Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of soft TQM and hard TQM on innovation performance: the moderating effect of organisational culture

Literature increasingly recognises the importance of organisational culture when implementing operations management practices. This paper examines the relationships among quality, innovation, and organisational culture under a moderation model. The research model is constructed based on well-established theories of competing values framework (CVF) and total quality management (TQM). A cross-sectional study was conducted amongst 106 ISO 9000-certified manufacturers where data were collected from senior managers with sufficient knowledge. Partial least square analysis indicates that: 1) innovation is influenced mainly by adopting soft (organisational) TQM elements and secondarily hard (process) TQM elements; 2) innovation organisational culture has a stronger moderating influence on process-related TQM than on organisational TQM, although its interactions are mostly insignificant. Therefore, practitioners are advised to emphasise the organisational aspect of TQM rather than process-related practices when assessing the innovation performance of an organisation. The findings recommend firms to have a balanced view on cultures in organisations.
Evaluation and bias correction of probabilistic volcanic ash forecasts

Abstract. Satellite retrievals of column mass loading of volcanic ash are incorporated into the HYSPLIT transport and dispersion modeling system for source determination, bias correction, and forecast verification of probabilistic ash forecasts of a short eruption of Bezymianny in Kamchatka. The probabilistic forecasts are generated with a dispersion model ensemble created by driving HYSPLIT with 31 members of the NOAA global ensemble forecast system (GEFS). An inversion algorithm is used for source determination. A bias correction procedure called cumulative distribution function (CDF) matching is used to very effectively reduce bias. Evaluation is performed with rank histograms, reliability diagrams, fractions skill score, and precision recall curves. Particular attention is paid to forecasting the end of life of the ash cloud when only small areas are still detectable in satellite imagery. We find indications that the simulated dispersion of the ash cloud does not represent the observed dispersion well, resulting in difficulty simulating the observed evolution of the ash cloud area. This can be ameliorated with the bias correction procedure. Individual model runs struggle to capture the exact placement and shape of the small areas of ash left near the end of the clouds lifetime. The ensemble tends to be overconfident but does capture the range of possibilities of ash cloud placement. Probabilistic forecasts such as ensemble-relative frequency of exceedance and agreement in percentile levels are suited to strategies in which areas with certain concentrations or column mass loadings of ash need to be avoided with a chosen amount of confidence.
Genetic Dissection of Tobacco ( Nicotiana tabacum L.) Plant Height Using Single-Locus and Multi-Locus Genome-Wide Association Studies

: Tobacco ( Nicotiana tabacum L.) plant height (PH) is a biologically important plant architecture trait linked to yield and controlled by polygenes. However, limited information is available on quantitative trait nucleotides (QTNs), alleles, and candidate genes. The plant height of 94 tobacco accessions and their 126,602 SNPs were measured to conduct a genome-wide association study (GWAS) using four multi-locus (ML) and two single-locus (SL) models to better understand its genetic basis. The ML and SL models detected 181 and 29 QTNs, respectively, across four environments/BLUP; LOD scores ranged from 3.01–13.45, and the phenotypic variance explained (PVE) ranged from 0.69–25.37%. Fifty-two novel, stable QTNs were detected across at least two methods and/or two environments/BLUP, with 0.64–24.76% PVE. Among these, 49 QTNs exhibited signiﬁcant phenotypic differences between two alleles; the distribution of elite and alternative alleles for each accession ranged from 3–42 and 6–46, respectively, in the mapping population. Seven cross combinations in two directions were predicted using alleles of validated QTNs, including Qinggeng × KY14 for taller plants and RG112 × VA115 for shorter plants. We identiﬁed 27 candidate genes in the vicinity of 49 stable QTNs based on comparative genomics, gene ontology (GO), and KEGG enrichment analysis, including AP2 , Nitab4. 5_0000343g0250. 1 ( ROC1 ), Nitab4. 5_0000197g0010. 1 ( VFB1 ), CDF3 , AXR6 , KUP8 , and NPY2. This is the ﬁrst study to use genotyping-by-sequencing (GBS) of SNPs to determine QTNs, potential candidate genes, and alleles associated with plant height. These ﬁndings could provide a new avenue for investigating the QTNs in tobacco by combining SL and ML association mapping and solid foundations for functional genomics, the genetic basis, and molecular breeding for PH in tobacco.
Improving the calibration-free complementary evaporation principle by linking with the Budyko framework

