Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering Complex Regularities by Adaptive Self Organizing Classification

useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization. The tool is used to classify macroeconomic data that report the most developed countries' import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.
Discovering Complex Regularities : from Tree to SemiLattice Classifications

is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optimize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is able to automatically suggest a strategy to optimize the number of classes optimization, but also support both tree classifications and semi-lattice organizations of the classes to give to the users the possibility of passing from one class to the ones with which it has some aspects in common. Examples of using tree and semi-lattice classifications are given to illustrate advantages and problems. The tool is applied to classify macroeconomic data that report the most developed countries' import and export. It is possible to classify the countries based on their economic behaviour and use the tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation. Possible interrelationships between the classes and their meaning are also discussed.
Distribución y abundancia del cardenal amarillo (Gubernatrix cristata, Passeriformes: Thraupidae) en el sur de la provincia de Buenos Aires

The Yellow Cardinal ( Gubernatrix cristata ) is an endangered species distrib- uted mainly in the South American Espinal. In Buenos Aires province it is mainly distributed in the departments of Bahia Blanca, Puan, Villarino and Patagones. The knowledge about its current distribution, population status and habitat use is currently scarce. This work makes an approximation to the knowledge of the current status of the populations of the species in the south of Buenos Aires, contributing new data on its distribution, abundance and on forest use. We performed 303 independent extensive, unlimited, radio sampling points with the use of playback over 13 transects, totaling 1,183 km between 2015 and 2017, during 11 sampling campaigns. The percentage of forest cover was estimated at each point within 100 m radius. We obtained 19 records of a total of 48 individuals: 24 males, 17 females, and 7 undeterminated individuals. The 78,9 % of records and the 83,3 % of individuals were observed in the southern area. Forest cover was similar between sites with and without Yellow Cardinal records. The low records at the North and Centre areas could be due to the illegal capture of individuals, as long as the species has been abundant in the past, but not sought, otherwise the species may have always been scarce in these areas.
Performance evaluation of unified medical language system®’s synonyms expansion to query PubMed

Performance evaluation of Unified Medical Language System(R)'s synonyms expansion to query PubMed BMC Medical Informatics and Decision Making 2012, 12:12 doi:10.1186/1472-6947-12-12 Nicolas Griffon (nicolas.griffon@chu-rouen.fr) Wiem Chebil (wiem.chebil@yahoo.fr) Laetitia Rollin (laetitia.rollin@chu-rouen.fr) Gaetan Kerdelhue (gaetan.kerdelhue@chu-rouen.fr) Benoit Thirion (benoit.thirion@chu-rouen.fr) Jean-Francois Gehanno (jean-francois.gehanno@chu-rouen.fr) Stefan J Darmoni (stefan.darmoni@chu-rouen.fr)
Multilingual Learning as Parameter Co-occurrence Clustering

On this view, what does one know when one knows, say, English? A collection of mostly overlapping but different systems of communication (registers, dialects, others’ idiolects), perhaps acquired to different degrees, together with when to use them. A bilingual English-French speaker knows an even larger collection of this sort. ⇒ How are people able to acquire, and distinguish among, the member systems of these complex collections? I will present a strategy (class of algorithms) for modeling how this might be accomplished within a parameterized linguistic theory. Though the approach outlined here is applicable at any level of linguistic analysis (phonology, morphology, syntax, . . . ) and in any theory that has a notion of parameters (with some caveats), for purposes of concreteness and testing/evalution, we’ll be working within an optimality theoretic (OT; Prince & Smolensky, 1993) framework for syllable shape phonotactics. Outline of the talk:
Climate change modelling for the Pangani Basin to support the IWRM planning process

The report describes the best possible climate scenarios for the middle of the 21st century for the Pangani Basin, utilising a range of General Circulation Models (GCMs) and a state of the art statistical downscaling procedure. This should enhance understanding on the implications of future climate change on the water resources of the Basin for pragmatic planning.
Optimizing Predictive Mining Techniques in HIV-Related Opportunistic Infections: Case for Botswana

