bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of Brainwaves for Sleep Stages by High-Dimensional FFT Features from EEG Signals
Authors: Delimayanti Mera Kartika , Purnama Bedy , Nguyen Ngoc Giang , Faisal Mohammad Reza , Mahmudah Kunti Robiatul , Indriani Fatma , Kubo Mamoru , Satou Kenji
Published: March 2020

Manual classification of sleep stage is a time-consuming but necessary step in the diagnosis and treatment of sleep disorders, and its automation has been an area of active study. The previous works have shown that low dimensional fast Fourier transform (FFT) features and many machine learning algorithms have been applied. In this paper, we demonstrate utilization of features extracted from EEG signals via FFT to improve the performance of automated sleep stage classification through machine learning methods. Unlike previous works using FFT, we incorporated thousands of FFT features in order to classify the sleep stages into 2–6 classes. Using the expanded version of Sleep-EDF dataset with 61 recordings, our method outperformed other state-of-the art methods. This result indicates that high dimensional FFT features in combination with a simple feature selection is effective for the improvement of automated sleep stage classification.
Relationship between Buchholz’s Apparent Power and Instantaneous Power in Three-Phase Systems
Authors: León-Martínez Vicente , Montañana-Romeu Joaquín , Peñalvo-López Elisa , Valencia-Salazar Iván
Published: March 2020

Similarly to how Steinmetz developed his theory of alternating current in single-phase sinusoidal systems, a few formal relationships between expressions of the instantaneous and Buchholz’s apparent power in three-phase systems were identified in this paper. Based on these relationships, a methodology to express Buchholz’s apparent power and its components in any three-phase, wye-configured system—sinusoidal or non-sinusoidal, balanced or unbalanced—through instantaneous power expressions was established. The application of the proposed method to the entire system allowed the determination of a novel quantity referred to as neutral-displacement power, which measured the impacts of the phenomena caused by the neutral path operation on the values of the source and load apparent power. These impacts were analyzed using a real-world urban installation with a neutral conductor deterioration simulation via an Excel platform as an application example.
Computer-Assisted Screening for Cervical Cancer Using Digital Image Processing of Pap Smear Images
Authors: Win Kyi Pyar , Kitjaidure Yuttana , Hamamoto Kazuhiko , Myo Aung Thet
Published: March 2020

Cervical cancer can be prevented by having regular screenings to find any precancers and treat them. The Pap test looks for any abnormal or precancerous changes in the cells on the cervix. However, the manual screening of Pap smear in the microscope is subjective with poorly reproducible criteria. Therefore, the aim of this study was to develop a computer-assisted screening system for cervical cancer using digital image processing of Pap smear images. The analysis of Pap smear image is important in the cervical cancer screening system. There were four basic steps in our cervical cancer screening system. In cell segmentation, nuclei were detected using a shape-based iterative method, and the overlapping cytoplasm was separated using a marker-control watershed approach. In the features extraction step, three important features were extracted from the regions of segmented nuclei and cytoplasm. RF (random forest) algorithm was used as a feature selection method. In the classification stage, bagging ensemble classifier, which combined the results of five classifiers—LD (linear discriminant), SVM (support vector machine), KNN (k-nearest neighbor), boosted trees, and bagged trees—was applied. SIPaKMeD and Herlev datasets were used to prove the effectiveness of our proposed system. According to the experimental results, 98.27% accuracy in two-class classification and 94.09% accuracy in five-class classification was achieved using the SIPaKMeD dataset. When the results were compared with five classifiers, our proposed method was significantly better in two-class and five-class problems.
Thermophysiological Comfort of Surgeons and Patient in an Operating Room Based on PMV-PPD and PHS Indexes
Authors: Angelova Radostina A. , Velichkova Rositsa
Published: March 2020

There are different actors in an operating room (OR), who have controversial requirements for the indoor thermal environment. While the patient is at risk of perioperative hypothermia, the surgeons are in a state of thermophysiological discomfort. The study presents an analysis of the thermophysiological comfort of both patient and surgeons in an OR. Surgical clothing ensembles with three values of clothing insulation are simulated. Different indoor environment conditions (air temperature and relative humidity) are tested. The analysis is based on the calculation of predicted mean vote and predicted percentage of dissatisfied (PMV-PPD) indexes and assessment of the climatic conditions categories. Discussion of the predicted heat strain is also presented. The simulated results and their analysis show considerable discrepancies between the thermophysiological comfort of the patient and the surgeons, even when dressed in a light protective ensemble, in the same indoor environment.
Development Experience of a Context-Aware System for Smart Irrigation Using CASO and IRRIG Ontologies
Authors: Nguyen Quang-Duy , Roussey Catherine , Poveda-Villalón María , de Vaulx Christophe , Chanet Jean-Pierre
Published: March 2020

