bluuebunny/crossref_metadata_2025 huggingface dataset:
Thymus zygis Essential Oil: Phytochemical Characterization, Bioactivity Evaluation and Synergistic Effect with Antibiotics against Staphylococcus aureus
Authors: Coimbra Alexandra , Miguel Sónia , Ribeiro Maximiano , Coutinho Paula , Silva Lúcia , Duarte Ana Paula , Ferreira Susana
Published: January 2022

Staphylococcus aureus is a nosocomial bacterium causing different infectious diseases, ranging from skin and soft-tissue infections to more serious and life-threatening infections such as sepsis, meningitis and endocarditis, which may be exacerbated by antibiotic resistance. Plant products may be seen as an alternative as antibacterial agents, namely, against S. aureus. Thus, the aim of this work was to characterize the chemical composition and evaluate the bioactive properties of the T. zygis essential oil (EO), with a focus on antimicrobial activity against S. aureus. Gas chromatography coupled with mass spectrometry was used to assess the chemical composition of the T. zygis EO, and the antioxidant activity was evaluated using the DPPH method and β-carotene-bleaching assay. The antimicrobial activity against S. aureus strains, the interaction with different antibiotics and the attenuation of this bacterium’s virulence were evaluated. The T. zygis EO showed antioxidant activity acting through two different mechanisms and antibacterial activity against S. aureus, with antibiofilm and antihaemolytic properties. This EO also demonstrated synergistic or additive interactions in combination with ampicillin, ciprofloxacin or vancomycin against S. aureus strains and, in some cases, changed the antibiotic-resistance phenotype from resistant to susceptible. Therefore, the present work demonstrates the good bioactive properties of the EO of T. zygis, mainly the antimicrobial activity against S. aureus, revealing its potential to be used as an antibacterial agent.
Synthesis of Alkyne-Substituted Dihydropyrrolones as Bacterial Quorum-Sensing Inhibitors of Pseudomonas aeruginosa
Authors: Almohaywi Basmah , Yu Tsz Tin , Iskander George , Sabir Shekh , Bhadbhade Mohan , Black David StC. , Kumar Naresh
Published: January 2022

The Quorum-sensing system in Pseudomonas aeruginosa is responsible for the pathogenicity and the production of virulence factors and biofilm formation. Dihydropyrrolones were previously found to act as inhibitors of QS-dependent bacterial phenotypes. In this study, a range of dihydropyrrolone (DHP) analogues was synthesized via the lactone-lactam conversion of lactone intermediates followed by the formation of novel acetylene analogues of dihydropyrrolones from brominated dihydropyrrolones via Sonogashira coupling reactions in moderate to high yields. Upon biological testing, the most potent compounds, 39–40 and 44, showed higher bacterial quorum-sensing inhibitory (QSI) activity against P. aeruginosa reporter strain at 62.5 µM. Structure–activity relationship studies revealed that di-alkynyl substituent at the exocyclic position of DHPs possessed higher QSI activities than those of mono-alkynyl DHPs. Moreover, a hexyl-substituent at C3 of DHPs was beneficial to QSI activity while a phenyl substituent at C4 of DHPs was detrimental to QSI activity of analogues.
Efficacy and Safety of Remdesivir in COVID-19 Positive Dialysis Patients
Authors: Butt Batool , Hussain Tajamul , Jarrar Mu’taman , Khalid Kashaf , Albaker Waleed , Ambreen Asma , Waheed Yasir
Published: January 2022

(1) Background: Immune compromised hemodialysis patients are more likely to develop COVID-19 infections, which increase the risk of mortality. The benefits of Remdesivir, despite less literature support on its effectiveness in dialysis patients due to renal toxicity, can outweigh the risks if prescribed early. The aim of this study was to evaluate the efficacy of Remdesivir on the 30-day in-hospital clinical outcome of hemodialysis population with COVID-19 infection and safety endpoints of adverse events. (2) Study design: A prospective quasi-experimental study design was used in the study. (3) Methods: The sample population consisted of 83 dialysis patients with COVID-19 who were administered Remdesivir at a dose of 100 mg before hemodialysis, as per hospital protocol. After the treatment with Remdesivir, we assessed the outcomes across two endpoints, namely primary (surviving vs. dying) as well as clinical and biochemical changes (ferritin, liver function test, C-reactive protein, oxygen requirements, and lactate dehydrogenase levels) and secondary (adverse effects, such as diarrhea, rise in ALT). In Kaplan–Meier analysis, the survival probabilities were compared between patients who received Remdesivir within 48 h of diagnosis and those who received it after 48 h. Cox regression analysis was employed to determine the predictors of outcome. (4) Results: Of the 83 patients, 91.5% survived and 8.4% died. Remdesivir administration did not reduce the death rate overall. Hospital stays were shorter (p = 0.03) and a nasopharyngeal swab for COVID-19 was negative earlier (p = 0.001) in survivors who had received Remdesivir within 48 h of diagnosis compared to those who had received Remdesivir after 48 h. The only variables linked to the 30-day mortality were serum CRP (p = 0.028) and TLC (p = 0.013). No major adverse consequences were observed with Remdesivir. (5) Conclusions: Remdesivir has the potential to shorten the recovery time for dialysis patients if taken within 48 h of onset of symptoms, without any adverse effects.
Exploring Titanium(IV) Complexes as Potential Antimicrobial Compounds
Authors: Rodríguez Israel , Fernández-Vega Lauren , Maser-Figueroa Andrea N. , Sang Branlee , González-Pagán Patricia , Tinoco Arthur D.
Published: January 2022

