Miracle-dz/UniFAR-FTUs huggingface dataset:
University of Michigan Law School Scholarship Repository University of Michigan Law School Scholarship Repository

Sex offender laws that target recidivism (e.g., community notiﬁcation and residency restriction regimes) are premised—at least in part—on the idea that sex offender proximity and victimization risk are positively correlated. We examine this relationship by combining past and current address information of registered sex offenders (RSOs) with crime data from Baltimore County, Maryland, to study how crime rates vary across neighborhoods with different concentrations of resident RSOs. Contrary to the assumptions of policymakers and the public, we ﬁnd that, all else equal, reported sex offense victimization risk is generally (although not uniformly) lower in neighborhoods where more RSOs live. To further probe the relationship between where RSOs live and where sex crime occurs, we consider whether public knowledge of the identity and proximity of RSOs may make offending in those areas more difﬁcult for (or less attractive to) all potential sex offenders. We exploit the fact that Maryland’s registry became searchable via the Internet during our sample period to investigate how laws that publicly identify RSOs may change the relationship between the residential concentration of RSOs and neighborhood victimization risk. Surprisingly, for some categories of sex crime, notiﬁcation appears to increase the relative risk of victimization in neighborhoods with greater concentrations of RSOs.
Development and demonstration of a water-window soft x-ray microscope using a Z-pinching capillary discharge source

The development and demonstration of a soft X-ray (SXR) microscope, based on a Z-pinching capillary discharge source has been realized. The Z-pinching plasma acts as a source of SXR radiation. A ceramic capacitor bank is pulsed charged up to 80 kV, and discharged through a pre- ionized nitrogen filled ceramic capillary. The discharge current has an amplitude of ~25 kA. Working within the water-window spectral region (λ = 2.88 nm), corresponding to the 1s2-1s2p quantum transition of helium-like nitrogen (N5+), the microscope has a potential in exploiting the natural contrast existing between the K-absorption edges of carbon and oxygen as the main constituents of biological materials, and hence imaging them with high spatial resolution. The SXR microscope uses the grazing incidence ellipsoidal condenser mirror for the illumination, and the Fresnel zone plate optics for the imaging of samples onto a BI-CCD camera. The half- pitch spatial resolution of 100 nm [1] was achieved, as demonstrated by the knife-edge test. In order to enhance the photon-flux at the sample plane, a new scheme for focusing the radiation, from multiple capillary sources has been investigated. Details about the source, and the construction of the microscope are presented and discussed.
Infinite Boltzmann Samplers and Applications to Branching Processes

In this short note, we extend the Boltzmann model for combinatorial random sampling [8] to allow for inﬁnite size objects; in particular, this extension now fully includes Galton-Watson processes. We then illustrate our idea with two examples, one of which is the generation of preﬁxes of inﬁnite Cayley trees.
Toponymy as Commodity: Exploring the Economic Dimensions of Urban Place Names

Over the past decade scholars have directed renewed critical attention to place names. This literature focuses not on the origins and etymology of place names, but instead on the cultural politics of naming itself (Alderman and Inwood, 2013). It examines the decisions involved when attributing (or not attributing) a name to a place and the agendas of those who oversee or sponsor this process. In particular, places names are treated as being implicated in broader issues of power, identity, memory and culture. Thus, there has been considerable critical attention to the practices of “toponymic inscription” (Rose-Redwood et al., 2010) within the urban environment. Urban toponymy is treated as an important element of larger cultural landscapes that are produced in support of a particular political agenda, but which can also be contested by the denizens of the city itself.
An algorithm for solving the Navier–Stokes equations with shear-periodic boundary conditions and its application to homogeneously sheared turbulence

