Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmacogenomics: The promise of personalized medicine

Pharmacogenetics and pharmacogenomics deal with the genetic basis underlying variable drug response in individual patients. The traditional pharmacogenetic approach relies on studying sequence variations in candidate genes suspected of affecting drug response. On the other hand, pharmacogenomic studies encompass the sum of all genes, i.e., the genome. Numerous genes may play a role in drug response and toxicity, introducing a daunting level of complexity into the search for candidate genes. The high speed and specificity associated with newly emerging genomic technologies enable the search for relevant genes and their variants to include the entire genome. These new technologies have essentially spawned a new discipline, termed pharmacogenomics, which seeks to identify the variant genes affecting the response to drugs in individual patients. Moreover, pharmacogenomic analysis can identify disease susceptibility genes representing potential new drug targets. All of this will lead to novel approaches in drug discovery, an individualized application of drug therapy, and new insights into disease prevention. Current concepts in drug therapy often attempt treatment of large patient populations as groups, irrespective of the potential for individual, genetically-based differences in drug response. In contrast, pharmacogenomics may help focus effective therapy on smaller patient subpopulations which although demonstrating the same disease phenotype are characterized by distinct genetic profiles. Whether and to what extent this individual, genetics-based approach to medicine results in improved, economically feasible therapy remain to be seen. To exploit these opportunities in genetic medicine, novel technologies will be needed, legal and ethical questions must be clarified, health care professionals must be educated, and the public must be informed about the implications of genetic testing in drug therapy and disease management.
A Heuristic Method to Isolate the State Space

is a key problem, these mentioned above approaches are build on the decomposition of the state space. In these approaches, the state space is decomposed according to the prior problem domain knowledge with the assistance of human, but that would make the decomposition is problem-specific, and also destroy the agent’s autonomy: the most merit of RL. In this work, we propose a heuristic method to isolate the larger state space into some smaller state spaces for decomposing learning task. When we record every training episode and remove the state loops from it to be acyclic episode. We found some states appear in most of acyclic episodes, even appear in all acyclic episodes. That is, these states have high probability (even to 1) to appear in all acyclic episodes. And some of these states are also the gates for agent can move from a part of state space enter another part of state space. This two characteristics are simultaneous processed by some of these states. That means if agent wants to reach goal state, then to pass these states are critical. We call these critical state as gate states. In real world, this situations are particular true, for example, before the state of ”downpour”, the state of ”darkly clouded” appears often. When these gate states are blocked, the whole state space is isolated naturally into some smaller state spaces. Our method is not very sophisticated, but is truly effective. When the target state space are decomposed, the improvement of learning is indubitable. The more important is our work makes agent processing the capability to decomposing its learning task according to what it learned, which keeps agent’s autonomy. We may not ensure this method can isolate the state space completely, that is to find every gate state and block it, because the method is built on the learned episodes. When the training episodes are scarce, it is possible that agent ”escape” from a small state space to enter another small state space from some unfound gate state. But the experiments on GridWorld problem show the isolation tend to be complete along with the increase of training episodes.
Real Estate Perspectives: An Introduction to Real Estate

Chapter 1.Real Estate Perspectives Part I. Investment Perspective Chapter 2:Basic Valuation Concepts Chapter 3:Investment Property Analysis Chapter 4:Federal Income Taxation Chapter 5:Forms of Ownership Chapter 6:Risk and Real Estate Investment Chapter 7:Management of Space and Assets Part II. Market Perspective Chapter 8:Real Estate Markets Chapter 9:Land Use, Planning, Zoning, Urban Problems and Environmental Hazards Chapter 10:Market and Feasibility Analysis Chapter 11:Introduction to Development Part III: Valuation Perspective Chapter 12:Valuation by the Sales Comparison and Cost Approaches Chapter 13:Valuation by the Income Approach Part IV: Mortgage Finance Perspective Chapter 14:Creation of Mortgages Chapter 15:Residential Mortgage Types and Borrower Decisions Chapter 16:Sources of Funds for Residential Mortgages Chapter 17:Commercial Property Financing Part V: Legal Perspective Chapter 18:Real Property Rights Chapter 19:Real Property Taxation Chapter 20:Transfer of Real Property Rights Chapter 21:Real Estate Brokerage and Listing Contracts Chapter 22:Contracts for Sale and Closing :Appendix A. Answers to Test Yourself Questions :Appendix B. Real Estate-Related Internet Information Sources
Literature Review in Creativity, New Technologies and Learning

