cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28532705.v1
title: JDS_26150 Supporting Information

description: Noroviruses are a leading cause of foodborne illnesses, responsible for over 50% of global gastroenteritis outbreaks. While reverse transcriptase polymerase chain reaction (RT-PCR) and other nucleic acid amplification methods are crucial for norovirus detection, their reliance on specialized equipment highlights the urgent need for more accessible detection methods. Herein, we propose an isothermal cascade signal amplification assay that integrates catalytic hairpin assembly (CHA) and CRISPR/Cas12a for rapid and accurate detection of norovirus in food samples. By incorporating the advantages of CHA and CRISPR/Cas12a, the dual signal enhancement sensing strategy can achieve high sensitivity low to 14 fM within 70 min, and good specificity in adenovirus, human enterovirus, rotavirus, and other interfering agents. The proposed dual enhancement strategy for norovirus detection has satisfactory accuracy and acceptable recoveries in milk samples compared to RT-PCR assay, and holds promise for improving food safety monitoring, particularly in dairy products.
DOI: 10.6084/m9.figshare.689805.v1
title: Code Review Defects

description: This document contains further details of the code review defects presented in [1]. Description of each defect type is given as well as notes describing the most typical cases. [1] Mäntylä, M. V. and Lassenius, C. "What Types of Defects Are Really Discovered in Code Reviews?" IEEE Transactions on Software Engineering, vol. 35, no 3, May/June 2009, pp. 430-448, Available online: http://dx.doi.org/10.1109/TSE.2008.71 http://lib.tkk.fi/Diss/2009/isbn9789512298570/article5.pdf
DOI: 10.17632/gys62x6z6n
title: Data for: Aerobic release and biodegradation of dissolved organic matter from frozen peat: Effects of temperature and heterotrophic bacteria

description: Physico-chemical data of aerobic incubation of frozen peat and frozen peat leachate at 4, 25 and 45 °C, with the addition of heterotrophic culturable bacteria.
DOI: 10.17632/wzjv88gftp
title: Python & R Scripts

description: The six scripts used to execute the quantitative CT workflow. Script 1 to 5 are made in Python, 6 in R.
DOI: 10.6084/m9.figshare.12814869.v1
title: FF_lrelu_2020-05-04T13:56:02

description: Thesis model files
DOI: 10.6084/m9.figshare.24226306.v1
title: Data from: Prenatal cues of predation risk modulate the lasting effects of postnatal predator exposure in gull chicks.

description: Prenatal environmental cues can affect embryo development to produce suitable phenotypes that match the expected conditions after birth. In gulls, parental alarm calls during incubation affect postnatal antipredator behaviour, but how chicks integrate reliable prenatal and postnatal information and how this influences their development and viability remain unclear. In this study, we performed a match/mismatch experiment in which we manipulated acoustic cues of predator presence during embryonic development (adult alarm calls vs. colony noise) and simulated predator intrusions during nestling period (mink vs. rabbit decoy) in yellow-legged gulls (<i>Larus michahellis</i>). Our results show that embryonic exposure to predator cues alters the antipredator responses of chicks in early postnatal life as indicated by increased tonic immobility. Chicks exposed to adult alarm calls also displayed rapid crouching behaviour, but only in the absence of predators during the postnatal period. Chicks exposed to postnatal predator presence showed less frequent begging vocalizations. The chicks experiencing mismatched prenatal and postnatal cues of predator presence showed smaller skeletal size and greater genomic damage at fledging, compared to those developed in matched environments. Our results highlight the importance of the late embryonic stage in shaping phenotypic outcomes, with fitness consequences depending on alignment with the postnatal environment.
DOI: 10.6084/m9.figshare.28039832.v3
title: <b>A</b><b> </b><b>G</b><b>lobal</b><b> </b><b>R</b><b>eview of Monitoring Cropland Abandonment</b><b> </b><b>U</b><b>sing Remote Sensing:</b><b> </b><b>Temporal</b><b>-spatial</b><b> </b><b>P</b><b>atterns, Causes, Ecological Effects, and Future Prospects</b>