The rapid development of information and communication technologies and wireless sensor networks has transformed agriculture practices. New tools and methods are used to support farmers in their activities. This paper presents a context-aware system that automates irrigation decisions based on sensor measurements. Automatic irrigation overcomes the water shortage problem, and automatic sensor measurements reduce the observational work of farmers. This paper focuses on a method for developing context-aware systems using ontologies. Ontologies are used to solve heterogeneity issues in sensor measurements. Their main goal is to propose a shared data schema that precisely describes measurements to ease their interpretations. These descriptions are reusable by any machine and understandable by humans. The context-aware system also contains a decision support system based on a rules inference engine. We propose two new ontologies: The Context-Aware System Ontology addresses the development of the context-aware system in general. The Irrigation ontology automates a manual irrigation method named IRRINOV®. These ontologies reuse well-known ontologies such as the Semantic Sensor Network (SSN) and Smart Appliance REFerence (SAREF). The decision support system uses a set of rules with ontologies to infer daily irrigation decisions for farmers. This project uses real experimental data to evaluate the implementation of the decision support system.
A Proposal for the Organisational Measure in Intelligent Systems
Authors: Román Jesús-Ángel , Pérez-Delgado María-Luisa
Published: March 2020

The collaboration within organisations and among organisations is a fundamental concept in the attainment of the overall objectives pursued by an enterprise network in human companies. Swarm systems are intelligent systems that show collaboration within the system; moreover, some models, such as multiple ant colonies, show the collaboration of several systems to achieve a global goal. The collaboration in this type of system optimises the achievement of the overall objectives as in an enterprise network in human organisations. Being able to measure this collaboration allows establishing a relationship between the improvement in the results of the system and the degree of collaboration, both at the level of specialisation of each element of the system and the systems as a whole. The performance of a swarm system depends on the number of members in many cases, so that if we can establish a measure of specialisation and collaboration, we could tipify and classify these systems in terms of the efficiency and the realiability to perform different tasks.
Material Characterization for Reliable Resin Transfer Molding Process Simulation
Authors: Falaschetti Maria Pia , Rondina Francesco , Zavatta Nicola , Gragnani Lisa , Gironi Martina , Troiani Enrico , Donati Lorenzo
Published: March 2020

Resin transfer molding (RTM) technologies are widely used in automotive, marine, and aerospace applications. The need to evaluate the impact of design and production critical choices, also in terms of final costs, leads to the wider use of numerical simulation in the preliminary phase of component development. The main issue for accurate RTM analysis is the reliable characterization of the involved materials. The aim of this paper is to present a validated methodology for material characterization to be implemented and introduce data elaboration in the ESI PAM-RTM software. Experimental campaigns for reinforcement permeabilities and resin viscosity measurement are presented and discussed. Finally, the obtained data are implemented in the software and then compared to experimental results in order to validate the described methodology.
Inorganic Mercury and Methyl-Mercury Uptake and Effects in the Aquatic Plant Elodea nuttallii: A Review of Multi-Omic Data in the Field and in Controlled Conditions
Authors: Cosio Claudia
Published: March 2020

(1) Background: Mercury is a threat for the aquatic environment. Nonetheless, the entrance of Hg into food webs is not fully understood. Macrophytes are both central for Hg entry in food webs and are seen as good candidates for biomonitoring and bioremediation; (2) Methods: We review the knowledge gained on the uptake and effects of inorganic Hg (IHg) and methyl-Hg (MMHg) in the macrophyte Elodea nuttallii found in temperate freshwaters; (3) Results: E. nuttallii bioaccumulates IHg and MMHg, but IHg shows a higher affinity to cell walls. At the individual level, IHg reduced chlorophyll, while MMHg increased anthocyanin. Transcriptomics and metabolomics in shoots revealed that MMHg regulated a higher number of genes than IHg. Proteomics and metabolomics in cytosol revealed that IHg had more effect than MMHg; (4) Conclusions: MMHg and IHg show different cellular toxicity pathways. MMHg’s main impact appears on the non-soluble compartment, while IHg’s main impact happens on the soluble compartment. This is congruent with the higher affinity of IHg with dissolved OM (DOM) or cell walls. E. nuttallii is promising for biomonitoring, as its uptake and molecular responses reflect exposure to IHg and MMHg. More generally, multi-omics approaches identify cellular toxicity pathways and the early impact of sublethal pollution.
Unsteady Aerodynamic Characteristics Simulations of Rotor Airfoil under Oscillating Freestream Velocity
Authors: Wang Qing , Zhao Qijun
Published: March 2020

The dynamic stall characteristics of rotor airfoil are researched by employing unsteady Reynolds-Averaged Navier-Stokes (RANS) method under oscillating freestream velocity conditions. In order to simulate the oscillating freestream velocity of airfoil under dynamic stall conditions, the moving-embedded grid method is employed to simulate the oscillating velocity. By comparing the simulated dynamic stall characteristics of two-dimensional airfoil and three-dimensional rotor, it is indicated that the dynamic stall characteristics of airfoil under oscillating freestream velocity reflect the actual dynamic stall characteristics of rotor airfoil in forward flight more accurately. By comparing the simulated results of OA209 airfoil under coupled freestream velocity/pitching oscillation conditions, it is indicated that the dynamic stall characteristics of airfoil associate with the critical value of Cp peaks (i.e., the dynamic stall characteristics of OA209 airfoil would be enhanced when the maximum negative pressure is larger than −1.08, and suppressed when this value is smaller than −1.08). By comparing the characteristics of vortices under different oscillating velocities, it indicates that the dissipation rate of leading edge vortex presents as exponent characteristics, and it is not sensitive to different oscillating velocities.
Cancer Development and Damped Electromagnetic Activity
Authors: Pokorný Jiří , Pokorný Jan , Kobilková Jitka , Jandová Anna , Holaj Robert
Published: March 2020

