Explore the vast range of titles available.

Forest plays a crucial role in mitigating soil erosion and preserving organic carbon, especially in mountainous regions of Himalayas. However, limited information exists on soil erosion rate, soil organic carbon stock (SOCS), and associated carbon loss in these areas because of the rugged terrain, which poses challenges for reliable estimation using both traditional and modelling approaches. This study used Fallout Radionuclide- 137 Cs to assess soil erosion and carbon loss across various forest types. Results showed that mixed forests had the lowest erosion rates, while degraded forests had the highest, following the order of mixed forest < oak ( Quercus ) <  Rhododendron  < deodar ( Cedrus ) < pine ( Pinus ) < apple ( Malus ) < degraded forests. Forests with dense canopy and understory cover experiences reduced erosion (5.9 ± 3.6 t ha −1 year −1 ) while degraded forests showed high soil erosion rates (15.5 ± 6.4 t ha −1 year −1 ) with corresponding carbon displacement of 0.75 ± 0.48 and 1.42 ± 0.71 t ha −1 year −1 and carbon emission of 0.23 ± 0.14 and 0.43 ± 0.21 t ha −1 year −1 respectively. SOCS (0–15 cm) was inversely correlated with erosion rates, being highest in mixed forests (73.7 ± 32.2 t ha −1 ) and lowest in apple orchard (23.41 ±  4.3 t ha -1 ) and degraded forests (46.3 ± 19.9 t ha −1 ). These findings underscore the need to maintain forest diversity and canopy cover to arrest soil erosion, enhance carbon sequestration, and to improve ecosystem resilience. Conservation and restoration in degraded areas are essential for climate change mitigation and environmental stability in the mountainous landscapes of Himalayas.

Soil micronutrients are critical for plant growth and reproductive processes to complete their key functionality of the life cycle. The availability of micronutrients in hilly and mountainous regions is influenced by topography-controlled soil processes at various hillslope positions. However, the ruggedness of terrains makes it challenging to gather comprehensive data on soil micronutrient status, which in turn limits effective micronutrient management. This issue is particularly significant to the acidic soils of the North-western Himalayas, where agriculture is the primary source of livelihood. Therefore, this study was designed to explore the availability and variability of major micronutrients (Zn, Cu, Fe, and Mn) in the soils of hilly and mountainous landscapes across five different hillslope positions and various cropping systems, and to examine their relationship with physico-chemical properties of soils. The study revealed that all micronutrients were present in sufficient quantities across the hillslope positions. However, a slight tendency toward zinc deficiency was observed at some hillslope positions. Principal component analysis (PCA) highlighted the importance of micronutrients Fe, Mn, Zn, and Cu to pH, organic matter, sand and silt contents in the landscape. It revealed that pH and organic matter were critical factors influencing micronutrient availability, with higher levels of organic matter generally enhancing the availability of these micronutrients. The study further concluded that a complex interplay of topography, soil management practices, and cropping systems influence soil micronutrient availability. The variability observed at the hillslope scale highlights the need for site-specific management approaches. Understanding these factors is crucial for optimizing soil micronutrient management and ensuring sustainable agricultural productivity in the soil erosion-prone fragile Himalayan region.

Hillslope elements and land cover types are primarily determining the spatial variability of soils in the hilly and mountainous landscape. Among the soil forming factors, topography strongly influences pedogenic process and governs the variability of soils in hilly and mountainous landscape. This study mainly focusses on characterizing soil quality parameters distribution based on the hillslope elements and soil–landscape units in the watershed. Digital terrain model (DTM)-derived topographic position index was used to delineate various hillslope elements. Land use/land cover map was generated using random forest machine learning technique. Hillslope elements, land use/land cover types and aspects were integrated in GIS environment to generate soil–landscape unit map of the watershed. Soil samples were collected based on various soil–landscape units to characterize soil quality parameters such as total carbon (TC) soil organic matter (SOM), total nitrogen (TN), aggregate stability (SAS) in the watershed. SOM ranged from 1.6% to 10.05% and higher estimated in shoulder (forest) followed by valley (agriculture) and toe slope (forest). TC and TN contents ranged from 0.93% to 5.84% and 0.11% to 0.38%, respectively. The C:N ratio ranged from 7.96% to 18.31% and high value was found in shoulder (forest) followed by valley (agriculture) and toe slope (forest). SAS under different hillslope elements in the area ranged from 0.0.552 to 0.615 indicating large spatial variation of soil quality parameters. The study indicates that in hilly and mountainous landscape, topography and land cover types have major role in determining soil quality. DTM-based soil–landscape units’ delineation can be helpful to study soil quality variability and can be used to generate soil map for the hilly and mountainous watershed. The significance of this study lies in its potential to make substantial contributions to land use planning, sustainable land management and environmental conservation planning in the challenging and ecologically fragile and sensitive Himalayan region.

