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Understanding consistent inter-individual variability in animal behaviour, known as personality traits, is essential for exploring the mechanisms and evolutionary consequences of behavioural diversity. Aggressive behaviour influences survival, resource acquisition, and reproduction, so clarifying individual differences can enhance our understanding of ecological dynamics and improve experimental design accuracy in behavioural studies. In this study, ornamental male Betta splendens, a model organism for aggression research, were analysed for intra- and inter-individual variability in aggressive responses to their mirror image-a standard method for assessing aggression in fish-once per week, and their consistency was evaluated over three consecutive weeks There were significant differences in aggressive behaviour across individuals, with coefficients of variation ranging from 29 to 60%. While most fish exhibited the full suite of aggressive displays, some showed no aggressive behaviour, while others only displayed threat behaviours but did not advance to the attacks. The consistency of individual threat and attack behaviours varied, but repeatability was high overall (intra-class correlation coefficients >= 0.5), indicating that individual fish have different levels of aggression. There was habituation to the mirror assay, with aggression decreasing significantly by the second week, though the degree of habituation, a form of learning, varied among individuals in some behaviours. Air-breathing frequency correlated positively with aggression behaviours and can be considered an indicator to infer aggression level in this species. These results indicate that inter-individual variation in aggressive behaviour and habituation to repeated testing using the mirror assay should be considered in aggression studies using B. splendens and potentially in other species.

<jats:p>To better inform the public about ambient air quality and associated health risks and prevent cardiovascular and chronic respiratory diseases in Macau, the local government authorities apply the Air Quality Index (AQI) for air quality management within its jurisdiction. The application of AQI requires first determining the sub-indices for several pollutants, including respirable suspended particulates (PM10), fine suspended particulates (PM2.5), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO). Accurate prediction of AQI is crucial in providing early warnings to the public before pollution episodes occur. To improve AQI prediction accuracy, deep learning methods such as artificial neural networks (ANNs) and long short-term memory (LSTM) models were applied to forecast the six pollutants commonly found in the AQI. The data for this study was accessed from the Macau High-Density Residential Air Quality Monitoring Station (AQMS), which is located in an area with high traffic and high population density near a 24 h land border-crossing facility connecting Zhuhai and Macau. The novelty of this work lies in its potential to enhance operational AQI forecasting for Macau. The ANN and LSTM models were run five times, with average pollutant forecasts obtained for each model. Results demonstrated that both models accurately predicted pollutant concentrations of the upcoming 24 h, with PM10 and CO showing the highest predictive accuracy, reflected in high Pearson Correlation Coefficient (PCC) between 0.84 and 0.87 and Kendall’s Tau Coefficient (KTC) between 0.66 and 0.70 values and low Mean Bias (MB) between 0.06 and 0.10, Mean Fractional Bias (MFB) between 0.09 and 0.11, Root Mean Square Error (RMSE) between 0.14 and 0.21, and Mean Absolute Error (MAE) between 0.11 and 0.17. Overall, the LSTM model consistently delivered the highest PCC (0.87) and KTC (0.70) values and the lowest MB (0.06), MFB (0.09), RMSE (0.14), and MAE (0.11) across all six pollutants, with the lowest SD (0.01), indicating greater precision and reliability. As a result, the study concludes that the LSTM model outperforms the ANN model in forecasting air pollutants in Macau, offering a more accurate and consistent prediction tool for local air quality management.</jats:p>

Aggressive behavior is an adaptive trait present across all taxa. However, the neuroendocrine mechanisms regulating it, particularly in fish, are not well understood. Oxytocin (OXT) and arginine vasotocin (VT) are known modulators of aggression, but their actions remain controversial. This study tested the possible modulation of endocrine and behavioral responses to an aggression challenge by these nonapeptides in Siamese fighting fish, Betta splendens, a species known for its intrinsic aggressiveness. Male B. splendens were injected with different dosages of either Manning compound or L-368,899, VT and OXT receptor antagonists respectively, and were exposed to a mirror challenge for 30 min. While all fish displayed high levels of aggression toward their mirror image, no differences were observed between control-injected and treatment fish. However, blocking VT inhibited the post-fight increase in plasma levels of the androgen 11-ketotestosterone (KT). To further investigate this result, testis tissue from males was incubated with and without VT and Manning compound, and KT levels were measured after 180 min. Results showed a direct effect of VT on in vitro KT secretion, indicating the presence of VT receptors in the testes of this species. Overall, the study does not support a modulatory role of VT or OXT in aggressive behavior, although VT might be implicated in the regulation of peripheral androgen response to aggression in B. splendens.

