cssi/SciSciGPT-SciSciNet huggingface dataset:
Routines and Routine Invocation

This chapter covers Structured Query Language (SQL): 1999's routine invocation algorithm as it applies to each form of SQL-invoked routine, giving both a “bird's-eye” view and the incredibly tedious details. An SQL-invoked routine can be a procedure , a function, or a method or it can be a routine that is invoked from SQL. The routine itself might be written in SQL in which case it is also an SQL routine; alternatively, it might be written in some other programming language, in which case it is an external routine. Among other factors, this chapter gives overview on SQL's path, how it affects selection of user-defined type for some contexts, and how it affects the routine invocation algorithm on the three forms of SQL-invoked routines. The most concise definition of an SQL-invoked routine is “a routine that is invoked from SQL code.” The phrase SQL-invoked routine has two components. The second component, the word routine, identifies the concept of a “subprogram” that is executed on behalf of another program, usually through the use of some particular syntax that identifies that subprogram. Over the decades, programming languages have used a variety of terminology for different sorts of subprograms, but the programming community appears to have settled on consistent nomenclature, and SQL's terms are in agreement with those of other modern languages. The first component, “SQL-invoked,” identifies subprograms that are executed in response to instructions issued from SQL statements or expressions.
Estimation and modeling of EEG amplitude-temporal characteristics using a marked point process approach

We propose a novel interpretation of single channel Electroencephalogram (EEG) traces based on the transient nature of encoded processes in the brain. In particular, the proposed framework models EEG as the output of the noisy addition of temporal, reoccurring, transient patterns known as phasic events. This is not only neurophysiologically sound, but it also provides additional information that classical EEG analysis often disregards. Furthermore, by utilizing sparse decomposition techniques, it is possible to obtain amplitude and timing that is further modeled using estimation and fitting techniques. We model Brain-Computer Interfaces (BCI) competition data features as Gaussian Mixture Model (GMM) samples in order to show the potential of working in the joint space of the parameters. The results not only preserve the topographic discriminant behavior but also expand the realm of possible EEG analysis.
Simulation of algorithms for pulse timing in FPGAs

Modern Field Programmable Gate Arrays (FPGAs) are capable of performing complex discrete signal processing algorithms with clock rates well above 100 MHz. This, combined with FPGA's low expense and ease of use, make them an ideal technology for pulse timing and are a central part of our next generation of electronics for our pre-clinical PET scanner systems. To that end, our laboratory has been developing a pulse timing technique that uses pulse fitting to achieve timing resolution well below the sampling period of the analog to digital converter (ADC). While ADCs with sampling rates in excess of 400 MS/s exist, we feel that using ADCs with lowing sampling rates has many advantages for positron emission tomography (PET) scanners. It is with this premise that we have started simulating timing algorithms using MATLAB in order to optimize the parameters before implementing the algorithm in Verilog. MATLAB simulations allow us to quickly investigate filter designs, ADC sampling rates and algorithms with real data before implementation in hardware. We report our results for a least squares fitting algorithm and a new version of a leading edge detector of PMT pulses.
Generating Community, Generating Justice? The production and circulation of value in community energy initiatives

In this paper, we explore the potentialities and interconnections between existing and hypothetical community energy systems and the concept of generative justice. New York State’s more recent official energy plan, for instance, includes provisions for community-scale microgrids, and several European nations offer significant financial support to citizens interested in building micro and intermediate-scale renewable energy systems. Such efforts and technologies appear to promise some degree of generative justice, returning much of the value generated by distributed renewable energy back to the community producing it. However, most currently conceived and implemented community energy systems recirculate value in very narrow and limited ways. Building upon an analysis of New York energy policy and on-the-ground cases, we explore community energy’s potential. What kinds of value are being generated by community energy systems and for whom? How could such efforts be more generative of justice across a broad range of values, not just electrons and dollars? Through the attempt to broaden thinking not only about community energy systems but also the concept of generative justice, we connect technological and organizational configurations of community energy systems and the forms of value they have the potential to generate: including, the production of grassroots energy and organizational expertise, the capacity for local and personal autonomy in energy planning and decision-making, and the enhancement of an affective sense and embodied experience of community. Finally, we examine some of the barriers to realizing more generatively just community energy systems.
The Analysis for Selecting Compensating Capacitances of Two-Coil Resonant Wireless Power Transfer System

In recent years, magnetically coupled resonant becomes an intense research in the study of wireless power transfer (WPT). Based on the two-coil resonant wireless power transfer system, this paper conducts research on the four topology models using circuit theory. First, the four topology models, which are: Series-Parallel (SP), Series-Series (SS), Parallel-Series (PS), Parallel-Parallel (PP), are built to describe the two-coil resonant WPT system. Next, the method of selecting compensating capacitances for the primary transmitting coils are deduced and presented. Then the transfer performance of these four topology models are analyzed and compared, and the conclusion is presented that Parallel-Parallel (PP) models is the best choice for a relatively far distance wireless power transfer system since it has a relatively high transfer power and efficiency. Finally, the simulations in PSPICE for the four topology models are carried out, the results validate the proposed conclusions.
The Gender Turing Test

