bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart Healthcare Systems: The Impact of IoT on Medical Diagnostics and Treatment
Authors: Manwal Manika
Published: May 2023

AbstractThe rapid advancement of technology has led to the development of the Internet of Things (IoT), which is revolutionizing various sectors, including healthcare. Smart healthcare systems, powered by IoT, have the potential to significantly improve medical diagnostics and treatment, thus enhancing patient outcomes and reducing healthcare costs. This paper aims to analyze the impact of IoT on medical diagnostics and treatment, focusing on three key areas: remote patient monitoring, telemedicine, and artificial intelligence (AI) in diagnostics. Remote patient monitoring allows for real-time data collection and analysis of patient health, enabling healthcare professionals to make informed decisions and provide prompt interventions. IoT devices, such as wearable sensors and smart medical equipment, facilitate the continuous monitoring of vital signs and symptoms, leading to timely detection of abnormalities and improved disease management. Telemedicine, enabled by IoT, allows healthcare providers to virtually consult with patients, reducing the need for in-person visits and expanding access to medical care, especially for individuals in remote or underserved areas. This technology enhances patient-provider communication, fosters a more personalized approach to medicine, and increases the efficiency of healthcare services. Finally, AI-powered diagnostic tools, integrated with IoT devices, can process and analyze large volumes of data to identify patterns and correlations, leading to more accurate and efficient diagnoses. These systems can also aid in treatment planning and decision-making, resulting in improved patient care and outcomes.
Healthcare Business in India: An Empirical Study of Challenges and Growth
Authors: Srivastava Barun
Published: May 2023

Health-Care services is considered one of the noble professions in the world. It is run by both private and public sector in India while there are examples of the countries where the whole sector is run by the government. Private players have definitely helped in providing people with a better accessibility although it may be subject to cost pf services. Poor still rely on government services to get themselves treated. Government has also played an important role in providing an equitable distribution of services. The business of healthcare services is among the fastest growing sectors. It is now a lucrative business for investors and thus many players are trying to enter. Although there are still many challenges and hindrance to growth of the sector in India. The study aims to point out the challenges as well path to growth of the health care sector. The study had considered 187 people from healthcare business sector to know the challenges and growth in healthcare business in India and concludes that there is significant effect of different challenges in growth of healthcare business in India.
Critical Analysis Reasons of Non-Performing Assets: An Analytical Study
Authors: Rawat Monika
Published: May 2023

“When a person delays the payment of the loan or an amount which was due on him through the delay in payment in either interests or instalments or principal amount, that particular loan or amount is termed as Non-Performing Asset.” The stability of a nation's banking sector is best gauged by the its margin of non-performing assets (NPAs) in the total assets. This study's objective is to examine the growing trend of the NPA in the sector in order to determine the specific contributions made by the major banks. Banks in the private sector’s NPA rise is not as quick as that of banking institutions, SBI, and its affiliates, according to study. Due to the ineffective management of the problem of subprime loans by the banking institutions and the affiliate banks of SBI, the rise in such loans has been very significant.
Reasons Of Credit Card Usage In India: An Empirical Study Of Young Indian Consumers
Authors: Rani Neha
Published: May 2023

Credit card usage and penetration in India have been found to be quite low when compared to debit cards. Even if banks provide the greatest services, there are still concerns regarding the hazards associated with carrying a credit card throughout India. As a result, this study explores the causes for credit card behaviour among Indian customers and identifies the aspects that impact acceptance. Yet, there aren't many studies that look at credit card adoption. The model analysis suggests that perceived utility, usefulness and ease of use, risk involved, facilitating conditions, perceived trust, social impact, and perceived advantages are the primary predictors of credit card usage in India.
Analyze the Progress of Quality Service Offered by Public Sector Banks
Authors: Batola Megha
Published: May 2023

The banking sector has been crucial to the expansion and diversification of the Indian economy. The primary goal of this research is to use the SERVQUAL model to compare the actual quality of service provided to a subset of the public with their expectations of that same quality. Banks essentially provide the same suite of services and products. What makes this company stand out is the high standard of service it provides. Many studies have examined the correlation between service quality and satisfied customers in retail banking. Nevertheless, it indicates that not enough research has been done to determine the effect of human and non-human factors on consumer satisfaction with regard to rural economic environments. In addition to the above research backdrop, The major purpose of this research was to identify the factors that contribute to consumer satisfaction with a service. A total of 210 residents in the Karur district were surveyed for this study. The conceptual framework was built using a deductive method, and hypotheses were developed as a result. Data were collected using a survey format, and were analyzed using the SPSS 20 suite of statistical programs. Co-Relations were used to test the hypotheses.
Behavior of the Consumer Towards the Advertisement
Authors: Kaur Rupinder
Published: May 2023

