Marine phytoplankton are vital for global primary production and carbon fixation in marine ecosystems. Understanding the distribution patterns and assembly mechanisms of phytoplankton in varying nutrient conditions is crucial for phytoplankton ecology, yet research in this field is limited. This study employed environmental DNA technology targeting the phytoplankton 23S rRNA gene to investigate the community structure and assembly processes of phytoplankton (algae and cyanobacteria) in the East China Sea. We identified 224 phytoplankton species: 72 Bacillariophyta, 44 Cyanobacteria, and 34 Chlorophyta. Bacillariophyta and Dinoflagellata were predominant in the nutrient-rich Changjiang Diluted Water (CDW), while cyanobacteria dominated in the low-nutrient Kuroshio Branch Current (KBC). Phytoplankton distribution was significantly influenced by salinity and nutrient levels. Deterministic processes mainly governed phytoplankton community assembly in both CDW and KBC. Co-occurrence network analysis revealed that interactions among phytoplankton in the KBC were significantly higher than in the CDW, indicating greater cooperation or competition in the KBC. Conversely, the modularity of the CDW network was notably higher, likely due to greater environmental heterogeneity. This study highlights the effectiveness of environmental DNA technology in exploring phytoplankton community structure and assembly mechanisms in different nutrient environments. These findings emphasize the significance of understanding phytoplankton dynamics, as enhanced carbon fixation could greatly impact carbon cycling and climate regulation in marine ecosystems.

Background And Aims: Invasive fungal infections (IFI) in children with newly diagnosed acute lymphoblastic leukemia (ALL) and lymphoblastic lymphoma (LBL) are poorly characterized, especially in lower-middle income countries (LMICs). This study aims to identify the incidence, risk factors and outcomes of IFI in a pediatric cohort with ALL/LBL. Methods: We retrospectively analysed pediatric patients diagnosed with ALL/LBL between January and December 2023 at a tertiary cancer center in India. Patients were risk-stratified and treated per the modified ICiCLe protocol. IFIs were classified as proven, probable and possible according to the revised EORTC/MSG consensus definition. Results: Among 407 patients, 392 (96%) had ALL. The overall incidence of IFI was 24%, with probable/proven infections in 12%. Mold infections predominated (79 cases, 77%), followed by yeast infections (21 cases, 21%). In comparison to patients without IFIs, those with IFIs were more likely to have received dexamethasone (30% vs 20%; p=0.009) and anthracycline (28% vs 14%; p=0.001) during induction. Chemotherapy interruptions occurred in 56% of IFI cases, impacting treatment continuity. The 6-week mortality rate of patients with IFI was 15%, rising to 26% in probable/proven cases. Coexisting bacterial infection was associated with increased mortality (odds ratio: 19.2[95%CI: 3.5-105]; p=0.001). Conclusion: IFIs are common in newly diagnosed ALL/LBL patients in LMICs, particularly during early phases of therapy. These infections are associated with considerable mortality, often compounded by concomitant bacterial sepsis. Given these findings, consideration of antifungal prophylaxis is warranted to mitigate morbidity and mortality due to IFIs.

Characterizing the temporal changes of biotic communities and disentangling the importance of their driving mechanisms are central themes in ecology and environmental management. Non-native species have multiple adverse impact on native communities and species. However, there is a dearth of information on how non-natives influence the long-term dynamics of native communities. In this study, we compared the role of non-native species alongside various local and regional factors in the long-term dynamics of stream fish assemblages in the catchment area of Lake Balaton, Hungary, the largest lake in Central-Europe. Although, we found no consistent trend in species re-ordering between native and non-native species, native fish assemblages indicated significantly lower temporal stability with increasing relative abundance of co-occurring non-natives. Structural equation modelling revealed that assemblage dynamic patterns were also determined by a habitat degradation gradient. Moreover, habitat degradation and the presence of fishponds increased the relative abundance of non-native species, further affecting native assemblages through indirect interactions. Fish assemblage dynamics showed also some degree of finer-scale spatial structure. Non-metric multidimensional scaling further reinforced the destabilizing effect of non-native species but highlighted that native fish assemblages could generally be described by non-directional gradual or saltatory changes over time, regardless of the relative abundance of non-natives. Our results thus revealed that the studied native fish assemblages may possess some degree of resilience against biological invasions. However, increasing temporal variability induced by non-natives makes native assemblages more vulnerable to environmental stochasticity threatening their long-term persistence. This is especially worrying, since the frequency and intensity of environmental disturbances are expected to rise in the future due to climate change and increasing anthropogenic pressure on aquatic ecosystems.

