Loss Of Area Research Articles

A blue–green ratio of urban wetlands as an ecosystem health indicator: the case of urban sprawl in Nagpur, India

ABSTRACT Rampant urban sprawl has affected the structure and function of existing urban green and blue spaces, exposing developing cities to unexpected disaster events. Drawing on a mixture of secondary information supported by GIS and field-based studies, we assessed the impact of growing impervious surfaces on the dynamic zones of urban wetlands in Nagpur, India. We compared decadal data (2000-2020) to understand the pattern of wetland loss and its drivers in the region. Our findings reveal a significant loss of wetland structure and area over the past two decades, raising alarming concerns regarding ecological and economic repercussions. To address these issues, we propose a blue–green buffer-based assessment approach that incorporates local knowledge and observations along with proactive monitoring of ecosystem health. Our study highlights the urgency of reducing the spatial complexity of landscape patches, restoring wetland buffers, declaring wetland buffers as no-go zones, and promoting corridor connectivity to urban wetlands to improve urban blue infrastructure health. Multi-sectoral and stakeholder cooperation, involvement, and strict enforcement of the Wetland Rules (2017) by local governing bodies can help build urban resilience by protecting urban blue–green infrastructure.

Modeling future projections of land use and land cover in the Kakataibo territory

Abstract. The Amazon region is undergoing a dynamic and extensive transformation from forested areas to human-altered landscapes, significantly impacting forests and indigenous territories. This research aims to create future land use and land cover (LULC) scenarios by examining past trends (2014–2022) and predicting future patterns for 2030, focusing on the Kakataibo territory in central Peru. Using the Dinamica EGO modelling platform, we projected LULC changes based on historical data and various predictive factors. Our findings reveal notable forest loss between 2014 and 2022, with this trend likely continuing through 2030. Within indigenous territories, deforestation was less severe, with a reduction of 30,247.4 hectares compared to the more significant loss in non-indigenous areas. This underscores the vital role these territories play in mitigating forest loss. However, the rapid expansion of agriculture and infrastructure within these regions signals an urgent need for stronger legal protections to halt further deforestation. This study highlights the critical importance of indigenous territories in forest conservation and offers valuable insights for future land management and conservation strategies in the Amazon.

Florida mangrove dieback on a decadal and centennial timescales

Hurricanes are considered some of the most devastating weather phenomena, causing deaths and destruction along the coast. Mangroves are perceived as natural defenses against coastal hazards. However, mangrove gaps, known as mangrove dieback, have occurred in southwestern Florida. This study implemented a spatial-temporal analysis based on satellite, lidar and unmanned aerial vehicle (UAV) images collected along the southwestern Florida coast between Tampa and Naples from 1994 to 2020 CE, and multi-proxy analyses on sediment cores sampled from two mangrove dieback sites to determine the cause(s) of mangrove death and the implications for the sustainability of these forests. The data indicated that out of the 86 identified dieback, 78 % arose between 2004 and 2017 CE, when one tropical storm and three hurricanes made landfall on the studied coast, suggesting hurricanes as the main driver for this mangrove degradation. Multi-proxy analysis indicated mangrove expansion since ~600 cal yr BP due to relative sea-level (RSL) rise. However, hurricanes caused losses in the mangrove area between 1930 and 1950 CE, and during the last two decades in the studied sites. Ground topographic data and aerophotogrammetry revealed circular dieback with permanent ponds (~30 cm depth) inhibiting mangrove recovery. The mangrove death occurred in <3 years, with a gradual dieback expansion due to positive feedback involving physicochemical processes in the sediments. In addition, recent hurricanes increased pre-existing dieback areas. Therefore, dieback sites are vulnerability hotspots for mangroves in the face of projected RSL rise and higher frequency of intense hurricane strikes. Mangrove dieback should be monitored on a temporal (seasonal - annual) and spatial (cm-m) resolution only possible through the combination of satellite and UAV data. Integrating remote sensing and stratigraphic analysis enabled us to identify mangrove diebacks on a decadal to centennial timescale, improving our comprehension of how catastrophic weather events affect these forests.

