Different Types Of Changes Research Articles

Outcomes and inflammation changes in different types of immunocompromised patients with critically ill COVID-19 admitted to ICU: a national multicenter study

BackgroundImmunocompromised patients face higher risks of Severe Acute Respiratory Syndrome Coronavirus 2 infection and co-infections, leading to a possibility of high disease severity and poor outcomes. Conversely, immunosuppression can mitigate the excessive inflammatory response induced by the virus, potentially reducing disease severity. This study aims to investigate the prognostic differences and early inflammatory response characteristics in various types of immunocompromised patients with severe coronavirus disease 2019 (COVID-19) admitted to intensive care unit (ICU), summarize their clinical features, and explore potential mechanisms.MethodsA retrospective analysis was conducted on critically ill COVID-19 patients admitted to the ICU of 59 medical centers in mainland China during the Omicron outbreak from November 2022 to February 2023. Patients were categorized into two groups based on their immunosuppression status: immunocompromised and immunocompetent. Immunocompromised patients were further subdivided by etiology into cancer patients, solid organ transplant (SOT) patients, and other immunocompromised groups, with immunocompetent patients serving as controls. The mortality rates, respiratory support, complications, and early inflammatory cytokine dynamics upon ICU admission among different populations were analyzed.ResultsA total of 2030 critically ill COVID-19 patients admitted to ICU were included, with 242 in the immunocompromised group and 1788 in the immunocompetent group. Cancer patients had a higher median age of 69 years (IQR 59, 77), while SOT patients were generally younger and had less severe illness upon ICU admission, with a median APACHE II score of 12.0 (IQR 8.0, 20.0). Cancer patients had a twofold increased risk of death (OR = 2.02, 95% CI 1.18–3.46, P = 0.010) compared to immunocompetent patients. SOT and cancer patients exhibited higher C-reactive protein and serum ferritin levels than the immunocompetent group in their early days of ICU admission. The CD8+ T cells dynamics were inversely correlated in cancer and SOT patients, with Interleukin-6 levels consistently lower in the SOT group compared to both immunocompetent and cancer patients.ConclusionCritically ill COVID-19 patients admitted to the ICU exhibit distinct clinical outcomes based on their immunosuppression status, with cancer patients facing the highest mortality rate due to variations in inflammatory responses linked to their immunosuppression mechanisms. Monitoring dynamic changes in inflammatory markers and immune cells, particularly CD8+ T lymphocytes and IL-6, may offer valuable prognostic insights for these patients.

An Assessment of Vegetation Changes in the Three-River Headwaters Region, China: Integrating NDVI and Its Spatial Heterogeneity

Assessing vegetation changes in alpine arid and fragile ecosystems is imperative for informed ecological restoration initiatives and adaptive ecosystem management. Previous studies primarily employed the Normalized Difference Vegetation Index (NDVI) to reveal vegetation dynamics, ignoring the spatial heterogeneity alterations caused by bare soil. In this study, we used a comprehensive analysis of NDVI and its spatial heterogeneity to examine the vegetation changes across the Three-River Headwaters Region (TRHR) over the past two decades. A random forest model was used to elucidate the underlying causes of these changes. We found that between 2000 and 2022, 9.4% of the regions exhibited significant changes in both NDVI and its spatial heterogeneity. These regions were categorized into six distinct types of vegetation change: improving conditions (62.1%), regrowing conditions (11.0%), slight degradation (16.2%), medium degradation (8.4%), severe degradation (2.0%), and desertification (0.3%). In comparison with steppe regions, meadows showed a greater proportion of improved conditions and medium degradation, whereas steppes had more instances of regrowth and slight degradation. Climate variables are the dominant factors that caused vegetation changes, with contributions to NDVI and spatial heterogeneity reaching 68.9% and 73.2%, respectively. Temperature is the primary driver of vegetation dynamics across the different types of change, with a more pronounced impact in meadows. In severely degraded steppe and meadow regions, grazing intensity emerged as the predominant driver of NDVI change, with an importance value exceeding 0.50. Notably, as degradation progressed from slight to severe, the significance of this factor correspondingly increased. Our findings can provide effective information for guiding the implementation of ecological restoration projects and the sustainable management of alpine arid ecosystems.

