bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Insect Pests on Soybean Leaves Based on SP-YOLO
Authors: Qin Kebei , Zhang Jie , Hu Yue
Published: July 2024

Soybean insect pests can seriously affect soybean yield, so efficient and accurate detection of soybean insect pests is crucial for soybean production. However, pest detection in complex environments suffers from the problems of small pest targets, large inter-class feature similarity, and background interference with feature extraction. To address the above problems, this study proposes the detection algorithm SP-YOLO for soybean pests based on YOLOv8n. The model utilizes FasterNet to replace the backbone of YOLOv8n, which reduces redundant features and improves the model’s ability to extract effective features. Second, we propose the PConvGLU architecture, which enhances the capture and representation of image details while reducing computation and memory requirements. In addition, this study proposes a lightweight shared detection header, which enables the model parameter amount computation to be reduced and the model accuracy to be further improved by shared convolution and GroupNorm. The improved model achieves 80.8% precision, 66.4% recall, and 73% average precision, which is 6%, 5.4%, and 5.2%, respectively, compared to YOLOv8n. The FPS reaches 256.4, and the final model size is only 6.2 M, while the number of computational quantities of covariates is basically comparable to that of the original model. The detection capability of SP-YOLO is significantly enhanced compared to that of the existing methods, which provides a good solution for soybean pest detection. SP-YOLO provides an effective technical support for soybean pest detection.
Zinc Oxide Nanoparticles in the “Soil–Bacterial Community–Plant” System: Impact on the Stability of Soil Ecosystems
Authors: Strekalovskaya Elena I. , Perfileva Alla I. , Krutovsky Konstantin V.
Published: July 2024

The use of man-made nanoparticles (NPs) has increased exponentially in recent years, many of which accumulate in significant quantities in soil, including through use in agriculture as nanofertilizers and nanopesticides. ZnO NPs are more environmentally friendly but have specific antimicrobial activity, which can affect soil microbiota, thereby influencing key microbial processes such as mineralization, nitrogen fixation and plant growth-promoting activities. Their behavior and persistence in soil depend on their chemical nature and soil characteristics. This review summarizes the applications of ZnO NPs in soil systems and their effects on various plants and soil microorganisms, particularly rhizobacteria that promote plant growth. A stimulating effect of ZnO NPs on the morphometric and biochemical characteristics of plants, as well as on soil microbiota and its activity at relatively low concentrations of up to 500 mg/mL and 250 mg/kg, respectively, is observed. As the concentration of ZnO NPs increases above these limits, toxic effects appear. The different effects of ZnO NPs are related to their size, dose, duration of exposure, solubility in water, as well as soil type, acidity and organic matter content. The review substantiates the need to study the behavior of ZnO NPs in the “soil-plant-microbiota” system for the possibility of using nanotechnologies in the agricultural industry and ensuring the safety of agricultural products.
Two-Stage Detection Algorithm for Plum Leaf Disease and Severity Assessment Based on Deep Learning
Authors: Yao Caihua , Yang Ziqi , Li Peifeng , Liang Yuxia , Fan Yamin , Luo Jinwen , Jiang Chengmei , Mu Jiong
Published: July 2024

Crop diseases significantly impact crop yields, and promoting specialized control of crop diseases is crucial for ensuring agricultural production stability. Disease identification primarily relies on human visual inspection, which is inefficient, inaccurate, and subjective. This study focused on the plum red spot (Polystigma rubrum), proposing a two-stage detection algorithm based on deep learning and assessing the severity of the disease through lesion coverage rate. The specific contributions are as follows: We utilized the object detection model YOLOv8 to strip leaves to eliminate the influence of complex backgrounds. We used an improved U-Net network to segment leaves and lesions. We combined Dice Loss with Focal Loss to address the poor training performance due to the pixel ratio imbalance between leaves and disease spots. For inconsistencies in the size and shape of leaves and lesions, we utilized ODConv and MSCA so that the model could focus on features at different scales. After verification, the accuracy rate of leaf recognition is 95.3%, and the mIoU, mPA, mPrecision, and mRecall of the leaf disease segmentation model are 90.93%, 95.21%, 95.17%, and 95.21%, respectively. This research provides an effective solution for the detection and severity assessment of plum leaf red spot disease under complex backgrounds.
Plant and Soil Effects of Alternative Sources of Phosphorus over Three Years of Application
Authors: Karpinska Anna , Kakouli-Duarte Thomais , Ashekuzzaman S.M. , Byrne John , Schmalenberger Achim , Forrestal Patrick J.
Published: July 2024

