bluuebunny/crossref_metadata_2025 huggingface dataset:
The safety and feasibility of laparoscopic right posterior sectionectomy vs. open approach: A systematic review and meta-analysis
Authors: Wang Meng-Xiao , Xiang Ji-Feng , Chen Sheng-Kai , Xiao Lin-Kang
Published: October 2022

Background

Laparoscopic right posterior sectionectomy (LRPS) is one of the most technically challenging and potentially hazardous procedures in laparoscopic liver resection. Although some available literature works demonstrated the safety and feasibility of LRPS, these data are limited to reports from a single institution and a small sample size without support from evidence-based medicine. So, we performed a meta-analysis to assess further the safety and feasibility of LRPS by comparing it with open right posterior sectionectomy (ORPS).

Methods

MEDLINE, Embase, and Cochrane Library were systematically searched for eligible studies comparing LRPS and open approaches. Random and fixed-effects models were used to calculate outcome measures.

Results

Four studies involving a total of 541 patients were identified for inclusion: 250 in the LRPS group and 291 in the ORPS group. The postoperative complication and margin were not statistically different between the two groups (OR: 0.49, 95% CI: 0.18 to 1.35, P = 0.17) (MD: 0.05, 95% CI: −0.47 to 0.57, P = 0.86), respectively. LRPS had a significantly longer operative time and shorter hospital stay (MD: 140.32, 95% CI: 16.73 to 263.91, P = 0.03) (MD: −1.64, 95% CI: −2.56 to −0.72, P = 0.0005) respectively.

Conclusion

Data from currently available literature suggest that LRPS performed by an experienced surgeon is a safe and feasible procedure in selected patients and is associated with a reduction in the hospital stay.
Comprehensive clinical analysis of patients with primary malignant tumor of pituitary gland: A population-based study
Authors: Sun Xu , Huo Lanqing , Wang Xin , Zhang Chunlan , Zhao Ailin
Published: October 2022

Background and Objectives

This study aims to perform a comprehensive clinical analysis of patients with primary malignant pituitary tumors (PMPT) that involves incidence, demographics, treatments, long-term survival, and death causes.

Materials and methods

Patients with PMPT were identified from registries of the Surveillance, Epidemiology, and End Results (SEER) database. Frequencies and average annual age-adjusted rate (AAR) were calculated for incidence trend analyses using Join-point regression. Univariate and multivariate Cox regression analyses were conducted to identify potential prognostic factors associated with patients' survival outcomes. Using the Kaplan–Meier method and log-rank test, survival curves were plotted and compared, respectively. Propensity score matching (PSM) was performed to balance baseline characteristics.

Results

The AAR for PMPT was 0.233 (95%CI: 0.205–0.264) per 1,000,000 using nine SEER registries from 1975 to 2017. The incidence trend has declined over years but without significance (–1.04% per year, P = 0.10). Besides, older age may indicate a higher incidence rate for both pediatric and adult patients. From 18 SEER registries, a total of 501 PMPT patients were also identified. Univariate and multivariate Cox regression showed age, sex, tumor extent, and marital status were independent prognostic factors for malignant pituitary tumors. Via PSM, we found that patients who received surgery, radiotherapy, and chemotherapy did not demonstrate significantly different survival than those who did not.

Conclusion

This study first conducts a comprehensive clinical analysis of patients with PMPT and provides guide effects on future study designs. More studies should be conducted to focus on its characteristics and therapy.
The Assignment Problem and Its Relation to Logistics Problems
Authors: Seda Milos
Published: October 2022

The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution, and scheduling problems. Showing such correlations is one of the aims of this paper. For some of the derived problems having exponential time complexity, the question arises of their solvability for larger instances. Instead of the traditional approach based on the use of approximate or stochastic heuristic methods, we focus here on the direct use of mixed integer programming models in the GAMS environment, which is now capable of solving instances much larger than in the past and does not require complex parameter settings or statistical evaluation of the results as in the case of stochastic heuristics because the computational core of software tools, nested in GAMS, is deterministic in nature. The source codes presented may be an aid because this tool is not yet as well known as the MATLAB Optimisation Toolbox. Benchmarks of the permutation flow shop scheduling problem with the informally derived MIP model and the traveling salesman problem are used to present the limits of the software’s applicability.
A Method of Accuracy Increment Using Segmented Regression
Authors: Al-Azzeh Jamil , Mesleh Abdelwadood , Zaliskyi Maksym , Odarchenko Roman , Kuzmin Valeriyi
Published: October 2022

The main purpose of mathematical model building while employing statistical data analysis is to obtain high accuracy of approximation within the range of observed data and sufficient predictive properties. One of the methods for creating mathematical models is to use the techniques of regression analysis. Regression analysis usually applies single polynomial functions of higher order as approximating curves. Such an approach provides high accuracy; however, in many cases, it does not match the geometrical structure of the observed data, which results in unsatisfactory predictive properties. Another approach is associated with the use of segmented functions as approximating curves. Such an approach has the problem of estimating the coordinates of the breakpoint between adjacent segments. This article proposes a new method for determining abscissas of the breakpoint for segmented regression, minimizing the standard deviation based on multidimensional paraboloid usage. The proposed method is explained by calculation examples obtained using statistical simulation and real data observation.
Manned Mars Mission Analysis Using Mission Architecture Matrix Method
Authors: Shen Diyang , Yue Yuxian , Wang Xiaohui
Published: October 2022

