Video Games and School Performances of Dakar High School Students

The triptych (Smartphones, Video games, adolescents) has imposed itself on the collective consciousness in the form of questioning to the point of becoming a social phenomenon. It thus raises concerns about the uses that adolescents make of it and the effects on their academic performance, which we proposed to study among middle school students from the Dakar academy inspection. Where appropriate, we used mixed methods with the collection techniques of questionnaire survey, semi-structured interviews respectively with middle school students, adults (parents, supervisors, teachers, etc.), participant observation and literature review. Concretely, before accessibility to video games, the middle school students were more idle and well-behaved, watched a lot of TV, played with their brothers and sisters or did household chores. The majority of young people had good, very good or excellent conduct and their averages were fair, fairly good or good. With access to a diverse digital environment, middle school students have passionately turned to video games. As a result, their learning time, concentration and submission to parental injunctions have declined significantly. This situation negatively affected their academic performance and encouraged bad behavior.

A Study on the Correlation Between LIWC Word Categories and Chinese Composition Writing Performance of Fourth,Fifth,and Sixth Grade Students

This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using LIWC(Linguistic Inquiry and Word Count)as a text analysis tool,the study explores the impact of LIWC categories on writing performance which is scaled by score.The results show that the simple LIWC word categories have a significant positive influence on the composition scores of lower-grade students;while complex LIWC word categories have a significant negative influence on the composition scores of lower-grade students but a significant positive influence on the composition scores of higher-grade students.Process word categories have a positive influence on the composition scores of all three grades,but the impact of complex process word categories increases as the grade level rises.

Effects of QD2R Numeracy Enhancement Strategy on the Mathematics Performance of Grade 10 Students

Learning mathematics requires an effective and strategic teaching approach.This study aimed to assess the mathematics performance of the learners with the implementation of the numeracy enhancement strategy QD2R(Questions,Drills,Repetition,and Recitation)and to propose a strategy implementation plan to elevate their performances.This study employed the use of a quasi-experimental research design,purposive sampling with 70 Grade 10 students of Lian National High School who were distributed equally to control and treatment groups.The pre-test and post-test results were statistically analyzed using independent and paired sample t-tests,and a survey questionnaire was examined by getting the mean and standard deviation.The results indicated that better performance was achieved by the students from the treatment group compared to the students from the control group,as revealed by the Mean Percentage Score(MPS)results,mean scores,and P values of their pre-test and post-test scores.The learners’perception of the implementation of this strategy was to a great extent,wherein it was perceived to be more helpful in concepts related to understanding the lesson compared to concepts related to developing their attitude and skills.Moreover,the proposed implementation plan of numeracy enhancement strategy QD2R had three expected outcomes:elevated understanding and performance in mathematics lessons;modified strategy to focus on the development of attitude and skills towards mathematics;and refined and well-implemented QD2R strategy in teaching mathematics.Relative to these expected outcomes,appropriate measures,timeframe,and resources of each were comprehensively formulated.

A Feature Learning-Based Model for Analyzing Students’ Performance in Supportive Learning

Supportive learning plays a substantial role in providing a quality edu-cation system.The evaluation of students’performance impacts their deeper insight into the subject knowledge.Specifically,it is essential to maintain the baseline foundation for building a broader understanding of their careers.This research concentrates on establishing the students’knowledge relationship even in reduced samples.Here,Synthetic Minority Oversampling TEchnique(SMOTE)technique is used for pre-processing the missing value in the provided input dataset to enhance the prediction accuracy.When the initial processing is not done substantially,it leads to misleading prediction accuracy.This research concentrates on modelling an efficient classifier model to predict students’perfor-mance.Generally,the online available student dataset comprises a lesser amount of sample,and k-fold cross-validation is performed to balance the dataset.Then,the relationship among the students’performance(features)is measured using the auto-encoder.The stacked Long Short Term Memory(s-LSTM)is used to learn the previous feedback connection.The stacked model handles the provided data and the data sequence for understanding the long-term dependencies.The simula-tion is done in the MATLAB 2020a environment,and the proposed model shows a better trade-off than the existing approaches.Some evaluation metrics like pre-diction accuracy,sensitivity,specificity,AUROC,F1-score and recall are evalu-ated using the proposed model.The performance of the s?LSTM model is compared with existing approaches.The proposed model gives 89% accuracy,83% precision,86%recall,and 87%F-score.The proposed model outperforms the existing systems in terms of the earlier metrics.

Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Educational Data Mining(EDM)is an emergent discipline that concen-trates on the design of self-learning and adaptive approaches.Higher education institutions have started to utilize analytical tools to improve students’grades and retention.Prediction of students’performance is a difficult process owing to the massive quantity of educational data.Therefore,Artificial Intelligence(AI)techniques can be used for educational data mining in a big data environ-ment.At the same time,in EDM,the feature selection process becomes necessary in creation of feature subsets.Since the feature selection performance affects the predictive performance of any model,it is important to elaborately investigate the outcome of students’performance model related to the feature selection techni-ques.With this motivation,this paper presents a new Metaheuristic Optimiza-tion-based Feature Subset Selection with an Optimal Deep Learning model(MOFSS-ODL)for predicting students’performance.In addition,the proposed model uses an isolation forest-based outlier detection approach to eliminate the existence of outliers.Besides,the Chaotic Monarch Butterfly Optimization Algo-rithm(CBOA)is used for the selection of highly related features with low com-plexity and high performance.Then,a sailfish optimizer with stacked sparse autoencoder(SFO-SSAE)approach is utilized for the classification of educational data.The MOFSS-ODL model is tested against a benchmark student’s perfor-mance data set from the UCI repository.A wide-ranging simulation analysis por-trayed the improved predictive performance of the MOFSS-ODL technique over recent approaches in terms of different measures.Compared to other methods,experimental results prove that the proposed(MOFSS-ODL)classification model does a great job of predicting students’academic progress,with an accuracy of 96.49%.

The Effect of “Think-Talk-Write” Strategy on EFL Tenth-Grade Students’ Writing Performance

This study investigated the effect of“Think-Talk-Write strategy”on English as a Foreign Language(EFL)tenth-grade students'writing performance.A quasi-experimental design with two groups was employed.The researcher randomly assigned two whole sections of grade 10 from Al-Kharaj Secondary School for Boys.The first section was chosen as the experimental group with(20)students,and the second as the control group with(20).To achieve the purpose of the study,a pre/post writing performance test was designed.In addition,Think-Talk-Write(TTW)strategy was used to teach the experimental group,whereas a control group was taught by the conventional teaching strategies,as suggested in the teacher's book.Results revealed that TTW strategy enhanced students’writing performance.In light of the research results,the researcher recommends to use TTW strategy on other genres of writing.

Unveiling the Pedagogical Potency of Quizlet:Enhancing Vocabulary Acquisition and Academic Performance Among Business English Major Students in China

The effectiveness of Quizlet,an online vocabulary learning tool,in enhancing vocabulary acquisition and academic performance among Business English major students in China was investigated in this study.With emphasis on the importance of vocabulary proficiency for English learners,especially those in English-related majors,this research aimed to understand the impact of Quizlet on vocabulary mastery and its connection to overall academic success.A one-academic-year longitudinal experiment was carried out involving two classes,utilizing quantitative methods for assessing vocabulary retention and academic progress.Improvement was seen in the final exam rankings and vocabulary retention rates in Quizlet-engaged classes.Hopefully,this study could provide valuable insights for educators,curriculum designers,and researchers,guiding the optimization of language acquisition strategies in the digital age.

Enhancing Numeracy Skills of Grade 3 Students Through Authentic Performance Tasks

Numeracy is the capacity to use mathematical ideas in all facets of life.It involves activities such as adding and subtracting numbers,counting,number recognition,solving number problems involving various operations,sorting,observing,identifying,and establishing patterns.It is one of the fundamental skills that students should have mastered by the end of their primary schooling.With the notable importance of mastery of numeracy skills,low achievement and performance of the learners were observed in this aspect.This study aimed in enhancing the numeracy skills of Grade 3 learners through authentic performance tasks.The variable in numeracy skills includes the four fundamental operations and problem solving.The quasi-experimental design was utilized wherein purposive sampling or non-randomized sampling was used.In this study,33 Grade 3 learners of Rizal Elementary School were selected to participate in the tests.Pre-test and post-test crafted by the teacher were the main instrument in the study.The result revealed that in the pre-test the learners obtained a mean percentage score(MPS)of 38.20%in four fundamental operations,which implied a non-numerate level.While in terms of problem solving,the learners obtained a MPS of 20.60%which is also in the non-numerate level.It has a grand mean of 29.40%with an interpretation of non-numerate level.In the post-test,it was observed that four fundamental operations have a MPS of 81.10%which is in average numerate level,while problem solving has a MPS of 76.30%with a grand mean of 78.70%with an interpretation of average numerate level.This implied that there is a significant difference between the pre-test and post-test in the four fundamental operations and problem solving.Thus,it can be concluded that the application of authentic performance tasks was effective to bridge the gap on numeracy skills.