Plant growth and food security depend heavily on phosphorus (P). Recovering and recycling P from animal, municipal, and food waste streams can significantly reduce dependency on traditional mineral P. This is particularly pertinent in the EU regions with limited native P supplies. The agronomic performance of including P-based recycling-derived fertilisers (two struvite and two ashes) or cattle slurry was compared to a conventional mineral P fertilisation programme along with no P and no fertiliser controls over three years. A field-scale experiment was set up to evaluate the perennial ryegrass dry matter yield (DMY), P uptake, and soil test P effects. Struvite, ash, and cattle slurry proved effective in replacing P mineral fertiliser and produced yields similar to those of the mineral fertiliser programme. Differences were observed in plant P recovery, with struvite-based programmes achieving a significantly higher P recovery than ash-based programmes, which had the lowest plant P recovery. Differences in Morgan’s soil test P were also noted, with potato waste struvite (PWS) and poultry litter ash (PLA) showing significantly higher soil test P values. The findings strongly indicate that a range of recycled bio-based fertilisers from the bioeconomy can be used to reduce reliance on conventional imported mineral P fertiliser, with some programmes based on recycled fertilisers even surpassing the performance of conventional linear economy mineral fertilisers.
Germination Biology of Three Cyperaceae Weeds and Their Response to Pre- and Post-Emergence Herbicides in Paddy Fields
Authors: Jiang Lilin , Chai Ke , Fida Mujeeba , Fang Bin , Wang Kun , Bi Yaling
Published: July 2024

(1) Background: Cyperaceae weeds have become a major type of weed in local paddy fields in China. (2) Methods: We assessed the impact of environmental factors, including temperature, light, salinity, water stress and soil depth, on the germination and emergence of three dominant Cyperaceae weeds: Cyperus difformis L., C. iria L. and Fimbristylis littoralis Gaudich. Using the dish dipping method, the performances of the pre- and post-emergence herbicides commonly used in paddy fields on three Cyperaceae weeds were evaluated using the pot method. (3) Results: The seeds optimally germinated at 35 °C in constant conditions and 25 °C/40 °C in alternating conditions. The seeds of the three Cyperaceae weeds were sensitive to light and could not germinate under dark conditions. The germination rate of the three weeds decreased with the increase in the NaCl concentration and water potential; the three weeds could not germinate at a 320 mmol·L−1 NaCl concentration and −0.1 MPa water potential. When the pH levels were 4 to 9, the germination rates of the three weeds were all greater than 80%. The burial depths to inhibit 50% of the emergence of C. difformis, C. iria and F. littoralis were 0.27, 1.06 and 0.42 cm, respectively. The control efficacy of the pre-emergence herbicides of pretilachlor, butachlor and oxyfluorfen on the three weeds were all above 90% at the recommended dose in the field. Halosulfuron-methyl, florpyrauxifen-benzyl and bentazone could effectively control the three Cyperaceae weeds; their performances on the three weeds at the 3- to 4-leaf stage were all above 82%. (4) Conclusions: The three Cyperaceae weed seeds have a strong adaptability to temperature, water potential, salinity and soil depth, and these weeds are sensitive to most pre- and post-emergence herbicides. Therefore, taking Cyperaceae weed seeds into the deep soil layer by tillage or selecting appropriate herbicides according to their growth stages can effectively control Cyperaceae weeds in rice fields.
Influence of Spirulina Extract on Physiological, Qualitative, and Productive Traits of Four Sugarcane Genotypes
Authors: Ghallab Marwa , Bukhari Najat , Salem El-Araby , El-Zaidy Mohamed , El-Sheikh Amr , Raja Ramalingam
Published: July 2024

This study was conducted at El-Sabahia Research Station (latitude 31°12′ N, longitude 29°58′ E) in Alexandria, Egypt to evaluate the effect of Spirulina platensis algae extract on the growth, yield, and juice quality of four sugarcane genotypes during the 2020/2021 and 2021/2022 seasons. The sugarcane genotypes tested (G.T. 54-9, G. 2003-47, G. 84-47, and G. 2004-27) were treated with four concentrations (0, 0.1, 0.2, and 0.3%) of spirulina algae extract (SE) during their development as plant cane and first ratoon crops. At harvest, the growth, physiological, and juice quality characteristics were documented, while relative chlorophyll content was measured 210 days after sowing. Spraying canes with 0.2% of SE was the most effective treatment in enhancing all of the evaluated characteristics compared to those left without SE. Cane yield was more closely correlated with stalk weight (r = 0.88), followed by leaf area index (r = 0.82), relative chlorophyll content (r = 0.82), stalk length (r = 0.76), and number of tillers (r = 0.73), while recoverable sugar yield was closely correlated (p < 0.01) with sugar content % (r = 0.76).
Genome-Wide Identification of Height-Related Genes Using Three Maize Dwarfs and RNA-Seq
Authors: Gao Yang , Ren Haojie , Wang Ruiyu , Cheng Danyang , Song Yinglu , Wen Xin , Zhang Zheng , Chang Jianzhong
Published: July 2024