This paper maps out the different perspectives on creativity, and the teaching and learning of creativity, and brings together latest thinking in this field. It is a rich resource of examples of the way that technology is currently used to support creativity through encouraging learners to make connections, develop ideas, create meaning, collaborate and communicate. It also highlights some of the key questions concerning assessment and creativity.
European Cultures in Sport: Examining the Nations and Regions

Sport occupies an important position in the cultural profile of a nation. This study is a comparative guide to sport across Europe, in terms of its relative political and social value, its development, and the ways in which it has contributed to national achievement. Covering sport in ten major European states, each native contributor to the study presents: -- brief historical background: major sports successes, Olympic positions, sporting traditions -- organization of sport: its structure and financing -- elite sport: how talent is spotted, nurtured and remunerated, sports academies, national qualification schemes -- the role of science and medicine in sport Following this format through each chapter, the book serves as a valuable guide to students of Sports Studies, enabling comparison of sport across culturally diverse regions of Europe.
On a novel integrable generalization of the sine-Gordon equation

We consider an integrable generalization of the sine-Gordon (sG) equation that was earlier derived by one of the authors using bi-Hamiltonian methods. This equation is related to the sG equation in the same way that the Camassa–Holm equation is related to the Korteweg–de Vries equation. In this paper we (a) derive a Lax pair, (b) use the Lax pair to solve the initial-value problem on the line, (c) analyze solitons, (d) show that the generalized sG and sG equations are related by a Liouville transformation, (e) derive conservation laws, and (f) analyze traveling-wave solutions.
Climate Clever: How Governments Can Tackle Climate Change (and Still Win Elections)

Why, despite two decades of climate policy, have affluent democracies made so little progress in cutting greenhouse gas emissions? We know that there are ways of doing this that are both practical and affordable. It is politics that is the problem. Stringent climate policies may lead companies to redirect investment elsewhere, or lead voters to retaliate at the ballot box. There are many political obstacles to stronger action. What can be done? Based on an analysis of the logic of policy making, plus observation of recent developments in climate politics, this book identifies a broad range of political strategies that are available to governments that wish to take more effective action against climate change while avoiding serious political damage. Separate chapters deal with strategies relating to unilateral action, persuasion, political exchange, and changing the terms of political exchange. This is the first book-length study of political strategy and climate change and will be of interest not only to policymakers but also to experts and activists looking to formulate politically realistic policy proposals, and scholars and students of politics and environmental studies.
MASTER THESIS by Paul Fink Ensemble methods for classification trees under imprecise probabilities Supervision : Prof

In this master thesis some properties of bags of imprecise classification trees, as introduced in Abellán and Masegosa (2010), are analysed. In the beginning the statistical background of imprecise classification trees is outlined – starting with an overview on measuring uncertainty within the concept of Dempster–Shafer theory is presented, followed by a discussion of its application in a tree–growing–algorithm, which employs the so–called Imprecise Dirichlet Model in the splitting process. The motivation of so–called ensemble methods is to reduce the instability of a single classification tree, increasing its predictive accuracy, but at cost of structural interpretability. A description of the well known ensemble methods, such as bagging, random forests and boosting, is given along with two approaches, generating the ensemble by allowing more than one splitting variable within a node. In the next step a bag of imprecise classification trees is generated; following, its sensitivity in relation to different ensemble aggregation/fusion rules (majority voting, disjunction and average rule), the external stopping criterion of minimal observations within a node and the main parameter of the Imprecise Dirichlet Model is analysed by a simulation study. The results of the simulation indicate that the commonly applied majority voting rule is also a fair choice for imprecise classification ensembles. Regarding the external stopping criterion the simulation indicates that such may be neglected, while the parameter does highly affect the predictive accuracy, favouring lower values of it.
Decision Methods for Forest Resource Management

