Long-term Behavior Research Articles

Exploring the lived experiences of deep vein thrombosis patients in Lahore, Pakistan: a qualitative phenomenological study on healthcare challenges, resilience and social support

ObjectiveThis study aimed to explore and describe the lived psychological and emotional experiences of sufferers of deep vein thrombosis (DVT) and to narrate the effect of those experiences on their...

Evaluation of Colour Stability of Activa Pronto and Beautifil Flow Plus in Three Different Solutions - An In Vitro Study

Objective: To assess the colour stability of two bioactive restorative materials Activa Pronto (Pulpdent, USA) and Beautifil Flow Plus (Shofu, Japan) when exposed to three commonly consumed beverages: coffee, tea, and Coca-Cola.Materials and Methods: 80 disc-shaped specimens were prepared, 40 samples each of the material and were divided into four groups based on the staining solution, which included: distilled water (control), coffee, tea, and Coca-Cola. The specimens were placed in the respective solution for 30 days. Solutions were replaced daily to avoid contamination. Color measurements were performed before (baseline) and after 30 days using a VITA Easyshade spectrophotometer, and the colour changes (ΔE) were calculated in the CIE Lab* system.Results: For the ΔE values, Activa Pronto showed significantly lower values than Beautifil Flow Plus in both coffee (p=0.001) and Coca-Cola (p=0.000) solutions. In the tea group, no significant difference was observed (p=0.223). Activa Pronto generally had more stable color, especially in acidic and staining solutions like coffee and Coca-Cola solutions.Conclusion: Activa Pronto presented greater color stability than Beautifil Flow Plus; therefore, it is a more suitable material for patients who would take much notice of the aesthetic appearances of their restorations in the long term. The most stained materials by Coca-Cola and coffee meant further investigation into the long-term clinical behaviour of these materials was essential.

Research on the Geosynthetic-Encased Gravel Pile Composite Highway Foundation in Low-Temperature Stable Permafrost Regions

In low-temperature stable permafrost regions, both active and passive cooling measures are commonly employed to ensure the long-term stability of highway structures. However, despite adopting these measures, various types of structural issues caused by permafrost degradation remain prevalent in high-grade highways. This indicates that in addition to preventing permafrost melting, structural reinforcement of the foundation is still necessary. Based on the analysis of the long-term foundation temperature field and settlement using the finite element method, which was validated through an indoor top-down freeze–thaw cycle test, this paper explores, for the first time, the feasibility of applying geosynthetic-encased gravel pile composite highway foundations—previously commonly used for permafrost destruction—in low-temperature stable permafrost areas where permafrost protection is the primary principle. By analyzing the long-term temperature field, settlement behavior, and pile–soil stress ratios of permafrost foundations influenced by both the highway structure and composite foundation, it was found that when the pile diameter is 0.5 m, pile spacing is 2 m, and pile length is 11 m, the mean monthly ground temperature of the permafrost foundation will not be significantly affected. Therefore, the properly designed geosynthetic-encased gravel pile composite highway foundation can be adopted in low-temperature stable permafrost regions where permafrost protection, rather than destruction, is required.

Long-term tracking of haematopoietic clonal dynamics and mutations in non-human primate undergoing transplantation of lentivirally barcoded haematopoietic stem and progenitor cells.

Haematopoietic stem and progenitor cell (HSPC) autologous gene therapies are promising treatment for a variety of blood disorders. Investigation of the long-term HSPC clonal dynamics and other measures of safety and durability following lentiviral-mediated gene therapies in predictive models are crucial for assessing risks and benefits in order to inform decisions regarding wider utilization. We established an autologous lentivirally barcoded HSPC transplantation model in rhesus macaque (RM), a model offering insights into haematopoiesis and gene therapies with direct relevance to human. Healthy young adult RMs underwent total body irradiation, followed by transplantation of autologous HSPCs transduced with a lentiviral vector containing a diverse genetic barcode library, uniquely labelling individual HSPCs and their progeny. With up to 131 months of follow-up, we now report quantitative clonal dynamics, characterizing the number, diversity, stability and lineage bias of hundreds of thousands of HSPC clones tracked in five RMs. We documented long-term stable and multi-lineage output from a highly polyclonal pool of HSPCs. Clonal succession after stable haematopoietic reconstitution was minimal. There was no evidence for accelerated acquisition of acquired somatic mutations following autologous lentivirally transduced HSPC transplantation. Our results provide relevant insights into long-term HSPC behaviours invivo following transplantation and gene therapies.

