bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Secure Health Monitoring System Using IOT
Authors: Bande Ganesh Et al.
Published: December 2023

The rapid progress of technology, particularly the Internet of Things (IoT), has introduced exciting opportunities for transforming the healthcare sector. One significant area where IoT has made a significant impact is in the creation of secure health monitoring systems. These systems utilize IoT devices and sensors to gather and transmit live health data, facilitating remote monitoring and individualized healthcare.The integration of IoT in healthcare monitoring offers numerous benefits, including improved patient outcomes, enhanced access to care, and increased efficiency in healthcare delivery.To develop you would typically follow a research methodology that involves several key steps. Clearly state the objectives of your research, such as designing and implementing a secure health monitoring system using IoT. Specify the aspects you want to focus on, such as data privacy, authentication, encryption, or device communication. Develop a high-level system architecture for your health monitoring system. Define the components, their functionalities, and how they interact with each other. Consider the security aspects, such as secure data transmission, authentication, access control, and data storage.By multiplying each of our goals by a weight provided by the user, we can scale our collection of goals into a single goal using the weighted sum approach. One of the most popular strategies is this one. Finding the appropriate weights to give each aim while using the weighted sum approach is a concern. Taken as alternative parameters for HMS1, HMS2, HMS3, HMS4, HMS5. Taken as evaluation parameters for Portability,Round-The-Clock Health Surveillance,ease of use,Reliability.HMS1 performance is good when compared to others so HMS 1 is preferred except HMS 1 performed better in secure health monitoring system using IIOD.
Network Based Intrusion Detection System Using Weighted Product Model (WPM)
Authors: Swapna Rani Et al.
Published: December 2023

A security technology called a network-based intrusion detection system (NIDS) was created to safeguard computer networks against unauthorised access and criminal activity. This technology works by analysing network traffic, spotting potential risks, and informing administrators of any possible incursions or attacks. NIDS research ensures that intrusion detection systems are built to minimise the gathering and storage of sensitive data by taking into account the value of privacy and data protection .In general, network-based intrusion detection system research has a major impact on how well these security measures operate, how efficiently they perform, and how adaptable they are.By addressing the evolving challenges posed by cyber threats, NIDS research helps organizations enhance their network security posture, protect sensitive information, and defend against potential intrusions and attacks." The weighted product model (WPM), a multi-criteria decision-making (MCDM) technique, is used to evaluate and rank solutions based on a variety of distinct criteria. It provides a methodical approach to decision-making by considering the relative importance of each attribute and the performance of other solutions in relation to those criteria. The WPM normalises the data, weights the criteria, and gives a weighted score for each alternative. The option with the greatest score is regarded as the ideal option. The weighted product model offers a structured framework for making decisions by taking into account many factors and their varying degrees of importance. It enables decision-makers to assess and contrast options using a wide range of criteria, resulting in more informed and unbiased choices. It's crucial to check nonetheless that the model's weights and normalisation techniques appropriately capture the decision-maker's preferences as well as the features of the choice problem.J48, Random Forest, JRIP, RIDOR, PART. The definition of true positive, false positive, true negative and false negative rates has already been established. These metrics for measuring the effectiveness of classification algorithms, anomaly detection systems, and binary decision-making processes are accurately presented. As can be seen from the results, J48 received the highest rank, while PART received the lowest .In order to increase the security of computer networks, network-based intrusion detection systems (NIDS) are essential. They provide real-time monitoring and analysis of network traffic to identify suspected breaches and malicious activities, enabling appropriate action to be taken. However, it is important to recognize that NIDS can have limitations and are not infallible.
Classification of Alzheimer’s and Parkinson’s Disease Based on VGG19 Features with Batch Normalization
Authors: Suganya A, Et al.
Published: December 2023

Dementia is a condition when thinking, reasoning and memory skills are lost and patients have emotional instability and personality changes. Researchers are looking into how the underlying disease processes that lead to various kinds of dementia begin and interact. Additionally, they keep researching the various diseases and conditions that cause dementia. Alzheimer’s and Parkinson's disease contribute to dementia development. Recently deep learning-based techniques have surpassed the performance of traditional algorithms in the field of machine vision, image detection, natural language handling, object detection, and medical image analysis. This study proposed a transfer learning-based model for Parkinson’s and Alzheimer’s disease classification from slices of MRI. Pretrained VGG19 with Batch normalization is used for feature extraction and the final dense (fully connected-FC) layers are fine-tuned to meet our requirements. The performance of the model is analyzed by varying hyperparameters. The proposed model outperformed other pre-trained CNN models by achieving an accuracy of 97.19%.
OHE2LM: A Hybrid Approach Towards Heart Attack Prediction using One-Hot Encoding based Extreme Learning Machine Model
Authors: Pawan Kumar Mall Et al.
Published: December 2023

