bluuebunny/crossref_metadata_2025 huggingface dataset:
Joining Forces in Basic Science: ITS Meeting 2.0
Authors: Pilat Nina , Issa Fadi , Luo Xunrong , Chong Anita , Bromberg Jonathan , Kotsch Katja
Published: September 2022

The second International Transplant Science (ITS) meeting jointly organized by the European Society for Organ Transplantation (ESOT), the American Society of Transplantation (AST), and The Transplantation Society (TTS) took place in May 2022 in one of Europe’s most iconic cities: Berlin, Germany. The ITS meeting 2022 was designed to serve as an international platform for scientific discussions on the latest ground-breaking discoveries in the field, while providing an excellent opportunity to present cutting-edge research to the scientific community. We think this is fundamental for the exchange of new ideas and establishment of collaborative work between advanced transplant experts, young professionals and early-stage researchers and students. Scientific sessions tackled hot topics in transplantation such as mechanisms of tolerance, biomarkers, big data and artificial intelligence. Our educational pre-meeting focused on the breakthrough and challenges in single-cell multimodal omics. The program included panel discussions illuminating various topics concerning conflicts and problems related to gender, such as challenges for female scientists. Attendees returned to their institutes with not only profound knowledge of the latest discoveries, technologies, and concepts in basic and translational science, but also inspired and excited after discussions and networking sessions with fellow scientists which have been duly missed during the pandemic.
Reasoning about Confidence in Goal Satisfaction
Authors: Baslyman Malak , Amyot Daniel , Mylopoulos John
Published: September 2022

Goal models are commonly used requirements engineering artefacts that capture stakeholder requirements and their inter-relationships in a way that supports reasoning about their satisfaction, trade-off analysis, and decision making. However, when there is uncertainty in the data used as evidence to evaluate goal models, it is crucial to understand the confidence or trust level in such evaluations, as uncertainty may increase the risk of making premature or incorrect decisions. Different approaches have been proposed to tackle goal model uncertainty issues and risks. However, none of them considers simple quality measures of collected data as a starting point. In this paper, we propose a Data Quality Tagging and Propagation Mechanism to compute the confidence level of a goal’s satisfaction level based on the quality of input data sources. The paper uses the Goal-oriented Requirement Language (GRL), part of the User Requirements Notation (URN) standard, in examples, with an implementation of the proposed mechanism and a case study conducted in order to demonstrate and assess the approach. The availability of computed confidence levels as an additional piece of information enables decision makers to (i) modulate the satisfaction information returned by goal models and (ii) make better-informed decisions, including looking for higher-quality data when needed.
On an Optimal Quadrature Formula in a Hilbert Space of Periodic Functions
Authors: Shadimetov Kholmat , Hayotov Abdullo , Abdikayimov Botir
Published: September 2022

The present work is devoted to the construction of optimal quadrature formulas for the approximate calculation of the integrals ∫02πeiωxφ(x)dx in the Sobolev space H˜2m. Here, H˜2m is the Hilbert space of periodic and complex-valued functions whose m-th generalized derivatives are square-integrable. Here, firstly, in order to obtain an upper bound for the error of the quadrature formula, the norm of the error functional is calculated. For this, the extremal function of the considered quadrature formula is used. By minimizing the norm of the error functional with respect to the coefficients, an optimal quadrature formula is then obtained. Using the explicit form of the optimal coefficients, the norm of the error functional of the optimal quadrature formula is calculated. The convergence of the constructed optimal quadrature formula is investigated, and it is shown that the rate of convergence of the optimal quadrature formula is O(hm) for |ω|<N and O(|ω|−m) for |ω|≥N. Finally, we present numerical results of comparison for absolute errors of the optimal quadrature formula with the exp(iωx) weight in the case m=2 and the Midpoint formula. There, one can see the advantage of the optimal quadrature formulas.
Application of the SSA for Optimal Reactive Power Compensation in Radial and Meshed Distribution Using D-STATCOMs
Authors: Mora-Burbano Javier Andrés , Fonseca-Díaz Cristian David , Montoya Oscar Danilo
Published: September 2022

This paper deals with the problem regarding the optimal placement and sizing of distribution static compensators (D-STATCOMs) in radial and meshed distribution networks. These grids consider industrial, residential, and commercial loads within a daily operation scenario. The optimal reactive power flow compensation problem is formulated through a mixed-integer nonlinear programming (MINLP) model. The objective function is associated with the minimization of the expected energy losses costs for a year of operation by considering the investment costs of D-STATCOMs. To solve the MINLP model, the application of a master–slave optimization approach is proposed, which combines the salp swarm algorithm (SSA) in the master stage and the matricial backward/forward power flow method in the slave stage. The master stage is entrusted with defining the optimal nodal location and sizes of the D-STATCOMs, while the slave stage deals with the power flow solution to determine the expected annual energy losses costs for each combination of nodes and sizes for the D-STATCOMs as provided by the SSA. To validate the effectiveness of the proposed master–slave optimizer, the IEEE 33-bus grid was selected as a test feeder. Numerical comparisons were made against the exact solution of the MINLP model with different solvers in the general algebraic modeling system (GAMS) software. All the simulations of the master–slave approach were implemented in the MATLAB programming environment (version 2021b). Numerical results showed that the SSA can provide multiple possible solutions for the studied problem, with small variations in the final objective function, which makes the proposed approach an efficient tool for decision-making in distribution companies.
An Optimized Data Analysis on a Real-Time Application of PEM Fuel Cell Design by Using Machine Learning Algorithms
Authors: Saco Arun , Sundari P. Shanmuga , J Karthikeyan , Paul Anand
Published: September 2022

