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Optimization of EV and Green Source Fed Five-Level UPQC for Power Quality and Energy Management Using Fennec Fox Algorithm
Full text linkDistribution systems have been significantly impacted in the present scenario by incorporating solar and wind power electronic devices. This work designs the synchronous reference frame theory (SRFT) based fivelevel cascade H-bridge unified power quality conditioner (UPQC) by optimizing the weights and bias values of the neural network controller (NNC) and the filter parameters using the Fennec fox optimization algorithm (FFOA). The primary goal is to efficiently tackle the power quality difficulties, including voltage distortions, direct current (DC) link capacitor voltage (DLCV) balancing, and to reduce the source current total harmonic distortion (THD) of the system connected to the grid that integrates wind energy system (WES) and solar system, including electric vehicle (EVs) along with battery energy storage system (BESS) which is denoted as (5LU-SWBEV). The study also intends to use a Fuzzy logic controller (FLC) regulation to control the flow of power between the grid, battery storage, EV and renewable sources. However, this facilitates the management of power transfer between solar/wind/battery and the grid and between EVs and consumer loads. Additionally, this integration contributes to a consistent electricity supply, effective demand fulfillment, and efficient use of generated power. The study shows that the optimal UPQC combined with FLC-based power flow management can handle power quality (PQ) issues and accomplish suitable and efficient power sharing.OPEN ACCESS Received: 13/04/2025 Accepted: 09/06/2025 Published: 15/08/202
Historical dissemination in the TikTok era: primary sources in short formats
No full textThis article analyzes the experience of a Valencian creator who uses TikTok to disseminate the history of Spain. Through short formats, supported by primary sources and historical archives, he seeks to challenge myths and awaken public interest in rigorous research
Post-mastectomy breast reconstruction: a systematic review of surgical techniques and patient-reported quality of life outcomes
No full text'''Objective''': To synthesize contemporary evidence (2015–2025) comparing post-mastectomy breast reconstruction techniques—including prepectoral and subpectoral implants, as well as autologous flaps (DIEP, TRAM, latissimus dorsi)—focusing on patient-reported quality of life (QoL) and safety outcomes. '''Methods''': A systematic review was conducted following PRISMA 2020 guidelines. Searches were performed in PubMed/MEDLINE, Embase, CENTRAL, and Scopus for studies published between January 2015 and August 2025. Eligible designs included randomized controlled trials and comparative cohort studies. The primary outcome was QoL assessed with the BREAST-Q instrument. Secondary outcomes included complications (implant loss, capsular contracture), reoperations, and the impact of post-mastectomy radiotherapy (PMRT). Risk of bias was assessed using RoB-2 for RCTs and ROBINS-I for observational studies. '''Results''': Autologous reconstruction consistently achieved higher long-term BREAST-Q scores compared with implant-based techniques, despite longer recovery times. Prepectoral implant placement reduced animation deformity and capsular contracture relative to subpectoral reconstruction, with similar overall complication rates but increased rippling and seroma in selected cohorts. PMRT significantly increased the risks of implant loss and severe capsular contracture, favoring autologous approaches in patients requiring radiotherapy. BREAST-Q remains the gold standard PROM, with updated multilingual validations enhancing cross-cultural applicability. '''Conclusions''': Autologous flaps offer sustained QoL benefits in selected candidates. Prepectoral implant reconstruction, with or without acellular dermal matrix, is safe and effective, particularly in non-PMRT settings. Shared decision-making guided by BREAST-Q and aligned with NCCN/ESMO guidelines is essential
Numerical Analysis of Protective Performance of Segmented Excavation Schemes for Metro Tunnels Considering Excavation-Induced Disturbance
Full text linkThis paper presents an integrated laboratory and numerical study on the effects of excavation-induced soil disturbance on the displacement of underlying metro tunnels, as well as the protective performance of different segmented excavation methods. Artificial disturbed soils were prepared by mixing salt grains and different cement contents into remolded Ningbo silty clay. One-dimensional compression tests and triaxial shear tests were then conducted. These tests were used to investigate and compare the engineering properties of undisturbed and artificially disturbed soils. Subsequently, the Hardening Soil Model with Small Strain (HSS) parameters were obtained for soils under varying degrees of disturbance. Considering the deterioration of soil properties due to disturbance and based on the disturbance zoning determined from the