Das Schädel - Hirn - Trauma im Kindesalter

In der vorliegenden Studie wurden in einem Zeitraum von 1985 bis 1995, 3487 Kinder mit Schädel-Hirn-Trauma retrospektiv untersucht. Analysiert wurden die Unfallursachen, Unfallhäufigkeit und Unfallort, der klinische und neurologische Befund und die im Rahmen der posttraumatischen Klärung durchgeführte EEG-Kontrollen. In Abhängigkeit vom Alter waren die Gipfel der Unfallhäufigkeiten um das zweite, achte und zwölfte Lebensjahr. In allen Altersstufen waren Jungen etwa doppelt so häufig von Schädel-Hirn-Traumata betroffen als Mädchen. Am häufigsten war das Schädel-Hirn-Trauma in allen Altersstufen Folge eines Sturzes und dies meistens von höheren Möbelstücken. Im Kleinkindesalter waren Spielunfälle doppelt so häufig wie Verkehrsunfälle. Unter den untersuchten Schädel-Hirn-Traumata überwogen mit 85% Schädelprellungen und commotiones. 10% der untersuchten Kinder nach Schädel-Hirn-Trauma hatten eine Schädelfraktur. Die Häufigkeit von Schädelfrakturen war im Säuglingsalter am höchsten und ging mit zunehmendem Alter zurück. Hirnblutungen fanden sich in der Studie bei 8% der Kinder mit einem Gipfel im 1. Lebensjahr. Mit zunehmendem Alter waren die Hirnblutungen rückläufig. Die EEG-Kontrollen wurden am dritten, siebten und einundzwanzigsten Tag durchgeführt. Hier standen die Schwere und die Art der EEG - Veränderungen in keinem klaren Zusammenhang zum Ableitungszeitpunkt. Alterationen der Grundrhythmus waren die häufigsten Veränderungen

Simulation and Modeling of Silicon Based Emerging Nanodevices: From Device to Circuit Level

Nanostructure based devices are very promising candidates for the emerging nanotechnologies with advantage in terms of power consumption and functional density. Nanowire Field Effect Transistor (NWFET) and Single Electron Transistor (SET) are the focus of this work. The serious challenges faced by the MOSFET due to scaling limits can be solved by these devices. NWFET provides better gate control and overcomes the short channel effects. SET operates in the quantum confinement regime where the basic operation of MOSFET becomes a challenge. SET works better when the dimensions are small encouraging the process of scaling down. Because of these characteristics of the nanodevices, they have achieved a huge interest from the viewpoint of theoretical as well as applied electronics. The studies focus on the understanding of the basic transport characteristics of the devices. The necessity is to develop a model which is efficient, can be used at circuit level and also provides physical insights of the device. The first part of this work focuses on developing the model for SET and to implement it at the circuit level. The transport properties of SET are studied through quantum simulations. The behavioral characterization of the device is performed and the effect of different device parameters on the transport is studied. Furthermore, the impact of gate voltage is analyzed which modulates the current by shifting the energy levels of the device. After observing the transport through SET, a model is developed that efficiently evaluates the IV characteristics of the device. The quantum simulations are used as reference and a huge computational over-head is achieved while maintaining accuracy. Then the model is implemented in hardware descriptive language showing its functional variability at circuit level by designing some logic circuits like AND, OR and FA. In the second part, the performance of the nanoarrays based on NWFET is characterized. A device level model is developed to evaluate the gate capacitance and drain current of NWFET. Starting from the output of the model, in-house simulator is modified and used to evaluate the switching activity of the devices in nanoarray. A nanoarray implementation for bio-sequence alignment based on a systolic array is realized and its essential performance is evaluated. The power consumption, area and performance of the nanoarray implementation are compared with CMOS implementation. A wide solution space can be explored to find the optimal solution trading power and performance and considering the technological limitations of a realistic implementation

Study the effect of thin film thickness on the optical features of (IR5 laser dye/CdSe nanoparticles) samples

The linear optical features such as (transmittance T, absorbance A, the effective length , absorption coefficient and refractive index ) for the thin films samples of (3x10-3 mol/l of (IR5) laser dye, 0.02 gm of (CdS) nanoparticles and 0.04 gm of pp polymer) had been studied at different values of film thickness in one time and at different number of Yb:GdVO4 laser pulses. The non-linear optical features in terms of transmittance difference Δ−, non-linear refractive index 2, non–linear phase shift Δ non-linear absorption coefficient and minimum normalized transmittance () have been computed in relation to obtained normalized transmittance data from setup of Z-scan with open and closed apertures, calculated for (3x10-3 mol/l of (IR5) laser dye, 0.02 gm of (CdSe) nanoparticles and 0.04 gm of (pp) polymer) thin films at different values of film thickness at in one time and at different Yb:GdVO4 laser pulses. Thick films causes in deleting the non-linear effects generated by different layers. The (CdSe) nanoparticles leads to an absorption shifting of the wavelengths to lengthier wavelengths of red shift. So, this can be used in selecting the nanoparticles and medium with applicable exciting wavelengths. The film thickness and the laser pulses have the main effects in consolidating the Non-linear optical features

