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International audience; Thermal treatments can be considered as an accelerated ageing, bringing partly similar changes in properties as naturally aged wood. Thermal treatment was applied on white mulberry (Morus alba L.), a dominant species for making musical instruments from middle-East to Far-East, to investigate the effects on the vibro-mechanical and physical properties of this wood, and the results compared to previously published data on spruce (Picea abies Karst.) as a reference for the soundboard of Western string instruments. Thermal treatment (TT) at 150 °C and 0% of relative humidity was applied to five analogous groups of specimens with five different durations (2.5, 8, 24, 72, 261 hours). Humidity reconditioning of specimens was done to explore the reversibility of TT effects. Physical and vibrational properties such as specific gravity (γ), equilibrium moisture content (EMC), CIELab colorimetric values, specific modulus of elasticity (E'/γ) and damping coefficient (tanδ) in longitudinal (L) and radial (R) directions, have been measured after stabilisation of samples in standard conditions (20 °C, 65% RH), before and after TT and then after reconditioning. Untreated mulberry had a low EMC, very low L/R anisotropy and low E'L/γ, and relatively low tanδ. Weight loss (WL) and CIELab values evolved similarly during TT for mulberry and for previous results on spruce, however, their EMC and vibrational properties were affected differently. This could be explained in part by the low anisotropy of mulberry, and in part by its particular extractives. The parts of irreversible effects, linked to chemical modification or degradation, and of reversible effects, linked to physical configuration, were different between mulberry and spruce. The applied treatments did not bring permanent "improvements" in vibrational properties of mulberry, yet its colour appearance was enhanced.

Purpose Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO2) into the atmosphere, resulting in adverse environmental impacts and high energy consumption. Increasing demand for CO2 consumption has urged construction companies and decision-makers to consider ecological efficiency affected by CO2 consumption. Therefore, this paper aims to develop a method capable of analyzing and assessing the eco-efficiency determining factor in Iran’s 22 local cement companies over 2015–2019. Design/methodology/approach This research uses two well-known artificial intelligence approaches, namely, optimization data envelopment analysis (DEA) and machine learning algorithms at the first and second steps, respectively, to fulfill the research aim. Meanwhile, to find the superior model, the CCR model, BBC model and additive DEA models to measure the efficiency of decision processes are used. A proportional decreasing or increasing of inputs/outputs is the main concern in measuring efficiency which neglect slacks, and hence, is a critical limitation of radial models. Thus, the additive model by considering desirable and undesirable outputs, as a well-known DEA non-proportional and non-radial model, is used to solve the problem. Additive models measure efficiency via slack variables. Considering both input-oriented and output-oriented is one of the main advantages of the additive model. Findings After applying the proposed model, the Malmquist productivity index is computed to evaluate the productivity of companies over 2015–2019. Although DEA is an appreciated method for evaluating, it fails to extract unknown information. Thus, machine learning algorithms play an important role in this step. Association rules are used to extract hidden rules and to introduce the three strongest rules. Finally, three data mining classification algorithms in three different tools have been applied to introduce the superior algorithm and tool. A new converting two-stage to single-stage model is proposed to obtain the eco-efficiency of the whole system. This model is proposed to fix the efficiency of a two-stage process and prevent the dependency on various weights. Converting undesirable outputs and desirable inputs to final desirable inputs in a single-stage model to minimize inputs, as well as turning desirable outputs to final desirable outputs in the single-stage model to maximize outputs to have a positive effect on the efficiency of the whole process. Originality/value The performance of the proposed approach provides us with a chance to recognize pattern recognition of the whole, combining DEA and data mining techniques during the selected period (five years from 2015 to 2019). Meanwhile, the cement industry is one of the foremost manufacturers of naturally harmful material using an undesirable by-product; specific stress is given to that pollution control investment or undesirable output while evaluating energy use efficiency. The significant concentration of the study is to respond to five preliminary questions.