Influence of photosynthetic active radiation on sap flow dynamics across forest succession stages in Dinghushan subtropical forest ecosystem

With the intensification of global change, forests are subjected to varying degrees of drought or high-temperature stress, which has an indelible impact on the growth of trees. However, knowledge on the response of sap flow to environmental changes in different types of forests is still rare, especially in China's subtropical forest ecosystem. Consequently, studying how different tree species regulate their sap flow in response to shifting environmental conditions is essential for understanding forest transpiration, water use efficiency, and drought stress resilience. Therefore, this study aimed to investigate the sap flow dynamics of seven tree species in five forest plots, i.e., pine forest (PF), two types of mixed conifer-broadleaf forests (MF1+MF2), monsoon evergreen broadleaved forest (MEBF), and montane monsoonal evergreen broad-leaf forest (MOBF) at Dinghushan National Reserve in Southern China, using the heat dissipation probe technique and synchronous environmental factor recordings. Results demonstrated a significant influence of photosynthetic active radiation (PAR) on sap flow across all tree species, with mean PAR values ranging from over 1200 to 425 μmol m−2 s−1, establishing it as the principal driving factor. This observation underscores the heightened responsiveness or sensitivity of tree species to variations in PAR as the forest undergoes development and maturation. The correlation between vapor pressure deficit (VPD) and tree sap flow decreased as succession progressed. Moreover, the influence of soil water content (SWC) on sap flow stability against environmental changes increased. Similar patterns were also found between the two MF, with MF-2 displaying ecological characteristics and environmental conditions more closely aligned with those of the late-successional MEBF. The study reveals the intricate relationship between environmental factors and sap flow regulation in tree species within a subtropical forest ecosystem. Addressing a comparative gap in sap flow correlation among dominant tree species at Dinghushan, it establishes a hydro-physiological foundation for understanding tree species substitution during forest succession. The results provide key insights for forest management and climate-related research. Future studies should delve into the long-term implications of observed sap flow dynamics, exploring their impact on tree species adaptability amid ongoing environmental changes.

Chewing characteristics of rice and reasons for differences between three rice types with different amylose contents

This study investigated the physicochemical structural changes in different types of rice (japonica rice [JR], indica rice [IR], and waxy rice [WR]) during oral digestion and explored the reasons for differences in oral digestion between the three different types. The results showed that, compared with JR (42.41 ± 3.06 mg/g) and WR (26.82 ± 0.67 mg/g), IR had the highest amylose content (49.95 ± 3.33 mg/g) and, related to this, hydrolysis rate. A correlation analysis showed that, the higher the amylose content, the harder the texture of rice, leading to longer chewing times and, as a result, a greater degree of hydrolysis. In addition, the higher the amylose content, the lower the exudate content and viscosity of rice, which affects chewing time and frequency, thereby affecting the degree of hydrolysis. Both X-ray computed tomography and scanning electron microscopy indicated that cooked IR had the loosest structure and the most pores, that were conducive to chewing and crushing and therefore contributed to the high hydrolysis rate. Analysis of the exudate structure showed that the amount of exudate affected rice pores. More exudates lead to pore coverage and a tight structure.

Circular RNA as a Biomarker for Diagnosis, Prognosis and Therapeutic Target in Acute and Chronic Lymphoid Leukemia.

