Towards an exact reconstruction of a time-invariant model from time series data

Dynamic processes in biological systems may be profiled by measuring system properties over time. One way of representing such time series data is through weighted interaction networks, where the nodes in the network represent the measurables and the weighted edges represent interactions between any pair of nodes. Construction of these network models from time series data may involve seeking a robust data-consistent and time-invariant model to approximate and describe system dynamics. Many problems in mathematics, systems biology and physics can be recast into this form and may require finding the most consistent solution to a set of first order differential equations. This is especially challenging in cases where the number of data points is less than or equal to the number of measurables. We present a novel computational method for network reconstruction with limited time series data. To test our method, we use artificial time series data generated from known network models. We then attempt to reconstruct the original network from the time series data alone. We find good agreement between the original and predicted networks

Antidumping and Retaliation Threats

This paper examines how the prospect of foreign retaliation affects the antidumping (AD) process in the United States. We separate the capacity for retaliation into two channels: (i) the capacity for foreign government retaliation under the dispute settlement procedures of the GATT/WTO system, and (ii) the capacity for foreign industry retaliation through reciprocal claims of dumping and the foreign pursuit of AD duties in countries with AD regimes. Using a nested logit framework and analyzing U.S. AD cases between 1980 and 1998, we find significant empirical evidence consistent with the theory that U.S. industry is influenced by the threat of reciprocal foreign ADDs in its decision of which foreign countries to name in the initial AD petition, and that the U.S. AD authority's antidumping decisions are influenced by the threat of foreign retaliation under the GATT/WTO dispute settlement mechanism.

China's export growth and the China safeguard : threats to the world trading system ?

Is there evidence from China's pre-WTO accession period that newly imposed U.S. or EU import restrictions deflect Chinese exports to third markets? The authors examine this question by drawing on a newly constructed data set of U.S. and EU product-level import restrictions on Chinese trade imposed between 1992 and 2001 and estimate their impact on Chinese exports to 38 alternative markets. There is no systematic evidence that the import restrictions imposed during this period resulted in Chinese exports surging to such alternate destinations. To the contrary, there is weak evidence of a chilling effect on China's exports to third markets.Free Trade,Economic Theory&Research,Trade Policy,Trade Law,Markets and Market Access

Virtual Site as an aid to first-year learning

Courses run by the School of the Built Environment have a range of entry requirements that enable diverse students and those with lower academic qualifications to gain entry. This results in a particular challenge for the Documentation & Estimating module, which is a very practical, skillsand competence-based module. It is delivered to large tutorial cohorts of mixed courses, abilities, ages and experience. Many students need one-toone guidance to understand what, practically, they have to do. They are given the theory first in a lecture and then have practical tutorials to carry out assessed exercises with limited tutor contact time. The module includes some basic surveying techniques and a levelling exercise which involves the transfer of a level from an assumed benchmark to establish a temporary benchmark some distance away. Many students have problems with computation of results. In spite of a careful introduction and explanation of the use of the instruments and techniques, many students find it difficult to visualise what is happening

Reverse engineering of drug induced DNA damage response signalling pathway reveals dual outcomes of ATM kinase inhibition

The DNA Damage Response (DDR) pathway represents a signalling mechanism that is activated in eukaryotic cells following DNA damage and comprises of proteins involved in DNA damage detection, DNA repair, cell cycle arrest and apoptosis. This pathway consists of an intricate network of signalling interactions driving the cellular ability to recognise DNA damage and recruit specialised proteins to take decisions between DNA repair or apoptosis. ATM and ATR are central components of the DDR pathway. The activities of these kinases are vital in DNA damage induced phosphorylational induction of DDR substrates. Here, firstly we have experimentally determined DDR signalling network surrounding the ATM/ATR pathway induced following double stranded DNA damage by monitoring and quantifying time dependent inductions of their phosphorylated forms and their key substrates. We next involved an automated inference of unsupervised predictive models of time series data to generate in silico (molecular) interaction maps. We characterized the complex signalling network through system analysis and gradual utilisation of small time series measurements of key substrates through a novel network inference algorithm. Furthermore, we demonstrate an application of an assumption-free reverse engineering of the intricate signalling network of the activated ATM/ATR pathway. We next studied the consequences of such drug induced inductions as well as of time dependent ATM kinase inhibition on cell survival through further biological experiments. Intermediate and temporal modelling outcomes revealed the distinct signaling profile associated with ATM kinase activity and inhibition and explained the underlying signalling mechanism for dual ATM functionality in cytotoxic and cytoprotective pathways

