Reviewerly/exHarmony huggingface dataset:
Conceptualization of the problem of creativity in the context of keystone fundamentals of cultural analysis

The aim of the work is to investigate the problem of creativity based on the potential of cultural analysis. The methodology of the research is based on general scientific principles, namely, terminological and systemic. The aim and objectives of the publication led to the usage of such research methods as analysis, synthesis, generalization, which made it possible to clarify the meaning of a number of concepts and terms. Scientific novelty. Emphasis is made on the importance of interdisciplinarity, and personalization as factors that “anatomize” creativity, highlighting such structural element as “artistic creativity”, deepening in this way, the idea of a creative personality that can not only create but also change the paradigm of art. The idea of “cultural turn” is involved, in the logic of which the idea of creativity is corrected. Conclusions. Based on the interpretation of the phenomenon “creativity - artistic creativity” and taking into account the experience of Ukrainian experts, a new definition of creativity is proposed: “Creativity is a purposeful activity to create fundamentally new spiritual and material values that have both universal and national historical and cultural significance”. The stated definition is based on an interdisciplinary basis and outlines areas for further theoretical investigation in the sphere of cultural knowledge, as it allows to identify topics that need deep study in the context of factors of cultural analysis.&#x0D; Key words: creativity, cultural analysis, “cultural turn”, “negative psychology”, avant-garde, purposeful activity, “fundamentally new”, experiment.
Encapsulating Secrets Using Lockable Obfuscation and a RMERS-Based Public Key Encryption

Lockable obfuscation, a new primitive that occurs in cryptography, makes it possible to execute arbitrary polynomial-sized functions and recover a secret under specific equality conditions. More concretely, if the function executed over a specific input produces an output that matches an expected target value, here denoted by a, some secret string of bits s is exposed. Written in algebraic terms, if f:X→A has the property that for some x,f(x)=a, s is revealed. This work explores the possibility for safely decrypting ciphertexts, and based on the recovered plaintext’s equality to a stored message, to reveal some secret. Concretely, this work provides a review of existing, well-known public key encryption schemes and argues for the efficiency of a new one relying on the ratio Mersenne hypothesis (RMERS), which is to be used in conjunction with a lockable obfuscator. This work explores the advantage conferred by this scheme, especially in the minimization of the branching program’s number of levels that need to be obfuscated. The drawbacks of such schemes are also pointed out, given that they currently require the LWE evaluations level-per-level, one output bit at a time.
Analisis Problematika Pendidik dalam Pembelajaran Daring pada Mata Pelajaran Matematika di Sekolah Menengah Pertama

Some obstacles will certainly be encountered in the online, but that is where the challenge is for teachers to face these obstacles and find the right solution to overcome the problems that occur in the midst of online. This study aims to describe the problems of educators in online learning in mathematics subjects in junior high schools. This research uses a qualitative approach with the type of library research. The qualitative approach is an approach that can be used to examine the condition of natural objects, where the researcher is the key instrument, the data analysis is qualitative. The results of this study indicate that the problems experienced by educators during online learning, especially in mathematics subjects in junior high school, are the understanding that students have of the mathematical concepts of junior high school students, the low motivation of students towards learning mathematics, especially junior high schools, attitudes from students who show negative attitudes, namely feelings of boredom, and internet quotas.
Current status of real-world big data research in the cardiovascular field in Japan

<h2>Summary</h2> Real-world data (RWD) are observational data obtained by collecting, structuring, and accumulating patient information among the medical big data. RWD are derived from a variety of patient medical care and health information outside of conventional research data, and include electronic health records, claims data, registry data of disease, drug and device, health check-up data, and more recently, patient information data from wearable devices. They are currently being utilized in various forms for optimal medical care and real-world evidence (RWE) is constructed through a process of hypothesis generation and verification based on the RWD research. Together with classic clinical research and pragmatic trials, RWE shapes the learning healthcare system and contributes to the improvement of medical care. In the cardiovascular medical care of the current super-aged society, the need for a variety of RWE and the research is increasing, since the guidelines established over time and the medical care based on it cannot necessarily be the best in accordance with the current medical situation. In this review, we focus on the RWD and RWE studies in the cardiovascular medical field and outlines their current status in Japan. Furthermore, we discuss the potential for extending the studies and issues related to the use of medical big data and RWD.
Fraudulent Account Detection in the Ethereum’s Network Using Various Machine Learning Techniques