International audience; Aim: The effects of nutrition and exercise on autophagy are not well studied. This study aimed to investigate the combined effects of high-fat diets (HFD) and exercise training (ET) on autophagy in white adipose tissue of mice.Materials and methods: Male C57BL/6 mice were assigned into four groups of 7 mice per group: (1) Control, (2) high-fat diet-induced obesity (HFD-Ob), (3) exercise training (ET), and (4) high-fat diet with exercise training (HFD-ET). The HFD-Ob group was fed a high-fat diet for 14 weeks, while the ET group continuously ran on a treadmill for five sessions per week for seven weeks, and the HFD-ET group had both HFD and exercise training. qReal-time-PCR and western blot were used to measure the mRNA and protein levels of autophagy markers in white adipose tissue.Results: Mice from the HFD group showed higher levels in autophagy-related gene5 (ATG5, p = 0.04), ATG7 (p = 0.002), cathepsin B (CTSB, p = 0.0004), LC3-II (p = 0.03) than control. Mice in the ET group displayed higher levels of genes for ATG7 (p = 0.0003), microtubule-associated protein1-light chain 3 (LC3, p = 0.05), lysosome-associated membrane protein 2 (LAMP2, p = 0.04) and cathepsin L (CTSL, p = 0.03) than control. Mice from the HFD-ET group had higher levels of genes for ATG7 (p = 0.05) and CTSL (p = 0.043) and lower levels of genes for CTSB (p = 0.045) compared to the HFD group and lower levels of LAMP2 (p = 0.02) compared to the ET group.Conclusion: There were increases in autophagosome formation in the white adipose tissue from mice in the HFD and ET groups. A combination of HFD and ET enhances autophagosome formation and modulates lysosomal degradation in white adipose tissue.

Garra roseae, new species, is described from the stream Tang-e-Sarhe in the Iranian Makran region. It is distinguished from its congeners in the Middle East by lacking barbels, having a small mental disc, 42-58 total scales along the lateral line, 24-30 scales along the predorsal midline, and 20-24 circumpeduncular scales. It is further characterised by having five diagnostic nucleotide substitutions and a minimum K2P distance of 5.39% to G. rossica and 5.49% to G. nudiventris in the mtDNA COI barcode region. Garra phryne from eastern Iran is considered to be a synonym of G. nudiventris., We are pleased to thank the University of Guilan for financial support.

International audience; Statistical parsers are trained on treebanks that are composed of a few thousand sentences. In order to prevent data sparseness and computational complexity, such parsers make strong independence hypotheses on the decisions that are made to build a syntactic tree. These independence hypotheses yield a decomposition of the syntactic structures into small pieces, which in turn prevent the parser from adequately modeling many lexico-syntactic phenomena like selectional constraints and subcategorization frames. Additionally, treebanks are several orders of magnitude too small to observe many lexico-syntactic regularities, such as selectional constraints and subcategorization frames. In this article, we propose a solution to both problems: how to account for patterns that exceed the size of the pieces that are modeled in the parser and how to obtain subcategorization frames and selectional constraints from raw corpora and incorporate them in the parsing process. The method proposed was evaluated on French and on English. The experiments on French showed a decrease of 41.6% of selectional constraint violations and a decrease of 22% of erroneous subcategorization frame assignment. These figures are lower for English: 16.21% in the first case and 8.83% in the second.

In Safragashteh forest of Fuman in north of Iran, there is a hazel stand, which has grown naturally. The aim of this research was to evaluate the plant communities and soil characteristics in the area. This study included 50 ha of hazel protected area. A selective sampling method was utilized to record 30 400 m2 for tree and shrub layers, and sub-plots of 100 m2 for herbaceous species. Soil samples were collected at the 30 plots. We found three ecological species groups in the study area. Corylus avellana and Epimedium pinnatum in first group, Fagus orientalis, Asperula odorata, Euphorbia amygdaloides, Carex sp., Fragaria vesca and Viola sylvestris in second group, and Crataegus microphylla, Ilex spinigera, Primula heterochroma, Sedum stoloniferum and Vicia crocea in thirth group were the indicator species. Sand percent was significantly highest in Corylus avellana group, while clay, nutrients elements, pH and SP were significantly highest in the other groups. Biodiversity indices in Corylus avellana group were significantly less than other stands. We recommend to provide comprehensive conservation and management programs in order to protect of common hazel, associated plant species, and to prevent of human activities such as recreational use and livestock.

