Hasil untuk "Natural history (General)"

Zewen Li, Fan Liu, Wenjie Yang et al.

A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much attention from both industry and academia in the past few years. The existing reviews mainly focus on CNN’s applications in different scenarios without considering CNN from a general perspective, and some novel ideas proposed recently are not covered. In this review, we aim to provide some novel ideas and prospects in this fast-growing field. Besides, not only 2-D convolution but also 1-D and multidimensional ones are involved. First, this review introduces the history of CNN. Second, we provide an overview of various convolutions. Third, some classic and advanced CNN models are introduced; especially those key points making them reach state-of-the-art results. Fourth, through experimental analysis, we draw some conclusions and provide several rules of thumb for functions and hyperparameter selection. Fifth, the applications of 1-D, 2-D, and multidimensional convolution are covered. Finally, some open issues and promising directions for CNN are discussed as guidelines for future work.

Albert Gu, Tri Dao, Stefano Ermon et al.

A central problem in learning from sequential data is representing cumulative history in an incremental fashion as more data is processed. We introduce a general framework (HiPPO) for the online compression of continuous signals and discrete time series by projection onto polynomial bases. Given a measure that specifies the importance of each time step in the past, HiPPO produces an optimal solution to a natural online function approximation problem. As special cases, our framework yields a short derivation of the recent Legendre Memory Unit (LMU) from first principles, and generalizes the ubiquitous gating mechanism of recurrent neural networks such as GRUs. This formal framework yields a new memory update mechanism (HiPPO-LegS) that scales through time to remember all history, avoiding priors on the timescale. HiPPO-LegS enjoys the theoretical benefits of timescale robustness, fast updates, and bounded gradients. By incorporating the memory dynamics into recurrent neural networks, HiPPO RNNs can empirically capture complex temporal dependencies. On the benchmark permuted MNIST dataset, HiPPO-LegS sets a new state-of-the-art accuracy of 98.3%. Finally, on a novel trajectory classification task testing robustness to out-of-distribution timescales and missing data, HiPPO-LegS outperforms RNN and neural ODE baselines by 25-40% accuracy.

Abhishek Das, Satwik Kottur, Khushi Gupta et al.

We introduce the task of Visual Dialog, which requires an AI agent to hold a meaningful dialog with humans in natural, conversational language about visual content. Specifically, given an image, a dialog history, and a question about the image, the agent has to ground the question in image, infer context from history, and answer the question accurately. Visual Dialog is disentangled enough from a specific downstream task so as to serve as a general test of machine intelligence, while being grounded in vision enough to allow objective evaluation of individual responses and benchmark progress. We develop a novel two-person chat data-collection protocol to curate a large-scale Visual Dialog dataset (VisDial). VisDial contains 1 dialog (10 question-answer pairs) on ~140k images from the COCO dataset, with a total of ~1.4M dialog question-answer pairs. We introduce a family of neural encoder-decoder models for Visual Dialog with 3 encoders (Late Fusion, Hierarchical Recurrent Encoder and Memory Network) and 2 decoders (generative and discriminative), which outperform a number of sophisticated baselines. We propose a retrieval-based evaluation protocol for Visual Dialog where the AI agent is asked to sort a set of candidate answers and evaluated on metrics such as mean-reciprocal-rank of human response. We quantify gap between machine and human performance on the Visual Dialog task via human studies. Our dataset, code, and trained models will be released publicly at https://visualdialog.org. Putting it all together, we demonstrate the first visual chatbot!.

Mikko Kivelä, A. Arenas, M. Barthelemy et al.

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such"multilayer"features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize"traditional"network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other, and provide a thorough discussion that compares, contrasts, and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks, and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions, and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.

Y. Liaw, J. Kao, T. Piratvisuth et al.

K. Bushby, R. Finkel, D. Birnkrant et al.

J. Hardcastle

M. Foucault

H. Godfray

Melanie Mitchell

K. K. Cetina, T. Schatzki, E. Savigny

C. Worth

M. Visser

D. Kazandjian

Zoey Cho Ting Wong, Franco Wing Tak Cheng, Ivy Lynn Mak et al.