Botswana was one of the first countries to establish a national Antiretroviral therapy (ART) programme in Africa. “Masa,” a native word depicting “a new dawn,” is the programme name. The AIDS epidemic has led to the emergence of several disease entities which in the pre-AIDS era seemed innoxious. Some HIV AIDS positive patients under the ART programme continue to be at risk of contracting related Opportunistic Infections (OIs) and little evidence based research work has been carried out so as to apply preventative or mitigating factors. The use of Data Mining (DM) techniques is becoming more popular for investigating subtle relationships in Clinical data. This paper proposes to build a robust classification and prediction model by mining the historical data stored in a data-warehouse to determine which patients might be at risk of contracting the afore-mentioned infections. Four supervised learning algorithms viz Generalized Linear Model (GLM), Support Vector Machine (SVM), Decision Tree (DT) and Naive Bayes (NB) were used for building the models. Their performances were analyzed and evaluated for their efficacy against the Confusion Matrix analytical performance, the Receiver Operating Characteristic (ROC) curve, the LIFT Cumulative and Profit analysis. Experimental results proved that the SVM exhibited superior performance and was therefore deployed in building the HIV related OI prediction model.
ScienceDirect Product-Service Systems across Life Cycle Product-Service System ( PSS ) design : using Design Thinking and Business Analytics to improve PSS design

Companies searching for new ways to be competitive in dynamic markets are integrating product and service to better fulfill customer demands and improve sales. A well designed and efficiently developed Product-Service System (PSS) is a solid alternative to achieve this goal. The PSS design should search for new ways to add value for both company and customers. The PSS design model may help the company to innovate, strengthen competitiveness and assure the desired profit. In this paper we propose a methodology that integrates Design Thinking (DT) and Business Analytics (BA) in the PSS design in a way to build a profitable and lasting PSS. Design Thinking is a human-centered and systematic approach to problem solving and is used in the model to deeply understand customer needs and satisfy their emotional requirements considering company’s resources and constraints. BA is the capacity to aggregate, to analyze and to use data in a way to optimize the business results. The large quantity of information available from sensors, logs and other machine sources, associated with information and communication technologies (ICT) advances allow companies to collect and analyze a large quantity of data. Through the data analysis, companies may evaluate consumer behavior, sense changes in the market quickly and identify new opportunities to innovate. Furthermore, companies may use the data as a third layer to add value besides the product and service layers. The proposed model addresses a lack in the literature of PSS design and adds relevant information for companies designing or reconfiguring a PSS. © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 8th Product-Service Systems across Life Cycle.
Ultrasound-guided intraoral botulinum toxin injection into the lateral pterygoid muscle for chronic temporomandibular joint dislocation

Objectives Botulinum toxin type A (BTX), a powerful neurotoxin, can be an effective treatment choice for diverse muscular disorders and can reduce abnormal muscle activities. Abnormal movements of the mandible can be caused by involuntary and uncontrolled contractions of the lateral pterygoid muscle (LP) in various pathological situations. Previous reports have shown that BTX can reduce abnormal contractions of the LP. However, needle placement into the LP for BTX injection requires skill, experience, and sufficient anatomical knowledge. To place the needle precisely into the LP, ultrasonography (USG) can be used as an effective needle-guidance modality. USG is a non-invasive imaging modality able to create real-time images without any potential risks, including radiation exposure. Patients and Methods The patients who had been performed USG-guided BTX injection into the LP using an intraoral approach were included in this study with a literature review and case presentations. Using the USG, four patients received BTX injections to treat recurrent temporomandibular dislocation and oromandibular dystonia resulting from involuntary LP activity. Result Involuntary movements of the mandible were improved successfully in all patients, and showed satisfactory results without significant complication. Conclusion The intraoral approach could prevent potential complications during needle placement. USG-guided BTX injection is an effective, convenient, and safe method that provides real-time imaging without unnecessary pain to the patient.
Long-term change of DOM contents of shallow lake water in central Japan

Experiments on the microbial loop have shown that dissolved organic matter (DOM) is the main component o f soluble detritus. In the past, materials such as algal exudates, decomposed microbes, and animal excreta were believed to be the main sources of DOM. Now, many studies report DOM (WETZEL 2001), but information on changes in the composition DOM in relation with the dynamics of ecosystems is stilllimited. Long-term monitoring of DOM associated with the total lake condition is likely to provide important information for this research field. Lake Shibire is a fairly shallow lake in Yamanashi Prefecture, in central Japan. In this study, we report the results o f monitoring water quality and the analysis ofDOM over a period of 10 years. During the research period a major event occurred: the immigration of a nonindigenous fish, Micropterus sa/moides (largemouth bass). The effects ofthis event on DOM contents are also discussed in this paper.
Earthquake Interaction, Fault Structure, and Source Properties of a Small Sequence in 2017 near Truckee, California

