bluuebunny/crossref_metadata_2025 huggingface dataset:
Multivariate Analysis of Grain Yield and Main Agronomic Traits in Different Maize Hybrids Grown in Mountainous Areas
Authors: Long Yun , Zeng Youlian , Liu Xiaohong , Yang Yun
Published: September 2024

Inconsistent reports exist on the relationships between key agronomic traits and maize yield. We performed a multivariate analysis of yield and 10 agronomic traits in 59 hybrids to explore maize yields in mountainous areas. The yield per plant (YP) was significantly and positively correlated with kernel weight (KW), growth period (GP), and kernel row number (KRN). KW and KRN had positive effects on YP, whereas kernel rows per ear (KRE) had a negative effect. GP indirectly affected YP. GP, KW, KRN, and ear length (EL) showed the highest grey relational degree with YP. The first four principal components cumulatively accounted for 73.36% of variation. EL, KW, plant height (PH), ear height (EH), GP, KRN, and YP contributed positively to the variation, whereas KRE, shelling percentage (SP), bald-tip length (BTL), and ear girth (EG) contributed negatively. Based on trait similarity, the 59 maize hybrids were classified into two clusters, Clusters I and II. A total of 11 traits were grouped into four clusters, Clusters A–D. Cluster D included KW, GP, KRN, EL, EH, PH, and YP, and the 22 maize hybrids in Cluster I performed better in these traits. These results provide a theoretical basis for the breeding of high-yield maize varieties in mountainous areas.
Effect of Harvest Maturity and Lactiplantibacillus plantarum Inoculant on Dynamics of Fermentation Characteristics and Bacterial and Fungal Community of Triticale Silage
Authors: Gao Run , Liu Yi , Wu Bo , Jia Chunlin , Yu Zhu , Wang Guoliang
Published: September 2024

(1) Background: Suitable harvest maturity stage selection and microbial inoculation during anaerobic fermentation are effective strategies for improving the quality of triticale (×Triticosecale) silage for ruminant nutrition. (2) Methods: In the present study, the fermentation characteristics, microbial communities, and their correlations were evaluated for triticale silages, as affected by Lactiplantibacillus plantarum (LP) inoculation at the heading, flowering, filling, milk-ripening, and wax-ripening stages. (3) Results: The results indicate that the filling and milk-ripening stages without LP inoculation resulted in lower pH and higher lactic acid than other harvest maturity stages (p < 0.05). Inoculating with LP decreased the pH at each harvest maturity stage, except for the filling stage, and increased the lactic acid concentration at the heading and filling stages (p < 0.05). The bacterial dynamics indicated that the abundances of Lactiplantebacilli and Monascus of the triticale silages without the LP inoculation were different between the harvest maturity stages (p < 0.05), and the abundance of Enterobacters was different between the harvest maturity stages in the triticale silage (p < 0.05). Remarkably, negative correlations were found between the Lactiplantebacillus, Monascus, and pH and positive correlations were found between the Lactiplantebacillus, Monascus, and lactic acid content (p < 0.05). (4) Conclusions: The filling and milk-ripening stages were the most suitable harvest maturity stages for the triticale silage. Inoculation with LP could enhance the fermentation quality, increase the abundances of beneficial microorganisms, and inhibit harmful microorganisms in triticale silage.
Physicochemical Characterization of Broiler Poultry Litter from Commercial Broiler Poultry Operation in Semiarid Tropics of India
Authors: Maruthamuthu Thirunavukkarasu , Karuppusamy Sivakumar , Veeramalai Ramesh , Nagarajan Murali , Manika Ragavan Purushothaman , Santiago Mahimairaja , Nallathambi Bharathy , Dharmalingam Anandha Prakash Singh , Radhakrishnan Karthika , Ramasamy Ajaykumar , Ramasamy Shri Rangasami Silambiah , Aranganoor Kannan Thriruvenkadan
Published: September 2024

This study characterized the physicochemical properties of broiler poultry litter (BPL) produced from intensively reared commercial broilers that were collected from 110 commercial poultry farms at the end of the production cycle (sixth week). A further 20 samples were collected from the end use point where BPL was utilized as a soil amendment by the farmers after a period of storage for improving poultry litter management practices, developing new litter treatment technologies, or enhancing its use as a sustainable resource. The dry matter (DM), moisture, ash, organic matter (OM), and organic carbon (OC) from the manure samples were 83.04, 16.96, 27.08, 72.92, and 42.39%, respectively. The pH, electrical conductivity (EC) (dS m−1), and Kjeldahl nitrogen (N) were 8.43, 5.74, and 24.2 g kg−1, respectively. The BPL from the cement floor had higher levels of P and K than the mud floor. The correlation studies revealed that the OM, C, N, and Zn had significant positive correlations; pH, moisture, and ash had positive correlations; and EC, DM, and Ca had positive correlations. The EC level of BPL negatively correlated with pH, Fe, and Mn. The N content was found to have a highly significant (p < 0.01) positive correlation with the OM, OC, Ca, and Zn content of BPL, and it was found to have a highly significant (p < 0.01) negative correlation with the ash content, pH, and K content of BPL. The P content of BPL showed a positive correlation (p < 0.01) with the K content and a negative correlation with the Zn (p < 0.05) and Fe (p < 0.01) contents of BPL. Zn was found to be negatively (p < 0.01) correlated with the ash content; the pH; and the K, Fe, and P content of BPL. According to the findings of this study, BPL as such at the end of the production cycle is rich in OM, nitrogen, macrominerals, and microminerals; however, at the point of utility (after a period of storage of 4 to 6 months), there was a loss of OM, N, and mineral concentrations, highlighting the importance of proper storage and composting. Overall, this study on the physicochemical properties of broiler poultry litter is crucial for improving agricultural practices, protecting the environment, and preserving the health and safety of human beings and livestock.
Effects of Different Drying Methods on Drying Characteristics and Quality of Small White Apricot (Prunus armeniaca L.)
Authors: Gao Jian-Rui , Li Meng-Yao , Cheng Zhe-Yu , Liu Xin-Yu , Yang Hao , Li Mao-Ting , He Rui-Ying , Zhang Qian , Yang Xu-Hai
Published: September 2024

