Information efficiency in the EU ETS during Phase III

This study examines the market efficiency of the European Union Emission Trading Scheme (EU ETS). Since 2005 it has seen increased importance and growth in trading volume. The EU ETS is the largest emission trading system by transaction volume and in this study tests if the market exhibits predictability of prices. It tests whether overreaction or momentum exists in the carbon price and if so, whether profitable trading strategies can be employed. The thesis documents short term overreaction and momentum along various time-series within the EU ETS. Statistically significant alphas were found in a number of strategies tested. These strategies provide excess returns that remain achievable even after transaction costs have been taken into consideration. The results provide evidence that the EU ETS in Phase III is not informationally efficient.Este estudo examina a eficiência do mercado do Regime de Comércio de Licenças de Emissões da União Europeia (RCLE-UE). Neste mercado, desde 2005, tem vindo a registar se um aumento da atividade comercial e um rápido crescimento. O RCLE-UE é o maior sistema de comércio de emissões em volume de transação. Este estudo testa se o mercado apresenta previsibilidade de preços. Mais precisamente, testa se existe uma reação excessiva ou momentum no preço do carbono e, caso exista, se podem ser utilizadas estratégias comerciais rentáveis. A tese documenta uma reacção excessiva e com momentum, a curto prazo, ao longo de várias séries temporais dentro do CELE da UE. Foram encontrados alfas estatisticamente significativos numa série de estratégias testadas. Estas estratégias proporcionam retornos em excesso que permanecem viáveis mesmo depois de os custos de transacção terem sido tomados em consideração. Assim, os resultados fornecem provas de que o CELE UE na Fase III não é eficiente do ponto de vista informativo

Breakdown Current Density of Graphene Nano Ribbons

Graphene nanoribbons (GNRs) with widths down to 16 nm have been characterized for their current-carrying capacity. It is found that GNRs exhibit an impressive breakdown current density, on the order of 10^8 A/cm2. The breakdown current density is found to have a reciprocal relationship to GNR resistivity and the data fit points to Joule heating as the likely mechanism of breakdown. The superior current-carrying capacity of GNRs will be valuable for their application in on-chip electrical interconnects. The thermal conductivity of sub-20 nm graphene ribbons is found to be more than 1000 W/m-K

Resistivity of Graphene Nanoribbon Interconnects

Graphene nanoribbon interconnects are fabricated, and the extracted resistivity is compared to that of Cu. It is found that the average resistivity at a given line-width (18nm<W<52nm) is about 3X that of a Cu wire, whereas the best GNR has a resistivity comparable to that of Cu. The conductivity is found to be limited by impurity scattering as well as LER scattering; as a result, the best reported GNR resistivity is 3X the limit imposed by substrate phonon scattering. This study reveals that even moderate-quality graphene nanowires have the potential to outperform Cu for use as on-chip interconnects.Comment: 10 pages, 3 figures, to be published in IEEE Electron Device Letter

Gold nanoparticles (AuNPs) impair LPS-driven immune responses by promoting a tolerogenic-like dendritic cell phenotype with altered endosomal structures

Dendritic cells (DCs) shape immune responses by influencing T-cell activation. Thus, they are considered both an interesting model for studying nano-immune interactions and a promising target for nano-based biomedical applications. However, the accentuated ability of nanoparticles (NPs) to interact with biomolecules may have an impact on DC function that poses an unexpected risk of unbalanced immune reactions. Here, we investigated the potential effects of gold nanoparticles (AuNPs) on DC function and the consequences for effector and memory T-cell responses in the presence of the microbial inflammatory stimulus lipopolysaccharide (LPS). Overall, we found that, in the absence of LPS, none of the tested NPs induced a DC response. However, whereas 4-, 8-, and 11 nm AuNPs did not modulate LPS-dependent immune responses, 26 nm AuNPs shifted the phenotype of LPS-activated DCs toward a tolerogenic state, characterized by downregulation of CD86, IL-12 and IL-27, upregulation of ILT3, and induction of class E compartments. Moreover, this DC phenotype was less proficient in promoting Th1 activation and central memory T-cell proliferation. Taken together, these findings support the perception that AuNPs are safe under homeostatic conditions; however, particular care should be taken in patients experiencing a current infection or disorders of the immune system

Major Depressive Disorder is Associated with Impaired Mitochondrial Function in Skin Fibroblasts

