A STAT1-driven inflammatory phenotype associated with response to checkpoint blocking antibodies sensitizes cancers to immunotherapy.

Species distribution modeling and niche dynamics of alien plants can aid in understanding the existing and future invasion potential in the wake of climate change. We describe the niche dynamics of S. viarum Dunal, and report on its present and predicted future distribution in Pakistan under scenarios of climate change. The results revealed that S. viarum had an extensive range of prospective distribution zones in Pakistan, with Central Punjab, Eastern Khyber Pakhtunkhwa, and Southern Balochistan being the most suitable. According to ROC curve data, the MaxEnt model has a great prediction precision and credible outcomes. The most important variables influencing S. viarum latent distribution may be precipitation and temperature. The current potential area of S. viarum is approximately 105,750 km² (12%). Under climate change regimes, the highly suitable area for S. viarum increases by 2–9% under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The outcomes of this study could help to develop control of regional invasions and climate change approaches in Pakistan. More importantly, the findings of niche dynamics in native and invaded S. viarum areas contribute to a better understanding of the nature of niche modifications in invasive species and the potential for invasion under climate change.

We present the idea of reservoir time series analysis (RTSA), a method by which the state space representation generated by a reservoir computing (RC) model can be used for time series analysis. We discuss the motivation for this with reference to the characteristics of RC and present three ad hoc methods for generating representative features from the reservoir state space. We then develop and implement a hypothesis test to assess the capacity of these features to distinguish signals from systems with varying parameters. In comparison to a number of benchmark approaches (statistical, Fourier, phase space, and recurrence analysis), we are able to show significant, generalized accuracy across the proposed RTSA features that surpasses the benchmark methods. Finally, we briefly present an application for bearing fault distinction to motivate the use of RTSA in application.

Transition detection in temporal and nontemporal signals is a problem encountered in various disciplines. We investigate the quadrant scan technique to analyze recurrence plots to identify tipping points of a dynamical system. We define two types of transition, state-transition and dynamic-transition, and prove analytically the ability of quadrant scans to detect both types. We then provide an extension by considering a weighting scheme to overcome limitations of the standard scheme. We further highlight the merits of the quadrant scan and our extension by studying several applications. The ability of the quadrant scan and its extension to deal with nontemporal, multivariate, or large data sets as well as their capability to classify multiscale transitions are demonstrated in detail through several examples and settings.

Modelling of 3D domain boundaries using information from drill holes is a standard procedure in mineral exploration and mining. Manual logging of drill holes can be difficult to exploit as the results may not be comparable between holes due to the subjective nature of geological logging. Exploration and mining companies commonly collect geochemical or mineralogical data from diamond drill core or drill chips; however, manual interpretation of multivariate data can be slow and challenging; therefore, automation of any of the steps in the interpretation process would be valuable. Hyperspectral analysis of drill chips provides a relatively inexpensive method of collecting very detailed information rapidly and consistently. However, the challenge of such data is the high dimensionality of the data’s variables in comparison to the number of samples. Hyperspectral data is usually processed to produce mineral abundances generally involving a range of assumptions. This paper presents the results of testing a new fast and objective methodology to identify the lithological boundaries from high dimensional hyperspectral data. This method applies a quadrant scan analysis to recurrence plots. The results, applied to nickel laterite deposits from New Caledonia, demonstrate that this method can identify transitions in the downhole data. These are interpreted as reflecting mineralogical changes that can be used as an aid in geological logging to improve boundary detection.