bluuebunny/crossref_metadata_2025 huggingface dataset:
Siglec-15 as a New Perspective Therapy Target in Human Giant Cell Tumor of Bone
Authors: Fan Mengke , Zhang Guochuan , Xie Mingfang , Liu Xinbo , Zhang Qi , Wang Ling
Published: October 2022

The main features of a giant cell tumor of bone (GCTB) are frequent recurrence and aggressive osteolysis, which leads to a poor prognosis in patients. Although the treatment methods for a GCTB, such as scraping and resection, effectively inhibit the disease, the tendency toward malignant transformation remains. Therefore, it is important to identify new treatment methods for a GCTB. In this study, we first found high Siglec-15 expression in GCTB tissues, which was significantly associated with Campanacci staging and tumor recurrence. In Spearman’s analysis, Siglec-15 expression was significantly correlated with Ki-67 levels in tumor tissues. In vitro, the mRNA and protein levels of Siglec-15 were high in GCTB stromal cells (Hs737. T), and Siglec-15 knockdown inhibited the biological characteristics of GCTB stromal cells. The RNA sequencing results enabled a prediction of the downstream genes by using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and MCODE analyses, and the findings showed that CXCL8 was significantly regulated by Siglec-15 and might be a promising downstream target gene of Siglec-15. Therefore, Siglec-15 may be a potential immunotherapy target for a GCTB.
Septic Pulmonary Emboli Detected by 18F-FDG PET/CT in a Patient with Central Venous Catheter-Related Staphylococcus aureus Bacteremia
Authors: Yoo Jang , Cheon Miju
Published: October 2022

We describe a case of 18F-FDG PET/CT detecting septic pulmonary emboli in a patient with Staphylococcus aureus catheter-related bloodstream infection (CRBSI). The patient, who had an implantable venous access port for chemotherapy, underwent 18F-FDG PET/CT to diagnose unsuspected infectious foci. The PET/CT examination made it possible to offer a suggestive diagnosis and yielded metastatic infectious foci.
Parallelistic Convolution Neural Network Approach for Brain Tumor Diagnosis
Authors: Mgbejime Goodness Temofe , Hossin Md Altab , Nneji Grace Ugochi , Monday Happy Nkanta , Ekong Favour
Published: October 2022

Today, Magnetic Resonance Imaging (MRI) is a prominent technique used in medicine, produces a significant and varied range of tissue contrasts in each imaging modalities, and is frequently employed by medical professionals to identify brain malignancies. With brain tumor being a very deadly disease, early detection will help increase the likelihood that the patient will receive the appropriate medical care leading to either a full elimination of the tumor or the prolongation of the patient’s life. However, manually examining the enormous volume of magnetic resonance imaging (MRI) images and identifying a brain tumor or cancer is extremely time-consuming and requires the expertise of a trained medical expert or brain doctor to manually detect and diagnose brain cancer using multiple Magnetic Resonance images (MRI) with various modalities. Due to this underlying issue, there is a growing need for increased efforts to automate the detection and diagnosis process of brain tumor without human intervention. Another major concern most research articles do not consider is the low quality nature of MRI images which can be attributed to noise and artifacts. This article presents a Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm to precisely handle the problem of low quality MRI images by eliminating noisy elements and enhancing the visible trainable features of the image. The enhanced image is then fed to the proposed PCNN to learn the features and classify the tumor using sigmoid classifier. To properly train the model, a publicly available dataset is collected and utilized for this research. Additionally, different optimizers and different values of dropout and learning rates are used in the course of this study. The proposed PCNN with Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm achieved an accuracy of 98.7%, sensitivity of 99.7%, and specificity of 97.4%. In comparison with other state-of-the-art brain tumor methods and pre-trained deep transfer learning models, the proposed PCNN model obtained satisfactory performance.
Monitoring and Cordoning Wildfires with an Autonomous Swarm of Unmanned Aerial Vehicles
Authors: Saffre Fabrice , Hildmann Hanno , Karvonen Hannu , Lind Timo
Published: October 2022

Unmanned aerial vehicles, or drones, are already an integral part of the equipment used by firefighters to monitor wildfires. They are, however, still typically used only as remotely operated, mobile sensing platforms under direct real-time control of a human pilot. Meanwhile, a substantial body of literature exists that emphasises the potential of autonomous drone swarms in various situational awareness missions, including in the context of environmental protection. In this paper, we present the results of a systematic investigation by means of numerical methods i.e., Monte Carlo simulation. We report our insights into the influence of key parameters such as fire propagation dynamics, surface area under observation and swarm size over the performance of an autonomous drone force operating without human supervision. We limit the use of drones to perform passive sensing operations with the goal to provide real-time situational awareness to the fire fighters on the ground. Therefore, the objective is defined as being able to locate, and then establish a continuous perimeter (cordon) around, a simulated fire event to provide live data feeds such as e.g., video or infra-red. Special emphasis was put on exclusively using simple, robust and realistically implementable distributed decision functions capable of supporting the self-organisation of the swarm in the pursuit of the collective goal. Our results confirm the presence of strong nonlinear effects in the interaction between the aforementioned parameters, which can be closely approximated using an empirical law. These findings could inform the mobilisation of adequate resources on a case-by-case basis, depending on known mission characteristics and acceptable odds (chances of success).
Synchronization in Finite-Time of Delayed Fractional-Order Fully Complex-Valued Dynamical Networks via Non-Separation Method
Authors: Kang Qiaokun , Yang Qingxi , Yang Jing , Gan Qintao , Li Ruihong
Published: October 2022