The increasing complexity of textual data requires language model architectures capable of not only syntactic processing but also deep semantic interpretation. Traditional approaches often fall short in capturing high-order relationships and resolving ambiguities within complex linguistic structures. To address this, the Semantic Pattern Resolution Mechanism (SPRM) was developed as an innovative enhancement to existing model frameworks, introducing layered attention and parallel semantic channels specifically designed to interpret and preserve meaning across multi-tiered contexts. Through a series of controlled experiments comparing SPRM-augmented models against baseline configurations, SPRM demonstrated significant improvements in semantic accuracy, computational efficiency, and contextual coherence, validating its potential as a robust component in language models deployed for domain-sensitive and real-time applications. Key performance metrics-including semantic resolution accuracy, response latency, and memory utilization-highlight SPRM's capacity to optimize resource use while maintaining interpretive depth, making it suitable for environments where high interpretative precision is critical. These findings indicate that SPRM effectively bridges the gap in semantic pattern resolution capabilities, providing an adaptable, resource-efficient foundation for future language model advancements.

1. IntroductionWe live in the world of communication. Through various modes of communication, we accomplish desired goals and life achievements. Without communication, human existence is indifferent to the state of a lifeless rock. As we communicate for various purposes across our lifespan, there is no social (human) context in which communication is unimportant (Keyton, 2015). In fact, communication is the sine qua non of human existence (Backlund & Morreale, 2015), because it is ” vital to health, relationships, and all collective human endeavors” (Hannawa & Spitzberg, 2015, p. 7). It is certainly advantageous if one can communicate effectively and appropriately at social events. In contrast, a lack of ability to communicate effectively and appropriately or deficient in communication skills can lead to failures, harm, and threaten our lives (Hannawa, 2015). The ability to communicate—speak, write, listen, and interact with others—is presumably a fundamental human life skill. Despite that, not everyone can communicate well all the time (Backlund & Morreale, 2015). Studies have shown that a certain amount of the population has suffered from the difficulties of communication (Hannawa & Spitzberg, 2015) in their life contexts. In several interactions, competent communication abilities can present valued life outcomes and personal and academic success” (Morreale, 2015, p. 466).  In contrast, “poor communication can cause conflict or even exacerbate existing conflicts “(Thompson, 2011, p. 183).Several communication scholars agree on communication competence is “the ability to use communication appropriately and effectively to achieve a desired outcome or goal” (Spitzberb, Canary, and Cupach, 1994 cited in Afifi & Coveleski, 2015, p. 317; Backlund & Morreale, 2015, p. 23). Understanding the students’ communication is advantageous because it can provide them from effective communication strategies to achieving their life goals. The study of communication competence of the students is also aligned with the UNESCO’s Sustainable Development Goal 4, which calls for teaching competencies beyond literacy and numeracy to prepare students for the challenges of the twenty-first century (Care, 2017).As people continue to rely on technology, such as mobile phones, instant messages (IM), and computers for communication, we must attempt to be competent communicators both in mediated and non-mediated worlds (Kelly & Keaten 2015). Several interaction-based disciplines, including ELT, continue to explore the prospects of communication in technology-mediated contexts.

Introduction: Hispanic emerging adults (HEAs) are a rapidly growing population in the United States that report high levels of alcohol consumption. Thus, there is a need to examine modifiable factors that can reduce alcohol consumption among this population. The present study addresses gaps by integrating social and cognitive determinants of alcohol use as they may be associated with alcohol use severity in HEAs. We investigated these relationships by a) examining the direct association between traditional gender roles and alcohol use severity among HEA college students, b) examining the indirect associations between traditional gender roles and alcohol use severity via drinking motives (DM), and c) the extent to which nativity status moderates the direct and indirect associations between traditional gender roles and alcohol use severity. Methods: A conditional process analysis was conducted on data from a convenience sample of 423 Hispanic college students from Texas and Florida who completed a cross-sectional online survey. Results: Higher levels of traditional gender roles were associated with higher alcohol use severity. Also, traditional gender roles had statistically significant indirect associations with alcohol use severity via DM-conformity and DM-coping. Lastly, nativity status moderated the direct and indirect associations between traditional gender roles and alcohol use severity whereby stronger associations were found among immigrants. Conclusion: Understanding the interplay of gender roles and drinking motives behind HEA’s alcohol use can help facilitate the development of culturally adapted interventions, especially when considering heterogeneity across nativity status.