Circular RNAs (circRNAs) are single-stranded RNAs that have received much attention in recent years. CircRNAs lack a 5' head and a 3' poly-A tail. The structure of this type of RNAs make them resistant to digestion by exonucleases. CircRNAs are expressed in different cells and have various functions. The function of circRNAs is done by sponging miRNAs, changing gene expression, and protein production. The expression of circRNAs changes in different types of cancers, which causes changes in cell growth, proliferation, differentiation, and apoptosis. Changes in the expression of circRNAs can cause the invasion and progression of tumors. Studies have shown that changes in the expression of circRNAs can be seen in acute lymphoid leukemia (ALL) and chronic lymphoid leukemia (CLL). The conducted studies aim to identify circRNAs whose expression has changed in these leukemias and their more precise function so that these circRNAs can be identified as biomarkers, prediction of patient prognosis, and treatment targets for ALL and CLL patients. In this study, we review the studies conducted on the role and function of circRNAs in ALL and CLL patients. The results of the studies show that there is a possibility of using circRNAs as biomarkers in the identification and treatment of patients in the future.

Surface roughness of different types of resin composites after artificial aging procedures: an in vitro study

BackgroundThe temperature changes, chemical agents, and brushing activity that resin composite restorations are exposed to in the oral environment can cause changes in surface roughness. In this study, the aim was to investigate in vitro the clinical one-year surface roughness changes of different types of composites (flowable or conventional) from the same companies by subjecting them to immersion in solutions, brushing, and thermal cycling procedures to simulate intraoral conditions.MethodsFour different resin composite brands were included in the study using both their conventional (Charisma Smart, 3M Filtek Ultimate Universal, Omnichroma, Beautifil II) and flowable resin composites (Charisma Flow, 3M Filtek Ultimate Flowable, Omnichroma Flow, Beautifil Flow Plus F00), giving 4 groups with 2 types of resin composite in each. 40 samples were prepared for each group/resin type, for a total of 320 samples. After initial surface roughness measurements by a mechanical profilometer, the samples were divided into 4 subgroups (n = 10) and immersed in solutions (distilled water, tea, coffee, or wine) for 12 days. The samples were then subjected to 10,000 cycles of brushing simulation and 10,000 cycles of thermal aging. Surface roughness measurements were repeated after the procedures. For statistical analysis, the 3-way analysis of variance and the Tukey test were used (p < 0.05).ResultsIt was concluded that composite groups and types had an effect on surface roughness at time t0 (p < 0.001). At time t1, the highest surface roughness value was obtained in the Beautifil-conventional interaction. When the surface roughness values between time t0 and t1 were compared, an increase was observed in the Beautifil II and Beautifil Flow Plus F00, while a decrease was observed in the other composite groups.ConclusionComposite groups, types, and solutions had an effect on the surface roughness of resin composites. After aging procedures, it was concluded that the Beautifil group could not maintain the surface structure as it exceeded the threshold value of 0.2 μm for bacterial adhesion.

Sliding and Adaptive Windows to Improve Change Mining in Process Variability

A configurable process Change Mining approach can detect changes from a collection of event logs and provide details on the unexpected behavior of all process variants of a configurable process. The strength of Change Mining lies in its ability to serve both conformance checking and enhancement purposes; users can simultaneously detect changes and ensure process conformance using a single, integrated framework. In prior research, a configurable process Change Mining algorithm has been introduced. Combined with our proposed preprocessing and change log generation methods, this algorithm forms a complete framework for detecting and recording changes in a collection of event logs. Testing the framework on synthetic data revealed limitations in detecting changes in different types of variable fragments. Consequently, it is recommended that the preprocessing approach be enhanced by applying a filtering algorithm based on sliding and adaptive windows. Our improved approach has been tested on various types of variable fragments to demonstrate its efficacy in enhancing Change Mining performance.

