Components Of System Research Articles

Systems analysis of the national performance management system for TVET lecturers in South Africa

A quality performance appraisal (PA) and continuing professional development (CPD) system is an essential component of a national performance management system for TVET lecturers. It is intended to support an improvement in lecturer quality and accountability, strengthens student graduation rates and feeds national human resource development for sustainable employment. The aim of this research study was to contribute to improvements in the functional integration and synergies between PA and the CPD system as applied in TVET colleges. The study involved the collection of qualitative data at six South African TVET colleges in order to develop a general description that captures the key features and interactions commonly shared across the case studies in a general analytic model. Data collection, coding and analysis informed the iterative development of a systems model based on causal loop analysis (CLA). This application of the CLA tool provided the means to represent multiple relationships and the feedback loops between them visually. We found that four main causal loops strongly influence the dynamics of PA and the CPD system. The findings offer an analytic platform for further research towards strengthening and reviewing the overall performance management system for TVET lecturers.

SOIL MOISTURE AND PH CONTROL DEVICE IN SPROUT CULTIVATION

Sprout cultivation is one of the practical and economical methods to obtain a type of food rich in nutrients. However, the success of sprout cultivation requires proper control of soil moisture and water pH in the cultivation environment. Watering begins when the moisture of the mung bean plant reaches the specified parameters with a soil moisture of 67 and a pH value of + 9. This tool aims to make manual work easier to automate, a benefit in watering sprout plants. This tool uses a water ph sensor and a soil moisture sensor or soil moisture sensor that functions as a soil moisture detector that will send commands to the Arduino uno to turn on the relay so that the water pump can automatically water according to the needs of the soil. The creation of this final project is carried out by designing, making and implementing system components which include Arduino uno as a controller, relay to turn on the water pump and turn off the water pump, LCD (linquit Crystal Display) to display the soil moisture value and water ph value. The results of the research value prove that the tools to be made can function properly and can be developed as expected.

Energy Enhancement for Grid Connection by Boost Inverter in Tripolar Operation with Novelty Quadcoupling Control

In this paper a single-phase differential boost inverter is presented that has two functions, first is boost up and second is active power quadcoupling without adding active power electronics components for smart grid system. There are three operating principals: First is pulse energy modulation which operates converter in continuous conduction mode (CCM), Second is quadcoupler which is designed by adding four boost converters and third is Tripolar technique which used to add two inductors and one capacitor for each boost converter. The proposed model consist of four boost converters in parallel with interleaving switching technique to get lower duty cycle. The energy is delivered to the quadcoupler through tripolar technique. When two grids are connected through DC to AC conversion the boost inverter can increase voltages on required demand. A Simulink model is designed that shows and proves properties of proposed system with high energy, high efficiency and power control with lower voltage stress.

Characterization of PFAS Residuals: A Case Study on PFAS Content in a Firefighting Foam Delivery System of an Aircraft Rescue and Firefighting Vehicle.

When fire suppression systems that held aqueous film forming foams (AFFF) are transitioned to per- and polyfluoroalkyl substance (PFAS)-free firefighting formulations, PFAS can dissolve from the wetted surfaces of the systems and release into the new firefighting formulations. The overall objective of this work was to characterize PFAS residual mass on the wetted surfaces of aircraft rescue and firefighting (ARFF) vehicle on-board fire suppression system components from the water, mixed fire water, and foam concentrate systems with various geometries, materials of construction, and locations within the fire suppression system. The ARFF vehicle components were dismantled from the system after a triple water rinse procedure which removed 19,600 mg total measured PFAS post-TOP assay from the foam concentrate system and 23 mg total measured PFAS post-TOP assay from the water system. Results for total mass of PFAS on each part indicate most of the residuals were present on parts which have large surfaces areas or the rubber or brass parts. For large surface area plastic parts (i.e., foam and water tanks), the overall mass on these parts was greater than other parts even though the PFAS residual concentrations were lower compared to other material types due to larger surface areas for accumulation. Parts constructed of rubber or brass appeared to have higher measured PFAS surface residual concentrations as compared to parts constructed of plastic or stainless steel.