Due to the rapid mutation of pathogenic microorganisms, drug-resistant superbugs have evolved. Antimicrobial-resistant germs may share their resistance genes with other germs, making them untreatable. The search for more combative antibiotic compounds has led researchers to explore metal-based strategies centered on perturbing the bioavailability of essential metals in microbes and examining the therapeutic potential of metal complexes. Given the limited knowledge on the application of titanium(IV), in this work, eight Ti(IV) complexes and some of their corresponding ligands were screened by the Community for Open Antimicrobial Drug Discovery for antimicrobial activity. The compounds were selected for evaluation because of their low cytotoxic/antiproliferative behavior against a human non-cancer cell line. At pH 7.4, these compounds vary in terms of their solution stability and ligand exchange lability; therefore, an assessment of their solution behavior provides some insight regarding the importance of the identity of the metal compound to the antimicrobial therapeutic potential. Only one compound, Ti(deferasirox)2, exhibited promising inhibitory activity against the Gram-positive bacteria methicillin-resistant Staphylococcus aureus and minimal toxicity against human cells. The ability of this compound to undergo transmetalation with labile Fe(III) sources and, as a consequence, inhibit Fe bioavailability and ribonucleotide reductase is evaluated as a possible mechanism for its antibiotic effect.
Determining the Clinical Utility of 16S rRNA Sequencing in the Management of Culture-Negative Pediatric Infections
Authors: Lim Peter Paul C. , Stempak Lisa M. , Malay Sindhoosha , Moore LeAnne N. , Cherian Sree Sarah S. , Desai Ankita P.
Published: January 2022

The use of 16S rRNA sequencing in culture-negative infections has improved identification of bacterial pathogens in select scenarios, but its clinical impact requires further elucidation, especially in the pediatric population. This retrospective study aims to determine the clinical utility of 16S rRNA sequencing on the clinical management of pediatric culture-negative infections in our institution. Significant clinical utility was identified in 30 (40.5%) of 74 clinical samples (p < 0.0001). Of all specimens, pulmonary samples yielded the most clinical utility (n = 9, 30%), followed equally by joint fluid (n = 6, 20%) and bone (n = 6, 20%), with no difference between fluid and fresh tissue specimens (p = 0.346). Although the difference was not statistically significant (p = 0.4111), the overall use of broad-spectrum coverage was decreased. The median number of antibiotics was decreased from two to one (p < 0.0001) based on 16S rRNA sequencing results. The results suggest that 16S rRNA sequencing has a significant impact on decreasing the number of antibiotics used in the treatment of pediatric culture-negative infections. 16S rRNA sequencing performed on pulmonary specimens has the highest likelihood of identifying a pathogen compared to other specimen types. Additional cost–benefit analysis needs to be completed to further determine clinical benefit.
Special Issue Advances in Neutron Imaging
Authors: Treimer Wolfgang
Published: January 2022

This Special Issue of Applied Sciences, “Advances in Neutron Imaging”, is published at a time when the COVID-19 epidemic is emerging worldwide [...]
Numerical Study of Near-Infrared Light Propagation in Aqueous Alumina Suspensions Using the Steady-State Radiative Transfer Equation and Dependent Scattering Theory
Authors: Fujii Hiroyuki , Terabayashi Iori , Aoki Toshiaki , Inoue Yuki , Na Hyeonwoo , Kobayashi Kazumichi , Watanabe Masao
Published: January 2022

Understanding light propagation in liquid phantoms, such as colloidal suspensions, involves fundamental research of near-infrared optical imaging and spectroscopy for biological tissues. Our objective is to numerically investigate light propagation in the alumina colloidal suspensions with the mean alumina particle diameter of 55 nm at the volume fraction range 1–20%. We calculated the light scattering properties using the dependent scattering theory (DST) on a length scale comparable to the optical wavelength. We calculated the steady-state radiative transfer and photon diffusion equations (RTE and PDE) using the DST results based on the finite difference method in a length scale of the mean free path. The DST calculations showed that the scattering and reduced scattering coefficients become more prominent at a higher volume fraction. The anisotropy factor is almost zero at all the volume fractions, meaning the scattering is isotropic. The comparative study of the RTE with the PDE showed that the diffusion approximation holds at the internal region with all the volume fractions and the boundary region with the volume fraction higher than 1%. Our findings suggest the usefulness of the PDE as a light propagation model for the alumina suspensions rather than the RTE, which provides accurate but complicated computation.
Inverse Identification of Residual Stress Distribution in Aluminium Alloy Components Based on Deep Learning
Authors: Xiong Tulin , Wang Lu , Gao Xianzhi , Liu Guangyan
Published: January 2022