In recent years, machine learning algorithms have been applied in many real-time applications. Crises in the energy sector are the primary challenges experienced today among all countries across the globe, regardless of their economic status. There is a huge demand to acquire and produce environmentally friendly renewable energy and to distribute and utilize it efficiently because of its huge production cost. PEMFC are known for their energy efficiency and comparatively low cost, and can be an alternative energy source. The efficiency of these PEMFC can still be enhanced with the help of advanced technologies like machine learning and artificial intelligence, as they provide an optimal solution to explore the hidden knowledge from the generated data. The proposed model attempts to compare several design techniques with varied humidity levels. To enhance the performance of PEMFC, the various humidification processes were considered during the experimental study. The humidification reduces the heat during energy generation and increases the performance of PEM fuel cell. The humidity levels such as 100%, 50%, and 10% were considered to be tested with the machine learning models. The SVMR, LR, and KNN algorithms were tested and observed with the RMSE value as the evaluation parameters. The observed results show that SVMR has an RMSE rate of 0.0046, the LR method has an RMSE rate of 0.0034, and KNN has an RMSE rate of 0.004. The analysis shows that the LR model provides better accuracy than other models. The LR model enhances the PEMFC performance.
Intelligent Driving Vehicle Object Detection Based on Improved AVOD Algorithm for the Fusion of LiDAR and Visual Information
Authors: Bai Ziwen , Bi Dawei , Wu Junjie , Wang Minxue , Zheng Quan , Chen Liqing
Published: September 2022

The detection of obstacles of intelligent driving vehicles becomes a primary condition to ensure safe driving. LiDAR and camera are the main sensors for intelligent vehicles to obtain information about their surroundings, and they each have their own benefits in terms of object detection. LiDAR can obtain the position and geometric structure of the object, and camera is very suitable for object recognition, but the reliance on environmental perception by a single-type sensor can no longer meet the detection requirements in complex traffic scenes. Therefore, this paper proposes an improved AVOD fusion algorithm for LiDAR and machine vision sensors. The traditional NMS (non-maximum suppression) algorithm is optimized using a Gaussian weighting method, while the 3D-IoU pose estimation loss function is introduced into the target frame screening module to upgrade the 2D loss function to 3D and design the 3D-IoU criterion. By comparing the detection accuracy of the algorithm proposed in this paper with that of the traditional method, it has been found that the improved AVOD fusion algorithm significantly improved the detection efficiency and the detection accuracy reached 96.3%. The algorithm proposed in this paper can provide a new approach for object detection of intelligent driving vehicles.
ECNN: Intelligent Fault Diagnosis Method Using Efficient Convolutional Neural Network
Authors: Zhang Chao , Huang Qixuan , Zhang Chaoyi , Yang Ke , Cheng Liye , Li Zhan
Published: September 2022

With outstanding deep feature learning and nonlinear classification abilities, Convolutional Neural Networks (CNN) have been gradually applied to deal with various fault diagnosis tasks. Affected by variable working conditions and strong noises, the empirical datum always has different probability distributions, and then different data segments may have inconsistent contributions, so more attention should be assigned to the informative data segments. However, most of the CNN-based fault diagnosis methods still retain black-box characteristics, especially the lack of attention mechanisms and ignoring the special contributions of informative data segments. To address these problems, we propose a new intelligent fault diagnosis method comprised of an improved CNN model named Efficient Convolutional Neural Network (ECNN). The extensive view can cover the special characteristic periods, and the small view can locate the essential feature using Pyramidal Dilated Convolution (PDC). Consequently, the receptive field of the model can be greatly enlarged to capture the location information and excavate the remarkable informative data segments. Then, a novel residual network feature calibration and fusion (ResNet-FCF) block was designed, which uses local channel interactions and residual networks based on global channel interactions for weight-redistribution. Therefore, the corresponding channel weight is increased, which puts more attention on the information data segment. The ECNN model has achieved encouraging results in information extraction and feature channel allocation of the feature. Three experiments are used to test different diagnosis methods. The ECNN model achieves the highest average accuracy of fault diagnosis. The comparison results show that ECNN has strong domain adaptation ability, high stability, and superior diagnostic performance.
An Effort to Use a Solid Propellant Engine Arrangement in the Moon Soft Landing Problem
Authors: Obreque Elías , Díaz Marcos
Published: September 2022

