Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical Analysis of Density-based Spatial Clustering of Applications with Noise (DBSCAN) Techniques

Clustering is the most used technique in data mining. Clustering maximize the intra-cluster similarity and minimize the inter clusters similarity. DBSCAN is the basic density based clustering algorithm. Cluster is defined as regions of high density are separated from regions that are less dense. DBSCAN algorithm can discover clusters of arbitrary shapes and size in large spatial databases. Beside its popularity, DBSCAN has drawbacks that its worst time complexity reaches to O (n2). Similarly, it cannot deal with varied densities. It is hard to know the initial value of input parameters. In this study, we have studied and discussed some significant enhancement of DBSCAN algorithm to tackle with these problems. We analysed all the enhancements to computational time and output to the original DBSCAN. Majority of variations adopted hybrid techniques and use partitioning to overcome the limitations of DBSCAN algorithm. Some of which performs better and some have their own usefulness and characteristics.
Spectrum of β-thalassemia Mutations in Iran, an Update

β -thalassemia major ( β –TM) is the most common thalassemia severe phenotype among Iranians. In recent years, molecular understanding of pathogenesis of β –TM has provided a great opportunity regarding diagnostic issues. Creating comprehensive molecular databases provides highly sensitive diagnostic tools for β –TM and effective prenatal diagnosis (PND) molecular screening tests. Despite a large body of research on molecular basis of β –TM, there are few review papers that consider a general view on the distribution of β –TM mutations in Iran. In the current review, common genetic defects identified in Iranian β –TM patients since 2005 to 2014 have been described. In addition, the prevalences and distributional trends of recognized mutations were discussed. It was found that IVSII-1 (G>A) and IVSI-5 (G>C) were by far the most frequent mutations detected in Iranian patients. Other common reported mutations included FSC 8/9 (+G), IVS I-110 (G>A), FSC 36/37 (– T), IVSI-1 (G>A), IVSI (-25bp), and codon 44 (-C). In conclusion, it was found that molecular profile of β –TM is highly variable among different Iranian populations; in particular, it seems that ethnicity and intra-migration can be most important participating
Spinal fractures as an indicator of concurrent other system injuries: An analysis of 242 cases

Introduction: The aim of the present study was to examine any non spinal tissue injuries accompanying spinal fractures in an attempt to determine if spinal fractures are an indicator of the presence, severity, and prognosis of concomitant organ/tissue injuries in two trauma center in Turkey. Methods: This study had a retrospective cross-sectional design that incorporated the information of the patients presenting to the emergency services of two level 1 trauma centres in the Central Anatolian Region of Turkey between January 2010 and December 2012. Among 242 spinal fracture patients, 98 (41.9%) had accompanying injuries in other regions. Results There was a statistically significant correlation between the accompanying injuries and the single Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation level spinal fractures, the anatomical localization of the spinal fracture (p=0.012, p=0.048). Accompanying injuries associated with Lumbar Spinal Associated Injury (LSAI) were the most common (n=54, 55%) while Servical Spinal Associated Injury (SSAI) were the least common (n=7, 7.14%). Conclusion: Every patient presenting to emergency department after a high-energy trauma should be regarded as vertebral fracture sunless proven otherwise, and any spine fractures should be taken serious with regard to potential internal organ injuries.
Formulation and evaluation of glipizide-loaded fast-dissolving tablets using husk of Plantago ovata as a superdisintegrant

