scholarly journals A County Town in Ruins: Memories, Emotions, and Sense of Place in Post-Earthquake Beichuan, China

2021 ◽  
Vol 13 (20) ◽  
pp. 11258
Author(s):  
Lili Qian ◽  
Chunhui Zheng ◽  
Qin Lai ◽  
Juncheng Guo
Keyword(s):  
Sense Of Place ◽  
Large Scale ◽  
Physical Dependence ◽  
Place Identity ◽  
Disaster Loss ◽  
Before And After ◽  
Multi Temporal ◽  
Local Residents ◽  
Post Disaster ◽  
County Town

Ruins serve as symbolic sites at which to re-examine people’s relationships with the past and bonds with places. In the context of the ruination caused by earthquakes and the displacement and resettlement of local residents post-disaster, this paper explores vernacular (residents’ and survivors’) memories, emotions, and senses of place triggered by the ruins of Beichuan county town, China. Results show vernacular memories of specific ruins were highly fragmented and multi-temporal. Interwoven before- and after-quake memories gave rise to complex emotions, mainly including traumatic feeling of sadness, fear, and painful nostalgia. The study further identifies people’s sense of place towards the ruined county town and finds that locals’ sense of place was not accompanied by the loss of physical dependence to the negative side; locals still expressed high levels of place identity (physical uniqueness, self-esteem, and meanings), place attachment (rootedness and emotional attachment), and positive consequences of place behaviours (protection intention and revisiting) post-earthquake. Moreover, it found that sociodemographic variables of age and length of residence in Beichuan and the variables of disaster loss had significant effect on people’s sense of place. This study balances the overriding focus on visual and representational concerns common in ruin scholarship and further reveals the complex psychological processes impacting on sense of place after large-scale disasters. The findings reflect on the relief practices of post-disaster planning and can serve to guide ruin preservation.

scholarly journals ESTIMATION OF DAMAGED AREAS DUE TO THE 2010 CHILE EARTHQUAKE AND TSUNAMI USING SAR IMAGERY OF ALOS/PALSAR

2016 ◽  
Vol III-8 ◽  
pp. 35-42
Author(s):  
Pertiwi Jaya Ni Made ◽  
Fusanori Miura ◽  
A. Besse Rimba
Keyword(s):  
Large Scale ◽  
Aerial Photographs ◽  
Alos Palsar ◽  
Aster Gdem ◽  
Tsunami Damage ◽  
Before And After ◽  
Chile Earthquake ◽  
Multi Temporal ◽  
Sar Imagery ◽  
Inundation Map

A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km<sup>2</sup>. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.

scholarly journals ESTIMATION OF DAMAGED AREAS DUE TO THE 2010 CHILE EARTHQUAKE AND TSUNAMI USING SAR IMAGERY OF ALOS/PALSAR

2016 ◽  
Vol III-8 ◽  
pp. 35-42 ◽  
Author(s):  
Pertiwi Jaya Ni Made ◽  
Fusanori Miura ◽  
A. Besse Rimba
Keyword(s):  
Large Scale ◽  
Aerial Photographs ◽  
Alos Palsar ◽  
Aster Gdem ◽  
Tsunami Damage ◽  
Before And After ◽  
Chile Earthquake ◽  
Multi Temporal ◽  
Sar Imagery ◽  
Inundation Map

A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km<sup>2</sup>. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.

The Effect of Active Site-inhibited Factor VIIa on Tissue Factor-initiated Coagulation Using Platelets before and after Aspirin Administration

1997 ◽  
Vol 78 (04) ◽  
pp. 1202-1208 ◽  
Author(s):  
Marianne Kjalke ◽  
Julie A Oliver ◽  
Dougald M Monroe ◽  
Maureane Hoffman ◽  
Mirella Ezban ◽  
...  
Keyword(s):  
Tissue Factor ◽  
Active Site ◽  
Large Scale ◽  
Thrombin Generation ◽  
Factor Viia ◽  
Dependent Manner ◽  
Antithrombotic Agent ◽  
Before And After ◽  
Ic50 Values