With the development of deep space exploration technology, manned missions to Mars are expected to be realized in the near future. However, the journey to Mars requires more supplies and fuel than near-Earth missions, including moon landings. Using the traditional Apollo-style mission method will result in the spacecraft reaching the LEO mass of 2000 tons, which is not easy to achieve. The use of the modular design method and multiple launches will significantly reduce the mass of a single launch. In addition, the use of nuclear power engines (Nuclear Thermal Propulsion, NTP, and Nuclear Electric Propulsion, NEP) can greatly improve propulsion efficiency, reducing the mass of the propellant. This paper uses the Mission Architecture Matrix (MAM) method to concisely and precisely analyze a series of mission architectures in the case of impulse maneuver transfer and low-thrust transfer. The results show that when only chemical propulsion (specific impulse is 440 s) is used, the maximum LEO launch mass in the optimal mission architecture is 325 tons, and the total LEO mass of the system is 1142 tons. With the usage of NTP (specific impulse is 900 s) and NEP (the specific impulse is 6000 s) technology, the maximum LEO launch mass in the optimal mission architecture is only 85 tons, and the total LEO mass of the system is only about 400 tons. Considering the current rocket technology, the total cost is about USD 1149 million US.
The Beneficial Effects of Insect Pollination and Biochar Seed Coating on Okra (Abelmoschus esculentus) Seed Quality at Varying Temperature Conditions
Authors: Adelabu Dolapo B. , Franke Angelinus C.
Published: October 2022

Underutilized crops, such as okra, have the potential to alleviate stress on crop production imposed by climate change and farming conditions, but their production is greatly hindered by poor seed quality. Insect pollination and seed coating with organic substances (biochar) may improve okra’s seed performance, but the beneficial effects of biochar seed coating and pollination on the seed quality of okra grown under stressful conditions is unknown. We examined the impact of pollination and biochar seed coating on okra seed performance under varying temperatures. Seeds were obtained from plants grown under complete insect pollination and exclusion. A factorial experiment was conducted in growth chambers with three factors: seed type, seed coating and temperature conditions. Insect-pollinated seeds with biochar coating had the highest chlorophyll content, seedling vigour index, shoot, and root growth and the heaviest seedling mass, but with a reduced speed of germination and emergence. The insect-pollinated seed without biochar coating had a lighter seedling mass (33% lower) than insect-pollinated, coated seed. Low temperature conditions during germination were ameliorated by biochar seed coating but biochar coating could not alleviate high temperature (35/30 °C) stress. Harnessing the pollinator’s benefits and biochar seed coating are possible sustainable solutions to enhance seed quality.
Effect of Maternal Dietary Condensed Tannins from Sainfoin (Onobrychis viciifolia) on Gut Health and Antioxidant-Immune Crosstalk in Suckling Lambs
Authors: Pelegrin-Valls Jonathan , Álvarez-Rodríguez Javier , Martín-Alonso María , Ramírez Gustavo , Baila Claudia , Lobon Sandra , Joy Margalida , Serrano-Pérez Beatriz
Published: October 2022

Ewes fed sainfoin (a source of condensed tannins “CT”) may influence the homeostasis of the gastrointestinal tract of suckling lambs. This study investigated the effects of CT from sainfoin in the maternal diet on plasma fructosamine, faecal coccidian excretion, and gene expression of immune and antioxidant markers in jejunum and ileum of suckling lambs. Twelve Rasa Aragonesa lambs with their dams were selected. The maternal diet was based on fresh sainfoin (SAINFOIN, n = 6) and sainfoin + polyethylene-glycol (SAINFOIN + PEG, as a CT-binder, n = 6) plus a daily supplement of 200 g barley in both groups. A lower percentage of lambs that shed more than 10 oocysts/g faeces was observed in SAINFOIN compared to the SAINFOIN + PEG group (p = 0.07). Jejunal gene expression of transforming growth factor-β1, tumour necrosis factor-α, and glutathione peroxidase (GPX) 1 and 4 were lower in the SAINFOIN group (p < 0.05). In contrast, ileal catalase and GPX2 expression were increased in the SAINFOIN group (p < 0.05). Overall, the results suggest that the presence of CT in the dams’ diets has a positive effect on reducing excreted coccidian oocysts and favours antioxidant-immune crosstalk at gut level in suckling lambs.
Changes in Spatial Distribution of Arable Land, Crop Production and Yield of Selected Crops in the EU Countries after 2004
Authors: Némethová Jana , Svobodová Hana , Věžník Antonín
Published: October 2022

