Functionality Of System Research Articles

Energy Sources in Natural and Anthropogenic Ecosystems

This study makes an inventory, a classification and a SWOT analysis of all energy sources that support the functionality of natural and man-made systems. The analysis is carried out at the planetary level, taking into account the entire ecosphere. It is an interdisciplinary study based on literature, integrating information from the field of ecology with that of physics, chemistry, biology, meteorology, and geography. The study carries out an inventory of all types of energy sources; makes a classification of these sources according to their origin and determines which is the most advantageous source through a SWOT analysis. The entire activity of the earth is supported by two large categories of energy sources, namely solar energy and telluric energy. Currently, ten types of energy sources are used or are in the experimental stage, five sources with solar origin and five sources with telluric origin. The most advantageous energy source in terms of regeneration capacity, production costs and ecological footprint is the biofuels. The conclusions of this study are very useful in the realization of energy production strategies and the selection of the most advantageous sources in terms of cost and benefit.

Development of Hill Cipher Method For Encryption And Decryption of Drug Prescriptions to Improve Data Security

A prescription is a written request from a doctor to a pharmacist, as not everyone can know the dosage or type of a particular drug, especially patients who need a prescription for the drug must be kept secret. Rapid technological advances can have an impact on all sectors, both private and government, including the medical field. One of the medical services that utilizes IT is to send prescription messages electronically to pharmacists in response to doctors' requests. The many misuse of prescription drugs by irresponsible people and misreading prescription drugs by pharmacists can be fatal for patients, so a solution is needed to overcome these problems. The purpose of this study is to create an encrypted electronic recipe application using the Hill Cipher method. This research method generally starts from data collection, data analysis and encryption model development. Applications designed with the Hill Cipher Algorithm are developed with modified algorithm keys using postal code patterns as the matrix keys, this aims to achieve the maximum level of security. The results of the system functionality test using the black box method obtained normal results for all system test scenarios. Validity testing yields valid results. The final test, through questionnaire testing, obtained a good level of system feasibility, namely an average level of Service of 83%, Features of 78% and Performance of 81%. Overall, the system has given a good performance score as the accuracy of the system is above 70%.

Vulnerability-based seismic resilience and post-earthquake recovery assessment for substation systems

The function of substation systems is significantly influenced by earthquakes. To assess the seismic resistance of substation systems and improve post-earthquake recovery efficiency, this study constructs a multi-module framework for seismic vulnerability assessment of substations. Based on the equipment functional status analysis module, a functional network model was established considering the structural function and electrical load of substation systems. The system functional state matrix was obtained through Monte Carlo simulation, and the seismic vulnerability was assessed from the aspects of electrical transmission reliability and the importance of power users. Subsequently, a substation functional index was established based on seismic vulnerability parameters. Post-earthquake functional recovery strategy analysis frameworks were constructed to quantitatively evaluate the recovery process. A stepped functional time-varying function was proposed through iterative analysis, thereby converting the probability parameters of functional status into seismic resilience deterministic indices. Through seismic resilience analysis of a typical 220 kV step-down substation, seismic vulnerability curves for both electrical transmission and power users were obtained. Furthermore, the seismic sensitive intervals of the substation and key equipment for post-earthquake recovery were clarified. Notably, the seismic resilience level and optimal recovery strategy of the typical 220 kV step-down substation were determined.

Functionality of XVE-inducible system and toxicity assessment of the bacterial PezT toxin in microalga, Messastrum gracile SE-MC4

Functionality of XVE-inducible system and toxicity assessment of the bacterial PezT toxin in microalga, Messastrum gracile SE-MC4

Integrating IoT and visual question answering in smart cities: Enhancing educational outcomes

