Atomistic modeling of resistivity evolution of copper nanoparticle in intense pulsed light sintering process

In this work, the intense pulsed light (IPL) sintering process of copper nanoparticle ink is simulated using molecular dynamics (MD) method. First, the neck size growth between the two copper nanoparticles during the IPL sintering process is computed. The resultant electrical resistivity is then calculated by substituting the neck size into the Reimann-Weber formula. Overall, a rapid decrease of electric resistivity is observed in the beginning of the sintering, which is caused by quick neck size growth, followed by a gradually decrease of resistivity. In addition, the correlation of the simulated temperature dependent resistivity is similar to that of the experimentally measured resistivity. The MD model is an effective tool for designers to optimize the IPL sintering process

Study on the technology and properties of 3D bioprinting SF/GT/n-HA composite scaffolds

In this paper, three kinds of natural polymer materials, silk fibroin (SF), gelatin (GT), and nano-hydroxyapatite (n-HA), are mixed as 3D printing bioink to mimic protein polysaccharide and collagen fibers in natural articular cartilage. By changing the SF content, SF/GT/n-HA composite scaffolds with different ratios are prepared using 3D bioprinting technology. The microstructure and morphology, biological properties and mechanical properties of composite scaffolds are characterized. The results show that the printing precision of the bioink with 10% SF is best, and the composite scaffold with 10% SF also exhibits better mechanical properties, whose tensile elastic modulus is 10.60 ± 0.32 MPa and the compression elastic modulus is 1.22 ± 0.06 MPa. These studies are helpful to understand the interaction between SF, GT and n-HA, and provide a theoretical basis for the preparation of better silk fibroin-based composite scaffolds

Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

Artemisinin derivative SM934, influences the activation, proliferation, differentiation and antibody-secreting capacity of β-cells in systemic lupus erythematosus mice via inhibition of TLR7/9 signaling pathway

Purpose: To study the influence of artemisinin derivative, SM934 on activation, proliferation, differentiation and antibody-secreting capacity of B cells of systemic lupus erythematosus (SLE) mice, and the underlying mechanism. Methods: Female MRL/lpr mice (n = 60) were randomly assigned to four groups of 15 mice each: SLE, 2.5 mg/kg SM934; 5 mg/kg SM934, and 10 mg/kg SM934 groups. Serum levels of interleukins 6, 10, 17 and 21 (IL-6, IL-17, IL-10 and IL-21) were determined. The secretions of immunoglobulins G and M (IgG and IgM) by B cells were determined. The population of B lymphocyte subtypes was determined flow cytometrically. The expressions of Blimp-1 and Bcl-6, Toll-like receptors 7 and 9 (TLR7 and TLR9) mRNAs were determined. Results: SLE-induced upregulation of serum IL-10, IL-6, IL-17 and IL-21 was significantly and dosedependently reduced following a 2-month treatment with SM934 (p < 0.01). Treatment with SM934 significantly and dose-dependently accentuated B cell germinal center B cell populations, but significantly and dose-dependently decreased the populations of plasma and activated B cells (p < 0.01). The splenic levels of IgG and IgM were decreased in a dose-dependent fashion after 8 weeks of treatment (p < 0.01). Artemisinin derivative SM934 decreased the expression of Blimp-1, and upregulated the expression of Bcl-6, both in a dose-dependent manner (p < 0.01). Moreover, SM934 decreased the mRNA expressions of TLR7 and TLR9 in a dose-based manner (p < 0.01). Conclusion: Artemisinin derivative SM934 mitigates LSE syndromes by suppressing the TLR-induced B-cell stimulation and plasma cell generatio

Quantifying Nonradiative Recombination and Resistive Losses in Perovskite Photovoltaics: A Modified Diode Model Approach

Pinpointing the origin of inefficiency can expedite the process of optimizing the efficiency of perovskite photovoltaics. However, it is challenging to discern and quantify the different loss pathways in a complete perovskite photovoltaic device under operational conditions. To address this challenge, we propose a modified diode model that can quantify bulk/interface defect-assisted recombination and series/shunt resistive losses. By adopting drift-diffusion simulation as the benchmark, we explore the physical meanings of the modified diode model parameters and evaluate the performance of the model for simulation parameters spanning many orders of magnitude. Our evaluation shows that, in most practical cases, the proposed model can accurately quantify all the aforementioned losses, and in some special cases, it is possible to identify the predominant loss pathway. Moreover, we apply the modified diode model to our lab-produced devices (based on Cs0.05FA0.95PbI3 perovskites), demonstrating its effectiveness in quantifying entangled losses in practice. Finally, we provide a set of guidelines for applying the modified diode model and interpreting the results. Source code available at https://github.com/WPT-Lab124/Modified-Diode-Model.Comment: 26 pages, 6 figures, published in Solar RR

Cloud Computing and Big Data for Oil and Gas Industry Application in China

The oil and gas industry is a complex data-driven industry with compute-intensive, data-intensive and business-intensive features. Cloud computing and big data have a broad application prospect in the oil and gas industry. This research aims to highlight the cloud computing and big data issues and challenges from the informatization in oil and gas industry. In this paper, the distributed cloud storage architecture and its applications for seismic data of oil and gas industry are focused on first. Then,cloud desktop for oil and gas industry applications are also introduced in terms of efficiency, security and usability. Finally, big data architecture and security issues of oil and gas industry are analyzed. Cloud computing and big data architectures have advantages in many aspects, such as system scalability, reliability, and serviceability. This paper also provides a brief description for the future development of Cloud computing and big data in oil and gas industry. Cloud computing and big data can provide convenient information sharing and high quality service for oil and gas industry

