cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/76msnn2tz8.1
title: TMA-Mate: An open-source modular toolkit for constructing tissue microarrays of arbitrary layouts 

description: Biomedical research and quality control procedures often demand a variety of microscopic analysis of numerous formalin-fixed and paraffin-embedded (FFPE) tissue samples from different individuals of both healthy and diseased regions of interest. Depending on the number of samples to be analyzed, conventional processing of each FFPE block separately can be laborious or impracticable. This effort can be drastically reduced by using tissue microarrays (TMAs). TMAs have a wide range of applications and can be considered as a high-throughput method to process up to hundreds of miniaturized tissue samples simultaneously on a single microscopy slide, in order to reduce labor, costs and sample consumption, and to increase results comparability. Several commercial and self-made solutions to fabricate TMAs with varying degrees of automation are available. However, these solutions may not be suitable for every situation, either due to high costs, high complexity, lack of precision or lack of flexibility, especially when diagnostically oriented pathology institutes or laboratories with constrained resources are considered. This article introduces the TMA-Mate, an open-source 3D printable modular toolkit for constructing high-density TMAs of arbitrary layouts, providing an affordable, lightweight, and accessible procedure to implement TMAs into existing histology processing pipelines. Step-by-step demonstration for replicating the Hardware and constructing TMAs are included.

Files description:

* The folder 'TMA_Mate_FCStd' contains the CAD model as a sigle 'FCStd' file created with the standart unmodified distribution of FreeCAD (version 0.20.1, revision number 29410/Git).

* The folder 'TMA_Mate_STL' contains Stereolithography files (.stl) for each individual part of the TMA-Mate and the accessories, created with the standart unmodified distribution of FreeCAD (version 0.20.1, revision number 29410/Git). Compressed archive files (.zip) within this folder contain variants of the indicated 3D printed parts. The stereolithography files for modular parts cannot be offered in all possible variations and are limited to a reasonable selection. The Rack (file 9. R_Rack.zip) is the only part that requires print supports and is therefore provided with and without print supports.
DOI: 10.17632/rpdhyzh899.1
title: A novel bypass-gas metal arc directed energy deposition for in-situ synthesis Al-Cu-Li alloy: exploring the microstructure and mechanical properties evolution from as-deposited state to T6 state

description: A novel bypass-gas metal arc directed energy deposition (bypass-GMA DED) was proposed to prepare high strength Al-Cu-Li-based components. An Al-5.51Cu-0.48Li alloy was successfully prepared, followed by subsequent T6 treatment. The microstructure evolution and improvement of mechanical properties after the T6 state were benchmarked against the as-deposited condition. The component fabricated by bypass-GMA DED has obvious periodic distribution characteristics, with a large number of fine equiaxed grains distributed near the interlayer fusion boundary and coarse columnar grains within the intralayer region. After heat treatment, the Al-5.51Cu-0.48Li alloy is mainly composed of four types of strengthening phases, θ’, θ”, δ’ and T1, which contrasts with the sole presence of θ phase in the deposited condition. These phases are conducive to the improvement of mechanical properties. The strength of the prepared alloy is higher than those additively manufactured Al-Cu-Li alloys, reaching values similar to those of conventional third generation Al-Cu-Li alloys.
DOI: 10.17632/65cjrm6xkm.1
title: Liposomal cytarabine and daunorubicin (CPX-351/Vyxeos)-associated distinct purpuric subtype of toxic erythema of chemotherapy: a retrospective review of 54 patients

description: Supplemental Appendix
DOI: 10.17632/jjbfcckrsp.2
title: Maize-Weed Image Dataset 

description: The dataset contains images of maize plants and weed species. The dataset contains 36874 images in total and is stored in four folders namely Annotated Maize-Weed Images, Data Description and Questionnaire, Dry Season Maize Weed Images, and Wet Season Maize Weed Images. The Dry Season contains 18187 images captured during the dry season farm survey, the Wet Season contains 18187 images captured during the wet season farm survey and the Annotated contains 500 annotated images selected from the Dry Season survey saved in JSON, XML, and txt format. The annotation was achieved using the Labelmg suite. The raw wet and dry seasons images have been captured using a high-resolution digital camera during the weed survey, while the annotation of the annotated image was done using the Labelmg suite. A total of 18 farm locations were visited in the North Central part of Nigeria for the data acquisition as part of an ongoing research effort on maize-weed identification in farmlands.
DOI: 10.17632/kw34hhw7xg.3
title: Battery Degradation Dataset (Fixed Current Profiles＆Arbitrary Uses Profiles)