Emerging as a paradigmatic shift in urban development, smart cities harness the potential of advanced information and communication technologies to seamlessly integrate urban functions, optimize resource allocation, and improve the effectiveness of city management. Within the domain of smart education, the imperative application of Visual Question Answering (VQA) technology encounters significant limitations at the prevailing stage, particularly the absence of a robust Internet of Things (IoT) framework and the inadequate incorporation of large pre-trained language models (LLMs) within contemporary smart education paradigms, especially in addressing zero-shot VQA scenarios, which pose considerable challenges. In response to these constraints, this paper introduces an IoT-based smart city framework that is designed to refine the functionality and efficacy of educational systems. This framework is delineated into four cardinal layers: the data collection layer, data transmission layer, data management layer, and application layer. Furthermore, we introduce the innovative TeachVQA methodology at the application layer, synergizing VQA technology with extensive pre-trained language models, thereby considerably enhancing the dissemination and assimilation of educational content. Evaluative metrics in the VQAv2 and OKVQA datasets substantiate that the TeachVQA methodology not only outperforms existing VQA approaches, but also underscores its profound potential and practical relevance in the educational sector.

Future outlook for food function research.

The results of research on food functionality in Japan have been passed on to society in the form of Foods for Specified Health Uses and Foods with Functional Claims. However, it is also true that there are people who do not experience any health benefits even when they consume these foods. To clarify the factors that cause such individual differences in the health benefits of food, research into the following points is important: 1) Elucidation of the molecular mechanisms behind why food factors exert their functionality. 2) Research into the functional interactions between food factors that exert their functionality in multi-component systems. 3) Research into the functionality of food factors that have not been the subject of research until now. We will introduce the results of our research in these areas. We will also discuss our expectations for the application of food functionality research to pharmaceutical development as an extension of this research.

Liver-specific actions of GH and IGF1 that protect against MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD; also known as nonalcoholic fatty liver disease) is a chronic condition associated with metabolic syndrome, a group of conditions that includes obesity, insulin resistance, hyperlipidaemia and cardiovascular disease. Primary growth hormone (GH) deficiency is associated with MASLD, and the decline in circulating levels of GH with weight gain might contribute to the development of MASLD. Raising endogenous GH secretion or administering GH replacement therapy in the context of MASLD enhances insulin-like growth factor 1 (IGF1) production and reduces steatosis and the severity of liver injury. GH and IGF1 indirectly control MASLD progression by regulating systemic metabolic function. Evidence supports the proposal that GH and IGF1 also have a direct role in regulating liver metabolism and health. This Review focuses on how GH acts on the hepatocyte in a sex-dependent manner to limit lipid accumulation, reduce stress, and promote survival and regeneration. In addition, we discuss how GH and IGF1 might regulate non-parenchymal cells of the liver to control inflammation and fibrosis, which have a major effect on hepatocyte survival and regeneration. Development of a better understanding of how GH and IGF1 coordinate the functions of specific, individual liver cell types might provide insight into the aetiology of MASLD initiation and progression and suggest novel approaches for the treatment of MASLD.

Designing A Blockchain-Empowered Telehealth Artifact for Decentralized Identity Management and Trustworthy Communication: Interdisciplinary Approach.

Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks. The main objectives of this study are to understand existing cybersecurity issues in identity management and trustworthy communication processes in telehealth platforms and to design a software architecture integrated with blockchain to improve security and trustworthiness with acceptable performance. We improved personal information security in existing telehealth platforms by adopting an innovative interdisciplinary approach combining design science, social science, and computer science in the health care domain, with prototype implementation. We used the design science research methodology to implement our overall design. We innovated over existing telehealth platforms with blockchain integration that improves health care delivery services in terms of security, privacy, and efficiency. We adopted a user-centric design approach and started with user requirement collection, followed by system functionality development. Overall system implementation facilitates user requirements, thus promoting user behavior for the adoption of the telehealth platform with decentralized identity management and an access control mechanism. Our investigation identified key challenges to identity management and trustworthy communication processes in telehealth platforms used in the current health care domain. By adopting distributed ledger technology, we proposed a decentralized telehealth platform to support identity management and a trustworthy communication process. Our design and prototype implementation using a smart contract-driven telehealth platform to provide decentralized identity management and trustworthy communication with token-based access control addressed several security challenges. This was substantiated by testing with 10,000 simulated transactions across 5 peers in the Rahasak blockchain network. The proposed design provides resistance to common attacks while maintaining a linear time overhead, demonstrating improved security and efficiency in telehealth services. We evaluated the performance in terms of transaction throughput, smart contract execution time, and block generation time. To create a block with 10,000 transactions, it takes 8 seconds on average, which is an acceptable overhead for blockchain-based applications. We identified technical limitations in current telehealth platforms. We presented several design innovations using blockchain to prototype a system. We also presented the implementation details of a unique distributed architecture for a trustworthy communication system. We illustrated how this design can overcome privacy, security, and scalability limitations. Moreover, we illustrated how improving these factors sets the stage for improving and standardizing the application and for the wide adoption of blockchain-enabled telehealth platforms.

