International Journal of Formal Sciences: Current and Future Research Trends
The International Journal of Social Sciences: Current and Future Research Trends (IJSSCFRT) is an open access International Journal for scientists and researchers to publish their scientific papers in Social Sciences related fields. IJSSCFRT plays its role as a refereed international journal to publish research results conducted by researchers. This journal accepts scientific papers for publication after passing the journal's double peer review process within 4 weeks. For detailed information about the journal kindly check About the Journal page. All IJSSCFRT published papers in Social Sciences will be available for scientific readers for free; no fees are required to download published papers in this international journal.
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Deep Review of Existing Literature on Quality of Life in Morocco: Bibliometric Analysis, Investigated Sectors, Limits, and Recommendations for Future Research
The objective of this study was to assess the quality of life (QoL) in Morocco, mainly the quality of life indices and evolution of scientific research. A comprehensive bibliography of existing research on the topic was compiled through electronic survey databases and search engines, including Scopus, PubMed, ScienceDirect, the Public Library of Science, JSTOR, Web of Science, and Google Scholar, and the WSU online database (PubChem). The literature search was conducted for publications between 2000 and 2025, emphasizing English-language sources. The bibliometric research showed that 323 documents were published on the quality of life in Morocco. The most dominant documents were scientific articles (92.6%), followed by review papers with 4.4%, and letters with 1.7%. In contrast, conference papers and chapters presented only 0.9 and 0.4%. In total, 80 documents were selected and analysed in this study. Morocco ranked third with a score of 110.8, behind South Africa, which finished first with 152.4, and Tunisia with 117.3. The field surveys in Morocco were concentrated in industry, education, and medicine. These investigations have addressed the employees, staff, and persons with illnesses and disabilities. However, the existing data were significantly variable depending on the topic and studied populations. Despite the classification of Morocco in third place concerning the quality of life, investigations addressing this topic are very limited. Equally, the investigated topics, targeted populations, geographical areas, and temporal features in studies addressing life quality were fragmented and limited. Therefore, we oriented future investigations to address the quality of work life and organizational involvement of administrative staff in different Moroccan sectors, such as the hospital sector.
Copyright (c) 2025 International Journal of Formal Sciences: Current and Future Research Trends https://creativecommons.org/licenses/by-nc-nd/4.0
Polymer / Surfactant Mixtures at the Cyclohexane-Water Interface
Measurements of interfacial tension of polymer/surfactant mixtures at oil-water interface are scarce. Here we report on measurements of interfacial tension of Sodium polystyrene sulfonate (NaPSS, anionic polyelectrolyte)/Benzyldimethylhexadecylammonium Chloride (BAC, cationic surfactant), Polyallylamine hydrochloride (PAACl, cationic polyelectrolyte)/sodium dodecyl benzene sulfonate (SDBS, anionic surfactant) and Polyvinyl alcohol (PVA, neutral water soluble polymer)/sodium dodecyl benzene sulfonate (SDBS) at the Cyclohexane-water interface. Individual polyelectrolytes NaPSS and PAACl are interfacial inactive. Polyvinyl Alcohol shows interfacial activity comparable to surface active agents due to its H-bonding forming capacity. For the system SDBS/PAACl, a hump in the interfacial tension was observed with a maxima in the interfacial tension. This is explained by changes of the amount of different polyelectrolyte/surfactant complex structures at the interface and their competition with complexes in the bulk. No hump nor maxima in the interfacial tension was observed for the system BAC/NaPSS but surprisingly an increase in the interfacial tension was observed. This increase is due to insufficient BAC molecules to neutralize the charges at the repeating units of NaPSS. To the best of our knowledge the finding here for the oppositely charge polymer/surfactant systems studied at the cyclohexane interface are reported for the first time.
