Miracle-dz/UniFAR-FTUs huggingface dataset:
Dealing with food shortage: larval dispersal behaviour and survival on non-prey food of the hoverfly

1. Predatory larvae often have to face food shortages during their development, and thus the ability to disperse and find new feeding sites is crucial for survival. However, the dispersal capacity of predatory larvae, the host finding cues employed, and their use of alternative food sources are largely unknown. These aspects of the foraging behaviour of the aphidophagous hoverfly (Episyrphus balteatus De Geer) larvae were investigated in the present study. 2. It was shown that these hoverfly larvae do not leave a plant as long as there are aphids available, but that dispersing larvae are able to find other aphid colonies in the field. Dispersing hoverfly larvae accumulated on large aphid colonies, but did not distinguish between different pea aphid race–plant species combinations. Large aphid colonies might be easier to detect because of intensified searching by hoverfly larvae following the encounter of aphid cues like honeydew that accumulate around large colonies. 3. It was further shown that non-prey food, such as diluted honey or pollen, was insufficient for hoverfly larvae to gain weight, but prolonged the survival of the larvae compared with unfed individuals. As soon as larvae were switched back to an aphid diet, they rapidly gained weight and some pupated after a few days. Although pupation and adult hatching rates were strongly reduced compared with hoverflies continuously fed with aphids, the consumption of non-prey food most probably increases the probability that hoverfly larvae find an aphid colony and complete their development.
Measuring Narrative Fluency by Analyzing Dynamic Interaction Networks in Textual Narratives

This study aims to assess the ﬂuency of narratives in textual multimedia (e.g., news articles, academic publications, novels, etc.). We measure the narrative ﬂuency based on whether relationships between entities in the narrative (i.e., subjects and objects of events that compose the narrative) are consistently described with adequate rapidity. The relationships are represented by a dynamic interaction network (called ‘en-tity network’), which has entities as nodes and co-occurrences between the entities as edges. Lack of consistency makes users confused about what the textual narratives want to present. If a narrative consistently concentrates on a topic or subject, its entity network will have few entities with high node centrality. Using consistency of the high centrality entities, we assess the ﬂuency with three criteria: (i) consistency in each paragraph, (ii) consistency in the overall narrative, and (iii) consistency between the title and body. The rapidity of narrative development has to be appropriate for expected readers of the textual narratives. Too low rapidity causes redundancy, and high rapidity hinders the under-standability of the narratives. We assume structural changes in the entity network reﬂect the narrative rapidity. The structural change is measured by embedding structures of the entity network. Finally, we evaluated the e ↵ ectiveness of the proposed methods using the editorials of the New York Times and human evaluators.
Finding Frequent Subgraphs and Subpaths through Static and Dynamic Window Filtering Techniques

Big data era has large volumes of data generated at high velocity from different data sources. Finding frequent subgraphs from the graph streams can be a challenging task as streams are non-uniformly distributed and continuously processed. Its applications include finding strongly interacting groups in social networks and sensor networks. To find frequent subgraphs, we proposed static single-window technique and dynamic sliding window techniques. We also proposed enhancements by extending proposed static approach with its variations and extending dynamic approach in variations of incremental strategy to find frequent subgraphs. We also solved the sub problem to extract frequent subpaths from sequence of paths. Its applications include finding congested sections in traffic analysis. We applied our proposed static and dynamic techniques to extract the frequent subpaths from sequence of paths. We experimented the proposed dynamic and static approaches with real and benchmark datasets. Received on 17 February 2020; accepted on 09 April 2020; published on 16 April 2020
Hierarchical Dirichlet Process for Dual Sentiment Analysis with Two Sides of One Review