Innovative teaching methods for developing basic skills in higher education students through real professional contexts

Introduction: The intensification of the significance of educational activity as an indicator of active social development under the conditions of global digitalisation creates prerequisites for actualising the issues of its informational support.Objective: The research is dedicated to analysing the functional capabilities of digitalisation in the context of forming critical competencies of students in conditions close to the realities of professional activity.Methods: The article outlines the functionality of innovative educational systems within the educational institution's information educational environment.Results: The study found that today's students at various levels are ready to implement elements of e-learning, artificial intelligence technologies, and immersive tools. It is proven that the introduction of innovative technological solutions into the educational environment creates learning conditions close to the realities of professional activity, increasing the motivation of students for an effective learning process, stimulating the involvement of reserves in the organisation of the continuous self-education process, and intensifying responsibility and self-organisation. Identified within modern information systems are tools and services that diversify the learning process and increase the effectiveness of the educational process, contributing to the formation of key competencies of higher education students.Conclusions: The research indicates a trend towards increasing the efficiency of student training based on the organisation of independent educational work with the implementation of innovative pedagogical opportunities in the educational process. The study's practical significance lies in determining the potential for improving the quality of education at the national level through modern information technologies

Task Scheduling Algorithm for Power Minimization in Low-Cost Disaster Monitoring System: A Heuristic Approach

This study investigates the optimization of a low-cost IoT-based weather station designed for disaster monitoring, focusing on minimizing power consumption. The system architecture includes application, middleware, communication, and sensor layers, with solar power as the primary energy source. A novel task scheduling algorithm was developed to reduce power usage by efficiently managing the sensing and data transmission periods. Experiments compared the energy consumption of polling and deep sleep techniques, revealing that deep sleep is more energy-efficient (4.73% at 15 s time intervals and 16.45% at 150 s time intervals). Current consumption was analyzed across different test scenarios, confirming that efficient task scheduling significantly reduces power consumption. The energy consumption models were developed to quantify power usage during the sensing and transmission phases. This study concludes that the proposed system, utilizing affordable hardware and solar power, is an effective and sustainable solution for disaster monitoring. Despite using non-low-power devices, the results demonstrate the importance of adaptive task scheduling in extending the operational life of IoT devices. Future work will focus on implementing dynamic scheduling and low-power routing algorithms to enhance system functionality in resource-constrained environments.

Special Requirements of Electronic Health Record Systems in Pediatrics: Clinical Report.

Pediatricians' use of electronic health record (EHR) systems has become nearly ubiquitous in the United States, yet many systems lack full functionality to deliver effective and efficient pediatric care. This clinical report seeks to provide a compendium of core pediatric functionality of importance to child health care providers that may serve as the focus for EHR developers and clinicians as they evaluate their EHR needs. Also reviewed are important but less critical functions, any of which might be of importance in a specific pediatric context. The major areas described here are immunization management, growth and development, social drivers of health tracking, decision support for orders, patient identification, data normalization, privacy, and system functionality standards in pediatric contexts.

