cssi/SciSciGPT-SciSciNet huggingface dataset:
Effects of lactation on postpartum blood pressure among women with gestational hypertension and preeclampsia

Background Women with a history of hypertensive disorders of pregnancy are at an increased risk of hypertension and cardiovascular disease in later life. Lactation has been associated with a reduced risk of maternal hypertension, both in the postpartum period and later life. However, little is known about whether lactation is also cardioprotective in women with hypertensive disorders of pregnancy such as preeclampsia or gestational hypertension. Objective This study aimed to characterize the relationship between lactation and postpartum blood pressure among women with preeclampsia and gestational hypertension. Study Design Data were obtained from women who participated in the Prenatal Exposures and Preeclampsia Prevention study (n = 379; 66% African American; 85% overweight or obese). Women enrolled during pregnancy and attended a postpartum visit (on average, 9.1 months after delivery) during which data on lactation duration and blood pressure were collected. The significance of the associations between postpartum blood pressure and lactation among women who remained normotensive during pregnancy, developed gestational hypertension, or developed preeclampsia were assessed with an analysis of variance. Linear regression models were used to adjust for maternal age, race, education, prepregnancy weight, and time since delivery. Results Gestational hypertension affected 42 subjects (11%) and preeclampsia affected 33 (9%). Lactation was reported by 217 (57%) with 78 (21%) reporting ≥ 6 months of lactation. Women who lactated were somewhat older, more educated, and had higher socioeconomic status. Among women who had gestational hypertension, lactation was associated with lower systolic blood pressure ( P = .02) and diastolic blood pressure ( P = .02). This association persisted after adjustment for age, race, education, prepregnancy weight, and time since delivery. However, for women who had preeclampsia and women who remained normotensive during pregnancy, lactation was not associated with postpartum blood pressure in either bivariate or multivariate analyses. Conclusion This study found that lactation is associated with lower postpartum blood pressure among overweight women who develop gestational hypertension but not among women who develop preeclampsia. Future studies are needed to explore the association of lactation and blood pressure in later life for women with hypertensive disorders of pregnancy.
Effect of Insecticides, Fungicides, and Insecticide-Fungicide Combinations on Development of Lepidopterous Larval Populations in Soybean

The fungicides benomyl, chlorothalonil, thiabendazole, and fentin hydroxide were applied alone and in combination with methyl parathion or methomyl to soybeans. Larval population levels of Plathypena scabra (F.), Anticarsia gemmatalis (Hubner), and Pseudoplusia includens (Walker) were monitored as well as selected arthropod predators and the incidence of the fungal entomopathogens Nomuraea rileyi (Farlow) Samson and Entomophthora gammae (Weiser). Application of fungicides at the recommended rates failed to suppress an epizootic of E. gammae in P. includens populations. The incidence of N. rileyi was suppressed in a low density population of A. gemmatalis . When larval density increased, no difference was detected in the incidence of N. rileyi infection in treated and untreated plots. Differences in predator population levels were not observed in a 1976 P. includens test but generally lower predator populations were noted in the 1977 P. includens-A. gemmatalis test in fungicide and/or insecticide treated plots. Fentin hydroxide alone and treatments which included methyl parathion or methomyl reduced larval populations of P. scabra and A. gemmatalis . Only treatments containing methomyl reduced larval populations of P. includens. Pseudoplusia includens population resurgence was detected following treatments with benomyl and methyl parathion, chlorothalonil + methyl parathion and fentin hydroxide + methyl parathion. Anticarsia gemmatalis population resurgence followed treatment with fentin hydroxide + methomyl.
Asymmetric Synthesis of Hydroxy Esters with Multiple Stereocenters via a Chiral Phosphoric Acid Catalyzed Kinetic Resolution

The kinetic resolution of hydroxy tert-butyl esters through a Bronsted acid catalyzed lactonization is described. The resulting enantioenriched molecules have cyclic backbones and/or multiple stereocenters. DFT calculations explore how small changes in substrate structure can have a large impact on the selectivity of the process.
Citizen surveys: a component of the budgetary process

An annual citizen survey can be a valuable component of the municipal budgeting process for cities that elect to institutionalize the process as a way to translate citizen feedback into budgetary priorities. This article explores uses of citizen surveys in identifying latent needs of the community that may not be detected through public hearings or other citizen participation methods. The authors suggest that properly developed and conducted citizen surveys can provide decision-makers with research data that will lead to more responsive public spending and debt financing decisions. The article concludes with a case study of Auburn, Alabama, a city that has successfully used citizen surveys in its budgeting system for the past seventeen years.
Discovery and Analysis of Natural-Product Compounds Inhibiting Protein Synthesis in Pseudomonas aeruginosa

