Long-term Interactions Research Articles

Roles of helminth extracellular vesicle-derived let-7 in host–parasite crosstalk

Helminth infections are a major public health problem as they can cause long-term chronic infections in their hosts for which there is no effective vaccine. During the long-term interaction between helminths and their hosts, helminth-derived extracellular vesicles (EVs) can participate in host immunomodulatory processes by secreting bioactive molecules (BMAs). Growing data suggests that microRNAs (miRNAs) in helminth EVs have a significant impact on the host’s immune system. The let-7 family is highly conserved among helminth EVs and highly homologous in the host, and its function in host–parasite crosstalk may reflect active selection for compatibility with the host miRNA machinery. In-depth studies targeting this aspect may better elucidate the mechanism of parasite-host interactions. Hence, this review summarizes the current studies on the cross-species involvement of helminth EV-derived let-7 in host immune regulation and discusses the barriers to related research and potential applications of helminth EVs.

End-to-end multiple object tracking in high-resolution optical sensors of drones with transformer models

Drone aerial imaging has become increasingly important across numerous fields as drone optical sensor technology continues to advance. One critical challenge in this domain is achieving both accurate and efficient multi-object tracking. Traditional deep learning methods often separate object identification from tracking, leading to increased complexity and potential performance degradation. Conventional approaches rely heavily on manual feature engineering and intricate algorithms, which can further limit efficiency. To overcome these limitations, we propose a novel Transformer-based end-to-end multi-object tracking framework. This innovative method leverages self-attention mechanisms to capture complex inter-object relationships, seamlessly integrating object detection and tracking into a unified process. By utilizing end-to-end training, our approach simplifies the tracking pipeline, leading to significant performance improvements. A key innovation in our system is the introduction of a trajectory detection label matching technique. This technique assigns labels based on a comprehensive assessment of object appearance, spatial characteristics, and Gaussian features, ensuring more precise and logical label assignments. Additionally, we incorporate cross-frame self-attention mechanisms to extract long-term object properties, providing robust information for stable and consistent tracking. We further enhance tracking performance through a newly developed self-characteristics module, which extracts semantic features from trajectory information across both current and previous frames. This module ensures that the long-term interaction modules maintain semantic consistency, allowing for more accurate and continuous tracking over time. The refined data and stored trajectories are then used as input for subsequent frame processing, creating a feedback loop that sustains tracking accuracy. Extensive experiments conducted on the VisDrone and UAVDT datasets demonstrate the superior performance of our approach in drone-based multi-object tracking.

A Human-Centered View of Continual Learning: Understanding Interactions, Teaching Patterns, and Perceptions of Human Users Toward a Continual Learning Robot in Repeated Interactions

Continual learning (CL) has emerged as an important avenue of research in recent years, at the intersection of Machine Learning (ML) and Human–Robot Interaction (HRI), to allow robots to continually learn in their environments over long-term interactions with humans. Most research in CL, however, has been robot-centered to develop CL algorithms that can quickly learn new information on systematically collected static datasets. In this article, we take a human-centered approach to CL, to understand how humans interact with, teach, and perceive CL robots over the long term, and if there are variations in their teaching styles. We developed a socially guided CL system that integrates CL models for object recognition with a mobile manipulator robot and allows humans to directly teach and test the robot in real time over multiple sessions. We conducted an in-person study with 60 participants who interacted with the CL robot in 300 sessions with 5 sessions per participant. In this between-participant study, we used three different CL models deployed on a mobile manipulator robot. An extensive qualitative and quantitative analysis of the data collected in the study shows that there is significant variation among the teaching styles of individual users indicating the need for personalized adaptation to their distinct teaching styles. Our analysis shows that the constrained experimental setups that have been widely used to test most CL models are not adequate, as real users interact with and teach CL robots in a variety of ways. Finally, our analysis shows that although users have concerns about CL robots being deployed in our daily lives, they mention that with further improvements CL robots could assist older adults and people with disabilities in their homes.

