bluuebunny/crossref_metadata_2025 huggingface dataset:
Vitamin C Supplementation in Healthy Individuals Leads to Shifts of Bacterial Populations in the Gut—A Pilot Study
Authors: Otten Antonius T. , Bourgonje Arno R. , Peters Vera , Alizadeh Behrooz Z. , Dijkstra Gerard , Harmsen Hermie J. M.
Published: August 2021

Gut microbes are crucial to human health, but microbial composition is often disturbed in a number of human diseases. Accumulating evidence points to nutritional modulation of the gut microbiota as a potentially beneficial therapeutic strategy. Vitamin C (ascorbic acid) may be of particular interest as it has known antioxidant and anti-inflammatory properties. In this study, we investigated whether supplementation with high-dose vitamin C may favourably affect the composition of the gut microbiota. In this pilot study, healthy human participants received 1000 mg vitamin C supplementation daily for two weeks. Gut microbiota composition was analysed before and after intervention by performing faecal 16S rRNA gene sequencing. In total, 14 healthy participants were included. Daily supplementation of high-dose vitamin C led to an increase in the relative abundances of Lachnospiraceae (p < 0.05), whereas decreases were observed for Bacteroidetes (p < 0.01), Enterococci (p < 0.01) and Gemmiger formicilis (p < 0.05). In addition, trends for bacterial shifts were observed for Blautia (increase) and Streptococcus thermophilus (decrease). High-dose vitamin C supplementation for two weeks shows microbiota-modulating effects in healthy individuals, with several beneficial shifts of bacterial populations. This may be relevant as these bacteria have anti-inflammatory properties and strongly associate with gut health.
Open Loop Position Control of Soft Hydraulic Actuators for Minimally Invasive Surgery
Authors: Runciman Mark , Avery James , Darzi Ara , Mylonas George
Published: August 2021

Minimally invasive surgery (MIS) presents many constraints on the design of robotic devices that can assist medical staff with a procedure. The limitations of conventional, rigid robotic devices have sparked interest in soft robotic devices for medical applications. However, problems still remain with the force exertion and positioning capabilities of soft robotic actuators, in conjunction with size restrictions necessary for MIS. In this article we present hydraulically actuated soft actuators that demonstrate highly repeatable open loop positioning and the ability to exert significant forces in the context of MIS. Open loop position control is achieved by changing the actuator volume, which causes contraction. In one degree of freedom (DOF) configurations, root mean square error (RMSE) values of 0.471 mm, 1.506 mm, and 0.350 mm were recorded for a single actuator against gravity, a single actuator with a pulley, and a horizontal antagonistic configuration, respectively. Hysteresis values of 0.711 mm, 0.958 mm, and 0.515 mm were reported in these experiments. In addition, different numbers of soft actuators were used in configurations two and three DOFs to demonstrate position control. When deactivated, the soft actuators are low-profile and flexible as they are constructed from thin films. As such, a robot with a deployable structure and three soft actuators was constructed. The robot is therefore able to reversibly transition from low to high volume and stiffness, which has potential applications in MIS. A user successfully controlled the deployable robot in a circle tracing task.
An Introduction to Indoor Localization Techniques. Case of Study: A Multi-Trilateration-Based Localization System with User–Environment Interaction Feature
Authors: Andò Bruno , Baglio Salvatore , Crispino Ruben , Marletta Vincenzo
Published: August 2021

The problem of estimating the indoor position of a person or an object, also known as indoor localization, has gained a lot of interest in the last decades. Actually, this feature would be valuable in many application contexts, from logistics to robotic and Assistive Technology. Different solutions have been proposed in the literature, exploiting a wide range of approaches. This paper aims to provide a brief review of the state-of-the-art approaches in the field, as well as to present the RESIMA case study. The latter exploits an ultrasound-based indoor localization system and a User–Environment Interaction functionality, which allows for performing the continuous estimation of the distance between the end-user and objects in the environment. The latter is valuable to provide the end-user with efficient assistance during the environment exploitation. The main focus of this work is related to the overall description of the system architecture, the trilateration algorithm adopted for the sake of user localization and the estimation of the delay time produced by user-distance computation under different operating conditions.
Robotic Assembly for Irregular Shaped Peg-in-Hole with Partial Constraints
Authors: Li Wei , Cheng Hongtai , Li Chengpeng , Zhang Xiaohua
Published: August 2021

The tight tolerance peg-in-hole process brings great challenges for robotic assembly. Force control-based methods have been proposed to generate complex compliant behavior to deal with the shape and clearance variances. However, existing solutions are based on the assumption that the peg and hole parts are fixed during the assembly process and can absorb the contact force completely. For this purpose, customized fixtures have to be designed and utilized, which greatly affect the system’s deployment cost, time, and flexibility. Considering the fact that in an assembly, the parts are naturally related to each other, this paper studies the irregular-shaped peg-in-hole assembly problem with partial constraints. Firstly, geometric and force model are developed for the natural constraints between the parts; by analyzing the behavior of the partial constraint, a control policy is proposed to compensate the position errors and drive the parts to a stable equilibrium point; For the irregular-shaped parts, a multiple-stage searching method is developed to efficiently search for the real hole location; Finally, a switching force/position hybrid controller is designed to coordinate the alignment, searching and insertion processes. The method is implemented in a real platform. The experiment results verify the effectiveness of the proposed methods.
Battery Energy Storage System Dimensioning for Reducing the Fixed Term of the Electricity Access Rate in Industrial Consumptions
Authors: Nájera Jorge , Santos-Herran Miguel , Blanco Marcos , Navarro Gustavo , Torres Jorge , Lafoz Marcos
Published: August 2021

