National Academies of Sciences, Engineering, and Medicine

During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks, and KDDCUP'99 is the mostly widely used data set for the evaluation of these systems. Having conducted a statistical analysis on this data set, we found two important issues which highly affects the performance of evaluated systems, and results in a very poor evaluation of anomaly detection approaches. To solve these issues, we have proposed a new data set, NSL-KDD, which consists of selected records of the complete KDD data set and does not suffer from any of mentioned shortcomings.

The Swift mission, scheduled for launch in 2004, is a multiwavelength observatory for gamma-ray burst (GRB) astronomy. It is a first-of-its-kind autonomous rapid-slewing satellite for transient astronomy and pioneers the way for future rapid-reaction and multiwavelength missions. It will be far more powerful than any previous GRB mission, observing more than 100 bursts yr-1 and performing detailed X-ray and UV/optical afterglow observations spanning timescales from 1 minute to several days after the burst. The objectives are to (1) determine the origin of GRBs, (2) classify GRBs and search for new types, (3) study the interaction of the ultrarelativistic outflows of GRBs with their surrounding medium, and (4) use GRBs to study the early universe out to z > 10. The mission is being developed by a NASA-led international collaboration. It will carry three instruments: a new-generation wide-field gamma-ray (15-150 keV) detector that will detect bursts, calculate 1'-4' positions, and trigger autonomous spacecraft slews; a narrow-field X-ray telescope that will give 5'' positions and perform spectroscopy in the 0.2-10 keV band; and a narrow-field UV/optical telescope that will operate in the 170-600 nm band and provide 0farcs3 positions and optical finding charts. Redshift determinations will be made for most bursts. In addition to the primary GRB science, the mission will perform a hard X-ray survey to a sensitivity of ~1 mcrab (~2 × 10-11 ergs cm-2 s-1 in the 15-150 keV band), more than an order of magnitude better than HEAO 1 A-4. A flexible data and operations system will allow rapid follow-up observations of all types of high-energy transients, with rapid data downlink and uplink available through the NASA TDRSS system. Swift transient data will be rapidly distributed to the astronomical community, and all interested observers are encouraged to participate in follow-up measurements. A Guest Investigator program for the mission will provide funding for community involvement. Innovations from the Swift program applicable to the future include (1) a large-area gamma-ray detector using the new CdZnTe detectors, (2) an autonomous rapid-slewing spacecraft, (3) a multiwavelength payload combining optical, X-ray, and gamma-ray instruments, (4) an observing program coordinated with other ground-based and space-based observatories, and (5) immediate multiwavelength data flow to the community. The mission is currently funded for 2 yr of operations, and the spacecraft will have a lifetime to orbital decay of ~8 yr.

This paper reports the genome sequence of domesticated tomato, a major crop plant, and a draft sequence for its closest wild relative; comparative genomics reveal very little divergence between the two genomes but some important differences with the potato genome, another important food crop in the genus Solanum. Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera1 and includes annual and perennial plants from diverse habitats. Here we present a high-quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, Solanum pimpinellifolium2, and compare them to each other and to the potato genome (Solanum tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show more than 8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness.

Abstract Technical aspects of the constant pressure molecular dynamics (MD) method proposed by Andersen and extended by Parrinello and Rahman to allow changes in the shape of the MD cell are discussed. The new MD method is extended to treat molecular systems and to include long range charge-charge interactions. Results on the conservation laws, the frequency of oscillation of the MD cell, and the equations which constrain the shape of the MD cell are also given. An additional constraint is introduced to stop the superfluous MD cell rotation which would otherwise complicate the analysis of crystal structures. The method is illustrated by examining the behaviour of solid nitrogen at high pressure. Issued as N.R.C.C. No. 22766. Issued as N.R.C.C. No. 22766. Notes Issued as N.R.C.C. No. 22766.

Abstract. We provide a framework for the analysis of a large class of discontinuous methods for second-order elliptic problems. It allows for the understanding and comparison of most of the discontinuous Galerkin methods that have been proposed over the past three decades for the numerical treatment of elliptic problems.

