bluuebunny/crossref_metadata_2025 huggingface dataset:
Rapid Fleet Condition Analysis through Correlating Basic Vehicle Tracking Data with Engine Oil FT-IR Spectra
Authors: Nagy András Lajos , Agocs Adam , Ronai Bettina , Raffai Péter , Rohde-Brandenburger Jan , Besser Charlotte , Dörr Nicole
Published: December 2021

Engine oil condition and tribological performance are strongly interrelated. Accordingly, oil condition monitoring is common in various applications. This is especially important, as oil condition depends on the fueling and utilization profile of an internal combustion engine. Common practice involves the measurement of various parameters, such as the total acid number and total base number, oxidation, nitration, viscosity, and elemental composition; thus, it can be time-consuming and resource-intensive. This study provides a methodology for rapid analysis for large vehicle fleets or sample sizes, using only Fourier-transformed infrared spectroscopy and the subsequent multivariate data analysis offers a rapid alternative to commonly available methods. The described method provides a rapid, cost-efficient, and intuitive approach to uncovering differences in the oil condition. Furthermore, understanding the underlying reasons in engine construction and the resulting chemical degradation is also possible.
2,2′-(1,4-Phenylene)bis(7-nitro-1H-benzimidazole 3-oxide)
Authors: Politano Fabrizio , Gran-Magano Ana K. , Leadbeater Nicholas E.
Published: December 2021

Bis(benzimidazol-2-yl-3-oxide)benzene derivatives have potential applications as energetic or photoactive materials. By using a two-step one-pot approach employing microwave heating as a tool, 2,2′-(1,4-phenylene)bis(7-nitro-1H-benzimidazole 3-oxide) (1) has been prepared in 94% yield. In the first step an SNAr reaction is performed using p-xylylenediamine as the central building block. Without isolating the intermediate, a base-mediated cyclization reaction follows in the second step. The product was isolated in analytically pure form by means of a pH-controlled precipitation.
11H-Indeno[1,2-b]quinoxalin-11-one 2-(4-ethylbenzylidene)hydrazone
Authors: Kovrizhina Anastasia R. , Samorodova Elizaveta I. , Khlebnikov Andrei I.
Published: December 2021

11H-Indeno[1,2-b]quinoxaline derivatives present an important type of nitrogen-containing heterocyclic compound that are useful intermediate products in organic synthesis and have potential pharmaceutical applications. A new 11H-indeno[1,2-b]quinoxalin-11-one-2-(4-ethylbenzylidene)hydrazone (compound 3) was synthesized. Compound 3 is the first example of an azine derivative based on the 11H-indeno[1,2-b]quinoxaline system. The Z,E-isomerism of compound 3 was investigated by DFT calculations. Bioavailability was evaluated in silico using ADME predictions. According to the ADME results, compound 3 is potentially highly bioavailable and has potential to be used for the treatment of neuroinflammation and ischemia–reperfusion injury.
Comparison of Calculation Methods of Elastic Bonding: Limits of the Gamma Method Using an Example of a Wood–Concrete Composite Floor with Single Loads
Authors: Huber Christian , Deix Karl
Published: December 2021

Various methods are available for the calculation of timber–concrete composite floors. The gamma method, which is important in construction practice, as well as the differential equation method, are based on the simplified assumption of a continuous bond between wood and concrete. This makes it possible to analytically calculate the internally statically indeterminate partial section sizes and deformation sizes, analogous to the force size method. In this paper, two typical load situations of concentrated loads (central and off-centre) were analytically and numerically evaluated and compared using the above-mentioned methods (gamma and differential equation), with a discrete method for the case of a timber beam reinforced with a concrete slab using screws as fasteners. The calculation results show significant deviations, which speak for the application of discrete methods in certain load situations and thus limit the usability of the gamma method under certain conditions. For the problem of deflection determination, which is not dealt with in the literature for the discrete method, a numerical method is described in the present work, which was first developed and presented by the first author.
Advances in Multi-Scale Mechanical Characterization of Materials with Optical Methods
Authors: Lamberti Luciano
Published: December 2021

The mechanical characterization of materials embraces many different aspects, such as, for example, (i) to assess materials’ constitutive behavior under static and dynamic conditions; (ii) to analyze material microstructure; (iii) to assess the level of damage developed in the material; (iv) to determine surface/interfacial properties; and (v) to optimize manufacturing processes in terms of process speed and reliability and obtain the highest quality of manufactured products [...]
Preparation and Properties of a Sulphoaluminate Magnesium-Potassium Phosphate Green Cementitious Composite Material from Industrial Solid Wastes
Authors: Ren Changzai , Wang Wenlong , Hua Dongliang , Wu Shuang , Yao Yonggang
Published: December 2021