Bacterial protein synthesis is the target for numerous natural and synthetic antibacterial agents. We have developed a poly(U) mRNA-directed aminoacylation/translation (A/T) protein synthesis system composed of phenylalanyl-tRNA synthetases (PheRS), ribosomes, and ribosomal factors from Pseudomonas aeruginosa This system has been used for high-throughput screening of a natural-compound library. Assays were developed for each component of the system to ascertain the specific target of inhibitory compounds. In high-throughput screens, 13 compounds were identified that inhibit protein synthesis with 50% inhibitory concentrations ranging from 0.3 to >80 μM. MICs were determined for the compounds against the growth of a panel of pathogenic organisms, including Enterococcus faecalis, Escherichia coli, Haemophilus influenzae, Moraxella catarrhalis, P. aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae Three of the compounds were observed to have broad-spectrum activity and inhibited a hypersensitive strain of P. aeruginosa with MICs of 8 to 16 μg/ml. The molecular target of each of the three compounds was determined to be PheRS. One compound was found to be bacteriostatic, and one compound was bactericidal against both Gram-positive and Gram-negative pathogens. The third compound was observed to be bacteriostatic against Gram-positive and bactericidal against Gram-negative bacteria. All three compounds were competitive with the substrate ATP; however, one compound was competitive, one was uncompetitive, and one noncompetitive with the amino acid substrate. Macromolecular synthesis assays confirm the compounds inhibit protein synthesis. The compounds were shown to be more than 25,000-fold less active than the control staurosporine in cytotoxicity MTT testing in human cell lines.
Intra-articular calcaneal fractures : current concepts

Intra-articular fractures of the calcaneus should be treated like any other fractures of major weight-bearing joints. Technology has advanced significantly in the evaluation of such complex pathology. Surgical instrumentation is now available to address any fracture classification. In the past, this had been a problem, as maintenance of the anatomic reduction, rigid internal/dynamic external fixation, and early mobilization may not have been attainable. The two remaining major variables are the mechanism of injury and its force that creates the fracture in combination with a very complex intra-articular anatomical structure. There will always be some morbidity in complex and serious fractures, but at least a more favorable outcome may be attainable with application of the current concepts discussed in this text. Finally, the most crucial factor when dealing with this trauma is the skill of the surgeon, which includes his or her decision-making, preoperative planning, surgical acumen, atraumatic technique, experience, and training and postoperative management of possible complications.
Retrospective Evaluation of a Teleretinal Screening Program in Detecting Multiple Nondiabetic Eye Diseases

Abstract Background: Diabetic teleretinal screening programs have been utilized successfully across the world to detect diabetic retinopathy (DR) and are well validated. Less information, however, exists on the ability of teleretinal imaging to detect nondiabetic ocular pathology. Introduction: This study performed a retrospective evaluation to assess the ability of a community-based diabetic teleretinal screening program to detect common ocular disease other than DR. Materials and Methods: A retrospective chart review of 1,774 patients who underwent diabetic teleretinal screening was performed. Eye clinic notes from the Veterans Health Administration's electronic medical record, Computerized Patient Record System, were searched for each of the patients screened through teleretinal imaging. When a face-to-face examination note was present, the physical findings were compared to those obtained through teleretinal imaging. Sensitivity, specificity, and positive and negative predictive values were calculated...
Satellite-aided radar imaging (SARI)

This paper describes a novel technique for radar imaging of space objects. The approach is founded on using a small satellite near the target of interest as the receive end of a high-power ground-based radar transmitter for imaging. The small satellite is equipped with an open loop receiver for sampling and processing the observed wideband signal and a GPS receiver for orbit determination. It also contains appropriate algorithms for signal processing and receive and transmit antennas for collecting the radar signal and transmitting telemetry to the ground. The discussion in this paper is limited mainly to a point design for simplicity. It should be noted that the reach and capability of the proposed approach go beyond the example presented in this paper.
Ionic liquids as modifiers for cationic and anionic nanoclays

