bluuebunny/crossref_metadata_2025 huggingface dataset:
Milk-Fat Intake and Differences in Abdominal Adiposity and BMI: Evidence Based on 13,544 Randomly-Selected Adults
Authors: Wilkinson Klarissa R. , Tucker Larry A. , Davidson Lance E. , Bailey Bruce W.
Published: May 2021

The primary purpose of this investigation was to evaluate the relationship between milk-fat intake and obesity, particularly abdominal obesity, in 13,544 U.S. adults. A lesser objective was to measure the degree to which the association was influenced by multiple potential confounding variables. This cross-sectional study used data from the 2011–2016 National Health and Nutrition Examination Survey (NHANES). Quantity of milk-fat regularly consumed was the exposure variable. Sagittal abdominal diameter (SAD), a measure of abdominal obesity, and body mass index (BMI) were the outcome variables. Sagittal abdominal diameter is a strong predictor of visceral abdominal fat, when measured by computed tomography, and has been shown to predict cardiometabolic disorders better than BMI. After controlling for age, race, gender, physical activity, leisure computer use and gaming, alcohol habits, and cigarette use, significantly lower BMIs were associated with consistent non-fat and full-fat milk consumption (F = 4.1, p = 0.0063). A significantly lower SAD was associated only with regular consumption of non-fat milk (F = 5.0, p = 0.0019). No significant differences were detected between the other milk-fat groups or milk abstainers. In this nationally representative sample, only 19.6% of adults regularly consumed low-fat milk. In conclusion, consistent non-fat milk intake was predictive of lower levels of abdominal adiposity compared to consumption of higher levels of milk-fat.
Foxtail Millet Improves Blood Glucose Metabolism in Diabetic Rats through PI3K/AKT and NF-κB Signaling Pathways Mediated by Gut Microbiota
Authors: Ren Xin , Wang Linxuan , Chen Zenglong , Hou Dianzhi , Xue Yong , Diao Xianmin , Shen Qun
Published: May 2021

Foxtail millet (FM) is receiving ongoing increased attention due to its beneficial health effects, including the hypoglycemic effect. However, the underlying mechanisms of the hypoglycemic effect have been underexplored. In the present study, the hypoglycemic effect of FM supplementation was confirmed again in high-fat diet and streptozotocin-induced diabetic rats with significantly decreased fasting glucose (FG), glycated serum protein, and areas under the glucose tolerance test (p < 0.05). We employed 16S rRNA and liver RNA sequencing technologies to identify the target gut microbes and signaling pathways involved in the hypoglycemic effect of FM supplementation. The results showed that FM supplementation significantly increased the relative abundance of Lactobacillus and Ruminococcus_2, which were significantly negatively correlated with FG and 2-h glucose. FM supplementation significantly reversed the trends of gene expression in diabetic rats. Specifically, FM supplementation inhibited gluconeogenesis, stimulated glycolysis, and restored fatty acid synthesis through activation of the PI3K/AKT signaling pathway. FM also reduced inflammation through inhibition of the NF-κB signaling pathway. Spearman’s correlation analysis indicated a complicated set of interdependencies among the gut microbiota, signaling pathways, and metabolic parameters. Collectively, the above results suggest that the hypoglycemic effect of FM was at least partially mediated by the increased relative abundance of Lactobacillus, activation of the PI3K/AKT signaling pathway, and inhibition of the NF-κB signaling pathway.
Occupational Allergies in Dentistry: A Cross-Sectional Study in a Group of French Dentists
Authors: Boudinar Lise , Offner Damien , Jung Sophie
Published: May 2021

Background: Dentists have a high risk of developing occupational allergies due to their repeated exposure to many professional allergens. The aim of this cross-sectional study was to assess occupation-related allergies in a group of French dentists and to determine the main associated risk factors. Methods: A self-administered questionnaire about allergies, particularly occupational allergies, was published online in a private group dedicated to French dentists. Results: Data from 584 French dentists were collected; 50.3% of the respondents presented allergies and 13.4% presented occupation-related allergies. Regarding professional allergens, natural rubber latex, cleaning products, and resins were the most frequently incriminated substances. Temporary interruption of activity was reported by 10.3% of individuals suffering from occupational allergies. Almost 65% of them used different reliever medications for the management of acute exacerbations, but maintenance treatment was implemented in only 34.6% of cases. Having a general allergy was the first predictor of occupational allergies with an odds ratio of 7.49. Conclusions: The frequency and the impact of occupational allergies were significant among our study population of French dentists, particularly in those with an associated allergic background. Education and prevention programs are key measures to minimize risk.
Serial Interferon-Gamma Release Assay (IGRA) Testing to Monitor Treatment Responses in Cases of Feline Mycobacteriosis
Authors: Mitchell Jordan L. , O’Halloran Conor , Stanley Paul , McDonald Kieran , Burr Paul , Gunn-Moore Danièlle A. , Hope Jayne C.
Published: May 2021

