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The present research on intelligent bearing fault diagnosis assumes that the same feature distribution is used to obtain training and testing data. However, the domain shift (distribution discrepancy) issue generally occurs in both datasets because of different operational conditions. The domain adaptation techniques are preferably applied for fault diagnosis to handle the domain shift issue. Moreover, collecting sufficient testing data or labelled data in real industries is a challenging task. Therefore, the multi-kernel joint distribution adaptation (MKJDA) with dynamic distribution alignment is proposed for bearing fault diagnosis. This method dynamically joins both the marginal and conditional distributions and uses the multi-kernel to solve the non-linear problems to extract the most effective and robust representation for cross-domain issues. Moreover, it runs with the unlabelled task domain to perform the diagnosis by iteratively updating the pseudo code. The experimental results (two public datasets and one experimental dataset) demonstrated that the proposed method (MKJDA) exhibited stable and robust accuracy while conducting bearing fault diagnosis. It can effectively address the most crucial issue: intelligent diagnosis methods must re-train the model when the distribution differs between the source domain (the model is learned) and the target domain (the learned model is applied).

Purpose It is usually difficult to obtain the accurate mechanical properties of pediatric brain and skull because of the absence of pediatric cadaver experiments. The goal of this work is to discuss how different brain mechanical properties influence pediatric head response.

We have developed a facile in-situ growth method for the deposition of magnetite (Fe3O4) particles on the surface of a graphitic carbon nitride (g-C3N4) nanosheet. The material was characterized by X-ray diffraction, transmission electron microscopy, Fourier transform infrared spectroscopy, and thermogravimetric analysis. The high affinity of g-C3N4 for phenolic acids in combination with the magnetism of Fe3O4 provides an efficient means for magnetic solid phase extraction. The adsorption, desorption and recoveries were examined. Under optimized conditions, the method has limits of detection in the range from 17.5–42.6 ng mL−1 (at an S/N of 3), and precisions from 2.8–3.8 % (for n = 5). The method was successfully applied to the determination of protocatechuic, caffeic, and ferulic acids in Salicornia herbacea L. plant extracts. Recoveries ranged from 92.4–99.5 %.

The trajectory model of dispersed phase drops and distribution model of drop diameters were derived. By numerical simulation, the analytical results indicate that a large number of dispersed phase drops accumulate on the upper plate in different directions and form a hydrodynamic area with the stream-wise location in the range of 0–0.4 m, where the flow of trickling film obtains kinetic drive from flowing field. The flowing field of trickling film exhibits an unstable state if the stream-wise location is less than 0.02 m, and a stable state otherwise. Moreover, different velocity vectors of drops in the x-y plane result in different interactions between the trickling film and drops. For the non-uniform distribution of drop diameters, there is a stronger interaction between the trickling film and drop if the stream-wise location is less than 0.02 m, because the amplitudes of velocity vectors are higher than those in the range of 0.02–1.0 m. The result reveals a complexity and diversity of stratified two-phase flowing field. On the other hand, both the basic flowing field and distributions of drop diameters have a great influence on the distributions of comparable kinetic energy of drops. The complicated motions of larger drops are helpful to coalescence because they will consume much more kinetic energy on the trickling film than those of smaller drops. The change of comparable kinetic energy of smaller drops is continuous and steady. The smaller drops are easily entrained by the liquid-liquid flowing field.

Thick and hard ceramic coatings were fabricated on A356 aluminum alloy by using plasma electrolytic oxidation (PEO) technique. The microstructure and phase composition of the PEO coatings were examined by using SEM and XRD method. It is found that the PEO coatings are mainly composed of crystalline α-Al2O3 and mullite. The dry sliding wear test of PEO coatings were carried out on a ring-on-ring wear machine. Results shows that there is hardly no wear loss of polished PEO coatings while the wear rate of uncoated aluminum alloy is 4.3 × 10−5 mm3.(N.m)−1 at a speed of 0.52 m.s−1 and a load of 40 N.

The molecular electronegativity-distance vector (MEDV) is employed to describe the chemical structure of bisphenol A analogs and their correlated estrogen activities. The result shows that the constructed models have good predictability and indicates substructures that may influence estrogen activities of chemicals.

Poor casting properties restrict the application of high strength casting Al-5.0% Cu alloy. The addition of element can improve the casting properties of this alloy. Effect of Si on the casting properties of Al-5.0% Cu alloy was studied. It has been found that the addition of Si can improve the casting properties of Al-5.0% Cu alloy obviously. With the increase of Si content, the hot cracking tendency of the alloy decreases significantly, and the fluidity of the alloy increases firstly and then decreases slowly. When the content of Si element is higher than 2wt.%, the fluidity of the alloy increases greatly with the increasing of Si content.