The Survival Family 2017
The Survival Family 2017 ->>> https://bytlly.com/2t7SuF
This film centers on the main character Yoshiyuki Suzuki (played by Fumiyo Kohinata) and his family. When the electricity in Tokyo stops due to a solar flare, the city is on the verge of panic. Yoshiyuki has to lead his family to strive for survival. The family is used to being spoilt by modern urban life. However, they learn to deal with the harsh realities of a dystopic Japan where the lack of electricity has led everyone to rediscover the olden ways that do not rely on technology.[2]
When a worldwide electrical outage occurs, everything that requires electricity comes to a stop. Yoshiyuki Suzuki decides to escape with his family from Tokyo, that is nearly ruined. Edit Translation
Insect pollinators such as bumblebees (Bombus spp.) are in global decline. A major cause of this decline is habitat loss due to agricultural intensification. A range of global and national initiatives aimed at restoring pollinator habitats and populations have been developed. However, the success of these initiatives depends critically upon understanding how landscape change affects key population-level parameters, such as survival between lifecycle stages, in target species. This knowledge is lacking for bumblebees, because of the difficulty of systematically finding and monitoring colonies in the wild. We used a combination of habitat manipulation, land-use and habitat surveys, molecular genetics and demographic and spatial modelling to analyse between-year survival of family lineages in field populations of three bumblebee species. Here we show that the survival of family lineages from the summer worker to the spring queen stage in the following year increases significantly with the proportion of high-value foraging habitat, including spring floral resources, within 250-1,000 m of the natal colony. This provides evidence for a positive impact of habitat quality on survival and persistence between successive colony cycle stages in bumblebee populations. These findings also support the idea that conservation interventions that increase floral resources at a landscape scale and throughout the season have positive effects on wild pollinators in agricultural landscapes.
サバイバルファミリー , Sabaibaru Famiri. Japan 2017. Directed by Yaguchi Shinobu. Starring Fumiyo Kohinata, Eri Fukatsu, Yuki Izumisawa, Wakana Aoi, Saburo Tokito, Norika Fujiwara, Takuro Ohno, Jun Shison. 117 mins. In Japanese with English subtitles.
However, part of the brilliance in the approach in focusing on drama within a single family is the ability to offer a grounded experience, as most of the narrative is conveyed through focusing on family only. Overall, the production balances the aesthetic and soul of independent cinema (by way of heartwarming drama) and big budgeted disaster film in a seamless and engaging manner, embodying the best of both cinematic experiences.
The production is backed by great casting choices, as each family member helps to establish a sense of realism and history as a single unit. However, it is Fumiyo Kohinata and Eri Fukatsu as the parental figures that offer the most depth and intrigue. With the nationwide power outage, the traditional role of breadwinner is put into a secondary role, while the mother’s social etiquette and bartering skills takes on greater importance. As a result, the father figure faces a large personal and emotional challenge when the skills he worked his entire life, seem to be more of a hindrance on his family’s survival. Overall, this struggle of the father to find a new validity within his family makes for a fascinating transition, one which gets the viewer to emphatically cheer him on.
The Mission of the Holy Family University Family Center is to provide resources to families through education, counseling, consultation, and advocacy. These resources serve to empower families to adapt to changes in the environment, changes in relationships within the family, and the changing needs of family members.
The crisis brings out both the best and the worst in humanity. As the family make their escape from the city on a series of bicycles, they pass a succession of salesmen all upping the price of bottled water by 100% each time. Profiteering is rife as the unscrupulous procure ordinary foodstuffs to be sold for vast amounts of money. Yet the Suzukis rarely find themselves on the wrong side of trickery and even encounter a few kindly souls willing to help them on their journey such as a gang of cycle wear clad survival experts and a very forgiving farmer who takes the family in when they help themselves to one of his escaped pigs (a sequence which allows Yaguchi to go on another Swing Girls-style pig chase only without the slo-mo and classical music).
