ReviewFlow: Intelligent Scaffolding to Support Academic Peer Reviewing

Peer review is a cornerstone of science. Research communities conduct peer reviews to assess contributions and to improve the overall quality of science work. Every year, new community members are recruited as peer reviewers for the first time. How could technology help novices adhere to their community's practices and standards for peer reviewing? To better understand peer review practices and challenges, we conducted a formative study with 10 novices and 10 experts. We found that many experts adopt a workflow of annotating, note-taking, and synthesizing notes into well-justified reviews that align with community standards. Novices lack timely guidance on how to read and assess submissions and how to structure paper reviews. To support the peer review process, we developed ReviewFlow -- an AI-driven workflow that scaffolds novices with contextual reflections to critique and annotate submissions, in-situ knowledge support to assess novelty, and notes-to-outline synthesis to help align peer reviews with community expectations. In a within-subjects experiment, 16 inexperienced reviewers wrote reviews in two conditions: using ReviewFlow and using a baseline environment with minimal guidance. With ReviewFlow, participants produced more comprehensive reviews, identifying more pros and cons. While participants appreciated the streamlined process support from ReviewFlow, they also expressed concerns about using AI as part of the scientific review process. We discuss the implications of using AI to scaffold the peer review process on scientific work and beyond.Comment: 19 pages, accepted at the 29th ACM Conference on Intelligent User Interfaces (IUI 2024

Effects of glucocorticoids on weight change during the treatment of Wegener's granulomatosis

Objective Weight gain is a side effect of glucocorticoid (GC) use, but the natural history and health implications of changes in weight that occur during the treatment of inflammatory disease are not understood. Methods We evaluated data from the Wegener's Granulomatosis Etanercept Trial. Patients were categorized according to clinical outcome at 1 year: remission (no disease flares), single flare, or multiple flares. Risk factors for gaining ≥10 kg were examined in multivariate models. Results Weights at baseline and 1 year were available for 157 (93%) of the 168 patients analyzed. During year 1, the mean cumulative prednisone dosage in the multiple flares subgroup was 7.9 gm, compared with 6.0 gm and 3.9 gm in the single flare and remission subgroups, respectively ( P 10 kg in the first year of treatment. The quantity of weight gained by patients during treatment has potential future health implications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58632/1/23561_ftp.pd

A Technique for Primary Beam Calibration of Drift-Scanning, Wide-Field Antenna Elements

We present a new technique for calibrating the primary beam of a wide-field, drift-scanning antenna element. Drift-scan observing is not compatible with standard beam calibration routines, and the situation is further complicated by difficult-to-parametrize beam shapes and, at low frequencies, the sparsity of accurate source spectra to use as calibrators. We overcome these challenges by building up an interrelated network of source "crossing points" -- locations where the primary beam is sampled by multiple sources. Using the single assumption that a beam has 180 degree rotational symmetry, we can achieve significant beam coverage with only a few tens of sources. The resulting network of crossing points allows us to solve for both a beam model and source flux densities referenced to a single calibrator source, circumventing the need for a large sample of well-characterized calibrators. We illustrate the method with actual and simulated observations from the Precision Array for Probing the Epoch of Reionization (PAPER).Comment: 10 pages, 9 figures, 1 table, revised to match version accepted by A

Integrative eQTL-Based Analyses Reveal the Biology of Breast Cancer Risk Loci

该论文是在本文通讯作者美国哈佛大学医学院代纳法伯癌症中心马修.弗里德曼教授实验室完成的。Germline determinants of gene expression in tumors are infrequently studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL)-based analyses using the multi-level information provided in The Cancer Genome Atlas (TCGA). Of the factors we measured, cis-acting eQTLs accounted for 1.2% of the total variation of tumor gene expression, while somatic copy-number alteration and CpG methylation accounted for 7.3% and 3.3%, respectively. eQTL analyses of 15 previously reported breast cancer risk loci resulted in the discovery of three variants that are significantly associated with transcript levels (false discovery rate [FDR] < 0.1). Our trans-based analysis identified an additional three risk loci to act through ESR1, MYC, and KLF4. These findings provide a more comprehensive picture of gene expression determinants in breast cancer as well as insights into the underlying biology of breast cancer risk loci

International Coercion, Emulation and Policy Diffusion: Market-Oriented Infrastructure Reforms, 1977-1999

Why do some countries adopt market-oriented reforms such as deregulation, privatization and liberalization of competition in their infrastructure industries while others do not? Why did the pace of adoption accelerate in the 1990s? Building on neo-institutional theory in sociology, we argue that the domestic adoption of market-oriented reforms is strongly influenced by international pressures of coercion and emulation. We find robust support for these arguments with an event-history analysis of the determinants of reform in the telecommunications and electricity sectors of as many as 205 countries and territories between 1977 and 1999. Our results also suggest that the coercive effect of multilateral lending from the IMF, the World Bank or Regional Development Banks is increasing over time, a finding that is consistent with anecdotal evidence that multilateral organizations have broadened the scope of the “conditionality” terms specifying market-oriented reforms imposed on borrowing countries. We discuss the possibility that, by pressuring countries into policy reform, cross-national coercion and emulation may not produce ideal outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/40099/3/wp713.pd

