Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of Genetic Relationships and Pathogenicity of Oral Candidiasis Etiological Agents in Pediatric Malignant Patients in Basrah Province, Iraq

The incidence of yeast infections increased coinciding with the medical advancement and rising of the immunocompromised patients community. Few studies were conducted to identify the pathogenic agents that caused oral infections in the pediatric cancer patient in Iraq. This study was designed to identify pathogenic yeasts causing oral infections in the pediatric cancer patients and evaluate the genetic relationship among isolates by constructing the phylogenetic tree. The capacity of isolates to express two important virulence factors (biofilm formation and hydrolytic enzymes, proteinase and phospholipase) was investigated. To achieve these goals, 24 swab samples were obtained from patients and identified by both conventional and advance methods. The majority of isolates were Candida albicans, while Candida non-albicans was minor. The identified isolates of Candida non-albicans were classified as C. dubliniensis, C. glabrata, and C. tropical, in addition to Rhodotorula mucilaginosa, and Kluyveromyces marxianus respectively by analyzing the sequences of ITS regions. R. mucilaginosa was enrolled for the first time in Iraq by sequencing ITS region. The phylogenetic tree was constructed by Maximum Likelihood (ML) analyses, isolates were categories into five clusters comparing with reference strains and public database. The results found that the majority of isolates produced enzymes and formed biofilm strongly. In conclusion, identification of etiological agents employing comparison between ITS region sequence and public database was a simple, precise and accurate method.
Tissue-Emulating Phantoms for In Vitro Experimentation at Radio Frequencies: Exploring characteristics, fabrication, and testing methods

This article provides one of the first comprehensive reviews of tissue-emulating phantoms available for the in vitro experimentation of radio-frequency (RF) antennas and other electromagnetic (EM) components. Diverse recipes and formulation approaches are available in the literature for such phantoms, but a holistic overview has yet to be reported. We review RF phantoms based on their textures (i.e., liquid, semisolid, and solid) and briefly discuss the use of readily available animal tissues for in vitro experimentation. For each phantom group, we present an overview of the various recipes and fabrication methods, specify the operating frequency range and tissue(s) they emulate, discuss the associated benefits and challenges, and summarize the wireless applications for which they have been employed to date. Further, we review various methods available in the literature to measure the electrical and thermal properties of RF phantoms as required to verify their tissue-emulating capabilities. This review creates a comprehensive resource for ongoing and future studies in the field and is intended to stimulate future research in the development of tissue-emulating phantoms and wireless RF components operating in, on, or near the body.
Study on the chemical constituents of chlorogenic acids from the dried leaves of Lonicera similis Hemsl.

[Objective] To study the chemical constituents in the dried leaves of Lonicera similis Hemsl. , so as to provide guidance for its further utilization and finding out new active substance. [Method] Chlorogenic acids were isolated and purified by solvent extraction and column chromatographic methods, and then identified by various spectroscopic methods. [Result] Six compounds were isolated from the dried leaves of Lonicera similis Hemsl. , including chlorogenic acid (I), chlorogenic acid methyl ester (II), chlorogenic acid ethyl ester (III), 5-caffeoyl-1, 3-quinide (IV), methyl 3, 4-di-O-caffeoyl quinate (V) and methyl 3, 5-di-O-caffeoyl quinate (VI). [Conclusion] Apart from the chlorogenic acids, other compounds were extracted from this plant for the first time.
The Resilience of the Socially Responsible Investment Networks

A network model is introduced and developed to compare portfolios of funds which are high ranked in Environmental Social and Governance (ESG) aspects with those with a poor ESG compliance. The nodes in the network represent funds and the edges are weighted on the basis of the capitalization due to the common components of the connected nodes. We specifically deal with the reactions of the considered financial networks to exogenous shocks of negative financial nature. To this aim, we provide a novel definition of the resilience of a financial network in terms of stability of its community structure. We test the theoretical proposal on different networks characterized by different ESG scores. We find that the high ranked funds networks are more resilient than the corresponding networks of low ranked funds.
Insecticide Treated Net usage among under-five Children in South-West Nigeria

Relevance of Insecticide Treated Nets (ITNs) in reducing the malaria scourge among most vulnerable groups has been reported. This study uses data from 2018 Nigeria Demographic Health Survey (NDHS) to assess utilization among under-five children in South-West of Nigeria, a region with lowest utilization in the country. The study aims at assessing effect of some covariates on utilization of ITNs among children under the age of five in South-West Nigeria. Binary logistic regression is used to assess effect of covariates on response variable and the chi-square test is used to assess dependency of some socio-demographic factors. All factors considered are significant to the response variable except the gender of the child. Utilization is mostly limited because of heat generated by the net and the irritating effects of usage. Rural dwellers are found to have an insignificant higher odds of sleeping under ITN compared to those in urban areas. Lagos state has the lowest utilization rate among states in the region while Ekiti has the highest. Children with fever two weeks preceding the survey have higher odds of sleeping under ITN. Utilization is highest among the poorest with odds of usage more than six times higher than those in richest wealth index category. For any intervention programme especially among the under-five children, identifying most important areas that will maximize efficiency and effectiveness of usually insufficient resources is very crucial. Attempts are to be made in educating caregivers on importance of utilizing ITN rather than the usual ownership sensitization. Keywords: Insecticide treated nets; under five children; binary logistic regression, Malaria, South-West Nigeria.
StyleGuide: Zero-Shot Sketch-Based Image Retrieval Using Style-Guided Image Generation

