Position Index Research Articles

Investigation of the Relationship between Topographic and Forest Stand Characteristics Using Aerial Laser Scanning and Field Survey Data

The article thoroughly investigates the relationships between terrain features and tree measurements derived from aerial laser scanning (ALS) data and field surveys in a 1067-hectare forested area. A digital elevation model (DEM) was generated from ALS data, which was then used to derive additional layers such as slope, aspect, topographic position index (TPI), and landforms. The authors developed a mathematical procedure to determine the radii for the topographic position index. The canopy height model was created, and individual trees were segmented using a novel voxel aggregation method, allowing for the calculation of tree height and crown size. Accuracy assessments were conducted between ALS-derived data and field-collected data. Terrain variability within each forest unit was evaluated using characteristics such as standard deviation, entropy, and frequency. The relationships between tree height and the derived topographic features within forest subcompartments, as well as the correlation between the height yield map for the entire area and the TPI layer, were analysed. The authors found strong correlation between the topographic position index and tree heights in both cases. The presented remote-sensing-based methodology and the results can be effectively used in digital forest site mapping, complemented by field sampling and laboratory soil analyses, and, as final goal, in carbon stock assessment.

Dentist: Wrist Position, Handgrip Strength, and Body Mass Index Associated with Carpal Tunnel Syndrome in Daily Practice

Dentist: Wrist Position, Handgrip Strength, and Body Mass Index Associated with Carpal Tunnel Syndrome in Daily Practice

Bimodal pattern of allometric scaling along grapevine shoots.

Each branch internode, and the organs growing on it, can be seen as a single morphological phytomer subunit, made of structurally and functionally interrelated components. However, allometric relationships between anatomy and morphology of these subunits remain unclear, particularly in the axial context. This study aims to address this knowledge gap, by measuring morpho-anatomical parameters and their allometric relationships along grapevine shoots. To facilitate comparison, shoot length was normalized and a relative position index was calculated for each internode, ranging from 0 at the base to 1 at the apex. Scaling relationships between morpho-anatomical parameters along the axis were developed and validated by statistical modeling. Most morpho-anatomical parameters displayed an axial behaviour of increasing then decreasing in size from base to apex, with the exception of shoot diameter and shoot vessel density. Relative position index of 0.2 acted as the data turning point for most variables analysed. During the first phase (relative position index below 0.2), the phytomer organs traits are uncoupled and show weak allometric correlation, and during the second phase the traits are strongly allometrically related. Our findings suggest that allometric relationships along grapevine shoots are not constant- they exhibit a bimodal pattern, possibly influenced by seasonal temperatures. This work could aid managing productivity shifts in agricultural and natural systems under global climate change and add to basic knowledge of differentiation and development of growth units in plants.

Unveiling Wheat’s Future Amidst Climate Change in the Central Ethiopia Region

Quantifying how climatic change affects wheat production, and accurately predicting its potential distributions in the face of future climate, are highly important for ensuring food security in Ethiopia. This study leverages advanced machine learning algorithms including Random Forest, Maxent, Boosted Regression Tree, and Generalised Linear Model alongside an ensemble approach to accurately predict shifts in wheat habitat suitability in the Central Ethiopia Region over the upcoming decades. An extensive dataset consisting of 19 bioclimatic variables (Bio1–Bio19), elevation, solar radiation, and topographic positioning index was refined by excluding collinear predictors to increase model accuracy. The analysis revealed that the precipitation of the wettest month, minimum temperature of the coldest month, temperature seasonality, and precipitation of the coldest quarter are the most influential factors, which collectively account for a significant proportion of habitat suitability changes. The future projections revealed that up to 100% of the regions currently classified as moderately or highly suitable for wheat could become unsuitable by 2050, 2070, and 2090, illustrating a dramatic potential decline in wheat production. Generally, the future of wheat cultivation will depend heavily on developing varieties that can thrive under altered conditions; thus, immediate and informed action is needed to safeguard the food security of the region.

Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping.

This study was carried out with the aim of applying Condorcet and Borda scoring algorithms based on Game Theory (GT) to determine flood points and Flood Susceptibility Mapping (FSM) based on Machine Learning Algorithms (MLA) including Random Forest (RF), Support Vector Regression (SVR), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in the Cheshmeh-Kileh watershed, Iran. Therefore, first, FS conditioning factors including Aspect (As), Elevation (El), Euclidean distance (Euc), Forest (F), NDVI, Precipitation (P), Plan Curvature (PlC), Profile Curvature (PrC), Residential (Re), Rangeland (Rl), Slope (Sl), Stream Power Index (SPI), Topographic Position Index (TPI), and Topographic Wetness Index (TWI) were quantified in each Sub-Watershed (SW). Based on this, flood and non-flood points were identified based on both GT algorithms. In the following, MLAs including Random Forest (RF), Support Vector Regression (SVR), Support Vector Machines (SVM), and K-Nearest Neighbors (KNN) were used for the distributional mapping of FS. Finally, based on optimal conjunct approaches, FS maps were presented in the study watershed. Based on the results, among the conjunct algorithms in FS classification, RF-Condorcet and RF-Borda models were selected as the most optimal MLA-GT hybrid models. The upstream SWs were highly susceptible. Also, the effectiveness of NDVI and forest conditioning factors in each classification approach was high. The similarity of SW prioritization based on Condorcet algorithm with RF-Condorcet algorithm was about 86.70%. Meanwhile, the degree of similarity in RF-Borda conjunct algorithm was around 73.33%. These results showed that Condorcet algorithm had an optimal classification compared to Borda scoring algorithm.

Dual‐mode codeword position index based SCMA with transmit diversity

AbstractCodeword position index based sparse code multiple access (CPI‐SCMA) is an effective scheme that expands codeword positions in the time domain and carries extra information by their index. This paper proposes a dual‐mode CPI‐SCMA (DCPI‐SCMA) scheme to improve the error propagation caused by the mismatch between SCMA codewords and information bits. Furthermore, a DCPI‐SCMA with transmit diversity scheme is proposed where index bits are repeatedly transmitted to obtain a transmit diversity gain; hence, a higher reliability can be achieved with a slight loss of spectral efficiency. An optimal approach for the codebook index pattern is derived where the decision of index bits is involved in the demodulation of SCMA. It can be seen from simulation results and system analysis that the proposed schemes achieve better bit error rate performance with a decrease in complexity and obtain better robustness and flexibility compared with the existing CPI‐based SCMA schemes under the same spectral efficiency.

Enhancing mutation detection in multiple myeloma with an error-corrected ultra-sensitive NGS assay without plasma cell enrichment

BackgroundRisk stratification in multiple myeloma (MM) patients is crucial, and molecular genetic studies play a significant role in achieving this objective. Enrichment of plasma cells for next-generation sequencing (NGS) analysis has been employed to enhance detection sensitivity. However, these methods often come with limitations, such as high costs and low throughput. In this study, we explore the use of an error-corrected ultrasensitive NGS assay called positional indexing sequencing (PiSeq-MM). This assay can detect somatic mutations in MM patients without relying on plasma cell enrichment.MethodDiagnostic bone marrow aspirates (BMAs) and blood samples from 14 MM patients were used for exploratory and validation sets.ResultsPiSeq-MM successfully detected somatic mutations in all BMAs, outperforming conventional NGS using plasma cells. It also identified 38 low-frequency mutations that were missed by conventional NGS, enhancing detection sensitivity below the 5% analytical threshold. When tested in an actual clinical environment, plasma cell enrichment failed in most BMAs (14/16), but the PiSeq-MM enabled mutation detection in all BMAs. There was concordance between PiSeq-MM using BMAs and ctDNA analysis in paired blood samples.ConclusionThis research provides valuable insights into the genetic landscape of MM and highlights the advantages of error-corrected NGS for detecting low-frequency mutations. Although the current standard method for mutation analysis is plasma cell-enriched BMAs, total BMA or ctDNA testing with error correction is a viable alternative when plasma cell enrichment is not feasible.