The finite-time synchronization (FNTS) problem for a class of delayed fractional-order fully complex-valued dynamic networks (FFCDNs) with internal delay and non-delayed and delayed couplings is studied by directly constructing Lyapunov functions instead of decomposing the original complex-valued networks into two real-valued networks. Firstly, a mixed delay fractional-order mathematical model is established for the first time as fully complex-valued, where the outer coupling matrices of the model are not restricted to be identical, symmetric, or irreducible. Secondly, to overcome the limitation of the use range of a single controller, two delay-dependent controllers are designed based on the complex-valued quadratic norm and the norm composed of its real and imaginary parts’ absolute values, respectively, to improve the synchronization control efficiency. Besides, the relationships between the fractional order of the system, the fractional-order power law, and the settling time (ST) are analyzed. Finally, the feasibility and effectiveness of the control method designed in this paper are verified by numerical simulation.
Rate-Compatible LDPC Codes for Continuous-Variable Quantum Key Distribution in Wide Range of SNRs Regime
Authors: Fan Xiaodong , Niu Quanhao , Zhao Tao , Guo Banghong
Published: October 2022

Long block length rate-compatible low-density parity-compatible (LDPC) codes are designed to solve the problems of great variation of quantum channel noise and extremely low signal-to-noise ratio in continuous-variable quantum key distribution (CV-QKD). The existing rate-compatible methods for CV-QKD inevitably cost abundant hardware resources and waste secret key resources. In this paper, we propose a design rule of rate-compatible LDPC codes that can cover all potential SNRs with single check matrix. Based on this long block length LDPC code, we achieve high efficiency continuous-variable quantum key distribution information reconciliation with a reconciliation efficiency of 91.80% and we have higher hardware processing efficiency and lower frame error rate than other schemes. Our proposed LDPC code can obtain a high practical secret key rate and a long transmission distance in an extremely unstable channel.
Performance Evaluation of a UWB Positioning System Applied to Static and Mobile Use Cases in Industrial Scenarios
Authors: Schjørring Allan , Cretu-Sircu Amalia Lelia , Rodriguez Ignacio , Cederholm Peter , Berardinelli Gilberto , Mogensen Preben
Published: October 2022

Indoor positioning systems are essential in the industrial domain for optimized production and safe operation of mobile elements, such as mobile robots, especially in the presence of static machinery and human operators. In this paper, we assess the performance of a commercial UWB radio-based positioning system deployed in a realistic industrial scenario, considering both static and mobile use cases. Our goal is to characterize the accuracy of this system in the context of industrial use cases and applications. For the static case, an extensive analysis was presented based on measurements performed at 72 measurement positions at 3 different heights (above, at similar a level to, and below the average clutter level) in different industrial clutter conditions (open and cluttered spaces). The extensive analysis in the mobile case considered several runs of a route covered by an autonomous mobile robot equipped with multiple tags in different positions. The results indicate that a similar degree of accuracy with a median 2D positioning error smaller than 20 cm is possible in both static and mobile conditions with an optimized anchor deployment. The paper provides a complete statistical characterization of the system’s accuracy and addresses the multiple deployment trade-offs and system dynamics observed for the different configurations.
The Integration of Traditional Transportation Infrastructure and Informatization Development: How Does It Affect Carbon Emissions?
Authors: Wang Nian , Zhu Yingming
Published: October 2022

With the advent of the “Information Era”, the development of an integrated infrastructure, which involves the integration of traditional transportation infrastructure and informatization development, has become a new impetus for economic growth. Meanwhile, its environmental performance remains uncovered. Using data from 30 Chinese provinces between 2013 and 2020, this study designed an index system and constructed the coupling coordination degree model to assess the development level of integrated infrastructure. The regression model was established to examine the nonlinear effect of the integrated infrastructure on carbon emissions. The influencing mechanism was also discussed through identifying the impacts of integrated infrastructure on the energy intensity, industrial structure, and technological innovation. The evaluation of the evolutionary trend showed that the level of integrated infrastructure continues to improve and displays a feature of “higher highs, lower lows”, although the regional disparity was significant. The regression analysis showed that there was an inverted U–shaped relationship between integrated infrastructure and CO2 emissions. It is also found that most provinces were below the turning point. In the mechanism analysis section, we can demonstrate that integrated infrastructure can enhance energy intensity, which might hamper reductions in emissions. However, an integrated infrastructure facilitates the development of tertiary industry, which can lead to lower carbon emissions. Based on the conclusions, some insightful policy implications are provided.
Energy and Comfort Evaluation of Fresh Air-Based Hybrid Cooling System in Hot and Humid Climates
Authors: Narayanan Ramadas , Sethuvenkatraman Subbu , Pippia Roberto
Published: October 2022