Residual stress within a structural component can significantly affect the mechanical performance and stability of a structure. Therefore, it is crucial to find a way to determine the residual stress distribution to maintain the normal working of structures. Conventional methods for residual stress determination primarily include experimental testing, finite element simulations and inverse identification. However, these methods suffer from disadvantages of high testing costs, long calculation time and low inverse efficiency. To avoid these shortcomings, this study developed a high-performance method based on a deep learning technique. In this method, an artificial neural network was used to replace the finite element calculation in the finite element model updating (FEMU) technique and the residual stress distribution of structural components was inversely obtained based on the measured residual stresses of a finite number of measuring points. Compared with the conventional FEMU technique, the calculation efficiency of the proposed method was considerably improved. Furthermore, the accuracy and efficiency of the method were verified by simulated four-point bending experiments considering an elastic-plastic material.
Asphalt Heat Recovery Application for Sustainable Green Energy
Authors: Dogeanu Angel , Tacutu Laurentiu , Iatan Elena , Nicolae Alin-Marius , Lungu Catalin Ioan
Published: January 2022

Increasing demand for energy due to comfort requirements in the built environment coupled with development of road networks and amplifying heat island effect call for a comprehensive approach that can answer both issues. The lifespan of an asphalt layer is affected by surface temperature. In this paper, we aim to study the feasibility of heat recovery and its effects in terms of energy harvesting efficiency and asphalt surface temperature by creating a numerical model and validating the model based on onsite measurements at laboratory scale. The experimental setup was developed at Technical University of Civil Engineering in Bucharest, and measurements were monitored during the summer. The heat recovery system used for this study was made of copper pipes, and material cost and layout optimization need to be addressed in future studies. The numerical model was validated using measured data. During this study, we obtained favorable results in terms of heat recovery, reducing surface temperature and selection of system materials. Further research is required for heat recovery system and pump automation (based on the surface temperature), in order to optimize energy consumption and improve overall efficiency.
Mineral Content Estimation of Lunar Soil of Lunar Highland and Lunar Mare Based on Diagnostic Spectral Characteristic and Partial Least Squares Method
Authors: Zhou Ping , Zhao Zhe , Wei Guangyuan , Huo Hongyuan
Published: January 2022

Extraction of mineral and rock information of lunar regolith is of far-reaching significance to the study of material composition, geological structure and historical evolution of lunar regolith. Visible and near-infrared spectra can reflect mineral composition information, and can be used to extract mineral composition and distribution characteristics of lunar regolith. In this paper, the LSCC (Lunar Soil Characterization Consortium) data of lunar regolith is taken as the research object. The partial least squares (PLS) regression model is used to estimate the spectra of lunar regolith measured in RELAB laboratory of Brown University. The mineral contents of plagioclase, pyroxene, olivine, ilmenite, agglutinate and volcanic glass in lunar regolith have been optimized and retrieved. The LSCC spectra of lunar regolith have been pre-processed by multivariate scattering correction (MSC), which highlight the spectral features of lunar regolith. The optimal number of principal components has been selected by cross-validation test. The PLS regression have been established for samples from lunar highland and lunar mare respectively. Two-thirds of samples have been randomly selected as experimental group to establish the prediction relationship between the spectra of lunar regolith and mineral content. The remaining one-third of samples have been used as verification group to further validate the prediction relationship. The results show that the partial least squares regression model has high accuracy and good stability. It is of theoretical and practical significance to optimize the inversion of mineral content in lunar regolith using spectral data of lunar regolith.
Improved Q Network Auto-Scaling in Microservice Architecture
Authors: Kim Yeonggwang , Park Jaehyung , Yoon Junchurl , Kim Jinsul
Published: January 2022

Microservice architecture has emerged as a powerful paradigm for cloud computing due to its high efficiency in infrastructure management as well as its capability of largescale user service. A cloud provider requires flexible resource management to meet the continually changing demands, such as auto-scaling and provisioning. A common approach used in both commercial and open-source computing platforms is workload-based automatic scaling, which expands instances by increasing the number of incoming requests. Concurrency is a request-based policy that has recently been proposed in the evolving microservice framework; in this policy, the algorithm can expand its resources to the maximum number of configured requests to be processed in parallel per instance. However, it has proven difficult to identify the concurrency configuration that provides the best possible service quality, as various factors can affect the throughput and latency based on the workloads and complexity of the infrastructure characteristics. Therefore, this study aimed to investigate the applicability of an artificial intelligence approach to request-based auto-scaling in the microservice framework. Our results showed that the proposed model could learn an effective expansion policy within a limited number of pods, thereby showing an improved performance over the underlying auto expansion configuration.
The Pharmacokinetics of Levetiracetam in Critically Ill Adult Patients: An Intensive Care Unit Clinical Study
Authors: Markantonis Sophia-Liberty , Markou Nikolaos , Karagkounis Apostolos , Koutrafouri Dionysia , Stefanatou Helen , Kousovista Rania , Karalis Vangelis
Published: January 2022

