Search Results (717)

430 stainless steel exhibits soft magnetic properties, excellent formability, and corrosion resistance, making it widely used in industrial applications. This study investigates the effects of different cold working rates on the properties of 430 stainless steel subjected to various magnetic annealing atmospheres (F-1.5Si, F-1.5Si-10%, F-1.5Si-40%, F-1.5Si-10% (MA), F-1.5Si-40% (MA), F-1.5Si-10% (H₂), and F-1.5Si-40% (H₂)). The results indicate that increasing the cold working rate improves the material’s mechanical properties; however, it negatively impacts its magnetic and corrosion resistance properties. Additionally, the magnetic annealing process improves the mechanical properties, while atmospheric magnetic annealing optimizes the overall magnetic performance. In contrast, magnetic annealing in a hydrogen atmosphere does not enhance the magnetic properties as effectively as atmospheric magnetic annealing. Still, it promotes the formation of a protective layer, preserving the mechanical properties and providing better corrosion resistance. Furthermore, regardless of whether magnetic annealing is conducted in an atmospheric or hydrogen environment, materials with 10% cold work rate (F-1.5Si-10% (MA) and F-1.5Si-10% (H₂)) exhibit the lowest coercive force (286 and 293 A/m in the 10 Hz test condition), making them ideal for electromagnetic applications. Full article

In this work, research on liquid-based resistive switching devices is carried out, using bottom printable electrodes fabricated from Silver (Ag) paste and silver nitrate (AgNO₃) solution. The self-crossing I-V curves are observed and repeatedly shown by applying 100 sweep cycles, demonstrating repeatability and stability. This liquid device can be refreshed by adding extra droplets of AgNO₃ so that self-crossing I-V hysteresis with up to 493 dual sweeps can be obtained. The ability to be refreshed by supplying a new liquid solution demonstrates an advantage of liquid-based memristive devices, in comparison to their solid counterparts, where the switching layer is fixed after fabrication. The switching mechanism is attributed to Ag migration in the liquid, which narrows the gap between electrodes, giving rise to the observed phenomenon. The devices further show some synaptic properties including excitatory post-synaptic current (EPSC) and potentiation-depression, presenting opportunities to utilize the devices in mimicking some functions of biological neurons. The simplicity and cost-effectiveness of these devices may advance research into fluidic memristors, in which devices with versatile forms and shapes could be fabricated. Full article

This study investigates the relationship between economic growth and energy consumption using the Energy Kuznets Curve (EKC) framework. Spatial econometric models, including the Spatial Panel Lag Model and the Spatial Dynamic Panel Lag IV Model, are employed to capture both spatial and dynamic effects. The results indicate that energy consumption in Thailand is spatially clustered, with energy use tending to spill over into neighboring provinces and concentrating in specific regions. Key factors that positively influence energy consumption include gross provincial product (GPP) per capita, population density, and road density. Regions characterized by favorable climates, sufficient infrastructure, and high levels of economic activity exhibit higher per capita energy consumption. The EKC analysis reveals a U-shape relationship between GPP per capita and energy consumption in the BKK&VIC, CE, EA, WE, and NE regions. As many regions continue to experience rising energy consumption, the findings underscore the importance of Thailand adopting more efficient energy usage strategies in tandem with its economic development. Full article

Background/Objectives: Surgical treatment is generally recommended for adolescent idiopathic scoliosis (AIS) when the Cobb angle exceeds 50 degrees even after skeletal maturity or 40 degrees with remaining growth potential. However, limited evidence exists regarding the natural history of curves between 40 and 50 degrees during the late stage of skeletal growth. This study aimed to evaluate the curve progression in AIS patients with a curve between 40 and 50 degrees at Risser stage IV or V. Methods: The inclusion criteria were as follows: (1) AIS patients at the late stage of skeletal growth (Risser IV or V) and a (2) curve between 40 and 50 degrees, with a minimum follow-up of 5 years. Sex, age, the magnitude of the curve, the location of the apex, Risser stage, height, and weight were measured at the baseline and the final follow-up. Curve progression was defined as an increase in the Cobb angle of ≥5 degrees. Patients were also categorized based on whether their final Cobb angle was <50 or ≥50 degrees to evaluate additional risk factors. Results: A total of 97 patients were included, with a mean follow-up of 97 months. Their mean age was 14.6 years at the baseline and 22.6 years at the final follow-up. The mean Cobb angle increased from 42.6 to 45.1 degrees, with a mean change of 2.7 degrees and an annual progression rate of 0.35 degrees. Curve progression was observed in 38 patients (39.2%), and 24 patients (24.7%) reached a final Cobb angle ≥ 50 degrees. Younger age (p = 0.004) and Risser stage IV (p = 0.014) were significantly associated with curve progression. In patients with a final Cobb angle ≥ 50 degrees, Risser stage IV (p = 0.050) and a larger baseline curve magnitude (p = 0.045) were also significant risk factors. Conclusions: In AIS patients at the late stage of skeletal growth, 39.2% experienced significant curve progression. A younger age and Risser stage IV were identified as risk factors for curve progression. A larger baseline curve magnitude and Risser stage IV were also associated with a final Cobb angle ≥ 50 degrees. Full article

