With the rapid development of intelligent transportation systems, especially in traffic image detection tasks, the introduction of the transformer architecture greatly promotes the improvement of model performance. However, traditional transformer models have high computational costs during training and deployment due to the quadratic complexity of their self-attention mechanism, which limits their application in resource-constrained environments. To overcome this limitation, this paper proposes a novel hybrid architecture, Mamba Hybrid Self-Attention Vision Transformers (MHS-VIT), which combines the advantages of Mamba state-space model (SSM) and transformer to improve the modeling efficiency and performance of visual tasks and to enhance the modeling efficiency and accuracy of the model in processing traffic images. Mamba, as a linear time complexity SSM, can effectively reduce the computational burden without sacrificing performance. The self-attention mechanism of the transformer is good at capturing long-distance spatial dependencies in images, which is crucial for understanding complex traffic scenes. Experimental results showed that MHS-VIT exhibited excellent performances in traffic image detection tasks. Whether it is vehicle detection, pedestrian detection, or traffic sign recognition tasks, this model could accurately and quickly identify target objects. Compared with backbone networks of the same scale, MHS-VIT achieved significant improvements in accuracy and model parameter quantity.

Skills Funding Agency contract values for Colleges, training organisations and employers who are in receipt of a contract for a given funding year.

Colleges, training organisations, local authorities and employers who receive funding from the Agency to deliver education and training are required to submit learner data via an Individualised Learner Record (ILR) to the Agency at regular points in the year. This information is used to tell the Agency how they are performing against their contract and to set contract allocations, performance manage against published criteria and to work out the final funded position for a funding year.

Further information about submitting data can be found from the Information authority website: http://www.theia.org.uk/ilr/ Further information about performance management and Final claims can be found from our website: http://skillsfundingagency.bis.gov.uk/providers/fundingdocuments/

Loudoun County 2020 Census Tracts as adjusted by the Virginia Division of Legislative Services.The United States decennial census is the primary data source on population, age, and race used in redistricting. While there is no federal requirement that census data be used for redistricting, § 24.2-304.1 of the Code of Virginia requires local governments to use the most recent decennial population figures for such county, city, or town for the purposes of redistricting and reapportioning representation. During the 2011 cycle, this Code section required the use of those “figures [that were] identical to those from the actual enumeration conducted by the United States Census Bureau (the Census Bureau) for the apportionment of representatives in the United States House of Representatives.” However, the 2020 Regular Session of the General Assembly amended this requirement so that in the 2021 redistricting cycle the data to be used will be the census data as adjusted by the Division of Legislative Services to reflect the reallocation of prison populations.

Panel A. Representative analysis of the fluorescence of BODIPY 493/503 in MHC II+ DLs. A1, A2. Control C57BL/6 DL cultures –i.e. not exposed to L. am amastigotes- were incubated or not at 34°C with 200 µM oleate for 21 hours. A3, A4. DsRed2-L. am were added to DL cultures at a ratio of 5 DsRed2-L. am per DL (+L. am). Oleic acid (200 µM) was added 3 hours post inoculation, (A4: +Oleate) or not (A3: −Oleate) for a further 21 hours at 34°C. Control and L. am-loaded DLs were then detached. LBs were stained with BODIPY 493/503 2 µg/ml in PBS for 30 minutes at 34°C. The cells were then incubated with anti MHC II- PE-Cy5 mAb to analyze only the MHC class II-positive DLs. FCM histograms show BODIPY 493/503 fluorescence for Ctrl (A1, A2: white histograms) and DsRed2 L. am-hosting DLs (A3, A4) (DsRed2+, black histograms) and amastigotes-free DLs (DsRed2−, grey histograms). Mean fluorescence intensity was indicated for each histogram. Panel B: Statistical analysis of the BODIPY 493/503 MFI values. Mean BODIPY 493/503 fluorescence by MHC II+ DLs was determined for n = 7 independent experiments. MFI in L. am-loaded cultures is shown for DsRed2+ and DsRed2− DLs as black and grey bars, respectively. Statistical analyses were performed by the Mann Whitney test.

Calculated particle diameters are given in nm. Errors indicate peak width. Peak 2 corresponds to ∼1% of the total mass of the protein sample and indicates higher order aggregates. Units are in nm. Values are means ± SD from three experiments.*non-detected.**I =  diameter calculated based on the distribution of intensities of scattering, V =  diameter calculated after normalization of the scattering distribution based on particle volume occupancy.

