cssi/SciSciGPT-SciSciNet huggingface dataset:
Quicktime Virtual Reality Maps for the Web

Publisher Summary Virtual Reality (VR) can enhance the effectiveness of maps by providing the user with a sense of immersion and control over the spatial environment. VR allows the viewer to examine and explore virtual objects and scenes from different points of view. This chapter focuses on VR and examines how Apple's QuickTime Virtual Reality (QTVR) can be used to transcend 2D maps by changing and improving the way spatial information is communicated. An interactive virtual landscape of Magnolia, Iowa, is also presented by the chapter to show how a static map can be transformed into a relatively immersive virtual environment. VR technology has the ability to expand human understanding by providing natural experiences in realistic virtual environments. In the future, virtual maps will be transformed into incredibly complex spatial environments that will be dynamically displayed for analysis on hand held devices for the convenience and enjoyment of map users.
Monitoring of Coastal Ocean Waters Receiving Wastewaters in the USA: Review of Two 1990 Publications of the USA National Research Council – National Academy of Sciences and National Academy of Engineering

Required monitoring of the physical, biological and chemical condition of the nearshore waters of the ocean receiving treated wastewaters has been underway in the U.S.A. since 1955 or about 35 years. When established the stated intent had been to utilize the information obtained to evaluate the effects of the diffusion of wastewaters upon the beneficial values of these receiving waters. That is upon the food web including game and food fish; upon water contact sports uses; upon aesthetics; and upon the local, regional, and worldwide ecology. To this end original requirements had included a provision that the regulatory agency reduce the data obtained from the monitoring effort to information useful to themselves as well as to facility design and operational authorities. Inasmuch as the monitoring effort in 1989 was using funds in excess of 130 million dollars per year and had a 35 year data base, the Marine Board of the National Research Council - National Academy of Sciences: National Academy of Engineering established committees of scientists to evaluate the progress of the national monitoring effort and of the longest and most complete program of the Southern California Bight. It was found that the essential portion of the program, that of reducing the data obtained to usable information, had not been carried on so that approximately 35 years of data existed with little to zero information. In addition the data existed in pools of intensive samplings around discharge points with very little overall study of the coastal waters. Whether the discharge points were significantly different from the “normal” coastal waters was not really known because “normal” was not known. The Committees recommended procedures to follow to rectify these basic problems including reallocation of current funding to cover the research, control, design and operational needs. Their findings are summarized in the paper.
Reasons for Leaving the Academy: a Case Study on the ‘Opt Out’ Phenomenon among Younger Female Researchers

This study provides a contemporary case for exploring the assumed ‘opt out’ phenomenon among early-career female researchers. Based on rich data from a Danish case study, we adopt an integrated, holistic perspective on women's reasons for leaving the academy. We propose the concept of ‘adaptive decision-making’ as a useful analytical starting point for synthesizing structure- and agency-centred perspectives on academic career choices. Our study provides new insights into the myriad of structural and cultural conditions circumscribing the career ambitions and expectations of younger female (and male) researchers, at a critical transition point epitomized by high demands for scholarly productivity, international mobility and accumulation of social capital. Located within the context of Danish higher education, our study also adds to the current discussion of why academic gender stratifications persist in a country renowned for its leading international position on issues of societal gender equality.
Local, Systemic, and Genetic Considerations of Endodontic Treatment Prognosis

The outcome of nonsurgical endodontic treatment/re-treatment and the survival of the endodontically treated tooth depend on many known and possibly unknown factors. Among the ones that have been identified in the literature, 21 factors will be discussed in this chapter. These factors are classified under local (including anatomical, preoperative, intraoperative, and postoperative) and systemic (including demographic, genetic, systemic disease and medications, and geriatric) factors. Each factor is reviewed, and its effect on the outcome of the endodontic treatment and/or survival of the treated tooth is discussed based on the highest available evidence. Among the factors discussed in this chapter, the ones that are believed to be strongly associated with the outcome of the root canal treatment/re-treatment are periapical status, apical extent of root canal filling, quality of the root canal filling, and quality of the restoration.
A Robot Experiment in Collective Perception

In this chapter, we support the generality of our design methodology by considering a novel problem scenario: collective perception. The collective perception scenario requires a swarm of robots to explore an environment and evaluate the abundance of certain features that are scattered therein (e.g., the availability of precious metals or other minerals) with the objective to determine which feature is the most frequent.
Dinuclear PhotoCORMs: Dioxygen-Assisted Carbon Monoxide Uncaging from Long-Wavelength-Absorbing Metal-Metal-Bonded Carbonyl Complexes.