Simulations of homogeneously sheared turbulence (HST) are conducted until a universal self-similar state is established at the long non-dimensional time $\unicode[STIX]{x1D6E4}t=20$ , where $\unicode[STIX]{x1D6E4}$ is the shear rate. The simulations are enabled by a new robust and discretely conservative algorithm. The method solves the governing equations in physical space using the so-called shear-periodic boundary conditions. Convection by the mean homogeneous shear flow is treated implicitly in a split step approach. An iterative Crank–Nicolson time integrator is chosen for robustness and stability. The numerical strategy captures without distortion the Kelvin modes, rotating waves that are fundamental to homogeneously sheared flows and are at the core of rapid distortion theory. Three direct numerical simulations of HST with the initial Taylor scale Reynolds number $Re_{\unicode[STIX]{x1D706}0}=29$ and shear numbers of $S_{0}^{\ast }=\unicode[STIX]{x1D6E4}q^{2}/\unicode[STIX]{x1D716}=3$ , 15 and 27 are performed on a $2048\times 1024\times 1024$ grid. Here, $\unicode[STIX]{x1D716}$ is the dissipation rate and $1/2q^{2}$ is the turbulent kinetic energy. The long integration time considered allows the establishment of a self-similar state observed in experiments but often absent from simulations conducted over shorter times. The asymptotic state appears to be universal with a long time production to dissipation rate ${\mathcal{P}}/\unicode[STIX]{x1D716}\sim 1.5$ and shear number $S^{\ast }\sim 10$ in agreement with experiments. While the small scales exhibit strong anisotropy increasing with initial shear number, the skewness of the transverse velocity derivative decreases with increasing Reynolds number.
Phages on filaments: A genetic screen elucidates the complex interactions between Salmonella enterica flagellin and bacteriophage Chi

The bacterial flagellum is a rotary motor organelle and important virulence factor that propels motile pathogenic bacteria, such as Salmonella enterica, through their surroundings. Bacteriophages, or phages, are viruses that solely infect bacteria. As such, phages have myriad applications in the healthcare field, including phage therapy against antibiotic-resistant bacterial pathogens. Bacteriophage χ (Chi) is a flagellum-dependent (flagellotropic) bacteriophage, which begins its infection cycle by attaching its long tail fiber to the S. enterica flagellar filament as its primary receptor. The interactions between phage and flagellum are poorly understood, as are the reasons that χ only kills certain Salmonella serotypes while others entirely evade phage infection. In this study, we used molecular cloning, targeted mutagenesis, heterologous flagellin expression, and phage-host interaction assays to determine which domains within the flagellar filament protein flagellin mediate this complex interaction. We identified the antigenic N- and C-terminal D2 domains as essential for phage χ binding, with the hypervariable central D3 domain playing a less crucial role. Here, we report that the primary structure of the Salmonella flagellin D2 domains is the major determinant of χ adhesion. The phage susceptibility of a strain is directly tied to these domains. We additionally uncovered important information about flagellar function. The central and most variable domain, D3, is not required for motility in S. Typhimurium 14028s, as it can be deleted or its sequence composition can be significantly altered with minimal impacts on motility. Further knowledge about the complex interactions between flagellotropic phage χ and its primary bacterial receptor may allow genetic engineering of its host range for use as targeted antimicrobial therapy against motile pathogens of the χ-host genera Salmonella, Escherichia, or Serratia.
Learning with Imprinted Weights

Human vision is able to immediately recognize novel visual categories after seeing just one or a few training examples. We describe how to add a similar capability to ConvNet classifiers by directly setting the final layer weights from novel training examples during low-shot learning. We call this process weight imprinting as it directly sets weights for a new category based on an appropriately scaled copy of the embedding layer activations for that training example. The imprinting process provides a valuable complement to training with stochastic gradient descent, as it provides immediate good classification performance and an initialization for any further fine-tuning in the future. We show how this imprinting process is related to proxy-based embeddings. However, it differs in that only a single imprinted weight vector is learned for each novel category, rather than relying on a nearest-neighbor distance to training instances as typically used with embedding methods. Our experiments show that using averaging of imprinted weights provides better generalization than using nearest-neighbor instance embeddings.
Non‐parametric Bayesian multivariate metaregression: an application in environmental epidemiology

