bluuebunny/crossref_metadata_2025 huggingface dataset:
L-Menthol-Loadable Electrospun Fibers of PMVEMA Anhydride for Topical Administration
Authors: Mira Amalia , Rubio-Camacho Marta , Alarcón David , Rodríguez-Cañas Enrique , Fernández-Carvajal Asia , Falco Alberto , Mallavia Ricardo
Published: November 2021

Poly(methyl vinyl ether-alt-maleic anhydride) (PMVEMA) of 119 and 139 molecular weights (P119 and P139, respectively) were electrospun to evaluate the resulting fibers as a topical delivery vehicle for (L-)menthol. Thus, electrospinning parameters were optimized for the production of uniform bead-free fibers from 12% w/w PMVEMA (±2.3% w/w menthol) solutions, and their morphology and size were characterized by field emission scanning electron microscopy (FESEM). The fibers of P119 (F119s) and P139 (F139s) showed average diameter sizes of approximately 534 and 664 nm, respectively, when unloaded, and 837 and 1369 nm when loaded with menthol. The morphology of all types of fibers was cylindrical except for F139s, which mostly displayed a double-ribbon-like shape. Gas chromatography-mass spectrometry (GC-MS) analysis determined that not only was the menthol encapsulation efficiency higher in F139s (92% versus 68% in F119s) but also that its stability over time was higher, given that in contrast with F119s, no significant losses in encapsulated menthol were detected in the F139s after 10 days post-production. Finally, in vitro biological assays showed no significant induction of cytotoxicity for any of the experimental fibers or in the full functionality of the encapsulated menthol, as it achieved equivalent free-menthol levels of activation of its specific receptor, the (human) transient receptor potential cation channel subfamily M (melastatin) member 8 (TRPM8).
Preparation and Evaluation of a Powdered Rebamipide Mouthwash as In-Hospital Formulation: Considering Dispersion before Use in Patients
Authors: Ishii Naoko , Mizobuchi Senri , Kawano Yayoi , Hanawa Takehisa
Published: November 2021

In Japan, rebamipide (RB) mouthwash (RB-MW) for oral mucositis induced by cancer chemotherapy has been prepared using in-hospital formulation. Usually, RB-MW is prepared by dispersing crushed commercial RB tablets in the dispersion medium; however, uniformity is difficult to obtain due to low solubility. The current study aims is to prepare homogenously dispersed formulations using the fine particles of crushed tablets by a method that is convenient for hospital use. Commercial RB tablets were pre-milled at different milling times as “RB-Ts”. A ground mixture was then prepared by co-grinding the RB-Ts with HPC-L or PVP K30 via a benchtop ball milling machine (MM400). The physicochemical properties of samples were evaluated for PXRD, FTIR, turbidity, particle size, and solubility. Although the milling of RB tablets decreased the crystallinity, the length of milling time did not affect them. In contrast, grinding using MM400 significantly decreased RB crystallinity; their PXRD patterns showed a halo, suggesting the amorphization of RB crystals by grinding. Although solubility and turbidity seemed to be affected by the type of polymer rather than the particle size, every ground mixture showed high dispersibility. Thus, grinding the RB-Ts with polymers appeared to be the most promising way to obtain stable dispersion as an in-hospital formulation.
Microfluidic Production of Polymeric Core-Shell Microspheres for the Delayed Pulsatile Release of Bovine Serum Albumin as a Model Antigen
Authors: van der Kooij Renée S. , Steendam Rob , Zuidema Johan , Frijlink Henderik W. , Hinrichs Wouter L. J.
Published: November 2021

For many vaccines, multiple injections are required to confer protective immunity against targeted pathogens. These injections often consist of a primer administration followed by a booster administration of the vaccine a few weeks or months later. A single-injection vaccine formulation that provides for both administrations could greatly improve the convenience and vaccinee’s compliance. In this study, we developed parenterally injectable core-shell microspheres with a delayed pulsatile release profile that could serve as the booster in such a vaccine formulation. These microspheres contained bovine serum albumin (BSA) as the model antigen and poly(dl-lactide-co-glycolide) (PLGA) with various dl-lactide:glycolide monomer ratios as the shell material. Highly monodisperse particles with different particle characteristics were obtained using a microfluidic setup. All formulations exhibited a pulsatile in vitro release of BSA after an adjustable lag time. This lag time increased with the increasing lactide content of the polymer and ranged from 3 to 7 weeks. Shell thickness and bovine serum albumin loading had no effect on the release behavior, which could be ascribed to the degradation mechanism of the polymer, with bulk degradation being the main pathway. Co-injection of the core-shell microspheres together with a solution of the antigen that serves as the primer would allow for the desired biphasic release profile. Altogether, these findings show that injectable core-shell microspheres combined with a primer are a promising alternative for the current multiple-injection vaccines.
Targeting of Inhaled Therapeutics to the Small Airways: Nanoleucine Carrier Formulations
Authors: Miller Danforth P. , Tarara Thomas E. , Weers Jeffry G.
Published: November 2021