Biologically Driven Synthesis of Cobalt Oxide Nanoparticles Using Kalanchoe Pinnata Aqueous Leaves Extract for Sustainable Biological Applications
The most pressing public health concern is infectious diseases, which calls for the creation of more potent infection control measures. Cobalt is a type of ultra-trace element that is necessary for many organisms' metabolism. Because cobalt nanoparticles (Co NPs) are good at targeting particular tissues and pathogenic microbes, many researchers are interested in the green production of Co NPs and their uses. This study's objectives are to create and describe CoNPs from Kalanchoe Pinnata leaves and verified by seeing the solution's color shift from yellow to brown, which was verified by spectrophotometric detection of optical density. The synthesized cobalt oxide nanoparticles were examined using UV-visible spectroscopy (UV) (range: 200-800 nm). The amorphous nature was identified using an X-Ray Diffraction (XRD) pattern (XRD) (size: 5 nm) whereas synthetic NPs' spherical or elliptical shape was confirmed by scanning electron microscopy analysis (SEM) (size range: 20-30 nm). The FTIR results indicate that hydroxyl group, C=O group and C-O group may function as the reducing agent which involve in synthesis. Therefore, the aim of this study was to compare and assess the antibacterial and fungicidal properties of CoNPs. The main hypothesis states that the biological activity of CoNPs is determined by the properties of stabilizing agent molecules adsorbed on their surfaces that have comparable size distributions, morphologies, and ion release profiles. A variety of bacterial cell types, including Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa, and P. maltophilia, were employed as models. The most pronounced fungicidal effects were noted. The clear zone of clearance at 100 ?g/mL indicates that CoO nanoparticles killed the colonies. It was found that a specific stabilizing agent can be used to modify the selectivity of CoNPs toxicity towards specific pathogens. E. coli was found to be more vulnerable to CoNP exposure than Bacillus subtilis, Pseudomonas aeruginosa, and P. maltophilia, regardless of CoNP size and surface.
Copyright (c) 2024 International Journal of Formal Sciences: Current and Future Research Trends https://creativecommons.org/licenses/by-nc-nd/4.0
Determinants of Well-Being among University Students in Ethnic Minority Regions of Sichuan Province, China
This study investigates the mediating role of mobile phone addiction in the relationships among physical health, academic performance, academic competence, technology features, and well-being among university students in ethnic minority regions of Sichuan, China. Drawing on data from 852 students across 14 faculties, the research employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test a hypothesized mediation model. Participants completed validated instruments measuring physical health, academic outcomes, mobile phone use, technology features, and well-being between October and December 2023. Findings indicate that physical health, academic performance, academic competence, and technology features are positively associated with well-being. Moreover, mobile phone addiction is negatively linked to physical health, academic performance, and academic competence, while it is positively associated with technology features. Mediation analysis revealed that mobile phone addiction significantly explains the indirect effects of all predictors on well-being. These results underscore the dual influence of individual and technological factors on students’ psychological outcomes and highlight mobile phone addiction as a critical mechanism through which these influences operate. The study contributes to the growing literature on digital behavior and student well-being in underrepresented populations.
Enhancing Hydrologic Modeling Skills of Hydraulic and Water Resources Engineering Students through Interactive Simulation Software: A Case Study at Wolkite University
This research investigates the enhancement of hydrologic modeling skills of hydraulic and water resources engineering (HWRE) students at Wolkite University through the use of interactive simulation software. A total of seventeen students were participated, which comprised two females and fifteen male students. The study also tried to include twelve lecturers, comprising three female and nine male lecturers. Both primary and secondary data were collected to assess skill levels and identify gaps in knowledge. Questionnaires were designed for both students and lecturers, focusing on existing competencies, teaching methodologies, and software usage experiences. The researchers conducted targeted training sessions mainly on two key software tools, which are HECH-GEOHMS (Hydraulic Engineering Center for Hydrology-Geospatial Hydrologic Modeling System) and HECH-HMS (Hydrologic Modeling System). The training program comprised hands-on software that allowed students to engage with real-world scenarios, thereby enhancing their understanding of hydrologic processes and modeling techniques. Pre- and post-training assessments demonstrated a significant increase in the students' proficiency in using the software, as well as their confidence in applying hydrologic modeling concepts. Results indicate that students exhibited drastic positive changes in skill levels, with an average improvement of over 80% in their ability to apply hydrologic modeling techniques effectively. The student’s improvement in hydrologic modeling skills was also evaluated by exam, desk observations, and project work. This research underscores the importance of interactive learning tools in engineering education and recommends further integration of simulation software into the curriculum. By bridging the gap between theoretical knowledge and practical application, this study contributes to the preparation of future engineers equipped to tackle real-world water resource challenges. Future research can explore long-term impacts on student career readiness and the potential for similar training programs in other engineering disciplines.