Spatial prioritization of groundwater resources in mountain region of Nepal: a GIS and AHP integrated framework

ABSTRACT Climate change and anthropogenic activities pose major challenges to water resource management in water-scarce mountain regions. Managing and monitoring groundwater effectively is crucial in mitigating these challenges. Understanding groundwater resources and their distribution is necessary for effective management. The present study covers Doramba rural municipality of Nepal. It employed the analytic hierarchy process (AHP) as a multi-criteria decision-making (MCDM) tool integrated with remote sensing (RS) data and geospatial techniques to identify groundwater potential zones (GPZs). The parameters for analysis include drainage density, slope, rainfall, lineament density, land use/land cover (LULC), soil, geology, curvature, roughness, topographic wetness index, and topographic position index. These 11 thematic layers of the study area were prioritized using Satty's AHP method for the delineation of GPZs. The results classified the study area into very high, high, moderate, low, and very low groundwater potential classes, covering 26.71, 27.98, 46.61, 34.71, and 4.89 km2, respectively. The delineated map accuracy was confirmed with a 70.7% prediction rate based on the spatial distribution of 56 springs in the study area. The study's results can be applied to the sustainable management of groundwater resources in the study region and other areas with similar hydrogeological conditions.

Variations in the Thermal Low-Pressure Location Index over the Qinghai–Tibet Plateau and Its Relationship with Summer Precipitation in China

The thermal and dynamic effects of the special topography of the Qinghai–Tibet Plateau have a significant impact on rainfall in China. Utilizing NCEP/NCAR monthly reanalysis data alongside precipitation observations from 1936 monitoring stations across China spanning from 1966 to 2022, this study establishes a location index for the thermal low-pressure center situated over the Qinghai–Tibet Plateau. Temporal variations in the location index and summer (July) precipitation patterns in China were studied. Over the past six decades, thermal low-pressure centers have been predominantly positioned near 90° E and 32.5° N within a geopotential height of 4360 gpm, with their distribution extending from east to west rather than from south to north. The longitudinal and latitudinal position indices showed the same linear trend, with a negative trend before the 21st century, and then began to turn positive. Mutation analysis highlights pronounced weakening mutations occurring in 1981 and 1973, with the longitudinal index transitioning from an interannual cycle of approximately 6–8 years, while the latitudinal index displays quasi-cyclic oscillations of 5 and 8 and 12–14 years. Strong negative correlations are evident between the location indices and precipitation along the southeastern edge of the Qinghai–Tibet Plateau and in southern China, contrasting with the positive correlations observed in the central-eastern plateau, northwest, north, and the Huang-Huai region of China. The center of the thermal low is located to the east and north, corresponding to the deeper surface thermal low in most areas east of China, and the stronger transport of warm and wet air from the southwest wind, leading to greater convergence of southwest wind and northwest wind in China’s northern region. The south of the Yangtze River is controlled by the strengthening West Pacific subtropical high and South Asia high, resulting in a significant decrease in precipitation, and the warm and humid air from the southwest on the west side of the West Pacific subtropical high is also transported to the north, increasing the precipitation in most parts of the north.

The Ecological Environmental Effects and Topographic Gradient Analysis of Transformation in the Production–Living–Ecological Spaces in the Northern Slope of the Tianshan Mountains

