Mechanical alterations in shale formations due to exposure to water-based fracturing fluids and supercritical carbon dioxide (ScCO2) significantly affect the performance of shale gas exploration and CO2 geo-sequestration. In this study, a hydrothermal (HT) reaction system was set up to treat Longmaxi shale samples of varying mineralogies (carbonate-, clay-, and quartz-rich) with different fluids, i.e. deionized (DI) water, 2% potassium chloride (KCl) solution, and ScCO2 under HT conditions expected in shale formation. Statistical micro-indentation was conducted to characterize the mechanical property alterations caused by the shale-fluid interactions. An in situ morphological and mineralogical identification technique that combines scanning electron microscopy (SEM) and backscattered electron (BSE) imaging with energy-dispersive X-ray spectroscopy (EDS) was used to analyze the microstructural and mineralogical changes of the treated shale samples. Results show no apparent changes in the Young's modulus, E, and hardness, H, after treatment with DI water under room temperature (20 degrees C) and atmospheric pressure for 7 d. In contrast, E and H were decreased by 31.2% and 37.5% at elevated temperature (80 degrees C) and pressure (8 MPa), respectively. The addition of 2% KCl into DI water mitigated degradation of the mechanical properties. Quartz-rich shale specimens are the least sensitive to the water-based fracturing fluids, followed by the clay-rich and carbonate-rich shale formations. Based on in situ morphological and mineralogical identification, the primary factors for the mechanical degradation induced by water-based fluids include carbonate dissolution, clay swelling, and pyrite oxidation. Slight increases in the measured E and H and compression of porous clay aggregates were observed after treatment with ScCO2. The major factor contributing to the mechanical changes resulting from the exposure to scCO2 appears to be the competition between swelling caused by adsorption and compression of shale matrix. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

Accurate structural health monitoring (SHM) is crucial for ensuring safety and preventing catastrophic failures. However, conventional parameter identification methods often assume a fixed-base foundation, neglecting the significant influence of soil-structure interaction (SSI) on the dynamic response, leading to inaccurate damage assessments, especially under seismic loading. Therefore, we introduce a novel approach that explicitly incorporates SSI effects into parameter identification for frame structures, utilizing an optimized variational mode decomposition (VMD) technique. The core innovation is the application of the Subtraction Average-Based Optimizer (SABO) algorithm, coupled with permutation entropy as the fitness function, to optimize the critical VMD parameters. This SABO-VMD method was rigorously validated through a shaking table test on a 12-story frame structure on soft soil. Comparative analysis with EMD and conventional VMD demonstrated that SABO-VMD provides a superior time-frequency representation of the structural response, capturing non-stationary characteristics more effectively. A novel energy entropy index, derived from the SABO-VMD output with SSI, was developed for quantitative damage assessment. It revealed 8.1% lower degree of structural damage compared to the fixed-base assumption. The proposed SABO-VMD-based approach, by explicitly accounting for SSI, offers a substantial advancement in SHM of frame structures, leading to more reliable safety evaluations and improved seismic resilience.

The importance of green areas in today's modern city concept is increasing day by day. In this understanding, the use of turfgrass [e.g. Bentgrass (Agrostis spp. L.); Kentucky Bluegrass (Poa pratensis L.); Common Bermudagrass Cynodon dactylon (L.) Pers. (Poales: Poaceae)] in sports fields is getting important. Golf courses mainly occurs turfgrass and not much nematological studies has been done in courses of T & uuml;rkiye. In this study, total of 51 soil and 3 water samples were taken from golf courses in Antalya, T & uuml;rkiye's largest golf tourism destination, in 2021. Within the scope of this study, plant parasitic nematode (PPN) species belonging to the genera Aphelenchoides Fischer, 1894 (Tylenchida: Aphelenchoididae), Aphelenchus Bastian, 1865 (Tylenchida: Aphelenchoididae), Criconemella (De Grisse & Loof, 1965) (Tylenchida: Criconematidae), Ditylenchus Filipjev, 1936 (Tylenchida: Anguinidae), Helicotylenchus Steiner, 1945 (Tylenchida: Hoplolaimidae), Hemicriconemoides Chitwood & Birchfield, 1957 (Tylenchida: Criconematidae), Hemicycliophora de Man, 1921 (Tylenchida: Hemicycliophoridae), Hoplolaimus von Daday, 1905 (Tylenchida: Hoplolaimidae), Longidorus Micoletzky, 1922 (Dorylaimida: Longidoridae), Paratrichodorus Siddiqi, 1974 (Triplonchida: Trichodoridae) and Tylenchus Bastian, 1865 (Tylenchida: Tylenchidae) were identified using morphological and morphometric methods. The most detected species in the samples was Hemicycliophora punensis Darekar & Khan, 1980 (Rhabditida: Hemicycliophoridae) (22.22%), while the least detected PPN species was Helicotylenchus dihystera (Cobb, 1893) Sher, 1961 (Tylenchida: Hoplolaimidae) (3.70%). In this study, it is important there are virus vector species among the identified plant parasitic nematode genera. These nematode species can play an active role in the spread of various viral diseases in turfgrass areas. In turfgrass areas where very sensitive cultivation is carried out, such as golf courses, PPN's cause direct damages by feeding, which serve as the source of entry of pathogens into the plants. This situation increases the prevalence and severity of the disease in infected fields. Therefore, early detection of the presence of PPN's in cultivation areas is important to determine effective control strategies.

