Dynamic Assessment Research Articles

Diagnosing and promoting learners’ L2 inferential reading development through hybrid computerised dynamic assessment in the Chinese EFL classroom

Dynamic assessment (DA) addresses the limitations of standardised assessments by integrating the understanding and promotion of learners’ emerging abilities during the assessment process for a more comprehensive view of their language performances. However, the conventional interactionist and interventionist DA approaches each have their deficiencies, failing to fulfil both DA practicality and contextualisation in L2 classrooms. Also, there is a scarcity of DA research on exploring learner performances over time. This study aims to address these gaps by putting forward a hybrid computerised dynamic assessment (hybrid C-DA) model implemented as a 7-week pedagogical programme in diagnosing and promoting learners’ L2 inferential reading in the Chinese university EFL classroom. With a quasi-experimental design, two parallel classes of first-year undergraduates participated as the experimental group (n = 34) and the control group (n = 38). Data were collected from participants’ numerical scores in the online pre-test, post-test, intervention tests and transfer tests centring on TOEFL iBT readings. Statistical analysis revealed the effectiveness of hybrid C-DA in promoting learners’ L2 inferential reading abilities as the experimental group performed significantly better than the control group. Within the one-shot hybrid C-DA test, multi-dimensional diagnostic profiles were instantiated through learners’ differentiated responses to mediations and varying mediation levels across question types. Meanwhile, learners’ fluctuated performances across multiple hybrid C-DA tests reflected the non-linear nature of development if viewed dialectically. Overall, we argue that the refined hybrid C-DA model has the capacity to contribute to learners’ L2 development while uncovering fine-grained diagnostic information unobtainable in standardised tests, which significantly informs future L2 instructions.

Assessment of the oxygen dynamics in microalgae–bacteria systems through respirometry

Assessment of the oxygen dynamics in microalgae–bacteria systems through respirometry

Dynamic assessment and pathway optimization of agricultural modernization in China under the sustainability framework: An empirical study based on dynamic QCA analysis

Accelerating agricultural modernization is vital for achieving sustainable agricultural development and ensuring food security. This paper uses the comprehensive evaluation model to measure the level of agricultural modernization in 30 provinces of China from 2012 to 2022. It inspects analyzes the spatial-temporal characteristics and regional differences through the Moran Index and Dagum Gini coefficient. Lastly, based on the configuration perspective, the dynamic qualitative comparative analysis method (QCA) is used to clarify the multiple improvement paths of China's agricultural modernization. The results indicate the following. First, China's agricultural modernization level is not high but has the potential for rapid growth. Regarding spatial distribution, the eastern region has the highest agricultural modernization level, followed by the central region, while the western region has the lowest level, showing a “high-high-low-low” clustering characteristic. Second, the overall disparity in China's agricultural modernization level is fluctuating and declining, with regional differences being the primary source of the overall disparity. The largest difference is between the eastern and western regions. Within regions, the western region has the largest internal disparity, but this disparity is gradually decreasing, whereas the gap in agricultural modernization level within the eastern region is continuously expanding. Third, the paths to improve China's agricultural modernization consist of multiple antecedent conditions. From the configuration perspective, there are four paths to enhance China's agricultural modernization level. These include the dual-strategy approach of “technology and policy,” the comprehensive tri-strategy model of “technology, market, and policy,” the synergistic enhancement model combining “technology and market,” and the multi-faceted core-driven approach.

Analysis and assessment of urbanization dynamics: actors and forms of encroachment on the agricultural land of Constantine in eastern Algeria (1985-2020)

The environmental concern has increasingly become a focus in recent research on town planning and regional development. This paper discusses the renewed issue of urbanization affecting agricultural land and natural environments, with a new approach combining spatio-temporal monitoring of the evolution of the urban area of the province of Constantine, in relation to the agronomic quality of the land. In this context, the present study is based on the agronomic classification of land in the province of Constantine carried out by BNEDER study office in 1987. In addition, it uses maps extracted from Landsat satellite images for the years 1985, 2000, and 2020, and the annual land use data from the agriculture department (DSA), recorded between the years 2000 and 2020. The results obtained from this approach highlight the negative impact of urbanization over the last two decades in the Constantine agglomeration, as well as the strong vulnerability of natural environments and agricultural soil expected in the coming years. The accelerated pace of land artificialization has led to a significant reduction in agricultural space in the Constantine province. The urbanization of the city of Constantine alone consumed more land in 13 years (between 1987 and 2000) than it had in the twenty-seven years following independence, and more than it had consumed in a century before independence. In the event that public authorities do not take corrective and environmental protection actions, the situation regarding this problem will become more difficult to resolve.