SummaryActive site-inactivated factor VIIa has potential as an antithrombotic agent. The effects of D-Phe-L-Phe-L-Arg-chloromethyl ketone-treated factor VIla (FFR-FVIIa) were evaluated in a cell-based system mimicking in vivo initiation of coagulation. FFR-FVIIa inhibited platelet activation (as measured by expression of P-selectin) and subsequent large-scale thrombin generation in a dose-dependent manner with IC50 values of 1.4 ± 0.8 nM (n = 8) and 0.9 ± 0.7 nM (n = 7), respectively. Kd for factor VIIa binding to monocytes ki for FFR-FVIIa competing with factor VIIa were similar (11.4 ± 0.8 pM and 10.6 ± 1.1 pM, respectively), showing that FFR-FVIIa binds to tissue factor in the tenase complex with the same affinity as factor VIIa. Using platelets from volunteers before and after ingestion of aspirin (1.3 g), there were no significant differences in the IC50 values of FFR-FVIIa [after aspirin ingestion, the IC50 values were 1.7 ± 0.9 nM (n = 8) for P-selectin expression, p = 0.37, and 1.4 ± 1.3 nM (n = 7) for thrombin generation, p = 0.38]. This shows that aspirin treatment of platelets does not influence the inhibition of tissue factor-initiated coagulation by FFR-FVIIa, probably because thrombin activation of platelets is not entirely dependent upon expression of thromboxane A2.

scholarly journals THU0642-HPR EVOLUTION OF THE PERCEPTIONS OF RA PATIENTS AFTER EDUCATION PATIENT SESSION TEACHING METHOTREXATE SELF-INJECTION A PROSPECTIVE PILOT STUDY

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 566.1-566
Author(s):  
S. Afilal ◽  
H. Rkain ◽  
B. Berchane ◽  
J. Moulay Berkchi ◽  
S. Fellous ◽  
...  
Keyword(s):  
Pilot Study ◽  
Patient Education ◽  
Median Duration ◽  
Large Scale ◽  
Education Session ◽  
Prospective Pilot Study ◽  
Mean Delay ◽  
Lack Of Information ◽  
Level Of Satisfaction ◽  
Before And After

Background:Methotrexate is a gold standard for treatment of RA. In our context, RA patients prefer to be injected by paramedics rather than self-injecting. This can be explained by patients’ bad perceptions of self-injection or lack of information. Appropriate self-injection education can therefore be an important element in overcoming these obstacles and improving disease self-management.Objectives:Compare the RA patients’ perceptions on methotrexate self-injection before and after a patient education session.Methods:Prospective pilot study that included 27 consecutive patients (81.5% female, mean age 44.4 years, illiteracy rate 40.7%) with RA (median duration of progression of 4 years, mean delay in referral for specialist of 6 months, median duration of methotrexate use of 1 year). The patients benefited from an individual patient education session to learn how to self-inject with methotrexate subcutaneously. The patient education session was supervised by a nurse and a rheumatologist with a control a week later. Perceptions of the reluctance to self-inject and the difficulties encountered by patients were assessed before the patient education session, after the 1st and 2nd self-injection of methotrexate using a 10 mm visual analog scale. Patients also reported their level of satisfaction (10 mm VAS) after the 1st and 2nd self-injection.Results:The mean duration of patient education session is 13 min.Table I compares the evolution of the degrees of reluctance to self-injection, the difficulties encountered, and the satisfaction experienced by the patients.Table 1.Evolution of RA patients’ perceptions on the methotrexate self-injection. (N = 27)BeforeAfter the 1stself-injectionAfter the 2end self-injectionpVAS reluctance (0-10mm)6,5 ± 3,62,2 ± 2,91,0 ± 2,3<0,0001VAS difficulty (0-10mm)7,5 ± 2,62,5 ± 2,71,0 ± 1,9<0,0001VAS satisfaction (0-10mm)-8,9 ± 1,89,5 ± 1,50,002Conclusion:This study suggests the effectiveness of a methotrexate self-injection patient education session in RA patients. It also highlights the value of patient education in rheumatologic care. A large-scale study is necessary to better interpret and complete these preliminary results from this pilot study.Disclosure of Interests:None declared