Maintaining mechanical ventilation has been identified as a potential strategy for reducing the risk of virus infections. However, in hot and humid climatic conditions, delivering fresh air to a building comes at an energy cost and could impact occupant comfort due to the persistent need for simultaneous cooling and dehumidification. In this paper, the performance of a novel hybrid air conditioning system that handles fresh air is studied. In this system, dehumidification is accomplished by a solid desiccant dehumidifier coupled with a cooling coil integrated with the cooling tower of an existing chiller system. Using the data available from an operational desiccant cooling system, a system-level model has been developed and validated to study the potential application of the system in hot and humid climates. The study found that such a system is effective in delivering sensible cooling in all types of climates; thanks to the two-stage cooling in cooling coil and chilled water coils, respectively. However, the system is effective in delivering thermal comfort in regions where the climate has a relatively moderate ambient humidity. For the tropical cities of Darwin, Kuala Lumpur and Bangkok, the system can provide comfortable temperatures, but faces challenges in keeping the humidity within the comfort zone. The system electrical coefficient of performance (COP) is higher than that of refrigerative systems. This system also has the benefit over the refrigerative system of the supply air, which is entirely fresh ambient air and is expected to improve the indoor environmental quality largely.
Analysis of Surface Texturing of Silicon with Surface Regular Microstructure Using C Method
Authors: Dehghanpour Hamid , Parvin Parviz , Mortazavi Seyedeh , Reyhani Ali , Chegenizadeh Amin , Aghaei Mohammadreza
Published: October 2022

Silicon, as the most abundant element in the earth’s crust and the most common material used in electronic and optical equipment, has attracted the attention of many individuals to change the properties of this material, improving its electronic and optical properties. One of these efforts relies on the reduction of surface reflection by making use of different methods. However, among them, the use of lasers in creating surface microstructures has been of special importance because there is no need for masks and other additional materials. In this work, a theoretical method is utilized to analyze these textures with the theorem of diffraction grating on a micrometer scale. The surface reflection of the microstructure created by excimer laser exposure on a silicon surface is simulated. The theoretical Coordinate transformation method (C method) gives out notable results against the experimental records by approximating triangular and trapezoidal microstructures. The model is useful for predicting the reflective response of the modified microstructural morphology. One of the main applications is the texturing of the solar cell front faces to enhance their efficiency, mainly due to photon trapping.
Energy Use Forecasting with the Use of a Nested Structure Based on Fuzzy Cognitive Maps and Artificial Neural Networks
Authors: Poczeta Katarzyna , Papageorgiou Elpiniki I.
Published: October 2022

The aim of this paper is to present a novel approach to energy use forecasting. We propose a nested fuzzy cognitive map in which each concept at a higher level can be decomposed into another fuzzy cognitive map, multilayer perceptron artificial neural network or long short-term memory network. Historical data related to energy consumption are used to construct a nested fuzzy cognitive map in order to better understand energy use behavior. Through the experiments, the usefulness of the nested structure in energy demand prediction is demonstrated, by calculating three popular metrics: Mean Square Error, Mean Absolute Error and the correlation coefficient. A comparative analysis is performed, applying classic multilayer perceptron artificial neural networks, long short-term memory networks and fuzzy cognitive maps. The results confirmed that the proposed approach outperforms the classic methods in terms of prediction accuracy. Moreover, the advantage of the proposed approach is the ability to present complex time series in the form of a clear nested structure presenting the main concepts influencing energy consumption on the first level. The second level allows for more detailed problem analysis and lower forecast errors.
Modeling and Analysis of Low-Frequency Oscillation for Electrified Railway under Mixed Operation of Passenger and Freight Trains
Authors: Wang Yunling , Li Ting , Liu Jiawei , Liu Fang , Su Yunche , Zhang Qiao , Zhang Weilu , Liu Zhigang
Published: October 2022

Addressing the shortcomings of existing low-frequency oscillation research on electrified railways, which has mainly focused on single-type trains and lacks the accurate modeling of traction inverter systems, in this paper we modeled and analyzed low-frequency oscillations in an electrified railway passenger and freight mixed-operation vehicle–grid system. First, an equivalent model of the DC side of the traction inverter was established, with the inverter system being equivalent to the parallel connection of the load resistance and the current source, and the specific mathematical expression was determined and verified by impedance measurement. Secondly, based on the equivalent model of the DC side of the traction inverter, a small signal model of the vehicle–grid system under the mixed operating conditions of CRH5 and HXD2B considering the inverter system was established. The generalized Nyqusit criterion was used to study the low-frequency oscillation characteristics under mixed transportation conditions. The accuracy of the established model and the correctness of the theoretical analysis were verified based on Matlab/Simulink. Finally, using the dominant pole theory to analyze the low-frequency stability conditions, the relationship between the number of mixed trains and the minimum short-circuit ratio was obtained, and the simulation verification was carried out.
Effects of Ammonium Perchlorate and CL-20 on Agglomeration Characteristics of Solid High-Energy Propellants
Authors: Lv Xiang , Ma Rong , An Yuxin , Fan Zhimin , Gou Dongliang , Liu Peijin , Ao Wen
Published: October 2022

