Magnitude Of Variation Research Articles

A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS

Abstract. The planetary boundary layer (PBL) is the lowermost part of the troposphere that governs the exchange of momentum, mass and heat between surface and atmosphere. To date, the radiosonde measurements have been extensively used to estimate PBL height (PBLH); suffering from low spatial coverage and temporal resolution, the radiosonde data are incapable of providing a diurnal description of PBLH across the globe. To fill this data gap, this paper aims to produce a temporally continuous PBLH dataset during the course of a day over the global land by applying machine learning algorithms to integrate high-resolution radiosonde measurements, ERA5 reanalysis, and the Global Land Data Assimilation System (GLDAS) product. This dataset covers the period from 2011 to 2021 with a temporal resolution of 3 h and a horizontal resolution of 0.25∘×0.25∘. The radiosonde dataset contains around 180 million profiles over 370 stations across the globe. The machine learning model was established by taking 18 parameters derived from ERA5 reanalysis and GLDAS as input variables, while the PBLH biases between radiosonde observations and ERA5 reanalysis were used as the learning targets. The input variables were presumably representative regarding the land properties, near-surface meteorological conditions, terrain elevations, lower tropospheric stabilities, and solar cycles. Once a state-of-the-art model had been trained, the model was then used to predict the PBLH bias at other grids across the globe with parameters acquired or derived from ERA5 and GLDAS. Eventually, the merged PBLH can be taken as the sum of the predicted PBLH bias and the PBLH retrieved from ERA5 reanalysis. Overall, this merged high-resolution PBLH dataset was globally consistent with the PBLH retrieved from radiosonde observations in terms of both magnitude and spatiotemporal variation, with a mean bias of as low as −0.9 m. The dataset and related codes are publicly available at https://doi.org/10.5281/zenodo.6498004 (Guo et al., 2022), and are of significance for a multitude of scientific research endeavors and applications, including air quality, convection initiation, climate, and climate change, to name but a few.

Investigating seasonal air quality variations consequent to the urban vegetation in the metropolis of Faisalabad, Pakistan

Urban atmospheric pollution is global problem and and have become increasingly critical in big cities around the world. Issue of toxic emissions has gained significant attention in the scientific community as the release of pollutants into the atmosphere rising continuously. Although, the Pakistani government has started the Pakistan Clean Air Program to control ambient air quality however, the desired air quality levels are yet to be reached. Since the process of mapping the dispersion of atmospheric pollutants in urban areas is intricate due to its dependence on multiple factors, such as urban vegetation and weather conditions. Therefore, present research focuses on two essential items: (1) the relationship between urban vegetation and atmospheric variables (temperature, relative humidity (RH), sound intensity (SI), CO, CO2, and particulate matter (PM0.5, PM1.0, and PM2.5) and (2) the effect of seasonal change on concentration and magnitude of atmospheric variables. A geographic Information System (GIS) was utilized to map urban atmospheric variables dispersion in the residential areas of Faisalabad, Pakistan. Pearson correlation and principal component analyses were performed to establish the relationship between urban atmospheric pollutants, urban vegetation, and seasonal variation. The results showed a positive correlation between urban vegetation, metrological factors, and most of the atmospheric pollutants. Furthermore, PM concentration showed a significant correlation with temperature and urban vegetation cover. GIS distribution maps for PM0.5, PM1.0, PM2.5, and CO2 pollutants showed the highest concentration of pollutants in poorly to the moderated vegetated areas. Therefore, it can be concluded that urban vegetation requires a rigorous design, planning, and cost–benefit analysis to maximize its positive environmental effects.