Energy Indicators for Sustainable Development in Sierra Leone: A Review
This review examines the application, challenges, and policy implications of energy indicators for sustainable development in Sierra Leone. The country continues to experience persistent energy access shortages and a high reliance on biomass as its primary energy source. Although global interest in monitoring progress toward Sustainable Development Goal 7 (Affordable and Clean Energy) is growing, the application of energy indicators to Sierra Leone's planning systems remains relatively narrow. The review, following PRISMA 2020 guidelines, synthesizes evidence from 63 peer-reviewed articles, policy briefs, and institutional documents from the period 2000-2025. The synthesis is based on a tripartite framework that considers the economic, social, and environmental dimensions of sustainability. The results reveal significant gaps in data, institutional capacity, and the absence of integrated monitoring frameworks. Even though national plans like the National Renewable Energy Action Plan and the Energy Sector Policy articulate sustainable energy targets, no specific performance measurement measures have been outlined. Evidence from other sub-Saharan countries, as well as international agencies such as the IAEA, IEA, and UNDESA, indicates that the adoption of a consistent yet context-appropriate energy indicator framework can improve the evidence-based formulation of energy policy. The review concludes with pragmatic recommendations that focus on institutionalizing energy indicators, simplifying data collection processes, and aligning Sierra Leone's energy policy with global sustainability standards.
Role of Elaeidobius kamerunicus as an Economic Arthropod Pollinator in Oil Palm Cultivation: A Review
Demand for oil palm is anticipated to rise due to it uses globally. Factor responsible for an increase in production per unit area should be address to meet this demand. Research on the fundamental factors affecting decrease in oil palm fruit set and palm oil yields is alarming by prevailing declines in oil palm fruit set, palm oil yields and the oil yield gap. Since 1980s the oil palm pollinator Elaeidobius kamerunicus has been widely known as the most primary effective pollinator. It is positively related to Elaeis guineensis with fluctuating degree of merits and a high acceptability level of oil palm fruit set with high oil yield returns, signifying efficient pollination as a result of adequate kamerunicus weevil population. However, in recent times, researchers have reported decline in its proficiency as the main pollinator. It has further been questioned if the existing populations of these weevils are sufficient to maintain excellent fruit set for better productivity. Research has proven a decline in the population of this pollinator, especially the male kamerunicus. High rainfall and temperature, application of chemicals and natural enemies could be the main reasons for decline in the Elaeidobius kamerunicus population. It could be suggested that further research be done in addressing the decline in Elaeidobius kamerunicus population.
About two types of Nonstationary Stochastic Processes
Based on satisfactory results of the early developed analytic approach application to analysis of 3-rd order non-stationary stochastic processes (NSPs), the well known mathematical procedure for describing a NSP in more detail was applied to analysis of the 2-nd order ones. Physical bases of the 2-nd order and 3-rd order NSPs were defined as various periods of the NSP development. Based on numerous experimental data the periods were defined as: incubation (preliminary), intensive development, saturation for a 3-rd order NSP and period of intensive development together with the saturation one for a 2-nd order NSP. The constitutive equation for the 2-nd order NSP was derived and analytically solved. Some basic properties of the solutions were considered. Full absence of an equilibrium specific point for a 2-nd order NSP and existence of oscillating trajectories in the phase spaces were shown. The combination of the revealed variants of a 2-nd order NSP development was explained by an action of the mechanism early proposed for the describing the 3-rd order NSPs development. The obtained results were interpreted in terms of unlimited number of 2-nd order NSPs development in countless Universes similar to ourself.
CNN Applications in Dermal Lesion Segmentation: Progress in Precision Diagnosis
Early identification of skin conditions, particularly skin cancer, is vital for enhancing treatment outcomes. Advanced technologies, such as Convolutional Neural Networks (CNNs), have significantly improved the accuracy and speed of skin lesion diagnosis. CNNs analyze medical images to identify and categorize skin lesions with impressive accuracy [1], frequently detecting early-stage cancer that might otherwise go unnoticed by healthcare professionals. This automation results in faster, more consistent diagnoses, reducing wait times and facilitating timely treatments.
