Miracle-dz/UniFAR-FTUs huggingface dataset:
Boosting Principal Component Analysis by Genetic Algorithm

This paper presents a new method of feature extraction by combining principal component analysis and genetic algorithm. Use of multiple pre-processors in combination with principal component analysis generates alternate feature spaces for data representation. The present method works out the fusion of these multiple spaces to create higher dimensionality feature vectors. The fused feature vectors are given chromosome representation by taking feature components to be genes. Then these feature vectors are allowed to undergo genetic evolution individually. For genetic algorithm, initial population is created by calculating probability distance matrix, and by applying a probability distance metric such that all the genes which lie farther than a defined threshold are tripped to zero. The genetic evolution of fused feature vector brings out most significant feature components (genes) as survivours. A measure of significance is adapted on the basis of frequency of occurrence of the surviving genes in the current population. Finally, the feature vector is obtained by weighting the original feature components in proportion to their significance. The present algorithm is validated in combination with a neural network classifier based on error backpropagation algorithm, and by analysing a number of benchmark datasets available in the open sources.Defence Science Journal, 2010, 60(4), pp.392-398, DOI:http://dx.doi. org/10.14429/dsj.60. 495
Microwave-assisted synthesis of molybdenum oxide nanoparticles

This paper focused on a simple approach for synthesis of molybdenum oxide (MoO3) nanoparticles and reports a facile route for synthesis of such nanoparticles, using microwave irradiation as a homogenous and powerful source of heating, using ethylene glycol as the solvent and heating medium. For more investigations, besides microwave heating, the obtained solutions were also treated by conventional heating. Finally, product particles were characterized and compared using scanning electron microscopy (SEM) and energy dispersive x-ray microanalysis (EDX). According to the results, microwave irradiated particles showed a good dispersion and stability in relation to the other sample. So, the obtained product was subjected to X-ray diffraction (XRD) analysis to survey the formation of MoO3 nanoparticles. The transmission electron microscope (TEM) micrographs were also recorded to study the size and morphology of the nanoparticles. According to the results, nanoparticles were spherical with an average size of about 50 nm. The absorbance spectrum of MoO3 nanoparticles was further studied using the UV-spectroscopy and the absorbance peak was observed at 257nm.
An array of WO3 and CTO heterojunction semiconducting metal oxide gas sensors used as a tool for explosive detection

Terrorists frequently use explosives and they represent an imminent threat to national and global security. Recent events highlight the necessity of explosive detection, demonstrating the need for developing and applying new sensors for explosive gas detection. Semiconducting metal oxide gas sensors can be incorporated into electronic noses, which provide a cheap, portable and highly sensitive device. Using unmodified, admixed and 2-layered sensors consisting of WO3 and chromium titanium oxide (CTO), an array of seven heterojunction semiconducting metal oxide sensors was produced. All seven sensors were tested against four gases associated with explosive materials. The sensitivity was improved by using 2-layered sensors in response to ethanol, ammonia and nitromethane, whereas the admixed sensors showed high sensitivity when exposed to nitrogen dioxide. The selectivity of the array of sensors was tested using machine-learning techniques with a support vector machine. The technique produced good data classification when classifying the gases used within the study.
Sign language recognition using model-based tracking and a 3 D Hopfield neural network

This paper presents a sign language recognition system which consists of three modules: model-based hand tracking, feature extraction, and gesture recognition using a 3D Hopfield neural network (HNN). The first one uses the Hausdorff distance measure to track shapevariant hand motion, the second one applies the scale and rotation-invariant Fourier descriptor to characterize hand figures, and the last one performs a graph matching between the input gesture model and the stored models by using a 3D modified HNN to recognize the gesture. Our system tests 15 different hand gestures. The experimental results show that our system can achieve above 91% recognition rate, and the recognition process time is about 10 s. The major contribution in this paper is that we propose a 3D modified HNN for gesture recognition which is more reliable than the conventional methods.
GENOME SIZE VARIATION IS CORRELATED WITH ALTITUDE WITHIN CHINESE SPECIES OF ALLIUM L

