Deciphering the Instability of the Black Hole Ringdown Quasinormal Spectrum.

The spectrum of the quasinormal modes of the gravitational waves emitted during the ringdown phase following the merger of two black holes is of primary importance in gravitational astronomy. However, the spectrum is extremely sensitive to small disturbances of the system, thus potentially jeopardizing the predictions of the gravitational-wave observables. We offer an analytical and intuitive explanation of such an instability and its properties based on the transfer matrix approach of quantum mechanics.

Assault rifle injuries in civilians: ballistics of wound patterns, assessment and initial management.

Purpose: Wounds from assault rifles and their commercial offspring have been encountered with increasing frequency in civilian practice. Our aim is to summarize wound ballistics related to the main injury patterns that can also affect management strategies.

Methods: An online search of the PubMed was conducted for research and review articles published after 2000 in English, using the MeSH terms "gunshot wounds", "mass casualty incidents", "war-related injuries", "soft tissue injuries", "vascular system injuries", "colon injuries", "wound infection", "antibiotic prophylaxis", "debridement", "hemorrhage", "penetrating head injuries", "pneumothorax" and additional free-text terms.

Analyzing LinkedIn data to explore the relationships between sustainable development goals, circular economy, and electoral dynamics.

In 2015, all United Nations Member States adopted 17 Sustainable Development Goals (SDGs) for the 2030 agenda. Addressing the issue of employing alternative data sources for exploring aspects of utilizing said goals, this paper explores the Circular Economy dimension within the SDG12 score, focusing on responsible production and consumption and the broader SDG index. Data from LinkedIn are collected, examining profiles, companies, job postings, and services using the keywords 'Sustainable Development Goals' and 'Circular Economy'.

Development of Alginate Hydrogels Incorporating Essential Oils Loaded in Chitosan Nanoparticles for Biomedical Applications.

A hybrid alginate hydrogel-chitosan nanoparticle system suitable for biomedical applications was prepared. Chitosan (CS) was used as a matrix for the encapsulation of lavender () essential oil (LEO) and Mentha () essential oil (MEO). An aqueous solution of an acidic Natural Deep Eutectic Solvent (NADES), namely choline chloride/ascorbic acid in a 2:1 molar ratio, was used to achieve the acidic environment for the dissolution of chitosan and also played the role of the ionic gelator for the preparation of the chitosan nanoparticles (CS-NPs).

Marketable and Banned Pesticides in Agriculture: Categorization, Simulation, and Crystallography Review.

Pesticides are playing a dominant role in modern cultivation practices to increase agricultural production but are also criticized for environmental depletion and soil and underground water degradation in field applications. An imperative need for greener pesticides has emerged in alignment with new innovations in agrarian and agricultural practices. This study provides a comprehensive review of marketable and banned pesticides that have been applied in past times or are still in use in agriculture.

Enhancing Tumor Targeted Therapy: The Role of iRGD Peptide in Advanced Drug Delivery Systems.

Chemotherapy remains the primary therapeutic approach in treating cancer. The tumor microenvironment (TME) is the complex network surrounding tumor cells, comprising various cell types, such as immune cells, fibroblasts, and endothelial cells, as well as ECM components, blood vessels, and signaling molecules. The often stiff and dense network of the TME interacts dynamically with tumor cells, influencing cancer growth, immune response, metastasis, and resistance to therapy.

In the quest of lossless slow light at surface plasmons.

Surface plasmons, namely, the waves guided at the boundaries between metals and dielectrics, are employed in a variety of engineering applications, spanning from photodetection and near-field scanning to biosensing and medical imaging. The spatial confinement of this effect makes it ideal for a quest towards low-loss guiding of slow light along the interfaces of similar heterostructures. Numerous pairs of materials are considered to determine the conditions for the emergence of strong surface waves, once the visible-light frequency is selected to secure minimum phase velocity or minimum propagation losses.

Towards circularity in the wind industry: Optimal reverse supply network design under various policy scenarios.

Wind energy is key to supply renewable energy. However, the increasing number of end-of-life wind turbines is still predominantly landfilled, while regulatory aspects such as waste shipment and landfilling rules hinder the development and scalable implementation of reverse supply networks. This work aims to understand how EU directives impact the structure and viability of circularity-enabling networks by investigating the optimal reverse supply network design for end-of-life wind turbine blades under different policy scenarios.

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.

Securing a Generative AI-Powered Healthcare Chatbot.

In Generative Artificial Intelligence (AI), Large Language Models (LLMs) like GPT-4, Gemini, Claude, and Llama, significantly impact healthcare by aiding in patient care, medical research, and administrative tasks. AI-powered chatbots offer real-time responses and manage chronic diseases, improving patient outcomes and operational efficiency. However, these models pose security and ethical challenges, necessitating robust data privacy, adversarial training, and ethical guidelines.

Leveraging Cancer Therapy Peptide Data: A Case Study on Machine Learning Application in Accelerating Cancer Research.

