bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of Maternal Dietary Patterns during Gestation and Offspring Neurodevelopment
Authors: Lv Siyuan , Qin Rui , Jiang Yangqian , Lv Hong , Lu Qun , Tao Shiyao , Huang Lei , Liu Cong , Xu Xin , Wang Qingru , Li Mei , Li Zhi , Ding Ye , Song Ci , Jiang Tao , Ma Hongxia , Jin Guangfu , Xia Yankai , Wang Zhixu , Geng Shanshan , Du Jiangbo , Lin Yuan , Hu Zhibin
Published: February 2022

The health effects of diet are long term and persistent. Few cohort studies have investigated the influence of maternal dietary patterns during different gestational periods on offspring’s health outcomes. This study investigated the associations between maternal dietary patterns in the mid- and late-gestation and infant’s neurodevelopment at 1 year of age in the Jiangsu Birth Cohort (JBC) Study. A total of 1178 mother–child pairs were available for analysis. A semiquantitative food frequency questionnaire (FFQ) was used to investigate dietary intake at 22–26 and 30–34 gestational weeks (GWs). Neurodevelopment of children aged 1 year old was assessed using Bayley-Ⅲ Screening Test. Principal component analysis (PCA) and Poisson regression were used to extract dietary patterns and to investigate the association between dietary patterns and infant neurodevelopment. After adjusting for potential confounders, the maternal ‘Aquatic products, Fresh vegetables and Homonemeae’ pattern in the second trimester was associated with a lower risk of being non-competent in cognitive and gross motor development, respectively (cognition: aRR = 0.84; 95% CI 0.74–0.94; gross motor: aRR = 0.80; 95% CI 0.71–0.91), and the similar pattern, ‘Aquatic products and Homonemeae’, in the third trimester also showed significant association with decreased risk of failing age-appreciate cognitive and receptive communication development (cognition: aRR = 0.89; 95% CI 0.80–0.98; receptive communication: aRR = 0.91; 95% CI 0.84–0.99). Notably, adherence to the dietary pattern with relatively high aquatic and homonemeae products in both trimesters demonstrated remarkable protective effects on child neurodevelopment with the risk of being non-competent in cognitive and gross motor development decreasing by 59% (95% CI 0.21–0.79) and 63% (95% CI 0.18–0.77), respectively. Our findings suggested that adherence to the ‘Aquatic products and Homonemeae’ dietary pattern during pregnancy may have optimal effects on offspring’s neurodevelopment.
Integrative Metabolomic Characterization Reveals the Mediating Effect of Bifidobacterium breve on Amino Acid Metabolism in a Mouse Model of Alzheimer’s Disease
Authors: Zhu Guangsu , Guo Min , Zhao Jianxin , Zhang Hao , Wang Gang , Chen Wei
Published: February 2022

Alzheimer’s disease (AD) is commonly accompanied by global alterations in metabolic profiles, resulting in cognitive impairment and neuroinflammation in the brain. Using ultraperformance liquid chromatography-mass spectrometry, we performed integrative untargeted metabolomic analysis of metabolite alterations in the serum and hippocampal tissues of amyloid-β (Aβ)-injected AD model mice and sham controls. Multivariate analysis revealed that a Bifidobacterium breve CCFM1025 intervention significantly restored the differential metabolites induced by Aβ-injection, resulting in B. breve CCFM1025 serum and hippocampal metabolomes clustering between control and model mice. Furthermore, pathway and metabolite set enrichment analysis found that these altered metabolites were predominantly linked to amino acid metabolism. Overall, the integrative metabolome analysis indicated that B. breve CCFM1025 supplementation could modulate serum and hippocampal metabolomes in the early stage of AD, with amino acids as a potential driver.
Determinants of Adherence to the Mediterranean Diet in Spanish Children and Adolescents: The PASOS Study
Authors: Bibiloni Maria del Mar , Gallardo-Alfaro Laura , Gómez Santiago F. , Wärnberg Julia , Osés-Recalde Maddi , González-Gross Marcela , Gusi Narcís , Aznar Susana , Marín-Cascales Elena , González-Valeiro Miguel A. , Serra-Majem Lluís , Terrados Nicolás , Segu Marta , Lassale Camille , Homs Clara , Benavente-Marín Juan Carlos , Labayen Idoia , Zapico Augusto G. , Sánchez-Gómez Jesús , Jiménez-Zazo Fabio , Alcaraz Pedro E. , Sevilla-Sánchez Marta , Herrera-Ramos Estefanía , Pulgar Susana , Sistac Clara , Schröder Helmut , Bouzas Cristina , Tur Josep A.
Published: February 2022

