Statistical Weight Research Articles

Landslide susceptibility mapping using hybridized block modular intelligence model

Landslide susceptibility map (LSM) provide useful tool for decision makers in hazard mitigation concerns. In the present paper, a novel hybrid block-based neural network model (HBNN) for the purpose of producing high-resolution LSM was developed. This hybrid approach was found through the mixture of expert modular structures and divide-and-conquer strategy incorporated with genetic algorithm (GA). The introduced HBNN then was applied on southern part of Guilan province (north of Iran) using 14 causative factors covering topographic and geomorphologic features, and geological and tectonical factors as well as hydrology, land data, and climate conditions. The landslide inventory map was provided using a synergy work from monitored events, interpretation of aerial photographs, and carried out geotechnical investigations in the area as well as field surveys. To insight, the predictability of proposed HBNN was compared with two developed models using multilayer perceptrons (MLPs) and generalized feed forward neural network (GFFN). The generated LSM was validated using receiver operating characteristic (ROC) curves, statistical error indices, and sensitivity and weight analyses as well as monitored landslides. Based on the compared metrics, HBNN with 86.52% and 90.15% in prediction and success rate as well as 89.36% for precision-recall curve demonstrated more consistent tool for future landslide susceptibility zonation. This implies on capability of developed HBNN in producing higher resolution and more reliable LSM for urban and land-use planners.

Evaluation of the efficacy of low-dose liraglutide in weight control among Taiwanese non-diabetes patients.

Aims/IntroductionObesity and metabolic syndrome are well‐known to be associated with multiple chronic diseases. Currently, high‐dose liraglutide has been used for weight control in non‐diabetic patients. Considering incretin‐based therapy is more effective in Asian populations, the effect of low‐dose liraglutide in weight control among these non‐diabetic groups has not been well evaluated. Our study aimed to evaluate the efficacy of low‐dose liraglutide in weight control among Taiwan patients.Materials and MethodsFrom July 2017 to December 2018, 46 non‐diabetic patients with metabolic syndrome were included. They had received low‐dose liraglutide at 0.6 or 1.2 mg per day for weight reduction for 12 weeks. After then, changes in bodyweight, waist and metabolic factors were examined. Overt bodyweight reduction was defined as a decrease of >5% within 12 weeks.ResultsWith 12 weeks of medication use, both groups showed statistical weight reduction. Higher doses of liraglutide had better efficacy, and 44.4% of patients in the liraglutide 1.2 mg group reached overt weight reduction, whereas just 32.1% in the 0.6 mg group had achieved this. Young age was found to be a predictor factor for a positive finding (odds ratio 0.941, P = 0.037). Early responders with decreased bodyweight of >4.2% within the first 4 weeks indicated a better chance to achieve measurable weight reduction.ConclusionsLow‐dose liraglutide still has high efficacy in weight reduction in Taiwanese people, especially for those of younger age.

