cssi/SciSciGPT-SciSciNet huggingface dataset:
The materials science of halide perovskites and solar cells

Organic-inorganic halide perovskite (OIHP) materials at the heart of perovskite solar cells (PSCs) have unique crystal structures, which entail rotating organic cations inside inorganic cages, imparting them with desirable optical, electronic, and defect-tolerance properties. To exploit these properties for PSCs application, the reliable deposition of high-quality OIHP thin films over large areas is critically important. The microstructures and grain-boundary networks in the resulting polycrystalline OIHP thin films are equally important as they control the PSC performance and stability. Fundamental phenomena pertaining to synthesis, crystallization, coarsening, microstructural-evolution, and grain-boundary functionalization involved in the processing of OIHP thin films for PSCs are discussed with specific examples. In addition, the unique mechanical behavior of halide perovskites, and its implication on the reliability of PSCs, are discussed.
CLAMP and Zelda function together to promote Drosophila zygotic genome activation

During the essential and conserved process of zygotic genome activation (ZGA), chromatin accessibility must increase to promote transcription. Drosophila is a well-established model for defining mechanisms that drive ZGA. Zelda (ZLD) is a key pioneer transcription factor (TF) that promotes ZGA in the Drosophila embryo. However, many genomic loci that contain GA-rich motifs become accessible during ZGA independent of ZLD. Therefore, we hypothesized that other early TFs that function with ZLD have not yet been identified, especially those that are capable of binding to GA-rich motifs such as chromatin-linked adaptor for male-specific lethal (MSL) proteins (CLAMP). Here, we demonstrate that Drosophila embryonic development requires maternal CLAMP to (1) activate zygotic transcription; (2) increase chromatin accessibility at promoters of specific genes that often encode other essential TFs; and (3) enhance chromatin accessibility and facilitate ZLD occupancy at a subset of key embryonic promoters. Thus, CLAMP functions as a pioneer factor that plays a targeted yet essential role in ZGA.
Elucidation of an anaerobic pathway for metabolism of l-carnitine-derived γ-butyrobetaine to trimethylamine in human gut bacteria.

Trimethylamine (TMA) is an important gut microbial metabolite strongly associated with human disease. There are prominent gaps in our understanding of how TMA is produced from the essential dietary nutrient l-carnitine, particularly in the anoxic environment of the human gut where oxygen-dependent l-carnitine–metabolizing enzymes are likely inactive. Here, we elucidate the chemical and genetic basis for anaerobic TMA generation from the l-carnitine–derived metabolite γ-butyrobetaine (γbb) by the human gut bacterium Emergencia timonensis. We identify a set of genes up-regulated by γbb and demonstrate that the enzymes encoded by the induced γbb utilization (bbu) gene cluster convert γbb to TMA. The key TMA-generating step is catalyzed by a previously unknown type of TMA-lyase enzyme that utilizes a putative flavin cofactor to catalyze a redox-neutral transformation. We identify additional cultured and uncultured host-associated bacteria that possess the bbu gene cluster, providing insights into the distribution of anaerobic γbb metabolism. Lastly, we present genetic, transcriptional, and metabolomic evidence that confirms the relevance of this metabolic pathway in the human gut microbiota. These analyses indicate that the anaerobic pathway is a more substantial contributor to TMA generation from l-carnitine in the human gut than the previously proposed aerobic pathway. The discovery and characterization of the bbu pathway provides the critical missing link in anaerobic metabolism of l-carnitine to TMA, enabling investigation into the connection between this microbial function and human disease.
Improving generalization of deep learning models for diagnostic pathology by increasing variability in training data: Experiments on osteosarcoma subtypes

Background: Artificial intelligence has an emerging progress in diagnostic pathology. A large number of studies of applying deep learning models to histopathological images have been published in recent years. While many studies claim high accuracies, they may fall into the pitfalls of overfitting and lack of generalization due to the high variability of the histopathological images. Aims and Objects: Use the model training of osteosarcoma as an example to illustrate the pitfalls of overfitting and how the addition of model input variability can help improve model performance. Materials and Methods: We use the publicly available osteosarcoma dataset to retrain a previously published classification model for osteosarcoma. We partition the same set of images into the training and testing datasets differently than the original study: the test dataset consists of images from one patient while the training dataset consists images of all other patients. We also show the influence of training data variability on model performance by collecting a minimal dataset of 10 osteosarcoma subtypes as well as benign tissues and benign bone tumors of differentiation. Results: The performance of the re-trained model on the test set using the new partition schema declines dramatically, indicating a lack of model generalization and overfitting. We show the additions of more and moresubtypes into the training data step by step under the same model schema yield a series of coherent models with increasing performances. Conclusions: In conclusion, we bring forward data preprocessing and collection tactics for histopathological images of high variability to avoid the pitfalls of overfitting and build deep learning models of higher generalization abilities.
Benchmarking Social Spending Using Efficiency Frontiers