The preparation of high-performance green cementitious material from industrial solid waste is a feasible large-scale utilization approach for industrial solid waste. This work investigates the feasibility of using industrial solid wastes in a sulphoaluminate–magnesium–potassium–phosphate cementitious composite material (SAC-MKPC) clinker preparation and the influence of the calcination temperature and clinker ingredients on the hydration behavior and mechanisms of the SAC-MKPC with a Mg/P ratio of 5. The results show that the novel SAC-MKPC that was prepared from aluminum slag, carbide slag, coal gangue, and magnesium desulfurization slag was composed mainly of mineral MgO, C4A3S¯, and C2S and the calcination temperature of the main mineral phases was 1250–1350 °C. The solid-waste-based SAC-MKPC had better mechanical properties and excellent water resistance compared with the MKPC. The optimal compressive strength reached 35.2, 70.9, 84.1, 87.7, and 101.6 MPa at 2 h, 1 d, 3 d, 7 d, and 28 d of hydration, respectively. The X-ray diffraction spectra and scanning electron micrographs of the hydration products of the SAC-MKPC clinker showed that AFt and K-struvite crystals coexisted and adhered to form a dense structure. This work provides an innovative idea to produce green cementitious material using industrial solid wastes and may promote the sustainable development of the power and mining industries.
Designing and Developing a Smart Yogurt Filling Machine in the Industry 4.0 Era
Authors: Salah Bashir , Alsamhan Ali M. , Khan Sajjad , Ruzayqat Mohammed
Published: December 2021

Industry 4.0 allows for greater flexibility in production processes so that products can be customized (i.e., mass customization). Innovative production techniques in an industrial liquid/yogurt filling machine (YFM) improved efficiency in the beverage industry. In this study, we have introduced the second phase designed control architecture of our YFM based on the concepts of industry 4.0 incorporating an NFC platform for improving customer satisfaction. Especially during this pandemic period, wireless technologies have been ubiquitous and pervasive for customized products. The basic components of the YFM have been described. High-level control architecture programmed fully automated filling operations, and the design stage of the development of a PFC-based controller for the YFM is elaborated. For the evaluation of the proposed control system, the operations of the electric/pneumatic input devices and actuators were simulated on FluidSIM-MecLab. The results of the simulation verify the design logic of the PFC-based controller. Comparisons were made between different production types using the developing YFM. A complex learning environment replicating a real production system to understand, learn, and apply modern manufacturing approaches has been developed. Through the creation of this YFM, the academic environment and industrial applications are combined. Consequently, the problem verification is becoming more realistic and more efficient than online (trial and error) automation programming.
Adaptive Admittance Control Scheme with Virtual Reality Interaction for Robot-Assisted Lower Limb Strength Training
Authors: Lin Musong , Wang Hongbo , Niu Jianye , Tian Yu , Wang Xincheng , Liu Guowei , Sun Li
Published: December 2021

Muscle weakness is the primary impairment causing mobility difficulty among stroke survivors. Millions of people are unable to live normally because of mobility difficulty every year. Strength training is an effective method to improve lower extremity ability but is limited by the shortage of medical staff. Thus, this paper proposes a robot-assisted active training (RAAT) by an adaptive admittance control scheme with virtual reality interaction (AACVRI). AACVRI consists of a stiffness variable admittance controller, an adaptive controller, and virtual reality (VR) interactions. In order to provide human-robot reality interactions corresponding to virtual scenes, an admittance control law with variable stiffness term was developed to define the mechanics property of the end effector. The adaptive controller improves tracking performances by compensating interaction forces and dynamics model deviations. A virtual training environment including action following, event feedback, and competition mechanism is utilized for improving boring training experience and engaging users to maintain active state in cycling training. To verify controller performances and the feasibility of RAAT, experiments were conducted with eight subjects. Admittance control provides desired variable interactions along the trajectory. The robot responds to different virtual events by changing admittance parameters according to trigger feedbacks. Adaptive control ensures tracking errors at a low level. Subjects were maintained in active state during this strength training. Their physiological signals significantly increased, and interaction forces were at a high level. RAAT is a feasible approach for lower limb strength training, and users can independently complete high-quality active strength training under RAAT.
GPS Path Tracking Control of Military Unmanned Vehicle Based on Preview Variable Universe Fuzzy Sliding Mode Control
Authors: Zhang Houzhong , Yang Xiangtian , Liang Jiasheng , Xu Xing , Sun Xiaoqiang
Published: December 2021

In the process of the continuous development and improvement of modern military systems, military unmanned vehicles play an important role in field reconnaissance and strategic deployment. In this paper, the precise tracking algorithm of a military unmanned vehicle, based on GPS navigation, is studied. Firstly, the optimal preview point is obtained according to the data points of a differential GPS signal. Secondly, the pure tracking algorithm is used to calculate the demand steering angle, and a variable universe fuzzy sliding mode controller is designed to control the lateral motion of the vehicle, which is verified by the joint simulation platform of Simulink and CarSim, under multiple working conditions. Finally, the actual vehicle is verified by using the Autobox platform. The results show that the lateral motion control of path tracking designed in this paper can achieve an accurate and effective control effect, and has real-time performance for engineering applications.
Assessment of Dynamic Bayesian Models for Gas Turbine Diagnostics, Part 2: Discrimination of Gradual Degradation and Rapid Faults
Authors: Zaccaria Valentina , Fentaye Amare Desalegn , Kyprianidis Konstantinos
Published: December 2021