This paper presents a control design strategy for the soft-landing problem on the Moon using solid propellant engines (SPEs). While SPEs have controllability issues and issues relating to the fact that they cannot be restarted, they are characterized by their reliability, simplicity, and cost-effectiveness. Consequently, our main contribution is to tackle this disadvantage by formulating a 1-dimensional landing optimization problem using an array of SPEs in a CubeSat platform, which is analyzed for different numbers of engines in the array and for three types of propellant grain cross-section (PGCS). The engines and control parameters are optimized by a genetic algorithm (GA) due to the non-linearity of the problem and the uncertainties of the state variables. Two design approaches for control are analyzed, where the robust design based on the uncertainties of the variables shows the best performance. The results of Monte Carlo simulations were used to demonstrate the effectiveness of the robust design, which decreases the impact velocity as the number of SPEs increases. Using an arrangement of ten SPEs, the landing was at −2.97 m/s with a standard deviation of 0.99 m/s; using sixteen SPEs, the landing was at −2.04 m/s with a standard deviation of 0.48 m/s. Both have regressive PGCS.
Influence of Flow Rate Distribution on Combustion Instability of Hypergolic Propellant
Authors: Gao Yushan , Zhang Bingbing , Cheng Jinbo , Li Jingxuan , Fu Qingfei
Published: September 2022

Combustion instability is the biggest threat to the reliability of liquid rocket engines, whose prediction and suppression are of great significance for engineering applications. To predict the stability of a combustion chamber with a hypergolic propellant, this work used the method of decoupling unsteady combustion and acoustic system. The turbulence is described by the Reynolds-averaged Navier–Stokes technique, and the interaction of turbulence and chemistry interaction is described by the eddy-dissipation model. By extracting the flame transfer function of the combustion field, the eigenvalues of each acoustic mode were obtained by solving the Helmholtz equation, thereby predicting the combustion stability for the combustion chamber. By predictions of the combustion chamber instability with different flow rate distributions, it was found that the increasing of inlet flow rate amplitude will improve the stability or instability of combustion. The combustion stability of the chamber was optimized when the flow rate distribution for the oxidant was set more uniform in the radial direction. The heterogeneity of the flow rate distribution in the circumferential direction is not recommended, considering that a homogeneous flow rate distribution in the circumferential direction is beneficial to the combustion stability of the chamber.
Analysis of Air-Gap Magnetic Field and Structure Optimization Design of Hollow-Cup Motor
Authors: Sun Jinji , Ren Jianyi , Le Yun , Wang Hanmou
Published: September 2022

Hollow-cup motors are usually used in spacecraft because of their low power consumption and high control accuracy. However, because the air-gap between the permanent magnets (PMs) and the rotor of the hollow-cup motor is uniform, the sinusoidal characteristic of the air-gap magnetic field waveform is inferior and the total harmonic distortion (THD) is large, resulting in torque ripple. For the large air-gap hollow-cup motor, the existing methods for optimizing the sinusoidal characteristics of the air gap magnetic field change the shape of PMs, but the changed PMs are difficult to manufacture and magnetize, resulting in the methods being limited and not being able to achieve the ideal optimization effect for the hollow-cup motor. Based on the characteristics of the inner rotor and outer rotor rotating synchronously during operation, a new structure design of the hollow-cup motor with an eccentric inner rotor is proposed instead of changing the PMs’ shape. Firstly, the mathematical model of the hollow-cup motor is established. Then, the FEM shows that the inner rotor’s eccentricity can bring the air-gap magnetic field waveform closer to the ideal sinusoidal waveform and can effectively reduce the THD. Finally, a prototype with the optimal eccentricity value is made for experimental verification.
Overexpression of CsGSH2 Alleviates Propamocarb Residues and Phytotoxicity in Cucumber by Enhancing Antioxidant and Glutathione Detoxification Properties
Authors: Li Shengnan , Wu Zedong , Liu Chunhong , Fan Lianxue , He Yongheng , Lu Ke , Liu Dajun , Feng Guojun
Published: September 2022

Propamocarb is a pesticide widely used to control cucumber downy mildew. The overuse of propamocarb has resulted in residues and phytotoxicity. However, the detoxification and metabolic process of propamocarb have not been documented well. Our previous work showed differences in the propamocarb residues among the different genotypes of cucumber and their regulation by multiple genes. Based on the already reported data on gene expression profiles under propamocarb treatment, we identified the glutathione pathway, including six different genes (Csa4M303130, Csa3M133380, Csa5M409710, Csa7M395820, Csa3M597320, and Csa1M571280), involved in propamocarb detoxification. The qPCR analysis showed that Csa1M571280 (CsGSH2) was most significantly and differentially expressed at 48 h after propamocarb spray in the cucumber varieties Y3F604 (low propamocarb residues) and M729 (high propamocarb residues). In Y3F604, CsGSH2 expression increased from 6 to 48 h after spraying propamocarb, and the expression was positively correlated with propamocarb residues, whereas M729 showed no significant difference in CsGSH2 expression. Therefore, we presumed CsGSH2 as a key gene in managing propamocarb residues. Gene functional analysis showed that propamocarb residues decreased in CsGSH2-overexpressing plants and increased in CsGSH2-antisense plants. Overexpression of CsGSH2 enhanced glutathione (GSH) accumulation and glutathione S-transferase (GST), glutathione reductase (GR), and glutathione peroxidase (GPX) activities, probably for propamocarb detoxification. The activity of antioxidant enzymes (SOD, POD, CAT, and APX) increased to maintain a high antioxidant capacity in CsGSH2-overexpressing plants. The superoxide (O2−), hydrogen peroxide (H2O2), and malondialdehyde (MDA) levels decreased in CsGSH2-overexpressing plants, promoting the antioxidant system composed of ascorbic acid and glutathione (AsA-GSH). Thus, we conclude that CsGSH2 alleviates propamocarb residues and phytotoxicity by enhancing cucumber’s antioxidant and glutathione detoxification potential.
Compact Convolutional Transformer (CCT)-Based Approach for Whitefly Attack Detection in Cotton Crops
Authors: Jajja Aqeel Iftikhar , Abbas Assad , Khattak Hasan Ali , Niedbała Gniewko , Khalid Abbas , Rauf Hafiz Tayyab , Kujawa Sebastian
Published: September 2022

