bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling DNA Methylation Profiles through a Dynamic Equilibrium between Methylation and Demethylation
Authors: De Riso Giulia , Fiorillo Damiano Francesco Giuseppe , Fierro Annalisa , Cuomo Mariella , Chiariotti Lorenzo , Miele Gennaro , Cocozza Sergio
Published: September 2020

DNA methylation is a heritable epigenetic mark that plays a key role in regulating gene expression. Mathematical modeling has been extensively applied to unravel the regulatory mechanisms of this process. In this study, we aimed to investigate DNA methylation by performing a high-depth analysis of particular loci, and by subsequent modeling of the experimental results. In particular, we performed an in-deep DNA methylation profiling of two genomic loci surrounding the transcription start site of the D-Aspartate Oxidase and the D-Serine Oxidase genes in different samples (n = 51). We found evidence of cell-to-cell differences in DNA methylation status. However, these cell differences were maintained between different individuals, which indeed showed very similar DNA methylation profiles. Therefore, we hypothesized that the observed pattern of DNA methylation was the result of a dynamic balance between DNA methylation and demethylation, and that this balance was identical between individuals. We hence developed a simple mathematical model to test this hypothesis. Our model reliably captured the characteristics of the experimental data, suggesting that DNA methylation and demethylation work together in determining the methylation state of a locus. Furthermore, our model suggested that the methylation status of neighboring cytosines plays an important role in this balance.
Hepatic Lipidomics and Molecular Imaging in a Murine Non-Alcoholic Fatty Liver Disease Model: Insights into Molecular Mechanisms
Authors: Rodríguez-Calvo Ricardo , Samino Sara , Girona Josefa , Martínez-Micaelo Neus , Ràfols Pere , García-Altares María , Guaita-Esteruelas Sandra , Junza Alexandra , Heras Mercedes , Yanes Oscar , Correig Xavier , Masana Lluis
Published: September 2020

An imbalance between hepatic fatty acid uptake and removal results in ectopic fat accumulation, which leads to non-alcoholic fatty liver disease (NAFLD). The amount and type of accumulated triglycerides seem to play roles in NAFLD progression; however, a complete understanding of how triglycerides contribute to NAFLD evolution is lacking. Our aim was to evaluate triglyceride accumulation in NAFLD in a murine model and its associations with molecular mechanisms involved in liver damage and adipose tissue-liver cross talk by employing lipidomic and molecular imaging techniques. C57BL/6J mice fed a high-fat diet (HFD) for 12 weeks were used as a NAFLD model. Standard-diet (STD)-fed animals were used as controls. Standard liver pathology was assessed using conventional techniques. The liver lipidome was analyzed by liquid chromatography–mass spectrometry (LC–MS) and laser desorption/ionization–mass spectrometry (LDI–MS) tissue imaging. Liver triglycerides were identified by MS/MS. The transcriptome of genes involved in intracellular lipid metabolism and inflammation was assessed by RT-PCR. Plasma leptin, resistin, adiponectin, and FABP4 levels were determined using commercial kits. HFD-fed mice displayed increased liver lipid content. LC–MS analyses identified 14 triglyceride types that were upregulated in livers from HFD-fed animals. Among these 14 types, 10 were identified in liver cross sections by LDI–MS tissue imaging. The accumulation of these triglycerides was associated with the upregulation of lipogenesis and inflammatory genes and the downregulation of β-oxidation genes. Interestingly, the levels of plasma FABP4, but not of other adipokines, were positively associated with 8 of these triglycerides in HFD-fed mice but not in STD-fed mice. Our findings suggest a putative role of FABP4 in the liver-adipose tissue cross talk in NAFLD.
4-Hydroxynonenal Immunoreactivity Is Increased in the Frontal Cortex of 5XFAD Transgenic Mice
Authors: Shin Sang-Wook , Kim Dong-Hee , Jeon Won Kyung , Han Jung-Soo
Published: September 2020

Oxidative stress was implicated in the functional impairment of the frontal cortex observed in early Alzheimer’s disease (AD). To elucidate this role in an animal AD model, we assessed cognitive function of 4-month-old five familial AD (5XFAD) transgenic (Tg) mice using a learning strategy-switching task requiring recruitment of the frontal cortex and measuring levels of 4-hydroxy-2-trans-nonenal (4-HNE), a marker of oxidative stress, in their frontal cortex. Mice were sequentially trained in cued/response and place/spatial versions of the water maze task for four days each. 5XFAD and non-Tg mice exhibited equal performance in cued/response training. However, 5XFAD mice used spatial search strategy less than non-Tg mice in the spatial/place training. Immunoblot and immunofluorescence staining showed that 4-HNE levels increased in the frontal cortex, but not in the hippocampus and striatum, of 5XFAD mice compared to those in non-Tg mice. We report early cognitive deficits related to the frontal cortex and the frontal cortex’s oxidative damage in 4-month-old 5XFAD mice. These results suggest that 4-month-old 5XFAD mice be a useful animal model for the early diagnosis and management of AD.
Impact of the Design of Walls Made of Compressed Earth Blocks on the Thermal Comfort of Housing in Hot Climate
Authors: Hema Césaire , Messan Adamah , Lawane Abdou , Van Moeseke Geoffrey
Published: September 2020

