Near-infrared unsymmetrical squaraine core-based sensitizers for co-sensitized high-photocurrent dye-sensitized solar cells

Increased conversion of near-infrared (NIR) photons to electricity is needed to improve dye-sensitized solar cells (DSCs). Here, we report two squaraine dyes (RR13 and RR14) with unsymmetrical cores as NIR dyes in DSCs. Both dyes feature a conjugated indolizine donor with an indoline donor on the opposite side of the squaraine core. The dyes are studied via absorption spectroscopy, computational interrogation, and electrochemical analysis. The use of the strongly donating indolizine donor results in NIR photon-to-current conversion extending beyond 800 nm on TiO2 in DSC devices. The DSC devices were characterized by current-voltage curves, incident photon-to-current conversion efficiency measurements, and electrical impedance spectroscopy. After co-sensitized DSC device optimizations, the NIR-absorbing squaraine dyes complemented with commercial organic dyes (D35 and Y123) gave a high photocurrent output of ∼21 mA/cm2 with a PCE of 9.4%

Aspects of Online Reviews and their Effects on Consumer Decisions

This dissertation examines different aspects of online reviews and their effects in consumer decisions. Online reviews are proliferating at a tremendous rate, with most consumers now stating that online reviews are the most important product attribute in online purchase decisions (BrightLocal 2017). As such, it is important to understand how various aspects of reviews affect consumers’ decisions, and outline the conditions by which some of these attributes may have conditional influences. To that end, we begin this dissertation by first investigating two numerical attributes of online reviews, average product ratings and review volumes. Furthermore, because online reviews are becoming such an influential tool, firms have begun to attempt exploiting consumers via fake reviews (Mayzlin, Dover, and Chevalier 2014; Luca and Zervas 2016). Thus, the second essay in this dissertation investigates how consumers respond when a website discloses that they have caught fake reviews being written for a specific brand. In Essay I, we investigate how average product ratings and review volumes influence consumers’ decisions when faced with a choice set in which there is no dominant option (i.e., when one option has a higher rating, but fewer reviews relative to another option). We argue that the diagnosticity (i.e., influence) of both average product ratings and review volumes are conditionally influenced by the other attribute, and as such, the choice between the higher-rated, fewer reviews option and lower-rated, more reviews option is dependent on the specific values of each attribute. While prior research has demonstrated the relative influence of both attributes, the findings are still debated (Floyd et al. 2014; You, Vadakkepatt, and Joshi 2015). By investigating the conditional effects of these attributes on choice, we help to rectify the divergent findings. We argue that average product ratings are inherently more diagnostic than review volumes due to the bound versus unbound nature of their scales, respectively. Whereas average product ratings have stable scale boundaries (e.g., one to five stars), review volumes do not (e.g., zero to infinity). As such, review volumes are more susceptible to relative comparisons made within the choice set. We demonstrate how the relative diagnosticity of these attributes are a function of the review volumes contained within the choice set, and how this ultimately governs choice. We conclude Essay I with the theoretical implications as well as a series of simulations demonstrating the practical implications for managers. In Essay II, we demonstrate the consequence of websites informing consumers that they have identified fake reviews for brands featured on their website. While a growing body of literature has investigated the characteristics of fake reviews (Mukherjee et al. 2013; Ott et al. 2013), as well as the firms which are likely to solicit them (Mayzlin, Dover, and Chevalier 2014; Luca and Zervas 2016), to the best of our knowledge, this is the first investigation into the effect of disclosing this information to consumers. While fake review alerts inform consumers that websites are monitoring the reviews for fraudulent information, we argue that the alerts also activate consumers’ persuasion knowledge (Friestad and Wright 1994), leading to attempts to correct for perceived biased information, as well as justice against the brand when it is the source of the fake reviews. We demonstrate that fake reviews lead consumers to not only attempt correction in their perception of the brand, but also in the information that they acquire (i.e., the reviews they read). Furthermore, we show that reducing consumers’ perceptions of inaccurate information attenuates their corrections. As such, this research holds relevance for website managers which provide reviews for their consumers. In both essays, we demonstrate the consequences of review information in consumers’ judgments and decisions. We argue that managers must carefully consider what information to provide consumers, and how to present it, in order to avoid biasing their consumers’ decisions

