cssi/SciSciGPT-SciSciNet huggingface dataset:
Interactions between soil properties, fungal communities, the soybean cyst nematode, and crop yield under continuous corn and soybean monoculture

Abstract Corn (Zea mays) and soybean (Glycine max) production forms an integral part of economies worldwide, but yields are limited by biotic and abiotic factors associated with short rotations and long-term monocultures. The objectives of this study were (i) to investigate the role of corn-soybean crop rotations and continuous monocultures in shaping bulk soil fungal communities, ii) to identify fungal taxa or functional guilds correlated with SCN density, and (iii) to characterize relationships between biotic and abiotic factors and their effects on corn and soybean yields. The study utilized a long-term rotation site with corn and soybean planted in annual rotation, five-year rotation, and long-term monoculture. High throughput sequencing of the ITS1 region of fungal rDNA revealed that soil fungal community structure varied significantly by crop sequence, with fungal communities under five consecutive years of monoculture becoming progressively similar to corresponding communities in long-term monoculture plots. Total fungal alpha diversity was greater under corn, but patterns of diversity and relative abundance of specific fungal functional guilds differed by crop, with more nematophagous fungi proliferating under soybean and more arbuscular mycorrhizal fungi (AMF) proliferating under corn. The relative abundance of nematode-trapping fungi and several putative nematode egg parasites was positively correlated with SCN density at several time points, suggesting that these fungi may proliferate as a result of the availability of the SCN as a nutrition source. Soil properties also varied by crop sequence, with higher pH and P under continuous soybean and higher Fe, Mn, and Cu under continuous corn. Lower levels of P corresponded with the relative abundance of several orders of fungi with roles in P uptake and transfer to plants (Glomerales, Paraglomerales, and Sebacinales), while higher P levels corresponded with the relative abundance of Mortierellales, a fungal order containing phosphate-solubilizing fungi. Structural equation modeling identified the SCN and soil nitrogen as the most important variables explaining soybean yield and fungal pathogens of corn and soil nitrogen as the most important variables explaining corn yield.
Learning Pain from Action Unit Combinations: A Weakly Supervised Approach via Multiple Instance Learning

Patient pain can be detected highly reliably from facial expressions using a set of facial muscle-based action units (AUs) defined by the Facial Action Coding System (FACS). A key characteristic of facial expression of pain is the simultaneous occurrence of pain-related AU combinations, whose automated detection would be highly beneficial for efficient and practical pain monitoring. Existing general Automated Facial Expression Recognition (AFER) systems prove inadequate when applied specifically for detecting pain as they either focus on detecting individual pain-related AUs but not on combinations or they seek to bypass AU detection by training a binary pain classifier directly on pain intensity data but are limited by lack of enough labeled data for satisfactory training. In this paper, we propose a new approach that mimics the strategy of human coders of decoupling pain detection into two consecutive tasks: one performed at frame level and the other at sequence level. Using state-of-the-art AFER tools to detect single AUs at the frame level, we propose two novel data structures to encode AU combinations . Two weakly supervised learning frameworks are employed to learn pain from video sequences. Experimental results show an 87% pain recognition accuracy with 0.94 AUC on the UNBC-McMaster dataset.
The proteasome regulator PI31 is required for protein homeostasis, synapse maintenance, and neuronal survival in mice

Proteasome-mediated degradation of intracellular proteins is essential for cell function and survival. The proteasome-binding protein PI31 (Proteasomal Inhibitor of 31kD) promotes 26S assembly and functions as an adapter for proteasome transport in axons. As localized protein synthesis and degradation is especially critical in neurons, we generated a conditional loss of PI31 in spinal motor neurons (MNs) and cerebellar Purkinje cells (PCs). A cKO of PI31 in these neurons caused axon degeneration, neuronal loss, and progressive spinal and cerebellar neurological dysfunction. For both MNs and PCs, markers of proteotoxic stress preceded axonal degeneration and motor dysfunction, indicating a critical role for PI31 in neuronal homeostasis. The time course of the loss of MN and PC function in developing mouse central nervous system suggests a key role for PI31 in human neurodegenerative diseases.
Spectral domain inverse design for accelerating nanocomposite metamaterials discovery

Inverse design techniques in the context of nanophotonics have helped in discovery of compact and counter-intuitive structures/shapes. We introduce the concept of spectral domain inverse design to search through the optical trade-space (dispersive permittivity) of nanocomposite metamaterials. We develop a hybrid optimization technique that combines genetic algorithms and gradient descent methods. We utilize this technique to inverse design an ultra-thin thermophotovoltaic emitter coating material. Our work can lead to an efficient approach to search for new multi-functional optical/thermal metamaterials with desired complex permittivity.
A matter of trust: Higher education institutions as information fiduciaries in an age of educational data mining and learning analytics