This paper reviews recent progress made in identifying electrocatalysts for carbon dioxide (CO2) reduction to produce low-carbon fuels, including CO, HCOOH/HCOO(-), CH2O, CH4, H2C2O4/HC2O4(-), C2H4, CH3OH, CH3CH2OH and others. The electrocatalysts are classified into several categories, including metals, metal alloys, metal oxides, metal complexes, polymers/clusters, enzymes and organic molecules. The catalyts' activity, product selectivity, Faradaic efficiency, catalytic stability and reduction mechanisms during CO2 electroreduction have received detailed treatment. In particular, we review the effects of electrode potential, solution-electrolyte type and composition, temperature, pressure, and other conditions on these catalyst properties. The challenges in achieving highly active and stable CO2 reduction electrocatalysts are analyzed, and several research directions for practical applications are proposed, with the aim of mitigating performance degradation, overcoming additional challenges, and facilitating research and development in this area.

In a seminal paper, Garrett Hardin argued in 1968 that users of a commons are caught in an inevitable process that leads to the destruction of the resources on which they depend. This article discusses new insights about such problems and the conditions most likely to favor sustainable uses of common-pool resources. Some of the most difficult challenges concern the management of large-scale resources that depend on international cooperation, such as fresh water in international basins or large marine ecosystems. Institutional diversity may be as important as biological diversity for our long-term survival.

In this work we present SENTIWORDNET 3.0, a lexical resource explicitly devised for supporting sentiment classification and opinion mining applications. SENTIWORDNET 3.0 is an improved version of SENTIWORDNET 1.0, a lexical resource publicly available for research purposes, now currently licensed to more than 300 research groups and used in a variety of research projects worldwide. Both SENTIWORDNET 1.0 and 3.0 are the result of automatically annotating all WORDNET synsets according to their degrees of positivity, negativity, and neutrality. SENTIWORDNET 1.0 and 3.0 differ (a) in the versions of WORDNET which they annotate (WORDNET 2.0 and 3.0, respectively), (b) in the algorithm used for automatically annotating WORDNET, which now includes (additionally to the previous semi-supervised learning step) a random-walk step for refining the scores. We here discuss SENTIWORDNET 3.0, especially focussing on the improvements concerning aspect (b) that it embodies with respect to version 1.0. We also report the results of evaluating SENTIWORDNET 3.0 against a fragment of WORDNET 3.0 manually annotated for positivity, negativity, and neutrality; these results indicate accuracy improvements of about 20 % with respect to SENTIWORDNET 1.0. 1.

Pathogen detection has become a major research area all over the world for water quality surveillance and microbial risk assessment. Therefore, designing simple and sensitive detection kits plays a key role in envisaging and evaluating the risk of disease outbreaks and providing quality healthcare settings. Herein, we have designed a facile and low-cost colorimetric sensing strategy for the selective and sensitive determination of β-galactosidase producing pathogens. The hexagonal boron nitride quantum dots (h-BN QDs) were established as a nanozyme that showed prominent peroxidase-like activity, which catalyzes 3,3',5,5'-tetramethylbenzidine (TMB) oxidation by H₂O₂. The h-BN QDs were embedded on a layer-by-layer assembled agarose biopolymer. The β-galactosidase enzyme partially degrades β-1,4 glycosidic bonds of agarose polymer, resulting in accessibility of h-BN QDs on the solid surface. This assay can be conveniently conducted and analyzed by monitoring the blue color formation due to TMB oxidation within 30 min. The nanocomposite was stable for more than 90 days and was showing TMB oxidation after incubating it with <i>Escherichia coli</i> (<i>E. coli</i>). The limit of detection was calculated to be 1.8 × 10⁶ and 1.5 × 10⁶ CFU/mL for <i>E. coli</i> and <i>Klebsiella pneumonia</i> (<i>K. pneumonia</i>), respectively. Furthermore, this novel sensing approach is an attractive platform that was successfully applied to detect <i>E. coli</i> in spiked water samples and other food products with good accuracy, indicating its practical applicability for the detection of pathogens in real samples.

