Sound Perception:Encapsulating Intangible Voice Memories in a Physical Memento

We live in a very busy world with a variety of sensory stimulation including the olfactory, visual, tactile, and auditory. The five senses are triggered by our surroundings and help us to form meaning about the world.ⅰ Based on where someone grows up, she or he is introduced to various sites and sounds, affecting how they interpret the world. Sounds relate meaning through the association between hearing, memory and an event. Hearing is one of the learning processes, in which individuals give, receive, and store information. We typically rely on our five senses, which contribute to the process of understanding, communicating, and comprehending information. Moving beyond visual perception requires systematic attention to individual learning modalities.ⅱ Sound is one of the developing areas in the field of perception that moves beyond vision to help people understand nature, objects, narratives and varieties of perception. In order to comprehend how people hear, it is important to understand the role of perception. Sound functions as a signal, but also varies according to the capacity to hear. An individual’s physical ability to hear, and their unique experiences with sound, differ from one person to the next, and can result in a range of emotions and reactions. Certain sounds, like the voice of a loved one, also have the power to trigger emotion and convey meaning due to the association between hearing, memory and specific events from one›s past In short, the three aspects of sound perception–signal, hearing, and emotional reaction–play an integral role in auditory perception and the subjectivity of sound. However, the value of sound is often taken for granted or viewed as secondary to visual perception. This thesis will explore the value of sound perception by investigating two of its primary aspects–hearing and emotional response–in application to memory. Through a series of experiential objects, that trigger the senses. The aim is to utilize design to memorialize precious sounds in order to raise awareness about the emotional value of sound to the human experience

Spatial Decision Support System for Animal Diseases

in this paper, a Spatial Decision Support System (SDSS) was presented to help decision makers in the decision making process. The proposed spatial decision support system utilizes the capabilities of Geographic Information System (GIS), Data warehouse and Online Analytical Processing (OLAP) to provide decision makers with their needed information about the infected animals, infected places and diseases outbreaks. This information is displayed as reports or charts or allocated in a map which illustrates the most and the least affected places in an easy and fast way.so that, decision makers can take the right decision to control the spread of diseases outbreaks. The proposed SDSS consists of three databases namely: TADinfo, BOVIS and Climate databases. Data warehouse generated from integrating those three databases and diagnosis data mart is subset of that data warehouse. OLAP capabilities integrated with data warehouse to enable decision makers browse diagnosis data from different views and generate needed reports and charts. The proposed SDSS enhanced with GIS capabilities to make various spatial analysis on diagnosis data and visualize the results as maps. The experimental results show that the proposed system can provide the decision makers with their needed information in a fast and easy way

Can Chronic Nitric Oxide Inhibition Improve Liver and Renal Dysfunction in Bile Duct Ligated Rats?

The aims of the present work were to study the effects of chronic NO inhibition on liver cirrhosis and to analyze its relationship with liver and kidney damage markers. Two inhibitors of NO synthesis (inducible NO synthase (iNOS) inhibitor, aminoguanidine (AG), and nonselective NOS inhibitor, L-nitroarginine methyl ester (L-NAME)) were administered for 6 weeks to bile duct ligated (BDL) rats 3 days after surgery. The present study showed that BDL was associated with liver injury and renal impairment. BDL increased liver NO content and myeloperoxidase (MPO) activity. This was corroborated by increased oxidative stress, TNF-α, TGF-1β, and MMP-13 genes overexpression. Although both drugs reduced NO synthesis and TNF-α gene overexpression, only AG improved renal dysfunction and liver damage and reduced liver oxidative stress. However, L-NAME exacerbated liver and renal dysfunction. Both drugs failed to modulate TGF-1β and MMP-13 genes overexpression. In conclusion, inhibition of NO production by constitutive nitric oxide synthase (cNOS) plays a crucial role in liver injury and renal dysfunction while inhibition of iNOS by AG has beneficial effect. TNF-α is not the main cytokine responsible for liver injury in BDL model. Nitric oxide inhibition did not stop the progression of cholestatic liver damage

Model Based Design Environment for the Embedded System Case Study: Inverter Power Supply

学位記番号：工博甲43

Loss of locus coeruleus noradrenergic neurons alters the inflammatory response to LPS in substantia nigra but does not affect nigral cell loss

This is the accepted version of the following article: Mahmoud M. Iravani, Mona Sadeghian, Sarah Rose and Peter Jenner, “Loss of locus coeruleus noradrenergic neurons alters the inflammatory response to LPS in substantia nigra but does not affect nigral cell loss”, Journal of Neural Transmission, Vol. 121(12): 1493-1505, first published online 30 April 2014. The version of record is available online via doi: 10.1007/s00702-014-1223-1. © Springer-Verlag Wien 2014In Parkinson's disease (PD), destruction of noradrenergic neurons in the locus coeruleus (LC) may precede damage to nigral cells and subsequently exaggerate dopaminergic cell loss. We examine if destruction of the locus coeruleus with N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP-4) alters dopaminergic cell loss in substantia nigra (SN) initiated by lipopolysaccharide (LPS) in the rat through an effect on glial cell activation. In rats, a single intraperitoneal dose of DSP-4 administered 8 days previously, caused a marked loss of tyrosine hydroxylase positive neurons in LC but no change in dopaminergic cell number in SN. Unilateral nigral LPS administration resulted in marked dopaminergic cell death with reactive microgliosis associated with enhanced p47 phox in OX-6 and OX-42 positive microglia. There was proliferation of inducible nitric oxide synthase (iNOS)-positive cells, formation of 3-nitrotyrosine (3-NT) and proliferation of astrocytes that expressed glial cell line-derived neurotrophic factor (GDNF). Following combined DSP-4 treatment and subsequent administration of LPS, unexpectedly, no further loss of tyrosine hydroxylase (TH)-immunoreactivity (-ir) occurred in the SN compared to the effects of LPS alone. However, there was a marked alteration in the morphology of microglial cell and a reduction of 3-NT- and iNOS-ir was evident. Expression of p47 phox was downregulated in microglia but up-regulated in TH-ir neurons. No further change in GFAP-ir was observed compared to that produced by DSP-4 alone or LPS alone, but the expression of GDNF was markedly reduced. This study suggests that in contrast to previous reports, prior LC damage does not influence subsequent nigral dopaminergic cell degeneration induced by LPS. Rather it appears to attenuate the microglial response thought to contribute to disease progression in PD.Peer reviewedFinal Accepted Versio