Recursive copula-augmented space-correlated temporal very-short term spatiotemporal probabilistic forecasting of the clear-sky index

This study introduces a recursive model framework for augmenting separate temporal probabilistic forecasts of multiple correlated time-series with a copula correlation model. The model is applied to the Markov-chain mixture distribution (MCM) model to spatiotemporally forecast minute resolution normalized solar irradiance, c.f. the clear-sky index, derived from radiometer array measurements of Global Horizontal Irradiance (GHI) for 18 geographically adjacent stations at Oahu, Hawaii, USA. The results are evaluated by univariate and multivariate probabilistic forecast metrics in comparison with forecasts from purely temporal MCM, Climatology and the spatiotemporal Multivariate Persistence Ensemble (MuPEn) benchmark. Results show that the Climatology and the MuPEn forecasts are most reliable, while superiority in sharpness, based on Prediction Interval Normalized Average Width (PINAW), depends on forecast horizon. In terms of accuracy, measured with the univariate measure Continuous Ranked Probability Score (CRPS), the MCM model (with and without copula) forecasts are most accurate for the first two steps ahead forecasts, while the Climatology and MuPEn both have superior score for longer horizons. In terms of multivariate scores, the accuracy estimate Energy Score results for the forecasts are similar to the CRPS, while the Variogram Score, which takes into consideration the correlational structure of the multivariate time-series, is significantly improved by the copula-augmented MCM model compared to the univariate MCM model. The MuPEn model generated the lowest Variogram Score among all models. Tests with fewer stations and swapped training and test data gave similar model-to-model relative dynamics with variations in magnitude.

Tantangan Pajak Karbon Sebagai Alternatif Kebijakan Transisi Energi Bersih di Indonesia Studi Kasus Industri Otomotif

Climate is the average weather where weather is the state of the atmosphere at a given point in time. Climate is defined as the average size and variability of relevant magnitudes of certain variables. Concrete activities in climate change mitigation are reducing and/or preventing greenhouse gas emissions released as a result of human activities. Various activities can be classified as climate change mitigation, including switching to public modes of transportation, using clean renewable energy, Carbon taxes are economically significant for reducing carbon emissions, Carbon Pricing can be used as a tool to determine the external cost of greenhouse gas (GHG) emissions. This study uses signaling theory which was first introduced by Spence in his research entitled job market signaling. The method used by researchers in qualitative descriptive writing with a literature review, the results of the study concluded that France, Sweden, Japan have succeeded in implementing taxes. Even though at the beginning of its implementation there were many objections from various parties and now it has succeeded in having a positive impact on the country's economy, while Indonesia will start implementing a carbon tax from April 2022 on the Coal-Fired Power Plant sector, the carbon tax rate applied is the same as the carbon price. on the carbon market but not less than IDR 30 per kilogram of CO? equivalent.

Person-centered maternity care during childbirth and associated factors among mothers who gave birth at public health institutions of Debre Markos town, Northwest Ethiopia, 2022: A cross-sectional study.

Person-centered maternity care is a crucial scheme for a positive childbirth experience. It enhances facility-based delivery, improves patient-provider communication, and increases women's satisfaction. However, there is limited evidence on the magnitude of person-centered care and certain variables were missed in Ethiopia. Therefore, this study assessed the magnitude of person-centered maternity care during childbirth and associated factors at health institutions of Debre Markos town, Ethiopia. Institution-based cross-sectional study was conducted at public health institutions of Debre Markos town. Participants were enrolled using systematic random sampling technique. Data were collected through face-to-face exit interviews, cleaned, coded, and entered into Epi-Data version 3.1 then exported to SPSS version 25 for analysis. After generating simple linear regression analysis, variables with p-value ⩽ 0.25 were fitted into multivariable linear regression model and p-value < 0.05 was declared statistically significant with 95% CI for β. Finally, study findings were presented using texts, tables, and figures. In this study, 380 women participated, with a response rate of 98.19%. The respondent's mean person-centered maternity care score was 56.83 with 95% CI: (55.83, 57.83). Mean score for sub-scale was 15.08 for dignity and respect, 14.42 for communication and autonomy, and 27.33 for supportive care. Commencing antenatal care during third trimester (β = -4.86, 95% CI: -8.22, -1.49), caesarean delivery (β = -5.78, 95% CI: -7.68, -3.87), college and above educational level of women (β = 3.75, 95% CI: 1.11, 6.39), being multiparous (β = 3.69, 95% CI: 1.85, 5.55), and health center delivery (β = 6.59, 95% CI: 4.17, 9.02) were factors significantly associated with person-centered maternity care. This study showed person-centered maternity care was low compared with World Health Organization standards. This informs local policymakers, district health offices, institutional healthcare administrators, and healthcare professionals of the discrepancies in achieving international standards of quality care.

