1,356 research outputs found
The development of generic definitions of hyperslice packages in Hyper/J
AbstractIn this paper we investigate the notion of reusability of aspect definitions. We discuss the development of generic aspects in Hyper/J and compare it with the AspectJ approach. In doing that, we follow the design principle of “developing with hyperslice packages” and we show that hyperspace structure, concern mapping, hyperslice definitions and merging stategies exhibit well-defined patterns. An approach to constructing and merging generic aspects with base core concerns in Hyper/J is presented
Prediction of water table in an alluvial aquifer using modflow
Groundwater is the main source of water in the Kingdom of Saudi Arabia (KSA). A larger part of groundwater is founded in alluvial (unconfined) aquifers. Prediction of water table elevations in unconfined aquifers is very useful in water resources planning and management. During the last two decades, many aquifers in different regions of the KSA experienced significant groundwater decline. The declines in these aquifers raised concerns over the quantity and quality of groundwater, as well as concerns over the planning and management policies used in KSA. The main objective of this study was to predict water table fluctuations and to estimate the annual change in water table at an alluvial aquifer at wadi Hada Al Sham near Makkah, KSA. The methodology was achieved using numerical groundwater model (MODFLOW). The model was calibrated and then used to predict water table elevations due to pumping for a period of 5 years. The output of the model was found to be in agreement with the previous records. Moreover, the simulation results also show reasonable declination of water table elevations in the study area during the study period
ASAP-SML: An Antibody Sequence Analysis Pipeline Using Statistical Testing and Machine Learning
Antibodies are capable of potently and specifically binding individual
antigens and, in some cases, disrupting their functions. The key challenge in
generating antibody-based inhibitors is the lack of fundamental information
relating sequences of antibodies to their unique properties as inhibitors. We
develop a pipeline, Antibody Sequence Analysis Pipeline using Statistical
testing and Machine Learning (ASAP-SML), to identify features that distinguish
one set of antibody sequences from antibody sequences in a reference set. The
pipeline extracts feature fingerprints from sequences. The fingerprints
represent germline, CDR canonical structure, isoelectric point and frequent
positional motifs. Machine learning and statistical significance testing
techniques are applied to antibody sequences and extracted feature fingerprints
to identify distinguishing feature values and combinations thereof. To
demonstrate how it works, we applied the pipeline on sets of antibody sequences
known to bind or inhibit the activities of matrix metalloproteinases (MMPs), a
family of zinc-dependent enzymes that promote cancer progression and undesired
inflammation under pathological conditions, against reference datasets that do
not bind or inhibit MMPs. ASAP-SML identifies features and combinations of
feature values found in the MMP-targeting sets that are distinct from those in
the reference sets
Making Free Trade Fair
Philosophers have done very little work on what makes trade fair. Perhaps the most extensive discussion is Malgorzata Kurjanska and Mathias Risse’s article, “Fairness in Trade II: export subsidies and the fair trade movement.”2 In their article, Kurjanska and Risse consider the case for trade subsidies and the Fair Trade movement. They suggest that it is not permissible for developed countries to give their producers subsidies because doing so does not strike an appropriate balance between meeting the needs of the global poor and protecting domestic workers (Kurjanska and Risse, 2008: 34). Kurjanska and Risse also argue that the case for Fair Trade hinges, primarily, on whether or not it is part of the best development strategy for poor countries. They do not think Fair Trade is part of the best development strategy and, so, they believe purchasing Fair Trade certified goods is only acceptable because doing so does not constitute a large share of the market in traded goods. This chapter argues that the case against subsidies and Fair Trade Kurjanska and Risse present is much weaker than they make out. To the contrary, it argues that giving some subsidies and purchasing some Fair Trade certified goods may even be necessary to make trade fair. Section 11.2 starts by saying a few words about the normative framework Kurjanska and Risse adopt
Thermodynamic Forecasts of the Mediterranean Sea Acidification
