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This review paper presents a comprehensive analysis of the mitochondrial DNA (mtDNA) of Apis mellifera, commonly referred to as the Western honey bee. The present study aims to examine the genetic diversity, population structure, and evolutionary history of a species of insect that holds economic significance. This study elucidates the genetic determinants that impact the adaptive capacity, behavioral patterns, and overall well-being of honey bees through the examination of mitochondrial DNA (mtDNA) sequences derived from diverse honey bee populations across the globe. Furthermore, this study examines the potential implications of mitochondrial DNA (mtDNA) research on various aspects of beekeeping practices, conservation initiatives, and the comprehension of honey bee biology. This paper serves as a significant asset for researchers, beekeepers, and conservationists with a keen interest in exploring the genetic characteristics of Apis mellifera

Inulin is a source of fiber that can be used as a functional food. Foods that contain inulin can help overcome health problems such as obesity, colon cancer risk, lower blood sugar levels and reduce insulin resistance. The purpose of this paper is to summarize some research results on inulin content in tubers and their extraction methods. The inulin content in dahlia, gembili, uwi, potato, sweet potato, jicama, onion and garlic tubers are 74%; 15%; 12%; 7%; 13%; 41% and 33%, respectively. Extraction methods used include ethanol:water precipitation, microwave-assisted extraction, hot water extraction and ultrasound. In the future, inulin is expected to contribute to the treatment of digestive-related diseases.

Today, climate change, an increase in anthropogenic factors, and changes in the natural environment have an adverse effect on insect diversity due to the changing climes around the world. There has been an increase in the number of pests of agricultural crops over the past few years because of the expansion of the cultivated areas in arid regions, including the number of insects of the Order Orthoptera. The formation of fauna in different regions of the globe needs to be identified in order to improve the methods of combating them, and therefore, it is necessary to identify their formation. A great deal of research on the class of insects has been conducted over the last 35 years, and most of those articles are published in English. However, the research work on Insecta: Orthoptera was carried out in different topics and ways during those 35 years. The scope of this article is to cover all articles that have been published about orthoptera between 1986 and 2021 in the Scopus database. Various categories were analyzed in order to determine the quality of this research, including the year of research, who was responsible for the research, and which of the major research institutes did the research. In the light of the analysis, it is possible to have a certain understanding of the current research problems that are being experienced in this area as a result of the analysis.

The production of alternative fuels is a promising direction in the development of energy. Nowadays, in science the technology of heat treatment of various materials, including household solid waste is used. In order to obtain an alternative type of fuel from waste, the technology of heat treatment of raw materials without access to oxygen – thermolysis is used. Under the influence of low temperatures (400–500ºС) and without access to oxygen, the material decomposes into several components: water, gas, fuel oil and dark heating oil. To ensure the correct operation of such a line, it is required to supply finely divided raw materials to form the required plug in the loading zone from raw materials. Moreover, raw material should not be homogeneous. It is known that a mixture of rubber and paper gives cleaner results during heat treatment. To ensure proper operation and obtain the desired mixed raw materials, a rotary centrifugal unit with a complex dynamic effect on the material was developed. Calculations and studies showed that such a grinder design is capable of qualitatively grinding raw materials and mixing it in the right proportions. Small dimensions and a design solution in the form of a single rotor with several mechanisms of action on the material allow reducing energy consumption for grinding. The practical value of the paper is in the creation of an improved design of a rotary centrifugal unit on the basis of theoretical and experimental studies. It increases the productivity and quality of the resulting mixture. The results of the study can be used in the industry of waste processing plants.

This paper poses the problem of fuel energy and ecology in Russia. The paper discusses in detail the operation of biogas production plants. Advantages and disadvantages of such production, material costs, and raw material costs are presented. The statistics of biofuel production in the countries of the world is visualised. The paper compares different types of propulsion systems using different fuels, identifies the advantages and disadvantages, and examines the operation of one of the largest biogas plants in the world.

The paper deals with the determination and study of the drying rate. The authors believe that it is necessary to present the curves for changing the mass of the product and time, to take into account the possible ranges of changes in the parameters of the coolant. In addition, the paper discusses the actual speeds of airflow around the product, the required drying modes will become known owing to the knowledge of the features of the drying process. In this regard, the authors of the paper consider the volumetric and hydrodynamic characteristics of the product layer. The purpose of the study was to determine the area of the free section in the layer of products, the speed of air movement, the pressure loss in the layer. The results of computational and experimental studies have shown the possibility of determining the true speed of drying of various products.

In engineering, the use of mobile robots to teach automatic control is becoming more common because of the interesting experiments that can be conducted with them. In this paper, a mobile robot that applies reinforcement learning in different scenarios is shown, to get rewards, the agent learns by acting in the environment. creating a balance between new information and our current understanding of the environment. In this way, the algorithm can be divided into two stages: the learning stage and the operational stage. In the first phase, the robot learns how to go from where it is to a known destination, it builds a learning matrix that is subsequently utilized during the operational stage using the rewards and environment data. In this paper, the algorithm was studied in terms of rapid learning for the mobile robot and reducing the process of repetition in learning by specifying the values of alpha (α) and gamma (γ) in a way that is appropriate for preserving the variance and differentiation between them. To evaluate the robot’s adaptability to various dynamic situations, several simulated test scenarios were executed. In the testing situations, several target motion kinds and numbers of obstacles with various dynamicity patterns were used. The test scenarios illustrated the robot’s adaptability to various settings.

