To date, few studies have investigated the simultaneous effects of macro-scale parameters (MSPs) such as land use, population density, geology, and erosion layers on micro-scale water quality ...variables (MSWQVs). This research focused on an evaluation of the relationship between MSPs and MSWQVs in the Siminehrood River Basin, Iran. In addition, we investigated the importance of water particle travel time (hydrological distance) on this relationship. The MSWQVs included 13 physicochemical and biochemical parameters observed at 15 stations during three seasons. Primary screening was performed by utilizing three multivariate statistical analyses (Pearson's correlation, cluster and discriminant analyses) in seven series of observed data. These series included three separate seasonal data, three two-season data, and aggregated three-season data for investigation of relationships between MSPs and MSWQVs. Coupled data (pairs of MSWQVs and MSPs) repeated in at least two out of three statistical analyses were selected for final screening. The primary screening results demonstrated significant relationships between land use and phosphorus, total solids and turbidity, erosion levels and electrical conductivity, and erosion and total solids. Furthermore, water particle travel time effects were considered through three geographical pattern definitions of distance for each MSP by using two weighting methods. To find effective MSP factors on MSWQVs, a multivariate linear regression analysis was employed. Then, preliminary equations that estimated MSWQVs were developed. The preliminary equations were modified to adaptive equations to obtain the final models. The final models indicated that a new metric, referred to as hydrological distance, provided better MSWQV estimation and water quality prediction compared to the National Sanitation Foundation Water Quality Index.
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•We explored relation between water quality and macro-scale parameters (MSPs).•This relation was explored by considering a new distance (hydrological) type.•Results indicated that water quality parameters were highly correlated with MSPs.
The relationships of antioxidant properties (AOPs), measured by four conventional in vitro methods, with monosaccharides and glycosyl linkages in the polysaccharide, were evaluated using multiple ...linear regression analysis with minor modifications. Polysaccharides extracted from culture broth filtrates of Lentinula edodes were used as model samples for evaluation. Results indicate that the composition of monosaccharides and the type of glycosyl linkage modulates the AOPs of the polysaccharides. The AOPs of the polysaccharides were dependent on the ratios of different monosaccharides in the composition. Among the monosaccharides, rhamnose was the most significant determinant factor associated with AOPs. The glycosyl linkages of the monosaccharides also affected the anti-oxidation characteristics of the polysaccharides. Specifically, the arabinose 1→4 and mannose 1→2 linkages of the side-chain were significantly related to the reducing power, whereas the glucose 1→6 linkage and arabinose 1→4 linkages were related to the scavenging on DPPH− radicals.
Quantitative structure-property relationships are crucial for the understanding and prediction of the physical properties of complex materials. For fluid flow in porous materials, characterizing the ...geometry of the pore microstructure facilitates prediction of permeability, a key property that has been extensively studied in material science, geophysics and chemical engineering. In this work, we study the predictability of different structural descriptors via both linear regressions and neural networks. A large data set of 30,000 virtual, porous microstructures of different types, including both granular and continuous solid phases, is created for this end. We compute permeabilities of these structures using the lattice Boltzmann method, and characterize the pore space geometry using one-point correlation functions (porosity, specific surface), two-point surface-surface, surface-void, and void-void correlation functions, as well as the geodesic tortuosity as an implicit descriptor. Then, we study the prediction of the permeability using different combinations of these descriptors. We obtain significant improvements of performance when compared to a Kozeny-Carman regression with only lowest-order descriptors (porosity and specific surface). We find that combining all three two-point correlation functions and tortuosity provides the best prediction of permeability, with the void-void correlation function being the most informative individual descriptor. Moreover, the combination of porosity, specific surface, and geodesic tortuosity provides very good predictive performance. This shows that higher-order correlation functions are extremely useful for forming a general model for predicting physical properties of complex materials. Additionally, our results suggest that artificial neural networks are superior to the more conventional regression methods for establishing quantitative structure-property relationships. We make the data and code used publicly available to facilitate further development of permeability prediction methods.
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•YREB land structure is stable, landscape is fragmented and connectivity is reduced.•HQ distribution varies significantly, with high HQ widely distributed at best.•High HQ gradually ...converts to low, with some risk of HQ degradation.•Global view, there are different correlations between different LSPI and HQ.•Local view, LSPI promote or inhibit HQ, with clear spatiotemporal heterogeneity.