Energy density, which is an important indicator of the performance of solid propellants, is known to increase with the addition of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20). However, it remains unclear how CL-20 affects the decomposition of ammonium perchlorate (AP) and energy release. Here, the effects of CL-20 on the combustion performance and agglomeration of propellants were investigated. The addition of CL-20 decreased AP decomposition temperature and the energy required for the transformation of AP crystals from orthorhombic to cubic. The burning rate and pressure exponent of the propellant with 42% CL-20 were significantly higher than those of the propellant containing 20% CL-20. Thus, adding CL-20 to the propellant improves the energy characteristics and burning rate and the pressure exponent increases. At low combustion chamber pressure, the agglomeration of the propellant containing a high content of CL-20 will be blown away from the combustion surface only after staying on that surface for a short time. In this process, the probability of volume growth of the agglomeration after merging with other agglomerations greatly decreases, thus reducing the overall agglomerate particle sizes; further, the addition of a small amount of CL-20 to the propellant may lead to a reduction in agglomerate particle sizes. AP with a smaller particle size weakens the agglomeration in the combustion process and decreases the number of agglomerates with large particle sizes. These findings lay the foundation for the development of novel high-energy propellants.
Technological and Sustainable Perception on the Advancements of Prefabrication in Construction Industry
Authors: Chippagiri Ravijanya , Bras Ana , Sharma Deepak , Ralegaonkar Rahul V.
Published: October 2022

The construction industry has experienced phenomenal growth because of technological advancements in the past couple of decades. Prefabrication constitutes a sizeable share of this industry and is being adopted all over the world. The method of casting construction elements in a controlled environment and assembling them on-site has revolutionised the industry. Research on various aspects of the technology is ongoing around the world, and an impressive number of articles have been published. However, the prefab technology, materials used, and terminology have varied across locations, which may have hindered the method’s wider acceptability. By evaluating technical articles published between 1991 and 2022, this report analyses the present body of knowledge regarding prefab technology, its evolution, sustainability, and stakeholder views. This technology effectively contributes around 40% in time saving, 27% in cost reduction, 30% in reduced carbon emissions, and 84% in on-site wastage reduction. It also increases quality, gives a dependable alternative for meeting mass construction targets, is energy efficient, and provides environmentally conscious options. This paper contributes to the body of knowledge by providing a snapshot of the prefab industry spanning three decades, detailing a wide range of factors affecting the industry.
Eradication of Solar Power Unsustainability through Cost-Benefit Analysis: KwaZulu Natal Case Study
Authors: Mdlolo Bantubenzani Nelson , Olanrewaju Oludolapo Akanni
Published: October 2022

As a developing country, South Africa relies on electricity as the most critical amenity needed for development. KwaZulu-Natal (KZN) is one of the nine provinces in South Africa that faces an energy supply challenge. KZN is also the warmest province among them all due to its location. As one of the warmest provinces, solar power could be utilised to assist in dealing with the energy crisis. This paper focuses on the cost uncertainties attributed to the implementation of solar power which will assist in meeting the demand of energy in the region. The unsustainability of energy has led to a near collapse of the region’s economy. This study also contributes to improving the scientific implementation of solar power in the region to deal with the unsustainability criteria observed. The employment of Cost Benefit Analysis (CBA) revealed solar power as one of the most reliable renewable energies for planned implementation bases. With the development of the Economical, Methodological and Environmental (EME) strategic framework which addresses all social cohesion of solar power, the early turn around has been seen through the use of cost-benefit analysis (CBA) in the region of KZN.
GHG Emissions by (Petro)Chemical Processes and Decarbonization Priorities—A Review
Authors: Isella Andrea , Manca Davide
Published: October 2022

Global warming is becoming an increasing issue, and greenhouse gas (GHG) emissions represent the engine of such a phenomenon. This review aims to identify the origin of GHG emissions and focus in detail on the ones related to (petro) chemical industries. The industrial sector is the primary GHG emitter among all the other anthropogenic sources. The chemical industry is the first in charge of that (having accounted for about 6.5% of the global GHG emissions in 2018). Thought-provoking data such as yearly productivities and emission factors related to the predominant chemicals prompt the reader to acquire a sense of the critical activities responsible for carbon-intensive emissions, which should be the first to be decarbonized. Specifically, ammonia synthesis and steam cracking resulted in the most polluting processes of the chemical industry, being responsible for the release of about 440 and 228 Mt-CO2,eq/y, respectively, in 2020. The same approach also applies to oil refining. Due to the massive amounts of oil barrels produced daily, oil refining is a key player in industrial GHG emissions (about 3% of the global emissions in 2018). Indeed, in 2020, refineries emitted nearly 1313 Mt-CO2,eq/y.
A Hybrid Model for GRU Ultra-Short-Term Wind Speed Prediction Based on Tsfresh and Sparse PCA
Authors: Wang Yaqi , Gui Renzhou
Published: October 2022