Industrial buildings account for very few high peaks of power demand. This situation forces them to contract a high fixed electricity term to cover it. A more intelligent use of the energy in industrial buildings, together with an improved efficiency of the transmission and distribution of the energy along the electric power grid, can be achieved by reducing the peak consumption of industrial buildings. Energy storage systems, and lithium ion (Li-ion) batteries in particular, are one of the most promising technologies for reducing this peak consumption. However, selecting a proper Li-ion battery requires a dimensioning process in terms of energy and power which is not straightforward. This paper proposes a dimensioning methodology that takes into consideration both technical and economic implications, and applies it to a case example with real industrial consumption data and a commercial battery. Results show that implementing batteries for reducing this peak consumption can lead to a cost–benefit improvement.
Morphological Foot Model for Temperature Pattern Analysis Proposed for Diabetic Foot Disorders
Authors: Arteaga-Marrero Natalia , Bodson Lucas Christian , Hernández Abián , Villa Enrique , Ruiz-Alzola Juan
Published: August 2021

Infrared thermography is a non-invasive and accessible tool that maps the surface temperature of a body. This technology is particularly useful for diabetic foot disorders, since it facilitates the identification of higher risk patients by frequent monitoring and therefore limits the incidence of disabling conditions. The aim of this work is to provide a methodology to explore the entire plantar aspects of both feet, based on infrared thermography, for the assessment of diabetic foot anomalies. A non-invasive methodology was established to identify areas of higher risk and track their progress via longitudinal monitoring. A standard morphological model was extracted from a group of healthy subjects, nine females and 13 males, by spatial image registration. This healthy foot model can be taken as a template for the assessment of temperature asymmetry, even in cases in which partial amputations or deformations are present. A pixel-wise comparison of the temperature patterns was carried out by Wilcoxon´s matched-pairs test using the corresponding template. For all the subjects, the left foot was compared to the contralateral foot, the right one, providing a map of statistically significant areas of variation, within the template, among the healthy subjects at different time points. In the female case, the main areas of variability were the boundaries of the feet, whereas for the male, in addition to this, substantial changes that exhibited a clear pattern were observed. A fast and simple monitoring tool is provided to be used for personalized medical diagnosis in patients affected by diabetic foot disorders.
Multimodal Tucker Decomposition for Gated RBM Inference
Authors: Maldonado-Chan Mauricio , Mendez-Vazquez Andres , Guardado-Medina Ramon Osvaldo
Published: August 2021

Gated networks are networks that contain gating connections in which the output of at least two neurons are multiplied. The basic idea of a gated restricted Boltzmann machine (RBM) model is to use the binary hidden units to learn the conditional distribution of one image (the output) given another image (the input). This allows the hidden units of a gated RBM to model the transformations between two successive images. Inference in the model consists in extracting the transformations given a pair of images. However, a fully connected multiplicative network creates cubically many parameters, forming a three-dimensional interaction tensor that requires a lot of memory and computations for inference and training. In this paper, we parameterize the bilinear interactions in the gated RBM through a multimodal tensor-based Tucker decomposition. Tucker decomposition decomposes a tensor into a set of matrices and one (usually smaller) core tensor. The parameterization through Tucker decomposition helps reduce the number of model parameters, reduces the computational costs of the learning process and effectively strengthens the structured feature learning. When trained on affine transformations of still images, we show how a completely unsupervised network learns explicit encodings of image transformations.
Analysis of Skim Reading on Desktop versus Mobile Screen
Authors: Alrizq Mesfer , Mehmood Sara , Mahoto Naeem Ahmed , Alqahtani Ali , Hamdi Mohammed , Alghamdi Abdullah , Shaikh Asadullah
Published: August 2021

Web readers usually skim through the text to keep up with the amount of available content. The effectiveness of skim reading is ensured by keeping the focus on the meaningful part of the text rather than the less meaningful part. To assure if the skim reading shows efficient results for a particular screen resolution, this research presents variations in the memory of significant data when a text is read on a mobile screen or a desktop screen. Moreover, the study aims to understand the knowledge gained from the text at a given time. In total, sixty participants contributed to the study and it is found that, relative to reading the text on a mobile screen, skimming showed improved memory for the ideas defined in the text on a computer screen. A software prototype is developed in this research study to analyze the impact of skim reading on a desktop computer screen versus a mobile device screen. The findings of the study have been interpreted as evidence in support of a skimming process called satisficing.
An Ultra-Low Temperature Transcritical R744 Refrigeration System for Future Detectors at CERN LHC
Authors: Barroca Pierre , Hafner Armin , Verlaat Bart , Petagna Paolo , Hulek Wojciech , Zwalinski Lukasz , Hanf Pierre , Battistin Michele , Davoine Loic , Teixeira Daniella
Published: August 2021