The interferon-gamma release assay (IGRA) is used to diagnose cases of feline mycobacteriosis, but the use of serial testing to monitor treatment responses has not been evaluated in this species. From a population of cats that underwent IGRA testing for diagnostic investigation, individuals were identified with a pre- and end-of-treatment IGRA that passed control thresholds. The number of cats which reverted to negative at the end-of-treatment IGRA, changes in paired antigen-specific optical density (OD) values and differences in the pre-treatment antigen-specific OD values for those which underwent reversion were compared. Factors to explain reversion or recurrence of disease post-treatment were explored. Four of 18 cats (22%) reverted to negativity at the point of clinical resolution (p = 0.33), there was no difference in paired antigen-specific OD values (p ≥ 0.12), and cats that reverted did not have a lower baseline OD value (p = 0.63). No statistically significant factors were identified to predict reversion (p ≥ 0.08). Remaining positive at the end of treatment IGRA was not associated with recurrence of disease post-treatment (p = 0.34). Overall, these data suggest there is limited value in the use of the IGRA to monitor treatment responses in cats.
Potential Tamoxifen Repurposing to Combat Infections by Multidrug-Resistant Gram-Negative Bacilli
Authors: Miró-Canturri Andrea , Ayerbe-Algaba Rafael , del Toro Raquel , Mejías Manuel Enrique-Jiménez , Pachón Jerónimo , Smani Younes
Published: May 2021

The development of new strategic therapies for multidrug-resistant bacteria, like the use of non-antimicrobial approaches and/or drugs repurposed to be used as monotherapies or in combination with clinically relevant antibiotics, has become urgent. A therapeutic alternative for infections by multidrug-resistant Gram-negative bacilli (MDR-GNB) is immune system modulation to improve the infection clearance. We showed that immunocompetent mice pretreated with tamoxifen at 80 mg/kg/d for three days and infected with Acinetobacter baumannii, Pseudomonas aeruginosa, or Escherichia coli in peritoneal sepsis models showed reduced release of the monocyte chemotactic protein-1 (MCP-1) and its signaling pathway interleukin-18 (IL-18), and phosphorylated extracellular signal-regulated kinase 1/2 (ERK1/2). This reduction of MCP-1 induced the reduction of migration of inflammatory monocytes and neutrophils from the bone marrow to the blood. Indeed, pretreatment with tamoxifen in murine peritoneal sepsis models reduced the bacterial load in tissues and blood, and increased mice survival from 0% to 60–100%. Together, these data show that tamoxifen presents therapeutic efficacy against MDR A. baumannii, P. aeruginosa, and E. coli in experimental models of infection and may be a new candidate to be repurposed as a treatment for GNB infections.
Myeloperoxidase Inhibitory and Antioxidant Activities of (E)-2-Hydroxy-α-aminocinnamic Acids Obtained through Microwave-Assisted Synthesis
Authors: Rivera-Antonio Astrid , Rosales-Hernández Martha Cecilia , Balbuena-Rebolledo Irving , Santiago-Quintana José Martín , Mendieta-Wejebe Jessica Elena , Correa-Basurto José , García-Vázquez Juan Benjamín , García-Báez Efrén Venancio , Padilla-Martínez Itzia I.
Published: May 2021

Myeloperoxidase (MPO) is an enzyme present in human neutrophils, whose main role is to provide defenses against invading pathogens. However, highly reactive oxygen species (ROS), such as HOCl, are generated from MPO activity, leading to chronic diseases. Herein, we report the microwave-assisted synthesis of a new series of stable (E)-(2-hydroxy)-α-aminocinnamic acids, in good yields, which are structurally analogous to the natural products (Z)-2-hydroxycinnamic acids. The radical scavenging activity (RSA), MPO inhibitory activity and cytotoxicity of the reported compounds were evaluated. The hydroxy derivatives showed the most potent RSA, reducing the presence of DPPH and ABTS radicals by 77% at 0.32 mM and 100% at 0.04 mM, respectively. Their mechanism of action was modeled with BDEOH, IP and ΔEH-L theoretical calculations at the B3LYP/6 − 31 + G(d,p) level. Compounds showed in vitro inhibitory activity of MPO with IC50 values comparable to indomethacin and 5-ASA, but cytotoxicities below 15% at 100–200 µM. Docking calculations revealed that they reach the amino acid residues present in the distal cavity of the MPO active site, where both the amino and carboxylic acid groups of the α-aminopropenoic acid arm are structural requirements for anchoring. (E)-2-hydroxy-α-aminocinnamic acids have been synthesized for the first time with a reliable method and their antioxidant properties demonstrated.
Bis-Bibenzyls from the Liverwort Pellia endiviifolia and Their Biological Activity
Authors: Ivković Ivana , Novaković Miroslav , Veljić Milan , Mojsin Marija , Stevanović Milena , Marin Petar D. , Bukvički Danka
Published: May 2021

