cssi/SciSciGPT-SciSciNet huggingface dataset:
Using simulation to improve semiconductor factory cycle time by segregation of preventive maintenance activities

Semiconductor manufacturing is a very costly and time-consuming process and any reduction in cycle time (CT) can result in a significant cost saving due to shorter time-to-market, reduced inventory and improved yield. This paper examines the topic of PM (Preventative Maintenance) segregation where the goal is to determine the optimum PM frequency that results in reduced fab CT. Much of the literature on this topic limits the scope of the study to CT performance of an individual toolset, without examining the wider impact on overall fab CT. The goal of this paper is to examine the fab-wide impact of PM segregation projects and reveal critical factors that will allow to identify toolsets with the most potential to improve overall fab CT by splitting PMs. Each toolset identified using these factors may improve fab CT by 1% or more, resulting in a very significant gain, if applied on multiple toolsets.
Modified EDSS for Use in Multiple Sclerosis Clinical Practice (P2.133)

Objective: To develop a modified version of the EDSS (mEDSS) and compare this modified version to the full EDSS. Background: The Expanded Disability Status Scale (EDSS) is the standard research measure of disability in multiple sclerosis (MS). Limitations for clinical use include time required for administration, scoring complexity, and technique redundancy. If simplified, the EDSS would provide a valuable numerical rating to monitor disease progression and treatment response in the clinical setting. Methods: Consensus among 3 MS specialists was reached for a more concise EDSS, reflecting exam techniques utilized for clinical monitoring. A retrospective chart review was used to collect EDSS scoring information, and the mEDSS was derived from these data. The two scores were compared using Spearman’s rank correlation coefficients and Bland-Altman plots. Reasons for discordant scores were delineated. Results: The mEDSS was derived from the EDSS for 102 patients (64.7[percnt] female), representing all subtypes of MS (65.7[percnt] RRMS, 13.7[percnt] PPMS, and 20.6[percnt] SPMS). The mEDSS had strong correlation with the EDSS, both overall (Spearman’s rho = 0.99 (95[percnt] CI 0.94 to 0.97, p<0.001)) and for each functional system (Spearman’s rho between 0.92 and 0.99, p-values <0.001). Correlations were consistent across the spectrum of EDSS values (ranging from 1.5 to 8.5). Longitudinal assessment of the mEDSS for stability and relapse sensitivity is in progress. Conclusions: The mEDSS was strongly correlated with the full EDSS and can therefore provide a useful rating for disability in clinical practice. Additionally, in our practice, this mEDSS can be performed in 5 minutes, an appealing attribute for a clinical assessment tool. Future work will examine the practicality and interrater reliability of the mEDSS. Disclosure: Dr. Baldassari has nothing to disclose. Dr. Longbrake has received personal compensation for activities with Genzyme. Dr. Cross has received personal compensation for activities with Biogen Idec, Genzyme Corporation, GlaxoSmithKline, Inc., Hoffman-La Roche, Teva Neuroscience, Novartis, and Questcor. Dr. Salter has received personal compensation for consulting services. Dr. Salter has received research support. Dr. Naismith received personal compensation for activities with Alkermes, Acorda, Bayer, Biogen Idec, Genentech Inc., Genzyme Corporation, EMD Serono, Novartis, and Questcor as a consultant and from Acorda Therapeutics and Genzyme Corporation as a speaker
Automated annotation and classification of BI-RADS assessment from radiology reports

