Features Of System Research Articles

Strategic investments in mobile and stationary energy storage for low-carbon power systems

The main feature and trend of the distribution system is the integration of renewable energy with high penetration rates. The variability and zero marginal cost characteristics of renewable energy will lead to drastically fluctuating locational marginal prices. In the deregulated electricity market, merchants have incentives to utilize energy storage and price arbitrage. Mobile energy storage has a short capital payback period and is widely recognized for transferring energy in the temporal and spatial dimensions. This paper analyses the interaction between merchants and distribution system operators and presents a hybrid energy storage strategic investment framework using bi-level programming. In the upper-level problem, the merchant formulates the capacity, location, and operation strategy of different energy storage to maximize the market revenue of hybrid energy storage, which is paid for by the locational marginal price. In the lower-level problem, the distribution system operator develops an optimal dispatch strategy considering renewable energy and merchant investments. A joint energy and reserve market clearing procedure is performed to derive the locational marginal prices. In the lower-level problem, a data-driven solution strategy based on machine learning is introduced. It uses deep neural networks to approximate the mapping relationship between distribution system states and locational marginal prices. The presented methodology is implemented in an IEEE-33 node system. The results demonstrate that, compared to the basic case, the hybrid energy storage investment strategy has led to an 8.1 % increase in merchant profits and a 12.9 % reduction in the operational costs of the distribution network. The deep neural network approximator fully avoids the lower-level problem with less than 5 % optimality loss.

S-слівна арифметика та високоточні обчислення

The intricacies of using S-word arithmetic, the influence of the value of the parameter S on the estimation of the rounding error are analyzed; what are high-precision calculations and where they are used. The problems of two-key cryptography, computer steganography and the problem of transcomputational complexity are considered as areas of application of S-word arithmetic. For the development of S-word arithmetic algorithms, sequential, parallel, quantum computing models are used, and systems of residual classes are used. The architectural features of the computer system for the implementation of an effective algorithm in various models of calculations are considered. For the parallel computing model, the importance of reducing the connected steps is indicated, which can increase the amount of processed data, but allows to involve a larger number of parallel processors. This approach is in conflict with a method that reduces the amount of processed data, and there is a need to maintain a balance between these two methods in a parallel computing model. For the quantum computing model, the connection of qubits is a key factor in determining the quantum volume. The physical scheme determines which pairs of qubits can be entangled in a quantum computer. Peculiarities of transferring algorithms to another computing model are considered. An analysis of the complexity of implementing S-word arithmetic operations in sequential, parallel, and quantum computing models is carried out. For the parallel computing model, the importance of reducing the connected steps is indicated, which can increase the amount of processed data, but allows to involve a larger number of parallel processors. This approach is in conflict with a method that reduces the amount of processed data, and there is a need to maintain a balance between these two methods in a parallel computing model. For the quantum computing model, the connection of qubits is a key factor in determining the quantum volume. The physical scheme determines which pairs of qubits can be entangled in a quantum computer. Information is provided about the ongoing scientific forum «Calculation optimization issues», the subject of which is closely related to the topic (1969-2023)

A novel system architecture of intelligent adaptive cruise control for safety aspects

Following industrial and safety standards for autonomous vehicles, Adaptive Cruise Control (ACC) is a widely employed Advanced Driving Assistance System (ADAS) feature in modern vehicles. ACC currently facilitates speed control based on the driver's desired speed value. This study introduces a significant advancement: the Intelligent Adaptive Cruise Control (IACC) feature, accompanied by the development of a control system architecture poised to make noteworthy contributions in scientific, economic, and social dimensions through its integration into autonomous vehicles. The design incorporates crucial elements such as Traffic Sign and Limit Recognition (TSLR), ADAS features, and Global Positioning System (GPS) data, primarily enhancing driver safety through these supportive features. The main focus revolves around designing a system architecture that accommodates these new features to ensure safe driving. The creation of the IACC system architecture is approached using Model-Based System Engineering (MBSE). Through this MBSE methodology, system-level diagrams were crafted, and security considerations were systematically addressed. Several scenarios were devised to evaluate the contributions and were subsequently tested and analyzed. The architecture places particular emphasis on the security aspects of IACC. Leveraging the TSLR feature, the system interprets traffic signs and acquires speed limit data from external sources, preventing the vehicle's speed from exceeding the specified limit. The comparison between the set speed value and the speed limit ensures adherence to safety parameters. In such scenarios, the system enhances driver support on winding roads by utilizing GPS data to recognize the vehicle in front. This approach significantly elevates the reliability of the IACC feature, particularly in terms of safety sensitivity, when compared to other adaptive cruise control concepts.

