Search Results (903)

A novel near-infrared (NIR) squaraine-based chemosensor, SQ-68, has been designed and synthesized for the sensitive and selective detection of Cu²⁺ and Ag⁺ ions, offering a compact solution for multi-analyte sensing. SQ-68 demonstrates high selectivity, with its performance influenced by the solvent environment: It selectively detects Cu²⁺ in acetonitrile and Ag⁺ in an ethanol–water mixture. Upon binding with either ion, SQ-68 undergoes significant absorption changes in the NIR region, accompanied by visible color changes, enabling naked-eye detection. Spectroscopic studies confirm a 1:1 binding stoichiometry with both Cu²⁺ and Ag⁺, accompanied by hypochromism. The detection limits are 0.09 μM for Cu²⁺ and 0.38 μM for Ag⁺, supporting highly sensitive quantification. The sensor’s practical applicability was validated in real water samples (sea, lake, and tap water), with recovery rates ranging from 73–95% for Cu²⁺ to 59–99% for Ag⁺. These results establish SQ-68 as a reliable and efficient chemosensor for environmental monitoring and water quality assessment. Its dual-analyte capability, solvent-tunable selectivity, and visual detection features make it a promising tool for rapid and accurate detection of heavy metal ions in diverse aqueous environments. Full article

Parametric changes in the first coordination shell (FCS) of a vitreous metallic Pd_42.5Cu₃₀Ni_7.5P₂₀ alloy are analysed, aiming to confirm the identification of the glass transition temperature (T_g) via processing of XRD patterns utilising radial and pair distribution functions (RDFs and PDFs) and their evolution with temperature. The Wendt–Abraham empirical criterion of glass transition and its modifications are confirmed in line with previous works, which utilised the kink of the temperature dependences of the minima and maxima of both the PDF and the maxima of the structure factor S(q). Massive fluctuations are, however, identified near the T_g of the derivatives of the minima and maxima of the PDF and maxima of S(q), which adds value to understanding the glass transition in the system as a true second-order-like phase transformation in the non-equilibrium system of atoms. Full article

Graphene is considered one of the most promising flexible transparent electrode materials as it has high charge carrier mobility, high electrical conductivity, low optical absorption, excellent mechanical strength, and good bendability. However, graphene-based flexible transparent electrodes face a critical challenge in balancing electrical conductivity and optical transmittance. Here, we present a green and scalable direct ink writing (DIW) strategy to fabricate graphene grid patterns by optimizing ink formulation with sodium dodecyl sulfate (SDS) and ethanol. SDS eliminates the coffee ring effect via Marangoni flow, while ethanol enhances graphene flake alignment during hot-pressing, achieving a high conductivity of 5.22 × 10⁵ S m⁻¹. The grid-patterned graphene-based flexible transparent electrodes exhibit a low sheet resistance of 21.3 Ω/sq with 68.5% transmittance as well as a high stability in high-temperature and corrosive environments, surpassing most metal/graphene composites. This method avoids toxic solvents and high-temperature treatments, demonstrating excellent stability in harsh environments. Full article

Optimising the friction coefficient helps reduce friction losses and improve the efficiency of mechanical systems. The purpose of this study is to experimentally investigate the impact of roughness orientation on the friction coefficient in elastohydrodynamic (EHD) contact. Tests were carried out on a twin-disc machine. Three pairs of discs of identical material (nitrided steel) and geometry were tested: a smooth pair (the root mean square surface roughness Sq = 0.07 µm), a pair with transverse roughness and another with longitudinal roughness. The two rough pairs have similar roughness amplitudes (Sq = 0.5 µm). A comparison of the friction generated by these different pairs was carried out to highlight the effect of the roughness orientation under different operating conditions (oil injection temperature from 60 to 80 °C, Hertzian pressure from 1.2 to 1.5 GPa and mean rolling speed from 5 to 30 m/s). Throughout all the tests conducted in this study, longitudinal roughness resulted in higher friction than transverse, with an increase of up to 30%. Moreover, longitudinal roughness is more sensitive to variations in operating conditions. Finally, in all tests, the asperities of longitudinal roughness were found to influence the friction behaviour, unlike transverse roughness. Full article

