bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparison of Diet Quality in a Sample of Rural and Urban Australian Adults
Authors: Pullen Rebekah , Kent Katherine , Sharman Matthew J. , Schumacher Tracy L. , Brown Leanne J.
Published: November 2021

The diet quality of rural Australians is under researched. Characterising disparities in diet quality between rural and urban populations may inform targeted interventions in at- risk groups. A cross-sectional study aimed to determine the relationship between diet quality, rurality and sociodemographic characteristics in a sample of Australian adults. Participants were recruited at rural and regional events between 2017 and 2020, in New South Wales, Australia. Diet quality was measured using the Healthy Eating Quiz or Australian Eating Survey to generate an Australian Recommended Food Score (ARFS). ARFS was compared by rurality and sociodemographic characteristics using multivariate regression. Participants (n = 247; 53% female) had a mean ± SD ARFS of 34.5 ± 9.0. There was no significant effect of rurality on ARFS (β-coefficient = −0.4; 95%CI −3.0, 2.3). Compared to participants aged 18–30 years, higher ARFS was evident for those aged 31–50 (β = 5.4; 95%CI 0.3, 10.4), 51–70 (β = 4.4; 95%CI 0.3, 8.5) and >71 years (β = 6.5; 95% CI 1.6–11.4). Compared to those living alone, participants living with a partner (β = 5.2; 95%CI 2.0, 8.4) and families with children (β = 5.6; 95%CI 1.4, 9.8) had significantly higher ARFS. ARFS was significantly lower with each additional self-reported chronic health condition (β = −1.4; 95%CI −2.3, −0.4). Our results indicate that diet quality as defined by the ARFS was classified as ‘getting there’ and that age, living arrangements and chronic health conditions, but not rurality, influenced diet quality in a sample of Australian adults.
Clinical Presentation of Celiac Disease and Diagnosis Accuracy in a Single-Center European Pediatric Cohort over 10 Years
Authors: Di Biase Anna Rita , Marasco Giovanni , Ravaioli Federico , Colecchia Luigi , Dajti Elton , Lecis Marco , Passini Erica , Alemanni Luigina Vanessa , Festi Davide , Iughetti Lorenzo , Colecchia Antonio
Published: November 2021

(1) Background: Changes in the clinical presentation of celiac disease (CD) in children have been reported. The guidelines of the European Society of Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) allow esophagogastroduodenoscopy (EGD) with biopsies to be avoided under specific circumstances. We aimed to assess the clinical picture of pediatric CD patients at diagnosis and to validate ESPGHAN non-biopsy criteria. (2) Methods: Patients with suspected CD or undergoing screening from 2004 to 2014 at the University Hospital in Modena, Italy were enrolled. The accuracy of ESPGHAN non-biopsy criteria and modified versions were assessed. (3) Results: In total, 410 patients were enrolled, of whom 403 were considered for analysis. Of the patients considered, 45 were asymptomatic and diagnosed with CD (11.2%) while 358 patients (88.2%) were symptomatic, of whom 295 were diagnosed with CD. Among symptomatic CD patients, 57 (19.3%) had gastrointestinal symptoms, 98 (33%) had atypical symptoms and 140 (47.4%) had both. No difference was found for the presence of gastrointestinal symptoms at different ages. The non-biopsy ESPGHAN criteria yielded an accuracy of 59.4% with a positive predictive value (PPV) of 100%; 173 out of 308 EGD (56.2%) could have been avoided. The modified 7× and 5× upper limit of normal cut-offs for IgA anti tissue-transglutaminase reached 60.7% and 64.3% of EGD avoided, respectively. (4) Conclusions: Over 10 years, late age at diagnosis and increased rates of atypical CD presentation were found. ESPGHAN non-biopsy criteria are accurate for CD diagnosis and allow half of unneeded EGD to be avoided. Modified versions allowed sparing a greater number of EGD.
Beliefs and Norms Associated with the Use of Ultra-Processed Commercial Milk Formulas for Pregnant Women in Vietnam
Authors: Nguyen Tuan T. , Cashin Jennifer , Ching Constance , Baker Phillip , Tran Hoang T. , Weissman Amy , Nguyen Thao T. , Mathisen Roger
Published: November 2021