The formaldehyde to urea molar ratio (F/U) plays an important role on the properties of urea formaldehyde (UF) resins and of the medium density fiber board (MDFs) bonded with them. This work presents a hypothesis that besides the final F/U molar ratio in UF resin preparation, the initial F/U affects both the formaldehyde emission levels and the physico-mechanical properties of the boards. Three initial molar ratios F/U of 1.9, 2.1 and 2.3 in resin synthesis have been examined in this work. The structural changes and thermal curing behavior of UF resins were tracked by 13C NMR and DSC, respectively. At parity of final F/U molar ratio, the resin with initial F/U = 2.1 yielded the highest proportion of linear methylol groups, resulted in the best internal bond strength and lowest thickness swelling of the board. A resin synthesized with the initial F/U = 1.9 provided the highest proportion of total methylene linkages, most methylene ether linkage and lowest free formaldehyde, consistently yielding the lowest formaldehyde emission. These results partially explained why UF resins with lower F/U molar ratios showed relatively poor adhesion when used to manufacture wood-based composites. MDFs bonded with a UF resin having the initial F/U = 2.3 had a relatively good performance with the exception of free formaldehyde, but also showed the best storage stability compared to the other resins having lower initial F/U molar ratios.

By increasing the changes in the last years of the second millennium, relying on the planning methods, which are based on forecasting, cannot meet the needs of management of countries at large scale. The heavy burden of uncertainties and emergence of interrupted and wild card events have changed the conditions in a way that future forecasting is not possible for planners. On the other hand, in regional and urban planning it is necessary to change the attitude from forecasting to foresight. Considering this, the paper attempts to introduce the approach of foresight as well as having a critical view of the current process of planning in foreseeing and future studies. Moreover, this study emphasizes the necessity of employing the foresight approach in the process of urban and regional studies.

International audience; For about 10 000 years, farmers have been managing cattle, sheep, and goats in a sustainable way, leading to animals that are well adapted to the local conditions. About 200 years ago, the situation started to change dramatically, with the rise of the concept of breed. All animals from the same breed began to be selected for the same phenotypic characteristics, and reproduction among breeds was seriously reduced. This corresponded to a strong fragmentation of the initial populations. A few decades ago, the selection pressures were increased again in order to further improve productivity, without enough emphasis on the preservation of the overall genetic diversity. The efficiency of modern selection methods successfully increased the production, but with a dramatic loss of genetic variability. Many industrial breeds now suffer from inbreeding, with effective population sizes falling below 50. With the development of these industrial breeds came economic pressure on farmers to abandon their traditional breeds, and many of these have recently become extinct as a result. This means that genetic resources in cattle, sheep, and goats are highly endangered, particularly in developed countries. It is therefore important to take measures that promote a sustainable management of these genetic resources; first, by in situ preservation of endangered breeds; second, by using selection programmes to restore the genetic diversity of industrial breeds; and finally, by protecting the wild relatives that might provide useful genetic resources.