The goal of zero-shot sketch-based image retrieval is to retrieve relevant images from a search set against a hand-drawn sketch query, which belongs to a class, previously unseen by the model. The knowledge gap between such unseen and seen classes along with the domain-gap between the query and search-set makes the problem extremely challenging. In this work, we address this problem by proposing a novel retrieval methodology, StyleGuide using style-guided fake-image generation. In addition, we further study the scenario of generalized zero-shot sketch-based image retrieval, where the search set contains images from both seen and unseen categories. Specifically, we propose a detection approach for unseen class samples in the search-set, based on pre-computed seen class-prototypes, to obtain a refined search-set for a particular unseen-class query. Thus, the query sketch needs to be compared only to those image data which are more likely to belong to the unseen classes, resulting in improved retrieval performance. Extensive experiments on two large-scale sketch-image datasets, Sketchy extended and TU-Berlin show that the proposed approach performs better or comparable to the state-of-the-art for ZS-SBIR and gives significant improvements over the state-of-the-art for generalized ZS-SBIR.
Tracer experiments in a non-uniform porous medium : implications of diffusive mass transfer on the late-time breakthrough behavior

approved: Roy Haggerty Mass transfer processes were evaluated in an artificial, non-uniform porous medium with a power law distribution of diffusion rate coefficients obtained from physical characterization of solute and porous medium. Breakthrough curves of several pulse experiments conducted at different velocities were compared (1) to analytical expressions for concentrations at mass transfer dominated times, and (2) to simulated breakthrough curves of a 1-D transport model. After correcting diffusion rate coefficients for irregularly shaped particles both analytical and numerical model were able to accurately represent breakthrough curves and latetime concentrations. The main conclusions of this study are the following. First, by connecting normalized breakthrough curves of experiments conducted at different velocities it is possible to obtain the derivative of the residence time distribution of the immobile domain, which completely describes the mass transfer behavior of the column. From the derivative of the residence time distribution, the scaling behavior of mass transfer dominated breakthrough curves can be predicted. Second, in presence of multiple rates of mass transfer the use of a single rate model may lead to velocity-dependent mass transfer rate coefficients. Third, a power law distribution of diffusion rate coefficients is directly related to the late-time slope of breakthrough curves, and, if pore diffusivity is constant for all particles of the porous medium, also to the distribution of grain sizes.
Brain Tumor Identification and Classification of MRI images using deep learning techniques

The detection, segmentation, and extraction from Magnetic Resonance Imaging (MRI) images of contaminated tumor areas are significant concerns; however, a repetitive and extensive task executed by radiologists or clinical experts relies on their expertise. Image processing concepts can imagine the various anatomical structure of the human organ. Detection of human brain abnormal structures by basic imaging techniques is challenging. In this paper, a Fully Automatic Heterogeneous Segmentation using Support Vector Machine (FAHS-SVM) has been proposed for brain tumor segmentation based on deep learning techniques. The present work proposes the separation of the whole cerebral venous system into MRI imaging with the addition of a new, fully automatic algorithm based on structural, morphological, and relaxometry details. The segmenting function is distinguished by a high level of uniformity between anatomy and the neighboring brain tissue. ELM is a type of learning algorithm consisting of one or more layers of hidden nodes. Such networks are used in various areas, including regression and classification. In brain MRI images, the probabilistic neural network classification system has been utilized for training and checking the accuracy of tumor detection in images. The numerical results show almost 98.51% accuracy in detecting abnormal and normal tissue from brain Magnetic Resonance images that demonstrate the efficiency of the system suggested.
Determination of Body Image, Self-Esteem and Depression States among Patients with Gynecological Cancer

METHODS The sample of the study consisted of 76 Turkish patients who had gynecological cancer. The Patient Information Form, Body Image Scale (BIS), Rosenberg Self-Esteem Scale (RSES) and Beck Depression Inventory (BDI) were used to collect data in this study. The independent-samples t-test, one-way ANOVA test, Tukey and tamhane’s t2 multiple comparison tests, and Pearson correlation analysis were used for the analyses of data in this study.
Revisiting the Effects of Sugar Taxes on Sugary Drink Consumption: Evidence from the Random-Coefficient Demand Mode