Species in the genus Allium L. (Alliaceae) are important economic crops. They exhibit variations in genome size and basic chromosome number. In the present study, the nuclear genome size of plants sampled from Allium populations was determined using flow cytometry occuring at altitudes from 43 m to 1530 m above sea level (asl) in Hubei province, China. Our results revealed that the values of 2C genome of these Allium populations distributed from 15.10 to 64.65 pg, the significant interspecific variation in the nuclear DNA contents. There is a positive correlation among these Allium population between altitude and genome size. This study will deepen the understanding of the relationship between the nuclear genome size and the habitat altitude in high altitude-dependent plants.
Nitrogen isotope (δ15N) patterns for amino acids in lemur bones are inconsistent with aridity driving megafaunal extinction in south‐western Madagascar

Most endemic species with body masses >10 kg on Madagascar went extinct within the past 1000 years. The extent to which human predation, anthropogenic landscape transformation and aridification may separately or together explain this extinction pattern remains controversial. We present nitrogen isotope (δ15N) values of individual amino acids preserved in bones from now‐extinct Pachylemur insignis and extant Propithecus verreauxi from two subfossil sites in south‐western Madagascar: Tsirave and Taolambiby. The amino acid‐specific approach allows us to identify environmental signals that are otherwise difficult to recognize in bulk collagen δ15N values. Specifically, we use the δ15N values of source amino acids (phenylalanine and lysine) as a proxy for habitat aridity between ca. 4000 years ago and present and the spacing of δ15N values between trophic and source amino acids to quantify trophic levels for these two lemur species. Despite paleoenvironmental evidence for lowering water tables and the expansion of relatively arid savanna between 4000 and 1000 years ago, our isotope data suggest that these lemurs did not live in increasingly arid habitats and did not change their trophic level. Together, our results support the hypothesis that aridity alone did not play a major role in late Holocene megafaunal extinctions in south‐western Madagascar.
Consumer understanding and use of nutrition labelling: a systematic review.

Objective: To explore published and unpublished research into consumer understanding and use of nutrition labelling which is culturally applicable in Europe. Design: A systematic review undertaken between July 2002 and February 2003. Results: One hundred and three papers were identified that reported on consumer understanding or use of nutrition labelling, most originating from North America or northern Europe. Only a few studies (9%) were judged to be of high or medium-high quality. We found that reported use of nutrition labels is high but more objective measures suggest that actual use of nutrition labelling during food purchase may be much lower. Whether or not consumers can understand and use nutrition labelling depends on the purpose of the task. Available evidence suggests that consumers who do look at nutrition labels can understand some of the terms used but are confused by other types of information. Most appear able to retrieve simple information and make simple calculations and comparisons between products using numerical information, but their ability to interpret the nutrition label accurately reduces as the complexity of the task increases. The addition of interpretational aids like verbal descriptors and recommended reference values helps in product comparison and in putting products into a total diet context. Conclusions: Improvements in nutrition labelling could make a small but important contribution towards making the existing point-of-purchase environment more conducive to the selection of healthy choices. In particular, interpretational aids can help consumers assess the nutrient contribution of specific foods to the overall diet.
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository

Researchers currently rely on ad hoc datasets to train automated visualization tools and evaluate the effectiveness of visualization designs. These exemplars often lack the characteristics of real-world datasets, and their one-off nature makes it difficult to compare different techniques. In this paper, we present VizNet: a large-scale corpus of over 31 million datasets compiled from open data repositories and online visualization galleries. On average, these datasets comprise 17 records over 3 dimensions and across the corpus, we find 51% of the dimensions record categorical data, 44% quantitative, and only 5% temporal. VizNet provides the necessary common baseline for comparing visualization design techniques, and developing benchmark models and algorithms for automating visual analysis. To demonstrate VizNet's utility as a platform for conducting online crowdsourced experiments at scale, we replicate a prior study assessing the influence of user task and data distribution on visual encoding effectiveness, and extend it by considering an additional task: outlier detection. To contend with running such studies at scale, we demonstrate how a metric of perceptual effectiveness can be learned from experimental results, and show its predictive power across test datasets.
UP versus NP

