Sentences with phrase «multiple combinations based»

There are many variations and we recommend multiple combinations based upon the objectives of the organization.

Not exact matches

These products may be sold in combination as a multiple element arrangement or separately on a stand - alone basis.

So I set out to create my own grain medley — a combination of multiple grains that could cook together for a more interesting base to my lunches.

The TruePrime Single - Cell Whole Genome Amplification (WGA) kit uses a revolutionary multiple displacement amplification method based on the combination of the recently discovered DNA primase Thermus thermophilus (Tth) PrimPol and the extremely processive, high - fidelity Phi29 DNA polymerase (Phi29 DNAP) to amplify uniformly total genomic DNA of either a single cell or a few cells.

Based on their results, Lu and her colleagues argue that the best strategy in such cases might be to use drug combinations that target multiple, parallel pathways involved in tumor development and maintenance.

Natural materials have extraordinary mechanical properties, which are based on sophisticated arrangements and combinations of multiple building blocks.

These findings highlight the need to (a) induce multiple neutralizing antibody lineages for a protective antibody - based vaccine and (b) the potential need to use combinations of purified mAb in therapeutic or prophylactic settings.

Based on those previous signals, Somaiah and colleagues conducted a phase II study testing the anti — PDL - 1 agent durvalumab in combination with the anti — CTLA - 4 agent tremelimumab in multiple sarcoma subtypes.

These effects include realistically complex galaxy models based on high - resolution imaging from space; spatially varying, physically - motivated blurring kernel; and combination of multiple different exposures.

The TruePrime ™ Necrotic cell - free / exosomal DNA amplification kit uses a novel multiple displacement amplification method based on the combination of the recently discovered DNA primase TthPrimPol, and the highly processive and high - fidelity Phi29 DNA polymerase, to amplify genomic DNA starting from cell - free DNA * obtained from plasma, serum, urine or any other bodily fluid.

This unique combination of grade - specific content helps students interact and compare across multiple sources and focus on citing evidence for their text - based writing — just like they will need to do to succeed on rigorous, high - stakes assessments.

Knowing the nature of the measures and the combination method in any particular application of multiple measures helps us understand the results and the value of decisions or consequences based on those results.

After meeting extensively with multiple other brokerages, Motley Fool Wealth Management partnered with Interactive Brokers as the custodian and broker for our Personalized Portfolios based on a combination of their low - cost trading fees and their ability to quickly and efficiently execute trades.

Often taking the form of landscapes, the Canadian - born, Newcastle, England - based artist's presentations - containing combinations of real and constructed imagery - are symbolic of the multiple realities we perceive when we engage contemporary media culture.

Canadian Ice Service, 4.7, Multiple Methods As with CIS contributions in June 2009, 2010, and 2011, the 2012 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicbased on observed end - of - winter arctic ice thicknesses and extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicBased (OFB) Model, which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

Canadian Ice Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicbased on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicBased Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

Canadian Ice Service; 5.0; Statistical As with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predicbased on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predicBased (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictors.

Canadian Ice Service, 4.7 (± 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicbased on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicBased Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

«The Earth's climate system is highly nonlinear: inputs and outputs are not proportional, change is often episodic and abrupt, rather than slow and gradual, and multiple equilibria are the norm... there is a relatively poor understanding of the different types of nonlinearities, how they manifest under various conditions, and whether they reflect a climate system driven by astronomical forcings, by internal feedbacks, or by a combination of both... [We] suggest a robust alternative to prediction that is based on using integrated assessments within the framework of vulnerability studies... It is imperative that the Earth's climate system research community embraces this nonlinear paradigm if we are to move forward in the assessment of the human influence on climate.»

As with previous CIS contributions, the 2016 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness / extent, as well as winter surface air temperature, spring ice conditions and the summer temperature forecast; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent time - series into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicbased on observed end - of - winter Arctic ice thickness / extent, as well as winter surface air temperature, spring ice conditions and the summer temperature forecast; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent time - series into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predicBased Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent time - series into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

This gives some interesting options, one of which is to draft the first filing in a way such that there is basis for multiple combinations of one or more or all features of the invention.

Calunius offers a mix of approaches to pricing, seeking returns on successful investments based around combinations of multiples of outlay, percentages of proceeds and / or minimum thresholds.

In our testing, we had multiple instances where a lock configured to auto - unlock based on geofencing or an electronic perimeter (which may use any combination of GPS, Bluetooth, your cellular signal, or Wi - Fi) triggered incorrectly — and more than once, late at night while we were at home in bed.

I believe that success is based on a combination of multiple things that one does on a consistent basis.