Automatic detection of landslide impact areas using Google Earth Engine

This research introduces an effective framework for automatically detecting landslide impact areas using Google Earth Engine (GEE). The Asia–Pacific region frequently experiences earthquakes and heavy rainfall, leading to frequent landslides that cause loss of life and property. Focusing on landslide catalogues from Taiwan and Japan, the study proposes an automatic landslide detection process using a new method termed multi-bitemporal images (MBTIs), which involves the collection of accumulated changes over time. First, set the event date and collect all images before and after the event. Second, analyse the change pixels in bi-temporal images. Third, review all change pixels to determine the total amount of accumulated changes. This method includes all bi-temporal image sets in the analysis, unlike traditional methods that only use single pairs of bi-temporal images. Clouds are filtered using a pixel-based approach and machine learning techniques. The landslide areas are analysed statistically, and appropriate thresholds for automatic landslide detection are suggested. Using reproducibility, which indicates the percentage of bi-temporal images that detect vegetation loss in mountainous areas, the proposed method achieves a 99% reduction in false positives with a reproducibility requirement of 24.21%, while maintaining true positives at 66.89%. This study analyzed 28–720 bi-temporal image sets from various regions using Sentinel-2 data, revealing that subsequent landslides can be 7–293 times larger than co-seismic landslides. In comparison, subsequent landslides were found to be 3–12 times larger than rainfall-induced landslides. Additionally, the impact of earthquake event on subsequent landslides is 2.3–24.4 times greater than that of rainfall-induced event. By using GEE, the accumulation of hundreds of satellite images can be completed within 15 min, depending on the processing requirements.

Evolution characteristics of mining-induced fractures in overburden strata under close-multi coal seams mining based on optical fiber monitoring

Large-scale mining fractures resulting from repeated mining are a major cause of surface water loss in the northern Shaanxi mining area, China. Accurately detecting the evolution of mining-induced fractures is crucial for addressing the fragile ecological environment and ensuring coalmine production safety in this area. This study focuses on the close-multi coal seams mining at the Ningtiaota coalmine, northern Shaanxi, China, investigating the failure types of overburden rock, the evolution of mining-induced fractures, and the height of fracture zones. The results indicate that the failure type of overburden strata transforms from a “trapezoid shape” to an “overlapping trapezoid shape”, with the fracture zone height extending from 64.5 m to 158.5 m due to the superposition of secondary mining. Furthermore, the evolution characteristics of mining-induced fractures shift from a “three-stage and three-step” model to a “three-stage and two-step” model. A characterization model of overburden deformation based on optical fiber sensing is proposed to effectively describe the strain distribution characteristics of overburden failure. This model reveals the spatiotemporal evolution of overburden deformation from the perspective of “horizontal three areas and vertical three zones”, enabling real-time characterization of overburden deformation. The results demonstrate a relative error of less than 5.0 % between optical fiber monitoring and other methods, excluding theoretical calculations. This study offers a technical solution for detecting mining-induced fractures in the northern Shaanxi mining area and holds significant implications for broader studies of overburden deformation and failure under repeated mining.

Synthesis of a lightweight and dual-band (K and Ka-band) microwave absorber based on cobalt ferrite/mesoporous carbon nanocomposite for stealth technology

Mesoporous carbon has gained significant attention as microwave absorber owing to its lightweight, high surface area and dielectric loss. Herein, for better impedance matching, CoFe2O4/mesoporous-carbon hybrid nanocomposites were synthesized with different content of mesoporous-carbon via a facile hydrothermal method and systematically investigated their K and Ka-band microwave absorption properties. RAMAN analysis establishes the strong interaction amid CoFe2O4 and mesoporous-carbon. Magnetic study confirmed the ferromagnetic nature of the nanocomposite which is helpful for high frequency range absorbers. The CoFe2O4/MC-60 nanocomposite presents a reflection loss of −51 dB at 2.5 mm thickness with an effective absorption bandwidth of 4.2 GHz. The |Zin/Z0| value for this hybrid nanocomposite was closer to 1. The superb absorption properties can be ascribed to best impedance matching and the synergistic effect of the heterogeneous interfaces between CoFe2O4 nanoparticles and carbon. This work can advance the development of magnetic/carbon absorber for high speed communication and military fields.

