-difference operator employed in the motor line current is found suitable for the detection of the sensor fault, while flux-linkage observer-based current estimation scheme performs the task of estimation of line current post the occurrence of the fault. Furthermore, a decision-making logic circuitry isolates the faulty signal and simultaneously selects the appropriate estimated current signal to make the drive fault-tolerant. The proposed current sensor FTC scheme is simple and unique in nature. Moreover, it can be universally applied with any speed control schemes involving IM drive. The proposed scheme is simulated and extensively tested in MATLAB/Simulink. The obtained simulation results are also verified using a dSPACE-1104-based IM drive laboratory prototype to show the effectiveness of the scheme.
Epigenetic Inactivation of Heparan Sulfate (Glucosamine) 3-O-Sulfotransferase 2 in Lung Cancer and Its Role in Tumorigenesis

Background This study was aimed at investigating the functional significance of heparan sulfate (glucosamine) 3-O-sulfotransferase 2 (HS3ST2) hypermethylation in non-small cell lung cancer (NSCLC). Methodology/ Principal Findings HS3ST2 hypermethylation was characterized in six lung cancer cell lines, and its clinical significance was analyzed using 298 formalin-fixed paraffin-embedded tissues and 26 fresh-frozen tissues from 324 NSCLC patients. MS-HRM (methylation-specific high-resolution melting) and EpiTYPERTM assays showed substantial hypermethylation of CpG island at the promoter region of HS3ST2 in six lung cancer cell lines. The silenced gene was demethylated and re-expressed by treatment with 5-aza-2′-deoxycytidine (5-Aza-dC). A promoter assay also showed the core promoter activity of HS3ST2 was regulated by methylation. Exogenous expression of HS3ST2 in lung cancer cells H460 and H23 inhibited cell migration, invasion, cell proliferation and whereas knockdown of HS3ST2 in NHBE cells induced cell migration, invasion, and cell proliferation in vitro. A negative correlation was observed between mRNA and methylation levels of HS3ST2 in 26 fresh-frozen tumors tissues (ρ = -0.51, P = 0.009; Spearman’s rank correlation). HS3ST2 hypermethylation was found in 95 (32%) of 298 primary NSCLCs. Patients with HS3ST2 hypermethylation in 193 node-negative stage I-II NSCLCs with a median follow-up period of 5.8 years had poor overall survival (hazard ratio = 2.12, 95% confidence interval = 1.25–3.58, P = 0.005) compared to those without HS3ST2 hypermethylation, after adjusting for age, sex, tumor size, adjuvant therapy, recurrence, and differentiation. Conclusions/ Significance The present study suggests that HS3ST2 hypermethylation may be an independent prognostic indicator for overall survival in node-negative stage I-II NSCLC.
ELIAD: Efficient lithography aware detailed router with compact post-OPC printability prediction

In this paper, we present ELIAD, an efficient lithography aware detailed router to optimize silicon image after optical proximity correction (OPC) in a correct-by-construction manner. We first propose a compact post-OPC litho-metric for a detailed router based on statistical characterization. We characterize the interferences among weak grids filled with one of predefined litho-prone shapes (e.g., jog-corner, via, line-end). Our litho-metric derived from the characterization shows high fidelity to total edge placement error (EPE) in large scale, compared with Calibre-OPC/ORC. As a chip itself is in the largest scale, ELIAD powered by the proposed metric can enhance the overall post-OPC printed silicon image. Experimental results on 65 nm industrial circuits show that ELIAD outperforms a ripup/rerouting approach such as RADAR [17] with 8times more EPE hotspot reduction and 12times speedup. Also, compared with a conventional detailed router, ELIAD is only about 50% slower.
Analyzing the Prevalence of Sports-Related Terms among the Web Sites of Global Corporations

This research investigates the prevalence of sports-related terms among the Web sites of the world’s leading companies, the Fortune Global 500. An automated process copied about four gigabytes of textual data, around 70 million words, from their sites. The subsequent analysis revealed regional and industry differences in the distribution of sports-related terms, the popularity of tennis stars and few references to sports stars, especially in Asia.
Same- and Other-Sex Popularity and Preference During Early Adolescence

This study examined the longitudinal and bidirectional relations between same-sex (SS) and other-sex (OS) popularity and preference across one school year. Participants were 271 sixth-grade students who completed peer nomination measures at three time points in their schools. Tests of cross-lagged autoregressive models indicated that SS popularity predicted later OS popularity and vice versa. OS preference predicted later SS preference but not vice versa. Findings highlight the importance of more carefully considering the distinctions and associations between SS and OS popularity and preference during early adolescence while setting the stage for future group-level peer relations research.
A 56–65 GHz Injection-Locked Frequency Tripler With Quadrature Outputs in 90-nm CMOS

