bluuebunny/crossref_metadata_2025 huggingface dataset:
Epigenome-Wide Association Study of Infant Feeding and DNA Methylation in Infancy and Childhood in a Population at Increased Risk for Type 1 Diabetes
Authors: Walker-Short Elizabeth , Buckner Teresa , Vigers Timothy , Carry Patrick , Vanderlinden Lauren A. , Dong Fran , Johnson Randi K. , Yang Ivana V. , Kechris Katerina , Rewers Marian , Norris Jill M.
Published: November 2021

We assessed associations between infant diet (e.g., breastfeeding and introduction to solid foods) and DNA methylation in infancy and childhood. We measured DNA methylation in peripheral blood collected in infancy (9–15 months of age) in 243 children; and in a subset of 50 children, we also measured methylation in childhood (6–9 years of age) to examine persistence, and at birth (in cord blood) to examine temporality. We performed multivariable linear regression of infant diet on the outcome of methylation using epigenome-wide and candidate site approaches. We identified six novel CpG sites associated with breastfeeding duration using an EWAS approach. One differentially methylated site presented directionally consistent associations with breastfeeding (cg00574958, CPT1A) in infancy and childhood but not at birth. Two differentially methylated sites in infancy (cg19693031, TXNIP; cg23307264, KHSRP) were associated with breastfeeding and were not present at birth; however, these associations did not persist into childhood. Associations between infant diet and methylation in infancy at three sites (cg22369607, AP001525.1; cg2409200, TBCD; cg27173510, PGBD5) were also present at birth, suggesting the influence of exposures other than infant diet. Infant diet exposures are associated with persistent methylation differences in CPT1A, which may be one mechanism behind infant diet’s long-term health effects.
Network Pharmacology Exploration Reveals Anti-Apoptosis as a Common Therapeutic Mechanism for Non-Alcoholic Fatty Liver Disease Treated with Blueberry Leaf Polyphenols
Authors: Wang Cai-Ren , Chen Hong-Wei , Li Yan , Zhou Ming-Yue , Wong Vincent Kam-Wai , Jiang Zhi-Hong , Zhang Wei
Published: November 2021

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease characterized by excessive fat accumulation in the liver. The aim of this study is to elucidate the multi-target mechanism of polyphenols in blueberry leaves (PBL) on NAFLD by network pharmacology and to validate its results via biological experiments. Twenty constituents in PBL were preliminarily determined by liquid chromatography-tandem mass spectrometry. Subsequently, 141 predicted drug targets and 1226 targets associated with NAFLD were retrieved from public databases, respectively. The herb-compound-target network and the target protein–protein interaction network (PPI) were established through Cytoscape software, and four compounds and 53 corresponding targets were identified. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed to explore the biological processes of the predicted genes. The results of cell experiments demonstrated that PBL could significantly improve the viability of the NAFLD cell model, and the protein expressions of caspase-3 and Bcl-2 were consistent with the expected mechanism of action of PBL. Those results systematically revealed that the multi-target mechanism of PBL against NAFLD was related to the apoptosis pathway, which could bring deeper reflections into the hepatoprotective effect of PBL.
Adherence to a Mediterranean-Style Dietary Pattern and Cancer Risk in a Prospective Cohort Study
Authors: Yiannakou Ioanna , Singer Martha R. , Jacques Paul F. , Xanthakis Vanessa , Ellison R. Curtis , Moore Lynn L.
Published: November 2021

A Mediterranean-style diet is a healthy eating pattern that may benefit cancer risk, but evidence among Americans is scarce. We examined the prospective association between adherence to such a diet pattern and total cancer risk. A Mediterranean-style dietary pattern (MSDP) score was derived from a semi-quantitative food frequency questionnaire at exam 5 (1991–1995). Subjects included 2966 participants of the Framingham Offspring Study who were free of prevalent cancer. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for demographic, lifestyle, and anthropometric measures. Cox-models were also used to examine effect modification by lifestyle and anthropometric measures. During 18 years of median follow-up, 259 women and 352 men were diagnosed with cancer. Women with moderate or higher adherence to the MSDP had ≥25% lower risks of cancer than women with the lowest MSDP (HR (moderate vs. lowest): 0.71, 95% CI: 0.52–0.97 and HR (highest vs. lowest): 0.74; 95% CI: 0.55–0.99). The association between MSDP score and cancer risk in men was weaker except in non-smokers. Beneficial effects of the MSDP in women were stronger among those who were not overweight. In this study, higher adherence to MSDP was associated with lower cancer risk, especially among women.
Nut Allergy: Clinical and Allergological Features in Italian Children
Authors: Tagliati Sylvie , Barni Simona , Giovannini Mattia , Liccioli Giulia , Sarti Lucrezia , Alicandro Tatiana , Paladini Erika , Perferi Giancarlo , Azzari Chiara , Novembre Elio , Mori Francesca
Published: November 2021