description: Using remote sensing methodologies to uncover the temporal-spatial patterns of cropland abandonment (CA) offers significant advantages at bothmacro scales and in real time. However, the current literature lacks a systematic review of specific typologies and methods regarding the application of remote sensing technology to CA monitoring. To address this knowledge gap, we systematically review remote sensing-based methods for monitoring CA, its causes, and ecological effects. Our results show thatthe methods for monitoring abandoned cropland can be classified into two major categories: those based on image spectral featuresand thosebased on land covertemporal trajectories and vegetation phenologydynamics. Among the eight subcategories, vegetation phenology and dynamic methods exhibit the highest average overall accuracy at 89.33±3.37%, compared to the other methods. It is crucial to assess the causes of CA through remote sensing observations, such as road density, spatial information of agricultural infrastructure, and the ecological effects resulting from abandonment, including food loss risks, carbon sequestration, wildfire risk, evapotranspiration, wilderness quality, biodiversity, and climate change. Through this systematic review, we argue that remote sensing has greater potential for monitoring CA in the future, with room for further progress in the classification of abandoned cropland types, the observation of fragmented and temporally unstable parcels, and the ecological effects in different scenarios. More importantly, we presenta trinity CA monitoring framework based on the cause-pattern-effect pillars, which offers a novel perspective for comprehensive research on CA. Overall, our work provides a systematic and insightful perspective for advancing remote sensing research on CA
DOI: 10.6084/m9.figshare.28342832.v1
title: Survey results.xlsx

description: Discharge summary training workshop survey results
DOI: 10.6084/m9.figshare.28668398.v2
title: <b>Predicting Stroke Risk Dataset</b>

description: This study addresses stroke as a critical global health issue by employing a comprehensive, data-driven approach to improve early risk prediction and intervention. Utilizing a dataset of 5,110 records, the research combines statistical analysis, machine learning (ML) classification, clustering techniques, and survival modeling to identify key predictors of stroke. Descriptive analysis highlights age, average glucose level, BMI, hypertension, and heart disease as the most significant risk factors, with stroke prevalence reaching 13.25% among hypertensive individuals and 17.03% among those with heart disease. Former and current smokers also demonstrate elevated stroke risk. Clustering using PCA and t-SNE reveals high-risk groups characterized by older age and high glucose levels. ML evaluation shows that XGBoost provides the best precision-recall balance, while Naïve Bayes achieves the highest recall (0.404), offering greater sensitivity to stroke detection. Feature importance analysis consistently ranks glucose, BMI, and age as dominant predictors, with XGBoost assigning high weight to cardiovascular conditions. Survival analysis using Kaplan-Meier and Cox regression models shows stroke risk increases sharply after age 60, with hypertension linked to a 31.9% higher risk. The results emphasize the value of early screening and targeted intervention, suggesting future improvements via class-balancing techniques and real-time clinical tools.
DOI: 10.17632/cj5d332zyv
title: Bridge failures/collapses 

description: Database used in the following articles: 

1. Can Past Failures Help Identify Vulnerable Bridges to Extreme Events? A Biomimetical Machine Learning Approach (DOI: 10.1007/s00366-019-00874-2)
2. Abedi, M., and M. Z. Naser. "RAI: Rapid, Autonomous and Intelligent machine learning approach to identify fire-vulnerable bridges." Applied Soft Computing 113 (2021): 107896.
3. Kodur, V. K., and M. Z. Naser. "Classifying bridges for the risk of fire hazard via competitive machine learning." Advances in Bridge Engineering 2.1 (2021): 1-12.
DOI: 10.17632/rpzsh6dnjv
title: A study on mathayomsuksa ii students achievement in social studies, religion and culture and critical thinking ability through the instructional methods based on 4 mat and 6 thinking hats