<jats:title>ABSTRACT</jats:title><jats:p>As intensive aquaculture continues to develop, substantial investments have been made in equipment to sustain high‐density farming. However, this has resulted in elevated noise levels within these aquaculture environments, particularly below 2000 Hz, matching the hearing range of most cultured fish species. Fish under noise conditions may experience hearing loss and physiological stress, which can negatively affect their growth, foraging efficiency, reproductive success, and increase their susceptibility to diseases. These adverse effects compromise the welfare of cultured fish, potentially decreasing production quality and increasing mortality rates. Despite these notable effects, the understanding and management of noise conditions in aquaculture systems lag behind other environmental parameters in terms of recognition and control. In this review, we cover the fundamentals of fish auditory systems, the hearing range of key cultured fish species, and the most common noise sources and levels prevalent in current intensive aquaculture systems. Additionally, we examine recent discoveries on the effects of anthropogenic noise on fish hearing, physiological responses, and behavior. Finally, we provide strategies for noise monitoring and management in the aquaculture industry, while also highlighting open questions for future research. Our goal is to assist researchers and practitioners in comprehending underwater noise and its effects on cultured fish species, providing a valuable resource for promoting the healthy and sustainable development of intensive aquaculture.</jats:p>

<jats:p>PM10 emissions have been a significant concern in rock crushing and quarry operations (study site #1) and iron ore mining projects (study site #2) in certain regions of Malaysia, posing fears to the health and well-being of nearby communities with severe air pollution. To address this issue, it is crucial to develop effective mitigation strategies to reduce dust particle emissions like PM10 in the ambient air. The AERMOD model was applied to predict PM10 emissions during quarry operations and iron ore mining projects, both with and without control measures. The results indicated that PM10 emissions were reduced when control measures were implemented. The modeling result shows the mean PM10 concentration with and without control measures in study site #1 is 74.85 µg/m3 and 20,557.69 µg/m3, respectively. In comparison, the average PM10 concentration with and without control measures in study site #2 is 53.95 µg/m3 and 135.69 µg/m3. Therefore, the control measure has successfully reduced the PM10 concentrations by 99.90% and 60.24% in study sites #1 and #2, respectively, and ensures the air quality complies with the Malaysian Ambient Air Quality Guidelines (MAAQG) 24 h threshold limits at 100 µg/m3. In addition, the AERMOD modeling results showed that mitigation measures performed better in rock crushing and quarry operations than in iron ore mining projects in this case study.</jats:p>

Nickel–cobalt-layered double hydroxide (NiCo-LDH) has received considerable attention in the field of supercapacitor; however, the low conductivity and structural instability limit its practical applications. In this paper, a facile strategy for the fabrication of NiCo-layered double hydroxide (NiCo-LDH) coating on nitrogen/oxygen co-doped carbon nanocages (NOCN) was proposed in this paper. This multicomponent nanocomposite, NiCo-LDH@NOCN, has a high specific capacitance of 1842 F g−1 at 1 A g−1, a remarkable rate capability of 68.1% increasing the current density to 30 A g−1, and excellent cycling stability of 72.1% after 1000 cycles. Furthermore, an asymmetric supercapacitor (ASC) composed of NiCo-LDH@NOCN as a positive electrode and NOCN as a negative electrode was fabricated. The ASC shows a superior energy density of 31.6 Wh kg−1 at a power density of 700 W kg−1, which suggests the great practical application potential of supercapacitor.