While it has performed well in predicting terrestrial evapotranspiration (ET a ) in many gauged locations over the world, the calibration-free complementary relationship (CR) depends on a questionable assumption that the Priestley-Taylor 10 coefficient (α e ) is spatially constant over an extensive area. In this work, we evaluated the predictive performance of this convenient method, which only requires atmospheric inputs, against in-situ flux observations and water balance estimates (ET wb ) in Australia. We found that the CR method with a spatially constant α e derived from fractional wet areas did not perform as highly as previous studies would suggest, underperforming three advanced ET a models in closing basin-scale water balance. This problem was remedied by linking the CR method with a traditional Budyko equation that allowed 15 upscaling of optimal α e values from gauged basins to ungauged locations. The CR method with the α e upscaled by the atmospheric inputs and the mean precipitation (P) better reproduced the grid ET wb available over the entire continent, and outperformed the three ET a models. This study suggests that the fixed α e could lead the CR method to biased ET a estimates, and it needs to be constrained by climate conditions to better close local water budgets.
Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset

Abstract. Tropical cyclones (TCs) are one of the most devastating natural disasters, which justifies monitoring and prediction on short and long timescales in the context of a changing climate. In this study, we have adapted and tested a convolutional neural network (CNN) for the classification of reanalysis outputs according to the presence or absence of TCs. This study compares the performance and sensitivity of a CNN to the learning dataset. For this purpose, we chose two meteorological reanalysis, ERA5 and MERRA-2, and used a number of meteorological variables from them to form TC-containing and background images. The presence of TCs is labeled from the HURDAT2 dataset. Special attention was paid to the design of the background image set to make sure it samples similar locations and times to the TC-containing images. We have assessed the performance of the CNN using accuracy but also the more objective AUC and AUPRC metrics. Many failed classifications can be explained by the meteorological context, such as a situation with cyclonic activity but not yet classified as TCs by HURDAT2. We also tested the impact of spatial interpolation and of “mixing and matching” the training and test image sets on the performance of the CNN. We showed that applying an ERA5-trained CNN to MERRA-2 images works better than applying a MERRA-2-trained CNN to ERA5 images.
Contrasting strategies of nutrient demand and use between savanna and forest ecosystems in a neotropical transition zone

Abstract. The total demand for and uptake of nutrients by vegetation is rarely quantified or compared across vegetation types. Here, we describe different nutrient use and allocation strategies in neotropical savanna (cerrado) and transitional forest (cerradão) tree communities composed of different species, report leaf nutrient resorption and calculate ecosystem-level nutrient use efficiency. We couple net primary productivity (NPP) estimates with nutrient stoichiometry to quantify nutrient demand and nutrient flows at the whole-stand scale for different components of vegetation biomass. Species from the two vegetation communities showed similar mean nutrient concentrations and nutrient resorption efficiency, except for wood P concentration that was fourfold higher in cerrado than cerradão species. The cerradão showed higher canopy NPP, while fine roots and wood NPP were similar for the two vegetation types. Nutrient requirement in the two vegetation types was dominated by the demands of the canopy, with canopy resorption generally contributing more than 50 % of the total canopy demand for nutrients, while less than 35 % of N, P, K, Ca and Mg were allocated to wood or fine roots. Proportionally, cerrado showed higher nutrient demand from fine roots (over 35 % of the total nutrient demand) and for the wood component (over 13 % of the total nutrient demand), while ∼ 60 %–70 % of the cerradão nutrient demand was allocated to the canopy. The proportional difference in nutrient allocation to the different biomass components suggests cerrado species allocate less nutrients to a given fine root biomass, but more nutrients to a given wood biomass. Our findings suggest that cerradão species are more limited in P and K than cerrado species, inducing higher resorption to compensate for low uptake. Moreover, we found that N uptake for cerradão was higher with lower N use efficiency, i.e. the amount of production per nutrient unit, leading higher N demand compared to the cerrado. This difference in nutrient dynamics explains how similar soils and the same climate dominated by savanna vegetation can also support forest-like formations. Tree species composition is likely the major factor regulating nutrient use, limiting vegetation transitions and influencing nutrient demand at landscape scales.
Precipitation fate and transport in a Mediterranean catchment through models calibrated on plant and stream water isotope data