Display Omitted We developed an NLP system to extract all BI-RADS categories from breast radiology reports.We evaluate the results of existing of an NLP system using a multi-step approach.ML classifiers can detect and assign laterality to all BI-RADS categories in a single report. The Breast Imaging Reporting and Data System (BI-RADS) was developed to reduce variation in the descriptions of findings. Manual analysis of breast radiology report data is challenging but is necessary for clinical and healthcare quality assurance activities.The objective of this study is to develop a natural language processing (NLP) system for automated BI-RADS categories extraction from breast radiology reports. We evaluated an existing rule-based NLP algorithm, and then we developed and evaluated our own method using a supervised machine learning approach. We divided the BI-RADS category extraction task into two specific tasks: (1) annotation of all BI-RADS category values within a report, (2) classification of the laterality of each BI-RADS category value. We used one algorithm for task 1 and evaluated three algorithms for task 2. Across all evaluations and model training, we used a total of 2159 radiology reports from 18 hospitals, from 2003 to 2015.Performance with the existing rule-based algorithm was not satisfactory. Conditional random fields showed a high performance for task 1 with an F-1 measure of 0.95. Rules from partial decision trees (PART) algorithm showed the best performance across classes for task 2 with a weighted F-1 measure of 0.91 for BIRADS 0-6, and 0.93 for BIRADS 3-5. Classification performance by class showed that performance improved for all classes from Nave Bayes to Support Vector Machine (SVM), and also from SVM to PART.Our system is able to annotate and classify all BI-RADS mentions present in a single radiology report and can serve as the foundation for future studies that will leverage automated BI-RADS annotation, to provide feedback to radiologists as part of a learning health system loop.
Multilevel Interactionist Perspective of Field-Based Learning – Performance Relations

US organizations continue to spend considerable funds on formal training and development programs, despite estimates that it accounts for as little as 25% of the learning that actually occurs in th...
Abstract 4781: Epigenetic regulation of neuroblastoma tumorigenicity through MLL1 and JMJD3 modulation in cancer stem cells

Introduction: Increasing evidence suggest that epigenetic regulators play a critical role in cancer cell heterogeneity and in maintaining tumor sub-populations with enhanced tumor-initiating and drug-resistant capacities. Recently, we discovered a drug-resistant, highly tumorigenic, self-renewing cell sub-population with features of cancer stem cells (CSCs) in pediatric neuroblastoma (NB). This sub-population, characterized by surface expression of G-CSF receptor (CD114), can escape initial therapy and cause refractory and aggressively invasive relapsed disease. Recently, we found that the CSF3R gene that code for CD114 is expressed specifically in CD114+ sub-population ( Methods: Chromatin immunoprecipitation (ChIP)-qPCR for the histone marks H3K4me3 and H3K27me3 was performed in sorted NB sub-populations. Pathway qPCR arrays and orthotopic xenografts mouse model were used to determine the effects of epigenetic inhibitors in vitro and in vivo. Results: We found that the epigenetic regulators mixed-lineage leukemia-1 (MLL1; KMT2A; a H3K4me3 methyltransferase) and Jumonji D3 (JMJD3; KDM6B; a H3K27me3 demethylase) are overexpressed in CD114+ NB cells. These regulators maintain a reversible epigenetic switch of high H3K4me3 and low H3K27me3 histone marks at the CSF3R locus in CD114+ cells for active transcription. Targeting these epigenetic regulators with specific small-molecule inhibitors MM-102 (inhibit MLL1) and GSK-J4 (inhibit JMJD3) in NB, reverses the histone patterns at CSF3R promoter locus and block gene expression, induces apoptosis selectively in CD114+ cells, and inhibits overall NB proliferation in vitro. These inhibitors also inhibit the expression of cancer stem cell specific genes as determined by pathway arrays. Inhibiting MLL1 and JMJD3 in NB orthotopic xenografts significantly decreases tumor size (p Conclusion: Overall, we demonstrate that epigenetic regulators MLL1 and JMJD3 regulate the expression of critical genes and maintain NB CSC sub-population. Targeting these epigenetic regulators reduce NB tumorigenicity, metastasis and increase drug sensitivity. Further developing these strategies will pave the way for incorporating epigenetic inhibitors in current therapies for effectivity improving long-term cure rates. Citation Format: Saurabh Agarwal, Zaowen Chen, Julie A. Tomolonis, Sanjeev A. Vasudevan, Jason M. Shohet. Epigenetic regulation of neuroblastoma tumorigenicity through MLL1 and JMJD3 modulation in cancer stem cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4781. doi:10.1158/1538-7445.AM2017-4781
Aldoxorubicin for the treatment of soft tissue sarcoma

Intoduction: Soft tissue sarcomas (STS) encompass a group of rare tumors arising from mesenchymal tissue. Traditionally, anthracycline-based chemotherapy, with doxorubicin, is the main treatment for advanced STS. Areas covered: Aldoxorubicin is a doxorubicin derivative containing a carboxylic hydrazone and serves as a prodrug of doxorubicin. It covalently binds to albumin in the blood until reaching the acidic tumor environment, which dissolves the hydrazone linker, thus releasing doxorubicin into the tissue. In this review paper, we analyze the pharmacokinetics, current phase I, phase II, and phase III trials, as well as adverse effect profile of aldoxorubicin in patients with advanced STS. Expert opinion: Aldoxorubicin represents a promising drug for treatment of sarcomas. The drug has minimal cardiac toxicity, which represents a significant advantage to doxorubicin. Preliminary phase 3 study results demonstrate PFS advantage in patients with leiomyosarcoma and liposarcoma. However, more studies are needed to establish the role of aldoxorubicin in sarcoma treatment.
Hydraulic Fracturing: A Review of Implications for Food Systems Planning

Food system and energy planners have given scant attention to the impacts on agrifood systems of a particular form of energy production—fracking—and its implications for planning and regulation. Im...
Pathology of Prostate Cancer

Although molecular pathology is a fast-growing and important area in the world of prostate cancer, the diagnosis of prostate cancer still requires histologic confirmation, and the foundation for virtually all treatment and research is still based on the tumor’s histomorphology. This chapter focuses on the pathology of prostate cancer, beginning with the diagnostic features of prostate cancer under the microscope. We also discuss the Gleason grading system as well as the newly adopted Grade Groups, which are prognostic groups that incorporate the modifications made to the Gleason system over the decades, provide a more meaningful framework for research, and allow for better patient understanding of their disease. The more common and clinically significant histologic variants of acinar and non-acinar prostate cancer are also reviewed, and applications of immunohistochemistry in prostate cancer diagnosis are also discussed. Treatment-related changes, such as those following radiation or hormone therapy, are examined as these can drastically change the morphology of the tumor as well as provide prognostic information. Finally, key aspects related to pathologic specimens, including their handling and the reporting of prostate cancer therein, are reviewed.
RASSF1A deficiency enhances RAS driven lung tumorigenesis

Mutant K-RAS has been shown to have both tumor-promoting and -suppressing functions, and growing evidence suggests that the RASSF family of tumor suppressors can act as RAS apoptosis and senescence effectors. It has been hypothesized that inactivation of the RASSF1A tumor suppressor facilitates K-RAS-mediated transformation by uncoupling it from apoptotic pathways such as the Hippo pathway. In human lung tumors, combined activation of K-RAS and inactivation of RASSF1A is closely associated with the development of the most aggressive and worst prognosis tumors. Here, we describe the first transgenic mouse model for activation of K-RAS in the lung in a RASSF1A-defective background. RASSF1A deficiency profoundly enhanced the development of K-RAS-driven lung tumors in vivo Analysis of these tumors showed loss of RASSF1A-uncoupled RAS from the proapoptotic Hippo pathway as expected. We also observed an upregulation of AKT and RALGEF signaling in the RASSF1A- tumors. Heterozygosity of RASSF1A alone mimicked many of the effects of RAS activation on mitogenic signaling in lung tissue, yet no tumors developed, indicating that nonstandard Ras signaling pathways may be playing a key role in tumor formation in vivo In addition, we observed a marked increase in inflammation and IL6 production in RASSF1A-deficient tumors. Thus, RASSF1A loss profoundly affects RAS-driven lung tumorigenesis and mitogenic signaling in vivo Deregulation of inflammatory pathways due to loss of RASSF1A may be essential for RAS-mediated tumorigenesis. These results may have considerable ramifications for future targeted therapy against RAS+/RASSF1A- tumors.Significance: A transgenic mouse model shows that suppression of RASSF1A dramatically enhances Ras-driven tumorigenesis and alters Ras signaling pathway activity.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/10/2614/F1.large.jpg Cancer Res; 78(10); 2614-23. ©2018 AACR.
Los avatares del deseo y la cuestión de la presencia: Los espacios virtual y transicional encuentran su borde liminal. De Pigmalión a Ella, de Spike Jonze, y más allá …