Preface Introduction Principles of Linear Programming: Formulations Principles of Linear Programming: Solutions: Even-Aged Management: A First Model Area - and Volume-Control Management with Linear Programming: A Dynamic Model of the Even-Aged Forest Economic Objectives and Environmental Policies for Even-Aged Forests Managing the Uneven-Aged Forest with Linear Programming Economic and Environmental Management of Uneven-Aged Forests Multiple Objectives Management with Goal Programming Forest Resource Programming Models with Integer Variables Project Management with CPM/PERT Multistage Decision Making with Dynamic Programming Simulation of Uneven-Aged Stand Management Simulation of Even-Aged Forest Management Projecting Forest Landscape and Income Under Risk with Markov Chains Optimizing Forest Income and Biodiversity with Markov Decision Processes Analysis of Forest Resource Investments Econometric Analysis and Forecasting of Forest Product markets Appendix A: Compounding and Discounting Appendix B: Elements of Matrix Algebra
Importance of microbial soil organic matter processing in dissolved organic carbon production.

Soil dissolved organic carbon (DOC) sources and its seasonal dynamics are poorly known. We aimed to determine the contribution of plant and soil organic matter (SOM) to size classes of DOC in a field experiment with C3 to C4 vegetation change on two soil types through different seasons. Stable isotope ratios of DOC size classes were measured using size exclusion chromatography (SEC) coupled online to liquid chromatography-isotope ratio mass spectrometry (LC-IRMS). SEC resolved DOC into three size classes: very high molecular weight/vHMW (> 10 kDa), high molecular weight/HMW (0.4-10 kDa), and low molecular weight/LMW (< 0.4 kDa). HMW DOC was most abundant in all seasons, soil types, and depths. In contrast, vHMW DOC was only seen postsnowmelt in upper 20 cm and was mainly (87 ± 9%) plant-derived. Through all seasons, HMW and LMW DOC had less than 30% recent plant contribution. Similar size range and source of DOC size classes and soil chloroform fumigation extracts suggest microbial origin of DOC. Thus, microbial SOM recycling is an important process in DOC production. We suggest that DOC molecules get partitioned manifold between soil solution and the mineral matrix (chromatography), thereby getting constantly decomposed, altered, or produced anew by soil microorganisms (reactive transport).
On Mesh-Independent Convergence of an Inexact Newton-Multigrid Algorithm

In this paper we revisit and prove optimal order and mesh–independent convergence of an inexact Newton method where the linear Jacobian systems are solved with multigrid techniques. This convergence is shown using Banach spaces and the norm, max{‖ · ‖1, ‖ · ‖0,∞}, a stronger norm than is used in previous work. These results are valid for a class of second order, semi–linear, finite element, elliptic problems posed on quasi–uniform grids. Numerical results are given which validate the theory.
Commuter Route Optimized Energy Management of Hybrid Electric Vehicles

Optimal energy management of hybrid electric vehicles requires a priori information regarding future driving conditions; the acquisition and processing of this information is nevertheless often neglected in academic research. This paper introduces a commuter route optimized energy management system, where the bulk of the computations are performed on a server. The idea is to identify commuter routes from historical driving data, using hierarchical agglomerative clustering, and then precompute an optimal solution to the energy management control problem with dynamic programming; the obtained solution can then be transmitted to the vehicle in the form of a lookup table. To investigate the potential of such a system, a simulation study is performed using a detailed vehicle model implemented in the Autonomie simulation environment for MATLAB/Simulink. The simulation results for a plug-in hybrid electric vehicle indicate that the average fuel consumption along the commuter route(s) can be reduced by 4%-9% and battery usage by 10%-15%.
Efficient 3D modeling of buildings using a priori geometric object information