Abstract. To predict hydrologic responses to inputs and perturbations, it is important to understand how precipitation is stored in catchments, released back to the atmosphere via evapotranspiration (ET), or transported to aquifers and streams. We investigated this partitioning of precipitation using stable isotopes of water (18O) at the Can Vila catchment in the Spanish Pyrenees mountains. The isotope data covered four years of measurements, comprising >550 rainfall and >980 stream water samples, capturing intra-event variations. They were complemented by fortnightly plant water isotope data sampled over eight months. The isotope data were used to quantify how long it takes for water to become evapotranspiration or to be discharged as streamflow using StorAge Selection (SAS) functions. We calibrated the SAS functions using a conventional approach fitting the model solely to stream water isotope data and a multi-objective calibration approach in which the model was simultaneously fitted to tree xylem water isotope data. Our results showed that the conventional model-fitting approach was not able to constrain the model parameters that represented the age of water supplying ET. Consequently, the ET isotope ratios simulated by the conventionally calibrated model failed to adequately simulate the observed xylem isotope ratios. However, the SAS model was capable of adequately simulating both observed stream water and xylem water isotope ratios, if those xylem water isotope observations were used in calibration (i.e., the multi-objective approach). The multi-objective calibration approach led to a more constrained parameter space facilitating parameter value identification. The model was tested on a segment of data reserved for validation showing a Kling–Gupta Efficiency of 0.72 compared to the 0.83 observed during in the calibration period. The water-age dynamics inferred from the model calibrated using the conventional approach differed substantially from those inferred from the multi-objective calibration model. The latter suggested that the median ages of water supplying evapotranspiration is much older (150–300 d) than what was suggested by the former (50–200 d). Regardless, the modeling results support recent findings in ecohydrological field studies that highlighted both subsurface heterogeneity of water storage and fluxes and the use of relatively old water by trees. We contextualized the SAS-derived water ages by also using young-water-fraction and endmember-splitting approaches, which respectively also showed the contribution of young water to streamflow was variable but sensitive to runoff rates and that ET was largely sourced by winter precipitation that must have resided in the subsurface across seasons.
Four-dimensional temperature, salinity and mixed-layer depth in the Gulf Stream, reconstructed from remote-sensing and in situ observations with neural networks

