Complex Index Research Articles

Adopting artificial intelligence algorithms for remote fetal heart rate monitoring and classification using wearable fetal phonocardiography

Fetal phonocardiography (FPCG) is a non-invasive Fetal Heart Rate (FHR) monitoring technique that can detect vibrations and murmurs in heart sounds. However, acquiring fetal heart sounds from a wearable FPCG device is challenging due to noise and artefacts. This research contributes a resilient solution to overcome the conventional issues by adopting Artificial Intelligence (AI) with FPCG for automated FHR monitoring in an end-to-end manner, named (AI-FHR). Four sequential methodologies were used to ensure reliable and accurate FHR monitoring. The proposed method removes low-frequency noises and high-frequency noises by using Chebyshev II high-pass filters and Enhanced Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ECEEMDAN) in combination with Phase Shifted Maximal Overlap Discrete Wavelet Transform (PS-MODWT) filters, respectively. The denoised signals are segmented to reduce complexity, and the segmentation is performed using multi-agent deep Q-learning (MA-DQL). The segmented signal is provided to reduce the redundancies in cardiac cycles using the Artificial Hummingbird Optimization (AHBO) algorithm. The segmented and non-redundant signals are converted into 3D spectrograms using a machine learning algorithm called variational auto-encoder-general adversarial networks (VAE-GAN). The feature extraction and classification are carried out by adopting a hybrid of the bidirectional gated recurrent unit (BiGRU) and the multi-boosted capsule network (MBCapsNet). The proposed method was implemented and simulated using MATLAB R2020a and validated by adopting effective validation metrics. The results demonstrate that the proposed method performed better than the current method with accuracy (81.34%), sensitivity (72%), F1-score (83%), Energy (0.808 J), and complexity index (13.34). Like other optimization methods, AHO needs precise parameter adjustment in order to function well. Its performance may be greatly impacted by the selection of parameters, including population size, exploration rate, and learning rate.

Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity

Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects’ PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.

Ecological security assessment of Yunnan Province, China in the context of Production-Living-Ecological space division.

With the rapid development of population, society and economy, human activities have caused serious adverse impacts on the environment, ecosystems and landscape patterns over the long term. In order to address the series of impacts of human activities on the environment, territorial space and resource use, the study of Production-Living-Ecological Space (PLES) and ecological security have all become academic frontiers in the field of sustainable development. In this study, we applied multi-source data and GIS technology to construct an ecological security evaluation model based on the results of PLES delineation and the Pressure-State-Response (PSR)framework, and carried out the three-period PLES ecological security evaluation for 2000, 2010 and 2020 at the county and grid scales in Yunnan Province. The PLES pattern in Yunnan Province is dominated by ecological space, which accounts for 75%, followed by 23% of production space, with ecological space shrinking from 2000 to 2020. Ecological security in ecological space and living space shows an improving trend from 2000 to 2020. The ecological security of production space improved in 2010 compared to 2000 but then showed a decreasing trend in 2020. Ecological security in ecological space shows that north-western and southern Yunnan is safer than central Yunnan, while ecological security in living space is safer in central Yunnan, and ecological security in production space is better in southern Yunnan than in northern Yunnan. Comparison with related research results shows that the ecological security evaluation results of PLES in Yunnan Province in this study are scientific and reasonable. The ecological security evaluation model of PLES constructed in this study solves the problem of complex and incomplete ecological security evaluation indexes in the past, and the results of the study are more refined and precise, which provides new ideas for the study of regional ecological security.

Importance of Hospital Performance Indicators in Contracting and Financing Medical Services in Surgical Wards.

