Global Journal of Pure and Applied Sciences

Insecticidal potential of indigenous plants leaf powder against rhyzopertha dominica fab. (coleoptera: bostrichidae) in stored maize (zea mays) grains in northeastern nigeria

2024-11-11T06:29:10+00:00

The study on the toxicity potential of plant leaf powders of Eucalyptus globulus, Citrus limon and Cassia occidentalis against maize weevil (Rhyzopertha dominica) infestation during storage was investigated in the Laboratory of the Department of Crop Protection, Faculty of Agriculture, Modibbo Adama University, Yola. The experiment was laid out in a Completely Randomized Design (CRD) with three replications and data collected were analyzed using General Linear Model Procedure of Statistical Analysis System (SAS, 2004) while, significance means will be compared using Duncan's Multiple Range Test (DMRT) at 5% probability level. Rhyzopertha dominica where exposed to four doses (0.2 g, 0.4 g, and 0.6 g) of these leaf powder per 50g of maize and a control treatment. Phytochemical analysis reveals the leaf powder of Eucalyptus globolus, Citrus limon, and Cassia occidentalis contain the following components (Saponin, Tanin, Steriod, Glycocide, Flavonoid, Tapinoid, Alkaloidand phenol). Though C. limon and C. occidentalis did not showed the presence of Tapinoid. The result of R. dominica mortality showed that at 3, 7, 14, and 21 days, highest mortality was observed on SAMMAZ 51 while SAMMAZ 15 had the lowest mortality. Mortality also of R. dominica on treated maize was highest at 0.6 g dosage, with effectiveness increasing over time. The Treated Maize exhibited less grain damage and weight loss compared to untreated controls. Germination percentage and palatability tests revealed no significant difference (P <0.05) between treated and untreated maize among the tested plant powders. C. occidentalis demonstrated the highest efficiency in controlling R. dominica which can be recommended as effective botanical insecticides for the control of R. dominica in stored maize, these offer a promising eco-friendly alternative for post-harvest pest management.

Evaluating Citrus Limon And Carica Papaya Seed Extracts In Coagulation-Flocculation For Improved Water Quality: Implications For Treatment Plants

2024-11-19T13:34:01+00:00

This study investigates the potential of Citrus limon (lemon) and Carica papaya (papaya) extracts as natural coagulants for improving water quality from the Great Kwa River in Calabar. Water samples from the river were treated with lemon peel extract (LPE) and papaya seed extract (PSE) to evaluate their effectiveness in coagulation-flocculation processes. The research employs a comparative approach, treating water samples with LPE, PSE, boiling, and utilizing an untreated control group for comparison. Water samples were collected from the Great Kwa River and subjected to treatment, samples were divided into three treatment groups; control (o) no treatment, LPE (B) (1: 10 liters of water) and PES (C) (0.5%: 10 liters of water). Parameters such as turbidity, total suspended solids (TSS), chemical oxygen demand (COD), total coliform bacteria (TCB), pH, lead (Pb), arsenic (As), glyphosate, atrazine, bisphenol, ibuprofen, and caffeine were measured during the treatment. Mean values for each parameter across treatment groups were compared using ANOVA to determine if there were significant differences between the groups. Treatment with LPE and PSE significantly reduced TCB, turbidity, COD, TSS, Pb, As, glyphosate, atrazine, bisphenol, ibuprofen, and caffeine compared to the control group. LPE treatment reduced TCB levels from 121.67 CFU/ml in the control group to 110.33 CFU/ml, while PSE treatment reduces to 117.67 CFU/ml. Similarly, LPE treatment reduces turbidity from 26.67 NTU to 18.75 NTU, while PSE treatment was reduced to 20.33 NTU. Mean values for COD, TSS, Pb, As, glyphosate, atrazine, bisphenol, ibuprofen, and caffeine also showed significant reductions following treatment with LPE and PSE compared to the control group. LPE and PSE demonstrated comparable efficacy to secondary boiling in improving water quality parameters. The optimal concentrations and conditions for each extract were identified, demonstrating their potential as eco-friendly and cost-effective alternatives to conventional chemical coagulants. Lemon Peel Extract (LPE) was more effective than Papaya Seed Extract (PSE) in improving water quality, as it achieved greater reductions in microbial pollutants, turbidity, chemical oxygen demand, total suspended solids, heavy metals, pesticides, and emerging contaminants by natural plant-based extracts for sustainable water treatment solutions in regions with limited access to advanced water purification technologies.