description: The purpose of this was to find the studying mathayomsuksa II students achievement in social studies, religion and culture and critical thinking ability through the instructional methods based on 4 Mat and 6 thinking hats.
The sample of the study were 80 students of Mathayomsuksa II of Srinakharinwirot University Laboratory School during the second semester of the 2010 academic year. They were randomly selected by using cluster random sampling method and assigned into two groups, with 40 students in each. The first experimental group was taught through learning using 4 Mat where as the second was taught through learning using 6 thinking hats. It took
20 teaching periods for each group. The research design of this study was Randomized group Pretest - Posttest. The t – test Independent sample and t – test for dependent sample (Different score) was used for data analysis. The results of this study indicated that.
1. The students approached by 4 Mat methods with 6 thinking hats model had achievement on social studies, religion and culture was not different.
2. The students approached by 4 Mat methods had their higher Post-Test achievement on social studies, religion and culture than pre-test.
3. The students approached by 6 thinking hats model had their higher Post-Test achievement on social studies, religion and culture than pre-test.
4. The students approached by 4 Mat methods with 6 thinking hats model had critical thinking ability was not different.
5. The students approached by 4 Mat methods had critical thinking ability higher Post-Test than pre-test.
6. The students approached by 6 thinking hats model had critical thinking ability higher Post-Test than pre-test.
DOI: 10.6084/m9.figshare.28098074.v1
title: Two new species of Placomaronea in Peru

description: ITS alignment and log files from iqtree and mrbayes.
DOI: 10.6084/m9.figshare.7686233.v1
title: Additional file 7: of Rootstock-induced molecular responses associated with drought tolerance in sweet orange as revealed by RNA-Seq

description: Table S6. Differentially expressed genes related to transcription factors and protein kinases in leaves of sweet orange (Citrus sinensis) grafted on ‘Rangpur’ lime. (XLSX 23 kb)
DOI: 10.6084/m9.figshare.9792680.v1
title: AR 0.1 distribution curve fitting.xlsx

description: Curve fitting parameters out put from MATLAB.
DOI: 10.17632/xg3mrv8s3b
title: Data for: Choosing a Good Toolkit: Reinforcement Learning

description: Simulation programs and results
DOI: 10.17632/zkbpdfhbh6
title: Raw data from spectroscopic ellipsometer

description: This dataset contains the Psi and Delta spectra obtained from the spectroscopic ellipsometer. Also, it contains the data after modelling with B-spline and Psemi_Tri general oscillator model. Furthermore, absorption and transmission spectra obtained from the UV-Vis spectrometer is also included in the data set. We calculate the transmission spectra from the obtained optical properties from the SE modelling. Research data_calculate T_DIB file has the calculated transmission spectra for different thicknesses sample.
DOI: 10.6084/m9.figshare.14790132.v1
title: E.mollis Data Files

description: Genome data and gff files for <i>E. mollis</i>
DOI: 10.6084/m9.figshare.5296348.v2
title: Financial News unprocessed

description: Raw News JSON files
DOI: 10.6084/m9.figshare.7358057.v1
title: Statistical data for the 25 bathymetric cross-section profiles, Mariana Trench

description: 518 observation points, crossing 4 tectonic plates (Mariana, Caroline, Pacific and Philippine). Statistical data (Min, Max, Mean, quantiles), nr of observation points by plates, nr. of points within the igneous volcanic areas, slope angle, slope class, sediment thickness, class of hillshade, aspect degree. Data are received from the QGIS vector layers by spatial analysis.
DOI: 10.6084/m9.figshare.27858228.v1
title: Data used in "Turbulence and Bedload Transport in Submerged Vegetation Canopies" (2024WR037694)

description: Profiles of mean and turbulent flow statistics in "Turbulence and Bedload Transport in Submerged Vegetation Canopies" (2024WR037694).
DOI: 10.6084/m9.figshare.28590062.v1
title: The latest genomic data of three sea buckthorn species.

description: Here contains the genome data of male <i>Hippophae gyantsensis</i>, female <i>Hippophae salicifolia</i> and male <i>Hippophae salicifolia</i>. Male <i>Hippophae salicifolia</i> included two sets of haplotype data, hap1 and hap2.
DOI: 10.6084/m9.figshare.28892351.v1
title: jurnal iza auliatul muna.pdf