The deformation characteristics of the surrounding rock in tunnel groups are considered critical for the design of support structures and the assurance of the long-term safety of deep-buried diversion tunnels. The deformation behavior of surrounding rock in tunnel groups was investigated to guide structural support design. Field tests and numerical simulations were performed to analyze the distribution of ground stress and the ground reaction curve under varying conditions, including rock type, tunnel spacing, and burial depth. A solid unit–structural unit coupled simulation approach was adopted to derive the two-liner support characteristic curve and to examine the propagation behavior of concrete cracks. The influences of surrounding rock strength, reinforcement ratio, and secondary lining thickness on the bearing capacity of the secondary lining were systematically evaluated. The following findings were obtained: (1) The tunnel group effect was found to be negligible when the spacing (D) was ≥65 m and the burial depth was 1600 m. (2) Both P_0.3 and P_max of the secondary lining increased linearly with reinforcement ratio and thickness. (3) For surrounding rock of grade III (IV), 95% u_lim and 90% u_lim were found to be optimal support timings, with secondary lining forces remaining well below the cracking stress during construction. (4) For surrounding rock of grade V in tunnels with a burial depth of 200 m, 90% u_lim is recommended as the initial support timing. Support timings for tunnels with burial depths between 400 m and 800 m are 40 cm, 50 cm, and 60 cm, respectively. Design parameters should be adjusted based on grouting effects and monitoring data. Additional reinforcement is recommended for tunnels with burial depths between 1000 m and 2000 m to improve bearing capacity, with measures to enhance impermeability and reduce external water pressure. These findings contribute to the safe and reliable design of support structures for deep-buried diversion tunnels, providing technical support for design optimization and long-term operation. Full article

Accurate photovoltaic (PV) panel characterization is critical for optimizing renewable energy systems, but it is often hindered by the high cost of commercial tracers or the slow, error-prone nature of manual methods. This paper presents a low-cost, Arduino-based I–V curve tracer that overcomes these limitations through fully automated resistive load switching. By integrating a relay-controlled resistor bank managed by a single microcontroller, the system eliminates the need for manual intervention, enabling rapid and repeatable measurements in just 45 s. This rapid acquisition is a key advantage over manual systems, as it minimizes the impact of fluctuating environmental conditions and ensures the resulting I–V curve represents a stable operating point. Compared to commercial alternatives, our open-source solution offers significant benefits in cost, portability, and flexibility, making it ideal for field deployment. The system’s use of fixed, stable resistive loads for each measurement point also ensures high repeatability and straightforward comparison with theoretical models. Experimental validation demonstrated high agreement with a single-diode PV model, achieving a mean absolute percentage error (MAPE) of 4.40% against the manufacturer’s data. Furthermore, re-optimizing the model with field-acquired data reduces the MAPE from 18.23% to 7.06% under variable irradiance. This work provides an accessible, robust, and efficient tool for PV characterization, democratizing access for research, education, and field diagnostics. Full article