As part of a broader effort to develop nanoclays functionalized with different heterocyclic aromatic structures for novel applications, preliminary data are reported on the modification of sodium montmorillonite, a cationic clay, and hydrotalcite, an anionic clay, with four low molecular weight pyridinium and imidazolium-based ionic liquids. Commercially available unmodified montmorilonite was treated with aqueous solutions of three ionic liquids: N-ethyl pyridinium tetrafluoroborate, 1-ethyl 3-methyl imidazolium bromide and 1-hexyl 3-methyl imidazolium chloride. Commercially available hydrotalcite was treated with N-ethyl pyridinium tetrafluoroborate and its amorphous calcined version was regenerated in the presence of N-ethyl pyridinium tetrafluoroborate and N-ethyl pyridinium trifluoroacetate aqueous solutions The modified materials were characterized qualitatively and quantitatively by FTIR, TGA, EDX, WXRD and elemental analysis. The cationic clay data show an overall increase in interlamellar spacing as a result of sodium cation exchange with the cations of the ionic liquids (in spite of their relative small size) and improved thermal stability vs. commercial nanoclays modified with long chain quaternary ammonium salts. The effects were dependent on the type of the ionic liquid. The anionic clay data showed no anion intercalation for the commercial hydrotalcite and mostly surface absorption, rather than intercalation, for the calcined clay; this is possibly due to the relatively small size of the anions and the presence of a strongly bound carbonate anion, not easily amenable to exchange.
Performance of balanced disk array schemes

The balanced information dispersal algorithm (BIDA) provides attractive reliability enhancements as well as modest performance gains for the storage of data at a number of storage sites. A balanced disk array (BDA) is an application of BIDA. Although a BDA appears as a single, very reliable, fast direct-access device, it actually consists of a number of independent disks that store data according to a selected dispersal scheme. BDA devices offer exceptionally high fault tolerance combined with better performance than their constituent disks. As a result, a BDA achieves high quality with relatively low-quality components. BDA schemes also offer the flexibility to arrange for a desired ratio between read and write times. The authors discuss the construction, failure tolerance, and performance of BDAs. >
Taking the Class out of the Classroom: Libraries, Literacy, and Service Learning

Abstract In the fall of 2013, the University of Minnesota, Morris (UMM), offered a First Year Seminar class focused on libraries and literacy with a service learning component. The students in the class spent part of class time learning about library science theory and the other part implementing that theory in three different service learning projects: leading storytimes for K-3 ESL students, offering computer literacy sessions for senior citizens, and assessing library use for the UMM campus library. The service learning component was a valuable tool in helping the students better understand the importance of libraries and literacy, especially in a small, rural community.
The impact of lymphadenectomy on survival endpoints in women with early stage uterine endometrioid carcinoma: A matched analysis.

Abstract Objectives The role of pelvic lymphadenectomy (LA) in women with stage I endometrial carcinoma (EC) is controversial. The objective of this study is to investigate the prognostic impact of LA on survival endpoints in matched cohorts of women with stage I EC solely of endometrioid histology. Survival endpoints included recurrence-free (RFS), disease-specific (DSS) and overall survival (OS). Methods and materials Patients with FIGO stage I EC who underwent hysterectomy with LA as part of their surgical staging between 1/1990 and 6/2015 were matched to a similar group that underwent hysterectomy without lymphadenectomy (NLA), based on stage, grade and adjuvant management. Univariate and multivariate modeling with Cox regression analysis was carried out for predictors of survival endpoints. Results 870 women constituted the study cohort (435 in each group). Median number of dissected lymph node in the LA group was 9 (range, 5–75). There was no statistically significant difference between the two groups in regards to 5-year OS (87.2% for LA vs. 91.7% for NLA) ( p =0.36), DSS 97.7% vs. 98% ( p =0.54) and RFS (93.7% vs. 90% ( p =0.08), respectively. Lymphadenectomy was not a predictor of any of the studied survival endpoints. On multivariate analysis for the entire cohort, older age, deep myometrial invasion and higher tumor grade were predictors of worse RFS. For DSS, higher tumor grade, lower uterine segment (LUS) involvement and FIGO stage IB were significant predictors of worse outcome. For OS, older age and LUS involvement were the only two independent predictors for shorter OS. Conclusions After matching for FIGO stage, grade and adjuvant management, it appears that lymphadenectomy in women with stage I EC does not impact survival endpoints.
ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.
Do cultures vary in self-enhancement? ERP, behavioral, and self-report evidence

Psychologists have long debated whether self-enhancement is universal or varies across cultures. Extant studies using explicit and implicit measures have provided mixed results. In this study (N = 93; 35 European American, 58 Chinese: 28 tested in English, 30 tested in Mandarin), we measured self-enhancement covertly using an ERP paradigm. Self-enhancement was also assessed via self-report and reaction-time based measures. Americans showed strong evidence of self-enhancement across all measures, whereas this effect was absent or weaker among Chinese, who instead showed an other-enhancing bias across measures. Language did not affect self-enhancement tendencies among Chinese participants, with the exception of one self-report measure. Nor did the two cultural groups differ in enhancement for a close other. This is the first study to directly compare self-enhancement across cultural groups using ERPs and provides evidence that positive self-regard does indeed vary by culture.
Synthesis and characterization of a photocleavable collagen-like peptide