Agriculture is not a major economic sector in EU member states in terms of economy, however, crop production in particular is necessary for the nutrition of the population, and it is also crucial for its non-agricultural functions. The aim of this paper was to analyse the differentiation in the spatial distribution of arable land, and the development of production and yield per hectare of selected crops—cereals, oilseeds and potatoes in the EU countries as these are the main crops in the EU. The analysis of the crop production development based on the comparison of the EU member states for the period from 2004 to 2019 through the index of change was performed. The results show no clear changes in the crop production across the EU member states and the monitored 5 to 6-year periods; however, dynamics in the “new” member states entering the EU after 2004 are higher. Above all, significant regional geographical differences between individual EU states were found, which mainly reflect different natural conditions and prerequisites for agriculture, as well as differences in the historical and social development of individual countries.
Effects of Biochar Application on Soil Hydrothermal Environment, Carbon Emissions, and Crop Yield in Wheat Fields under Ridge–Furrow Rainwater Harvesting Planting Mode
Authors: Ma Xiangcheng , Lv Mengfan , Huang Fangyuan , Zhang Peng , Cai Tie , Jia Zhikuan
Published: October 2022

The ridge–furrow rainwater harvesting (RFRH) planting mode is widely used in arid and semi-arid areas to solve the problems of agricultural water shortage and low productivity. However, the impact of film mulching on the stability of soil carbon pools makes this planting mode vulnerable to the risk of increased soil carbon emissions and carbon pool losses. In order to clarify the relationship between soil carbon emissions and hydrothermal factors, as well as the regulatory effect of biochar application on soil carbon sequestration and reduced emissions under this planting mode, we set up a biochar application experiment. The effects of the biochar application (at 10 Mg ha−1 biochar and 20 Mg ha−1 biochar) on the soil water dynamics, soil temperature changes, CO2-C and CH4-C flux dynamics, grain yield, carbon emission efficiency, and the net ecosystem carbon budget in wheat fields under the RFRH planting mode were investigated, with no biochar application as the control. The results showed that applying biochar increased the soil water content, soil average temperature, cumulative CH4-C uptake, wheat grain yield, and carbon emission efficiency by 3.10–12.23%, 0.98–3.53%, 59.27–106.65%, 3.51–16.42%, and 18.52–61.17%, respectively; reduced the cumulative CO2-C emissions by 7.51–31.07%; and increased the net ecosystem carbon budget by 2.91 Mg C ha−1 to 6.06 Mg C ha−1. The results obtained by equation fitting showed that in wheat fields under RFRH, the CO2-C emission fluxes had negative and positive exponential relationships with the soil water content and soil temperature, respectively, while the CH4-C uptake fluxes had no significant correlation with the soil water content and had an inverse U-shaped quadratic function relationship with soil temperature. Overall, these results suggest that the application of biochar to wheat fields under RFRH can improve grain yield, farmland carbon emission efficiency, and the net ecosystem carbon budget, and change wheat fields from a carbon source to a carbon sink. These results can provide a theoretical basis and technical support for efficient, green, and sustainable production in farmland in arid and semi-arid areas.
A Novel Approach for Monitoring of Smart Greenhouse and Flowerpot Parameters and Detection of Plant Growth with Sensors
Authors: Kirci Pinar , Ozturk Erdinc , Celik Yavuz
Published: October 2022

Studies carried out in different parts of the world and in different climatic conditions have made it clear that it is very important to use smart technologies in solving the problems experienced in the field of agriculture globally and locally. Another important aim of the studies is to ensure that agricultural products are grown in smart greenhouse environments outside of arable lands. For this reason, growing agricultural products in greenhouses controlled by smart systems by creating suitable soil and climatic conditions and facilitating people’s access to these products has been an important research and application subject. In this paper, the topics of “Smart Agriculture” and “Smart Greenhouse” were worked on. Therefore, a prototype of a smart greenhouse was constructed. Then, it was programmed according to the decided climatic conditions. Consequently, the main aim of this study was to improve the project according to the collected data by the sensors. One of the most important aims of our study was to question the possibility of growing different plants in the same greenhouse. In this context, in our study, a flower and three different vegetables with close growing conditions were grown in the same greenhouse in the same environment. These plants were grown individually both in the smart greenhouse prototype and in the pots outdoors in a natural environment. The differences between the two environments and the differences in the development of the plants were examined and the necessary results were obtained based on the findings. Based on the results obtained, it has been discussed what can be done if the plants grown in the greenhouse, of which we have created a small-scale prototype, are grown in a large-scale smart greenhouse. According to the results obtained, the smart greenhouse made a positive difference in the development of begonia, tomato and pepper. Although, the cucumbers grew more in the pots. In the study, it was observed that the plants were healthier in the smart greenhouse. The cucumbers in the greenhouse grew to 132 mm, the peppers to 61 mm and the tomatoes to 70 mm. The cucumbers in the pot grew to 163 mm, the peppers to 37 mm and the tomatoes to 60 mm. This shows that the yield was positively affected in the smart greenhouse. According to the collected results, the smart greenhouse system saved approximately 16.5% of water compared to the pot. The fact that the system can work both manually and autonomously provides a great convenience for the person controlling the greenhouse.
Real-Time Foreign Object and Production Status Detection of Tobacco Cabinets Based on Deep Learning
Authors: Wang Chengyuan , Zhao Junli , Yu Zengchen , Xie Shuxuan , Ji Xiaofei , Wan Zhibo
Published: October 2022