This research piece examines how advertisements influence consumers' final purchase choices. Customers' attitudes and actions toward a product may be impacted by the advertising campaign's portrayal of the brand, its persuasiveness, and the presence of a celebrity endorsing the product. Advertising influences consumer behavior through shaping consumers' perceptions of the product. The research shows that consumers are greatly influenced by commercials that are both creative and well produced. Quality and cost are also taken into account since they have an effect on customer decisions. The point of advertising is to see how it affects consumers' purchasing decisions.
Study the Awareness Level on Environment Accounting and Disclosure Practices
Authors: Singh Bhanu Pratap
Published: May 2023

This research was conducted to have a better understanding of the state of environmental accounting disclosure in India and the steps that may be done to enhance its quality. The purpose of this article is to examine Environmental Accounting from a business perspective and highlight its significance. It has been noted that India does not have a uniform approach to the presentation of information related to environmental accounting. Tech Mahindra was evaluated on a number of fronts. Although environmental reporting has been included into corporate reporting, the absence of comparability and verifiability, two defining characteristics of accounting data, is evident from the examined sample units. Public annual reports of environmentally conscious Indian enterprises were gathered for 2018-2019 in order to analyze their environmental disclosure policies. The yearly reports were subjected to a content examination.
Relevance Feature Discovery for Text Mining
Authors: Sharma Vikrant
Published: May 2023

Due to large size words also data patterns, it is difficult to ensure the quality of relevant characteristics that are found in text documents that describe user preferences. Most widely used text mining and classification techniques now in use have embraced term-based strategies. However, polysemy and synonymy issues have affected them all. The theory that pattern-based approaches should outperform term-based ones in performance in expressing user preferences has been often held throughout the years, however text mining still struggles with how to employ large-scale patterns successfully. This research introduces a novel methodology for relevance feature discovery to address this hard problem. It finds higher level features in text texts that are both positive and negative patterns and uses them instead of low-level features (terms). Additionally, it organised terms into categories and updates term weights according to the patterns and specificity of those distributions. Significant tests employing this model on the datasets RCV1, TREC themes, and Reuters-21578 reveal that it performs noticeably better than both the most advanced term-based approaches and pattern-based methods.
Automated Soil Moisture Monitoring using Wireless Sensor Networks
Authors: Panwar Neeraj
Published: May 2023

In order to maximize the use of water for agricultural crops, an automated soil moisture monitoring system was created. A wirelessly dispersed network of soil-moisture and temperature sensors is employed in the system to monitor conditions in the root zone of the plants. In addition to these functions, a gateway device can manage the data collected by sensors, trigger actuators, and transmit data to a web application. A microcontroller-based gateway was built with an algorithm that was based on temperature and soil moisture threshold values for the purpose of managing the amount of water that was available. The electricity for the system came from photovoltaic panels, and it had a bidirectional communication connection that was built on an interface between cellular technology and the internet. This gave customers the ability to plan watering and analyse data via a web page. When compared to the conventional irrigation methods that are utilised in the agricultural zone, the automated system's test run on a field of sage crops resulted in water savings of up to 90 percent. The test lasted for 120 days. Since its implementation 18 months ago, the automated technology has been utilised effectively in all three of its designated places. Due to the low cost and energy independence of the gadget, it has the potential to be useful in places that have limited access to water and are located in remote areas.
Investigation and Analysis of the Impact of Interference on Wireless Communication Systems
Authors: Kumar Nitin
Published: May 2023

Wireless communication systems are widely used in modern society, and their reliability is paramount to ensure effective communication. The aim of this investigation is to analyze the effects of interference on wireless communication systems. Interference is a major issue in wireless communication systems and can significantly degrade the system's performance. This paper presents a survey of investigations into the effect of interference on wireless communication systems. It provides an overview of the various types of interference and their effects on wireless communication systems, as well as techniques used to mitigate interference in wireless communication systems. It also reviews recent research on interference in wireless communication systems, which has shown that interference can significantly degrade the performance of wireless communication systems. The paper also discusses the challenges and future directions in the investigation of interference in wireless communication systems, such as the development of interference models that accurately capture the complex nature of interference, the design of interference mitigation techniques that can adapt to changing interference conditions, and the optimization of wireless communication systems to minimize the impact of interference. Finally, the survey highlights the importance of investigating the effect of interference on wireless communication systems and provides a comprehensive overview of the various techniques used to mitigate interference.
Understand the Performance of Service Employees in Selected White Goods
Authors: Batola Megha
Published: May 2023

All customers have needs that they want to have met, and they feel strongly about doing so. Consumers shop for products with the expectation that such items would fulfill their needs. If he is not certain that the product will meet his demands, he will reject it and look for one that does. For this reason, it is essential for every business to provide for the demands of its customers. Consumers are treated as if they were royalty, especially in a free market economy. This research is important because it will help us determine whether or not the things we've chosen to employ around the home are really meeting the needs of our consumers. It's not easy to deduce what consumers want when they're shopping for a product or service. Household appliances for the general public make things even more complicated.
A Study on Enhancing the Properties of Geopolymer Concrete with Hybrid Fibers
Authors: Shah Mahesh Chandra
Published: May 2023

