bluuebunny/crossref_metadata_2025 huggingface dataset:
Electromagnetic Modulation Signal Classification Using Dual-Modal Feature Fusion CNN
Authors: Bai Jiansheng , Yao Jinjie , Qi Juncheng , Wang Liming
Published: May 2022

AMC (automatic modulation classification) plays a vital role in spectrum monitoring and electromagnetic abnormal signal detection. Up to now, few studies have focused on the complementarity between features of different modalities and the importance of the feature fusion mechanism in the AMC method. This paper proposes a dual-modal feature fusion convolutional neural network (DMFF-CNN) for AMC to use the complementarity between different modal features fully. DMFF-CNN uses the gram angular field (GAF) image coding and intelligence quotient (IQ) data combined with CNN. Firstly, the original signal is converted into images by GAF, and the GAF images are used as the input of ResNet50. Secondly, it is converted into IQ data and as the complex value network (CV-CNN) input to extract features. Furthermore, a dual-modal feature fusion mechanism (DMFF) is proposed to fuse the dual-modal features extracted by GAF-ResNet50 and CV-CNN. The fusion feature is used as the input of DMFF-CNN for model training to achieve AMC of multi-type signals. In the evaluation stage, the advantages of the DMFF mechanism proposed in this paper and the accuracy improvement compared with other feature fusion algorithms are discussed. The experiment shows that our method performs better than others, including some state-of-the-art methods, and has superior robustness at a low signal-to-noise ratio (SNR), and the average classification accuracy of the dataset signals reaches 92.1%. The DMFF-CNN proposed in this paper provides a new path for the AMC field.
Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects
Authors: Nafkha-Tayari Wafa , Ben Elghali Seifeddine , Heydarian-Forushani Ehsan , Benbouzid Mohamed
Published: May 2022

Recently, the integration of distributed generation and energy systems has been associated with new approaches to plant operations. As a result, it is becoming increasingly important to improve management skills related to distributed generation and demand aggregation through different types of virtual power plants (VPPs). It is also important to leverage their ability to participate in electricity markets to maximize operating profits. The present study focuses on VPP concepts, its different potential services, various control methodologies, distinct optimization approaches, and some practical implemented real cases. To this end, a comprehensive review of the most recent scientific literature is conducted. The paper concludes with remained challenges and future trends in the topic.
Adaptive Local Mean Decomposition and Multiscale-Fuzzy Entropy-Based Algorithms for the Detection of DC Series Arc Faults in PV Systems
Authors: Wang Lina , Lodhi Ehtisham , Yang Pu , Qiu Hongcheng , Rehman Waheed Ur , Lodhi Zeeshan , Tamir Tariku Sinshaw , Khan M. Adil
Published: May 2022

DC series arc fault detection is essential for improving the productivity of photovoltaic (PV) stations. The DC series arc fault also poses severe fire hazards to the solar equipment and surrounding building. DC series arc faults must be detected early to provide reliable and safe power delivery while preventing fire hazards. However, it is challenging to detect DC series arc faults using conventional overcurrent and current differential methods because these faults produce only minor current variations. Furthermore, it is hard to define their characteristics for detection due to the randomness of DC arc faults and other arc-like transients. This paper focuses on investigating a novel method to extract arc characteristics for reliably detecting DC series arc faults in PV systems. This methodology first uses an adaptive local mean decomposition (ALMD) algorithm to decompose the current samples into production functions (PFs) representing information from different frequency bands, then selects the PFs that best characterize the arc fault, and then calculates its multiscale fuzzy entropies (MFEs). Eventually, MFE values are inputted to the trained SVM algorithm to identify the series arc fault accurately. Furthermore, the proposed technique is compared to the logistic regression algorithm and naive Bayes algorithm in terms of several metrics assessing algorithms’ validity for detecting arc faults in PV systems. Arc fault data acquired from a PV arc-generating experiment platform are utilized to authenticate the effectiveness and feasibility of the proposed method. The experimental results indicated that the proposed technique could efficiently classify the arc fault data and normal data and detect the DC series arc faults in less than 1 ms with an accuracy rate of 98.75%.
Research on Motor Speed Control Method Based on the Prevention of Vehicle Rollover
Authors: Jiang Fuhuai , Dong Mengyuan , Fan Yuezhen , Wang Qingchun
Published: May 2022

Vehicle driving safety is an important performance indicator for vehicles, and there is still much room for development in the active safety control of electric vehicles. Vehicles are susceptible to rollover when making sharp turns or overtaking at high speed. In order to improve the anti-rollover stability of electric vehicles (EV), this study proposes a real-time motor control strategy, mainly according to the acquisition of vehicle attitude data and real-time monitoring of the vehicle’s operating state. The lateral load transfer rate was defined as the vehicle rollover evaluation index. When the real-time rollover indicator exceeded the limit safety threshold this article set, the motor speed would be reduced through active control to avoid rollover or reduce the risk of rollover. Both simulation results in Carsim and Simulink showed that the motor control strategy is highly reliable and real-time capable, and the active safety of EV was improved significantly.
Research on Prediction Method of Volcanic Rock Shear Wave Velocity Based on Improved Xu–White Model
Authors: Qiao Hanqing , Zhang Bing , Liu Cai
Published: May 2022

