Reichsanzeiger-GT: An OCR ground truth dataset based on the historical newspaper "Deutscher Reichsanzeiger und Preußischer Staatsanzeiger" (German Imperial Gazette and Prussian Official Gazette) (1819-1945).

Reichsanzeiger-GT is a ground truth dataset for OCR training and evaluation based on the historical German newspaper "Deutscher Reichsanzeiger und Preußischer Staatsanzeiger" (German Imperial Gazette and Prussian Official Gazette), which was published from 1819 to 1945 and printed mostly in the typeface Fraktur (Black Letter). The dataset consists of 101 newspaper pages for the years 1820-1939, that cover a wide variety of topics, page layouts (lists, tables, and advertisements) as well as different typefaces. Using the transcription software Transkribus and the open-source OCR engine Tesseract we automatically created and manually corrected layout segmentations and transcriptions for each page, resulting in 65,563 text regions, 412 table regions, 119,429 text lines and 490,679 words. By applying transcription guidelines that preserve the printing conditions, the dataset contains language and printing specific phenomena like the historical use of glyphs like long s (s), rotunda r (ꝛ), and historical currency symbols (M, ₰) among others. The dataset is provided in two variants in PAGE XML format. The first one contains ground truth data with table regions transformed to text regions for easier processing. The second variant preserves all table regions. Researchers can reuse this dataset to train new or finetune existing text recognition or layout segmentation models. The dataset can also be used to evaluate the accuracy of existing OCR models. Using specific, community driven transcription guidelines our dataset is easily interoperable and reusable with other datasets based on the same transcription level.

The effect of value on context and target recollection in memory for truth and falsity.

Memory for truth and falsity has recently been investigated from the perspective of the dual-recollection theory, showing better context and target recollection for truth than falsity. In this paper, we examine whether these memory effects obtained for true statements are similar to the value effect, whereby true statements are given higher priority in encoding. For this purpose, we implemented value-directed remembering (VDR) into the conjoint-recognition paradigm. In our first experiment, the primary goal was to verify how VDR influences the processes defined by dual-recollection theory. At study, prioritized/important items were linked to higher numerical values (e.g., 10), while unimportant ones had lower values (e.g., 1). At test, the participants' task was to recognize whether a particular sentence was important, unimportant, or new. We found that both context and target recollection were better for important items. In the second experiment, the main goal was to study the combined effects of importance and veracity on memory. In the between-subjects design, participants were monetarily rewarded for memorizing true or false sentences. The results demonstrated differences in the ability to prioritize truth over falsity. Specifically, we found a substantial increase in context recollection for prioritized true information but not for prioritized false information. Moreover, we found higher context recollection for true than false sentences in the true-prioritized condition, but not in the false-prioritized condition. These results indicated that people are able to prioritize true information better than false, and suggested that memory for truth may be a special case of the value effect.

Illusions of knowledge due to mere repetition.

Repeating information increases people's belief that the repeated information is true. This truth effect has been widely researched and is relevant for topics such as fake news and misinformation. Another effect of repetition, which is also relevant to those topics, has not been extensively studied so far: Do people believe they knew something before it was repeated? We used a standard truth effect paradigm in four pre-registered experiments (total N = 773), including a presentation and judgment phase. However, instead of "true"/"false" judgments, participants indicated whether they knew a given trivia statement before participating in the experiment. Across all experiments, participants judged repeated information as "known" more often than novel information. Participants even judged repeated false information to know it to be false. In addition, participants also generated sources of their knowledge. The inability to distinguish recent information from well-established knowledge in memory adds an explanation for the persistence and strength of repetition effects on truth. The truth effect might be so robust because people believe to know the repeatedly presented information as a matter of fact.

A template for creating and sharing ground truth data in digital forensics.

Ground truth data (GTD) is used by those in the field of digital forensics (DF) for a variety of purposes including to evaluate the functionality of undocumented, new, or emerging technology and services and the digital traces left behind following their usage. Most accepted and reliable trace interpretations must be derived from an examination of relevant GTD, yet despite the importance of it to the DF community, there is little formal guidance available for supporting those who create it, to do so in a way that ensures any data is of good quality, reliable, and therefore usable. In an attempt to address this issue, this work proposes a minimum standard of documentation that must accompany the production of any GTD, particularly when it is intended for use in the process of discovering new knowledge, proposing original interpretations of a digital trace, or determining the functionality of any technology or service. A template structure is discussed and provided in Appendix S1 which sets out a minimum standard for metadata describing any GTD's production process and content. It is suggested that such an approach can support the maintenance of trust in any GTD and improve the shareability of it.