The Cognitive Emotion Regulation Questionnaire is one of the most widely used instruments to measure cognitive emotion regulation, and its psychometric properties have been evaluated in various studies and cultural contexts. However, the 9-factor internal structure originally proposed for the scale measures does not present consistent evidence in the literature. The exclusive use of the confirmatory factor model in previous literature may largely explain this inconsistency. In the present research, we propose to estimate innovative measurement models for this questionnaire, the exploratory structural equation models. For this purpose, we worked with a large sample of Argentines and compared the fit of the models. The results favored the exploratory structural equation models, indicating that we are not observing indicators that reflect simple factorial structures. This refined understanding can ultimately improve the reliability of Cognitive Emotion Regulation Questionnaire scores in clinical settings, enhancing the quality of patient care and treatment outcomes.

Synthetic cathinones (SC) are central nervous system stimulants similar to amphetamines, affecting neurotransmitters pathways like dopamine, serotonin, and norepinephrine. However, the increasing use of SC has led to higher rates of toxicity and mortality. This study presents four cases of fatal multiple-drug intoxication involving SC in Taiwan.

To improve the accuracy of identifying armor damage points in battlefield environments, we developed an advanced semantic segmentation model based on SegNet, tailored specifically for segmenting damage points in armor images. The original SegNet model exhibited limitations, such as unclear segmentation and feature loss during armor image processing. To address these issues, we integrated the DenseNet architecture, which facilitates direct connections between feature maps across different network layers. This innovation enables efficient reuse of image features, significantly enhancing segmentation accuracy. Our improved model demonstrates greater flexibility in feature utilization compared to traditional architectures like U-Net and Fully Convolutional Networks (FCN), allowing for effective integration and transmission of feature information across layers. To validate our approach, we constructed a dataset comprising images of three distinct types of armor and trained the model using the PyTorch deep learning framework. We conducted a comprehensive comparison between the original SegNet model and our enhanced version using standard evaluation metrics. The experimental results indicate that the improved model achieved a precision of 85.32%, recall of 83.87%, specificity of 84.36%, and a Dice coefficient of 84.81%. Additionally, the enhanced SegNet model demonstrated a 3.53% increase in recognition success rate compared to the original model, while maintaining similar processing times for batches of 100 images. These findings underscore the effectiveness of our model in accurately segmenting damage points under challenging battlefield conditions, thereby contributing to more reliable assessments of armor integrity and improved decision-making in military applications.

This article reports a case of a middle-aged man who was admitted to the hospital for sudden upper abdominal pain several hours later. After being given the painkiller Compound Diclofenac Sodium in the outpatient clinic, the patient developed systemic itching, redness, and rash. Acute pancreatitis was diagnosed after admission. During treatment, the patient was found to have allergic reactions to multiple drugs. This case is rare. This article uses case reports to improve clinical pharmacists and clinicians understanding of multi-drug allergies, and provides certain reference for solving the safety and effectiveness of medication in patients with multi-drug allergies.

Bone defects are common surgical complications, and stem cell and gene therapies are key strategies for bone repair and regeneration. Transcription factor 7-like 2 (TCF7L2) is a key regulator of the Wnt signaling pathway, with potential applications in gene editing. However, the role of TCF7L2 in the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) remains poorly understood. We knocked down or overexpressed TCF7L2 to evaluate its effect on erastin-induced ferroptosis in BMSCs. Simultaneously, we assessed the impact of TCF7L2 overexpression on the osteogenic capacity of BMSCs. To confirm the involvement of Glutathione peroxidase 4 (GPX4), we conducted rescue experiments by knocking down GPX4 expression. A mouse cranial defect model was established to analyze the effect of TCF7L2 overexpression on cranial bone healing. The results showed that TCF7L2 knockdown promoted, while TCF7L2 overexpression inhibited, erastin-induced ferroptosis in BMSCs. Mechanistic studies revealed that TCF7L2 knockdown reduced, while TCF7L2 overexpression enhanced GPX4 expression, thereby regulating ferroptosis. Conversely, GPX4 knockdown significantly attenuated the regulatory effects of TCF7L2 overexpression on cell proliferation and ferroptosis inhibition. Furthermore, TCF7L2 overexpression promoted cell proliferation, osteogenic differentiation, and mineralization in vitro, while enhancing cranial defect healing in vivo. This study is the first to reveal the dual role of TCF7L2: regulating ferroptosis in BMSCs via GPX4, while promoting BMSC proliferation and osteogenic differentiation. These findings provide novel molecular targets and theoretical foundations for the treatment of bone defects.

