Articles tagged with Databases
A supersized database of over 45,000 traits tracks the behavior, distribution, and life patterns of fruit eaters and birds in Central and South America. The Frugivoria database provides crucial insights into their role in maintaining forest composition and health.
The Adaptive Spatio-Temporal Attention Neural Network (ASTANN) is proposed for cross-database micro-expression recognition. It extracts optical flow information and combines it with facial images to generate new representations, which are then processed by a deep neural network with spatiotemporal attention mechanisms.
A study presented at the American College of Cardiology's Care of the Athletic Heart conference found that only 50% of athletes surveyed reported knowing what sudden cardiac arrest is or being concerned about it during play. The researchers identified 46 cases of sports-related cardiac arrests between 1984 and 2022 involving CPR, with ...
Researchers developed a method to detect forest disturbance by combining strengths from time-series algorithms and 2-date detection methods. The new technique facilitates more effective forest management and policy.
Online radiologists choose studies based on financial attractiveness, leading to delays in high-priority cases. This study found that expedited priority class contained the highest percentage of delayed studies.
Researchers develop a new composite strategy to produce clean Landsat images with reduced cloud and shadow errors. The approach uses an algorithm to select pixels from multiple dates to create a virtual median-value point, detecting and replacing clouds and shadows in the process.
The study revealed lower age-standardized rate of NENs incidence in China (1.14 per 100,000) compared to the USA (6.26 per 100,000). The most common sites for primary NEN tumors progressed were found to be the pancreas, stomach, lungs, and rectum.
GPMeta accelerates pathogen detection in metagenomic sequencing (mNGS) tests, achieving higher accuracy while significantly reducing processing time. The approach uses a succinct hash index scheme and multi-GPU support to handle massive data sets.
The study highlights the importance of language documentation and revitalization to preserve human communication, culture, and cognition. Grambank reveals that language loss is occurring unevenly across major linguistic regions, with indigenous languages in northeast South America, Alaska, and northern Australia at highest risk.
The Grambank database provides an unprecedented level of detail on language structure, showcasing the diversity of human languages. Researchers found that languages exhibit greater similarity to their common ancestors than those they are in contact with, highlighting the importance of genealogical constraints on linguistic diversity.
Human macrophages use Siglec-14 receptors to recognize and engulf carbon nanotubes, leading to inflammation. The discovery could pave the way for developing safer carbon nanotubes and therapies to prevent inflammatory diseases.
A novel database, CycPeptMPDB, has been created to facilitate the development of drugs based on cyclic peptides. The database contains information on thousands of cyclic peptides and their membrane permeability values, enabling researchers to select candidate peptides that can penetrate human cell membranes.
A new Rutgers study finds that childhood asthma diagnoses decreased by 52% in the US during the first year of the pandemic compared to previous years. Researchers attribute this decline to fewer colds and the practice of wearing masks, which may have reduced the risk of asthma triggers.
A large-scale study found that diagnostic errors in neuroradiology were associated with longer interpretation times and higher shift volumes. The study also revealed a significant increase in diagnostic errors during weekend work, highlighting the need for targeted quality improvement interventions.
Researchers Paul Byrne and Rebecca Hahn have compiled a global catalog of 85,000 volcanoes on Venus, providing the most comprehensive understanding of the planet's volcanic properties. The dataset includes detailed analyses of volcano distribution, size, and clustering, which will aid in locating future active lava flows.
A meta-analysis of commercially available STI tests found vaginal swabs to be more sensitive than urine specimens in detecting chlamydia, gonorrhea, and trichomonas. The study supports the CDC's recommendation for vaginal swab testing as the optimal sample type for women.
A new database has been launched to provide accurate and consistent data on minority-serving institutions (MSIs) in the US. The MSI Data Project offers dashboards with data on institutional characteristics, enrollment, and graduation metrics for MSIs from 2017-2021.
The Fermi Gamma-ray Space Telescope has captured a dynamic animation of the gamma-ray sky, revealing frenzied activity over nearly 15 years. The data, now publicly available, includes records of source brightness changes and sheds light on blazars and multimessenger astronomy.
A study of US newspaper articles found that lung cancer screening was generally positively covered between 2010 and 2022. However, crucial aspects such as enrollment criteria and cost issues were frequently omitted, highlighting a need for radiologists to take an active role in media coverage.
A meta-analysis of 34 studies found a significant association between autism spectrum disorder (ASD) and increased risks of developing diabetes, dyslipidemia, and heart disease. Children with ASD were more likely to develop these metabolic complications, prompting clinicians to monitor them closely.
