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117 results for “Boston”
Microbial, Plant, and Soil Impacts on Soil Nutrient Cycling in Harvard Forest and Greater Boston 2021-2022
Microbes are the driving force behind nutrient cycling within soils, secreting enzymes necessary to break down organic matter, immobilizing nutrients and C, or transferring nutrients to plant hosts. Even though nutrients would almost never move through ecosystems without microbes, we know little about how their composition and activity is related to ecosystem nutrient cycling, and their importance relative to plant and soil abiotic factors. In this study, we sought to determine which commonly measured soil microbial community characteristics best explain soil N and P cycling, and the relative contributions of microbial, plant, and abiotic factors in explaining these processes.
Environmental Data for Soil, Leaf, and Root samples Boston Street Trees and Massachusetts Rural and Urban Forests in Summer 2021
This dataset provides detailed environmental and tree-level data and metadata for over 850 samples collected from 91 trees across an urban-to-rural gradient in Massachusetts. The dataset captures key variables characterizing urban environmental gradients, including soil moisture, pH, temperature, and nitrogen availability. Tree-level attributes include species identification, diameter at breast height (DBH), and growth rate based on previous tree census data. Geographic coordinates and site-specific context (urban forest, rural forest, street tree, forest edge, forest interior) are included to enable spatial analyses. The microbial sequence data associated with this environmental metadata can be found in the NCBI SRA under BioProject accession number PRJNA1297772.
Monthly mean sea level data (1921-2018) relative to NAVD88 for Boston, Massachusetts, NOAA/NOS
Monthly sea level data for NOAA/NOS station 8443970, Boston, Massachusetts. The tide station is located on the right side of the U.S. Coast Guard Building adjacent to Northern Avenue Bridge. NOAA/NOS Center for Operational Oceanographic Products and Services (CO-OPS)
From Boston to Eden - or how to get systems that are really autonomous and sufficiently intelligent to survive in their niche
<p><a href="https://www.researchgate.net/project/Theoretical-artificial-intelligence/update/5e5f931a3843b0499fec8f6f?_iepl%5BviewId%5D=FMNsczWoobvAHwiOMdftISgB&_iepl%5Bcontexts%5D%5B0%5D=projectUpdatesLog&_iepl%5BinteractionType%5D=projectUpdateDetailClickThrough">From Boston to Eden - or how to get systems that are really autonomous and sufficiently intelligent to survive in their niche</a></p> <p>[lecture for the Dept. of AI, University of Groningen, Tuesday, March 3rd, 2020]</p> <p>As impressive as the robots of the Boston Dynamics company are (no AI involved) and as impressive the many results of deep learning are (no AI involved, either), the goal of creating autonomous, intelligent machines is as far away as it ever was. <br> In this presentation, I will give a brief overview of several deep-learning projects in our group. As a next step I will try to indicate <br> what may be missing, as regards 'real' AI. We may need a closer look at biological systems, i.e., the brain of animals. There exists a wide gap between the control systems at the low level of reflexive movement and the equilibria that need to be maintained ('Boston') versus the higher levels of processing, up to the levels of cognition and reasoning, which are very much upstairs ('Eden'). The missing middleware layer should not be underestimated: It contains the brain stem, up to the thalamus in animals and humans. <br> It corresponds to the 300-million year period before the 200 million years period where the neocortex was present. <br> What is this middleware doing? The conclusion may be that there is no autonomy without self protection, possible due to the presence of a separate and specialized valuation network that determines probability times utility (p*U), similar to what brain stem, midbrain and amygdala are doing in animals.</p>
Field data for seasonal synoptic sampling of 100 urban streams in Boston, Massachusetts (USA) from 2021-2022
This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Boston, Massachusetts (USA) metropolitan area. Field collection took place during four synoptic sampling events (September 2021, November 2021, April 2022, and July 2022) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
High-frequency water quality data for three urban streams in Boston, MA (USA), 2021-2022
This dataset contains high-frequency water quality data for three urban stream locations in the great Boston, Massachusetts metropolitan area. Multiparameter sondes with sensors to measure temperature, pH, specific conductivity, optical dissolved oxygen (DO), turbidity, colored dissolved organic matter (CDOM), and optical brighteners (OB) were deployed from 23 November 2021 to 20 December 2022. Data were collected at 15-minute intervals.