As the manufacture of one ton of Portland cement releases about one ton of CO2 into the atmosphere, and since burning lime stone releases CO2 directly, the cement industry is responsible for around 7% of global CO2 emissions. In the calcination process, the calcium carbonate in limestone is transformed into calcium oxide and carbon dioxide. This step alone is responsible for half of the cement industry's carbon footprint. The use of fossil fuels to heat the kiln results in indirect emissions. When these fuels are used, they contribute to the release of more carbon dioxide. Human activities release greenhouse gases like CO2 into the atmosphere, leading to global warming. In terms of greenhouse gases, carbon dioxide is responsible for around 65% of the warming effect. Geopolymer concrete reinforced with hybrid fibers is the subject of this work.
Adapting Transformer Networks for Document Summarization and Sentiment Analysis
Authors: Mehra Nidhi
Published: May 2023

Due to the increasing number of text-based content sources, the demand for effective sentiment analysis and document summarization techniques has been increasing. Several transformer-based models, including “ELECTRA, BERT, XLNet, RoBERTa, DistilBERT, and ALBERT” have emerged as promising alternatives to traditional methods. This paper aims to study the effectiveness of the different transformer models for performing sentiment analysis and document summarization on the Yelp dataset. The paper aims to analyze the various transformer models' performance on the tasks, identify their weaknesses, and suggest possible improvements. It also thoroughly studies the Yelp dataset, which has over 5 million reviews. The paper introduces the different transformer models that are used for performing document summarization and analysis on the Yelp dataset. We then perform evaluation on these models using various metrics to measure their performance. Some of these include ROUGE, F1-score, AUC-ROC, and accuracy. According to the paper's experimental results, the RoBERTa and BERT models perform better than the other transformer models when it comes to document summarization. In addition, we identified the weaknesses and strengths of each model. We suggest implementing domain-specific training and fine-tuning techniques to improve their performance. The results of the experiment revealed that the RoBERTa and BERT models perform better than the other ones when it comes to document summarization. We also found that the models have weaknesses and strengths, and we suggest using domain-specific training and fine-tuning techniques to improve their performance. The paper contributes to the literature related to the use of transformer-based models in sentiment analysis and documents summarization by providing an extensive analysis of the different models' performance in the Yelp dataset. It also suggests various modifications to improve their capabilities.
A Smart Home System Using Internet of Things (IoT) Technology
Authors: Kumar Divesh
Published: May 2023

The goal of this study is to propose a smart home system that uses internet of things (IoT)-based technologies to improve the effectiveness of home automation and boost energy savings. The system integrates a wide range of sensors, gadgets, and appliances into a coherent system, creating a smart environment that can be remotely controlled and monitored by using an application on a mobile device. The system's goal is to reduce energy consumption by automatically adjusting the temperature, lighting, and other systems in accordance with user preferences and environmental circumstances. In order to learn more about the advantages and disadvantages of installing a smart home system as well as previous studies and research that had been done on the issue, a review of the pertinent literature was conducted. Homeowners in the neighborhood that made up the study's sample were given questionnaires as part of the research process. We surveyed this group of homeowners to learn more about their level of interest in upgrading to a smart home system and their current home automation habits. The results show that there is a lot of interest in and readiness for installing a smart home system, with utility bill savings acting as the primary motivator. The findings also show that there is a high level of readiness to reduce utility expenses. We will discuss the study's limitations in this area, as well as some suggestions for further research, along with the implications for policy and practices. The findings of this study suggest that a smart home system based on internet of things technology has the potential to significantly improve both the quality of life and energy efficiency of homeowners.
Modelling the Velocity Distribution around the Hydraulic Structure
Authors: Chandra Shah Mahesh
Published: May 2023

Intense pressure and velocity oscillations, as well as extensive air entrainment, make the investigation of the hydraulic leap created in stilling basins very difficult. Its intricacy, coupled with the real-world need for stilling basins to dissipate energy, puts physical modelling front and center. Despite stilling basins' essential role in engineering, bibliographic research has often focused primarily on the more familiar case of the classical hydraulic leap. Thus, a physical model of a typical USBR II stilling basin was used to investigate the features of the hydraulic leap in this work. Under this framework, the model investigated the hydraulic jump's free surface profile and velocity distribution. A series of experiments were conducted to compare the efficacy of modern tools like the time-of-flight camera with that of more conventional ones like the Pitot tube. Notwithstanding some of the stated constraints, the findings demonstrated a good depiction of the free sample surface and the velocity distribution. In addition, the used instruments demonstrated the substantial impact the energy dissipation devices had on the flow parameters. In comparison to traditional hydraulic leaps, significant variations in hydraulic jump form and maximum velocity locations within recorded vertical profiles were discovered.
A Low-Power, High-Bandwidth Wireless Communication System for Industrial IoT Applications
Authors: Manda Rajarao
Published: May 2023