This study investigated the impact of the design of wall systems, mainly made of compressed earth blocks (CEB), on the indoor thermal comfort of naturally ventilated housing in hot climates of Burkina Faso. Conventional housing was modeled and calibrated using the WUFI® Plus dynamic simulation tool based on typical field surveys and the literature. This allowed testing the ability of different wall designs to impact thermal comfort. Thermal discomfort was assessed through an adaptive approach and was based on the annual weighted exceedance hours of overheating. Six designs of walls made of CEB and other locally available materials were simulated and compared to those made of classical hollow concrete blocks. The results of the simulation reveal that the profiles of thermal discomfort vary depending on the wall designs and building spaces. Thus, the wall made, from the outside toward the inside surface, of plywood of 2 cm, an insulation layer of 5 cm and a CEB layer of 29 cm thickness is the most suitable for an annual reduction in overheating for the living room. Regarding the bedroom, the most suitable wall is made of a 14 cm CEB layer, 5 cm insulating layer and 2 cm wood layer from the outside toward the inside surface.
Gemcitabine and Platinum-Based Agents for the Prediction of Cancer-Associated Venous Thromboembolism: Results from the Vienna Cancer and Thrombosis Study
Authors: Moik Florian , van Es Nick , Posch Florian , Di Nisio Marcello , Fuereder Thorsten , Preusser Matthias , Pabinger Ingrid , Ay Cihan
Published: September 2020

Gemcitabine and platinum-based agents could increase the risk of venous thromboembolism (VTE) in patients with cancer. We evaluated the additive predictive utility of these agents towards cancer-associated VTE beyond a recently developed and externally validated clinical prediction model, which was based on tumor entity and continuous D-dimer levels. Analysis was performed in the derivation cohort of this model, obtained from the Vienna Cancer and Thrombosis Study (CATS), a prospective observational cohort study (n = 1409). Patients were followed for the occurrence of VTE for a maximum of two years. Competing-risk analysis was performed to obtain cumulative incidences and to conduct between-group comparisons of VTE risk. Cumulative two-year incidences of VTE were not elevated with gemcitabine treatment (10.2% vs. 7.5%, p = 0.148), whereas they were higher for platinum-based therapy (11.6% vs. 5.9%, p < 0.001). In a multivariable analysis, adjusting for tumor site category and D-dimer, gemcitabine was not associated with increased risk of VTE (subdistribution hazard ratio (SHR) 0.82, 95% confidence interval (CI) 0.53–1.28, p = 0.390), whereas platinum-based therapy predicted for a numerically increased VTE risk (SHR 1.44, 95% CI 0.96–2.17, p = 0.080). Similar results were obtained in a sensitivity analysis (updated cohort, n = 1870). Our findings suggest limited additional value of chemotherapy for the prediction of cancer-associated VTE, beyond a validated clinical prediction model.
Targeted Therapies for Melanoma
Authors: Smetana Karel , Lacina Lukáš , Kodet Ondřej
Published: September 2020

The incidence of cutaneous malignant melanoma (CMM) is significantly increasing worldwide.[...]
Tumors of the Central Nervous System: An Update
Authors: Mucignat-Caretta Carla
Published: September 2020

The brain may be affected by a variety of tumors of different grade, which originate from different cell types at distinct locations, thus impacting on the brain structure and function [...]
Insights into Differentiation of Melanocytes from Human Stem Cells and Their Relevance for Melanoma Treatment
Authors: Mirea Madalina , Eckensperger Stefan , Hengstschläger Markus , Mikula Mario
Published: September 2020

Malignant melanoma represents a highly aggressive form of skin cancer. The metastatic process itself is mostly governed by the so-called epithelial mesenchymal transition (EMT), which confers cancer cells migrative, invasive and resistance abilities. Since EMT represents a conserved developmental process, it is worthwhile further examining the nature of early developmental steps fundamental for melanocyte differentiation. This can be done either in vivo by analyzing the physiologic embryo development in different species or by in vitro studies of melanocytic differentiation originating from embryonic human stem cells. Most importantly, external cues drive progenitor cell differentiation, which can be divided in stages favoring neural crest specification or melanocytic differentiation and proliferation. In this review, we describe ectopic factors which drive human pluripotent stem cell differentiation to melanocytes in 2D, as well as in organoid models. Furthermore, we compare developmental mechanisms with processes described to occur during melanoma development. Finally, we suggest differentiation factors as potential co-treatment options for metastatic melanoma patients.
RNA Sequencing of Hepatobiliary Cancer Cell Lines: Data and Applications to Mutational and Transcriptomic Profiling
Authors: Scherer Dominique , Dávila López Marcela , Goeppert Benjamin , Abrahamsson Sanna , González Silos Rosa , Nova Igor , Marcelain Katherine , Roa Juan C. , Ibberson David , Umu Sinan U. , Rounge Trine Ballestad , Roessler Stephanie , Lorenzo Bermejo Justo
Published: September 2020