A study on the effect of green marketing on consumers’ purchasing intention

During the past two decades, there have been significant damages on environment such as ozone layer depletion, global warming effects, etc. and people are getting more concerned about taking necessary actions to help environment. The purpose of this paper is to study the effect of green marketing on consumers’ purchasing intention in dairy industry. The proposed study designs a questionnaire and distributes it among 154 randomly selected people who purchase dairy products in four different regions of city of Babol, located in north region of Iran. Using structural equation modeling, the study has detected that green marketing influences on consumers’ purchasing intention, positively

The effect of thin film coatings and nitriding on the mechanical properties and wear resistance of tool steel

The wear characteristics and mechanical properties of three different coatings deposited on different types of tool steel have been investigated. Four types of tool steels D2, D3, Vanadis 4 and Vanadis 10 were used as substrate materials. These materials were cut to the desired dimension 55mm x 25mm x 5mm and prepared for treatment and coating. The specimens were nitrided using gas nitriding, a case depth of 150 |im was achieved in all cases. Three types of coating TiC, TiN and AI2O3 were commercially deposited on the treated and untreated samples using the magnetron sputtering technique. A thin film coating of ~ 4|nm thickness was measured on each sample. The coatings were characterized in their thickness, hardness, adhesion and chemical composition. A wear test rig designed, constructed and commissioned at DCU was adapted for the wear tests. Wear characteristics of coated, nitrided, and prenitrided coated samples were investigated and compared to the uncoated samples characteristics. The microhardness of the surfaces coated and nitrided show an increase in hardness, with the highest hardness in the case of TiC coated Vanadis 10 samples. Wear test results show that titanium carbide coatings and nitriding treatment prove to have good wear resistance, on the other hand titanium nitride showed slight improve in wear resistance while alumina did not. Nitriding of the samples prior to the deposition of the coatings improved the wear resistance of the substrate materials particularly in the case of TiN and AI2O3 coatings. Adhesion evaluation of the coatings confirmed the observation of the wear and hardness. The substrate materials have a profound effect on the wear resistance and mechanical properties of the coated surfaces

A User-Centric and Sentiment Aware Privacy-Disclosure Detection Framework Based on Multi-Input Neural Network

Data and information privacy is a major concern of today’s world. More specifically, users’ digital privacy has become one of the most important issues to deal with, as advancements are being made in information sharing technology. An increasing number of users are sharing information through text messages, emails, and social media without proper awareness of privacy threats and their consequences. One approach to prevent the disclosure of private information is to identify them in a conversation and warn the dispatcher before the conveyance happens between the sender and the receiver. Another way of preventing information (sensitive) loss might be to analyze and sanitize a batch of offline documents when the data is already accumulated somewhere. However, automating the process of identifying user-centric privacy disclosure in textual data is challenging. This is because the natural language has an extremely rich form and structure with different levels of ambiguities. Therefore, we inquire after a potential framework that could bring this challenge within reach by precisely recognizing users’ privacy disclosures in a piece of text by taking into account - the authorship and sentiment (tone) of the content alongside the linguistic features and techniques. The proposed framework is considered as the supporting plugin to help text classification systems more accurately identify text that might disclose the author’s personal or private information

Modeling of Personalized Privacy Disclosure Behavior: A Formal Method Approach

In order to create user-centric and personalized privacy management tools, the underlying models must account for individual users' privacy expectations, preferences, and their ability to control their information sharing activities. Existing studies of users' privacy behavior modeling attempt to frame the problem from a request's perspective, which lack the crucial involvement of the information owner, resulting in limited or no control of policy management. Moreover, very few of them take into the consideration the aspect of correctness, explainability, usability, and acceptance of the methodologies for each user of the system. In this paper, we present a methodology to formally model, validate, and verify personalized privacy disclosure behavior based on the analysis of the user's situational decision-making process. We use a model checking tool named UPPAAL to represent users' self-reported privacy disclosure behavior by an extended form of finite state automata (FSA), and perform reachability analysis for the verification of privacy properties through computation tree logic (CTL) formulas. We also describe the practical use cases of the methodology depicting the potential of formal technique towards the design and development of user-centric behavioral modeling. This paper, through extensive amounts of experimental outcomes, contributes several insights to the area of formal methods and user-tailored privacy behavior modeling