In anticipation for an automated future, the Internet of Things (IoT) has rapidly connected more gadgets. Thus, IoT applications' performance requirements present new challenges. Power consumption, service quality, localization, security, and exact wireless channel propagation modelling and characterization are potential issues. When connecting separate sensors wirelessly, the latter is crucial. Channel modelling varies by location because environmental factors affect wireless signal range and quality. Wireless communication technologies are widely used for disaster victim and responder tracking and machine health monitoring in networked manufacturing. Data communication in such systems must be real-time or risk financial losses or human lives. Facilitating real-time medium access via license-free bands in uncontrolled situations is difficult because all communicating stations must be synchronized. (real and nonreal-time). In open communication, medium access protocols cannot filter out unmonitored station traffic.Real-time data collection and analysis improve system efficiency, preventative maintenance, and energy savings. Modulation systems, antenna designs, and power management are just a few of the various ways that must be considered throughout system design and development. IIoT applications also have power, security, and dependability issues. A Low-Power, High-Bandwidth Wireless Communication System for Industrial IoT Applications has a bright future thanks to artificial intelligence and machine learning, 5G networks, new low-power communication technologies, improved security, and blockchain technology. Without this technology, IIoT growth is impossible.
Hate Speech and Reality Check Analysis of Disaster Tweets using BERT Deep Learning Model
Authors: Manchala Sadanandam B. V. Pranay Kumar,
Published: May 2023

This study looks into the application of the BERT model for a reality check analysis of disaster-related tweets. The project intends to tackle the problem of authenticating information on natural disasters posted on social media, which is frequently inaccurate or misleading. Modern natural language processing models like the BERT model have shown promise in various language understanding tasks. The "Disaster Tweets" dataset, which includes tweets linked to genuine disasters and tweets unrelated to disasters, is used in the study to assess the performance of the BERT model. A fine-tuning method is used to train the BERT model on the training set after dividing the dataset into training and testing sets. The model is then put to the test on the test set, and its performance is assessed using metrics like accuracy, precision, recall, and f1-score.

The experimental findings show that the BERT model performed well overall in categorizing tweets about disasters. The model performed well for both groups, with somewhat superior performance for tweets about actual disasters, according to the criteria of precision, recall, and f1-score. According to the accuracy metric, the model's overall accuracy was 86%, which is a promising outcome. The BERT model's potential uses in disaster response and management are also covered in this essay. The model can be used to track down false information about catastrophes, estimate the severity of damage caused by disasters, plan response activities, and create predictive models for future disasters. It can also be used to gauge the sentiment of tweets about disasters. The BERT model must, however, be used in a manner that takes into account a number of issues, including data quality, generalizability, computational resources, interpretability, and ethical considerations.

Overall, this research emphasizes the significance of utilizing NLP approaches to validate the veracity of catastrophe-related information published on social media and enhance disaster response and management initiatives. The BERT model is a useful instrument for reaching this objective, but more investigation is required to solve the model's difficulties and constraints and guarantee its efficacy and dependability in a range of situations.
Implementation of Unsupervised ML Techniques for Behavioural-Based Credit Card Users Segmentation in Africa
Authors: Bumrah Kuljinder Singh
Published: May 2023

A strategy used in marketing is segmentation, which is used to categorise consumers or other entities based on traits like behaviour or demographics. Finding consumer groups that may react similarly to particular marketing strategies, including such email subject lines or display ads, is beneficial. Due to the fact that it allows firms to customise marketing messaging and timing to increase response rates and enhance customer experiences. Customers often exhibit a wide range of behaviours. Businesses frequently employ segments that are based on thresholds. A scientifically based approach to categorise clients is required due to the expanding amount of characteristics and the overall theme of tailored products. The solution is clustering based on behavioural data. The goal of this study is to appropriately classify credit card users so that we can better understand their requirements and behaviour and provide them with relevant marketing offers. We must use the credit card segmentation dataset in our procedure. The input dataset was gathered from a repository of datasets. The pre-processing procedure must then be carried out. After that, feature extraction must be used. The system is then created using the k-means method to come up with the best segmentation plan. We must compute the silhouette score using the k-means technique. The findings of the experiment indicate that the visualisation and customer segmentation based on clustering algorithm.
A Weakly Supervised Refinement Framework for Single Image De-Hazing
Authors: Bhandari Bina
Published: May 2023

Both computational intelligence and pattern recognition include brain damage segmentation and classification as essential components. In this procedure, an effective algorithm was used to segment the damaged area and extract the data from the images using characteristics like GLCM. Based fuzzy C-means clustering technique (M-FCM) is suggested for clustering during the segmentation process. In order to categorise the severity of the brain input, a procedure to identify brain lesions is used in the medical area, along with a way to classify its characteristics using KNN. The major goals of this method are to locate the malignant area on an MRI of the brain and to categorise the severity of that brain in order to increase process efficiency.
Spatiotemporal Image Encoding for Cross-Subject Zero Calibration Driver’s Drowsiness Detection through EEG Signals
Authors: Singh Sumeshwar
Published: May 2023