Encryption is vital for data security, converting information into an unreadable format to ensure privacy in online communication and sensitive sectors. Advanced encryption balances innovation and security in user-friendly applications. Image encryption employs techniques to protect image data from unauthorized access during transmission or storage, particularly crucial for safeguarding sensitive images in various applications. The goal is to prevent unauthorized access and ensure the safety of associated information. In this paper, I present a study on previous research related to my investigation, which focuses on encryption in general and image encryption in particular. The paper also discusses the methods used, particularly those closely related to my work, involving either SHA-256, MD5, or a combination of both. The review will look at the many strategies and techniques employed, as well as how precisely the task was completed by applying a set of parameters in comparison to earlier studies.

Individual Home Address is considered as an important sub set of attributes, and never find personnel record, whether a person is student, patient, or employee, etc. without having a home address. It is required to be recorded, registered, and documented in all personnel information systems, whether the system is manual or computerized. This research concern on the Coding, and Digitization of home address of Iraqi personnel in order to enhancing storage efficiency and reduce processing time. The conventional method of maintaining paper-based records for personnel home addresses has proven to be costly, and timeconsuming, and in most cases inefficient. The proposed solution involves the conversion of physical addresses into digital formats, allowing for streamlined data storage and faster retrieval, and update processes. The work starting by indicate the current challenges related to the paper-based address systems, including the demands on physical storage space and the delays incurred during information retrieval. Subsequently, it explores the potential benefits of digitizing home addresses, such as reduced storage requirements, improved data accessibility, and enhanced overall organizational efficiency. To implement this digitization process, the research investigates various technological solutions, including geographic information systems (GIS), databases, and data management protocols. The study also addresses potential concerns related to data security and privacy, proposing measures to safeguard sensitive information. The proposed solution for Digitization, Coding, with Optimizing the Personnel Home Address provide at least 85% of Optimizing Factor for each individual personnel record required storage space and processing time, this solution subsequently leed to better daily decision-making process in most business organizations.

Human face recognition and tracking (FRT) plays a vital role in various fields, including security, authentication, and human-computer interaction. The main modules of the FRT system are detection, feature extraction, and FRT. Using a database, these units recognize faces as well as their location, movement, and visible features. The framework aims to process large visual data in real-time, enabling accurate and fast FRT. The paper develops a real-time FRT framework using a lightweight CNN convolutional neural network to accurately match images of faces and environments with different illumination and expression differences to improve performance. This paper focused on the development of real-time facial recognition and tracking systems. The model used to achieve this is based on deep learning (DL) using a lightweight convolutional neural network (CNN) and post-feature extraction using linear discriminant analysis (LDA). Histogram of Oriented Gradients (HOG) experiments demonstrate that DL with lightweight CNN models provides a good solution for FRT tasks, even in challenging situations including changes in position, expression, illumination, and occlusion. The results of CNN-based DL were compared with several experiments. The model was also compared with many modern methods and achieved better results. The lightweight CNN model for DL outperformed it 100% of the time. When the split rate is 70:30 and the learning rate is 0.001, the epoch is 100. This demonstrates the dominance of DL over other techniques and shows how well it handles FRT tasks using lightweight and even real-time CNN methods.

Visible Light Communications (VLC) represents a new technology of wireless communications allowing high data rate, high-speed internet access, green and friendly communication system, especially for indoor users, where the use of Light Emitting Diodes (LEDs) is growing as a viable alternative to traditional illumination. Orthogonal frequency division multiplexing (OFDM) is a promising modulation format for optical wireless communication (OWC); however, precise channel estimation is required for synchronization and equalization. Moreover, one of the challenging issues for OFDM is its high Peak-to-Average Power Ratio (PAPR) due to the superposition of all subcarriers; therefore, the system requires a high linearity and dynamic range. This paper provides a systematic overview of OFDM-based VLC systems, highlighting the essential aspects of PAPR reduction and channel estimation techniques. Several technical challenges have been addressed to realize the full potential of OFDM-based VLC technology. Moreover, we provide new insights into the over-explored and under-explored areas, which lead us to identify open research problems of VLC based on OFDM. Concisely, this paper serves as a guide and a starting point for researchers willing to research VLC using OFDM.

Cryptography and Steganography are two main components of information security. Utilizing encryption and Steganography to establish many layers of protection is a commendable approach. Our main objective of this paper is to build an integrated method of securely transmitting data through a combination of cryptography and Steganography. Cryptography and Steganography are two common methods of secretly transmitting information. RC4 is used in this paper to change information from plaintext to cipher, and then cipher text is integrated into the image by Least Significant Bit (LSB). The results are defined in terms of the processing time, the peak signal-to-noise ratio (PSNR), and mean square error (MSE). The experimental results showed the stego image’s acceptable quality and combining the two techniques provides additional security in the original Steganography.

The Internet of Things (IoT), is changing practically every aspect of modern life. The proliferation of IoT has led to a rise in the frequency of cyber catastrophes. The threat landscape that security professionals face is dynamic, complex, and diversified. This paper proposes a novel approach to enhance Internet of Things applications by fusing the swarm intelligence of Salp Swarm Algorithms (SSA) with the predictive power of Random Forest (RF) and Decision Tree (DT) models Even though there is a lot of interest in the topic of explainable Artificial Intelligence (XAI) these days, more research is still needed to fully understand how successful XAI is at finding attack surfaces and vectors when implemented in cyber security applications. The growing use of machine/deep learning models in cyber defense, especially anomaly-based IDS, requires understanding the architecture of the models and providing evidence for their predictions to determine the probability of intrusions. Numerous approaches to interpretation have been proposed. They help researchers comprehend things like which variables have influenced the machine learning predictions. In this paper, we primarily address two popular local interpretation methods in machine learning: Shapley values and Local Interpretable Model-Agnostic Explanations (LIME).