Cancer cell lines allow the identification of clinically relevant alterations and the prediction of drug response. However, sequencing data for hepatobiliary cancer cell lines in general, and particularly gallbladder cancer (GBC), are sparse. Here, we apply RNA sequencing to characterize 10 GBC, eight hepatocellular carcinoma, and five cholangiocarcinoma (CCA) cell lines. RNA extraction, quality control, library preparation, sequencing, and pre-processing of sequencing data were implemented using state-of-the-art techniques. Public data from the MSK-IMPACT database and a large cohort of Japanese biliary tract cancer patients were used to illustrate the usage of the released data. The total number of exonic mutations varied from 7207 for the cell line NOZ to 9760 for HuCCT1. Researchers planning experiments that require TP53 mutations could use the cell lines NOZ, OCUG-1, SNU308, or YoMi. Mz-Cha-1 showed mutations in ATM, SNU308 presented SMAD4 mutations, and the only investigated cell line that showed ARID1A mutations was GB-d1. SNU478 was the cell line with the global gene expression pattern most similar to GBC, intrahepatic CCA, and extrahepatic CCA. EGFR, KMT2D, and KMT2C generally presented a higher expression in the investigated cell lines than in Japanese primary GBC tumors. We provide the scientific community with detailed mutation and gene expression data, together with three showcase applications, with the aim of facilitating the design of future in vitro cell culture assays for research on hepatobiliary cancer.
Production of Levulinic Acid from Cellulose and Cellulosic Biomass in Different Catalytic Systems
Authors: Liu Chen , Lu Xuebin , Yu Zhihao , Xiong Jian , Bai Hui , Zhang Rui
Published: September 2020

The reasonable and effective use of lignocellulosic biomass is an important way to solve the current energy crisis. Cellulose is abundant in nature and can be hydrolyzed to a variety of important energy substances and platform compounds—for instance, glucose, 5-hydroxymethylfurfural (HMF), levulinic acid (LA), etc. As a chemical linker between biomass and petroleum processing, LA has become an ideal feedstock for the formation of liquid fuels. At present, some problems such as low yield, high equipment requirements, difficult separation, and serious environmental pollution in the production of LA from cellulose have still not been solved. Thus, a more efficient and green catalytic system of this process for industrial production is highly desired. Herein, we focus on the reaction mechanism, pretreatment, and catalytic systems of LA from cellulose and cellulosic biomass, and a series of existing technologies for producing LA are reviewed. On the other hand, the industrial production of LA is discussed in depth to improve the yield of LA and make the process economical and energy efficient. Additionally, practical suggestions for the enhancement of the stability and efficiency of the catalysts are also proposed. The use of cellulose to produce LA is consistent with the concept of sustainable development, and the dependence on fossil resources will be greatly reduced through the realization of this process route.
Polyhedral Effects on the Mass Activity of Platinum Nanoclusters
Authors: Kaatz Forrest H. , Bultheel Adhemar
Published: September 2020

We use a coordination-based kinetics model to look at the kinetics of the turnover frequency (TOF) for the oxygen reduction reaction (ORR) for platinum nanoclusters. Clusters of octahedral, cuboctahedral, cubic, and icosahedral shape and size demonstrate the validity of the coordination-based approach. The Gibbs adsorption energy is computed using an empirical energy model based on density functional theory (DFT), statistical mechanics, and thermodynamics. We calculate the coordination and size dependence of the Gibbs adsorption energy and apply it to the analysis of the TOF. The platinum ORR follows a Langmuir–Hinshelwood mechanism, and we model the kinetics using a thermodynamic approach. Our modeling indicates that the coordination, shape, and the Gibbs energy of adsorption all are important factors in replicating an experimental TOF. We investigate the effects of size and shape of some platinum polyhedra on the oxygen reduction reaction (ORR) and the effect on the mass activity. The data are modeled quantitatively using lognormal distributions. We provide guidance on how to account for the effects of different distributions due to shape when determining the TOF.
Enhanced Visible and Ultraviolet Light-Induced Gas-Phase Photocatalytic Activity of TiO2 Thin Films Modified by Increased Amount of Acetylacetone in Precursor Solution for Spray Pyrolysis
Authors: Spiridonova Jekaterina , Mere Arvo , Krunks Malle , Rosenberg Merilin , Kahru Anne , Danilson Mati , Krichevskaya Marina , Oja Acik Ilona
Published: September 2020

TiO2 thin films, modified by acetylacetone (AcacH) in solution, were deposited on glass substrate by ultrasonic spray pyrolysis and tested for photocatalytic activity in a multi-section continuous flow reactor by degradation of acetone and acetaldehyde under ultraviolet and visible light. The increase in molar ratio of AcacH in respect of titanium (IV) isopropoxide (TTIP) from 1:5 to 1:8 modified the electronic structure of the films, favoring enhanced photocatalytic activity. The photocatalytic activity was enhanced approximately twofold on the film with molar ratio 1:8 under both irradiations; the film completely oxidized 10 ppm of acetone and acetaldehyde. The photocatalytic efficacy of TiO2 films in oxidation of air pollutants was three times higher compared to the industrial glass Pilkington ActivTM. Moreover, all the synthesized films indicate antibacterial efficiency against E. coli of over 99% under ultraviolet. TiO2 film, with TTIP:AcacH molar ratio 1:8 having great possibility for its commercial use as a material for indoor air purification.
Deep Eutectic Solvents as Smart Cosubstrate in Alcohol Dehydrogenase-Catalyzed Reductions
Authors: Chanquia Santiago Nahuel , Huang Lei , García Liñares Guadalupe , Domínguez de María Pablo , Kara Selin
Published: September 2020

