Wyniki wyszukiwania - Biblioteka Nauki

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Application of a biconical dense medium cyclone to pre-treat a low-grade Pb-Zn sulfide ore

100%

Jian S. , Sun W. , Zheng Y.-x.

tom Vol. 55, iss. 4

981--990

A biconical dense medium cyclone (BDMC) was applied to reject the gangue from a low-grade Pb-Zn sulfide ore for the first time. Based on mineralogy and heavy liquid separation tests, it was found that the rejection of gangue by the BDMC prior to grinding and flotation was promising. The results revealed that the particle size clearly affected the heavy liquid separation process. The effects of several parameters, such as medium specific gravity (SG), spigot diameter, tilt angle, cone angle and medium/ore mass ratio, on the yield of floats and on the metal recoveries in the floats were examined and the optimal parameters were determined. The results showed that 51.22% of floats were obtained with a lead recovery of 7.92% and a zinc recovery of 12.50%. The extended tests were further carried out with the BDMC being capable of throughputs about 3 t/h, which verified the results obtained in the laboratory experiments. The use of this equipment to pre-treat the refractory ore is promising.

Pharmacokinetics of panasenoside in rats and tissue distribution in mice by ultra-performance liquid chromatography tandem mass spectrometry

63%

Chen R. , Lu M. , Tu X. , Sun W. , Ye W. , Ma J. , Wen C. , Wang X. , Geng P.

tom Vol. 31, no. 2

146--150

We developed an ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) method for quantification of panasenoside pharmacokinetics in rat plasma and tissue distribution in mouse. Twelve male Sprague-Dawley rats were used for pharmacokinetics after intravenous (2 or 10 mg/kg) administration of panasenoside, six rats for each dose. Thirty mice were randomly divided into six groups (five mice for each group, one group for each time point) and received 20 mg/kg of panasenoside by intraperitoneal administration. Calibration plots were in the range of 2–2000 ng/mL for panasenoside in rat plasma and 2–3000 ng/mL in mouse tissues. The relative standard deviation (RSD) of inter-day and intra-day precision was less than 14%. The accuracy was between 89.6% and 110.0%. The AUC(0-t) was 160.8 ± 13.0 and 404.9 ± 78.0 ng/mL*h, and t1/2 of 3.2 ± 1.2 and 4.6 ± 1.7 h, CL (clearance) of 10.0 ± 2.0, and 21.4 ± 2.0 L/h/kg after intravenous administration 2 mg/kg and 10 mg/kg of panasenoside, respectively. The tissue distribution results indicated that the panasenoside diffuses rapidly and widely into major organs. The level of panasenoside was highest in mouse liver, followed by kidney, lung, and spleen. The overwhelming accumulation in liver indicated that liver was responsible for the extensive metabolism.

Time-frequency Representation -enhanced Transfer Learning for Tool Condition Monitoring during milling of Inconel 718

63%

Zhou Y. , Sun W. , Ye C. , Peng B. , Fang X. , Lin C. , Wang G. , Kumar A. , Sun W.

tom Vol. 25, no. 2

art. no. 165926

Accurate tool condition monitoring (TCM) is important for the development and upgrading of the manufacturing industry. Recently, machine-learning (ML) models have been widely used in the field of TCM with many favorable results. Nevertheless, in the actual industrial scenario, only a few samples are available for model training due to the cost of experiments, which significantly affects the performance of ML models. A time-series dimension expansion and transfer learning (TL) method is developed to boost the performance of TCM for small samples. First, a time-frequency Markov transition field (TFMTF) is proposed to encode the cutting force signal in the cutting process to two-dimensional images. Then, a modified TL network is established to learn and classify tool conditions under small samples. The performance of the proposed TFMTF-TL method is demonstrated by the benchmark PHM 2010 TCM dataset. The results show the proposed method effectively obtains superior classification accuracies for small samples and outperforms other four benchmark methods.