Accurate estimation of erupted lava volumes is essential for understanding volcanic processes, interpreting eruptive cycles, and assessing volcanic hazards. Traditional methods based on Mid-Infrared (MIR) satellite imagery require clear-sky conditions during eruptions and are prone to sensor saturation, limiting data availability. Here, we present an alternative approach based on the post-eruptive Thermal InfraRed (TIR) signal, using the recently proposed VRP_TIR method to quantify radiative energy loss during lava flow cooling. We identify thermally anomalous pixels in VIIRS I5 scenes (11.45 µm, 375 m resolution) using the TIRVolcH algorithm, this allowing the detection of subtle thermal anomalies throughout the cooling phase, and retrieve lava flow area by fitting theoretical cooling curves to observed VRP_TIR time series. Collating a dataset of 191 mafic eruptions that occurred between 2010 and 2025 at (i) Etna and Stromboli (Italy); (ii) Piton de la Fournaise (France); (iii) Bárðarbunga, Fagradalsfjall, and Sundhnúkagígar (Iceland); (iv) Kīlauea and Mauna Loa (United States); (v) Wolf, Fernandina, and Sierra Negra (Ecuador); (vi) Nyamuragira and Nyiragongo (DRC); (vii) Fogo (Cape Verde); and (viii) La Palma (Spain), we derive a new power-law equation describing mafic lava flow thickening as a function of time across five orders of magnitude (from 0.02 Mm³ to 5.5 km³). Finally, from knowledge of areas and episode durations, we estimate erupted volumes. The method is validated against 68 eruptions with known volumes, yielding high agreement (R² = 0.947; ρ = 0.96; MAPE = 28.60%), a negligible bias (MPE = −0.85%), and uncertainties within ±50%. Application to the February-March 2025 Etna eruption further corroborates the robustness of our workflow, from which we estimate a bulk erupted volume of 4.23 ± 2.12 × 10⁶ m³, in close agreement with preliminary estimates from independent data. Beyond volume estimation, we show that VRP_TIR cooling curves follow a consistent decay pattern that aligns with established theoretical thermal models, indicating a stable conductive regime during the cooling stage. This scale-invariant pattern suggests that crustal insulation and heat transfer across a solidifying boundary govern the thermal evolution of cooling basaltic flows. Full article

Background/Objectives: The clinical value of KRAS mutations in lung adenocarcinoma, alone or in combination with other mutations, has been assessed especially in advanced stages. This study evaluates how KRAS and the presence of co-mutations could affect survival in early-stage lung. Methods: We analyzed a real-world cohort including all staged NSCLC patients diagnosed and treated from 2018 to 2022 at our Institute with availability of NGS molecular data. Statistical analyses were made using log-rank test, the two-tailed Fisher’s exact test and Kaplan-Meier survival curves. Results: KRAS mutations were observed in 179/464 cases (38.6%). The majority of KRAS co-mutations were in TP53 (74%) and STK11 (14.3%) genes. KRAS+TP53 co-mutations were more frequent compared to KRAS-only tumors in stage IV NSCLC (p = 0.01). In early stage and locally advanced cases (stage I-III), better prognosis was associated to KRAS-only mutated NSCLC and to KRAS+STK11 mutated cases compared to KRAS+TP53 (p = 0.008). In particular, patients carrying KRAS+TP53 in stage I and II displayed a shorter survival, similar to patients diagnosed at stage III. Conclusions: Routine NGS provides important information for potential actionable mutations but also for the prognostic and predictive role of the presence of co-occurring mutations. In particular, the presence of KRAS+TP53 in stage I and II NSCLC may be considered an unfavorable prognostic marker possibly leading to adapt the perioperative chemo-immunotherapy. Full article

Current–voltage (I–V) characteristics are an important measure of photovoltaic (PV) generators, corresponding to environmental conditions regarding solar irradiance and temperature. The I–V curve tracer is a widely used instrument in power engineering to evaluate system performance and detect fault conditions in PV power systems. Several technologies have been applied to develop the device and trace I–V characteristics, improving accuracy, speed, and portability. Focusing on the outdoor environment, this paper presents an in-depth analysis and comparison of the system design and dynamics to identify the I–V tracing performance based on different power conversion topologies and data acquisition methods. This is a valuable reference for industry and academia to further the technology and promote sustainable power generation. Full article

Bifacial photovoltaic technology is made up of solar cells with the ability to generate electrical power on both sides of the cell (front and rear), consequently, they generate more energy in the same area compared to conventional or monofacial solar cells. The present work deals with the calculation of the energy yield using bifacial solar cells under the specific environmental conditions of Tampico, Tamaulipas, Mexico. Two configurations were compared: (1) tilted, optimized in height and angle, oriented to the south, and (2) vertically optimized in height, oriented east–west. The results were also compared with a standard monofacial solar cell optimally tilted and oriented south. The experimental data were acquired using a current–voltage (I-V) curve tracer designed for this purpose. This study shows that the vertically optimized bifacial solar cell produces similar electrical power to the conventional monofacial solar cell, with the benefit of maximum production in peak hours (8:30 and 16:30). In contrast, in the case of the inclined bifacial solar cell, about 26% more in the production of electrical power was reached. These results guide similar studies in other places of the Mexican Republic and regions with similar latitudes and climate. Full article