In our Behavioral Cybersecurity course at Howard University in last spring (2016), students for their final exam were asked to write an opinion on the following question: “We know, in general in the US as well as at Howard, that only about 20% of Computer Science majors are female. Furthermore, of those CS students choosing to concentrate in Cybersecurity, fewer than 10% are female. Can you suggest any reason or reasons that so many fewer female computer scientists choose Cybersecurity?” In the course of reviewing the answers, it became clear that the challenge of determining the gender of the writer was a difficult problem. To that end, a sample of approximately 50 readers have analyzed the students’ texts and tried to determine the gender of the writers. The distribution of answers, to be presented in the full paper, has provided interesting options for further development of this research. In some aspects, the challenge of determining gender from a source absent of physical signals is similar to the challenge of the original Turing Test, which Turing formulated in order to present the challenge of determining whether or not machines could be said to possess intelligence.
Bendazzoli and Claudia, (Eds.), 2016, Addressing methodological challenges in interpreting studies research

This article reviews Addressing methodological challenges in interpreting studies research 978-1443890670
Pregnant women should not be categorised as a 'vulnerable population' in biomedical research studies: ending a vicious cycle of 'vulnerability'.

A new study published in Journal of Medical Ethics by van der Zande et al 1 further highlights why classifying pregnant women as a ‘vulnerable population’ in the context of research is deeply problematic. Because the designation of ‘vulnerable’ is otherwise applied to populations whose decision-making capacity about research participation is somehow compromised—such as children and adults of limited cognitive ability—many of us have been arguing for some time that using this designation for pregnant women is inappropriate and disrespectful.2–4 There is nothing about the state of pregnancy that renders pregnant women incapable of offering valid research consents or refusals. Moreover, rather than protecting the health interests of pregnant women and their offspring, this designation has had the opposite effect. It has contributed to the widespread exclusion of pregnant women from research activities, which is itself pernicious to the health of pregnant women.5 We know that pregnant women encounter a range of health needs across their pregnancies. In the USA, for example, approximately 9 out of every 10 women use some kind of medication during pregnancy to manage health conditions.6 Yet because pregnant women have largely been …
Factors associated with the use of cognitive aids in operating room crises: a cross-sectional study of US hospitals and ambulatory surgical centers

Operating room (OR) crises are high-acuity events requiring rapid, coordinated management. Medical judgment and decision-making can be compromised in stressful situations, and clinicians may not experience a crisis for many years. A cognitive aid (e.g., checklist) for the most common types of crises in the OR may improve management during unexpected and rare events. While implementation strategies for innovations such as cognitive aids for routine use are becoming better understood, cognitive aids that are rarely used are not yet well understood. We examined organizational context and implementation process factors influencing the use of cognitive aids for OR crises. We conducted a cross-sectional study using a Web-based survey of individuals who had downloaded OR cognitive aids from the websites of Ariadne Labs or Stanford University between January 2013 and January 2016. In this paper, we report on the experience of 368 respondents from US hospitals and ambulatory surgical centers. We analyzed the relationship of more successful implementation (measured as reported regular cognitive aid use during applicable clinical events) with organizational context and with participation in a multi-step implementation process. We used multivariable logistic regression to identify significant predictors of reported, regular OR cognitive aid use during OR crises. In the multivariable logistic regression, small facility size was associated with a fourfold increase in the odds of a facility reporting more successful implementation (p = 0.0092). Completing more implementation steps was also significantly associated with more successful implementation; each implementation step completed was associated with just over 50% higher odds of more successful implementation (p ≤ 0.0001). More successful implementation was associated with leadership support (p < 0.0001) and dedicated time to train staff (p = 0.0189). Less successful implementation was associated with resistance among clinical providers to using cognitive aids (p < 0.0001), absence of an implementation champion (p = 0.0126), and unsatisfactory content or design of the cognitive aid (p = 0.0112). Successful implementation of cognitive aids in ORs was associated with a supportive organizational context and following a multi-step implementation process. Building strong organizational support and following a well-planned multi-step implementation process will likely increase the use of OR cognitive aids during intraoperative crises, which may improve patient outcomes.
Employee Turnover: New Perspectives

Models and empirical research on employee turnover have improved our understanding of factors related to employees leaving their jobs. However, there are many reasons for employees to stay or to le...
Investigating heterogeneous planning spaces