A 34-amino acid long collagen-like peptide rich in proline, hydroxyproline, and glycine, and with four photoreactive N-acyl-7-nitroindoline units incorporated into the peptide backbone was synthesized by on-resin fragment condensation. Its circular dichroism supports a stable triple helix structure. The built-in photochemical function enables the decomposition of the peptide into small peptide fragments by illumination with UV light of 350 nm in aqueous solution. Illumination of a thin film of the peptide, or a thin film of a photoreactive amino acid model compound containing a 5-bromo-7-nitroindoline moiety, with femtosecond laser light at 710 nm allows for the creation of well-resolved micropatterns. The cytocompatibility of the peptide was demonstrated using human mesenchymal stem cells and mouse embryonic fibroblasts. Our data show that the full-length peptide is cytocompatible as it can support cell growth and maintain cell viability. In contrast, the small peptide fragments created by photolysis are somewhat cytotoxic and therefore less cytocompatible. These data suggest that biomimetic collagen-like photoreactive peptides could potentially be used for growing cells in 2D micropatterns based on patterns generated by photolysis prior to cell growth.
No Cause for Alarm: Decreasing Inappropriate Pulse Oximetry Use in Bronchiolitis

“I need you to come look at the baby in room 8! The monitor keeps alarming for desaturations.” I walk to the patient room thinking through the many other tasks on my to-do list. As I enter the room, the smiling but noisy breathing child with bronchiolitis greets me. “We’ve deep suctioned him and he’s breathing more comfortably, but the pulse oximeter keeps dipping into the high 80s.” I look at the bedside monitor continuously tracking the patient’s heart rate, respiratory rate and oxyhemoglobin saturation, which now reads a perfect 100%. As I complete my assessment, I cannot help but wonder, “Why is this happy, well-appearing patient on a monitor?” As trainees, we are the frontline clinicians who rotate through different units within the hospital, and we observe situations like this almost every day, if not multiple times a day. Our perspective should make us the ideal stewards for identifying care processes that deviate from standard guidelines, but we are often not empowered to implement changes to improve the system and rather rely on the “higher-ups” to solve systems-based issues. As the call for “bending the value curve” has echoed through hospital systems and training programs, it is essential that we not only teach trainees about health care value but also empower them to identify examples of low-value care and give them tools and resources to be a more effective part of the solution.1 As part of the Hospital …
What Powers Ultra-Luminous IRAS Galaxies?

I report here centimeter-wavelength observations carried out at the Very Large Array (VLA) to help resolve two questions. First, what is the source of the far infrared (FIR) emission in infrared-luminous IRAS galaxies, active nuclei or more widely distributed star formation? And what physics underlies the tight correlation (Helou et al., 1985) between FIR and radio flux? To test potential answers to these questions, we believe it is important to study the most luminous IRAS galaxies. We selected 39 for study from the ultraluminous catalog of Strauss et al.(1990 and 1992). All sources had FIR luminosity ≥ 1011. 4 L⊙. Radio wavelength observations of these systems provide several advantages. First, in the radio there is no obscuration, so we can “see” the active galactic nuclei, if present. Radio spectral indices can distinguish between synchrotron and thermal emission. And finally, observations at the VLA provide sub-kpc resolution. We observed these sources with the VLA in its C configuration. At 1460 MHz, the effective resolution was ∼ 15″; and ∼ 4″ at 4860 MHz. We made follow-up observations on 24 sources in the A configuration with resolution at 4860 MHz of ∼ 0″.5 (or 300–800 h−1 pc for these sources).
Concepts in conceptual clustering

Although it has a relatively short history, conceptual clustering is an especially active area of research in machine learning. There are a variety of ways in which conceptual patterns (the AI contribution to clustering) play a role in the clustering process. Two distinct conceptual clustering paradigms (conceptual sorting of exemplars and concept discovery) are described briefly. Then six types of conceptual clustering algorithms are characterized, attempting to cover the present spectrum of mechanisms used to conceptualize the clustering process.
Educating Leaders For The New Competitive Environment

I woke up this morning to find that the world had changed. Almost without my realising it, we had moved from the industrial age into the information age. The dominant technology had changed from the machine to the computer; the primary output from goods to information; the strategic resource from capital to knowledge; the primary energy source from fossil fuel to the mind.
Learning Loop Invariants for Program Verification