The aim of this study was to investigate levetiracetam pharmacokinetics in critically ill adult intensive care patients and to identify pathophysiological factors affecting its kinetics. Fourteen critically ill patients in an intensive care unit were enrolled in the study and received intravenous levetiracetam. Blood samples were collected at specific time points to determine the levetiracetam pharmacokinetics. Patient characteristics such as renal function, demographics, disease severity, organ dysfunction, and biochemical laboratory tests were evaluated for their influence on the kinetics of levetiracetam. Estimated glomerular filtration rate (eGFR) had a statistically significant (p = 0.001) effect on levetiracetam clearance. None of the other patient characteristics had a statistically significant effect on the pharmacokinetics. Simulations of dosing regimens revealed that even typically administered doses of levetiracetam may result in significantly increased concentrations and risk of drug toxicity in patients with impaired renal function. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score differed significantly among the three groups with different epileptic activity (p = 0.034). The same groups also differed in terms of renal function (p = 0.031). Renal dysfunction should be considered when designing levetiracetam dosage. Patients with a low APACHE II score had the lowest risk of experiencing epileptic seizures.
Time-Dependence of the Mechanical Behavior of Loess after Dry-Wet Cycles
Authors: Liu Kai , Gu Tianfeng , Wang Xingang , Wang Jiading
Published: January 2022

The structure, time-dependent mechanical deformation, and strength characteristics of loess, which is loose and porous with well-developed vertical joints, are greatly affected by the dry-wet cycles, which are attributed to periodic artificial irrigation, rainfall, and water evaporation. To better understand the creep characteristics of loess under the effect of dry-wet cycles, Q2 loess samples obtained from the South Jingyang County, China, were subjected to different dry-wet cycles (0, 5, 10, 15, 20) and sheared in triaxial creep tests. The experimental results revealed that: firstly, the maximum value of the deviatoric stress corresponding to creep failure gradually decreases with an increase in the dry-wet cycles. Secondly, the long-term strength of the loess after dry-wet cycles were obtained through the Isochronous Curve Method. It is found that the long-term strength and the number of dry-wet cycles showed an exponential decreasing relationship. In addition, the creep damage mechanism of loess due to dry-wet cycles is proposed. This study may provide the basis for understanding the mechanical behavior of the loess under the effect of dry-wet cycles, as well as guidelines for the prevention and prediction of loess landslide stability.
Quantifying the Occurrence of Multi-Hazards Due to Climate Change
Authors: Vlachogiannis Diamando , Sfetsos Athanasios , Markantonis Iason , Politi Nadia , Karozis Stelios , Gounaris Nikolaos
Published: January 2022

This paper introduces a climatic multi-hazard risk assessment for Greece, as the first-ever attempt to enhance scientific knowledge for the identification and definition of hazards, a critical element of risk-informed decision making. Building on an extensively validated climate database with a very high spatial resolution (5 × 5 km2), a detailed assessment of key climatic hazards is performed that allows for: (a) the analysis of hazard dynamics and their evolution due to climate change and (b) direct comparisons and spatial prioritization across Greece. The high geographical complexity of Greece requires that a large number of diverse hazards (heatwaves—TX, cold spells—TN, torrential rainfall—RR, snowstorms, and windstorms), need to be considered in order to correctly capture the country’s susceptibility to climate extremes. The current key findings include the dominance of cold-temperature extremes in mountainous regions and warm extremes over the coasts and plains. Extreme rainfall has been observed in the eastern mainland coasts and windstorms over Crete and the Aegean and Ionian Seas. Projections of the near future reveal more warm extremes in northern areas becoming more dominant all over the country by the end of the century.
Impact of Frost on the Morphology and Chemical Composition of cv. Santulhana Olives
Authors: Rodrigues Nuno , Casal Susana , Rodrigues Ana I. , Cruz Rebeca , Peres António M. , Pereira José Alberto
Published: January 2022

Frost events and extreme weather phenomena greatly affect several characteristics of the olive fruit. This study evaluated the impact of frost on the morphology, composition (moisture, fat, fatty acids, tocopherols, and total phenolic contents), and antioxidant activity of olives of cv. Santulhana. A total of 14 trees from the same geographical region (Santulhão, northeast of Portugal) were chosen, including trees subjected or not subjected to frost conditions (n = 7 each). The results showed that frost led to morphological changes in olive fruits, particularly in terms of weight and diameter, which were imposed by a huge decrease in the moisture content (−20%). Fat relative content increased as a consequence of the water loss (+29% in fresh pulp weight), with a slight reduction of the relative abundance of saturated fatty acids (−4%) and tocopherol contents in the fat (−17%). However, the total phenolic contents and antioxidant activity were severely affected (−70% and −42%, respectively), with potential consequences for the olive oil stability and sensorial attributes. Principal component analysis showed that both morphological and chemical parameters could be used as biomarkers to identify olives subjected or not subjected to frost. The overall negative impact of frost on the minor antioxidant contents of cv. Santulhana olives may anticipate a quality loss of olive oils extracted from olives affected by frost.
Implementation of Robots Integration in Scaled Laboratory Environment for Factory Automation
Authors: Mišković Dragiša , Milić Lazar , Čilag Andrej , Berisavljević Tanja , Gottscheber Achim , Raković Mirko
Published: January 2022

