bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis, Characterization, and Bactericidal Activity of a 4-Ammoniumbuthylstyrene-Based Random Copolymer
Authors: Alfei Silvana , Piatti Gabriella , Caviglia Debora , Schito Anna
Published: April 2021

The growing resistance of bacteria to current chemotherapy is a global concern that urgently requires new and effective antimicrobial agents, aimed at curing untreatable infection, reducing unacceptable healthcare costs and human mortality. Cationic polymers, that mimic antimicrobial cationic peptides, represent promising broad-spectrum agents, being less susceptible to develop resistance than low molecular weight antibiotics. We, thus, designed, and herein report, the synthesis and physicochemical characterization of a water-soluble cationic copolymer (P5), obtained by copolymerizing the laboratory-made monomer 4-ammoniumbuthylstyrene hydrochloride with di-methyl-acrylamide as uncharged diluent. The antibacterial activity of P5 was assessed against several multi-drug-resistant clinical isolates of both Gram-positive and Gram-negative species. Except for strains characterized by modifications of the membrane charge, most of the tested isolates were sensible to the new molecule. P5 showed remarkable antibacterial activity against several isolates of genera Enterococcus, Staphylococcus, Pseudomonas, Klebsiella, and against Escherichia coli, Acinetobacter baumannii and Stenotrophomonas maltophilia, displaying a minimum MIC value of 3.15 µM. In time-killing and turbidimetric studies, P5 displayed a rapid non-lytic bactericidal activity. Due to its water-solubility and wide bactericidal spectrum, P5 could represent a promising novel agent capable of overcoming severe infections sustained by bacteria resistant the presently available antibiotics.
Effects of Dentine Pretreatment Solutions Containing Flavonoids on the Resin Polymer-Dentine Interface Created Using a Modern Universal Adhesive
Authors: Dávila-Sánchez Andrés , Gutierrez Mario Felipe , Bermudez Jorge Pailover , Méndez-Bauer Luján , Pulido Camilo , Kiratzc Fagner , Alegria-Acevedo Luisa Fernanda , Farago Paulo Vitor , Loguercio Alessandro Dourado , Sauro Salvatore , Arrais Cesar Augusto Galvão
Published: April 2021

The aim of the present study was to evaluate the influence of several experimental pretreatment crosslinker solutions on the resin polymer–dentine interface created using a representative universal adhesive system, by means of microtensile bond strength testing (μTBS), nanomechanical properties and ultramorphology confocal laser scanning microscopy (CLSM). Five experimental solutions containing different flavonoids were applied as dentine pretreatment after acid etching. A control pretreatment group containing no flavonoid was also employed. A representative modern universal adhesive was then applied, followed by a 3 mm thick composite built up. Specimens were sectioned into sticks and submitted to a μTBS test or nanoindentation analysis along the interface (24 h or 25,000 thermocycles). The ultramorphology of the polymer–resin interface was also evaluated using CLSM. The results were analyzed using two-way ANOVA and Bonferroni’s post hoc test (α = 0.05). All flavonoids improved short- and long-term μTBS values (p < 0.01), while only some specific such solutions improved the nanomechanical properties (p < 0.05) and preserved the structural morphology of the interface after aging. Pretreatment of acid-etched dentine using specific flavonoid-containing solutions may be a promising approach to improve both the nanomechanical properties and the durability of modern universal adhesive systems.
Spider Web-Inspired Lightweight Membrane-Type Acoustic Metamaterials for Broadband Low-Frequency Sound Isolation
Authors: Huang Heyuan , Cao Ertai , Zhao Meiying , Alamri Sagr , Li Bing
Published: April 2021

Membrane-type acoustic metamaterial (MAM) has exhibited superior sound isolation properties, as well as thin and light characteristics. However, the anti-resonance modes of traditional MAMs are generated intermittently in a wide frequency range causing discontinuities in the anti-resonance modes. Achieving broadband low-frequency sound attenuation with lightweight MAM design is still a pivotal research aspect. Here, we present a strategy to realize wide sound-attenuation bands in low frequency range by introducing the design concept of bionic configuration philosophy into the MAM structures. Built by a polymeric membrane and a set of resonators, two kinds of MAM models are proposed based on the insight of a spider web topology. The sound attenuation performance and physical mechanisms are numerically and experimentally investigated. Multi-state anti-resonance modes, induced by the coupling of the bio-inspired arrangement and the host polymer film, are systematically explored. Significant sound attenuation is numerically and experimentally observed in both the lightweight bio-inspired designs. Remarkably, compared with a traditional MAM configuration, a prominent enhancement in both attenuation bandwidth and weight-reduction performance is verified. In particular, the bio-inspired MAM Model I exhibits a similar isolation performance as the reference model, but the weight is reduced by nearly half. The bio-inspired Model II broadens the sound attenuation bandwidth greatly; meanwhile, it retains a lighter weight design. The proposed bio-inspired strategies provide potential ways for designing sound isolation devices with both high functional and lightweight performance.
Experimental Characterization Framework for SLA Additive Manufacturing Materials
Authors: Martín-Montal Jordi , Pernas-Sánchez Jesus , Varas David
Published: April 2021

Additive manufacturing (AM) is driving a change in the industry not only regarding prototyping but due to the ease of including printed parts in final designs. Engineers and designers can go deeper into optimization and improvements of their designs without drawbacks of long manufacturing times. However, some drawbacks such as the limited available materials or uncertainty about mechanical properties and anisotropic behavior of 3D printed parts prevent use in large-scale production. To gain knowledge and confidence about printed materials it is necessary to know how they behave under different stress states and strain-rate regimes, and how some of the printing parameters may affect them. The present work proposes an experimental methodology framework to study and characterize materials printed by stereolithography (SLA) to clarify certain aspects that must be taken into account to broaden the use of this kind of material. To this end, tensile and compression tests at different strain rates were carried out. To study the influence of certain printing parameters on the printed material behavior, samples with different printing angles (θ = [0–90]) and different printing resolution (layer height of 50 and 100 µm) were tested. In addition, the effects of curing time and temperature were also studied. The testing specimens were manufactured in the non-professional SLA machine Form 2 from Formlabs® using resin called Durable. Nevertheless, the proposed experimental methodology could be extended to any other resin.
Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer
Authors: Said Mokhtar , Shaheen Abdullah M. , Ginidi Ahmed R. , El-Sehiemy Ragab A. , Mahmoud Karar , Lehtonen Matti , Darwish Mohamed M. F.
Published: April 2021

Recently, the use of diverse renewable energy resources has been intensively expanding due to their technical and environmental benefits. One of the important issues in the modeling and simulation of renewable energy resources is the extraction of the unknown parameters in photovoltaic models. In this regard, the parameters of three models of photovoltaic (PV) cells are extracted in this paper with a new optimization method called turbulent flow of water-based optimization (TFWO). The applications of the proposed TFWO algorithm for extracting the optimal values of the parameters for various PV models are implemented on the real data of a 55 mm diameter commercial R.T.C. France solar cell and experimental data of a KC200GT module. Further, an assessment study is employed to show the capability of the proposed TFWO algorithm compared with several recent optimization techniques such as the marine predators algorithm (MPA), equilibrium optimization (EO), and manta ray foraging optimization (MRFO). For a fair performance evaluation, the comparative study is carried out with the same dataset and the same computation burden for the different optimization algorithms. Statistical analysis is also used to analyze the performance of the proposed TFWO against the other optimization algorithms. The findings show a high closeness between the estimated power–voltage (P–V) and current–voltage (I–V) curves achieved by the proposed TFWO compared with the experimental data as well as the competitive optimization algorithms, thanks to the effectiveness of the developed TFWO solution mechanism.
Special Issue “Green Synthesis Processes of Polymers & Composites”
Authors: Kali Gergely , Bhowmick Anil K.
Published: April 2021

Undoubtedly, polymers and composites are the most important materials in the late XXth and early XXIst century [...]
Co-Creation Facilitates Translational Research on Upper Limb Prosthetics
Authors: Jones Hannah , Dupan Sigrid , Coutinho Maxford , Day Sarah , Desmond Deirdre , Donovan-Hall Margaret , Dyson Matthew , Ekins-Coward Thea , Kenney Laurence , Krasoulis Agamemnon , McIntosh Doug , Memarzadeh Kaveh , Small Edward , Wheeler Gemma , Wu Hancong , Nazarpour Kianoush
Published: April 2021

People who either use an upper limb prosthesis and/or have used services provided by a prosthetic rehabilitation centre, hereafter called users, are yet to benefit from the fast-paced growth in academic knowledge within the field of upper limb prosthetics. Crucially over the past decade, research has acknowledged the limitations of conducting laboratory-based studies for clinical translation. This has led to an increase, albeit rather small, in trials that gather real-world user data. Multi-stakeholder collaboration is critical within such trials, especially between researchers, users, and clinicians, as well as policy makers, charity representatives, and industry specialists. This paper presents a co-creation model that enables researchers to collaborate with multiple stakeholders, including users, throughout the duration of a study. This approach can lead to a transition in defining the roles of stakeholders, such as users, from participants to co-researchers. This presents a scenario whereby the boundaries between research and participation become blurred and ethical considerations may become complex. However, the time and resources that are required to conduct co-creation within academia can lead to greater impact and benefit the people that the research aims to serve.
Multitemporal InSAR Coherence Analysis and Methods for Sand Mitigation
Authors: Manzoni Marco , Molinari Monia Elisa , Monti-Guarnieri Andrea
Published: April 2021

Dunes and sand sheets motion natural hazard affect many desertic areas worldwide and require careful assessment to develop effective mitigation plans to protect populated sites, infrastructure, and human activities. The study explores the suitability of Synthetic Aperture Radar (SAR) coherent methods to detect desert area instabilities and estimate sand accumulations displacements. The SAR methods have been applied to long time series of images provided by Sentinel-1. Moreover, the research introduces a novel robust index, named Temporal Stability Index, able to characterize the percentage of stability of a target with time. The work reports the experiments performed on the United Arab Emirates (UAE) and Egypt desertic areas and proves the usefulness of SAR coherent methods to support sand mitigation measures.
Dimensionality Reduction of Hyperspectral Image Based on Local Constrained Manifold Structure Collaborative Preserving Embedding
Authors: Shi Guangyao , Luo Fulin , Tang Yiming , Li Yuan
Published: April 2021

Graph learning is an effective dimensionality reduction (DR) manner to analyze the intrinsic properties of high dimensional data, it has been widely used in the fields of DR for hyperspectral image (HSI) data, but they ignore the collaborative relationship between sample pairs. In this paper, a novel supervised spectral DR method called local constrained manifold structure collaborative preserving embedding (LMSCPE) was proposed for HSI classification. At first, a novel local constrained collaborative representation (CR) model is designed based on the CR theory, which can obtain more effective collaborative coefficients to characterize the relationship between samples pairs. Then, an intraclass collaborative graph and an interclass collaborative graph are constructed to enhance the intraclass compactness and the interclass separability, and a local neighborhood graph is constructed to preserve the local neighborhood structure of HSI. Finally, an optimal objective function is designed to obtain a discriminant projection matrix, and the discriminative features of various land cover types can be obtained. LMSCPE can characterize the collaborative relationship between sample pairs and explore the intrinsic geometric structure in HSI. Experiments on three benchmark HSI data sets show that the proposed LMSCPE method is superior to the state-of-the-art DR methods for HSI classification.
Improvement of Earthquake Risk Awareness and Seismic Literacy of Korean Citizens through Earthquake Vulnerability Map from the 2017 Pohang Earthquake, South Korea
Authors: Han Ju , Nur Arip , Syifa Mutiara , Ha Minsu , Lee Chang-Wook , Lee Ki-Young
Published: April 2021

Earthquake activities in and around the Korean Peninsula are relatively low in number and intensity compared with neighboring countries such as Japan and China. However, recent seismic activity caused great alarm and concern among citizens and government authorities, and uncovered the level of preparedness toward earthquake disasters. A survey has been conducted on 1256 participants to investigate the seismic literacy of Korean citizens, including seismic knowledge, awareness and management using a questionnaire of citizen earthquake literacy (CEL). The results declared that the citizens had low awareness and literacy, which means that they are not properly prepared for earthquake hazards. To develop an earthquake risk reduction plan and program efficiently and effectively, not only must it appropriately characterize the target audience, but also indicate high potential earthquake zones and potential earthquake damage. Therefore, this study mapped and analyzed the seismic vulnerability in southeast Korea using LogitBoost, logistic model tree (LMT), and logistic regression (LR) machine learning algorithms based on a building damage inventory map. The damaged buildings’ locations were generated after the 2017 Pohang earthquake using the damage proxy map (DPM) method from the Sentinel-1 synthetic aperture radar (SAR) data. DPMs detected coherence loss, which indicates damaged buildings in urban areas in the Pohang earthquake and shows a good correlation with the Korea Meteorological Administration (KMA) report with modified Mercalli intensity (MMI) scale values of more than VII (seven). The damage locations were randomly divided into two datasets: 50% for training the vulnerability models and 50% for validating the models in terms of accuracy and reliability. Fifteen seismic-related factors were used to construct a model of each algorithm. Model validation based on the area under the receiver operating curve (AUC) was used to determine model accuracy. The AUC values of seismic vulnerability maps using the LogitBoost, LMT, and LR algorithms were 0.769, 0.851, and 0.749, respectively. We suggest that earthquake preparedness efforts should focus on reconstruction, retrofitting, renovation, and seismic education in areas with high seismic vulnerability in South Korea. The results of this study are expected to be beneficial for engineers and policymakers aiming at developing disaster risk reduction plans, policies, and programs due to future seismic activity in South Korea.
Selecting Optimal Combination of Data Channels for Semantic Segmentation in City Information Modelling (CIM)
Authors: Cai Yuanzhi , Huang Hong , Wang Kaiyang , Zhang Cheng , Fan Lei , Guo Fangyu
Published: April 2021

Over the last decade, a 3D reconstruction technique has been developed to present the latest as-is information for various objects and build the city information models. Meanwhile, deep learning based approaches are employed to add semantic information to the models. Studies have proved that the accuracy of the model could be improved by combining multiple data channels (e.g., XYZ, Intensity, D, and RGB). Nevertheless, the redundant data channels in large-scale datasets may cause high computation cost and time during data processing. Few researchers have addressed the question of which combination of channels is optimal in terms of overall accuracy (OA) and mean intersection over union (mIoU). Therefore, a framework is proposed to explore an efficient data fusion approach for semantic segmentation by selecting an optimal combination of data channels. In the framework, a total of 13 channel combinations are investigated to pre-process data and the encoder-to-decoder structure is utilized for network permutations. A case study is carried out to investigate the efficiency of the proposed approach by adopting a city-level benchmark dataset and applying nine networks. It is found that the combination of IRGB channels provide the best OA performance, while IRGBD channels provide the best mIoU performance.
Spatio-Temporal Models for Vibration Monitoring of Elongated Structures Using Profile Laser Scans
Authors: Holst Christoph , Neuner Hans
Published: April 2021