With the rapid advance of the Internet of Things (IoT), technology has entered a new era. It is changing the way smart devices relate to such fields as healthcare, smart cities, and transport. However, such rapid expansion also challenges data processing, latency, and QoS. This paper aims to consider fog computing as a key solution for addressing these problems, with a special emphasis on the function of load balancing to improve the quality of service in IoT environments. In addition, we study the relationship between IoT devices and fog computing, highlighting why the latter acts as an intermediate layer that can not only reduce delays but also achieve efficient data processing by moving the computational resources closer to where they are needed. Its essence is to analyze various load balancing algorithms and their impact in fog computing environments on the performance of IoT applications. Static and dynamic load balancing strategies and algorithms have been tested in terms of their impact on throughput, energy efficiency, and overall system reliability. Ultimately, dynamic load balancing methods of this sort are better than static ones for managing load in fog computing scenarios since they are sensitive to changing workloads and changes in the system. The paper also discusses the state of the art of load balancing solutions, such as secure and sustainable techniques for Edge Data Centers (EDCs), It manages the allocation of resources for scheduling. We aim to provide a general overview of important recent developments in the literature while also pointing out limitation where improvements might be made. To this end, we set out to better understand and describe load balancing in fog computing and its importance for improving QoS. We thus hope that a better understanding of load balancing technologies can lead us towards more resilient and secure systems.

This paper presented a new technique for encrypting original texts based on multiplying the coefficients defined in the Taylor series of the logarithmic function by its equivalent index. As for decryption, a Sadik integral transform and its inverse were applied. Through this new technique, new mathematical techniques for encryption and decryption were discovered. This paper includes a practical example in order to demonstrate the efficiency of this technique.

Recognizing sign language is one of the most challenging tasks of our time. Researchers in this field have focused on different types of signaling applications to get to know typically, the goal of sign language recognition is to classify sign language recognition into specific classes of expression labels. This paper surveys sign language recognition classification based on machine learning (ML), deep learning (DL), and optimization algorithms. A technique called sign language recognition uses a computer as an assistant with specific algorithms to evaluate basic sign language recognition. The letters of the alphabet were represented through sign language, relying on hand movement to communicate between deaf people and normal people. This paper presents a literature survey of the most important techniques used in sign language recognition models

In this paper, the generation of green hydrogen utilizing the sun powered warm partition strategy is analyzed from a financial and natural point of view, and the arrangements of researchers and analysts to create this innovation and decrease its costs are considered, and insights are displayed for the generation of green hydrogen by this strategy. This paper analyzes the generation of green hydrogen utilizing sun oriented warm partition from a financial and natural point of view. It investigates the endeavors of researchers and analysts to create this innovation and decrease costs. The paper too presents insights on the generation of green hydrogen through this strategy.

Short Message Service (SMS) is widely used for its accessibility, simplicity, and cost-effectiveness in communication, bank notifications, and identity confirmation. The increase in spam text messages presents significant challenges, including time waste, potential financial scams, and annoyance for users and carriers. This paper proposes a novel deep learning model based on parallel structure in the feature extraction step to address this challenge, unlike the traditional models that only enhance the classifier. This parallel model fuses local and temporal features to enhance feature representation by combining convolutional neural networks (CNN) and long short-term memory networks (LSTM). The performance of this model has been evaluated on the UCI SMS Collection V.1 dataset, which comprises both spam and ham messages. The model achieves an accuracy of 99.28% on this dataset. Also, the model demonstrates good precision, recall, and F1 score. This paper aims to provide the best protection from unwanted messages for mobile phone users.

The purpose of this paper is to define and examine two novel forms of Nano βPC- continuity, namely Nano contra βPC- continuity and Nano almost contra βPC- continuity, and to provide several fundamental characteristics and attributes related to these mappings. Moreover, , paper is done on Nano almost continuously. The connections between these mappings and other well-known functions are found.

The soil water characteristics curve (SWCC) demonstrates a link between soil moisture content and suction. The SWCC is almost treated as an index parameter in unsaturated soil. The soil permeability and shear strength can be linked to SWCC. SWCC is established using filter paper for the wetting path. This paper compares SWCC for both cases stress-dependent and no stress (reference) in the wetting path. The samples of soil are brought from Al-Najaf City with a gypsum content of 29%, Iraq. The stress-SWCC is studied using a modified Oedometer cell with controlled water and air entrance to apply a specific matric suction. While the reference SWCC is estimated using the filter paper method. Matric suction is conducted at a range of pressures from 90 kPa to 0 kPa. The tests use three net normal stresses of 100, 200, and 400 kPa. The results show that there are decreasing values of the SWCC with increasing normal stresses. An interesting result is that this decrease is high and has zero matric suction. The water entry value (WEV) with the most significant value of the water entry change is represented by the matric suction of 50 kPa.

The thermodynamic cycles for energy generation are the baseline for development in different types of energy generation, and they are the primary principle for the mix of fossil and renewable energy. In this paper, a detailed description of the organic Rankine and Brayton-Joule cycles has been presented as a comprehensive reference library for linking renewable energy and fossil energy, and an explanation of the governing and basic equations that formulate When developed to be flexible in the use of the research methodology used in this field. This paper provides a comprehensive reference library for linking renewable energy and fossil energy by presenting a detailed description of the organic Rankine and Brayton-Joule cycles. It includes an explanation of the governing equations and basic formulations, as well as a flexible research methodology for use in this field.

