scholarly journals Urban Informatics in Sustainable Waste Management: A Spatial Analysis of Korea’s Informal Recycling Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 3076
Author(s):  
Jaehong Lee ◽  
Hans Han ◽  
Jong-Yoon Park ◽  
David Lee
Keyword(s):  
Urban Planning ◽  
Waste Management ◽  
Large Scale ◽  
Developing Economies ◽  
Large Data ◽  
Informal Recycling ◽  
Urban Informatics ◽  
Recycling Networks ◽  
Recent Developments ◽  
Future Policy

Large-scale informal recycling networks often emerge among developing economies in response to the challenges of modern urban waste accumulation. South Korea, despite its highly industrialized, developed economy, still maintains an extensive informal recycling sector made up of networks of local junk shops and individual waste pickers. As cities’ large data sources have become more widely available, the use of urban informatics in sustainable smart waste management has become more widespread. In this paper, we use geographic information system (GIS) analysis in order to uncover patterns within Korea’s informal recycling system, looking at the relationship between population demographics, waste levels, and urban planning with the prevalence of junk shops across Korea. We then interviewed junk shop owners, urban planning researchers, and government officials in order to better understand the factors that led to the coexistence of the country’s informal and formal systems of waste management and how junk shops have changed their operations over time in response to recent developments in cities’ urban fabrics. We conclude by giving suggestions for how the usage of urban informatics could increase the efficiency and sustainability of the country’s waste management systems, while also discussing the possible pitfalls of using such existing datasets for future policy decisions.

Recent Developments in the Downstream Processing of Phycobiliproteins from Algae: A Review

2021 ◽  
Vol 06 ◽  
Author(s):  
Ayekpam Chandralekha Devi ◽  
G. K. Hamsavi ◽  
Simran Sahota ◽  
Rochak Mittal ◽  
Hrishikesh A. Tavanandi ◽  
...  
Keyword(s):  
Cell Wall ◽  
Large Scale ◽  
Downstream Processing ◽  
Review Article ◽  
Current Status ◽  
Wall Structure ◽  
Scale Production ◽  
Cell Wall Disruption ◽  
Recent Developments ◽  
Macro Algae

Abstract: Algae (both micro and macro) have gained huge attention in the recent past for their high commercial value products. They are the source of various biomolecules of commercial applications ranging from nutraceuticals to fuels. Phycobiliproteins are one such high value low volume compounds which are mainly obtained from micro and macro algae. In order to tap the bioresource, a significant amount of work has been carried out for large scale production of algal biomass. However, work on downstream processing aspects of phycobiliproteins (PBPs) from algae is scarce, especially in case of macroalgae. There are several difficulties in cell wall disruption of both micro and macro algae because of their cell wall structure and compositions. At the same time, there are several challenges in the purification of phycobiliproteins. The current review article focuses on the recent developments in downstream processing of phycobiliproteins (mainly phycocyanins and phycoerythrins) from micro and macroalgae. The current status, the recent advancements and potential technologies (that are under development) are summarised in this review article besides providing future directions for the present research area.

scholarly journals Urban Policies and Large Projects in Central City Areas: The Example of Madrid (Spain)

Urban Science ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 42
Author(s):  
Dolores Brandis García
Keyword(s):  
Urban Planning ◽  
20Th Century ◽  
Large Scale ◽  
Central City ◽  
Global Market ◽  
Late 20Th Century ◽  
Public And Private ◽  
Urban Policies ◽  
Starting Point ◽  
The City

Since the late 20th century major, European cities have exhibited large projects driven by neoliberal urban planning policies whose aim is to enhance their position on the global market. By locating these projects in central city areas, they also heighten and reinforce their privileged situation within the city as a whole, thus contributing to deepening the centre–periphery rift. The starting point for this study is the significance and scope of large projects in metropolitan cities’ urban planning agendas since the final decade of the 20th century. The aim of this article is to demonstrate the correlation between the various opposing conservative and progressive urban policies, and the projects put forward, for the city of Madrid. A study of documentary sources and the strategies deployed by public and private agents are interpreted in the light of a process during which the city has had a succession of alternating governments defending opposing urban development models. This analysis allows us to conclude that the predominant large-scale projects proposed under conservative policies have contributed to deepening the centre–periphery rift appreciated in the city.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

scholarly journals On the geophysical processes impacting palaeo-sea-level observations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yusuke Yokoyama ◽  
Anthony Purcell
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Global Climate ◽  
Sea Level Change ◽  
Sea Level Changes ◽  
Factors Affecting ◽  
Ice Volume ◽  
Level Change ◽  
Recent Developments ◽  
Geophysical Processes