A progressive shift away from traditional healthy dietary patterns, such as the Mediterranean diet (MedDiet), has been observed in recent decades. The aim of this study was to assess determinants of optimal adherence to the MedDiet in Spanish children and adolescents. A cross-sectional analysis was included in the PASOS nationwide representative study in Spain. Participants were 3607 children and adolescents; 8–16 years old. Primary and secondary outcome measures of weight and height were measured. Adherence to the MedDiet, physical activity, and sedentary behavior in children and adolescents, as well as parental physical activity and dietary habits, were assessed. Optimal adherence to the MedDiet was observed in 45.5% of primary school students and 34.8% of secondary school students (OR: 0.65; 95%CI: 0.56–0.75). Optimal adherence to the MedDiet was higher in children/adolescents meeting daily recommended moderate and vigorous physical activity (OR: 2.39, 95%CI: 1.97–2.89) and in those meeting daily recommended screen time on weekdays (OR: 2.05, 95%CI: 1.77–2.38) and weekends (OR: 1.76, 95%CI: 1.48–2.10). Participants with optimal adherence to the MedDiet were more likely to have mothers with a high-level education and high-tercile of SDQS, mothers who never smoked or were former smokers, and mothers who met the recommended physical activity and screen time. It can be concluded that a low prevalence of optimal adherence to the MedDiet was found among current Spanish children and adolescents. Optimal adherence to the MedDiet was associated with reaching the recommendations on physical activity and screen time, with the highest maternal educational level, and healthier maternal lifestyles.
Spatial and Temporal Circulation of Babesia caballi and Theileria equi in France Based on Seven Years of Serological Data
Authors: Nadal Clémence , Marsot Maud , Le Metayer Gaël , Boireau Pascal , Guillot Jacques , Bonnet Sarah I.
Published: February 2022

Caused by two blood parasites, Babesia caballi and Theileria equi, equine piroplasmosis is a tick-borne disease that poses major health and economic issues for the equine industry. Our objective was to gain insight into the spatio-temporal variations of parasite circulation in France, where the disease is known to be enzootic, but has been the subject of few studies. Seroprevalence was assessed for each parasite thanks to 16,127 equine sera obtained between 1997 and 2003 from all over France and analysed through complement fixation tests. Results indicated that 13.2% (5–27% depending on the region) of horses were seropositive for T. equi and 9.5% (3–25%) for B. caballi. Regardless of the year, horses from the southern regions of France were the most affected by B. caballi or T. equi infection, while the proportion of horses having antibodies against T. equi increased over time. These results highlight the heterogeneity of the circulation of both piroplasms, which may be linked with ecological diversity and vector distribution. Our data provide baseline information regarding the sero-epidemiology of B. caballi and T. equi infection in horses in France, making it now possible to select regions for future studies on risk factors, and design and implement effective targeted measures against equine piroplasms.
Plant GDSL Esterases/Lipases: Evolutionary, Physiological and Molecular Functions in Plant Development
Authors: Shen Gaodian , Sun Wenli , Chen Zican , Shi Lei , Hong Jun , Shi Jianxin
Published: February 2022

GDSL esterases/lipases (GELPs), present throughout all living organisms, have been a very attractive research subject in plant science due mainly to constantly emerging properties and functions in plant growth and development under both normal and stressful conditions. This review summarizes the advances in research on plant GELPs in several model plants and crops, including Arabidopsis, rice, maize and tomato, while focusing on the roles of GELPs in regulating plant development and plant–environment interactions. In addition, the possible regulatory network and mechanisms of GELPs have been discussed.
Identification of Peanut Aux/IAA Genes and Functional Prediction during Seed Development and Maturation
Authors: Zhang Xiurong , Zhang Kun , Luo Lu , Lv Yuying , Li Yuying , Zhu Suqing , Luo Bing , Wan Yongshan , Zhang Xiansheng , Liu Fengzhen
Published: February 2022

Auxin-responsive genes AUX/IAA are important during plant growth and development, but there are few relevant reports in peanut. In this study, 44 AhIAA genes were identified from cultivated peanut, of which 31 genes were expressed in seed at varying degrees. AhIAA-3A, AhIAA-16A and AhIAA-15B were up-regulated, while AhIAA-11A, AhIAA-5B and AhIAA-14B were down-regulated with seed development and maturation. The expression patterns of seven genes, AhIAA-1A, AhIAA-4A, AhIAA-10A, AhIAA-20A, AhIAA-1B, AhIAA-4B and AhIAA-19B, were consistent with the change trend of auxin, and expression in late-maturing variety LM was significantly higher than that in early-maturing EM. Furthermore, allelic polymorphism analysis of AhIAA-1A and AhIAA-1B, which were specifically expressed in seeds, showed that three SNP loci in 3′UTR of AhIAA-1A could effectively distinguish the EM- and LM- type germplasm, providing a basis for breeding markers development. Our results offered a comprehensive understanding of Aux/IAA genes in peanut and provided valuable clues for further investigation of the auxin signal transduction pathway and auxin regulation mechanism in peanut.
Improving Seed Germination by Cold Atmospheric Plasma
Authors: Yan Dayun , Lin Li , Zvansky Michelle , Kohanzadeh Leat , Taban Shannon , Chriqui Sabrina , Keidar Michael
Published: February 2022

Cold atmospheric plasma (CAP) is a tunable source of reactive species and other physical factors. It exerts luxuriant biochemical effects on diverse cells, including bacterial cells, mammalian cells, and plant cells. Over the past decade, CAP has shown promising application in modern agriculture. Here, we focused on the state of the art of plasma agriculture, particularly the improvement of seed germination rates. Typical plasma sources, underlying physical principles, and the chemical and cellular mechanism of plasma’s effect on plants seeds have been discussed in depth.
A Brief Overview of Polymers Science and Technology, in Spain
Authors: Mijangos Carmen
Published: February 2022