Copyright (c) 2024 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
Financial Marketing in E-Commerce: An Effective Approach to Intelligent Investment Strategies
This study explores the application of machine learning in predicting stock market prices, focusing on how techniques like neural networks and regression improve forecasting accuracy. By analyzing market patterns and trends, the proposed model enhances investment decision-making. Experimental results indicate that machine learning outperforms traditional methods, offering investors better predictive insights [1],[2]. These advancements contribute to more effective risk management and strategic financial planning in volatile markets [3].
Comparative Analysis of Deep Learning Models for Crop Diseases and Pest Classification
The deep learning models for crop diseases and pest classification research examined how deep learning might improve farming methods, particularly to accurately classify pests and diseases that affect crops. The importance of crop diseases and pests to world food security was highlighted in the introduction, along with the need for new approaches, such as deep learning models, to improve the accuracy and effectiveness of pest and disease control in farming. To evaluate the classification accuracy, the secondary datasets obtained from the Kaggle website were used to train and test various deep learning models, one of which was DenseNet. The researcher used a thorough assessment methodology to compare DenseNet's performance to that of other models, including AlexNet, EfficientNet, Visual Geometry Group, and Convolutional Neural Network. With an impressive accuracy score of 96.988% on the maize disease dataset and 96.9382% on the pest dataset, DenseNet proved to be the best model among the others. More accurate predictions were the result of DenseNet's capacity to effectively collect intricate characteristics and patterns within the visual data, which led to its improved performance. The researcher examined the implications of DenseNet's high accuracy in the discussion section, implying that its sophisticated design rendered it optimal for the categorization of agricultural diseases and pests. In addition, the researcher investigated the feasibility of incorporating DenseNet into practical agricultural systems, where its strong performance might greatly enhance methods of crop monitoring and disease control. The discussion came to a close with suggestions for future studies, such as looking at whether DenseNet can be used for other types of crops and if hybrid models or transfer learning may improve its performance.
National Health Information System and Mortality Surveillance in Cameroon: Case of the Yaoundé Emergency Center
Purpose: Improvements in life expectancy are based on population morbidity and mortality data. The initial cause of death is of public health interest. The aim of this study was to describe the causes of death at the Yaoundé Emergency Centre (CURY). Research problem: Mortality data in Africa are poorly informed. Policies and programs use reliable data on the health of populations to improve their health. The main question is whether the introduction of medical certification of causes of death (MCCD) initiated a few years ago could improve national death statistics. Methods: A retrospective descriptive study was carried out at the CURY from July 2021 to December 2022. This is one of the pilot sites for the implementation of the MCCD in Cameroon. All deaths recorded at the health facility during this period were included. The main data collection tools used were complete death declaration and certification forms and departmental death registries. For analysis, the data were extracted from DHIS2. Ethical considerations were taken into account. Results: A total of 967 deaths were recorded during the study period. The monthly average was 54 deaths or 5% of admissions. For analysis, 502/513 (97.05%) deaths were recorded in DHIS2. The mean age was 50.81 years (0-103 years). The sex ratio was 1.36 in favor of males. Four categories of death were identified. Diseases were the main type of death (67.74%). As far as the initial causes are concerned, sepsis is the main disease (13.15%) and poorly formulated causes 19.52%.Death certification needs to be performed properly to provide better information on the health of the population. Data quality remains an important challenge. Conclusion: Diseases were the main manner of death. Sepsis was the most important disease in the initial causes. The causes of death to be reformulated represented almost half of the initial causes. Verbal and medical autopsies, as well as improving the quality of the MCCD through the ICD-11, could improve national statistics. Significance of the research project: This study which is part of the mortality surveillance system, makes it possible to study the causes of death at CURY.