Taking the northern slope of the Tianshan Mountains (NSTM) in Xinjiang as the research area, this study analyzes the changes in the Production–Living–Ecological (P-L-E) Spaces and their Ecological Environmental Effects, providing a basis for optimizing the spatial pattern of the P-L-E Spaces and regional ecological environment protection in this area. Based on land use data and DEM data, various methods were used for analysis. These methods include the land use transfer matrix, ecological environment quality index, hot spot analysis, ecological contribution rate, and Terrain Position Index. The analysis focused on changes in the spatial pattern of the P-L-E Spaces from 1980 to 2020. It also examined the spatiotemporal distribution of ecological environment quality (EEQ). Furthermore, it explored the differentiation characteristics of EEQ in terrain gradients. The conclusions are as follows: (1) On the NSTM, Ecological Space decreased while Production and Living Space expanded. From 1980 to 2020, Agricultural Production Space increased rapidly. Industrial Production Space also saw rapid growth during this period. Urban Living Space expanded significantly from 1980 to 2020. Rural Living Space experienced steady growth over the same period. Forest Ecological Space initially increased but later decreased. Water Ecological Space showed an initial increase followed by a decrease from 1980 to 2020. (2) The EEQ first remained stable, declined slightly from 2000 to 2010, improved significantly, and then deteriorated from 2010 to 2020. The distribution of EEQ exhibits a “high in the northwest, low in the southeast” pattern. EEQ hot spots on the NSTM are concentrated in the Tianshan Mountains, with clustering increasing in both northern and southern areas. Cold spots are found in the southern, eastern, and northern NSTMs, with aggregation strengthening in the south and north and slightly weakening in the east. Hot spots of EEQ changes on the NSTM show stable distribution, with stronger aggregation from 2000 to 2020. However, aggregation of cold spots has gradually weakened, yet noticeable aggregation persists throughout the study period. (3) There is a significant gradient difference in EEQ distribution. Higher terrain gradients have a higher EEQ. From 1980 to 2020, lower terrain gradients saw improvement, while higher gradients experienced deterioration. The EEQ on the NSTM has declined, showing significant spatial differences, with better quality on the northern side than the southern side. Future efforts should focus on restoring the environment at lower gradients, mitigating deterioration at higher gradients, and enhancing water conservation in the Tianshan Mountains.

Gone with the wind: environmental variation influences detection efficiency in a coastal acoustic telemetry array

Range tests play a critical role in designing acoustic telemetry studies, guiding equipment configuration, deployment techniques, and the analysis of animal movement data. These studies often strive to capture the effects of environmental variation on detection efficiency over time but are frequently limited in spatial and temporal scale. This could lead to disparities between test results and the circumstances encountered during animal tracking studies. In this study, we evaluated detection range and efficiency at two distinct spatial and temporal scales in a dynamic intertidal ecosystem. Two range tests were conducted, the first being a small-scale study using 6 receivers deployed over 1 month. Using modern acoustic receivers with built-in transmitters and environmental sensors, we then conducted a large-scale range test with 22 receiver stations over a full year to approximate the area and duration of a typical animal movement study. Differences in detection range between the two studies occurred as a result of environmental variation and tag power output, with midpoint ranges estimated as 123 m (small scale, low power), 149 m (small scale, high power) and 311 m (large scale, very high power). At both scales, wind speed emerged as the most influential factor explaining temporal variation in predicted detection efficiency. However, this effect was modulated by wind direction which varied as a result of land sheltering and fetch between the two study scales. At the small scale, detection efficiency decreased with winds from the south and east, while at the large scale, northern and westerly winds were most detrimental. Water temperature had a positive effect on predicted detection efficiency at both scales, while relative water level was positive at the small scale and negative at the large scale. Additional factors, including precipitation and Topographic Position Index, were found to influence detection efficiency at a large scale. Moreover, sensors associated with receivers in the larger array revealed the significant influences of receiver tilt and ambient noise. These discrepancies in the outcomes of the two studies underscore the critical role of scale in range test design and emphasize the need for long-term, in situ range testing at relevant spatial scales.

Simulating the Entire Clinical Process for an Implant-Supported Fixed Prosthesis: In Vitro Study on the Vertical Implications of Implant-Abutment Connections and Rotational Freedom.

