JUSTIFICATION OF THE CHOICE OF THE PROCESSOR FOUR FUEL WOOD MODEL FOR DIFFERENT FOREST REGIONS OF THE RUSSIAN FEDERATION

В реалиях XXI века дрова являются конкурентоспособным топливом, не уступающим по теплоте сгорания торфу, сланцам, а по некоторым другим свойствам, таким как зольность, содержание серы и др., древесина является лучшим из всех видов твердого топлива. В последние годы наблюдается увеличение спроса на короткомерные колотые дрова на внутреннем рынке России. кроме того, данный вид лесной продукции становится экспортным товаром. В работе представлены результаты исследования распределения дров по ступеням толщины в зависимости от среднего объёма хлыста. В Российской Феде- рации это тонкомерные до 0,3 м3 древостои средней крупности 0,3–0,7 м3, толстомерные древостои свыше 0,7 м3. были рассчитаны проценты распределения дровяной древесины по толщинам в зависимости от среднего объёма хлыста. В древостоях различной крупномерности распределение дров по группам диаметров значительно отличается. Рассмотрена зависимость толщины древостоя от места его произрастания. На предприятиях Российской Федерации широко применяются финские процессоры марки PALAPOWER и словенские процессоры марки RCA, также используются отечественные процессоры марки ДРС. Результаты исследования имеют практическое значение и могут быть использованы для выбора моделей процессоров в различных лесозаготовительных регионах Российской Федерации. кроме того, эти данные можно применять в расчёте производительности работ по производству дров. Firewood is a competitive fuel in the realities of the XXI century, not inferior in terms of heat of combustion to peat, shale, and in some other properties, such as ash content, sulfur content, etc., wood is the best of all types of solid fuel. In recent years, there has been an increase in demand for short-sized chopped firewood in the domestic market of Russia. In addition, this type of forest products becomes an export commodity. The paper presents the results of a study of the distribution of firewood by thickness steps depending on the average volume of the whip. In the Russian Federation, these are thin-dimensional stands of up to 0,3 m3, medium – sized stands of 0,3–0,7 m3, thick-dimensional stands of over 0,7 m3. The percentages of the distribution of woodwood by thickness were calculated depending on the average volume of the whip. In stands of various sizes, the distribution of firewood by diameter groups differs significantly. The dependence of the thickness of the stand on the place of its growth is considered. Processors of various brands that differ in the parameter of processing raw materials are studied. Finnish processors of the PALAPOWER brand and Slovenian processors of the RCA brand are widely used at enterprises of the Russian Federation, domestic processors of the DRS brand are also used. The results of the study are of practical importance and can be used to select processor models in various logging regions of the Russian Federation. In addition, these data can be used to calculate the productivity of work on the production of firewood.

PSV-14 Using Bayesian Hamiltonian Monte Carlo and a nonlinear model for the estimation of genetic parameters for lactation curves in goats

Hamiltonian Monte Carlo (HMC) is an algorithm of the Markov Chain Monte Carlo (MCMC) method that uses dynamics to propose samples that follow a target distribution. This algorithm enables more effective and consistent exploration of the probability interval and is more sensitive to correlated parameters. Therefore, Bayesian-HMC is a promising alternative to estimate individual parameters of complex functions such as nonlinear models, especially when using small datasets. Our objective was to estimate genetic parameters for milk traits defined based on nonlinear model parameters predicted using the Bayesian-HMC algorithm. A total of 64,680 milk yield test-day records from 2,624 first, second, and third lactations of Saanen and Alpine goats were used. First, the Wood model was fitted to the data. Second, lactation persistency (LP), peak time (PT), peak yield (PY), and total milk yield [estimated from zero to 50 (TMY50), 100(TMY100), 150(TMY150), 200(TMY200), 250(TMY250), and 300(TMY300) days-in-milk] were predicted for each animal and parity based on the output of the first step (the individual phenotypic parameters of the Wood model). Thereafter, these predicted phenotypes were used for estimating genetic parameters for each trait. In general, the heritability estimates across lactations ranged from 0.10 to 0.20 for LP, 0.04 to 0.07 for PT, 0.26 to 0.27 for PY, and 0.21 to 0.28 for TMY (considering the different intervals). Lower heritabilities were obtained for the nonlinear function parameters (A, b and l) compared to its predicted traits (except PT), especially for the first and second lactations (range: 0.09 to 0.18). Higher heritability estimates were obtained for the third lactation traits. To our best knowledge, this study is the first attempt to use the HMC algorithm to fit a nonlinear model in animal breeding. The two-step method proposed here allowed us to estimate genetic parameters for all traits evaluated.

