Integrating Field Monitoring and Numerical Modeling to 3 Evaluate Performance of a Levee under 4 Climatic and Tidal Variations

Several short-duration and extreme hydraulic loadings impose time-dependent variably saturated seepage conditions on earthen 7 slopes and embankments. Difficulty assigning appropriate input parameters and lack of full-scale validation are among the main factors 8 introducing uncertainty and lack of confidence when performing numerical transient seepage analysis. This case study demonstrates how 9 to effectively use field-monitoring data to improve the numerical analysis of a levee under climatic and tidal variations. The case study 10 includes a silty sand setback levee located near Seattle. An array of tensiometers and soil moisture sensors installed within the levee’s embank11 ment and foundation, along with a nearly real-time data acquisition system, were used to collect and process the in situ data for a period of 12 about 15 months. Climatic and weather data, including precipitation, temperature, humidity, and wind speed, were collected from a weather 13 station at the site, and tidal water fluctuations were monitored using a water level sensor. The field-measured matric suction and water content 14 were used along with a suction stress–based representation of effective stress to compute suction stress and effective stress profiles versus time. 15 A finite-element model of transient seepage under saturated-unsaturated conditions was developed. The numerical model was calibrated and 16 then validated using the measured pore-water pressures and the piezometric surface. The application of the numerical model was illustrated by 17 modeling the seepage and stability of the levee during a 100-year flood event. The results highlight the need to consider climatic variables and 18 soil–atmosphere interaction when performing transient seepage analysis. DOI: 10.1061/(ASCE)GT.1943-5606.0002134. © 2019 American 19 Society of Civil Engineers

Practical Use of ChatGPT in Psychiatry for Treatment Plan and Psychoeducation

Artificial Intelligence (AI) has revolutionized various fields, including medicine and mental health support. One promising application is ChatGPT, an advanced conversational AI model that uses deep learning techniques to provide human-like responses. This review paper explores the potential impact of ChatGPT in psychiatry and its various applications, highlighting its role in therapy and counseling techniques, self-help and coping strategies, mindfulness and relaxation techniques, screening and monitoring, education and information dissemination, specialized support, group and family support, learning and training, expressive and artistic therapies, telepsychiatry and online support, and crisis management and prevention. While ChatGPT offers personalized, accessible, and scalable support, it is essential to emphasize that it should not replace the expertise and guidance of qualified mental health professionals. Ethical considerations, such as user privacy, data security, and human oversight, are also discussed. By examining the potential and challenges, this paper sheds light on the responsible integration of ChatGPT in psychiatric research and practice, fostering improved mental health outcomes

Banishayban in the Islamic era

Genealogists have related BaniShayban origin from Mosni-bin HarithaShaybani to prophet’s 19th ancestor called Nazar. Mosni-bin HarithaShaybani was a significant character who played a basic role in the events of early Islam. He managemd to earn reputation among Arabs due to his victory over the army of Iran in Zuqar battle, so that the first and second caliphs let him attack Iranian borders with other Islamic commanders.In addition to Zuqar battle under commandment of Mosni-bin HarithaShaybani, BaniShayban tribe had several battles with Shahrbaraz, Iranian self-styled king, including battle of chains and battle of Ullais during 11 to 14 A.H years. They participated in battle of the bridge with Abu Obadiah, another commander of the Muslim Arabs. They were also present at the battle of Boveib. The commander of Shaybanis attended the battle of al-Qādisiyyah with several injuries on his body and wished to participate in the battle of Jalula, but his life came to its end before that.In the days of Imam Ali, Shaybanis helped him and were his commanders, particularly in the  battle of Siffin, because of being allied with the descendants of Abu Talib. Although some of them stood against Imam Ali, some others lost their lives guilty of friendship with him. They acquired high positions at the time of Umayyad and Bani Abbas and were even appointed in Armenia.The most important question is whether Shaybanis had any relationships with caliphs in early Islam; what role did they play in early Muslim conquests; and what positions were they assigned in the early centuries of Islam? The present study investigates the role of Shaybanis in Islamic era, particularly during early Islam as well as Umayyad and Bani Abbas reign.Keywords: BaniShayban, Mosni-bin Haritha, Iranian army, Umayyad, Bani Abba

Interdependencies Between Wildfire-Induced Alterations in Soil Properties, Near-Surface Processes, and Geohazards