The lacustrine to deltaic depositional systems of the Upper Jurassic Qigu Formation in the Yongjin area constitute a significant petroleum reservoir in the central Junggar Basin, China. Based on core observations, petrology analyses, paleoenvironment indicators and modern sedimentary analyses, sequence stratigraphy, lithofacies associations, sedimentary environment, evolution, and models were investigated. The Qigu Formation can be divided into a third-order sequence consisting of a lowstand systems tract (LST) and a transgressive systems tract (TST), which is further subdivided into six fourth-order sequences. Thirteen lithofacies and five lithofacies associations were identified, corresponding to shallow-water delta-front deposits. The paleoenvironment of the Qigu Formation is generally characterized by an arid freshwater environment, with a dysoxic to oxic environment. During the LST depositional period (SQ1–SQ3), the water depth was relatively shallow with abundant sediment supply, resulting in a widespread distribution of channel and mouth bar deposits. During the TST depositional period (SQ4–SQ6), the rapid rise in base level, combined with reduced sediment supply, resulted in swift delta retrogradation and widespread lacustrine sedimentation. Combined with modern sedimentary analysis, the shallow-water delta in the study area primarily comprises a composite system of single main channels and distributary channel-mouth bar complexes. The channel-bar complex eventually forms radially distributed bar assemblages with lateral incision and stacking. The distributary channel could incise a mouth bar deeply or shallowly, typically forming architectural patterns of going over or in the mouth bar. Reservoir test data suggest that the mouth bar sandstones are favorable targets for lithological reservoir exploration in shallow-water deltas. Full article

The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess near real-time flood inundation patterns associated with extreme weather events, including recent cyclones between 2017 to 2024 (namely, Mora, Titli, Fani, Amphan, Yaas, Sitrang, Midhili, and Remal) as well as intense monsoonal rainfall during the same period, across a large spatial scale, to support disaster risk management efforts. Three machine learning algorithms, namely, random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN), were applied to flood extent data derived from SAR imagery to enhance flood detection accuracy. Among these, the SVM algorithm demonstrated the highest classification accuracy (75%) and exhibited superior robustness in delineating flood-affected areas. The analysis reveals that both cyclone intensity and rainfall magnitude significantly influence flood extent, with the western coastal zone (e.g., Morrelganj and Kaliganj) being most consistently affected. The peak inundation extent was observed during the 2023 monsoon (10,333 sq. km), while interannual variability in rainfall intensity directly influenced the spatial extent of flood-affected zones. In parallel, eight major cyclones, including Amphan (2020) and Remal (2024), triggered substantial flooding, with the most severe inundation recorded during Cyclone Remal with an area of 9243 sq. km. Morrelganj and Chakaria were consistently identified as flood hotspots during both monsoonal and cyclonic events. Comparative analysis indicates that cyclones result in larger areas with low-level inundation (19,085 sq. km) compared to monsoons (13,829 sq. km). However, monsoon events result in a larger area impacted by frequent inundation, underscoring the critical role of rainfall intensity. These findings underscore the utility of SAR-ML integration in operational flood monitoring and highlight the urgent need for localized, event-specific flood risk management strategies to enhance flood resilience in the GBM delta. Full article

