Miracle-dz/UniFAR-FTUs huggingface dataset:
Ironing Out the Unconventional Mechanisms of Iron Acquisition and Gene Regulation in Chlamydia

The obligate intracellular pathogen Chlamydia trachomatis, along with its close species relatives, is known to be strictly dependent upon the availability of iron. Deprivation of iron in vitro induces an aberrant morphological phenotype termed “persistence. ” This persistent phenotype develops in response to various immunological and nutritional insults and may contribute to the development of sub-acute Chlamydia-associated chronic diseases in susceptible populations. Given the importance of iron to Chlamydia, relatively little is understood about its acquisition and its role in gene regulation in comparison to other iron-dependent bacteria. Analysis of the genome sequences of a variety of chlamydial species hinted at the involvement of unconventional mechanisms, being that Chlamydia lack many conventional systems of iron homeostasis that are highly conserved in other bacteria. Herein we detail past and current research regarding chlamydial iron biology in an attempt to provide context to the rapid progress of the field in recent years. We aim to highlight recent discoveries and innovations that illuminate the strategies involved in chlamydial iron homeostasis, including the vesicular mode of acquiring iron from the intracellular environment, and the identification of a putative iron-dependent transcriptional regulator that is synthesized as a fusion with a ABC-type transporter subunit. These recent findings, along with the noted absence of iron-related homologs, indicate that Chlamydia have evolved atypical approaches to the problem of iron homeostasis, reinvigorating research into the iron biology of this pathogen.
Analysis using Twitter to predict the 2016 US Presidential Election

ocial media is a social platform that is made up of people who are connected S several interdependencies. Social media has changed the nature of information in terms of availability, importance and volume. Through social media like Twitter and Facebook, participants reveal personal information that has real values, as they can be extracted and mined to improve decision making. In this paper, a small sized data was extracted from twitter and analysed using a data mining classification algorithm known as sentiment analysis (also referred to as opinion extraction, opinion mining, sentiment mining and subjective analysis). Sentiment analysis is a technique used by several researchers to measure the emotions of social media participants in online text, in our case it was used to determine the opinion of people or participants towards the 2016 US presidential candidates. Whereas data mining is the technique of discovering and extracting useful information from large data sets or databases. Additionally, the result of the analysis was used to predict the outcome of the aforementioned election.
Design and implementation of a lip reading system in smart phone environment

This study proposes a real-time lip-reading method in smart phone environment. In smart-phone environment where the resources are limited compared to existing PC environment, it is hard to operate lip-reading in real-time. To solve this problem, this study proposes the lip area detection method and feature extraction method suitable for smart-phone environment. First, to find the accurate lip area, the face area is detected by means of face color information, and the eyes are located to detect the lip area with the geometrical relation. To extract the outstanding features of the lip area in terms of changes in light according to the changes of surroundings, histogram matching, lip folding, and RASTA filter are applied, and the extracted data of features by means of PCA are used in recognition. As a result of the experiment, the changes were recognized almost in real-time, and 30 words of 50 were recognized, which indicates 60% recognition rates.
The ‘8Gs’—a blueprint for Geoheritage, Geoconservation, Geo-education and Geotourism

Abstract In the growing field of Geoheritage, Geoconservation, Geo-education and Geotourism, there is a need to manage sites of geoheritage significance. While there is some great geology in nature available to appreciate for scenic value, education, tourism and research, many locations need to be protected from people and commercialism (e.g. the Iridium layer at the K/T boundary in Gubbio, Italy, the Ediacaran fauna in South Australia, the Burgess Shale in Canada or the zircon crystals at Jack Hills, among many others), and some locations need hazard management to protect people (e.g. continuously collapsing cliffs that have potential to be hazardous via rock falls, or slippery slopes, or high cliffs that are treacherous, or ‘king waves’ on rocky shores). The concept of the ‘8Gs’ is intended as a policy-style guidance that logically and progressively links Geology and Geoheritage through a series of steps to Geo-education and Geotourism. There is a logical progression from Geology the Science, through to Geoheritage and the identification of sites of geoheritage significance, to the establishment of Geosites/Geoparks, Geoconservation, leading to Geomanagement, Geo-education and Geotourism. Geomanagement needs to be undertaken prior to the use of sites for Geo-education and Geotourism. In relation to Geomanagement, sites need to be investigated for safety issues, and for the protection of their geological features. Geodiversity, the eighth ‘G’, is outside the progression but plays an important part in underpinning biodiversity. There is also a need to address and manage geodiversity in a given region or specific site to help understand and manage biodiversity.
Firm-Specific Variation and Capital Openness