Influence Of Land Use/Land Cover On Land Surface Temperature In Lagos State, Nigeria

2024-11-11T07:01:43+00:00

The research was carried out to assess the land use and land cover (LULC) changes in Lagos State for 23 years as well as its impact on the land surface temperature. Landsat 8 images of the years 2000 and 2023 were downloaded and analyzed to determine these changes using supervised classification method after which the land surface temperature was estimated using appropriate formula where necessary. The result showed that barren land and built-up areas increased in 2000 from 0.16% and 47.03% to 5.84% and 50.80% respectively while vegetation and water body decreased from 36.43% and 16.39% to 28.81% and 14.55% respectively. Also, land surface temperature ranged from 17.04°C to 35.38°C in 2000 while in 2023, 17.54°C to 39.85°C. Within the 23yrs of the research, it showed that land use and land cover changes in the state impacted the temperature increase which was majorly caused by the reduction in vegetation and water body. The research conclude that Lagos is becoming warmer and therefore the research recommend that urban forestry should be encouraged by the government.

Effects Of Aflatoxin B1-Contaminated Diets On Growth Performance, Haematological, And Physiological Health In Broilers

2024-11-11T07:21:45+00:00

Aflatoxin B1 (AFB1) contamination in poultry feed significantly threatens broiler health and performance. This study investigated the effects of different levels of AFB1 (0%, 25%, 35%, 45%, and 55%) on growth performance and hematological parameters in broiler diets. The experiment was structured as a completely randomized design (CRD) with five treatment groups, each having three replicates: Group A (0.025 ppm AFB1), Group B (0.035 ppm AFB1), Group C (0.045 ppm AFB1), Group D (0.055 ppm AFB1), and Group E (Control, 0% AFB1). Weekly measurements included body weight (BW), feed conversion ratio (FCR), growth rate (GR), total feed intake (TFI), and hematological indices (HMI). Body weight was recorded weekly, feed intake was tracked daily, and FCR was calculated by dividing total feed intake by total weight gain. Blood samples were taken at weeks 5 and 10 for hematological analysis using the haemacytometer method. Broilers fed diets containing higher concentrations of AFB1 showed marked reductions in final body weight, with birds on the control diet (0% AFB1) gaining the most weight (1.69 kg), compared to 1.24 kg, 1.10 kg, 0.92 kg, and 0.76 kg for the 25%, 35%, 45%, and 55% AFB1 groups, respectively. Feed intake also significantly decreased (p<0.05) from 19.38 kg (Control) to 9.55 kg (TA) as AFB1 levels increased. Hematological analysis revealed significant decreases (p<0.01) in hemoglobin (Hb), packed cell volume (PCV), and red blood cell (RBC) counts in birds fed higher AFB1 concentrations. Birds on the control diet had the highest Hb (12.48 g/dl), PCV (24.73%), and RBC counts (10.34 × 10⁶/ul), while the 55% AFB1 group showed the lowest values. No significant changes were observed in white blood cell (WBC) counts (p>0.05), indicating a less pronounced impact on the immune system. These findings underscore the detrimental effects of AFB1 on broiler growth and blood health, emphasizing the need for stringent aflatoxin control in poultry feed to ensure healthy broiler production.

A Systematic Review On The Trends, Progresses, And Challenges In The Application Of Artificial Intelligence In Water Quality Assessment And Monitoring In Nigeria

2024-11-11T10:38:58+00:00

In recent decades, machine learning (ML) artificial intelligence has found wide application in water quality monitoring and prediction due to the increasing complexity of water quality data. This complexity has been attributed to the global upsurge in anthropogenic activities and climatic variations. It is therefore critical to identify the most accurate and suitable ML model for water quality prediction. In this study, a systematic literature review (SLR) was carried out to explore the trend and progress in the application of ML models in water quality monitoring and prediction in Nigeria from 2003-2024. A comprehensive review of the effectiveness of advanced ML models as well as the gaps in their application in the area of water quality assessment and monitoring was also carried out using the PRISMA-P meta-analysis technique. Forty publications were used to perform bibliographic analysis and visualization using the VOS viewer software. The study found that globally, the use of hybrid ML models in water quality prediction has not been well explored; a majority of the prediction has been based on the use of artificial neural networks (ANN). Among the ANN algorithms, the adaptive neuro-fuzzy inference system (ANFIS), and Wavelet-Adaptive Neural Fuzzy Interference System (W-ANFIS) hybrid models are the most accurate in prediction; with temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), and total dissolved solids (TDS) among the most frequently predicted parameters. Nigeria is grossly lagging in the application of ML in water quality prediction. This limitation is largely attributed to inadequate data on environmental monitoring. It is critical therefore for future water quality monitoring and prediction studies in Nigeria to take advantage of the rapidly evolving field of machine learning; with more emphasis placed on the hybridized machine learning algorithms