Early Cretaceous biogeographic and oceanographic synthesis of Leg 123 (off Northwestern Australia)

Biogeographic observations made by Leg 123 shipboard paleontologists for Lower Cretaceous nannofossils, foraminifers, radiolarians, belemnites, and inoceramids are combined in this chapter to evaluate the paleoceanographic history of the northwestern Australian margin and adjacent basins. Each fossil group is characterized at specific intervals of Cretaceous time and compared with data from Tethyan and Southern Hemisphere high-latitude localities. Special attention is given to the biogeographic observations made for the Falkland Plateau (DSDP Legs 36 and 71) and the Weddell Sea (ODP Leg 113). Both areas have yielded valuable Lower Cretaceous fossil records of the circumantarctic high latitudes. In general, the Neocomian fossil record from DSDP and ODP sites off northwestern Australia has important southern high-latitude affinities and weak Tethyan influence. The same is true for the pelagic lithofacies: radiolarian chert and/or nannofossil limestone, dominant in the Tethyan Lower Cretaceous, are minor lithologies in the Exmouth-Argo sites. These observations, together with the young age of the Argo crust and plate tectonic considerations, suggest that the Argo Basin was not part of the Tethys Realm. The biogeography of the Neocomian radiolarian and nannofossil assemblages suggests opening of a seaway during the Berriasian that connected the circumantarctic area with the Argo Basin, which resulted in the influx of southern high-latitude waters. This conclusion constrains the initial fit and break-up history of Gondwana. Our results favor the loose fit of the western Australian margin with southeast India by Ricou et al. (1990), which accounts for a deeper water connection with the Weddell-Mozambique basins via drowned marginal plateaus as early as the Berriasian. In fits of the du Toit-type (1937), India would remain attached to Antarctica, at least until the late Valanginian, making such a connection impossible. After the Barremian, increasing Tethyan influence is evident in all fossil groups, although southern high-latitude taxa are still present. Biogeographic domains, such as the southern extension of Nannoconus and Ticinella suggest paleolatitudes of about 50°S for the Exmouth-Argo area. Alternatively, if paleolatitudes of about 35° are accepted, these biogeographic limits were displaced northward at least 15° along Australia in comparison to the southern Atlantic. In this case, the proto-circumantarctic current was deflected northward into an eastern boundary current off Australia and carried circumantarctic cold water into the middle latitudes. Late Aptian/early Albian time is characterized by mixing of Tethyan and southern faunal elements and a significant gradient in Albian surface-water temperatures over 10° latitude along the Australian margin, as indicated by planktonic foraminifers. Both phenomena may be indicative of convergence of temperate and antarctic waters near the Australian margin. High fertility conditions, reflected by radiolarian cherts, are suggestive of coastal upwelling during that time

Matrix operations for the simulation and immediate reverse-engineering of time series data

We present a new method for constructing and decomposing square matrices. This method, based on the computed parameterisation of their implied determinants and minors, operates on the product of factors of a new form of matrix decomposition. This method may be employed to build new matrices with fixed determinant(s). We demonstrate that this new approach is fundamentally well-connected to the Cholesky decomposition if applied on symmetric matrices. We also demonstrate that it is related to the LU decomposition method via a diagonal matrix multiplier. Also through this new method a direct relation between Cholesky decomposition and LU factorisation is shown. This method, presented for the first time, is useful for (re)constructing matrices with a predefined determinant and simulating inverse problems. The inference method introduced here also is based on new matrix manipulation techniques that we have developed for the identification of systems from reproducible time series data

A fifty year record of winter glacier melt events in southern Chile, 38°–42°S

Little is known about the frequency and potential mass balance impact of winter glacier melt events. In this study, daily atmospheric temperature soundings from the Puerto Montt radiosonde (41.43°S) are used to reconstruct winter melting events at the glacier equilibrium line altitude in the 38°–42°S region of southern Chile, between 1960 and 2010. The representativeness of the radiosonde temperatures to near-surface glacier temperatures is demonstrated using meteorological records from close to the equilibrium line on two glaciers in the region over five winters. Using a degree-day model we estimate an average of 0.28 m of melt and 21 melt days in the 15 June–15 September period each year, with high inter-annual variability. The majority of melt events are associated with midlatitude migratory high pressure systems crossing Chile and northwesterly flows, that force adiabatic compression and warm advection, respectively. There are no trends in the frequency or magnitude of melt events over the period of record, but the annual frequency of winter melt days shows a significant, although rather weak and probably non-linear, relationship to late winter and early spring values of a multivariate El Niño Southern Oscillation Index (MEI)

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan