cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/cshjdvp7x2
title: Good And Bad Classification Of Boiled Rice

description: For the Good and Bad Classification of Boiled Rice project, the dataset comprises 1000 samples, evenly distributed between two classes: 500 "good" boiled rice samples and 500 "bad" boiled rice samples. The classification task aims to distinguish between the quality of boiled rice, with "good" indicating well-cooked rice and "bad" representing overcooked, undercooked, or otherwise poorly cooked rice.

Dataset Composition:
Total Samples: 1000
Good Rice: 500 samples
Bad Rice: 500 samples
Data Features:
Each sample is characterized by multiple features that reflect both physical and sensory attributes of the boiled rice. These features help capture the differences in quality between the good and bad samples. The specific features may include:

Moisture Content:

A critical determinant of rice quality, this feature captures the water content in the boiled rice, which is expected to vary between good and bad samples.
Texture Score:

Measured either through machine-based or manual sensory evaluation, texture indicates firmness or stickiness. Good boiled rice typically has an ideal firmness, while bad samples may be too hard or too mushy.
Color Measurement:

The color of the rice, usually quantified in terms of brightness or yellowness. Overcooked rice might appear darker or yellowish, while properly boiled rice retains a whiter appearance.
Aroma:

The intensity of aroma could serve as a distinguishing feature, as poorly cooked rice may emit different smells, often indicating burning, overcooking, or spoilage.
Cooking Time:

The duration for which the rice was boiled. Too short or too long cooking times generally correlate with bad rice quality.
Grain Structure:

A measure of grain integrity after cooking, indicating if the grains are intact, broken, or overly sticky. Good rice samples are expected to have individual, unbroken grains, whereas bad samples may show broken or clumped grains.
pH Level:

pH value may influence taste and texture, which is a subtle yet useful parameter to assess the quality of boiled rice.
Sensory Rating:

Subjective ratings provided by testers on the overall quality of the rice. This feature can be aggregated from multiple sensory dimensions (texture, taste, aroma) and serves as a holistic quality indicator.
Data Collection:
The samples were obtained from controlled cooking environments, ensuring consistency in raw rice type and cooking conditions. Variability between good and bad samples was introduced intentionally by altering parameters like water-to-rice ratio, cooking time, and heat intensity. The evaluation of each sample’s quality was carried out through both objective methods (e.g., moisture analysis, texture measurement) and subjective assessments (e.g., sensory panel evaluations).

Data Preprocessing:
Before applying machine learning models, the dataset underwent the following preprocessing steps:

Normalization/Standardization: Continuous variables such as moisture content and cooking time were normalized to ensure
DOI: 10.17632/ww5dfy53cw
title: COVID-19 CNN MFCC classifier

description: High accuracy classification of COVID-19 coughs using Mel-frequency cepstral coefficients and a Convolutional Neural Network with a use case for smart home devices. Diagnosing COVID-19 early in domestic settings is possible through smart home devices that can classify audio input of coughs, and determine whether they are COVID-19. Research is currently sparse in this area and data is difficult to obtain. How- ever, a few small data collection projects have en- abled audio classification research into the application of different machine learning classification algorithms, including Logistic Regression (LR), Support Vector Machines (SVM), and Convolution Neural Networks (CNN). We show here that a CNN using audio converted to Mel-frequency cepstral coefficient spectrogram images as input can achieve high accuracy results; with classification of validation data scoring an accuracy of 97.5% cor- rect classification of covid and not covid labelled audio. The work here provides a proof of concept that high accuracy can be achieved with a small dataset, which can have a significant impact in this area. The results are highly encouraging and provide further opportunities for research by the academic community on this important topic. Preprint: https://www.researchgate.net/publication/343376336_High_accuracy_classification_of_COVID-19_coughs_using_Mel-frequency_cepstral_coefficients_and_a_Convolutional_Neural_Network_with_a_use_case_for_smart_home_devices
DOI: 10.6084/m9.figshare.7285061.v1
title: Supplementary Material for: Leiomyosarcoma of the Urinary Bladder in Adult Patients: A Systematic Review of the Literature and Meta-Analysis