In the Rafsanjan plain, Iran, the excessive use of groundwater for pistachio irrigation has resulted in a severe water level decline, a major reason for land subsidence. An abrupt decrease in groundwater level results in soil compaction and gradual land sinking, leading to land subsidence, an alarming environmental problem for infrastructure, agriculture, roads, houses, and water supply systems. But which factors are explicitly affecting the substantial depletion of groundwater? And how can sustainable groundwater management and managed aquifers address this issue? Firstly, this study will broadly discuss these topics in the context of the Rafsanjan plain. Secondly, various causes of the Rafsanjan plain’s land subsidence will be presented, including overuse of groundwater, a semi-arid climate with little precipitation, uncontrolled abstraction, and a slower rate of aquifer recharge. Lastly, feasible solutions (i.e., modern irrigation techniques) that may decrease land subsidence in the study area up to 50% by 2050 will be discussed. In this study, a broad collection of academic peer-reviewed articles was studied to present credible data to qualify each problem and discuss solutions.

Grassland ecosystems, which cover over one-third of the Earth’s land area, store 10-30% of global soil carbon (C). However, these ecosystems face substantial impacts from human activities, including mining. This study investigates the spatial distribution of soil C and related environmental factors in reclaimed grasslands on former uranium mine sites in Wyoming. We hypothesized that grazing duration and environmental factors would influence soil C levels. Interactions between topography, vegetation diversity, soil properties, and soil C in the context of grazing management in both natural and reclaimed grasslands from of a wide range of periods from 1 year to 100 years were analyzed using Geographically Weighted Regression models. Data collected from 2022-23 showed that total carbon was consistently higher in natural grasslands (1.2-4.9%) than in reclaimed grasslands (0.8-1.3%). Additionally, soil C was significantly higher in natural grasslands grazed for 1 year compared to those grazed for 100 years. In contrast, reclaimed grasslands had lower soil C in areas grazed for 1 year compared to those grazed for 7 or 14 years. The absolute values of coefficients from environmental covariates indicated that areas grazed for a shorter duration (~1 year) were more influenced by biotic and abiotic factors than areas grazed for longer periods (>7 years). Our findings show moderate grazing increases the resiliency of grassland ecosystem when grazed 7 years or longer and acknowledge the roles of topographic, soil, and vegetative factors in enhancing soil C concentration and developing sustainable land management practice in rangeland conditions.

Kaitalin White1*, Freya Cornwell-Davison2*, Christopher Cockel1, Ted Chapman 1, Efisio Mattana1, Juan Viruel2†

Since the 18th CPC National Congress,China has prioritized green and low-carbon development. With this article, we selected 39 indicators from six subsystems to assess the level of green and low-carbon development, utilizing the DPSIRM model as a framework.To enhance the evaluation framework, we incorporate the digital inclusive finance index as a driving force indicator and add the environmental protection Baidu index and the carbon dioxide Baidu index as impact indicators.We used simulated annealing to optimize a projection pursuit model, assessing the green, low-carbon development of 30 Chinese provinces from 2011 to 2021.We analyzed the results through various methods, focusing on provincial and regional aspects. Kernel density estimation and Moran’s I index revealed spatiotemporal distribution characteristics, while the Theil index measured regional disparities in green, low-carbon development.This research enhances understanding of China’s green and low-carbon development, actively promoting global sustainable development and environmental improvement.