Owing to the need for continuous improvement in building energy performance standards (BEPSs), facilities must adhere to benchmark performances in their quest to achieve net-zero performance. This research explores machine learning models that leverage historical energy data from a cluster of buildings, along with relevant ambient weather data and building characteristics, with the objective of predicting the buildings’ energy performance through the year 2040. Using the forecasted emission results, the portfolio of buildings is analyzed for the incurred carbon non-compliance fees based on their on-site fossil fuel CO_2e emissions to assess and pinpoint facilities with poor energy performance that need to be prioritized for decarbonization. The forecasts from the machine learning algorithms predicted that the portfolio of buildings would incur an annual average penalty of $31.7 million ($1.09/sq. ft.) and ~$348.7 million ($12.03/sq. ft.) over 11 years. To comply with these regulations, the building portfolio would need to reduce on-site fossil fuel CO_2e emissions by an average of 58,246 metric tons (22.10 kg/sq. ft.) annually, totaling 640,708 metric tons (22.10 kg/sq. ft.) over a period of 11 years. This study demonstrates the potential for robust machine learning models to generate accurate forecasts to evaluate carbon compliance and guide prompt action in decarbonizing the built environment. Full article

Silver nanowire (AgNW)-based transparent conductive films are essential for flexible electronics due to their superior optoelectronic properties and mechanical flexibility. This review examines the characteristics and fabrication methods of AgNW thin films in detail. Among various fabrication techniques, the AgNW thin film produced by silk-screen printing exhibits the highest quality factor of 568.47, achieving 95.3% visible light transmittance of 95.3% and 13.6 Ω/sq sheet resistance. Ensuring the stability of AgNW films requires the deposition of protective layers through physical or chemical approaches. This review also systematically evaluates the different methods for preparing these protective layers, including their respective advantages and limitations. Furthermore, the review proposes strategies to enhance the conductivity, transparency, and flexibility of AgNW films. Finally, it discusses potential future applications and challenges, offering valuable insights for the development of next-generation flexible transparent electrodes. Full article

The flexible transparent conductive films (TCFs) of a ZnS/Cu/Ag/TiO₂ multilayered structure were deposited on a flexible PET substrate with high surface roughness using magnetic sputtering, and the effects of structural characteristics on the performance of the films were analyzed. The TCFs with TiO₂/Cu/Ag/TiO₂ and ZnS/Cu/Ag/ZnS symmetric structures were also prepared for comparison. The TCF samples were deposited using ZnS, TiO₂, Cu and Ag targets, and they were analyzed using scanning electronic microscopy, atomic force microscopy, grazing incidence X-ray diffraction, spectrophotometry and a four-probe tester. The TCFs exhibit generally uniform surface morphology, excellent light transmittance and electrical conductivity with optimized structure. The optimal values are 84.40%, 5.52 Ω/sq and 33.19 × 10⁻³ Ω⁻¹ for the transmittance, sheet resistance and figure of merit, respectively, in the visible spectrum. The satisfactory properties of the asymmetric multilayered TCF deposited on a rough-surface substrate should be mainly attributed to the optimized structure parameters and reasonable interfacial compatibilities. Full article

Phewa Lake, Nepal’s second-largest natural lake, is under increasing ecological stress due to sedimentation, shoreline encroachment, and water quality decline driven by rapid urban growth, fragile mountainous catchments, and changing climate patterns. This study employs an integrated approach combining sediment yield estimation from its catchment using RUSLE, shoreline encroachment analysis via satellite imagery and historical records, and identification of pollution sources and socio-economic factors through field surveys and community consultations. The results show that steep, sparsely vegetated slopes are the primary sediment sources, with Harpan Khola (a tributary of Phewa Lake) contributing over 80% of the estimated 339,118 tons of annual sediment inflow. From 1962 to 2024, the lake has lost approximately 5.62 sq. km of surface area, primarily due to a combination of sediment deposition and human encroachment. Pollution from untreated sewage, urban runoff, and invasive aquatic weeds further degrades water quality and threatens biodiversity. Based on the findings, this study proposes a way forward to mitigate sedimentation, encroachment, and pollution, along with a sustainable revitalization plan. The approach of this study, along with the proposed sustainability measures, can be replicated in other lake systems within Nepal and in similar watersheds elsewhere. Full article