Proposal of the Land Valuation Process in Vietnam According to the Rules of the Market when the State Acquires Land
When the State acquires land, the price of land use rights is valued by compensation, which is one of the essential bases for guaranteeing land users. Resolution No. 18/NQ-TW also clearly states that land valuation must have a method valued according to market principles. Regulations on valuing specific land prices in the 2013 Land Law, amended and supplemented in 2018, have also revealed limitations related to failing to ensure specialization, objectivity, fairness, participation in supervision, and access to information of people whose land is acquired. The article proposes to develop a land valuation process in Vietnam according to market principles when the State acquires land to ensure a balance of benefits for those whose land is acquired.
Copyright (c) 2023 International Journal of Formal Sciences: Current and Future Research Trends https://creativecommons.org/licenses/by-nc-nd/4.0
Theoretical Review on Future Financing and Investment in Nigeria
Little is known about Future Financing and investments, as only a small number of surveys exist. This paper analyzed future finance and investments in our country of origin and covered current practices and motivations, obstacles to future finance and investment, addressing obstacles and other incentive mechanisms, and preferences for future finance and investment. Most countries strive to achieve high investment because of its literature acknowledged advantages as a tool of economic growth. Nigeria though faced by the problem of saving investment gap has one of its principal objectives under the new democratic dispensation as “the towards growth sustenance”. The result clearly shown that investment financing has a positive and strong relationship with economic growth in Nigeria, from the findings some of the problems of investment financing in Nigeria that were identified are the issues of Inadequate macroeconomic framework and policy inconsistencies, Low level of domestic savings, and Low return on investment. Therefore, the research recommended that government should pursue strong macroeconomic policies, improve economic efficiency, and increase public investment towards human capital development and improve infrastructures in the country to enhance productivity and efficiency.
Artificial Intelligence-A Key Note Biomarker in Drug Discovery and Development Running Title: ARTIFICIAL INTELLIGENCE
The application of artificial intelligence (AI) has recently accelerated in several societal domains, with the pharmaceutical sector leading the way. This paper highlights the useful applications of AI in the pharmaceutical industry, including medication discovery and development, drug repurposing, and pharmaceutical quality improvement. Among others, productivity, clinical trials, etc., have reduced the workload of people and expedited the completion of goals. Crosstalk about the methods and instruments used to enforce AI, ongoing problems, and solutions to them is also explored, as is the role of AI in terms of efficiency, accuracy, and speed. AI has the potential to revolutionize the drug discovery process. However, the availability of high-quality data, addressing ethical issues, and using AI effectively all depend on an understanding of the limitations of AI-based techniques. This article discusses the advantages of AI in this field, along with potential solutions. The suggested barriers to the situation are the addition of data, comprehensible AI, and the incorporation of the potential benefits of AI in the pharmaceutical industry, as well as how it compares to conventional experimental methods. This paper underlines the potential of artificial intelligence in drug discovery and gives details about the possibilities for attaining.
Architecture of Deep Learning Algorithms in Image Classification: Systematic Literature Review
The number of data points predicted correctly out of the total data points is known as accuracy in image classification models. Assessment of the accuracy is very important since it compares the correct images to the ones that have been classified by the image classification models. Image classification accuracy is a challenge since image classification models classify images to the class they don’t belong to hence there is an inaccurate relationship between the predicted class and the actual class which results in a low model accuracy score. Therefore, there is a need for a model that can classify the images with the highest accuracy. The paper presents image classification models together with the feature extraction methods used to classify maize disease images. The researcher used an augmented maize leaf disease dataset obtained from the Kaggle website. Features are extracted from maize disease images and passed to the machine learning classification algorithm to identify the possible disease based on the features detected using the feature extraction method. The maize disease images used include images of common rust, leaf spot, and northern leaf blight and healthy images. An evaluation was done for the feature extraction methods and the outcomes revealed Histogram of Oriented Gradients performed best with classifiers compared to KAZE and Oriented FAST and rotated BRIEF. The experimental outcome also indicated that the Artificial Neural Network model had the highest accuracy of 0.82 compared to Logistic Regression, K-Nearest Neighbors, Random Forest, Linear Support Vector Classifier, Decision Tree, and Support Vector Machine.