The cooling systems of the future tracking detectors of the ATLAS and CMS experiments at the Large Hadron Collider (LHC) at CERN will be entirely based on CO2 refrigeration technology. The system is a booster refrigeration system, composed of a two stage primary part with transcritical R744 equipment and a low temperature secondary CO2 pumped loop. The primary refrigeration sub-system installed on surface provides cold R744 at −53∘C to the CO2 pumped loops installed 100 m underground and rejects the heat exchanged. The process must be reliable and remain stable regardless of the amount of heat exchanged, which will amount to hundreds of kilowatts and is expected to vary throughout the lifetime of the detectors. The paper discusses the concept adopted for the innovative transcritical R744 cycle and describes the technical details of the first prototype built.
Male-Female Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: A State-by-State Analysis
Authors: Xu Jay J. , Chen Jarvis T. , Belin Thomas R. , Brookmeyer Ronald S. , Suchard Marc A. , Ramirez Christina M.
Published: August 2021

Males are at higher risk relative to females of severe outcomes following COVID-19 infection. Focusing on COVID-19-attributable mortality in the United States (U.S.), we quantified and contrasted years of potential life lost (YPLL) attributable to COVID-19 by sex based on data from the U.S. National Center for Health Statistics as of 31 March 2021, specifically by contrasting male and female percentages of total YPLL with their respective percent population shares and calculating age-adjusted male-to-female YPLL rate ratios, both nationally and for each of the 50 states and the District of Columbia. Using YPLL before age 75 to anchor comparisons between males and females and a novel Monte Carlo simulation procedure to perform estimation and uncertainty quantification, our results reveal a near-universal pattern across states of higher COVID-19-attributable YPLL among males compared to females. Furthermore, the disproportionately high COVID-19 mortality burden among males is generally more pronounced when measuring mortality burden in terms of YPLL compared to death counts, reflecting dual phenomena of males dying from COVID-19 at higher rates and at systematically younger ages relative to females. The U.S. COVID-19 epidemic also offers lessons underscoring the importance of cultivating a public health environment that recognizes sex-specific needs as well as different patterns in risk factors, health behaviors, and responses to interventions between men and women. Public health strategies incorporating focused efforts to increase COVID-19 vaccinations among men are particularly urged.
Synovial Sarcoma of the Extremities: A Literature Review
Authors: Faur Cosmin Ioan , Pop Daniel Laurentiu , Abu Awwad Ahmed , Zamfir Carmen Lacramioara , Folescu Roxana , Gurgus Daniela , Motoc Andrei Gheorghe Marius , Patrascu Jenel Marian , Motoi Sorin Bogdan , Belei Oana , Ungureanu Ana Maria
Published: August 2021

Synovial sarcoma (SS) is a rare and highly malignant tumor and a type of soft tissue sarcoma (STS), for which survival has not improved significantly in recent years. Synovial sarcomas occur mostly in adolescents and young adults (15–35 years old), usually affecting the deep soft tissues near the large joints of the extremities, with males being at a slightly higher risk. Despite its name, synovial sarcoma is neither related to the synovial tissues that are a part of the joints, i.e., the synovium, nor does it express synovial markers; however, the periarticular synovial sarcomas can spread as a secondary tumor to the joint capsule. SS was initially described as a biphasic neoplasm comprising of both epithelial and uniform spindle cell components. Synovial sarcoma is characterized by the presence of the pathognomonic t (X; 18) (p11.2; q11.2) translocation, involving a fusion of the SS18 (formerly SYT) gene on chromosome 18 to one of the synovial sarcoma X (SSX) genes on chromosome X (usually SSX1 or SSX2), which is seen in more than 90% of SSs and results in the formation of SS18-SSX fusion oncogenes.
Automatic Classification of A-Lines in Intravascular OCT Images Using Deep Learning and Estimation of Attenuation Coefficients
Authors: Cheimariotis Grigorios-Aris , Riga Maria , Haris Kostas , Toutouzas Konstantinos , Katsaggelos Aggelos K. , Maglaveras Nicos
Published: August 2021

Intravascular Optical Coherence Tomography (IVOCT) images provide important insight into every aspect of atherosclerosis. Specifically, the extent of plaque and its type, which are indicative of the patient’s condition, are better assessed by OCT images in comparison to other in vivo modalities. A large amount of imaging data per patient require automatic methods for rapid results. An effective step towards automatic plaque detection and plaque characterization is axial lines (A-lines) based classification into normal and various plaque types. In this work, a novel automatic method for A-line classification is proposed. The method employed convolutional neural networks (CNNs) for classification in its core and comprised the following pre-processing steps: arterial wall segmentation and an OCT-specific (depth-resolved) transformation and a post-processing step based on the majority of classifications. The important step was the OCT-specific transformation, which was based on the estimation of the attenuation coefficient in every pixel of the OCT image. The dataset used for training and testing consisted of 183 images from 33 patients. In these images, four different plaque types were delineated. The method was evaluated by cross-validation. The mean values of accuracy, sensitivity and specificity were 74.73%, 87.78%, and 61.45%, respectively, when classifying into plaque and normal A-lines. When plaque A-lines were classified into fibrolipidic and fibrocalcific, the overall accuracy was 83.47% for A-lines of OCT-specific transformed images and 74.94% for A-lines of original images. This large improvement in accuracy indicates the advantage of using attenuation coefficients when characterizing plaque types. The proposed automatic deep-learning pipeline constitutes a positive contribution to the accurate classification of A-lines in intravascular OCT images.
Characterization of a Quantum Random Number Generator Based on Vacuum Fluctuations
Authors: Ferreira Maurício J. , Silva Nuno A. , Pinto Armando N. , Muga Nelson J.
Published: August 2021

