The occurrences of invasive candidiasis has increased over the previous few decades. Although Candida albicans considers as one of the most common species of organisms, that cause acquired fungal infections. Candida albicans is an opportunistic fungal pathogen and inherent in as a lifelong, the yeast is present in healthy individuals as a commensal, and can reside harmlessly in human body. However, in immuno-compromised individuals, the fungus can invade tissues, producing superficial infections and, in severe cases, life-threatening systemic infections. This review wills emphasis on virulence factor of C. albicans including (adhesion, invasion, candida proteinase, and phenotypic switching and biofilm formation. I

A study of the hadiths of supplication orchestration

       Praise be to God, and prayers and peace be upon our master Muhammad, the Messenger of God, and upon his family, companions, and those who are guided by his guidance.

Then:

       Our Islamic jurisprudence and its basic principles are fixed, namely: the Noble Qur’an, then the Prophet’s Sunnah, then consensus, then analogy. However, it is characteristic of what makes it developed to meet the requirements of renewed life, including: sent interests, custom, approval, blocking pretexts, changing times. That is why it went through different stages, growth, brilliance, stagnation and endowment; Therefore, many scholars of Islamic jurisprudence divided its stages into four sections: the stage of inf

The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

PV connected systems are worldwide installed because it allows consumer to reduce energy consumption from the electricity grid. This paper presents the results obtained from monitoring a 1.1 kWp. The system was monitored for nine months and all the electricity generated was fed to the fifth floor for physics and renewable energy building   220 V, 50 Hz. Monthly, and daily performance parameters of the PV system are evaluated which include: average generated of system Ah per day, average system efficiency, solar irradiation around these months. The average generated kWh per day was 8 kWh/day, the average solar irradiation per day was 5.6 kWh/m²/day, the average inverter efficiency was 95%, the average modules efficien

In this paper we present the theoretical foundation of forward error analysis of numerical algorithms under;• Approximations in "built-in" functions.• Rounding errors in arithmetic floating-point operations.• Perturbations of data.The error analysis is based on linearization method. The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. The condition numbers enable simple general, quantitative bounds definitions of numerical stability. The theoretical results have been applied a Gaussian elimination, and have proved to be very effective means of both a prior

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a