bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Oxygen Vacancy on the Conduction Modulation Linearity and Classification Accuracy of Pr0.7Ca0.3MnO3 Memristor
Authors: Pyo Yeon , Woo Jong-Un , Hwang Hyun-Gyu , Nahm Sahn , Jeong Jichai
Published: October 2021

An amorphous Pr0.7Ca0.3MnO3 (PCMO) film was grown on a TiN/SiO2/Si (TiN–Si) substrate at 300 °C and at an oxygen pressure (OP) of 100 mTorr. This PCMO memristor showed typical bipolar switching characteristics, which were attributed to the generation and disruption of oxygen vacancy (OV) filaments. Fabrication of the PCMO memristor at a high OP resulted in nonlinear conduction modulation with the application of equivalent pulses. However, the memristor fabricated at a low OP of 100 mTorr exhibited linear conduction modulation. The linearity of this memristor improved because the growth and disruption of the OV filaments were mostly determined by the redox reaction of OV owing to the presence of numerous OVs in this PCMO film. Furthermore, simulation using a convolutional neural network revealed that this PCMO memristor has enhanced classification performance owing to its linear conduction modulation. This memristor also exhibited several biological synaptic characteristics, indicating that an amorphous PCMO thin film fabricated at a low OP would be a suitable candidate for artificial synapses.
Unipolar Parity of Ferroelectric-Antiferroelectric Characterized by Junction Current in Crystalline Phase Hf1−xZrxO2 Diodes
Authors: Hsiang Kuo-Yu , Liao Chun-Yu , Wang Jer-Fu , Lou Zhao-Feng , Lin Chen-Ying , Chiang Shih-Hung , Liu Chee-Wee , Hou Tuo-Hung , Lee Min-Hung
Published: October 2021

Ferroelectric (FE) Hf1−xZrxO2 is a potential candidate for emerging memory in artificial intelligence (AI) and neuromorphic computation due to its non-volatility for data storage with natural bi-stable characteristics. This study experimentally characterizes and demonstrates the FE and antiferroelectric (AFE) material properties, which are modulated from doped Zr incorporated in the HfO2-system, with a diode-junction current for memory operations. Unipolar operations on one of the two hysteretic polarization branch loops of the mixed FE and AFE material give a low program voltage of 3 V with an ON/OFF ratio >100. This also benefits the switching endurance, which reaches >109 cycles. A model based on the polarization switching and tunneling mechanisms is revealed in the (A)FE diode to explain the bipolar and unipolar sweeps. In addition, the proposed FE-AFE diode with Hf1−xZrxO2 has a superior cycling endurance and lower stimulation voltage compared to perovskite FE-diodes due to its scaling capability for resistive FE memory devices.
3D Self-Supported Nitrogen-Doped Carbon Nanofiber Electrodes Incorporated Co/CoOx Nanoparticles: Application to Dyes Degradation by Electro-Fenton-Based Process
Authors: Barhoum Ahmed , Favre Therese , Sayegh Syreina , Tanos Fida , Coy Emerson , Iatsunskyi Igor , Razzouk Antonio , Cretin Marc , Bechelany Mikhael
Published: October 2021

We developed free-standing nitrogen-doped carbon nanofiber (CNF) electrodes incorporating Co/CoOx nanoparticles (NPs) as a new cathode material for removing Acid Orange 7 (AO7; a dye for wool) from wastewater by the heterogeneous electro-Fenton reaction. We produced the free-standing N-doped CNF electrodes by electrospinning a polyacrylonitrile (PAN) and cobalt acetate solution followed by thermal carbonation of the cobalt acetate/PAN nanofibers under a nitrogen atmosphere. We then investigated electro-Fenton-based removal of AO7 from wastewater with the free-standing N-doped-CNFs-Co/CoOx electrodes, in the presence or not of Fe2+ ions as a co-catalyst. The electrochemical analysis showed the high stability of the prepared N-doped-CNF-Co/CoOx electrodes in electrochemical oxidation experiments with excellent degradation of AO7 (20 mM) at acidic to near neutral pH values (3 and 6). Electro-Fenton oxidation at 10 mA/cm2 direct current for 40 min using the N-doped-CNF-Co/CoOx electrodes loaded with 25 wt% of Co/CoOx NPs led to complete AO7 solution decolorization with total organic carbon (TOC) removal values of 92.4% at pH 3 and 93.3% at pH 6. The newly developed N-doped-CNF-Co/CoOx electrodes are an effective alternative technique for wastewater pre-treatment before the biological treatment.
Determining the Influence of Habitual Dietary Protein Intake on Physiological Muscle Parameters in Youth and Older Age
Authors: Mathewson Sophie L. , Gordon Adam L. , Smith Kenneth , Atherton Philip J. , Greig Carolyn A. , Phillips Bethan E.
Published: October 2021

