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This study examines the impacts of economic growth, energy consumption, tourism, and natural resources on the ecological footprint in the ASEAN countries for spanning from 1995 to 2016. For this purpose, the cross-sectional dependent test, the second-generation unit root test, and the Westerlund cointegration test have been applied. The Driscoll-Kraay panel regression model has been used to check the long-run relationship among the series. Also, the Dumitrescu-Hurlin panel causality test is used to determine the paths of causal interactions. These tests help to overcome the problem of cross-sectional dependence in panel data analysis. The results showed an inverted U-shaped EKC behavior in ASEAN countries, hence a negative relation between tourism and natural resources with the ecological footprint. This implies that tourism and natural resources help to improve the environmental quality in ASEAN countries.

Phenol-formaldehyde resin has a wide range of moldings. The phenolic resin retains properties at the freezing point; hence, it is difficult to determine its age. However, it has immense consumption in manufacturing electrical equipment due to its insulating property. There are many types of topological indices such as degree-based topological indices, distance-based topological indices, etc. Topological indices correlate some physiochemical properties of chemical compounds. In this article, the degree-based topological indices of phenol-formaldehyde resin have been determined. Furthermore, the Revan index, hyper Revan index, modified Revan index, sum connectivity Revan index, harmonic Revan index, and inverse Revan index have been calculated.

Bacillus spp. produce a broad spectrum of lipopeptide biosurfactants, among which surfactin, iturin and fengycin are widely studied families. The goals of this study were to characterize the biosurfactant activity of Bacillus spp. and to investigate their motility and biofilm formation capabilities. In addition, we extracted lipopeptides from these bacteria to assess their antifungal activities and analyzed these products by mass spectrometry (MS). B. amyloliquefaciens FZB42, Bacillus sp. NH 217 and B. subtilis NH-100 exhibited excellent biosurfactant and surface spreading activities, whereas B. atrophaeus 176s and Paenibacillus polymyxa C1225 showed moderate activity, and B. subtilis 168 showed no activity. Strains FZB42, NH-100, NH-217, 176s and CC125 exhibited excellent biofilm formation capabilities. Lipopeptide extracts displayed good antifungal activity against various phytopathogens and their associated diseases, such as Fusarium moniliforme (rice bakanae disease), Fusarium oxysporum (root rot), Fusarium solani (root rot) and Trichoderma atroviride (ear rot and root rot). Lipopeptide extracts of these strains also showed hemolytic activity, demonstrating their strong potential to produce surfactants. LCMS-ESI analyses identified the presence of surfactin, iturin and fengycin in the extracts of Bacillus strains. Thus, the strains assayed in this study show potential as biocontrol agents against various Fusarium and Trichoderma species.

This review article attempts to provide a comprehensive review of the recent progress in cerium oxide (CeO2)-based resistive random-access memories (RRAMs). CeO2 is considered the most promising candidate because of its multiple oxidation states (Ce3+ and Ce4+), remarkable resistive-switching (RS) uniformity in DC mode, gradual resistance transition, cycling endurance, long data-retention period, and utilization of the RS mechanism as a dielectric layer, thereby exhibiting potential for neuromorphic computing. In this context, a detailed study of the filamentary mechanisms and their types is required. Accordingly, extensive studies on unipolar, bipolar, and threshold memristive behaviors are reviewed in this work. Furthermore, electrode-based (both symmetric and asymmetric) engineering is focused for the memristor’s structures such as single-layer, bilayer (as an oxygen barrier layer), and doped switching-layer-based memristors have been proved to be unique CeO2-based synaptic devices. Hence, neuromorphic applications comprising spike-based learning processes, potentiation and depression characteristics, potentiation motion and synaptic weight decay process, short-term plasticity, and long-term plasticity are intensively studied. More recently, because learning based on Pavlov’s dog experiment has been adopted as an advanced synoptic study, it is one of the primary topics of this review. Finally, CeO2-based memristors are considered promising compared to previously reported memristors for advanced synaptic study in the future, particularly by utilizing high-dielectric-constant oxide memristors.

[This corrects the article DOI: 10.1371/journal.pone.0198107.].

Perovskite materials have received a lot of attention due to their distinctive structural, electronic, and optical characteristics, particularly in photocatalytic water splitting applications. This work aims to explore structural, electronic, optical, elastic, and mechanical properties of cubic-phase A 2 LiBiI 6 (A = Na, K, Rb) double perovskites using DFT within the GGA-PBE framework. All compounds exhibit negative formation energies (−1.45, −1.14, and −1.07 eV) along with the tolerance factors ranging from 0.820 to 0.896, which fall within the perovskite stability domain. In the phonon dispersion analysis of all compounds, no imaginary frequencies appeared, confirming their dynamic stability. The materials possess a bandgap 1.891–2.014 eV (GGA-PBE) and 1.896–2.038 eV (YS-PBE0), appropriate for visible light absorption, with band gap energies increasing systematically with A-site ionic radius (Na < K < Rb). Dielectric function analysis reveals stable dispersion across the visible spectrum, with static dielectric constants ranging from 3.9 to 4.7, indicating a high degree of polarizability. Mechanical assessments, including positive shear modulus (G) values and Pugh’s ratio (B/G > 1.75), confirm their ductile and stable nature. This work lays the groundwork for designing cost-effective photocatalytic materials for hydrogen evolution reaction (HER).

