Fast Estimation of True Bounds on Bermudan Option Prices under Jump-diffusion Processes

Fast pricing of American-style options has been a difficult problem since it was first introduced to financial markets in 1970s, especially when the underlying stocks' prices follow some jump-diffusion processes. In this paper, we propose a new algorithm to generate tight upper bounds on the Bermudan option price without nested simulation, under the jump-diffusion setting. By exploiting the martingale representation theorem for jump processes on the dual martingale, we are able to explore the unique structure of the optimal dual martingale and construct an approximation that preserves the martingale property. The resulting upper bound estimator avoids the nested Monte Carlo simulation suffered by the original primal-dual algorithm, therefore significantly improves the computational efficiency. Theoretical analysis is provided to guarantee the quality of the martingale approximation. Numerical experiments are conducted to verify the efficiency of our proposed algorithm

Adenovirus E4 Open Reading Frame 4-Induced Dephosphorylation Inhibits E1A Activation of the E2 Promoter and E2F-1-Mediated Transactivation Independently of the Retinoblastoma Tumor Suppressor Protein

AbstractPrevious studies have shown that the cell cycle-regulated E2F transcription factor is subjected to both positive and negative control by phosphorylation. Here we show that in transient transfection experiments, adenovirus E1A activation of the viral E2 promoter is abrogated by coexpression of the viral E4 open reading frame 4 (E4-ORF4) protein. This effect does not to require the retinoblastoma protein that previously has been shown to regulate E2F activity. The inhibitory activity of E4-ORF4 appears to be specific because E4-ORF4 had little effect on, for example, E4-ORF6/7 transactivation of the E2 promoter. We further show that the repressive effect of E4-ORF4 on E2 transcription works mainly through the E2F DNA-binding sites in the E2 promoter. In agreement with this, we find that E4-ORF4 inhibits E2F-1/DP-1-mediated transactivation. We also show that E4-ORF4 inhibits E2 mRNA expression during virus growth. E4-ORF4 has previously been shown to bind to and activate the cellular protein phosphatase 2A. The inhibitory effect of E4-ORF4 was relieved by okadaic acid, which inhibits protein phosphatase 2A activity, suggesting that E4-ORF4 represses E2 transcription by inducing transcription factor dephosphorylation. Interestingly, E4-ORF4 did not inhibit the transactivation capacity of a Gal4-E2F hybrid protein. Instead, E4-ORF4 expression appears to result in reduced stability of E2F/DNA complexes

Estimating perfluorocarbon emission factors for industrial rare earth metal electrolysis

Rare earth (RE) metals have been widely applied in new materials, leading to their drastic production increase in the last three decades. In the production process featured by the molten-fluoride electrolysis technology, perfluorocarbon (PFC) emissions are significant and therefore deserve full accounting in greenhouse gas (GHG) emission inventories. Yet, in the ‘2006 IPCC Guidelines for National Greenhouse Gas Inventories’, no method currently exists to account for PFC emissions from rare earth metal production. This research aims to determine emission factors for industrial rare earth metals production through on-site monitoring and lab analysis of PFC concentrations in the exhaust gases from rare earth metal electrolysis. Continuous FTIR measurements and time-integrated samples (analysed off-site by high-precision Medusa GC–MS) were conducted over 24–60 h periods from three rare earth companies in China, covering production of multiple rare earth metals/alloys including Pr-Nd, La and Dy-Fe. The study confirmed that PFC emissions are generated during electrolysis, typically in the form of CF4 (∼90% wt of detected PFCs), C2F6 (∼10%) and C3F8 (<1%); trace levels of c-C4F8 and C4F10 were also detected. In general, PFC emission factors vary with rare earth metal produced and from one facility to another, ranging from 26.66 to 109.43 g/t-RE for CF4 emissions, 0.26 to 10.95 g/t-RE for C2F6, and 0.03 to 0.27 g/t-RE for C3F8. Converted to 211.60 to 847.41 kg CO2-e/t-RE for total PFCs, this emissions intensity for rare earths electrolysis is of lower (for most RE production) or similar (Dy-Fe production) level of magnitude to industrial aluminium electrolysis

SMYD3 contributes to a more aggressive phenotype of prostate cancer and targets Cyclin D2 through H4K20me3