Current dry powder formulations for inhalation deposit a large fraction of their emitted dose in the upper respiratory tract where they contribute to off-target adverse effects and variability in lung delivery. The purpose of the current study is to design a new formulation concept that more effectively targets inhaled dry powders to the large and small airways. The formulations are based on adhesive mixtures of drug nanoparticles and nanoleucine carrier particles prepared by spray drying of a co-suspension of leucine and drug particles from a nonsolvent. The physicochemical and aerosol properties of the resulting formulations are presented. The formulations achieve 93% lung delivery in the Alberta Idealized Throat model that is independent of inspiratory flow rate and relative humidity. Largely eliminating URT deposition with a particle size larger than solution pMDIs is expected to improve delivery to the large and small airways, while minimizing alveolar deposition and particle exhalation.
An Understanding of the Drivers of Infectious Diseases in the Modern World Can Aid Early Control of Future Pandemics
Authors: Aremu Taiwo Opeyemi , Oluwole Oluwatosin Esther , Adeyinka Kehinde Oluwatosin
Published: November 2021

Infectious diseases have been a significant challenge to health and wellbeing from ancient times, with substantial economic implications globally. Despite the advent of technology, infectious diseases continue to affect people of various social statuses and across geographical locations. Understanding some of the drivers of infectious diseases, antimicrobial resistance, vaccination, and vaccine hesitancy is a step towards thriving in the modern world, achieving fewer morbidities and mortalities, and adequately controlling future pandemics. Pharmacists are strategically placed as healthcare team members to promote early disease control through health education, advocacy, cross-professional and specialty collaboration, communal trust-building, research, and global unity. Not forgetting that infectious diseases in the modern world are about people and science, credible crisis communication during the early phases of disease outbreaks paves the way for well-informed guidance globally.
Gain-Assisted Optical Pulling Force on Plasmonic Graded Nano-Shell with Equivalent Medium Theory
Authors: Wu Yamin , Huang Yang , Ma Pujuan , Gao Lei
Published: November 2021

The tunable optical pulling force on a graded plasmonic core-shell nanoparticle consisting of a gain dielectric core and graded plasmonic shell is investigated in the illumination of a plane wave. In this paper, the electrostatic polarizability and the equivalent permittivity of the core-shell sphere are derived and the plasmonic enhanced optical pulling force in the antibonding and bonding dipole modes of the graded nanoparticle are demonstrated. Additionally, the resonant pulling force occurring on the dipole mode is shown to be dependent on the aspect ratio of the core-shell particle, which is illustrated by the obtained equivalent permittivity. This shows that the gradation of the graded shell will influence the plasmonic feature of the particle, thus further shifting the resonant optical force peaks and strengthening the pulling force. The obtained results provide an additional degree of freedom to manipulate nanoparticles and give a deep insight into light–matter interaction.
Cyanidiophyceae (Rhodophyta) Tolerance to Precious Metals: Metabolic Response to Palladium and Gold
Authors: Sirakov Maria , Palmieri Maria , Iovinella Manuela , Davis Seth J. , Petriccione Milena , di Cicco Maria Rosa , De Stefano Mario , Ciniglia Claudia
Published: November 2021

Polyextremophilic red algae, which belong to the class Cyanidiophyceae, are adapted to live in geothermal and volcanic sites. These sites often have very high concentrations of heavy and precious metals. In this study, we assessed the capacity of three strains of Galdieria (G. maxima, G. sulphuraria, and G. phlegrea) and one strain of Cyanidiumcaldarium to tolerate different concentrations of precious metals, such as palladium (Cl4K2Pd) and gold (AuCl4K) by monitoring algal growths in cultures exposed to metals, and we investigated the algae potential oxidative stress induced by the metals. This work provides further understanding of metals responses in the Cyanidiophyceae, as this taxonomic class is developed as a biological refinement tool.
Exploring the Universe of Natural Products: Recent Advances in Synthesis, Isolation and Structural Elucidation
Authors: Pollastro Federica , Minassi Alberto
Published: November 2021

Historically, plants have represented an invaluable source of compounds with complex structures and interesting pharmacological profiles [...]
Effect of Glue Spreads on the Structural Properties of Laminated Veneer Lumber from Spindleless Rotary Veneers Recovered from Short Rotation Hevea Plantation Logs
Authors: Khoo Pui San , Chin Kit Ling , Lee Chuan Li , H’ng Paik San , Hafizuddin Mohd Sahfani
Published: November 2021

Unproductive young rubber trees (15 years old) with smaller diameters (15 to 18 cm) compared to conventional rubber logs, harvested at the age of 25 years old, were selected for the production of laminated panels. Spindleless rotary veneer peeling was applied to logs from short-rotation rubber forest plantations to produce veneers for structural purposes. This raises questions about the utilization of these small-diameter logs with respect to its effect on the quality of veneer and laminated panels produced. This study examines the effect of the glue spread rates on the physical and mechanical properties of rubberwood laminated veneer lumber (LVL). Analysis of variance shows that the application of a 280 g/m2 glue spread rate significantly improved the density, water absorption and dimensional stability of rubberwood LVL. The mechanical properties of rubberwood LVL produced with a 200 g/m2 glue spread rate met the minimum requirement for the 2.1E-3100F stress class; 91.05 MPa for the modulus of rupture in the flatwise direction and 50.23 MPa for compressive strength parallel to the longitudinal axis. The modulus of elasticity in the flatwise direction of 11,189.55 MPa reached the minimum requirement for the 1.5E-2250F stress class.
Preparation and Characterization of Self-Healing Polyurethane Powder Coating Using Diels–Alder Reaction
Authors: Farshchi Negin , Gedan-Smolka Michaela , Stommel Markus
Published: November 2021