scholarly journals Dynamic variations in salinity and potassium grade of a potassium-rich brine deposit in Lop Nor basin, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lichun Ma ◽  
Kai Wang ◽  
Yu Zhang ◽  
Qingfeng Tang ◽  
Hui Yan
Keyword(s):  
Large Scale ◽  
Sustainable Use ◽  
Potassium Sulfate ◽  
Middle Pleistocene ◽  
Underground Brine ◽  
Average Decrease ◽  
Rational Development ◽  
Mining History ◽  
Before And After ◽  
Lop Nor

AbstractThe Quaternary Lop Nor playa is the largest production base of potassium sulfate in the world. It has a mining history of more than 10 years, and its share in the Chinese potassium sulfate market is about 50% to-date. In this basin, the high-salinity potassium-rich brines are mainly contained in Middle Pleistocene–Holocene glauberite strata. Based on the monitoring of the underground brine table and geochemical analysis, this study reveals variations in the underground brine table and potassium-bearing grade before and after large-scale mining in the Lop Nor potash deposit. The results showed that the underground brine table and potassium sulfate grade decreased by varying degrees over sub-mineral areas after large-scale mining. The underground brine table declined by 8.5 m, on average, in the Luobei depression, by 6.4 m in the Tenglong platform and by 1.9 m in the Xinqing platform. However, the potassium-bearing grade showed the different trend. The Tenglong platform had the largest decline with average decreases in layers W1, W2 and W3 of 18.2%, 13.0% and 24.8%, respectively. In the Xinqing platform, the average decrease in layersW2 and W3 were 17.4% and 16.0% respectively. The Luobei depression decreases were relatively small (W1, W2 and W3 decreased 4.3%, 4.2% and 3.1%, respectively). This research provides a theoretical basis for the rational development and sustainable use of the potassium-rich brines in the Lop Nor basin.

scholarly journals Species and characteristics of volatile organic compounds emitted from an auto-repair painting workshop

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Y. Song ◽  
H. Chun
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Large Scale ◽  
Butyl Acetate ◽  
Small Scale ◽  
Indoor Environments ◽  
Voc Emissions ◽  
Volatile Organic ◽  
Before And After ◽  
Adsorption Systems

AbstractVolatile organic compounds (VOCs) are secondary pollutant precursors having adverse impacts on the environment and human health. Although VOC emissions, their sources, and impacts have been investigated, the focus has been on large-scale industrial sources or indoor environments; studies on relatively small-scale enterprises (e.g., auto-repair workshops) are lacking. Here, we performed field VOC measurements for an auto-repair painting facility in Korea and analyzed the characteristics of VOCs emitted from the main painting workshop (top coat). The total VOC concentration was 5069–8058 ppb, and 24–35 species were detected. The VOCs were mainly identified as butyl acetate, toluene, ethylbenzene, and xylene compounds. VOC characteristics differed depending on the paint type. Butyl acetate had the highest concentration in both water- and oil-based paints; however, its concentration and proportion were higher in the former (3256 ppb, 65.5%) than in the latter (2449 ppb, 31.1%). Comparing VOC concentration before and after passing through adsorption systems, concentrations of most VOCs were lower at the outlets than the inlets of the adsorption systems, but were found to be high at the outlets in some workshops. These results provide a theoretical basis for developing effective VOC control systems and managing VOC emissions from auto-repair painting workshops.

scholarly journals Correcting for experiment-specific variability in expression compendia can remove underlying signals

GigaScience ◽  
2020 ◽  
Vol 9 (11) ◽  
Author(s):  
Alexandra J Lee ◽  
YoSon Park ◽  
Georgia Doing ◽  
Deborah A Hogan ◽  
Casey S Greene
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Original Signal ◽  
Batch Effects ◽  
Technical Variability ◽  
The Past ◽  
Statistical Correction ◽  
Before And After ◽  
Data Collections ◽  
Biological Patterns