Characterizing the most demanding passages of kinematic and mechanical activity in elite football: a multifactorial approach.

This study investigated the 5-minute most demanding passages (MDP) of kinematic (distance covered) and mechanical (acceleration and deceleration) activities in elite male football according to multifactorial criterion performance variables. Global positioning systems data were collected from 39 players across 45 matches in the Swedish first division (n = 329 observations). The multifactorial kinematic variable (MDPk) was composed of the concurrent distances covered at moderate-speed running, high-speed running, and sprinting distances, and the multifactorial mechanical (MDPm) considered the concurrent occurrences of high-intensity acceleration and deceleration activities. A moving average method was used to identify the MDP across a 5-minute period. The frequency distribution of the multifactorial variables, and differences in the time of occurrence and magnitude between multifactorial performance variables and their univariate constituent variables were investigated. Frequency distribution analysis revealed MDPk and MDPm peaked in the first 5 min of the match (MDPk: χ 2 (15, N = 329) = 135.88, p ≤ 0.001, W: 0.64, 115.99 ± 32.7 s; MDPm: χ 2 (15, N = 329) = 31.02, p ≤ 0.001, W: 0.31, 101.21 ± 25.1 s; p ≤ 0.0004). Within each half, differences in the MDP commencement time between the multifactorial variables and their respective discrete univariate constituent variables were trivial to small (MDPk effect size (ES): 0.04-0.21; MDPm ES: 0.02-0.11). Linear mixed model analysis demonstrated that the MDP magnitude of multifactorial variables were approximately 8-28% and 8-21% lower across the match and halves, respectively, compared to the MDP of their respective univariate constituent variables (p ≤ 0.001; r = 0.26-0.62). The greatest differences between the respective multifactorial and discrete constituent variables were observed for sprinting (-28%) and high-intensity acceleration (-22%). The results reveal that the MDP is distinguished based on peak kinematic and mechanical demands, which occur at discrete periods and exhibit distinct locomotor profiles across the match and within each half. Practitioners should consider the methods of identifying the MDP, as the selection of univariate and multifactorial kinematic and mechanical performance variables can impact MDP characterization, which can qualify the designing of bespoke training protocols.

The Relationship between Institutional Framework and International Trade: An Application of the Gravity Model

This study empirical investigated the relationship between institutional framework and Nigerian Trade spanning from 1998 to 2023 through the application of gravity model. The study considered rule of law (RoL), government effectiveness (GE), control of corruption (CoC), regulatory quality (RQ) and political and operational stability (POS) as tenets of institutional framework. The gravity regression model was used to determine the direction and magnitude of the independent variables on the dependent variable. The matrix correlation was used to check for multicollinearity among the independent variables, while the descriptive statistics was used to test for the normality of the variables. The results revealed that Nigeria has weak institutional framework. Also, the result revealed that POS, RoL and CoC had significant impact on Nigerian trade while RQ and GE had insignificant impact on Nigerian trade. The researcher recommended that Nigeria government should improve on its current institutional framework statue in-order to improve its trade.