Although powder coating systems offer many environmental, ecological and energy related benefits over liquid based coatings, in the case of uretdione based polyurethane systems, high curing temperature is still an issue. On the other hand, powder coating systems make it possible to reduce the costs and enhance the process of forming complex 3D structures using the deep drawing method by pre-coated metal substrates. During this processing method, there is a probability of micro crack formation in the coated film due to strain impact on the coating layer. A powder coating with self-healing ability is an ultimate solution to face not only this kind of fraction but also any other possible ones (such as defects caused by any impact on film surface during processing, transporting or even service). Here, a single molecule that is prepared via Diels–Alder cycloaddition reaction and retro Diels–Alder cleavage reaction was utilized as a self-healing additive to achieve self-healing ability in the powder coating system that is based on a commercially available uretdione cross-linker and OH-polyester resin. Coatings were prepared through melt mixing of components in a lab mixer, milling, sieving, and then application on the metal substrate through the electrostatic spraying method. To illustrate the role of self-healing additive, various concentrations (4 and 9% wt.) in combination with different curing temperatures (80 °C to 200 °C) were investigated. Both samples containing HA showed self-healing ability at elevated temperature around 120 °C for about 30 min with acceptable roughness and surface properties. Hardness measurement of cured film as well as thermal investigation indicate the chemical reaction of HA in a cross-linked network of cross-linker and resin. In addition, using HA leads to a 40 K drop in curing temperature of the system without using any catalyst. A 2.58% improvement in hardness values at a lower curing temperature and healing time of around 12.5 min at 120 °C to recover 100% of initial scratch (more than 10 cycles) in the sample containing 9% wt. HA was observed.
Combustion of a Solid Recovered Fuel (SRF) Produced from the Polymeric Fraction of Automotive Shredder Residue (ASR)
Authors: Acha Esther , Lopez-Urionabarrenechea Alexander , Delgado Clara , Martinez-Canibano Lander , Perez-Martinez Borja Baltasar , Serras-Malillos Adriana , Caballero Blanca María , Unamunzaga Lucía , Dosal Elena , Montes Noelia , Barrenetxea-Arando Jon
Published: November 2021

The use of alternative fuels derived from residues in energy-intensive industries that rely on fossil fuels can cause considerable energy cost savings, but also significant environmental benefits by conserving non-renewable resources and reducing waste disposal. However, the switching from conventional to alternative fuels is challenging for industries, which require a sound understanding of the properties and combustion characteristics of the alternative fuel, in order to adequately adapt their industrial processes and equipment for its utilization. In this work, a solid recovered fuel (SRF) obtained from the polymeric fraction of an automotive shredder residue is tested for use as an alternative fuel for scrap preheating in an aluminium refinery. The material and chemical composition of the SRF has been extensively characterized using proximate and ultimate analyses, calorific values and thermal degradation studies. Considering the calorific value and the chlorine and mercury contents measured, the SRF can be designated as class code NCV 1; Cl 2; Hg 2 (EN ISO 21640:2021). The combustion of the SRF was studied in a laboratory-scale pilot plant, where the effects of temperature, flow, and an oxidizer were determined. The ash remaining after combustion, the collected liquid, and the generated gas phase were analysed in each test. It was observed that increasing the residence time of the gas at a high temperature allowed for a better combustion of the SRF. The oxidizer type was important for increasing the total combustion of the vapour compounds generated during the oxidation of the SRF and for avoiding uncontrolled combustion.
Analysis of the Heterogeneities of First and Second Order of Cellulose Derivatives: A Complex Challenge
Authors: Mischnick Petra , Voiges Kristin , Cuers-Dammann Julia , Unterieser Inga , Sudwischer Patrick , Wubben Anika , Hashemi Payam
Published: November 2021

The complexity of the substituent distribution in polysaccharide derivatives is discussed and defined. The challenges regarding analytical characterization that results from various interrelated categories of distributions, including molecular weight, chemical composition, and microstructure, are outlined. Due to these convoluted levels of complexity, results should always be interpreted with carefulness. Various analytical approaches which have been applied to starch and cellulose derivatives are recapped, including enzymatic, mass spectrometric, and chromatographic methods. The relation of heterogeneities of first and second order among and along the polysaccharide chains is addressed. Finally, examples of own analytical work on cellulose ethers are presented, including the MS analysis of methyl cellulose (MC) blends and fractionation studies of fully esterified MC, especially its 4-methoxybenzoates by gradient HPLC on normal phase. Preparative fractionation according to the degree of substitution (DS) allows follow-up analysis in order to get more detailed information on the substituent distribution in such sub-fractions.
Basic and Applied Research to Sustain Health, Welfare and Production of Poultry
Authors: Hess Michael
Published: November 2021