Prostate cancer (PCa) is one of the most incident cancers worldwide but clinical and pathological parameters have limited ability to discriminate between clinically significant and indolent PCa. Altered expression of histone methyltransferases and histone methylation patterns are involved in prostate carcinogenesis. SMYD3 transcript levels have prognostic value and discriminate among PCa with different clinical aggressiveness, so we decided to investigate its putative oncogenic role on PCa.We silenced SMYD3 and assess its impact through in vitro (cell viability, cell cycle, apoptosis, migration, invasion assays) and in vivo (tumor formation, angiogenesis). We evaluated SET domain's impact in PCa cells' phenotype. Histone marks deposition on SMYD3 putative target genes was assessed by ChIP analysis.Knockdown of SMYD3 attenuated malignant phenotype of LNCaP and PC3 cell lines. Deletions affecting the SET domain showed phenotypic impact similar to SMYD3 silencing, suggesting that tumorigenic effect is mediated through its histone methyltransferase activity. Moreover, CCND2 was identified as a putative target gene for SMYD3 transcriptional regulation, through trimethylation of H4K20.Our results support a proto-oncogenic role for SMYD3 in prostate carcinogenesis, mainly due to its methyltransferase enzymatic activity. Thus, SMYD3 overexpression is a potential biomarker for clinically aggressive disease and an attractive therapeutic target in PCa.Liga Portuguesa Contra o Cancro – Núcleo Regional do Norte , Research Center of Portuguese Oncology Institute – Porto (CI-IPOP 4-2012) and European Community’s Seventh Framework Programme – Grant number FP7-HEALTH-F5-2009-241783. FQV and SS-S are supported by FCT-Fundação para a Ciência e a Tecnologia grants (SFRH/BD/70564/2010 and PTDC/ SAU-MET/113415/2009), IG is a Posdoc fellow from FCT (PEst-OE/SAU/UI0776/2014)

Detect what you want: Target Sound Detection

Human beings can perceive a target sound type from a multi-source mixture signal by the selective auditory attention, however, such functionality was hardly ever explored in machine hearing. This paper addresses the target sound detection (TSD) task, which aims to detect the target sound signal from a mixture audio when a target sound's reference audio is given. We present a novel target sound detection network (TSDNet) which consists of two main parts: A conditional network which aims at generating a sound-discriminative conditional embedding vector representing the target sound, and a detection network which takes both the mixture audio and the conditional embedding vector as inputs and produces the detection result of the target sound. These two networks can be jointly optimized with a multi-task learning approach to further improve the performance. In addition, we study both strong-supervised and weakly-supervised strategies to train TSDNet and propose a data augmentation method by mixing two samples. To facilitate this research, we build a target sound detection dataset (\textit{i.e.} URBAN-TSD) based on URBAN-SED and UrbanSound8K datasets, and experimental results indicate our method could get the segment-based F scores of 76.3$\%$ and 56.8$\%$ on the strongly-labelled and weakly-labelled data respectively.Comment: Submitted to DCASE workshop202

Migration and Enrichment Behaviors of Ca and Mg Elements during Cooling and Crystallization of Boron-Bearing Titanium Slag Melt

Synthetic rutile was prepared from titanium slag melt with low energy consumption and a small amount of additive (B2O3) in our previous work. The modification mechanism of titanium slag was not clear enough. The migration and enrichment behaviors of Ca and Mg elements during cooling and crystallization of boron-bearing titanium slag melt were characterized by XRF, FESEM, EMPA, and XPS. Results show that when additive (B2O3) is added, Ti elements are migrated and enriched in the area to generate rutile, while Ca, Mg, and B elements are migrated and enriched in another area to generate borate. With the additive (B2O3) amount increased, Ca and Mg element migration is complete and more thorough. Additive (B2O3) promotes rutile formation and inhibits the formation of anosovite during cooling and crystallization of titanium slag melt. With the additive (B2O3) amount increasing from 0% to 6%, the proportion of Ti3+ in the modified titanium slag reduces from 9.15% to 0%, and the proportion of Ti4+ increases from 90.85% to 100% under the same cooling and crystallization condition. The result will lay the foundation for the efficient preparation of synthetic rutile by adding B2O3 to the titanium slag melt