This study examined the effects of hot air drying (HAD), infrared radiation drying (IRD), microwave vacuum drying (MVD), freeze drying (FD), and freeze drying combined with microwave vacuum drying (FD-MVD) on the drying kinetics, color, rehydration ratio, titratable acidity, and vitamin C content of small white apricots (Prunus armeniaca L.). Results showed drying times of 12.5 h (IRD), 14.1 h (FD), 16 h (HAD), 0.53 h (MVD), and 6.15 h (FD-MVD). FD-MVD significantly outperformed MVD, HAD, and IRD in color, vitamin C, titratable acidity, and rehydration, though was slightly inferior to FD. Microstructural analysis revealed that FD-MVD preserved the most uniform pore structure, better maintaining apricots’ original appearance. In contrast, IRD and HAD caused severe surface shriveling, compromising quality. In conclusion, FD-MVD emerges as a promising drying method to enhance apricot quality and market competitiveness in food processing.
Research on the Impact of Agricultural Production Outsourcing on Farmers’ Fertilizer Application Intensity: An Inverse U-Shaped Relationship
Authors: Niu Yongze , Li Jiahui , Xia Xianli
Published: September 2024

Agricultural production outsourcing services encourage a shift in the way crops are grown in developing countries and make it easier for small farmers to join the social division of labor in agriculture. This makes production more efficient and has a big effect on the inputs used in agriculture, especially fertilizer. This paper empirically tests the impact of production outsourcing on farmers’ fertilizer intensity using the instrumental variables method with non-planar panel data from the 2020–2022 China Land Economy Survey (CLES) of farm plots. The results showed that there was a significant inverted U-shaped relationship between the degree of agricultural production outsourcing and the intensity of fertilization on farmers’ plots. Mechanistic analysis shows that agricultural production outsourcing affects the fertilizer intensity by changing the labor allocation of farmers. Especially as the degree of agricultural production outsourcing increases, the intensity of farm labor inputs by farmers gradually decreases, and the impact of fertilizer intensity on the plots showed a tendency to be promoted first and then suppressed. The moderating effect showed that plot size was a major moderating factor. This means that the bigger the plot, the flatter the inverted U-shaped curve became, and the same level of outsourcing could lead to less fertilizer application. This happened by moving the inflection point of the inverted U-shaped curve to the left, which stopped the fertilizer application at a lower level of outsourcing. Heterogeneity analysis showed that participation in technology-intensive production outsourcing was beneficial in terms of reducing fertilizer intensity, and that an increased degree of agriculture production outsourcing was beneficial for farmers with large plot sizes and younger heads of household.
A Novel SPOTTED LEAF1-1 (SPL11-1) Gene Confers Resistance to Rice Blast and Bacterial Leaf Blight Diseases in Rice (Oryza sativa L.)
Authors: Lin Shaojun , He Niqing , Cheng Zhaoping , Huang Fenghuang , Wang Mingmin , Al Aboud Nora M. , Abou-Elwafa Salah F. , Yang Dewei
Published: September 2024

Programmed cell death (PCD) plays critical roles in plant immunity but must be regulated to prevent excessive damage. In this study, a novel spotted leaf (spl11-1) mutant was identified from an ethyl methane sulfonate (EMS) population. The SPL11-1 gene was genetically mapped to chromosome 12 between the Indel12-37 and Indel12-39 molecular markers, which harbor a genomic region of 27 kb. Annotation of the SPL11-1 genomic region revealed the presence of two candidate genes. Through gene prediction and cDNA sequencing, it was confirmed that the target gene in the spl11-1 mutant is allelic to the rice SPOTTED LEAF (SPL11), hereafter referred to as spl11-1. Sequence analysis of SPL11 revealed a single bp deletion (T) between the spl11-1 mutant and the ‘Shuangkang77009’ wild type. Moreover, protein structure analysis showed that the structural differences between the SPL11-1 and SPL11 proteins might lead to a change in the function of the SPL11 protein. Compared to the ‘Shuangkang77009’ wild type, the spl11-1 mutant showed more disease resistance. The agronomical evaluation showed that the spl11-1 mutant showed more adverse traits. Through further mutagenesis treatment, we obtained the spl11-2 mutant allelic to spl11-1, which has excellent agronomic traits and more improvement and may have certain breeding prospects in future breeding for disease resistance.
Impact of Organic Fertilization Strategies on Soil Bacterial Community and Honey Pomelo (Citrus maxima) Properties
Authors: Li Jinbiao , Wei Zhike , Tao Lin , Zhong Jingqi , Liu Xiumei , Ji Jianhua , Lan Xianjin , Hou Hongqian , Feng Zhaobin , Xiao Jingshang , Hu Anyong , Liu Yiren , Lv Zhenzhen
Published: September 2024

