Hasil untuk "Natural history (General)"

Lei Zhang, B. Liu

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online.

A. Barberán, S. Bates, E. Casamayor et al.

O. John, S. Srivastava

T. A. Stewart

M. Foucault, J. Miskowiec

M. Antrop

F. Hayes-Roth

R. Bonow, B. Carabello, A. C. D. Leon et al.

B. Campbell

Ilias Diakonikolas, Gautam Kamath, D. Kane et al.

We study high-dimensional distribution learning in an agnostic setting where an adversary is allowed to arbitrarily corrupt an epsilon fraction of the samples. Such questions have a rich history spanning statistics, machine learning and theoretical computer science. Even in the most basic settings, the only known approaches are either computationally inefficient or lose dimension dependent factors in their error guarantees. This raises the following question: Is high-dimensional agnostic distribution learning even possible, algorithmically? In this work, we obtain the first computationally efficient algorithms for agnostically learning several fundamental classes of high-dimensional distributions: (1) a single Gaussian, (2) a product distribution on the hypercube, (3) mixtures of two product distributions (under a natural balancedness condition), and (4) mixtures of k Gaussians with identical spherical covariances. All our algorithms achieve error that is independent of the dimension, and in many cases depends nearly-linearly on the fraction of adversarially corrupted samples. Moreover, we develop a general recipe for detecting and correcting corruptions in high-dimensions, that may be applicable to many other problems.

N. Williams, E. Crone, T. Roulston et al.

W. White, M. R. Carvalho, B. Séret et al.

Cedric Khayale, Erustus Kanga, Patrick Omondi et al.

The black rhinoceros (Diceros bicornis) experienced precipitous declines across Africa during the 1970s and 1980s, primarily driven by poaching. The decline was particularly severe for the eastern subspecies (D. b. michaeli). Kenya’s population, which once supported a significant proportion of the species, declined from approximately 20,000 to 370 individuals by 1989, at the time that the Kenya Wildlife Service (KWS) was established. Over the last three decades, considerable effort and resources have been deployed, and an enabling policy and legislative framework have been enacted to recover rhino populations. As a result, the declining trend has been reversed, and the number of indigenous black rhinos is increasing. Remarkable progress has been achieved through strategic interventions and population recovery initiatives, with Kenya’s black rhinos reaching a confirmed total of 1,059 individuals in 2024—marking a historic milestone. We document Kenya’s rhino conservation progression, including the current population status, challenges and future strategies aimed at supporting the long-term vision of achieving 2,000 individuals, thereby securing the future of D. b. michaeli.

Rui Nobre Moreira

A proposta apresentada neste texto tenta esbater as desmesuradas desigualdades remuneratórias hoje existentes em sociedades ditas democráticas.  Desmesuradas desigualdades remuneratórias serão sempre incompatíveis com o funcionamento genuinamente democrático de uma sociedade. A sua própria existência é uma prova de que vivemos em democracias disfuncionais. A ideologia neoliberal, que tem imperado em quase todo o mundo nos últimos 40 anos, tem vindo a acentuá-las. É hoje cada vez mais evidente a existência de uma oligarquia plutocrática, com um poder excessivo para sociedades que se pretendem democráticas. Quando usam o termo “democracia liberal”, para designar as sociedades em que vivemos, temos de considerá-lo um eufemismo. Vivemos sim em plutocracias neoliberais, em que uma percentagem ínfima dos cidadãos possui um excessivo e ilegítimo poder, sempre enquistado no sistema financeiro, mantendo sequestrados os Estados. Se esta situação é inaceitável, também o é uma situação em que a desigualdade remuneratória se esbata tanto, que impeça premiar o mérito social da atividade de cada um dos cidadãos. Esta proposta tenta encontrar um ponto de equilíbrio entre estas dois extremos. Por um lado, não permitir a existência de oligarquias plutocráticas, mas permitindo premiar, dentro de limites socialmente aceitáveis, o mérito social da atividade de cada um dos cidadãos.