description: <b>ABSTRA</b>Penelitian ini mengkaji urgensi adab menuntut ilmu bagi mahasiswa keperawatan dalam konteks implementasi nilai-nilai Islam dalam etika profesional pelayanan kesehatan. Tujuan penelitian adalah memahami pentingnya adab dalam menuntut ilmu dan aplikasinya dalam pembentukan etika profesional mahasiswa keperawatan. Menggunakan pendekatan kualitatif melalui studi pustaka, penelitian ini menganalisis literatur klasik dan kontemporer mengenai adab, pendidikan karakter, dan etika profesi kesehatan. Hasil penelitian menunjukkan bahwa adab dalam menuntut ilmu berperan krusial dalam membentuk karakter mahasiswa keperawatan yang tidak hanya kompeten secara akademis, tetapi juga memiliki integritas moral dan etika yang tinggi. Kesimpulannya, penerapan nilai-nilai adab dan prinsip etika dalam praktik keperawatan dapat meningkatkan profesionalisme dan kualitas pelayanan kesehatan, serta menghasilkan tenaga medis berakhlak mulia yang bertanggung jawab terhadap kesejahteraan pasien. Rekomendasi praktis meliputi integrasi pendidikan etika Islami dalam kurikulum keperawatan, pengembangan program pelatihan etika berkelanjutan, dan penguatan peran advokasi perawat dalam melindungi hak-hak pasien.<i>Kata kunci: adab, etika keperawatan, nilai-nilai Islam, profesionalisme kesehatan</i>
DOI: 10.6084/m9.figshare.5674348.v1
title: Additional file 1: Table S1. of Transcription coupled repair and biased insertion of human retrotransposon L1 in transcribed genes

description: Characteristics of recovered de novo L1 inserts in CSA-deficient cells. This table describes the general characteristics of the L1 inserts isolated from the CSA-minus cells. Table S2. Characteristics of recovered de novo L1 inserts in stably complemented CSAâ +â cells. This table describes the general characteristics of the L1 inserts isolated from the cells that have been complemented to be CSA+. Table S3A&B. DNA sequences flanking rescued L1 inserts. S3A has the sequence data from the L1 insertion rescues for the CSA-minus cells, while S3B has similar data for the complemented cells that are now CSA plus. Table S4. FPKM values for de novo L1 inserts in HeLa cells that inserted within genes. (ZIP 130 kb)
DOI: 10.17632/4cnvn89pvn
title: Rhythm Training in the Classroom

description: This data is associated with the publication:
Zanto, T.P., Giannakopoulou, A., Gallen, C.L., Ostrand, A.E., Younger, J.W., Anguera-Singla, R., Anguera, J.A., Gazzaley, A. (2024). Digital rhythm training improves reading fluency in children. Developmental Science.

The csv data is formatted for use in JASP. I believe it will also be read correctly in SPSS.
DOI: 10.17632/9zfncc3t8j
title: Wild bats briefly decouple sound production from wingbeats to increase sensory flow during prey captures
DOI: 10.17632/fzcmhhjs76
title: Stimulation Artifact Source Separation

description: Transcranial alternating current stimulation (tACS) can affect perception, learning and cognition, but the underlying mechanisms are not well understood. A promising strategy to elucidate these mechanisms aims at applying tACS while electric or magnetic brain oscillations targeted by stimulation are recorded. However, reconstructing brain oscillations targeted by tACS remains a challenging problem due to stimulation artifacts. Besides lack of an established strategy to effectively supress such stimulation artifacts, there are also no resources available that allow for the development and testing of new and effective tACS artefact suppression algorithms, such as adaptive spatial filtering using beamforming or signal-space projection. Here, we provide a full dataset comprising encephalographic (EEG) recordings across six healthy human volunteers who underwent 10-Hz amplitude-modulated tACS (AM-tACS) during a 10-Hz steady-state visually evoked potential (SSVEP) paradigm. Moreover, data and scripts are provided related to the validation of a novel stimulation artefact suppression strategy, Stimulation Artifact Source Separation (SASS), removing EEG signal components that are maximally different in the presence versus absence of stimulation. Besides including EEG single-trial data and comparisons of 10-Hz brain oscillatory phase and amplitude recorded across three conditions (condition 1: no stimulation, condition 2: stimulation with SASS, condition 3: stimulation without SASS), also power spectra and topographies of SSVEP amplitudes across all three conditions are presented. Moreover, data is provided for assessing nonlinear modulations of the stimulation artifact in both time and frequency domains due to heartbeats. Finally, the dataset includes eigenvalue spectra and spatial patterns of signal components that were identified and removed by SASS for stimulation artefact suppression at the target frequency. Besides providing an valuable resource to assess properties of AM-tACS artifacts in the EEG, this dataset allows for testing different artifact rejection methods and offers in-depth insights into the workings of SASS.
DOI: 10.6084/m9.figshare.14519463.v1
title: Data for Molecular diet analysis of the marine fish-eating bat, Myotis vivesi, and potential mercury exposure

