Given the paucity and toxicity of available drugs for leishmaniasis, coupled with the advent of drug resistance, the discovery of new therapies for this neglected tropical disease is recognised as being of the utmost urgency. As such antimicrobial peptides (AMPs) have been proposed as promising compounds against the causative Leishmania species, insect vector-borne protozoan parasites. Here the AMP temporins A, B and 1Sa have been synthesised and screened for activity against Leishmania mexicana insect stage promastigotes and mammalian stage amastigotes, a significant cause of human cutaneous disease. In contrast to previous studies with other species the activity of these AMPs against L. mexicana amastigotes was low. This suggests that ama

The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

The research aims to find the impact of a proposed strategy according to the Luria model on realistic thinking among fifth-class scientific students and their achievement in mathematics. To achieve it, the experimental research method and the quasi-experimental design were used for two equal groups, one of them is a control group taught in traditional way and the other is an experimental one taught according to strategy based on Luria model. The research community represents the students of the fifth scientific class from the General Directorate of Education of Karkh First. The research sample (40) students were deliberately chosen and distributed equally between the two groups after making sure that they were equals in their previo

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

E-Learning packages are content and instructional methods delivered on a computer
(whether on the Internet, or an intranet), and designed to build knowledge and skills related to
individual or organizational goals. This definition addresses: The what: Training delivered
in digital form. The how: By content and instructional methods, to help learn the content.
The why: Improve organizational performance by building job-relevant knowledge and
skills in workers.
This paper has been designed and implemented a learning package for Prolog Programming
Language. This is done by using Visual Basic.Net programming language 2010 in
conjunction with the Microsoft Office Access 2007. Also this package introduces several
fac

Songs are considered as an educational and a substantial dependable references used in teaching and learning, particularly the so - called foreign language learning that allows learners to adapt to the target language culture and to develop their language learning skills including: listening comprehension, reading comprehension, speaking and writing. Consequently, it can be said that the Francophone songs with the musical richness and resonance specifically facilities French language learning skills  for all levels of education and achieve short and long terms predetermined educational language learning goals.  

     In fact, language learning through songs method does not only include the

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it