Plant height is an important grain yield-associated trait in maize. To date, few genes related to plant height have been characterized in maize. To better understand the genetic mechanisms of plant height in maize, we revealed the transcriptional changes of three dwarf mutants compared to the wild type. By ethyl methane sulfonate treatment of the wild-type maize cultivar PH6WC, we obtained three dwarfs—PH6WCdwarf1 (pd1), PH6WCdwarf2 (pd2), and PH6WCdwarf3 (pd3)—and their plant heights were reduced by 42%, 38%, and 24%, respectively. RNA-Seq data suggested that 1641 differentially expressed genes (DEGs) overlapped with each other among the three dwarfs at the seedling stage. Further analysis showed that the DEGs were divided into four groups with different expression patterns. Functional analysis revealed that these DEGs were commonly enriched in 47 GO terms mainly involved in cytokinesis, hormone, and energy metabolism pathways. Among them, An1, involved in the GA biosynthesis pathway, and mutations in An1 result in reduced plant height. EREB182 encodes ethylene-responsive element binding protein 2, which is critical for internode elongation. Microtubule-related genes Zmtub2, Zmtub3, Zmtub5, Zmtub6, and TUBG2 were commonly enriched among the three comparisons. Previous studies have shown that mutations in microtubule-associated genes cause the dwarf phenotype. However, nearly half of the common DEGs had no functional information, such as Zm00001d000107, Zm00001d000279, etc., implying their novel and specific functions in maize. Overall, this study identifies several potential plant height-related genes and contributes to linking genetic resources with maize breeding.
Fatty Acids and Volatile Flavor Components of Adipose Tissue from Local Tibetan Sheep in Qinghai with Dietary Supplementation of Palm Kernel Meal (PKM)
Authors: Ma Ying , Han Lijuan , Hou Shengzhen , Gui Linsheng , Sun Shengnan , Yuan Zhenzhen , Yang Chao , Wang Zhiyou , Yang Baochun
Published: July 2024

Substituting traditional protein feed with palm kernel meal (PKM) in the diet of Tibetan sheep can be a cost-effective feeding strategy. To determine the impact of PKM on flavor development in different adipose tissues of Tibetan sheep, subjects were fed with 15% and 18% of PKM, while the control group received no PKM. The fatty acids and volatile compounds in the samples were then analyzed by GC-MS and HS-GC-IMS. Adding PKM to the diet significantly increased the C12:0, C14:0, C16:0 and C18:1N9 content in adipose tissues compared with the control, and most of these were associated with flavor formation (p < 0.05). The flavor compounds in the adipose tissues predominantly consisted of alcohols, ketones, acids and aldehydes. In particular, including PKM in the diet increased the proportion of ketones but decreased the proportion of alcohols, acids and aldehydes in subcutaneous and tail fat. Specifically, the proportion of acetone, acetoin monomer, 2,3-butanedione, 2-butanone monomer, 2-methyl-2-propanol, 2-methyl-2-propanol and methyl acetate increased significantly in the subcutaneous and tail fat (p < 0.05), while that of ethanol, 1-propanol monomer, butanol monomer, acetic acid monomer and acetic acid monomer decreased. Intermuscular fat exhibited variable results, mainly because the addition of PKM resulted in higher proportions of alcohols, including ethanol, 1-propanol and butanol monomer, especially at 15% PKM. In summary, the addition of PKM improved the flavor of Tibetan sheep fat and increased the amount of favorable volatile flavor compounds. This study can serve as reference for understanding the effects of dietary PKM on the adipose tissue flavor profile of Tibetan sheep.
Optimized Depilation Method and Comparative Analysis of Hair Growth Cycle in Mouse Strains
Authors: Magalhaes Joana , Lamas Sofia , Portinha Carlos , Logarinho Elsa
Published: July 2024

In mice, hair growth follows a mosaic or wavy patterning. Therefore, synchronization of the hair growth cycle is required to adequately evaluate any trichogenic interventions pre-clinically. Depilation is the established method for synchronizing the growth phase of mouse hair follicles. When attempting to reproduce procedures reported in the literature, C57BL/6J mice developed severe wounds. This led us not only to optimize the procedure, but also to test the procedure in other strains, namely Sv129 and the F1 generation from C57BL/6J crossed with Sv129 (B6129F1 mixed background), for which the hair growth cycle has not been ascertained yet. Here, we describe an optimized depilation procedure, using cold wax and an extra step to protect the animal skin that minimizes injury, improving experimental conditions and animal welfare in all strains. Moreover, our results show that, although hair cycle kinetics are similar in all the analyzed strains, Sv129 and B6129F1 skins are morphologically different from C57BL/6J skin, presenting an increased number and size of hair follicles in anagen, consistent to the higher hair density observed macroscopically. Altogether, the results disclose an optimized mouse depilation method that excludes the detrimental and confounding effects of skin injury in hair growth studies and reveals the hair cycle features of other mouse strains, supporting their use in hair growth pre-clinical studies.
Associations of Socio-Demographic Characteristics of Dairy Goat Farmers in Greece with Biosecurity-Related Practices in the Farms
Authors: Lianou Daphne T. , Fthenakis George C.
Published: July 2024