Extracting information from an information platform, site or system is possible if the information is structured or annotated in a way that is convenient for subsequent analysis and data processing, decision making and reasoning. The goal of this paper is to review and categorize various techniques, tools, and libraries for extracting information from unstructured web content (platforms, sites, systems), and to develop a JavaScript application that crawls and extracts data from dynamic web pages without the need to browse, read and search the page content. The paper presents an implementation of a particular JavaScript web scraper that retrieves a list of news headlines from the official European Union Agriculture and Rural Development website without the need for the content of the document to be read by users. The web scraper is configured to extract the searched content directly from the source HTML code of the document, regardless of whether the information is explicit or implicit. It also searches all pages related to the document. Finally exports data in a proper format. The benefits of such a tool for extracting web content from source code are related to saving time, manual labour and means of generating quality content in the biotech and agriculture industry.

Fruit shape and size in Solanaceae family plays an important role in the determining the economic value and agronomic traits of the crop. This paper presents a comprehensive review of the genetic regulation of some Solanaceae fruit morphology, focusing on the role of CLAVATA1 (CLV1), OVATE family protein (OFP), SUN family gene (SUN), locule number (LC), and fasciated (FAS) genes. The aim of this article is to explore previous studies that reveal how the complex interactions between these genes regulate fruit shape. The SUN and OVATE genes have important roles in regulating fruit elongation, with the SUN gene affecting longitudinal and transverse cell growth, while mutations in the OVATE gene change the fruit shape from round to pear. In addition, the FAS and LC genes contribute to increasing the number of loci in the fruit, while the CLAVATA1 gene controls fruit size by regulating stem cell activity. This review paper provides a deep insight into the current understanding of the genes that regulate fruit shape and presents them in the context of current research. It is hoped that this article will provide a strong foundation for future research to improve the quality and productivity of tomato plants.

The paper examines the possibilities of the active influence of religious tourism on the preservation of the ecology of tourist regions. Currently, religious tourism is becoming more popular, every year more and more people are looking for peace in religious (often historical) monasteries, away from noisy cities and all-inclusive hotels. This article substantiates the idea that religious tourism is not only an opportunity to study the history of the emergence and development of a people, but also to gain new emotions by learning such enduring concepts as morality, humility, goodness, decency, faith. Many temples and monasteries are located in unique regions: in the mountains, on steppe plains or in virgin forests. Such a variety of landscapes in which holy monasteries are located makes it possible to realize all the greatness and uniqueness of nature, to awaken a desire to preserve it in its original form. Staying in holy monasteries is another opportunity for those who want to understand the essence and uniqueness of the world around us. This paper is also devoted to a philosophical understanding of the problem of the influence of religion on human behavior and attitude towards nature. Religion instills in a person responsibility for his actions. It is the moral institution of society. One of the goals of religion is the need to achieve a respectful attitude towards life. The prospect of a gradual improvement in the global environmental situation is largely associated with the revival of spiritual values and religious and ethnic norms.

Participation in a tender is an integral part of the activities of contracting construction organizations. The difficulty lies in the fact that contractors have to make a decision on participation or non-participation in the tender quite quickly from the moment the customer posts information about the procurement. Incorrect decisions made by the contractor at this stage lead to lost profits, financial losses, ineffectiveness, loss of reputation and other unpleasant consequences. To level out this situation, the paper describes existing approaches to assessing the risks of participation in tender activities, which can protect the contractor from participating in unwanted procurement. In order to assess the feasibility of participating in a procurement, the authors propose the development of an algorithm for express risk assessment of a contractor's participation in a tender, which suggests, under limited time, to make a reasonable decision on the need to participate in a particular tender. This requires a qualitative and quantitative assessment of the contractor’s main risks, which are combined into two main groups: the risk of loosing the tender and the risk of future losses. The authors propose methods for assessing risks and classifying them as high, medium and low levels. The paper provides an example of practical testing of the proposed express assessment.

Soft corals can produce bioactive compounds that act as antibacterials. Sinularia sp. is a soft coral that can produce antibacterial compounds. Symbion bacteria are bacteria that can produce bioactive compounds that tend to be the same as their host. The use of symbiont bacteria can be an alternative to exploit the potential of Sinularia sp. without harming marine life. This study aims to determine the antibacterial potential of the symbiont bacteria obtained from the soft coral Sinularia sp. in inhibiting the growth of Propionibacterium acnes and Staphylococcus epidermidis. The antibacterial activity test was carried out by the agar diffusion method using disc paper. Antibacterial activity was indicated by the formation of a clear zone around the disc paper. The results showed that LA7 isolate had the best antibacterial activity with an average clear zone size of 14.6 mm against Staphylococcus epidermidis and 16.6 mm against Propionibacterium acnes. LA7 isolates identified species based on the 16S rRNA gene with primers 27F and 1492R. Based on molecular species support, it was found that LA7 isolate is Bacillus aerius with a homology level of 98.17%.

This paper aims to determine the effect of waste management on the implementation of waste reduction in the Supit Urang landfill. This study uses weighbridge and quartering methods to determine waste generation and composition. The study is conducted at the sorting and composting facilities in the Supit Urang Landfill under the Emision Reduction in City-Solid Waste Management (ERiC-SWM) program, each facilities having a capacity of 35.000 kg/day for the sorting facility and 15.000 kg/day for the composting facility. The waste reduction at Supit Urang Landfill through the ERiC-SWM program is still relatively low, with a total waste reduction of 1.561,78 kg/day or 2,54 %. The composition of the reduced waste consists of three types of waste at the sorting facility: paper waste at 6,29%, plastic waste at 38,95%, and metal waste at 0,64%. Meanwhile, at the composting facility, only organic waste is reduced, accounting for 10,56 %.

