Hasil untuk "Natural history (General)"

Yakir Aharonov, Guy Hetzroni

This oral history interview provides Yakir Aharonov's perspective on the theoretical discovery of the Aharonov-Bohm effect in 1959, during his PhD studies in Bristol with David Bohm, the reception of the effect, the efforts to test it empirically (up to Tonomura's experiment), and some of the debates regarding the existence of the effect and its interpretation. The interview also discusses related later developments until the 1980s, including modular momentum and Berry's phase. It includes recollections from meetings with Werner Heisenberg, Richard Feynman, and Chen-Ning Yang, also mentioning John Bell, Robert Chambers, Werner Ehrenberg, Sir Charles Frank, Wendell Furry, Gunnar Källén, Maurice Pryce, Nathan Rosen, John Wheeler, and Eugene Wigner.

Hiroto Sato, Konan Shimizu

In social learning environments, agents acquire information from both private signals and the observed actions of predecessors, referred to as history. We define the value of history as the gain in expected payoff from accessing both the private signal and history, compared to relying on the signal alone. We first characterize the information structures that maximize this value, showing that it is highest under a mixture of full information and no information. We then apply these insights to a model of markets for history, where a monopolistic data seller collects and sells access to history. In equilibrium, the seller's dynamic pricing becomes the value of history for each agent. This gives the seller incentives to increase the value of history by designing the information structure. The seller optimal information discloses less information than the socially optimal level.

Kan Wang, Hang Xu, Hao Wang et al.

Ports are of great significance in processing cargo containers and facilitating global marine logistics. Nevertheless, the susceptibility of the container shipping network for hazardous cargo is likely to intensify in the event of a significant disruption at a major port, such as adverse weather conditions, inadequate management practices, or unforeseen catastrophes. Such situations require the deployment of port protection emergency response and prevention in advance. This study proposes a digital twin (DT) model that employs extensive and trajectory data within containers to comprehensively analyze the occurrence of hazardous cargo failures within the port storage process. The virtual models of physical entities in the port are created through a data-driven approach, and the behavior of these entities in a port environment with big data is then simulated. A combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) algorithm is employed to provide predictions for the service layer of the DT system. The predicted correlation coefficients of temperature and humidity in the container reach 0.9855 and 0.9181, respectively. The developed system driven by DT models integrated with a CNN and the LSTM algorithm can more effectively assist the safety manager in achieving prevention in port operations. This study enables marine authorities and decision-makers to optimize emergency procedures, thereby reducing the probability of accidents in port operations and logistics.

Kodera Chie, Bret Yann, Eyraud Frederic et al.

This study explores the efficacy and reliability of high-pressure freezing (HPF) as a sample preparation technique for electron microscopy (EM) analysis across a diverse range of biological samples. Utilizing the HPM Live µ technology, based on the historical hydraulic HPM010 from BalTec, we demonstrate the reliability of our industrial equipment to achieve the critical parameters necessary for vitrification (2076 bars, cooling rate above 2000 K/s). By directly measuring physical values within the HPF chamber, we evaluate the proper functioning of the equipment, contributing to the technique’s reliability. A meticulous approach was adopted for each sample type, acknowledging the uniqueness of each specimen, and associating the final sample analysis with its HPF curve, aiding in protocol optimization. Samples including human cell pellets, cell monolayer, mouse brain and liver biopsies, and Arabidopsis thaliana root and seedlings were processed for EM analysis following HPF. The ultrastructure of each sample type was rigorously examined, revealing homogeneous preservation and minimal ice nucleation artefacts. Overall, our work underscores the robustness and versatility of our HPM Live µ in preserving biological ultrastructure, offering valuable insights for researchers employing EM techniques in diverse biological studies.

M. Emilia Bravo, Miriam I. Brandt, Jesse M. A. van der Grient et al.

The deep ocean comprises complex ecosystems made up of numerous community and habitat types that provide multiple services that benefit humans. As the industrialization of the deep sea proceeds, a standardized and robust set of methods and metrics need to be developed to monitor the baseline conditions and any anthropogenic and climate change-related impacts on biodiversity, ecosystem function, and ecosystem services. Here, we review what we have learned from studies involving offshore-energy industries, including state-of-the-art technologies and strategies for obtaining reliable metrics of deep-sea biodiversity and ecosystem function. An approach that includes the detection and monitoring of ecosystem services, with open access to baseline data from multiple sectors, can help to improve our global capacity for the management of the deep ocean.