P versus NP is considered as one of the most important open problems in computer science. This consists in knowing the answer of the following question: Is P equal to NP? A precise statement of the P versus NP problem was introduced independently in 1971 by Stephen Cook and Leonid Levin. Since that date, all eﬀorts to ﬁnd a proof for this problem have failed. Another major complexity class is UP. Whether UP = NP is another fundamental question that it is as important as it is unresolved. To attack the UP = NP question the concept of NP-completeness is very useful. If any single NP-complete problem is in UP, then UP = NP. Quadratic Congruences is a well-known NP-complete problem. We prove Quadratic Congruences is also in UP. In this way, we demonstrate that UP = NP.
Futurescapes of urban regeneration: ten years of design for the unfolding urban legacy of London’s Olympic Games, 2008–2018

ABSTRACT Much of the literature on the urban legacy of the 2012 Olympics Games emerging in recent years has emphasized the form that development has taken and the ways in which this aligns (or not) with specific promises made in terms of regeneration before the Games. Though plenty of discussion of planning procedure has occurred in this context, less emphasis has been placed on how the process, rather than the products, of urban change has been envisioned through legacy planning and urban design, and the significance of this for regeneration. Given that London’s much-heralded ‘regeneration legacy’ was, from the early days of the Olympic bid, portrayed as a long-term process aimed at addressing historical issues of socio-economic disparity in East London, and that planning and urban design would play key roles in anticipating it, this contribution to the literature is timely. The paper focuses on the period from 2008 to 2018, beginning with the launch of the what was called the Legacy Masterplan Framework. Drawing on empirical analysis of documents describing the main stages of legacy planning and design between these years, it then examines how regeneration as a ‘futurescape’ encompassing numerous aspects of timing and temporality has been anticipated, planned and evolved.
Graphics Preprocessing and Storage Data Filtering Feature Extraction Threads Reconstruction Visualization Hadoop Data Store Twitter Anomalous Threads Detection Analysis Multidimensional Scaling Hierarchical Content Clustering User Interaction Graph Extraction

We present FluxFlow, an interactive visual analysis system for revealing and analyzing anomalous information spreading in social media. Everyday, millions of messages are created, commented, and shared by people on social media websites, such as Twitter and Facebook. This provides valuable data for researchers and practitioners in many application domains, such as marketing, to inform decision-making. Distilling valuable social signals from the huge crowd’s messages, however, is challenging, due to the heterogeneous and dynamic crowd behaviors. The challenge is rooted in data analysts’ capability of discerning the anomalous information behaviors, such as the spreading of rumors or misinformation, from the rest that are more conventional patterns, such as popular topics and newsworthy events, in a timely fashion. FluxFlow incorporates advanced machine learning algorithms to detect anomalies, and offers a set of novel visualization designs for presenting the detected threads for deeper analysis. We evaluated FluxFlow with real datasets containing the Twitter feeds captured during significant events such as Hurricane Sandy. Through quantitative measurements of the algorithmic performance and qualitative interviews with domain experts, the results show that the back-end anomaly detection model is effective in identifying anomalous retweeting threads, and its front-end interactive visualizations are intuitive and useful for analysts to discover insights in data and comprehend the underlying analytical model.
PREDICTION MODEL FOR UNSATURATED HYDRAULIC CONDUCTIVITY OF HIGHWAY SOILS

A method of predicting the hydraulic conductivites of subgrades and highway soil materials is discussed. In this method, the relation of soil moisture content and suction head is used to calculate the unsaturated hydraulic conductivity of soil. The value of the hydraulic conductivity at saturation (the soil permeability) is used as a matching factor during the calculations. The soil moisture content and suction head relation and the saturated conductivities of subgrades were determined in the laboratory by using the commercially available Tempe cell. Disturbed and undisturbed samples of Drummer and Fayette-C subgrades, Ottawa sand, and class X concrete sand were used in this study. The comparison between the experimental and the calculated values shows that the method successfully predicts the hydraulic conductivities of highway soil materials. /Author/
Homicide in Ireland 1992 - 1996.

