Search Results (93)

Background/Objectives: Ibrutinib is a selective Bruton’s tyrosine kinase inhibitor approved for the treatment of chronic lymphocytic leukemia (CLL). This drug exhibits significant variability in response and toxicity profile, possibly due to genetic polymorphisms in drug-metabolizing enzymes and transporters. The aim of this observational study is to address interindividual variability in the efficacy and safety of ibrutinib treatment in 49 CLL patients. Methods: Genotyping of nine polymorphisms was performed by quantitative polymerase chain reaction (qPCR) using a ViiA7^® PCR Instrument and TaqMan assays, and ibrutinib plasma concentrations were determined using high-performance liquid chromatography coupled to a tandem mass spectrometry detector (HPLC-MS/MS). Results: Our study confirmed a high response rate, with 62% of patients achieving complete remission (CR), 9% CR with incomplete hematologic recovery (CRi), and 24% partial remission (PR). The impact of genetic polymorphisms on the CR rate was evaluated, revealing no statistically significant associations for CYP3A4, CYP3A5, ABCB1, ABCG2, and SLCO1B1 variants. However, a tendency was observed for patients carrying ABCB1 rs1128503, rs1045642 T/T, or rs2032582 A/A genotypes to achieve a higher CR rate. Adverse drug reactions (ADRs) were frequent, with vascular disorders (39%) and infections (27%) being the most common. Genetic polymorphisms influenced ibrutinib toxicity, with CYP3A4 *1/*22 appearing to be protective against overall ADRs. Conclusions: The unexpected association between CYP3A4 *1/*22 genotype and lower ADR incidence, as well as the trend toward improved treatment response in patients carrying ABCB1 genotypes, suggests compensatory metabolic mechanisms. However, given the small sample size, larger studies are needed to confirm these findings and their clinical implications, while also aiming to uncover other non-genetic factors that may contribute to a better understanding of the variability in treatment response and toxicity. Full article

This paper reports the levels of radon (Rn), thoron (Tn), and their progeny (TnP) concentrations in dwellings; studies factors influencing these concentrations; and assesses the associated lung cancer risk in Akonolinga’s area in Cameroon, where rutile deposits have been identified but are not yet industrially exploited. Indoor Rn and Tn were determined using CR39-based detectors. Additionally, Rn in soil gas, ²²⁶Ra, and ²³²Th concentrations in soil were measured using Markus 10, high purity germanium detector (HPGe), respectively. On average, indoor Rn, Tn concentration, and the equilibrium equivalent Thoron concentration (EETC) or TnP were 39.5, 68.1, and 5.0 Bq m⁻³, respectively. Average concentrations of Rn in soil gas, ²²⁶Ra, and ²³²Th in soil were 24.3 kBq m⁻³, 17 Bq kg⁻¹, and 27 Bq kg⁻¹, respectively. Correlation analysis indicates that indoor radon and thoron levels were tightly linked with factors such as their precursor concentrations in soil, the building materials, dwelling architecture, and inhabitant living habits. Furthermore, it was observed that Rn and TnP were the major contributors to the inhalation effective dose, accounting for 39.6% and 56.7% of the total, respectively. The estimated excess lifetime cancer risk (ELCR) from the exposition to Rn and TnP was found to be 2.93 × 10⁻³ and 4.36 × 10⁻³, respectively, exceeding the global average, raising health concerns. Full article

We present the performance and application of a commercial off-the-shelf Si PIN diode (Hamamatsu S14605) as a charged particle detector in a compact ion beam system (IBS) capable of generating D–D and p–B fusion charged particles. This detector is inexpensive, widely available, and operates in photoconductive mode under a reverse bias voltage of 12 V, supplied by an A23 battery. A charge-sensitive preamplifier (CSP) is mounted on the backside of the detector’s four-layer PCB and powered by two ±3 V lithium batteries (A123). Both the detector and CSP are housed together on the vacuum side of the IBS, facing the fusion target. The system employs a CF-2.75-flanged DB-9 connector feedthrough to supply the signal, bias voltage, and rail voltages. To mitigate the high sensitivity of the detector to optical light, a thin aluminum foil assembly is used to block optical emissions from the ion beam and target. Charged particles generate step responses at the preamplifier output, with pulse rise times in the order of 0.2 to 0.3 µs. These signals are recorded using a custom-built data acquisition unit, which features an optical fiber data link to ensure the electrical isolation of the detector electronics. Subsequent digital signal processing is employed to optimally shape the pulses using a CR-RCⁿ filter to produce Gaussian-shaped signals, enabling the accurate extraction of energy information. Performance results indicate that the detector’s baseline RMS ripple noise can be as low as 0.24 mV. Under actual laboratory conditions, the estimated signal-to-noise ratios (S/N) for charged particles from D–D fusion—protons, tritons, and helions—are approximately 225, 75, and 41, respectively. Full article