Employing deep learning in crisis management and decision making through prediction using time series data in Mosul Dam Northern Iraq

Specifically, Iraq is threatened in its second-largest northern city, Mosul, by the collapse of the Mosul Dam due to problems at the root of the dam, causing a wave of floods that will cause massive loss of life, resources, and public property. The objective of this study is to effectively monitor the level of dam water by predicting the level of water held by the dam In anticipation of achieving flood stage and breaking the dam, and supporting its behavior through formation 14-day time series data to predict seven days later. Used six deep learning models (deep neural network (DNN), convolutional neural network (CNN), convolutional neural network long short-term memory (CNN-LSTM), CNN-LSTM-Skip and CNN-LSTM Skip Attention) that models were trained to predict the water level in the dam; these levels of being under surveillance and prepared In case of danger, alert people to potential flood threats depending on the dam’s water level. These time series were created from the actual data sets of the dam; it’s a fundamental historical reading for 13 years (1993–2006) of the water level stored in the Mosul dam and was adopted in coordination with the Iraqi Ministry of Water Resources and the Centre for Research on Dams and Water Resources at Mosul University. The methodology applied in this study shows the model’s performance efficiency and the prediction results’ low error rate. It also compares those practical results to determine and adopt the performance-efficient model and a lower error rate. The comparison of these results proved the accuracy of its results, and superior to the CNN-LSTM model, it has the highest ability to perform through high accuracy with MAE = 0.087153 and time steps = 0 s 196 ms/step and loss = 0.00067. The current study demonstrated the ability to predict the water level in Mosul Dam, which suffers from foundation problems and may collapse in the future. Therefore, the water level in the dam must be monitored accurately. It also aims to test the effectiveness of the six models proposed in this study after evaluating their performance and applying the prediction process within a scenario to obtain predictive values after 14 days. The results showed the practical effectiveness of the hybrid CNN-LSTM model in correctly and accurately obtaining predictive values within the integrated framework of the required scenario. The study concluded that it is possible to enhance the ability to monitor and identify the potential risk of Mosul Dam at an early stage, and it also allows for proactive crisis management and sound decision-making, thus mitigating the adverse effects of crises on public safety and infrastructure and reducing human losses in areas along the Tigris River.

The Effect of the Root Bark of Lycium chinense (Lycii Radicis Cortex) on Experimental Periodontitis and Alveolar Bone Loss in Sprague-Dawley Rats

Lycii Radicis Cortex (LRC), the dried root bark of Lycium chinese Mill., has traditionally been used as a medicinal herb in East Asia to treat fever and hyperhidrosis. In the present study, we investigated the effects of LRC extract on ligation-induced experimental periodontitis and associated alveolar bone loss in rats. Twenty-four hours after ligation placement, LRC was orally administered once daily for 10 days. Firstly, LRC administration inhibited anaerobic bacterial proliferation and inflammatory cell infiltration in gingival tissues. Additionally, LRC exhibited anti-inflammatory effects by reducing the expression of inflammatory mediators, including prostaglandin E2, interleukin-1β, and tumor necrosis factor-α. LRC treatment also downregulated mRNA expression of these inflammatory mediators in lipopolysaccharide-stimulated RAW 264.7 cells by inhibiting the mitogen-activated protein kinases and nuclear factor-κB (NF-κB) signaling pathways. Furthermore, LRC showed an antioxidant effect by decreasing the malondialdehyde level and inducible nitric oxide synthase activity in gingival tissues. Moreover, LRC effectively prevented the connective tissue degradation by inhibiting matrix metalloproteinase-8 expression and the loss of collagen-occupied areas in gingival tissues. LRC also decreased the receptor activator of NF-κB ligand/osteoprotegerin (RANKL/OPG) ratio, as well as the number and occupied areas of osteoclasts on the alveolar bone surface, thereby inhibiting alveolar bone loss. In summary, these findings suggest that LRC is a promising medicinal herb for alleviating periodontitis and related alveolar bone loss through its antimicrobial, anti-inflammatory, and antioxidant properties.