In biomedical research, meta‐analysis is a popular tool to combine evidence from multiple studies to investigate an exposure–response association. A two‐stage analytical approach is used in meta‐analysis for its computational convenience and flexibility. The first stage estimates the association for each study whereas the second stage combines the study‐specific estimates correcting for the study‐specific error. The second stage often incorporates study‐specific covariates (metapredictors) and is called metaregression. One application where the two‐stage meta‐analysis is useful is an epidemiological study for the health effects of environmental exposure, which often analyses time series data of exposure and health outcome collected from multiple locations. The first stage models location‐specific association, which is often represented by multiple parameters as the association is non‐linear or delayed, and the second stage conducts a multivariate metaregression with location‐specific characteristics as metapredictors. The currently used multivariate metaregression is a form of normal linear regression, which may be limited as it assumes linearity in metapredictors, residual normality and homoscedasticity. In the paper, we propose a flexible multivariate metaregression in a non‐parametric Bayesian modelling framework incorporating a residual spatial dependence. The proposed metaregression was evaluated through a simulation study and applied to investigate a temperature–mortality association in the 135 US cities.
Seasonal dietary shifts alter the gut microbiota of a frugivorous lizard Teratoscincus roborowskii (Squamata, Sphaerodactylidae)

Abstract Seasonal dietary shifts in animals are important strategies for ecological adaptation. An increasing number of studies have shown that seasonal dietary shifts can influence or even determine the composition of gut microbiota. The Turpan wonder gecko, Teratoscincus roborowskii, lives in extreme desert environments and has a flexible dietary shift to fruit‐eating in warm seasons. However, the effect of such shifts on the gut microbiota is poorly understood. In this study, 16S rRNA sequencing and LC–MS metabolomics were used to examine changes in the gut microbiota composition and metabolic patterns of T. roborowskii. The results demonstrated that the gut microbes of T. roborowskii underwent significant seasonal changes, and the abundance of phylum level in autumn was significantly higher than spring, but meanwhile, the diversity was lower. At the family level, the abundance and diversity of the gut microbiota were both higher in autumn. Firmicutes, Bacteroidetes, and Proteobacteria were the dominant gut microbes of T. roborowskii. Verrucomicrobia and Proteobacteria exhibited dynamic ebb and flow patterns between spring and autumn. Metabolomic profiling also revealed differences mainly related to the formation of secondary bile acids. The pantothenate and CoA biosynthesis, and lysine degradation pathways identified by KEGG enrichment symbolize the exuberant metabolic capacity of T. roborowskii. Furthermore, strong correlations were detected between metabolite types and bacteria, and this correlation may be an important adaptation of T. roborowskii to cope with dietary shifts and improve energy acquisition. Our study provides a theoretical basis for exploring the adaptive evolution of the special frugivorous behavior of T. roborowskii, which is an important progress in the study of gut microbes in desert lizards.
The p- and B-spline versions of the geometrically nonlinear finite cell method and hierarchical refinement strategies for adaptive isogeometric and embedded domain analysis

The thesis at hand addresses two recently introduced concepts intended to support an efficient interaction between geometrical models and finite element analysis: the finite cell method (FCM) and isogeometric analysis (IGA). In the context of the FCM, the B-spline version is introduced, which applies high-order and high-continuity B-spline bases within the FCM concept. Furthermore, the idea of deformation resetting is motivated, which allows for the extension of the finite cell method to geometrically nonlinear problems, and the FCM is combined with hierarchical hp-d adaptivity for local mesh refinement. In the context of IGA, the principle of subdivision is used to derive a hierarchical refinement procedure for non-uniform rational B-splines (NURBS), which combines full analysis suitability with straightforward implementation in tree data structures and simple generalization to higher dimensions.
Assessing Actuarial Projections Accuracy: Traditional vs. Experimental Strategy

