Książki na temat „Dose coefficients”

This article examines whether economic inequality undermines economic development and democracy in the long run. After reviewing the literature on the effect of inequality on economic development and democracy, it considers three approaches that have been put forward to explain why inequality harms the economy and democracy: (1) the political economy approach, (2) the social unrest approach, and (3) the credit market imperfections approach. A complete data set on inequality is generated using three measures of inequality: the capital share data set of Ortega and Rodriguez (2006), the Gini coefficients data set of Solt (2009), and the income Gini coefficients of the “Estimated Household Income Inequality” (EHII) data set, developed by the University of Texas Inequality Project (UTIP). The article then tests the relationship between inequality and democracy using dynamic probit models.

Friction, lubrication, adhesion, and wear are prevalent physical phenomena in everyday life and in many key technologies. The goal of this book is to incorporate a bottom up approach to friction, lubrication, and wear into a versatile textbook on tribology. This is done by focusing on how these tribological phenomena occur on the small scale—the atomic to the micrometer scale—a field often called nanotribology. The book covers the microscopic origins of the common tribological concepts: roughness, elasticity, plasticity, friction coefficients, and wear coefficients. Some macroscale concepts (like elasticity) scale down well to the micro- and atomic scale, while other macroscale concepts (like hydrodynamic lubrication) do not. In addition, this book also has chapters on topics not typically found in tribology texts: surface energy, surface forces, lubrication in confined spaces, and the atomistic origins of friction and wear. These chapters covered tribological concepts that become increasingly important at the small scale: capillary condensation, disjoining pressure, contact electrification, molecular slippage at interfaces, atomic scale stick-slip, and bond breaking. Numerous examples are provided throughout the book on how a nanoscale understanding of tribological phenomena is essential to the proper engineering of important new technologies such as MEMS, disk drives, and nanoimprinting. For the second edition, all the chapters have been revised and updated, with many new sections added to incorporate the most recent advancements in nanoscale tribology. Another important enhancement to the second edition is the addition of problem sets at the end of each chapter.

Queller’s version of Hamilton’s rule (HRG), derived from the Price equation, states that the mean breeding value for a social character increases if and only if rb > c, where r is the coefficient of relatedness between social partners, b is the benefit conferred on recipients, and c is the cost incurred by actors. The value of HRG lies in its ability to provide an organizing framework for social evolution theory, helping us to interpret, classify, and compare more detailed models of particular scenarios. HRG does this by allowing us to classify causal explanations of positive change by their commitments regarding the sign of rb and c. This leads to a four-part taxonomy of explanations, comprising indirect fitness explanations, direct fitness explanations, hybrid explanations, and wholly or partially non-selective explanations. There are plausible instances of all four categories in the natural world.

Bones are multifunctional passive organs of movement that supports soft tissue and directly attached muscles. They also protect internal organs and are a reserve of calcium, phosphorus and magnesium. Each bone is covered with periosteum, and the adjacent bone surfaces are covered by articular cartilage. Histologically, the bone is an organ composed of many different tissues. The main component is bone tissue (cortical and spongy) composed of a set of bone cells and intercellular substance (mineral and organic), it also contains fat, hematopoietic (bone marrow) and cartilaginous tissue. Bones are a tissue that even in adult life retains the ability to change shape and structure depending on changes in their mechanical and hormonal environment, as well as self-renewal and repair capabilities. This process is called bone turnover. The basic processes of bone turnover are: • bone modeling (incessantly changes in bone shape during individual growth) following resorption and tissue formation at various locations (e.g. bone marrow formation) to increase mass and skeletal morphology. This process occurs in the bones of growing individuals and stops after reaching puberty • bone remodeling (processes involve in maintaining bone tissue by resorbing and replacing old bone tissue with new tissue in the same place, e.g. repairing micro fractures). It is a process involving the removal and internal remodeling of