Cancer can be initiated in a cell or a fibroblast by short-circuiting of the cellular electromagnetic field by various fibers, parasitic energy consumption, virus infections, and mitochondrial defects, leading to a damped cellular electromagnetic field. Except short-circuiting (e.g., by asbestos fibers), the central process is mitochondrial dysfunction in cancer cells (the Warburg effect) or in fibroblasts associated with a cancer cell (the reverse Warburg effect), critically lowered respiration, reversed polarity of the ordered water layers around mitochondria, and damped electromagnetic activity of the affected cells. Frequency and power changes of the generated electromagnetic field result in broken communication between cells and possibly in reduced control over chemical reactions, with an increased probability of random genome mutations. An interdisciplinary framework of phenomena related to cancer development is presented, with special attention to the causes and consequences of disturbed cellular electromagnetic activity. Our framework extends the current knowledge of carcinogenesis, to clarify yet unexplained phenomena leading to genome mutation and cancer initiation.
An Optimized Brain-Based Algorithm for Classifying Parkinson’s Disease
Authors: Olivares Rodrigo , Munoz Roberto , Soto Ricardo , Crawford Broderick , Cárdenas Diego , Ponce Aarón , Taramasco Carla
Published: March 2020

During the last years, highly-recognized computational intelligence techniques have been proposed to treat classification problems. These automatic learning approaches lead to the most recent researches because they exhibit outstanding results. Nevertheless, to achieve this performance, artificial learning methods firstly require fine tuning of their parameters and then they need to work with the best-generated model. This process usually needs an expert user for supervising the algorithm’s performance. In this paper, we propose an optimized Extreme Learning Machine by using the Bat Algorithm, which boosts the training phase of the machine learning method to increase the accuracy, and decreasing or keeping the loss in the learning phase. To evaluate our proposal, we use the Parkinson’s Disease audio dataset taken from UCI Machine Learning Repository. Parkinson’s disease is a neurodegenerative disorder that affects over 10 million people. Although its diagnosis is through motor symptoms, it is possible to evidence the disorder through variations in the speech using machine learning techniques. Results suggest that using the bio-inspired optimization algorithm for adjusting the parameters of the Extreme Learning Machine is a real alternative for improving its performance. During the validation phase, the classification process for Parkinson’s Disease achieves a maximum accuracy of 96.74% and a minimum loss of 3.27%.
Gut–Brain Axis: Focus on Neurodegeneration and Mast Cells
Authors: Conte Carmela , Sichetti Marzia , Traina Giovanna
Published: March 2020

Many studies highlighted that a bidirectional communication between the gut and the central nervous system (CNS) exists. A vigorous immune response to antigens must be avoided, and pathogenic organisms crossing the gut barrier must be detected and killed. For this reason, the immune system developed fine mechanisms able to maintain this delicate balance. The microbiota is beneficial to its host, providing protection against pathogenic bacteria. It is intimately involved in numerous aspects of host physiology, from nutritional status to behavior and stress response. In the last few years, the implication of the gut microbiota and its bioactive microbiota-derived molecules in the progression of multiple diseases, as well as in the development of neurodegenerative disorders, gained increasing attention. The purpose of this review is to provide an overview of the gut microbiota with particular attention toward neurological disorders and mast cells. Relevant roles are played by the mast cells in neuroimmune communication, such as sensors and effectors of cytokines and neurotransmitters. In this context, the intake of beneficial bacterial strains as probiotics could represent a valuable therapeutic approach to adopt in combination with classical therapies. Further studies need to be performed to understand if the gut bacteria are responsible for neurological disorders or if neurological disorders influence the bacterial profile.
Fence-Sitting and an Opportunity to Unsettle the Settled: Placing Critical Pressure on Creative Holography
Authors: Pepper Andrew
Published: March 2020

The field of creative holography is not known for its critical introspection [...]
A Preliminary Study of Cu Exposure Effects upon Alzheimer’s Amyloid Pathology
Authors: Pilozzi Alexander , Yu Zhanyang , Carreras Isabel , Cormier Kerry , Hartley Dean , Rogers Jack , Dedeoglu Alpaslan , Huang Xudong
Published: March 2020

A large body of evidence indicates that dysregulation of cerebral biometals (Fe, Cu, Zn) and their interactions with amyloid precursor protein (APP) and Aβ amyloid may contribute to the Alzheimer’s disease (AD) Aβ amyloid pathology. However, the molecular underpinnings associated with the interactions are still not fully understood. Herein we have further validated the exacerbation of Aβ oligomerization by Cu and H2O2 in vitro. We have also reported that Cu enhanced APP translations via its 5′ untranslated region (5′UTR) of mRNA in SH-SY5Y cells, and increased Aβ amyloidosis and expression of associated pro-inflammatory cytokines such as MCP-5 in Alzheimer’s APP/PS1 doubly transgenic mice. This preliminary study may further unravel the pathogenic role of Cu in Alzheimer’s Aβ amyloid pathogenesis, warranting further investigation.
New Insights into Mechanisms of Long-term Protective Anti-tumor Immunity Induced by Cancer Vaccines Modified by Virus Infection
Authors: Schirrmacher Volker
Published: March 2020