Zhijian Hou, Lei Ji, Difei Gao et al.

In this report, we present our champion solution for Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2023. Essentially, to accurately ground in a video, an effective egocentric feature extractor and a powerful grounding model are required. Motivated by this, we leverage a two-stage pre-training strategy to train egocentric feature extractors and the grounding model on video narrations, and further fine-tune the model on annotated data. In addition, we introduce a novel grounding model GroundNLQ, which employs a multi-modal multi-scale grounding module for effective video and text fusion and various temporal intervals, especially for long videos. On the blind test set, GroundNLQ achieves 25.67 and 18.18 for R1@IoU=0.3 and R1@IoU=0.5, respectively, and surpasses all other teams by a noticeable margin. Our code will be released at\url{https://github.com/houzhijian/GroundNLQ}.

Luiz Carlos Santos Junior, Kamylla Balbuena Michelutti, Rafaella Caroline Bernardi et al.

Intracolonial recognition among social insects is performed mainly by means of cuticular hydrocarbons (CHCs) that provide chemical communication, although their primary function is the avoidance of desiccation. Therefore, the ability to adjust to climatic variation may be related to the composition of CHCs. The hypothesis adopted in this work was that workers of the ant Odontomachus brunneus, when exposed to higher or lower average temperatures, change the CHCs composition, as a readjustment to the new conditions, and that this, in turn, leads to a change in intraspecific recognition capacity. To test this hypothesis, colonies of O. brunneus reared in the laboratory were subdivided into four groups. Two groups were kept at the same temperature, in order to assess the effect of isolation itself, while one group was kept at high temperature and another was kept at low temperature. Two groups were maintained at 25 °C, with no further conditions imposed. Subsequently, encounters were induced between individuals from these groups and from the high and low temperature groups, followed by the extraction of CHCs from each individual. The results indicated significant differences in recognition time and CHC composition between the high/low temperature groups and those kept at 25 °C. Antennation time during nestmate encounters was significantly longer for the groups submitted to temperature treatments (high and low), compared to those kept at 25 °C, suggesting recognition difficulty. In order to adjust to changing temperature conditions, O. brunneus undergoes changes in the composition of CHCs and in intraspecific recognition capacity.

Alvise Finotello, Alvise Finotello, Andrea D’Alpaos et al.

We present a new bidimensional, spatially-explicit ecological model describing the dynamics of halophytic vegetation in tidal saline wetlands. Existing vegetation models employ relatively simple deterministic or stochastic mechanisms, and are driven by local environmental conditions. In the proposed model, in contrast, vegetation dynamics depend not only on the marsh local habitat, but also on spatially-explicit mechanisms of dispersal and competition among multiple interacting species. The role of habitat quality, here determined by the local elevation relative to the mean sea level as a proxy for environmental conditions, is mathematically modeled by a logistic function that represents the fundamental (theoretical) niche of each halophytic species. Hence, the model does not artificially impose any constraints to the ability of a species to colonize elevated areas where it is usually not observed: such limitations naturally arise through competition with fitter species across marsh topographic gradients. We qualitatively test our model against field data based on a suitable assemblage of focus species, and perform a sensitivity analysis aimed at determining how dynamic equilibria in vegetation distributions are affected by changes in model input parameters. Results indicate that the model is robust and can predict realistic vegetation distributions and species-richness patterns. More importantly, the model is also able to effectively reproduce the outcomes of classical ecological experiments, wherein a species is transplanted to an area outside its realized niche. A direct comparison shows that previous models not accounting for dispersal and interspecific competitions are unable to reproduce such dynamics. Our model can be easily integrated into virtually any existing morphodynamic model, thereby strengthening our ability to simulate the coupled biotic and abiotic evolution of salt marshes under changing climate forcings.

Laila Thomaz Sandroni, Katia Maria Paschoaletto Micchi de BarrosFerraz, Silvio Marchini et al.