Volcanic rock reservoirs have received extensive attention from scholars all over the world because of their geothermal, mineral, and oil and gas resources. Shear wave velocity is the essential information for AVO (amplitude variation with offset) analysis and the reservoir description of volcanic rocks. However, due to factors such as cost, technical reasons, and so on, shear wave velocity is not provided in many logging data. This paper proposes a shear wave velocity prediction method suitable for the conventional logging of volcanic rocks. Firstly, the Xu–White model is improved. The probability distributions formed by the prior information of the logging area are used to initialize the key petrophysical parameters in the model instead of the fixed parameter value to establish the statistical petrophysical model between the logging curve and shear wave velocity. Then, based on the Bayesian inversion method, the simulated P-wave velocity is matched with the actual P-wave logging data to calculate the key petrophysical parameters, and is then used for S-wave velocity prediction. The method is applied to the actual logging data of the No. 5 structure in Nanpu Sag, eastern China. The prediction effect of shear wave velocity is better than that of the conventional method, indicating the feasibility and effectiveness of this method. This study will provide more accurate shear wave velocity data for the exploration and development of volcanic reservoirs.
Numerical Investigation on the Performance of a Transonic Axial Compressor with Inlet Distortion and Low Reynolds Number
Authors: Li Zhiping , Zhu Xingyu , Yan Zhaoqi , Pan Tianyu
Published: May 2022

The performance and stability of the transonic fan stage with a nonuniform inflow is a key issue in aero engine operation, and the coupling of inlet distortion and low Reynolds numbers at high altitude creates more severe challenges to aero engines. This work used computational methods to explore the performance and stability of a transonic fan stage with inlet distortion and a low Reynolds number. To investigate this issue, the transonic fan stage NASA stage 67 with a 180° total pressure distortion at a low Reynolds number was selected as the test case. Full-annulus 3D unsteady simulations were conducted to reveal the details of the flow field under coupling conditions. The computational results under different conditions were analyzed and showed that the coupling effect was not linearly stacked with single factors. The low Reynolds number in the coupling case thickened the boundary layer on the blade surface, and, on the one hand, the profile loss in the hub region increased. On the other hand, the structure of shock wave was converted in the tip region, which increased the shock loss significantly. In addition, the variation in the shock wave structure reconstructed the pressure distribution on the blade surface, allowing the fluid to migrate to the tip region, which affected the tip flow structure and ultimately delayed the stability boundary.
Continuous Extraction and Continuous Backfill Mining Method Using Carbon Dioxide Mineralized Filling Body to Preserve Shallow Water in Northwest China
Authors: Xu Yujun , Ma Liqiang , NGO Ichhuy , Zhai Jiangtao
Published: May 2022

The exploitation and utilization of coal resources are not only prone to causing water table lowering, but also produce a large amount of CO2 and coal-based solid waste. A scientific concept that employs the CO2 and solid wastes to develop filling bodies and inject them into the mined-out area, to sequestrate CO2 and mitigate the overburden migration and thus preserve the overlying aquifer, is proposed. Continuous extraction and continuous backfill (CECB) mining was selected as the mining method to meet the aforementioned objectives. Additionally, carbon dioxide mineralized filling body (CMFB) under ambient temperature and pressure was developed, with fly ash as aggregate, and CO2 gas, silicate additives and cement as accessories. The uniaxial compressive strength (UCS) and tensile strength of CMFB with various curing times and fly ash contents were tested indoors. A physical analogue simulation and FLAC3D numerical calculation were then successively implemented on the premise of determining a similar material ratio of CMFB in analogue simulation and calibrating the parameters of the CMFB in numerical simulation. The deformation of aquifuge and water level lowering while using CECB and CMFB with various proportion of fly ash were obtained. When using the CMFB with 75% fly ash content and 28 d curing time, the maximum values of vertical displacement, horizontal displacement, inclination, horizontal deformation and curvature of aquiclude were 26 mm, 6.5 mm, 0.12 mm/m, 0.08 mm/m and 0.0015 mm/m2, respectively, and the water table decreased 0.47 m. The results show that the CMFB with 75% fly ash is the most appropriate ratio to realize water preservation mining, CO2 sequestration and harmless treatment of solid wastes, contributing to the green and sustainable development of coal areas.
Sustainable Systems for the Production of District Heating Using Meat-Bone Meal as Biofuel: A Polish Case Study
Authors: Kowalski Zygmunt , Makara Agnieszka
Published: May 2022

