Reviewerly/exHarmony huggingface dataset:
Increase Your Organization's Cultural Competence

The Major Gifts ReportVolume 23, Issue 9 p. 3-3 Diversity and Inclusion Measures Increase Your Organization's Cultural Competence First published: 29 July 2021 https://doi.org/10.1002/mgr.31775Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume23, Issue9September 2021Pages 3-3 RelatedInformation
Discourse of the Development of Students’ Media Literacy with Reference to Meta-subject Connections as a Platform for New Didactics: Semantic, Technological, Social Implementation Space

Students' media literacy concerning the development of meta-subject connections as a key segment of new didactics is highly relevant in the context of solving the problem of enriching the content of educational policy in modern Russia.Today, the transformational processes taking place in the society bring up the problem under study to the "rank" of particular importance.In this regard, drawing active attention of the educational theorists and practitioners to the new understanding of the "media literacy" concept in the transforming realities of the new millennium is very important today.The authors' reflections on the topic of the formation of media literacy in regard to the content of the development of meta-subject connections are determined by the urgent need to disclose the semantic content of concepts, to identify integrative components and the significance of the formation process itself in the modern educational paradigm to create a holistic picture and approach of the studied content.The social, economic, informational, cultural context in correlation with the national and global peculiarities has a significant impact at the present stage.The authors conclude that at the present stage, socio-economic, information-technological, utilitarian-pragmatic, cultural-historical contexts in their close connection with the national and global specifics have a decisive influence.In addition, the authors are convinced that the development of educational clusters that include integrative components of the phenomenon of functional literacy (information, communication, social, reading, global competencies) is an important factor of the reconstruction of the education structure, many-faceted facilitation of the educational context.Besides, media literacy is one of the key characteristics of global competencies.It seems that information and media literacy as an integrative component of functional literacy is an important quality of a modern person in an information society; media competence as a quality of a person is becoming an essential condition for successful functioning in the modern society.
Formation of Professional Competence of Assistant Teacher of Inclusive Education in Secondary Education Institutions

The research is devoted to the theoretical and experimental study of forming the professional competence of a would-be teacher assistant of inclusive education through pedagogic modeling. The authors specify the notions of “a tutor” (teacher assistant), “inclusive education”, “persons with special needs”, “individual development program”, and “modeling”. The essence of “pedagogical modeling” is defined, as well as the groups of its objects within the professional competence of the would-be teacher assistants in the inclusive education; the implementation of the psychological-pedagogic modeling of an individual development program for persons with special needs is substantiated. It is proved that any model has a sign nature, thus, the psychological bases of the research are the theory of content-based summarization and the “sign” concept of the educational process. The study reflects the methodological system of forming the professional competence of the would-be teacher assistants of inclusive education through pedagogic modeling and substantiates the content component of the model, implemented in the individual development program of persons with special needs and through applying the relevant methods, forms and means of education. It is proved that the efficiency of forming the professional competence of the teacher assistants of inclusive education by the means of pedagogic modeling depends on introduction of an experimental technique, which provides support and increase of the qualitative indicators of both the teaching and the personal properties of the persons with special needs receiving educational services. Due to the synergetic impact of professional knowledge, the would-be teacher assistants of inclusive education develop an increased motivation to forming the professional skills and competences when working with persons with special needs.
Advanced Object-Relational Mapping

Every application is different, and, while most have some elements of complexity in them, the difficult parts in one application will tend to be different than those in other types of applications. Chances are that whichever application you are working on at any given time will need to use at least one advanced feature of the API. This chapter introduces and explains some of these more advanced ORM features.
Convolutional Neural Network–Based Automatic Classification of Colorectal and Prostate Tumor Biopsies Using Multispectral Imagery: System Development Study

