top of page

Meinewebsite Group

Öffentlich·85 Mitglieder

Decline



WASHINGTON, Sept. 19, 2018 Fewer people are living in extreme poverty around the world, but the decline in poverty rates has slowed, raising concerns about achieving the goal of ending poverty by 2030 and pointing to the need for increased pro-poor investments, the World Bank finds.




decline


Download: https://www.google.com/url?q=https%3A%2F%2Fgohhs.com%2F2uhYWP&sa=D&sntz=1&usg=AOvVaw3xOEQbw0BmIBpq8ldC79Mz



The deceleration in global numbers stems mainly from an increasing concentration of extreme poverty in regions where poverty reduction has lagged. A case in point is Sub-Saharan Africa, where, under all but the most optimistic scenarios, poverty will remain in double digits by 2030, absent significant shifts in policy. Slowing declines in poverty also reflect falling commodity prices, conflict, and other economic challenges for developing countries.


The WHO Guidelines on risk reduction of cognitive decline and dementia provide evidence-based recommendations on lifestyle behaviours and interventions to delay or prevent cognitive decline and dementia.


Results: In adjusted mixed models, the MIND score was positively associated with slower decline in global cognitive score (β = 0.0092; P


Discussion: The study findings suggest that the MIND diet substantially slows cognitive decline with age. Replication of these findings in a dietary intervention trial would be required to verify its relevance to brain health.


Results: A statistically significant decline in empathy scores was observed when comparing students in the preclinical (years 1 and 2) and the clinical (years 3 and 4) phases of medical school (P


Conclusions: Differences in DO-granting and MD-granting medical education systems, such as emphasis on provision of holistic care, hands-on approaches to diagnosis and treatment, and patient-centered care, provide plausible explanations for disparity in the magnitude of empathy decline in DO compared with MD students. More research is needed to examine changes in empathy in longitudinal study and explore reasons for changes to avert erosion of empathy in medical school.


In November 1978, California voters passed Proposition 8, which amended Article XIII A to allow temporary reductions in assessed value in cases where real property suffers a decline in value. Proposition 8 is codified by section 51(a)(2) of the Revenue and Taxation Code.


A decline in value occurs in any year in which the current market value of real property is less than its adjusted base year value as of the lien date, January 1. A property's base year value is the market value of real property as established in 1975 or when the property last changed ownership or underwent new construction. The base year value is adjusted annually by lower of the percentage change in the consumer price index (CPI), or 2 percent. The adjusted base year value is also known as the factored base year value.


The market value of real property may decline from one lien date to the next lien date; however, the property will not benefit from a lower assessment unless its market value falls below the current factored base year value.


For example, if you purchase your property during a time when the real estate market falls dramatically, or if your property is substantially damaged due to a storm or fire that causes a reduction in your property's value, it is likely that your property will benefit from a Proposition 8 reassessment. The decline in value is typically temporary and may be the result of changes in the real estate market, the neighborhood, or the property itself.


Once a property's assessment has been reduced under Proposition 8, the assessor reviews the assessment annually to determine whether it should remain in decline-in-value status. The assessed value of a property in decline-in-value status may increase each lien date (January 1) by more than the standard two percent maximum allowed for properties assessed under Proposition 13; however, unless there is a change in ownership or new construction, a property's assessed value can never increase above its existing factored base year value.


Most county assessors will review a property's assessment for a possible decline in value upon request. The review may be provided as an informal discussion with assessor's staff, or the assessor may require the property owner complete a request form. Contact your local assessor to determine the requirements for a decline-in-value review in your county.


LTAs provide an ongoing advisory service for county assessors and others interested in the property tax system in California. The letters present Board staff's interpretation of rules, laws, and court decisions on property tax assessment. The following LTAs pertain to assessment or procedural issues involving declines in value in California.


Annotated legal opinions are summaries of the conclusions reached in selected legal rulings of California State Board of Equalization counsel. The following legal opinions pertain to questions involving declines in value.