Modeling of the Microsoft Stock Prices Using Machine Learning and Classical Models: Identification of Optimal Model for Application
In this study, Microsoft stock price was modeled using two traditional time series models and two machine learning models for reliable predictions of the future behavior of the stock prices and more gainful investment. Model metrics such as AIC, BIC, Log-likelihood, RMSE, and confidence set test were the basis for comparison of the models. The results showed that the GARCH model outperformed the ARIMA and Support Vector Regression models while the Long Short-Time Memory –Recurrent model outperformed the GARCH model. Forecasts from the Long Short-Time Memory were made and found to be highly reliable. The results of the forecast also showed an uptrend movement up to a price of around $275 from November 2023 to January 2024. In conclusion, the LSTM-RNN is capable of accurately tracking and forecasting movements of volatile stock prices and is preferred over the other models considered in this study.
DDOS (Distributed Denial of Service) Attack Detection and Mitigation Using Statistical and Machine Learning Methods in SDN (Software-Defined Networking)
This study focuses on addressing the growing threat of Distributed Denial of Service (DDoS) attacks in Software-Defined Networking (SDN) environments. DDoS(Distributed Denial of Service attacks can cause significant disruption to network services by overwhelming target systems with a flood of malicious traffic. To combat this, we propose a novel approach that combines statistical and machine learning methods for the detection and mitigation of DDoS(Distributed Denial of Service attacks in SDN .To implement the detection and mitigation system, we design and deploy a comprehensive framework within the SDN infrastructure [1].
Transmission Control Protocol YNchronization
A Review on Housing Policies and their Reflections on Real Estate Values in the Case of Turkey
In this study, the housing sector will be examined with a financial approach, based on the housing policies in Turkey and the housing policies implemented in the planned and unplanned period after the proclamation of the Republic. In this study, housing finance systems applied in the world were examined and then an attempt was made to develop a financing model suitable for Turkey. The applicability of the model in question to real life was examined with a feasibility project. In the study, based on the definition of the concept of housing, the cost factors affecting the sector and the size of the sector in fixed capital investments are mentioned.
Information Technology Use and Evidence-Based Practice among Librarians in University Libraries in South-West, Nigeria
Evidence-based practice (EBP) is a professional approach that involves the process of collecting, interpreting and integrating valid and reliable data in decision making in library practice to enhance continuous professional improvement. The concept gives additional value to library and information science in many aspects of librarianship activities and services. The study investigated information technology use and evidence-based practice among librarians in universities in South-West, Nigeria. This study adopts survey research methodology and used questionnaire for data collection. The data collected was analysed using descriptive and inferential statistics. The findings of the study revealed that the level of evidence-based practice of librarians was high on the scale of four (4). The finding further shown that information technology use influenced evidence-based practice of librarians in universities in South-West, Nigeria. The study concluded that information technology use is crucial to evidence-based practice of librarians in universities in South-West, Nigeria. The study recommended that appropriate policies should be introduced and implemented by library management and professional librarians in continuous training and retraining of librarians on evidence-based practice implementation and information technology use.
Correlate of Blue Economy Potentials: Challenges and Prospects for Economic Development in Nigeria
This paper examined the maritime industry and marine ecosystem in Nigeria with a view to determine the relationship between revenue generated through maritime related activities by the Nigeria Ports Authority and Gross Domestics Product (GDP)-index for economic development. It analyzed the challenges of blue economy in spite of its economic potential. Secondary data from ports revenue and GDP were correlated and random selection of communities where blue economy is to be practiced selected across the littoral States. The communities were selected through stratified sampling techniques around the major Nigerian seaports in Apapa, Tin Can, Bonny Island in Port Harcourt, Old terminal in Calabar, Okerenko in Warrri, FOT at Onne, Ilaje in Ondo State and Yenegoa in Bayelsa State. 186 respondents were able to provide information on challenges that blue economy concept may face in Nigeria. Results revealed that, there is no correlation between revenue and GDP though with progressive revenue over the years which made us to accept the null hypothesis. The challenges of blue economy ranging from habitat degradation (30%), over exploration (14%), bunkering (13%), over fishing (9%) among others were identified. The research recommended the exploration of blue economy concept without degrading the marine ecosystem with policy initiatives.
