bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Invasive Identification of Nutrient Components in Grain
Authors: Farber Charles , Islam A. S. M. Faridul , Septiningsih Endang M. , Thomson Michael J. , Kurouski Dmitry
Published: May 2021

Digital farming is a modern agricultural concept that aims to maximize the crop yield while simultaneously minimizing the environmental impact of farming. Successful implementation of digital farming requires development of sensors to detect and identify diseases and abiotic stresses in plants, as well as to probe the nutrient content of seeds and identify plant varieties. Experimental evidence of the suitability of Raman spectroscopy (RS) for confirmatory diagnostics of plant diseases was previously provided by our team and other research groups. In this study, we investigate the potential use of RS as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of nutrient components in the grains from 15 different rice genotypes. We demonstrate that spectroscopic analysis of intact rice seeds provides the accurate rice variety identification in ~86% of samples. These results suggest that RS can be used for fully automated, fast and accurate identification of seeds nutrient components.
Analytical Methods for Determination of Non-Nutritive Sweeteners in Foodstuffs
Authors: Oktavirina Viki , Prabawati Nadhila B. , Fathimah Rohmah Nur , Palma Miguel , Kurnia Kiki Adi , Darmawan Noviyan , Yulianto Brian , Setyaningsih Widiastuti
Published: May 2021

Sweeteners have been used in food for centuries to increase both taste and appearance. However, the consumption of sweeteners, mainly sugars, has an adverse effect on human health when consumed in excessive doses for a certain period, including alteration in gut microbiota, obesity, and diabetes. Therefore, the application of non-nutritive sweeteners in foodstuffs has risen dramatically in the last decade to substitute sugars. These sweeteners are commonly recognized as high-intensity sweeteners because, in a lower amount, they could achieve the same sweetness of sugar. Regulatory authorities and supervisory agencies around the globe have established the maximum amount of these high-intensity sweeteners used in food products. While the regulation is getting tighter on the market to ensure food safety, reliable analytical methods are required to assist the surveillance in monitoring the use of high-intensity sweeteners. Hence, it is also necessary to comprehend the most appropriate method for rapid and effective analyses applied for quality control in food industries, surveillance and monitoring on the market, etc. Apart from various analytical methods discussed here, extraction techniques, as an essential step of sample preparation, are also highlighted. The proper procedure, efficiency, and the use of solvents are discussed in this review to assist in selecting a suitable extraction method for a food matrix. Single- and multianalyte analyses of sweeteners are also described, employing various regular techniques, such as HPLC, and advanced techniques. Furthermore, to support on-site surveillance of sweeteners’ usage in food products on the market, non-destructive analytical methods that provide practical, fast, and relatively low-cost analysis are widely implemented.
Application of Co-Culture Technology to Enhance Protease Production by Two Halophilic Bacteria, Marinirhabdus sp. and Marinobacter hydrocarbonoclasticus
Authors: Anh Hoang Thi Hong , Shahsavari Esmaeil , Bott Nathan J. , Ball Andrew S.
Published: May 2021

Although axenic microbial cultures form the basis of many large successful industrial biotechnologies, the production of single commercial microbial strains for use in large environmental biotechnologies such as wastewater treatment has proved less successful. This study aimed to evaluate the potential of the co-culture of two halophilic bacteria, Marinirhabdus sp. and Marinobacter hydrocarbonoclasticus for enhanced protease activity. The co-culture was significantly more productive than monoculture (1.6–2.0 times more growth), with Marinobacter hydrocarbonoclasticus being predominant (64%). In terms of protease activity, enhanced total activity (1.8–2.4 times) was observed in the co-culture. Importantly, protease activity in the co-culture was found to remain active over a much broader range of environmental conditions (temperature 25 °C to 60 °C, pH 4–12, and 10–30% salinity, respectively). This study confirms that the co-culturing of halophilic bacteria represents an economical approach as it resulted in both increased biomass and protease production, the latter which showed activity over arange of environmental conditions.
Lipoic Acid Combined with Melatonin Mitigates Oxidative Stress and Promotes Root Formation and Growth in Salt-Stressed Canola Seedlings (Brassica napus L.)
Authors: Javeed Hafiz Muhammad Rashad , Ali Mazhar , Skalicky Milan , Nawaz Fahim , Qamar Rafi , Rehman Atique ur , Faheem Maooz , Mubeen Muhammad , Iqbal Muhammad Mohsin , Rahman Muhammad Habib ur , Vachova Pavla , Brestic Marian , Baazeem Alaa , EL Sabagh Ayman
Published: May 2021