We describe a new strategy for triggering the photochemical release of caged carbon monoxide (CO) in aerobic media using long-wavelength visible and near-infrared (NIR) light. The dinuclear rhenium–manganese carbonyl complexes (CO)5ReMn(CO)3(L), where L = phenanthroline (1), bipyridine (2), biquinoline (3), or phenanthrolinecarboxaldehyde (4), each show a strong metal–metal-bond-to-ligand (σMM → πL*) charge-transfer absorption band at longer wavelengths. Photolysis with deep-red (1 and 2) or NIR (3 and 4) light leads to homolytic cleavage of the Re–Mn bonds to give mononuclear metal radicals. In the absence of trapping agents, these radicals primarily recombine to reform dinuclear complexes. In oxygenated media, however, the radicals react with dioxygen to form species much more labile toward CO release via secondary thermal and/or photochemical reactions. Conjugation of 4, with an amine-terminated poly(ethylene glycol) oligomer, gives a water-soluble derivative with similar photochemistry. In this contex...
Does this interface make my sensor look bad? Basic principles for designing usable, useful interfaces for sensor technology operators

Even as remote sensing technology has advanced in leaps and bounds over the past decade, the remote sensing community lacks interfaces and interaction models that facilitate effective human operation of our sensor platforms. Interfaces that make great sense to electrical engineers and flight test crews can be anxiety-inducing to operational users who lack professional experience in the design and testing of sophisticated remote sensing platforms. In this paper, we reflect on an 18-month collaboration which our Sandia National Laboratory research team partnered with an industry software team to identify and fix critical issues in a widely-used sensor interface. Drawing on basic principles from cognitive and perceptual psychology and interaction design, we provide simple, easily learned guidance for minimizing common barriers to system learnability, memorability, and user engagement.
Star coupler for high-etendue LIDAR

A 1:480 star coupler is designed for high-etendue LIDAR applications and demonstrated using silicon waveguides. A large 0.96-mm output aperture and dense output waveguide spacing of 2 μm allows for a narrow 0.072° far-field spot.
An Application of Spectral Regularization to Machine Learning and Cancer Classification

We adapt supervised statistical machine learning methods to regularize noisy unsupervised feature vectors. Theorems on two graph-based denoising approaches taken from numerical analysis and harmonic spectral methods are discussed. A feature vector x = (x1, …, x p ) = {x q } q = 1 p is viewed as a function f(q) on its index set. This function can be regularized or smoothed using a graph/metric structure on the index set. This smoothing can involve a penalty functional on feature vectors analogous to those in statistical learning. Our regularization of feature vectors is independent of their role in subsequent supervised learning tasks. An application is given to cancer prediction/classification in computational biology.
Mechanochemical nitration of aromatic compounds

ABSTRACTNitration of organic compounds is necessary to produce many energetic materials, such as TNT and nitrocellulose. The conventional nitration process uses a mixture of concentrated sulfuric and nitric acids as nitrating agents and multiple solvents. The chemicals are corrosive and require special handling and disposal procedures. In this study, aromatic nitration has been achieved using solvent-free mechanochemical processing of environmentally benign precursors. Mononitrotoluene was synthesized by milling toluene with sodium nitrate and molybdenum trioxide as a Lewis acid catalyst. Several parameters affecting the desired product yield were identified and varied. A number of byproducts, i.e., dimers of toluene were also produced, but the selectivity was observed to increase with increasing mononitrotoluene yield. Both absolute mononitrotoluene yields and selectivity of its production increased with the increase in the energy transferred to the material from the milling tools.
The effects of dispersal and river spatial structure on asynchrony in consumer–resource metacommunities

Author(s): Anderson, KE; Hayes, SM | Abstract: River network structure influences many important population and community processes. Previous work examining ecological dynamics in river networks has focused on within-trophic-level dynamics, with less emphasis on food-web interactions. Yet, trophic interactions in rivers are influenced by processes that may interact with network structure and position. Using a spatially explicit consumer–resource model, we explore how trophic dynamics are influenced by the branching nature of river networks. We focus on cases where the consumer–resource interaction is prone to temporal oscillations and periodic low population sizes. In these cases, we find that the influence of network structure and dispersal can reduce temporal variability and increase persistence of consumers and resources at the metacommunity scale. The effects of network structure and dispersal on our observed metacommunity dynamics result from asynchrony among dynamics of local communities: when asynchronous local fluctuations are averaged, consumer–resource dynamics become less variable and bounded higher above zero at regional spatial scales. Fluctuations synchronise across clusters of linked local communities. Communities that connect to only one other downstream community typically vary independently of other patches and show high variability, while communities that are linked to multiple upstream and downstream habitats show greater clustering and less variability. These patterns suggest that headwater versus mainstem locations in river networks may show different levels of population variability and thus differential responses to management and restoration efforts.
End-On Bridging Dinitrogen Complex of Scandium

