Crowd source

The COVID-19 pandemic disrupted regular global activities in every possible way. This pandemic, caused by the transmission of the infectious Coronavirus, is characterized by main symptoms such as fever, fatigue, cough, and loss of smell. A current key focus of the scientific community is to develop automated methods that can effectively identify COVID-19 patients and are also adaptable for foreseen future virus outbreaks. To classify COVID-19 suspects, it is required to use contactless automatic measurements of more than one symptom...

Learning from crowds describes that the annotations of training data are obtained with crowd-sourcing services. Multiple annotators each complete their own small part of the annotations, where labeling mistakes that depend on annotators occur frequently. Modeling the label-noise generation process by the noise transition matrix is a powerful tool to tackle the label noise. In real-world crowd-sourcing scenarios, noise transition matrices are both annotator- and instance-dependent. However, due to the high complexity of annotator- and instance-dependent transition matrices (AIDTM), annotation sparsity, which means each annotator only labels a tiny part of instances, makes modeling AIDTM very challenging...

Industrial land is currently the main carrier and important source of global carbon emissions, and as the world's largest developing country, China's large-scale and diversified industrial land supply has made it the world's largest carbon emitter. Therefore, researching the impact of different supply methods of industrial land on carbon emissions and its impact paths in China can help provide a reference for other countries to reduce carbon emissions from the perspective of urban industrial land management, which is of great significance for effectively promoting global carbon reduction...

This study aims to automate the segmentation of retinal arterioles and venules (A/V) from digital fundus images (DFI), as changes in the spatial distribution of retinal microvasculature are indicative of cardiovascular diseases, positioning the eyes as windows to cardiovascular health.

Approach: We utilized active learning to create a new DFI dataset with 240 crowd-sourced manual A/V segmentations performed by 15 medical students and reviewed by an ophthalmologist. We then developed LUNet, a novel deep learning architecture optimized for high-resolution A/V segmentation...

The crowded bacterial cytoplasm is comprised of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial Genetically Encoded Multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (-2160 to +1800 e) in live Escherichia coli cells...

OBJECTIVE: Artificial intelligence (AI)-based decision support systems (DSS) are utilized in medicine but underlying decision-making processes are usually unknown. Explainable AI (xAI) techniques provide insight into DSS, but little is known on how to design xAI for clinicians. Here we investigate the impact of various xAI techniques on a clinician's interaction with an AI-based DSS in decision-making tasks as compared to a general population. METHODS: We conducted a randomized, blinded study in which members of the Child Neurology Society and American Academy of Neurology were compared to a general population...

This study takes Shanghai's restaurants as a case study of urban soft infrastructure, employing big data sets from third-party website platforms for multi-source data fusion, to deeply analyze the impact of urban land expansion and population dynamics on the availability, affordability, acceptability, and accessibility of restaurants. The case study reveals that, despite the Shanghai municipal authorities' focus on mitigating overcrowding in the central urban areas, soft infrastructure such as restaurants in new urban districts remains at a relative disadvantage...

Several methods have been developed to computationally predict cell-types for single cell RNA sequencing (scRNAseq) data. As methods are developed, a common problem for investigators has been identifying the best method they should apply to their specific use-case. To address this challenge, we present CHAI (consensus Clustering tHrough similArIty matrix integratIon for single cell type identification), a wisdom of crowds approach for scRNAseq clustering. CHAI presents two competing methods which aggregate the clustering results from seven state of the art clustering methods: CHAI-AvgSim and CHAI-SNF...

Crowd movement analysis (CMA) is a key technology in the field of public safety. This technology provides reference for identifying potential hazards in public places by analyzing crowd aggregation and dispersion behavior. Traditional video processing techniques are susceptible to factors such as environmental lighting and depth of field when analyzing crowd movements, so cannot accurately locate the source of events. Radar, on the other hand, offers all-weather distance and angle measurements, effectively compensating for the shortcomings of video surveillance...

This paper describes the analysis of electrodermal activity (EDA) in the context of students' scholastic activity. Taking a multidisciplinary, citizen science and maker-centric approach, low-cost, bespoken wearables, such as a mini weather station and biometric wristband, were built. To investigate both physical health as well as stress, the instruments were first validated against research grade devices. Following this, a research experiment was created and conducted in the context of students' scholastic activity...

Space charge effects are the Achilles' heel of all high-resolution ion optical devices. In time-of-flight mass analyzers, these may manifest as reduction of resolving power, mass measurement shift, peak coalescence, and/or transmission losses, while highly sensitive modern ion sources and injection devices ensure that such limits are easily exceeded. Space charge effects have been investigated, by experiment and simulation study, for the astral multi-reflection analyzer, incorporating ion focusing via a pair of converging ion mirrors, and fed by a pulsed extraction ion trap...