Deciphering the fate of granulation tissue in the human inflammatory alveolar microenvironment using single-cell RNA sequencing

Objective: To investigate the cellular composition and heterogeneity of granulation tissue in human alveolar sockets and construct single-cell transcriptomic maps to elucidate the potential outcomes of natural resolution in the inflammatory microenvironment. Methods: Granulation tissues from 12 alveolar sockets undergoing tooth extraction due to periodontitis and scheduled for delayed site preservation or autologous tooth transplantation were collected in the Department of Oral and Maxillofacial Surgery, School of stomatology Fourth Military Medical University from September 2022 to August 2023. This study used HE staining and single-cell RNA sequencing (scRNA-seq) to observe the cellular composition and morphological changes of different types of granulation tissues. This approach enabled us to identify cellular sequence variations in the inflammatory dental alveolar granulation tissue within specific microenvironments, construct single-cell atlases for different types of human dental alveolar granulation tissues, and explore the spatiotemporal patterns of cell type distribution and key gene changes during the resolution process of inflammatory granulation tissue. Results: HE staining revealed extensive infiltration of inflammatory cells in the dental alveolar inflammatory granulation tissue. After allowing the inflammatory granulation tissue to naturally resolve for three weeks, its histological morphology was essentially consistent with that of reparative granulation tissue. ScRNA-seq captured a total of 20 448 cells from granulation tissues, and the gene expression quantification analysis revealed total gene counts of 33 835 for inflammatory granulation tissue, 36 058 for naturally resolved granulation tissue, and 34 719 for reparative granulation tissue. At the single-cell level, granulation tissue was annotated into ten cell subgroups, including vascular endothelial cells, mesenchymal stem cells, and fibroblasts. Differences were observed in the proportion of cell compositions between inflammatory and naturally resolved granulation tissues. Pseudo-temporal analysis illustrated two main outcomes in tissue resolution and healing, involving immune responses and angiogenesis. Among these, genes associated with inflammation regulation and immune response, such as Igbp5, Zfp36, and Hspa1b, as well as genes involved in extracellular matrix secretion and the formation of vessels and fibers such as Timp3, Postn, and Rgs5, showed significant differences in expression between the two types of granulation tissues. Conclusions: Inflammatory granulation tissue exhibits heterogeneity in cell composition, gene expression, and biological functions compared to naturally resolved granulation tissue. When the inflammatory granulation tissue in the alveolar socket is left undisturbed to undergo natural resolution, it displays a cellular composition similar to that of reparative granulation tissue at both the histological and single-cell levels. Moreover, it modulates the inflammatory response and the healing process through immune reactions and tissue remodeling.

Strategic, tactical, complex and simple changes to farm systems

AbstractPressure has grown to reconfigure commercial farm systems to ameliorate resource degradation as governments have increasingly sought to halt or reverse the damaging effects of agriculture on the environment. Now, climate change is creating additional pressure to redesign farm systems to withstand more variable, and historically more extreme, seasonal conditions. Meeting these pressures is thought to require a combination of responses ranging from incremental adjustments to farm systems through to their complete transformation into entirely new enterprises. Implementing each of these entails different resources, time horizons, skills, knowledge and planning, and this has corresponding consequences for any government or industry policies intended to promote adoption or compliance. While there is an extensive literature on the adoption of technology and management practices in agriculture, the literature on different types of change to farm systems, and the criteria for distinguishing between types, is limited. We describe a novel approach to classifying changes to farm systems by integrating a method for describing the strategic and tactical flexibility of farm systems with a method for describing the complexity of changes to farm systems. The resulting classification provides a framework for inferring the nature of the resources, skills, knowledge, planning and time needed to implement the different types of change. We provide illustrative examples drawn from a series of interviews with farmers of each type of change and discuss the implications for extension, agricultural and environmental policy and policy regarding adaptation to climate change. We found that heterogeneity in farm systems translates into heterogeneity in adoption processes. We believe that our approach provides a practical way of translating commonly used broad descriptors of adaptation, such as ‘incremental’, ‘systems’ and ‘transformational’, into the specific type of the change that farmers must make to their farm systems to enact adaptations, with consequent implications for the effective policy support of adaptation.