description: <b><i>Purpose:</i></b> Leiomyosarcoma of the urinary bladder is exceedingly rare. Most clinicians come across only a few cases during their career, and information regarding treatment and outcome is scattered in the scientific literature. Interested clinicians and patients have to undertake troublesome search for treatment and outcome information. <b><i>Material and methods:</i></b> We performed a systematic review of the literature using the PubMed and Web of Science databases and included all identified cases published in English language between 1970 and June 2018 into a meta-analysis. Prior to the literature search, key questions were formulated and with the data obtained, answers to these questions should be derived. <b><i>Results:</i></b> We analyzed clinical data of 210 cases of urinary bladder leiomyosarcoma revealed by this review and seen in our institution. The mean age of patients was 52 years. The majority (75%) of the tumors was classified as high-grade sarcomas. We found no report of a prior radiation therapy to the pelvic organs, but some authors suggested an association between cyclophosphamide treatment and the development of bladder leiomyosarcoma, especially in patients with retinoblastoma. For the whole sample, we determined 5- and 10-year cancer-specific cumulative mortality rates of 38 and 50%. Patients with high-grade sarcomas had a trend toward a higher mortality compared with low-grade tumors (<i>p</i> = 0.0280). The most promising treatment option seems to be surgery (radical or partial cystectomy) with negative resection margins, possibly supplemented by chemotherapy or radiation. <b><i>Conclusion:</i></b> About half of patients with bladder leiomyosarcoma survived on the long run. Low-grade tumors may have a better outcome with, nevertheless, countable long-term mortality. For better assessment of that rare bladder tumor, its best treatment options, and the influence of neoadjuvant or adjuvant therapies on the outcome of patients, a larger series with long-term survival data is required.
DOI: 10.17632/2pwtrtcc72
title: ALERT (Analysis of Linguistic Extremism in Religious Text)

description: The widespread dissemination of religiously aggressive content on social media platforms poses significant threats to social cohesion and communal harmony. Social media has emerged as a prevalent venue for discussing diverse topics, including religion which frequently result in debates. These debates often fuel animosity, incite violence, and spread life-threatening messages that disrupt societal peace and security. To address this challenge, we developed a novel Bengali dataset, ALERT, accompanied by English translations, to identify and classify religious aggression in texts. 

The dataset was obtained from several online platforms, including Facebook, YouTube, blogs, online news portals, and group discussions. We executed multiple stages for data preprocessing, including the elimination of duplicates, special characters, emoji to improve the coherence of the dataset. Each instance in the dataset was annotated by two of the lists of four annotators with diverse academic, religious, and racial backgrounds, with any discrepancies resolved by expert review.

The ALERT dataset is a collection of 4,003 Bangla texts categorized as
1. hate speech (1,007), 
2. vandalism (998), 
3. life-threatening (994), 
4. no aggression (1,004).
The dataset is structured with the following fields:
• Annotator 1
• Annotator 2 
• Final Annotation
• Text
• English Translation 
Our developed dataset contains a mix of formal and informal Bangla texts, reflecting how people communicate in real life. Instead of simply labeling content as aggressive or not, it offers more detailed categories, helping with more precise content moderation. The dataset is publicly accessible for research purposes to promote innovation and collaboration within the Bengali NLP community.
DOI: 10.6084/m9.figshare.28806815.v2
title: SSVEP 40class dataset

description: 40-class Beta range stimuli, SSVEP-based BCI Speller datasets
DOI: 10.17632/n9kwxvxvwx
title: Skill Knowledge Attitude of Homestays in Terengganu, Malaysia

description: This dataset explains the competencies that include skill, knowledge, and attitude of entrepreneurs about digital marketing in the homestay industry in Terengganu, Malaysia.
DOI: 10.6084/m9.figshare.28457450.v1
title: GEE classification output for the Venezuelan Seagrass Mapping project

