bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal ECG Signal Denoising Using DWT with Enhanced African Vulture Optimization
Authors: Balasubramanian S. , Tewari Gaurav , Naruk Mahaveer Singh
Published: January 2023

Cardiovascular diseases (CVDs) are the world's leading cause of death; therefore cardiac health of the human heart has been a fascinating topic for decades. The electrocardiogram (ECG) signal is a comprehensive non-invasive method for determining cardiac health. Various health practitioners use the ECG signal to ascertain critical information about the human heart. In this paper, the noisy ECG signal is denoised based on Discrete Wavelet Transform (DWT) optimized with the Enhanced African Vulture Optimization (AVO) algorithm and adaptive switching mean filter (ASMF) is proposed. Initially, the input ECG signals are obtained from the MIT-BIH ARR dataset and white Gaussian noise is added to the obtained ECG signals. Then the corrupted ECG signals are denoised using Discrete Wavelet Transform (DWT) in which the threshold is optimized with an Enhanced African Vulture Optimization (AVO) algorithm to obtain the optimum threshold. The AVO algorithm is enhanced by Whale Optimization Algorithm (WOA). Additionally, ASMF is tuned by the Enhanced AVO algorithm. The experiments are conducted on the MIT-BIH dataset and the proposed filter built using the EAVO algorithm, attains a significant enhancement in reliable parameters, according to the testing results in terms of SNR, mean difference (MD), mean square error (MSE), normalized root mean squared error (NRMSE), peak reconstruction error (PRE), maximum error (ME), and normalized root mean error (NRME) with existing algorithms namely, PSO, AOA, MVO, etc.
Attenuate the Network Lifetime in Wireless Sensor Networks
Authors: Dadhirao Chandrika , Sankar Sangam Ravi
Published: January 2023

Wireless Sensor Networks are one of the well-established and as well as im- proving areas, which have a prominent role in many existing technologies. The day-to-day advancement in this field made a direction for growing low-power, low-cost, along with multi functioning of the sensors. This collective formation of the system with motes or sensors is Wireless Sensor Network (WSN). WSNs follow the principle of ”EAAs” stands for Everyone, Anywhere, Anytime. The nodes in the network have certain limitations in terms of memory, power, etc. Clustering the nodes in the network is an efficient and most preferable technique to address the problem of better performance of the wireless sensor networks. In this work, we provide a re-modified approach for cluster head selection for the transmission of data between nodes, cluster heads, and mote with a low packet loss ratio.  The Statistical results of the two existing approaches and the pro- posed approach are compared for 100 iterations and shown in results. The time complexity of the proposed approach is also calculated.
Symbiotic Organisms Search Optimization to Predict Optimal Thread Count for Multi-threaded Applications
Authors: H. Malave Sachin , K. Shinde Subhash
Published: January 2023

Multicore systems have emerged as a cost-effective option for the growing demands for high-performance, low-energy computing. Thread management has long been a source of concern for developers, as overheads associated with it reduce the overall throughput of the multicore processor systems. One of the most complex problems with multicore processors is determining the optimal number of threads for the execution of multithreaded programs. To address this issue, this paper proposes a novel solution based on a modified symbiotic organism search (MSOS) algorithm which is a bio-inspired algorithm used for optimization in various engineering domains. This technique uses mutualism, commensalism and parasitism behaviours seen in organisms for searching the optimal solutions in the available search space. The algorithm is simulated on the NVIDIA DGX Intel-Xeon E5-2698-v4 server with PARSEC 3.0 benchmark suit.  The results show that keeping the thread count equal to the number of processors available in the system is not necessarily the best strategy to get maximum speedup when running multithreaded programs. It was also observed that when programs are run with the optimal thread count, the execution time is substantially decreased, resulting in energy savings due to the use of fewer processors than are available in the system.
Exploring Post-Adoption Behavior of the UPI users with Cognitive and Affective Factors
Authors: Kaur Sandeep , Katoch Rupinder , Rana Avinash
Published: January 2023

The National Payments Corporation of India (NPCI) has invested a sizable amount of money in the country's massive payment infrastructure in an effort to enhance the user experience. However, in order for investments to be profitable, NPCI must guarantee the ongoing use of technological solutions and post-adoptive behaviors like continuance and recommendation intention. The impact of cognitive factors (i.e. Performance expectancy, effort expectancy, social influences, facilitating conditions; personal innovativeness) and affective factors (such as satisfaction) on conative factors (such as continuation and recommendation intention) in the perspective of UPI applications (apps) was investigated using the UTAUT model. Partial Least Square Structural Equation Modeling when applied on 651 users (PLS-SEM) showed that satisfaction had a direct impact on continuation intentions, which in turn had an impact on recommendations intentions. It was discovered that all cognitive factors, including performance expectations, effort expectations, and facilitating conditions, have an impact on satisfaction. According to the study, adding a significant individual difference variable—personal innovativeness with regard to information technology—would aid in our understanding of the role that these factors play in the development of continuous intention. It further examines the influence of trust and security, and the pace of innovation on continued intentions. Through the mediating function  of user satisfaction, it also looked at the impact of performance expectancy, effort expectancy, social influence, facilitating variable, and personal innovativeness on the continuance intentions of the UPI system. All factors have been shown to be significant. Future researchers will find it extremely helpful that the study used a validated instrument to better understand user adherence and referral intentions. Therefore, this study adds to the limited body of knowledge in the payment industry literature by examining how users perceive UPI apps and post-adoption behaviors.
A Novel Ensemble Model Using Learning Classifiers to Enhance Malware Detection for Cyber Security Systems
Authors: Das Abhijit , Pramod Pramod
Published: January 2023