Higher education institutions are mining and analyzing student data to effect educational, political, and managerial outcomes. Done under the banner of “learning analytics,” this work can—and often does—surface sensitive data and information about, inter alia, a student's demographics, academic performance, offline and online movements, physical fitness, mental wellbeing, and social network. With these data, institutions and third parties are able to describe student life, predict future behaviors, and intervene to address academic or other barriers to student success (however defined). Learning analytics, consequently, raise serious issues concerning student privacy, autonomy, and the appropriate flow of student data. We argue that issues around privacy lead to valid questions about the degree to which students should trust their institution to use learning analytics data and other artifacts (algorithms, predictive scores) with their interests in mind. We argue that higher education institutions are paradigms of information fiduciaries. As such, colleges and universities have a special responsibility to their students. In this article, we use the information fiduciary concept to analyze cases when learning analytics violate an institution's responsibility to its students.
Strengthening the Case for a Bayesian Approach to Car-following Model Calibration and Validation using Probabilistic Programming

Compute and memory constraints have historically prevented traffic simulation software users from fully utilizing the predictive models underlying them. When calibrating car-following models, particularly, accommodations have included 1) using sensitivity analysis to limit the number of parameters to be calibrated, and 2) identifying only one set of parameter values using data collected from multiple car-following instances across multiple drivers. Shortcuts are further motivated by insufficient data set sizes, for which a driver may have too few instances to fully account for the variation in their driving behavior. In this paper, we demonstrate that recent technological advances can enable transportation researchers and engineers to overcome these constraints and produce calibration results that 1) outperform industry standard approaches, and 2) allow for a unique set of parameters to be estimated for each driver in a data set, even given a small amount of data. We propose a novel calibration procedure for car-following models based on Bayesian machine learning and probabilistic programming, and apply it to real-world data from a naturalistic driving study. We also discuss how this combination of mathematical and software tools can offer additional benefits such as more informative model validation and the incorporation of true-to-data uncertainty into simulation traces.
An Examination of Circadian Impacts on Judgments

Abstract. Many people suffer from insufficient sleep and the adverse effects of sleep deprivation are well documented. Research has shown that people’s judgments can be affected by circadian timing...
Generalized Lexicographic Products and the Index Coding Capacity

The index coding problem studies the fundamental limit on broadcasting multiple messages to their respective receivers with different sets of side information that are represented by a directed graph. The generalized lexicographic product structure in the side information graph is introduced as a natural condition under which the corresponding index coding problem can be decomposed into multiple interacting subproblems, each consisting of vertices with the same adjacency pattern with respect to other subproblems. For side information graphs with this structure, the capacity region is characterized in terms of the subproblem capacity regions combined in the same product structure. The proof is based on dual uses of random coding—one for a new multiletter characterization of the capacity region of a general index coding problem via joint typicality decoding and the other for a construction of a new multiletter code of matching rates from a single-letter code via joint typicality encoding. Several special cases are discussed that recover and strengthen known structural properties of the index coding capacity region.
Link Prediction Under Imperfect Detection: Collaborative Filtering for Ecological Networks

Matrix completion based collaborative filtering is considered scalable and effective for online service link prediction (e.g., movie recommendation) but does not meet the challenges of link prediction in ecological networks. A unique challenge of ecological networks is that the observed data are subject to systematic imperfect detection , due to the difficulty of accurate field sampling. In this work, we propose a new framework customized for ecological bipartite network link prediction. Our approach starts with incorporating the Poisson $N$ N -mixture model, a widely used framework in statistical ecology for modeling imperfect detection of a single species in field sampling. Despite its extensive use for single species analysis, this model has never been considered for link prediction between different species, perhaps because of the complex nature of both link prediction and $N$ N -mixture model inference. By judiciously combining the Poisson $N$ N -mixture model with a probabilistic nonnegative matrix factorization (NMF) model in latent space, we propose an intuitive statistical model for the problem of interest. We also offer a scalable and convergence-guaranteed optimization algorithm to handle the associated maximum likelihood identification problem. Experimental results on synthetic data and two real-world ecological networks data are employed to validate our proposed approach.
First results of the KATRIN neutrino mass experiment and their consistency with an exotic $3+3$ model

Although the first results of the KATRIN neutrino mass experiment are consistent with a newimproved upper limit of 1.1 eV for the effective mass of the electron neutrino, surprisingly they arealso consistent with an exotic model of the neutrino masses put forward in 2013 that includes onetachyonic mass state doublet having m2 ∼ -0.2 keV2 . A definnitive conclusion on the validity of themodel should be possible after less than one year of KATRIN data-taking.
SPINT2 inhibits proteases involved in activation of both influenza viruses and metapneumoviruses.