In recent years poultry meat became the main animal protein for human consumption on a global level with a continuous increase being predicted [...]
Salt-Mediated Organic Solvent Precipitation for Enhanced Recovery of Peptides Generated by Pepsin Digestion
Authors: Baghalabadi Venus , Razmi Habib , Doucette Alan
Published: November 2021

Conventional solvent-based precipitation makes it challenging to obtain a high recovery of low mass peptides. However, we previously demonstrated that the inclusion of salt ions, specifically ZnSO4, together with high concentrations of acetone, maximizes the recovery of peptides generated from trypsin digestion. We herein generalized this protocol to the rapid (5 min) precipitation of pepsin-digested peptides recovered from acidic matrices. The precipitation protocol extended to other organic solvents (acetonitrile), with high recovery from dilute peptide samples permitting preconcentration and purification. Mass spectrometry profiling of pepsin-generated peptides demonstrated that the protocol captured peptides as small as 800 u, although with a preferential bias towards recovering larger and more hydrophobic peptides. The precipitation protocol was applied to rapidly quench, concentrate, and purify pepsin-digested samples ahead of MS. Complex mixtures of yeast and plasma proteome extracts were successfully precipitated following digestion, with over 95% of MS-identified peptides observed in the pellet fraction. The full precipitation workflow—including the digestion step—can be completed in under 10 min, with direct MS analysis of the recovered peptide pellets showing exceptional protein sequence coverage.
The Impact of a Rural School-Based Solid Waste Management Project on Learners’ Perceptions, Attitudes and Understanding of Recycling
Authors: Mkhonto Busisiwe , Mnguni Lindelani
Published: November 2021

Continued environmental degradation necessitates innovative strategies to improve society’s attitude towards and understanding of recycling solid waste. Previous research has shown that school-based projects integrated into the school curriculum could effectively enhance learners’ knowledge of recycling and attitudes towards recycling. However, not much is known about the impact of such projects if they are driven by learners, particularly in under-resourced rural schools. Therefore, in the current research, we aimed to determine the impact of a school-based recycling project, integrated as practical work, on learners’ understanding of recycling, their attitude towards recycling, and the perceived impact of the project on the school environment, in an under-resourced rural school. Our findings showed that participating in a rural school-based recycling project may not enhance Grade 7 Natural Sciences learners’ perceptions of, attitudes towards, and understanding of recycling. We posit that various factors may affect the effectiveness of a recycling project. Further research is required to explore these factors further.
Atomic Metaphors, Victims, and the Contestations of Nuclear Discourse
Authors: DiNitto Rachel
Published: November 2021

Atomic metaphors permeated daily life as the world reacted to the atomic bombings of Japan and the nuclear threat of the Cold War. These metaphors reveal a widespread sense of ownership of atomic narratives and public conceptions of victimhood that are often divorced from actual nuclear victims. Japan faced the reality of the nuclear again in 2011 when three reactors at the Fukushima Daiichi Nuclear Power Plant exploded, spreading toxic radiation far and wide. Rather than turn to religion to make sense of the traumatic destruction and existential threat of this invisible force, the Japanese have processed the catastrophe through a secular discussion of victimhood. In the decade since the Fukushima accident, the discourse about victims in Japan has narrowed to emphasize the authority of the tōjisha—victims with direct experience of the disaster—to tell their story. The debate over narrative ownership has challenged the literary community, and post-disaster Japanese literature is an important site of imaginative exploration of this victimhood. Using the theories of Jean-Luc Nancy and Michael Rothberg, this article examines collective memory and the catastrophic equivalence of Hiroshima and Fukushima, as well as the Japanese terminology for victims, in order to provide insight into the struggles for ownership of atomic narratives. Rather than proposing solutions, the article interrogates the ongoing literary controversy over the victim/non-victim divide.
Indonesian Hotels’ Dynamic Capability under the Risks of COVID-19
Authors: Amar Muhammad Yunus , Syariati Alim , Ridwan Ridwan , Parmitasari Rika Dwi Ayu
Published: November 2021

The effects of COVID-19 on tourism are irreversible, with potential reductions in income, job losses, shifting working landscapes, and visible health-related fears. These adversities are reinforced in the hospitality business, particularly for hotels, the income streams of which rely on individual movements. This study investigates the process undertaken by the hotel industry in Indonesia to face the current challenges, particularly in terms of the dynamic capabilities possessed by hotel businesses. This construct discusses the potentiality of maximizing existing resources and its impact on innovation norms to leverage hotel dynamics. A total of 329 hotel managers responded to the survey, and the data were finalized by employing PLS-SEM. The findings primarily support the hypothesized direct relationships, but refute the presence of indirect relationships. The results amplify how past investments in sustainable resources are easily deployed assets during COVID-19 and create a welcoming environment for dynamic innovation among hotels during periods of change.
Deep Spatial-Spectral Subspace Clustering for Hyperspectral Images Based on Contrastive Learning
Authors: Hu Xiang , Li Teng , Zhou Tong , Peng Yuanxi
Published: November 2021

