Response Of System Research Articles

Effect of connection modes on seismic responses of a diaphragm wall-subway station system subjected to mainshock-aftershock sequences

Most existing seismic behavior analyses of underground structures simply consider a single earthquake. Meanwhile, the diaphragm wall, as an enclosure structure, is regarded as a security reserve and is always ignored in current studies. Herein, the characteristics of a diaphragm wall-subway station system with different connection modes under earthquake sequences were investigated using numerical simulation. The damage degree of the structural component was calculated through quantitative analysis of the tensile damage picture. The seismic damage level of the station structure was evaluated to characterize the damage transition effect induced by the aftershock according to the inter-story drift angle. Moreover, an empirical model for predicting the inter-story drift angle with respect to different peak accelerations was proposed. The research results indicate that the effect of the connection mode between the sidewall and the diaphragm wall on the damage evolution and deformation behavior of the station structure is significant. Compared with that of the compound wall structure, the seismic damage to the sidewall of the composite wall structure is much less severe, but the slabs become more vulnerable and suffer more severe damage. The accumulative damage triggered by aftershocks aggravates the extent of structural damage and even leads to damage transition. The conclusions illustrated in this paper contribute to a better understanding of the seismic resistance design of diaphragm wall-subway station systems under earthquake sequences.

Collaboration for implementation of decentralisation policy of multi drug-resistant tuberculosis services in Zambia

BackgroundMulti-drug-resistant tuberculosis (MDR-TB) infections are a public health concern. Since 2017, the Ministry of Health (MoH) in Zambia, in collaboration with its partners, has been implementing decentralised MDR-TB services to address the limited community access to treatment. This study sought to explore the role of collaboration in the implementation of decentralised multi drug-resistant tuberculosis services in Zambia.MethodsA qualitative case study design was conducted in selected provinces in Zambia using in-depth and key informant interviews as data collection methods. We conducted a total of 112 interviews involving 18 healthcare workers, 17 community health workers, 32 patients and 21 caregivers in healthcare facilities located in 10 selected districts. Additionally, 24 key informant interviews were conducted with healthcare workers managers at facility, district, provincial, and national-levels. Thematic analysis was employed guided by the Integrative Framework for Collaborative Governance.FindingsThe principled engagement was shaped by the global health agenda/summit meeting influence on the decentralisation of TB, engagement of stakeholders to initiate decentralisation, a supportive policy environment for the decentralisation process and guidelines and quarterly clinical expert committee meetings. The factors that influenced the shared motivation for the introduction of MDR-TB decentralisation included actors having a common understanding, limited access to health facilities and emergency transport services, a shared understanding of challenges in providing optimal patient monitoring and review and their appreciation of the value of evidence-based decision-making in the implementation of MDR- TB decentralisation. The capacity for joint action strategies included MoH initiating strategic partnerships in enhancing MDR-TB decentralisation, the role of leadership in organising training of healthcare workers and of multidisciplinary teams, inadequate coordination, supervision and monitoring of laboratory services and joint action in health infrastructural rehabilitation.ConclusionsPrincipled engagement facilitated the involvement of various stakeholders, the dissemination of relevant policies and guidelines and regular quarterly meetings of clinical expert committees to ensure ongoing support and guidance. A shared motivation among actors was underpinned by a common understanding of the barriers faced while implementing decentralisation efforts. The capacity for joint action was demonstrated through several key strategies, however, challenges such as inadequate coordination, supervision and monitoring of laboratory services, as well as the need for collaborative efforts in health infrastructural rehabilitation were observed. Overall, collaboration has facilitated the creation of a more responsive and comprehensive TB care system, addressing the critical needs of patients and improving health outcomes.

