Controlled Size Characterization Process for In-Situ TiB2 Particles from Al Matrix Composites Using Nanoparticle Size Analysis.

The wide size range and high tendency to agglomerate of in-situ TiB2 particles in reinforced Al matrix composites introduce great difficulties in their size characterization. In order to use a nanoparticle size analyzer (NSA) to obtain the precise size distribution of TiB2 particles, a controlled size characterization process has been explored. First, the extraction and drying processes for TiB2 particles were optimized. In the extraction process, alternated applications of magnetic stirring and normal ultrasound treatments were proven to accelerate the dissolution of the Al matrix in HCl solution. Furthermore, freeze-drying was found to minimize the agglomeration tendency among TiB2 particles, facilitating the acquisition of pure powders. Such powders were quantitatively made into an initial TiB2 suspension. Second, the chemical and physical dispersion technologies involved in initial TiB2 suspension were put into focus. Chemically, adding PEI (M.W. 10000) at a ratio of mPEI/mTiB2 = 1/30 into the initial suspension can greatly improve the degree of TiB2 dispersion. Physically, the optimum duration for high-energy ultrasound application to achieve TiB2 dispersion was 10 min. Overall, the corresponding underlying dispersion mechanisms were discussed in detail. With the combination of these chemical and physical dispersion specifications for TiB2 suspension, the bimodal size distribution of TiB2 was able to be characterized by NSA for the first time, and its number-average diameter was 111 ± 6 nm, which was reduced by 59.8% over the initial suspension. Indeed, the small-sized and large-sized peaks of the TiB2 particles characterized by NSA mostly match the results obtained from transmission electron microscopy and scanning electron microscopy, respectively.

Optimizing the Heat Treatment Method to Improve the Aging Response of Al-Fe-Ni-Sc-Zr Alloys.

This work has studied the co-addition of Sc and Zr elements into the Al-1.75wt%Fe-1.25wt%Ni eutectic alloy. The changes in the microstructure, electrical conductivity, and Vickers hardness of the Al-1.75wt%Fe-1.25wt%Ni-0.2wt%Sc-0.2wt%Zr alloy during heat treatment were studied. The results showed that two-step aging can effectively improve the aging response of the alloy over the single-step aging method. This was ascribed to the minimization of the diffusion difference between Sc and Zr elements. Furthermore, the homogenization treatment can also improve the aging response of the alloy by alleviating the uneven distribution of Sc and Zr. Nevertheless, the micro-alloyed elements exceeded the solid solubility limit in the Al-1.75wt%Fe-1.25wt%Ni-0.2wt%Sc-0.2wt%Zr alloy, and their strengthening effect has ever achieved the best prospect. Finally, both Sc and Zr contents were reduced simultaneously, and the aging response of the Al-1.75wt%Fe-1.25wt%Ni-0.15wt%Sc-0.1wt%Zr alloy was improved by optimized heat treatment. The underlying mechanisms for this alloy design and the corresponding microstructure-mechanical property relationship were analytically discussed.

Variable selection for individualised treatment rules with discrete outcomes.

An individualised treatment rule (ITR) is a decision rule that aims to improve individuals' health outcomes by recommending treatments according to subject-specific information. In observational studies, collected data may contain many variables that are irrelevant to treatment decisions. Including all variables in an ITR could yield low efficiency and a complicated treatment rule that is difficult to implement. Thus, selecting variables to improve the treatment rule is crucial. We propose a doubly robust variable selection method for ITRs, and show that it compares favourably with competing approaches. We illustrate the proposed method on data from an adaptive, web-based stress management tool.

Thyroid collision tumour with pulmonary metastases treated effectively with nedaplatin and paclitaxel chemotherapy: A case report.

Collision tumour of the thyroid is a rare entity for which surgical resection is the primary treatment. We present here a case of a collision thyroid tumour of oncocytic and papillary carcinoma with lung metastases occurring in a 62-year-old woman who initially presented with a rapidly enlarging cervical mass and dyspnoea. The patient had extensive venous tumour thrombosis in the internal jugular and subclavian veins. The patient received six cycles of combined chemotherapy with nedaplatin and paclitaxel which significantly reduced the size of the metastases in the lungs. Following discharge from the hospital, the patient was treated with oral anlotinib and at 14 months follow up she had not experienced any serious side effects and the metastases in her lung and thyroid surgery areas were well controlled.

Variable selection in high dimensions for discrete-outcome individualized treatment rules: Reducing severity of depression symptoms.

Despite growing interest in estimating individualized treatment rules, little attention has been given the binary outcome setting. Estimation is challenging with nonlinear link functions, especially when variable selection is needed. We use a new computational approach to solve a recently proposed doubly robust regularized estimating equation to accomplish this difficult task in a case study of depression treatment. We demonstrate an application of this new approach in combination with a weighted and penalized estimating equation to this challenging binary outcome setting. We demonstrate the double robustness of the method and its effectiveness for variable selection. The work is motivated by and applied to an analysis of treatment for unipolar depression using a population of patients treated at Kaiser Permanente Washington.

Recent Progress in Gd-Containing Materials for Neutron Shielding Applications: A Review.

With the rising demand for nuclear energy, the storage/transportation of radioactive nuclear by-products are critical safety issues for humans and the environment. These by-products are closely related to various nuclear radiations. In particular, neutron radiation requires specific protection by neutron shielding materials due to its high penetrating ability to cause irradiation damage. Herein, a basic overview of neutron shielding is presented. Since gadolinium (Gd) has the largest thermal neutron capture cross-section among various neutron absorbing elements, it is an ideal neutron absorber for shielding applications. In the last two decades, there have been many newly developed Gd-containing (i.e., inorganic nonmetallic-based, polymer-based, and metallic-based) shielding materials developed to attenuate and absorb the incident neutrons. On this basis, we present a comprehensive review of the design, processing methods, microstructure characteristics, mechanical properties, and neutron shielding performance of these materials in each category. Furthermore, current challenges for the development and application of shielding materials are discussed. Finally, the potential research directions are highlighted in this rapidly developing field.

