bluuebunny/crossref_metadata_2025 huggingface dataset:
Guarding the Genome: CENP-A-Chromatin in Health and Cancer
Authors: Mahlke Megan A. , Nechemia-Arbely Yael
Published: July 2020

Faithful chromosome segregation is essential for the maintenance of genomic integrity and requires functional centromeres. Centromeres are epigenetically defined by the histone H3 variant, centromere protein A (CENP-A). Here we highlight current knowledge regarding CENP-A-containing chromatin structure, specification of centromere identity, regulation of CENP-A deposition and possible contribution to cancer formation and/or progression. CENP-A overexpression is common among many cancers and predicts poor prognosis. Overexpression of CENP-A increases rates of CENP-A deposition ectopically at sites of high histone turnover, occluding CCCTC-binding factor (CTCF) binding. Ectopic CENP-A deposition leads to mitotic defects, centromere dysfunction and chromosomal instability (CIN), a hallmark of cancer. CENP-A overexpression is often accompanied by overexpression of its chaperone Holliday Junction Recognition Protein (HJURP), leading to epigenetic addiction in which increased levels of HJURP and CENP-A become necessary to support rapidly dividing p53 deficient cancer cells. Alterations in CENP-A posttranslational modifications are also linked to chromosome segregation errors and CIN. Collectively, CENP-A is pivotal to genomic stability through centromere maintenance, perturbation of which can lead to tumorigenesis.
Preferentially Paternal Origin of De Novo 11p13 Chromosome Deletions Revealed in Patients with Congenital Aniridia and WAGR Syndrome
Authors: Vasilyeva Tatyana A. , Marakhonov Andrey V. , Sukhanova Natella V. , Kutsev Sergey I. , Zinchenko Rena A.
Published: July 2020

The frequency of pathogenic large chromosome rearrangements detected in patients with different Mendelian diseases is truly diverse and can be remarkably high. Chromosome breaks could arise through different known mechanisms. Congenital PAX6-associated aniridia is a hereditary eye disorder caused by mutations or chromosome rearrangements involving the PAX6 gene. In our recent study, we identified 11p13 chromosome deletions in 30 out of 91 probands with congenital aniridia or WAGR syndrome (characterized by Wilms’ tumor, Aniridia, and Genitourinary abnormalities as well as mental Retardation). The loss of heterozygosity analysis (LOH) was performed in 10 families with de novo chromosome deletion in proband. In 7 out of 8 informative families, the analysis revealed that deletions occurred at the paternal allele. If paternal origin is not random, chromosome breaks could arise either (i) during spermiogenesis, which is possible due to specific male chromatin epigenetic program and its vulnerability to the breakage-causing factors, or (ii) in early zygotes at a time when chromosomes transmitted from different parents still carry epigenetic marks of the origin, which is also possible due to diverse and asymmetric epigenetic reprogramming occurring in male and female pronuclei. Some new data is needed to make a well-considered conclusion on the reasons for preferential paternal origin of 11p13 deletions.
Classification of Microarray Gene Expression Data Using an Infiltration Tactics Optimization (ITO) Algorithm
Authors: Zahoor Javed , Zafar Kashif
Published: July 2020

A number of different feature selection and classification techniques have been proposed in literature including parameter-free and parameter-based algorithms. The former are quick but may result in local maxima while the latter use dataset-specific parameter-tuning for higher accuracy. However, higher accuracy may not necessarily mean higher reliability of the model. Thus, generalized optimization is still a challenge open for further research. This paper presents a warzone inspired “infiltration tactics” based optimization algorithm (ITO)—not to be confused with the ITO algorithm based on the Itõ Process in the field of Stochastic calculus. The proposed ITO algorithm combines parameter-free and parameter-based classifiers to produce a high-accuracy-high-reliability (HAHR) binary classifier. The algorithm produces results in two phases: (i) Lightweight Infantry Group (LIG) converges quickly to find non-local maxima and produces comparable results (i.e., 70 to 88% accuracy) (ii) Followup Team (FT) uses advanced tuning to enhance the baseline performance (i.e., 75 to 99%). Every soldier of the ITO army is a base model with its own independently chosen Subset selection method, pre-processing, and validation methods and classifier. The successful soldiers are combined through heterogeneous ensembles for optimal results. The proposed approach addresses a data scarcity problem, is flexible to the choice of heterogeneous base classifiers, and is able to produce HAHR models comparable to the established MAQC-II results.
RNA-Seq Analysis Reveals Localization-Associated Alternative Splicing across 13 Cell Lines
Authors: Zeng Chao , Hamada Michiaki
Published: July 2020

Alternative splicing, a ubiquitous phenomenon in eukaryotes, is a regulatory mechanism for the biological diversity of individual genes. Most studies have focused on the effects of alternative splicing for protein synthesis. However, the transcriptome-wide influence of alternative splicing on RNA subcellular localization has rarely been studied. By analyzing RNA-seq data obtained from subcellular fractions across 13 human cell lines, we identified 8720 switching genes between the cytoplasm and the nucleus. Consistent with previous reports, intron retention was observed to be enriched in the nuclear transcript variants. Interestingly, we found that short and structurally stable introns were positively correlated with nuclear localization. Motif analysis reveals that fourteen RNA-binding protein (RBPs) are prone to be preferentially bound with such introns. To our knowledge, this is the first transcriptome-wide study to analyze and evaluate the effect of alternative splicing on RNA subcellular localization. Our findings reveal that alternative splicing plays a promising role in regulating RNA subcellular localization.
P14ARF: The Absence that Makes the Difference
Authors: Cilluffo Danilo , Barra Viviana , Di Leonardo Aldo
Published: July 2020