<jats:p>Electric vehicles (EVs) must be used as the primary mode of transportation as part of the gradual transition to more environmentally friendly clean energy technology and cleaner power sources. Vehicle-to-grid (V2G) technology has the potential to improve electricity demand, control load variability, and improve the sustainability of smart grids. The operation and principles of V2G and its varieties, the present classifications and types of EVs sold on the market, applicable policies for V2G and business strategy, implementation challenges, and current problem-solving techniques have not been thoroughly examined. This paper exposes the research gap in the V2G area and more accurately portrays the present difficulties and future potential in V2G deployment globally. The investigation starts by discussing the advantages of the V2G system and the necessary regulations and commercial representations implemented in the last decade, followed by a description of the V2G technology, charging communication standards, issues related to V2G and EV batteries, and potential solutions. A few major issues were brought to light by this investigation, including the lack of a transparent business model for V2G, the absence of stakeholder involvement and government subsidies, the excessive strain that V2G places on EV batteries, the lack of adequate bidirectional charging and standards, the introduction of harmonic voltage and current into the grid, and the potential for unethical and unscheduled V2G practices. The results of recent studies and publications from international organizations were altered to offer potential answers to these research constraints and, in some cases, to highlight the need for further investigation. V2G holds enormous potential, but the plan first needs a lot of financing, teamwork, and technological development.</jats:p>

Fish body mucus plays a protective role, especially in Halobatrachus didactylus, which inhabits intertidal zones vulnerable to anthropogenic contaminants. In silico predicted bioactive peptides were identified in its body mucus, namely, EDNSELGQETPTLR (HdKTLR), DPPNPKNL (HdKNL), PAPPPPPP (HdPPP), VYPFPGPLPN (HdVLPN), and PFPGPLPN (HdLPN). These peptides were studied in vitro for bioactivities and aggregation behavior under different ionic strengths and pH values. Size exclusion chromatography revealed significant peptide aggregation at 344 mM and 700 mM ionic strengths at pH 7.0, decreasing at pH 3.0 and pH 5.0. Although none exhibited antimicrobial properties, they inhibited Pseudomonas aeruginosa biofilm formation. Notably, HdVLPN demonstrated potential antioxidant activity (ORAC: 1.560 mu mol TE/mu mol of peptide; ABTS: 1.755 mu mol TE/mu mol of peptide) as well as HdLPN (ORAC: 0.195 mu mol TE/mu mol of peptide; ABTS: 0.128 mu mol TE/mu mol of peptide). Antioxidant activity decreased at pH 5.0 and pH 3.0. Interactions between the peptides and mucus synergistically enhanced antioxidant effects. HdVLPN and HdLPN were non-toxic to Caco-2 and HaCaT cells at 100 mu g of peptide/mL. HdPPP showed potential antihypertensive and antidiabetic effects, with IC50 values of 557 mu g of peptide/mL for ACE inhibition and 1700 mu g of peptide/mL for alpha-glucosidase inhibition. This study highlights the importance of validating peptide bioactivities in vitro, considering their native environment (mucus), and bioprospecting novel bioactive molecules while promoting species conservation.

While soundscapes shape the structure and function of auditory systems over evolutionary timescales, there is limited information regarding the adaptation of wild fish populations to their natural acoustic environments. This is particularly relevant for freshwater ecosystems, which are extremely diverse and face escalating pressures from human activities and associated noise pollution. The Siamese fighting fish Betta splendens is one of the most important cultured species in the global ornamental fish market and is increasingly recognized as a model organism for genetics and behavioural studies. This air-breathing species (Anabantoidei), characterized by the presence of a suprabranchial labyrinth organ that enhances auditory sensitivity, is native to Southeast Asia and inhabits low flow freshwater ecosystems that are increasingly threatened due to habitat destruction and pollution. We characterized the underwater soundscape, along with various ecological parameters, across five marshland habitats of B. splendens, from lentic waterbodies to small canals near a lake in Chiang Rai province (Thailand). All habitats exhibited common traits of low dissolved oxygen and dense herbaceous vegetation. Soundscapes were relatively quiet with Sound Pressure Level (SPL) around 102-105 dB re 1 mu Pa and most spectral energy below 1,000 Hz. Sound recordings captured diverse biological sounds, including potential fish vocalizations, but primarily insect sounds. Hearing thresholds were determined using auditory evoked potential (AEP) recordings, revealing best hearing range within 100-400 Hz. Males exhibited lower hearing thresholds than females at 400 and 600 Hz. This low-frequency tuning highlights the potential susceptibility of B. splendens to anthropogenic noise activities. This study provides first characterization of the auditory sensitivity and natural soundscape of B. splendens, establishing an important ground for future hearing research in this species. The information provided on the auditory sensory adaptation of B. splendens emphasizes the importance of preserving quiet soundscapes from lentic freshwater ecosystems.

