Germany's main stock market index, the DE40, rose to 24297 points on July 23, 2025, gaining 1.06% from the previous session. Over the past month, the index has climbed 2.77% and is up 32.14% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Germany. Germany Stock Market Index (DE40) - values, historical data, forecasts and news - updated on July of 2025.

SAM 40: Dataset of 40 subject EEG recordings to monitor the induced-stress while performing Stroop color-word test, arithmetic task, and mirror image recognition task

presents a collection of electroencephalogram (EEG) data recorded from 40 subjects (female: 14, male: 26, mean age: 21.5 years). The dataset was recorded from the subjects while performing various tasks such as Stroop color-word test, solving arithmetic questions, identification of symmetric mirror images, and a state of relaxation. The experiment was primarily conducted to monitor the short-term stress elicited in an individual while performing the aforementioned cognitive tasks. The individual tasks were carried out for 25 s and were repeated to record three trials. The EEG was recorded using a 32-channel Emotiv Epoc Flex gel kit. The EEG data were then segmented into non-overlapping epochs of 25 s depending on the various tasks performed by the subjects. The EEG data were further processed to remove the baseline drifts by subtracting the average trend obtained using the Savitzky-Golay filter. Furthermore, the artifacts were also removed from the EEG data by applying wavelet thresholding. The dataset proposed in this paper can aid and support the research activities in the field of brain-computer interface and can also be used in the identification of patterns in the EEG data elicited due to stress.

Some relevant supplementary materials about the research of Chaofa Bian, including Excel with the coordinate positions of 40 lunar sampling sites and the reflectance averages of 26 band CE-1 IIM images and CF images within 2×2 pixels, as well as 27-band tif images of 40 lunar sampling sites.

Financial overview and grant giving statistics of Voiture Nationale La Societe De 40 169

Derm Good, protective day cream with probiotics, performed the best in the consumer ranking of 40+ face creams in Poland in 2025, followed by Lancôme, Rénergie Multi-Lift Ultra.

The data includes the validation parameters in terms of apparent recoveries, matrix effect, instrumental limits of detection and quantification, and instrumental linear range for teh determination of 40 abuse drugs in urine samples. This encompasses a total of 4 files: one for instrumental validation and three for method validation at 3 different levels of concentration. The availability of this data is necessary to analyse urine samples and determine the consumption of these drugs

Germany DE: Population: Male: Ages 40-44: % of Male Population data was reported at 6.458 % in 2023. This records an increase from the previous number of 6.355 % for 2022. Germany DE: Population: Male: Ages 40-44: % of Male Population data is updated yearly, averaging 6.944 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 9.152 % in 2006 and a record low of 4.067 % in 1960. Germany DE: Population: Male: Ages 40-44: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Male population between the ages 40 to 44 as a percentage of the total male population.;United Nations Population Division. World Population Prospects: 2022 Revision.;;

South of Interstate 40 mule deer reside in Game Management Units (GMU) 8 and 6B in Arizona. The herd summers in high-elevation open meadows and ponderosa pine habitat southwest of Flagstaff, Arizona. In late October, the herd migrates west to lower elevation pinyon-juniper and shrub habitats near the junction of Interstate 40 and U.S. Highway 89. With funding support by the U.S. Department of the Interior (USDI) through Secretarial Order 3362, research on this herd’s migration began in February 2020. Additional GPS collars were deployed in January 2022 with support from the U.S. Forest Service, Mule Deer Foundation, and other partners. Primary threats to the herd’s migration involve high volume roads including Interstate 40, and U.S. Highways 89 and 89A. These mapping layers show the location of the migration stopovers for mule deer (Odocoileus hemionus) in the South of I-40 population in Arizona. They were developed from 20 migration sequences collected from a sample size of 7 adult animals comprising GPS locations collected approximately every 3 hours.

Population as at 1 January by age group and sex.

The Database of Faces

Our Database of Faces, (formerly 'The ORL Database of Faces'), contains a set of face images taken between April 1992 and April 1994 at the lab. The database was used in the context of a face recognition project carried out in collaboration with the Speech, Vision and Robotics Group of the Cambridge University Engineering Department.

There are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement). A preview image of the Database of Faces is available.

The files are in PGM format, and can conveniently be viewed on UNIX (TM) systems using the 'xv' program. The size of each image is 92x112 pixels, with 256 grey levels per pixel. The images are organised in 40 directories (one for each subject), which have names of the form sX, where X indicates the subject number (between 1 and 40). In each of these directories, there are ten different images of that subject, which have names of the form Y.pgm, where Y is the image number for that subject (between 1 and 10).