1 Animal Genetic Resource Department, Institute of Biodiversity Conservation, Addis Ababa, Ethiopia 2 Laboratoire d’Ecologie Alpine, CNRS UMR 5553, Universite Joseph Fourier, Grenoble, France 3 Department of Environmental Sciences, University of Milano-Bicocca, Milano, Italy 4 Natural Resources Faculty, University of Guilan, Guilan, Iran 5 Environmental Sciences Department, Gorgan University of Agriculture and Natural Resources, Gorgan, Iran 6 Centro de Investigacao em Biodiversidade e Recursos Geneticos (CIBIO-UP), Universidade do Porto, Vairao, Portugal 7 Division of Biological Sciences, University of Montana, Missoula, MT, USA 8 Norwegian Institute for Nature Research, Trondheim, Norway

Fire usually causes changes in the composition and diversity of herbaceous species. The present paper aimed to study the effect of repeated fire incidents on understory species diversity in the Saravan forests of Guilan Province located in the north of Iran. To do so, three 50-hectare areas with identical physiographical conditions and overstory (hand-planted softwood Pinus taeda) were selected. Seven fire incidences occurred for the 10-year period in one of the areas and the other area experienced three fire incidents within the same period. The area with no fire incidents was considered as the control area. All the fire incidents were surface ones. The systematic random method with a sample size 100 × 200 m was used for collecting data. Based on the above, 25 samples were determined in each area. The whole coverage of the understory was taken into consideration using Whittaker’s method and the Domain criterion so as to calculate species diversity indices. The results showed that Shannon-Wiener diversity and Menhinick’s richness in the regions which experienced 3 and 7 fire incidents were maximum and minimum, respectively, whereas no significant difference was seen between the regions with regard to Smith and Wilson’s evenness index.

Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Rosetta model were employed to develop pedotransfers functions (PTFs) for soil moisture prediction using available soil properties for northern soils of Iran. The Rosetta model is based on ANN works in a hierarchical approach to predict water retention curves. For this purpose, 240 soil samples were selected from the south of Guilan province, Gilevan region, northern Iran. The data set was divided into two subsets for calibration and testing of the models. The general performance of PTFs was evaluated using coefficient of determination ( R 2 ), root mean square error (RMSE) and mean biased error between the observed and predicted values. Results showed that ANN with two hidden layers, Tan-sigmoid and linear functions for hidden and output layers respectively, performed better than the others in predicting soil moisture. In the other hand, ANN can model non-linear functions and showed to perform better than MLR. After ANN, MLR had better accuracy than Rosetta. The developed PTFs resulted in more accurate estimation at matric potentials of 100, 300, 500, 1000, 1500 kPa. Whereas, Rosetta model resulted in slightly better estimation than derived PTFs at matric potentials of 33 kPa. This research can provide the scientific basis for the study of soil hydraulic properties and be helpful for the estimation of soil water retention in other places with similar conditions, too.

The study focused on the effect of different intensities of fire on physical and chemical properties of soil in Zagros forests of western Iran. The dominant tree species in these forests is oak (Quercus persica). Three sites were selected; high severity burned site (HS), low severity burned site (LS) and control (not burned) site (C). Soil chemical properties such as: organic matter (OM), the total nitrogen (N), NO3-N, soluble potassium (K), soil phosphorus (P), pH, soil electrical conductivity (EC), cation exchangeable capacity (CEC), base cations (Ca, Mg, Na), CO2 and soil physical properties such as saturation percentage (SP), bulk density (BD), sand, clay and silt percentages were assessed in soil samples. To determine significance of differences among the three observed sites and most effective variables in the separation of sample plots, one-way analysis of variance and principal component analysis were used, respectively. Mean pH, N, NO3- N, OM, SP, P, K, and CEC at HS site were lower than at the sites with other fire intensities but the EC value for HS site was higher in comparison with other sites observed. According to Duncan’s test, mean BD value for HS site was higher when compared with other sites but SP value was comparatively lowest. At LS site, mean sand content was lowest and the amount of silt was highest, in comparison with other sites. The results showed that observed fire severities had significant effects on physical and chemical properties of soil, yet fire low severity and control sites were very similar to each other in terms of investigated factors. Therefore, it can be concluded that lowseverity fire regime has no significant influence on soil properties. In a management strategy, controlled low-severity fire regime can be an alternative management tool in improving soil conditions.