AbstractPast sea-level change represents the large-scale state of global climate, reflecting the waxing and waning of global ice sheets and the corresponding effect on ocean volume. Recent developments in sampling and analytical methods enable us to more precisely reconstruct past sea-level changes using geological indicators dated by radiometric methods. However, ice-volume changes alone cannot wholly account for these observations of local, relative sea-level change because of various geophysical factors including glacio-hydro-isostatic adjustments (GIA). The mechanisms behind GIA cannot be ignored when reconstructing global ice volume, yet they remain poorly understood within the general sea-level community. In this paper, various geophysical factors affecting sea-level observations are discussed and the details and impacts of these processes on estimates of past ice volumes are introduced.

scholarly journals A primary human T-cell spectral library to facilitate large scale quantitative T-cell proteomics

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Harshi Weerakoon ◽  
Jeremy Potriquet ◽  
Alok K. Shah ◽  
Sarah Reed ◽  
Buddhika Jayakody ◽  
...  
Keyword(s):  
T Cell ◽  
Large Scale ◽  
Large Data ◽  
Spectral Library ◽  
Proteomics Data ◽  
Cell Library ◽  
Public Resource ◽  
Human T Cell ◽  
Theoretical Mass ◽  
Current Resource

AbstractData independent analysis (DIA) exemplified by sequential window acquisition of all theoretical mass spectra (SWATH-MS) provides robust quantitative proteomics data, but the lack of a public primary human T-cell spectral library is a current resource gap. Here, we report the generation of a high-quality spectral library containing data for 4,833 distinct proteins from human T-cells across genetically unrelated donors, covering ~24% proteins of the UniProt/SwissProt reviewed human proteome. SWATH-MS analysis of 18 primary T-cell samples using the new human T-cell spectral library reliably identified and quantified 2,850 proteins at 1% false discovery rate (FDR). In comparison, the larger Pan-human spectral library identified and quantified 2,794 T-cell proteins in the same dataset. As the libraries identified an overlapping set of proteins, combining the two libraries resulted in quantification of 4,078 human T-cell proteins. Collectively, this large data archive will be a useful public resource for human T-cell proteomic studies. The human T-cell library is available at SWATHAtlas and the data are available via ProteomeXchange (PXD019446 and PXD019542) and PeptideAtlas (PASS01587).

scholarly journals Compartment and hub definitions tune metabolic networks for metabolomic interpretations

GigaScience ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
T Cameron Waller ◽  
Jordan A Berg ◽  
Alexander Lex ◽  
Brian E Chapman ◽  
Jared Rutter
Keyword(s):  
Large Scale ◽  
Metabolic Networks ◽  
Shortest Paths ◽  
Large Data ◽  
Differential Regulation ◽  
Large Data Sets ◽  
Data Sets ◽  
Human Metabolism ◽  
Experimental Conditions ◽  
Systemic Model

Abstract Background Metabolic networks represent all chemical reactions that occur between molecular metabolites in an organism’s cells. They offer biological context in which to integrate, analyze, and interpret omic measurements, but their large scale and extensive connectivity present unique challenges. While it is practical to simplify these networks by placing constraints on compartments and hubs, it is unclear how these simplifications alter the structure of metabolic networks and the interpretation of metabolomic experiments. Results We curated and adapted the latest systemic model of human metabolism and developed customizable tools to define metabolic networks with and without compartmentalization in subcellular organelles and with or without inclusion of prolific metabolite hubs. Compartmentalization made networks larger, less dense, and more modular, whereas hubs made networks larger, more dense, and less modular. When present, these hubs also dominated shortest paths in the network, yet their exclusion exposed the subtler prominence of other metabolites that are typically more relevant to metabolomic experiments. We applied the non-compartmental network without metabolite hubs in a retrospective, exploratory analysis of metabolomic measurements from 5 studies on human tissues. Network clusters identified individual reactions that might experience differential regulation between experimental conditions, several of which were not apparent in the original publications. Conclusions Exclusion of specific metabolite hubs exposes modularity in both compartmental and non-compartmental metabolic networks, improving detection of relevant clusters in omic measurements. Better computational detection of metabolic network clusters in large data sets has potential to identify differential regulation of individual genes, transcripts, and proteins.

scholarly journals Advances in the automated synthesis of 6-[18F]Fluoro-L-DOPA

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ângela C. B. Neves ◽  
Ivanna Hrynchak ◽  
Inês Fonseca ◽  
Vítor H. P. Alves ◽  
Mariette M. Pereira ◽  
...  
Keyword(s):  
Large Scale ◽  
Neuroendocrine Tumours ◽  
Radiochemical Yield ◽  
Clinical Applications ◽  
Clinical Use ◽  
Molar Activity ◽  
Neuropsychiatric Diseases ◽  
Recent Developments ◽  
Key Issues ◽  
Improved Methods