The database can be retrieved from http://www.cl.cam.ac.uk/Research/DTG/attarchive:pub/data/att_faces.tar.Z as a 4.5Mbyte compressed tar file or from http://www.cl.cam.ac.uk/Research/DTG/attarchive:pub/data/att_faces.zip as a ZIP file of similar size.

A convenient reference to the work using the database is the paper Parameterisation of a stochastic model for human face identification. Researchers in this field may also be interested in the author's PhD thesis, Face Recognition Using Hidden Markov Models, available from http://www.cl.cam.ac.uk/Research/DTG/attarchive/pub/data/fsamaria_thesis.ps.Z (~1.7 MB).

When using these images, please give credit to AT&T Laboratories Cambridge.

UNIX is a trademark of UNIX System Laboratories, Inc.

Contact information Copyright © 2002 AT&T Laboratories Cambridge

Credit: https://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

This graph displays the total population size of citizens aged from between 40 and 44 years old in Europe in 2018, by country. That year there were roughly **** million inhabitants of this age group in Germany, which was followed by Italy and France with approximately **** million and **** million inhabitants respectively.

GC40 100_

## Overview

GC40 100_ is a dataset for object detection tasks - it contains SCDE annotations for 1,353 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

About this dataset

Context

The dataset tabulates the Selbyville population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Selbyville. The dataset can be utilized to understand the population distribution of Selbyville by age. For example, using this dataset, we can identify the largest age group in Selbyville.

Key observations

The largest age group in Selbyville, DE was for the group of age 35 to 39 years years with a population of 285 (9.80%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Selbyville, DE was the 80 to 84 years years with a population of 40 (1.38%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Selbyville is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Selbyville total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Selbyville Population by Age. You can refer the same here

URL: https://geoscience.data.qld.gov.au/dataset/mr008303

The ALMADEN A Mine map was published in 1966, charted in 1971 at 40 Chains to an Inch as part of the FIELD SHEET series to administer permit and permit related spatial information. The map was maintained internally as a provisional office chart and is located within the Chillagoe (7863) 1:100 000 map area.
The map product is available to all government agencies, industry and the public for reference.
Title and Image reference number is ALMADEN A_2794.

Cancelled 1976

VERA PalmVein is a dataset for palmvein recognition. The dataset consists of 2200 NIR imagesfrom 110 clients captured with an Open Sensor.

Database Description

All palmvein images have been recorded using palm vein prototype sensor developed by Haute Ecole Spécialisée de Suisse Occidentale in Sion.

110 clients presented their 2 hands to the sensor in two sessions and recorded 5 images per palm. Results is a Database of 2200 images of palmvein images.

The recordings have been performed at 2 different locations, always inside buildings with normal lightening conditions. The first 78 clients in the Database are from one location and the remaining 32 are from another.

The Database is composed of 40 women and 70 men whose ages are between 18 and 60 with an average at 33. Information about gender and age of clients are given as metadata for each client ID in the text file METADATA.txt.

Images are labeled as follow: ID_hand_session_shot.png where "ID" is a 3 digits number that stands for client's ID, "hand" stands for the considered hand which can be "R" or "L" ("Right" or "Left"), and "session" stands for the considered session number which can be "1" or "2" (2 session per hand), and finally, "shot" stands for the considered shot number which can be "1" to "5" (5 shots per palm).

Images from the same client are regrouped into a single folder labeled as follow: ID-Gender, where "ID" is a 3 digits number that stands for client's ID and "Gender" stands for client's gender which can be "M" or "F" ("Male" or "Female").

Two different folders are provided "raw" and "roi". The "raw" stands the full palm vein image captured by the sensor and the "roi" stands the region of interest generated by the sensor in the acquisition process.

The format of the images is PNG. Size of the images is 480 x 680 pixels. Size of the files is around 165 kbytes per images.

Database Protocol

Clients were asked to put their hand on the sensor and then adjust the position such that the palm is on the center of the image. The Graphical User Interface (GUI) provided by the sensor was used for visual feedback, Near Infra Red light control and acquisition. When the automated light control was performing unproperly the operator adjusted manually the intensities of the leds to achieve a better contrast of the vein pattern.

Clients first presented the left hand, then the other, each session. The whole process took 5 minutes per clients in average.

