Предрогнозна оцінка структури майна і капіталу промислового підприємства

Однією зі складових управління фінансами підприємства є прогнозування фінансового стану, яке дозволяє виявити здатність підприємства до стійкого функціонування і розвитку в умовах зміни зовнішнього і внутрішнього середовища господарювання. Сьогодні неможна недооцінювати роль прогнозування, оскільки функціонування підприємства завжди пов'язане з невизначеністю майбутніх наслідків дій того або іншого управлінського рішення. Однією із дисциплінуючих умов прогнозування фінансового стану промислових підприємств виступає оцінка їх фінансового стану у динаміці взагалі та предпрогнозна оцінка структури майна і капіталу зокрема.Одной из составляющих управления финансами предприятия является прогнозирование финансового состояния, которое позволяет выявить способность предприятия к стойкому функционированию и развитию в условиях изменения внешней и внутренней среды ведения хозяйства. Сегодня невозможно недооценивать роль прогнозирования, поскольку функционирование предприятия всегда связано с неопределенностью будущих последствий действий того или другого управленческого решения. Одним из дисциплинирующих условий прогнозирования финансового состояния промышленных предприятий выступает оценка их финансового состояния в динамике вообще и предпрогнозируемая оценка структуры имущества и капитала в частности

Ethnicity and baseline symptomatology in patients with an At Risk Mental State for psychosis

Ethnicity has been associated with different incidence rates and different symptom profiles in young patients with psychotic-like disorders. No studies so far have examined the effect of ethnicity on symptoms in people with an At Risk Mental State (ARMS). In this cross-sectional study, we analysed the relationship between ethnicity and baseline data on the severity of psychopathology scores in 201 help-seeking patients who met the ARMS criteria and agreed to participate in the Dutch Early Detection and Intervention (EDIE-NL) trial. Eighty-seven of these patients had a non-Dutch ethnicity. We explored the possible mediating role of ethnic identity. Higher rates of negative symptoms, and of anhedonia in particular, were found in the ethnic minority group. This result could be attributed mainly to the Moroccan-Dutch and Turkish-Dutch subgroups, who also presented with more depression symptoms when the groups were examined separately. The ethnic minority group displayed a lower level of ethnic group identity compared to the immigrants of the International Comparative Study of Ethnocultural Youth (ICSEY). Ethnic identity was inversely related to symptoms in the Moroccan-Dutch patient group. The prevalence of more severe negative symptoms and depression symptoms in ethnic minority groups deserves more attention, as the experience of attenuated positive symptoms when accompanied by negative symptoms or distress has proven to be predictive for transition to a first psychotic episod

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

What's in a Day? : A Guide to Decomposing the Variance in Intensive Longitudinal Data

In recent years there has been a growing interest in the use of intensive longitudinal research designs to study within-person processes. Examples are studies that use experience sampling data and autoregressive modeling to investigate emotion dynamics and between-person differences therein. Such designs often involve multiple measurements per day and multiple days per person, and it is not clear how this nesting of the data should be accounted for: That is, should such data be considered as two-level data (which is common practice at this point), with occasions nested in persons, or as three-level data with beeps nested in days which are nested in persons. We show that a significance test of the day-level variance in an empty three-level model is not reliable when there is autocorrelation. Furthermore, we show that misspecifying the number of levels can lead to spurious or misleading findings, such as inflated variance or autoregression estimates. Throughout the paper we present instructions and R code for the implementation of the proposed models, which includes a novel three-level AR(1) model that estimates moment-to-moment inertia and day-to-day inertia. Based on our simulations we recommend model selection using autoregressive multilevel models in combination with the AIC. We illustrate this method using empirical emotion data from two independent samples, and discuss the implications and the relevance of the existence of a day level for the field

Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data

The Experience Sampling Method is a common approach in psychological research for collecting intensive longitudinal data with high ecological validity. One characteristic of ESM data is that it is often unequally spaced, because the measurement intervals within a day are deliberately varied, and measurement continues over several days. This poses a problem for discrete-time (DT) modeling approaches, which are based on the assumption that all measurements are equally spaced. Nevertheless, DT approaches such as (vector) autoregressive modeling are often used to analyze ESM data, for instance in the context of affective dynamics research. There are equivalent continuous-time (CT) models, but they are more difficult to implement. In this paper we take a pragmatic approach and evaluate the practical relevance of the violated model assumption in DT AR(1) and VAR(1) models, for the N = 1 case. We use simulated data under an ESM measurement design to investigate the bias in the parameters of interest under four different model implementations, ranging from the true CT model that accounts for all the exact measurement times, to the crudest possible DT model implementation, where even the nighttime is treated as a regular interval. An analysis of empirical affect data illustrates how the differences between DT and CT modeling can play out in practice. We find that the size and the direction of the bias in DT (V)AR models for unequally spaced ESM data depend quite strongly on the true parameter in addition to data characteristics. Our recommendation is to use CT modeling whenever possible, especially now that new software implementations have become available.Peer Reviewe

On the use of mixed Markov models for intensive longitudinal data

Markov modeling presents an attractive analytical framework for researchers who are interested in state-switching processes occurring within a person, dyad, family, group, or other system over time. Markov modeling is flexible and can be used with various types of data to study observed or latent state-switching processes, and can include subject-specific random effects to account for heterogeneity. We focus on the application of mixed Markov models to intensive longitudinal data sets in psychology, which are becoming ever more common and provide a rich description of each subject's process. We examine how specifications of a Markov model change when continuous random effect distributions are included, and how mixed Markov models can be used in the intensive longitudinal research context. Advantages of Bayesian estimation are discussed and the approach is illustrated by two empirical applications.status: publishe

Best practice for passaging murine embryonic enteric neuronal cell line before differentiation

The enteric nervous system (ENS) is a complex network of neurons in the gut, regulating many local, vital functions of the gastro-intestinal tract. The ENS is also part of the bidirectional gut-brain axis. The murine immorto fetal enteric neuronal (IM-FEN) cell line was chosen as a model to study enteric neurons. This cell line can be differentiated into cells with a neuronal phenotype, although they do not produce action potentials in vitro. It was concluded that the differentiation process in our laboratory was successful, based on positive staining for neuronal proteins. Proliferating IM-FEN cells have an unstable growth rate in our laboratory. An indicator of growth rate was calculated, and this indicator was found to be related to seeding density and number of days in culture, and was unrelated to person culturing, previous overconfluency or passage number. The indicator of growth rate was also unrelated to successful use of differentiated cells in follow-up experiments. We recommend the following conditions for optimal culture of IM-FEN cells. Keep cells in culture until 80 % confluent before passaging, seed cells at a density of 0.0133 million cells per cm2, and anticipate on unstable growth rates and the risk for overconfluency