(2016). Los avatares del deseo y la cuestion de la presencia: Los espacios virtual y transicional encuentran su borde liminal. De Pigmalion a Ella, de Spike Jonze, y mas alla … The International Journal of Psychoanalysis (en espanol): Vol. 2, No. 6, pp. 1716-1727.
Omniscience and Knowledge De Se Et De Praesenti

In class as well as over coffee, hence on blackboards and on napkins, Ed Gettier is always exceptionally clear and insightful on matters of scope, reference, and indexicality. Thus, as a former student of Ed’s, I am delighted that my discussion of some aspects of these topics as they arise in connection with the concept of omniscience appears in a volume in his honor.
ALTERATIONS IN NUTRITIONAL AND METABOLIC PATTERNS OF TETRAHYMENA DURING FACULTATIVE PARASITISM

Publisher Summary This chapter discusses the alterations in nutritional and metabolic patterns of tetrahymena during facultative parasitism. Studies were carried out of the incorporation of C14-l-leucine into both free-living and roach-recovered ciliates. Proteose peptone-yeast extract cultures of both free-living and roach-recovered cells were washed, concentrated, and incubated for 1 h. With C14-l-leucine under various conditions; in water, in an amino acid mixture, a purine and pyrimidine mixture, a mixture of inorganic salts, a vitamin mixture, and a complete medium. When amino acids were included in the mixtures, unlabeled leucine was omitted to avoid radioactive dilution effects. In the various mixtures, the total incorporation into the cold trichloracetic acid-insoluble fraction was measured. The fractions were further subdivided into their protein, DNA, and RNA components by the Schmidt–Thannhauser procedure.
Risk of dementia after TBI — a cause of growing concern

Moderate and severe traumatic brain injuries (TBIs) have long been recognized as risk factors for dementia, but the relationship between mild TBI (mTBI) and dementia is unclear. New research demonstrates that even an mTBI without loss of consciousness is associated with a twofold increase in the risk of dementia.
Implementation and Shared Governance in the US Intergovernmental System: Lessons from the American Recovery and Reinvestment Act

Today, in many areas of public policy, the U.S. federal government does little by itself. Instead, federal officials rely heavily on complex networks of state and local governments and nonprofit and business organizations to help implement federal programs. Unfortunately, our understanding of this new system of shared governance has not kept pace with developments on the ground. Our evolving knowledge has so far stopped short of providing policy makers, managers, or citizens with the information or knowledge they need to navigate in this new system of federal governance. This paper draws upon findings from a research project studying implementation of the 2009 economic stimulus program or Recovery Act to identify network governance and management principles for federal policy makers and managers. The American Recovery and Reinvestment Act (ARRA), with $787 billion in federal spending and tax provisions, provides an excellent window into our system of shared governance. Under the stimulus law, the federal government worked with network partners in state and local governments, businesses, nonprofit organizations, and other institutions to put Americans back to work and to advance federal priorities in education, energy, telecommunications, assistance to low-income families, and other areas. Given the strains of the economic downturn, the rapid decline of tax revenues, and short timeframes for implementation, this constituted a form of “stress test” for the system of intergovernmental and networked governance which can be used to reveal important patterns of behavior by key participants across a broad range of policy domains. Specifically, this paper reports findings drawn from seven case studies of ARRA programs and accountability networks. The findings of the seven cases are summarized and overarching “lessons learned” are synthesized below. The research was designed with both the academic and policy communities in mind. On a theoretical level, the analysis contributes to the growing body of work on networked governance and intergovernmental policy implementation in the United States. Research findings will also help policymakers fine-tune existing programs and develop future policy initiatives informed by a better understanding of the realities of shared governance. Ultimately, the research effort is designed to yield practical guidance for public managers in the shared governance environment. Consequently, our findings suggest a number of observations about what sets the ARRA experience apart from the “tools of government” focused research and raises a series of propositions about the role of networks in the implementation of the Act. We also offer some analysis of the unique roles played by the Recovery Accountability and Transparency Board, OMB, the White House ARRA Office, and the Vice President. Draft -- Please do not quote or cite without permission of the authors.
Will my child do better if she enrolls in a clinical trial

The question of whether children with cancer who enroll in clinical trials have superior outcomes compared with those who do not participate has been pursued for more than 4 decades, and recent studies have provided conflicting answers. Whether clinical trial participation influences outcome has important implications for how clinicians should present trial participation to patients and families. Methodological challenges limit generalizations about the impact of clinical trial participation on outcome compared with nonparticipation. Oncologists should inform patients and families that clinical trials are the engine for future progress because they identify more effective therapies and that clinical trial participation is a reasonable option to consider for children with cancer. However, as noted in by Truong and colleagues in this issue, the rationale for trial enrollment should not include an expectation of better outcomes compared with nonenrollment.
Embedded landscapes

In this paper we introduce embedded landscapes as an extension of NK landscapes and MAXSAT problems. This extension is valid for problems where the representation can be expressed as a simple sum of subfunctions over subsets of the representation domain. This encompasses many additive constraint problems and problems expressed as the interaction of subcomponents, where the critical features of the subcomponents are represented by subsets of bits in the domain. We show that embedded landscapes of fixed maximum epistasis K are exponentially sparse in epistatic space with respect to all possible functions. We show we can compute many important statistical features of these functions in polynomial time including all the epistatic interactions and the statistical moments of hyperplanes about the function mean and hyperplane mean. We also show that embedded landscapes of even small fixed K can be NP-complete. We can conclude that knowing the epistasis and many of the hyperplane statistics is not enough to solve the exponentially difficult part of these general problems and that the difficulty of the problem lies not in the epistasis itself but in the interaction of the epistatic parts.
The Eucharist and the Church in the Thought of Henri De Lubac and Rowan Williams: Sacramental Ecclesiology and the Place of the Church in the World:

Henri de Lubac and Rowan Williams have, in different ways, insisted upon the bond between the eucharist and the church. For both theologians, the eucharist is not simply the product of the ecclesia...
Dosimetric Factors Related to Radiation Necrosis After 5-Fraction Radiosurgery for Patients With Resected Brain Metastases.

Abstract Purpose Stereotactic radiosurgery (SRS) is increasingly used in the management of patients with resected brain metastases (rBMs). A significant complication of this therapy can be radiation necrosis (RN). Despite radiation therapy dose de-escalation and the delivery of several rather than a single dose fraction, rates of RN after SRS for rBMs remain high. We evaluated the dosimetric parameters associated with radiographic RN for rBMs. Methods and Materials From 2008 to 2016, 55 rBMs at a single institution that were treated postoperatively with 5-fraction linear accelerator–based SRS (25-35 Gy) with minimum 3 months follow-up were evaluated. For each lesion, variables recorded included radiation therapy dose to normal brain, location and magnitude of hotspots, clinical target volume (CTV), and margin size. Hotspot location was stratified as within the tumor bed alone (CTV) or within the planning target volume (PTV) expansion margin volume (PTV minus CTV). Cumulative incidence with competing risks was used to estimate rates of RN and local recurrence. Optimal cut-points predicting for RN for hotspot magnitude based on location were identified via maximization of the log-rank test statistic. Results Median age for all patients was 58.5 years. For all targets, the median CTV was 17.53 cm3, the median expansion margin to PTV was 2 mm, and the median max hotspot was 111%. At 1 year, cumulative incidence of radiographic RN was 18.2%. Univariate analysis showed that max hotspots with a hazard ratio of 3.28 (P = .045), hotspots within the PTV expansion margin with relative magnitudes of 105%, 110%, and 111%, and an absolute dose of 33.5 Gy predicted for RN (P = .029, P = .04, P = .038, and P = .0488, respectively), but hotspots within the CTV did not. Conclusions To our knowledge, this is the first study that investigated dosimetric factors that predict for RN after 5-fraction hypofractionated SRS for rBM. Hotspot location and magnitude appear important for predicting RN risk, thus these parameters should be carefully considered during treatment planning.
Method for Characterizing Electric Current Effects on the Deformation of Metals