Artificial intelligence techniques for dynamic security assessments - a survey

The increasing uptake of converter-interfaced generation (CIG) is changing power system dynamics, rendering them extremely dependent on fast and complex control systems. Regularly assessing the stability of these systems across a wide range of operating conditions is thus a critical task for ensuring secure operation. However, the simultaneous simulation of both fast and slow (electromechanical) phenomena, along with an increased number of critical operating conditions, pushes traditional dynamic security assessments (DSA) to their limits. While DSA has served its purpose well, it will not be tenable in future electricity systems with thousands of power electronic devices at different voltage levels on the grid. Therefore, reducing both human and computational efforts required for stability studies is more critical than ever. In response to these challenges, several advanced simulation techniques leveraging artificial intelligence (AI) have been proposed in recent years. AI techniques can handle the increased uncertainty and complexity of power systems by capturing the non-linear relationships between the system’s operational conditions and their stability without solving the set of algebraic-differential equations that model the system. Once these relationships are established, system stability can be promptly and accurately evaluated for a wide range of scenarios. While hundreds of research articles confirm that AI techniques are paving the way for fast stability assessments, many questions and issues must still be addressed, especially regarding the pertinence of studying specific types of stability with the existing AI-based methods and their application in real-world scenarios. In this context, this article presents a comprehensive review of AI-based techniques for stability assessments in power systems. Different AI technical implementations, such as learning algorithms and the generation and treatment of input data, are widely discussed and contextualized. Their practical applications, considering the type of stability, system under study, and type of applications, are also addressed. We review the ongoing research efforts and the AI-based techniques put forward thus far for DSA, contextualizing and interrelating them. We also discuss the advantages, limitations, challenges, and future trends of AI techniques for stability studies.

Real-Time Visibility Assessment in an Interactive Immersive Virtual Reality Application for Urban Public Space Design

Abstract. The design of urban public spaces (UPSs) aims to facilitate users’ physical and mental well-being by facilitating dynamic and stationary activities. The success of a UPS is often measured by its users’ engagement and experiences. However, UPSs frequently exhibit varying usage patterns, with some areas being heavily frequented and others neglected. This discrepancy is often due to users’ perceptions of safety, comfort, and liveliness. Failure to anticipate and address these aspects during the design phase of UPSs can result in dysfunctional urban spaces that fail to meet users’ needs. People experience UPSs primarily through their senses, with vision being the predominant sense and key to spatial cognition in UPSs. Therefore, adequate visibility of the spatial configuration must be integral to UPS design as a design goal. As a result of recent advances in Immersive Virtual Reality (IVR) end-users can participate in, interact and experience the possible UPS design scenarios, however, most IVR applications do not provide real-time feedback for design goals such as visibility. Established methods exist for analyzing visibility in UPS. However, these techniques are not usually integrated into VR apps to assess the effects of the designs. This paper addresses the gap for the lack of real-time visibility feedback within IVR applications for UPS design and its technical challenge. Building on a previous IVR application, CoHeSIVE, which was developed for UPS design, we integrated a ray-casting method and Unity’s built-in callbacks for dynamic visibility assessment of the features within the user’s field of view. The visibility assessment is then presented on a dashboard within the IVR app. This study serves as a cornerstone for future real-time feedback mechanisms of visibility assessment within IVR applications for urban design, facilitating informed design decisions.

Identifying Gifted Potential Through Positive Psychology Content

Traditional identification approaches have often excluded many students from underrepresented backgrounds from gifted and talented service programs. This study introduces an innovative identification method based on the Bull’s Eye Model for Affective Development—Expansion (BEM-e), which focuses on identifying giftedness and talents through targeted positive psychological traits. This method is integrated within an affective curriculum designed to create authentic learning environments that align with students’ interests and strengths, fostering deeper engagement, motivation, and self-efficacy. Grounded in the positive psychology theory, the curriculum includes engaging, activity-oriented modules with comprehensive dynamic assessments. These assessments allow teachers to identify a broad range of talents and abilities, promoting equity and a holistic identification process, which contributes to a more equitable and comprehensive education system.

Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 Emissions

The environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus regarding the EKC hypothesis among countries and regions of different income groups. This study revisits the EKC hypothesis by employing cross-correlation analysis to explore the income–CO2 emissions relationship across 158 countries and 44 regions from 1990 to 2020. The empirical method utilizes a dynamic cross-correlation coefficient (CCC) approach, allowing for the assessment of lead-lag dynamics between income and CO2 emissions over time. By categorizing nations into the World Bank’s income classifications, we found a heterogeneous EKC pattern highlighting distinct environmental–economic dynamics across different income groups. The findings indicate that high-income countries show a decoupling of economic growth from CO2 emissions; whereas, low-income countries still exhibit a positive correlation between both variables. This underscores the necessity for tailored policy interventions that promote carbon neutrality, while considering each country’s unique development stage. Our research contributes to the ongoing issue of sustainable economic development by providing empirical evidence of the different pathways nations follow in balancing growth with environmental preservation.

Dynamics assessment of free economic zones development in Russia in the system of the state investment strategy

Dynamics assessment of free economic zones development in Russia in the system of the state investment strategy

Renal medullary perfusion differs from that in renal cortex in patients with sepsis associated acute kidney injury and correlates with renal function prognosis: A prospective cohort study.

Renal perfusion status remains poorly studied at the bedside during sepsis associated acute kidney injury (AKI). The aim of the study is to examine renal cortical and medullary perfusion using renal contrast enhanced ultrasound (CEUS) in septic patients. In this single-center, prospective longitudinal study, septic patients were enrolled. Renal ultrasonography was performed within 24 hours of ICU admission (D1), then repeated at D3, D5 and D7. Each measurement consisted of three destruction replenishment sequences that were recorded for delayed analysis with dedicated software (Vuebox). Renal cortex and medulla perfusion were quantified by measuring time to peak (TTP). Receiver operating characteristic (ROC) analysis was used to evaluate 28-day renal prognosis. The study included 149 septic patients, including 70 non-AKI patients and 79 AKI patients. Both renal cortical and medullary TTP was longer in the AKI group than in the non-AKI group. The difference of TTP between renal cortex and medulla in AKI group was higher than that in the non-AKI group (p = 0.000). Medullary TTP on day 3 had the best performance in predicting the prognosis of 28-day renal function (AUC 0.673, 95% confidence interval 0.528-0.818, p = 0.024), and its cut-off value was 45 s with a sensitivity 52.2% and a specificity of 82.1%. Cortical TTP on day 3 also had the performance in predicting the prognosis of 28-day renal function (AUC 0.657, 95% confidence interval 0.514-0.800, p = 0.039), and its cut-off value was 33 s with a sensitivity 78.3% and a specificity of 55.0%. Renal medullary perfusion alterations differ from those in cortex, with the medulla is worse. Simultaneous and dynamic assessment of cortical and medullary microcirculatory flow alterations necessary. TTP on day 3, especially medullary TTP, seems to be a relatively stable and useful indicator, which correlates with 28-day renal function prognosis in septic patients. Early correction of renal cortical and medullary perfusion alterations reduces the incidence of adverse renal events.

Assessment of Carbon Stock and Sequestration Dynamics in Response to Land Use and Land Cover Changes in a Tropical Landscape

Quantitative analysis of LULC changes and their effects on carbon stock and sequestration is important for mitigating climate change. Therefore, this study examines carbon stock and sequestration in relation to LULC changes using the Land Change Modeler (LCM) and Ecosystem Services Modeler (ESM) in tropical dry deciduous forests of West Bengal, India. The LULC for 2006, 2014, and 2021 were classified using Google Earth Engine (GEE), while LULC changes and predictions were analyzed using LCM. Carbon stock and sequestration for present and future scenarios were estimated using ESM. The highest carbon was stored in forest land (124.167 Mg/ha), and storage outside the forest declined to 13.541 Mg/ha for agricultural land and 0–8.123 Mg/ha for other lands. Carbon stock and economic value decreased from 2006 to 2021, and are likely to decrease further in the future. Forest land is likely to contribute to 94% of future carbon loss in the study region, primarily due to its conversion into agricultural land. The implementation of multiple-species plantations, securing tenure rights, proper management practices, and the strengthening of forest-related policies can enhance carbon stock and sequestration. These spatial-temporal insights will aid in management strategies, and the methodology can be applied to broader contexts.

Scale for the assessment of mucosal wave dynamics of the free edges during stroboscopic examination: clinical validation study and analysis of results.