An Appraisal Of The Impact Of Leachates From A Waste Dumpsite On Coastal Soils And Groundwater System Of The Metropolitan Area Of Lagos, Southwestern Nigeria

2024-11-11T13:48:17+00:00

Open dump being the common waste disposal practice in most of the urban centres has posed serious challenges to groundwater quality especially within its vicinity. This study assessed the impact of solid waste disposal on the quality of groundwater and soils in Oke-Odo area of Metropolitan Lagos, Nigeria. Field physicochemical parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS) and temperature were measured using PC Testre Model 35. A total of 36 water samples, two leachate samples and 15 soil samples were analyzed for their major ions and trace metal components using titration and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) methods. Results revealed a decrease in concentrations of trace and major elements with respect to their distance from the waste dumpsite. A decrease in concentrations of Fe was observed with distances from the dumpsite with values ranging from 12.6 to 0.03mg/l and 4.3 to 0.03mg/l for samples within 500 m and 500-1,500 m, respectively. With exception of a few locations having higher concentrations of Fe, Al, Br, Cu, Mn and Pb, the groundwater sources in the study area are chemically potable with respect to their chemical compositions and generally conform to the World Health Organization and the Nigerian Standard for drinking Water Quality standards for drinking water; and thus, fit for domestic purposes. Sodium adsorption ratio ranges between 0.82 and 5.80 %, indicating low sodium and medium to high salinity hazards. This implies suitability of the water for irrigation purpose. The leachate from the active part of the waste dumpsite showed high concentrations of heavy metals such as Pb (4 mg/l), Cd (0.7 mg/l), Zn (6.54 mg/l) and Cu (3.57 mg/l), which indicates a potential environmental risk. The absence of these metals in the groundwater can be attributed to the attenuating role of the soil above the water table as confirmed by higher concentration of the measured trace metals in comparison to the control sites, with values ranging from 280 to 636 mg/l for Pb, 2 to 9.9 mg/l for Cd, 1041 to 10,000 mg/l for Zn and 102 to 1,307 mg/l for Cu. A total of 66.6 % of soil samples havevery high degree of contamination while 33.3% is considerably contaminated. Hydrochemical characterization of the water revealed predominant Na-K-Cl end-member water type and Ca-Mg-Cl water type which could be attributed to the influence of leachate from the waste dumpsite and possible contribution of seawater from the adjoining lagoons and cation exchange process. This study has revealed that soils and groundwater quality within the vicinity of Oke-Odo dumpsite has been impacted minimally.

Assessing The Carcinogenic And Non-Carcinogenic Health Risk Of Heavy Metal Contamination In Soils From Ratcon Quarry Site In Ibadan, Sw Nigeria

2024-11-11T14:11:50+00:00

This study estimates the health risks due to the concentration of heavy metals in the soil samples around a quarry near Ibadan, Nigeria. Soil samples were collected in triplicates (three samples collected per sampling point) from ten sampling points in the quarry site and control.

The soil samples were digested for 17 heavy metals (Al, As, Co, Cd, Cr, Cu, Fe, Hg, Mn, Mo, Pb, Sb, Se, Sn, V, and Zn) and quantified using Inductively Coupled Plasma- Optical Emission Spectrometry)- (ICP-OES). Health risk was assessed for metals including hazard quotient (HQ), hazard index (HI) and cancer risk (CR). Data obtained were subjected to descriptive (Mean ±SD) and inferential (Anova) statistics. Results showed that 16 heavy metals were detected, Fe had highest concentration (4354±17.4 mg/kg), followed by Al (1678 ±0.15 mg/kg) and Mn (192±1.29 mg/kg), Cd was not detected. The estimation of non-carcinogenic risks in this study indicated that all identified heavy metals in soils do not pose a non-carcinogenic risk to the health of children and adults. Hazard quotient (HQ) and hazard index (HI) values consistently were less than one (< 1). Also, this study revealed that values of most metals assessed were below 1 × 10^-6 lower limit for CR, except for chromium (1.97 X 10^-1), which poses a cancer risk in adults.