Small RNA changes en route to distinct cellular states of induced pluripotency

MicroRNAs (miRNAs) are critical to somatic cell reprogramming into induced pluripotent stem cells (iPSCs), however, exactly how miRNA expression changes support the transition to pluripotency requires further investigation. Here we use a murine secondary reprogramming system to sample cellular trajectories towards iPSCs or a novel pluripotent ‘F-class’ state and perform small RNA sequencing. We detect sweeping changes in an early and a late wave, revealing that distinct miRNA milieus characterize alternate states of pluripotency. miRNA isoform expression is common but surprisingly varies little between cell states. Referencing other omic data sets generated in parallel, we find that miRNA expression is changed through transcriptional and post-transcriptional mechanisms. miRNA transcription is commonly regulated by dynamic histone modification, while DNA methylation/demethylation consolidates these changes at multiple loci. Importantly, our results suggest that a novel subset of distinctly expressed miRNAs supports pluripotency in the F-class state, substituting for miRNAs that serve such roles in iPSCs

From Chalcogen Bonding to S–π Interactions in Hybrid Perovskite Photovoltaics

The stability of hybrid organic–inorganic halide perovskite semiconductors remains a significant obstacle to their application in photovoltaics. To this end, the use of low‐dimensional (LD) perovskites, which incorporate hydrophobic organic moieties, provides an effective strategy to improve their stability, yet often at the expense of their performance. To address this limitation, supramolecular engineering of noncovalent interactions between organic and inorganic components has shown potential by relying on hydrogen bonding and conventional van der Waals interactions. Here, the capacity to access novel LD perovskite structures that uniquely assemble through unorthodox S‐mediated interactions is explored by incorporating benzothiadiazole‐based moieties. The formation of S‐mediated LD structures is demonstrated, including one‐dimensional (1D) and layered two‐dimensional (2D) perovskite phases assembled via chalcogen bonding and S–π interactions, through a combination of techniques, such as single crystal and thin film X‐ray diffraction, as well as solid‐state NMR spectroscopy, complemented by molecular dynamics simulations, density functional theory calculations, and optoelectronic characterization, revealing superior conductivities of S‐mediated LD perovskites. The resulting materials are applied in n‐i‐p and p‐i‐n perovskite solar cells, demonstrating enhancements in performance and operational stability that reveal a versatile supramolecular strategy in photovoltaics

From Chalcogen Bonding to S–π Interactions in Hybrid Perovskite Photovoltaics

The stability of hybrid organic–inorganic halide perovskite semiconductors remains a significant obstacle to their application in photovoltaics. To this end, the use of low‐dimensional (LD) perovskites, which incorporate hydrophobic organic moieties, provides an effective strategy to improve their stability, yet often at the expense of their performance. To address this limitation, supramolecular engineering of noncovalent interactions between organic and inorganic components has shown potential by relying on hydrogen bonding and conventional van der Waals interactions. Here, the capacity to access novel LD perovskite structures that uniquely assemble through unorthodox S‐mediated interactions is explored by incorporating benzothiadiazole‐based moieties. The formation of S‐mediated LD structures is demonstrated, including one‐dimensional (1D) and layered two‐dimensional (2D) perovskite phases assembled via chalcogen bonding and S–π interactions, through a combination of techniques, such as single crystal and thin film X‐ray diffraction, as well as solid‐state NMR spectroscopy, complemented by molecular dynamics simulations, density functional theory calculations, and optoelectronic characterization, revealing superior conductivities of S‐mediated LD perovskites. The resulting materials are applied in n‐i‐p and p‐i‐n perovskite solar cells, demonstrating enhancements in performance and operational stability that reveal a versatile supramolecular strategy in photovoltaics

The DESI One-Percent survey: constructing galaxy-halo connections for ELGs and LRGs using auto and cross correlations

In the current Dark Energy Spectroscopic Instrument (DESI) survey, emission line galaxies (ELGs) and luminous red galaxies (LRGs) are essential for mapping the dark matter distribution at $z \sim 1$. We measure the auto and cross correlation functions of ELGs and LRGs at $0.8<z\leq 1.0$ from the DESI One-Percent survey. Following Gao et al. (2022), we construct the galaxy-halo connections for ELGs and LRGs simultaneously. With the stellar-halo mass relation (SHMR) for the whole galaxy population (i.e. normal galaxies), LRGs can be selected directly by stellar mass, while ELGs can also be selected randomly based on the observed number density of each stellar mass, once the probability $P_{\mathrm{sat}}$ of a satellite galaxy becoming an ELG is determined. We demonstrate that the observed small scale clustering prefers a halo mass-dependent $P_{\mathrm{sat}}$ model rather than a constant. With this model, we can well reproduce the auto correlations of LRGs and the cross correlations between LRGs and ELGs at $r_{\mathrm{p}}>0.1$ $\mathrm{Mpc}\,h^{-1}$. We can also reproduce the auto correlations of ELGs at $r_{\mathrm{p}}>0.3$ $\mathrm{Mpc}\,h^{-1}$ ($s>1$ $\mathrm{Mpc}\,h^{-1}$) in real (redshift) space. Although our model has only seven parameters, we show that it can be extended to higher redshifts and reproduces the observed auto correlations of ELGs in the whole range of $0.8<z<1.6$, which enables us to generate a lightcone ELG mock for DESI. With the above model, we further derive halo occupation distributions (HODs) for ELGs which can be used to produce ELG mocks in coarse simulations without resolving subhalos.Comment: 27 pages, 16 figures, accepted by Ap