description: 77 nominally identical high-energy 18650 lithium-ion batteries are cycled with fixed or arbitrary uses current profiles. 22 batteries are cycled with fixed current profiles of charge current (1C, 2C, or 3C) and discharge current (1C, 2C, or 3C). 55 batteries are cycled with arbitrary uses profiles of charge current (obeys a uniform distribution among 1C, 2C, or 3C, and changes randomly every 5 cycles)  and a specified discharge current (3C).

All the battery degradation tests were carried out by the Advanced Energy Storage and Application (AESA) Group at Beijing Institute of Technology.

If you make use of our data, please cite our dataset directly using its DOI, as well as the following papers: 
[1] Lu, J., Xiong, R., Tian, J., Wang, C., Hsu, C. W., Tsou, N. T., Sun, F., & Li, J. (2022). Battery Degradation Prediction Against Uncertain Future Conditions with Recurrent Neural Network Enabled Deep Learning. Energy Storage Materials, 50, 139-151. https://doi.org/10.1016/j.ensm.2022.05.007
[2] Tian, J., Xiong, R., Shen, W., Lu, J., & Yang, X. G. (2021). Deep neural network battery charging curve prediction using 30 points collected in 10 min. Joule, 5(6), 1521-1534. https://doi.org/10.1016/j.joule.2021.05.012

Please also consider citing our papers on these topics, see:
http://en.aesa.net.cn/About.aspx?ClassID=12
DOI: 10.17632/htdcngcvr9.1
title: The inverse approach for early diagnosis of lentigo maligna

description: The inverse approach is a new dermatoscopic method for the early diagnosis of lentigo maligna. It originated from previous evidence demonstrating that the classic pattern analysis results in poor diagnostic accuracy when it comes to differentiate early lentigo maligna from pigmented actinic keratosis and solar lentigo. The inverse approach suggests that lentigo maligna should be diagnosed by exclusion of the other 2 tumors, based on the absence of prevalent dermatoscopic features. We tested the effect of the inverse approach on the diagnostic performance of 78 clinicians participating in a dermatoscopy masterclass (Dermoscopy Excellence). We found that it significantly improved all measures of diagnostic accuracy and especially the sensitivity for lentigo maligna. We also used a previously tested convolutional neural network for comparison purposes. More than 50% of human readers outperformed the convolutional neural network when using the inverse approach. The latter study was published in 2020 in the Journal of the American Academy of Dermatology. The current dataset describes the details of the inverse approach and can be used an an educative material.
DOI: 10.17632/7pbjvjsbvb.2
title: Sustainability or Performance? Ratings and Fund Managers’ Incentives

description: Replication package. The March 9 updated version includes the following minor comments from the data editor:
 1. Information about the hardware and computational time for the analyses to the readme file 
2. Code "set varabbrev on" to the do file Code for data construction.do
3. We use the full name of a variable instead of the abbreviation in Code for data construction.do,
DOI: 10.17632/9m2dcb5mmr.2
title: Indigenous Dataset for Apple Leaf Disease Detection and Classification

description: This dataset, suitable for training Machine Learning and Deep Learning models, has been built by collecting images from the apple cultivation fields of Jammu and Kashmir. The dataset contains 7569 images belonging to three categories viz Healthy, Alternaria and Apple-Mosaic.
DOI: 10.17632/dvntn9yhd2.1
title: Covid19-Pneumonia-Normal Chest X-Ray Images

description: - It is a medical images directory structure branched into 3 subfolders (COVID, NORMAL, PNEUMONIA) containing Chest X-ray (CXR) Images.
- All images are preprocessed and resized to 256x256 in PNG format.
- It helps the researcher and medical community to detect and classify COVID19 and Pneumonia from Chest X-Ray Images using Deep Learning.