description: GEE classification output for the Venezuelan Seagrass Mapping.
DOI: 10.6084/m9.figshare.19750090.v2
title: GSE183904

description: 48 primary gastric cancer tumor samples, ranging from stages I to IV, distinct histologic subtypes (diffuse and intestinal), molecular subtypes (TCGA), primary tumors to distant (peritoneal) metastases, and matched normal gastric tissues.
DOI: 10.6084/m9.figshare.24080871.v1
title: Saved model parameters for Crack-Net

description: The Saved model parameters for Crack-Net
DOI: 10.6084/m9.figshare.27011998.v1
title: WF-PPG: A Wrist-finger Dual-Channel Dataset for Studying the Impact of Contact Pressure on PPG Morphology

description: Welcome to the WF-PPG dataset repository! This dataset, "WF-PPG: A Wrist-Finger Dual-channel Dataset," is designed to study the impact of wrist postures on Photoplethysmography (PPG) morphology. It is intended to facilitate research into how varying contact pressures between PPG sensors and the skin affect the quality of the PPG signals, particularly for wearable health monitoring applications.
DOI: 10.17632/6w2k42kytt
title: 2023 CODEX HCC article Segmentation output raw datasets

description: This file contains the Segmentation results by StarDist in Qupath. The analysis method can be found in the manuscript. 
Each TMA contains multiple regions in it. Each region represents a tissue spot in TMA. The clinical information was in HCC401_new.Rdata. Each row in the seg-file represents the information of a single cell, containing the marker intensity, the x and y coordinates, and some other segmentation-related information. 
HCC401_new.Rdata and Qupath cell segmentation ouptut.zip can serve as the input of Part 1 "discovery cohort pre-processing and cell type phenotype definition" in https://github.com/sanrishiguang/ChenleiLab_CODEX_HCC. And the output file of Part 1 with defined cell type/phenotype information was testing_allReg_seurat_._analysis_20220315_AllSubtypes_withoutartifact.csv. 
HCC401_new.Rdata and the output file of Part 1 are provided in https://data.mendeley.com/datasets/km2df7y256/1.
DOI: 10.17632/h6sw4dpnft
title: Intervention Programme - Smovey rings - Parkinsonians

description: Selected Data - results of dynamic tests of Timed up-and-go test (TUG), Full turn, and Standing up and static test of Upright stand in parkinsonians and control group - before, during and after a specialized intervention program with Smovey rings.
DOI: 10.6084/m9.figshare.13338923.v1
title: Table S1.docx

description: Risk of bias assessment of included studies using modified Newcastle-Ottawa scale
DOI: 10.6084/m9.figshare.19248926.v1
title: Non-mycorrhizal fungal presence within roots increases across an urban gradient in Berlin

description: The dataset used in the study "Non-mycorrhizal fungal presence within roots increases across an urban gradient in Berlin". Dataset includes:Site nameSite location (longitude and latitude)Dependent variables:AM-fungal presence (%)Arbuscule presence (%)Vesicle presence (%)Log vesicle presence (%)Coil presence (%)Log coil presence (%)Non-AM fungal presence (%)Root hair presence (%)Independent variables:PCA axis 1 - represeneting urbanityPCA axis 2 - representing soil chemistryPCA axis 3 - representing site connectivity
DOI: 10.6084/m9.figshare.22691233.v2
title: Untitled Item

description: The MIDOG++ dataset represents an extension of the data set used in the MIDOG 2021 and 2022 challenges. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The human and canine samples were processed and stained at different human and veterinary pathology laboratories with standard H&E dye and digitized with different digital whole slide image scanners. We provide labels for 11,937 mitotic figures that have been differentiated against 14,351 imposter cells in a blinded consensus by two pathologists and a final decision by a third pathologist for disagreed labels.
DOI: 10.6084/m9.figshare.24625350.v1
title: Prior features for PriLer models