Comprehensive assessment of the management of acute cholecystitis in Scotland : population-wide cohort study

Funding The study was funded by an NHS Grampian endowment fund (NER 11062). © The Author(s) 2023. Published by Oxford University Press on behalf of BJS Society Ltd. Elements of this paper were presented as an oral presentation at the Surgical Research Society in Nottingham, UK on 25 March 2023. Data from this paper have also been presented in the Moynihan prize presentation section of the Association of Surgeons of Great Britain and Ireland, Harrogate, UK on 18 May 2023Peer reviewedPublisher PD

CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds

Clouds play a significant role in global temperature regulation through their effect on planetary albedo. Anthropogenic emissions of aerosols can alter the albedo of clouds, but the extent of this effect, and its consequent impact on temperature change, remains uncertain. Human-induced clouds caused by ship aerosol emissions, commonly referred to as ship tracks, provide visible manifestations of this effect distinct from adjacent cloud regions and therefore serve as a useful sandbox to study human-induced clouds. However, the lack of large-scale ship track data makes it difficult to deduce their general effects on cloud formation. Towards developing automated approaches to localize ship tracks at scale, we present CloudTracks, a dataset containing 3,560 satellite images labeled with more than 12,000 ship track instance annotations. We train semantic segmentation and instance segmentation model baselines on our dataset and find that our best model substantially outperforms previous state-of-the-art for ship track localization (61.29 vs. 48.65 IoU). We also find that the best instance segmentation model is able to identify the number of ship tracks in each image more accurately than the previous state-of-the-art (1.64 vs. 4.99 MAE). However, we identify cases where the best model struggles to accurately localize and count ship tracks, so we believe CloudTracks will stimulate novel machine learning approaches to better detect elongated and overlapping features in satellite images. We release our dataset openly at {zenodo.org/records/10042922}.Comment: 11 pages, 5 figures, submitted to Journal of Machine Learning Researc

“Looks familiar, but I do not know who she is”:The role of the anterior right temporal lobe in famous face recognition

Processing a famous face involves a cascade of steps including detecting the presence of a face, recognizing it as familiar, accessing semantic/biographical information about the person, and finally, if required, production of the proper name. Decades of neuropsychological and neuroimaging studies have identified a network of occipital and temporal brain regions ostensibly comprising the 'core' system for face processing. Recent research has also begun to elucidate upon an 'extended' network, including anterior temporal and frontal regions. However, there is disagreement about which brain areas are involved in each step, as many aspects of face processing occur automatically in healthy individuals and rarely dissociate in patients. Moreover, some common phenomena are not easily induced in an experimental setting, such as having a sense of familiarity without being able to recall who the person is. Patients with the semantic variant of Primary Progressive Aphasia (svPPA) often recognize a famous face as familiar, even when they cannot specifically recall the proper name or biographical details. In this study, we analyzed data from a large sample of 105 patients with neurodegenerative disorders, including 43 svPPA, to identify the neuroanatomical substrates of three different steps of famous face processing. Using voxel-based morphometry, we correlated whole-brain grey matter volumes with scores on three experimental tasks that targeted familiarity judgment, semantic/biographical information retrieval, and naming. Performance in naming and semantic association significantly correlates with grey matter volume in the left anterior temporal lobe, whereas familiarity judgment with integrity of the right anterior middle temporal gyrus. These findings shed light on the neuroanatomical substrates of key components of overt face processing, addressing issues of functional lateralization, and deepening our understanding of neural substrates of semantic knowledge

Genetic dissection of triplicated chromosome 21 orthologs yields varying skeletal traits in Down syndrome model mice