Protein ingestion is a potent stimulator of skeletal muscle protein synthesis (MPS). However, older adults demonstrate resistance to anabolic stimuli. Some evidence has demonstrated that a larger acute protein dose is required in older compared to younger adults to elicit the same synthetic response, suggesting that older adults should be consuming higher habitual dietary protein to optimise muscle mass. However, limited research has explored dietary habits in different age groups or the relationship between habitual dietary intake and mechanistic physiological parameters associated with muscle mass and function. This work investigated the effect of habitual dietary intake in young (n = 10, 25.9 (3.2y)) and older (n = 16, 70.2 (3.2y)) community-dwelling adults (16:10 male: female) on physiological muscle parameters. Dietary intake was assessed using four-day diet diaries. Post-absorptive MPS and MPS responses to feeding (4.25x basal metabolic rate; 16% protein) were determined in muscle biopsies of the m. vastus lateralis via stable isotope tracer ([1, 2−13C2]-leucine) infusions with mass-spectrometric analyses. Body composition was measured by dual-energy x-ray absorptiometry. Whole body strength was assessed via 1-repetition maximum assessments. No significant differences in habitual dietary intake (protein, fat, carbohydrate and leucine as g.kgWBLM−1.day−1) were observed between age groups. Whole-body lean mass (61.8 ± 9.9 vs. 49.8 ± 11.9 kg, p = 0.01) and knee-extensor strength (87.7 ± 28.3 vs. 56.8 ± 16.4 kg, p = 0.002) were significantly higher in young adults. Habitual protein intake (g.kg−1.day−1) was not associated with whole-body lean mass, upper-leg lean mass, whole-body strength, knee-extensor strength, basal MPS or fed-state MPS across both age groups. These findings suggest that differences in muscle mass and strength parameters between youth and older age are not explained by differences in habitual dietary protein intake. Further research with a larger sample size is needed to fully explore these relationships and inform on interventions to mitigate sarcopenia development.
Relation between Attachment and Obesity in Preschool Years: A Systematic Review of the Literature
Authors: Santos Ana F. , Martins Mariana C. , Fernandes Carla , Bost Kelly K. , Veríssimo Manuela
Published: October 2021

Increasing evidence suggests that attachment plays an important role in obesity. However, few studies examined this relationship in preschool children. This study aimed to systematically examine the empirical, peer-reviewed evidence regarding the relationship between attachment quality and obesity in the preschool years. Using established guidelines, relevant peer-reviewed literature published between 2000 and July 2021 was searched through EBSCO. This yielded a total of 1124 records for review. Established inclusion criteria comprised: empirical studies published in peer-review journals; include at least one anthropometric measure and/or food consumption measure. Exclusion criteria comprised: attachment measures not following Bowlby-Ainsworth conceptualization of the construct; children in institutionalized settings; context of severe mental illness, documented substance use disorders, or eating disorders; include only a measure of the psychological aspects of eating; intervention programs. After exclusions, eight studies with a total of 9225 participants met the inclusion criteria. Results support the role of attachment in weight-related outcomes, suggesting that considering attachment in the risk of obesity could contribute to the elaboration of effective prevention and intervention programs. Limitations included the small number of studies, predominately cross-sectional designs, the diversity of methodologies, most samples not including fathers, and lack of evidence about the developmental mechanisms underlying the association between attachment and obesity. More evidence is needed to determine how attachment and obesity are linked, and the potential underlying mechanisms accounting for this relationship.
Utilising Co-Axial Electrospinning as a Taste-Masking Technology for Paediatric Drug Delivery
Authors: Abdelhakim Hend E. , Coupe Alastair , Tuleu Catherine , Edirisinghe Mohan , Craig Duncan Q. M.
Published: October 2021

The present study describes the use of two taste-masking polymers to fabricate a formulation of chlorpheniramine maleate for paediatric administration. Co-axial electrospinning was utilized to create layered nanofibres; the two polymers, Eudragit® E PO and Kollicoat® Smartseal, were alternated between the core and the shell of the system in order to identify the optimum taste-masked formulation. The drug was loaded in the core on all occasions. It was found that the formulation with Kollicoat® Smartseal in the core with the drug, and Eudragit® E PO in the shell showed the most effective taste-masking compared to the other formulations. These fibres were in the nano-range and had smooth morphology as verified by scanning electron microscopy. Solid-state characterization and thermal analysis confirmed that amorphous solid dispersions were formed upon electrospinning. The Insent E-tongue was used to assess the taste-masking efficiency of the samples, and it was found that this formulation was undetectable by the bitter sensor, indicating successful taste-masking compared to the raw version of the drug. The E-tongue also confirmed the drug’s bitterness threshold as compared to quinine HCl dihydrate, a parameter that is useful for formulation design and taste-masking planning.
The Effects of Accelerated Temperature-Controlled Stability Systems on the Release Profile of Primary Bile Acid-Based Delivery Microcapsules
Authors: Mooranian Armin , Carey Louise , Ionescu Corina Mihaela , Walker Daniel , Jones Melissa , Wagle Susbin Raj , Kovacevic Bozica , Foster Thomas , Chester Jacqueline , Johnston Edan , Mikov Momir , Al-Salami Hani
Published: October 2021

