Nieuwere inzichten omtrent prikkels bij planten

Saxa crescunt, Plantae crescunt et vivunt, Animalia crescunt, vivunt et sentiunt, zoo luidt een oud adagium, dat kort en kernachtig wenschte aan te duiden, welk verschil men aantreft tusschen de drie rijken der natuur. Hoe ver staan wij met onze tegenwoordige kennis daarvan af! Vooreerst al, omdat de vergelijking van den groei van een kristal met dien van een levend wezen ons toch wel wat al te oppervlakkig lijkt! De grens tusschen de saxa aan den eenen, de georganiseerde wereld aan den anderen kant, is veel scherper dan men vroeger ooit gedacht heeft. Maar daarentegen is de scheidingslijn tusschen plant en dier niet te trekken en het verschil zeer zeker niet te zoeken in het reactievermogen ten opzichte van uitwendige prikkels. Immers zoo zou ik het „sentiunt" in onze tegenwoordige termen willen vertalen

Ondoelmatigheid in de levende natuur

Er bestaat een oud verhaal van algemeene bekendheid, waarvan de bedoeling is, de waanwijsheid van menschen te doen uitkomen, die kritiek op de natuur uitoefenen. Een man betreurt het, dat aan de boomen niet even groote vruchten hangen als de pompoenen, die hij naast zich op den grond ziet groeien; daarna legt hij zich neer onder een boom en valt in slaap. Een van de vruchten, die hem zooeven te klein toeschenen, valt en zijn neus komt er in onzachte aanraking mede. Hij looft nu de wijsheid van den Schepper en ziet zijn eigen domheid in, want had die vrucht de grootte en het gewicht van een pompoen gehad, dan zou zijn hoofd zeker verbrijzeld zijn geworden

Die Bedeutung des Wuchsstoffes (Auxin) für Wachstum, photo- und geotropische Krümmungen

Neue Zellen entstehen durch Teilung an den sog. Vegetationspunkten, welche man beim Sproß in der Knospe, bei der Wurzel an der äußersten Spitze antrifft. Mit dieser Zellteilung ist nur eine sehr geringe Volumvergrößerung verbunden. Diese findet erst statt, wenn die Zellen selbst zu wachsen anfangen; man spricht dann von Zellstreckung. Die Plasmamenge vermehrt sich dabei kaum, erheblich dagegen der zentrale Saftraum mit dem darin enthaltenen Zellsaft; auch die Menge der Zellhaut nimmt zu

The Investigation of Structure Heterogeneous Joint Welds in Pipelines

Welding joints of dissimilar steels don’t withstand design life. One of the important causes of premature destructions can be the acceleration of steel structural degradation due to cyclic mechanical and thermal gradients. Two zones of tube from steel 12H18N9T, exhibiting the structural instability at early stages of the decomposition of a supersaturated solid austenite solution, were subjected to investigation. Methods of x-ray spectral and structure analysis, micro hardnessmetry were applied for the research. Made the following conclusions, inside and outside tube wall surfaces of hazardous zones in welding joint have different technological and resource characteristics. The microhardness very sensitive to changes of metal structure and can be regarded as integral characteristic of strength and ductility. The welding processes are responsible for the further fibering of tube wall structure, they impact to the characteristics of hot-resistance and long-term strength due to development of ring cracks in the welding joint of pipeline. The monitoring of microhardness and structural phase conversions can be used for control by changes of mechanical properties in result of post welding and reductive heat treatment of welding joints