Comparison of Short Fast Fourier Transform and Continuous Wavelet Transform in Study of Stride Interval

Neurodegenerative diseases (NDD) are a heterogeneous group of complex diseases characterized by neuronal loss and progressive degeneration of different areas of the nervous system. Gait analysis presents an early recognition system for NDD which is important to increase the patient’s awareness of their health conditions. However, it is very difficult to identify and formulate suitable digital biomarkers from the data collected from gait experiments such as stride interval and swing. The objective of this paper is to compare the result of Short - Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) on the collected stride interval of healthy young people and healthy old people. In this paper, STFT and CWT are performed on the collected stride interval and from the result of the STFT and CWT, further features are extracted like instantaneous RMS and maximum RMS value. STFT is performed on the collected stride interval from a window length of 64 to 512 while CWT is performed on the collected stride interval from the scale of 128 to 2048. The processing time of the STFT and CWT with varied window lengths and scales respectively are collected. Besides, the actual maximum time from the time - frequency plot derived from STFT and CWT is also collected. Both STFT and CWT show that the young group has a higher maximum RMS, an indication of higher stride interval than the old group and higher variance, an indication of higher gait complexity. The suitable window lengths for STFT in analyzing the stride interval are 64 and 128 while the scale for CWT should be set to the lowest scale. Overall, STFT with a window length of 64 and 128 is better in analyzing the stride interval due to low processing time at the expense of slightly less accurate time - frequency representation.

Mild cognitive impairment in amyotrophic lateral sclerosis: current view.

Amyotrophic lateral sclerosis (ALS) is a fatal multi-system neurodegenerative disorder with no effective treatment or cure. Although primarily characterized by motor degeneration, cognitive dysfunction is an important non-motor symptom that has a negative impact on patient and caregiver burden. Mild cognitive deficits are present in a subgroup of non-demented patients with ALS, often preceding motor symptoms. Detailed neuropsychological assessments reveal deficits in a variety of cognitive domains, including those of verbal fluency and retrieval, language, executive function, attention and verbal memory. Mild cognitive impairment (MCI), a risk factor for developing dementia, affects between 10% and over 50% of ALS patients. Neuroimaging revealed atrophy of frontal and temporal cortices, disordered white matter Integrity, volume reduction in amygdala and thalamus, hypometabolism in the frontal and superior temporal gyrus and anterior insula. Neuronal loss in non-motor brain areas, associated with TDP-43 deposition, one of the morphological hallmarks of ALS, is linked to functional disruption of frontostriatal and frontotemporo-limbic connectivities as markers for cognitive deficits in ALS, the pathogenesis of which is still poorly understood. Early diagnosis by increased cerebrospinal fluid or serum levels of neurofilament light/heavy chain or glial fibrillary acidic protein awaits confirmation for MCI in ALS. These fluid biomarkers and early detection of brain connectivity signatures before structural changes will be helpful not only in establishing early premature diagnosis but also in clarifying the pathophysiological mechanisms of MCI in ALS, which might serve as novel targets for prohibition/delay and future adequate treatment of this debilitating disorder.

Spiral shaped highly sensitive rectangular PCF-based cancer cells detector in terahertz regime

Abstract The increasing fatality rate of cancer in the modern world has become a global concern. To address this issue, early detection of cancer cells in human blood is essential. In this article, a rectangular spiral shaped photonic crystal fiber has been proposed for sensing cancer cells in terahertz regime. The proposed PCF based sensor features a square shaped core surrounded by rectangular air holes of different sizes in a spiral manner. Finite element method based COMSOL Multiphysics software has been used for the design and analysis of the model. The model is sensitive to refractive index variation for the identification of cancer cells. The values of effective refractive index, effective mode area, relative sensitivity, non-linearity, and confinement loss are obtained for MCF-7, MDA-MB-231, Jurkat, HeLa, Basal and PC-12. The PCF based sensor resulted in excellent results of relative sensitivity and Confinement loss as good as 99.377% and 8.59 × 10−12 dBm−1 respectively. Furthermore, the present PCF based sensor model is fabrication feasible, and we hope that it can be utilized at industrial level for biosensing applications in terahertz waveguide regime.