In the Internet of Things arena, smart gadgets are employed to offer quick and dependable access to services. IoT technology has the ability to recognize extensive information, provide information reliably, and process that information intelligently. Data networks, controllers, and sensors are increasingly used in industrial systems nowadays. Attacks have increased as a result of the growth in connected systems and the technologies they employ. These attacks may interrupt international business and result in significant financial losses. Utilizing a variety of methods, including deep learning (DL) and machine learning (ML), cyber assaults have been discovered. In this research, we provide an ensemble staking approach to efficiently and quickly detect cyber-attacks in the IoT. The NSL, credit card, and UNSW information bases were the three separate datasets used for the experiments. The suggested novel combinations of ensemble classifiers are done better than the other individual classifiers from the base model. Additionally, based on the test outcomes, it could be concluded that all tree and bagging-based combinations performed admirably and that, especially when their corresponding hyperparameters are set properly, differences in performance across methods are not significant statistically. Additionally, compared to other comparable PE (Portable Executable) malware detectors that were published recently, the suggested tree-based ensemble approaches outperformed them.
Modified Firefly Optimization with Deep Learning based Multimodal Biometric Verification Model
Authors: Ramana N. Venkata , Nair S. Anu H. , Sanal Kumar K. P.
Published: January 2023

Biometric security has become a main concern in the data security field. Over the years, initiatives in the biometrics field had an increasing growth rate. The multimodal biometric method with greater recognition and precision rate for smart cities remains to be a challenge. By comparison, made with the single biometric recognition, we considered the multimodal biometric recognition related to finger vein and fingerprint since it has high security, accurate recognition, and convenient sample collection. This article presents a Modified Firefly Optimization with Deep Learning based Multimodal Biometric Verification (MFFODL-MBV) model. The presented MFFODL-MBV technique performs biometric verification using multiple biometrics such as fingerprint, DNA, and microarray. In the presented MFFODL-MBV technique, EfficientNet model is employed for feature extraction. For biometric recognition, MFFO algorithm with long short-term memory (LSTM) model is applied with MFFO algorithm as hyperparameter optimizer. To ensure the improved outcomes of the MFFODL-MBV approach, a widespread experimental analysis was performed. The wide-ranging experimental analysis reported improvements in the MFFODL-MBV technique over other models.
Classification and Segmentation of MRI Brain Images using Support Vector Machine and Fuzzy C-means Clustering
Authors: Dwivedi Sampurnanand , Singhal Vipul
Published: January 2023

An early diagnosis of brain disorders is very important for timely treatment of such diseases.Several imaging modalities are used to capture the anomalities by obtaining either the  physiological or morphological information. The scans obtained using imaging modalities such as magnetic resonance imaging (MRI) are investigated by the radiologists in order to diagnose the diseases. However such investigations are time consuming and might involve errors. In this paper, a fuzzy c-means clustering method is used for brain MRI image segmentation.The GLCM features are obtained from the segmented images and are subsequently mapped in to a PCA space. A support vector machine (SVM) classifier is used to classify brain MRI images taken from BRATS-13 images. The method is evaluated by employing various performance measures such as  Jaccard index, Dice index, mean square error (MSE), peak signal to noise ratio (PSNR). The results show that the method outperforms the existing methods.
Design of Digital Frequency Synthesizer for 5G SDR Systems
Authors: Bhaskar C. Vijaya , Munaswamy P.
Published: January 2023

The previous frequency synthesizer techniques for scalable SDR are not compatible with high end applications due to its complex computations and the intolerance over increased path interference rate which leads to an unsatisfied performance with improved user rate in real time environment. Designing an efficient frequency synthesizer framework in the SDR system is essential for 5G wireless communication systems with improved Quality of service (QoS). Consequently, this research has been performed based on the merits of fully digitalized frequency synthesizer and its explosion in wide range of frequency band generations. In this paper hardware optimized reconfigurable digital base band processing and frequency synthesizer model is proposed without making any design complexity trade-off to deal with the multiple standards. Here fully digitalized frequency synthesizer is introduced using simplified delay units to reduce the design complexity. Experimental results and comparative analyzes are carried out to validate the performance metrics and exhaustive test bench simulation is also carried out to verify the functionality.
Modernized Wildlife Surveillance and Behaviour Detection using a Novel Machine Learning Algorithm
Authors: Gogula Sreenivasulu , Khanna M. Rajesh , Neelappa Neelappa , Sundaram Ajith , Kumar E. Rajesh , Kumar R. Sravanth
Published: January 2023

