iTrench: a study of user reactions to the use of information technology in field archaeology

This article describes work undertaken by the VERA project to investigate how archaeologists work with information technology (IT) on excavation sites. We used a diary study to research the usual patterns of behaviour of archaeologists digging the Silchester Roman town site during the summer of 2007. Although recording had previously been undertaken using pen and paper, during the 2007 season a part of the dig was dedicated to trials of IT and archaeologists used digital pens and paper and Nokia N800 handheld PDAs to record their work. The goal of the trial was to see whether it was possible to record data from the dig whilst still on site, rather than waiting until after the excavation to enter it into the Integrated Archaeological Database (IADB) and to determine whether the archaeologists found the new technology helpful. The digital pens were a success, however, the N800s were not successful given the extreme conditions on site. Our findings confirmed that it was important that technology should fit in well with the work being undertaken rather than being used for its own sake, and should respect established work flows. We also found that the quality of data being entered was a recurrent concern as was the reliability of the infrastructure and equipment.

Threshold-free object and ground point separation in LIDAR data

Light Detection And Ranging (LIDAR) is an important modality in terrain and land surveying for many environmental, engineering and civil applications. This paper presents the framework for a recently developed unsupervised classification algorithm called Skewness Balancing for object and ground point separation in airborne LIDAR data. The main advantages of the algorithm are threshold-freedom and independence from LIDAR data format and resolution, while preserving object and terrain details. The framework for Skewness Balancing has been built in this contribution with a prediction model in which unknown LIDAR tiles can be categorised as “hilly” or “moderate” terrains. Accuracy assessment of the model is carried out using cross-validation with an overall accuracy of 95%. An extension to the algorithm is developed to address the overclassification issue for hilly terrain. For moderate terrain, the results show that from the classified tiles detached objects (buildings and vegetation) and attached objects (bridges and motorway junctions) are separated from bare earth (ground, roads and yards) which makes Skewness Balancing ideal to be integrated into geographic information system (GIS) software packages.

An overview of the use of neural networks for data mining tasks

In the recent years, the area of data mining has been experiencing considerable demand for technologies that extract knowledge from large and complex data sources. There has been substantial commercial interest as well as active research in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from large datasets. Artificial neural networks (NNs) are popular biologically-inspired intelligent methodologies, whose classification, prediction, and pattern recognition capabilities have been utilized successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction, and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks. © 2012 Wiley Periodicals, Inc.

Higher Education: Understanding the impact of distance learning mode on user information assimilation and satisfaction

There is increasing pressure to capture of video within Higher Education. Although much research has looked at how communication technologies enhance information transfer during playback of video, consideration of technical issues seems incongruous if we do not consider how presentation mode affects information assimilated by, and satisfaction of, learners with a range of individual differences, and from a range of different backgrounds. This paper considers whether a relationship exists between the media and presentation mode used in recorded content, and the level of information assimilation and satisfaction perceived by learners with a range of individual differences. Results aim to inform learning practitioners whether generic delivery is justified, or whether tailoring content delivery enhances the experience of specific learner groups.

The effect of a single episode of antimicrobial photodynamic therapy in the treatment of experimental periodontitis. Microbiological profile and cytokine pattern in the dog mandible

