scholarly journals Family Practices and Temporality at Breakfast: Hot Spots, Convenience and Care

Sociology ◽  
2021 ◽  
pp. 003803852110155
Author(s):  
Daniela Pirani ◽  
Vicki Harman ◽  
Benedetta Cappellini
Keyword(s):  
Hot Spots ◽  
Hot Spot ◽  
Family Meals ◽  
Personal Integrity ◽  
Structured Interviews ◽  
Time Saving ◽  
Family Time ◽  
Dominant Feature ◽  
Family Practices ◽  
Cold Spots

Drawing on 34 semi-structured interviews, this study investigates the temporality of family practices taking place in the hot spot. It does so by looking at how breakfast is inserted in the economy of family time in Italy. Our data show that breakfast, contrary to other meals, allows the adoption of more individualised and asynchronous practices, hinged on the consumption of convenience products. These time-saving strategies are normalised as part of doing family. Although the existing literature suggests that convenience and care are in opposition, and consumers of convenience products can experience anxiety and a lack of personal integrity, such features were not a dominant feature of our participants’ accounts. These findings suggest that the dichotomies of hot/cold spots and care/convenience are not always experienced in opposition when embedded within family practices. Hence, this study furthers understandings of family meals, temporality and the distinction between hot and cold spots.

scholarly journals The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China

2020 ◽  
Author(s):  
Dingwen Lin ◽  
Zhezhe Cui ◽  
Virasakdi Virasakdi ◽  
Prasit Palittapongarnpim ◽  
Angkana Chaiprasert ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hot Spots ◽  
Hot Spot ◽  
Cold Spot ◽  
Sequencing Analysis ◽  
Spot Area ◽  
H37rv Strain ◽  
Lineage 2 ◽  
Cold Spots ◽  
Genomic Clusters

Abstract Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. Objective This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China. Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed. Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots.Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.

scholarly journals The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China

2020 ◽  
Author(s):  
Dingwen Lin ◽  
Zhezhe Cui ◽  
Virasakdi Virasakdi ◽  
Prasit Palittapongarnpim ◽  
Angkana Chaiprasert ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hot Spots ◽  
Hot Spot ◽  
Cold Spot ◽  
Sequencing Analysis ◽  
Spot Area ◽  
H37rv Strain ◽  
Lineage 2 ◽  
Cold Spots ◽  
Genomic Clusters

Abstract Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China. Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed. Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots. Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.

scholarly journals Identifying diabetes management opportunity areas in the USA

2020 ◽  
Vol 8 (1) ◽  
pp. e000293 ◽  
Author(s):  
Michael Topmiller ◽  
Kyle Shaak ◽  
Peter J Mallow ◽  
Autumn M Kieber-Emmons
Keyword(s):  
Hot Spots ◽  
Diabetes Management ◽  
Hot Spot ◽  
The United States ◽  
Cold Spot ◽  
United States Census ◽  
Preventable Hospitalisation ◽  
Cold Spots ◽  
Medicare Spending ◽  
Management Services

Using adherence to diabetes management guidelines as a case study, this paper applied a novel geospatial hot-spot and cold-spot methodology to identify priority counties to target interventions. Data for this study were obtained from the Dartmouth Atlas of Healthcare, the United States Census Bureau’s American Community Survey and the University of Wisconsin County Health Rankings. A geospatial approach was used to identify four tiers of priority counties for diabetes preventive and management services: diabetes management cold-spots, clusters of counties with low rates of adherence to diabetes preventive and management services (Tier D); Medicare spending hot-spots, clusters of counties with high rates of spending and were diabetes management cold-spots (Tier C); preventable hospitalisation hot-spots, clusters of counties with high rates of spending and are diabetes management cold-spots (Tier B); and counties that were located in a diabetes management cold-spot cluster, preventable hospitalisation hot-spot cluster and Medicare spending hot-spot cluster (Tier A). The four tiers of priority counties were geographically concentrated in Texas and Oklahoma, the Southeast and central Appalachia. Of these tiers, there were 62 Tier A counties. Rates of preventable hospitalisations and Medicare spending were higher in Tier A counties compared with national averages. These same counties had much lower rates of adherence to diabetes preventive and management services. The novel geospatial mapping approach used in this study may allow practitioners and policy makers to target interventions in areas that have the highest need. Further refinement of this approach is necessary before making policy recommendations.