Predicting heart attacks stands as a significant concern contributing to global morbidity. Within clinical data analysis, cardiovascular disease emerges as a pivotal focus for forecasting, wherein Data Science and machine learning (ML) offer invaluable tools. These methodologies aid in predicting heart attacks by considering various risk factors Just like high blood pressure, increased cholesterol levels, irregular pulse rates, and diabetes, this research aims to enhance the accuracy of predicting heart disease through machine learning techniques.This study introduces a MLdriven approach, termed ML-ELM, dedicated to forecasting heart attacks by analysing diverse risk factors. The proposed ML-ELM model is compared with alternative Utilizing machine learning techniques like Support Vector Machines, Logistic Regression, Naïve Bayes, and XGBoost is a key aspect of this exploration into different approaches for predictive modeling., is part of the research strategy. The dataset utilized for heart disease symptoms is sourced from the UCI ML Repository. The outcomes reveal that our proposed ML-ELM model has demonstrated superior predictive performance among the ML techniques tested. ML models show notable efficiency in identifying heart attack symptoms, particularly with boosting algorithms. Accuracy assessments were employed to gauge the predictive ability, Our suggested model demonstrated an outstanding accuracy rate of 96.77%.
Smart Aquaponics with Integration of AI and IoT for Yield Enhancement through Real-Time Monitoring and Decision Support
Authors: Kiran Kumari Gayam Et al.
Published: December 2023

Technological advancements have become the key factor for major changes and upgradations in numerous industries and domain. Agriculture is no exception, technology stacks like IoT and AI are being integrated into agriculture up to a large extent starting from best crop prediction to crop health analysis, nutrient analysis to yield prediction. The intervention of technology is even more prominent in various smart agriculture methods including aquaponics, hydroponics, etc. Aquaponics is a sustainable method of agriculture, that combines aquaculture (fish farming) with hydroponics. This innovative system allows for the cultivation of fish and plants simultaneously, enabling a symbiotic relationship that enhances nutrient recycling. To lead the way for smart aquaponics, as technology continues to advance, the integration of artificial intelligence (AI) and the Internet of Things (IoT) holds immense potential for transforming traditional aquaponics into smart aquaponics. By harnessing real-time monitoring and decision support, AI and IoT can revolutionize various aspects of aquaponics that includes a major paradigm shift in agriculture, promising increased productivity, reduced resource usage, and improved environmental conservation. This article explores the transformative potential of leveraging AI and IoT technologies in aquaponics systems for yield enhancement, sustainability, and overall efficiency.
ALBERT-Based Personalized Educational Recommender System: Enhancing Students’ Learning Outcomes in Online Learning
Authors: Ipseeta Nanda Et al.
Published: December 2023

Online learners must navigate vast educational resources to find materials that meet their needs. This study introduces an ALBERT-based personalized educational recommender system to improve student learning. ALBERT (A Lite BERT), an optimized variant of the BERT algorithm, captures contextualized word representations and understands the semantic meaning of learning resources, student profiles, and interactions. This study evaluates the ALBERT-based recommender system’s personalized learning recommendations. To assess learning outcomes, a diverse group of students from different educational domains is evaluated. Before and after the recommender system, academic performance, knowledge retention, and engagement are assessed. User satisfaction surveys assess recommendation quality, relevance, and user experience. The recommender system uses ALBERT’s model optimization to improve recommendation accuracy, learner engagement, and personalized learning. The evaluation shows the ALBERT-based personalized recommender system improves online learning outcomes. System-generated recommendations boost student engagement, knowledge retention, and academic performance. User satisfaction surveys show that the ALBERT-based system meets learners’ needs by providing relevant and high-quality recommendations. This research shows how advanced deep learning algorithms like ALBERT can improve personalized online learning. ALBERT’s optimized training and inference speeds up the recommender system’s scalability. This empowers learners to access tailored and high-quality educational resources, maximizing their learning outcomes and potential in online learning.
Identifying Trustful Node Using Hybrid Trust Evaluation Method
Authors: S. Ramesh Et al.
Published: December 2023

A wireless sensor network referred as (WSN) is defined as a collection of distributed sensor nodes to work together for monitoring the physical and environmental conditions. Trust metrics in the wireless sensor networks is denoted as the important problem and it helps in solving the problem of access control, reliable communication, privacy and secure routing scheme. This paper establishes a new kind of approach to evaluate the trust value in WSN. The proposed algorithm and its evaluation made on the trust value of each node seen in the network depends on the metrics, trust attributesand trust parameters.
Enhancing Cyber Security through Machine Learning-Based Anomaly Detection in IoT Networks
Authors: Shreyas J Et al.
Published: December 2023

The rapid proliferation of IOT (Internet of Things) networks has brought transformative benefits to industries and everyday life. However, it has also introduced unprecedented cyber security challenges, necessitating advanced techniques for anomaly detection. This research focuses on enhancing cyber security through the application of machine learning-based anomaly detection methods, specifically One-Class Support Vector Machine (SVM) and Isolation Forest, in the context of IOT networks. While Isolation Forest effectively isolates anomalies by building isolation trees, One-Class SVM models the normal data distribution, effectively separating anomalies. To provide a strong security framework for IoT networks, we suggest a comprehensive strategy that combines both algorithms. Our method enables the detection of anomalies in real-time IOT data streams, facilitating prompt responses to new threats. Data collection, preprocessing, and model training are key components. This study helps protect IOT ecosystems and maintain data integrity and privacy in an increasingly connected world by utilizing the benefits of One-Class SVM and Isolation Forest.
Stochastic Gradient Deep Multilayer Neural Network based Linear Congruential Generative Cryptosystem for Secured Data Communication in Cloud
Authors: Krishnaveni R Et al.
Published: December 2023