Hydrological classification of mine pit lakes using modelling experiments

With the growing global prevalence of open-pit mining activities, there is an increasing necessity for sustainable mine life cycle plans with an early outlook towards mine closure. A major consideration in mine closure planning is the potential formation of lakes in the mine void and how these “pit lakes” can be managed to minimise risks and, if possible, create benefits. Understanding the long-term interactions between pit lakes, groundwater, and surface water systems is essential for that purpose. While numerous site-specific studies have been undertaken, there have been no studies that aim to provide a general, broadly applicable understanding of how pit lake hydrology relates to geographical context, and no efforts to hydrologically classify pit lakes using geographical criteria. This research employs an integrated generic pit lake water balance model to examine mine pit lake interactions with the surrounding surface water and groundwater. Simulating 243 scenarios, the influence of five input factors (climate, hydraulic conductivity, regional groundwater level, catchment area and pit slope) on pit lake behaviour up to 6000 years beyond the closure of the mine was considered. The assessment focused on four pit lake hydrological attributes once the system reached equilibrium: water level, time to equilibrium, the fraction of days where the pit recharges groundwater, and the fraction of days where there is surface overflow from the lake. All scenarios were assigned to one of five hydrological classes based on the interactions between the pit lake and the surrounding surface water and groundwater. Our findings show that, in many contexts, general data on climate type and subsurface hydraulic conductivity can yield reliable predictions of a pit lake's long-term hydrological classification without having to develop a detailed, site-specific pit lake model. The classification needs improvements in non-arid climates where inter-annual variation in rainfall is pronounced. The pit lake classification is particularly valuable for first-pass risk assessments to determine whether site-specific modelling is required.

The Jyndevad Experiment: Revealing long-term interactions between liming and phosphorus fertilization in a coarse sand soil

The Jyndevad field experiment, initiated in 1942 on a coarse sand soil in South of Denmark, explores the effect of four liming levels (0, 4, 8 and 12 Mg lime ha−1). These were in 1944 combined with two levels of mineral phosphorus (P) fertilizer (0 and 15.6 kg P ha−1 year−1), with or without a high initial dose of 156 kg mineral P ha−1. This study assesses interactions between liming and P fertilization on soil pH, Olsen-P contents and barley yields covering the last three decades. Annual P application improved barley yield regardless of liming, but the optimal liming level differed from year to year. This emphasizes the need for long-term field experiments to detect the complex interactions between liming and P availability on crop performance. The initial high P dose in 1944 and annual P fertilization increased Olsen-P contents in soil. The unlimed soil with pH(CaCl2) values below 4 had the highest Olsen-P content. The Jyndevad Experiment now harbors wide gradients in soil P (Olsen-P contents: 9–82 mg P kg−1 soil) and pH (3.6–6.9), providing a unique research platform for future studies on interactions between liming and P fertilization on coarse sand soils. We present a selection of studies that have used the Jyndevad Experiment to illustrate the research potential of the experiment.

Early diagnosis of Alzheimer’s disease using a group self-calibrated coordinate attention network based on multimodal MRI

Convolutional neural networks (CNNs) for extracting structural information from structural magnetic resonance imaging (sMRI), combined with functional magnetic resonance imaging (fMRI) and neuropsychological features, has emerged as a pivotal tool for early diagnosis of Alzheimer’s disease (AD). However, the fixed-size convolutional kernels in CNNs have limitations in capturing global features, reducing the effectiveness of AD diagnosis. We introduced a group self-calibrated coordinate attention network (GSCANet) designed for the precise diagnosis of AD using multimodal data, including encompassing Haralick texture features, functional connectivity, and neuropsychological scores. GSCANet utilizes a parallel group self-calibrated module to enhance original spatial features, expanding the field of view and embedding spatial data into channel information through a coordinate attention module, which ensures long-term contextual interaction. In a four-classification comparison (AD vs. early MCI (EMCI) vs. late MCI (LMCI) vs. normal control (NC)), GSCANet demonstrated an accuracy of 78.70%. For the three-classification comparison (AD vs. MCI vs. NC), it achieved an accuracy of 83.33%. Moreover, our method exhibited impressive accuracies in the AD vs. NC (92.81%) and EMCI vs. LMCI (84.67%) classifications. GSCANet improves classification performance at different stages of AD by employing group self-calibrated to expand features receptive field and integrating coordinated attention to facilitate significant interactions among channels and spaces. Providing insights into AD mechanisms and showcasing scalability for various disease predictions.