Developing and low-income economies face the challenge of increasing public spending to address sizeable infrastructure and social gaps while simultaneously restoring the fiscal discipline weakened to countervail the effect of the global recession. Increasing the efficiency of social spending could be the key policy to address the dilemma as it allows the optimization of the existing resources by reducing spending inefficiencies. This paper quantifies the efficiency gap in the health and education sectors for a large sample of developing and emerging countries and proposes measures to reduce these gaps for the specific cases of El Salvador, Guatemala, and Honduras.
Simulating the dynamics of braiding of Majorana zero modes using an IBM quantum computer

We preform dynamic state evolution on an IBM quantum computer using a simulation of braiding Majorana zero modes as a benchmark for success. We find the native quantum gates introduce too much noise to observe braiding. Instead, we use Qiskit Pulse to develop scaled 2-qubit quantum gates that better match the unitary time evolution operator and enable us to observe braiding. This paper demonstrates that quantum computers can be used for simulation, and highlights the use of pulse-level control for programming quantum computers and constitutes the first experimental evidence of braiding via dynamical Hamiltonian evolution.
Harmonic analysis on the positive rationals: computation of character sums

The authors carry out detailed calculations of group character sums attached to the multiplicative representation of positive rationals by pairs of sequences $$an+b$$ , $$An+B$$ , $$n = 1, 2 \dots $$ , with the integer coefficients a, b, A, B satisfying $$a>0$$ , $$A>0$$ , $$aB - Ab \ne 0$$ . Non-intuitive examples are given.
Vector and Functional Commitments from Lattices.

Vector commitment (VC) schemes allow one to commit concisely to an ordered sequence of values, so that the values at desired positions can later be proved concisely. In addition, a VC can be statelessly updatable, meaning that commitments and proofs can be updated to reflect changes to individual entries, using knowledge of just those changes (and not the entire vector). VCs have found important applications in verifiable outsourced databases, cryptographic accumulators, and cryptocurrencies. However, to date there have been relatively few post-quantum constructions, i.e., ones that are plausibly secure against quantum attacks.
Weakly Supervised Registration of Prostate MRI and Histopathology Images

The interpretation of prostate MRI suffers from low agreement across radiologists due to the subtle differences between cancer and normal tissue. Image registration addresses this issue by accurately mapping the ground-truth cancer labels from surgical histopathology images onto MRI. Cancer labels achieved by image registration can be used to improve radiologists’ interpretation of MRI by training deep learning models for early detection of prostate cancer. A major limitation of current automated registration approaches is that they require manual prostate segmentations, which is a time-consuming task, prone to errors. This paper presents a weakly supervised approach for affine and deformable registration of MRI and histopathology images without requiring prostate segmentations. We used manual prostate segmentations and mono-modal synthetic image pairs to train our registration networks to align prostate boundaries and local prostate features. Although prostate segmentations were used during the training of the network, such segmentations were not needed when registering unseen images at inference time. We trained and validated our registration network with 135 and 10 patients from an internal cohort, respectively. We tested the performance of our method using 16 patients from the internal cohort and 22 patients from an external cohort. The results show that our weakly supervised method has achieved significantly higher registration accuracy than a state-of-the-art method run without prostate segmentations. Our deep learning framework will ease the registration of MRI and histopathology images by obviating the need for prostate segmentations.
Optimizing microtubule arrangements for rapid cargo capture.

Abstract Cellular functions such as autophagy, cell signaling, and vesicular trafficking involve the retrograde transport of motor-driven cargo along microtubules. Typically, newly formed cargo engages in slow undirected movement from its point of origin before attaching to a microtubule. In some cell types, cargo destined for delivery to the perinuclear region relies on capture at dynein-enriched loading zones located near microtubule plus ends. Such systems include extended cell regions of neurites and fungal hyphae, where the efficiency of the initial diffusive loading process depends on the axial distribution of microtubule plus ends relative to the initial cargo position. We use analytic mean first-passage time calculations and numerical simulations to model diffusive capture processes in tubular cells, exploring how the spatial arrangement of microtubule plus ends affects the efficiency of retrograde cargo transport. Our model delineates the key features of optimal microtubule arrangements that minimize mean cargo capture times. Namely, we show that configurations with a single microtubule plus end abutting the distal tip and broadly distributed other plus ends allow for efficient capture in a variety of different scenarios for retrograde transport. Live-cell imaging of microtubule plus ends in Aspergillus nidulans hyphae indicates that their distributions exhibit these optimal qualitative features. Our results highlight important coupling effects between the distribution of microtubule tips and retrograde cargo transport, providing guiding principles for the spatial arrangement of microtubules within tubular cell regions.
Ssl2/TFIIH function in transcription start site scanning by RNA polymerase II in Saccharomyces cerevisiae.