Investigation of self-selective RRAM based on V/ITO structure with rapid thermal annealed ITO for synapse emulation

This paper focuses on the investigation of V/ITO (O2 Rapid Thermal Annealing)-based Self-Selective Resistive Random-Access Memory (RRAM) device. In this study, the natural oxidation of Vanadium top electrode and the rapid thermal annealing (RTA) process greatly simplified the device fabrication process. The VO2-based Selector, formed by the natural oxidation of the Vanadium electrode, effectively suppresses current and is directly integrated with the ITO layer, eliminating the need for additional serial Selector. The oxygen content of the ITO film is significantly increased by the RTA process, enabling the previously conductive ITO material to be used as the RRAM insulating layer without the need for additional deposition of insulating layer. This V/ITO (O2 RTA) structure not only exhibits highly uniform resistance distributions (σ/μ<2.8 %) and endurance stability (10000 cycles), but also effectively simulates synaptic plasticity, exhibiting both short-term and long-term memory behaviors. Notably, potentiation and depression characteristics are displayed by the device when continuous pulse voltage is applied. These advancements underscore the innovation and applicability of RTA-treated ITO films in next-generation memory technologies.

Enhancing Movie Recommendation Systems Through CNN-Based Feature Extraction and Optimized Collaborative Filtering

Abstract. This paper presents the design and implementation of a movie recommendation model that combines collaborative filtering with Convolutional Neural Networks (CNNs) to tackle the challenge of information overload in extensive movie databases. The primary objective is to enhance the user experience by developing an efficient and personalized recommendation system. The proposed model integrates CNNs to extract detailed image features from movie posters, enriching the movie representations used in the recommendation process. This feature extraction is coupled with an optimized collaborative filtering algorithm to deliver more accurate and tailored movie suggestions. The study is based on a dataset that includes movie information, user ratings, and user behavior data. Experimental results demonstrate that the proposed model significantly improves the accuracy and personalization of movie recommendations, thereby offering users a superior selection experience. The practical implications of this research are substantial, as it has the potential to boost user satisfaction and engagement on movie recommendation platforms. Future work will focus on further enhancing the model by incorporating long-term user behavior patterns and integrating multi-modal data sources for even more precise recommendations.

Comparison of The Trapezoidal and Adam Bashforth Approaches in The Lotka-Volterra Prey-Predator Dynamics

This study primarily focuses on comparing the numerical methods of the Adams-Bashforth and Trapezoidal methods with the exact solution for solving the Lotka-Volterra prey-predator model. These methods are evaluated for their ability to reliably and accurately solve the non-linearity of the model. Based on the results, both methods offer precise solutions, with the Adams-Bashforth method providing a more accurate approximation for short-term predictions and the Trapezoidal method demonstrating better stability for long-term simulations. The study utilizes data from lynx-rabbit and bat-moth interactions to assess the performance of these methods using software tools. For both models, the short-term predictions align closely with observed data, while long-term stability analyses reveal the strengths of the Trapezoidal method. The equilibrium and stability analyses offer critical insights into the long-term behavior and stability of the system. The predator population trails behind the prey population: a rise in prey numbers is followed by a delayed increase in predator numbers as predators consume more prey. The phase portraits show the regularity of these oscillations. The curves move counterclockwise: prey numbers increase when predator numbers are at their lowest, and prey numbers decrease at their highest. These insights are essential for understanding and predicting the dynamics of predator-prey interactions and have significant implications for ecological modeling and conservation strategies.