Complex organic molecules in low-mass protostars on Solar System scales

Context. Complex organic molecules (COMs) are thought to form on icy dust grains in the earliest phase of star formation. The evolution of these COMs from the youngest Class 0/I protostellar phases toward the more evolved Class II phase is still not fully understood. Since planet formation seems to start early, and mature disks are too cold for characteristic COM emission lines, studying the inventory of COMs on Solar- System scales in the Class 0/I stage is relevant. Aims. Our aim is to determine the abundance ratios of oxygen-bearing COMs in Class 0 protostellar systems on scales of ~100 AU radius. We aim to compare these abundances with one another, and to the abundances of other low-mass protostars such as IRAS 16293-2422B and HH 212. Additionally, using both cold and hot COM lines, the gas-phase abundances can be tracked from a cold to a hot component, and ultimately be compared with those in ices to be measured with the James Webb Space Telescope (JWST). The abundance of deuterated methanol allows us to probe the ambient temperature during the formation of this species. Methods. ALMA Band 3 (3 mm) and Band 6 (1 mm) observations are obtained for seven Class 0 protostars in the Perseus and Serpens star-forming regions. By modeling the inner protostellar region using local thermodynamic equilibrium models, the excitation temperature and column densities are determined for several O-bearing COMs including methanol (CH3OH), acetaldehyde (CH3CHO), methyl formate (CH3OCHO), and dimethyl ether (CH3OCH3). Abundance ratios are taken with respect to CH3OH. Results. Three out of the seven of the observed sources, B1-c, B1-bS (both Perseus), and Serpens S68N (Serpens), show COM emission. No clear correlation seems to exist between the occurrence of COMs and source luminosity. The abundances of several COMs such as CH3OCHO, CH3OCH3, acetone (CH3COCH3), and ethylene glycol ((CH2OH)2) are remarkably similar for the three COM-rich sources; this similarity also extends to IRAS 16293-2422B and HH 212, even though collectively these sources originate from four different star-forming regions (i.e., Perseus, Serpens, Ophiuchus, and Orion). For other COMs like CH3CHO, ethanol (CH3CH2OH), and glycolaldehyde (CH2OHCHO), the abundances differ by up to an order of magnitude, indicating that local source conditions become important. B1-c hosts a cold (Tex ≈ 60 K), more extended component of COM emission with a column density of typically a few percent of the warm/hot (Tex ~ 200 K) central component. A D/H ratio of 1–3% is derived for B1-c, S68N, and B1-bS based on the CH2DOH/CH3OH ratio (taking into account statistical weighting) suggesting a temperature of ~15 K during the formation of methanol. This ratio is consistent with other low-mass protostars, but is lower than for high-mass star-forming regions. Conclusions. The abundance ratios of most O-bearing COMs are roughly fixed between different star-forming regions, and are presumably set at an earlier cold prestellar phase. For several COMs, local source properties become important. Future mid-infrared facilities such as JWST/MIRI will be essential for the direct observation of COM ices. Combining this with a larger sample of COM-rich sources with ALMA will allow ice and gas-phase abundances to be directly linked in order to constrain the routes that produce and maintain chemical complexity during the star formation process.

Using Statistical Weighting and Popularity Ranking for Extractive Summarization

This paper presents additions to the TextRank technique in extractive summarization. While the paper outlines several methods, the most novel method involves a combination of the TextRank algorithm (Mihalcea and Tarau, 2004) and a statistical weighted distribution. This system highlights which parts of the text are best for an extractive summarization. The results of this system are marginally better than our baseline and comparable to the Lede-3 Baseline (Grusky et al., 2018) which is the current best extractive system tested under the Cornell NEWSROOM dataset (Grusky et al., 2018),

To What Extend Does the Eddy Covariance Footprint Cutoff Influence the Estimation of Surface Energy Fluxes Using Two Source Energy Balance Model and High-Resolution Imagery in Commercial Vineyards?

Validation of surface energy fluxes from remote sensing sources is performed using instantaneous field measurements obtained from eddy covariance (EC) instrumentation. An eddy covariance measurement is characterized by a footprint function / weighted area function that describes the mathematical relationship between the spatial distribution of surface flux sources and their corresponding magnitude. The orientation and size of each flux footprint / source area depends on the micro-meteorological conditions at the site as measured by the EC towers, including turbulence fluxes, friction velocity (ustar), and wind speed, all of which influence the dimensions and orientation of the footprint. The total statistical weight of the footprint is equal to unity. However, due to the large size of the source area / footprint, a statistical weight cutoff of less than one is considered, ranging between 0.85 and 0.95, to ensure that the footprint model is located inside the study area. This results in a degree of uncertainty when comparing the modeled fluxes from remote sensing energy models (i.e., TSEB2T) against the EC field measurements. In this research effort, the sensitivity of instantaneous and daily surface energy flux estimates to footprint weight cutoffs are evaluated using energy balance fluxes estimated with multispectral imagery acquired by AggieAir sUAS (small Unmanned Aerial Vehicle) over commercial vineyards near Lodi, California, as part of the ARS-USDA Agricultural Research Service's Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project. The instantaneous fluxes from the eddy covariance tower will be compared against instantaneous fluxes obtained from different TSEB2T aggregated footprint weights (cutoffs). The results indicate that the size, shape, and weight of pixels inside the footprint source area are strongly influenced by the cutoff values. Small cutoff values, such as 0.3 and 0.35, yielded high weights for pixels located within the footprint domain, while large cutoffs, such as 0.9 and 0.95, result in low weights. The results also indicate that the distribution of modelled LE values within the footprint source area are influenced by the cutoff values. A wide variation in LE was observed at high cutoffs, such as 0.90 and 0.95, while a low variation was observed at small cutoff values, such as 0.3. This happens due to the large number of pixel units involved inside the footprint domain when using high cutoff values, whereas a limited number of pixels are obtained at lower cutoff values.

