Advancing Open Science

Diseases of the gastrointestinal tract (GI) represent a major global health burden, leading to more than eight million deaths each year, largely driven by malignant conditions such as cancers and tumors. Early detection of such conditions can significantly improve survival rates. In this work, we present a compact two-port MIMO topology for high-speed telemetry and sensing. This system integrates two identical antennas, each operating at 915 MHz, positioned only 0.55 mm apart. It has just 11.9 mm³ (6.9 mm × 6.9 mm × 0.25 mm) volume, achieved through the use of meandered resonator and a high-dielectric laminate for miniaturization. Despite its small size, the design delivers a measured peak gain of −25.1 dBi at resonance. Low mutual coupling in the antenna-system is made possible by maintaining an optimized spacing and introducing a slot in the ground plane, resulting in isolation levels above 27.9 dB. The MIMO configuration was evaluated using standard performance metrics, and at an SNR of 20 dB, the system reached a better performance than single-element antenna. Beyond communication, this design also functions as a sensor, with its resonant frequency shifting in response to changes in the surrounding tissue’s permittivity: enabling real-time monitoring of internal physiological changes. Throughout the sensing process, the design maintains good gain and impedance matching, making it a strong candidate for biomedical implants.

Dissemination of unit of mass is one of the key processes in mass metrology and involves a large number of measurements to determine the mass of weights across a wide range (e.g., 1 mg–10 kg in the case of the Czech Metrology Institute, CMI). Evaluation of such measurements can be challenging, and to address this, the European Metrology Programme for Innovation and Research (EMPIR) project 19RPT02 “Improvements of the realisation of the mass scale” developed RealMass software solution (currently available in version 1.1) and a draft calibration procedure. However, standard procedures usually assume either identical densities of the weights or use the volume of the weights for buoyancy correction. In the latter case, if the volume is not known, the usual approach is to estimate it by dividing the nominal mass by the density. If the weights differ in either volume or density, these procedures lead to incorrect results. CMI developed a model and evaluation script to address these issues. The comparison data show that the developed model is consistent with the results obtained by RealMass software and other examples. The examples given in the text show how incorrect assumptions can lead to incorrect results and how they are evaluated by the approach presented in this paper.

This study investigates the application of the Pure Random Orthogonal Search (PROS) method, introduced in the literature in 2021, for approximating force and displacement measurement data obtained from rock specimen testing, using granite as a case study. The primary objective is to simplify the data approximation procedure and improve the accuracy of experimental data analysis by reducing the influence of subjective factors within a predefined protocol. The research focuses on determining the maximum value of the tangent modulus of elasticity during the pre-peak deformation stage of granite specimens under uniaxial compression. The study employs methods of mathematical modeling of rock mechanical behavior and experimental data analysis. To approximate the experimental data, a modified two-parameter S-curve equation is proposed. The optimal parameter values are determined using the PROS method, which reduces the problem to solving a two-dimensional objective function minimization task. The dimensionality of this optimization problem remains independent of the number of experimental data points, thereby enhancing computational efficiency. A systematic computational procedure is developed for the automated calculation of the approximating equation’s parameters and the determination of the maximum tangent modulus of elasticity. In the context of challenges associated with accurately measuring displacements using conventional testing machines, a numerical correction procedure is proposed and implemented to account for the compliance of the loading system. The results of the study are consistent with both the literature-reported experimental data and the data obtained in this work. The methodology and findings can be adapted for analyzing the properties of concrete as an artificial analog of natural rock materials.

Analyzing customer feedback is critical for identifying unmet needs in product development and innovation processes. However, current studies often focus only on identifying customer-expressed problems, neglecting to systematically match these problems with technological solutions and transform them into potential product features. This study aims to propose a sentiment and semantic analysis-based approach that correlates problems derived from customer feedback with patent-based solutions. The proposed approach utilizes Aspect-Based Sentiment Analysis to identify unmet needs from customer feedback, the BERTopic algorithm to extract solution-oriented themes from patent documents, and short text semantic similarity methods to associate problem-solution pairs. The applicability of the approach is demonstrated using 476 customer product reviews and 3548 patents in the Heating, Ventilation, and Air Conditioning (HVAC) field. The results show that customer-expressed problems can be semantically correlated with patent-based technological solutions, and these matches contribute to the identification of potential product features. The resulting problem-solution matches are structured along technological development horizons and presented as a technology roadmap output. The proposed approach offers a framework supporting systematic problem–solution matching based on sentiment and semantic analysis in technology-intensive sectors with large volumes of unstructured text data.