description: Data analyzed in the paper. <br>
DOI: 10.6084/m9.figshare.15111990.v1
title: Supplementary Material for: Incidental Bladder Cancer Found on Cystoscopy during Prostate Biopsy: Prevalence, Pathological Findings, and Oncological Outcome

description: <b><i>Introduction:</i></b> We examined the prevalence, pathological findings, and oncological outcomes of incidental bladder cancer found on cystoscopy among patients eligible for prostate biopsy (PB). <b><i>Methods:</i></b> We retrospectively reviewed 803 patients who underwent cystoscopy prior to PB between January 2010 and September 2020. In cases of bladder tumor-like findings on cystoscopy, biopsy or transurethral resection of the bladder tumor was performed. The primary and secondary outcomes were the prevalence of incidental bladder cancer and pathological and oncological outcomes of incidental bladder cancer, respectively. <b><i>Results:</i></b> Incidental findings were observed in 31/803 patients (3.9%). Bladder tumor-like findings were found in 24/803 patients (3%), while 9/803 patients (1.1%) were pathologically diagnosed with urothelial carcinoma. The stage and grade of incidental bladder cancer were pTa in 8/9 patients and pT1 in 1/9 and low grade in 8/9 and high in 1/9, respectively. The median tumor size of the papillary pedunculated type was 0.5 cm. At 26-month median follow-up, no recurrence was observed. <b><i>Conclusion:</i></b> Cystoscopy during PB may yield incidental bladder cancer findings, although the prevalence is very low. Incidental bladder cancer was of low stage and grade, which seemed unrelated to survival. Moreover, performing routine cystoscopy in conjunction with PB is not recommended as it may lead to overdiagnosis of low-risk bladder cancer.
DOI: 10.17632/3yfxnh5bn5
title: Diatomic-py: A Python module for calculating the rotational and hyperfine structure of 1Σ molecules

description: We present a computer program to calculate the quantised rotational and hyperfine energy levels of 1Σ diatomic molecules in the presence of dc electric, dc magnetic, and off-resonant optical fields. Our program is applicable to the bialkali molecules used in ongoing state-of-the-art experiments with ultracold molecular gases. We include functions for the calculation of space-fixed electric dipole moments, magnetic moments and transition dipole moments.
DOI: 10.17632/pmbc875pr7
title: Potato Disease Recognition Dataset

description: 1. Potatoes provide nutrition, along with rice and wheat. Additionally, potatoes are easily digestible as a food. Potatoes contain a good amount of dietary energy. Moreover, they also contain vitamins and mineral salts. Potatoes can be used to prepare various delicious dishes, including sweets, semai, and various types of bhartas. In addition to eating curry, housewives and girls can benefit financially by processing and selling chips. 2. Potato is the most popular vegetable among Indians. Its role in food and nutrition is unparalleled. Due to the widespread cultivation and use of potatoes in the past year, there has been an increase in potato production. Potatoes are susceptible to various diseases at different times. Among them, some notable diseases have been discussed in this potato dataset. 3. Diseases in crops pose a significant challenge to agricultural production, impacting the quality and productivity of the crops. Due to environmental factors, diseases in crops can have adverse effects on both yield and quality. For instance, potato diseases can negatively impact the yield and quality of potatoes, leading to significant economic losses for farmers. Traditional methods of identifying and managing crop diseases are often time-consuming, labor-intensive, inefficient, and subjective. 4. Such classification and identification tasks have been a promising area for computer vision in recent years. 5. A large dataset of five different potato classes—Healthy Potato, Blackspot Bruising Disease, Soft Rot Disease, Brown Rot Disease, and Dry Rot Disease—is shown in order to create machine vision-based algorithms. 6. In this dataset, there are 495 original images of potatoes. Then, in order to increase the number of data points, shifting, flipping, zooming, shearing, brightness enhancement, and rotation techniques are used to create a total of 3465 augmented images from these original images.