Visual inspection plays an important role in industrial production and can detect product defects at the production stage to avoid major economic losses. Most factories mainly rely on manual inspection, resulting in low inspection efficiency, high costs, and potential safety hazards. A real-time production status and foreign object detection framework for smoke cabinets based on deep learning is proposed in this paper. Firstly, the tobacco cabinet is tested for foreign objects based on the YOLOX, and if there is a foreign object, all production activities will be immediately stopped to avoid safety and quality problems. Secondly, the production status of tobacco cabinet is judged to determine whether it is in the feeding state by the YOLOX position locating method and canny threshold method. If it is not in the feeding state, then the three states of empty, full, and material status of the tobacco cabinet conveyor belt are judged based on the ResNet-18 image classification network. Ultilizing our proposed method, the accuracy of foreign object detection, feeding state detection and the conveyor belt of tobacco cabinet state detection are 99.13%, 96.36% and 95.30%, respectively. The overall detection time was less than 1 s. The experimental results show the effectiveness of our method. It has important practical significance for the safety, well-being and efficient production of cigarette factories.
Integration of Machine Learning-Based Attack Detectors into Defensive Exercises of a 5G Cyber Range
Authors: Mozo Alberto , Pastor Antonio , Karamchandani Amit , de la Cal Luis , Rivera Diego , Moreno Jose Ignacio
Published: October 2022

Cybercrime has become more pervasive and sophisticated over the years. Cyber ranges have emerged as a solution to keep pace with the rapid evolution of cybersecurity threats and attacks. Cyber ranges have evolved to virtual environments that allow various IT and network infrastructures to be simulated to conduct cybersecurity exercises in a secure, flexible, and scalable manner. With these training environments, organizations or individuals can increase their preparedness and proficiency in cybersecurity-related tasks while helping to maintain a high level of situational awareness. SPIDER is an innovative cyber range as a Service (CRaaS) platform for 5G networks that offer infrastructure emulation, training, and decision support for cybersecurity-related tasks. In this paper, we present the integration in SPIDER of defensive exercises based on the utilization of machine learning models as key components of attack detectors. Two recently appeared network attacks, cryptomining using botnets of compromised devices and vulnerability exploit of the DoH protocol (DNS over HTTP), are used as the support use cases for the proposed exercises in order to exemplify the way in which other attacks and the corresponding ML-based detectors can be integrated into SPIDER defensive exercises. The two attacks were emulated, respectively, to appear in the control and data planes of a 5G network. The exercises use realistic 5G network traffic generated in a new environment based on a fully virtualized 5G network. We provide an in-depth explanation of the integration and deployment of these exercises and a complete walkthrough of them and their results. The machine learning models that act as attack detectors are deployed using container technology and standard interfaces in a new component called Smart Traffic Analyzer (STA). We propose a solution to integrate STAs in a standardized way in SPIDER for the use of trainees in exercises. Finally, this work proposes the application of Generative Adversarial Networks (GANs) to obtain on-demand synthetic flow-based network traffic that can be seamlessly integrated into SPIDER exercises to be used instead of real traffic and attacks.
Iron Deficiency Modulates Secondary Metabolites Biosynthesis and Antioxidant Potential in Sulla carnosa L. Primed with Salicylic Acid
Authors: Jelali Nahida , Wasli Hanen , Youssef Rim Ben , Hessini Kamel , Cardoso Susana M.
Published: October 2022

Iron (Fe) is a vital nutrient for the development of many plants. Therefore, enhancing plant performance and production in relation to Fe deficiency is becoming a serious challenge. In this work, we intended to survey the effect of seed pretreatment with salicylic acid (SA) on oxidative status, phenolic composition, and related antioxidant activities in two varieties of Sulla carnosa (Sidi Khlif: SK and Kalbia: KA) treated with different Fe concentrations. In unprimed plants, the levels of phenolic compounds were very distinguishable among the two varieties, being superior in KA compared to SK. Interestingly, priming KA seeds with SA under control conditions or deficient conditions (D+SA treatment) caused a decreasing tendency in the contents of total phenolic compounds (TPC) and total flavonoids (TFC), whereas an opposite behavior was observed in SK. Moreover, an improvement of hydroxycinnamic and flavonoid groups, in addition to antioxidant activities (TAC, DPPH●, β-carotene and FRAP), was markedly found in SK primed with SA. According to these findings, SA seed pretreatment had a beneficial effect on the metabolic performance of this species under different Fe supply, regardless of whether the intensity of improvement was related to Fe concentration applied, variety, as well as plant organ. The results suggest that SA can account for the effective modulation of the secondary metabolites metabolism in S. carnosa plants to deal with the detrimental impacts of Fe deficiency.
Kerr-Lens Mode-Locking: Numerical Simulation of the Spatio-Temporal Dynamics on All Time Scales
Authors: Parshani Idan , Bello Leon , Meller Mallachi-Elia , Pe’er Avi
Published: October 2022