Interactive Cycles between Energy Education and Energy Preferences: A Literature Review on Empirical Evidence

The ultimate goal of energy education is to cultivate citizens with energy literacy, which in turn influences the energy preferences of the general public. Various aspects, such as teaching, practice, publicity, and participation, all profoundly impact the formation of energy literacy. This study reviews the role of energy education in educational policy-making, the operation of educational systems, the design of innovative energy industry environments, and public participation. Through a systematic review, this study integrates empirical research across various contexts and environments. The relevant topics of empirical research include ‘energy education’, ‘energy literacy’, ‘energy preferences’, ‘energy education policy’, ‘operation of energy education systems’, ‘creation of a renewable energy industry environment’, and ‘public participation’. These studies indicate that energy education can enhance participants’ awareness of energy through knowledge transfer, enabling them to adopt more effective energy solutions and cultivate citizens with energy literacy. Energy education not only shapes the public’s energy literacy but also further influences energy preferences, which in turn can have profound effects on social interactions, market outcomes, and political and social systems. Finally, from the perspectives of ‘educational shaping’ and ‘cultural shaping’, the research explores the impact of energy education on the energy environment and people’s values. The findings reveal that society gradually forms a consensus on energy through long-term interactions, establishing a unique energy culture that subsequently influences the direction and implementation of national energy policies. There exist interactive cycles between energy education and energy policy: energy education influences public energy preferences, while energy culture, in turn, affects policy formulation.

Spontaneous Formation of Evolutionary Game Strategies for Long-Term Carbon Emission Reduction Based on Low-Carbon Trading Mechanism

In the context of increasing global efforts to mitigate climate change, effective carbon emission reduction is a pressing issue. Governments and power companies are key stakeholders in implementing low-carbon strategies, but their interactions require careful management to ensure optimal outcomes for both economic development and environmental protection. This paper addresses this real-world challenge by utilizing evolutionary game theory (EGT) to model the strategic interactions between these stakeholders under a low-carbon trading mechanism. Unlike classical game theory, which assumes complete rationality and perfect information, EGT allows for bounded rationality and learning over time, making it particularly suitable for modeling long-term interactions in complex systems like carbon markets. This study builds an evolutionary game model between the government and power companies to explore how different strategies in carbon emission reduction evolve over time. Using payoff matrices and replicator dynamics equations, we determine the evolutionarily stable equilibrium (ESE) points and analyze their stability through dynamic simulations. The findings show that in the absence of a third-party regulator, neither party achieves an ideal ESE. To address this, a third-party regulatory body is introduced into the model, leading to the formulation of a tripartite evolutionary game. The results highlight the importance of regulatory oversight in achieving stable and optimal low-carbon strategies. This paper offers practical policy recommendations based on the simulation outcomes, providing a robust theoretical framework for government intervention in carbon markets and guiding enterprises towards sustainable practices.

