Search Results (5,881)

A flow cell is a critical measurement interface for many optical instruments. However, the flows are often sampled under harsh conditions, such as under high pressure and/or high temperature, in the presence of particles, moisture, vapors with high dew points or corrosive gases. Therefore, obtaining a high-optical-quality flow cell that does not perturb the measurement is a significant challenge. To address this challenge, we proposed a new flow cell that employs a unique laminar coaxial flow field (for the purge and sample flows). A test system was built to conduct particle size distribution (PSD) measurements with no sampling bias using a state-of-the-art analyzer (Malvern Panalytical Insitec). The results revealed that the measurement zone is well defined solely by the sample flow, and the optical windows are well protected by the purge flow, with minimal risk of any depositions from the sample flow. Using this flow cell, the Insitec can successfully measure PSD under high pressure and temperature under moist, corrosive conditions without generating any sampling bias. Importantly, we successfully applied this flow cell for on-line PSD measurement for the flue gas of a 100 kW_th pressurized oxy-coal combustor operating at 15 bara. Full article

Due to climate change, the temperature monitoring of reinforced-concrete (RC) structures is becoming critical for preventive maintenance and extending their lifespan. Significant temperature variations in RC elements can affect their natural frequencies and modulus of elasticity or generate abnormal stress levels, potentially leading to structural damage. Data from thermal monitoring systems are invaluable for testing and validating numerical methodologies for estimating internal thermal responses and aiding in prevention/maintenance decision making. Despite its importance, few experimental outdoor data on the internal and external temperatures of concrete structures are available. This study presents a comprehensive dataset from a 120-day temperature-monitoring campaign on a 1.2 m long reinforced-concrete slab-on-I-beam model under tropical conditions in Bucaramanga, Colombia. The monitoring system measured the internal temperatures at 40 points using embedded thermocouples, while the surface temperatures were recorded with handheld and drone-mounted thermal cameras. Simultaneously, the ambient temperature, solar radiation, rainfall, wind velocity, and other parameters were monitored using a weather station. The instrumentation ensured the synchronization and high spatial resolution of the thermal data. The data, collected at 30 min intervals, are openly available in CSV format, offering valuable resources for validating numerical models, studying thermal gradients, and enhancing structural health-monitoring frameworks. Full article

Healthcare 4.0 addresses modernization and digital transformation challenges, such as home-based care and precision treatments, by leveraging advanced technologies to enhance accessibility and efficiency. Semantic technologies, particularly knowledge graphs (KGs), have proven instrumental in representing interconnected medical data and improving clinical decision-support systems. We previously introduced a semantic framework to assist medical experts during patient interactions. Operating iteratively, the framework prompts medical experts with relevant questions based on patient input, progressing toward accurate diagnoses in time-constrained settings. It comprises two components: (a) a KG representing symptoms, diseases, and their relationships, and (b) algorithms that generate questions and prioritize hypotheses—a ranked list of symptom–disease pairs. An earlier extension enriched the KG with a symptom ontology, incorporating hierarchical structures and inheritance relationships to improve accuracy and question-generation capabilities. This paper further extends the framework by introducing strategies tailored to specific medical domains. Strategies integrate domain-specific knowledge and algorithms, refining decision making while maintaining the iterative nature of expert–patient interactions. We demonstrate this approach using an emergency medicine case study, focusing on life-threatening conditions. The KG is enriched with attributes tailored to emergency contexts and supported by dedicated algorithms. Boolean rules attached to graph edges evaluate to TRUE or FALSE at runtime based on patient-specific data. These enhancements optimize decision making by embedding domain-specific goal-oriented knowledge and inference processes, providing a scalable and adaptable solution for diverse medical contexts. Full article

