Radar Chart Research Articles

Investment Analysis of New Fire Truck: A Case Study of Purchase or Rent Option

PKT, as a petrochemical company with high potential hazards, prioritizes emergency preparedness and response by complying with regulations and standards. In addition to serving its own needs, PKT’s fire and rescue department also provides emergency services to four neighboring companies through an annual fee cooperation scheme. To enhance the emergency response services, PKT conducted an evaluation and identified the need for an additional fire truck unit with up-to-date technology. To determine the most suitable option, PKT is considering purchasing or renting the new fire truck units. A financial modeling analysis was conducted using income from health and safety services. The financial feasibility analysis, considering parameters such as NPV, IRR, and discounted payback period, resulted in a feasible outcome. The Purchase option exhibited better economic value, with a predicted NPV of Rp. 569,276,495, an IRR of 11.56% (higher than the discount rate of 10.5%), and a discounted payback period of 9.35 years. Sensitivity analysis, using tornado and spider charts, revealed that the annual fee from clients or joint venture companies had the most significant impact on the project’s financial performance, followed by manpower costs. A 20% increase in annual fees led to a significant increase in NPV Rp. 6,639,013,466, while a 20% decrease resulted in a significant decrease in NPV (−Rp. 5,500,460,477). Similarly, a 20% increase in manpower costs resulted in a decreased NPV of Rp. −3,500,609,667. Based on the sensitivity analysis, the two significant factors influencing the purchase option were identified as the annual fee and manpower cost. Recommendations that are also put forward for this study are identification to anticipate increases in labor costs and to keep manpower costs under control. The increase in manpower costs must be accompanied by an increase in income. Exploring opportunities to attract additional clients, particularly companies in the industrial complex that do not yet have an agreement with PKT, is also advised. By implementing these recommendations and ensuring cost control, PKT can optimize its emergency response services and maintain a financially viable operation.

In Search of the Proper Dimensions of the Optimum In-Wheel Permanent Magnet Synchronous Motor Design

In this paper, a new approach to the optimized design of outer rotor Permanent Magnet Synchronous Motors (PMSMs) for in-wheel light electric vehicle (LEV) applications is presented. The optimized design study is based on various dimensions such as back iron depth, permanent magnet depth and air gap length. The novel method is developed to reveal the quality factor of design (QFD), which implies the maximum possible performance results, and determine the best possible design for in-wheel PMSMs for direct-drive LEV applications. Therefore, the thickness of the back iron, permanent magnet and air gap dimensions are altered accordingly to obtain an optimized design. This design study is conducted for an in-wheel PMSM that has rated values of 2.5 kW, 150 V, 900 min−1, and 24-slot/20-pole configuration intended for LEV propulsion. These designs are simulated in order to obtain the maximized combination of efficiency, shaft power, shaft torque and a minimized combination of total weight, iron losses, copper losses, input current and cogging torque. The measure of the optimized parameters is named QFD, which indicates the goodness of the design through the use of radar charts. The values of the essential coefficients of QFD may vary for different applications, e.g., the design of PMSMs used in traction applications has some certain criteria that imply high-performance operation. Additionally, the QFD can guide motor manufacturers as a starting point for a design study.