Background: Nut allergies are an increasingly frequent health issue in the pediatric population. Tree nuts (TN) and peanuts are the second cause of food anaphylaxis in Italy. Unfortunately, knowledge of the clinical characteristics of a TN allergy in Italian children is limited. Our study aimed to identify the clinical and allergological characteristics of Italian children with a nut allergy (TN and peanut). Methods: A retrospective observational analysis was performed on the clinical charts of children with a history of nut reaction referred to the allergy unit of the hospital from 2015 to 2019. The studied population was represented by children with a confirmed nut allergy based on positive prick by prick and/or serum-specific IgE to nut plus a positive nut oral food challenge. Demographic, clinical, and allergological features were studied and compared among different nuts. Results: In total, 318 clinical charts were reviewed. Nut allergy was confirmed in 113 patients. Most patients (85/113, 75%) had a familial history of allergy and/or a concomitant allergic disorder (77/113, 68%). Hazelnut and walnut were the more common culprit nuts observed in allergic children. Anaphylaxis was the first clinical manifestation of nut allergy in a high percentage of children (54/113, 48%). The mean age of the first nut reaction was statistically higher with pine nuts. Over 75% of children reported a single nut reaction. During the OFCs, the signs and symptoms involved mainly the gastrointestinal system (82/113, 73%) and resolved spontaneously in most cases. Severe reactions were not frequent (22/113, 19%). Conclusion: To our knowledge, this is the first Italian study that provided a comprehensive characterization of children with a nut allergy. These results are important for clinicians treating children with a nut allergy.
Coix Seed Consumption Affects the Gut Microbiota and the Peripheral Lymphocyte Subset Profiles of Healthy Male Adults
Authors: Jinnouchi Minami , Miyahara Taisei , Suzuki Yoshio
Published: November 2021

A systematic examination of the effects of traditional herbal medicines including their mechanisms could allow for their effective use and provide opportunities to develop new medicines. Coix seed has been suggested to promote spontaneous regression of viral skin infection. Purified oil from coix seed has also been suggested to increase the peripheral CD4+ lymphocytes. We, herein, attempt to shed more light on the way through which coix seed affects the human systemic immune function by hypothesizing that a central role to these changes could be played through changes in the gut microbiota. To that end, healthy adult males (n = 19) were divided into two groups; 11 of them consumed cooked coix seed (160 g per day) for 7 days (intervention), while the other eight were given no intervention. One week of coix seed consumption lead to an increase of the intestinal Faecalibacterium abundance and of the abundance (as % presence of overall peripheral lymphocytes) of CD3+CD8+ cells, CD4+ cells, CD4+CD25+ cells, and naïve/memory T cell ratio. As the relationship of microbiota and skin infection has not been clarified, our findings could provide a clue to a mechanism through which coix seed could promote the spontaneous regression of viral skin infections.
Mechanistic Insight into Apoptotic Induction in Human Rhabdomyosarcoma and Breast Adenocarcinoma Cells by Chnoospora minima: A Sri Lankan Brown Seaweed
Authors: Gunathilaka Thilina Lakmini , Dilrangi Kulathungage Hiranthi , Ranasinghe Pathmasiri , Samarakoon Kalpa W. , Peiris L. Dinithi C.
Published: November 2021

The current study determined the cytotoxic and apoptotic potential of the polyphenol-rich methanol extract of Chnoospora minima (C. minima) and its fractions against human breast adenocarcinoma (MCF-7) and rhabdomyosarcoma (RMS) cells. MTT and neutral red assays were used to determine cytotoxicity. The clonogenic assay evaluated the antineoplastic activity, while the apoptotic activity was determined by cellular morphological changes, caspase 3/7 activity, and DNA fragmentation. Morphological alterations in apoptosis were observed by an inverted phase-contrast microscope and Hoechst 33342 staining methods. The total phenolic, flavonoids, alkaloids, and antioxidant activity in the hexane and chloroform fractions were determined, based on their cytotoxic activity. The hexane fraction of C. minima effectively reduced the cell growth that is concentration-dependent in human RMS and MCF-7 cell lines. It also exhibited low cytotoxicity on Vero cells. The characteristic cellular and nuclear apoptotic morphological features were observed. A noticeable caspase 3/7 activation and the fragmented DNA were detected only in the hexane fraction treated RMS cells, whereas MCF-7 cells showed low caspase 3/7 activation due to a lack of caspase 3 and no evidence of having a typical ladder pattern of apoptosis. Further analysis revealed that the hexane fraction-treated RMS cells upregulated the p53 gene twofold (2.72) compared to the p21 (0.77) gene, whereas in the MCF-7 cells, a 2.21-fold upregulation of p53 was observed compared to the p21 (0.64) gene. The hexane fraction exhibited moderate total phenolics, flavonoids, alkaloids content, and antioxidant activity. According to the different antioxidant mechanisms, hexane and chloroform fractions showed the highest antioxidant activities by FRAP and ORAC assays, respectively. GC-MS analysis of hexane fraction revealed the presence of methyl tetradecanoate (38.314%) as the most abundant compound. The study’s findings highlighted that the non-polar compounds present in the hexane fraction of C. minima suppressed cell proliferation and induced apoptosis-mediated cell death in RMS and MCF-7 cells, mainly via the activation of the p53 gene. Hence, the isolation of compounds is warranted. However, more studies are required to understand the mechanistic insights of these observations.
Radiolabeled Silicon-Rhodamines as Bimodal PET/SPECT-NIR Imaging Agents
Authors: Kanagasundaram Thines , Laube Markus , Wodtke Johanna , Kramer Carsten Sven , Stadlbauer Sven , Pietzsch Jens , Kopka Klaus
Published: November 2021