P14ARF is a tumor suppressor encoded by the CDKN2a locus that is frequently inactivated in human tumors. P14ARF protein quenches oncogene stimuli by inhibiting cell cycle progression and inducing apoptosis. P14ARF functions can be played through interactions with several proteins. However, the majority of its activities are notoriously mediated by the p53 protein. Interestingly, recent studies suggest a new role of p14ARF in the maintenance of chromosome stability. Here, we deepened this new facet of p14ARF which we believe is relevant to its tumor suppressive role in the cell. To this aim, we generated a monoclonal HCT116 cell line expressing the p14ARF cDNA cloned in the piggyback vector and then induced aneuploidy by treating HCT116 cells with the CENP-E inhibitor GSK923295. P14ARF ectopic re-expression restored the near-diploid phenotype of HCT116 cells, confirming that p14ARF counteracts aneuploid cell generation/proliferation.
Translator Exposure APIs: Open Access to Data on Airborne Pollutant Exposures, Roadway Exposures, and Socio-Environmental Exposures and Use Case Application
Authors: Valencia Alejandro , Stillwell Lisa , Appold Stephen , Arunachalam Saravanan , Cox Steven , Xu Hao , Schmitt Charles P. , Schurman Shepherd H. , Garantziotis Stavros , Xue William , Ahalt Stanley C. , Fecho Karamarie
Published: July 2020

Environmental exposures have profound effects on health and disease. While public repositories exist for a variety of exposures data, these are generally difficult to access, navigate, and interpret. We describe the research, development, and application of three open application programming interfaces (APIs) that support access to usable, nationwide, exposures data from three public repositories: airborne pollutant estimates from the US Environmental Protection Agency; roadway data from the US Department of Transportation; and socio-environmental exposures from the US Census Bureau’s American Community Survey. Three open APIs were successfully developed, deployed, and tested using random latitude/longitude values and time periods as input parameters. After confirming the accuracy of the data, we used the APIs to extract exposures data on 2550 participants from a cohort within the Environmental Polymorphisms Registry (EPR) at the National Institute of Environmental Health Sciences, and we successfully linked the exposure estimates with participant-level data derived from the EPR. We then conducted an exploratory, proof-of-concept analysis of the integrated data for a subset of participants with self-reported asthma and largely replicated our prior findings on the impact of select exposures and demographic factors on asthma exacerbations. Together, the three open exposures APIs provide a valuable resource, with application across environmental and public health fields.
Investigation of the Environmental and Socio-Economic Characteristics of Counties with a High Asthma Burden to Focus Asthma Action in Utah
Authors: Vowles Maureen , Kerry Ruth , Ingram Ben , Mason Linda
Published: July 2020

Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a large burden on public health in Utah (UT), a high-altitude state in the Great Basin Desert, USA. This warrants an investigation of the characteristics of the counties with the highest asthma burden within UT to improve allocation of health resources and for planning. The relations between several predictor environmental, health behavior and socio-economic variables and two health outcome variables, AAP and AER visits, were investigated for UT’s 29 counties. Non-parametric statistical comparison tests, correlation and linear regression analysis were used to determine the factors significantly associated with AER visits and AAP. Regression kriging with Utah small area data (USAD) as well as socio-economic and pollution data enabled local Moran’s I cluster analysis and the investigation of moving correlations between health outcomes and risk factors. Results showed the importance of desert/mining dust and socio-economic status as AAP and AER visits were greatest in the south of the state, highlighting a marked north–south divide in terms of these factors within the state. USAD investigations also showed marked differences in pollution and socio-economic status associated with AAP within the most populous northern counties. Policies and interventions need to address socio-economic inequalities within counties and between the north and south of the state. Fine (PM2.5) and coarse (PM10) particulate matter monitors should be installed in towns in central and southern UT to monitor air quality as these are sparse, but in the summer, air quality can be worse here. Further research into spatiotemporal variation in air quality within UT is needed to inform public health interventions such as expanding clean fuel programs and targeted land-use policies. Efforts are also needed to examine barriers to routine asthma care.
B-Cell-Activating Factor Depletion Ameliorates Aging-Dependent Insulin Resistance via Enhancement of Thermogenesis in Adipose Tissues
Authors: Kim Bobae , Hyun Chang-Kee
Published: July 2020

