Rupesh Kumar

With Royal Challengers Bengaluru (RCB) already storming into the final after dismantling Gujarat Titans in Dharamsala, the Titans are left licking their wounds.

With the curtain about to fall on arguably the biggest T20 carnival of the year, Royal Challengers Bengaluru (RCB) are set to meet Gujarat Titans (GT) in the final of the Indian Premier League (IPL) 2026.

As speculation intensifies around Suryakumar Yadav's potential removal as India's T20I captain, the debate has shifted to who could step into the role.

At first glance, the upcoming India vs Afghanistan one‑off Test in New Chandigarh may appear inconsequential, a game outside the ICC World Test

Predicting the compressive strength of cement-based mortars has become increasingly important because modern mortar systems often contain recycled powders, supplementary cementitious materials, chemical modifiers, and different curing conditions that produce highly nonlinear strength responses. Although machine learning has been widely applied in cementitious-material research, the evidence on ensemble, hybrid, and stacked learning models for mortar compressive-strength prediction remains scattered and difficult to compare across studies. Existing studies also show recurring limitations, including heterogeneous mortar datasets, inconsistent predictor definitions, mixed curing-age structures, small or imbalanced data sources, weak or random validation designs, incomplete reporting of preprocessing and hyperparameter tuning, limited external validation, and limited uncertainty-aware performance reporting. These limitations make direct comparison of reported accuracy values unreliable and justify the need for a focused critical review. This review addresses that need by providing a PRISMA-based systematic and critical synthesis focused specifically on cement-based mortars, compressive strength, and advanced ensemble-family predictors. Scopus and PubMed were searched for English-language records published during 2010–2026, with Scopus further restricted to journal articles. The search identified 680 records, removed 55 duplicates, screened 625 unique records, and retained 33 full-text studies for qualitative synthesis. The main contribution of this review is a model-family-level synthesis that separates bagging/tree ensembles, boosting ensembles, hybrid or metaheuristic-tuned models, and stacked or blended models, while linking their reported performance to mortar type, dataset composition, curing-age coverage, validation design, tuning transparency, and interpretability practice. A further methodological contribution is the use of a quality-weighted within-study rank synthesis, which reduces the risk of misleading cross-study comparison caused by heterogeneous datasets, different strength ranges, and inconsistent reporting of performance metrics. The reviewed evidence shows a clear acceleration of research after 2021, with strong attention to sustainable and recycled-modified cement mortars. Bagging/tree ensembles and boosting methods are the most frequently reported model families, while hybrid/metaheuristic-tuned models are also common and stacking/blending remains comparatively recent. The synthesis indicates that model superiority claims depend strongly on validation rigor, preprocessing transparency, dataset structure, and reporting quality. Interpretability tools such as SHAP, feature importance analysis, and partial dependence plots are becoming more common, but uncertainty-aware reporting remains limited. Overall, ensemble-family models show strong potential for mortar compressive-strength prediction, but broader claims require stricter validation, clearer reporting, stronger external testing, and more reproducible benchmarking protocols.

June 6, 2026, will go down as a watershed moment in India's cricketing history. As the All India Senior Men's Selection Committee convened in Mumbai, the writing was already on the wall.

Overview With the ICC Women's T20 World Cup 2026 just days away, anticipation is building as England prepare to host the tournament for the first time since the inaugural edition in 2009.

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