An Ecological Discourse Analysis of University English Textbook Discourses

Textbooks are important carriers for knowledge construction and value penetration. In this paper, two discourses are selected and analyzed from the perspective of ecological discourse analysis. By analyzing the distribution features of transitivity processes, mood and modality system, the paper explores the implied ecological ideology in the discourses.

Development and Implementation of Automated Notarial Data Management System

The Automated Notarial Data Management System presents a comprehensive overview of the development, implementation, and assessment of a digital system designed specifically for notarial offices. The system used Agile Software Development which is more appropriate for the completion of the system. The features of the new system include file upload and download functionalities, file sharing, folder creation, deletion, renaming, and viewing. The system evaluation focused on efficiency, usability, and reliability based on a survey conducted among office staff. The implementation results showcase improved workflow and document organization within the notary office, increasing efficiency and client satisfaction.

A multi-view feature representation for predicting drugs combination synergy based on ensemble and multi-task attention models

This paper proposes a novel multi-view ensemble predictor model that is designed to address the challenge of determining synergistic drug combinations by predicting both the synergy score value values and synergy class label of drug combinations with cancer cell lines. The proposed methodology involves representing drug features through four distinct views: Simplified Molecular-Input Line-Entry System (SMILES) features, molecular graph features, fingerprint features, and drug-target features. On the other hand, cell line features are captured through four views: gene expression features, copy number features, mutation features, and proteomics features. To prevent overfitting of the model, two techniques are employed. First, each view feature of a drug is paired with each corresponding cell line view and input into a multi-task attention deep learning model. This multi-task model is trained to simultaneously predict both the synergy score value and synergy class label. This process results in sixteen input view features being fed into the multi-task model, producing sixteen prediction values. Subsequently, these prediction values are utilized as inputs for an ensemble model, which outputs the final prediction value. The ‘MVME’ model is assessed using the O’Neil dataset, which includes 38 distinct drugs combined across 39 distinct cancer cell lines to output 22,737 drug combination pairs. For the synergy score value, the proposed model scores a mean square error (MSE) of 206.57, a root mean square error (RMSE) of 14.30, and a Pearson score of 0.76. For the synergy class label, the model scores 0.90 for accuracy, 0.96 for precision, 0.57 for kappa, 0.96 for the area under the ROC curve (ROC-AUC), and 0.88 for the area under the precision-recall curve (PR-AUC).

Reasons Explaining High Emergency Department Use in Patients With Mental Illnesses: Different Staff Perspectives.

For patients with mental illnesses (MIs), emergency departments (EDs) are often the entry point into the healthcare system, or their only resort for quickly accessing mental health treatment. A better understanding of the various barriers justifying high ED use among patients with MIs may help recommend targeted interventions that better meet their needs. This explorative qualitative study aimed to identify such barriers and the solutions brought forth to reduce ED use based on the perspectives of clinicians and managers working in EDs, other hospital departments or the community sector. Interviews were conducted between April 2021 and February 2022; 86 mental health professionals (22% were nurses) from four large urban ED sites in Quebec (Canada) were interviewed. Barriers were identified in relation to patient profiles, healthcare system and organisational features and professional characteristics. The key barriers that were found to explain high ED use were patients having serious MIs (e.g., psychotic disorders) or social issues (e.g., poverty), lack of coordination and patient referrals between EDs and other health services, insufficient access to mental health and addiction services and inadequacy of care. Very few solutions were implemented to improve care for high ED users. Better deployment of ED interventions in collaboration with outpatient care may be prioritised to reduce high ED use for patients with MIs. Improvements to the referral and transfer processes to outpatient care, particularly through care plans and case management programs, may be implemented to reduce high ED use and improve outpatient care among patients with multiple health and social needs.