In the Romanian healthcare system, public hospitals' contract for the provision of healthcare services with the National Health Insurance Services (NHIS) is the main source of revenue in a hospital's income and expenditure budget. In Romania, for acute diseases, payment is made on a per-case basis for hospitals financed under the diagnostic-related groups (DRG) system, which is calculated according to the indicators achieved. The main objective of the study aimed at the quantitative and comparative analysis of hospital performance indicators used in the calculation of the contracted amount with NHIS, in order to quantify the results and evaluate the effectiveness of the measures taken in the surgical wards of the Emergency Clinical County Hospital of Oradea (ECCHO) compared to the annual average values at the national level, in the period 2012-2022. The indicators, such as the number of beds, number of cases, average length of hospitalization (LOH), and case complexity index (CCI), were analyzed at the level of the ECCHO, a tertiary care hospital in the surgical wards. Rehabilitation and modernization of wards, laboratories, operating theatres, and high-performance equipment have been made possible through efficient management and monthly monitoring of medical and financial activity. The average LOH actually carried out on the surgical wards has been decreasing over the 11 years analyzed, with a lower number of hospital days than at the national level. The CCI achieved by the hospital's surgical wards has had an increasing evolution throughout the period analyzed, higher than the national value. The maximum amount contracted and the amount contracted by the hospital is higher when the LOH and CCI indicators achieved by each section are included in the formula than the indicators established at the national level. A lower LOH and a higher CCI than the national values facilitated the contracting of a higher amount. Optimization of the indicators by hospital performance is correlated with improved funding by the NHIS. Increasing the contracted amount facilitates the contracting of an exponential annual number of cases, resulting in more efficient medical services in the surgical wards.

Towards the Sustainable Nexus of Higher Economic Complexity Index, Lower Carbon Emissions and Accelerated Economic Growth:

Towards the Sustainable Nexus of Higher Economic Complexity Index, Lower Carbon Emissions and Accelerated Economic Growth:

Quantifying Microvascular Structure in Healthy and Infarcted Rat Hearts Using Optical Coherence Tomography Angiography.

Myocardial infarction (MI) is a life-threatening medical emergency resulting in coronary microvascular dysregulation and heart muscle damage. One of the primary characteristics of MI is capillary loss, which plays a significant role in the progression of this cardiovascular condition. In this study, we utilized optical coherence tomography angiography (OCTA) to image coronary microcirculation in fixed rat hearts, aiming to analyze coronary microvascular impairment post-infarction. Various angiographic metrics are presented to quantify vascular features, including the vessel area density, vessel complexity index, vessel tortuosity index, and flow impairment. Pathological differences identified from OCTA analysis are corroborated with histological analysis. The quantitative assessments reveal a significant decrease in microvascular density in the capillary-sized vessels and an enlargement for the arteriole/venule-sized vessels. Further, microvascular tortuosity and complexity exhibit an increase after myocardial infarction. The results underscore the feasibility of using OCTA to offer qualitative microvascular details and quantitative metrics, providing insights into coronary vascular network remodeling during disease progression and response to therapy.

Mapping the associations among task complexity, emotionality, and linguistic complexity in L2 writing

This study explored the relationship between task complexity, textual emotionality, and linguistic complexity in second language (L2) writing. Fifty-eight L2 English learners performed simple and complex versions of an argumentative writing task manipulated along with resource-­directing variables. The essays were first analysed for textual emotionality with sentiment analysis and then examined using a set of lexical and syntactic complexity and cohesiveness indices. Regarding emotionality, the complex task elicited more positive and negative emotions than the simple task. Further, the complex task led to greater lexical complexity and cohesiveness than the simple task, but the two tasks were not statistically different from each other in terms of syntactic complexity features. Varied patterns of correlations were observed between emotionality metrics and indices of different dimensions of linguistic complexity in the two tasks. Our findings focusing on the intersections of cognitive, socio-emotive, and linguistic components suggest that different task complexity manipulations could generate varying cognitive demands, affecting L2 written production. These findings provide theoretical and pedagogical implications for TBLT researchers and L2 writing practitioners.

Complex and highly saturated soundscapes in restored oak woodlands reflect avian richness and abundance.

Temperate woodlands are biodiverse natural communities threatened by land use change and fire suppression. Excluding historic disturbance regimes of periodic groundfires from woodlands causes degradation, resulting from changes in the plant community and subsequent biodiversity loss. Restoration, through prescribed fire and tree thinning, can reverse biodiversity losses, however, because the diversity of woodland species spans many taxa, efficiently quantifying biodiversity can be challenging. We assessed whether soundscapes in an eastern North American woodland reflect biodiversity changes during restoration measured in a concurrent multitrophic field study. In five restored and five degraded woodland sites in Wisconsin, USA, we sampled vegetation, measured arthropod biomass, conducted bird surveys, and recorded soundscapes for five days of every 15-day period from May to August 2022. We calculated two complementary acoustic indices: Soundscape Saturation, which focuses on all acoustically active species, and Acoustic Complexity Index (ACI), which was developed to study vocalizing birds. We used generalized additive models to predict both indices based on Julian date, time of day, and level of habitat degradation. We found that restored woodlands had higher arthropod biomass, and higher richness and abundance of breeding birds. Additionally, soundscapes in restored sites had higher mean Soundscape Saturation and higher mean ACI. Restored woodland acoustic indices exhibited greater magnitudes of daily and seasonal peaks. We conclude that woodland restoration results in higher soundscape saturation and complexity, due to greater richness and abundance of vocalizing animals. This bioacoustic signature of restoration offers a promising monitoring tool for efficiently documenting differences in woodland biodiversity.

