The Role of Light Irradiation and Dendrimer Generation in Directing Electrostatic Self-Assembly.

pH-responsive polyamidoamine (PAMAM) dendrimers are used as well-defined building blocks to design light-switchable nano-assemblies in solution. The complex interplay between the photoresponsive di-anionic azo dye Acid Yellow 38 (AY38) and the cationic PAMAM dendrimers of different generations is presented in this study. Electrostatic self-assembly involving secondary dipole-dipole interactions provides well-defined assemblies within a broad size range (10 nm-1 μm) with various shapes.

Shifting Focus to Quality: An Innovative Modeling Approach Includes Processing History for Rubber Part Quality Simulation.

An innovative modeling approach for the simulative description of the part quality of rubber materials, including the processing history, is presented in this paper. This modeling approach, the so-called average curing speed (ACS) model, is based on the degree of cure and the average curing speed instead of the conventionally considered temperature approach. Such approach neglects the processing history by calculating only the degree of cure.

Development of an Analytical Model for Predicting the Shear Viscosity of Polypropylene Compounds.

The need for an efficient adaptation of existing polypropylene (PP) formulations or the creation of new formulations has become increasingly important in various industries. Variations in viscosity resulting from changes in raw materials, fillers, and additives can have a significant impact on the processing and quality of PP products. This study presents the development of an analytical model designed to predict the shear viscosity of complex PP blends.

Fully Automated Production of ((()-1-Carboxy-5-(6-([F]fluoro)-2-methoxynicotinamido)pentyl)carbamoyl)-l-glutamic Acid ([F]JK-PSMA-7).

The radiotracer [F]JK-PSMA-7, a prostate cancer imaging agent for positron emission tomography (PET), was previously synthesized by indirect radiofluorination using an F-labeled active ester as a prosthetic group, which had to be isolated and purified before it could be linked to the pharmacologically active Lys-urea-Glu motif. Although this procedure could be automated on two-reactor modules like the GE TRACERLab FX2N (FXN) to afford the tracer in modest radiochemical yields (RCY) of 18-25%, it is unsuitable for cassette-based systems with a single reactor. To simplify implementation on an automated synthesis module, the radiosynthesis of [F]JK-PSMA-7 was devised as a one-pot, two-step reaction.

Cytotoxic Activity of Bisphosphonic Derivatives Obtained by the Michaelis-Arbuzov or the Pudovik Reaction.

Methylenebisphosphonic derivatives including hydroxy-methylenebisphosphonic species may be of potential biological activity, and a part of them is used in the treatment of bone diseases. Methylenebisphosphonates may be obtained by the Michaelis-Arbuzov reaction of suitably α-substituted methylphosphonates and trialkyl phosphites or phosphinous esters, while the hydroxy-methylene variations are prepared by the Pudovik reaction of α-oxophosphonates and different >P(O)H reagents, such as diethyl phosphite and diarylphosphine oxides. After converting α-hydroxy-benzylphosphonates and -phosphine oxides to the α-halogeno- and α-sulfonyloxy derivatives, they were utilized in the Michaelis-Arbuzov reaction with trialkyl phosphites and ethyl diphenylphosphinite to afford the corresponding bisphosphonate, bis(phosphine oxide) and phosphonate-phosphine oxide derivatives.

Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance.

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of the tumor microenvironment (TME), leading to important advancements toward a much deeper understanding of how tumor microenvironment heterogeneity contributes to cancer progression and therapeutic resistance. These technologies are able to integrate data from molecular genomic, transcriptomic, proteomics, and metabolomics studies of cells at a single-cell resolution scale that give rise to the full cellular and molecular complexity in the TME. Understanding the complex and sometimes reciprocal relationships among cancer cells, CAFs, immune cells, and ECs has led to novel insights into their immense heterogeneity in functions, which can have important consequences on tumor behavior.

From Infection to Tumor: Exploring the Therapeutic Potential of Ciprofloxacin Derivatives as Anticancer Agents.

Ciprofloxacin, a widely used second-generation fluoroquinolone for treating bacterial infections, has recently shown notable anticancer properties. This review explores progress in developing ciprofloxacin derivatives with anticancer properties, emphasizing key structural changes that improve their therapeutic effectiveness by modifying the basic group at position 7, the carboxylic acid group at position 3, or both. It further investigates the mechanisms by which these derivatives fight cancer, such as inducing apoptosis, arresting the cell cycle, inhibiting topoisomerase I and II, preventing tubulin polymerization, suppressing interleukin 6, blocking thymidine phosphorylase, inhibiting multidrug resistance proteins, and hindering angiogenesis.