The subject of this paper is the research that aims at efficiency improvement of acquisition of 3D building models from digital images for Computer Aided Architectural Design (CAAD). The results do not only apply to CAAD, but to all applications where polyhedral objects are involved. The research is concentrated on the integration of a priori geometric object information in the modeling process. Parallelism and perpendicularity are examples of the a priori information to be used. This information leads to geometric constraints in the mathematical model. This model can be formulated using condition equations with observations only. The advantage is that the adjustment does not include object parameters and the geometric constraints can be incorporated in the model sequentially. As with the use of observation equations statistical testing can be applied to verify the constraints. For the initial values of orientation parameters of the images we use a direct solution based on a priori object information as well. For this method only two sets of (coplanar) parallel lines in object space are required. The paper concentrates on the mathematical model with image lines as the main type of observations. Advantages as well as disadvantages of a mathematical model with only condition equations are discussed. The parametrization of the object model plays a major role in this discussion.
Cohort Crowding and Youth Labor Markets: A Cross-National Analysis

We assess the evidence on the contribution of changes in the population age structure to the changing fortunes of youths in labor markets in advanced economies over the 1970s, 1980s and early 1990s, and use this evidence to project the likely effects of future cohort sizes on youth labor markets. We estimate a series of regression models to isolate the effects of exogenous changes in potential youth labor supply on youth employment and unemployment rates using a panel data set on 15 countries over more than 20 years. Our preferred estimates show large youth cohorts lead to increases in the unemployment rate of youths, with elasticities as high as . 5 or . 6. But the estimates generally indicate little effect of relative cohort size on employment rates of youths. We also find some evidence, though statistically weak, that labor market institutions that decrease flexibility lead to sharper responses of youth unemployment and employment rates to fluctuations in youth cohort size. Finally, due to recent declines in fertility, some European countries will see reductions in the size of youth cohorts over the next 16 years (especially Ireland, Italy, Portugal, and Spain). Projections suggest declining youth shares should improve youth labor markets in these countries, although the effects are not large compared with longer-term changes in youth unemployment rates. Other countries cannot expect demographic changes to improve youth labor markets since youth population shares are projected to decline moderately or to increase.
Disability and labour force participation in Cameroon

This paper examines the effect of disability on labour force participation using the Cameroon 2007 Household Survey. Statistical and econometric tests indicate that disability represents a barrier to employment in the Cameroon labour market. For instance, disability status reduces men’s probability of getting into the labour market by 0.8% for the public sector, 0.05% for the formal private sector and by 2.9% for the informal sector. Other noteworthy results are the fact that women face greater constraints in entering the labour market and investments in general and specific human capital increase the probability of getting a job in the Cameroon.
The Orbits of 48 Globular Clusters in a Milky Way-like Barred Galaxy

The effect of a barred potential (such as the one of the Milky Way) on the Galactic orbits of 48 globular clusters for which absolute proper motions are known is studied. The orbital characteristics are compared with those obtained for the case of an axisymmetric Galactic potential. Tidal radii are computed and discussed for both the better known axisymmetric case and that including a bar. The destruction rates due to bulge and disk shocking are calculated and compared in both Galactic potentials.
Heating of blue compact dwarf galaxies: gas distribution and photoionization by stars in I Zw 18