We present a complete numerical analysis and simulation of the full spatio-temporal dynamics of Kerr-lens mode-locking in a laser. This dynamic, which is the workhorse mechanism for generating ultrashort pulses, relies on the intricate coupling between the spatial nonlinear propagation and the temporal nonlinear compression. Our numerical tool emulates the dynamical evolution of the optical field in the cavity on all time-scales: the fast time scale of the pulse envelope within a single round trip, and the slow time-scale between round-trips. We employ a nonlinear ABCD formalism that fully handles all relevant effects in the laser, namely—self focusing and diffraction, dispersion and self-phase modulation, and space-dependent loss and gain saturation. We confirm the validity of our model by reproducing the pulse-formation in all aspects: The evolution of the pulse energy, duration, and gain during the entire cavity buildup, demonstrating the nonlinear mode competition in full, as well as the dependence of the final pulse in steady state on the interplay between gain bandwidth, dispersion, and self-phase modulation. The direct observation of the nonlinear evolution of the pulse in space-time is a key enabler to analyze and optimize the Kerr-lens mode-locking operation, as well as to explore new nonlinear phenomena.
Survival Prediction of Glioma Patients from Integrated Radiology and Pathology Images Using Machine Learning Ensemble Regression Methods
Authors: Rathore Faisal Altaf , Khan Hafiz Saad , Ali Hafiz Mudassar , Obayya Marwa , Rasheed Saim , Hussain Lal , Kazmi Zaki Hassan , Nour Mohamed K. , Mohamed Abdullah , Motwakel Abdelwahed
Published: October 2022

Gliomas are tumors of the central nervous system, which usually start within the glial cells of the brain or the spinal cord. These are extremely migratory and diffusive tumors, which quickly expand to the surrounding regions in the brain. There are different grades of gliomas, hinting about their growth patterns and aggressiveness and potential response to the treatment. As part of routine clinical procedure for gliomas, both radiology images (rad), such as multiparametric MR images, and digital pathology images (path) from tissue samples are acquired. Each of these data streams are used separately for prediction of the survival outcome of gliomas, however, these images provide complimentary information, which can be used in an integrated way for better prediction. There is a need to develop an image-based method that can utilise the information extracted from these imaging sequences in a synergistic way to predict patients’ outcome and to potentially assist in building comprehensive and patient-centric treatment plans. The objective of this study is to improve survival prediction outcomes of gliomas by integrating radiology and pathology imaging. Multiparametric magnetic resonance imaging (MRI), rad images, and path images of glioma patients were acquired from The Cancer Imaging Archive. Quantitative imaging features were extracted from tumor regions in rad and path images. The features were given as input to an ensemble regression machine learning pipeline, including support vector regression, AdaBoost, gradient boost, and random forest. The performance of the model was evaluated in several configurations, including leave-one-out, five-fold cross-validation, and split-train-test. Moreover, the quantitative performance evaluations were conducted separately in the complete cohort (n = 171), high-grade gliomas (HGGs), n = 75, and low-grade gliomas (LGGs), n = 96. The combined rad and path features outperformed individual feature types in all the configurations and datasets. In leave-one-out configuration, the model comprising both rad and path features was successfully validated on the complete dataset comprising HGFs and LGGs (R=0.84 p=2.2×10−16). The Kaplan–Meier curves generated on the predictions of the proposed model yielded a hazard ratio of 3.314 [95%CI:1.718−6.394], log−rank(P)=2×10−4 on combined rad and path features. Conclusion: The proposed approach emphasizes radiology experts and pathology experts’ clinical workflows by creating prognosticators upon ‘rad’ radiology images and digital pathology ‘path’ images independently, as well as combining the power of both, also through delivering integrated analysis, that can contribute to a collaborative attempt between different departments for administration of patients with gliomas.
Conflict Risk Assessment between Non-Cooperative Drones and Manned Aircraft in Airport Terminal Areas
Authors: Zhu Renwei , Yang Zhao , Chen Jun
Published: October 2022