Seasonal sonic patterns reveal phenological phases (sonophases) associated with climate change in subarctic Alaska

Given that ecosystems are composed of sounds created by geophysical events (e.g., wind, rain), animal behaviors (e.g., dawn songbird chorus), and human activities (e.g., tourism) that depend on seasonal climate conditions, the phenological patterns of a soundscape could be coupled with long-term weather station data as a complimentary ecological indicator of climate change. We tested whether the seasonality of the soundscape coincided with common weather variables used to monitor climate. We recorded ambient sounds hourly for five minutes (01 January–30 June) over three years (2019–2021) near a weather station in a subarctic ecosystem in south-central Alaska. We quantified sonic information using the Acoustic Complexity Index (ACItf), coupled with weather data, and used machine learning (TreeNet) to identify sonic-climate relationships. We grouped ACItf according to time periods of prominent seasonal events (e.g., days with temperatures >0°C, no snow cover, green up, dawn biophony, and road-based tourism) and identified distinct sonic phenophases (sonophases) for groups with non-overlapping 95% confidence intervals. In general, sonic activity increased dramatically as winter transitioned to spring and summer. We identified two winter sonophases, a spring sonophase, and a summer sonophase, each coinciding with hours of daylight, temperature, precipitation, snow cover, and the prevalence of animal and human activities. We discuss how sonophases and weather data combined serve as a multi-dimensional, systems-based approach to understanding the ecological effects of climate change in subarctic environments.

The challenge of securing growth in times of crises: does economic complexity matter?

ABSTRACT This paper investigates the moderating role of economic complexity in mitigating the negative impact of global economic and financial crises on a country’s economic growth. Utilizing panel data from 133 countries spanning from 1998 to 2021, we employ a robust empirical methodology, considering economic growth as the dependent variable and the Economic Complexity Index (ECI) as the main moderating variable. Three dimensions of ECI, namely Trade, Technology, and Research, are meticulously analysed for their impact on economic resilience during crises. Our findings reveal a consistent negative effect of global crises on economic growth across all specifications. Significantly, economic complexity emerges as a positive moderator, implying that more complex and diversified economies experiencing less severe negative impacts. The nuanced interaction with the Human Development Index (HDI) emphasises the varying importance of economic complexity across different development levels. This study underscores the vital role of economic complexity in enhancing economic resilience during crises, offering policymakers valuable insights for fostering economic diversification, innovation, and adaptability in a dynamic global landscape.

Development and assessment of an abbreviated medication regimen complexity index (the A-MRCI).

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Adaptation of the Medication Regimen Complexity Index (MRCI) for automation in an electronic medical record has the potential to improve medication optimization and patient outcomes. The purpose of this study was to develop and evaluate an abbreviated medication regimen complexity index (A-MRCI) and compare its associations with patient-level factors to those of the MRCI. The MRCI was modified via several rounds of review with an expert panel of clinical pharmacists and outcomes researchers. Medication data from 138 electronic health records were abstracted to calculate MRCI and A-MRCI scores for dosage form, dosing frequency, and additional directions. Comparison between indices was performed using inferential statistics for a 1-month sample of patients admitted to a cardiology or advanced heart failure service in 2017. A-MRCI scores were higher than MRCI scores (mean difference of 3.97, P < 0.0005; 95% CI, 2.21-5.71). A significant association was observed between the A-MRCI score and both length of stay (P = 0.0005) and polypharmacy (P < 0.0005), whereas an association between MRCI score and the patient-level factors examined was not demonstrated. On average, A-MRCI scores were higher and more likely to be associated with several patient-level factors. Internal analyses show the potential for integration into an electronic health record for automation. However, further exploration of the A-MRCI in a larger external validation sample is warranted.