The objective of the present study was to develop fast-dissolving tablets (FDTs) of glipizide, a sulfonylurea antidiabetic drug. The husk of Plantago ovata and pregelatinized husk of P. ovata were used as disintegrating agents. Microcrystalline cellulose was used as binder and starch (soluble) was used as bulk-forming agent. The powder blends were evaluated for angle of repose, compressibility index and Hausner ratio. The results of angle of repose, compressibility index (%) and Hausner ratio ranged from 24.23±0.57 to 29.34±0.78, 15.76±0.82 to 20.12±1.25 and 1.18±0.011 to 1.25±0.019, respectively. The tablet blends were converted into tablets by using direct compression method. The tablets were evaluated for disintegration test, hardness test, friability test, drug entrapment efficiency, content uniformity tests and drug release study. Formulations, which contained pregelatinized husk of P. ovata as a superdisintegrant, showed faster disintegration, higher percentage friability and lesser hardness than formulations containing husk of P. ovata as a superdisintegrant. Drug entrapment efficiency was found to be uniform among different batches of the tablets and ranged from 97.53±0.52 to 99.72±0.45. The results of content uniformity test of all the batches were found in the official range.The batches containing husk of P. ovata as a superdisintegrant released 15%–27% of glipizide per minute and those containing pregelatinized husk of P. ovata as a superdisintegrant released more than 95% of the drug within a minute.These results revealed that pregelatinized husk of P. ovata can be used as a superdisintegrant for obtaining FDTs.
Stacking order, interaction, and weak surface magnetism in layered graphene sheets

Recent transport experiments have demonstrated that rhombohedral-stacking trilayer graphene is an insulator with an intrinsic gap of 6 meV and Bernal-stacking trilayer graphene is a metal. We propose a Hubbard model with a moderate $U$ for layered graphene sheets, and show that the model well explains the experiments on the stacking-dependent energy gap. The moderate on-site Coulomb repulsion drives the metallic phase of the noninteracting system to a weak surface antiferromagnetic insulator for the rhombohedral stacking layers, while the interaction-opened energy gaps for the Bernal stacking layers are much smaller.
Segmentation des Coupes Histologiques Osseuses Par la Ligne de Partage des Eaux

Resume: La coupe histologique osseuse est une lame qui presente la structure interne de l`os a l`echelle microscopique. Le screening (etape de lecture d’une lame) est une activite humaine manuelle subjective en cytologie. Un systeme informatique semi-automatique pourrait contribuer a la detection des erreurs de screening grâce a une meilleure fiabilite. La maladie de l’osteoporose peut etre predite a partir des caracteristiques histologiques des coupes osseuses. L’objectif de la segmentation des images numerises des coupes histologiques osseuses est d’isoler le reseau trabeculaire de l’espace medullaire. Nous presentons dans ce papier une nouvelle strategie de segmentation basee sur l’utilisation de la ligne de partage des eaux contrainte par marqueurs. Ces travaux ont ete realises en collaboration avec la faculte de medecine de Sfax. La quantification transforme la coupe histologique a traiter en un ensemble de parametres numeriques qui resument les caracteristiquement de constitution du reseau trabeculaire.
WORD RECOGNITION IN INDIC SCRIPTS

Optical Character Recognition (OCR) problems are often formulated as isolated character (symbol) classification task followed by a post-classification stage (which contains modules like UNICODE generation, error correction etc. ) to generate the textual representation, for most of the Indian scripts. Such approaches are prone to failures due to (i) difficulties in designing reliable word-to-symbol segmentation module that can robustly work in presence of degraded (cut/fused) images and (ii) converting the outputs of the classifiers to a valid sequence of UNICODES. In this work, we look at two important aspects of word recognition – word image to text string conversion and error detection and correction in words represented as UNICODES. In this thesis, we propose a formulation, where the expectations on the two critical modules of a traditional OCR (i.e, segmentation and isolated character recognition) is minimized. And the harder recognition task is modelled as learning of an appropriate sequence to sequence transcription scheme. We thus formulate the recognition as a direct transcription problem. Given many examples of feature sequences and their corresponding UNICODE representations, our objective is to learn a mapping which can convert a word directly into a UNICODE sequence. This formulation has multiple practical advantages: (i) This reduces the number of classes significantly for the Indian scripts. (ii) It removes the need for a word-to-symbol segmentation. (ii) It does not require strong annotation of symbols to design the classifiers, and (iii) It directly generates a valid sequence of UNICODES. We test our method on more than 5000 pages of printed documents for multiple languages. We design a script independent, segmentation free architecture which works well for 7 Indian scripts. Our method is compared against other state-of-the-art OCR systems and evaluated using a large corpora. Second contribution of this thesis is in investigating the possibility of error detection and correction in highly inflectional languages. We take Malayalam and Telugu as the examples. Error detection in OCR output using dictionaries and statistical language models (SLMs) have become common practice for some time now, while designing post-processors. Multiple strategies have been used successfully in English to achieve this. However, this has not yet translated towards improving error detection performance in many inflectional languages, especially In-
Towards an Understanding of Fake News

