Der Glaube an Gott in Bibel und Koran

Das arabische Wort Allah entspricht dem deutschen Wort "Gott". Dabei handelt sich nicht nur um einen Eigennamen Gottes, also lediglich um eine Form der Anrede, sondern um den Begriff "Gott" in seinem vollen Inhalt. So verwenden auch die arabischen Christen für Gott das Wort Allah. Sprachlich besteht ein Zusammenhang mit dem hebräischen Elohim, aramäisch Aloy = Allah = Gott. Hier ist zu unterscheiden zwischen Allah und Ilah, wobei das letztere Wort für irgendeinen Gott steht, Allah aber für den einen bestimmten und einzigen Gott, der nach der islamischen Lehre schon im Juden- und Christentum bekannt war. Wenn der Prophet Muhammad von Allah spricht, ist daher immer dieser eine und einzige Gott gemeint und nicht eine unbestimmte Person unter mehreren. Im Begriff Gott ist also eine gemeinsame Grundlage des Judentums, Christentums und des Islam gegeben. Allerdings haben die Bibel und der Koran verschiedene Vorstellungen von Gott, was besonders in der Beschreibung seiner Eigenschaften zu Tage tritt. ..

Novel Characteristics of Murine Bone Marrow-Derived Macrophages and Human Macrophage-Like Cells

These studies provide evidence for novel properties of macrophages derived from bone marrow stem cells. In study 1, treatment of activated mouse bone marrow-derived macrophages (BMM) with either catecholamine synthesis inhibitors (α-methyl-para-tyrosine and fusaric acid) or the β2 adrenergic receptor antagonist ICI 118,551 demonstrated that BMM produce catecholamines. The catecholamines modulated macrophage cytokine production through autocrine actions on adrenergic receptors. In study II, undifferentiated human bone marrow cells were incubated in 30% mouse L929 fibroblast conditioned medium and generated adherent cells within three days. The cells were clearly identifiable as macrophages based on surface proteins and phagocytic activity but produced only low levels of the cytokines tumor necrosis factor-α and interleukin-lβ. Cytokine production did not increase in response to the bacterial endotoxin lipopolysaccharide (LPS). Generation of these macrophage-like cells was not repeatable with other samples of human bone marrow, but the cells continue to proliferate in cell culture and will be investigated further in future studies

Clinical and ultrasonographic findings of some ocular conditions in sheep and goats

This study was carried out to describe the ultrasonographic findings in relation to the clinical symptoms of some common ocular conditions in sheep and goats. Fifty animals (32 goats and 18 sheep) with different ocular problems were examined. Ultrasonographic examination was performed using a B-mode ocular ultrasound unit, and the structure of the globe was evaluated at a depth of 4-6 cm. Early cases (n=35, 70%) showed varying ocular conditions; hypopyon, (n=8, 16%), stromal abscesses, (n=4, 8%), and anterior uveitis (n=23, 46%). Hypopyon appeared clinically as a white or yellowish material in the anterior chamber, and ultrasonographically as a hyperechoic mass in the anterior chamber. Severe iridocyclitis was noticed in acute cases of infectious keratoconjunctivitis (IKC) accompanied by blepharospasm, photophobia, excessive tearing and eyelid margin crust formation. Ultrasonographically, the pupil appeared constricted with increased hyperechoic thickening of the ciliary body. In chronic cases of IKC, corneal pigmentation (n=5, 10%) and cataract (n=10, 20%) were seen. Ultrasonographically the type and degree of cataract were diagnosed. The present study provides an inside view of the inner ocular structures during the course of certain eye diseases where ophthalmoscopic examination is not possible. Our findings, although preliminary, are relevant for the more complete diagnosis of certain external ocular conditions in sheep and goat herds

Personal identification based on mobile-based keystroke dynamics

This paper is addressing the personal identification problem by using mobile-based keystroke dynamics of touch mobile phone. The proposed approach consists of two main phases, namely feature selection and classification. The most important features are selected using Genetic Algorithm (GA). Moreover, Bagging classifier used the selected features to identify persons by matching the features of the unknown person with the labeled features. The outputs of all Bagging classifiers are fused to determine the final decision. In this experiment, a keystroke dynamics database for touch mobile phones is used. The database, which consists of four sets of features, is collected from 51 individuals and consists of 985 samples collected from males and females with different ages. The results of the proposed model conclude that the third subset of features achieved the best accuracy while the second subset achieved the worst accuracy. Moreover, the fusion of all classifiers of all ensembles will improve the accuracy and achieved results better than the individual classifiers and individual ensembles

One-dimensional vs. two-dimensional based features: Plant identification approach