Dissolved organic matter characterization for seasonal synoptic sampling of 100 urban streams in Boston, Massachusetts (USA) from 2021-2022
This dataset contains dissolved organic matter (DOM) characteristics from surface water samples collected at 100 urban stream locations in the greater Boston, Massachusetts metropolitan area. Samples were collected four times (September 2021, November 2021, April 2022, and July 2022) to capture spatial and seasonal variation in DOM characteristics. Fluorescent optical properties were measured on filtered water samples to understand the chemical composition of DOM. Excitation-Emission Matrices (EEMs) were measured using a Horiba Aqualog spectrometer. DOM characteristics were quantified using both standard fluorescence and absorbance metrics as well as through parallel factor (PARAFAC) analysis. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Dissolved organic carbon concentrations for seasonal synoptic sampling of 100 urban streams in Boston, Massachusetts (USA) from 2021-2022
This dataset contains dissolved organic carbon (DOC) concentrations from surface water samples collected at 100 urban stream locations in the greater Boston, Massachusetts metropolitan area. Samples were collected four times (September 2021, November 2021, April 2022, and July 2022) to capture spatial and seasonal variation in DOC concentrations. Filtered stream samples were analyzed for dissolved organic carbon concentration. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Data from: Maps made with smartphones highlight lower noise pollution during COVID-19 pandemic lockdown at four locations in Boston
<p>Noise pollution in cities has major negative effects on the health of both humans and wildlife. Using iPhones, we collected sound-level data at hundreds of locations in four areas of Boston, Massachusetts (USA) before, during, and after the fall 2020 pandemic lockdown, during which most people were required to remain at home. These spatially dispersed measurements allowed us to make detailed maps of noise pollution that are not possible when using standard fixed sound equipment. The four sites were: the Boston University campus (which sits between two highways), the Fenway/Longwood area (which includes an urban park and several hospitals), Harvard Square (home of Harvard University), and East Boston (a residential area near Logan Airport). Across all four sites, sound levels averaged 6.4 dB lower during the pandemic lockdown than after. Fewer high noise measurements occurred during lockdown as well. The resulting sound maps highlight noisy locations such as traffic intersections and quiet locations such as parks. This project demonstrates that changes in human activity can reduce noise pollution and that simple smartphone technology can be used to make highly detailed maps of noise pollution that identify sources of high sound levels potentially harmful to humans in urban environments.</p>
News data for studying media exposure to the Boston Marathon bombings
<p>The news data sets released here have been used to study the relationship between media exposure and individuals' threat perception. Media exposure to mass violence has been shown to have a detrimental impact on people's threat perception and mental wellness, but little has been done to explore how exposure to different news content may impact mental health in people's everyday lives. In our study, we empirically test how emotionally potent media coverage of a real-world threat, namely, the Boston Marathon bombings occurred in 2013, alters threat perception of the community members over the first and the third anniversaries (in 2014 and 2016).</p> <p>The data were collected using a wave-based longitudinal design. There are two data sets, and each covers three waves:</p> <ul> <li>Dataset (I) -- news coverage before (Wave 1), during (Wave 2), and after (Wave 3) 2014 anniversary</li> <li>Dataset (II) -- news coverage before (Wave 1), during (Wave 2), and after (Wave 3) 2016 anniversary</li> </ul> <p>The collection procedure was informed by our survey study. Based on the survey completed by our subjects, we identified the four most frequent news outlets in the response: Metro (MT), New York Times (NY), Boston Globe (BG), and Boston Herald (BH). Other outlets, such as USA Today and Wall Street Journal, were reported by less than ten respondents. Therefore, our data collection focused on the news published by the four most frequent outlets.</p> <p>The data sets include the metadata of the news coverage over the aforementioned six waves. The raw content of the news stories was removed to respect the copyright owners.</p> <p><strong>Summary of the data collection procedure </strong></p> <p>We used news aggregators including Google and Yahoo news, to retrieve news articles published by the four outlets on a daily basis. We first collected the URLs of the news articles from the news aggregators and retrieved and parsed the news content using an HTML parser. In total, we collected over 38.5K and 54.1K news articles in dataset I and II, respectively.