Classification of real and bogus transients using active learning and semi-supervised learning

The mounting data stream of large time-domain surveys renders the visual inspections of a huge set of transient candidates impractical. Techniques based on deep learning-based are popular solutions for minimizing human intervention in the time domain community. The classification of real and bogus transients is a fundamental component in real-time data processing systems and is critical to enabling rapid follow-up observations. Most existing methods (supervised learning) require sufficiently large training samples with corresponding labels, which involve costly human labeling and are challenging in the early stages of a time-domain survey. One method that can make use of training samples with access to only a limited amount of labels is highly desirable for future large time-domain surveys. These include the forthcoming 2.5-meter Wide-Field Survey Telescope (WFST) six-year survey and the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Deep-learning-based methods have been favored in astrophysics owing to their adaptability and remarkable performance. They have been applied to the task of the classification of real and bogus transients. Unlike most existing approaches, which necessitate massive and expensive annotated data, we aim to leverage training samples with only 1000 labels and discover real sources that vary in brightness over time in the early stages of the WFST six-year survey. We present a novel deep learning method that combines active learning and semi-supervised learning to construct a competitive real-bogus classifier. Our method incorporates an active learning stage, where we actively select the most informative or uncertain samples for annotation. This stage aims to achieve higher model performance by leveraging fewer labeled samples, thus reducing annotation costs and improving the overall learning process efficiency. Furthermore, our approach involves a semi-supervised learning stage that exploits the unlabeled data to enhance the model's performance and achieve superior results, compared to using only the limited labeled data. Our proposed methodology capitalizes on the potential of active learning and semi-supervised learning. To demonstrate the efficacy of our approach, we constructed three newly compiled datasets from the Zwicky Transient Facility (ZTF), achieving average accuracies of 98.8<!PCT!>, 98.8<!PCT!>, and 98.6<!PCT!> across these three datasets. It is important to note that our newly compiled datasets only work in terms of testing our deep learning methodology and there may be a potential bias between our datasets and the complete data stream. Therefore, the observed performance on these datasets cannot be assumed to directly translate to the general alert stream for general transient detection in actual scenarios. The algorithm will be integrated into the WFST pipeline, enabling an efficient and effective classification of transients in the early period of a time-domain survey.

A STAND-ALONE HYBRID POWER SYSTEM BASED ON PV ENERGY AND HYDROGEN FUEL CELLS WITH ENERGY STORAGE SYSTEMS

This article is focused on the construction of a stand-alone residential 5-kW hybrid power system to feed different domestic loads at a typical house in Thi-Qar City, Iraq, including lighting loads, Table fan, Smartphone charger, TV, Microwave and Cooler. The stand-alone residential 5-kW hybrid power system consists of PV generator, PEMFC, storage batteries, Electrolyzer and hydrogen tank. The battery and hydrogen subsystem, composed of a fuel cell (FC), electrolyzer, and hydrogen storage tank, act as energy storage and support systems. The research in steps includes the design of the hybrid system. A program has been used in MATLAB to size system components in order to match the load of the site in the most cost-effective way. Evaluation of the economic feasibility of the same hybrid system when using a solar tracking system for photovoltaic cells. The simulation results demonstrate the hybrid system's ability to supply the required electrical energy to the loads, as well as the increase in hydrogen production when using the solar tracking system, which makes it possible to store excess hydrogen in the long term for later use when the photovoltaic energy decreases according to the seasons of the year.

Inferentialist Resource Semantics

In systems modelling, a 'system' typically comprises located resources relative to which processes execute. One important use of logic in informatics is in modelling such systems for the purpose of reasoning (perhaps automated) about their behaviour and properties. To this end, one requires an interpretation of logical formulae in terms of the resources and states of the system; such an interpretation is called a 'resource semantics' of the logic. This paper shows how inferentialism -- the view that meaning is given in terms of inferential behaviour -- enables a versatile and expressive framework for resource semantics. Specifically, how inferentialism seamlessly incorporates the assertion-based approach of the logic of Bunched Implications, foundational in program verification (e.g., as the basis of Separation Logic), and the renowned number-of-uses reading of Linear Logic. This integration enables reasoning about shared and separated resources in intuitive and familiar ways, as well as about the composition and interfacing of system components.