The ambiguity of "true" in English, German, and Chinese.

Through a series of empirical studies involving native speakers of English, German, and Chinese, this paper reveals that the predicate "true" is inherently ambiguous in the empirical domain. Truth statements such as "It is true that Tom is at the party" seem to be ambivalent between two readings. On the first reading, the statement means "Reality is such that Tom is at the party." On the second reading, the statement means "According to what X believes, Tom is at the party." While there appear to exist some cross-cultural differences in the interpretation of the statements, the overall findings robustly indicate that "true" has multiple meanings in the realm of empirical matters.

Truth for the Moment and Importance to Nursing.

In the article that follows the authors present information focused on nursing care delivery involving Neuman systems theory and improving the stress and stability. The authors then follow up with a clinical scenario which utilizes the Neuman system model as a means to prevent and ameliorate aggression and violence. The structure and evidence guided by Betty Neuman's systems model centers on managing and reducing stresses and working towards reconstitution. The thoughts contained in this article highlight some considerations regarding the importance of truth and truth for the moment for the nursing discipline.

Ground penetrating radar at work: A realistic perspective on utility surveying in the Netherlands through a comprehensive ground-truth dataset.

This dataset provides a comprehensive compilation of Ground Penetrating Radar (GPR) surveys across 125 utility surveying activities in the Netherlands. The dataset details the specific use of GPR in each authentic real-life utility surveying activity, whether employed independently or as a complementary tool alongside existing surveying methods, with or without post-processing. The dataset includes 959 radargrams, ground-truth information obtained from trial trenches, and an inventory of construction, geophysical, infrastructural, and technical features. The GPR utilised in all activities is an air-coupled radar with a 500 MHz frequency antenna, a GNSS RTK positioning system, and a measuring wheel encoder. This ground-truth dataset provides researchers with a valuable resource to further assess the practical efficacy of GPR as a utility surveying method, refine radargram processing algorithms and techniques, and explore the possibilities of predictive modelling.

Elementary school-aged children's perceptions of academic dishonesty: Definitions and moral evaluations of cheating behaviors in school.

A total of 76 children (Mage = 9 years 5 months, SD = 2.22 years) participated in a structured interview about their experiences with and knowledge of academic dishonesty. Overall, 27% of the sample reported having cheated in school. Most of these children were 10 to 13 years old, and the most prevalent form of cheating behavior reported was using forbidden materials during a test. Children's age group was a significant positive predictor of their reported cheating history; however, no significant difference was found between children's gender and engagement with cheating. Children's moral evaluations of cheating did not predict their reported cheating history, nor did children's parents' cheating history. Vignette type (cheating vs. non-cheating), age group, and the interaction between vignette type and age group were significant predictors of children's ability to accurately identify behaviors that constitute cheating. Children rated cheating behaviors as significantly less moral than non-cheating behaviors. Overall, the current results provide insight into what forms of cheating behavior children engage in at the elementary school-age level.

Fit for Purpose Approach To Evaluate Detection of Amino Acid Substitutions in Shotgun Proteomics.

Amino acid substitutions (AASs) alter proteins from their genome-expected sequences. Accumulation of substitutions in proteins underlies numerous diseases and antibiotic mechanisms. Accurate global detection of AASs and their frequencies is crucial for understanding these mechanisms. Shotgun proteomics provides an untargeted method for measuring AASs but introduces biases when extrapolating from the genome to identify AASs. To characterize these biases, we created a "ground-truth" approach using the similarities betweenEscherichia coli and Salmonella typhimurium to model the complexity of AAS detection. Shotgun proteomics on mixed lysates generated libraries representing ∼100,000 peptide-spectra and 4161 peptide sequences with a single AAS and defined stoichiometry. Identifying S. typhimurium peptide-spectra with only the E. coli genome resulted in 64.1% correctly identified library peptides. Specific AASs exhibit variable identification efficiencies. There was no inherent bias from the stoichiometry of the substitutions. Short peptides and AASs localized near peptide termini had poor identification efficiency. We identify a new class of "scissor substitutions" that gain or lose protease cleavage sites. Scissor substitutions also had poor identification efficiency. This ground-truth AAS library reveals various sources of bias, which will guide the application of shotgun proteomics to validate AAS hypotheses.