Long-term observations of a sponge in situ reveal a rich repertoire of contractile behaviors, including winter dormancy

Sponges are remarkably active animals with a range of behaviors that are broadly termed sneezes. Little is known about what triggers sneezes or how sneezes propagate in an animal that lacks either muscular or nervous systems. We explored the triggers of sponge behavior in situ in the demosponge Suberites concinnus. The placement of this tennis ball-sized sponge at the focal point of a camera array on an instrument platform in Barkley Sound, BC, Canada, provided a unique opportunity for our investigation. The observatory has a suite of environmental sensors measuring parameters such as photosynthetically active radiation (PAR), oxygen, turbidity, salinity, pressure, current speed, and temperature. An array of 8 cameras designed for 3D imaging was used to capture hourly images. Our findings revealed both long-term (annual) and short-term (daily) behaviors in S. concinnus. The sponge contracted for 2 mo each winter. In February, it gradually expanded and became very active with short-term full-body contractions each lasting 11 h through the summer. A meta-analysis of contraction behaviors in other species of sponge showed that contraction duration is a factor of sponge size and that all sponges contract faster than they expand. Invertebrates and fish were frequently in contact with the sponge, but no single interaction was found to correlate with patterns of sponge behavior. However, significant correlations between sponge behaviors and chlorophyll and turbidity were found using generalized additive mixed models. Our study underscores the dynamic nature of these sessile filter feeders and their responses to their environment.

The Impact of Violent Media on Aggressive Behavior

In contemporary society, advancements in technology and the proliferation of online social media have provided numerous channels for accessing video and gaming content. Despite these developments, the depiction of violence in videos and games remains a contentious issue due to its potential aggressive impact on users. The relationship between exposure to violent media and subsequent aggressive behavior is multifaceted, involving both internal factors (such as perceived aggression, trait anger, violent emotions, and implicit aggression) and external factors (including cultural differences, age of exposure, proximity to real-life violence, domestic violence, and life setbacks). Internal factors significantly influence how individuals process and react to violent media, potentially reinforcing aggressive tendencies. External factors further moderate these effects, with cultural context and early exposure playing crucial roles in shaping long-term behavior. To address the aggression stemming from violent media, a multi-faceted approach is necessary. This includes monitoring and regulating young individuals' media consumption, implementing media literacy programs, providing robust support systems for those facing domestic violence or significant life setbacks, and therapeutic interventions such as cognitive-behavioral therapy. Moreover, promoting cooperative gaming environments and culturally tailored interventions can enhance the effectiveness of these strategies. Ultimately, a comprehensive understanding of the interplay between internal predispositions and external influences is crucial for mitigating the negative societal impacts of violent media.

Tail probability bounds for acceptable random variables of partial sums and their application in linear models

Exponential probability inequalities play an important role in many parts of probability and statistics, offering a fundamental tool for tail probability bounding and modeling stochastic processes. The present work proposes a new exponential inequality for acceptable random variables. This class covers dependencies that are not embraced by the standard independence assumptions. Our results extend the theoretical perspective by placing sharper bounds on the above-mentioned variables, which tends to increase the accuracy of probabilistic modeling. Moreover, we study complete convergence in first-order autoregressive processes with acceptable innovations. The complete convergence framework gives further insights into the long-term behavior of the wide class of processes commonly used in time series analysis, econometrics, and other areas of applied research. In turn, our results on the influence of acceptable innovations on the properties of complete convergence establish bridges between theoretical probability inequalities and statistical applications. In addition, these contributions provide new tools in investigating the stability and predictability of the autoregressive models. These considerations consequently set up significant perspectives and enrich a developing body of research related to stochastic processes by reinforcing the theoretical framework as well as the methodological apparatus of probability theory.

Fundamentals of leadership development: a randomized pilot study to evaluate implementation of a leadership curriculum for diversity, equity, and inclusion.

