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A vital protein kinase, known as the mitogen-activated protein kinases (MAPKs), they be instrumental for controlling cellular tasks ranging from dividing, growing, and staying alive. This review gives a brief idea at the pathogenic involvement of MAPK signaling pathways in many human ailments. Dysregulated ERK1/2 activity in polycystic ovarian syndrome (PCOS) accelerates disease development by influencing gene transcription and cell proliferation. Tumor development and metastasis are encouraged by prolonged MEK-ERK signaling gives rise to mutations in Ras and B-Raf within the ERK pathway in cancer. Function of ERK in tumor survival is highlighted by its phosphorylation of proteins including MCL-1 and BIM; sorafenib, a Raf inhibitor, has therapeutic promise. For glucose triggered insulin release and gene transcription in pancreatic promote beta cells, ERK1/2 activation is essential in diabetes mellitus. Beta cell death is encouraged and insulin gene transcription is hampered by chronic hyperglycemia's disruption of ERK1/2 signaling.

Deep Reinforcement Learning applications are growing due to their capability of teaching the agent any task autonomously and generalizing the learning. However, this comes at the cost of a large number of samples and interactions with the environment. Moreover, the robustness of learned policies is usually achieved by a tedious tuning of hyper-parameters and reward functions. In order to address this issue, this paper proposes an evolutionary RL algorithm for the adaptive optimization of hyper-parameters. The policy is trained using an on-policy algorithm, Proximal Policy Optimization (PPO), coupled with an evolutionary algorithm. The achieved results demonstrate an improvement in the sample efficiency of the RL training on a robotic grasping task. In particular, the learning is improved with respect to the baseline case of a non-evolutionary agent. The evolutionary agent needs 60 % fewer samples to completely learn the grasping task, enabled by the adaptive transfer of knowledge between the agents through the evolutionary algorithm. The proposed approach also demonstrates the possibility of updating reward parameters during training, potentially providing a general approach to creating reward functions.

Erlotinib hydrochloride (ERL), a tyrosine kinase inhibitor, is effective in treating various cancers. However, low aqueous solubility limits its bioavailability and therapeutic efficacy. We developed an amorphous solid dispersion (ASD) of ERL with biocompatible polymers, polyvinylpyrrolidone (PVP-K30), and polyethylene glycol (PEG-4000) for enhanced amorphization, miscibility, and molecular interactions. The present study focuses on the physicochemical characterization of formulated ASD of ERL using Fourier Transform Infrared Spectroscopy (FTIR), X-ray Powder Diffraction (PXRD), UV–Visible Spectroscopy, and High-Performance Liquid Chromatography (HPLC), along with biological evaluation including antioxidant, cytotoxicity, and antitumor studies in mouse tumor models. FTIR analysis confirmed the retention of ERL’s characteristic peaks in ASDs with PVP, PEG, and PVP/PEG, with shifts to lower frequencies for C=O bending, CH₂ deformation and CH symmetric deformation, indicating reduced molecular vibration energy, increased molecular flexibility, and strong drug–polymer interactions. PXRD analysis confirmed the transformation of crystalline ERL into an amorphous state in ASDs, as evidenced by the diminished ERL peaks at 11.7°, 16.2°, 21.7°, 24.75°, 25.56°, and 29.37°. UV spectroscopy revealed shifts in absorption peaks (256 nm), suggesting favorable drug–polymer interactions. HPLC demonstrated enhanced release rates at 4.72 retention time. In dissolution studies, the ERL + PEG formulation attained the greatest dissolution rate (80%). ERL + PVP showed superior DPPH radical scavenging activity with an IC 50 value of 100 µg/mL, while ERL + PEG demonstrated stronger hydroxyl radical scavenging activity with an IC 50 of 200 µg/mL. In the MTT assay, ERL + PEG exhibited the most potent cytotoxicity against MCF-7 cells, with an IC 50 of 19 μM, whereas the ERL + PEG + PVP combination was most effective against HCT-116 cells, with IC 50 of 19.5 μM. In vivo, ERL + PEG significantly reduced tumor volumes to 0.167 ± 0.002 g and 0.063 ± 0.004 g, corresponding to a tumor reduction of 98.78%. This study highlights the successful development of erlotinib ASD, particularly with PEG, which significantly improved ERL’s solubility, dissolution rate, antioxidant activity, cytotoxicity, and antitumor efficacy. These enhancements are attributed to physical modifications such as enhanced amorphization and strong drug–polymer interactions, without any chemical alteration of ERL, underscoring the potential of this formulation as an effective and promising drug delivery strategy for cancer therapy.

COVID-19 forced the digitalisation of teaching and learning in a response often described as emergency remote teaching (ERT). This rapid response changed the social, spatial, and temporal arrangements of higher education and required important adaptations from educators and students alike. However, while the literature has examined the constraints students faced (e.g. availability of the internet) and the consequences of the pandemic (e.g. student mental health), students’ active management of these constraints for learning remains underexplored. This paper aims to “think with” COVID-19 to explore student agency in home learning under constrained circumstances. This qualitative study used semi-structured interviews to understand the day-to-day actions of nineteen undergraduate students managing their learning during the COVID-19 lockdowns in Victoria, Australia. Emirbayer and Mische’s multiple dimensions of agency — iterative, projective, and practical-evaluative — are used to explore student experience. The findings illustrate students’ adaptability and agency in navigating life-integrated learning, with most of their actions oriented to their present circumstances. This practical evaluative form of agency was expressed through (1) organising self, space, time, and relationships; (2) self-care; and (3) seeking help. Although this study took place in the context of ERT, it has implications beyond the pandemic because higher education always operates under constraints, and in other circumstances, many students still experience emotionally and materially difficult times.