existing bone and is responsible for maintaining tissue mass and architecture of mature bones. Bone turnover is regulated by two types of transformation: • osteoclastogenesis, i.e. formation of cells responsible for bone resorption • osteoblastogenesis, i.e. formation of cells responsible for bone formation (bone matrix synthesis and mineralization) Bone maturity can be defined as the completion of basic structural development and mineralization leading to maximum mass and optimal mechanical strength. The highest rate of increase in pig bone mass is observed in the first twelve weeks after birth. This period of growth is considered crucial for optimizing the growth of the skeleton of pigs, because the degree of bone mineralization in later life stages (adulthood) depends largely on the amount of bone minerals accumulated in the early stages of their growth. The development of the technique allows to determine the condition of the skeletal system (or individual bones) in living animals by methods used in human medicine, or after their slaughter. For in vivo determination of bone properties, Abstract 10 double energy X-ray absorptiometry or computed tomography scanning techniques are used. Both methods allow the quantification of mineral content and bone mineral density. The most important property from a practical point of view is the bone’s bending strength, which is directly determined by the maximum bending force. The most important factors affecting bone strength are: • age (growth period), • gender and the associated hormonal balance, • genotype and modification of genes responsible for bone growth • chemical composition of the body (protein and fat content, and the proportion between these components), • physical activity and related bone load, • nutritional factors: – protein intake influencing synthesis of organic matrix of bone, – content of minerals in the feed (CA, P, Zn, Ca/P, Mg, Mn, Na, Cl, K, Cu ratio) influencing synthesis of the inorganic matrix of bone, – mineral/protein ratio in the diet (Ca/protein, P/protein, Zn/protein) – feed energy concentration, – energy source (content of saturated fatty acids - SFA, content of polyun saturated fatty acids - PUFA, in particular ALA, EPA, DPA, DHA), – feed additives, in particular: enzymes (e.g. phytase releasing of minerals bounded in phytin complexes), probiotics and prebiotics (e.g. inulin improving the function of the digestive tract by increasing absorption of nutrients), – vitamin content that regulate metabolism and biochemical changes occurring in bone tissue (e.g. vitamin D3, B6, C and K). This study was based on the results of research experiments from available literature, and studies on growing pigs carried out at the Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences. The tests were performed in total on 300 pigs of Duroc, Pietrain, Puławska breeds, line 990 and hybrids (Great White × Duroc, Great White × Landrace), PIC pigs, slaughtered at different body weight during the growth period from 15 to 130 kg. Bones for biomechanical tests were collected after slaughter from each pig. Their length, mass and volume were determined. Based on these measurements, the specific weight (density, g/cm3) was calculated. Then each bone was cut in the middle of the shaft and the outer and inner diameters were measured both horizontally and vertically. Based on these measurements, the following indicators were calculated: • cortical thickness, • cortical surface, • cortical index. Abstract 11 Bone strength was tested by a three-point bending test. The obtained data enabled the determination of: • bending force (the magnitude of the maximum force at which disintegration and disruption of bone structure occurs), • strength (the amount of maximum force needed to break/crack of bone), • stiffness (quotient of the force acting on the bone and the amount of displacement occurring under the influence of this force). Investigation of changes in physical and biomechanical features of bones during growth was performed on pigs of the synthetic 990 line growing from 15 to 130 kg body weight. The animals were slaughtered successively at a body weight of 15, 30, 40, 50, 70, 90, 110 and 130 kg. After slaughter, the following bones were separated from the right half-carcass: humerus, 3rd and 4th metatarsal bone, femur, tibia and fibula as well as 3rd and 4th metatarsal bone. The features of bones were determined using methods described in the methodology. Describing bone growth with the Gompertz equation, it was found that the earliest slowdown of bone growth curve was observed for metacarpal and metatarsal bones. This means that these bones matured the most quickly. The established data also indicate that the rib is the slowest maturing bone. The femur, humerus, tibia and fibula were between the values of these features for the metatarsal, metacarpal and rib bones. The rate of increase in bone mass and length differed significantly between