Effects of thinning on the understory light environment of different stands and the photosynthetic performance and growth of the reforestation species Phoebe bournei

Light levels determine regeneration in stands and a key concern is how to regulate the light environment of different stand types to the requirements of the understory.In this study,we selected three stands typical in south China(a Cryptomeria japonica plantation,a Quercus acutissima plantation,and a mixed stand of both)and three thinning intensities to determine the best understory light environ-ment for 3-year-old Phoebe bournei seedlings.The canopy structure,understory light environment,and photosynthe-sis and growth indicators were assessed following thin-ning.Thinning improved canopy structure and understory light availability of each stand;species composition was the reason for differences in the understory light environ-ment.Under the same thinning intensity,the mixed stand had the greatest light radiation and most balanced spectral composition.P.bournei photosynthesis and growth were closely related to the light environment;all three stands required heavy thinning to create an effective and sustained understory light environment.In a suitable understory light environment,the efficiency of light interception,absorption,and use by seedlings was enhanced,resulting in a higher carbon assimilation the main limiting factor was stomatal conductance.As a shade-avoidance signal,red/far-red radia-tion is a critical factor driving changes in photosynthesis and growth of P.bournei seedlings,and a reduction increased light absorption and use capacity and height:diameter ratios.The growth advantage transformed from diameter to height,enabling seedlings to access more light.Our findings suggest that the regeneration of shade-tolerant species such as P.bournei could be enhanced if a targeted approach to thinning based on stand type was adopted.

Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints

The problem of prescribed performance tracking control for unknown time-delay nonlinear systems subject to output constraints is dealt with in this paper. In contrast with related works, only the most fundamental requirements, i.e., boundedness and the local Lipschitz condition, are assumed for the allowable time delays. Moreover, we focus on the case where the reference is unknown beforehand, which renders the standard prescribed performance control designs under output constraints infeasible. To conquer these challenges, a novel robust prescribed performance control approach is put forward in this paper.Herein, a reverse tuning function is skillfully constructed and automatically generates a performance envelop for the tracking error. In addition, a unified performance analysis framework based on proof by contradiction and the barrier function is established to reveal the inherent robustness of the control system against the time delays. It turns out that the system output tracks the reference with a preassigned settling time and good accuracy,without constraint violations. A comparative simulation on a two-stage chemical reactor is carried out to illustrate the above theoretical findings.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Optimum Profiles of Endwall Contouring for Enhanced Net Heat Flux Reduction and Aerodynamic Performance

Successfully utilized non-axisymmetric endwalls to enhance turbine efficiencies(aerodynamic and turbine inlet temperatures)by controlling the characteristics of the secondary flow in a blade passage.This is accomplished by steady-state numerical hydrodynamics and deep knowledge of the field of flow.Because of the interaction between mainstream and purge flow contributing supplementary losses in the stage,non-axisymmetric endwalls are highly susceptible to the inception of purge flow exit compared to the flat and any advantage rapidly vanishes.The conclusions reveal that the supreme endwall pattern could yield a lowering of the gross pressure loss at the design stage and is related to the size of the top-loss location being productively lowered.This has led to diminished global thermal exchange lowered in the passage of the vane alone.The reverse flow adjacent to the suction side corner of the endwall is migrated farther from the vane surface,as the deviated pressure spread on the endwall accelerates the flow and progresses the reverse flow core still downstream.The depleted association between the tornado-like vortex and the corner vortex adjacent to the suction side corner of the endwall is the dominant mechanism of control in the contoured end wall.In this publication,we show that the non-axisymmetric endwall contouring by selective numerical shape change method at most prominent locations is advantageous in lowering the thermal load in turbines to augment the net heat flux reduction as well as the aerodynamic performance using multi-objective optimization.