Ultraviolet A (UVA) radiation has been identified as a significant factor contributing to skin photoaging and skin diseases, operating through the excessive generation of reactive oxygen species (ROS) and the subsequent induction of DNA damage. Plant-derived antioxidants have demonstrated efficacy in mitigating UVA-induced damage; nevertheless, their instability limits their therapeutic potential. This study investigates the mechanisms of antioxidant and cytoprotective effects of squalane (Sq), a stable, plant-derived triterpene, in human dermal fibroblasts (HDFs) exposed to UVA radiation. Sq was administered at concentrations ranging from 0.005% to 0.015% prior to UVA exposure (10 J/cm²). It has been found that Sq counteracted UVA-induced ROS formation, decreased the level of reduced thiol groups, activated apoptosis, and inhibited DNA biosynthesis. Immunofluorescence analysis revealed that Sq suppressed the UVA-induced expression of p53, caspase-3, caspase-9, and PARP, while restoring the activity of the pro-survival p-Akt/mTOR pathway. The findings indicate that Sq exerts protective effects on UVA-induced fibroblast damage through a combination of antioxidant and anti-apoptotic mechanisms. Full article

The Lower–Middle Jurassic of the Kuqa Depression consists of terrestrial clastic deposits containing coal seams and thick lacustrine mudstones, and is of great significance for oil and gas exploration. Based on the comprehensive analysis of core, well-logging, outcrop, and seismic data, the sequence stratigraphy, depositional systems, and the controlling factors of the basin filling in the depression are systematically documented. Four primary depositional systems, including braided river delta, meandering river delta, lacustrine, and swamp deposits, are identified within the Ahe, Yangxia, and Kezilenuer Formations of the Lower–Middle Jurassic. The basin fills can be classified into two second-order and nine third-order sequences (SQ1–SQ9) confined by regional or local unconformities and their correlative conformities. This study shows that the sedimentary evolution has undergone the following three stages: Stage I (SQ1–SQ2) primarily developed braided river, braided river delta, and shallow lacustrine deposits; Stage II (SQ3–SQ5) primarily developed meandering river, meandering river delta, and extensive deep and semi-deep lacustrine deposits; Stage III (SQ6–SQ9) primarily developed swamp (SQ6–SQ7), meandering river delta, and shore–shallow lacustrine deposits (SQ8–SQ9). The uplift of the Tianshan Orogenic Belt in the Early Jurassic (Stage I) may have facilitated the development of braided fluvial–deltaic deposits. The subsequential expansion of the sedimentary area and the weakened sediment supply can be attributed to the planation of the source area and widespread basin subsidence, with the transition of the depositional environments from braided river delta deposits to meandering river delta and swamp deposits. The regional expansion or rise of the lake during Stage II was likely triggered by the hot and humid climate conditions, possibly associated with the Early Jurassic Toarcian Oceanic Anoxic Event. The thick swamp deposits formed during Stage III may be controlled by the interplay of rational accommodation, warm and humid climatic conditions, and limited sediment supply. Milankovitch cycles identified in Stage III further reveal that coal accumulation was primarily modulated by long-period eccentricity forcing. Full article

Background and Objective: Bladder cancer (BC) is the ninth most common malignancy worldwide. Squamous cell carcinoma (SqCC), a rare histological variant, accounts for approximately 2–5% of all BC cases. Compared to urothelial carcinoma, the predominant subtype, research on SqCC remains limited and shows inconsistent findings regarding prognosis. This study aimed to compare survival outcomes between patients with SqCC and those with pure urothelial carcinoma (PUC). Methods: This retrospective, observational study analyzed pathology reports from 2549 transurethral resections of bladder tumors and 632 cystectomies performed at our institution between 1 December 2010 and 31 December 2023. Following pathological re-evaluation, 33 patients with SqCC and 132 with PUC were identified. After 1:3 propensity score matching, 20 patients with SqCC and 58 with PUC were included in the final analysis. Demographic, clinicopathological features, and survival outcomes were compared between groups. Results: The median follow-up was 2.31 years (range: 0.17–13.50). No significant differences in baseline demographic or clinical characteristics were observed, except for the type of surgery. Kaplan–Meier analysis demonstrated no significant differences in disease-free survival (DFS; p = 0.961) or overall survival (OS; p = 0.847) between SqCC and PUC groups. Multivariate Cox regression analysis identified T stage, nodal involvement, and adjuvant chemotherapy (CT) as independent predictors of DFS, while sex and metastasis at diagnosis were significant predictors of OS. Conclusion: Survival outcomes (DFS and OS) did not significantly differ between patients with SqCC and patients with PUC. Prognosis was more closely associated with disease stage at diagnosis, sex, and adjuvant CT. Further large-scale studies are warranted. Full article

