bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Islet Transplantation Method Combining Mesenchymal Stem Cells with Recombinant Peptide Pieces, Microencapsulated Islets, and Mesh Bags
Authors: Kogawa Ryo , Nakamura Kentaro , Mochizuki Yusuke
Published: August 2020

Microencapsulated islet transplantation was widely studied as a promising treatment for type 1 diabetes mellitus. However, micro-encapsulated islet transplantation has the following problems—early dysfunction of the islets due to the inflammatory reaction at the transplantation site, and hyponutrition and hypoxia due to a lack of blood vessels around the transplantation site, and difficulty in removal of the islets. On the other hand, we proposed a cell transplantation technique called CellSaic, which was reported to enhance the vascular induction effect of mesenchymal stem cells (MSCs) in CellSaic form, and to enhance the effect of islet transplantation through co-transplantation. Therefore, we performed islet transplantation in diabetic mice by combining three components—microencapsulated islets, MSC-CellSaic, and a mesh bag that encapsulates them and enables their removal. Mesh pockets were implanted in the peritoneal cavity of Balb/c mice as implantation sites. After 4 weeks of implantation, a pocket was opened and transplanted with (1) pancreatic islets, (2) microencapsulated islets, and (3) microencapsulated islets + MSC-CellSaic. Four weeks of observation of blood glucose levels showed that the MSC-CellSaic co-transplant group showed a marked decrease in blood glucose levels, compared to the other groups. A three-component configuration of microcapsules, MSC-CellSaic, and mesh bag was shown to enhance the efficacy of islet transplantation.
Bioabsorbable Osteofixation Materials for Maxillofacial Bone Surgery: A Review on Polymers and Magnesium-Based Materials
Authors: On Sung-Woon , Cho Seoung-Won , Byun Soo-Hwan , Yang Byoung-Eun
Published: August 2020

Clinical application of osteofixation materials is essential in performing maxillofacial surgeries requiring rigid fixation of bone such as trauma surgery, orthognathic surgery, and skeletal reconstruction. In addition to the use of titanium plates and screws, clinical applications and attempts using bioabsorbable materials for osteofixation surgery are increasing with demands to avoid secondary surgery for the removal of plates and screws. Synthetic polymeric plates and screws were developed, reaching satisfactory physical properties comparable to those made with titanium. Although these polymeric materials are actively used in clinical practice, there remain some limitations to be improved. Due to questionable physical strength and cumbersome molding procedures, interests in resorbable metal materials for osteofixation emerged. Magnesium (Mg) gained attention again in the last decade as a new metallic alternative, and numerous animal studies to evaluate the possibility of clinical application of Mg-based materials are being conducted. Thanks to these researches and studies, vascular application of Mg-based biomaterials was successful; however, further studies are required for the clinical application of Mg-based biomaterials for osteofixation, especially in the facial skeleton. The review provides an overview of bioabsorbable osteofixation materials in maxillofacial bone surgery from polymer to Mg.
The Use of Electrochemical Voltammetric Techniques and High-Pressure Liquid Chromatography to Evaluate Conjugation Efficiency of Multiple Sclerosis Peptide-Carrier Conjugates
Authors: Deskoulidis Efstathios , Petrouli Sousana , Apostolopoulos Vasso , Matsoukas John , Topoglidis Emmanuel
Published: August 2020

Recent studies have shown the ability of electrochemical methods to sense and determine, even at very low concentrations, the presence and quantity of molecules or analytes including pharmaceutical samples. Furthermore, analytical methods, such as high-pressure liquid chromatography (HPLC), can also detect the presence and quantity of peptides at very low concentrations, in a simple, fast, and efficient way, which allows the monitoring of conjugation reactions and its completion. Graphite/SiO2 film electrodes and HPLC methods were previously shown by our group to be efficient to detect drug molecules, such as losartan. We now use these methods to detect the conjugation efficiency of a peptide from the immunogenic region of myelin oligodendrocyte to a carrier, mannan. The HPLC method furthermore confirms the stability of the peptide with time in a simple one pot procedure. Our study provides a general method to monitor, sense and detect the presence of peptides by effectively confirming the conjugation efficiency. Such methods can be used when designing conjugates as potential immunotherapeutics in the treatment of diseases, including multiple sclerosis.
Vascular Shutdown by Photodynamic Therapy Using Talaporfin Sodium
Authors: Suzuki Taketo , Tanaka Mamoru , Sasaki Makiko , Ichikawa Hiroshi , Nishie Hirotada , Kataoka Hiromi
Published: August 2020