Quantum random number generators (QRNGs) are currently in high demand across a large number of cryptographic applications as secure sources of true randomness. In this work, we characterize the conditions from which randomness can be extracted in a QRNG based on homodyne measurements of vacuum fluctuations by assessing the impact of experimental limitations, such as the digitizer resolution or the presence of excess local oscillator (LO) noise due to an unbalanced detection. Moreover, we propose an estimation method to quantify the excess entropy contribution introduced by an unbalanced detection and analyze the implementation of the post-processing algorithm. Finally, we submitted the generated numbers to a set of statistical tests to assess the quality of its output randomness and verified that it passes the standard libraries.
The Numerical Investigation of Structural Strength Assessment of LNG CCS by Sloshing Impacts Based on Multiphase Fluid Model
Authors: Hwang Se-Yun , Lee Jang-Hyun
Published: August 2021

Sloshing flows of liquid natural gas (LNG) with multi-phase flow characteristics consisting of liquids and gases can affect the load conditions and structural response of cargo containment systems (CCS). The compressible properties of the sloshing flow can limit the maximum pressure, so a multi-phase fluid model is required to represent the sloshing physics. In this study, we identified a suitable numerical model to simulate the sloshing flow and structural strength evaluation based on the inhomogeneous fluid model. The computational fluid dynamics (CFD) is based on a Eulerian domain model, which is in turn based on the constant volume based finite element method (CVFEM) in a commercial Reynolds-averaged Navier–Stokes CFD code (ANSYS CFX). It includes the interphase momentum transfer between the liquids and gasses. The physics for the sloshing assessment were considered to identify the main aspects of the inhomogeneous multiphase model. For numerical analysis of the sloshing, we conducted a sloshing simulation on the experimental data of the model scale to examine the validity of the results. The velocity of the sloshing flow was extended to the real scale and applied to a local two-way fluid structure interaction (FSI) analysis model. Structural strength evaluation of the LNG CCS by sloshing flow was performed by FSI analysis. Through the example of structural response analysis of Mark III type CCS, the results were discussed and effectiveness of the proposed structural response assessment model by sloshing was reviewed.
Fourier Transform Infrared (FTIR) Spectroscopy for Measurements of Vehicle Exhaust Emissions: A Review
Authors: Giechaskiel Barouch , Clairotte Michaël
Published: August 2021

Pollution from vehicles is a serious concern for the environment and human health. Vehicle emission regulations worldwide have limits for pollutants such as hydrocarbons, CO, and NOx. The measurements are typically conducted at engine dynamometers (heavy-duty engines) sampling from the tailpipe or at chassis dynamometers (light-duty vehicles) sampling from the dilution tunnel. The latest regulations focused on the actual emissions of the vehicles on the road. Greenhouse gases (GHG) (such as CO2, CH4, N2O), and NH3 have also been the subject of some regulations. One instrument that can measure many gaseous compounds simultaneously is the Fourier transform infrared (FTIR) spectrometer. In this review the studies that assessed FTIRs since the 1980s are summarized. Studies with calibration gases or vehicle exhaust gas in comparison with well-established techniques were included. The main conclusion is that FTIRs, even when used at the tailpipe and not at the dilution tunnel, provide comparable results with other well-established techniques for CO2, CO, NOx, while for hydrocarbons, higher deviations were noticed. The introduction of FTIRs in the regulation needs a careful description of the technical requirements, especially interference tests. Although the limited results of prototype portable FTIRs for on-road measurement are promising, their performance at the wide range of environmental conditions (temperature, pressure, vibrations) needs further studies.
The Wingate Anaerobic Test, a Narrative Review of the Protocol Variables That Affect the Results Obtained
Authors: Castañeda-Babarro Arkaitz
Published: August 2021

The Wingate Anaerobic Test (WAT) has been widely used since its creation in 1974. The WAT involves performing a 30 s “all-out” cycling test. The test is currently applied with some modifications, partly due to the evolution of the material used to perform it. The purpose of this text is to act as a guide for the correct use and application of the test, as well as to highlight the importance of controlling many of the variables that may influence its results. Methods: A literature search was conducted in PUBMED/MEDLINE and Web of Science with different combinations of keywords all related to the WAT to obtain a search of 113 papers. Results and discussion: It was observed that variables such as the duration of the test or the resistance used in the cycle ergometer must be adjusted according to the objective and the population evaluated, while others such as the warm-up or the supplementation of different substances can improve performance on the WAT. Conclusions: In order to apply the WAT correctly, variables such as duration, resistance used or warm-up time and intensity must be adjusted according to the evaluated subjects and the aim of the study. Other variables such as position on the bike or equipment used should also be controlled if we want to guarantee its replicability.
A Top-N Movie Recommendation Framework Based on Deep Neural Network with Heterogeneous Modeling
Authors: Gong Jibing , Zhang Xinghao , Li Qing , Wang Cheng , Song Yaxi , Zhao Zhiyong , Wang Shuli
Published: August 2021

