The geological origins and soil properties of loess-like silty clay: a case study in the jinan area.

This study, using Jinan as a case study, systematically investigates the characteristics and geological genesis of loess-like silty clay in the middle and lower reaches of the Yellow River. The primary distribution of loess-like silty clay is revealed through field surveys, laboratory experiments, and previous literature reviews. The chemical and physical properties of the loess-like silty clay were examined, in addition to investigations into its mineral composition, microstructural characteristics, and engineering mechanical properties, in order to enhance comprehension of its attributes and formation mechanisms. The research suggests that the distinctive soil environment in the area has been influenced by numerous instances of the Yellow River overflow and channel shifts over its history, as well as the impacts of climate change, geological factors, and human activities. The primary sources of material for the loess-like silty clay consist of loess, Hipparion Red Clay, and paleosol layers. The discussion also addresses the impact of regional climate on the formation of mineral components. The aforementioned findings hold significant implications for advancing the understanding of historical climatic and paleogeographic shifts, as well as for addressing engineering challenges associated with the distribution of loess-like silty clay.

Dual Stabilization of a Tri-Metallofullerene Radical Er3@C80: Exohedral Derivatization and Endohedral Three-Center Bonding.

The enclosed space within fullerene molecules, capable of trapping metal clusters, offers an opportunity to investigate the behavior of metal atoms in a highly confined sub-nanometer environment. However, the studies on trimetallofullerenes M3@C80 have been very limited due to their difficult obtainability. In this paper, we present a new method for obtaining a tri-metallofullerene Er3@C80 through exohedral modification of the fullerene cage. Our findings reveal that Er3@C80 exhibits a radical character and can react with the dichlorobenzene radical to generate a stable derivative Er3@C80PhCl2. Theoretical calculations demonstrate the presence of a three-center two-electron metal-metal bond in the center of the fullerene cage. This bond serves to counterbalance the Coulomb repulsion between the Er ions. Consequently, both exohedral derivatization and endohedral three-center bonding contribute to the substantial stability of Er3@C80PhCl2. Furthermore, molecular dynamics simulations indicate that the Er3 cluster within the molecule possesses a rigid triangle structure. The availability of M3@C80 derivatives opens avenues for future investigations into interactions among metal atoms, such as magnetic coupling, within fullerene cages.

Te-doped-WSe2/W as a stable monolith catalyst for ampere-level current density hydrogen evolution reaction.

The development of efficient electrocatalysts for the hydrogen evolution reaction (HER) holds immense importance in the context of large-scale hydrogen production from water. Nevertheless, the practical application of such catalysts still relies on precious platinum-based materials. There is a pressing need to design high-performing, non-precious metal electrocatalysts capable of generating hydrogen at substantial current levels. We report here a stable monolith catalyst of Te-doped-WSe2 directly supported by a highly conductive W mesh. This catalyst demonstrates outstanding electrocatalytic performance and stability in acidic electrolytes, especially under high current conditions, surpassing the capabilities of commercial 5% Pt/C catalysts. Specifically, at current densities of 10 and 1200 mA cm-2, it exhibits a minimal overpotential of 79 and 232 mV, along with a small Tafel slope of 55 mV dec-1, respectively. The remarkable catalytic activity of Te-WSe2 can be attributed to the exceptional electron transfer facilitated by the stable monolithic structure, as well as the abundant and efficient active sites in the material. In addition, density functional theory calculations further indicate that Te doping adjusts H atom adsorption on various positions of WSe2, making it closer to thermal neutrality compared to the original material. This study presents an innovative approach to develop cost-effective HER electrocatalysts that perform optimally under high current density conditions.

Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China.