Use of the Win Ratio in Cardiovascular Trials

ObjectivesThe purpose of this study was to compare the win ratio (WR) with the corresponding hazard ratios (HRs) and 1/HR. BackgroundThe primary outcome in many cardiovascular trials is a composite that includes nonfatal and fatal events. The time-to-first event analysis gives equal statistical weighting to each component event. The WR, which takes into account the clinical importance and timing of the outcomes, has been suggested as an alternative approach. MethodsCox proportional hazards models and WR. ResultsIn the these trials (n = 16) the WR and HR differed only slightly. For example, in the PARADIGM-HF (sacubitril/valsartan vs. enalapril), the primary outcome of time to first heart failure hospitalization (HFH) or cardiovascular death (CVD) and use of the Cox model gave a 1/HR of 1.25 (95% confidence interval [CI]: 1.12 to 1. 41; z-score = 4.8). Using WR for testing this composite in the hierarchical order of CVD and HFH gave a WR of 1.27 (95% CI: 1.15 to 1.39; z-score = 4.7), reflecting an effect similar to that of sacubitril/valsartan therapy on CVD and HFH. In the DIG (digoxin vs. placebo) trial, the outcome of time-to-first HFH or CVD using Cox gave a 1/HR of 1.18 (95% CI: 1.10 to 1.27; z-score = 4.5). Using the WR for testing this composite in the hierarchical order of CVD and HFH gave a WR of 1.14 (95% CI: 1.05 to 1.20; z-score = 3.1), reflecting a larger effect of digoxin on HFH than on CVD. Several other trials and endpoints including patient-reported measurements were studied. ConclusionsIn 16 large cardiovascular outcome trials, HR and WR provided similar estimates of treatment effects. The WR allows prioritization of fatal outcomes and the hierarchical testing of broader composite endpoints including patient-reported outcomes. In this way, the WR allows for the incorporation of patient-centered and other outcomes, while prioritizing the competing risk of death and hospital admission.

SPIRITUALITY OR SOCIO-ECOLOGY? – STUDY OF THE PSYCHOMETRIC PROPERTIES OF SPIRITUAL WELL-BEING QUESTIONNAIRE IN AN ECLECTIC SAMPLE OF BELIEVERS

The Spiritual Well-being Questionnaire (SWBQ) was widely studied as a psychological instrument; yet, there is a lack of its use in non-religious research. This study aimed to investigate the psychometric properties of the SWBQ in a sample of practising believers, non-practising believers, sceptics and atheists. A total number of 279 participants aged between 17 and 69 (M=24.42, SD=9.463) completed the SWBQ and socio-demographic measurements. The SWBQ’s factorial structure proved to be different from the original version, suggesting inconsistencies between content validity and factorial validity. Environmental Domain was the factor with the greatest statistical weight in the scale's total variance. SWBQ’s metrical properties are contrary to a synergic spirituality.

Scaling factors for multi-region stock assessments, with an application to Indian Ocean tropical tunas

Stock assessments may be spatially structured, with regions that contain separate but linked subpopulations. In such multi-region models we must determine the relative abundances among regions. Regional scaling, which has been used since 2005 in tuna assessments, estimates the relative abundance distribution from regional catch rates and areas. We describe the method and explore potential improvements to the current practice. Supported improvements included using cell ocean areas in scaling calculations; adjusting statistical weights in the standardization model based on the density of samples; including fleet effects in the standardization model; and using a region-season interaction term in the standardization model rather than a year-season term. We also recommend the use of operational data to estimate regional scaling factors.