Down syndrome (DS) phenotypes result from triplicated genes, but it is generally unknown how specific three copy human chromosome 21 (Hsa21) orthologous genes or interactions between genes affect these traits. A mouse mapping panel genetically dissecting Hsa21 syntenic regions was used to investigate the contributions and interactions triplicated Hsa21 orthologous genes on mouse chromosome 16 (Mmu16). Four-month-old femurs of male and female Dp9Tyb, Dp2Tyb, Dp3Tyb, Dp4Tyb, Dp5Tyb, Dp6Tyb, Ts1Rhr, and Dp1Tyb;Dyrk1a+/+/- mice were analyzed by micro-computed tomography and 3-point bending to assess skeletal structure and mechanical properties. Male and female Dp1Tyb mice, with the entire Hsa21 homologous region of Mmu16 in three copies, display specific bone deficits similar to humans with DS and were used as a baseline comparison for the other strains in the panel. Bone phenotypes varied based on triplicated gene content, sex, and bone compartment. Three copies of Dyrk1a played a sex-specific, essential role in trabecular deficits and may interact with other genes to influence cortical deficits related to DS. Triplicated genes in Dp9Tyb and Dp2Tyb mice improved some skeletal deficits. As triplicated genes may both improve and worsen bone deficits, it is important to understand the interaction between and molecular mechanisms of skeletal alterations affected by these genes

Improved Orbital Constraints and Hα\alpha Photometric Monitoring of the Directly Imaged Protoplanet Analog HD 142527 B

Companions embedded in the cavities of transitional circumstellar disks have been observed to exhibit excess luminosity at H$\alpha$, an indication that they are actively accreting. We report 5 years (2013-2018) of monitoring of the position and H$\alpha$ excess luminosity of the embedded, accreting low-mass stellar companion HD 142527 B from the MagAO/VisAO instrument. We use pyklip, a python implementation of the Karhounen-Loeve Image Processing algorithm, to detect the companion. Using pyklip forward modeling, we constrain the relative astrometry to $1-2 \mathrm{mas}$ precision and achieve sufficient photometric precision ($\pm0.2 \mathrm{mag}, 3\%$ error) to detect changes in the H$\alpha$ contrast of the companion over time. In order to accurately determine the relative astrometry of the companion, we conduct an astrometric calibration of the MagAO/VisAO camera against 20 years of Keck/NIRC2 images of the Trapezium cluster. We demonstrate agreement of our VisAO astrometry with other published positions for HD 142527 B, and use orbitize! to generate a posterior distribution of orbits fit to the relative astrometry of HD 142527 B. Our data suggest that the companion is close to periastron passage, on an orbit significantly misinclined with respect to both the wide circumbinary disk and the recently observed inner disk encircling HD 142527 A. We translate observed H-alpha contrasts for HD 142527 B into mass accretion rate estimates on the order of $4-9\times10^{-10} \mathrm{M_\odot}\mathrm{yr}^{-1}$. Photometric variation in the H-alpha excess of the companion suggests that the accretion rate onto the companion is variable. This work represents a significant step towards observing accretion-driven variability onto protoplanets, such as PDS 70 b\&c.Comment: Accepted to the Astronomical Journal. 32 pages, 16 figures, 8 tables, 4 appendice

AI ATAC 1: An Evaluation of Prominent Commercial Malware Detectors

This work presents an evaluation of six prominent commercial endpoint malware detectors, a network malware detector, and a file-conviction algorithm from a cyber technology vendor. The evaluation was administered as the first of the Artificial Intelligence Applications to Autonomous Cybersecurity (AI ATAC) prize challenges, funded by / completed in service of the US Navy. The experiment employed 100K files (50/50% benign/malicious) with a stratified distribution of file types, including ~1K zero-day program executables (increasing experiment size two orders of magnitude over previous work). We present an evaluation process of delivering a file to a fresh virtual machine donning the detection technology, waiting 90s to allow static detection, then executing the file and waiting another period for dynamic detection; this allows greater fidelity in the observational data than previous experiments, in particular, resource and time-to-detection statistics. To execute all 800K trials (100K files $\times$ 8 tools), a software framework is designed to choreographed the experiment into a completely automated, time-synced, and reproducible workflow with substantial parallelization. A cost-benefit model was configured to integrate the tools' recall, precision, time to detection, and resource requirements into a single comparable quantity by simulating costs of use. This provides a ranking methodology for cyber competitions and a lens through which to reason about the varied statistical viewpoints of the results. These statistical and cost-model results provide insights on state of commercial malware detection