Cotton is one of the world’s most economically significant agricultural products; however, it is susceptible to numerous pest and virus attacks during the growing season. Pests (whitefly) can significantly affect a cotton crop, but timely disease detection can help pest control. Deep learning models are best suited for plant disease classification. However, data scarcity remains a critical bottleneck for rapidly growing computer vision applications. Several deep learning models have demonstrated remarkable results in disease classification. However, these models have been trained on small datasets that are not reliable due to model generalization issues. In this study, we first developed a dataset on whitefly attacked leaves containing 5135 images that are divided into two main classes, namely, (i) healthy and (ii) unhealthy. Subsequently, we proposed a Compact Convolutional Transformer (CCT)-based approach to classify the image dataset. Experimental results demonstrate the proposed CCT-based approach’s effectiveness compared to the state-of-the-art approaches. Our proposed model achieved an accuracy of 97.2%, whereas Mobile Net, ResNet152v2, and VGG-16 achieved accuracies of 95%, 92%, and 90%, respectively.
Application of Desert DSEs to Nonhost Plants: Potential to Promote Growth and Alleviate Drought Stress of Wheat Seedlings
Authors: Li Xia , Liu Yanxia , Ye Qiannan , Xu Minghui , He Xueli
Published: September 2022

To evaluate the applicability of desert dark septate endophytes (DSEs) in crop cultivation, Alternaria alternata (Fr.) Keissl. (Aa), Paraphoma pye Moslemi & P.W.J. Taylor (Pp), and Paraphoma radicina (McAlpine) Morgan-Jones & J.F. White (Pr) were inoculated into nonhost wheat growing under three water conditions. The plants’ biomass, vegetative growth, and physiological parameters were investigated. At harvest, all DSE strains were effective colonizers under all treatments. These DSEs generally positively affected wheat growth but varied among different DSE species, and this promoting effect was more obvious under drought conditions. Under mild drought (MD) treatments, Aa and Pr increased the leaf number and plant height of hosts. Pr showed a significant beneficial influence on the wheat’s total biomass under all treatments, while Aa and Pp showed benefits only under the well-watered or MD treatment. The response mechanisms of DSE-inoculated wheat under stress may be due to the enhanced photosynthetic efficiency and antioxidant system. Generally, Pr had a stronger beneficial effect. The improved growth and fitness of the inoculated hosts under drought stress may reduce their water supply requirements during seedling growth. We speculate that inoculating wheat with this strain could be a promising approach for water-saving cultivation in arid environments.
Development Status and Research Progress of a Tractor Electro-Hydraulic Hitch System
Authors: Sun Xiaoxu , Lu Zhixiong , Song Yue , Cheng Zhun , Jiang Chunxia , Qian Jin , Lu Yang
Published: September 2022

A tractor electro-hydraulic hitch system is considered one of the most important systems that play a strategic role in the power transmission and operation depth control of a tractor’s field operation. Its performance directly affects the operation quality of the whole work unit of the tractor. Furthermore, a tractor electro-hydraulic hitch system has gained the interest of many in the agricultural machinery sector because of its stable performance, high production efficiency, good operation quality and its low energy consumption. To fully benefit from the potential of the tractor electro-hydraulic hitch system, it is significant to understand and address the problems and challenges associated with it. This study, therefore, aims to contribute to the development of the tractor electro-hydraulic hitch system by investigating the research methods, technical characteristics and emerging trends in three key aspects that include the tillage depth adjustment method, the tillage depth control algorithm and the core components of the electro-hydraulic hitch system. The characteristics and applicable conditions of the different tillage depth adjustment methods of the electro-hydraulic hitch system were summarized. The realization methods and the control characteristics of the different algorithms were elaborated and discussed for both the PID control algorithm and the intelligent control algorithm. The working characteristics of the core components of the electro-hydraulic hitch system were analyzed based on the hydraulic control valves and sensing elements. The results have shown that the multi-parameter tillage depth adjustment method met the operation quality standard while taking the engine load stability and traction efficiency into account, and it has a greater research significance and value. The working quality can be improved effectively by introducing the intelligent algorithm. In addition, the study of smart valves with built-in sensing elements and how to improve the anti-interference ability of sensing elements, are the aspects that requires further consideration. Aiming to improve the working quality and reduce energy consumption, further research into the tractor electro-hydraulic hitch system is necessary. The results of this comprehensive review provide a reference for the intelligent operation of tractors under the precision agriculture.
Salinity Effect on Plant Growth Parameters and Fruit Bioactive Compounds of Two Strawberry Cultivars, Coupled with Environmental Conditions Monitoring
Authors: Denaxa Nikoleta-Kleio , Nomikou Aggeliki , Malamos Nikolaos , Liveri Eleni , Roussos Petros Anargyrou , Papasotiropoulos Vasileios
Published: September 2022