SeaTrack: Rethinking Observation-Centric SORT for robust Nearshore Multiple Object Tracking

Nearshore Multiple Object Tracking (NMOT) aims to locate and associate nearshore objects. Current approaches utilize Automatic Identification Systems (AIS) and radar to accomplish this task. However, video signals can describe the visual appearance of nearshore objects without prior information such as identity, location, or motion. In addition, sea clutter will not affect the capture of living objects by visual sensors. Recognizing this, we analyzed three key long-term challenges of the vision-based NMOT and proposed a tracking pipeline that relies solely on motion information. Maritime objects are highly susceptible to being obscured or submerged by waves, resulting in fragmented tracklets. We first introduced guiding modulation to address the long-term occlusion and interaction of maritime objects. Subsequently, we modeled confidence, altitude, and angular momentum to mitigate the effects of motion blur, ringing, and overshoot artifacts to observations in unstable imaging environments. Additionally, we designed a motion fusion mechanism that combines long-term macro tracklets with short-term fine-grained tracklets. This correction mechanism helps reduce the estimation variance of the Kalman Filter (KF) to alleviate the substantial nonlinear motion of maritime objects. We call this pipeline SeaTrack, which remains simple, online, and real-time, demonstrating excellent performance and scalability in benchmark evaluations.

Long-term interaction of metals and phosphate with ferrihydrite in artificial seawater and implications for past and present environments

The FeIII hydroxide ferrihydrite (Fh) is highly reactive towards dissolved metals and other aqueous compounds. This reactivity suggests a possible role for Fh in environmental remediation and in controlling ambient concentrations of metals and nutrients in both modern and ancient aqueous environments. Though the reactivity of Fh towards a variety of aqueous compounds has been determined in previous studies, its reactivity under seawater-like conditions has not been systematically explored. Since solution chemistry can have a profound effect on the uptake of metals and oxyions through its effects on the surface chemistry of Fh and the speciation of metals in solution, the dearth of experiments under seawater-like conditions translates into a knowledge gap of metal-Fh interactions in natural marine systems. Furthermore, metal- and nutrient-Fh interactions have been investigated under dissimilar conditions, making a quantitative comparison of these interactions difficult. Lastly, the fate of the aqueous metals and nutrients taken up by Fh upon its aging has been examined in only a few studies and mostly for a duration up to ∼8 months.We bridged these gaps in a series of adsorption and co-precipitation experiments of various metals and phosphate with Fh, in seawater-analog solutions, at circumneutral pH (pH 7.5 and 8.0) and 25 °C. We quantified the effect of interaction with Fh on the aqueous concentrations of CdII, CoII, CrVI, CuII, MnII, MoVI, NiII, VV, UVI, ZnII, and phosphate (PO43−). The experimental results are provided as uptake percentages (quantified as the metal:Fe ratio in the solid phase relative to the metal:Fe ratio added) at different metal:Fe ratios and as a series of partition coefficients of the studied metals and PO43− between aqueous solution and Fh. Additionally, aging experiments of up to ∼4 years in duration were used to determine the potential effects of grain coarsening, surface modification and mineral transformation on the uptake of the metals and PO43−. Uptake of CrVI, MoVI and UVI was negligible in both the adsorption and co-precipitation experiments. Uptake of VV and PO43− by co-precipitation was as much as twice their uptake by adsorption, and we suggest that stabilization of colloidal Fh with a large surface area explains these findings. For CuII, NiII, CoII, MnII, and CdII differences in uptake between the co-precipitation and adsorption experiments were less pronounced, and we ascribe these differences to relatively minor incorporation of these metals into Fh. No significant transformation of Fh to more stable phases was observed under our experimental conditions and duration. Nevertheless, the uptake of several metals and phosphate was affected by Fh aging. Approximately 75% of the PO43− initially taken up by co-precipitation with Fh was released, as was approximately 30% of the VV. A pronounced increase in the uptake of MnII may be related to its oxidation and precipitation as MnIII,IV oxides. For other metals the changes in uptake were less pronounced.We discuss the mechanisms of metal and PO43− uptake by Fh, the effects of solution composition on uptake, and the implications of our findings for modern and ancient natural environments and for environmental remediation.

The biogeographic patterns of the olive fly and its primary symbiont Candidatus Erwinia dacicola across the distribution area of the olive tree.