Radiolabeled fluorescent dyes are decisive for bimodal imaging as well as highly in demand for nuclear- and optical imaging. Silicon-rhodamines (SiRs) show unique near-infrared (NIR) optical properties, large quantum yields and extinction coefficients as well as high photostability. Here, we describe the synthesis, characterization and radiolabeling of novel NIR absorbing and emitting fluorophores from the silicon-rhodamine family for use in optical imaging (OI) combined with positron emission tomography (PET) or single photon emission computed tomography (SPECT), respectively. The presented photostable SiRs were characterized using NMR-, UV-Vis-NIR-spectroscopy and mass spectrometry. Moreover, the radiolabeling conditions using fluorine-18 or iodine-123 were extensively explored. After optimization, the radiofluorinated NIR imaging agents were obtained with radiochemical conversions (RCC) up to 70% and isolated radiochemical yields (RCY) up to 54% at molar activities of g.t. 70 GBq/µmol. Radioiodination delivered RCCs over 92% and allowed to isolate the 123I-labeled product in RCY of 54% at a molar activity of g.t. 7.6 TBq/µmol. The radiofluorinated SiRs exhibit in vitro stabilities g.t. 70% after two hours in human serum. The first described radiolabeled SiRs are a promising step toward their further development as multimodal PET/SPECT-NIR imaging agents for planning and subsequent imaging-guided oncological surgery.
The Analysis of Chlorogenic Acid and Caffeine Content and Its Correlation with Coffee Bean Color under Different Roasting Degree and Sources of Coffee (Coffea arabica Typica)
Authors: Tsai Chia-Fang , Jioe Irvan Prawira Julius
Published: November 2021

Coffee is one of the main economic crops in the world and is now widely grown throughout Taiwan. The process of roasting coffee begins with the heating and smooth expansion of raw beans, which leads to changes in appearance and color while affecting the flavor and taste of coffee. So far, most coffee manufacturers have used visual inspection or colorimeter methods to identify differences in coffee quality. Moreover, there is no literature discussing the correlation of roasted bean color with caffeine and chlorogenic acid content. Therefore, the purpose of this experiment was to analyze the chlorogenic acid and caffeine content and their correlation with bean color under different roasting degrees and from different sources to establish basic data for the rapid identification of coffee quality in the future. In this experiment, the coffee Coffea arabica typica from Dongshan, Gukeng, and Sumatra’s Indonesian rainforest was used, and the beans were roasted into four degrees: raw bean, light, medium, and dark roast, to investigate the appearance of the coffee beans and its correlation with caffeine and chlorogenic acid content. The results showed that with a higher roasting degree, caffeine content increased gradually, except for Indonesian beans, but the chlorogenic acid content in all samples showed a declining trend with the increase in roasting degree. The correlation between the chlorogenic acid content and the color space value of the coffee bean color shows that L*, a*, and h° in both ground and unground coffee are highly correlated. The C* value of the ground and unground coffee showed a correlation coefficient of r = 0.159 ns and 0.299 ns, respectively. The correlation between the caffeine content and the color space value of the unground coffee bean shows that the a*, b*, and C* value is highly correlated with the caffeine content. The color space values of ground coffee beans show no correlation with caffeine.
Purchase Intentions for Brazilian Recycled PET Products—Circular Economy Opportunities
Authors: Queiroz Fernanda Cristina Barbosa Pereira , Lima Nilton Cesar , da Silva Christian Luiz , Queiroz Jamerson Viegas , de Souza Gustavo Henrique Silva
Published: November 2021

Circular economy involves structural changes in traditional business models and consumers’ behavior toward recycled products. The recycling of PET products is increasing but there is still a gap between consumption and demand for PET packaging in Brazil. In this research, waste reduction was examined under a projective scenario to the current ecological purposes in Brazil for reducing environmental pollution. In that manner, this paper aimed to comprehend the intention to purchase recycled PET products of Brazilian consumers. With a non-probabilistic and convenience sample, the study counts 422 participants. The method employed was based on structural equation modelling and partial least Squares, used to test the hypotheses of causality among the variables. Results showed the perception of low quality about recycled products reduced consumers’ intention to purchase. Additionally, the sustainability of recycled products positively influenced the intention to purchase. In addition, recycled products presented a negative impact on the perceived safety, which could influence the purchase of recycled products in Brazil. We conclude that the image that Brazilian consumers have about recycled products positively affects the intention to purchase.
A Critical Analysis of Volatility Surprise in Bitcoin Cryptocurrency and Other Financial Assets
Authors: Doumenis Yianni , Izadi Javad , Dhamdhere Pradeep , Katsikas Epameinondas , Koufopoulos Dimitrios
Published: November 2021