Temperature Control System Design Via Fuzzy PID

This paper investigates the integration of Fuzzy Logic with PID (Proportional, Integral, Derivative) controllers to enhance the performance of temperature control systems. Traditional PID controllers, widely used in various applications, often encounter difficulties with nonlinear, time-varying, and uncertain systems, resulting in performance issues like oscillations and overshoots. To mitigate these challenges, the adoption of Fuzzy PID control, which improves adaptability, robustness, and responsiveness by incorporating fuzzy logic into the control mechanism. The study involves simulations using Simulink to compare three distinct control models: conventional PID, standalone Fuzzy Control, and the hybrid Fuzzy PID Control across standardized control scenarios. Our results show that Fuzzy PID controllers significantly outperform traditional methods, especially in complex environments lacking precise mathematical modeling. The enhanced system response times and stability demonstrated by Fuzzy PID controllers suggest substantial potential for broader application across diverse industries, promising considerable improvements in operational efficiency and reliability.

Soundbox-based sound insulation measurement of composite panels with viscoelastic damping

Sound transmission loss (STL), an essential index for assessing the sound insulation performance of composite laminated structures, typically relies on experimental methods to measure. The soundbox method (SBM), a straightforward technique for measuring the STL, is sensitive to microphones’ positions. Within the framework of the Chebyshev-Ritz method, a semi-analytical vibro-acoustic model extended to composite laminated panels with viscoelastic damping (VED) is proposed for the first time. Based on the developed simplified layer-wise theory, the panel is modeled using three layers: the top face layer, the VED layer, and the bottom face layer. A closed cavity is added to the model as the soundbox enclosure used in actual measurements. By employing the Hamilton's principle, the governing equation for the coupling system is derived, and the vibration and internal acoustic responses of the coupling system are calculated. A discretization strategy is introduced to address the frequency-dependent properties of the VED layer, avoiding the need to reconstruct the stiffness matrix at each frequency. To obtain the STL of the panel, sound pressures at external measurement points are calculated based on the Rayleigh integral. The proposed model is validated against numerical results from finite element analyses. The influences of the microphone position inside and outside the cavity on the measured STL are studied. Furthermore, parametric studies over the microphones' positions are performed to enhance the SBM-based evaluation of the composite panel's sound insulation performance. The optimal locations for two internal microphones and one external microphone are recommended. Finally, experimental studies are carried out to guide the implementation of the SBM.

Aquifer system deformation in the San Luis Valley: A new framework for modeling subsidence in agricultural regions

The San Luis Valley (SLV), Colorado, is challenged with implementing sustainable groundwater management in the face of increasing surface water scarcity due to climate change. Groundwater extraction in unconsolidated aquifers such as the SLV can cause cm-scale subsidence and rebound. This study utilizes Interferometric Synthetic Aperture Radar (InSAR) data, validated by Global Navigation Satellite System (GNSS) measurements, to measure subsidence and analyze the groundwater dynamics that cause it. Addressing the challenges of phase decorrelation and data gaps, notably from September 2018 to April 2019, we adopted a modified DS-interpolation algorithm, alongside a Singular Spectrum Analysis (SSA)-based gap filling technique. Furthermore, we enhanced the temporal resolution of groundwater level data through the Theis curve interpolation. These methodologies enabled the integration of observational well data with satellite measurements to calibrate a one-dimensional deformation model, capturing both the elastic and inelastic responses of the aquifer system. Our investigation, spanning 2015 to 2021, reveals both seasonal and long-term subsidence, with the confined aquifer section experiencing up to 1 cm/year of subsidence alongside notable seasonal fluctuations. The methodology presented here provides a path to model subsidence in regions with sparse groundwater level and noisy InSAR data. It also provides valuable insights for developing effective water management strategies in the SLV.