In a natural ecosystem, understanding the difficulties of the wildlife surveillance is helpful to protect and manage animals also gain knowledge around animals count, behaviour and location. Moreover, camera trap images allow the picture of wildlife as unobtrusively, inexpensively and high volume it can identify animals, and behaviour but  it has the issues of high expensive, time consuming, error, and low accuracy. So, in this research work, designed a novel wildlife surveillance framework using DCNN for accurate prediction of animals and enhance the performance of detection accuracy. The executed research work is implemented in the python tool and 2700 sample input frame datasets are tested and trained to the system. Furthermore, analyze whether animals are present or not using background subtraction and features extracted is performed to extract the significant features. Finally, classification is executed to predict the animal using the fitness of seagull. Additionally, attained results of the developed framework are compared with other state-of-the-art techniques in terms of detection accuracy, sensitivity, F-measure and error.
ICKSC :An Efficient Methodology for Predicting Kidney Stone From CT Kidney Image Dataset using Conventional Neural Networks
Authors: Sarada J. , Lakshmi N. V. Muthu
Published: January 2023

Chronic Kidney Diseases (CKD) has become one among the world wide health crisis and needs the associated efforts to prevent the complete organ damage. A considerable research effort has been put forward onto the effective separation and classification of kidney Stones from the kidney CT Images. Emerging machine learning along with deep learning algorithms have waved the novel paths of kidney stone detections. But these methods are proved to be laborious and its success rate is purely depends on the previous experiences. To achieve the better classification of kidney stone, this paper proposes a novel Intelligent CNN based Kidney Stone Classification (ICKSC) system which is based on transfer learning mechanism and incorporates 8 Layered CNN, densenet169_model, mobilenetv2_model, vgg19_model and xception_model. The extensive experimentation has been conducted to evaluate the efficacy of the recommended structure and matched with the other prevailing hybrid deep learning model. Experimentation demonstrates that the suggested model has showed the superior predominance over the other models and exhibited better performance in terms of training loss, accuracy, recall and precision.
Histopathological Image Classification Methods and Techniques in Deep Learning Field
Authors: Rani V Sudha , Kumar M Jogendra
Published: January 2023

A cancerous tumour in a woman's breast, Histopathology detects breast cancer. Histopathological images are a hotspot for medical study since they are difficult to judge manually. In addition to helping doctors identify and treat patients, this image classification can boost patient survival. This research addresses the merits and downsides of deep learning methods for histopathology imaging of breast cancer. The study's histopathology image classification and future directions are reviewed. Automatic histopathological image analysis often uses complete supervised learning where we can feed the labeled dataset to model for the classification. The research methods are frequentlytrust on feature extraction techniques tailored to specific challenges, such as texture, spatial, graph-based, and morphological features. Many deep learning models are also created for picture classification. There are various deep learning methods for classifying histopathology images.
An Adaptive Feature Centric XG Boost Ensemble Classifier Model for Improved Malware Detection and Classification
Authors: Pavithra J. , Samy S. Selvakumara
Published: January 2023

Machine learning (ML) is often used to solve the problem of malware detection and classification and various machine learning approaches are adapted to the problem of malware classification; still  acquiring poor performance by the way of feature selection, and classification. To manage the issue, an efficient Adaptive Feature Centric XG Boost Ensemble Learner Classifier “AFC-XG Boost” novel algorithm is presented in this paper. The proposed model has been designed to handle varying data sets of malware detection obtained from Kaggle data set. The model turns the process of XG Boost classifier in several stages to optimize the performance. At preprocessing stage, the data set given has been noise removed, normalized and tamper removed using Feature Base Optimizer “FBO” algorithm. The FBO would normalize the data points as well as performs noise removal according to the feature values and their base information. Similarly, the performance of standard XG Boost has been optimized by adapting Feature selection using Class Based Principle Component Analysis “CBPCA” algorithm, which performs feature selection according to the fitness of any feature for different classes. Based on the selected features, the method generates regression tree for each feature considered. Based on the generated trees, the method performs classification by computing Tree Level Ensemble Similarity “TLES” and Class Level Ensemble Similarity “CLES”. Using both method computes the value of Class Match Similarity “CMS” based on which the malware has been classified. The proposed approach achieves 97% accuracy in malware detection and classification with the less time complexity of 34 seconds for 75000 samples
128-bit Vectorization on Cha-Cha20 Algorithm for Device-to-Device Communication
Authors: Kumar M. Satish , Rao PVRD Prasada
Published: January 2023