The present study analyzes the global ionospheric response to the intense geomagnetic storm of 10–11 October 2024 (SYM—H minimum of −346 nT), using observations from COSMIC—2 and Swarm satellites, GNSS TEC, and Digisondes. Significant uplift of the F-region was observed across both Hemispheres on the dayside, primarily driven by equatorward thermospheric winds and prompt penetration electric fields (PPEFs). However, this uplift did not correspond with increases in foF2 due to enhanced molecular nitrogen-promoting recombination in sunlit regions and the F2 peak rising beyond the COSMIC—2 detection range. In contrast, in the Southern Hemisphere nightside ionosphere exhibited pronounced Ne depletion and low hmF2 values, attributed to G-conditions and thermospheric composition changes caused by storm-time circulation. Strong vertical plasma drifts exceeding 100 m/s were observed during both the main and recovery phases, particularly over Ascension Island, driven initially by southward IMF—Bz-induced PPEFs and later by disturbance dynamo electric fields (DDEFs) as IMF—Bz turned northward. Swarm data revealed a poleward expansion of the Equatorial Ionization Anomaly (EIA), with more pronounced effects in the Southern Hemisphere due to seasonal and longitudinal variations in ionospheric conductivity. Additionally, the storm excited Large-Scale Travelling Ionospheric Disturbances (LSTIDs), triggered by thermospheric perturbations and electrodynamic drivers, including PPEFs and DDEFs. These disturbances, along with enhanced westward thermospheric wind and altered zonal electric fields, modulated ionospheric irregularity intensity and distribution. The emergence of anti-Sq current systems further disrupted quiet-time electrodynamics, promoting global LSTID activity. Furthermore, storm-induced equatorial plasma bubbles (EPBs) were observed over Southeast Asia, initiated by enhanced PPEFs during the main phase and suppressed during recovery, consistent with super EPB development mechanisms. Full article

One of the important parameters of the sheet metal forming process is the coefficient of friction (CoF). Therefore, monitoring the friction coefficient value is essential to ensure product quality, increase productivity, reduce environmental impact, and avoid product defects. Conventional CoF monitoring techniques pose a number of problems, including the difficulty in identifying the features of force signals that are sensitive to the variation in the coefficient of friction. To overcome these difficulties, this paper proposes a new approach to apply unsupervised artificial intelligence techniques with unbalanced data to classify the CoF of DP780 (HCT780X acc. to EN 10346:2015 standard) steel sheets in strip-drawing tests. During sheet metal forming (SMF), the CoF changes owing to the evolution of the contact conditions at the tool–sheet metal interface. The surface topography, the contact loads, and the material behaviour affect the phenomena in the contact zone. Therefore, classification is required to identify possible disturbances in the friction process causing the change in the CoF, based on the analysis of the friction process parameters and the change in the sheet metal’s surface roughness. The Kohonen self-organising map (SOM) was created based on the surface topography parameters collected and used for CoF classification. The CoF determinations were performed in the strip-drawing test under different lubrication conditions, contact pressures, and sliding speeds. The results showed that it is possible to classify the CoF using an SOM for unbalanced data, using only the surface roughness parameter Sq and selected friction test parameters, with a classification accuracy of up to 98%. Full article