АНАЛІЗ ТА ОЦІНЮВАННЯ ТРАНСФОРМАЦІЇ ВЛАСТИВОСТЕЙ ІНТЕЛЕКТУАЛЬНОГО КАПІТАЛУ УКРАЇНИ

The research is dedicated to the analysis and evaluation of the transformation of intellectual capital (IC) properties in the pre-war period of the country. The study enhances and categorizes contemporary indicators for assessing intellectual capital properties, classifies indicators based on their qualitative impact on the level of intellectual capital, normalizes indicators for constructing radar charts, and determines the level of intellectual capital in Ukraine. The research identifies the impact level of the dynamics of intellectual capital properties on the country's GDP changes. Methodology: To achieve the set goal, the study employs the dialectical method, analysis, and synthesis (investigation of human, organizational, and structural (client) capitals and changes in their properties), graphical method (for illustrating research results); system-structural and expert analysis (to determine the impacts of changes in intellectual capital properties on GDP). Scientific novelty lies in determining the influence of transformations in intellectual capital properties on GDP changes to define a strategy for optimizing the country's intellectual capital structure. Practical significance involves recommending indicators for assessing IC properties for further development of incentive measures using digital technologies and artificial intelligence to enhance the structure of intellectual capital, providing grounds for developing a strategy for IC optimization in the country. Keywords: intellectual capital, digitization, structural capital, consumer capital, human capital, assessment, transformations, properties.

Assessing climate/air quality synergies and cost-effectiveness for Beijing transportation: Insights into sustainable development

CO2 emission reduction policies can simultaneously reduce air pollutant emissions in the transport sector, but the extent of their cost-effective is under-evaluated. To explore sustainable transportation in a mega-city, the potential synergies and cost-effectiveness of CO2 and air pollutant emission reductions in Beijing transportation are quantitatively evaluated by radar chart analysis, total cost of ownership (TCO) and marginal abatement cost curves (MACC) under various mitigation measures. The findings show that the adoption of electric light-duty vehicles can achieve a significant synergistic effect and cost-effectiveness of emission reductions, and would be implemented as a high priority. Moreover, improving emission standards and fuel economy have an obvious cost-effectiveness and effective mitigation for air pollutants, but with poor synergies due to low CO2 mitigation. In contrast, the clean energy for large and heavy vehicles, and bio-fuel for aviation are essential measures for achieving carbon neutrality, but with high costs. Furthermore, changes of transport modes have good cost-effectiveness, but there are no synergies due to the emission increments of PM2.5 and NOx. Given that transportation plays a crucial role in achieving carbon neutrality and enhancing air quality, more stringent and effective environmental policies targeting emission reduction can expedite the sustainable transition in Beijing transportation.

Research on quantitative evaluation of revise requirements of Specifications of Air Sampling for Hazardous Substances Monitoring in the Workplace (GBZ 159-2004)

Objective: To conduct quantitative evaluation on the revise requirements of Specifications of Air Sampling for Hazardous Substances Monitoring in the Workplace (GBZ 159-2004) , clarify the problems and suggestions during its implementation for improvement, and provide a basis for the revision of the standard. Methods: From April to September 2021, stratified convenient sampling method was adopted and semi-open questionnaire was used to investigate the occupational health personnel in CDC, occupational prevention and control institutes, employers, third-party technical service institutions and universitie. The entropy weight of each index and the score based on entropy weight of GBZ 159 were calculated. Spearman rank correlation analysis was used to describe the correlation between the two indexes and radar chart was drawn for comprehensive evaluation. Results: A total of 151 questionnaires were received from the respondents, of which 147 were valid, with an effective recovery rate of 97.35%, involving 29 provinces, autonomous regions and municipalities. The median G scores of the necessity and urgency of GBZ 159 revision based on entropy weight were 2.84 and 3.17, respectively, and the difference was statistically significant (M=-25.50, P<0.001) . The trend of the score G of necessity and urgency based on entropy weight was basically the same for all secondary items (r(s)=0.9998, P<0.001) , and the score G of urgency based on entropy weight was higher than that of necessity. The highest score G of necessity and urgency based on entropy weight was "3.13 long time sampling", which were 7.56 and 8.23 respectively. This was followed by "3.12 short time sampling", which were 7.19 and 7.13 respectively. Conclusion: GBZ 159 has encountered some new problems and challenges in the implementation process, and some of its technical indicators have been out of line with the actual practice of occupational health at present. These are the two items that urgently needs to be revised and improved, such as "3.13 long time sampling" and "3.12 short time sampling" and other items need to be revised and improved.