With the continuous improvement of the capabilities of robots and the increasing complexity of the environments they successfully traverse, this paper presents useful concepts and definitions about the heterogeneous nature of planning spaces within the context of motion planning. Our methodology uses the property of visibility, expansiveness and homotopy class to develop algorithms that represent the heterogeneity of the planning space. Our algorithm also include a machine learning technique that identifies sub regions and then intelligently applies necessary existing strategies to create well connected maps in that sub region. We make comparisons with two other machine learning methods in a variety of simulated robot environments ranging from simple homogeneous rooms to complicated maze environments. Our method outperforms the other two methods in terms of time to build a roadmap, the number of nodes needed and the number of connected components generated.
Target Data Breach: Accounting for Contingent Liabilities

This is a flexible case that provides for discussion about the form and content of 10-K reports, managerial discussion and analysis, non-GAAP reporting, and accounting for contingent liabilities. What is unique is that Target included lengthy disclosures about the data breach, but many questions remain because the breach occurred shortly before year end. Further, the instructor can compare the contingent liability of $17 million reported in the 2013 10-K to the $201 million costs incurred by Target related to the breach as of the 2015 year end. Excerpt UVA-C-2390 Oct. 6, 2017 Target Data Breach: Accounting for Contingent Liabilities It was December 19, 2013, and Josiah Thrasher had just hung up the phone. His grandmother was very worried about the news disclosed that day that millions of credit cards were stolen from Target Corporation (Target) because she loved shopping at Target and was not sure what the news meant for her. Was she at risk of fraud? Thrasher was not sure what it meant for himself, either, as Target was a publicly traded company (NYSE: TGT) in his portfolio of investments. Thrasher figured it was worth the time to get to the bottom of the story. He read the press release Target issued, which indicated that 40 million credit and debit cards belonging to customers who had shopped at Target stores from November 27 through December 15, 2013 had been compromised. The next day, Target issued two press releases. The first reassured customers that they would not be responsible for any fraudulent charges to their cards, and the second was a more personal message from the CEO, Gregg Steinhafel, which confirmed Target's commitment to its customers and offered a 10% discount for all shoppers on December 21 and 22. “That seems generous,” Thrasher thought, but he wondered who would shop at a store that had just been hacked. The next several days were busy for Target's public relations group, and it continued to issue security updates throughout December. What bad luck to be on the receiving end of the largest hack of a retailer in history, right in the middle of the busiest shopping season of the year! Luckily for Thrasher, though, Target's stock had barely budged (Exhibit 1). While the Internet was full of discussion about the breach, very little of it related to the costs Target was likely to incur. Target had just filed Q3 results on November 27, 2013, and would not file year-end results until March because, as a retailer, it had a fiscal year that ended on an unusual date. The current fiscal year would end on February1. Thrasher would have to wait until then to figure out the extent of the financial damage caused by the data breach. . . .
Essential Functions of Topoisomerase IIIα in the Nucleus and Mitochondria

Topoisomerase IIIα (Top3α) is the essential eukaryotic member of the type IA class of topoisomerases. The absence of Top3α leads to embryonic lethality in fruit flies and mice. One of the main roles of the enzyme in the nucleus appears to be prevention of aberrant recombination by resolving double Holliday junction structures into non-crossover products; this role requires the formation of a complex with functional Bloom’s helicase as well as the structural Rmi proteins. While the exact stoichiometry and mechanism of action of the complex is not yet known, we present two models for how the resolution may occur. In addition, Top3α appears to play a key role in the mitochondria, where it may assist in the segregation of daughter chromosomes; a model for the role of Top3α in late replication intermediates is also presented. In this chapter, we outline the discovery, known functions, and future implications of Top3α in the cell.
Directive Principles of State Policy: Theory and Practice

The Directive Principles of State Policy (“DPSPs”) occupy an ambiguous place in our Constitutional scheme. They are framed as a set of obligations incumbent upon the State. Nonetheless, the constitutional text expressly renders them unenforceable. The members of the Constituent Assembly were deeply divided over the DPSPs. Many could not see the utility of an unenforceable set of exhortations. Some recommended scrapping the Chapter altogether, while others argued for placing it within the domain of Part III and the fundamental rights. Still others argued over the level of detail that the Principles set out. And some of them pointed out the contradictions inherent in placing abstract principles of economic justice alongside concrete policies like prohibition and controlling cow slaughter. Nonetheless, Part IV survived the birth-pangs of the Constitution relatively unscathed. Yet its life after that has been anything but straightforward. Judicial approaches to the interpretation of Part IV as a whole, to individual Principles, and to their relationship with fundamental rights, have been inconsistent. And lately, directive principles such as the provision of universal primary education have been shifted from Part IV to Part III via Constitutional amendment – raising the question whether there is any genuine conceptual distinction between fundamental rights and directive principles in the first place. In this medley of diverging voices and with such a checkered history, is it at all possible to ground the DPSPs within a coherent intellectual vision, one that is justified both constitutionally and philosophically? In this essay, I shall argue that it is. Drawing upon the text of the Constitution, its structure, its history, judicial precedent and political philosophy, I shall make two claims. First, the directive principles are best interpreted as providing the framework of values that structure and constrain the interpretation and construction of fundamental rights; and secondly, in giving teeth to the DPSPs, the Court has regularly adopted a limiting principle that constrains its own role in interpretive exercise, one that is grounded in ideas of institutional competence and legitimacy.
Employing Dyadic Data to Assess the Accuracy of Salespersons’ Perceptions of Their Customers: Antecedents to and Impact on Performance