In eukaryotic organisms such as yeast, the process of converting genes into proteins begins with the transcription of DNA sequences into mRNA molecules. An enzyme called RNA Polymerase II (Pol II) is responsible for creating new strands of mRNA, but a variety of other so called transcription factors is also needed to kickstart the transcription process. These transcription factors are delivered to genes, where they attach to specific sequences, or promoters, which sit at the beginning of each gene. Once these transcription factors are in place, the double stranded DNA is unzipped to provide access to the DNA that will serve as the template for transcription. In budding yeast, Pol II and another specific transcription factor, known as TFIIH, work together to scan these promoter sequences to find the appropriate start sites of mRNA synthesis. However, several aspects of this process, such as how TFIIH works in promoter scanning, how far its scanning functions can extend, and how its activity is controlled, are currently poorly understood. Zhao et al. have investigated these questions in budding yeast. Using a range of genetic and genomic techniques, Zhao et al. found that certain sections of TFIIH were involved in choosing specific transcription start sites of mRNA synthesis during promoter scanning. These sections were identical in different eukaryotic organisms from yeast to humans, suggesting that these regions may be important for tuning or controlling the activity of TFIIH. Moreover, in yeast, the activity of TFIIH determines how far the scanning unit was able to move along the promoter DNA. Finally, Zhao et al. found that the initiation by promoter scanning was regulated by two distinct networks. The first network controlled how well mRNA synthesis could be initiated at individual transcription start sites; and the second network – driven by TFIIH – controlled which promoter sequences could be scanned to initiate transcription. This research provides an in-depth look into the early steps of the process of converting DNA into mRNA. The biological machinery used to initiate and control this action is highly conserved between yeast and humans, suggesting that the mechanisms for controlling the activity of these factors could be similar, even if their initiation processes may differ.
Identification of Causal Effects Within Principal Strata Using Auxiliary Variables

In causal inference, principal stratification is a framework for dealing with a posttreatment intermediate variable between a treatment and an outcome. In this framework, the principal strata are defined by the joint potential values of the intermediate variable. Because the principal strata are not fully observable, the causal effects within them, also known as the principal causal effects, are not identifiable without additional assumptions. Several previous empirical studies leveraged auxiliary variables to improve the inference of principal causal effects. We establish a general theory for the identification and estimation of principal causal effects with auxiliary variables, which provides a solid foundation for statistical inference and more insights for model building in empirical research. In particular, we consider two commonly used assumptions for principal stratification problems: principal ignorability and the conditional independence between the auxiliary variable and the outcome given principal strata and covariates. Under each assumption, we give nonparametric and semiparametric identification results without modeling the outcome. When neither assumption is plausible, we propose a large class of flexible parametric and semiparametric models for identifying principal causal effects. Our theory not only establishes formal identification results of several models that have been used in previous empirical studies but also generalizes them to allow for different types of outcomes and intermediate variables.
Thermodynamically consistent physics-informed neural networks for hyperbolic systems

Abstract Physics-informed neural network architectures have emerged as a powerful tool for developing flexible PDE solvers that easily assimilate data. When applied to problems in shock physics however, these approaches face challenges related to the collocation-based PDE discretization underpinning them. By instead adopting a least squares space-time control volume scheme, we obtain a scheme which more naturally handles: regularity requirements, imposition of boundary conditions, entropy compatibility, and conservation, substantially reducing requisite hyperparameters in the process. Additionally, connections to classical finite volume methods allows application of inductive biases toward entropy solutions and total variation diminishing properties. For inverse problems in shock hydrodynamics, we propose inductive biases for discovering thermodynamically consistent equations of state that guarantee hyperbolicity. This framework therefore provides a means of discovering continuum shock models from molecular simulations of rarefied gases and metals. The output of the learning process provides a data-driven equation of state which may be incorporated into traditional shock hydrodynamics codes.
Situational Confidence Assistance for Lifelong Shared Autonomy