The Pierre Auger Observatory, the world’s largest ultra-high-energy (UHE) cosmic ray (CR) detector, plays a crucial role in multi-messenger astroparticle physics with its high sensitivity to UHE photons and neutrinos. Recent Auger Observatory studies have set stringent limits on the diffuse and point-like fluxes of these particles, enhancing constraints on dark-matter models and UHECR sources. Although no temporal coincidences of neutrinos or photons with LIGO/Virgo gravitational wave events have been observed, competitive limits on the energy radiated in these particles have been established, particularly from the GW170817 binary neutron star merger. Additionally, correlations between the arrival directions of UHECRs and high-energy neutrinos have been explored using data from the IceCube Neutrino Observatory, ANTARES, and the Auger Observatory, providing additional neutrino flux constraints. Efforts to correlate UHE neutron fluxes with gamma-ray sources within our galaxy continue, although no significant excesses have been found. These collaborative and multi-faceted efforts underscore the pivotal role of the Auger Observatory in advancing multi-messenger astrophysics and probing the most extreme environments of the Universe. Full article

A leaf spring caliper is a device used to detect the geometry and defects of the inner wall of oil and gas pipelines. The detection principle involves installing strain gauges on the detecting arm, which can be bent elastically. The strain gauge signal is connected to the voltage-detecting equipment to detect the inner wall of the pipeline through the voltage signal. This equipment has the advantages of high detection accuracy and small structure size. However, the detection arm of the leaf spring caliper works via contact detection, and the detection arm will be worn out when working, thus reducing the detection accuracy. This paper establishes a wear model of the leaf spring caliper and constructs a wear test system based on the model. The wear test system simulates wear between the detection arm material 51CrV4 (ISO 683-2-2016) and the oil pipeline material L555Q (ISO 3183:2012). By changing the coating material of the detection arm, such as nickel-phosphorus coating, epoxy acrylic resin coating, or polytetrafluoroethylene (PTFE) coating, the wear pattern of the detection arm is explored and the experimental results are analyzed and summarized to select the most suitable coating material. A polynomial fit to the test data, followed by a Reye–Archard wear model fit, was performed to finally derive the wear function for leaf springs with different coating materials. A prediction algorithm was used to predict the wear pattern of the detector arm, and the extended wear length was calibrated. The results show that the average error between the predicted data and the actual observed data is in accordance with the experimental expectations. Therefore, the wear prediction model and its corresponding wear function can be applied to wear error correction to improve the detection accuracy of leaf spring calipers. Full article

The potentially toxic element pollution of agricultural soils has become a significant environmental threat to food safety and human health. Accurately identifying sources of potentially toxic element pollution is key to developing effective pollution prevention and control measures. In this study, regional potentially toxic element pollution of the soils in the Nanliujiang River Basin was analyzed using the positive matrix factorization (PMF) model and the geo-detector model. First, topsoil samples from the study area were collected to analyze eight potentially toxic elements in the soil, including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The PMF model was used to conduct source apportionment of the potentially toxic element data and identify the primary pollution sources and their contribution rates. Then, the geo-detector model was used to analyze the key factors affecting the spatial distribution of the potentially toxic elements and the influence of natural and human factors on the distribution of the potentially toxic elements. There are four potentially toxic element pollution sources of the agricultural soil in the study area: geological background, agricultural activities, industrial discharge, and river irrigation. The geological background contributed the most. The main factors affecting the spatial distribution of potentially toxic elements included agricultural activities, industrial discharge, and river irrigation. This integrated method can analyze the formation of potentially toxic element pollution in depth from the perspectives of source apportionment and spatial differentiation and provide a scientific basis and decision support for preventing and controlling potentially toxic element pollution in agricultural soils. This study provides a new method and scientific basis for identifying and preventing potentially toxic element pollution sources in agricultural soil and can guide the formulation of targeted soil pollution control measures. Full article

This article shows the results of research conducted on the corrosion resistance of the FeAl (Fe40Al5Cr0.2TiB) alloy in two variants: the alloy after casting and after homogenization annealing (1000 °C, 93 h). Analysis of the microstructure of these alloys was conducted on the light microscope, and the phase composition was determined by X-ray diffraction. Resistance to electrochemical corrosion was tested in a 5% NaCl solution using the potentiodynamic polarization technique and electrochemical impedance spectroscopy. The surface of alloys after corrosion tests was examined by scanning electron microscopy. Chemical composition tests were conducted using an energy-dispersive X-ray spectrometer. The structure analysis was made with an electron backscatter diffraction detector. Based on the studies, it was found that the corrosion resistance of the FeAl alloy after homogenization annealing was higher than that of the FeAl alloy after casting. This alloy showed a more non-homogeneous and coarse-grained microstructure compared to the alloy after homogenization annealing. The investigation of the surface condition of FeAl alloys after corrosion tests showed the presence of pits, particularly in the case of the alloy after casting. Full article