Cloud computing is a kind of distributed computing that use a vast network of interconnected resources accessible over the internet.   Security is a crucial concern in cloud computing due to the fact that users save their data on the cloud for convenient access from any location and at any time.   Consequently, many users are worried about safeguarding their sensitive data in an unsafe location.  Therefore, cloud computing architecture requires an innovative cryptographic method that ensures the secrecy, authenticity, integrity, and non-repudiation of data transfer in the cloud.  A new technique called SEMcrypt, which stands for Stochastic Gradient DEep Multilayer Neural Network based Linear Congruential Generative Cryptography, has been developed to enhance secure data transmission. SEMcrypt ensures higher data confidentiality and reduces the time required for communication between the cloud user (i.e., patient) and the server. The SEMcrypt approach has two distinct processes: categorization and secure data transport.  Initially, the data is gathered from the patients and is used as input for the stochastic gradient regularised deep multilayer neural network.   The deep neural network consists of one input layer, two hidden layers, and one output layer.   At first, the information is gathered from the patients and sent to the input layer.   Next, the patient data that has been gathered is examined in hidden layer 1 using the generalised Tikhonov regularisation function.   The patient data that has been analysed is sent to hidden layer 2.   The hyperbolic tangent activation function is used at that layer to classify the patient data.   Subsequently, the categorised data undergoes encryption via the use of Linear Congruential Generative Goldwasser-Micali encryption, ensuring safe transfer of the data.  Subsequently, the encrypted data is sent to the cloud server.   The patient data is encrypted on the server side using the Linear Congruential Generative Goldwasser-Micali decryption technique to prevent unauthorised access or assaults.   Consequently, the authorised recipient receives the unaltered information, which is then kept in the database for further analysis.   Secured data transmission is achieved by ensuring better levels of data confidentiality and reducing the time required for the process.   The experimental assessment focuses on criteria such as the time it takes to generate keys, the level of data confidentiality and integrity, the computing time, and the accuracy of categorization.    The empirical findings demonstrate that our suggested SEMcrypt approach delivers efficient performance outcomes by attaining superior levels of data confidentiality and integrity within a minimal timeframe.
Integrating Temporal Fluctuations in Crop Growth with Stacked Bidirectional LSTM and 3D CNN Fusion for Enhanced Crop Yield Prediction
Authors: Kolipaka Venkata Rama Rao , Namburu Anupama
Published: December 2023

Optimizing farming methods and guaranteeing a steady supply of food depend critically on accurate predictions of crop yields. The dynamic temporal changes that occur during crop growth are generally ignored by conventional crop growth models, resulting in less precise projections. Using a stacked bidirectional Long Short-Term Memory (LSTM) structure and a 3D Convolutional Neural Network (CNN) fusion, we offer a novel neural network model that accounts for temporal oscillations in the crop growth process. The 3D CNN efficiently recovers spatial and temporal features from the crop development data, while the bidirectional LSTM cells capture the sequential dependencies and allow the model to learn from both past and future temporal information. Our model's prediction accuracy is improved by combining the LSTM and 3D CNN layers at the top, which better captures temporal and spatial patterns. We also provide a novel label-related loss function that is optimized for agricultural yield forecasting. Because of the relevance of temporal oscillations in crop development and the dynamic character of crop growth, a new loss function has been developed. This loss function encourages our model to learn and take advantage of the temporal trends, which improves our ability to estimate crop yield. We perform comprehensive experiments on real-world crop growth datasets to verify the efficacy of our suggested approach. The outcomes prove that our unified strategy performs far better than both baseline crop growth prediction algorithms and cutting-edge applications of deep learning. Improved crop yield prediction accuracy is achieved with the integration of temporal variations via the merging of bidirectional LSTM and 3D CNN and a unique loss function. This study helps move the science of estimating crop yields forward, which is important for informing agricultural policy and ensuring a steady supply of food.
Security Mechanisms of Distributed Denial-Of-Service (DDOS) Attack in Everything-as-a-Service (XaaS) - Survey
Authors: Almerri Mubarak H M M J Et al.
Published: December 2023

— This paper illustrates research on DDoS attack which overload targeted servers with traffic to render hosted resources inaccessible and unavailable. The attacks are increasingly being launched from multiple locations, gradually spreading over larger networks, consequently to obscure the attack origin. The precipitous cloud computing as the new ‘anywhere anytime’ paradigm, in the form of Everything-as-a-Service (XaaS), transforms these attack mechanisms to become progressively destructive, affecting Quality Of Service (QoS) performance. The attack vectors examination ranges from volumetric attack that flood network links, to application layer attack that target specific services, to protocol attack that exhaust network's resources, with evolving consequences. DDoS attacks mitigation in XaaS environments poses unique challenges. Current literature explores the limitations of traditional on-premise and XaaS-based mitigation techniques to instantaneously detect and mitigate malicious traffic. The role of intelligent analytics in distinguishing legitimate and malicious traffic are also being investigated by application of machine learning algorithms to safeguard against prospective interruptions to XaaS-based services’ availability and reliability
Applications of Difital Image Stegnographic Techniques in Medical Image Analysis
Authors: Nalini Bodasingi Et al.
Published: December 2023