Salinity stress is one of the most vital abiotic stresses, impairing the productivity of crops in both irrigated and dry areas. A pot experiment was carried out in a greenhouse environment, aiming to examine the relevant tolerances and evaluate the effect of salinity stress on plant growth, fruit physiological, and quality traits of two strawberry cultivars, Camarosa and Rociera. The plants were irrigated with water with electrical conductivity (EC) of 0.4 dS m−1 (control), or with a salt solution with either ECs 2 dS m−1 (moderate salt stress) or 4 dS m−1 (elevated salt stress). Furthermore, several meteorological parameters, as well as soil moisture, were monitored inside the greenhouse. The results showed that salinity induced osmotic stress, water deprivation, and toxic effects, affecting the growth parameters and yield of both cultivars. The elevated salt stress imposed a negative impact on Rociera’s fruits carbohydrates, organic acids, and anthocyanins, while the antioxidant capacity increased. However, Rociera exhibited high total yield/plant and total yield even under elevated salt stress compared to Camarosa. Camarosa plants grown under high salt levels presented low salinity tolerance index, plant water content, and growth parameters. The fruits exhibited low fresh weight but high sweetness index and antioxidant power. An accumulation of soluble sugars under saline conditions, especially sucrose, was also detected in cv. Camarosa fruits when compared to Rociera. Therefore, the two cvs. exhibited a different pattern of response to salinity stress concerning their physiological, biochemical and nutritional characteristics; however, either could be an interesting alternative for cultivation in areas where a slight salinization of the water or soil imposes a limitation on the rather salt-sensitive crops. Agronomic and biochemical evaluation of salinity stress coupled with monitoring of greenhouse microclimatic conditions will lead to a better understanding of the effects on plant growth and quality characteristics, enhancing the productivity of strawberry cultivars, especially under salt-affected environments.
Simulation Analysis and Test of Pneumatic Distribution Fertilizer Discharge System
Authors: Cheng Biao , He Ruiyin , Xu Yong , Zhang Xuzheng
Published: September 2022

Precision fertilizer application technology is necessary to improve the utilization efficiency of fertilizers in agricultural production. Traditional mechanical fertilization systems risk blockages and uneven application when working in multiple crop rows. Pneumatic fertilization systems have improved efficiency and fertilization quality, however, fewer studies have characterized their designs in regards to the motion of the fertilizer particles. Here, we design and evaluate the parameters of the key components of a pneumatic fertilizer discharge system. Numerical simulations were conducted using a coupled EDEM-FLUENT and gas-phase models together with bench tests to examine the effects of inlet wind speed on the efficiency and consistency of the pneumatic fertilization system. The EDEM-FLUENT simulations showed that the number of fertilizer particles in the grid box set by EDEM was 60 particles in the range from t = 0.275 s to t = 0.5 s, and there was no blockage or cut-off in the pipe. The gas-phase simulation showed that there were tiny vortices in the fertilizer conveying pipe, and the maximum flow rate of its backflow was lower than 3.59 m/s, which had little effect on the fertilizer conveyance. The bench test showed that the inlet wind speed was 35–40 m/s, and the fertilization efficiency was 0.29–0.41 kg/s when the maximum variation coefficient of the row discharge consistency of the pneumatic distribution fertilizer discharge system was 5.55%. The coefficient of variation of the average row discharge consistency was 3.93%, and the average fertilizer discharge met the design requirements. Therefore, the pneumatic distribution system achieves stable operation and meets the requirements of fertilization operations.
The Optimization of the Physical–Thermal and Bioactive Properties of Pumpkin Slices Dried in a Hybrid Microwave–Convective Dryer Using the Response Surface Method
Authors: Joudi-Sarighayeh Fatemeh , Abbaspour-Gilandeh Yousef , Kaveh Mohammad , Hernández-Hernández José Luis
Published: September 2022

This study investigates the applicability of a microwave–convective dryer (MCD) to the processing of pumpkin slices considering the influence of process variables such as air temperature and microwave power on some thermal (drying time and specific energy consumption (SEC)), quality (rehydration ratio (RR), shrinkage (S), color, and vitamin C content), and bioactive (total phenol (TPC) and antioxidant contents (AC)) features. The impacts of temperature and microwave power were explored on the thermal, quality, and bioactive properties using the the response surface method (RSM). In each experiment, 100 g of the pumpkin samples was dried at an airflow of 1 m/s and various air temperatures (50, 60, and 70 °C) and microwave powers (180, 360, and 540 W). The results indicated that the temperature and microwave power can significantly affect the drying time and SEC (p ≤ 0.01) such that increasing the temperature and microwave power decreased the drying time and SEC. The highest RR, AC, TPC, and vitamin C, as well as the lowest color variation and shrinkage, were observed at microwave power of 360 W and temperature of 60 °C. The optimal drying of the pumpkin samples involved the temperature of 63.66 °C and microwave power of 426.94 W. The predicted response for the mentioned condition included the drying time of 47.38 min, SEC of 30.87 MJ/kg, S of 25.44%, color of 12.74, RR of 5.21, TPC of 658.24 MgGA/100 gdw, AC of 82.11%, and VC of 4.78 mg/g DM.
The Effect of Rotational Cropping of Industrial Hemp (Cannabis sativa L.) on Rhizosphere Soil Microbial Communities
Authors: Tang Lili , Fan Chao , Yuan Hongmei , Wu Guangwen , Sun Jing , Zhang Shuquan
Published: September 2022