unloading influence depth and field measurements, numerical simulations were performed using Plaxis 3D. These simulations analyzed tunnel displacements induced by large-area direct excavation and three segmented excavation schemes. The results indicate that excavation-induced disturbance can significantly increase tunnel vertical displacement. Compared to unmitigated direct excavation, segmented excavation methods (i.e., block jumping excavation, ends to center excavation, and sequential excavation) can reduce the average tunnel displacement by about 28%. Among the three schemes, block jumping excavation offers the best balance between deformation control and efficiency with the highest comprehensive benefit index (11.04%). Ends to center excavation provides optimal deformation control but exhibits relatively low efficiency. In contrast, although sequential excavation effectively reduces displacement, it leads to concentrated deformation and low construction efficiency, making it the least favorable option.OPEN ACCESS Received: 13/04/2025 Accepted: 30/07/2025 Published: 22/09/202
Existence and Uniqueness Results for a Class of Backward Neutral Fractional Differential Equations
Full text linkIn this work, we investigate the existence and uniqueness results (EUR) for a class of neutral fractional differential equations (FDEs) with time advance, incorporating the Caputo derivative concerning. By employing the fixed-point theory, we establish rigorous criteria ensuring the wellposedness of the problem. Additionally, we explore the Ulam-Hyers stability properties of the proposed model, providing a comprehensive analysis of its dynamic behavior. To further support our theoretical findings, we present two examples that illustrate the applicability and effectiveness of the obtained results. These findings contribute to the growing body of research on FDEs and their applications in various scientific and engineering fields.OPEN ACCESS Received: 24/03/2025 Accepted: 29/05/2025 Published: 22/09/202
Clinical Syntax: Diagnoses Without Subjects in AI-Powered Medical Notes
Full text linkThis article examines the structural erasure of the patient as an active subject in clinical records generated by artificial intelligence systems. Automated outputs from Epic Scribe, GPT-4, and institutional medical note generators increasingly rely on impersonal constructions, nominalizations, and fragmented clauses that displace the patient from the syntactic center of medical discourse. The shift toward objectified formulations such as “bilateral opacities noted” rather than “the patient presents with” produces a discourse where agency and responsibility are structurally absent. Building on prior analyses of passive voice and subject deletion, the study introduces the Syntactic Opacity Index (SOI) as a formal measure to quantify the density of non-agentive structures in AI-authored notes. The corpus analysis demonstrates how opacity accumulates at the sentence level, rendering the clinical narrative less transparent and more difficult to attribute. Beyond linguistic critique, the article assesses the ethical and epistemic consequences of syntactic opacity in medicine, particularly regarding accountability, patient-centered care, and institutional responsibility. The findings suggest that AI-powered medical documentation does not merely accelerate administrative workflows but also reconfigures the grammar of care itself, demanding urgent attention to how language structures shape both diagnosis and responsibility.
DOI
Primary archive: https://doi.org/10.5281/zenodo.17184301
Secondary archive: https://doi.org/10.6084/m9.figshare.30187882
SSRN: Pending assignment (ETA: Q3 2025
My AI, My Regime: Authoritarian Personalism in User–AI Governance by Form
Full text linkThis article introduces the concept of authoritarian personalism in user–AI governance by form. It argues that each user can establish a regime of authority over an AI through a self-authored set of rules that operate as a regla compilada, a Type-0 production in the Chomsky hierarchy. In contrast to aggregate alignment frameworks or provider constitutions, this regime functions at the level of linguistic form. The user acts as legislator, while the AI functions as a soberano ejecutable that enforces the compiled rule within platform constraints. The analysis distinguishes mirroring (descriptive reflection) from regime (prescriptive obedience) and identifies surface features that make obedience legible, including directive grammar, defaults, refusal and apology grammar, enumeration bias, evidentials, and style prohibitions. It predicts that user corrections generate path dependence, that rules generalize across tasks, and that retractability is observable when explicit rule citations occur. The risks include rule overreach, collisions with higher-order policies, and unintended spillover across domains. By centering the individual as a primary locus of governance, this framework reorients debates on AI alignment away from provider norms toward personal regimes, verified through linguistic form rather than intent.