Lipoic acid (LA) and melatonin (MT) are pleiotropic molecules participating in plant stress resistance by modulating cellular biochemical changes, ion homeostasis, and antioxidant enzyme activities. However, the combined role of these two molecules in counteracting the detrimental impacts of salinity stress is still unknown. In the present study, we determined the effects of exogenous LA (0.5 µM), MT (1 µM) and their combination (LA + MT) on growth performance and biomass accumulation, photosynthetic pigments, enzymatic and non-enzymatic antioxidant activities, and ions homeostatic in canola (Brassica napus L.) seedlings under salinity stress (0, 100 mM) for 40 days. The results indicate that exogenous application of LA + MT improved the phenotypic growth (by 25 to 45%), root thickness (by 68%), number of later lateral roots (by 52%), root viability (by 44%), and root length (by 50%) under salinity stress. Moreover, total soluble protein, chlorophyll pigments, the concentration of superoxide dismutase (SOD), catalase peroxidase (CAT), and ascorbic peroxidase (ASA) increased with the presence of salt concentration into the growth media and then decreased with the addition of LA + MT to saline solution. Leaf protein contents and the degradation of photosynthetic pigments were lower when LA + MT treatments were added into NaCl media. The proline and phenol contents decreased in the exogenous application of LA + MT treatments more than individual LA or MT treatments under the salinity stress. The incorporation of LA or MT or a combination of LA + MT to saline solution decreased salinity-induced malondialdehyde and electrolyte leakage. In conclusion, the alteration of metabolic pathways, redox modulation, and ions homeostasis in plant tissues by the combined LA and MT application are helpful towards the adaptation of Brassica napus L. seedlings in a saline environment. The results of this study provide, for the first time, conclusive evidence about the protective role of exogenous LA + MT in canola seedlings under salinity stress.
Back to the Roots—An Overview of the Chemical Composition and Bioactivity of Selected Root-Essential Oils
Authors: Lunz Karin , Stappen Iris
Published: May 2021

Since ancient times, plant roots have been widely used in traditional medicine for treating various ailments and diseases due to their beneficial effects. A large number of studies have demonstrated that—besides their aromatic properties—their biological activity can often be attributed to volatile constituents. This review provides a comprehensive overview of investigations into the chemical composition of essential oils and volatile components obtained from selected aromatic roots, including Angelica archangelica, Armoracia rusticana, Carlina sp., Chrysopogon zizanioides, Coleus forskohlii, Inula helenium, Sassafras albidum, Saussurea costus, and Valeriana officinalis. Additionally, their most important associated biological impacts are reported, such as anticarcinogenic, antimicrobial, antioxidant, pesticidal, and other miscellaneous properties. Various literature and electronic databases—including PubMed, ScienceDirect, Springer, Scopus, Google Scholar, and Wiley—were screened and data was obtained accordingly. The results indicate the promising properties of root-essential oils and their potential as a source for natural biologically active products for flavor, pharmaceutical, agricultural, and fragrance industries. However, more research is required to further establish the mechanism of action mediating these bioactivities as well as essential oil standardization because the chemical composition often strongly varies depending on external factors.
Roles of Nrf2 in Gastric Cancer: Targeting for Therapeutic Strategies
Authors: Farkhondeh Tahereh , Pourbagher-Shahri Ali Mohammad , Azimi-Nezhad Mohsen , Forouzanfar Fatemeh , Brockmueller Aranka , Ashrafizadeh Milad , Talebi Marjan , Shakibaei Mehdi , Samarghandian Saeed
Published: May 2021

Nuclear Factor Erythroid 2-Related Factor 2 (Nrf2) is a specific transcription factor with potent effects on the regulation of antioxidant gene expression that modulates cell hemostasis under various conditions in tissues. However, the effects of Nrf2 on gastric cancer (GC) are not fully elucidated and understood. Evidence suggests that uncontrolled Nrf2 expression and activation has been observed more frequently in malignant tumors, including GC cells, which is then associated with increased antioxidant capacity, chemoresistance, and poor clinical prognosis. Moreover, Nrf2 inhibitors and the associated modulation of tumor cell redox balance have shown that Nrf2 also has beneficial effects on the therapy of various cancers, including GC. Based on previous findings on the important role of Nrf2 in GC therapy, it is of great interest to scientists in basic and clinical tumor research that Nrf2 can be active as both an oncogene and a tumor suppressor depending on different background situations.
Nutritional Disorders in a Group of Children and Adolescents with Syndromes or Diseases Involving Neurodysfunction
Authors: Podgórska-Bednarz Justyna , Perenc Lidia , Drużbicki Mariusz , Guzik Agnieszka
Published: May 2021