Variable selection in regression-based estimation of dynamic treatment regimes.

Dynamic treatment regimes (DTRs) consist of a sequence of decision rules, one per stage of intervention, that aim to recommend effective treatments for individual patients according to patient information history. DTRs can be estimated from models which include interactions between treatment and a (typically small) number of covariates which are often chosen a priori. However, with increasingly large and complex data being collected, it can be difficult to know which prognostic factors might be relevant in the treatment rule. Therefore, a more data-driven approach to select these covariates might improve the estimated decision rules and simplify models to make them easier to interpret. We propose a variable selection method for DTR estimation using penalized dynamic weighted least squares. Our method has the strong heredity property, that is, an interaction term can be included in the model only if the corresponding main terms have also been selected. We show our method has both the double robustness property and the oracle property theoretically; and the newly proposed method compares favorably with other variable selection approaches in numerical studies. We further illustrate the proposed method on data from the Sequenced Treatment Alternatives to Relieve Depression study.

Diffusion kurtosis imaging-derived histogram metrics for prediction of resistance to neoadjuvant chemoradiotherapy in rectal adenocarcinoma: Preliminary findings.

PURPOSE: This study aimed to evaluate the potential role of diffusion kurtosis imaging (DKI)-derived parameters for assessing resistance to CRT in patients with Locally advanced rectal cancer (LARC) by using histogram analysis derived from whole-tumor volumes. METHOD: 136 consecutive patients with histologically confirmed rectal adenocarcinoma who underwent MRI examination before and after chemoradiotherapy were enrolled in our retrospective study. The parameters D, K, and conventional apparent diffusion coefficient (ADC) were measured using whole-tumor volume histogram analysis. The AJCC tumor regression grading (TRG) system was the standard reference (resistance: TRG 3; non-resistance: TRG 0-2). Receiver operating characteristic (ROC) curves were used for evaluating the diagnostic performance. RESULTS: Aside from the skew and kurtosis values, we found all the histogram metrics of D and ADC values significantly increased after CRT (all p < 0.001). In contrast, the histogram metrics of K values significantly decreased after CRT. The majority of percentiles metrics of D, K, and ADC values were correlated with tumor resistance before and after CRT (P < 0.05), except for the skew and kurtosis values. Regarding the comparison of the diagnostic performance of all the histogram metrics, the percentage Dmean change (ΔDmean) showed the highest AUC value of 0.939, and the corresponding sensitivity, specificity, PPV, and NPV were 84.1% and 94.6%, 88.1% and 92.6%, respectively. CONCLUSIONS: These preliminary results demonstrated that DKI-derived histogram metrics, especially the pre-treatment metrics and ΔDmean, were useful to assess tumoral resistance to CRT and individual clinical management for patients with LARC.

Morphological Evolutions of Ni-Rich Phases in Al-Si Piston Alloys during 250-400 °C Thermal Exposure Processes.

The thermal stability of the Al-Si alloys during the thermal exposure process from 250 °C to 400 °C was systematically investigated. The relationships between the morphological evolution and the mechanical changes of the alloys were determined through the Vickers hardness test and materials characterization method. Initially, the alloys exhibited similar thermal degradation behavior. For example, the exposure process of the alloy at 300 °C can be divided into two stages according to the changes of the alloy hardness and the matrix micro-hardness. In detail, the first stage (0-2 h) exhibited a severe reduction of the alloy hardness while the second stage showed a more leveled hardness during the following 98 h. There are three identified morphological characteristics of Ni-rich phases in the alloy. Furthermore, the differences in both composition and the micro-hardness between these Ni-rich phases were confirmed. The underlying relationships between the morphological transformation of the Ni-rich phases and hardness fluctuation in the alloy were correlated and elucidated. The observed alloy hardness increase when the exposure temperature was 400 °C was unexpected. This behavior was explained from the perspectives of both Ni-rich phases evolution and dispersoid formation.

Micro/nano hierarchical structured titanium treated by NH4OH/H2O2 for enhancing cell response.

In this paper, two kinds of titanium surfaces with novel micro/nano hierarchical structures, namely Etched (E) surface and Sandblast and etched (SE) surface, were successfully fabricated by NH4OH and H2O2 mixture. And their cellular responses of MG63 were investigated compared with Sandblast and acid-etching (SLA) surface. Scanning electron microscope (SEM), Surface profiler, X-ray photoelectron spectroscopy (XPS), and Contact angle instrument were employed to assess the surface morphologies, roughness, chemistry and wettability respectively. Hierarchical structures with micro holes of 10-30 µm in diameter and nano pits of tens of nanometers in diameter formed on both E and SE surfaces. The size of micro holes is very close to osteoblast cell, which makes them wonderful beds for osteoblast. Moreover, these two kinds of surfaces possess similar roughness and superior hydrophilicity to SLA. Reactive oxygen species were detected on E and SE surface, and thus considerable antimicrobial performance and well fixation can be speculated on them. The cell experiments also demonstrated a boost in cell attachment, and that proliferation and osteogenic differentiation were achieved on them, especially on SE surface. The results indicate that the treatment of pure titanium with H2O2/NH4OH is an effective technique to improve the initial stability of implants and enhance the osseointegration, which may be a promising surface treatment to titanium implant.