This study examines the characteristics of homicides occurring in Ireland during the five year period 1 January 1992 to 31 December 1996. The data builds on that which was presented in a previous similar study1 covering the twenty year period prior to that covered in the present study. To facilitate overall comparison a number of tables and figures will amalgamate data from the previous study with that outlined here to present a twenty-five year cohort.
AKARI Near- to Mid-Infrared Imaging and Spectroscopic Observations of the Small Magellanic Cloud. I Bright Point Source List

We carried out a near- to mid-infrared imaging and spectroscopic observations of the patchy areas in the Small Magellanic Cloud using the Infrared Camera on board AKARI. Two 100 arcmin2 areas were imaged in 3.2, 4.1, 7, 11, 15, and 24 um and also spectroscopically observed in the wavelength range continuously from 2.5 to 13.4 um. The spectral resolving power (lambda/Delta lambda) is about 20, 50, and 50 at 3.5, 6.6 and 10.6 um, respectively. Other than the two 100 arcmin2 areas, some patchy areas were imaged and/or spectroscopically observed as well. In this paper, we overview the observations and present a list of near- to mid-infrared photometric results, which lists ~ 12,000 near-infrared and ~ 1,800 mid-infrared bright point sources detected in the observed areas. The 10 sigma limits are 16.50, 16.12, 13.28, 11.26, 9.62, and 8.76 in Vega magnitudes at 3.2, 4.1, 7, 11, 15, and 24 um bands, respectively.
Existence of different kind of solutions for discrete time equations

Abstract The aim of this paper is to extend the classical linear condition concerning diagonal dominant bloc matrix to fully nonlinear equations. Even if assumptions are strong, we obtain an explicit condition which exactly extend the one known in linear case, and the setting allows also to consider bicontinuous operator instead of the schift and as particular case, we receive periodic or almost periodic solutions for discrete time equations.
Evaluation of lipid profile status in nondiabetic and diabetic hypothyroidism patients

In the last few decades, abnormality in lipid profile is a serious concern in various diseases including diabetes mellitus. However, limited studies have been documented on lipid abnormality in hypothyroidism (HT) along with diabetes. The objective of present study was to determine the glycemic and lipid profile in nondiabetic and diabetic hypothyroidism patients and to determine their role in disease complexity. Fasting and post prandial blood glucose levels along with serum total cholesterol, triglycerides, HDL, LDL and VLDL levels were estimated by using standard methods in 100 patients of HT divided into two groups of 50 HT nondiabetic patients and 50 HT diabetic patients as Group II and Group III respectively, and compared it with 50 age matched healthy controls (Group I). The values were expressed as Mean ± SD and data from patients and controls were compared using students‘t’ test. Serum total cholesterol, triglycerides, LDL and VLDL levels along with fasting blood sugar were significantly high (p<0.001) and serum HDL levels were significantly low (p<0.001) in Group III patients as compared to control. However, serum total cholesterol, triglycerides, LDL and VLDL levels were altered significantly (p<0.05) in Group II subjects. These finding suggest that diabetic HT patients are at enhanced risk to develop cardiovascular complication due to their altered glycemic and lipid profile with respect to nondiabetic HT patients. Therefore, maintenance of normal thyroid profile, regular monitoring of cardiac markers, control on blood sugar level along with proper treatment of dyslipidemia and diabetes in these patients can prove to be protective.
GALACTO-FORENSIC OF LARGE MAGELLANIC CLOUD'S ORBITAL HISTORY AS A PROBE FOR THE DARK MATTER POTENTIAL IN THE OUTSKIRTS OF THE GALAXY