The Influence of Maturity Status on Drop Jump Kinetics in Male Youth

Abstract Kumar, NTA, Radnor, JM, Oliver, JL, Lloyd, RS, CSCSD, Pedley, JS, Wong, MA, and Dobbs, IJ. The influence of maturity status on drop jump kinetics in male youth. J Strength Cond Res 38(1): 38–46, 2024—The aim of this study was to examine the effects of maturity status on drop jump (DJ) kinetics in young male athletes (categorized as early-pre–peak height velocity [PHV] [&lt;−2.51 years], late-pre-PHV [−1.99 to −1.00 years], circa-PHV [−0.50 to 0.50 years], and post-PHV [&gt;1.00 years]). All athletes performed a DJ from a 30-cm box onto force plates with performance variables (jump height, ground contact time, and reactive strength index) and absolute and relative kinetic variables during the braking and propulsive phases assessed. Subjects were categorized into GOOD (no impact-peak and spring-like), MODERATE (impact-peak and spring-like), or POOR (impact-peak and not spring-like) stretch-shortening cycle (SSC) function. The post-PHV group exhibited significantly greater values for most absolute kinetic variables compared with early-pre-PHV, late-pre-PHV, and circa-PHV (p &lt; 0.05). The differences observed between consecutive maturity groups were similar in magnitude for most absolute variables (Cohen's d = 0.53–1.70). Post-PHV male athletes outperform their less mature counterparts during a DJ, and this may be attributed to the growth and maturity-related structural and motor control strategy changes that occur in children. Stretch-shortening cycle function in boys seems to improve with maturity status reflected by a greater number of post-PHV participants displaying GOOD SSC function (65.8%) and a greater number of early-pre-PHV participants displaying POOR SSC function (54.4%). However, a number of mature boys displayed POOR SSC function (17.8%), suggesting that the development of SSC function is not exclusively related to maturation.

Cascade effects of climate and vegetation influencing the spatial variation of evapotranspiration in China

Evapotranspiration (ET) is generally affected by climate and vegetation, but the main factor controlling the spatial variation of ET largely varied with different regions. Clarifying the characteristics and dominant factor of ET in China is essential for understanding the regional ecosystem water balance. This study quantitatively assessed the magnitude and spatial variations of ET in China's terrestrial ecosystems using data measured by eddy covariance from 150 observation sites and investigated its underlying direct and indirect influencing factors. The results demonstrated that the ET of China's terrestrial ecosystems varied from 146.95 to 1125.33 mm, with an average value of 551.00 ± 204.12 mm. The ET showed a general increasing trend from the North to South, aligning with the latitudinal patterns of water availability (mean annual precipitation (MAP)), energy conditions (mean annual net radiation (MARn), and mean annual temperature (MAT)). Compared to regions at the same latitude, the North China Plain exhibited relatively higher ET because of the extensive cropland sites in the area. Furthermore, significant positive linear correlations were found between ET and MAT in the majority of ecosystems. However, a negative correlation of ET with MAT was observed in grasslands, which may be attributed to inconsistent responses of ET to MAT on the Tibetan Plateau and Inner Mongolia. Fractional vegetation coverage (FVC) exhibited a more significant direct influence on ET than climate factors (MARn, MAT, and MAP). Nevertheless, climate factors not only exert a direct influence on ET but also have cascade effects that affect FVC, thereby indirectly influencing the ET. When considering these cascade effects, MAP emerged as the dominant driver of spatial variations in ET of China's terrestrial ecosystems. This study provides essential information on variations of ET in China's terrestrial ecosystem and valuable insights for future explorations into the adaptive mechanisms underlying spatial variations of ET.

Obstructive Sleep Apnea: a risk for uncontrolled and more severe asthma in adults that we should keep an eye on.

Background. Asthma control can be influenced by several factors, including obstructive sleep apnea (OSA). The literature reports variable prevalence and magnitude of OSA impact on asthma outcomes. The aim of our study is to analyze the frequency of high-risk for OSA in asthma patients and its impact on disease severity and control. Methods. We conducted a cross-sectional study at an Allergy Department with adult asthma patients recruited while undergoing routine lung function tests. Data on sex, age, body mass index, allergen sensitization, smoking habits, risk of OSA (using the Berlin questionnaire), rhinitis control (through CARAT), asthma severity (based on GINA 2023), asthma control (using the ACT), adherence to asthma treatment (through Treatment Adherence Measure) and pulmonary function test results were collected. Results. We included 216 patients, predominantly women (70.4%), with a median (P25-P75) age of 29.0 (21.0-45.0) years, of whom 28.2% were on GINA treatment levels 4-5. In 75.5% of cases asthma was controlled. High-risk for OSA was identified in 21.8% of patients. Asthma patients with high-risk for OSA were more likely to have uncontrolled [(47.8%; n = 22) vs (15.8%; n = 26); p less than 0.001] and more severe disease [(44.7%; n = 21) vs (23.7%; n = 40), p = 0.006]. In multivariable analysis, high-risk for OSA (OR 2.81 [95%CI 1.1.28-6.17], p = 0.010), sex (women) (OR 5.21 [95% CI 1.70-15.96], p = 0.004), uncontrolled rhinitis (OR 3.65 [95%CI 1.38-9.64], p = 0.009) and GINA asthma treatment steps 4-5 (OR 2.46 [95%CI 1.15-5.26], p = 0.020) were associated with uncontrolled asthma. Conclusions. It is crucial to actively investigate OSA, especially in patients with uncontrolled and more severe forms of asthma.