A study of the literature shows the lack of data on a comprehensive analysis of eating disorders in children with neurodysfunction, which constitute a clinical subgroup with an increased risk of abnormalities in this area. Therefore, the aim of this study was to determine the relationship between the coexistence of nutritional disorders and diseases or syndromes associated with neurodysfunction based on data collected during hospitalization at a rehabilitation center for children and adolescents. A retrospective analysis was carried out in a group of 327 children and adolescents aged 4–18 years. The study group covered various types of diseases or syndromes involving damage to the central nervous system. A retrospective analysis of baseline data (age, sex, main and additional diagnosis and Body Mass Index—BMI) was performed. Two assessment criteria of nutritional status were taken into account (z-score BMI and other previously published normative values). In the study group, malnutrition was found more frequently (18.0% of the respondents) than obesity (11.3% of the subjects). Hypothyroidism coexisting with malnutrition was identified in the study group (N% = 43.8%, p = 0.011) and malnutrition with tetraplegia in the subgroup of spastic cerebral palsy (N% = 34.2 %, p = 0.029).
Periodontal Health, Nutrition and Anthropometry in Professional Footballers: A Preliminary Study
Authors: Botelho João , Vicente Filipa , Dias Laura , Júdice André , Pereira Paula , Proença Luís , Machado Vanessa , Chambrone Leandro , Mendes José
Published: May 2021

Poor oral health in elite sport is a pressing issue, however little is known about the periodontal status of professional footballers. The aim of this study was to examine the prevalence of periodontitis in a group of professional footballers and its association with nutritional parameters and self-report non-traumatic injuries. Additionally, we assessed its association with anthropometric, dietary inflammatory load and self-reported muscular and/or articular injuries. Twenty-two professional footballers were evaluated at the beginning of the 2020–2021 season via full-mouth periodontal inspection, anthropometric measurements and the application of the dietary inflammatory index through a food intake measurement of 24 h dietary recall on two different days. Self-reporting non-traumatic muscular and articular injuries for the past 6 months were recorded from each athlete. Then we compared clinical measurements according to the periodontal status and we correlated age, periodontal and nutritional parameters. Overall, the prevalence of periodontitis was 40.9% and peri-implantitis was also observed. No significant differences were found regarding age or nutritional parameters according to the periodontal status. More non-traumatic muscular events in the past 6 months were found in the periodontitis group (55.6% vs. 38.4%), although the difference was non-significant. Both clinical attachment loss, periodontal pocket depth and the periodontal epithelial surface area revealed a significant moderate correlation with the percentage of fat mass, muscle mass, muscle mass index and total adipose folds. This group of professional footballers showed an alarming prevalence of periodontitis. Further studies shall examine whether periodontitis and periodontal treatment impact the performance of this group of athletes.
Zebrafish, an In Vivo Platform to Screen Drugs and Proteins for Biomedical Use
Authors: Lee Hung-Chieh , Lin Cheng-Yung , Tsai Huai-Jen
Published: May 2021

The nearly simultaneous convergence of human genetics and advanced molecular technologies has led to an improved understanding of human diseases. At the same time, the demand for drug screening and gene function identification has also increased, albeit time- and labor-intensive. However, bridging the gap between in vitro evidence from cell lines and in vivo evidence, the lower vertebrate zebrafish possesses many advantages over higher vertebrates, such as low maintenance, high fecundity, light-induced spawning, transparent embryos, short generation interval, rapid embryonic development, fully sequenced genome, and some phenotypes similar to human diseases. Such merits have popularized the zebrafish as a model system for biomedical and pharmaceutical studies, including drug screening. Here, we reviewed the various ways in which zebrafish serve as an in vivo platform to perform drug and protein screening in the fields of rare human diseases, social behavior and cancer studies. Since zebrafish mutations faithfully phenocopy many human disorders, many compounds identified from zebrafish screening systems have advanced to early clinical trials, such as those for Adenoid cystic carcinoma, Dravet syndrome and Diamond–Blackfan anemia. We also reviewed and described how zebrafish are used to carry out environmental pollutant detection and assessment of nanoparticle biosafety and QT prolongation.
Jojoba Oil: An Updated Comprehensive Review on Chemistry, Pharmaceutical Uses, and Toxicity
Authors: Gad Heba A. , Roberts Autumn , Hamzi Samirah H. , Gad Haidy A. , Touiss Ilham , Altyar Ahmed E. , Kensara Osama A. , Ashour Mohamed L.
Published: May 2021

Jojoba is a widely used medicinal plant that is cultivated worldwide. Its seeds and oil have a long history of use in folklore to treat various ailments, such as skin and scalp disorders, superficial wounds, sore throat, obesity, and cancer; for improvement of liver functions, enhancement of immunity, and promotion of hair growth. Extensive studies on Jojoba oil showed a wide range of pharmacological applications, including antioxidant, anti-acne and antipsoriasis, anti-inflammatory, antifungal, antipyretic, analgesic, antimicrobial, and anti-hyperglycemia activities. In addition, Jojoba oil is widely used in the pharmaceutical industry, especially in cosmetics for topical, transdermal, and parenteral preparations. Jojoba oil also holds value in the industry as an anti-rodent, insecticides, lubricant, surfactant, and a source for the production of bioenergy. Jojoba oil is considered among the top-ranked oils due to its wax, which constitutes about 98% (mainly wax esters, few free fatty acids, alcohols, and hydrocarbons). In addition, sterols and vitamins with few triglyceride esters, flavonoids, phenolic and cyanogenic compounds are also present. The present review represents an updated literature survey about the chemical composition of jojoba oil, its physical properties, pharmacological activities, pharmaceutical and industrial applications, and toxicity.
Chitosan-Based Nanoparticles of Targeted Drug Delivery System in Breast Cancer Treatment
Authors: Herdiana Yedi , Wathoni Nasrul , Shamsuddin Shaharum , Joni I Made , Muchtaridi Muchtaridi
Published: May 2021

