Abstract
While an understanding of evolutionary processes in shifting environments is vital in the context of rapid ecological change, one of the most potent selective forces, sexual selection, remains curiously unexplored. Variation in sexual selection across a species range, especially across a gradient of temperature regimes, has the potential to provide a window into the possible impacts of climate change on the evolution of mating patterns. Here, we investigated some of the links between temperature and indicators of sexual selection, using a cold-water pipefish as model. We found that populations differed with respect to body size, length of the breeding season, fecundity, and sexual dimorphism across a wide latitudinal gradient. We encountered two types of latitudinal patterns, either linear, when related to body size, or parabolic in shape when considering variables related to sexual selection intensity, such as sexual dimorphism and reproductive investment. Our results suggest that sexual selection intensity increases toward both edges of the distribution and that the large differences in temperature likely play a significant role. Shorter breeding seasons in the north and reduced periods for gamete production in the south certainly have the potential to alter mating systems, breeding synchrony, and mate monopolization rates. As latitude and water temperature are tightly coupled across the European coasts, the observed patterns in traits related to sexual selection can lead to predictions regarding how sexual selection should change in response to climate change. Based on data from extant populations, we can predict that as the worm pipefish moves northward, a wave of decreasing selection intensity will likely replace the strong sexual selection at the northern range margin. In contrast, the southern populations will be followed by heightened sexual selection, which may exacerbate the problem of local extinction at this retreating boundary.

Abstract
Aims. To investigate the inner regions of protoplanetary discs, we performed near-infrared interferometric observations of the classical T Tauri binary system S CrA. Methods. We present the first VLTI-GRAVITY high spectral resolution (R similar to 4000) observations of a classical T Tauri binary, S CrA (composed of S CrAN and S CrA S and separated by similar to 1".4), combining the four 8m telescopes in dual-field mode. Results. Our observations in the near-infrared K-band continuum reveal a disc around each binary component, with similar halfflux radii of about 0.1 au at d similar to 130 pc, inclinations (i = 28 +/- 3 degrees and i = 22 +/- 6 degrees), and position angles (PA = 0 degrees +/- 6 degrees and PA = -2 degrees +/- 12 degrees), suggesting that they formed from the fragmentation of a common disc. The S CrAN spectrum shows bright He i and Br gamma line emission exhibiting inverse PCygni profiles, typically associated with infalling gas. The continuum-compensated Br gamma line visibilities of S CrAN show the presence of a compact Br gamma emitting region whose radius is about similar to 0.06 au, which is twice as big as the truncation radius. This component is mostly tracing a wind. Moreover, a slight radius change between the blue-and red-shifted Br gamma line components is marginally detected. Conclusions. The presence of an inverse PCygni profile in the He i and Br gamma lines, along with the tentative detection of a slightly larger size of the blue-shifted Br gamma line component, hint at the simultaneous presence of a wind and magnetospheric accretion in S CrA N.

Abstract
This chapter aims to provide an overview of renewable energy systems (RESs) and the underlying issues related to the RES theme such as climate change and its mitigation. The types of RESs are also briefly discussed focusing on their characteristics and technological aspects. This is followed by the most important economic aspects as well as the challenges and opportunities of integrating RESs in power systems. This chapter also discusses the need for optimization tools adequately equipped to effectively capture the intrinsic characteristics of RESs and facilitate their optimal integration in power systems. All this leads to an efficient exploitation of their wide-range benefits while sufficiently minimizing their negative impacts. Finally, the chapter is summarized with some concluding remarks.

Abstract
Predicting whether a student will pass or fail is one of the most important actions to take while giving lectures. Usually, the experienced teacher is able to detect problematic situations at early stages. However, this is only true for classes up to a hundred students. For bigger ones, automatic methods are needed. In this paper, we present a predictive system based on three criteria retrieved and computed from the logs of the learning management system. We built fast frugal decision trees to help predict and prevent student failures, using data retrieved from their resource usage patterns. Evaluation of the decision system shows that the system's accuracy is very high both in train and test phases, surpassing logistic regression and CART. © 2017 IEEE.

Abstract
A manufacturing system often consists of multiple units as workcells with complex work systems to achieve the desired outcomes in an efficient and effective manner. Uncertain events such as machine down time or scheduled maintenance are unavoidable in any manufacturing unit. In this paper, we are trying to find the maximum workload of the remaining machines to fulfill the production requirements. To achieve this, a dynamic workload adjustment strategy has been proposed with dynamic upgradation of residual life distribution model. With parallel configurations and different benchmark instances the simulation experiments has been conducted to evaluate the degradation rate of different units. Results show that the proposed method is effective for finding the residual life of multi-unit systems.

Abstract
Reading room conditions such as illumination, ambient light, human factors and display luminance, play an important role on how radiologists analyze and interpret images. Indeed, serious diagnostic errors can appear when observing images through everyday monitors. Typically, these occur whenever professionals are ill-positioned with respect to the display or visualize images under improper light and luminance conditions. In this work, we show that virtual reality can assist radiodiagnostics by considerably diminishing or cancel out the effects of unsuitable ambient conditions. Our approach combines immersive head-mounted displays with interactive surfaces to support professional radiologists in analyzing medical images and formulating diagnostics. We evaluated our prototype with two senior medical doctors and four seasoned radiology fellows. Results indicate that our approach constitutes a viable, flexible, portable and cost-efficient option to traditional radiology reading rooms.