The topic is how to achieve long-term protective anti-tumor immunity by anti-cancer vaccination and what are its mechanisms. Cancer vaccines should instruct the immune system regarding relevant cancer targets and contain signals for innate immunity activation. Of central importance is T-cell mediated immunity and thus a detailed understanding of cognate interactions between tumor antigen (TA)-specific T cells and TA-presenting dendritic cells. Microbes and their associated molecular patterns initiate early inflammatory defense reactions that can contribute to the activation of antigen-presenting cells (APCs) and to costimulation of T cells. The concommitant stimulation of naive TA-specific CD4+ and CD8+ T cells with TAs and costimulatory signals occurs in T-APC clusters that generate effectors, such as cytotoxic T lymphocytes and T cell mediated immunological memory. Information about how such memory can be maintained over long times is updated. The role that the bone marrow with its specialized niches plays for the survival of memory T cells is emphasized. Examples are presented that demonstrate long-term protective anti-tumor immunity can be achieved by post-operative vaccination with autologous cancer vaccines that are modified by virus infection.
A Study of the Mechanisms of Guaiacol Pyrolysis Based on Free Radicals Detection Technology
Authors: Li Guoxiang , Luo Zhongyang , Wang Wenbo , Cen Jianmeng
Published: March 2020

In order to understand the reaction mechanism of lignin pyrolysis, the pyrolysis process of guaiacol (o-methoxyphenol) as a lignin model compound was studied by free radical detection technology (electron paramagnetic resonance, EPR) in this paper. It was proven that the pyrolysis reaction of guaiacol is a free radical reaction, and the free radicals which can be detected mainly by EPR are methyl radicals. This paper proposes a process in which four free radicals (radicals 1- C6H4(OH)O*, radicals 5- C6H4(OCH3)O*, methyl radicals, and hydrogen radicals) are continuously rearranged during the pyrolysis of guaiacol.
An Ecolabel for the World Heritage Brand? Developing a Climate Communication Recognition Scheme for Heritage Sites
Authors: Lafrenz Samuels Kathryn , Platts Ellen J.
Published: March 2020

This study develops a climate communication recognition scheme (CCRS) for United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage Sites (WHS), in order to explore the communicative power of heritage to mobilize stakeholders around climate change. We present this scheme with the aim to influence site management and tourist decision-making by increasing climate awareness at heritage sites and among visitors and encouraging the incorporation of carbon management into heritage site management. Given the deficits and dysfunction in international governance for climate mitigation and inspired by transnational environmental governance tools such as ecolabels and environmental product information schemes, we offer “climate communication recognition schemes” as a corollary tool for transnational climate governance and communication. We assess and develop four dimensions for the CCRS, featuring 50 WHS: carbon footprint analysis, narrative potential, sustainability practices, and the impacts of climate change on heritage resources. In our development of a CCRS, this study builds on the “branding” value and recognition of UNESCO World Heritage, set against the backdrop of increasing tourism—including the projected doubling of international air travel in the next 15–20 years—and the implications of this growth for climate change. The CCRS, titled Climate Footprints of Heritage Tourism, is available online as an ArcGIS StoryMap.
Monitoring Climate Change in World Heritage Properties: Evaluating Landscape-Based Approach in the State of Conservation System
Authors: Guzman Paloma , Fatorić Sandra , Ishizawa Maya
Published: March 2020

Climate change is increasingly being recognized as a threat to natural and cultural World Heritage (WH) sites worldwide. Through its interaction with other stressors, climate change accelerates existing risks while also creating new obstacles. A more considerable focus is needed in both research and practice to explore proactive measures for combatting this issue (e.g., mitigation and actions prior to impacts occurring). World Heritage values in climate change decision-making processes is an important factor in this regard. This paper explores a discussion of climate change within the WH monitoring system. It offers an overview of practice based on the extent to which WH properties (natural, mixed and cultural) implement landscape-based approaches alongside the conservation and management of their outstanding universal value within the context of climate uncertainty and environmental change. Landscape approaches are gaining importance in the WH conservation system, where they aim to provide concepts and tools for managing heritage toward sustainable practices. This research analyses the state of conservation reports and provides an overview of practice across time, categories and geographical regions. Based on a theoretical approach, empirical analyses identify four landscape principles that are increasingly shaping the debate around climate change issues in WH properties. Although these are highly relevant to advancing much-needed collaboration among scientific disciplines and governance sectors, we argue that further understanding is required on the transformational process of heritage values, as well as on the nature–culture relationship, in order to underpin heritage as a source for local resilience and climate mitigation.
Interoperability Challenges in the Cybersecurity Information Sharing Ecosystem
Authors: Rantos Konstantinos , Spyros Arnolnt , Papanikolaou Alexandros , Kritsas Antonios , Ilioudis Christos , Katos Vasilios
Published: March 2020