In this digital signal processing procedure, which analyses Electroencephalogram (EEG) data within a specified framework, the signal's frequency sub-bands were broken down using DWT, and a collection of features representing the distribution of wavelet coefficients was retrieved from the sub-bands. With the use of feature extraction techniques like mean, standard deviation, and variance, the size of the data is decreased. Following that, the classifier utilised these attributes as input to determine if the input data was normal or drowsy, and it classified the data accordingly. To demonstrate the superiority of the classification process, the performance of classification is evaluated. The system's main goal is to increase the precision of patient monitoring systems, remove variations in EEG signals, and enhance process accuracy.
Data Mining Techniques for Early Prediction of Diabetes Mellitus
Authors: Chamoli Sushant
Published: May 2023

The prevalence of diabetes mellitus (DM) as a disease is considered to be a leading cause of mortality rate in the world and tends to effect eye sight, kidney and heart of a human body. Since its occurrence triggers diversity in health issues; detecting it at the right phase is mandatory. For this reason, multiple research scholars have contributed their work in this field of study by adapting to various data mining techniques and thereby reducing the overall workload of medical practitioners. Detection of diabetes mellitus using such techniques have also resulted in its early diagnosis and thereby enhanced the overall treatment of detection at the right stage. The phenomenon of diabetes mellitus can however be categorized as Type 1 and Type 2 diabetes; wherein Type 2 diabetes is responsible to cause heart diseases. Therefore, the primary aim of the research study is to detect the occurrence of DM by utilizing techniques of data mining. For this reason, the authors have implemented the back propagation technique to classify whether an individual is diabetic positive or not. In addition to the back propagation technique, the authors have also implemented Naïve Bayes, Random Forest and J48 with input of neural networks having 8 parameters. The execution of these algorithms is performed using 6 hidden layers of neuron on the PIMA dataset and is further applied on R studio. Throughout the implementation, it has been observed that the back propagation technique generated highest accuracy in comparison to the working implementation of Naïve Bayes, Random Forest and J48.
Speech recognition technology in radiology
Authors: Kudryavtsev Nikita D. , Bardasova Kristina A. , Khoruzhaya Anna N.
Published: May 2023

Speech recognition devices are promising tools for the healthcare system. Speech recognition technology has had a relatively long history of use in Western healthcare systems since the 1970s. However, it became widely used at the beginning of the 21st century, replacing medical transcriptionists. This technology is relatively new in home healthcare. Its active development began only in the early 2010s, and its implementation in healthcare started in late 2010. This delay is due to the idiosyncrasies of the Russian language and the limited computational power present at the beginning of the 21st century.
Currently, complexes of devices and software for speech recognition are used in the voice filling of medical records and can reduce the time for preparing reports for radiological examinations compared with traditional (keyboard) text input.
The literature review provides a brief history of speech recognition technology development and application in radiography. Key scientific studies showing its efficacy in Western healthcare systems are reflected. Voice recognition technology in the home is demonstrated, and its effectiveness is evaluated. The prospects for further development of this technology in Russian healthcare are described.
Double-reading mammograms using artificial intelligence technologies: A new model of mass preventive examination organization
Authors: Vasilev Yuriy A. , Tyrov Ilya A. , Vladzymyrskyy Anton V. , Arzamasov Kirill M. , Shulkin Igor M. , Kozhikhina Daria D. , Pestrenin Lev D.
Published: May 2023