This Special Issue State-of-the-Art on Polymer Science and Technology in Spain is comprised of a collection of 42 publications/contributions related to very different topics undertaken by the numerous research groups working in Spain in Polymer Science and Technology. This monograph collects the contributions of more than 200 different authors from 24 different national Institutions (>30 different centers/departments) from Universities and CSIC centers distributed throughout the whole of Spain. Two-thirds of the contributions to this Special Issue arise from Institutional collaborations, half of which are international collaborations with European research groups and the other half with other international research groups outside Europe including China, Australia or United States of America among others. This brief overview communication provides a general overview of the research lines in Polymer Science and Technology covered in Spain and show most of the representative polymer groups and their distribution throughout Spain. Most of Spanish polymer groups belong to the Grupo Especializado de Polímeros (GEP) being part of the European Polymer Federation (EPF). It also shows how Spanish science about polymers is positioned at European level.
Stochastic Optimization Operation of the Integrated Energy System Based on a Novel Scenario Generation Method
Authors: Zhang Delong , Jiang Siyu , Liu Jinxin , Wang Longze , Chen Yongcong , Xiao Yuxin , Jiao Shucen , Xie Yu , Zhang Yan , Li Meicheng
Published: February 2022

The application of integrated energy systems is significant for realizing the comprehensive utilization of various energy sources and improving the utilization rate of renewable energy. At present, the optimal operation of integrated energy systems is a research hotspot. However, shortcomings remain in the stochastic optimization operation and the scenario generation method. This paper proposes a stochastic optimization operation model of an integrated energy microgrid based on an advanced multi-scenario generation method. First, this paper establishes the time-divided probability distribution model of the forecasting error of the uncertain factors, such as photovoltaic (PV) power and load, which provide the basis for generating scenarios. Moreover, the covariance matrix is used to calculate the time correlation of the time-divided probabilistic distributed models, and the parameters of the covariance matrix are optimized. Second, based on multiple typical scenarios, the stochastic optimization operation model of the integrated energy microgrid is established. Finally, the real data is used to verify the proposed method. The results show that the nonparametric kernel density estimation method has the best fitting effect. On this basis, the time correlation and the operation costs are compared with the scenario sets generated by other methods, which proves the advantages of the proposed multi-scenario generation method and stochastic optimization operation model.
Recent Advances on Waste Plastic Thermal Pyrolysis: A Critical Overview
Authors: Yansaneh Osman Y. , Zein Sharif H.
Published: February 2022

Post-consumer plastic management, otherwise termed waste plastic (WP) management, is a great challenge in today’s world, mainly because of its characteristic biodegradation properties. The quantity of waste plastics correspondingly increases with the increase in demand for plastic use. Research has shown that this demand increases yearly. Most of these waste plastics include high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyethylene terephthalate (PET) and polystyrene (PS). Potentially, these wastes are a wealth, and studies have explored that pyrolysis is a reputable mechanism to accomplish this. In this critical review, an extensive investigation on waste plastics thermal pyrolysis (WPTP) is carried out. The factors that affect the product’s yield and selectivity are discussed, and a comparative quality guarantee of WPTP is examined. This paper presents an assurance into the current findings of WPTP and reveals some common gaps and misconceptions surrounding this field, which are recommendable towards the support of further research work. The significant role of co-pyrolysis of plastics with biomass in this field is also emphasised, and a glimpse into the influence of mixed waste plastics in pyrolysis is presented.
Obtaining DHA–EPA Oil Concentrates from the Biomass of Microalga Chlorella sorokiniana
Authors: Toumi Amira , Politaeva Natalia , Đurović Saša , Mukhametova Liliya , Ilyashenko Svetlana
Published: February 2022

Microalgae have attracted growing interest all around the world due to their potential applications in multiple sectors of industry, such as energetics, nutraceuticals, pharmaceuticals, agriculture, and ecology. Concepts of biorefinery of microalgae lipids for biodiesel production coupled with other applications have been suggested in several studies. However, very few studies focus on overcoming the degree of unsaturation of microalgae lipids using methods of fractionation. This study presents a method for obtaining two oil fractions from microalgae Chlorella sorokiniana suitable for food and biofuels via urea complex formation with further production of a long-chain PUFA concentrated oil suitable for the nutraceutical industry. A DHA–EPA-rich fraction was obtained from the dry microalga biomass using a succession of extraction, urea-complexation, fractionation, and esterification with glycerol. Analytical and organoleptic methods were used to assess the quality of the final product. Results show that the urea-complexation method allowed the obtaining of two lipid fractions with different fatty acid profiles. The urea complexed fraction (UCF) contained a majority of saturated fatty acids (54.46%); thus, it could find applications in the biofuels or food industry. The non-urea complexed fraction (NUCF) was rich in polyunsaturated fatty acids (PUFA) (81.00%), especially long-chain PUFA with 16.52% EPA and 35.08% DHA. The recovery rates of EPA and DHA in the NUCF reached 59% and 87.14%, respectively. Finally, the physicochemical and organoleptic characteristics of the DHA–EPA oil concentrate were determined and found conform to the norms recommended by the WHO/FAO standards for edible oils and the Russian State Standard GOST 1129-2013.
Comparing Methods to Extract Crop Height and Estimate Crop Coefficient from UAV Imagery Using Structure from Motion
Authors: Malachy Nitzan , Zadak Imri , Rozenstein Offer
Published: February 2022