The number of endangered species has been increased due to shifts in the agricultural production, climate change, and poor urban planning. This has led to investigating new methods to address the problem of plant species identification/classification. In this paper, a plant identification approach using 2D digital leaves images was proposed. The approach used two features extraction methods based on one-dimensional (1D) and two-dimensional (2D) and the Bagging classifier. For the 1D-based methods, Principal Component Analysis (PCA), Direct Linear Discriminant Analysis (DLDA), and PCA + LDA techniques were applied, while 2DPCA and 2DLDA algorithms were used for the 2D-based method. To classify the extracted features in both methods, the Bagging classifier, with the decision tree as a weak learner was used. The five variants, i.e. PCA, PCA + LDA, DLDA, 2DPCA, and 2DLDA, of the approach were tested using the Flavia public dataset which consists of 1907 colored leaves images. The accuracy of these variants was evaluated and the results showed that the 2DPCA and 2DLDA methods were much better than using the PCA, PCA + LDA, and DLDA. Furthermore, it was found that the 2DLDA method was the best one and the increase of the weak learners of the Bagging classifier yielded a better classification accuracy. Also, a comparison with the most related work showed that our approach achieved better accuracy under the same dataset and same experimental setup

One-dimensional vs. two-dimensional based features: Plant identification approach

The number of endangered species has been increased due to shifts in the agricultural production, climate change, and poor urban planning. This has led to investigating new methods to address the problem of plant species identification/classification. In this paper, a plant identification approach using 2D digital leaves images was proposed. The approach used two features extraction methods based on one-dimensional (1D) and two-dimensional (2D) and the Bagging classifier. For the 1D-based methods, Principal Component Analysis (PCA), Direct Linear Discriminant Analysis (DLDA), and PCA + LDA techniques were applied, while 2DPCA and 2DLDA algorithms were used for the 2D-based method. To classify the extracted features in both methods, the Bagging classifier, with the decision tree as a weak learner was used. The five variants, i.e. PCA, PCA + LDA, DLDA, 2DPCA, and 2DLDA, of the approach were tested using the Flavia public dataset which consists of 1907 colored leaves images. The accuracy of these variants was evaluated and the results showed that the 2DPCA and 2DLDA methods were much better than using the PCA, PCA + LDA, and DLDA. Furthermore, it was found that the 2DLDA method was the best one and the increase of the weak learners of the Bagging classifier yielded a better classification accuracy. Also, a comparison with the most related work showed that our approach achieved better accuracy under the same dataset and same experimental setup

Towards a new framework for TPM compliance testing

Trusted Computing Group (TCG) has proposed the Trusted Computing (TC) concept. Subsequently, TC becomes a common base for many new computing platforms, called Trusted Platform (TP) architecture (hardware and software) that, practically, has a built-in trusted hardware component mounted at the hardware layer and a corresponding trusted software component installed at the operating system level. The trusted hardware component is called Trusted Platform Module (TPM) whose specification has been issued by TCG group and it is implemented by the industry as a tamper- resistant integrated circuit. In practice, the security of an IT TPM-enabled system relies on the correctness of its mounted TPM. Thus, TPM testing is urgently needed to assist in building confidence of the users on the security functionality provided by the TPM. This paper presents the state of the art of the modelling methods being used in the TPM compliance testing. Finally, the paper proposes new framework criteria for TPM Testing that aim at increasing the quality of TPM testing

Nanoemulsion as a topical delivery system of antipsoriatic drugs

Psoriasis is one of the most common skin diseases, affecting 2–5% of the world's population. It is a skin autoimmune disorder, resulting in an excessive growth and aberrant differentiation of keratinocytes. Psoriasis is an incurable lifetime disease which can only be controlled and relieved through medication. Various approaches have been explored to treat the disease. Treatment of psoriasis includes topical therapy, systemic therapy and phototherapy. Topical therapy is the first line treatment and it is the most practical medication method for psoriasis patients. However, the conventional topical treatments such as gel and cream have low efficiency, poor cosmetic and aesthetic appeal, leading to poor patient compliance or adherence, while systemic and photo therapy produce significant adverse side effects. Nanoemulsion is defined as an emulsion system consisting of oil, surfactant, and water with an isotropic, transparent (or translucent) appearance. The emulsion droplet size is defined to be less than 200 nm. Nonetheless, if the emulsion has low surfactant content and is kinetically stable, a size of less than 500 nm can be accepted as nanoemulsion. A small droplet size would enhance the delivery and penetration of a drug through the psoriasis skin layer. There has been a growing interest in using nanoemulsions in topical applications, due to their high stability and their optical transparency or translucency, which make them good and very dermatologically attractive. A good selection of oils and surfactants would enhance the transdermal treatment efficacy. This review highlights the potential of drug-loaded nanoemulsions for the treatment of psoriasis towards achieving better efficacy and eliminating side effects