: Sentiment categorization is a fundamental process in sentiment examination, by means of it’s intended to categorize the sentiment into either positive or negative for given text. The wide-ranging perform in sentiment categorization follow the procedure in conventional topic-based text categorization, where the Bag-of-Words (BOW) is one of the most widely used methods in the recent work for the classification of text data in sentiment analysis. In the BOW method, an examination text is characterized by means of a vector of self-determining words. On the other hand, the performance of BOW occasionally leftovers restricted because of handling the polarity shift difficulty. To solve this problem in earlier introduce a new method named as Dual Sentiment Analysis (DSA) for classification of text data in Sentiment Analysis (SA). In DSA model, Logistic regression is second-hand for the binary classification difficulty. But in this DSA model some other categories of the sentiment classification such as intermediary and subjunctive reversed reviews are not maintained, to conquer this problem in this work proposed a new method called as Hierarchical Dirichlet Process (HDP) to modeling groups of text data based on the mixture components. Hybrid nested/ hierarchical Dirichlet processes (hNHDP), a prior with the intention of combine the advantageous aspects of together the HDP and the nested Dirichlet Process (NDP). Particularly, introduce a nested method to groups the original and reversed reviews. The results of the proposed hNHDP process demonstrate that best text classification results for sentiment analysis when compare to conventional text classification methods of DSA
Assessing the feasibility of estimating axon diameter using diffusion models and machine learning

Axon diameter estimation has been a focus of the diffusion MRI community for the past decade. The main argument has been that while diffusion models always overestimate the true axon diameter, their estimation still correlates with changes in true value. Until now, this remains more as a discussion point. The aim of this paper is to clarify this hypothesis using a recently acquired cat spinal cord data set, where the diffusion MRI signal of both a multi-shell and Ax-Caliber acquisition have been registered with the underlying histology values. We find that the axon diameter as estimated by signal models and AxCaliber does not correlate with their true sizes for axon diameters smaller than 3 µm. On the other hand, we also train a random forest machine learning algorithm to map signal-based features to histology values of axon diameter and volume fraction. The results show that, in this dataset, this approach leads to a more reliable estimation of physically relevant axon diameters than using sophisticated diffusion models.
SAM Centrality: a Hop-Based Centrality Measure for Ranking Users in Social Network

Majority of researcher are attracted by the social network analysis due to the rush of people towards social network. Along with many problems, social network analysis is facing an interesting problem that is ranking of users in social network which is gaining more attention due to the increasing number of social users. Measuring centrality of nodes in a social graph, have been important issue in social network analysis. Lot of centrality methods have been proposed in this regard. In this paper, hop based centrality measures called SAM is purposed. To investigate the measure, we applied on various dataset. In comparisons, on all these social graphs, we obtain better results than other centrality measures (i.e., Degree, PageRank, Betweeness and Closeness) using SIR model.
Statistical shape models based 2D/3D registration methods for knee orthopaedic surgery

In orthopaedic surgery, and in case of Total Knee Arthroplasty (TKA) for osteoarthritic subjects, planning of the intervention is of fundamental importance. The insertion of the prosthetic components is extremely delicate because the deformations induced by the osteophytes must be resected and at the same time the mechanical axis of the leg must be corrected. The size of the implant and the plane of resection are estimated through a standing X-ray projection that covers the whole leg. This view gives a hint on the direction of the mechanical axis that must be restored, but cannot evaluate how the kinematics of the knee is influenced by the insertion. The possibility to check the pre-operative kinematic of the knee under weight bearing conditions, in order to evaluate tension of the ligaments and the distance between the bones, would be of great importance for the success of the intervention, giving to the surgeon the possibility to check the bone’s motion before entering in the surgery room. This evaluation is currently intraoperatively performed by the surgeon, who performs passive movements of the joint to check the correct placement of the prosthetic components, although the conditions are not similar to the real stress applied during everyday life, as weight and muscles strengths are missing. The use of fluoroscopic sequences is common in clinics to rapidly evaluate the knee kinematics. These fast and low dose X-ray images allow an accurate visualization of the bone movements without the invasiveness typical of other methodologies. Knee motion analysis is cur-
Antioxidant and Anti-skin cancer potential of a Ketocarotenoid pigment Astaxanthin isolated from a green microalga Haematococcus pluvialis Flotow