Land degradation is accelerating in the Himalayan ecosystem, resulting in the loss of soil nutrients due to severe erosion. Soil erosion presents a significant environmental challenge, resulting in both on-site and off-site consequences, such as reduced soil productivity and siltation in reservoirs. Soil erodibility (K factor), an inherent soil property, determines the susceptibility of soils to erosion. Sampling across hilly and mountainous terrain pose challenges due to its complex landscape. Despite these challenges, it is essential to study K factor variations in different land use/land cover types to comprehend the threat of erosion. Digital soil mapping offers an opportunity to overcome this limitation by providing spatial predictions of soil properties. The objective of our study is to map the spatial distribution of soil erodibility using the Random Forest (RF) model, a machine learning method based on sampled in situ soil data and environmental covariates. We collected 556 surface soil samples from the mountainous catchment (Tehri dam catchment) using the stratified random sampling approach. The model performed satisfactorily in both training ( r 2  = 0.91; RMSE = 0.00185) and testing ( r 2  = 0.45; RMSE = 0.00318) phases. Subsequently, we generated a digital map with a resolution of 12.5 m to depict the distribution of the K factor. Our analysis revealed that key environmental variables influencing the prediction of the K factor included geology, mean NDVI, and climatic factors. The average K factor value was estimated at 0.0304 and ranging from 0.0251 to 0.0400 t ha h ha −1  MJ −1  mm −1 . A higher K factor was observed in the barren land (0.0344) primarily located in the higher and trans-Himalayan region of seasonally snow-covered areas. These areas typically feature young soils with weak soil formation and unstable soil aggregates. Subsequently cropland/cultivated soils (0.0307) exhibited higher K factor values due to the breakdown of soil aggregates by ploughing activities and exposing carbon to decomposition. The average K factor value of evergreen (0.0294) and deciduous (0.0295) forests were the lowest compared to other land use/land cover types indicating the role of forests in resisting soil erosion. By assessing and predicting soil erodibility, land planners and farmers can implement erosion control measures to protect soil health, prevent sedimentation in water bodies, and sustain agricultural productivity in the Himalayas.

The Himalayan region is characterized by its heterogeneous topography and diverse land use/land cover types that significantly influence the weather and climatic patterns in the Indian sub-continent. Predicting future precipitation is crucial for understanding and mitigating the impacts of climate change on water resources, land degradation including soil erosion by water as well as sustainability of the natural resources. The study aimed to downscale future precipitation with Shared Socioeconomic Pathway (SSP) scenarios using machine learning methods in the Tehri Dam catchment area, located in the North-Western Himalayas, India. The study compared the performance of multiple linear regression (MLR), artificial neural network (ANN), and random forest (RF) models for statistical downscaling. During the training and testing phases, RF and ANN demonstrated reasonably satisfactory results in comparison to MLR. In general, models performed best on a monthly time scale compared to daily and yearly scales where RF model performed quite well. Therefore, the RF model was used to generate future climate scenarios for the near (2015–2040), mid (2041–2070), and far (2071–2100) future periods under the shared socioeconomic pathway (SSP) scenarios. An increasing trend in precipitation was observed across the area (grids), with varying magnitudes. The SSP1-2.6 scenario was projected the least change, ranging from 1.4 to 3.3%, while the SSP2-4.5 scenario indicated an average increase of 3.7 to 14.0%. The highest emission scenario (SSP5-8.5) predicted an increase of 8.4 to 27.5% in precipitation during the twenty-first century. In general, the increase in precipitation was higher in the far future compared to the mid and near future period. This projected increase in the precipitation may have the serious implications on food security, hydrological behaviour, land degradation, and accelerated sedimentation in the Himalayan region.