A one-year case-control study found increased rates of adverse outcomes among adults with long COVID compared to those without COVID-19, highlighting the need for continued monitoring, particularly in cardiovascular and pulmonary management. The study's findings underscore the importance of addressing at-risk individuals.
A case series study of 373,000 patients found that time from diagnosis to surgery over eight weeks was associated with worse overall survival. This delay may be linked to disadvantageous social determinants of health, suggesting the importance of timely surgical interventions in breast cancer care.
Researchers from Hiroshima Shudo University and the University of Tokyo have successfully identified species of deep-sea brittle stars using a novel metabarcoding approach. This method analyzes environmental DNA released from marine invertebrates, enabling efficient and cost-effective monitoring of biodiversity.
A Chinese Medical Journal study analyzed the temporal and spatial distribution of epilepsy across China, finding significant increases in incidence and prevalence rates between 1990 and 2019. The study also showed a general decrease in age-standardized DALY rates with increasing socio-demographic index.
Research suggests that rapid ocean warming could force plankton to move away from the tropics, negatively affecting marine food chains. The study used microfossils to track the history of zooplankton and found that tropical plankton populations lived in waters more than 2,000 miles from their current location 8 million years ago.
The new grant enables LJI to lead the Human Immunology Project Consortium Data Coordinating Center, providing access to human immunoprofiling data from over 11,000 participants. This will fuel scientific collaboration in understanding immune responses to viruses, autoimmune diseases, and more.
Researchers found that some states, such as Ohio and Nevada, have the highest per-capita visits to emergency departments for mental health conditions, while others, like Colorado and West Virginia, have the lowest. Heavy reliance on emergency departments is problematic due to a lack of suitable care in these areas.
A systematic review and meta-analysis found that MRI-based surveillance after surgical treatment can detect clinically occult local recurrences, potentially improving patient outcomes. The study included 19 studies and showed a significant association between high-intensity surveillance and the detection of local recurrences.
A new study published in the Journal of the American Heart Association found that people hospitalized for sepsis are at a higher risk of heart failure and rehospitalization within 12 years. The researchers analyzed data from over 2 million adults who survived non-surgical hospitalizations between 2009 and 2019.
Researchers found that academic emigration rates decrease with economic development until a certain GDP threshold, then increase. This challenges the assumption that economic growth leads to brain drain in low- and middle-income countries.
Disparities in access to pediatric ophthalmological care have increased over the past 15 years, with lower socioeconomic status being a significant factor. Online sources can lead to inaccurate databases, highlighting the need for accurate publicly available information.
A nationwide study led by Harvard researchers found that patients in health systems receive marginally better care but report slightly better experiences, while care comes at a much higher price. The analysis suggests that health systems have not realized their potential for better care at equal or lower cost.
A UTHSC team developed a unique community-focused COVID-19 data registry, MEMPHI-SYS, to guide public health policies and interventions nationwide. The registry collects demographic information, geographic locations, medical history, and risk factors, providing insights into the spread and presentation of COVID.
Researchers successfully applied AlphaFold AI to an end-to-end platform, discovering a novel target and developing a potent hit molecule for liver cancer. The study demonstrates the potential of AI-powered drug discovery to accelerate treatment development.
Recent national data analyzed by leading cardiology and cardiothoracic surgical researchers found that the rate of successful repair has reached over 90% in the US, with an extremely low risk of mortality across nearly all age ranges. A novel risk model was developed to predict 30-day outcomes based on patient health conditions.
A team of researchers from Chung-Ang University evaluated three different MALDI-TOF MS approaches used in domestic clinical settings for the identification of molds. They compared the performance and diagnostic accuracy of the Bruker Biotyper, ASTA MicroIDSys, and Vitek MS instruments.
Researchers from North Carolina State University identified a fundamental flaw in a commonly used pandemic model that causes it to severely underestimate disease spread. By modifying parts of an existing model, they substantially improved its accuracy when compared to real-world data on the COVID-19 Omicron variant.
A new cancer protein profile database has been created by KTH Royal Institute of Technology, mapping 1,463 proteins to 12 different cancer types. This database allows for the identification of individual cancer types using just a drop of blood, providing a promising new approach to cancer prediction and diagnosis.
A new open-access Raman spectral library enables scientists to detect molecular 'fingerprints' of particles and better trace sources of ocean plastic pollution. The database adds 42 polymer types, including those from non-plastic particles, to improve accuracy.
The Kessler Foundation team, led by Dr. Amanda Botticello, has received a $4.5 million federal grant to advance spinal cord injury research. The goal of the five-year project is to build a database resource to identify neighborhood factors that shape independent community living after spinal cord injury.