Who am I? – Exploring secondary education school leaders’ professional identity

This study explored school leaders’ professional identity by examining the guiding standards school leaders pursue in their jobs and the professional roles they identify themselves with. Using professional roles in school leadership that were formulated in (inter)national frameworks, 36 Dutch school leaders in secondary education provided their identity standards and their professional role identification. Standards were grouped per topic for each professional role. Role identification was visualized and grouped using radar charts. Results showed that in general ‘interactions and interpersonal contact’ formed significant aspects of these school leaders’ professional identities. Identity standards covered all professional roles and were mostly formulated in terms of contact and interaction. School leaders sometimes identified themselves primarily with a specific social or analytical role. Some school leaders identified themselves with multiple professional roles. Additionally, a new role, focusing on performing practical ‘hands on’ tasks, emerged. The identity standards as well as the identification patterns can be used in helping school leaders to gain more insight into their personal leadership preferences and their motivation for certain dimensions in their work and how these relate to specific demands and expectations in the work context.

A comprehensive evaluation of asphalt concrete modified with ACP based on improved AHP and radar chart method

Microwave heating, as an efficient and environmentally friendly heating technology, is used in solving rapid deicing issues of asphalt pavement. In this study, activated carbon powder (ACP) was adopted to partly replace mineral powder and improve the microwave heating efficiency of asphalt concrete. Some tests of key indexes about deicing, microwave heating, asphalt concrete and asphalt mastic were conducted in laboratory. In order to comprehensively compare and analyze the performance of asphalt concrete at different replacements and recommend the best type of asphalt concrete with laboratory data, an advanced data processing and mathematical model was established based on improved Analytic Hierarchy Process (AHP) and radar chart method. The results show that the fi representing the comprehensive performance of each type of asphalt concrete can be ranked as f6&amp;gt;f5&amp;gt;f4&amp;gt;f3&amp;gt;f2&amp;gt;f1. Therefore, it can be easily recommended that the type of asphalt concrete that meets the expected requirements is that with 100% ACP replacement amount. Additionally, the established model has proved feasible and effective through the application of this research. Finally, this research’s process and results can provide a new idea and reference for resolution of similar problems in the future.

Using data clustering to reveal trainees’ behavior in cybersecurity education

AbstractIn cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students’ cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the designers in performing such analytic and evaluation tasks is ad-hoc and insufficient. With unsupervised machine learning methods, we designed a tool for clustering the trainee actions that can exhibit their strategies or help pinpoint flaws in the training design. By using a k-means++ algorithm, we explore clusters of trainees that unveil their specific behavior within the training sessions. The final visualization tool consists of views with scatter plots and radar charts. The former provides a two-dimensional correlation of selected trainee actions and displays their clusters. In contrast, the radar chart displays distinct clusters of trainees based on their more specific strategies or approaches when solving tasks. Through iterative training redesign, the tool can help designers identify improper training parameters and improve the quality of the courses accordingly. To evaluate the tool, we performed a qualitative evaluation of its outcomes with cybersecurity experts. The results confirm the usability of the selected methods in discovering significant trainee behavior. Our insights and recommendations can be beneficial for the design of tools for educators, even beyond cyber security.

Assessment of quality of life in follow-up patients with COVID-19 pneumonia: A prospective, observational study from a tertiary care center.

This study intended to assess the quality of life (QOL) with telephonic interview using the Short Form 12 (SF-12) Scale in follow-up patients admitted to the intensive care unit (ICU) with COVID-19 pneumonia. This prospective, noninterventional follow-up study was conducted at a tertiary care center. COVID-19 pneumonia patients discharged from ICU were recruited for telephonic interviews. Interviews were performed using SF-12 Scale to assess QOL 6 months after discharge. The SF-12 survey measures general health status in eight domains. A radar chart was used for the interpretation of health component scores. One hundred and fifty patients could complete the telephonic interview. The first-stage depression risk was 50%, which was 30% more than general position incidence (20%). As compared to the general population, physical component summary (PCS-12) was 60% below and mental component summary (MCS-12) was 67% below the general norm. Role emotional was the most affected followed by role physical. QOL in follow-up ICU patients with COVID-19 pneumonia was worse in terms of physical and mental scores. By employing a comprehensive, longitudinal assessment of QOL in follow-up patients, using validated SF-12 Scale, this study captures a multifaceted view of their health status postrecovery.