Evaluating the performance of water distribution network deterioration using customer-oriented performance indices

ABSTRACT Water distribution networks (WDNs) are an essential urban infrastructure, with their performance directly influencing societal well-being. Our study applied to a real network model that employs a 24-h simulation with 1-h time steps and evaluates the impact of leaks and loss in the pipe cross-sectional area on WDN hydraulic performance as experienced by end users. Adhering to a UK utility's 20-m head pressure requirement as the water main benchmark, we present two new customer-oriented performance indices (CPIs) centred on network reliability and pressure deficit severity. The new CPIs adeptly quantify network performance degradation due to pipe deterioration. This degradation translates directly to a poor customer experience, highlighting the potential for these CPIs to pinpoint areas of the network where performance levels are compromised. Furthermore, the CPIs identify individual pipes within the network where defects would severely impact network performance and the sets of pipes which, when simultaneously experiencing defects, would lead to a more severe loss in network performance. Results show that the CPIs capture relatively small performance declines and identify sensitive pipes impacting network performance, providing insights for optimised inspection and maintenance intervention to provide better customer service.

Short‐Term Grasslands in Agriculture Support Both Natural Enemy and Phytophagous Arthropod Populations

ABSTRACTSimplified agricultural land with high chemical input is increasingly replacing natural habitats in many parts of the world. This loss and fragmentation of natural areas may have profound impacts on an array of wildlife, including predatory arthropods that provide natural biocontrol of agricultural pests. There is increasing interest in utilising short‐term seminatural habitat restoration in agricultural systems to support populations of beneficial organisms. We assessed the impact of two types of short‐term set‐asides on the diversity and abundance/activity density of phytophagous and predatory arthropods. We found that flower‐enhanced set‐asides supported higher abundances of both phytophagous and predatory arthropods compared to control crop fields. In addition, we found that both set‐aside types (flower enhanced and traditional) supported a more active and diverse community of beneficial predatory carabid beetles, with particularly strong trends in set‐asides supplemented with flowering plants. These results suggest that small‐scale, temporary, seminatural habitats in agricultural systems provide support for a diverse and abundant community of both beneficial and phytophagous arthropods.

White matter protection with insulin-like growth factor-1 after hypoxia-ischaemia in preterm foetal sheep.

Perinatal hypoxia-ischaemia in extremely preterm infants is associated with long-term neurodevelopmental impairment, for which there is no specific treatment. Insulin-like growth factor-1 can reduce acute brain injury, but its effects on chronic white matter injury after hypoxia-ischaemia are unclear. Preterm-equivalent foetal sheep (0.6 gestation) received either sham-asphyxia or asphyxia induced by umbilical cord occlusion for 30 min, and recovered for either 3 or 35 days after asphyxia. The 35 day recovery groups received either an intracerebroventricular infusion of insulin-like growth factor-1 (1 µg/24 h) or vehicle, from 3 to 14 days after asphyxia. Asphyxia was associated with ventricular enlargement, and loss of frontal and parietal white matter area (P < 0.05 versus sham-asphyxia). This was associated with reduced area fraction of myelin basic protein and numbers of oligodendrocyte transcription factor 2 and mature, anti-adenomatous polyposis coli-positive oligodendrocytes in periventricular white matter (P < 0.05), with persistent inflammation and caspase-3 activation (P < 0.05). Four of eight foetuses developed cystic lesions in temporal white matter. Prolonged infusion with insulin-like growth factor-1 restored frontal white matter area, improved numbers of oligodendrocyte transcription factor 2-positive and mature, anti-adenomatous polyposis coli-positive oligodendrocytes, with reduced astrogliosis and microgliosis after 35 days recovery (P < 0.05 versus asphyxia). One of four foetuses developed temporal cystic lesions. Functionally, insulin-like growth factor-1-treated foetuses had faster recovery of EEG power, but not spectral edge. Encouragingly, these findings show that delayed, prolonged, insulin-like growth factor-1 treatment can improve functional maturation of periventricular white matter after severe asphyxia in the very immature brain, at least in part by suppressing chronic neural inflammation.

