Influence of gamma irradiation on uranium determination by Arsenazo III in the presence of Fe(II)/Fe(III)

International audienceArsenazo III is a widely used reagent for the concentration measurement of uranium and other actinides in aqueous samples. This study indicates that, for routine aqueous samples, due to the strong complexing ability with Arsenazo III, Fe(III) can significantly decrease the UV-Vis absorbance of the U(VI)-Arsenazo III complex, whereas the influence of Fe(II) on the absorbance is negligible. However, when Fe(II) is present in a gamma-irradiated U(VI) aqueous sample, it can give rise to the Fenton reaction, which produces oxidizing radicals that decompose the subsequently added Arsenazo III, leading to a sharp decrease in the absorbance of the U(VI)-Arsenazo III complex. The decrease in absorbance depends on the iron content and irradiation dose. Furthermore, the oxidizing radicals from the Fenton reaction induced by gamma irradiation can be continually produced. Even if the irradiated solution has been aged for more than one month in the absence of light at room temperature and without the exclusion of oxygen, the reactivity of the radicals did not decrease toward the subsequently added Arsenazo III. This finding demonstrates that the presence of Fe(II) in gamma-irradiated U(VI) aqueous samples can lead to incorrect U(VI) measurement using the Arsenazo III method, and a new method needs to be developed for the quantitative determination of U(VI) in the presence of gamma radiation and ferrous iron

Study on thermal anomalies of earthquake process by using tidal-force and outgoing-longwave-radiation

Four earthquakes above magnitude 5.0 in Yunnan and Tibet, China occurred from 2010 to 2011. By calculating the tidal-force changes induced by celestial bodies in this region, we found that the earthquakes occurred when tidal-forces continuous¬ly grew from low to peak levels and approached the maximum amplitude phase, which indicated a tidal-force that had a trigger or inducing effect of active tectonic earthquakes when the ground stress reached a critical point. At the same time analyzing the abnormal changes of outgoing longwave radiation (OLR), along with the tidal cycle, indicated that the regional distribution of the enhancement region of OLR anomalies was closely related to geologic structure, especially ac¬tive faults. The OLR radiation anomaly evolved: an initial infrared rise, followed by an enhancement reaching peak, attenuation, and then a return to normal. The entire process was similar to changes observed in rock-breaking process under stress loads. Our investigation showed that the tidal-force changes caused by ce¬lestial bodies could trigger an earthquake when tectonic stress reached its critical breaking point, and the OLR anomaly was the radiation signature of the change in seismic tectonic stress. Therefore, the method of combining measurements of the tidal-force changes induced by celestial bodies with those of thermal-anomaly changes has some practical value for detecting the precursor state of impending earthquakes

Heavy standard model-like Higgs boson and a light stop from Yukawa-deflected gauge mediation

To obtain a SM-like Higgs boson around 125 GeV in the Minimal Supersymmetric Standard Model with minimal gauge mediation of supersymmetry breaking (GMSB), a heavy stop at multi-TeV level is needed and incurs severe fine-tuning, which can be ameliorated in the framework of the deformed GMSB with visible-hidden direct Yukawa interactions (YGMSB). We examine some general features of the YGMSB and focus on the scenario with Higgs-messenger couplings (H-YGMSB) which can automatically maintain the minimal flavor violation (MFV). It turns out that such a Yukawa mediation scenario can give a large -A_t and -m_{stop_L,R}^2, leading to a maximal stop mixing, and thus can readily give a light stop (stop_1) below the TeV scale. However, we find that in the minimal H-YGMSB scenario, m_{H_u}^2 is too large and then the electroweak symmetry breaking is inconsistent with the large stop mixing. To solve this problem, we modify the hidden sectors in two ways, adding a new strong gauge dynamics or introducing the (10,10_bar) messengers. For each case we present some numerical study.Comment: version in PRD (refs and discussions added

GenU-Net++: An Automatic Intracranial Brain Tumors Segmentation Algorithm on 3D Image Series with High Performance

Automatic segmentation of intracranial brain tumors in three-dimensional (3D) image series is critical in screening and diagnosing related diseases. However, there are various challenges in intracranial brain tumor images: (1) Multiple brain tumor categories hold particular pathological features. (2) It is a thorny issue to locate and discern brain tumors from other non-brain regions due to their complicated structure. (3) Traditional segmentation requires a noticeable difference in the brightness of the interest target relative to the background. (4) Brain tumor magnetic resonance images (MRI) have blurred boundaries, similar gray values, and low image contrast. (5) Image information details would be dropped while suppressing noise. Existing methods and algorithms do not perform satisfactorily in overcoming these obstacles mentioned above. Most of them share an inadequate accuracy in brain tumor segmentation. Considering that the image segmentation task is a symmetric process in which downsampling and upsampling are performed sequentially, this paper proposes a segmentation algorithm based on U-Net++, aiming to address the aforementioned problems. This paper uses the BraTS 2018 dataset, which contains MR images of 245 patients. We suggest the generative mask sub-network, which can generate feature maps. This paper also uses the BiCubic interpolation method for upsampling to obtain segmentation results different from U-Net++. Subsequently, pixel-weighted fusion is adopted to fuse the two segmentation results, thereby, improving the robustness and segmentation performance of the model. At the same time, we propose an auto pruning mechanism in terms of the architectural features of U-Net++ itself. This mechanism deactivates the sub-network by zeroing the input. It also automatically prunes GenU-Net++ during the inference process, increasing the inference speed and improving the network performance by preventing overfitting. Our algorithm’s PA, MIoU, P, and R are tested on the validation dataset, reaching 0.9737, 0.9745, 0.9646, and 0.9527, respectively. The experimental results demonstrate that the proposed model outperformed the contrast models. Additionally, we encapsulate the model and develop a corresponding application based on the MacOS platform to make the model further applicable

Comparison of SWAT and GWLF Model Simulation Performance in Humid South and Semi-Arid North of China

Watershed models have gradually been adapted to support both decision and policy making for global environmental pollution control. In this study, two watershed models with different complexity, the Soil and Water Assessment Tool (SWAT) and the Generalized Watershed Loading Function (GWLF), were applied in two catchments in data scarce China, namely the Tunxi and the Hanjiaying basins with contrasting climatic conditions (humid and semi-arid, respectively). The performances of both models were assessed via comparison between simulated and measured monthly streamflow, sediment yield, and total nitrogen. Time series plots as well as four statistical measures (the coefficient of determination (R2), the Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE (root mean square error)—observations standard deviation ratio (RSR)) were used to estimate the performance of both models. The results show that both models were generally able to simulate monthly streamflow, sediment, and total nitrogen loadings during the simulation period. However, SWAT performed better for detailed representations, while GWLF could produce much better average values of the observed data. Thus, GWLF offers a user-friendly prospective alternative watershed model that requires little input data and that is applicable for areas where the input data required for SWAT are not always available. SWAT is more suitable for projects that require high accuracy and offers an advantage when measured data are scarce