The Early Cenozoic Volcanism of the Northern Okhotsk Region System of Grabens and Faults

Abstract —We studied geochemical compositions of the early Paleocene basaltic and andesite dikes associated to linear zones of the Lankovo–Omolon shearing system (Northern Okhotsk region) and basalts of the Evdyreveem volcanic field associated to the Okhotsk–Penzhinsk fault system, and compared them to other synchronous manifestations of basic volcanism: andesibasalts and andesites of the studied earlier Garmanda field, as well as with the Late Cretaceous basalts of the Mygdykit Formation of the Northern Okhotsk region, roofing the Okhotsk–Chukotka volcanic belt. The isotopic composition of Sr and Nd in dikes, the distribution of major and trace elements with the ratios of noncoherent elements indicate the formation of volcanic bodies in the environment of continental margin rifting, which is confirmed by the combination of depleted, intraplate and above subduction geochemical features of their composition. Such behavior of the elements indicates multi-stage processes of the earlier Mesozoic supra-subduction fluid metasomatosis. Melting of an ancient buried Cretaceous slab may explain the appearance of such “above subduction” marks as the Nb–Ta negative anomalies in the studied basaltoids. Andesite dikes are characterized by higher isotope ratios of Nd and lower Sr, with lower absolute concentrations of trace elements and more pronounced anomalies on spider plots.

IBRtools: An R package for calculating integrated biomarker indexes.

Multibiomarker studies are useful to evaluate the early warning signs of environmental degradation, and their unified responses are often assessed through two common indexes, Integrated Biomarker Response (IBR) and Integrated Biological Responses version 2 (IBRv2). The R package IBRtools allows users to calculate both IBR and IBRv2 while simultaneously incorporating all the biomarkers under evaluation. The package includes functions for calculating the indexes IBR and IBRv2 and obtaining their standardized values, as well a function for radar chart creation and three example datasets. Here we describe the main algorithms involved in IBR and IBRv2 calculations, a description of the novel package and illustrate a workflow using data examples available on the package to guide the user on how to accurately acquire the values for either the IBR index or the IBRv2 index. The IBRtools package provides a user-friendly platform for R users to obtain IBR index and IBRv2 values, making it straightforward even for large datasets.

Unraveling the web of frailty: A novel approach to frailty using a CGA-derived spider plot.

Unraveling the web of frailty: A novel approach to frailty using a CGA-derived spider plot.

Tuberculosis: Interdisciplinary View and Representation Using Artificial Intelligence