Identification of a New Pentafluorosulfanyl-Substituted Chalcone with Activity Against Hepatoma and Human Parasites.

Background/objectives: New drugs are required for the treatment of liver cancers and protozoal parasite infections. Analogs of the known anticancer active and antileishmanial 2',4',6'-trimethoxychalcone SU086 were prepared and investigated.

Methods: The chalcones were prepared according to the Claisen-Schmidt condensation protocol and analyzed.

Pharmaceutical Humanities and Narrative Pharmacy: An Emerging New Concept in Pharmacy.

The complexity of our life experiences and the rapid progress in science and technology clearly necessitate reflections from the humanities. The ever-growing intersection between science and society fosters the emergence of novel interdisciplinary fields of research. During the past decade, Medical Humanities arose to meet the need to unravel hidden information beyond technology-driven and fact-based medicine.

Comparison of ZnS(Ag) Scintillator and Proportional Counter Tube for Alpha Detection in Thin-Layer Chromatography.

(1) : Targeted alpha therapy is an emerging field in nuclear medicine driven by two advantages: overcoming resistance in cancer-suffering patients to beta therapies and the practical application of lower activities of Pb- and Ac-labelled peptides to achieve the same doses compared to beta therapy due to the highly cytotoxic nature of alpha particles. However, quality control of the Pb/Ac-radiopharmaceuticals remains a challenge due to the low activity levels used for therapy (100 kBq/kg) and the formation of several free daughter nuclides immediately after the formulation of patient doses; (2) : The routine alpha detection on thin-layer chromatograms (TLC) of Pb- and Ac-labelled peptides using a MiniScanPRO+ scanner combined with an alpha detector head was compared with detection using an AR-2000 scanner equipped with an open proportional counter tube. Measurement time, resolution and validity were compared for both scanners; (3) : For Ac, the quality control values of the radiochemical purity (RCP) were within the acceptance criteria 2 h after TLC development, regardless of when the TLC probe was taken.

Molecular Epidemiology, Drug-Resistant Variants, and Therapeutic Implications of Hepatitis B Virus and Hepatitis D Virus Prevalence in Nigeria: A National Study.

Information on circulating HBV (sub-)genotype, variants, and hepatitis D virus (HDV) coinfection, which vary by geographical area, is crucial for the efficient control and management of HBV. We investigated the genomic characteristics of HBV (with a prevalence of 8.1%) and the prevalence of HDV in Nigeria.

Archival and Newly Isolated Historical Strains Populate the Deeper Phylogeny of the A.Br.075(Sterne) Clade.

The anthrax pathogen can remain dormant as spores in soil for many years. This applies to both natural foci and to sites of anthropogenic activity such as tanneries, abattoirs, or wool factories. The A.

Tiny Machine Learning Implementation for Guided Wave-Based Damage Localization.

This work leverages ultrasonic guided waves (UGWs) to detect and localize damage in structures using lightweight Artificial Intelligence (AI) models. It investigates the use of machine learning (ML) to train the effects of the damage on UGWs to the model. To reduce the number of trainable parameters, a physical signal processing approach is applied to the raw data before passing the data to the model.

Is the EnodePro a Valid Tool to Determine the Bar Velocity in the Bench Press and Barbell Back Squat? A Comparative Analysis.

Unlabelled: In recent years, the EnodePro device has been one of the most frequently used velocity sensors to track the bar velocity in resistance training, with the aim of providing load-velocity profiles. However, recent articles highlight a lack of reliability and validity in the estimated maximal strength, which can cause a serious health risk due to the overestimation of the bar velocity. With this study, we aimed to investigate whether imprecision in the measurement could explain the variance in this measurement error.

GravelSens: A Smart Gravel Sensor for High-Resolution, Non-Destructive Monitoring of Clogging Dynamics.