Factory-Related Environmental Pollution: A Study Of The Impact Of Cement Dust On Soil Quality Around Dangote Cement Plant, Tse-Kutcha, Gboko Local Government Area, Benue State

2024-11-11T14:36:02+00:00

Environmental pollution has been a close embodiment of the human society since man’s first appearance on the planet earth some few hundreds of thousand years ago. This paper examines the impact of dust emission from the exploitation and processing of limestone by the Dangote Cement Factory on the soils of Tse-kucha community. Soil profile at the depth of 0 – 80 cm were dug at distances of 0.5 km (Tse-Kucha), 1.0 km (Amua) and 1.5 km (Amua) and soil samples were collected from each horizon of the soil profile. Soil samples were also collected from another profile dug at Gaando, a nearby community to Tse-kucha where there are no cement dusts in soils for comparison. The soil samples were analysed for some physical and chemical properties related to soil fertility such as pH, organic carbon, exchangeable bases; Ca, Mg, Na and K, exchangeable acidity, infiltration capacities, available phosphorous, total nitrogen, cation exchange capacity and percentage base saturation using standard analytical procedures. Additionally, structured questionnaire was designed and administered on the respondents of the study area to complement information needed on the impact of Dangote cement plant on soil quality of the study area. The results revealed a predominantly sandy-loamy composition with significant (p < 0.05) difference in the soil parameters tested. Furthermore, the result revealed that cement dust emissions from the factory significantly affect the yield of crops in study area. area.

Perception of health workers and assessment of tree spp. Composition in adeoyo general hospital, ibadan, oyo state

2024-11-12T09:43:34+00:00

Trees as a crucial component of forest play a vital role in providing a wide range of products and services including health benefits. The lack of information on tree species composition and diversity around public health care facilities in Ibadan may hinder comprehensive understanding of the ecological value and potential benefits that trees provide to the surrounding environment and public health care facilities. This study assessed the perceptions of health workers and evaluation of trees within the premises of Adeoyo General Hospital, Ibadan. Forty-nine (49) Structured questionnaire was used to derive the perceptions, while total enumeration of all the trees with diameter at breast height (DBH) greater than or equal to 10 cm were identified and enumerated in the study area. Tables and percentages were used to analyze the perception of the health workers while data collected on dbh (cm) and total height (m) were used to compute basal area (m²) and volume (m³). The analysis of socio-demographic data revealed a higher representation of female health workers (61.2%), a concentration of professionals in the 30 to 39 age group (46.9%), and a predominant presence of married individuals with tertiary education. Examining health workers' perceptions, a significant consensus emerges on the positive effects of tree exposure. Workers believed that exposure to trees improve patient clinical outcomes, speeds up recovery, and boosts the immune system (42.9%). There is also recognition of the role of trees in reducing stress levels and enhancing focus for both patients and healthcare workers. The positive correlation between trees around healthcare facilities and increased staff satisfaction is noteworthy. In the study area, Azadirachta indica was the dominant tree species constituting 42.2% of the total population. Terminalia catappa and Gliricidia sepium are also of great significance. Mean diameter, height, basal area, and volume suggest a diverse forest with a wide range of tree sizes. Meliaceae dominated the families with 42.2% while other families like Fabaceae and Combretaceae also contributed to biodiversity and ecological significance. In DBH, Delonix regia had the highest value of 198.3cm while Newbouldia laevis had 15.1 cm as the lowest value. Antiaris africana and Azadirachta indica both had the maximum values of 19.8 m and 51.8 m³ in height and basal area respectively. Species diversity indices indicated a diverse forest ecosystem with 13 identified taxa and 64 individuals. The diversity index (Shannon-Wienner) of 1.89 - though it is low- is within the general limit for tropical forests. It is therefore recommended that integration and management of green spaces in healthcare facility design, development of employee wellness programs, promoting nature exposure, educational initiatives on the benefits of nature and economic valuation studies should be greatly considered.

Determinants Of Adherence To Anti-Glycaemic Drugs Among Patients With Diabetes Attending A Diabetic Clinic Of A Tertiary Hospital In South-South, Nigeria

2024-11-12T09:51:45+00:00

INTRODUCTION: Adherence to anti-glycaemic drugs are important to achieve optimal glycaemic control and desirable patient health outcomes. Poor adherence could increase diabetic-related morbidities and mortality. This study aimed to assess adherence to anti-glycaemic drugs and its determinants among patients with diabetes who attended the diabetic clinic in the University of Calabar Teaching Hospital, Calabar, Nigeria from January 2018 to December 2021.