Universally, astaxanthin is known for its powerful antioxidant potential which occurs naturally in various marine and fresh water organisms. Haematococcus pluvialis, a unicellular green microalga is one of the efficient producers of astaxanthin but comparatively in high concentration. The skin cancer is a major crisis coupled with direct exposure of radiations from the sunlight due to ozone depletion. Especially, in Australia two/third of the people has been diagnosed skin cancer below the age of 70. In this present study, the isolated pigment astaxanthin has been appraised for the antioxidant and anti-skin cancer potential. About 90% of astaxanthin was extracted from the enriched biomass of green alga Haematococcus pluvialis. The IC50 value of astaxanthin towards antioxidant and anticancer activity was found to be 39.1 ± 1.14 μg/ml and 63 ± 0.22 μg/ml respectively. The gene expression fold of caspase 3 was enhanced further for different time periods of 0, 6 and 12 hours during the treatment of astaxanthin with the skin cancer cells. While investigating the gene expression of oncogene Bcl-2 and tumor suppressor gene p53, the IC50 concentration of astaxanthin was found to suppress and induce both the genes respectively. Hence, it has been proven that astaxanthin can prevent the proliferation of skin cancer cells.
Capturing Experts' Mental Models to Organize a Collection of Haptic Devices: Affordances Outweigh Attributes

Humans rely on categories to mentally organize and understand sets of complex objects. One such set, haptic devices, has myriad technical attributes that affect user experience in complex ways. Seeking an effective navigation structure for a large online collection, we elicited expert mental categories for grounded force-feedback haptic devices: 18 experts (9 device creators, 9 interaction designers) reviewed, grouped, and described 75 devices according to their similarity in a custom card-sorting study. From the resulting quantitative and qualitative data, we identify prominent patterns of tagging versus binning, and we report 6 uber-attributes that the experts used to group the devices, favoring affordances over device specifications. Finally, we derive 7 device categories and 9 subcategories that reflect the imperfect yet semantic nature of the expert mental models. We visualize these device categories and similarities in the online haptic collection, and we offer insights for studying expert understanding of other human-centered technology.
Urinary tract infection among children and adolescents of Garhwal Region of Uttarakhand, India

Urinary tract comprises of kidney, ureter, urethra and genital organ and under normal circumstances these organs are sterile. Inflammation of these organ and parts may indicate the possibility of Urinary Tract Infection (UTI). It may be due to the colonization of wide range of bacteria either from normal microflora that is Escherichia coli or from other Gram negative or Gram positive bacteria. The present study was carried out to determine the prevalence of urinary tract infection in children and adolescents of hilly areas of Garhwal region of Uttarakhand, India. The sample collection was done from April 2013 to December 2013 from the Out Patient Department (OPD) and In Patient Department (IPD) of Hemvati Nandan Bahuguna Base Hospital, Srinagar Garhwal at an average height of 560 m (1837 ft) above sea level at foothills of Himalayas. Clean voided mid-stream urine samples were collected in sterile universal containers from 76 children of age group 0 to 10 years and 129 adolescents of age group 11 to 20 years. Bacterial counts greater than or equal to 1x10 5 CFU/mL in culture plates were taken as positive, which was an indication of UTI as introduced by Kass. Colony morphological characteristics were used for identification of bacterial isolation followed by Gram’s staining and biochemical tests. Our study showed a high prevalence of E. coli as the most dominant bacteria causing UTI in children and adolescents of hilly Garhwal region of Uttarakhand.
DIGITAL CARTOGRAPHY AND GIS, DECISION TOOLS FOR SUSTANAIBLE DEVELOPMENT IN THE PROVINCE OF CUENCA (CENTRAL SPAIN)