Alcohol dehydrogenase (ADH) catalyzed reductions in deep eutectic solvents (DESs) may become efficient and sustainable alternatives to afford alcohols. This paper successfully explores the ADH-catalyzed reduction of ketones and aldehydes in a DES composed of choline chloride and 1,4-butanediol, in combination with buffer (Tris-HCl, 20% v/v). 1,4-butanediol (a DES component), acts as a smart cosubstrate for the enzymatic cofactor regeneration, shifting the thermodynamic equilibrium to the product side. By means of the novel DES media, cyclohexanone reduction was optimized to yield maximum productivity with low enzyme amounts (in the range of 10 g L−1 d−1). Notably, with the herein developed reaction media, cinnamaldehyde was reduced to cinnamyl alcohol, an important compound for the fragrance industry, with promising high productivities of ~75 g L−1 d−1.
Beta-Cyclodextrin-Assisted Synthesis of Silver Nanoparticle Network and Its Application in a Hydrogen Generation Reaction
Authors: Huff Clay , Long Julia M. , Abdel-Fattah Tarek M.
Published: September 2020

The unsustainable nature of carbon-based fuels has prompted scientists and engineers to investigate alternative sources of energy. Silver nanoparticle networks (AgNPNs) were synthesized using beta-cyclodextrin for applications in hydrogen evolution reactions from sodium borohydride (NaBH4). The identities of the AgNPNs were confirmed using ultraviolet–visible spectroscopy, X-ray diffraction, and Transmission electron microscopy (TEM). The catalytic activity of the hydrogen evolution reactions was measured using a gravimetric water displacement system. The data collected show an increase in the efficiency of the hydrogen generation reaction with the addition of AgNPN. The silver nanoparticle network catalyst performed best at 22 °C with an increased concentration of NaBH4 producing hydrogen at a rate of 0.961 mL∙min−1∙mLcat−1. The activation energy was calculated to be 50.3 kJ/mol.
Effects of Childhood Adversity and Its Interaction with the MAOA, BDNF, and COMT Polymorphisms on Subclinical Attention Deficit/Hyperactivity Symptoms in Generally Healthy Youth
Authors: Tsai Meng-Che , Jhang Kai-Jyun , Lee Chih-Ting , Lin Yu-Fang , Strong Carol , Lin Yi-Ching , Hsieh Yi-Ping , Lin Chung-Ying
Published: September 2020

We aimed to investigate the effects of childhood adversity and its interaction with the polymorphisms in the monoamine oxidase A (MAOA), brain-derived neurotrophic factor (BDNF), and catechol-O-methyltransferase (COMT) genes on attention and hyperactivity disorder (ADHD) symptoms in a community sample of generally healthy youth. Participants (N = 432) completed questionnaires assessing ADHD symptoms (i.e., inattention, hyperactivity, and impulsiveness) and adverse childhood experiences, such as adverse environments (AEs) and childhood maltreatment (CM). Salivary genomic DNA was used to test polymorphisms in MAOA, BDNF, and COMT genes. A gene score (GS) was created based on the number of risk allele in the studied genes. Multiple linear regressions were used to examine the genetic and environmental effects on ADHD symptoms. The univariate analysis indicated that CM was significantly associated with inattention (β = 0.48 [95% confidence interval 0.16–0.79]), hyperactivity (0.25 [0.06–0.45]), and impulsiveness (1.16 [0.26–2.05]), while the GS was associated with hyperactivity (0.22 [0.11–0.33]) and impulsiveness (0.56 [0.06–1.05]). Only the GS remained significantly associated with hyperactivity (0.25 [0.12–0.37]) and impulsiveness (0.79 [0.20–1.38]) when the gene-environment interaction term was added in the model. No effects were found for AE and the gene-environment interaction term. In conclusion, CM was associated with ADHD symptoms in emerging adulthood. Genetic factors may also play a significant role in the association with these outcomes.
Petawatt Femtosecond Laser Pulses from Titanium-Doped Sapphire Crystal
Authors: Kiriyama Hiromitsu , Pirozhkov Alexander S. , Nishiuchi Mamiko , Fukuda Yuji , Sagisaka Akito , Kon Akira , Miyasaka Yasuhiro , Ogura Koichi , Dover Nicholas P. , Kondo Kotaro , Sakaki Hironao , Koga James K. , Esirkepov Timur Zh. , Huang Kai , Nakanii Nobuhiko , Kando Masaki , Kondo Kiminori , Bock Stefan , Ziegler Tim , Püschel Thomas , Zeil Karl , Schramm Ulrich
Published: September 2020

Ultra-high intensity femtosecond lasers have now become excellent scientific tools for the study of extreme material states in small-scale laboratory settings. The invention of chirped-pulse amplification (CPA) combined with titanium-doped sapphire (Ti:sapphire) crystals have enabled realization of such lasers. The pursuit of ultra-high intensity science and applications is driving worldwide development of new capabilities. A petawatt (PW = 1015 W), femtosecond (fs = 10−15 s), repetitive (0.1 Hz), high beam quality J-KAREN-P (Japan Kansai Advanced Relativistic ENgineering Petawatt) Ti:sapphire CPA laser has been recently constructed and used for accelerating charged particles (ions and electrons) and generating coherent and incoherent ultra-short-pulse, high-energy photon (X-ray) radiation. Ultra-high intensities of 1022 W/cm2 with high temporal contrast of 10−12 and a minimal number of pre-pulses on target has been demonstrated with the J-KAREN-P laser. Here, worldwide ultra-high intensity laser development is summarized, the output performance and spatiotemporal quality improvement of the J-KAREN-P laser are described, and some experimental results are briefly introduced.
Information Retrieval and Awareness about Evidence-Based Dentistry among Dental Undergraduate Students—A Comparative Study between Students from Malaysia and Finland
Authors: Nieminen Pentti , Uma Eswara , Pal Sudipta , Laitala Marja-Liisa , Lappalainen Olli-Pekka , Varghese Eby
Published: September 2020