Shared autonomy enables robots to infer user intent and assist in accomplishing it. But when the user wants to do a new task that the robot does not know about, shared autonomy will hinder their performance by attempting to assist them with something that is not their intent. Our key idea is that the robot can detect when its repertoire of intents is insufficient to explain the user's input, and give them back control. This then enables the robot to observe unhindered task execution, learn the new intent behind it, and add it to this repertoire. We demonstrate with both a case study and a user study that our proposed method maintains good performance when the human's intent is in the robot's repertoire, outperforms prior shared autonomy approaches when it isn't, and successfully learns new skills, enabling efficient lifelong learning for confidence-based shared autonomy.
CADA: Multi-scale Collaborative Adversarial Domain Adaptation for Unsupervised Optic Disc and Cup Segmentation

Abstract Recently, deep neural networks have demonstrated comparable and even better performance than board-certified ophthalmologists in well-annotated datasets. However, the diversity of retinal imaging devices poses a significant challenge: domain shift, which leads to performance degradation when applying the deep learning models trained on one domain to new testing domains. In this paper, we propose a domain adaptation framework comprising of multi-scale inputs along with multiple domain adaptors applied hierarchically in both feature and output spaces. The proposed training strategy and novel unsupervised domain adaptation framework, called Collaborative Adversarial Domain Adaptation (CADA), can effectively overcome the domain shift challenge. Multi-scale inputs can reduce the information loss due to the pooling layers used in the network for feature extraction, while our proposed CADA is an interactive paradigm that presents an exquisite collaborative adaptation through both adversarial learning and ensembling weights at different network layers. In particular, to produce a better prediction for the unlabeled target domain data, we simultaneously achieve domain invariance and model generalizability via adversarial learning at multi-scale outputs from different levels of network layers and maintaining an exponential moving average (EMA) of the historical weights during training. Without annotating any sample from the target domain, multiple adversarial losses in encoder and decoder layers guide the extraction of domain-invariant features to confuse the domain classifier. Meanwhile, the ensembling of weights via EMA reduces the uncertainty of adapting multiple discriminator learning. Comprehensive experimental results demonstrate that our CADA model incorporating multi-scale input training can overcome performance degradation and outperform state-of-the-art domain adaptation methods in segmenting retinal optic disc and cup from fundus images stemming from the REFUGE, Drishti-GS, and Rim-One-r3 datasets. The code is available at https://github.com/cswin/CADA.
ZIP9 is a Druggable Determinant of Sex Differences in Melanoma.

Melanoma and most other cancers occur more frequently and have worse prognosis in males compared with females. Though sex steroids are thought to be involved, classical androgen and estrogen receptors are not detectable in most melanomas. Here we show that testosterone promotes melanoma proliferation by activating ZIP9 (SLC39A9), a zinc transporter that is widely expressed in human melanoma but not intentionally targeted by available therapeutics. This testosterone activity required an influx of zinc, activation of MAPK, and nuclear translocation of YAP. FDA-approved inhibitors of the classical androgen receptor also inhibited ZIP9, thereby antagonizing the pro-tumorigenic effects of testosterone in melanoma. In male mice, androgen receptor inhibitors suppressed growth of ZIP9-expressing melanomas but had no effect on isogenic melanomas lacking ZIP9 or on melanomas in females. These data suggest that ZIP9 might be effectively targeted in melanoma and other cancers by repurposing androgen receptor inhibitors that are currently approved only for prostate cancer.
Methylation studies in Peromyscus: aging, altitude adaptation, and monogamy

DNA methylation-based biomarkers of aging have been developed for humans and many other mammals and could be used to assess how stress factors impact aging. Deer mice (Peromyscus) are long-living rodents that have emerged as an informative model to study aging, adaptation to extreme environments, and monogamous behavior. In the present study, we have undertaken an exhaustive, genome-wide analysis of DNA methylation in Peromyscus, spanning different species, stocks, sexes, tissues, and age cohorts. We describe DNA methylation-based estimators of age for different species of deer mice based on novel DNA methylation data generated on highly conserved mammalian CpGs measured with a custom array. The multi-tissue epigenetic clock for deer mice was trained on 3 tissues (tail, liver, and brain). Two human-Peromyscus clocks accurately measure age and relative age, respectively. We present CpGs and enriched pathways that relate to different conditions such as chronological age, high altitude, and monogamous behavior. Overall, this study provides a first step towards studying the epigenetic correlates of monogamous behavior and adaptation to high altitude in Peromyscus. The human-Peromyscus epigenetic clocks are expected to provide a significant boost to the attractiveness of Peromyscus as a biological model.
PT-Symmetry-Enabled Spin Circular Photogalvanic Effect in Antiferromagnetic Insulators.