Given the significance of goat farming in Greece, our study aimed to explore biosecurity conditions on goat farms and refers to an investigation performed on 119 farms countrywide in Greece. The objective of the present work was to evaluate and report on potential associations between the socio-demographic characteristics of goat farmers and practices that play a role in biosecurity on farms. Data were obtained during a large cross-sectional study performed across Greece in 119 goat herds. The socio-demographic characteristics of farmers, as well as 16 variables related to biosecurity, were recorded; these were practices or events that could potentially enhance or compromise biosecurity on farms. A score based on all the biosecurity-related variables was devised by assigning a ‘1’ or ‘−1’ mark for each variable recorded on a farm that could enhance or compromise, respectively, biosecurity. Among variables potentially enhancing biosecurity on farms, the application of disinfections on the farm and the maintenance of isolation for sick animals were practiced more frequently; among variables potentially compromising biosecurity on farms, the presence of hunters in the area around the farm and grazing practices for animals were recorded more frequently. The median overall score for biosecurity-related practices for all farms in the study was 1 (interquartile range: 2.5; minimum: −4; maximum: 5). Among socio-demographic characteristics, the presence of working staff on a farm was associated with five individual biosecurity-related practices and the length of farming experience with three individual biosecurity-related practices. In the multivariable analysis, female farmers (p = 0.007) and the presence of working staff on the farm (p = 0.025) emerged as the two significant socio-demographic characteristics with an association with the overall biosecurity level on farms. This knowledge can be useful when developing biosecurity programs on goat farms. Recognition of locally applied farm-level practices enhancing biosecurity could form a basis for farmers to apply more rigorous and effective relevant plans.
Force and Deformation Characteristics of Large-Scale Zoning Excavation in Soft Soil: A Case Study in Hangzhou
Authors: Lin Gang , Lin Zhaorui , Zhao Yi , Xu Changjie , Sun Feng , Duan Yun , Fang Tao
Published: July 2024

The zoning excavation method is fully employed to control the deformation of foundation pits constructed in urban soft soil areas. However, the similarities and differences in forces and deformations between foundation pits excavated by the zonal method and those excavated by the conventional method still need to be further explored. In this study, the deformation was monitored and analyzed by taking the zonal excavation of a foundation pit of the ‘New World’ project in Hangzhou City as the research object. The measured results showed that the pre-built diaphragm wall for the first excavated foundation pit restricted the deformation of the first excavated diaphragm wall. The presence of extensive construction and unloading activities also changed the deformation pattern of the soil. Further, finite element simulations were carried out. The simulation results revealed that excavating the foundation pit first caused displacements in the pre-built diaphragm wall. The displacements transmitted by non-adjacent pits through the pre-built diaphragm wall were small and were concentrated at the junction of the two sub-pits. Adjacent foundation pits caused large displacements of the pre-built diaphragm wall with similar displacement patterns. The results of the study can provide effective guidance for foundation pit excavation in soft soil areas in the future.
Numerical Computation of 2D Domain Integrals in Boundary Element Method by (α, β) Distance Transformation for Transient Heat Conduction Problems
Authors: Dong Yunqiao , Tan Zhengxu , Sun Hengbo
Published: July 2024

When the time-dependent boundary element method, also termed the pseudo-initial condition method, is employed for solving transient heat conduction problems, the numerical evaluation of domain integrals is necessitated. Consequently, the accurate calculation of the domain integrals is of crucial importance for analyzing transient heat conduction. However, as the time step decreases progressively and approaches zero, the integrand of the domain integrals is close to singular, resulting in large errors when employing standard Gaussian quadrature directly. To solve the problem and further improve the calculation accuracy of the domain integrals, an (α, β) distance transformation is presented. Distance transformation is a simple and efficient method for eliminating near-singularity, typically applied to nearly singular integrals. Firstly, the (α, β) coordinate transformation is introduced. Then, a new distance transformation for the domain integrals is constructed by replacing the shortest distance with the time step. With the new method, the integrand of the domain integrals is substantially smoothed, and the singularity arising from small time steps in the domain integrals is effectively eliminated. Thus, more accurate results can be obtained by the (α, β) distance transformation. Different sizes of time steps, positions of source point, and shapes of integration elements are considered in numerical examples. Comparative studies of the numerical results for the domain integrals using various methods demonstrate that higher accuracy and efficiency are achieved by the proposed method.
Locally Convex Spaces with Sequential Dunford–Pettis Type Properties
Authors: Gabriyelyan Saak
Published: July 2024

Let p,q,q′∈[1,∞], q′≤q. Several new characterizations of locally convex spaces with the sequential Dunford–Pettis property of order (p,q) are given. We introduce and thoroughly study the sequential Dunford–Pettis* property of order (p,q) of locally convex spaces (in the realm of Banach spaces, the sequential DP(p,∞)* property coincides with the well-known DPp* property). Being motivated by the coarse p-DP* property and the p-Dunford–Pettis relatively compact property for Banach spaces, we define and study the coarse sequential DP(p,q)* property, the coarse DPp* property and the p-Dunford–Pettis sequentially compact property of order (q′,q) in the class of all locally convex spaces.
Gemtuzumab Ozogamicin and Stem Cell Mobilization for Autologous Stem Cell Transplantation in Favorable Risk Acute Myeloid Leukemia
Authors: Martinez Flores Danaë , Akhoundova Dilara , Seipel Katja , Legros Myriam , Kronig Marie-Noelle , Daskalakis Michael , Bacher Ulrike , Pabst Thomas
Published: July 2024