Photodynamic therapy (PDT) is an attractive cancer treatment modality. Talaporfin sodium, a second-generation photosensitizer, results in lower systemic toxicity and relatively better selective tumor destruction than first-generation photosensitizers. However, the mechanism through which PDT induces vascular shutdown is unclear. In this study, the in vitro effects of talaporfin sodium-based PDT on human umbilical vein endothelial cells (HUVECs) were determined through cell viability and endothelial tube formation assays, and evaluation of the tubulin and F-actin dynamics and myosin light chain (MLC) phosphorylation. Additionally, the effects on tumor blood flow and tumor vessel destruction were assessed in vivo. In the HUVECs, talaporfin sodium-based PDT induced endothelial tube destruction and microtubule depolymerization, triggering the formation of F-actin stress fibers and a significant increase in MLC phosphorylation. However, pretreatment with the Rho-associated protein kinase (ROCK) inhibitor, Y27632, completely prevented PDT-induced stress fiber formation and MLC phosphorylation. The in vivo analysis and pathological examination revealed that the PDT had significantly decreased the tumor blood flow and the active area of the tumor vessel. We concluded that talaporfin sodium-based PDT induces the shutdown of existing tumor vessels via the RhoA/ROCK pathway by activating the Rho-GTP pathway and decreasing the tumor blood flow.
Utility of Comprehensive Serum Glycopeptide Spectra Analysis (CSGSA) for the Detection of Early Stage Epithelial Ovarian Cancer
Authors: Matsuo Koji , Tanabe Kazuhiro , Hayashi Masaru , Ikeda Masae , Yasaka Miwa , Machida Hiroko , Shida Masako , Sato Kenji , Yoshida Hiroshi , Hirasawa Takeshi , Imanishi Tadashi , Mikami Mikio
Published: August 2020

Comprehensive serum glycopeptide spectra analysis (CSGSA) evaluates >10,000 serum glycopeptides and identifies unique glycopeptide peaks and patterns via supervised orthogonal partial least-squares discriminant modeling. CSGSA was more accurate than cancer antigen 125 (CA125) or human epididymis protein 4 (HE4) for detecting early stage epithelial ovarian cancer. Combined CSGSA, CA125, and HE4 had improved diagnostic performance. Thus, CSGSA may be a useful screening tool for detecting early stage epithelial ovarian cancer.
Transition Metal Carbides (TMCs) Catalysts for Gas Phase CO2 Upgrading Reactions: A Comprehensive Overview
Authors: Zhang Qi , Pastor-Pérez Laura , Gu Sai , Ramirez Reina Tomas
Published: August 2020

Increasing demand for CO2 utilization reactions and the stable character of CO2 have motivated interest in developing highly active, selective and stable catalysts. Precious metal catalysts have been studied extensively due to their high activities, but their implementation for industrial applications is hindered due to their elevated cost. Among the materials which have comparatively low prices, transition metal carbides (TMCs) are deemed to display catalytic properties similar to Pt-group metals (Ru, Rh, Pd, Ir, Pt) in several reactions such as hydrogenation and dehydrogenation processes. In addition, they are excellent substrates to disperse metallic particles. Hence, the unique properties of TMCs make them ideal substitutes for precious metals resulting in promising catalysts for CO2 utilization reactions. This work aims to provide a comprehensive overview of recent advances on TMCs catalysts towards gas phase CO2 utilization processes, such as CO2 methanation, reverse water gas shift (rWGS) and dry reforming of methane (DRM). We have carefully analyzed synthesis procedures, performances and limitations of different TMCs catalysts. Insights on material characteristics such as crystal structure and surface chemistry and their connection with the catalytic activity are also critically reviewed.
The Photocatalytic Degradation of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin in the Presence of Silver–Titanium Based Catalysts
Authors: Samara Fatin , Ghalayini Thouraya , Abu Farha Nedal , Kanan Sofian
Published: August 2020

Polychlorinated dibenzo-p-dioxins (PCDD) are persistent toxic compounds that are ubiquitous in the environment. The photodegradation of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the presence of silver titanium oxide (AgTi) and silver titanium doped into the Y-zeolite (AgTiY) was tested using high (254 nm) and mid (302 nm) energy UV irradiation sources. AgTi and AgTiY, both showed success in the photodegradation of 2,3,7,8-TCDD dissolved in methanol/tetrahydrofuran solution. Both catalysts were found to effectively decompose TCDD at 302 nm (lower energy) reaching in between 98–99% degradation after five hours, but AgTiY showed better performance than AgTi at 60 min reaching 91% removal. Byproducts of degradation were evaluated using Gas chromatography/mass spectrometry (GC–MS), resulting in 2,3,7-trichlorodibenzo-p-dioxin, a lower chlorinated congener and less toxic, as the main degradation product. Enzyme Linked Immunosorbent Assay (ELISA) was used to evaluate the relative toxicity of the degradation byproducts were a decrease in optical density indicated that some products of degradation could be potentially more toxic than the parent TCDD. On the other hand, a decrease in toxicity was observed for the samples with the highest 2,3,7,8-TCDD degradation, confirming that AgTiY irradiated at 302 nm is an excellent choice for degrading TCDD. This is the first study to report on the efficiency of silver titanium doped zeolites for the removal of toxic organic contaminants such as dioxins and furans from aquatic ecosystems.
Insights into Interface Charge Extraction in a Noble-Metal-Free Doped Z-Scheme NiO@BiOCl Heterojunction
Authors: Yang Jun , Zhu Quanxi , Xie Taiping , Wang Jiankang , Peng Yuan , Wang Yajing , Liu Chenglun , Xu Longjun
Published: August 2020