A Multi-Phase Brushless Direct Current Motor Design and Its Implementation in Medium-Altitude Long-Endurance Unmanned Aerial Vehicles

Nowadays, electric propulsion system implementation in vehicles is popular, and many studies and prototypes have been accomplished in this field. Aircraft are important members of the vehicle family, and Unmanned Aerial Vehicles (UAVs) are part of this family as well. Some UAVs still have conventional propulsion systems, which are less efficient and are harmful to the environment. In addition, conventional systems are vulnerable to faults in their propulsion system components. To overcome these problems, we designed a multi-phase Brushless Direct Current (BLDC) motor, to achieve fault-tolerant operation. Our designed BLDC motor was implemented in a UAV model that was created on MATLAB Simulink, based on a currently used UAV. Our design and performance analysis are shown for the BLDC motor, both standalone and as implemented in the created UAV model. The electric propulsion system performance is shown, according to the determined flight profile. We observed that the designed electric machine is capable of producing the required torque to create thrust for lifting the UAV. There are some advantages and disadvantages to using the designed electric machine in this class of UAV. This is shown in the related sections.

CHLORINE RESIDUALS IN WASTEWATER TREATMENT: IMPLICATIONS FOR PATHOGEN INACTIVATION AND ENVIRONMENTAL IMPACT

Chlorine residuals are a critical component of wastewater treatment systems. Inactivation of pathogens is a crucial goal to protect public health and stop the spread of waterborne illnesses. The purpose of this study is to find out more about the use of chlorination to dominate all pathogenic bacteria in a safe environment. The method used in this paper is an approach to literature review, which is carried out by publishing articles, including browsing the internet, Google Scholar, and related journals. The study highlights the importance of understanding the relationship between the chlorine doses given and the resulting concentration of the residuals. In addition, the study emphasizes the potential consequences of an ecosystem, such as excessive algae growth and the contribution of methane gas production to greenhouse effects. Our findings focus on the need for a comprehensive approach to managing chlorine residuals, considering aspects of health in humans, effective inactivation that is pathogenic, and preserving the environment for long-term sustainability.

RECEIVING AND ADSORPTION CHARACTERISTICS OF BIOCARBON MATERIALS FROM HOUSEHOLD WASTE

The aim of this research is the development of new carbon materials based on agricultural waste and a detailed study of their physicochemical properties, which allows to evaluate the potential directions of use of these materials in industry and environmental technologies. Within the framework of the work, four types of waste were chosen, in particular, wood sawdust, apple cake, as well as wheat and corn husks, which are widely available and rarely used as raw materials for creating adsorbents. The selected materials were subjected to the process of pyrolysis at a temperature of 500°C for one hour, which effectively preserves the porous structure of the material and improves its adsorption properties. The obtained samples of biocarbon materials were analyzed using nitrogen porosimetry, which made it possible to determine their adsorption potential, porosity, and total surface area. The results of the study showed a significant difference in the adsorption capacity of the samples, depending on the type of raw material. The sample based on corn husk demonstrated the highest adsorption activity, which indicates its potential for water purification from various types of pollution, including organic and inorganic compounds, heavy metals and other toxic substances. In addition, an additional analysis of the samples was carried out in order to assess their potential in other industries. In particular, the revealed porosity and surface area of ​​the materials allow us to consider them as promising components for filtration systems, catalysts in chemical reactions, materials for energy storage, as well as means for environmental protection and environmental restoration. The results of the study confirm that the use of agricultural waste for the creation of functional carbon materials is not only economically beneficial, but also an ecologically appropriate approach, which contributes to reducing the amount of waste and creating new opportunities for sustainable development.