Crop rotation affects soil properties and soil microbial diversity and structure. Currently, it is not well understood how soil microbial diversity changes following different crop rotation systems of industrial hemp, an ancient and economically important crop. Therefore, these changes were analyzed in this study. Our results showed that different rotation systems significantly affected the wilt disease incidence, plant height, yield, soil physicochemical properties and soil microbial communities in the greenhouse. The rotation systems used in this study significantly reduced the plant mortality and increased the yield compared with a monoculture system. The levels of alkaline hydrolysis and available phosphorus in the soil decreased significantly compared with a monoculture cropping system. Using MiSeq high-throughput sequencing, we showed that the soil diversity and number of bacteria and fungi were significantly higher for rotation systems and controls compared to the monoculture system. The relative abundance of pathogens increased with a monoculture system. Redundancy analysis suggests that soil properties may also affect the soil microbial composition. Taken together, different rotation systems used in this study significantly decreased the disease incidence, increased plant yields and increased soil microbial diversity compared with monoculture for industrial hemp. We believe that applying these rotation systems is an efficient and eco-friendly approach to control soil borne pathogenic diseases and increase floral yields.
Fe(II)-OM Complexes Formed by Straw Returning Combined with Optimized Nitrogen Fertilizer Could Be Beneficial to Nitrogen Storage in Saline-Alkaline Paddy Soils
Authors: Jiang Yinghui , Zhang Shirong , Gao Bing , Wei Ruxue , Ding Xiaodong
Published: September 2022

Soil organic carbon (SOC) plays a crucial role in controlling the nitrate-dependent Fe(II) oxidation (NDFO) process, especially for saline-alkaline soils. The effects of straw returning combined with Nitrogen (N) fertilizer application on soil NO3−-N content, Fe(II) form and nirK genes in saline-alkaline soil were studied in a five-year field experiment to explore the regulatory mechanism of SOC on NDFO process. Six treatments were designed with two factors (1) three straw returning rates (C0, C1 and C2, which was 0, 4500 and 9000 kg C ha−1, respectively) and (2) two N fertilization rates (N1 and N2, which was 255 and 400 kg N ha−1, respectively). Under both N levels, compared with C0 and C2 rates, NO3−-N content was increased by 65% and 50% in C1 rate, respectively. NirK genes were decreased with straw returning, in which they were 42.9–58.8% lower in C1 and C2 treatments than that in C0 treatment, respectively. In the N1C1 treatment, the increase of SOC reduced the denitrification by converting aqueous Fe(II) (Fe(II)aq) into Fe(II)-OM complexes and reducing the abundance of nirK genes. Overall, appropriate straw returning (C1) under optimal N fertilization rate (N1) could reduce N loss by decreasing the NDFO process in saline-alkaline paddy soils.
Effects of Ascorbic Acid and/or α-Tocopherol on Agronomic and Physio-Biochemical Traits of Oat (Avena sativa L.) under Drought Condition
Authors: El-Beltagi Hossam S. , Sulaiman  , Mohamed Maged Elsayed Mohamed , Ullah Sami , Shah Sikandar
Published: September 2022

Water stress is notably a critical environmental condition restricting plant growth and economic outputs in semi-arid and arid environments. In a pot experiment, we explored the potential function of α-tocopherol (α-toc) and/or ascorbic acid (AsA) on the agronomic and physio-biochemical features of oat grown in water-scarce conditions. Drought duration significantly reduced the soil electrical conductivity and pH but increased the soil temperature, influencing the nutrient availability and uptake. For example, post-drought (25 days) soil analysis indicated that electrical conductivity decreased from 597 to 306 mS/m, total dissolved solids from 298 to 153 mg/L, and pH from 7.5 to 6.3 in 25 days of drought. Further, the drought-stressed leaves also contained significantly lower metabolites, such as proline, protein, sugar, and glycine betaine, than the control leaves, indicating impaired plant defense mechanisms. Significantly increased enzymatic antioxidants in leaves (e.g., superoxide dismutase, ascorbate peroxidase, and peroxidase) suggested the inability of oat plants to overcome drought-induced oxidative damage. In contrast, AsA and/or α-toc significantly amplified the seed germination rates and plant growth. Taken together, our results demonstrate that AsA and α-toc have the capability to mitigate adverse effects of drought conditions on oat plants by improving leaf relative water contents, photosynthetic pigments, and the antioxidant defense system.
A Physiologically Based ODE Model for an Old Pest: Modeling Life Cycle and Population Dynamics of Bactrocera oleae (Rossi)
Authors: Rossini Luca , Bruzzone Octavio Augusto , Contarini Mario , Bufacchi Livio , Speranza Stefano
Published: September 2022

