Reviewerly/exHarmony huggingface dataset:
A new method for estimating the probability of causal relationships from observational data: Application to the study of the short-term effects of air pollution on cardiovascular and respiratory disease

In this paper we investigate which airborne pollutants have a short-term causal effect on cardiovascular and respiratory disease using the Ancestral Probabilities (AP) procedure, a novel Bayesian approach for deriving the probabilities of causal relationships from observational data. The results are largely consistent with EPA assessments of causality, however, in a few cases AP suggests that some pollutants thought to cause cardiovascular or respiratory disease are associated due purely to confounding. The AP procedure utilizes maximal ancestral graph (MAG) models to represent and assign probabilities to causal relationships while accounting for latent confounding. The algorithm does so locally by marginalizing over models with and without causal features of interest. Before applying AP to real data, we evaluate it in a simulation study and investigate the benefits of providing background knowledge. Overall, the results suggest that AP is an effective tool for causal discovery.
Layer-wise regularized adversarial training using layers sustainability analysis framework

Deep neural network models are used today in various applications of artificial intelligence, the strengthening of which, in the face of adversarial attacks is of particular importance. An appropriate solution to adversarial attacks is adversarial training, which reaches a trade-off between robustness and generalization. This paper introduces a novel framework (Layer Sustainability Analysis (LSA)) for the analysis of layer vulnerability in an arbitrary neural network in the scenario of adversarial attacks. LSA can be a helpful toolkit to assess deep neural networks and to extend the adversarial training approaches towards improving the sustainability of model layers via layer monitoring and analysis. The LSA framework identifies a list of Most Vulnerable Layers (MVL list) of the given network. The relative error, as a comparison measure, is used to evaluate representation sustainability of each layer against adversarial inputs. The proposed approach for obtaining robust neural networks to fend off adversarial attacks is based on a layer-wise regularization (LR) over LSA proposal(s) for adversarial training (AT). This means that the AT-LR procedure could be used with any benchmark adversarial attack to reduce the vulnerability of network layers and to improve conventional adversarial training approaches. The proposed idea performs well theoretically and experimentally for state-of-the-art multilayer perceptron and convolutional neural network architectures. Additionally, a measure named robustness and generalization score or R&G score is defined to better evaluate each adversarially trained model over a variety of significant perturbations. Compared with the AT-LR and its corresponding base adversarial training, the R&G score on Moon, MNIST, and CIFAR-10 benchmark datasets was increased by 56.52%, 75.82%, and 6.54%, respectively for more significant perturbations. The LSA framework is available and published at https://github.com/khalooei/LSA.
UHA‐CycleGAN: Unpaired hybrid attention network based on CycleGAN for terahertz image super‐resolution

Abstract In recent years, terahertz imaging technology has been widely used in security, medicine, and other fields. However, the image resolution is low due to the limits of imaging equipment and diffraction. Traditional super‐resolution methods based on machine learning use artificial paired image datasets, and their image degradation process is quite different from the actual terahertz imaging mechanism. In the paper, an unpaired hybrid attention network is proposed, using the real unpaired high‐resolution and low‐resolution terahertz images as the original input, two sub‐networks are trained: degenerate reconstruction network and super‐resolution network. The degenerate reconstruction network is used to learn the degradation process of the real terahertz imaging system, and reconstruct the generated degradation images into the fixed mapping down‐sampled image of high‐resolution terahertz image. The super‐resolution network uses the generated paired image with fixed correspondence to train the super‐resolution network of paired terahertz images, to improve the imaging resolution of the network in the super‐resolution work of real low‐resolution terahertz images. In addition, the no‐reference image quality evaluation system is introduced to objectively evaluate the network performance. The experimental results show that the UHA‐CycleGAN network outperforms the traditional paired super‐resolution network on both open‐source and self‐built datasets.
Developing a breast lesion simulator and remover in mammograms using Cycle-GAN: focusing on its impacts on a computer aided detection algorithm