Aims. Photoionization models so far are unable to account for the high electron temperature T e ([$\ion{O}{iii}$]) implied by the line intensity ratio [$\ion{O}{iii}$] λ 4363 A/[$\ion{O}{iii}$] λ 5007 A in low-metallicity blue compact dwarf galaxies, casting doubt on the assumption of photoionization by hot stars as the dominant source of heating of the gas in these objects of large cosmological significance. Methods. Combinations of runs of the 1D photoionization code NEBU are used to explore alternative models for the prototype giant $\ion{H}{ii}$ region shell I Zw 18 NW, with no reference to the filling factor concept and with due consideration for geometrical and stellar evolution constraints. Results. Acceptable models for I Zw 18 NW are obtained, which represent schematically an incomplete shell comprising radiation-bounded condensations embedded in a low-density matter-bounded diffuse medium. The thermal pressure contrast between gas components is about a factor 7. The diffuse phase can be in pressure balance with the hot superbubble fed by mechanical energy from the inner massive star cluster. The failure of previous models is ascribed to (1) the adoption of an inadequate small-scale gas density distribution, which proves critical when the collisional excitation of hydrogen contributes significantly to the cooling of the gas, and possibly (2) a too restrictive implementation of Wolf-Rayet stars in synthetic stellar cluster spectral energy distributions. A neutral gas component heated by soft X-rays, whose power is less than 1% of the star cluster luminosity and consistent with CHANDRA data, can explain the low-ionization fine-structure lines detected by SPITZER. [O/Fe] is slightly smaller in I Zw 18 NW than in Galactic Halo stars of similar metallicity and [C/O] is correlatively large. Conclusions. Extra heating by, e.g., dissipation of mechanical energy is not required to explain T e ([$\ion{O}{iii}$]) in I Zw 18. Important astrophysical developments depend on the 5% uncertainty attached to [$\ion{O}{iii}$] collision strengths.
Identification of item features in microblogging data

In recent years, microblogging services have become very popular. The larger volume of real-time information generated by millions of users, more important to extract useful information from the microblogging services will be. In this work, we want to use opinion mining to find the relevant and significant features of items from the microblogging services, like Twitter. We construct a sentiment-based framework to identify the relevant features in microblogging. Our method consists of two stages. First, the data process stage processes the raw data from microblogging services. Then, in second stage we extract the relevant features by the sentiment characteristics from these messages and utilize these extracted features to construct the relevant feature network and group them according their concepts relations. Therefore, our system could be applied for knowing the characteristics of a product quickly and explicitly. In our experiments, our system can identify the popular item features in different domains effectively and the same concept features can cluster together in small groups.
Effects of aerosol organics on cloud condensation nucleus (CCN) concentration and first indirect aerosol effect

Aerosol microphysics, chemical composition, and CCN properties were measured on the Department of Energy Gulfstream-1 aircraft during the Marine Stratus/Stratocumulus Experiment (MASE) conducted over the coastal waters between Point Reyes National Seashore and Monterey Bay, California, in July 2005. Aerosols measured during MASE included free tropospheric aerosols, marine boundary layer aerosols, and aerosols with high organic concentration within a thin layer above the cloud. Closure analysis was carried out for all three types of aerosols by comparing the measured CCN concentrations at ~0.2% supersaturation to those predicted based on size distribution and chemical composition using Kohler theory. The effect of aerosol organic species on predicted CCN concentration was examined using a single hygroscopicity parameterization. For aerosols with organics volume fraction up to 70%, such as the marine boundary layer and free troposphere aerosols, CCN concentration and the corresponding first indirect aerosol effect are insensitive to the properties of organics, and can be accurately predicted with a constant hygroscopicity for all organic species. This simplification can facilitate the prediction of indirect aerosol effects using physically-based parameterizations in large scale models. However, for the aerosols within the thin layers above clouds, organics contributed up to 90% of the total aerosol volume, and an accurate knowledge of the overall organic hygroscopicity is required to accurately predict CCN concentrations. Derivations of organic properties in future closure studies, when aerosols are dominated by organic species, would help constrain the descriptions of organics and aerosol-cloud parameterizations in large scale models.