Anthropogenic CO2 is a major driver of the present ocean acidification. This latter is threatening the marine ecosystems and has been identified as a major environmental and economic menace. This study aims to forecast from the thermodynamic equations, the acidification variation (ΔpH) of the Mediterranean waters over the next few decades and beyond this century. In order to do so, we calculated and fitted the theoretical values based upon the initial conditions from data of the 2013 MedSeA cruise. These estimates have been performed both for the Western and for the Eastern basins based upon their respective physical (temperature and salinity) and chemical (total alkalinity and total inorganic carbon) properties. The results allow us to point out four tipping points, including one when the Mediterranean Sea waters would become acid (pH<7). In order to provide an associated time scale to the theoretical results, we used two of the IPCC (2007) atmospheric CO2 scenarios. Under the most optimistic scenario of the “Special Report: Emissions Scenarios” (SRES) of the IPCC (2007), the results indicate that in 2100, pH may decrease down to 0.245 in the Western basin and down to 0.242 in the Eastern basin (compared to the pre-industrial pH). Whereas for the most pessimistic SRES scenario of the IPCC (2007), the results for the year 2100, forecast a pH decrease down to 0.462 and 0.457, for the Western and for the Eastern basins, respectively. Acidification, which increased unprecedentedly in recent years, will rise almost similarly in both Mediterranean basins only well after the end of this century. These results further confirm that both basins may become undersaturated (< 1) with respect to calcite and aragonite (at the base of the mixed layer depth), only in the far future (in a few centuries)
Therapeutic distant organ effects of regional hypothermia during mesenteric ischemia-reperfusion injury
IntroductionMesenteric ischemia-reperfusion injury (IRI) leads to systemic inflammation and multiple organ failure in clinical and laboratory settings. We investigated the lung structural, functional, and genomic response to mesenteric IRI with and without regional intraischemic hypothermia (RIH) in rodents and hypothesized that RIH would protect the lung and preferentially modulate the distant organ transcriptome under these conditions.MethodsSprague-Dawley rats underwent sham laparotomy or superior mesenteric artery occlusion (SMAO) for 60 minutes with or without RIH. Gut temperature was maintained at 15°-20°C during SMAO, and systemic normothermia (37°C) was maintained throughout the study period. At 6 or 24 hours, lung tissue was collected for (1) histology, (2) myeloperoxidase activity, (3) bronchoalveolar lavage (BAL) fluid protein concentrations, (4) lung wet/dry ratios, and (5) total RNA isolation and hybridization to Illumina's Sentrix BeadChips (>22,000 probes) for gene expression profiling. Significantly affected genes (false discovery rate <5% and fold change ≥1.5) were linked to gene ontology (GO) terms using MAPPFinder, and hypothermia-suppressed genes were further analyzed with Pubmatrix.ResultsMesenteric IRI-induced lung injury, as evidenced by leukocyte trafficking, alveolar hemorrhage, and increased BAL protein and wet/dry ratios, and activated a proinflammatory lung transcriptome compared with sham. In contrast, rats treated with RIH exhibited lung histology, BAL protein, and wet/dry ratios similar to sham. At 6 hours, GO analysis identified 232 hypothermia-suppressed genes related to inflammation, innate immune response, and cell adhesion, and 33 hypothermia-activated genes related to lipid and amine metabolism and defense response. Quantitative real-time polymerase chain reaction validated select array changes in top hypothermia-suppressed genes lipocalin-2 (lcn-2) and chemokine ligand 1 (CXCL-1), prominent genes associated with neutrophil activation and trafficking.ConclusionsTherapeutic hypothermia during SMAO provides distant organ protection and preferentially modulates the IRI-activated transcriptome in the rat lung. This study identifies potential novel diagnostic and therapeutic targets of mesenteric IRI and provides a platform for further mechanistic study of hypothermic protection at the cellular and subcellular level.Clinical RelevanceVisceral organ ischemia-reperfusion injury (IRI) is a common clinical problem in the settings of shock, sepsis, vascular surgery, and organ transplantation and is a particularly vexing problem in the repair of complex aortic aneurysms. IRI is associated with considerable patient morbidity and mortality, for which there are virtually no therapeutic options. It systematically causes local organ injury and dysfunction, systemic inflammation, and multiple organ failure. Clinical trials investigating the efficacy of pharmacologic blockade of individual downstream inflammatory mediators in critically ill patients have been largely unsuccessful, and such studies highlight the need for novel top-down approaches, such as gene expression profiling for biologic discovery, as well as application of broader therapeutic interventions, such as targeted hypothermia. In this study, we demonstrate the potential application of visceral cooling for distant organ protection during mesenteric IRI, identify broad changes in lung gene expression under these conditions, and have elucidated potential novel diagnostic and therapeutic targets for disease targeting