Wind power is a popular renewable energy source, and the accurate prediction of wind speed plays an important role in improving the power generation efficiency of wind turbines and ensuring the normal operation of wind power equipment. Due to the instability and randomness of wind speed, it is difficult to achieve accurate prediction by traditional prediction methods. To improve the power generation efficiency of wind turbines and realize the predictability of wind speed, a hybrid wind speed prediction model based on GRUs (gated recurrent units) was constructed in this paper based on a deep neural network and feature extraction method. The hybrid model feature extraction module was implemented based on a combination of Tsfresh (a python package for time series feature extraction) and sparse PCA (sparse principal component analysis), and the network structure and other hyperparameters of the GRU module were determined through experiments. The model was validated using actual wind measurement data from a wind farm on the west coast of the United States. The results showed that the proposed model had less computational time and higher computational accuracy than the SARIMAX (seasonal auto-regressive integrated moving average with exogenous factors) and LSTM (long short-term memory) models.
Screening of Nickel and Platinum Catalysts for Glycerol Conversion to Gas Products in Hydrothermal Media
Authors: Alves Carine T. , Onwudili Jude A.
Published: October 2022

The production of low-carbon gaseous fuels from biomass has the potential to reduce greenhouse gas emissions and promote energy sustainability, stability and affordability around the world. Glycerol, a large-volume by-product of biodiesel production, is a potential feedstock for the production of low-carbon energy vectors. In this present work, an aqueous solution of pure glycerol was reacted under hydrothermal conditions using a total of 10 types of heterogeneous catalysts to evaluate its conversion to gas products (hydrogen, methane, CO, CO2 and C2–C4 hydrocarbon gases). Two bimetallic Ni-Fe and Ni-Cu catalysts, three Pt-based catalysts and physical mixtures of the five catalysts were tested. The reactions were carried out in a batch reactor for 1 h reaction time, using a 9:1 mass ratio of water/glycerol (10 wt%) and the reaction temperatures ranged between 250–350 °C using and without using 1 g of catalyst. The effects of the catalysts and reaction conditions on the conversion of glycerol in terms of carbon and hydrogen gasification efficiencies, selectivity and yields of components in the gas products were investigated. CO2 remained the most dominant gas product in all experiments. The results indicated that increasing the reaction temperature favoured gas formation and both carbon and hydrogen gasification efficiencies. The combination of Ni-Cu and Pt/C catalysts was the most selective catalyst for gas formation at 350 °C, giving carbon gasification efficiency of 95.6 wt%. Individually, the catalyst with the highest hydrogen production was Pt/C and the highest propane yield was obtained with the Ni-Cu bimetallic catalyst. Some catalysts showed good structural stability in hydrothermal media but need improvements towards better yields of desired fuel gases.
Pilot Study of Sap Properties of Norway Spruce (Picea abies (L.) Karst.) Trees Used and Not Used for Sap-Feeding by Three-Toed Woodpeckers (Picoides tridactylus)
Authors: Jyske Tuula , Keinänen Sini , Hölttä Teemu , Lintunen Anna , Pranovich Andrey , Laakso Tapio , Suuronen Jussi-Petteri , da Silva Viana Gabriel , Pakkala Timo
Published: October 2022

The ecophysiology of the Norway spruce (Picea abies (L.) Karst.) trees that were used by three-toed woodpeckers (TTW) (Picoides tridactylus) for their sap-feeding activities were investigated. The pilot study was conducted in southern Finland (61°15′ N, 25°00′ E). During April–June 2015, three different tree categories of Norway spruce were selected for monitoring: trees that were frequently used by the TTWs for phloem sap-feeding for several previous years; trees that were only recently used by TTWs for sap-feeding; and control trees that were not used at all for sap-feeding. Phloem sap and phloem tissue samples were frequently extracted from tree trunks and analyzed for the content and composition of nonstructural carbohydrates, phloem sap osmolality, solute, and water content, as well as for the content and composition of secondary metabolites typical for defense reactions in the phloem. Simple crown characteristics were also measured, including tree height, diameter at breast height, and their ratio (slenderness index). According to our results, the TTWs preferred Norway spruce trees that showed advanced spring phenology to feed on, as evidenced especially by the lower ratio of raffinose (typically high during the winter months) to total soluble sugars of phloem tissues as compared to non-used control trees. The lower slenderness index of the trees chosen by the TTWs indicates low canopy competition pressure with good access to light (i.e., the sun heats the trunks well in spring). There were no differences in the phloem osmolality or solute content between the used or unused control trees. The trees used by the TTWs had significantly higher concentrations of antioxidant phenolic (+)-catechins and stilbene glycosides in phloem tissue, and the stilbene content was also higher in the extracted sap. The phenolics content of the phloem tissue had a clear seasonal trend, being the highest in the early spring and lower towards the onset of the cambial growth processes. The phloem sap is rich in antioxidants and soluble sugars that are potentially beneficial for the TTWs, but more quantitative research is needed to explore the importance of the sap properties to TTWs.
Identification of Endophytic Microbiota of Phytoplasma-Infected Russian Olive Trees “Elaeagnus angustifolia L.” in the Northwest of Iran
Authors: Azizpour Nadia , Nematollahi Sevil , Khakvar Reza , Jamshidi Manizheh , Norouzi-Beirami Mohammad Hossein
Published: October 2022