Fake news articles are intentionally fabricated to be deceptive and can be proven that they are false. Fake news and spread of misinformation are important concepts which may have serious real world consequences. Even though this concept exists for so many years, with the advancements in technology the speed of di usion of misinformation and, how people consume and produce news has changed a lot. So the e ort towards detecting fake news quickly and correctly has became a challenge. Today most of the fact checking is done by professional journalists but the research towards the automatic detection of fake news increases rapidly. For automatic detection of fake news, linguistic and machine learning techniques are the most frequently used techniques. In this paper, we analyze these techniques in three main groups: Content based methods, user based methods and network based methods. We also give a short introduction to the concepts and present some preliminary research results towards an understanding of fake news. It was not so long ago that the term fake news started to appear frequently in the media. Even though the terms like deception, hoax, clickbait and credibility detection of news articles are within the focus of researchers for some time, with the frequent use of the term fake news , a new de tion and more speci c work towards detecting it was required. Even though the term fake news is quite new, there was always some newspapers trying to take more attention from the readers through exaggerated headlines and articles containing misinformation [7] [1]. In the internet era, where every individual have an opportunity to publish and be visible by many others, it is not surprising that the generation of fake news has increased. One of the main reasons of generating fake news is the economic gain which can be acquired by getting more clicks or generating paid fake content [5] for parties who want to get more clicks. Fake news can cause sudden changes in stock market and this can easily be converted to an economic gain by the parties who published the fake news articles [2]. Another common reason for generating fake news is trying to create a deception and/or a political bias within users in order to get more supporters. On the other hand where to draw the line between fake news and expression of opinions is important. Copyright held by the author(s). NOBIDS 2017
A component-based approach to study the effect of Indian music on emotions

The emotional impact of Indian music on human listeners has been studied mainly with respect to ragas. Although this approach aligns with the traditional and musicological views, some studies show that raga-speciﬁc effects may not be consistent. In this paper, we propose an alternative method of study based on the components of Indian Classical Music, which may be viewed as consisting of constant-pitch notes (CPNs) provid-ing the context, and transients, the detail. One hundred concert pieces in four ragas each in Carnatic music (CM) and Hindustani music (HM) are analyzed to show that the transients are, on average, longer than CPNs. Further, the deﬁned scale of the raga is not always mirrored in the CPNs for CM. We also draw upon the result that CPNs and transients scale non-uniformly when changing the tempo of CM pieces. Based on the observations and previous results on the emotional impact of the major and minor scales in Western music, we propose that the effect of CPNs and transients should be analyzed separately. We present a preliminary experiment that brings outs related challenges.
ICLR 2019 D 2 KE : From Distance to Kernel and Embedding via Random Features For Structured Inputs

We present a new methodology that constructs a family of positive definite kernels from any given dissimilarity measure on structured inputs whose elements are either real-valued time series or discrete structures such as strings, histograms, and graphs. Our approach, which we call D2KE (from Distance to Kernel and Embedding), draws from the literature of Random Features. However, instead of deriving random feature maps from a user-defined kernel to approximate kernel machines, we build a kernel from a random feature map, that we specify given the distance measure. We further propose use of a finite number of random objects to produce a random feature embedding of each instance. We provide a theoretical analysis showing that D2KE enjoys better generalizability than universal Nearest-Neighbor estimates. On one hand, D2KE subsumes the widely-used representative-set method as a special case, and relates to the well-known distance substitution kernel in a limiting case. On the other hand, D2KE generalizes existing Random Features methods applicable only to vector input representations to complex structured inputs of variable sizes. We conduct classification experiments over such disparate domains as time series, strings, and histograms (for texts and images), for which our proposed framework compares favorably to existing distance-based learning methods in terms of both testing accuracy and computational time.
Intra-abdominal reactive lymphadenopathy developing 5 years after endoscopic submucosal dissection for early gastric cancer