Background: A fundamental skill in education includes the ability to search for, evaluate, and synthesize information, and this cannot be underestimated in dental education. The aim of this study was to assess how dental students from Malaysia and Finland acquire scientific information and to compare their information retrieval skills. Methods: Fourth and fifth-year dental students from Malaysia and Finland were invited to participate. A self-administered structured questionnaire including items about the use of information sources, subjective assessment of literature retrieval skills and knowledge was used. Results: A total of 226 dental students participated in the survey: 131 from Malaysia and 95 from Finland. In both countries, the highest interest for data retrieval among students was found in the oral surgery specialty. The three most used sources of information among Malaysian students were personal lecture notes, dental textbooks, and colleagues; while Finnish students used colleagues, lecture notes, and current clinical guidelines. Students’ knowledge of evidence-based practice was inadequate in both student groups. Though the majority of participants reported that they had good or passable skills in literature retrieval, more students from Finland judged themselves to have at least good skills compared to those from Malaysia. Conclusion: Dental education in both countries includes information retrieval studies and mandatory research projects. However, students did not often use those sources that are considered essential in evidence-based dentistry. Universities should further develop educational and training interventions that guide students to use knowledge resources more effectively for critically appraising scientific evidence.
Indirect Inference Estimation of Spatial Autoregressions
Authors: Bao Yong , Liu Xiaotian , Yang Lihong
Published: September 2020

The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the properly recentered OLS estimator and proposes a new estimator that is based on the indirect inference (II) procedure. The resulting estimator can always be used regardless of the degree of aggregate influence on each spatial unit from other units and is consistent and asymptotically normal. The new estimator does not rely on distributional assumptions and is robust to unknown heteroscedasticity. Its good finite-sample performance, in comparison with existing estimators that are also robust to heteroscedasticity, is demonstrated by a Monte Carlo study.
Is Data Literacy a Catalyst of Social Justice? A Response from Nine Data Literacy Initiatives in Higher Education
Authors: Elisa Raffaghelli Juliana
Published: September 2020

Is education and more specifically, data literacy initiatives in Higher Education, an appropriate instrument to promote social justice in a context of datafication? Education is (and has been) at the center of the debate over the achievement of social justice as a desirable quality of the human society. However, which type of educational interventions should be promoted to deal with a complex, multi-layered, emergent problem, such is the case of datafication in society? Since the problem is heavily entrenched with a shifting socio-economic model (the so called “surveillance capitalism”) and the technological infrastructures connected to it, educational approaches could be diversified and even contradictory in their purpose of heralding the skills to live in a datafied society. This paper explores nine initiatives in Higher Education aimed at developing the literacies to deal with data in society. Their efforts are concentrated in promoting freedom of choice, awareness, and agency. Though their original intention is not promoting social justice, the analysis is carried out on the theoretical basis provided by Martha Nussbaum on social justice. The initiatives span educational activities with open data as open educational resources, to more formal data literacy activities such as educational engagement with students’ data and students’ personal and educational data. There emerges a still fragmented panorama in responding to the need of promoting social justice in a context of datafication. Given this fragmentation, the article provides a conceptual scheme to address further pedagogical reflection and practice with the aim of supporting social justice against datafication.
Blockchain-Based Continued Integrity Service for IoT Big Data Management: A Comprehensive Design
Authors: Oktian Yustus Eko , Lee Sang-Gon , Lee Byung-Gook
Published: September 2020

The state-of-the-art centralized Internet of Things (IoT) data flow pipeline has started aging since it cannot cope with the vast number of newly connected IoT devices. As a result, the community begins the transition to a decentralized pipeline to encourage data and resource sharing. However, the move is not trivial. With many instances allocating data or service arbitrarily, how can we guarantee the correctness of IoT data or processes that other parties offer. Furthermore, in case of dispute, how can the IoT data assist in determining which party is guilty of faulty behavior. Finally, the number of Service Level Agreement (SLA) increases as the number of sharing grows. The problem then becomes how we can provide a natural SLA generation and verification that we can automate instead of going through a manual and tedious legalization process through a trusted third party. In this paper, we explore blockchain solutions to answer those issues and propose continued data integrity services for IoT big data management. Specifically, we design five integrity protocols across three phases of IoT operations—during the transmission of IoT data (data in transit), when we physically store the data in the database (data at rest), and at the time of data processing (data in process). In each phase, we first lay out our motivations and survey the related blockchain solutions from the literature. We then use curated papers from our surveys as building blocks in designing the protocol. Using our proposal, we augment the overall value of IoT data and commands, generated in the IoT system, as they are now tamper-proof, verifiable, non-repudiable, and more robust.
On the Performance of Cloud Services and Databases for Industrial IoT Scalable Applications
Authors: Ferrari Paolo , Sisinni Emiliano , Depari Alessandro , Flammini Alessandra , Rinaldi Stefano , Bellagente Paolo , Pasetti Marco
Published: September 2020