Robotic systems for research and development of factory automation are complex and unavailable for broad deployment in robotic laboratory settings. The usual robotic factory automation setup consists of series of sensors, robotic arms and mobile robots integrated and orchestrated by a central information system. Cloud-based integration has been gaining traction in recent years. In order to build such a system in a laboratory environment, there are several practical challenges that have to be resolved to come to a point when such a system can become operational. In this paper, we present the development of one such system composed of (i) a cloud-based system built on top of open platform for innovation in logistics, (ii) a prototyped mobile robot with a forklift to manipulate pallets in a “factory” floor, and (iii) industrial robot ABB IRB 140 with a customized gripper and various sensors. A mobile robot is designed as an autonomous four Mecanum wheels system with on-board LiDAR and RGB-D sensor for simultaneous localization and mapping. The paper shows a use case of the overall system and highlights the advantages of having a laboratory setting with real robots for the research of factory automation in a laboratory environment. Moreover, the proposed solution could be scaled and replicated in real factory automation applications.
Impact of Environmental Conditions on the Degree of Efficiency and Operating Range of PV-Powered Electric Vehicles
Authors: Schuss Christian , Fabritius Tapio
Published: January 2022

This paper investigates the impact of environmental conditions on the possible output power of photovoltaic (PV) installations on top of hybrid electric vehicles (HEVs) and battery-powered electric vehicles (BEVs). First, we discuss the characteristics and behavior of PV cells in order to provide an understanding of the energy source that we aim to integrate into vehicles. Second, we elaborate on how PV cells and panels can be simulated to estimate the potential extension of the electrical driving range (ERE) of BEVs and HEVs. In particular, we concentrate on the impact of the vehicle’s curved roof surface on the possible output of the PV installation. In this research, we present considerations for vehicles in both parking and driving conditions. More precisely, we demonstrate how the frequently changing environmental conditions that occur while driving represent significant challenges to the control of the operating voltage of PV cells. As the area for deploying PV cells on top of an electric vehicle is limited, attention needs to be paid to how to optimize and maximize the degree of efficiency of PV-powered electric vehicles.
Experimental Study on Properties of Ultrasonic Coupling Agent with Graphene in NDT
Authors: Mao Hanling , Lan Shun , Mao Hanying , Ren Jiaming , Yi Xiaoxu , Huang Zhenfeng , Li Xinxin
Published: January 2022

An ultrasonic coupling agent, as an acoustic medium between the ultrasonic probe and the surface of the specimens, is indispensable in Nondestructive Testing (NDT). Whether it is liquid, air, or solid coupling agent, the problem of improving the efficiency of ultrasonic propagation in a coupling agent is one worth studying. Glycerol and hydrogels are two common liquid coupling agents in NDT. This study intended to investigate the effect of graphene addition on the performance of these coupling agents in NDT. Firstly, based on the theory of acoustic impedance matching, the authors established an index system to evaluate the performance of ultrasonic coupling agent by experiments. Secondly, hydrogel–graphene and glycerol–graphene composite coupling agents were prepared by adding three-dimensional graphene structure powders with mass fraction of 0.25%, 0.5%, 0.75%, and 1% to CG-98 hydrogel coupling agent and HG-99 glycerol coupling agent, respectively. Corresponding experiments were conducted on these composite coupling agents. Peak-to-peak value, attenuation coefficient, and energy value of first echo are calculated at different frequencies. The experimental results showed that graphene can significantly improve the ultrasonic propagation performance of hydrogel and glycerin coupling agents. In addition, when the mass fraction of graphene added was 0.75%, the coupling agent had the best performance. Finally, we measured the acoustic impedance values of the composite couplings with different graphene contents to demonstrate the reliability of the experimental results.
Performance Comparison between Mini-LED Backlit LCD and OLED Display for 15.6-Inch Notebook Computers
Authors: Yang Zhiyong , Hsiang En-Lin , Qian Yizhou , Wu Shin-Tson
Published: January 2022

We evaluated and compared the performance of a 15.6-inch mini-LED backlit LCD (mLCD) with a commercial OLED (organic light-emitting diode) panel. Both displays exhibited outstanding properties, but the mLCD had advantages in peak brightness, gamma curve, luminance uniformity at low gray scales, color volume, power consumption, and ambient contrast ratio. In comparison with previous measurement methods, our color measurement adopted the reference method recently recommended by the International Committee for Display Metrology (ICDM). The LMK imaging photometer with a high-resolution CMOS sensor was employed to characterize the halo effect and reconstruct the real luminance profiles based on the non-ideal luminance profile of the OLED display. We also proposed a novel strategy to measure the point spread function of the backlight module.
Release of Sterile Mosquitoes with Drones in Urban and Rural Environments under the European Drone Regulation
Authors: Garcia Manuel , Maza Ivan , Ollero Anibal , Gutierrez Daniel , Aguirre Idoia , Viguria Antidio
Published: January 2022