Impaired glucose tolerance is a common feature associated with human aging, which is caused by defects in insulin secretion, insulin action or both. Recent studies have suggested that B-cell-activating factor (BAFF), a cytokine that modulates proliferation and differentiation of B cells, and its receptors are expressed in mature adipocytes and preadipocytes, proposing BAFF as a potential regulator of energy metabolism. In this study, we show that systemic BAFF depletion improves aging-dependent insulin resistance. In aged (10-month-old) BAFF−/− mice, glucose tolerance and insulin sensitivity were significantly improved despite higher adiposity as a result of expansion of adipose tissues compared to wild-type controls. BAFF−/− mice displayed an improved response to acute cold challenge, commensurate with the up-regulated expression of thermogenic genes in both brown and subcutaneous adipose tissues. These changes were found to be mediated by both increased M2-like (alternative) macrophage activation and enhanced leptin and FGF21 production, which may account for the improving effect of BAFF depletion on insulin resistance. In addition, leptin-deficient mice (ob/ob) showed augmented BAFF signaling concomitant with impaired thermogenic activity, identifying BAFF as a suppressive factor to thermogenesis. Our findings suggest that suppression of BAFF could be a therapeutic approach to attenuate aging-dependent insulin resistance.
Non-Invasive Risk Stratification of Hypertension: A Systematic Comparison of Machine Learning Algorithms
Authors: Sannino Giovanna , De Falco Ivanoe , De Pietro Giuseppe
Published: July 2020

One of the most important physiological parameters of the cardiovascular circulatory system is Blood Pressure. Several diseases are related to long-term abnormal blood pressure, i.e., hypertension; therefore, the early detection and assessment of this condition are crucial. The identification of hypertension, and, even more the evaluation of its risk stratification, by using wearable monitoring devices are now more realistic thanks to the advancements in Internet of Things, the improvements of digital sensors that are becoming more and more miniaturized, and the development of new signal processing and machine learning algorithms. In this scenario, a suitable biomedical signal is represented by the PhotoPlethysmoGraphy (PPG) signal. It can be acquired by using a simple, cheap, and wearable device, and can be used to evaluate several aspects of the cardiovascular system, e.g., the detection of abnormal heart rate, respiration rate, blood pressure, oxygen saturation, and so on. In this paper, we take into account the Cuff-Less Blood Pressure Estimation Data Set that contains, among others, PPG signals coming from a set of subjects, as well as the Blood Pressure values of the latter that is the hypertension level. Our aim is to investigate whether or not machine learning methods applied to these PPG signals can provide better results for the non-invasive classification and evaluation of subjects’ hypertension levels. To this aim, we have availed ourselves of a wide set of machine learning algorithms, based on different learning mechanisms, and have compared their results in terms of the effectiveness of the classification obtained.
Postscript: Feminist Legal Theory in the 21st Century
Authors: Thornton Margaret
Published: July 2020

This editorial takes the form of a short postscript to a special issue of Laws published in 2019–20. It shows how feminist legal theory (FLT), a corollary of second wave feminism, was initially embraced by law schools but soon subjected to a backlash. FLT was nevertheless able to turn around the negative discourse of post-feminism to show that the “post” can mean not just the end but a new beginning. The Special Issue attests to the resurgence of FLT in the 21st century.
Efficacy and Cytotoxicity of Binary Mixtures as Root Canal Filling Solvents
Authors: Ferreira Inês , Grenho Liliana , Gomes Pedro , Braga Ana Cristina , Fernandes Maria Helena , Lopes Maria Ascensão , Pina-Vaz Irene
Published: July 2020

Objectives: This study reports the efficacy of two solvent mixtures on the dissolution of gutta-percha and AH Plus sealer, together with the cytotoxicity. Methods: Methyl ethyl ketone (MEK), orange oil, tetrachloroethylene, MEK/tetrachloroethylene (1:1), MEK/orange oil (1:1), and chloroform (control) were tested. Twelve groups (n = 15) of standardized stainless-steel molds filled with softened gutta-percha cones and twelve (n = 15) filled with AH Plus were immersed in the corresponding mixture or individual solvent, in an ultrasonic bath, for either 2 or 5 min. The effect of the solvents was assessed qualitatively by a topographical analysis (scanning electron microscopy) and chemical analysis (Fourier transform infrared spectroscopy), and quantitatively by a weight loss and viscoelastic property (dynamic mechanical analysis) evaluation. The cytotoxicity was assessed on MG63 human osteoblastic cells. Results: The mixtures did not show the formation of new compounds. Both presented significantly higher efficacies compared to their individual solvents, suggesting a synergistic effect. Their dissolution efficacy was similar to that of chloroform, showing high cytocompatibility. Conclusions: The proposed strategy, incorporating ultrasound agitation and profiting from the synergy of adequate solvents, might enhance root canal cleanliness allowing a single-step procedure to dissolve gutta-percha and the sealer remnants, while assuring cytocompatibility with the periapical tissues.
Mitigation of Membrane Wetting by Applying a Low Temperature Membrane Distillation
Authors: Gryta Marek
Published: July 2020