* Doctoral Student, The University of Alberta Business School, Edmonton, Canada T6G 2R6. Tel: (780) 492-5435. Fax: (780) 492-3325. E-mail: kli@ualberta.ca. ** Stephen A. Jarislowsky Distinguished Professor of Finance, School of Business, University of Alberta, Edmonton, Alberta, Canada, T6G 2R6. Tel: (780) 492-5683. Fax: (780) 492 3325. E-mail randall.morck@ualberta.ca; Research Associate, National Bureau of Economic Research, 1050 Massachusetts Avenue, Cambridge, MA 02138 USA. *** Doctoral Student, The University of Alberta Business School, Edmonton, Canada T6G 2R6. Tel: (780) 492-5435. Fax: (780) 492-3325. E-mail: fyang@ualberta.ca. **** Abraham Krasnoff Professor of International Business and Professor of Economics, Stern School of Business, New York University, New York, NY 10012. Tel: (212) 998-0425. Fax: (212) 995-4221. E-mail byeung@stern.nyu. edu.
Adapting the artificial bee colony metaheuristic to optimize image multilevel thresholding

The main idea of this paper is to adapt the Artificial Bee Colony metaheuristic to solve the problem of multilevel thresholding for image segmentation. More precisely, this method is exploited to optimize two maximizing functions namely the between-class variance (the Otsu's function) and the entropy thresholding (the Kapur's function). This leads, respectively, to two versions of the ABC metaheuristic: the ABC-Otsu and the ABC-Kapur. The robustness and proficiency of these two thresholding algorithms are demonstrated by applying them on a set of well-known benchmark images. Furthermore, the experimental results show the efficiency of these two thresholding methods.
An enhanced classification approach to change detection in semi-arid environments

The use of Lanbsat digital classifications or enhancements to monitor change in semi-arid environments has generally met with limit~d success. This can be partially attributed to unique physical and human factors which complicate change detection in these environments. An enhanced classification approach which combines image enhancement to isolate chartge with multispectral classification to identify change dynamics has been developed. The technique has been applie1d in northwestern Nigeria to dry season Landsat MSS images acquired for dates before and after construction of the Bakolori dam and reservoir. These images span a nine-year period during which marked changes have occurred as ~ result of dam construction and stream regulation associated with the Bakolori project. The results show evidence of land degradation in flood plain areas downstream of the Bakolori dam where flood plain cultivation has been reducJd by as much as 50 percent. Comparisons with ground survey data confirm that the enhanced classification approach pr6vides more accurate information on change by minimizing errors associated with misregistration and misclassification and by allowing the suppression of environmental factors through the separation of natural and human-induced change.
Epidemiological methods to tackle causal questions.

It is a dull day when there is not at least one media report of a claim that research has identified some new environmental cause of disease. Such claimed causes concern a wide range of supposed hazards including medical interventions such as the measles-mumps-rubella (MMR) vaccine, the thimerasol (mercury) preservative in other vaccines, dietary factors of many different kinds (coffee, alcohol, food additives, etc.), prenatal stresses or the intra-uterine exposure to the effects of maternal smoking or ingestion of alcohol, use of mobile phones, and living near radiation sources—to mention just a few examples. It is problematic, however, that many of these claims are not confirmed by other research and some are even reversed. Unsurprisingly both professionals and the lay public have developed a scepticism about claims on environmental causes of disease. Because much of the evidence derives from epidemiological studies of one kind or another, epidemiological science itself has come under scrutiny both within and outside the profession. Some have argued that only laboratory experiments and randomized controlled trials (RCT) can provide acceptable evidence on causation. That cannot be a solution, however, because so many of the putative environmental causes are ones that cannot be manipulated in humans—for a mixture of both ethical and practical reasons. Because the identification of environmental causes is of such importance, and because the solution of the causal inference problem has no obvious single, simple solution, the Academy of Medical Sciences set up a working party (made up of clinical scientists, epidemiologists, statisticians, policy leaders and scientific media specialists) to answer the key questions of 'how should we decide what to believe and when to take action? ' The report 1 emphasized the need to focus on individual components in the causal process and not on some misleading abstract notion of a single basic cause. It also notes the many reasons why an observed association or correlation might not reflect an environmentally mediated causal effect. Such reasons include genetic mediation of the causal risk effect, social selection (allocation bias), and reverse causation to mention but three out of a much longer list of possibilities. It was also noted that the main problem in moving from an observed association to a causal inference did not lie in the effect of known, measured confounders, but rather in the effect of unknown, unmeasured confounders. In recent years, there have been important statistical developments that go beyond the traditional …
TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction

Transcription activator-like (TAL) effectors are repeat-containing proteins used by plant pathogenic bacteria to manipulate host gene expression. Repeats are polymorphic and individually specify single nucleotides in the DNA target, with some degeneracy. A TAL effector-nucleotide binding code that links repeat type to specified nucleotide enables prediction of genomic binding sites for TAL effectors and customization of TAL effectors for use in DNA targeting, in particular as custom transcription factors for engineered gene regulation and as site-specific nucleases for genome editing. We have developed a suite of web-based tools called TAL Effector-Nucleotide Targeter 2.0 (TALE-NT 2.0; https://boglab.plp.iastate.edu/) that enables design of custom TAL effector repeat arrays for desired targets and prediction of TAL effector binding sites, ranked by likelihood, in a genome, promoterome or other sequence of interest. Search parameters can be set by the user to work with any TAL effector or TAL effector nuclease architecture. Applications range from designing highly specific DNA targeting tools and identifying potential off-target sites to predicting effector targets important in plant disease.
Predicting vulnerable software components

Where do most vulnerabilities occur in software? Our Vulture tool automatically mines existing vulnerability databases and version archives to map past vulnerabilities to components. The resulting ranking of the most vulnerable components is a perfect base for further investigations on what makes components vulnerable. In an investigation of the Mozilla vulnerability history, we surprisingly found that components that had a single vulnerability in the past were generally not likely to have further vulnerabilities. However, components that had similar imports or function calls were likely to be vulnerable. Based on this observation, we were able to extend Vulture by a simple predictor that correctly predicts about half of all vulnerable components, and about two thirds of all predictions are correct. This allows developers and project managers to focus their their efforts where it is needed most: "We should look at nsXPInstallManager because it is likely to contain yet unknown vulnerabilities. ".
An Effective Clustering Algorithm for Data Mining

This paper proposes an effective clustering algorithm for databases, which are benchmark data sets of data mining applications. We present a Genetic Clustering Algorithm (GCA) that finds a globally optimal partition of a given data sets into a specified number of clusters. The algorithm is distance-based and creates centroids. To evaluate the proposed algorithm, we use some artificial data sets and compare with results of K-means. Experimental results show that the proposed algorithm has better performance and efficiently finds accurate clusters.
Multiplicative optical tomography of cardiac electrical activity

Cardiac electrical activity can be mapped today through the response of voltage-sensitive dyes; but poor transparency of muscle tissue has enforced shallow-depth imaging. We present a three-dimensional (3D) reconstruction method for electrical activity deep inside the myocardial wall. Our approach is nonlinear and differs substantially from standard diffusive optical tomography. It does not require matrix inversion, data regularization or a priori information concerning the original object. Opposite sides of a slab-shaped preparation are scanned in parallel by detection and illumination points with a constant vector offset between illumination and detection axes (biaxial scanning). Scanning is performed in two perpendicular directions. In each direction, a pair of 2D images is obtained under offsets of opposite signs. These two pairs are the input for a multiplicative reconstruction algorithm, whose output is a 3D image. The overall procedure was successfully tested on computer-generated sources that include points, lines and hemispheres, patterned after actual electrophysiological excitations. The algorithm is computationally efficient and stable with respect to varying noise levels in the raw data.
Thermal Conductivity of a Nanoscale Yttrium Iron Garnet Thin-Film Prepared by the Sol-Gel Process

The thermal conductivity of a nanoscale yttrium iron garnet (Y3Fe5O12, YIG) thin-film prepared by a sol-gel method was evaluated using the ultrafast pump-probe technique in the present study. The thermoreflectance change on the surface of a 250 nm thick YIG film, induced by the irradiation of femtosecond laser pulses, was measured, and curve fitting of a numerical solution for the transient heat conduction equation to the experimental data was performed using the finite difference method in order to extract the thermal property. Results show that the film’s thermal conductivity is 22–83% higher than the properties of bulk YIG materials prepared by different fabrication techniques, reflecting the microstructural characteristics and quality of the film.
Declining Coral Skeletal Extension for Forereef Colonies of Siderastrea siderea on the Mesoamerican Barrier Reef System, Southern Belize

