GA-Based Model Predictive Control of Semi-Active Landing Gear

AbstractSemi-active landing gear can provide good performance of both landing impact and taxi situation, and has the ability for adapting to various ground conditions and operational conditions. A kind of Nonlinear Model Predictive Control algorithm (NMPC) for semi-active landing gears is developed in this paper. The NMPC algorithm uses Genetic Algorithm (GA) as the optimization technique and chooses damping performance of landing gear at touch down to be the optimization object. The valve's rate and magnitude limitations are also considered in the controller's design. A simulation model is built for the semi-active landing gear's damping process at touchdown. Drop tests are carried out on an experimental passive landing gear systerm to validate the parameters of the simulation model. The result of numerical simulation shows that the isolation of impact load at touchdown can be significantly improved compared to other control algorithms. The strongly nonlinear dynamics of semi-active landing gear coupled with control valve's rate and magnitude limitations are handled well with the proposed controller

Growth Factor Signaling Enhances Aromatase Activity of Breast Cancer Cells Via Post-Transcriptional Mechanisms

It has been demonstrated that growth factors produced by breast cancer cells stimulate aromatase expression in both breast cancer and adjacent adipose fibroblasts and stromal cells. However, whether these growth factors affect aromatase activity by other mechanisms still remain unclear. In the current study, MCF-7aro and T47Daro aromatase transfected breast carcinoma cells were used to explore the mechanisms of post-transcriptional regulation of aromatase activity by growth factor pathways. Our study reveals that PI3K/Akt and MAPK inhibitors suppressed aromatase activity in MCF-7aro cells. However, PI3K/Akt pathway inhibitors stimulated aromatase activity in T47Daro cells. This is due to enhanced MAPK phosphorylation as compensation after the PI3K/Akt pathway has been blocked. IGF-1 treatment increased aromatase activity in both breast cancer cell lines. In addition, LTEDaro cells (long-term estrogen deprived MCF-7aro cells) which have enhanced MAPK activity, show higher aromatase activity compared to parental MCF-7aro cells, but the aromatase protein level remains the same. These results suggest that aromatase activity could be enhanced by growth factor signaling pathways via post-transcriptional mechanisms

COX-2 Inhibitor Nimesulide Analogs are Aromatase Suppressors in Breast Cancer Cells

Cyclooxygenase-2 (COX-2) inhibitor nimesulide derivatives compounds A and B decreased aromatase activity in breast cancer cells via a novel mechanism different to aromatase inhibitors (AIs), and were defined as “aromatase suppressors”. Breast carcinoma cells (MCF-7aro and T47Daro) transfected with aromatase full gene were used to explore the mechanisms of the two compounds. They dose and time-dependently suppressed aromatase activity in MCF-7aro and T47Daro cells in the nanomole range. However, they neither directly inhibited aromatase, nor improved aromatase degradation even at much higher concentrations. They could also suppress androgen stimulated cell growth, but did not affect estrogen enhanced cell proliferation. These results suggest that compounds A and B selectively interfere with aromatase in breast cancer cells, but not estrogen receptor (ER) downstream to disrupt androgen mediated cell growth. Interestingly, compound B effectively inhibited LTED (long-term estrogen deprived MCF-7aro cell) cell growth, which is a model for AIs resistance, with an IC50 of 4.68 ± 0.54 μM. The results indicate that compound B could potentially overcome AI resistance in breast cancer cell and could be used as a lead to design more potent derivatives

Growth Factor Signaling Enhances Aromatase Activity of Breast Cancer Cells Via Post-Transcriptional Mechanisms

It has been demonstrated that growth factors produced by breast cancer cells stimulate aromatase expression in both breast cancer and adjacent adipose fibroblasts and stromal cells. However, whether these growth factors affect aromatase activity by other mechanisms still remain unclear. In the current study, MCF-7aro and T47Daro aromatase transfected breast carcinoma cells were used to explore the mechanisms of post-transcriptional regulation of aromatase activity by growth factor pathways. Our study reveals that PI3K/Akt and MAPK inhibitors suppressed aromatase activity in MCF-7aro cells. However, PI3K/Akt pathway inhibitors stimulated aromatase activity in T47Daro cells. This is due to enhanced MAPK phosphorylation as compensation after the PI3K/Akt pathway has been blocked. IGF-1 treatment increased aromatase activity in both breast cancer cell lines. In addition, LTEDaro cells (long-term estrogen deprived MCF-7aro cells) which have enhanced MAPK activity, show higher aromatase activity compared to parental MCF-7aro cells, but the aromatase protein level remains the same. These results suggest that aromatase activity could be enhanced by growth factor signaling pathways via post-transcriptional mechanisms