In 5G networks, device to device(D2D) communication is the advanced technology, and it has the major advantages when compared with traditional systems. The coverage area of the system increases by device-to-device transmission which renders with low latency. No doubt, for the upcoming technologies D2D communications is an added advantage but in various views this kind of transmission is still under risk. D2D communication is transferring the information from one device to another device without the involvement of base station. So, the communication is possible with less delay time. Attackers are possible into the D2D communications. To provide the security in communication, encryption algorithms are used. The main theme of the Encryption algorithms is it should execute with less delay time to provide faster communication and in particular CHA-CHA20 offers the secure communication for encrypting the data packets to securing the data. Vectorization on Cha-Cha20 Algorithm provides the security with less delay time compared to AES encryption Algorithm and Cha-Cha20 algorithm. Compared to other encryption algorithms in cryptography, Cha-Cha20 is suited for resource constrained devices.
Places of Forced Detention under the Jurisdiction of the Ministry of Internal Affairs of Russia
Authors: Sabaeva S. V.
Published: January 2023

The paper is devoted to the study of detention, conditions of medical care, nutrition, visiting rights as well as other rights of persons in places of forced detention under the jurisdiction of the Ministry of Internal Affairs of Russia. The author determines the features of the legal status of these persons in relation to their location: 1) in a report room of a police station; 2) in a special reception center for detention of persons under administrative arrest; 3) in a temporary detention facility for suspects and the accused; 4) in a temporary detention center for juvenile offenders; 5) in a temporary detention center for foreign citizens or stateless persons subject to administrative expulsion from the Russian Federation. Results of the analysis of federal laws and administrative and legal acts made it possible to conclude that it is advisable to develop a single standard of detention conditions and ensuring the rights of persons in centers of short-term detention. The author proposes the structure of the Standard which can be prepared on the basis of international standards and that can be of a methodological nature.
NFT as an Object of Legal Regulation
Authors: Sitnik A. A.
Published: January 2023

The paper is devoted to the study of the legal nature of a non-fungible token — NFT. The paper discusses the concept and types of tokens. The author defines a token as a unit of accounting in a distributed ledger that digitally represents financial instruments or other assets that expresses the economic value of the objects being represented and allows the rights associated with them to be exercised. According to a common point of view, NFT serves as a means of digital expression of a particular object, it has characteristics (signs) inherent exclusively to it, by virtue of which it cannot be exchanged for another token, and the cost of one NFT is not conditioned by the cost of other tokens. The author notes that the listed features are not inherent in NFT in all cases. In addition, using the example of NFT, the author draws attention to the problem of artificial limitations of the mechanism of legal regulation of fundamentally new digital objects. It is determined that, with regard to NFT, today in the Russian Federation, both the legislator and the financial market regulator maintain the status quo: the state intervenes in public relations that develop during the turnover of non-fungible tokens only if transactions involving them violate the law. Meanwhile, it can be expected that eventually the problems of the issue and circulation of NFT in the financial market will receive their regulatory and legal resolution.
Robot (Artificial Intelligence System) as a Subject (Quasi-Subject) of Law
Authors: Channov S. E.
Published: January 2023

The paper analyzes the possibility and expediency of recognizing robots and artificial intelligence systems as subjects or quasi-subjects of law. The author states that there are three approaches to understanding the subject matter: 1) the formal legal (positivist) approach; 2) the anthropocentric approach; and 3) the naturalistic approach Only within the framework of the latter, attempts are made to identify objectively existing features of the subject of law. At the same time, unlike a quasi-subject, the subject of law always has such a feature as freedom of will. The solution to the question of whether a robot (an artificial intelligence system) has its own will depends on understanding the concept of «will» itself, which is also far from unambiguous. The author identifies two main approaches to the concept of will: 1) the will as a manifestation of self-consciousness; 2) the will as the ability to achieve a goal. Modern robots (artificial intelligence systems) do not have self-awareness, therefore, within the framework of this approach, giving them the status of a legal entity is possible only in an indefinite perspective. The second approach to understanding the will can be applied to many already existing systems. Thus, the author states that the potential for subjectivity of robots (artificial intelligence systems) exists. However, the advantages of such a solution are not obvious in comparison with their consideration as quasi-subjects of law. In this regard, it is justified that the introduction into the legal sphere of such a fundamentally new subject of law as a robot (an artificial intelligence system) is premature. However, there is an objective need to recognize a number of them as quasi-legal entities that represent a certain legal value.
Online Dispute Resolution in the Field of Intellectual Property: Russian and Foreign Experience
Authors: Shakhnazarova E. A.
Published: January 2023