Vibration monitoring is a frequent task within the general topic of Structural Health Monitoring. For this monitoring, usually accelerometers, strain gauges, fibre optic sensors or Global Navigation Satellite System (GNSS) receivers are placed on pre-selected positions on the structure and the point-wise measurements are individually processed to estimate the relevant modal parameters, for example, oscillating amplitudes and natural frequencies. If laser scanners were used for vibration monitoring, the analyses could be performed with a significantly higher spatial resolution that would be beneficial especially for locating structural weaknesses. However, to apply laser scanners rigorously to vibration monitoring, spatio-temporal models need to be set up. With this study, we develop and discuss four spatio-temporal models applied to the simulated vibration monitoring of a bridge deck. Therefore, we formulate either functional as well as stochastic connections between neighbored measurement positions within the estimation of the parameters of a harmonic oscillation. We reveal that those models allow an improved parameter estimation compared to the usually used strategies—even at lower measurement frequencies and shorter observation lengths.
Active Mapping and Robot Exploration: A Survey
Authors: Lluvia Iker , Lazkano Elena , Ansuategi Ander
Published: April 2021

Simultaneous localization and mapping responds to the problem of building a map of the environment without any prior information and based on the data obtained from one or more sensors. In most situations, the robot is driven by a human operator, but some systems are capable of navigating autonomously while mapping, which is called active simultaneous localization and mapping. This strategy focuses on actively calculating the trajectories to explore the environment while building a map with a minimum error. In this paper, a comprehensive review of the research work developed in this field is provided, targeting the most relevant contributions in indoor mobile robotics.
Baseline-Free Structural Damage Identification for Beam-Like Structures Using Curvature Waveforms of Propagating Flexural Waves
Authors: Xu Y. F. , Kim J. S.
Published: April 2021

Curvatures in mode shapes and operating deflection shapes have been extensively studied for vibration-based structural damage identification in recent decades. Curvatures of mode shapes and operating deflection shapes have proved capable of localizing and manifesting local effects of damage on mode shapes and operating deflection shapes in forms of local anomalies. The damage can be inversely identified in the neighborhoods of the anomalies that exist in the curvatures. Meanwhile, propagating flexural waves have also been extensively studied for structural damage identification and proved to be effective, thanks to their high damage-sensitivity and long range of propagation. In this work, a baseline-free structural damage identification method is developed for beam-like structures using curvature waveforms of propagating flexural waves. A multi-resolution local-regression temporal-spatial curvature damage index (TSCDI) is defined in a pointwise manner. A two-dimensional auxiliary TSCDI and a one-dimensional auxiliary damage index are developed to further assist the identification. Two major advantages of the proposed method are: (1) curvature waveforms of propagating flexural waves have relatively high signal-to-noise ratios due to the use of a multi-resolution central finite difference scheme, so that the local effects of the damage can be manifested, and (2) the proposed method does not require quantitative knowledge of a pristine structure associated with a structure to be examined, such as its material properties, waveforms of propagating flexural waves and boundary conditions. Numerical and experimental investigations of the proposed method are conducted on damaged beam-like structures, and the effectiveness of the proposed method is verified by the results of the investigations.
Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios
Authors: Verde Paula , Díez-González Javier , Ferrero-Guillén Rubén , Martínez-Gutiérrez Alberto , Perez Hilde
Published: April 2021

Local Positioning Systems (LPS) have become an active field of research in the last few years. Their application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization, or low-level flights in restricted environments. LPS consists of ad-hoc deployments of sensors which meets the design requirements of each activity. Among LPS, those based on temporal measurements are attracting higher interest due to their trade-off among accuracy, robustness, availability, and costs. The Time Difference of Arrival (TDOA) is extended in the literature for LPS applications and consequently we perform, in this paper, an analysis of the optimal sensor deployment of this architecture for achieving practical results. This is known as the Node Location Problem (NLP) and has been categorized as NP-Hard. Therefore, heuristic solutions such as Genetic Algorithms (GA) or Memetic Algorithms (MA) have been applied in the literature for the NLP. In this paper, we introduce an adaptation of the so-called MA-Solis Wets-Chains (MA-SW-Chains) for its application in the large-scale discrete discontinuous optimization of the NLP in urban scenarios. Our proposed algorithm MA-Variable Neighborhood Descent-Chains (MA-VND-Chains) outperforms the GA and the MA of previous proposals for the NLP, improving the accuracy achieved by 17% and by 10% respectively for the TDOA architecture in the urban scenario introduced.
Reconstruction of Relative Phase of Self-Transmitting Devices by Using Multiprobe Solutions and Non-Convex Optimization
Authors: Tena Sánchez Rubén , Rodríguez Varela Fernando , Foged Lars J. , Sierra Castañer Manuel
Published: April 2021