Although it is common to consider crop height in agricultural management, variation in plant height within the field is seldom addressed because it is challenging to assess from discrete field measurements. However, creating spatial crop height models (CHMs) using structure from motion (SfM) applied to unmanned aerial vehicle (UAV) imagery can easily be done. Therefore, looking into intra- and inter-season height variability has the potential to provide regular information for precision management. This study aimed to test different approaches to deriving crop height from CHM and subsequently estimate the crop coefficient (Kc). CHMs were created for three crops (tomato, potato, and cotton) during five growing seasons, in addition to manual height measurements. The Kc time-series were derived from eddy-covariance measurements in commercial fields and estimated from multispectral UAV imagery in small plots, based on known relationships between Kc and spectral vegetation indices. A comparison of four methods (Mean, Sample, Median, and Peak) was performed to derive single height values from CHMs. Linear regression was performed between crop height estimations from CHMs against manual height measurements and Kc. Height was best predicted using the Mean and the Sample methods for all three crops (R2 = 0.94, 0.84, 0.74 and RMSE = 0.056, 0.071, 0.051 for cotton, potato, and tomato, respectively), as was the prediction of Kc (R2 = 0.98, 0.84, 0.8 and RMSE = 0.026, 0.049, 0.023 for cotton, potato, and tomato, respectively). The Median and Peak methods had far less success in predicting both, and the Peak method was shown to be sensitive to the size of the area analyzed. This study shows that CHMs can help growers identify spatial heterogeneity in crop height and estimate the crop coefficient for precision irrigation applications.
Impact of Road Marking Retroreflectivity on Machine Vision in Dry Conditions: On-Road Test
Authors: Babić Darko , Babić Dario , Fiolić Mario , Eichberger Arno , Magosi Zoltan Ferenc
Published: February 2022

(1) Background: Due to its high safety potential, one of the most common ADAS technologies is the lane support system (LSS). The main purpose of LSS is to prevent road accidents caused by road departure or entrance in the lane of other vehicles. Such accidents are especially common on rural roads during nighttime. In order for LSS to function properly, road markings should be properly maintained and have an adequate level of visibility. During nighttime, the visibility of road markings is determined by their retroreflectivity. The aim of this study is to investigate how road markings’ retroreflectivity influences the detection quality and the view range of LSS. (2) Methods: An on-road investigation comprising measurements using Mobileye and a dynamic retroreflectometer was conducted on four rural roads in Croatia. (3) Results: The results show that, with the increase of markings’ retroreflection, the detection quality and the range of view of Mobileye increase. Additionally, it was determined that in “ideal” conditions, the minimal value of retroreflection for a minimum level 2 detection should be above 55 mcd/lx/m2 and 88 mcd/lx/m2 for the best detection quality (level 3). The results of this study are valuable to researchers, road authorities and policymakers.
Thermal Conductivity Gas Sensor with Enhanced Flow-Rate Independence
Authors: Wang Jiayu , Liu Yanxiang , Zhou Hong , Wang Yi , Wu Ming , Huang Gang , Li Tie
Published: February 2022

In this article, novel thermal gas sensors with newly designed diffusion gas channels are proposed to reduce the flow-rate disturbance. Simulation studies suggest that by lowering the gas flow velocity near the hot film, the maximum normalized temperature changes caused by flow-rate variations in the two new designs (Type-H and Type-U) are decreased to only 1.22% and 0.02%, which is much smaller than in the traditional straight design (Type-I) of 20.16%. Experiment results are in agreement with the simulations that the maximum normalized flow-rate interferences in Type-H and Type-U are only 1.51% and 1.65%, compared to 24.91% in Type-I. As the introduced CO2 flow varied from 1 to 20 sccm, the normalized output deviations in Type-H and Type-U are 0.38% and 0.02%, respectively, which are 2 and 3 orders of magnitude lower than in Type-I of 10.20%. In addition, the recovery time is almost the same in all these sensors. These results indicate that the principle of decreasing the flow velocity near the hot film caused by the two novel diffusion designs can enhance the flow-rate independence and improve the accuracy of the thermal conductivity as well as the gas detection.
Near-Infrared Sensors for Onsite and Noninvasive Quantification of Macronutrients in Breast Milk
Authors: Melendreras Candela , Forcada Sergio , Fernández-Sánchez María Luisa , Fernández-Colomer Belén , Costa-Fernández José M. , López Alberto , Ferrero Francisco , Soldado Ana
Published: February 2022