Comorbidities and use of health services in people with diabetes mellitus according to risk levels by adjusted morbidity groups

BackgroundPeople with diabetes mellitus frequently have other comorbidities and involve greater use of primary and hospital care services. The aim of this study was to describe the comorbidities and use of primary and hospital care services of people with diabetes according to their risk level by adjusted morbidity groups (AMG) and to analyse the factors associated with the utilisation of these services.MethodsCross-sectional study. People with diabetes were identified within the population of patients with chronic conditions of an urban health care centre by the AMG stratification tool integrated into the primary health care electronic clinical record of the Community of Madrid. Sociodemographic, functional, clinical characteristics and annual health care services utilisation variables were collected. Univariate, bivariate and Poisson regression analyses were performed.ResultsA total of 1,063 people with diabetes were identified, representing 10.8% of patients with chronic conditions within the health centre. A total of 51.4% were female, the mean age was 70 years, 94.4% had multimorbidity. According to their risk level, 17.8% were high-risk, 40.6% were medium-risk and 41.6% were low-risk. The most prevalent comorbidities were hypertension (70%), dyslipidaemia (67%) and obesity (32.4%). Almost 50% were polymedicated. Regarding health services utilisation, 94% were users of primary care, and 59.3% were users of hospital care. Among the main factors associated with the utilisation of both primary and hospital care services were AMG risk level and complexity index. In primary care, utilisation was also associated with the need for primary caregivers, palliative care and comorbidities such as chronic heart failure and polymedication, while in hospital care, utilisation was also associated with comorbidities such as cancer, chronic obstructive pulmonary disease or depression.ConclusionsPeople with diabetes were older, with important needs for care, many associated comorbidities and polypharmacy that increased in parallel with the patient’s risk level and complexity. The utilisation of primary and hospital care services was very high, being more frequent in primary care. Health services utilization were principally associated with functional factors related to the need of care and with clinical factors such as AMG medium and high-risk level, more complexity index, some serious comorbidities and polymedication.

Dendrochronological analysis of conifers in avalanche catchments of the Northwestern Altai (Korgon River basin)

The purpose of the study was to date the powerful snow avalanches occurred in the avalanche catchment area in the river Korgon basin (Northwestern Altai) by the dendrochronological method. The paper presents the results of the analysis of a number of dendrochronological indicators of avalanches: the age of trees, the relation between widths of annual rings from opposite sides of the trunk, the presence of reactive (compressional) wood and traumatic resin canals, the dates of death and formation of wounds in trees, the presence of clearing effects (a sharp increase in growth) in three avalanche catchments, as well as a complex dendrochronological index of the avalanche activity. The dates of releases of the powerful avalanches were established down to 1570. It has been found that against the background of increasing amount of winter precipitation in these catchments, there are different trends in occurrence of the avalanches, which is determined by their morphological properties. In the avalanche areas with steeper slopes, due to repeated unloading of the avalanche centers in winter, the probability of releasing of powerful avalanches decreases. For the same reason, the powerful avalanches do not release during the years of maximum snow accumulation. The trends in the avalanche activity in the region under consideration had been obtained for the first time. The dendrochronological index of the avalanche activity, which is the ratio of the number of the tree growth failures to the number of the examined trees, is a good indicator of a release of a powerful avalanche even at a value of 0.85, provided that the number of examined trees in the lower part of the transit zone and in the zone of accumulation is 25–35 units. The results of this study may be used to predict the territorial differentiation of changes in the avalanche activity due to climate change. In connection with the recreational development of the Altai territory, they may also be of practical importance.

Performance Evaluation of Multiple Aging-Regeneration of SBS-Modified Bitumen Regenerated by a Composite Rejuvenator

In this study, compound regeneration of SBS-modified bitumen (SMB) was carried out by a composite rejuvenator composed of furfural extraction oil (FEO) and 1,6-hexanediol diglycidyl ether (HDDGE) in the presence of catalyst triethanolamine (TEOA). SMB was subjected to three aging-regeneration cycles, and the physical and rheological properties, toughness and tenacity, and chemical structures of the SMB after each aging-regeneration cycle were tested to investigate the regeneration effect of the composite rejuvenator on SMB at different numbers of cycles. The ductility decreases and low-temperature properties deteriorate as the number of cycles increased, but the high-temperature properties of the SMB are improved. The complex modulus aging index and phase angle aging index indicate that the viscous behavior of SMB weakens after the second and third aging. The degree of viscoelasticity and toughness recovery decreases with the increase in the number of cycles, and the tenacity of SMB after the third aging-regeneration cycle is basically lost. The results of the Fourier transform infrared (FTIR) spectra tests prove that with the increase in the aging–regeneration cycles of SMB, the intensity of FTIR peaks of oxygen-containing functional groups is greater, and the recovery of aged SMB is gradually weakened.

