Reviewerly/exHarmony huggingface dataset:
Treating bone pain syndrome of the patients with uncomplicated vertebral compression fractures during II and III stages of rehabilitation treatment

The aim of this prospective study is to improve the results of treating type A1 and A2 uncomplicated vertebral compression fractures using intratissual electric stimulation (ITES) during II and III stages of rehabilitation treatment. Materials and Methods. The study analyses the use of intratissual electric stimulation (ITES) for treating bone pain syndrome of the patients with type A1 and A2 mono and bisegmental spinal fractures (according to Magerl classification) in a distant period. The whole population is 86 patients, aged from 45 to 65. In-patients were treated using vertebral column extension, some physical therapy and medication. The observation period lasted 12-36 months. It is the stage of control observation. The patients who complained of constant and reemerging pain syndrome were treated using intratissual electric stimulation (ITES). Immediate, short- and long-term outcome analysis was carried out. It is the final stage of the treatment. Clinical, neurotic and rehabilitation status of the patients is analized taking into account Sagittal balance parameters, the spinal canal condition and rehabilitation vectors with numerical ratings. The objective pain assessment was performed by measuring skin surface electric potential according to Gerasimov (1991). The quality of life was assessed using Oswestry Disability Index (ODI). Results. The analysis of morphometric characteristics pointed out changes in sacro-pelvic correlation (LSB), flattening of lumbar lordosis, stenosis of the spinal canal, post-traumatic changes and involution in lumbar and thoracic vertebrae. The control stage of the research revealed significant improvement of patients’ sacro-pelvic balance parameters, pain syndrome elimination and the improvement of the quality life. Conclusion. The pathogenetically substantiated method of treating adult or elderly patients with spinal traumas, the use of intratissual electric stimulation at the outpatient rehabilitation stage prove to be effective.
Simulation and optimization for pressing system of hydraulic brick press based on AMESim

Abstract In order to solve the problems of impact vibration and roar in the working process of the automatic hydraulic brick press, a simulation model of the hydraulic system was established based on AMESim, and the dynamic simulation analysis of the upper cylinder was carried out to find out the cause of the problem. It was solved by installing a deceleration circuit and improving a pressure relief circuit. Finally, the optimized hydraulic system was simulated and verified, and the results proved that the optimized hydraulic system achieved the desired effect.
Tensile and Hardness Tests on Steel Specimen

Steel specimens were subjected to both tensile tests and hardness tests. The tests were carried out Mild steel .The specimens were tested under various conditions. The maximum hardness was for the specimen quenched with water, however the tensile strength of that particular specimen was the minimum. While the tensile strength was highest for slow cooling and furnace cooling .However the hardness for slow cooling was the least. While furnace cooling was comparatively higher. The other specimens had varied tensile strength and hardness and it was not possible to map a relationship of the two. The motivation for this work has been that the students involved have recently been exposed to material strength and its variation with temperature.
An Extensive Exploration of Privacy and Compliance Considerations for Hybrid Cloud Deployments

Public cloud and private cloud domains combine together to form a platform known as hybrid cloud, which provides deployment methods to carry out various applications in different dimensions. In public hybrid cloud environments, many companies are facing issues in handling access control operations in shared infrastructures. Also, it lets the companies to choose where to place the loads to embrace audit and compliance policies. According to the recently conducted studies, hybrid cloud is vulnerable to malicious attacks and breaching of privacy. The main issues faced by the hybrid cloud are minimal security controls and risk management. This hybrid storage service has opened up scope for progress in the organizational development. The other limitations encountered could be accountability of shared responsibilities between both the stakeholders, internally and externally. With respect to these issues, this chapter aims at highlighting the privacy and compliance methodologies that are primarily necessary for efficient functioning of hybrid cloud storage. As a functional discipline, this chapter aims to bring out advanced privacy and security models for hybrid cloud models with state-of-the-art techniques.
COMMUNICATIVE-DIGITAL TECHNOLOGIES OF EDUCATIONAL VALUES DEANTHROPOLOGIZATION