The Fundamentals of Leadership Development (FLD) Curriculum was created to increase integration of diversity, equity, and inclusion (DEI) in leadership skills. The pilot FLD course was utilized 1) evaluate short-term impact of the curriculum, and 2) evaluate optimal delivery methods of curricular interventions on diversity in a leadership context in a randomized fashion. After IRB approval, the pilot FLD course was opened to all SAGES Committee members for enrollment. All participants had access to the same online modules and discussion forum, but were randomized either to a 4-week longitudinal or 2-day intensive didactic session. Participants were asked to assess the curricular content after each online module and provide overall course feedback on all sessions. This data was collected along with leadership experience, course participation, and course completion data. A total of 79 participants registered for the FLD course, with 55 (69.7%) of participants completing the course. Of those that registered, 46 (58.2%) self-identified as underrepresented in medicine, 32 (40.5%) self-identified with she/her/hers pronouns, and 45 (57.0%) held an institutional leadership position. Fifty-nine (74.6%) participants were willing to be randomized. Course engagement was higher in the intensive course with 64.1% and 48.7% participation over days 1 and 2, respectively. In the longitudinal course, participation dropped off every week from 70%, 47.5%, 35%, and 27.5%, throughout the 4-week course. Participants who accessed the online modules spent a median time of 3h and 34min.User confidence after completion of each individual module were "somewhat confident" and "completely confident" for almost all survey respondents on a 5-tier Likert scale. The pilot FLD course appealed to SAGES members in leadership roles and who identified as. URiM. Course engagement was higher in the intensive course. Long-term behavior changes after course completion will need to be assessed with additional qualitative interviews. (300/300 words).

Frequency Range Optimization for Linear Viscoelastic Characterization of Burger's Model

The linear viscoelastic behavior of materials is represented using mechanical models of choice, which are further utilized in different numerical investigations, such as finite element simulations and discrete element simulations. Burger's model is one of the widely adopted mechanical models and remains highly favored in contemporary research due to its multiple advantages. Specifically, it excels in representing long-term creep and stress relaxation behavior in a relatively simplified manner. Accurate identification of the long-term behavior for the viscoelastic material, particularly asphalt concrete, is crucial, as it serves as a key indicator of asphalt pavement performance over its service life. However, past research studies show that the parameters of Burger's model should be back-calculated from experimental data only within a limited range of frequency, otherwise, the parameters fail to represent the true material behavior. To the best of the authors’ knowledge, there is no approach for researchers to obtain the critical frequency range in which the experiments should be performed. Therefore, this study proposes a novel framework to find the critical frequency range to obtain appropriate model parameters of Burger's model, to better characterize the viscoelastic behavior of the materials. To examine the framework, asphalt concrete mixtures are used as examples in this study. Necessary laboratory tests including complex modulus tests and stress relaxation tests, are performed on two distinctive types of asphalt concrete mixtures. The generalized Maxwell model with different number of Maxwell chains are used to evaluate the performance of Burger's model. Furthermore, since commercially available finite element packages generally do not have a direct built-in Burger's model, the article shows a way of implementing Burger's model in finite element simulation. The simulations corresponding to the laboratory tests are carried out in both frequency domain and time domain to thoroughly evaluate the performance of Burger's model. The optimal frequency range of 0.1-20 Hz for the examined mixtures is found to significantly improve the accuracy of the descriptive master curve. The results also suggest that the generalized Maxwell model requires a minimum of four Maxwell chains to maintain good performance in accurately characterizing the behavior of asphalt mixtures. However, adding more Maxwell chains beyond a critical limit may not provide significant benefits. Finite element simulations demonstrate that the stress relaxation behavior predicted by the obtained Burger's model parameters aligns more closely with experimental data over longer time intervals. This makes Burger's model a strong choice for aiding in the design of simulations for studies focused on the long-term behavior of materials.

Boosting Acetylcholine Signaling by Cannabidiol in a Murine Model of Alzheimer's Disease.

Alzheimer's disease (AD) is a challenging medical issue that requires efficacious treatment options to improve long-term quality of life. Cannabidiol (CBD) is a cannabis-derived phytocannabinoid with potential health benefits, including reports from our laboratory and others showing a therapeutic role in the pre-clinical treatment of AD; however, the mechanisms whereby CBD affects AD progression remain undefined. Innate lymphoid cells (ILCs) are recently discovered immune cells that initiate and orchestrate inflammatory responses. ILC2, a sub-class of ILCs, is proposed to have a role in cognitive function via unknown mechanisms. In this present study, we explored whether CBD ameliorates AD symptoms via the enhancement of acetylcholine (ACh), a cholinergic neurotransmitter involved in cognition that may regulate ILC2. 5xFAD mice were chronically treated by inhalation of a formulation of broad-spectrum CBD for seven months. ACh production, ILC2s profile, brain histopathology, and long-term behavior were assessed. Together, our studies showed that long-term inhalation of CBD improved cognitive function and reduced senile plaques in a murine AD model, effects that were associated with enhanced ACh production and altered ILC2s distribution within the CNS. These findings indicate that inhaled CBD could offer a cost-effective, non-invasive, and effective treatment for managing AD. The beneficial effects of CBD inhalation may be linked to increased ACh production and an altered distribution of ILC2s, highlighting the need for further research in this area.