the examined bones, but in all cases it was lower (coefficient b <1) than the growth rate of the whole body of the animal. The fastest growth rate was estimated for the rib mass (coefficient b = 0.93). Among the long bones, the humerus (coefficient b = 0.81) was characterized by the fastest rate of weight gain, however femur the smallest (coefficient b = 0.71). The lowest rate of bone mass increase was observed in the foot bones, with the metacarpal bones having a slightly higher value of coefficient b than the metatarsal bones (0.67 vs 0.62). The third bone had a lower growth rate than the fourth bone, regardless of whether they were metatarsal or metacarpal. The value of the bending force increased as the animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. The rate of change in the value of this indicator increased at a similar rate as the body weight changes of the animals in the case of the fibula and the fourth metacarpal bone (b value = 0.98), and more slowly in the case of the metatarsal bone, the third metacarpal bone, and the tibia bone (values of the b ratio 0.81–0.85), and the slowest femur, humerus and rib (value of b = 0.60–0.66). Bone stiffness increased as animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. Abstract 12 The rate of change in the value of this indicator changed at a faster rate than the increase in weight of pigs in the case of metacarpal and metatarsal bones (coefficient b = 1.01–1.22), slightly slower in the case of fibula (coefficient b = 0.92), definitely slower in the case of the tibia (b = 0.73), ribs (b = 0.66), femur (b = 0.59) and humerus (b = 0.50). Bone strength increased as animals grew. Regardless of the growth point tested, bone strength was as follows femur > tibia > humerus > 4 metacarpal> 3 metacarpal> 3 metatarsal > 4 metatarsal > rib> fibula. The rate of increase in strength of all examined bones was greater than the rate of weight gain of pigs (value of the coefficient b = 2.04–3.26). As the animals grew, the bone density increased. However, the growth rate of this indicator for the majority of bones was slower than the rate of weight gain (the value of the coefficient b ranged from 0.37 – humerus to 0.84 – fibula). The exception was the rib, whose density increased at a similar pace increasing the body weight of animals (value of the coefficient b = 0.97). The study on the influence of the breed and the feeding intensity on bone characteristics (physical and biomechanical) was performed on pigs of the breeds Duroc, Pietrain, and synthetic 990 during a growth period of 15 to 70 kg body weight. Animals were fed ad libitum or dosed system. After slaughter at a body weight of 70 kg, three bones were taken from the right half-carcass: femur, three metatarsal, and three metacarpal and subjected to the determinations described in the methodology. The weight of bones of animals fed aa libitum was significantly lower than in pigs fed restrictively All bones of Duroc breed were significantly heavier and longer than Pietrain and 990 pig bones. The average values of bending force for the examined bones took the following order: III metatarsal bone (63.5 kg) <III metacarpal bone (77.9 kg) <femur (271.5 kg). The feeding system and breed of pigs had no significant effect on the value of this indicator. The average values of the bones strength took the following order: III metatarsal bone (92.6 kg) <III metacarpal (107.2 kg) <femur (353.1 kg). Feeding intensity and breed of animals had no significant effect on the value of this feature of the bones tested. The average bone density took the following order: femur (1.23 g/cm3) <III metatarsal bone (1.26 g/cm3) <III metacarpal bone (1.34 g / cm3). The density of bones of animals fed aa libitum was higher (P<0.01) than in animals fed with a dosing system. The density of examined bones within the breeds took the following order: Pietrain race> line 990> Duroc race. The differences between the “extreme” breeds were: 7.2% (III metatarsal bone), 8.3% (III metacarpal bone), 8.4% (femur). Abstract 13 The average bone stiffness took the following order: III metatarsal bone (35.1 kg/mm) <III metacarpus (41.5 kg/mm) <femur (60.5 kg/mm). This indicator did not differ between the groups of pigs fed at different intensity, except for the metacarpal bone, which was more stiffer in pigs fed aa libitum (P<0.05). The femur of animals fed ad libitum showed a tendency (P<0.09) to be more stiffer and a force of 4.5 kg required for its displacement by 1 mm. Breed differences in stiffness were found for the femur (P <0.05) and III metacarpal bone (P <0.05). For femur, the highest value of this indicator was found in Pietrain pigs (64.5 kg/mm), lower in pigs of 990 line (61.6 kg/mm) and the lowest in Duroc pigs (55.3 kg/mm). In turn, the 3rd metacarpal bone of Duroc and Pietrain pigs had similar stiffness (39.0 and 40.0 kg/mm respectively) and was smaller than that of line 990 pigs (45.4 kg/mm). The