It is of great significance to thoroughly explore the interface charge extraction and migration in heterojunction systems, which could guide us to synthesize higher-efficiency photocatalytic materials. A novel noble-metal-free doped Z-scheme NiO@BiOCl heterojunction was found in this work. The corresponding heterostructure, interface electron extraction, and electron migration were investigated via first-principles calculation. 5,5′-dimethyl-1-pyrroline-N-oxide (DMPO) spin-trapping electron spin resonance (ESR) and time-resolved photoluminescence (TRPL) tests were implemented to confirm the calculation results, which showed that electrons and holes stayed in the NiO (100) facet and BiOCl (110) facet, respectively. Owing to the large chemical potential of 2.40 V (vs ENHE) for the BiOCl valence-band hole, it possessed super activity to oxidize water into hydroxyl radicals or molecular oxygen. We hope this promising multifunctional photocatalytic material, therefore, NiO@BiOCl can be applied in advanced treatment of organic wastewater and oxygen production from photolysis water.
Ischemia-Like Stress Conditions Stimulate Trophic Activities of Adipose-Derived Stromal/Stem Cells
Authors: Bachmann Julia , Ehlert Elias , Becker Matthias , Otto Christoph , Radeloff Katrin , Blunk Torsten , Bauer-Kreisel Petra
Published: August 2020

Adipose-derived stromal/stem cells (ASCs) have been shown to exert regenerative functions, which are mainly attributed to the secretion of trophic factors. Upon transplantation, ASCs are facing an ischemic environment characterized by oxygen and nutrient deprivation. However, current knowledge on the secretion capacity of ASCs under such conditions is limited. Thus, the present study focused on the secretory function of ASCs under glucose and oxygen deprivation as major components of ischemia. After exposure to glucose/oxygen deprivation, ASCs maintained distinct viability, but the metabolic activity was greatly reduced by glucose limitation. ASCs were able to secrete a broad panel of factors under glucose/oxygen deprivation as revealed by a cytokine antibody array. Quantification of selected factors by ELISA demonstrated that glucose deprivation in combination with hypoxia led to markedly higher secretion levels of the angiogenic and anti-apoptotic factors IL-6, VEGF, and stanniocalcin-1 as compared to the hypoxic condition alone. A conditioned medium of glucose/oxygen-deprived ASCs promoted the viability and tube formation of endothelial cells, and the proliferation and migration of fibroblasts. These findings indicate that ASCs are stimulated by ischemia-like stress conditions to secrete trophic factors and would be able to exert their beneficial function in an ischemic environment.
Arabidopsis thaliana cbp80, c2h2, and flk Knockout Mutants Accumulate Increased Amounts of Circular RNAs
Authors: Philips Anna , Nowis Katarzyna , Stelmaszczuk Michal , Podkowiński Jan , Handschuh Luiza , Jackowiak Paulina , Figlerowicz Marek
Published: August 2020

Circular RNAs (circRNAs) are the products of the non-canonical splicing of pre-mRNAs. In contrast to humans and animals, our knowledge of the biogenesis and function of circRNAs in plants is very scarce. To identify proteins involved in plant circRNA generation, we characterized the transcriptomes of 18 Arabidopsis thaliana knockout mutants for genes related to splicing. The vast majority (>90%) of circRNAs were formed in more than one variant; only a small fraction of circRNAs was mutant-specific. Five times more circRNA types were identified in cbp80 and three times more in c2h2 mutants than in the wild-type. We also discovered that in cbp80, c2h2 and flk mutants, the accumulation of circRNAs was significantly increased. The increased accumulation of circular transcripts was not accompanied by corresponding changes in the accumulation of linear transcripts. Our results indicate that one of the roles of CBP80, C2H2 and FLK in splicing is to ensure the proper order of the exons. In the absence of one of the above-mentioned factors, the process might be altered, leading to the production of circular transcripts. This suggests that the transition toward circRNA production can be triggered by factors sequestering these proteins. Consequently, the expression of linear transcripts might be regulated through circRNA production.
Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning
Authors: Ye Xiucai , Zhang Weihang , Futamura Yasunori , Sakurai Tetsuya
Published: August 2020

High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes causing cell-to-cell variability for understanding tumor heterogeneity. However, most existing methods detect the related genes separately, without considering gene interactions. In this paper, we proposed a novel learning framework to detect the interactive gene groups for scRNA-seq data based on co-expression network analysis and subgraph learning. We first utilized spectral clustering to identify the subpopulations of cells. For each cell subpopulation, the differentially expressed genes were then selected to construct a gene co-expression network. Finally, the interactive gene groups were detected by learning the dense subgraphs embedded in the gene co-expression networks. We applied the proposed learning framework on a real cancer scRNA-seq dataset to detect interactive gene groups of different cancer subtypes. Systematic gene ontology enrichment analysis was performed to examine the detected genes groups by summarizing the key biological processes and pathways. Our analysis shows that different subtypes exhibit distinct gene co-expression networks and interactive gene groups with different functional enrichment. The interactive genes are expected to yield important references for understanding tumor heterogeneity.
Considerations for Comparing Video Game AI Agents with Humans
Authors: Madan Christopher R.
Published: August 2020

Video games are sometimes used as environments to evaluate AI agents’ ability to develop and execute complex action sequences to maximize a defined reward. However, humans cannot match the fine precision of the timed actions of AI agents; in games such as StarCraft, build orders take the place of chess opening gambits. However, unlike strategy games, such as chess and Go, video games also rely heavily on sensorimotor precision. If the “finding” was merely that AI agents have superhuman reaction times and precision, none would be surprised. The goal is rather to look at adaptive reasoning and strategies produced by AI agents that may replicate human approaches or even result in strategies not previously produced by humans. Here, I will provide: (1) an overview of observations where AI agents are perhaps not being fairly evaluated relative to humans, (2) a potential approach for making this comparison more appropriate, and (3) highlight some important recent advances in video game play provided by AI agents.
Ranchers Adapting to Climate Variability in the Upper Colorado River Basin, Utah
Authors: Akbar Hadia , Allen L. , Rosenberg David , Chikamoto Yoshimitsu
Published: August 2020