The developed production of heat (steam) by Farmutil Company enables use of renewable energy from biofuel meat-bone meal which is incinerated in rotary kilns utilising vapours and odours from its production, instead of natural gas, to ensure Farmutil’s own needs for heat. The transformation of existing district heating in Piła city (currently using coal) into a fourth generation district heating system was proposed, predicting the use of heat (hot water) after combustion of biofuel meat-bone meal as district heating in the city of Piła. The maximum possible surplus amount of heat that can be produced at Farmutil exceeds the needs for the district heating demands of the city of Piła (860,200 GJ/y) by 53.2% at a meat-bone meal burning scale of 150,000 t/y. The use of 52,000 t/y of meat-bone meal for district heating production also results in an increase in incomes through the sale of hydroxyapatite ash from its combustion, amounting 1.638 million EUR/y. The closure of the coal-fired heating plant eliminates the consumption of 44,000 t/y of coal and the need to pay CO2 emission permits amount to over 5.588 million EUR/y.
Natural Gas Conversion and Liquid/Solid Organic Waste Gasification by Ultra-Superheated Steam
Authors: Frolov Sergey M. , Smetanyuk Viktor A. , Sadykov Ilias A. , Silantiev Anton S. , Shamshin Igor O. , Aksenov Viktor S. , Avdeev Konstantin A. , Frolov Fedor S.
Published: May 2022

The technology of a pulsed detonation gun for gasification of organic waste with ultra-superheated steam has been experimentally demonstrated for the first time. Experiments were performed on natural gas conversion as well as on the gasification of liquid (waste machine oil) and solid (wood sawdust) waste by hot detonation products of natural gas–oxygen mixture at a frequency of detonation pulses f = 1 Hz. Periodic release of detonation products to a 100 L flow reactor provided a time-averaged mean temperature and pressure in the reactor at about 1200 K and 0.1 MPa. It is shown that the technology of a pulsed detonation gun can provide complete (100%) natural gas conversion to syngas containing H2 and CO with a H2/CO ratio of 1.25. During the gasification of liquid and solid wastes, the total volume fraction of combustible gases (H2, CO, and CH4) in the product syngas was 80 and 65% with H2/CO ratios of 0.8 and 0.5, respectively. Comparison of the experiments on natural gas conversion and liquid/solid organic waste gasification under the same conditions at f = 1 Hz showed that the composition of the product syngas in terms of H2 and CO content almost did not depend on the type of used feedstock. The estimated ideal energy gain defined as the ratio of the total energy of product syngas to the energy spent in its production from dry wood sawdust is about 4.6, i.e., the pulsed detonation technology of biomass gasification is economically very attractive.
Design and Analysis of Novel Synchronous Motion Technique for a Multi-Module Permanent Magnet Linear Synchronous Motor
Authors: Zhang Fugang , Yin Haibin , Zhang Han
Published: May 2022

Traditionally, synchronous motion among multi-module permanent magnet linear synchronous motors (PMLSM) has been achieved by adopting independent power supply and control. This method, however, requires multiple drivers and has control time delays. This paper proposes a novel approach to overcome these drawbacks, in which the windings of each module connect in series. Aiming at this electrical connection, we conduct research on electromagnetic and synchronous characteristics. Firstly, a two-module PMLSM is created as a case. Secondly, accurate mathematical models considering coupling inductance for this novelty structure are established, which are essential to driving control. The synchronous characteristics of the two-module are then compared with the independent control of each module. Furthermore, this comparison is conducted under both external and no external disturbance. Finally, experimental results verify the correctness of mathematical models, and reveal that this novel technique could eliminate control time delay and acquire better anti-disturbance performance between the two-module.
Feasibility of Hybrid Desalination Plants Coupled with Small Gas Turbine CHP Systems
Authors: Sokolova Ekaterina , Sadeghi Khashayar , Ghazaie Seyed Hadi , Barsi Dario , Satta Francesca , Zunino Pietro
Published: May 2022

Nowadays, several technologies for desalination processes are available and widely employed. However, they consume a considerable amount of energy and involve high capital and operating costs. Therefore, the techno-economic analysis of a system coupling different energy sources with the desalination processes is of value. The possibility of coupling a small gas turbine combined heat and power system (GT CHP) with hybrid desalination plants (HDPs) has been assessed in this study. The proposed gas turbine power generation system, based on a single-stage centrifugal compressor and an uncooled centripetal turbine, provides design simplicity and reasonable installation costs for the power generating plant. The hybrid desalination technique, based on the use of two different desalination technologies, i.e., Reverse Osmosis (RO) and a thermal desalination process, has been chosen to better exploit the electrical and thermal energy produced by the mini CHP plant. The proposed solution is numerically investigated from both thermodynamic and economic points of view, and the results of the thermodynamic analysis of the cycle are used as input for the evaluation of the amount of freshwater produced and of costs. The economic assessment of standalone desalination systems is also shown for the comparison with the hybrid solutions here proposed. Results show that the total cost of the water produced by MED + RO was less than the total cost of the water obtained by MSF + RO, and that the energy cost of MED + RO hybrid desalination system was about 15% less than that for stand-alone RO desalination technology. Thus, the MED + RO hybrid desalination system can be considered a promising solution for the coupling with the proposed mini GT CHP plant, which, due to the small size and cost, as well as the easy installation, can be easily applied in off-grid or remote areas.
Control Techniques for Gob-Side Entry Driving in an Extra-Thick Coal Seam with the Influence of Upper Residual Coal Pillar: A Case Study
Authors: Xie Shengrong , Guo Fangfang , Wu Yiyi
Published: May 2022