Soil health is a critical factor in sustainable agriculture, particularly in fruit production, where fertilization strategies play a vital role in maintaining the soil quality and enhancing fruit production and quality. This study investigates the effects of different fertilization strategies on soil bacterial communities and honey pomelo (Citrus maxima) properties in Ji’an City, Jiangxi Province, China. Three fertilization treatments were compared: conventional fertilization (CF: botanical organic plus chemical compound fertilizers), organic material fermented fertilization (OF: organic material including duck manure fermented fertilizer plus chemical compound fertilizer), and a special honey pomelo fertilizer (SF: organic material fermented fertilizer only during the whole honey pomelo growing season). Soil samples were collected at two depths (0–20 cm and 20–40 cm) from nine plots (three treatments × three replicates) and analyzed for their soil properties, bacterial community diversity and composition, and fruit characteristics. The results indicate that the OF and SF significantly improved the soil pH, soil organic matter (SOM), and nutrient availability compared to the CF. Additionally, the OF and SF treatments led to a 13.6% and 16.6% increase in fruit weight, respectively, and higher bacterial diversity, although no significant differences were observed in fruit quality parameters such as vitamin C, soluble sugar, and titratable acid. Acidobacteriota, Proteobacteria, Actinobacteria, and Chloroflexi were the dominant bacterial phyla. The soil bacterial composition structures were significantly different among the different fertilization strategies, and were well explained by soil properties such as the pH, SOM, total phosphorus, and available nutrients. Our study suggests that applying fermented organic fertilizers which use duck manure as part of the raw materials, either alone or in combination with chemical compound fertilizers, increases honey pomelo fruit production and improves soil health, contributing to the sustainable development of orchards.
Impact of Pulse Electric Field Stimulation on Negative Air Ion Release Capacity of Snake Plants
Authors: Liu Jin , Huang Deyao , Cheng Zhiyuan , Wu Renye
Published: September 2024

To investigate the effects of pulse electric field stimulation on the photosynthetic electron transport chain and negative air ion (NAI) release capacity of snake plants, the chlorophyll content, fluorescence induction kinetics curve (OJIP curve), chlorophyll fluorescence parameters, and NAI release concentration of snake plants kept under identical greenhouse conditions under different pulse electric field stimulations were compared and analyzed. The experimental results show that (1) after pulse electric field stimulation, the chlorophyll content in treatment group T1 (5 kv) and T2 (7 kv) of snake plants increased by 6.30% and 6.70%, respectively, with significant differences observed between the two treatment groups and the control group (CK). (2) In both treatment groups, the OJIP curve exhibited higher values for the inflection point (I) and peak (P) compared to the origin (O) and inflection point (J) values, with the rising trend in the I–P segment being more gentle than that of the O–J segment. Additionally, the J band was above 0, with the peak value in the T2 group being higher than that in the T1 group. (3) The chlorophyll fluorescence parameters showed fluctuating variations. Specifically, Fm, TRo/CSo, ETo/CSo, and DIo/CSo showed ascending trends in the treatment groups. Fv/Fo, Sm, and ABS/RC exhibited descending trends; Fv/Fm, Vj, ETo/RC, and φEo showed relatively minor changes. The PIabs displayed a decreasing trend. The PItotal in the CK was greater than that in the T1 and T2 groups. (4) After 4 h of pulse electric field stimulation, the NAI concentration increased by 87.60% in the T1 group and by 62.09% in the T2 group, compared to the same measurement taken at 3 h. Pulse electric field impacts the photosynthetic electron transport chain of snake plants, thereby influencing their NAI release capacity. This study aims to elucidate the physiological responses of the chloroplasts in snake plants to pulsed electric field stimulation and to lay the foundation for enhancing the plant’s release of negative air ion concentrations through physical and technological means.
Laser Weeding Technology in Cropping Systems: A Comprehensive Review
Authors: Yaseen Muhammad Usama , Long John M.
Published: September 2024

Weed infestations pose significant challenges to global crop production, demanding effective and sustainable weed control methods. Traditional approaches, such as chemical herbicides, mechanical tillage, and plastic mulches, are not only associated with environmental concerns but also face challenges like herbicide resistance, soil health, erosion, moisture content, and organic matter depletion. Thermal methods like flaming, streaming, and hot foam distribution are emerging weed control technologies along with directed energy systems of electrical and laser weeding. This paper conducts a comprehensive review of laser weeding technology, comparing it with conventional methods and highlighting its potential environmental benefits. Laser weeding, known for its precision and targeted energy delivery, emerges as a promising alternative to conventional control methods. This review explores various laser weeding platforms, discussing their features, applications, and limitations, with a focus on critical areas for improvement, including dwell time reduction, automated navigation, energy efficiency, affordability, and safety standards. Comparative analyses underscore the advantages of laser weeding, such as reduced environmental impact, minimized soil disturbance, and the potential for sustainable agriculture. This paper concludes by outlining key areas for future research and development to enhance the effectiveness, accessibility, and affordability of laser weeding technology. In summary, laser weeding presents a transformative solution for weed control, aligning with the principles of sustainable and environmentally conscious agriculture, and addressing the limitations of traditional methods.
Screening Low-Cadmium and High-Mineral Nutrient Rapeseed (Brassica napus L.) Cultivars According to the Uptake and Transport Characteristics of Elements
Authors: Tang Xu , Tian Hui , Zhang Haoran , Chai Guohua , Wu Xiuwen
Published: September 2024