In complex mountainous areas where earthquakes are frequent, landslide hazards pose a significant threat to human life and property due to their high degree of concealment, complex development mechanism, and abrupt nature. In view of the problems of the existing landslide hazard susceptibility evaluation model, such as poor effectiveness and inaccuracy of landslide hazard data and the need for experts to participate in the calculation of a large number of evaluation factor weight classification statistics. In this paper, a combined SBAS-InSAR (Small Baseline Subsets-Interferometric Synthetic Aperture Radar) and PSO-RF (Particle Swarm Optimization-Random Forest) algorithm was proposed to evaluate the susceptibility of landslide hazards in complex mountainous regions characterized by frequent earthquakes, deep river valleys, and large terrain height differences. First, the SBAS-InSAR technique was used to invert the surface deformation rates of the study area and identified potential landslide hazards. Second, the study area was divided into 412,585 grid cells, and the 16 selected environmental factors were analyzed comprehensively to identify the most effective evaluation factors. Last, 2722 landslide (1361 grid cells) and non-landslide (1361 grid cells) grid cells in the study area were randomly divided into a training dataset (70%) and a test dataset (30%). By analyzing real landslide and non-landslide data, the performances of the PSO-RF algorithm and three other machine learning algorithms, BP (back propagation), SVM (support vector machines), and RF (random forest) algorithms were compared. The results showed that 329 potential landslide hazards were updated using the surface deformation rates and existing landslide cataloguing data. Furthermore, the area under the curve (AUC) value and the accuracy (ACC) of the PSO-RF algorithm were 0.9567 and 0.8874, which were higher than those of the BP (0.8823 and 0.8274), SVM (0.8910 and 0.8311), and RF (0.9293 and 0.8531), respectively. In conclusion, the method put forth in this paper can be effectively updated landslide data sources and implemented a susceptibility prediction assessment of landslide disasters in intricate mountainous areas. The findings can serve as a strong reference for the prevention of landslide hazards and decision-making mitigation by government departments.

Clinical features and short-term outcomes of elderly patients with COVID-19.

BACKGROUND: The outbreak of Coronavirus Disease 2019 (COVID-19) has become a global public health emergency. METHODS: 204 elderly patients (≥60 years old) diagnosed with COVID-19 in Renmin Hospital of Wuhan University from January 31st to February 20th, 2020 were included in this study. Clinical endpoint was in-hospital death. RESULTS: Of the 204 patients, hypertension, diabetes, cardiovascular disease, and chronic obstructive pulmonary disease (COPD) were the most common coexisting conditions. 76 patients died in the hospital. Multivariate analysis showed that dyspnea (hazards ratio (HR) 2.2, 95% confidence interval (CI) 1.414-3.517; p < 0.001), older age (HR 1.1, 95% CI 1.070-1.123; p < 0.001), neutrophilia (HR 4.4, 95% CI 1.310-15.061; p = 0.017) and elevated ultrasensitive cardiac troponin I (HR 3.9, 95% CI 1.471-10.433; p = 0.006) were independently associated with death. CONCLUSION: Although so far the overall mortality of COVID-19 is relatively low, the mortality of elderly patients is much higher. Early diagnosis and supportive care are of great importance for the elderly patients of COVID-19.

Technical Note: U-net-generated synthetic CT images for magnetic resonance imaging-only prostate intensity-modulated radiation therapy treatment planning.

PURPOSE: Clinical implementation of magnetic resonance imaging (MRI)-only radiotherapy requires a method to derive synthetic CT image (S-CT) for dose calculation. This study investigated the feasibility of building a deep convolutional neural network for MRI-based S-CT generation and evaluated the dosimetric accuracy on prostate IMRT planning. METHODS: A paired CT and T2-weighted MR images were acquired from each of 51 prostate cancer patients. Fifteen pairs were randomly chosen as tested set and the remaining 36 pairs as training set. The training subjects were augmented by applying artificial deformations and feed to a two-dimensional U-net which contains 23 convolutional layers and 25.29 million trainable parameters. The U-net represents a nonlinear function with input an MR slice and output the corresponding S-CT slice. The mean absolute error (MAE) of Hounsfield unit (HU) between the true CT and S-CT images was used to evaluate the HU estimation accuracy. IMRT plans with dose 79.2 Gy prescribed to the PTV were applied using the true CT images. The true CT images then were replaced by the S-CT images and the dose matrices were recalculated on the same plan and compared to the one obtained from the true CT using gamma index analysis and absolute point dose discrepancy. RESULTS: The U-net was trained from scratch in 58.67 h using a GP100-GPU. The computation time for generating a new S-CT volume image was 3.84-7.65 s. Within body, the (mean ± SD) of MAE was (29.96 ± 4.87) HU. The 1%/1 mm and 2%/2 mm gamma pass rates were over 98.03% and 99.36% respectively. The DVH parameters discrepancy was less than 0.87% and the maximum point dose discrepancy within PTV was less than 1.01% respect to the prescription. CONCLUSION: The U-net can generate S-CT images from conventional MR image within seconds with high dosimetric accuracy for prostate IMRT plan.

Dosimetric Evaluation of Incorporating Patient Geometric Variations Into Adaptive Plan Optimization Through Probabilistic Treatment Planning in Head and Neck Cancers.