Gemtuzumab ozogamicin (GO), a CD33-targeting antibody drug conjugate, previously showed longer relapse-free survival when combined with induction chemotherapy in patients with favorable-risk acute myeloid leukemia (AML). In this patient population, characterized by lower relapse risk as compared to other ELN risk groups, autologous stem cell transplantation (ASCT) can be used as consolidation strategy. However, there are limited data on the impact of GO on the peripheral blood stem cell (PBSC) mobilization potential. We therefore retrospectively analyzed data from 54 AML patients with favorable-risk AML treated with (n = 17) or without (n = 37) GO during induction treatment. We observed no significant differences in the PBSC mobilization rate between patients treated with vs. without GO. The mobilization success in a first attempt directly following cycle 2 was 65% vs. 70% (p = 0.92); and the mobilization success in a subsequent second attempt after hematologic recovery and repeated stimulation procedure was 24% vs. 19% (p = 0.56). No significant impact on treatment outcome in terms of EFS (p = 0.31) or OS (p = 0.99) was observed. Thus, our results suggest that the addition of GO to induction regimens does not negatively impact PBSC mobilization in favorable-risk AML patients. To our best knowledge, this is the first study comparing the stem cell mobilization potential in favorable-risk AML patients treated with vs. without GO.
Superior Anticancer and Antifungal Activities of New Sulfanyl-Substituted Niclosamide Derivatives
Authors: Ma Jingyi , Veeragoni Dileepkumar , Ghosh Hindole , Mutter Nicole , Barbosa Gisele , Webster Lauren , Schobert Rainer , Sande Wendy van de , Dandawate Prasad , Biersack Bernhard
Published: July 2024

The approved anthelmintic salicylanilide drug niclosamide has shown promising anticancer and antimicrobial activities. In this study, new niclosamide derivatives with trifluoromethyl, trifluoromethylsulfanyl, and pentafluorosulfanyl substituents replacing the nitro group of niclosamide were prepared (including the ethanolamine salts of two promising salicylanilides) and tested for their anticancer activities against esophageal adenocarcinoma (EAC) cells. In addition, antifungal activity against a panel of Madurella mycetomatis strains, the most abundant causative agent of the neglected tropical disease eumycetoma, was evaluated. The new compounds revealed higher activities against EAC and fungal cells than the parent compound niclosamide. The ethanolamine salt 3a was the most active compound against EAC cells (IC50 = 0.8–1.0 µM), and its anticancer effects were mediated by the downregulation of anti-apoptotic proteins (BCL2 and MCL1) and by decreasing levels of β-catenin and the phosphorylation of STAT3. The plausibility of binding to the latter factors was confirmed by molecular docking. The compounds 2a and 2b showed high in vitro antifungal activity against M. mycetomatis (IC50 = 0.2–0.3 µM) and were not toxic to Galleria mellonella larvae. Slight improvements in the survival rate of G. mellonella larvae infected with M. mycetomatis were observed. Thus, salicylanilides such as 2a and 3a can become new anticancer and antifungal drugs.
Inhibition of Protease-Activated Receptor-2 Activation in Parkinson’s Disease Using 1-Piperidin Propionic Acid
Authors: Quarta Santina , Sandre Michele , Ruvoletto Mariagrazia , Campagnolo Marta , Emmi Aron , Biasiolo Alessandra , Pontisso Patrizia , Antonini Angelo
Published: July 2024

In Parkinson’s disease, neuroinflammation is a double-edged sword; when inflammation occurs it can have harmful effects, despite its important role in battling infections and healing tissue. Once triggered by microglia, astrocytes acquire a reactive state and shift from supporting the survival of neurons to causing their destruction. Activated microglia and Proteinase-activated receptor-2 (PAR2) are key points in the regulation of neuroinflammation. 1-Piperidin Propionic Acid (1-PPA) has been recently described as a novel inhibitor of PAR2. The aim of our study was to evaluate the effect of 1-PPA in neuroinflammation and microglial activation in Parkinson’s disease. Protein aggregates and PAR2 expression were analyzed using Thioflavin S assay and immunofluorescence in cultured human fibroblasts from Parkinson’s patients, treated or untreated with 1-PPA. A significant decrease in amyloid aggregates was observed after 1-PPA treatment in all patients. A parallel decrease in PAR2 expression, which was higher in sporadic Parkinson’s patients, was also observed both at the transcriptional and protein level. In addition, in mouse LPS-activated microglia, the inflammatory profile was significantly downregulated after 1-PPA treatment, with a remarkable decrease in IL-1β, IL-6, and TNF-α, together with a decreased expression of PAR2. In conclusion, 1-PPA determines the reduction in neuroglia inflammation and amyloid aggregates formation, suggesting that the pharmacological inhibition of PAR2 could be proposed as a novel strategy to control neuroinflammation.
Advanced Kidney Models In Vitro Using the Established Cell Line Renal Proximal Tubular Epithelial/Telomerase Reverse Transcriptase1 for Nephrotoxicity Assays
Authors: Lacueva-Aparicio Alodia , Martínez-Gimeno Laura , Torcal Pilar , Ochoa Ignacio , Giménez Ignacio
Published: July 2024