Introduction: Bile acid-based drug encapsulation for oral delivery has been recently explored in our laboratory and has shown to be beneficial in terms of drug-targeted delivery and release profile, but stability at various temperatures has not previously been examined; hence, this is the aim of this study. Methods: Various types of bile acid-based microcapsules containing the drug metformin were produced and tested for accelerated temperature-controlled profiles, as well as morphology, elemental composition, drug content, resilience, floatability, wettability and release profiles at various pH values. Results: Accelerated temperature-controlled analysis showed negligible effects on morphology, size, or shape at very low temperatures (below 0 °C), while higher temperatures (above 25 °C) caused alterations. Drug contents, morphology and elemental composition remained similar, while wettability and the release profiles showed formulation-dependent effects. Discussion and Conclusion: Results suggest that bile acid-based microcapsules containing metformin are affected by temperature; hence, their shelf life is likely to be affected by storage temperature, all of which have a direct impact on drug release and stability profiles.
Nitrogen Assimilation Related Genes in Brassicanapus: Systematic Characterization and Expression Analysis Identified Hub Genes in Multiple Nutrient Stress Responses
Authors: He Xuyou , Zhang Hao , Ye Xiangsheng , Hong Juan , Ding Guangda
Published: October 2021

Nitrogen (N) is an essential macronutrient for plants. However, little is known about the molecular regulation of N assimilation in Brassica napus, one of the most important oil crops worldwide. Here, we carried out a comprehensive genome-wide analysis of the N assimilation related genes (NAGs) in B. napus. A total of 67 NAGs were identified encoding major enzymes involved in N assimilation, including asparagine synthetase (AS), glutamate dehydrogenase (GDH), glutamine oxoglutarate aminotransferase (GOGAT), glutamine synthetase (GS), nitrite reductase (NiR), nitrate reductase (NR). The syntenic analysis revealed that segmental duplication and whole-genome duplication were the main expansion pattern during gene evolution. Each NAG family showed different degrees of differentiation in characterization, gene structure, conserved motifs and cis-elements. Furthermore, diverse responses of NAG to multiple nutrient stresses were observed. Among them, more NAGs were regulated by N deficiency and ammonium toxicity than by phosphorus and potassium deprivations. Moreover, 12 hub genes responding to N starvation were identified, which may play vital roles in N utilization. Taken together, our results provide a basis for further functional research of NAGs in rapeseed N assimilation and also put forward new points in their responses to contrasting nutrient stresses.
The Impact of Light Spectrum and Intensity on the Growth, Physiology, and Antioxidant Activity of Lettuce (Lactuca sativa L.)
Authors: Mohamed Shiren J. , Rihan Hail Z. , Aljafer Naofel , Fuller Michael P.
Published: October 2021

This study focused on the physiology, growth and antioxidant activity response of hydroponically grown lettuce (Lactuca sativa L.) under sole-source LED lighting of differing spectra. Lighting spectra were provided by differing combinations of LEDs of three different peak wavelengths, (Blue 435, Blue 450, and Red 663 nm) with ratios of B450/R663: 1.25 ± 0.1, B450/R663: 1.25 ± 0.1, and B450/R663 1:1 at two light intensities of photosynthetically active radiation (PAR) (270 μmol m−2 s−1 and 60 μmol m−2 s−1). A further experiment was conducted, in which Blue and Red LEDs were supplemented with Green (Blue 450, Red 663, and Green 520 nm) with ratios of B435/R663: 1.25 ± 0.1, B450/R663/G520: 1/0.73/0.26, and B450/R663: 1.25 ± 0.1. LED light intensities under the different spectra were adjusted to deliver the same level of PAR (270 ± 20 μmol m−2 s−1). Results from the first experiment showed that increased fraction of blue 435 nm in combination with red light at 663 nm at high irradiance enhanced the physiology of lettuce (i.e., significantly increased assimilation rate, stomatal conductance and transpiration rate) and increased the yield while having no significant effect on antioxidant activity. At the lower irradiance, the B435/R663 significantly increased antioxidant activity compared to other spectra. Results from the second experiment showed no significant effect of the spectra of LEDs on the physiology and yield of lettuce, but antioxidant activity was very significantly induced by B450/R663 at the ratio of 1.25 ± 0.1. However, the amount was still less than that obtained by B435/R663 1.25 ± 0.1 from the first experiment. This study indicates that LED light with a spectrum of B435/R663 at a ratio of 1.25 ± 0.1 significantly improves lettuce yield and antioxidant activity.
A Comparison among Lignin Modification Methods on the Properties of Lignin–Phenol–Formaldehyde Resin as Wood Adhesive
Authors: Younesi-Kordkheili Hamed , Pizzi Antonio
Published: October 2021