Breast milk is an optimal food that covers all the nutritional needs of the newborn. It is a dynamic fluid whose composition varies with lactation period. The neonatal units of hospitals have human milk banks, a service that analyzes, stores, and distributes donated human milk. This milk is used to feed premature infants (born before 32 weeks of gestation or weighing less than 1500 g) whose mothers, for some reason, cannot feed them with their own milk. Here, we aimed to develop near-infrared spectroscopy (NIRS) measures for the analysis of breast milk. For this purpose, we used a portable NIRS instrument scanning in the range of 1396–2396 nm to collect the spectra of milk samples. Then, different chemometrics were calculated to develop 18 calibration models with and without using derivatives and the standard normal variate. Once the calibration models were developed, the best treatments were selected according to the correlation coefficients (r2) and prediction errors (SECVs). The best results for the assayed macronutrients were obtained when no pre-treatment was applied to the NIR spectra of fat (r2 = 0.841, SECV = 0.51), raw protein (r2 = 0.512, SECV = 0.21), and carbohydrates (r2 = 0.741, SECV = 1.35). SNV plus the first derivative was applied to obtain satisfactory results for energy (r2 = 0.830, SECV = 9.60) quantification. The interpretation of the obtained results showed the richness of the NIRS spectra; moreover, the presence of specific bands for fat provided excellent statistics in quantitative models. These results demonstrated the ability of portable NIRS sensors in a methodology developed for the quality control of macronutrients in breast milk.
A Multi-User Collaborative AR System for Industrial Applications
Authors: Wang Junyi , Qi Yue
Published: February 2022

Augmented reality (AR) applications are increasingly being used in various fields (e.g., design, maintenance, assembly, repair, training, etc.), as AR techniques help improve efficiency and reduce costs. Moreover, collaborative AR systems extend applicability, allowing for collaborative environments for different roles. In this paper, we propose a multi-user collaborative AR system (aptly called the “multi-user collaborative system”, or MUCSys); it is composed of three ends—MUCStudio, MUCView, and MUCServer. MUCStudio aims to construct industrial content with CAD model transformation, simplification, database update, marker design, scene editing, and exportation, while MUCView contains sensor data analysis, real-time localization, scene loading, annotation editing, and virtual–real rendering. MUCServer—as the bridge between MUCStudio and MUCView—presents collaborative and database services. To achieve this, we implemented the algorithms of local map establishment, global map registration, optimization, and network synchronization. The system provides AR services for diverse industrial processes via three collaborative ways—remote support, collaborative annotation, and editing. According to the system, applications for cutting machines were presented to improve efficiency and reduce costs, covering cutting head designs, production line sales, and cutting machine inspections. Finally, a user study was performed to prove the usage experience of the system.
User-Independent Hand Gesture Recognition Classification Models Using Sensor Fusion
Authors: Colli Alfaro Jose Guillermo , Trejos Ana Luisa
Published: February 2022

Recently, it has been proven that targeting motor impairments as early as possible while using wearable mechatronic devices for assisted therapy can improve rehabilitation outcomes. However, despite the advanced progress on control methods for wearable mechatronic devices, the need for a more natural interface that allows for better control remains. To address this issue, electromyography (EMG)-based gesture recognition systems have been studied as a potential solution for human–machine interface applications. Recent studies have focused on developing user-independent gesture recognition interfaces to reduce calibration times for new users. Unfortunately, given the stochastic nature of EMG signals, the performance of these interfaces is negatively impacted. To address this issue, this work presents a user-independent gesture classification method based on a sensor fusion technique that combines EMG data and inertial measurement unit (IMU) data. The Myo Armband was used to measure muscle activity and motion data from healthy subjects. Participants were asked to perform seven types of gestures in four different arm positions while using the Myo on their dominant limb. Data obtained from 22 participants were used to classify the gestures using three different classification methods. Overall, average classification accuracies in the range of 67.5–84.6% were obtained, with the Adaptive Least-Squares Support Vector Machine model obtaining accuracies as high as 92.9%. These results suggest that by using the proposed sensor fusion approach, it is possible to achieve a more natural interface that allows better control of wearable mechatronic devices during robot assisted therapies.
Ageing Safely in the Digital Era: A New Unobtrusive Activity Monitoring Framework Leveraging on Daily Interactions with Hand-Operated Appliances
Authors: Bousbiat Hafsa , Leitner Gerhard , Elmenreich Wilfried
Published: February 2022

Supporting the elderly to maintain their independence, safety, and well-being through Active Assisted Living (AAL) technologies, is gaining increasing momentum. Recently, Non-intrusive Load Monitoring (NILM) approaches have become the focus of these technologies due to their non-intrusiveness and reduced price. Whilst some research has been carried out in this respect; it still is challenging to design systems considering the heterogeneity and complexity of daily routines. Furthermore, scholars gave little attention to evaluating recent deep NILM models in AAL applications. We suggest a new interactive framework for activity monitoring based on custom user-profiles and deep NILM models to address these gaps. During evaluation, we consider four different deep NILM models. The proposed contribution is further assessed on two households from the REFIT dataset for a period of one year, including the influence of NILM on activity monitoring. To the best of our knowledge, the current study is the first to quantify the error propagated by a NILM model on the performance of an AAL solution. The results achieved are promising, particularly when considering the UNET-NILM model, a multi-task convolutional neural network for load disaggregation, that revealed a deterioration of only 10% in the f1-measure of the framework’s overall performance.
Hands-Free Authentication for Virtual Assistants with Trusted IoT Device and Machine Learning
Authors: Hayashi Victor Takashi , Ruggiero Wilson Vicente
Published: February 2022