Abstract Viruses possessing class I fusion proteins require proteolytic activation by host cell proteases to mediate fusion with the host cell membrane. The mammalian SPINT2 gene encodes a protease inhibitor that targets trypsin-like serine proteases. Here we show the protease inhibitor, SPINT2, restricts cleavage-activation efficiently for a range of influenza viruses and for human metapneumovirus (HMPV). SPINT2 treatment resulted in the cleavage and fusion inhibition of full-length influenza A/CA/04/09 (H1N1) HA, A/Aichi/68 (H3N2) HA, A/Shanghai/2/2013 (H7N9) HA and HMPV F when activated by trypsin, recombinant matriptase or KLK5. We also demonstrate that SPINT2 was able to reduce viral growth of influenza A/CA/04/09 H1N1 and A/X31 H3N2 in cell culture by inhibiting matriptase or TMPRSS2. Moreover, inhibition efficacy did not differ whether SPINT2 was added at the time of infection or 24 h post-infection. Our data suggest that the SPINT2 inhibitor has a strong potential to serve as a novel broad-spectrum antiviral.
Health Inequality among Chinese Older Adults: The Role of Childhood Circumstances

This paper examines the extent to which childhood circumstances contribute to health inequality in old age and how the contributions may vary across key dimensions of health. We link the China Health and Retirement Longitudinal Study (CHARLS) in 2013 and 2015 with its Life History Survey in 2014 to quantify health inequality due to childhood circumstances for which they have little control. We evaluate comprehensive dimensions of health ranging from cognitive health, mental health, physical health, self-rated health to mortality. Our analytic sample includes about 8,000 Chinese persons age above 60. Using the Shapley value decomposition approach, we first show that childhood circumstances may explain 1-23 percent of health inequality in old age across multiple health outcomes. Second, while both direct health-related circumstances and indirect health-related circumstances contribute significantly to health inequality, the latter tends to be more sizable. Our findings support the value of a life course approach in identifying the key determinants of health in old age.
When human-computer interaction meets community citizen science

Human-computer interaction (HCI) studies the design and use of interfaces and interactive systems. HCI has been adopted successfully in modern commercial products. Recently, its use for promoting social good and pursuing sustainability, known as sustainable HCI, has begun to receive wide attention. Conventionally, scientists and decision-makers apply top-down approaches to lead research activities that engage lay people in facilitating sustainability, such as saving energy. We introduce an alternative framework, Community Citizen Science (CCS), to closely connect research and social issues by empowering communities to produce scientific knowledge, represent their needs, address their concerns, and advocate for impact. CCS advances the current science-oriented concept to a deeper level that aims to sustain community engagement when researchers are no longer involved after the intervention of interactive systems.
Reporter system architecture affects measurements of noncanonical amino acid incorporation efficiency and fidelity

The ability to genetically encode noncanonical amino acids (ncAAs) within proteins supports a growing number of applications ranging from fundamental biological studies to enhancing the properties of biological therapeutics. Currently, our quantitative understanding of ncAA incorporation systems is confounded by the diverse set of characterization and analysis approaches used to quantify ncAA incorporation events. While several effective reporter systems support such measurements, it is not clear how quantitative results from different reporters relate to one another, or which details influence measurements most strongly. Here, we evaluate the quantitative performance of single-fluorescent protein reporters, dual-fluorescent protein reporters, and cell surface-displayed protein reporters of ncAA insertion in response to the TAG (amber) codon in yeast. While different reporters support varying levels of apparent readthrough efficiencies, flow cytometry-based evaluations with dual reporters yielded measurements exhibiting consistent quantitative trends and precision across all evaluated conditions. Further investigations of dual-fluorescent protein reporter architecture revealed that quantitative outputs are influenced by stop codon location and N- and C-terminal fluorescent protein identity. Both dual-fluorescent protein reporters and a “drop-in” version of yeast display support quantification of ncAA incorporation in several single-gene knockout strains, revealing strains that enhance ncAA incorporation efficiency without compromising fidelity. Our studies reveal critical details regarding reporter system performance in yeast and how to effectively deploy such reporters. These findings have substantial implications for how to engineer ncAA incorporation systems—and protein translation apparatuses—to better accommodate alternative genetic codes for expanding the chemical diversity of biosynthesized proteins.
Charge-Transfer Character in Excimers of Perylenediimides Self-Assembled on Anodic Aluminum Oxide Membrane Walls

Chromophore aggregation strongly impacts the efficiency of organic photovoltaics (OPVs). Perylene-3,4:9,10-bis(dicarboximide) (PDI)-based electron acceptors have been shown to be excellent alternat...
High-frequency traders and price informativeness during earnings announcements