The research aim of this work is to determine the influence of lignin modification methods on lignin–phenol–formaldehyde (LPF) adhesive properties. Thus, glyoxal (G), phenol (P), ionic liquid (IL), and maleic anhydride (MA) were used to modify lignin. The modified lignins were used for phenol substitution (50 wt%) in phenol–formaldehyde adhesives. The prepared resins were then used for the preparation of wood particleboard. These LPF resins were characterized physicochemically, namely by using standard methods to determine gel time, solids content, density, and viscosity, thus the physicochemical properties of the LPF resins synthesized. The panels dimensional stability, formaldehyde emission, bending modulus, bending strength, and internal bond (IB) strength were also measured. MA-modified lignin showed by differential scanning calorimetry (DSC) the lowest temperature of curing than the resins with non-modified lignin and modified with IL, phenolared lignin, and glyoxal. LPF resins with lignin treated with maleic anhydride presented a shorter gel time, higher viscosity, and solids content than the resins with other lignin modifications. Equally, the particleboard panels prepared with LPF resins with maleic anhydride or with ionic liquid had the lowest formaldehyde emission and the highest mechanical strength among all the synthesized resins. The dimensional stability of all panels bonded with modified lignin LPF resins presented no difference of any significance.
Dynamic Optimization of Chemical Processes Based on Modified Sailfish Optimizer Combined with an Equal Division Method
Authors: Zhang Yuedong , Mo Yuanbin
Published: October 2021

The optimal solution of the chemical dynamic optimization problem is the basis of automatic control operation in the chemical process, which can reduce energy consumption, increase production efficiency, and maximize economic benefit. In this paper, a modified sailfish optimizer (MSFO) combined with an equal division method is proposed for solving chemical dynamic optimization problems. Based on the basic sailfish optimizer, firstly, the tent chaotic mapping strategy is introduced to disturb the initialization of sailfish and sardine populations to avoid the loss of population diversity. Secondly, an adaptive linear reduction strategy of attack parameters is proposed to enhance the exploration and exploitation ability of sailfish. Thirdly, the updating formula of sardine position is modified, and the global optimal solution is used to attract all sardine positions, which can avoid the premature phenomenon of the algorithm. Eventually, the MSFO is applied to solve six classical optimization cases of chemical engineering to evaluate its feasibility. The experimental results are analyzed and compared with other optimization methods to prove the superiority of the MSFO in solving chemical dynamic optimization problems.
Parameter Identification of a Quasi-3D PEM Fuel Cell Model by Numerical Optimization
Authors: Haslinger Maximilian , Steindl Christoph , Lauer Thomas
Published: October 2021

Polymer electrolyte membrane fuel cells (PEMFCs) supplied with green hydrogen from renewable sources are a promising technology for carbon dioxide-free energy conversion. Many mathematical models to describe and understand the internal processes have been developed to design more powerful and efficient PEMFCs. Parameterizing such models is challenging, but indispensable to predict the species transport and electrochemical conversion accurately. Many material parameters are unknown, or the measurement methods required to determine their values are expensive, time-consuming, and destructive. This work shows the parameterization of a quasi-3D PEMFC model using measurements from a stack test stand and numerical optimization algorithms. Differential evolution and the Nelder–Mead simplex algorithm were used to optimize eight material parameters of the membrane, cathode catalyst layer (CCL), and gas diffusion layer (GDL). Measurements with different operating temperatures and gas inlet pressures were available for optimization and validation. Due to the low operating temperature of the stack, special attention was paid to the temperature dependent terms in the governing equations. Simulations with optimized parameters predicted the steady-state and transient behavior of the stack well. Therefore, valuable data for the characterization of the membrane, the CCL and GDL was created that can be used for more detailed CFD simulations in the future.
Islam under the Rule of Law in Europe: How Consistent Is the Human Rights Test?
Authors: Foblets Marie-Claire
Published: October 2021

This contribution draws attention to human rights as an instrument of justice to deal with requests that are either made directly or may prove indirectly to be relevant to Muslims who claim the protection of freedom of religion and faith in contemporary European societies. The analysis is distributed over two distinct but complementary illustrations of such claims. The position defended here is that the key to a successful multicultural society lies in enabling adherents of all religions and beliefs, and thus also Muslims, to participate to the same extent, fully and actively, in social life, both as citizens and as private individuals. The challenge lies in finding the balance between looking after the interests of the majority society and meeting the needs and wishes of minority groups and communities, including those communities that are perceived to be ‘new’.
The Creation of Adam and the Biblical Origins of Race in The Slave’s Friend (1836–1838)
Authors: Sonia Kerry M.
Published: October 2021

The creation of Adam out of dust is a familiar tradition from the Book of Genesis. In abolitionist literature of the nineteenth century, this biblical narrative became the basis for a theory about the origins of race, arguing that because Adam was formed from red clay, neither he nor his descendants were white. This interpretation of Genesis underscored the value of non-white ancestors both in the biblical narrative and in human history and undermined popular theological arguments that upheld color-based racial hierarchies that privileged whiteness in the United States. This article examines the creation of Adam in Genesis 2 and its use in racial theory and abolitionist rhetoric, focusing on the children’s anti-slavery periodical The Slave’s Friend, published from 1836 to 1838.
The Politics of Calendars: State Appropriations of the Contested Iranian Past
Authors: Kashfi Ehsan
Published: October 2021