BACKGROUND: In recent years, the availability of medical datasets and technologies for software development based on artificial intelligence technology has resulted in a growth in the number of solutions for medical diagnostics, particularly mammography. Registered as a medical device, this program can interpret digital mammography, significantly saving time, material, and human resources in healthcare while ensuring the quality of mammary gland preventive studies.
AIM: This study aims to justify the possibility and effectiveness of artificial intelligence-based software for the first interpretation of digital mammograms while maintaining the practice of a radiologists second description of X-ray images.
MATERIALS AND METHODS: A dataset of 100 digital mammography studies (50 absence of target pathology and 50 ― presence of target pathology, with signs of malignant neoplasms) was processed by software based on artificial intelligence technology that was registered as a medical device in the Russian Federation. Receiver operating characteristic analysis was performed. Limitations of the study include the values of diagnostic accuracy metrics obtained for software based on artificial intelligence technology versions, relevant at the end of 2022.
RESULTS: When set to 80.0% sensitivity, artificial intelligence specificity was 90.0% (95% CI, 81.798.3), and accuracy was 85.0% (95% CI, 78.092.0). When set to 100% specificity, artificial intelligence demonstrated 56.0% sensitivity (95% CI, 42.269.8) and 78.0% accuracy (95% CI, 69.986.1). When the sensitivity was set to 100%, the artificial intelligence specificity was 54.0% (95% CI, 40.267.8), and the accuracy was 77.0% (95% CI, 68.885.2). Two approaches have been proposed, providing an autonomous first interpretation of digital mammography using artificial intelligence. The first approach is to evaluate the X-ray image using artificial intelligence with a higher sensitivity than that of the double-reading mammogram by radiologists, with a comparable level of specificity. The second approach implies that artificial intelligence-based software will determine the mammogram category (absence of target pathology or presence of target pathology), indicating the degree of confidence in the obtained result, depending on the corridor into which the predicted value falls.
CONCLUSIONS: Both proposed approaches for using artificial intelligence-based software for the autonomous first interpretation of digital mammograms can provide diagnostic quality comparable to, if not superior to, double-image reading by radiologists. The economic benefit from the practical implementation of this approach nationwide can range from 0.6 to 5.5 billion rubles annually.
Using a mobile computer tomography scanner in a field hospital setting to manage patients with COVID-19
Authors: Kudryavtsev Nikita D. , Petraikin Alexey V. , Ahkmad Ekaterina S. , Kiselev Fyodor A. , Burashov Vyacheslav V. , Mukhortova Anna N. , Soldatov Iliya V. , Shkoda Andrey S.
Published: May 2023

The global outbreak of COVID-19 has posed unprecedented challenges to healthcare systems worldwide. Healthcare administrators had to make quick and effective decisions to ensure high quality of medical care standards in new conditions. The need to form a reserve bed fund during the pandemic was due to the high load on city hospitals in Moscow. Due to this fact, temporary reserved hospitals for COVID-19 patients were organized in non-core facilities, such as ice arenas, shopping malls, and exhibition pavilions. This urgency prompted a search for solutions that could provide the necessary level of diagnosis and treatment appropriate to specialized medical facility. Given the technical and time constraints associated with the installation of a fixed computer tomographic scanner, the deployment of mobile computer tomographic scanners emerged as a viable option.
The study aims to share insights gained from using a mobile computer tomographic scanner within a temporary backup hospital setting to treating patients with COVID-19 coronavirus infection. The paper discusses the features, advantages, and disadvantages of mobile computer tomography. It also presents hardware and control room layouts, along with the placement options for the computer tomography device. The research includes the results of dosimetry studies and provides a clinical assessment of the applicability of this type of diagnostic devices.
Introduction to the Digitization of Seismic Data: A User’s Guide
Authors: Ringler Adam T. , Anthony Robert E. , Bastien Patrick , Pascale Adam , Merchant Bion J.
Published: May 2023

Modern seismic data are collected, distributed, and analyzed using digital formats, and this has become a standard for the field. Although most modern seismometers still make use of analog electronic circuits, their data are converted from an analog voltage output to time-tagged counts by way of digitization. Although much of the digitization process is not complicated to conceptualize, there is a fair bit of jargon in digitizer specifications, and a few pitfalls that can arise in the processes of recording and analyzing ground-motion data. In this article, we review some of the fundamental physical properties of data acquisition systems and the basic steps in digitizing data from an analog instrument (specifically a seismometer). We then briefly discuss the digitization process and some of the key properties needed to make these data useful for seismological applications. Finally, we discuss some of the filtering processes that naturally arise from digitization and how it can affect the processing workflow. The end goal is to provide a user guide that will enable seismologists to have a working knowledge of the digitization process. We focus on aspects central to seismological applications and have tried to avoid getting bogged down in signal processing formalism.
Seismic Noise Reduction as a Function of Depth Recorded by a Vertical Array Installed in a 285-m-Deep Borehole at a Gas Storage Field in Northern Italy
Authors: Rossi Camilla , Grigoli Francesco , Gasperini Paolo , Gandolfi Stefano , Cocorullo Chiara , Gukov Timur , Macini Paolo
Published: May 2023

The background seismic noise can be generated by different sources such as, ocean waves (microseisms), atmospheric disturbances (strong wind and storms), and anthropogenic activities, temperature changes and magnetic field variations. Such disturbances are characterized by specific frequency bands, time occurrence (diurnal and seasonal variation), and site location (close to populated areas or to the coasts). Reducing the pernicious effect of these noise sources is one of the main challenges that seismologists and engineers need to face when designing seismic monitoring networks and, more specifically when selecting the hosting site of a seismic station. A solution to partially attenuate the seismic noise effect is achieved by deploying seismic stations in boreholes. A general law estimating the sufficient depth to gain to detect even low seismic events, highly masked by background noise, is fundamental for defining the capability of microseismic network. Here, we aim to characterize the seismic noise level at S. Potito-Cotignola in the Po Valley, Italy, from January 2019 to December 2021 recorded by a broadband seismic station at surface and a vertical array composed by six short-period three-component seismometers installed at depth ranging between 35 and 285 m in borehole. We compute the amplitude noise reduction as a function of depth for different frequencies and we evaluate the depth dependency of the signal to noise ratio for 18 seismic events, with different magnitude (from −0.1 to 2.9) and hypocentral distances (from 12.9 to 37.2 km). Results show that (1) the dependence of noise level with depth follows a logarithmic empirical trend and (2) most of the selected seismic events show that signal to noise ratio increases with depth. The empirical relationships we estimated can be used to help the design of microseismic monitoring networks in similar geological settings.
Breast cancer and the molecular mechanism of estrogen signaling
Authors: ERZURUMLU Yalçın , DOĞAN Hatice Kübra
Published: May 2023