The short timescale spin dynamics in antiferromagnets is an attractive feature from the standpoint of ultrafast spintronics. Yet generating highly polarized spin current at room temperature remains a fundamental challenge for antiferromagnets. We propose a spin circular photogalvanic effect (spin CPGE), in which circularly polarized light can produce a highly spin-polarized current at room temperature, through an ``injection-current-like'' mechanism in parity-time ($PT$)-symmetric antiferromagnetic (AFM) insulators. We demonstrate this effect by first-principles simulations of bilayer ${\mathrm{CrI}}_{3}$ and room-temperature-AFM hematite. The spin CPGE is significant, and the magnitude of spin photocurrent is comparable with the widely observed charge photocurrent in ferroelectric materials. Interestingly, this spin photocurrent is not sensitive to spin-orbit interactions, which were regarded as fundamental mechanisms for generating spin current. Given the fast response of light-matter interactions, large energy scale, and insensitivity to spin-orbit interactions, our work gives hope to realizing fast-dynamic and temperature-robust pure spin current in a wide range of $PT$-symmetric AFM materials, including topological axion insulators and weak-relativistic magnetic insulators.
CondiDiag1.0: A flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.
SD-QA: Spoken Dialectal Question Answering for the Real World.

Question answering (QA) systems are now available through numerous commercial applications for a wide variety of domains, serving millions of users that interact with them via speech interfaces. However, current benchmarks in QA research do not account for the errors that speech recognition models might introduce, nor do they consider the language variations (dialects) of the users. To address this gap, we augment an existing QA dataset to construct a multi-dialect, spoken QA benchmark on five languages (Arabic, Bengali, English, Kiswahili, Korean) with more than 68k audio prompts in 24 dialects from 255 speakers. We provide baseline results showcasing the real-world performance of QA systems and analyze the effect of language variety and other sensitive speaker attributes on downstream performance. Last, we study the fairness of the ASR and QA models with respect to the underlying user populations.
A Simple Model of Corporate Fiduciary Duties: With an Application to Corporate Compliance

This article models the duty of care as a response to moral hazard where the principal seeks to induce effort that is costly to the agent and unobservable by the principal. The duty of loyalty, by contrast, is modeled as a response to adverse selection where the principal seeks truthful disclosure of private information held by the agent. This model of corporate loyalty differs importantly with standard adverse selection models, however, in that the principal cannot use an observable and verifiable outcome as a screening mechanism to ensure honest disclosure and must rely upon an external third-party audit technology, such as the court system. This article extends these simple models to the issue of corporate compliance and argues that the optimal judicial approach would define the duty to monitor as a subset of due care–and not loyalty–but hold that the usual legal protections provided for due care violations no longer apply. The framework set forth provides a theoretical justification for drawing such a conceptual distinction.
Facial landmark points detection using knowledge distillation-based neural networks

Abstract Facial landmark detection is a vital step for numerous facial image analysis applications. Although some deep learning-based methods have achieved good performances in this task, they are often not suitable for running on mobile devices. Such methods rely on networks with many parameters, which makes the training and inference time-consuming. Training lightweight neural networks such as MobileNets are often challenging, and the models might have low accuracy. Inspired by knowledge distillation (KD), this paper presents a novel loss function to train a lightweight Student network (e.g., MobileNetV2) for facial landmark detection. We use two Teacher networks, a Tolerant-Teacher and a Tough-Teacher in conjunction with the Student network. The Tolerant-Teacher is trained using Soft-landmarks created by active shape models, while the Tough-Teacher is trained using the ground truth (aka Hard-landmarks) landmark points. To utilize the facial landmark points predicted by the Teacher networks, we define an Assistive Loss (ALoss) for each Teacher network. Moreover, we define a loss function called KD-Loss that utilizes the facial landmark points predicted by the two pre-trained Teacher networks (EfficientNet-b3) to guide the lightweight Student network towards predicting the Hard-landmarks. Our experimental results on three challenging facial datasets show that the proposed architecture will result in a better-trained Student network that can extract facial landmark points with high accuracy.
Transient absorption microscopy studies of single metal and semiconductor nanostructures

Transient absorption microscopy is an experimental technique that allows nanomaterials to be studied with ultrafast time resolution and diffraction limited spatial resolution. This paper describes recent results from using transient absorption microscopy to investigate energy relaxation processes in single metal and semiconductor nanowires. The processes that have been examined include charge carrier trapping in semiconductor nanostructures, the motion of surface plasmon polaritons in metal nanowires, and the damping of the acoustic breathing modes of metal nanowires by high viscosity solvents.
Iron function and dysfunction in the brain: A pediatric neurologist's perspective