Berkeley’s initiative on sugar tax policy is currently debated and it is quickly expanding to other states in the United States. Previous literature highlights the importance of consumer heterogeneity in evaluating the effect of sugar taxes. In this study, we use a demand model in characteristic space —BLP RC Logit demand— to identify the policy effect on preferences for sugary drinks and potential substitution patterns over 22 sugary drink products. Our results suggest that sugar taxes cause average valuation of sugar content to change from negative to positive. This type of “reactance” response is not driven by consumers with higher than average SSB consumption patterns. An examination on demand elasticities suggests Berkeley consumers become more responsive to prices of sugary drinks due to the policy implementation; however, it does not drive consumers to shift to diet drinks.
Direct Non-Invasive Measuring Techniques of Nanometric Liquid Level Variations Using Extrinsic Fiber Fabry–Perot Interferometers

This article investigates two different non-contact non-invasive solutions for measuring nanometric-order liquid-surface displacements with Extrinsic Fiber Fabry-Perot interferometers. They are investigated for developing hydrostatic leveling sensor (HLS) systems targeting the detection of very slowly-evolving movements in geophysics and geotechnics. In the first technique, the sensing beam from the interferometer traverses a liquid of known refractive index and is reflected by a mirror submerged at the bottom of the HLS vessel. The liquid-level variation is thus sensed as a variation of the optical path length of the interrogating beam. The second solution, on the other hand, directly exploits the reflection of the sensing beam at the air-liquid interface in the absence of a reflective surface in the vessel. The subsequent variation of liquid level is then measured directly as the beam’s optical path variation in air. The common denominator of these two techniques is an Extrinsic Fabry-Perot sensor with nanometric precision operating at a wavelength of ~1310 nm. The interrogating beam suffers from high IR absorption in water, hence the latter solution is more advantageous in terms of dynamic range. In applications where liquids other than water can be employed, the use of low optical absorption liquids such as Polydimethylsiloxanic fluids is recommended at this operating wavelength. Being more viscous and less volatile than water, these fluids can significantly improve the noise floor of HLS systems, hence contributing to a larger dynamic range, lower instrumental drift and higher signal-to-noise ratio.
Image Recognition and Safety Risk Assessment of Traffic Sign Based on Deep Convolution Neural Network

A neural network model based on deep learning is utilized to explore the traffic sign recognition (TSR) and expand the application of deep intelligent learning technology in the field of virtual reality (VR) image recognition, thereby assessing the road traffic safety risks and promoting the construction of intelligent transportation networks. First, a dual-path deep CNN (TDCNN) TSR model is built based on the convolutional neural network (CNN), and the cost function and recognition accuracy are selected as indicators to analyze the training results of the model. Second, the recurrent neural network (RNN) and long-short-term memory (LSTM) RNN are utilized to assess the road traffic safety risks, and the prediction and evaluation effects of them are compared. Finally, the changes in safety risks of road traffic accidents are analyzed based on the two key influencing factors of the number of road intersections and the speed of vehicles traveling. The results show that the learning rate of the network model and the number of hidden neurons in the fully-connected layer directly affect the training results, and there are differences in the choices between the early and late training periods. Compared with RNN, the LSTM network model has higher evaluation accuracy, and its corresponding root square error (RSE) is 0.36. The rational control of the number of intersections and the speed of roads traveled has a significant impact on improving the safety level and promoting road traffic efficiency. The VR image recognition algorithm and safety risk prediction method based on a neural network model positively affect the construction of an intelligent transport network.
A Varactor-Based Tunable Combline Bandpass Filter Using Suspended Integrated Stripline (SISL)

In this article, a varactor-based tunable combline suspended integrated stripline (SISL) bandpass filter with a tuning range of 2.3–3.9 GHz is designed and built. The filter is realized with five different substrate layers to implement an air cavity around the filter layer, creating the suspended stripline. Surface mount varactors are soldered onto the filter to allow for frequency tuning by reverse biasing the varactors at different dc voltages. The filter design concept is explained, detailed models are provided, and simulated results are given. The fabricated filter is shown and the measured results are compared with the simulated results and analyzed. The resulting filter demonstrates a tunable S-band filter implemented using SISL to allow for integration within a substrate.
Digital-Enabled Public Service Innovation in China's eHealth Sector: An Institutional Logics Perspective