Commercial milk formula for pregnant women (CMF-PW) is an expensive, ultra-processed food with a high concentration of sugar, the consumption of which may be linked to negative health outcomes. However, CMF-PWs are promoted as beneficial for pregnant women and lactating mothers as well as their children. To date, little is known about the factors associated with the use of CMF-PW among pregnant women. We performed this analysis to examine the association between the use of CMF-PW and related beliefs and norms among pregnant women in Vietnam. We interviewed 268 pregnant women in their second and third trimesters from two provinces and one municipality representing diverse communities in Vietnam. Multinomial (polytomous) logistic regression, structural equation modeling (SEM), and propensity score matching (PSM) analysis were used to examine associations between beliefs and social norms related to CMF-PW and reported consumption, characterized as occasional, recent, and never during the current pregnancy. Overall, 64.6% of pregnant women reported using CMF-PW during the current pregnancy and 34.7% consumed CMF-PW on the day prior to the interview. Strong beliefs that CMF-PW will make a child smart and healthy (53.7%) and the perception that use of CMF-PW is common (70.9%) were associated with increased use on the previous day (beliefs: aOR: 3.56; 95% Confidence Interval (95% CI): 1.65, 7.71; p < 0.01 and social norms aOR: 2.29; 95% CI: 1.13, 4.66; p < 0.05). SEM and PSM analyses confirmed these findings for both occasional and regular CMF-PW use. Results are consistent with observations of CMF-PW product labels and marketing tactics in Vietnam. The prevalent use of CMF-PW in Vietnam is associated with the belief that these products make children smart and healthy and the perceived social norm that most mothers use these products, which mirrors marketing messages and approaches employed by the CMF industry.
Probiotics in Intestinal Mucosal Healing: A New Therapy or an Old Friend?
Authors: Filidou Eirini , Kolios George
Published: November 2021

Inflammatory bowel disease (IBD), Crohn’s disease, and ulcerative colitis are characterized by chronic and relapsing inflammation, while their pathogenesis remains mostly unelucidated. Gut commensal microbiota seem to be one of the various implicated factors, as several studies have shown a significant decrease in the microbiome diversity of patients with IBD. Although the question of whether microbiota dysbiosis is a causal factor or the result of chronic inflammation remains unanswered, one fact is clear; active inflammation in IBD results in the disruption of the mucus layer structure, barrier function, and also, colonization sites. Recently, many studies on IBD have been focusing on the interplay between mucosal and luminal microbiota, underlining their possible beneficial effect on mucosal healing. Regarding this notion, it has now been shown that specific probiotic strains, when administrated, lead to significantly decreased inflammation, amelioration of colitis, and improved mucosal healing. Probiotics are live microorganisms exerting beneficial effects on the host’s health when administered in adequate quantity. The aim of this review was to present and discuss the current findings on the role of gut microbiota and their metabolites in intestinal wound healing and the effects of probiotics on intestinal mucosal wound closure.
The Inhibitory Effects of Terminalia catappa L. Extract on the Migration and Invasion of Human Glioblastoma Multiforme Cells
Authors: Chung Hsiao-Hang , Hsieh Ming-Ju , Hsieh Yih-Shou , Chen Pei-Ni , Ko Chung-Po , Yu Nuo-Yi , Lin Chiao-Wen , Yang Shun-Fa
Published: November 2021

Glioblastoma multiforme (GBM) is one of the most aggressive and common types of brain tumor. Due to its high proliferation ability, a high lethality rate has been observed with this malignant glial tumor. Terminalia catappa L. (T. catappa) is currently known to have anti-inflammatory and anti-carcinogenesis effects. However, few studies have examined the mechanisms of the leaf extracts of T. catappa (TCE) on GBM cells. In the current study, we demonstrated that TCE can significantly inhibit the migration and invasion capabilities of GBM cell lines without showing biotoxic effects. Matrix metalloproteinases-2 (MMP-2) activity and protein expression were attenuated by reducing the p38 phosphorylation involved in the mitogen-activated protein kinase (MAPK) pathway. By treating with TCE and/or p38 inhibitor (SB203580), we confirmed that p38 MAPK is involved in the inhibition of cell migration. In conclusion, our results demonstrated that TCE inhibits human GBM cell migration and MMP-2 expression by regulating the p38 pathway. These results reveal that TCE contains potent therapeutic compounds which could be applied for treating GBM brain tumors.
Progress in Nanocarriers Codelivery System to Enhance the Anticancer Effect of Photodynamic Therapy
Authors: Yang Yu-Ling , Lin Ke , Yang Li
Published: November 2021

Photodynamic therapy (PDT) is a promising anticancer noninvasive method and has great potential for clinical applications. Unfortunately, PDT still has many limitations, such as metastatic tumor at unknown sites, inadequate light delivery and a lack of sufficient oxygen. Recent studies have demonstrated that photodynamic therapy in combination with other therapies can enhance anticancer effects. The development of new nanomaterials provides a platform for the codelivery of two or more therapeutic drugs, which is a promising cancer treatment method. The use of multifunctional nanocarriers for the codelivery of two or more drugs can improve physical and chemical properties, increase tumor site aggregation, and enhance the antitumor effect through synergistic actions, which is worthy of further study. This review focuses on the latest research progress on the synergistic enhancement of PDT by simultaneous multidrug administration using codelivery nanocarriers. We introduce the design of codelivery nanocarriers and discuss the mechanism of PDT combined with other antitumor methods. The combination of PDT and chemotherapy, gene therapy, immunotherapy, photothermal therapy, hyperthermia, radiotherapy, sonodynamic therapy and even multidrug therapy are discussed to provide a comprehensive understanding.
Chitosan–Platelet-Rich Plasma Implants Improve Rotator Cuff Repair in a Large Animal Model: Pivotal Study
Authors: Chevrier Anik , Hurtig Mark B. , Lavertu Marc
Published: November 2021