thickness of the cortical bone layer took the following order: III metatarsal bone (2.25 mm) <III metacarpal bone (2.41 mm) <femur (5.12 mm). The feeding system did not affect this indicator. Breed differences (P <0.05) for this trait were found only for the femur bone: Duroc (5.42 mm)> line 990 (5.13 mm)> Pietrain (4.81 mm). The cross sectional area of the examined bones was arranged in the following order: III metatarsal bone (84 mm2) <III metacarpal bone (90 mm2) <femur (286 mm2). The feeding system had no effect on the value of this bone trait, with the exception of the femur, which in animals fed the dosing system was 4.7% higher (P<0.05) than in pigs fed ad libitum. Breed differences (P<0.01) in the coross sectional area were found only in femur and III metatarsal bone. The value of this indicator was the highest in Duroc pigs, lower in 990 animals and the lowest in Pietrain pigs. The cortical index of individual bones was in the following order: III metatarsal bone (31.86) <III metacarpal bone (33.86) <femur (44.75). However, its value did not significantly depend on the intensity of feeding or the breed of pigs.

The aim of the paper was to determine the influence of root systems of chosen tree species found in the Polish Flysch Carpathians on the increase of soil shear strength (root cohesion) in terms of slope stability. The paper's goal was achieved through comprehensive tests on root systems of eight relatively common in the Polish Flysch Carpathians tree species. The tests that were carried out included field work, laboratory work and analytical calculations. As part of the field work, the root area ratio (A IA) of the roots was determined using the method of profiling the walls of the trench at a distance of about 1.0 m from the tree trunk. The width of the. trenches was about 1.0 m, and their depth depended on the ground conditions and ranged from 0.6 to 1.0 m below the ground level. After preparing the walls of the trench, the profile was divided into vertical layers with a height of 0.1 m, within which root diameters were measured. Roots with diameters from 1 to 10 mm were taken into consideration in root area ratio calculations in accordance with the generally accepted methodology for this type of tests. These measurements were made in Biegnik (silver fir), Ropica Polska (silver birch, black locust) and Szymbark (silver birch, European beech, European hornbeam, silver fir, sycamore maple, Scots pine, European spruce) located near Gorlice (The Low Beskids) in areas with unplanned forest management. In case of each tested tree species the samples of roots were taken, transported to the laboratory and then saturated with water for at least one day. Before testing the samples were obtained from the water and stretched in a. tensile testing machine in order to determine their tensile strength and flexibility. In general, over 2200 root samples were tested. The results of tests on root area ratio of root systems and their tensile strength were used to determine the value of increase in shear strength of the soils, called root cohesion. To this purpose a classic Wu-Waldron calculation model was used as well as two types of bundle models, the so called static model (Fiber Bundle Model — FIRM, FBM2, FBM3) and the deformation model (Root Bundle Model— RBM1, RBM2, mRBM1) that differ in terms of the assumptions concerning the way the tensile force is distributed to the roots as well as the range of parameters taken into account during calculations. The stability analysis of 8 landslides in forest areas of Cicikowicleie and Wignickie Foothills was a form of verification of relevance of the obtained calculation results. The results of tests on root area ratio in the profile showed that, as expected, the number of roots in the soil profile and their ApIA values are very variable. It was shown that the values of the root area ratio of the tested tree species with a diameter 1-10 ram are a maximum of 0.8% close to the surface of the ground and they decrease along with the depth reaching the values at least one order of magnitude lower than close to the surface at the depth 0.5-1.0 m below the ground level. Average values of the root area ratio within the soil profile were from 0.05 to 0.13% adequately for Scots pine and European beech. The measured values of the root area ratio are relatively low in relation to the values of this parameter given in literature, which is probably connected with great cohesiveness of the soils and the fact that there were a lot of rock fragments in the soil, where the tests were carried out. Calculation results of the Gale-Grigal function indicate that a distribution of roots in the soil profile is similar for the tested species, apart from the silver fir from Bie§nik and European hornbeam. Considering the number of roots, their distribution in the soil profile and the root area ratio it appears that — considering slope stability — the root systems of