Traditional metal forming requires large forces and substantial tooling, high power, and large amounts of energy. Passing an electric current through the metal during forming has been shown to reduce the deformation energy and increase the materials’ formability, leading to the possibility of increased formed-shape complexity. The primary challenge in characterizing electric current effects on plastic deformation has been decoupling the current and intrinsic Joule heating effects. Many of the experiments reported in the literature have specimen geometry and fixturing features that can lead to concentrations of stress, deformation, current, and/or temperature. The presence of one or more localized field concentrations in the specimen gage length can bias the observed deformation behavior and lead to erroneous conclusions. In this work, we addressed this challenge by conducting independent electro- and thermo-mechanical experiments for the current- and temperature-controlled characterizations, respectively. For the former, a novel cylindrical tensile specimen and grip design were developed to enable larger current densities with uniform deformations, currents, and temperature conditions in the gage section. Forced-air convection with vortex tube cooling was used to maintain uniform temperature conditions within the gage section. Non-contact video strain and infrared temperature measurements were employed, and test control and data acquisition were computer automated. A laboratory materials test system with an environmental chamber was used for tensile testing the cylindrical specimens under near-identical temperature histories as the applied current tests. These techniques were used to characterize the electro-deformation behavior of several pure metals, i.e., copper, iron, and titanium. The results convincingly demonstrated an electric current effect on the plastic deformation behavior of the titanium but not the copper and iron. Details of the experiments and methodology are described and discussed along with candidate mechanisms for current effects on the plastic deformation behavior of the titanium.
Understanding Religious Experience: From Conviction to Life's Meaning

In this book, Paul K. Moser offers a new approach to religious experience and the kind of evidence it provides. Here, he explains the nature of theistic and non-theistic experience in relation to the meaning of human life and its underlying evidence, with special attention given to the perspectives of Tolstoy, Buddha, Confucius, Krishna, Moses, the apostle Paul, and Muhammad. Among the many topics explored in this timely volume are: religious experience characterized in a unifying conception; religious experience naturalized relative to science; religious experience psychologized in merely psychological phenomena; and religious experience cognized relative to potential defeaters from evil, divine hiddenness, and religious diversity. Understanding Religious Experience will benefit those interested in the nature of religion and can be used in relevant courses in religious studies, philosophy, theology, Biblical studies, and the history of religion.
Anionic speciation in sodium and potassium silicate glasses near the metasilicate ([Na,K]2SiO3) composition: 29Si, 17O, and 23Na MAS NMR

Abstract Alkali silicate glasses near to the metasilicate composition provide sensitive tests of anionic speciation. However, reports on 29Si NMR data vary considerably in their derived proportions of silicate species. In some cases, an apparent deficit in the content of non-bridging oxygen has been attributed to up to 5 to 10% “free” oxide ions. Here we provide new NMR data on a series of sodium silicate glasses ranging from 56 to 45 mol% silica with accurately analyzed compositions. High signal-to-noise data for a 29Si-enriched glass provide improved constraints on fitting models for spectra, and suggests a slight asymmetry in the main Q2 component. Data are consistent with conventional models in which “free” oxide contents are below detection limits of about 0.5 to 1%. Spectra for an 17O-enriched K-silicate glass with about 53% silica confirm that there is no obvious direct signature for “free” oxide species in this compositional range.
Chapter 13 – Cytokines and Bone Remodeling