The Self-Regulation vs. External-Regulation Theory (2017) has postulated a continuum of regulation/non-regulation/dys-regulation that is present both in the individual and in the individual’s context. This gives rise to a behavioral heuristic that can predict and explain other health-related variables, such as psychological reactance and student health. On a voluntary basis, 269 university students completed validated questionnaires on variables of regulation, reactance and health. Using an ex post facto design, we performed correlational analysis and structural linear regression to build a structural equations model (SEM) with acceptable statistical values. The results showed various predicted relationships: self-regulation was associated with and positively predicted self-regulated health behavior; external health-regulating contexts were associated with and positively predicted self-regulated health behavior; non-regulatory and dysregulatory contexts negatively predicted self-regulated health behavior and students’ health itself, as well as positively predicting psychological reactance behavior. Implications are established for explaining variability in general and health-related self-regulation, as well as for intervening in these variables in health programs.

The strategic delineation of the urban development boundary (UDB) is an effective initiative for efficient land resource allocation and for facilitating planned urban development. To align with sustainable development objectives, UDB definitions have evolved to reconcile urban development with ecological preservation. This study presents a UDB delineation framework from an integrated perspective that incorporates both demand-oriented and comprehensive constraints. Specifically, the urban construction land demand area was estimated based on population projections, meanwhile, the ecological red line (ERL) was delineated and integrated into the evaluation of the construction land suitability. Subsequently, with the demand area as the simulation target and unsuitable areas as comprehensive constraints, the UDB was delineated by simulating future land use patterns. The proposed framework was applied to Wuhan, a rapidly urbanizing city in central China, where the delineation of the UDB serves the dual purpose of managing the rapid expansion of built-up land and achieving a harmonious balance between urban development imperatives and ecological protection goals. Moreover, based on the results and analysis, policy implications for the rational spatial planning of Wuhan were proposed, encompassing the spatial patterns and scientific decision-making in ecological conservation and urban development. The results demonstrate that the efficacy of adopting a comprehensive perspective in delineating UDB effectively reconciles the competing needs of urban development and conservation. The framework and the policy insights derived in this study could inform spatial planning efforts not only in Wuhan but also in other cities facing the dilemma of urban development and ecological protection.

Alerting has been hypothesized to affect spatial orienting either by accelerating the speed of attentional shift toward the cued target location (the accelerating hypothesis) or by enhancing the orienting effect without changing its time course (the enhancing hypothesis). To investigate the neural underpinnings of the effect of phasic alerting on endogenous orienting, we recorded the electroencephalogram (EEG) in a variant of the spatial cueing task with a tone presented 100 ms before the cue as a phasic alerting signal, and calculated cue-evoked event-related lateralizations (ERLs) providing a precise assessment of preparatory visuospatial attention. Behavioral results showed that the spatial orienting effect was increased under the phasic alerting condition, as expected. The EEG results showed that an orienting-related ERL component called a late directing attention positivity (LDAP) had shorter onset latency and larger amplitude in the alerting condition than in the no-alerting (no-tone) condition. In conclusion, phasic alerting seems to both accelerate and enhance orienting-related preparatory modulations within the ventral visual stream.

Boost converters play a crucial role in power electronics but present control challenges due to their non-minimum phase behavior and nonlinear dynamics at high switching frequencies. To address these issues, this work proposes a Fractional-order adaptive Model Predictive Control (FO-MPC) framework incorporating Exponential Regressive Least Squares (ERLS) for system identification. Traditional MPC frameworks often rely on accurate mathematical models, which are difficult to obtain in real-world scenarios. This adaptive modelling approach based on ERLS identification method eliminates the need for precise system models, improving robustness and adaptability under parameter variations. Additionally, a FO derivative term enhances damping, stability, and noise resistance, overcoming conventional MPC limitations. To optimize controller performance, Grey Wolf Optimization (GWO) is employed for fine-tuning FO-MPC parameters, ensuring improved tracking accuracy and disturbance rejection. The proposed FO-MPC is validated through simulations and experimental evaluations using an Arduino DUE-based setup. Comparative studies against PID and FO-PID controllers, also optimized with GWO, confirm the superior performance, stability, and adaptability of the FO-MPC, making it a practical and effective solution for high-performance Boost converter applications.

This paper presents a fast-reaching law of sliding mode control for the slotless self-bearing motor (SSBM) with fully embedded of the load torque on the speed axis. This is a new consideration of the disturbance on the speed control axis in compare with the previous works. Furthermore, the uncertain values of the fabrication, winding process, and modeling are all matched with the control input channel, which are rejected by the robust control method. To obtain the gold of expectations with robustness, the mathematical model of SSBM is firstly given with an explanation of sources of the uncertainties. Second, the exponential reaching law sliding mode control (ERL-SMC) is employed to design the controller of all positions and speed axes, respectively. Third, the stability analysis is given to show the correction of the designed controllers. Fourth, the simulation by using MATLAB software and experimental by using laboratory motor prototype were used to show the effectiveness of the designed control method. The obtained results show that the settling times are small, the steady-states are stable with uncertainties and external load torque.

Nine metals including Al, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn were analysed from sediment samples collected from 29 stations since 2007 from Bahraini waters. Within this study, it was investigated whether concentrations of these determinants are at concentrations above internationally established Assessment Criteria (AC). The majority of sites were considered not to pose a toxicological risk in terms of metal contamination. Where breaches occurred, they were mainly from historic samples related to Cr, Cu and Ni contamination. A trend assessment revealed that out of 59 significant trends, 36 were downwards and 23 upwards, indicating that some determinants like Al, Zn and Ni are improving strongly across some sites, whilst areas associated with industrial activity still see some increasing trends for Al, Cd, Pb and Zn.