Recent years have seen an increase in events of drone incursion into airport terminal areas, leading to safety concerns and disruptions to airline operations. It is of great importance to identify the potential conflict, especially for those non-cooperative drones, as their intentions are always unknown. For the safe operation of air traffic, this paper proposes a conflict risk assessment method between non-cooperative drones and manned aircraft in the terminal area. First, the trajectory data of manned aircraft and drones are obtained. Real-time cylindrical protection zones are established around manned aircraft according to the separation interval for safe operation between the drone and the manned aircraft at different altitudes. Secondly, trajectory predictions for the manned aircraft and the drone are conducted, respectively. A quartile regression bidirectional gate recurrent unit neural network is proposed in this research for the trajectory prediction of the drones. The model integrates the bidirectional gated recurrent unit structure and the quartile regression structure. The performance indicators confirm the superiority of the proposed model. Based on the trajectory prediction results, it is then determined whether there is a conflict risk between the drone and manned aircraft by comparing the position distribution of the drone as well as the real-time cylindrical protection zone of the manned aircraft. The conflict probability between the drone and the manned aircraft is then calculated. The prediction accuracy of conflict probability is estimated by Monte Carlo simulation methods. The collision probability prediction accuracy of manned aircraft and drones at different flight stages and altitudes ranges from 73% to 97%, which shows the reliability of the proposed method. Finally, the collision probability between the drone and the manned aircraft at the closest encountering point and the estimated time to reach the closest encountering point are calculated. This paper predicts the conflict risk between the drone and manned aircraft, thus providing theoretical support for the safe operation of air transport in low-altitude environments.
Measurements and Correctness Criteria for Determining the Line Length of the Data Image Obtained in the Process of Electromagnetic Infiltration
Authors: Kubiak Ireneusz , Przybysz Artur
Published: October 2022

The protection of information against electromagnetic penetration is one of the most important aspects related to the protection of information against its non-invasive acquisition. Compared to the activities of cybercriminals, the use of electromagnetic emissions in the electromagnetic infiltration process does not leave any traces of activity, and the owner of the information is not aware of its loss. The most common activities of electromagnetic eavesdropping are related to the infiltration of emission sources, graphically revealing the processing of information using both analog and digital methods. This allows for the presentation of reconstructed data in the form of images. Correct display of the acquired information requires knowledge of raster parameters such as line length and the number of lines building the reconstructed image. Due to the lack of direct access to the intercepted device, knowledge in this field does not allow for the correct determination of the aforementioned parameters, and thus, for recreating an image that would contain legible and understandable data. Additionally, incorrect values of the parameters result in failure of further processing of the obtained image, e.g., by using a coherent summation of images. Therefore, it is necessary to propose a solution that will allow not so much to roughly define the raster parameters but to estimate them precisely. Moreover, it should enable the automation of the process after the implementation of an appropriate algorithm. The article proposes an algorithm for estimating the line length of the reconstructed image. The raster parameter estimated with the use of the algorithm allows for summarizing images several dozen times with a significant improvement in the image quality and readability of the data contained in it. The image summation algorithm is very often used as one of the main image processing methods in the electromagnetic infiltration process. Incorrect raster parameters often make coherent summation useless. The proposed algorithm for estimating the line length of the reconstructed image uses three methods of determining the line length of the image for a given accuracy. At the same time, criteria were indicated that must be met to determine the correct length of the image line for the assumed accuracy of estimation. Obtained results confirmed that the proposed methods and criteria are effective in the process of electromagnetic infiltration. These methods allow us to determine the line length of reconstructed images with accuracy up to 10−5.
Elasto-Plastic Short Exoskeleton to Improve the Dynamic and Seismic Performance of Frame Structures
Authors: Di Egidio Angelo , Pagliaro Stefano , Contento Alessandro
Published: October 2022

The coupling with external mechanical systems such as oscillating masses working as tuned mass dampers, dynamic mass absorbers, elasto-plastic dampers, and rigid walls is an effective method to reduce the displacements and drifts of structures under external loads. An alternative method is provided by the coupling of the structure with an independent, auxiliary elasto-plastic system. This paper investigates the dynamic and seismic behaviour of a structure rigidly coupled with an auxiliary yielding mechanical system under harmonic and seismic ground excitation. A two-degree-of-freedom model is used to describe the dynamic and seismic behaviour of the main structure rigidly coupled to the yielding system, which is described by a one-degree-of-freedom model. The auxiliary system has an elasto-plastic constitutive behaviour that is modelled by a Bouc-Wen model. The equations of motion of the coupled system are obtained by a direct approach. The coupling with the yielding system is considered beneficial if the displacements of the coupled system reduce with respect to those of the stand-alone frame structure. An extensive parametric analysis is performed to point out the role of the mechanical parameters that describe the elasto-plastic constitutive behaviour of the auxiliary system. Results reveal that in large ranges of the parameters’ values, the coupling with the elasto-plastic system improves the performance of the frame structure.
DLP Light-Curing 3D Printing Combustible Lighting Shell and Performance Study
Authors: Wang Haibo , Ba Shuhong , Zhang Bo , Li Linpeng
Published: October 2022

In order to further improve the luminous intensity of illuminating flares, the technique of 3D printing of the combustible shell of the illuminating flare using DLP light-curing was proposed, and the combustion spectrum of the combustible shell was made consistent with the combustion spectrum of the illuminating agent. A combustible illuminating candle shell slurry formulation was designed, with light-curing resin, magnesium powder, and sodium nitrate as the main components, and was printed and molded by DLP light-curing 3D printing technology to test its luminescence properties, mechanical properties, compatibility, and moisture absorption. The results show that the optimal formulation mass fraction of energy-containing slurry for the 3D printing of the combustible lighting candle shell is 50% for light-curing resin, 41% for sodium nitrate (NaNO3), and 9% for magnesium powder (Mg). The mechanical properties of the shell are good, with tensile strength up to 9.82 MPa and compressive strength of 102.86 MPa, and the compatibility of the components of the formulation is good, with stable combustion, and can provide 4.73% of light intensity for the lighting candle.
Pasteurization of Foods with Ultrasound: The Present and the Future
Authors: Bermudez-Aguirre Daniela , Niemira Brendan A.
Published: October 2022