Ternate and Trine - Spermatocytic Tumour

Spermatocytic Tumour emerges as a polymorphous, tripartite germ cell neoplasm reminiscent of developing spermatogonia, non-concordant to germ cell neoplasia in situ and demonstrates favorable prognostic outcomes. Tumefaction demonstrates aneuploidy and tumour cells characteristically lack anomalies within chromosome 12p. Cytological examination exhibits a cellular neoplastic component of variable magnitude as miniature cells, predominant intermediate cells and enlarged cells. Upon microscopy, pathognomonic tripartite cellular component is constituted of cells of variable magnitude described as miniature cells, intermediate cells and giant cells. Tumour configures nodules, cord-like pattern or peripheral inter-tubular cells enmeshed within a fibrinous perimeter.

Genetic Evaluation of Mid-Season Pea Genotypes of Himachal Pradesh, India

The prime and foremost objective of the study was to estimate the magnitude of genetic variability, heritability and genetic advance as per cent of the mean during the Rabi season of 2019-20 at the Research Farm of Dr YSP UHF, Nauni, (H.P.) among 30 genotypes and one check variety i.e. Pb-89, for quantitative traits. i.e. days to 50 per cent flowering, number of seeds per pod, Shelling (%), seed yield per plant (g) and 100 seed weight. As per the ANOVA result all the traits of genotypes vary significantly which shows that there is a large range of genetic variability. Based on mean performances, UHF PEA 42 and UHF PEA 63 were found superior to the recommended variety i.e. Pb-89. The value of PCV was found higher than the GCV. High values of GCV and PCV were recorded for seed yield. High heritability and high genetic advance were found for seed yield per plant indicating that these characteristics are genetically controlled by additive gene action and can be used for pea improvement through selection. The genotypes which showed superior results for the objectives under study were UHF PEA 42, UHF PEA 63 and Pb-89 and can be utilized for further breeding programmes of peas.

Predicting opinion using deep learning: From burning to sustainable management of organic waste in Indian State of Punjab.

In winter season, the burning of crop residues for ease of sowing the next crop, along with industrial emissions and vehicular pollution leads to settling of a thick layer of smog in northern part of India. Therefore, to understand the opinion of farmers regarding sustainable management of organic waste, the present study was conducted in Ludhiana district of Indian state of Punjab. An ex post facto research design was used and a total of 800 dairy farmers having significant crop area were selected randomly for the study, grouped equally as small and large dairy farmers. Results revealed that majority of farmers had a highly favourable opinion regarding organic waste management due to the fact that they were aware of the ill-effects of undesirable practices like crop residue burning. Further, to predict the farmers' opinion and the effect of independent variables on farmers' opinion, a multi-layer perceptron feed-forward deep neural network was developed with mean squared error of 0.036 and 0.137 for validation and training data sets respectively, marking a novel approach of analysing farmers' behaviour. The neural network highlighted that with increase in the magnitude of input variables, namely, education, experience in dairying, information source utilisation, knowledge regarding organic waste management, etc., the farmers' opinion regarding sustainable waste management increases. The study concluded with the impression that cognitive processes like education, information and knowledge play a significant role in forming the opinion of the farmers. Therefore, efforts focusing on enhancing cognition should be made for sustainable management of organic waste.

Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted Tg N2 O-N year-1 and Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

Estimation of Nature and Magnitude of Genetic Variability, Heritability and Genetic Advance for Yield and Its Contributing Traits in Wheat (Triticum aestivum L.)