A comprehensive lung CT landmark pair dataset for evaluating deformable image registration algorithms.

PURPOSE: Deformable image registration (DIR) is a key enabling technology in many diagnostic and therapeutic tasks, but often does not meet the required robustness and accuracy for supporting clinical tasks. This is in large part due to a lack of high-quality benchmark datasets by which new DIR algorithms can be evaluated. Our team was supported by the National Institute of Biomedical Imaging and Bioengineering to develop DIR benchmark dataset libraries for multiple anatomical sites, comprising of large numbers of highly accurate landmark pairs on matching blood vessel bifurcations. Here we introduce our lung CT DIR benchmark dataset library, which was developed to improve upon the number and distribution of landmark pairs in current public lung CT benchmark datasets. ACQUISITION AND VALIDATION METHODS: Thirty CT image pairs were acquired from several publicly available repositories as well as authors' institution with IRB approval. The data processing workflow included multiple steps: (1) The images were denoised. (2) Lungs, airways, and blood vessels were automatically segmented. (3) Bifurcations were directly detected on the skeleton of the segmented vessel tree. (4) Falsely identified bifurcations were filtered out using manually defined rules. (5) A DIR was used to project landmarks detected on the first image onto the second image of the image pair to form landmark pairs. (6) Landmark pairs were manually verified. This workflow resulted in an average of 1262 landmark pairs per image pair. Estimates of the landmark pair target registration error (TRE) using digital phantoms were 0.4 mm ± 0.3 mm. DATA FORMAT AND USAGE NOTES: The data is published in Zenodo at https://doi.org/10.5281/zenodo.8200423. Instructions for use can be found at https://github.com/deshanyang/Lung-DIR-QA. POTENTIAL APPLICATIONS: The dataset library generated in this work is the largest of its kind to date and will provide researchers with a new and improved set of ground truth benchmarks for quantitatively validating DIR algorithms within the lung.

The illusory certainty: Information repetition and impressions of truth enhance subjective confidence in validity judgments independently of the factual truth.

People not only judge repeatedly perceived information as more likely being true (the so-called truth effect) they also tend to be more confident after judging the validity of repeated information. These phenomena are assumed to be caused by a higher subjective feeling of ease (i.e., fluency) when processing repeated (vs. new) information. Based on the suggestion that a higher number of coherent mental activations is promoting a fluency experience, we argue that besides repetition an already existing information network, that is (nonspecific) prior knowledge, can enhance fluency. Following this argumentation, information repetition as well as the act of judging incoming information as being true (vs. false) should feed into subjective confidence - independently of the factual truth (when judging under uncertainty). To test this, we reanalyzed two published data sets and conducted a new study. In total, participants (N = 247) gave 29,490 truth judgments and corresponding ratings of subjective confidence while attending two judgement phases (i.e., 10 min and 1 week after the exposure phase in each experiment). Results showed that (a) repetition (in 3 of 3 data sets) and (b) impressions of truth (in 2 of 3 data sets) were systematically related to higher subjective confidence. Moreover, we found (c) a significant positive interaction between repetition and impressions of truth after both intervals in all data sets. Our analyses further underline the moderating effect of time: Influences of repetition significantly decreased with increasing time interval. Notably, the factual truth did not systematically affect any of the above reported effects.

Fast and accurate 3-D spine MRI segmentation using FastCleverSeg.

Accurate and efficient segmenting of vertebral bodies, muscles, and discs is crucial for analyzing various spinal diseases. However, traditional methods are either laborious and time-consuming (manual segmentation) or require extensive training data (fully automatic segmentation). FastCleverSeg, our proposed semi-automatic segmentation approach, addresses those limitations by significantly reducing user interaction while maintaining high accuracy. First, we reduce user interaction by requiring the manual annotation of only two or three slices. Next, we automatically Estimate the Annotation on Intermediary Slices (EANIS) using traditional computer vision/graphics concepts. Finally, our proposed method leverages improved voxel weight balancing to achieve fast and precise volumetric segmentation in the segmentation process. Experimental evaluations on our assembled diverse MRI databases comprising 179 patients (60 male, 119 female), demonstrate a remarkable 25 ms (30 ms standard deviation) processing time and a significant reduction in user interaction compared to existing approaches. Importantly, FastCleverSeg maintains or surpasses the segmentation quality of competing methods, achieving a Dice score of 94%. This invaluable tool empowers physicians to efficiently generate reliable ground truths, expediting the segmentation process and paving the way for future integration with deep learning approaches. In turn, this opens exciting possibilities for future fully automated spine segmentation.