In the modern world, taking into account scientific and technological progress and the need for innovative development, many states are improving their legislation and approaches to regulating relations in the field of intellectual property by modernizing the justice system. With the use of Internet technologies, it becomes possible to carry out various settlement procedures, both judicial and extrajudicial. Due to the intangible nature of intellectual property objects, online dispute resolution in this area increases the level of protection of rights, expands access to justice, and the effectiveness of resolving disputes. In addition, the use of the blockchain distributed registry system allows you to create a platform for storing information related to the circulation of intellectual property. The experience of Russia, China, Thailand and Canada in the field of online resolution of disputes arising from infringement of intellectual property rights is studied. It is noted that a common understanding of the protection of copyright, as well as objects of industrial property, based on the provisions of fundamental international treaties, as well as modern technologies, including those built on the basis of artificial intelligence, with their correct structured application, will allow resolving such disputes promptly in pre-trial order, thereby unloading the judicial system. At the same time, their clear correlation with the provisions of international agreements is necessary.
Conflict of Interest between Subjects of Corporate Legal Relations in Shares Transactions
Authors: Levushkin A. N.
Published: January 2023

Considering transactions in the authorized capital of a joint-stock company, it is necessary to differentiate them according to the degree of influence on the corporate legal status of the participant. We believe that transactions that give rise to a conflict of interest at its highest stage have a complex structure and are associated with the acquisition of corporate control. The presence of a large number of initially and subsequently interested parties in the process of transactions with shares, especially those affecting control in society, is in itself characterized by a certain universality, which, in turn, predetermines the need to consider the issue raised in a comprehensive and multifaceted way. The category of conflict of interest in the plane of joint-stock relations traditionally manifests itself in disagreements between majority and minority participants, which take various legal forms. Equity transactions, whatever forms they may take, certainly fulfill the most important task of optimizing and regulating the modern economic system. The paper defines legal approaches to conflicts of interest between subjects of corporate legal relations when conducting transactions with shares, identifies the most essential and urgent problems, and suggests ways to solve them.
Influence of cooling of high temperature vane systems on efficiency gas turbine units regarding working substance specific heat capacity dependence on temperature
Authors: Basati Panah Mehdi , Rassokhin Viktor A. , Barskov Viktor V. , Okunev Egor I. , Laptev Mikhail A. , Kortikov Nikolai N. , Chu Van Chung , Gong Bowen
Published: January 2023

BACKGROUND: Gas turbine units (GTU) are widely used in power plants, shipbuilding, aerospace and other industry sectors. Main performance indicators of units are effective cycle efficiency and useful internal power. It is known that gas turbine power grows on 1525% for each 100C of turbine inlet temperature increases in range of 10001400 K, which makes it possible to save fuel significantly. Further growth of turbine inlet temperature demands more drastic increase of cooling air flow rate for the sake of cooling of the GTU flow channel, that leads to decrease of effective efficiency of a GTU. Consequently, the research of cooling and heat capacity properties influence needs to be done in order to improve gas turbine unit performance in the turbine inlet temperature range of 10001400 K.
AIMS: Issues of influence of cooling of high temperature GTUs as well as issues of influence of working substance specific heat capacity dependence on temperature are studied in the article.
METHODS: The study contains comparative analysis of four gas turbine units (GTU) such as: the 3,13 MW Teeda GTU (Iran), the 4,13 MW UEC Perm Engines GTU-4P (Russia), the 5,1 MW Siemens SGT-100 (Germany) and the 5,67 MW Solar Turbines TAURUS 60 (USA).
RESULTS: As a result, dependencies of efficiency, specific effective work and GTU useful work coefficient on cooling were obtained. Working substance specific heat capacity dependence on temperature was considered in order to increase accuracy of calculations.
CONCLUSIONS: The completed calculation study allows judging on perfection of the heat layout of GTU, the flow channel of GTU and making a comparison of them for the sake of further optimization of operational processes.
The Study of the Sound Waves Transmission along the Fluid Line through the TsN-2 Electric Pump
Authors: Brainin Boris P. , Veselov Alexey A. , Lomakin Vladimir O. , Mikheev Konstantin G. , Petrov Alexey I.
Published: January 2023