Reinforcement Learning for Intra- & Inter-Node Recommender Data Pipeline Optimization

Deep learning-based recommender models (DLRMs) have become an essential component of many modern recommender systems. Several companies are now building large compute clusters reserved for DLRM training, driving new interest in cost- & time- saving optimizations. The systems challenges faced in this setting are unique; while typical deep learning (DL) training jobs are dominated by model execution times, the most important factor in DLRM training performance is often online data ingestion. In this paper, we study real-world DLRM data processing pipelines taken from our compute cluster at Netflix to observe the performance impacts of online ingestion and identify shortfalls in existing data pipeline optimizers. Our studies lead us to design a new solution for data pipeline optimization, InTuneX . InTuneX is designed for production-scale multi-node recommender data pipelines. It unifies & tackles the challenges of both intra- and inter- node pipeline optimization. We achieve this with a multi-agent reinforcement learning (RL) design, simultaneously optimizing node assignments at the cluster level & CPU assignments within nodes. Our experiments show that InTuneX can build optimized data pipeline configurations within minutes. We apply InTuneX to our cluster, and find that it increases single-node data ingestion throughput by as much as 2.29X versus state-of-the-art optimizers, while improving the cost-efficiency of multi-node pipelines by 15-25%.

CD8+ T cell exhaustion in the tumor microenvironment of breast cancer

CD8+ T cells are crucial cytotoxic components of the tumor immune system. In chronic inflammation, they become low-responsive, a state known as T cell exhaustion (TEX). The aim of immune checkpoint blockade is to counteract TEX, yet its dynamics in breast cancer remain poorly understood. This review defines CD8+ TEX and outlines its features and underlying mechanisms. It also discusses the primary mechanisms of CD8+ TEX in breast cancer, covering inhibitory receptors, immunosuppressive cells, cytokines, transcriptomic and epigenetic alterations, metabolic reprogramming, and exosome pathways, offering insights into potential immunotherapy strategies for breast cancer.

1-Bit Reconfigurable Transmitarray Antenna with Out-of-Band RCS Reduction

Stealth reconfigurable transmitarray antennas (RTAs) are essential components in wireless communication and radar detection systems. Therefore, in this study, we propose a 1-bit RTA with out-of-band radar cross-section (RCS) reduction. The antenna consists of an absorptive frequency selective transmission (AFST) layer and RTA layer separated by air. Specifically, the AFST layer achieves out-of-band RCS reduction and in-band transmission utilizing the first three resonant modes of a bent metallic strip with a centrally loaded resistor. Meanwhile, the RTA layer adopts a receiver–transmitter structure with an active receiving dipole and a passive orthogonal transmitting dipole. 1-bit phase shift is achieved by alternating two pin diodes integrated on the active dipole to reverse its current direction. To evaluate the proposed design, a 16 × 16-element prototype was designed, fabricated, and measured. For scattering, the bandwidth of 10 dB RCS reduction was about 52.5% and 43.8%, respectively. For radiation, the measured gain was 20.1 dBi at 7.5 GHz, corresponding to an aperture efficiency of 12.7%. The gain loss of beam scans to ±60° was about 5 dB in both two principal planes.

Spatiotemporal changes in the congestion index of streets and roads in the armed conflict conditions

This article examines the impact of war on the formation of urban transport flows. During armed conflicts, the transport infrastructure of cities undergoes significant changes, which greatly affects the mobility and safety of the population. The need to study this issue is particularly relevant in the context of the ongoing Russian-Ukrainian war, which has caused the largest migration in Europe since World War II. The paper explores the dynamics of these changes and ways to adapt urban transportation systems to war conditions. The study aims to determine the parameters of urban transport zones with specific disruptions in network link congestion indices during different phases of the full-scale invasion of Ukraine by the Russian Federation. The research methodology is based on analyzing statistical data on population movements, applying traffic flow models, and conducting a systematic analysis of the interaction between various components of urban transport systems. The goal of this study is to establish the relationships between the areas of cities where disruptions in congestion indices were observed during the initial phase of the invasion. The cities studied are Lviv and Kyiv, whose road networks are also described in the article. Polynomial regression models with two independent variables (the congestion index and the number of days from the beginning of each phase) were developed for three predefined time phases, each with distinct features of the armed conflict. The dependent variable is the area of the city experiencing disruptions in the congestion index relative to normal traffic flow conditions. The study concludes that the relationship between changes in the congestion index and the area of the city experiencing deviations is directly proportional. The absolute values of the indicators studied are lower for Lviv’s network than for Kyiv’s.