On the Ethereum network, users communicate with one another through a variety of different accounts. Pseudo-anonymity was enforced over the network to provide the highest level of privacy. By using accounts that engage in fraudulent activity across the network, such privacy may be exploited. Like other cryptocurrencies, Ethereum blockchain may exploited with several fraudulent activities such as Ponzi schemes, phishing, or Initial Coin Offering (ICO) exits, etc. However, the identification of parameters with abnormal account characteristics is not an easy task and requires an intelligent approach to distinguish between normal and fraudulent activities. Therefore, this paper has attempted to solve this a problem by using machine learning techniques to introduce a robust approach that can detect fraudulent accounts on Ethereum. We have used a K-Nearest Neighbor, Random Forest and XGBoost over a collected dataset of 4,681 instances along with 2,179 fraudulent accounts associated and 2,502 regular accounts. The XGBoost, RF, and KNN techniques achieved average accuracies of 96.80 %, 94.8 8%, and 87.85% and an average AUC of 0.995, 0.99 and 0.93, respectively.
Model Compression and Acceleration Based on Progressive Random Pruning Algorithm

The deep neural network model usually has a large number of weight parameters. In order to reduce its occupation of storage space, a large number of weights pruning algorithms haw been proposed successively. Given the above problems, we found that the traditional weight pruning algorithm needs a lot of computation to evaluate the importance of parameters before pruning. This paper omits the step of evaluating the importance of parameters, proposes random pruning, and proves that the model after random pruning can still have a good performance after fine- tuning. In addition, a sparsity function is introduced in the pruning process, and the model sparsity is used to guide the pruning to enhance the stability of the network. Finally, the low-rank decomposition algorithm is combined to further realize the acceleration of the network. This paper uses the CFAR-10 dataset to compare the proposed algorithm with similar algorithms on ResNet-50 and VGG-16 networks, and it is superior to similar algorithms in terms of compression rate, FLOP and stability. Compared with the benchmark network, the algorithm in this paper achieves 1.99 x and 2. 8x the compression rate, 1.87 x and 1.83 x the acceleration effect on the two networks, respectively.
Few-Shot Text Classification via Semi-Supervised Contrastive Learning

Text classification is a longstanding research topic in natural language processing (NLP). Deep learning has emerged as an effective paradigm for solving text classification problems. However, the performance of a deep model is heavily reliant on large-scale human-annotated data. In this paper, we propose a Semi-Supervised Contrastive Learning (SSCL) framework for text classification, which can significantly improve the performance of deep models in the case of limited labeled data. The proposed framework consists of two components: a pseudo label generation strategy and a contrastive learning scheme for text classification. We first devise a prompt-based strategy for training Bidirectional Encoder Representation from Transformers (BERT), with a small amount of human-labeled data, to obtain a task-correlation model capable of generating pseudo labels for unlabeled text. Then, for the text classification task, we use a two-step contrastive learning scheme: pre-training a deep model with pseudo labels as supervision to capture inter-class patterns while mitigating the negative impact of pseudo label noise, and then fine-tuning the pre-trained model with human-labeled data using a supervised contrastive learning approach. Benefiting from the generated pseudo labels and anti-noise contrastive pre-training, we only use a small amount of labeled data during the training process for the downstream text classification tasks. Experimental results on the twitter sentiment classification dataset and the aspect classification dataset show that our method significantly outperforms baseline methods in a few-shot setting.
Implementing SQL Server Audit via SQL Scripts

To make SQL Server auditing work, you need two or three components depending on what you want to audit. Chapter 3, “What Is SQL Server Audit?”, covered what each of these components are and the audit categories and groups associated with them. In this chapter, you will learn how to set up the audit with SQL scripts. Chapter 4, “Implementing SQL Server Audit via the GUI,” covered how to set up SQL Server Audit via the GUI in SSMS. In this chapter, you will learn how to set up SQL Server Audit via scripts.
Does entrepreneurship financing contribute to industrial development in Nigeria Evidence from small and medium scale enterprises

Underdevelopment of industrial sector has been one of the critical challenges confronting Nigeria in the last few decades. Against this backdrop, this study focuses on the relationship between entrepreneurship financing and industrial development in Nigeria between 1990 and 2018. Data were collected from the Central Bank of Nigeria Statistical Bulletin using Dynamic Ordinary Least Square and Granger causality as techniques of estimation. Consequently, manufacturing and food processing business financing and industrial output have an insignificant positive relationship. Aggregate commercial banks financing has a significant positive impact on industrial output. Meanwhile, manufacturing and food processing business financing Granger caused industrial output in the country. Therefore, the following recommendations are made for the policymakers in Nigeria. If the goal of the Nigerian policy makers is industrial development, manufacturing and food process SMEs business financing should be encouraged by all the financial institutions especially deposit money banks in disbursement of loans and advances.
Measuring the level of administrative and financial corruption and its impact on economic development: A field study on workers in the public sector in Lebanon