We use relocation and source parameter analysis, including stress drop and directivity, to investigate fault structure and earthquake interaction of smallmagnitude earthquakes within a sequence in the Walker Lane tectonic region. Two high-angle, left-lateral strike-slip earthquakes (Mw 3.65 foreshock andMw 3.85 mainshock), occurred 7 min apart, ∼20 km north of Truckee, California, on 27 June 2017. Both events were felt over a wide area in northeastern California and northwestern Nevada and happened nearby Holocene fault zones including the Polaris, Mohawk Valley, and Dog Valley Quaternary fault zones that pose a significant hazard to the populated regions in the area. We use waveform cross correlation to relocate the earthquakes and empirical Green’s-function methods to estimate the source parameters of allML > 2 events. Also, we estimate the rupture directivity for the two largest events. We relocate 50 out of 52 earthquakes within the sequence, with an average relative error of < 30 m. The events define a single structure between 5 and 6 km depth, trending ∼N45°E and dipping ∼70°–80° to the northwest. The distribution of relocations matches the northeast-striking plane from both the moment tensor solutions and computed first-motion focal mechanisms, indicating sinistral strike-slip motion on a previously unmapped fault. We observe average stress drops of ∼5 MPa using P and S waves and spatial variation related to the rupture areas of the foreshock and mainshock. We are able to detect components of directivity toward the northeast for the foreshock (Mw 3.65) and directivity toward the southwest for the mainshock (Mw 3.85), both aligning with the fault plane. This analysis illustrates details in source properties and rupture propagation that can be derived with high-precision event locations within dense regional networks and provides more data and a better understanding as it relates to potential seismic hazard. Electronic Supplement: Figures of waveform fit, relocated earthquakes, example of stress drop, empirical Green’s function (EGF), bilateral rupture analysis, tables of stress-drop information, and event IDs.
Epoxidase inhibitor-aspirin resistance and the relationship with genetic polymorphisms: a review

Strokes are the leading cause of death in most regions of the world. Epoxidase inhibitors include the drug aspirin (acetylsalicylic acid). Aspirin is widely used as first-line treatment for the prevention of cardiovascular and cerebrovascular diseases in at-risk patients. However, patients using conventional doses of aspirin can still develop ischaemic cardiovascular and cerebrovascular diseases, a phenomenon known as aspirin resistance. The occurrence of aspirin resistance hinders the prevention and treatment of ischaemic cardiovascular and cerebrovascular diseases. There are many factors affecting aspirin resistance, such as sex, drug dose, metabolic disease, genetic polymorphisms, drug interactions and pharmacokinetics. Genetic polymorphism refers to the simultaneous and frequent presence of two or more discontinuous variants or genotypes or alleles in a population of organisms. Platelets contain a large number of highly polymorphic transmembrane glycoprotein receptors encoded by two or more isomeric alleles. Changes in gene polymorphisms in various pathways during platelet aggregation can lead to aspirin resistance. This narrative review describes the gene polymorphisms that have been demonstrated to be significantly associated with aspirin resistance. Research on the mechanisms of aspirin resistance and increased knowledge should provide accurate drug guidance in individuals that require first-line antiplatelet therapy.
Distinctive Seafloor Fabric Produced Near Western Versus Eastern Ridge‐Transform Intersections of the Northern Mid‐Atlantic Ridge: Possible Influence of Ridge Migration

Multibeam bathymetry compiled along fracture zones of the northern Atlantic reveals a striking morphological asymmetry. Seafloor fabric produced at western ridge‐transform intersections (RTIs) tends to consist of linear ridges, small in amplitude, and regularly spaced, and oceanic core complexes (OCCs) occur infrequently. In contrast, seafloor fabric produced at eastern RTIs is more irregular and blocky and displays characteristics usually associated with melt‐poor accretion: These include more than double the occurrence of OCCs as well as greater seafloor depths, even where seafloor is younger than that on the opposite side of the fracture zone. We propose that this asymmetry is a consequence of the westward migration of the Mid‐Atlantic Ridge. Such migration is expected to result in an enhanced melt supply at leading (western) RTIs compared to trailing (eastern) RTIs. The morphological asymmetry is observed for ridge offsets of ~40 to ~200 km, a range that may be related to the width of melting regimes that supply ridge segments. At slow spreading ridges, contrasting melt supplies across fracture zones may therefore be best expressed in the distinct seafloor fabrics preserved beyond the dynamically maintained relief of the axial rift valley and walls rather than in the contrasting axial depths documented for faster spreading ridges. Although OCCs appear to form preferentially at spreading rates lower than 30 mm/year, their common occurrence along the northern Mid‐Atlantic Ridge may also reflect the significantly higher rates at which it is migrating compared to the southern Mid‐Atlantic Ridge.
Gigaxonin Suppresses Epithelial-to-Mesenchymal Transition of Human Cancer Through Downregulation of Snail