Analysis of Lie symmetry, bifurcations with phase portraits, sensitivity and diverse W − M-shape soliton solutions for the (2 + 1)-dimensional evolution equation

This research investigates the Kadomtsev-Petviashvili-Benjamin-Bona-Mahony (KP-BBM) equation, a key model in nonlinear wave dynamics, particularly for shallow water waves. By integrating the features of the KP and BBM equations, it offers a comprehensive framework for studying the propagation, stability, and interactions of long waves. Using Lie group analysis for symmetry reductions and bifurcation with phase portraits to explore dynamic behaviour, the study also applies chaos theory to examine system features. Additionally, the new extended direct algebraic method (NEDAM) is employed to derive novel soliton solutions, including dark, bright-dark, W-shape, singular, periodic, and mixed forms. Sensitivity analysis is performed, and 3D, 2D, contour, and density plots visually demonstrate the results. These findings show that NEDAM effectively extracts exact solitons, providing a basis for further studies in nonlinear wave theory and its applications in engineering and physics.

A quasi-zero-stiffness vibration isolator inspired by Kresling origami

Vibration isolators are widely used to mitigate undesirable vibrations in engineering systems and structures, but low-frequency vibration isolation remains a challenge. Origami-inspired structures, with their tunable stiffness and transformative capabilities, offer potential for vibration isolation. Inspired by conical Kresling origami, this study proposes a quasi-zero-stiffness vibration isolation system. Static analysis of the origami structure reveals that the system exhibits near-zero dynamic stiffness at the static equilibrium position, while maintaining static stiffness during the load-bearing process. The amplitude-frequency characteristic formula and vibration transmissibility formula are derived using the harmonic balance method. The effects of varying damping ratios and excitation amplitudes on the amplitude-frequency and transmissibility curves are examined. It is shown that the vibration isolation range increases with the number of layers. A comparison of the system's response to harmonic vibrations under different compressive deformations highlights the effectiveness of the origami quasi-zero-stiffness system as a vibration attenuator. Compared to existing quasi-zero-stiffness dampers, the origami-inspired system features a wider isolation frequency band, a lower initial isolation frequency, and reduced vibration transmissibility, demonstrating superior isolation performance, particularly at low frequencies.

An improved tetracycline-inducible expression system for fission yeast.

The ability to manipulate gene expression is valuable for elucidating gene function. In the fission yeast Schizosaccharomyces pombe, the most widely used regulatable expression system is the nmt1 promoter and its two attenuated variants. However, these promoters have limitations, including a long lag, incompatibility with rich media, and unsuitability for non-dividing cells. Here, we present a tetracycline-inducible system free of these shortcomings. Our system features the enotetS promoter, which achieves a similar induced level and a higher induction ratio compared to the nmt1 promoter, without exhibiting a lag. Additionally, our system includes four weakened enotetS variants, offering an expression range similar to the nmt1 series promoters but with more intermediate levels. To enhance usability, each promoter is combined with a Tet-repressor-expressing cassette in an integration plasmid. Importantly, our system can be used in non-dividing cells, enabling the development of a synchronous meiosis induction method with high spore viability. Moreover, our system allows for the shutdown of gene expression and the generation of conditional loss-of-function mutants. This system provides a versatile and powerful tool for manipulating gene expression in fission yeast.

Motion-free high-resolution on-chip microscopy using LED matrix

Lensless microscopy is an imaging technique that allows high-resolution imaging over a large field of view with a cost-effective design. Conventional lensless microscopy often utilizes multi-height phase retrieval and pixel-super-resolution algorithms to reconstruct high-resolution images, requiring mechanical stages for three-dimensional relative movements between a light source, camera, and sample. However, the excessive use of stages inevitably increases the bulkiness of the system and extends the image acquisition time. Here, we propose a motion-free lensless microscope that incorporates an RGB LED matrix array. A high-resolution holographic image is reconstructed from subpixel-shifted color images obtained with LED illuminations without any mechanical movement. Using a prototype system, we have demonstrated a spatial-bandwidth product of 30 megapixels with a resolution of 0.87 µm and a field of view of 24 mm2. The usability of the proposed method has been further tested for histopathologic examination. Our system features a compact and high-performance design with inexpensive optoelectronic elements, a conventional CMOS sensor and an LED matrix, which are well-aligned with the original design motivation of lensless imaging methods.