This study proposes an end-to-end mathematical framework to automatically transform warehouse layout images into optimization-ready route matrices. The objective is to convert visual spatial information into a discrete, graph-based representation suitable for combinatorial route optimization. The problem is formulated as a mapping from continuous image space to a structured grid representation, integrating image segmentation, graph construction, and Traveling Salesman Problem (TSP)-based routing. Synthetic warehouse layouts were generated to create labeled training data, and a U-Net convolutional neural network was trained to perform multi-class segmentation of warehouse elements. The predicted grid representation was then converted into a graph structure, where feasible cells define vertices and adjacency defines edges. Shortest path distances were computed using Breadth-First Search, and the resulting distance matrix was used to solve a TSP instance. The segmentation model achieved approximately 98% training accuracy and 95–97% validation accuracy. The generated route matrices enabled successful construction of feasible and optimal round-trip routes in all tested scenarios. The proposed framework demonstrates that warehouse layouts can be automatically transformed into discrete mathematical representations suitable for logistics optimization, reducing manual preprocessing and enabling scalable integration into digital logistics systems.

Background/Objectives: This study aimed to assess the safety and efficacy of lung surgery for the treatment of early-stage non-small cell lung cancer (NSCLC) in octogenarians, with a specific focus on the Uniportal-VATS approach, evaluating surgical outcomes and short-term oncological results within a precision medicine perspective. Methods: This retrospective, single-center study included octogenarian patients who underwent surgical treatment for early-stage NSCLC between January 2018 and March 2024. Among 1329 patients treated during the study period, 136 octogenarians were carefully evaluated by a multidisciplinary board and selected for surgical management. Results: The mean age was 82.41 ± 2.72 years, with a prevalence of men (63.2%). In 107 (78.7%) cases, lung resection was performed using the Uniportal-video-assisted thoracic surgery (U-VATS) approach. Overall, 71 lobectomies (52.2%) and 65 segmentectomies or wedge resections (47.8%) were performed, balancing oncological radicality with comorbidities. Only minor complications occurred, such as atelectasis (2.9%), atrial fibrillation (4.4%), pneumonia (1.5%), or air-leakage (2.2%). Factors significantly associated with postoperative complications included open approach (p = 0.014), lobectomy as the extent of resection (p = 0.008), and chronic obstructive pulmonary disease (COPD) (p = 0.010). On multivariable analysis, lobectomy remained the only independent predictor for postoperative complications (OR: 5.95, 95% CI [1.24–28.62], p = 0.026). In-hospital and 90-day mortality were null. The median length of hospital stay in octogenarians was 6 days and was significantly shorter in the Uniportal-VATS group compared with the open surgery one (p < 0.001). All patients were discharged home independently. One- and three-year overall survival rates were 88% and 71%, respectively. No risk factor was associated with mortality in our series. Conclusions: Lung surgery, particularly the Uniportal-VATS approach, appears to be a safe and effective treatment option for octogenarian patients with early-stage NSCLC, provided that patient selection is carefully based on individual clinical characteristics within a multidisciplinary framework based on individualized risk stratification. When feasible, sublobar resection should be preferred in order to minimize postoperative complications.

The analytical surveillance of sulfite species (SO₃²⁻, SO₂ and HSO₃⁻) is critical for food safety due to their roles as preservatives and potent allergens. Despite stringent regulations, conventional methods like Monier-Williams distillation remain limited by labor-intensive protocols and matrix interferences. This review elucidates the chemical mechanisms of sulfites in food matrices and critically evaluates recent advancements in electrochemical sensing. A primary focus is placed on delineating physicochemical bottlenecks, such as electrode fouling and cross-reactivity from polyphenols and organic acids, which hinder commercialization. We analyze the strategic integration of nanostructured interfaces—including bimetallic nanoparticles, carbon-based hybrids (rGO/PPy), and nanozymes—to reduce oxidation overpotentials and enhance sensitivity below regulatory thresholds. Furthermore, the transition from laboratory prototypes to decentralized, field-deployable platforms using screen-printed electrodes (SPEs) and smartphone-based potentiostats is explored. By synthesizing technical innovations with “green” analytical principles, this work provides a roadmap for real-time quality control in the food industry, bridging the gap between fundamental electrochemistry and industrial scalability.

Hepatic encephalopathy is a severe complication of liver failure, traditionally investigated through brain–liver interactions; however, the involvement of extrahepatic organs remains poorly understood. This study examined splenic histopathological changes in a mouse model of acute hepatic encephalopathy induced by ammonium acetate administration, focusing on iron metabolism and macrophage activation. Although conventional hematoxylin and eosin staining revealed no overt structural abnormalities, unstained spleen sections demonstrated abundant black deposits, predominantly in the red pulp. Prussian blue staining confirmed a significant increase in hemosiderin-positive cells; however, a subset of black deposits was iron-negative. Immunohistochemical analyses revealed that these iron-negative pigments were localized within F4/80-positive macrophages and colocalized with heme oxygenase-1 (HO-1), suggesting enhanced heme degradation. Ultrastructural observations further identified electron-dense granules consistent with hematin accumulation in splenic macrophages. Hematological analyses revealed significant reductions in red blood cell count and hemoglobin levels, indicating accelerated erythrocyte destruction. Collectively, these findings demonstrate that acute hepatic encephalopathy induces splenic macrophage activation, accompanied by disordered iron metabolism and hematin accumulation. This study highlights the spleen as a previously underappreciated extrahepatic organ involved in the pathophysiology of hepatic encephalopathy and suggests that splenic heme–iron handling may represent a novel therapeutic target.