Soil erosion poses a critical challenge in mountainous regions which threaten the ecosystem stability and agricultural productivity. Conventional erosion assessment methods often fail to capture the spatial heterogeneity and complex topography of the Himalayan landscape. However, the application of the Fallout Radionuclide (FRN) 137 Cs technique offers a reliable and effective approach for quantifying long-term soil redistribution under such challenging terrain. This study evaluated soil erosion and deposition patterns on a representative steep Himalayan hillslope comprising both cultivated and abandoned terraced fields. The highest erosion rate (-34.6 ± 4.47 t ha⁻¹ yr⁻¹) was observed at the abandoned terraces located on the upper hillslopes, whereas the highest sediment deposition (+ 11.5 ± 3.00 t ha⁻¹ yr⁻¹) occurred at the lower and valley positions. Notably, regardless of the hillslope position, the hillslope shape exerted a significant influence on erosion and deposition dynamics, wherein convex slopes facilitated soil loss, while concave slopes promoted sediment accumulation. Abandoned terraces exhibited significantly higher soil erosion compared to cultivated fields emphasising the adverse consequences of land abandonment. Although, Well-maintained terraces at lower and valley hillslope positions effectively trap soil and sediment from upslope areas. The ¹³⁷Cs method effectively captured the spatial patterns of soil redistribution across the rugged terrain, it also demonstrated the pronounced variability in erosion and deposition driven by topographic heterogeneity. The findings underscore the need for regular terrace maintenance, enhanced vegetative cover, and integrated soil conservation strategies. Policy interventions promoting terrace preservation, sustainable land-use practices and preventing land abandonment are crucial for mitigating soil erosion and supporting resilient mountain agriculture in the Himalayan region.

Forest plays a crucial role in mitigating soil erosion and preserving organic carbon, especially in mountainous regions of Himalayas. However, limited information exists on soil erosion rate, soil organic carbon stock (SOCS), and associated carbon loss in these areas because of the rugged terrain, which poses challenges for reliable estimation using both traditional and modelling approaches. This study used Fallout Radionuclide- Cs to assess soil erosion and carbon loss across various forest types. Results showed that mixed forests had the lowest erosion rates, while degraded forests had the highest, following the order of mixed forest < oak (Quercus) < Rhododendron < deodar (Cedrus) < pine (Pinus) < apple (Malus) < degraded forests. Forests with dense canopy and understory cover experiences reduced erosion (5.9 ± 3.6 t ha year ) while degraded forests showed high soil erosion rates (15.5 ± 6.4 t ha year ) with corresponding carbon displacement of 0.75 ± 0.48 and 1.42 ± 0.71 t ha year and carbon emission of 0.23 ± 0.14 and 0.43 ± 0.21 t ha year respectively. SOCS (0-15 cm) was inversely correlated with erosion rates, being highest in mixed forests (73.7 ± 32.2 t ha ) and lowest in apple orchard (23.41 ±  4.3 t ha ) and degraded forests (46.3 ± 19.9 t ha ). These findings underscore the need to maintain forest diversity and canopy cover to arrest soil erosion, enhance carbon sequestration, and to improve ecosystem resilience. Conservation and restoration in degraded areas are essential for climate change mitigation and environmental stability in the mountainous landscapes of Himalayas.

In order for low and middle income countries (LMIC) to transition to Human Papilloma Virus (HPV) test based cervical cancer screening, a greater understanding of how to implement these evidence based interventions (EBI) among vulnerable populations is needed. This paper documents outcomes of an implementation research on HPV screening among women from tribal, rural, urban slum settings in India. A mixed-method, pragmatic, quasi-experimental trial design was used. HPV screening on self-collected cervical samples was offered to women aged 30-60 years. Implementation strategies were 1) Assessment of contextual factors using both qualitative and quantitative methods like key informant interviews (KII), focus group discussions (FGDs), pre-post population sample surveys, capacity assessment of participating departments 2) enhancing provider capacity through training workshops, access to HPV testing facility, colposcopy, thermal ablation/cryotherapy at the primary health care centers 3) community engagement, counselling for self-sampling and triage process by frontline health care workers (HCWs). Outcomes were assessed using the RE-AIM (Reach, Effectiveness, adoption, implementation, maintenance) framework. Screening rate in 8 months' of study was 31.0%, 26.7%, 32.9%, prevalence of oncogenic HPV was 12.1%, 3.1%, 5.5%, compliance to triage was 53.6%, 45.5%, 84.6% in tribal, urban slum, rural sites respectively. Pre-cancer among triage compliant HPV positive women was 13.6% in tribal, 4% in rural and 0% among urban slum women. Unique challenges faced in the tribal setting led to programme adaptations like increasing honoraria of community health workers for late-evening work and recalling HPV positive women for colposcopy by nurses, thermal ablation by gynaecologist at the outreach camp site. Self-collection of samples combined with HCW led community engagement activities, flexible triage processes and strengthening of health system showed an acceptable screening rate and better compliance to triage, highlighting the importance of identifying the barriers and developing strategies suitable for the setting. CTRI/2021/09/036130.