Phase reconstruction is in general a non-trivial problem when it comes to devices where the reference is not accessible. A non-convex iterative optimization algorithm is proposed in this paper in order to reconstruct the phase in reference-less spherical multiprobe measurement systems based on a rotating arch of probes. The algorithm is based on the reconstruction of the phases of self-transmitting devices in multiprobe systems by taking advantage of the on-axis top probe of the arch. One of the limitations of the top probe solution is that when rotating the measurement system arch, the relative phase between probes is lost. This paper proposes a solution to this problem by developing an optimization iterative algorithm that uses partial knowledge of relative phase between probes. The iterative algorithm is based on linear combinations of signals when the relative phase is known. Phase substitution and modal filtering are implemented in order to avoid local minima and make the algorithm converge. Several noise-free examples are presented and the results of the iterative algorithm analyzed. The number of linear combinations used is far below the square of the degrees of freedom of the non-linear problem, which is compensated by a proper initial guess. With respect to noisy measurements, the top probe method will introduce uncertainties for different azimuth and elevation positions of the arch. This is modelled by considering the real noise model of a low-cost receiver and the results demonstrate the good accuracy of the method. Numerical results on antenna measurements are also presented. Due to the numerical complexity of the algorithm, it is limited to electrically small- or medium-size problems.
Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making
Authors: Kuc Alexander , Grubov Vadim V. , Maksimenko Vladimir A. , Shusharina Natalia , Pisarchik Alexander N. , Hramov Alexander E.
Published: April 2021

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).
Detection of the Lunar Surface Soil Permittivity with Megahertz Electromagnetic Wave
Authors: Rao Qingwen , Xu Guanjun , Mao Wangchen
Published: April 2021

In this paper, the detection of the lunar surface soil permittivity with megahertz electromagnetic (EM) waves by spaceborne radar is studied based on the EM scattering theory, the Boltzmann–Shukla equations, and the improved scattering matrix method (ISMM). The reflection characteristics of the lunar surface soil subject to megahertz waves are analyzed through the EM scattering theory and expressed by the lunar surface soil permittivity. Then, the lunar ionosphere is assumed to be composed of dusty plasma, and its EM characteristics are described with the Boltzmann–Shukla equations. Finally, the transmission and reflection characteristics of the propagation of EM waves in the lunar ionosphere are numerically calculated with ISMM. Thus, the complex permittivity of lunar surface soil is obtained. In addition, the effects of detection environment situations, such as the lunar illumination intensity, characteristics of the lunar dust and dust charging process in the lunar ionosphere, on the amplitude and phase of EM waves are also investigated in this study. The simulation results show that an EM wave at a high frequency induces a strong effective wave with a stable phase shift and a significantly small interferential wave. Moreover, the lunar illumination is more effective under EM waves in low frequency bands; the characteristics of the lunar dust have a notable influence on the transmission and absorption coefficients of the effective waves. These conclusions help in real applications involving the detection of the lunar surface soil permittivity by spaceborne radar in various lunar environments.
Rule-Based Detection of False Data Injections Attacks against Optimal Power Flow in Power Systems
Authors: Umar Sani , Felemban Muhamad
Published: April 2021

Cyber-security of modern power systems has captured a significant interest. The vulnerabilities in the cyber infrastructure of the power systems provide an avenue for adversaries to launch cyber attacks. An example of such cyber attacks is False Data Injection Attacks (FDIA). The main contribution of this paper is to analyze the impact of FDIA on the cost of power generation and the physical component of the power systems. Furthermore, We introduce a new FDIA strategy that intends to maximize the cost of power generation. The viability of the attack is shown using simulations on the standard IEEE bus systems using the MATPOWER MATLAB package. We used the genetic algorithm (GA), simulated annealing (SA) algorithm, tabu search (TS), and particle swarm optimization (PSO) to find the suitable attack targets and execute FDIA in the power systems. The proposed FDIA increases the generation cost by up to 15.6%, 45.1%, 60.12%, and 74.02% on the 6-bus, 9-bus, 30-bus, and 118-bus systems, respectively. Finally, a rule-based FDIA detection and prevention mechanism is proposed to mitigate such attacks on power systems.
Actigraphic Measurement of the Upper Limbs for the Prediction of Ischemic Stroke Prognosis: An Observational Study
Authors: Reale Giuseppe , Giovannini Silvia , Iacovelli Chiara , Castiglia Stefano Filippo , Picerno Pietro , Zauli Aurelia , Rabuffetti Marco , Ferrarin Maurizio , Maccauro Giulio , Caliandro Pietro
Published: April 2021