The purpose of this study was to evaluate the effect of a single application of antimicrobial photodynamic therapy (aPDT) on microbiological profile and cytokine pattern in dogs. Periodontal disease was induced by placing 3.0 silk ligatures around the mandibular pre-molars bilaterally during 8 weeks. The dogs were randomly treated with aPDT using a dye/laser system, scaling and root planning (SRP), or with the association of treatments (SRP + aPDT). Plaque samples were collected at baseline, 1, 3, and 4 weeks, and the mean counts of 40 species were determined using DNA-DNA hybridization. Gingival biopsies were removed and the expression of tumor necrosis factor alpha (TNF-alpha), receptor activator of NF-kB ligand (RANKL), osteoprotegerin (OPG), matrix metalloproteinase (MMP-1), interleukin (IL) 6, IL-10 and total bacterial load by analysis of 16 S rRNA gene were evaluated through real-time PCR. The results shows that the levels of the majority of the species were reduced 1 week post-therapy for all treatments, however, an increase in counts of Prevotella intermedia (p = 0.00), Prevotella. nigrescens (p = 0.00) and Tannerella forsythia (p = 0.00) was observed for aPDT and SRP + aPDT. After 4 weeks, a regrowth of Porphyromonas gingivalis (p = 0.00) and Treponema denticola (p = 0.00), was observed for all treatments. Also, a strikingly reduction of counts on counts of Aggregatibacter actinomycetemcomitans was observed for the aPDT (p = 0.00). For the cytokine pattern, the results were similar for all treatments, and a reduction in the expression of cytokines and bacterial load was observed throughout the study. Our results suggest that SRP, aPDT in a single application, and SRP + aPDT affects different bacterial species and have similar effects on the expression of cytokines evaluated during the treatment of ligature-induced periodontitis.

Transdural motor cortex stimulation reverses neuropathic pain in rats: A profile of neuronal activation

Motor cortex stimulation (MCS) has been used to treat patients with neuropathic pain resistant to other therapeutic approaches; however, the mechanisms of pain control by MCS are still not clearly understood. We have demonstrated that MCS increases the nociceptive threshold of naive conscious rats, with opioid participation. In the present study, the effect of transdural MCS on neuropathic pain in rats subjected to chronic constriction injury of the sciatic nerve was investigated. In addition, the pattern of neuronal activation, evaluated by Fos and Zif268 immunolabel, was performed in the spinal cord and brain sites associated with the modulation of persistent pain. MCS reversed the mechanical hyperalgesia and allodynia induced by peripheral neuropathy. After stimulation, Fos immunoreactivity (Fos-IR) decreased in the dorsal horn of the spinal cord and in the ventral posterior lateral and medial nuclei of the thalamus, when compared to animals with neuropathic pain. Furthermore, the MCS increased the Fos-IR in the periaqueductal gray, the anterior cingulate cortex and the central and basolateral amygdaloid nuclei. Zif268 results were similar to those obtained for Fos, although no changes were observed for Zif268 in the anterior cingulate cortex and the central amygdaloid nucleus after MCS. The present findings suggest that MCS reverts neuropathic pain phenomena in rats, mimicking the effect observed in humans, through activation of the limbic and descending pain inhibitory systems. Further investigation of the mechanisms involved in this effect may contribute to the improvement of the clinical treatment of persistent pain. (c) 2010 European Federation of International Association for the Study of Pain Chapters. Published by Elsevier Ltd. All rights reserved.

Single Synapse Information Coding in Intraburst Spike Patterns of Central Pattern Generator Motor Neurons

Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

Assessing Threshold Concepts for Information Literacy

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Combining collaborative and content-based filtering to recommend research papers

The number of research papers available today is growing at a staggering rate, generating a huge amount of information that people cannot keep up with. According to a tendency indicated by the United States’ National Science Foundation, more than 10 million new papers will be published in the next 20 years. Because most of these papers will be available on the Web, this research focus on exploring issues on recommending research papers to users, in order to directly lead users to papers of their interest. Recommender systems are used to recommend items to users among a huge stream of available items, according to users’ interests. This research focuses on the two most prevalent techniques to date, namely Content-Based Filtering and Collaborative Filtering. The first explores the text of the paper itself, recommending items similar in content to the ones the user has rated in the past. The second explores the citation web existing among papers. As these two techniques have complementary advantages, we explored hybrid approaches to recommending research papers. We created standalone and hybrid versions of algorithms and evaluated them through both offline experiments on a database of 102,295 papers, and an online experiment with 110 users. Our results show that the two techniques can be successfully combined to recommend papers. The coverage is also increased at the level of 100% in the hybrid algorithms. In addition, we found that different algorithms are more suitable for recommending different kinds of papers. Finally, we verified that users’ research experience influences the way users perceive recommendations. In parallel, we found that there are no significant differences in recommending papers for users from different countries. However, our results showed that users’ interacting with a research paper Recommender Systems are much happier when the interface is presented in the user’s native language, regardless the language that the papers are written. Therefore, an interface should be tailored to the user’s mother language.