There are many challenges that an effective diagnostic system must overcome for successful fault diagnosis in gas turbines. Among others, it has to be robust to engine-to-engine variations in the fleet, it has to discriminate between gradual deterioration and abrupt faults, and it has to identify sensor faults correctly and be robust in case of such faults. To combine their benefits and overcome their limitations, two diagnostic methods were integrated in this work to form a multi-layer system. An adaptive performance model was used to track gradual deterioration and detect rapid or abrupt anomalies, while a series of static and dynamic Bayesian networks were integrated to identify component degradation, component abrupt faults, and sensor faults. The proposed approach was tested on synthetic data and field data from a single-shaft gas turbine of 50 MW class. The results showed that the approach could give acceptable accuracy in the isolation and identification of multiple faults, with 99% detection and isolation accuracy and 1% maximum error in the identified fault magnitude. The approach was also proven robust to sensor faults, by replacing the faulty signal with an estimated value that had only 3% error compared to the real measurement.
A New Hybrid Ensemble Deep Learning Model for Train Axle Temperature Short Term Forecasting
Authors: Yan Guangxi , Yu Chengqing , Bai Yu
Published: December 2021

The axle temperature is an index factor of the train operating conditions. The axle temperature forecasting technology is very meaningful in condition monitoring and fault diagnosis to realize early warning and to prevent accidents. In this study, a data-driven hybrid approach consisting of three steps is utilized for the prediction of locomotive axle temperatures. In stage I, the Complementary empirical mode decomposition (CEEMD) method is applied for preprocessing of datasets. In stage II, the Bi-directional long short-term memory (BILSTM) will be conducted for the prediction of subseries. In stage III, the Particle swarm optimization and gravitational search algorithm (PSOGSA) can optimize and ensemble the weights of the objective function, and combine them to achieve the final forecasting. Each part of the combined structure contributes its functions to achieve better prediction accuracy than single models, the verification processes of which are conducted in the three measured datasets for forecasting experiments. The comparative experiments are chosen to test the performance of the proposed model. A sensitive analysis of the hybrid model is also conducted to test its robustness and stability. The results prove that the proposed model can obtain the best prediction results with fewer errors between the comparative models and effectively represent the changing trend in axle temperature.
IGBT Open-Circuit Fault Diagnosis for MMC Submodules Based on Weighted-Amplitude Permutation Entropy and DS Evidence Fusion Theory
Authors: Shen Yifei , Wang Tianzhen , Amirat Yassine , Chen Guodong
Published: December 2021

Modular multilevel converters (MMCs) have a complex structure and a large number of submodules (SMs). If there is a fault in one of the SMs, it will affect the reliable operation of the system. Therefore, rapid fault diagnosis and accurate fault positioning are crucial to ensuring the continuous operation of the system. However, the IGBT open-circuit faults in different submodules of MMCs have similar fault features, and the traditional fault feature extraction method cannot effectively extract the key features of the fault so as to accurately locate the faulty submodules. In response to this problem, this paper proposes a fault diagnosis method based on weighted-amplitude permutation entropy (WAPE) and DS evidence fusion theory. The simulation results show that WAPE has better feature extraction ability than basic permutation entropy, and the fused multiscale feature decision output has better diagnostic accuracy than the single-scale feature. Compared with traditional fault diagnosis methods, this method achieves the diagnosis of multiple fault types by collecting a single signal, which greatly reduces the number of samples and leads to higher diagnostic accuracy and faster diagnostic speed.
A 6DoF Pose Estimation Dataset and Network for Multiple Parametric Shapes in Stacked Scenarios
Authors: Zhang Xinyu , Lv Weijie , Zeng Long
Published: December 2021

Most industrial parts are instantiated from different parametric templates. The 6DoF (6D) pose estimation tasks are challenging, since some part objects from a known template may be unseen before. This paper releases a new and well-annotated 6D pose estimation dataset for multiple parametric templates in stacked scenarios donated as Multi-Parametric Dataset, where a training set (50K scenes) and a test set (2K scenes) are obtained by automatical labeling techniques. In particular, the test set is further divided into a TEST-L dataset for learning evaluation and a TEST-G dataset for generalization evaluation. Since the part objects from the same template are regarded as a class in the Multi-Parametric Dataset and the number of part objects is infinite, we propose a new 6D pose estimation network as our baseline method, Multi-templates Parametric Pose Network (MPP-Net), aiming to have sufficient generalization ability for parametric part objects in stacked scenarios. To our best knowledge, our dataset and method are the first to jointly achieve 6D pose estimation and parameter values prediction for multiple parametric templates. Many experiments are conducted on the Multi-Parametric Dataset. The mIoU and Overall Accuracy of foreground segmentation and template segmentation on the two test datasets exceed 99.0%. Besides, MPP-Net achieves 92.9% and 90.8% on mAP under the threshold of 0.5cm for translation prediction, achieves 41.9% and 36.8% under the threshold of 5∘ for rotation prediction, and achieves 51.0% and 6.0% under the threshold of 5% for parameter values prediction, on the two test set, respectively. The results have shown that our dataset has exploratory value for 6D pose estimation and parameter values prediction tasks.
STEP-NC-Compliant Implementation to Support Mixed-Control Technologies Applied to Stone-Processing Machines Based on Industrial Automation Standards
Authors: Garrido Julio , Silva Diego , Sáez Juan
Published: December 2021