Rising forest exposure and fire severity from climate warming amplify tree cover losses from wildfire in California

Abstract Warmer temperatures and severe drought are driving increases in wildfire activity in the western United States, threatening forest ecosystems. However, identifying the influence of fire severity on tree cover loss (TCL) is challenging using commonly used categorical metrics. In this study, we quantify regional trends in wildfire-driven TCL as the product of annual burned area, average forest exposure (pre-fire tree cover), and average fire severity (relative loss of tree cover). We quantified these trends with Landsat-based 30 m resolution fire and tree cover datasets for California wildfires from 1986–2021. Rates of TCL rose faster than trends in burned area, with the magnitude of tree cover area loss per unit of area burned increasing by 70% from 0.20 ± 0.05 during 1986–1996 to 0.34 ± 0.10 during 2011–2021. Forest exposure (pre-fire tree cover) within fires increased by 41% from a decadal mean of 23.4% ± 5.5% (1986–1996) to 33.1% ± 7.8% (2011–2021). Increasing forest exposure is associated with a recent expansion of fires in dense northern forests. Concurrently, fire severity (relative TCL) rose by 30% from a decadal mean of 50.4% ± 7.2% during 1986–1996 to 65.6% ± 6.5% during 2011–2021. We developed and applied a simple conceptual framework to quantify the combined effect of wildfires affecting denser forests and burning more severely. The combined effect of these two processes contributed to nearly half (47%) of the TCL since 1986, highlighting that recent changes in burned areas alone cannot explain observed tree cover trends. Linear regression analysis revealed that warmer summers and drier winters were significant drivers of increasing forest exposure, fire severity, and burned area (R 2 from 0.54 to 0.80, p ⩽ 0.001), particularly in the northern forests. Climate extremes had a disproportionate impact on dense forests that were once more resistant to wildfire but now face risks from a shifting wildfire regime.

Genetic diversity loss in the Anthropocene will continue long after habitat destruction ends.

Genetic diversity within species is the basis for evolutionary adaptive capacity and has recently been included as a target for protection in the United Nations' Global Biodiversity Framework (GBF). However, there is a lack of reliable large-scale predictive frameworks to quantify how much genetic diversity has already been lost, let alone to quantitatively predict future losses under different conservation scenarios in the 21st century. Combining spatio-temporal population genetic theory with population genomic data of 18 plant and animal species, we studied the dynamics of genetic diversity after habitat area losses. We show genetic diversity reacts slowly to habitat area and population declines, but lagged losses will continue for many decades even after habitats are fully protected. To understand the magnitude of this problem, we combined our predictive method with species' habitat area and population monitoring reported in the Living Planet Index, the Red List, and new GBF indicators. We then project genetic diversity loss in 13,808 species with a short-term genetic diversity loss of 13 - 22% and long-term loss of 42 - 48% with substantial deviations depending on the level of habitat fragmentation. These results highlight that protection of only current habitats is insufficient to ensure the genetic health of species and that continuous genetic monitoring alone likely underestimates long term impacts. We provide an area-based spatio-temporal predictive framework to develop quantitative scenarios of global genetic biodiversity.

Differences in Anthropogenic Impacts of Typical Mid- to High-Latitude Wetlands in the Heilongjiang Basin

Wetlands represent one of the three principal ecosystems and serve a vital function in the protection of water resources and the regulation of climate. However, wetlands are currently experiencing significant challenges, particularly in the agriculturally productive wetlands of the Heilongjiang River Basin, which have been considerably impacted by human activities. This study focuses on three representative wetlands situated within the Heilongjiang River Basin. This study analyses changes in wetland area and landscape patterns from 2002 to 2022, as well as the impact of agriculture and impervious surface expansion on the wetlands. The findings indicate that agricultural expansion is the primary driver of wetland area loss. The wetland area affected by agriculture demonstrates the most significant change, with the largest observed shift reaching 47.2%. The expansion of impervious surfaces was found to have a significant impact on wetland fragmentation, resulting in a notable decrease in wetland connectivity. This was evidenced by a reduction in the average patch size, which decreased by 14.68 ha over the decade from 2007 to 2017, a period during which impervious surfaces expanded. This paper identifies the distinctions in the influence of diverse human activities on wetland landscape patterns in the Heilongjiang Basin and employs natural samples for control, thereby attenuating the impact of the natural environment. This study offers a novel perspective on the processes of wetland change and the maintenance of wetland health, which is crucial for the realisation of clean water and sanitation (Sustainable Development Goal 6.6).