In multi-seam mining, the residual coal pillar (RCP) in the upper gob has an important influence on the layout of the roadway in the lower coal seam. At present, few papers have studied the characteristics of the surrounding rock of gob-side entry driving (GED) with different coal pillar widths under the influence of RCP. This research contributes to improving the recovery rate of the extra-thick coal seam under this condition. The main research contents were as follows: (1) The mechanical parameters of the rock and coal mass were obtained using laboratory experiments coupled with Roclab software. These parameters were substituted into the established main roof structure mechanics model to derive the breakage position of the main roof with the influence of RCP, and the rationality of the calculation results was verified by borehole-scoping. (2) Based on numerical simulation, the evolution laws of the lateral abutment stress in the lower working face at different relative distances to the RCP were studied. FLAC3D was used to study the whole space-time evolution law of deviatoric stress and plastic zone of GED during driving and retreating periods with various coal pillar widths under the influence of RCP. (3) The plasticization factor P was introduced to quantify the evolution of the plastic zone in different subdivisions of the roadway surrounding rock, so as to better evaluate the bearing performance of the surrounding rock, which enabled a more effective determination of the reasonable coal pillar width. The field application results showed that it was feasible to set up the gob-side entry with an 8 m coal pillar below the RCP. The targeted support techniques with an 8 m coal pillar could effectively control the surrounding rock deformation.
Analysis of Video Transmission Capabilities in a Simulated OFDM-Based Supplementary BPL-PLC System
Authors: Debita Grzegorz , Falkowski-Gilski Przemysław , Zamłyńska Monika , Habrych Marcin , Miedziński Bogdan , Kupczyk Teresa , Polnik Bartosz
Published: May 2022

The design and maintenance of a reliable communication system, especially in harsh working conditions for the oil and mining industry, brings many challenges. With the use of a video transmission system, one can monitor the crew and their working environment. Broadband over power line–power line communication (BPL-PLC) seems an ideal medium for such a service, since it enables the use of the existing wired infrastructure for supplementary applications. In this paper, we perform a set of simulations for a dedicated wired medium as well as analyses of a visual data transmission system, designed to deliver video content with quadrature amplitude modulation (QAM) and orthogonal frequency division multiplexing (OFDM). We investigate a set of video sequences at 480 × 270 resolution under varying network conditions, including signal-to-noise ratio (SNR) and bit error rate (BER). We perform a subjective evaluation study of video content transmitted over our simulated communication link. The results of this study may aid parties involved in designing additional services for portable devices and user terminals, including reliable means of contact, surveillance and monitoring. The obtained results may be of particular interest to researchers and professionals related to the Industry 4.0 and Internet of things (IoT) concepts.
Parameter Effect Analysis of Non-Darcy Flow and a Method for Choosing a Fluid Flow Equation in Fractured Karstic Carbonate Reservoirs
Authors: Wang Yueying , Yao Jun , Huang Zhaoqin
Published: May 2022

Fractured karstic carbonate reservoirs have obvious multi-scale characteristics and severe heterogeneity due to the development of abundant karst caves and fractures with different scales. Darcy and non-Darcy flows coexist due to this property. Therefore, selecting the appropriate flow equations for different regions in the numerical simulation of fluid flows, particularly two-phase and multiphase flows, is a critical topic. This paper compares and analyses the displacement distance differences of waterfront travel using the Darcy, Forchheimer and Barree–Conway equations, as well as analyzes the influence of the Forchheimer constant, fluid viscosity, flow rate and absolute permeability on inertia action based on the Buckley–Leverett theory. The results show that the Forchheimer number/Reynolds number of water/oil two-phase flow is not a constant value and varies with water saturation, making it difficult to determine whether the inertial action should be considered solely based on these values; the influence of inertial action can be measured well by comparing the difference between the displacement distances of the waterflood front, and the quantitative standard is given for the selection of the flow equation of different regions by calculating the allowable error of the displacement distance of the waterflood front. The magnitude of the inertial effect is affected by the physical properties of the fluid and reservoir medium and the fluid velocity. The smaller the difference in the viscosity of the oil/water fluid, the smaller the inertial effect is. This technique was used a preliminary attempt to analyze the fractured karstic carbonate reservoirs at Tarim, and the results confirmed the validity of the method described in this article.
A Classy Multifacet Clustering and Fused Optimization Based Classification Methodologies for SCADA Security
Authors: Khadidos Alaa , Manoharan Hariprasath , Selvarajan Shitharth , Khadidos Adil , Alyoubi Khaled , Yafoz Ayman
Published: May 2022