Background: It is often challenging to formulate a reliable prognosis for patients with acute ischemic stroke. The most accepted prognostic factors may not be sufficient to predict the recovery process. In this view, describing the evolution of motor deficits over time via sensors might be useful for strengthening the prognostic model. Our aim was to assess whether an actigraphic-based parameter (Asymmetry Rate Index for the 24 h period (AR2_24 h)) obtained in the acute stroke phase could be a predictor of a 90 d prognosis. Methods: In this observational study, we recorded and analyzed the 24 h upper limb movement asymmetry of 20 consecutive patients with acute ischemic stroke during their stay in a stroke unit. We recorded the motor activity of both arms using two programmable actigraphic systems positioned on patients’ wrists. We clinically evaluated the stroke patients by NIHSS in the acute phase and then assessed them across 90 days using the modified Rankin Scale (mRS). Results: We found that the AR2_24 h parameter positively correlates with the 90 d mRS (r = 0.69, p < 0.001). Moreover, we found that an AR2_24 h > 32% predicts a poorer outcome (90 d mRS > 2), with sensitivity = 100% and specificity = 89%. Conclusions: Sensor-based parameters might provide useful information for predicting ischemic stroke prognosis in the acute phase.
Study of the Performance of DSSS UAC System Depending on the System Bandwidth and the Spreading Sequence
Authors: Kochanska Iwona , Salamon Roman , Schmidt Jan H. , Schmidt Aleksander M.
Published: April 2021

A signal transmitted in an Underwater Acoustic Communication (UAC) system operating in a shallow-water channel suffers from strong time dispersion due to multipath propagation. This causes the Inter-Symbol Interference (ISI) observed in the received signal, which significantly limits the communication system’s reliability and transmission rate. In such propagation conditions, the Direct-Sequence Spread Spectrum (DSSS) method is one of the solutions that make reliable data transmission possible. In systems with one-to-one communication, it ensures communication with a satisfactory Bit Error Rate (BER). Additionally, it makes it possible to implement the Code-Division Multiple Access (CDMA) protocol in underwater acoustic networks. This paper presents the results of simulation and experimental communication tests on a DSSS-based UAC system using three types of spreading sequence, namely m-sequences, Kasami codes and Gold codes, and occupying different bandwidths from 1 kHz to 8 kHz around a carrier frequency equal to 30 kHz. The UAC channel was simulated by impulse responses calculated by the virtual sources method and the UAC chanel models available in the Watermark simulator. The experimental tests were conducted in a model pool. Based on the obtained results, a transmission rate was estimated, which is possible to achieve in strong multipath propagation conditions, assuming reliability expressed as BER less than 0.001.
Selecting the Safest CNC Machining Workshop Using AHP and TOPSIS Approaches
Authors: Cioca Lucian-Ionel , Breaz Radu-Eugen , Racz Sever-Gabriel
Published: April 2021

Machining operations on computer numerically controlled (CNC) machine tools are essential for the machining industry. Most of these operations take place in machining workshops. Safety issues in machining workshops shops can affect not only the health of the operators, which is extremely important, but also the productivity of the process and the accuracy of the parts. The research presented in this article addresses the issue of evaluating the safety of a CNC machining workshop, using a combined approach based on the analytic hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) methods. A set of four evaluation criteria was proposed and the methods of processing the information for each criterion were used to extract the significant data needed for the evaluation. The proposed method was used to select the safest CNC machining workshop out of a total of three considered for assessment.
Cost-Effective Simultaneous Separation and Quantification of Phenolics in Green and Processed Tea Using HPLC–UV–ESI Single-Quadrupole MS Detector and Python Script
Authors: Rha Chan-Su , Choi Yun-Mi , Kim Jong-Chan , Kim Dae-Ok
Published: April 2021

Phenolic composition of green tea (Camellia sinensis) varies according to manufacturing processes that result in deglycosylation of glycosylated phenolics and condensation, epimerization, and degalloylation of flavan-3-ols (catechins). Ambiguous phenolic assignments based on UV absorbance alone can occur when the chromatographic peaks overlapped slightly. We established an improved method using an HPLC–UV coupled with a single-quadrupole MS detector (MS1) that can reject false UV peaks after checking the preceding MS1 peaks. Adjusted UV data coded by the Python algorithm were deployed to compare tea phenolics. Performance validation of the MS1 and UV analysis methods for 19 phenolics revealed a sensitivity of 0.17 and 0.47 pmol/injection, limit of detection of 15 and 33 μg/L, limit of quantification of 50 and 110 μg/L, intra-day precision of 5% and 1% relative standard deviation, and trueness of 83–135% and 97–100%, respectively. Our results suggest that the HPLC–UV–MS1 method, which is a low operational cost method, potentially provides the precise phenolic composition of teas.
The “Scrubbing Brush Technique” for Access to Tight Lateral Recess of the Sphenoid Sinus: A Single Case Report
Authors: Zhang Margaret , Subramaniam Somasundram , Ng Chew Lip
Published: April 2021

