bluuebunny/crossref_metadata_2025 huggingface dataset:
Comprehensive Volatilome and Metabolome Signatures of Colorectal Cancer in Urine: A Systematic Review and Meta-Analysis
Authors: Mallafré-Muro Celia , Llambrich Maria , Cumeras Raquel , Pardo Antonio , Brezmes Jesús , Marco Santiago , Gumà Josep
Published: May 2021

To increase compliance with colorectal cancer screening programs and to reduce the recommended screening age, cheaper and easy non-invasiveness alternatives to the fecal immunochemical test should be provided. Following the PRISMA procedure of studies that evaluated the metabolome and volatilome signatures of colorectal cancer in human urine samples, an exhaustive search in PubMed, Web of Science, and Scopus found 28 studies that met the required criteria. There were no restrictions on the query for the type of study, leading to not only colorectal cancer samples versus control comparison but also polyps versus control and prospective studies of surgical effects, CRC staging and comparisons of CRC with other cancers. With this systematic review, we identified up to 244 compounds in urine samples (3 shared compounds between the volatilome and metabolome), and 10 of them were relevant in more than three articles. In the meta-analysis, nine studies met the criteria for inclusion, and the results combining the case-control and the pre-/post-surgery groups, eleven compounds were found to be relevant. Four upregulated metabolites were identified, 3-hydroxybutyric acid, L-dopa, L-histidinol, and N1, N12-diacetylspermine and seven downregulated compounds were identified, pyruvic acid, hydroquinone, tartaric acid, and hippuric acid as metabolites and butyraldehyde, ether, and 1,1,6-trimethyl-1,2-dihydronaphthalene as volatiles.
Photocatalytic Degradation of Valsartan by MoS2/BiOCl Heterojunctions
Authors: Grilla Eleni , Kagialari Maria Nefeli , Petala Athanasia , Frontistis Zacharias , Mantzavinos Dionissios
Published: May 2021

In the present study, the removal of valsartan (VLS), an antihypertensive agent, under simulated solar radiation with the use of molybdenum sulfide-bismuth oxychloride composites (MoS2/BiOCl), of variable MoS2 content (0.1–10.0 wt.%) was investigated. The physicochemical properties of the photocatalysts were examined by XRD, DRS, BET and TEM/HRTEM. Preliminary tests were conducted to examine the photocatalytic efficiency of the synthesized MoS2/BiOCl composites towards VLS degradation in ultrapure water (UPW). It was found that the activity of pure BiOCl is improved with the addition of MoS2. The degradation rate was maximized with the use of the catalyst containing 0.25 wt.% MoS2. It was also found that the increase in catalyst concentration (50–1000 mg/L) enhances VLS degradation. It was found that VLS removal decreased by increasing VLS concentration. The effect of the water matrix on VLS removal was studied by carrying out experiments in real and synthetic water matrices. VLS degradation in UPW was faster than in bottled water (BW) and wastewater (WW), mainly due to the existence of organic matter in real aqueous media. Lastly, 0.25 wt.% MoS2/BiOCl showed great stability after 360 min of irradiation, serving as a promising catalyst for water remediation of emerging contaminants under solar irradiation.
Aftertreatment Technologies for Diesel Engines: An Overview of the Combined Systems
Authors: Martinovic Ferenc , Castoldi Lidia , Deorsola Fabio Alessandro
Published: May 2021

The abatement of the pollutants deriving from diesel engines in the vehicle sector still represents an interesting scientific and technological challenge due to increasingly limiting regulations. Meeting the stringent limits of NOx and soot emissions requires a catalytic system with great complexity, size of units, and number of units, as well as increased fuel consumption. Thus, an after-treatment device for a diesel vehicle requires the use of an integrated catalyst technology for a reduction in the individual emissions of exhaust gas. The representative technologies devoted to the reduction of NOx under lean-burn operation conditions are selective catalytic reduction (SCR) and the lean NOx trap (LNT), while soot removal is mainly performed by filters (DPF). These devices are normally used in sequence, or a combination of them has been proposed to overcome the drawbacks of the individual devices. This review summarizes the current state of NOx and soot abatement strategies. The main focus of this review is on combined technologies for NOx removal (i.e., LNT–SCR) and for the simultaneous removal of NOx and soot, like SCR-on-Filter (SCRoF), in series LNT/DPF and SCR/DPF, and LNT/DPF and SCR/DPF hybrid systems.
Nucleoporin TPR Affects C2C12 Myogenic Differentiation via Regulation of Myh4 Expression
Authors: Uhlířová Jana , Šebestová Lenka , Fišer Karel , Sieger Tomáš , Fišerová Jindřiška , Hozák Pavel
Published: May 2021

The nuclear pore complex (NPC) has emerged as a hub for the transcriptional regulation of a subset of genes, and this type of regulation plays an important role during differentiation. Nucleoporin TPR forms the nuclear basket of the NPC and is crucial for the enrichment of open chromatin around NPCs. TPR has been implicated in the regulation of transcription; however, the role of TPR in gene expression and cell differentiation has not been described. Here we show that depletion of TPR results in an aberrant morphology of murine proliferating C2C12 myoblasts (MBs) and differentiated C2C12 myotubes (MTs). The ChIP-Seq data revealed that TPR binds to genes linked to muscle formation and function, such as myosin heavy chain (Myh4), myocyte enhancer factor 2C (Mef2C) and a majority of olfactory receptor (Olfr) genes. We further show that TPR, possibly via lysine-specific demethylase 1 (LSD1), promotes the expression of Myh4 and Olfr376, but not Mef2C. This provides a novel insight into the mechanism of myogenesis; however, more evidence is needed to fully elucidate the mechanism by which TPR affects specific myogenic genes.
Review of Fiber Optical Sensors and Its Importance in Sewer Corrosion Factor Analysis
Authors: Raju Bharathi , Kumar R. , Dhanalakshmi Samiappan , Dooly Gerard , Duraibabu Dinesh Babu
Published: May 2021