High frequency traders (HFTs) account for a significant fraction of the total market volume. Prompted by concerns that HFTs reap unfair advantages over other traders by using super-fast trading technologies, some regulatory proposals aim to curb HFTs’ ultra-low-latency activities. However, research suggests that HFTs also play beneficial roles in financial markets, including liquidity provision as voluntary market makers. Currently, little is known about their role in incorporating firm-specific fundamental information into prices. Employing a novel dataset that identifies trades by HFTs and non-HFTs, we find that earnings response coefficients are larger and abnormal price impact of trades are lower when HFTs trade more following earnings announcements, suggesting that HFTs facilitate efficient assimilation of earnings news. HFTs also enhance the forecasting capabilities of financial analysts. Furthermore, HFT participation increases return synchronicity around earnings announcements when multiple firms in the same industry announce earnings on the same day. The evidence suggests that HFTs help incorporate relevant industry information, and this effect arises from HFTs’ liquidity supplying function. We address the endogenous preference of HFTs for large and liquid stocks by including multiple controls for firm size and liquidity, implementing abnormal or change specification for the price impact tests, and performing pre-treatment placebo tests for all of our analyses.
A language for describing boundary scan devices

Boundary scan (IEEE Standard 1149.1-1990) technology is beginning to be embraced in chip and board designs. One key need is a way to simply and effectively describe the feature set of a boundary scan compliant device in a manner both user friendly and suitable for software to utilize. A language subset of VHDL is proposed here for this purpose. As with any new standard, the industry is learning how to apply its rules and mistakes will occur. A derivative effect of the language proposed here is that if a device is not describable by the language, then that device does not comply with the 1149.1 standard. While the converse is not true, the language still allows a syntactic check for compliance as well as a number of semantic checks.
Vanishing-off subgroups and supercharacter theory products

In this paper, we study the vanishing-off subgroups of supercharacters, and use these to determine several new characterizations of supercharacter theory products. In particular, we give a characte...
Remarks on rational points of universal curves

In this notes, we will give some remarks on the results in Rational points of universal curves by Hain. In particular, we consider the universal curves $\mathcal{M}_{g,n+1}\to \mathcal{M}_{g,n}$ and the sections of their algebraic fundamental groups.
Reconstruction and Error-Correction Codes for Polymer-Based Data Storage

Motivated by polymer-based data-storage platforms that use chains of binary synthetic polymers as the recording media and read the content via tandem mass spectrometers, we propose a new family of codes that allows for unique string reconstruction and correction of one mass error. Our approach is based on introducing redundancy that scales logarithmically with the length of the string and allows for the string to be uniquely reconstructed based only on its erroneous substring composition multiset. The key idea behind our unique reconstruction approach is to interleave Catalan-type paths with arbitrary binary strings and “reflect” them so as to allow prefixes and suffixes of the same length to have different weights. For error correction, we add a constant number of bits that provides information about the weights of reflected pairs of bits and hence enable recovery from a single mass error. The asymptotic code rate of the scheme is one, and decoding is accomplished via a simplified version of the backtracking algorithm used for the Turnpike problem.
Finding structure in multi-armed bandits.

Abstract How do humans search for rewards? This question is commonly studied using multi-armed bandit tasks, which require participants to trade off exploration and exploitation. Standard multi-armed bandits assume that each option has an independent reward distribution. However, learning about options independently is unrealistic, since in the real world options often share an underlying structure. We study a class of structured bandit tasks, which we use to probe how generalization guides exploration. In a structured multi-armed bandit, options have a correlation structure dictated by a latent function. We focus on bandits in which rewards are linear functions of an option’s spatial position. Across 5 experiments, we find evidence that participants utilize functional structure to guide their exploration, and also exhibit a learning-to-learn effect across rounds, becoming progressively faster at identifying the latent function. Our experiments rule out several heuristic explanations and show that the same findings obtain with non-linear functions. Comparing several models of learning and decision making, we find that the best model of human behavior in our tasks combines three computational mechanisms: (1) function learning, (2) clustering of reward distributions across rounds, and (3) uncertainty-guided exploration. Our results suggest that human reinforcement learning can utilize latent structure in sophisticated ways to improve efficiency.
Non-Markovian models of environmentally-driven disentanglement in molecular charge qubits

Models of quantum disentanglement are developed for nanometer-scale molecular charge qubits (MCQs). Two MCQs, A and B, are prepared in a Bell state and separated for negligible A– B interact...
Journaling to Develop a Study Abroad Course for Business Majors