Convolutional neural networks and seismogram fingerprints as a tool for recognizing the nature of seismic events

In the presented article, two facts are convincingly demonstrated based on the results of numerous experiments. Firstly, fingerprints are informative enough representations of signal seismograms, despite their compression, to carry information about the nature of a seismic event. Secondly, the study showed that it is practically possible to design and train an artificial neural network capable of classifying events by origin based on their fingerprints with high accuracy. Fingerprints are a tenthousandfold compressed representation of the original seismogram obtained using the onedimensional wavelet transform and the twodimensional Haar wavelet transform. They carry information about all significant frequencytime phenomena contained in the primary seismogram. Convolutional neural networks were chosen as a class of neural network classifier based on the conducted review of publications on this topic. They have proven themselves to be excellent in recognizing objects and persons in raster images. And the fingerprints used in this study are binary images measuring 64×64 pixels. The convolutional neural network prepared to work with them has one of the simplest architectures for this type of network and a very small number of adjustable parameters. By means of it, the classification accuracy of 95% was easily achieved. To prove that this result is not accidental, a strategy for modeling the architecture of convolutional neural networks using specially developed software, the Trova system, is demonstrated. This software allows the researcher to easily and conveniently operate seismograms, obtain binary fingerprints from them, correctly augment data, create, train and test neural networks. An important feature of the Trova system is the advanced functionality of the graphical representation of multidimensional modeling results.

Arionidae (Mollusca, Gastropoda, Stylommatophora) of the fauna of Belarus

The available data about the recent distribution of slugs of the family Arionidae on the territory of Belarus are summarised. The findings of a species formally new to the malacofauna of Belarus, A. fasciatus, are discussed. The material was collected in the period from 2018 to 2024 on the territory of the Gomel region (South-Eastern Belarus). The original illustrations of the habitus and anatomical features of the reproductive system are given.

Developing Standard Sets of Indicators for Patient-Centered Outcome Measures

The article describes how working groups of medical specialists led by the International Consortium for Health Outcomes Measurement (ICHOM) develop standard sets of indicators for patient-centered outcome measures. The main stages of working groups’ activity, methods, and criteria for including indicators were defined. The study showed that outcomes are comparable across countries since standard sets of indicators can be used by healthcare organizations all over the world, regardless of the healthcare model. While it is confirmed that the data obtained using PROM questionnaires are valid and reliable, it is recommended, based on the literature review, to fine-tune the standard sets of indicators for some nosologies to the features of the local healthcare system.

Supply chain agility in humanitarian organisations: examining the role of self-organisation, information integration and adaptability in South Sudan

PurposeThe purpose of this paper is to propose and validate a theoretical model to investigate the relationship between self-organisation, information integration, adaptability and supply chain agility in humanitarian organisations.Design/methodology/approachA theoretical model was developed from extant studies and assessed through a structured questionnaire survey of 86 humanitarian organisations operating in South Sudan. The data were analysed using partial least square structural equation modelling.FindingsThe study found that self-organisation has a discernible positive influence on supply chain agility not only directly but also indirectly through adaptability. Further, information integration does not significantly influence supply chain agility directly but is fully mediated by adaptability. Together, the antecedent variables account for 53.9% variance in supply chain agility.Research limitations/implicationsThis study contributes to providing an empirical understanding of a humanitarian supply chain as a complex adaptive system and hence the need to incorporate self-organising and adaptive dimensions in supply chain management practice. Furthermore, it confirms the centrality of the complex adaptive system feature of adaptability when building supply chain agility through self-organisation and information integration.Practical implicationsThe findings provide a firm ground for managerial decisions on investment in self-organisation and information integration dimensions so as to enhance adaptability and improve supply chain agility in humanitarian organisations.Originality/valueThis study is distinctive in the sense that it uses the complex adaptive system variables to empirically validate the relationships between self-organisation, information integration, adaptability and supply chain agility in humanitarian organisations in the world’s youngest developing economy with a long history of conflict and humanitarian intervention. The mediating influence of adaptability examined in this study is also novel.

Investigation of Innovative High-Response Piezoelectric Actuator Used as Smart Actuator–Sensor System

This paper presents an experimental analysis of a high-response piezoelectric actuator system for the modular design of hydraulic digital fluid control units. It focuses on determining static and dynamic characteristics, forming the basis for developing a smart Industry 4.0 component that incorporates both actuator and sensor function. The design process examines the main challenges, advantages, disadvantages, and working principles to define parameters that impact the actuator’s behaviour and performance. The new piezoelectric actuator system features three piezoelectric stack actuators in series, enabling simultaneous actuation and sensing by applying and measuring the electrical voltage at each piezo element. The experimental setup and test methodology are explained in detail, revealing that the new design, combined with an appropriate open-loop or closed-loop control method, offers superior actuator stroke control, high stroke resolution, and a high-dynamic step response. This paper proposes a concept of a smart piezo actuator system focused on I4.0 and an actuator administration shell, integrated with 5G and RFID technology, which will allow automatic plug-and-play functionality and efficient interconnection, communication, and data transfer between the hydraulic valve and the piezoelectric actuator system.