Influence of the Nature of the Incoming Sludge on the Performance of a Vertical Flow Reed Beds in Dakar-Senegal

This work investigates the influence of the type sludge on drainage, plant development, purification performances and biosolids quality. Drainage properties were measured through the frequency of clogging, the percentage of leachate recovered and the dryness of accumulated sludge. Plant development was measured through the density, the height and the stem diameter. Purification performance was evaluated from the reduction rate. Biosolids quality was measured after 3 months of maturation. The results show that the clogging frequencies were 9.5%;0% and 3.7%;the volume of leachate recovered was 42.2%;20.4% and 24.7% and, the dryness was 33.4%;61.1% and 52.4% for FS-ST, FS-STT and SS respectively. Plants densities were about, with densities 197.1, 171.3 and 178.3 plants/m2 in beds fed respectively with FS-ST, FS-STT and SS. Despite the high removal rates, the concentrations of pollutants in the leachates are above the Senegalese standard NS 05-061 for discharge into the environment. The biosolids are all mature with C/N and NH4+/NO3?ratios lower than 12 and 1 respectively. The biosolids are also rich in organic and mineral elements. The concentrations of Ascaris eggs are higher than the WHO recommendations. These biosolids should be stored for additional time or composted.

Design and optimization of fluid lubricated bearings operated with extreme working performances——a comprehensive review

Fluid lubricated bearings have been widely adopted as support components for high-end equipment in metrology,semiconductor devices,aviation,strategic defense,ultraprecision manufacturing,medical treatment,and power generation.In all these applications,the equipment must deliver extreme working performances such as ultraprecise movement,ultrahigh rotation speed,ultraheavy bearing loads,ultrahigh environmental temperatures,strong radiation resistance,and high vacuum operation,which have challenged the design and optimization of reliable fluid lubricated bearings.Breakthrough of any related bottlenecks will promote the development course of high-end equipment.To promote the advancement of high-end equipment,this paper reviews the design and optimization of fluid lubricated bearings operated at typical extreme working performances,targeting the realization of extreme working performances,current challenges and solutions,underlying deficiencies,and promising developmental directions.This paper can guide the selection of suitable fluid lubricated bearings and optimize their structures to meet their required working performances.

Investigation of the Acceptability of Cultured Meat in University Students

Background: Over the past 20 years, cultured meat has drawn a lot of public attention as a potential solution to issues with animal husbandry, including inadequate use of natural sources, improper animal welfare practices, and possible risks to public health and safety. The novel method of producing meat through culture reduces the need for animals to produce muscle fiber, thereby obviating the necessity for animal slaughter. Apart from its ethical advantages, cultured meat presents a possible way to fulfill the expanding need for food among growing populations. The purpose of this research was to find out whether Turkish students would be willing to pay for and accept cultured meat. Technique: Method: 371 university students who willingly consented to fill out a questionnaire and provide demographic data make up the research sample. Questions from previous studies on the acceptability of cultured meat were compiled to create the survey. The research’s data collection took place in March and April of 2022. The research was completed in June 2022 after the data had been processed and analyzed. Results: The results showed that the majority of participants were female and had omnivorous eating habits. Based on the results of the Bonferroni correction test, students with a higher intention to purchase and consume cultured meat were those who received economics and business education. Students with two years of university education had a higher overall survey score than those with four years of education (p < 0.05). Furthermore, it is discovered that there is a negative correlation between the participants’ ages and their Factor 2 (using cultured meat as an alternative to industrial meat) and Factor 3 (consuming and purchasing it) section points (r = -109, p = 0.036) (r = -0.121, p = 0.019). In conclusion, university students generally have a negative outlook on health-related issues, such as eating cultured meat as an alternative.

Avoiding Sabatier's limitation through pulsed electrocatalysis for enhanced nitrogen oxidation performance

1.Introduction The activation and conversion of the Earth’s abundant inert nitrogen resources into high-value-added products epitomize one of nature’s most critical processes[1-3].Nitric acid(HNO_(3)),as a pivotal industrial raw material,showcases an extensive range of applications and possesses substantial economic value in the production of indispensable chemical compounds[4-6].