STEP-NC (Standard for the Exchange of Product Model Data–Numerical Control) for metal milling and turning is not implemented by industrial computer numerical controllers. Solutions reported are prototypes based on post-processing in G-code. Moreover, minority machining processes, such as stone cutting, have not yet been contemplated in the STEP-NC standard. This article takes that sector as a use case. An extended STEP-NC model for circular saw stone-cutting operations is proposed, and a prototype automation implementation is developed to work with this extended model. This article shows how modern technological resources for coordinated axes control provided by many industrial controllers for the automation of general-purpose machines can speed up the processes of implementing STEP-NC numerical controllers. This article proposes a mixed and flexible approach for STEP-NC-based machine automation, where different strategies can coexist when it comes to executing STEP-NC machining files, so controllers do not need to implement the standard in an exhaustive way for all the possible features, but only at selected ones when convenient. This is demonstrated in a prototype implementation which is able to process STEP-NC product files with mixed-feature types: standard milling and non-standard sawblade features for stone processing.
Correlation between the Flow and Curing Behavior of Hard Magnetic Fillers in Thermosets and the Magnetic Properties
Authors: Rösel Uta , Drummer Dietmar
Published: December 2021

Polymer bonded magnets based on thermoplastics are economically produced by the injection molding process for applications in sensor and drive technology. Especially the lack of orientation in the edge layer, as well as the chemical resistance and the creep behavior limit the possible implementations of thermoplastic based polymer bonded magnets. However, thermoset based polymer bonded magnets have the opportunity to expand the applications by complying with the demands of the chemical industry or pump systems through to improved chemical and thermal resistance, viscosity and creep behavior of thermosets. This paper investigates the influence of hard magnetic particles on the flow and curing behavior of highly filled thermoset compounds based on an epoxy resin. The basic understanding of the behavior of those highly filled hard magnetic thermoset systems is essential for the fabrication of polymer bonded magnets based on thermosets in the injection molding process. It is shown that several factors like the crystal structure, the particle shape and size, as well as the thermal conductivity and the adherence between filler and matrix influence the flow and curing behavior of highly filled thermoset compounds based on epoxy resin. However, these influencing factors can be applied to any filler system with respect to a high filler amount in a thermoset compound, as they are based on the material behavior of particles. Further, the impact of the flow and curing behavior on the magnetic properties of polymer bonded magnets based on thermosets is shown. With that, the correlation between material based factors and magnetic properties within thermosets are portrayed.
Syntheses, Structures and Magnetic Properties of M2 (M = Fe, Co) Complexes with N6 Coordination Environment: Field-Induced Slow Magnetic Relaxation in Co2
Authors: Yang Qianqian , Li Xiao-Lei , Tang Jinkui
Published: December 2021

Two dinuclear complexes [M2(H2L)2](ClO4)4·2MeCN (M = Co for Co2 and Fe for Fe2) were synthesized using a symmetric hydrazone ligand with the metal ions in an N6 coordination environment. The crystal structures and magnetic properties were determined by single-crystal X-ray diffraction and magnetic susceptibility measurements. The crystal structure study revealed that the spin centers were all in the high-spin state with a distorted octahedron (Oh) geometry. Dynamic magnetic properties measurements revealed that complex Co2 exhibited field-induced single-molecule magnet properties with two-step relaxation in which the fast relaxation path was from QTM and the slow relaxation path from the thermal relaxation under an applied field.
Solid-State Heating Using the Multicaloric Effect in Multiferroics
Authors: Vopson Melvin M. , Fetisov Yuri K. , Hepburn Ian
Published: December 2021

The multicaloric effect is defined as the adiabatic reversible temperature change in multiferroic materials induced by the application of an external electric or magnetic field, and it was first theoretically proposed in 2012. The multicaloric effects in multiferroics, as well as other similar caloric effects in single ferroics, such as magnetocaloric, elastocaloric, barocaloric, and electrocaloric, have been the focus of much research due to their potential commercialization in solid-state refrigeration. In this short communication article, we examine the thermodynamics of the multicaloric effect for solid-state heating applications. A possible thermodynamic multicaloric heating cycle is proposed and then implemented to estimate the solid-state heating effect for a known electrocaloric system. This work offers a path to implementing caloric and multicaloric effects to efficient heating systems, and we offer a theoretical estimate of the upper limit of the temperature change achievable in a multicaloric cooling or heating effect.
Neural Network Modelling for Prediction of Zeta Potential
Authors: Marsalek Roman , Kotyrba Martin , Volna Eva , Jarusek Robert
Published: December 2021