Breast cancer remains one of the world’s most dangerous diseases because of the difficulty of finding cost-effective and specific targets for effective and efficient treatment methods. The biodegradability and biocompatibility properties of chitosan-based nanoparticles (ChNPs) have good prospects for targeted drug delivery systems. ChNPs can transfer various antitumor drugs to targeted sites via passive and active targeting pathways. The modification of ChNPs has attracted the researcher to the loading of drugs to targeted cancer cells. The objective of our review was to summarize and discuss the modification in ChNPs in delivering anticancer drugs against breast cancer cells from published papers recorded in Scopus, PubMed, and Google Scholar. In order to improve cellular uptake, drug accumulation, cytotoxicity, and selectivity, we examined different kinds of modification of ChNPs. Notably, these forms of ChNPs use the characteristics of the enhanced permeability and retention (EPR) effect as a proper parameter and different biological ligands, such as proteins, peptides, monoclonal antibodies, and small particles. In addition, as a targeted delivery system, ChNPs provided and significantly improved the delivery of drugs into specific breast cancer cells (MDA-MB-231, 4T1 cells, SK-BR-3, MCF-7, T47D). In conclusion, a promising technique is presented for increasing the efficacy, selectivity, and effectiveness of candidate drug carriers in the treatment of breast cancer.
Long-Term Observations of Microwave Brightness Temperatures over a Metropolitan Area: Comparison of Radiometric Data and Spectra Simulated with the Use of Radiosonde Measurements
Authors: Belikovich Mikhail V. , Kulikov Mikhail Yu. , Makarov Dmitry S. , Skalyga Natalya K. , Ryskin Vitaly G. , Shvetsov Alexander A. , Krasil’nikov Alexander A. , Dementyeva Svetlana O. , Serov Evgeny A. , Feigin Alexander M.
Published: May 2021

Ground-based microwave radiometers are increasingly used in operational meteorology and nowcasting. These instruments continuously measure the spectra of downwelling atmospheric radiation in the range 20–60 GHz used for the retrieval of tropospheric temperature and water vapor profiles. Spectroscopic uncertainty is an important part of the retrieval error budget, as it leads to systematic bias. In this study, we analyze the difference between observed and simulated microwave spectra obtained from more than four years of microwave and radiosonde observations over Nizhny Novgorod (56.2° N, 44° E). We focus on zenith-measured and elevation-scanning data in clear-sky conditions. The simulated spectra are calculated by a radiative transfer model with the use of radiosonde profiles and different absorption models, corresponding to the latest spectroscopy research. In the case of zenith-measurements, we found a systematic bias (up to ~2 K) of simulated spectra at 51–54 GHz. The sign of bias depends on the absorption model. A thorough investigation of the error budget points to a spectroscopic nature of the observed differences. The dependence of the results on the elevation angle and absorption model can be explained by the basic properties of radiative transfer and by cloud contamination at elevation angles.
Study on Local to Global Radiometric Balance for Remotely Sensed Imagery
Authors: Liu Xiaofan , Zhou Guoqing , Zhang Wuming , Luo Shezhou
Published: May 2021

Due to the difference of factors, such as lighting conditions, shooting environments, and time, there is compound brightness difference between adjacent images, which includes local brightness difference and radiometric difference. This paper proposed a method to eliminate the compound brightness difference of adjacent images after mosaicking, named local to global radiometric balance. It includes the brightness compensation model and brightness approach model. Firstly, the weighted average value of each row and column of image are calculated to express the brightness change; secondly, according to weighted average value, the brightness compensation model is built; thirdly, combined with the blocking method, the brightness compensation model is applied to image. Based on the value after above process, the brightness approach model is established to make the gray value of adjacent images approach to the mosaic line. In the paper, the standard deviation, MSE (mean square error) and mean value are used as the measure indices of the effect of brightness balance. The three groups of experimental results show that compared with the brightness stretch method, the histogram equalization method and the radiometric balance method, the local to global radiometric balance method not only realizes compound brightness balance, but also has better visual effects than others.
Discrimination and Quantitation of Biologically Relevant Carboxylate Anions Using A [Dye•PAMAM] Complex
Authors: Xu Yifei , Bonizzoni Marco
Published: May 2021

