Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

This document is an international evidence-based guideline on the diagnosis and management of idiopathic pulmonary fibrosis, and is a collaborative effort of the American Thoracic Society, the European Respiratory Society, the Japanese Respiratory Society, and the Latin American Thoracic Association. It represents the current state of knowledge regarding idiopathic pulmonary fibrosis (IPF), and contains sections on definition and epidemiology, risk factors, diagnosis, natural history, staging and prognosis, treatment, and monitoring disease course. For the diagnosis and treatment sections, pragmatic GRADE evidence-based methodology was applied in a question-based format. For each diagnosis and treatment question, the committee graded the quality of the evidence available (high, moderate, low, or very low), and made a recommendation (yes or no, strong or weak). Recommendations were based on majority vote. It is emphasized that clinicians must spend adequate time with patients to discuss patients' values and preferences and decide on the appropriate course of action.

An Official ATS/ERS/JRS/ALAT Statement: Idiopathic Pulmonary Fibrosis: Evidence-Based Guidelines for Diagnosis and Management

Acute kidney injury (AKI) is a complex disorder for which currently there is no accepted definition. Having a uniform standard for diagnosing and classifying AKI would enhance our ability to manage these patients. Future clinical and translational research in AKI will require collaborative networks of investigators drawn from various disciplines, dissemination of information via multidisciplinary joint conferences and publications, and improved translation of knowledge from pre-clinical research. We describe an initiative to develop uniform standards for defining and classifying AKI and to establish a forum for multidisciplinary interaction to improve care for patients with or at risk for AKI. Members representing key societies in critical care and nephrology along with additional experts in adult and pediatric AKI participated in a two day conference in Amsterdam, The Netherlands, in September 2005 and were assigned to one of three workgroups. Each group's discussions formed the basis for draft recommendations that were later refined and improved during discussion with the larger group. Dissenting opinions were also noted. The final draft recommendations were circulated to all participants and subsequently agreed upon as the consensus recommendations for this report. Participating societies endorsed the recommendations and agreed to help disseminate the results. The term AKI is proposed to represent the entire spectrum of acute renal failure. Diagnostic criteria for AKI are proposed based on acute alterations in serum creatinine or urine output. A staging system for AKI which reflects quantitative changes in serum creatinine and urine output has been developed. We describe the formation of a multidisciplinary collaborative network focused on AKI. We have proposed uniform standards for diagnosing and classifying AKI which will need to be validated in future studies. The Acute Kidney Injury Network offers a mechanism for proceeding with efforts to improve patient outcomes.

Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury

Device and method of monitoring activity in fish. Device located in the operculum to monitor the metabolic state and well-being of fish through joint and simultaneous measures of respiratory rate and physical activity by means of a plurality of coplanar accelerations (x, y) and normal to the operculum (z axis). The substrate is flexible and covered with a waterproof coating, where an electronic circuit with acceleration sensor (208), a control unit (202), a microcontroller (206) configured to run at least one activity monitoring routine is located, a memory (210) and a battery (204). The data collection is carried out through an external unit (201) that can eventually process them totally or partially. These types of measurements can be processed together with other types of measurements, obtained from other environmental parameters sensors. (Machine-translation by Google Translate, not legally binding)

DEVICE AND METHOD OF MONITORING OF ACTIVITY IN FISH (Machine-translation by Google Translate, not legally binding)

Parent–offspring conflict theory predicts that offspring seek to prolong the parental care period, while parents strive to shorten it as much as possible. Transition to the creche phase in penguins involves changes in the dynamic of parental investment in chicks, and thus may be modulated by interests that benefit parent or offspring. We explored parent–offspring interactions in the Chinstrap Penguin (Pygoscelis antarctica) to understand the influence such interactions would have on transition to creche phase. We studied the effect of hatching date, nestling age, brood size, and nest location on parent–offspring interactions and the length of the guard phase. All behavioral variables related to nestling demands for parental investment increased as well as parental aggression towards their chicks, with increased nestling age. Brood size showed significant effects on both nestling and parental behavior. Hatching date was negatively correlated with the age at creche. Consequently, the decision to leave the chicks unguarded seemed to be more based on the condition of adults rather than of the chicks. Given the short time available for breeding in Antarctica and that penguins are long-lived birds with several opportunities to breed, there may be conflicting selective factors between investment in feeding chicks versus extending the period of resource acquisition and storage prior to moult.

/pdf/parent-offspring-conflict-and-transition-to-creche-phase-in-4hh8jiydwm.pdf

Parent–offspring conflict and transition to crèche phase in Chinstrap Penguins (Pygoscelis antarctica)

This present work presents different feature reduction methods, applied to Deoxyribonucleic Acid (DNA) marker, and in order to identify a success of 100% based on Discriminate Common Vectors (DCV), Principal Component Analysis (PCA), and Independent Component Analysis (ICA) using as classifiers Support Vector Machines (SVM) and Artificial Neural Networks. In particular, the biochemical parameterization has 89 Random Amplified polymorphic DNA (RADPS) markers of Pejibaye palm landraces, and it has been reduced from 89 to a 3 characteristics, for the best method using ICA. The interest of this application is due to feature reduction and therefore, the reduction of computational load time versus the use of all features. This method allows having a faster supervised classification system for the process of the plant certification with origin denomination. Therefore, this system can be transferred to voice applications in order to reduce load time, keeping or improving the success rates.

Reducing features from pejibaye palm DNA marker for an efficient classification

Kinetic Study of Formation of (Co(H2PO4)(H2O)5)2+ (I) at Various Acidities and Ionic Strengths.

Thispaperpresents a multimodal biometric identification systembasedon thecombination of geometrical, palmandfinger print features ofthehuman hand. Theright handimages areacquired byacommercial scanner with a150dpiresolution. Thegeometrical features areobtained fromthebinarized images andconsist on15 measures. A Support Vector Machines isusedasverifier. Thepalmprint andfinger texture areobtained bymeansof different 2D Gaborphaseencoding schemes. A robust coordinate system isdefined toassure theimagealignment. AHamming distance andthreshold areusedforverifying the identity. A feature, score anddecision level fusion results haveshown theimprovement ofthecombined scheme.

Miguel Ferrer

Papers

DEVICE AND METHOD OF MONITORING OF ACTIVITY IN FISH (Machine-translation by Google Translate, not legally binding)

Parent–offspring conflict and transition to crèche phase in Chinstrap Penguins (Pygoscelis antarctica)

Reducing features from pejibaye palm DNA marker for an efficient classification

Kinetic Study of Formation of (Co(H2PO4)(H2O)5)2+ (I) at Various Acidities and Ionic Strengths.

LowCostMultimodal Biometric identification System Based onHandGeometry, PalmandFinger Print Texture