In this digitized world maintaining the security of the secret information is a challenging task. While, sending secret information through the internet draws the attention of hackers.  The highly authenticated information can be hidden by using Steganography. Image processing plays a very important role in such stenographic techniques. The advantage of stenography can be enhanced to medical images and creation of database for a particular patient under one authentication with security. Steganography techniques used in bio-medical field to hide the person medical data like prescription, X-ray, Iris, MRI, CT scan images behind a single cover media. In this paper the embedding Schemes to store complete medical data under one authentication is done by using Spatial and transform domains. The performance of the techniques is compared and the best method to hide medical information by using steganographic techniques with high PSNR, less MSE and high SSIM is identified for different modalities. Implementation of steganography in bio-medical field yields high imperceptibility and embedding capacity
Hydrological Modeling of Large River Basin Using Soil Moisture Accounting Model and Monte Carlo Simulation
Authors: Gauri Patil Et al.
Published: December 2023

This description outlines a Geographic Information System (GIS)-based rainfall-runoff model that simulates the flow of water in a river basin. The model operates on a daily time step and consists of four non-linear storage components: interception, soil moisture, channel, and groundwater. It employs (SCS) Unit Hydrograph model to determine unit hydrograph ordinates. The model replicates the movement and storage of water in various parts of the basin, including vegetation, the soil surface, the soil profile, and groundwater layers. To address uncertainty, a Monte Carlo simulation feature is integrated into the model. This feature generates required number of sample sets with random parameter values. The model is run for all these realizations during a calibration period, and performance metrics like NSE are calculated for each calibration yearTo assess prediction uncertainty, model parameter weights are computed by normalizing the corresponding likelihood values. These weights sum up to one and represent the probabilistic distribution of predicted variables, illustrating the impact of structural and parameter errors on model predictions. A sensitivity analysis reveals that the Muskingum constants K and X have the greatest influence on model performance, while parameters ?GW, ?SW, ?fc, and ?pc have a minimal effect on the model's performance.
Grey Wolf Cuckoo Search Algorithm for Training Feedforward Neural Network and Logic Gates Design
Authors: Layak Ali Et al.
Published: December 2023

This paper presents a new hybrid Swarm Intelligence (SI) algorithm based on the Cuckoo Search Algorithm (CSA) and Grey Wolf Optimizer (GWO) called the Grey Wolf Cuckoo Search (GWCS) algorithm. The GWCS algorithm extracts and combines CSA and GWO features for efficient optimization. To carry out the comprehensive validation, the developed algorithm is applied to three different scenarios with their counterparts. The first validation is carried out on standard optimization benchmark problems. Further, they are used to train Feedforward Neural Networks and finally applied to design logic gates. The comprehensive results are presented and it is found that the proposed GWCS algorithms perform better compared to the state-of-the-art.
New Light on the Discovery of Penicillin
Authors: Sabour Amal
Published: December 2023

Although penicillin was discovered by Alexander Fleming at St Marys Hospital, London in the autumn of 1928 it was not widely available for medical use until the late 1940s. Here, emphasis will be placed on the discovery and development of penicillin in England during this period, particularly on the so-called “penicillin-interregnum”, i.e. the period between Fleming’s discovery and its purification by the Oxford group, led by Howard Flory and Ernst Chain. Emphasis will be placed on some lesser-known aspects of the story, including the role played by Cecil George Paine, the first person to achieve documented cures using unpurified penicillin filtrates. Attempts will also be made to correct a number of common misunderstandings about the discovery, including the myth that Fleming stopped working on penicillin soon after its discovery.
Soil decontamination: bioremediation and phytoremediation
Authors: Nunes Cosmo Bruno Marcos , Galeriani Tatiani Mayara , Leoti Zanetti Willian Aparecido
Published: December 2023

Practically all agro-industrial activities and the maintenance of cities have the potential to pollute and contaminate the environment. Thus, measures to mitigate the impacts of these activities must be evaluated, including bioremediation. In this sense, this work aimed to characterize the process of soil decontamination using bioremediation and phytoremediation. To this end, a bibliographic review based on scientific articles, books, dissertations, and theses was used. Bioremediation refers to the use of living organisms to remove, reduce, or neutralize pollutants from the environment. The technique can be performed on-site (in situ) or off-site (ex situ). Plants can also be used for bioremediation, characterizing, in this case, phytoremediation. Plants for phytoremediation must show tolerance to the contaminant and the ability to absorb and metabolize it. These plants include pigeon peas, pig beans, crotalaria, vetiver grass, and others. Bioremediation is expanding, requiring further studies.
Virus respiratorios y características epidemiológicas de pacientes con infección respiratoria
Authors: Luna Orozco Karen , Valencia José David , Agudelo Omar
Published: December 2023