Iron plays a critical role in brain development and physiology, cytoplasmic protein function, and mitochondrial reactions. Brain iron levels are regulated tightly, and pathologies can result from both iron deficiency (learning and memory deficits, neuronal and dendritic developmental alterations, impaired myelin function, and abnormal neurotransmitter regulation) and iron overload (free radical production and oxidative stress, as proposed for Parkinson and Alzheimer diseases as well as rare genetic disorders of iron accumulation). This review briefly summarizes the roles of iron in normal and abnormal brain function, with emphasis on the developing brain, and describes some disorders deriving from deficient or excessive iron levels.
The miR-124-Prolyl Hydroxylase P4HA1-MMP1 axis plays a critical role in prostate cancer progression

Collagen prolyl hydroxylases (C-P4HAs) are a family of enzymes involved in collagen biogenesis. One of the isoforms of P4HA, Prolyl 4-hydroxylase, alpha polypeptide I (P4HA1), catalyzes the formation of 4-hydroxyproline that is essential for the proper three-dimensional folding of newly synthesized procollagen chains. Here, we show the overexpression of P4HA1 in aggressive prostate cancer. Immunohistochemical analysis using tissue microarray demonstrated that P4HA1 expression was correlated with prostate cancer progression. Using in vitro studies, we showed that P4HA1 plays a critical role in prostate cancer cell growth and tumor progression. Expression profiling studies using P4HA1-modulated prostate cells suggested regulation of Matrix metalloprotease 1. The invasive properties of P4HA1 overexpressing cells were reversed by blocking MMP1. Our studies indicate P4HA1 copy number gain in a subset of metastatic prostate tumors and its expression is also regulated by microRNA-124. MiR-124 in turn is negatively regulated by transcriptional repressors EZH2 and CtBP1, both of which are overexpressed in aggressive prostate cancer. Chick chorioallantoic membrane (CAM) assay and mice xenograft investigations show that P4HA1 is required for tumor growth and metastasis in vivo. Our observations suggest that P4HA1 plays a critical role in prostate cancer progression and could serve as a viable therapeutic target.
The Immigration Hotel

The image of a hotel with each floor representing different immigration statuses provides a way to introduce students to the confounding immigration system we have in the United States, on both technical and policy levels. The imagery of the hotel helps to explain how one gets into the immigration hotel (the admissions process), and also how one gets kicked out (through various forms of removal proceedings). Analogies to different forms of eviction allow for parallels as well, depending on the nature of the building in question (e.g. hotel room, apartment, or condo) and the legal status of the person being removed (temporary traveler, renter/lease holder, home owner). Drawing on property law also allows for different floors to represent different types of immigration status. In a nutshell, citizenship occupies the top floor and is akin to cooperative or condominium ownership. Legal permanent residency occupies the apartment floor, with occupants tied to leases with strict terms. Breaking the terms of the lease can lead to eviction (i.e., deportation). Traditional hotel rooms are reserved for temporary non-immigrant visa holders. Sandwiched on a hard-to-get-to floor between the apartments and the hotel rooms is the sanctuary: a place for refugees, survivors of crimes and human trafficking, unaccompanied children, and those stranded in the US as the result of natural and human made disasters in their homelands. The lobby serves not only as the admissions entry point, but also as a place of legal limbo (sort of like an easement), where people are sometime allowed to hangout for years on end in renewable quasi-status like parole and deferred action. Finally, the basement holds those without status – either they never had it, by entering unauthorized at an unregulated entry point; or those who entered legally but have violated their terms of status. The cellar or dungeon is immigration detention. The building analogy proves durable – both on the surface as an explanatory heuristic (e.g., “citizenship is like ownership”) and as a way to explore the history behind immigration categories (e.g., who has been entitled to citizenship mirrors who has been entitled to own real property). Parallels between the history of property real ownership and its protection (through the use of restrictive covenants) and the history of immigration regulation (such as the Chinese Exclusion Acts) illustrate how the analogy can also do more than just explain the current operation of immigration law, but illuminate how the laws came into being in larger historical context. Racial and economic barriers to real property ownership and control are often paralleled in the immigration hotel – the poor and marginalized often face high challenges to securing immigration status as well as stable and living situations.
Blind identification of OFDM channel using receiver diversity