Natural rubber, a renewable material with unique properties, is crucial for various products on the modern market. Crepe rubber, a versatile form of natural rubber, is widely used in numerous applications, including footwear soles, medical devices, automotive parts, adhesives, sports equipment, industrial components, musical instruments, and recreational products. Sri Lanka holds a prominent position as a leading producer of premium-quality crepe rubber but faces environmental challenges in its production process. Since previous life cycle assessments (LCAs) in the rubber industry are inadequate to capture the overall environmental impact, the present study attempted to address the gaps by conducting a detailed LCA of a Sri Lankan crepe rubber factory, incorporating a novel index termed the trade-off valuation index (TOVI). The research revealed that fertilizer, water, and electricity use contribute most significantly to crepe rubber production’s environmental impact. To mitigate these impacts, four key improvement options were identified and evaluated through scenario analysis: (1) enhancing fertilizer efficiency, (2) repairing leaky joints and valves, (3) implementing a water reuse system, and (4) installing solar panels. The integration of the TOVI allowed for the prioritization of these options, providing actionable insights for industry stakeholders. This study paves the way for targeted interventions to enhance the sustainability of the natural rubber industry by balancing economic viability with environmental stewardship. Full article

The complex resistivity (CR) measurement constitutes a practical methodology for investigating the internal structures of rocks and ores alongside their mineralogical compositions and the chemical properties of fluids. However, during complex resistivity testing, particularly at high frequencies, the leakage current caused by the distributed capacitance of the instrument’s acquisition channels reduces the measurement accuracy. Additionally, the contact impedance of the measuring devices and the electromagnetic coupling effects of the measurement cables further affect the complex resistivity test results of samples. To accurately characterize samples’ intrinsic induced polarization (IP) properties, we developed a broadband complex resistivity measurement system (1 mHz–100 kHz) for rocks and ores, comprising a complex resistivity analyzer and a sample holder, employing the four-electrode method. In this study, we establish a circuit model for the measurement system to analyze the influence of the distributed capacitance of the acquisition channels on the test results at elevated frequencies. We derive the error terms inherent in the instrument’s measurements across various circuit design configurations and propose a novel method for calculating the distributed capacitance of the instrument’s acquisition channels, the parasitic capacitance of the sampling resistor, and for calibrating data by reversing the polarity of the excitation signal. Furthermore, we investigate the effect of contact impedance within the measurement setup on test results and design two sample-testing devices. Through extensive testing on multiple circuit models and samples, the system achieves an accuracy of up to 1% within the 10 MΩ range. Its overall performance surpasses that of the Solartron 1260A impedance analyzer and traditional signal source forward connection calibration methods. This advancement holds significant implications for complex resistivity measurements and the study of rock physical properties. Full article

Crude oil prices have a key meaning for the economies of most countries. Their levels shape the general production costs in many sectors. Oil prices are also a base for financial derivatives like CFD contracts, which are popular nowadays. Due to these reasons, the possibility of an effective prediction of the direction of future changes in the price of crude oil is especially significant. Most existing works focus on the analysis of daily closing prices. This kind of approach results, on the one hand, in losing important information about the dynamics of changes during the day. On the other hand, it does not allow for the modelling of short-term price changes that are especially important in cases of financial derivatives having crude oil as their base instrument. The goal of the following article is the analysis of possible applications of a binary–temporal representation in the modelling and construction of effective decision support systems on the crude oil market. The analysis encompasses all researched state models, e.g., those applying mean and trend analysis. Also, the selection of parameters was optimized for Brent crude oil rates. The presented research confirms the high effectiveness of our state modelling system in predicting oil prices on a level that allows for the construction of financially effective investment decision support systems. The obtained results were verified based on proper backtests from different quotation periods. The presented results can be used both in scientific analyses and in the construction of investment support tools for the crude oil market. Full article