Aplikasi Image Thresholding Untuk Segmentasi Objek

Salah satu operasi di dalam analisis citra adalah segmentasi citra, yaitu memisahkan objek dari latar belakangnya atau dari objek lain yang tidak menjadi perhatian. Metode sementasi yang sederhana adalah dengan operasi pengambangan (thresholding). Operasi pengambangan menghasilkan citra biner, yang dalam hal ini objek yang diacu di-set berwarna putih sedangkan latar belakangnya di-set berwarna hitam (atau sebaliknya bergantung kasusnya). Makalah ini mempresentasikan penggunaan operasi pengambangan untuk melakukan segmentasi objek. Eksperimen dilakukan dengan menggunakan kakas MATLAB. Hasil eksperimen memperlihatkan bahwa pemilihan nilai ambang (threshold) yang tepat sangat menentukan keberhasilan segmentasi

Quantum Attacks on Type-1 Generalized Feistel Schemes

Generalized Feistel schemes (GFSs) are extremely important and extensively researched cryptographic schemes. In this paper, we investigate the security of Type-1 GFS in quantum circumstances. On the one hand, in the qCCA setting, we give a new quantum polynomial-time distinguisher on $(d^2-1)$-round Type-1 GFS with branches $d\geq3$, which extends the previous results by $(d-2)$ rounds. This leads to a more efficient analysis of type-1 GFS, that is, the complexity of some previous key-recovery attacks is reduced by a factor of $2^{\frac{(d-2)k}{2}}$, where $k$ is the key length of the internal round function. On the other hand, for CAST-256, which is a certain block cipher based on Type-1 GFS, we give a 17-round quantum distinguisher in the qCPA setting. Based on this, we construct an $r (r>17)$-round quantum key-recovery attack with complexity $O(2^{\frac{37(r-17)}{2}})$

Quantum Attacks on Beyond-Birthday-Bound MACs

In this paper, we investigate the security of several recent MAC constructions with provable security beyond the birthday bound (called BBB MACs) in the quantum setting. On the one hand, we give periodic functions corresponding to targeted MACs (including PMACX, PMAC with parity, HPxHP, and HPxNP), and we can recover secret states using Simon algorithm, leading to forgery attacks with complexity $O(n)$. This implies our results realize an exponential speedup compared with the classical algorithm. Note that our attacks can even break some optimally secure MACs, such as mPMAC+-f, mPMAC+-p1, mPMAC+-p2, mLightMAC+-f, etc. On the other hand, we construct new hidden periodic functions based on SUM-ECBC-like MACs: SUM-ECBC, PolyMAC, GCM-SIV2, and 2K-ECBC$_{-}$Plus, where periods reveal the information of the secret key. Then, by applying Grover-meets-Simon algorithm to specially constructed functions, we can recover full keys with $O(2^{n/2}n)$ or $O(2^{m/2}n)$ quantum queries, where $n$ is the message block size and $m$ is the length of the key. Considering the previous best quantum attack, our key-recovery attacks achieve a quadratic speedup

The ADH1B Arg47His polymorphism in East Asian populations and expansion of rice domestication in history

<p>Abstract</p> <p>Background</p> <p>The emergence of agriculture about 10,000 years ago marks a dramatic change in human evolutionary history. The diet shift in agriculture societies might have a great impact on the genetic makeup of Neolithic human populations. The regionally restricted enrichment of the class I alcohol dehydrogenase sequence polymorphism (ADH1BArg47His) in southern China and the adjacent areas suggests Darwinian positive selection on this genetic locus during Neolithic time though the driving force is yet to be disclosed.</p> <p>Results</p> <p>We studied a total of 38 populations (2,275 individuals) including Han Chinese, Tibetan and other ethnic populations across China. The geographic distribution of the ADH1B*47His allele in these populations indicates a clear east-to-west cline, and it is dominant in south-eastern populations but rare in Tibetan populations. The molecular dating suggests that the emergence of the ADH1B*47His allele occurred about 10,000~7,000 years ago.</p> <p>Conclusion</p> <p>We present genetic evidence of selection on the ADH1BArg47His polymorphism caused by the emergence and expansion of rice domestication in East Asia. The geographic distribution of the ADH1B*47His allele in East Asia is consistent with the unearthed culture relic sites of rice domestication in China. The estimated origin time of ADH1B*47His allele in those populations coincides with the time of origin and expansion of Neolithic agriculture in southern China.</p