In the Upper Colorado River Basin, agriculture is a major contributor to Utah’s economy, which may be stressed due to the changing climate. In this study, two data-mining techniques and interview data are used to explore how climate variability affects agricultural production and the way the farmers have been adapting their practices to these changes. In the first part of the study, we used multilinear regression and random forest regression to understand the relationship between climate and agricultural production using temperature, precipitation, water availability, hay production, and cattle herd size. The quantitative results showed weak relations among variables. In the second part of the study, we interviewed ranchers to fill the gaps in the quantitative analysis. Over the 35 years (1981–2015), the quantitative analysis shows that temperature has affected cattle and hay production more than precipitation. Among non-climatic variables, resource availability and commodity prices are the most important factors that influence year-to-year production. Farmers are well-aware of these effects and have adapted accordingly. They have changed irrigation practices, cropping patterns, and are experimenting to produce a hybrid species of cattle, that are resilient to a hotter temperature and can use a wider variety of forage.
Impact of Climate Change on Land Suitability for the Optimization of the Irrigation System in the Anger River Basin, Ethiopia
Authors: Dawit Meseret , Dinka Megarsa Olumana , Leta Olkeba Tolessa , Muluneh Fiseha Behulu
Published: August 2020

Evaluating climate change impacts and the suitability of potential land resources is crucial for sustainable irrigated agricultural systems. This study applied a multi-criteria analysis supported by the Geographic Information System (GIS) application to produce irrigation suitability maps for the Anger River basin’s (Ethiopia) irrigation command area to optimize its irrigation system. Six irrigation suitability factors, such as distance to water sources (rivers), slope, land use/land cover, soil texture, drainage, and depth, including climate change impacts, were used. These factors were spatially analyzed using a comparison matrix and overlying the factors with 30 m resolutions to estimate the potential irrigable area. About 40% of the study area was classified as moderately to highly suitable for surface water irrigation systems. Moreover, we found that a large proportion of the study area is suitable for surface irrigation system, suggesting the relevance of implementing an enhanced irrigation system for improving the surface irrigation water productivity of the basin. However, future climate change is predicted to negatively affect the irrigation suitable area due to water scarcity. Therefore, this study provides useful information on the irrigation suitability and potential of the study area that could be used to facilitate the water resource development and food security plans.
Simulation of Porous Magnetite Deposits on Steam Generator Tubes in Circulating Water at 270 °C
Authors: Jeon Soon-Hyeok , Shim Hee-Sang , Lee Ji-Min , Han Jeoh , Hur Do Haeng
Published: August 2020

In the secondary side of pressurized water reactors (PWRs), the main corrosion product accumulated on the steam generator (SG) tubes is magnetite, which has a porous structure. The purpose of this work is to simulate the porous magnetite deposited to the SG tubes using a loop system. We newly developed a circulating loop system for a porous magnetite deposition test. A test section was designed as a single hydraulic flow channel, and a cartridge heater was fabricated and mounted into a commercial SG tube to provide an equal heating source for the primary water. After the deposition test, the simulated magnetite deposits were characterized for comparison to real SG tube deposits collected from an operating PWR plant. The magnetite deposits produced using the loop system were appropriate for simulating the real SG tube deposits because the particle characteristics, phase, and porous morphology are closely similar to those of real deposit samples. Using the loop system, the chemical impurities such as Na and Cl can be easily concentrated within the pores of the simulated magnetite deposits. These simulated magnetite samples are expected to be widely utilized in various research fields such as the heat transfer degradation and magnetite accelerated corrosion of SG tubes.
The Role of Substitution in the Apex Position of the Bent-Core on Mesomorphic Properties of New Series of Liquid Crystalline Materials
Authors: Skopalová Helena , Špaček Petr , Kozmík Václav , Svoboda Jiří , Novotná Vladimíra , Pociecha Damian , Kohout Michal
Published: August 2020

We present the synthesis and mesomorphic properties of the new series of bent-core liquid crystals based on 3-hydroxybenzoic acid bearing a lateral substituent in the apex position. Four different substituents of various sizes and electronic properties have been used. We have found that only compounds substituted with fluorine are mesogenic and exhibit one mesophase, whose type differs when prolonging the terminal alkyl chain. For homologues with shorter alkyl chains (octyl, decyl), a columnar B1-type of a mesophase was observed, while materials with longer terminal chains (dodecyl, tetradecyl) exhibited a switchable lamellar SmCAPA phase. Calorimetric measurements, texture observations under a polarizing microscope were performed and electro-optical properties studied. Additionally, dielectric measurements were realized to characterize the molecular dynamics in the SmCAPA phase. All mesogenic compounds were further studied by X-ray measurements to confirm phase identification and obtain more information about their structural parameters.
Electron-Beam-Induced Current and Cathodoluminescence Study of Dislocations in SrTiO3
Authors: Yi Wei , Chen Jun , Sekiguchi Takashi
Published: August 2020