INTRODUCCION La infección respiratoria aguda es una de las primeras causas de consulta médica a nivel mundial. Condiciona una alta carga en términos de morbimortalidad especialmente para poblaciones en edades extremas. OBJETIVO Identificar los virus respiratorios y las características epidemiologias de pacientes con infección respiratoria aguda en la ESE San Rafael de Yolombo, octubre de 2021 – abril de 2022. MATERIALES METODOS Se hizo un estudio de corte transversal bajo el análisis de fuente de información secundaria. La muestra (n= 212) incluyó todos los casos de octubre de 2021 a abril de 2022 que reunieron criterios para el diagnóstico de infección respiratoria aguda. Se desarrolló un análisis descriptivo de las características demográficas y clínicas de la muestra. RESULTADOS El porcentaje de positividad global fue de 15,7 %. La mayor positividad (19,2 %) se registró en el grupo de pacientes entre los cero y cuatro años. Del total de casos positivos un 54,4 % fueron causados por el virus sincitial respiratorio, 24,2 % por influenza tipo A, 15,2 % por metapneumovirus y 6,1 % por Parainfluenza tipo 3. El 78,8% de los casos ameritó manejo intrahospitalario y de estos 7.8% fue derivado a un centro de mayor complejidad. Entre infantes un 13,5 % registró historia de prematurez y en la adulta un 45,8 % padecía alguna enfermedad cardiometabólica. CONCLUSION La atención de la infección respiratoria aguda demandó una alta carga de recursos teniendo en cuenta que más del 70 % de los casos ameritó manejo intrahospitalario. La continuidad de programas de vigilancia epidemiológica de este evento en zonas dispersas del país constituye una herramienta crucial para la planeación de su manejo desde el campo de la salud pública.
Nanomedicine and Liver Cancer Stem Cells
Authors: Bai Ling , Jin Cheng
Published: December 2023

In recent years, overwhelming experimental and clinical data demonstrate the existence of a unique subpopulation of highly malignant tumor cells termed as cancer stem cells (CSCs). They have been found in many solid tumors, including liver cancer. Liver CSCs may be known as the source of malignant cells, the reason for resistance to chemotherapy and radiotherapy, and the cells source of distant metastases. Therefore, new and effective treatment strategies targeting liver CSCs are urgently needed. Nanomedicine-based nanotechniques and biomaterials have emerged as some of the most promising carrier systems for medical imaging and drug delivery. The advances of nanomedicine result in the concept of precision medicine and the opportunity for early diagnoses and highly-effective targeted therapy. This review will focus on the properties of liver CSCs, discuss the preclinical and clinical available applications of nanomedicine, and explore the future implications and challenges.
Pancreatic Cancer: Current Situation and Challenges
Authors: Cheng Jin  , Ling Bai
Published: December 2023

Pancreatic cancer, which is characterized as an occult disease, has a high degree of malignancy, and ductal adenocarcinoma accounts for more than 90% of pancreatic cancer.It is accompanied by delayed diagnosis, low resection rate, high mortality rate, and poor prognosis. In recent years, the incidence of pancreatic cancer is on the rise. Because the diagnosis is mostly late, only 10–20% of the patients can be arranged for surgical treatment according to the imaging examination. The 5-year survival rate of patients with pancreatic cancer is only 10–25%. The survival rate of the patients with lymph node metastasis is even lower. It is estimated that by 2030, pancreatic cancer will become the second most common cause of cancer-related mortality in human beings, while the lung cancer will still remain at the top spot in the list.
Acute Epiploic Appendagitis as a Rare Case of Acute Abdomen: A Case Report
Authors: Jin Yu Chieng  , Yoong Fei Chiang  , Yan Pan
Published: December 2023

We reported the unusual case of a 39-year-old man, who presented to a private hospital located at Kuala Lumpur, Malaysia, with intense left iliac fossa abdominal pain. The diagnosis of acute epiploic appendagitis (EA) was made based on the computed tomography (CT) findings of a well-defined ovoid lesion of fat density at the junction of sigmoid and descending colon, with thin hyperdense rim, together with surrounding mesenteric fat, and thickening of the adjacent peritoneum. He was treated conservatively without surgery, and the pain subsided gradually. Our case reaffirmed that careful diagnosis is necessary to avoid invasive surgical interventions that are largely unnecessary as a treatment for acute EA.
Phosphatidylinositol-3-kinase/Protein Kinase B Signaling Pathway: A Pivotal Factor for Stimulating Multidrug Resistance in Hepatocellular Carcinoma Cells
Authors: Chao Zhang  , Mengsen Li  , Mingyue Zhu
Published: December 2023

Hepatocellular carcinoma (HCC) is a common malignant tumor. Chemotherapy is one of its principal modes of treatment, but multidrug resistance (MDR) poses an obstacle in HCC treatment. MDR is mainly mediated through drug transmembrane transporter activity, apoptosis inhibitory pathway abnormality, and changes in the intracellular enzyme. On top of that, phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt) pathway dysregulation is also one of the most common mechanisms of MDR. This signaling pathway plays critical roles in the differentiation, proliferation, and apoptosis of cancer cells, and is a new target of MDR treatment. This review article discusses the mechanisms of MDR in HCC with a strong emphasis on the significance and role of PI3K/Akt pathway in MDR, and the reversal of MDR by inhibiting PI3K/Akt pathway.
Activation of the Warburg Effect by Pyruvate Kinase M2 Promotes the Occurrence and Development of Liver Cancer
Authors: Yuli Zhou  , Mengsen Li  , Mingyue Zhu
Published: December 2023