The purpose of this study was to assess the safety and efficacy of chitosan–platelet-rich plasma (PRP) hybrid implants used as an adjunct to surgical rotator cuff repair in a pivotal Good Laboratory Practice (GLP)-compliant study. The infraspinatus tendon was transected in 48 skeletally mature ewes and repaired with a transosseous-equivalent (TOE) technique. In the two treatment groups, a chitosan–PRP solution was injected at the footprint between the tendon and the bone and on top of the repaired site (2 mL or 3 mL doses, n = 12 per group). To further assess chitosan safety, a chitosan–water solution was injected at the same sites (3 mL, n = 12). Outcome measures included Magnetic Resonance Imaging (MRI) assessment and clinical pathology at 3 months and 6 months and histopathology at 6 months. The tendon gap was decreased at 3 months on MRI images and certain histopathological features were improved at 6 months by chitosan–PRP treatment compared to controls. The group treated with chitosan–water was not different from controls. Chitosan–PRP treatment induced no negative effects in the sheep, which suggests high safety. This study provides further evidence on the safety and efficacy of chitosan–PRP for rotator cuff repair augmentation, which could eventually be used in a clinical setting.
Variability of Tacrolimus Trough Concentration in Liver Transplant Patients: Which Role of Inflammation?
Authors: Chavant Anaelle , Fonrose Xavier , Gautier-Veyret Elodie , Hilleret Marie Noelle , Roustit Matthieu , Stanke-Labesque Francoise
Published: November 2021

Tacrolimus presents high intra and inter-individual variability in its blood trough concentration (Cmin). Knowledge of the factors that are involved in tacrolimus Cmin variability is thus clinically important to prevent or limit it. Inflammation can affect the pharmacokinetic properties of drugs. We evaluated the contribution of acute inflammation in the pharmacokinetic variability of tacrolimus blood Cmin in a large cohort of liver transplant patients. Demographic, biological, and clinical data from 248 liver transplant patients treated with tacrolimus from January 2010 to December 2016 were retrospectively collected from medical records. In total, 1573 Cmin/dose and concomitant C-reactive protein (CRP) measurements were analysed. In multivariate analysis, the log Cmin/dose of tacrolimus was significantly and positively associated with the hematocrit, ALAT, and CRP concentrations. CRP concentrations were higher (p = 0.003) for patients with tacrolimus overexposure (i.e., tacrolimus Cmin > 15 µg/L) (median CRP (10th–90th percentiles): 27 mg/L (3–149 mg/L), n = 91) than they were for patients with a tacrolimus Cmin ≤ 15 µg/L (13 mg/mL (3–95 mg/L), n = 1482)). CRP in the fourth quartile (49 to 334 mg/L) was associated with a 2.6-fold increased risk of tacrolimus Cmin overexposure. Our study provides evidence that inflammation contributes to tacrolimus Cmin variability and suggests that inflammation should be considered for the correct interpretation of tacrolimus blood concentration.
Intersystem Bias in GPS, GLONASS, Galileo, BDS-3, and BDS-2 Integrated SPP: Characteristics and Performance Enhancement as a Priori Constraints
Authors: Pan Lin , Zhang Zhehao , Yu Wenkun , Dai Wujiao
Published: November 2021

Global navigation satellite systems (GNSSs) have been booming in recent years, and the space segment of all four of the GNSSs, including BDS (BDS-3/BDS-2), Galileo, GPS, and GLONASS, has almost been fully deployed at present. The single point positioning (SPP) technology, which is widely used in satellite navigation and low-accuracy positioning, can benefit from the multi-GNSS integration, but the additional intersystem bias (ISB) parameters should be introduced to ensure the compatibility among different GNSSs. In this study, the ISB estimates derived from four-system integrated SPP are carefully characterized, and the performance enhancement attributed to a priori ISB constraints by prediction for position solutions under open sky and constrained visibility environments is rigorously evaluated. The results indicate that the ISB between BDS-3 and BDS-2 cannot be ignored. The daily ISBs show step changes when encountering the replacement of receiver types, while it is not the case for the receiver firmware versions. The daily ISBs are roughly consistent for the stations equipped with the same type of receivers. The short-term stability of epochwise ISBs for GLONASS, Galileo, BDS-2, and BDS-3 with respect to GPS can be 2.335, 1.262, 1.741, and 1.532 ns, respectively, whereas the corresponding long-term stability for daily ISBs can be 1.258, 1.288, 2.713, and 2.566 ns, respectively. The single-day prediction accuracy of daily ISBs for GLONASS, Galileo, BDS-2, and BDS-3 with respect to GPS can be 1.055, 0.640, 1.242, and 0.849 ns, respectively. The improvements on positioning accuracy after introducing a priori ISB constraints can be over 20% at an elevation mask of 40° and 50° with a time span of ISB prediction of a day. As to the availability, it is only 64.0% for traditional four-system SPP under a cutoff elevation of 50°, while the corresponding availability is increased to approximately 90.0% after considering a priori ISB constraints. For completeness, the characteristics of ISBs estimated with the low-cost u-blox M8T receiver and the Xiaomi Mi8 smartphone as well as the contribution of a priori ISB constraints to the multisystem SPP solutions with these devices are also investigated.
A Novel Anti-Drift Visual Object Tracking Algorithm Based on Sparse Response and Adaptive Spatial-Temporal Context-Aware
Authors: Su Yinqiang , Liu Jinghong , Xu Fang , Zhang Xueming , Zuo Yujia
Published: November 2021