The olive fly, Bactrocera oleae (Rossi, 1790), is the major insect pest of olives attacking both cultivated and wild olive. Bactrocera oleae carries a primary and vertically transmitted symbiont, the bacterium Candidatus Erwinia dacicola. As any primary symbiont, it plays an important role in the reproduction and lifespan of the fly. The genetic 16S rRNA diversity of the primary symbiont and the mitochondrial haplotype variation of the insect host were simultaneously examined in 54 olive fly populations. The aim was to unravel the biogeographic patterns of this economically relevant host-bacteria interaction across a wide distribution area. Three symbiont haplotypes were identified. The primary symbiont showed a lower haplotype diversity than that of its host, a characteristic indicative of a long-term interaction. A significant genetic and geographic association between host and primary symbiont was observed, with an East-West genetic differentiation pattern in the Mediterranean basin, coinciding with the historical genetic distribution of the olive tree. The study shows promise, informing and aiding the development of future tools for the control of the olive fly.

Reconstructing palaeogeography and landscapes around the ancient Greek colony of Abdera (Thrace, NE gr.): an integrated remote sensing approach

ABSTRACT We developed a multi-source, integrated remote sensing approach to characterize the geomorphological features of the alluvial and coastal lowlands around the ancient Abdera (coastal Thrace, Gr.). By combining multi-temporal composites of satellite imagery, DEM-derived products, orthophotography, and different cartographic resources, more than 1000 linear km of ancient landforms have been identified and mapped. When crossed with archaeological and historical data, our results allowed to propose a reconstruction of the palaeogeographic evolution and geomorphological dynamics in the eastern lobe of the Nestos Delta, the Kosynthos plain, Lake Vistonida and the Porto Lagos coast since the Antiquity. Our results suggest that the delta developed mainly between Hellenistic times and the Late Antiquity, when it had reached a shape similar to the current. Most of the large palaeochannels visible in the delta seem to be Nestos’ short-lived avulsions occurring in late Byzantine and Ottoman periods. Eastwards progradation of the Kosynthos plain, especially during Byzantine and Ottoman periods and accelerating in the 20th c. due to river channelization, was the main cause of the silting and a significant size reduction of Lake Vistonida since the Antiquity. Lake Lafra was also partially silted in late Byzantine and Ottoman times, likely due to the sedimentary discharge of the Kosynthos after a change in its course. By contrast, other lagoons and wetlands in the coast of Porto Lagos seem relatively stable in the last millennia with only minor silting and coastline progradation. Further geomorphological and geoarchaeological research in the area will allow to draw more precisely long-term interaction of past societies with environmental dynamics and resulting landscape change.

Blockchain Technology Adoption by Critical Stakeholders in Prefabricated Construction Supply Chain Based on Evolutionary Game and System Dynamics

Blockchain technology (BT) is a promising solution to address information asymmetry and trust issues in the prefabricated construction supply chain (PCSC). However, its practical application in PCSC remains limited under the influence of stakeholders’ adoption strategies. While previous studies have analyzed drivers and barriers to BT adoption, they often take a static view, neglecting the long-term dynamic decision-making interactions between stakeholders. This study addresses this gap by examining the interests of owners, general contractors, and subcontractors, and by developing a tripartite evolutionary game model to analyze the interaction mechanism of the strategy of adopting BT in PCSC. Additionally, a system dynamics simulation validates the evolution of stabilization strategies and examines the impact of key parameters. The results indicate that successful BT adoption requires technology maturity to surpass a threshold between 0.5 and 0.7, along with a fair revenue and cost-sharing coefficient between general contractors and subcontractors, ranging from 0.3 to 0.5 at the lower limit and 0.7 to 0.9 at the upper limit. Notably, general contractors play a pivotal role in driving BT adoption, acting as potential leaders. Furthermore, appropriate incentives, default compensation, and government subsidies can promote optimal adoption strategies, although overly high incentives may reduce owners’ willingness to mandate BT adoption. This study provides practical insights and policy recommendations for critical stakeholders to facilitate the widespread adoption of BT in PCSC.