Threat intelligence helps businesses and organisations make the right decisions in their fight against cyber threats, and strategically design their digital defences for an optimised and up-to-date security situation. Combined with advanced security analysis, threat intelligence helps reduce the time between the detection of an attack and its containment. This is achieved by continuously providing information, accompanied by data, on existing and emerging cyber threats and vulnerabilities affecting corporate networks. This paper addresses challenges that organisations are bound to face when they decide to invest in effective and interoperable cybersecurity information sharing and categorises them in a layered model. Based on this, it provides an evaluation of existing sources that share cybersecurity information. The aim of this research is to help organisations improve their cyber threat information exchange capabilities, to enhance their security posture and be more prepared against emerging threats.
The Surface-Roughness Effects on Light Beam Interactions between the CsI Phosphor and Optical Sensing Materials
Authors: Liaparinos Panagiotis , David Stratos
Published: March 2020

In digital phosphor-based imaging modalities, one important intermediate stage is the optical coupling between the phosphor material and the optical sensor. The performance of the optical compatibility is affected by surface-roughness issues, for which further research should be paid. This paper investigates the surface-roughness influence between the CsI phosphor material and the optical sensing materials (i.e., the silicon dioxide—SiO2, the indium tin oxide—ITO, and the indium gallium arsenide—InGaAs) employed in several image devices. Results showed that for all sensing materials, the transmission factor t of the optical signal follows qualitatively the variation of their refractive indexes and quantitatively the variation of the surface roughness and the incident polar angle. Finally, with respect to light wavelength, the curve of variation was found to be continuous for ITO and SiO2 sensing materials; however, lower and sharper variations were observed in the first case.
Twist-Bend Nematogenic Supramolecular Dimers and Trimers Formed by Hydrogen Bonding
Authors: Walker Rebecca , Pociecha Damian , Martinez-Felipe Alfonso , Storey John MD , Gorecka Ewa , Imrie Corrie T
Published: March 2020

A selection of novel non-symmetric supramolecular liquid crystal dimers and trimers formed by hydrogen-bonding have been prepared and their phase behaviour characterised by polarised optical microscopy, X-ray diffraction and temperature-dependent Fourier-transform infrared spectroscopy. We mix the bent twist-bend nematogen 4-[6-(4’-cyanobiphenyl-4-yl) hexyloxy]-benzoic acid (CB6OBA) with a series of small stilbazole-based compounds 4-[(E)-2-(n-alkoxyphenyl)ethenyl]pyridines (nOS) of varying terminal chain length (n) to obtain the CB6OBA:nOS complexes. Complexes with n ≤ 7 exhibit nematic and twist-bend nematic behaviour, followed on cooling by a smectic C phase for n = 4–7, and finally, a hexatic-type smectic X phase for n = 3–7. Mixtures with n = 8–10 exhibit a smectic A phase below the conventional nematic phase, and on further cooling, a biaxial smectic Ab phase and the same hexatic-type SmX phase. Supramolecular trimers, CB6OBA:CB6OS and CB6OBA:1OB6OS, formed between CB6OBA and dimeric stilbazoles [(E)-2-(4-{[6-(4’-methoxy[1,1’-biphenyl]-4-yl)hexyl]oxy}phenyl)ethenyl]pyridine (1OB6OS) or 4-[(E)-4’-(6-{4-[(E)-2-(pyridin-4-yl)ethenyl]phenoxy}hexyl)[1,1’-biphenyl]-4- carbonitrile (CB6OS), exhibit nematic and twist-bend nematic phases, and are the first hydrogen-bonded trimers consisting of unlike donor and acceptor fragments to do so.
Offshore Neopycnodonte Oyster Reefs in the Mediterranean Sea
Authors: Angeletti Lorenzo , Taviani Marco
Published: March 2020

Oysters are important ecosystem engineers best known to produce large bioconstructions at shallow depth, whilst offshore deep-subtidal oyster reefs are less widely known. Oyster reefs engineered by Neopycnodonte cochlear (family Gryphaeidae) occur at various sites in the Mediterranean Sea, between 40 and 130 m water depths. Remotely Operated Vehicle surveys provide new insights on this rather neglected reef types with respect to their shape, dimensions and associated biodiversity. We suggest that these little contemplated reefs should be taken in due consideration for protection.
Contribution to the Knowledge on Distribution of Tardigrada in Turkey
Authors: Berdi Duygu , Altındağ Ahmet
Published: March 2020

Tardigrades have been occasionally studied in Turkey since 1973. However, species number and distribution remain poorly known. In this study, distribution of Tardigrades in the province of Karabük, which is located in northern coast (West Black Sea Region) of Turkey, was carried out. Two moss samples were collected from the entrance of the Bulak (Mencilis) Cave. A total of 30 specimens and 14 eggs were extracted. Among the specimens; Echiniscus granulatus (Doyère, 1840) and Diaforobiotus islandicus islandicus (Richters, 1904) are new records for Karabük. Furthermore, this study also provides a current checklist of tardigrade species reported from Turkey, indicating their localities, geographic distribution and taxonomical comments.
Superiority of Droplet Digital PCR Over Real-Time Quantitative PCR for JAK2 V617F Allele Mutational Burden Assessment in Myeloproliferative Neoplasms: A Retrospective Study
Authors: La Rocca Francesco , Grieco Vitina , Ruggieri Vitalba , Zifarone Emanuela , Villani Oreste , Zoppoli Pietro , Russi Sabino , Laurino Simona , Falco Geppino , Calice Giovanni , Marinaccio Anna , Natalicchio Maria Iole , Albano Francesco , Musto Pellegrino
Published: March 2020