To provide more accurate and stable recommendations, it is necessary to combine display information with implicit information and to dig out potential information. Existing methods only consider explicit feedback information or implicit feedback information unilaterally and ignore the potential information of explicit feedback information and implicit feedback information, which is also crucial to the accuracy of the recommendation system. However, the traditional Heterogeneous Information Networks (HIN) recommendation ignores the attribute information in the meta-path and the interaction between the user and the item and, instead, only considers the linear characteristics of the user-object often ignoring its non-linear characteristics. Aiming at the potential information acquisition problem from assorted feedback, we propose a new top-N recommendation method MFDNN for Heterogeneous Information Networks (HINs). First, we consider explicit and implicit feedback information to determine the potential preferences of users and the potential features of the product. Then, matrix factorization (MF) and a deep neural network (DNN) are fused to learn independent feature embeddings through MF and DNN, and fully considering the linear and non-linear characteristics of the user-object. MFDNN was tested on several real data sets, such as Movie-Lens, and compared with benchmark experiments. MFDNN significantly improved the hit ratio (HR) and normalized discounted cumulative gain (NDCG). Further research showed that the meta-path bias had an excellent effect on the gain of potential information mining and the fusion of explicit and implicit information in the accuracy and stability of user interest classification.
Designing Reenacted Chatbots to Enhance Museum Experience
Authors: Noh Yeo-Gyeong , Hong Jin-Hyuk
Published: August 2021

The increased availability of chatbots has drawn attention and interest to the study of what answers they provide and how they provide them. Chatbots have become a common sight in museums but are limited to answering only simple and basic questions. Based on the observed potential of chatbots for history education in museums, we investigate how chatbots impact history education and improve the overall experience according to their appearance and language style. For this, we built three models, designed by factors on embodiment and reflection, and 60 sets of answer–questions, designed for the National Museum of Korea. We conducted a study with a total of 34 participants and carried out a variety of analyses covering individual learning styles, museum experience scales, gaze data, in-depth interviews and observations from researchers. We present various results and lessons regarding the effect of embodiment and reflection on the museum experience. Our findings show how people with different learning styles connect with chatbot models and how visitors’ behavior in the museum changes depending on the chatbot model. Specifically, the chatbot model equipped with embodiment and reflection shows its superiority in enhancing the museum experience, in general.
The Indirect Role of Gluteus Medius Muscle in Knee Joint Stability during Unilateral Vertical Jump and Landing on Unstable Surface in Young Trained Males
Authors: Sebesi Balázs , Fésüs Ádám , Varga Mátyás , Atlasz Tamás , Vadász Kitty , Mayer Petra , Vass Lívia , Meszler Balázs , Balázs Bence , Váczi Márk
Published: August 2021

(1) In the present investigation, we tested the hypothesis that unilateral countermovement jump performance is associated with knee joint stabilization ability during unilateral landing on unstable surface. (2) Twenty-five male sport students were tested for dynamometric knee extension and flexion, and hip abduction isometric strength. Myolectric activity of vastus lateralis and medialis, gluteus medius, and biceps femoris muscles were measured during unilateral countermovement vertical jump performed on a force plate, and during unilateral landing on unstable surface. (3) Vertical jump impulse negatively correlated with biceps femoris activation at landing. Participants with greater hip abduction force performed greater vertical jump impulse, and activated the biceps femoris less when landing on unstable surface. Furthermore, participants with smaller knee flexion/extension torque ratio increased biceps femoris/vastus medialis activation ratio at landing. (4) We conclude that hip abduction strength is an important contributor to unilateral vertical jump performance. Because biceps femoris is considered the synergist of the anterior cruciate ligament, we also propose that hip abductors are primary frontal plane protectors of the knee joint by reducing knee valgus and stress, allowing for smaller biceps femoris co-activation (secondary protection) at landing on unstable surface.
Thermal Performance Enhancement Using Absorber Tube with Inner Helical Axial Fins in a Parabolic Trough Solar Collector
Authors: Zaboli Mohammad , Mousavi Ajarostaghi Seyed Soheil , Saedodin Seyfolah , Saffari Pour Mohsen
Published: August 2021

In the present work, a parabolic trough solar (PTC) collector with inner helical axial fins as swirl generator or turbulator is considered and analyzed numerically. The three-dimensional numerical simulations have been done by finite volume method (FVM) using a commercial CFD code, ANSYS FLUENT 18.2. The spatial discretization of mass, momentum, energy equations, and turbulence kinetic energy has been obtained by a second-order upwind scheme. To compute gradients, Green-Gauss cell-based method has been employed. This work consists of two sections where, first, four various geometries are appraised, and in the following, the selected schematic of the collector from the previous part is selected, and four various pitches of inner helical fins including 250, 500, 750 and 1000 mm are studied. All the numerical results are obtained by utilizing the FVM. Results show that the thermal performance improvement by 23.1% could be achieved by using one of the proposed innovative parabolic trough solar collectors compare to the simple one. Additionally, the minimum and maximum thermal performance improvement (compare to the case without fins) belong to the case with P = 250 mm by 14.1% and, to the case with P = 1000 mm by 21.53%, respectively.
Lightweight Convolutional Neural Networks with Model-Switching Architecture for Multi-Scenario Road Semantic Segmentation
Authors: Lin Peng-Wei , Hsu Chih-Ming
Published: August 2021