The study aims to measure the degree of administrative and financial corruption and its impact on economic development, and it included an independent variable (administrative and financial corruption) and a dependent variable (economic development), where the descriptive analytical approach was adopted. The study sample consisted of 130 employees in 4 ministries in Lebanon (at the level of heads of departments and divisions). randomly selected, The (SPSS) program was used through descriptive statistical methods, frequencies, arithmetic averages, standard deviations, Cronbach Alpha coefficient, Correlation Coefficient, Simple Linear Regression, and(ANOVA) to test the validity of the hypotheses, and the study reached the following results: The total arithmetic mean of the administrative and financial corruption variable reached (3.87), which is a high level of importance. There is a medium inverse correlation between financial and administrative corruption and economic development. There is a statistically significant effect at the level (α ≤ 0.05) between financial and administrative corruption and economic development. The most important recommendations: Issuing a law to lift banking secrecy and developing a comprehensive national strategy to combat corruption in various economic and non-economic fields, which would reduce or prevent the spread of administrative and financial corruption.
An Introduction to The Development of Accounting Guidelines for Cryptocurrencies (Experimental Study)

Cryptocurrency is a form of decentralized digital money that exists only electronically and transcends international borders, due to its innovative characteristics and its growing popularity in the economic and technological worlds, Bitcoin and other digital “currencies” are expected to become dominant, leading to the need for processing its accounting. There are no guidelines on how to process cryptocurrency transactions. The aim of this research is to define a conceptual approach to accounting for encrypted digital currencies, and to benefit from new theories. Qualitative analysis is applied where relevant studies are analyzed to determine the main characteristics of cryptocurrencies and to identify issues of accounting policy. The characteristics of encrypted digital currencies and the issues of accounting policy constitute the main questions in the questionnaire being analyzed. The analysis is carried out using the statistical program Stata and statistics to clarify the relationship between the characteristics of cryptocurrencies and the issues of accounting policy that are identified. Where the study found that the accounting policy recommended by cryptocurrencies is to recognize and measure the fair value
P9.01: Impact of the Pandemic on Liver Transplantation and Use of Telemedicine – Clinical Hospital UNICAMP

Introduction: The covid-19 pandemic has led to changes in the care of transplant patients, including authorization from the SNT/MS/Brazil for its use since April 2020. Objective: To assess the impact of COVID-19 on kidney and liver transplantation and the use of telemedicine. Method: To verify the number of visits, number of transplants, types of assessments, incidence of COVID-19 in transplant recipients, use of immunosuppression and impact on the number of transplants, descriptive statistics were used. Result: A specific TCLE was implemented for the pandemic season, teleguidance and teleconsultations were carried out institutionally with medical, nursing, psychology and social assistance assessments, the return frequency changed thanks to the 6-month LME (saving in TFD about 20 thousand/patient). 4,000 consultations were carried out in 2020, with a 50% drop in face-to-face consultations (4 outpatient clinics/week) with directed anamnesis, the sending of images and outpatient results was done by institutional email as well as renewal of the MELD (for patients in list). There was a 25% reduction in the number of transplants (lack of an ICU bed and patient refusal due to fear/fear), a 50% drop in the number of patients enrolled in the list. The immunosuppression adjustment was mainly performed in the second wave (November 2020 to March 2021). We observed 30 COVID cases in 750 follow-up liver transplants and 100 cases in 3000 follow-up kidney transplants. In liver transplantation the mortality was 25% and in kidney transplantation it was 26%. The most frequent comorbidities were age > 60 years, presence of diabetes and time greater than ten years after transplantation. 2 patients with COVID-19 and 2 with kidney transplants were transplanted with liver, which evolved well and there was 1 patient transplanted due to complications after IVM/COVID-19 who also evolved well. Conclusion: COVID-19 had a high impact on transplantation in our service and telemedicine is probably here to stay.
A Robust Phase Unwrapping Algorithm With High Measurement Range Based on Unscented Kalman Filter in Interferometric Optical Fiber Sensing

Phase unwrapping is the prerequisite to obtain the true phase in interferometric fiber sensing. This article proposes a method based on an unscented Kalman filter (UKF) for interferometric fiber sensors. This method can break the limitation that the traditional phase unwrapping methods fail with a high probability when the differences in phase change are more than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> radians according to the Itoh criterion. Then, the measurement range of the phase signal can be expanded. This method combines the true phase and the phase gradient into the state vector estimation for UKF. The feasibility of this method is verified theoretically and experimentally. In the specific experiment, the phase signal with a maximum absolute phase difference of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.5\pi $ </tex-math></inline-formula> (about 4.705) between adjacent sampling points can be recovered perfectly. The time and frequency domain results using this method show better performance. This method can effectively improve the detection range of the system and reduce the sampling rate to a certain extent, which is suitable for large-scale array systems.
INFORMATION SYSTEM MODEL OF WEBSITE-BASED TAX PAYMENT AND VILLAGE BUILDING