Carboxylate anions are analytical targets with environmental and biological relevance, whose detection is often challenging in aqueous solutions. We describe a method for discrimination and quantitation of carboxylates in water buffered to pH 7.4 based on their differential interaction with a supramolecular fluorescent sensor, self-assembled from readily available building blocks. A fifth-generation poly(amidoamine) dendrimer (PAMAM G5), bound to organic fluorophores (calcein or pyranine) through noncovalent interactions, forms a [dye•PAMAM] complex responsive to interaction with carboxylates. The observed changes in absorbance, and in fluorescence emission and anisotropy, were interpreted through linear discriminant analysis (LDA) and principal component analysis (PCA) to differentiate 10 structurally similar carboxylates with a limit of discrimination around 100 μM. The relationship between the analytes’ chemical structures and the system’s response was also elucidated. This insight allowed us to extend the system’s capabilities to the simultaneous identification of the nature and concentration of unknown analytes, with excellent structural identification results and good concentration recovery, an uncommon feat for a pattern-based sensing system.
SCARE: A Novel Switching and Collision Avoidance pRocEss for Connected Vehicles Using Virtualization and Edge Computing Paradigm
Authors: Tropea Mauro , De Rango Floriano , Nevigato Nicolas , Bitonti Luigi , Pupo Francesco
Published: May 2021

In this paper, some collision avoidance systems based on MEC in a VANET environment are proposed and investigated. Micro services at edge are considered to support service continuity in vehicle communication and advertising. This considered system makes use of cloud and edge computing, allowing to switch communication from edge to cloud server and vice versa when possible, trying to guarantee the required constraints and balancing the communication among the servers. Simulation results were used to evaluate the performance of three considered mechanisms: the first one considering only edge with load balancing, the second one using edge/cloud switching and the third one using edge with load balancing and collision avoidance advertising.
Experimental Strain Measurement Approach Using Fiber Bragg Grating Sensors for Monitoring of Railway Switches and Crossings
Authors: Kerrouche Abdelfateh , Najeh Taoufik , Jaen-Sola Pablo
Published: May 2021

Railway infrastructure plays a major role in providing the most cost-effective way to transport freight and passengers. The increase in train speed, traffic growth, heavier axles, and harsh environments make railway assets susceptible to degradation and failure. Railway switches and crossings (S&C) are a key element in any railway network, providing flexible traffic for trains to switch between tracks (through or turnout direction). S&C systems have complex structures, with many components, such as crossing parts, frogs, switchblades, and point machines. Many technologies (e.g., electrical, mechanical, and electronic devices) are used to operate and control S&C. These S&C systems are subject to failures and malfunctions that can cause delays, traffic disruptions, and even deadly accidents. Suitable field-based monitoring techniques to deal with fault detection in railway S&C systems are sought after. Wear is the major cause of S&C system failures. A novel measuring method to monitor excessive wear on the frog, as part of S&C, based on fiber Bragg grating (FBG) optical fiber sensors, is discussed in this paper. The developed solution is based on FBG sensors measuring the strain profile of the frog of S&C to determine wear size. A numerical model of a 3D prototype was developed through the finite element method, to define loading testing conditions, as well as for comparison with experimental tests. The sensors were examined under periodic and controlled loading tests. Results of this pilot study, based on simulation and laboratory tests, have shown a correlation for the static load. It was shown that the results of the experimental and the numerical studies were in good agreement.
PyFF: A Fog-Based Flexible Architecture for Enabling Privacy-by-Design IoT-Based Communal Smart Environments
Authors: Benhamida Fatima Zohra , Navarro Joan , Gómez-Carmona Oihane , Casado-Mansilla Diego , López-de-Ipiña Diego , Zaballos Agustín
Published: May 2021

The advent of the Internet of Things (IoT) and the massive growth of devices connected to the Internet are reshaping modern societies. However, human lifestyles are not evolving at the same pace as technology, which often derives into users’ reluctance and aversion. Although it is essential to consider user involvement/privacy while deploying IoT devices in a human-centric environment, current IoT architecture standards tend to neglect the degree of trust that humans require to adopt these technologies on a daily basis. In this regard, this paper proposes an architecture to enable privacy-by-design with human-in-the-loop IoT environments. In this regard, it first distills two IoT use-cases with high human interaction to analyze the interactions between human beings and IoT devices in an environment which had not previously been subject to the Internet of People principles.. Leveraging the lessons learned in these use-cases, the Privacy-enabling Fog-based and Flexible (PyFF) human-centric and human-aware architecture is proposed which brings together distributed and intelligent systems are brought together. PyFF aims to maintain end-users’ privacy by involving them in the whole data lifecycle, allowing them to decide which information can be monitored, where it can be computed and the appropriate feedback channels in accordance with human-in-the-loop principles.
Utilization of Micro-Doppler Radar to Classify Gait Patterns of Young and Elderly Adults: An Approach Using a Long Short-Term Memory Network
Authors: Hayashi Sora , Saho Kenshi , Shioiri Keitaro , Fujimoto Masahiro , Masugi Masao
Published: May 2021