Electron-beam-induced current (EBIC) and cathodoluminescence (CL) have been applied to investigate the electrical and optical behaviors of dislocations in SrTiO3. The electrical recombination activity and defect energy levels of dislocations have been deduced from the temperature-dependent EBIC measurement. Dislocations contributed to resistive switching were clarified by bias-dependent EBIC. The distribution of oxygen vacancies around dislocations has been obtained by CL mapping. The correlation between switching, dislocation and oxygen vacancies was discussed.
A Novel Shadowgraphic Inline Measurement Technique for Image-Based Crystal Size Distribution Analysis
Authors: Wirz Dominic , Hofmann Marc , Lorenz Heike , Bart Hans-Jörg , Seidel-Morgenstern Andreas , Temmel Erik
Published: August 2020

A novel shadowgraphic inline probe to measure crystal size distributions (CSD), based on acquired greyscale images, is evaluated in terms of elevated temperatures and fragile crystals, and compared to well-established, alternative online and offline measurement techniques, i.e., sieving analysis and online microscopy. Additionally, the operation limits, with respect to temperature, supersaturation, suspension, and optical density, are investigated. Two different substance systems, potassium dihydrogen phosphate (prisms) and thiamine hydrochloride (needles), are crystallized for this purpose at 25 L scale. Crystal phases of the well-known KH2PO4/H2O system are measured continuously by the inline probe and in a bypass by the online microscope during cooling crystallizations. Both measurement techniques show similar results with respect to the crystal size distribution, except for higher temperatures, where the bypass variant tends to fail due to blockage. Thiamine hydrochloride, a substance forming long and fragile needles in aqueous solutions, is solidified with an anti-solvent crystallization with ethanol. The novel inline probe could identify a new field of application for image-based crystal size distribution measurements, with respect to difficult particle shapes (needles) and elevated temperatures, which cannot be evaluated with common techniques.
A National Survey of Managed Honey Bee Colony Winter Losses (Apis mellifera) in China (2013–2017)
Authors: Tang Jiao , Ma Cuiyan , Shi Wei , Chen Xiao , Liu Zhiguang , Wang Huihua , Chen Chao
Published: August 2020

Surveys of managed honey bee colony losses worldwide have become fundamental for engineering a sustainable and systematic approach to protect honey bees. Though China is a member of the world’s apiculture superpowers, the investigation of honey bee colony losses from Chinese government was not formally launched until recently. In this study, we investigated the colony winter losses of the western honey bee (Apis mellifera) of four consecutive years in 2013–2017 from 19 provinces in China, with a total of 2387 responding Chinese beekeepers (195 hobby beekeepers, 1789 side-line beekeepers, 403 commercial beekeepers) providing the records of overwintering mortality of honey bee colonies. The calculated colony losses were 8.7%, a relatively low mortality below the world average. There still exist considerable variations in total losses among provinces (ranging from 0.9% to 22.0%), years (ranging from 8.1% to 10.6%) and scales of apiaries (ranging from 7.5% to 10.0%). Furthermore, we deeply analyzed and estimated the effects of potential risk factors on the colonies’ winter losses, and speculated that the queen problems, the operation sizes and proportion of new queens are leading causes of the high honey bee colony mortality in China. More research and advanced technical methods are still required for correlation analysis and verification in future surveys of managed honey bee colony winter losses.
Inferring Species Interactions from Long-Term Monitoring Programs: Carnivores in a Protected Area from Southern Patagonia
Authors: Díaz-Ruiz Francisco , Rodríguez Alejandro , Procopio Diego , Zapata Sonia , Zanón-Martínez Juan Ignacio , Travaini Alejandro
Published: August 2020

Protected areas recently created in Argentina often include previously degraded lands, such as sheep ranches in the Patagonian deserts. We show the results of a 14-year monitoring program of three formerly persecuted carnivores, the culpeo fox (Lycalopex culpaeus), the South American grey fox (Lycalopex griseus) and the puma (Puma concolor), in two abandoned sheep ranches that were incorporated into a Patagonian national park approximately 25 years ago. The culpeo fox population underwent an average annual decline of 10–23%, whereas the grey fox and puma populations increased at an average annual rate of 7% and 19%, respectively. The grey fox’s increasing trends were strongly correlated with the decline of the culpeo fox, whereas the correlations between the fox and puma trends were weaker. Culpeo fox decline was stronger in the ranch where sheep and predator controls had been removed earlier. These relationships between species trends support the competitive release hypothesis, assuming that puma competition with the culpeo fox for trophic resources is stronger than competition with the grey fox, and that the puma can exclude culpeo foxes through interference. Species trends suggest a competitive hierarchy between fox species, with grey fox being the inferior competitor. However, mechanisms other than competition could not be discounted. Our study illustrates how long-term monitoring of interacting species allows a better understanding of ecological processes and wildlife ecology.
microRNA Expression Profile in Single Hormone Receptor-Positive Breast Cancers Is Mainly Dependent on HER2 Status—A Pilot Study
Authors: Kunc Michał , Popęda Marta , Szałkowska Anna , Niemira Magdalena , Bieńkowski Michał , Pęksa Rafał , Łacko Aleksandra , Radecka Barbara S. , Braun Marcin , Pikiel Joanna , Litwiniuk Maria , Pogoda Katarzyna , Iżycka-Świeszewska Ewa , Krętowski Adam , Żaczek Anna J. , Biernat Wojciech , Senkus-Konefka Elżbieta
Published: August 2020

