Effect of cultivation conditions on growth and antifungal activity of Mycena leptocephala

Growth and production of antifungal agent by Mycena leptocephala was investigated in different culture media composition at various initial pH and temperatures. Maximum growth and activity was observed at the initial pH of 5.5 and 25oC. No detectable growth and activity was observed at pH of 3.5 and 7.5. Growth of the fungus and antifungal activity were also very low at 37oC and 20oC. The organism grew better and culture extract showed higher level of antifungal activity when malt extract plus glucose were used as carbon source and yeast extract was used as nitrogen source. Meanwhile the lowest level of growth and antifungal activity were observed when starch was used as carbon source for growth of the fungus. Key Words: Culture conditions, basidiomycetes, bioactive compounds, carbon source, nitrogen source and temperature. African Journal of Biotechnology Vol.3(11) 2004: 606-60

Fault Type Estimation in Power Systems

Abstract: This paper presents a novel approach for fault type estimation in power systems. The Fault type estimation is the first step to estimate instantaneous voltage, voltage sag magnitude and duration in a three-phase system at fault duration. The approach is based on time-domain state estimation where redundant measurements are available. The current based model allows a linear mapping between the measured variable and the states to be estimated. This paper shows a possible for fault instance detection, fault location identification and fault type estimation utilizing residual analysis and topology error processing. The idea is that the fault status does not change measurement matrix dimensions but changes some elements of the measurement matrix. The paper addresses how to rebuilt measurement matrix for each type of faults. The proposed algorithm is shown that the method has high effectiveness and high performance for forecasting fault type and for estimating instantaneous bus voltage. The performance of the novel approach is tested on IEEE 14-bus test system and the results are shown

International Centre for Guidance Studies (iCeGS) Annual Review 2023 - 25th Anniversary

This publication offers a brief insight into the wide range of activities the iCeGS team has been involved with over the year and the last 25 years. It explores our contribution to policy, research and practice within the career development sector both in the UK and wider afield. iCeGS Annual Review also allows the team to reflect on our many achievements over the last year. Like other years, we feel particularly proud of several activities this year

A Novel Mutation in the OFD1 Gene in a Family with Oral-Facial-Digital Syndrome Type 1: A Case Report.

Oral-facial-digital syndrome as heterogeneous developmental conditions is characterized by abnormalities in the oral cavity, facial features and digits. Furthermore, central nervous system (CNS) abnormalities can also be part of this developmental disorder. At least 13 forms of OFDS based on their pattern of signs and symptoms have been identified so far. Type 1 which is now considered to be a ciliopathy accounts for the majority of cases. It is transmitted in an X-linked dominant pattern and caused by mutations in OFD1 gene, which can result in embryonic male lethality. In this study, we present a family suffering from orofaciodigital syndrome type I who referred to Medical Genetics Research Center, Shahid Sadoughi University of Medical Sciences in 2015. Two female siblings and their mother shared a novel 2-base pair deletion (c.1964-1965delGA) in exon 16 of OFD1 gene. Clinically, the sibling had oral, facial and brain abnormalities, whereas their mother is very mildly affected. She also had history of recurrent miscarriage of male fetus

Bayesian inference of population expansions in domestic bovines

The past population dynamics of four domestic and one wild species of bovine were estimated using Bayesian skyline plots, a coalescent Markov chain Monte Carlo method that does not require an assumed parametric model of demographic history. Four domestic species share a recent rapid population expansion not visible in the wild African buffalo (Syncerus caffer). The estimated timings of the expansions are consistent with the archaeological records of domestication

A computational model of ureteral peristalsis and an investigation into ureteral reflux.

The aim of this study is to create a computational model of the human ureteral system that accurately replicates the peristaltic movement of the ureter for a variety of physiological and pathological functions. The objectives of this research are met using our in-house fluid-structural dynamics code (CgLes-Y code). A realistic peristaltic motion of the ureter is modelled using a novel piecewise linear force model. The urodynamic responses are investigated under two conditions of a healthy and a depressed contraction force. A ureteral pressure during the contraction shows a very good agreement with corresponding clinical data. The results also show a dependency of the wall shear stresses on the contraction velocity and it confirms the presence of a high shear stress at the proximal part of the ureter. Additionally, it is shown that an inefficient lumen contraction can increase the possibility of a continuous reflux during the propagation of peristalsis

Other Side of Breast Cancer: Factors Associated with Caregiver Burden

Purpose This study aimed to determine factors associated with caregiver burden among primary caregivers of women with breast cancer in Iran. Methods This was a descriptive correlation study conducted in 2012 on 150 main caregivers of patients with breast cancer who came to the oncology clinic of Shahid Ghazi hospital in Tabriz, Iran. A questionnaire which included caregiving-related factors and the Zarit Burden Interview was used for data collection after its validity and reliability were determined. Data was analyzed using SPSS 13.0 software with descriptive and analytic statistics. The association between significant variables and the dependent variable with an observation of the effects of other variables was assessed using the multiple linear regression model. Results The mean age of caregivers was 39.60 ± 13.80 years old, and 77 (51.3) of them were men. The mean score of the Zarit Burden Interview was 30.55 ± 19.18. In the regression model, the mean score of activities of daily living, level of education, gender, and financial status were identified as the determining factors of the burden of caregivers. Conclusions Primary caregivers need to be financially supported by the relevant organizations. Care skills training and providing palliative care seem helpful in reducing the pain and the burden of family caregivers for patients with breast cancer. © 201

DMRN+17: Digital Music Research Network One-day Workshop 2022

DMRN+17: Digital Music Research Network One-day Workshop 2022 Queen Mary University of London - Tuesday 20th December 2022. The Digital Music Research Network (DMRN) aims to promote research in the area of Digital Music, by bringing together researchers from UK and overseas universities and industry for its annual workshop. The workshop will include invited and contributed talks and posters. The workshop will be an ideal opportunity for networking with other people working in the area. Keynote speakers: Sander Dieleman Tittle: On generative modelling and iterative refinement. Bio: Sander Dieleman is a Research Scientist at DeepMind in London, UK, where he has worked on the development of AlphaGo and WaveNet. He obtained his PhD from Ghent University in 2016, where he conducted research on feature learning and deep learning techniques for learning hierarchical representations of musical audio signals. His current research interests include representation learning and generative modelling of perceptual signals such as speech, music and visual data. DMRN+17 is sponsored by The UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM); a leading PhD research programme aimed at the Music/Audio Technology and Creative Industries, based at Queen Mary University of London