METHODS: Cross-sectional descriptive study design was used. Systematic sampling technique was used to select 167 study participants. Adherence to diabetic treatment was determined through self-reports of how patients had been taking their medications within the past one week before the interview. Data was analysed using SPSS version 25.0, p-value set at 0.05 and Confidence Interval was set at 95%.

RESULTS: of the 167 patients studied, 46.1% were males while 53.9% were females. The prevalence of adherence to anti-glycaemic medication was 61.7%. Forgetfulness, side effects of drugs, feeling that the dose is high, multiple drugs, how/when to take the drug, type of medication and comorbidities were significantly associated with adherence. Binary logistic regression showed that forgetfulness, side effects and comorbidities were significant determinants of adherence.

CONCLUSION: There is need for targeted interventions to promote adherence to anti-glycaemic drugs.

Magnetic Resonance Imaging Brain Findings Among Patients With Seizure Disorder In Port Harcourt Metropolis

2024-11-12T09:57:02+00:00

OBJECTIVE: Seizure disorder is one of the most common chronic neurological disorders, affecting approximately 50 million worldwide. About 100,000 new cases are reported in Nigeria each year. To comprehend the prevalence of Magnetic Resonance Imaging (MRI) abnormalities and their correlation with seizures, local data is essential.

METHOD: A retrospective study design was adopted to review clinical data and MRI reports of 122 patients at a tertiary medical imaging facility in Port Harcourt, Rivers State between January 2015 and January 2023. Demography, image findings, and the relationship between the MRI findings, age, and sex were data obtained and analysed using descriptive and inferential statistics with the degree of significance set at p < 0.05.

RESULTS: This study involved 64 females and 58 males, aged 0 to 89 years. About 69 (57%) patients had normal brain MRI findings, while 53 (43%) were abnormal. The most common pathologies noted were cerebrovascular disorder 14 (11.48%), followed by white matter disease 13 (10.66%), and brain tumour 10 (8.20%). Age group 0-17 years had the highest number of pathological findings (20/53; 37%), followed by age group 36-53 years (11/53; 21%), and the age group 54-57 years (9/53; 17%). Age group spanning from 73 to 86 years, had the least of abnormal findings (4/53; 0.1%). No significant association existed between sex and MRI findings.

CONCLUSION: Brain MRI findings were normal in majority of seizure patients; the most common findings were cerebrovascular abnormalities, white matter disease, and brain tumours respectively, which were more common in younger patients. The study emphasizes the significance of early MRI scans in identifying seizure-related brain pathologies, particularly in children and adolescents in their diagnostic workup of seizure disorder.

Bayesian Accelerated Failure Time Model With Spatial Dependency: Application To Under Five Mortality Rate

2024-11-12T10:04:52+00:00

Nigeria is one of the top five in the world with the highest under-five mortality (U5M) rate. The risk of U5M in Nigeria is assumed to vary from one state to another due to diversity in socio-economic and even environmental factors. Thus, this study aimed to quantified the hazard of U5M using Bayesian Accelerated Failure Time (AFT) with spatial dependency. The data for the study were obtained from 2018 Nigerian Demographic and Health Survey (NDHS). The study utilized Bayesian technique based on Markov Chain Monte Carlo (MCMC) technique to obtained the posterior estimates of the parameters. The Loglogistic, Weibull and Lognormal AFT models with and without spatial dependency were considered in this study. Out of these models used, the log-logistic AFT model with Intrinsic Conditional Autoregressive (ICAR) spatial prior performed better than the other models considered in the study. The findings revealed that the survival of under-five children (U5C) was not homogeneous across the states (95% CI: 2.6330, 11.4630). The subject-specific factors such as maternal age at birth, duration of breast feeding, preceding birth intervals, maternal educational qualification, wealth index, region, number of antenatal visits, duration of pregnancy, gender of child, twin status, contraceptive used and toilet facility were the significant risk factors of U5M. Based on these findings, it was recommended among others that the disparities observed across states should be taken into account at the policy level in order to meet the Sustainable Development Goal (SDG) 2030 targets.