Information mining and visualization of data from the Brazilian Supreme Court (STF): a case study

EMAp - Escola de Matemática Aplicada

Perfil de beta talassemia heterozigota obtido a partir de análise data mining em banco de dados

Variations in the phenotypic expression of heterozygous beta thalassemia reflect the formation of different populations. To better understand the profile of heterozygous beta-thalassemia of the Brazilian population, we aimed at establishing parameters to direct the diagnosis of carriers and calculate the frequency from information stored in an electronic database. Using a Data Mining tool, we evaluated information on 10,960 blood samples deposited in a relational database. Over the years, improved diagnostic technology has facilitated the elucidation of suspected beta thalassemia heterozygote cases with an average frequency of 3.5% of referred cases. We also found that the Brazilian beta thalassemia trait has classic increases of Hb A2 and Hb F (60%), mainly caused by mutations in beta zero thalassemia, especially in the southeast of the country.

EthoSeq: A tool for phylogenetic analysis and data mining in behavioral sequences

This article introduces the software program called EthoSeq, which is designed to extract probabilistic behavioral sequences (tree-generated sequences, or TGSs) from observational data and to prepare a TGS-species matrix for phylogenetic analysis. The program uses Graph Theory algorithms to automatically detect behavioral patterns within the observational sessions. It includes filtering tools to adjust the search procedure to user-specified statistical needs. Preliminary analyses of data sets, such as grooming sequences in birds and foraging tactics in spiders, uncover a large number of TGSs which together yield single phylogenetic trees. An example of the use of the program is our analysis of felid grooming sequences, in which we have obtained 1,386 felid grooming TGSs for seven species, resulting in a single phylogeny. These results show that behavior is definitely useful in phylogenetic analysis. EthoSeq simplifies and automates such analyses, uncovers much of the hidden patterns of long behavioral sequences, and prepares this data for further analysis with standard phylogenetic programs. We hope it will encourage many empirical studies on the evolution of behavior.

Metacarpophalangeal pattern profile in Marfan syndrome and Marfan-like patients

Marfan syndrome (MFS) is an autosomal dominant trait due to mutations in the fibrillin gene (FBN1). The MFS expressivity is variable, and its diagnosis relies completely on clinical criteria. Atypical cases and Marfan- like (marfanoid) clinical presentations are commonly found. The metacarpophalangeal pattern profile (MCPP), a radiological method in which the 19 tubular hand bones are assessed, has been used in the diagnosis of various syndromes. To investigate whether the MCPP was adequate to discriminate between MFS and Marfan-like subjects, we studied 38 patients who were referred to our service because they had an MFS diagnosis, diagnostic hypothesis, or differential diagnosis or had arachnodactyly with dolichostenomelia. Two groups were formed: 1) MFS: 21 patients with a mean age of 18.3 (10.8 S.D.) years and 2) Marfan-like syndromes: 16 patients who did not meet the current criteria, with a mean age of 14.6 (4.6 S.D.) years. The MCPP was performed in each case following the classical technique, and a characteristic mean profile was obtained for group I (MFS), with Z scores ranging from 0.69 to 2.73 (1.80 ± 0.50; mean ± S.D.). In group I, three cases had no correlation with the typical MFS pattern. In group II, three cases had an MFS pattern. The correlation with the mean MCPP of MFS permitted the differential diagnosis of MFS and marfanoid syndromes with 86% sensitivity, 81% specificity, and 86% positive and 81% negative predictive values. The results suggest that MCPP can be used effectively as an auxiliary tool in the nosology of these conditions and, because there is no change in MCPP with age, can be helpful in early diagnosis.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.