The frequency, severity, and spatial extent of destructive wildfires have increased in several regions globally over the past decades. While direct impacts from wildfires are devastating, the hazardous legacy of wildfires affects nearby communities long after the flames have been extinguished. Post-wildfire soil conditions control the persistence, severity, and timing of cascading geohazards in burned landscapes. The interplay and feedback between geohazards and wildfire-induced changes to soil properties, land cover conditions, and near-surface and surface processes are still poorly understood. Here, we synthesize wildfire-induced processes that can affect the critical attributes of burned soils and their conditioning of subsequent geohazards. More specifically, we discuss the state of knowledge pertaining to changes in mineralogical, hydraulic, mechanical, and thermal properties of soil due to wildfire with a focus on advances in the past decade. We identify how these changes in soil properties alter evapotranspiration, interception, sediment transport, infiltration, and runoff. We then link these alterations to the evolution of different geohazards, including dry raveling, erosion, rockfalls, landslides, debris flows, and land subsidence. Finally, we identify research gaps and future directions to advance knowledge on how wildfires control the evolution of various earth surface processes and geohazards over time

Artificial Intelligence in Fetal Resting-State Functional MRI Brain Segmentation: A Comparative Analysis of 3D UNet, VNet, and HighRes-Net Models

Introduction: Fetal resting-state functional magnetic resonance imaging (rs-fMRI) is a rapidly evolving field that provides valuable insight into brain development before birth. Accurate segmentation of the fetal brain from the surrounding tissue in nonstationary 3D brain volumes poses a significant challenge in this domain. Current available tools have 0.15 accuracy. Aim: This study introduced a novel application of artificial intelligence (AI) for automated brain segmentation in fetal brain fMRI, magnetic resonance imaging (fMRI). Open datasets were employed to train AI models, assess their performance, and analyze their capabilities and limitations in addressing the specific challenges associated with fetal brain fMRI segmentation. Method: We utilized an open-source fetal functional MRI (fMRI) dataset consisting of 160 cases (reference: fetal-fMRI - OpenNeuro). An AI model for fMRI segmentation was developed using a 5-fold cross-validation methodology. Three AI models were employed: 3D UNet, VNet, and HighResNet. Optuna, an automated hyperparameter-tuning tool, was used to optimize these models. Results and Discussion: The Dice scores of the three AI models (VNet, UNet, and HighRes-net) were compared, including a comparison between manually tuned and automatically tuned models using Optuna. Our findings shed light on the performance of different AI models for fetal resting-state fMRI brain segmentation. Although the VNet model showed promise in this application, further investigation is required to fully explore the potential and limitations of each model, including the HighRes-net model. This study serves as a foundation for further extensive research into the applications of AI in fetal brain fMRI segmentation

Toward impact-based monitoring of drought and its cascading hazards

Growth in satellite observations and modelling capabilities has transformed drought monitoring, offering near-real-time information. However, current monitoring efforts focus on hazards rather than impacts, and are further disconnected from drought-related compound or cascading hazards such as heatwaves, wildfires, floods and debris flows. In this Perspective, we advocate for impact-based drought monitoring and integration with broader drought-related hazards. Impact-based monitoring will go beyond top-down hazard information, linking drought to physical or societal impacts such as crop yield, food availability, energy generation or unemployment. This approach, specifically forecasts of drought event impacts, would accordingly benefit multiple stakeholders involved in drought planning, and risk and response management, with clear benefits for food and water security. Yet adoption and implementation is hindered by the absence of consistent drought impact data, limited information on local factors affecting water availability (including water demand, transfer and withdrawal), and impact assessment models being disconnected from drought monitoring tools. Implementation of impact-based drought monitoring thus requires the use of newly available remote sensors, the availability of large volumes of standardized data across drought-related fields, and the adoption of artificial intelligence to extract and synthesize physical and societal drought impacts.</p

Synergistic Approach: Photobiomodulation, Neuromodulation, and Drug Therapy in Neuropsychiatry. A Promising Strategy to Enhance PBM Adoption and Neurotherapy Efficacy

Photobiomodulation (PBM) is an effective method for treating neuropsychiatric diseases, yet its universal acceptance and utilization remain constrained. In this Letter to the Editor/Expert Opinion, we address the challenges confronting PBM researchers and pioneers, striving to establish universal confidence in its exclusive application for neuropsychiatric patient care. Despite encouraging animal experiments and selecting positive human clinical trial outcomes, PBM&rsquo;s widespread acceptance of PBM is hindered by factors including limited clinical studies and clashes with established therapies, such as drug therapy and psychotherapy.To overcome these obstacles and broaden PBM&rsquo;s adoption and application of PBM in neuropsychiatry, we propose a combinatorial therapy approach. By integrating PBM with interventions such as Cognitive Behavioral Therapy (CBT) or drug therapy, a cumulative effect can be attained, benefiting both patients and therapists. Patients gain access to diverse treatment options and experience synergistic effects of combined therapies, thereby enhancing outcomes. Therapists benefit from expanded intervention choices and improved quality of patient care.This study introduces a novel strategy of amalgamating PBM with recognized interventions, such as CBT and drug therapy, to address existing challenges. This combined approach offers a practical solution to augment PBM acceptance and usage in the realm of neuropsychiatry.To endorse this strategy, a shift in the research direction is imperative. Future studies should investigate the amalgamated use of PBM with other neurointerventions, such as CBT or drug therapy. Robust clinical trials contrasting groups like &ldquo;PBM + CBT&rdquo; and &ldquo;PBM (sham) + rTMS&rdquo; are vital to persuade clinicians and patients toward embracing combined PBM therapies.Although PBM&rsquo;s eventual autonomy as a neuropsychiatric treatment is an overarching goal, the present combination therapy approach proves practical, inevitable, and mutually beneficial. By bridging conventional therapies with PBM, this strategy may facilitate wider acceptance and utilization in neuropsychiatry