Monitoring and assessing of sustainable development in the urban area of Ouagadougou based on SDG 11.3.1 indicator and the city biodiversity index

Urban growth can induce changes in the use and transformation of urban land. In the context of rapid urbanization, monitoring key indicators of sustainable development is essential. The aim of this study was to monitor and assess the level of sustainable development in the city of Ouagadougou between 2002 and 2022, based on global indicators such as Sustainable Development Goal 11.3.1 indicator and the Singapore City Biodiversity Index. A remote sensing and Geographic Information System approach was used to acquire and analyze open-source geospatial data. The results show an increasing inefficiency in land use, with excessive consumption to population growth until 2013. Between 2013 and 2022, this trend declined, but urban biodiversity nevertheless decreased significantly, with a 40% loss of natural areas between 2002 and 2022. Fragmentation of natural areas, due to infrastructure development, has amplified this degradation, posing ecological risks to the city. This study underlines the importance of strengthening the ecological connectivity of urban spaces to improve their sustainability and resilience. It also recommends reorienting urban strategies by integrating nature-based solutions and placing biodiversity preservation at the heart of sustainable urban development policies.

Humidity-Induced Degradation Mapping of Pt3Co ORR Catalyst for PEFC by In-Operando Electrochemistry and Ex Situ SAXS.

Understanding the degradation mechanisms of Pt-alloy catalysts is crucial for enhancing their durability. This study investigates the impact of relative humidity on Pt and Pt3Co catalysts using potential-cycling-based accelerated stress tests. Two conditions are investigated: 100% relative humidity on both sides, and a gradient with 30% at the anode and over 100% at the cathode. Pt3Co demonstrates sensitivity, with 77% performance loss and reductions in electrocatalyst surface area. Results demonstrate a 30% decrease in potential loss for Pt catalysts and a 77% increase for Pt3Co catalysts, indicating significant performance degradation in high humidity conditions, with Pt3Co exhibiting greater sensitivity. Measurements of electrochemically active surface area reinforce these findings. Resistance analysis using electrochemical impedance spectroscopy using equivalent circuit modeling reveals a threefold increase in Pt3Co MEAs' cathode charge transfer resistance and mass transport resistance during accelerated stress tests. Local current distribution analysis highlights differences between Pt catalyst and Pt3Co, with the latter displaying dealloying effects. Small-angle X-ray scattering reveals changes in particle and cluster sizes, indicating structural changes. Scanning electron microscopy highlights catalyst and membrane thickness variations, suggesting heterogeneity in Pt3Co. Under humidity gradients, Ostwald ripening plays a significant role in altering the catalyst's Pt3Co structure and subsequently impacting its performance.

Estimation of the soil erosion and sediment trapping using Gerlach troughs in different Land Uses in Luangprabang Province

This study aims to study sediment loss in different areas by collecting data from the Reservoir and Gerlach troughs in the Luangprabang Province, Laos The implementation of this experiment was a selection of study areas to install soil sediment retention tools (Gerlach trough) according to 6 treatments such as T1: No teak+Ruzi grass; T2: No teak + Fallow; T3: Teak with low understory density + Natural regrowth; T4: Teak with low understory density + Ruzi grass; T5: Teak with high understory density+ Natural regrowth; T6: Teak with high understory density+ mixed fodder cover (Ruzi and Napier grass). In 3 replicates/treatments by RCBD design, a total of 18 instruments will be installed by installing them in a row on both sides of the soil, to trap the soil sediment that flows with the water, then there will be a collection of samples that can be collected, and then filter the soil sediment and dry it at a temperature of 105 degrees, for a period of 48 hours and calculate the amount of soil sediment loss in the area. Results found that the highest soil loss (sediment) was in the area planted teak with low understory density + Natural regrowth (T3) followed by the area planted teak with low understory density + Ruzi grass, (T4), and the lowest soil loss was in the area no teak+Ruzi grass (T1) and the area no teak + fallow (T2). While the highest surface water runoff was in the area planted teak with low understory density + Natural regrowth (T3) and the area planted teak with low understory density + Ruzi grass, (T4). On the other hand, factors that are related to surface water runoff and soil sediment loss such as percentage of land cover density, slope of the land, and residue or humus on the land were found that the area no teak with planted Ruzi grass and the area no teak with fallow (natural growth) had lowest rate of surface water runoff and lowest soil sediment loss compared to other areas. It can be concluded that the land cover factor has an important role in helping to reduce surface water runoff and help prevent soil sediments from being lost to runoff in agricultural land and upland cultivation.