In the Industry 4.0 the communication infrastructure is derived from the Internet of Things (IoT), and it is called Industrial IoT or IIoT. Smart objects deployed on the field collect a large amount of data which is stored and processed in the Cloud to create innovative services. However, differently from most of the consumer applications, the industrial scenario is generally constrained by time-related requirements and its needs for real-time behavior (i.e., bounded and possibly short delays). Unfortunately, timeliness is generally ignored by traditional service provider, and the Cloud is treated as a black box. For instance, Cloud databases (generally seen as “Database as a service”—DBaaS) have unknown or hard-to-compare impact on applications. The novelty of this work is to provide an experimental measurement methodology based on an abstract view of IIoT applications, in order to define some easy-to-evaluate metrics focused on DBaaS latency (no matter the actual implementation details are). In particular, the focus is on the impact of DBaaS on the overall communication delays in a typical IIoT scalable context (i.e., from the field to the Cloud and the way back). In order to show the effectiveness of the proposed approach, a real use case is discussed (it is a predictive maintenance application with a Siemens S7 industrial controller transmitting system health status information to a Cloudant DB inside the IBM Bluemix platform). Experiments carried on in this use case provide useful insights about the DBaaS performance: evaluation of delays, effects of involved number of devices (scalability and complexity), constraints of the architecture, and clear information for comparing with other implementations and for optimizing configuration. In other words, the proposed evaluation strategy helps in finding out the peculiarities of Cloud Database service implementations.
Switch Open-Fault Detection for a Three-Phase Hybrid Active Neutral-Point-Clamped Rectifier
Authors: Kim Sang-Hun , Kim Seok-Min , Park Sungmin , Lee Kyo-Beum
Published: September 2020

This paper proposes a fault-detection method for open-switch failures in hybrid active neutral-point-clamped (HANPC) rectifiers. The basic HANPC topology comprises two SiC-based metal-oxide-semiconductor field-effect transistors (MOSFETs) and four Si insulated-gate bipolar transistors (IGBTs). A three-phase rectifier system using the HANPC topology can produce higher efficiency and lower current harmonics. An open-switch fault in a HANPC rectifier can be a MOSFET or IGBT fault. In this work, faulty cases of six different switches are analyzed based on the current distortion in the stationary reference frame. Open faults in MOSFET switches cause immediate and remarkable current distortions, whereas, open faults in IGBT switches are difficult to detect using conventional methods. To detect an IGBT fault, the proposed detection method utilizes some of the reactive power in a certain period to make an important difference, using the direct-quadrant (dq)-axis current information derived from the three-phase current. Thus, the proposed detection method is based on three-phase current measurements and does not use additional hardware. By analyzing the individual characteristics of each switch failure, the failed switch can be located exactly. The effectiveness and feasibility of the proposed fault-detection method are verified through PSIM simulations and experimental results.
Approaching the Optimal Solution of the Maximal α-quasi-clique Local Community Problem
Authors: Conde-Cespedes Patricia
Published: September 2020

Complex networks analysis (CNA) has attracted so much attention in the last few years. An interesting task in CNA complex network analysis is community detection. In this paper, we focus on Local Community Detection, which is the problem of detecting the community of a given node of interest in the whole network. Moreover, we study the problem of finding local communities of high density, known as α-quasi-cliques in graph theory (for high values of α in the interval ]0,1[). Unfortunately, the higher α is, the smaller the communities become. This led to the maximal α-quasi-clique community of a given node problem, which is, the problem of finding local communities that are α-quasi-cliques of maximal size. This problem is NP-hard, then, to approach the optimal solution, some heuristics exist. When α is high (>0.5) the diameter of a maximal α-quasi-clique is at most 2. Based on this property, we propose an algorithm to calculate an upper bound to approach the optimal solution. We evaluate our method in real networks and conclude that, in most cases, the bound is very accurate. Furthermore, for a real small network, the optimal value is exactly achieved in more than 80% of cases.
End-To-End Deep Learning Framework for Coronavirus (COVID-19) Detection and Monitoring
Authors: El-Rashidy Nora , El-Sappagh Shaker , Islam S. M. Riazul , El-Bakry Hazem M. , Abdelrazek Samir
Published: September 2020

Coronavirus (COVID-19) is a new virus of viral pneumonia. It can outbreak in the world through person-to-person transmission. Although several medical companies provide cooperative monitoring healthcare systems, these solutions lack offering of the end-to-end management of the disease. The main objective of the proposed framework is to bridge the current gap between current technologies and healthcare systems. The wireless body area network, cloud computing, fog computing, and clinical decision support system are integrated to provide a comprehensive and complete model for disease detection and monitoring. By monitoring a person with COVID-19 in real time, physicians can guide patients with the right decisions. The proposed framework has three main layers (i.e., a patient layer, cloud layer, and hospital layer). In the patient layer, the patient is tracked through a set of wearable sensors and a mobile app. In the cloud layer, a fog network architecture is proposed to solve the issues of storage and data transmission. In the hospital layer, we propose a convolutional neural network-based deep learning model for COVID-19 detection based on patient’s X-ray scan images and transfer learning. The proposed model achieved promising results compared to the state-of-the art (i.e., accuracy of 97.95% and specificity of 98.85%). Our framework is a useful application, through which we expect significant effects on COVID-19 proliferation and considerable lowering in healthcare expenses.
Bi-Level Operation Scheduling of Distribution Systems with Multi-Microgrids Considering Uncertainties
Authors: Esmaeili Saeid , Anvari-Moghaddam Amjad , Azimi Erfan , Nateghi Alireza , P. S. Catalão João
Published: September 2020

