Reviewerly/exHarmony huggingface dataset:
Response to letter entitled: Re: Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review

In their letter referring to our systematic review on combined image analysis and omics classifiers [ [1] Schneider L. Laiouar-Pedari S. Kuntz S. Krieghoff-Henning E. Hekler A. Kather J.N. et al. Integration of deep learning-based image analysis and genomic data in cancer pathology: a systematic review. Eur J Cancer. 2022; 160: 80-91 Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar ], the authors propose Electrical Impedance Spectroscopy (EIS) as another, unrelated method that might also have the potential to improve current cancer diagnostics [ [2] Sohag M.H. Nicoud O. Amine R. Khalil-Mgharbel A. Alcaraz J.P. Vilgrain et al. Improved micro-impedance spectroscopy to determine cell barrier properties. Eurobiotech J. 2020; 4: 150-116 155https://doi.org/10.2478/ebtj-2020-0017 Crossref Google Scholar ]. Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic reviewEuropean Journal of CancerVol. 160PreviewOver the past decade, the development of molecular high-throughput methods (omics) increased rapidly and provided new insights for cancer research. In parallel, deep learning approaches revealed the enormous potential for medical image analysis, especially in digital pathology. Combining image and omics data with deep learning tools may enable the discovery of new cancer biomarkers and a more precise prediction of patient prognosis. This systematic review addresses different multimodal fusion methods of convolutional neural network-based image analyses with omics data, focussing on the impact of data combination on the classification performance. Full-Text PDF Open AccessLetter re: Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review: Label-free diagnostic technique to differentiate cancer cells from healthy cellsEuropean Journal of CancerVol. 172PreviewWe were very interested to read the recent review article by Schneider et al. [1] who emphasised that innovations in cancer diagnostics and therapy are urgently required. Those authors analysed 11 studies aimed to enhance cancer diagnostics by combining molecular omics data with image analysis of haematoxylin and eosin (H&E)-stained slides of tumour tissue. The analysis of H&E-stained slides is a gold standard in cancer diagnosis, and it is a time-consuming process for pathologists and presents a major challenge to develop methods for automated analysis. Full-Text PDF
Determination of Stress Concentration Effects Using Micro-Digital Image Correlation Techniques in PMMA Specimens

The present paper analyses the possibility of using the digital image correlation technique to study the mechanical behavior of small scale components. A microscope is supplemented to the equipment for magnification, together with a miniature tensile testing machine. Several samples with already studied stress concentrators were analyzed. For comparison purposes, a finite element model of the geometry, with appropriate loading conditions, is created and the strain field is compared, in orderv to be validated to the experimental one. Results show that an accurate reading can be made by using this technique. Furthermore, crack initiation and its propagation path can be determined, by the appearance of high strains in the region.
Evaluation of current earthquake activity on the Ganos Fault: MONGAN network test analysis

The Ganos Fault MONGAN earthquake monitoring network data presents significant opportunities and challenges for earthquake detection, location and magnitude calculations, source mechanism solutions, and discovery of fault zone waves. This study consists mostly of primary data analysis and seismological evaluations. While stations located in a local area allow the discovery of earthquakes at micro earthquake level, they create significant difficulties in determining the source parameters of these earthquakes. Extracting small earthquakes from continuous data shows that special strategies need to be developed. Network data revealed the presence of many earthquakes with magnitude M
National identity: Prediction model of relationship between language decency and language character

The expression of decency in communication triggers individual character in formation of national identity. Language decency always applies in Malay language education context during learning session. But, how far it can shape the generation’s identity is still vague. Aim of this research was to thorough the relationship of language education decency with language character among students in public and private universities. A survey was conducted on 380 students of several universities in Malaysia. The data were collected by using Google Form with cooperation from university representatives. The quantitative data was analyzed by using SPSS and AMOS software through correlation and regression analysis by structural equation modelling (SEM). Findings showed that the most decency form used by students was words with value β=.67, p=.000. Language decency education had contributed 80% of R2 value for language character among students. The prediction model of relationship between decency language and character language had achieved equivalence value which RMSEA=.067, GFI=.977, CFI=.995, TLI=.991 and Chisq/df=2.682. Therefore, factor of decency language that applies among students in Malay language course can contribute on generation with nice language character and strong national identity.
Applications of Human-Computer Interaction in Health Psychology