Virtual assistants, deployed on smartphone and smart speaker devices, enable hands-free financial transactions by voice commands. Even though these voice transactions are frictionless for end users, they are susceptible to typical attacks to authentication protocols (e.g., replay). Using traditional knowledge-based or possession-based authentication with additional invasive interactions raises users concerns regarding security and usefulness. State-of-the-art schemes for trusted devices with physical unclonable functions (PUF) have complex enrollment processes. We propose a scheme based on a challenge response protocol with a trusted Internet of Things (IoT) autonomous device for hands-free scenarios (i.e., with no additional user interaction), integrated with smart home behavior for continuous authentication. The protocol was validated with automatic formal security analysis. A proof of concept with websockets presented an average response time of 383 ms for mutual authentication using a 6-message protocol with a simple enrollment process. We performed hands-free activity recognition of a specific user, based on smart home testbed data from a 2-month period, obtaining an accuracy of 97% and a recall of 81%. Given the data minimization privacy principle, we could reduce the total number of smart home events time series from 7 to 5. When compared with existing invasive solutions, our non-invasive mechanism contributes to the efforts to enhance the usability of financial institutions’ virtual assistants, while maintaining security and privacy.
Simultaneous ThermoBrachytherapy: Electromagnetic Simulation Methods for Fast and Accurate Adaptive Treatment Planning
Authors: Androulakis Ioannis , Mestrom Rob M. C. , Christianen Miranda E. M. C. , Kolkman-Deurloo Inger-Karine K. , van Rhoon Gerard C.
Published: February 2022

The combination of interstitial hyperthermia treatment (IHT) with high dose rate brachytherapy (HDR-BT) can improve clinical outcomes since it highly enhances the efficiency of cell kill, especially when applied simultaneously. Therefore, we have developed the ThermoBrachy applicators. To effectively apply optimal targeted IHT, treatment planning is considered essential. However, treatment planning in IHT is rarely applied as it is regarded as difficult to accurately calculate the deposited energy in the tissue in a short enough time for clinical practice. In this study, we investigated various time-efficient methods for fast computation of the electromagnetic (EM) energy deposition resulting from the ThermoBrachy applicators. Initially, we investigated the use of an electro-quasistatic solver. Next, we extended our investigation to the application of geometric simplifications. Furthermore, we investigated the validity of the superpositioning principle, which can enable adaptive treatment plan optimization without the need for continuous recomputation of the EM field. Finally, we evaluated the accuracy of the methods by comparing them to the golden standard Finite-Difference Time-Domain calculation method using gamma-index analysis. The simplifications considerably reduced the computation time needed, improving from >12 h to a few seconds. All investigated methods showed excellent agreement with the golden standard by showing a >99% passing rate with 1%/0.5 mm Dose Difference and Distance-to-Agreement criteria. These results allow the proposed electromagnetic simulation method to be used for fast and accurate adaptive treatment planning.
Individualization of Pinus radiata Canopy from 3D UAV Dense Point Clouds Using Color Vegetation Indices
Authors: Cabrera-Ariza Antonio M. , Lara-Gómez Miguel A. , Santelices-Moya Rómulo E. , Meroño de Larriva Jose-Emilio , Mesas-Carrascosa Francisco-Javier
Published: February 2022

The location of trees and the individualization of their canopies are important parameters to estimate diameter, height, and biomass, among other variables. The very high spatial resolution of UAV imagery supports these processes. A dense 3D point cloud is generated from RGB UAV images, which is used to obtain a digital elevation model (DEM). From this DEM, a canopy height model (CHM) is derived for individual tree identification. Although the results are satisfactory, the quality of this detection is reduced if the working area has a high density of vegetation. The objective of this study was to evaluate the use of color vegetation indices (CVI) in canopy individualization processes of Pinus radiata. UAV flights were carried out, and a 3D dense point cloud and an orthomosaic were obtained. Then, a CVI was applied to 3D point cloud to differentiate between vegetation and nonvegetation classes to obtain a DEM and a CHM. Subsequently, an automatic crown identification procedure was applied to the CHM. The results were evaluated by contrasting them with results of manual individual tree identification on the UAV orthomosaic and those obtained by applying a progressive triangulated irregular network to the 3D point cloud. The results obtained indicate that the color information of 3D point clouds is an alternative to support individualizing trees under conditions of high-density vegetation.
A Review on Magnetic Induction Spectroscopy Potential for Fetal Acidosis Examination
Authors: Abdul Halim Siti Fatimah , Zakaria Zulkarnay , Pusppanathan Jaysuman , Mohd Noor Anas , Norali Ahmad Nasrul , Fazalul Rahiman Mohd Hafiz , Mohd Muji Siti Zarina , Abdul Rahim Ruzairi , Engku-Husna Engku Ismail , Ali Hassan Muhamad Khairul , Aziz Safar Muhammad Juhairi , Salleh Ahmad Faizal , Mat Som Mohd Hanafi
Published: February 2022

Fetal acidosis is one of the main concerns during labor. Currently, fetal blood sampling (FBS) has become the most accurate measurement of acidosis detection. However, it is invasive and does not provide a real time measurement due to laboratory procedures. Delays in diagnosis of acidosis have caused serious injury to the fetus, especially for the brain and the heart. This paper reviews the new technique in diagnosis of acidosis non-invasively. Magnetic Induction Spectroscopy (MIS) has been proposed to be a new device for acidosis detection in recent years. This paper explains the basic principle of MIS and outlines the design specifications and design considerations for a MIS pH probe. It is expected that readers will gain a basic understanding of the development of a MIS pH probe from this review.
Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals
Authors: Chalumuri Yekanth Ram , Kimball Jacob P. , Mousavi Azin , Zia Jonathan S. , Rolfes Christopher , Parreira Jesse D. , Inan Omer T. , Hahn Jin-Oh
Published: February 2022