Characterization of Ancient Egyptian Wall Paintings, the Excavations of Cairo University at Saqqara

The present study aims at characterizing some Egyptian wall paintings discovered during the excavations of Cairo University (since 1988 and recently in 2005) at Saqqara area in the south of Cairo. There, a number of tombs dating back to the 19th dynasty (c.1293–1185 BC) were discovered. The walls of these tombs are carved with bass and raised reliefs and painted with different colours. The characterization of the wall paintings was done by means of optical microscopy (OM), scanning electron microscopy (backscattered electron mode, BSE) equipped with an energy dispersive X-ray detector (EDS), micro XRF spectrometry (µ-XRF), and X-ray diffraction analysis (XRD). The analysis of the examined samples indicated that the blue pigment is Egyptian blue (Cuprorivaite), the green pigment is Egyptian green, the red pigment is red ochre, and the yellow pigment is a blended layer of yellow ochre and orpiment (As2S3). The results will help in providing an image concerning some painting materials used during the new Kingdom in ancient Egyp

NARINGIN AND RUTIN PREVENT D-GALACTOSAMINE-INDUCED HEPATIC INJURY IN RATS VIA ATTENUATION OF THE INFLAMMATORY CASCADE AND OXIDATIVE STRESS

The dried stems and leaves of Citrus jambhiri Lush. (Rutaceae) were extracted with aqueous methanol and the extracts were fractionated using light petroleum, chloroform and ethyl acetate. Column chromatography of the ethyl acetate fractions resulted in the isolation of naringin, rutin, hesperidin, and neohesperidin. Their structures were identified by MS and different NMR techniques. Liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) of these fractions allowed the identification 7 flavonoid glycosides. Hepatoprotective properties of naringin and rutin were evaluated in d-galactosamine (d-GalN)-induced hepatic injury in rats. d-GalN increased serum aminotransferase activity, total bilirubin, liver tumor necrosis factor-α level (TNF-α), hepatic lipid peroxidation, nuclear factor κB and decreased hepatic glutathione content, IL-10 levels and the IL-10/TNF-α ratio. These changes were attenuated in rats pretreated with rutin and naringin (40 mg/kg body weight). They increased liver IL-10 levels and the IL-10/TNF-α ratio. Rutin but not naringin down-regulated NF-κB gene expression and decreased gamma-glutamyltransferase (GGT) activity

Bacterial Biofilm Growth on Various Dental Stabilization Systems for Avulsed and Luxated Teeth

With the increased incidence of traumatic injuries and the advanced understanding of the periodontal and alveolar healing process, teeth splinting has become a common practice for stabilizing traumatized teeth. Consequently, several splinting materials and techniques have been introduced in the past few years. Despite the detrimental role of bacterial biofilm on healing, the level of biofilm development on these material surfaces has not been well investigated. Bacterial biofilms are severely detrimental for periodontal healing of avulsed and luxated teeth. Thus, biofilm growth becomes a critical factor in selecting the material of choice for dental splints. In this study, we aim to assess the level of oral biofilm growth on four different splinting systems: Ribbond©, orthodontic NiTi wire, monofilament fishing line, and Titanium Trauma Splint. A total of 72 extracted anterior teeth were divided into four groups. We splinted six rows of three teeth each per group. The teeth selected were caries-free and periodontitis-free at the time of extraction. To assess biofilm growth, a supragingival dental plaque sample was cultured and directly inoculated into all groups. After 7 days, bacterial growth was quantified by live/dead fluorescent microscopy assay and colony forming unit counts (CFU). Using one-way ANOVA and Bonferroni’s post hoc tests, we demonstrated that all splint systems allowed for bacterial growth. However, the Titanium Trauma Splint (TTS) allowed for the least amount of biofilm growth compared to other splint systems

TOMATO DISEASE DETECTION MODEL BASED ON DENSENET AND TRANSFER LEARNING

Plant diseases are a foremost risk to the safety of food. They have the potential to significantly reduce agricultural products quality and quantity. In agriculture sectors, it is the most prominent challenge to recognize plant diseases. In computer vision, the Convolutional Neural Network (CNN) produces good results when solving image classification tasks. For plant disease diagnosis, many deep learning architectures have been applied. This paper introduces a transfer learning based model for detecting tomato leaf diseases. This study proposes a model of DenseNet201 as a transfer learning-based model and CNN classifier. A comparison study between four deep learning models (VGG16, Inception V3, ResNet152V2 and DenseNet201) done in order to determine the best accuracy in using transfer learning in plant disease detection. The used images dataset contains 22930 photos of tomato leaves in 10 different classes, 9 disorders and one healthy class. In our experimental, the results shows that the proposed model achieves the highest training accuracy of 99.84% and validation accuracy of 99.30%