The Human-Computer Interaction (HCI) manages the plan, assessment and utilization of data and correspondence advancements. From man-made consciousness to social robots and robots for sexual problems, HCI covers a wide scope of uses. Abilities an interdisciplinary methodology, in light of the joint effort between intellectual mechanical technology and kid brain research, for oneself supporting plan of intellectual and conduct abilities in engineered intellectual specialists, including robots, that is animated by thoughts and formative systems found in kids. Cyberpsychology examines every one of the ones mental peculiarities which are identified with age and pursuits to examinations the strategies of substitute welcomed on through the exchange among fellow and the fresh out of the box new media. This paper discusses how artificial intelligence and HCI applications are handling psychological issues that affect health in an efficient manner. The paper explains how AI and human consciousness are interlinked and different factors play a very important role to provide the support for behavioral issues and diseases. The contribution of Artificial Intelligence in transforming HCI is discussed through case studies, applications and systems in the paper.
Geochemical Characteristics Of The Trace Elements And Heavy Metals In The Sequences In Gachsaran Formation, West Of Iran

In the present study, the geochemical characteristics of sequences of the Gachsaran Formation, located in the west of Kermanshah province, Iran - Iraq border zones, were studied. In order to determine the concentration of the elements, the XRF and ICP-mass techniques were employed, and the XRD technique was used to identify the mineralogical composition and finally, the evaluation of the level of pollution caused by these elements were carried out using statistical and pollution index software. The results illuminated that the concentrations of CaO, MgO, TiO2, and concentrations of two elements, i.e., Cd and Sb were higher than their mean values in the earth’s crust. Based on the CF pollution index, the elements of Cd and Sb with the values of 1.52 and 2 show the moderate contamination. Enrichment factor (EF) revealed moderate contamination for Cs (2.46), Ga (3.86), Rb (2) and Ti (2.35). This index showed the high pollution and anthropogenic origin for Ti (8), Cd (10.41), U (11.26) and Sb (13.43). The results of the correlation between the elements indicated the presence of positive and significant correlation between Cs, Hf, La, Nb, Nd, Rb, Sc, Sm, Ta, Tb, Th, Tl, W, Y, Yb, and Zr. There was no positive and significant correlation between U and none of the elements. Three elements of Sb, U, and Cd showed a negative correlation with most of the studied elements. According to the results of cluster analysis, three separate groups were obtained so that each of Ti and Fe was classified as separate groups and Fe showed the highest difference in comparison with other elements. Based on the results of the Principal Component Analysis (PCA), the highest effect was related to the elements of Cs, Hf, La, Nb, Rb, Sc, Sm, Tb, Th, Tl, W, Y, Yb, Zr, Fe in the first Component, Sb, Cd in second component and U in the third component.
Unravel the Outlier Detection for Indian Ayurvedic Plant Organ Image Dataset

Image-based outlier detection has been a fundamental research problem for machine learning and computer vision researchers. This paper unravels the outlier detection process for the data preparation framework of the Indian Ayurvedic plant organ image dataset. While creating dataset the outlier images might get introduce due to human or device errors. Identification and rectification of such outlier images are crucial part for creating clean dataset. This paper evaluated and compared four well-known and state-of-the-art outlier detection algorithms, namely Isolation Forest, Local Outlier Factor, Histogram-Based Outlier Score, and One-Class Support Vector Machine for detecting the outliers from the dataset of Indian Ayurvedic plant organ images. For this experiment dataset containing 690 images of “Centella asiatica” was used and augmented to generate more image samples. In total, 21 morphological, geometric, color, and texture features have been extracted from each plant organ image. The experiment shows the isolation forest giving superior results with 91% accuracy, at the same time Histogram-Based Outlier Score proves to be the fastest in execution time.
A Note on Some New Generalized Wavelets

In this paper, we define new real wavelets based on the Hartley kernel and Boas transforms. These wavelets have possible application in analyzing both the symmetries of an asymmetric real signal. We give various results to obtain their higher vanishing moments. Finally, we give a sufficient condition under which Hartley-Boas-Like wavelets associated with Riesz projector forms a convolution filter with transfer function vanishing for the positive frequencies.
Statistical Analysis in Determining the UIN Kiai Haji Achmad Siddiq (UIN KHAS) Jember Students' Readiness Toward the Internet-Based Learning System

This research focuses on finding out how far the readiness of UIN KHAS Jember students in facing this e-learning learning system is, so research is carried out in the form of a survey. From the survey results, it is hoped that data can be obtained regarding what factors influence the e-Learning-based learning system to be applied to UIN KHAS Jember students. The variables used are Study Habits and Technology Habits. The data analysis method used in this research is the 1 sample proportion test and the Chi-Square test. Respondents used were UIN KHAS Jember students Class of 2015, 2016, 2017, and 2018. From a series of data collection to the analysis stage, several conclusions can be drawn, namely the number of UIN KHAS Jember students ready to face the e-learning learning system by 60% (or more than 50% of students). The variables that affect student readiness in dealing with e-learning learning systems are study habits and technology habits. From each of these variables, it turns out that only the attitude factor towards the learning system and the length of time on the internet are very significant or affect student readiness.
Folding over Neural Networks