The purpose of this paper is to investigate the viability as compared with other financial assets of cryptocurrencies as a currency or as an asset investment. This paper also aims to see which macro variable relates more to the price of cryptocurrencies, especially Bitcoin. Since the whole concept of cryptocurrencies is quite novel, an attempt has been made to briefly explain the underlying blockchain technology that forms the bedrock of cryptocurrencies. In this study, we use secondary data, i.e., the price history of Bitcoin from September 2014 to September 2021 for the last seven years, captured from trading exchanges. We predicted monthly returns of Bitcoin with that of Standard & Poor’s 500 Index (S&P 500), gold, and Treasury Bonds. Our findings show that Bitcoin has very high volatility compared to S&P 500, Gold and Treasury Bonds. Also, our findings show that there is a positive correlation between Bitcoin’s price volatility and the other three financial assets before and during COVID-19. Hence, Bitcoin is acting more as a speculative asset rather than a steady store of value. This can be drawn from the comparison with the debt market i.e., a Treasury Bond that invests in long-dated (30 years) US treasuries with which Bitcoin shows no relationship. The findings of this study could help with understanding the future of Bitcoin. This has important implications for Bitcoin investors. The current study contributes to the extant literature by providing empirical evidence on long-term social sustainability vis-à-vis supply chain traceability.
Phenology and Spectral Unmixing-Based Invasive Kudzu Mapping: A Case Study in Knox County, Tennessee
Authors: Shen Ming , Tang Maofeng , Li Yingkui
Published: November 2021

As an invasive plant species, kudzu has been spreading rapidly in the Southeastern United States in recent years. Accurate mapping of kudzu is critical for effective invasion control and management. However, the remote detection of kudzu distribution using multispectral images is challenging because of the mixed reflectance and potential misclassification with other vegetation. We propose a three-step classification process to map kudzu in Knox County, Tennessee, using multispectral Sentinel-2 images and the integration of spectral unmixing analysis and phenological characteristics. This classification includes an initial linear unmixing process to produce an overestimated kudzu map, a phenological-based masking to reduce misclassification, and a nonlinear unmixing process to refine the classification. The initial linear unmixing provides high producer’s accuracy (PA) but low user’s accuracy (UA) due to misclassification with grasslands. The phenological-based masking increases the accuracy of the kudzu classification and reduces the domain for further processing. The nonlinear unmixing further refines the kudzu classification via the selection of an appropriate nonlinear model. The final kudzu classification for Knox County reaches relatively high accuracy, with UA, PA, Jaccard, and Kappa index values of 0.858, 0.907, 0.789, and 0.725, respectively. Our proposed method has potential for continuous monitoring of kudzu in large areas.
Preliminary Results on Tropospheric ZTD Estimation by Smartphone
Authors: Benvenuto Lorenzo , Dabove Paolo , Ferrando Ilaria , Sguerso Domenico
Published: November 2021

The Global Navigation Satellite System (GNSS) receiver is one of the many sensors embedded in smartphones. The early versions of the Android operating system could only access limited information from the GNSS, allowing the related Application Program Interface (API) to obtain only the location. With the development of the Android 7.0 (Nougat) operating system in May 2016, raw measurements from the internal GNSS sensor installed in the smartphone could be accessed. This work aims to show an initial analysis regarding the feasibility of Zenith Total Delay (ZTD) estimation by GNSS measurements extracted from smartphones, evaluating the accuracy of estimation to open a new window on troposphere local monitoring. Two different test sites have been considered, and two different types of software for data processing have been used. ZTDs have been estimated from both a dual-frequency and a multi-constellation receiver embedded in the smartphone, and from a GNSS Continuously Operating Reference Station (CORS). The results have shown interesting performances in terms of ZTD estimation from the smartphone in respect of the estimations obtained with a geodetic receiver.
Improved Classification Models to Distinguish Natural from Anthropic Oil Slicks in the Gulf of Mexico: Seasonality and Radarsat-2 Beam Mode Effects under a Machine Learning Approach
Authors: de Oliveira Matias Ítalo , Genovez Patrícia Carneiro , Torres Sarah Barrón , de Araújo Ponte Francisco Fábio , de Oliveira Anderson José Silva , de Miranda Fernando Pellon , Avellino Gil Márcio
Published: November 2021

Distinguishing between natural and anthropic oil slicks is a challenging task, especially in the Gulf of Mexico, where these events can be simultaneously observed and recognized as seeps or spills. In this study, a powerful data analysis provided by machine learning (ML) methods was employed to develop, test, and implement a classification model (CM) to distinguish an oil slick source (OSS) as natural or anthropic. A robust database containing 4916 validated oil samples, detected using synthetic aperture radar (SAR), was employed for this task. Six ML algorithms were evaluated, including artificial neural networks (ANN), random forest (RF), decision trees (DT), naive Bayes (NB), linear discriminant analysis (LDA), and logistic regression (LR). Using RF, the global CM achieved a maximum accuracy value of 73.15. An innovative approach evaluated how external factors, such as seasonality, satellite configurations, and the synergy between them, limit or improve OSS predictions. To accomplish this, specific classification models (SCMs) were derived from the global ones (CMs), tuning the best algorithms and parameters according to different scenarios. Median accuracies revealed winter and spring to be the best seasons and ScanSAR Narrow B (SCNB) as the best beam mode. The maximum median accuracy to distinguish seeps from spills was achieved in winter using SCNB (83.05). Among the tested algorithms, RF was the most robust, with a better performance in 81% of the investigated scenarios. The accuracy increment provided by the well-fitted models may minimize the confusion between seeps and spills. This represents a concrete contribution to reducing economic and geologic risks derived from exploration activities in offshore areas. Additionally, from an operational standpoint, specific models support specialists to select the best SAR products and seasons for new acquisitions, as well as to optimize performances according to the available data.
Application of a Convolutional Neural Network for the Detection of Sea Ice Leads
Authors: Hoffman Jay P. , Ackerman Steven A. , Liu Yinghui , Key Jeffrey R. , McConnell Iain L.
Published: November 2021