To develop a daily monitoring system for early detection of fall risk of elderly people during walking, this study presents a highly accurate micro-Doppler radar (MDR)-based gait classification method for the young and elderly adults. Our method utilizes a time-series of velocity corresponding to leg motion during walking extracted from the MDR spectrogram (time-velocity distribution) in an experimental study involving 300 participants. The extracted time-series was inputted to a long short-term memory recurrent neural network to classify the gaits of young and elderly participant groups. We achieved a classification accuracy of 94.9%, which is significantly higher than that of a previously presented velocity-parameter-based classification method.
The Concurrent Validity, Test–Retest Reliability and Usability of a New Foot Temperature Monitoring System for Persons with Diabetes at High Risk of Foot Ulceration
Authors: Veneman Tim , Schaper Nicolaas C. , Bus Sicco A.
Published: May 2021

At-home foot temperature monitoring may be useful in the early recognition of imminent foot ulcers that occur through biomechanical loading in people with diabetes. We assessed the concurrent validity, test–retest reliability, and usability of a new plantar foot temperature monitoring device in 50 people with diabetes and peripheral neuropathy. We compared plantar foot temperature measurements with a platform system that consists of embedded temperature sensors with those from a handheld infrared thermometer that was used as a reference. Repeated platform assessments were compared for test–retest reliability. Usability was assessed in 15 participants who used both devices daily for two weeks at home, after which they completed a questionnaire. Agreement between devices was excellent for the metatarsal heads and heel (ICCs ≥ 0.98, LOA: −0.89 °C; 1.16 °C) and hallux and lateral midfoot (0.93 ≤ ICC ≤ 0.96, LOA: −2.87 °C; 2.2 °C), good for digits 2–5 (0.75 ≤ ICC ≤ 0.88, LOA: −5.04 °C; 2.76 °C), and poor for the medial midfoot (ICC = 0.19, LOA: −8.21 °C; −0.05 °C). Test–retest reliability was high (ICC = 0.99, LOA: −0.59 °C; 1.35 °C). Participants scored between 3.8 and 4.3 on a 5-point Likert scale for willingness to measure, ease of use, measurement comfort, and duration. In conclusion, the platform shows good concurrent validity in foot regions where most ulcers occur, good test–retest reliability, and good usability for measuring plantar foot temperature. Further research should assess the clinical validity of the platform to help prevent plantar diabetic foot ulcers.
Review of Weed Detection Methods Based on Computer Vision
Authors: Wu Zhangnan , Chen Yajun , Zhao Bo , Kang Xiaobing , Ding Yuanyuan
Published: May 2021

Weeds are one of the most important factors affecting agricultural production. The waste and pollution of farmland ecological environment caused by full-coverage chemical herbicide spraying are becoming increasingly evident. With the continuous improvement in the agricultural production level, accurately distinguishing crops from weeds and achieving precise spraying only for weeds are important. However, precise spraying depends on accurately identifying and locating weeds and crops. In recent years, some scholars have used various computer vision methods to achieve this purpose. This review elaborates the two aspects of using traditional image-processing methods and deep learning-based methods to solve weed detection problems. It provides an overview of various methods for weed detection in recent years, analyzes the advantages and disadvantages of existing methods, and introduces several related plant leaves, weed datasets, and weeding machinery. Lastly, the problems and difficulties of the existing weed detection methods are analyzed, and the development trend of future research is prospected.
Prediction of Flight Status of Logistics UAVs Based on an Information Entropy Radial Basis Function Neural Network
Authors: Yang Qin , Ye Zhaofa , Li Xuzheng , Wei Daozhu , Chen Shunhua , Li Zhirui
Published: May 2021

Aiming at addressing the problems of short battery life, low payload and unmeasured load ratio of logistics Unmanned Aerial Vehicles (UAVs), the Radial Basis Function (RBF) neural network was trained with the flight data of logistics UAV from the Internet of Things to predict the flight status of logistics UAVs. Under the condition that there are few available input samples and the convergence of RBF neural network is not accurate, a dynamic adjustment method of RBF neural network structure based on information entropy is proposed. This method calculates the information entropy of hidden layer neurons and output layer neurons, and quantifies the output information of hidden layer neurons and the interaction information between hidden layer neurons and output layer neurons. The structural design and optimization of RBF neural network were solved by increasing the hidden layer neurons or disconnecting unnecessary connections, according to the connection strength between neurons. The steepest descent learning algorithm was used to correct the parameters of the network structure to ensure the convergence accuracy of the RBF neural network. By predicting the regression values of the flight status of logistics UAVs, it is demonstrated that the information entropy-based RBF neural network proposed in this paper has good approximation ability for the prediction of nonlinear systems.
Hyperspectral Three-Dimensional Fluorescence Imaging Using Snapshot Optical Tomography
Authors: Juntunen Cory , Woller Isabel M. , Sung Yongjin
Published: May 2021

Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection optical tomography (SPOT) and Fourier-transform spectroscopy (FTS). SPOT allows us to instantaneously acquire the projection images corresponding to different viewing angles, while FTS allows us to perform hyperspectral imaging at high spectral resolution. Using fluorescent beads and sunflower pollens, we demonstrate the imaging performance of the developed system.
Software Sensor to Enhance Online Parametric Identification for Nonlinear Closed-Loop Systems for Robotic Applications
Authors: Sidhom Lilia , Chihi Ines , Kamavuako Ernest Nlandu
Published: May 2021

This paper proposes an online direct closed-loop identification method based on a new dynamic sliding mode technique for robotic applications. The estimated parameters are obtained by minimizing the prediction error with respect to the vector of unknown parameters. The estimation step requires knowledge of the actual input and output of the system, as well as the successive estimate of the output derivatives. Therefore, a special robust differentiator based on higher-order sliding modes with a dynamic gain is defined. A proof of convergence is given for the robust differentiator. The dynamic parameters are estimated using the recursive least squares algorithm by the solution of a system model that is obtained from sampled positions along the closed-loop trajectory. An experimental validation is given for a 2 Degrees Of Freedom (2-DOF) robot manipulator, where direct and cross-validations are carried out. A comparative analysis is detailed to evaluate the algorithm’s effectiveness and reliability. Its performance is demonstrated by a better-quality torque prediction compared to other differentiators recently proposed in the literature. The experimental results highlight that the differentiator design strongly influences the online parametric identification and, thus, the prediction of system input variables.
Car2Car Communication Using a Modulated Backscatter and Automotive FMCW Radar
Authors: Lazaro Antonio , Lazaro Marc , Villarino Ramon , Girbau David , de Paco Pedro
Published: May 2021

This work proposes the use of a modulated tag for direct communication between two vehicles using as a carrier the wave emitted by an FMCW radar installed in the vehicle for advanced driver assistance. The system allows for real-time signals detection and classification, such as stop signal, turn signals and emergency lights, adding redundancy to computer video sensors and without incorporating additional communication systems. A proof-of-concept tag has been designed at the microwave frequency of 24 GHz, consisting of an amplifier connected between receiving and transmitting antennas. The modulation is performed by switching the power supply of the amplifier. The tag is installed on the rear of the car and it answers when it is illuminated by the radar by modulating the backscattered field. The information is encoded in the modulation switching rate used. Simulated and experimental results are given showing the feasibility of the proposed solution.
Privacy-Preserving Smart Road-Pricing System with Trustworthiness Evaluation in VANETs
Authors: Zhu Qingfeng , Ji Sai , Shen Jian , Ren Yongjun
Published: May 2021

With the advanced development of the intelligent transportation system, vehicular ad hoc networks have been observed as an excellent technology for the development of intelligent traffic management in smart cities. Recently, researchers and industries have paid great attention to the smart road-tolling system. However, it is still a challenging task to ensure geographical location privacy of vehicles and prevent improper behavior of drivers at the same time. In this paper, a reliable road-tolling system with trustworthiness evaluation is proposed, which guarantees that vehicle location privacy is secure and prevents malicious vehicles from tolling violations at the same time. Vehicle route privacy information is encrypted and uploaded to nearby roadside units, which then forward it to the traffic control center for tolling. The traffic control center can compare data collected by roadside units and video surveillance cameras to analyze whether malicious vehicles have behaved incorrectly. Moreover, a trustworthiness evaluation is applied to comprehensively evaluate the multiple attributes of the vehicle to prevent improper behavior. Finally, security analysis and experimental simulation results show that the proposed scheme has better robustness compared with existing approaches.
Quantitative Metrics for Performance Monitoring of Software Code Analysis Accredited Testing Laboratories
Authors: Chapetta Wladmir Araujo , das Neves Jailton Santos , Machado Raphael Carlos Santos
Published: May 2021

Modern sensors deployed in most Industry 4.0 applications are intelligent, meaning that they present sophisticated behavior, usually due to embedded software, and network connectivity capabilities. For that reason, the task of calibrating an intelligent sensor currently involves more than measuring physical quantities. As the behavior of modern sensors depends on embedded software, comprehensive assessments of such sensors necessarily demands the analysis of their embedded software. On the other hand, interlaboratory comparisons are comparative analyses of a body of labs involved in such assessments. While interlaboratory comparison is a well-established practice in fields related to physical, chemical and biological sciences, it is a recent challenge for software assessment. Establishing quantitative metrics to compare the performance of software analysis and testing accredited labs is no trivial task. Software is intangible and its requirements accommodate some ambiguity, inconsistency or information loss. Besides, software testing and analysis are highly human-dependent activities. In the present work, we investigate whether performing interlaboratory comparisons for software assessment by using quantitative performance measurement is feasible. The proposal was to evaluate the competence in software code analysis activities of each lab by using two quantitative metrics (code coverage and mutation score). Our results demonstrate the feasibility of establishing quantitative comparisons among software analysis and testing accredited laboratories. One of these rounds was registered as formal proficiency testing in the database—the first registered proficiency testing focused on code analysis.
An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space
Authors: Khan Noman , Muhammad Khan , Hussain Tanveer , Nasir Mansoor , Munsif Muhammad , Imran Ali Shariq , Sajjad Muhammad
Published: May 2021