Abstract Motivation In the past two decades, scientists in different laboratories have assayed gene expression from millions of samples. These experiments can be combined into compendia and analyzed collectively to extract novel biological patterns. Technical variability, or "batch effects," may result from combining samples collected and processed at different times and in different settings. Such variability may distort our ability to extract true underlying biological patterns. As more integrative analysis methods arise and data collections get bigger, we must determine how technical variability affects our ability to detect desired patterns when many experiments are combined. Objective We sought to determine the extent to which an underlying signal was masked by technical variability by simulating compendia comprising data aggregated across multiple experiments. Method We developed a generative multi-layer neural network to simulate compendia of gene expression experiments from large-scale microbial and human datasets. We compared simulated compendia before and after introducing varying numbers of sources of undesired variability. Results The signal from a baseline compendium was obscured when the number of added sources of variability was small. Applying statistical correction methods rescued the underlying signal in these cases. However, as the number of sources of variability increased, it became easier to detect the original signal even without correction. In fact, statistical correction reduced our power to detect the underlying signal. Conclusion When combining a modest number of experiments, it is best to correct for experiment-specific noise. However, when many experiments are combined, statistical correction reduces our ability to extract underlying patterns.

scholarly journals Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

2021 ◽  
Vol 13 (5) ◽  
pp. 905
Author(s):  
Chuyi Wu ◽  
Feng Zhang ◽  
Junshi Xia ◽  
Yichen Xu ◽  
Guoqing Li ◽  
...  
Keyword(s):  
Damage Assessment ◽  
Large Scale ◽  
Binary Classification ◽  
Open Data ◽  
Building Damage ◽  
Attention Mechanism ◽  
Large Scale Dataset ◽  
Data Program ◽  
The Impact ◽  
Post Disaster

The building damage status is vital to plan rescue and reconstruction after a disaster and is also hard to detect and judge its level. Most existing studies focus on binary classification, and the attention of the model is distracted. In this study, we proposed a Siamese neural network that can localize and classify damaged buildings at one time. The main parts of this network are a variety of attention U-Nets using different backbones. The attention mechanism enables the network to pay more attention to the effective features and channels, so as to reduce the impact of useless features. We train them using the xBD dataset, which is a large-scale dataset for the advancement of building damage assessment, and compare their result balanced F (F1) scores. The score demonstrates that the performance of SEresNeXt with an attention mechanism gives the best performance, with the F1 score reaching 0.787. To improve the accuracy, we fused the results and got the best overall F1 score of 0.792. To verify the transferability and robustness of the model, we selected the dataset on the Maxar Open Data Program of two recent disasters to investigate the performance. By visual comparison, the results show that our model is robust and transferable.

Synthetic Environments for Investigating Collaborative Information Seeking: An Application in Emergency Restoration of Critical Infrastructures

2015 ◽  
Vol 12 (3) ◽  
Author(s):  
David Mendonça ◽  
William A. Wallace ◽  
Barbara Cutler ◽  
James Brooks
Keyword(s):  
Information Seeking ◽  
Large Scale ◽  
Critical Infrastructure ◽  
Future Research ◽  
Critical Infrastructures ◽  
Close Collaboration ◽  
Number Of Factors ◽  
Computer Based ◽  
Collaborative Information Seeking ◽  
Post Disaster

AbstractLarge-scale disasters can produce profound disruptions in the fabric of interdependent critical infrastructure systems such as water, telecommunications and electric power. The work of post-disaster infrastructure restoration typically requires information sharing and close collaboration across these sectors; yet – due to a number of factors – the means to investigate decision making phenomena associated with these activities are limited. This paper motivates and describes the design and implementation of a computer-based synthetic environment for investigating collaborative information seeking in the performance of a (simulated) infrastructure restoration task. The main contributions of this work are twofold. First, it develops a set of theoretically grounded measures of collaborative information seeking processes and embeds them within a computer-based system. Second, it suggests how these data may be organized and modeled to yield insights into information seeking processes in the performance of a complex, collaborative task. The paper concludes with a discussion of implications of this work for practice and for future research.

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