A nationwide retrospective study showed that adjuvant chemotherapy after neo-adjuvant chemotherapy and surgery significantly improved overall survival in patients with pancreatic adenocarcinoma, regardless of lymph node status or resection margins. The study included nearly 900 patients and was published in JAMA Oncology.
Researchers at MIT have developed a scheme for private information retrieval that is about 30 times faster than other comparable methods. The technique enables users to search an online database without revealing their query to the server, with potential applications in private communication and targeted advertising.
A new study maps the global landscape of antimicrobial resistance, revealing surprising transmissions in Sub-Saharan Africa and highlighting the need for tailored strategies to combat resistance. The research, which analyzed sewage samples from 243 cities in 101 countries, found that resistance genes are more frequently transmitted acr...
Researchers found that buprenorphine use was associated with better outcomes for the baby, including lower risk of preterm birth, small size for gestational age, and low birth weight. The study suggests increasing access to buprenorphine treatment among pregnant individuals with opioid-use disorder.
A new study by Rutgers researchers found that young people treated for sleep disorders with benzodiazepines like Xanax may be at a higher risk of overdose. The study examined over 90,000 newly prescribed benzodiazepine patients and found an increased risk of overdose compared to other prescription sleep medications.
Researchers developed SDCBench, a benchmark suite that evaluates workload co-location in datacenters, enabling cloud tenants to understand performance isolation ability and choose their best-fitted cloud services. The tool also helps cloud providers improve service quality to increase revenue.
The 'Nature's Envelope' is a simple model that depicts the scope and scale of biology by compiling information about all living organisms' processes. The model plots sizes of participants and durations of processes on a logarithmic grid, revealing broad S-shaped envelope encompassing half of decadal blocks.
A novel multi-modal image retrieval system, DenseBert4Ret, has been developed by researchers from Gwangju Institute of Science and Technology (GIST) using deep learning algorithms. The system outperforms state-of-the-art models in retrieving images based on both image and text features.
The BiCIKL project has reached its halfway stage, launching a European community of key research infrastructures and stakeholders in biodiversity and life sciences. The FAIR Data Place online platform aims to provide scientists with access to all types of biodiversity data 'at their fingertips'.
Research found high levels of sweet and fruit-flavour chemicals in 'tobacco-flavoured' e-cigarette liquids, particularly fruity and caramellic flavour chemicals. The study suggests manufacturers are getting around regulations by using these flavour chemicals in products marketed as 'tobacco-flavoured', raising concerns about their safety.
The Global Jukebox, an online tool for exploring music and performing arts from around the world, has made its dataset and data available to the public. The database includes 5,776 recordings representing 1,026 societies, with detailed musical style categorization data and additional features such as breath management and instrumentation.
Researchers found that structural racism and insurance barriers limit access to advanced epilepsy care for minority groups in New Jersey. Black patients with private insurance and Medicaid had the lowest EMU admission rates relative to emergency room visits.
Researchers at KAUST developed an inverse mixture-design approach using machine learning to create high-performance transport fuels. The model accurately predicted fuel properties and identified suitable blends, offering a promising solution to reduce greenhouse gas emissions.
Mount Sinai researchers created a cloud-based digital framework, Employee Health COVID-19 REDCap Registry, to track employee health data and mitigate COVID-19 spread. The platform reduced case follow-up times from days to hours and helped identify occupational and non-occupational risk factors.
Dr. Daijiang Li is building Phenobase, a global database on plant phenology using AI and machine learning to extract information from millions of images and existing records.
A new platform has been created using 214,000 microbiome samples to track antibiotic-resistant bacteria globally. The data can be used to tailor guidelines on combating resistance in different regions.
A new AI algorithm, SISH, uses self-supervised learning to find similar cases in large pathology image repositories, assisting with the diagnosis of rare diseases. The algorithm outperforms other methods in retrieving interpretable disease subtype information from vast databases, even at large scales.
Researchers aim to create a unified database network for battery data, facilitating AI analysis and predictions. The Battery Data Genome will collect data across the entire battery lifecycle, from discovery to deployment, with uniform standards for metadata.
A study by the BMJ found that less than a third of FDA regulatory actions are backed by published research findings or public assessments. The researchers analyzed drug safety signals from 2008 to 2019 and found that most regulatory actions were based on changes to drug labeling, with only about 30% corroborated by relevant studies.
Researchers developed a tool that encodes patient data as DNA sequences to link health databases accurately. The platform uses BLAST and machine learning algorithms to integrate data from multiple administrative databases, overcoming typographical errors and inconsistencies.