A sub-harmonic injection-locked tripler multiplies a 20-GHz differential input to 60-GHz quadrature (I/Q) output signals. The tripler consists of a two-stage ring oscillator driven by a single-stage polyphase input filter and 50-Omega I and Q-signal output buffers. Each gain stage incorporates a hard limiter to triple the input frequency for injection locking and a negative resistance cell with two positive feedback loops to increase gain. Regenerative peaking is also used to optimize the gain/bandwidth performance of the 50-Omega output buffers. Fabricated in 90-nm CMOS, the tripler has a free-running frequency of 60.6 GHz. From a 0-dBm RF source, the measured output lock range is 56.5-64.5 GHz, and the measured phase noise penalty is 9.2 plusmn 1 dB with respect to a 20.2-GHz input. The 0.3 times 0.3 mm2 tripler (including passives) consumes 9.6 mW, while the output buffers consume 14.2 mW, all from a 1-V supply.
Personalized social search based on the user's social network

This work investigates personalized social search based on the user's social relations -- search results are re-ranked according to their relations with individuals in the user's social network. We study the effectiveness of several social network types for personalization: (1) Familiarity-based network of people related to the user through explicit familiarity connection; (2) Similarity-based network of people "similar" to the user as reflected by their social activity; (3) Overall network that provides both relationship types. For comparison we also experiment with Topic-based personalization that is based on the user's related terms, aggregated from several social applications. We evaluate the contribution of the different personalization strategies by an off-line study and by a user survey within our organization. In the off-line study we apply bookmark-based evaluation, suggested recently, that exploits data gathered from a social bookmarking system to evaluate personalized retrieval. In the on-line study we analyze the feedback of 240 employees exposed to the alternative personalization approaches. Our main results show that both in the off-line study and in the user survey social network based personalization significantly outperforms non-personalized social search. Additionally, as reflected by the user survey, all three SN-based strategies significantly outperform the Topic-based strategy.
Implementing CoreNet to Reach Out to Businesses - A Case Study of the Singapore Government's IT Initiatives

Over the years, more and more sophisticated e-government systems are being created to reach out to both businesses and citizens alike. However, many such projects have been fraught with difficulties due to myriad barriers which may hinder adoption and inhibit progress during the various phases of the implementation. Against this backdrop, an example of a country with an advanced e-government agenda and a successful track record is Singapore. In this study, we first propose a 3-stage theoretical framework that takes into account the barriers that may hinder a successful e-government implementation and the corresponding change intervention actions to address such barriers. We then demonstrate and refine the applicability of the proposed framework in the context of the Singapore Government’s experience in implementing the CORENET project in the construction and real estate industry. The insights gained and the lessons learnt from this study may have valuable implications for research and practice.
Financial volatility trading using recurrent neural networks

We simulate daily trading of straddles on financial indexes. The straddles are traded based on predictions of daily volatility differences in the indexes. The main predictive models studied are recurrent neural nets (RNN). Such applications have often been studied in isolation. However, due to the special character of daily financial time-series, it is difficult to make full use of RNN representational power. Recurrent networks either tend to overestimate noisy data, or behave like finite-memory sources with shallow memory; they hardly beat classical fixed-order Markov models. To overcome data nonstationarity, we use a special technique that combines sophisticated models fitted on a larger data set, with a fixed set of simple-minded symbolic predictors using only recent inputs. Finally, we compare our predictors with the GARCH family of econometric models designed to capture time-dependent volatility structure in financial returns. GARCH models have been used to trade volatility. Experimental results show that while GARCH models cannot generate any significantly positive profit, by careful use of recurrent networks or Markov models, the market makers can generate a statistically significant excess profit, but then there is no reason to prefer RNN over much more simple and straightforward Markov models. We argue that any report containing RNN results on financial tasks should be accompanied by results achieved by simple finite-memory sources combined with simple techniques to fight nonstationarity in the data.
Presynaptic Localization of Kv1.4-Containing A-Type Potassium Channels Near Excitatory Synapses in the Hippocampus

Mammalian Shaker voltage-gated potassium channels that contain the Kv1.4 subunit exhibit rapid activation and prominent inactivation processes, which enable these channels to integrate brief (approximiately milliseconds) depolarizations over time intervals of up to tens of seconds. In the hippocampus, Kv1.4 immunoreactivity is detected at greatest density in two regions: (1) the middle molecular layer (MML), where perforant path axons synapse with dentate granule cells, and (2) the stratum lucidum (SL) of CA3, where the mossy fibers travel in tight fasciculi and form en passante synapses onto CA3 pyramidal cells. We have studied the localization of Kv1.4 within these regions in detail. First, we compared the distribution of Kv1.4 and synaptophysin (a synaptic vesicle protein primarily localized near termini) under confocal immunofluorescence microscopy. In the MML, Kv1.4 and synaptophysin immunofluorescence appeared to overlap. In the SL, however, Kv1.4 and synaptophysin staining was detected in nonoverlapping, irregular patches (∼5–10 μm in diameter). Ultrastructural studies of these two regions revealed that Kv1.4 immunoreactivity was absent from the surface membranes of cell bodies and dendrites and occurred prominently on axons, including axonal “necks” near termini. Small excitatory synaptic boutons also were labeled in the MML; by contrast, the mossy fiber synaptic expansions in the SL were not stained. These localizations may enable Kv1.4-containing channels to regulate the process of neurotransmitter release at these excitatory synapses.
Competitive Intelligence Practices and Firm Performance