Summary: Background: Many existing randomised controlled trials lack sufficient power to assess primary kidney outcomes. This study aimed to evaluate whether statin therapy offers a clinically meaningful reno-protective effect in patients with chronic kidney disease (CKD). Methods: In this retrospective cohort study, electronic health records in Hong Kong were extracted to perform sequential target trial emulation. Eligible adults (aged 18+ years) with CKD who met the indication for statin initiation between Jan 1, 2008 and Dec 31, 2017 were included; those with history of estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m2 were excluded. Participants were categorised as statin initiators or non-initiators at each calendar month during inclusion period, where statin initiators were propensity score-matched with non-initiators. Follow-up data were collected for all participants until the occurrence of outcomes, death, loss to follow-up (2 years after last records), or the end of data availability (Dec 31, 2022), whichever occurred first. The hazard ratio (HR) of all-cause mortality, eGFR deterioration (eGFR <15 mL/min/1.73 m2, ≥30% eGFR decline, and ≥50% eGFR decline) and composite outcomes (all-cause mortality, eGFR <15 mL/min/1.73 m2, and ≥50% eGFR decline) was estimated by pooled logistic regression using intention-to-treat (ITT) and per-protocol (PP) approach. Findings: 1,437,014 eligible person-trials were identified (statin initiators n = 30,907; non-initiators n = 1,406,107), from which 30,892 statin initiators and 108,380 non-initiators were included after propensity-score matching. Relative to non-initiators, significant risk reduction was found among statin initiators in all-cause mortality (HR [95% confidence interval (CI)], ITT: 0.97 [0.95–0.98]; PP: 0.91 [0.88–0.93]), progression to eGFR <15 mL/min/1.73 m2 (ITT: 0.91 [0.89–0.93]; PP: 0.77 [0.74–0.80]), ≥50% eGFR decline (ITT: 0.95 [0.93–0.98]; PP: 0.89 [0.84–0.93]), and composite outcomes (ITT: 0.96 [0.94–0.97]; PP: 0.90 [0.88–0.92]). Statin therapy initiation was also associated significantly with reduced risk of ≥30% eGFR decline using PP approach (0.94 [0.92–0.96]). Interpretation: Over a 10-year follow-up period, initiating statin therapy in patients with CKD was associated with a small yet significant decrease in all-cause mortality and a modest reno-protective effect. Future research should aim to clarify the effects of statin intensity, duration, and adherence. Funding: National Natural Science Foundation of China.

Caroline Leuchtenberger, Lívia A. Rodrigues, Abigail Martin et al.

IONUȚ COJOCARU

The history of the Court of Accounts is part of Romania's history. The Court of Accounts is representative among the state institutions, having a role of control and balance. Maintaining balance in the country's budget means great responsibility. Therefore, we consider it useful and necessary for the activity of the Court of Accounts to be known to the citizens it honorably represents. The institution's history begins with the consolidation process of the modern Romanian state. We could say that the Court of Accounts institution is older than the country's first Constitution. In a state where Alexandru Ioan Cuza, together with the elites of that period, started the construction process based on the Western model and the ideas of the 1848 revolution, the Court of Accounts could not be missing from this democratic system. The need to establish an institution to oversee the spending of public money was natural. We are talking about an institution established 158 years ago, during the reign of Alexandru Ioan Cuza, in 1864, on a symbolic day for all Romanians. The birth certificate of the Court of Accounts is dated January 24, 1864.Symbolically, the Court of Accounts is linked to this historic day, a longawaited day, a day when the ideal of Romanians took shape.

Violeta Zhelyazkova, Nicola Fischer, Sebastien Puechmaille

White-nose disease (WND), caused by the psychrophilic fungus Pseudogymnoascus destructans, represents one of the greatest threats for North American hibernating bats. Research on molecular data has significantly advanced our knowledge of various aspects of the disease, yet more studies are needed regarding patterns of P. destructans genetic diversity distribution. In the present study, we investigate three sites within the native range of the fungus in detail: two natural hibernacula (karst caves) in Bulgaria, south-eastern Europe and one artificial hibernaculum (disused cellar) in Germany, northern Europe, where we conducted intensive surveys between 2014 and 2019. Using 18 microsatellite and two mating type markers, we describe how P. destructans genetic diversity is distributed between and within sites, the latter including differentiation across years and seasons of sampling; across sampling locations within the site; and between bats and hibernaculum walls. We found significant genetic differentiation between hibernacula, but we could not detect any significant differentiation within hibernacula, based on the variables examined. This indicates that most of the pathogen’s movement occurs within sites. Genotypic richness of P. destructans varied between sites within the same order of magnitude, being approximately two times higher in the natural caves (Bulgaria) compared to the disused cellar (Germany). Within all sites, the pathogen’s genotypic richness was higher in samples collected from hibernaculum walls than in samples collected from bats, which corresponds with the hypothesis that hibernacula walls represent the environmental reservoir of the fungus. Multiple pathogen genotypes were commonly isolated from a single bat (i.e. from the same swab sample) in all study sites, which might be important to consider when studying disease progression.