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice and the involvement of children during training, without any practical testing examination to check the learned abilities of a child before their exposure to real-world environments. Therefore, in this paper, we propose a 3D realistic open-ended VR and Kinect sensor-based training setup using the Unity game engine, wherein children are educated and involved in road safety exercises. The proposed system applies the concepts of VR in a game-like setting to let the children learn about traffic rules and practice them in their homes without any risk of being exposed to the outside environment. Thus, with our interactive and immersive training environment, we aim to minimize road accidents involving children and contribute to the generic domain of healthcare. Furthermore, the proposed framework evaluates the overall performance of the students in a virtual environment (VE) to develop their road-awareness skills. To ensure safety, the proposed system has an extra examination layer for children’s abilities evaluation, whereby a child is considered fit for real-world practice in cases where they fulfil certain criteria by achieving set scores. To show the robustness and stability of the proposed system, we conduct four types of subjective activities by involving a group of ten students with average grades in their classes. The experimental results show the positive effect of the proposed system in improving the road crossing behavior of the children.
LightGBM Indoor Positioning Method Based on Merged Wi-Fi and Image Fingerprints
Authors: Zhang Huiqing , Li Yueqing
Published: May 2021

Smartphones are increasingly becoming an efficient platform for solving indoor positioning problems. Fingerprint-based positioning methods are popular because of the wide deployment of wireless local area networks in indoor environments and the lack of model propagation paths. However, Wi-Fi fingerprint information is singular, and its positioning accuracy is typically 2–10 m; thus, it struggles to meet the requirements of high-precision indoor positioning. Therefore, this paper proposes a positioning algorithm that combines Wi-Fi fingerprints and visual information to generate fingerprints. The algorithm involves two steps: merged-fingerprint generation and fingerprint positioning. In the merged-fingerprint generation stage, the kernel principal component analysis feature of the Wi-Fi fingerprint and the local binary pattern features of the scene image are fused. In the fingerprint positioning stage, a light gradient boosting machine (LightGBM) is trained with mutually exclusive feature bundling and histogram optimization to obtain an accurate positioning model. The method is tested in an actual environment. The experimental results show that the positioning accuracy of the LightGBM method is 90% within a range of 1.53 m. Compared with the single-fingerprint positioning method, the accuracy is improved by more than 20%, and the performance is improved by more than 15% compared with other methods. The average locating error is 0.78 m.
Associations between Parental Mental Health and Child Maltreatment: The Importance of Family Characteristics
Authors: Ben David Vered
Published: May 2021

The study expands the literature on parents’ mental health and risk of poor parenting by exploring the association between parental mental health diagnoses and types of child maltreatment among 522 parents who were adjudicated for child maltreatment by Israeli courts. The study was cross-sectional and used a manual for the content analysis of court cases. The results showed that 62% of the parents suffered from mental health problems, including emotional problems, personality disorders, mental illness or intellectual disability. Child neglect was associated with all types of mental health diagnoses for both the mothers and fathers. However, child abuse and specifically physical abuse were associated only with the mother’s mental health diagnoses. The mother’s mental illness and personality disorder predicted child neglect and the mother’s personality disorder predicted child abuse, after controlling for poverty, child’s intellectual disability and age. No mental health diagnosis of the father predicted child maltreatment. The study concluded that the effect of mental health condition is greater for mothers. A mother’s personality disorder and mental illness should raise a special concern. Screening for maternal mental health in every case involved in the child welfare system and implications of the findings for prevention of child maltreatment are discussed.
Design of Pumping Stations Using a Multicriteria Analysis and the Application of the AHP Method
Authors: Sánchez-Ferrer Diana S. , Briceño-León Christian X. , Iglesias-Rey Pedro L. , Martínez-Solano F. Javier , Fuertes-Miquel Vicente S.
Published: May 2021

The pumping station is a very important hydraulic system in urban water supplies because the pumps raise the water head, ensuring the minimum pressure required in drinking water systems. In the design of a pumping station, one of the most important criteria is the number of pumps. However, in the traditional design, this criterion is defined arbitrarily. The other criteria are defined from the number of pumps and can produce a design that is not optimal. In addition, the traditional design does not consider the importance of the environment in choosing the pumps. The objective of this paper is to define a new design methodology for pumping stations. It has been developed using a multicriteria analysis in which nine criteria are evaluated. The application of the analytic hierarchy process (AHP) allows for finding an optimal solution. These design criteria have been associated in three cluster factors: technical factors; environmental factors; and economic factors. The results obtained allow us not only to validate the methodology but also to offer a solution to the problem of determining the most suitable model and the number of pumps for a pumping station.