European beech and black locust are the most optimal, which coincides with tests results given in literature. The results of tensile strength tests showed that the roots of the tested tree species have different tensile strength. The roots of European beech and European hornbeam had high tensile strength, whereas the roots of conifers and silver birch in deciduous trees — low. The analysis of test results also showed that the roots of the studied tree species are characterized by high variability of mechanical properties. The values Of shear strength increase are mainly related to the number and size (diameter) of the roots in the soil profile as well as their tensile strength and pullout resistance, although they can also result from the used calculation method (calculation model). The tests showed that the distribution of roots in the soil and their tensile strength are characterized by large variability, which allows the conclusion that using typical geotechnical calculations, which take into consideration the role of root systems is exposed to a high risk of overestimating their influence on the soil reinforcement. hence, while determining or assuming the increase in shear strength of soil reinforced with roots (root cohesion) for design calculations, a conservative (careful) approach that includes the most unfavourable values of this parameter should be used. Tests showed that the values of shear strength increase of the soil reinforced with roots calculated using Wu-Waldron model in extreme cases are three times higher than the values calculated using bundle models. In general, the most conservative calculation results of the shear strength increase were obtained using deformation bundle models: RBM2 (RBMw) or mRBM1. RBM2 model considers the variability of strength characteristics of soils described by Weibull survival function and in most cases gives the lowest values of the shear strength increase, which usually constitute 50% of the values of shear strength increase determined using classic Wu-Waldron model. Whereas the second model (mRBM1.) considers averaged values of roots strength parameters as well as the possibility that two main mechanism of destruction of a root bundle - rupture and pulling out - can occur at the same. time. The values of shear strength increase calculated using this model were the lowest in case of beech and hornbeam roots, which had high tensile strength. It indicates that in the surface part of the profile (down to 0.2 m below the ground level), primarily in case of deciduous trees, the main mechanism of failure of the root bundle will be pulling out. However, this model requires the knowledge of a much greater number of geometrical parameters of roots and geotechnical parameters of soil, and additionally it is very sensitive to input data. Therefore, it seems practical to use the RBM2 model to assess the influence of roots on the soil shear strength increase, and in order to obtain safe results of calculations in the surface part of the profile, the Weibull shape coefficient equal to 1.0 can be assumed. On the other hand, the Wu-Waldron model can be used for the initial assessment of the shear strength increase of soil reinforced with roots in the situation, where the deformation properties of the root system and its interaction with the soil are not considered, although the values of the shear strength increase calculated using this model should be corrected and reduced by half. Test results indicate that in terms of slope stability the root systems of beech and hornbeam have the most favourable properties - their maximum effect of soil reinforcement in the profile to the depth of 0.5 m does not usually exceed 30 kPa, and to the depth of 1 m - 20 kPa. The root systems of conifers have the least impact on the slope reinforcement, usually increasing the soil shear strength by less than 5 kPa. These values coincide to a large extent with the range of shear strength increase obtained from the direct shear test as well as results of stability analysis given in literature and carried out as part of this work. The analysis of the literature indicates that the methods of measuring tree's root systems as well as their interpretation are very different, which often limits the possibilities of comparing test results. This indicates the need to systematize this type of tests and for this purpose a root distribution model (RDM) can be used, which can be integrated with any deformation bundle model (RBM). A combination of these two calculation models allows the range of soil reinforcement around trees to be determined and this information might be used in practice, while planning bioengineering procedures in areas exposed to surface mass movements. The functionality of this solution can be increased by considering the dynamics of plant develop¬ment in the calculations. This, however, requires conducting this type of research in order to obtain more data.