The most damaging disease of oil palm is Fusarium wilt caused by a soilborne fungal pathogen, Fusarium oxysporum f. sp. elaeidis (Foe). The disease is endemic to Africa and affects oil palm production there. Limited Fusarium wilt outbreaks have occurred in South America, but the disease has not yet been reported in South-East Asia. An earlier review of Foe in 2006 provided updates on symptoms, spread and the difficulty in managing the disease. This paper updates our knowledge of oil palm, socio-economic and environmental impacts of cultivation, Fusarium wilt disease epidemiology, Foe detection techniques, disease management strategies and biosecurity perspectives. Breeding for tolerant plant materials has significantly advanced in Africa, but financial constraints in several countries have limited the production of tolerant oil palm seed materials. Other emerging technologies for Foe control are also presented here, acknowledging the specific challenges to help inform the oil palm industry. We highlight the need to strengthen biosecurity plans in disease-free regions. In these countries/regions that are currently free from the pathogen but cultivating susceptible plant materials, biosecurity protocols are essential to reduce threat of disease introduction and spread. Climatic change is another challenge for oil palm-producing countries, both those currently free from the disease and those where Foe is endemic, and should be taken into consideration when planning and implementing biosecurity measures.

Vessel collisions on bridge piers have become a potential threat to the safety of bridges crossing navigation waterways. Such collision will cause inevitable damage on bridge piers and hence reduce the performance of the whole structure. It is therefore critical to identify the condition of abridge pier after a vessel collision event to judge whether it can still be used or certain rehabilitation is required to recover its normal operation. This paper develops an intelligent approach based on machine learning algorithms to identify the evolution process of damage on abridge pier during collision using sensor-measured acceleration time-history data considering the effects of multi-hazards. A barge vessel is employed and atypical reinforced concrete (RC) bridge pier is considered in this study. A coupled vessel-pier collision model (CVCM) considering soil-pile interactions and material non-linearity of RC components is developed and employed to generate pseudo-experimental data to assess the accuracy of the proposed damage identification strategy. The results demonstrate the potential of the proposed strategy for intelligent damage identification of waterway-crossing bridge piers after vessel collision.

Bio-cement is a green and energy-saving building material, which has received wide attention in the field of ecological environment and geotechnical engineering in recent years. The aim of this study is to investigate the improvement effect of plant-based bio-cement (PBBC) in synergistic treatment of sand with organic materials, to highlight the effective use of tap water in PBBC, and to analyze the crack evolution pattern during the damage of specimens by using image processing techniques. The results showed that tap water can be used as a solvent for PBBC instead of deionized water. The characteristic trend of urease solutions prepared at different temperature environments was obvious, and the activity value of urease solution with low concentration is positively correlated with the ambient temperature, although the activity value is not high, it is not easy to inactivate. The incorporation of organic materials increased the peak stress up to 1809.30 kPa compared to the specimens modified only by PBBC. The damage of the specimens under uniaxial compression consisted of four stages: compaction, elastic deformation, pre-peak brittle damage and post-peak macroscopic damage. The corresponding crack evolution is the interpenetration of small-sized cracks into large-sized main cracks. The large-sized main cracks transform into penetration cracks before damage, and the small-sized cracks are distributed around the penetration cracks. The crack evolution parameters obtained by MATLAB processing are positively correlated with the strain.