Adverse effects of wastewater on the hygiene of human and circumstances is a major issue in society. Appropriate refining systems with high efficiency is required to treat the wastewater. Sewage treatment plant plays a major and important role in conserving incredible nature of the environment. Microbiologically Induced Corrosion (MIC) is an important phenomenon in sewage structures which causes the deterioration of infrastructures. Huge capital has been spent and efforts have been made on wastewater treatment infrastructure to increase operating efficiency and reliability of compliance. The investments in reimbursement and maintenance of sewer structures upsurge with an increase in the rate of MIC. The focus of this review is to describe MIC in sewer structure and the factors influencing the corrosion such as the generation of Sulfuric acid (H2SO4), Relative Humidity (RH), pH of the concrete structure and temperature. Modern developments in the design of Fiber Optical Sensors (FOSs) for observing the parameters including pH, Hydrogen Sulfide (H2S), RH and temperature will be discussed.
Assessment of Genetical, Pre, Peri and Post Natal Risk Factors of Deciduous Molar Hypomineralization (DMH), Hypomineralized Second Primary Molar (HSPM) and Molar Incisor Hypomineralization (MIH): A Narrative Review
Authors: Butera Andrea , Maiorani Carolina , Morandini Annalaura , Simonini Manuela , Morittu Stefania , Barbieri Stefania , Bruni Ambra , Sinesi Antonia , Ricci Maria , Trombini Julia , Aina Elisa , Piloni Daniela , Fusaro Barbara , Colnaghi Arianna , Pepe Elisa , Cimarossa Roberta , Scribante Andrea
Published: May 2021

Objectives: Analyze defects in the state of maturation of the enamel result in an adequate volume of enamel, but in an insufficient mineralization, which can affect both deciduous teeth and permanent teeth. Among the most common defects, we recognize Deciduous Molar Hypominerlization (DMH), Hypomineralized Second Primary Molar (HSPM), and Molar Incisor Hypomineralization (MIH). These, in fact, affect the first deciduous molars, the second deciduous molars and molars, and permanent incisors, respectively, but their etiology remains unclear. The objective of the paper is to review studies that focus on investigating possible associations between genetic factors or prenatal, perinatal, and postnatal causes and these enamel defects. Materials and methods: A comprehensive and bibliometric search for publications until January 2021 was conducted. The research question was formulated following the Population, Intervention, Comparison, Outcome strategy. Case-control, cross-sectional, cohort studies, and clinical trials investigating genetic and environmental etiological factors of enamel defects were included. Results: Twenty-five articles are included. For genetic factors, there is a statistical relevance for SNPs expressed in the secretion or maturation stage of amelogenesis (16% of studies and 80% of studies that investigated these factors). For prenatal, perinatal, and postnatal causes, there is a statistical relevance for postnatal factors, such as the breastfeeding period (2%), asthma (16%), high fever episodes (20%), infections/illnesses (20%), chickenpox (12%), antibiotic intake (8%), diarrhea (4%), and pneumonia (4%). Conclusions: The results are in agreement with the multifactorial idea of the dental enamel defects etiology, but to prove this, further studies enrolling larger, well-diagnosed, and different ethnic populations are necessary to expand the investigation of the genetic and environmental factors that might influence the occurrence of DMH, HPSM, and MIH.
Characterization of Three Surface Treatments on TiZr—Coating Properies and Corrosion Behavior
Authors: Voicu Manuela Elena , Stoian Andrei Bogdan , Demetrescu Ioana , Ionita Daniela
Published: May 2021

Titanium implants remain a reliable treatment for patients in need of restorative orthopedic and oral cavity works due to their high flexibility in manufacturing. Multiple strategies for improving Ti implants have been successfully tested and employed including alloying and surface coatings. Polylactic acid (PLA) based nanofibers can be interesting due to their large surface-to-volume ratio and ability to interact with large volumes of other substances. This paper offers an in-depth characterization of a nanofibrous PLA coating obtained by electrospinning on TiZr oxide. Analyses include morphology characterization, investigation of forces present on the surface, and the observation of the evolution of the coatings immersed in two bioelectrolytes.
Educational Challenges for Computational Thinking in K–12 Education: A Systematic Literature Review of “Scratch” as an Innovative Programming Tool
Authors: Montiel Hugo , Gomez-Zermeño Marcela Georgina
Published: May 2021