Parameterization of dilute Ising model for iron-containing lanthanum gallate and aluminate solid solutions based on first-principles calculations

Calculations of the cubic models of two solid solutions LaGa0.5Fe0.5O3 and LaAl0.5Fe0.5O3 have been performed within the hybrid density functional theory. Multiple configurations have been considered for the solid solutions resulting from a different distribution of Fe atoms over the p-metal (Ga or Al) positions accounting for different spin orientation for Fe atoms themselves. It was demonstrated that 27 structures for both LaGa0.5Fe0.5O3 and LaAl0.5Fe0.5O3 should be treated to account for all the possible configurations in case of cubic 2 × 2 × 2 supercell. Optimized geometry, energy, and electron properties were calculated for all the obtained configurations. Statistical weights and probabilities were estimated for each symmetry non-equivalent configuration of the solid solutions within the canonical ensemble. A new parameterization for the dilute Ising model has been proposed. In this model, we account for non-magnetic contributions, which are absent in the simple Ising model, using the lattice approach based on the concept of interchange energy. Two model parameters (the magnetic coupling constant and interchange energy) were fitted to the calculated total energies of all considered configurations of both solid solutions. The dilute Ising model confirmed the benefit of Fe-clustering in doped lanthanum gallate against aluminate. Different signs of the estimated interchange energy enable us to explain the reasons for such differences.

Charge and spin degrees of freedom in strongly correlated systems: Mott states opposite Hund’s metals

A correlated metallic state can arise as a result of the presence either strong charge or strong spin fluctuations. In the first case, as was shown first in (2004 Phys. Today 57 53) for the Hubbard model on the Bethe lattice, the system is a correlated metallic state close to the Mott-insulator state if the ratio of the value of the Coulomb interaction parameter U and the band width W is . The later case exist if and Hund’s exchange parameter . In both cases narrowing of the bands near the Fermi level and renormalization of the effective electron mass is observed, although the mechanism for realizing this state will be fundamentally different. We performed the electronic structure calculations of the paramagnetic phase -iron which is a typical Hund’s metal. We showed that the statistical distribution of charge between possible electronic d-configurations has a very weak dependence on the exchange interaction and is specific for metals. At the same time, the distribution of statistical weights between different spin configurations fundamentally changes with the inclusion of J. If we neglect Hund’s interaction by setting J = 0, the contributions from the low-spin configurations for all possible charge states dominate. The exchange interaction causes a redistribution of probability in favor of high-spin multiplets, leading to the formation of a larger local moment. We also performed calculations for the two-bands half-filled model. By varying the values of the Coulomb and Hund’s exchange interaction parameters, we reproduced the region of the phase diagram of the model in which the system undergoes a transition from the Mott-insulator state to the Hund’s metal. This transition is accompanied by a change in the statistical probability distribution of possible multiple configurations. In the region corresponding to the Hund’s metal state, a change of J leads to the effect of weights redistribution similar that we observe in -iron.

Modification and optimization of DRASTIC model for groundwater vulnerability and contamination risk assessment for Bhiwadi region of Rajasthan, India

