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This paper presents a migration from relational databases (RDB) to NoSQL databases, leveraging a data model that utilizes concepts such as objects, semantic enrichment, and metadata. It addresses the limitations of previous approaches and extends them to overcome issues encountered in the relational model, allowing for simpler and faster handling of large datasets. This approach eliminates problems related to joins, incorporates the concepts of references and embedded documents, and includes a comparative study between our approach and other methods for migrating from RDB to NoSQL. This comparison covers aspects such as structural changes, insertion rates, selection, and deletion. Automated migration uses document-oriented nested types to store related data in one database record. This simplifies the design phase and reduces queries and updates, speeding up user responses. This research provides a comprehensive summary of the achievement of migrating from a relational database to a document-oriented NoSQL database. The essence of this migration lies in its automatic nature, aimed at transforming the pre-existing relational model into an object-oriented model. This transition aims to align the database structure with MongoDB's documentoriented paradigm, ensuring optimal integration and efficient utilization of the technology's features. This research significantly distinguishes itself from previous work, primarily due to its ability to facilitate automatic database migration. It accomplishes this task by autonomously identifying object concepts, including those related to inheritance. This functionality is unique and represents a significant advancement, as no other migration method has thus far been capable of performing this automatic detection of object concepts, especially inheritance. The result of the migration provides several advantages in terms of reducing record count, particularly as we deal with massive data sets, and in terms of the time required for data deletion and insertion. A prototype shows how effective this automated approach is. Maintain that the migration process is automated. [ABSTRACT FROM AUTHOR]

Aims: Multidrug-resistant bacteria urinary tract infections (MDR-UTI) are a global concern, leading to increased morbidity, mortality and financial costs. The aim of this study was to determine the prevalence of MDR-UTI and establish the epidemiological profile of UTI due to different phenotypes of MDR-UTI. Methodology and results: This is a retrospective study of MDR-UTI assessed at the microbiology laboratory of Mohammed VI University Hospital Center of Oujda over 37 months from March 2016 to April 2019. The study included all requests for cytobacteriological examination of urine (CBEU) according to the instructions of the medical microbiology guidelines. An agar medium was utilized for bacterial culture experimentation. Antibiotic susceptibility testing was performed according to the European Committee on Antimicrobial Susceptibility Testing guidelines. CBEU in UTIs allowed the isolation of 1078 isolates. They were dominated by Gram-negative bacteria (87.65%; n=945), followed by Gram-positive bacteria for 12.34% (n=133). This included 181 (16.80%) multidrug-resistant strains, which were dominated by extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E) (n=144; 79.55%). Young male adults exhibited a higher occurrence of isolated ESBL-E and carbapenem-resistant Acinetobacter baumannii (CRAB). As for the distribution by department, there was a near equality between the MDR isolates isolated from outpatients (n= 88; 49%) versus the inpatients (n= 93; 51%). Exactly 152 (84%) isolated MDR cases were observed in patients who did not have a urinary catheter, 157 (87%) and 141 (78%) cases of MDR of UTI were not associated with care and occurred in non-immunocompromised patients, respectively. Prior antibiotic exposure was observed in only 58 (32%) cases. Conclusion, significance and impact of study: This study confirmed the increasing prevalence of multidrug-resistant urinary tract infections in the community and hospitals. The fight against this problem will require all stakeholders' involvement to achieve the goals from one health perspective in line with international agenda. [ABSTRACT FROM AUTHOR]

The models transformation is the fundamental key in Model Driven Architecture approach. In Model Driven Architecture there are two transformations kinds: the CIM to PIM transformation and the PIM to PSM transformation. The researchers focused on the transformation from PIM level to PSM level, because there are several points in common between these two levels. However, the transformation from CIM level to PIM level is rarely discussed in research subjects because they are two completely different levels. This paper proposes a model transformation method to master the transformation from CIM to PIM web-based in accordance with the Model Driven Architecture approach. Indeed, the main value of this method is to propose a transformation from business-oriented models to web-oriented models. This method is founded on building a good CIM level via well-defined rules, allowing us to win precious models that facilitate the task of the transformation from CIM to PIM web-based. Then, we define a set of well- selected rules to move from CIM to PIM web-based so as to ensure a semi-automatic transformation. This method conforms to MDA recommendations by considering the business dimension in the CIM level, and by modeling this latter level using UML activity diagram which is one of OMG standards for modeling business process. Nevertheless, we used UML models into the PIM level, because UML is recommended by MDA in this level. [ABSTRACT FROM AUTHOR]

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In this work, we derive a one-parameter family of Super Halley’s method for finding simple roots of nonlinear equations. The scheme is powerful since it regenerates an infinity interesting methods. The convergence analysis shows that the order of convergence of each method of the proposed family is at least three. The originality of the new family manifests in the fact that all these methods are governed by a recurring formula that depends on a natural integer parameter p. Moreover, under certain conditions, the convergence speed of these methods improves by increasing p. A fairly detailed study on their global convergence is carried out. To illustrate the abilities and performances of proposed family, numerical comparisons have been made with several other existing third order and higher order methods. [ABSTRACT FROM AUTHOR]

Background: dermatophytoses are a current fungal infection, caused by keratinophilic fungi (dermatophytes) able to invade the nails, hair and skin of humans and animals., Aim: the aim of this study was to establish the epidemiological and mycological profile of dermatophytes isolated in the parasitology-mycology laboratory of the Mohammed VI University Hospital in Oujda., Methods: this is a 48-month retrospective study from January 2019 to December 2022.The study includes samples taken or sent to our parasitology-mycology laboratory for mycological study. A direct examination and culture were performed on each biological specimen. Species identification was based on macroscopic and microscopic colony criteria., Results: in the present report we reviewed 950 mycological samples. Dermatophytes were isolated in 505 (53.15%) cases. The most common infections were tinea unguium (n=353; 69.90%), followed by tinea corporis (n=123; 5.74%) and tinea capitis (n=29; 5.98%). Trichophyton rubrum was the most frequently incriminated species., Conclusion: dermatophytes are the most frequent mycoses in humans. They are generally benign and often develop in a chronic and frequently recurrent pattern. Mycological examination is essential. It confirms the fungal origin and isolates the species responsible, in order to identify the source of contamination and implement an appropriate treatment.

Introduction: The pre-analytical step of cytobacteriological examination of urine (CBEU) is one of the most critical in microbiology., Aim: To analyze quantitatively and qualitatively the pre-analytical non-conformities related to the CBEU in order to propose reliable corrective measures., Method: This was a 76-month retrospective study from March 2016 to June 2022. The study included all CBEU referred to our laboratory. The conformity of the requests was evaluated according to the requirements of the medical microbiology standard (REMIC). It concerned the CBEU request, the urine sample and its packaging., Result: We collected 66631 CBEU requests. The urine was not conform in 1646 (2.47%) cases. The majority of non-conformities came from the emergency department (n= 653; 39.67%). The predominant non-conformities were (i) deteriorated sample (53.53%; n=878), (ii) delayed transport (28.55%; n=469) and (iii) damaged equipment (4.62%; n= 76)., Conclusion: In our study, pre-analytical non-conformities of CBEU were frequent and affected all steps of the pre-analytical process. They had a direct clinical and economic impact on the patient. Continuous improvement of the pre-analytical phase of the CBEU is necessary in our institution.