The first (N═N)2– complex of a rare-earth metal with an end-on dinitrogen bridge, {K(crypt)}2{[(R2N)3Sc]2[μ-η1:η1-N2]} (crypt = 2.2.2-cryptand, R = SiMe3), has been isolated from the reduction of Sc(NR2)3 under dinitrogen at −35 °C and characterized by X-ray crystallography. The structure differs from the characteristic side-on structures previously observed for over 40 crystallographically characterized rare-earth metal (N═N)2– complexes of formula [A2Ln(THF)x]2[μ-η2:η2-N2] (Ln = Sc, Y, and lanthanides; x = 0, 1; A = anionic ligand such as amide, cyclopentadienide, and aryloxide). The 1.221(3) A N—N distance and the 1644 cm–1 Raman stretch are consistent with the presence of an (N═N)2– bridge. The observed paramagnetism of the complex by Evans method measurements is consistent with DFT calculations that suggest a triplet (3A2) ground state in D3 symmetry involving two degenerate Sc—N2—Sc bonding orbitals. Upon brief exposure of the orange Sc3+ bridging dinitrogen complex to UV-light, photolysis to form t...
How do Regulators Regulate? Enforcement of the Pure Food and Drugs Act, 1907–38

Economists have devoted relatively little attention to analyzing how government officials actually enforce regulation. This is a significant omission, since the efficacy of regulatory enforcement and the effects of regulation on economic outcomes may depend on how regulators regulate. This article sheds light on these issues by examining how the fledgling Food and Drug Administration (FDA) enforced the Pure Food and Drugs Act from 1907 to 1938. I argue that because the FDA's ability to enforce this law through deterrence was limited, effective enforcement could be obtained only in those instances where the agency had the capacity to offer benefits to compliant firms in the way of quality certification or direct assistance in improving product quality. The available evidence on the FDA's enforcement activities is consistent with this prediction. The analysis presented may help to explain why contemporary regulatory agencies spend considerable resources on advisory enforcement activities. Copyright 2006, Oxford University Press.
Mass Digitization of Early Modern Texts With Optical Character Recognition

Optical character recognition (OCR) engines work poorly on texts published with premodern printing technologies. Engaging the key technological contributors from the IMPACT project, an earlier project attempting to solve the OCR problem for early modern and modern texts, the Early Modern OCR Project (eMOP) of Texas A8M received funding from the Andrew W. Mellon Foundation to improve OCR outputs for early modern texts from the Eighteenth Century Collections Online (ECCO) and Early English Books Online (EEBO) proprietary database products—or some 45 million pages. Added to print problems are the poor quality of the page images in these collections, which would be too time consuming and expensive to reimage. This article describes eMOP's attempts to OCR 307,000 documents digitized from microfilm to make our cultural heritage available for current and future researchers. We describe the reasoning behind our choices as we undertook the project based on other relevant studies; discoveries we made; the data and the system we developed for processing it; the software, algorithms, training procedures, and tools that we developed; and future directions that should be taken for further work in developing OCR engines for cultural heritage materials.
Convolutional neural network for clinical narrative categorization

Stacked or sequential convolutional layers in a Convolutional Neural Network (CNN) have shown state-of-the-art results in Image and Pattern Recognition. Recently, CNN's have shown promising results in Natural Language Processing (NLP) tasks. Using a CNN with concurrent convolutional layers, we conduct text categorization on a clinical narrative dataset with imbalance classes. Clinical narratives are written in natural language, documenting the clinical encounter as observed from the clinician along with the process of care. For this research, we experiment with various CNN architectures with a focus on the embedding layer, the first layer in an NLP-based CNN. The input to the embedding layer is the document matrix and the length is typically determined by a maximum document length. This may not be the best option in the case of highly imbalanced classes. Using simple data analysis, we obtain an optimal document length for the document matrix in the embedding layer of the CNN. Comparing the results from our previous published research on classifying clinical narratives, this CNN architecture provides a significant improvement in the F 1 -Score to our previous ensemble-based approach incorporating multiple methods.
Features of prescription drug monitoring programs associated with reduced rates of prescription opioid-related poisonings.

Abstract Background The United States is in the midst of an opioid epidemic. In addition to other system-level interventions, all states have responded during the crisis by implementing prescription drug monitoring programs (PDMPs). This study examines associations between specific administrative features of PDMPs and changes in the risk of prescription opioid-related poisoning (RxORP) over time. Methods This longitudinal, observational study utilized a ‘natural experiment’ design to assess associations between PDMP features and risk of RxORP in a nationally-representative population of privately-insured adults from 2004 to 2014. Administrative health claims data were used to identify inpatient hospital admissions and emergency department visits related to RxORP. Generalized estimating equation Poisson regression models were used to examine associations between specific PDMP features and changes in relative risk (RR) of RxORP over time. Results In adjusted analyses, states without PDMPs experienced an average annual increase in the rate of RxORP of 9.51% over the study period, while states with operational PDMPs experienced an average annual increase of 3.17%. The increase in RR of RxORP over time in states with operational PDMPs was significantly less than increases in states without PDMPs. States with specific features, including those that monitored more schedules or required more frequent data reporting, experienced stronger protective effects on the RR of RxORP over time. Conclusion This study examined associations between specific PDMP features and RxORP rates in a nationally-representative population of privately-insured adults. Results of this study may be used as empirical evidence to guide PDMP best practices.
Impact and Prevalence of Physical and Verbal Violence Toward Healthcare Workers.