AbstractThe neurotracer 6-[18F] FDOPA has been, for many years, a powerful tool in PET imaging of neuropsychiatric diseases, movement disorders and brain malignancies. More recently, it also demonstrated good results in the diagnosis of other malignancies such as neuroendocrine tumours, pheochromocytoma or pancreatic adenocarcinoma.The multiple clinical applications of this tracer fostered a very strong interest in the development of new and improved methods for its radiosynthesis. The no-carrier-added nucleophilic 18F-fluorination process has gained increasing attention, in recent years, due to the high molar activities obtained, when compared with the other methods although the radiochemical yield remains low (17–30%). This led to the development of several nucleophilic synthetic processes in order to obtain the product with molar activity, radiochemical yield and enantiomeric purity suitable for human PET studies.Automation of the synthetic processes is crucial for routine clinical use and compliance with GMP requirements. Nevertheless, the complexity of the synthesis makes the production challenging, increasing the chance of failure in routine production. Thus, for large-scale clinical application and wider use of this radiopharmaceutical, progress in the automation of this complex radiosynthesis is of critical importance.This review summarizes the most recent developments of 6-[18F]FDOPA radiosynthesis and discusses the key issues regarding its automation for routine clinical use.

A Review of Machine Learning and Data Mining Approaches for Business Applications in Social Networks

2013 ◽  
Vol 9 (1) ◽  
pp. 36-53
Author(s):  
Evis Trandafili ◽  
Marenglen Biba
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Social Networks ◽  
Large Scale ◽  
Viral Marketing ◽  
Social Network Mining ◽  
Business Applications ◽  
Mining Community ◽  
Recent Developments ◽  
Analysis Of Social Networks

Social networks have an outstanding marketing value and developing data mining methods for viral marketing is a hot topic in the research community. However, most social networks remain impossible to be fully analyzed and understood due to prohibiting sizes and the incapability of traditional machine learning and data mining approaches to deal with the new dimension in the learning process related to the large-scale environment where the data are produced. On one hand, the birth and evolution of such networks has posed outstanding challenges for the learning and mining community, and on the other has opened the possibility for very powerful business applications. However, little understanding exists regarding these business applications and the potential of social network mining to boost marketing. This paper presents a review of the most important state-of-the-art approaches in the machine learning and data mining community regarding analysis of social networks and their business applications. The authors review the problems related to social networks and describe the recent developments in the area discussing important achievements in the analysis of social networks and outlining future work. The focus of the review in not only on the technical aspects of the learning and mining approaches applied to social networks but also on the business potentials of such methods.

scholarly journals Extreme Learning Machines on High Dimensional and Large Data Applications: A Survey

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Jiuwen Cao ◽  
Zhiping Lin
Keyword(s):  
Linear System ◽  
Video Processing ◽  
Large Data ◽  
Feedforward Neural Networks ◽  
High Dimensional ◽  
Recent Developments ◽  
Learning Machine ◽  
Hidden Layer ◽  
Hidden Neurons ◽  
The Cost

Extreme learning machine (ELM) has been developed for single hidden layer feedforward neural networks (SLFNs). In ELM algorithm, the connections between the input layer and the hidden neurons are randomly assigned and remain unchanged during the learning process. The output connections are then tuned via minimizing the cost function through a linear system. The computational burden of ELM has been significantly reduced as the only cost is solving a linear system. The low computational complexity attracted a great deal of attention from the research community, especially for high dimensional and large data applications. This paper provides an up-to-date survey on the recent developments of ELM and its applications in high dimensional and large data. Comprehensive reviews on image processing, video processing, medical signal processing, and other popular large data applications with ELM are presented in the paper.

scholarly journals Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Rong Guo ◽  
Xiaoya Song ◽  
Peiran Li ◽  
Guangming Wu ◽  
Zhiling Guo
Keyword(s):  
Urban Planning ◽  
Urban Development ◽  
Large Scale ◽  
Green Space ◽  
Sustainable Urban Development ◽  
Environmental Index ◽  
Wide Range ◽  
Transportation Accessibility ◽  
Urban Function ◽  
Green Model

Urban sustainable renewal has received extensive attention in a wide range of fields, including urban planning, urban management, energy management, and transportation. Given that environmental resource conservation is critical to urban sustainability renewal, this study highlighted the imbalance among green space, urban development, and transportation accessibility. Here, a novel node-place-green model is presented to measure sustainable urban development; meanwhile, deep learning is utilized to identify and extract the green space to measure the environmental index. Based on the generated node, place, and green value, urban developing status could be classified into nine modes for further analysis of transportation, urban function, and ecological construction. The experimental results of Harbin reveal the feasibility of the proposed method in providing specific guidelines for urban planning and policies on sustainable development.

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