Engineers, geomorphologists, and ecologists acknowledge the need for temporally and spatially resolved measurements of sediment clogging (also known as colmation) in permeable gravel-bed rivers due to its adverse impacts on water and habitat quality. In this paper, we present a novel method for non-destructive, real-time measurements of pore-scale sediment deposition and monitoring of clogging by using wire-mesh sensors (WMSs) embedded in spheres, forming a smart gravel bed (GravelSens). The measuring principle is based on one-by-one voltage excitation of transmitter electrodes, followed by simultaneous measurements of the resulting current by receiver electrodes at each crossing measuring pores.

A Magnetoelectric Distance Estimation System for Relative Human Motion Tracking.

Clinical motion analysis plays an important role in the diagnosis and treatment of mobility-limiting diseases. Within this assessment, relative (point-to-point) tracking of extremities could benefit from increased accuracy. Given the limitations of current wearable sensor technology, supplementary spatial data such as distance estimates could provide added value.

Determination of Vibration Properties and Reliable Frequency Estimation for Synchronous Vibrations Through Improved Blade Tip Timing Techniques Without a Once-per-Revolution Sensor.

Synchronous vibrations, which are caused by periodic excitations, can have a severe impact on the service life of impellers. Blade Tip Timing (BTT) is a promising technique for monitoring synchronous vibrations due to its non-intrusive nature and ability to monitor all blades at once. BTT generally employs a Once-per-Revolution (OPR) sensor that is mounted on the shaft for blade identification and deflection calculation.

An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control.

This paper focuses on the modeling, control, and simulation of an over-actuated hexacopter tilt-rotor (HTR). This configuration implies that two of the six actuators are independently tilted using servomotors, which provide high maneuverability and reliability. This approach is predicted to maintain zero pitch throughout the trajectory and is expected to improve the aircraft's steering accuracy.

Enhancing Localization Accuracy and Reducing Processing Time in Indoor Positioning Systems: A Comparative Analysis of AI Models.

This paper presents a comparative study of different AI models for indoor positioning systems, emphasizing improvements in localization accuracy and processing time. This study examines Artificial Neural Networks (ANNs), Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNNs), and the Kalman filter using a real Received Signal Strength Indicator (RSSI) and 9-axis ICM-20948 sensor. An in-depth analysis is provided in this paper for data cleaning and feature selection to reduce errors for all the models.

A Hybrid Approach for Sports Activity Recognition Using Key Body Descriptors and Hybrid Deep Learning Classifier.

This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descriptors, including MSER (Maximally Stable Extremal Regions), SURF (Speeded-Up Robust Features), distance transform, and DOF (Degrees of Freedom), were applied to skeleton points, while BRIEF (Binary Robust Independent Elementary Features), HOG (Histogram of Oriented Gradients), FAST (Features from Accelerated Segment Test), and Optical Flow were used on silhouettes or full-body points to capture both geometric and motion-based features.

Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines.

Assessing vines' vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features).

Multi-Person Localization Based on a Thermopile Array Sensor with Machine Learning and a Generative Data Model.

Thermopile sensor arrays provide a sufficient counterbalance between person detection and localization while preserving privacy through low resolution. The latter is especially important in the context of smart building automation applications. Current research has shown that there are two machine learning-based algorithms that are particularly prominent for general object detection: You Only Look Once (YOLOv5) and Detection Transformer (DETR).

TARREAN: A Novel Transformer with a Gate Recurrent Unit for Stylized Music Generation.

Music generation by AI algorithms like Transformer is currently a research hotspot. Existing methods often suffer from issues related to coherence and high computational costs. To address these problems, we propose a novel Transformer-based model that incorporates a gate recurrent unit with root mean square norm restriction (TARREAN).

Graphene/TiO Heterostructure Integrated with a Micro-Lightplate for Low-Power NO Gas Detection.

Low-power gas sensors that can be used in IoT (Internet of Things) systems, consumer devices, and point-of-care devices will enable new applications in environmental monitoring and health protection. We fabricated a monolithic chemiresistive gas sensor by integrating a micro-lightplate with a 2D sensing material composed of single-layer graphene and monolayer-thick TiO. Applying ultraviolet (380 nm) light with quantum energy above the TiO bandgap effectively enhanced the sensor responses.

Clinical Whole-Body Gait Characterization Using a Single RGB-D Sensor.

Instrumented gait analysis is widely used in clinical settings for the early detection of neurological disorders, monitoring disease progression, and evaluating fall risk. However, the gold-standard marker-based 3D motion analysis is limited by high time and personnel demands. Advances in computer vision now enable markerless whole-body tracking with high accuracy.