Nephrotoxicity stands as one of the most limiting effects in the development and validation of new drugs. The kidney, among the organs evaluated in toxicity assessments, has a higher susceptibility, with nephrotoxic potential frequently evading detection until late in clinical trials. Traditional cell culture, which has been widely used for decades, does not recapitulate the structure and complexity of the native tissue, which can affect cell function, and the response to cytotoxins does not resemble what occurs in the kidney. In the current study, we aimed to address these challenges by creating in vitro kidney models that faithfully biomimic the dynamics of the renal proximal tubule, using the well-established RPTEC/TERT1 cell line. For doing so, two models were developed, one recreating tubule-like structures (2.5D model) and the other using microfluidic technology (kidney-on-a-chip). The 2.5D model allowed tubular structures to be generated in the absence of hydrogels, and the kidney-on-a-chip model allowed shear stress to be applied to the cell culture, which is a physiological stimulus in the renal tissue. After characterization of both models, different nephrotoxic compounds such as cisplatin, tacrolimus, and daunorubicin were used to study cell responses after treatment. The developed models in our study could be a valuable tool for pre-clinical nephrotoxic testing of drugs and new compounds.
Allergen Microarrays and New Physical Approaches to More Sensitive and Specific Detection of Allergen-Specific Antibodies
Authors: Sokolov Pavel , Evsegneeva Irina , Karaulov Alexander , Sukhanova Alyona , Nabiev Igor
Published: July 2024

The prevalence of allergic diseases has increased tremendously in recent decades, which can be attributed to growing exposure to environmental triggers, changes in dietary habits, comorbidity, and the increased use of medications. In this context, the multiplexed diagnosis of sensitization to various allergens and the monitoring of the effectiveness of treatments for allergic diseases become particularly urgent issues. The detection of allergen-specific antibodies, in particular, sIgE and sIgG, is a modern alternative to skin tests due to the safety and efficiency of this method. The use of allergen microarrays to detect tens to hundreds of allergen-specific antibodies in less than 0.1 mL of blood serum enables the transition to a deeply personalized approach in the diagnosis of these diseases while reducing the invasiveness and increasing the informativeness of analysis. This review discusses the technological approaches underlying the development of allergen microarrays and other protein microarrays, including the methods of selection of the microarray substrates and matrices for protein molecule immobilization, the obtainment of allergens, and the use of different types of optical labels for increasing the sensitivity and specificity of the detection of allergen-specific antibodies.
Hydroponics with Microalgae and Cyanobacteria: Emerging Trends and Opportunities in Modern Agriculture
Authors: Renganathan Prabhaharan , Puente Edgar Omar Rueda , Sukhanova Natalia V. , Gaysina Lira A.
Published: July 2024

The global population is expected to reach 9.5 billion, which means that crop productivity needs to double to meet the growing population’s food demand. Soil degradation and environmental factors, such as climate events, significantly threaten crop production and global food security. Furthermore, rapid urbanization has led to 55% of the world’s population migrating to cities, and this proportion is expected to increase to 75% by 2050, which presents significant challenges in producing staple foods through conventional hinterland farming. Numerous studies have proposed various sustainable farming techniques to combat the shortage of farmable land and increase food security in urban areas. Soilless farming techniques such as hydroponics have gained worldwide popularity due to their resource efficiency and production of superior-quality fresh products. However, using chemical nutrients in a conventional hydroponic system can have significant environmental impacts, including eutrophication and resource depletion. Incorporating microalgae into hydroponic systems as biostimulants offers a sustainable and ecofriendly approach toward circular bioeconomy strategies. The present review summarizes the plant growth-promoting activity of microalgae as biostimulants and their mechanisms of action. We discuss their effects on plant growth parameters under different applications, emphasizing the significance of integrating microalgae into a closed-loop circular economy model to sustainably meet global food demands.
Evaluating Use of Hydraulic Modified Sulfur Powder in Concrete Pavements: Laboratory Testing and Field Application
Authors: Oh Sangwoo , Choi Seongcheol
Published: July 2024

This study comprehensively evaluates the field applicability of hydraulic modified sulfur (HMS) as a concrete additive. We assessed the microstructural characteristics, mechanical properties, and durability performance of HMS at various replacement ratios in a laboratory setting. In addition, a field study was conducted by removing an existing conventional concrete pavement measuring (6000 × 12,000 × 70 mm, W × L × T) and overlaying it with HMS concrete. The experimental results revealed that HMS enhanced the mechanical and durability performance when used as a cement replacement at rates below 9%. These results satisfied the quality control standards and performance criteria specified in the Korean standard specification for cement-concrete pavements. The comparative analysis revealed that HMS concrete outperformed conventional concrete mixtures by 62.6% in sulfuric acid penetration depth, 14.8% in compressive strength retention after sulfuric acid immersion, and 53.1% in chloride-ion penetration resistance. Furthermore, no anomalies were detected during the 3-month follow-up period.
Building Digital Twins to Overcome Digitalization Barriers for Automating Construction Site Management
Authors: Torres Jorge , San-Mateos Rosa , Lasarte Natalia , Mediavilla Asier , Sagarna Maialen , León Iñigo
Published: July 2024