Semi-hydro-equivalent design and performance extrapolation between 100 kJ-scale and NIF-scale indirect drive implosion

Extrapolation of implosion performance between different laser energy scales is investigated for indirect drive through a semi-hydroequivalent design.Since radiation transport is non-hydro-equivalent,the peak radiation temperature of the hohlraum and the ablation velocity of the capsule ablator are not scale-invariant when the sizes of the hohlraum and the capsule are scale-varied.A semi-hydro-equivalent design method that keeps the implosion velocity V_(i),adiabat α_(F),and P_(L)/R_(hc)^(2) (where P_(L) is the laser power and R_(hc) is the hohlraum and capsule scale length)scale-invariant,is proposed to create hydrodynamically similar implosions.The semi-hydro-equivalent design and the scaled implosion performance are investigated for the 100 kJ Laser Facility(100 kJ-scale)and the National Ignition Facility(NIF-scale)with about 2 MJ laser energy.It is found that the one-dimensional implosion performance is approximately hydro-equivalent when V_(i) and α_(F) are kept the same.Owing to the non-hydro-equivalent radiation transport,the yield-over-clean without α-particle heating(YOC_(noα))is slightly lower at 100 kJ-scale than at NIF-scale for the same scaled radiation asymmetry or the same initial perturbation of the hydrodynamic instability.The overall scaled two-dimensional implosion performance is slightly lower at 100 kJ-scale.The general Lawson criterion factor scales asχ_(noα) ^(2D)∼S^(1.06±0.04)(where S is the scale-variation factor)for the semi-hydro-equivalent implosion design with a moderate YOC_(noα).Our study indicates that χ_(noα)≈0.379 is the minimum requirement for the 100 kJ-scale implosion to demonstrate the ability to achieve marginal ignition at NIF-scale.

Comparison of vergence mechanisms between university students with good and poor sleep quality

AIM:To compare the vergence mechanisms between good and poor sleepers in university students.METHODS:A total of 64 university students were recruited in this study.The validated Malay version of Pittsburgh Sleep Quality Index questionnaire(PSQI-M)was used to measure the participants’sleep quality over the past month.Participants were categorized as good sleepers(n=32)and poor sleepers(n=32)based on the PSQI-M scores.Heterophoria and fusional vergences were measured at distance and near.Mann-Whitney U test was used to compare heterophoria,negative fusional vergence(NFV),and positive fusional vergence(PFV)at distance and near between good and poor sleepers.Spearman correlation analysis was used to study the relationship between PSQI-M score and PFV at distance.RESULTS:Both distance and near heterophorias were not significantly different between good and poor sleepers(P>0.05).There was a difference in distance PFV(P<0.05)between good and poor sleepers,but not in distance NFV,near NFV,and near PFV(P>0.05).Distance PFV was negatively correlated with PSQI-M score(rs=-0.33,P<0.05).CONCLUSION:University students with poor sleep quality demonstrates a reduced ability to maintain fusion with increasing convergence demand at distance.Sleep quality assessment during binocular vision examination in university students is recommended.

Impact of Dietary Lactobacillus plantarum Postbiotics on the Performance of Layer Hens under Heat Stress Conditions

This experiment was conducted to determine the performance of heat-stressed layers fed a diet containing the probiotic Lactobacillus plantarum RS5 or its products of fermentation (postbiotics). Twenty-week-old Isa White layers, were subdivided into six treatments of 32 individually caged birds. Half of the birds were reared under regular temperature conditions, while the other half was subjected to cyclic daily heat stress. Layers were offered one of three diets: 1) Control;2) Control + Lactobacillus plantarum RS5 probiotic;3) Control + Lactobacillus plantarum RS5 postbiotics. Birds were tested for performance and visceral organ development for 5 months. Heat stress negatively affected the birds’ feed intake, egg weight, shell weight percentage, Haugh unit, shell thickness, yolk color, body weight and spleen weight percentage. Postbiotics significantly increased egg production (p < 0.05) in comparison to the control and the probiotic fed group (94.8% vs 92.6% vs 93.1%, respectively). Birds under probiotic or postbiotic diet showed a significantly higher (p < 0.05) feed intake and egg weight, although the probiotic had a more pronounced and gradual effect. Specific gravity, yolk weight percentage and shell thickness didn’t show differences among dietary groups. The Haugh Unit was significantly higher (p < 0.05) in probiotic group which also showed a significantly lower yolk color index (p < 0.05). The different feed treatments did not impact the bird’s viscera weight percentage, except for the ileum that was significantly lower (p < 0.05) under postbiotic supplementation. Both probiotics and postbiotics could be used as a potential growth promoters and might alleviate heat stress impact in poultry industry.

Two-Way Neural Network Performance PredictionModel Based onKnowledge Evolution and Individual Similarity

Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,etc.Compared with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is relativelysmall.It makes building models to predict students’performance accurately in such an environment even morechallenging.This paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course achievements.Extensive experiments on a real dataset show that our model performs better thanthe baselines in many indicators.