The aim of this in vitro study was to investigate whether and to what extent different scenarios of rotational freedom in different IAC designs affect the vertical dimension of a three-part fixed partial denture (FPD). At the same time, the experimental setup should simulate all clinical and laboratory steps of the implementation of such an FPD as accurately as possible. Twenty identical pairs of jaw models were fabricated from aluminum, each lower-jaw model holding two implants with conical or flat IACs. Three impressions of each model were taken to fabricate stone casts and three-unit FPDs. Three assembly scenarios were compared for the vertical position stability they offered for these FPDs, differing by how the sequential implant components (impression posts > laboratory analogs > abutments 1 > abutments 2) were aligned with the positional index of the IAC. In this way, a total of 60 stone casts and FPDs were fabricated and statistically analyzed for changes in vertical dimension (p < 0.05). Regardless of whether a conical/flat IAC was used (p > 0.05), significantly greater mean changes in vertical dimension were consistently (all comparisons p < 0.0001) found in a "worst-case scenario" of component alignment alternating between the left- and right-limit stop of the positional index (0.286/0.350 mm) than in a "random scenario" of 10 dentists and 10 technicians with varying levels of experience freely selecting the alignment (0.003/0.014 mm) or in a "best-case scenario" of all components being aligned with the right-limit stop (-0.019/0.005 mm). The likelihood of integrating a superstructure correctly in terms of vertical dimension appears to vary considerably more with assembly strategies than with IAC designs. Specifically, our findings warrant a recommendation that all implant components should be aligned with the right-limit stop of the positioning index.

Comparing Frequency Ratio and Analytical Hierarchy Models for Landslide Susceptibility in the Dharan Sub-Metropolitan Region of Eastern Nepal

This study compares the application of Frequency Ratio (FR) (statistical/quantitative) and Analytical Hierarchy Process (AHP) (heuristic/semi-quantitative) for landslide susceptibility analysis in Dharan Sub-Metropolitan Region of eastern Nepal. Nine different thematic layers including slope, aspect, curvature, geology, land use, distance to roads, distance to thrusts, topographic position index (TPI), and distance to streams were used for analysis. A landslide inventory map was prepared by identifying the landslides in recent Google Earth images, and it was then verified by field observations. The resulting susceptibility map with different susceptibility levels was validated using the Area Under the Curve (AUC) method, and the resulting AUC values were determined to be 78% for FR and 76.8% for AHP. Both methods offer a reliable strategy for landslide susceptibility mapping with a good prediction rate. The FR model enclosed 41%, 31%, 20%, 7% and 1% of the area as very low, low, moderate, high, and very high susceptibility, respectively, whereas AHP showed 21%, 24%, 27%, 21% and 7% of the area for the respective susceptibility levels. The specific zones identified within the range from very low to very high susceptibility provide valuable insights for local authorities, planners, and decision-makers, allowing them to identify areas susceptible to landslides and implement mitigation measures to aid in targeted risk management efforts.

Co-seismic and rainfall-triggered landslide hazard susceptibility assessment for Uganda derived using fuzzy logic and geospatial modelling techniques

AbstractUganda has suffered from many damaging landslides like the 1966 Rwenzori, 1994 Kisomoro and 2010 Bududa events. Despite escalating landslide risks exacerbated by rapid deforestation, urbanization and population growth coupled with a substandard building stock, comprehensive national co-seismic and rainfall-induced landslide hazard and risk maps for Uganda do not exist. This study therefore aims to conduct landslide hazard assessment and zonation for Uganda using a geospatial-based fuzzy logic methodology. In this methodology, landslide frequency ratios obtained for the 1966 Toro and 1994 Kisomoro earthquakes are assigned to the stochastic event-based probabilistic seismic hazard map derived using OpenQuake-engine. The available co-seismic and rainfall-induced landslide inventory datasets are used to derive the distribution of landslide frequency ratios based on geology, topographic slope position index, slope aspect, slope angle, distance from streams, and proximity to major active faults. The spatial distribution of fuzzy membership functions obtained from frequency ratios are overlaid and aggregated to produce landslide susceptibility maps showing relative probabilities of landslide occurrences across Uganda. Results indicate that the highest overall landslide hazard susceptibility is expected in areas comprising highly weathered outcropping rocks of precambrian granites, dominantly metasedimentary, and granulites and gneisses geologies within 40 km from major active faults; where the bedrock peak ground acceleration ≥ 0.1 g, topographic position index ≥ 3.8, slope gradient ≥ 10°, and the distance from streams ≤ 1.25 km. These findings can inform Uganda’s directorate of disaster preparedness and management towards pioneering the development of co-seismic landslide risk mitigation measures for the country.