Colorectal and prostate cancers are the most common types of cancer in men worldwide. To diagnose colorectal and prostate cancer, a pathologist performs a histological analysis on needle biopsy samples. This manual process is time-consuming and error-prone, resulting in high intra and interobserver variability, which affects diagnosis reliability. This study aims to develop an automatic computerized system for diagnosing colorectal and prostate tumors by using images of biopsy samples to reduce time and diagnosis error rates associated with human analysis. We propose a CNN model for classifying colorectal and prostate tumors from multispectral images of biopsy samples. The key idea was to remove the last block of the convolutional layers and halve the number of filters per layer. Our results showed excellent performance, with an average test accuracy of 99.8% and 99.5% for the prostate and colorectal data sets, respectively. The system showed excellent performance when compared with pretrained CNNs and other classification methods, as it avoids the preprocessing phase while using a single CNN model for classification. Overall, the proposed CNN architecture was globally the best-performing system for classifying colorectal and prostate tumor images. The proposed CNN was detailed and compared with previously trained network models used as feature extractors. These CNNs were also compared with other classification techniques. As opposed to pretrained CNNs and other classification approaches, the proposed CNN yielded excellent results. The computational complexity of the CNNs was also investigated, it was shown that the proposed CNN is better at classifying images than pretrained networks because it does not require preprocessing. Thus, the overall analysis was that the proposed CNN architecture was globally the best-performing system for classifying colorectal and prostate tumor images.
Reviewer Acknowledgements

Applied Finance and Accounting [AFA] would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether AFA publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 7, Number 2Adina Criste, “Victor Slavescu” Centre for Financial and Monetary Research, Romanian Academy, RomaniaAnastasia Kopaneli, University of Patras, GreeceDapeng Zhu, Shanghai Lixin University of Accounting and Finance, ChinaFabio Rizzato, University of Turin, ItalyHaitham Nobanee, Abu Dhabi University, UAEHajar Jahangard, Central Bank of Iran(CBI), IranHassan Rkein, Al Maaref University , LebanonJayendra S. Gokhale, Embry-Riddle Aeronautical University, USAMawih Kareem Alani, Dhofar University, OmanVolodymyr Vysochansky, Uzhhorod National University, UkraineZi-Yi Guo, Wells Fargo Bank, N.A., USA Angelia EvelynEditorial AssistantOn behalf of,The Editorial Board of Applied Finance and AccountingRedfame Publishing9450 SW Gemini Dr. #99416Beaverton, OR 97008, USAURL: http://afa.redfame.com
Practical Method to Discriminate the Pores Shapes on Carbonate Rocks Using the Kuster and Toksöz Model

Summary On this work we present a method to discriminate the pores shape in a carbonate rock using the Kuster and Toksöz model, like so, the determination of dolomitization process using laboratory samples characterized with the Digital 2D Imaging Analysis. We conclude that is possible using the Kuster and Toksöz model to classify the distinct pore shapes, like spheres, needles, and Penny-Shaped Cracks and determine their dolomitization process using a graph of velocity versus porosity for carbonated rocks with presence of dolomite. On the other hand, we observed that is necessary to refine the interpretation with the Digital 2D Imaging Analysis, given that, there is not correspondence with certain geometries in this work. And finally, we observed that is necessary to add more curves like ellipsoids in our graph to improve the interpretation of the pore shapes and including the samples that were not characterized with the curves presented on this work
News from the Field

MSU Library awards faculty OER grantsLYRASIS, Columbia University Libraries announce e-books partnershipSpringer Nature, UC-Berkeley Library sign new open access book partnershipASERL, DOAJ forge new partnershipLexisNexis introduces Nexis Data LabSpringshare announces new LibCal mapping featuresEx Libris, DataCite launch new integration features
Adaptive Sparse Domain Selection for Weather Radar Superresolution

Accurate and high-resolution weather radar data reflecting detailed structure information of radar echo plays an important role in analysis and forecast of extreme weather. Typically, this is done using interpolation schemes, which only use several neighboring data values for computational approximation to get the estimated, resulting the loss of intense echo information. Focus on this limitation, a superresolution reconstruction algorithm of weather radar data based on adaptive sparse domain selection (ASDS) is proposed in this article. First, the ASDS algorithm gets a compact dictionary by learning the precollected data of model weather radar echo patches. Second, the most relevant subdictionaries are adaptively select for each low-resolution echo patches during the spare coding. Third, two adaptive regularization terms are introduced to further improve the reconstruction effect of the edge and intense echo information of the radar echo. Experimental results show that the ASDS algorithm substantially outperforms interpolation methods for ×2 and ×4 reconstruction in terms of both visual quality and quantitative evaluation metrics.
Accurate Prognostic Prediction for Breast Cancer Based on Histopathological Images by Artificial Intelligence