Waveform generation as part of on-chip built-in self-test (BIST) circuitry often necessitates sufficient linearity without expensive hardware overhead. Achieving high linearity is critical for accurate signal generation, especially in applications requiring high precision, such as biomedical and instrumentation applications. Currently, achieving the high linearity and precision required in signal generators often relies on costly hardware such as automated test equipment (ATE). This paper presents a DAC-based arbitrary waveform generator (AWG). We use a low-cost DAC and a fully digital on-chip testing and calibration approach to nullify the effect of the DAC’s non-linearity on the generated waveform. The ultra-low cost and high linearity benefit of the proposed waveform generator makes it highly suitable for integration into resource-constrained systems. The proposed approach is validated using simulation results of the small-area DAC designed in TSMC 0.18 μm technology and the testing and calibration algorithms implemented in MATLAB. The DAC, designed with a matching accuracy at only the 5-bit level, is able to generate a signal with an ENOB of 12 bits alongside an SFDR and THD surpassing 100 dB. This high level of signal purity is consistently maintained across 100 Monte Carlo simulations, demonstrating the robustness of the architecture against PVT variations as well as random mismatches. Full article

To facilitate the effective assessment of respiratory entropy during poultry breeding, a novel oxygen (O₂) and carbon dioxide (CO₂) sensor was developed based on the off−axis integrated cavity output spectroscopy technique, featuring effective absorption optical paths of 15.5 m and 8.5 m, respectively. The sensor employs integrated environmental control technology, substantially enhancing detection precision. To improve the instrument’s response speed, the miniaturization of the cavity and structural optimization were implemented, achieving a rapid response time of merely 6.22 s, addressing the stringent requirements for quick responsiveness in poultry respiration thermometry research. A signal processing model tailored for on−site applications was designed, boosting the system’s signal−to−noise ratio by 4.7 times under complex environmental noise conditions. Utilizing Allan variance analysis, the sensor’s detection limits for O₂ and CO₂ were ascertained to be 2.9 ppm and 7.4 ppb, respectively. A 24−h field application test conducted in Gongzhuling demonstrated that the sensor’s results align with the respiratory characteristics of poultry under normal physiological conditions, validating its extensive potential for application in respiratory analysis, environmental monitoring, and industrial sectors. Full article

An important way to realize urban–rural integration and regional coordinated development is to attract labor forces back to rural areas. Most of the existing studies consider the impact of individual factors on population migration, they lack a systematic framework to analyze the combined impact of different factors on rural return migration. Furthermore, in practice, the interaction within the rural social ecosystem as an important driver of return migration is always ignored. Using data from 131 villages in 14 cities in Guangxi, China, combined with the Coupled Infrastructure System framework and the sustainable livelihoods framework, this paper analyzes the comprehensive impact of internal components of the rural social ecosystem on return migration. Qualitative comparative analysis is used to identify four condition combinations that can effectively promote return migration and five condition combinations that make return migration vulnerable. The main conclusions are as follows. First, high-level public infrastructure providers are an important driving factor for labor return to rural areas, and a substitution effect exists between them and livelihood capitals. Second, sufficient human capital and social capital are crucial for return migration, highlighting the importance of the structure of rural members and the collective atmosphere. Third, natural capital and economic capital emphasized by previous research are not key conditions for forming a high level of return migration. Fourth, the vulnerability of return migration is mainly caused by the decline of social capital, the loss of public infrastructure providers, and excessive dependence on economic or physical capital input. To attract return migration, rural areas need to pay attention to the integration and synergy of multi-dimensional capital and public infrastructure providers, and special emphasis should be placed on the cultivation of public leadership to promote the enhancement of human capital and social capital. This paper provides a more comprehensive and instrumental analytical perspective for understanding and promoting rural return migration. While deepening the understanding of the dynamic relationship between rural social ecosystem and labor mobility, it also offers policy insights for developing countries to achieve integrated urban–rural development. Full article