The objective of the study is to estimate groundwater vulnerability against contamination in Bhiwadi region of Rajasthan by applying geographical information system (GIS)-based DRASTIC model which considers seven hydrogeological parameters of an aquifer: depth to water (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C). The groundwater vulnerability (intrinsic vulnerability) and risk assessment (specific vulnerability) is done using original DRASTIC as well as modified DRASTIC to find the best-suited model for the study area. Groundwater risk assessment is done by integrating land use map with appropriate weight and ratings with vulnerability map. The study methodology includes modification of DRASTIC parameter ratings based on the mean chromium (Cr) concentration of each parameter range through simple statistical technique and DRASTIC parameter weight modification by two different methods: (1) maximizing coefficient of correlation between vulnerability index and chromium (Cr) concentration using generalized reduced gradient (GRG) solver package in excel (2) single parameter sensitivity analysis (SPSA) for evaluating effective weight based on influence of individual parameter on vulnerability index. The DRASTIC parameter ratings modified on the basis of chromium concentration gives very low correlation coefficient (r = 0.24) due to less correlation of ratings of depth to the water table, slope and vadose zone to chromium concentration, hence no revision of parameter ratings is required for the study area. Compared to the correlation coefficient (r = 0.3) of original DRASTIC, weight modified DRASTIC, based on SPSA method gives r = 0.35 and GRG optimizing solver gives r = 0.37, indicating improvement in correlation coefficient due to weight modification. The result also shows that GRG optimizing solver gives better correlation coefficient than SPSA method. The best correlation coefficient (r = 0.41) between vulnerability index and chromium concentration is obtained by weight modification (using GRG optimizing solver) and including land-use layer in the original DRASTIC model. The result indicates that integration of DRASTIC with land use improved the correlation coefficient between chromium concentration and vulnerability index for original as well as ratings and weight modified DRASTIC models. The sensitivity analysis test performed indicates that recharge is the most sensitive parameter whereas soil is the least sensitive parameter in the study area. The study confirms that modification and optimization of DRASTIC model by means of weight modification as well as the integration of land use layer in original DRASTIC increases the correlation coefficient and gives a more accurate assessment of groundwater vulnerability to chromium contamination in the study area.

Bivariate superstatistics based on generalized gamma distribution

The univariate gamma (chi-squared) superstatistics has been used in several applications by assuming independence between systems. However, in some cases it seems more reasonable to consider a dependence structure. This fact motivates the introduction of a family of bivariate superstatistics based on an extension of the gamma distribution, defined by generalized hypergeometric functions. The particular cases include Boltzmann and other statistical weighting factors in the literature. Numerical illustrations show the behaviour of the proposed superstatistics.

Reducing the Dependence of the Neural Network Function to Systematic Uncertainties in the Input Space

Applications of neural networks to data analyses in natural sciences are complicated by the fact that many inputs are subject to systematic uncertainties. To control the dependence of the neural network function to variations of the input space within these systematic uncertainties, several methods have been proposed. In this work, we propose a new approach of training the neural network by introducing penalties on the variation of the neural network output directly in the loss function. This is achieved at the cost of only a small number of additional hyperparameters. It can also be pursued by treating all systematic variations in the form of statistical weights. The proposed method is demonstrated with a simple example, based on pseudo-experiments, and by a more complex example from high-energy particle physics.

In vivo anti-obesity effects of Monascus pigment threonine derivative with enhanced hydrophilicity

Abstract The hydrophobicity and anti-obesity characteristics of the threonine (Thr) derivative of Monascus pigment were determined and compared with 2-(p-tolyl)-ethylamine (TEA) and tryptophan (Trp) derivatives of the same. Treatment by all three derivatives decreased body weight gain, epididymal fat weight, and abdominal fat in mice. The lowest body weight gain and epididymal fat weight were observed with the Monascus-Thr derivative treatment, which is more hydrophilic than other the other treatments tested. Further in vivo tests with the Thr derivative at different concentrations demonstrated that body weight, epididymal fat weight, and serum lipid level are reduced in a concentration-dependent manner. Significant reduction was exhibited at 0.10 mg/g-mouse/day of the Thr derivative, and less reduction was observed at 0.05 or 0.01 mg/g-mouse/day. In comparison with mice fed a normal diet, there was no statistical weight change in the liver, kidney, or spleen, indicating the Thr derivative was not toxic to mice.