In recent years, several countries have developed the use of sterile insect techniques (SIT) to fight against mosquitoes that transmit diseases. From a technical and economic point of view, the use of drones in the aerial release of sterile mosquitoes leads to important improvements in aerial coverage and savings in operational costs due to the requirement of fewer release sites and field staff. However, these operations are under the European drone regulation, one of the most advanced in the world. The main contribution and novelty of this paper with respect to previous work is the analysis of the SIT application with drones under the European risk-based regulation in two scenarios: urban and rural areas. The specific operations risk assessment (SORA) methodology has been applied to assess the risk of drone operations in these scenarios. The paper presents the operational requirements for aerial release of mosquitoes with drones along with the regulatory considerations that must be applied. Finally, an overview of the conditions in operation that could relax risks and mitigation measures is also discussed.
Evaluation of the Effectiveness of Joint Use of Wood and Other Renewable Energy Sources in the Baikal Region
Authors: Marchenko Oleg , Solomin Sergei , Shamanskiy Vitaly , Donskoy Igor
Published: January 2022

This paper addresses the assessment of woody biomass resources in Russia and the Baikal region. The analysis of the literature demonstrates that the Baikal region has considerable amounts of waste from the logging, timber processing, and pulp and paper industries (up to 220 PJ). A review of utilization technologies for woody biomass demonstrates that the existing technologies based on biomass gasification are promising for energy purposes. The gasification of biomass for small-capacity power plants has some advantages compared to its combustion. This paper considers an autonomous power system that consists of photovoltaic converters, wind turbines, storage batteries, a biomass gasification power plant, and a diesel power plant. A mathematical model used to optimize the system’s structure finds the minimum of the total discounted costs for the creation and operation of the system with some constraints met. Based on mathematical modeling, the cost-effectiveness of such a power supply system is assessed for different climatic zones of the Baikal region and the coastal area of Lake Baikal. The findings indicate that the optimal solution is the integration of various renewable energy sources in hybrid power systems. The proportion of energy sources of different types in the installed capacities is found. The study demonstrates that the optimal structure of the power system can provide significant savings (the total discounted costs are reduced by almost 2.5 times compared to the option using a diesel power plant alone).
Simulation-Aided Development of a CNN-Based Vision Module for Plant Detection: Effect of Travel Velocity, Inferencing Speed, and Camera Configurations
Authors: Sanchez Paolo Rommel , Zhang Hong
Published: January 2022

In recent years, Convolutional Neural Network (CNN) has become an attractive method to recognize and localize plant species in unstructured agricultural environments. However, developed systems suffer from unoptimized combinations of the CNN model, computer hardware, camera configuration, and travel velocity to prevent missed detections. Missed detection occurs if the camera does not capture a plant due to slow inferencing speed or fast travel velocity. Furthermore, modularity was less focused on Machine Vision System (MVS) development. However, having a modular MVS can reduce the effort in development as it will allow scalability and reusability. This study proposes the derived parameter, called overlapping rate (ro), or the ratio of the camera field of view (S) and inferencing speed (fps) to the travel velocity (v⇀) to theoretically predict the plant detection rate (rd) of an MVS and aid in developing a CNN-based vision module. Using performance from existing MVS, the values of ro at different combinations of inferencing speeds (2.4 to 22 fps) and travel velocity (0.1 to 2.5 m/s) at 0.5 m field of view were calculated. The results showed that missed detections occurred when ro was less than 1. Comparing the theoretical detection rate (rd,th) to the simulated detection rate (rd,sim) showed that rd,th had a 20% margin of error in predicting plant detection rate at very low travel distances (<1 m), but there was no margin of error when travel distance was sufficient to complete a detection pattern cycle (≥10 m). The simulation results also showed that increasing S or having multiple vision modules reduced missed detection by increasing the allowable v⇀max. This number of needed vision modules was equal to rounding up the inverse of ro. Finally, a vision module that utilized SSD MobileNetV1 with an average effective inferencing speed of 16 fps was simulated, developed, and tested. Results showed that the rd,th and rd,sim had no margin of error in predicting ractual of the vision module at the tested travel velocities (0.1 to 0.3 m/s). Thus, the results of this study showed that ro can be used to predict rd and optimize the design of a CNN-based vision-equipped robot for plant detections in agricultural field operations with no margin of error at sufficient travel distance.
Facades-as-a-Service: The Role of Technology in the Circular Servitisation of the Building Envelope
Authors: Azcarate-Aguerre Juan F. , Klein Tillmann , Konstantinou Thaleia , Veerman Martijn
Published: January 2022

The servitisation of the built environment, through the implementation of product–service systems, is considered a promising business strategy to achieve a circular economy transition. This servitisation faces a number of practical challenges, among them the technological readiness and effective integration and application of existing and emerging products, manufacturing processes, and digital monitoring and management tools. The research builds on targeted literature review, and on a research-through-design approach based on full-scale pilot projects developed in an ongoing feedback loop between researchers, planners, and industry partners representing both the demand and supply sides of the façade industry in the Netherlands. The paper analyses the technical implementation challenges currently preventing the façade industry from adopting performance-based contracts. It then proposes the roles that existing and emerging digital design and engineering technologies, manufacturing processes, and asset management systems can play in the development, implementation, and fulfilment of such contracts. The paper proposes a multi-stakeholder, systemic model for the development and application of façade technologies capable of overcoming many of the technical implementation barriers to the delivery of performance-based contracts for integrated facades. From this it concludes that an effective development of building technologies should strategically align with the solving of economic and contractual challenges such as circularity-readiness, profitability, risk distribution, legal demarcation, performance monitoring, and residual value stewardship. The resulting framework provides a strategic and conceptual basis for the development of circularity-enabling façade technologies, accounting for the diverse and sometimes conflicting interests of the multitude of stakeholders involved throughout a project’s lifecycle. The framework aims to support planners, manufacturers, and builders accelerate the circular deep energy renovation of the built environment while also exploring new business opportunities.
Study on the Light Field Regulation of UVC-LED Disinfection for Cold Chain Transportation
Authors: Guan Zuwei , Liu Peng , Zhou Tianfeng , Zhou Lin , Zhang Danmei , Xie Qiuchen , Yu Qian , He Yupeng , Wang Sijiang , Wang Xibin , Zhao Wenxiang
Published: January 2022