Our purpose is to develop a breast lesion simulator and remover using Cycle-GAN that can simulate plausible breast lesions in normal mammograms and remove existing lesions from mammograms. We curated 10310 screening mammograms from 4832 women (2416 normal/healthy and 2416 with recalled lesions). We divided our dataset into development and testing with a ratio of 8:2. We segmented 400 by 400 pixel patches, containing lesions from recalled cases and the same sized patches from the center of a normal breast mammogram. CycleGAN consists of two GANs and each GAN works as a lesion simulator and lesion remover when we train it on recalled lesions and normal patches. We used the development set to optimize the Cycle-GAN. Once trained, we applied Cycle-GAN on our test set to create lesion-simulated-normal controls and lesion-removed-recalled cases. After that, we trained ResNet18 as our CADe algorithm and tested it on our test set under four conditions: 1) original images (ResNet18<sub>Control</sub>), 2) original lesion cases + lesion simulated normal (ResNet18<sub>LSimul</sub>), 3) lesion removed + original normal controls (ResNet18<sub>LRemov</sub>), and 4) lesion removed + lesion simulated normal (ResNet18<sub>LSimul+LRemov</sub>). The test AUCs of ResNet18<sub>Control</sub>, ResNet18<sub>LSimul</sub>, ResNet18<sub>LRemov</sub>, and ResNet18<sub>LSimul+LRemov</sub> were 0.92, 0.79, 0.79, and 0.6, and their pairwise differences were statistically significant (p-value ¡ 0.0001), except the difference between ResNet18<sub>LSimul</sub> and ResNet<sub>18LRemov</sub>. Cycle-GAN can add plausible lesions to normal mammograms and remove existing lesions from mammograms such that the resulting images confused the computer-aided detection algorithm trained on the original mammograms.
First-Order Theory of Rewriting for Linear Variable-Separated Rewrite Systems: Automation, Formalization, Certification

The first-order theory of rewriting is decidable for linear variable-separated rewrite systems. We present a new decision procedure which is the basis of FORT, a decision and synthesis tool for properties expressible in the theory. The decision procedure is based on tree automata techniques and verified in Isabelle. Several extensions make the theory more expressive and FORT more versatile. We present a certificate language that enables the output of FORT to be certified by the certifier FORTify generated from the formalization, and we provide extensive experiments.
TOWARDS A NEW PARADIGM FOR THE LANGUAGE RESEARCH: SYNERGISTIC CONTEXT

The globalization changes in the world contribute to the growing importance of scientific knowledge in general and fundamental science in particular. Current difficulties in understanding of the mechanisms of possible changes in the language system require attention to enriching the methodology of linguistics with an interdisciplinary scientific toolkit in order to obtain new linguistic knowledge, and also reorients researchers from the position of analysis to the position of synthesis.
Scientific and methodical bases of the new evaluation process in higher schools

The Educational Reforms carried out in the direction of improving the quality of education in the Republic of Azerbaijan envisage the implementation of programs that ensure the development of education with innovative approaches. Quality control in education, its management and evaluation are characterized as the conclusion of the pedagogical process. Based on the social order of the state, education is a superstructure phenomenon that requires evaluation of the results as the main characteristic, which includes the development trend and dynamics of the society. Evaluating the results of education requires new approaches to its evaluation mechanisms. Thus, in a time when information and means of obtaining it are increasing day by day, the analysis of the results of the pedagogical process characterizes the extent to which the necessary information is perceived by the students and what skills they acquire in this use. Determining the content of education in the globalized era has been involved in numerous studies. Since the determination of the content is based on previously achieved educational achievements, the importance and relevance of assessment in the pedagogical process is always maintained. Thus, by means of evaluation mechanisms, the improvement of the quality of education, the development of new approaches in the application of training technologies, the anticipation of norms and the increase of effectiveness in the application of pedagogical innovations, the provision of integration and the expansion of liberalization are carried out. The study of these issues is carried out with reference to the evaluation results.
Estimation and Distribution of Some Heavy Metals in Urban Soils at Kufa, Najaf Governorate: An Environmental Geochemistry Research

Kufa, considered one of the important cities in Iraq, is facing a rapid increase in population proportion and urban development in buildings and industry. Therefore, the concentration of several hazardous heavy metals is the main focus of this study. It presents the distribution and Estimation of heavy metals in urban lands in the Kufa area as an environmental geochemical study. Twenty samples of urban surface soils were collected in many sites to determine concentrations, distribution, and contamination of elements Cu, Zn, Co, Ni, Th, U, Pb, Hf, Nb, and Fe. The mean concentrations of heavy metals were compared with the local studies, UCC guidelines, and the world reference. To distinguish anthropogenic pollution, EF and Igeo guides were calculated. The obtained results established that contamination in Kufa soil land was slightly polluted by U (2.83ppm) and Nb (10.81ppm) and moderately polluted by Pb (31.7ppm) and Hf (9.75ppm). The research revealed that the reason for the elevation in the lead in the Kufa soil is that it often suffers from severe vehicle overcrowding during religious occasions.
Ways to Improve Arsenal's Lack of Overseas Fans