Analysis of Lake Area Dynamics and Driving Forces in the Jianghan Plain Based on GEE and SEM for the Period 1990 to 2020

The lakes of Jianghan Plain, as an important component of the water bodies in the middle and lower reaches of the Yangtze River plain, have made significant contributions to maintaining the ecological health and promoting the sustainable development of the Jianghan Plain. However, there is a relatively limited understanding regarding the trends of lake area change for different types of lakes and their dominant factors over the past three decades in the Jianghan Plain. Based on the Google Earth Engine (GEE) platform, combined with the water body index method, the changes in area of three different types of lakes (area &gt; 1 km2) in the Jianghan Lake Group from 1990 to 2020 were extracted and analyzed. Additionally, the Partial least squares structural equation model (PLS-SEM) was utilized to analyze the driving factors affecting the changes in water body area of these lakes. The results show that from 1990 to 2020, the area of the lakes of the wet season and level season exhibited a decreasing trend, decreasing by 893.1 km2 and 77.9 km2, respectively. However, the area of dry season lakes increased by 59.27 km2. The areas of all three types of lakes reached their minimum values in 2006. According to the PLS-SEM results, the continuous changes in the lakes’ area are mainly controlled by environmental factors overall. Furthermore, human factors mainly influence the mutation of the lakes’ area. This study achieved precise extraction of water body areas and accurate analysis of driving factors, providing a basis for a comprehensive understanding of the dynamic changes in the lakes of Jianghan Plain, which is beneficial for the rational utilization and protection of water resources.

Just-in-Time crash prediction for mobile apps

Just-In-Time (JIT) defect prediction aims to identify defects early, at commit time. Hence, developers can take precautions to avoid defects when the code changes are still fresh in their minds. However, the utility of JIT defect prediction has not been investigated in relation to crashes of mobile apps. We therefore conducted a multi-case study employing both quantitative and qualitative analysis. In the quantitative analysis, we used machine learning techniques for prediction. We collected 113 reliability-related metrics for about 30,000 commits from 14 Android apps and selected 14 important metrics for prediction. We found that both standard JIT metrics and static analysis warnings are important for JIT prediction of mobile app crashes. We further optimized prediction performance, comparing seven state-of-the-art defect prediction techniques with hyperparameter optimization. Our results showed that Random Forest is the best performing model with an AUC-ROC of 0.83. In our qualitative analysis, we manually analysed a sample of 642 commits and identified different types of changes that are common in crash-inducing commits. We explored whether different aspects of changes can be used as metrics in JIT models to improve prediction performance. We found these metrics improve the prediction performance significantly. Hence, we suggest considering static analysis warnings and Android-specific metrics to adapt standard JIT defect prediction models for a mobile context to predict crashes. Finally, we provide recommendations to bridge the gap between research and practice and point to opportunities for future research.