Background Threatening and assaultive behaviors against healthcare workers are a growing national concern.1,2,3 Objective To assess the incidence and impact of aggression against healthcare workers, a safety and quality improvement project was initiated in an academic, tertiary care, urban hospital. Methods Through the Northwestern Academy of Quality and Safety Initiatives program, an invitation to complete an online survey was sent to healthcare workers. The survey inquired about prevalence, location, and type of experience of physical or verbal abuse by patients or families. Other goals were: 1) worker knowledge and use of reporting systems, 2) effect on healthcare worker engagement, and 3) report of posttraumatic symptoms. Results 34.4% of healthcare workers reported any incident of verbal or physical violence in the preceeding 12 months, with 13.5% reporting physical assault. Of those with any incident of physical or verbal violence, 60.2% endorsed at least one posttraumatic symptom, 9.4% missed work, and 30.1% had thoughts about leaving their job or career. The reported impact was the same for physical or verbal incidents. Discussion Physical and verbal abuse of healthcare workers is prevalent and has a significant impact on employee engagement and posttraumatic spectrum symptoms. These results are based on a cross-sectional survey at one institution and may have a significant selection and response bias. Conclusion Assessment of both verbal and physical aggression against healthcare workers should be standard. Front-line consulting psychiatrists and psychiatric programs for employee wellness could assess and manage this impact.
Types of Status Epilepticus

What is status epilepticus? For all the criticisms leveled at the now-traditional definition accepted by the International League Against Epilepsy (ILAE) and based on the 1962 Marseilles conference, “a condition characterized by an epileptic seizure which is so frequently repeated or so prolonged as to create a fixed and lasting epileptic condition” (1), this definition does capture the concepts nearly everyone wants. The condition is necessarily epileptic, i.e., related to abnormal electrical activity in the brain with a clinical, and unhealthy, alteration in neurologic function. The patient in status epilepticus (SE) is clearly in a different and worse state than one who has an individual epileptic seizure only. Shorvon notes that SE is “not simply an iterative version of ordinary epilepsy” (2). Whether it is a more serious and fulminant etiology of seizures that produces their prolongation and repetition, or whether there is a fundamentally different failure of inhibition (more than occurs between a spike and a clinical seizure), the patient in status epilepticus has entered a new and worse condition. Discrete epileptic seizures come to an end, although there may be a prolonged postictal state. In SE, however, there is a definite clinical imperative to interrupt seizures because the patient may suffer grievous harm otherwise. Not only are there extensive physiologic, and sometimes pathologic, changes occurring during SE (3), but there is also a fundamentally different and urgent clinical problem for the patient and physician.
A Global Optimization Algorithm using Lagrangian Underestimates and the Interval Newton Method

Convex relaxations can be used to obtain lower bounds on the optimal objective function value of nonconvex quadratically constrained quadratic programs. However, for some problems, significantly better bounds can be obtained by minimizing the restricted Lagrangian function for a given estimate of the Lagrange multipliers. The difficulty in utilizing Lagrangian duality within a global optimization context is that the restricted Lagrangian is often nonconvex. Minimizing a convex underestimate of the restricted Lagrangian overcomes this difficulty and facilitates the use of Lagrangian duality within a global optimization framework. A branch-and-bound algorithm is presented that relies on these Lagrangian underestimates to provide lower bounds and on the interval Newton method to facilitate convergence in the neighborhood of the global solution. Computational results show that the algorithm compares favorably to the Reformulation–Linearization Technique for problems with a favorable structure.
Counterpoise Model Implementation and New Graphical User Interface for Lightning Transient Analysis in OpenETran

A counterpoise ground model is added to EPRI's open source transient simulator. The approach to integrate this model is based on nodal analysis of the counterpoise conductor and electrical transient computations. A new graphical user interface for OpenETran is added and described in this paper. The user-interface regroups a tab window replacing the previous Excel spreadsheet interface for OpenETran, and adds a line visualization tool for more efficient line design in terms of shield wires, grounds, insulation and line arresters.
Assessment of acoustic Doppler current profiler heading errors on water velocity and discharge measurements

Abstract Boat-mounted acoustic Doppler current profilers (ADCPs) are commonly used to make both water velocity and discharge measurements. Most ADCPs measure the direction of travel of the water and boat using an internal compass. The effect of the heading on measurements made with an ADCP depends on the type of measurement and the boat velocity reference. When bottom track is used for the boat velocity reference a heading error will cause a rotational error in the measured water velocity, but the magnitude of the velocity and the computed discharge is unaffected. When an external boat velocity reference such as a global positioning system is used, the effect of heading errors can be substantial. Potential heading errors include errors in the compass reading caused by distortion in the earth magnetic field due to local objects on the boat and errors in determining the magnetic variation for a specific location. When using an external boat velocity reference heading errors will affect both measured water velocity and discharge. Analytical assessment of the heading errors shows the effect of these errors on velocity and discharge is directly proportional to the ratio of the boat speed to water speed. Therefore, maintaining a slow boat speed is imperative to accurately measuring water velocity and discharge when using an external boat velocity reference.
Self-reports of salt intake by 10- to 18-year-olds: relationship to urinary sodium excretion.