Failure criterion and seismic fragility evaluation of isolated nuclear power plant piping system using BP neural network

The pipeline connecting the isolated nuclear island and the non-isolated turbine building is prone to significant relative displacements during intensive earthquakes. Generally, elbows closest to the isolation layer are considered to be at particularly high risk of seismic damage. The failure criterion is the critical part in determining the damage state of elbows throughout the loading cycle. Therefore, in this study, a three-tier, four-category failure criterion was firstly proposed in response to the damage patterns of elbows. A BP neural network model was subsequently developed using extensive simulation data derived from a verified numerical model, accompanied by influence analysis of the three failure indices. Finally, a fragility evaluation was conducted based on the seismic response of the piping system, and a comparison is made between the new criterion and the existing ones. The results indicate that the new failure criterion demonstrates comprehensiveness and safety, enabling a more detailed division of damage before elbow failure and providing more conservative estimates upon failure occurrence. Additionally, the study finds that under the current design of nuclear power plants, elbows across isolation layers fail to meet the requirements for safe shutdown earthquakes in certain directions. By adjusting the elbow parameters, the resistance of the elbows to damage under seismic conditions can be improved to some extent.

'The Lost Peace': Evidencing the Syndemic Relationship between Neglected Tropical Diseases and Mental Distress in Liberia.

Neglected Tropical Diseases (NTDs) are a group of chronic infectious diseases of poverty affecting over one billion people globally. Intersections of NTDs, disability, and mental ill-health are increasingly evidenced but are rarely studied from a mixed-methods perspective. Here, we advance syndemic understandings by further assessing and contextualising the syndemic relationship between NTDs (particularly their associated disability) and mental distress in Liberia. Participatory qualitative methods, including body mapping (56 participants), social mapping (28 participants), and in-depth interviews (12) provided space for persons affected by NTDs to narrate their experiences. Simultaneously, 201 surveys explored experiences of common mental health conditions among persons affected by skin NTDs. An intersectionality approach was applied within the analysis for both qualitative and quantitative methods informed by Meyer's minority stress model, adapted for NTDs. Qualitative data was analysed thematically and gender-disaggregated, univariable and multivariable analyses were applied to survey data for the outcome measures depression (PHQ-9) and anxiety (GAD-7). Disability was associated with higher levels of depression and anxiety (p < 0.001). An interaction between disability and being a women increased incidence risk ratio of depression (p < 0.001). In alignment with qualitative findings, persons affected experienced additional generalised (financial concerns), external (experience of stigma) and internal (experience of pain and physical symptoms) minority stressors, to varying degrees, which contributed towards their mental distress, and mental health conditions. These findings were used to co-develop a syndemic-informed person-centred health system response to address the suffering associated with NTDs and mental distress, including a focus on strengthening relationships between formal and informal community health actors and the broader health system.

A hybrid Bi-level management framework for caching and communication in Edge-AI enabled IoT

The proliferation of IoT devices has led to a surge in network traffic, resulting in higher energy usage and response delays. In-network caching has emerged as a viable solution to address this issue. However, caching IoT data faces two key challenges: the transient nature of IoT content and the unknown spatiotemporal content popularity. Additionally, the use of a global view on dynamic IoT networks is problematic due to the high communication overhead involved. To tackle these challenges, this paper presents an adaptive management approach that jointly optimizes caching and communication in IoT networks using a novel bi-level control method called BC3. The approach employs two types of controllers: a global ILP-based optimal controller for long-term timeslots and local learning-based controllers for short-term timeslots. The long-term controller periodically establishes a global cache policy for the network and sends specific cache rules to each edge server. The local controller at each edge server solves the joint problem of bandwidth allocation and cache adaptation using deep reinforcement learning (DRL) technique. The main objective is to minimize energy consumption and system response time with utilizing the global and local observations. Experimental results demonstrate that the proposed approach increases cache hit rate by approximately 12% and uses 11% less energy compared to the other methods. Increasing the cache hit rate can lead to a reduction in about 17% in response time for user requests. Our bi-level control approach offers a promising solution for leveraging the network's global visibility while balancing communication overhead (as energy consumption) against system performance. Additionally, the proposed method has the lowest cache eviction, around 19% lower than the lowest eviction of the other comparison methods. The eviction metric is a metric to evaluate the effectiveness of adaptive caching approach designed for transient data.