The study is focused on monitoring the influence of selected parameters on the zeta potential values of titanium dioxide nanoparticles. The influence of pH, temperature, ionic strength, and mass content of titanium dioxide in the suspension was assessed. More than a thousand samples were measured by combining these variables. On the basis of results, the model of artificial neural network was proposed and tested. The authors have rich experiences with neural networks applications and this case shows that the neural network model works with a very high prediction success rate of zeta potential. Clearly, pH has the greatest effect on zeta potential values. The influence of other variables is not so significant. However, it can be said that increasing temperature results in an increase in the value of the zeta potential of titanium dioxide nanoparticles. The ionic force affects the zeta potential depending on the pH; in the vicinity of the isoelectric point, its effect is negligible. The effect of the mass content of titanium dioxide in the suspension is absolutely minor.
Rotational Activity around an Obstacle in 2D Cardiac Tissue in Presence of Cellular Heterogeneity
Authors: Konovalov Pavel , Mangileva Daria , Dokuchaev Arsenii , Solovyova Olga , Panfilov Alexander V.
Published: December 2021

Waves of electrical excitation rotating around an obstacle is one of the important mechanisms of dangerous cardiac arrhythmias occurring in the heart damaged by a post-infarction scar. Such a scar is also surrounded by the region of heterogeneity called a gray zone. In this paper, we perform the first comprehensive numerical study of various regimes of wave rotation around an obstacle surrounded by a gray zone. We use the TP06 cellular ionic model for human cardiomyocytes and study how the period and the pattern of wave rotation depend on the radius of a circular obstacle and the width of a circular gray zone. Our main conclusions are the following. The wave rotation regimes can be subdivided into three main classes: (1) functional rotation, (2) scar rotation and the newly found (3) gray zone rotation regimes. In the scar rotation regime, the wave rotates around the obstacle, while in the gray zone regime, the wave rotates around the gray zone. As a result, the period of rotation is determined by the perimeter of the scar, or gray zone perimeter correspondingly. The transition from the scar to the gray rotation regimes can be determined from the minimal period principle, formulated in this paper. We have also observed additional regimes associated with two types of dynamical instabilities which may affect or not affect the period of rotation. The results of this study can help to identify the factors determining the period of arrhythmias in post-infarction patients.
A Novel Trading Strategy Framework Based on Reinforcement Deep Learning for Financial Market Predictions
Authors: Cheng Li-Chen , Huang Yu-Hsiang , Hsieh Ming-Hua , Wu Mu-En
Published: December 2021

The prediction of stocks is complicated by the dynamic, complex, and chaotic environment of the stock market. Investors put their money into the financial market, hoping to maximize profits by understanding market trends and designing trading strategies at the entry and exit points. Most studies propose machine learning models to predict stock prices. However, constructing trading strategies is helpful for traders to avoid making mistakes and losing money. We propose an automatic trading framework using LSTM combined with deep Q-learning to determine the trading signal and the size of the trading position. This is more sophisticated than traditional price prediction models. This study used price data from the Taiwan stock market, including daily opening price, closing price, highest price, lowest price, and trading volume. The profitability of the system was evaluated using a combination of different states of different stocks. The profitability of the proposed system was positive after a long period of testing, which means that the system performed well in predicting the rise and fall of stocks.
Immune Status and Hepatic Antioxidant Capacity of Gilthead Seabream Sparus aurata Juveniles Fed Yeast and Microalga Derived β-glucans
Authors: Reis Bruno , Gonçalves Ana Teresa , Santos Paulo , Sardinha Manuel , Conceição Luís E. C. , Serradeiro Renata , Pérez-Sánchez Jaume , Calduch-Giner Josep , Schmid-Staiger Ulrike , Frick Konstantin , Dias Jorge , Costas Benjamín
Published: December 2021

This work aimed to evaluate the effects of dietary supplementation with β-glucans extracted from yeast (Saccharomyces cerevisiae) and microalga (Phaeodactylum tricornutum) on gene expression, oxidative stress biomarkers and plasma immune parameters in gilthead seabream (Sparus aurata) juveniles. A practical commercial diet was used as the control (CTRL), and three others based on CTRL were further supplemented with different β-glucan extracts. One was derived from S. cerevisiae (diet MG) and two different extracts of 21% and 37% P. tricornutum-derived β-glucans (defined as Phaeo21 and Phaeo37), to give a final 0.06% β-glucan dietary concentration. Quadruplicate groups of 95 gilthead seabream (initial body weight: 4.1 ± 0.1 g) were fed to satiation three times a day for 8 weeks in a pulse-feeding regimen, with experimental diets intercalated with the CTRL dietary treatment every 2 weeks. After 8 weeks of feeding, all groups showed equal growth performance and no changes were found in plasma innate immune status. Nonetheless, fish groups fed β-glucans supplemented diets showed an improved anti-oxidant status compared to those fed CTRL at both sampling points (i.e., 2 and 8 weeks). The intestinal gene expression analysis highlighted the immunomodulatory role of Phaeo37 diet after 8 weeks, inducing an immune tolerance effect in gilthead seabream intestine, and a general down-regulation of immune-related gene expression. In conclusion, the results suggest that the dietary pulse administration of a P. tricornutum 37% enriched-β-glucans extract might be used as a counter-measure in a context of gut inflammation, due to its immune-tolerant and anti-oxidative effects.
Omacor Protects Normotensive and Hypertensive Rats Exposed to Continuous Light from Increased Risk to Malignant Cardiac Arrhythmias
Authors: Egan Benova Tamara , Viczenczova Csilla , Szeiffova Bacova Barbara , Zurmanova Jitka , Knezl Vladimir , Andelova Katarina , Tribulova Narcis
Published: December 2021