Cancer is a complex pathology that occurs due to the uncontrolled proliferation and growth of cells in any organ or tissue of the body. Breast cancer is the most frequently diagnosed cancer among women worldwide and is the second leading cause of cancer-related deaths. Breast cancer is a pathology that exhibits heterogeneity in which genetic and environmental risk factors play a role. Although many treatment approaches have been developed for breast cancer today, the frequency of the number of patients diagnosed with breast cancer and lost their lives due to this reason is increasing in the world. The most significant limitation to the success of the treatment approaches developing drug resistance in breast cancer cells, and the disease relapses after a certain period and exhibits a more aggressive profile. Therefore, understanding the molecular biology of breast cancer is essential for developing potent therapeutic approaches. It is known that the development of breast cancer is related to changes in direct and indirect signaling mechanisms mediated by estrogen and estrogen receptor. These signaling mechanisms exhibit highly complex interaction patterns. This review summarizes the pathology of breast cancer, estrogenic compounds, estrogen receptors, genomic and non-genomic molecular signaling mechanisms mediated by estrogen and estrogen receptor.
ISTEK AISYIYAH: Aktualisasi Pemikiran Progresif Komunitas Perempuan SULTRA
Authors: Alifuddin Muhammad , Muallimah Muallimah , Irayanti Irma , Rosmini Rosmini
Published: May 2023

Penelitian ini bertujuan menjelaskan pemikiran progresif Aisyiyah dalam bidang pendidikan serta bagaimana startegi Aisyiyah Sultra mengelola kesempatan dan memobilisasi kekuatannya untuk mewujudkan layananan pendidikan tinggi bagi masyarakat. Data-data penelitian ini diperoleh melalui wawancara mendalam, observasi dan telaah dokumen.  Seluruh data dianalisis dengan menggunakan paradigma Miles dan Huberman.  Merujuk pada data serta analisis yang dilakukan diperoleh kesimpulan sebagai berikut: (1). Aisyiyah Sultra mampu dengan baik mendorong energi positif warganya untuk mengaktualkan ide menjadi monument sekaligus membuktikan diri sebagai perempuan berkarakter progressive, kerja keras, dan berbudaya filantropis. ISTEK adalah penanda identitas dan eksistensial bahwa Aisyiyah Sultra terus bergerak membangun kebaikan semesta. Ruang kesempatan poltik yang terbuka dimanfaatkan secara elegan untuk semakin maksimal dalam menunjukkan bakti kepada negeri. (2). Bahwa dalam faktanya Aisyiyah tidak memiliki fundamental ekonomi sebagai sumber pembiayaan, tidak kemudian menjadikannya lesu dara dan kehilangan semangat. Daya filantropi sebagai karakter DNA Aisyiyah di manage secara elegan oleh aktor dengan cara menyuntikkan narasi-narasi positif (framing) yang kemudian mampu memicu, melipatgandakan semangat berderma elemen Aisyiyah, sehingga dalam waktu dua tahun, ISTEK sebagai penanda gerakan dan pikira progresif Aisyiyah di bidang pendidikan terwujud.  (3). Sebagai perguruan tinggi pertama di Indonesia Timur yang diinisiasi oleh organ perempuan, ISTEK merupakan bukti ril bahwa Aisyiyah adalah komunitas perempuan yang tidak hanya progresif dalam ide, tetapi sekaligus dapat menunjukkan kemampuannya untuk merubah momen menjadi monument.
Alternative esthetic pediatric crowns using digital approach: A case series
Authors: Thakkar Shruti , Naik Saraswathi V , Nadig Basappa , Naik Deepak S
Published: May 2023

Pediatric digital dentistry incorporates computer-aided designing and manufacturing of the crowns which enhances their marginal and internal adaptation. This allows the application of newer materials for the fabrication of crowns. Most importantly, digital workflow makes the procedure easy and comfortable for pediatric patients. The objective of this case series was to evaluate the clinical appearance and success of custom-made esthetic crowns for pediatric population. The case series presents two cases of PMMA crowns using subtractive manufacturing and two of photopolymer resin crowns using additive manufacturing. Both subtractive manufacturing and additive manufacturing have shown better marginal integrity and improved aesthetics in this case series. According to the current literature available and the present case series, these crowns have good biocompatibility, are esthetic, and more importantly relatively inexpensive.
Теоретические основы управления персоналом и влияние управления на результат деятельности организации
Authors: Алимгафарова Л.Р. , Байгузина Л.З.
Published: May 2023