The use of information and communications technologies (ICTs) has emerged as an educational response amidst the COVID-19 pandemic, providing students the technological tools that enable them to acquire or strengthen the necessary digital skills to develop computational knowledge. The purpose of this study was to analyze Scratch, a programming language used to foster the teaching of computational thinking, particularly in K–12 education. A systematic literature review (SLR) was conducted, identifying 30 articles on the topic of Scratch and computational thinking in the database ProQuest Central from January 2010 to May 2020. These articles were analyzed to identify the use of Scratch worldwide and the educational impact it has on computational thinking, specifically in K–12 education. The results highlight the following: (1) countries which incorporated Scratch into their teachers’ study plans (curricula); (2) the transformation of learning environments that Scratch promotes; and (3) the importance of incorporating tools like Scratch in the current curricula and, more importantly, developing the framework for innovative ICTs capable of transforming education.
Hydrothermal Synthesis, Crystal Structure, and Spectroscopic Properties of Pure and Eu3+-Doped NaY[SO4]2 ∙ H2O and Its Anhydrate NaY[SO4]2
Authors: Buyer Constantin , Enseling David , Jüstel Thomas , Schleid Thomas
Published: May 2021

The water-soluble colorless compound NaY[SO4]2 ∙ H2O was synthesized with wet methods in a Teflon autoclave by adding a mixture of Na2[SO4] and Y2[SO4]3 ∙ 8 H2O to a small amount of water and heating it up to 190 °C. By slow cooling, single crystals could be obtained and the trigonal crystal structure of NaY[SO4]2 ∙ H2O was refined based on X-ray diffraction data in space group P3221 (a = 682.24(5) pm, c = 1270.65(9) pm, Z = 3). After its thermal decomposition starting at 180 °C, the anhydrate NaY[SO4]2 can be obtained with a monoclinic crystal structure refined from powder X-ray diffraction data in space group P21/m (a = 467.697(5) pm, b = 686.380(6) pm, c = 956.597(9) pm, β = 96.8079(5), Z = 2). Both compounds display unique Y3+-cation sites with eightfold oxygen coordination (d(Y–Os = 220–277 pm)) from tetrahedral [SO4]2− anions (d(S–O = 141–151 pm)) and a ninth oxygen ligand from an H2O molecule (d(Y–Ow = 238 pm) in the hydrate case. In both compounds, the Na+ cations are atoms (d(Na–Os = 224–290 pm) from six independent [SO4]2− tetrahedra each. Thermogravimetry and temperature-dependent PXRD experiments were performed as well as IR and Raman spectroscopic studies. Eu3+-doped samples were investigated for their photoluminescence properties in both cases. The quantum yield of the red luminescence for the anhydrate NaY[SO4]2:Eu3+ was found to be almost 20 times higher than the one of the hydrate NaY[SO4]2 ∙ H2O:Eu3+. The anhydrate NaY[SO4]2:Eu3+ exhibits a decay time of about τ1/e = 2.3 µm almost independent of the temperature between 100 and 500 K, while the CIE1931 color coordinates at x = 0.65 and y = 0.35 are very temperature-consistent too. Due to these findings, the anhydrate is suitable as a red emitter in lighting for emissive displays.
Magnetic Compton Scattering on Sr-Doped LaCoO3
Authors: Kobayashi Yoshihiko , Tsuji Naruki , Sakurai Yoshiharu
Published: May 2021

We carried out magnetic Compton scattering experiments on the Sr-doped perovskite cobaltite La1−xSrxCoO3 for the paramagnetic insulator (x = 0.1) and the ferromagnetic metallic (x = 0.3) phases in order to investigate the electron-orbital state relevant to its unusual magnetic and electronic transport properties. The ratio of the orbital moments to the spin moments (Morbital/Mspin) is less than 1/10 at low temperatures for x = 0.3, whereas Morbital/Mspin is about 0.4 almost independent of temperature for x = 0.1. The shape of Jmag(pz) shows no apparent difference between the paramagnetic insulator and the ferromagnetic metallic phases.
Ecological Scenarios and Parasite Diversity in Anurans of West Africa: A Review
Authors: Aisien Martins S. O. , Edo-Taiwo Omoyemwen , Imasuen Abigail A.
Published: May 2021

This paper is a survey of the parasite diversity, prevalence and infection intensity in anurans in diverse ecological settings in West Africa. The settings included natural habitats (rainforests, freshwater creeks, Guinea and Sudan savannas), monoculture plantations (cocoa, cotton and oil palm), urbanized and urbanizing rainforest biotopes and polluted environments due to oil industry activities. The natural habitats had higher amphibian species diversity, moderate parasite prevalence and low infection intensity, showing a balance in the host/parasite relationship. These habitats yielded most of the monogeneans, among which were new species. The freshwater creek biotope had low amphibian diversity, but hosts from this environment harbored several parasite taxa, a situation attributed to a prolonged wet season, high environmental humidity and persistent breeding pools for insect vectors in this area. The monoculture plantations were characterized by high parasite prevalence but lower infection intensity. For example, in the Pendjari Biosphere Reserve in Bénin Republic, the Agricultural Zone (AZ) had higher parasite prevalence values, while the National Park (NP) and Buffer Zone (BZ) had higher infection intensities. Higher prevalence was attributed to the single or combined effects of vector population explosion, immune-suppression by agrochemicals, nutrient enrichment and eutrophication from fertilizer use. The lower infection intensity was attributed to the inhibitory effect of the pesticide-contaminated environment on the free-living larval stages of parasites. The adverse effect of pesticide contamination was also evident in the lower infection intensity recorded in the anurans from the cocoa plantations at Ugboke in comparison to those from the pesticide-free village settlement. Urbanization reduced host diversity and numbers and increased the vector population, resulting in unusually high parasite prevalence and infection intensities at Diobu and Port Harcourt and high prevalence recorded for Ophidascaris larvae in the anurans of Evbuabogun. Oil pollution in the mangrove community reduced both host and parasite diversity; infection intensity was also low due to the adverse conditions confronting free-living stages of parasites in their development milieu. The high prevalence values obtained for monogeneans (Polystoma spp.) in Ptychadena spp. from Ogoniland was presumed to have resulted from host tadpole sequestration and exposure to high oncomiracidia burden in the few hospitable ponds. Also reviewed is the phenomenon of amphibian paratenism, a strategy on which many helminth parasites rely on for their trophic transmission to their definitive hosts.
Outcomes of Esophageal Cancer after Esophagectomy in the Era of Early Injection Laryngoplasty
Authors: Fang Tuan-Jen , Pei Yu-Cheng , Lu Yi-An , Chung Hsiu-Feng , Chiang Hui-Chen , Li Hsueh-Yu , Wong Alice M. K.
Published: May 2021

