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This study took a humanities approach to climate change education, focusing on climate fiction texts in the literature classroom, namely: Barakat Akinsiku’s “The God of the Sea,” Sigrid Marianne Gayangos’s “Galansiyang,” and Jules Hogan’s “Those They Left Behind” from Everything Change: An Anthology of Climate Fiction, Volume III (2021). This encompassed the Quarter 3, Week 7 literature competency in the DepEd Grade 10 curriculum context. In-depth discussion of the cli-fi texts was made possible through the crafting of a lesson exemplar, writing of discussion questions through an ecocritical lens, and using Collaborative Digital Text Annotation (CDTA) as an evaluative reading tool which engendered student responses to the text and interactions within the CDTA activity. Thematic analysis was used in interpreting the digital text annotations which revealed four different themes: drawing out story elements, connecting the text to the real world, performing evaluative reading, and expressing random reactions under which the students' responses to the cli-fi texts were classified. The researchers recommend using online applications such as Google Docs as digital annotation tools during collaborative classroom reading. Also, literature classroom facilitators should create a concrete reward system to encourage students' enthusiasm during the CDTA activities and to achieve the collaborative aspect of the CDTA. Lastly, other reading strategies for evaluating cli-fi texts must be explored.

Cumulative distribution function CFL Compact fluorescent lamp CHP Combined heat and power CPP Critical peak pricing CPS Cyber

Free Access IEEE Press Series on Systems Science and Engineering Lin Li, Lin Li University of Illinois at Chicago, Chicago, IL, USASearch for more papers by this authorMengChu Zhou, MengChu Zhou University Heights, Newark, NJ, USASearch for more papers by this author Book Author(s):Lin Li, Lin Li University of Illinois at Chicago, Chicago, IL, USASearch for more papers by this authorMengChu Zhou, MengChu Zhou University Heights, Newark, NJ, USASearch for more papers by this author First published: 27 October 2022 https://doi.org/10.1002/9781119578314.scard AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Sustainable Manufacturing Systems: An Energy Perspective RelatedInformation

The disturbance storm time (Dst) index is an important and useful measurement in space weather research. It has been used to characterize the size and intensity of a geomagnetic storm. A negative Dst value means that the Earth's magnetic field is weakened, which happens during storms. In this paper, we present a novel deep learning method, called the Dst Transformer, to perform short-term, 1-6 hour ahead, forecasting of the Dst index based on the solar wind parameters provided by the NASA Space Science Data Coordinated Archive. The Dst Transformer combines a multi-head attention layer with Bayesian inference, which is capable of quantifying both aleatoric uncertainty and epistemic uncertainty when making Dst predictions. Experimental results show that the proposed Dst Transformer outperforms related machine learning methods in terms of the root mean square error and R-squared. Furthermore, the Dst Transformer can produce both data and model uncertainty quantification results, which can not be done by the existing methods. To our knowledge, this is the first time that Bayesian deep learning has been used for Dst index forecasting.

In this paper, we present a second-generation wireless ultrasonic beamforming system, aiming for a truly wearable device for brain stimulation in small behaving animals. The fully-integrated, battery-operated system enables a self- contained untethered system. The system is partitioned into two parts for weight distribution: (1) a 1D capacitive micromachined transducer (CMUT) array on a separate head-mountable flexible printed circuit board (PCB), (2) a rigid back-mountable PCB including electronics such as a custom ASIC, a power management unit, a wireless module, and a battery. The newly developed ASIC not only enables a compact electronic system (30.5 mm x 63.5 mm) but also generates 3.4 times higher acoustic pressure (1.89 MPaPP), which corresponds to a spatial-peak pulse-average intensity (ISPPA) of 33.5 W/cm2, at a depth of 5 mm, compared to the first-generation ASIC. The full width at half maximum (FWHM) of the pressure is estimated to be 0.6 mm, achieving a sub-millimeter lateral resolution by using 5-MHz focused waves.

Fluorescent contrast agents are important tools in cell biology and medical imaging due to their high sensitivity and relative availability. Diketopyrrolopyrrole (DPP) derivatives have been recently studied for applications in bioimaging, but certain drawbacks due to their inherent structure have stifled progress towards their widespread implementation. Aggregation caused quenching (ACQ) associated with π-π stacking in relatively rigid extended conjugation systems as well as hydrophobicity of previously reported DPPs make most unsuitable for biological imaging applications. Addressing these deficiencies, we report the synthesis and photophysical characterization of two new water-soluble diketopyrrolopyrole (DPP) probes that exhibit pronounced protein-induced fluorescence enhancement (PIFE) upon binding serum albumin protein. In vitro studies were also performed showing low cytotoxicity for the new DPP probes. Two-photon fluorescence microscopy (2PFM) images were obtained via excitation at 810 nm and emission in the NIR window of biological transparency, illustrating the potential of these compounds as nonlinear optical bioimaging probes.

New high-tech firms have extensively used strategic alliances with large incumbent partners to access complimentary resources and capabilities and to finance their technology projects. However, due to their initially weak bargaining position, they tend to relinquish a disproportional amount of control rights to the larger firm that finances the R&D alliance. This raises the question: How can new high-tech firms, e.g. biotech firms, leverage their knowledge resources to retain control in alliance with larger partners, e.g. pharmaceutical incumbent firms? And, does alliance experience add to their leverage? Focusing on equity and non-equity types of alliance governance, we examine how the firm's depth and breadth of technological knowledge resources impact the choice of governance structure. Our findings suggest that high-tech firms with deeper technological resources are better able to retain control when allying with the larger firm. The relationship is stronger when the new firm has more alliance experience.

Nonlinear dynamics of a clamped–clamped micro-beam exposed to a two sided electrostatic actuation is investigated to determine super sensitive regions for mass detection. The objective is to investigate the sensitivity of the frequency spectrum of various regions in the phase space to the added mass and force the system to operate in its super sensitive regions by applying an appropriate pulse to its control electrodes. The electrostatic actuation in the top electrode is a combination of a DC, AC and a pulse voltage, the excitation on the lower electrode is only a DC and a pulse voltage. The governing equation of the motion, derived using the Hamiltonian principle, is discretized to an equivalent single-degree of freedom system using the Galerkin method. Depending on the applied electrostatic voltage to the micro-beam, it is demonstrated that the number and types of equilibrium points of the system can be modified. In this study, the level of the DC electrostatic voltage is chosen such a way that the system has three equilibrium points including two centers and a saddle node where the homoclinic orbit originates. According to the reported results, the mass sensing sensitivity depends on the operating orbit; some orbits exhibit considerably higher mass detection sensitivity to the added mass compared to that of a typical quartz crystal micro balance instrument.

Constant temperature and replica-exchange molecular dynamics simulations of two Aβ21-30 decapeptides in explicit solvent reveal metastable dimer states that are abundant near physiological temperatures. As Alzheimer's disease is associated with the neurotoxic oligomers of amyloid β-protein, the formation of these dimers provides insight into oligomer assembly.