JAK2 V617F mutational status is an essential diagnostic index in myeloproliferative neoplasms (MPNs). Although widely used for detection of JAK2 V617F mutation in peripheral blood (PB), sensitive real-time quantitative PCR (qPCR) presents some methodological limitations. Recently, emerging alternative technologies, like digital droplet PCR (ddPCR), have been reported to overcome some of qPCR’s technical drawbacks. The purpose of this study was to compare the diagnostic utility of ddPCR to qPCR for JAK2 V617F detection and quantification in samples from MPNs patients. Sensitivity and specificity of qPCR and ddPCR in the detection of the mutation were assessed by using a calibrator panel of mutated DNA on 195 JAK2 positive MPN samples. Based on our results, ddPCR proved to be a suitable, precise, and sensitive method for detection and quantification of the JAK2 V617F mutation.
Circulating Tumor Cells as a Tool of Minimal Residual Disease Can Predict Lung Cancer Recurrence: A longitudinal, Prospective Trial
Authors: Wu Ching-Yang , Lee Chia-Lin , Wu Ching-Feng , Fu Jui-Ying , Yang Cheng-Ta , Wen Chi-Tsung , Liu Yun-Hen , Liu Hui-Ping , Hsieh Jason Chia-Hsun
Published: March 2020

Background: The role of circulating tumor cells (CTCs) for predicting the recurrence of cancer in lung cancer patients after surgery remains unclear. Methods: A negatively selected protocol of CTC identification was applied. For all the enrolled patients, CTC testing was performed before and after surgery on the operation day (day 0), postoperative day 1, and day 3. The daily decline and trend of CTCs were analyzed to correlate with cancer relapse. The mixed model repeated measures (MMRM) adjusted by cancer characteristics was applied for statistical significance. Results: Fifty patients with lung mass undergoing surgery were enrolled. Among 41 primary lung cancers, 26 (63.4%) were pathological stage Tis and I. A total of 200 CTC tests were performed. MMRM analysis indicated that surgery could contribute to a CTC decline after surgery in all patients with statistical significance (p = 0.0005). The daily decrease of CTCs was statistically different between patients with and without recurrence (p = 0.0068). An early rebound of CTC counts on postoperative days 1 and 3 was associated with recurrence months later. Conclusion: CTC testing can potentially serve as a tool for minimal residual disease detection in early-staged lung cancer after curative surgery.
Prevalence and Occlusal Risk Factors for Fractured Incisors among 11–12-Year-Old Children in the Trinidad and Tobago Population
Authors: Hoyte Trudee , Kowlessar Anne , Ali Anil , Bearn David
Published: March 2020

This cross-sectional survey was carried out to ascertain the prevalence of fractured incisors in 11–12-year-olds. In addition we explored the relationship with overjet, incompetent lips, incisor inclination and to determine if there was any association with ethnicity and gender. All permanent incisors were examined in 672 children comprising 356 females (53.1%) and 315 males (46.9%). The sample comprised 11–12-year-olds in high schools across Trinidad and Tobago. Statistical analysis was undertaken using Chi-square test, independent t-test, and binary logistic regression. The prevalence of fractured incisors was 18.9%. Boys presented with an increased incidence of fractured incisors than girls. 86.3% of dental trauma was untreated. The average overjet of subjects with fractured incisors was 4.2 mm. 18.62% of subjects with fractured incisors had incompetent lips. The most common malocclusion (18.81%) with fractured incisors was class 2 division 1. The Afro-Trinidadian ethnicity had the highest prevalence of fractured incisors (11.0%) when compared to mixed ethnicities, which was statistically significant. Maxillary central incisors were the most commonly injured teeth. Most patients delayed in seeking dental treatment for fractured incisors in our population. Early orthodontic treatment is recommended to help reduce the risk of dental trauma.
Mahalanobis Distances on Factor Model Based Estimation
Authors: Dai Deliang
Published: March 2020

A factor model based covariance matrix is used to build a new form of Mahalanobis distance. The distribution and relative properties of the new Mahalanobis distances are derived. A new type of Mahalanobis distance based on the separated part of the factor model is defined. Contamination effects of outliers detected by the new defined Mahalanobis distances are also investigated. An empirical example indicates that the new proposed separated type of Mahalanobis distances predominate the original sample Mahalanobis distance.
Less but Better? Teaching Maths in Further Education and Collateral Growth
Authors: Nixon Lawrence , Cooper John B.
Published: March 2020