This article describes and presents initial empirical tests of a theory that links values, beliefs, attitudes, and behavior within a preference construction framework that emphasizes the activation of personal environmental norms. Environmental concern is related to egoistic, social‐altruistic, and biospheric value orientations and also to beliefs about the consequences of environmental changes for valued objects. Two studies generally support the hypothesized relationships and demonstrate links to the broader theory of values. However, the biospheric value orientation postulated in the theoretical literature on environmentalism does not differentiate from social‐altruism in a general population sample. Results are discussed in terms of value change, the role of social structural factors (including gender) in environmentalism, theories of risk perception, and the mobilization strategies of social movements, including environmental justice movements.

A social-psychological model is developed to examine the proposition that environmentalism represents a new way of thinking. It presumes that action in support of environmental quality may derive from any of three value orientations: egoistic, social-altruistic, or biospheric, and that gender may be implicated in the relation between these orientations and behavior. Behavioral intentions are modeled as the sum across values of the strength of a value times the strength of beliefs about the consequences of environmental conditions for valued objects. Evidence from a survey of 349 college students shows that beliefs about consequences for each type of valued object independently predict willingness to take political action, but only beliefs about consequences for self reliably predict willingness to pay through taxes. This result is consistent with other recent findings from contingent valuation surveys. Women have stronger beliefs than men about consequences for self, others, and the biosphere, but there is no gender difference in the strength of value orientations.

We have identified a new protein fold--the alpha/beta hydrolase fold--that is common to several hydrolytic enzymes of widely differing phylogenetic origin and catalytic function. The core of each enzyme is similar: an alpha/beta sheet, not barrel, of eight beta-sheets connected by alpha-helices. These enzymes have diverged from a common ancestor so as to preserve the arrangement of the catalytic residues, not the binding site. They all have a catalytic triad, the elements of which are borne on loops which are the best-conserved structural features in the fold. Only the histidine in the nucleophile-histidine-acid catalytic triad is completely conserved, with the nucleophile and acid loops accommodating more than one type of amino acid. The unique topological and sequence arrangement of the triad residues produces a catalytic triad which is, in a sense, a mirror-image of the serine protease catalytic triad. There are now four groups of enzymes which contain catalytic triads and which are related by convergent evolution towards a stable, useful active site: the eukaryotic serine proteases, the cysteine proteases, subtilisins and the alpha/beta hydrolase fold enzymes.

Studies on monocyte and macrophage biology and differentiation have revealed the pleiotropic activities of these cells. Macrophages are tissue sentinels that maintain tissue integrity by eliminating/repairing damaged cells and matrices. In this M2-like mode, they can also promote tumor growth. Conversely, M1-like macrophages are key effector cells for the elimination of pathogens, virally infected, and cancer cells. Macrophage differentiation from monocytes occurs in the tissue in concomitance with the acquisition of a functional phenotype that depends on microenvironmental signals, thereby accounting for the many and apparently opposed macrophage functions. Many questions arise. When monocytes differentiate into macrophages in a tissue (concomitantly adopting a specific functional program, M1 or M2), do they all die during the inflammatory reaction, or do some of them survive? Do those that survive become quiescent tissue macrophages, able to react as naïve cells to a new challenge? Or, do monocyte-derived tissue macrophages conserve a "memory" of their past inflammatory activation? This review will address some of these important questions under the general framework of the role of monocytes and macrophages in the initiation, development, resolution, and chronicization of inflammation.

The paper presents MeshLab, an open source, extensible, mesh processing system that has been developed at the Visual Computing Lab of the ISTI-CNR with the helps of tens of students. We will describe the MeshLab architecture, its main features and design objectives discussing what strategies have been used to support its development. Various examples of the practical uses of MeshLab in research and professional frameworks are reported to show the various capabilities of the presented system.

Missing data in clinical trials can have a major effect on the validity of the inferences that can be drawn from the trial. This article reviews methods for preventing missing data and, failing that, dealing with data that are missing.