Hyperspectral image (HSI) clustering is a major challenge due to the redundant spectral information in HSIs. In this paper, we propose a novel deep subspace clustering method that extracts spatial–spectral features via contrastive learning. First, we construct positive and negative sample pairs through data augmentation. Then, the data pairs are projected into feature space using a CNN model. Contrastive learning is conducted by minimizing the distances of positive pairs and maximizing those of negative pairs. Finally, based on their features, spectral clustering is employed to obtain the final result. Experimental results gained over three HSI datasets demonstrate that our proposed method is superior to other state-of-the-art methods.
End-to-End SAR Deep Learning Imaging Method Based on Sparse Optimization
Authors: Zhao Siyuan , Ni Jiacheng , Liang Jia , Xiong Shichao , Luo Ying
Published: November 2021

Synthetic aperture radar (SAR) imaging has developed rapidly in recent years. Although the traditional sparse optimization imaging algorithm has achieved effective results, its shortcomings are slow imaging speed, large number of parameters, and high computational complexity. To solve the above problems, an end-to-end SAR deep learning imaging algorithm is proposed. Based on the existing SAR sparse imaging algorithm, the SAR imaging model is first rewritten to the SAR complex signal form based on the real-value model. Second, instead of arranging the two-dimensional echo data into a vector to continuously construct an observation matrix, the algorithm only derives the neural network imaging model based on the iteration soft threshold algorithm (ISTA) sparse algorithm in the two-dimensional data domain, and then reconstructs the observation scene through the superposition and expansion of the multi-layer network. Finally, through the experiment of simulation data and measured data of the three targets, it is verified that our algorithm is superior to the traditional sparse algorithm in terms of imaging quality, imaging time, and the number of parameters.
The Effect of Spatial Resolution and Temporal Sampling Schemes on the Measurement Error for a Moon-Based Earth Radiation Observatory
Authors: Duan Wentao , Liu Jiandong , Yan Qingyun , Ruan Haibing , Jin Shuanggen
Published: November 2021

The Moon-Based Earth Radiation Observatory (MERO) is a new platform, which is expected to advance current Earth radiation budget (ERB) research with better observations. For the instrument design of a MERO system, ascertaining the spatial resolution and sampling scheme is important. However, current knowledge about this is still limited. Here we proposed a simulation method for the MERO-measured Earth top of atmosphere (TOA) outgoing shortwave radiation (OSR) and outgoing longwave radiation (OLR) fluxes and constructed the “true” Earth TOA OSR and OLR fluxes based on the Clouds and Earth’s Radiant Energy System (CERES) data. Then we used them to reveal the effects of spatial resolution and temporal scheme (sampling interval and the temporal sampling sequence) on the measurement error of a MERO. Our results indicate that the spatial sampling error in the unit of percentage reduces linearly as the spatial resolution varies from 1000 km to 100 km; the rate is 2.5%/100 km for the Earth TOA OSR flux, which is higher than that (1%/100 km) of the TOA OLR flux. Besides, this rate becomes larger when the spatial resolution is finer than 40 km. It is also demonstrated that a sampling temporal sequence of starting time of 64 min with a sampling interval of 90 min is the optimal sampling scheme that results in the least temporal sampling error for the MERO system with a 40 km spatial resolution, note that this conclusion depends on the temporal resolution and quality of the data used to construct the “true” Earth TOA OSR and OLR fluxes. The proposed method and derived results in this study could facilitate the ascertainment of the optimal spatial resolution and sampling scheme of a MERO system under certain manufacturing budget and measurement error limit.
Harnessing the Challenges and Solutions to Improve Security Warnings: A Review
Authors: Zaaba Zarul Fitri , Lim Xin Yi Christine , Amran Ammar , Omar Mohd Adib
Published: November 2021

The security warning is a representation of communication that is used to warn and to inform a person whether security menaces have been discovered in order to prevent any consequences of damage from taking place. The purpose of a security warning is to provide a legitimate alert (to notify and to warn) to the users so that a secure manner of action is safely conducted. It is worth noting that the majority of computer users prefer to dismiss security warnings due to lack of attention, the use of technical words, and the deficiency of information provided. This paper determines to achieve two outcomes: firstly, a thorough review of problems, challenges, and approaches to improving security warnings. Our work complements the previous classifications in the identification of problems and challenges in security warnings by value-adding a new classification, namely immersion in the primary task. Then, we add other related works within the known classifications accordingly. In addition, our work also presents the classifications of approaches to improving security warnings. Secondly, we propose two timelines by addressing the problems, challenges, and approaches to improving security warnings. It is expected that the outcomes of this research will be useful to researchers within the niche area for analysing trends and providing the groundwork in security warning studies, respectively.
Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
Authors: Hou Huiling , Yang Zhiliang , Pang Cunsuo
Published: November 2021