Analysis of Death Cases of Children Hospitalized at the Koutiala URENI from October 01, 2021 to March 31, 2022
Infant and child mortality remains a major concern worldwide and more particularly in developing countries such as Mali. This is to better understand the reasons for this high mortality in Koutiala in the Sikasso region of Mali. Its objective was to assess the main determinants of deaths of malnourished children under 5 years of age occurring at the URENI (Unit for Recovery and Intensive Nutritional Education) in Koutiala. Materials/Methods: this was a cross-sectional descriptive study that took place in the URENI pediatrics department of the Koutiala reference health center, an exchange with the district management team, the documentary review , Observations on the task of the agents, Interviews of the actors involved in the care, analysis of the medical files of the malnourished children and the individual sheets for the follow-up of the malnourished cases admitted to the URENI. A pre-established framework made it possible to collect data through the admission register of malnourished children. The entry and analysis of the data collected were carried out using SPSS 21.0 and EXCEL 2016 software. Results: Children aged 6 to 23 months who died represented 44.4% and 72.2% were male. 11.1% of the children came from the urban city and 18.1% who were from the rural area; the most frequent type of malnutrition was marasmus with 59.7% followed by kwashiorkor with 20.8%. More than half (88.9%) of the children were seen by referral. Conclusion: this study revealed in Koutiala that marasmus was the most frequent form of malnutrition and many children who died came from outside the health district. It was also noted that infection (sepsis) was the main cause of death of children hospitalized at the URENI in Koutiala.
Investigation of Yellow Fever Cases in the Manankoro Area, Bougouni Health District, Sikasso Region, December 2019
Introduction : Following the confirmation of two (2) cases in the health district of Bougouni on 03/12/2019. We conducted an investigation whose objective was to describe the cases of yellow fever in the Manankoro health area in time, place and people and to put in place control and prevention measures against the epidemic. Methodology : We conducted a cross- sectional descriptive study in December 2019, a case of yellow fever was any person who stayed in Manankoro or surrounding village between October 20 to December 05, 2019 and who presented during this period the following signs : Fever or notion of fever in the previous days and jaundice in the 2 weeks following the onset of the signs . We conducted a search for other unreported cases based on data collected using a questionnaire. The data was analyzed in time, place and person. Results : Case confirmed by the laboratory , this is a 25-year-old adult , farmer , male gender , residence Kémingouara / Republic of Côte d'Ivoire, came on November 06, 2019 for consultation at the Lafia cabinet in Manankoro in a table of coma and referred to the CSRéf of Bougouni for better care where Hey died 11 hours after his blood sample on 08/11/2019. Conclusion : The investigation made it possible to identify 12 additional cases among which 3 cases of death , the age group of 30 to 34 years was the most represented , that is to say 33%. The male sex was predominant with 10 boxes. Fever, jaundice and vomiting were the most frequent symptoms . The Aedes species responsible for yellow fever was not found during this investigation.
Convalescent Plasma Treatment in Patient with Multiple Myeloma and Severe Sars-Cov-2 Infection
Multiple myeloma (MM) is a plasma cell dyscrasia characterized by uncontrolled cell division, leading mainly to kidney and bone damage. Since it affects the cell specialized in producing antibodies, the disease can cause immunodeficiency. This can be temporarily accentuated by chemotherapy, which could explain the high mortality rate of patients with MM and COVID-19. This report describes a 63-year-old woman with relapsed MM and severe SARS-CoV-2 infection, which presents a clinical picture of progressive deterioration of respiratory function, requiring invasive mechanical intubation because there was no clinical response to the usual treatment; convalescent plasma was administered, evidencing recovery of ventilatory parameters after infusion. The patient was extubated and discharged from the Hospital in good general condition.
A Model for Face Recognition using EigenFace Algorithm
The use of a computer to recognize a person by the means of their face is what is known as face recognition in artificial intelligence. The term biometrics is an umbrella term that includes face recognition as well as signature, fingerprint, eye scanning, gait, and palm print recognition. The principal component analysis technique was used in this paper to extract distinctive features from the faces which are matched with other faces stored in the database and predictive results indicated which faces were recognized and the ones that were not recognized. The accuracy of these techniques was calculated and the principal component analysis technique was found to be 86.3636% accurate and it was concluded that the technique performs better when it comes to face recognition.