Screening the edible parts of low-cadmium (Cd) and high-nutrient crop cultivars is an effective method for reducing Cd intake and enhancing the absorption of beneficial elements for humans. In a hydroponic experiment with Cd toxicity treatment (5 μmol/L CdCl2), we analyzed the differences in the absorption and transport characteristics of Cd and mineral nutrients in 30 rapeseed (Brassica napus L.) cultivars during the seedling stage, as well as the correlations between various elements. Firstly, Pearson correlation analysis indicated that Cd content in the shoot parts of 30 rapeseed cultivars was not correlated with the Cd uptake ability of the roots and was obviously positively correlated with the Cd translocation coefficient from root to shoot (r = 0.452 *, p < 0.05). Hierarchical clustering selected 26 cultivars with lower Cd content in the shoots, and correlation analysis of Cd and other nutrient element contents in the shoots of the 26 cultivars revealed significant negative correlations (r = −0.40 *, p < 0.05; r = −0.45 *, p < 0.05) between iron (Fe) and magnesium (Mg) content and Cd content, while potassium (K), calcium (Ca), manganese (Mn), and zinc (Zn) content had no correlation with Cd content. Then, hierarchical clustering screened 19 cultivars with higher dry weight, 4 cultivars with higher K content, 1 cultivar with higher Ca content, 8 cultivars with higher Mn content, and 3 cultivars with higher Zn content. Finally, a Venn diagram identified four superior rapeseed cultivars with lower Cd and higher nutrients in the shoots, namely, OJ114 (lower Cd, higher Mn and K content), BN365 (lower Cd, higher Mn, Fe, and Zn content), BN275 (lower Cd, higher Ca, Zn, Mn, and Fe content), and BN112 (lower Cd, higher K, Mg, Fe, and Mn content).
Spectral Intelligence: AI-Driven Hyperspectral Imaging for Agricultural and Ecosystem Applications
Authors: Ali Faizan , Razzaq Ali , Tariq Waheed , Hameed Akhtar , Rehman Abdul , Razzaq Khizar , Sarfraz Sohaib , Rajput Nasir Ahmed , Zaki Haitham E. M. , Shahid Muhammad Shafiq , Ondrasek Gabrijel
Published: September 2024

Ensuring global food security amid mounting challenges, such as population growth, disease infestations, resource limitations, and climate change, is a pressing concern. Anticipated increases in food demand add further complexity to this critical issue. Plant pathogens, responsible for substantial crop losses (up to 41%) in major crops like wheat, rice, maize, soybean, and potato, exacerbate the situation. Timely disease detection is crucial, yet current practices often identify diseases at advanced stages, leading to severe infestations. To address this, remote sensing and Hyperspectral imaging (HSI) have emerged as robust and nondestructive techniques, exhibiting promising results in early disease identification. Integrating machine learning algorithms with image data sets enables precise spatial–temporal disease identification, facilitating timely detection, predictive modeling, and effective disease management without compromising fitness or climate adaptability. By harnessing these cutting-edge technologies and data-driven decision-making, growers can optimize input costs while achieving enhanced yields, making significant strides toward global food security in the face of climate change risks. This review will discuss some of the foundational concepts of remote sensing, several platforms used for remote sensing data collection, successful application of the approach, and its future perspective.
Activity of Organoboron Compounds against Biofilm-Forming Pathogens
Authors: Konaklieva Monika I. , Plotkin Balbina J.
Published: September 2024

Bacteria have evolved and continue to change in response to environmental stressors including antibiotics. Antibiotic resistance and the ability to form biofilms are inextricably linked, requiring the continuous search for alternative compounds to antibiotics that affect biofilm formation. One of the latest drug classes is boron-containing compounds. Over the last several decades, boron has emerged as a prominent element in the field of medicinal chemistry, which has led to an increasing number of boron-containing compounds being considered as potential drugs. The focus of this review is on the developments in boron-containing organic compounds (BOCs) as antimicrobial/anti-biofilm probes and agents.
Reactive Oxygen Species in Cystic Kidney Disease
Authors: Subhash Sanat , Vijayvargiya Sonya , Parmar Aetan , Sandhu Jazlyn , Simmons Jabrina , Raina Rupesh
Published: September 2024