Correlation filter (CF) based trackers have gained significant attention in the field of visual single-object tracking, owing to their favorable performance and high efficiency; however, existing trackers still suffer from model drift caused by boundary effects and filter degradation. In visual tracking, long-term occlusion and large appearance variations easily cause model degradation. To remedy these drawbacks, we propose a sparse adaptive spatial-temporal context-aware method that effectively avoids model drift. Specifically, a global context is explicitly incorporated into the correlation filter to mitigate boundary effects. Subsequently, an adaptive temporal regularization constraint is adopted in the filter training stage to avoid model degradation. Meanwhile, a sparse response constraint is introduced to reduce the risk of further model drift. Furthermore, we apply the alternating direction multiplier method (ADMM) to derive a closed-solution of the object function with a low computational cost. In addition, an updating scheme based on the APCE-pool and Peak-pool is proposed to reveal the tracking condition and ensure updates of the target’s appearance model with high-confidence. The Kalam filter is adopted to track the target when the appearance model is persistently unreliable and abnormality occurs. Finally, extensive experimental results on OTB-2013, OTB-2015 and VOT2018 datasets show that our proposed tracker performs favorably against several state-of-the-art trackers.
A Review on the Development of Earthquake Warning System Using Low-Cost Sensors in Taiwan
Authors: Wu Yih-Min , Mittal Himanshu
Published: November 2021

Seismic instrumentation for earthquake early warnings (EEWs) has improved significantly in the last few years, considering the station coverage, data quality, and the related applications. The official EEW system in Taiwan is operated by the Central Weather Bureau (CWB) and is responsible for issuing the regional warning for moderate-to-large earthquakes occurring in and around Taiwan. The low-cost micro-electro-mechanical system (MEMS)-based P-Alert EEW system is operational in Taiwan for on-site warnings and for producing shakemaps. Since 2010, this P-Alert system, installed by the National Taiwan University (NTU), has shown its importance during various earthquakes that caused damage in Taiwan. Although the system is capable of acting as a regional as well as an on-site warning system, it is particularly useful for on-site warning. Using real-time seismic signals, each P-Alert system can provide a 2–8 s-long warning time for the locations situated in the blind zone of the CWB regional warning system. The shakemaps plotted using this instrumentation help to assess the damage pattern and rupture directivity, a key feature in the risk mitigation process. These shakemaps are delivered to the intended users, including the disaster mitigation authorities, for possible relief purposes. Earlier, the network provided only peak ground acceleration (PGA) shakemaps, but has now been updated to include peak ground velocity (PGV), spectral acceleration (Sa) at different periods, and CWB intensity maps. The PGA and PGV shakemaps plotted using this network have proven helpful in establishing the fact that PGV is a better indicator of damage detection than PGA. This instrumentation is also useful in structural health-monitoring and estimating co-seismic deformations. Encouraged by the performance of the P-Alert network, more instruments are installed in Asia-Pacific countries.
Configurable IoT Open-Source Hardware and Software I-V Curve Tracer for Photovoltaic Generators
Authors: González Isaías , Portalo José María , Calderón Antonio José
Published: November 2021

Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.
Outage Analysis of the Power Splitting Based Underlay Cooperative Cognitive Radio Networks
Authors: Tin Phu Tran , Phan Van-Duc , Nguyen Tan N. , Tu Lam-Thanh , Minh Bui Vu , Voznak Miroslav , Fazio Peppino
Published: November 2021

In the present paper, we investigate the performance of the simultaneous wireless information and power transfer (SWIPT) based cooperative cognitive radio networks (CCRNs). In particular, the outage probability is derived in the closed-form expressions under the opportunistic partial relay selection. Different from the conventional CRNs in which the transmit power of the secondary transmitters count merely on the aggregate interference measured on the primary networks, the transmit power of the SWIPT-enabled transmitters is also constrained by the harvested energy. As a result, the mathematical framework involves more correlated random variables and, thus, is of higher complexity. Monte Carlo simulations are given to corroborate the accuracy of the mathematical analysis and to shed light on the behavior of the OP with respect to several important parameters, e.g., the transmit power and the number of relays. Our findings illustrate that increasing the transmit power and/or the number of relays is beneficial for the outage probability.
3D-Printed Liquid Cell Resonator with Piezoelectric Actuation for In-Line Density-Viscosity Measurements
Authors: Toledo Javier , Ruiz-Díez Víctor , Velasco Jaime , Hernando-García Jorge , Sánchez-Rojas José Luis
Published: November 2021