Purpose: Histological image containing numerus tissue morphology information, is now the golden standard for breast cancer (BC) diagnosis, but it contributes little to prognosis in routine clinic practice. This study aims to assess the ability of pathology image for accurate prognostic prediction that might improve clinical decision making.Experimental Design: We used large-scale clinical datasets including 7,464 pathology images from 3,653 BC patients in three independent cohorts for pathological image-based model (PI model) establishment and independent testing. We trained a mask region-convolution neural network model to automatically label the nuclei in each tile sliced from WSIs. A total of 884 morphological features were distilled from each tile. The machine learning algorithm XGBoost was introduced to efficiently learn prognostic risk scores for PI model. Independent datasets from Hebei Province Cancer Hospital (HCH) and The Cancer Genome Atlas (TCGA) were used for testing.Results: For classification, the independent testing set of HCH could effectively differentiate cancerous from non-cancerous tiles with AUC at 0.947. For prognosis, independent testing set of TCGA showed good ability to differentiate high-risk patients from low-risk patients for overall survival (OS) in all the patients, and confirmed in each molecular subtypes and different AJCC stages (p<0.05, C-index ranges 0.60 to 0.69). Disease-Free Survival (DFS) prediction model also confirmed good performance ability (p<0.05, C-index ranges 0.61 to 0.73).Conclusions: Our data shows that deep mining of pathology image feature have good ability for BC prognosis prediction, which suggest potential applications for supporting clinical treatment decision making in the future.Funding Information: 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (ZYGD18012, ZYJC21035), and Science and Technology Department of Sichuan Province of China under Grant 2021YFS0236.Declaration of Interests: The authors declare that they have no competing interests.Ethics Approval Statement: This study was approved by the Ethics Committee of West China Hospital (reference number: 2021-764).
Automatic Generation of Large-Granularity Pull Request Description

In GitHub platform, many project contributors often ignore the descriptions of Pull Requests (PRs) when submitting PRs, making their PRs easily neglected or rejected by reviewers.Therefore, it is necessary to generate PR descriptions automatically to help increase the PR pass rate.The performances of existing PR description generation methods are usually affected by PR granularity, so it is difficult to generate descriptions for large-granularity PRs effectively.For such reasons, this work focuses on generating descriptions for large-granularity PRs.The text information is first preprocessed in PRs and word-sentence heterogeneous graphs are constructed where the words are taken as secondary nodes, so as to establish the connections between PR sentences.Subsequently, feature extraction is performed on the heterogeneous graphs, and then the features are input to a graph neural network for further graph representation learning, from which the sentence nodes can learn more abundant content information through message delivery between nodes.Finally, the sentences with key information are selected to form a PR description.In addition, the supervised learning method cannot be used for training due to the lack of manually labeled tags in the dataset; therefore, reinforcement learning is adopted to guide the generation of PR descriptions.The goal of model training is minimizing the negative expectation of rewards, which does not require the ground truth and directly improves the performance of the results.The experiments are conducted on real dataset and the experimental results show that the proposed method is superior to existing methods in F 1 and readability.
Extraneous Cognitive Load (ECL) Mahasiswa Calon Guru dalam Pelaksanaan Perkuliahan Pendidikan Biologi

This study aims to determine the ECL of prospective teacher students during lectures. ECL is obtained from the mental effort of students in attending lectures or teaching and learning processes because it will affect the process of constructing students' cognitive schemas from the information received during the learning process. Learning activities are effective and efficient if the ECL of students is in the low category. Data collection was carried out on biology education students who attended group lectures for pedagogic courses and biological science content in the odd semester 2020/2021. This is a descriptive study which was conducted in March-September 2021, with the determination of the sample, namely purposive random sampling. ECL was measured using a mental effort questionnaire in each course in the learning process. The data obtained were analyzed in the conversion of low to high scores, then compared between semester levels to provide an overview of student ECL. The results showed that the mental effort of prospective teacher students was in the low category. The ECL of prospective biology education teacher students is low.
Methodology of applying structural and logical schemes in the study of general physics in a technical university