Recently, rapid economic development of the Yangtze River Economic Belt region in China and the growing problem of regional habitat quality have seriously threatened the process of biodiversity conservation in the Yangtze River Basin. Studying the impact of changes in landscape pattern indexes on habitat quality in the Yangtze River Economic Belt can provide policy insights for biodiversity conservation in the Yangtze River Basin. However, existing studies are still lacking in exploring the effects of changing landscape pattern indices on habitat quality under future scenarios. Based on the land use data of the Yangtze River Economic Belt from 2000 to 2020, this study simulates the land use situation in 2030, and analyzes the landscape pattern indexes and habitat quality during the 30 years, to investigate the impact of landscape pattern indexes on habitat quality at global and local scales through various methods. The results show that landscape patterns were significantly affected by human activities and land use types, with the Yangtze River Economic Belt experiencing increased levels of land use and structural stabilization during the three decades (Shannon Diversity Index increased from 0.90 in 2000 to 0.94 in 2030), fragmentation of the landscape (Landscape fragmentation index increase from 0.094 in 2000 to 0.102 in 2030), and weakened connectivity (contagion index decrease from 48.213 in 2000 to 45.437 in 2030). The Habitat Quality has a large variation in spatial distribution at the county scale, with an average change in habitat quality of 1.04 % from 2000 to 2030, and an overall downward trend. There is a strong localized spatial autocorrelation between landscape pattern indices and habitat quality, with significant spatial heterogeneity and some form of variability at time scales. The results of this study help to further understand the eco-environmental problems of the Yangtze River Economic Belt, and provide theoretical references for the formulation of ecological environmental protection policies and ecological functional area planning.
Kebutuhan masyarakat akan ruang untuk memenuhi kegiatannya benar-benar menyebabkan meningkatnya persaingan dalam pemerolehan dan juga meningkatnya nilai tanah. Ada banyak faktor yang mempengaruhi ...nilai tanah, salah satunya adalah jenis penggunaan lahan untuk memenuhi ruang untuk mendukung kegiatan mereka. Kondisi ini dapat diidentifikasi tidak hanya di daerah perkotaan tetapi juga di daerah pinggiran kota yang salah satu kebutuhan utama rumah tangga adalah memiliki ruang untuk tempat tinggal. Akibatnya, rumah tangga berusahan untuk memperoleh tanah, baik berasal dari lahan pertanian ataupun lahan permukiman, untuk pembangunan rumah. Tujuan dari penelitian ini adalah untuk menganalisis pola transaksi tanah dan peningkatan nilai tanah lahan pertanian dan lahan pemukiman di daerah perkotaan. Kabupaten Magelang Selatan dipilih sebagai daerah studi kasus karena ketersediaan data dan aksesibilitas untuk mengamati secara empiris faktor-faktor yang mempengaruhi nilai tanah. Analisis regresi berganda dipilih untuk memodelkan estimasi nilai tanah pertanian dan permukiman pada tahun 2016 dan 2019, sehingga peningkatan dan pola spasial nilai tanah dapat disajikan pada peta. Hasilnya menunjukkan bahwa selama 3 tahun, peningkatan nilai tanah pada lahan pertanian dan lahan permukiman tidak berbeda secara signifikan. Tercatat kenaikan lahan pertanian dan lahan permukiman sekitar Rp 360.000,- dan Rp 400.000,-. Dalam hal pola spasial, telah diidentifikasi bahwa semakin kecil ukuran tanah dan semakin dekat ke daerah permukiman, semakin tinggi estimasi nilai tanahnya.
•Inverse associations between chemical mixtures and child’s FIQ were observed.•Prenatal exposure to Pb and BPA were associated with decreased child’s FIQ.•Sex-stratified analyses showed stronger ...effects of chemical exposures in boys.•Integrating multiple statistical methods were beneficial to draw a more accurate conclusion.
Prenatal exposure to heavy metals, pesticides and phenols has been suggested to interfere with neurodevelopment, but the neurotoxicity of their mixtures is still unclear. We aimed to elucidate the associations of maternal urinary concentrations of selected chemical mixtures with intelligence quotient (IQ) in children.
Maternal urinary concentrations of selected heavy metals, pesticide metabolites, and phenols were quantified in pregnant women who participated in the Sheyang Mini Birth Cohort Study (SMBCS) from June 2009 to January 2010. At age 7 years, child’s IQ score was assessed using the Chinese version of Wechsler Intelligence Scale for Children (C-WISC) by trained pediatricians. Generalized linear regression models (GLM), Bayesian kernel machine regression (BKMR) models and elastic net regression (ENR) models were used to assess the associations of urinary concentrations individual chemicals and their mixtures with IQ scores of the 7-year-old children.
Of 326 mother-child pairs, single-chemical models indicated that prenatal urinary concentrations of lead (Pb) and bisphenol A (BPA) were significantly negatively associated with full intelligence quotient (FIQ) among children aged 7 years β = −2.31, 95% confidence interval (CI): −4.13, −0.48; p = 0.013, sex interaction p-value = 0.076; β = −1.18, 95% CI: −2.21, −0.15; p = 0.025; sex interaction p-value = 0.296, for Pb and BPA, respectively. Stratified analysis by sex indicated that the associations were only statistically significant in boys. In multi-chemical BKMR and ENR models, statistically significant inverse association was found between prenatal urinary Pb level and boy’s FIQ scores at 7 years. Furthermore, BKMR analysis indicated that the overall mixture was associated with decreases in boy’s IQ when all the chemicals’ concentrations were at their 75th percentiles or higher, compared to at their 50th percentiles. ENR models revealed that maternal urinary Pb levels were statistically significantly associated with lower FIQ scores (β = −2.20, 95% CI: −4.20, −0.20; p = 0.031).