Redundancy Control Strategy for a Dual-Redundancy Steer-by-Wire System

Currently, key factors hindering application of steer-by-wire systems are their inadequate safety and reliability, which are significant criteria for evaluating automotive active safety. Based on the steer-by-wire platform, a dual-redundant steering motor control system is proposed, featuring dual three-phase permanent magnet synchronous motors as execution motors, achieving redundancy from hardware. A torque vector-space-decoupling control method is introduced for these motors to ensure balanced and stable torque output. Upon a fault, fault-tolerant measures are taken by disconnecting power supply to the affected motor, which, despite reducing system functionality, allows for normal steering control. This research starts with modeling the dual three-phase motors to construct a simulation model. It then proceeds with hardware-in-the-loop testing integrated with the dual-redundancy steer-by-wire control system, conducting tests under dual-lane-change trajectory conditions. Finally, a steering system fault is simulated to assess fault handling and functional degradation. These experiments confirmed that the proposed method enabled balanced torque output from the dual three-phase motors in the redundant steering control and facilitated fault-tolerant processing post fault, ensuring the vehicle’s steering functions were maintained.

Climate‐resilient irrigation: Essential changes to balance food production and water security on a livable planet

AbstractClimate‐resilient irrigation is a necessity for sustainable development, aligning with broader goals of poverty alleviation, food security and environmental stewardship. By embracing adaptive strategies and fostering collaborative efforts, communities can navigate the challenges posed by a changing climate, safeguarding livelihoods and ecosystems. Climate‐resilient irrigation can improve coping measures and build resilience for communities through pathways which help improve agriculture. The relationship between agriculture, irrigation, water resources and climate change calls for an evolution of traditional irrigation practices towards climate‐resilient irrigation approaches, such as farmer‐led irrigation development; innovation and modernization to ensure the long‐term viability and functionality of irrigation systems and infrastructure; financing mechanisms to support the transition towards climate resilience; partnerships between governments, international organizations and the private sector to mobilize resources effectively; and efficient service delivery mechanisms, promoting equitable access and effective management of water resources. Emphasizing the need climate‐resilient irrigation to balance food production and water security, this essay advocates a paradigm shift towards sustainable water management, ensuring resilience in the face of climate uncertainties while safeguarding agricultural productivity and environmental integrity for a livable planet.

Comparative Investigation of Mobile Portable Complex System Functional and Laboratory Diagnostics with Stationary Equipment

The aim of the current study is to evaluate the effectiveness of using mobile portable complex system functional and laboratory diagnostics in patients compared to stationary equipment. The scientific study examined the results of functional and laboratory diagnostics of 123 patients who were at JSC NSMC at the time of diagnosis and treatment. The study covered a 1-year period from January 2023 to December 2023. Patients were divided into two groups: 1 group  - 63 patients, who were diagnosed using expert stationary equipment of NNMC; 2 group- 60 patients who were diagnosed using the mobile portable complex Health Examination System HES-7 (Konsung Technology; 2023). Results: Laboratory diagnostics were performed in 63 (100%) patients of the 1<sup>st</sup> group and in 60 (100%) patients of 2<sup>nd</sup> group. The compared groups had the same characteristics, for instance anaemia was detected in 4 (6.35%) patients of first group and in 5 (8.33%) patients of the second group. Mortality was not observed in the compared groups. According to all data obtained minor differences in diagnostic findings were found (1 to 6%). In addition, HES-7 demonstrated quite accurate functional analysis: electrocardiography, pulse oximetry, and spirography. Conclusion: The use of the digital mobile complex of functional and laboratory diagnostics Health Examination System HES-7 is safe and can be effectively used in primary health care settings by experienced nursing staff.

DSC-Net: Enhancing Blind Road Semantic Segmentation with Visual Sensor Using a Dual-Branch Swin-CNN Architecture.

In modern urban environments, visual sensors are crucial for enhancing the functionality of navigation systems, particularly for devices designed for visually impaired individuals. The high-resolution images captured by these sensors form the basis for understanding the surrounding environment and identifying key landmarks. However, the core challenge in the semantic segmentation of blind roads lies in the effective extraction of global context and edge features. Most existing methods rely on Convolutional Neural Networks (CNNs), whose inherent inductive biases limit their ability to capture global context and accurately detect discontinuous features such as gaps and obstructions in blind roads. To overcome these limitations, we introduce Dual-Branch Swin-CNN Net(DSC-Net), a new method that integrates the global modeling capabilities of the Swin-Transformer with the CNN-based U-Net architecture. This combination allows for the hierarchical extraction of both fine and coarse features. First, the Spatial Blending Module (SBM) mitigates blurring of target information caused by object occlusion to enhance accuracy. The hybrid attention module (HAM), embedded within the Inverted Residual Module (IRM), sharpens the detection of blind road boundaries, while the IRM improves the speed of network processing. In tests on a specialized dataset designed for blind road semantic segmentation in real-world scenarios, our method achieved an impressive mIoU of 97.72%. Additionally, it demonstrated exceptional performance on other public datasets.