This research gathered dyadic data from a sample of manufacturers apparel representatives and their customers to test hypotheses related to the accuracy of salespersons’ perceptions of their customers and sales performance. The research does show significant variation in the accuracy of salespersons’ perceptions about their customers’ performance expectations and ratings of evaluative criteria.
Load balancing distributed file system servers: a rule-based approach

In this paper, we present a new methodology for managing read-write filesets across multiple file servers of a Distributed File System, thus balancing the load of file access requests across servers. The proposed methodology is based on a rule-based data mining technique and graph theory algorithms. The rule-based technique generates rules from access request data to identify present file access patterns in the system. We then use the rules, graph analysis and statistical information (usage and size of the filesets) to relocate the filesets between different file servers. The algorithm for fileset relocation is based on the graph coloring problem. We tested our algorithms on data collected for five months on DFS file servers in a production environment. Experiments with the data show that our methodology can make intelligent decisions about file system transfers in order to balance the access request load across DFS servers.
Hematopoietic stem cell transplant (HSCT) utilization in Hodgkin lymphoma (HL) after treatment failure from a statewide claims database.

e18739Background: In the era of novel therapies, the first line and subsequent lines of therapies are rapidly evolving in the treatment of patients with HL in order to optimize disease control and ...
A “Moral Ecology” of Afrikaner Settlement in German East Africa, 1902–1914

Afrikaner immigration to German East Africa before the First World War was a bellwether for further white settlement, providing Afrikaners escape from British rule following the South African War. Settled primarily around Mt. Meru, Afrikaner immigration expedited the enclosing of the landscape, the displacement of African agro-pastoralists, and curtailment of their rights to land, pasture, and water. But Afrikaners themselves quickly contested German policies, especially restrictions on hunting, transhumance, and mobility. Drawing on moral frameworks derived from their South African past, Afrikaners were an unusual example of agents of colonial enclosure resisting its main prerequisite, namely the requirement to fence their lands. Depicted in colonial-era discourses as a violent and backward population, this chapter uncovers the hidden history of Afrikaner resistance to German settlement policy.
Incidence of Dexmedetomidine Withdrawal in Adult Critically Ill Patients: A Pilot Study.

To determine the incidence of dexmedetomidine withdrawal in adult critically ill patients. Design This was a prospective, observational study of patients from November 2017 to December 2018. Setting Medical-surgical, cardiothoracic, and neurosurgical ICUs in a tertiary care hospital. Patients Adult critically ill patients on dexmedetomidine infusions for at least 3 days. Interventions Indicators of withdrawal were assessed at baseline and at least daily during the dexmedetomidine wean period. Delirium was assessed using the Confusion Assessment Method for the ICU. Sedation was assessed using the Richmond Agitation-Sedation Scale. The Withdrawal Assessment Tool-1 was performed and vital signs were recorded during each assessment. Patients were considered positive for dexmedetomidine withdrawal if they had two or more of the following symptoms: positive Confusion Assessment Method for the ICU, Richmond Agitation-Sedation Scale greater than +1, positive Withdrawal Assessment Tool-1 assessment, tachycardia (heart rate > 90 beats/min), and hypertension (systolic blood pressure > 140 mm Hg or mean arterial pressure > 90). Measurements and main results Forty-two patients were included in the study, with 64% of patients experiencing signs of dexmedetomidine withdrawal. The median time on dexmedetomidine for all patients was 9.6 days (5.8-12.7 d), and the median dose of dexmedetomidine received was 0.8 µg/kg/hr (0.5-1 µg/kg/hr). Of the patients who were positive for withdrawal, the most prevalent withdrawal symptoms observed included delirium, hypertension, and agitation (93%, 48%, and 33%, respectively). We found no correlation between chronic opioid tolerance and incidence of withdrawal symptoms. Peak dexmedetomidine doses greater than 0.8 µg/kg/hr and cumulative daily doses of dexmedetomidine greater than 12.9 µg/kg/d were associated with a higher incidence of withdrawal. Conclusions The majority of patients in our study demonstrated signs that may be indicative of dexmedetomidine withdrawal. Peak and cumulative daily dexmedetomidine dose, rather than duration of therapy, may be associated with a higher incidence of withdrawal signs. Regular screening of patients on prolonged dexmedetomidine infusions is recommended to ensure safe and effective use in critically ill patients.
Soil Displacement Terramechanics for Wheel-Based Trenching with a Planetary Rover