A 73-year-old man presented with an enlarged intraperitoneal lymph node. In 2003, endoscopic submucosal dissection had been performed for an early gastric cancer that complied with current guidelines for endoscopic treatment. The lesion was completely resected en bloc, curative endoscopic submucosal dissection. The patient was followed up on an outpatient basis, with no evidence of metastasis or recurrence. In November 2008, abdominal ultrasonography during a medical check-up showed an enlarged lymph node, about 20 mm in diameter. Computed tomography and positron emission tomography showed no contrast effects or abnormal accumulations of tracer in the affected region, but malignancy could not be ruled out. In August 2009, laparoscopic intra-abdominal lymphadenectomy was performed. Histopathological examination revealed no atypical cells, and reactive lymphadenopathy was diagnosed. The patient was followed up on an outpatient basis and currently remains well, with no recurrence.
Variation in Anatomical Characteristics of Bamboo, Bambusa rigida

The culms of bamboo Bambusa rigida ranging from 1, 3 and 5 year old were obtained and investigated for anatomical characteristics in different ages, heights and zones in radial direction of culm wall thickness. The vascular bundles were denser and smaller at the top portion and outer zone of all age groups. No significant differences in vascular bundle frequency and size were found among the tree age groups. Metaxylem vessels did not vary significantly among ages. Fibre and parenchyma were longer in the middle portion of the height and middle zone in radial direction of culms wall. No significant differences in fibre and parenchyma length were observed in all age groups. The wall thicknesses of fibre and parenchyma were thicker in the top portion and outer zone. Furthermore, the wall thicknesses of fibre and parenchyma increased significantly from 1 to 3 year, showing that there is a maturing progress from 1 to 3 year.
Metabolites in the milk of buffalo, Holstein cross, indigenous and Red Chittagong cattle of Bangladesh

PKSF, Agargaon, Dhaka, Bangladesh Low molecular weight chemical compounds or intermediate products of a metabolism or other cellular processes are called metabolites. The objective of the present study was to investigate the variations in the metabolite concentration in the milk from crossbred water Buffalo (B), Holstein cross (H), Indigenous cattle (I) and Red Chittagong Cattle (R) and the relationships among those metabolites. The concentration of citric acid, α -keto glutaric acid (α-keto GA), orotic acid, pyruvic acid, succinic acid, lactic acid, formic acid, uric acid and propionic acid were measured by using High Performance Liquid Chromatography. Pooled milk samples of nine B, fifteen I and twenty R cows were collected from the research farm of Bangladesh Livestock Research Institute, Savar, Dhaka, Bangladesh. The pooled milk samples of H were collected from twenty five cows of Central Cattle Breeding Station and Dairy Farm, Savar, Dhaka, Bangladesh. All the sampling was done from the morning milking. The samples were preserved by adding ‘bronopol tablet’ and frozen and stored at -20 °C. Except propionic acid, all the metabolites varied significantly (p<0.01) among the milk types and B milk had lowest concentration of them. The highest concentration of citric acid (ppm) was 2245.50±39.90 in I milk followed by 2156.60±26.60 in R, 1858.30±8.70 in H and 1366.70±33.70 in B milk. The H, I and R milk were found similar in their α-keto GA content. Similarities were also found for succinic acid between H and R milk and so for H and I milk in uric acid content. Highest formic acid was found in H milk (392.78±2.23 ppm) and the lowest was 308.91±3.75 ppm in R milk while B and I milk was found similar. The lowest concentration of uric acid was found 0.44±0.26 ppm in B milk and R milk had the highest content (11.38±1.10 ppm). Pyruvic, formic and propionic acids showed no significant relationship among them and with others as well. The most highly significant (p<0.01) correlation was found between orotic and α-keto GA (r=0.915) and between uric and succinic acid (r=0.914). So, the metabolites showed a considerable variation in their concentration in different types of milk and also some of the parameters showed significant relationship among them.
A third cluster of red supergiants in the vicinity of the massive cluster RSGC3