Identifying the mucosal wave (MW) is essential when studying the voice; however, its characterization and perceived measurement during laryngeal stroboscopy (LS) are not well defined or standardized because of the subjectivity of its interpretation. This article proposed and validated a scale that characterized and approximated MW measurement during LS, applied it to participants divided into a healthy group and groups with free edge conditions, and identified differences between them. This is a descriptive and clinical validation study of the "VASQ (Vertical axis, Anteroposterior axis, Symmetry and Quantity) mucosal wave score" scale based on stroboscopy images of 137 adult men and women divided into a control group and functional and organic pathology groups. The images were analyzed by three evaluators according to an established protocol. Measurements dictating the reproducibility and validity criteria as well as the MW score in each group were obtained. The reliability of the scale was α = 0.90, internal consistency success rate was 91%, intra-observer reliability was 0.83, inter-observer reliability was 0.83, content validity coefficient was 0.92, and factor loading was 0.37-0.53. The MW total score values between 5 and 6 were established as a reference for normality (P < 0.05). Organic pathology showed lower MW score values (P < 0.05), and functional pathology to a lesser extent (P > 0.05). The proposed scale is a consistent, valid, and reliable tool. Its widespread application would favor commonly used terminology and facilitate quantitative comparisons in future studies.

Activatable Multiplexed 19F NMR Probes for Dynamic Monitoring of Biomarkers Associated with Cellular Senescence.

Simultaneous detection of multiple biomarkers is crucial to achieve specific and dynamic analysis of cellular senescence, given its intrinsic high heterogeneity. Current approaches for senescence detection largely rely on fluorescence imaging, but fluorescent probes inevitably suffer from issues including autofluorescence and spectral overlap when being applied for the simultaneous detection of multiple biomarkers. Herein, we report an alternative strategy and design activatable multiplexed senoprobes based on 19F NMR for dynamic monitoring of cellular senescence. Differing from previous approaches, our strategy has two unique advantages. First, this strategy utilizes the changes in the 19F chemical shift as the signal output, which features by its fingerprint and quantifiable characters, thereby significantly enhancing the detection throughput toward biomarkers with minimized spectral overlapping. Second, the background signal is minimized, benefiting from the extremely low abundance of F in biological samples, and the detection accuracy can thus be improved. As a proof of concept, two activatable 19F NMR molecular probes are synthesized that specially respond to two key senescence-associated biomarkers (β-gal and ROS) and have been successfully demonstrated for dynamical and quantitative assessment of the changes of these biomarkers in different cellular models of senescence, without causing obvious cytotoxicity. Owing to the flexible molecular design, this work may offer a useful platform to create diversified 19F NMR senoprobes for deep understanding of cellular senescence across a wide range of aging-related diseases.

Noninvasive Assessment of Temporal Dynamics in Sympathetic and Parasympathetic Baroreflex Responses.

The baroreflex system is crucial for cardiovascular regulation and autonomic homeostasis. A comprehensive assessment requires understanding the simultaneous temporal dynamics of its multiple functional branches, which traditional methods often overlook. To develop and validate a noninvasive method for simultaneously assessing the temporal dynamics of sympathetic and parasympathetic baroreflexes using pulse contour analysis and the sequence method. Beat-to-beat blood pressure and ECG recordings were analyzed from 55 preoperative cardiothoracic surgery patients in the supine position and 21 subjects from the EUROBAVAR dataset in both supine and standing positions. Systolic arterial pressure (SAP), interbeat interval (IBI), cardiac output (CO), myocardial contraction (dP/dt max ), and systemic vascular resistance (SVR) were estimated using pulse contour analysis. Baroreflex sensitivity (BRS) was calculated via the sequence method and correlated with hemodynamic and heart rate variability (HRV) parameters. Parasympathetic BRS for IBI was correlated with the root mean square of successive differences of ECG RR intervals (RMSSD-HRV) at 0-beat delay. Sympathetic BRS for SVR strongly correlated with SVR, CO, and RMSSD-HRV, particularly at 3-beat delay, and was uniquely associated with SAP at 1-beat delay. Sympathetic BRS for dP/dt max correlated with dP/dt max at 1-beat delay. In contrast, BRS for CO correlated with CO and SVR at 0- and 3-beat delays. Postural changes mainly affected parasympathetically-mediated BRS for IBI and, to a lesser extent, the sympathetic vascular and myocardial branches. This method effectively captures multiple baroreflex responses and their temporal dynamics, revealing distinct autonomic mechanisms and the impact of postural changes. Further validation is warranted.