The in-line monitoring of liquid properties, such as density and viscosity, is a key process in many industrial areas such as agro-food, automotive or biotechnology, requiring real-time automation, low-cost and miniaturization, while maintaining a level of accuracy and resolution comparable to benchtop instruments. In this paper, 3D-printed cuboid-shaped liquid cells featuring a rectangular vibrating plate in one of the sides, actuated by PZT piezoelectric layers, were designed, fabricated and tested. The device was resonantly excited in the 3rd-order roof tile-shaped vibration mode of the plate and validated as a density-viscosity sensor. Furthermore, conditioning circuits were designed to adapt the impedance of the resonator and to cancel parasitic effects. This allowed us to implement a phase-locked loop-based oscillator circuit whose oscillation frequency and voltage amplitude could be calibrated against density and viscosity of the liquid flowing through the cell. To demonstrate the performance, the sensor was calibrated with a set of artificial model solutions of grape must, representing stages of a wine fermentation process. Our results demonstrate the high potential of the low-cost sensor to detect the decrease in sugar and the increase in ethanol concentrations during a grape must fermentation, with a resolution of 10 µg/mL and 3 µPa·s as upper limits for the density and viscosity, respectively.
Blockchain-Based Context-Aware Authorization Management as a Service in IoT
Authors: Sylla Tidiane , Mendiboure Leo , Chalouf Mohamed Aymen , Krief Francine
Published: November 2021

Internet of Things (IoT) applications bring evolved and intelligent services that can help improve users’ daily lives. These applications include home automation, health care, and smart agriculture. However, IoT development and adoption face various security and privacy challenges that need to be overcome. As a promising security paradigm, context-aware security enables one to enforce security and privacy mechanisms adaptively. Moreover, with the advancements in edge computing, context-aware security services can dynamically be placed close to a user’s location and enable the support of low latency communication and mobility. Therefore, the design of an adaptive and decentralized access control mechanism becomes a necessity. In this paper, we propose a decentralized context-aware authorization management as a service based on the blockchain. The proposed architecture extends the Authentication and Authorization for Constrained Environments (ACE) framework with blockchain technology and context-awareness capabilities. Instead of a classic Open Authorization 2.0 (OAuth) access token, it uses a new contextual access token. The evaluation results show our proposition’s effectiveness and advantages in terms of usability, security, low latency, and energy consumption.
Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning
Authors: Luna-Jiménez Cristina , Griol David , Callejas Zoraida , Kleinlein Ricardo , Montero Juan M. , Fernández-Martínez Fernando
Published: November 2021

Emotion Recognition is attracting the attention of the research community due to the multiple areas where it can be applied, such as in healthcare or in road safety systems. In this paper, we propose a multimodal emotion recognition system that relies on speech and facial information. For the speech-based modality, we evaluated several transfer-learning techniques, more specifically, embedding extraction and Fine-Tuning. The best accuracy results were achieved when we fine-tuned the CNN-14 of the PANNs framework, confirming that the training was more robust when it did not start from scratch and the tasks were similar. Regarding the facial emotion recognizers, we propose a framework that consists of a pre-trained Spatial Transformer Network on saliency maps and facial images followed by a bi-LSTM with an attention mechanism. The error analysis reported that the frame-based systems could present some problems when they were used directly to solve a video-based task despite the domain adaptation, which opens a new line of research to discover new ways to correct this mismatch and take advantage of the embedded knowledge of these pre-trained models. Finally, from the combination of these two modalities with a late fusion strategy, we achieved 80.08% accuracy on the RAVDESS dataset on a subject-wise 5-CV evaluation, classifying eight emotions. The results revealed that these modalities carry relevant information to detect users’ emotional state and their combination enables improvement of system performance.
Mobile Eye-Tracking Data Analysis Using Object Detection via YOLO v4
Authors: Kumari Niharika , Ruf Verena , Mukhametov Sergey , Schmidt Albrecht , Kuhn Jochen , Küchemann Stefan
Published: November 2021

Remote eye tracking has become an important tool for the online analysis of learning processes. Mobile eye trackers can even extend the range of opportunities (in comparison to stationary eye trackers) to real settings, such as classrooms or experimental lab courses. However, the complex and sometimes manual analysis of mobile eye-tracking data often hinders the realization of extensive studies, as this is a very time-consuming process and usually not feasible for real-world situations in which participants move or manipulate objects. In this work, we explore the opportunities to use object recognition models to assign mobile eye-tracking data for real objects during an authentic students’ lab course. In a comparison of three different Convolutional Neural Networks (CNN), a Faster Region-Based-CNN, you only look once (YOLO) v3, and YOLO v4, we found that YOLO v4, together with an optical flow estimation, provides the fastest results with the highest accuracy for object detection in this setting. The automatic assignment of the gaze data to real objects simplifies the time-consuming analysis of mobile eye-tracking data and offers an opportunity for real-time system responses to the user’s gaze. Additionally, we identify and discuss several problems in using object detection for mobile eye-tracking data that need to be considered.
Hydrogel Microparticles for Fluorescence Detection of miRNA in Mix-Read Bioassay
Authors: Mazzarotta Alessia , Caputo Tania Mariastella , Battista Edmondo , Netti Paolo Antonio , Causa Filippo
Published: November 2021