The paper presents and explores the experience of maths students studying in a context shaped by a core concept maths curriculum. The three vignettes that illuminate experience are drawn from a larger research project that worked with five teachers and 630 learners aged 16–18 in Further Education classrooms in England. Analysis involved distinguishing different understandings of being good at maths, different views of a good maths curriculum and identifying enablers and barriers to being a ‘successful’ maths student. Dewey’s ideas about focused experience and collateral learning were used to deepen this analysis. The paper reports a surprising finding. In some cases, students recognize the positive impact learning maths had on developing their wider human capabilities. Maths teachers in England, working in the context of ‘new public management’, may find reasons to take heart from the accounts of teaching and learning presented. For the international reader who is grappling with the challenge of reengaging maths students, the accounts of what matters to students could spur a reconsideration of priorities and practice.
An Extensive Review of Multilevel Inverters Based on Their Multifaceted Structural Configuration, Triggering Methods and Applications
Authors: Sunddararaj Suvetha Poyyamani , Srinivasarangan Rangarajan Shriram , N Subashini
Published: March 2020

Power electronic converters are used to transform one form of energy to another. They are classified into four types depending upon the nature of the input and output voltages. The inverter is one among those types; it converts direct electrical current into alternating electrical current at desired frequency. Conventional types of inverters are capable of producing voltage at the output terminal that can only switch between two levels. The range of output voltage generated at the output is low when they are used for high power applications. To improve the voltage profile and efficiency of the overall system, multilevel inverters (MLIs) are introduced. In multilevel inverters the voltage at the output terminal is generated from several DC voltage levels fed at its input. The generated output is more appropriate to a sine wave and the dv/dt rating is also less leading to the reduction in EMI. Though they possess many advantages compared to the conventional inverters, the structural complexity and triggering techniques involved in designing multilevel inverters are high. Many studies are being carried out in defining new topologies of MLI with reduced switch as well as with the implementation of different PWM techniques. This paper will provide an extensive review on variety of MLI configurations based on the parameters such as the number of switches, switching techniques, symmetric, asymmetric, hybrid topologies, configurations based on applications, THD and power quality.
Framework for Delay Guarantee in Multi-Domain Networks Based on Interleaved Regulators
Authors: Joung Jinoo
Published: March 2020

The key to the asynchronous traffic shaping (ATS) technology being standardized in IEEE 802.1 time sensitive network (TSN) task group (TG) is the theorem that a minimal interleaved regulator (IR), attached to a FIFO system does not increase delay upper bound while suppresses the burst accumulation. In this work it is observed that the FIFO system can be a network for flows that share same input/output ports and same queues of the network, and are treated with a scheduling scheme that guarantees the FIFO property within a queue. Based on this observation, a framework for delay bound guarantee is further proposed, in which the networks with flow aggregates (FAs) scheduling and minimal IRs per FA attached at the network edge are interconnected. The framework guarantees the end-to-end delay bound with reduced complexity, compared to the traditional flow-based approach. Numerical analysis shows that the framework yields smaller bound than both the flow-based frameworks such as the integrated services (IntServ) and the class-based ATS, at least in the networks with identical flows and symmetrical topology.
A Study on Design and Case Analysis of Virtual Reality Contents Developer Training based on Industrial Requirements
Authors: Kang HoSeong , Kim JungYoon
Published: March 2020

The fourth industrial revolution has evolved at an exponential pace that has raised the level of virtual reality (VR) technology industry development. The VR-based contents industry has significantly grown in convergence with other areas; however, its production suffers from lack of skilled human resources. In this regard, this paper provides a study on educational courses dealing with VR contents production. The study identifies the current status of VR contents industry and evaluates the training contents currently being used at relevant training institutions. As a result, an industrial demand-customized educational model and its operations based on cooperative relationship between training institutions and industrial companies by means of cooperative projects and mentoring was designed. The outcome of the evaluation on the results of training courses operation served as a basis for the design of the proposed educational model and indicates the effectiveness of the training.
Resource Allocation with a Rate Guarantee Constraint in Device-to-Device Underlaid Cellular Networks
Authors: Kwon Doyle , Kim Duk Kyung
Published: March 2020

Device-to-device (D2D) communication is a crucial technique for various proximity services. In addition to high-rate transmission and high spectral efficiency, a minimum data rate is increasingly required in various applications, such as gaming and real-time audio/video transmission. In this paper, we consider D2D underlaid cellular networks and aim to minimize the total channel bandwidth while every user equipment (UE) needs to achieve a pre-determined target data rate. The optimization problem is jointly involved with matching a cellular UE (CU) to a D2D UE (DU), and with channel assignment and power control. The optimization problem is decoupled into two suboptimization problems to solve power control and channel assignment problems separately. For arbitrary matching of CU, DU, and channel, the minimum channel bandwidth of the shared channel is derived based on signal-to-interference-plus-noise ratio (SINR)-based power control. The channel assignment is a three-dimensional (3-D) integer programming problem (IPP) with a triple (CU, DU, channel). We apply Lagrangian relaxation, and then decompose the 3-D IPP into two two-dimensional (2-D) linear programming problems (LPPs). From intensive numerical results, the proposed resource allocation scheme outperforms the random selection and greedy schemes in terms of average channel bandwidth. We investigate the impact of various parameters, such as maximum D2D distance and the number of channels.
Optimizing the Performance of Breast Cancer Classification by Employing the Same Domain Transfer Learning from Hybrid Deep Convolutional Neural Network Model
Authors: Alzubaidi Laith , Al-Shamma Omran , Fadhel Mohammed A. , Farhan Laith , Zhang Jinglan , Duan Ye
Published: March 2020