Our data indicated that self-reports of consumption of salty foods by children and adolescents were associated with 24-hour urinary sodium excretion. Specifically, youths 10 to 18 years of age who selected a poster depicting high-sodium foods excreted significantly more sodium than youths who selected a poster depicting low-sodium foods. Future research is needed to refine simplified self-report measures, to corroborate the validity of the measures, and to extend the studies to other samples, e.g., younger children.
Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

Asymptomatic left ventricular dysfunction (ALVD) is present in 3–6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found1–4. An inexpensive, noninvasive screening tool for ALVD in the doctor’s office is not available. We tested the hypothesis that application of artificial intelligence (AI) to the electrocardiogram (ECG), a routine method of measuring the heart’s electrical activity, could identify ALVD. Using paired 12-lead ECG and echocardiogram data, including the left ventricular ejection fraction (a measure of contractile function), from 44,959 patients at the Mayo Clinic, we trained a convolutional neural network to identify patients with ventricular dysfunction, defined as ejection fraction ≤35%, using the ECG data alone. When tested on an independent set of 52,870 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.93, 86.3%, 85.7%, and 85.7%, respectively. In patients without ventricular dysfunction, those with a positive AI screen were at 4 times the risk (hazard ratio, 4.1; 95% confidence interval, 3.3 to 5.0) of developing future ventricular dysfunction compared with those with a negative screen. Application of AI to the ECG—a ubiquitous, low-cost test—permits the ECG to serve as a powerful screening tool in asymptomatic individuals to identify ALVD. A deep learning algorithm applied to the electrocardiogram—a test of the heart’s electrical activity—can detect abnormally low contractile function of the heart, opening up the possibility for a simple screening tool for this condition.
Noise Flooding for Detecting Audio Adversarial Examples Against Automatic Speech Recognition

Neural models enjoy widespread use across a variety of tasks and have grown to become crucial components of many industrial systems. Despite their effectiveness and extensive popularity, they are not without their exploitable flaws. Initially applied to computer vision systems, the generation of adversarial examples is a process in which seemingly imperceptible perturbations are made to an image, with the purpose of inducing a deep learning based classifier to misclassify the image. Due to recent trends in speech processing, this has become a noticeable issue in speech recognition models. In late 2017, an attack was shown to be quite effective against the Speech Commands classification model. Limited-vocabulary speech classifiers, such as the Speech Commands model, are used quite frequently in a variety of applications, particularly in managing automated attendants in telephony contexts. As such, adversarial examples produced by this attack could have real-world consequences. While previous work in defending against these adversarial examples has investigated using audio preprocessing to reduce or distort adversarial noise, this work explores the idea of flooding p articular frequency bands of an audio signal with random noise in order to detect adversarial examples. This technique of flooding, which does not require retraining or modifying the model, is inspired by work done in computer vision and builds on the idea that speech classifiers are relatively robust to natural noise. A combined defense incorporating 5 different frequency bands for flooding the signal with noise outperformed other existing defenses in the audio space, detecting adversarial examples with 91.8% precision and 93.5% recall.
Mesalamine-Induced Myopericarditis: A Case Report and Literature Review

Inflammation of the myocardium (myocarditis) or pericardium (pericarditis) or both (myopericarditis) as side effects of mesalamine, a drug widely used in the treatment of inflammatory bowel disease, is a rare, but potentially lethal complication. We report a case of myopericarditis occurring in a young Caucasian woman 14 days following initiation of mesalamine therapy for treatment of a newly diagnosed ulcerative colitis (UC). She presented with pleuritic chest pain, elevated troponin levels and pre-syncope. The diagnosis of myopericarditis was made based on the clinical features, electrocardiogram (EKG) and cardiac magnetic resonance, which showed trace pericardial effusion. The patient's symptom and condition were dramatically improved upon discontinuing mesalamine, and a full recovery was achieved. Mesalamine-induced inflammation of the myocardium (myocarditis) or pericardium (pericarditis) or both (myopericarditis) is rare, but has fatal side effects. Early recognition of these side effects by clinicians and patients is important to prevent progression of the inflammation. Furthermore, patients should be educated to seek urgent medical attention if cardiac symptoms arise.
Critical time for weed removal in glyphosate-resistant soybean as influenced by preemergence herbicides