Introduction: Robot-assisted minimally invasive gastrectomy (RAMIG) represents a significant advancement in the surgical management of gastric cancer, offering superior dexterity, enhanced visualization, and improved ergonomics compared to laparoscopic gastrectomy (LG). This review systematically evaluates the current evidence on perioperative outcomes, oncological efficacy, learning curves, and economic considerations, providing insights into RAMIG’s potential role in modern gastric cancer surgery. Methods: A thorough analysis of retrospective, prospective, and meta-analytic studies was conducted to compare RAMIG with LG. Key outcomes, including operative time, intraoperative blood loss, lymph node retrieval, postoperative complications, learning curve duration, and cost-effectiveness, were assessed. Emphasis was placed on both short-term and long-term oncological outcomes to determine the clinical value of RAMIG. Results: Evidence indicates that RAMIG is associated with reduced intraoperative blood loss, lower morbidity rates, and a shorter learning curve, with proficiency achieved after 11–25 cases compared to 40–60 cases for LG. The robotic platform’s articulated instruments and enhanced three-dimensional visualization enable more precise lymphadenectomy, particularly in complex anatomical regions. Despite these advantages, operative time remains longer, and costs remain higher due to system acquisition, maintenance, and consumable expenses. However, emerging data suggest a gradual narrowing of cost disparities. While short-term outcomes are favorable, further high-quality, multicenter studies are needed to validate long-term oncological efficacy and survival outcomes. Conclusion: RAMIG offers significant technical and clinical advantages over conventional LG, particularly in terms of precision and learning efficiency. However, the long-term oncological benefits and economic feasibility require further validation. Future research should focus on cost optimization, advanced technological integration such as near-infrared fluorescence and artificial intelligence, and multicenter trials to solidify RAMIG’s role as a standard approach for gastric cancer surgery. Full article

Solar eclipses present a valuable opportunity for controlled in situ ionosphere studies. This work explores the response of the upper atmosphere’s F-layer during the total eclipse of April 8, 2024, which was primarily visible across North and South America. Employing a multi-instrument approach, we analyze the impact on the ionosphere’s Total Electron Content (TEC) and Very Low Frequency (VLF) signals over a three-day period encompassing the eclipse (April 7 to 9, 2024). Ground-based observations leverage data from ten International GNSS Service (IGS)/Global Positioning System (GPS) stations and four VLF stations situated along the eclipse path. We compute vertical TEC ($VTEC$) alongside temporal variations in the VLF signal amplitude and phase to elucidate the ionosphere’s response. Notably, the IGS station data reveal a decrease in $VTEC$ during the partial and total solar eclipse phases, signifying a reduction in ionization. While VLF data also exhibit a general decrease, they display more prominent fluctuations. Space-based observations incorporate data from Swarm and COSMIC-2 satellites as they traverse the eclipse path. Additionally, a spatiotemporal analysis utilizes data from the Global Ionospheric Map (GIM) database and the DLR’s (The German Aerospace Center’s) database. All space-based observations consistently demonstrate a significant depletion in $VTEC$ during the eclipse. We further investigate the correlation between the percentage change in $VTEC$ and the degree of solar obscuration, revealing a positive relationship. The consistent findings obtained from this comprehensive observational campaign bolster our understanding of the physical mechanisms governing ionospheric variability during solar eclipses. The observed depletion in $VTEC$ aligns with the established principle that reduced solar radiation leads to decreased ionization within the ionosphere. Finally, geomagnetic data analysis confirms that external disturbances do not significantly influence our observations. Full article

Normal pressure hydrocephalus (NPH) is a recognized cause of reversible cognitive and motor decline, with gait and balance impairments often emerging early. Technologies providing gait and balance measures can aid in early detection, diagnosis, and prognosis of the disease. This systematic review comprehensively discusses previous studies on the instrumental assessment of gait and balance in NPH. A PubMed search following PRISMA guidelines identified studies published between 2000 and 2024 that used laboratory instruments to assess gait and balance in NPH. Studies underwent quality assessment for internal, statistical, and external validity. Methodological details such as motor tasks, instruments, analytical approaches, and main findings were summarized. Overall, this review includes 41 studies on gait and 17 on balance, most of which used observational, cross-sectional designs. These studies employed various tools, such as pressure-sensitive platforms, optoelectronic motion-capture systems, and wearable inertial sensors. Significant differences in kinematic measures of gait and balance have been found in NPH patients compared to healthy controls and individuals with other neurological conditions. Finally, this review explores potential pathophysiological mechanisms underlying the kinematic changes in gait and balance in NPH and emphasizes the absence of longitudinal data, which hinders drawing definitive conclusions for prognostic purposes. Full article