Based on previous investigations where bis-bibenzyls isolated from liverworts showed various biological activities (cytotoxic, antimicrobial, and antiviral), we investigated their cytotoxic activity in several human cancer cell lines. From the methylene-chloride/methanol extract of the liverwort Pellia endiviifolia, three bis-bibenzyls of the perrottetin type were isolated, namely perrottetin E, 10′-hydroxyperrottetin E, and 10,10′-dihydroxyperrottetin E. The last two were found for the first time in this species. Their structures were resolved using 1D and 2D NMR, as well as by comparison with data in the literature. Cytotoxic activity of the isolated compounds was tested on three human leukemia cell lines, HL-60 (acute promyelocytic leukemia cells), U-937 (acute monocytic leukemia cells), and K-562 (human chronic myelogenous leukemia cells), as well as on human embryonal teratocarcinoma cell line (NT2/D1) and human glioblastoma cell lines A-172 and U-251, and compared to the previously isolated bis-bibenzyls (perrottetins) of similar structure. The isolated compounds exhibited modest activity against leukemia cells and significant activity against NT2/D1 and A-172. Overall, the most active cytotoxic compounds in this investigation were perrottetin E (1), isolated in this work from Pellia endiviifolia, and perrottetin F phenanthrene derivative (7), previously isolated from Lunularia cruciata and added for a comparison of their cytotoxic activity.
Profiling of Plant Growth-Promoting Metabolites by Phosphate-Solubilizing Bacteria in Maize Rhizosphere
Authors: Shen Minchong , Li Jiangang , Dong Yuanhua , Liu Hong , Peng Junwei , Hu Yang , Sun Yang
Published: May 2021

Microbial treatment has recently been attracting attention as a sustainable agricultural strategy addressing the current problems caused by unreasonable agricultural practices. However, the mechanism through which microbial inoculants promote plant growth is not well understood. In this study, two phosphate-solubilizing bacteria (PSB) were screened, and their growth-promoting abilities were explored. At day 7 (D7), the lengths of the root and sprout with three microbial treatments, M16, M44, and the combination of M16 and M44 (Com), were significantly greater than those with the non-microbial control, with mean values of 9.08 and 4.73, 7.15 and 4.83, and 13.98 and 5.68 cm, respectively. At day 14 (D14), M16, M44, and Com significantly increased not only the length of the root and sprout but also the underground and aboveground biomass. Differential metabolites were identified, and various amino acids, amino acid derivatives, and other plant growth-regulating molecules were significantly enhanced by the three microbial treatments. The profiling of key metabolites associated with plant growth in different microbial treatments showed consistent results with their performances in the germination experiment, which revealed the metabolic mechanism of plant growth-promoting processes mediated by screened PSB. This study provides a theoretical basis for the application of PSB in sustainable agriculture.
A Study of the Adsorption and Removal of Sb(III) from Aqueous Solution by Fe(III) Modified Proteus cibarius with Mechanistic Insights Using Response Surface Methodology
Authors: Li Xiaojian , Deng Renjian , Tang Zhie , Zhou Saijun , Zeng Xing , Wang Jianqun , Hursthouse Andrew
Published: May 2021

Environmental pollution caused by excessive Sb(III) in the water environment is a global issue. We investigated the effect of processing parameters, their interaction and mechanistic details for the removal of Sb(III) using an iron salt-modified biosorbent (Fe(III)-modified Proteus cibarius (FMPAs)). Our study evaluated the optimisation of the adsorption time, adsorbent dose, pH, temperature and the initial concentration of Sb(III). We use response surface methodology to optimize this process, determining optimal processing conditions and the adsorption mechanism evaluated based on isotherm model and adsorption kinetics. The results showed that—(1) the optimal conditions for the adsorption of Sb(III) by FMPAs were an adsorption time of 2.2 h, adsorbent dose of 3430 mg/L, at pH 6.0 and temperature 44.0 °C. For the optimum initial concentration of Sb(III) 27.70 mg/L, the removal efficiency of Sb(III) reached 97.60%. (2) The adsorption process for Sb(III) removal by FMPAs conforms to the Langmuir adsorption isotherm model, and its maximum adsorption capacity (qmax) is as high as 30.612 mg/g. A pseudo-first-order kinetic model provided the best fit to the adsorption process, classified as single layer adsorption and chemisorption mechanism. (3) The adsorption of Sb(III) takes place via the hydroxyl group in Fe–O–OH and EPS–Polyose–O–Fe(OH)2, which forms a new complex Fe–O–Sb and X≡Fe–OH. The study showed that FMPAs have higher adsorption capacity for Sb(III) than other previously studied sorbents and with low environmental impact, it has a great potential as a green adsorbent for Sb(III) in water.
Optimization of a Fuzzy Automatic Voltage Controller Using Real-Time Recurrent Learning
Authors: Espitia Helbert , Machón Iván , López Hilario
Published: May 2021