Human exposure to aerosol from indoor gas stove cooking and the resulting cardiovascular system responses

The effect of cooking aerosol on the human heart was investigated in this study. The heart rate and blood pressure of 33 healthy adults were monitored before, exactly after, and two hours post-exposure (30 minutes, 60 minutes, 90 minutes, and 120 minutes after cooking). One hundred twenty grams of ground beef was fried in sunflower oil for twenty minutes using a gas stove without ventilation. Ultrafine particles, indoor temperature, relative humidity, carbon dioxide, oil, and meat temperatures were monitored during the experiment. The average particle emission rate (S) and average decay rate (a+k) for meat frying were found to be 2.09×1013 (SD=3.94 ×1013, R2=0.98, P <0.0001) particles/min, and 0.055 (SD=0.019, R2=0.91, P <0.0001) particles/min, respectively. No statistically significant changes in diastolic blood pressure (DBP) and heart rate (HR) were observed. The average systolic blood pressure (SBP) statistically significantly increased from 98 mmHg (before the exposure) to 106 mmHg 60 minutes after the exposure. The results suggested that frying emission statistically significantly impacted blood pressure.

Exploring the Relationship Between Voice Disorders in Indian Classical Music and the Guru-Shishya Parampara Through an Understanding of the Autonomic Nervous System

ABSTRACT The Guru-Shishya Parampara (GSP), translated as the teacher-student tradition, is a lineage-based oral tradition in Indian Classical Music (ICM). This study explores the relationship between GSP’s traditional obedience-authority dynamic and prevalent voice disorders experienced by ICM practitioners. Combining Constructivist Grounded Theory document analysis and a narrative literature review, the research investigates how disciplinarian tendencies and power differentials in authoritarian implementations of the GSP may contribute to or reinforce voice disorders resulting from psychological strain. Adopting the Indigenous Research Paradigm, the study prioritizes insights from ICM practitioners’ lived experiences within the cultural context of ICM within the analysis. A narrative review of existing literature on the links between autonomic nervous system responses associated with psychological stressors and voice disorders is discussed to further understand the impact of authoritarian GSPs on singers’ voices. Literature on compassion is additionally explored to discuss potential solutions to address the identified issues. Through this approach, the study offers insights into the complex interactions between power dynamics, psychological strain, and voice disorders within obedience-expectant GSPs, aiming to contribute to the development of effective interventions, highlighting that which already exists within ICM culture, to promote vocal health and overall well-being in this ancient and culturally significant tradition.

Estimate for the Bulk Viscosity of Strongly Coupled Quark Matter Using Perturbative QCD and Holography.

Modern hydrodynamic simulations of core-collapse supernovae and neutron-star mergers require knowledge not only of the equilibrium properties of strongly interacting matter, but also of the system's response to perturbations, encoded in various transport coefficients. Using perturbative and holographic tools, we derive here an improved weak-coupling and a new strong-coupling result for the most important transport coefficient of unpaired quark matter, its bulk viscosity. These results are combined in a simple analytic pocket formula for the quantity that is rooted in perturbative quantum chromodynamics at high densities but takes into account nonperturbative holographic input at neutron-star densities, where the system is strongly coupled. This expression can be used in the modeling of unpaired quark matter at astrophysically relevant temperatures and densities.