Analysis of Client Anonymity in the Tor Network

The Tor Network has emerged as the most popular service providing sender anonymity on the Internet. It is a community-driven network with most of the infrastructure operated by volunteers. Peer-to-Peer (P2P) file sharing applications, such as BitTorrent, take up a large portion of the available resources in Tor, which reduce the quality of service for those browsing the web through Tor. In this thesis, experiences from operating a Tor exit relay with a reduced exit policy are recounted. Additionally, the lifecycle of the exit relay is presented and an analysis of the application distribution of exit traffic is done. This analysis uncovers that the reduced exit policy may reduce the BitTorrent traffic share as the total, byte-wise traffic share constituted by BitTorrent was 25.4%, which is lower than in similar analyses done earlier. Tor is a low latency service, thus it is possible that packet latency can leak information about either the source, the destination or both ends of the encrypted Tor traffic. There have been numerous proposals for side-channel attacks in the Tor Network, with one of the most interesting being the website fingerprinting attack. The website fingerprinting attack attempts to map encrypted client-side traffic with a web page by utilizing side-channel information from web page visits to train a machine learning classifier, which in turn is used to predict the web page corresponding to encrypted, client-side Tor traffic. This thesis aims to review existing website fingerprinting attacks as well as to propose a basic attack sorting under this category. The thesis argues that it is feasible that state of the art web site fingerprinting attacks can be applied in a real-world scenario under the assumption that certain Tor users visit censored web pages repeatedly. Website fingerprinting attacks proposed up until now attempt to identify individual web pages from an encrypted traffic stream. This thesis proposes a web site fingerprinting attack, an attack related to the general website fingerprinting attack, but instead of web pages, it attempts to identify web sites. The attack utilizes, among other things, the browsing pattern to attempt to map encrypted client-side traffic to a web site. The browsing pattern data is collected from a test group made up of volunteers who are asked to browse web sites as they feel natural. In one of the most successful experiments, the attack resulted in a True Positive Rate (TPR) of 91.7% and a corresponding False Positive Rate (FPR) of 0.95% from a total of 222 attempted web site predictions

Better to be Approximately Right than Precisely Wrong: Empirical Insights into Parameter Choice and Industry Effects in the KMV-Merton Corporate Default Risk Model

We examine the choice of strike price and time to maturity in the standard academic application of the KMV-Merton model based on Merton’s (1974) structural credit risk model. We define the standard academic application utilises a fixed proportion of debt for strike price, and maturity is assumed in 1 year. The proxy values for each parameter we analyse are combinations of both random guesses and more sophisticated choices. We extend the thesis by introducing a conditional test on aggregated industry categories. Results are compared to (1) the standard academic parameters, (2) a naive alternative which applies the functional form of Merton, and (3) an experimental approach where we match expected default frequencies to respective maturities. We find that the standard strike price performs better than the alternative parameters, and we fail to find a combination of strike price and time to maturity that overall yields increased explanatory and predictive power. However, when conditioning the analysis on aggregated industries, we find increased explanatory and predictive power. The best performing parameter combinations will for some industries perform better than the naive model, which the standard model could not. The functional form of the KMV model proves relevant, as it manages to capture variation in corporate bond spreads. Interestingly, the naive model proposed by Bharath & Shumway (2008) performs surprisingly well compared to more complex approaches. We believe this stems from estimation errors, particularly in volatility of asset

an evaluation of data sources to determine the number of people living with HIV who are receiving antiretroviral therapy in Germany

Background This study aimed to determine the number of people living with HIV receiving antiretroviral therapy (ART) between 2006 and 2013 in Germany by using the available numbers of antiretroviral drug prescriptions and treatment data from the ClinSurv HIV cohort (CSH). Methods The CSH is a multi-centre, open, long-term observational cohort study with an average number of 10.400 patients in the study period 2006–2013. ART has been documented on average for 86% of those CSH patients and medication history is well documented in the CSH. The antiretroviral prescription data (APD) are reported by billing centres for pharmacies covering >99% of nationwide pharmacy sales of all individuals with statutory health insurance (SHI) in Germany (~85%). Exactly one thiacytidine-containing medication (TCM) with either emtricitabine or lamivudine is present in all antiretroviral fixed-dose combinations (FDCs). Thus, each daily dose of TCM documented in the APD is presumed to be representative of one person per day receiving ART. The proportion of non-TCM regimen days in the CSH was used to determine the corresponding number of individuals in the APD. Results The proportion of CSH patients receiving TCMs increased continuously over time (from 85% to 93%; 2006–2013). In contrast, treatment interruptions declined remarkably (from 11% to 2%; 2006–2013). The total number of HIV-infected people with ART experience in Germany increased from 31,500 (95% CI 31,000-32,000) individuals to 54,000 (95% CI 53,000-55,500) over the observation period (including 16.3% without SHI and persons who had interrupted ART). An average increase of approximately 2,900 persons receiving ART was observed annually in Germany. Conclusions A substantial increase in the number of people receiving ART was observed from 2006 to 2013 in Germany. Currently, the majority (93%) of antiretroviral regimens in the CSH included TCMs with ongoing use of FDCs. Based on these results, the future number of people receiving ART could be estimated by exclusively using TCM prescriptions, assuming that treatment guidelines will not change with respect to TCM use in ART regimens

