Last-male sperm precedence in Rhynchophorus ferrugineus (Olivier): observations in laboratory mating experiments with irradiated males

The Red PalmWeevil (RPW)Rhynchophorus ferrugineus(Olivier 1790) is an invasive pest from southeastern Asia and Melanesia that in the last 30 years has spread widely in the Middle East and Mediterranean Basin. Its stem-boring larvae cause great damage to several palm species of the Arecaceae family, many of which are economically important for agricultural and ornamental purposes. Therefore, great attention has recently been focused in studying this species to identify sustainable and effective eradication strategies, such as sterile insect technique (SIT). The rapid spread of RPW is associated with its high reproductive success. To evaluate the suitability of a SIT strategy, particular physiological and behavioral aspects of RPW reproduction, such as the presence of polyandry and post-copulatory sperm selection mechanisms, were investigated. To determine paternity of progeny from multiply mated females, double-crossing experiments were carried out confining individual females with either a wild-type male or a γ-irradiated male (Co-60). Fecundity and fertility of females were scored to evaluate post-copulatory sperm selection. Results showed that progeny were almost exclusively produced by the sperm of the second male, suggesting that a last-male sperm precedence is expressed at high levels in this species, and providing interesting insights for an area-wide RPW management strategy such as the SIT

Making informed decisions in cutting tool maintenance in milling: A KNN based model agnostic approach

In machining processes, monitoring the condition of the tool is a crucial aspect to ensure high productivity and quality of the product. Using different machine learning techniques in Tool Condition Monitoring TCM enables a better analysis of the large amount of data of different signals acquired during the machining processes. The real time force signals encountered during the process were acquired by performing numerous experiments. Different tool wear conditions were considered during the experimentation. A comprehensive statistical analysis of the data and feature selection using decision trees was conducted, and the KNN algorithm was used to perform classification. Hyperparameter tuning of the model was done to improve the models performance. Much research has been done to employ machine learning approaches in tool condition monitoring systems, however, a model agnostic approach to increase the interpretability of the process and get an in depth understanding of how the decision making is done is not implemented by many. This research paper presents a KNN based white box model, which allows us to dive deep into how the model performs the classification and how it prioritizes the different features included. This approach helps in detecting why the tool is in a certain condition and allows the manufacturer to make an informed decision about the tools maintenance

The 'K' selected oligophilic bacteria: a key to uncultured diversity?

Molecular techniques have made it increasingly clear that a large proportion of bacterial diversity in natural habitats is uncultured and therefore unexplored. We suggest and give evidence in support of a hypothesis that a large proportion, if not all, of the uncultured diversity from a variety of aquatic and terrestrial habitats are oligophilic (oligotrophic) bacteria. Oligophilic bacteria grow only on dilute nutrient media and form small or microscopic colonies. A technique to cultivate and isolate the moderately oligophilic bacteria was developed and 90 cultures isolated, The twelve bacterial cultures characterized showed high growth yield coefficients and carbon conversion efficiencies at low substrate concentrations and progressively decreased with increasing substrate concentrations. Most of the growth yields were substantially higher than those reported in the literature and lie near the theoretical maximum. Slow growth rates and high yields indicate that they are 'K' selected species. 16S rDNA partial sequence analysis of the isolates indicates that it is a novel as well as diverse group

Pictorial essay: Coronary artery variants and anomalies

CT coronary angiography has helped radiologists understand the variations and anomalies of the anatomy of the coronary arteries and, thus, to alert the cardiologist whenever such an anomaly is present. This can be of immense help to the clinician planning interventional procedures such as stenting, balloon dilatation, or graft surgery, particularly when there are secondary changes of calcification, plaque formation and stenosis