Detecting intrusions from the supervisory control and data acquisition (SCADA) systems is one of the most essential and challenging processes in recent times. Most of the conventional works aim to develop an efficient intrusion detection system (IDS) framework for increasing the security of SCADA against networking attacks. Nonetheless, it faces the problems of complexity in classification, requiring more time for training and testing, as well as increased misprediction results and error outputs. Hence, this research work intends to develop a novel IDS framework by implementing a combination of methodologies, such as clustering, optimization, and classification. The most popular and extensively utilized SCADA attacking datasets are taken for this system’s proposed IDS framework implementation and validation. The main contribution of this work is to accurately detect the intrusions from the given SCADA datasets with minimized computational operations and increased accuracy of classification. Additionally the proposed work aims to develop a simple and efficient classification technique for improving the security of SCADA systems. Initially, the dataset preprocessing and clustering processes were performed using the multifacet data clustering model (MDCM) in order to simplify the classification process. Then, the hybrid gradient descent spider monkey optimization (GDSMO) mechanism is implemented for selecting the optimal parameters from the clustered datasets, based on the global best solution. The main purpose of using the optimization methodology is to train the classifier with the optimized features to increase accuracy and reduce processing time. Moreover, the deep sequential long short term memory (DS-LSTM) is employed to identify the intrusions from the clustered datasets with efficient data model training. Finally, the proposed optimization-based classification methodology’s performance and results are validated and compared using various evaluation metrics.
Capital Structure, Corporate Governance, Equity Ownership and Their Impact on Firms’ Profitability and Effectiveness in the Energy Sector
Authors: Georgakopoulos George , Toudas Kanellos , Poutos Evangelos I. , Kounadeas Theodoros , Tsavalias Stefanos
Published: May 2022

This paper aimed to research the interrelation between capital structure, corporate governance, equity ownership, and how they affect firm performance. The sample used consisted of 10 leading-energy-sector companies traded in the NYSE, most of which rank among the largest companies in the world by market capitalization, while the US-based ones are also Fortune 500 companies. Over the eleven-year period examined, from 2009 to 2019, a sampling frame of 110 data series was gathered and analyzed using panel data methodologies. The impact of the key parameters of capital structure, corporate governance, and equity ownership was tested using regression analysis (panel data method) on firm performance, measured by profitability. Our results support a significant relation among major capital structure and corporate governance parameters and firm performance, whereas no evidence was found to support a significant impact of equity ownership on the dependent variable found ascertained. Furthermore, our findings support that in our sample firms, pecking order and agency cost theories play an important role in the financing of these firms, while static trade and irrelevance theory find no support.
The Influence of Sugar Composition and pH Regulation in Batch and Continuous Acetone–Butanol–Ethanol Fermentation
Authors: Capilla Miguel , Silvestre Carlos , Valles Alejo , Álvarez-Hornos Francisco Javier , San-Valero Pau , Gabaldón Carmen
Published: May 2022

Acetone–butanol–ethanol (ABE) fermentation is influenced by external conditions. This work aimed to study the influence of pH regulation on monosaccharide composition in batch and continuous fermentation processes to determine butanol production and productivity. Batch fermentations with ammonium acetate or calcium carbonate combined with minimum pH control (pH ≥ 4.8 or 5.1) were assessed with pure xylose and glucose/xylose mixtures (ratios of 1:1 and 3:1). Continuous two-stage fermentation was developed using plastic rings to retain the biomass. Although batch fermentations with pure xylose performed better without active minimum pH control with both buffers, minimum pH control was necessary to metabolize xylose in the presence of glucose. Xylose uptake was favored by the use of calcium carbonate and pH ≥ 5.1 at a ratio of 1:1, while ammonium acetate and a pH ≥ 4.8 was the best option for a 3:1 ratio. The best butanol production and productivity values with sugar mixtures in batch reactors were 8.8 g L−1 and 0.61 g L−1 h−1 with an ammonium acetate pH ≥ 4.8 (ratio 3:1). The glucose/xylose ratio combined with pH regulation thus modulated xylose metabolism and solvent production in batch modes. Immobilized cells combined with operating at D = 0.333 h−1 and pH regulation increased butanol productivity almost fourfold up to 2.4 ± 0.2 g L−1 h−1.
The Mechanical Response of Epoxy–Sisal Composites Considering Fiber Anisotropy: A Computational and Experimental Study
Authors: Sinitsky Olga , Trabelsi Nir , Priel Elad
Published: May 2022

Natural-fiber-reinforced composites are seen as a good alternative to traditional synthetic-fiber composites. However, to successfully implement these materials in engineering applications, along with these materials demonstrating satisfactory load-bearing capacity, it is necessary to provide engineers with effective material properties, as well as calculation methods that take into account the distinctive features of natural fibers. This study investigated the effective elastic properties and strength of materials composed of unidirectional sisal fibers within a thermosetting polymer matrix, containing 20%, 40% and 60% fiber-volume fraction. Experiments with axial and off-axis loads in conjunction with finite-element modeling were utilized to determine the effective mechanical response of the composites. Analytical and numerical models were considered, using both isotropic- and anisotropic-fiber approaches. It is shown that only by taking into account the sisal-fiber anisotropy can the experimental results of the off-axis experiments be reproduced. The influence of sisal-fiber transverse modulus on the overall mechanical response is a function of the sisal-fiber volume fraction. It has been shown that the longitudinal specific strength of sisal-fiber-reinforced composites is comparable to classical aluminum alloys or steel. Thus, this environmentally friendly composite can be considered as an alternative in some engineering applications, such as reinforcement in concrete composites.
Inter-Otolith Differences in Strontium Markings: A Case Study on the Juvenile Crucian Carp Carassius carassius (Linnaeus, 1758)
Authors: Zhu Yahua , Jiang Tao , Chen Xiubao , Liu Hongbo , Phelps Quinton , Yang Jian
Published: May 2022