Access to the lateral recess has always been a difficult task, especially in cases where the entrance to the lateral recess is very narrow. Various strategies have been described to approach it. Our study proposes a unique method of clearing debris in patients with concretions within the lateral recess. The “scrubbing brush technique” is based on easily accessible tools and has the exceptional advantage of being user friendly and having minimal potential side effects.
Big Data-Based Assessment of Political Risk along the Belt and Road
Authors: Sun Xiaohui , Gao Jianbo , Liu Bin , Wang Zhenzhen
Published: April 2021

Political risk assessment has become increasingly important in recent years, especially with the launch of the Belt and Road Initiative (BRI) and with Covid-19 still ravaging the world. This study aims to assess systematically the political risk of BRI countries during the period from 2013 to 2019 based on three big data sets, the Global Database of Events, Language, and Tone (GDELT), China Global Investment Tracker (CGIT), and Armed Conflict Location & Event Data Project (ACLED). It is found that to properly quantify the political risks for BRI countries, the type of events, “Material Conflict”, and a variable characterizing the degree of cooperation/conflicts of the events, the Goldstein Scale, are of critical importance. Based on the chosen type of events and variable, we design a normalized variable to assess political risk of any country in any year so that comparison among different countries can be meaningly made. By decomposing political risk into two components, domestic and international, and examining the spatiotemporal evolution of political risk along the Belt and Road, we find that the sum of the number of BRI countries with the extremely high level and the high level of domestic, international, and (overall) political risk all reached the peak in 2015, and decreased thereafter, and that often the level of domestic political risk along the Belt and Road was higher than the international political risk. It is also found that a strong positive correlation exists between political risk and China’s total investments and construction contracts along the Belt and Road during this period. The implications of this positive correlation are discussed. The analysis presented here may help to promote the sustainable development of BRI, and be extended to examine the risks associated with foreign investments other than BRI projects.
Effects of Sales-Related Capabilities of Personal Selling Organizations on Individual Sales Capability, Sales Behaviors and Sales Performance in Cosmetics Personal Selling Channels
Authors: Yi Ho-Taek , Cha Young-Bong , Amenuvor Fortune Edem
Published: April 2021

This study sets out to assess the effects of sales-related capabilities of personal selling organizations on individual sales capabilities, sales behaviors, and sales performance in cosmetics personal selling channels. Data are collected from 151 salespeople, their sales organizations, and their visiting customers (151) in South Korea. The proposed hypotheses are tested through the structural equation modelling technique. The study finds that both types of sales-related capabilities (salesforce management capabilities and personal selling capabilities) have significant positive effects on the individual sales capabilities, respectively. Further, the individual sales capability of salespeople has a stronger impact on customer-oriented sales behavior than on selling-oriented sales behavior. Similarly, selling-oriented sales behavior has a negative effect on customer satisfaction while customer-oriented sales behavior has a positive effect. The study further finds that customer-oriented sales behavior has a positive effect, while selling-oriented sales behavior has no statistically significant effect on sales performance. The relationship length, the study finds, moderates the relationship between customer-oriented sales behavior and customer satisfaction. The study offers practical and theoretical insights into understanding the nuances of sales-related capabilities of sales organizations and how they affect the individual selling capabilities of salespeople, their selling behaviors and sales performance. The results also have crucial consequences for sales organizations, as they can help sales managers design strategies and develop a culture that focuses on building and enhancing the selling capabilities of the firm and the salesforce. The present study demonstrates how the selling capabilities of the personal selling organization can influence the individual selling capabilities of the salesperson and how these could engender positive selling behaviors and sales performance.
Transforming Agricultural Extension Service Delivery through Innovative Bottom–Up Climate-Resilient Agribusiness Farmer Field Schools
Authors: Osumba Joab J. L. , Recha John W. , Oroma George W.
Published: April 2021

Conventional approaches to agricultural extension based on top–down technology transfer and information dissemination models are inadequate to help smallholder farmers tackle increasingly complex agroclimatic adversities. Innovative service delivery alternatives, such as field schools, exist but are mostly implemented in isolationistic silos with little effort to integrate them for cost reduction and greater technical effectiveness. This article presents a proof-of-concept effort to develop an innovative, climate-resilient field school methodology, integrating the attributes of Farmers’ Field School, Climate Field School, Climate-Smart Agriculture and indigenous technical knowledge of weather indicators in one package to address the gaps, while sensitizing actors on implications for policy advocacy. Some 661 local facilitators, 32% of them women and 54% youth, were trained on the innovation across East Africa. The initiative has reached 36 agribusiness champions working with 237,250 smallholder farmers in Kenya, Tanzania and Uganda. Initial results show that the innovation is strengthening adaptation behaviour of agribusiness champions, farmers and supply chain actors, and reducing training costs. Preliminary findings indicate that the process is rapidly shaping group adaptive thinking. The integrated approach offers lessons to transform extension and to improve food security and resilience. The approach bundles the costs of previously separate processes into the cost of one joint, simultaneous process, while also strengthening technical service delivery through bundled messaging. Experience from this initiative can be leveraged to develop scalable participatory extension and training models, especially scaling out through farmer-to-farmer replication and scaling up through farmer group networks.
Morpho-Biometrical, Nutritional and Phytochemical Characterization of Carrot Landraces from Puglia Region (Southern Italy)
Authors: Bonasia Anna , Conversa Giulia , Lazzizera Corrado , Gambacorta Giuseppe , Elia Antonio
Published: April 2021