The latest trends in the cimbalom repertoire of the 21st century

Statement of the problem. Today, cimbalom art is experiencing a new stage of development, the prominent features of which are the use of composition techniques of the 20th century, as well as the development of an arsenal of extended cimbalom playing techniques. Compared to other folk instruments, this stage of enrichment of the cimbalom repertoire begins later and falls mainly on the 21st century, when a number of innovative works appear, both for cimbalom solo and in combination with other instruments. However, at present, this layer of the cimbalom repertoire remains almost unexplored. Objectives, methods, and novelty of the research. The purpose of the study is to identify the principles of implementing the latest trends in the development of the cimbalom repertoire in the work of composers of the 21st century. For the first time, the concept of extended performance techniques and their differentiation is introduced into the scientific circulation of cimbalom studies, and the works by P. Machajd&amp;#237;k, J. Huffman, J. Seo, F. van Wijck, D. Lazariev, which were not previously considered by musicologists, are highlighted from this viewpoint. Historical approach, comparative, performance, structural and functional types of analysis allowed tracing the main trends in the development of the latest solo and ensemble cimbalom repertoire. Research results and conclusion. After analyzing a number of musical studies and scores of modern composers, the typical features of the latest samples of the cimbalom repertoire was found. The typical its features are a significant variety of composition techniques, among which we find aleatorics (J. Seo, J. Pereira), microchromatics (J. Seo), sonorics (F. Van Wijck, J. Pereira), dodecaphony (J. Pereira, D. Lazariev). In modern works both, the traditional techniques of playing, which were successful in cimbalom performance even before that (flageolets, playing with a normal beat, pizzicato, glissando), and the various advanced techniques are used. Among the latter are: – non-traditional types of glissando using a finger stick (D. Lazarіev), nails (J. Seo), marimba sticks (J. Pereira); – percussion finger technique (J. Pereira); – imitation of clusters – hitting the strings with the palms of the hands (F. Van Wijck); – playing with non-traditional objects, such as glasses (P. Machajdik); – preparation of the cimbalom (J. Huffman, D. Lazariev). A common feature of modern cimbalom compositions is an active change of different types of sticks during one piece, sometimes in the middle of a part, as well as their alternation with sticks from other instruments (marimba, bells, xylophone), which can be considered as part of an arsenal of extended performance techniques. For example, in the works of J. Seo, J. Pereira and D. Lazariev, playing with marimba sticks and playing with plastic sticks from orchestral bells is assumed. Preparation of the instrument is less often used (J. Huffman used a metal needle for this purpose, and D. Lazariev – two chains and foil). It was concluded that extended performance techniques are at the stage of development and study by musicologists, but despite all the difficulties, the knowledge on them is gradually being introduced into scientific circulation. It should also be emphasized that modern composers show interest in the developing of advanced performance techniques, which certainly inspires hope for writing of new works for cimbalom and its research.

How structural variants shape avian phenotypes: Lessons from model systems.

Despite receiving significant recent attention, the relevance of structural variation (SV) in driving phenotypic diversity remains understudied, although recent advances in long-read sequencing, bioinformatics and pangenomic approaches have enhanced SV detection. We review the role of SVs in shaping phenotypes in avian model systems, and identify some general patterns in SV type, length and their associated traits. We found that most of the avian SVs so far identified are short indels in chickens, which are frequently associated with changes in body weight and plumage colouration. Overall, we found that relatively short SVs are more frequently detected, likely due to a combination of their prevalence compared to large SVs, and a detection bias, stemming primarily from the widespread use of short-read sequencing and associated analytical methods. SVs most commonly involve non-coding regions, especially introns, and when patterns of inheritance were reported, SVs associated primarily with dominant discrete traits. We summarise several examples of phenotypic convergence across different species, mediated by different SVs in the same or different genes and different types of changes in the same gene that can lead to various phenotypes. Complex rearrangements and supergenes, which can simultaneously affect and link several genes, tend to have pleiotropic phenotypic effects. Additionally, SVs commonly co-occur with single-nucleotide polymorphisms, highlighting the need to consider all types of genetic changes to understand the basis of phenotypic traits. We end by summarising expectations for when long-read technologies become commonly implemented in non-model birds, likely leading to an increase in SV discovery and characterisation. The growing interest in this subject suggests an increase in our understanding of the phenotypic effects of SVs in upcoming years.

Diabetes and osteoporosis: a two-sample mendelian randomization study

BackgroundThe effects on bone mineral density (BMD)/fracture between type 1 (T1D) and type 2 (T2D) diabetes are unknown. Therefore, we aimed to investigate the causal relationship between the two types of diabetes and BMD/fracture using a Mendelian randomization (MR) design.MethodsA two-sample MR study was conducted to examine the causal relationship between diabetes and BMD/fracture, with three phenotypes (T1D, T2D, and glycosylated hemoglobin [HbA1c]) of diabetes as exposures and five phenotypes (femoral neck BMD [FN-BMD], lumbar spine BMD [LS-BMD], heel-BMD, total body BMD [TB-BMD], and fracture) as outcomes, combining MR-Egger, weighted median, simple mode, and inverse variance weighted (IVW) sensitivity assessments. Additionally, horizontal pleiotropy was evaluated and corrected using the residual sum and outlier approaches.ResultsThe IVW method showed that genetically predicted T1D was negatively associated with TB-BMD (β = -0.018, 95% CI: -0.030, -0.006), while T2D was positively associated with FN-BMD (β = 0.033, 95% CI: 0.003, 0.062), heel-BMD (β = 0.018, 95% CI: 0.006, 0.031), and TB-BMD (β = 0.050, 95% CI: 0.022, 0.079). Further, HbA1c was not associated with the five outcomes (β ranged from − 0.012 to 0.075).ConclusionsOur results showed that T1D and T2D have different effects on BMD at the genetic level. BMD decreased in patients with T1D and increased in those with T2D. These findings highlight the complex interplay between diabetes and bone health, suggesting potential age-specific effects and genetic influences. To better understand the mechanisms of bone metabolism in patients with diabetes, further longitudinal studies are required to explain BMD changes in different types of diabetes.