In the last two decades, much research has been carried out using ultrasound as an alternative for pasteurization. Cavitation, the main effect of ultrasound, can disrupt and perforate cell membranes, generate free radicals, and produce sonoluminescence. Ultrasound in combination with additional hurdles such as temperature, pressure, or antimicrobials can achieve a 5-log reduction. Pathogens, spoilage microorganisms, yeast, and molds have been successfully inactivated by this novel technology. Currently, ultrasound is investigated as an option to reduce the content of aflatoxins during pasteurization. Ultrasound can inactivate those enzymes related to the stability of pasteurized food products, extending the shelf-life of the products. New uses of sonication are surging; for example, ultrasound has been studied as an option for pasteurizing plant-based foods. An important area of research is ultrasound’s effect on food’s bioactive compounds. Results exhibit an increase in the concentration of phenolics, carotenoids, anthocyanins, and other nutrients after the use of ultrasound because of an extractive effect. Finally, an area of concern in the early ages of ultrasound has been studied, food quality. In most cases, sonicated products have similar quality parameters to raw products. Lastly, there are some areas of opportunity in ultrasound’s future, such as the equipment improvement, regulation, and toxicology of sonicated products.
Reliability Modelling Considering Self-Exciting Mechanisms of Shock Damage
Authors: Wu Yaguang
Published: October 2022

This study investigates reliability modelling and optimal preventive maintenance polices for engineering systems subject to shocks, considering two types of self-exciting mechanisms. Under trigger mechanism 1, if the accumulative number of δ—ineffective shocks reaches the trigger threshold k1 among the run of ineffective shocks, then the self-exciting mechanism will be activated, resulting in the accumulative number of effective shocks increasing by m1. Under trigger mechanism 2, if the consecutive number of δ—ineffective shocks reaches a fixed threshold K2 among the run of ineffective shocks, then the self-exciting mechanism will be triggered and the accumulative number of effective shocks will increase by m2. The system breaks down when the accumulative number of effective shocks exceeds the fixed threshold. Based on the established shock models, the reliability indices are obtained through the finite Markov chain imbedding approach. According to the operation of the system under different monitoring conditions, two types of preventive maintenance strategies are considered; then, optimization models are established, and the optimal preventive maintenance thresholds are determined. Finally, the proposed models are illustrated by numerical examples.
Physics-Informed Generative Adversarial Network-Based Modeling and Simulation of Linear Electric Machines
Authors: Wu Huihuan , Niu Shuangxia , Zhang Yunpeng , Fu Weinong
Published: October 2022

The demand for fast magnetic field approximation for the optimal design of electromagnetic devices is urgent nowadays. However, due to the lack of a publicly available dataset and the unclear definition of each parameter in the magnetic field dataset, the expansion of data-driven magnetic field approximation is severely limited. This study presents a physics-informed generative adversarial network (PIGAN), as well as a permanent magnet linear synchronous motor (PMLSM)-based magnetic field dataset, for fast magnetic field approximation. It includes the current density, material distribution, electromagnetic material properties, and other parameters of the electric machine. Physics-informed loss functions are utilized in the training process, making the output governed by Maxwell’s equation. Different slot-pole combinations of the PMLSM are involved in the dataset to extend the generalization of PIGAN. Some indicators for the further evaluation of magnetic approximation performance, including image-based metrics and calculation methods for the performance of electric motors, are presented in this study. Some challenges of magnetic field approximation using PIGAN are also discussed. The effectiveness of the physics-informed method is verified by comparing the magnetic field approximation results and the performance analysis results of the PMLSM with FEM, and the speed of PIGAN is approximately 40 times faster than that of FEM, while the accuracy is similar.
An Implementation of Actor-Critic Algorithm on Spiking Neural Network Using Temporal Coding Method
Authors: Lu Junqi , Wu Xinning , Cao Su , Wang Xiangke , Yu Huangchao
Published: October 2022

Taking advantage of faster speed, less resource consumption and better biological interpretability of spiking neural networks, this paper developed a novel spiking neural network reinforcement learning method using actor-critic architecture and temporal coding. The simple improved leaky integrate-and-fire (LIF) model was used to describe the behavior of a spike neuron. Then the actor-critic network structure and the update formulas using temporally encoded information were provided. The current model was finally examined in the decision-making task, the gridworld task, the UAV flying through a window task and the avoiding a flying basketball task. In the 5 × 5 grid map, the value function learned was close to the ideal situation and the quickest way from one state to another was found. A UAV trained by this method was able to fly through the window quickly in simulation. An actual flight test of a UAV avoiding a flying basketball was conducted. With this model, the success rate of the test was 96% and the average decision time was 41.3 ms. The results show the effectiveness and accuracy of the temporal coded spiking neural network RL method. In conclusion, an attempt was made to provide insights into developing spiking neural network reinforcement learning methods for decision-making and autonomous control of unmanned systems.
Numerical Study of Influencing Factors of Safety and Stability of Tunnel Structure under Airport Runway
Authors: Yang Liuchuan , Wei Xiaogang , Fa Jingyu , Li Guanghui , Shi Xiushan , Bi Sifu
Published: October 2022