Herein we describe the development of a mix-read bioassay based on a three-dimensional (3D) poly ethylene glycol—(PEG)-hydrogel microparticles for the detection of oligonucleotides in complex media. The key steps of hydrogels synthesis and molecular recognition in a 3D polymer network are elucidated. The design of the DNA probes and their density in polymer network were opportunely optimized. Furthermore, the diffusion into the polymer was tuned adjusting the polymer concentration and consequently the characteristic mesh size. Upon parameters optimization, 3D-PEG-hydrogels were synthetized in a microfluidic system and provided with fluorescent probe. Target detection occurred by double strand displacement assay associated to fluorescence depletion within the hydrogel microparticle. Proposed 3D-PEG-hydrogel microparticles were designed for miR-143-3p detection. Results showed 3D-hydrogel microparticles with working range comprise between 10−6–10−12 M, had limit of detection of 30 pM and good specificity. Moreover, due to the anti-fouling properties of PEG-hydrogel, the target detection occurred in human serum with performance comparable to that in buffer. Due to the approach versatility, such design could be easily adapted to other short oligonucleotides detection.
Gait Disorder Detection and Classification Method Using Inertia Measurement Unit for Augmented Feedback Training in Wearable Devices
Authors: Kim Hyeonjong , Kim Ji-Won , Ko Junghyuk
Published: November 2021

Parkinson’s disease (PD) is a common neurodegenerative disease, one of the symptoms of which is a gait disorder, which decreases gait speed and cadence. Recently, augmented feedback training has been considered to achieve effective physical rehabilitation. Therefore, we have devised a numerical modeling process and algorithm for gait detection and classification (GDC) that actively utilizes augmented feedback training. The numerical model converted each joint angle into a magnitude of acceleration (MoA) and a Z-axis angular velocity (ZAV) parameter. Subsequently, we confirmed the validity of both the GDC numerical modeling and algorithm. As a result, a higher gait detection and classification rate (GDCR) could be observed at a higher gait speed and lower acceleration threshold (AT) and gyroscopic threshold (GT). However, the pattern of the GDCR was ambiguous if the patient was affected by a gait disorder compared to a normal user. To utilize the relationships between the GDCR, AT, GT, and gait speed, we controlled the GDCR by using AT and GT as inputs, which we found to be a reasonable methodology. Moreover, the GDC algorithm could distinguish between normal people and people who suffered from gait disorders. Consequently, the GDC method could be used for rehabilitation and gait evaluation.
Reproducibility of an Intraoperative Pressure Sensor in Total Knee Replacement
Authors: Fary Camdon , McKenzie Dean , Steiger Richard de
Published: November 2021

Appropriate soft tissue tension in total knee replacement (TKR) is an important factor for a successful outcome. The purpose of our study was to assess both the reproducibility of a modern intraoperative pressure sensor (IOP) and if a surgeon could unconsciously influence measurement. A consecutive series of 80 TKRs were assessed with an IOP between January 2018 and December 2020. In the first scenario, two blinded sequential measurements in 48 patients were taken; in a second scenario, an initial blinded measurement and a subsequent unblinded measurement in 32 patients were taken while looking at the sensor monitor screen. Reproducibility was assessed by intraclass correlation coefficients (ICCs). In the first scenario, the ICC ranged from 0.83 to 0.90, and in the second scenario it ranged from 0.80 to 0.90. All ICCs were 0.80 or higher, indicating reproducibility using a IOP and that a surgeon may not unconsciously influence the measurement. The use of a modern IOP to measure soft tissue tension in TKRs is a reproducible technique. A surgeon observing the measurements while performing IOP may not significantly influence the result. An IOP gives additional information that the surgeon can use to optimize outcomes in TKR.
An Assessment of Balance through Posturography in Healthy about Women: An Observational Study
Authors: Escamilla-Martínez Elena , Gómez-Maldonado Ana , Gómez-Martín Beatriz , Castro-Méndez Aurora , Díaz-Mancha Juan Antonio , Fernández-Seguín Lourdes María
Published: November 2021

The incidence of falls in adults constitutes a public health problem, and the alteration in balance is the most important factor. It is necessary to evaluate this through objective tools in order to quantify alterations and prevent falls. This study aims to determine the existence of alteration of balance and the influence of age in a population of healthy women. Static posturography was performed on 49 healthy adult women with no history of falls in four different situations using the Romberg test with the NedSVE/IBV® platform. The variables studied were the body sway area and the anteroposterior and mediolateral displacements. The situation of maximum instability occurred in RGC (p = 0.001), with a significant increase in anteroposterior oscillations regarding the ML (p < 0.001), with no correlation to age. Age alone does not influence the balance in the sample studied, other factors must come together to alter it. The joint cancellation of visual and somatosensory afferents could facilitate the appearance of falls, given that it is a situation of maximum instability. Proprioceptive training is interesting as a preventive strategy for falls.
A Novel Complete-Surface-Finding Algorithm for Online Surface Scanning with Limited View Sensors
Authors: Poole Alastair , Sutcliffe Mark , Pierce Gareth , Gachagan Anthony
Published: November 2021