The release of hatchery-reared fish fry for restocking is important for the enrichment of fishery resources; however, the effective evaluation of the success rate of marking such fish is challenging. We exposed juvenile crucian carp (Carassius carassius) to a single concentration of SrCl2·6H2O for 5 d and evaluated the efficiency of Sr marking of the fish otoliths (sagittae, asterisci, and lapilli) using an electron probe micro-analyzer. Sr marking signatures formed a peak in all otolith types, with a marking success rate of 100%. The ratio of Sr to Ca in the lapilli and sagittae was higher than that in the asterisci. It took 2 d from the beginning of immersion to the deposition of Sr on the lapilli and sagittae, and the time delay for asterisci was 1 d. For the lapilli and sagittae, it took 16 d to terminate Sr marking and fully recover to the pre-marking Sr level, whereas it was 12 d for the asterisci. The application of the Sr dose had no effect on the survival or growth of the carp. This study demonstrated that the lapilli are the most suitable otolith type for Sr marking observations in crucian carp and provides a theoretical basis and technical support for carp restocking using the Sr marking approach.
Utilization of Fishery-Processing By-Product Squid Pens for Scale-Up Production of Phenazines via Microbial Conversion and Its Novel Potential Antinematode Effect
Authors: Nguyen Thi , Wang San-Lang , Nguyen Thi , Doan Manh , Tran Thi , Ngo Van , Ho Nhat , Tran Thi , Doan Chien , Do Van , Nguyen Anh , Nguyen Van
Published: May 2022

Fishery by-products (FBPs) have been increasingly investigated for the extraction and production of a vast array of active molecules. The aim of this study was to produce phenazine compounds from FBPs via microbial fermentation and assess their novel antinematode effect. Among various FBPs, squid pen powder (SPP) was discovered as the most suitable substrate for phenazine production by Pseudomonas aeruginosa TUN03 fermentation. Various small-scale experiments conducted in flasks for phenazine production indicated that the most suitable was the newly designed liquid medium which included 1% SPP, 0.05% MgSO4, and 0.1% Ca3(PO4)2 (initial pH 7). Phenazines were further studied for scale-up bioproduction in a 14 L bioreactor system resulting in a high yield (22.73 µg/mL) in a much shorter cultivation time (12 h). In the fermented culture broth, hemi-pyocyanin (HPC) was detected as a major phenazine compound with an area percentage of 11.28% in the crude sample. In the bioactivity tests, crude phenazines and HPC demonstrate novel potential nematicidal activity against black pepper nematodes, inhibiting both juveniles (J2) nematodes and egg hatching. The results of this work suggest a novel use of SPP for cost-effective bioproduction of HPC, a novel potential nematodes inhibitor. Moreover, the combination of MgSO4 and Ca3(PO4)2 was also found to be a novel salt composition that significantly enhanced phenazine yield by P. aeruginosa fermentation in this work.
Approach to the Chemotaxonomic Characterization of Traditional Cultivation Grape Varieties through Their Varietal Aroma Profile
Authors: Díaz-Fernández Ángela , Díaz-Losada Emilia , Cortés-Diéguez Sandra
Published: May 2022

In this study, the aroma profile of 12 minority grape varieties of Vitis vinifera L., included in the ‘Caiño group’, was defined along three vintages by solid phase microextraction followed by the gas chromatography–mass spectrometry method (SPME-GC-MS). Principal objectives were to assess the aromatic profile as a useful fingerprint to differentiate them, recover traditionally cultivated grape varieties for the differentiation of an important wine-growing area and discover their chemotaxonomic potential. In each variety, free and bound volatile profile was carried out by grouping varietal compounds into thirteen families. In total, 339 volatile compounds were identified, 230 as free forms and 205 as aromatic precursors. Remarkable quantitative differences were observed between aromatic profiles for terpenes in the free fraction and for C6 compounds, alcohols, sesquiterpenes and phenols in the glycosidic fraction. Principal component analysis based on their aromatic profile highlights a good differentiation between varieties and suggests a certain degree of aromatic chemotaxonomic proximity between previously known parental varieties, ‘Caiño Blanco’ with respect to ‘Caiño Bravo’ and ‘Albariño’. This study shows the preliminary results of a large research project involving a larger number of grape varieties and thus a broader spectrum of genetic relationships between them.
Hadamard-Type Fractional Integro-Differential Problem: A Note on Some Asymptotic Behavior of Solutions
Authors: Mugbil Ahmad , Tatar Nasser-Eddine
Published: May 2022

As a follow-up to the inherent nature of Hadamard-Type Fractional Integro-differential problem, little is known about some asymptotic behaviors of solutions. In this paper, an integro-differential problem involving Hadamard fractional derivatives is investigated. The leading derivative is of an order between one and two whereas the nonlinearities may contain fractional derivatives of an order between zero and one as well as some non-local terms. Under some reasonable conditions, we prove that solutions are asymptotic to logarithmic functions. Our approach is based on a generalized version of Bihari–LaSalle inequality, which we prove. In addition, several manipulations and crucial estimates have been used. An example supporting our findings is provided.
Current Understanding of Hydrogel for Drug Release and Tissue Engineering
Authors: Lei Lanjie , Bai Yujing , Qin Xinyun , Liu Juan , Huang Wei , Lv Qizhuang
Published: May 2022