PURPOSE: Four-dimensional (4D) adaptive radiation therapy (ART) treatment planning is an alternative to the conventional margin-based treatment planning approach. In 4D ART, interfraction patient geometric variations, gathered from computed tomography (CT) or cone beam CT (CBCT) images acquired during the patient treatment course, are directly incorporated into the adaptive plan optimization using a probabilistic treatment planning method. The goal of the present planning study was to evaluate the dosimetric differences between 4D ART and conventional margin-based adaptive planning strategies for head and neck cancers. In addition, we examined whether the dose differences achieved with 4D ART would translate into clinically relevant toxicity reductions using the existing normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: For 18 head and neck cancer patients, the treatment plans were retrospectively generated for 4 different treatment strategies, including a solely image guided radiation therapy (IGRT) strategy (IGRT-only), 2 conventional adaptive treatment planning strategies using 3- and 0-mm planning target volume (PTV) margins, and the 4D ART strategy. In the IGRT-only strategy, a conventional 3-mm PTV margin treatment plan was applied for the entire treatment course. In the 2 conventional adaptive strategies, 2 new treatment plans were generated during the treatment course using diagnostic planning CT scans acquired after the 10th and 22nd fractions. The 4D ART followed the same adaptive schedule, except that the 4D adaptive plan was generated using 5 CBCT images acquired during the 5 most recent treatment fractions. For each strategy, the actual delivered dose for the entire treatment course was constructed by calculating the daily doses on 35 CBCT scans, deforming back to the pretreatment planning CT scan, and accumulating over all 35 fractions. The target coverage was evaluated using the percentage of target volume receiving ≥100% of the prescription dose (V100%) and the minimum dose to 99% of the target volume (D99). It was considered adequate if the V100% was ≥95% and the dose deficit in D99 was ≤2 Gy (with respect to the prescription dose). For each strategy, the dose received by the organs at risk (OARs) was also evaluated, and the corresponding NTCP values were subsequently calculated using 3 NTCP models. RESULTS: Adequate target coverage was achieved for the primary clinical target volume (CTV1) and elective nodal CTV (CTV2) with a 3-mm PTV margin, regardless of adaptation. The 3-mm ART plan reduced the OAR mean dose by 1 to 2 Gy compared with the IGRT-only plan. The 0-mm ART plan further reduced the OAR dose by another 2 to 3 Gy at the expense of target coverage: 3 and 1 patient had V100% <95%, and 6 and 5 patients had a >2 Gy dose deficit in D99 for the CTV1 and CTV2, respectively. Use of 4D ART improved target coverage and attained OAR sparing similar to that with 0-mm ART. The number of patients with V100% <95% and >2 Gy D99 deficit decreased to 0 and 0 for CTV1 and 0 and 2 for CTV2, respectively. The NTCP calculations suggested that 4D ART could benefit a substantial portion of patients compared with IGRT-only because 17 and 12 patients had ≥5% and ≥10% NTCP reductions for parotid toxicity and 18 and 3 patients had ≥5% and ≥10% NTCP reductions for swallowing toxicity, respectively. CONCLUSIONS: Compared with margin-based adaptive planning strategies, 4D ART provides a better balance between target coverage and OAR sparing. NTCP estimation predicted for theoretical clinical benefits that warrant further clinical validation.

A feasibility study of intrafractional tumor motion estimation based on 4D-CBCT using diaphragm as surrogate.

PURPOSE: To investigate the intrafractional stability of the motion relationship between the diaphragm and tumor, as well as the feasibility of using diaphragm motion to estimate lung tumor motion. METHODS: Eighty-five paired (pre and posttreatment) daily 4D-CBCT images were obtained from 20 lung cancer patients who underwent SBRT. Bony registration was performed between the pre- and post-CBCT images to exclude patient body movement. The end-exhalation phase image of the pre-CBCT image was selected as the reference image. Tumor positions were obtained for each phase image using contour-based translational alignments. Diaphragm positions were obtained by translational alignment of its apex position. A linear intrafraction model was constructed using regression analysis performed between the diaphragm and tumor positions manifested on the pretreatment 4D-CBCT images. By applying this model to posttreatment 4D-CBCT images, the tumor positions were estimated from posttreatment 4D-CBCT diaphragm positions and compared with measured values. A receiver operating characteristic (ROC) test was performed to determine a suitable indicator for predicting the estimate accuracy of the linear model. RESULTS: Using the linear model, per-phase position, mean position, and excursion estimation errors were 1.12 ± 0.99 mm, 0.97 ± 0.88 mm, and 0.79 ± 0.67 mm, respectively. Intrafractional per-phase tumor position estimation error, mean position error, and excursion error were within 3 mm 95%, 96%, and 99% of the time, respectively. The residual sum of squares (RSS) determined from pretreatment images achieved the largest prediction power for the tumor position estimation error (discrepancy < 3 mm) with an Area Under ROC Curve (AUC) of 0.92 (P < 0.05). CONCLUSION: Utilizing the relationship between diaphragm and tumor positions on the pretreatment 4D-CBCT image, intrafractional tumor positions were estimated from intrafractional diaphragm positions. The estimation accuracy can be predicted using the RSS obtained from the pretreatment 4D-CBCT image.