Planetary exploration rovers are expensive, weight constrained, and cannot be serviced once deployed. Here, we explore one way to increase their capabilities while avoiding the cost, mass, and complexity leading to these issues. We propose to re-use the large wheel actuators for trenching and other digging operations, which will enable a range of missions such as sampling deeper layers of soil. We present a new, closed-form model of the soil displaced by an angled, spinning wheel to analyze the trenching potential of a driving strategy and inform the control of the wheel. The model is demonstrated with single wheel experiments under different driving conditions. The model suggests: that a deep trench does not require large tractive efforts; that the shape of the trench can be controlled; and that a rear wheel has a lower risk of entrapment when trenching than a front wheel. Ultimately this model could be used in a nonprehensile manipulation planning or learning algorithm to enable autonomous trenching.
Physics-Informed Learning Machines for Partial Differential Equations: Gaussian Processes Versus Neural Networks

We review and compare physics-informed learning models built upon Gaussian processes and deep neural networks for solving forward and inverse problems governed by linear and nonlinear partial differential equations. We define a unified data model on which Gaussian processes, physics-informed Gaussian processes, neural networks, and physics-informed neural networks are based. We develop continuous-time and discrete-time models to facilitate different application scenarios. We present a connection between a Gaussian process and an infinitely wide neural network, which enables us to obtain a “best” kernel, which is determined directly by the data. We demonstrate the implementation of physics-informed Gaussian processes and physics-informed neural networks using a pedagogical example. Additionally, we compare physics-informed Gaussian processes and physics-informed neural networks for two nonlinear partial differential equations, i.e. the 1D Burgers’ equation and the 2D Navier–Stokes, and provide guidance in choosing the proper machine learning model according to the problem type, i.e. forward or inverse problem, and the availability of data. These new methods for solving partial differential equations governing multi-physics problems do not require any grid, and they are simple to implement, and agnostic to specific application. Hence, we expect that variants and proper extensions of these methods will find broad applicability in the near future across different scientific disciplines but also in industrial applications.
An “extra life” for the arcade? Entrepreneurship, hybridization, and industry renewal

Abstract Entrepreneurs pursue opportunities in a variety of contexts. Research has focused on opportunity creation and recognition in new and emerging industries. However, how entrepreneurs pursue opportunities in struggling industries at the end of their lifecycles is not clear. To investigate this phenomenon and induce an empirically grounded theoretical model that explains how it unfolds, this study examined the case of the U.S. arcade industry – an industry that despite precipitous declines has experienced a recent and unexpected rebirth through entrepreneurial activity. The findings contribute to research on entrepreneurship in unmunificent environments and suggest that dying industries contain the seeds for renewal through entrepreneurship and business model hybridization.
Inferring active cis-regulatory modules to predict functional regulatory elements

Abstract Transcription factors (TFs) often function as cis-regulatory modules (CRMs) including both master factors and mediator coactivators to activate enhancers or promoters and regulate target gene transcription. Cell type-specific ChIP-seq profiling of multiple TFs makes it feasible to infer functional CRMs for a particular cell type. Yet, approaches based on co-localization of TF ChIP-seq peaks to infer CRMs are applied but many weak binding events, especially of those mediators, are missed by peak callers, resulting in an incomplete identification of CRMs. We developed a ChIP-seq data-based CRM inference approach with Gibbs-Sampling (ChIP-GSM). In a Bayesian framework, ChIP-GSM samples read counts of TFs iteratively for the joint effect of each potential TF combination. Using inferred CRMs as novel features, ChIP-GSM employs a logistic regression model to predict active regulatory elements. Performance validation on FANTOM5 enhancer or promoter regions revealed the superior performance of CRMs on regulatory region activity prediction than TFs. Finally, integrating CRMs inferred for K562 cells and gene expression data we found that CRMs are likely to activate regulatory regions or genes at different time points to mediate distinct cellular functions. Author Summary Accurately inferring cis-regulatory modules (CRMs) from a large set of TFs is a challenging task because the binding signals of TFs are often weak, noisy and sensitive to the cellular environment. Nevertheless, investigating TF associations may help understand the difference between enhancer and promoter activation mechanisms. In this paper, we develop a computational method (ChIP-GSM) to infer CRMs acting on regulatory elements at enhancer and promote regions. The novel method is built upon a Bayesian framework with Gibbs sampling that can be used to infer CRMs reliably hence to predict regulatory elements. The performance of ChIP-GSM is compared to that of existing methods, demonstrating its improved performance. Experimental results demonstrate that CRMs identified by ChIP-GSM are likely activating regulatory regions at different time points to mediate distinct cellular functions.
Pregnancy Outcomes Among Women With and Without Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Importance Published data suggest that there are increased hospitalizations, placental abnormalities, and rare neonatal transmission among pregnant women with coronavirus disease 2019 (COVID-19). Objectives To evaluate adverse outcomes associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in pregnancy and to describe clinical management, disease progression, hospital admission, placental abnormalities, and neonatal outcomes. Design, Setting, and Participants This observational cohort study of maternal and neonatal outcomes among delivered women with and without SARS-CoV-2 during pregnancy was conducted from March 18 through August 22, 2020, at Parkland Health and Hospital System (Dallas, Texas), a high-volume prenatal clinic system and public maternity hospital with widespread access to SARS-CoV-2 testing in outpatient, emergency department, and inpatient settings. Women were included if they were tested for SARS-CoV-2 during pregnancy and delivered. For placental analysis, the pathologist was blinded to illness severity. Exposures SARS-CoV-2 infection during pregnancy. Main Outcomes and Measures The primary outcome was a composite of preterm birth, preeclampsia with severe features, or cesarean delivery for abnormal fetal heart rate among women delivered after 20 weeks of gestation. Maternal illness severity, neonatal infection, and placental abnormalities were described. Results From March 18 through August 22, 2020, 3374 pregnant women (mean [SD] age, 27.6 [6] years) tested for SARS-CoV-2 were delivered, including 252 who tested positive for SARS-CoV-2 and 3122 who tested negative. The cohort included 2520 Hispanic (75%), 619 Black (18%), and 125 White (4%) women. There were no differences in age, parity, body mass index, or diabetes among women with or without SARS-CoV-2. SARS-CoV-2 positivity was more common among Hispanic women (230 [91%] positive vs 2290 [73%] negative; difference, 17.9%; 95% CI, 12.3%-23.5%;P Conclusions and Relevance In a large, single-institution cohort study, SARS-CoV-2 infection during pregnancy was not associated with adverse pregnancy outcomes. Neonatal infection may be as high as 3% and may occur predominantly among asymptomatic or mildly symptomatic women. Placental abnormalities were not associated with disease severity, and hospitalization frequency was similar to rates among nonpregnant women.
Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples

Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI-FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against the gold standard, nasopharyngeal swab specimens. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.
Shared Clinical Decision-Making Recommendations for Adult Immunization: What Do Physicians Think?

In 2019, the Advisory Committee on Immunization Practices (ACIP) incorporated the terminology “shared clinical decision-making” (SDM) into recommendations for two adult vaccines. To assess among general internal medicine physicians (GIMs) and family physicians (FPs) nationally (1) attitudes about and experience with ACIP SDM recommendations, (2) knowledge of insurance reimbursement for vaccines with SDM recommendations, (3) how SDM recommendations are incorporated into vaccine forecasting software, and (4) physician and practice characteristics associated with not knowing how to implement SDM. Survey conducted in October 2019–January 2020 by mail or internet based on preference. Networks of GIMs and FPs recruited from American College of Physicians (ACP) and American Academy of Family Physicians (AAFP) who practice ≥ 50% in primary care. Post-stratification quota sampling performed to ensure networks similar to ACP and AAFP memberships. Responses on 4-point Likert scales (attitudes/experiences), true/false options (knowledge), and categorical response options (forecasting). Multivariable modeling with outcome of “not knowing how to implement SDM” conducted. Response rate was 64% (617/968). Most physicians strongly/somewhat agreed SDM requires more time than routine recommendations (90%FP; 95%GIM, p = 0.02) and that they need specific talking points to guide SDM discussions (79%FP; 84%GIM, p = NS). There was both support for SDM recommendations for certain vaccines (81%FP; 75%GIM, p = 0.06) and agreement that SDM creates confusion (64%FP; 76%GIM, p = 0.001). Only 41%FP and 43%GIM knew vaccines recommended for SDM would be covered by most health insurance. Overall, 38% reported SDM recommendations are displayed as “recommended” and 23% that they did not result in any recommendation in forecasting software. In adjusted multivariable models, GIMs [risk ratio 1.44 (1.15–1.81)] and females [1.28 (1.02–1.60)] were significantly associated with not knowing how to implement SDM recommendations To be successful in a primary care setting, SDM for adult vaccination will require thoughtful implementation with decision-making support for patients and physicians.
Visual Perception: How Better Imaging Can Make Things Worse

Summary Visual search is critical to daily life and to socially important tasks — from cancer screening to airport security. New research shows how a technological advancement can interact with the human visual system to improve search for one type of target while making matters worse for another. Part of the problem is that we are surprisingly bad at knowing where we have looked.
Sustainable values and willingness to pay: an analysis of an analytical technique

The concept of sustainability has become popular in today's business environment as consumers' environmental concerns remain a top priority for consumers. With the US consumer market projected to spend over USD 150 billion by 2021 in the sustainability segment, the importance of offering sustainable products has taken a renewed interest. Today, the agenda for sustainability has gained more traction among small and medium-sized businesses. However, such resource constrained companies do not typically have access to sophisticated tools to discern the drivers of consumer's willingness to pay (WTP) for sustainable products. In this paper we study the factors that influence consumer's WTP for sustainable products in the grocery industry. We show how traditional techniques of analysis such as regression analysis failed to bring out deeper insights that can be gained by using no-code machine learning. Implications of these findings and directions for future research are discussed in detail.
A Novel Xenograft Model Demonstrates Human Fibroblast Behavior During Skin Wound Repair and Fibrosis.