This paper seeks to investigate how commemorative practices, rituals, and holidays are invented, deployed, and recast for political and ideological purposes, to reinforce and sustain a particular narrative of national identity. It argues that the choice of particular moments of a country’s past to be commemorated in calendars as national holidays and the way in which the collective past is preserved and remembered both reflect and articulate a country’s vision of its present essence, of who its people are. Recognizing the link between the collective memory and national identity, the Iranian states before and after the 1979 revolution made a special effort to articulate their narrative of the past by commemorating a particular set of holidays and rituals. Viewing the calendar as a political artifact, this paper compares changes in the Iranian national calendars in the Pahlavi era (1925–1979) and the Islamic Republic (1979–2018). It examines the inclusion of new religious holidays and the removal of national days associated with the monarchy as well as the assignment of new meanings and celebratory practices to the old ones as the signifiers of a political maneuver to articulate a new shared public memory and narrative of identity since the 1979 revolution. It then examines two nationwide celebrations before and after the 1979 revolution, representing two state-sponsored, competing narratives of Iranian identity: firstly, the 2500-year celebration of the Persian Empire in 1953, and, secondly, the Ashura commemoration, a religious gathering dedicated to the remembrance of Shia Imams. These commemorations provided the state a unique political opportunity to present its own appraisal of the past and, in turn, national identity.
Hyperspectral Image Super-Resolution Based on Spatial Correlation-Regularized Unmixing Convolutional Neural Network
Authors: Lu Xiaochen , Yang Dezheng , Zhang Junping , Jia Fengde
Published: October 2021

Super-resolution (SR) technology has emerged as an effective tool for image analysis and interpretation. However, single hyperspectral (HS) image SR remains challenging, due to the high spectral dimensionality and lack of available high-resolution information of auxiliary sources. To fully exploit the spectral and spatial characteristics, in this paper, a novel single HS image SR approach is proposed based on a spatial correlation-regularized unmixing convolutional neural network (CNN). The proposed approach takes advantage of a CNN to explore the collaborative spatial and spectral information of an HS image and infer the high-resolution abundance maps, thereby reconstructing the anticipated high-resolution HS image via the linear spectral mixture model. Moreover, a dual-branch architecture network and spatial spread transform function are employed to characterize the spatial correlation between the high- and low-resolution HS images, aiming at promoting the fidelity of the super-resolved image. Experiments on three public remote sensing HS images demonstrate the feasibility and superiority in terms of spectral fidelity, compared with some state-of-the-art HS image super-resolution methods.
Evaluation and Projection of Wind Speed in the Arid Region of Northwest China Based on CMIP6
Authors: Long Yunxia , Xu Changchun , Liu Fang , Liu Yongchang , Yin Gang
Published: October 2021

Near surface wind speed has significant impacts on ecological environment change and climate change. Based on the CN05.1 observation data (a gridded monthly dataset with the resolution of 0.25 latitude by 0.25 longitude over China), this study evaluated the ability of 25 Global Climate Models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating the wind speed in the Arid Region of Northwest China (ARNC) during 1971–2014. Then, the temporal and spatial variations in the surface wind speed of ARNC in the 21st century were projected under four Shared Socioeconomic Pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0, and SP5-8.5. The results reveal that the preferred-model ensemble (PME) can fairly evaluate the temporal and spatial distribution of surface wind speed with the temporal and spatial correlation coefficients exceeding 0.5 at the significance level of p = 0.05 when compared to the 25 single models and their ensemble mean. After deviation correction, the PME can reproduce the distribution characteristics of high wind speed in the east and low in the west, high in mountainous areas, and low in basins. Unfortunately, no models or model ensemble can accurately reproduce the decreasing magnitude of observed wind speed. In the 21st century, the surface wind speed in the ARNC is projected to increase under SSP1-2.6 scenario but will decrease remarkably under the other three scenarios. Moreover, the higher the emission scenarios, the more significant the surface wind speed decreases. Spatially, the wind speed will increase significantly in the west and southeast of Xinjiang, decrease in the north of Xinjiang and the south of Tarim Basin. What’s more, under the four scenarios, the surface wind speed will decrease in spring, summer and autumn, especially in summer, and increase in winter. The wind speed will decrease significantly in the north of Tianshan Mountains in summer, decrease significantly in the north of Xinjiang and the southern edge of Tarim Basin in spring and autumn, and increase in fluctuation with high values in Tianshan Mountains in winter.
Improving Machine Learning Classification Accuracy for Breathing Abnormalities by Enhancing Dataset
Authors: Rehman Mubashir , Shah Raza Ali , Khan Muhammad Bilal , Shah Syed Aziz , AbuAli Najah Abed , Yang Xiaodong , Alomainy Akram , Imran Muhmmad Ali , Abbasi Qammer H.
Published: October 2021

The recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as coronavirus disease (COVID)-19, has appeared as a global pandemic with a high mortality rate. The main complication of COVID-19 is rapid respirational deterioration, which may cause life-threatening pneumonia conditions. Global healthcare systems are currently facing a scarcity of resources to assist critical patients simultaneously. Indeed, non-critical patients are mostly advised to self-isolate or quarantine themselves at home. However, there are limited healthcare services available during self-isolation at home. According to research, nearly 20–30% of COVID patients require hospitalization, while almost 5–12% of patients may require intensive care due to severe health conditions. This pandemic requires global healthcare systems that are intelligent, secure, and reliable. Tremendous efforts have been made already to develop non-contact sensing technologies for the diagnosis of COVID-19. The most significant early indication of COVID-19 is rapid and abnormal breathing. In this research work, RF-based technology is used to collect real-time breathing abnormalities data. Subsequently, based on this data, a large dataset of simulated breathing abnormalities is generated using the curve fitting technique for developing a machine learning (ML) classification model. The advantages of generating simulated breathing abnormalities data are two-fold; it will help counter the daunting and time-consuming task of real-time data collection and improve the ML model accuracy. Several ML algorithms are exploited to classify eight breathing abnormalities: eupnea, bradypnea, tachypnea, Biot, sighing, Kussmaul, Cheyne–Stokes, and central sleep apnea (CSA). The performance of ML algorithms is evaluated based on accuracy, prediction speed, and training time for real-time breathing data and simulated breathing data. The results show that the proposed platform for real-time data classifies breathing patterns with a maximum accuracy of 97.5%, whereas by introducing simulated breathing data, the accuracy increases up to 99.3%. This work has a notable medical impact, as the introduced method mitigates the challenge of data collection to build a realistic model of a large dataset during the pandemic.
Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends
Authors: Martinez-Hernandez Uriel , Metcalfe Benjamin , Assaf Tareq , Jabban Leen , Male James , Zhang Dingguo
Published: October 2021

Wearable assistive robotics is an emerging technology with the potential to assist humans with sensorimotor impairments to perform daily activities. This assistance enables individuals to be physically and socially active, perform activities independently, and recover quality of life. These benefits to society have motivated the study of several robotic approaches, developing systems ranging from rigid to soft robots with single and multimodal sensing, heuristics and machine learning methods, and from manual to autonomous control for assistance of the upper and lower limbs. This type of wearable robotic technology, being in direct contact and interaction with the body, needs to comply with a variety of requirements to make the system and assistance efficient, safe and usable on a daily basis by the individual. This paper presents a brief review of the progress achieved in recent years, the current challenges and trends for the design and deployment of wearable assistive robotics including the clinical and user need, material and sensing technology, machine learning methods for perception and control, adaptability and acceptability, datasets and standards, and translation from lab to the real world.
A Review: Application and Implementation of Optic Fibre Sensors for Gas Detection
Authors: Allsop Thomas , Neal Ronald
Published: October 2021

At the present time, there are major concerns regarding global warming and the possible catastrophic influence of greenhouse gases on climate change has spurred the research community to investigate and develop new gas-sensing methods and devices for remote and continuous sensing. Furthermore, there are a myriad of workplaces, such as petrochemical and pharmacological industries, where reliable remote gas tests are needed so that operatives have a safe working environment. The authors have concentrated their efforts on optical fibre sensing of gases, as we became aware of their increasing range of applications. Optical fibre gas sensors are capable of remote sensing, working in various environments, and have the potential to outperform conventional metal oxide semiconductor (MOS) gas sensors. Researchers are studying a number of configurations and mechanisms to detect specific gases and ways to enhance their performances. Evidence is growing that optical fibre gas sensors are superior in a number of ways, and are likely to replace MOS gas sensors in some application areas. All sensors use a transducer to produce chemical selectivity by means of an overlay coating material that yields a binding reaction. A number of different structural designs have been, and are, under investigation. Examples include tilted Bragg gratings and long period gratings embedded in optical fibres, as well as surface plasmon resonance and intra-cavity absorption. The authors believe that a review of optical fibre gas sensing is now timely and appropriate, as it will assist current researchers and encourage research into new photonic methods and techniques.
Heart and Lung Sound Measurement Using an Esophageal Stethoscope with Adaptive Noise Cancellation
Authors: Mohamed Nourelhuda , Kim Hyun-Seok , Kang Kyu-Min , Mohamed Manal , Kim Sung-Hoon , Kim Jae Gwan
Published: October 2021

In surgeries where general anesthesia is required, the auscultation of heart and lung sounds is essential to provide information on the patient’s cardiorespiratory system. Heart and lung sounds can be recorded using an esophageal stethoscope; however, there is huge background noise when this device is used in an operating room. In this study, a digital esophageal stethoscope system was designed. A 3D-printed case filled with Polydimethylsiloxane material was designed to hold two electret-type microphones. One of the microphones was placed inside the printed case to collect the heart and lung sound signals coming out from the patient through the esophageal catheter, the other was mounted on the surface of the case to collect the operating room sounds. A developed adaptive noise canceling algorithm was implemented to remove the operating room noise corrupted with the main heart and lung sound signals and the output signal was displayed on software application developed especially for this study. Using the designed case, the noise level of the signal was reduced to some extent, and by adding the adaptive filter, further noise reduction was achieved. The designed system is lightweight and can provide noise-free heart and lung sound signals.
Edge Structural Health Monitoring (E-SHM) Using Low-Power Wireless Sensing
Authors: Buckley Tadhg , Ghosh Bidisha , Pakrashi Vikram
Published: October 2021