A structural and logical scheme is a visual image of the logical connection of the main elements of knowledge within the framework of a training course, section or topic. When studying physics as an applied discipline in a technical university, its professional orientation and applied knowledge corresponding to this function come out in the first place. But applied knowledge as a consequence of physical theories is not enough for the development of a modern quantum-relativistic worldview. The idea of our research is to precede the systematic study of general physics with systematic ideas about the place and meaning of each physical theory, namely: before studying classical physics, to show its connection with quantum and relativistic physics. To do this, it is necessary to apply a preliminary and final generalization at different stages of the study of physics with the help of appropriate structural and logical schemes. When implementing this idea, the following methods were used: the method of structural and logical analysis of the course of general physics with the allocation of knowledge elements, the method of systematization based on clarifying the connection between physical theories and the method of generalization, leading to the construction of new generalized schemes of this course. In the proposed schemes "Connection of mechanical theories" and "Scales of the Universe-Velocities", we identify structural elements that reveal the specifics of the methodological representations of the theory in accordance with its place in the Universe and the velocities of its objects. The proposed methodology is based on two types of generalization: preliminary and final. The preliminary generalization shows the place of physical theory in the system of physical knowledge in the course of general physics, the final generalization is used to make students aware of the specifics of the entire range of methodological concepts used in this physical theory. The methodology is aimed at forming students ' systematic knowledge of general physics and at developing their modern quantum-relativistic worldview.
A Momentous Time for Humankind

The opening chapter introduces the reader to the ongoing genome-editing revolution, which is spearheaded by the discovery of CRISPR. To set the appropriate context for the book, the chapter discusses human ingenuity, its presence throughout the history of civilization, and the power it holds to transform the world. The chapter lays out a foundation on which to argue that transformative technologies—such as the printing press, the Internet, nuclear weapons, and other technological feats that induced massive cultural and social change—share a common modus operandi. This exposition aims to help the audience grasp the significance of having access to the specialized tools required to rationally manipulate the genetic composition of living organisms. The chapter provides a high-level overview of the book’s contributions to the literature and discusses the importance of interdisciplinary inquiry to bridge gaps between science, law, and policy.
Extended course offers deep dive on major gift campaigns

Nonprofit Business AdvisorVolume 2021, Issue 380 p. 9-9 Resources Extended course offers deep dive on major gift campaigns First published: 08 April 2021 https://doi.org/10.1002/nba.30994Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume2021, Issue380May 2021Pages 9-9 RelatedInformation
BCF's launches #essentialcoatings and #essentialinks campaign campaign

Following the theft of sand from the Coral Springs beach in Jamaica, authorities approached the International Centre for Environmental and Nuclear Sciences to determine if geochemical analysis could add evidentiary value to collected sediment samples. Forty-three beach sediments comprising of scene and suspect samples were submitted for inorganic elemental investigation by neutron activation analysis. The samples were analyzed for thirty-five elements of which nine (Al, Ca, Ce, Cr, Dy, Fe, Mn, Sc and Sr) were used in statistical evaluation including agglomerative hierarchical clustering, of the dataset. Al, Fe and Sc were the elements with greatest discriminatory power. The methodology illustrated clear similarities in elemental profiles between the donor beach and some suspected receptor beaches while excluding other suspected receptor beaches and potential donor beaches. Interrogation of the dataset provided additional and important information for the authorities and indicated that neutron activation analysis with the use of multivariate statistics can contribute significantly to geoforensic investigations.
We learn «digital», we study «digital»: EdTech in the era of digital transformation of the state and society

The interrelated concepts — «digitalization», «educational technologies EdTech», «education throughout life» are considered. Using the example of the Republic of Belarus and the Russian Federation, it is shown that the digitalization of education is accompanied by the widespread introduction of digital educational platforms and the development of technologies and the EdTech market. It was noted that the coronavirus pandemic has updated teachers and students request for mastering innovative ways of organizing learning activities, for more flexible interaction in the network, while at the same time turning the EdTech market into one of the fastest growing in the world.