This study leverages the DCTPep database, a comprehensive repository of cancer therapy peptides, to explore the application of machine learning in accelerating cancer research. We applied Principal Component Analysis (PCA) and K-means clustering to categorize cancer therapy peptides based on their physicochemical properties. Our analysis identified three distinct clusters, each characterized by unique features such as sequence length, isoelectric point (pI), net charge, and mass.

A new strategy for modelling sonochemical reactors: Coupling of the non-linear Louisnard model with mass and heat transport equations with applications to cavitating viscous fluids.

In this work, novel numerical models were developed and validated to offer new strategies in modelling sonochemical reactors. More specifically, in our original approach the non-linear Louisnard model was coupled with heat and mass transport equations to predict gradients in temperature and species concentration in a sonicated reactor. Additionally, a new operating window was investigated by modelling mixtures of increasing viscosity on both micro- and macroscale sonochemical effects.

Effective management of urban water resources under various climate scenarios in semiarid mediterranean areas.

Climate change has a significant impact on water resources, making it essential to re-evaluate water management strategies and incorporate climate scenarios in assessments. The Municipal Department of Aigeiros is located in the northern part of Greece. Water consumption is high in Aigeiros and the increased future temperatures projected during the summer period will create significant pressures on water resources.

Easy-MODA: Simplifying standardised registration of scientific simulation workflows through MODA template guidelines powered by the Enalos Cloud Platform.

Modelling Data (MODA) reporting guidelines have been proposed for common terminology and for recording metadata for physics-based materials modelling and simulations in a CEN Workshop Agreement (CWA 17284:2018). Their purpose is similar to that of the Quantitative Structure-Activity Relationship (QSAR) model report form (QMRF) that aims to increase industry and regulatory confidence in QSAR models, but for a wider range of model types. Recently, the WorldFAIR project's nanomaterials case study suggested that both QMRF and MODA templates are an important means to enhance compliance of nanoinformatics models, and their underpinning datasets, with the FAIR principles (Findable, Accessible, Interoperable, Reusable).

Predicting the acute aquatic toxicity of organic UV filters used in cosmetic formulations.

Background And Purpose: Organic UV filters are commonly used in sunscreen and cosmetic formulations to protect against harmful UV radiation. However, concerns have emerged over their potential toxic effects on aquatic organisms. This study aims to investigate the acute aquatic toxicity of 13 organic UV filters and determine whether phospholipid binding, measured through biomimetic chromatographic methods, is a better predictor of toxicity than the traditionally used octanol-water partition coefficient (log ).

Simple model for the fracture of a polymer chain: Single-bond potential of mean force and tension-based rate constants for chain rupture.

A linear chain of N particles connected by Morse bonds with periodic boundaries in a Brownian bath is considered as a model for polymer fracture. The potential of mean force (pomf) with respect to the length of a bond and its energy and entropic components are computed via Langevin Dynamics simulations at various chain elongations λ > 1. A narrow range of λ values is identified over which equilibrium is established between an intact (i) and a fractured (f) state over a pomf barrier.

Computer-Aided Identification and Design of Ligands for Multi-Targeting Inhibition of a Molecular Acute Myeloid Leukemia Network.

Background/objectives: Acute myeloid leukemia (AML) is characterized by therapeutic failure and long-term risk for disease relapses. As several therapeutic targets participate in networks, they can rewire to eventually evade single-target drugs. Hence, multi-targeting approaches are considered on the expectation that interference with many different components could synergistically hinder activation of alternative pathways and demolish the network one-off, leading to complete disease remission.

Numerical Study on the Development of Adiabatic Shear Bands During High Strain-Rate Compression of AISI 1045 Steel: A Comparative Analysis Between Plane-Strain and Axisymmetric Problems.

This work studies numerically the development of adiabatic shear banding (ASB) during high strain-rate compression of AISI 1045 steel. Plane strain and cylindrical axisymmetric compressions are simulated in LS-DYNA, considering rectangular and cylindrical steel samples, respectively. Also, a parametric analysis in height-to-base ratio is conducted in order to evaluate the effect of geometry and dimensional ratio of the sample on ASB formation.

Vascular complications in TAVI procedures: assessment, management, and outcomes-a retrospective study.

Objective: Transcatheter Aortic Valve Implantation (TAVI) has emerged as a pivotal therapeutic modality for aortic stenosis, predominantly in the elderly population. Despite its clinical success, the incidence and implications of vascular complications during TAVI remain a subject of critical concern.

Methods: A retrospective analysis was conducted on 140 patients who experienced vascular complications during TAVI procedures from a total cohort of 1343 cases.

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine.

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone.

3D printer audio and vibration side channel dataset for vulnerability research in additive manufacturing security.

This dataset provides a comprehensive set of side channels from fused deposition modeling 3D printers in order to enable the research in the security of additive manufacturing processes against side channel attacks. These attacks exploit indirect signal emanations from physical processes to extract information about a system. Our data was collected using two different methods (iPhone app and Teensy 4.