In this study, Russian olive trees exhibiting witches’-broom symptoms were collected from urban green areas in Tabriz, in the northwest of Iran. PCR analysis confirmed that phytoplasma caused the disease and, according to the resulting Sanger sequencing electropherogram, a mixed infection with two or more phytoplasma species within the Russian olive trees was revealed. Next-generation sequencing analyses, using the Illumina method, were performed on total DNA from the infected Russian olive plants to recognize the microbial genomic content and assemble the whole genome of the causative pathogen(s). The use of MetaphlAn2 and Kraken2 to analyze species composition revealed the very diverse and unique compositions of different Prokaryotic and Eukaryotic species within the infected plants. Several bacteria and fungi were discovered inside the samples, among which Mycoplasmatota was significantly dominating. Interestingly, the results also revealed a high level of endosymbiotic bacteria and Archaea (Methanobacteria) genome contents within the samples. Bowtie2, metaSPAdes, and CD-HIT pipelines were used to perform the initial genome assembly, and the whole genome of the notable phytoplasma species was assembled and submitted to Genbank.
Flexural Strengthening of Reinforced Concrete Beams with Variable Compressive Strength Using Near-Surface Mounted Carbon-Fiber-Reinforced Polymer Strips [NSM-CFRP]
Authors: Al-zu’bi Hebah , Abdel-Jaber Mu’tasim , Katkhuda Hasan
Published: October 2022

An experimental and analytical investigation was conducted on reinforced concrete (RC) beams strengthened in flexure using the near-surface mounted carbon-fiber-reinforced polymers (NSM-CFRPs) technique. A total of 11 full-scale RC rectangular beams were cast and tested under a monotonic three-point bending test, up to failure. The main test variables adopted in this study were the concrete compressive strength (high, medium, and low), the number of CFRP strips, and the strip length. The results indicated that the use of NSM-CFRPs strips in different configurations efficiently increased the load-carrying capacity of the strengthened RC beams, in which all these beams exhibited a higher moment resistance than the corresponding un-strengthened beam. Results also showed that all strengthening schemes were successful in increasing the flexural capacity of the specimens tested. Such increases ranged between 10.36% and 52.28%. Notably, a significant improvement in the ultimate load ratio was observed with beams having a low compressive strength of 17-MPa, then followed by the beams with medium strength (32-MPa), and finally beams with high compressive strength (47-MPa). The NSM technique reduced the occurrence possibility of the CFRP de-bonding failure mode. Furthermore, the test results were compared with theoretical predictions using the ACI 440.2R17 guidelines and showed a good agreement between these results.
On the Large Eddy Simulation Modelling of Water Suppression Systems Droplet Impact and Coverage Area
Authors: De Cachinho Cordeiro Ivan Miguel , Liu Hengrui , Yuen Anthony Chun Yin , Chen Timothy Bo Yuan , Li Ao , Wang Cheng , Cao Ruifeng , Yeoh Guan Heng
Published: October 2022

In this article, a collective database from validated numerical simulation has been established to study the suppression effects of water-based suppression systems under a single-compartment fire scenario at various suppression configurations and fire locations. Five fuel locations along the axis between the centre and corner of the room were configurated to dynamically analyse how the horizontal distance between the nozzle and fuel pan affects the heat release rate (HRR), temperature cooling phenomena at different heights and also the velocity profile. Throughout the fuel pan relocations, the water-mist system has achieved an average suppression time of 25 s for all the locations, it was found that the water mist system can effectively control the fire under 200 °C that is distanced over 2 m spanwise displacement from the nozzle against the fire, while the sprinkler has exhibited an excellent fuel surface cooling effect due to large momentum and heat capacity within the coverage area with an average suppression time of 50 s. The results of this study have further explored the spray coverage and droplet penetrability of different suppression systems at different locations corresponding to the fire source, and the quantitative assessment of fuel locations could also contribute to the future development of performance-based fire safety designs.
Nutritional Components, Biochemical Characteristics, Enzyme Activities, and Growth Differences of Five Freshwater Fish Species?
Authors: Jiang Xiaona , Li Yan , Tian Jingwen , Li Chitao , Ge Yanlong , Hu Xuesong , Cheng Lei , Shi Xiaodan , Shi Lianyu , Jia Zhiying
Published: October 2022