Objective: Analyze the selection of concepts associated with Tuberculosis with an interdisciplinary approach by students from four Medical Sciences programs at a privately managed university in the city of Mar del Plata in 2023.&#x0D; Materials and Methods: Descriptive, longitudinal research. Sample of 198 students of Medicine Research methodology, Bachelor's Degree in Nutrition, Kinesiology and Physiatry and Speech Therapy.&#x0D; Results: The activity takes place in 4 phases, each lasting one week and is carried out asynchrony using documents shared online, monitored by the teaching team. In Phase 1, the Bulletin on Tuberculosis in Argentina is presented. All students are divided into 8 groups with members from the 4 majors. Each of them must propose three concepts associated with tuberculosis from their respective disciplines, which cannot be repeated with those selected by their classmates. In the second week, each person chooses one of the three concepts they selected the previous week and places it in a new grid in column A next to your name. In column B you must justify in 30 words why the concept you chose and placed in column A is associated with tuberculosis. In the third column you will indicate the concept of your group and what career the classmate who proposed it is from, pointing with the corresponding color. In the third week, they are presented with a diagram, called a spider web. (Minnaard,2019). In this case, the diagram presents 8 well-defined areas. Four of which correspond to each discipline indicated with preset colors: Speech Therapy, Medicine, Kinesiology, Nutrition. The concept of Tuberculosis is located centrally in the spider web located after the grid. An important aspect, the concepts that are considered most significant should be close to the center and the least significant ones further away. Exchanges between students from different majors must be recorded in this file indicating the name and surname of the person who proposes the concept or agrees with another participant, below the spider web diagram, for example, or if I decide to move it to the intermediate area. It is established that the minimum number of concepts to pass this activity is 20 and the maximum is 30. In the last week, students carefully observe in the spider web the concepts that were selected by students from two or more majors. They select two and create a prompt with them and the concept of tuberculosis using some Artificial Intelligence (AI) chat. The length should not exceed 20 words. Analyze the results of your classmates and together select the most relevant one. Based on this, they develop a research problem contemplating the aspects that are always considered. Place the result in the second box. That question is transformed into a statement and placed in the AI chat requesting to make an image inspired by the styles of famous abstract and cubist painters.&#x0D; Conclusions: The implementation of strategies that encourage creativity and reflective thinking has been and is a challenge for higher-level teachers.

Kinematic Analysis of Human Gait in Healthy Young Adults Using IMU Sensors: Exploring Relevant Machine Learning Features for Clinical Applications.

Gait is the manner or style of walking, involving motor control and coordination to adapt to the surrounding environment. Knowing the kinesthetic markers of normal gait is essential for the diagnosis of certain pathologies or the generation of intelligent ortho-prostheses for the treatment or prevention of gait disorders. The aim of the present study was to identify the key features of normal human gait using inertial unit (IMU) recordings in a walking test. Gait analysis was conducted on 32 healthy participants (age range 19-29 years) at speeds of 2 km/h and 4 km/h using a treadmill. Dynamic data were obtained using a microcontroller (Arduino Nano 33 BLE Sense Rev2) with IMU sensors (BMI270). The collected data were processed and analyzed using a custom script (MATLAB 2022b), including the labeling of the four relevant gait phases and events (Stance, Toe-Off, Swing, and Heel Strike), computation of statistical features (64 features), and application of machine learning techniques for classification (8 classifiers). Spider plot analysis revealed significant differences in the four events created by the most relevant statistical features. Among the different classifiers tested, the Support Vector Machine (SVM) model using a Cubic kernel achieved an accuracy rate of 92.4% when differentiating between gait events using the computed statistical features. This study identifies the optimal features of acceleration and gyroscope data during normal gait. The findings suggest potential applications for injury prevention and performance optimization in individuals engaged in activities involving normal gait. The creation of spider plots is proposed to obtain a personalised fingerprint of each patient's gait fingerprint that could be used as a diagnostic tool. A deviation from a normal gait pattern can be used to identify human gait disorders. Moving forward, this information has potential for use in clinical applications in the diagnosis of gait-related disorders and developing novel orthoses and prosthetics to prevent falls and ankle sprains.

Designing a 3D gestural interface to support user interaction with time-oriented data as immersive 3D radar charts

The design of intuitive three-dimensional user interfaces is vital for interaction in virtual reality, allowing to effectively close the loop between a human user and the virtual environment. The utilization of 3D gestural input allows for useful hand interaction with virtual content by directly grasping visible objects, or through invisible gestural commands that are associated with corresponding features in the immersive 3D space. The design of such interfaces remains complex and challenging. In this article, we present a design approach for a three-dimensional user interface using 3D gestural input with the aim to facilitate user interaction within the context of Immersive Analytics. Based on a scenario of exploring time-oriented data in immersive virtual reality using 3D Radar Charts, we implemented a rich set of features that is closely aligned with relevant 3D interaction techniques, data analysis tasks, and aspects of hand posture comfort. We conducted an empirical evaluation (n=12)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(n=12)$$\\end{document}, featuring a series of representative tasks to evaluate the developed user interface design prototype. The results, based on questionnaires, observations, and interviews, indicate good usability and an engaging user experience. We are able to reflect on the implemented hand-based grasping and gestural command techniques, identifying aspects for improvement in regard to hand detection and precision as well as emphasizing a prototype’s ability to infer user intent for better prevention of unintentional gestures.