Effective Structural Health Monitoring (SHM) often requires continuous monitoring to capture changes of features of interest in structures, which are often located far from power sources. A key challenge lies in continuous low-power data transmission from sensors. Despite significant developments in long-range, low-power telecommunication (e.g., LoRa NB-IoT), there are inadequate demonstrative benchmarks for low-power SHM. Damage detection is often based on monitoring features computed from acceleration signals where data are extensive due to the frequency of sampling (~100–500 Hz). Low-power, long-range telecommunications are restricted in both the size and frequency of data packets. However, microcontrollers are becoming more efficient, enabling local computing of damage-sensitive features. This paper demonstrates the implementation of an Edge-SHM framework through low-power, long-range, wireless, low-cost and off-the-shelf components. A bespoke setup is developed with a low-power MEM accelerometer and a microcontroller where frequency and time domain features are computed over set time intervals before sending them to a cloud platform. A cantilever beam excited by an electrodynamic shaker is monitored, where damage is introduced through the controlled loosening of bolts at the fixed boundary, thereby introducing rotation at its fixed end. The results demonstrate how an IoT-driven edge platform can benefit continuous monitoring.
Human-like Decision-Making System for Overtaking Stationary Vehicles Based on Traffic Scene Interpretation
Authors: Yang Jinsoo , Lee Seongjin , Lim Wontaek , Sunwoo Myoungho
Published: October 2021

There are multifarious stationary vehicles in urban driving environments. Autonomous vehicles need to make appropriate overtaking maneuver decisions to navigate through the stationary vehicles. In literature, overtaking maneuver decision problems have been addressed in the perspective of either discretionary lane-change or parked vehicle classification. While the former approaches are prone to generating undesired overtaking maneuvers in urban traffic scenarios, the latter approaches induce deadlock situations behind a stationary vehicle which is not distinctly classified as a parked vehicle. To overcome the limitations, we analyzed the significant decision factors in the traffic scenes and designed a Deep Neural Network (DNN) model to make human-like overtaking maneuver decisions. The significant traffic-related and intention-related decision factors were harmoniously extracted in the traffic scene interpretation process and were utilized as the inputs of the model to generate overtaking maneuver decisions in the same manner with the human driver. The overall validation results convinced that the extracted decision factors contributed to increasing the learning performance of the model, and consequently, the proposed decision-making system enabled the autonomous vehicles to generate more human-like overtaking maneuver decisions in various urban traffic scenarios.
GO-DEVS: Storage and Retrieval System for DEVS Models Using Graph and Ontology Representation
Authors: Lee Chun-Hee , Bae Jang Won , Paik Euihyun
Published: October 2021

DEVS is a powerful formal language to describe discrete event systems in modeling and simulation areas and useful for component-based design. One of the advantages of component-based design is reusability. To reuse or share DEVS models developed by many other modelers, a system to systematically store and retrieve many DEVS models should be supported. However, to the best of our knowledge, there does not exist such a system. In this paper, we propose GO-DEVS (Graph/Ontology-represented DEVS storage and retrieval system) to store and retrieve DEVS models using graph and ontology representation. For effective model sharing, an ontology is introduced when a DEVS model is developed. To search for DEVS models in an effective and efficient way, we propose two types of queries, IO query and structure query, and provide a method to store and query DEVS models on an RDBMS. Finally, we experimentally show GO-DEVS can process the queries efficiently.
An Index for Quantitative Evaluation of the Mixing in Ethanol Precipitation of Traditional Chinese Medicine
Authors: Tai Yanni , Pan Jingjing , Qu Haibin , Gong Xingchu
Published: October 2021

(1) Background: Ethanol precipitation is widely used in the manufacturing traditional Chinese medicines (TCMs). Insufficient mixing of ethanol solution and concentrate usually results in the coating loss of active ingredients. However, there is no index for quantitative evaluation of the mixing in ethanol precipitation. Therefore, this study aimed to define an index for quantitative evaluation of the mixing effect in ethanol precipitation of TCMs. (2) Methods: The concept and requirements of a mixing indicator were proposed. The mass percentage of concentrate fully mixed with ethanol solution (well-mixing ratio, WMR) was used as an index to evaluate the mixing effect. The formula for calculation of WMR was derived. The utility of the WMR was evaluated on stirring devices and a micromesh mixer. (3) Results: Increasing stirring speed, decreasing total solid content of the concentrate, and decreasing the diameter of the ethanol solution droplets all resulted in higher retention rates for lobetyolin and higher WMR. The WMR increased with the increasing flow rate of the concentrate and ethanol solution in the micromesh mixer. The mixing of ethanol solution and concentrate was better when using a micromesh mixer with a smaller internal mixing zone. The results revealed that WMR could be used to quantitatively characterize the mixing of concentrate and ethanol solution, although it has some limitations. (4) Conclusions: The proposed index WMR could guide quality control of the TCM ethanol precipitation process. This study represents a new contribution to improving ethanol precipitation equipment, optimizing process parameters, and enhanced properties of concentrate for TCM enterprises.
Hemp Growth Factors and Extraction Methods Effect on Antimicrobial Activity of Hemp Seed Oil: A Systematic Review
Authors: Ostapczuk Klaudia , Apori Samuel Obeng , Estrada Giovani , Tian Furong
Published: October 2021