Robotised Non-Destructive Testing (NDT) has revolutionised the field, increasing the speed of repetitive scanning procedures and ability to reach hazardous environments. Application of robot-assisted NDT within specific industries such as remanufacturing and Aersopace, in which parts are regularly moulded and susceptible to non-critical deformation has however presented drawbacks. In these cases, digital models for robotic path planning are not always available or accurate. Cutting edge methods to counter the limited flexibility of robots require an initial pre-scan using camera-based systems in order to build a CAD model for path planning. This paper has sought to create a novel algorithm that enables robot-assisted ultrasonic testing of unknown surfaces within a single pass. Key to the impact of this article is the enabled autonomous profiling with sensors whose aperture is several orders of magnitude smaller than the target surface, for surfaces of any scale. Potential applications of the algorithm presented include autonomous drone and crawler inspections of large, complex, unknown environments in addition to situations where traditional metrological profiling equipment is not practical, such as in confined spaces. In simulation, the proposed algorithm has completely mapped significantly curved and complex shapes by utilising only local information, outputting a traditional raster pattern when curvature is present only in a single direction. In practical demonstrations, both curved and non-simple surfaces were fully mapped with no required operator intervention. The core limitations of the algorithm in practical cases is the effective range of the applied sensor, and as a stand-alone method it lacks the required knowledge of the environment to prevent collisions. However, since the approach has met success in fully scanning non-obstructive but still significantly complex surfaces, the objectives of this paper have been met. Future work will focus on low-accuracy environmental sensing capabilities to tackle the challenges faced. The method has been designed to allow single-pass scans for Conformable Wedge Probe UT scanning, but may be applied to any surface scans in the case the sensor aperture is significantly smaller than the part.
An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
Authors: Barry Daniel , Willig Andreas , Woodward Graeme
Published: November 2021

Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown environment, where the goal is to locate all transmitters in as short a time as possible. Existing solutions in the UAV search space typically search for a single target, assume a simple environment, assume target properties are known or have other unrealistic assumptions. We simulate large, complex environments with limited a priori information about the environment and transmitter properties. We propose a Bayesian search algorithm, Information Exploration Behaviour (IEB), that maximizes predicted information gain at each search step, incorporating information from multiple sensors whilst making minimal assumptions about the scenario. This search method is inspired by the information theory concept of empowerment. Our algorithm shows significant speed-up compared to baseline algorithms, being orders of magnitude faster than a random agent and 10 times faster than a lawnmower strategy, even in complex scenarios. The IEB agent is able to make use of received transmitter signals from unknown sources and incorporate both an exploration and search strategy.
An Anti-Jamming Method against Two-Dimensional Deception Jamming by Spatial Location Feature Recognition
Authors: Liu Zhidong , Zhang Qun , Li Kaiming
Published: November 2021

Interrupted sampling repeater jamming (ISRJ) is an effective method for implementing deception jamming on chirp radars. By means of frequency-shifting jamming processing of the target echo signal and pulse compression during image processing, a group of false targets will appear in different spatial locations around the true target. Extracting the features of these false targets is complex and limited to existing countering methods against ISRJ. This paper proposes an anti-jamming method to identify the spatial location characteristics of two-dimensional deception false targets. By adjusting the parameters of the radar transmitted signal, the method simultaneously transmits the anti-jamming signal and carries out false target identification and elimination in the range and azimuth dimensions. Eventually, the optimal signal parameter design of the anti-jamming signal is obtained by comparing different anti-jamming strategies in the range dimension. The validity of the proposed method is proved by deducing the mathematical model between the spatial distribution characteristics of the false targets and the radar transmitted signal parameters and demonstrated by simulations.
Intelligent Transport System Using Time Delay-Based Multipath Routing Protocol for Vehicular Ad Hoc Networks
Authors: Ghaemi Yashar , El-Ocla Hosam , Yadav Nitin Ramesh , Madana Manisha Reddy , Raju Dheeraj Kurugod , Dhanabal Vignesh , Sheshadri Vishal
Published: November 2021