Objective - This research explored the cultural and educational insights in Thailand to develop a study abroad course for Business Communication students including a pre-departure segment followed by a trip to Thailand. The context was a small mid-western teaching university in the United States of America. Methodology/Technique - The primary researcher collected textual data by means of keeping a daily journal in Thailand including visits and stays in both urban and rural areas for over a period of two months. The journaling included reflections on the primary researcher's observations and comments about learning sites, opportunities and cultural activities. The data collection also included videotaped interviews, photos of sites, local people, and cultural artifacts to be utilized in the course. Finding & Novelty - Content analysis of the journal yielded three sets of themes which resulted in the development of the course: a) Identification of opportunities to develop and practice intercultural sensitivity, intercultural development, and intercultural competencies; b) recognition of cultural artifacts to bring awareness to the culture of the country visited; and c) identification of a set of practical issues related to international travel. Type of Paper - Empirical.
Have the ACA's Exchanges Succeeded? It's Complicated

The fight over health insurance exchanges epitomizes the rapid evolution of health reform politics in the decade since the passage of the Affordable Care Act (ACA). The ACA's drafters did not expect the exchanges to be contentious because they would expand private insurance coverage to low- and middle-income individuals who were increasingly unable to obtain employer-sponsored health insurance. Instead, exchanges became one of the primary fronts in the war over Obamacare. Have the exchanges been successful? The answer is not straightforward and requires a historical perspective through a federalism lens. What the ACA has accomplished has depended largely on whether states were invested in or resistant to implementation, as well as individual decisions by state leaders working with federal officials. Our account demonstrates that the states that have engaged with the ACA most consistently appear to have experienced greater exchange-related success. But each aspect of states' engagement with or resistance to the ACA must be counted to fully paint this picture, with significant variation among states. This variation should give pause to those considering next steps in health reform, because state variation can mean innovation and improvement but also lack of coverage, disparities, and diminished access to care.
Optimal Timing of Moving Target Defense: A Stackelberg Game Model

As an effective approach to thwarting advanced attacks, moving target defense (MTD) has been applied to various domains. Previous works on MTD, however, mainly focus on deciding the sequence of system configurations to be used and have largely ignored the equally important timing problem. Given that both the migration cost and attack time vary over system configurations, it is crucial to jointly optimize the spatial and temporal decisions in MTD to better protect the system from persistent threats. In this work, we propose a Stackelberg game model for MTD where the defender commits to a joint migration and timing strategy to cope with configuration-dependent migration cost and attack time distribution. The defender's problem is formulated as a semi-Markovian decision process and a nearly optimal MTD strategy is derived by exploiting the unique structure of the game.
Influence of thermomechanical loads on the energetics of precipitation in magnesium aluminum alloys

Abstract We use first principles calculations to study the influence of thermomechanical loads on the energetics of precipitation in magnesium-aluminum alloys. Using Density Functional Theory simulations, we present expressions of the energy of magnesium-aluminum binary solid solutions as a function of concentration, strain and temperature. Additionally, from these calculations, we observe an increase in equilibrium volume (and hence the equilibrium lattice constants) with the increase in concentration of magnesium. We also observe an increase in the cohesive energy of solutions with increase in concentration, and also present their dependence on strain. Calculations also show that the formation enthalpy of β phase solutions to be strongly influenced by hydrostatic stress, however the formation enthalpy of α phase solutions remain unaffected by hydrostatic stress. We present an expression of the free energy of any magnesium aluminum solid solution, that takes into account the contributions of strain and temperature. We note that these expressions can serve as input to process models of magnesium-aluminum alloys. We use these expressions to report the influence of strains and temperature on the solubility limits and equilibrium chemical potential in Mg-Al alloys. Finally, we report the influence of thermomechanical loads on the growth of precipitates, where we observe compressive strains along the c axis promotes growth of precipiates with a (0001)α habit plane, whereas strains along the a and b directions do not influence the growth of precipitates.
Alcohol Induces Mitochondrial Fragmentation and Stress Responses to Maintain Normal Muscle Function in Caenorhabditis Elegans

Chronic excessive ethanol consumption has distinct toxic and adverse effects on a variety of tissues. In skeletal muscle, ethanol causes alcoholic myopathy, which is characterized by myofiber atrophy and the loss of muscle strength. Alcoholic myopathy is more prevalent than all inherited muscle diseases combined. Current evidence indicates that ethanol directly impairs muscle organization and function. However, the underlying mechanism by which ethanol causes toxicity in muscle is poorly understood. Here, we show that the nematode Caenorhabditis elegans exhibits the key features of alcoholic myopathy when exposed to ethanol. As in mammals, ethanol exposure impairs muscle strength and induces the expression of protective genes, including oxidative stress response genes. In addition, ethanol exposure causes the fragmentation of mitochondrial networks aligned with myofibril lattices. This ethanol-induced mitochondrial fragmentation is dependent on the mitochondrial fission factor DRP-1 (dynamin-related protein 1) and its receptor proteins on the outer mitochondrial membrane. Our data indicate that this fragmentation contributes to the activation of the mitochondrial unfolded protein response (UPR). We also found that robust, perpetual mitochondrial UPR activation effectively reduces muscle weakness caused by ethanol exposure. Our results strongly suggest that the modulation of mitochondrial stress responses may provide a method to ameliorate alcohol toxicity and damage to muscle.
TGFβ Regulation of Perilacunar/Canalicular Remodeling Is Sexually Dimorphic