This paper gives an overview of the Lee Carter method and reiterates the feasibility of using it to construct mortality forecast for the population data. In a first step, the model is fitted in a traditional way and used to extrapolate forecast of the time-varying mortality index. The observed pattern of the mortality rates shows a different variability at different ages, highlighting that the homoscedasticity hypothesis is quite unrealistic. Thus, in a second step, the paper aims to produce more reliable mortality forecasting, focusing on the errors in the estimation of the model parameters. The robustness of the estimated parameter is analysed throughout an experimental strategy which allows to assess the robustness of the Lee Carter model by inducing the errors to satisfy the homoscedasticity hypothesis. The graphical and numerical results are tested by means of a comparison in terms of prediction accuracy.
Order Reduction of Second Order Systems with Proportional Damping ALA 2006

A common result of modeling (for instance by finite element methods) in some fields like Electrical Circuits and Micro-Electro-Mechanical Systems (MEMS) is a large number of second order differential equations. The most practical solution to handle such large scale models is offered by order reduction. In reduced order modeling of such systems, not only the behavior of the original system should be approximated in the frequency range of interest, but also it is advisable to preserve the structure of the original model. We consider the second order system of the form, { Mz(t) +Dz(t) +Kz(t) = Gu(t), y(t) = Lz(t). (1)
The expression levels of NOS2, HMOX1, and VEGFC in cumulus cells are markers of oocyte maturation and fertilization rate

Throughout the reproductive life of women, cumulus cells (CC) protect the dormant oocyte from damage, act as sensors of the follicular microenvironment, and act as a gatekeeper for oocyte developmental potential. One such mechanism relies on the hypoxia‐tolerance response, which, with age, decreases systematically, including in the ovary. We aimed to evaluate the association between gene expression related to hypoxia and aging in CC and reproductive results in in vitro fertilization cycles. We recruited 94 women undergoing controlled ovarian stimulation. Total RNA was extracted from pooled CCs collected after oocyte pick‐up (OPU) and reverse‐transcribed to complementary DNA using random hexamers to test 14 genes related to hypoxia response via HIF1α activation, oxidative stress, and angiogenic responses. The expression of CLU, NOS2, and TXNIP had a positive correlation with age (rs = 0.25, rs = 0.24, and rs = 0.35, respectively). Additionally, NOS2 and HMOX1 expression correlated positively with the retrieval of immature oocytes (rs = 0.22 and rs = 0.40, respectively). Moreover, VEGFC levels decreased overall with increasing fertilization rate, independently of age (rs = −0.29). We found that the fertilization potential of a cohort of oocytes is related to the ability of CC to respond to oxidative stress and hypoxia with age, pointing at NOS2, HMOX1, and VEGFC expression as markers for oocyte maturation and fertilization success.
Optimization of Exposure Time Division for Multi-object Photometry

Optical observations of wide fields of view entail the problem of selecting the best exposure time. As many objects are usually observed simultaneously, the quality of photometry of the brightest ones is always better than that of the dimmer ones, even though all of them are frequently equally interesting for astronomers. Thus, measuring all objects with the highest possible precision is desirable. In this paper, we present a new optimization algorithm, dedicated for the division of exposure time into sub-exposures, which enables photometry with a more balanced noise budget. The proposed technique increases the photometric precision of dimmer objects at the expense of the measurement fidelity of the brightest ones. We have tested the method on real observations using two telescope setups, demonstrating its usefulness and good consistency with theoretical expectations. The main application of our approach is a wide range of sky surveys, including ones performed by space telescopes. The method can be used to plan virtually any photometric observation of objects that show a wide range of magnitudes.
Opportunistic Routing-Aided Cooperative Communication Network With Energy Harvesting

In this article, a cooperative communication network based on energy-harvesting (EH) decode-and-forward (DF) relays that harvest energy from the ambience using buffers with the harvest-store-use (HSU) architecture is considered. An opportunistic routing (OR) protocol, which selects the transmission path of packet based on the node transmission priority, is proposed to improve data delivery in this network. Additionally, an algorithm based on the state transition matrix (STM) is proposed to obtain the probability distribution of the candidate broadcast node set. Based on the probability distribution, the existence conditions and the theoretical expressions for the limiting distribution of energy in energy buffers using a discrete-time continuous-state space Markov chain (DCSMC) model are derived. Furthermore, the closed-form expressions for network outage probability and throughput are obtained with the help of the limiting distributions of energy stored in buffers. Numerous experiments have been performed to validate the derived theoretical expressions of the performance of this cooperative communication network.
The Binarized Scoring Rule of Belief Elicitation