The present research investigation was conducted at AKS University, Satna, Madhya Pradesh during rabi Season of 2022. Altogether 20 wheat genotypes were grown under RBD design with three replications. In the present study various parameters of genetic variability, broad sense heritability and genetic advance estimates of wheat crop. Analysis of variance revealed that the mean sum of square showed significant due to genotypes for all the 12 characters studied. Analysis of variance for the design of experiment revealed highly significant difference for all the characters which expressed huge amount of diversity among 20 genotypes of wheat. Phenotypic coefficients of variation (PCV) were higher than genotypic coefficients of variation (GCV) for all the characters. The maximum GCV and PCV were observed for ear length (cm) (26.37 &amp; 27.04) followed by number of productive tillers per plant (23.72 &amp; 25.65) and test weight (21.76 &amp; 22.57 g). The maximum value of heritability was shown by number of spikelets per ear (98.05), number of seed per spike (97.59), ear length (95.12cm), test weight (92.99 g), biological yield per plant (91.99 g), plant height (89.86 cm), seed yield per plant (87.28 g), days to maturity (86.67) and number of productive tillers per plant (85.56). The highest genetic advance was found for number of productive tillers per plant (45.20), number of seed per spike (43.60), test weight (43.24 g), seed yield per plant (37.37 g), no of ears par plant (34.99) and number of spikelets per ear (31.49). High heritability coupled with high genetic advance for the characters number of productive tillers per plant, no of ears per plant, ear length, number of spikelets per ear, number of seed per spike, test weight and seed yield per plant which indicated that above characters were governed by additive gene action and direct selection may be useful for further improvement program.

Modelling the seasonal cycle of Uranus’s colour and magnitude, and comparison with Neptune

ABSTRACT We present a quantitative analysis of the seasonal record of Uranus’s disc-averaged colour and photometric magnitude in Strömgren b and y filters (centred at 467 and 551 nm, respectively), recorded at the Lowell Observatory from 1950 to 2016, and supplemented with HST/WFC3 observations from 2016 to 2022. We find that the seasonal variations of magnitude can be explained by the lower abundance of methane at polar latitudes combined with a time-dependent increase of the reflectivity of the aerosol particles in layer near the methane condensation level at 1 – 2 bar. This increase in reflectivity is consistent with the addition of conservatively scattering particles to this layer, for which the modelled background haze particles are strongly absorbing at both blue and red wavelengths. We suggest that this additional component may come from a higher proportion of methane ice particles. We suggest that the increase in reflectivity of Uranus in both filters between the equinoxes in 1966 and 2007, noted by previous authors, might be related to Uranus’s distance from the Sun and the production rate of dark photochemical haze products. Finally, we find that although the visible colour of Uranus is less blue than Neptune, due to the increased aerosol thickness on Uranus, and this difference is greatest at Uranus’s solstices, it is much less significant than is commonly believed due to a long-standing misperception of Neptune’s ‘true’ colour. We describe how filter-imaging observations, such as those from Voyager-2/ISS and HST/WFC3, should be processed to yield accurate true colour representations.

Magnetocaloric, magnetostrictive and 57Fe Mössbauer studies of the multicomponent (Er,Y,Sm)Fe[formula omitted] compounds

The effect of substitutional 4f-elements on the magnetism of rare-earth compounds RFe2-type with the Laves phase structure is studied to find new multifunctional materials, as well as to define the macro- and microscopic parameters of multicomponent magnets. The crystal structure of (Er,Y,Sm)Fe2 compounds is investigated by X-ray powder diffraction. Detailed information on the magnetic properties of the iron sublattice for multicomponent compounds with three different rare-earth elements is obtained for the first time by means of the 57Fe Mössbauer spectroscopy. The main regularities in the magnitude variation of magnetocaloric effect and magnetostriction (linear, anisotropic and volume) in varying composition of the (Er,Y,Sm)Fe2 compounds are determined.