Passive radar has drawn a lot of attention due to its applications across military and civilian sectors. Under this working paradigm, the utilization of antenna arrays is instrumental, as it increases the signal quality and enables precise target positioning. These promising features rely, however, on the precise calibration of the antenna array, as the different hardware components introduce impairments that compromise the beamforming capabilities of the system. We propose a technique that employs a low-power external beacon signal to produce precise information about the target location, avoiding the angular ambiguities present in other solutions in the literature. The experimental results demonstrate the method’s ability to effectively correct the amplitude and phase inconsistencies while compensating for frequency drifts, enabling beamforming capabilities and direction-of-arrival estimation. Among the tested beacon waveforms, the pseudo-random noise-based signals proved the most robust, especially in low-power scenarios. Additionally, the method was validated in a passive radar setup, where it successfully detected a vessel using opportunistic signals. These findings highlight the method’s potential to enhance passive radar performance while maintaining a low probability of detection, a key aspect in military applications, as well as its applicability to civilian purposes, such as infrastructure monitoring, environmental observation, and traffic management. Full article

Fiber-optic sensing has shown promising development for use in detecting magnetic fields for downhole and biomedical applications. Coupling existing fiber-based strain sensors with highly magnetostrictive materials allows for a new method of magnetic characterization capable of distributed and high-sensitivity field measurements. This study investigates the strain response of the highly magnetostrictive alloys Metglas^® 2605SC and Vitrovac^® 7600 T70 using Fiber Bragg Grating (FBG) acoustic sensors and an applied AC magnetic field. Sentek Instrument’s picoDAS interrogated the distributed FBG sensors set atop a ribbon of magnetostrictive material, and the corresponding strain response transferred to the fiber was analyzed. Using the Vitrovac^® ribbon, a minimal detectable field amplitude of 60 nT was achieved. Using Metglas^®, an even better sensitivity was demonstrated, where detected field amplitudes as low as 3 nT were measured via the strain response imparted to the FBG sensor. Distributed FBG sensors are readily available commercially, easily integrated into existing interrogation systems, and require no bonding to the magnetostrictive material for field detection. The simple sensor configuration with nanotesla-level sensitivity lends itself as a promising means of magnetic characterization and demonstrates the potential of fiber-optic acoustic sensors for distributed measurements. Full article

The use of a dense network of commercial high-cost seismographs for earthquake monitoring is often financially unfeasible. A viable alternative to address this limitation is the development of a network of low-cost seismographs capable of monitoring local seismic events with a precision comparable to that of high-cost instruments within a specified distance from the epicenter. The primary aim of this study is to compare the performance of an advanced, contemporary low-cost seismograph with that of a commercial, high-cost seismograph. The proposed system is enhanced through the integration of a 24-bit analog-to-digital converter board and an optimized architecture for a low-noise signal amplifier employing active components for seismic signal detection. To calibrate and assess the performance of the low-cost seismograph, an installation was deployed in a region of high seismic activity in Evgiros, Lefkada Island, Greece. The low-cost system was co-located with a high-resolution 24-bit commercial digitizer, equipped with a broadband (30 s—50 Hz) seismometer. An uninterrupted dataset was collected from the low-cost system over a period of more than two years, encompassing 60 local events with magnitudes ranging from 0.9 to 3.2, epicentral distances from 5.71 km to 23.45 km, and focal depths from 1.83 km to 19.69 km. Preliminary findings demonstrate a significant improvement in the accuracy of earthquake magnitude estimation compared to the initial configuration of the low-cost seismograph. Specifically, the proposed system achieved a mean error of ±0.087 when benchmarked against the data collected by the high-cost commercial seismograph. These results underscore the potential of low-cost seismographs to serve as an effective and financially accessible solution for local seismic monitoring. Full article