This paper presents a novel computational algorithm to estimate blood volume decompensation state based on machine learning (ML) analysis of multi-modal wearable-compatible physiological signals. To the best of our knowledge, our algorithm may be the first of its kind which can not only discriminate normovolemia from hypovolemia but also classify hypovolemia into absolute hypovolemia and relative hypovolemia. We realized our blood volume classification algorithm by (i) extracting a multitude of features from multi-modal physiological signals including the electrocardiogram (ECG), the seismocardiogram (SCG), the ballistocardiogram (BCG), and the photoplethysmogram (PPG), (ii) constructing two ML classifiers using the features, one to classify normovolemia vs. hypovolemia and the other to classify hypovolemia into absolute hypovolemia and relative hypovolemia, and (iii) sequentially integrating the two to enable multi-class classification (normovolemia, absolute hypovolemia, and relative hypovolemia). We developed the blood volume decompensation state classification algorithm using the experimental data collected from six animals undergoing normovolemia, relative hypovolemia, and absolute hypovolemia challenges. Leave-one-subject-out analysis showed that our classification algorithm achieved an F1 score and accuracy of (i) 0.93 and 0.89 in classifying normovolemia vs. hypovolemia, (ii) 0.88 and 0.89 in classifying hypovolemia into absolute hypovolemia and relative hypovolemia, and (iii) 0.77 and 0.81 in classifying the overall blood volume decompensation state. The analysis of the features embedded in the ML classifiers indicated that many features are physiologically plausible, and that multi-modal SCG-BCG fusion may play an important role in achieving good blood volume classification efficacy. Our work may complement existing computational algorithms to estimate blood volume compensatory reserve as a potential decision-support tool to provide guidance on context-sensitive hypovolemia therapeutic strategy.
MEMS Underwater Directional Acoustic Sensor in Near Neutral Buoyancy Configuration
Authors: Alves Fabio , Park Jaehyun , McCarty Leland , Rabelo Renato , Karunasiri Gamani
Published: February 2022

A MEMS directional acoustic sensor housed in an air cavity and operated underwater in a near-neutral buoyancy configuration is demonstrated. The sensor consists of two wings connected by a bridge and attached to a substrate by two centrally mounted torsional legs. The frequency response showed two resonant peaks corresponding to a rocking mode (wings moving in opposite directions) and a bending mode (wings moving in the same direction). Initial tests of the sensor using a shaker table showed that the response is highly dependent on the vibration direction. In air, the sensor showed a maximum sensitivity of about 95 mV/Pa with a cosine directional response. Underwater, the maximum sensitivity was about 37 mV/Pa with a similar cosine directional response. The measured maximum SNR was about 38 dB for a signal generated by a sound stimulus of 1 Pa when the sensor is operated near the bending resonance. The results indicate that this type of MEMS sensor can be operated in a near-neutral buoyant configuration and achieve a good directional response.
Acknowledgment to Reviewers of Societies in 2021
Authors:   Societies Editorial Office
Published: February 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Black, Female, and Divorced: A Discourse Analysis of Wangarĩ Maathai’s Leadership with Reflections from Naleli Morojele‘s Study of Rwandan and South African Female Political Leaders
Authors: Stuhlhofer Eunice Wangui
Published: February 2022

Marriage and divorce are factors that impact female leadership in Africa. Women are defined by their roles as wives and mothers and less as leaders. There is a dearth of research on the influence of marriage and divorce on female leadership in Africa. Most studies have focused on the societal importance of marriage and the negative effects of divorce on families. Using Wangarĩ Maathai’s biography Unbowed, this paper explores the role of marriage and divorce and their intersection with Maathai’s leadership. To enrich the analysis, I introduce insights from Naleli Morojele’s study of Rwandan and South African female political leaders. African feminist thought, transformative leadership theory, and African concepts of marriage and divorce form the theoretical framework. The main findings indicate that Maathai’s leadership is transformative. African feminism recognizes the role of men in women’s equality. Female leadership has increased in Africa, though it contends with socio-cultural attitudes and colonial legacies that fuel its skepticism. Marriage is a duty and the focus of existence in African thought and divorce is synonymous with failure. Women’s disunity on gender issues is problematic. Female leadership is very demanding and costly to family relationships. These findings are important in identifying gaps between policy and social attitudes on female leadership in Africa.
Big Data: The Engine to Future Cities—A Reflective Case Study in Urban Transport
Authors: Pettit Christopher James , Zarpelon Leao Simone , Lock Oliver , Ng Matthew , Reades Jonathan
Published: February 2022

