An experiment was conducted to assess the genetic variability and relationship among the important horticultural traits in lettuce (Lactuca sativa L.). A wide range of variability among selected genotypes was observed for specific traits. A little or very less difference was observed between the genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) for all traits indicated the least environmental influence, which suggests that selection can be done based on the phenotypic performance. Higher estimates of heritability coupled with higher genetic advance for plant weight, yield, average leaf weight, leaf width indicated the presence of additive gene action, through which selection can be done. Yield (q/ha) showed highly significant positive correlation with plant weight, stem diameter, leaf size at genotypic and phenotypic level. Significant positive direct effect on yield by average plant weight, leaf length, average leaf weight and stem diameter and their significant positive correlation with yield as well as high heritability coupled with high genetic advance suggested them as the most important components contributing to yield. Thus, more weight should be given to these traits in yield improvement programme of lettuce for future line of work.

The extremes of long term distribution of rainfall in drought hit hot semiarid agro ecoregion of Yavatmal district, Maharashtra have significant implications on rainfed cotton productivity and socioeconomic activity of farming community. In the present approach, the occurrence of week wise dry spells during crop calendar were examined with the computation of standardized precipitation Index(SPI) covering the period of 1971 to 2005. The standard week wise rainfall analysis further showed that 27 th to 35 th week have mean of 43±35.9 to 65±93.2 mm with coefficient of variation of 83.6 to 141.4 per cent. The week wise SPI values for 35 years were categorized into 6 classes such as near normal dry periods occurring 63 % followed by 19.73% of normal wet periods, 5.71% of severely wet periods, 4.72% of moderately wet periods, 4.28% of extremely wet periods and 2.41% of moderately dry weeks. The occurrence of prolonged dry spells with mean of 38 to 41.36 % in 36th to 44 th week during critical cotton growth stages (branching and flowering stages) often coincides with reduction in lint yield. The study demonstrated that SPI considered as valuable tool to construct historical events of dry spells and its impact on soil water content in shrink-swell soils in drought hit areas.

In this study, the researchers narrowed their focus to the application of algorithmic decision-making in ranking job applicants. Instead of comparing algorithms to human decision-makers, the study examined participants' perceptions of different types of algorithms. The researchers varied the complexity and transparency of the algorithm to understand how these factors influenced participants' perceptions. The study explored participants' trust in the algorithm's decision-making abilities, fairness of the decisions, and emotional responses to the situation. Unlike previous work, the study emphasized the impact of algorithm design and presentation on perceptions. The findings are important for algorithm designers, especially employers subject to public scrutiny for their hiring practices.

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