Bone fragility is the product of defects in bone mass and bone quality, both of which show sex-specific differences. Despite this, the cellular and molecular mechanisms underpinning the sexually dimorphic control of bone quality remain unclear, limiting our ability to effectively prevent fractures, especially in postmenopausal osteoporosis. Recently, using male mice, we found that systemic or osteocyte-intrinsic inhibition of TGFβ signaling, achieved using the 9.6-kb DMP1 promoter-driven Cre recombinase (TβRIIocy-/- mice), suppresses osteocyte perilacunar/canalicular remodeling (PLR) and compromises bone quality. Because systemic TGFβ inhibition more robustly increases bone mass in female than male mice, we postulated that sex-specific differences in bone quality could likewise result, in part, from dimorphic regulation of PLR by TGFβ. Moreover, because lactation induces PLR, we examined the effect of TGFβ inhibition on the female skeleton during lactation. In contrast to males, female mice that possess an osteocyte-intrinsic defect in TGFβ signaling were protected from TGFβ-dependent defects in PLR and bone quality. The expression of requisite PLR enzymes, the lacunocanalicular network (LCN), and the flexural strength of female TβRIIocy-/- bone was intact. With lactation, however, bone loss and induction in PLR and osteocytic parathyroid hormone type I receptor (PTHR1) expression, were suppressed in TβRIIocy-/- bone, relative to the control littermates. Indeed, differential control of PTHR1 expression, by TGFβ and other factors, may contribute to dimorphism in PLR regulation in male and female TβRIIocy-/- mice. These findings provide key insights into the sex-based differences in osteocyte PLR that underlie bone quality and highlight TGFβ signaling as a crucial regulator of lactation-induced PLR. © 2020 American Society for Bone and Mineral Research.
Congestion-aware Routing and Rebalancing of Autonomous Mobility-on-Demand Systems in Mixed Traffic

This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on demand mobility under mixed traffic conditions. Specifically, we first devise a network flow model to optimize the AMoD routing and rebalancing strategies in a congestion-aware fashion by accounting for the endogenous impact of AMoD flows on travel time. Second, we capture reactive exogenous traffic consisting of private vehicles selfishly adapting to the AMoD flows in a user centric fashion by leveraging an iterative approach. Finally, we showcase the effectiveness of our framework with a case-study considering the transportation sub-network in New York City. Our results suggest that for high levels of demand, pure AMoD travel can be detrimental due to the additional traffic stemming from its rebalancing flows, whilst the combination of AMoD with walking or micro mobility options can significantly improve the overall system performance.
A proof of the Multijoints Conjecture and Carbery's generalization

We present a new proof of the Joints Theorem without taking derivatives. Then we generalize the proof to prove the Multijoints Conjecture and Carbery's generalization. All results are in any dimension over an arbitrary field.
Disparate expression specificities coded by a shared Hox-C enhancer.

Can a single regulatory sequence be shared by two genes undergoing functional divergence? Here we describe a single promiscuous enhancer within the Drosophila Antennapedia Complex, EO053, that directs aspects of the expression of two adjacent genes, pb (a Hox2 ortholog) and zen2 (a divergent Hox3 paralog), with disparate spatial and temporal expression patterns. We were unable to separate the pb-like and zen2-like specificities within EO053, and we identify sequences affecting both expression patterns. Importantly, genomic deletion experiments demonstrate that EO053 cooperates with additional pb- and zen2-specific enhancers to regulate the mRNA expression of both genes. We examine sequence conservation of EO053 within the Schizophora, and show that patterns of synteny between the Hox2 and Hox3 orthologs in Arthropods are consistent with a shared regulatory relationship extending prior to the Hox3/zen divergence. Thus, EO053 represents an example of two genes having evolved disparate outputs while utilizing this shared regulatory region. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
Decentralized Governance of Digital Platforms

Over the past decade, the rise of blockchain technology has led to the emergence of a growing number of decentralized platforms that are governed less by platform owners and more through community ...
Tiling-based models of perimeter and area