The formation of deposits on the membrane surface during membrane distillation is considered as one of the main reasons for membrane wetting. To assess the intensity of this phenomenon, long-term studies were performed comparing the membrane wettability with non-fouling feed (NaCl solutions) and feeds containing various foulants (lake and Baltic Sea water). The polypropylene membranes used were non-wetted by NaCl solutions during several hundred hours of water desalination. However, the occurrence of CaCO3 or other salt crystallization caused the membranes to be partially wetted, especially when periodical membrane cleaning was applied. The scaling intensity was significantly reduced by lowering the feed temperature from 353 to 315 K, which additionally resulted in the limitation of the degree of membrane wetting.
On the Effect of Modified Carbohydrates on the Size and Shape of Gold and Silver Nanostructures
Authors: Yazgan Idris , Gümüş Abdurrahman , Gökkuş Kutalmış , Demir Mehmet Ali , Evecen Senanur , Sönmez Hamide Ayçin , Miller Roland M. , Bakar Fatma , Oral Ayhan , Popov Sergei , Toprak Muhammet S.
Published: July 2020

Gold (Au) and silver (Ag) nanostructures have widespread utilization from biomedicine to materials science. Therefore, their synthesis with control of their morphology and surface chemistry have been among the hot topics over the last decades. Here, we introduce a new approach relying on sugar derivatives that work as reducing, stabilizing, and capping agents in the synthesis of Au and Ag nanostructures. These sugar derivatives are utilized alone and as mixture, resulting in spherical, spheroid, trigonal, polygonic, and star-like morphologies. The synthesis approach was further tested in the presence of acetate and dimethylamine as size- and shape-directing agents. With the use of transmission electron microscopy (TEM), selected area electron diffraction (SAED), x-ray diffraction (XRD), scanning electron microscopy (SEM), and ultraviolet-visible (UV-vis) absorption spectroscopy techniques, the particle size, shape, assembly, aggregation, and film formation characteristics were evaluated. NPs’ attributes were shown to be tunable by manipulating the sugar ligand selection and sugar ligand/metal-ion ratio. For instance, with an imine side group and changing the sugar moiety from cellobiose to lactose, the morphology of the Ag nanoparticles (NPs) transformed from well dispersed cubic to rough and aggregated. The introduction of acetate and dimethylamine further extended the growth pattern and morphological properties of these NPs. As examples, L5 AS, G5AS, and S5AS ligands formed spherical or sheet-like structures when used alone, which upon the use of these additives transformed into larger multicore and rough NPs, revealing their significant effect on the NP morphology. Selected samples were tested for their stability against protein corona formation and ionic strength, where a high chemical stability and resistance to protein coating were observed. The findings show a promising, benign approach for the synthesis of shape- and size-directed Au and Ag nanostructures, along with a selection of the chemistry of carbohydrate-derivatives that can open new windows for their applications.
Toxicity to RAW264.7 Macrophages of Silica Nanoparticles and the E551 Food Additive, in Combination with Genotoxic Agents
Authors: Dussert Fanny , Arthaud Pierre-Adrien , Arnal Marie-Edith , Dalzon Bastien , Torres Anaëlle , Douki Thierry , Herlin Nathalie , Rabilloud Thierry , Carriere Marie
Published: July 2020

Synthetic amorphous silica (SAS) is used in a plethora of applications and included in many daily products to which humans are exposed via inhalation, ingestion, or skin contact. This poses the question of their potential toxicity, particularly towards macrophages, which show specific sensitivity to this material. SAS represents an ideal candidate for the adsorption of environmental contaminants due to its large surface area and could consequently modulate their toxicity. In this study, we assessed the toxicity towards macrophages and intestinal epithelial cells of three SAS particles, either isolated SiO2 nanoparticles (LS30) or SiO2 particles composed of agglomerated-aggregates of fused primary particles, either food-grade (E551) or non-food-grade (Fumed silica). These particles were applied to cells either alone or in combination with genotoxic co-contaminants, i.e., benzo[a]pyrene (B[a]P) and methane methylsulfonate (MMS). We show that macrophages are much more sensitive to these toxic agents than a non-differenciated co-culture of Caco-2 and HT29-MTX cells, used here as a model of intestinal epithelium. Co-exposure to SiO2 and MMS causes DNA damage in a synergistic way, which is not explained by the modulation of DNA repair protein mRNA expression. Together, this suggests that SiO2 particles could adsorb genotoxic agents on their surface and, consequently, increase their DNA damaging potential.
Modeling Salt Marsh Vegetation Height Using Unoccupied Aircraft Systems and Structure from Motion
Authors: DiGiacomo Alexandra E. , Bird Clara N. , Pan Virginia G. , Dobroski Kelly , Atkins-Davis Claire , Johnston David W. , Ridge Justin T.
Published: July 2020