The article is devoted to the issues of Russian youth education in the conditions of the modern information society development. The purpose of the study is to analyze the communicative and digital technologies that have a destructive impact on the individual in the context of the development of the project “non-figurative education” in Russia. The article substantiates the position that “non-figurative education” is aimed at deanthropologization, which is designed to revise the ideals of humanism, subject the personality to spiritual and moral degradation, by primitivizing the value bases and orientations of the individual. Conclusions. Today, mankind as a specific way of existence is turning into a transforming force on a planetary scale. Understanding of a person in this way reveals the urgent need for interdisciplinary research focused both on the analysis of existing socio-humanitarian theories of human existence, and the search for new forms of his interaction with the multitude of all structures in reality.
Label-free digital histopathology for human breast cancer grading at the subcellular level

The current gold standard for tissue histopathology is based on the examination of stained tissue slices by pathologists. To save time and minimize human efforts, computerized methods in nuclei segmentation and classification have been advanced and popularized for histopathology applications. Digital histopathology has been increasingly applied to cancer diagnosis and prognosis. We proposed a label-free digital histopathology method based on refractive index maps measured from a large field of view optical diffraction tomography system. We measured breast cancer tissue slices and digitally processed the data for cancer grading.
Siamese dual path aggregation network for object tracking

Siamese trackers have attracted great attention on visual object tracking due to their real-time speed and high accuracy. In this paper, we propose a dual path aggregation network (SiamDPAN) for high-performance tracking. First, we build a multi-level similarity maps aggregation (MSA) structure, which predicts and fuses the similarity maps from multi-level features. Second, we propose a mask path aggregation module (MPA) for better capturing the appearance changes of objects by propagating maps in low-layers. We conduct sufficient ablation studies to demonstrate the effectiveness of our proposed tracker. We only train our network with two datasets, achieving 0.436 EAO and 0.351 EAO on VOT2016 and VOT2018.
A SURVEY ON THE SECURITY AND PRIVACY OF BLOCKCHAIN SYSTEMS

Since when bitcoin make an entry in cryptocurrency which is based on blockchain technology gets so much popularity just from initial phase itself, now most of the cryptocurrency are moving towards blockchain framework and using different hashing function. In this advancement most of the works are now using blockchain technology from cryptocurrency to smart online retails platforms which has been used by Walmart. since its going to be most used term and popular technology most of the attackers are targeting and just by using some loopholes and any other technical glitches or any other way they are attacking over this technology. since its going to be future and everyone is concerned for its security and privacy, here we did a good comparison of many attacks already did on this blockchain frameworks and we summarize this attacks and we tried to give our own opinion to make it more reliable and flexible. Key Words: Consensus, PoW, PoS, PoL, PoI, Bloch Chain,
Technical debt in the software development lifecycle: code smells

This paper is dedicated to the review of the most popular code smells, which is one of the technical debt components, in addition to methods and instruments for their detection. We conduct a comparative analysis of multiple instruments such as DesigniteJava, PMD, SonarQube. We apply existing tools to set of open-source projects to deduce detection precision and coherence of the selected instruments. We highlight strengths and weaknesses of the approach based on metrics computation and threshold filtering that is used in instruments. Citing of code smells detected by the instruments shows low percentage of true positives (10% for god class and 20% for complex method). We perform literature review of papers suggesting enhancements of the standard approach and alternative approaches that doesn’t involve metrics. To assess the potential of alternative methods we introduce our long method detection prototype with a false positive filtering system based on machine learning methods.
Blockchain in IoT healthcare: case study

Chapter Contents: 6.1 Overview 6.2 Existing models to secure IoT healthcare 6.3 Blockchain to secure IoT healthcare 6.3.1 Proposed system 6.3.2 System implementation 6.4 Conclusions References
GRAPHICAL USER INTERFACE PERSONALIZATION: USER STUDY OF IMAGE FREQUENCY PREFERENCES

Recommending systems are undoubtedly a breakthrough in technology.Recommending systems are helpful to produce intelligent systems.These systems are becoming more and more popular and their main components are other embedded subsystems.The final result of intelligent system visible to the end-user is the graphical interface, which mainly consists of the graphical representation.It turns out, that wrongly chosen image frequency, to detail, chaotic and so, can affects the user's work efficiency.Thus, the image frequency is one of the components that should be investigated during graphical interfaces design.The main purpose of this work is to analyze the impact of the selection of the frequency level of images depending on the human thinking styles.The paper presents the selection of images with given frequency depending of one thinking style.To test the research hypothesis, we conducted perceptual experiments in which images with different intensity in different frequency bands were presented.Finally, we obtained statistical significance between the selection of images with different levels of frequency bands of images for the group of respondents with the thinking style based on the Ideas and the rest of the thinking groups.
3. Quantum optimization for machine learning