During the last decade, the research on Intelligent Transportation System (ITS) has improved exponentially in real-life scenarios to provide optimized transport network performance. It is a matter of importance that alert messages are delivered promptly to prevent vehicular traffic problems. The fact is an ITS system per se could be a part of a vehicular ad hoc network (VANET) which is an extension of a wireless network. In all sorts of wireless ad hoc networks, the network topology is subjected to change due to the mobility of network nodes; therefore, an existing explored route between two nodes could be demolished in a minor fraction of time. When it comes to the VANETs, the topology likely changes due to the high velocity of nodes. On the other hand, time is a crucial factor playing an important role in message handling between the network’s nodes. In this paper, we propose Time delay-based Multipath Routing (TMR) protocol that effectively identifies an optimized path for packet delivery to the destination vehicle with a minimal time delay. Our algorithm gives a higher priority to alert messages compared to normal messages. It also selects the routes with the short round-trip time (RTT) within the RTT threshold. As a result, our algorithm would realize two goals. Firstly, it would speed up the data transmission rate and deliver data packets, particularly warning messages, to the destination vehicle promptly and therefore avoid vehicular problems such as car accidents. Secondly, the TMR algorithm reduces the data traffic load, particularly of the normal messages, to alleviate the pressure on the network and therefore avoids network congestion and data collisions. This, in turn, lessens the packets’ retransmissions. To demonstrate the effectiveness of the proposed protocol, the TMR has been compared with the other protocols such as AOMDV, FF-AOMDV, EGSR, QMR, and ISR. Simulation results demonstrate that our proposed protocol proves its excellent performance compared to other protocols.
Are We Satisfying the Right Conditions for the Mobility Transition? A Review and Evaluation of the Dutch Urban Mobility Policies
Authors: van der Koogh Mylène , Chappin Emile , Heller Renée , Lukszo Zofia
Published: November 2021

Global climate agreements call for action and an integrated perspective on mobility, energy and overall consumption. Municipalities in dense, urban areas are challenged with facilitating this transition with limited space and energy resources, and with future uncertainties. One important aspect of the transition is the adoption of electric vehicles, which includes the adequate design of charging infrastructure. Another important goal is a modal shift in transportation. This study investigated over 80 urban mobility policy measures that are in the policy roadmap of two of the largest municipalities of the Netherlands. This analysis consists of an inventory of policy measures, an evaluation of their environmental effects and conceptualizations of the policy objectives and conditions within the mobility transitions. The findings reveal that the two municipalities have similarities in means, there is still little anticipation of future technology and policy conditions could be further satisfied by introducing tailored measures for specific user groups.
Production of Biodiesel from Spirogyra elongata, a Common Freshwater Green Algae with High Oil Content
Authors: Saeed Aasma , Hanif Muhammad Asif , Hanif Asma , Rashid Umer , Iqbal Javed , Majeed Muhammad Irfan , Moser Bryan R. , Alsalme Ali
Published: November 2021

The need for exploring nonfood low-cost sustainable sources for biodiesel production is ever increasing. Commercial and industrial algae cultivation has numerous uses in biodiesel production. This study explores S. elongata as a new algal feedstock for the production of biodiesel that does not compete with food production. The major fatty acids identified in S. elongata oil were oleic (30.5%), lauric (29.9%), myristic (17.0%), and palmitic (14.2%) acids. Transesterification to FAME was conducted using basic (KOH), acidic (HCl), and Zeolitic catalysts for assessment. The yields with acidic (54.6%) and zeolitic (72.7%) catalysts were unremarkable during initial screening. The highest biodiesel yield (99.9%) was achieved using KOH, which was obtained with the optimum reaction conditions of 1.0% catalyst, 60 °C, 4 h, and an oil-to-methanol volume ratio of 1:4. The resulting S. elongata oil methyl esters exhibited densities, CNs, and IVs, that were within the ranges specified in the American (ASTM D6751) and European (EN 14214) biodiesel standards, where applicable. In addition, the high SVs and the moderately high CPs and PPs were attributed to the presence of large quantities of short-chain and saturated FAME, respectively. Overall, the composition and properties of FAME prepared from S. elongaae oil indicate that S. elongata is suitable as an alternative algal feedstock for the production of biodiesel.
Management and Logistics of Returnable Transport Items: A Review Analysis on the Pallet Supply Chain
Authors: Tornese Fabiana , Gnoni Maria Grazia , Thorn Brian K. , Carrano Andres L. , Pazour Jennifer A.
Published: November 2021

Pallets are among the most used returnable transport items (RTIs), and they are critical assets for a supply chain as they have significant environmental and economic impacts during their whole life cycle. Differently from other packaging products, pallets are specifically designed to be repeatably repaired and reinjected for use. While this environmentally is beneficial as it reduces waste, it can create complex interactions between the stakeholder-involved manufacturers, pallet providers, users and recyclers. Further, the number of different actors is usually high, and the flow of materials among them needs to be coordinated. In addition, different business models can be implemented (such as internal management versus outsourcing) as well as logistics alternatives (closed- versus open-loop). Thus, the aims of this study are first to propose a systematization of design and management decisions regarding the pallet supply chain; next, to review the state of the art models and tools adopted to support each decision process relying on an analysis of the archival literature published between 1978 and 2021 on pallet management, to summarize the main decision problems addressed by the different stakeholders involved in the pallet life cycle and the adopted methods, and, finally, to highlight potential existing research gaps. This effort helps to outline potential contributions towards more sustainable pallet supply chains and can support pallet operators and companies in evaluating solutions to increase the economic and environmental sustainability of their pallet management. Results show that the perspectives of the pallet provider and of the supply chain are the most widely addressed in the existing literature, while those of pallet manufacturers and repairers should be further analyzed.