The automatic voltage regulator is an important component in energy generation systems; therefore, the tuning of this system is a fundamental aspect for the suitable energy conversion. This article shows the optimization of a fuzzy automatic voltage controller for a generation system using real-time recurrent learning, which is a technique conventionally used for the training of recurrent neural networks. The controller used consists of a compact fuzzy system based on Boolean relations, designed having equivalences with PI, PD, PID, and second order controllers. For algorithm implementation, the training equations are deduced considering the structure of the second order compact fuzzy controller. The results show that a closed-loop fuzzy control strategy was successfully implemented using real-time recurrent learning. In order to implement the controllers optimization, different weighting values for error and control action are used. The results show the behavior of the configurations used and its performance considering the steady state error, overshoot, and settling time.
Effect of Processing on Phenolic Composition of Olive Oil Products and Olive Mill By-Products and Possibilities for Enhancement of Sustainable Processes
Authors: Safarzadeh Markhali Fereshteh
Published: May 2021

The bio-functional properties of olive oil products and by-products rely greatly on the proportions and types of the endogenous phenolics that may favorably/unfavorably change during various processing conditions. The olive oil industrial activities typically produce (i) olive oils, the main/marketable products, and (ii) olive mill by-products. The mechanical processing of olive oil extraction is making progress in some areas. However, the challenges inherent in the existing system, taking into consideration, the susceptibilities of phenolics and their biosynthetic variations during processing, hamper efforts to ascertain an ideal approach. The proposed innovative means, such as inclusion of emerging technologies in extraction system, show potential for sustainable development of olive oil processing. Another crucial factor, together with the technological advancements of olive oil extraction, is the valorization of olive mill by-products that are presently underused while having great potential for extended/high-value applications. A sustainable re-utilization of these valuable by-products helps contribute to (i) food and nutrition security and (ii) economic and environmental sustainability. This review discusses typical processing factors responsible for the fate of endogenous phenolics in olive oil products/by-products and provides an overview of the possibilities for the sustainable processing to (i) produce phenolic-rich olive oil and (ii) optimally valorize the by-products.
Temperature Sensing Optimization for Home Thermostat Retrofit
Authors: Seri Federico , Arnesano Marco , Keane Marcus Martin , Revel Gian Marco
Published: May 2021

Most existing residential buildings adopt one single-zone thermostat to control the heating of rooms with different thermal conditions. This solution often provides poor thermal comfort and inefficient use of energy. The current market proposes smart thermostats and thermostatic radiator valves (TRVs) as cheap and relatively easy-to-install retrofit solutions. These systems provide increased freedom of installation, due to the use of wireless communication; however, the uncertainty of the measured air temperature, considering the thermostat placement, could impact the final heating performance. This paper presents a sensing optimization approach for a home thermostat, in order to determine the optimal retrofit configuration to reduce the sensing uncertainty, thus achieving the required comfort level and minimizing the retrofit’s payback period. The methodology was applied to a real case study—a dwelling located in Italy. The measured data and a simulation model were used to create different retrofit scenarios. Among these, the optimal scenario was achieved through thermostat repositioning and a setpoint of 21 °C, without the use of TRVs. Such optimization provided an improvement of control performance due to sensor location, with consequent energy savings of 7% (compared to the baseline). The resulting payback period ranged from two and a half years to less than a year, depending on impact of the embedded smart thermostat algorithms.
Cloud-Based Single-Frequency Snapshot RTK Positioning
Authors: Liu Xiao , Ribot Miguel Ángel , Gusi-Amigó Adrià , Rovira-Garcia Adria , Sanz Jaume , Closas Pau
Published: May 2021

With great potential for being applied to Internet of Things (IoT) applications, the concept of cloud-based Snapshot Real Time Kinematics (SRTK) was proposed and its feasibility under zero-baseline configuration was confirmed recently by the authors. This article first introduces the general workflow of the SRTK engine, as well as a discussion on the challenges of achieving an SRTK fix using actual snapshot data. This work also describes a novel solution to ensure a nanosecond level absolute timing accuracy in order to compute highly precise satellite coordinates, which is required for SRTK. Parameters such as signal bandwidth, integration time and baseline distances have an impact on the SRTK performance. To characterize this impact, different combinations of these settings are analyzed through experimental tests. The results show that the use of higher signal bandwidths and longer integration times result in higher SRTK fix rates, while the more significant impact on the performance comes from the baseline distance. The results also show that the SRTK fix rate can reach more than 93% by using snapshots with a data size as small as 255 kB. The positioning accuracy is at centimeter level when phase ambiguities are resolved at a baseline distance less or equal to 15 km.
Enhanced Monitoring of Sleep Position in Sleep Apnea Patients: Smartphone Triaxial Accelerometry Compared with Video-Validated Position from Polysomnography
Authors: Ferrer-Lluis Ignasi , Castillo-Escario Yolanda , Montserrat Josep Maria , Jané Raimon
Published: May 2021

Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG.
End-To-End Computer Vision Framework: An Open-Source Platform for Research and Education
Authors: Orhei Ciprian , Vert Silviu , Mocofan Muguras , Vasiu Radu
Published: May 2021

Computer Vision is a cross-research field with the main purpose of understanding the surrounding environment as closely as possible to human perception. The image processing systems is continuously growing and expanding into more complex systems, usually tailored to the certain needs or applications it may serve. To better serve this purpose, research on the architecture and design of such systems is also important. We present the End-to-End Computer Vision Framework, an open-source solution that aims to support researchers and teachers within the image processing vast field. The framework has incorporated Computer Vision features and Machine Learning models that researchers can use. In the continuous need to add new Computer Vision algorithms for a day-to-day research activity, our proposed framework has an advantage given by the configurable and scalar architecture. Even if the main focus of the framework is on the Computer Vision processing pipeline, the framework offers solutions to incorporate even more complex activities, such as training Machine Learning models. EECVF aims to become a useful tool for learning activities in the Computer Vision field, as it allows the learner and the teacher to handle only the topics at hand, and not the interconnection necessary for visual processing flow.
A Convolutional Neural Network Combining Discriminative Dictionary Learning and Sequence Tracking for Left Ventricular Detection
Authors: Wang Xuchu , Wang Fusheng , Niu Yanmin
Published: May 2021

Cardiac MRI left ventricular (LV) detection is frequently employed to assist cardiac registration or segmentation in computer-aided diagnosis of heart diseases. Focusing on the challenging problems in LV detection, such as the large span and varying size of LV areas in MRI, as well as the heterogeneous myocardial and blood pool parts in LV areas, a convolutional neural network (CNN) detection method combining discriminative dictionary learning and sequence tracking is proposed in this paper. To efficiently represent the different sub-objects in LV area, the method deploys discriminant dictionary to classify the superpixel oversegmented regions, then the target LV region is constructed by label merging and multi-scale adaptive anchors are generated in the target region for handling the varying sizes. Combining with non-differential anchors in regional proposal network, the left ventricle object is localized by the CNN based regression and classification strategy. In order to solve the problem of slow classification speed of discriminative dictionary, a fast generation module of left ventricular scale adaptive anchors based on sequence tracking is also proposed on the same individual. The method and its variants were tested on the heart atlas data set. Experimental results verified the effectiveness of the proposed method and according to some evaluation indicators, it obtained 92.95% in AP50 metric and it was the most competitive result compared to typical related methods. The combination of discriminative dictionary learning and scale adaptive anchor improves adaptability of the proposed algorithm to the varying left ventricular areas. This study would be beneficial in some cardiac image processing such as region-of-interest cropping and left ventricle volume measurement.
A Sawn Timber Tree Species Recognition Method Based on AM-SPPResNet
Authors: Ding Fenglong , Liu Ying , Zhuang Zilong , Wang Zhengguang
Published: May 2021

Sawn timber is an important component material in furniture manufacturing, decoration, construction and other industries. The mechanical properties, surface colors, textures, use and other properties of sawn timber possesed by different tree species are different. In order to meet the needs of reasonable timber use and product quality of sawn timber products, sawn timber must be identified according to tree species to ensure the best use of materials. In this study, an optimized convolution neural network was proposed to process sawn timber image data to identify the tree species of the sawn timber. The spatial pyramid pooling and attention mechanism were used to improve the convolution layer of ResNet101 to extract the feature vector of sawn timber images. The optimized ResNet (simply called “AM-SPPResNet”) was used to identify the sawn timber image, and the basic recognition model was obtained. Then, the weight parameters of the feature extraction layer of the basic model were frozen, the full connection layer was removed, and using support vector machine (SVM) and XGBoost classifier which were commonly used in machine learning to train and learn the 21 × 1024 dimension feature vectors extracted by feature extraction layer. Through a number of comparative experiments, it is found that the prediction model using linear function as the kernel function of support vector machine learning the feature vectors extracted from the improved convolution layer performed best, and the F1 score and overall accuracy of all kinds of samples were above 99%. Compared with the traditional methods, the accuracy was improved by up to 12%.
PCA-Based Denoising Algorithm for Outdoor Lidar Point Cloud Data
Authors: Cheng Dongyang , Zhao Dangjun , Zhang Junchao , Wei Caisheng , Tian Di
Published: May 2021

