MiR-103a-3p targets the 5\u27 UTR of GPRC5A in pancreatic cells.

MicroRNAs (miRNAs) are short noncoding RNAs that regulate the expression of their targets in a sequence-dependent manner. For protein-coding transcripts, miRNAs regulate expression levels through binding sites in either the 3\u27 untranslated region (3\u27 UTR) or the amino acid coding sequence (CDS) of the targeted messenger RNA (mRNA). Currently, for the 5\u27 untranslated region (5\u27 UTR) of mRNAs, very few naturally occurring examples exist whereby the targeting miRNA down-regulates the expression of the corresponding mRNA in a seed-dependent manner. Here we describe and characterize two miR-103a-3p target sites in the 5\u27 UTR of GPRC5A, a gene that acts as a tumor suppressor in some cancer contexts and as an ongocene in other cancer contexts. In particular, we show that the interaction of miR-103a-3p with each of these two 5\u27 UTR targets reduces the expression levels of both GPRC5A mRNA and GPRC5A protein in one normal epithelial and two pancreatic cancer cell lines. By ectopically expressing sponges that contain instances of the wild-type 5\u27 UTR targets we also show that we can reduce miR-103a-3p levels and increase GPRC5A mRNA and protein levels. These findings provide some first knowledge on the post-transcriptional regulation of this tumor suppressor/oncogene and present additional evidence for the participation of 5\u27 UTRs in miRNA driven post-transcriptional regulatory control

Dampening bullwhip effect of order-up-to inventory strategies via an optimal control method

In this paper, we consider the bullwhip effect problem of an Order-Up-To (OUT) inventory strategy for a supply chain system. We firstly establish a new discrete-time dynamical model which is suitable to describe the OUT inventory strategy. Then, we analyze the bullwhip effect for the dynamical model of the supply chain system. We thus transform the bullwhip effect's dampening problem to a discrete-time optimal control problem. By using the Pontryagin's maximum principle, we compute the corresponding optimal control and obtain the optimal manufacturer productivity of goods. Finally, we carry out numerical simulation experiments to show that the devised optimal control strategy is useful to dampen the bullwhip effect which always happens in the supply chain system

Hybrid intelligence model based on image features for the prediction of flotation concentrate grade

In flotation processes, concentrate grade is the key production index but is difficult to be measured online. The mechanism models reflect the basic tendency of concentrate grade changes but cannot provide adequate prediction precision. The data-driven models based on froth image features provide accurate prediction within well-sampled space but rely heavily on sample data with less generalization capability. So, a hybrid intelligent model combining the two kinds of model is proposed in this paper. Since the information of image features is enormous, and the relationship between image features and concentrate grade is nonlinear, a B-spline partial least squares (BS-PLS) method is adopted to construct the data-driven model for concentrate grade prediction. In order to gain better generalization capability and prediction accuracy, information entropy is introduced to integrate the mechanism model and the BS-PLS model together and modify the model output online through an output deviation compensation strategy. Moreover, a slide window scheme is employed to update the hybrid model in order to improve its adaptability. The industrial practical data testing results show that the performance of the hybrid model is better than either of the two single models and it satisfies the accuracy and stability requirements in industrial applications

Characterization of Rock Mechanical Properties Using Lab Tests and Numerical Interpretation Model of Well Logs

The tight gas reservoir in the fifth member of the Xujiahe formation contains heterogeneous interlayers of sandstone and shale that are low in both porosity and permeability. Elastic characteristics of sandstone and shale are analyzed in this study based on petrophysics tests. The tests indicate that sandstone and mudstone samples have different stress-strain relationships. The rock tends to exhibit elastic-plastic deformation. The compressive strength correlates with confinement pressure and elastic modulus. The results based on thin-bed log interpretation match dynamic Young’s modulus and Poisson’s ratio predicted by theory. The compressive strength is calculated from density, elastic impedance, and clay contents. The tensile strength is calibrated using compressive strength. Shear strength is calculated with an empirical formula. Finally, log interpretation of rock mechanical properties is performed on the fifth member of the Xujiahe formation. Natural fractures in downhole cores and rock microscopic failure in the samples in the cross section demonstrate that tensile fractures were primarily observed in sandstone, and shear fractures can be observed in both mudstone and sandstone. Based on different elasticity and plasticity of different rocks, as well as the characteristics of natural fractures, a fracture propagation model was built

Magnetic Properties of Ni-doped ZnO Nanocombs by CVD Approach

The search for above room temperature ferromagnetism in dilute magnetic semiconductors has been intense in recent year. Arrays of perpendicular ferromagnetic nanowire/rods have recently attracted considerable interest for their potential use in many areas of advanced nanotechnology. We report a simple low-temperature chemical vapor deposition (CVD) to create self-assembled comb-like Ni-/undoped ZnO nanostructure arrays. The phases, compositions, and physical properties of the studied samples were analyzed by different techniques, including high-resolution X-ray diffraction/photoelectron spectroscopy/transmission electron microscopy, photoluminescence, and MPMS. In particular, the Ni-doped ZnO nanocombs (NCs) with ferromagnetic and superparamagnetic properties have been observed whereas undoped ZnO NCs disappear. The corresponding ferromagnetic source mechanism is discussed, in which defects such as O vacancies would play an important role

Interlayer transmission of magnons in dynamic spin valve structures

Magnonic devices are promising alternatives to conventional charge-current-driven spintronic devices. As the basic unit of spintronic devices, the spin valve is of limited use in magnonics because its dynamics is rarely studied. Here, we investigate the interlayer transmission of magnons in dynamic spin valve structures using the time-resolved magneto-optical Kerr effect. Interaction between magnons and the interfacial dissipation are studied by comparing three samples with different spin valve structures. Magnons with different intrinsic frequencies have strong interactions. In contrast, magnons with similar intrinsic frequencies have relatively weak interactions. Interfacial dissipations of magnons are increased by rare earth insertion, which can reduce the interactions between magnons indirectly. This work extends the application of spin valve structures to magnonic devices beyond their conventional use

Printability and Applicability of 3D Printing System Loaded with Chlorogenic Acid Hydrogel

Three-dimensional food printing (3DFP) is an efficient way of food processing in line with the future lifestyle. As a delivery system, hydrogel has become a research hotspot because of its remarkable characteristics such as directed delivery. The purpose of this study was to explore the effects of 3DFP on the structure, physical properties and functions of hydrogels containing methylcellulose (MC), chlorogenic acid (CA) and hyaluronic acid (HA) for the purpose of revealing the printability and applicability of hydrogels in 3DFP processing. Texture properties, rheological properties, microstructure, embedding rate and digestive properties of the 3D printed products were measured. The results showed that the best CA-loaded hydrogel system for 3DFP processing consisted of MC, HA and CA at a mass ratio of 8:0.5:0.5. Its printed product showed the smallest width deviation (13.40%), the highest hardness, the maximum elasticity, and the minimum adhesiveness, had compact structure and uniform porosity, was not easy to collapse, and had good supportability and the best printing moldability. 3DFP well optimized the physical structure of hydrogel without changing its chemical properties. The embedding rate of CA was 22.09 percentage points higher than that before 3D printing. In simulated gastrointestinal digestion test, the release rate of CA from the printed product was significantly higher than that of the unprinted samples, showing a good sustained release effect, and the in vitro release of CA was fitted to the Ritger-Peppas model. These results showed that the hydrogel system had good printability and applicability, and 3DFP could significantly improve the targeted release of CA loaded in hydrogel