Due to their good absorption, satisfactory biocompatibility, and high safety, hydrogels have been widely used in the field of biomedicine, including for drug delivery and tissue regeneration. In this review, we introduce the characteristics and crosslinking methods of natural and synthetic hydrogels. Then, we highlight the design and principle of intelligent hydrogels (i.e., responsive hydrogels) used for drug release. Moreover, we introduce the application of the application of hydrogels in drug release and tissue engineering, and the limitations and research directions of hydrogel in drug release and tissue engineering are also considered. We hope that this review can provide a reference for follow-up studies in related fields.
Advances on Hydrogels for Oral Science Research
Authors: Ye Shengjia , Wei Bin , Zeng Li
Published: May 2022

Hydrogels are biocompatible polymer systems, which have become a hotspot in biomedical research. As hydrogels mimic the structure of natural extracellular matrices, they are considered as good scaffold materials in the tissue engineering area for repairing dental pulp and periodontal damages. Combined with different kinds of stem cells and growth factors, various hydrogel complexes have played an optimistic role in endodontic and periodontal tissue engineering studies. Further, hydrogels exhibit biological effects in response to external stimuli, which results in hydrogels having a promising application in local drug delivery. This review summarized the advances of hydrogels in oral science research, in the hopes of providing a reference for future applications.
A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
Authors: Kathirvel Kandasamy , Haribalaganesh Ravinarayanan , Krishnadas Ramasamy , Muthukkaruppan Veerappan , Willoughby Colin E. , Bharanidharan Devarajan , Senthilkumari Srinivasan
Published: May 2022

Aim: To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. Methods: Using paired human donor eyes, human organ-cultured anterior segment (HOCAS) was established in one eye to characterize GC responsiveness based on intra ocular pressure (IOP) change and, in the other eye, primary HTM cell culture was established. For RNA sequencing, total RNA extracted from GC-responder (GC-R) and non-responder (GC-NR) cells after dexamethasone (DEX) or ethanol (ETH) treatment for 7d was used. Differentially expressed genes (DEGs) were compared among five groups and validated. Results: In total, 616 and 216 genes were identified as significantly dysregulated in Group #1 and #2 (#1: ETH vs. DEX-treated GC-R; #2: ETH vs. DEX-treated GC-NR), respectively. Around 80 genes were commonly dysregulated in Group #3 (overlapping DEGs between #1 and #2), whereas 536 and 136 genes were uniquely expressed in GC-R (#4) and GC-NR HTM (#5) cells, respectively. Pathway analysis revealed that WNT signaling, drug metabolism cytochrome p450, cell adhesion, TGF-β signaling, and MAPK signaling were associated with GC responsiveness. Conclusion: This is the first study reporting distinct gene signatures and their associated pathways for GC-R and GC-NR HTM cells. WNT and MAPK signaling are potential therapeutic targets for the management of GC-induced glaucoma.
Genome-Wide Gene Expression Profiling Defines the Mechanism of Anticancer Effect of Colorectal Cancer Cell-Derived Conditioned Medium on Acute Myeloid Leukemia
Authors: Lee Ji-Eun , Kwon Chan-Seong , Jeon Byeol-Eun , Kim Woo Ryung , Lee Du Hyeong , Koh Sara , Kim Heui-Soo , Kim Sang-Woo
Published: May 2022

Acute myeloid leukemia (AML) is the most common type of leukemia in adults, accounting for 30% of all adult leukemia cases. While there have been recent improvements in the prognosis of the disease, the prognosis remains grim, and further understanding of AML and the development of new therapeutic agents is critical. This study aimed to investigate the potential interaction between colorectal cancer (CRC) cells and AML cells. Unexpectedly, we found that CRC cell-derived conditioned medium (CM) showed anticancer activities in AML cells by inducing apoptosis and differentiation. Mechanistic studies suggest that these phenotypes are closely associated with the suppression of PI3K/AKT/mTOR and MAPK survival signaling, the upregulation of myeloid differentiation-promoting transcription factors c/EBPα and PU.1, and the augmentation of executioner caspases-3/7. Importantly, bioinformatic analyses of our gene expression profiling data, including that derived from principal component analysis (PCA), volcano plots, boxplots, heat maps, kyoto encyclopedia of genes and genomes (KEGG) pathways, and receiver operating characteristic (ROC) curves, which evaluate gene expression profiling data, provided deeper insight into the mechanism in which CRC-CM broadly modulates apoptosis-, cell cycle arrest-, and differentiation-related gene expression, such as BMF, PLSCR3, CDKN1C, and ID2, among others, revealing the genes that exert anticancer effects in AML cells at the genomic level. Collectively, our data suggest that it may be worthwhile to isolate and identify the molecules with tumor-suppressive effects in the CM, which may help to improve the prognosis of patients with AML.
A New Computational Deconvolution Algorithm for the Analysis of Forensic DNA Mixtures with SNP Markers
Authors: Yin Yu , Zhang Peng , Xing Yu
Published: May 2022