In an effort to support the achievement of SGD, especially pillar No.13 (Climate Change), the existence of a technological model that enables to reduce negative impact of carbon emissions is one of the prerequisites for supporting the sustainability of life on Earth. To answer these challenges, this paper aims to introduce the idea of carbon capture technology in residential called SIMPLEX (Smart Integrated Housing Complex). This idea aims to introduce the use of engineering wood products as one of the innovative solutions to combat the adverse effects of carbon emissions. SIMPLEX is arranged in a housing complex inside there are Transparent Wood, Transparent Nano paper, Wind Turbines, Structural Applications, Water Treatment, and Energy Storage Devices. In the end, consideration of the negative impacts of SIMPLEX and the need for regulations supporting the implementation of SIMPLEX at the public level is conveyed. The SIMPLEX idea will also initiate the achievement of zero carbon emission building in Indonesia. In contrast to efforts to reduce carbon emissions by using alternative energy approaches and mobilizing the use of electric cars, efforts to reduce carbon emissions through a residential management approach based on carbon capture technology is a breakthrough that overlooked by Indonesian policymakers.

Implementing intelligent monitoring systems for Agricultural Machinery (AM) is hindered by the intricate and costly nature of the Internet of Things (IoT) sensor technologies. The heavy reliance on cloud and fog computing, the availability of network infrastructure, and the need for expert knowledge pose challenges in rural areas that lack network connectivity. Using edge devices, such as smartphones, which possess significant computational capabilities, is a potential solution that has not yet been fully realized in the commercial sphere. Furthermore, the increasing demand from users for economically viable and user-friendly technology serves as a driving force for transitioning away from expensive and intricate sensors towards more cost-effective alternatives. In the IoT era, there is anticipated to be a widespread network connection between a vast array of AM and service centers. Using smartphone applications has increased the potential for edge computation on smartphones to significantly aid in network traffic control. The development of an Artificial Intelligence (AI) - -based data analytic method poses a significant challenge due to the need to optimize for the limited computational capabilities of smartphones. However, the users’ demand for affordable technology renders it resistant to easy penetration. This paper uses IoT and AI to propose a Smart Health Monitoring System for Agricultural Machines with Deep Learning-based Optimization (SHMAM-DLO). This paper aims to propose a Fusion Genetic Algorithm (FGA) methodology and Artificial Neural Network (ANN) for optimization during monitoring the health of AM. The proposed approach enables cost-effective utilization of smartphone end devices by leveraging their built-in microphones instead of relying on expensive IoT sensors.

In this paper the association among renewable, non-renewable energy consumption and GDP growth is analyzed by using the secondary date of The World Bank and International Energy Agency for the period 1990-2021 of Uzbekistan. The paper employs the Autoregressive Distributed Lags (ARDL) model to estimate the long-run and short-run dynamic multipliers of energy consumption variables. Empirical results show that hydropower energy consumption (renewable energy) has a positive effect on GDP growth in the long term. Also, consumption of non-renewable energy resources (coal, natural gas, oil) has a positive effect on GDP growth in the short and long term. In addition, the increase in the consumption of non-renewable energy resources has a positive effect on CO2 emissions, which in turn means that the government should take measures to increase the share of renewable energy resources.

This paper examines the effects of Foreign Direct Investment, Economic Growth, Trade Openness, Energy Consumption, and Renewable Energy on CO2 Emissions in BRICS nations. This study employs the panel ARDL model to investigate the short- and long-term effects of an association between variables. The PMG estimator has shown itself to be more trustworthy and performs at a higher level of efficiency, leading us to the conclusion that it is the preferable technique. Because the error correction parameter, also known as the adjustment coefficient, is negatively significant, the findings demonstrate that there is a long-term relationship. According to the paper’s findings, there are both short-term and long-term effects of free trade and energy consumption on CO2 emissions. In the short run, FDI has positive impact on CO2 emissions, whilst renewable energy has detrimental effect. Surprisingly, the BRICS countries have not shown a correlation between economic development and carbon dioxide emissions. These findings may encourage policymakers in these countries in better recognizing the complexities of this occurrence, which in turn can assist direct future choices about this growing international security danger. Keywords: BRICS, Energy, Trade, CO2, Panel ARDL.

The agricultural sector serves as a fundamental cornerstone of the economies of numerous countries, necessitating technological advancements despite limited financial resources. The Internet of Things (IoT) presents a novel aspect within the field of soil health monitoring, which has significant implications for advancing smart agriculture and farming practices. Integrating conventional agricultural practices with cutting-edge technologies, such as the IoT and Wireless Sensor Networks (WSN), can foster Smart Agriculture (SA). This paper presents IoT Integration for Enhanced Turmeric Cultivation (IoT-ETmC) in the context of SA. The TurmFox IoT and Edge-to-Cloud (ETC) technology can analyze gathered data and send it to the user through internet connectivity. The work involves the implementation of TurmFox in experiments focused on turmeric cultivation. The results demonstrate a notable improvement in the quality of turmeric as a direct outcome of this intervention. The curcumin levels in the given product are notably higher, ranging from 4450 to 5450 mg per 120g. This paper also aims to demonstrate the intuitive configuration of sensor-to-actuator connections for implementing desired SA. The real-time data obtained from Turmfox provides information on the pH values, moisture levels, and temperature, allowing for observing dynamic variations in environmental conditions within the specified period. The pH level was 6.5 at 09:00, with a moisture content of 51 g/m3 and a temperature of 293 K.

The article focusses on the special nature of system structural changes occurring in modern Russian society, which directly reflect large-scale changes associated with internal and external aspects of integration of social, political, and legal institutions in the modern political and legal reality of the state, which significantly expands the instrumental sphere in the system of legal regulation, both in the general social context and in the strategic directions of the functioning of the Russian state. The authors have defined educational and legal-educational environment special spheres of modern state-legal space as the object of research because the most important system elements of the modern state function in the conditions of transformational changes in socio-economic, political-legal and socio-cultural plan. The aim of the work is the necessity to actualise a new concept of education in general, and higher education in particular, since in the modern world the institution of higher education is considered to be the most important factor in the development of human resources, in view of the fact that the factor of education in the future will be considered almost the main criterion for sustainable and successful development of any state. The methodological context of this paper is based on a combination of classical general scientific methodology and special techniques and means of scientific knowledge: comparative-legal, historical-legal, and concrete-sociological study of the problems posed in the paper.