This article introduces the design and development of a space environment monitoring unit embedded in the versatile experimental assembly for electronic components outside the China space station’s Wentian laboratory cabin module. A newly designed comprehensive detection system is being used for the first time in this kind of detector. The sensor head of the instrument includes a silicon telescope (composed of two silicon semiconductors) for measuring the LET spectrum and radiation dose rate, a typical chip for monitoring a single-event upset, and a CR-39 plastic nuclear track detector for detecting heavy ion tracks. The two silicon sensors stacked up and down are used for measuring the LET spectrum, which ranges from 0.001 to 100 MeV·cm²/mg. A sensor charge allocation method is adopted to divide the detection range into four cascaded levels, each achieving different detection ranges separately and then concatenated together, while traditional detection methods need multiple sets of probes to achieve the same dynamic range. At the same time, using the two sensors mentioned above, the silicon absorption dose rate under two different shielding thicknesses can be obtained through calculation, ranging from 10⁻⁵ to 10⁻¹ rad (Si)/h. Multiple calibration methods are applied on the ground. The preliminary in-orbit detection results are provided and compared with the simulation results obtained using the existing space environment model, and we analyze and discuss their differences. Full article

This review aimed to explore advances in radon detection methods, emphasizing cost-effectiveness and accessible techniques such as CDs, DVDs, and glass-based detectors. In this review, we compared traditional methods like alpha track detectors and continuous radon monitors with emerging innovations that leverage polycarbonate material and IoT-integrated systems. Our evaluation of the synthesis suggests that CDs and DVDs provide scalable solutions for long-term radon monitoring, while glass-based detectors like CR-39 offer high sensitivity for epidemiological studies. The integration of IoT and AI technologies further enhances real-time radon monitoring, paving the way for precise, scalable, and affordable radon mitigation strategies. This work highlights the importance of low-cost, innovative approaches in reducing radon-related lung cancer risks and informs future research on optimizing the technologies for diverse environments. Full article

Radon (Rn 222) is a significant contributor to natural radiation exposure in residential environments such as single-family houses and multistory buildings. This study monitored radon activity concentration (RAC) in 455 apartments in 30 multistory buildings in Buzău, Romania. Integrated measurements of the RAC using CR-39 nuclear track detectors were conducted for a period of 3 to 4 months. The results revealed that the RAC varies between buildings, with an annual average between 33 and 77 Bq/m³. This variation may be attributed to poor ventilation and the chimney effect in common ventilation ducts, which may facilitate radon displacement vertically. Also, apartments with low occupancy or inadequate ventilation showed higher radon levels of up to 285 Bq/m³. The study highlights the potential risk of increased radon exposure in energy-efficient buildings due to poor ventilation, emphasizing the need for special attention to radon mitigation measures in building design. The results emphasize that the RAC is influenced by building characteristics, room use, and ventilation, with significant implications for health risks in urban residential environments. Full article

The oxidation behaviour of iron-based 316L stainless steel was investigated in the temperature range of 700 to 1000 °C. The test specimens in the shape of plates were produced by selective laser melting. After fabrication, the samples were sandblasted and then annealed in air for different periods of time (0.5, 2, 8, 32 h). Under the influence of temperature and time, stainless steels tend to form an oxide layer. Scanning electron microscopy, energy dispersive analysis, and X-ray diffraction were employed to analyse the composition of this layer. Notably, a thin oxide layer primarily composed of (Fe-Cr) formed on the surface due to temperature effects. In addition, with increasing temperature (up to 1000 °C), the oxide of the main alloying elements, specifically Mn₂(Fe-Cr)O₄, appeared alongside the Fe-Cr oxide. Furthermore, the samples were subjected to conversion X-ray (CXMS) and conversion electron (CEMS) Mössbauer spectroscopy. CXMS revealed a singlet with a decreasing Mössbauer effect based on the surface metal oxide thickness. CEMS revealed the presence of Fe³⁺ in the surface layer (0.3 µm). Moreover, an interesting phenomenon occurred at higher temperature levels due to the inhomogeneously thick surface metal oxide layer and the tangential direction of the Mössbauer radiation towards the electron detector. Full article