Common carp (Cyprinus carpio) is an economically important fish worldwide, with many of its species bred for consumption. However, there are few reports on the comprehensive comparative analysis of the muscle nutritional quality and stress resistance characteristics of different common carp species. In this study, after 15 months of feeding in the same environment, the nutritional components, serum biochemical indices, liver antioxidant and intestinal digestive enzyme activities, and muscle growth-related gene expression were determined in Songpu mirror carp (SPM; Cyprinus carpio Songpumirror), Heilongjiang wild carp (HLJ; Cyprinus carpio haematopirus), cold-resistant strain of purse red carp (CPR; Cyprinus carpio ‘Red purse cold-resistant’), Songhe carp (SH; Cyprinus carpio ‘Songhe’), and Songpu carp (SP; Cyprinus carpio Songpu). Muscle nutrient composition showed that HLJ had a significantly lower crude fat content and higher docosahexaenoic acid (DHA) + eicosapentaenoic acid (EPA) proportion than the other four common carp species (p < 0.05). The contents of lysine (Lys) and aspargine (Asp) were significantly higher in the CPR than in other species (p < 0.05). Serum biochemical parameters showed that total protein (TP), total cholesterol (T-CHO), triglycerides (TG), and low-density lipoprotein (LDL) were significantly lower in SPM than in the other species (p < 0.05). The results of tissue enzyme activity showed that the activities of superoxide dismutase (SOD) and catalase from Micrococcus lysodeikticus (CAT) in the liver were significantly higher, while the activities of lipase (LPS), trypsin (TRS), and α-amylase (α-AMS) in the intestine were significantly the lower in HLJ than in the other species (p < 0.05). In addition, the relative expression levels of growth hormone (GH), growth hormone receptor (GHR), insulin-like growth factor 1 (IGF1), insulin-like growth factor receptor (IGF1R), and myoblast determination factor (MyoD) in SP and SH were significantly higher than those in the other species, while the relative expression of myostatin (MSTN) in HLJ was significantly higher (p < 0.05). Therefore, there were significant differences in muscle nutritional quality, serum biochemical indices, liver, and intestinal enzyme activities, and muscle growth potential among the five species of common carp. This study could provide a theoretical basis for the germplasm evaluation and variety improvement of common carp.
Development of a Fluorescence Polarization Assay for Multi-Determination of 10 Aminoglycosides in Pork Muscle Sample Based on Ribosomal Protein S12 and Studying Its Recognition Mechanism
Authors: Xia Wanqiu , Zhang Lei , Wang Jianping
Published: October 2022

The residues of aminoglycosides in foods of animal origin are a potential risk to consumers. There have been some immunoassays reported for the screening of aminoglycoside residues, but the method showing the broadest detection spectrum can only be used to detect two drugs. This is because a broad specific recognition reagent is not available. In the present study, the receptor of aminoglycosides (ribosomal protein S12 of Lysinibacillussphaericus) was expressed, and its affinities and recognition mechanisms for 10 aminoglycosides were studied by using surface plasmon resonance and molecular docking, respectively. Then the receptor was used as a recognition reagent to develop a fluorescence polarization assay on a 96-well microplate for the detection of the 10 drugs in pork muscle samples. The limits of detection for the 10 drugs ranged from 5.25 to 30.25 ng/g. The sensitivities for the 10 drugs were generally consistent with their respective receptor affinities and binding energies. After comprehensive comparison, the method performances were better than all the previously reported immunoassays for aminoglycosides. This is the first study reporting the recognition mechanisms of ribosomal protein S12 of Lysinibacillussphaericus for 10 aminoglycosides and the use of it as a recognition reagent to develop a pseudo-immunoassay for the multi-determination of aminoglycosides in food samples.
A Study on the Effects of Calcium Lactate on the Gelling Properties of Large Yellow Croaker (Pseudosciaena crocea) Surimi by Low-Field Nuclear Magnetic Resonance and Raman Spectroscopy
Authors: Sang Shangyuan , Chen Xiaoyun , Qin Ying , Tong Li , Ou Changrong
Published: October 2022

Divalent calcium ions (Ca2+) are often used in surimi gels to improve their physicochemical characteristics. The present study aimed to investigate the effect of calcium lactate on the physicochemical properties, state distribution of water, and protein structure changes of surimi gels made from large yellow croaker. The results showed that the addition of calcium lactate (0%, 0.5%, 1.5%, 2.5%, 3.5%, and 4.5% on wet surimi) significantly (p < 0.05) increased gel strength and whiteness, while cooking loss decreased. The water-holding capacity increased first and then decreased. When calcium lactate was added to 1.5%, the water-holding capacity reached the best value. Using low-field nuclear magnetic resonance to study the distribution of water state, the bound water content first increased and then decreased with the addition of calcium lactate, reaching the highest at 1.5%. In addition, the relaxation time of immobilized water was shortest at the addition of 1.5% calcium lactate. Analyzing the protein structural changes by Raman spectroscopy showed that there was a significant decrease (p < 0.05) in the α-helix accompanied by an increase in β-sheets, turns, and random coils after the addition of calcium lactate. The above changes were due to the Ca2+ that was bound to the negatively charged myofibrils to form a protein-Ca2+-protein cross-linking. Therefore, the addition of calcium lactate had a significant positive effect on the gelling ability of surimi.
A Novel Nonlinear Pseudorandom Sequence Generator for the Fractal Function
Authors: Feng Yelai , Wang Huaixi , Chang Chao , Lu Hongyi , Yang Fang , Wang Chenyang
Published: October 2022