With the approaching commercialization of PEM fuel cell technology, developing active, inexpensive non-precious metal ORR catalyst materials to replace currently used Pt-based catalysts is a necessary and essential requirement in order to reduce the overall system cost. This review paper highlights the progress made over the past 40 years with a detailed discussion of recent works in the area of non-precious metal electrocatalysts for oxygen reduction reaction, a necessary reaction at the PEM fuel cell cathode. Several important kinds of unsupported or carbon supported non-precious metal electrocatalysts for ORR are reviewed, including non-pyrolyzed and pyrolyzed transition metal nitrogen-containing complexes, conductive polymer-based catalysts, transition metal chalcogenides, metal oxides/carbides/nitrides/oxynitrides/carbonitrides, and enzymatic compounds. Among these candidates, pyrolyzed transition metal nitrogen-containing complexes supported on carbon materials (M–Nx/C) are considered the most promising ORR catalysts because they have demonstrated some ORR activity and stability close to that of commercially available Pt/C catalysts. Although great progress has been achieved in this area of research and development, there are still some challenges in both their ORR activity and stability. Regarding the ORR activity, the actual volumetric activity of the most active non-precious metal catalyst is still well below the DOE 2015 target. Regarding the ORR stability, stability tests are generally run at low current densities or low power levels, and the lifetime is far shorter than targets set by DOE. Therefore, improving both the ORR activity and stability are the major short and long term focuses of non-precious metal catalyst research and development. Based on the results achieved in this area, several future research directions are also proposed and discussed in this paper.

An ordered draft sequence of the 17-gigabase hexaploid bread wheat (Triticum aestivum) genome has been produced by sequencing isolated chromosome arms. We have annotated 124,201 gene loci distributed nearly evenly across the homeologous chromosomes and subgenomes. Comparative gene analysis of wheat subgenomes and extant diploid and tetraploid wheat relatives showed that high sequence similarity and structural conservation are retained, with limited gene loss, after polyploidization. However, across the genomes there was evidence of dynamic gene gain, loss, and duplication since the divergence of the wheat lineages. A high degree of transcriptional autonomy and no global dominance was found for the subgenomes. These insights into the genome biology of a polyploid crop provide a springboard for faster gene isolation, rapid genetic marker development, and precise breeding to meet the needs of increasing food demand worldwide.

[1] We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5° × 0.5° spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 ± 7 J × 1018 yr−1), H (164 ± 15 J × 1018 yr−1), and GPP (119 ± 6 Pg C yr−1) were similar to independent estimates. Our global TER estimate (96 ± 6 Pg C yr−1) was likely underestimated by 5–10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.

Most climate change policy attention has been addressed to long-term options, such as inducing new, low-carbon energy technologies and creating cap-and-trade regimes for emissions. We use a behavioral approach to examine the reasonably achievable potential for near-term reductions by altered adoption and use of available technologies in US homes and nonbusiness travel. We estimate the plasticity of 17 household action types in 5 behaviorally distinct categories by use of data on the most effective documented interventions that do not involve new regulatory measures. These interventions vary by type of action and typically combine several policy tools and strong social marketing. National implementation could save an estimated 123 million metric tons of carbon per year in year 10, which is 20% of household direct emissions or 7.4% of US national emissions, with little or no reduction in household well-being. The potential of household action deserves increased policy attention. Future analyses of this potential should incorporate behavioral as well as economic and engineering elements.

This paper describes BEAM, a general purpose Monte Carlo code to simulate the radiation beams from radiotherapy units including high-energy electron and photon beams, 60Co beams and orthovoltage units. The code handles a variety of elementary geometric entities which the user puts together as needed (jaws, applicators, stacked cones, mirrors, etc.), thus allowing simulation of a wide variety of accelerators. The code is not restricted to cylindrical symmetry. It incorporates a variety of powerful variance reduction techniques such as range rejection, bremsstrahlung splitting and forcing photon interactions. The code allows direct calculation of charge in the monitor ion chamber. It has the capability of keeping track of each particle's history and using this information to score separate dose components (e.g., to determine the dose from electrons scattering off the applicator). The paper presents a variety of calculated results to demonstrate the code's capabilities. The calculated dose distributions in a water phantom irradiated by electron beams from the NRC 35 MeV research accelerator, a Varian Clinac 2100C, a Philips SL75-20, an AECL Therac 20 and a Scanditronix MM50 are all shown to be in good agreement with measurements at the 2 to 3% level. Eighteen electron spectra from four different commercial accelerators are presented and various aspects of the electron beams from a Clinac 2100C are discussed. Timing requirements and selection of parameters for the Monte Carlo calculations are discussed.