The explorations as a part of the regional BiodiverSO Programme of vegetable genetic resource rescue revealed that in the arenili (sandy shores) of “Salterns of Margherita di Savoia” (SMS), a coastal landscape area of Puglia region (southern Italy), along the commercial genotypes of small rooting species, landraces are still cultivated. The morpho-biometrical, nutritional and phytochemical properties of two carrot landraces (“Carota a punta lunga” and “Carota a punta tonda”) and a commercial carrot hybrid (“Presto”) collected from the SMS area are examined. The study highlighted that the pedological conditions of the arenili of the SMS area are the main driving force in controlling the nutritional and nutraceutical characteristics of carrot, conferring to genotypes grown in this area a high profile in comparison with literature data. In the site of cultivation of arenili, a large variability in the morpho-qualitative traits emerged among carrot genotypes. “Carota a punta tonda” stands for a promising genotype being very rich in phenols (209.8 mg kg−1 fw) (mainly di-caffeic acid derivative and chlorogenic acid), ß-carotene (21,512 µg 100 g−1 fw), and high antioxidative proprieties. “Carota a punta tonda” could be considered as a healthy product for consumers and also amenable to selection for breeding purpose. Increasing the knowledge about nutritional and nutraceutical properties of local landraces may push the preference of consumers beyond the local community and, at the same time, farmers can be stimulated to continue their cultivation. Thus, the promotion of their on-farm/in situ conservation (cultivation) could represent an efficient strategy for agro-biodiversity preservation.
Potentials, Utilization, and Bioengineering of Plant Growth-Promoting Methylobacterium for Sustainable Agriculture
Authors: Zhang Cong , Wang Meng-Ying , Khan Naeem , Tan Ling-Ling , Yang Song
Published: April 2021

Plant growth-promoting bacteria (PGPB) have great potential to provide economical and sustainable solutions to current agricultural challenges. The Methylobacteria which are frequently present in the phyllosphere can promote plant growth and development. The Methylobacterium genus is composed mostly of pink-pigmented facultative methylotrophic bacteria, utilizing organic one-carbon compounds as the sole carbon and energy source for growth. Methylobacterium spp. have been isolated from diverse environments, especially from the surface of plants, because they can oxidize and assimilate methanol released by plant leaves as a byproduct of pectin formation during cell wall synthesis. Members of the Methylobacterium genus are good candidates as PGPB due to their positive impact on plant health and growth; they provide nutrients to plants, modulate phytohormone levels, and protect plants against pathogens. In this paper, interactions between Methylobacterium spp. and plants and how the bacteria promote crop growth is reviewed. Moreover, the following examples of how to engineer microbiomes of plants using plant-growth-promoting Methylobacterium are discussed in the present review: introducing external Methylobacterium spp. to plants, introducing functional genes or clusters to resident Methylobacterium spp. of crops, and enhancing the abilities of Methylobacterium spp. to promote plant growth by random mutation, acclimation, and engineering.
Regional Development in Romania: Empirical Evidence Regarding the Factors for Measuring a Prosperous and Sustainable Economy
Authors: Cristina Ibinceanu Onica Mihaela , Nicoleta Cristache , Cătălin Dobrea Răzvan , Margareta Florescu
Published: April 2021

The present study aims to present, evaluate and identify the factors required to measure the prosperity and sustainability of Romania’s economy over the specific period 2000–2020 in light of sustainable regional development assessments, and examines how the main factors—as considered by the authors—may be integrated into regional development policies. The focus throughout the study is on the need to permanently support the development of Romanian regions in direct relation to the sustainable indicators presented within the model—through the use of data from empirical analysis—which are measures of Romania’s economic prosperity and long-term economic growth. Therefore, the study intends to assess the progress of each region of the country, showing the evolution and selection of factors that are related to sustainability, namely, child survival, poverty and education, with implications for regional development strategies and local initiatives that must promote wider sustainable regional development. Furthermore, the aim of the study is to analyse the influence of sustainable inflows on economic prosperity, reflected in the Gross Domestic Product (GDP) per capita for each region in Romania, considering factors related to sustainability and the major differences between the regions, depending on the effectiveness of these public policy applications. With this approach, our goal—considering all the macroregions of the country—is to emphasize the significance of two main aims in sustainable regional development: a better allocation of the means which actively aim to decrease the unemployment rate and a better infrastructure for public services. National, regional and local administrations play important roles in promoting coherent sustainability in economic, social and environmental activities. Regardless of the level at which development policies are devised—local, county or regional—they must take into consideration and monitor the determinants of sustainable development in cases where development is the ultimate goal.