Due to the complexity of surrounding environments, lidar point cloud data (PCD) are often degraded by plane noise. In order to eliminate noise, this paper proposes a filtering scheme based on the grid principal component analysis (PCA) technique and the ground splicing method. The 3D PCD is first projected onto a desired 2D plane, within which the ground and wall data are well separated from the PCD via a prescribed index based on the statistics of points in all 2D mesh grids. Then, a KD-tree is constructed for the ground data, and rough segmentation in an unsupervised method is conducted to obtain the true ground data by using the normal vector as a distinctive feature. To improve the performance of noise removal, we propose an elaborate K nearest neighbor (KNN)-based segmentation method via an optimization strategy. Finally, the denoised data of the wall and ground are spliced for further 3D reconstruction. The experimental results show that the proposed method is efficient at noise removal and is superior to several traditional methods in terms of both denoising performance and run speed.
Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method
Authors: Li Wenfei , Li Huiyun , Xu Kun , Huang Zhejun , Li Ke , Du Haiping
Published: May 2021

Vehicle dynamic parameters are of vital importance to establish feasible vehicle models which are used to provide active controls and automated driving control. However, most vehicle dynamics parameters are difficult to obtain directly. In this paper, a new method, which requires only conventional sensors, is proposed to estimate vehicle dynamic parameters. The influence of vehicle dynamic parameters on vehicle dynamics often involves coupling. To solve the problem of coupling, a two-stage estimation method, consisting of multiple-models and the Unscented Kalman Filter, is proposed in this paper. During the first stage, the longitudinal vehicle dynamics model is used. Through vehicle acceleration/deceleration, this model can be used to estimate the distance between the vehicle centroid and vehicle front, the height of vehicle centroid and tire longitudinal stiffness. The estimated parameter can be used in the second stage. During the second stage, a single-track with roll dynamics vehicle model is adopted. By making vehicle continuous steering, this vehicle model can be used to estimate tire cornering stiffness, the vehicle moment of inertia around the yaw axis and the moment of inertia around the longitudinal axis. The simulation results show that the proposed method is effective and vehicle dynamic parameters can be well estimated.
Novel Real-Time OEP Phase Angle Feedback System for Dysfunctional Breathing Pattern Training—An Acute Intervention Study
Authors: Smyth Carol M. E. , Winter Samantha L. , Dickinson John W.
Published: May 2021

Dysfunctional breathing patterns (DBP) can have an impact on an individual’s quality of life and/or exercise performance. Breathing retraining is considered to be the first line of treatment to correct breathing pattern, for example, reducing ribcage versus abdominal movement asynchrony. Optoelectronic plethysmography (OEP) is a non-invasive 3D motion capture technique that measures the movement of the chest wall. The purpose of this study was to investigate if the use of a newly developed real-time OEP phase angle and volume feedback system, as an acute breathing retraining intervention, could result in a greater reduction of phase angle values (i.e., an improvement in movement synchrony) when compared to real-time OEP volume feedback alone. Eighteen individuals with a DBP performed an incremental cycle test with OEP measuring chest wall movement. Participants were randomly assigned to either the control group, which included the volume-based OEP feedback or to the experimental group, which included both the volume-based and phase angle OEP feedback. Participants then repeated the same cycle test using the real-time OEP feedback. The phase angle between the ribcage versus abdomen (RcAbPhase), between the pulmonary ribcage and the combined abdominal ribcage and abdomen (RCpAbPhase), and between the abdomen and the shoulders (AbSPhase) were calculated during both cycle tests. Significant increases in RcAbPhase (pre: −2.89°, post: −1.39°, p < 0.01), RCpAbPhase (pre: −2.00°, post: −0.50°, p < 0.01), and AbSPhase (pre: −2.60°, post: −0.72°, p < 0.01) were found post-intervention in the experimental group. This indicates that the experimental group demonstrated improved synchrony in their breathing pattern and therefore, reverting towards a healthy breathing pattern. This study shows for the first time that dysfunctional breathing patterns can be acutely improved with real-time OEP phase angle feedback and provides interesting insight into the feasibility of using this novel feedback system for breathing pattern retraining in individuals with DBP.
Model of a Device-Level Combined Wireless Network Based on NB-IoT and IEEE 802.15.4 Standards for Low-Power Applications in a Diverse IoT Framework
Authors: García-Martín Juan Pablo , Torralba Antonio
Published: May 2021

With the development of the Internet of Things (IoT), Low Data Rate-Personal Area Networks (LR-WPAN) have been deployed for different applications. Now comes the need to integrate these networks in search of greater connectivity, performances, and geographic coverage. This integration is facilitated by the recent deployment of low power wide area networks (LPWAN) in the licensed bands, especially narrowband IoT (NB-IoT) and long-term evolution for machine-type communications (LTE-M), which are standardized technologies that will continue evolving as part of the fifth generation (5G) specifications. This paper proposes a design methodology for combined networks using LR-WPAN and LPWAN technologies. These networks are combined at the device level using a cluster-tree topology. An example is shown here, where an existing IEEE 802.15.4 network is combined with NB-IoT. To this end, new dual nodes are incorporated, acting as cluster heads. The paper discusses the different aspects of formation and operation of the combined network. A dynamic link selection (DLS) algorithm is also proposed, based on which cluster headers dynamically determine the preferred link, depending on link quality and type of traffic. Extensive simulations show that the DLS algorithm significantly increases battery life on dual nodes, which are the nodes with the highest power demands.
Robot-Assisted Autism Therapy (RAAT). Criteria and Types of Experiments Using Anthropomorphic and Zoomorphic Robots. Review of the Research
Authors: Szymona Barbara , Maciejewski Marcin , Karpiński Robert , Jonak Kamil , Radzikowska-Büchner Elżbieta , Niderla Konrad , Prokopiak Anna
Published: May 2021