Polycystic kidney disease (PKD) is a rare but significant renal condition with major implications for global acute and chronic patient care. Oxidative stress and reactive oxygen species (ROS) can significantly alter its pathophysiology, clinical outcomes, and treatment, contributing to negative outcomes, including hypertension, chronic kidney disease, and kidney failure. Inflammation from ROS and existing cysts propagate the generation and accumulation of ROS, exacerbating kidney injury, pro-fibrotic signaling cascades, and interstitial fibrosis. Early identification and prevention of oxidative stress and ROS can contribute to reduced cystic kidney disease progression and improved longitudinal patient outcomes. Increased research regarding biomarkers, the pathophysiology of oxidative stress, and novel therapeutic interventions alongside the creation of comprehensive guidelines establishing methods of assessment, monitoring, and intervention for oxidative stress in cystic kidney disease patients is imperative to standardize clinical practice and improve patient outcomes. The integration of artificial intelligence (AI), genetic editing, and genome sequencing could further improve the early detection and management of cystic kidney disease and mitigate adverse patient outcomes. In this review, we aim to comprehensively assess the multifactorial role of ROS in cystic kidney disease, analyzing its pathophysiology, clinical outcomes, treatment interventions, clinical trials, animal models, and future directions for patient care.
Functional Properties and Sensory Quality of Kombucha Analogs Based on Herbal Infusions
Authors: Czarnowska-Kujawska Marta , Klepacka Joanna , Starowicz Małgorzata , Lesińska Patrycja
Published: September 2024

Traditionally, kombucha is produced by the fermentation of black or green tea infusions with the use of SCOBY (Symbiotic Culture of Bacteria and Yeasts). However, SCOBY exhibits the ability to ferment other substrates as well, which can be used to create novel products with new sensory and health-promoting properties. This paper investigates the antioxidant activity, chemical composition, and sensory properties of mint, nettle, and blackcurrant leaf-based kombucha analogs. It has been demonstrated that the fermentation process with SCOBY significantly influenced (p ≤ 0.05) sugar, organic acids, and mineral contents, with the increase in iron, magnesium, and calcium amounts in all tested herbal kombucha. The study shows that the type of herb infusion has a significant influence on the parameters associated with antioxidant potential. The fermentation with SCOBY resulted in an increase in antioxidant activity as measured by the superoxide anion radical (O2•−) inhibition of all three tested herbal infusions, with the greatest changes observed in nettle kombucha. Herbal kombucha was characterized by significantly increased total phenolic content as determined by Folin’s reagent and a changed phenolic compound profile by LC-MS/MS (liquid chromatography with tandem mass spectrometry) in comparison to nonfermented infusions. Very high sensory scores were achieved for fermented mint and blackcurrant-based kombucha.
Deep Learning for Water Quality Prediction—A Case Study of the Huangyang Reservoir
Authors: Chen Jixuan , Wei Xiaojuan , Liu Yinxiao , Zhao Chunxia , Liu Zhenan , Bao Zhikang
Published: September 2024

Water quality prediction is a fundamental prerequisite for effective water resource management and pollution prevention. Accurate predictions of water quality information can provide essential technical support and strategic planning for the protection of water resources. This study aims to enhance the accuracy of water quality prediction, considering the temporal characteristics, variability, and complex nature of water quality data. We utilized the LTSF-Linear model to predict water quality at the Huangyang Reservoir. Comparative analysis with three other models (ARIMA, LSTM, and Informer) revealed that the Linear model outperforms them, achieving reductions of 8.55% and 10.51% in mean square error (MSE) and mean absolute error (MAE), respectively. This research introduces a novel method and framework for predicting hydrological parameters relevant to water quality in the Huangyang Reservoir. These findings offer a valuable new approach and reference for enhancing the intelligent and sustainable management of the reservoir.
Dynamic Analysis and Energy Harvesting Potential of Slitted Cantilever Beam Fitted with Piezoelectric Transducer
Authors: Almokmesh Saad F. , Alzuwayer Bashar B. , Almutairi Abdulrahman S. , Alhashem Abdulwahab
Published: September 2024

This research investigates how slitted beams fitted with piezoelectric transducers (PZTs) behave when generating energy from environmental vibrations. By changing slit widths, slit lengths, and tip masses, we investigated the frequency response of these beams using analytical methods and finite element analysis (FEA). The obtained results demonstrate that resonance peaks are brought closer together, and coupling between vibrational modes is enhanced by larger slit spacing, whether or not anti-resonance dips are present, though the magnitudes of these peaks are affected by the width of the slits. The possibility of energy harvesting can be enhanced when resonance peaks are shifted and amplified by heavier tip masses. The FEA results support the analytical model, showing other characteristics such as sharp dips or anti-resonance troughs. This work provides valuable information for future design improvements by highlighting the significance of optimizing slit parameters and tip masses to enhance the efficiency of piezoelectric energy harvesters. This study demonstrates the benefits of using slitted beams with piezoelectric energy harvesting and provides recommendations for their efficient design.
Impact of Four Different Chlorella vulgaris Strains on the Properties of Durum Wheat Semolina Pasta
Authors: Baune Marie-Christin , Lickert Thomas , Schilling Frank , Bindrich Ute , Tomasevic Igor , Heinz Volker , Smetana Sergiy , Terjung Nino
Published: September 2024