Comparison of ATR-FTIR and NIR spectroscopy for identification of microplastics in biosolids

Biosolids are considered a potentially major input of microplastics (MPs) to agricultural soils. Our study aims to identify the polymeric origin of MPs extracted from biosolid samples by comparing their Attenuated Total Reflection (ATR) - Fourier-transform infrared (FTIR) spectra with the corresponding near-infrared (NIR) spectra. The reflectance spectra were preprocessed by Savitzky-Golay (SG), first derivative (FD) and compared with analogous spectra acquired on a set of fifty-two selected commercial plastic (SCP) materials collected from readily available products. According to the results portrayed in radar chart and built from both ATR-FTIR and NIR spectral datasets, the MPs showed high correlations with polymers such as polyethylene (LDPE, HDPE), polyethylene terephthalate (PET), polystyrene (PS), polypropylene (PP) and polyamide (PA), determined in SCP samples. Each unknown MP sample had on average three or more links to several types of SCP, according to the correlation coefficients for each polymer ranging from 0.7 up to 1. The comparison analysis classified the majority of MPs as composed mainly by LDPE/HDPE, according to the top correlation coefficients (r > 0.90). PP and PET were better identified with NIR than ATR-FTIR. In contrast to ATR-FTIR analysis, NIR was unable to identify PS. Based on these results, the primary sources of MPs in the biosolids could be identified as discarded consumer packaging (containers, bags, bottles) and fibers from laundry, disposable glove, and cleaning cloth. SynopsisMicroplastics (MPs) are considered contaminants of emerging concern. This study compares two simple and fast spectroscopy techniques to identify microplastics in the biosolid matrix.

Diagnosis and location of inter-turn short circuit fault in pumped storage unit

In order to monitor the inter-turn insulation health of the rotor windings of pumped storage unit (PSU) in real time, a fault diagnosis method based on magnetic field detection is proposed in this study. Firstly, the characteristic harmonics of the air-gap flux density (AGFD) corresponding to the different states are obtained by deriving the expressions for the AGFD in the normal and inter-turn short circuit (ITSC) states of the rotor winding. Secondly, the detection principle of Hall sensor and its application are studied, and an intelligent detection theory combining frequency-resolved spectrum (FRS) and radar chart is proposed. Thirdly, constructing a electromagnetic model based on the actual operating PSU size, then the time/frequency characteristics of the Hall induced electromotive force (HIEF) are analysed, from which the intelligent diagnostic spectrums are constructed for fault detection. Finally, the Hall probe detection sensitivity is calibrated to 1 mV/mT. By installing Hall probe on the slot wedge surface of the generator stator, HIEF signals for different ITSC levels are acquired and integrated with pole positioning signals for condition monitoring, which can effectively identify and locate ITSC fault, while the detection sensor has significant advantages in terms of size and installation simplicity.

The Shape of Relations to Come: Multidimensional Analyses of Complex Human Behavior

AbstractScience, understood to be the behavior of scientists, falls within the purview of behavior analysis. All scientists use scientific instruments to study a natural phenomenon, and for the behavior analyst, perhaps no tool is more important than the graph used to show changes in level, trend, and variability, and upon which behavior analysts make data-based decisions. Modern behaviorism as we know it dates back to the development of the cumulative recorder first developed in the 1930s. Though revolutionary to the science of behavior, two-dimensional graphs may be limited in application for analyzing complex human behavior. In the current article, we conceptualize verbal behavior as a multidimensional field of environmental relations, and introduce the use of multi-axial radar charts for its visual and quantitative analysis. From there, we survey the use of radar charts toward advancing a behavior-analytic understanding of human language and cognition. We demonstrate the use of radar charts for calculating simple shape descriptors as a quantitative measure of dynamic interactants, and show how they can be used to measure change over time.