Abstract Transdisciplinary projects are fundamental to a more effective and just conservation, but their application and coherent framing present challenges, since their nature is to bring together different epistemological backgrounds and world views. This paper identifies the possibilities offered by stakeholder mapping as a tool for generating common understandings in transdisciplinary conservation research projects. Lessons are drawn from experiential learning through the case of jaguar conservation in the Brazilian Atlantic Forest (BAF). Stakeholder mapping proved to be an essential diagnostic tool that generated an overview of the material context of human–jaguar interactions in the BAF to stakeholders engaged in the project. The process and overview drew attention to gaps in stakeholder knowledge that need to be addressed to enhance conviviality between humans and jaguars in fragmented landscapes. Recognizing these knowledge gaps assists in the production of methodologies that can effectively encompass different social groups, and increase all parties' perceptions of the legitimacy of conservation activities. We argue that, due to its collective nature, stakeholder mapping can foster mutual learning and deeper communication in the context of divergent framings of complex nature conservation problems, such as in jaguar conservation.

Xiaodong Zhang, Zhifei Liu, Yulong Zhao et al.

Marine microplastics are widely distributed in deep-sea sedimentary environments and are altering sediment compositions and ecological conditions on the seafloor. However, the relation between the distribution of microplastics in deep-sea sediments and the sedimentary dynamic conditions is poorly understood. In this study, we collected surface sediments from some typical geomorphological units (sand dune, sediment drift, and submarine canyon channel/levee) in the northern South China Sea to study composition and distribution of the deep-sea microplastics and their controlling factors. The results show that the microplastic abundance in surface sediments ranges from 19 to 347 p·kg–1, and the identified microplastics consist of 10 types, including dominant polycarbonate (29%), polyethylene (27%), polyester fiber (16%), polyvinyl chloride (13%), and polypropylene (7%), and minor polyethylene terephthalate resin, acrylonitrile-butadiene-styrene, epoxy resin, hydrocarbon resin, and acrylic. The source analysis shows that the deep-sea microplastics may be influenced by riverine inputs from Taiwan and South China. In addition, the microplastic spatial distribution shows that the sand dune and canyon channel contain the highest abundances (136–347 p·kg–1) and more types (4–6 types) of microplastics, which are dominated by relatively high-density polycarbonate or polyvinyl chloride. The canyon levee contains the lowest abundances (19–132 p·kg–1) and less types (1–3 types) of microplastics, which are dominated by relatively low-density polyester fiber or polyethylene. Nevertheless, the microplastic composition of the sediment drift is between those of the canyon channel and the canyon levee. The abundance and polymer type (density) of microplastics all increase with the increased mean grain size of detrital sediments, which represents the progressively enhanced intensity of sedimentary dynamic conditions. We therefore infer that the sedimentary dynamic conditions control the composition and distribution of microplastics in the deep-sea sediments. This study highlights that some deep-sea environments with stronger sedimentary dynamic conditions may accumulate more microplastics, which is of great significance for evaluating the storage and ecological damage of deep-sea microplastics.

Kelly A. Kearney, Kelly A. Kearney, Steven J. Bograd et al.

Climate change may impact ocean ecosystems through a number of mechanisms, including shifts in primary productivity or plankton community structure, ocean acidification, and deoxygenation. These processes can be simulated with global Earth system models (ESMs), which are increasingly being used in the context of fisheries management and other living marine resource (LMR) applications. However, projections of LMR-relevant metrics such as net primary production can vary widely between ESMs, even under identical climate scenarios. Therefore, the use of ESM should be accompanied by an understanding of the structural differences in the biogeochemical sub-models within ESMs that may give rise to these differences. This review article provides a brief overview of some of the most prominent differences among the most recent generation of ESM and how they are relevant to LMR application.

Arne B.R. Witt, Winnie Nunda, Tim Beale et al.