GW with hybrid functionals for large molecular systems

A low-cost approach for stochastically sampling static exchange during time-dependent Hartree–Fock-type propagation is presented. This enables the use of an excellent hybrid density functional theory (DFT) starting point for stochastic GW quasiparticle energy calculations. Generalized Kohn–Sham molecular orbitals and energies, rather than those of a local-DFT calculation, are used for building the Green function and effective Coulomb interaction. The use of an optimally tuned hybrid diminishes the starting point dependency in one-shot stochastic GW, effectively avoiding the need for self-consistent GW iterations.

Impact of diabetes mellitus on endodontic treatment outcomes

Diabetes mellitus (DM) is a chronic metabolic disorder that affects various systemic functions, including oral health. Its impact on endodontic treatment outcomes has become a significant concern for dental practitioners. The relationship between DM and endodontic outcomes is complex, involving several pathophysiological mechanisms. Hyperglycemia leads to the formation of advanced glycation end-products, causing vascular dysfunction and impaired blood supply to the pulp, which exacerbates pulpal inflammation and increases the risk of necrosis. Additionally, chronic low-grade inflammation and an impaired immune response in diabetic patients contribute to a higher susceptibility to infections, delayed healing, and compromised tissue repair after endodontic procedures. Diabetic patients often experience lower success rates and prolonged recovery following endodontic treatment due to these systemic challenges. Reduced bone healing, persistent periapical lesions, and altered microbial flora are common complications that can hinder treatment success. Effective management of endodontic treatment in diabetic patients requires a multifaceted approach that includes strict glycemic control, the use of enhanced antimicrobial strategies, and the adoption of minimally invasive techniques to reduce tissue trauma. Additionally, patient education and close monitoring of the healing process are essential for minimizing complications. Understanding the pathophysiological interactions between diabetes and pulpal inflammation, as well as the factors that influence healing and success rates, is crucial for optimizing endodontic care in diabetic patients. By addressing both systemic and local factors, dental practitioners can improve the prognosis of endodontic treatment and ensure better outcomes for patients with diabetes. Ongoing research into the mechanisms underlying these complications will further enhance the ability of clinicians to manage endodontic cases effectively in this growing patient population.

Assessing the Predictive Utility of the C-Reactive Protein-to-Lymphocyte Ratio for Mortality in Isolated Traumatic Brain Injury: A Single-Center Retrospective Analysis.

Introduction: Early identification of high-risk traumatic brain injury (TBI) patients is crucial for optimizing treatment strategies and improving outcomes. The C-reactive protein-to-lymphocyte ratio (CLR) reflects systemic immunology and inflammation function and serves as a new biomarker for patient stratification. This study aimed to assess the predictive value of the CLR for mortality in patients with isolated moderate to severe TBI. Methods: A retrospective analysis of trauma registry data from 2009 to 2022 was conducted, including 1641 adult patients with isolated moderate to severe TBI. Patient demographics, the CLR, injury characteristics, and outcomes were compared between deceased and surviving patients. Univariate and multivariate analyses were performed to identify mortality risk factors. The optimal CLR cut-off value for predicting mortality was determined using receiver operating characteristic (ROC) curve analysis. Results: The CLR was significantly higher in deceased patients compared to survivors (60.1 vs. 33.9, p < 0.001). The optimal CLR cut-off value for predicting mortality was 54.5, with a sensitivity of 0.328 and a specificity of 0.812. The area under the ROC curve was 0.566, indicating poor discriminative ability. In the multivariate analysis, the CLR was not a significant independent predictor of mortality (OR 1.03, p = 0.051). After propensity score matching to attenuate the difference in baseline characteristics, including sex, age, comorbidities, conscious level, and injury severity, the high-CLR group (CLR ≥ 54.5) did not have significantly higher mortality compared to the low-CLR group (CLR < 54.5). Conclusion: While the CLR was associated with mortality in TBI patients, it demonstrated poor discriminative ability as a standalone predictor. The association between a high CLR and worse outcomes may be primarily due to other baseline patient and injury characteristics, rather than the CLR itself.