The Spanish High Council for Scientific Research and an association for rural development are promoting the implementation of the Local Agenda 21 which aims at reaching sustainable development in La Mancha Alta Conquense. A GIS has been produced to implement Local Agenda 21 which includes environmental and socioeconomic cartographic variables. Socio-economic variables from statistical sources were considered also on a municipal level. Sustainability indicators were obtained to provide a territorial diagnosis. The GIS produced is a valuable tool both to help spatial decision making on different management levels and to guide the Local Action Plan. Cartography is used as the tool to communicate this information to the local population in a double sense: showing the current situation of their territory and the proposals for territorial planning.
Poverty of Feminization: Factors and Survive Strategy of Poor Female Householder

This study aims to analyze the alleviation of rural poverty feminization, especially the poor female householder, but also analyzes the supporting and inhibiting factors within the Feminization of Poverty Alleviation of Jalin Matra Program in Tulusbesar Village, Tumpang District and Malang Regency, East Java Indonesia. This program launched by the Governor of East Java in 2014-2019 which aims to empower the poor society in East Java (Pergub Number 5 in 2018). Tulusbesar Village being the village with a number of Jalin Matra target Households in the Feminization of Poverty Program in 2016. The method used in this study is descriptive-qualitative, in which the basic data is taken with interviews while documents are the secondary data. There were 9 informants were poor Female Householder. The results showed that of the KRTP occurs because of four things, such as: divorce by death, parting from the prior husband due to incompatibility, disability husband or permanently sick husband so that he cannot provide for his family and got abandoned by the husband. The women empowerment at the Tulusbesar Village can be said to be successful due to the most of the KRTP beneficiaries of Jalin Matra succeed or could develop their business well, but still, need to be improved according to their potential and capabilities.
Enhancing the Quality of Sampled Phase-Only Hologram (SPOH) Based on Time-Division Comb Filtering

Generation of digital phase-only Fresnel holograms is an important research area in digital holography, as it leads to a substantial simplification of a holographic display system. However, the quality of the reconstructed image of a hologram without the magnitude component is heavily degraded. The problem can be reduced by down-sampling the intensity of an image prior to generating the hologram. The method, referred to as “sampled phase-only hologram” (SPOH) generation, results in reconstructed images that are masked with the pattern of the down-sampling lattice. This paper reports a novel, low complexity method to alleviate this problem through the concept of comb filtering. Results reveal prominent enhancement on the reconstructed image of a SPOH.
New computation methods in granular dynamics

: The dynamics of collections of bodies, treated as perfectly rigid, involves nonsmooth mathematical relations, arising from the unilaterality of impenetrability constraints, from the formulation of dry friction and from the velocity jumps produced by possible collisions. The presented numerical methods treat nonsmoothness without resorting to regularization procedures. The examples shown concern populations of balls contained is a vertically vibrated rectangular box. First, a comparison is made with some experiments pe1formed by other authors, about the paradoxical shape taken by the free surface when vibration is not strong enough to fluidize it. Other examples reveal an unexpected mechanism of size segregation.
opticskxi : OPTICS K-Xi Density-Based Clustering

Density-based clustering methods are well adapted to the clustering of high-dimensional data and enable the discovery of core groups of various shapes despite large amounts of noise. The opticskxi R package provides a novel density-based cluster extraction method, OPTICS k-Xi, and a framework to compare k-Xi models using distance-based metrics to investigate datasets with unknown number of clusters. This article ﬁrst introduces density-based algorithms with simulated datasets, then presents and evaluates the k-Xi cluster extraction method. Finally, the models comparison framework is described and experimented on 2 genetic datasets to identify groups and their discriminating features. The k-Xi algorithm is a novel OPTICS cluster extraction method that speciﬁes directly the number of clusters and does not require ﬁne-tuning of the steepness parameter as the OPTICS Xi method. Combined with a framework that compares models with varying parameters, the OPTICS k-Xi method can identify groups in noisy datasets with unknown number of clusters.
Finite Element Model of a Ferroelectric