Salt marshes provide important services to coastal ecosystems in the southeastern United States. In many locations, salt marsh habitats are threatened by coastal development and erosion, necessitating large-scale monitoring. Assessing vegetation height across the extent of a marsh can provide a comprehensive analysis of its health, as vegetation height is associated with Above Ground Biomass (AGB) and can be used to track degradation or growth over time. Traditional methods to do this, however, rely on manual measurements of stem heights that can cause harm to the marsh ecosystem. Moreover, manual measurements are limited in scale and are often time and labor intensive. Unoccupied Aircraft Systems (UAS) can provide an alternative to manual measurements and generate continuous results across a large spatial extent in a short period of time. In this study, a multirotor UAS equipped with optical Red Green Blue (RGB) and multispectral sensors was used to survey five salt marshes in Beaufort, North Carolina. Structure-from-Motion (SfM) photogrammetry of the resultant imagery allowed for continuous modeling of the entire marsh ecosystem in a three-dimensional space. From these models, vegetation height was extracted and compared to ground-based manual measurements. Vegetation heights generated from UAS data consistently under-predicted true vegetation height proportionally and a transformation was developed to predict true vegetation height. Vegetation height may be used as a proxy for Above Ground Biomass (AGB) and contribute to blue carbon estimates, which describe the carbon sequestered in marine ecosystems. Employing this transformation, our results indicate that UAS and SfM are capable of producing accurate assessments of salt marsh health via consistent and accurate vegetation height measurements.
A Robust RANSAC-Based Planet Radius Estimation for Onboard Visual Based Navigation
Authors: de Gioia Francesco , Meoni Gabriele , Giuffrida Gianluca , Donati Massimiliano , Fanucci Luca
Published: July 2020

Individual spacecraft manual navigation by human operators from ground station is expected to be an emerging problem as the number of spacecraft for space exploration increases. Hence, as an attempt to reduce the burden to control multiple spacecraft, future missions will employ smart spacecraft able to navigate and operate autonomously. Recently, image-based optical navigation systems have proved to be promising solutions for inexpensive autonomous navigation. In this paper, we propose a robust image processing pipeline for estimating the center and radius of planets and moons in an image taken by an on-board camera. Our custom image pre-processing pipeline is tailored for resource-constrained applications, as it features a computationally simple processing flow with a limited memory footprint. The core of the proposed pipeline is a best-fitting model based on the RANSAC algorithm that is able to handle images corrupted with Gaussian noise, image distortions, and frame drops. We report processing time, pixel-level error of estimated body center and radius and the effect of noise on estimated body parameters for a dataset of synthetic images.
Collision-Free Transmissions in an IoT Monitoring Application Based on LoRaWAN
Authors: Haiahem Rahim , Minet Pascale , Boumerdassi Selma , Azouz Saidane Leila
Published: July 2020

With the Internet of Things (IoT), the number of monitoring applications deployed is considerably increasing, whatever the field considered: smart city, smart agriculture, environment monitoring, air pollution monitoring, to name a few. The LoRaWAN (Long Range Wide Area Network)architecture with its long range communication, its robustness to interference and its reduced energy consumption is an excellent candidate to support such applications. However, if the number of end devices is high, the reliability of LoRaWAN, measured by the Packet Delivery Ratio (PDR), becomes unacceptable due to an excessive number of collisions. In this paper, we propose two different families of solutions ensuring collision-free transmissions. The first family is TDMA (Time-Division Multiple Access)-based. All clusters transmit in sequence and up to six end devices with different spreading factors belonging to the same cluster are allowed to transmit in parallel. The second family is FDMA (Frequency Divsion Multiple Access)-based. All clusters transmit in parallel, each cluster on its own frequency. Within each cluster, all end devices transmit in sequence. Their performance are compared in terms of PDR, energy consumption by end device and maximum number of end devices supported. Simulation results corroborate the theoretical results and show the high efficiency of the solutions proposed.
Workforce Localization in the Arab Gulf Countries: How Do Organizations Socialize the Members of a Powerful Minority?
Authors: Waxin Marie-France , Kumra Savita , Zhao Fang
Published: July 2020

This paper addresses a key social–cultural aspect of sustainability in the Gulf region: Workforce localization (WL). Our research objective is to empirically explore organizational socialization (OS) practices in the context of WL in the United Arab Emirates (UAE), where National Citizens (NCs) are a powerful minority in the workforce. This research adopts a qualitative methodology, using semi-structured interviews with managers in charge of the WL program in 14 organizations in the UAE, across different industrial sectors and ownership. We found five major OS practices: Establishing thorough orientation programs, providing formal training programs (skills, diversity/cultural awareness, supervisor, mentoring and coaching team building), redesigning NCs’ jobs and work teams, engaging expatriates in NCs’ OS processes, and organizing networking events. All organizations rigorously evaluated the effectiveness of their OS practices. This study contributes to the empirical literature on management OS, WL, and diversity management in a non-western, emerging Arab country. It contributes to theory development on the content of OS practices, showing how a minority can be a powerful group around whom socialization processes are tailored to integrate them fully into the organization. Practically, our findings inform managers of how to adapt their existing OS practices to the specific needs of minority members, and support Gulf Cooperation Council (GCC)-based organizations and policymakers with the design, monitoring, and implementation of WL programs, and with the development of a sustainable workforce.
An Economic Analysis of Tropical Forest Resource Conservation in a Protected Area
Authors: Assogba Noel Perceval , Zhang Daowei
Published: July 2020

In this paper, we develop a reduced form model for factors influencing the conservation of forest resources. We then estimate it using a bivariate negative binomial regression model with cases of illegal farming and illegal cattle grazing in the W Reserve in West Africa. Our results show that population size and farm area in the periphery of the W Reserve are associated with an increase of 2.4% and 7.1% of the illegal farming, respectively. On the other hand, income level, the existence of a checkpoint, and the distance between the villages and the reserve decrease the illegal grazing activities by 7.3%, 63.2%, and 2.3%, respectively.
Method of Choice: A Fluorescent Penetrant Taking into Account Sustainability Criteria
Authors: Pacana Andrzej , Siwiec Dominika , Bednárová Lucia
Published: July 2020