Long term properties of Nano-engineered temperature self-controlled concrete served for mass concrete structure

Due to the advantages of low-cost and superior electrical conductivity, Nano-carbon black (NCB) can endow hydraulic concrete with long-term and stable self-heating capacities at affordable costs, thus allowing active and intelligent temperature control for high-altitude and high-latitude dams. This study, for the first time, investigated the long-term mechanical behaviors, freeze-thaw resistance and impermeability of temperature self-controlled concrete (TSC). Moreover, the modification mechanisms of TSC were revealed with the help of mercury intrusion porosimetry (MIP), thermogravimetric analysis (TGA) and scanning electron microscope (SEM). Finally, the long-term performance and cost assessment of TSC are comprehensively evaluated by the entropy weight method. The results indicate that the incorporation of 4.5wt% NCB improves the compressive and splitting tensile strengths of TSC at 180 days by 17.4% and 7.9%, respectively, and shows an excellent response against impermeability and a slightly lower response against frost resistance. Besides, NCB accelerates the hydration degree and repairs the interfacial transition zone of TSC. The presence of NCB densifies the microstructures of the matrix and reduces the content of harmful pores by nearly 50%. Finally, TSC with 4.5wt% NCB is the optimal mixture that shows excellent comprehensive performances.

Long-term persistency of a strong non-dipole field in the South Atlantic

Earth’s magnetic field exhibits a dominant dipole morphology. Notwithstanding, significant deviations from the dipole are evident today, particularly the South Atlantic Anomaly (SAA), characterized by anomalously low-field intensity and high directional variability, diminishing the field’s shielding effect. To assess the persistence of SAA-like features over multimillion-year scales, we combine paleomagnetic data from Trindade Island (20°30’S, 29°22’W) with an evaluation of paleosecular variation (PSV) over the past 10 Myr. We employ synthetic models to explore how the position and intensity of magnetic flux patches at the core-mantle boundary can influence the long-term field behavior. Here we present results that reveal anomalous field signatures in the South Atlantic and the Atlantic-Pacific hemispheric asymmetries are enduring features, likely linked to a bottom-up control of PSV by the inner core’s heterogeneities but with contributions from mantle anomalies in the long-time range.

Thermo-hydro-mechanical modelling of the heterogeneous subsidence and swelling in the desiccation cracked clayey strata

Soil desiccation cracking as a consequence of severe environmental changes alters soil deformation mechanisms significantly. Therefore, this study aims to explore the effect of crack characteristics and environmental conditions on the heterogeneous deformation of desiccation-cracked soils using thermo-hydro-mechanical analyses. The model framework consists of balance equations, thermal, hydraulic, and mechanical constitutive equations, while the model scenarios were determined based on statistical analyses. The meteorological record of Qom city was used for three years, from 2015 to 2017, to capture long-term behaviour under wetting-drying cycles. Findings revealed that cracks extend the deformation range, potentially up to six times, with variation based on crack dimensions and spacing. Notably, narrower cracks experienced more pronounced deformation than wider ones. The cracked soil with a crack depth of 2.5 m showed 1.5 times higher swelling and subsidence than crack depth of 1 m. Furthermore, the wider cracks indicated a lower rate of increase in their dimensions compared to the initial state during drying. The investigation also highlights the mechanisms of soil surface shape due to swelling and shrinkage, resulting in concave and convex surfaces, respectively. The results provide new perspectives on the behaviour of fine-grained deposits in arid to semi-arid climates with deep groundwater levels.