This paper presents a new approach to the automated detection and quantification of pulmonary emphysema and pneumoconiosis using computed tomography images. The proposed method employs computer vision and neural network algorithms to improve the accuracy and speed of lung diagnosis, as well as the monitoring of emphysema and its changes over time. The study analyzes existing approaches and demonstrates the novelty of the proposed method. The paper reports high accuracy of emphysema extraction and size measurements based on three different patient cases, as evaluated by an expert, and the successful segmentation of pneumosclerosis. The proposed method has the potential to significantly improve medical image segmentation, particularly in the detection and diagnosis of diseases such as Chronic Obstructive Pulmonary Disease (COPD) and COVID-19. The study concludes that the proposed method may also be useful in other areas of medical imaging, contributing to the ongoing effort to develop new and improved methods for medical image analysis and interpretation.

The problem of reindustrialisation of the country and its transition to the sixth technological mode is of particular relevance for the Russian economy at present. At the same time, for the effective management of reindustrialisation, it is necessary, first of all, to develop a system of target setting for sustainable innovative development of industrial enterprises and production sectors. The aim of the paper is to consider and use a new methodological approach to the formation of such a system of target indicators. It is shown that there is no direct possibility of using for this purpose the theory of endogenous economic growth, the theory of long waves and the concept of technological patterns, the theory of sustainable development of economic systems. The paper presents ways and means of solving three problems arising in the process of effective management of sustainable innovation development of industrial production at the level of industries and enterprises: taking into account the impact on the activation of innovation activity of incoming open “tangible” innovations (patents, licences, software products) and closed innovations in the form of R&D costs; identifying the predominant impact on the resource efficiency of enterprises and industries of certain types of technological innovation-process and product innovations; determining for each type of technological innovation (process and product innovations); determining the impact of the innovation activity of incoming enterprises and industries on the resource efficiency of enterprises and industries.

This article examines Internet self-regulation as an adjunct to network regulation. The paper analysed the elements of an integrated approach to be undertaken to enhance regulatory effectiveness. The paper analyses and investigates the aspect of self-regulation as a way to strengthen legal relations in the network, considering the preservation of the balance of interests of the individual, society and the state. The “Manila Principles for Intermediaries”, which is one of the multi-stakeholder approaches to strengthen self-regulatory practices, were analysed in detail. The principles reviewed highlighted a number of advantages that are contained in the current legislation in promoting self-regulation. The results of the analysis highlighted some critical success factors in Internet regulatory issues that are essential for further official recognition.

An algorithm has been developed and implemented in this paper, which allows automating the process of forming and controlling scenarios for the movement of a collaborative robot (“Cobot”) through a database of points without specific interfaces, services, and software tools characteristic of each Cobot model. The unification of the developed single graphical interface is achieved by automating the work with Cobot controllers through specialised structured file formats and Robot Operation System (ROS), and by automatically detecting marks as movement points in the image received from the stereo camera using neural network-based models and image processing techniques. Research based on a series of experiments ensured the selection of the most effective image processing method and neural network model in terms of accuracy, speed, resource consumption. The approach formalised in the paper and the graphical interface allowed to implement a classical set of industrial tasks of Cobot motion control.

The paper presents the results of a study of certain aspects of the technological development of timber enterprises. The main attention is paid to the equipment replacement mechanism at these enterprises. The solution is to determine the optimal policy for its replacement or preservation within the planning period. The dynamic programming apparatus can be one of the tools. The paper presents the main features of its use. An example of its approbation on the basis of one of the timber enterprises of the Krasnoyarsk Krai is also given. The results obtained testified in favor of its use in practice. At the moment, the enterprise that acted as the object of approbation is implementing the development into its management policy. It was revealed that, depending on the specifics and characteristics of the enterprise, the profit from the use of author’s developments can be from 10 to 25%. The hypothesis that the use of mathematical tools to determine the policy of forest industry enterprises in terms of equipment replacement can significantly increase their economic efficiency has been fully confirmed.

The paper describes the technology for generating electrical energy in small hydroelectric power plants, in the absence of a natural descent of water flows. It is known that the main parameter for obtaining electrical energy is the water flow, which includes the speed of the water. Along with this, the paper theoretically considers the calculation of the resulting velocities of water flows in small hydropower structures. The calculations took into account the ideal, natural and real model of the process of increasing the efficiency in the hydraulic system when using artificial reservoirs with a dam. At the same time, the pattern of modeling various vectors from the initial flow, a term with the potential energy of the accumulated total mass in the cavity of the hydropower structure itself, was considered. This ensured growth and increase in modulus and in other parameters of the vector and force characteristics of the flow, leading to an increase in the overall efficiency of the complete structure. And this already led to an increase in the generation of electrical energy in the installation itself, which has a direct dependence on the momentum and on the flow rate. In conclusion, an output expression is given for calculating the resulting velocity in the system. It is concluded that the construction of the proposed hydropower structures increases the efficiency of hydroelectric power generation.