Background Natural and anthropogenic stressors are predicted to have increasingly negative impacts on coral reefs. Understanding how these environmental stressors have impacted coral skeletal growth should improve our ability to predict how they may affect coral reefs in the future. We investigated century-scale variations in skeletal extension for the slow-growing massive scleractinian coral Siderastrea siderea inhabiting the forereef, backreef, and nearshore reefs of the Mesoamerican Barrier Reef System (MBRS) in the western Caribbean Sea. Methodology/Principal Findings Thirteen S. siderea cores were extracted, slabbed, and X-rayed. Annual skeletal extension was estimated from adjacent low- and high-density growth bands. Since the early 1900s, forereef S. siderea colonies have shifted from exhibiting the fastest to the slowest average annual skeletal extension, while values for backreef and nearshore colonies have remained relatively constant. The rates of change in annual skeletal extension were −0.020±0.005, 0.011±0.006, and −0.008±0.006 mm yr−1 per year [mean±SE] for forereef, backreef, and nearshore colonies respectively. These values for forereef and nearshore S. siderea were significantly lower by 0.031±0.008 and by 0.019±0.009 mm yr−1 per year, respectively, than for backreef colonies. However, only forereef S. siderea exhibited a statistically significant decline in annual skeletal extension over the last century. Conclusions/Significance Our results suggest that forereef S. siderea colonies are more susceptible to environmental stress than backreef and nearshore counterparts, which may have historically been exposed to higher natural baseline stressors. Alternatively, sediment plumes, nutrients, and pollution originating from watersheds of Guatemala and Honduras may disproportionately impact the forereef environment of the MBRS. We are presently reconstructing the history of environmental stressors that have impacted the MBRS to constrain the cause(s) of the observed reductions in coral skeletal growth. This should improve our ability to predict and potentially mitigate the effects of future environmental stressors on coral reef ecosystems.
Image copy-move forgery detection using hierarchical feature point matching

Copy-move forgery is one of the most commonly used manipulations for tempering digital images. Keypoint-based detection methods have been reported to be very effective in revealing copy-move evidences, due to their robustness against geometric transforms. However, these methods fail to handle the cases when copy-move forgery only involves small or smooth regions, where the number of keypoints is very limited. To tackle this challenge, we propose a simple yet effective copy-move forgery detection approach. By lowering the contrast threshold and rescaling the input image, we first generate a sufficient number of keypoints that exist even in the small or smooth regions. Then, a novel hierarchical matching strategy is developed for solving the keypoint matching problems. Finally, a novel iterative homography estimation technique is suggested through exploiting the dominant orientation information of each keypoint. Extensive experimental results are provided to demonstrate the superior performance of the proposed scheme.
Rapid Development of a Flexible Validated Processor Model

validated models. Unfortunately, they only present anecdotal and secondary evidence to support their claims. In this paper, we present our experience using this methodology to construct a validated flexible model of Intel’s Itanium 2 processor. Our practical experience lends support to the above claims. Our initial model was constructed by a single researcher in only 11 weeks and predicts processor cycles-per-instruction (CPI) to within 7.9% on average for the entire SPEC CINT2000 benchmark suite. Our experience with this model showed us that aggregate accuracy for a metric like CPI is not sufficient. Aggregate measures like CPI may conceal remaining internal “offsetting errors” which can adversely affect conclusions drawn from the model. Using this as our motivation, we explore the flexibility of the model by modifying it to target specific error constituents, such as front-end stall errors. In 2 1 person-weeks, average CPI error was reduced to 5.4%. The targeted error constituents were reduced more dramatically; front-end stall errors were reduced from 5.6% to 1.6%. The swift implementation of significant new architectural features on this model further demonstrated its flexibility.
Advanced swarm robots addressing innovative tasks such as assembly, search, rescue, mapping, communication, aerial and other original applications

Purpose – The purpose of this paper is to review some of the various worldwide projects to develop and apply innovative swarm-type robots to many challenging applications. Design/methodology/approach – An in-depth review of published information and interviews with researchers and developers of swarm robot technology were conducted. Findings – Swarm robots continue to be developed to match an ever-increasing number of interesting and innovative applications. Practical implications – Readers may be very surprised at the tasks that autonomous swarm robots can address and the developments that are underway to further extend the abilities of swarm robots. Originality/value – This paper is a review of a wide range of the latest swarm robot developments, innovations and applications.
Large Scale Neurocognitive Networks Underlying Episodic Memory

Large-scale networks of brain regions are believed to mediate cognitive processes, including episodic memory. Analyses of regional differences in brain activity, measured by functional neuroimaging, have begun to identify putative components of these networks. To more fully characterize neurocognitive networks, however, it is necessary to use analytical methods that quantify neural network interactions. Here, we used positron emission tomography (PET) to measure brain activity during initial encoding and subsequent recognition of sentences and pictures. For each type of material, three recognition conditions were included which varied with respect to target density (0, 50, 100). Analysis of large-scale activity patterns identified a collection of foci whose activity distinguished the processing of sentences vs. pictures. A second pattern, which showed strong prefrontal cortex involvement, distinguished the type of cognitive process (encoding or retrieval). For both pictures and sentences, the manipulation of target density was associated with minor activation changes. Instead, it was found to relate to systematic changes of functional connections between material-specific regions and several other brain regions, including medial temporal, right prefrontal and parietal regions. These findings provide evidence for large-scale neural interactions between material-specific and process-specific neural substrates of episodic encoding and retrieval.