Machine learning is a branch of Artificial Intelligence that seeks to make machines learn from data. It is being applied for solving real world problems with huge amount of data. Though, Machine Learning is receiving wide acceptance, however, execution time is one of the major concerns in practical implementations of Machine Learning techniques. It largely comprises of a set of techniques that trains a model by reducing the error between the desired or actual outcome and an estimated or predicted outcome, which is often called as loss function. Thus, training in machine learning techniques often requires solving a difficult optimization problem, which is the most expensive step in the entire model-building process and its applications. One of the possible solutions in near future for reducing execution time of training process in Machine learning techniques is to implement them on quantum computers instead of classical computers. It is conjectured that quantum computers may be exponentially faster than classical computers for solving problems which involve matrix operations. Some of the machine learning techniques like support vector machines make extensive use of matrices, which can be made faster by implementing them on quantum computers. However, their efficient implementation is non-trivial and requires existence of quantum memories. Thus, another possible solution in near term is to use a hybrid of Classical Quantum approach, where a machine learning model is implemented in classical computer but the optimization of loss function during training is performed on quantum computer instead of classical computer. Several Quantum optimization algorithms have been proposed in recent years, which can be classified as gradient based and gradient free optimization techniques. Gradient based techniques require the nature of optimization problem being solved to be convex, continuous and differentiable otherwise if the problem is non-convex then they can find local optima only whereas gradient free optimization techniques work well even with non-continuous, non-linear and nonconvex optimization problems. This chapter discusses a global optimization technique based on Adiabatic Quantum Computation (AQC) to solve minimization of loss function without any restriction on its structure and the underlying model, which is being learned. Further, it is also shown that in the proposed framework, AQC based approach would be superior to circuit-based approach in solving global optimization problems.
Chinese poetry generation model with UniLM

Many existing Chinese poetry generation models are based on Recurrent Neural Network Language Model. The Chinese poetry generated by these methods have serious defects in rhythm and fluency. A method of using Unfied Language Model Pre-training for Natural Language Understanding and Generation(UniLM) to generate Chinese poetry is proposed. The model is based on Transformer network. UniLM not only has the same good natural language understanding ability as BERT, but also has the ability of natural language generation. It is a pre-training language model that can generate and understand. This paper uses UniLM to realize the automatic generation of Chinese poetry, through the experiment on Chinese poetry data set, it can show that the Chinese poetry generation method based on UniLM is better than the proposed ones. It has significantly improve in fluency, rhythm and poetry.
Looking for Some Historical Roots

Knowledge comes from the observation that what surrounds us is provoked by the questions people poses when thinking on it; is reachecorrespondingd thanks to reasoning, and usually through establishing hypotheses and further testing them and their consequences against the reality. Speculation lays at the basic level of both ‘thinking on it’, and ‘establishing and testing hypotheses’.
Virtual Dog

Present project aims to develop a navigator mobile application for blind people, in such a way that it is not just a routing path guide; it will describe your current environment in a configurable radio. It will be integrated in a social network that allows adding new elements into the environment that will be shared by all the users. And it will also work inside building by estimating the current position using step counter, compass, altimeter, etc.
Generalized Multi-server Platform-Based Remote User Authentication

The user authentication scheme based on the multi-server environment approach provides an additional facility over the traditional single server environment. The proposed method uses a combination of a user’s random string and password to design a remote user authentication scheme over a multi-server environment. The involvement of a smart card provides the user’s access to different servers after registering once with the registration center and uses the same identity and password to access the several. This phenomenon resolved the problem of users managing and memorizing the different credentials that enhance the security level compared to the traditional single server model. In addition, the proposed scheme contains all the goals and security requirements. The corresponding simulation is performed using the extensively used automated validation application tool AVISPA, and the derived simulation will indicate that the proposed scheme is secure and lightweight.
Pedagogical Applications of Corpus Linguistics in the Twenty-First Century