Microalgae are a promising protein source due to their high protein content; high reproductivity; and low carbon, water, and arable land footprints. In this study, the impact of adding 3 and 5% of four Chlorella vulgaris strains, namely Smooth (SCV), Honey (HCV), White (WCV), and New Honey C. vulgaris (NHCV), on the processing, cooking behavior, color, firmness, structure, and sensory properties of durum wheat semolina pasta was investigated. It was hypothesized that (1) changes in physical properties depend on strain and concentration, (2) acceptability varies by strain due to different colors, odors, and flavors, and (3) the absence of fishy odors and flavors is crucial for acceptance rather than color. The results show that high-quality pasta could be produced with all C. vulgaris strains and concentrations. Cooking time and water absorption of all samples decreased but only significantly for the samples with NHCV added. Also, the bite resistance (determined instrumentally and sensorially) increased for almost all samples due to increasing protein and fiber content. A clear concentration dependency could not be found. In terms of sensory acceptance, NHCV performed the best, and an unaltered typical odor was identified to be crucial rather than color or the absence of fishy odor.
An Insulator Fault Diagnosis Method Based on Multi-Mechanism Optimization YOLOv8
Authors: Gong Chuang , Jiang Wei , Zou Dehua , Weng Weiwei , Li Hongjun
Published: September 2024

Aiming at the problem that insulator image backgrounds are complex and fault types are diverse, which makes it difficult for existing deep learning algorithms to achieve accurate insulator fault diagnosis, an insulator fault diagnosis method based on multi-mechanism optimization YOLOv8-DCP is proposed. Firstly, a feature extraction and fusion module, named CW-DRB, was designed. This module enhances the C2f structure of YOLOv8 by incorporating the dilation-wise residual module and the dilated re-param module. The introduction of this module improves YOLOv8’s capability for multi-scale feature extraction and multi-level feature fusion. Secondly, the CARAFE module, which is feature content-aware, was introduced to replace the up-sampling layer in YOLOv8n, thereby enhancing the model’s feature map reconstruction ability. Finally, an additional small-object detection layer was added to improve the detection accuracy of small defects. Simulation results indicate that YOLOv8-DCP achieves an accuracy of 97.7% and an mAP@0.5 of 93.9%. Compared to YOLOv5, YOLOv7, and YOLOv8n, the accuracy improved by 1.5%, 4.3%, and 4.8%, while the mAP@0.5 increased by 3.0%, 4.3%, and 3.1%. This results in a significant enhancement in the accuracy of insulator fault diagnosis.
Editorial: Applications of Artificial Intelligence and Machine Learning in Games
Authors: Mozgovoy Maxim
Published: September 2024

Recent developments in AI and machine learning technologies have significantly expanded their application area in games [...]
Multi-Scale Integrated Corrosion-Adjusted Seismic Fragility Framework for Critical Infrastructure Resilience
Authors: Urlainis Alon , Lifshitz Sherzer Gili , Shohet Igal M.
Published: September 2024

This study presents a novel framework for integrating corrosion effects into critical infrastructure seismic risk assessment, focusing on reinforced concrete (RC) structures. Unlike traditional seismic fragility curves, which often overlook time-dependent degradation such as corrosion, this methodology introduces an approach incorporating corrosion-induced degradation into seismic fragility curves. This framework combines time-dependent corrosion simulation with numerical modeling, using the finite–discrete element method (FDEM) to assess the reduction in structural capacity. These results are used to adjust the seismic fragility curves, capturing the increased vulnerability due to corrosion. A key novelty of this work is the development of a comprehensive risk assessment that merges the corrosion-adjusted fragility curves with seismic hazard data to estimate long-term seismic risk, introducing a cumulative risk ratio to quantify the total risk over the structure’s lifecycle. This framework is demonstrated through a case study of a one-story RC moment frame building, evaluating its seismic risk under various corrosion scenarios and locations. The simulation results showed a good fit, with a 3% to 14% difference between the case study and simulations up to 75 years. This fitness highlights the model’s accuracy in predicting structural degradation due to corrosion. Furthermore, the findings reveal a significant increase in seismic risk, particularly in moderate and intensive corrosion environments, by 59% and 100%, respectively. These insights emphasize the critical importance of incorporating corrosion effects into seismic risk assessments, offering a more accurate and effective strategy to enhance infrastructure resilience throughout its lifecycle.
Interpolation-Filtering Method for Image Improvement in Digital Holography
Authors: Kozlov Alexander V. , Cheremkhin Pavel A. , Svistunov Andrey S. , Rodin Vladislav G. , Starikov Rostislav S. , Evtikhiev Nikolay N.
Published: September 2024

Digital holography is actively used for the characterization of objects and 3D-scenes, tracking changes in medium parameters, 3D shape reconstruction, detection of micro-object positions, etc. To obtain high-quality images of objects, it is often necessary to register a set of holograms or to select a noise suppression method for specific experimental conditions. In this paper, we propose a method to improve filtering in digital holography. The method requires a single hologram only. It utilizes interpolation upscaling of the reconstructed image size, filtering (e.g., median, BM3D, or NLM), and interpolation to the original image size. The method is validated on computer-generated and experimentally registered digital holograms. Interpolation methods coefficients and filter parameters were analyzed. The quality is improved in comparison with digital image filtering up to 1.4 times in speckle contrast on the registered holograms and up to 17% and 29% in SSIM and NSTD values on the computer-generated holograms. The proposed method is convenient in practice since its realization requires small changes of standard filters, improving the quality of the reconstructed image.
Transferable Deep Learning Models for Accurate Ankle Joint Moment Estimation during Gait Using Electromyography
Authors: Ali Amged Elsheikh Abdelgadir , Owaki Dai , Hayashibe Mitsuhiro
Published: September 2024