</p> <p>There are six files; each correspond to news coverage from the outlets in each wave. In these files, each line contains four columns: outlet, time, title, url which indicate the outlet of each news article, the time of publishing, the title of the article, and the URL to the article.</p> <p>We are making the data sets available for academic researchers and public use, to enable the discovery of new insights and development of better techniques to improve crisis communication and mental wellness.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 4. Intelligent robots (accessed 01.11.2017). 4.1. Erica, a humanoid robot (https://www.tech-review.com/erica-is-the-latest-japanese-robot-with-human-appearance.html). 4.2. Atlas, a bipedal humanoid robot developed by Boston Dynamics (https://en.wikipedia.org/wiki/Atlas_(robot))
<p>One of the most highly quoted and interesting definitions of machine intelligence was presented by Alan Turing (1950). Turing considered a computing system intelligent if a human assessor could not decide the nature of the system (being human or artificial) based on questions asked from a room hidden from a human assessor. Until recently there were performed different discussions and comments on the Turing test. Hernández-Orallo (2000) presents an interesting study related to the Turing Test. Dowe and Hajek, (1998) propose a computational extension of the Turing Test. The design and development of intelligent systems are historically very recent. But, even if the advance of hardware and software is very fast, it will take a longer time until the artificial computing systems will attain a similar intelligence with the humans. Based on this fact, we consider that is not appropriate to formulate the problem of the direct comparison at a general level of human intelligence with the machine intelligence. Different definitions were proposed for the intelligence of the agents (Russell, & Norvig, 2003; Iantovics, & Zamfirescu, 2013). Many authors (Russell, & Norvig, 2003; Iantovics, 2005) argue that the intelligence of the agents cannot be defined universally. The impossibility to give a universal definition to the human intelligence is based mostly on the enormous complexity of the human brain and complexity of the human thinking and decision making. Similarly, we may consider the impossibility of universal definition of intelligence of the agents based on the very large variety (by type and complexity) of intelligent agents. The machine intelligence frequently is defined based on different abilities such as (Iantovics, 2005; Sharkey, 2006): autonomous learning, self-adaptation, and evolution. These principles of considering the intelligence are inspired by biological life forms able to learn autonomously during their life cycle, to adapt to the environment and to evolve during more generations. We would like to outline that not all the designed agents are intelligent. There is not a required property of an agent to be intelligent.</p>
Boston Fingerprints 2014 - Images
<p>SPARC Project: BostonFingerprints_2014<br> Principle Investigators: Joseph Bagley and Jennifer Poulsen<br> Contributors: Rachel Opitz (SPARC)</p> <p>Joseph Bagley and Jennifer Poulsen (Boston Landmarks Commission) and Rachel Opitz (SPARC researcher) used a structured light scanner to create detailed 3D models of ceramic artifacts featuring finger and hand prints from the Parker-Harris Pottery Site and Three Cranes tavern Site in Charlestown, Massachusetts. These sites were excavated in the early- and mid-1980s in advance of Boston’s Big Dig as part of the Central Artery North Area, and are now listed in the National Register of Historic Places as part of the City Square Archaeological District. The Parker-Harris Pottery Site was the location of early coarse earthenware (redware) ceramic production in Boston. It was destroyed on June 17, 1775 by British troops who burned Charlestown as part of the Battle of Bunker Hill. The Three Cranes Tavern was founded in the former Great House of Governor John Winthrop in the center of Charlestown, only 100 meters from the Parker-Harris property. The tavern passed through a series of owners resulting in a near-continual use of the property as a Tavern for 140 years. During archaeological investigation numerous privies and features were identified with tightly-dated ceramic assemblages, including numerous coarse earthenwares with the distinct decorative elements of the Parker or Harris pottery. This project aimed to establish that biometric identifiers directly connect pottery from consumption sites to production sites when there are known sales between production and consumption sites, tightly dated deposits that limit association of pottery to specific potters, and a limited number of potters producing these vessels. This type of research could establish previously-unknown associations and commercial networks of domestic redware potters across the eastern United States. With data as unique and personal as a fingerprint, the results of this analysis brings a personal and evocative light to these significant assemblages, allowing the public to appreciate these forgotten and sometimes nameless potters through the intimate association of their hands.