A fundamental problem in program verification concerns inferring loop invariants. The problem is undecidable and even practical instances are challenging. Inspired by how human experts construct loop invariants, we propose a reasoning framework Code2Inv that constructs the solution by multi-step decision making and querying an external program graph memory block. By training with reinforcement learning, Code2Inv captures rich program features and avoids the need for ground truth solutions as supervision. Compared to previous learning tasks in domains with graph-structured data, it addresses unique challenges, such as a binary objective function and an extremely sparse reward that is given by an automated theorem prover only after the complete loop invariant is proposed. We evaluate Code2Inv on a suite of 133 benchmark problems and compare it to three state-of-the-art systems. It solves 106 problems compared to 73 by a stochastic search-based system, 77 by a heuristic search-based system, and 100 by a decision tree learning-based system. Moreover, the strategy learned can be generalized to new programs: compared to solving new instances from scratch, the pre-trained agent is more sample efficient in finding solutions.
Path-based function embedding and its application to error-handling specification mining

Identifying relationships among program elements is useful for program understanding, debugging, and analysis. One such kind of relationship is synonymy. Function synonyms are functions that play a similar role in code; examples include functions that perform initialization for different device drivers, and functions that implement different symmetric-key encryption schemes. Function synonyms are not necessarily semantically equivalent and can be syntactically dissimilar; consequently, approaches for identifying code clones or functional equivalence cannot be used to identify them. This paper presents Func2vec, a technique that learns an embedding mapping each function to a vector in a continuous vector space such that vectors for function synonyms are in close proximity. We compute the function embedding by training a neural network on sentences generated using random walks over the interprocedural control-flow graph. We show the effectiveness of Func2vec at identifying function synonyms in the Linux kernel. Finally, we apply Func2vec to the problem of mining error-handling specifications in Linux file systems and drivers. We show that the function synonyms identified by Func2vec result in error-handling specifications with high support.
Balance in chronic traumatic brain injury: correlations between clinical measures and a self-report measure

Objective: To assess associations among commonly used self-report and clinical measures of balance in chronic TBI.Design: Cross-sectional analysis of balance in a convenience sample of individuals ...
Follower Position Does Not Affect Waggle Dance Information Transfer

It is known that the honey bee waggle dance communicates the distance and direction of some item of interest, most commonly a food source, to nestmates. Previous work suggests that, in order to successfully acquire the information contained in a dance, other honey bees must follow the dancer from behind. We revisit this topic using updated methodology, including a greater distance from the hive to the feeder, which produced longer, more easily-read dances. Our results are not congruent with those of earlier work, and we did not conclude that honey bees must follow a dancer from behind in order to obtain the dance information. Rather, it is more likely that a follower can successfully acquire a dance’s information regardless of where she may be located about a dancer.
Injury and illness surveillance during the 2016 department of defense warrior games: review of methods and results.

Introduction Surveillance systems have become a valuable tool to capture epidemiological data at multi-sport events, with findings serving to predict and prevent injury, reduce illness, and guide efficient utilization of medical resources. In 2016, the first injury and illness surveillance tool for the Department of Defense (DoD) Warrior Games was established to inform the required medical footprint. The purpose of this paper is to describe the methods and findings from the 2016 DoD Warrior Games surveillance system, which included a database of injuries and illness. Materials and methods A total of 245 wounded warrior (WW) athletes were followed over 19 days, to include train-up and competition periods, as they competed for their respective teams of Army, Navy, Air Force, Marines, Special Operations, and United Kingdom. Medical personnel recorded injuries and illnesses treated utilizing a standardized surveillance form and data were entered into a daily tracker to examine patterns or areas for prevention. Reports included sex, age, event discipline, previous injury or illness, reason for presentation, and treatment provided. Results From June 3 to June 21, 2016, 114 individual encounters were recorded on the standard form and entered into the surveillance database. Athletes accounted for 67% of all encounters. Illness accounted for 30.7% of all visits, while injuries accounted for 69.2%. The incident proportion of injuries in athletes was 23.3 injuries per 100 athletes (95% CI 17.6, 30.1) and incident rate of 12.2 injuries per 1000 athlete days. Integrative medicine treatments including acupuncture, osteopathic manipulative treatment (OMT), massage therapy, and gua sha accounted for the largest forms of treatment (31%). Conclusions From the surveillance data, staff levels and treatment supplies can be adjusted. In addition an improved surveillance tool can be created. Continuous surveillance is required to provide information on trends in injury and illness to support prevention strategies.
Impact of Overseeded Grass Species, Seeding Rate and Seeding Time on Establishment and Persistence in Bermudagrass

Abstract Cool-season grass species are often overseeded into bermudagrass turf for both aesthetics and functionality during the winter months. When the overseeded grass persists beyond the spring, however, it becomes a weed. Experiments were conducted to evaluate overseeded grass species and seeding rate on turf cover during the fall, spring, and summer. The ability of perennial ryegrass, Italian ryegrass, and hybrid bluegrass to then persist in bermudagrass one year after seeding was determined. Both perennial ryegrass and Italian ryegrass produced acceptable ground cover in the spring after fall seeding. Hybrid bluegrass did not establish well, resulting in unacceptable cover. Perennial ryegrass generally had the most persistence one year after seeding, either because of the survival of plants through the summer or because of new germination the following fall. The highest cover seen one year after seeding was 24% with perennial ryegrass in the 2005 trial. Maximum cover seen with Italian ryegrass and hy...
Modular evolution of a chiral auxiliary for the 1,3-dipolar cycloaddition of isomünchnones with vinyl ethers.