Mitchell H Keylor, Bryan S. Matsuura, C. Stephenson

Since the dawn of the 20th century, the average life expectancy at birth has nearly doubled due to advances in science and medicine. As medical records grew more reliable, it became apparent that, while overall life span was increasing, there were significant epidemiological differences between geographical regions, with people from countries such as Japan, France, and Switzerland enjoying longer life expectancy as compared to other regions of the world. The causative factors for these disparities in both mortality and morbidity have been attributed not only to genetics but also to the contributions of highly variable lifestyle and environmental influences.1 Barring differences in modernization and public health policy, diet is the most significant epidemiological factor cross-culturally and is thought to be a profoundly important contributor to health and overall well-being. Prior to the early 1990s, there was a general consensus in support of the belief that moderate alcohol consumption significantly lowered the risk of coronary heart disease (CHD).2 However, it was not clear whether this was true of all alcoholic beverages or which constituents in the drinks were responsible for these beneficial properties.3 In 1992, Siemann and Creasy4 reported that resveratrol (1) was present in significant concentrations in red wine, drawing attention to the fact that it was also an active principle found in Japanese and Chinese folk medicines used to treat ailments related to the liver, skin, heart, and lipid metabolism.5 The discovery of resveratrol in wine was particularly timely; although the correlation between high fat and cholesterol consumption and coronary heart disease was widely accepted,6 certain populations, namely the French, had a low incidence of CHD mortality despite a diet and lifestyle that exposed these individuals to elevated risk factors.7 The cardioprotective ability of resveratrol, its oligomers, along with other phytochemicals present in wine, appeared to resolve this “French Paradox” and advanced the notion that a chemical constituent of one’s diet could be beneficial to health.8 Although the reality of the French Paradox remains contentious,9,10 research into the health benefits of resveratrol has exploded as a result. The reported biological activities of resveratrol are numerous, including antioxidant,11 anticancer,12 antidiabetic,13,14 cardioprotective,15 and even antiaging properties,16 to name a few. The body of literature regarding the biological activity of resveratrol is expansive and beyond of the scope of this review. We invite the readers to the following resources for background on this exciting and ongoing field of research.17−21 Despite its enormous popularity, resveratrol is but a single compound in a large, structurally diverse class of oligomeric stilbenoids that are present in the wines and foods that we consume.22,23 Until recently, access to these oligomeric natural products was limited to isolation from natural sources, which severely hampered their biological evaluation. The scientific interest in resveratrol has undoubtedly instigated the renewed attention in these compounds by the chemical community. Advances in the characterization, isolation techniques, and synthesis of these natural products have significantly enriched our understanding of their chemistry and biology. Our review seeks to document the history and recent progress in the isolation, chemical synthesis, and biology of this fascinating class of phytochemicals, while providing new insight on the biosynthesis and future prospects for the field as a whole.

Nataliia Suriadna, Halyna Mykytynets

Frogs of the genus Rana Linnaeus, 1758 are represented in the steppe zone of Ukraine by their southernmost populations. The distribution of brown frogs in the steppe zone of Ukraine is closely related to the floodplain forests of major rivers (Dnipro, Dnister, Danube, Southern Bug, Oril, Samara, Donets, etc.). The paper presents for the first time data on the distribution, ecological and population features, habitats, specifics of reproduction and development of brown frogs. New habitats of R. arvalis were found in the floodplain habitats of the lower reaches of the Dnipro River in Kherson Oblast and populations were confirmed in Dnipropetrovsk and Kirovohrad oblasts. The southern border is intrazonal. The new southernmost localities are described from Kherson Oblast (the villages of Pravi Solontsi and Krynky). The habitats belong to forest type habitats (G). The mean abundance of frogs is 5–10 individuals per 1 km of route and can reach 50 individuals per 10 m2 during the spawning season (Black Forest Reserve, Kirovohrad Oblast). The breeding season is in late March to early April at air temperatures of +3–4 to 8–12°C and water temperatures of +7–9°C. The mating process is short. The Dnipro isolates of R. arvalis may be of relict nature, form a series of refugia and be of important historical and indicator value. Given the overall reduction in the range of R. arvalis within its core area, active populations in the south can be valuable reserves for the conservation of the species and the sustainability of steppe biodiversity. Two other species, R. temporaria and R. dalmatina, were not found and their habitat within the steppe zone has not yet been confirmed. As typical forest species, they are common closer to the forest-steppe zone. Given the current state of brown frog populations in the steppe zone of Ukraine, their low numbers and isolation, they need regional protection along with their habitats. The issue of determining the origin of the identified populations in order to form an idea of the historical and genetic value of the southernmost populations of brown frogs in Ukraine remains promising.

Jared D. Hall, Heather A. Mathewson, Shaun L. Oldenburger et al.