We introduce a simple method of constructing an incentive compatible scoring rule to elicit an agent’s belief about a random variable. The method does not depend on the exact form of the agent’s utility function. Independent of her risk preference, it is optimal to report the value that minimizes the expected value of a loss function specified in the incentive scheme. The agent receives a fixed prize when her prediction error, defined by the relevant loss function, is smaller than a randomly generated value and earns a smaller prize or a penalty otherwise. Adjusting the loss function according to the belief elicitation objective, the scoring rule can be used in a rich assortment of situations. Results from our probability elicitation experiment show that subjects’ predictions are closer to the true probability under this scoring rule compared to the quadratic scoring rule.
Episodic future thinking in type 2 diabetes: Further development and validation of the Health Information Thinking control for clinical trials

Episodic Future Thinking (EFT) reduces delay discounting and may have the potential as a clinical tool to increase the likelihood of health-promoting behaviors. However, evaluations of EFT in clinical settings require control conditions that match the effort and frequency of cue generation, as well as participants’ expectations of improvement. The Health Information Thinking (HIT) control addresses these issues, but how this control affects delay discounting in individuals with diabetes and obesity when utilizing diabetes-management specific health-information vignettes is unknown. Moreover, little research has explored whether EFT reduces delay discounting in individuals with type 2 diabetes. To this end, we examined the impact of EFT, HIT, and a secondary no-cue control condition (NCC; assessments as usual) on delay discounting in 434 adults with self-reported type 2 diabetes and obesity recruited using Amazon Mechanical Turk. After completing an initial screening questionnaire, eligible participants reported demographics, then were randomized to EFT, HIT, or NCC conditions. Following the generation of seven EFT or HIT cues, participants assigned to EFT or HIT conditions completed a delay discounting task while imagining EFT or HIT cues; no-cue participants completed the task without cues. EFT participants demonstrated significantly lower delay discounting levels than HIT or NCC participants; no differences in delay discounting between HIT and NCC participants were observed. These results suggest that engaging in EFT, but not diabetes-specific HIT, results in lower delay discounting in adults with type 2 diabetes and obesity. This provides further evidence for the appropriateness of the HIT control for clinical trials examining the effect of EFT on delay discounting in adults with self-reported type 2 diabetes.
Effects of nature-adapted lighting solutions (“Virtual Sky”) on subjective and objective correlates of sleepiness, well-being, visual and cognitive performance at the workplace

Exposure to natural daylight benefits human well-being, alertness, circadian rhythms and sleep. Many workplaces have limited or no access to daylight. Thus, we implemented a light-panel (“Virtual Sky“), which reproduced nature-adapted light scenarios. In a laboratory office environment, three lighting scenarios were presented during the day: two lighting conditions with nature-adapted spectral light distributions, one with static and one with dynamic clouds, and a standard office lighting condition. We compared the impact of the three lighting scenarios on subjective and objective measures of alertness, cognitive performance, wellbeing, visual comfort, contrast sensitivity, and cortisol levels in 18 healthy young male volunteers in a within-participant cross-over study design. We found no evidence that an 8-h lighting scenario with static or dynamic clouds during the waking day (9am-5pm) was associated with any significant effect on objective and/or subjective alertness, cognitive performance and morning cortisol concentrations compared to standard workplace lighting. However, the dynamic light scenario was accompanied with lower levels of perceived tensionafter completing cognitive tasks and less effort to concentrate compared to the static lighting scenarios. Our findings suggest that apart from smaller effects on tension and concentration effort, nature-adapted lighting conditions did not improve daytime alertness and cognitive performance in healthy well-rested young participants, as compared to standard office lighting.