Julie M. Kern, Paul G. McDonald

Mobbing is a widespread, vocally coordinated behaviour where species approach and harass a threat. The noisy miner (Manorina melanocephala) is a notorious native Australian honeyeater, well‐known for its hyperaggressive mobbing. Numerous studies have identified negative impacts of their mobbing behaviour, highlighting the exclusion of competitors from colony areas and the resulting loss of woodland‐bird biodiversity. Despite this, few studies have investigated mobbing itself, and our understanding of the factors which influence its expression remains limited. Here, we use a field‐based playback experiment to investigate whether mobbing responses vary in relation to colony borders and caller familiarity. Noisy miners were more likely to respond, reacted more quickly and responded more strongly to mobbing calls broadcast inside as opposed to outside the colony. These behavioural differences likely arise from variation in the relative costs and benefits of responding. When noisy miners did mob outside the colony, more individuals joined in response to unfamiliar as opposed to familiar callers. Our results reveal that noisy miner mobbing may not be as indiscriminate as often assumed, with caller familiarity and location influencing this behaviour. We suggest there are benefits to greater consideration of the factors impacting noisy miner mobbing behaviour. Keywords: Avian biodiversity, interspecific aggression, mobbing behaviour, noisy miner, vocal communication

Jacinda Tran, Christine Lee Hathaway, Cara Jill Broshkevitch et al.

IntroductionWomen living with human immunodeficiency virus (WLHIV) face elevated risks of human papillomavirus (HPV) acquisition and cervical cancer (CC). Coverage of CC screening and treatment remains low in low-and-middle-income settings, reflecting resource challenges and loss to follow-up with current strategies. We estimated the health and economic impact of alternative scalable CC screening strategies in KwaZulu-Natal, South Africa, a region with high burden of CC and HIV.MethodsWe parameterized a dynamic compartmental model of HPV and HIV transmission and CC natural history to KwaZulu-Natal. Over 100 years, we simulated the status quo of a multi-visit screening and treatment strategy with cytology and colposcopy triage (South African standard of care) and six single-visit comparator scenarios with varying: 1) screening strategy (HPV DNA testing alone, with genotyping, or with automated visual evaluation triage, a new high-performance technology), 2) screening frequency (once-per-lifetime for all women, or repeated every 5 years for WLHIV and twice for women without HIV), and 3) loss to follow-up for treatment. Using the Ministry of Health perspective, we estimated costs associated with HPV vaccination, screening, and pre-cancer, CC, and HIV treatment. We quantified CC cases, deaths, and disability-adjusted life-years (DALYs) averted for each scenario. We discounted costs (2022 US dollars) and outcomes at 3% annually and calculated incremental cost-effectiveness ratios (ICERs).ResultsWe projected 69,294 new CC cases and 43,950 CC-related deaths in the status quo scenario. HPV DNA testing achieved the greatest improvement in health outcomes, averting 9.4% of cases and 9.0% of deaths with one-time screening and 37.1% and 35.1%, respectively, with repeat screening. Compared to the cost of the status quo ($12.79 billion), repeat screening using HPV DNA genotyping had the greatest increase in costs. Repeat screening with HPV DNA testing was the most effective strategy below the willingness to pay threshold (ICER: $3,194/DALY averted). One-time screening with HPV DNA testing was also an efficient strategy (ICER: $1,398/DALY averted).ConclusionsRepeat single-visit screening with HPV DNA testing was the optimal strategy simulated. Single-visit strategies with increased frequency for WLHIV may be cost-effective in KwaZulu-Natal and similar settings with high HIV and HPV prevalence.