Does Foreign-Accented Speech Affect Credibility? Evidence from the Illusory-Truth Paradigm.

In a pioneering study, Lev-Ari and Keysar (2010) observed that unknown statements are judged less credible when uttered with foreign accent compared to native accent. This finding was interpreted in terms of processing fluency; when intelligibility is reduced, the credibility of the message decreases. Here, we use the illusory truth paradigm to explore how accent affects credibility. In a between-participant design, participants were exposed to unknown statements uttered by native-accented or foreign-accented speakers. After a distractor task, the same statements were presented with new statements, and participants assessed their truthfulness. Truthfulness ratings were higher for repeated statements than for new statements, replicating the illusory truth effect. Contrary to the processing fluency hypothesis, the effect was similar in both the foreign-accented and native-accented speech groups. A new group of participants rated the speakers' voices on various social traits. A negative bias against foreign speakers was observed. However, this negative-bias did not affect truth ratings.The impact of foreign-accented speech on message credibility is discussed in the context of two factors, processing fluency and out-group stereotype activation.

Tamil handwritten palm leaf manuscript dataset (THPLMD).

Most palm leaf manuscripts are generally accessible in deteriorated condition, including cracks, discoloration, moisture and humidity, and insects bite. Such a manuscript is considered challenging in the research field. We captured deteriorated Tamil palm leaves around 262 dataset samples are 'Naladiyar(27)',' Tholkappiyam(221)', and' Thirikadugam(14)' which are genned up mortal health, discipline, authoritative text on Tamil grammar. We contribute the high-quality raw dataset with the aid of a Nikon camera, pre-enhance samples by editing software tool, and applied the Otsu threshold to deliver the ground images through binarization as readily accessible content presenting a highly time-consuming task to play a vital role in Machine/Deep/ Transfer learning, AI, and ANN.

Automatic caries detection in bitewing radiographs-Part II: experimental comparison.

OBJECTIVE: The objective of this study was to compare the detection of caries in bitewing radiographs by multiple dentists with an automatic method and to evaluate the detection performance in the absence of a reliable ground truth. MATERIALS AND METHODS: Four experts and three novices marked caries using bounding boxes in 100 bitewing radiographs. The same dataset was processed by an automatic object detection deep learning method. All annotators were compared in terms of the number of errors and intersection over union (IoU) using pairwise comparisons, with respect to the consensus standard, and with respect to the annotator of the training dataset of the automatic method. RESULTS: The number of lesions marked by experts in 100 images varied between 241 and 425. Pairwise comparisons showed that the automatic method outperformed all dentists except the original annotator in the mean number of errors, while being among the best in terms of IoU. With respect to a consensus standard, the performance of the automatic method was best in terms of the number of errors and slightly below average in terms of IoU. Compared with the original annotator, the automatic method had the highest IoU and only one expert made fewer errors. CONCLUSIONS: The automatic method consistently outperformed novices and performed as well as highly experienced dentists. CLINICAL SIGNIFICANCE: The consensus in caries detection between experts is low. An automatic method based on deep learning can improve both the accuracy and repeatability of caries detection, providing a useful second opinion even for very experienced dentists.

A Modular Implementation to Handle and Benchmark Drift Correction for High-Density Extracellular Recordings.

High-density neural devices are now offering the possibility to record from neuronal populations in vivo at unprecedented scale. However, the mechanical drifts often observed in these recordings are currently a major issue for "spike sorting," an essential analysis step to identify the activity of single neurons from extracellular signals. Although several strategies have been proposed to compensate for such drifts, the lack of proper benchmarks makes it hard to assess the quality and effectiveness of motion correction. In this paper, we present a benchmark study to precisely and quantitatively evaluate the performance of several state-of-the-art motion correction algorithms introduced in the literature. Using simulated recordings with induced drifts, we dissect the origins of the errors performed while applying a motion correction algorithm as a preprocessing step in the spike sorting pipeline. We show how important it is to properly estimate the positions of the neurons from extracellular traces in order to correctly estimate the probe motion, compare several interpolation procedures, and highlight what are the current limits for motion correction approaches.