In this study, we comprehensively compare electrical conduction behavior under an applied electric field and electrical conductivity variation with temperature in low-density polyethylene (LDPE)/CNT composites with different dispersions and covalent functionalizations. Composites with different dispersions were prepared using solution and melt mixing processes. The solution-mixed composites exhibited better dispersion and higher electrical conductivity compared to the melt-mixed composites. At a high critical content (beyond the percolation threshold), the current–voltage (I–V) curve of the solution-mixed composites exhibited linear conduction behavior due to the formation of a continuous conductive network. In contrast, the melt-mixed composites exhibited nonlinear conduction behavior, with the conductive mechanism attributed to the field emission effect caused by poor interfacial contact between the CNTs. Additionally, LDPE/CNT-carboxyl (LDPE/CNT-COOH) and LDPE/CNT-hydroxy (LDPE/CNT-OH) composites demonstrated better dispersion but displayed lower electrical conductivity and similar nonlinear conduction behavior when compared to unmodified ones. This is attributed to the surface defects caused by the modification process, which lead to an increased energy barrier and a decreased transition frequency in the field emission effect. Furthermore, the temperature-dependent electrical conductivity results indicate that the variation trend in current with temperature differed among LDPE/CNT composites with different dispersions and covalent functionalizations. These differences were mainly influenced by the gap width between CNTs (mainly affected by dispersion and aspect ratio of CNTs), as well as the electrical conductivity of CNTs (mainly influenced by surface modification and intrinsic electrical conductivity of CNTs). Full article

In clinical applications of surface-enhanced Raman spectroscopy (SERS) immunosensors, accurately determining analyte biomarker concentrations is essential. This study presents a non-invasive approach for quantifying various breast cancer biomarkers—including human epidermal growth factor receptor II (HER-II) (2+, 3+ (I), 3+ (II), 3+ (III), and positive IV) and CA 15-3—using a directional, plasmonically active, label-free SERS sensor. Each stage of sensor functionalization, conjugation, and biomarker interaction was verified by UV–Vis spectroscopy. Atomic force microscopy (AFM) characterized the morphology of gold nanourchin (GNU)-immobilized printed circuit board (PCB) substrates. An enhancement factor of ≈ 0.5 × 10⁵ was achieved using Rhodamine 6G as the probe molecule. Calibration curves were initially established using standard HER-II solutions at concentrations ranging from 1 to 100 ng/mL and CA 15-3 at concentrations from 10 to 100 U/mL. The SERS signal intensities in the 620–720 nm region were plotted against concentration, yielding linear sensitivity with R² values of 0.942 and 0.800 for HER-II and CA15-3, respectively. The same procedure was applied to breast cancer serum (BCS) samples, allowing unknown biomarker concentrations to be determined based on the corresponding calibration curves. SERS data were processed using the filtfilt filter from scipy.signal for smoothing and then baseline-corrected with the Improved Asymmetric Least Squares (IASLS) algorithm from the pybaselines.Whittaker library. Principal Component Analysis (PCA) effectively distinguished the sample groups and revealed spectral differences before and after biomarker interactions. Key Raman peaks were attributed to functional groups including N–H (primary and secondary amines), C–H antisymmetric stretching, C–N (amines), C=O antisymmetric stretching, NH₃⁺ (amines), carbohydrates, glycine, alanine, amides III, C=N stretches, and NH₂ in primary amides. Full article