Acknowledgement

If you use this database, please cite the following publication:

Pedro Tome and Sébastien Marcel,"On the Vulnerability of Palm Vein Recognition to Spoofing Attacks", IAPR International Conference on Biometrics (ICB), 2015. 10.1109/ICB.2015.7139056 http://publications.idiap.ch/index.php/publications/show/3096

WD-40 reported $68.85M in Cost of Sales for its fiscal quarter ending in May of 2025. Data for WD-40 | WDFC - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last July in 2025.

In December 2021, the highest cost of renting a ** square meter apartment in Poland was recorded in Warsaw at *** thousand zloty per month. The lowest costs were noted in Sosnowiec at *** thousand per month.

Links to code and bioRxiv pre-print: 1. Multi-lens Neural Machine (MLNM) Code 2. An AI-assisted Tool For Efficient Prostate Cancer Diagnosis (bioRxiv Pre-print) Digitized hematoxylin and eosin (H&E)-stained whole-slide-images (WSIs) of 40 prostatectomy and 59 core needle biopsy specimens were collected from 99 prostate cancer patients at Tan Tock Seng Hospital, Singapore. There were 99 WSIs in total such that each specimen had one WSI. H&E-stained slides were scanned at 40× magnification (specimen-level pixel size 0·25μm × 0·25μm) using Aperio AT2 Slide Scanner (Leica Biosystems). Institutional board review from the hospital were obtained for this study, and all the data were de-identified. Prostate glandular structures in core needle biopsy slides were manually annotated and classified using the ASAP annotation tool (ASAP). A senior pathologist reviewed 10% of the annotations in each slide, ensuring that some reference annotations were provided to the researcher at different regions of the core. It is to be noted that partial glands appearing at the edges of the biopsy cores were not annotated. Patches of size 512 × 512 pixels were cropped from whole slide images at resolutions 5×, 10×, 20×, and 40× with an annotated gland centered at each patch. This dataset contains these cropped images. This dataset is used to train two AI models for Gland Segmentation (99 patients) and Gland Classification (46 patients). Tables 1 and 2 illustrate both gland segmentation and gland classification datasets. We have put the two corresponding sub-datasets as two zip files as follows: gland_segmentation_dataset.zip gland_classification_dataset.zip Table 1: The number of slides and patches in training, validation, and test sets for gland segmentation task. There is one H&E stained WSI for each prostatectomy or core needle biopsy specimen. #Slides Train Valid Test Total Prostatectomy 17 8 15 40 Biopsy 26 13 20 59 Total 43 21 35 99 #Patches Train Valid Test Total Prostatectomy 7795 3753 7224 18772 Biopsy 5559 4028 5981 15568 Total 13354 7781 13205 34340 Table 2: The number of slides and patches in training, validation, and test sets for gland classification task. There is one H&E stained WSI for each prostatectomy or core needle biopsy specimen. The gland classification datasets are the subsets of the gland segmentation datasets. GS: Gleason Score. B: Benign. M: Malignant. #Slides (GS 3+3:3+4:4+3) Train Valid Test Total Biopsy 10:9:1 3:7:0 6:10:0 19:26:1 #Patches (B:M) Train Valid Test Total Biopsy 1557:2277 1216:1341 1543:2718 4316:6336 NB: Gland classification folder (gland_classification_dataset.zip) may contain extra patches, labels of which could not be identified from H&E slides. They were not used in the machine learning study. This study was funded by the Biomedical Research Council of the Agency for Science, Technology and Research, Singapore.

CholecT40 is the first endoscopic dataset introduced to enable research on fine-grained action recognition in laparoscopic surgery.

It consists of 40 videos of laparoscopic cholecystectomy surgery annotated with triplet information in the form of

The dataset is used as benchmark for developing deep learning solution for the recognition of surgical activities in the form of a triplet. It is first surgical data science effort to replicate activity recognition in the same level as human-object interaction (HOI) in natural vision tasks.

The parent dataset is CholecT50.

About this dataset

Context

The dataset tabulates the Gantt population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Gantt. The dataset can be utilized to understand the population distribution of Gantt by age. For example, using this dataset, we can identify the largest age group in Gantt.

Key observations

The largest age group in Gantt, AL was for the group of age 30 to 34 years years with a population of 40 (20.20%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Gantt, AL was the 25 to 29 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Gantt is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Gantt total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gantt Population by Age. You can refer the same here