Indoor radon concentrations constitute a major source of exposure to ionizing radiation for humans. It has been estimated that radon contributes about 10% of deaths from lung cancer in the USA and Europe. In Italy, current legislation establishes that the concentration of radon must be monitored in all workplaces located in a basement and on the ground floor. In this study, the indoor radon concentration of 20 multi-floor buildings on the Cardarelli Hospital was measured during two consecutive semesters. The survey was carried out with CR-39 solid-state nuclear track detectors (SSNTDs). Radon concentrations were found to range from 4 Bq/m³ to 424 Bq/m³, with a median of 24 Bq/m³. The dependence of the radon concentrations on the measurement floor and the room-to-room spatial variation was also analyzed. Full article

This study investigates the radiological impact of ²²²Rn activity concentrations in bottled drinking water sourced from local markets in Baghdad, Iraq. Utilizing the solid-state nuclear track detector (SSNTD) technique with CR-39 detectors, ²²²Rn activity concentrations were measured in 25 bottled water samples. Concentrations ranged from 1.5 to 11.12 Bq/L, with an average value of 4.58 Bq/L. To assess the potential health risks, the annual effective dose (AED) due to ²²²Rn ingestion was calculated. The potential radiation doses ranged from $3.21\times {10}^{-6}$ Sv/y for infants to $1.17\times {10}^{-5}$ Sv/y for adults. These values are significantly lower than the established dose limit of $0.1\times {10}^{-3}$ Sv/y, thereby indicating a negligible radiological risk to consumers. The study also explored the correlation between total dissolved solids (TDS) and ²²²Rn concentrations, finding a direct relationship between higher TDS values and elevated ²²²Rn levels. The findings of this research contribute to the understanding of natural radionuclide levels in drinking water and their implications for public health. Full article

The current study aimed to quantify the value of color spaces and channels as a potential superior replacement for standard grayscale images, as well as the relative performance of open-source detectors and descriptors for general feature-based image registration purposes, based on a large benchmark dataset. The public dataset UDIS-D, with 1106 diverse image pairs, was selected. In total, 21 color spaces or channels including RGB, XYZ, Y′CrCb, HLS, L*a*b* and their corresponding channels in addition to grayscale, nine feature detectors including AKAZE, BRISK, CSE, FAST, HL, KAZE, ORB, SIFT, and TBMR, and 11 feature descriptors including AKAZE, BB, BRIEF, BRISK, DAISY, FREAK, KAZE, LATCH, ORB, SIFT, and VGG were evaluated according to reprojection error (RE), root mean square error (RMSE), structural similarity index measure (SSIM), registration failure rate, and feature number, based on 1,950,984 image registrations. No meaningful benefits from color space or channel were observed, although XYZ, RGB color space and L* color channel were able to outperform grayscale by a very minor margin. Per the dataset, the best-performing color space or channel, detector, and descriptor were XYZ/RGB, SIFT/FAST, and AKAZE. The most robust color space or channel, detector, and descriptor were L*a*b*, TBMR, and VGG. The color channel, detector, and descriptor with the most initial detector features and final homography features were Z/L*, FAST, and KAZE. In terms of the best overall unfailing combinations, XYZ/RGB+SIFT/FAST+VGG/SIFT seemed to provide the highest image registration quality, while Z+FAST+VGG provided the most image features. Full article

Isotopic composition measurements of singly charged cosmic rays (CR) provide essential insights into CR transport in the Galaxy. The Alpha Magnetic Spectrometer (AMS-02) can identify singly charged isotopes up to about 10 GeV/n. However, their identification presents challenges due to the small abundance of CR deuterons compared to the proton background. In particular, a high accuracy for the velocity measured by a ring-imaging Cherenkov detector (RICH) is needed to achieve a good isotopic mass separation over a wide range of energies. The velocity measurement with the RICH is particularly challenging for $Z=1$ isotopes due to the low number of photons produced in the Cherenkov rings. This faint signal is easily disrupted by noisy hits leading to a misreconstruction of the particles’ ring. Hence, an efficient background reduction process is needed to ensure the quality of the reconstructed Cherenkov rings and provide a correct measurement of the particles’ velocity. Machine learning methods, particularly boosted decision trees, are well suited for this task, but their performance relies on the choice of the features needed for their training phase. While physics-driven feature selection methods based on the knowledge of the detector are often used, machine learning algorithms for automated feature selection can provide a helpful alternative that optimises the classification method’s performance. We compare five algorithms for selecting the feature samples for RICH background reduction, achieving the best results with the Random Forest method. We also test its performance against the physics-driven selection method, obtaining better results. Full article