Light pollution disturbs circadian rhythm, and this can also be deleterious to the heart by increased susceptibility to arrhythmias. Herein, we investigated if rats exposed to continuous light had altered myocardial gene transcripts and/or protein expression which affects arrhythmogenesis. We then assessed if Omacor® supplementation benefitted affected rats. Male and female spontaneously hypertensive (SHR) and normotensive Wistar rats (WR) were housed under standard 12 h/12 h light/dark cycles or exposed to 6-weeks continuous 300 lux light for 24 h. Half the rats were then treated with 200 mg/100 g b.w. Omacor®. Continuous light resulted in higher male rat vulnerability to malignant ventricular fibrillation (VF). This was linked with myocardial connexin-43 (Cx43) down-regulation and deteriorated intercellular electrical coupling, due in part to increased pro-inflammatory NF-κB and iNOS transcripts and decreased sarcoplasmic reticulum Ca2+ATPase transcripts. Omacor® treatment increased the electrical threshold to induce the VF linked with amelioration of myocardial Cx43 mRNA and Cx43 protein levels and the suppression of NF-κB and iNOS. This indicates that rat exposure to continuous light results in deleterious cardiac alterations jeopardizing intercellular Cx43 channel-mediated electrical communication, thereby increasing the risk of malignant arrhythmias. The adverse effects were attenuated by treatment with Omacor®, thus supporting its potential benefit and the relevance of monitoring omega-3 index in human populations at risk.
Metabolomics Tools Assisting Classic Screening Methods in Discovering New Antibiotics from Mangrove Actinomycetia in Leizhou Peninsula
Authors: Lu Qin-Pei , Huang Yong-Mei , Liu Shao-Wei , Wu Gang , Yang Qin , Liu Li-Fang , Zhang Hai-Tao , Qi Yi , Wang Ting , Jiang Zhong-Ke , Li Jun-Jie , Cai Hao , Liu Xiu-Jun , Luo Hui , Sun Cheng-Hang
Published: December 2021

Mangrove actinomycetia are considered one of the promising sources for discovering novel biologically active compounds. Traditional bioactivity- and/or taxonomy-based methods are inefficient and usually result in the re-discovery of known metabolites. Thus, improving selection efficiency among strain candidates is of interest especially in the early stage of the antibiotic discovery program. In this study, an integrated strategy of combining phylogenetic data and bioactivity tests with a metabolomics-based dereplication approach was applied to fast track the selection process. A total of 521 actinomycetial strains affiliated to 40 genera in 23 families were isolated from 13 different mangrove soil samples by the culture-dependent method. A total of 179 strains affiliated to 40 different genera with a unique colony morphology were selected to evaluate antibacterial activity against 12 indicator bacteria. Of the 179 tested isolates, 47 showed activities against at least one of the tested pathogens. Analysis of 23 out of 47 active isolates using UPLC-HRMS-PCA revealed six outliers. Further analysis using the OPLS-DA model identified five compounds from two outliers contributing to the bioactivity against drug-sensitive A. baumannii. Molecular networking was used to determine the relationship of significant metabolites in six outliers and to find their potentially new congeners. Finally, two Streptomyces strains (M22, H37) producing potentially new compounds were rapidly prioritized on the basis of their distinct chemistry profiles, dereplication results, and antibacterial activities, as well as taxonomical information. Two new trioxacarcins with keto-reduced trioxacarcinose B, gutingimycin B (16) and trioxacarcin G (20), together with known gutingimycin (12), were isolated from the scale-up fermentation broth of Streptomyces sp. M22. Our study demonstrated that metabolomics tools could greatly assist classic antibiotic discovery methods in strain prioritization to improve efficiency in discovering novel antibiotics from those highly productive and rich diversity ecosystems.
Ethical and Legal Challenges of Telemedicine in the Era of the COVID-19 Pandemic
Authors: Solimini Renata , Busardò Francesco Paolo , Gibelli Filippo , Sirignano Ascanio , Ricci Giovanna
Published: December 2021

Background and objective: Telemedicine or telehealth services has been increasingly practiced in the recent years. During the COVID-19 pandemic, telemedicine turned into and indispensable service in order to avoid contagion between healthcare professionals and patients, involving a growing number of medical disciplines. Nevertheless, at present, several ethical and legal issues related to the practice of these services still remain unsolved and need adequate regulation. This narrative review will give a synthesis of the main ethical and legal issues of telemedicine practice during the COVID-19 pandemic. Material and Methods: A literature search was performed on PubMed using MeSH terms: Telemedicine (which includes Mobile Health or Health, Mobile, mHealth, Telehealth, and eHealth), Ethics, Legislation/Jurisprudence, and COVID-19. These terms were combined into a search string to better identify relevant articles published in the English language from March 2019 to September 2021. Results: Overall, 24 out of the initial 85 articles were considered eligible for this review. Legal and ethical issues concerned important aspects such as: informed consent (information about the risks and benefits of remote therapy) and autonomy (87%), patient privacy (78%) and confidentiality (57%), data protection and security (74%), malpractice and professional liability/integrity (70%), equity of access (30%), quality of care (30%), the professional–patient relationship (22%), and the principle of beneficence or being disposed to act for the benefit of others (13%). Conclusions: The ethical and legal issues related to the practice of telehealth or telemedicine services still need standard and specific rules of application in order to guarantee equitable access, quality of care, sustainable costs, professional liability, respect of patient privacy, data protection, and confidentiality. At present, telemedicine services could be only used as complementary or supplementary tools to the traditional healthcare services. Some indications for medical providers are suggested.
Outcomes and Risk Factors of Critically Ill Patients with Hematological Malignancy. Prospective Single-Centre Observational Study
Authors: Judickas Šarūnas , Stasiūnaitis Raimundas , Žučenka Andrius , Žvirblis Tadas , Šerpytis Mindaugas , Šipylaitė Jūratė
Published: December 2021