Estrogen (ER) and progesterone (PgR) receptors and HER2 are crucial in the assessment of breast cancer specimens due to their prognostic and predictive significance. Single hormone receptor-positive breast cancers are less common and their clinical course is less favorable than ER(+)/PgR(+) tumors. Their molecular features, especially microRNA (miRNA) profiles, have not been investigated to date. Tumor specimens from 36 chemonaive breast cancer patients with known ER and PgR status (18 ER(+)/PgR(−) and 18 ER(−)/PgR(+) cases) were enrolled to the study. The expression of 829 miRNAs was evaluated with nCounter Human v3 miRNA expression Assay (NanoString). miRNAs differentiating between ER/PgR/HER2 phenotypes were selected based on fold change (FC) calculated for the mean normalized counts of each probe in compared groups. The differences were estimated with Student’s t-test or Two-Way ANOVA (considering also the HER2 status). The results were validated using The Cancer Genome Atlas (TCGA) dataset. Following quality control of raw data, fourcases were excluded due to low sample quality, leaving 14 ER(+)/PgR(−) and 18 ER(−)/PgR(+) cases. After correction for multiple comparisons, we did not find miRNA signature differentiating between ER(−)/PgR(+) and ER(+)/PgR(−) breast cancers. However, a trend for differing expression (p-value ≤ 0.05; FDR > 0.2; ANOVA) in eight miRNAs was observed. The ER(+)/PgR(−) group demonstrated elevated levels of four miRNAs—miR-30a-5p, miR-29c-3p, miR-141-3p and miR-423-5p—while the ER(−)/PgR(+) tumors were enriched in another four miRNAs—miR-514b-5p, miR-424-5p, miR-495-3p, and miR-92a-3p. For one of the miRNAs—miR-29c-3p—the association with the ER(+)/PgR(−) phenotype was confirmed in the TCGA cohort (p-value = 0.024; t-test). HER2 amplification/overexpression in the NanoString cohort was related to significant differences observed in 33 miRNA expression levels (FDR ≤ 0.2; ANOVA). The association with HER2 status was confirmed in the TCGA cohort for four miRNAs (miR-1180-3p, miR-223-3p, miR-30d-5p, and miR-195-5p). The main differences in miRNA expression amongst single hormone receptor-positive tumors were identified according to their HER2 status. However, ER(+)/PgR(−) cases tended to express higher levels of miRNAs associated with ER-positivity (miR-30a-5p, miR-29c-3p, miR-141-3p), whereas ER(−)/PgR(+) cancers showed elevated levels of miRNAs characteristic for double- and triple-negative tumors (miR-92a-3p, miR-424-5p). Further studies are necessary to comprehensively analyze miRNA signatures characteristic of ER(−)/PgR(+) and ER(+)/PgR(−) tumors.
The Model for Early COvid-19 Recognition (MECOR) Score: A Proof-of-Concept for a Simple and Low-Cost Tool to Recognize a Possible Viral Etiology in Community-Acquired Pneumonia Patients during COVID-19 Outbreak
Authors: Sambataro Gianluca , Giuffrè Mauro , Sambataro Domenico , Palermo Andrea , Vignigni Giovanna , Cesareo Roberto , Crimi Nunzio , Torrisi Sebastiano Emanuele , Vancheri Carlo , Malatino Lorenzo , Colaci Michele , Del Papa Nicoletta , Pignataro Francesca , Roman-Pognuz Erik , Fabbiani Massimiliano , Montagnani Francesca , Cassol Chiara , Cavagna Lorenzo , Zuccaro Valentina , Zerbato Verena , Maurel Cristina , Luzzati Roberto , Di Bella Stefano
Published: August 2020

This study aims to assess the peripheral blood cell count “signature” of Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) to discriminate promptly between COronaVIrus Disease 19 (COVID-19) and community-acquired pneumonia (CAP). We designed a retrospective case-control study, enrolling 525 patients (283 COVID-19 and 242 with CAP). All patients had a fever and at least one of the following signs: cough, chest pain, or dyspnea. We excluded patients treated with immunosuppressants, steroids, or affected by diseases known to modify blood cell count. COVID-19 patients showed a significant reduction in white blood cells (neutrophils, lymphocytes, monocytes, eosinophils) and platelets. We studied these parameters univariately, combined the significant ones in a multivariate model (AUROC 0.86, Nagelkerke PSEUDO-R2 0.5, Hosmer–Lemeshow p-value 0.9) and examined its discriminative performance in an internally-randomized validation cohort (AUROC 0.84). The cut-off selected according to Youden’s Index (−0.13) showed a sensitivity of 84% and a specificity of 72% in the training cohort, and a sensitivity of 88% and a specificity of 73% in the validation cohort. In addition, we determined the probability of having COVID-19 pneumonia for each Model for possible Early COvid-19 Recognition (MECOR) Score value. In conclusion, our model could provide a simple, rapid, and cheap tool for prompt COVID-19 diagnostic triage in patients with CAP. The actual effectiveness should be evaluated in further, prospective studies also involving COVID-19 patients with negative nasopharyngeal swabs.
Application of the Variance Delay Fuzzy Approximate Entropy for Autonomic Nervous System Fluctuation Analysis in Obstructive Sleep Apnea Patients
Authors: Li Yifan , Wu Shan , Yang Quanan , Liu Guanzheng , Ge Leijiao
Published: August 2020