Investigation of the causality between participation in global value chains and CO2 emissions between developed and developing countries

The production and consumption activities are cross-border and therefore, it is important to understand the role of Global Value Chains (GVCs) in fulfilling a country’s specific climate commitments. This study examines the causal relationship between selected GVC indices and CO2 emissions. We use the GVC position index, considered robust in comparison to the frequently used GVC participation index, for determining the impact on emissions. The forward and backward participation indices are considered in the analysis. The paper presents an analysis of 62 developing and developed economies from 1995 to –2018 using the Juodis A., Y. Karavias, and V. Sarafidis [2021. “A Homogeneous Approach to Testing for Granger non-Causality in Heterogeneous Panels.” Empirical Economics 60 (1): 93–112] approach, which is an improvement over the traditional approaches to analysing causality. The results show that the overall position in GVCs positively affects CO2 emissions for developing countries but a causal relationship does not exist for the developed countries. The developed countries attain a higher participation index but a lower position index. On the other hand, developing countries with fewer stringent environmental regulations may opt for an upstream position (more export-oriented) and by design specialize in more pollution-intensive industries. Noteworthy, production-based emissions in developed countries are reduced because of an increase in imports of emission-intensive products from developing countries.

Diatomite evidence for a small palaeo mountain lake at 3400 m asl, Lesotho, southern Africa

ABSTRACTThe Eastern Lesotho Highlands experience an excess of rainfall sufficient to form the country's primary export, supplying the economic hub of southern Africa, Gauteng South Africa. However, there is currently only one natural lake in the country, Letšeng‐la Letsie, and evidence of palaeolakes in the region is therefore of particular interest. This study presents the analysis of a diatomite outcrop from a depression northwest of Mafadi Summit, at 3400 m asl. The presence of diatomite, dominated by the facultative planktonic species Staurosirella pinnata and Staurosira construens and abundant planktonic Aulacoseira ambigua, is indicative of the continuous presence of a shallow lake between ~4600 and 100 cal a bp. Comparative analysis of rainfall for the Mafadi and Letšeng‐la Letsie regions from CHIRPS gridded rainfall data demonstrates sufficient rainfall for a lake of comparable size, if not larger, as Mafadi receives considerably more rainfall than Letšeng‐la Letsie. Analysis of the SRTM 30‐m Digital Elevation Model and Topographic Position Index calculations demonstrate the feasibility of a shallow surface water feature at Mafadi. The conversion of this palaeolake into the contemporary wetland is hypothesized to be the result of post‐industrial warming, possibly augmented by migration of livestock into the Eastern Lesotho Highlands.

Effective Use of Catastrophe Multicriteria Decision Analysis in Delineating Groundwater Recharge Potential Zones