Multi-objective optimization of regional integrated energy system matrix modeling considering exergy analysis and user satisfaction

Integrated energy system achieves the collaborative optimization of different energy forms such as electricity/gas/heat/cold, and it is an important strategic development direction in the international energy field in the future. However, with the development of smart grid technology and the increase of renewable energy penetration, it needs more flexible load to adapt to the changing energy supply–demand relationship. Considering the impact of user-side load fluctuations on the system, this paper establishes a two-tier closed-loop system model formed by users and the market. The upper-layer is based on the user’s perspective. A comprehensive user satisfaction model is established by the radar chart area method and consumer preference theory. The lower-layer is based on the market perspective. It proposes an improved layering matrix Energy Hub model and conducts the regional integrated energy system exergy efficiency evaluation study. Then, taking economy, carbon emission and exergy efficiency as objective functions, a multi-objective optimization model is constructed. Non-dominated Sorting Genetic Algorithms-II is applied to solve the model, and the output parameters is a Pareto front surface. A combination weighting TOPSIS method is used to select a compromise solution of multi-objective optimization from the optimal solution set. Compared with the primary energy utilization efficiency as the objective function, the exergy efficiency reduces the system cost by 8.64%. Finally, the multi-objective optimization solution based on different user satisfaction is obtained. Through the analysis of the examples, compared with the original load, the introduction of the upper-layer user satisfaction model reduces the system cost by 2.8%. The reasonable setting of user satisfaction and load adjustment amount can improve the economy of system, which verifies the effectiveness of the two-tier closed-loop system based on user satisfaction model.

Concentration-dependent effects of lithium on Daphnia magna: Life-history profiles and integrated biomarker response implementation

The growing use of lithium (Li) in industrial and energy applications and increasing demand worldwide has inevitably resulted in its wide dispersal, representing a significant threat to aquatic systems. Unfortunately, as a ubiquitous emerging contaminant, the comprehensive toxicological information regarding Li at multifarious levels is limited. To diminish this gap, this work was focused to explore Li-induced cascading effects on Daphnia magna as a key species in freshwater ecosystems. Specifically, the organisms were chronically exposed to gradient Li concentrations with emphasis on characterizing life-history traits from individual to population scale, primarily as observed by a markedly concentration-dependent decrease along exposure gradients. In parallel, a robust set of biomarkers relating to energy reserves, antioxidant and biotransformation enzymes, cellular damage, ionoregulation and neurotoxicity were assayed for further understanding potential underlying mechanisms. As a result, biomarker alterations were characterized by significant decreases in energy storage and enzymatic profiles of antioxidant and biotransformation systems, not only triggering an imbalance between reactive oxygen species (ROS) generation and elimination under Li exposure, but compromising the fecundity fitness of phenotypical costs. In contrast, malondialdehyde (MDA) levels were remarkably enhanced as a consequence of inefficient antioxidant and biotransformation capacity leading to lipid peroxidation (LPO). Additionally, Li exerted a dose-dependent biphasic effect on the activities of superoxide dismutase (SOD), Na+,K+-ATPase and acetylcholinesterase (AChE) by interfering with inherent balance. In terms of responsive patterns and dose-effect trends, the integrated biomarker response indices (IBRv2) and star plots were consistent with the differences in biomarker profiles, not only presenting comprehensively biological effects in a visualized form, but signaling the importance of progressive induced changes in an integrative way. Overall, these findings highlighted the need for elucidating Li-produced impacts from a comprehensive perspective, providing valuable insights into better understanding the toxicity of Li in relation to aquatic ecosystem functioning and ecological relevance.