We investigate non data-aided channel estimation for OFDM systems. By exploiting channel diversity with multiple receive antennas, we propose a blind deterministic algorithm that can perfectly recover the channel response using only a single OFDM block. We study the extension of the proposed algorithm to the case when virtual carriers are present and provide some important identifiability results. In addition to being data efficient, the proposed algorithm is independent of the input symbol constellation, computationally efficient, and superior in performance compared with most existing blind algorithms.
Mapping Mars at Global to Human Scales

We report on current Mars mapping projects in support of NASA planetary exploration. This includes a summary of the current state and accuracy of such mapping at global, regional, and local (human) scales. The availability of Mars Orbiter Laser Altimeter data has revolutionized such mapping. Aside from its use as a global topographic dataset, images can easily be correlated to it with absolute uncertainties of ≈100 m horizontally. We are using this to create a revised version of the global Mars digital image mosaic (MDIM) that will have absolute errors of ≈231 m (one pixel) and improved cosmetic characteristics. We are undertaking stereo-topographic mapping at regional to local scales, using Viking and Mars Orbiter Camera Narrow Angle (NA) images, with horizontal resolutions of 600 to 5 m, and expected vertical precision of 200 to 1 m. Derived topography and altimetric information can also be used to calibrate shape-from-shading (photoclinometry) topographic models at down to single-pixel resolution (i.e. 1.4 m for NA images). Products of these efforts have a multitude of purposes, from assisting in large-scale geologic mapping, to characterizing the geology/safety of proposed landing sites. Plans are underway to also use THEMIS, HRSC, and HiRISE camera data in future efforts.
Estimates of Apparent Survival Rates for Forest Birds in Eastern Ecuador

Knowledge of survival rates of Neotropical landbirds remains limited, with estimates of apparent survival available from relatively few sites and species. We used capture–mark–recapture models to estimate apparent survival of 31 species from eastern Ecuador based on data collected from 2001 to 2006. Models assuming constant survival had highest support for 27 species; models incorporating effects of transients were highest for four. Average apparent survival across 30 species of passerines was 0.58 (± 0.02 SE); apparent survival was lower during the first interval after initial capture (φ 1 :m ean= 0.49 ± 0.03) than during subsequent intervals (φ 2 :m ean= 0.60 ± 0.02). Apparent survival was similar among three families represented by at least four species (Thamnophilidae: 0.57 ± 0.03, N = 10; Furnariidae: 0.59 ± 0.03, N = 5; Pipridae: 0.56 ± 0.02, N = 4). There was no indication that species that occur in flocks had higher survival than nonflocking species (obligate flock members: 0.57 ± 0.03, N = 10; facultative flock members: 0.56 ± 0.04, N = 5; nonflocking: 0.59 ± 0.03, N = 15). Comparisons of published estimates of apparent survival of tropical species demonstrated substantial differences among species and, in some cases, within species across different site si n the Neotropics. Our results support previous studies that concluded that early estimates of high (> 85%) survival in tropical birds may not be representative of all tropical species. Future studies should focus on understanding factors (e.g., life-history traits) that promote differences in survival among species within tropical forests.
Effects of Habitat Loss and Fragmentation on the Behavior and Demography of Gray-Tailed Voles

We monitored the short term behavioral and demographic responses of gray-tailed voles ( Microtus canicaudus ) to the reduction and fragmentation of their habitat. Our objectives were (1) to test whether ani- mals perished or moved into remaining fragments after 70% of their habitat was removed; and (2) to test the null hypothesis that the social structure and demography of animals would not differ between habitats con- sisting of one large continuous fragment (625 m 2 ), a mosaic of 25 small fragments (each 25 m 2 ) separated by 4 m of bare ground, and control, unmanipulated habitats (1850 m 2 ). We conducted the experiment in 12, 0.2-ha enclosures planted with alfalfa with four replicates for each of two manipulated treatments and a control. A 70% reduction in habitat did not adversely affect adult survival, reproductive rate, juvenile recruitment, or population size. However, an influx of unrelated females into habitat fragments resulted in decreased juve- nile recruitment in those fragments. Voles from cleared habitat moved into the remaining habitat and did not measurably affect the resident population. Similarly, the demography of voles did not differ significantly among the large-fragment, small-fragment, and control enclosures. Peak density estimates based on the amount of habitat in each enclosure were 545 animals per hectare in control, 1056 in large-fragment, and 2880 in small-fragment enclosures. Reduced movement of animals among the small fragments was the most obvious effect of habitat fragmentation. Six percent of females and 15% of males moved among small frag- ments within a week compared to approximately 60% moving comparable distances in large-fragment and control enclosures. Rates of juvenile dispersal and sexual maturation declined throughout the summer on all treatments, were associated with season and density, and were only marginally associated with habitat loss and fragmentation. We conclude that at the time of habitat removal and fragmentation, populations were small enough to accommodate a 70% reduction in habitat and still continue to increase in numbers. The so- cial system of gray-tailed voles was sufficiently flexible to accommodate an influx of animals to withstand densities . 1000 voles per ha. The behavioral and demographic features of gray-tailed voles are similar to those reported for other small mammals, thus confirming the use of voles for ecological model systems in hab- itat fragmentation studies.
PARTNER AGGRESSION SEVERITY AS A RISK MARKER FOR MALE AND FEMALE VIOLENCE RECIDIVISM