(1) Background: severe weight loss was reported to be related to unilateral vocal fold paralysis (UVFP) after esophagectomy and could thus impair survival. Concomitant radical lymph node dissection along the recurrent laryngeal nerve during esophageal cancer surgery is controversial, as it might induce UVFP. Early intervention for esophagectomy-related UVFP by administering intracordal injections of temporal agents has recently become popular. This study investigated the survival outcomes of esophagectomy for esophageal squamous cell carcinoma (ESCC) after the introduction of early injection laryngoplasty (EIL). (2) Methods: a retrospective review of patients with ESCC after curative-intent esophagectomy was conducted in a tertiary referral medical center. The necessity of EIL with hyaluronic acid was comprehensively discussed for all symptomatic UVFP patients. The survival outcomes and related risk factors of ESCC were evaluated. (3) Results: among the cohort of 358 consecutive patients who underwent esophagectomy for ESCC, 42 (11.7%) showed postsurgical UVFP. Twenty-nine of them received office-based EIL. After EIL, the glottal gap area, maximum phonation time and voice outcome survey showed significant improvement at one, three and six months measurements. The number of lymph nodes in the resected specimen was higher in those with UVFP than in those without UVFP (30.1 ± 15.7 vs. 24.6 ± 12.7, p = 0.011). The Kaplan–Meier overall survival was significantly better in patients who had UVFP (p = 0.014), received neck anastomosis (p = 0.004), underwent endoscopic resection (p < 0.001) and had early-stage cancer (p < 0.001). Multivariate Cox logistic regression analysis showed two independent predictors of OS, showing that the primary stage and anastomosis type are the two independent predictors of OS. (4) Conclusion: EIL is effective in improving UVFP-related symptoms, thus providing compensatory and palliative measures to ensure the patient’s postsurgical quality of life. The emerging use of EIL might encourage cancer surgeons to radically dissect lymph nodes along the recurrent laryngeal nerve, thus changing the survival trend.
Radiomics and Machine Learning with Multiparametric Breast MRI for Improved Diagnostic Accuracy in Breast Cancer Diagnosis
Authors: Daimiel Naranjo Isaac , Gibbs Peter , Reiner Jeffrey S. , Lo Gullo Roberto , Sooknanan Caleb , Thakur Sunitha B. , Jochelson Maxine S. , Sevilimedu Varadan , Morris Elizabeth A. , Baltzer Pascal A. T. , Helbich Thomas H. , Pinker Katja
Published: May 2021

The purpose of this multicenter retrospective study was to evaluate radiomics analysis coupled with machine learning (ML) of dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) radiomics models separately and combined as multiparametric MRI for improved breast cancer detection. Consecutive patients (Memorial Sloan Kettering Cancer Center, January 2018–March 2020; Medical University Vienna, from January 2011–August 2014) with a suspicious enhancing breast tumor on breast MRI categorized as BI-RADS 4 and who subsequently underwent image-guided biopsy were included. In 93 patients (mean age: 49 years ± 12 years; 100% women), there were 104 lesions (mean size: 22.8 mm; range: 7–99 mm), 46 malignant and 58 benign. Radiomics features were calculated. Subsequently, the five most significant features were fitted into multivariable modeling to produce a robust ML model for discriminating between benign and malignant lesions. A medium Gaussian support vector machine (SVM) model with five-fold cross validation was developed for each modality. A model based on DWI-extracted features achieved an AUC of 0.79 (95% CI: 0.70–0.88), whereas a model based on DCE-extracted features yielded an AUC of 0.83 (95% CI: 0.75–0.91). A multiparametric radiomics model combining DCE- and DWI-extracted features showed the best AUC (0.85; 95% CI: 0.77–0.92) and diagnostic accuracy (81.7%; 95% CI: 73.0–88.6). In conclusion, radiomics analysis coupled with ML of multiparametric MRI allows an improved evaluation of suspicious enhancing breast tumors recommended for biopsy on clinical breast MRI, facilitating accurate breast cancer diagnosis while reducing unnecessary benign breast biopsies.
Molecular Characteristics of the Serological Weak D Phenotype in Koreans
Authors: Jeong Dajeong , Oh Sujin , Song Eun Young , Hong Yun Ji , Park Kyoung Un
Published: May 2021