Abstract We consider polygonal tilings of certain regions and use these to give intuitive definitions of tiling-based perimeter and area. We apply these definitions to rhombic tilings of Elnitsky polygons, computing sharp bounds and average values for perimeter tiles in convex centrally symmetric 2n-gons. These bounds and values have implications for the combinatorics of reduced decompositions of permutations. We also classify the permutations whose polygons gave minimal perimeter, defined in two different ways. We conclude by looking at some of these questions in the context of domino tilings, giving a recursive formula and generating function for one family, and describing a family of minimal-perimeter regions.
Real Estate Bubbles and Urban Development

Real estate booms have regularly occurred throughout the world, leaving painful busts and financial crises in their wake. Real estate is a natural investment for more passive debt investors, includ...
Are Consumers Poorly Informed about Fuel Economy? Evidence from Two Experiments

It is often asserted that consumers are poorly informed about and inattentive to fuel economy, causing them to buy low-fuel economy vehicles despite their own best interest. This paper presents evidence on this assertion through two experiments providing fuel economy information to new vehicle shoppers. Results show zero statistical or economic effect on average fuel economy of vehicles purchased. In the context of a simple optimal policy model, the estimates suggest that current and proposed US fuel economy standards are significantly more stringent than needed to address the classes of imperfect information and inattention addressed by our interventions.
Catastrophism versus Uniformitarianism in the History of Star Formation

Author(s): Trimble, V | Abstract: Several early-literate traditions that have come down to us include some view of star formation. That of the Babylonians (and of the Old Testament Jews which derives from the Babylonian) take star formation to have been a single event, part and parcel with the formation of earth, sun, planets, and whatever else exists. Greek mythology, on the other hand, describes a series of events, deriving from interactions between the Gods and mankind. Egyptian pharaohs could join the stars (presumably happy events), while the Chinese tradition expected changes in the heavens normally of unpleasant purport. This separation of views between "long ago, when conditions were very different" (catastrophism) and "ongoing, hence amenable to study" (uniformitarianism) continued until the middle of the 20th century, and we explore some of the events that led to mainstream opinion switching back and forth and to the gradual convergence to the on-going point of view. © 2009 WILEY-VCH Verlag GmbH a Co. KGaA, Weinheim.
5 – Mandatory Roles

Publisher Summary One of the steps of conceptual schema design procedure requires adding mandatory role constraints and check for logical derivations. Once mandatory role constraints are added, a logical derivation check should be performed to see if some fact types are derivable using logical rather than arithmetic operations. Constraints on a derived fact type should normally be derivable. If there is a chain of two or more functional fact types with uniqueness constraints on all the first roles, a functional binary from the start to the end of this chain is derivable if it is defined by projecting on the joint of these fact types—its uniqueness constraint is transitively implied. Derivation rules should be biconditionals. A role is mandatory if and only if, for all states of the database, the role must be played by every member of the population of its object type; otherwise the role is optional. A mandatory role is also called a total role, since it is played by the total population of its object type.
Markov Perfect Equilibria in Repeated Asynchronous Choice Games

Abstract This paper examines the issue of multiplicity of Markov Perfect equilibria in alternating move repeated games. Such games are canonical models of environments with repeated, asynchronous choices due to inertia or replacement. Our main result is that the number of Markov Perfect equilibria is generically finite with respect to stage game payoffs. This holds despite the fact that the stochastic game representation of the alternating move repeated game is “non-generic” in the larger space of state dependent payoffs. We further obtain that the set of completely mixed Markov Perfect equilibria is generically empty with respect to stage game payoffs.
Generalized Linear Mixed Models

This article provides an overview of generalized linear mixed models (GLMMs), how they are fit to data, and the inferences possible when using them. GLMMs are a class of statistical models that handle a wide variety of distributions for the outcome, accommodate nonlinear models, and model correlated data. As regression methods, they are not only capable of estimation and testing of covariate effects but also can be used to draw inferences about correlation structures in the data and are able to calculate predicted values that take into account not only covariates but also observed outcomes. We briefly describe software available for fitting GLMMs.
Body temperature maintenance acclimates in a winter-tenacious songbird.

Flexibility in heat generation and dissipation mechanisms provides endotherms the ability to match their thermoregulatory strategy with external demands. However, the degree to which these two mechanisms account for seasonal changes in body temperature regulation is little explored. Here we present novel data on the regulation of avian body temperature to investigate how birds alter mechanisms of heat production and heat conservation to deal with variation in ambient conditions. We subjected Dark-eyed Juncos (Junco hyemalis) to chronic cold acclimations of varying duration and subsequently quantified their metabolic rates, thermal conductance, and ability to maintain normothermia. Cold-acclimated birds adjusted traits related to both heat generation (increased summit metabolic rate) and heat conservation (decreased conductance) to improve their body temperature regulation. Increases in summit metabolic rate occurred rapidly, but plateaued after one week of cold exposure. In contrast, changes to conductance occurred only after nine weeks of cold exposure. Thus, the ability to maintain body temperature continued to improve throughout the experiment, but the mechanisms underlying this improvement changed through time. Our results demonstrate the ability of birds to adjust thermoregulatory strategies in response to thermal cues and reveal that birds may combine multiple responses to meet the specific demands of their environments.
Who Wants Affordable Housing in their Backyard? An Equilibrium Analysis of Low Income Property Development

We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimato...
Economic conditions and alcohol problems.