Ferroelectric technology continues attracting significant interest due to its wide range of applications (capacitors, nonvolatile memories, accelerometers .). In this work we present a finite element model of a simple ferroelectric structure. Piezoelectric and ferroelectric matrices are included. The coupling between the piezoelectric and ferroelectric parameters will be introduced formally using a thermodynamic approach. Using the Comsol finite element nonlinear analysis, the ferroelectric loop (polarization versus electric field) and butterfly loop (strain versus electric field) in ferroelectric materials is obtained and discussed. The experimental results are compared to the finite element simulations
A Population-Based Study on the Prevalence and Risk Factors of Chronic Kidney Disease in the Adult Population of Shiraz, Southern Iran

Background: Currently, we are facing a significant increase in the new cases of the end-stage renal disease in developing countries. Hence, it seems vital to work on strategies aimed at reducing its development and progression. Determining the related risk factors can provide an insight into achieving these policymaking goals. Therefore, this study was conducted to identify risk factors associated with chronic kidney disease (CKD) in the Iranian adult population. Materials and Methods: This cross-sectional study was performed in Shiraz, Southern Iran, through a cluster random sampling technique that involved 819 subjects, including 340 male and 479 female adult participants. Factors such as the body mass index, waist circumference, blood pressure, and biochemical profile were determined. We evaluated the prevalence of CKD according to the glomerular filtration rate (GFR), as well as possible risk factors associated with it. GFR was calculated on the basis of the "Chronic Kidney Disease Epidemiology Collaboration" creatinine equation. Results: The cluster comprised 58.5% females and 41.5% males. The mean age of our participants was 43.0 ± 14.0 years. Our results showed that 16.6% of adult urban inhabitants in Iran had CKD (stages 3 to 5, eGFR ≤60), that is, GFR less than 60 mL/min/1.73 m2. The proportion of participants having hypertension, obesity, high waist circumference, diabetes mellitus, and history of cardiovascular disease was 17.3%, 19.3%, 35%, 9.4%, and 5.3%, respectively. Multiple regression analysis indicated an independent correlation between age, sex, dyslipidemia, and hypertension with CKD. Conclusion: This study indicates that CKD is a substantial health burden in Iranian adult population. Additionally, the results of this study addressed the importance of integrated strategies that aimed to identify, prevent, and treat noncommunicable diseases fueling the development of CKD.
A Novel Approach to Detect and Prevent Known and Unknown Attacks in Local Area Network

The most challenging task for organization in today’s world is to meet security needs. Various Intrusion detection and prevention techniques have been evolving for many years. This paper present a solution to combine signature based IDS along with honeypot. Our system has been developed in the LAN environment keeping in view the analysis of requirements of software engineering framework, design, implementation and testing. For IPS system, we deploy Signature based IDS (snort base) along with low interaction honeypot in order to detect and prevent known and unknown attacks. Moreover, By means of using different vulnerability scanners, our proposed model is able to make signature based IDS to learn the critical behavior of network attacks in more closer investigation which will in turn enhance the performance of our system with a less number of false positives and high detection rate.
Effect of Composition Variables on the UV Curing Behavior of Conductive Ink Formulations

Solvent-free UV-hardenable conductive ink formulations for printed microelectronics were designed to retain thermoplastic behavior after UV exposure. The binder system consists of a monofunctional liquid acrylate monomer along with an acrylic resin as viscosity modifier/ stabilizer for conductive particles. Conductive fillers used for this system were different types of silver particles in the micrometer and nanometer sizes. The kinetics of the photopolymerization and degree of conversion were studied by real time FTIR (RT-FTIR) and photo differential scanning calorimetry (photoDSC) experiments. Increasing silver particle concentration reduced the conversion of double bonds. Formulations containing silver nanoparticles had lower conversion than those with silver flakes. At higher filler loading, it was necessary to employ dual curing technique (UV followed by thermal) to get optimum conversion.