[reaction: see text]. The 1,3-dipolar cycloaddition reaction has long been recognized as a powerful methodology in organic synthesis. More recently, this reaction has become a popular manifold for the construction of chemical diversity. Herein, we report the development of a chiral template for the facially selective cycloaddition of isomunchnones, a common class of 1,3-dipoles. The modular format of the asymmetric unit allowed a systematic optimization of selectivity. In addition, the chiral auxiliary was removed through an unusually facile ester aminolysis.
The Forgotten Step in Tennis

(1947). The Forgotten Step in Tennis. The Journal of Health and Physical Education: Vol. 18, No. 2, pp. 75-104.
The construction of an international: Debord, Jorn, and situationist praxis

Though the Situationist International (SI) was a network connecting artists and theorists across Europe, scholars have mainly focused on its Paris branch. Guy Debord, its leading French member, has...
State Governments and Judges May Moderate the Impact of the Trump Administration’s Promotion of Medicaid Work Requirements

In January 2018, the Center for Medicare and Medicaid Services (CMS) released guidance that encouraged states to submit Section 1115 waivers that impose work requirements on some Medicaid beneficiaries. To evaluate the potential impact of a policy, we need to accurately predict both how far a policy will spread and how durable it will prove over time. This commentary draws upon recent political science scholarship to describe potential constraints that changes in state-level partisan control can impose on CMS's current waiver strategy, as well as how state-level constraints might interact with judicial review to further limit the policy's spread.
Preparing for adulthood: parent and school personnel priorities and approaches to supporting transition-age youth with Autism Spectrum Disorder (ASD)

Date Presented 04/05/19 The purpose of this study was to compare parent and school personnel perspectives regarding transition needs and approaches for youth with ASD. The findings provide insight into: (a) parents’ and school personnel's desired outcomes; and (b) a tension between developing consistency and routines as well as the ability to adapt to changes and participate in novel experiences or situations. These findings raise important theoretical questions related to our current approaches to working with these students. Primary Author and Speaker: Jennifer Chen Contributing Authors: Ellen Cohn, Gael Orsmond
Coupling in situ experiments and modeling – Opportunities for data fusion, machine learning, and discovery of emergent behavior

Abstract This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.
Law as a Battlefield: The U.S., China, and Global Escalation of Lawfare

Law is increasingly being used as a weapon of war. Unable or unwilling to challenge other states militarily, states use legal strategies to weaken the enemy’s legitimacy. Such “lawfare” can be used to achieve a kinetic objective, to forestall one, to degrade the enemy’s will to fight, and to shape the narrative of war. The Chinese military prioritizes lawfare as one of the “Three Warfares” that shape its military’s influence operations. Meanwhile, the U.S. has no similar lawfare doctrine or strategy, even as China is forcing it to fight back. This Article argues that the U.S. needs to develop a lawfare strategy to combat its adversaries. It will first define the concept of lawfare and discuss how its use has evolved and escalated globally in recent years. It will illustrate this phenomenon by examining three different case studies of lawfare between China and the U.S. or its allies: international arbitration over China’s claims to the Spratly Islands, China’s non-uniformed maritime militias, and litigation involving the U.S. and Huawei. After discussing the rise of lawfare globally, including lawfare efforts by Russia and the U.S., the article concludes with some recommendations for a U.S. lawfare strategy.
Evolving neural networks for strategic decision-making problems

Evolution of neural networks, or neuroevolution, has been a successful approach to many low-level control problems such as pole balancing, vehicle control, and collision warning. However, certain types of problems - such as those involving strategic decision-making - have remained difficult for neuroevolution to solve. This paper evaluates the hypothesis that such problems are difficult because they are fractured: The correct action varies discontinuously as the agent moves from state to state. A method for measuring fracture using the concept of function variation is proposed and, based on this concept, two methods for dealing with fracture are examined: neurons with local receptive fields, and refinement based on a cascaded network architecture. Experiments in several benchmark domains are performed to evaluate how different levels of fracture affect the performance of neuroevolution methods, demonstrating that these two modifications improve performance significantly. These results form a promising starting point for expanding neuroevolution to strategic tasks.
Confinement Time Required to Avoid a Quick Rebound of COVID-19: Predictions From a Monte Carlo Stochastic Model