In an era of smart cities, artificial intelligence and machine learning, data is purported to be the ‘new oil’, fuelling increasingly complex analytics and assisting us to craft and invent future cities. This paper outlines the role of what we know today as big data in understanding the city and includes a summary of its evolution. Through a critical reflective case study approach, the research examines the application of urban transport big data for informing planning of the city of Sydney. Specifically, transport smart card data, with its diverse constraints, was used to understand mobility patterns through the lens of the 30 min city concept. The paper concludes by offering reflections on the opportunities and challenges of big data and the promise it holds in supporting data-driven approaches to planning future cities.
What Shapes Activity Preferences? The Role of Tourist Personality, Destination Personality and Destination Image: Evidence from Serbia
Authors: Kovačić Sanja , Jovanović Tamara , Vujičić Miroslav D. , Morrison Alastair M. , Kennell James
Published: February 2022

Understanding activity preferences and their antecedents is essential for creating personalized tourism offers and effective destination marketing, vital components of a sustainable tourism destination. Previous studies have provided insights into tourist behavior and activity choices, but without research on activity preferences and their relationship with perceptions of destinations. The literature still lacks an integrative model exploring the antecedents of activity preferences, including tourist characteristics, destination personality, and destination image, and explaining the nature of the relationships between them. This research proposes and tests a structural model of individual characteristics, destination image, destination personality, and activity preferences. A survey was conducted on a sample of 502 visitors to The Trail of Roman Emperors in Serbia. The results confirmed the influence of personality (extraversion, agreeableness, conscientiousness, and openness) and destination personality (sincerity and ruggedness) on activity preferences. Additionally, the model revealed the significant influence of individual characteristics on perceptions of destination personality and image. Managerial implications were given in light of the importance of this research for destination branding that will support long-term destination sustainability.
Current Status and Review of Waste-to-Biogas Conversion for Selected European Countries and Worldwide
Authors: Zupančič Matevž , Možic Valerija , Može Matic , Cimerman Franc , Golobič Iztok
Published: February 2022

Growing world population and increasing population density are leading to increasing waste production with biological waste amounting to several billion tonnes annually. Together with the increasing need for renewable energy sources, waste-to-biogas conversion as a prime example of waste-to-energy technology represents a facile way of solving two problems simultaneously. This review aims to address the recent progress in the field of waste-to-biogas technology, which is lately facing intensive research and development, and present the current status of this waste treatment method both in technological and legislative terms. The first part provides an overview of waste and waste management issues. This is followed by a detailed description of applicable waste-to-energy (WtE) technologies and their current implementation in selected European countries. Moreover, national energy and climate plans (NECPs) of selected EU Member States are reviewed and compared with a focus on implementation of WtE technologies. In a further section, biogas production from waste around the world is reviewed and compared country wise. Finally, an outlook into the future of WtE technologies is provided alongside the conclusions based upon the reviewed data.
Drivers of Sustainable Apparel Purchase Intention: An Empirical Study of Malaysian Millennial Consumers
Authors: Hasbullah Nornajihah Nadia , Sulaiman Zuraidah , Mas’od Adaviah , Ahmad Sugiran Hanis Syuhada
Published: February 2022

The fashion industry has expanded at the expense of the environment. Consumption and environmental pollution both serve as a wake-up call to the global endeavour to adopt more socially and environmentally responsible behaviours. It implies, in particular, a paradigm shift in consumer behaviour away from conventional to green products. Understanding the factors that influence consumer purchasing decisions is critical in developing the demand for and commitment to sustainable apparel consumption. In support of the United Nation’s efforts to promote sustainable consumption in Malaysia, a study was conducted to determine the motivating factors that influence consumers’ purchase intentions for sustainable apparel. The moderating effect of fashion consciousness on the outcome was also examined. An extended model of the Motivation-Opportunity-Ability (MOA) Theory and Self-Determination Theory (SDT) was developed and tested using 324 responses collected from the Malaysian millennial generation in six major urban locations. The results of the structural equation modelling analysis indicated that the elements of motivation, opportunity, and ability were all positively linked with the sustainable apparel purchase intention. Fashion consciousness had a moderating effect on the relationships between the three drivers (motivation, opportunity, and ability) and purchase intention. The research findings provide valuable insights for businesses to formulate a sustainable and unified business model that incorporates environmental, social, and consumer considerations into core business practices. These insights would also help designers to advance the development of sustainable products as an area of innovation and support policymakers in achieving the UN’s 17 Sustainable Development Goals (SDGs).
Investors’ Moral and Financial Concerns—Ethical and Financial Divestment in the Fossil Fuel Industry
Authors: Zhang Yiping , Weber Olaf
Published: February 2022

It is discussed intensively whether divestment decease sales in the fossil fuel industry or whether investors divest from the fossil fuel industry because of stranded assets. Furthermore, it is unclear what the consequences of these activities are for the fossil fuel industry. Therefore, the study explores the direction of causality between cash flow factors, such as production factors and sources of financing and sales of the fossil fuel industry using lagged regression models and applying the Granger causality test. Our sample consists of fossil fuel companies from the Carbon Underground 200 list. Because R-squared values for both lagged financial factors and lagged sales were similar, we suggest a “bi-directional causality” between the financial flow factors and sales. We conclude that divestment (because of ethical concerns) can cause lower sales and that lower sales can cause divestment because of fear of the risk of stranded assets. Because a third factor usually causes bi-directional causations, we conclude that the need for the fossil fuel industry to reduce greenhouse gas emissions is the third factor that influences both the ethical and financial motivation of divestment. Consequently, the study contributes to theoretical approaches to divestment.