HSAA-CD: A Hierarchical Semantic Aggregation Mechanism and Attention Module for Non-Agricultural Change Detection in Cultivated Land

Cultivated land plays a fundamental role in the sustainable development of the world. Monitoring the non-agricultural changes is important for the development of land-use policies. A bitemporal image transformer (BIT) can achieve high accuracy for change detection (CD) tasks and also become a key scientific tool to support decision-making. Because of the diversity of high-resolution RSIs in series, the complexity of agricultural types, and the irregularity of hierarchical semantics in different types of changes, the accuracy of non-agricultural CD is far below the need for the management of the land and for resource planning. In this paper, we proposed a novel non-agricultural CD method to improve the accuracy of machine processing. First, multi-resource surveying data are collected to produce a well-tagged dataset with cultivated land and non-agricultural changes. Secondly, a hierarchical semantic aggregation mechanism and attention module (HSAA) bitemporal image transformer method named HSAA-CD is performed for non-agricultural CD in cultivated land. The proposed HSAA-CD added a hierarchical semantic aggregation mechanism for clustering the input data for U-Net as the backbone network and an attention module to improve the feature edge. Experiments were performed on the open-source LEVIR-CD and WHU Building-CD datasets as well as on the self-built RSI dataset. The F1-score, intersection over union (IoU), and overall accuracy (OA) of these three datasets were 88.56%, 84.29%, and 68.50%; 79.84%, 73.41%, and 59.29%; and 98.83%, 98.39%, and 93.56%, respectively. The results indicated that the proposed HSAA-CD method outperformed the BIT and some other state-of-the-art methods and proved to be suitable accuracy for non-agricultural CD in cultivated land.

Understanding policy evolution using institutional grammar: net metering policies in the United States

Policy process scholars have expressed a long-standing interest in policy evolution, though such assessments offer a limited understanding of how policy language changes across time. These micro-level assessments of policy design evolution lend insights into substantive aspects of policy adjustment over time. In this paper, we conduct a comparative case study of changes in the text of net metering legislation in four US states. Specifically, using the Institutional Grammar (IG), we measure policy evolution as: (1) change in policy provisions that define the net metering policy system or regulate behavior, (2) change in different types of provisions (rules), and (3) calibration of policy provisions. Furthermore, we identify the dynamics of policy patching and packaging with these measures, demonstrating more information is revealed about the dynamics of policy evolution at the micro-level. For scholars and practitioners, our novel micro-level measurement allows discernment of changes in who is being incentivized, in what ways they are being incentivized, and the extent to which they are being incentivized. Furthermore, our approach can assist practitioners in identifying policy provisions and the language of those provisions that are changing more frequently, as we find policy language does not evolve evenly.