COVID-19: 1626 images
NORMAL: 1802 images
PNEUMONIA: 1800 images


References:
-If you are using this dataset for research purposes then cite the below articles:

1. Shastri, S., Kansal, I., Kumar, S. et al. CheXImageNet: a novel architecture for accurate classification of Covid-19 with chest x-ray digital images using deep convolutional neural networks. Health Technol. 12, 193–204 (2022). https://doi.org/10.1007/s12553-021-00630-x

2. Kumar S, Shastri S, Mahajan S, et al. LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images. Int J Imaging Syst Technol. 2022;1‐17. DOI: https://doi.org/10.1002/ima.22770
DOI: 10.17632/xmc894xmhv.1
title: Figure S1. Prevalence of prurigo nodularis by age, sex, race and ethnicity, and disease group.

description: Prevalence of prurigo nodularis by age, sex, race and ethnicity, and disease group.
DOI: 10.17632/3mpkm4hsfh.1
title: Obesity Management

description: Using Liraglutide for obesity management
DOI: 10.17632/29n74jyv3m.1
title: Literature on Online Grocery Shopping Adoption

description: This study uses a systematic analysis of the available corpus on OGS adoption literature published between 2000 and 2020. The scope of this article was to identify the relevant topics and research streams in the domain of OGS adoption research from a consumer perspective. Data was collected using the search phrase “online grocery shopping adoption” – separated via AND operators (where applicable) – from the following databases: Google Scholar (998 entries), Science Direct (534), Crossref (200), Scopus (30) and Web of Science (16). Harzings Publish or Perish software (Harzing 2007) aided in the data collection and enabled a high level of data consistency in the raw data material, initially consisting of a total of n = 1,778 data entries.
The created data-set underwent a series of specific adjustments along a four-stage selection process (as outlined in figure 2). Besides the (rather technical) procedures in the first selection step, the process was conducted by two researchers independently, differing classifications were discussed and resolved. For the selection process, the current iteration of Microsoft Excel was used. The adjustment procedure followed these stages:

First, a number of technical reductions was performed by removing duplicates (-58), non-English literature (-5), non-journal documents like book chapters and undergraduate theses (- 26) and corrupted data entries (-171; e.g. empty data fields).
Next, the remaining articles were screened for suitability on the scope of this article based on their title and keywords. A large proportion of data entries was removed due to either being focussed on a supply-side perspective or focussing on the overall topics of adoption and online shopping without any (online) food-related context.
The data-set was further trimmed down upon inspection of the abstract. Other literature reviews (-6, incl. the two OGS-related reviews presented in an earlier section) were removed from the data set at this point.
All papers that reached this selection step were eligible for analysis including reference search to determine the degree of concept exhaustion in our data-set. Reference search revealed an additional twelve articles. 
Thus, the final data-set consisted of a total of n = 103 unique articles on online grocery shopping adoption that were included in the bibliometric analysis of this article.
DOI: 10.17632/5fvjd6xt45.1
title: https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)

description: Breast Cancer Data-set is also used for collecting the data for constructing the patient record files. The numbers of attributes are Id number, cell size, and shape, class attributes such as a benign tumor or malicious tumor and so on.
DOI: 10.15468/dl.vucqzm
title: Occurrence Download

description: A dataset containing 522 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prosopis pubescens Benth.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 522 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009302-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/945fp2j762.1
title:  Assessing Innovative Reading Public policies 

description: This collection of references corresponds to the bibliography that supports the article Assessing the impact of Innovative Public Policies for the Development of Reading Skills in Elementary Schools: Recommendations from a Systematic Literature Review. This bibliography considers that which supports the literature review on the topic and the highligts of the article. It also includes the references of the articles identified as relevant in this systematic literature review. In order to select the articles, previously established inclusion and exclusion criteria and an exhaustive method typical of systematic literature reviews were used. Therefore, in this collection you will find all the references included in the article.
DOI: 10.17632/8r5cttwh7f.2
title: Sorani Tweet Sent Dataset (STSD)