Nanomedicine for COVID-19: the role of nanotechnology in the treatment and diagnosis of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the recent outbreak of coronavirus 2019 (COVID-19). Although nearly two decades have passed since the emergence of pandemics such as SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), no effective drug against the CoV family has yet been approved, so there is a need to find newer therapeutic targets. Currently, simultaneous research across the globe is being performed to discover efficient vaccines or drugs, including both conventional therapies used to treat previous similar diseases and emerging therapies like nanomedicine. Nanomedicine has already proven its value through its application drug delivery and nanosensors in other diseases. Nanomedicine and its components can play an important role in various stages of prevention, diagnosis, treatment, vaccination, and research related to COVID-19. Nano-based antimicrobial technology can be integrated into personal equipment for the greater safety of healthcare workers and people. Various nanomaterials such as quantum dots can be used as biosensors to diagnose COVID-19. Nanotechnology offers benefits from the use of nanosystems, such as liposomes, polymeric and lipid nanoparticles, metallic nanoparticles, and micelles, for drug encapsulation, and facilitates the improvement of pharmacological drug properties. Antiviral functions for nanoparticles can target the binding, entry, replication, and budding of COVID-19. The toxicity-related inorganic nanoparticles are one of the limiting factors of its use that should be further investigated and modified. In this review, we are going to discuss nanomedicine options for COVID-19 management, similar applications for related viral diseases, and their gap of knowledge

Effect of Elevated Temperatures on Lateral Earth Pressures in Unsaturated Soils

Near-surface unsaturated soils can be exposed to elevated temperatures due to soil-atmospheric interactions under drought events, wildfires, heatwaves, and warm spells, or the heat induced by emerging geotechnical and geo-environmental technologies such as geothermal boreholes and thermally active earthen systems. Elevated temperatures can affect the hydro-mechanical characteristics of unsaturated soils, which in turn can alter lateral earth pressures developed in the backfill soil. The main objective of this study is to quantify the effect of elevated temperatures on active and passive earth pressures of unsaturated soils. For this purpose, the paper presents the derivation of an analytical framework to extend Rankine’s earth pressure theory to account for the effect of temperature under hydrostatic conditions. The equations are derived by incorporating the effect of temperature into the soil water retention curve and a suction stress-based effective stress representation. The proposed effective stress equation considers the temperature-induced changes in the contact angle, surface tension, and enthalpy of immersion. To investigate the impact of temperature on active and passive earth pressures, the proposed method is then used in a set of parametric studies to determine active and passive earth pressure profiles for three hypothetical soils of clay, silt, and sand at different temperatures. Results suggest that elevated temperatures can cause variation in active and passive earth pressures for all the soils considered. The findings of this study can contribute toward analyzing earth retaining structures subjected to elevated temperatures

A model for ultimate bearing capacity of piles in unsaturated soils under elevated temperatures

Geo-energy applications such as energy piles can expose unsaturated, deep foundation soils to elevated temperatures. This paper presents a closed-form equation for the ultimate bearing capacity of piles in unsaturated soils subject to elevated temperatures under drained conditions. For this purpose, a temperature-dependent effective stress model was incorporated into calculations of skin resistance and end bearing resistance of piles. The proposed temperature-dependent model is an extension of the modified β method for determining the ultimate pile bearing capacity of unsaturated soils under drained conditions. Employing the proposed model, a parametric study was carried out to evaluate the ultimate pile bearing capacity for hypothetical clay and silt soils at temperatures ranging from 25 °C to 55 °C. For both clay and silt, the results indicated that the ultimate pile bearing capacity varies with an increase in temperature. Different trends with temperature were observed for clay and silt. A monotonic increase in pile resistance was observed in clays. For silt, the pile resistance increased at relatively low matric suction whereas it decreased at higher matric suctions