How long should we self-isolate at home to reduce the chances of a second wave of COVID-19? This is a question that billions of people are wondering early 2020 due to the outbreak of the novel coronavirus SARS-CoV-2. This virus can produce a severe pneumonia that has killed over 230,000 people so far, was detected for the first time late 2019 in Wuhan (China), and has spread all over the world due, in part, to the difficulty of detecting and isolating asymptomatic or mild-symptomatic cases. In this paper, we explore how long suppression strategies (i.e., home confinement and social distancing) must be put into practice in highly populated cities to reduce the chances that a quick rebound of COVID-19 infections occur again over the next months. This is explored, using New York City (USA), San Francisco (USA), and Madrid (Spain) as case studies, through a simple but realistic Monte Carlo stochastic model that takes into account that part of the undetected infected individuals remain in circulation propagating the virus. Our simulations reflect that, if suppression strategies are not properly applied, they can be counterproductive because there are high chances that the confinement time has to be lengthened without reducing the total number of infections. We also estimate that, in the most conservative scenario and under the model assumptions, home confinement is effective if applied at least ~110 days in New York City, ~80 days in San Francisco, and ~70 days in Madrid, i.e., until mid-July 2020, early June 2020, and late May 2020, respectively.
Integer Linear Programming formulations in Natural Language Processing

Making decisions in natural language processing problems often involves assigning values to sets of interdependent variables where the expressive dependency structure can influence, or even dictate what assignments are possible. This setting includes a broad range of structured prediction problems such as semantic role labeling, named entity and relation recognition, co-reference resolution, dependency parsing and semantic parsing. The setting is also appropriate for cases that may require making global decisions that involve multiple components, possibly pre-designed or pre-learned, as in event recognition and analysis, summarization, paraphrasing, textual entailment and question answering. In all these cases, it is natural to formulate the decision problem as a constrained optimization problem, with an objective function that is composed of learned models, subject to domain or problem specific constraints.Over the last few years, starting with a couple of papers written by (Roth & Yih, 2004, 2005), dozens of papers have been using the Integer linear programming (ILP) formulation developed there, including several award-winning papers (e.g., (Martins, Smith, & Xing, 2009; Koo, Rush, Collins, Jaakkola, & Sontag., 2010; Berant, Dagan, & Goldberger, 2011)).This tutorial will present the key ingredients of ILP formulations of natural language processing problems, aiming at guiding readers through the key modeling steps, explaining the learning and inference paradigms and exemplifying these by providing examples from the literature. We will cover a range of topics, from the theoretical foundations of learning and inference with ILP models, to practical modeling guides, to software packages and applications.The goal of this tutorial is to introduce the computational framework to broader ACL community, motivate it as a generic framework for learning and inference in global NLP decision problems, present some of the key theoretical and practical issues involved and survey some of the existing applications of it as a way to promote further development of the framework and additional applications. We will also make connections with some of the “hot” topics in current NLP research and show how they can be used within the general framework proposed here. The tutorial will thus be useful for many of the senior and junior researchers that have interest in global decision problems in NLP, providing a concise overview of recent perspectives and research results.
Separating Persistent Homology of Noise from Time Series Data Using Topological Signal Processing.

We introduce a novel method for separating significant features in the sublevel set persistence diagram based on a statistics analysis of the sublevel set persistence of a noise distribution. Specifically, the statistical analysis of the sublevel set persistence of additive noise distributions are leveraged to provide a noise cutoff or confidence interval in the sublevel set persistence diagram. This analysis is done for several common noise models including Gaussian, uniform, exponential and Rayleigh distributions. We then develop a framework implementing this statistical analysis of sublevel set persistence for signals contaminated by an additive noise distribution to separate the sublevel sets associated to noise and signal. This method is computationally efficient, does not require any signal pre-filtering, is widely applicable, and has open-source software available. We demonstrate the functionality of the method with both numerically simulated examples and an experimental data set. Additionally, we provide an efficient $O(nlog(n))$ algorithm for calculating the zero-dimensional sublevel set persistence homology.
Peshmerga Battlefield Participation

In studying the diversity of international warfare, it’s easy to overlook the fundamental constant: people, mostly young men, facing the possibility of death on the battlefield as they try to kill one another. Building on existing literature, I argue that effective training can increase battlefield participation by making soldiers calculate that their odds of surviving and achieving the mission are higher on the battlefield than they were without training. By uniting the analysis of training and combat motivation into the framework of battlefield participation, we can better understand individual and collective propensities to engage in the dangerous work of combat or to shirk in the face of danger. This article tests this theory battlefield participation through a survey of 2,301 Peshmerga (Kurdish soldiers) at bases inside the Kurdistan Region of Iraq in the summer of 2017, after three years of combat against the Islamic State of Iraq and Syria (ISIS). Around a third of the Peshmerga had been trained in basic tactics and marksmanship by the anti-ISIS coalition of Western countries. Coalition-trained Peshmerga reported higher levels of battlefield participation and confidence than their untrained counterparts but did not vary in their self-reported cognitions during combat or their assessment of social cohesion in their unit. These results support the proposed theory and offer a new paradigm for understanding an age-old question.
The clinical course of COVID-19 in the outpatient setting: a prospective cohort study