To conduct, in an effective way, the non-destructive testing (NDT) of products—in particular, the fluorescent penetrant inspection (FPI)—remains a challenge. Therefore, the aim of this work is to propose the method of support in the choice of a fluorescent penetrant to be used in FPI research. In the results of the usage of the proposed procedure, it is demonstrated that it is possible to reduce the negative impacts on the environment by FPI processes (through sustainability), while including other criteria, i.e., financial, security, productive (Industry 4.0), and societal (Society 5.0) criteria. The essence of the proposed method is to integrate two methods of decision support. These were the analytic hierarchy process (AHP) method and the cost–quality analysis (AKJ). Using the AHP method, the quality level of fluorescent penetrant (to the satisfaction of the customer)—which included the sustainability criteria—are calculated. These criteria include natural environment, reactivity, combustibility, level of sensitivity, and type of washing (emulsification). Then, with the help of the AKJ, the most favorable penetrant—in terms of quality and cost—is calculated and, thus, indicated. This choice must include the concept of sustainable development. Therefore, this method can be used to choose fluorescent penetrants in manufacturing and service enterprises which carry out FPI.
High-Quality Resolution of the Outbreak-Related Zika Virus Genome and Discovery of New Viruses Using Ion Torrent-Based Metatranscriptomics
Authors: I. Sardi Silvia , H. Carvalho Rejane , C. Pacheco Luis G. , P. d. Almeida João P. , M. d. A. Belitardo Emilia M. , S. Pinheiro Carina , S. Campos Gúbio , R. G. R. Aguiar Eric
Published: July 2020

Arboviruses, including the Zika virus, have recently emerged as one of the most important threats to human health. The use of metagenomics-based approaches has already proven valuable to aid surveillance of arboviral infections, and the ability to reconstruct complete viral genomes from metatranscriptomics data is key to the development of new control strategies for these diseases. Herein, we used RNA-based metatranscriptomics associated with Ion Torrent deep sequencing to allow for the high-quality reconstitution of an outbreak-related Zika virus (ZIKV) genome (10,739 nt), with extended 5′-UTR and 3′-UTR regions, using a newly-implemented bioinformatics approach. Besides allowing for the assembly of one of the largest complete ZIKV genomes to date, our strategy also yielded high-quality complete genomes of two arthropod-infecting viruses co-infecting C6/36 cell lines, namely: Alphamesonivirus 1 strain Salvador (20,194 nt) and Aedes albopictus totivirus-like (4618 nt); the latter likely represents a new viral species. Altogether, our results demonstrate that our bioinformatics approach associated with Ion Torrent sequencing allows for the high-quality reconstruction of known and unknown viral genomes, overcoming the main limitation of RNA deep sequencing for virus identification.
Use of orthokeratology contact lenses in the treatment of progressive myopia
Authors: Olenich Mariya
Published: July 2020

Orthokeratology is a method of non-surgical correction of refraction, which is based on the principle of biomechanical changes in the curvature of the cornea under the influence of «reverse geometry». This method was developed more than 50 years ago, however, it became widely used only in the early 2000s. The basis of this method is the use of special orthokeratology lenses that patients wear during the night. Peculiarity of these lenses is the ability to change curvature of the cornea, resulting in a flattening of its central part and thickening of the paracentral and peripheral sections, which leads to the formation of positive spherical aberration of the optical system. Such changes in the cornea resulting from partial desquamation of keratocytes and changes in their shape during 7–8 hours of influence during the night, lead to the normalization of refraction, which persists for the next 24 hours. Most often this method of vision correction is used in children and adolescents, since it allows not only to optimize visual acuity for a certain period of time, but also to stop the progression of myopia. Another indication for the correction of vision using orthokeratology lenses includes active sports and situations that exclude the possibility of wearing glasses or soft contact lenses.
Clinical manifestations and diagnosis of keratoconus. Treatment of iatrogenic keratoconus
Authors: Ermolyuk Fedor
Published: July 2020

Keratoconus is a dystrophic disease of the cornea, when it is thinned with the formation of a conus-like protrusion (protrusion of the cornea). This disease belongs to the group of keratectasia, it has a multifactorial nature and occurs in approximately 25 % of all corneal pathologies. The disease can be either primary, which is based on dystrophic changes in the cornea, or secondary, which develops against the background of prenatal keratitis. Keratoconus of iatrogenic origin, which develops as a result of refractive eye microsurgery, has become widespread during the last 20 years. Most often primary keratoconus manifests during puberty, progresses to 30–40 years, after which its development slows down. An early clinical manifestation of this corneal pathology is a progressive decrease in visual acuity, development of double vision (binocular diplopia) with the development of a strong headache against this background. Monocular polyopia — images and symbols with multiple contours — develops subsequently. Severe dry eyes, itching, photophobia appear in advanced stages. Diagnosis of keratoconus in some cases can be a significant difficulty, since the use of conventional research methods only allow to suspect refractive errors in the form of myopia or astigmatism. It is necessary to take into account the impossibility of correcting visual impairment using conventional methods — glasses or contact lenses — to make correct diagnosis. As a rule, diagnosis of keratoconus requires use of expanded spectrum of instrumental research methods.
DoS and DDoS Attack Detection Using Deep Learning and IDS
Authors: Shurman Mohammad , Khrais Rami , Yateem Abdulrahman
Published: July 2020