</p> <p>This project includes raw and processed data captured using a Breuckmann Smartscan HE structured light scanner with 250mm lenses using Optocat 2013 software. Sixty ceramics were scanned - 30 from Parker-Harris Kiln and 30 from Three Cranes Tavern.</p> <p>This upload contains .pdf files of each ceramic scanned, with fingerprints marked clearly on the sherd. Parker-Harris ceramics are noted as 'ph' while Three Cranes ceramics are noted as 'tc'.</p> <p>Raw data for each ceramic can be found at: https://zenodo.org/deposit/1239541<br> Processed meshes of each ceramic can be found at: https://zenodo.org/deposit/1237528<br> <br> Project Name: Boston Fingerprints<br> Survey Location: City of Boston Archaeology Laboratory<br> Survey Dates: 20 - 24 October 2014<br> Scanner Details: Breuckmann Smartscan HE structured light scanner - 250mm lenses<br> Operator Name: Rachel Opitz<br> Calibration Files: BostonFingerprints2014_RawData_Calib2<br> Total Number of Scans: 194<br> Final Datasets for Archive: Raw scan data from Optocat<br> Images from Survey: 388<br> Software: Optocat 2013</p>
Boston Fingerprints 2014 - Raw Data
<p>SPARC Project: BostonFingerprints_2014<br> Principle Investigators: Joseph Bagley and Jennifer Poulsen<br> Contributors: Rachel Opitz (SPARC)</p> <p>Joseph Bagley and Jennifer Poulsen (Boston Landmarks Commission) and Rachel Opitz (SPARC researcher) used a structured light scanner to create detailed 3D models of ceramic artifacts featuring finger and hand prints from the Parker-Harris Pottery Site and Three Cranes tavern Site in Charlestown, Massachusetts. These sites were excavated in the early- and mid-1980s in advance of Boston’s Big Dig as part of the Central Artery North Area, and are now listed in the National Register of Historic Places as part of the City Square Archaeological District. The Parker-Harris Pottery Site was the location of early coarse earthenware (redware) ceramic production in Boston. It was destroyed on June 17, 1775 by British troops who burned Charlestown as part of the Battle of Bunker Hill. The Three Cranes Tavern was founded in the former Great House of Governor John Winthrop in the center of Charlestown, only 100 meters from the Parker-Harris property. The tavern passed through a series of owners resulting in a near-continual use of the property as a Tavern for 140 years. During archaeological investigation numerous privies and features were identified with tightly-dated ceramic assemblages, including numerous coarse earthenwares with the distinct decorative elements of the Parker or Harris pottery. This project aimed to establish that biometric identifiers directly connect pottery from consumption sites to production sites when there are known sales between production and consumption sites, tightly dated deposits that limit association of pottery to specific potters, and a limited number of potters producing these vessels. This type of research could establish previously-unknown associations and commercial networks of domestic redware potters across the eastern United States. With data as unique and personal as a fingerprint, the results of this analysis brings a personal and evocative light to these significant assemblages, allowing the public to appreciate these forgotten and sometimes nameless potters through the intimate association of their hands.</p> <p>This project includes raw and processed data captured using a Breuckmann Smartscan HE structured light scanner with 250mm lenses using Optocat 2013 software. Sixty ceramics were scanned - 30 from Parker-Harris Kiln and 30 from Three Cranes Tavern.</p> <p>This upload contains the raw Optocat 2013 data for each ceramic scanned. Parker-Harris ceramics are noted as 'ph' while Three Cranes ceramics are noted as 'tc'. Some ceramics have more than one set of raw data due to either having fingerprints on multiple sides (marked as 'sideA' or 'sideB') or to testing different parameters (noted as 'parameter1' or 'parameter2'). Each .zip file contains the complete raw data for each object as well as a FileList.txt file indexing all files that are included in the .zip file. <br> <br> Project Name: Boston Fingerprints<br> Survey Location: City of Boston Archaeology Laboratory<br> Survey Dates: 20 - 24 October 2014<br> Scanner Details: Breuckmann Smartscan HE structured light scanner - 250mm lenses<br> Operator Name: Rachel Opitz<br> Calibration Files: BostonFingerprints2014_RawData_Calib2<br> Total Number of Scans: 194<br> Final Datasets for Archive: Raw scan data from Optocat<br> Images from Survey: 388<br> Software: Optocat 2013</p>
Move Together Boston Feasibility Pilot (Sit Less, Move More App for Black Breast Cancer Survivors & At-Risk Relatives)
ClinicalTrials.gov study NCT05011279. IPD Sharing: YES. Countries: 1. Publications: 1.