This current study assessed the toxicity of selected heavy metals in paddy and sediments of non-major production sites in Southern Peninsular Malaysia, complemented by bibliometric analysis of research trends and health implications of rice contamination. Paddy (grains, stems, roots) and soil samples were collected from seven selected sites in the Southern parts of Peninsular Malaysia and analyzed for their heavy metals content. The health risk assessments were conducted based on estimated daily intake, and the Web of Science database was used for bibliometric analysis. The results indicated elevated levels of manganese, Mn (0.4 ± 0.07), especially in the roots, compared to other heavy metals. Generally, the heavy metal levels in paddy grains were below FAO/WHO’s tolerable daily intake levels, indicating minimal non-carcinogenic risks to both adults and children. The bibliometric analysis indicated a significant increase in related publications, reflecting growing academic interest. This study highlights the potential of non-major sites to produce rice with lower contamination levels, provides insights into research trends, and identifies future investigation areas, especially for major production sites and post-COVID-19 periods. Therefore, this study offers a robust scientific context, identifies research gaps, benchmarks findings, and guides future research directions, ensuring an in-depth perception on heavy metal contamination and its health risks. © This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The peacock blenny Salaria pavo is notorious for its extreme male sexual polymorphism, with large males defending nests and younger reproductive males mimicking the appearance and behavior of females to parasitically fertilize eggs. The lack of a reference genome has, to date, limited the understanding of the genetic basis of the species phenotypic plasticity. Here, we present the first reference genome assembly of the peacock blenny using PacBio HiFi long-reads and Hi-C sequencing data. The final assembly of the S. pavo genome spanned 735.90 Mbp, with a contig N50 of 3.69 Mbp and a scaffold N50 of 31.87 Mbp. A total of 98.77% of the assembly was anchored to 24 chromosomes. In total, 24,008 protein-coding genes were annotated, and 99.0% of BUSCO genes were fully represented. Comparative analyses with closely related species showed that 86.2% of these genes were assigned to orthogroups. This high-quality genome of S. pavo will be a valuable resource for future research on this species’ reproductive plasticity and evolutionary history.

<jats:p>Antibiotic pollution poses a serious environmental concern worldwide, posing risks to ecosystems and human well-being. Transforming waste activated sludge into adsorbents for antibiotic removal aligns with the concept of utilizing waste to treat waste. However, the adsorption efficiency of these adsorbents is currently limited. This study identified KOH modification as the most effective method for enhancing tetracycline (TC) adsorption by sludge biochar through a comparative analysis of acid, alkali, and oxidant modifications. The adsorption characteristics of TC upon unmodified sludge biochar (BC) as well as KOH-modified sludge biochar (BC-KOH) were investigated in terms of equilibrium, kinetics, and thermodynamics. BC-KOH exhibited higher porosity, greater specific surface area, and increased abundance of oxygen-based functional groups compared to BC. The TC adsorption on BC-KOH conformed the Elovich and Langmuir models, with a maximum adsorption capacity of 243.3 mg/g at 298 K. The adsorption mechanisms included ion exchange, hydrogen bonding, pore filling, and electrostatic adsorption, as well as π-π interactions. Interference with TC adsorption on BC-KOH was observed with HCO3−, PO43−, Ca2+, and Mg2+, whereas Cl−, NO3−, and SO42− ions exhibited minimal impact on the adsorption process. Following three cycles of utilization, there was a slight 5.94% reduction in the equilibrium adsorption capacity, yet the adsorption capacity remained 4.5 times greater than that of unmodified sludge BC, underscoring its significant potential for practical applications. This research provided new insights to the production and application of sludge biochar for treating antibiotic-contaminated wastewater.</jats:p>