Transient voltage measurement data DLS pulse experiment 1 mA– 6 mA.

ObjectiveTo supply the attending doctor’s diagnosis of the persisting of cerebral small vessel disease and speed up their work effectively, we developed a “deep learning system (DLS)” for cerebral small vessel disease predication. The reliability and the disease area segmentation accuracy, of the proposed DLS, was also investigated.MethodsA deep learning model based on the convolutional neural network was designed and trained on 1,010 DWI b1000 images from 1010 patients diagnosed with segmentation of subcortical infarction, 359 T2∗ images from 359 patients diagnosed with segmentation of cerebral microbleed, as well as 824 T1-weighted and T2-FLAIR images from 824 patients diagnosed with segmentation of lacune and WMH. Dicw accuracy, recall, and f1-score were calculated to evaluate the proposed deep learning model. Finally, we also compared the DLS prediction capability with that of 6 doctors with 3 to 18 years’ clinical experience (8 ± 6 years).ResultsThe results support that an appropriately trained DLS can achieve a high-level dice accuracy, 0.598 in the training section over all these four classifications on 30 patients (0.576 for young neuroradiologists), validation accuracy is 0.496 in lacune, 0.666 in WMH, 0.728 in subcortical infarction, and 0.503 in cerebral microbleeds. It is comparable to attending doctor with a few years of experience, regardless of whether the emphasis is placed on the segmentation or detection of lesions with less time-spending compared with manual analysis, about 4.4 s/case, which is dramatically less than doctors about 634 s/case.ConclusionThe results of our comparison lend support to the case that an appropriately trained DLS can be trusted to the same extent as one would trust an attending doctor with a few years of experience, regardless of whether the emphasis is placed on the segmentation or detection of lesions.

Code and description relevant to files can be found on https://github.com/dad/pab1-phase-2017/blob/master/src/biophysics/DLS.np

NYC TLC Licensed FHV drivers that are currently active and in good standing. This list is accurate to the date and time represented in the Last Date Updated and Last Time Updated fields.

Feature layer depicting the centre of quarter sections, parish lots and others in Manitoba. The purpose of this layer is to provide search criteria for Manitoba legal descriptions.

This feature layer is comprised of point locations that represent the centre of the bounds of the corresponding legal parcel. The types of legal descriptions include quarter sections (D.L.S.), river lots, parish lots, wood lots, outer two mile lots, and settlement lots. The point may not fall exactly on the centre of the legal parcel of land. This feature layer is meant as a search tool to locate the general location of the given legal description and it may not be exact. The points were initially derived from a variety of sources. Most of the points came from the Southern and Northern Grid of DLS section boundaries created by Sustainable Development. Fields included (Alias (Field Name): Field Description) OBJECTID (OBJECTID_1): Sequential unique whole numbers that area automatically generated Informal Legal Description (LEGAL_DESC): The informal legal description (No leading zeros on numbers). Formal Legal Description (LEGAL_DESC0): The formal legal description (Leading zeros on numbers). Type (TYPE): The type of legal division ('Quarter' = Quarter section, 'RL' = River lot, 'Lot' = Township lot, 'OT' = Outer two mile lot, 'PL' = Parish lot, 'SL' = Settlement lot, 'WL' = Wood lot). Quarter (QUARTER): Which DLS quarter section the point is referencing (NE, NW, SE or SW meaning respectfully North-east, North-west, South-east or South-west) Section (SECTION): The DLS section the point is referencing (1-36). Township (TOWNSHIP): The DLS township the point is referencing. Range (RANGE): The DLS range the point is referencing. Lot No. (LOT_NO): The lot number of the corresponding river, settlement, township, outer two mile or parish lot. Meridian (MERIDIAN): The meridian of the section (East 1, East 2 or West 1). Parish Name (PARISH_NAME): The name of the parish that the lot belongs to. Range Addition (RANGEADD): The added text for specific range values (if applicable).