The olive fruit fly Bactrocera oleae is one of the key insect pests infesting olive orchards in Mediterranean areas. Its coevolution with the olive tree, Olea europaea, made this pest highly specialized for this crop, being responsible for several yield reductions in terms of olive fruits and olive oil organoleptic properties. Monitoring is, to date, the main tool to assess the entity of infestations, but the increasing availability of biological information is making possible a quantitative interpretation of B. oleae’s biological traits in mathematical language. In this study, we aim to synthesize this plethora of information by applying a general physiologically based model theory of recent introduction. As a result, we obtained a parameterized model capable of describing B. oleae populations and with a high potential for implementation in Decision Support System programs. Besides the parameterization, model validation has been carried out in a three-year survey conducted in two representative productive areas of Sabina (Lazio, Central Italy). The model showed overall reliability in describing the field data trend, and it is a good starting point to be further improved.
Novel Nematocidal Compounds from Shrimp Shell Wastes Valorized by Bacillus velezensis RB.EK7 against Black Pepper Nematodes
Authors: Trinh Thi Huyen Trang , Wang San-Lang , Nguyen Van Bon , Phan Tu Quy , Doan Manh Dung , Tran Thi Phuong Hanh , Nguyen Thi Huyen , Le Thi Anh Hong , Ton That Quang , Nguyen Anh Dzung
Published: September 2022

Among various organic wastes, shrimp shell powder (SSP) was the most suitable carbon/nitrogen source for producing antinematode compounds (ANCs) via Bacillus veleznesis RB.EK7 fermentation. The fermentation process for the enhancement of antinematode activity was investigated. B. veleznesis RB.EK7 produced the highest antinematode activity in the medium containing 0.8% SSP with an initial pH of 6.5–7.0, and fermentation was performed at 35–37 °C with a saking speed of 150 rpm for 72 h. Targeting ANCs were purified from the fermented culture broth and identified as thymine (1) and hexahydropyrrolo [1,2-a]pyrazine-1,4-dione (2) based on nuclear magnetic resonance (NMR) and mass spectra analysis and were compared to those of the reported compounds. Notably, for the first time, these compounds were found as novel ANCs. Thymine (1) demonstrated a potential nematicidal effect with near 100% mortality of second-stage juvenile (J2) nematodes and anti-egg hatching effects of 70.1%, while hexahydropyrrolo [1,2-a]pyrazine-1,4-dione showed moderate antinematode activities with 64.2% mortality of J2 nematodes and anti-egg hatching effects of 57.9%. The docking study coupled with experimental enzyme inhibition results indicated that the potent nematicidal effect of these compounds may be possibly due to the inhibition of the targeting enzyme acetylcholinesterase. The data of this study suggest that SSP can be potentially reused for the eco-friendly production of ANCs for the management of black pepper nematodes.
The Use of Camera Traps and Auxiliary Satellite Telemetry to Estimate Jaguar Population Density in Northwestern Costa Rica
Authors: Montalvo Víctor H. , Sáenz-Bolaños Carolina , Cruz-Díaz Juan C. , Carrillo Eduardo , Fuller Todd K.
Published: September 2022

Regular evaluation of jaguar (Panthera onca) population status is an important part of conservation decision-making. Currently, camera trapping has become the standard method used to estimate jaguar abundance and demographic parameters, though evidence has shown the potential for sex ratio biases and density overestimates. In this study, we used camera trap data combined with satellite telemetry data from one female jaguar to estimate jaguar population density in the dry forest of Santa Rosa National Park in the Guanacaste Conservation Area of northwestern Costa Rica. We analyzed camera trap data collected from June 2016 to June 2017 using spatial capture-recapture methods to estimate jaguar density. In total, 19 individual jaguars were detected (11 males; 8 females) with a resulting estimated population density of 2.6 females (95% [CI] 1.7–4.0) and 5.0 male (95% [CI] 3.4–7.4) per 100 km2. Based on telemetry and camera trap data, camera placement might bias individual detections by sex and thus overall density estimates. We recommend population assessments be made at several consecutive 3-month intervals, that larger areas be covered so as not to restrict surveys to one or two individual home ranges, as in our case, and to carry out long-term camera monitoring programs instead of short-term studies to better understand the local population, using auxiliary telemetry data to adjust field designs and density estimations to improve support for jaguar conservation strategies.
The European Pine Marten Martes martes (Linnaeus, 1758) Is Autochthonous in Sicily and Constitutes a Well-Characterised Major Phylogroup within the Species (Carnivora, Mustelidae)
Authors: Vecchioni Luca , Marrone Federico , Costa Simone , Muscarella Calogero , Carra Elena , Arizza Vincenzo , Arculeo Marco , Faraone Francesco Paolo
Published: September 2022

No molecular data are currently available for the Sicilian populations of the European pine marten Martes martes, thus preventing any sound inference about its native or non-native status on the island, as well as the local phylogeography of the species. In order to investigate these issues, we sequenced two mtDNA markers in road-killed specimens collected in Sicily. Both markers consistently demonstrated the existence of a well-characterised Sicilian clade of the species, which is endemic to the island and constitutes the sister group of a clade including the Mediterranean and Central–North European major phylogroups of the European pine marten. Such evidence supports the autochthony of Martes martes in Sicily and points to a natural Pleistocene colonisation of the island followed by isolation. The occurrence of a, to date undetected, major phylogroup of the species in Sicily calls for the dedicated monitoring of the Sicilian populations of the species in order to preserve this evolutionarily significant unit.
Cryopreservation of Roughscale Sole (Clidoderma asperrimum) Sperm: Effects of Cryoprotectant, Diluent, Dilution Ratio, and Thawing Temperature
Authors: Zidni Irfan , Lee Hyo-Bin , Yoon Ji-Hye , Park Jung-Yeol , Jang Hyun-Seok , Cho Youn-Su , Seo Young-Seok , Lim Han-Kyu
Published: September 2022