Evaluation of Different Test-Day Milk Recording Protocols by Wood’s Model Application for the Estimation of Dairy Goat Milk and Milk Constituent Yield

Goats have important social and economic roles in many countries because of their ability to survive and be productive in marginal areas. The overarching aim of this study was to compare the application of Wood’s model to different test-day milk recording protocols for estimation of total milk, fat, and protein yield in dairy goats. A total of 465 goats were used (Garganica, 78; Girgentana, 81; Jonica, 76; Maltese, 77; Red Mediterranean, 76; Saanen, 77). Milk yield was recorded every 15 days throughout lactation of 210 days, for a total of 14 collection days, during both morning and afternoon milking sessions. Milk samples were collected and analyzed for protein and fat. The fat-corrected milk was standardized at 35g fat/kg of milk. Wood models showed high R2 values, and thus good fitting, in all the considered breeds. Wood model applied to first, second, fourth, and sixth month recordings (C) and ICAR estimation showed total milk yield very close to Wood’s model applied to all 14 recordings (A) (p > 0.38). Differently, Wood’s model applied to the first, second, third, and fourth month recording (B) estimation showed great differences (p < 0.01). This could be applied for farms that had the necessity to synchronize flock groups for kidding in order to produce kid meat. In farms that apply the estrus induction and/or synchronization for kidding, it would be possible to perform only four test-day milk recordings and to apply the Wood’s model on them in order to obtain the estimation of total milk, fat, and protein yield during lactation for animals inscribed, or to be inscribed, to the genealogical book.

Dynamic Testing of Lime-Tree (Tilia Europoea) and Pine (Pinaceae) for Wood Model Identification

The paper presents the results of dynamic testing of two wood species: lime-tree (Tilia europoea) and pine (Pinaceae). The dynamic compressive tests were carried out using the traditional Kolsky method in compression tests. The Kolsky method was modified for testing the specimen in a rigid limiting holder. In the first case, stress–strain diagrams for uniaxial stress state were obtained, while in the second, for uniaxial deformation. To create the load a gas gun was used. According to the results of the experiments, dynamic stress–strain diagrams were obtained. The limiting strength and deformation characteristics were determined. The fracture energy of lime and pine depending on the type of test was also obtained. The strain rates and stress growth rates were determined. The influence of the cutting angle of the specimens relative to the grain was noted. Based on the results obtained, the necessary parameters of the wood model were determined and their adequacy was assessed by using a special verification experiment.

Comparison of the fit of automatic milking system and test-day records with the use of lactation curves

Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas.Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit.Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values.Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.

The Vidovdan Temple of Ivan Meštrović

The sculptures of Ivan Meštrović (1883-1962) known as the Kosovo Cycle, Vidovdan Cycle or Vidovdan Fragments, sculpturally shaped to become part of the monumental Vidovdan Temple that was to be erected in Kosovo, along with a wood model of the building, represent the only material trace of this ambitiously conceived but unrealized project.

Activation of glucose with Fenton’s reagent: chemical structures of activated products and their reaction efficacy toward cellulosic material

The release of harmful volatiles, such as formaldehyde, is a major issue of the chemical modification of wood that limits the utilization of the modified wood in indoor environment. In this study, glucose (Glc) was activated with Fenton’s reagent under various conditions and the chemical structure of the activated Glc was characterized. Also, the reactivity of the activated Glc toward filter paper as a wood model was evaluated. The results show that the H2O2concentration controlled the activation ratio of Glc. Additionally, the Fe(II) concentration and activation temperature determined mainly the oxidation reaction rate. The Fenton reaction in an acidic solution resulted in higher activation efficacy of Glc and better fixation in the filter paper, compared to the reaction in an alkaline solution. The Glc cannot be fixed in the filter paper, but the activated Glc exhibited a fixation ratio of up to 48.2% due to the formation of carboxyl and aldehyde groups, as evidenced by Fourier-transform infrared (FTIR) spectroscopy and gas chromatography-mass spectrometry (GC-MS). It was demonstrated that activation of Glc with the Fenton’s reagent is a feasible and eco-friendly approach and the activated products have a high potential for wood modification.