The micro-Doppler signal generated by the rotors of an Unmanned Aerial Vehicle (UAV) contains the structural features and motion information of the target, which can be used for detection and classification of the target, however, the standard STFT has the problems such as the lower time-frequency resolution and larger error in rotor parameter estimation, an FRFT (Fractional Fourier Transform)-FSST (STFT based synchrosqueezing)-based method for micro-Doppler signal detection and parameter estimation is proposed in this paper. Firstly, the FRFT is used in the proposed method to eliminate the influence of the velocity and acceleration of the target on the time-frequency features of the echo signal from the rotors. Secondly, the higher time-frequency resolution of FSST is used to extract the time-frequency features of micro-Doppler signals. Moreover, the specific solution methodologies for the selection of window length in STFT and the estimation of rotor parameters are given in the proposed method. Finally, the effectiveness and accuracy of the proposed method for target detection and rotor parameter estimation are verified through simulation and measured data.
Applications of Pose Estimation in Human Health and Performance across the Lifespan
Authors: Stenum Jan , Cherry-Allen Kendra M. , Pyles Connor O. , Reetzke Rachel D. , Vignos Michael F. , Roemmich Ryan T.
Published: November 2021

The emergence of pose estimation algorithms represents a potential paradigm shift in the study and assessment of human movement. Human pose estimation algorithms leverage advances in computer vision to track human movement automatically from simple videos recorded using common household devices with relatively low-cost cameras (e.g., smartphones, tablets, laptop computers). In our view, these technologies offer clear and exciting potential to make measurement of human movement substantially more accessible; for example, a clinician could perform a quantitative motor assessment directly in a patient’s home, a researcher without access to expensive motion capture equipment could analyze movement kinematics using a smartphone video, and a coach could evaluate player performance with video recordings directly from the field. In this review, we combine expertise and perspectives from physical therapy, speech-language pathology, movement science, and engineering to provide insight into applications of pose estimation in human health and performance. We focus specifically on applications in areas of human development, performance optimization, injury prevention, and motor assessment of persons with neurologic damage or disease. We review relevant literature, share interdisciplinary viewpoints on future applications of these technologies to improve human health and performance, and discuss perceived limitations.
A New Variance-Covariance Matrix for Improving Positioning Accuracy in High-Speed GPS Receivers
Authors: Rahemi Narjes , Mosavi Mohammad Reza , Martín Diego
Published: November 2021

One of the main challenges in using GPS is reducing the positioning accuracy in high-speed conditions. In this contribution, by considering the effect of spatial correlation between observations in estimating the covariances, we propose a model for determining the variance–covariance matrix (VCM) that improves the positioning accuracy without increasing the computational load. In addition, we compare the performance of the extended Kalman filter (EKF) and unscented Kalman filter (UKF) combined with different dynamic models, along with the proposed VCM in GPS positioning at high speeds. To review and test the methods, we used six motion scenarios with different speeds from medium to high and examined the positioning accuracy of the methods and some of their statistical characteristics. The simulation results demonstrate that the EKF algorithm based on the Gauss–Markov model, along with the proposed VCM (based on the sinusoidal function and considering spatial correlations), performs better and provides at least 30% improvement in the positioning, compared to the other methods.
Study of Building Safety Monitoring by Using Cost-Effective MEMS Accelerometers for Rapid After-Earthquake Assessment with Missing Data
Authors: Lin Jian-Fu , Li Xue-Yan , Wang Junfang , Wang Li-Xin , Hu Xing-Xing , Liu Jun-Xiang
Published: November 2021

Suffering from structural deterioration and natural disasters, the resilience of civil structures in the face of extreme loadings inevitably drops, which may lead to catastrophic structural failure and presents great threats to public safety. Earthquake-induced extreme loading is one of the major reasons behind the structural failure of buildings. However, many buildings in earthquake-prone areas of China lack safety monitoring, and prevalent structural health monitoring systems are generally very expensive and complicated for extensive applications. To facilitate cost-effective building-safety monitoring, this study investigates a method using cost-effective MEMS accelerometers for buildings’ rapid after-earthquake assessment. First, a parameter analysis of a cost-effective MEMS sensor is conducted to confirm its suitability for building-safety monitoring. Second, different from the existing investigations that tend to use a simplified building model or small-scaled frame structure excited by strong motions in laboratories, this study selects an in-service public building located in a typical earthquake-prone area after an analysis of earthquake risk in China. The building is instrumented with the selected cost-effective MEMS accelerometers, characterized by a low noise level and the capability to capture low-frequency small-amplitude dynamic responses. Furthermore, a rapid after-earthquake assessment scheme is proposed, which systematically includes fast missing data reconstruction, displacement response estimation based on an acceleration response integral, and safety assessment based on the maximum displacement and maximum inter-story drift ratio. Finally, the proposed method is successfully applied to a building-safety assessment by using earthquake-induced building responses suffering from missing data. This study is conducive to the extensive engineering application of MEMS-based cost-effective building monitoring and rapid after-earthquake assessment.
Predicting Popularity of Video Streaming Services with Representation Learning: A Survey and a Real-World Case Study
Authors: Sá Sidney Loyola de , Rocha Antonio A. de A. , Paes Aline
Published: November 2021

The Internet’s popularization has increased the amount of content produced and consumed on the web. To take advantage of this new market, major content producers such as Netflix and Amazon Prime have emerged, focusing on video streaming services. However, despite the large number and diversity of videos made available by these content providers, few of them attract the attention of most users. For example, in the data explored in this article, only 6% of the most popular videos account for 85% of total views. Finding out in advance which videos will be popular is not trivial, especially given many influencing variables. Nevertheless, a tool with this ability would be of great value to help dimension network infrastructure and properly recommend new content to users. In this way, this manuscript examines the machine learning-based approaches that have been proposed to solve the prediction of web content popularity. To this end, we first survey the literature and elaborate a taxonomy that classifies models according to predictive features and describes state-of-the-art features and techniques used to solve this task. While analyzing previous works, we saw an opportunity to use textual features for video prediction. Thus, additionally, we propose a case study that combines features acquired through attribute engineering and word embedding to predict the popularity of a video. The first approach is based on predictive attributes defined by resource engineering. The second takes advantage of word embeddings from video descriptions and titles. We experimented with the proposed techniques in a set of videos from GloboPlay, the largest provider of video streaming services in Latin America. A combination of engineering features and embeddings using the Random Forest algorithm achieved the best result, with an accuracy of 87%.
Pollution and Weather Reports: Using Machine Learning for Combating Pollution in Big Cities
Authors: Popa Cicerone Laurentiu , Dobrescu Tiberiu Gabriel , Silvestru Catalin-Ionut , Firulescu Alexandru-Cristian , Popescu Constantin Adrian , Cotet Costel Emil
Published: November 2021

Air pollution has become the most important issue concerning human evolution in the last century, as the levels of toxic gases and particles present in the air create health problems and affect the ecosystems of the planet. Scientists and environmental organizations have been looking for new ways to combat and control the air pollution, developing new solutions as technologies evolves. In the last decade, devices able to observe and maintain pollution levels have become more accessible and less expensive, and with the appearance of the Internet of Things (IoT), new approaches for combating pollution were born. The focus of the research presented in this paper was predicting behaviours regarding the air quality index using machine learning. Data were collected from one of the six atmospheric stations set in relevant areas of Bucharest, Romania, to validate our model. Several algorithms were proposed to study the evolution of temperature depending on the level of pollution and on several pollution factors. In the end, the results generated by the algorithms are presented considering the types of pollutants for two distinct periods. Prediction errors were highlighted by the RMSE (Root Mean Square Error) for each of the three machine learning algorithms used.
Phytochemical Constituents Identified from the Aerial Parts of Lespedeza cuneata and Their Effects on Lipid Metabolism during Adipocyte Maturation
Authors: Kang Heesun , Yoo Min , Yi Sang , Kim Tae , Ha Ji , Na Myung , Park Kun , Kim Seon-Hee , Han Jeung-Whan , Jang Tae , Kim Ki
Published: November 2021

Lespedeza cuneata, belonging to Fabaceae, is well-known as Chinese bushclover, and it has been used in traditional folk medicines for the treatment of disorders, such as diabetes, hematuria, and insomnia. As part of continuing research projects to discover interesting natural compounds with biological activities from Korean medicinal plants, the phytochemical investigation of L. cuneata resulted in the isolation of five chemical constituents: α-tocopherol (1), 7a-methoxy-α-tocopherol (2), 13(R)-hydroxy-octadeca-(9Z,11E,15Z)-trien-oic acid (3), α-dimorphecolic acid (4), and lupeol (5). The structural determination of the isolated compounds was elucidated from data gathered through nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography–mass spectrometry (LC/MS). Until now, this study is the first to report these five compounds from the plant L. cuneata. Moreover, these isolated compounds (1–5) were evaluated for their anti-adipogenesis effects and their role in lipid metabolism during adipocyte maturation. As a result, the upregulation of mRNA expression levels of Fabp4 from 3T3-L1 pre-adipocytes treated with compounds 3 and 4 demonstrated that these compounds efficiently induced adipocyte differentiation. Furthermore, compounds 3 and 4 were found to regulate lipid metabolism by the induction of lipolytic and of lipogenic gene expressions. Therefore, experimental data from these findings supported that the compounds 3 and 4 induce the adipogenesis of 3T3-L1 pre-adipocytes and regulate lipid metabolism.
Alternative Method for HDL and Exosome Isolation with Small Serum Volumes and Their Characterizations
Authors: Praja Rian Ka , Phoksawat Wisitsak , Tippayawat Patcharaporn , Jumnainsong Amonrat , Leelayuwat Chanvit
Published: November 2021

High-density lipoprotein (HDL) and exosomes are promising sources of biomarkers. However, the limited sample volume and access to the ultracentrifuge equipment are still an issue during HDL and exosome isolation. This study aimed to isolate HDL and exosomes using an ultracentrifugation-free method with various small serum volumes. HDL was isolated from 200 µL (HDL200) and 500 µL (HDL500) of sera. Three different volumes: 50 µL (Exo50), 100 µL (Exo100), and 250 µL (Exo250) were used for exosome isolation. HDL and exosomes were isolated using commercial kits with the modified method and characterized by multiple approaches. The HDL levels of HDL200 and HDL500 were not significantly different (p > 0.05), with percent recoveries of >90%. HDL200 and HDL500 had the same protein pattern with a biochemical similarity of 99.60 ± 0.10%. The particle sizes of Exo50, Exo100, and Exo250 were in the expected range. All isolated exosomes exhibited a similar protein pattern with a biochemical similarity of >99%. In conclusion, two different serum volumes (200 and 500 µL) and three different serum volumes (50, 100, and 250 µL) can be employed for HDL and exosome isolation, respectively. The possibility of HDL and exosome isolation with small volumes will accelerate biomarker discoveries with various molecular diagnostic approaches.
New Perspectives on the Community Impact of Rural Education Deserts
Authors: Park Paige N. , Sanders Scott R. , Cope Michael R. , Muirbrook Kayci A. , Ward Carol
Published: November 2021