Abstract Gigaxonin is an E3 ubiquitin ligase that plays a role in cytoskeletal stability. Its role in cancer is not yet clearly understood. Our previous studies of head and neck cancer had identified gigaxonin interacting with p16 for NFκB ubiquitination. To explore its role in cancer cell growth suppression, we analyzed normal and tumor DNA from cervical and head and neck cancers. There was a higher frequency of exon 8 SNP (c.1293 C>T, rs2608555) in the tumor (46% vs. 25% normal, P = 0.011) pointing to a relationship to cancer. Comparison of primary tumor with recurrence and metastasis did not reveal a statistical significance. Two cervical cancer cell lines, ME180 and HT3 harboring exon 8 SNP and showing T allele expression correlated with higher gigaxonin expression, reduced in vitro cell growth and enhanced cisplatin sensitivity in comparison with C allele expressing cancer cell lines. Loss of gigaxonin expression in ME180 cells through CRISPR-Cas9 or siRNA led to aggressive cancer cell growth including increased migration and Matrigel invasion. The in vitro cell growth phenotypes were reversed with re-expression of gigaxonin. Suppression of cell growth correlated with reduced Snail and increased e-cadherin expression. Mouse tail vein injection studies showed increased lung metastasis of cells with low gigaxonin expression and reduced metastasis with reexpression of gigaxonin. We have found an association between C allele expression and RNA instability and absence of multimeric protein formation. From our results, we conclude that gigaxonin expression is associated with suppression of epithelial–mesenchymal transition through inhibition of Snail. Significance: Our results suggest that GAN gene exon 8 SNP T allele expression correlates with higher gigaxonin expression and suppression of aggressive cancer cell growth. There is downregulation of Snail and upregulation of e-cadherin through NFκB ubiquitination. We hypothesize that exon 8 T allele and gigaxonin expression could serve as diagnostic markers of suppression of aggressive growth of head and neck cancer.
An Upstream G-Quadruplex DNA Structure Can Stimulate Gene Transcription

Four-stranded G-quadruplexes (G4s) are DNA secondary structures that can form in the human genome. G4 structures have been detected in gene promoters and are associated with transcriptionally active chromatin and the recruitment of transcription factors and chromatin remodelers. We adopted a controlled, synthetic biology approach to understand how G4s can influence transcription. We stably integrated G4-forming sequences into the promoter of a synthetic reporter gene and inserted these into the genome of human cells. The integrated G4 sequences were shown to fold into a G4 structure within a cellular genomic context. We demonstrate that G4 structure formation within a gene promoter stimulates transcription compared to the corresponding G4-negative control promoter in a way that is not dependent on primary sequence or inherent G-richness. Systematic variation in the stability of folded G4s showed that in this system, transcriptional levels increased with higher stability of the G4 structure. By creating and manipulating a chromosomally integrated synthetic promoter, we have shown that G4 structure formation in a defined gene promoter can cause gene transcription to increase, which aligns with earlier observational correlations reported in the literature linking G4s to active transcription.
Object Detection in Ground-Penetrating Radar Images Using a Deep Convolutional Neural Network and Image Set Preparation by Migration

Ground-penetrating radar allows the acquisition of many images for investigation of the pavement interior and shallow geological structures. Accordingly, an efficient methodology of detecting objects, such as pipes, reinforcing steel bars, and internal voids, in ground-penetrating radar images is an emerging technology. In this paper, we propose using a deep convolutional neural network to detect characteristic hyperbolic signatures from embedded objects. As a first step, we developed a migration-based method to collect many training data and created 53510 categorized images. We then examined the accuracy of the deep convolutional neural network in detecting the signatures. The accuracy of the classification was 0.945 (94.5%)–0.979 (97.9%) when using several thousands of training images and was much better than the accuracy of the conventional neural network approach. Our results demonstrate the effectiveness of the deep convolutional neural network in detecting characteristic events in ground-penetrating radar images.