description: Prior features used to build PriLer gene expression models
DOI: 10.6084/m9.figshare.25019879.v1
title: beetle_data_Laos_ORG-vs-CONV.csv

description: We present an updated version of our dataset for the classification of beetles into morphospecies. In this study, we examined beetle community composition in three organic and three conventional farming systems in Vientiane, Lao PDR. Our results indicate that beetle abundance was relatively consistent in both farm types, while species richness was higher in organic farming compared to conventional farming. Furthermore, predators were over 18 times more abundant, and insect pests 9 times less abundant, in organic farming, suggesting an enhanced pest control. Abundance and richness of beetles also exhibited seasonal variation during the year.These findings have enormous significance for the promotion of sustainable agriculture and the preservation of biodiversity in Southeast Asia and tropical countries in general, and they greatly advance our understanding of the ecological effects of various farming methods. They may also contribute to assisting government policy, particularly the Ministry of Agriculture, which plays a crucial role in promoting and supporting the development of organic agriculture in Lao PDR.
DOI: 10.6084/m9.figshare.26264708.v1
title: Data support for “Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks”

description: Numerical forecasting data in paper “Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks”.See also inHailun He, Benyun Shi, Yingjian Hao, Liu Feng, Xinyan Lyu, Zheng Ling. Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks. Atmospheric Research, 2024: 107578.https://doi.org/10.1016/j.atmosres.2024.107578<br><br>
DOI: 10.6084/m9.figshare.7629383.v1
title: An early divergence of plastids within an expanded cyanobacterial phylogeny

description: The files contained here are alignment files and phylogenetic trees relating to our paper, "An early divergence of plastids within an expanded cyanobacterial phylogeny". All files are labeled and listed by the figure number to which they correspond in the paper.
DOI: 10.17632/rgbh3ttfzn
title: Evaluating the Independence of Age, Sex, and Race in Judgment of Faces

description: Three experiments have been conducted in the current work. All experiments applied the Garner methodology to the facial dimensions of age, sex, and race. The main goal was to provide an exhaustive assessment of their dimensional relations. The degree of separability was evaluated in a pairwise fashion. Each experiment was designed to test one pair. In Experiment 1a and 1b, sex and race were entered into the Garner test. The dimensional separability of these social categories was investigated with an eye on the potential influence of a social bias on the level of separability (Johnson et al., 2012). It was assumed that the presence of a social bias (Experiment 1b) should increase the likelihood of integrality among these dimensions. Experiment 2 was set to assess the separabilty of sex and race. And Experiment 3 was aimed at evaluating the separability of age and sex. In combination, the three experiments covered all the possible pairing of these dimensions.
DOI: 10.6084/m9.figshare.5109766.v1
title: Pakistan Women's Health Data Deidentified.xlsx

description: This study was done in a highly affluent residential sector of Islamabad, Pakistan in order to assess the prevalence of depression and understand if an association exists between barriers to healthcare access and mental illness. Between May and June 2016, an anonymous, cross-sectional study was carried out amongst women above age 18 living in the I-8 sector of Islamabad with the help of 18 key informants. Convenience sampling was used due to significant security restrictions present. The survey was based off the Pakistan Demographic Health Survey, and included the Center for Epidemiological Studies Depression (CESD) scale. The study instrument was then translated into Urdu, pre-tested before administration, and distributed in both Urdu and English. Data was cleaned and analyzed using Microsoft Excel and Stata 14. Overall, 103 women filled out the overall survey of which 88.3% filled out the CESD scale.<br><br>Question numbers on the end of variable names are corresponding to the survey question numbers. <br>
DOI: 10.6084/m9.figshare.12921941.v1
title: P16INK4a expression in patients with penile cancer

