Two studies were conducted to explore the use of complex data in character description and hybrid identification. In order to determine if complex data allow the production of better characters, eight groups of plant systematists were given two classes of drawings of plant parts, and asked to divide them into character states (clusters) in two separate experiments. The first class of drawings consisted only of cotyledons. The second class consisted of triplets of drawings: a cotyledon, seedling leaf, and inflorescence bract. The triplets were used to simulate complex data such as might be garnered by looking at a plant. Each experiment resulted in four characters (groups of clusters), one for each group of systematists. Visual and statistical analysis of the data showed that the systematists were able to produce smaller, more precisely defined character states using the more complex drawings. The character states created with the complex drawings also were more consistent across systematists, and agreed more closely with an independent assessment of phylogeny. To investigate the utility of complex data in an applied task, four observers rated 250 hybrids of Dubautia ciliolata X arborea based on the overall form (Gestalt) of the plants, and took measurements of a number of features of the same plants. A composite score of the measurements was created using principal components analysis. The correlation between the scores on the first principal component and the Gestalt ratings was computed. The Gestalt ratings and PC scores were significantly correlated, demonstrating that assessments of overall similarity can be as useful as more conventional approaches in determining the hybrid status of plants.

According to the 2024 Stack Overflow Developer Survey, nearly one in three developers reported that artificial intelligence (AI) was good at handling complex tasks in the development workflow. While only three percent of developers reported that AI was performing very well at handling complex tasks. In contrast, 12 percent of developers reported that AI was very poor at handling complex tasks.

A collection of data serving as documentation of Stillwater National Wildlife Refuge Complex priority resources of concern.

The Complex Event Processing (CEP) Software Market Report is Segmented by Type (Services, Software), Type of User (Small and Medium Enterprise, Large Enterprise), End-User Vertical (BFSI, Retail, Government and Defense, Healthcare), and Geography (North America, Europe, Asia-Pacific, Latin America, Middle East, and Africa). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

These reports are provided as a historic archive only and are not current. If you have an ongoing requirement to use the statistics, to meet a legislative or policy requirement, please seek advice from the relevant WA Government Department or Authority rather than contacting the Data Custodians listed under Key Information. If you use the reports, please include a caveat stating the following: (1) year of currency, (2) a statement that the statistics presented may now be out of date, and (3) the report citation. Overview of the Report From 2016 to 2018, DBCA provided annual updates of statistics on the pre-European and current extent of the vegetation complexes of the south-west of Western Australia and are based on more detailed vegetation complex mapping than the Statewide vegetation association mapping. The statistics were used for several purposes including conservation planning, land use planning and when assessing development applications. The statistics provided a general overview of the status of vegetation complexes, noting the limitations detailed in the README document relating to scale, remnant vegetation mapping and currency of the analysis. They were intended to be used in conjunction with other information on the biodiversity values of an area and with input and advice from people familiar with the vegetation complex and the vegetation condition of an area of interest. For the Swan Coastal Plain and South-West Forests regions, three reports are included: CAR Report - provides information on the progress towards achieving a conservation reserve system that is comprehensive, adequate, and representative (CAR Reserve Analysis); Region Scheme Report – provides supporting statistics regarding EPA policies for Region Scheme areas; LGA Report – summary statistics for each LGA. A CAR system of reserves helps conserve our biodiversity. Please contact DBCA for advice on the CAR statistics.

In performance maintenance in large, complex systems, sensor information from sub-components tends to be readily available, and can be used to make predictions about the system's health and diagnose possible anomalies.

However, existing methods can only use predictions of individual component anomalies to guess at systemic problems, not accurately estimate the magnitude of the problem, nor prescribe good solutions.

Since physical complex systems usually have well-defined semantics of operation, we here propose using anomaly detection techniques drawn from data mining in conjunction with an automated theorem prover working on a domain-specific knowledge base to perform systemic anomalydetection on complex systems.

For clarity of presentation, the remaining content of this submission is presented compactly in Fig 1.

The JSA_SLC_1P product is comparable to the ESA SLC/IMS images generated for Envisat ASAR and ERS SAR instruments. It is a slant-range projected complex image in zero-Doppler SAR coordinates. The data is sampled in natural units of time in range and along track, with the range pixel spacing corresponding to the reciprocal of the platform ADC rate and the along track spacing to the reciprocal of the PRF. Data is processed to an unweighted Doppler bandwidth of 1000Hz, without sidelobe reduction. The product is suitable for interferometric, calibration and quality analysis applications. Data acquired by ESA ground stations. Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service.