A bi-level operation scheduling of distribution system operator (DSO) and multi-microgrids (MMGs) considering both the wholesale market and retail market is presented in this paper. To this end, the upper-level optimization problem minimizes the total costs from DSO’s point of view, while the profits of microgrids (MGs) are maximized in the lower-level optimization problem. Besides, a scenario-based stochastic programming framework using the heuristic moment matching (HMM) method is developed to tackle the uncertain nature of the problem. In this regard, the HMM technique is employed to model the scenario matrix with a reduced number of scenarios, which is effectively suitable to achieve the correlations among uncertainties. In order to solve the proposed non-linear bi-level model, Karush–Kuhn–Tucker (KKT) optimality conditions and linearization techniques are employed to transform the bi-level problem into a single-level mixed-integer linear programming (MILP) optimization problem. The effectiveness of the proposed model is demonstrated on a real-test MMG system.
Investigation of the Interaction of Gadolinium with Several Organic Ligands and Humic Acid by Ligand Competition Using 4-(2-Pyridylazo)-Resorcinol (PAR)
Authors: Steinberg Spencer , Hodge Vernon , Becerra-Hernandez Luis
Published: September 2020

Gd3+ forms a strongly colored complex with 4-(2-pyridylazo)-resorcinol (PAR) in aqueous solutions. We characterized the Gd3+-PAR complex in order to use it as a probe of Gd3+ speciation in the presence of environmentally relevant ligands. The formation of the Gd3+-PAR complex was investigated from pH 5 to 8 in the presence of excess PAR. The absorbance of the Gd3+-PAR complex dramatically increased from pH 5 to 8 and application of the method of continuous variation indicates that the complex was primarily 1:2 Gd(PAR)2 at pH 8. Stability constants for Gd3+ with other ligands can be quantified by competitive displacement of the PAR ligand. To establish the viability of this approach, we measured the stability constants between Gd3+ and several organic acids and carbonate. Our measurements show reasonable agreement with the literature values. We used the competitive displacement approach to establish that humic acids can competitively displace PAR from the Gd(PAR)2 complex.
Using a Multi-Century Post-Fire Chronosequence to Develop Criteria to Distinguish Prior and Bowman’s (2020) Post-Fire Obligate Coloniser and Fire-Intolerant Flora
Authors: Gosper Carl R. , Prober Suzanne M.
Published: September 2020

Prior and Bowman added a new dimension to existing frameworks of post-fire responses of woody plants, by including the trait of colonisation ability (C) for those taxa which neither resprout (Rf−) nor produce seedlings (Sf−) after fire. Specifically, they recognised distinctions between: (i) post-fire obligate colonisers, being species that neither resprout nor produce seedlings from persistent seed banks post-fire but are able to colonise burnt areas through dispersal from unburnt populations, and (ii) fire-intolerant, which are unable to recover after fire by either resprouting, seeding or colonisation. We use data on temporal and spatial patterns of colonisation of Rf−Sf− mistletoes from a chronosequence study with an exceptionally long span of times since fire as a practical example of the delineation of post-fire obligate coloniser and fire-intolerant species. We propose that when a population of a species is burnt, if the species is unable to regularly colonise and reach reproductive maturity in burnt areas spatially distant from fire edges within plausible and regularly-occurring maximum fire-return intervals for the now-burnt community type, it would be classified as fire-intolerant. In our examples, Lysiana meets the criteria for fire-intolerant in obligate-seeder eucalypt woodland, while Amyema is classed as a post-fire obligate coloniser.
Strategies for Sustainable Substitution of Livestock Meat
Authors: Jiang Guihun , Ameer Kashif , Kim Honggyun , Lee Eun-Jung , Ramachandraiah Karna , Hong Geun-Pyo
Published: September 2020

The consequences of climate change are becoming increasingly discernible everywhere, and initiatives have been taken worldwide to mitigate climate change. In agriculture, particularly meat production from the livestock sector is known to contribute to greenhouse gas emissions (GHG) that drive climate change. Thus, to mitigate climate impact, strategies that include a shift in consumption patterns, technological advancements and reduction in food wastes/losses have been discussed. In this review, strategies that focus on meat consumption patterns are evaluated from the technological feasibility, environmental impact and consumer acceptance viewpoints. While plant-based substitutes have efficient nutrient conversion and lower GHG emissions, consumer perception, cost, and other trade-offs exist. Although cultured meat precludes the need of any animals and large land areas, its environmental impact is not clear and is contingent upon production systems and the achievement of decarbonization. Reducing wastes and the re-use of meat processing by-products have the potential to lower the environmental impact. Valuable proteins, heat, electricity and biofuels extracted from wastes and by-products not only reduce the disposal of wastes but also offset some GHG emissions. Perception related challenges that exist for all substitution strategies require specific consumer target marketing strategies. Policy measures such as taxation of meat products and subsidies for alternatives are also met with challenges, thereby requiring reforms or new policies.
Innovative Rough Beer Conditioning Process Free from Diatomaceous Earth and Polyvinylpolypyrrolidone
Authors: Cimini Alessio , Moresi Mauro
Published: September 2020