Abstract Banding data are commonly used to estimate vital rates for migratory game bird management. We used white‐winged dove (Zenaida asiatica) banding data to estimate molt and hatch chronology in Texas. We used Texas Parks and Wildlife Department's long‐term, state‐wide banding data (71,675 banded individuals) from 1 June to 15 August 2007–2016 to investigate primary feather molt and hatching in white‐winged doves in Texas. We estimated primary feather molt and used individual recapture data to determine reliability of models predicting primary feather molt rates. For hatching, we used primary feather molt scores of captured hatch‐year doves to backdate to an estimated hatch date. Our modeling predicted mean after‐hatch‐year primary feather molt rate of 13.21 ± 0.93 days. We predicted 95% of adult white‐winged doves began molting between 7 April to 8 July and completed molt between 17 August to 17 November. Across all years, white‐winged doves hatched as early as 6 January and as late as 27 July, with 95% of all hatching occurring between 22 March and 18 June and peaking on 4 May. Primary feather molt initiation peaked 16 days after the peak of hatching, suggesting that white‐winged doves delay the onset of primary molt until reproductive activity slows. Secondary data collected during banding operations on migratory game birds may be used to understand additional life processes without the requirement to initiate additional survey efforts.

Donna D. Zhang, E. Chapman

Covering: up to 2020The transcription factor NRF2 is one of the body's major defense mechanisms, driving transcription of >300 antioxidant response element (ARE)-regulated genes that are involved in many critical cellular processes including redox regulation, proteostasis, xenobiotic detoxification, and primary metabolism. The transcription factor NRF2 and natural products have an intimately entwined history, as the discovery of NRF2 and much of its rich biology were revealed using natural products both intentionally and unintentionally. In addition, in the last decade a more sinister aspect of NRF2 biology has been revealed. NRF2 is normally present at very low cellular levels and only activated when needed, however, it has been recently revealed that chronic, high levels of NRF2 can lead to diseases such as diabetes and cancer, and may play a role in other diseases. Again, this "dark side" of NRF2 was revealed and studied largely using a natural product, the quassinoid, brusatol. In the present review, we provide an overview of NRF2 structure and function to orient the general reader, we will discuss the history of NRF2 and NRF2-activating compounds and the biology these have revealed, and we will delve into the dark side of NRF2 and contemporary issues related to the dark side biology and the role of natural products in dissecting this biology.

Kenneth B. Raposa, Michael Bradley, Caitlin Chaffee et al.

Heightened recognition of impacts to coastal salt marshes from sea-level rise has led to expanding interest in using thin-layer sediment placement (TLP) as an adaptation tool to enhance future marsh resilience. Building on successes and lessons learned from the Gulf and southeast U.S. coasts, projects are now underway in other regions, including New England where the effects of TLP on marsh ecosystems and processes are less clear. In this study, we report on early responses of a drowning, microtidal Rhode Island marsh (Ninigret Marsh, Charlestown, RI) to the application of a thick (10–48 cm) application of sandy dredged material and complimentary extensive adaptive management to quickly build elevation capital and enhance declining high marsh plant species. Physical changes occurred quickly. Elevation capital, rates of marsh elevation gain, and soil drainage all increased, while surface inundation, die-off areas, and surface ponding were greatly reduced. Much of the marsh revegetated within a few years, exhibiting aspects of classic successional processes leading to new expansive areas of high marsh species, although low marsh Spartina alterniflora recovered more slowly. Faunal communities, including nekton and birds, were largely unaffected by sediment placement. Overall, sediment placement provided Ninigret Marsh with an estimated 67–320 years of ambient elevation gain, increasing its resilience and likely long-term persistence. Project stakeholders intentionally aimed for the upper end of high marsh plant elevation growth ranges to build elevation capital and minimize maintenance costs, which also resulted in new migration corridors, providing pathways for future marsh expansion.

M. Chevrette, Athina Gavrilidou, Shrikant S. Mantri et al.

This review covers literature between 2003-2021The development and application of genome mining tools has given rise to ever-growing genetic and chemical databases and propelled natural products research into the modern age of Big Data. Likewise, an explosion of evolutionary studies has unveiled genetic patterns of natural products biosynthesis and function that support Darwin's theory of natural selection and other theories of adaptation and diversification. In this review, we aim to highlight how Big Data and evolutionary thinking converge in the study of natural products, and how this has led to an emerging sub-discipline of evolutionary genome mining of natural products. First, we outline general principles to best utilize Big Data in natural products research, addressing key considerations needed to provide evolutionary context. We then highlight successful examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes. Rather than an exhaustive list of evolution-driven discoveries, we highlight examples where Big Data and evolutionary thinking have been embraced for the evolutionary genome mining of natural products. After reviewing the nascent history of this sub-discipline, we discuss the challenges and opportunities of genomic and metabolomic tools with evolutionary foundations and/or implications and provide a future outlook for this emerging and exciting field of natural product research.