In this paper, the pain point that cold chain transportation urgently needs for an efficient disinfection method is pointed out. Thus, this work aims at solving the problems and improving the disinfection efficiency in cold chain transportation. While Ultraviolet-C (UVC) irradiation is an effective method by which to kill viruses, it is difficult to apply the commonly used UVC-LED disinfection light source to ice-covered cold chain transportation due to its uneven light field distribution. Thus, the light field regulation of UVC-LED disinfection for cold chain transportation is studied. A UVC-LED chip with a wavelength of 275 nm was used as a light source, and parallel light was obtained by collimating lenses. Then, microlens array homogenization technology was used to shape the UVC light into a uniform light spot, with an energy space uniformity rate of 96.4%. Moreover, a simulation was conducted to compare the effects of the ice layer on the absorption of UVC light. Finally, an experiment was carried out to verify that the disinfection efficiency can be increased nearly by 30% with the proposed system by disinfecting E. coli (Escherichia coli), and the results indicate that the proposed system is an effective disinfection solution during cold chain transportation.
Comparative Analysis of Emotion Classification Based on Facial Expression and Physiological Signals Using Deep Learning
Authors: Oh SeungJun , Kim Dong-Keun
Published: January 2022

This study aimed to classify emotion based on facial expression and physiological signals using deep learning and to compare the analyzed results. We asked 53 subjects to make facial expressions, expressing four types of emotion. Next, the emotion-inducing video was watched for 1 min, and the physiological signals were obtained. We defined four emotions as positive and negative emotions and designed three types of deep-learning models that can classify emotions. Each model used facial expressions and physiological signals as inputs, and a model in which these two types of input were applied simultaneously was also constructed. The accuracy of the model was 81.54% when physiological signals were used, 99.9% when facial expressions were used, and 86.2% when both were used. Constructing a deep-learning model with only facial expressions showed good performance. The results of this study confirm that the best approach for classifying emotion is using only facial expressions rather than data from multiple inputs. However, this is an opinion presented only in terms of accuracy without considering the computational cost, and it is suggested that physiological signals and multiple inputs be used according to the situation and research purpose.
Toward Predicting Student’s Academic Performance Using Artificial Neural Networks (ANNs)
Authors: Baashar Yahia , Alkawsi Gamal , Mustafa Abdulsalam , Alkahtani Ammar Ahmed , Alsariera Yazan A. , Ali Abdulrazzaq Qasem , Hashim Wahidah , Tiong Sieh Kiong
Published: January 2022

Student performance is related to complex and correlated factors. The implementation of a new advancement of technologies in educational displacement has unlimited potentials. One of these advances is the use of analytics and data mining to predict student academic accomplishment and performance. Given the existing literature, machine learning (ML) approaches such as Artificial Neural Networks (ANNs) can continuously be improved. This work examines and surveys the current literature regarding the ANN methods used in predicting students’ academic performance. This study also attempts to capture a pattern of the most used ANN techniques and algorithms. Of note, the articles reviewed mainly focused on higher education. The results indicated that ANN is always used in combination with data analysis and data mining methodologies, allowing studies to assess the effectiveness of their findings in evaluating academic achievement. No pattern was detected regarding selecting the input variables as they are mainly based on the context of the study and the availability of data. Moreover, the very limited tangible findings referred to the use of techniques in the actual context and target objective of improving student outcomes, performance, and achievement. An important recommendation of this work is to overcome the identified gap related to the only theoretical and limited application of the ANN in a real-life situation to help achieve the educational goals.
Species Diversity, Growing Stock Variables and Carbon Mitigation Potential in the Phytocoenosis of Monotheca buxifolia Forests along Altitudinal Gradient across Pakistan
Authors: Ali Fayaz , Khan Nasrullah , Abd_Allah Elsayed Fathi , Ahmad Adnan
Published: January 2022