Supporting the development of a child with autism is a multi-profile therapeutic work on disturbed areas, especially understanding and linguistic expression used in social communication and development of social contacts. Previous studies show that it is possible to perform some therapy using a robot. This article is a synthesis review of the literature on research with the use of robots in the therapy of children with the diagnosis of early childhood autism. The review includes scientific journals from 2005–2021. Using descriptors: ASD (Autism Spectrum Disorders), Social robots, and Robot-based interventions, an analysis of available research in PubMed, Scopus and Web of Science was done. The results showed that a robot seems to be a great tool that encourages contact and involvement in joint activities. The review of the literature indicates the potential value of the use of robots in the therapy of people with autism as a facilitator in social contacts. Robot-Assisted Autism Therapy (RAAT) can encourage child to talk or do exercises. In the second aspect (prompting during a conversation), a robot encourages eye contact and suggests possible answers, e.g., during free conversation with a peer. In the third aspect (teaching, entertainment), the robot could play with autistic children in games supporting the development of joint attention. These types of games stimulate the development of motor skills and orientation in the body schema. In future work, a validation test would be desirable to check whether children with ASD are able to do the same with a real person by learning distrust and cheating the robot.
A Driver’s Visual Attention Prediction Using Optical Flow
Authors: Kang Byeongkeun , Lee Yeejin
Published: May 2021

Motion in videos refers to the pattern of the apparent movement of objects, surfaces, and edges over image sequences caused by the relative movement between a camera and a scene. Motion, as well as scene appearance, are essential features to estimate a driver’s visual attention allocation in computer vision. However, the fact that motion can be a crucial factor in a driver’s attention estimation has not been thoroughly studied in the literature, although driver’s attention prediction models focusing on scene appearance have been well studied. Therefore, in this work, we investigate the usefulness of motion information in estimating a driver’s visual attention. To analyze the effectiveness of motion information, we develop a deep neural network framework that provides attention locations and attention levels using optical flow maps, which represent the movements of contents in videos. We validate the performance of the proposed motion-based prediction model by comparing it to the performance of the current state-of-art prediction models using RGB frames. The experimental results for a real-world dataset confirm our hypothesis that motion plays a role in prediction accuracy improvement, and there is a margin for accuracy improvement by using motion features.
Non-Parental Investment in Children and Child Outcomes after Parental Death or Divorce in a Patrilocal Society
Authors: Perry Gretchen
Published: May 2021

Children rely on support from parental helpers (alloparents), perhaps especially in high-needs contexts. Considerable evidence indicates that closer relatives and maternal relatives are the most likely to provide this care, as inclusive fitness theory suggests, but whether this is equally true across different family types and in culturally patrilocal societies requires investigation. This structured interview study (N = 208 respondents with 323 dependent children) focuses on who helps raise children in rural Bangladesh after the father’s or mother’s death, or divorce, in comparison to families with both parents present or the father temporarily a migrant laborer. Family types differed in where and with whom children resided, who served as their primary and secondary caregivers, and who provided material support, but mother’s kin played a major role, and were the primary providers of material resources from outside the child’s household in all family types. Despite the patrilineal ideology, only one-quarter of children of divorce lived with the father or his family, and even after the death of the mother, only 59% remained with father or other paternal kin. Household income varied by family type and was a strong predictor of child height and weight. The children of deceased mothers moved between successive caregivers especially frequently, and were uniquely likely to have no schooling. The typology of Bangladeshi society as patrilocal obscures the extent to which matrilateral family support children’s well-being.
Hungarian Stay-at-Home Fathers: A New Alternative for Family Wellbeing
Authors: Sztáray Kézdy Éva , Drjenovszky Zsófia
Published: May 2021