Energy-Efficient Three-Wheel Bleedless Electrical Environmental Control System for a Passenger Aircraft

Abstract The environmental control system (ECS) of an aircraft is designed to create a comfortable and suitable atmosphere for both passengers and crew, as well as the avionics. Additionally, the ECS represents the highest power consumers within nonpropulsive systems in an aircraft. With sustainable technology development for aircraft, secondary systems such as the ECS are evolving from conventional bleed air to electric-type to improve energy efficiency by reducing fuel consumption. This study introduces a novel electrically driven ECS (EECS) that is designed to replace the existing bleed-air-driven three-wheel air cycle system (ACS) and the high-pressure water separation subsystem (HPWS) of the Airbus 320 (A320) passenger aircraft's ECS during cruise conditions. matlab was used to construct the system component model of the ECS to verify the accuracy of the data from A320. The performance of the proposed EECS was compared with that of the existing bleed-air system in terms of cabin requirements. The conventional ECS's bleed-air off-take from the engine caused a 50% higher fuel mass penalty for missions lasting 5–15 h, which exceeds the shaft power off-take of the EECS. The energy required for the conventional ECS and EECSs was 3.59 MJ and 1.78 MJ, respectively.

Activation of cannabinoid receptor 2 by turmeric oleoresin reduces inflammation and oxidative stress in an osteoarthritis in vitro model

IntroductionOsteoarthritis (OA) is a chronic degenerative joint disease characterized by the progressive degradation of articular cartilage, resulting in pain and reduced mobility. Turmeric (Curcuma longa L.) has been widely recognized for its anti-inflammatory and antioxidant properties, but the molecular mechanisms underlying its therapeutic effects remain inadequately explored. This study investigates the potential of turmeric oleoresin (TUR) to activate Cannabinoid Receptor 2 (CBR2) and its role in mediating anti-inflammatory and antioxidant effects in an in vitro OA model.Material and methodsMolecular docking and cAMP quantification assays were used to evaluate TUR’s agonistic activity on CBR2. Human chondrosarcoma cells (SW-1353) were treated with TUR under oxidative stress induced by menadione or inflammatory conditions simulated with IL-1β and TNF-α. The effects of TUR were assessed in the presence and absence of the CBR2 antagonist SR144528. Outcomes included changes in reactive oxygen species (ROS) production, inflammatory marker expression, oxidative defense markers and endocannabinoid system components and receptors.ResultsTUR was confirmed as a CBR2 agonist and significantly reduced ROS production, downregulated pro-inflammatory cytokines (IL-6, COX-2, metalloproteases), and suppressed signaling pathways such as NFKB1, ERK 1/2, and c-Myc. These effects were reversed upon CBR2 inhibition. TUR also enhanced HMOX-1 expression and modulated endocannabinoid-related enzymes, highlighting its impact on oxidative stress and the endocannabinoid system.DiscussionThese findings suggest that CBR2 activation is central to TUR’s anti-inflammatory and antioxidant effects. By modulating key pathways and endocannabinoid system components, TUR demonstrates potential as a novel therapeutic agent for OA management. Future studies could explore its clinical applications and further validate its molecular mechanisms in vivo.

Guide to microfluidic systems and the preparation of emulsions

AbstractMicrofluidic technology, as an effective method for precise manipulation of microfluid volumes, has demonstrated significant potential in the preparation of emulsions. This guideline introduces key components of a microfluidic operating system, including the design of microfluidic chips (such as T‐junction, flow‐focusing, and co‐flowing structures), fluid driving systems, control systems, and observation and detection systems, explaining how they collaborate to accurately control the droplet generation process. In terms of specific steps for emulsion preparation, the guideline details the workflow utilizing microfluidic technology to fabricate both single‐layer O/W and W/O emulsions, as well as complex multi‐layer emulsions, emphasizing critical considerations during experimentation. Through in‐depth understanding and judicious application of microfluidic technology, there is a promise to advance emulsion preparation techniques across various domains, including drug delivery, food technology, biotechnology, and materials science.