<jats:p>To comply with the United Nations Sustainable Development Goals (UN SDGs), in particular with SDG 3, SDG 11, and SDG 13, a reliable air pollution prediction model must be developed to construct a sustainable, safe, and resilient city and mitigate climate change for a double win. Machine learning (ML) and deep learning (DL) models have been applied to datasets in Macau to predict the daily levels of roadside air pollution in the Macau peninsula, situated near the historical sites of Macau. Macau welcomed over 28 million tourists in 2023 as a popular tourism destination. Still, an accurate air quality forecast has not been in place for many years due to the lack of a reliable emission inventory. This work will develop a dependable air pollution prediction model for Macau, which is also the novelty of this study. The methods, including random forest (RF), support vector regression (SVR), artificial neural network (ANN), recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU), were applied and successful in the prediction of daily air pollution levels in Macau. The prediction model was trained using the air quality and meteorological data from 2013 to 2019 and validated using the data from 2020 to 2021. The model performance was evaluated based on the root mean square error (RMSE), mean absolute error (MAE), Pearson’s correlation coefficient (PCC), and Kendall’s tau coefficient (KTC). The RF model best predicted PM10, PM2.5, NO2, and CO concentrations with the highest PCC and KTC in a daily air pollution prediction. In addition, the SVR model had the best stability and repeatability compared to other models, with the lowest SD in RMSE, MAE, PCC, and KTC after five model runs. Therefore, the results of this study show that the RF model is more efficient and performs better than other models in the prediction of air pollution for the dataset of Macau.</jats:p>

<jats:p>The mass production of uniform, high-quality polymer nanofibers remains a challenge. To enhance spinning yield, a multi-string standing wave electrospinning apparatus was developed by incorporating a string array into a standing wave electrospinning device. The process parameters such as string spacing, quantity, and phase difference were optimized, and their effects on the electric field distribution within the spinning area were analyzed using electric field simulations. When the string spacing was less than 40 mm or the number of strings exceeded two, the electric field strength significantly decreased due to electric field interference. However, this interference could be effectively mitigated by setting the string standing wave phase difference to half a period. The optimal string array parameters were identified as string spacing of 40 mm, two strings, and a phase difference of half a period. Multi-string standing wave electrospinning produced fibers with diameters similar to those obtained with single-string standing wave electrospinning (178 ± 72 nm vs. 173 ± 48 nm), but the yield increased by 88.7%, reaching 2.17 g/h, thereby demonstrating the potential for the large-scale production of nanofibers. This work further refined the standing wave electrospinning process and provided valuable insights for optimizing wire-type electrospinning processes.</jats:p>

The convergence of air pollution control and climate change mitigation is critical in the pursuit of sustainable development. Therefore, technological innovations are pivotal in addressing the dual challenges of air pollution and global warming. This work presents an overview of technological solutions aimed at reducing air pollution and mitigating GHG emissions. While evaluating their technological strengths and limitations in real applications, this work offers a framework to promote a transition toward blue skies and net-zero emissions. This work also identifies the main sources and negative impacts of air pollution on public health and the environment. A literature overview of published articles from 1976 to 2024 showed that integrating emission reduction technologies are vital in real-word applications. More than 98% of the SO2 in the flue gas can be removed using cutting-edge desulfurization technology. SO2 is eliminated from the environment either unaltered or as sulfuric acid and sulfates. Meanwhile, thermal incinerators boast an impressive efficiency, capable of eliminating 99% of gaseous pollutants. Although existing pollution control technologies are promising to mitigate climate change, they still require further research, development, demonstration, and deployment to overcome barriers and achieve their potential. By examining the effectiveness of control technologies and proposing adaptable strategies, this work highlights the potential of integrating air quality improvement efforts with climate actions. Not only this addresses the global need for cleaner air, but also contributes to the overarching goal of climate stabilization. © The Author(s), under exclusive licence to the Institute of Chemistry, Slovak Academy of Sciences 2024.