Prenatal exposure to selected chemical mixtures may affect intellectual performance at 7 years of age, particularly in boys. Pb and BPA were suspected as primary chemicals associated with child neurodevelopment.
In this study, the rheological properties of cementitious systems were investigated through modeling studies on structural build-up and breakdown area. The area values were calculated using Herschel ...Bulkley analysis and hysteresis area method. The properties were examined by varying the composition of the cementitious system (cement fineness, C4AF, C3S, C2S, C3A, equivalent alkali and metakaolin ratio) and changes made in the rheological measurement processes (applied shear rate, maximum shear rate and duration). For this purpose, cement paste mixtures were prepared by substituting metakaolin at four different ratios (3%, 6%, 9%, and 12%) into cements with varying C3A content (2.13, 3.60, 6.82, 9.05%). The modeling study of the obtained results was conducted using three different learning methods: Linear Regression Analysis (LR), AdaBoost, and K Nearest Neighbor (KNN), encompassing machine learning and ensemble learning techniques. It was determined that the most dominant parameter affecting the rheology and thixotropic properties of the mixtures is the metakaolin usage ratio. The pre-shear rate was dominant over the duration and maximum shear rate parameters. Effect of the C3A content on dynamic yield stress and viscosity becomes more pronounced with an increase in the applied shear rate. The KNN method has yielded the best results in all experimental modeling studies. Euclidean distance criterion was used in the KNN method. Although the AdaBoost method obtained results close to the KNN method, the opposite situation was observed depending on the number of data. Logcosh, MAE and RMSE metrics were used to evaluate the experimental results. When the results for 3 different metrics in all modeling studies were examined, the success order of the metrics was found to be Logcosh, MAE and RMSE.
•Increase in C3A content and metakaolin ratio leads to an increase in DYS, V, and SBU.•KNN method has yielded the best results in all experimental modeling studies.•AdaBoost requires training with a large amount of data.
Herein, detailed mechanistic investigations into formamide-catalyzed nucleophilic substitution (S N ) of alcohols are reported. Alkoxyiminium chlorides and hexafluorophosphates were synthesized and ...characterized as a key intermediate of the catalytic cycle. The determination of reaction orders and control experiments indicated that the nucleophilic attack of the formamide catalyst onto the reagent BzCl is the rate-determining step. Linear free energy relationship revealed a correlation between the quantified Lewis basicity strength of formamides by means of 11B NMR spectroscopy and their catalytic activity in S N -transformations. The observed difference in catalytic ability was attributed to the natural bond order charge, dipole moment, and Sterimol parameter B5. Importantly, this rationalization enables the prediction of the capacity of formamides to promote S N -type transformations in general.
The theoretical study on the fixation and release of nitric oxide (NO) by N‐heterocyclic carbenes (NHCs) is explored by utilizing a multivariate linear regression approach. We utilized data‐driven ...tools to establish correlations between molecular descriptors of NHC and reaction outputs of the formation and NO release of NHC nitric oxide radicals (NHCNOs). A key electronic parameter, the singlet‐triplet energy gap (ΔEST), plays a pivotal role in the thermodynamics of NHCNO formation (ΔGf) and NO release (ΔGr). The activation energy models highlight HOMO energy level (EHOMO), C–N bond length (dC–N), and NBO charge on N atom (qNBON) as crucial factors for the formation of NHCNO (ΔG‡f), while the activation energy for the NO release (ΔG‡r) significantly correlates with free energy difference (ΔGr), resulting a strong ΔEST dependency. This study provides valuable insights into the thermodynamics and kinetics of NHCNO processes, offering predictive capabilities to design NHCs tailored for NO release.
In the countries such as Pakistan, for analyzing the losses and techniques in the power distribution and for mitigating, are the two active areas of research which is spread globally for increasing ...the accessibility of power irrespective of installing future generation equipment. As, the Technical Loss and the Non-Technical Loss are accounted by the total energy losses. They both are also referred as TL and NTLs. In terms of the non-technical losses there are major financial losses for the utility companies present in the countries that are in the developing stage. NTLs is the major cause for the additional losses and also it includes the part of damaging the network that includes the infrastructure and network reliability reduction. This paper is subjected to investigating the non-technical losses in terms of the power distribution systems. In addition to that, the consumer energy consumption information is used for analyzing the NTLs from Rawalpindi region from the different feeder source. The data of Low Voltage (LV) of the distribution network are focused more that consists of commercial, industrial, residential and agricultural consumers by the use of KWh interval data which is captured over a month using the smart meter infrastructure. The discussion of this review paper determines analysis and prevention techniques of NTLs to safeguard from the illegal use of the electricity in the distribution of electrical power system.
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