Design and Implementation of Remote Lab PID Controller Experiment Based on IoT

The education sector has increasingly embraced distance education to ensure a safe and uninterrupted learning process, especially in wars or epidemics. This paper focuses on designing and implementing a PID (Proportional-Integral-Derivative) controller experiment in remote laboratories utilizing the Internet of Things (IoT). Also, a laboratory experiment was developed using a naturally unstable system, specifically a cart-inverted pendulum. The experiments aim to enhance students' understanding of PID controller tuning within a real-world context. This system was chosen due to its dual motion characteristics, with a linear motion for the cart and a circular motion for the pendulum. Two controllers were designed and implemented for the system to enable control and feedback. Additionally, the Blynk platform was integrated into the experiment setup, allowing for real-time visualization of the system's response, control of PID parameters, and the ability to view the video stream via platforms like Skype. For remote connectivity, NodeMCU, an IoT development board, controlled the pendulum, collected system parameters, and transmitted them to the cloud through the Internet. Moreover, the sensors and the system were mathematically modeled, and their transfer functions were extracted. That allows the students to do the PID experiment theoretically and practically and compare the results. This complete setup enables local and remote access to the experiment, ensuring students can experiment regardless of their physical location. As a result of the study, designing and implementing a remote laboratory PID controller experiment utilizing IoT technology provides students with an innovative and immersive learning experience.

Healthcare professionals' views on the response of the primary healthcare system of Sarajevo Canton in the conditions of the COVID-19 pandemic

Uvod: Pandemija COVID-19 pokazala je nedostatke zdravstvenih sustava na globalnoj razini, a najveći utjecaj pandemije doživjeli su zdravstveni profesionalci koji rade u izravnom kontaktu s oboljelim pacijentima. Cilj: Cilj je rada ispitati stavove i mišljenja zdravstvenih profesionalaca koji rade u ruralnim i urbanim područjima Kantona Sarajevo o mjerama zaštite na radnom mjestu, zdravstvenom kadru i organizaciji rada tijekom pandemije COVID-19 od strane nadležnih institucija. Metode: Ispitani su zdravstveni profesionalci koji rade u urbanim i ruralnim područjima u Kantonu Sarajevo koristeći anonimne anketne upitnike čija je osnova bila check lista za provjeru spremnosti zdravstvenih ustanova za pandemiju COVID-19 koju je kreirala Svjetska zdravstvena organizacija. Kriterij za uključivanje u studiju bio je dobrovoljni pristanak ispitanika da sudjeluju u istraživanju. Rezultati: Analiza ustanove i spremnosti sustava na COVID-19 pandemiju ukazala je na mnoge nedostatke zdravstvenog sustava u Kantonu Sarajevo. Utvrđen je umjeren rizik kod odgovora zdravstvenog sustava primarne zdravstvene zaštite na području cijelog Kantona, s tim da je značajno veći rizik utvrđen u urbanim dijelovima Kantona. Utvrđena je značajna statistička razlika u ukupnom riziku (p &amp;lt; 0,001). Na skali od 8 do 40, ukupan rizik u urbanim sredinama iznosio je 21,95 (19 – 25), dok je u ruralnim sredinama iznosio 19,3 (16 – 23). Zaključak: Uvažavanje stavova i mišljenja zdravstvenih profesionalaca koji rade u izravnom kontaktu s pacijentima trebalo bi biti temelj za donošenje odluka u javnoj zdravstvenoj politici. U našoj se studiji, ali i ranije opisanim studijama, uočava pojam adaptabilnosti koji ukazuje na to da se, prema prijašnjim iskustvima, trebaju napraviti korektivne mjere kako bi zdravstveni sustav bio spreman za moguće epidemije i pandemije u budućnosti.

Development of a Neural Network for Target Gas Detection in Interdigitated Electrode Sensor-Based E-Nose Systems.