BACKGROUND: Noise at production site or at any other place where technical equipment operates is a huge issue. It has a strong negative effect on human nervous system, reduces average lifespan and causes a number of severe diseases. That is why reduction of noise, produced by pumps, is one of the current priorities of hydraulic engineering.
AIMS: In this study, the experimental research of sound transmission through an operating pump and a non-operating pump was carried out. The aim of the research is to find out, whether the last stage of a multistage pump is the main source of hydrodynamic noise (HDN) in pressure line (or the first stage in suction line), or all stages somehow contribute to HDN.
METHODS: The experiment was carried out on the TsN-2 two-stage impeller pump. In order to generate a sinusoidal signal, an imbedded generator, a vibration test rig and a power amplifier were used. Data acquisition for measurement of HDN and vibrations was performed with use of a conditioning amplifier, a hydrophone and an accelerometer. A 4-channel spectrum analyzer served as a device for processing the studied signal. In addition, a theoretical calculation, considering some physical assumptions, was carried out in order to obtain a more general and accurate concept.
RESULTS: After completing the experiment, hydrodynamic noise levels and differences for three cases were obtained. These cases are for the switched-on pump, the switched-off pump and for the pump with the removed stage. The data obtained with hydrophones (hydrodynamic noise levels) was correlated with the data obtained with accelerometers (vibration levels). As the correlated data analysis result, the sound insolation distribution over the spectrum was obtained.
CONCLUSIONS: According to the study results, it can be concluded that the absence of one of two stages ambiguously affected on the sound-insolation properties of the pump. Moreover, no firm conclusions can be drawn about the pump operation influence on the change in its sound-insolation properties.
Factors contributing to the late diagnosis of appendicitis in children: the results of a retrospective study
Authors: Yanitskaya Maria Yu. , Kharkova Olga A. , Markov Nikolay V. , Zolotarev Nikolay V.
Published: January 2023

BACKGROUND: The diagnosis of acute appendicitis in children is often established late, which leads to complications, lethal outcomes are recorded.
AIM: To identify and analyze the factors contributing to the late diagnosis of acute appendicitis in children.
MATERIALS AND METHODS: A retrospective analysis of 279 case histories of children was carried out. The duration of symptoms is divided into time 1 (before hospitalization) and time 2 (from hospitalization to surgery). Patients were divided into two groups: 1st with destructive uncomplicated appendicitis (phlegmonous, gangrenous), 2nd with complicated appendicitis (unrestricted peritonitis, infiltrate, abscess). The causes of late hospitalization, symptoms indicated in the case histories, examinations performed, postoperative complications were analyzed. The diagnosis was established on the basis of intraoperative data, histological examination.
RESULTS: In the 1st group, time 1 and time 2 were significantly less than in the 2nd (p 0.001; 0.028). Late presentation (24 hours) in 21.9%, misdiagnosis in 12.2% of cases. In the hospital, the observation of the patient 12 hours in 21.1% of patients. The frequency of presence / absence of a description of clinical and laboratory signs of acute appendicitis is from 100 to 19.7%. The 2nd group was characterized by: duration of symptoms 24 hours, repeated vomiting (p 0.001), febrile condition (p 0.001), increase in neutrophils 90% (8792%). Ultrasound examination with evaluation of the appendix in 20.1% of cases with a diagnostic accuracy of 89.3%. Laparoscopic appendectomy in 53.2% Alvarado scores are significantly higher in 2nd group (810) than in 1st group (79, p 0.001). In 1st group, complications were significantly less than 3.4% than in 2nd group 22.7 % (p 0.001).
CONCLUSIONS: Factors contributing to the late diagnosis of appendicitis in children are: late treatment, diagnostic errors at the prehospital stage, incomplete clinical examination and observation, insufficient use of laboratory and instrumental methods.
Methods of local anesthesia in postoperative anesthesia of oncosurgical operations on the nasopharynx in children
Authors: Korobova Lyudmila S. , Matinyan Nune  V. , Merkulov Oleg  A. , Korolev Vladimir  A. , Lazarev Vladimir  V. , Ovchar Tatiana  A. , Akimov Vasily P. , Kovaleva Ekaterina  A.
Published: January 2023

BACKGROUND: Postoperative analgesia should begin even in the operating room, so that at the time of awakening the patient does not experience pain and discomfort. The work is devoted to the problems of postoperative analgesia using local anesthesia techniques in oncosurgery of the nasopharynx in children.
AIM: The aim of the study to analyze the primary results of the use of local anesthesia methods in postoperative analgesia in pediatric oncosurgery of the nasopharynx.
MATERIALS AND METHODS: A study was conducted in the immediate postoperative period (16 hours) in ten patients, whose average age was 14 years with ENT surgical pathology. The physical status of the children corresponded to the III class according to the ASA classification. The patients were divided into two equal groups of 5 people: the 1st group included children who, for the purpose of postoperative analgesia at the end of the surgical intervention, underwent conduction anesthesia of the nose from three points according to Weisblat; the 2nd group (comparison group) is represented by patients in whom infraorbital anesthesia was used after surgery. Non-invasive monitoring of systolic and diastolic blood pressure, heart rate was carried out. The oxygen status was monitored by pulse oximetry.
RESULTS: The data obtained from the analysis of hemodynamic parameters, pain assessment by VAS (Visual Analog Scale) testified to the effectiveness of pain relief in patients in the study groups. The main hemodynamic parameters and pain assessment data for the groups were similar to each other and were within the reference values. There were differences in the duration of postoperative analgesia.
CONCLUSIONS: The proposed methods of postoperative analgesia make it possible to abandon the use of narcotic drugs, synthetic opioid analgesics, non-steroidal anti-inflammatory drugs, but not excluding analgesics antipyretics. The positive first results of this study provide for the need for a further set of observations, possibly in different clinics due to the relative rarity of oncological pathology of the nasopharynx in childhood.
Impact of malnutrition and its correction on mortality in older adults
Authors: Turusheva Anna V.
Published: January 2023