The investigation of this article was based on Building on the context of the global COVID-19 (Corona Virus Disease 2019) pandemic all over the world. Nowadays, there are not many passages on how to increase the number of fans overseas. Hence, this was a gap in this field and this passage applies Arsenal as an example to analyze this problem. This research applied the case analysis suggestion to analyze this problem. After the investigation, the passage said that Arsenal makes a huge financial loss because of COVID-19. Thus, they need to perform something that will make a positive difference, improve Arsenal's performance and the number of titles, and manage what their players say on social media. These three suggestions were since the Internet is very developed in today's era. The Internet can help Information spread quickly. Also, as the Internet gets better and better in the future, it could be a good idea for Arsenal to plug in its financial losses and make more money.
Philosophical approach to technical translation

The article deals with technical translation from a philosophical point of view. Different approaches to definitions to the technical translation have been considered. The analysis of the modern philosophy of technical translation shows that its other important task is the formation of a new concept of nature, to which technology is related as a factor that has the greatest impact on it.
The impact of in-service and retraining education on the professional development of teachers in international practice

In our republic, as in all fields, successful reforms are ongoing in the field of education. Integration of Azerbaijani education into world education, adaptation to international standards, use of progressive world experience at all stages and levels of education serves sustainable development. The fulfillment of a global task, such as the transformation of material resources into human capital, requires, first of all, the introduction of new mechanisms at all stages and levels of education. The rapid flow of information in society results in the rapid change of knowledge and information. Even in the most perfect educational system, a significant part of the acquired knowledge loses its activity from time to time. Therefore, in the rapidly changing, globalized world, knowledge and skills need to be constantly renewed, improved, and reconciled with the requirements of the time. From this point of view, it is necessary to change and improve the professional knowledge of professionals working in all areas of public life, including teaching staff, both quantitatively and qualitatively. The continuous training of pedagogical personnel working in the field of education, who shape the intellectual potential of the society and the future of the nation, are considered the most leading direction in the state's policy, is needed today. Experience shows that the educational system of society's development poses many important problems, the realization of which depends on the level of professionalism of the teaching staff.
The management activity of the director of the kindergarten to ensure the quality of education and care in early childhood

The article provides a theoretical overview of the new requirements and policies for early childhood education and care, which ensure a high quality of educational services in kindergarten. Key aspects of management that enable the development of children's full potential to ensure their long-term well-being and the role of the headteacher in this context are analysed. Adequate to the new conditions, management solutions are being sought to ensure the children's readiness for formal education and to support the specialists in the kindergarten to ensure the quality of training, education and socialization in early childhood development. A management model is presented.
A multi-agent framework for collaborative geometric modeling in virtual environments

The use of collaborative applications in which several individuals interact to solve a problem is an important strategy both in educational settings as well as professional environments. Virtual Reality (VR) technology, in particular, has acquired a predominant role in many industries. However, as the level of immersion and realism of the VR experience increases, so does the demand for computational resources, as rendering processes become increasingly intensive and can negatively affect other communication processes that are critical in collaborative environments. In this paper, we present a software framework based on multi-agent systems that enables the separation of rendering processes from internal data management tasks and communication processes between users, which are prevalent in collaborative virtual reality applications. The results of our validation studies show that, compared to other techniques based on protocol or network enhancements, the proposed architecture can significantly improve collaborative processes in general, and virtual reality-based applications in particular.
Let "Flippity" Speak: Using Online Board Game to Improve Speaking Skills Among Elementary Pupils

&lt;p style="text-align:justify"&gt;The significance of speaking English has been emphasized in Malaysia education. However, speaking problems such as lack of enthusiasm and poor speaking performance emerge among ESL pupils. To resolve this, an online board game “Flippity” is implemented in online speaking lessons. This paper aims to explore the usefulness of the online board game “Flippity” to improve speaking skills among elementary pupils who are in Year 5 as well as to investigate pupils’ perceptions towards the use of the online board game “Flippity”. The study employed a quasi-experimental mixed method design to collect data from thirty Year 5 pupils from a Chinese primary school. Data was collected through speaking pre-test and post-test, semi-structured interview and questionnaire. The results indicated a significant improvement in pupils’ speaking skills in terms of accuracy, fluency, range, interaction and coherence. Pupils also displayed preferences and positive attitude in learning to speak while playing “Flippity”. Further studies are recommended to be done on how “Flippity” could be exploited when learning other language skills such as listening, reading, writing and grammar.&lt;/p&gt;
Development of Digital Shearography for Dual Sensitivity Simultaneous Measurement Using Carrier Frequency Spatial Phase Shift Technology