Value of multi-b value DWI in the assessment of early cerebral changes in asymptomatic HIV-positive adolescents.

Background Magnetic resonance imaging (MRI) and functional MRI techniques have been widely used in the diagnosis of human immunodeficiency virus (HIV) infection related diseases. Purpose To explore whether magnetic resonance diffusion-weighted imaging (DWI) can track water molecular diffusion changes in the brain of asymptomatic HIV-positive adolescents. Material and Methods Multi-b value DWI was performed in 23 adolescents, including 15 HIV-positive participants and eight HIV-negative healthy participants. Mean apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (ADCs) values, fast apparent diffusion coefficient (ADCf) values, distribution diffusion coefficient (DDC) values, and heterogeneity index (α) values were calculated within regions of interest (ROIs) in the frontal lobes, basal ganglia, and temporal lobe. Non-parametric tests were then performed. Results In the bilateral frontal lobes, the mean α values in HIV-positive participants were significantly increased compared with those in healthy participants (right side P = 0.001; left side P = 0.000). In the left frontal lobe, the mean DDC value in HIV-positive participants was significantly increased compared with that in healthy participants ( P = 0.008). In the bilateral frontal lobes, the mean ADCf values in HIV-positive participants were significantly lower than those in healthy participants (right side P = 0.011; left side P = 0.008). In the left basal ganglia, the mean α values in HIV-positive participants were significantly lower than that in healthy participants ( P = 0.013). Conclusion Multi-b value DWI could reflect the early characteristics of water molecule diffusion in HIV infections.

Application of brain multi-b-value diffusion-weighted imaging (DWI) in adolescent orphans from AIDS families.

OBJECTIVE: To evaluate the application value of multi-b-value diffusion-weighted imaging (DWI) with mono-exponential model and stretched-exponential model in the diagnosis of HIV-positive patients. METHODS: Multi-b-value (0, 50, 150, 200, 400, 600, 800 s mm(-2)) DWI was performed in 23 adolescent orphans from AIDS families, including 15 HIV-positive subjects and 8 HIV-negative healthy subjects. Apparent diffusion coefficient (ADC) values were fitted by mono-exponential model; distribution diffusion coefficient (DDC) values and heterogeneity index (α) values were fitted by stretched-exponential model in bilateral basal ganglia, then non-parametric tests were performed. RESULTS: The signal intensity attenuation in multi-b-value DWI could be well described by both mono-exponential model and stretched-exponential model. In the left basal ganglia, mean α-values in HIV-positive subjects (α = 0.848 ± 0.068) were significantly lower than that in healthy subjects (α = 0.923 ± 0.050, p = 0.013). There was no statistical difference of α-values between HIV-positive subjects and healthy control subjects in the right basal ganglia. Apart from these, there were also no statistical differences of DDC values or ADC values between two groups in bilateral basal ganglia (all p > 0.05). In bilateral basal ganglia, DDC values were positively correlated with ADC values in HIV-positive patients (right basal ganglia: r = 0.832, p = 0.000; left basal ganglia: r = 0.770, p = 0.001) as well as in healthy cases (right basal ganglia: r = 0.927, p = 0.001; left basal ganglia: r = 0.878, p = 0.004). Receiver operating characteristic (ROC) curve analysis yielded area under the ROC curve (Az) values of 0.817 (p = 0.014 < 0.05) in the left basal ganglia. The sensitivity and specificity were 62.5% and 86.7%, respectively. CONCLUSION: Through the study of asymptomatic HIV-positive subjects when b < 1000 s mm(-2), we can see stretched-exponential model DWI can provide more information than mono-exponential model DWI. ADVANCES IN KNOWLEDGE: Multi-b-value DWI was performed in subjects with HIV. DWI measurements could be neuroimaging biomarkers of cerebral injury in the course of HIV infection.