Despite accounting for a small fraction of the surface area in the Arctic, long and narrow sea ice fractures, known as “leads”, play a critical role in the energy flux between the ocean and atmosphere. As the volume of sea ice in the Arctic has declined over the past few decades, it is increasingly important to monitor the corresponding changes in sea ice leads. A novel approach has been developed using artificial intelligence (AI) to detect sea ice leads using satellite thermal infrared window data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS). In this new approach, a particular type of convolutional neural network, a U-Net, replaces a series of conventional image processing tests from our legacy algorithm. Results show the new approach has a high detection accuracy with F1 Scores on the order of 0.7. Compared to the legacy algorithm, the new algorithm shows improvement, with more true positives, fewer false positives, fewer false negatives, and better agreement between satellite instruments.
Compact Thermal Imager (CTI) for Atmospheric Remote Sensing
Authors: Wu Dong L. , Jennings Donald E. , Choi Kwong-Kit , Jhabvala Murzy D. , Limbacher James A. , Flatley Thomas , Kim Kyu-Myong , La Anh T. , Salawitch Ross J. , Oman Luke D. , Gong Jie , Holmes Thomas R. , Morton Douglas C. , Hewagama Tilak , Swap Robert J.
Published: November 2021

The demonstration of a newly developed compact thermal imager (CTI) on the International Space Station (ISS) has provided not only a technology advancement but a rich high-resolution dataset on global clouds, atmospheric and land emissions. This study showed that the free-running CTI instrument could be calibrated to produce scientifically useful radiance imagery of the atmosphere, clouds, and surfaces with a vertical resolution of ~460 m at limb and a horizontal resolution of ~80 m at nadir. The new detector demonstrated an excellent sensitivity to detect the weak limb radiance perturbations modulated by small-scale atmospheric gravity waves. The CTI’s high-resolution imaging was used to infer vertical cloud temperature profiles from a side-viewing geometry. For nadir imaging, the combined high-resolution and high-sensitivity capabilities allowed the CTI to better separate cloud and surface emissions, including those in the planetary boundary layer (PBL) that had small contrast against the background surface. Finally, based on the ISS’s orbit, the stable detector performance and robust calibration algorithm produced valuable diurnal observations of cloud and surface emissions with respect to solar local time during May–October 2019, when the CTI had nearly continuous operation.
Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications
Authors: Alberternst Sebastian , Anisimov Alexander , Antakli Andre , Duppe Benjamin , Hoffmann Hilko , Meiser Michael , Muaz Muhammad , Spieldenner Daniel , Zinnikus Ingo
Published: November 2021

The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a meaningful way. In this paper, we present a thing registry and an agent-based orchestration framework, which we combine to support semantic orchestration of IoT use cases across several federated cloud environments. We use the concept of virtual sensors based on machine learning (ML) services as abstraction, mediating between the instance level and the semantic level. We present examples of virtual sensors based on ML models for activity recognition and describe an approach to remedy the problem of missing or scarce training data. We illustrate the approach with a use case from an assisted living scenario.
Reliability and Validity of the SHFT Running Power Meter
Authors: Linkis Jesper Emil , Bonne Thomas Christian , Bejder Jacob , Rasmussen Esben Krogh , Breenfeldt Andersen Andreas , Nordsborg Nikolai Baastrup
Published: November 2021

The SHFT device is a novel running wearable consisting of two pods connected to your smartphone issuing several running metrics based on accelerometer and gyroscope technology. The purpose of this study was to investigate the reliability and validity of the power output (PO) metric produced by the SHFT device. To assess reliability, 12 men ran on an outdoor track at 10.5 km·h−1 and 12 km·h−1 on two consecutive days. To assess validity, oxygen uptake (VO2) and SHFT data from eight men and seven women were collected during incremental submaximal running tests on an indoor treadmill on one to four separate days (34 tests in total). SHFT reliability on the outdoor track was strong with coefficients of variance (CV) of 1.8% and 2.4% for 10.5 and 12 km·h−1, respectively. We observed a very strong linear relationship between PO and VO2 (r2 = 0.54) within subjects, and a very strong linear relationship within each subject within each treadmill test (r2 = 0.80). We conclude that SHFT provides a reliable running power estimate and that a very strong relationship between SHFT-Power and metabolic rate exists, which places SHFT as one of the leading commercially available running power meters.
Test-Retest Reliability of PODOSmart® Gait Analysis Insoles
Authors: Loukovitis Andreas , Ziagkas Efthymios , Zekakos Dimitrios Xypolias , Petrelis Alexandros , Grouios George
Published: November 2021