The joint moment is a key measurement in locomotion analysis. Transferable prediction across different subjects is advantageous for calibration-free, practical clinical applications. However, even for similar gait motions, intersubject variance presents a significant challenge in maintaining reliable prediction performance. The optimal deep learning models for ankle moment prediction during dynamic gait motions remain underexplored for both intrasubject and intersubject usage. This study evaluates the feasibility of different deep-learning models for estimating ankle moments using sEMG data to find an optimal intrasubject model against the inverse dynamic approach. We verified and compared the performance of 1302 intrasubject models per subject on 597 steps from seven subjects using various architectures and feature sets. The best-performing intrasubject models were recurrent convolutional neural networks trained using signal energy features. They were then transferred to realize intersubject ankle moment estimation.
The Design of a Long-Distance Signal Transmission System in a Bistatic RCS Testing System
Authors: He Yuchen , Hong Tao , Chen Zhihua , Liu Penghao , Wang Yiran
Published: September 2024

In wireless communication and radar systems, long-distance signal transmission poses significant challenges that affect overall system performance. In this paper, we propose an innovative bistatic radar cross section (RCS) testing system designed to address these challenges, with a particular focus on its long-distance signal transmission capabilities. This system is capable of accurately measuring the RCS of a target and improving multipath channel modeling accuracy by using precise RCS values. The integrated upper computer software extracts amplitude and phase information from received echo signals, processes these data, and provides detailed outputs including the target’s RCS, one-dimensional image, and two-dimensional image. The experimental results obtained prove that this system can not only achieve effective long-distance signal transmission but also substantially enhance the accuracy of RCS measurements, offering reliable support for multipath channel modeling. However, the conclusions drawn are preliminary and require further experimental validation to fully substantiate this system’s performance. Future work will focus on improving system accuracy, minimizing the impact of environmental noise, and optimizing data-processing methods to enhance the efficiency of wireless communication and radar applications.
Soft Sets Extensions: Innovating Healthcare Claims Analysis
Authors: Gifu Daniela
Published: September 2024

In the dynamic arena of healthcare research, where the complexities of data often rival the intricacies of biological systems, the ability to model and analyze such multifaceted datasets is crucial. This comprehensive review delves into the evolution and application of soft sets and their extensions, including HyperSoft Sets, SuperHyperSoft Sets, IndetermSoft Sets, IndetermHyperSoft Sets, and TreeSoft Sets, in healthcare claims data analysis. These extensions address intricate challenges in data analysis, offering versatile frameworks for managing the uncertainty and indeterminacy inherent in healthcare claims data. By exploring their definitions and applications, this review elucidates how these mathematical tools have evolved and their significance in advancing healthcare research and enhancing data analysis methodologies. Real-world examples underscore the implications of these tools, emphasizing their pivotal role in facilitating informed decision-making and knowledge discovery in healthcare. The review systematically examines various case studies and research findings to illustrate the practical utility of soft set extensions. Detailed analyses of real-world scenarios highlight advancements in processing complex healthcare data. The conclusions drawn from this analysis indicate that the adoption of soft sets and their extensions can significantly improve the accuracy and efficiency of healthcare data analysis, ultimately contributing to better healthcare outcomes and more informed policy-making. Future research directions are also discussed, suggesting further potential applications and developments in this field.
Optical Measurement System for Monitoring Railway Infrastructure—A Review
Authors: Zschiesche Kira , Reiterer Alexander
Published: September 2024

Rail infrastructure plays an important role in fulfilling the demand for freight and passenger transportation. Increases in traffic volume, heavier axles and vehicles, higher speeds, and increasing climate extremes all contribute to the constant strain on the infrastructure. Due to their major importance in the transportation of people and freight, they are subject to continuous condition monitoring. This is an essential requirement for the selective planning of maintenance tasks and ultimately for safe and reliable operation. Various measuring systems have been developed for this purpose. These must measure precisely, quickly, and robustly under difficult conditions. Whether installed from mobile or stationary platforms, they have to cope with a wide range of ambient temperatures and lighting conditions, harsh environmental influences, and varying degrees of reflection. Despite these circumstances, railway operators require precise measurement data, high data densities even at high traveling speeds, and a user-friendly presentation of the results. Photogrammetry, laser scanning, and fiber optics are light-based measurement methods that are used in this sector. They are able to record with high precision rail infrastructure such as overhead contact systems, clearance profiles, rail tracks, and much more. This article provides an overview of the established and modern optical sensing methods, as well as the use of artificial intelligence as an evaluation method, and highlights their advantages and disadvantages.
Probabilistic Analysis of Orbital Characteristics of Rotary Systems with Centrally and Off-Center Mounted Unbalanced Disks
Authors: Šavrnoch Zdenko , Sapieta Milan , Dekýš Vladimír , Drvárová Barbora , Pijáková Katarína , Sapietová Alžbeta , Sága Milan
Published: September 2024

