The research aims to how to deal with certain situation to ensure the continuous competitive excellence of business market under the situation of covid-19, especially how to deal with major challenges, identifying the capabilities of tourism industry, investigating the ability of tourism agencies to resist the dynamic change of both internal as well as external environment to ensure their sustainability.

The important here as the paper notice, is how to be efficient and trying to find solutions in order to grow and survive through choosing certain strategies that aligned the critical issues.

Thus to achieve this level, many scenarios planed that could adopt in case of such pande

Periodontitis is a persistent bacterial-causing disease which damages the supporting periodontium of the teeth. The complexity of supporting tissue structure makes the regeneration a challenge for periodontists. Early investigations were focused on discovering therapeutic substitutes that are biocompatible, simple to prepare and economic. This might cause a local release of growth factors that accelerate the healing process of the soft and hard tissue. Recently, platelet-rich fibrin (PRF) has received a wide attention as a biocompatible regenerative material in both dental and medical fields. PRF is a natural fibrin-derived biomaterial, and it is easy to obtain. It can be gotten from individual blood without the use of any external anticoag

Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

BACKGROUND: CRC is one of the most common cancers in the world. K-ras is proto-oncogene with GTPase activity that is lost when the gene is mutated. Analysis of K-ras mutational status is very important for CRC treatment, being the most important predictors of resistance to targeted therapy. OBJECTIVE: This study aims to determine the frequency and spectrum of K-ras mutation among Iraqi patients with sporadic CRC. PATIENTS, MATERIALS AND METHODS: This study enrolled 35 cases with sporadic CRC; their clinicopathological parameters were analyzed. The FFPE blocks were used for DNA extraction; PCR amplification of K-ras gene and hybridization of allele-specific oligoprobes were performed. The assay covers 29 mutations in the K-ras gene (codons 1

       The present study was performed to spotlight the potential role of soil bacteria in the Al-Rumaila oil field as a bioindicator of heavy metals pollution. For this purpose, nine soil samples were collected from different sites, with 20cm depth, to assess the pollution status depending on the total and available concentrations of heavy metals.  The result indicates pollution of the studied soils with the following metals: Cd, Cu, Fe, Zn, and Pb. The mean of total concentration for all studied metals was higher than the allowed maximum limit based on the international limit:(3.394, 3.994, 39.993, 8844.979,150.372, and 103.347 µg/g), respectively. While measuring the total Metal concentration is important in determining the de

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121