It is recognized that gait analysis is a powerful tool used to capture human locomotion and quantify the related parameters. PODOSmart® insoles have been designed to provide accurate measurements for gait analysis. PODOSmart® insoles are lightweight, slim and cost-effective. A recent publication presented the characteristics and data concerning the validity of PODOSmart® insoles in gait analysis. In literature, there is still no evidence about the repeatability of PODOSmart® gait analysis system. Such evidence is essential in order to use this device in both research and clinical settings. The aim of the present study was to assess the repeatability of PODOSmart® system. In this context, it was hypothesized that the parameters of gait analysis captured by PODOSmart® would be repeatable. In a sample consisting of 22 healthy male adults, participants performed two walking trials on a six-meter walkway. The ICC values for 28 gait variables provided by PODOSmart® indicated good to excellent test-retest reliability, ranging from 0.802 to 0.997. The present findings confirm that PODOSmart® gait analysis insoles present excellent repeatability in gait analysis parameters. These results offer additional evidence regarding the reliability of this gait analysis tool.
An Empirical Study of Training Data Selection Methods for Ranking-Oriented Cross-Project Defect Prediction
Authors: Luo Haoyu , Dai Heng , Peng Weiqiang , Hu Wenhua , Li Fuyang
Published: November 2021

Ranking-oriented cross-project defect prediction (ROCPDP), which ranks software modules of a new target industrial project based on the predicted defect number or density, has been suggested in the literature. A major concern of ROCPDP is the distribution difference between the source project (aka. within-project) data and target project (aka. cross-project) data, which evidently degrades prediction performance. To investigate the impacts of training data selection methods on the performances of ROCPDP models, we examined the practical effects of nine training data selection methods, including a global filter, which does not filter out any cross-project data. Additionally, the prediction performances of ROCPDP models trained on the filtered cross-project data using the training data selection methods were compared with those of ranking-oriented within-project defect prediction (ROWPDP) models trained on sufficient and limited within-project data. Eleven available defect datasets from the industrial projects were considered and evaluated using two ranking performance measures, i.e., FPA and Norm(Popt). The results showed no statistically significant differences among these nine training data selection methods in terms of FPA and Norm(Popt). The performances of ROCPDP models trained on filtered cross-project data were not comparable with those of ROWPDP models trained on sufficient historical within-project data. However, ROCPDP models trained on filtered cross-project data achieved better performance values than ROWPDP models trained on limited historical within-project data. Therefore, we recommended that software quality teams exploit other project datasets to perform ROCPDP when there is no or limited within-project data.
A Comparative Study on the Voxel Values in Alveolar Bones Acquired by MDCT and Newly Developed Dental Dual-Energy CBCT
Authors: Chang Sungho , Lee Sang Chul
Published: November 2021

The purpose of this study was to analyze the effectiveness of newly developed dental dual-energy (DE) cone-beam computed tomography (CBCT) to compare both the voxel values in hard bone tissue of DE-CBCT and multidetector computed tomography (MDCT) images, collected in a clinical trial conducted at Seoul National University Dental Hospital. A software implemented as a scripted module of a three-dimensional (3D) slicer was developed to register the volume data from the MDCT space to DE-CBCT, locate the same 3D regions of interest (ROIs) in each image space, and extract the statistics of the ROIs. The mean values were paired and used as representative values of the ROIs. A scatter plot with the line of equality and Bland–Altman (BA) plot of difference for a pair of measured means were used for statistical analysis. Of the ROI pairs, 96% were within ±15% from the identity line, and more than 95% of the measured ROI pairs were within the limits of agreement of the 95% confidence intervals (CIs), with the CI of the limits in BA plots. The newly developed dental DE-CBCT showed a level of voxel value accuracy similar to that of MDCT.
A New Inductive Debris Sensor Based on Dual-Excitation Coils and Dual-Sensing Coils for Online Debris Monitoring
Authors: Wu Xianwei , Zhang Yinghong , Li Nian , Qian Zhenghua , Liu Dianzi , Qian Zhi , Zhang Chenchen
Published: November 2021

Lubricants are of key importance for mechanical processing, and exist in nearly every mechanical system. When the equipment is in operation, debris particles will be generated in mechanical lubricants. The detection of debris particles can indicate the wear degree of machinery components, and provide prognosis warning for the system before the fault occurs. In this work, a novel type of inductive debris sensor consisting of two excitation coils and two sensing coils is proposed for online debris monitoring. The developed sensor was proven to be of high sensitivity through experimental verification. The testing results show that, using the designed sensor, ferrous metal debris with a size of 115 μm and nonferrous metal debris with a size of 313 μm in a pipe with an inner diameter of 12.7 mm can be effectively detected. Moreover, the proposed inductive debris sensor structure has better sensitivity at higher throughput and its design provides a useful insight into the development of high-quality sensors with superior performances.
Dual-Rate Extended Kalman Filter Based Path-Following Motion Control for an Unmanned Ground Vehicle: Realistic Simulation
Authors: Carbonell Rafael , Cuenca Ángel , Casanova Vicente , Pizá Ricardo , Salt Llobregat Julián J.
Published: November 2021