Purpose: This study assesses the concentrations of iron (Fe), fluoride (Fl), zinc (Zn), and copper (Cu) in water and sediment from three sites along the Kabul River: Attock, Nowshera, and Warsak Dam. Methods: Water and sediment samples were collected over four months (April-July 2024) and Spectrophotometry (AAS) for trace metals and lon-Selective Electrode (ISE) for fluoride. Results: Results show that Fe concentrations in water exceed WHO limits at all sites, with Nowshera having the highest Fe levels (125.28 mg/L), followed by Attock (100.58 mg/L) and Warsak Dam (90.64 mg/L). In sediment, Warsak Dam exhibits the highest Fe accumulation (192.18 mg/kg). Fl in water remains within safe limits, but sediment at Warsak Dam records the highest Fl levels (4.415 mg/kg). Zn concentrations in water remain below WHO thresholds, while sediment Zn accumulation is highest at Warsak Dam (6.891 mg/kg). Cu contamination is a major concern, with Warsak Dam's water showing the highest Cu level (3.06 mg/L), surpassing the WHO limit of 1.3 mg/L. In sediment, Cu exceeds the USEPA safe limit (0.2 mg/ks) at all sites, peaking in Nowshera (1.965 mg/kg). Conclusions: These findings indicate significant Fe and Cu contamination in Nowshera and Warsak Dam, necessitating urgent water quality management

Background. Solar ultraviolet radiation A (UVA, 320-400 nm) is a significant risk factor leading to various human skin conditions such as premature aging or photoaging. This condition is enhanced by UVA-mediated iron release from cellular iron proteins affecting huge populations across the globe. Purpose. Quercetin-loaded zinc oxide nanoparticles (quercetin@ZnO NPs) were prepared to examine its cellular iron sequestration ability to prevent the production of reactive oxygen species (ROS) and inflammatory responses in HaCaT cells. Methods. Quercetin@ZnO NPs were synthesized through a homogenous precipitation method, and the functional groups were characterized by Fourier transform infrared (FTIR) spectroscopy, whereas scanning electron microscopy (SEM) described the morphologies of NPs. MTT and qRT-PCR assays were used to examine cell viability and the expression levels of various inflammatory cytokines. The cyclic voltammetry (CV) was employed to evaluate the redox potential of quercetin-Fe3+/quercetin-Fe2+ complexes. Results. The material characterization results supported the loading of quercetin molecules on ZnO NPs. The CV and redox potential assays gave Fe-binding capability of quercetin at 0.15 mM and 0.3 mM of Fe(NO3)3. Cytotoxicity assays using quercetin@ZnO NPs with human HaCaT cells showed no cytotoxic effects and help regain cell viability loss following UVA (150 kJ/m2). Conclusion. Quercetin@ZnO NPs showed that efficient quercetin release action is UV-controlled, and the released quercetin molecules have excellent antioxidant, anti-inflammatory, and iron sequestration potential. Quercetin@ZnO NPs have superior biocompatibility to provide UVA protection and medication at once for antiphotoaging therapeutics.

PurposeTechnology has emerged as a leading tool to address concerns regarding climate change in the recent era. As a result, the green mobile application – Ant Forest – was developed, and it has considerable potential to reduce negative environmental impacts by encouraging its users to become involved in eco-friendly activities. Ant Forest is a novel unexplored green mobile gaming phenomenon. To address this gap, this study explores the influence of user experience (cognitive experience and affective experience), personal attributes (affection and altruism) and motivational factors in game play (reward for activities and self-promotion) on the continuation intention toward Ant Forest.Design/methodology/approachThe authors assessed the data using partial least squares structural equation modeling (PLS-SEM) for understanding users' continuation intention toward Ant Forest.FindingsThrough a survey of 337 Ant Forest users, the results reveal that cognitive and affective experiences substantially affect Ant Forest continuation intention. Personal attributes and motivational factors also stimulate users to continue using Ant Forest.Originality/valueThe authors build and confirm a conceptual framework to understand users' continuation intention toward a novel unexplored Ant Forest phenomenon.

In deep learning, the choice of activation function plays a vital role in enhancing model performance. We propose AHerfReLU, a novel activation function that combines the rectified linear unit (ReLU) function with the error function (erf), complemented by a regularization term 1/1+x2, ensuring smooth gradients even for negative inputs. The function is zero centered, bounded below, and nonmonotonic, offering significant advantages over traditional activation functions like ReLU. We compare AHerfReLU with 10 adaptive activation functions and state-of-the-art activation functions, including ReLU, Swish, and Mish. Experimental results show that replacing ReLU with AHerfReLU leads to 3.18% improvement in Top-1 accuracy on the LeNet network for the CIFAR100 dataset, 0.63% improvement on CIFAR10%, and 1.3% improvement in mean average precision (mAP) on the SSD300 model in the Pascal VOC dataset. Our results demonstrate that AHerfReLU enhances model performance, offering improved accuracy, loss reduction, and convergence stability. The function outperforms existing activation functions, providing a promising alternative for deep learning tasks.