Single nucleotide polymorphisms (SNPs) support robust analysis on degraded DNA samples. However, the development of a systematic method to interpret the profiles derived from the mixtures is less studied, and it remains a challenge due to the bi-allelic nature of SNP markers. To improve the discriminating power of SNPs, this study explored bioinformatic strategies to analyze mixtures. Then, computer-generated mixtures were produced using real-world massively parallel sequencing (MPS) data from the single samples processed with the Precision ID Identity Panel. Moreover, the values of the frequency of major allele reads (FMAR) were calculated and applied as key parameters to deconvolve the two-person mixtures and estimate mixture ratios. Four custom R language scripts (three for autosomes and one for Y chromosome) were designed with the K-means clustering method as a core algorithm. Finally, the method was validated with real-world mixtures. The results indicated that the deconvolution accuracy for evenly balanced mixtures was 100% or close to 100%, which was the same as the deconvolution accuracy of inferring the genotypes of the major contributor of unevenly balanced mixtures. Meanwhile, the accuracy of inferring the genotypes of the minor contributor decreased as its proportion in the mixture decreased. Moreover, the estimated mixture ratio was almost equal to the actual ratio between 1:1 and 1:6. The method proposed in this study provides a new paradigm for mixture interpretation, especially for inferring contributor profiles of evenly balanced mixtures and the major contributor profile of unevenly balanced mixtures.
Does an Overcrowded Emergency Department Reduce Moral Hazard? Lessons from Emergency Department Visits to Three Hospitals in an Israeli Metropolitan Area
Authors: Basis Fuad , Tur-Sinai Aviad , Haklai Ziona
Published: May 2022

Metropolitan Haifa, Israel, has three hospitals: Rambam Health Care Campus, Bnai Zion Medical Center, and Carmel Medical Center. In 2007–2014, the length of stay at RHCC’s emergency department increased, while the number of visits decreased. We ask whether the increase in LOS is associated with the falling numbers of visits to other EDs, whether an increase in LOS induces more referrals to competing hospitals in the metropolitan area, and whether it pays to be a crowded ED in mitigating moral hazard. Average LOS at Rambam climbed from 3.5 h in 2000–2007 to 6.4 in 2008–2018. While the number of visits to Rambam decreased significantly, those to Bnai Zion increased significantly and quite linearly. A one-way ANOVA test reveals a statistically significant difference among the three hospitals. In addition, Rambam was significantly different from Carmel but not from Bnai Zion. When LOS stabilized at Rambam from 2016 to 2018 and increased at Bnai Zion, referrals to Rambam went up again. Policymakers should instruct all hospitals to publish LOS data, regulate referrals to EDs, and find an optimal LOS that will reduce competition, non-urgent visits, and moral hazard.
Learning from Acceleration Data to Differentiate the Posture, Dynamic and Static Work of the Back: An Experimental Setup
Authors: Muşat Elena Camelia , Borz Stelian Alexandru
Published: May 2022

Information on body posture, postural change, and dynamic and static work is essential in understanding biomechanical exposure and has many applications in ergonomics and healthcare. This study aimed at evaluating the possibility of using triaxial acceleration data to classify postures and to differentiate between dynamic and static work of the back in an experimental setup, based on a machine learning (ML) approach. A movement protocol was designed to cover the essential degrees of freedom of the back, and a subject wearing a triaxial accelerometer implemented this protocol. Impulses and oscillations from the signals were removed by median filtering, then the filtered dataset was fed into two ML algorithms, namely a multilayer perceptron with back propagation (MLPBNN) and a random forest (RF), with the aim of inferring the most suitable algorithm and architecture for detecting dynamic and static work, as well as for correctly classifying the postures of the back. Then, training and testing subsets were delimitated and used to evaluate the learning and generalization ability of the ML algorithms for the same classification problems. The results indicate that ML has a lot of potential in differentiating between dynamic and static work, depending on the type of algorithm and its architecture, and the data quantity and quality. In particular, MLPBNN can be used to better differentiate between dynamic and static work when tuned properly. In addition, static work and the associated postures were better learned and generalized by the MLPBNN, a fact that could provide the basis for cheap real-world offline applications with the aim of getting time-scaled postural profiling data by accounting for the static postures. Although it wasn’t the case in this study, on bigger datasets, the use of MLPBPNN may come at the expense of high computational costs in the training phase. The study also discusses the factors that may improve the classification performance in the testing phase and sets new directions of research.
The “Lost Guardians” of Dante’s Inferno: Medium Wave Infrared Imaging Investigations of a XIV Century Illuminated Manuscript
Authors: Orazi Noemi , Mercuri Fulvio , Cicero Cristina , Caruso Giovanni , Zammit Ugo , Ceccarelli Sofia , Paoloni Stefano
Published: May 2022

On the occasion of the 700th centenary of the death of Dante Alighieri, medium wave infrared imaging analysis of illuminations of the XIV-century code of the Divina Commedia (MS. 1102), hosted in the Biblioteca Angelica in Rome, was performed and discussed. The investigation was carried out by means of thermographic and reflectographic techniques on illuminations where the iconographic representation appeared severely damaged. In particular, through the combined use of both techniques, it was possible to recover the images of the damaged parts of the pictorial layer of the illuminations and of their underdrawings, displaying details of the “lost guardians”, which was useful to reconstruct the conservative history of the precious manuscript.