Intra- and inter-individual cognitive variability in schizophrenia and bipolar spectrum disorder: an investigation across multiple cognitive domains

There is substantial cognitive heterogeneity among patients with schizophrenia (SZ) and bipolar disorders (BD). More knowledge about the magnitude and clinical correlates of performance variability could improve our understanding of cognitive impairments. Using double generalized linear models (DGLMs) we investigated cognitive mean and variability differences between patients with SZ (n = 905) and BD spectrum disorders (n = 522), and healthy controls (HC, n = 1170) on twenty-two variables. The analysis revealed significant case-control differences on 90% of the variables. Compared to HC, patients showed larger intra-individual (within subject) variability across tests and larger inter-individual (between subject) variability in measures of fine-motor speed, mental processing speed, and inhibitory control (SZ and BD), and in verbal learning and memory and intellectual functioning (SZ). In SZ, we found that lager intra -and inter (on inhibitory control and speed functions) individual variability, was associated with lower functioning and more negative symptoms. Inter-individual variability on single measures of memory and intellectual function was additionally associated with disorganized and positive symptoms, and use of antidepressants. In BD, there were no within-subject associations with symptom severity. However, greater inter-individual variability (primarily on inhibitory control and speeded functions) was associated with lower functioning, more negative -and disorganized symptoms, earlier age at onset, longer duration of illness, and increased medication use. These results highlight larger individual differences in patients compared to controls on various cognitive domains. Further investigations of the causes and correlates of individual differences in cognitive function are warranted.

The distribution of depth, volume, and basin shape for lakes in the conterminous United States

AbstractDepth regulates many attributes of aquatic ecosystems, but relatively few lakes are measured, and existing datasets are biased toward large lakes. To address this, we used a large dataset of maximum (Zmax; n = 16,831) and mean (Zmean; n = 5,881) depth observations to create new depth models, focusing on lakes &lt; 1,000 ha. We then used the models to characterize patterns in lake basin shape and volume. We included terrain metrics, water temperature and reflectance, polygon attributes, and other predictors in a random forest model. Our final models generally outperformed existing models (Zmax ; root mean square error [RMSE] = 8.0 m and Zmean ; RMSE = 3.0 m). Our models show that lake depth followed a Pareto distribution, with 2.8 orders of magnitude fewer lakes for an order of magnitude increase in depth. In addition, despite orders of magnitude variation in surface area, most size classes had a modal maximum depth of ~ 5 m. Concave (bowl‐shaped) lake basins represented 79% of all lakes, but lakes were more convex (funnel‐shaped) as surface area increased. Across the conterminous United States, 9.8% of all lake water was within the top meter of the water column, and 48% in the top 10 m. Excluding the Laurentian Great Lakes, we estimate the total volume in the conterminous United States is 1,057–1,294 km3, depending on whether Zmax or Zmean was modeled. Lake volume also exhibited substantial geographic variation, with high volumes in the upper Midwest, Northeast, and Florida and low volumes in the southwestern United States.

Earth observation satellite data-based assessment of wetland dynamics in the Kashmir Himalaya.

Earth observation (EO) technology offers enormous opportunities to assess the magnitude and patterns of spatial variability in wetlands over time. This study aims to assessthe spatial and temporalchanges in the wetlands of the Kashmir valley using multiple remote sensing satellite data products, Geographic Information System (GIS), and field observations. Moreover, role of major factors operating at different time scales including regional geology, climate, and human activities in driving the wetland change is presented. The dynamics of the wetlands are illustrated in the occurrence, seasonality, and recurrence of surface water, land cover transitions and loss patterns particularly for the period from 1984 to 2021. Constituting about 3% (495 Km2) of the total area, substantial and variable patterns of seasonal and annual changes are exhibited by the wetlands. The main transitions of the water surface reveal that 2% of the area has changed from permanent to seasonal; 8% is lost; 15% is new seasonal; 0.12% is permanently lost; and 0.3% is new permanent. About 22% of the area reveals increase in the intensity of water surface occurrence, whereas 44% shows no change, and 34% exhibits decrease. Bathymetric analysis suggests that the average depth of the wetlands ranges between 0.6 and 16.6m. In general, alpine wetlands are relatively deeper and mostly static in their structure whereas those in the floodplain are shallow, fragmented, and showing signs of depletion during the assessment period. The results of this assessment will inform the policy on conservation and sustainability of wetlands in the Kashmir Himalaya.