Serological weak D is a reaction of 2+ or less to anti-D reagent and includes weak D and partial D phenotypes. Although identifying the RhD subtype is important for transfusion safety, serological tests are insufficient for defining the RhD subtype, and molecular tests are needed. To analyze the molecular characteristics of D variants in Koreans to facilitate the formulation of individualized transfusion strategies, molecular tests such as RhD genotyping using real-time polymerase chain reaction (PCR) and partial-D and/or weak-D sequence-specific amplification (SSP) were performed on 105 Korean Rare Blood Program (KRBP) patients exhibiting serological weak D. In total, 58 out of 68 serologically determined weak D KRBP patients were typed as having weak D or partial D phenotypes via RhD genotyping. In detail, eight (13.8%) were typed as partial DVa or DBS, nine (15.5%) as weak D type 15, and four others (6.8%) as partial DVI, partial DVII, weak D type 2, or weak D type 41 or 45, whereas the rest (n = 37, 63.8%) was typed as having either weak D or partial D. This suggests that serological weak D Koreans who require transfusion should be treated as D-negative.
Assessment of the Adaptive Force of Elbow Extensors in Healthy Subjects Quantified by a Novel Pneumatically Driven Measurement System with Considerations of Its Quality Criteria
Authors: Dech Silas , Bittmann Frank N. , Schaefer Laura V.
Published: May 2021

Adaptive Force (AF) reflects the capability of the neuromuscular system to adapt adequately to external forces with the intention of maintaining a position or motion. One specific approach to assessing AF is to measure force and limb position during a pneumatically applied increasing external force. Through this method, the highest (AFmax), the maximal isometric (AFisomax) and the maximal eccentric Adaptive Force (AFeccmax) can be determined. The main question of the study was whether the AFisomax is a specific and independent parameter of muscle function compared to other maximal forces. In 13 healthy subjects (9 male and 4 female), the maximal voluntary isometric contraction (pre- and post-MVIC), the three AF parameters and the MVIC with a prior concentric contraction (MVICpri-con) of the elbow extensors were measured 4 times on two days. Arithmetic mean (M) and maximal (Max) torques of all force types were analyzed. Regarding the reliability of the AF parameters between days, the mean changes were 0.31–1.98 Nm (0.61%–5.47%, p = 0.175–0.552), the standard errors of measurements (SEM) were 1.29–5.68 Nm (2.53%–15.70%) and the ICCs(3,1) = 0.896–0.996. M and Max of AFisomax, AFmax and pre-MVIC correlated highly (r = 0.85–0.98). The M and Max of AFisomax were significantly lower (6.12–14.93 Nm; p ≤ 0.001–0.009) and more variable between trials (coefficient of variation (CVs) ≥ 21.95%) compared to those of pre-MVIC and AFmax (CVs ≤ 5.4%). The results suggest the novel measuring procedure is suitable to reliably quantify the AF, whereby the presented measurement errors should be taken into consideration. The AFisomax seems to reflect its own strength capacity and should be detected separately. It is suggested its normalization to the MVIC or AFmax could serve as an indicator of a neuromuscular function.
Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations
Authors: Callewaert Bram , Jones Elizabeth A. V. , Himmelreich Uwe , Gsell Willy
Published: May 2021

Alterations to the cerebral microcirculation have been recognized to play a crucial role in the development of neurodegenerative disorders. However, the exact role of the microvascular alterations in the pathophysiological mechanisms often remains poorly understood. The early detection of changes in microcirculation and cerebral blood flow (CBF) can be used to get a better understanding of underlying disease mechanisms. This could be an important step towards the development of new treatment approaches. Animal models allow for the study of the disease mechanism at several stages of development, before the onset of clinical symptoms, and the verification with invasive imaging techniques. Specifically, pre-clinical magnetic resonance imaging (MRI) is an important tool for the development and validation of MRI sequences under clinically relevant conditions. This article reviews MRI strategies providing indirect non-invasive measurements of microvascular changes in the rodent brain that can be used for early detection and characterization of neurodegenerative disorders. The perfusion MRI techniques: Dynamic Contrast Enhanced (DCE), Dynamic Susceptibility Contrast Enhanced (DSC) and Arterial Spin Labeling (ASL), will be discussed, followed by less established imaging strategies used to analyze the cerebral microcirculation: Intravoxel Incoherent Motion (IVIM), Vascular Space Occupancy (VASO), Steady-State Susceptibility Contrast (SSC), Vessel size imaging, SAGE-based DSC, Phase Contrast Flow (PC) Quantitative Susceptibility Mapping (QSM) and quantitative Blood-Oxygenation-Level-Dependent (qBOLD). We will emphasize the advantages and limitations of each strategy, in particular on applications for high-field MRI in the rodent’s brain.
Discriminating Small-Sized (2 cm or Less), Noncalcified, Solitary Pulmonary Tuberculoma and Solid Lung Adenocarcinoma in Tuberculosis-Endemic Areas
Authors: Zhang Jingping , Han Tingting , Ren Jialiang , Jin Chenwang , Zhang Ming , Guo Youmin
Published: May 2021