A convolutional neural network (CNN) that was trained using datasets for multiple scenarios was proposed to facilitate real-time road semantic segmentation for various scenarios encountered in autonomous driving. However, the CNN inhibited the mutual suppression effect between weights; thus, it did not perform as well as a network that was trained using a single scenario. To address this limitation, we used a model-switching architecture in the network and maintained the optimal weights of each individual model which required considerable space and computation. We, subsequently, incorporated a lightweight process into the model to reduce the model size and computational load. The experimental results indicated that the proposed lightweight CNN with a model-switching architecture outperformed and was faster than the conventional methods across multiple scenarios in road semantic segmentation.
Say What You Are Looking At: An Attention-Based Interactive System for Autistic Children
Authors: Deng Furong , Zhou Yu , Song Sifan , Jiang Zijian , Chen Lifu , Su Jionglong , Sun Zhenglong , Zhang Jiaming
Published: August 2021

Gaze-following is an effective way for intention understanding in human–robot interaction, which aims to follow the gaze of humans to estimate what object is being observed. Most of the existing methods require people and objects to appear in the same image. Due to the limitation in the view of the camera, these methods are not applicable in practice. To address this problem, we propose a method of gaze following that utilizes a geometric map for better estimation. With the help of the map, this method is competitive for cross-frame estimation. On the basis of this method, we propose a novel gaze-based image caption system, which has been studied for the first time. Our experiments demonstrate that the system follows the gaze and describes objects accurately. We believe that this system is competent for autistic children’s rehabilitation training, pension service robots, and other applications.
Installation of Clip-Type Bird Flight Diverters on High-Voltage Power Lines with Aerial Manipulation Robot: Prototype and Testbed Experimentation
Authors: Rodriguez-Castaño Angel , Nekoo Saeed Rafee , Romero Honorio , Salmoral Rafael , Acosta José Ángel , Ollero Anibal
Published: August 2021

This work presents the application of an aerial manipulation robot for the semi-autonomous installation of clip-type bird flight diverters on overhead power line cables. A custom-made prototype is designed, developed, and experimentally validated. The proposed solution aims to reduce the cost and risk of current procedures carried out by human operators deployed on suspended carts, lifts, or manned helicopters. The system consists of an unmanned aerial vehicle (UAV) equipped with a custom-made tool. This tool allows the high force required for the diverter installation to be generated; however, it is isolated from the aerial robot through a passive joint. Thus, the aerial robot stability is not compromised during the installation. This paper thoroughly describes the designed prototype and the control system for semi-autonomous operation. Flight experiments conducted in an illustrative scenario validate the performance of the system; the tests were carried out in an indoor testbed using a power line cable mock-up.
A Hybrid Approach Combining Fuzzy c-Means-Based Genetic Algorithm and Machine Learning for Predicting Job Cycle Times for Semiconductor Manufacturing
Authors: Lee Gyu M. , Gao Xuehong
Published: August 2021

Job cycle time is the cycle time of a job or the time required to complete a job. Prediction of job cycle time is a critical task for a semiconductor fabrication factory. A predictive model must forecast job cycle time to pursue sustainable development, meet customer requirements, and promote downstream operations. To effectively predict job cycle time in semiconductor fabrication factories, we propose an effective hybrid approach combining the fuzzy c-means (FCM)-based genetic algorithm (GA) and a backpropagation network (BPN) to predict job cycle time. All job records are divided into two datasets: the first dataset is for clustering and training, and the other is for testing. An FCM-based GA classification method is developed to pre-classify the first dataset of job records into several clusters. The classification results are then fed into a BPN predictor. The BPN predictor can predict the cycle time and compare it with the second dataset. Finally, we present a case study using the actual dataset obtained from a semiconductor fabrication factory to demonstrate the effectiveness and efficiency of the proposed approach.
Isomorphic Circuits of Independent Amplitude Tunable Voltage-Mode Bandpass Filters and Quadrature Sinusoidal Oscillators
Authors: Wang San-Fu , Chen Hua-Pin , Ku Yitsen , Chen Wei-Yuan
Published: August 2021