Objective: Xenografts of human skin in immunodeficient mice provide a means of assessing human skin physiology and its response to wounding. Approach: We describe a novel xenograft model using full-thickness human neonatal foreskin to examine human skin wound repair. Full-thickness 8 mm human neonatal foreskin biopsies were sutured into the dorsum of NOD scid gamma (NSG; NOD.Cg-Prkdc scidIl2rgtm1Wjl/SzJ) pups as subcutaneous grafts. At postnatal day 21 the subcutaneous grafts were exposed to cutaneous grafts. Following maturation of 2 months, xenografts were then wounded with 5 mm linear incisions and monitored until postwound day (PWD) 14 to study skin repair and fibrosis. To explore whether our model can be used to test the efficacy of topical therapies, wounded xenografts were injected with antifibrotic fibroblast growth factor 2 (FGF2) for the first four consecutive PWDs. Xenografts were harvested for analysis by histology and fluorescence-activated cell sorting (FACS). Results: Xenografts were successfully engrafted with evidence of mouse-human anastomoses and resembled native neonatal foreskin at the gross and microscopic level. Wounded xenografted skin scarred with human collagen and an expansion of CD26-positive human fibroblasts. Collagen scar was quantitated by neural network analysis, which revealed distinct clustering of collagen fiber networks from unwounded skin and wounded skin at PWD7 and PWD14. Collagen fiber networks within FGF2-treated wounds at PWD14 resembled those in untreated wounded xenografts at PWD7, suggesting that FGF2 treatment at time of wounding can reduce fibrosis. Innovation and Conclusion: This novel xenograft model can be used to investigate acute fibrosis, fibroblast heterogeneity, and the efficacy of antifibrotic agents during wound repair in human skin.
Selenomethionine modulates insulin secretion in the MIN6-K8 mouse insulinoma cell line.

Selenium is an essential trace element of interest for its potential role in glucose homeostasis. The present study investigated the impact of selenium supplementation as selenomethionine (SeMet) on insulin secretion in MIN6-K8 cells, a pancreatic β-cell model. We found that SeMet enhanced percent insulin secretion, while also increasing tolbutamide- and KCl-induced percent insulin secretion. RNA-sequencing showed that SeMet supplementation altered expression of several selenoproteins, including glutathione peroxidase 3 (Gpx3) and selenoprotein P (SelP). Targeted knockdown of Gpx3 increased both percent and total insulin release, while SelP knockdown increased insulin content and insulin release. Collectively, these studies support a putative role for selenium and selenoproteins in the regulation of insulin secretion, glucose homeostasis, and diabetes risk.
Comparative Aspects of Nucleotide and Amino-acid Metabolism in Toxoplasma gondii and other Apicomplexa

Publisher Summary Nucleotides and amino acids are of fundamental importance in the replication and development of Toxoplasma gondii and other apicomplexan parasites. Nucleotides are in particular essential for replication of DNA and transcription of RNA in rapidly dividing stages. Nucleotides are also essential in providing the cellular energy sources (ATP and GTP), and are involved in numerous other metabolic roles. Nucleotides are either synthesized from small molecules and amino acids, or they are acquired via salvage pathways from preformed host-derived nucleobases and nucleosides. The apicomplexan parasites considered in this chapter, Toxoplasma gondii, Plasmodium falciparum, and Cryptosporidium parvum, are important pathogens of humans that cause significant morbidity and mortality. Notably, current treatment strategies in human infections caused by T. gondii or P. falciparum are based on blocking the accumulation of nucleotides. This validated approach to chemotherapy highlights the significance of further research to dissect details of nucleotide metabolism in the Apicomplexa as well as the potential for this research to lead to the development of new treatments.
Nonlinear Model Control Revisited

We investigate the stability and robustness of nonlinear, adaptive feedback systems of the form: z(t) = - LN z (t) + r(t). Here z(t) is an input signal, r(t) is a bounded input, L is a linear, casual operator and N is a sector bonded nonlinearity representing model uncertainties due to nonlinearities and low order modeling. The above feedback system arises where we use nonlinear model feeback control with sodel mismatch.
Studies of gapped DNA substrate binding by mammalian DNA polymerase beta. Dependence on 5'-phosphate group.