Amylase has numerous applications in the processing food sector, including brewing, animal feed, baking, fruit juice manufacturing, starch syrups, and starch liquefaction. Practical applications have been the primary focus of recent research on novel properties of bacterial alpha-amylases. Many amylolytic-active bacterial isolates were obtained from samples of organic-rich, salinity-rich soil. Morphological and 16S rRNA gene sequence studies clearly revealed that the organism belongs to Bacillus sp. and was named Bacillus cereus strain GL2 (PP463909.1 (When pH 6.0, 45 degrees C, and 12 hours of incubation were met the optimal growth conditions for the strain produced the highest amount of alpha-amylase activity. B. cereus strain GL2 alpha-amylase isoenzyme was purified to homogeneity using Sephacryl (TM) S-200 chromatography and ammonium sulfate precipitation. The electrophoretic molecular weight of B. cereus alpha-amylase was 58 kDa. The optimal pH and temperature for measuring alpha-amylase activity were 50 degrees C and 6.0, respectively. alpha-Amylase did not change at 50 degrees C. The purified enzyme improves bread texture by reducing stiffness while improving cohesiveness and flexibility. Purified alpha-amylase was added to the flour, which improved the rheological properties and overall bread quality. As a result, the alpha-amylase from B. cereus strain GL2 can be used to promote bread-making.

Fractional calculus is a powerful mathematical tool for solving mechanical modeling problems. It is used to simulate soils between ideal solids and fluids. Using Riemann-Liouville's fractional calculus operator and theory, fractional order viscous element, nonlinear viscous element and viscoplastic body are connected in series to establish a fractional nonlinear creep damage model, which is used to simulate the nonlinear gradient process of rock creep under different water content conditions. The constitutive equation of the model is constructed. The parameters of creep damage model are identified based on the principle of least squares. The results show that the correlation between theoretical model and experimental data is more than 0.98, which can simulate the creep characteristics of rock well. The effect of model parameters on deformation is further explored, so that the effectiveness of model parameters can be analyzed and verified, and the applicability of the model in other complex stress environments is increased. The research results can provide theoretical basis for stability analysis and disaster prevention of soft rock slopes.

Identification, incidence, and management of the chafer beetle, Protaetia terrosa, on cluster beans was carried out in semi-arid Indian conditions. The P. terrosa was identified using morphological and molecular characters. The distinguishing morphometric characteristics of P. terrosa were viz., head (length: 2.21 mm; width: 2.94 mm), thorax (length: 4.95 mm; width: 6.87 mm), elytra (length: 10.08 mm; width: 8.68 mm), and other morphological features. For molecular identification, a gene fragment of 655 bp size encoding mitochondrial cytochrome c oxidase I enzyme was amplified, sequenced and submitted to NCBI (MW008478), and the barcode was generated as BIN Number BOLD: AEF1461. This is the first report of the partial mt Co1 gene sequence of P. terrosa, with a unique barcode as diagnostic tool. The BLAST P and phylogenetic analysis revealed highest sequence similarity of P. terrosa with P. cuprea, and P. fusca. The P. terrosa infestation results in wilting, drying and ultimately dying of cluster bean plants. The chafer beetle infested plants have a visible white portion (pith) of the stem with little or devoid of lateral roots. The study recorded up to 14.23% infestation by chafer beetles under natural unprotected conditions. The soil drenching with clothianidin 50% WDG @ 250 gm/ha resulted significant reduction in damage by P. terrosa, and could prevent up to 19.36% loss in yield. In nutshell, regular crop monitoring and adoption of suitable management practices are highly important to keep this pest under check.

Root-lesion nematodes (Pratylenchus spp.) are significant plant parasites, causing substantial crop damage worldwide. This study aimed to characterize Pratylenchus spp. in New Zealand maize fields using molecular techniques and map their prevalence. Soil sampling from 24 maize fields across the North and South Islands provided 381 composite samples. Root-lesion nematodes were extracted using the sieving-centrifugal-sugar flotation method and differentiated into five morphospecies. Molecular characterization involved direct partial sequencing of the D2/D3 28S rDNA, ITS rDNA, and COX1 mtDNA regions using Sanger technology from a single nematode. Five Pratylenchus species were identified: P. neglectus, P. crenatus, P. thornei, P. penetrans, and P. pratensis, confirmed by phylogenetic analysis. Prevalence mapping showed P. neglectus and P. crenatus in all sampled fields, while P. thornei, P. penetrans, and P. pratensis were more localized. This study is the first to report these Pratylenchus species on maize in New Zealand and provides the first partial sequences of the D2/D3, COX1, and ITS regions for these species on maize in New Zealand. The findings highlight the diversity of Pratylenchus populations in New Zealand maize fields and emphasize the need for region-specific management strategies to mitigate crop damage.