PSII-10 Comparison of short- and long-term equine interaction for promoting perceived skill development, stress reduction, and self-perception within college students

Abstract The mental health crisis across college campuses became evident with the onset of the COVID-19 pandemic. Following the pandemic, research showed an uptick in depression, anxiety, and substance abuse within the college student population. This trend led to campuses expanding therapeutic intervention opportunities for students to promote mental health including the introduction of campus-based equine interaction programs. However, research concerning the required length of curriculum utilizing equine interaction for promoting student mental health is conflicting. Therefore, the objectives of this study were to compare a short-term, 1-d equine interaction program to that of a long-term, semester-long program for promoting skill development, stress reduction, and self-perception among college students. College students selected between participation in one of the following non-therapeutic based equine interaction programs: 1) short-term (n = 8): a 1-h session taking place on 1 d, or 2) long-term (n = 32): a 10-hh program spread out across a semester (15 wk). Each group performed ground-based equine handling activities working with the same mental health professional. Both groups completed a pre- and post- survey instrument with questions targeting equine-based skill development (18 questions), academic-related stress levels (6 questions), and views associated with self-perception (7 questions). Data were analyzed using a two-tailed t-test to determine differences between pre- and post- survey instrument responses. Additionally, a mixed linear model in SAS was utilized to determine differences between the two groups. Significance was set at P ≤ 0.05. While long-term equine interaction did not significantly promote skill development within the student participants (P > 0.05), the students within the short-term equine interaction perceived a significant improvement in basic handling skills working with specific breeds (P = 0.029). As for student stress levels, the short-term equine interaction resulted in students perceiving a reduction in stress associated with the following four areas: typical daily stress levels (P = 0.009), stress levels concerning grades (P = 0.033), studying for finals (P = 0.019), and taking finals (P = 0.005). Students in the long-term equine interaction reported perceived stress reduction in only two areas: overall grade point average (P = 0.044) and general test anxiety (P = 0.029). While students in the short-term equine interaction reported no improvement in self-perception (P > 0.05), students in the long-term equine interaction perceived significant improvements in three areas of self-perception: confidence (P = 0.028), assertiveness (P = 0.035), and goal pursuit (P = 0.012). Nevertheless, no significant differences were found between the two groups for pre-responses (P = 0.312), post-responses (P = 0.604), nor pre-post -response differences (P = 0.962). These survey results suggest long-term equine interaction improved self-perception but did not offer additional benefits from that of the short-term equine interaction. This conclusion allows for colleges to offer programming that is more conducive to the schedule of the students allowing for scheduling that targets specific timepoints where mental health challenges may be heightened.

Illuminating the path to decarbonization: Nuclear energy consumption, clean energy production, and sustainable fuel production for long-term development

The global concern over carbon emissions has necessitated a deep understanding of energy use and air pollution. The fossil fuel- and nuclear-dependent Russian economy is an exciting exception. It examined how nuclear energy consumption (NEC), electricity generation, R&D investment, clean energy production technology, e-commerce penetration, capital creation, and carbon pollution affect the Russian economy. Short- and long-term interactions between these variables are assessed using the ARDL-Bound testing model for 1995Q1–2020Q4. The results show that NEC negatively correlates with CO2 emissions. The study also supports the inverted U-shaped Environmental Kuznets Curve (EKC) hypothesis, showing a positive and significant relationship between clean power production technology and CO2 emissions and a negative and significant relationship between square clean alternative energy innovation and CO2 emissions. Scientific and technical expenditures, fossil fuel coal liquefaction, and investment all negatively and statistically significantly affect CO2 emissions. However, the analysis implies that e-commerce increases CO2 emissions. These findings highlight the need for significant R&D investment to create precise and realistic ways to decrease carbon emissions and protect the environment in accordance with COP 26 targets. These findings have significant implications for the Russian economy, showing that improving energy sources and investing more in R&D may reduce carbon emissions.