In large-sized breweries, rough beer clarification is still carried out using Kieselguhr filters notwithstanding their environmental and safety implications. The main aim of this work was to test an innovative rough beer clarification and stabilization process involving enzymatic treating with Brewers Clarex®, centrifuging, rough filtering across 1.4-μm ceramic hollow-fiber membrane at 30 °C, and fine filtering through 0.45-μm cartridge filter. When feeding an enzymatically-pretreated and centrifuged rough beer with permanent haze (HP) of 2 or 14 European Brewery Convention unit (EBC-U), its primary clarification under periodic CO2 backflushing yielded a permeate with turbidity of 1.0–1.5 EBC-U at a high permeation flux (2.173 ± 51 or 593 ± 100 L m−2 h−1), much greater than that typical of powder filters. The final beer was brilliant (HP = 0.57 ± 0.08 EBC-U) with almost the same colloidal stability of the industrial control and an overall log reduction value (~5.0 for the selected beer spoilage bacterium or 7.6 for the brewing yeast) in line with the microbial effectiveness of current sterilizing membranes. It was perceived as significantly different in flavor and body from the industrial control at a probability level of 10% by a triangle sensory test, as more likely related to the several lab-scale beer-racking steps used than to the novel process itself.
Gut Microbiota between Environment and Genetic Background in Familial Mediterranean Fever (FMF)
Authors: Di Ciaula Agostino , Stella Alessandro , Bonfrate Leonilde , Wang David Q. H. , Portincasa Piero
Published: September 2020

The gastrointestinal tract hosts the natural reservoir of microbiota since birth. The microbiota includes various bacteria that establish a progressively mutual relationship with the host. Of note, the composition of gut microbiota is rather individual-specific and, normally, depends on both the host genotype and environmental factors. The study of the bacterial profile in the gut demonstrates that dominant and minor phyla are present in the gastrointestinal tract with bacterial density gradually increasing in oro-aboral direction. The cross-talk between bacteria and host within the gut strongly contributes to the host metabolism, to structural and protective functions. Dysbiosis can develop following aging, diseases, inflammatory status, and antibiotic therapy. Growing evidences show a possible link between the microbiota and Familial Mediterranean Fever (FMF), through a shift of the relative abundance in microbial species. To which extent such perturbations of the microbiota are relevant in driving the phenotypic manifestations of FMF with respect to genetic background, remains to be further investigated.
Bacteria Belonging to Pseudomonas typographi sp. nov. from the Bark Beetle Ips typographus Have Genomic Potential to Aid in the Host Ecology
Authors: Peral-Aranega Ezequiel , Saati-Santamaría Zaki , Kolařik Miroslav , Rivas Raúl , García-Fraile Paula
Published: September 2020

European Bark Beetle Ips typographus is a secondary pest that affects dead and weakened spruce trees (Picea genus). Under certain environmental conditions, it has massive outbreaks, resulting in the attacks of healthy trees, becoming a forest pest. It has been proposed that the bark beetle’s microbiome plays a key role in the insect’s ecology, providing nutrients, inhibiting pathogens, and degrading tree defense compounds, among other probable traits yet to be discovered. During a study of bacterial associates from I. typographus, we isolated three strains identified as Pseudomonas from different beetle life stages. A polyphasic taxonomical approach showed that they belong to a new species for which the name Pseudomonas typographi sp nov. is proposed. Genome sequences show their potential to hydrolyze wood compounds and synthesize several vitamins; screening for enzymes production was verified using PNP substrates. Assays in Petri dishes confirmed cellulose and xylan hydrolysis. Moreover, the genomes harbor genes encoding chitinases and gene clusters involved in the synthesis of secondary metabolites with antimicrobial potential. In vitro tests confirmed the capability of the three P. typographi strains to inhibit several Ips beetles’ pathogenic fungi. Altogether, these results suggest that P. typographi aids I. typographi nutrition and resistance to fungal pathogens.
Time-Pattern Profiling from Smart Meter Data to Detect Outliers in Energy Consumption
Authors: Hurst William , Montañez Casimiro A. Curbelo , Shone Nathan
Published: September 2020

Smart meters have become a core part of the Internet of Things, and its sensory network is increasing globally. For example, in the UK there are over 15 million smart meters operating across homes and businesses. One of the main advantages of the smart meter installation is the link to a reduction in carbon emissions. Research shows that, when provided with accurate and real-time energy usage readings, consumers are more likely to turn off unneeded appliances and change other behavioural patterns around the home (e.g., lighting, thermostat adjustments). In addition, the smart meter rollout results in a lessening in the number of vehicle callouts for the collection of consumption readings from analogue meters and a general promotion of renewable sources of energy supply. Capturing and mining the data from this fully maintained (and highly accurate) sensing network, provides a wealth of information for utility companies and data scientists to promote applications that can further support a reduction in energy usage. This research focuses on modelling trends in domestic energy consumption using density-based classifiers. The technique estimates the volume of outliers (e.g., high periods of anomalous energy consumption) within a social class grouping. To achieve this, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Ordering Points to Identify the Clustering Structure (OPTICS) and Local Outlier Factor (LOF) demonstrate the detection of unusual energy consumption within naturally occurring groups with similar characteristics. Using DBSCAN and OPTICS, 53 and 208 outliers were detected respectively; with 218 using LOF, on a dataset comprised of 1,058,534 readings from 1026 homes.