A pseudorandom sequence is a repeatable sequence with random statistical properties that is widely used in communication encryption, authentication and channel coding. The pseudorandom sequence generator based on the linear feedback shift register has the problem of a fixed sequence, which is easily tracked. Existing methods use the secret linear feedback shift register (LFSR) and built-in multiple LFSRs and is difficult to prevent cracking based on the hardware analysis. Since the plaintext depends on a specific language to be generated, using pseudo-random sequence encryption, it faces the problem that the encryptor cannot hide the characteristics of the plaintext data. Fractal functions have the following properties: chaotic, unpredictable and random. We propose a novel pseudorandom sequence generator based on the nonlinear chaotic systems, which is constructed by the fractal function. Furthermore, we design a data processing matrix to hide the data characteristics of the sequence and enhance the randomness. In the experiment, the pseudo-random sequences generator passed 16 rigorous test items from the National Institute of Standards and Technology (NIST), which means that the nonlinear pseudorandom sequence generator for the fractal function is effective and efficient.
An Extended Dissipative Analysis of Fractional-Order Fuzzy Networked Control Systems
Authors: Vadivel Rajarathinam , Hammachukiattikul Porpattama , Vinoth Seralan , Chaisena Kantapon , Gunasekaran Nallappan
Published: October 2022

This study presents an extended dissipative analysis of fractional order fuzzy networked control system with uncertain parameters. First, we designed the network-based fuzzy controller for the considered model. Second, a novel Lyapunov-Krasovskii functional (LKF) approach, inequality techniques, and some sufficient conditions are established, which make the proposed system quadratically stable under the extended dissipative criteria. Subsequently, the resultant conditions are expressed with respect to linear matrix inequalities (LMIs). Meanwhile, the corresponding controller gains are designed under the larger sampling interval. Finally, two numerical examples are presented to illustrate the viability of the obtained criteria.
Hereditary Breast and Ovarian Cancer Service in Sparsely Populated Western Pomerania
Authors: Felbor Ute , Bülow Robin , Schmutzler Rita K. , Rath Matthias
Published: October 2022

The German Consortium Hereditary Breast and Ovarian Cancer (GC-HBOC) consists of 23 academic centers striving to provide high-quality regional care for affected individuals and healthy at-risk family members. According to the standard operating procedures defined by the GC-HBOC, a Familial Breast and Ovarian Cancer Center was implemented at the University Medicine Greifswald over a four-year period from 2018 to 2021, despite the COVID-19 pandemic. Genetic analyses were performed in a total of 658 individuals, including 41 males, which paved the way to local annual risk-adapted breast cancer surveillance for 91 women and prophylactic surgery for 34 women in 2021. Our experience in the North Eastern part of Germany demonstrates that it is possible to establish a high-risk breast and ovarian cancer service even in a sparsely populated region. Major facilitators are the interdisciplinary collaboration of dedicated local experts, the support of the GC-HBOC, fruitful clinical and scientific cooperations and the use of technical improvements. As a blueprint, our project report may help to further expand the network of specialized and knowledge-generating care for HBOC families.
Effects of Potassium Application on Lilium davidii var. unicolor Growth, Polysaccharide Accumulation, and Metabolism
Authors: Sha Xiaorong , Zhang Ping , Yang Ying , Bu Hubai , Ma Ying , Jin Lei
Published: October 2022

Lilium davidii var. unicolor is an important variety of lily with high economic, ornamental, edible, and medicinal values. Up to now, the research on polysaccharide as the main active substance is not vast, especially the effect of potassium on lily polysaccharide. Here, we investigated the effects of potassium fertilizer application on the growth and development, polysaccharide accumulation in the bulb, and differential metabolites in L. davidii var. unicolor. It was treated with fixed amounts of nitrogen (N) and phosphorus (P), and four K concentrations comprising K0 (0 mg·L−1), K1 (447.6 mg·L−1), K2 (671.4 mg·L−1), or K3 (895.2 mg·L−1). The growth indexes were determined for L. davidii var. unicolor under different K concentrations in different growth stages. The polysaccharide contents of the bulbs were determined using the sulfuric acid−phenol method. An analysis of the differential polysaccharide metabolites was also conducted. The application of potassium promoted the growth and increased the bulb polysaccharide content of L. davidii var. unicolor, and the most suitable K concentration of 671.4 mg·L−1 had the most significant effects. Non-targeted metabolomics analysis screened 37 differential polysaccharide metabolites under K0 and K2, where 25 were significantly upregulated and 12 were significantly downregulated. Three metabolic pathways were enriched in polysaccharide-related differential metabolites, i.e., the galactose metabolism, amino sugar and nucleotide sugar metabolism, and starch and sucrose metabolism. The results could provide a theoretical basis for an improved fertilization management and the high-quality cultivation of L. davidii var. unicolor.