Background: Pancreatic cancer is among the most lethal malignancies, with poor prognosis and limited survival despite treatment advances. Accurate survival modeling is critical for prognostication and clinical decision-making. This study had three primary aims: (1) to determine the best-fitting survival distribution among patients diagnosed and deceased from pancreatic cancer across stages and treatment types; (2) to construct and compare predictive risk classification models; and (3) to evaluate survival probabilities using parametric, semi-parametric, non-parametric, machine learning, and deep learning methods for Stage IV patients receiving both chemotherapy and radiation. Methods: Using data from the SEER database, parametric models (Generalized Extreme Value, Generalized Pareto, Log-Pearson 3), semi-parametric (Cox), and non-parametric (Kaplan–Meier) methods were compared with four machine learning models (gradient boosting, neural network, elastic net, and random forest). Survival probability heatmaps were constructed, and six classification models were developed for risk stratification. ROC curves, accuracy, and goodness-of-fit tests were used for model validation. Statistical tests included Kruskal–Wallis, pairwise Wilcoxon, and chi-square. Results: Generalized Extreme Value (GEV) was found to be the best-fitting distribution in most of the scenarios. Stage-specific survival differences were statistically significant. The highest predictive accuracy (AUC: 0.947; accuracy: 56.8%) was observed in patients receiving both chemotherapy and radiation. The gradient boosting model predicted the most optimistic survival, while random forest showed a sharp decline after 15 months. Conclusions: This study emphasizes the importance of selecting appropriate analytical models for survival prediction and risk classification. Adopting these innovations, with the help of advanced machine learning and deep learning models, can enhance patient outcomes and advance precision medicine initiatives. Full article

Geological hazards pose significant threats to ecological stability, human lives, and infrastructure, necessitating precise and robust risk assessment methodologies. This study evaluates geological hazard risks in Dawukou District, Shizuishan City, Ningxia Hui Autonomous Region, using the information value (IV) model. The study systematically identifies susceptibility, hazard, and vulnerability factors influencing geological disaster risks by integrating diverse datasets encompassing geological conditions, meteorological parameters, and anthropogenic activities. The key findings reveal that hilly landforms, slope gradients, and vegetation indices are the dominant contributors to hazard development. Additional factors, including lithology, fault proximity, and precipitation, were also found to play critical roles. The results categorize the district into four risk zones: high-risk areas (1.55% of the total area), moderate-risk areas (10.16%), Low-risk areas (23.32%), and very-low-risk areas (64.97%). These zones exhibit a strong spatial correlation with geomorphic features, tectonic activity, and human engineering interventions, such as mining and infrastructure development. High-risk zones are concentrated near mining regions and fault lines with steep slopes, while low-risk zones are predominantly in flat plains and urban centers. The reliability of the risk assessment was validated through cross-referenced geological hazard occurrence data and Receiver Operating Characteristic (ROC) curve analysis, achieving a high predictive accuracy (AUC = 0.88). The study provides actionable insights for disaster prevention, mitigation strategies, and urban planning, offering a scientific basis for resource allocation and sustainable development. The methodology and findings serve as a replicable framework for geological hazard risk assessments in similar regions facing diverse environmental and anthropogenic challenges. Full article

Belle II is a particle physics experiment working at an high luminosity collider within a hard irradiation environment. The Time-Of-Propagation detector, aimed at the charged particle identification, surrounds the Belle II tracking detector on the barrel part. This detector is composed by 16 modules, each module contains a finely fused silica bar, coupled to microchannel plate photomultiplier tube (MCP-PMT) photo-detectors and readout by high-speed electronics. The MCP-PMT lifetime at the nominal collider luminosity is about one year, this is due to the high photon background degrading the quantum efficiency of the photocathode. An alternative to these MCP-PMTs is multi-pixel photon counters (MPPC), known as silicon photomultipliers (SiPM). The SiPMs, in comparison to MCP-PMTs, have a lower cost, higher photon detection efficiency and are unaffected by the presence of a magnetic field, but also have a higher dark count rate that rapidly increases with the integrated neutron flux. The dark count rate can be mitigated by annealing the damaged devices and/or operating them at low temperatures. We tested SiPMs, with different dimensions and pixel sizes from different producers, to study their time resolution (the main constraint that has to satisfy the photon detector) and to understand their behavior and tolerance to radiation. For these studies we irradiated the devices to radiation up to $5\times {10}^{11}1$ MeV neutrons equivalent (neq) per cm² fluences; we also started studying the effect of annealing on dark count rates. We performed several measurements on these devices, on top of the dark count rate, at different conditions in terms of overvoltage and temperatures. These measurements are: IV-curves, amplitude spectra, time resolution. For the last two measurements we illuminated the devices with a picosecond pulsed laser at very low intensities (with a number of detected photons up to about twenty). We present results mainly on two types of SiPMs. A new SiPM prototype developed in collaboration with FBK with the aim of improving radiation hardness, is expected to be delivered in September 2025. Full article