Pretreatment aggression severity was examined as a risk marker for recidivism in the treatment of partner aggression. Intact married couples experiencing husband-to-wife partner aggression were recruited from the community and participated in either conjoint group treatment or gender-specific group treatment. Elevated levels of husband and wife physical aggression and wife psychological aggression before treatment predicted the continuation and severity of physical aggression by both spouses during treatment and in the following year, with no significant differences across treatment formats. These results indicate that high levels of psychological and physical aggression signify a poor prognosis for both conjoint and gender-specific group treatment programs, suggesting the need for interventions of greater intensity, duration, and/or focus for individuals highest in psychological and physical aggression.
Magnetic resonance force microscopy of nuclear spins: Detection and manipulation of statistical polarization

We have detected and manipulated the naturally occurring $\sqrt{N}$ statistical polarization in nuclear spin ensembles using magnetic resonance force microscopy. Using protocols previously developed for detecting single electron spins, we have measured signals from ensembles of nuclear spins in a volume of roughly ${(150\phantom{\rule{0.3em}{0ex}}\mathrm{nm})}^{3}$ with a sensitivity of roughly 2000 net spins in a $2.5\phantom{\rule{0.3em}{0ex}}\mathrm{h}$ averaging window. Three systems have been studied, $^{19}\mathrm{F}$ nuclei in $\mathrm{Ca}{\mathrm{F}}_{2}$, and $^{1}\mathrm{H}$ nuclei (protons) in both polymethylmethacrylate and collagen, a naturally occurring protein. By detecting the statistical polarization, we not only can work with relatively small ensembles, but we eliminate any need to wait a longitudinal relaxation time ${T}_{1}$ to polarize the spins. We have also made use of the fact that the statistical polarization, which can be considered a form of spin noise, has a finite correlation time. A method similar to one previously proposed by Carlson et al. [Bull. Am. Phys. Soc. 44, 541 (1999)] has been used to suppress the effect of the statistical uncertainty and extract meaningful information from time-averaged measurements. By implementing this method, we have successfully made nutation and transverse spin relaxation time measurements in $\mathrm{Ca}{\mathrm{F}}_{2}$ at low temperatures.
Auger electron and characteristic energy loss spectra for electro-deposited americium-241

Abstract Auger electron energy spectra for electro-deposited americium-241 on platinum substrate were obtained using a cylindrical mirror analyzer. Characteristic energy loss spectra for this sample were also obtained at primary electron beam energies of 990 and 390 eV. From these measurements PI, PII, and PIII energy levels for americium-241 are determined. Auger electron energies are compared with theoretically calculated values. Minimum detectability under the present condition of sample preparation and equipment was estimated at approximately 1.2×10−8 g/cm2 or 3.9×10−8 Ci/cm2. Minimum detectability for plutonium-239 under similar conditions was estimated at about 7.2×10−10 Ci/cm2.
Lateral diffusion and electron transfer in the mitochondrial inner membrane

Abstract The concept that a structurally ordered chain of electron transferring proteins is required for a rapid and sequential transfer of electrons in a protein-dense mitochondrial inner membrane is examined. New observations are presented which indicate that the membrane proteins are not structurally ordered or densely packed in the membrane plane. It appears that the sequence and rate of electron transfer are mediated through random lateral diffusion and energetically favorable collisions between the electron transferring components.
Hyperfine splitting in the electron spin resonance of Dy and Er in the transition metal-Rh

Abstract The first observation of the hyperfine splitting of the Dy localized moment in a metal is reported. The measured shifts for Gd, Dy and Er and the hyperfine constants for Dy and Er in rhodium, are presented and discussed.
Cyclical fluctuations in centrally planned economies: A critique of the literature

(1986). Cyclical fluctuations in centrally planned economies: A critique of the literature. Soviet Studies: Vol. 38, No. 1, pp. 36-52.