Reduced systemic microvascular function in patients with resistant hypertension and microalbuminuria: an observational study.

Resistant hypertension (RH) may be associated with microalbuminuria (MAU), a marker of cardiovascular risk and target organ damage, and both may be related to microvascular damage. Laser speckle contrast imaging (LSCI) is an innovative approach for noninvasively evaluating systemic microvascular endothelial function useful in the context of RH with or without MAU. Microalbuminuria was defined as a urine albumin-to-creatinine ratio between 30 and 300 mg/g. Microvascular reactivity was evaluated using LSCI to perform noninvasive measurements of cutaneous microvascular perfusion changes. Pharmacological (acetylcholine [ACh], or sodium nitroprusside [SNP]) and physiological (postocclusive reactive hyperemia [PORH]) stimuli were used to evaluate vasodilatory responses. Thirty-two patients with RH and a normal urine albumin-to-creatinine ratio (RH group) and 32 patients with RH and microalbuminuria (RH + MAU) were evaluated. Compared with patients without MAU, patients with RH + MAU showed reduced endothelial-dependent systemic microvascular reactivity, as demonstrated by an attenuation of microvascular vasodilation induced by PORH. On the other hand, ACh-induced vasodilation did not differ between groups. The results also revealed reduced endothelial-independent (SNP-induced) microvascular reactivity in hypertensive patients with MAU compared with patients without MAU. In this study, there was evidence of endothelial dysfunction associated with impaired microvascular smooth muscle function in patients with RH + MAU. This may suggest that patients with RH need more intensive therapeutic strategies for the control of blood pressure to avoid further vascular damage and the resulting consequences.The study was registered at ClinicalTrials.gov ( https://register.clinicaltrials.gov ) under protocol # NCT05464849, initial release 12/07/2022.

Glial swip-10 controls systemic mitochondrial function, oxidative stress, and neuronal viability via copper ion homeostasis

Cuprous copper [Cu(I)] is an essential cofactor for enzymes that support many fundamental cellular functions including mitochondrial respiration and suppression of oxidative stress. Neurons are particularly reliant on mitochondrial production of ATP, with many neurodegenerative diseases, including Parkinson's disease, associated with diminished mitochondrial function. The gene MBLAC1 encodes a ribonuclease that targets pre-mRNA of replication-dependent histones, proteins recently found in yeast to reduce Cu(II) to Cu(I), and when mutated disrupt ATP production, elevates oxidative stress, and severely impacts cell growth. Whether this process supports neuronal and/or systemic physiology in higher eukaryotes is unknown. Previously, we identified swip-10, the putative Caenorhabditis elegans ortholog of MBLAC1, establishing a role for glial swip-10 in limiting dopamine (DA) neuron excitability and sustaining DA neuron viability. Here, we provide evidence from computational modeling that SWIP-10 protein structure mirrors that of MBLAC1 and locates a loss of function coding mutation at a site expected to disrupt histone RNA hydrolysis. Moreover, we find through genetic, biochemical, and pharmacological studies that deletion of swip-10 in worms negatively impacts systemic Cu(I) levels, leading to deficits in mitochondrial respiration and ATP production, increased oxidative stress, and neurodegeneration. These phenotypes can be offset in swip-10 mutants by the Cu(I) enhancing molecule elesclomol and through glial expression of wildtype swip-10. Together, these studies reveal a glial-expressed pathway that supports systemic mitochondrial function and neuronal health via regulation of Cu(I) homeostasis, a mechanism that may lend itself to therapeutic strategies to treat devastating neurodegenerative diseases.