This paper presents isomorphic circuits of voltage-mode (VM) non-inverting bandpass filters (NBPFs) and VM quadrature sinusoidal oscillators (QSOs) with independent amplitude control functionality. The proposed VM NBPFs and VM QSOs exhibit low-output impedance and independent amplitude control, which are important for easily cascading the VM operation and independent control of the amplitude gain. The proposed isomorphic circuits employ three LT1228 commercial integrated circuits (ICs), two grounded capacitors, two grounded resistors and one floating resistor. The use of grounded capacitors is beneficial for the implementation of the IC. Both NBPFs have a high-input impedance and have a wide range of independent amplitude tunable passband gain without affecting the quality factor (Q) and center frequency (fo). The Q and fo parameters of the proposed NBPFs are orthogonal tunability. By feeding back each input signal to the output response of the NBPF, two VM fully uncoupled QSOs are also proposed. The proposed VM fully uncoupled QSOs have two quadrature sinusoidal waveforms with two low-output impedances and one independent amplitude tunable sinusoidal waveform. The frequency of oscillation (FO) and the condition of oscillation (CO) are fully uncoupled and controlled electronically. The performances of the proposed isomorphic circuits have been tested with a ±5 volt power supply and are demonstrated by experimental measurements which confirm the theoretical assumptions.
Evaluation of the Microsoft Excel Solver Spreadsheet-Based Program for Nonlinear Expressions of Adsorption Isotherm Models onto Magnetic Nanosorbent
Authors: Suwannahong Kowit , Wongcharee Surachai , Kreetachart Torpong , Sirilamduan Chadrudee , Rioyo Javier , Wongphat Akkharaphong
Published: August 2021

The sorption of basic dyes onto magnetic nanosorbent is commonly used as a novel material to combat powdered activated carbon, which is difficult to handle and separate during water and wastewater treatment. This adsorption method is commonly implemented in water and wastewater treatment due to its low cost and high performance. To explore the feasibility of adsorption, six different nonlinear isotherm models were applied and introduced to evaluate the performance and adsorption mechanisms via Microsoft Excel, and they were then compared to those of MATLAB and OriginPro. The Langmuir best provided the sorption of methylene blue adsorbed for a two-parameter isotherm model. The three-parameter model Toth gave a goodness of fit indicating a heterogeneous sorbent surface. Error function analysis found that the Residual Sum of Squares Error, Chi-square, Coefficient of determination, Average Relative Error, Hybrid Fractional Error Function, Marquardt’s Percent Standard Deviation and Root Mean Square Error provided the best overall results. In comparison, it could be concluded that six isotherm models showed the confidence interval that is simply the best fit at all experimental data points provided by the three software tools. All error function results indicated that the Microsoft Excel Solver function spreadsheet method satisfied all the statistic measures to predict the real variance of the probability of experimental data for all six isotherm models of adsorption of basic dye removal. One added benefit of this Microsoft Excel software tool is the built-in function associated with the desired type of application, which designates the desired type of error/statistical functions not mentioned in this research to the adsorbent materials used.
Deep Learning Based Uncertainty Analysis in Computational Micromechanics of Composite Materials
Authors: Sepahvand Kian K.
Published: August 2021

Design of new materials is quite a difficult task owing to various time and length scales and affiliated uncertainties. The major challenge is to include all these in a conventional model. Hyperparameter models in machine learning can be used to overcome these issues. In this paper, an artificial neural network (ANN) model is developed to estimate the effective elastic parameters of unidirectional fiber reinforced composites using representative volume elements (RVE) considering uncertainty in the fiber diameter. The diameter probability distribution is constructed from the acquired gray images by employing image processing operations. The generalized Polynomial Chaos (gPC) expansion is then used to represent the distribution as a random input parameter for finite element analysis, from where the effective parameters are realized. Similarly, the outputs of the FE model, i.e., elastic parameters, are approximated by gPC expansions having unknown deterministic coefficients and random orthogonal Hermite polynomials. A set of collocation points are generated from roots of the random polynomials; from there, the unknown coefficients are estimated. The realization samples are utilized to train an ANN algorithm based on supervised deep learning. The developed ANN model is later tested and validated for a new sample set of data. It is shown that the ANN model with few hidden layers and neurons has a high accuracy for estimation of the elastic parameters directly from the information on the distribution of fiber diameters.
Seasonal Evolution of the Chemical Composition of Atmospheric Aerosol in Terra Nova Bay (Antarctica)
Authors: Vagnoni Flavio , Illuminati Silvia , Annibaldi Anna , Memmola Francesco , Giglione Giada , Falgiani Anna Maria , Girolametti Federico , Fanelli Matteo , Scarponi Giuseppe , Truzzi Cristina
Published: August 2021

Atmospheric aerosol samples were collected at Faraglione Camp, 3 km away from the Italian Mario Zucchelli Station (Terra Nova Bay, Ross Sea), from 1 December 2013 to 2 February 2014. A two-step extraction procedure was applied to characterize the soluble and insoluble components of PM10-bound metals. Samples were analyzed for Al, Fe, Cd, Cu, and Pb by square wave anodic stripping voltammetry (SWASV) and by graphite furnace atomic absorption spectrophotometer (GF-AAS). The mean atmospheric concentrations were (reported as means ± SD) Al 24 ± 3 ng m−3; Fe 23 ± 4 ng m−3; Cd 0.92 ± 0.53 pg m−3; Cu 43 ± 9 pg m−3, and Pb 16 ± 5 pg m−3. The fractionation pattern was metal-specific, with Al, Fe, and Pb mainly present in the insoluble fractions, Cd in the soluble one, and Cu equally distributed between the two fractions. The summer evolution showed overall constant behavior of both fractions for Al and Fe, while a bell-shaped trend was observed for the three trace metals. Cd and Cu showed a bell-shaped evolution involving both fractions. A seasonal increase in Pb occurred only for the insoluble fraction, while the soluble fraction remained almost constant. Sequential extraction and enrichment factors indicated a crustal origin for Al, Fe, and Pb, and additional (marine or anthropogenic) contributions for Cd and Cu. Back trajectory analysis showed a strong contribution of air masses derived from the Antarctic plateau. A potential low contribution from anthropized areas cannot be excluded. Further studies are necessary to better characterize the chemical composition of the aerosol, to discriminate between natural and anthropogenic sources, and to evaluate a quantitative source apportionment.
Uptake of Biotinylated Spermine in Astrocytes: Effect of Cx43 siRNA, HIV-Tat Protein and Polyamine Transport Inhibitor on Polyamine Uptake
Authors: Malpica-Nieves Christian J. , Rivera Yomarie , Rivera-Aponte David E. , Phanstiel Otto , Veh Rüdiger W. , Eaton Misty J. , Skatchkov Serguei N.
Published: August 2021