Forecasting freight rates volatility – A hybrid forecasting comparison approach

Shipping er en svært volatil sektor, hvor markedsaktører med stor risikotoleranse kontinuerlig balanserer risiko og avkastning. Selv om volatiliteten i shippingsektoren har blitt modellert i begrenset omfang ved bruk av standard GARCH-modeller, har maskinlæring og komponentvolatilitetsmodeller ennå ikke blitt brukt til å utarbeide volatilitetsprognoser. Denne masteroppgaven undersøker hvordan hybridmodeller presterer i forhold til tradisjonelle GARCH-modeller og populære maskinlæringsmodeller for å predikere volatilitet i tørrbulk- og tankrater. Treffsikkerheten til modellene vurderes basert på tre metoder: minimalt aggregert tap, Model Confidence Set og Superior Predictive Ability-testen. Våre resultater viser at maskinlæringsmodellene presterer bedre enn GARCH-modellene i kortsiktige prognoser, hvor hybridmodellen Stacked Average, som inkluderer eksogene variabler, gir de mest robuste prognoseresultatene. De økonometriske modellene har derimot bedre treffsikkerhet over lengre prognoseperioder, tilsvarende ukentlige og månedlige intervaller – spesielt når markedsbalanseindeksene integreres gjennom GARCH-MIDAS-spesifikasjonen. For de mest volatile seriene peker resultatene mot at en kombinasjon av modellene er den mest optimale konfigurasjonen på tvers av prognoseperiodene. Følgelig gir denne masteroppgaven et solid bidrag til forskningen på volatilitetsdynamikken i shippingrater og hvordan lavfrekvente makroøkonomiske indikatorer kan anvendes i prognosemodeller. Dette er av stor verdi for alle markedsaktører i shippingsektoren som ønsker å forbedre sine analyser og risikostyring.Shipping is an inherently volatile sector, where market participants with high-risk tolerance constantly strive to navigate risk and reward. While volatility dynamics in the shipping sector have been modeled to some extent using standard GARCH models, machine learning and component volatility models have not yet been applied in volatility forecasting. This thesis examines the performance of hybrid models compared to traditional GARCH and popular machine learning models for forecasting volatility in dry bulk and tanker freight rates. Forecasting accuracy is assessed through three approaches: minimum aggregated loss, the Model Confidence Set, and the Superior Predictive Ability test. Our results suggest that machine learning models significantly outperform GARCH models in short-term forecasting, with the hybrid model Stacked Average incorporating exogenous features yielding the most robust results. Econometric models demonstrate superior performance over extended forecast horizons, resembling weekly and monthly forecast steps, particularly when market tightness indices are integrated through the GARCH-MIDAS specification. For the most volatile series, the results point towards a combination of the models being the most optimal configuration across the forecasting steps. Consequently, this thesis makes an innovative contribution to the research on shipping rate volatility dynamics and the relationship with low-frequency macroeconomic indicators – valuable insights that significantly empower shipping market participants to enhance their forecasting models and risk management strategies

Ilmkuulus Italia rööwlipealik Rinaldo Rinaldini : Kõige suurem Italia rahwa roman

40. andel puuduvad viimased lehed.https://www.ester.ee/record=b1372904*es