Note: Metal alloys or bimetallic nanoparticles have a high superparamagnetic property  , which makes them suitable for  electromagnetic nanomolecules or electromagnetic nanocarriers  . In addition to this, the electromagnetic property  of the surface of these nanoparticles allows surface active substances to  be placed  on the surface of the nanoparticles,  which can be used to dissolve the nanoparticles  .

Note: Cobalt nanowires technology in the approximate dimensions of 1 to 100 nm, where only one phenomenon of its kind offers descriptive applications, is in the capacity of matter. Cobalt nanowires exhibit electromagnetic absorbing behavior at medium temperature and when the magnetic field is applied perpendicular to the nanowires, these nanoelectronic devices have a larger coercive field compared to when the electromagnetic field is parallel to the nanowires. Cobalt wires are formed. Nanotechnology encompasses science, engineering and non-scale technology, imaging, measurement, design and manipulation of materials at this length scale. Due to nanotechnology, the speed of computers has increased compared to the past and the value of calculations has decreased. In the immersion method, the nanowires  have enough time to transfer from the particles of the nanowires to the holes; The step of forming uniform nanoparticles is done slowly and finally uniform nanowires are formed. Structural investigation with FESEM  in the immersion method of uniform nanowires in all pores and in a wide area in nanowire particles. The simple answer to this question is any particle less than 100 nanometers.  But as  the scale of 1-100 nm determines the size range of a nanoparticle.  In order to prevent particle contact, a cluster of atoms may be removed below 1 nm, but the electron movement in nanoparticles has to particles <1 nm.  Because particles are three-dimensional.

The exponential increase in information volume handled by contemporary artificial intelligence systems has magnified the need for efficient, context-sensitive knowledge structuring within language models to support accurate and adaptable responses across diverse applications. Introducing Dynamic Cognitive Pathway Extraction, this study offers a novel solution that restructures retrieval pathways autonomously and dynamically, aligning with each query's contextual requirements. Designed to overcome the limitations of static and semi-static architectures, the pathway extraction method leverages a multi-layered approach to organize and prioritize knowledge nodes, achieving a high degree of retrieval coherence, reduced memory overhead, and optimized resource allocation under variable query loads. Through an experimental evaluation on an open-source language model, the results show that this adaptive pathway mechanism yields significant performance improvements, including reduced retrieval latency and enhanced memory utilization, especially in scenarios requiring rapid adaptability across complex and ambiguous queries. Furthermore, the pathway model's feedbackdriven refinement of retrieval structures enhances contextual retention, fostering a scalable, resource-efficient framework for knowledge management in AI-driven applications. Altogether, Dynamic Cognitive Pathway Extraction emerges as a robust methodological advancement, enabling intelligent systems to structure and retrieve knowledge with a precision and flexibility essential for the evolving demands of modern information processing.

Caves are unique depositional environments that hold great potential for long-term preservation of DNA due to their typically cool and stable internal climates; buffered from external climate extremes. Bones from caves have long been recognised as an excellent source of ancient DNA, yet the potential for DNA preservation in cave sediments themselves has only recently begun to be explored. Here, we discuss features of caves that make them well-suited to long-term preservation of sedimentary ancient DNA (sedaDNA), focussing specifically on sources, taphonomy and preservation of cave sedaDNA. We also highlight opportunities for future work to improve our understanding of the processes influencing long-term DNA preservation within cave sediments. These recommendations seek to improve our understanding of sedimentary ancient DNA taphonomy within caves and enhance the level of insights about the past that can be gained from it, and include: (1) designation of reference sections and sample repositories; (2) routine collection of sediment, mineralogy and geochemistry data; (3) routine collection of cave climate data; (4) increased application of microstratigraphic and spatial analyses; (5) advocating use of multiple proxies when interpreting results; and (6) ensuring ethical best practices are followed.

La cal sodada es un compuesto químico producto de la mezcla de hidróxido de calcio e hidróxido de sodio, se destaca por su capacidad de absorber el dióxido de carbono presente en el aire exhalado que circula a través de ella. Este material ha sido fundamental en la evolución de la anestesia, siendo el primer dispositivo de anestesia del mundo que incorporó un sistema de reinhalación desarrollado por la empresa Dräger en 1924. Este avance marcó un hito en la práctica anestésica, permitiendo una mayor eficiencia en el uso de gases anestésicos y un mejor control del equilibrio respiratorio del paciente.