Polyamines (PAs) are polycationic biomolecules containing multiple amino groups. Patients with HIV-associated neurocognitive disorder (HAND) have high concentrations of the polyamine N-acetylated spermine in their brain and cerebral spinal fluid (CSF) and have increased PA release from astrocytes. These effects are due to the exposure to HIV-Tat. In healthy adult brain, PAs are accumulated but not synthesized in astrocytes, suggesting that PAs must enter astrocytes to be N-acetylated and released. Therefore, we tested if Cx43 hemichannels (Cx43-HCs) are pathways for PA flux in control and HIV-Tat-treated astrocytes. We used biotinylated spermine (b-SPM) to examine polyamine uptake. We found that control astrocytes and those treated with siRNA-Cx43 took up b-SPM, similarly suggesting that PA uptake is via a transporter/channel other than Cx43-HCs. Surprisingly, astrocytes pretreated with both HIV-Tat and siRNA-Cx43 showed increased accumulation of b-SPM. Using a novel polyamine transport inhibitor (PTI), trimer 44NMe, we blocked b-SPM uptake, showing that PA uptake is via a PTI-sensitive transport mechanism such as organic cation transporter. Our data suggest that Cx43 HCs are not a major pathway for b-SPM uptake in the condition of normal extracellular calcium concentration but may be involved in the release of PAs to the extracellular space during viral infection.
Potential of Activin B as a Clinical Biomarker in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)
Authors: Gravelsina Sabine , Nora-Krukle Zaiga , Vilmane Anda , Svirskis Simons , Vecvagare Katrine , Krumina Angelika , Murovska Modra
Published: August 2021

Reliable serum biomarkers are of immense need for diagnostic purposes of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)—a disabling and complex disease for which diagnosis is mainly based on clinical symptoms. The aim of this study was to evaluate a possible diagnostic potential of activin B by directly comparing 134 cases of ME/CFS with 54 healthy controls. Analyses of human activin B level in plasma samples were performed using a validated human activin B ELISA assay. The results of the study show that activin B levels did not differ statistically significantly between ME/CFS patients and healthy controls (p = 0.6511). No gender or age-related differences in activin B levels were observed in the ME/CFS group and healthy controls. The level of activin B tended to decrease with increasing visual analogue scale score (r = −0.2004; p = 0.5085) nevertheless the results obtained so far does not support the clinical utility of activin B as a biomarker for ME/CFS.
The Application of Fe-EDTA and Sodium Silicate Affects the Polyphenols Content in Broccoli and Radish Sprouts
Authors: Dębski Henryk , Wiczkowski Wiesław , Szablińska-Piernik Joanna , Horbowicz Marcin
Published: August 2021

The effects of elicitors on broccoli (Brassica oleracea L. var. Italica) and radish (Raphanus sativus L.) sprouts were evaluated. Seeds and then sprouts were soaked daily for 30 min over 6 days in water (control) or a mixture of FeEDTA and sodium silicate or sodium silicate alone. The contents of the flavonoids and phenolic acids (free, esters, and glycosides) were determined using HPLC-ESI-MS/MS. Phenolic compounds were released from the esters after acid hydrolysis and from the glycosides using alkaline hydrolysis. Quercetin, kaempferol, (‒)-epicatechin, naringenin, apigenin, and luteolin derivatives were found in broccoli and radish sprouts, while derivatives of iso-rhamnetin, orientin, and vitexin were not present at measurable levels. The flavonoid contents, especially derivatives of quercetin, were considerably higher in the broccoli sprouts than in the radish sprouts. The quantitatively major phenolic acid content in the sprouts of both species was found to be p-hydroxybenzoic acid. Its content in the radish sprouts was several times higher than in the broccoli sprouts. The total flavonoid content of broccoli sprouts was 507–734 µg/g DW, while that of the radish sprouts ranged from 155 µg/g DW to 211 µg/g DW. In contrast, total phenolic acids were higher in radish sprouts, ranging from 11,548 to 13,789 µg/g DW, while in broccoli sprouts, they ranged from 2652 to 4527 µg/g DW, respectively. These differences resulted radish sprouts having higher antioxidant activity compared to broccoli sprouts. The applied elicitors increased the content of the total phenolic acids and the antioxidant activity of radish and broccoli sprouts, while they decreased the level of the total flavonoids in broccoli sprouts.