Obstructive sleep apnea (OSA) is a fatal respiratory disease occurring in sleep. OSA can induce declined heart rate variability (HRV) and was reported to have autonomic nerve system (ANS) dysfunction. Variance delay fuzzy approximate entropy (VD_fApEn) was proposed as a nonlinear index to study the fluctuation change of ANS in OSA patients. Sixty electrocardiogram (ECG) recordings of the PhysioNet database (20 normal, 14 mild-moderate OSA, and 26 severe OSA) were intercepted for 6 h and divided into 5-min segments. HRV analysis were adopted in traditional frequency domain, and nonlinear HRV indices were also calculated. Among these indices, VD_fApEn could significantly differentiate among the three groups (p < 0.05) compared with the ratio of low frequency power and high frequency power (LF/HF ratio) and fuzzy approximate entropy (fApEn). Moreover, the VD_fApEn (90%) reached a higher OSA screening accuracy compared with LF/HF ratio (80%) and fApEn (78.3%). Therefore, VD_fApEn provides a potential clinical method for ANS fluctuation analysis in OSA patients and OSA severity analysis.
Testing the Ricardian Equivalence Theorem: Time Series Evidence from Turkey
Authors: İkiz Ahmet Salih
Published: August 2020

Two of the most common measures adopted by the government to stimulate the economy are increasing government borrowings and implementing tax cuts. These tax cuts are financed through increased debt. According to the Ricardian equivalence theory, the consumers will not change their current spending when they anticipate a tax increase in the future. In order to pay high taxes in the future, the government should increase its present savings. However, the extent of applicability of Ricardian equivalence could vary across nations. In this context, the present study explores the long-running relationship between domestic borrowing and private savings in Turkey. For this purpose, the researcher collected the data for key variables, gross domestic savings, and government debt, for the period of 1980–2017. The researcher used unit root, cointegration, VECM, and the Granger causality test to examine the relationships among the variables. Apart from this, ARDL regression was used in order to examine the long-term relationships among the variables. The empirical results indicate that there is presence of bidirectional causality, indicating that Ricardian equivalence is applicable in the economy. Households display a rational behavior by increasing their savings during the periods in which high government expenditure is incurred.
Ecocentric Education: Introduction to a Special Collection of Essays
Authors: Kopnina Helen
Published: August 2020

This Special Issue “Ecocentric education” contains articles focused on ecological values in environmental education (EE) and education for sustainable development (ESD) [...]
Scientific Mapping of Gamification in Web of Science
Authors: López-Belmonte Jesús , Parra-González Mª Elena , Segura-Robles Adrián , Pozo-Sánchez Santiago
Published: August 2020

Education is a constantly changing field. The new teaching processes are developed today and all teachers should be prepared. Gamification is one of the methodologies with the greatest impact on the learning process. The objective of the study is to analyze the relevance and progression that the concepts “gamification” and “learning” have acquired in the scientific literature of Web of Science. This research has been based on a bibliometric methodology. A classic bibliometric and thematic analyses have been carried out. A 1230 document matrix analysis has been selected. For descriptive bibliometrics, the Bibliometrix library is used, while Scimat is used for the thematic analysis. Both tools are widely used in this type of study. Results indicate that growth on the study of these topics is booming. There are also authors who accumulate most of the documents, such as Martí Parreño. English is positioned as the predominant language. The topics studied have evolved from how classic games affect learning to the study of video games and their impact on performance. It is concluded that these types of studies are still relevant and with a great future prospect. Furthermore, research focuses especially on video games, on the effects of technology on learning and on the study of flipped learning experiences.
A Bi-Level Path Planning Algorithm for Multi-AGV Routing Problem
Authors: Yuan Zhiheng , Yang Zhengmao , Lv Lingling , Shi Yanjun
Published: August 2020

Avoiding the multi-automated guided vehicle (AGV) path conflicts is of importance for the efficiency of the AGV system, and we propose a bi-level path planning algorithm to optimize the routing of multi-AGVs. In the first level, we propose an improved A* algorithm to plan the AGV global path in the global topology map, which aims to make the path shortest and reduce the AGV path conflicts as much as possible. In the second level, we present the dynamic rapidly-exploring random trees (RRT) algorithm with kinematic constraints to obtain the passable local path with collisions in the local grid map. Compared to the Dijkstra algorithm and classic A* algorithm, the simulation results showed that the proposed bi-level path planning algorithm performed well in terms of the search efficiency, significantly reducing the incidence of multiple AGV path conflicts.
Flexible and Scalable Software Defined Radio Based Testbed for Large Scale Body Movement
Authors: Ashleibta Aboajeila Milad , Zahid Adnan , Shah Syed Aziz , Abbasi Qammer H. , Imran Muhammad Ali
Published: August 2020

Human activity (HA) sensing is becoming one of the key component in future healthcare system. The prevailing detection techniques for IHA uses ambient sensors, cameras and wearable devices that primarily require strenuous deployment overheads and raise privacy concerns as well. This paper proposes a novel, non-invasive, easily-deployable, flexible and scalable test-bed for identifying large-scale body movements based on Software Defined Radios (SDRs). Two Universal Software Radio Peripheral (USRP) models, working as SDR based transceivers, are used to extract the Channel State Information (CSI) from continuous stream of multiple frequency subcarriers. The variances of amplitude information obtained from CSI data stream are used to infer daily life activities. Different machine learning algorithms namely K-Nearest Neighbour, Decision Tree, Discriminant Analysis and Naïve Bayes are used to evaluate the overall performance of the test-bed. The training, validation and testing processes are performed by considering the time-domain statistical features obtained from CSI data. The K-nearest neighbour outperformed all aforementioned classifiers, providing an accuracy of 89.73%. This preliminary non-invasive work will open a new direction for design of scalable framework for future healthcare systems.
Recent Progress in Sensing and Computing Techniques for Human Activity Recognition and Motion Analysis
Authors: Meng Zhaozong , Zhang Mingxing , Guo Changxin , Fan Qirui , Zhang Hao , Gao Nan , Zhang Zonghua
Published: August 2020

