The Benzodiazepines: Kinetic-Dynamic Relationships

Author(s):  
David J. Greenblatt
2013 ◽  
Vol 24 (1) ◽  
pp. 27-45
Author(s):  
Morten Ejrnæs ◽  
Jørgen Elm Larsen

Fattigdom har fået fornyet aktualitet, fordi andelen af fattige i Danmark er steget kraftigt siden 2001. Denne stigning falder tidsmæssigt sammen med indførelsen af de såkaldte ”fattigdomsydelser”. Det har gjort spørgsmålet om årsagerne til fattigdom påtrængende, fordi det er blevet hævdet, dels at det lave ydelsesniveau ville øge incitamentet til lønarbejde og således reducere fattigdommen, dels at det netop ville skabe fattigdom. Derfor forsøger vi i denne artikel at nuancere belysningen af årsager til fattigdom. Årsager til fattigdom opdeles traditionelt i strukturelle, kulturelle og individuelle forhold eller karakteristika, uden at kausaliteten og deres indbyrdes sammenhæng diskuteres grundigt. I artiklen skelnes mellem: makrostrukturelle forhold som fx lavkonjunktur; institutionelle forhold som fx socialpolitiske tiltag; lokalsamfundsforhold der knytter sig til det boligområde eller den egn, man er bosat i; og individuelle karakteristika, der fremtræder som kendetegn ved individet. Endelig inddrages biografi i form af livsfaser og nøglebegivenheder gennem et livsforløbs faser som fx sygdom, skilsmisse og arbejdsløshed som perioder, begivenheder eller kæder af begivenheder, der kan forklare fattigdom. Med udgangspunkt i denne opdeling vises det, hvorledes forskellige faktorer, processer eller mekanismer i to konkrete cases bidrager til at skabe fattigdom for den enkelte, men også hvordan intentioner, valg og handlinger samt tilfældigheder i de enkelte livsforløb kan have en afgørende betydning. ENGELSK ABSTRACT: Morten Ejrnæs and Jørgen Elm Larsen: Causes of Poverty This article focuses on causes of poverty. Causes of poverty are normally divided into structural, cultural and individual conditions or characteristics without fully considering causality and the dynamic relationships between them. In this article we distinguish between macro structural conditions such as recession, institutional conditions such as social policy measures, local conditions related to the residential area where one lives, and individual characteris-tics. Finally we include biography in terms of life phases and constraining key events during a life course such as teenage pregnancy, illness, divorce or unemployment as periods, events or chains of events that can explain why and how poverty emerges. This perspective is shown to illustrate how different factors, processes and mechanisms contribute to throwing the individual into poverty, but also how intentions, choices, actions and coincidences in the individual’s life course may have a crucial impact. This is illustrated by two case studies in which the trajectory of one’s life shows how key events in the form of coincidences cause poverty. However, the analysis also shows that because of their different age, habitus and possession of various forms of capital, the two individuals examined here will develop different life trajectories and attachment to the labour market. Key words: Poverty, causes, habitus, capital, reflexion, life trajectory.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaobin Wang ◽  
Yun Tong ◽  
Yupeng Fan ◽  
Haimeng Liu ◽  
Jun Wu ◽  
...  

AbstractSince spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google’s mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Soren Wainio-Theberge ◽  
Annemarie Wolff ◽  
Georg Northoff

AbstractSpontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Di Zhu ◽  
Xinyue Ye ◽  
Steven Manson

AbstractWe describe the use of network modeling to capture the shifting spatiotemporal nature of the COVID-19 pandemic. The most common approach to tracking COVID-19 cases over time and space is to examine a series of maps that provide snapshots of the pandemic. A series of snapshots can convey the spatial nature of cases but often rely on subjective interpretation to assess how the pandemic is shifting in severity through time and space. We present a novel application of network optimization to a standard series of snapshots to better reveal how the spatial centres of the pandemic shifted spatially over time in the mainland United States under a mix of interventions. We find a global spatial shifting pattern with stable pandemic centres and both local and long-range interactions. Metrics derived from the daily nature of spatial shifts are introduced to help evaluate the pandemic situation at regional scales. We also highlight the value of reviewing pandemics through local spatial shifts to uncover dynamic relationships among and within regions, such as spillover and concentration among states. This new way of examining the COVID-19 pandemic in terms of network-based spatial shifts offers new story lines in understanding how the pandemic spread in geography.


Author(s):  
Jeffrey Wright ◽  
Man-Keun Kim ◽  
Hernan A. Tejeda ◽  
Hwa-Neyon Kim

Abstract The dominant market where information is discovered plays the role of price leader providing substantial market information to other markets. This study investigates the dynamic relationships of 30 cattle markets across regions, cattle types, and cash/futures markets. The comparison of many markets, using an error correction model, is accomplished with the introduction of a tournament with a hierarchical cluster analysis, which allows us to conclude that the leading price for the U.S. cattle markets is discovered in the futures markets for both feeder and fed cattle.


Sign in / Sign up

Export Citation Format

Share Document