Biobased-functionalized metal-organic frameworks (Bio-FUN-MOFs) stand out from the crowd of candidates in the flame-retardant field due to their multipathway flame-retardant mechanisms and green synthesis processes. However, exploring and designing Bio-FUN-MOFs tend to counteract the problem of compromising the flame-retardant advantages of MOFs themselves, which inevitably results in a waste of resources. Herein, a strategy in which MOFs are ecologically regulated through acid-base balance is presented for controllable preparation of Bio-FUN-MOFs by two birds with one stone, i...

This research introduces the Multi-Objective Liver Cancer Algorithm (MOLCA), a novel approach inspired by the growth and proliferation patterns of liver tumors. MOLCA emulates the evolutionary tendencies of liver tumors, leveraging their expansion dynamics as a model for solving multi-objective optimization problems in engineering design. The algorithm uniquely combines genetic operators with the Random Opposition-Based Learning (ROBL) strategy, optimizing both local and global search capabilities. Further enhancement is achieved through the integration of elitist non-dominated sorting (NDS), information feedback mechanism (IFM) and Crowding Distance (CD) selection method, which collectively aim to efficiently identify the Pareto optimal front...

The proliferation of novel psychoactive substances (NPSs) continues to challenge toxicology laboratories. In particular, the United Nations Office on Drugs and Crime considers designer benzodiazepines to be a current primary threat among all NPSs. Herein, we report detection of a new emerging designer benzodiazepine, clobromazolam, using high-resolution mass spectrometry and untargeted data acquisition in combination with a "suspect screening" method built from the crowd-sourced HighResNPS.com database. Our laboratory first detected clobromazolam in emergency department presenting intoxications included within the Emerging Drugs Network of Australia-Victoria project in the state of Victoria, Australia, from April 2022 to March 2023...

Macromolecular crowding can induce the collapse of a single long polymer into a globular form due to depletion forces of entropic nature. This phenomenon has been shown to play a significant role in compacting the genome within the bacterium Escherichia coli into a well-defined region of the cell known as the nucleoid. Motivated by the biological significance of this process, numerous theoretical and computational studies have searched for the primary determinants of the behavior of polymer-crowder phases. However, our understanding of this process remains incomplete and there is debate on a quantitatively unified description...

Background The predominant source of respiratory infections in Northern Canada stems from RSV, leading to potentially life-threatening lower respiratory tract infections in children below the age of 2. Typically, RSV begins to appear in November or December and persists until April or May. Synagis® (Palivizumab), a monoclonal antibody, is employed to mitigate or reduce the effects of RSV. Past research indicated a reduction in hospitalizations with the use of Synagis®. Aim The aim is to estimate the cost-benefit analysis by comparing the health services cost with Synagis® program cost...

The ongoing destruction of habitats in the tropics accelerates the current rate of species extinction. Range-restricted species are exceptionally vulnerable, yet we have insufficient knowledge about their protection. Species' current distributions, range sizes, and protection gaps are crucial to determining conservation priorities. Here, we identified priority range-restricted bird species and their conservation hotspots in the Northern Andes. We employed maps of the Area of Habitat (AOH), that better reflect their current distributions than existing maps...

During the COVID-2021 epidemic, a large number of antibiotics were used for clinical treatment in hospitals or daily prevention. Sewage from hospital sewage treatment centers (HSTC) and wastewater treatment plants (WWTP) produced a lot of antibiotic-resistance genes/mobile genetic elements (ARGs/MGEs). In this study, the sewage and bioaerosol in the biochemical tank (BT) of an HSTC and a WWTP were sampled throughout the year. The results showed that the average absolute abundance of sewage in BT of WWTP (BTW-W) was higher than sewage in BT of HSTC (BTW-H)...

Within the 2030 Sustainable Development Agenda, large hydropower dams are positioned as a sustainable energy source, notwithstanding their adverse impacts on societies and ecosystems. This study contributed to ongoing discussions about the persistence of critical social issues, even after the investments of large amounts of resources in areas impacted by the construction of large hydropower dams. Our study focused on food insecurity and evaluated this issue in the city of Altamira in the Brazilian Amazon, which has been profoundly socially and economically impacted by the construction, between 2011 and 2015, of Brazil's second-largest dam, namely, Belo Monte...

BACKGROUND: The large amphibious freshwater apple snail is an important invasive species in China, but there is currently no method available for their surveillance. The development and popularization of smartphones provide a new platform for research on surveillance technologies for the early detection and effective control of invasive species. METHODS: The ASI surveillance system was developed based on the infrastructure of the WeChat platform and Amap. The user can directly enter the game interface through the WeChat port on their mobile phone, and the system automatically obtains their location...