Classification and recognition method of rice situation based on gray correlation degree

Grain storage is a complex process, affected by factors such as mold, temperature, humidity, and moisture. The use of multiple sensors to detect changes in rice pile parameters has gained prominence as a means to ensure the accuracy and timeliness of grain condition monitoring. However, the current technology does not effectively utilize data. The assessment criteria primarily rely on grain temperature, and the analysis of grain condition is simplistic. Additionally, it fails to adequately integrate information on temperature, humidity, moisture, gas concentration, and other parameters of the grain pile to form a unified assessment result. To address the isolated and one-sided reaction of various parameters in the grain pile, this thesis conducts research on the storage characteristics of heating, condensation, and mold condition. It combines the information fusion of temperature, humidity, moisture, and CO2 with normal grain conditions, constructs an assessment model based on the classification and identification of grain conditions under gray correlation, and achieves real-time dynamic assessment of the state of the grain pile. The experimental results show that the assessment model based on gray correlation can accurately discriminate between normal and mold conditions, but the accuracy in distinguishing heating and condensation still requires improvement. The overall recognition rate of the four types of grain conditions is 79%, which demonstrates the effectiveness of the model in identifying abnormal grain states.

Influence of dynamic assessment on Taiwanese undergraduates and graduate students’ academic writing of research proposals

Abstract Dynamic assessment (DA) integrates assessment and instruction between the instructor and learners. It emphasizes the learning process. DA was introduced to 24 undergraduates and 9 graduate students in two academic writing courses in Taiwan. The analysis of the pre- and post-tests, writing portfolios, observations, and interviews reached the following major conclusions. First, participants had a positive attitude toward DA, particularly regarding expert evaluation as the mediation for identifying global and local errors. Secondly, the integration of DA influenced the participants’ academic writing on research proposals, particularly the structure and the use of the APA format. Thirdly, participants regarded the instructor’s model writing and the exemplary journal articles as useful mediations. Suggestions on the effective integration of DA into academic writing courses are provided.

Wetland Landscape Dynamics and Multi-Functional Assessment of Wuhan City, China

Under the dual pressures of rapid urbanization and intensifying global climate change, China has proposed governance policies aimed at promoting ecological urban construction. Wetland landscapes play a key role in sustaining human and social well-being. As a significant city in the middle reaches of the Yangtze River, Wuhan’s wetland resources play an irreplaceable role in maintaining the regional ecological balance and promoting sustainable economic and social development. However, urbanization poses a severe challenge to the ecological service functions of wetlands. Consequently, in this study, we analyzed the spatial–temporal evolution patterns of the sub-functional systems of carbon sequestration, biodiversity conservation, water yield, and water purification in five wetland types in Wuhan City from 2000 to 2020 by using the CASA model and InVEST model. Then, a wetland multi-functional assessment framework was constructed to quantify the comprehensive multi-function score. It is imperative to unravel the underlying mechanisms driving the changes in wetland functions and to explore the equilibrium point between wetland conservation and urban sustainable development. Our results show that the wetland area of Wuhan City decreased from 5077.33 km2 in 2000 to 4696.60 km2 in 2020, and the wetland multi-functions exhibited significant spatial heterogeneity from 2000 to 2020. Wetland carbon sequestration increased from 0.94 Tg in 2000 to 1.11 Tg in 2020. The wetland habitat quality declined from 0.13 in 2000 to 0.11 in 2020. The water production of the wetlands increased from 5.43 × 109 t in 2000 to 22.59 × 109 t in 2020. The wetland N loss decreased from 55,850.58 t in 2000 to 49,209.93 t in 2020. The highest multi-function score was in paddy fields, which increased from 0.41 ± 0.12 to 0.51 ± 0.12, followed by tidal flats, which increased from 0.39 ± 0.14 to 0.50 ± 0.16, and the lowest was rivers, which also increased from 0.33 ± 0.12 to 0.41 ± 0.14. The multi-function score was closely related to the wetland type and urban development direction over the past two decades, and it was negatively correlated with production and living density, providing new ideas for wetland ecological protection and construction in Wuhan City.