Abstract. Despite the ever-growing number of ocean data, the interior of the ocean remains undersampled in regions of high variability such as the Gulf Stream. In this context, neural networks have been shown to be effective for interpolating properties and understanding ocean processes. We introduce OSnet (Ocean Stratification network), a new ocean reconstruction system aimed at providing a physically consistent analysis of the upper ocean stratification. The proposed scheme is a bootstrapped multilayer perceptron trained to predict simultaneously temperature and salinity (T−S) profiles down to 1000 m and the mixed-layer depth (MLD) from surface data covering 1993 to 2019. OSnet is trained to fit sea surface temperature and sea level anomalies onto all historical in situ profiles in the Gulf Stream region. To achieve vertical coherence of the profiles, the MLD prediction is used to adjust a posteriori the vertical gradients of predicted T−S profiles, thus increasing the accuracy of the solution and removing vertical density inversions. The prediction is generalized on a 1/4∘ daily grid, producing four-dimensional fields of temperature and salinity, with their associated confidence interval issued from the bootstrap. OSnet profiles have root mean square error comparable with the observation-based Armor3D weekly product and the physics-based ocean reanalysis Glorys12. The lowest confidence in the prediction is located north of the Gulf Stream, between the shelf and the current, where the thermohaline variability is large. The OSnet reconstructed field is coherent even in the pre-Argo years, demonstrating the good generalization properties of the network. It reproduces the warming trend of surface temperature, the seasonal cycle of surface salinity and mesoscale structures of temperature, salinity and MLD. While OSnet delivers an accurate interpolation of the ocean stratification, it is also a tool to study how the ocean stratification relates to surface data. We can compute the relative importance of each input for each T−S prediction and analyse how the network learns which surface feature influences most which property and at which depth. Our results demonstrate the potential of machine learning methods to improve predictions of ocean interior properties from observations of the ocean surface.
Pacific Decadal Oscillation modulates the Arctic sea-ice loss influence on the midlatitude atmospheric circulation in winter

Abstract. The modulation of the winter impacts of Arctic sea-ice loss by the Pacific Decadal Oscillation (PDO) is investigated in the IPSL-CM6A-LR ocean–atmosphere general circulation model. Ensembles of simulations are performed with constrained sea-ice concentration following the Polar Amplification Model Intercomparison Project (PAMIP) and initial conditions sampling warm and cold phases of the PDO. Using a general linear model, we estimate the simulated winter impact of sea-ice loss, PDO and their combined effects. On the one hand, a negative North Atlantic Oscillation (NAO)-like pattern appears in response to sea-ice loss together with a modest deepening of the Aleutian Low. On the other hand, a warm PDO phase induces a large positive Pacific–North America pattern, as well as a small negative Arctic Oscillation pattern. Both sea-ice loss and warm PDO responses are associated with a weakening of the poleward flank of the eddy-driven jet, an intensification of the subtropical jet and a weakening of the stratospheric polar vortex. These effects are partly additive; the warm PDO phase therefore enhances the response to sea-ice loss, while the cold PDO phase reduces it. However, the effects of PDO and sea-ice loss are also partly non-additive, with the interaction between both signals being slightly destructive. This results in small damping of the PDO teleconnections under sea-ice loss conditions, especially in the stratosphere. The sea-ice loss responses are compared to those obtained with the same model in atmosphere-only simulations, where sea-ice loss does not significantly alter the stratospheric polar vortex.
Comparison of Injury Severity Score (ISS), New Injury Severity Score (NISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) In Predicting Mortality In Polytrauma Patients At Haji Adam Malik General Hospital

Background : Polytrauma is a trauma that involves injury to 2 or more body regions, where at least one of them can cause death. Definitive follow-up of trauma patients can reduce mortality. Trauma scoring can make it easier for clinicians to assess the severity of a patient's trauma and assist in deciding what management to choose. Methods : This study used an observational diagnostic test design by taking secondary data from medical records from January 2019-July 2021 as many as 150 people. This study aimed for differences in the sensitivity and specificity values of the ISS, NISS, RTS, and TRISS scoring systems in predicting mortality of polytrauma patients at RSUP HAM. Results : The sensitivity, specificity, positive predictive value and negative predictive value of ISS with a cut-off point of 37.5 were 83.9%, 90.8%, 70.3%, 95.6%; NISS with 49 cut-off points are 67.7%, 96.6%, 84%, and 92%, respectively; RTS with a cut-point value of 6.952 are 9.7% and 22.7%, respectively, and TRISS with a cut-point value of 96.83, respectively, is 3.2% and 55.5%. Discussion : ISS and NISS can be used as predictors of mortality in polytrauma patients, while RTS and TRISS cannot be predictors of mortality due to their low sensitivity and specificity because these scores relied on physiological factors and didn't exclude systemic comorbidities.
Mediatory role of executive functioning in children and youth with Down syndrome