This study investigates the relationship between macroeconomic conditions and two alcohol-related outcomes — liquor consumption and highway vehicle fatalities. Fixed effect models are estimated for the 48 contiguous states over the 1975-1988 time period. Alcohol consumption and traffic deaths vary procyclically, with a major portion of the effect of economic downturns attributed to reductions in incomes, rather than employment. The intake of hard liquor is the most sensitive to the state of the macroeconomy. There is no evidence, however, that fluctuations in economic conditions have a disproportionate impact on the drunk-driving of young adults.
Best and Brightest? The Impact of Student Visa Restrictiveness on Who Attends College in the US

Recent immigration policies have created massive uncertainty for international students to obtain F-1 visas. Yet, before the COVID-19 pandemic, student visa applicants already faced an approximately 27 percent refusal rate that varies by time and region. Using data on the universe of SAT takers between 2004 and 2015 matched with college enrollment records, we examine how the anticipated F-1 visa restrictiveness influences US undergraduate enrollment outcomes of international students. Using an instrumental variables approach, we find that a higher anticipated F-1 student visa refusal rate decreases the number of international SAT takers, decreases the probability of sending SAT scores to US colleges, and decreases international student enrollment in the US. The decreases are larger among international students with higher measured academic achievement. We also document academic achievement of international students and show that over 40 percent of high-scoring international SAT takers do not pursue US college education.
Explicit Characterization of Performance of a Class of Networked Linear Control Systems

We quantify performance of a class of interconnected linear dynamical networks with arbitrary nodal dynamics. It is shown that the steady-state variance of the output, which is equivalent to the squared $\mathcal {H}_2$ norm of the network, as a performance measure, can be expressed explicitly as a summation of a rational function over the Laplacian eigenvalues of the underlying graph of the network. Our results generalize the existing works on $\mathcal {H}_2$ -norm characterization for the first- and second-order consensus networks to general consensus-type linear dynamical networks with arbitrary nodal dynamics. We characterize several fundamental limits and scaling laws for the performance of this class of networks. To show the practical usefulness of our results, we discuss how to design decentralized observer-based output feedback mechanisms and how to analyze the performance of composite networks. Numerous examples support our theoretical contributions.
Gut microbiota features on nursing home admission are associated with subsequent acquisition of antibiotic resistant organism colonization

Nursing home (NH) patients often acquire colonization with antibiotic-resistant organisms (AROs). We show that patients exposed to broad-spectrum antibiotics during previous hospitalizations have elevated enterococcal relative abundances on NH admission and higher risk of subsequent ARO acquisition. Our findings suggest that interventions preventing ARO spread should extend beyond NH doors.
Forecasting sequential data using Consistent Koopman Autoencoders

Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physics-based methods related to Koopman theory has been introduced, offering an alternative for processing nonlinear dynamical systems. In this work, we propose a novel Consistent Koopman Autoencoder model which, unlike the majority of existing work, leverages the forward and backward dynamics. Key to our approach is a new analysis which explores the interplay between consistent dynamics and their associated Koopman operators. Our network is directly related to the derived analysis, and its computational requirements are comparable to other baselines. We evaluate our method on a wide range of high-dimensional and short-term dependent problems, and it achieves accurate estimates for significant prediction horizons, while also being robust to noise.
What Happened Following Comprehensive Developmental Education Reform in the Sunshine State? The Impact of Florida’s Developmental Education Reform on Introductory College-Level Course Completion:

Florida’s Senate Bill 1720 allowed many students to bypass developmental education and enroll directly in introductory college-level courses. We use an interrupted time series design to introductor...
Women's Suffrage and Children's Education

While a growing literature shows that women, relative to men, prefer greater investment in children, it is unclear whether empowering women produces better economic outcomes. Exploiting plausibly exogenous variation in US suffrage laws, we show that exposure to suffrage during childhood led to large increases in educational attainment for children from disadvantaged backgrounds, especially Blacks and Southern Whites. We also find that suffrage led to higher earnings alongside education gains, although not for Southern Blacks. Using newly digitized data, we show that education increases are primarily explained by suffrage-induced growth in education spending, although early-life health improvements may have also contributed.