Background and Objectives: Oncohematological patients have a high risk of mortality when they need treatment in an intensive care unit (ICU). The aim of our study is to analyze the outcomes of oncohemathological patients admitted to the ICU and their risk factors. Materials and Methods: A prospective single-center observational study was performed with 114 patients from July 2017 to December 2019. Inclusion criteria were transfer to an ICU, hematological malignancy, age >18 years, a central line or arterial line inserted or planned to be inserted, and a signed informed consent form. Univariate and multivariable logistic regression models were used to evaluate the potential risk factors for ICU mortality. Results: ICU mortality was 44.74%. Invasive mechanical ventilation in ICU was used for 55.26% of the patients, and vasoactive drugs were used for 77.19% of patients. Factors independently associated with it were qSOFA score ≥2, increase of SOFA score over the first 48 h, mechanical ventilation on the first day in ICU, need for colistin therapy, lower arterial pH on arrival to ICU. Cut-off value of the noradrenaline dose associated with ICU mortality was 0.21 μg/kg/min with a ROC of 0.9686 (95% CI 0.93–1.00, p < 0.0001). Conclusions: Mortality of oncohematological patients in the ICU is high and it is associated with progression of organ dysfunction over the first 48 h in ICU, invasive mechanical ventilation and need for relatively low dose of noradrenaline. Despite our findings, we do not recommend making decisions regarding treatment limitations for patients who have reached cut-off dose of noradrenaline.
Being Heard: A Qualitative Study of Lithuanian Health Care Professionals’ Perceptions of Dignity at the End-of-Life
Authors: Butkevičienė Rūta , Kuznecovienė Jolanta , Harrison David , Peičius Eimantas , Urbonas Gvidas , Astromskė Kristina , Kalėdienė Ramunė
Published: December 2021

Background: The literature on professionals’ perceptions of dignity at the end-of-life (EOL) shows that there is a need for studies set in different cultural contexts. Lithuania represents one of these little-studied contexts. The aim of this study is to understand professionals’ attitudes, experiences, and suggestions concerning EOL dignity to provide knowledge upon which efforts to improve EOL care can be grounded. The research questions are “How do Lithuanian health care professionals understand the essence of dignity at the end-of-life of terminally ill patients?” and “How do they believe that dignity at the EOL can be enhanced?”. Materials and Methods: The study was exploratory and descriptive. It employed an interpretive phenomenological method to understand the essence of the phenomenon. Lightly structured interviews were conducted with professionals who had EOL experience, primarily with elderly and late middle-aged patients. from medicine, nursing, social work, and spiritual services. The interviews were primarily conducted by audiovisual means due to pandemic restrictions. Using a constant comparative method, the research team systematically codified text and developed themes by consensus after numerous analytic data iterations. Results: Four primary themes about EOL dignity were identified: Physical Comfort, Place of Care and Death, Effects of Death as a Taboo Topic, and Social Relations and Communication. A fifth, overarching theme, Being Heard, included elements of the primary themes and was identified as a key component or essence of dignity at the EOL. Conclusions: Patient dignity is both a human right and a constitutional right in Lithuania, but in many settings, it remains an aspiration rather than a reality. Being Heard is embedded in internationally recognized patient-centered models of EOL care. Hearing and acknowledging individuals who are dying is a specific skill, especially with elderly patients. Building the question “Is this patient being heard?” into practice protocols and conventions would be a step toward enhancing dignity at the EOL.
Individual and Organizational Conditions Leading to Quality of Care in Healthcare: A Fuzzy-Set Qualitative Comparative Analysis
Authors: Gonçalves Tiago , Curado Carla
Published: December 2021