This is the first assessment of naturalised, invasive and potentially invasive alien plant species present in Laikipia County, Kenya, which hosts the highest populations of endangered large mammals in the country. We undertook broad-scale roadside surveys in Laikipia, recording all naturalised and invasive species, and based on an extensive literature review, also compiled a list of those alien species present that are known to threaten biodiversity and livelihoods elsewhere in the world. The data were supplemented by CLIMEX eco-climatic niche models of nine species that we consider to pose the biggest threat to conservation initiatives in the East African region. Of the 145 alien plant species recorded, 67 and 37 (including four species of uncertain origin) were considered to be already naturalised or invasive, respectively, and a further 41 species had been recorded as being naturalised or invasive outside of Laikipia. Most (141) of these species were introduced as ornamentals only or had uses in addition to being ornamentals, with the majority (77) having their origins in tropical America. Widespread species in the county included Opuntia stricta, O. ficus-indica, Austrocylindropuntia subulata and other succulents. Based on the current eco-climatic conditions, most of Laikipia is unsuitable for Chromolaena odorata, marginally suitable for Mimosa pigra and Lantana camara, and a better climatic match, ranked from least to most favourable, for Tithonia diversifolia, Cryptostegia grandiflora, Parthenium hysterophorus, Prosopis juliflora, O. stricta and Parkinsonia aculeata. Conservation implications: Invasive alien plants are known to have negative impacts on biodiversity, and as such pose significant threats to protected area ecosystems worldwide. Without efforts to eradicate, contain or control invasive plant species in Laikipia, one of the most important conservation areas in eastern Africa many rare and iconic wildlife species may be lost.

Martina Toshevska, Frosina Stojanovska, Jovan Kalajdjieski

Distributed language representation has become the most widely used technique for language representation in various natural language processing tasks. Most of the natural language processing models that are based on deep learning techniques use already pre-trained distributed word representations, commonly called word embeddings. Determining the most qualitative word embeddings is of crucial importance for such models. However, selecting the appropriate word embeddings is a perplexing task since the projected embedding space is not intuitive to humans. In this paper, we explore different approaches for creating distributed word representations. We perform an intrinsic evaluation of several state-of-the-art word embedding methods. Their performance on capturing word similarities is analysed with existing benchmark datasets for word pairs similarities. The research in this paper conducts a correlation analysis between ground truth word similarities and similarities obtained by different word embedding methods.

Richard de Grijs

Longitude determination at sea gained increasing commercial importance in the late Middle Ages, spawned by a commensurate increase in long-distance merchant shipping activity. Prior to the successful development of an accurate marine timepiece in the late-eighteenth century, marine navigators relied predominantly on the Moon for their time and longitude determinations. Lunar eclipses had been used for relative position determinations since Antiquity, but their rare occurrences precludes their routine use as reliable way markers. Measuring lunar distances, using the projected positions on the sky of the Moon and bright reference objects--the Sun or one or more bright stars--became the method of choice. It gained in profile and importance through the British Board of Longitude's endorsement in 1765 of the establishment of a Nautical Almanac. Numerous 'projectors' jumped onto the bandwagon, leading to a proliferation of lunar ephemeris tables. Chronometers became both more affordable and more commonplace by the mid-nineteenth century, signaling the beginning of the end for the lunar distance method as a means to determine one's longitude at sea.

Chen Qu, Liu Yang, Minghui Qiu et al.

Conversational question answering (ConvQA) is a simplified but concrete setting of conversational search. One of its major challenges is to leverage the conversation history to understand and answer the current question. In this work, we propose a novel solution for ConvQA that involves three aspects. First, we propose a positional history answer embedding method to encode conversation history with position information using BERT in a natural way. BERT is a powerful technique for text representation. Second, we design a history attention mechanism (HAM) to conduct a "soft selection" for conversation histories. This method attends to history turns with different weights based on how helpful they are on answering the current question. Third, in addition to handling conversation history, we take advantage of multi-task learning (MTL) to do answer prediction along with another essential conversation task (dialog act prediction) using a uniform model architecture. MTL is able to learn more expressive and generic representations to improve the performance of ConvQA. We demonstrate the effectiveness of our model with extensive experimental evaluations on QuAC, a large-scale ConvQA dataset. We show that position information plays an important role in conversation history modeling. We also visualize the history attention and provide new insights into conversation history understanding.

Thalita Gabínio, Thaysse Ricci, Jeffrey P. Kahn et al.