Multicriteria decision analysis based on Thom’s [1] Catastrophe Theory (CT) has been applied extensively in solving various social, physical and natural sciences problems. It has become a key tool for identifying the groundwater potentiality of an area with a Geographic Information System (GIS). This paper aimed to apply catastrophe theory effectively by utilizing the standardization formulae suggested by Li et al. [2] and the modified formulae provided by Hongwei Zhu [3]. Depending on the nature of a hydrogeological parameter, CT formulae were chosen to ensure that the least important features also get attention during standardization using Hongwei Zhu's formulae where applicable, which were not possible using Li’s formulae. The standardized values of the features of all the themes obtained using four formulae were sorted in ascending order to estimate the normalized values to ensure that no normalized value of a feature exceeds the others having very close but lower standardized values. The effective use of CT technique was employed in a GIS environment to delineate groundwater recharge potential zones of the middle-west part of Kushtia district, Bangladesh, by integrating influential recharge factors, such as land type, slope, drainage density, distance from surface water bodies, soil permeability, surface clay thickness, rainfall, topographic ruggedness index, topographic curvature index, topographic wetness index and topographic position index. The groundwater recharge potential zones were classified as very good (28.76%), good (32.17%), and moderately good (39.05%) for effective CT technique. But in case of the improper use of CT covering area were 17.24%, 54.05% and 28.71% respectively, and the respective most sensitive factors are rainfall and drainage density. Finally, recharge potential zones were validated using groundwater recharge data with a determinant coefficient of 0.92 and 0.84 for effective and improper use of CT technique respectively.

Application effect and influencing factors of early awake prone position in patients with mild-to-moderate acute respiratory distress syndrome

To investigate the application effect of early awake prone position in mild-to-moderate acute respiratory distress syndrome (ARDS) patients, and analyze the related factors affecting the prone position outcome. A prospective cohort study was conducted. The mild-to-moderate ARDS patients admitted to the emergency department of Yingshang County People's Hospital from January 2020 to June 2023 were enrolled as the research subjects. According to the results of prone tolerance test, the patients were divided into awake prone position group and non-prone position group. All patients were given high flow nasal cannula (HFNC) according to the standard procedures. The patients in the awake prone position group received prone position treatment within 12 hours after admission, in addition to the standard treatment. This could be performed in several times, at least once a day, and at least 2 hours each time. In order to prolong the prone position as much as possible, the patients were allowed to move or keep a small angle side prone. The changes of oxygenation index (PaO2/FiO2) at 0, 24, 48, and 72 hours after admission, the rate of intensive care unit (ICU) transfer, the use rate and use time of non-invasive ventilation (NIV), the total hospital stay, and the daily prone position time and 2-hour ROX index [ratio of pulse oxygen saturation/fraction of inspired oxygen (SpO2/FiO2) and respiratory rate (RR)] of prone position patients were recorded. The successful termination of HFNC was defined as the successful prone position, and the failure of prone position was defined as switching to NIV or transferring to ICU. Subgroup analysis was performed, and the binary multivariate Logistic regression analysis was used to screen the influencing factors of the early awake prone position outcome. A total of 107 patients were finally enrolled, with 61 in the awake prone position group and 46 in the non-prone position group. Both groups showed a gradual increase in PaO2/FiO2 with prolonged admission time. The PaO2/FiO2 at 24 hours after admission in the awake prone position group was significantly higher than that at 0 hour [mmHg (1 mmHg ≈ 0.133 kPa): 191.94±17.86 vs. 179.24±29.27, P < 0.05], while the difference in the non-prone position group was only statistically significant at 72 hours (mmHg: 198.24±17.99 vs. 181.24±16.62, P < 0.05). Furthermore, the PaO2/FiO2 at 48 hours and 72 hours after admission in the awake prone position group was significantly higher than that in the non-prone position group. The use rate of NIV in the awake prone position group was significantly lower than that in the non-prone position group [36.1% (22/61) vs. 56.5% (26/46), P < 0.05]; Kaplan-Meier curve analysis further confirmed that the patients in the awake prone position group used NIV later, and the cumulative rate of NIV usage was significantly lower than that in the non-prone position group (Log-Rank test: χ 2 = 5.402, P = 0.020). Compared with the non-prone position group, the ICU transfer rate in the awake prone position group was significantly lowered [11.5% (7/61) vs. 28.3% (13/46), P < 0.05], and the HFNC time, NIV time, and total hospital stay were significantly shortened [HFNC time (days): 5.71±1.45 vs. 7.24±3.36, NIV time (days): 3.27±1.28 vs. 4.40±1.47, total hospital stay (days): 11 (7, 13) vs. 14 (10, 19), all P < 0.05]. Of the 61 patients who underwent awake prone positioning, 39 were successful, and 22 failed. Compared with the successful group, the patients in the failure group had a higher body mass index [BMI (kg/m2): 26.61±4.70 vs. 22.91±5.50, P < 0.05], lower PaO2/FiO2, proportion of asymptomatic hypoxemia and 2-hour ROX index of prone position [PaO2/FiO2 (mmHg): 163.73±24.73 vs. 185.69±28.87, asymptomatic hypoxemia proportion: 18.2% (4/22) vs. 46.2% (18/39), 2-hour ROX index of prone position: 5.75±1.18 vs. 7.21±1.45, all P < 0.05], and shorter daily prone positioning time (hours: 5.87±2.85 vs. 8.05±1.99, P < 0.05). Binary multivariate Logistic regression analysis showed that all these factors were influencing factors for the outcome of awake prone positioning (all P < 0.05), among which BMI [odds ratio (OR) = 1.447, 95% confidence interval (95%CI) was 1.105-2.063] and non-asymptomatic hypoxemia (OR = 13.274, 95%CI was 1.548-117.390) were risk factors for failure of prone position, while PaO2/FiO2 (OR = 0.831, 95%CI was 0.770-0.907), daily prone positioning time (OR = 0.482, 95%CI was 0.236-0.924), and 2-hour ROX index of prone position (OR = 0.381, 95%CI was 0.169-0.861) were protective factors. Early awake prone positioning in patients with mild-to-moderate ARDS supported by HFNC is safe and feasible, reducing the use rate and duration of NIV, lowering the ICU transfer rate, and shortening the hospital stay. High BMI and non-asymptomatic hypoxemia are risk factors for failed prone position, while higher PaO2/FiO2 and the ROX index within 2 hours of prone position (the patient's good response to prone position), and prolonged daily prone position can improve the success rate of prone position.