Background overview and rationale We co-developed a multi-component virtual care solution (TtLIVE) for the home mechanical ventilation (HMV) population using the aTouchAway™ platform (Aetonix). The TtLIVE intervention includes (1) virtual home visits; (2) customizable care plans; (3) clinical workflows that incorporate reminders, completion of symptom profiles, and tele-monitoring; and (4) digitally secure communication via messaging, audio, and video calls; (5) Resource library including print and audiovisual material. Objectives and brief methods Our primary objective is to evaluate the TtLIVE intervention compared to a usual care control group using an eight-center, pragmatic, parallel-group single-blind (outcome assessors) randomized controlled trial. Eligible patients are children and adults newly transitioning to HMV in Ontario, Canada. Our target sample size is 440 participants (220 each arm). Our co-primary outcomes are a number of emergency department (ED) visits in the 12 months after randomization and change in family caregiver (FC) reported Pearlin Mastery Scale score from baseline to 12 months. Secondary outcomes also measured in the 12 months post randomization include healthcare utilization measured using a hybrid Ambulatory Home Care Record (AHCR-hybrid), FC burden using the Zarit Burden Interview, and health-related quality of life using the EQ-5D. In addition, we will conduct a cost-utility analysis over a 1-year time horizon and measure process outcomes including healthcare provider time using the Care Coordination Measurement Tool. We will use qualitative interviews in a subset of study participants to understand acceptability, barriers, and facilitators to the TtLIVE intervention. We will administer the Family Experiences with Care Coordination (FECC) to interview participants. We will use Poisson regression for a number of ED visits at 12 months. We will use linear regression for the Pearlin Mastery scale score at 12 months. We will adjust for the baseline score to estimate the effect of the intervention on the primary outcomes. Analysis of secondary outcomes will employ regression, causal, and linear mixed modeling. Primary analysis will follow intention-to-treat principles. We have Research Ethics Board approval from SickKids, Children’s Hospital Eastern Ontario, McMaster Children’s Hospital, Children’s Hospital-London Health Sciences, Sunnybrook Hospital, London Health Sciences, West Park Healthcare Centre, and Ottawa Hospital. Discussion This pragmatic randomized controlled single-blind trial will determine the effectiveness and cost-effectiveness of the TtLIVE virtual care solution compared to usual care while providing important data on patient and family experience, as well as process measures such as healthcare provider time to deliver the intervention. Trial registration ClinicalTrials.gov NCT04180722 . Registered on November 27, 2019.

We previously reported that the compound O‐2093 is a selective inhibitor of the reuptake of the endocannabinoid anandamide (AEA). We have now re‐examined the activity of O‐2093 in vivo and synthesized four structural analogs (O‐2247, O‐2248, O‐3246, and O‐3262), whose activity was assessed in: (a) binding assays carried out with membranes from cells overexpressing the human CB1 and CB2 receptors; (b) assays of transient receptor potential of the vanilloid type‐1 (TRPV1) channel functional activity (measurement of [Ca2+]i); (c) [14C]AEA cellular uptake and hydrolysis assays in rat basophilic leukaemia (RBL‐2H3) cells; (d) the mouse ‘tetrad’ tests (analgesia on a hot plate, immobility on a ‘ring’, rectal hypothermia and hypolocomotion in an open field); and (e) the limb spasticity test in chronic relapsing experimental allergic encephalomyelitis (CREAE) mice, a model of multiple sclerosis (MS). O‐2093, either synthesized by us or commercially available, was inactive in the ‘tetrad’ up to a 20 mg kg−1 dose (i.v.). Like O‐2093, the other four compounds exhibited low affinity in CB1 (Ki from 1.3 to >10 μM) and CB2 binding assays (1.310 μM), very low potency as fatty acid amide hydrolase (FAAH) inhibitors (IC50>25 μM) and were inactive in the ‘tetrad’ up to a 30 mg kg−1 dose (i.v.). While O‐2247 and O‐2248 were poor inhibitors of [14C]AEA cellular uptake (IC50>40 μM), O‐3246 and O‐3262 were quite potent in this assay. O‐3246, which exhibits only a very subtle structural difference with O‐2093, is the most potent inhibitor of AEA uptake reported in vitro under our experimental conditions (IC50=1.4 μM) and is 12‐fold more potent than O‐2093. When injected intravenously O‐3246 and O‐3262, again like O‐2093 and unlike O‐2247 and O‐2248, significantly inhibited limb spasticity in mice with CREAE. These data confirm the potential utility of selective AEA uptake inhibitors as anti‐spasticity drugs in MS and, given the very subtle chemical differences between potent and weak inhibitors of uptake, support further the existence of a specific mechanism for this process. British Journal of Pharmacology (2006) 147, 83–91. doi:10.1038/sj.bjp.0706418