Public service innovation is relatively poorly understood, in which innovators need to navigate between the changes of technologies and organizations. By drawing on the perspective of institutional logics as a potential approach to explain the changes of the institutions, in this article we contribute to the understanding of how innovation may emerge among different norms and practices in the public service field. Case study evidence from a longitudinal analysis of China's electronic healthcare evolution is applied to examine the interaction of institutional, technological, and partnerships’ changes in the public service innovation. The result suggests that the successful implementation of public service innovation requires to utilize the existing institutions and elaborately design and deploy the institutional changes to trigger the technological and partnerships’ changes in public service innovation. The institutional adjustment-leveled institutional changes lead to the partnerships’ quantitative increase and the technology diffusion, which is usually implemented at the beginning of each developing stage. The strategic transformation-leveled institutional changes trigger the structural changes of the partnerships and the alignment of the technological capabilities. Thus, implications for institutional design for public service innovation are then provided.
Effect of green microalgal extracts exhibiting antibacterial activity on viability of human malignant and non‐malignant cells

Microalgae have been investigated for their ability to produce metabolites that exhibit antibacterial activity. However, as research on antibacterial activity progresses, the effect of microalgal extracts on mammalian cells needs to be also assessed. The in vitro effect of microalgal extracts with demonstrated antibacterial activity against the human opportunistic pathogen Staphylococcus aureus was examined on the viability of non‐malignant (MCF10A and 184B5 cells) and malignant human cell lines (A2780 and MCF7). Direct cell counts indicated that the MTT (3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide) proliferation assay was found to under/overestimate cell viability when specific microalgal extracts and/or concentrations were tested. From direct cell counts, the viability of non‐malignant cells was not reduced after exposure to the extracts, whereas the viability of malignant cells was affected by specific microalgal extracts and concentrations. The results suggest that green microalgae are worthy of further investigation as potential sources of antibiotics, since they did not show a negative effect on the non‐malignant cell lines, MCF10A and 184B5. Additional studies should evaluate the compounds responsible for the anti‐proliferative activity of specific microalgal extracts observed on the malignant cells A2780 and MCF7.
Monster mash

We present a new framework for sketch-based modeling and animation of 3D organic shapes that can work entirely in an intuitive 2D domain, enabling a playful, casual experience. Unlike previous sketch-based tools, our approach does not require a tedious part-based multi-view workflow with the explicit specification of an animation rig. Instead, we combine 3D inflation with a novel rigidity-preserving, layered deformation model, ARAP-L, to produce a smooth 3D mesh that is immediately ready for animation. Moreover, the resulting model can be animated from a single viewpoint --- and without the need to handle unwanted inter-penetrations, as required by previous approaches. We demonstrate the benefit of our approach on a variety of examples produced by inexperienced users as well as professional animators. For less experienced users, our single-view approach offers a simpler modeling and animating experience than working in a 3D environment, while for professionals, it offers a quick and casual workspace for ideation.
Comparative Transcriptome Analysis of the Ovary and Testis in Noble Scallop (Chlamys nobilis)

1Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, PR China 2Guangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation, Beibu Gulf University, Qinzhou, PR China Article Information Received 26 January 2019 Revised 12 June 2019 Accepted 04 March 2020 Available online 18 June 2020
ANTAGONISTIC ACTINOBACTERIAL DIVERSITY OF MARINE SEDIMENTS COLLECTED FROM COASTAL TAMIL NADU

Objective: The main objective of the current investigation is to identify the antagonistic potential of marine sediment actinobacterial population collected from coastal regions of Tamil Nadu and Kerala.Methods: A total of 60 marine sediment samples were collected from 27 locations of coastal Tamil Nadu and Kerala. A total of 85 morphologically distinct actinobacterial strains were isolated and taxonomically characterized. The strains were screened for its antagonistic potential against selected bacteria strains, and the obtained results were statistically analyzed. Further, the strains excelled in producing antimicrobial substances were subjected to electron microscopic and chemotaxonomic studies to get more taxonomic details.Results: The isolates were identified as different species of Streptomyces, Micromonospora, Saccharopolyspora, Actinopolyspora, Nocardia, Nocardioides, Kitasatospora, and the rest of them were categorized as “unidentified. ” All the isolates were subjected to antimicrobial assay through cross-streak and well diffusion methods that endorsed 34 (40%) of them to be active against clinical and reference bacterial strains such as Staphylococcus aureus MTCC 3160, S. aureus (methicillin-resistant), Bacillus pumilus NCIM 2327, Escherichia coli MTCC 1698, E. coli, Shigella flexneri MTCC 1457, and Proteus vulgaris. The predominance of Streptomyces (18) was ascertained and followed by Saccharopolyspora (7), Micromonospora (5), Nocardia (2), and Kitasatospora (2) with considerable antimicrobial activities. Statistical analysis revealed that the isolates BDK01, BMT01, BPY03, and BRS07 showed significant antimicrobial activities. Phenotypic and chemotaxonomic analysis revealed that all four isolates are belonging under Streptomyces genus.Conclusion: The output of the present investigation revealed that the Streptomyces species are predominant in marine sediments and gain more attention for their antagonistic potential. Therefore, assessment and evaluation of marine microbial diversity were done, which could serve as a potential source for novel antibiotics.