Wafer yield is a key indicator to pursuing excellence in semiconductor manufacturing. With the increased wafer size, the enhanced complexity and precision of wafer fabrication is possible. Using monitoring to improve the process by predicting the yield has become an important quality issue. Most research uses the number of wafer defects, the area of the wafer, and fixed statistical distribution to predict the yield. Such methods fail to establish a high yield model due to the random and system-wide distribution of wafer defects. This study proposes the Mahalanobis-Taguchi system (MTS) to determine the key variables from the wafer acceptance test (WAT), and establish a classification model of yield grade. The general regression neural network (GRNN) was used to build a predicted model of the wafer probe yield from selected common variables. A real case from a Taiwan manufacturer of dynamic random-access memory (DRAM) is used as an example. It can get the 82 key and significant sequence variables of the WAT, with classification precision of over 90/ and the R² of the GRNN prediction model at 0.73. Through demonstration, the result can effectively increase the yield and reduce the quality cost in DRAM manufacturing.

Flinteropbrengs is 'n sleutel indikator vir halfgeleiervervaardiging. Die toename in flintergrootte maak dit moontlik om die kompleksiteit en presisie van flintervervaardiging te verbeter. Wanneer monitering gebruik word om die opbrengsskatting te verbeter word dit 'n gehalte kwessie. Die meeste navorsing gebruik die aantal defekte, die flinteroppervlakte, en vasgestelde statistiese verdelings om die opbrengs te skat. Sulke metodes faal egter om 'n hoë-opbrengs model te bewerkstellig as gevolg van die lukrake en stelselwye verspreiding van defekte. Hierdie studie gebruik die Mahalanobis-Taguchi stelsel om die sleutel veranderlikes van die flinter aanvaardingstoets te bepaal en skep dan n klassifikasie model van die opbrengsgehalte. n Veralgemeende regressie neurale netwerk is gebruik om 'n skatting van die opbrengs te maak van gekose gemeenskaplike veranderlikes. 'n Gevallestudie van 'n Taiwannese vervaardiger van dinamies ewetoeganklike geheue word as voorbeeld gebruik. Die benadering kan twee-en-tagtig van die sleutel en noemenswaardige veranderlikes van die aanvaringstoets identifiseer met n klassifikasiepresisie van meer as negentig persent. Die R²-koëffisiënt van die neurale netwerk is 0.73. Die resultaat kan die opbrengs verhoog en die gehaltekoste van dinamies ewetoeganklike geheue vervaardiging verminder.

Inflammation of cartilage is a primary symptom for knee-joint osteoarthritis. Matrix metalloproteinases (MMPs) are known to play an important role in the articular cartilage destruction related to osteoarthritis. Naringenin is a plant-derived flavonoid known for its anti-inflammatory properties. We studied the effect of naringenin on the transcriptional expression, secretion and enzymatic activity of MMP-3 in vivo in the murine monosodium iodoacetate (MIA) osteoarthritis model. The assessment of pain behavior was also performed in the MIA rats. The destruction of knee-joint tissues was analyzed microscopically. Moreover, the effect of naringenin was also studied in vitro in IL-1β activated articular chondrocytes. The transcriptional expression of MMP-3, MMP-1, MMP-13, thrombospondin motifs (ADAMTS-4) and ADAMTS-5 was also studied in primary cultured chondrocytes of rats. Naringenin caused significant reduction in pain behavior and showed marked improvement in the tissue morphology of MIA rats. Moreover, a significant inhibition of MMP-3 expression in MIA rats was observed upon treatment with naringenin. In the in vitro tests, naringenin caused a significant reduction in the transcriptional expression, secretion and enzymatic activity of the studied degradative enzymes. The NF-κB pathway was also found to be inhibited upon treatment with naringenin in vitro. Overall, the study suggests that naringenin alleviated pain and regulated the production of matrix-metalloproteinases via regulation of NF-κB pathway. Thus, naringenin could be a potent therapeutic option for the treatment of osteoarthritis.

Refractory and relapsed leukemia is a major problem during cancer therapy, which is due to the aberrant activation of Wnt/β-catenin signaling pathway. Activation of this pathway is promoted by wingless (Wnt) proteins and induces co-activator β-catenin binding to lymphoid enhancer factor (LEF)/T-cell factor protein (TCF). To provide a convenient system for the screening of anti-Wnt/β-catenin agents, we designed a bi-functional pGL4-TOP reporter plasmid that contained 3X β-catenin/LEF/TCF binding sites and a selectable marker. After transfection and hygromycin B selection, HEK 293-TOP and Jurkat-TOP stable clones were established. The luciferase activity in the stable clone was enhanced by the recombinant Wnt-3A (rWnt-3A; 100-400 ng/mL) and GSK3β inhibitor (2’Z,3’E)-6-bromoindirubin-3’-oxime (BIO; 5 µM) but was inhibited by aspirin (5 mM). Using this reporter model, we found that norcantharidin (NCTD; 100 µM) reduced 80% of rWnt-3A-induced luciferase activity. Furthermore, 50 µM NCTD inhibited 38% of BIO-induced luciferase activity in Jurkat-TOP stable cells. Employing ³H-thymidine uptake assay and Western blot analysis, we confirmed that NCTD (50 µM) significantly inhibited proliferation of Jurkat cells by 64%, which are the dominant β-catenin signaling cells and decreased β-catenin protein in a concentration-dependent manner. Thus, we established a stable HEK 293-TOP clone and successfully used it to identify the Wnt/β-catenin signaling inhibitor NCTD.