Liver cancer, which is one of the most common malignancies, has a high incidence and case fatality rate, and is the third most common cause of death attributed to cancer. Warburg effect is a form of modified cell metabolism by which tumor cells obtain energy by glycolysis instead of oxidative phosphorylation, whether in an aerobic or anaerobic environment. It plays an important role in tumor proliferation, growth, invasion, and treatment. Pyruvate kinase M2 (PKM2), an essential key enzyme in the glycolytic process, is significantly elevated in multiple tumor tissues and plays a crucial role in the Warburg effect. Recently, increasing attention has been devoted to the mechanism of action of PKM2 in tumors, and interference with the glycolysis pathway is one of the new strategies for cancer treatment. This paper provides a review of the Warburg effect of PKM2 activation and its relationship with tumorigenesis and development and the potential value of Warburg effect in clinical diagnosis, treatment, and prognostic evaluation of liver cancer.
Vestibular evoked myogenic and auditory brainstem evoked potentials in a female migraine population
Authors: Inan Rahşan , Ulutaş Samiye , Yildirim Ahmet
Published: December 2023

Background and purpose – The purpose of the present study was to evaluate ocular vestibular evoked myogenic potential (oVEMP), cervical vestibular evoked myogenic potential (cVEMP), and brainstem auditory evoked potential (BAEP) response characteristics and to understand the pathophysiology of vestibular dysfunction in female migraineurs with vertigo symptoms. We also aimed to assess the electrophysiological di­agnostic significance of the VEMP responses in vestibular migraine (VM). Methods – 23 patients with migraine without aura (MoA), 23 patients with VM, and 20 sex-and age-matched healthy controls, a total of 66 female participants were enrolled in this study. The outcome parameters were asymmetry ratios (ARs), amplitudes of oVEMP, cVEMP, N1P1, P13N23, and the respective latencies (mean ± SD). From the BAEP graphs, absolute and interpeak interval latencies of waves were analyzed. Results – 30.4% of the MoA group and 21.7% of the VM group had uni- or bilaterally absent cVEMP responses which were statistically significant only in the MoA group (p=0.035) in comparison to control group. Both groups displayed statistically insignificant absent or asymmetrical responses for oVEMP (13.1%). Cervical VEMP P13 and N23 latency, peak-to-peak amplitude, interaural latencies, and amplitude ARs did not show any significant difference between MoA and VM patients and healthy controls. No significant difference was detected among the three groups in the oVEMP and BAEP parameters. Conclusion – Although absent cVEMP responses were more common in MoA and VM patients than in healthy individuals, the VEMP and BAEP test results should not be used in the differential diagnosis of VM and MoA.
The results of intellectual activity of the Pedagogical University: state and prospects
Authors: Милинский А.Ю.
Published: December 2023

Представлен опыт создания продуктов интеллектуальной деятельности на примере Благовещенского государственного педагогического университета (2013–2023 гг.). Анализируются преимущества и недостатки педагогического вуза, влияющие на патентную активность. Предложены направления деятельности профессорско-преподавательского состава, которые будут способствовать кратному увеличению результатов интеллектуальной деятельности университета.

The experience of creating products of intellectual activity is presented on the example of the Blagoveshchensk State Pedagogical University (2013–2023). The advantages and disadvantages of a pedagogical university that affect patent activity are analyzed. Proposed areas of activity of the teaching staff, which will contribute to a multiple increase in the results of the intellectual activity of the university.
Training professionally-oriented translation to students of a non-linguistic university
Authors: Микова И.М.
Published: December 2023

Рассматриваются вопросы обучения профессионально-ориентированному переводу студентов неязыкового вуза, а также различные виды перевода. Проведено анкетирование на базе кафедры иностранных языков с курсом русского Рязанского государственного медицинского университета имени И.П. Павлова, которое позволило выявить какие виды перевода вызывают наибольшие трудности у студентов при обучении профессионально-ориентированному переводу на занятиях по иностранному языку. Сделан вывод о том, что основную трудность у студентов неязыкового вуза вызывает устный последовательный перевод с иностранного языка на русский. Представлены рекомендации по преодолению трудностей, возникающих в процессе обучения профессионально-ориентированному переводу.

The issues of teaching professionally oriented translation to students of a non-linguistic university, as well as various types of translation, are considered. A survey was conducted on the basis of the Department of Foreign Languages with the course of the Russian Ryazan State Medical University named after I.P. Pavlov, which made it possible to identify which types of translation cause the greatest difficulties for students in teaching professionally oriented translation in foreign language classes. It is concluded that the main difficulty for students of a non-linguistic university is oral consecutive translation from a foreign language into Russian. Recommendations are presented for overcoming the difficulties that arise in the process of teaching professionally oriented translation.
Pedagogical communication as an indicator of the lecturer's professional competence in the educational ecosystem environment
Authors: Куклина Л.В. , Куклин С.Я.
Published: December 2023

Рассматриваются актуальные исследования современных авторов по теме статьи, базовые характеристики эффективного взаимодействия преподавателей университета и студентов, конструирование педагогического общения на принципах человеко- и природосообразности. В качестве общих признаков психологически безопасной экологичной образовательной среды выдвигаются субъект-субъектные отношения, формирование благоприятной атмосферы профессионального и межличностного общения путем сотрудничества и совместной деятельности участников образовательного процесса. Сравниваются различные подходы, эффективные модели и формы педагогического общения, выступающие индикатором профессиональной компетентности преподавателя. Приведены результаты опроса студентов, отражающие степень их удовлетворенности качеством образовательной среды, в том числе взаимодействием с педагогами. Материалы статьи могут быть использованы для инновационного построения профессионального педагогического общения в рамках образовательной экосистемы университета.