Under Proposition 13, base year values may not be increased more than two percent per year. Properties in decline-in-value status under Proposition 8, however, are not limited to the maximum two percent increase, since such properties are not assessed according to their factored base year values. Instead, where a property remains in decline-in-value status for two or more consecutive years, the year-to-year change in value will reflect the change in market value regardless of the magnitude or direction of the change. In all cases, the factored base year value is restored once the market value increases to the point where it is equal to or greater than the factored base year value.


Global declines in insects have sparked wide interest among scientists, politicians, and the general public. Loss of insect diversity and abundance is expected to provoke cascading effects on food webs and to jeopardize ecosystem services. Our understanding of the extent and underlying causes of this decline is based on the abundance of single species or taxonomic groups only, rather than changes in insect biomass which is more relevant for ecological functioning. Here, we used a standardized protocol to measure total insect biomass using Malaise traps, deployed over 27 years in 63 nature protection areas in Germany (96 unique location-year combinations) to infer on the status and trend of local entomofauna. Our analysis estimates a seasonal decline of 76%, and mid-summer decline of 82% in flying insect biomass over the 27 years of study. We show that this decline is apparent regardless of habitat type, while changes in weather, land use, and habitat characteristics cannot explain this overall decline. This yet unrecognized loss of insect biomass must be taken into account in evaluating declines in abundance of species depending on insects as a food source, and ecosystem functioning in the European landscape.


All trap locations were situated in protected areas, but with varying protection status: 37 locations are within Natura2000 sites, seven locations within designated Nature reserves, nine locations within Protected Landscape Areas (with funded conservation measures), six locations within Water Protection Zones, and four locations of protected habitat managed by Regional Associations. For all location permits have been obtained by the relevant authorities, as listed in the S1 Appendix. In our data, traps located in nutrient-poor heathlands, sandy grasslands, and dune habitats provide lower quantities of biomass as compared to nutrient nutrient-rich grasslands, margins and wastelands. As we were interested in whether the declines interact with local productivity, traps locations were pooled into 3 distinct habitat clusters, namely: nutrient-poor heathlands, sandy grassland, and dunes (habitat cluster 1, n = 19 locations, Fig 1A), nutrient-rich grasslands, margins and wasteland (habitat cluster 2, n = 41 locations, Fig 1B) and a third habitat cluster that included pioneer and shrub communities (n = 3 locations).


Climate change is a well-known factor responsible for insect declines [15, 18, 21, 37]. To test if weather variation could explain the observed decline, we included mean daily temperature, precipitation and wind speed in our analysis, integrating data from 169 weather stations [38] located within 100km to the trap locations. We examined temporal trends in each weather variable over the course of the study period to assess changes in climatic conditions, as a plausible explanation for insect decline. Estimates of each weather variable at the trap locations were obtained by interpolation of each variable from the 169 climate stations.


Our estimate of decline is based on our basic model, from which we can derive seasonal estimates of daily biomass for any given year. The basic model includes only a temporal (annual and seasonal effects, as well as interactions) and a basic habitat cluster distinction (additive effects only) as well as a random trap location effect. We here report the annual trend coefficient, as well as a weighted estimate of decline that accounts for the within season differences in biomass decline. The weighted insect biomass decline was estimated by projecting the seasonal biomass (1-April to 30-October) for years 1989 and 2016 using coefficients our basic model, and then dividing the summed (over the season) biomass of 2016 by the summed biomass over 1989.


Using our final model, we assessed the relative contribution (i.e. net effect) of the explanatory variables to the observed decline, both combined and independently. To this aim we projected the seasonal daily biomass for the years 1989 and 2016 twice: first we kept covariates at their mean values during the early stages of the study period, and second we allowed covariate values to change according to the observed mean changes (see S2 and S3 Figs). Difference in the total biomass decline between these two projections are interpreted as the relative contribution of the explanatory variables to the decline. The marginal (i.e. independent) effects of each covariate were calculated by projecting biomass increase/decline as result of the observed temporal developments in each variable separately, and expressing it as percentual change. 041b061a72


Info

Welcome to the group! You can connect with other members, ge...
bottom of page