Widespread and repeated use of glyphosate resulted in an increase in glyphosate-resistant (GR) weeds. This led to an urgent need for diversification of weed control programs and use of PRE herbicides with alternative sites of action. Field experiments were conducted over a 4-yr period (2015 to 2018) across three locations in Nebraska to evaluate the effects of PRE-applied herbicides on critical time for weed removal (CTWR) in GR soybean. The studies were laid out in a split-plot arrangement with herbicide regime as the main plot and weed removal timing as the subplot. The herbicide regimes used were either no PRE or premix of either sulfentrazone plus imazethapyr (350 + 70 g ai ha-1) or saflufenacil plus imazethapyr plus pyroxasulfone (26 + 70 + 120 g ai ha-1). The weed removal timings were at V1, V3, V6, R2, and R5 soybean stages, with weed-free and weedy season-long checks. Weeds were removed by application of glyphosate (1,400 g ae ha-1) or by hoeing. The results across all years and locations suggested that the use of PRE herbicides delayed CTWR in soybean. In particular, the CTWR without PRE herbicides was determined to be around the V1 to V2 (14 to 21 d after emergence [DAE]) growth stage, depending on the location and weed pressure. The use of PRE-applied herbicides delayed CTWR from about the V4 (28 DAE) stage up to the R5 (66 DAE) stage. These results suggest that the use of PRE herbicides in GR soybean could delay the need for POST application of glyphosate by 2 to 5 wk, thereby reducing the need for multiple applications of glyphosate during the growing season. Additionally, the use of PRE herbicides could provide additional modes of action needed to manage GR weeds in GR soybean.Nomenclature: Glyphosate; imazethapyr; pyroxasulfone; saflufenacil; sulfentrazone; soybean; Glycine max (L.) Merr
Mucosa Biology and the Development of Rheumatoid Arthritis: Potential for Prevention by Targeting Mucosal Processes

As the goal in rheumatoid arthritis (RA) management shifts toward the prevention of joint disease, it is important to consider the role of mucosal sites in the pathogenesis of RA because they may be potential targets for preventive interventions. Multiple mucosal sites demonstrate immune dysregulation and inflammation in individuals with classifiable RA as well as, importantly, in individuals with systemic autoimmunity related to RA. The lung, gingival, and gastrointestinal mucosae are most strongly implicated in RA pathogenesis and may be sites where autoimmunity in RA initially develops. Targeting the exact site where the initial immune dysregulation in RA occurs is an appealing approach to prevention because it could avoid unwanted side effects of systemic therapies. However, several challenges must be addressed before mucosa-targeted interventions are a readily available option for RA prevention. Studies are needed to determine whether all RA-related immune dysregulation at mucosal sites will progress to joint disease and whether one or multiple mucosal sites demonstrate dysregulation prior to the development of classifiable RA. These areas of future research are likely to provide crucial pieces in the understanding of RA pathogenesis and ultimately RA prevention.
Chapter 6 – Analysis: 100 Percent Renewable Energy Systems

Publisher Summary This chapter describes the efforts of the Los Angeles Community College District to implement a 100 percent renewable energy system for each of its nine college campuses and at the national level; two studies of Denmark are presented. The design of renewable energy systems involves three major technological changes: energy savings on the demand side, efficiency improvements in the energy production, and the replacement of fossil fuels by various sources of renewable energy. The analysis of such systems includes strategies for integrating renewable sources into complex energy systems, which are influenced by energy savings and efficiency measures. Based on the case of Denmark, this chapter presents two studies that analyze the problems and perspectives of converting the present energy system into a 100 percent renewable energy system. The first study is a one-person university study; the second study is based on the technical inputs of embers of the Danish Society of Engineers (IDA).
Investigating Predictors of Increased Length of Stay After Resection of Vestibular Schwannoma Using Machine Learning.

OBJECTIVE To evaluate the predictors of prolonged length of stay (LOS) after vestibular schwannoma resection. STUDY DESIGN Retrospective chart review. SETTING Tertiary referral center. PATIENTS Patients who underwent vestibular schwannoma resection between 2008 and 2019. INTERVENTIONS Variables of interest included age, body mass index, comorbidities, symptoms, previous intervention, microsurgical approach, extent of resection, operative time, preoperative tumor volume, and postoperative complications. Predictive modeling was done through multivariable linear regression and random forest models with 80% of patients used for model training and the remaining 20% used for performance testing. MAIN OUTCOME MEASURES LOS was evaluated as the number of days from surgery to discharge. RESULTS Four hundred one cases from 2008 to 2019 were included with a mean LOS of 3.0 (IQR = 3.0-4.0). Postoperatively, 14 (3.5%) of patients had LOS greater than two standard deviations from the mean (11 days). In a multivariate linear regression model (adjusted R2 = 0.22; p < 0.001), preoperative tumor volume (p < 0.001), coronary artery disease (p = 0.002), hypertension (p = 0.029), and any major complication (p < 0.001) were associated with increased LOS (by 0.12, 3.79, 0.87, and 3.20 days respectively). A machine learning analysis using a random forest identified several potential nonlinear relationships between LOS and preoperative tumor dimensions (length, volume) and operative time that were not captured on regression. The random forest model had lower prediction error compared to the regression model (RMSE 5.67 vs. 44.59). CONCLUSIONS Tumor volume, coronary artery disease, hypertension, and major complications impact LOS. Machine learning methods may identify nonlinear relationships worthy of targeted clinical investigation and allow for more accurate patient counseling.
Abstract OT-13-01: A phase I study of preoperative ipilimumab, nivolumab, and talimogene laherparepvec for localized breast cancer