The paper presents a digital model of psychophysiological support for students, organized at various sites of the university. The digital model of psychophysiological support includes a set of procedures and activities aimed at ensuring the impact and support of health indicators, biological functions of homeostasis, and the psychophysiological well-being of students. Among the components of the digital model is the innovative project “Online Curator”, which contains a step-by-step description of the sequence of pedagogical actions of curators of student groups, which are based on the constantly updated information resource “Electronic methodological library”. Pedagogical actions are carried out by curators based on the results of annual monitoring and identification of risk groups among the students. Typical problems of students identified during testing in 2021 were problems of the emotional and personal sphere; communication problems; intrapersonal problems and difficulties of adaptation. The resource “Electronic methodological library” described in the paper is an original bank of methodological information designed to improve the psychological and pedagogical competence of curators and to directly organize a variety of extracurricular work with students. The inclusion of the curator’s figure in collective and individual activities for the psychological support of students using IS resources allows him to effectively carry out socializing, preventive, regulatory functions, providing effective support for the psychological well-being of students.

The impurity of menstrual blood is a universal myth that spans across all societies and cultures. This notion has also established a barrier to gender equality, as females are instructed, throughout cultures, that menstruation is disgraceful. This belief restricts their capacity to conduct regular duties when they are bleeding, hence making them organize their lives around their menstrual period. The need to fill the inadequate understanding of the menstrual cycle in society is a necessity. The third wave of feminism encouraged society to discuss certain challenging topics, which led to considerable breakthroughs in beliefs around menstruation. The day when feminist discussions were limited to people who could pay to express their opinions has long since passed. The concept of feminism in the twenty-first century encompasses a larger spectrum of opinions. Strong arguments on women’s cleanliness and the need for understanding menstruation only serve to emphasize how crucial and significant the issue is. The present paper attempts to explore the myths and taboos, cultural and political perspectives on menstruation, and the role literature is playing in altering society’s attitudes about menstruation. The paper will attempt to comprehend how important literature is in eradicating the stigma associated with menstruation and how it contributes to raising awareness of menstrual hygiene among people.

Cryptocurrency has emerged as a revolutionary innovation that has been replacing traditional finances and enthralling the worldwide technology landscape. This has gained a lot of popularity worldwide for its potential to enable peer-to-peer transactions and offer opportunities for investment and novelty. Nevertheless, it gives rise to issues concerning regulatory adherence, instability, and security apprehensions, turning them into a topic of continuous evaluation and investigation within the fields of finance and technology. This research paper presents a comprehensive exploration of the historical evolution of “Ethereum” as one of the leading blockchain platforms, with a primary focus on price prediction using a long-short-term memory (LSTM) machine learning model. The study includes various critical aspects of Ethereum, starting from its historical evolution to its potential future scope in scaling solutions and payments, and also covering the insights of Ethereum’s tokenomics, utility, and beyond. In addition, the methodology involves using the LSTM model to analyze data from Ethereum. The accuracy of price predictions is assessed by evaluating error metrics and further improved by visualizing the data through graphs that show indicators. This paper gives an in-depth perspective for anyone who is seeking a holistic understanding of cryptocurrencies, mainly concentrated on Ethereum, and also provides valuable guidance to investors, developers, and enthusiasts, encouraging them to make knowledgeable decisions in the ever-changing blockchain ecosystem.

With the continuous development of communication, sensor and caching technologies, IoT technology has gained rapid opportunities for growth and a huge digital revolution has taken place at all levels of society. Blockchain technology has emerged rapidly in recent years and can be seen as a distributed, time-based ledger of distributed data. It utilises technologies such as consensus protocols, modern cryptography, P2P and smart contracts, which can provide a secure, stable, transparent, auditable and low-consumption system architecture that has a traceable, stable and efficient security management capability, and can provide a new solution to identity security for the Internet of Things. This paper absorbs the existing blockchain-based access management approach and improves it, proposing a new private chain-based security management approach that solves the problems of access dynamics, low intelligence and high overhead in the traditional access management approach. This paper designs a new control management architecture, the Novel-Capability-Based Access Control (NCBAC), which draws on the microkernel and microservice ideas of operating systems. Firstly, this paper abstracts the concept of management node to solve the problem of weak computing power and low storage performance of IoT devices that cannot meet the difficulty of direct communication between IoT devices and blockchain, and at the same time can reduce the network operation overhead; secondly, it constructs a multi-level smart contract system and designs three kinds of smart contracts, AC, ACC and AMC, to build a trusted and reliable access control entity model; finally, it adopts radial basis based (RBF) neural network and combines with access policy to dynamically generate the credit degree threshold of access nodes to build an intelligent access authority management model for IoT mass sensors. The model proposed in this paper designs a token mechanism based on the fact that IoT systems have multiple requests within a short period of time in a real production environment, which, according to experimental results, improves the performance of the system to a certain extent.

Based on the requirements of the computer technology background in the new era, this paper takes Chinese biopharmaceutical enterprises as the research object, outlines the general characteristics of innovation in Chinese biopharmaceutical enterprises, and analyses the current situation of innovation development in biopharmaceutical enterprises from four aspects: policy, economy, society and technology, followed by an analysis of the current problems faced by innovation in Chinese biopharmaceutical enterprises and the reasons for their generation. Based on literature research, theoretical studies and analysis of the causes of the current innovation problems of Chinese biopharmaceutical enterprises, the factors affecting the innovation performance of Chinese biopharmaceutical enterprises are summarised. The specifics of the conditional variables, as well as the outcome variables, are then identified according to the specific manifestations of poor innovation performance of biopharmaceutical firms. Finally, corresponding countermeasures are proposed in terms of the level of corporate R&D investment, the level of financing channels, the level of government policy support, and the internal management of biopharmaceutical companies, in conjunction with the characteristics of different path models. This paper combines the big data foundation to research and analyse the development of biopharmaceutical enterprises, laying a new research foundation and providing a more efficient research path for the development of the biopharmaceutical industry.