Joint multitemporal SAR and optical mapping of urban changes

AbstractThis paper presents a methodology designed to leverage multitemporal sequences of synthetic aperture radar (SAR) and multispectral data and automatically extract urban changes. The approach compares results using different radar and optical sensors, describing the advantages and drawbacks of using SAR data from the COnstellation of small Satellites for the Mediterranean basin Observation (COSMO)/SkyMed, SAtélite Argentino de Observación COn Microondas (SAOCOM), and Sentinel-1 constellations, as well as nighttime light data or Sentinel-2 images. Multiple indexes obtained from multispectral data are compared, too, and results obtained by an unsupervised clustering procedure are analyzed. The results show that using different datasets it is possible to obtain consistent results about different types of changes in urban areas (e.g., demolition, development, and densification) with different levels of spatial details.

Analysis of asphalt microscopic and force curves under water-temperature coupling with AFM

Asphalt, as a crucial material in road construction, is affected by external environmental factors, among which water and temperature are the primary causes of water damage to asphalt pavements. Different hydro-thermal environments can cause varying types of damage to asphalt or the asphalt-aggregate interface. To analyze the micro-performance changes of different types of asphalt under various hydro-thermal environments, this study conducts tests onPG64–22 matrix asphalt, PG76–22 SBS-modified asphalt and PG82–34 high viscosity asphalt under different hydro-thermal coupling and freeze-thaw cycle conditions using Atomic Force Microscopy (AFM). The analysis is based on the obtained micro-morphology images and mechanical properties, exploring the impact mechanisms of different hydro-thermal environments on various asphalts. Results show that under different hydro-thermal conditions, the three asphalts exhibit different morphological changes: the asphalt surface's “bee-shaped structure” is gradually destroyed after hydro-thermal coupling, while a “disappearance-reappearance” phenomenon is observed under freeze-thaw cycles. Moreover, the roughness of the two modified asphalts shows a different trend from that of the matrix asphalt, indicating that the modifier alters the micro-structure of asphalt to some extent. Under hydro-thermal coupling, the adhesion force of the three asphalts decreases linearly, with matrix asphalt decreasing by 89.2% after 3 hours, SBS modified asphalt by 63.1%, and high-viscosity asphalt by 23.9%, showing that high-viscosity asphalt has better waterproof and heat-resistant performance. During freeze-thaw cycles, the adhesion force between the asphalt and the tip shows varying degrees of recovery. Additionally, there are differences in adhesion force across different areas of the asphalt surface, which tend to diminish with hydro-thermal coupling or freeze-thaw cycles. These results indicate that hydro-thermal coupling and freeze-thaw cycles have different mechanisms of damage to the internal structure of asphalt, providing important data for understanding the damage mechanisms in depth.

Adaptive goal recognition using process mining techniques

Goal Recognition (GR) is a research problem that studies ways to infer the goal of an intelligent agent based on its observed behavior and knowledge of the environment in which the agent operates. A common assumption of GR is that the environment is static. However, in many real-world scenarios, for example, recognizing customers’ preferences, it is necessary to recognize the goals of multiple agents or multiple goals of a single agent over an extended period. Therefore, it is reasonable to expect the environment to change throughout a series of goal recognition tasks. This paper presents three process mining-based solutions to the problem of adaptive GR in a changing environment implemented as different control strategies of a system for solving standard GR problems. As a standard GR system that gets controlled, we use the system grounded in process mining techniques, as it can adjust its internal GR mechanisms based on data collected while observing the operating agents. We evaluated our control strategies over synthetic and real-world datasets. The synthetic datasets were generated using the extended version of the Goal Recognition Amidst Changing Environments (GRACE) tool. The datasets account for different types of changes and drifts in the environment. The evaluation results demonstrate a trade-off between the GR performance over time and the effort invested in adaptations of the GR mechanisms of the system, showing that few well-planned adaptations can lead to a consistently high GR performance.

Analysis of Semantic Change from a Lexical Perspective

Semantic change is a universal phenomenon in human language. This article analyzes the trends of semantic change and the possible reasons behind them from a lexical perspective. By illustrating the five different types of changes that happen on the lexicon, the study finds that factors like language contacts, cultural trends and social norms significantly impact semantic changes. Besides, people’s cognitive mode and their concept of collocations also contribute to the changes in the lexicon.