In this paper, a two-wheel drive unmanned ground vehicle (UGV) path-following motion control is proposed. The UGV is equipped with encoders to sense angular velocities and a beacon system which provides position and orientation data. Whereas velocities can be sampled at a fast rate, position and orientation can only be sensed at a slower rate. Designing a dynamic controller at this slower rate implies not reaching the desired control requirements, and hence, the UGV is not able to follow the predefined path. The use of dual-rate extended Kalman filtering techniques enables the estimation of the fast-rate non-available position and orientation measurements. As a result, a fast-rate dynamic controller can be designed, which is provided with the fast-rate estimates to generate the control signal. The fast-rate controller is able to achieve a satisfactory path following, outperforming the slow-rate counterpart. Additionally, the dual-rate extended Kalman filter (DREKF) is fit for dealing with non-linear dynamics of the vehicle and possible Gaussian-like modeling and measurement uncertainties. A Simscape Multibody™ (Matlab®/Simulink) model has been developed for a realistic simulation, considering the contact forces between the wheels and the ground, not included in the kinematic and dynamic UGV representation. Non-linear behavior of the motors and limited resolution of the encoders have also been included in the model for a more accurate simulation of the real vehicle. The simulation model has been experimentally validated from the real process. Simulation results reveal the benefits of the control solution.
Pyrophosphate-Enhanced Oxidase Activity of Cerium Oxide Nanoparticles for Colorimetric Detection of Nucleic Acids
Authors: Kim Seokhwan , Han Jinjoo , Chung Heeseok , Choi Yong-Keun , Hashkavayi Ayemeh Bagheri , Zhou Yu , Park Ki Soo
Published: November 2021

In recent years, cerium oxide (CeO2) nanoparticles (NPs) have drawn significant attention owing to their intrinsic enzyme mimetic properties, which make them powerful tools for biomolecular detection. In this work, we evaluated the effect of pyrophosphate (PPi) on the oxidase activity of CeO2 NPs. The presence of PPi was found to enhance the oxidase activity of CeO2 NPs, with enhanced colorimetric signals. This particular effect was then used for the colorimetric detection of target nucleic acids. Overall, the PPi-enhanced colorimetric signals of CeO2 NPs oxidase activity were suppressed by the presence of the target nucleic acids. Compared with previous studies using CeO2 NPs only, our proposed system significantly improved the signal change (ca. 200%), leading to more sensitive and reproducible colorimetric analysis of target nucleic acids. As a proof-of-concept study, the proposed system was successfully applied to the highly selective and sensitive detection of polymerase chain reaction products derived from Klebsiella pneumoniae. Our findings will benefit the rapid detection of nucleic acid biomarkers (e.g., pathogenic bacterial DNA or RNA) in point-of-care settings.
An Overview of Machine Learning and 5G for People with Disabilities
Authors: Domingo Mari Carmen
Published: November 2021

Currently, over a billion people, including children (or about 15% of the world’s population), are estimated to be living with disability, and this figure is going to increase to beyond two billion by 2050. People with disabilities generally experience poorer levels of health, fewer achievements in education, fewer economic opportunities, and higher rates of poverty. Artificial intelligence and 5G can make major contributions towards the assistance of people with disabilities, so they can achieve a good quality of life. In this paper, an overview of machine learning and 5G for people with disabilities is provided. For this purpose, the proposed 5G network slicing architecture for disabled people is introduced. Different application scenarios and their main benefits are considered to illustrate the interaction of machine learning and 5G. Critical challenges have been identified and addressed.
Toward Integrated and Inclusive Education for Sustainability with School–University Cooperation
Authors: Naukkarinen Johanna , Jouhkimo Laura
Published: November 2021

Sustainable development has been a topic in the Finnish core curriculum for several years, but integrating this cross-cutting theme into a subject-based curriculum is perceived to be difficult. Hence, the city of Lappeenranta has developed its own educational model to support the development of pupils’ ecosocial attitudes and abilities. This study evaluates the implemented educational model by empirically examining the pupils’ perceptions of sustainability as well as studying differences between different groups of pupils. Analysis methods consisted of a combination of factor analysis, linear regression, and statistical tests for group differences. Young people were discovered to hold three different kinds of orientations to environmental issues and ecological sustainability. These were coupled with different perceptions of science, technology, and business in a way that indicates three different types of perceptions of a more holistic conception of sustainability. The significant differences in the sustainability-related perceptions between girls and boys as well as between pupils with different educational aspirations suggest that in the future, special attention needs to be paid to develop the educational model for better equity and inclusivity.
Determining the Environmental Potentials of Urban Pavements by Applying the Cradle-to-Cradle LCA Approach for a Road Network of a Midscale German City
Authors: Siverio Lima Mayara S. , Hajibabaei Mohsen , Hesarkazzazi Sina , Sitzenfrei Robert , Buttgereit Alexander , Queiroz Cesar , Haritonovs Viktors , Gschösser Florian
Published: November 2021

