The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

Background: The aim of this study was to evaluate and compare the static frictional forces produced by monocrystalline ceramic (sapphire) bracket and polycrystalline ceramic bracket. Materials and methods: one hindered twenty brackets/segment of archwire combinations were used, each bracket/segment of archwire combination was tested 10 times. The tests were performed in a universal testing Instron machine. The data was submitted to in depended t-test. Results: The independent sample t-tests showed a highly significant difference in the static frictional forces between monocrystalline ceramic (sapphire) bracket and polycrystalline ceramic bracket. Conclusion: According to the biomechanical result gained from the present study, the monocryst

The development of new building materials, able of absorbing more energy is an active research area. Engineering Cementitious Composite (ECC) is a class of super-elastic fiberreinforced cement composites characterized by high ductility and tight crack width control. The use of bendable concrete produced from Portland Limestone Cement (PLC) may lead to an interest in new concrete mixes. Impact results of bendable concrete reinforced with steel mesh and polymer fibers will provide data for the use of this concrete in areas subject to impact loading. The experimental part consisted of compressive strength and impact resistance tests along with a result comparison with unreinforced concrete. Concrete samples, with dimensions of 100×

Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Background: Nanotechnology has emerged as a pivotal domain in material science research with extensive applications across various sectors including biotechnology and medicine. Nanoparticles offer unique properties facilitating advancements in nanobiotechnology, particularly in nanomedicine, to combat bacterial infections and antibiotic resistance. This study aimed to determine the application of nanoparticles, specifically nano-TiO2, in treating plasmid-mediated antibiotic resistance in both Gram-negative and Gram-positive bacteria. Method: We evaluated antibiotic and nanomaterial sensitivity through disc diffusion and broth microdilution assays. Plasmid curing experiments were conducted using varying concentrations of nano-TiO2 an

Background: Pseudomonas aeruginosa is a devious pathogen with the tendency to prompt many acute and serious chronic diseases. This study aims to detect novel genes (Toxins-Antitoxins II system), especially; higB and higA encoded from P. aeruginosa by PCR technique and the relation between these genes and antibiotic resistance of P. aeruginosa. Methods: This study detected 50 isolates of P. aeruginosa from distinct clinical sources. The most common origin of isolates was (44%) burn swabs, (22%) urine culture, (12%) wound swabs, (14%) sputum, and (8%) ear swabs. The bacteria were isolated using implantation MacConkey agar and blood agar, as well as biochemical tests including oxidase test, catalase test then VITEK-2 System of P. aerug

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at