Vision Restoration With a Collagen Crosslinked Boston Keratoprosthesis Unit
ClinicalTrials.gov study NCT02863809. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Maps made with smartphones highlight lower noise pollution during COVID-19 pandemic lockdown at four locations in Boston
Open the record for dataset details and reuse information.
Cântaro Boston 98.932
O seguinte modelo 3D foi produzido com base no artefato Boston 98.932 -localizado no Museu de Belas Artes de Boston - por Vander Gabriel Camargo, estudante de História da UFRGS e integrante do CTA (Centro de Tecnologia Acadêmica), em outubro de 2020. Modelagem do objeto para fins didáticos, uso em salas de aula. Dados do objeto original: - Proveniência: Atenas, Ática, Grécia - Artístas: Hieron (ceramista) e pintor de Anfitrite (iconografia) - Técnica: Figuras Vermelhas - Data: 470 - 460 a.C. - Dimenções: 26.5 x 28 cm - Localização atual: EUA, Massachusetts, Boston, MFA: 98.932. - Beazley Archive Pottery Database: 205038 (https://www.beazley.ox.ac.uk/XDB/ASP/recordDetails.asp?id=%7B5B430A85-F94F-4CB9-AADB-FEBDEA9590F3%7D&noResults=1&recordCount=1&databaseID=%7B12FC52A7-0E32-4A81-9FFA-C8C6CF430677%7D&search=%20%7BAND%7D%20205038) Licenças: Atribuição ao autor do modelo 3D; e imagens conforme © Museum of Fine Arts, termos de uso do MFA (disponível em https://www.mfa.org/about/terms-of-use). Source: Objaverse 1.0 / Sketchfab
Boston Common Pipe
Recovered from an archaeological dig on Boston Common in the 1980's, this unusually small clay pipe bowl may have been used as a novelty, toy, or as a way to smoke extremely small amounts of tobacco! Dating to the late 18th to early 19th century, it was likely lost by one of the many visitors to the Common, which was first established in 1634 and remains an active center for the City of Boston.Scanned by Brian Schools. Source: Objaverse 1.0 / Sketchfab
WSPR raw .wav baseband data received at Boston University
<p>WSPR stations received at W1BUR Boston University ham radio station using 20m end-fed dipole or broadband HF dipole.</p>
Boston 98.932
O seguinte modelo 3D foi produzido com base no artefato Boston 98.932 -localizado no Museu de Belas Artes de Boston - por Vander Gabriel Camargo, estudante de História da UFRGS, integrante do laboratório CTA (Centro de Tecnologia Acadêmica) e **Ergane**, em outubro de 2020. Dados do objeto original: - Proveniência: Atenas, Ática, Grécia - Artístas: Hieron (ceramista) e pintor de Anfitrite (iconografia) - Técnica: Figuras Vermelhas - Data: 470 - 460 a.C. - Dimenções: 26.5 x 28 cm - Localização atual: EUA, Massachusetts, Boston, MFA: 98.932. - Beazley Archive Pottery Database: 205038 (https://www.beazley.ox.ac.uk/XDB/ASP/recordDetails.asp?id=%7B5B430A85-F94F-4CB9-AADB-FEBDEA9590F3%7D&noResults=1&recordCount=1&databaseID=%7B12FC52A7-0E32-4A81-9FFA-C8C6CF430677%7D&search=%20%7BAND%7D%20205038) **Licenças**: Atribuição ao autor do modelo 3D; e imagens conforme © Museum of Fine Arts, termos de uso do MFA (disponível em https://www.mfa.org/about/terms-of-use). Source: Objaverse 1.0 / Sketchfab
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