Construction sites are highly unpredictable environments involving a wide variety of stakeholders with complex information exchanges, which lead to the well-known inefficiencies and unproductivity of the construction sector. The adoption of Building Digital Twins (BDT) in the construction site is a promising solution to this issue, by automating data acquisition and knowledge extraction processes and providing what-if scenario simulation capabilities. Furthermore, the current research sets the principles to define, replicate, and scale-up the architecture of a Building Digital Twin Platform (BDTP), conceived as a scalar ecosystem, which allows to seamlessly manage on-site construction processes, integrating cross-cutting domains for the construction site optimization (Progress monitoring, Quality control, Operational Health and Safety, Equipment control, and Production planning). The starting point of the research is a comprehensive diagnosis of on-site process inefficiencies and the barriers to its digitalization leading to the user requirements, which have been underpinned by questionnaires and interviews addressed within an open innovation user-centered approach around Living Labs. The research has been conceived following the Design Science Research (DSR) methodology and based on the Plan-Do-Check-Act (PDCA) analysis for the continuous improvement of the construction process. By means of the adoption of the standard Business Process Model and Notation (BPMN), based on the BDTP architecture, the research has resulted in BPMN workflows stemmed from the Digital Twin (DT) where the DT itself is an actor in a service-oriented data-exchange workflow. Moreover, the use of a BDTP can pave the way for the transition from user-driven construction management to hybrid management, coexisting with both human and digital actors and merging expert knowledge with artificial intelligence techniques.
Challenge for Chinese BIM Software Extension Comparison with International BIM Development
Authors: Wang Yao , Zhao Bin , Nie Ying , Jiang Li , Zhang Xiaolong
Published: July 2024

This study provides an in-depth analysis of the current status of the promotion and application of BIM software in China, highlighting its differences from the international market. Chinese BIM software shows advantages in data security, cost-effectiveness, user habit adaptability, and localization standards, but faces challenges in terms of technological maturity and ecosystem development. By employing bibliometric methods and utilizing literature resources from CNKI and the Web of Science, the study offers a comprehensive analysis of the market and policy environment and proposes targeted recommendations. The study indicates that Chinese BIM software has significant advantages in enhancing data security and cost-effectiveness but lacks technological maturity and requires improvements in ecosystem development. User habits are crucial for the promotion of BIM software, and the localization and adaptability of the software need further enhancement. To promote the widespread application of BIM in the architecture, engineering, and construction (AEC) industries, a robust market mechanism needs to be established. The government should strengthen policy support and improve regulatory frameworks; software developers should enhance product functionality and work closely with users; and application enterprises should actively provide feedback to promote software improvements. Moreover, the introduction of reasonable capital and the collaboration between educational institutions and enterprises to cultivate professional talent are critical for the promotion and application of BIM technology. The research emphasizes that forming a cross-departmental joint mechanism to promote a virtuous cycle in the AEC market is key to achieving the widespread application of BIM technology. These measures can provide strong market impetus for the development of BIM software, accelerate the maturity and ecosystem construction of Chinese BIM software, and ultimately realize the comprehensive upgrading of informatization and digitization in the construction industry.
Local Deformation Analysis and Optimization of Steel Box Girder during Incremental Launching
Authors: Zhao Lin , Xu Runze , Wang Youzhi , Tian Changjin , Qiu Kai
Published: July 2024

Due to the significant weight of the steel box girder and the substantial gap between temporary piers, the stress concentration and localized deformation of the girder’s bottom plate are pronounced during the incremental launching construction process. In this study, the multi-scale finite element method was employed to simulate the incremental launching process of the steel box girder, analyze the pattern of localized deformation in the bottom plate contact area, and propose corresponding optimization control measures. Additionally, the entire incremental launching process was monitored, and the improvement in localized deformation before and after the optimization of the incremental launching scheme was analyzed. The results illustrate that the original incremental launching scheme led to substantial localized deformation in the bottom plate contact area of the steel box girder. Optimal control measures were implemented for the four incremental launching construction schemes. The optimal scheme significantly mitigated the localized deformation of the steel box girder’s bottom plate, with an average decrease in deformation of 48.32%. These findings can provide robust technical guidance and data support for the control of localized deformation in large-span steel box girders during the incremental launching construction process.
Short-Term Energy Forecasting to Improve the Estimation of Demand Response Baselines in Residential Neighborhoods: Deep Learning vs. Machine Learning
Authors: Gassar Abdo Abdullah Ahmed
Published: July 2024

Promoting flexible energy demand through response programs in residential neighborhoods would play a vital role in addressing the issues associated with increasing the share of distributed solar systems and balancing supply and demand in energy networks. However, accurately identifying baseline-related energy measurements when activating energy demand response events remains challenging. In response, this study presents a deep learning-based, data-driven framework to improve short-term estimates of demand response baselines during the activation of response events. This framework includes bidirectional long-term memory (BiLSTM), long-term memory (LSTM), gated recurrent unit (GRU), convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN). Their performance is evaluated by considering different aggregation levels of the demand response baseline profile for 337 dwellings in the city of La Rochelle, France, over different time horizons, not exceeding 24 h. It is also compared with fifteen traditional statistical and machine learning methods in terms of forecasting accuracy. The results demonstrated that deep learning-based models, compared to others, significantly succeeded in minimizing the gap between the actual and forecasted values of demand response baselines at all different aggregation levels of dwelling units over the considered time-horizons. BiLSTM models, followed by GRU and LSTM, consistently demonstrated the lowest mean absolute percentage error (MAPE) in most comparison experiments, with values up to 9.08%, 8.71%, and 9.42%, respectively. Compared to traditional statistical and machine learning models, extreme gradient boosting (XGBoost) was among the best, with a value up to 11.56% of MAPE, but could not achieve the same level of forecasting accuracy in all comparison experiments. Such high performance reveals the potential of the proposed deep learning approach and highlights its importance for improving short-term estimates of future baselines when implementing demand response programs in residential neighborhood contexts.
Intelligent Prediction and Application Research on Soft Rock Tunnel Deformation Based on the ICPO-LSTM Model
Authors: Zhang Chunpeng , Liu Haiming , Peng Yongmei , Ding Wenyun , Cao Jing
Published: July 2024