In this digital era, the role of computer technology as a resource for instruction of foreign language learners is increasing as educators recognise the ability of computer technology to produce both independent and collaborative learning environments. Computer technologies, for example the Internet, multimedia, and hypermedia have been introduced in English Language Learning and Teaching (ELLT) to foster language learning process, all of which fall under the category of Computer-Assisted Language Learning (CALL). Corpus linguistics is a systematic analysis of the actual (real) production of language (either spoken or written), in which texts are assembled using computer technology (concordancer) to form a large collection of authentic texts, called a corpus (plural-corpora) that comes in various sizes. However, despite immense research on corpus linguistics in these recent decades, the potentials and limitations of Data-Driven Learning (DDL), the application of corpus linguistics in English Language teaching (ELLT) have not been widely discussed. Hence, this chapter aims to review the potentials and limitations of DDL as a means of opening up opportunities for further studies. The pedagogical application of DDL was instantiated in the chapter for indicating the differences between DDL and non-DDL approaches. This insightful information is highlighted as a means of promoting DDL and producing independent learners in the 21st century classroom. The DDL type of learning also trains learners to be independent, self-corrective, constructive, and autonomous especially in finishing the communicative tasks.
Stress Finite Element Modeling Analysis of Simply Supported Beam Bridge

Abstract In order to quickly and accurately analyze the stress and strain of simply supported beam bridge, overcome the problems of insufficient lightweight of finite element analysis software, single analysis type and difficult expansion, a bridge stress and stress weakness analysis method based on finite element analysis is proposed. This method improves the analysis accuracy by independently designing the analysis program and using symbolic computation, and can optimize and supplement the existing analysis software according to the demand. The example verification shows that this method can effectively analyze the bridge stress, accurately analyze multiple stress weaknesses of the model, and display its position. The accuracy and speed of the analysis are considerable.
Conclusions for Part II

Human beings are animals endowed with a great curiosity. They continuously ask themselves how things are, where they come from, and where they go to. Questioning is at the origins of reasoning; and possibly, without the capability of self-questioning and guessing, neither directed thinking, nor reasoning, will exist. Their existence makes them a matter of study.
Retraction: Automatic Voting System Using Convolutional Neural Network (J. Phys.: Conf. Ser. 1916 012074)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation. IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process. IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further. [1] Cabanac G, Labbé C and Magazinov A 2021 arXiv: 2107.06751v1 Retraction published: 23 February 2022
Learning structure-aware transformations for arbitrary image style transfer

Arbitrary image style transfer aims to mimic the artistic features of a randomly given style image while maintaining the semantic characters of a reference content image. Existing algorithms have achieved astonishing style transfer results. However, they are insufficient to capture the global information of the content image due to the locality in convolutional neural networks. As a result, the content structures of the stylized images are disrupted by scattered textures. To address this issue, we propose to embed additional global spatial information of the reference content image into image style transfer algorithms with the adaptive instance normalization trick. We train a light-weighted network to distill the global structural information provided by the depth map of the reference content image. We then utilize the refined results to enhance the transformations between deep features of the inputs. Experimental results show that our proposed method can generate stylized outputs with more consistent structures and less unwanted textures, achieving impressive visual effects.
Smartphones at Schools? Yes, Why not?

During ages, new and innovative learning technologies are often criticized or rejected, while their full acceptance is commonly delayed. As a result, the progress of Smart Learning Environments is noticed nowadays to be delayed, while educator debate about the technology used in classroom effectiveness. Author’s objective is to explore potential factors in order to render modern communication devices such as mobile phones and tablets suitable for learning in schools, taking into consideration possible advantages or disadvantages. In the case that students use mobile devices during learning procedure, a shortage of suitable content as well as adequate integration of educational and edutainment systems employing gamification techniques within the school framework. These factors are considered to be sufficient enough to strengthen and improve learning experience and effectiveness.
Video Indexing System Based on Multimodal Information Extraction Using Combination of ASR and OCR

With the ever-increasing internet penetration across the world, there has been a huge surge in the content on the worldwide web. Video has proven to be one of the most popular media. The COVID-19 pandemic has further pushed the envelope, forcing learners to turn to E-Learning platforms. In the absence of relevant descriptions of these videos, it becomes imperative to generate metadata based on the content of the video. In the current paper, an attempt has been made to index videos based on the visual and audio content of the video. The visual content is extracted using an Optical Character Recognition (OCR) on the stack of frames obtained from a video while the audio content is generated using an Automatic Speech Recognition (ASR). The OCR and ASR generated texts are combined to obtain the final description of the respective video. The dataset contains 400 videos spread across 4 genres. To quantify the accuracy of our descriptions, clustering is performed using the video description to discern between the genres of video.