Atomic Data for Calculation of the Intensities of Stark Components of Excited Hydrogen Atoms in Fusion Plasmas

Motional Stark effect (MSE) spectroscopy represents a unique diagnostic tool capable of determining the magnitude of the magnetic field and its direction in the core of fusion plasmas. The primary excitation channel for fast hydrogen atoms in injected neutral beams, with energy in the range of 25–1000 keV, is due to collisions with protons and impurity ions (e.g., He 2 + and heavier impurities). As a result of such excitation, at the particle density of 10 13 –10 14 cm − 3 , the line intensities of the Stark multiplets do not follow statistical expectations (i.e., the populations of fine-structure levels within the same principal quantum number n are not proportional to their statistical weights). Hence, any realistic modeling of MSE spectra has to include the relevant collisional atomic data. In this paper we provide a general expression for the excitation cross sections in parabolic states within n = 3 for an arbitrary orientation between the direction of the motion-induced electric field and the proton-atom collisional axis. The calculations make use of the density matrix obtained with the atomic orbital close coupling method and the method can be applied to other collisional systems (e.g., He 2 + , Be 4 + , C 6 + , etc.). The resulting cross sections are given as simple fits that can be directly applied to spectral modeling. For illustration we note that the asymmetry detected in the first classical cathode ray experiments between the red- and blue-shifted spectral components can be quantitatively studied using the proposed approach.

Comparison of locally weighted PLS strategies for regression and discrimination on agronomic NIR data

AbstractIn multivariate calibrations, locally weighted partial least squared regression (LWPLSR) is an efficient prediction method when heterogeneity of data generates nonlinear relations (curvatures and clustering) between the response and the explicative variables. This is frequent in agronomic data sets that gather materials of different natures or origins. LWPLSR is a particular case of weighted PLSR (WPLSR; ie, a statistical weight different from the standard 1/n is given to each of the n calibration observations for calculating the PLS scores/loadings and the predictions). In LWPLSR, the weights depend from the dissimilarity (which has to be defined and calculated) to the new observation to predict. This article compares two strategies of LWPLSR: (a) “LW”: the usual strategy where, for each new observation to predict, a WPLSR is applied to the n calibration observations (ie, entire calibration set) vs (b) “KNN‐LW”: a number of k nearest neighbors to the observation to predict are preliminary selected in the training set and WPLSR is applied only to this selected KNN set. On three illustrating agronomic data sets (quantitative and discrimination predictions), both strategies overpassed the standard PLSR. LW and KNN‐LW had close prediction performances, but KNN‐LW was much faster in computation time. KNN‐LW strategy is therefore recommended for large data sets. The article also presents a new algorithm for WPLSR, on the basis of the “improved kernel #1” algorithm, which is competitor and in general faster to the already published weighted PLS nonlinear iterative partial least squares (NIPALS).

Combined Linear Interaction Energy and Alchemical Solvation Free-Energy Approach for Protein-Binding Affinity Computation.

Calculating free energies of binding (ΔGbind) between ligands and their target protein is of major interest to drug discovery and safety, yet it is still associated with several challenges and difficulties. Linear interaction energy (LIE) is an efficient in silico method for ΔGbind computation. LIE models can be trained and used to directly calculate binding affinities from interaction energies involving ligands in the bound and unbound states only, and LIE can be combined with statistical weighting to calculate ΔGbind for flexible proteins that may bind their ligands in multiple orientations. Here, we investigate if LIE predictions can be effectively improved by explicitly including the entropy of (de)solvation into our free-energy calculations. For that purpose, we combine LIE calculations for the protein–ligand-bound state with explicit free-energy perturbation to rigorously compute the unbound ligand’s solvation free energy. We show that for 28 Cytochrome P450 2A6 (CYP2A6) ligands, coupling LIE with alchemical solvation free-energy calculation helps to improve obtained correlation between computed and reference (experimental) binding data.