Mitochondrial malfunction is supposed to be involved in the etiology and pathology of major depressive disorder (MDD). Here, we aimed to identify and characterize the molecular pathomechanisms related to mitochondrial dysfunction in adult human skin fibroblasts, which were derived from MDD patients or non-depressive control subjects. We found that MDD fibroblasts showed significantly impaired mitochondrial functioning: basal and maximal respiration, spare respiratory capacity, non-mitochondrial respiration and adenosine triphosphate (ATP)-related oxygen consumption was lower. Moreover, MDD fibroblasts harbor lower ATP levels and showed hyperpolarized mitochondrial membrane potential. To investigate cellular resilience, we challenged both groups of fibroblasts with hormonal (dexamethasone) or metabolic (galactose) stress for one week, and found that both stressors increased oxygen consumption but lowered ATP content in MDD as well as in non-depressive control fibroblasts. Interestingly, the bioenergetic differences between fibroblasts from MDD or non-depressed subjects, which were observed under non-treated conditions, could not be detected after stress. Our findings support the hypothesis that altered mitochondrial function causes a bioenergetic imbalance, which is associated with the molecular pathophysiology of MDD. The observed alterations in the oxidative phosphorylation system (OXPHOS) and other mitochondria-related properties represent a basis for further investigations of pathophysiological mechanisms and might open new ways to gain insight into antidepressant signaling pathways

TGF-β1 and TGF-β2 abundance in liver diseases of mice and men

TGF-β1 is a major player in chronic liver diseases promoting fibrogenesis and tumorigenesis through various mechanisms. The expression and function of TGF-β2 have not been investigated thoroughly in liver disease to date. In this paper, we provide evidence that TGF-β2 expression correlates with fibrogenesis and liver cancer development. Using quantitative realtime PCR and ELISA, we show that TGF-β2 mRNA expression and secretion increased in murine HSCs and hepatocytes over time in culture and were found in the human-derived HSC cell line LX-2. TGF-β2 stimulation of the LX-2 cells led to upregulation of the TGF-β receptors 1, 2, and 3, whereas TGF-β1 treatment did not alter or decrease their expression. In liver regeneration and fibrosis upon CCl4 challenge, the transient increase of TGF-β2 expression was accompanied by TGF-β1 and collagen expression. In bile duct ligation-induced fibrosis, TGF-β2 upregulation correlated with fibrotic markers and was more prominent than TGF-β1 expression. Accordingly, MDR2-KO mice showed significant TGF-β2 upregulation within 3 to 15 months but minor TGF-β1 expression changes. In 5 of 8 hepatocellular carcinoma (HCC)/hepatoblastoma cell lines, relatively high TGF-β2 expression and secretion were observed, with some cell lines even secreting more TGF-β2 than TGF-β1. TGF-β2 was also upregulated in tumors of TGFα/cMyc and DEN-treated mice. The analysis of publically available microarray data of 13 human HCC collectives revealed considerable upregulation of TGF-β2 as compared to normal liver. Our study demonstrates upregulation of TGF-β2 in liver disease and suggests TGF-β2 as a promising therapeutic target for tackling fibrosis and HCC

The recombinant inhibitor of DNA binding Id2 forms multimeric structures via the helix-loop-helix domain and the nuclear export signal

The inhibitor of DNA binding and cell differentiation 2 (Id2) is a helix-loop-helix (HLH) protein that acts as negative dominant regulator of basic-HLH transcription factors during development and in cancer. The structural properties of Id2 have been investigated so far by using synthetic or recombinant fragments reproducing single domains (N-terminus, HLH, C-terminus): the HLH domain tends to dimerize into a four-helix bundle, whereas the flanking regions are flexible. In this work, the intact protein was expressed in E. coli, solubilized from inclusion bodies with urea, purified and dissolved in water at pH4. Under these conditions, Id2 was obtained with both cysteine residues disulfide-bonded to -mercaptoethanol that was present during the solubilization process. Moreover, it existed in a self-assembled state, in which the N-terminus remained highly flexible, while the HLH domain and, surprisingly, part of the C-terminus, which corresponds to the nuclear export signal (NES), both were involved in slowly tumbling, rigid structures. The protein oligomers also formed twisted fibrils that were several micrometers long and up to 80 nm thick. These results show that self-assembly decreases the backbone flexibility of those two protein regions (HLH and NES) that are important for interaction with basic-HLH transcription factors or for nucleocytoplasmic shuttling.(VLID)253307

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Measurement of CNGS muon neutrino speed with Borexino

We have measured the speed of muon neutrinos with the Borexino detector using short-bunch CNGS beams. The final result for the difference in time-of-flight between a =17 GeV muon neutrino and a particle moving at the speed of light in vacuum is {\delta}t = 0.8 \pm 0.7stat \pm 2.9sys ns, well consistent with zero.Comment: 6 pages, 5 figure