: Individuals with Down syndrome (DS) commonly experience challenges with sleep, executive functioning, everyday memory, and symptoms of attention deficit hyperactivity disorder (ADHD). A path analysis was conducted to determine if executive function mediated the relationship between sleep problems and both everyday memory and ADHD symptoms. Parents of 96 children and youth with DS completed questionnaires related to sleep, executive functioning, everyday memory, and ADHD symptoms. Results showed that executive functioning fully mediated the relation between sleep and both everyday memory and ADHD symptoms. Implications for education and intervention for children and youth with DS are discussed. role of Abstract Individuals with Down syndrome (DS) commonly experience challenges with sleep, executive functioning, everyday memory, and symptoms of attention deficit hyperactivity disorder (ADHD). A path analysis was conducted to determine if executive function mediated the relationship between sleep problems and both everyday memory and ADHD symptoms. Parents of 96 children and youth with DS completed questionnaires related to sleep, executive functioning, everyday memory, and ADHD symptoms. Results showed that executive functioning fully mediated the relation between sleep and both everyday memory and ADHD symptoms. Implications for education and intervention for children and youth with DS are discussed. Everyday Memory. Observer Memory Questionnaire-Parent Form (OMQ-PF). The OMQ-PF is a 27-item questionnaire designed to measure child memory function in everyday scenarios from a parent’s perspective (Gonzalez et al., 2008). Each item is scored on a 5-point Likert scale and includes reverse-scored items. Higher scores are indicative of better memory function. The OMQ-PF demonstrates sound internal consistency among typically developing children (Gonzalez et al., 2008), adequate psychometric properties, and sound sensitivity to track the status of everyday memory function in participants with DS, ages 3-35 (Liogier d'Ardhuy et al., 2015; Spanò & Edgin, 2017). The OMQ-PF total score was used in analyses. a of each a 4-point scale: a summed score of the 18 items. Higher scores indicate more challenges with ADHD symptoms. The VADPRS acceptable internal consistency adequate for measuring ADHD in both clinical and research settings
Impact of a long-lived anticyclonic mesoscale eddy on seawater anomalies in the northeastern tropical Pacific Ocean: a composite analysis from hydrographic measurements, sea level altimetry data, and reanalysis model products

Abstract. Using observational data, satellite altimeters, and reanalysis model products, we have investigated eddy-induced seawater anomalies and heat and salt transport in the northeastern tropical Pacific Ocean. An eddy detection algorithm (EDA) was used to identify eddy formation at the Mexican Tehuantepec Gulf (TT) in July 2018 during an unusually strong summer wind event. The eddy separated from the coast with a mean translation velocity of 11 cm s−1 and a mean radius of 115 km and traveled 2050–2400 km westwards off the Central American coast, where it was followed at approx 114∘ W and 11∘ N for oceanographic observation between April and May 2019. The in situ observations show that the major eddy impacts are restricted to the upper 300 m of the water column and are traceable down to 1500 m water depth. In the eddy core at 92 m water depth an extreme positive temperature anomaly of 8.2 ∘C, a negative salinity anomaly of −0.78 psu, a positive fluorescence anomaly of +0.8 mg m−3, and a positive dissolved oxygen concentration anomaly of 137 µmol kg−1 are observed. Compared with annual climatological averages in 2018, the water trapped within the eddy is estimated to transport an average positive westward zonal heat anomaly of 85×1012 W and an average westward negative salt anomaly of -2.1×106 kg s−1. The heat transport is the equivalent of 1 % of the total annual zonal eddy-induced heat transport at this latitude in the Pacific Ocean. Understanding the dynamics of long-lived mesoscale eddies that may reach the seafloor in this region of the Pacific Ocean is especially important in light of potential deep-sea mining activities that are being targeted on this area.