Rotor dynamics plays a crucial role in the performance and safety of rotating machinery, with disk position and unbalance significantly impacting system behavior. This study investigates the dynamic characteristics of two rotor configurations: a centrally mounted unbalanced disk (Rotor05un) and an off-center unbalanced disk (Rotor025un). Using numerical simulations and Monte Carlo analysis, we examined critical speeds and orbital patterns for both configurations. Probability distributions of shaft orbital positions revealed distinct patterns for each configuration. Quantile analysis revealed approximate linear trends for Rotor025un, suggesting higher system stiffness and more predictable behavior near critical speeds. Cross-sectional analyses of the orbits provided insights into the complex interactions between disk position, gyroscopic effects, and system natural frequencies. These findings provide valuable insights for rotor system design, particularly for applications with non-ideal mass distributions. The study goes beyond traditional critical speed analysis to examine orbital patterns and point on orbit occurrence from a probabilistic perspective. Based on the simulation of the orbits, an orbital is determined that allows the probability of the shaft occurring at the analyzed distance from the origin to be determined. The paper also offers insights into the complex interaction behavior of chosen rotor configurations and highlights the importance of considering disk position in predicting and optimizing rotor dynamic behavior, contributing to the development of more robust and efficient rotating machinery.
ExamVoice: Innovative Solutions for Improving Exam Accessibility for Blind and Visually Impaired Students in Saudi Arabia
Authors: Al-Eidarous Walla , Alsiyami Aeshah , Aljabri Malak , Alqethami Sara , Almutanni Badriah
Published: September 2024

Ensuring equitable educational opportunities for blind and visually impaired (BVI) students in Saudi Arabian higher education remains challenging despite legislative and institutional efforts. This paper proposes a system to assist BVI students independently during exams, aiming to create an inclusive exam environment that minimizes distractions and facilitates their participation alongside peers. Key contributions include the development of a secure platform, ensuring exam confidentiality, and fostering confidence and active engagement among BVI individuals. The study highlights the importance of integrating innovative assistive technologies and implementing rigorous policies to overcome systemic barriers and improve support mechanisms for BVI students in educational settings.
Remote Sensing Evaluation and Monitoring of Spatial and Temporal Changes in Ecological Environmental Quality in Coal Mining-Intensive Cities
Authors: Huo Qiqi , Cheng Xiaoqian , Du Weibing , Zhang Hao , Han Ruimei
Published: September 2024

In coal-dependent urban economies, the dichotomy between resource exploitation and ecological conservation presents a pronounced challenge. Traditional remote sensing ecological assessments often overlook the interplay between mining activities and urban environmental dynamics. To address this gap, researchers developed an innovative Resource-Based City Ecological Index (RCEI), anchored in a Pressure–State–Response (PSR) framework and synthesized from six discrete ecological indicators. Utilizing geodetic remote sensing data, the RCEI facilitated a comprehensive spatiotemporal analysis of Jincheng City’s ecological quality from 1990 to 2022. The findings corroborated the RCEI’s efficacy in providing a nuanced portrayal of the ecological state within mining regions. (1) Jincheng City’s ecological quality predominantly sustained a mudhopper-tier status, exhibiting an overarching trend of amelioration throughout the study period. (2) Disparities in ecological landscape quality were pronounced at the county level, with Moran’s Index exceeding 0.9, signifying a clustered ecological quality pattern. High–high (H–H) zones were prevalent in areas of elevated altitude and dense vegetation, whereas low–low (L–L) zones were prevalent in urban and mining sectors. (3) Further, a buffer zone analysis of two coal mines, differing in their mining chronology, geographical positioning, and operational status, elucidated the ecological impact exerted over a 32-year trajectory. These insights furnish a robust scientific and technical foundation for resource-centric cities to fortify ecological safeguarding and to advance sustainable development stratagems.
Flexibility Assessment of Ternary Pumped Storage in Day-Ahead Optimization Scheduling of Power Systems
Authors: Wu Zhiyu , Wang Junzhou , Peng Sui , Zhang Yining , Pan Wenxuan , Tang Junjie
Published: September 2024

To explore the advantages in the flexibility of ternary pumped storage units (T-PSUs) compared with fixed-speed pumped storage units (FS-PSUs) and variable-speed pumped storage units (VS-PSUs) in the day-ahead optimal scheduling of power systems, this paper firstly establishes the mathematical model of T-PSUs which is suitable for the target application, and establishes a new hybrid pumped storage model combining both FS-PSUs and T-PSUs for the purpose of improving existing FS-PSUs. Secondly, a day-ahead optimal scheduling model used for a wind-thermal-pumped storage bundled transmission system with the goal of obtaining the lowest operating cost is established. Additionally, various indicators are proposed to comprehensively evaluate the flexibility of different pumped storage unit types on day-ahead optimal scheduling. Finally, a sensitivity analysis is conducted from three aspects: covering the wind power capacity, load rate, and pumped storage capacity. The results indicate that T-PSUs are superior to FS-PSUs and VS-PSUs in maintaining the smooth, economic, and robust operation of thermal power units, as well as in promoting wind power consumption. This provides a significant reference for evaluating the technical and economic benefits of the different types of pumped storage units in applications of future power grids.