The sub-tropical broadleaved forests in Pakistan are the main constituents of the ecosystem services playing a vital role in the global carbon cycle. Monotheca buxifolia (Falc.) A. DC. is an important constituent of these forests, encompassing a variety of ecological and commercial uses. To our best knowledge, no quantitative studies have been conducted in these forests across the landscape to establish a baseline for future monitoring. We investigated the forest structural attributes, growing stock characteristics and total biomass carbon stock and established relationships among them in the phytocoenosis of Monotheca forests along an altitudinal gradient in Pakistan to expand an eco-systemic model for assessment of the originally-implemented conservation strategies. A floristic survey recorded 4986 individuals of 27 species in overstory and 59 species in the understory stratum. Species richness (ANOVA; F = 3.239; p = 0.045) and Simpson’s diversity (ANOVA; F = 2.802; p = 0.043) differed significantly in three altitudinal zones, with a maximum value for lower elevations, followed by middle and higher elevations. Based on the importance values, Acacia modesta and Olea ferruginea are strong companions of M. buxifolia at lower and higher altitudes, whereas forests at mid elevation represent pure crop of M. buxifolia (IVI = ≥85.85%). A similar pattern in stem density, volume and Basal area were also recorded. The carbon stock in trees stratum (51.81 T ha−1) and understory vegetation (0.148 T ha−1) contributes high values in the lower elevation forests. In contrast, soil carbon had maximum values at higher elevation (36.21 T ha−1) and minimum at lower elevation (16.69 T ha−1) zones. Aboveground biomass carbon stock (AGB BMC) of woody trees, understory vegetation and soil organic carbon (SOC) were estimated higher (77.72 T ha−1) at higher and lower (68.65 T ha−1) elevations. Likewise, the AGB BMC exhibited a significant (p < 0.05) negative correlation with elevation and positive correlation with soil carbon. We concluded that lower elevation forests are more diverse and floristically rich in comparison to higher altitudinal forests. Similarly, the biomass carbon of Monotheca forests were recorded maximum at low altitudes followed by high and middle ranges, respectively.
Effect of Whole Body Vibration Conditions on Lower Limb Muscles during Sling Exercise
Authors: Woo Hyun-Ji , Yu Mi , Kwon Tae-Kyu
Published: January 2022

Exercising in an unstable environment, such as with the use of a sling, improves neuromuscular adaptation by providing effective training stimuli. Moreover, whole body vibration has been used to restore the physical function of patients with nervous system and musculoskeletal disorders. However, there have been few studies on the most appropriate exercise method of combining unstable surface and WBV. The purpose of this study was to investigate the effect of a sling and sonic vibration stimulation on muscle activation while performing a Bulgarian split squat (BSS). Twenty male subjects (age 25.95 ± 2.42 years old, height: 172.59 ± 5.56 cm, weight: 77.74 ± 10.82 kg) participated in the study. The participants randomly performed five types of BS using a sling and sonic vibration (BSS–0 Hz, BSS–4 Hz, BSS–8 Hz, BSS–12 Hz, BSS–20 Hz, and BSS–30 Hz). Each condition was repeated five times. A 60-s break was given for each condition to minimize muscle fatigue. We measured the muscular activities in the gluteus medius, biceps femoris, rectus femoris, vastus medialis, and vastus lateralis. It was observed that muscle activation increased during exercise conditions that provided a sling and sonic vibration in all muscles. In particular, the highest activation appeared in the condition wherein a vibration of 30 Hz was provided. Our results show that the sling exercise combined with a sonic vibration of 30 Hz during the BSS has positive effects on lower limb muscle activity.
Temporal Graphs and Temporal Network Characteristics for Bio-Inspired Networks during Optimization
Authors: DiBrita Nicholas S. , Eledlebi Khouloud , Hildmann Hanno , Culley Lucas , Isakovic A. F.
Published: January 2022

Temporal network analysis and time evolution of network characteristics are powerful tools in describing the changing topology of dynamic networks. This paper uses such approaches to better visualize and provide analytical measures for the changes in performance that we observed in Voronoi-type spatial coverage, particularly for the example of time-evolving networks with a changing number of wireless sensors being deployed. Specifically, our analysis focuses on the role different combinations of impenetrable obstacles and environmental noise play in connectivity and overall network structure. It is shown how the use of (i) temporal network graphs, and (ii) network centrality and regularity measures illustrate the differences between various options developed for the balancing act of energy and time efficiency in network coverage. Last, we compare the outcome of these measures with the less abstract classification variables, such as percent area covered and cumulative distance traveled.
Pain Relief and Antimicrobial Activity in Alveolar Osteitis after Platelet-Rich Fibrin Application—A Non-Randomized Controlled Study
Authors: Chybicki Damian , Janas-Naze Anna
Published: January 2022

The objective was to compare pain relief in alveolar osteitis achieved by the application of platelet-rich fibrin (PRF) and aspirin cones, and to assess the influence of both treatments on bacterial concentrations in post-extraction wounds. A split-mouth, single-center, non-randomized controlled trial was conducted in 30 patients. Pain relief was assessed using the visual analog scale at three time points (before, 24 h after, and 48 h after intervention). Bacterial concentrations were evaluated from cultures of swab samples collected at the three time points. A Wilcoxon matched-pairs signed-rank test was performed to detect differences in distributions of scalar variables between treatment with PRF and aspirin cones. Pain relief at 24 h and 48 h after treatment was significantly higher (p = 0.003) with PRF application than with aspirin cone placement. Additionally, PRF application caused a significantly higher reduction in aerobic bacteria concentration, an average increase, instead of a decrease, in lactic acid bacilli concentration in the first 24 h, and a significantly greater increase in streptococci concentration at 48 h follow-up. PRF provides better pain relief than aspirin cones in alveolar osteitis. Bacterial concentrations in the extraction wounds are consistent with the pain relief achieved after PRF or aspirin application.