Virtual Reality Technology in Analysis of the Sarek National Park Soundscape in Sweden

The paper presents an in-depth analysis of the soundscape within Sarek National Park, the oldest national park in Europe, situated in Lapland, northern Sweden. The comprehensive acoustic measurements, ambisonic recordings, and 360X video recordings were carried out during a scientific expedition in the summer of 2020. The aim of the paper is to show the soundscape analysis of carefully selected characteristic locations in various parts of the valley. The paper extensively discusses the findings derived from the recorded data using both classical acoustic methods and the soundscape approach. The classic acoustic parameters, commonly employed in environmental acoustics as well as eco-acoustic indices such as: ACI (acoustic complexity index), ADI (acoustic diversity index), AEI (acoustic evenness index), NDSI (normalized difference soundscape index), BIO (energy level of biophony), amplitude index (M), and total entropy (H) were calculated. To gain further insights, listening tests, facilitated through virtual reality tools, were conducted, enabling participants to engage in soundwalk experiences. By employing a combination of traditional acoustic methods and innovative soundscape approaches, the paper presents a holistic evaluation of the auditory environment in Sarek National Park. The main contribution of the presented research is providing new data from the unique, geographically inaccessible region of the world, the Sarek National Park. This research not only enriches our understanding of the national park’s soundscape but also offers valuable insights into the interaction between the natural environment and human perception of sound.

Low-Budget Households in the Conditions of Digitalization in US Regions

The digitalization of the economy and society of the highly developed countries, along with technological improvements in production and social relations, introduces a number of significant problems associated with the widening income gap and the flow of the economically active population from the knowledge economy to the “traditional activity” sectors. The subjective expression of this process in the 21st century Low Budget Families, an increase in the share of which has been observed in the United States during the period of increased digitalization and reindustrialization, starting in 2010. The growth trend of Low Budget Families in the United States has an intra-country spatial nature, quantitatively and qualitatively different both at the level of subregions and individual states of the country. The regional aspects of the relationship between the growth of the share of Low Budget Families, depending on the level of digitalization of the economy and society, reflected through the corresponding “complex index”, considered in the article, find empirical confirmation, generally characterized by a direct dependence and causality associated with the release of an increasingly significant number of labor potential from the advanced sectors of the economy. The problem of the flow of economically active citizens, who represent the basis of Low Budget Families in which the level of official income, taxes, consumption and savings is declining, is being solved differently in different US states. Based on a comparison of the criteria for identifying Low Budget Families, a priority for the authorities of various regions of the country, a general “spatial picture” of polarization of subregions and states is formed based on the share of Low Budget Families, depending on the level of digitalization and the choice of directions of state regional policy to smooth out the negative problems of inequality and hidden employment, caused by the digital transformation of social relations.

Hazardous wildfire smoke events can alter dawn soundscapes in dry forests of central and eastern Washington, United States