Long-term coastal dynamics: The evolution of a mixed sediment mega-nourishment consisting of colliery spoil

Mega-nourishments, where large volumes of sediment are deposited on coastlines, are increasingly employed to manage shoreline erosion, yet our understanding of their long-term behaviour is limited by the fact that most current schemes are less than 15 years old. However, on the County Durham coast, 39 million m3 of coal spoil was tipped onto beaches between the late 1800s and 1993, acting as a de facto mixed sediment mega-nourishment. Our findings reveal key insights into the long-term dynamics of mega-nourishment schemes, including evidence of effective sediment dispersal around headlands into normally disconnected units of coast. Following cessation of tipping, shorelines retreated up to 12 m yr−1, with 150 m overall retreat in 12 years. Subsequently, retreat slowed but the present-day shoreline remains seaward of its 1860 position and is subject to ongoing coastal recession. We document significant fining of the deposited material in the years post deposition through abrasion and chemical breakdown. Furthermore, we show that the highest erosion rates now occur downdrift from the initial dump site, indicating that nourishment impacts migrate through time. These findings highlight the need for holistic and adaptive management approaches to mega-nourishment schemes, showing the behaviour of the nourishment to continually change in both location and magnitude as the system evolves. We demonstrate that mixed sediment mega-nourishments can be a cost-effective and durable solution to mitigate erosive losses, even in the absence of a planned approach to the location or composition of deposited sediment. Our results suggest that lessons from this historical intervention can inform the design and management of future mega-nourishment schemes, particularly in mixed sediment environments.

Long-Term Physical Activity Behavior Change in Pulmonary Rehabilitation: Promoting Motivation.

Long-Term Physical Activity Behavior Change in Pulmonary Rehabilitation: Promoting Motivation.

Sustainability Awareness and Behavior of Management Accounting Students: Basis for Course Activity Development

Sustainability refers to both the planet’s health and humanity’s future well-being, encompassing actions humans take to prevent the depletion of natural resources. Education for Sustainable Development (ESD) plays a vital role in course curricula by helping students develop critical thinking, decision-making, socio-emotional, and behavioral skills. This study examined the awareness and behavior of BS Management Accounting (BSMA) students regarding the three pillars of sustainability as well as the relationship between sustainability education and their awareness and behavior. Using the Knowledge-Attitudes-Practices (KAP) and Knowledge-Attitude-Behavior (KAB) frameworks, this quantitative descriptive research collected data from 349 out of 399 BSMA students (87.47% participation rate) enrolled during SY 2023–2024 at the University of Saint Louis, Northern Philippines. The results revealed that students were generally aware of sustainability and exhibited positive attitudes toward sustainable practices. Enrollment in the SASA 1013 course significantly increased sustainability awareness, but neither year level nor course enrollment had a significant impact on actual sustainability behavior. This study offers insights into the relationship between students’ sustainability awareness and their behavior across the three sustainability pillars. The novelty of this research lies in its focus on BSMA students and the specific role of the SASA 1013 course in fostering sustainability awareness. The study concludes with recommendations for curriculum development and policy initiatives to further promote students’ long-term sustainability awareness and behavior.

A Novel Deep Learning Model for Stock Prediction Integrating Historical Prices, Core Volatility Trends and Financial News

Accurate stock price forecasting is crucial for investors and analysts aiming to make informed decisions and mitigate risks in financial markets. While deep learning models have proven effective in identifying complex patterns in quantitative data, they often struggle to account for non-quantitative factors such as corporate events, market sentiment, and regulatory changes that can cause unpredictable stock price movements. To address this challenge, an ensemble model is introduced that integrates historical price data, financial news, and stock fundamentals to predict next-day stock prices. The model combines one-dimensional Convolutional Neural Networks (1D CNNs), Long Short-Term Memory networks (LSTMs), and Gated Recurrent Units (GRUs), applied independently to each data stream and concurrently as a unified ensemble, to capture both short-term and long-term market behaviors. NVIDIA (NVDA) stock was selected for testing due to its high volatility and rapid price fluctuations, presenting a challenging case for predictive modeling. Using data spanning from April 2014 to March 2024, the model achieved a coefficient of determination (R²) of 0.983 and a mean absolute error (MAE) of $12.72. These results suggest that the ensemble approach effectively captures both quantitative and qualitative factors, making it a promising tool for improving stock price prediction in volatile market conditions.