The three-dimensional observed velocities of the Large and Small Magellanic Clouds (LMC and SMC) provide an opportunity to probe the Galactic potential in the outskirt of the Galactic halo. Based on a canonical NFW model of the Galactic potential, Besla et al. reconstructed LMC and SMC's orbits and suggested that they are currently on their first perigalacticon passage about the Galaxy. Motivated by several recent revisions of the Sun's motion around the Galactic center, we re-examine the LMC's orbital history and show that it depends sensitively on the dark matter's mass distribution beyond its present Galactic distance. We utilize results of numerical simulations to consider a range of possible structural and evolutionary models for the Galactic potentials. We find that within the theoretical and observational uncertainties, it is possible for the LMC to have had multiple perigalacticon passages on the Hubble timescale, especially if the Galactic circular velocity at the location of the Sun is greater than ∼228 km s−1. Based on these models, a more accurate determination of the LMC's motion may be used to determine the dark matter distribution in the outskirt of the Galactic halo.
Assessment of functional connectivity impairment in rat brains

While the rodent model has long been used in brain research, there exists no standardised processing routine that can be employed for analysis and investigation of disease models. The present thesis attempts to investigate a diseased brain model by implementing a collection of scripts, combined with algorithms from existing neuroimaging software, and adapting them to the rodent brain, in an attempt to examine when and how monaural canal atresia affects the functional connectivity of the brain. We show that it is possible to use software tailored to the human brain to pre-process the rodent model. Following conventional pipelines and resting state functional MRI (rs-fMRI)-specific strategies, the developed processing routine implements the most basic steps suggested in literature. On the single-subject level, skull stripping was done using Mialite software, motion correction and distortion correction were based on FMRIB software library (FSL) algorithms and motion artefacts were removed using ICA-based Automatic Removal Of Motion Artifacts (ICA-AROMA). Following denoising, normalisation to standard space, smoothing and temporal filtering, group level analysis was performed. A univariate, hypothesis-driven method and a multivariate, data-driven method were used for group comparison and statistical inference. While seed-based correlation analysis (SCA) did not return any significant results, independent component analysis (ICA) identified two components that show activation in areas of interest.
Title CLUSTAG : Hierarchical clustering and graph methods forselecting tag SNPs

Summary: Cluster and set-cover algorithms are developed to obtain a set of tag single nucleotide polymorphisms (SNPs) that can represent all the known SNPs in a chromosomal region, subject to the constraint that all SNPs must have a squared correlation R2 > C with at least one tag SNP, where C is specified by the user. Availability: http://hkumath.hku. hk/web/link/CLUSTAG/CLUSTAG.
An efficient regeneration system for the genetic transformation of Nicotiana tabacum L . cv . Petit Havana SR 1 without Auxine and optimization of Hygromycin concentration for selection

This is a new in vitro regeneration and genetic transformation protocol for Tobacco (Nicotiana tabacum L. cv. Petit Havana SR1). Transformation and regeneration of tobacco leaf explants was done using only Benzyl amino purine (BAP) without auxin supplement as with other available protocols for tobacco. Furthermore this work evaluates the Agrobacterium-mediated transformation efficiency of Tobacco under the selection pressure of herbicide hygromycin. Leaves of 6 week old seedlings were used as explants. Transformation was carried out, using the Agrobacterium tumifaciens LBA4404 harbouring pCAMBIA1302 with hygromycin phosphor transferase gene as the selectable marker gene and the green fluorescence protein (GFP) gene as the reporter. The result showed that the optimum concentration of hygromycin for selection of transformants was 25mg L -1 . Multiple shoots were regenerated from each explant when Murashige and Skoog basal medium supplemented with only 3mg L -1 BAP had been used. Transformation efficiency of explants was 100% under the optimized conditions. The presence of the transgene was confirmed by PCR with primers corresponding to a 454bp sequence of the gfp gene. Integration and expression of the transgene cassette within the transformants were further confirmed by visualizing transformed tissue under fluorescence microscope with UV of specific wavelength for GFP, to visualize the expression of the gfp gene. Here we have standardized a suitable transformation system for tobacco with minimum hormone supplement resulting in the highest possible transformation efficiency.