In this study, a neural network was developed for the detection of acetone, ethanol, chloroform, and air pollutant NO2 gases using an Interdigitated Electrode (IDE) sensor-based e-nose system. A bioimpedance spectroscopy (BIS)-based interface circuit was used to measure sensor responses in the e-nose system. The sensor was fed with a sinusoidal voltage at 10 MHz frequency and 0.707 V amplitude. Sensor responses were sampled at 100 Hz frequency and converted to digital data with 16-bit resolution. The highest change in impedance magnitude obtained in the e-nose system against chloroform gas was recorded as 24.86 Ω over a concentration range of 0-11,720 ppm. The highest gas detection sensitivity of the e-nose system was calculated as 0.7825 Ω/ppm against 6.7 ppm NO2 gas. Before training with the neural network, data were filtered from noise using Kalman filtering. Principal Component Analysis (PCA) was applied to the improved signal data for dimensionality reduction, separating them from noise and outliers with low variance and non-informative characteristics. The neural network model created is multi-layered and employs the backpropagation algorithm. The Xavier initialization method was used for determining the initial weights of neurons. The neural network successfully classified NO2 (6.7 ppm), acetone (1820 ppm), ethanol (1820 ppm), and chloroform (1465 ppm) gases with a test accuracy of 87.16%. The neural network achieved this test accuracy in a training time of 239.54 milliseconds. As sensor sensitivity increases, the detection capability of the neural network also improves.

Flipbook-ENA: Towards a dynamic Ecological Network Analysis under changing environmental conditions

Changes in abiotic parameters can affect ecosystem structure and function. Network models with subsequent Ecological Network Analysis (ENA) are often used for the quantification of ecosystem-wide properties with descriptive system indices. However, dynamic abiotic alterations of an ecosystem cannot be resolved with the “state of the art” ENA as the methodology of analyses is static in both space and time. In this study, we present a new, almost dynamic ENA “Flipbook-ENA” which allows for the trend analysis of system indices over a defined range of abiotic factors. Flipbook-ENA enables an approximation of the dynamic system response by discretizing the continuous influence of abiotic factors and by calculating the corresponding changes in the model for each discretization step. ENA indices are therefore obtained as a discrete function of the abiotic conditions. We applied this new concept to two aquatic food web models as case studies, using temperature as the influencing abiotic factor. Flipbook-ENA can be considered an enhancement of ENA flexibility, also facilitating the provision of a quantitative assessment basis for socially, economically and ecologically-balanced management of ecosystems in unstable environmental conditions under the pressure of climate change.

Riding safety prediction of a high-speed train running on transition zone under foundation settlement

The settlement of piers and subgrade bending deformation are widely recognized as common issues in the transition zones of high-speed railway bridges. This study aims to investigate the settlement behavior within these transition zones and its impact on the dynamic interaction between trains and the track. To achieve this, a vehicle-track-transition zone mapping relationship model is developed to analyze both the settlement behavior and the resulting dynamic response characteristics. The study employs the finite element method and multi-body dynamics to construct the simulation model. Settlement effects are simulated using the Newton-Raphson iterative method, with the additional rail deformation caused by foundation settlement serving as the excitation for the vehicle-track-transition zone dynamic interaction system. In the numerical analysis, the dynamic effects of three key factors—train speed, transition zone length, and the amplitude of foundation settlement—are examined based on the performance of the vehicle-track-transition zone interaction. The time-frequency technique is utilized to comprehensively reveal and clarify the spatial-frequency characteristics of system responses influenced by settlement excitation. Moreover, the relationship between the safety-based settlement threshold and these three factors is calibrated.

The effects of four hours of normobaric hypoxia on the vestibular control of balance.