Neural networks are typically represented as data structures that are traversed either through iteration or by manual chaining of method calls. However, a deeper analysis reveals that structured recursion can be used instead, so that traversal is directed by the structure of the network itself. This paper shows how such an approach can be realised in Haskell, by encoding neural networks as recursive data types, and then their training as recursion scheme patterns. In turn, we promote a coherent implementation of neural networks that delineates between their structure and semantics, allowing for compositionality in both how they are built and how they are trained.
Hospital cyberattacks on the rise, no hospital too small to be vulnerable

One in three health care organizations worldwide reported falling prey to a ransomware attack in 2020. In this type of cyberattack, software that is downloaded onto a health-system computer—typically by an unwitting authorized user—encrypts the files that run the computer. Hackers then demand a ransom from the hospital to decrypt the files and relinquish control of the computers.
The Cognitive Neuroscience of Working Memory and Language

Working memory and language are tightly intertwined cognitive systems. Working memory enables language acquisition and vocabulary expansion; it supports both language comprehension and language production. Language, on the other hand, provides key representations that support efficient and robust encoding and maintenance of information in working memory, as well as the ability to compress information and the redundancy to reconstruct it in case of partial information loss. The close relationship can also be observed in the overlap and integration of brain systems and networks supporting working memory and language processing. This chapter examines the brain substrate of working memory and language processes, focusing on their interdependence, synergy, and the mechanisms underlying their close integration. It integrates key theoretical models and empirical evidence from behavioural and neuroimaging studies, computational modelling, and insights based on patterns of working memory and language dysfunctions due to brain injury and disease.
Intake

OpflowVolume 48, Issue 6 p. 2-2 Departments Intake First published: 08 July 2022 https://doi.org/10.1002/opfl.1696Read 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 onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume48, Issue6July/August 2022Pages 2-2 RelatedInformation
A Comprehensive Empirical Study of Query Performance Across GPU DBMSes

In recent years, GPU database management systems (DBMSes) have rapidly become popular largely due to their remarkable acceleration capability obtained through extreme parallelism in query evaluations. However, there has been relatively little study on the characteristics of these GPU DBMSes for a better understanding of their query performance in various contexts. To fill this gap, we have conducted a rigorous empirical study to identify such factors and to propose a structural causal model, including key factors and their relationships, to explicate the variances of the query execution times on the GPU DBMSes. To test the model, we have designed and run comprehensive experiments and conducted in-depth statistical analyses on the obtained data. As a result, our model achieves about 77% amount of variance explained on the query time and indicates that reducing kernel time and data transfer time are the key factors to improve the query time. Also, our results show that the studied systems still need to resolve several concerns such as bounded processing within GPU memory, lack of rich query evaluation operators, limited scalability, and GPU under-utilization.
Concordance of core needle biopsy and post-operative histo-pathological grading in breast cancer patient

Objectives: This study aimed to evaluate the concordance of histological types, grade and components of grading, between CNB and open surgical specimens.&#x0D; Methods: In this study patients with paired CNB and open surgical biopsy diagnosed with invasive breast cancer are involved, from January 2012 to October 2015 were recreated. Revision of (579) patients were done, but only (116) patients were included in our study according to inclusion criteria, in the breast center department of Slemani Teaching Hospital in Slemani Governorate.&#x0D; Results: There were 116 patients with invasive breast cancer analyzed for concordance rate between CNB and open surgical specimen for tumor type, grade, tubule formation, nuclear pleomorphism, and mitotic count were 93.1%, 73.3%, 77.6%, 73.3%, 62.9% respectively, mitotic count was under estimated in CNB samples(kappa 0.4 P value 0.001).&#x0D; Conclusion: These results indicate that pre-operative CNB can reliably provide useful preoperative prognostic and predictive information in breast cancer patients which can play a major role in planning treatment strategies. Core needle biopsy has significant accuracy in determining invasive breast cancer and histological type and grading.
Applying flipped classroom model in teaching Organic Chemistry in grade 11 to develop the self-study capacity of students at high schools