The article is devoted to analysis of contemporary authors experience in the fi eld of pedagogical communication within the ecosystem educational environment. It considers the basic characteristics of eff ective interaction between university lecturers and students, the design of pedagogical communication on the principles of societal and nature conformity. Subject-subject relations, students’ competence, the formation of a favorable professional and interpersonal communication are put forward as general signs of a psychologically safe friendly educational environment via collaboration tools. Various conceptual approaches, formation models of a favorable psychological climate are compared to measure lecturer’s professional competence level. The article also focuses on the student survey results, refl ecting the degree of their satisfaction with the educational environment quality including interaction with teaching staff. The materials of the article can be applied for the innovative design of professional pedagogical communication within the educational ecosystem of the contemporary university.
Features of digital literacy of future educational specialists and their attitude to the use of digital tools and technologies in education
Authors: Шнейдер Л.Б. , Богатырев К.А.
Published: December 2023

Рассматривается проблема формирования цифровой грамотности у студентов как важнейшей составляющей ИКТ-компетентности. Представлены материалы эмпирического исследования, направленного на определение уровня, структурно-содержательных характеристик цифровой грамотности будущих специалистов образовательной сферы, показано их отношение к использованию цифровых средств в обучении и профессиональной деятельности. Установлено, что цифровая грамотность у будущих специалистов образовательной сферы соответствует «продвинутому» (среднему) уровню. У будущих педагогов-психологов он наименьший. Выявлено, что отношение у будущих специалистов образовательной сферы к использованию в обучении цифровых средств и технологий носит вариативный и неоднозначный характер: от их неприятия до творческого использования. Структурно-содержательные характеристики цифровой грамотности имеют более высокие показатели по параметрам, обусловленным личным или учебным интересом обучающихся, и заниженные, когда за ними обнаруживается профессионально-цифровая необходимость.

The problem of the formation of digital literacy among students as the most important component of ICT competence is considered. The materials of an empirical study aimed at determining the level, structural and content characteristics of digital literacy of future specialists in the educational sphere are presented, their attitude to the use of digital tools in training and professional activities is shown. It has been established that the digital literacy of future educational specialists corresponds to the “advanced” (medium) level. For future educational psychologists, it is the smallest. It was revealed that the attitude of future educational specialists to the use of digital tools and technologies in teaching is variable and ambiguous: from their rejection to creative use. The structural and content characteristics of digital literacy have higher indicators in terms of parameters due to the personal or educational interest of students, and underestimated when a professional digital need is found behind them.
Partisipasi Masyarakat dalam Pengurusan Administrasi Akta Kematian berdasarkan Peraturan Daerah Kebupaten Pesisi Selatan Nomor 7 Tahun 2017
Authors: Rizki Agra Leo
Published: December 2023

Penelitian ini bertujuan untuk menganalisis partisipasi masyarakat dalam pengurusan administrasi akta kematian berdasarkan Peraturan Daerah Kabupaten Pesisir Selatan Nomor 7 Tahun 2017. Partisipasi masyarakat dalam pengurusan administrasi akta kematian menjadi sangat penting dalam memastikan proses pendaftaran dan pengurusan akta kematian yang efektif dan efisien. Metode penelitian yang digunakan adalah metode penelitian kualitatif dengan pendekatan deskriptif. Data dikumpulkan melalui wawancara mendalam dengan berbagai pihak terkait, termasuk petugas administrasi, keluarga yang mengurus akta kematian, dan masyarakat umum. Analisis data dilakukan dengan menggunakan pendekatan kualitatif, dengan fokus pada tema-tema yang muncul dari wawancara. Hasil penelitian menunjukkan bahwa partisipasi masyarakat dalam pengurusan administrasi akta kematian masih terbatas. Faktor-faktor seperti kurangnya pemahaman tentang pentingnya akta kematian, keterbatasan akses ke kantor pendaftaran, dan biaya administrasi yang tinggi menjadi kendala dalam partisipasi masyarakat. Selain itu, implementasi Peraturan Daerah Kabupaten Pesisir Selatan Nomor 7 Tahun 2017 belum sepenuhnya efektif dalam mendorong partisipasi masyarakat. Dalam rangka meningkatkan partisipasi masyarakat, disarankan adanya sosialisasi yang lebih intensif tentang pentingnya akta kematian, peningkatan aksesibilitas pendaftaran akta kematian, dan peninjauan kembali kebijakan administrasi yang terkait dengan biaya dan prosedur pendaftaran. Diharapkan penelitian ini dapat memberikan kontribusi untuk memperbaiki pengelolaan administrasi akta kematian dan mendorong partisipasi masyarakat yang lebih aktif dalam proses tersebut.
Teratocarcinosarcoma: A rare malignant tumor of sinonasal tract
Authors: Raj T S Preetham , C Nirmala
Published: December 2023

Sinonasal teratocarcinosarcoma is an extremely rare malignant tumor arising in the sinonasal tract, having combined histological features of teratoma and carcinosarcoma. Here, we are presenting a case of sinonasal teratocarcinosarcoma in a 44 year‑old male patient.