The polder systems legacies in the early twentieth century affect the contemporary landscape in the Jianghan Plain of Hubei, China

The long-term interaction between the environment and humans has significantly shaped contemporary landscapes worldwide. As a heritage landscape, the polder is essential for understanding the impact of the past human activities on contemporary landscape on low-lying area of land. In this case study, we reconstructed the regional spatial distribution of the polders in the early twentieth century and examined their coherence over the past century using historical maps and other materials in the Jianghan Plain. The results revealed several key findings: (1) In the early twentieth century, there were 1571 polders covering an area of 11,826.1 km2 with a perimeter of 17,035.9 km. (2) These polders exhibited a J-shaped distribution, with few large-scale polders despite their substantial areas. (3) The shape of these polders reflected an ability to balance human needs and the natural environment. (4) Considerable regional differences in these polders were attributed to centuries-old interactions between humans and the environment. (5) The remnants of these early twentieth century polders have had a lasting influence on the contemporary landscape, particularly in rural areas. This case study underscores how taking into account a broader historical perspective can enhance our understanding of present-day landscapes and, more importantly, the role that past human actions have played in shaping them.

The coupling of winds, ocean turbulence, and High Salinity Shelf Water in the Terra Nova Bay Polynya

The Terra Nova Bay (TNB) Polynya in the Western Ross Sea of Antarctica is a major producer of High Salinity Shelf Water (HSSW), a precursor to Antarctica Bottom Water (AABW). Processes occurring in and around the polynya can therefore effect change in the lower limb of overturning circulation in this region. Here, we use data from a densely-instrumented upper-ocean mooring, deployed for 1 year in a region of active HSSW formation within TNB, to examine the coupling of surface brine rejection and vertical mixing to katabatic wind forcing. We find a high correlation between salinity and winds during the wintertime HSSW production season at the mooring site, with a lag-response of 20 h in near-surface (∼47 m) salinity to winds measured at the nearby Automatic Weather Station (AWS) Manuela. Salinity and temperature measurements show a fully destratified water column by June, with a lag-response of near-seabed (∼360 m) salinity to near-surface salinity of just 5 h. Measurements of turbulent kinetic energy (TKE) dissipation rate (ɛ) from moored pulse-coherent acoustic Doppler current profilers (ADCPs) show general agreement with classic boundary layer scaling (BLS), and calculations of a vertical mixing timescale using the Obukhov length scale average to ∼2.5 h during austral winter, consistent with the 5-h lag time observed in the salinity data. Comparisons to data from concurrent mooring deployments along the southern boundary of TNB, as well as to previously published assessments of model simulations and data from Climatic Long-term Interaction for the Mass-balance in Antarctica (CLIMA) moorings, allow us to explore spatial variability in the coupling of winds and salinity across TNB and to speculate on possible HSSW circulation pathways.

Engineering PDA@CNTs-Enhanced sulfobetaine methacrylate hydrogels for superior flexible sensor applications

Conductive hydrogels have attracted significant attention as versatile materials for flexible sensors, with potential implementation in wearable technologies, electronic skins, and health diagnostics. However, traditional hydrogel models are frequently limited by their inadequate mechanical strength, poor conductivity, weak adhesion, and low durability, which pose significant barriers to their further application in flexible sensors. In this work, we prepared composite multifunctional hydrogels as flexible sensors, which were synthesized from sulfobetaine methacrylate SBMA) and acrylamide (AM), infused with dodecyl quaternary ammonium salt (Q12), and incorporated with poly(dopamine)-functionalized carbon nanotubes (PDA@CNTs). The PDA modification enhances the compatibility of CNTs with the hydrogel matrix. The incorporation of PDA@CNTs into the hydrogel matrix, along with the establishment of multiple dynamic bonds—such as ionic bonds, hydrogen bonds, cation-π interactions, and π-π stacking between polymer chains and PDA moieties—significantly enhances its tensile strength (53.79 kPa), toughness (134.77 kJ/m3), adhesive capabilities (29.84 kPa to paper), and electrical conductivity (0.2 S/m). Moreover, the composite hydrogel reveals a remarkable mechanical strain response, coupled with impressive stability and durability over prolonged periods. It efficiently differentiates between mild elongations (10%–40 %) and substantial elongations (50%–300 %), thereby showcasing its capability for real-time biomechanical motion monitoring. Additionally, the composite hydrogel displays remarkable photothermal antibacterial efficacy upon exposure to near-infrared (NIR) radiation, along with outstanding biocompatibility under standard conditions, thereby confirming its suitability for safe and long-term biological interactions. The exceptional functionality of these composite hydrogels renders them highly conducive to diverse applications in the realm of wearable sensor technologies.