description: The Kurdish language is part of the Indo-Iranian branch of the Indo-European language family and is closely linked to Persian. It is spoken by approximately 40 million people residing at the crossroads of Iran, Turkey, Iraq, and Syria. Kurdish is recognized as an official language in Iraq and holds regional language status in Iraq. The language comprises various dialects, with Central Kurdish (Sorani) and Northern Kurdish (Kurmanji) being the primary ones. Additionally, there are minor dialects such as Gorani (Hawrami), spoken in parts of Iraq and Iran, and Zazaki, used in Turkey. Throughout history, Kurdish has been written using different alphabets, including Cyrillic, Armenian, Latin, and Arabic. The Sorani dialect, which is the focus of this dataset, consists of 36 letters representing vowels and consonants. Despite its rich linguistic heritage and a substantial number of speakers, the Kurdish language unfortunately lacks many essential natural language processing (NLP) tools, including comprehensive datasets.

In the given context, the Kurdish Sentiment Analysis Dataset stands as a noteworthy contribution to the field of natural language processing for low-resource languages, specifically focusing on the Sorani dialect of Kurdish. The dataset initially consisted of 30,009 texts gathered from Twitter using the Twitter API 2.0. Following thorough processing and refinement, the final dataset encompasses 24,668 high-quality texts, establishing a robust foundation for various NLP tasks. The data was collected during the global COVID-19 pandemic, adding a unique contextual backdrop to the dataset. As a result, a significant proportion of the tweets revolve around COVID-19 related topics, reflecting the societal concerns and discussions prevalent during this unprecedented time. 

The dataset stands out due to its meticulous annotation process. Each tweet was manually labeled by three human annotators across multiple dimensions, greatly enhancing its suitability for machine-learning applications. The annotations encompass four key aspects: subjectivity, sentiment, offensiveness, and the presence of a specific target. This comprehensive approach to labeling enables a nuanced comprehension of the text, empowering researchers to train models for tasks such as sentiment analysis, subjectivity detection, and identifying offensive language. The creation of this dataset fills a crucial gap in language resources for Kurdish, especially the Sorani dialect. Given Kurdish's status as a low-resource language, extensive datasets essential for the development of advanced NLP models have historically been lacking. Consequently, this dataset paves the way for new avenues in research and development in Kurdish language processing, offering the potential for enhanced language technologies for Kurdish speakers.
DOI: 10.17632/c3jhnkgr8p.1
title: Simulation code for "Optimal Default Options" JPubE September 2024

description: This code generates the simulations reported in "Optimal Default Options" by B. Douglas Bernheim and Jonas Mueller-Gastell, published in the Journal of Public Economics, September 2024.
DOI: 10.17632/k76xhm22yj.1
title: Real-Time ICS SCADA System Cyber Kit Testbed with Industrial Hacking Scenarios

description: An innovative and cost-effective real-time network traffic testbed, which can mimic the industrial control system operation is introduced. The ICS portable kit package provides real industrial network flow data for research and to develop anomaly-based Machine learning algorithms for intrusion detection in ICS systems. The ICS cyber portable test kit can overcome the main concern for researchers on the dependence on public datasets which usually do not include all types of attacks to train and test the machine learning algorithms The ICS portable kit package consists of following components: PLC (IP address-192.168.101.22): SIMATIC S7-1200 Siemens for process operation simulation HMI (IP address-192.168.101.23): SIMATIC Basic panel Siemens for graphical interface Ethernet switch (IP address: 192.168.101.25): Scalance XB213 Siemens with mirror port facility to copy the operational technology (OT)network traffic Process simulation modules- Analogue, digital inputs/outputs for field process simulation Physical sensor: Data collection of network traffic with Deep Packet Inspection (DPI) Attacker system: Launch OT attacks with Penetration test software Kali Linux Industrial Process Plant Operations: The ICS kit is possessed with input/output modules to mimic the field devices and its process variables, which are connected to PLC systems and to the HMI panel Mirrored Ethernet Switch: The ICS components of kit (PLC, HMI) are connected to Siemens ethernet switch for copying OT traffic Industrial Sensor: OT Sensors are used in passive mode, connected to the ethernet switch for metadata OT traffic extraction The test kit can also be attacked and tested with hacking penetration tools to obtain the industrial datasets, which are very difficult to get from the industries due to its sensitivity and criticality Each of the dataset instance has 06 data columns ( Timestamp of each packet, Source IP, Destination IP, OT Protocols, Summarized packet Info for DPI) The datasets include normal operation along with attack scenarios dedicated to OT ICS protocols domain and the contents include: 1. Stable mode of control system operation maintained for at least 10 minutes has 68965 instances 2. MITM attack scenario (ARP) with Ettercap tool for PLC/HMI communication has 52600 instances 3. Telnet communication for PLC/HMI ethernet switch has 13076 instances 4. Web-server access (HTTP) of PLC system with programming tool laptop scenario has 21435 instances The metadata extracted from info column in matrix data is pre-processed, transformed for Deep learning ML techniques for cyber attack abnormality detection MODBUS TCP -S7 ARP TELNET MODBUS LLDP HTTP [27617 x 4] [238x3] [89 x 1] [1503 x 5] [251 x 2] [910 x 1] More information is provided in the data paper which is currently under review: M. H. Habaebi,S. Mubarak (2021),Real-Time ICS SCADA System Testbed with Industrial Datasets Scenarios and Attack Detection Using Machine Learning Techniques, IASC
DOI: 10.17632/w9wkd7g43f.5
title: BAAD6: Bangla Authorship Attribution Dataset