Background Outpatient coronavirus disease 2019 (COVID-19) has been insufficiently characterized. To determine the progression of disease and determinants of hospitalization, we conducted a prospective cohort study. Methods Outpatient adults with positive reverse transcription polymerase chain reaction results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were recruited by phone between April 21 and July 23, 2020, after receiving outpatient or emergency department testing within a large health network in Maryland, United States. Symptoms were collected by participants on days 0, 3, 7, 14, 21, and 28, and portable pulse oximeter oxygen saturation (SaO2), heart rate, and temperature were collected for 15 consecutive days. Baseline demographics, comorbid conditions, and vital signs were evaluated for risk of subsequent hospitalization using negative binomial and logistic regression. Results Among 118 SARS-CoV-2-infected outpatients, the median age (interquartile range [IQR]) was 56.0 (50.0-63.0) years, and 50 (42.4%) were male. Among individuals in the first week of illness (n = 61), the most common symptoms included weakness/fatigue (65.7%), cough (58.8%), headache (45.6%), chills (38.2%), and anosmia (27.9%). Participants returned to their usual health a median (IQR) of 20 (13-38) days from symptom onset, and 66.0% of respondents were at their usual health during the fourth week of illness. Over 28 days, 10.9% presented to the emergency department and 7.6% required hospitalization. The area under the receiver operating characteristics curve for the initial home SaO2 for predicting subsequent hospitalization was 0.86 (95% CI, 0.73-0.99). Conclusions Symptoms often persisted but uncommonly progressed to hospitalization among outpatients with COVID-19. Home SaO2 may be a helpful tool to stratify risk of hospitalization.
Refining breast cancer prognosis by incorporating age at diagnosis into clinical prognostic staging: introduction of a novel online calculator

American Joint Committee on Cancer (AJCC) clinical staging is used to estimate breast cancer prognosis, but individual patient survival within each stage varies considerably by age at diagnosis. We hypothesized that the addition of age at diagnosis to the staging schema will enable more refined risk stratification. We performed a retrospective population analysis of adult women diagnosed with invasive breast cancer between 2010 and 2015 registered in SEER. Multivariable Cox hazards models were used to evaluate the association of AJCC 8th edition clinical prognostic stage (CPS) and age with risk of overall mortality. Separate hierarchical models were fit to the data: Model 1: CPS alone; Model 2: CPS + age + age2; and Model 3: CPS + age + age2 + CPS x age + CPS x age2. Models were compared by the Akaike information criterion (AIC), the c-statistic for time-dependent receiver operator characteristic curves, and category-free net reclassification improvement (NRI). Internal validation was performed using bootstrapping samples. Among 86,637 women, the median follow-up was 36 months and 3-year overall survival was 91.9% ± 0.1%. Age significantly modified the effect of CPS on survival (p < 0.0001). Model 3 was the most precise, with the lowest AIC (126,619.63), the highest c-statistic (0.8212, standard error 0.0187), and superior NRI indices. Age at diagnosis is a highly prognostic variable that warrants consideration for inclusion in future editions of the AJCC Breast Cancer Staging Manual.
SmartMon: Misbehavior Detection via Monitoring Smart Home Automations

The rapid expansion of Internet of Things (IoT) has brought unprecedented changes to our daily life. Among all, smart home technologies are the most widely adopted. They leverage various devices in home environment to build a connected network, over which automation is implemented for enhancing device interoperability. Such automations usually execute on platforms that are provided by device vendors, such as Samgsung, Google and Amazon. However, back-end cloud may not always be trustworthy due to malware, unknown third-party applications and possible side-channel attacks. Specifically for the IoT platforms, we identify two security threats that may gain unauthorized control of smart home devices: over-privilege issue and spooking events. In this thesis, we presents SmartMon, a framework that is designed to detect such security violations by statically analyzing automation application (SmartApp) control logic and comparing them with dynamic execution patterns. Through evaluations, we demonstrate that SmartMon could achieve high precision (> 95%) in detecting both violations. We also evaluate its detection capability in more complex settings, where multiple SmartApps execute simultaneously, resulting in potential dependencies. The evaluation results show that SmartMon remains high accuracy in this scenario as well.