Linguistic precision, and declared use of ChatGPT, needed for radiology literature.

There is a need to ensure the accuracy of linguistic descriptors in the medical literature, including that related to radiology, to allow peers and professionals to communicate ideas and scientific results in a clear and unambiguous manner. This letter highlights an issue that could undermine the clarity of scientific writing in radiology literature, namely the presence of non-standard terminology for established jargon, and emphasizes the need for authors to transparently declare the use of language editing services and AI-driven tools, such as ChatGPT, if these have been used to formulate text and ideas in their papers. Ultimately, clear radiology papers that are compliant with current publishing ethics will serve radiologists and patients well.

Breaking bad news in ophthalmology: a literature review / Comunicação de más notícias em oftalmologia: uma revisão de literatura

ABSTRACT Medical specialties have recognized that breaking bad news assists clinical practice by mitigating the impact of difficult conversations. This scenario also encourages various studies on breaking bad news in ophthalmology since certain ocular diagnoses can be considered bad news. Thus, the objective is to review the scientific literature on breaking bad news in ophthalmology. The literature databases like MEDLINE/PUBMED, EMBASE, LILACS, SCOPUS, COCHRANE, and SCIELO, were screened for related research publications. Two independent reviewers read all the articles and short-listed the most relevant ones. Seven articles, in the formats of original article, review, editorial, oral communication, and correspondence, were reviewed. Conclusively it reveals that ophthalmologists are concerned with communicating bad news effectively but lack related studies. Nevertheless, there is a growing realization that training in breaking bad news can increase physicians' confidence during communication, thus, benefiting the therapeutic relationship with the patient and his family. Therefore, it would be valuable to include breaking bad news training in the curriculum of residencies.

RESUMO O reconhecimento sobre a comunicação de más notícias como mitigadora de conversas difíceis por outras especialidades médicas, incentiva o estudo desta temática na oftalmologia. Sendo assim, o objetivo deste estudo é revisar a produção de pesquisas científicas sobre a comunicação de más notícias em oftalmologia. Para isso, foi realizada uma revisão de literatura. As bases de dados utilizadas foram MEDLINE/PUBMED, EMBASE, LILACS, SCOPUS, COCHRANE e SCIELO. Dois revisores independentes leram todos os artigos e selecionaram a amostra final. Sete artigos foram escolhidos nos formatos de artigo original, revisão, editorial, comunicação oral e correspondência. Os oftalmologistas estão preocupados em comunicar as más notícias de forma eficaz, mas faltam estudos sobre o tema. No entanto, há uma crescente percepção de que o treinamento de comunicação de más notícias aumenta a confiança dos médicos na comunicação, beneficiando a relação terapêutica. Portanto, seria valioso incluir este treinamento no currículo das residências.

The Communication of Bad News in Palliative Care: The View of Professionals in Spain.

BACKGROUND: Communication is one of the central axes around which end-of-life care revolves in the context of palliative care. Communication of bad news is reported as one of the most difficult and stressful tasks by palliative care professionals. Therefore, the aim of this study is to identify aspects related to the communication of bad news in palliative care in Spain. METHODS: Descriptive cross-sectional study. An ad hoc questionnaire was designed and sent by e-mail to all palliative care teams in Spain. RESULTS: Overall, 206 professionals (102 nurses, 88 physicians and 16 psychologists) completed the questionnaire. A total of 60.2% considered their communication of bad news skills to be good or very good. This was related to older age, experience in both the profession and palliative care, and to having received specific postgraduate training (P < .001). Around 42.2% perform communication of bad news with the patient first, which is associated with lower skill (P = .013). About 78.15% of the professionals do not use any specific protocol. CONCLUSION: This study suggests that patients access palliative care with little information about their diagnosis and prognosis. The barriers identified in the communication of bad news are the lack of specific education and training in protocol management, the difficult balance between hope and honesty, the young age of the patient, and the family.