description: A dataset consisting of text samples from 6 authors with 350 samples per author and total word count of 2.3+ million.
DOI: 10.17632/bhmdr45bh2.4
title: The IQ-OTH/NCCD lung cancer dataset

description: The Iraq-Oncology Teaching Hospital/National Center for Cancer Diseases (IQ-OTH/NCCD) lung cancer dataset was collected in the above-mentioned specialist hospitals over a period of three months in fall 2019. It includes CT scans of patients diagnosed with lung cancer in different stages, as well as healthy subjects. IQ-OTH/NCCD slides were marked by oncologists and radiologists in these two centers. The dataset contains a total of 1190 images representing CT scan slices of 110 cases. These cases are grouped into three classes: normal, benign, and malignant. of these, 40 cases are diagnosed as malignant; 15 cases diagnosed with benign; and 55 cases classified as normal cases. The CT scans were originally collected in DICOM format. The scanner used is SOMATOM from Siemens. CT protocol includes: 120 kV, slice thickness of 1 mm, with window width ranging from 350 to 1200 HU and window center from 50 to 600 were used for reading. with breath hold at full inspiration. All images were de-identified before performing analysis. Written consent was waived by the oversight review board. The study was approved by the institutional review board of participating medical centers. Each scan contains several slices. The number of these slices range from 80 to 200 slices, each of them represents an image of the human chest with different sides and angles. The 110 cases vary in gender, age, educational attainment, area of residence and living status. Some of them are employees of the Iraqi ministries of Transport and Oil, others are farmers and gainers. Most of them come from places in the middle region of Iraq, particularly, the provinces of Baghdad, Wasit, Diyala, Salahuddin, and Babylon.

if you use this dataset you should cite the following articles:

1- Diagnosis of lung cancer based on CT scans using CNN
can be cited as :
(H. F. Al-Yasriy, M. S. Al-Husieny, F. Y. Mohsen, E. A. Khalil, and Z. S. Hassan, "Diagnosis of Lung Cancer Based on CT Scans Using CNN," IOP Conference Series: Materials Science and Engineering, vol. 928, 2020.)

2- Evaluation of SVM performance in the detection of lung cancer in marked CT scan dataset
can be cited as:
(H. F. Kareem, M. S. A.-Husieny, F. Y. Mohsen, E. A. Khalil, and Z. S. Hassan, “Evaluation of SVM performance in the detection
of lung cancer in marked CT scan dataset,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 21, no. 3,
pp. 1731-1738, 2021, doi: 10.11591/ijeecs.v21.i3.pp1731-1738.)

3- The IQ-OTH/NCCD lung cancer dataset
can be cited as :
(alyasriy, hamdalla; AL-Huseiny, Muayed  (2023), “The IQ-OTH/NCCD lung cancer dataset”, Mendeley Data, V4, doi: 10.17632/bhmdr45bh2.4)