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Digital shearography has many advantages, such as full-field, non-contact, high sensitivity, and good robustness. It was widely used to measure the deformation and strain of materials, also to the application of nondestructive testing (NDT). However, most digital sherography applications can only work in one field of view per measurement, and some small defects may not be detected as a result. Multiple measurements of different fields of view are needed to solve this issue, which will increase the measurement time and cost. The difficulty in performing multiple measurements may also increase for cases where the loading is not repeatable. Therefore, a system capable of measuring dual fields of view at the same time is necessary. The carrier frequency spatial phase shift method may be a good candidate to reach this goal because it can simultaneously record phase information of multiple images, e.g. two speckle interferograms with different fields of view. It then obtains the phase information of each interferogram by separating them from the spectrum using the Fourier Transform (FT) method. The challenge of using this method is that the phase information can partially overlap on the spectrogram, resulting in a bad phase map. This paper presents a new idea for separating the phase information on the spectrogram. The new idea adjusts the shearing directions, leading to complete separation of the spectrums of the two images, e.g. one in the horizontal direction and the other in the vertical direction. The phase information of each interferogram can then be excavated by windowing the corresponding spectrum and taking the inverse Fourier Transform. In digital shearography, the phase information is directly related to gradient of surface deformation; thus, gradient of surface deformation with different fields of view, also called dual sensitivity, can be obtained. The principle of this method will be described and demonstrated by experiment results.&lt;/div&gt;&lt;/div&gt;
A Unified Frequency Understanding of Image Corruptions and its Application to Autonomous Driving

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Image corruptions due to noise, blur, contrast change, etc., could lead to a significant performance decline of Deep Neural Networks (DNN), which poses a potential threat to DNN-based autonomous vehicles. Previous works attempted to explain corruption from a Fourier perspective. By comparing the absolute Fourier spectrum difference between corrupted images and clean images in the RGB color space, they regard the noise from some corruptions (Gaussian noise, defocus blur, etc.) as concentrating on the high-frequency components while others (contrast, fog, etc.) concentrate on the low-frequency components. In this work, we present a new perspective that unifies corruptions as noise from high frequency and thus propose an image augmentation algorithm to achieve a more robust performance against common corruptions. First, we notice the 1/&lt;i&gt;f&lt;sup&gt;α&lt;/sup&gt;&lt;/i&gt; statistical rule of the natural image's spectrum and the channels-wise differential sensitivity on the YCbCr color space of the Human Visual System. Thus we present a new perspective of the relative Fourier spectrum in the YCbCr color space which unifies the noise from all 15 common corruptions as noise concentrating on the high-frequency components. From the new perspective, the SOTA (state-of-the-art) image augmentation algorithm shows insufficient coverage of frequency change compared with common corruptions and an insufficient improvement in robustness against perturbations on the frequency domain. Second, based on the unified understanding of image corruptions and limitations of the SOTA image augmentation algorithm, we present a frequency-based image augmentation that adds noise to the high-frequency components in the YCbCr color space with the amplitude of noise proportional to the spectrum amplitude of the image. Compared with previous works, the proposed method achieves SOTA performance against corruptions on common datasets (CIFAR-10 and tiny-ImageNet) and real-world driving tests.&lt;/div&gt;&lt;/div&gt;
Expert System for Detecting Malnutrition in Toddlers Using the WEB-Based Certainty Factor Method

Malnutrition is based on the nutritional status indexes Weight Loss by Age (W / A) &lt;-3 SD is severely underweight equivalent term. Where there are two types of malnutrition are kwashiorkor, marasmus. if the lack of nutrition the infants are susceptible to malnutrition because of the growth and development of this cycle requires nutrients were greater than the age of the other so easily suffer from nutritional disorders, if not treated immediately will cause death and chronic infection. In the current system there are some drawbacks such as the absence of security following safety features such as anti-virus as a means to protect the database on these weaknesses then designed and built an expert system Identifying Malnutrition In Toddlers with certainty factor method designed web- based using program based on Macromedia Dreamweaver 8, especially PHP and using MySQL as database. The report is designed using iReport and the modeling system is done with UML 2.0. design aims to build an expert system to identify symptoms of malnutrition using the method of Certainty Factor (CF) and to build an expert system that will generate information from experts (books, as well as references that support) accurately.