A six-degree-of-freedom mathematical model and mechanical balance equation of a “five-point-contact” aircraft are established in this study. The model and equation are used to investigate the safety and stability of a tunnel structure under the runway of an airport, particularly when aircraft taxi or move on the runway. ABAQUS is used to construct a three-dimensional finite element model of the cooperative deformation of the airport runway–soil–tunnel structure. The analysis focuses on the response and evolution of structural safety mechanical indices from the perspective of three influencing factors: type of aircraft, road surface, and burial depth. The results show that the distribution position of the main landing gear wheel is more concentrated using the dynamic load equation of different aircraft. A rigid pavement is not easily deformed when subjected to aircraft loads, whereas a flexible pavement has an excellent attenuation effect on diffusing forces. The shear stresses on the upper and lower arches of the tunnel structure differ depending on the pavement material. The deformation of the arches under shear stress is more intense than that of other parts. With an increase in burial depth, the tunnel structure withstanding the aircraft load disturbance exhibits an attenuation trend. The disturbance caused by soil stress to the tunnel structure must not be ignored. When the burial depth of the tunnel exceeds 64 m, the tunnel structure ceases to be disturbed by aircraft loads. The research results can significantly guide airport construction and be used as a reference for investigating the safety and stability of substructures under airport runways.
The Limit of the Lateral Fundamental Frequency and Comfort Analysis of a Straddle-Type Monorail Tour Transit System
Authors: Guo Fengqi , Ji Yanqiang , Liao Qiaoyun , Liu Bo , Li Chenjia , Wei Shiqi , Xiang Ping
Published: October 2022

The straddle-type monorail tour transit system is a light overhead steel structure, and the lateral stiffness is generally low. However, the limit of the lateral natural vibration frequency is not clear in the current codes of China, and designers may ignore it. Weak lateral stiffness will lead to a violent vibration during vehicle operation and crowds walking, affecting human comfort and structural safety. Based on a practical project, we tested the acceleration of a monorail vehicle under full load conditions, and its running stability and ride comfort were assessed. Then, the impact of pedestrians on lateral vibration under some working conditions was measured and analyzed. Furthermore, the influence of different structural parameters on the lateral fundamental frequency was investigated. The results showed the following: (i) The vehicle’s running stability and riding comfort was good. However, human comfort was poor due to the weak lateral stiffness of the structure, which was affected by human-induced vibration. (ii) The comprehensive response of the structure increased with the increase in walking frequency, increased with the increase in the number of people working or weight, and the growth speed slowed down. (iii) The structural stiffness was most sensitive to the change in steel column diameter. (iv) The recommended value of the lateral fundamental frequency limit for different spans of the straddle-type monorail tour transit system was put forward. The recommended lower limit of fundamental frequency for a 15 m span is 5.0 Hz, for an 18 m span it is 3.5 Hz, and for a 25 m span it is 2.8 Hz.
Seismic Response of Immersed Tunnel Subject to Oblique Incidence of SV Wave
Authors: He Cong , Xu Guoyuan , Zhang Zhigang , Li Wei
Published: October 2022

In view of the near-field seismic action, considering that oblique incidence of seismic waves is more realistic than vertical incidence, the seismic response of the Hong Kong–Zhuhai–Macao immersed tunnel subjected to an obliquely incident SV wave is investigated. Using the finite element method and time-domain wave method, the seismic input is transformed into an equivalent node load with a viscous–spring artificial boundary, and a three-dimensional simulation technology for SV waves of oblique incidence is presented. A half-space numerical example is given to demonstrate the accuracy of the proposed simulation technology. Taking the stress field formed by the self-weight stress and hydrostatic pressure as the initial state of the dynamic response analysis, the static–dynamic coupling numerical simulation of the seismic response of a soil-immersed tunnel system is realized. The results show that the amplification in the vertical and longitudinal response of the tunnel, due to the oblique incidence, reaches maximum when the incident angle is close to the critical angle. Furthermore, the horizontal response and incident angle show the inverse relation and tend to be stable. In addition, the oblique incidence also causes asymmetric shearing in symmetric parts of the tunnel. The root of the shear key easily produces tensile cracks, while the end angle of the shear key is prone to stress concentration and local damage. Thus, the impact of oblique incidence should be considered in the seismic design, and attention should be paid to the optimization of the end angle of the shear key and the configuration of anti-crack reinforcement at the root of shear key to meet the seismic requirements.