Mountainous regions are regarded as significant biodiversity hotspots, offering a diverse range of vital ecosystem services to the communities who reside in them and the surrounding plains. The black grouse (Lyrurus tetrix), a galliform species emblematic of the European Alps, is currently threatened by habitat change. The estimation of population dynamics, and in particular the reproductive success of this species, represents a significant challenge for the long-term conservation of the black grouse. In this study, we attempted to map black grouse brood habitat suitability (BHS) at the scale of an Alpine bioregion, coupling a species distribution model (SDM) with multi-source remote sensing data. To extract landscape composition features likely to influence BHS, convolutional neural networks (CNNs) were employed to characterise very high spatial resolution (VHSR) SPOT6-7 imagery. Altitude, phenological indices derived from Sentinel-2 time series (NDVImax, NDWI1max), and a texture feature derived from the SPOT6-7 images (Haralick entropy) were used to refine landscape characterisation. An SDM based on a random forest ensemble model was used to map black grouse BHS. Altitude, ericaceous heathland and NDVImax emerged as the three most significant variables, consistent with the ecological needs of black grouse. The proportion of ericaceous heathland was especially representative of the foraging needs of female black grouse; the main ecological determinant of habitat suitability for brood rearing with sufficient vegetation cover. This study highlights the effectiveness of integrating VHSR and multispectral time series, together with the advantages offered by deep learning techniques, in extracting species-specific information tailored to conservation issues. The BHS map, produced on a regional scale, constitutes a significant advances in the monitoring of the current population dynamics of black grouse at the western limit of the species’ geographical distribution.

High native species diversity generally suppresses non-native invasions, but many ecosystems are now characterized by non-native assemblages that vary in species diversity. How this non-native species diversity affects subsequent invaders and its environmental dependence remain unclear. Here, we conducted a plant-soil feedback experiment to investigate how non-native plant species diversity affects the growth of subsequent non-native plants, the role of soil microbes in this process, and the dependence of these patterns on drought. We found that under well-watered conditions, the biomass of subsequent invaders was higher with soil inocula generated by high non-native diversity, which was associated with higher arbuscular mycorrhizal fungal richness. However, under drought conditions, the biomass of subsequent invaders did not depend on soil inocula generated by non-native diversity. Our study reveals soil microbial legacies likely contribute to the commonly observed co-occurrence of multiple non-native species in nature and the importance of environmental conditions for these effects.

Avian reproductive strategies exhibit remarkable plasticity in various scenarios, posing challenges in determining the optimal pathway through which parents enhance their reproductive success. we addressed this question by employing structural equation modeling (SEM) analysis in a long-term field survey for the azure-winged magpie (Cyanopica cyanus), which had accumulated datasets for multiple reproductive components, including extra-pair fertilization (EPF), hatching failure, nest predation by predators and conspecific raiders, and offspring starvation. Our initial findings revealed a significant variation of these additional reproductive components with the nest’s reproductive initiation time (RIT). Subsequently, SEM analysis was conducted to investigate the interplay among female and male breeding conditions, cooperative breeding, nest RIT, and individual reproductive success. The results from our SEM analysis suggest that both sexes predominantly rely on conventional reproductive pathways – females tend to favor early RIT while males prefer forming social partnerships with higher-quality females – instead of adopting alternative reproductive strategies to enhance their reproductive success. Furthermore, considering intra-sexual variations in breeding conditions observed in both sexes, our findings also indicate that early RIT may be adaptive for experienced females and those males pairing with higher-quality females; whereas delayed RIT is advantageous for inexperienced females and males with a higher probability of acquiring EPF. Overall, our study demonstrates how integrating various aspects of avian reproduction through multivariate analysis provides a comprehensive understanding of avian reproductive success rather than focusing solely on a single strategy.

In recent years, there has been a global surge in research, development, and deployment of satellite internet, leading to the rapid advancement of low-Earth orbit satellite communication constellations. To meet the growing demands of satellite communications, these constellations have incorporated inter-satellite laser links to enhance communication capacity. This paper explores the single-wavelength all-optical satellite network architecture, with a particular focus on addressing congestion issues in such networks. Correspondingly, it proposes path planning algorithms and strategies to effectively mitigate these challenges.