In this article, the effect of prolonged fire (24-hour duration) on reinforced concrete beams made with recycled aggregates from demolished concrete was experimentally investigated. Demolished concrete was used recycled coarse aggregates in equal proportion with natural coarse aggregates. Normal and rich mix concrete with water-cement ratio equal to 0.54 were used. As a control specimen, beams with all-natural aggregates were also cast to compare with the results of the proposed beams. All beams were cured for 28 days and exposed to fire at 1000°C in an oven for 24 hours. After the elapse of this fire period, the beams were allowed to air cool, followed by testing till failure in a universal load testing machine. Comparison of the test results shows that rich mix concrete beams more reduction in flexural strength, more increase in maximum load carrying capacity and deflection than normal mix beams. The maximum reduction in flexural strength was 32.41% for beams cast with 50% RCA and rich mix. Although the fire duration used in this study is rare, yet the outcome provides guidelines for taking proper decisions for retrofitting/strengthening of the fire affected structure before putting it back in service.

This paper is aimed to evaluate the effect of mould size on compressive strength of concrete cubes made with recyclable concrete aggregates. Natural coarse aggregates were replaced with 50% recycled aggregates from old demolished concrete. Five different mould sizes were used to cast 420 concrete cubes using 1:2:4 mix and 0.55 water/cement ratio. In each size equal number of cubes was cured for 3, 7, 14 and 28-day. After curing, weight of cubes was determined followed by testing for compressive strength in universal load testing machine with gradually increasing load. From the obtained results the strength correction coefficients were computed keeping 28-day cured standard size cubes as control specimens. Also, numerical expression based on regression analysis was developed to predict the compressive strength using weight of cube, area of mould and curing age as input parameter. The numerical equation predicts the compressive strength very well with maximum of 10.86% error with respect to experimental results.

Sindhi language models struggle with Romanized Sindhi as there is variation in the spellings of everyday words, and short prompts do not explicitly state the task or target language. In this study, the remaining source record of a small DeepSeek-R1 probe, which was based on seven canonical prompts and fourteen alleged A/B records, was audited. The screenshot captions were compared with the visible inputs and outputs, and duplication of images was checked. It was only relabeled when there was a single unambiguous canonical prompt that matched the visible input to a record. Task choice and exact target-string occurrence were then coded separately. Six records were auditable, three of which were recovered by relabeling; eight records were not auditable due to being duplicated, contaminated with a supplied answer, associated with a different phrase, or missing the user input or lost after label repair. Four of the six audited records adhered to the experimenter’s task, one provided a reasonably good English translation when the experimenter did not include the target language, and one resulted in an incompatible cross-linguistic reading. Five had the target (English/Sindhi) string and one did not. The screenshots do not demonstrate clear “standard” and “chain of thought” conditions: all audited B-labeled inputs are in the form of a simple prompt and there are no paired wrapper texts remaining. These are descriptive counts, not accuracy estimates and do not provide proof of causal benefit of prompt explicitness. The audit demonstrates the necessity of full prompt–response documentation, independently verified linguistic references, reruns, information-matched prompts, and preregistered evaluation plans in studies with low resources.