As the main drug for the treatment of type II diabetes, presently used α-glucosidase. inhibitors generally have serious side effects. Developing new, effective, safe, and economical α-glucosidase inhibitors from medicinal and edible plant resources have become a research hotspot. In this paper, Kombucha was used for the fermentation of dried mulberry leaves (ML-DS) and fresh mulberry leaves (ML-FS), with the aim of increasing the content and α-glucosidase inhibitory efficiency of active substances in ML.The research results indicated that both dried and fresh mulberry could be used as fermentation substrates for Kombucha, especially ML-FS. After 12 d of fermentation, pH value and reducing sugar concentration of the ML-FS was rapidly decreased from 6.46 to 2.78 and from 108.43 ± 5.33 mg/ml to 19.40 ± 1.67 mg/ml, respectively. As for the total flavonoid content in the extract of ML (MLF), the MLF content in the ML-FS that fermented for 12 d (ML-D12-FS) was increased by 49.46% compared to that in the unfermented ML (ML-D0-FS). Meanwhile, Kombucha fermentation also can significantly improve the α-glucosidase inhibitory activity of MLF. At the concentration of 45.6 mg/L, the inhibition rate of ML-D12-FS on α-glucosidase reached to 85.88%, and the IC50 value decreased to 5.5 mg/L which was 16.7 mg/L for ML-D0-FS. This paper would provide an economical and green method for the production of α-glucosidase inhibitors from mulberry leaves.

Autophagy of vessels endothelial cells is the critical pathological process in atherosclerosis (AS). Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a kind of long non-coding RNA (lncRNA) that regulates the autophagy of vessels endothelial cells, including microautophagy. However, the relationship between AS and MALAT1 is not completely understood, and microautophagy has been ignored. In this study, I designed the experiments to research the impact of MALAT1 in endothelial cells, which could regulate the progression of AS. In the present study, I design to establish the AS model mice with low MALAT1 level. The expression level of MALAT1 needs to be detected to verify the mouse model. Then, the intensity of microautophagy of endothelial cells of mouse model and normal mouse are detected by RT-qPCR, immunofluorescence assay, and observation directly with electron microscope. The atherosclerosis progression and plaque stability are detected by comparing the rations of macrophage/vascular smooth muscle cell and collagen/lipid. This paper only provides theoretical experiment design and possible results about how MALAT1 affects AS by regulating microautophagy of vascular endothelial cells (VECs) which needs additional research in the pathology of atherosclerosis. This paper provided the possibility that MALTA1 regulates the microautophagy in VECs and MALTA1 may be the target to cure AS.

Research on the potential anticancer effects of citrus has been widely published in scientific journals. Still, a bibliometric analysis concerning this topic has not been executed. This study employed bibliometric mapping to analyze articles related to citrus anticancer from the Scopus Database and visualized the results using the VOSviewer. In this review, 442 papers published between 1995 and 2023 were selected. Jeju National University in South Korea is recognized as a top contributor. According to the analysis, apoptosis and anticancer are the two specific keywords in the field with the highest co-occurrence. The other keywords in the selected papers were hesperidin, naringenin, nobiletin, apoptosis, and flavonoids. We also found the following steps in this research area: formulation, synthesis, and in vivo preclinical studies. Research trends have shifted from the crude extract to practical applications of specific flavonoid compounds with structure modification to improve their anticancer properties. Still, clinical trials in humans are lacking in this research area and should be further investigated to embrace citrus flavonoids as an anticancer candidate. This analysis and mapping provide a comprehensive understanding of research on the potential anticancer effect of citrus.

A paper contains materials on the study of bog bilberry in the conditions of Central Yakutia, which are presented in the paper. In the species, there is a variability in the morphological, endogenous, individual, geographical and ecological variability of generative and vegetative organs, as well as phenological development. Among the following traits, there was greatest variability: number of berries per bush (30.1%), and size of the branch (leaf blade length and thickness) 30.9% and 29.3%, respectively. Less variables were berry weight (15%) and height of fruit-bearing bushes (14.9%), but they were not much different from other variable traits. Among the traits that have been studied, the taiga zone of South Yakutia can be considered an ecological optimum for V.uliginosum due to the manifestation in most of the studied traits. Bog bilberry in the conditions of Central Yakutia requires more thorough study and brand-new agrotechnical cultivation methods due to the slow entry of plants into the generative stage of development. The introduction is required for an improved approach to plant production, as well as new agrotechnical techniques that are adapted to support the slow entry of plants into the generative stage of development.

The integration of digital technologies in agriculture has great prospects in solving the problems of global food security in the 21st century. The future lies in big data and the analyses based on it. This paper analyses existing research in order to reveal the impact of digital agriculture on food security. The paper considers technologies such as the Internet of Things (IoT), global positioning system (GPS) and blockchain. These technologies are analysed for their role in optimizing agricultural processes and transforming traditional farming practices. The results of the study reveal the impact of data analytics on data-driven decision making, accurate resource management, and greater transparency across the entire food value chain. Data analytics empowers both large enterprises and SMEs by promoting sustainable practices while adapting to the challenges of climate change. This study also focuses on technology accessibility, data security, knowledge integration, and policy frameworks. Aligning technological solutions with socio-economic, environmental and ethical considerations, digital agriculture becomes a key solution to achieve sustainable and equitable global food security.

This keynote presentation was developed to provide a baseline research understanding of marine science education. The aim is to provide an entry point for conversations among educators of marine education in Southeast Asia, particularly Indonesia. Conversations are needed to develop the perceptions of marine education among policymakers not only in education but also in the economy. Marine education is under-researched and under-taught in most countries, even those with long coastlines. Yet, without our oceans, life on Earth cannot exist. This paper presents a rapid review of 149 research papers located in a systematic search of the ERIC via ProQuest that followed the PRISMA exclusion process. The findings are presented as eight themes and a set of recommendations.