A Class Of Positive Definite Spherical Functions On The Euclidean Motion Groups

2024-11-12T10:14:05+00:00

Let be the Euclidean motion group realized as the semi-direct product of and . Let be a compact subgroup of . The set of positive definite spherical functions on is studied. Among other things, a result of Bochner which characterizes a K- bi-invariant positive definite spherical function in any locally compact group, is extended to the Gelfand pair ).

Unsteady Hydromagnetic Flow Of A Nanofluid In The Presence Of Inclined Magnetic Field In A Porous Media

2024-11-12T10:22:54+00:00

The unsteady hydromagnetic flow of a nanofluid in the presence of an angled magnetic field in porous media is investigated, with consideration given to the effect of the nanofluid’s viscosity variation parameter. The governing partial differential equations are obtained and transformed into dimensionless form by employing dimensionless quantities. Because of its stability, consistency, and high convergence rate, the finite difference approach is used to derive the numerical schemes of transformed partial differential equations, in line with the Crank-Nicolson method. The study subsequently examined at how dimensionless numbers, a viscosity variation parameter, and the magnetic field’s inclination angle affected velocity and temperature profiles. The results show that raising the Reynolds number and magnetic parameter increases the velocity profiles of the nanofluid, whereas increasing the permeability parameter reduces the velocity of the nanofluid.

Higher Reynolds, Eckert, and Prandtl numbers lead to larger temperature profiles of the fluid flow. Moreover, study found that increasing the viscosity parameter and magnetic field inclination angle can accelerate fluid flow velocity profiles. In addition, the temperature profiles of the fluid flow grow with the viscosity parameter and the angle of inclination of the magnetic field. The current findings are consistent with previous research, indicating their correctness and validity.

The Computational Effect And Hyperparameters Tuning Of Deep Convolutional Layer Depth Of High- Ranking Tuberculosis Detection Models

2024-11-12T10:27:02+00:00

In the past decade, artificial intelligence (AI) solutions have seen widespread application in medical fields, which include automated detection of breast cancer, brain tumors, physiological monitoring and detection of lung diseases such as pneumonia from chest X-Rays (CXRs). Machine learning, a subset of AI, empowers computers to learn autonomously, without direct human programming, by extracting patterns (feature extraction) from data (images). Deep learning, a specialized branch of machine learning, employs multiple convolutional layers to extract complex features from raw input data. This article examines the impact of varying the convolutional layers in deep learning models on their efficiency, focusing on algorithm complexity and parameter counts. We discuss theoretical foundations, and relevant factors affecting efficiency, and analyze algorithm complexity of high-ranking models developed for detecting tuberculosis from chest x-ray (CXR) using convolutional neural networks. The number of convolutional layers significantly influences model efficiency, affecting both performance and computational complexity. We could conclude practically that optimal layer depth balances model efficiency, accuracy and resource utilization. This assertion was reached by developing a model with fewer convolutional layer depth using the ResNet18 architecture. The parameters count of the ResNet18 model developed was compared with other model developed to detect tuberculosis from chest X-Ray images. The result of this comparison proved that fewer layer depth with the right hyperparameter tuning can produce a better and more efficient deep learning solutions to societal problems. This article also gives insights for future research and practical applications which includes the exploration of adaptive architectures that can dynamically adjust their depth based on the complexity of the task and available resources. Further research can also scientifically probe other methods of reducing the computational overhead of deep neural networks while maintaining priority for high computational performance, model scalability and efficiency.

Enhancing Student Learning Through Computational Techniques: A Review Of Educational Technologies In Computer Science

2024-11-12T10:37:30+00:00

This paper presents a systematic literature review on the integration of computational techniques and educational technologies in computer science education. The study explores three main research questions: (1) Which computational techniques and educational technologies are most effective in enhancing student learning outcomes in computer science? (2) How do these technologies influence key aspects of learning, such as cognitive development, problem-solving abilities, and student engagement? (3) What are the main challenges and limitations associated with the implementation of these technologies, and how can they be addressed? Through an analysis of recent studies, we identify the most effective technologies, including virtual reality (VR), artificial intelligence (AI), learning analytics, and gamification. These tools significantly improve cognitive development, foster problem-solving skills, and boost student engagement. However, the findings also highlight several challenges, such as infrastructure limitations, lack of teacher training, and issues related to student accessibility and equity. To address these challenges, we propose recommendations focusing on infrastructure development, professional development for educators, and strategies to promote equitable access and integration. The paper concludes that while educational technologies offer significant potential to transform computer science education, addressing implementation barriers is critical to realizing their full impact.