Background. Pulmonary tuberculoma can mimic lung malignancy and thereby pose a diagnostic dilemma to clinicians. The purpose of this study was to establish an accurate, convenient, and clinically practical model for distinguishing small-sized, noncalcified, solitary pulmonary tuberculoma from solid lung adenocarcinoma. Methods. Thirty-one patients with noncalcified, solitary tuberculoma and 30 patients with solid adenocarcinoma were enrolled. Clinical characteristics and CT morphological features of lesions were compared between the two groups. Multivariate logistic regression analyses were applied to identify independent predictors of pulmonary tuberculoma and lung adenocarcinoma. Receiver operating characteristic (ROC) analysis was performed to investigate the discriminating efficacy. Results. The mean age of patients with tuberculoma and adenocarcinoma was 46.8 ± 12.3 years (range, 28–64) and 61.1 ± 9.9 years (range, 41–77), respectively. No significant differences were observed concerning smoking history and smoking index, underlying disease, or tumor markers between the two groups. Univariate and multivariate analyses showed age and lobulation combined with pleural indentation demonstrated excellent discrimination. The sensitivity, specificity, accuracy, and the area under the ROC curve were 87.1%, 93.3%, 90.2%, and 0.956 (95% confidence interval (CI), 0.901–1.000), respectively. Conclusion. The combination of clinical characteristics and CT morphological features can be used to distinguish noncalcified, solitary tuberculoma from solid adenocarcinoma with high diagnostic performance and has a clinical application value.
Cold Atmospheric Plasma Improves Shear Bond Strength of Veneering Composite to Zirconia
Authors: Bunz Oskar , Kalz Paul , Benz Carla I. , Naumova Ella A. , Arnold Wolfgang H. , Piwowarczyk Andree
Published: May 2021

Chipping of veneering is the most common clinical complication for zirconia restorations. Veneering composite could be a promising alternative to renew restorations. Zirconia discs (3-YSZ) were prepared with varying surface treatments and bonded to indirect composite as follows: air abrasion and Scotchbond Universal (A/SU); air abrasion and Clearfil Ceramic Primer (A/C); air abrasion and MKZ Primer (A/M); air abrasion and Monobond Plus (A/MP); silica-coating and Scotchbond Universal (S/SU); air abrasion (AP/SU), additional cold atmospheric plasma treatment, and Scotchbond Universal. An indirect composite material was then applied to the zirconia specimens. Specimens were divided into subgroups for short-term (14 days storage at 37 °C and 5000 thermal cycles) and long-term (250 days storage and 37,500 thermal cycles) artificial aging. Shear bond strength measurement (SBS) was performed, and data were analyzed by Kruskal–Wallis-test and multiple comparison testing with Dunn’s correction (p ≤ 0.05). The median SBS values (MPa) of short- and long-term artificial aging were: 3.09/1.36 (A/SU); 0.77/1.43 (S/SU); 2.82/2.15 (AP/SU); 1.97/1.80 (A/C); 2.01/1.58 (A/M); and 1.70/1.68 (A/MP). For short-term artificial aging A/SU showed the highest median SBS values, whereas in the long-term trial, AP/SU showed the highest values and the difference was significant. A prolonged artificial aging decreased SBS in all groups, except S/SU. In summary, treatment with CAP can improve SBS in the long-term.
Neural Estimator of Information for Time-Series Data with Dependency
Authors: Molavipour Sina , Ghourchian Hamid , Bassi Germán , Skoglund Mikael
Published: May 2021

Novel approaches to estimate information measures using neural networks are well-celebrated in recent years both in the information theory and machine learning communities. These neural-based estimators are shown to converge to the true values when estimating mutual information and conditional mutual information using independent samples. However, if the samples in the dataset are not independent, the consistency of these estimators requires further investigation. This is of particular interest for a more complex measure such as the directed information, which is pivotal in characterizing causality and is meaningful over time-dependent variables. The extension of the convergence proof for such cases is not trivial and demands further assumptions on the data. In this paper, we show that our neural estimator for conditional mutual information is consistent when the dataset is generated with samples of a stationary and ergodic source. In other words, we show that our information estimator using neural networks converges asymptotically to the true value with probability one. Besides universal functional approximation of neural networks, a core lemma to show the convergence is Birkhoff’s ergodic theorem. Additionally, we use the technique to estimate directed information and demonstrate the effectiveness of our approach in simulations.
A New Regression Model for the Analysis of Overdispersed and Zero-Modified Count Data
Authors: Bertoli Wesley , Conceição Katiane S. , Andrade Marinho G. , Louzada Francisco
Published: May 2021

Count datasets are traditionally analyzed using the ordinary Poisson distribution. However, said model has its applicability limited, as it can be somewhat restrictive to handling specific data structures. In this case, the need arises for obtaining alternative models that accommodate, for example, overdispersion and zero modification (inflation/deflation at the frequency of zeros). In practical terms, these are the most prevalent structures ruling the nature of discrete phenomena nowadays. Hence, this paper’s primary goal was to jointly address these issues by deriving a fixed-effects regression model based on the hurdle version of the Poisson–Sujatha distribution. In this framework, the zero modification is incorporated by considering that a binary probability model determines which outcomes are zero-valued, and a zero-truncated process is responsible for generating positive observations. Posterior inferences for the model parameters were obtained from a fully Bayesian approach based on the g-prior method. Intensive Monte Carlo simulation studies were performed to assess the Bayesian estimators’ empirical properties, and the obtained results have been discussed. The proposed model was considered for analyzing a real dataset, and its competitiveness regarding some well-established fixed-effects models for count data was evaluated. A sensitivity analysis to detect observations that may impact parameter estimates was performed based on standard divergence measures. The Bayesian p-value and the randomized quantile residuals were considered for the task of model validation.
Deepening Our Knowledge about Sustainability Education in the Early Years: Lessons from a Water Project
Authors: Ampartzaki Maria , Kalogiannakis Michail , Papadakis Stamatios
Published: May 2021