Abstract Objective To evaluate attachment patterns in subjects with schizophrenia and their relationships to early traumatic events, psychotic symptoms and comorbidities. Methods Twenty patients diagnosed with schizophrenia according to criteria from the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) underwent retrospective symptom assessment and careful assessment of the number and manner of childhood caregiver changes. The Diagnostic Interview for Psychosis and Affective Disorders (DI-PAD) was used to assess symptoms related to schizophrenia (positive and negative symptoms), depression and mania. Anxiety disorder comorbidities were assessed by the Liebowitz Social Anxiety Scale (LSAS), Yale-Brown Obsessions and Compulsions Scale (Y-BOCS) and Panic and Schizophrenia Interview (PaSI). Experience in Close Relationships – Relationship Structures (ECR-RS) and Early Trauma Inventory Self Report-Short Form (ETISR-SF) were used to assess attachment patterns and traumatic history, respectively. Results Moderate and significant correlations between attachment patterns and early trauma showed that greater severity of anxious attachment was predicted by a higher frequency of total early traumas (Spearman ρ = 0.446, p = 0.04), mainly general traumas (ρ = 0.526, p = 0.017; including parental illness and separation, as well as natural disaster and serious accidents). Among the correlations between early trauma and comorbid symptoms, panic attacks occurring before the onset of schizophrenia showed significant and positive correlations with ETISR-SF total scores and the sexual trauma subscale. Conclusion Children with an unstable early emotional life are more vulnerable to the development of psychopathology, such as panic anxiety symptoms. Traumatic events may also predict later schizophrenia.

Zhen Xu, Haroun N. Shah, Raju Misra et al.

Abstract Background Coagulase negative staphylococci (CoNS) are important reservoirs of antibiotic resistance genes and associated mobile genetic elements and are believed to contribute to the emergence of successful methicillin resistant Staphylococcus aureus (MRSA) clones. Although, these bacteria have been linked to various ecological niches, little is known about the dissemination and genetic diversity of antibiotic resistant CoNS in general public settings. Methods Four hundred seventy-nine samples were collected from different non-healthcare/general public settings in various locations (n = 355) and from the hands of volunteers (n = 124) in London UK between April 2013 and Nov 2014. Results Six hundred forty-three staphylococcal isolates belonging to 19 staphylococcal species were identified. Five hundred seventy-two (94%) isolates were resistant to at least one antibiotic, and only 34 isolates were fully susceptible. Sixty-eight (11%) mecA positive staphylococcal isolates were determined in this study. SCCmec types were fully determined for forty-six isolates. Thirteen staphylococci (19%) carried SCCmec V, followed by 8 isolates carrying SCCmec type I (2%), 5 SCCmec type IV (7%), 4 SCCmec type II (6%), 1 SCCmec type III (2%), 1 SCCmec type VI (2%), and 1 SCCmec type VIII (2%). In addition, three isolates harboured a new SCCmec type 1A, which carried combination of class A mec complex and ccr type 1. MLST typing revealed that all S. epidermidis strains possess new MLST types and were assigned the following new sequence types: ST599, ST600, ST600, ST600, ST601, ST602, ST602, ST603, ST604, ST605, ST606, ST607 and ST608. Conclusions The prevalence of antibiotic resistant staphylococci in general public settings demonstrates that antibiotics in the natural environments contribute to the selection of antibiotic resistant microorganisms. The finding of various SCCmec types in non-healthcare associated environments indicates the complexity of SCCmec. We also report on new MLST types that were assigned for all S. epidermidis isolates, which demonstrates the genetic variability of these isolates.

Farida El-Baz Mohamed, Rasha T. Hamza, Nermine H. Amr et al.