Effectiveness and User Experience of a Smoking Cessation Chatbot: Mixed Methods Study Comparing Motivational Interviewing and Confrontational Counseling.

Cigarette smoking poses a major public health risk. Chatbots may serve as an accessible and useful tool to promote cessation due to their high accessibility and potential in facilitating long-term personalized interactions. To increase effectiveness and acceptability, there remains a need to identify and evaluate counseling strategies for these chatbots, an aspect that has not been comprehensively addressed in previous research. This study aims to identify effective counseling strategies for such chatbots to support smoking cessation. In addition, we sought to gain insights into smokers' expectations of and experiences with the chatbot. This mixed methods study incorporated a web-based experiment and semistructured interviews. Smokers (N=229) interacted with either a motivational interviewing (MI)-style (n=112, 48.9%) or a confrontational counseling-style (n=117, 51.1%) chatbot. Both cessation-related (ie, intention to quit and self-efficacy) and user experience-related outcomes (ie, engagement, therapeutic alliance, perceived empathy, and interaction satisfaction) were assessed. Semistructured interviews were conducted with 16 participants, 8 (50%) from each condition, and data were analyzed using thematic analysis. Results from a multivariate ANOVA showed that participants had a significantly higher overall rating for the MI (vs confrontational counseling) chatbot. Follow-up discriminant analysis revealed that the better perception of the MI chatbot was mostly explained by the user experience-related outcomes, with cessation-related outcomes playing a lesser role. Exploratory analyses indicated that smokers in both conditions reported increased intention to quit and self-efficacy after the chatbot interaction. Interview findings illustrated several constructs (eg, affective attitude and engagement) explaining people's previous expectations and timely and retrospective experience with the chatbot. The results confirmed that chatbots are a promising tool in motivating smoking cessation and the use of MI can improve user experience. We did not find extra support for MI to motivate cessation and have discussed possible reasons. Smokers expressed both relational and instrumental needs in the quitting process. Implications for future research and practice are discussed.

Long-term evolution of binary orbits induced by circumbinary disks

Circumbinary disks are found in a variety of astrophysical scenarios, spanning binary star formation to accreting supermassive black hole binaries. Depending on the characteristics of the system, the interaction with a circumbinary disk can either damp or excite the binary’s eccentricity and can also widen or shrink the orbit. To predict the outcome of the long-term disk-binary interaction, we present a new formalism based on the results of recent suites of hydrodynamic simulations, which resolve the complex geometry of the gas in the vicinity of the binary and fully account for the gravitational and accretion forces. We released a python package, spindler, that implements our model. We show that – under the assumed thin disk model with a fixed thickness and viscosity prescription – accretion onto the binary depletes the disk mass before inducing a significant change in the orbital separation or the mass ratio, unless the mass reservoir feeding the disk is comparable to the mass of the binary. This finding implies that, in most scenarios, an interaction with a circumbinary disk is not an efficient mechanism to shrink the orbit of the binary. However, the interaction can excite the eccentricity up to an equilibrium value, and induce a statistical correlation between the mass ratio and eccentricity, as long as the mass of the disk is at least a few percent of the mass of the binary. We consider the applicability of our model to a variety of astrophysical scenarios: during star formation, in evolved stellar binaries, triples, and in supermassive black hole binaries. We discuss the theoretical and observational implications of our predictions.