Climatological variations of total alkalinity and total dissolved inorganic carbon in the Mediterranean Sea surface waters
Abstract. A compilation of data from several cruises between 1998 and 2013 was used to derive polynomial fits that estimate total alkalinity (AT) and total dissolved inorganic carbon (CT) from measurements of salinity and temperature in the Mediterranean Sea surface waters. The optimal equations were chosen based on the 10-fold cross-validation results and revealed that second- and third-order polynomials fit the AT and CT data respectively. The AT surface fit yielded a root mean square error (RMSE) of ± 10.6 μmol kg−1, and salinity and temperature contribute to 96 % of the variability. Furthermore, we present the first annual mean CT parameterization for the Mediterranean Sea surface waters with a RMSE of ± 14.3 μmol kg−1. Excluding the marginal seas of the Adriatic and the Aegean, these equations can be used to estimate AT and CT in case of the lack of measurements. The identified empirical equations were applied on the 0.25° climatologies of temperature and salinity, available from the World Ocean Atlas 2013. The 7-year averages (2005–2012) showed that AT and CT have similar patterns with an increasing eastward gradient. The variability is influenced by the inflow of cold Atlantic waters through the Strait of Gibraltar and by the oligotrophic and thermohaline gradient that characterize the Mediterranean Sea. The summer–winter seasonality was also mapped and showed different patterns for AT and CT. During the winter, the AT and CT concentrations were higher in the western than in the eastern basin. The opposite was observed in the summer where the eastern basin was marked by higher AT and CT concentrations than in winter. The strong evaporation that takes place in this season along with the ultra-oligotrophy of the eastern basin determines the increase of both AT and CT concentrations
View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation
The primate brain contains a hierarchy of visual areas, dubbed the ventral
stream, which rapidly computes object representations that are both specific
for object identity and relatively robust against identity-preserving
transformations like depth-rotations. Current computational models of object
recognition, including recent deep learning networks, generate these properties
through a hierarchy of alternating selectivity-increasing filtering and
tolerance-increasing pooling operations, similar to simple-complex cells
operations. While simulations of these models recapitulate the ventral stream's
progression from early view-specific to late view-tolerant representations,
they fail to generate the most salient property of the intermediate
representation for faces found in the brain: mirror-symmetric tuning of the
neural population to head orientation. Here we prove that a class of
hierarchical architectures and a broad set of biologically plausible learning
rules can provide approximate invariance at the top level of the network. While
most of the learning rules do not yield mirror-symmetry in the mid-level
representations, we characterize a specific biologically-plausible Hebb-type
learning rule that is guaranteed to generate mirror-symmetric tuning to faces
tuning at intermediate levels of the architecture
Current status and future perspectives of lithium metal batteries
With the lithium-ion technology approaching its intrinsic limit with graphite-based anodes, Li metal is recently receiving renewed interest from the battery community as potential high capacity anode for next-generation rechargeable batteries. In this focus paper, we review the main advances in this field since the first attempts in the mid-1970s. Strategies for enabling reversible cycling and avoiding dendrite growth are thoroughly discussed, including specific applications in all-solid-state (inorganic and polymeric), Lithium–Sulfur (Li–S) and Lithium-O2 (air) batteries. A particular attention is paid to recent developments of these battery technologies and their current state with respect to the 2030 targets of the EU Integrated Strategic Energy Technology Plan (SET-Plan) Action 7
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