Background: Immunotherapy has emerged as a novel therapeutic strategy in many solid malignancies. In breast cancer, treatment with checkpoint inhibitors alone showed minimal response rates, likely because breast cancers are not sufficiently immunogenic to induce adequate baseline T cell activation. Talimogene laherparepvec (T-VEC) is an attenuated herpes simplex virus 1 (HSV-1) engineered to introduce the GM-CSF gene selectively into tumor cells to thereby enhance the immunogenicity of transduced tumor cells. T-VEC has been approved in the treatment of patients with advanced melanoma and injectable tumors. In a phase 1b clinical trial, T-VEC was well tolerated in combination with immunotherapy in patients with advanced melanoma. We evaluated the safety and tolerability of T-VEC, nivolumab, and ipilimumab in the preoperative treatment of early stage localized triple-negative breast cancer (TNBC) and hormone receptor (HR)-positive breast cancer. Trial design and eligibility criteria: This is a single site open-label phase 1b window of opportunity trial of neoadjuvant T-VEC in combination with nivolumab and ipilimumab in patients with localized breast cancer. Twenty patients with localized TNBC or HR-positive breast cancer with palpable tumors will be included. T-VEC is administered intratumorally in week 1 (106 plaque-forming units/mL [pfu/ml]) and then every 3 weeks (108 plaque-forming units/mL [pfu/ml]) for a total of 3 injections. Nivolumab (240 mg) is administered intravenously in week 1 and every 2 weeks for a total of 4 infusions. Ipilimumab (1 mg/kg) is administered intravenously in week 1 and week 6 for a total of 2 infusions. Breast cancer surgery will be carried out after completion of study treatment. Neoadjuvant chemotherapy could be administered before or after study treatment. Study objectives: The primary objective is to evaluate the safety and tolerability of T-VEC in combination with nivolumab and ipilimumab in this population. The secondary objectives are 1) to assess tumor response to T-VEC, nivolumab, and ipilimumab and 2) to descriptively analyze surgical specimens for evidence of tumor necrosis and inflammatory infiltration on histopathological examination. Present accrual: To date, 5 patients have been enrolled. As described above, the projected sample size is 20 patients. Clinical trials identification: NCT04185311 Citation Format: Vina P. Nguyen, Helena R. Chang, Maggie L. DiNome, Denise K. Oseguera, Deborah J. Wong, Anthony T. Nguyen, Stephen L. Shiao, John A. Glaspy. A phase I study of preoperative ipilimumab, nivolumab, and talimogene laherparepvec for localized breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr OT-13-01.
Post-operative Renal Failure, Shunt Type and Mortality after Norwood Palliation.

Abstract Background The Single Ventricle Reconstruction (SVR) trial demonstrated increased risk of death or heart transplant one year post-Norwood in subjects randomized to Blalock-Taussig shunts (mBTS) compared to right ventricle-to-pulmonary artery (RV-PA) shunts. We used the SVR public use database to evaluate incidence and risk factors for post-operative renal failure and relationships between renal failure, shunt type and outcomes post-Norwood. Methods Post-operative renal failure was defined a-priori as a 3-fold rise in creatinine from baseline, or dialysis use, within 7 days of Norwood. We used multivariate logistic regression to evaluate risk factors for post-operative renal failure and Cox hazard regression to determine the association between post-operative renal failure and one-year post-Norwood mortality. Results Overall, post-operative renal failure occurred in 8.4% (46/544) with risk factors including receipt of a mBTS (aOR 3.3, p=0.02), low center volume (aOR 2.7, p=0.005), presence of ≥2 pre-op complications (aOR 4.0, p Conclusions Post-operative renal failure is common after Norwood and is independently associated with mortality. Although renal failure is more common after mBTS, the highest mortality risk with renal failure occurs after RV-PA shunt.
The Polemics of Exile in Jeremiah 26–45: THE “WORDS OF JEREMIAH” AND SERAIAH'S COLOPHON IN THE MT AND LXX TRADITIONS