In the recent years, Denial-of-Service (DoS) or Distributed Denial-of-Service (DDoS) attack has spread greatly and attackers make online systems unavailable to legitimate users by sending huge number of packets to the target system. In this paper, we proposed two methodologies to detect Distributed Reflection Denial of Service (DrDoS) attacks in IoT. The first methodology uses hybrid Intrusion Detection System (IDS) to detect IoT-DoS attack. The second methodology uses deep learning models, based on Long Short-Term Memory (LSTM) trained with latest dataset for such kinds of DrDoS. Our experimental results demonstrate that using the proposed methodologies can detect bad behaviour making the IoT network safe of Dos and DDoS attacks
On Detection and Prevention of Zero-Day Attack Using Cuckoo Sandbox in Software-Defined Networks
Authors: Al-Rushdan Huthifh , Shurman Mohammad , Alnabelsi Sharhabeel
Published: July 2020

Networks attacker may identify the network vulnerability within less than one day; this kind of attack is known as zero-day attack. This undiscovered vulnerability by vendors empowers the attacker to affect or damage the network operation, because vendors have less than one day to fix this new exposed vulnerability. The existing defense mechanisms against the zero-day attacks focus on the prevention effort, in which unknown or new vulnerabilities typically cannot be detected. To the best of our knowledge the protection mechanism against zero-day attack is not widely investigated for Software-Defined Networks (SDNs). Thus, in this work we are motivated to develop a new zero-day attack detection and prevention mechanism for SDNs by modifying Cuckoo sandbox tool. The mechanism is implemented and tested under UNIX system. The experiments results show that our proposed mechanism successfully stops the zero-day malwares by isolating the infected clients, in order to prevent the malwares from spreading to other clients. Moreover, results show the effectiveness of our mechanism in terms of detection accuracy and response time
Streaming Video Classification Using Machine Learning
Authors: Shaout Adnan , Crispin Brennan
Published: July 2020

This paper presents a method using neural networks and Markov Decision Process (MDP) to identify the source and class of video streaming services. The paper presents the design and implementation of an end-to-end pipeline for training and classifying a machine learning system that can take in packets collected over a network interface and classify the data stream as belonging to one of five streaming video services: You Tube, You Tube TV, Netflix, Amazon Prime, or HBO
Incorporating Intelligence for Overtaking Moving Threatening Obstacles
Authors: Shuaib Mohammed , Zainuddin Zarita
Published: July 2020

Crowd management and fire safety studies indicate that the correct prediction of the threat caused by fire is crucial behavior which could lead to survival. Incorporating intelligence into exit choice models for accomplishing evacuation simulations involving such behavior is essential. Escaping from moving source of panic such as fire is of tremendous frightening event while evacuation situation. Predicting the dynamic of fire spreading and the exit clogging are intelligent aspects which help the individuals follow the correct behaviors for their evacuation. This article proposes an intelligent approach to accomplishing typical evacuations. The agents are provided with the ability to find optimal routes that enable them overcome spreading fire. Fire and safe floor fields are proposed to provide the agents with the capability of determining intermediate points to compose optimal routes toward the effective chosen exit. The instinct human behavior of being far from the fire to protect himself from sudden unexpected attack is introduced as essential factor risen in emergency situation. Simulations are conducted in order to examine the simulated evacuees’ behavior regarding overtaking the fire and to test the efficiency of making smart and effective decisions during emergency evacuation scenarios
Discovery of Arbitrary-Shapes Clusters Using DENCLUE Algorithm
Authors: Khader Mariam , Al-Naymat Ghazi
Published: July 2020

One of the main requirements in clustering spatial datasets is the discovery of clusters with arbitrary-shapes. Density-based algorithms satisfy this requirement by forming clusters as dense regions in the space that are separated by sparser regions. DENCLUE is a density-based algorithm that generates a compact mathematical form of arbitrary-shapes clusters. Although DENCLUE has proved its efficiency, it cannot handle large datasets since it requires large computation complexity. Several attempts were proposed to improve the performance of DENCLUE algorithm, including DENCLUE 2. In this study, an empirical evaluation is conducted to highlight the differences between the first DENCLUE variant which uses the Hill-Climbing search method and DENCLUE 2 variant, which uses the fast Hill-Climbing method. The study aims to provide a base for further enhancements on both algorithms. The evaluation results indicate that DENCLUE 2 is faster than DENCLUE 1. However, the first DECNLUE variant outperforms the second variant in discovering arbitrary-shapes clusters
Default Prediction Model: The Significant Role of Data Engineering in the Quality of Outcomes
Authors: Al-qerem Ahmad , Al-Naymat Ghazi , Alhasan Mays , Al-Debei Mutaz
Published: July 2020