This research is partially supported by the Spanish Ministerio de Ciencia e Innovacion (MCINN) under AYA2010-21697-C05-5 and the Consolider-Ingenio 2010 programme grant CSD2006-00070: First Science with the GTC (http://www.iac.es/consolider-ingenio-gtc).
ASYMPTOTIC BEHAVIOUR OF ARITHMETICALLY

This paper addresses problems on arithmetic Macaulayfications of projective schemes. We give a surprising complete answer to a question poised by Cutkosky and Herzog. Let Y be the blow-up of a projective scheme X = Proj R along the ideal sheaf of I ⊂ R. It is known that there are embeddings Y ∼= Proj k[(I)c] for c ≥ d(I)e + 1, where d(I) denotes the maximal generating degree of I, and that there exists a Cohen-Macaulay ring of the form k[(I)c] (which gives an arithmetic Macaulayfication of X) if and only if H(Y,OY ) = k, H(Y,OY ) = 0 for i = 1, . , dim Y − 1, and Y is equidimensional and Cohen-Macaulay. We show that under these conditions, there are well-determined invariants ε and e0 such that k[(I)c] is Cohen-Macaulay for all c > d(I)e + ε and e > e0, and that these bounds are the best possible. We also investigate the existence of a Cohen-Macaulay Rees algebra of the form R[(I)ct]. If R has negative a∗-invariant, we prove that such a CohenMacaulay Rees algebra exists if and only if π∗OY = OX , Rπ∗OY = 0 for i > 0, and Y is equidimensional and Cohen-Macaulay. Moreover, these conditions imply the Cohen-Macaulayness of R[(I)ct] for all c > d(I)e + ε and e > e0.
Gestión del Conocimiento Abierto

ha denominado “Datos Abiertos”, la cual consiste en poner a disposición de la sociedad los datos de interés común de la ciudadanía para que de cualquier manera, estos puedan desarrollar una nueva idea o aplicación que entregue nuevos datos, conocimientos u servicios que el gobierno no es capaz de entregar. El uso del conocimiento para una mejora de las estructuras organizativas y sociales ha dado lugar a un gran abanico de herramientas tecnológicas cuya finalidad es soportar estas estructuras y facilitar los flujos de conocimiento entre los agentes que las componen. Esta línea de investigación aborda el tema de “Gestión del Conocimiento Abierto” en las organizaciones para gestionar en forma eficaz el conocimiento. Es también de gran importancia en las instituciones educativas tener y potenciar buenos sistemas de gestión del conocimiento abiertos a la innovación y la actualización continua, que cuenten con la participación activa de todos sus miembros, para lo cual es clave el uso común de los nuevos medios sociales digitales.
KNOWLEDGE FORMS OF ENTERPRISE AND THE RESEARCH OF ITS IDENTIFICATION AND DISTRIBUTION

Knowledge has been a kind of important factor in enterprise, the status of knowledge is the same as resource and manpower under knowledge economy. To enterprise, knowledge is very abstract, in order to make use of knowledge, we should know the basic forms of knowledge firstly, then we can identify the knowledge and know its distribution rule. The knowledge is surveyed on the base of summarizing knowledge concept in the thesis, and its rules of identification and distribution is also given.
A Model of Sympatric Speciation Through Reinforcement

Sympatric speciation, i.e. the evolutionary split of one species into two in the same environment, has been a highly troublesome concept. It has been a questioned if it is actually possible. Even though there have been a number of reported results both in the wild and from controlled experiments in laboratories, those findings are both hard to get and hard to analyze, or even repeat. In the current study we propose a mathematical model which addresses the question of sympatric speciation and the evolution of reinforcement. Our aim has been to capture some of the essential features such as: phenotype, resources, competition, heritage, mutation, and reinforcement, in as simple a way as possible. Still, the resulting model is not too easy to grasp with purely analytical tools, so we have also complemented those studies with stochastic simulations. We present a few results that both illustrates the usefulness of such a model, but also rises new biological questions about sympatric speciation and reinforcement in particular.