Anticancer peptides (ACPs) are promising future therapeutics, but their experimental discovery remains time-consuming and costly. To accelerate the discovery process, we propose a computational screening workflow to identify, filter, and prioritize peptide sequences based on predicted class probability, antitumor activity, and toxicity. The workflow was applied to identify novel ACPs with potent activity against colorectal cancer from the genome sequences of Candida albicans. As a result, four candidates were identified and validated in the HCT116 colon cancer cell line. Among them, PCa1 and PCa2 emerged as the most potent, displaying IC50 values of 3.75 and 56.06 μM, respectively, and demonstrating a 4-fold selectivity for cancer cells over normal cells. In the colon xenograft nude mice model, the administration of both peptides resulted in substantial inhibition of tumor growth without causing significant adverse effects. In conclusion, this work not only contributes a proven computational workflow for ACP discovery but also introduces two peptides, PCa1 and PCa2, as promising candidates poised for further development as targeted therapies for colon cancer. The method as a web service is available at https://app.cbbio.online/acpep/home and the source code at https://github.com/cartercheong/AcPEP_classification.git.

<jats:p>Rapid urbanization and changing climatic procedures can activate the present surface urban heat island (SUHI) effect. An SUHI was considered by temperature alterations among urban and rural surroundings. The urban zones were frequently warmer than the rural regions because of population pressure, urbanization, vegetation insufficiency, industrialization, and transportation systems. This investigation analyses the Surface-UHI (SUHI) influence in Kolkata Municipal Corporation (KMC), India. Growing land surface temperature (LST) may cause an SUHI and impact ecological conditions in urban regions. The urban thermal field variation index (UTFVI) served as a qualitative and quantitative barrier to the SUHI susceptibility. The maximum likelihood approach was used in conjunction with supervised classification techniques to identify variations in land use and land cover (LULC) over a chosen year. The outcomes designated a reduction of around 1354.86 Ha, 653.31 Ha, 2286.9 Ha, and 434.16 Ha for vegetation, bare land, grassland, and water bodies, correspondingly. Temporarily, from the years 1991–2021, the built-up area increased by 4729.23 Ha. The highest LST increased by around 7.72 °C, while the lowest LST increased by around 5.81 °C from 1991 to 2021. The vegetation index and LST showed a negative link, according to the correlation analyses; however, the built-up index showed an experimentally measured positive correlation. This inquiry will compel the administration, urban planners, and stakeholders to observe humanistic activities and thus confirm sustainable urban expansion.</jats:p>

The investigation of pharmaceuticals as emerging contaminants in marine biota has been insufficient. In this study, we examined the presence of 51 pharmaceuticals in edible oysters along the coasts of the East and South China Seas. Only nine pharmaceuticals were detected. The mean concentrations of all measured pharmaceuticals in oysters per site ranged from 0.804 to 15.1 ng g–1 of dry weight, with antihistamines being the most common. Brompheniramine and promethazine were identified in biota samples for the first time. Although no significant health risks to humans were identified through consumption of oysters, 100–1000 times higher health risks were observed for wildlife like water birds, seasnails, and starfishes. Specifically, sea snails that primarily feed on oysters were found to be at risk of exposure to ciprofloxacin, brompheniramine, and promethazine. These high risks could be attributed to the monotonous diet habits and relatively limited food sources of these organisms. Furthermore, taking chirality into consideration, chlorpheniramine in the oysters was enriched by the S-enantiomer, with a relative potency 1.1–1.3 times higher when chlorpheniramine was considered as a racemate. Overall, this study highlights the prevalence of antihistamines in seafood and underscores the importance of studying enantioselectivities of pharmaceuticals in health risk assessments.