The roughscale sole, Clidoderma asperrimum is categorized as an endangered species. Sperm freezing is essential for preserving gametes. This study examined the CPA concentration, diluent, dilution ratio, and thawing temperature to design a sperm cryopreservation protocol for roughscale sole. The variables examined included sperm motility and kinematics, cell survival, fertilization, and DNA fragmentation. Sperm motility parameters were assessed via computer-assisted sperm analysis using a CEROS II instrument. Cell survival rate and DNA damage were assessed using the Cell Counting Kit-8 and single-cell gel electrophoresis assay, respectively. Sperm preservation was tested using several CPAs, including ethylene glycol, dimethyl sulfoxide (DMSO), glycerol, propylene glycol, and methanol. The diluents tested were 300 mM sucrose, 300 mM glucose, Stein’s solution, Ringer’s solution, and Hank’s solution. The optimal conditions for sperm cryopreservation were 10% DMSO + Stein’s solution. After thawing, sperm motility was highest with a 1:1 dilution ratio (sperm to CPA + diluent), at 69.20 ± 0.32%; thawing at 10 °C was optimal for post-thaw motility (72.03 ± 0.95%). The highest fertilization rate (40.00 ± 1.22%) was obtained using DMSO. The fresh sperm had the lowest tail DNA, followed by 10% DMSO + Stein’s solution. The developed cryopreservation methods can be used in roughscale sole hatcheries.
Feeding Corn Oil in a Nanoemulsified Form Alters the Unsaturated Fatty Acids in the Milk of Zaraibi Dairy Goats
Authors: Yousef Mahmoud Atef , Farouk Mohammed Hamdy , Azzaz Hossam H. , Khattab Mostafa S. A. , Abd El Tawab Ahmed M. , El-Sherbiny Mohamed
Published: September 2022

Oil in water nanoemulsion represents a new and unstudied form of oil supplementation to the ruminant diet; that is why the aim was to evaluate the potential of nanoemulsified corn oil in dairy goats’ diets on milk productivity and fatty acid proportion. Twenty-four lactating Zaraibi goats in early lactation were randomly allocated to the following treatments: control—a basal diet without any supplementation, CO—the control diet + corn oil supplied at 3% on a dry matter basis (DM), NCO—the control diet + nanoemulsified corn oil provided at 3% on a DM basis. A completely randomized design that lasted 30 days (25 days of adaptation + 5 days of sampling) was used with eight goats in each treatment. The control diet consisted of 50% concentrate and 50% Egyptian berseem clover. The NCO increased the milk production, fat percentage, and yield compared to the CO and the control. The proportions of oleic, linoleic, and linolenic acids were higher in the NCO compared to the control and CO. The NCO had less effect on the biohydrogenation intermediates’ profile than the CO; noticeably, higher proportions of unsaturated fatty acid (UFA) were associated with the NCO. In conclusion, the NCO increased milk production and decreased the transformation rate of UFA to saturated fatty acids in the biohydrogenation environment.
Thoracic and Abdominal Mesothelioma in an Older Horse in Lazio Region
Authors: Passantino Giuseppe , Sassi Emilio , Filippi Ilaria , Serata Valerio , Tinelli Antonella , Zizzo Nicola
Published: September 2022

A Quarter Horse, a gelding aged 22, was subjected to a clinical examination for colic syndrome. During admission to the clinic, blood counts and ultrasound examination were performed. Ultrasound revealed abdominal masses and abundant accumulation of pleural (50 L) and abdominal fluid (100 L). Cytology was performed on the aspirated fluid. The patient was euthanized. The autopsy examination revealed abundant effusion and nodular masses on the peritoneum, omentum, lungs, heart, and mediastinum. A diagnosis of epithelioid mesothelioma was made via histopathology and confirmed with immunohistochemistry; it showed positive antibodies against cytokeratin (CK) and vimentin. Mesothelioma is a rare cancer in older horses. It is important to employ the correct differential diagnostics using the available methods, providing valid ante-mortem support to the clinical veterinarian and monitoring the territory using this species as a valid biological indicator.
Exploring Epigallocatechin-3-Gallate Autoxidation Products: Specific Incubation Times Required for Emergence of Anti-Amyloid Properties
Authors: Ziaunys Mantas , Smirnovas Vytautas
Published: September 2022

Amyloidogenic protein/peptide aggregation into fibrillar aggregates is associated with multiple amyloidoses, including widespread neurodegenerative disorders. Despite years of research and a well-understood mechanism, there are still very few treatments available for the increasing number of amyloid-related disorders. In recent years, the search for potential anti-aggregation compounds has shifted toward naturally occurring molecules, with one of the most promising being epigallocatechin-3-gallate (EGCG). This polyphenolic compound was shown to inhibit the aggregation of several amyloidogenic proteins/peptides, including amyloid-beta (related to Alzheimer’s disease) and alpha-synuclein (related to Parkinson’s disease). However, multiple reports have indicated its limited stability under physiological conditions and the possibility of EGCG autoxidation products being the actual inhibitory compounds. In this work, we explore how different EGCG autoxidation products associate with non-aggregated insulin, as well as how they affect its aggregation and resulting fibril structure. We also show that there is a specific incubation time required for the emergence of compounds, which alters the amyloid aggregation process.