In tunnel construction, the prediction of the surrounding rock deformation is related to the construction safety and stability of the tunnel structure. In order to achieve an accurate prediction of the surrounding rock deformation in soft rock tunnel construction, a Long Short-Term Memory (LSTM) neural network is used to construct a prediction model of the vault settlement and the horizontal convergence of the upper conductor in soft rock tunnels. The crested porcupine optimisation (CPO) algorithm is used to realise the hyper-parameter optimisation of the LSTM model and to construct the framework of the calculation process of the CPO-LSTM model. Taking the soft rock section of the Baoshishan Tunnel as an example, the large deformation of the surrounding rock is measured and analysed in situ, and the monitoring data of arch settlement and superconducting level convergence are obtained, which are substituted into the CPO-LSTM model for calculation, and compared and analysed with traditional machine learning and optimisation algorithms. The results show that the CPO-LSTM model has an R2 of 0.9982, a MAPE of 0.8595% and an RMSE of 0.1922, which are the best among all the models. In order to further improve the optimisation capability of the CPO, some improvements were made to the CPO and an Improved Crested Porcupine Optimiser (ICPO) was proposed. The ICPO-LSTM prediction model was established, and the ZK6 + 834 section was selected as a research object for comparison and analysis with the CPO-LSTM model. The results of the error analysis show that the prediction accuracy of the improved ICPO-LSTM model has been further improved, and the prediction accuracy of the model meets the requirements of guiding construction.
FBG Sensing Data Motivated Dynamic Feature Assessment of the Complicated CFRP Antenna Beam under Various Vibration Modes
Authors: Chen Cong , Zhang Chao , Ma Jie , He Shi-Zhong , Chen Jian , Sun Liang , Wang Hua-Ping
Published: July 2024

Carbon fiber-reinforced polymer (CFRP) components were extensively used and current studies mainly refer to CFRP laminates. The dynamic performance of the complicated CFRP antenna beams is yet to be explored. Therefore, a sensor layout based on fiber Bragg gratings (FBGs) in series was designed to measure the dynamic response of the CFRP antenna beam, and various vibration tests (sweep frequency test, simulated long-life vibration test, shock vibration test, functional vibration test, and constant frequency vibration test) were conducted. The time and frequency domain analysis on FBG sensing signals was performed to check the vibration performance and assess the health condition of this novel CFRP structure. The results indicate that strain values reach a maximum of only 300 µε under different test conditions. The antenna beam exhibited clear vibration patterns, with the first four intrinsic frequencies identified at 44, 94.87, 107.1, and 193.45 Hz. It shows that strain distribution and vibration modes of the antenna beam can be characterized from the sensing data, and the dynamic feature can be much more accurately assessed. The FBG sensors attached on the surface of CFRP antenna beam can accurately and stably measure the dynamic response, which validates that the interfaces between optical fiber sensing elements and CFRP material have excellent interfacial bonding characteristics. The novel CFRP antenna beam exhibits the excellent dynamic performance and stability, offering the replacement of traditional steel antenna beams. The study can finally instruct the development of self-sensing CFRP antenna beams assembled with FBGs in series.
Advances in Road Engineering: Innovation in Road Pavements and Materials
Authors: Baliello Andrea , Wang Di
Published: July 2024

The road pavement sector is currently gaining more and more attractivity as a peculiar field of civil engineering [...]
Adding Green to Architectures: Empirical Research Based on Indoor Vertical Greening of the Emotional Promotion on Adolescents
Authors: Wang Chengcheng , Hu Qizhi , Zhou Zijun , Li Di , Wu Linjia
Published: July 2024

Good architectural space design can bring positive emotional stimulation and relaxation to users, but few studies have investigated the quantitative indicators in architectural space design and their impact on user emotions. This study takes the right-angle sandwich interface system in architecture as an example to guide the next vertical greening simulation experiment by comparing the spatial quantitative differences in connection value, integration degree, and population agglomeration. Eighty adolescent volunteers were recruited into a control (artificial decorative wall) and experimental (green wall) group based on wall type. We compared their physiological and psychological indicators, including blood pressure and blood oxygen, and psychological indicators, including POMS and SIAI-S scales. Then, we made predictive factor judgements on vertical green elements. The quantification of the interior space of the building showed consistency in parameter changes, with the central area being the area of connectivity, integration, and crowd aggregation values. After the experiment, the experimental group showed a significant decrease in diastolic blood pressure, systolic blood pressure, and heart rate (p = 0.00) and a significant decrease in tension, anger, fatigue, depression, and panic (p = 0.00). The quantitative relationship between vertical greening elements and emotional promotion using stepwise linear exploration shows that the “vine” element is a significant predictive factor for diastolic blood pressure, T-A emotion, and SIAI-S values. The results enrich the indoor optimization and creation expansion paths of interface systems for various spatial experiences and further provide guidance for urban indoor green construction plans and green landscape facility planning via the emotional influence of indoor vertical space greening on young people.