As global wildfire activity increases, wildlife are facing greater exposure to hazardous smoke pollution – with unknown consequences for biodiversity. Research on the effects of smoke on wild animals is extremely limited, in part due to the inherent logistical challenges of observing how animals respond to smoke in real time. Passive acoustic monitoring may be a powerful tool to safely and effectively monitor biodiversity before, during, and after major smoke events. In this study, we used data collected from a large-scale network of bioacoustic recorders at 92 sites in central and eastern Washington state during August–September, 2019–2020 to investigate the effect of wildfire smoke on dawn soundscapes and, by extension, acoustically active wildlife. We used acoustic indices to document and characterize changes in soundscapes related to smoke exposure, including the Acoustic Complexity Index (ACI), Bioacoustic Index (BI), and Normalized Difference Soundscape Index (NDSI). Higher values of these indices likely indicate higher levels of biodiversity in our study area. We hypothesized that wildfire smoke would reduce bird vocalizations, leading to declines in ACI, BI, and NDSI at dawn, when birds are most active. We used linear and quantile regression models to test for an effect of daily exposure to fine particulate matter (PM2.5), a marker of wildfire smoke, on the mean daily values and the upper 90th percentile of each index at dawn. We also conducted a before-during-after analysis of a particularly hazardous smoke event that impacted our study area on September 12–14, 2020. We did not observe linear effects of daily PM2.5 on average or peak daily values of acoustic indices; however, we did observe a significant reduction in ACI and BI during the three-day smoke event in 2020 and in the two weeks following this air pollution episode. Our results indicate that, on average, ACI and BI were reduced by 2.7 % and 15.9 % during and 1.5 % and 11.0 % afterward, respectively. These findings add further evidence that wildfire smoke alters soundscapes, likely due to changes in the presence, abundance, or behavior of acoustically active animals. Furthermore, our study demonstrates that wildfire smoke may have delayed and/or cumulative effects on acoustically active wildlife. Our study highlights the potential for passive acoustic monitoring to document wildlife responses to smoke pollution and identify potentially relevant exposure periods.

Model of Growth of the Region’s Economy Based on the Index of Economic Complexity

Model of Growth of the Region’s Economy Based on the Index of Economic Complexity

The role of agroforestry in solving the agricultural landscapes vulnerabilities in the Po Plain district

AbstractThe current trend of biodiversity deterioration in rural systems is a complex issue that operates across multiple spatial scales. Agroforestry practices have the potential to positively contribute towards addressing these trends by shaping the structure of agricultural landscapes and their underlying ecological functions. This study aims to test a multi-scale analytical approach to understand and account for these processes. Specifically, the study seeks to assess the contributions that agroforestry practices at the farm scale can make towards supporting biodiversity, in response to the wider-scale landscape eco-mosaic structural and functional challenges and requirements (both at the local and extra-local landscape systems). To achieve this, a series of landscape ecology analyses are conducted on an agroforestry-based rice farm located in the western Po Plain region of Northern Italy. These analyses examine various landscape structural traits (such as matrix composition, patch size, shape complexity, and diversity indices) and functional traits (including connectivity and bionomic indices), with different levels of detail for each scale of analysis. This allows for the evaluation of the current ecological status of both the extra-local and local scale landscape systems (including drivers of vulnerability and resilience) and the assessment of the farm's current contributions to biodiversity support. Based on these findings, strategic agroforestry interventions are identified at the farm scale to enhance its capacity to address the wider-scale ecological gaps. Two design scenarios are assessed, wherein functional ecological traits such as landscape diversity, connectivity, and ecological stability are improved. The results confirm the role of farm scale agroforestry management as a buffering tool, demonstrating how it contributes to the restoration of broader-scale landscape vulnerabilities. The applied approach provides cost-effective assessments of biodiversity-related ecological processes, with the accuracy of the findings dependent on the comprehensive multi-scale analysis conducted.

Nexus of natural resources exploitation, social protection, and sustainable environment: COP27 is a sufficient solution?

A pervasive threat regarding human health, ecological balance, progress, and sustainability marks the current era. Many nations are grappling with the consequences of climate change and global warming caused by excessive carbon emissions from various harmful activities. Consequently, while some nations face resource constraints, they also work hard to keep the environment clean and green to promote sustainable growth. Concerns about the effects of climate change and global warming have recently shifted the focus of national governments and policymakers. Furthermore, these issues take center stage in developed nations due to the scarcity of natural resources, leading to increased carbon emissions. This research uses a panel data set that covers the top 20 developed countries from 2000 to 2021 to examine the relationship between nature's bounty (NAT) and welfare (SP) and carbon emissions (CO2). The next-generation panel assembly root test verified that all indicators were stationarity at the first difference, and the cross-sectional dependence (CSD) mirrored the panel countries' CSD. The second-generation cointegration technique (Wester Lund and Edgerton) was used to find an equation involving the variables. The rigorous check by the Cup-BC test and long-run empirical estimates from the Cup-FM estimation highlighted that technical innovation, social protection, and higher levels of green energy contribute to greater environmental sustainability and lower CO₂ emissions. Environmental quality declines and CO2 emissions rise in developed countries due to population, natural resource availability, and economic complexity index. The study's results may illuminate the reasons for environmental deterioration and propose solutions.