For financial institutions and the banking industry, it is very crucial to have predictive models for their core financial activities, and especially those activities which play major roles in risk management. Predicting loan default is one of the critical issues that banks and financial institutions focus on, as huge revenue loss could be prevented by predicting customer’s ability not only to pay back, but also to be able to do that on time. Customer loan default prediction is a task of proactively identifying customers who are most probably to stop paying back their loans. This is usually done by dynamically analyzing customers’ relevant information and behaviors. This is significant so as the bank or the financial institution can estimate the borrowers’ risk. Many different machine learning classification models and algorithms have been used to predict customers’ ability to pay back loans. In this paper, three different classification methods (Naïve Bayes, Decision Tree, and Random Forest) are used for prediction, comprehensive different pre-processing techniques are being applied on the dataset in order to gain better data through fixing some of the main data issues like missing values and imbalanced data, and three different feature extractions algorithms are used to enhance the accuracy and the performance. Results of the competing models were varied after applying data preprocessing techniques and features selections. The results were compared using F1 accuracy measure. The best model achieved an improvement of about 40%, whilst the least performing model achieved an improvement of 3% only. This implies the significance and importance of data engineering (e.g., data preprocessing techniques and features selections) course of action in machine learning exercises
Identity Identification and Management in the Internet of Things
Authors: Houhamdi Zina , Athamena Belkacem
Published: July 2020

Henceforth, users agreed on the necessity of continuous Internet connection independently of the place, the manner, and the time. Nowadays, several elite services are accessible by people over the Internet of Things (IoT), which is a heterogeneous network defined by machine-to-machine communication. Despite the fact that the devices are used to establish the communication, the users can be considered as the actual producers of input data and consumers of the output data. Consequently, the users should be viewed as a smart object in IoT; therefore, user identification, authentication, authorization are required. However, the user identification process is too complicated because the users are worried to share their confidential and private data. on the other hand, this private data should be used by some of their devices. Accordingly, an equitable mechanism to identify users and manage their identities is necessary. In addition, the user plays an extreme important role in the establishment of rules needed for identity identification and in ensuring the continuity of receptive services.The main purpose of this paper is to develop a new framework for Identity Management System (IdMS) for IoT. The primary contributions of this paper are: the proposition of a device recognition algorithm for user identification, the proposition of a new format for the identifier, and a theoretical framework for IdMS
Explotación de guanacos por cazadores-recolectores durante el Holoceno medio en la costa sur de Tierra del Fuego (Argentina)
Authors: Alunni Daniela , Vázquez Martín , Zangrando Atilio Francisco
Published: July 2020

En este trabajo se discuten los modos de explotación de guanacos (Lama guanicoe) por cazadores-recolectores costeros que habitaron el litoral sur de Tierra del Fuego durante el Holoceno medio. Este período constituyó un momento clave en el proceso de poblamiento humano del archipiélago fueguino, dado que se propuso como escenario inicial de una adaptación al ambiente de canales e islas del extremo sur americano. En este contexto, se evalúan las estrategias de aprovisionamiento de guanacos y el rol que pudieron haber tenido los espacios terrestres para la economía de los cazadores-recolectores y pescadores que ocuparon estos espacios. Para ello, se analizan y comparan tres conjuntos arqueológicos correspondientes a ese período pero ubicados en entornos ambientales disímiles y que ofrecen distintas condiciones para la captura y transporte de guanacos. Los resultados muestran que estas prácticas se desarrollaron bajo estrategias diferentes según cada sector, y que esta variabilidad no necesariamente estuvo relacionada con las disposiciones espaciales y estacionales alternantes que presenta el recurso, sino también con diversas contingencias o requerimientos nutricionales de los grupos humanos que habitaron estas costas durante el Holoceno medio.
Imágenes, códigos y comunicación: un análisis del arte rupestre en el Extremo Sur del Macizo del Deseado (Patagonia, Argentina)
Authors: Acevedo Agustín , Fiore Danae
Published: July 2020

En este trabajo se evalúan las reglas de composición que vinculan motivos rupestres y soportes rocosos, comparando para ello un total de 1.273 motivos y 76 tipos de motivos (TM) registrados en 33 sitios de dos localidades arqueológicas de la región centro-sur de Patagonia (Argentina). Los análisis demuestran que: a) los emplazamientos de los motivos en los soportes rocosos no siguen reglas claras de composición visual y b) del total de TM, las dos localidades comparten solo 14, lo cual indicaría la existencia de bajos niveles de comunicación visual entre ambas. Esto es discutido en función de diferentes formas de integración de cada localidad dentro de circuitos mayores de movilidad e intercambio de información a escala regional. A su vez, los 14 TM compartidos representan más del 60% de la producción rupestre de cada una, lo cual implica un claro énfasis de selección de determinadas porciones del repertorio para la producción artística de cada localidad. Se argumenta entonces que la comunicación visual generada por cazadores-recolectores en ambas localidades habría sido más fluida y menos reglada que lo esperado en términos generales de las teorías de comunicación, más acorde con un bajo grado de control social característico de estas sociedades.