Background: Melanocortinergic system represents a known system involved in the central regulation of body weight with the central proopiomelanocortin (POMC) neurons forming a potent anorexigenic network. Polymorphisms in the POMC gene locus are associated with obesity phenotypes. Aim: To assess the contribution of the POMC gene 9-bp insertional polymorphism in the susceptibility to obesity and its relation to body mass index (BMI) and adiposity-related co-morbidities in obese children and adolescents; as well as binge eating behavior. Patients and methods: Fifty obese children and adolescents with simple obesity were screened for Binge Eating Disorder (BED) by The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), they were compared to 50 age, sex and pubertal stage-matched non obese controls. Anthropometric measurements, blood pressure, abdominal ultrasound for fatty liver, measurement of fasting lipid profile, fasting insulin, fasting blood glucose and assessment of POMC gene 9-bp insertional polymorphism were done. Results: Obese patients had significantly higher anthropometric measurements, blood pressure percentiles, fasting glucose, fasting insulin, homeostasis model assessment for insulin resistance (HOMA-IR) and fasting lipid profiles, and higher frequency of occurrence of non alcoholic fatty liver disease and BED. Allelic frequencies of POMC gene 9 bp insertional polymorphism were comparable in patients and controls (p = 0.956). Fasting insulin levels were significantly higher in the heterozygous cases having the polymorphism than in wild homozygous cases; whereas no difference was observed among the controls. Conclusion: This polymorphism was associated with higher fasting insulin levels in the obese patients only. These findings support the hypothesis that the melanocortin pathway may modulate glucose metabolism in obese subjects indicating a possible gene-environment interaction. POMC variant may be involved in the natural history of polygenic obesity, contributing to the link between type 2 diabetes and obesity.

Peter S. Coates, Michael L. Casazza, Brian J. Halstead et al.

Radar systems designed to detect avian activity at airfields are useful in understanding factors that influence the risk of bird and aircraft collisions (bird strikes). We used an avian radar system to measure avian activity at Beale Air Force Base, California, USA, during 2008 and 2009. We conducted a 2-part analysis to examine relationships among avian activity, bird strikes, and meteorological and time-dependent factors. We found that avian activity around the airfield was greater at times when bird strikes occurred than on average using a permutation resampling technique. Second, we developed generalized linear mixed models of an avian activity index (AAI). Variation in AAI was first explained by seasons that were based on average migration dates of birds at the study area. We then modeled AAI by those seasons to further explain variation by meteorological factors and daily light levels within a 24- hour period. In general, avian activity increased with decreased temperature, wind, visibility, precipitation, and increased humidity and cloud cover. These effects differed by season. For example, during the spring bird migration period, most avian activity occurred before sunrise at twilight hours on clear days with low winds, whereas during fall migration, substantial activity occurred after sunrise, and birds generally were more active at lower temperatures. We report parameter estimates (i.e., constants and coefficients) averaged across models and a relatively simple calculation for safety officers and wildlife managers to predict AAI and the relative risk of bird strike based on time, date, and meteorological values. We validated model predictability and assessed model fi t. These analyses will be useful for general inference of avian activity and risk assessment efforts. Further investigation and ongoing data collection will refine these inference models and improve our understanding of factors that influence avian activity, which is necessary to inform management decisions aimed at reducing risk of bird strikes.

Mark C Ladd, Mark C Ladd, Andrew A Shantz et al.

AbstractCoral restoration is gaining traction as a viable strategy to help restore degraded reefs. While the nascent field of coral restoration has rapidly progressed in the past decade, significant knowledge gaps remain regarding the drivers of restoration success that may impede our ability to effectively restore coral reef communities. Here, we conducted a field experiment to investigate the influence of coral density on the growth, habitat production, and survival of corals outplanted for restoration. We used nursery-raised colonies of Acropora cervicornis to experimentally establish populations of corals with either 3, 6, 12, or 24 corals within 4m2 plots, generating a gradient of coral densities ranging from 0.75 corals m-2 to 12 corals m-2. After 13 months we found that density had a significant effect on the growth, habitat production, and survivorship of restored corals. We found that coral survivorship increased as colony density decreased. Importantly, the signal of density dependent effects was context dependent. Our data suggest that positive density dependent effects influenced habitat production at densities of 3 corals m-2, but further increases in density resulted in negative density dependent effects with decreasing growth and survivorship of corals. These findings highlight the importance of density dependence for coral restoration planning and demonstrate the need to evaluate the influence of density for other coral species used for restoration. Further work focused on the mechanisms causing density dependence such as increased herbivory, rapid disease transmission, or altered predation rates are important next steps to advance our ability to effectively restore coral reefs.