Data-Driven Dynamic Security Partition Assessment of Power Systems Based on Symmetric Electrical Distance Matrix and Chebyshev Distance

A rapid dynamic security assessment (DSA) is crucial for online preventive and restoration decision-making. The deep learning-based DSA models have high efficiency and accuracy. However, the complex model structure and high training cost make them hard to update quickly. This paper proposes a dynamic security partition assessment method, aiming to develop accurate and incrementally updated DSA models with simple structures. Firstly, the power grid is self-adaptively partitioned into several local regions based on the mean shift algorithm. The input of the mean shift algorithm is a symmetric electrical distance matrix, and the distance metric is the Chebyshev distance. Secondly, high-level features of operating conditions are extracted based on the stacked denoising autoencoder. The symmetric electrical distance matrix is modified to represent fault locations in local regions. Finally, DSA models are constructed for fault locations in each region based on the radial basis function neural network (RBFNN) and Chebyshev distance. An online incremental updating strategy is designed to enhance the model adaptability. With the simulation software PSS/E 33.4.0, the proposed dynamic security partition assessment method is verified in a simplified provincial system and a large-scale practical system in China. Test results demonstrate that the Chebyshev distance can improve the partition quality of the mean shift algorithm by approximately 50%. The RBFNN-based partition assessment model achieves an accuracy of 98.96%, which is higher than the unified assessment with complex models. The proposed incremental updating strategy achieves an accuracy of over 98% and shortens the updating time to 30 s, which can meet the efficiency of online application.

Sustainable Development in Regional Socio-Economic Strategies in the Central Chernozem Macro-Region

The concept of sustainable development in modern territorial management is gaining momentum more intensively and dynamically. Socio-economic and environmental aspects are embedded in strategic national and regional documents of a long-term nature. The degree of achievement of the Sustainable Development Goals (SDG) adopted by the UN Agenda is assessed and monitored in various reports of international and industry organizations, which affects the reputational characteristics of countries. The publication presents the results of a review of the achievement of Sustainable Development Goals N 9 (SDG-9): “Industrialization, innovation and infrastructure” (Creation of sustainable infrastructure, promotion of inclusive and sustainable industrialization and innovation) in 5 subjects of the Russian Federation of the Central Chernozem macro-region for the period 2015–2022. Indicators for monitoring the achievement of SDG-9 in the regional context were proposed by the authors when comparing the national set of SDG indicators and statistical indicators characterizing the development of the subjects of the Russian Federation. The main research methods are systematization, content analysis and the method of structural and dynamic assessment. In the course of the study, a unified regional list of SDG-9 indicators was formed; an empirical assessment of this list of indicators was carried out on the materials of 5 subjects of the Central Chernozem macro-region and an overview of the degree of achievement of this goal in the studied regions. The authors conducted a comparative review of the strategies of social and economic development of the subjects of the Central Chernozem macro-region for the existence of principles of sustainable development.

Novel dual-color fluorescence probe for monitoring the fluctuation of lysosomal polarity and viscosity during apoptosis

Apoptosis is pivotal in the pathogenesis of cancer and various other diseases. Real-time monitoring of apoptosis is crucial for assessing cell viability and facilitating drug screening. The process of apoptosis tends to cause changes in cellular microenvironmental factors. The variations of the microenvironment can serve as an indicator of the degree of apoptosis. Thus, the development of a smart and facile probe responding to cellular microenvironmental factors is significant for visualizing the apoptotic process. In this research, we designed a novel dual-color fluorescent probe, Lyso-DCPV, which incorporates N, N-diethyl coumarin as its polarity-responsive module, and the twisting double bond between N, N-diethyl coumarin and N-propyl quinoline as its viscosity-responsive module. The green fluorescence of Lyso-DCPV is sensitive to polarity changes, diminishing as polarity increases. Conversely, the red fluorescence intensifies with escalating viscosity. The probe specifically targets lysosomes, producing green fluorescence in live cells. Due to Lyso-DCPV’s acute sensitivity to changes in polarity and viscosity, it is well-suited to observe variations in the intracellular lysosomal microenvironment during drug-induced apoptosis. We also employed Lyso-DCPV for the dynamic assessment of polarity and viscosity during peroxide-induced apoptosis, enabling the observation of cell viability through variations in the probe’s emission color and intensity. The distinct probe will pave the way for novel strategies in evaluating apoptosis-related drugs. Moreover, Lyso-DCPV stands as an exemplary molecular instrument to elucidate the interplay between polarity and viscosity, facilitating the exploration of the interrelation in the cellular microenvironment during apoptosis.