Quality of care is a complex performance measure of healthcare performance that considers the influence of several contributors. This study enlarges our understanding of how such influences occur. We analyze individual and organizational level characteristics that have a complex relationship with quality of care. We examine specific patterns that lead to both the presence and absence of quality of care using a fuzzy-set qualitative comparative analysis. Our data comes from an online survey of healthcare professionals from a Portuguese university hospital, namely nursing and medical professionals. Our results reveal that combinations of individual-level characteristics, such as the quality of social support among professional peers and the perceived robustness of social networks, contribute to perceptions of quality of care. In addition, the results indicate that combinations of organizational-level characteristics, such as the presence of ethical leadership and the awareness of knowledge management systems, also lead to perceptions of quality of care. The solutions leading to the presence and absence of quality of care are discussed. We conclude that managerial practices in the university hospital should foster informal communication and peer support, given how pervasive their influence is on quality of care, even in circumstances where ethical leadership and awareness of knowledge management systems are absent from the configurations. Additionally, we reveal combinations of both individual-level and organizational-level characteristics that generate the absence of such quality of care, and thus we alert managers for the need to fight such situations.
Mechanisms, Growth Rates, and Morphologies of Gas Hydrates of Carbon Dioxide, Methane, and Their Mixtures
Authors: Martinez Camilo , Sandoval Juan F. , Ortiz Nathalia , Ovalle Sebastian , Beltran Juan G.
Published: December 2021

Mechanisms of growth and dissociation, growth rates, and morphology of gas hydrates of methane, carbon dioxide, and two CH4:CO2 mixtures (80:20 and 30:70 nominal concentration) were studied using using high resolution images and very precise temperature control. Subcooling and a recently proposed mass transfer-based driving force were used to analyze the results. When crystal growth rates did not exceed 0.01 mm/s, all systems showed faceted, euhedral crystal habits at low driving forces. At higher driving forces and growth rates, morphologies were different for all systems. These results solve apparent contradictions in literature about the morphology of hydrates of methane, carbon dioxide, and their mixtures. Differences in the growth mechanism of methane-rich and carbon dioxide-rich hydrates were elucidated. It was also shown that hydrate growth of methane, carbon dioxide, and their mixtures proceed via partial dissociation of the growing crystal. Temperature gradients were used to dissociate hydrates at specific locations, which revealed a most interesting phenomenon: On dissociation, carbon dioxide-rich hydrates propagated onto the bare substrate while drawing water from the opposite side of the sample. Furthermore, it was shown that an abrupt change in morphology common to all systems could be correlated to a change in the slope of growth rate data. This change in morphology was explained by a shift in the crystal growth mechanism.
Modeling and Simulations of 4H-SiC/6H-SiC/4H-SiC Single Quantum-Well Light Emitting Diode Using Diffusion Bonding Technique
Authors: Rashid Muhammad Haroon , Koel Ants , Rang Toomas , Nasir Nadeem , Mehmood Haris , Cheema Salman
Published: December 2021

In the last decade, silicon carbide (SiC) has emerged as a potential material for high-frequency electronics and optoelectronics applications that may require elevated temperature processing. SiC exists in more than 200 different crystallographic forms, referred to as polytypes. Based on their remarkable physical and electrical characteristics, such as better thermal and electrical conductivities, 3C-SiC, 4H-SiC, and 6H-SiC are considered as the most distinguished polytypes of SiC. In this article, physical device simulation of a light-emitting diode (LED) based on the unique structural configuration of 4H-SiC and 6H-SiC layers has been performed which corresponds to a novel material joining technique, called diffusion welding/bonding. The proposed single quantum well (SQW) edge-emitting SiC-based LED has been simulated using a commercially available semiconductor device simulator, SILVACO TCAD. Moreover, by varying different design parameters, the current-voltage characteristics, luminous power, and power spectral density have been calculated. Our proposed LED device exhibited promising results in terms of luminous power efficiency and external quantum efficiency (EQE). The device numerically achieved a luminous efficiency of 25% and EQE of 16.43%, which is at par performance for a SQW LED. The resultant LED structure can be customized by choosing appropriate materials of varying bandgaps to extract the light emission spectrum in the desired wavelength range. It is anticipated that the physical fabrication of our proposed LED by direct bonding of SiC-SiC wafers will pave the way for the future development of efficient and cost-effective SiC-based LEDs.
Phytoplankton Morpho-Functional Trait Variability along Coastal Environmental Gradients
Authors: Lehtinen Sirpa , Suikkanen Sanna , Hällfors Heidi , Tuimala Jarno , Kuosa Harri
Published: December 2021

We utilized the trait-based approach in a novel way to examine how specific phytoplankton traits are related to physical features connected to global change, water quality features connected to catchment change, and nutrient availability connected to nutrient loading. For the analyses, we used summertime monitoring data originating from the coastal northern Baltic Sea and generalized additive mixed modeling (GAMM). Of the physical features connected to global climate change, temperature was the most important affecting several studied traits. Nitrogen-fixing, buoyant, non-motile, and autotrophic phytoplankton, as well as harmful cyanobacteria, benefited from a higher temperature. Salinity and stratification did not have clear effects on the traits. Water transparency, which in the Baltic Sea is connected to catchment change, had a mostly negative relation to the studied traits. Harmfulness was negatively correlated with transparency, while the share of non-harmful and large-sized phytoplankton was positively related to it. We used nutrient loading source type and total phosphorus (TP) as proxies for nutrient availability connected to anthropogenic eutrophication. The nutrient loading source type did not relate to any of the traits. Our result showing that N-fixing was not related to TP is discussed. The regionality analysis demonstrated that traits should be calculated in both absolute terms (biomass) and proportions (share of total biomass) to get a better view of community changes and to potentially supplement the environmental status assessments.