Community-Wide Prevention of COVID-19: A Systematic Analysis of Hot vs. Cold Spots

2021 ◽  
Author(s):  
Mackenzie Davis ◽  
E Scott Geller ◽  
Zach Mastrich
Keyword(s):  
Hot Spots ◽  
Large Scale ◽  
Hot Spot ◽  
Virginia Tech ◽  
University Of Kansas ◽  
Prevention Measures ◽  
Systematic Analysis ◽  
University Of Florida ◽  
Western Michigan University ◽  
Cold Spots

Universities in five different states are collaborating on an original large-scale COVID-prevention effort by asking many of their students to complete an innovative survey that strategically asks them to identify areas on and around campus that are “hot spots” for spreading the coronavirus. These universities—Virginia Tech, Appalachian State, Western Michigan, University of Kansas, and University of Florida—are also observing mask wearing, social distancing, and other COVID prevention measures in their communities to analyze the risk management and wellness precautions taken by students, faculty, and the surrounding communities. Mapping hot-spot areas provides invaluable information for prevention and intervention creation.

scholarly journals The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China

2020 ◽  
Author(s):  
Dingwen Lin ◽  
Zhezhe Cui ◽  
Virasakdi Virasakdi ◽  
Prasit Palittapongarnpim ◽  
Angkana Chaiprasert ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hot Spots ◽  
Hot Spot ◽  
Cold Spot ◽  
Sequencing Analysis ◽  
Spot Area ◽  
H37rv Strain ◽  
Lineage 2 ◽  
Cold Spots ◽  
Genomic Clusters

Abstract Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China. Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed. Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots. Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.

scholarly journals Geospatial cluster analyses of pneumonia-associated hospitalisations among adults in New York City, 2010–2014

2018 ◽  
Vol 147 ◽  
Author(s):  
P. A. Kache ◽  
T. Julien ◽  
R. E. Corrado ◽  
N. M. Vora ◽  
D. C. Daskalakis ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Hot Spots ◽  
Hot Spot ◽  
Severe Pneumonia ◽  
Cold Spot ◽  
Staten Island ◽  
Cluster Analyses ◽  
Cold Spots

AbstractPneumonia is a leading cause of death in New York City (NYC). We identified spatial clusters of pneumonia-associated hospitalisation for persons residing in NYC, aged ⩾18 years during 2010–2014. We detected pneumonia-associated hospitalisations using an all-payer inpatient dataset. Using geostatistical semivariogram modelling, local Moran'sIcluster analyses andχ2tests, we characterised differences between ‘hot spots’ and ‘cold spots’ for pneumonia-associated hospitalisations. During 2010–2014, there were 141 730 pneumonia-associated hospitalisations across 188 NYC neighbourhoods, of which 43.5% (N= 61 712) were sub-classified as severe. Hot spots of pneumonia-associated hospitalisation spanned 26 neighbourhoods in the Bronx, Manhattan and Staten Island, whereas cold spots were found in lower Manhattan and northeastern Queens. We identified hot spots of severe pneumonia-associated hospitalisation in the northern Bronx and the northern tip of Staten Island. For severe pneumonia-associated hospitalisations, hot-spot patients were of lower mean age and a greater proportion identified as non-Hispanic Black compared with cold spot patients; additionally, hot-spot patients had a longer hospital stay and a greater proportion experienced in-hospital death compared with cold-spot patients. Pneumonia prevention efforts within NYC should consider examining the reasons for higher rates in hot-spot neighbourhoods, and focus interventions towards the Bronx, northern Manhattan and Staten Island.

scholarly journals ANALYZING THE SPATIAL TEMPORAL OF PROPERTY CRIME HOT SPOTS. A CASE STUDY OF KUCHING, SARAWAK

2020 ◽  
Vol 18 (14) ◽  
Author(s):  
Norita Jubit ◽  
Tarmiji Masron ◽  
Azizan Marzuki
Keyword(s):  
Hot Spots ◽  
Spatial Clustering ◽  
Hot Spot ◽  
Statistical Significance ◽  
Property Crime ◽  
Management Planning ◽  
Police Station ◽  
Exogenous Factors ◽  
Cold Spots