Breast cancer is a significant factor in female mortality. An early cancer diagnosis leads to a reduction in the breast cancer death rate. With the help of a computer-aided diagnosis system, the efficiency increased, and the cost was reduced for the cancer diagnosis. Traditional breast cancer classification techniques are based on handcrafted features techniques, and their performance relies upon the chosen features. They also are very sensitive to different sizes and complex shapes. However, histopathological breast cancer images are very complex in shape. Currently, deep learning models have become an alternative solution for diagnosis, and have overcome the drawbacks of classical classification techniques. Although deep learning has performed well in various tasks of computer vision and pattern recognition, it still has some challenges. One of the main challenges is the lack of training data. To address this challenge and optimize the performance, we have utilized a transfer learning technique which is where the deep learning models train on a task, and then fine-tune the models for another task. We have employed transfer learning in two ways: Training our proposed model first on the same domain dataset, then on the target dataset, and training our model on a different domain dataset, then on the target dataset. We have empirically proven that the same domain transfer learning optimized the performance. Our hybrid model of parallel convolutional layers and residual links is utilized to classify hematoxylin–eosin-stained breast biopsy images into four classes: invasive carcinoma, in-situ carcinoma, benign tumor and normal tissue. To reduce the effect of overfitting, we have augmented the images with different image processing techniques. The proposed model achieved state-of-the-art performance, and it outperformed the latest methods by achieving a patch-wise classification accuracy of 90.5%, and an image-wise classification accuracy of 97.4% on the validation set. Moreover, we have achieved an image-wise classification accuracy of 96.1% on the test set of the microscopy ICIAR-2018 dataset.
Peak Shaving through Battery Storage for Low-Voltage Enterprises with Peak Demand Pricing
Authors: Papadopoulos Vasileios , Knockaert Jos , Develder Chris , Desmet Jan
Published: March 2020

The renewable energy transition has introduced new electricity tariff structures. With the increased penetration of photovoltaic and wind power systems, users are being charged more for their peak demand. Consequently, peak shaving has gained attention in recent years. In this paper, we investigated the potential of peak shaving through battery storage. The analyzed system comprises a battery, a load and the grid but no renewable energy sources. The study is based on 40 load profiles of low-voltage users, located in Belgium, for the period 1 January 2014, 00:00–31 December 2016, 23:45, at 15 min resolution, with peak demand pricing. For each user, we studied the peak load reduction achievable by batteries of varying energy capacities (kWh), ranging from 0.1 to 10 times the mean power (kW). The results show that for 75% of the users, the peak reduction stays below 44% when the battery capacity is 10 times the mean power. Furthermore, for 75% of the users the battery remains idle for at least 80% of the time; consequently, the battery could possibly provide other services as well if the peak occurrence is sufficiently predictable. From an economic perspective, peak shaving looks interesting for capacity invoiced end users in Belgium, under the current battery capex and electricity prices (without Time-of-Use (ToU) dependency).
Application of Promising Electrode Materials in Contact with a Thin-Layer ZrO2-Based Supporting Electrolyte for Solid Oxide Fuel Cells
Authors: Osinkin Denis A. , Antonova Ekaterina P. , Lesnichyova Alena S. , Tropin Evgeniy S. , Chernov Mikhail E. , Chernov Efim I. , Farlenkov Andrey S. , Khodimchuk Anna V. , Eremin Vadim A. , Kovrova Anastasia I. , Kuzmin Anton V. , Ananyev Maxim V.
Published: March 2020

The paper presents the results of an investigation into thin single- and triple-layer ZrO2-Sc2O3-based electrolytes prepared using the tape-casting technique in combination with promising electrodes based on La2NiO4+δ and Ni-Ce0.8Sm0.2O2-δ materials. It is shown that pressing and joint sintering of single electrolyte layers allows multilayer structures to be obtained that are free of defects at the layer interface. Electrical conductivity measurements of a triple-layer electrolyte carried out in longitudinal and transverse directions with both direct and alternating current showed resistance of the interface between the layers on the total resistance of the electrolyte to be minimal. Long-term tests have shown that the greatest degradation in resistance over time occurs in the case of an electrolyte with a tetragonal structure. Symmetrical electrochemical cells with electrodes fabricated using a screen-printing method were examined by means of electrochemical impedance spectroscopy. The polarization resistance of the electrodes was 0.45 and 0.16 Ohm∙cm2 at 800 °C for the fuel and oxygen electrodes, respectively. The distribution of relaxation times method was applied for impedance data analysis. During tests of a single solid oxide fuel cell comprising a supporting triple-layer electrolyte having a thickness of 300 microns, a power density of about 160 mW/cm2 at 850 °C was obtained using wet hydrogen as fuel and air as an oxidizing gas.