The bioactive Hemp Seed Oil (HSO) is becoming very popular in the medical and research fields due to its antimicrobial properties against several diseases caused by bacteria and fungi. However, the effect of hemp-growing factors and extraction methods on the bioactivity of HSO does not receive adequate research attention. Therefore, this review aims to investigate the effect of growth factors and extraction methods on the antimicrobial activity of HSO. Articles were retrieved from Google Scholar and the Scopus database and screened against inclusion and exclusion criteria. The study revealed that HSO prefers warm climates and favorable humidity ranging from 20 to 39 °C and 79–100% per year, respectively, and rainfall of 324 mm daily. The multivariate linear regression shown excellent prediction (R2 = 0.94) with climates upon Zone of Growth Inhibition (ZGI) of Gram-positive bacteria. Temperature is the strongest predictor (p < 0.01) followed by humidity and rainfall (p < 0.05). Furthermore, well-drained loam soil rich in organic matter seems to stimulate the antimicrobial activity of HSO. The major constituents that influence HSO’s antimicrobial ability to Staphylococcus aureus were cannabidiol (CBD), β-caryophyllene, and limonene. The extraction methods showed less influence on the HSO bioactivity. HSO did not show significant antioxidant activity, but Hemp Seed Hull (HSH), Hemp Seed Flour (HSF), and Hydrolyzed Hemp Seed Protein (HPH), expressed promising DPPH scavenging ability.
Rapid, Highly-Sensitive and Ecologically Greener Reversed-Phase/Normal-Phase HPTLC Technique with Univariate Calibration for the Determination of Trans-Resveratrol
Authors: Alam Prawez , Shakeel Faiyaz , Alqarni Mohammed H. , Foudah Ahmed I. , Ghoneim Mohammed M. , Alshehri Sultan
Published: October 2021

The rapid, highly-sensitive and ecologically greener reversed-phase (RP)/normal-phase (NP) high-performance thin-layer chromatography (HPTLC) densitometric technique has been developed and validated for the determination of trans-resveratrol (TRV). The reversed-phase HPTLC-based analysis of TRV was performed using ethanol–water (65:35, v v−1) combination as the greener mobile phase, while, the normal-phase HPTLC-based estimation of TRV was performed using chloroform–methanol (85:15, v v−1) combination as the routine mobile phase. The TRV detection was carried out at 302 nm for RP/NP densitometric assay. The linearity was recorded as 10–1200 and 30–400 ng band−1 for RP and NP HPTLC techniques, respectively. The RP densitometric assay was observed as highly-sensitive, accurate, precise and robust for TRV detection in comparison with the NP densitometric assay. The contents of TRV in commercial formulation were recorded as 101.21% utilizing the RP densitometric assay, while, the contents of TRV in commercial formulation were found to be 91.64% utilizing the NP densitometric assay. The greener profile of RP/NP technique was obtained using the analytical GREEnness (AGREE) approach. The AGREE scales for RP and NP densitometric assays were estimated 0.75 and 0.48, respectively. The recorded AGREE scale for the RP densitometric assay indicated that this technique was highly green/the ecologically greener compared to the NP densitometric assay. After successful optimization of analytical conditions, validation parameters, AGREE scale and chromatography performance, the RP densitometric assay with univariate calibration was found to be better than the NP densitometric assay for the analysis of TRV.
Self-Compassion and Empathy as Predictors of Happiness among Late Adolescents
Authors: Inam Attiya , Fatima Hafsa , Naeem Hira , Mujeeb Hamna , Khatoon Roquyya , Wajahat Tallat , Andrei Liviu Catalin , Starčević Slađana , Sher Farooq
Published: October 2021

Happiness is a fundamental characteristic of life, helping individuals to become healthy and productive members of society. Pakistan has been ranked as the 67th happiest country out of 156 countries in the world. Self-compassion (SC) and empathy are considered some of the finest emotions and moral values of human beings leading to a happier life. This is the first study in South Asia that examined self-compassion as a moderator between empathy and happiness. Furthermore, we also determined self-compassion and empathy as predictors of happiness among late adolescents. Data collected from 566 students, selected randomly from different educational institutions in Lahore, suggested that self-compassion (r = 0.273) and empathy (r = 0.131) had a significant positive relationship with happiness. Self-compassion and empathy both significantly predicted happiness. Male adolescents had slightly higher self-compassion and mindfulness than females. Self-compassion (F (3, 562) = 29.74, p = 0.000) was found to significantly moderate the relationship between empathy and happiness. Self-compassion can be highly beneficial to relate to oneself, specifically for adolescents who are involved in developing their identities and self-worth, and it makes their transition from adolescence to adulthood easy.