Whole-body vestibular-evoked balance responses decrease following ~ 55min of normobaric hypoxia. It is unclear how longer durations of hypoxia affect the vestibular control of balance at the muscle and whole-body levels. This study examined how four hours of normobaric hypoxia influenced the vestibular control of balance. Fifteen participants (4 females; 11 males) stood on a force plate with vision occluded and head rotated rightward while subjected to three blocks of binaural, bipolar stochastic electrical vestibular stimulation (EVS; 0-25Hz, root mean square amplitude = 1.1mA) consisting of two, 90-s trials. The relationship between EVS and anteroposterior (AP) forces or medial gastrocnemius (MG) electromyography (EMG) was estimated in the time and frequency domains at baseline (BL; 0.21 fraction of inspired oxygen-FIO2) and following two (H2) and four (H4) hours of normobaric hypoxia (0.11 FIO2). The EVS-MG EMG short-latency peak and peak-to-peak amplitudes were smaller than BL at H2 and H4, but the medium-latency peak amplitude was only lower at H4. The EVS-AP force medium-latency peak amplitude was lower than BL at H4, but the short-latency peak and peak-to-amplitudes were unchanged. The EVS-MG EMG coherence and gain were reduced compared to BL at H2 and H4 across multiple frequencies ≥ 7Hz, whereas EVS-AP force coherence was blunted at H4 (≤ 4Hz), but gain was unaffected. Overall, the central nervous system's response to vestibular-driven signals during quiet standing wasdecreased forup to four hours of normobaric hypoxia, and vestibular-evoked responses recorded within postural muscles may be more sensitive than the whole-body response.

Therapeutic Targeting of Pattern Recognition Receptors to Modulate Inflammation in Atherosclerosis.

Atherosclerosis (AS), a potentially fatal cardiovascular disease (CVD), is a chronic inflammatory condition. The disease's onset and progression are influenced by inflammatory and immunological mechanisms. The innate immune pathways are essential in the progression of AS, as they are responsible for detecting first danger signals and causing long-term changes in immune cells. The innate immune system possesses distinct receptors known as pattern recognition receptors (PRRs) which can identify both pathogen-associated molecular patterns and danger-associated molecular signals. Activation of PRRs initiates the inflammatory response in various physiological systems, such as the cardiovascular system. This review specifically examines the contribution of the innate immune response and PRRs to the formation and advancement of AS. Studying the role of these particular receptors in AS would enhance our understanding of the development of AS and offer novel approaches for directly improving the inflammatory response associated with it.

Rare earth metallic elements in plants: assessing benefits, risks and mitigating strategies.

Rare earth elements (REEs) comprises of a uniform group of lanthanides and scandium (Sc) and yttrium (Y) finding their key importance in agriculture sectors, electronic and defense industries, and renewable energy production. The immense application of REEs as plant growth promoters has led to their undesirable accumulation in the soil system raising concerns for REE pollution as upcoming stresses. This review mainly addresses the chemistry of REEs, uptake and distribution and their biphasic responses in plant systems and possible plausible techniques that could mitigate/alleviate REE contamination. It extends beyond the present understanding of the biphasic impacts of rare earth elements (REEs) on physio-biochemical attributes. It not only provides landmarks for further exploration of the interrelated phytohormonal and molecular biphasic nature but also introduces novel approaches aimed at mitigating their toxicities. By delving into innovative strategies such as recycling, substitution, and phytohormone-assisted mitigation, the review expands upon existing knowledge of REEs whilst also offering pathways to tackle the challenges associated with REE utilization.

Dielectric Response of ZnO/PMMA Nanocomposites with Atmospheric Pressure Plasma-Modified Surfaces.

In this work, the effect of etching the surface of polymer matrix nanocomposites with atmospheric pressure plasma targeting to achieve enhanced dielectric properties was investigated. Polymer nanocomposites, with varying reinforcing phase content, were modified by atmospheric-pressure plasma resulting in an increase in the surface filler's concentration. Polymethyl methacrylate (PMMA) matrix nanocomposites reinforced with zinc oxide (ZnO) nanoparticles were prepared and dielectrically studied as a function of the nanoparticle content and the plasma modified surfaces. The electrical response of the composite systems was studied by means of Broadband Dielectric Spectroscopy (BDS) over a wide range of temperatures and frequencies. The dielectric permittivity increased with the embedded phase content and with plasma surface treatment. Energy density followed the same trend as dielectric permittivity, and the plasma-treated nanocomposite with the higher ZnO content exhibited approximately 27% higher energy density compared to the unreinforced matrix.