BACKGROUND: Malnutrition is associated with decreased levels of physical function, cognitive decline, and an increased risk of all-cause mortality, making it important to identify risk factors for malnutrition, especially in old age.
AIM: To identify factors associated with an increase and decrease in the risk of developing malnutrition, as well as to assess the impact of malnutrition and its correction on mortality in older adults.
MATERIALS AND METHODS: A prospective cohort study of a random sample of 611 people aged 65 years and older. Mini Nutritional Assessment, Geriatric Depression Scale, Mini-Mental State Examination, dynamometry, Barthel Index, chronic noncommunicable diseases, clinical blood count, C-reactive protein. 2 examinations, 9 years of total follow-up.
RESULTS: Risk factors for deterioration in nutritional status are decrease in emotional status (odds ratio 5.439; 95% confidence interval 2.79410.588), progression of autonomy decline (odds ratio 2.428; 95% confidence interval 1.3424.393), low physical function (odds ratio 2.877; 95% confidence interval 1.5775.250). A high level of physical function reduces the risk of malnutrition by 64.1%. Malnutrition increases the risk of five-year mortality by 2.7 times. A normal nutritional status reduces the risk of nine-year mortality by 50.2%. Improve nutrition status leads to a lower risk of mortality.
CONCLUSIONS: The main factors in the deterioration of nutritional status are a decrease in emotional status, loss of autonomy and a low level of physical function. Early detection of older adults with malnutrition and its correction can reduce the risk of mortality.
Question-Driven Ensembles of Flexible ETAS Models
Authors: Mizrahi Leila , Nandan Shyam , Savran William , Wiemer Stefan , Ben-Zion Yehuda
Published: January 2023

The development of new earthquake forecasting models is often motivated by one of the following complementary goals: to gain new insights into the governing physics and to produce improved forecasts quantified by objective metrics. Often, one comes at the cost of the other. Here, we propose a question-driven ensemble (QDE) modeling approach to address both goals. We first describe flexible epidemic-type aftershock sequence (ETAS) models in which we relax the assumptions of parametrically defined aftershock productivity and background earthquake rates during model calibration. Instead, both productivity and background rates are calibrated with data such that their variability is optimally represented by the model. Then we consider 64 QDE models in pseudoprospective forecasting experiments for southern California and Italy. QDE models are constructed by combining model parameters of different ingredient models, in which the rules for how to combine parameters are defined by questions about the future seismicity. The QDE models can be interpreted as models that address different questions with different ingredient models. We find that certain models best address the same issues in both regions, and that QDE models can substantially outperform the standard ETAS and all ingredient models. The best performing QDE model is obtained through the combination of models allowing flexible background seismicity and flexible aftershock productivity, respectively, in which the former parameterizes the spatial distribution of background earthquakes and the partitioning of seismicity into background events and aftershocks, and the latter is used to parameterize the spatiotemporal occurrence of aftershocks.
Investigating a Role for CHTF18 in Meiotic Crossover Formation
Authors:   , Gubbi Namitha L. , Padrick Shae B
Published: January 2023

Formation of DNA crossovers is a key process in meiosis that increases genetic diversity and ensures accurate chromosome segregation in gametes. Each pair of homologs must possess at least one crossover, called the obligate crossover, to properly segregate during meiosis I. Previously, we revealed a role for the DNA replication protein, CHTF18 (Chromosome Fidelity Factor 18), in mammalian meiosis. In Chtf18-/- mice, meiotic DSB repair is defective, homologs separate prematurely, and spermatocytes and oocytes possess fewer crossovers than wild-type mice. In addition, some homologs completely lack crossovers. These findings indicate a function for CHTF18 in regulating crossover number and ensuring the obligate crossover. Currently, we utilized Chtf18-/- male meiotic chromosome spreads to investigate a role for CHTF18 in crossover formation. We performed immunofluorescence microscopy and evaluated intermediates in the main crossover pathway (Class I). We found that MSH4, an early marker of crossover intermediates, is decreased during the pachytene stage of prophase I in Chtf18-/- spermatocytes compared to wild-type controls. We confirmed that MLH1 foci, a marker of final crossovers, are also decreased. Since MSH4 recruitment is important for crossover formation, these results suggest that CHTF18 may play a role in crossover formation. Finally, we optimized our method of preparing male meiotic spreads for imaging with structured illumination microscopy (SIM). We were able to visualize complete and incomplete synapsis of homologs in zygotene cells at a higher resolution with SIM than conventional microscopy. Collectively, our results provide a foundation to investigate further a role for CHTF18 in crossover formation.
Lithostratigraphy of the “Schist-Greywacke Domain” in Portugal: a reappraisal
Authors: De Meireles Carlos , Castro Paulo F. , Vaz Nuno , Ângelo Carlos , Ferreira Narciso , Sequeira António J. D. , Sá Artur A.
Published: January 2023