Urban flash flood prediction modelling using probabilistic and statistical approaches

The development of a detailed strategy to mitigate the negative consequences of any natural calamities depends on accurately identifying sensitive zones where natural hazards frequently happen. In the present investigations, three widely utilized probabilistic approaches viz., frequency ratio (FR), statistical index (SI), and weighting factor (WF) have been utilized for prediction of flsh flood susceptibility zones in the Coochbehar urban and peri-urban area (CUPUA) (area = 26.22 km2). Ten flash flood conditioning factors have been used in this assessment based on previous literatures and experts' opinions. In the FR model, 29.40 % area is observed in the high and very high flood zones, whereas 36.27 % and 31.16 % area is identified in SI and WF model, respectively. The FR model demonstrates that five conditioning factors, viz., topographic position index (TPI), land use and land cover (LULC), normalized difference vegetation index (NDVI), distance to drainage (DtD) and rainfall were highly impacted in flash flood prediction (FFP) analysis; in SI model, LULC is the major influencing parameter, and in WF model LULC, rainfall, NDVI, and distance to road (DtR) are the effective parameters. The success rate curve of the FR, SI and WF models manifest SI model has highest training (AUC=0.903) and prediction (AUC=0.925) accuracy, and FR and WF also have very good accuracy as their AUC values are 0.899 and 0.877 (in success rate curve) and 0.900 and 0.881 (in prediction rate curve). Therefore, the application of probabilistic approaches in this active flash flood-prone region is excellently performed, and the results of this study will help hydrologists, engineers, and water management administrators to control the areas that are extremely susceptible to flash floods and reduce possible damages.

Investigating the spatial distribution of flood inundation and landforms using topographic position index (TPI) and geomorphon-based automated landform classification methods

Investigating the spatial distribution of flood inundation and landforms using topographic position index (TPI) and geomorphon-based automated landform classification methods