The Complex Fertilizers Market estimated size and share is projected to exceed USD 67.07 billion by 2034, with a forecasted CAGR of 5.7% during the period.

There were approximately 45.3 thousand employees in the arcade, food and entertainment complex sector in the United States in 2022, up from the previous year's total of 86.85 thousand employees. Employment in this sector peaked in 2021.

The global prothrombin complex concentrates market is expected to be valued at US$ 772.0 million in 2023 and reach a valuation of US$ 1.2 billion by 2033. The demand for prothrombin complex concentrates is estimated to record a steady CAGR of 4.1%, with the United Kingdom, the United States., China, and India emerging as key producers.

A dataset listing all subway and Staten Island Railway stations, with data aggregated by station complex. This dataset includes information on station names, their locations, Station IDs, Complex IDs, GTFS Stop IDs, the services that stop there, the type of structure the station is on or in, whether they are in Manhattan’s Central Business District (CBD), and their ADA-accessibility status.

Proteomics is a data-rich science with complex experimental designs and an intricate measurement process. To obtain insights from the large data sets produced, statistical methods, including machine learning, are routinely applied. For a quantity of interest, many of these approaches only produce a point estimate, such as a mean, leaving little room for more nuanced interpretations. By contrast, Bayesian statistics allows quantification of uncertainty through the use of probability distributions. These probability distributions enable scientists to ask complex questions of their proteomics data. Bayesian statistics also offers a modular framework for data analysis by making dependencies between data and parameters explicit. Hence, specifying complex hierarchies of parameter dependencies is straightforward in the Bayesian framework. This allows us to use a statistical methodology which equals, rather than neglects, the sophistication of experimental design and instrumentation present in proteomics. Here, we review Bayesian methods applied to proteomics, demonstrating their potential power, alongside the challenges posed by adopting this new statistical framework. To illustrate our review, we give a walk-through of the development of a Bayesian model for dynamic organic orthogonal phase-separation (OOPS) data.

The East Asian double or complex silicates market fell to $1.2B in 2024, reducing by -7.1% against the previous year. Over the period under review, consumption recorded a pronounced descent. Over the period under review, the market hit record highs at $2.1B in 2019; however, from 2020 to 2024, consumption failed to regain momentum.

The Sudanese double or complex silicates market was finally on the rise to reach $250K in 2024, after two years of decline. Over the period under review, consumption recorded a strong increase. Over the period under review, the market reached the maximum level at $753K in 2018; however, from 2019 to 2024, consumption failed to regain momentum.

COMPLEX NETWORKS IN CLIMATE SCIENCE: PROGRESS, OPPORTUNITIES AND CHALLENGES KARSTEN STEINHAEUSER, NITESH V. CHAWLA, AND AUROOP R. GANGULY Abstract. Networks have been used to describe and model a wide range of complex systems, both natural as well as man-made. One particularly interesting application in the earth sciences is the use of complex networks to represent and study the global climate system. In this paper, we motivate this general approach, explain the basic methodology, report on the state of the art (including our contributions), and outline open questions and opportunities for future research.

In 2024, the global double or complex silicates market increased by 4.2% to $4.3B, rising for the second consecutive year after three years of decline. In general, consumption saw a slight setback. As a result, consumption reached the peak level of $6.9B. From 2014 to 2024, the growth of the global market remained at a lower figure.

The Complex Injectables Market Report is Segmented by Route of Administration (Intramuscular (IM), Intravenous (IV), and Subcutaneous), Formulation (Liposomes, Microspheres, and Other Formulations), Drug Molecule (Leuprolide, Octreotide, Paclitaxel, Pegasparagase, Risperidone, and Others), Application (Cardiovascular, Cancer, Central Nervous System Disorders, Diabetes, Endocrinology, and Other Disorders) and Geography (North America, Europe, Asia Pacific, Middle East and Africa, and South America) the Report Offers the Value (USD) for all the Above Segments.

All evaluation metrics are presented in percentage (%).

Transgenic mice expressing the calcium-sensitive fluorescent indicator GCamp6f were trained in the Accumulating Towers task and two-photon calcium imaging was performed of functionally identified primary and secondary visual cortical areas, as well as retrosplenial cortex. Regions of interest representing putative single neurons were extracted using a semi-customized demixing and deconvolution procedure. Behavioral data were separately collected by a computer that ran a virtual reality control engine, and synchronized with imaging data via a synchronization timestamp sent to the imaging computer at every graphics refresh cycle.

To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.