44 year old male presented to us with complains of nasal obstruction and intermittent epistaxis since 1 month. On examination polypoidal mass was noted in left nasal cavity which bleeds on touch. On MRI, well defined heterogeneously enhancing lesion completely filling the left nasal cavity was noted. Histopathological examination of resected specimen revealed, malignant epithelial components being adenocarcinoma and squamous cell carcinoma, mesenchymal component composed of spindle cells, along with primitive mesenchymal and blastemal components. Immunohistochemistry showed epithelial and stromal markers positive for Cytokeratin and Vimentin respectively.

Sinonasal teratocarcinosarcoma (TCS) is a rare and aggressive malignant neoplasm characterized by the combination of malignant teratoma and carcinosarcoma. Most common presentation being nasal obstruction and epistaxis with male preponderance. The tumor shows heterogeneous morphology with varying proportions of benign and malignant epithelial, mesenchymal, and blastemal components. Less than 100 cases have been reported in literature.

Teratocarcinosarcoma is a rare aggressive sinonasal tumor. Total excision of the tumor and aggressive sampling for histopathological examination is necessary to avoid misdiagnosis of olfactory neuroblastoma and carcinosarcoma.
A voz do desenvolvimento: Os primeiros anos da telefonia no Brasil e o começo da atuação do Grupo Light no serviço telefônico (1877-1916)
Authors: Pereira da Silva Marcel , Macchione Saes Alexandre
Published: December 2023

O presente artigo analisa os primeiros anos da telefonia no Brasil, com destaque para as regiões de atuação do grupo canadense Light, conhecido principalmente por operar serviços de energia elétrica, iluminação e bondes elétricos nas cidades de São Paulo, Rio de Janeiro e alguns outros municípios. Embora este serviço não estivesse nos planos originais da empresa, a entrada da Light reorganizou, incorporou e ampliou companhias telefônicas dispersas em parte dos estados do Rio de Janeiro (inclusive capital federal), São Paulo e Minas Gerais. Uma alteração na legislação federal ocorrida em 1916, limite do recorte deste trabalho, permitiu à companhia expandir e conectar suas linhas nos três estados que passou a atuar desde então, possibilitando uma considerável ampliação de seus serviços a partir deste momento.
The Rude Pomeranian: About a Stereotype, an Anecdote and the Pomeranians
Authors: Wójcik Bartosz
Published: December 2023

Die Geschichte über den groben Pommern wird seit fast einem halben Jahrtausend – jeweils von voneinander unabhängigen Redakteuren – immer wieder revidiert und modifiziert. Sie wurde von ca. 35 Autoren in ca. 40 Fassungen publiziert. Ihre Wurzeln muten anekdotisch an; sie wurde in epischen, lyrischen und dramatischen Texten bearbeitet. Sie nahm Bezug auf ein altbewährtes, negativ konnotiertes Stereotyp über die Region Pommern und ihre Bewohner. Auf der einen Seite zeigte sie die Wahrnehmung der autochthonen Bevölkerung, auf der anderen Seite bot aber auch einen Umgang mit diesem nachteilig behafteten Bild an. Der Beitrag vergleicht einzelne Varianten der Geschichte und deutet diese imagologisch.
Simple Forms – Mytological proverbial expressions – The liveness of idioms
Authors: Komenda-Earle Barbara
Published: December 2023

Das Ziel des Beitrags ist es, Zusammenhänge zwischen den Einfachen Formen im Sinne von André Jolles‘ und dem Begriff der Lebendigkeit von Idiomen aufzuzeigen und demnächst die Lebendigkeit der idiomatischen Einheiten zu untersuchen. Die Lebendigkeit der Idiome, ein linguistisches Konzept, das die mentale Präsenz und die Gebräuchlichkeit der Idiome umfasst, erscheint kompatibel mit solchen Elementen des Konzepts der Einfachen Formen wie sprachliche Gebärde, Vergegenwärtigung (Sprichwort – Redensart), Stetigkeit und Vielfältigkeit (Varianten, Modifikationen), Geistesbeschäftigung. Unter Einfachen Formen werden der Mythos, das Sprichwort und die sprichwörtliche Redensart (Idiom) angesprochen. Nach einer Charakteristik der Idiome mythologischer Herkunft im Deutschen wird am Beispiel des Idioms zwischen Szylla und Charybdis und formell-inhaltlich zusammenhängenden Formen die Lebendigkeit dieser Idiome im 19. und im 20.-21. Jh. untersucht. Die Untersuchung ist lexikographisch und korpuslinguistisch gestützt.