The Viscosity Characteristics for the Mixed Refrigerant HFO-1234yf + HFC-152a

Refrigerants are improved with the development of refrigeration and air conditioning industry. Because of the long-term use of chlorine-containing halogenated hydrocarbon substances, the ozone depletion and global warming become important issues around the world. Searching for refrigerants with low GWP (Global Warming Potential) and zero ODP (Ozone Depletion Potential) is urgent. HFC-134a used to be a widely used refrigerant with zero ODP. However, its high GWP of 1300 and long atmospheric lifetime of 14 years would cause the problem of global warming. Thus, for the sake of environment, the substitution of HFC-134a is imperative. In recent years, HFO-1234yf has been regarded as one of the widely used substitutions of HFC-134a because of low GWP of 4 and similar thermophysical properties to HFC-134a. However, its COP is slightly smaller than that of HFC-134a. In order to make better use of HFO-1234yf, some HFO-1234yf + HFCs or HFO-1234yf + HCs binary mixtures were proposed as alternative refrigerants. HFC-152a with low GWP of 140 and a short atmospheric lifetime of 1.5 years was selected as component in refrigerant mixtures. The mixture HFO-1234yf + HFC-152a is a promising alternative refrigerant. Before the actual application of alternative refrigerants in the refrigeration and air conditioning systems, thermophysical properties of mixed refrigerants need to be carefully investigated. Knowledge of viscosity characteristics, as one of the major concerns in the study of the thermophysical properties of alternative refrigerants, has significant impact on heat transfer and pressure drop in the flow, and viscosity data with high accuracy are of considerable value in the calculation of heat transfer and fluid flow. Â Â Â Â Â Â Thus, in this work, the measurement of liquid viscosity of the mixture was carried out with a new type of gravitational capillary viscometer developed in our previous work. The liquid viscosity experimental system used in this paper consists of a gravitational capillary viscometer made of glass, a pressure vessel with sight glasses, a thermostatic bath system and a measurement system. The measurement system consists of a high accurate temperature measure system (the standard temperature uncertainty is less than 0.011K) and a high accurate pressure measure system (the standard pressure uncertainty is within 1.4 kPa). The expanded uncertainty of dynamic viscosity was 1.58 %. The reliability of the experimental apparatus has been validated with HFO-1234yf and the binary mixture HFC-22 + HFC-134a (0.7 + 0.3, by mole fraction) in previous work. Based on this, the gravitational capillary viscometer was firstly calibrated with HCFC-22, and then, the liquid viscosity data of the binary mixture HFO-1234yf + HFC-152a (0.81 + 0.19, by mole fraction) were given from 278.15 K to 333.15 K. Two most commonly used viscosity models based on the Andrade equation were used to correlate the experimental data of the mixture HFO-1234yf + HFC-152a (0.81 + 0.19, by mole fraction). The correlation results were discussed

Suppression of Spry4 enhances cancer stem cell properties of human MDA-MB-231 breast carcinoma cells

BACKGROUND: Cancer stem cells contribute to tumor initiation, heterogeneity, and recurrence, and are critical targets in cancer therapy. Sprouty4 (Spry4) is a potent inhibitor of signal transduction pathways elicited by receptor tyrosine kinases, and has roles in regulating cell proliferation, migration and differentiation. Spry4 has been implicated as a tumor suppressor and in modulating embryonic stem cells. OBJECTIVES: The purpose of this research was to test the novel idea that Spry4 regulates cancer stem cell properties in breast cancer. METHODS: Loss-of function of Spry4 in human MDA-MB-231 cell was used to test our hypothesis. Spry4 knockdown or control cell lines were generated using lentiviral delivery of human Spry4 or non-targeting control shRNAs, and then selected with 2 μg/ml puromycin. Cell growth and migratory abilities were determined using growth curve and cell cycle flow cytometry analyses and scratch assays, respectively. Xenograft tumor model was used to determine the tumorigenic activity and metastasis in vivo. Cancer stem cell related markers were evaluated using immunoblotting assays and fluorescence-activated cell sorting. Cancer stem cell phenotype was evaluated using in vitro mammosphere formation and drug sensitivity tests, and in vivo limiting dilution tumor formation assay. RESULTS: Two out of three tested human Spry4 shRNAs significantly suppressed the expression of endogenous Spry4 in MDA-MB-231 cells. Suppressing Spry4 expression increased MDA-MB-231 cell proliferation and migration. Suppressing Spry4 increased β3-integrin expression, and CD133(+)CD44(+) subpopulation. Suppressing Spry4 increased mammosphere formation, while decreasing the sensitivity of MDA-MB-231 cells to Paclitaxel treatment. Finally, suppressing Spry4 increased the potency of MDA-MB-231 cell tumor initiation, a feature attributed to cancer stem cells. CONCLUSIONS: Our findings provide novel evidence that endogenous Spry4 may have tumor suppressive activity in breast cancer by suppressing cancer stem cell properties in addition to negative effects on tumor cell proliferation and migration