A synthesis of the knowledge of the Schist-Greywacke Domain (SGD) in Portugal is here presented. Until recently, this sequence assumed the designation of Dúrico-Beirão Supergroup composed by the Douro Group (DG) and the Beiras Group (BG). The DG is considered of Neoproterozoic – Cambrian age and the BG is of Neoproterozoic age. The identification and mapping in the BG of an unconformity as the Cadomian unconformity identified in Spain, which splits the Neoproterozoic in “lower Alcudian” and “upper Alcudian”, is a turning point for the understanding and establishment of consistent stratigraphic sequences that now compose the Fróia and the Lousã groups assembled in the Beiras Supergroup. These new groups are correlated with the Neoproterozoic sequences currently recognized in Spain: the Lousã group is equivalent to the Ibor Group (upper Alcudian) and the Fróia Group is equivalent pro parte, to the Domo Extremeño Supergroup.
Transportando vitriolo en el siglo XIX: El viaje trasatlántico de 4 vasijas de gres renano
Authors: Prieto-Martínez M. Pilar , Lantes Suárez Oscar
Published: January 2023

Se presentan los resultados del estudio realizado en cuatro vasijas de gres renano del siglo XIX que, siendo recuperadas en Cuba, probablemente han sido fabricadas en Alemania por encargo de la Corona Británica, rellenadas de vitriolo en la propia Alemania o Inglaterra y, después transportadas por barco a América. El estudio comprende un análisis formal, partiendo del concepto de cadena operativa, y analítico (TAC, DRX, FRX, SEM-EDX). La síntesis de ambas aproximaciones permite llegar a reconstruir en detalle la biografía de las vasijas.
Uso de cosmogénicos estables y radioactivos para la datación en España
Authors: Vidal-Romaní Juan Ramón , Arce Chamorro Carlos , Fernández Mosquera Daniel
Published: January 2023

Desde siempre la mayor dificultad en los trabajos de geomorfología ha sido la datación absoluta de superficies geomorfológicas que llegan al máximo cuando la superficie carece de cualquier tipo de recubrimiento. Es entonesc cuando el único criterio es, o la imaginación creativa o el uso de los isótopos cosmogénicos estables y en su defecto de los radioactivos ya que siempre que se pueda garantizar la estabilidad de una superficie el método dará una edad absoluta para la superficie. La datación tiene una precisión diferente según cual sea el isótopo utilizado. Para el caso de los cosmogénicos estables no hay limitación de edad aunque en otros (cosmogénicos radioactivos) estaría limitada por la vida media del isótopo utilizado. No debe nunca desdeñarse, mas que en cualquier otro tipo de datación, el análisis detallado de la historia geológica y geomorfológica de la superficie analizada.
Tourists' attitudes toward green product buying behaviours: the role of demographic variables
Authors:   Tourism Faculty, Necmettin Erbakan University, Konya, Türkiye, Pekerşen Yeliz , Canöz Fatma ,   Social Science Institute, Necmettin Erbakan University, Konya, Türkiye
Published: January 2023

Green products do not harm the environment or natural resources and support recycling. Due to tourists having different demographic characteristics, their demands and needs differ, and therefore their thoughts on green products also vary. Therefore, this study focuses on tourists' green product buying behaviours. In this context, the research aims to determine whether tourists' green product buying behaviours differ concerning demographic variables. The survey form prepared for this purpose was applied to 418 tourists visiting Istanbul. As a result of the research, foreign tourists' demographic variables were determined to affect their green product buying behaviours, with factors other than marital status and income level not contributing to tourists' environmental product preferences or their environmental sensitivity. Research has found that single tourists are more sensitive to the environment than married tourists. In addition, economically strong individuals were determined to be willing to pay more money for green products if they had sufficient purchasing power.
Adoption of renewable energy innovations among hoteliers in Portugal
Authors:   Centre for Research In Anthropology (CRIA), NOVA FCSH, Lisbon, Portugal, Silva Luís
Published: January 2023

This article examines the owners' and/or managers' perceptions and attitudes towards the adoption of renewable energy innovations in hotels in Portugal, as well as the factors that affect the adoption. The study is based on an e-mail-based survey conducted with hoteliers in 2022 (n = 208). First, the results demonstrate that despite the respondents' positive perceptions of renewable energy, the adoption level of renewable energy innovations in hotels is low. Second, the reasons given for this gap relate mainly to unfavourable market factors. Third, market factors have a statistically significant influence on adoption. In contrast, the characteristics of the hotels and hoteliers, their opinion about the need to cut the carbon footprint of tourist accommodations and the type of hotel ownership have no significant influence.