Today, along with the explosive development of information and communication technology, many new teaching models have emerged besides the traditional face-to-face teaching model, typical of which are blended learning models. The flipped classroom is one of the blended learning models and has advantages in developing students' self-study capacity. This article presents the results of applying the flipped classroom model according to a specific process towards the goal of developing self-study capacity for students in the Organic Chemistry of grade 11. The experimental data obtained have shown the feasibility and positive effect of applying this model in teaching at high schools, meeting the requirements of current educational innovation.
Aragonesisms in Current Use

This study focuses on the diatopic variant from the Spanish region of Aragón (Comunidad Autónoma de Aragón), also known as castellian-aragones. We will inform how this variant differs from other variants and construct a short list of Aragonesisms, including expressions, which are in common use at the present almost exclusively in this region. In the context of Teaching Spanish as FL in Korea, a proxy translation to the Korean language has also been included for each word and expression. Due to the extension constraints for this work we will be narrow down to a maximum of 50 entries, from an initial list of more than 200 Aragonesisms. We select those terms that best meet both requirements: a) the terms are in common use at the present in Aragón, b) they are mostly unknown in other regions or not included in the DRAE. With this criteria, a contrast survey is distributed to native speakers from different regions of Spain to know whether if they are used in their respective regions at the present.
Performance Evaluation of the Weighted Least Connection Scheduling for Datacenters with BigHouse Simulator

In this paper, we investigate the performance of a weighted least connection algorithm for scheduling jobs in datacenters. The novelty of the proposed algorithm is that the weights for the compute units in the datacenter are determined based on their current dynamic power consumption. The algorithm is implemented inside the BigHouse simulation framework and compared against the default least utilized scheduling approach of the framework. Simulation experiments show that the proposed algorithm provides significantly better performance for large number of large queries per second (QPS) values as well as lower power consumption. In addition, the computational runtime is linear with respect to the increase in queries per second. However, while linear, the computational runtime is longer than that of the default scheduler due to the increased computational complexity required to determine where a job should be placed. These results indicate a tradeoff between performance (i.e., latency of all scheduled jobs) and computational runtime of the scheduling algorithm.
A Contrastive Study on Object Pronouns of Korean and Indonesian for Korean Language Learners - Based on Korean-Indonesian Parallel Corpus -

This study aims to describe and analyze Korean and Indonesian object pronouns based on a Korean-Indonesian parallel corpus. Both Korean and Indonesian are categorized as ‘discourse pro-drop languages’ that allow arguments(subjects and objects) to be dropped. However, the object elliption in Indonesian is more restrained because in independent clauses the object cannot be ommited. The results of the Korean-Indonesian parallel corpus showed that there were instances when Korean object pronouns corresponded with Indonesian object pronouns and when they did not. The Indonesian object pronoun is controlled by its verb’s transitivity and therefore can appear even when the object pronoun in the Korean text was expressed using zero anaphor. The Korean object pronoun when overtly expressed, displayed new information, focus or emphasis. In addition, we also observed cases on the account of different language expression, Korean and Indonesian preference on expression was discovered.
Clarity in social intelligence of secondary school students developing comminicative skills for children with autism spectrum disorders learning in inclusive middle schools

Due to struggle finding in the communication of students with autism spectrum disorders (ASD) learning in inclusive middle schools, those children have performed significant limitations in initiate a greeting, interaction, and a dialogue with their peers. Those difficulties greatly become barriers to the learning process as well as the integration of students. The article is aimed to provide research results in developing communication of children with ASD through setting up 08 educational activities of a 4-step procedure to apply communicative skills as follows: (1) Actively and maintaining communication with people; (2) Recognizing and handling situations of saying thank you and sorry; (3) Adhere to basic principles of communication; (4) Expand the conversation and help people. 2 educational activities on instructing children with ASD to implement each step in one skill were developed to model each step of the communicative skill application procedure. The results showed a significant improvement in students’ skill performance by mean score increasing from M = 1.5 to M = 2.85.
El Laboratorio Nacional de Materiales Orales, conceptos, antecedentes, código de ética y protocolo de documentación

This paper presents some results of the systematization work that the National Laboratory of Oral Materials (Mexico) has done. A brief history of LANMO and its theoretical bases is first presented, and then two of the instruments it has generated: a code of ethics and a protocol for the documentation of oral materials in field work.
Migration Patterns for Applications in Cloud Computing Environments

The trend of adopting container-based systems become increasingly relevant for companies and their IT departments. Improved scalability and shorter deployment cycles in IT production are the most mentioned benefits of the technology. The adoption of container-based technologies in an existing IT system landscape requires a consideration of migration strategies. The paper at hand examines general migration patterns for the transition of virtual systems into container-based systems from a cloud computing perspectives. Several strategies are derived for a specific use case.