The transformative agenda of sustainability education constitutes the focus of early-years education. In quality sustainability educational projects, children are supported to draw links between nature and society and relate to the studied phenomena. Is this methodological approach realized in educational programs for the early years? The present work presents some of the significant findings of a case study on implementing a water project in early-year settings around Europe. It explores the characteristics and the methodological approaches the project implementation developed. Three types of implementation are derived from the qualitative analysis of data and reveal that there are still cases in which sustainability projects are focused on a descriptive approach rather than critical inquiry and analysis. In this sense, the need for educational designs that help children deepen their understanding of sustainability issues and become empowered citizens who will work for a sustainable future is highlighted.
AI-Enabled Efficient and Safe Food Supply Chain
Authors: Kollia Ilianna , Stevenson Jack , Kollias Stefanos
Published: May 2021

This paper provides a review of an emerging field in the food processing sector, referring to efficient and safe food supply chains, ’from farm to fork’, as enabled by Artificial Intelligence (AI). The field is of great significance from economic, food safety and public health points of views. The paper focuses on effective food production, food maintenance energy management and food retail packaging labeling control, using recent advances in machine learning. Appropriate deep neural architectures are adopted and used for this purpose, including Fully Convolutional Networks, Long Short-Term Memories and Recurrent Neural Networks, Auto-Encoders and Attention mechanisms, Latent Variable extraction and clustering, as well as Domain Adaptation. Three experimental studies are presented, illustrating the ability of these AI methodologies to produce state-of-the-art performance in the whole food supply chain. In particular, these concern: (i) predicting plant growth and tomato yield in greenhouses, thus matching food production to market needs and reducing food waste or food unavailability; (ii) optimizing energy consumption across large networks of food retail refrigeration systems, through optimal selection of systems that can be shut-down and through prediction of the respective food de-freezing times, during peaks of power demand load; (iii) optical recognition and verification of food consumption expiry date in automatic inspection of retail packaged food, thus ensuring safety of food and people’s health.
Memcapacitor and Meminductor Circuit Emulators: A Review
Authors: Romero Francisco J. , Ohata Akiko , Toral-Lopez Alejandro , Godoy Andres , Morales Diego P. , Rodriguez Noel
Published: May 2021

In 1971, Prof. L. Chua theoretically introduced a new circuit element, which exhibited a different behavior from that displayed by any of the three known passive elements: the resistor, the capacitor or the inductor. This element was called memristor, since its behavior corresponded to a resistor with memory. Four decades later, the concept of mem-elements was extended to the other two circuit elements by the definition of the constitutive equations of both memcapacitors and meminductors. Since then, the non-linear and non-volatile properties of these devices have attracted the interest of many researches trying to develop a wide range of applications. However, the lack of solid-state implementations of memcapacitors and meminductors make it necessary to rely on circuit emulators for the use and investigation of these elements in practical implementations. On this basis, this review gathers the current main alternatives presented in the literature for the emulation of both memcapacitors and meminductors. Different circuit emulators have been thoroughly analyzed and compared in detail, providing a wide range of approaches that could be considered for the implementation of these devices in future designs.
Using a Hybrid Recommending System for Learning Videos in Flipped Classrooms and MOOCs
Authors: Jordán Jaume , Valero Soledad , Turró Carlos , Botti Vicent
Published: May 2021

New challenges in education require new ways of education. Higher education has adapted to these new challenges by means of offering new types of training like massive online open courses and by updating their teaching methodology using novel approaches as flipped classrooms. These types of training have enabled universities to better adapt to the challenges posed by the pandemic. In addition, high quality learning objects are necessary for these new forms of education to be successful, with learning videos being the most common learning objects to provide theoretical concepts. This paper describes a new approach of a previously presented hybrid learning recommender system based on content-based techniques, which was capable of recommend useful videos to learners and lecturers from a learning video repository. In this new approach, the content-based techniques are also combined with a collaborative filtering module, which increases the probability of recommending relevant videos. This hybrid technique has been successfully applied to a real scenario in the central video repository of the Universitat Politècnica de València.
Machine Learning Approach Equipped with Neighbourhood Component Analysis for DDoS Attack Detection in Software-Defined Networking
Authors: Tonkal Özgür , Polat Hüseyin , Başaran Erdal , Cömert Zafer , Kocaoğlu Ramazan
Published: May 2021

The Software-Defined Network (SDN) is a new network paradigm that promises more dynamic and efficiently manageable network architecture for new-generation networks. With its programmable central controller approach, network operators can easily manage and control the whole network. However, at the same time, due to its centralized structure, it is the target of many attack vectors. Distributed Denial of Service (DDoS) attacks are the most effective attack vector to the SDN. The purpose of this study is to classify the SDN traffic as normal or attack traffic using machine learning algorithms equipped with Neighbourhood Component Analysis (NCA). We handle a public “DDoS attack SDN Dataset” including a total of 23 features. The dataset consists of Transmission Control Protocol (TCP), User Datagram Protocol (UDP), and Internet Control Message Protocol (ICMP) normal and attack traffics. The dataset, including more than 100 thousand recordings, has statistical features such as byte_count, duration_sec, packet rate, and packet per flow, except for features that define source and target machines. We use the NCA algorithm to reveal the most relevant features by feature selection and perform an effective classification. After preprocessing and feature selection stages, the obtained dataset was classified by k-Nearest Neighbor (kNN), Decision Tree (DT), Artificial Neural Network (ANN), and Support Vector Machine (SVM) algorithms. The experimental results show that DT has a better accuracy rate than the other algorithms with 100% classification achievement.
A Battery Management System with EIS Monitoring of Life Expectancy for Lead–Acid Batteries
Authors: Olarte Javier , Martínez de Ilarduya Jaione , Zulueta Ekaitz , Ferret Raquel , Fernández-Gámiz Unai , Lopez-Guede Jose Manuel
Published: May 2021