Property tax is one of the instruments in obtaining funding for village development. Property tax proceeds are used to finance development in the area. Good management is needed to maximize property tax revenue. This study aims to help the model to design and develop an e-village property tax information system. the method used is the description method and is used to model the system while the prototype method is used to build the e-village system. The testing stage uses the black box technique and the usability test to test the quality, usability, and reliability of the system functions that have been made. This research succeeded in building an e-village model that is efficient and can be used easily to carry out property tax transactions. the results of this study also help villagers easily obtain information and assist in the processing of village data that is structured, organized and to help calculate the amount of property tax costs to be paid. The conclusion of this study is that the system has been made to facilitate the community and village officials in calculating the property tax, managing and obtaining village information more effectively and efficiently.
Investigating the Effects of Glyphosate on the Bumblebee Proteome and Microbiota

Glyphosate is one of the most widely used herbicides globally. It acts by inhibiting an enzyme in an aromatic amino synthesis pathway specific to plants and microbes, leading to the view that it poses no risk to other organisms. However, there is growing concern that glyphosate is associated with health effects in humans and an ever-increasing body of evidence suggests potential deleterious effects on other animals including pollinating insects such as bees. Although pesticides have long been considered a factor in the decline of wild bee populations, most research on bees has focussed on demonstrating and understanding the effects of insecticides. To assess whether glyphosate poses a risk to bees, we characterised the changes in survival, behaviour, sucrose solution consumption, the digestive tract proteome, and the microbiome in the bumblebee Bombus terrestris after chronic exposure to field relevant doses of technical grade glyphosate or the glyphosate-based formulation, RoundUp Optima+®. Regardless of source, there were changes in response to glyphosate exposure in important cellular and physiological processes in the digestive tract of B. terrestris , with the abundance of proteins associated with oxidative stress regulation, metabolism, cellular adhesion, the extracellular matrix, and various signalling pathways being altered. Interestingly, proteins associated with endocytosis, oxidative phosphorylation, the TCA cycle, and carbohydrate, lipid, and amino acid metabolism were differentially altered depending on whether the exposure source was glyphosate alone or RoundUp Optima+®. In addition, there were alterations to the digestive tract fungal microbiota of bees depending on the glyphosate source. No impacts on survival, behaviour, or food consumption were observed. Our research provides insights into the potential mode of action and consequences of glyphosate exposure at the molecular and cellular levels in bumblebees and highlights issues with current risk assessment of pesticide formulations where the impact of co-formulants on non-target organisms are generally overlooked.
Health Certificate Exchange for Travel Management in Pandemic: Review and Perspectives

Since 2020, the COVID-19 pandemic severely disrupted regular off-line business activities. This unprecedented situation inspires the valuable research on facilitating off-line business under pandemics. In this article, we conceptualized the problem as travel management in pandemic (TMiP) and analyzed it from the technological perspective. Enabling travel in a pandemic not only needs a health certificate to prove that the traveler is safe but also entry/exit permissions from both the origin and the destination regions, determined by the local situation and measures. Thus, TMiP is related to technical, social, economic, and administrative factors. By conducting a review on the literature covering the health certificate technology, its adoption in practice, and the exchange system technology published during the COVID-19 pandemic, we learned about their usefulness and limitations in TMiP. Second, we analyzed the review outcomes to infer the six distinctive technical challenges of TMiP. Third, we analyzed the feasibility of referential solutions to these challenges and showed their applicability and limitations. Finally, we offered the perspectives on new TMiP solutions and concluded that they rely on adapting existing solutions, creating new ones, and integrating all of them. We also presented future research directions in a holistic view of TMiP technical solutions. Overall, the findings of the study will stimulate more research on a more coordinated, comprehensive, and intelligent TMiP solution. We also hope this article can help practitioners to restart economies in a pandemic.
Auditing Azure SQL Managed Instance

This chapter will show you how to audit your Azure SQL Managed Instance. In some cases, it’s similar to SQL Server auditing, and in other cases, it’s different. Azure SQL Managed Instance can be audited with SQL Server Audit and/or extended events, but each require some different settings when compared with SQL Server auditing on a VM.