Abstract This study examines the level of competitive intelligence practices undertaken by Malaysian publiclisted companies, and the relationship between competitive intelligence and firm performance. Data was collected from 123 companies across various industry categories. The study finds that competitive intelligence has been practiced at an early stage and in a moderate level among Malaysian companies. The top three intelligence sectors rated by the sampled companies are customers, competitors and the economy. Competitive intelligence is mostly used in making strategic decisions regarding capacity expansion, new product development, and strategic alliance. Competitive intelligence practice relates positively to firm performance. Companies with a formal versus informal competitive intelligence unit achieve higher firm performance as measured by organizational growth and profitability. The article includes implications and recommendations for future studies.
Computationally expanding infinium HumanMethylation450 BeadChip array data to reveal distinct DNA methylation patterns of rheumatoid arthritis

MOTIVATION DNA methylation signatures in rheumatoid arthritis (RA) have been identified in fibroblast-like synoviocytes (FLS) with Illumina HumanMethylation450 array. Since <2% of CpG sites are covered by the Illumina 450K array and whole genome bisulfite sequencing is still too expensive for many samples, computationally predicting DNA methylation levels based on 450K data would be valuable to discover more RA-related genes. RESULTS We developed a computational model that is trained on 14 tissues with both whole genome bisulfite sequencing and 450K array data. This model integrates information derived from the similarity of local methylation pattern between tissues, the methylation information of flanking CpG sites and the methylation tendency of flanking DNA sequences. The predicted and measured methylation values were highly correlated with a Pearson correlation coefficient of 0.9 in leave-one-tissue-out cross-validations. Importantly, the majority (76%) of the top 10% differentially methylated loci among the 14 tissues was correctly detected using the predicted methylation values. Applying this model to 450K data of RA, osteoarthritis and normal FLS, we successfully expanded the coverage of CpG sites 18.5-fold and accounts for about 30% of all the CpGs in the human genome. By integrative omics study, we identified genes and pathways tightly related to RA pathogenesis, among which 12 genes were supported by triple evidences, including 6 genes already known to perform specific roles in RA and 6 genes as new potential therapeutic targets. AVAILABILITY AND IMPLEMENTATION The source code, required data for prediction, and demo data for test are freely available at: http://wanglab.ucsd.edu/star/LR450K/ CONTACT: wei-wang@ucsd.edu or gfirestein@ucsd.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
An Ensemble Diversity Approach to Binary Hashing ❦

Introduction Information retrieval tasks such as searching for a query image or document in a database are essentially a nearest-neighbor search. When the dimensionality of the query and the size of the database is large, approximate search is necessary. We focus on binary hashing, where the query and database are mapped onto low-dimensional binary vectors, where the search is performed. This has two speedups: computing Hamming distances (with hardware support) is much faster than computing distances between high-dimensional floating-point vectors; and the entire database becomes much smaller, so it may reside in fast memory rather than disk (for example, a database of 1 billion real vectors of dimension 500 takes 2 TB in floating point but 8 GB as 64-bit codes).
Special Education as Reconciliation

This paper presents special education as a ministry of reconciliation designed to promote community and to recognize wholeness in the presence of disability. It is offered as part of an ongoing discussion of the need for an inclusive world view founded on Christian principles. Including the excluded –reaching out to those ignored or pushed away by society – was a characteristic of Jesus' ministry and must be a hallmark of Christian educators and churches. The hope is that the ideas expressed herein will foster collaborative efforts between general and special educators which lead to the creation of positive, caring classroom communities that value and promote unity and equality while also celebrating diversity. Christian teacher training programs must encourage and model an inclusive worldview in which individuals with disabilities are also recognized as God's image-bearers, and where there is acknowledgment of the abilities and gifts they bring to the classroom community.
Fitting Models to Distributed Representations of Vision

Many representations in early vision can be constructed by performing orientation analysis along several sampling dimensions. Texture is often oriented in space, motion is oriented in space-time, and stereo is oriented in space-disparity. In these modalities, we can construct distributed representations with oriented energy measures used in models of biological vision. Surface models of orientation, velocity, and disparity can easily be fit to distributed representations of texture, motion, and stereo by combining tools of orientation analysis and regularization. We describe base representation construction and model fitting processes in these domains.
Antinociceptive activity of carvacrol (5‐isopropyl‐2‐methylphenol) in mice

Objectives Carvacrol (5‐isopropyl‐2‐methylphenol) is a monoterpenic phenol which is present in the essential oil of oregano and thyme. We have investigated the behavioural effects of carvacrol in animal models of pain, such as acetic acid‐induced abdominal constriction, formalin and hot‐plate tests in mice. The spontaneous motor activity of animals treated with carvacrol was investigated using open‐field and rotarod tests.