The two significant factors that influence subjective wellbeing are job and life satisfaction, so the work–life balance, that is, balancing between the two areas, is related to several wellbeing outcomes. This issue is of particular interest in those families, where, even if only temporarily, they have chosen the non-traditional sharing of roles, in which the father becomes the primary caregiver and the mother assumes the role of breadwinner. Very few Hungarian studies focus on families where the mother is the prime breadwinner and there has been no research specifically relating to stay-at-home father–working mother families. The qualitative gap filling research that we conducted was utilized to explore the relationship between achieving work-life balance and wellbeing in case of Hungarian stay-at-home father–working mother couples. A total of 31 families were examined through a semi-structured in-depth interview with the fathers and a short questionnaire with the mothers. All participants were white, heterosexual couples with one to four children. As a result of the analysis, four typical patterns in terms of the stay-at-home father and working mother family dynamics could be identified, including to what extent this non-traditional family format contributes to the father’s, mother’s, or both of their wellbeing.
A Comparison of Match Demands Using Ball-in-Play versus Whole Match Data in Professional Soccer Players of the English Championship
Authors: Mernagh Dylan , Weldon Anthony , Wass Josh , Phillips John , Parmar Nimai , Waldron Mark , Turner Anthony
Published: May 2021

This is the first study to report the whole match, ball-in-play (BiP), ball-out-of-play (BoP), and Max BiP (worst case scenario phases of play) demands of professional soccer players competing in the English Championship. Effective playing time per soccer game is typically <60 min. When the ball is out of play, players spend time repositioning themselves, which is likely less physically demanding. Consequently, reporting whole match demands may under-report the physical requirements of soccer players. Twenty professional soccer players, categorized by position (defenders, midfielders, and forwards), participated in this study. A repeated measures design was used to collect Global Positioning System (GPS) data over eight professional soccer matches in the English Championship. Data were divided into whole match and BiP data, and BiP data were further sub-divided into different time points (30–60 s, 60–90 s, and >90 s), providing peak match demands. Whole match demands recorded were compared to BiP and Max BiP, with BiP data excluding all match stoppages, providing a more precise analysis of match demands. Whole match metrics were significantly lower than BiP metrics (p < 0.05), and Max BiP for 30–60 s was significantly higher than periods between 60–90 s and >90 s. No significant differences were found between positions. BiP analysis allows for a more accurate representation of the game and physical demands imposed on professional soccer players. Through having a clearer understanding of maximum game demands in professional soccer, practitioners can design more specific training methods to better prepare players for worst case scenario passages of play.
Supply Chain Ambidexterity and Green SCM: Moderating Role of Network Capabilities
Authors: Khan Asif , Chen Chih-Cheng , Lu Kuan-Hua , Wibowo Ardy , Chen Shih-Chih , Ruangkanjanases Athapol
Published: May 2021

The purpose of this paper is to examine how supply chain ambidexterity facilitates assistance for green supply chain management and to build on previous work by evaluating how networking capability helps to explain the impact of supply chain ambidexterity on GSCM. This study focuses on the top-level management of different manufacturing companies located in Pakistan. A total of 34 manufacturing industries were selected using a cluster sampling technique. The data collected from 125 top-level managers were analyzed using a partial least square method, while the moderation analysis was conducted by using variance analysis. First, supply chain ambidexterity positively influences green supply chain management. However, networking capabilities do not moderate the relationship between supply chain ambidexterity and green supply chain management. This research was restricted to manufacturing industries in Pakistan because the research intended to gain an understanding of the several supply chain ambidexterity practices in Pakistani businesses and wanted to determine how these practices are associated with various parts of GSCM. Further studies can be extended to examine the impact in other industrial settings and countries. The findings of this research study will allow the managers to identify the right mix of exploitation and exploration techniques required to manage the supply chain in a green and sustainable manner.
Physiological and Biochemical Responses of Invasive Species Cenchrus pauciflorus Benth to Drought Stress
Authors: Zhou Liye , Tian Xun , Cui Beimi , Hussain Adil
Published: May 2021

The invasive plant Cenchrus pauciflorus Benth exhibits strong adaptability to stress, especially drought. When newly introduced certain plant species can become invasive and quickly spread in an area due to lack of competition, potentially disturbing the ecological balance and species diversity. C. pauciflorus has been known to cause huge economic losses to agriculture and animal husbandry. Thus, understanding the physiological responses of C. pauciflorus to drought stress could help explore the role of C. pauciflorus in population expansion in sandy land environments. In this study, we evaluated the response of C. pauciflorus to induced low, moderate, and severe drought stress conditions. Results showed a linear reduction in the fresh weight (FW), dry weight (DW), and relative water content (RWC) of the aboveground parts of C. pauciflorus following drought stress as compared to the control plants (no drought stress). Chemical analyses showed that the drought treatments significantly induced the production of proline, soluble proteins, soluble sugars, MDA, and free amino acids as compared to the control treatment (no drought stress). On the other hand, the starch content was significantly reduced in drought-treated plants. This was also accompanied by a significant linear increase in the antioxidant enzyme activities (SOD, POD, and CAT) in plants subjected to drought stress. On the basis of physiological and biochemical analyses, we propose that C. pauciflorus has evolved to survive harsh drought stress conditions of the desert via sophisticated biochemical adjustment and antioxidant reprograming that allows protection against damage caused by drought stress.