Analysis of the first overtone bands of isotopologues of CO and SiO in stellar spectra

Context.This study is based on models of the first overtone (Δv= 2) bands of the monosubstituted isotopologues of CO at 2.3μm in the spectrum of Arcturus (K2 III) and of the monosubstituted isotopologues of SiO at 4μm in the spectrum of the red giant HD 196610 (M6 III).Aims.We aim to investigate problems involving the computation of the first overtone bands of isotopologues of CO and SiO in the spectra of late-type stars and to determine isotopic abundances.Methods.We used fits of theoretical synthetic spectra to the observed stellar molecular bands of CO and SiO for determining the abundances for isotopes of C, O, and Si.Results.Fits of synthetic spectra of the12C16O first overtone bands at 2.3μm computed with three available line lists to the observed spectrum of Arcturus provide the same carbon abundance [C] = − 0.6 and isotopic ratio of carbon12C/13C = 10 ± 2. However, the quality of fits to the observed spectrum differ for three line lists used. Furthermore, the derived oxygen isotopic ratio16O/18O = 2000 ± 500 is larger than that known in the solar system, where16O/18O = 500. The silicon isotopic ratio in the atmosphere of the red giant HD 196610 has been revised. Using the ExoMol SiO line list with appropriate statistical weights for the SiO isotopologues, the “non-solar” ratio28Si:29Si:30Si = 0.86 ± 0.03:0.12 ± 0.02:0.02 ± 0.01 is obtained.Conclusions.We find that: (a) the computed isotopic carbon and silicon ratios determined by the fits to the observed spectrum depend on the adopted abundance of C and Si, respectively; and (b) Correct treatment of the nuclear spin degeneracies parameter is of crucial importance for today’s application of HITRAN and ExoMol line lists in the astrophysical computations.

When classical trajectories get to quantum accuracy: II. The scattering of rotationally excited H2 on Pd(111).

The classical trajectory method in a quantum spirit assigns statistical weights to classical paths on the basis of two semiclassical corrections: Gaussian binning and the adiabaticity correction. This approach was recently applied to the heterogeneous gas-surface reaction between H2 in its internal ground state and Pd(111) surface e.g. [A. Rodríguez-Fernández et al., J. Phys. Chem. Lett., 2019, 10, 7629]. Its predictions of the sticking and state-resolved reflection probabilities were found to be in surprisingly good agreement with those of exact quantum time-dependent calculations where standard quasi-classical trajectory calculations failed. We show in this work that the quality of the previous calculations is maintained or even improved when H2 is rotationally excited.

Structural geological methods in the geotechnical practice – rock mass rating. Advantages and problems of the rating methods

This paper presents a review of the most common geotechnical rock rating methods. The directional properties of the rock’s anisotropies are exemplified, by a case of resolution of stresses in folded and foliated metamorphic rocks. In such rocks, depending on the geometry of the folds, the ambient stress field can generate varying shear potential along the foliation planes in different parts of the excavation. The commonly used rating schemes, with accent on the geological feasibility of the classifications, are discussed – Protodiakonov’s rock scale, Terzaghi’s grading for construction of tunnels, then the rock quality designation of Deere, the Bieniawski’s rock mass rating (RMR), the Hoek, and Brown’s GSI and the Barton’s Q-system. It is emphasized that in spite of its broad use, the RQD is distorting the statistical weight of the joint groups as some steeply dipping joints may be completely neglected. It is recognized that the RMR is the simplest to use but underestimates the directional properties of the rock anisotropies, which require better definition and has no provision for lithologically varying rock packages, although it has the advantage of using the uniaxial compressive strength, which other systems do not employ. The Hoek and Brown’s criterion went too far with complex empirical relationships, which rely on extensive laboratory testing, so it is no more field criterion. Besides, its geological descriptive powers are rather poor and now, new form of GSI classification is offered for nearly every lithological type. Barton’s Q-system, being best suited to case studies of actual underground constructions, suffers from the fact that is centered nearly exclusively on joints, which may be justified in Norway, where mainly magmatic and high grade metamorphic rocks are present but should be applied cautiously in areas, where sedimentary, volcanic and strongly foliated rocks are exposed. In general, for all the discussed geomechanical classification systems (RMR, GSI, Q) the rule is valid, that they work better in an isotropic, strong but jointed rock masses and do not work well in week layered and foliated rocks.