В данной научной статье рассмотрено понятие капитала предприятия. Охарактеризована сущность собственного и заемного капитала, а также оптимизации капитала. Описаны методы оптимизации структуры капитала.
Разработка рекомендаций по улучшению условий труда при проведении строительно-монтажных работ на примере ООО «УНА строймонтаж»
Authors: Ваулина Д.В.
Published: May 2023

Статья посвящена исследованию состояния условий труда на примере строительной отрасли в современных экономических условиях и определению эффективных методов улучшения условий труда при проведении монтажных работ. В процессе работы были проанализированы существующие методы и общие тенденции практической деятельности по организации охраны труда, изучено и проанализировано состояние условий труда в строительной отрасли. Разработаны организационные и стратегические решения по улучшению условий труда при проведении монтажных работ, на исследуемом строительном предприятии.
Разработка модуля электронной информационно-образовательной системы «Казанского государственного энергетического университета»
Authors: Агафонова В.В. , Плетенева Е.В. , Филимонова Т.К.
Published: May 2023

В данной статье рассматривается современная модель развития информационной системы Казанского государственного энергетического университета (КГЭУ), позволяющая не только выявлять наиболее заинтересованных в инженерном творчестве обучающихся, но и представителям от предприятий и фирм отбирать будущих мотивированных работников. В статье описаны составляющие части информационной системы КГЭУ для четкого понимания работы сайта «Приемная Кампания» и сайта «Олимпиады», с помощью которой происходит выявление одаренных обучающихся.
Разработка методов преподавания дисциплин по экотехносферной безопасности
Authors: Букейханов Н.Р. , Гвоздкова С.И. , Бутримова Е.В.
Published: May 2023

Обоснованно для отражения общих свойств экологической и техносферной безопасности использовать термин «экотехносферная безопасность». Особое внимание уделено материалам по формированию у студентов компетенции по умению работать креативно, которые представлены примерами методов разработки проектов решения проблем экотехносферной безопасности.
Методология сбора и регистрации статистической информации по эксплуатации объектов промышленной энергетики
Authors: Злобин В.Г. , Пилипенко Н.Н.
Published: May 2023

Рассматривается методология сбора, обработки и анализа статистической информации по эксплуатации объектов промышленной энергетики. Приведены требования к статистической информации и форме ее регистрации, сущность статистической обработки и статистического анализа данных эксплуатации теплоэнергетических объектов.
Модификация зубьев
Authors: Беспалов В.В. , Клочкова Н.С.
Published: May 2023

В статье рассматривается модификация зубьев цилиндрических зубчатых колес с помощью изготовления проточек для повышения плавности их зацепления и тем самым снижения уровня шума. Изменяя количество, место и глубину проточек можно направленно уменьшать уровень шума зубчатого зацепления.
Утилизация теплоты отработавших газов (ОГ) в судовых дизелях
Authors: Тимофеев В.Н. , Тихонов Н.Ф.
Published: May 2023

Проанализированы системы утилизации ОГ, отражены наиболее перспективные и экономически выгодные из них. Рассмотрены основные этапы по повышению эффективности и технико-экономических показателей судовых энергетических установок (СЭУ) за счѐт применения ТЭГ (термоэлектрических генераторов) для утилизации тепловой энергии ОГ судовых дизелей, комплексной автоматизации систем, повышению их коэффициента полезного действия. Произведен анализ основных задач и перспектив развития эксплуатационных достоинств современных систем утилизации в дизелях.
Институт пограничных представителей в Кыргызской Республике
Authors: Аликулов Б.М, , Кулдышева Г.К,
Published: May 2023

Статья посвящена раскрытию правового статуса пограничных представителей Кыргызской Республики. Формировавшись еще в прошлом столетии, институт пограничных представителей на сегодняшний день представляет собой специфический вид согласительной процедуры для урегулирования пограничных конфликтов и инцидентов, применяемый Кыргызской Республикой. Выполнение пограничными представителями функции превентивного характера способствует предупреждению возникновения пограничных инцидентов.
Возможности ольфакторного экспертного метода в раскрытии и расследовании неочевидных преступлений
Authors: Ярощук И.А.
Published: May 2023

Статья посвящена анализу судебной экспертизы запаховых следов человека и лежащего в еѐ основе ольфакторного метода. Делается акцент на том, что запах каждого человека генетически детерминирован, обусловлен и неповторим. Особое внимание уделяется рассмотрению уникальной криминалистической методики. Отмечается важность и эффективность работы животного-биодетектора как гибкого инструмента в руках исследователя в процессе идентификации преступника.