Comparing particle size distributions of an arbitrary shape

Prediction Model of Dry Fertilizer Crushing Force Based on P-DE-SVM

The accurate prediction of fertilizer crushing force could reduce the crushing rate in the process of transportation and utilization and ensure the efficient utilization of the fertilizer so as to realize the sustainable and clean production of crops. To achieve this goal, a fertilizer crushing force prediction model based on the shape characteristics was proposed in this paper using the Pearson correlation coefficient, differential evolution algorithm, and the support vector machine (P-DE-SVM). First, the shape characteristics and crushing force of fertilizers were measured by an independently developed agricultural material shape analyzer and digital pressure gauge, and the shape characteristics related to the fertilizer crushing force were proposed based on the Pearson correlation coefficient. Second, a fertilizer crushing force prediction model based on a support vector machine was constructed, in which the optimal kernel function was the radial basis function. Finally, a differential evolution algorithm was proposed to optimize the internal parameters of the fertilizer-crushing force prediction model, and at the same time, a fertilizer granularity inspection range was calculated. The experimental results showed that the maximum error rate of the fertilizer crushing force prediction model was between -10.4 and 10.9%, and the fertilizer granularity inspection range was reasonable. The proposed prediction model in this paper could lay a solid foundation for fertilizer production and quality inspection, which would help reduce fertilizer crushing and improve fertilizer utilization to realize the sustainable and clean production of crops.

Effect of LTLT heat treatment on cathepsin B and L activities and denaturation of myofibrillar proteins of pork

The aim was to study biophysical and chemical changes during low-temperature long-time (LTLT) heat treatment of pork by measuring cathepsin B+L activity, surface hydrophobicity of myofibrils, particle size of myofibrils and effect on meat toughness as indicated by Allo-Kramer shear force. Longissimus thoracis et lumborum muscles were divided into large pieces, vacuum packaged and cooked in water baths at 53, 58, 63, 68 and 73 °C for 1, 8 and 24 h. The results showed that the meat toughness was markedly lower at temperatures of 53 °C and 58 °C and decreased with increasing holding time. Myofibrillar surface hydrophobicity increased with temperature, but not with time, indicating aggregation and/or gelation phenomena took place. Treatments with the lowest shear force values generally had smaller particles and were associated with high cathepsin B+L activity. A mechanism by which these cathepsins might affect the aggregation dynamics and change the mechanical properties of meat is proposed.

Information Entropy as a Reliable Measure of Nanoparticle Dispersity

Nanoparticle size impacts properties vital to applications ranging from drug delivery to diagnostics and catalysis. As such, evaluating nanoparticle size dispersity is of fundamental importance. Conventional approaches, such as standard deviation, usually require the nanoparticle population to follow a known distribution and are ill-equipped to deal with highly poly- or heterodisperse populations. Herein, we propose the use of information entropy as an alternative and assumption-free method for describing nanoparticle size distributions. This measure works equally well for mono-, poly-, and heterodisperse populations and represents an unbiased route to evaluation and optimization of nanoparticle synthesis. We provide intuitive software tools for analysis and supply guidelines for interpretation with respect to known standards.

CTC phenotyping for a preoperative assessment of tumor metastasis and overall survival of pancreatic ductal adenocarcinoma patients

BACKGROUND

The evaluation for surgical resectability of pancreatic ductal adenocarcinoma (PDAC) patients is not only imaging-based but highly subjective. An objective method is urgently needed. We report on the clinical value of a phenotypic circulating tumor cell (CTC)-based blood test for a preoperative prognostic assessment of tumor metastasis and overall survival (OS) of PDAC patients.

METHODS

Venous blood samples from 46 pathologically confirmed PDAC patients were collected prospectively before surgery and immunoassayed using a specially designed TU-chip™. Captured CTCs were differentiated into epithelial (E), mesenchymal and hybrid (H) phenotypes. A further 45 non-neoplastic healthy donors provided blood for cell line validation study and CTC false positive quantification.

FINDINGS

A validated multivariable model consisting of disjunctively combined CTC phenotypes: "H-CTC≥15.0 CTCs/2ml OR E-CTC≥11.0 CTCs/2ml" generated an optimal prediction of metastasis with a sensitivity of 1.000 (95% CI 0.889-1.000) and specificity of 0.886 (95% CI 0.765-0.972). The adjusted Kaplan-Meier median OS constructed using Cox proportional-hazard models and stratified for E-CTC < 11.0 CTCs/2 ml was 16.5 months and for E-CTC ≥ 11.0 CTCs/2 ml was 5.5 months (HR = 0.050, 95% CI 0.004-0.578, P = .016). These OS results were consistent with the outcome of the metastatic analysis.

INTERPRETATION

Our work suggested that H-CTC is a better predictor of metastasis and E-CTC is a significant independent predictor of OS. The CTC phenotyping model has the potential to be developed into a reliable and accurate blood test for metastatic and OS assessments of PDAC patients. FUND: National Natural Science Foundation of China; Zhejiang Province Science and Technology Program; China Scholarship Council.