The objective of this research was to answer three questions as follows: (1) did proximity to nearby burning structures factor into the probability of home survival, (2) did fuels associated with nearby vegetation factor into the probability of home survival, and (3) was the full adoption in 2008 of Chapter 7A into the California Building Code associated with improved odds of home survival?
To determine the relative strength of factors associated with home survival, we used a generalized linear model fit for binary response data, with a logit link function and weighting to account for the sampling scheme. Variables in the initial model were as follows:
We then designed models to first test the effect of variables that may have directly influenced home survival during the fire and second, to test the effect of just the variables available prior to the fire. The latter variables were ones that might be mitigated preemptively through planning, retrofitting, or vegetation management. For each of these models, we determined the effect size and performed a regression tree analysis. Variables included for each approach (accounting for the fire, pre-fire only):
To quantify the relative strength of continuous variables for explaining home survival, each of the dependent (x) variables were centered and scaled to have a mean of zero and standard deviation of one. Logistic regression (McCullagh and Nelder 1989) was then used to calculate coefficients and compare effect sizes. The logistic regression models were fit using the svyglm function from the survey package in R (Lumly 2020). A decision tree for predicting home survival was produced using the rpart function in the rpart package (Therneau and Atkinson 2019) in R, fit for binary response data with a logit link function (Breiman 1998). This approach is similar to logistic regression, where the linear predictor is a decision tree model. To determine the number of splits in the decision trees, we performed cross-validation 10,000 times to compute the optimal pruning parameters. We then used the average of the 10,000 optimal pruning parameters as the pruning parameter in the final decision tree. The latter group of statistical analyses was completed using R version 4.0.0 (R Core Team 2020). Figures were made in R using the ggplot2 package (Wickham 2016).
Effect sizes for two logistic regression models of home survival in the town of Paradise during the 2018 Camp Fire, including continuous variables a present during the fire and b only variables present pre-fire. Regressions were based on a random sample of 400 homes
Regression trees for predicting home survival in the town of Paradise in the 2018 Camp Fire, with models including continuous variables a present during the fire and b only variables present pre-fire, both based on a random sample of 400 homes. Survival proportion is listed in bold under each branch, along with the percentage of homes in Paradise that each branch applied to (in parenthesis)
Our analysis of post-fire outcomes in the town of Paradise suggested that both the proximity to other burning structures and nearby wildland fuels factored in the probability of home survival, with several measures of distance and density of destroyed structures and nearby pre-fire overstory canopy cover emerging as significant explanatory variables. The relative importance of nearby burning home variables versus surrounding vegetation in explaining outcomes has varied among studies, with Gibbons et al. (2012) reporting canopy cover within 40m of the home to be the strongest predictor. Number of buildings within 40m was also a significant variable in their analysis. Even though nearby burning structure and vegetation variables were both included in the models in our study, interpretations about relative strength of these two sets of factors are tempered by limitations of the vegetation data, with overstory canopy cover an imperfect measure of wildland fuel hazard.
While the survival rate for homes built in the 11 years after the adoption of Chapter 7A to the California Building Code in 2008 was numerically slightly higher than the survival rate of homes built in the 11 years immediately before, the difference was not statistically significant. It is possible that significance might have been found with a larger sample size, but even so, any influence of the building code update was likely overwhelmed by other factors. This was not a surprise because of the many interacting variables that affect building performance, in addition to building products rated to resist exterior fire exposures. The 2008 Chapter 7A building code update institutionalized several important and worthwhile changes to construction in high fire hazard zones, including the use of ember and flame-resistant vents. These changes may improve the probability of survival for some types of wildfire (e.g., vegetation and wind-driven fires); however, the changes were apparently not sufficient to fully protect buildings from radiant heat exposures from nearby burning structures. One of the primary mechanisms for radiant heat impact is the breaking of window glass, which can allow embers to enter the building (Penman et al. 2019). A common method for complying with Chapter 7A is through the use of tempered glass in one pane of a double-paned window. However, the magnitude of radiant heat exposure was likely still too much in many cases, or other vulnerabilities remained. 2b1af7f3a8