The recent scientific and technical advances in Internet of Things (IoT) based pervasive sensing and computing have created opportunities for the continuous monitoring of human activities for different purposes. The topic of human activity recognition (HAR) and motion analysis, due to its potentiality in human–machine interaction (HMI), medical care, sports analysis, physical rehabilitation, assisted daily living (ADL), children and elderly care, has recently gained increasing attention. The emergence of some novel sensing devices featuring miniature size, a light weight, and wireless data transmission, the availability of wireless communication infrastructure, the progress of machine learning and deep learning algorithms, and the widespread IoT applications has promised new opportunities for a significant progress in this particular field. Motivated by a great demand for HAR-related applications and the lack of a timely report of the recent contributions to knowledge in this area, this investigation aims to provide a comprehensive survey and in-depth analysis of the recent advances in the diverse techniques and methods of human activity recognition and motion analysis. The focus of this investigation falls on the fundamental theories, the innovative applications with their underlying sensing techniques, data fusion and processing, and human activity classification methods. Based on the state-of-the-art, the technical challenges are identified, and future perspectives on the future rich, sensing, intelligent IoT world are given in order to provide a reference for the research and practices in the related fields.
Toward Blockchain-Enabled Privacy-Preserving Data Transmission in Cluster-Based Vehicular Networks
Authors: Joshi Gyanendra Prasad , Perumal Eswaran , Shankar K. , Tariq Usman , Ahmad Tariq , Ibrahim Atef
Published: August 2020

In recent times, vehicular ad hoc networks (VANET) have become a core part of intelligent transportation systems (ITSs), which aim to achieve continual Internet connectivity among vehicles on the road. The VANET has been used to improve driving safety and construct an ITS in modern cities. However, owing to the wireless characteristics, the message transmitted through the network can be observed, altered, or forged. Since driving safety is a major part of VANET, the security and privacy of these messages must be preserved. Therefore, this paper introduces an efficient privacy-preserving data transmission architecture that makes use of blockchain technology in cluster-based VANET. The cluster-based VANET architecture is used to achieve load balancing and minimize overhead in the network, where the clustering process is performed using the rainfall optimization algorithm (ROA). The ROA-based clustering with blockchain-based data transmission, called a ROAC-B technique, initially clusters the vehicles, and communication takes place via blockchain technology. A sequence of experiments was conducted to ensure the superiority of the ROAC-B technique, and several aspects of the results were considered. The simulation outcome showed that the ROAC-B technique is superior to other techniques in terms of packet delivery ratio (PDR), end to end (ETE) delay, throughput, and cluster size.
Optimal User Selection for High-Performance and Stabilized Energy-Efficient Federated Learning Platforms
Authors: Jeon Joohyung , Park Soohyun , Choi Minseok , Kim Joongheon , Kwon Young-Bin , Cho Sungrae
Published: August 2020

Federated learning-enabled edge devices train global models by sharing them while avoiding local data sharing. In federated learning, the sharing of models through communication between several clients and central servers results in various problems such as a high latency and network congestion. Moreover, battery consumption problems caused by local training procedures may impact power-hungry clients. To tackle these issues, federated edge learning (FEEL) applies the network edge technologies of mobile edge computing. In this paper, we propose a novel control algorithm for high-performance and stabilized queue in FEEL system. We consider that the FEEL environment includes the clients transmit data to associated federated edges; these edges then locally update the global model, which is downloaded from the central server via a backhaul. Obtaining greater quantities of local data from the clients facilitates more accurate global model construction; however, this may be harmful in terms of queue stability in the edge, owing to substantial data arrivals from the clients. Therefore, the proposed algorithm varies the number of clients selected for transmission, with the aim of maximizing the time-averaged federated learning accuracy subject to queue stability. Based on this number of clients, the federated edge selects the clients to transmit on the basis of resource status.
IoT-Inspired Framework of Intruder Detection for Smart Home Security Systems
Authors: Ahanger Tariq Ahamed , Tariq Usman , Ibrahim Atef , Ullah Imdad , Bouteraa Yassine
Published: August 2020

The proliferation of IoT devices has led to the development of smart appliances, gadgets, and instruments to realize a significant vision of a smart home. Conspicuously, this paper presents an intelligent framework of a foot-mat-based intruder-monitoring and detection system for a home-based security system. The presented approach incorporates fog computing technology for analysis of foot pressure, size, and movement in real time to detect personnel identity. The task of prediction is realized by the predictive learning-based Adaptive Neuro-Fuzzy Inference System (ANFIS) through which the proposed model can estimate the possibility of an intruder. In addition to this, the presented approach is designed to generate a warning and emergency alert signals for real-time indications. The presented framework is validated in a smart home scenario database, obtained from an online repository comprising 49,695 datasets. Enhanced performance was registered for the proposed framework in comparison to different state-of-the-art prediction models. In particular, the presented model outperformed other models by obtaining efficient values of temporal delay, statistical performance, reliability, and stability.