Copyright (c) 2023 International Scientific Research and Researchers Association (ISRRA) https://creativecommons.org/licenses/by-nc-nd/4.0
Implementation of The Banker's Code of Ethics In Providing Protection For Bank Consumers
Code of ethics are moral principles attached to a profession and arranged systematically. This study aims to determine the proper application of the banker's code of ethics in protecting bank consumers. A code of ethics is needed because there are many more complex demands from society, which is the basis for forming professional organizations. This current research is normative legal research by examining library materials which are secondary legal materials, also called library law research. The results show that the application of a banker's code of ethics can be supported by good banking business management, honest and proper quality professional bankers, and strict enforcement of the banker's professional code of ethics.
How Aromatherapy Can Promote Alertness and Wakefulness
This study delves into the impact of aromatherapy on influencing both sleep and wakefulness via the use of essential oils including lavender and peppermint. Firstly, the study challenges the misconception that scents can't wake you up by showing strong evidence that our bodies naturally respond to smells, even when in a state of slumber. Further, through the expansion of a diverse array of studies, the research uncovers the ways in which aromatherapy exerts a strong influence on levels of drowsiness and alertness, alongside the numerous advantages that ensue. Ultimately, this study attests to the significance of essential oils and the influence they have on bodily processes that inherently transpire.
Potential of Coffee Grounds as a Sandy Soil Amendment and its Effect on Growth and Fruit Quality of Strawberry
Coffee grounds are discarded as solid waste in landfills which makes them an environmental hazard since it contains great quantities of caffeine and tannins. The efficiency of coffee grounds use in sandy soils is still scientifically unsupported and still lacks confirmation on its effect on fruit crops. The study aimed at assessing the potential of Coffee grounds (fresh FCG vs. composted CCG) as a sandy soil amendment and its effect on strawberry growth and fruit quality. The experimental design was a two factorial design conducted in a green house in a layout of Randomized Block Design. Treatment ratios were 3kg of sandy soil as constant mixture with 1kg or 2kg of Coffee Grounds (composted and fresh) and control (Co), replicated 16 times for each treatment. The sandy soil nutrient content (N, P, K, Mg and Ca levels) were significantly high (P-value < 0.05) in CCG (2kg) and FCG (2kg) than in the FCG (1kg), CCG (1kg) and control (Co) at post-harvest analysis. Both CCG treatments produced strawberry plants with highest germination percentage and seed vigour index at 14 days after planting. FCG treatments inhibited plant growth in the first 2 weeks after planting which improved greatly thereafter with no significant difference with the CCG treatments in plant vegetative growth by week 12. CCG (2kg) produced the best significant value for total number of fruits at 86.33 and fruit weight at 7.907. The FCG (2kg) and CCG (2kg) had the highest titratable acidity, soluble sugars and total soluble solids. CCG (2kg) had the highest mean value at 64.61 of ascorbic acid. This study delivers new understanding that experimental treatment of composted coffee grounds in rates of (2kg) gave significantly better results for strawberry in sandy soils compared to the lower rates of (1kg) and the control.
Regularization Methods for an Ill-Posed Elliptic Problem
We study an abstract elliptic Cauchy problem associated with an unbounded self-adjoint positive operator, which has a continuous spectrum. It is well-known that such a problem is severely ill-posed; that is, the solution does not depend continuously on the Cauchy data.
Exploring the Thiol (-SH)/Metal Interface
L-cysteine is one of the promising amino-acid that has drawn an immense interest in bio-electronics applications. Through multiple functional groups, it acts as a linker between proteins of biomolecules and metal electrodes of inorganic metals. Hence the interaction between metal and L-cysteine considered to be an area that a greater understanding is required. Photoelectron spectroscopic methods have been successfully used to resolve electronic configurations at these interfaces. When using these spectroscopic methods, it starts with thin films at around 1 - 2 angstroms and then reaching bulky layers so that the change of interaction is revealed through photoelectron kinetic energy. In many cases single crystals and in some cases poly-crystals of metals. Here we review metal-cysteine interaction through the thiol (-SH) and noble metal bond in brief.
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