Internship Information System at PT Biro Klasifikasi Indonesia Samarinda Branch

The rapid development of information technology has led almost all companies and certain sectors to desire that all processes in their offices become fast and practical, including the internship application and registration process. PT Biro Klasifikasi Indonesia, Samarinda Branch, is a company that utilizes information technology; however, there are still aspects of information technology use that are not yet effective and efficient. One such aspect is the student internship registration, which is still done by registering directly at the company. This process is quite time-consuming and has many weaknesses. These weaknesses include long processing times and inadequate accuracy, such as incomplete or lost documents upon receipt, which can disadvantage applicants. As a result, this registration system poses difficulties for prospective interns outside the area. Therefore, the purpose of designing and developing a web-based internship information system at PT Biro Klasifikasi Indonesia Samarinda Branch is to simplify the internship registration process and assist the admin in verifying registration status, managing certificate data, and making it easier for applicants to fill out the registration form, view registration results, and check registration status through the website. The system development method used in this research is the waterfall model. To implement this internship registration information system, supporting components must function properly. These components use the Laravel framework and MySQL database. The results of this research, based on black box testing and respondent questionnaires, indicate that all features of this web-based internship information system can be used effectively and function as intended, thereby helping users manage internship registration.

Small field chaos in spin glasses: Universal predictions from the ultrametric tree and comparison with numerical simulations

Replica symmetry breaking (RSB) for spin glasses predicts that the equilibrium configuration at two different magnetic fields are maximally decorrelated. We show that this theory presents quantitative predictions for this chaotic behavior under the application of a vanishing external magnetic field, in the crossover region where the field intensity scales proportionally to [Formula: see text], being N the system size. We show that RSB theory provides universal predictions for chaotic behavior: They depend only on the zero-field overlap probability function [Formula: see text] and are independent of other system features. In the infinite volume limit, each spin-glass sample is characterized by an infinite number of states that have a tree-like structure. We generate the corresponding probability distribution through efficient sampling using a representation based on the Bolthausen-Sznitman coalescent. Using solely [Formula: see text] as input we can analytically compute the statistics of the states in the region of vanishing magnetic field. In this way, we can compute the overlap probability distribution in the presence of a small vanishing field and the increase of chaoticity when increasing the field. To test our computations, we have simulated the Bethe lattice spin glass and the 4D Edwards-Anderson model, finding in both cases excellent agreement with the universal predictions.

Design and operational features of an active condensation system for enhanced energy efficiency in a biomass-fired district heating plant

The study addresses the design and operational features of an active condensation (AC) system aimed at improving the energy efficiency of a 3rd generation district heating (DH) plant. Several similar biomass-utilizing plants have recently been built in the Republic of Serbia. The plant is equipped with biomass-fired boilers totaling 2 MW capacity, utilizing varying qualities of wet wood chips. The goals are: (i) to determine optimal constant and variable quench temperatures; (ii) to calculate the electricity consumption of ancillary devices and assess their impact on AC system performance; (iii) to evaluate the effect of biomass moisture variations on system size and performance; (iv) to assess the economic viability of integrating the AC system; and (v) to establish selection and design criteria for the heat pump (HP). For a given commercial HP, an optimal quench temperature exists, dependent on the minimal temperature lift required by the HP. This temperature can be calculated simply by subtracting the minimal HP lift from the lowest possible temperature that the HP can supply to a DH system at the average outdoor temperature. Consequently, an optimal variable quench temperature exists that should be adjusted to enable the HP to operate with its minimal temperature lift.

A Review of Structural Systems to be Built on Planets

The architectural construction process on planets is an architectural issue that develops day by day due to extreme environmental conditions and uncertainties. Architectural design needs structural systems to survive. Structural systems on planets encounter load factors that are different from the load factors on Earth. Choosing the optimum structural system is important for the structures planned to be built on planets to survive under the effects and loads of the environment and to adapt to human physiology. Some of the different types of structural systems used on Earth are featured in the literature for building a structure on planets. An evaluation system has been created to determine the correct system type for the first settlements on planets among the prominent structural system types and to narrow down the selection area of these system features. In line with this evaluation system in this study, a structural system model that stands up to harsh environmental conditions and protects human health is proposed for the first settlements on the planets. It is aimed that the evaluation system will be developed in the light of research emerging from developing technologies and can be used in future studies.