Natural killer cells as promising candidates in Cancer therapeutics and related immune resistance in tumor microenvironment

Natural killer (NK) cells, as critical components of the innate immune system, have emerged as promising candidates in cancer therapy due to their ability to recognize and destroy tumor cells without prior sensitization. Their mechanisms of action, including perforin-granzyme release and antibody-dependent cellular cytotoxicity (ADCC), position them as versatile agents in cancer immunotherapy. Recent advancements, such as chimeric antigen receptor (CAR)-NK cells and cytokine-based stimulation, have demonstrated enhanced efficacy and reduced side effects compared to conventional immunotherapies. However, the immunosuppressive tumor microenvironment (TME) remains a significant obstacle, imposing challenges like immune checkpoint activation, cytokine suppression, and metabolic constraints that impair NK cell activity. This paper explores the therapeutic potential of NK cells, the challenges of immune resistance in the TME, and emerging strategies to enhance NK cell efficacy. Addressing these challenges is crucial for optimizing NK cell-based treatments and achieving durable responses in cancer patients.

A Model of Design and Implementation Micro-credentials in TVET: A Promising and Flexible Pathway to Employment and Skill Development

The article explores the increasing importance of micro-credentials in Vocational Education and Training (VET) as an innovative response to the rapidly changing demands of the job market. Micro-credentials are defined as short, focused educational programs that provide learners with specific skills or competencies. Unlike traditional qualifications, which often require extensive time and cover a broad range of topics, micro-credentials offer a more streamlined pathways approach to education, addressing targeted skills directly relevant to industry needs. The article emphasizes the benefits of micro-credentials, which include improved employability, personalized learning experiences, cost-effectiveness, and enhanced support for lifelong learning. These benefits make micro-credentials particularly attractive in industries where specialized skills are highly valued. The growing recognition of micro-credentials among employers underscores their increasing relevance as a means to bridge the gap between education and workforce requirements. The methodology presented in the article is grounded in secondary data analysis. This approach serves as a foundation for the development of a unique, personalized model designed by the author. The model specifically addresses the integration of micro-credentials into TVET, with a focus on technical programs. The model aims to align TVET offerings with labor market demands, taking into account the skills gaps and trends identified through data analysis. By employing existing research and insights, the author has crafted a framework that emphasizes practicality and relevance in meeting workforce needs. The findings highlight the transformative potential of micro-credentials in fostering skill acquisition and professional development. These programs are shown to provide a flexible and targeted learning approach, effectively addressing the specific competencies required by modern industries. The author’s model demonstrates how micro-credentials can be seamlessly integrated into TVET programs, offering tailored solutions for addressing workforce challenges. The increasing acceptance of micro-credentials by employers further validates their relevance as an essential component of modern education systems. In conclusion, the article advocates for the integration of micro-credentials into TVET systems as a strategic approach to enhancing workforce readiness and adaptability. By offering a practical, cost-effective, and flexible pathway to skills development, micro-credentials bridge the gap between education and employment. The proposed model provides a robust framework for incorporating micro-credentials into technical programs, ensuring alignment with industry requirements and fostering lifelong learning opportunities. This integration represents a vital step in addressing the dynamic needs of the labor market.

Radio-Frequency Electromagnetic Background Created by Mobile (Cellular) Communications

The technique of integral assessment of the radio frequency electromagnetic background (EMB) intensity created by wireless information services is presented, based on the forecast of the average electromagnetic loading on area created by radiations of spatially distributed base stations and mobile terminal devices. This loading can be determined both on the basis of a direct estimate of the average total irradiation power of the Earth’s surface by base stations or the average total radiation power of terminal devices per unit of its area, and on the basis of an estimate of the average area traffic capacity and known parameters of equipment and topology of mobile communication networks. Expressions to estimate the conditional average levels of EMB generated by stationary and mobile components of mobile communication systems, and the results of calculations illustrating the processes of its generation by these systems in different frequency ranges with different average area traffic capacity and different sizes of service areas of base stations are given. These calculations confirm the real danger of an unacceptable decrease in the level of electromagnetic safety of the population and deterioration of the ecology of the habitat without the implementation of scientifically based restrictions on the characteristics of mobile communication systems and services.