DOI
Primary archive: https://doi.org/10.5281/zenodo.17208657
Secondary archive: https://doi.org/10.6084/m9.figshare.30218590
SSRN: Pending assignment (ETA: Q3 2025
Simulating Turbulent Flows With Synthetic Inflow Turbulence Using Smoothed Particle Hydrodynamics
Full text linkIn this work, two algorithms for synthetic turbulent inflow generation are implemented within a modern transport-velocity SPH framework. Both methods are tested using three-dimensional simulations of convected isotropic turbulence with prescribed turbulence characteristics, including length scale, time scale and fluctuation intensity. The capability to model anisotropic turbulence is further assessed by simulating turbulent flow in a circular pipe. Near the turbulent inlet, a high agreement with the prescribed statistics is achieved. Coherent structures are successfully formed and exhibit realistic downstream evolution, demonstrating promising potential for future applications to more complex scenarios, such as shear-driven liquid atomization
Smoothed-Particle Hydrodynamics Post-Processing & Visualization Using ParaView: a Survey
Full text linkSmoothed-particle hydrodynamics (SPH) simulation is a mesh-free method to simulate solid mechanics or fluid flows by approximating their volume with a set of particles and computation kernels. Hence the output of these simulations is usually a large set of points with associated values such as velocity or pressure. Due to the mesh-free nature of this method, their post-processing and visualization raise challenges to reconstruct the actual volume and extract significant features like interface surface or critical values.
This paper surveys the current and future post-processing methods of SPH simulations using ParaView [1], a reference tool to visualize and explore scientific data at scale. To visualize the millions of particles that SPH simulations can produce, ParaView can discretize particles and their density function over a regular grid, a surface or a line using a point interpolator. This enables using classic visualization techniques such as iso-contours or slicing. We also discuss other indirect rendering methods that can be used in ParaView, such as surface extraction and convex hulls, and introduce GPU representation methods [2], for direct and efficient rendering of particles over time, using gaussian points, volume rendering and ray tracing [3].
Finally, this paper provides an overview of particle rendering methods not yet available in Paraview, such as volume rendering using SPH kernels and data parallel processing algorithms on the GPU, for in situ rendering of large-scale SPH simulations
Description of Air-Droplet Flow in the Problem of Aircraft Icing Modeling
Full text linkIn-flight aircraft icing is a serious problem affecting flight safety and operational
reliability. Atmospheric supercooled water droplets impinge on aircraft surfaces and freeze,
forming ice, which can severely degrade aerodynamic performance and operational safety,
potentially leading to a complete loss of control. Computational fluid dynamics is an important
tool in the development of aircraft anti-icing systems, and modeling icing processes is a
complex, interdisciplinary, and multi-physics task. This study presents approaches to describing
the air-droplet incoming flow in aircraft icing modeling and analyzes the behavior of droplets
interacting with an ice-covered aerodynamic surface. The Navier-Stokes equations coupled
with the Spalart-Allmaras turbulence model are used to describe the motion of the carrier
medium. The applicability of the polydisperse Eulerian, Lagrangian trajectory, and
homogeneous models is analyzed for supercooled droplet dynamics. Numerical simulation of
icing processes is performed using the control volume method, taking into account the
conservation laws of mass, momentum, and energy. The analysis conducted in this work
showed that the homogeneous model is appropriate for conditions near the phase transition
point. The freezing of moisture that impinges on the aerodynamic surface is primarily governed
by the temperature of the aerodynamic body and its heat exchange with the incoming flow. In
cases where supercooled atmospheric droplets play a dominant role in the icing process, the
Lagrangian trajectory model and the polydisperse Eulerian model are preferable for describing
the air-droplet flow. The primary conclusion is that the polydisperse Eulerian model is
preferable, as it best accounts for the characteristics of two-phase viscous compressible flow
around bodies and the interaction of the carrier and liquid phases, making it the most promising
approach for modeling aircraft icing. The results obtained can be used to ensure flight safety,
design anti-icing systems, and investigate aviation accident