Understanding how the lack of higher education opportunities due to geographic distance affects perceptions of communities and education is essential in creating sustainable education systems in rural areas. More specifically, this research examines how geographic distance and the absence of institutes, sometimes called an education desert, affect perceptions of community and the perceived value of education. We used data from the 2017 Rural Utah Community Study (RUCS) of residents living in twenty-five rural communities, with a sample size of 1286, and found that the proximity to different types of higher education, four- and two-year institutions, can significantly influence community well-being and the perceived value of education.
Resource Efficiency and Circular Economy in European SMEs: Investigating the Role of Green Jobs and Skills
Authors: Bassi Francesca , Guidolin Mariangela
Published: November 2021

This study explored the size and potential of green employment for circular economy (CE) in small and medium enterprises (SMEs) in the European Union, and investigated the role of green jobs and skills for the implementation of CE practices. The data were collected in a Eurobarometer survey, and refer to resource efficiency, green markets, and CE procedures. Lack of environmental expertise is one of the factors that might be perceived as an obstacle when trying to implement resource-efficiency actions. Previous research has shown that, although resource-efficiency practices are adopted by firms in all European countries, there are differences both within and between countries. The analysis of the determinants of green behavior by European SMEs was completed by a study of heterogeneity across firms and within countries with a multilevel latent class model, a hierarchical clustering method. A general important observation is that having no workers dedicated to green jobs is strongly correlated to the probability of adopting resource-efficiency practices, while perceiving the need of extra environmental skills has a positive effect on the intention to implement actions in the future. Other characteristics of the firms play a significant impact on resource efficiency: in general, older and bigger firms, with larger yearly turnover, are more prone to implement actions.
Can Green Finance Development Reduce Carbon Emissions? Empirical Evidence from 30 Chinese Provinces
Authors: Chen Xi , Chen Zhigang
Published: November 2021

Dealing with the relationship between environment and economic development is the core issue of China’s sustainable development. At present, China’s economic transformation is urgent, and green finance is being widely concerned. This paper measured the development level of China’s green finance from the perspective of green credit, green securities, green investment, and green insurance. Then, it used a spatial dynamic panel model to empirically test the mechanism of the impact of green finance on carbon emissions with panel data of 30 Chinese provinces from 2005 to 2018. The following can be seen from the results: (1) The development of green finance contributes to carbon emission reduction. (2) The spatial spillover effect of green finance is significant. Specifically, the development of green finance can not only reduce the carbon emissions of the local region but also inhibit that of adjacent areas. (3) The development of green finance indirectly leads to a decrease in carbon emissions by reducing financing constraints and boosting green technology innovation. In order to stimulate the carbon emission reduction effect of green finance to a greater extent, we should further support the development of green finance, reduce the financing constraints of energy-saving and environmental-protection enterprises, and encourage the research and development of green innovative technologies.
Exploring the Potential for Utilization of Medium and Highly Sulfidic Mine Tailings in Construction Materials: A Review
Authors: Martins Natalia Pires , Srivastava Sumit , Simão Francisco Veiga , Niu He , Perumal Priyadharshini , Snellings Ruben , Illikainen Mirja , Chambart Hilde , Habert Guillaume
Published: November 2021

Medium and highly sulfidic tailings are high-volume wastes that can lead to severe environmental damage if not properly managed. Due to the high content of sulfide minerals, these tailings can undergo weathering if put in contact with oxygen and water, generating acid mine drainage (AMD). The moderate-to-high sulfide content is also an important technical limitation for their implementation in the production of construction materials. This paper reviews the use of sulfidic tailings as raw material in construction products, with a focus on cement, concrete, and ceramics. When used as aggregates in concrete, this can lead to concrete degradation by internal sulfate attack. In building ceramics, their implementation without prior treatment is undesirable due to the formation of black reduction core, efflorescence, SOx emissions, and their associated costs. Moreover, their intrinsic low reactivity represents a barrier for their use as supplementary cementitious materials (SCMs) and as precursors for alkali-activated materials (AAMs). Nevertheless, the production of calcium sulfoaluminate (CSA) cement can be a suitable path for the valorization of medium and highly sulfidic tailings. Otherwise difficult to upcycle, sulfidic tailings could be used in the clinker raw meal as an alternative raw material. Not only the SO3 and SiO2-rich bulk material is incorporated into reactive clinker phases, but also some minor constituents in the tailings may contribute to the production of such low-CO2 cements at lower temperatures. Nevertheless, this valorization route remains poorly explored and demands further research.