the absence of the “words of jeremiah” notice in the lxx ver sion of Seraiah's colophon has contributed to the view that the MT position of this notice obtained only secondarily, added at a time of the MT's growth subsequent to the emergence of the LXX corpus. According to this model, Seraiah's reediting of an earlier corpus involved his moving his colophon to the end of the work, along with the OAN, and then adding the words of Jeremiah notice, closing the early MT version of the book. The appearance of the words of Jeremiah in MT Jer 51:64 provides a very neat closure to the collection beginning with the identical phraseology in Jer 1:1, but it would not have been the result of Seraiah's editing of an earlier LXX corpus that already included the Supplement. Rather, it would have arisen from the development of an early version of Jeremiah 1–25+OAN that the author of the Supplement inherited. The inclusio device one finds in the MT version of Jer 1:1 and 51:64 is already put to use extensively in the early layers of the Jeremianic corpus, and would have been readily deployed when the basic theme of the prophet's words had been proved true and his oracles were collected sometime after the deportation of 597 BCE. The words of Jeremiah notice would have been at the end of the early OAN collection that included Seraiah's colophon.
Removal of introduced inorganic content from chipped forest residues via air classification

Abstract Inorganic content in biomass decreases the efficiency of conversion processes, especially thermochemical conversions. The combined concentrations of specific ash forming elements are the primary attributes that cause pine residues to be considered a degraded energy conversion feedstock, as compared to clean pine. Air classification is a potentially effective and economical tool to isolate high inorganic content biomass fractions away from primary feedstock sources to reduce their ash content. In this work, loblolly pine forest residues were air classified into 10 fractions whose ash content and composition were measured. Ash concentrations were highest in the lightest fractions (5.8–8.5 wt%), and in a heavy fraction of the fines (8.9–15.1 wt%). The removal of fractions with high inorganic content resulted in a substantial reduction in the ash content of the remaining biomass in forest thinnings (1.69–1.07 wt%) and logging residues (1.09–0.68 wt%). These high inorganic content fractions from both forest residue types represented less than 7.0 wt% of the total biomass, yet they contained greater than 40% of the ash content by mass. Elemental analysis of the air classified fractions revealed the lightest fractions were comprised of high concentrations of soil elements (silicon, aluminum, iron, sodium, and titanium). However, the elements of biological origin including calcium, potassium, magnesium, sulfur, manganese, and phosphorous were evenly distributed throughout all air classified fractions, making them more difficult to isolate into fractions with high mineral concentrations. Under the conditions reported in this study, an economic analysis revealed air classification could be used for ash removal for as little as $2.23 per ton of product biomass. This study suggests air classification is a potentially attractive technology for the removal of introduced soil minerals from pine forest residues.
Asian Americans and workplace discrimination: The interplay between sex of evaluators and the perception of social skills

Summary In two role-playing scenarios, we investigate how White male and female evaluators perceive an Asian American versus White job candidate on the dimensions of competence and social skills and how these perceptions affect evaluators' decisions in hiring and promotion. Specifically, Study 1 examines how the perceptions of competence and social skills affect Asian (versus White) college graduates' chance of obtaining a non-technical (versus technical) position, and Study 2 tests how these perceptions affect Asians' probability of promotion relative to Whites'. Our findings suggest that female evaluators were less likely to select Asian than White candidates into positions involving social skills and were less likely to promote Asian than White candidates into these types of positions. Furthermore, female evaluators' perception that Asians were less socially skilled than Whites mediated both of these decisions. This paper contributes to the understanding of workplace discrimination of Asian Americans. Copyright © 2012 John Wiley & Sons, Ltd.
Familiarity, Legitimation, and Frequency: The Influence of Others on the Criminal Self-view*

From an identity theory perspective, reflected appraisals from others are relevant for social behavior, because behavior is motivated by the desire to achieve congruence between reflected appraisals and the self-view for a particular identity. This study extends prior identity theory work from the laboratory setting by examining identity processes with respect to the criminal identity in the unique “natural” setting of a total institution. The findings build on prior work which finds that reflected appraisals do have an influence on identities and behavior by demonstrating that the relationship one has to the source of reflected appraisals is important for the way in which reflected appraisals influence the criminal self-view for an incarcerated population.
Influence of estradiol on apparent phosphatidyl choline synthesis in rats

SUMMARY Oophorcctomized Sprague-Dawley rats, 28 to 30 days old, were maintained for 31 days on either a normal diet or a high fat, low protein, low choline diet, with or without vitamin BIZ. Twice weekly injections of sesame oil or estradiol in sesame oil were administered subcutaneously. The animals kept on the high fat, low choline diet showed severe fatty metamorphosis of the liver, a decreased hepatic lecithin concentration, and a twofold increase in the relative specific activity of lecithin. Estradiol inhibited fatty metamorphosis and increased the lecithin concentration slightly. The animals receiving a vitamin Blrsupplemented diet and estradiol showed the greatest lipotropic effect and an increased liver lecithin concentration. Estradiol alone, or combined with vitamin B,?, did not correct the apparent choline deficiency, as meaaued by the abnormally high rate of P32 incorporation into lecithin. The results suggest, therefore, that the prevention of fatty livers by estradiol depends on mechanisms other than those involved in the lipotropic properties of choline or vitamin B12.