This study used a cradle-to-cradle Life Cycle Assessment (LCA) approach to evaluate the environmental potentials of urban pavements. For this purpose, the urban road network of the City of Münster (Germany) was selected as the case study, and comprehensive data for several phases were collected. The entire road network is composed of flexible pavements designed according to specific traffic loads and consists of main roads (MRs), main access roads (MARs), and residential roads (RSDTs). Asphalt materials, pavement structures, and maintenance strategies are predefined for each type of road and are referred to as “traditional” herein. Some pavement structures have two possible maintenance strategies, denoted by “A” and “B”, with distinguished periods of intervention. To evaluate the impact of using recycled materials, we considered alternative pavement structures composed of asphalt materials containing a greater amount of reclaimed asphalt pavement (RAP). The study was carried out considering analysis periods of 20, 50, 80, and 100 years and using two indicators: non-renewable cumulative energy demand (nr-CED) and global warming potential (GWP). The results show that the use of higher amounts of RAP can mitigate negative environmental impacts and that certain structures and maintenance strategies potentially enhance the environmental performance of road pavements. This article suggests initiatives that will facilitate the decision-making process of city administrators to achieve more sustainable road pavement constructions and provides an essential dataset inventory to support future environmental assessment studies, particularly for European cities.
Effects and Interactions of Researcher’s Motivation and Personality in Promoting Interdisciplinary and Transdisciplinary Research
Authors: Katoh Shogo , Aalbers Rick (H.L.) , Sengoku Shintaro
Published: November 2021

Motivation is one of the most important factors driving innovative activities such as interdisciplinary research (IDR) and transdisciplinary research (TDR) for the achievement of sustainable development goals (SDGs). While there has been progress in developing ex-post indicators to evaluate their performance, only a few trials have been conducted to explore how researchers’ motivations are related to their proactive participation. To address this issue, this study empirically investigates the effect of researchers’ personality traits on their attitudes toward IDR/TDR collaboration. A questionnaire survey of 228 researchers in the natural sciences, mathematics, engineering, and related interdisciplinary fields was used to test the hypotheses by regression analysis that included interaction terms. The results show that researchers’ intrinsic motivation positively affects both IDR and TDR, while their extrinsic motivation mainly affects TDR. Furthermore, researchers’ personality traits have a significant effect on interdisciplinary collaboration and regional/societal collaboration. These findings provide cues on how to effectively integrate knowledge of IDR/TDR and how to motivate and allocate researchers for successful TDR/IDR collaboration.
A Spatially-Explicit Economic and Financial Assessment of Closed-Loop Ground-Source Geothermal Heat Pumps: A Case Study for the Residential Buildings of Valle d’Aosta Region
Authors: Novelli Antonio , D’Alonzo Valentina , Pezzutto Simon , Poggio Rubén Aarón Estrada , Casasso Alessandro , Zambelli Pietro
Published: November 2021

Ground Source Heat Pumps (GSHPs) take advantage of the high thermal inertia of the ground to achieve a higher energy efficiency compared to Air Source Heat Pumps. GSHPs, therefore, have the potential to reduce heating, cooling, and domestic hot water costs, however the high installation cost of borehole heat exchangers (BHEs) limits the growth of such installations. Nevertheless, GSHPs can be profitable under certain conditions (climate, expensive fuels, subsidies, etc.), which can be identified using geo-referenced data and Geographical Information Systems (GIS). The proposed work investigates the economic and financial ability of GSHPs to cover the heat demand of the residential building stock of the Italian region Valle d’Aosta. To identify the opportunities offered by GSHPs in the Valle d’Aosta region, more than 40,000 residential buildings were analyzed using a GIS-based method. The return on the investment was then assessed based on the occurrence of two conditions—the Italian subsidies of the “Conto Termico” and the installation of rooftop photovoltaic (PV) systems—which contribute to the reduction of the initial and operation costs, respectively. The life-cycle costs of the four resulting combinations were compared with conventional systems composed of an oil/gas boiler and an air-source chiller. One of the main findings of this study is that subsidies exert a key role in the financial feasibility of GSHPs, especially for replacing gas boilers, whereas the presence of a PV system has a minor influence on the financial analysis carried out.
Research on a Compound Dual Innovation Capability Model of Intelligent Manufacturing Enterprises
Authors: Wu Shan , Zhang Jinlong
Published: November 2021

The innovation capability of enterprises is reflected in whether their products and services can meet the needs of customers and adapt to the market. After analyzing the main differences between traditional manufacturing enterprises and intelligent manufacturing enterprises, it is proposed that intelligent manufacturing enterprises share the main characteristics of digitization, automation, platformization and flat manufacturing. Based on the theory of “ambidextrous innovation”, this paper analyzes the mechanism of the innovation capability of intelligent manufacturing enterprises and notes that informatization and intellectualization are the driving forces between the innovation capability of enterprises. In addition, a “dual drive” and “ambidextrous innovation” have a direct effect on manufacturing and management, promoting products and services and comprehensively improving the quality of such products and services to enhance the core competitiveness of intelligent manufacturing enterprises. A compound dual innovation capability model for intelligent manufacturing enterprises is constructed, and the evaluation indices of the model are provided for reference. The present work provides research focuses and a theoretical framework for follow-up research on the innovation capability of intelligent manufacturing enterprises to promote the innovation and development of intelligent manufacturing enterprises.