The present work represents a continuation of a former study where the simultaneous determination of thermal and mutual diffusivity for binary mixtures of n-octacosane (n-C28H58) with dissolved carbon monoxide (CO), hydrogen (H2), or water (H2O) by using dynamic light scattering (DLS) was demonstrated. Here, the same properties are studied for binary mixtures of the n-alkanes n-dodecane (n-C12H26) or n-tetracontane (n-C40H82) with dissolved CO, H2, or H2O. In most cases, expanded relative uncertainties (k = 2) ranging from 2 to 12 % and 3 to 25 % for the thermal and mutual diffusivities could be obtained. The experimental mutual diffusivities for mixtures of n-C12H26 with CO, H2, or H2O measured at temperatures from 398 to 524 K and pressures from 0.2 to 4.2 MPa at saturation conditions agree well with molecular dynamics (MD) simulations using atomistic models and with experimental data from literature. Binary mixtures of n-C40H82 with dissolved CO, H2, or H2O were investigated in a temperature range from 447 to 498 K and pressures from 0.3 to 3.9 MPa. For mixtures with n-C40H82, the accessible temperature range was limited due to a change in the optical characteristics of the sample at elevated temperatures where DLS measurements suffered from absorption effects and particle scattering.

Model performance comparison of 10-year major adverse cardiovascular events (MACE) risk prediction between DLS versus other methods for the non-operating point dependent metrics.

A division of the Department of Labor Standards (DLS), the goals of the Occupational Safety and Health Statistics Program strives to protect workers in Massachusetts.

OE Results of BBPSO, PBBPSO, DLS-BBPSO and TBBPSO.

DSF and DLS of SOSIP.v9 proteins and SOSIP-I53-50 NPs.

This dataset contains the underway data from Voyage 7 1992-93 (KROCK) of the Aurora Australis. This was a manned marine science voyage. The observations were taken between January and March 1993 on route from Hobart to Davis to Mawson to Casey and back to Hobart. DLS and NoQalms data types were logged. See the Marine Science Support Data Quality and Programmer's Reports at the Related_URL section.

Also available is a scan of a printed plot of a section of the Voyage 7 1992/93 (KROCK) track:
transects north of the Antarctic coastline between 60 degrees East and 83 degrees East, 15 January to 7 February 1993.

From the voyage leader's report:

The principal purpose of the voyage was to carry out marine science research in the Prydz Bay region in two phases:

1) A biological phase of 22 days, dominated by research into the distribution, abundance and biology of krill, zooplankton and fish,
2) A geological phase of 10 days to study the sedimentary history of the region.

A number of secondary programs involved the study of; krill chemistry, water chemistry distribution, abundance and description of benthos, distribution and abundance of birds, and distribution of icebergs.

After completion of the marine science program, RTA expeditioners and cargo were to be collected at Davis and Mawson, some cargo was transferred from Davis to Mawson. During the course of the voyage, Casey RTA expeditioners and cargo were added, giving a full expeditioner complement of 109 on the return journey to Hobart.

Controls (left panels) and L. am amastigote-loaded DLs (right panels) were incubated or not with oleate as described previously. Cells were then detached, deposited on coverslips, and LBs were evidenced by the incorporation of BODIPY 493/503 2 µg/ml in PBS for 30 minutes at 34°C (in green). Cells were fixed and stained with M5/114 mAb (in red). DL and amastigote nuclei were stained with Hoechst 33,342 (blue spots indicated by arrowheads).

Análisis DLS de nanopartículas de Cu obtenidas por síntesis verde para determinar la distribución, el índice de polidispersión (IPD) y el tamaño promedio. Se observan los Histogramas de las nanopartículas evidenciando que O: original, S: sobrenadante, P: Pellet

Mean is the mean value from 31 independent runs, STD is the standard deviation of the 31 runs, Rank is the rank of 4 algorithms.

Panel A: TEM pictures of DL cultures exposed or not to live L. am amastigotes and incubated or not with oleate. Representative pictures are shown for control (Ctrl; upper left panel), oleate-treated (Oleate, lower left panel), amastigote-loaded (L. am, upper right panel) and amastigote-loaded treated by oleate (L. am+ oleate, lower right panel) C57BL/6 DL cultures. LBs are indicated. Panel B: Analysis of LBs in control and live L. am amastigote-hosting C57BL/6 DLs incubated or not with oleate. LB were counted and their area determined in TEM section pictures. The results are represented as box and whisker plots. B1: number of cytosolic LBs in Ctrl DLs and DLs hosting live L. am amastigotes in the absence or presence of oleate. B2: LB area in Ctrl DLs and LDs hosting live L. am amastigotes in the absence or presence of oleate. Statistical analyses were performed by the Mann Whitney test after analysing at least 60 sections of DL samples. (*): p<0.001.