This work presents a battery management system for lead–acid batteries that integrates a battery-block (12 V) sensor that allows the online monitoring of a cell’s temperature, voltage, and impedance spectra. The monitoring and diagnostic capabilities enable the implementation of improved battery management algorithms in order to increase the life expectancy of lead–acid batteries and report the battery health conditions. The novelty is based on the online monitoring of the evolution of electrochemical impedance spectroscopy (EIS) over a battery’s life as a way to monitor the battery’s performance. Active cell balancing is also proposed as an alternative to traditional charge equalization to minimize excessive electrolyte consumption. A battery-block sensor (VTZ) was validated by using the correlation between experimental data collected from electrochemical impedance spectroscopy lab-testing equipment and sensors that were implemented in a series of 12 V lead–acid battery blocks. The modular design and small size allow easy and direct integration into different commercial cell formats, and the proposed methodology can be used for applications ranging from automotive to stationary energy storage.
Cloud and Edge Computing-Based Computer Forensics: Challenges and Open Problems
Authors: Prakash Vijay , Williams Alex , Garg Lalit , Savaglio Claudio , Bawa Seema
Published: May 2021

In recent years, there has been a dramatic change in attitude towards computers and the use of computer resources in general. Cloud and Edge computing have emerged as the most widely used technologies, including fog computing and the Internet of Things (IoT). There are several benefits in exploiting Cloud and Edge computing paradigms, such as lower costs and higher efficiency. It provides data computation and storage where data are processed, enables better data control, faster understanding and actions, and continuous operation. However, though these benefits seem to be appealing, their effects on computer forensics are somewhat undesirable. The complexity of the Cloud and Edge environments and their key features present many technical challenges from multiple stakeholders. This paper seeks to establish an in-depth understanding of the impact of Cloud and Edge computing-based environmental factors. Software and hardware tools used in the digital forensic process, forensic methods for handling tampered sound files, hidden files, image files, or images with steganography, etc. The technical/legal challenges and the open design problems (such as distributed maintenance, multitasking and practicality) highlight the various challenges for the digital forensics process.
D-GENE-Based Discovery of Frequent Occupational Diseases among Female Home-Based Workers
Authors: Yasir Muhammad , Ashraf Ayesha , Chaudhry Muhammad Umar , Hassan Farhad , Lee Jee-Hyong , Jasiński Michał , Leonowicz Zbigniew , Jasińska Elżbieta
Published: May 2021

A considerable fraction of the female workforce worldwide is making ends meet by doing various jobs informally at home or in nearby places, rather than at employers’ premises. The contribution of these female home-based workers (FHBWs) is significant to the country’s economic growth. FHBWs are often confronted with numerous occupational diseases due to a lack of awareness of occupational safety and health measures, and unhealthy living and working conditions. The informality of FHBWs prevents them from getting proper healthcare, safety, and other dispensations enjoyed by formal employees. Despite their undeniable importance, health issues of FHBWs are still overlooked. This study is an attempt to discover the frequent co-occurring occupational diseases encountered by FHBWs in Punjab, a province of Pakistan. Frequent itemset mining (FIM) or co-occurrence grouping is a technique of data science that identifies the associations among different entities in the data. Based on FIM, the D-GENE algorithm is applied in this study to efficiently discover frequent co-occurring diseases in the data obtained from the Punjab Home-based Workers Survey (2016). The far-reaching goal of the study is to bring awareness of the occupational health issues and safety risks to the health authorities as well as to the FHBWs.
Effect of Stratification of Cathode Catalyst Layers on Durability of Proton Exchange Membrane Fuel Cells
Authors: Nondudule Zikhona , Chamier Jessica , Chowdhury Mahabubur
Published: May 2021

To decrease the cost of fuel cell manufacturing, the amount of platinum (Pt) in the catalyst layer needs to be reduced. In this study, ionomer gradient membrane electrode assemblies (MEAs) were designed to reduce Pt loading without sacrificing performance and lifetime. A two-layer stratification of the cathode was achieved with varying ratios of 28 wt. % ionomer in the inner layer, on the membrane, and 24 wt. % on the outer layer, coated onto the inner layer. To study the MEA performance, the electrochemical surface area (ECSA), polarization curves, and electrochemical impedance spectroscopy (EIS) responses were evaluated under 20, 60, and 100% relative humidity (RH). The stratified MEA Pt loading was reduced by 12% while maintaining commercial equivalent performance. The optimal two-layer design was achieved when the Pt loading ratio between the layers was 1:6 (inner:outer layer). This MEA showed the highest ECSA and performance at 0.65 V with reduced mass transport losses. The integrity of stratified MEAs with lower Pt loading was evaluated with potential cycling and proved more durable than the monolayer MEA equivalent. The higher ionomer loading adjacent to the membrane and the bi-layer interface of the stratified catalyst layer (CL) increased moisture in the cathode CL, decreasing the degradation rate. Using ionomer stratification to decrease the Pt loading in an MEA yielded a better performance compared to the monolayer MEA design. This study, therefore, contributes to the development of more durable, cost-effective MEAs for low-temperature proton exchange membrane fuel cells.