年官制度の本質

Uppsatsens syfte är att utreda hur företag i form av aktiebolag skall kostnadsföra organisationskostnader av olika slag. Organisationskostnader är kostnader som är kopplade till företagets organisation och förvaltning och det kan till exempel vara fråga om utredningskostnader, flyttningskostnader och förvaltningskostnader. I uppsatsen behandlas inte organisationskostnader i form av utgifter för forskning och utveckling. Uppsatsens fokus ligger på den skatterättsliga behandlingen där omfångs- och periodiseringsfrågan för organisationskostnader enligt gällande rätt diskuteras. Även den redovisningsrättsliga behandlingen diskuteras kortfattat. Idag är kostnadsföringen av de flesta organisationskostnaderna fastställd men det finns fortfarande en del frågetecken där det saknas lagrum och där det fortfarande råder osäkerhet i rättspraxis hur kostnaden skall behandlas. Avslutningsvis ges förslag på förändringar som enligt min mening skulle förenkla hanteringen av organisationskostnader för företaget. Framförallt skulle det underlätta för företaget om samtliga utredningskostnader blev omedelbart avdragsgilla

Simulation of Information Spreading on Twitter Concerning Radiation After the Fukushima Nuclear Power Plant Accident

Information spreading on social media is a crucial issue to build a safe society. In particular, during emergencies, misinformation and uncertain information can lead to social disruption and cause significant damage to our lives. Here we built a retweet network from 24 million radiation-related tweets by 1.3 million accounts in the immediate aftermath of the Fukushima nuclear power plant accident in 2011. Then we simulated the information spreading on the network to explore ways to spread scientifically accurate information. Our simulation replicated the reality in which the number of scientific evidence-based tweets experienced a gradual decline while the number of emotional tweets increased. We also showed that increasing new direct retweets from the influencers could effectively spread scientific evidence-based information in our hypothetical simulations

A visual analytics system to support the formation of a hypothesis from calcium wave data

In most species, calcium waves in the oocyte are considered common phenomena in the activation of eggs. However, the mechanism of calcium waves has not yet been clarified. By collaborating with biologists studying Caenorhabditis elegans (C. elegans), which is widely used as a model organism, we observed that the following requirements must be satisfied to form a useful hypothesis based on calcium waves captured using high-speed in vivo imaging: (1) the ability to obtain an overview of how the calcium waves are propagated and (2) the ability to understand the propagation of waves in a narrow region. However, conventional visualization methods cannot satisfy these requirements simultaneously. Therefore, we propose a visual analytics system that allows users to understand and explore calcium wave images using cross-correlation analysis of the time-series data of the Ca²⁺ fluorescence intensity at each point. The interface of this system comprises an overview visualization, a detail visualization, and user interactions to satisfy these requirements and realize exploratory visualization. Some views present an overview visualization that displays the clustering results of a directed graph calculated using cross-correlation analysis. These views enable the users to understand the overview of wave propagation, thereby helping users find a region of interest. The detail visualization shows the relationship between the region of interest and other areas. Furthermore, users can use the proposed system with overview-detail and brush-link exploration to assign meaning to the region of interest and construct a hypothesis for its role. In this paper, we demonstrate how the proposed visual analytics approach works and how new hypotheses can be formed using the analysis of C. elegans calcium waves

Visualization of JOV abstracts

Since the abstract can be found at the beginning of most scientific articles and is an essential part of the article, several attempts have been made to explore the rhetorical moves of abstracts in various research fields. These studies dealt only with accepted articles since they can be easily accessed. Although the findings of such works have some pedagogical implications for academic writing courses for young researchers who are relatively new to their fields, they do not contribute enough to the transparency of the peer review processes conducted in research fields. Increasing transparency requires considering rejected articles since they help to clarify the decision criteria in the peer review. Based on 591 abstracts of accepted or rejected articles submitted to Journal of Visualization (JOV), the present study aimed at exploring the differences between the accepted and rejected abstracts. The results show that there are significant differences in the structures of the abstracts. Since we also successfully develop a classification model for the decision using a machine-learning technique, the findings of this study have some implications for developing a semi-automatic reviewing system that can reduce the reviewer’s burden and increase the review quality

Urine diacetylated spermine might be a nonspecific tumor marker in canine neoplasia

Diacetylated spermine, a polyamine, is clinically used as a tumor marker in human medicine. The purpose of this study was to evaluate the usefulness of diacetylated spermine as a nonspecific tumor marker in dogs. One hundred six dogs were randomly selected and divided into 4 groups (cancer-bearing, n=23; control, n=44; young, n=24; inflammatory, n=15). Urine samples were collected to measure diacetylated spermine and creatinine levels. The diacetylated spermine concentration was determined by enzyme-linked immunoassay, standardized by creatinine concentration. The urine diacetylated spermine concentration was markedly significant elevated in cancer-bearing dogs, as compared to that in control dogs (P=0.0081). Whilst the urine diacetylated spermine level in cancer-bearing group was not markedly different from that in the young group, there was significant different between levels in the control and young groups (P=0.019). No significant difference was observed between the inflammatory and cancer-bearing groups. It is suggested that urine diacetylated spermineis a useful tumor marker in dogs over 2 years of age

Twitter use in scientific communication revealed by visualization of information spreading by influencers within half a year after the Fukushima Daiichi nuclear power plant accident.

Scientific communication through social media, particularly Twitter has been gaining importance in recent years. As such, it is critical to understand how information is transmitted and dispersed through outlets such as Twitter, particularly in emergency situations where there is an urgent need to relay scientific information. The purpose of this study is to examine how original tweets and retweets on Twitter were used to diffuse radiation related information after the Fukushima Daiichi nuclear power plant accident. Out of the Twitter database, we purchased all tweets (including replies) and retweets related to Fukushima Daiichi nuclear power plant accident and or radiation sent from March 2nd, 2011 to September 15th, 2011. This time frame represents the first six months after the East Japan earthquake, which occurred on March 11th, 2011. Using the obtained data, we examined the number of tweets and retweets and found that only a small number of Twitter users were the source of the original posts that were retweeted during the study period. We have termed these specific accounts as "influencers". We identified the top 100 influencers and classified the contents of their tweets into 3 groups by analyzing the document vectors of the text. Then, we examined the number of retweets for each of the 3 groups of influencers, and created a retweet network diagram to assess how the contents of their tweets were being spread. The keyword "radiation" was mentioned in over 24 million tweets and retweets during the study period. Retweets accounted for roughly half (49.7%) of this number, and the top 2% of Twitter accounts defined as "influencers" were the source of the original posts that accounted for 80.3% of the total retweets. The majority of the top 100 influencers had individual Twitter accounts bearing real names. While retweets were intensively diffused within a fixed population, especially within the same groups with similar document vectors, a group of influencers accounted for the majority of retweets one month after the disaster, and the share of each group did not change even after proven scientific information became more available