Purified mammalian DNA polymerase beta (beta-pol) fills short gaps of up to 6 nucleotides by a processive mechanism, and this gap-filling activity requires a PO4 group on the 5'-side of the gap (Singhal, R. K., and Wilson, S. H. (1993) J. Biol. Chem. 268, 15906-15911). To assess details of bimolecular binding between beta-pol and a 5-nucleotide (nt) gapped radiolabeled heteropolymeric DNA substrate, beta-pol.DNA complexes were formed, photochemically cross-linked using UV light, and analyzed by SDS-polyacrylamide gel electrophoresis and autoradiography. A 39-nt template was annealed with two 17-mer oligonucleotides, generating a 5-nt gap. The results indicate that beta-pol binds to both the template and primer strands, and binding is strongly enhanced by a 5'-PO4 on the downstream oligonucleotide, even though little cross-linking is observed to this oligonucleotide. The results suggest that beta-pol recognizes the 5'-side of a long single-stranded gap in DNA, provided it contains a 5'-PO4. Additional beta-pol.DNA binding measurements were performed using a competition assay to assess the ability of heteropolymeric DNA to inhibit synthesis on a homopolymeric template-primer system. The results indicate that in addition to the 5'-PO4, the length of the single-stranded template nucleic acid adjacent to the 5'-PO4 is also important for tight binding. Proteolysis of the cross-linked beta-pol.DNA complex with trypsin resulted in a single radiolabeled tryptic product corresponding to nucleic acid cross-linked to the 8-kDa domain. The results demonstrate that the role of the 8-kDa domain is to direct beta-pol binding to the phosphorylated 5'-position in gapped DNA substrates.
The increased frequency of acute myocardial infarction during summer months in a warm climate; a study of 1,386 cases from Dallas, Texas.

Abstract The seasonal and monthly frequency of occurrence in a series of 1,386 cases of proved myocardial infarction is reported from Dallas, Texas. The greatest number of cases occurred in the summer months, and the lowest number of cases in the winter months. No previous data from the United States have been reported concerning the seasonal variation in occurrence of this disease in a hot climate. The increased summer frequency of this illness is entirely different from previous reports from northern United States cities where the greatest number of cases have been found to occur during the winter months. The importance of very hot weather as a precipitating or predisposing factor in acute myocardial infarction is discussed.
Thermal conductivity of evacuated glass beads: Line source measurements in a large volume bead bed between 225 and 300 K

Line source measurements of thermal conductivity have been made in a large tank of evacuated glass beads that were used as a thermal simulator for the Lunar Heat Flow Experiment. Measurements were made with two 3/16 inch diameter probes 87 inches long that contained five (5) evenly spaced thermocouples and a double filament heater wire. The probes were inserted vertically from the top into the bead bed, which allowed ten (10) measurements of conductivity to be made over an interval of depth of 55 inches in tank. Power densities used ranged from 1.2 to 2.2 MW/cm. The bead tank is 21 inches in diameter by 86.75 inches in depth with temperature control at the outer walls. This tank was contained in a vacuum chamber that could be evacuated to gas pressure 10 - 5 to 10 - 4 Torr. Measurements were made at various bead bed temperatures between 225 and 300 K. Measurements at 225 K gave a range of conductivity values from 1.0 to 4.0 × 10 - 4 watt/cm.K. The conductivity increased uniformity over the interval of depth measured. Extrapolation of the values to the surface of the bead tank indicates an average conductivity of 0.7 × 10 - 4 watt/cm K. Measurements using the Lunar Heat Flow Experiment probes at 225 K yield values in good agreement, ′ 10%, with the line source data. All of the probe qualification tests were made at 225 K. These comparisons demonstrate that valid conductivity measurements can be made with the heat flow probe. The increase in conductivity with depth is due to an increase in compressive stress. However, the observed increase at 225 K is much greater than would be expected from "hydrostatic" loading alone. Measurements at higher bead bed temperatures, 246 K and 258 K, yield lower values of conductivity. If the increase of conductivity with depth is due to "hydrostatic" loading alone, an increase of conductivity with increasing temperature would be expected. The opposite observed effect suggests that compressive stresses from thermal contraction of the bead jacket are important.
Good features to track for visual SLAM

Not all measured features in SLAM/SfM contribute to accurate localization during the estimation process, thus it is sensible to utilize only those that do. This paper describes a method for selecting a subset of features that are of high utility for localization in the SLAM/SfM estimation process. It is derived by examining the observability of SLAM and, being complimentary to the estimation process, it easily integrates into existing SLAM systems. The measure of estimation utility is formulated with temporal and instantaneous observability indices. Efficient computation strategies for the observability indices are described based on incremental singular value decomposition (SVD) and greedy selection for the temporal and instantaneous observability indices, respectively. The greedy selection is near-optimal since the observability index is (approximately) submodular. The proposed method improves localization and data association. Controlled synthetic experiments with ground truth demonstrate the improved localization accuracy, and real-time SLAM experiments demonstrate the improved data association.