DETERMINATION OF VOLUMETRIC CONTRACTION AND DRYING KINETICS OF THE DRYED BANANA

Banana (Musa spp.) is one of the most nutritious and consumed fruits, especially in tropical countries. The drying of the fruit is an alternative against the injuries suffered, mainly during the post-harvest process. Thus, the knowledge of the physical properties of the product that is intended to be processed has a big importance for the dimensioning of equipment. Therefore, the objective of this work was to study the drying kinetics of the banana, transforming it into dried banana, besides evaluating the volumetric contraction suffered during drying. The bananas were dried in an oven at temperatures of 70, 60 and 50 ºC. The volumetric measurements were carried out before and after drying to determine the volumetric contraction during the process. After drying, the experimental data were modeled by nonlinear regression analysis by the Quase-Newton method, to adjust 4 mathematical models of moisture ratio and 5 mathematical models of volumetric contraction. Among the models tested, the best fit for the prediction of the Moisture Ratio was the exponential model, and for the Volumetric Contraction was the modified BALA and WOOD model.

From virtual to real. A wood model for the philological reconstruction of the Alessandrino district, in the Central Archaeological Area of Rome

<p>Esta contribución muestra el resultado de años de investigación del Departamento de Arquitectura de Roma Tre sobre la reconstrucción virtual del barrio Alessandrino, demolido para favorecer la Via dell’Impero en los años 30. El estudio de los documentos de archivo, la digitalización, la reconstrucción de un modelo virtual muy detallado, y la búsqueda de las fuentes y de las fotografías históricas han confluido en el esfuerzo de realizar una maqueta de madera para el Museo di Roma, gracias a las continuas relaciones culturales con la <em>Soprintendenza Capitolina</em>.</p>

Prediction models for above-ground wood of some fast growing trees of Nepal's eastern Terai

Biomass study of Acacia auriculiformis, Acacia catechu, Dalbergia sissoo, Eucalyptus camaldulensis and Eucalyptus tereticornis was conducted on a five and half years old 'Fuelwood Species Trial under Short Rotation' through destructive sampling at Tarahara, Sunsari District of Nepal. The lowest Furnival Index (FI) was the main criteria for selecting a model. Among the six models tested, the transformed model Ln W= a + b Ln DBH from a power equation W = a DBHb (W = weights of stem or branch or above-ground wood in kg, DBH= Diameter at breast height in cm) was selected. Selected prediction models of tree components and above-ground wood (green as well as oven dry), and their coefficient of determination (R2) values, regression constant and coefficient, correction factor, precision and bias percent of five species are presented. With the exclusion of branchwood models, R2 is higher in a range of 88.7% for oven dry stemwood of Acacia catechu to 99.3% for above-ground wood model of Dalbergia sissoo. However, R2 is less than 80% in branchwood (green and oven dry) of Acacia auriculiformis, Eucalyptus camaldulensis, and Eucalyptus tereticornis showing moderate relationship between branchwood and DBH. In the case of E. tereticornis, precision is more than 49% which leads to low reliability in biomass estimation resulting in true biomass deviation in a range of about 49.51% to 56.74%, so biomass model's could not be used for estimation of tree components and above-ground wood. Despite it, generally, precision percent of the selected models has been found less than 15%. Bias percent was found quite large for allometric branchwood model comparatively to stemwood and above-ground wood models. D. sissoo had less than 10 % bias. Bias percent was the highest (23.11%) for green branchwood of Acacia auriculiformis. Others had in a range of 0.5% for green aboveground wood model of D. sissoo to 18.4% for green and oven dry branchwood models of E. tereticornis.