description: Background<br>Infection with human papillomavirus (HPV) is reported to be present in 30–50% of penile cancer cases. The immunohistochemical test for p16<sup>INK4a</sup> is used as an indicator of the presence of HPV and as a prognostic marker for squamous cell carcinomas in various sites. However, the role of this marker in penile carcinoma has not yet been completely elucidated. The aim of this study was to analyze whether the expression of p16<sup>INK4a</sup> is associated with the presence of HPV, histological parameters, and survival in penile cancer.<br>Methods<br>A study was conducted from 2014 to 2016 that included 55 patients with penile carcinoma. HPV DNA was detected through PCR using fresh tumor tissue, and immunohistochemistry was performed for analysis of p16<sup>INK4a</sup> protein using paraffin-embedded tissue. Evaluation of histological parameters was performed following complete embedding of the tumor tissue in paraffin.<br>Results<br>HPV DNA (low-risk and high-risk genotypes) was found in 49 (89.1%) cases, and 46/49 (93.9%) showed high-oncogenic risk HPV (HR-HPV). Of the 22 cases positive for p16<sup>INK4a</sup>, HR-HPV DNA was present in 21 (95.5%) (p = 0.032). Regarding histological parameters, p16<sup>INK4a</sup> and HR-HPV were significantly associated only with tumor subtype (p = 0.036 and p = 0.032, respectively); all carcinomas with basaloid characteristics were positive for p16<sup>INK4a</sup>. Although HPV+ patients had a higher disease-free survival (p &lt;0.001), p16<sup>INK4a</sup> expression was not associated with patient survival.<br>Conclusions<br>Our study, using fresh tissue samples, showed the highest incidence of HPV compared to that observed in the literature. Expression of the p16<sup>INK4a</sup> protein was significantly associated with the presence of HR-HPV and this expression may serve as a marker for the presence of the virus. The p16<sup>INK4a</sup> protein was not associated with the histological prognostic parameters, with the exception of tumor subtype, nor with patient survival. In the results, we showed that the objective of the present study was reached.
DOI: 10.17632/zc9z7m7gcd
title: Multilayer Cyberattacks Identification and Classification Using Machine Learning in Internet of Blockchain (IoBC)-Based Energy Networks.

description: • The data provides insights into cyberattacks, helping in the development of predictive models that can anticipate future threats and vulnerabilities in energy and power systems.
• Data analysis helps in customizing security protocols and measures tailored to specific threats and vulnerabilities in distributed energy systems, enhancing overall system security.
• Data contributes to a better understanding of the current security posture of the energy and power systems, aiding in strategic decision-making and resource allocation for cybersecurity.
• Cybersecurity and smart grid agencies, along with other stakeholders, can leverage these datasets to develop a more intelligent and resilient data exchange network. This forward-thinking strategy will help in identifying and mitigating different types of cyberattacks, ensuring the protection of the confidentiality of employees, companies, and clients.
DOI: 10.6084/m9.figshare.12774539.v1
title: Reference data for WhichTF software

description: To identify functionally important transcription factors (TFs), we present WhichTF, a computational method that ranks TFs based on experimentally characterized chromatin accessibility measurements. <br> This dataset contains the reference data for this new method described in the following paper: <br> Y. Tanigawa, E. S. Dyer, and G. Bejerano. WhichTF is dominant in your open chromatin data? <em>PLOS Comput Biol</em> <strong>18</strong>(8): e1010378. (2022). https://doi.org/10.1371/journal.pcbi.1010378 <br> <br> Here, we provide the pre-computed reference for the software. There are 4 tar.gz compressed files, each of them correspond to one genome assembly of human or mouse genomes (human: hg19 and hg38 and mouse: mm9 and mm10). <br> Please see our manuscript and our Bitbucket repository (https://bitbucket.org/bejerano/whichtf) for more information about our method and the software.<br> If you use this dataset, please cite our pre-print.
DOI: 10.6084/m9.figshare.19607085.v1
title: SSR marker

description: Marker development of Solanum tuberosum cDNA sequences