This study aims to determine the monthly hot spots of property crime in Kuching, Sarawak from January-December, 2015-2017. Hot Spot Analysis (Getis Ord Gi*) was chosen for this study because it can detect the areas that have spatial clustering with similar values around its neighboring boundaries. It can present an output for hot spots and cold spots with different levels of statistical significance. Gita Police Station sector boundaries were identified as a high-value cluster for eight months in 2015 and also have a high-value cluster for seven months in 2016. However, in 2017 Padungan Police Station sector boundary was identified as a high-value cluster for four months. The hot spots of property crime in Kuching, Sarawak change over time and places. This study found that holidays and festivals are exogenous factors that can influence the increases of property crime rate in Kuching, Sarawak. The findings of this study can help police to predict temporal crime trends accurately which would be beneficial for management planning.

Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

2018 ◽  
Vol 18 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Hot Spots ◽  
Land Surface ◽  
Hot Spot ◽  
Monitoring Network ◽  
Residential Areas ◽  
Hotspot Analysis ◽  
The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

The family Orthotrichaceae (Bryophyta) in flora of Russia: results of revision and biogeographical review

2018 ◽  
Vol 52 (2) ◽  
pp. 519-534 ◽  
Author(s):  
V. E. Fedosov
Keyword(s):  
Hot Spots ◽  
Latitudinal Gradient ◽  
Hot Spot ◽  
Spatial Differentiation ◽  
Taxonomic Composition ◽  
Undescribed Species ◽  
Longitudinal Gradient ◽  
Biogeographic Pattern ◽  
The Family ◽  
North Pacific Region

Recent studies on Orthotrichoid mosses in Russia are summarized genus by genus. Orthotrichum furcatum Otnyukova is synonymized with Nyholmiella obtusifolia. Orthotrichum vittii is excluded from the Russian moss flora. Description of O. dagestanicum is amended. Fifty four currently recognized species from 9 genera of the Orthotrichaceae are presently known to occur in Russia; list of species with common synonyms and brief review of distribution in Russia is presented. Numerous problematic specimens with unresolved taxonomy were omitted for future. Revealed taxonomical inconsistencies in the genera Zygodon, Ulota, Lewinskya, Nyholmiella, Orthotrichum are briefly discussed. Main regularities of spatial differentiation of the family Orthotrichaceae in Russia are considered. Recently presented novelties contribute to the certain biogeographic pattern, indicating three different centers of diversity of the family, changing along longitudinal gradient. Unlike European one, continental Asian diversity of Orthotrichaceae is still poorly known, the Siberian specimens which were previously referred to European species in most cases were found to represent other, poorly known or undescribed species. North Pacific Region houses peculiar and poorly understood hot spot of diversity of Orthotrichoid mosses. Thus, these hot spots are obligatory to be sampled in course of revisions of particular groups, since they likely comprise under-recorded cryptic- or semi-cryptic species. Latitudinal gradient also contributes to the spatial differentiation of the revealed taxonomic composition of Orthotrichaceae.

Investigation of On-Chip Hot Spot Cooling Using Microchannel Heat Sink

2013 ◽  
Vol 455 ◽  
pp. 466-469
Author(s):  
Yun Chuan Wu ◽  
Shang Long Xu ◽  
Chao Wang
Keyword(s):  
Heat Flux ◽  
Heat Sink ◽  
Hot Spots ◽  
Hot Spot ◽  
High Heat ◽  
High Heat Flux ◽  
Microchannel Heat Sink ◽  
Three Dimensional Model ◽  
Spot Cooling ◽  
On Chip

With the increase of performance demands, the nonuniformity of on-chip power dissipation becomes greater, causing localized high heat flux hot spots that can degrade the processor performance and reliability. In this paper, a three-dimensional model of the copper microchannel heat sink, with hot spot heating and background heating on the back, was developed and used for numerical simulation to predict the hot spot cooling performance. The hot spot is cooled by localized cross channels. The pressure drop, thermal resistance and effects of hot spot heat flux and fluid flow velocity on the cooling of on-chip hot spots, are investigated in detail.

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