Publisher Summary Bone is continuously remodeled in normal individuals and this is achieved via a finely regulated balance between the processes of bone formation and resorption mediated by osteoblasts and osteoclasts, respectively. This bone remodeling is regulated, in part, by local factors including cytokines generated in the bone microenvironment. The purpose of this chapter is to summarize what is currently known about the role of cytokines and their receptors in bone remodeling. Recent advances in molecular biological techniques have meant that most of the biological activities ascribed to cytokines have now been associated with specific molecules, and their receptors identified and molecularly cloned. Several cytokines and their cognate receptors have been shown to be expressed by bone cells, marrow cells, or accessory cells in the bone microenvironment. Moreover, studies using knockout and transgenic mice have increased the understanding of the complex signal transduction mechanisms utilized by cytokines and are opening up new and exciting areas of study. Cytokines tend to be pleiotropic and multifactorial, and may have overlapping and seemingly redundant biological effects. Some of this redundancy is apparent in the receptor mechanisms and signal transduction pathways used by groups of cytokines. Classic examples that illustrate this vividly are the various cytokines belonging to the interleukin (IL)-6 family, such as IL-6, leukemia inhibitory factor, oncostatin-M, and IL-11, which utilize a common signal transduction protein known as gp130. These cytokines bind to distinct membrane-associated receptors, which form hetero- or homo-dimers upon binding to the ligand. Further, there is now a body of data derived from in vivo studies in animals which show that over- or under-production of certain cytokines cause profound effects on bone. These fundamental observations have the potential of not only increasing the understanding of the pathophysiology of osteoporosis, but also leading to new and better forms of therapy using these molecules as targets for drug discovery programs.
In situ liquid SEM imaging analysis revealing particle dispersity in aqueous solutions

A quantitative description on dispersity of boehmite (γ-AlOOH) particles, a key component for waste slurry at Hanford sites, can provide useful knowledge for understanding various physicochemical nature of the waste. In situ liquid scanning electron microscopy (SEM) was used to evaluate the dispersity of particles in aqueous conditions using a microfluidic sample holder, System for Analysis at Liquid Vacuum Interface (SALVI). Secondary electron (SE) images and image analyses were performed to determine particle centroid locations and the distance to the nearest neighbour particle centroid, providing reliable rescaled interparticle distances as a function of ionic strength in acidic and basic conditions. Our finding of the particle dispersity is consistent with physical insights from corresponding particle interactions under physicochemical conditions, demonstrating delicate changes in dispersity of boehmite particles based on novel in situ liquid SEM imaging and analysis. LAY DESCRIPTION: In situ liquid scanning electron microscopy (SEM) was used to determine the interparticle distance of boehmite (γ-AlOOH) particles, a key component for waste slurry at Hanford sites. This type of quantitative measurement is important to understand various physicochemical nature of the radiological waste containing boehmite. In situ liquid SEM was enabled by a unique vacuum compatible microfluidic cell, System for Analysis at Liquid Vacuum Interface (SALVI). We collected secondary electron (SE) images and performed image analyses to determine particle centroid locations and the distance to the nearest neighbour particle centroid to arrive at the interparticle distances in acidic and basic conditions. Our results show that delicate changes occur among boehmite particles under different pH conditions using novel in situ SEM imaging.
Meta-analysis Exploring Sinopulmonary Outcomes of Aspirin Desensitization in Aspirin-Exacerbated Respiratory Disease:

ObjectiveThe objective of this study is to explore the sinopulmonary outcomes of aspirin desensitization through a systematic review and meta-analysis.Data SourcesEmbase and OVID Medline databases....
Submitting Images for Publication

Photography plays an important role in medicine. Photographs allow the physician to document clinical findings, evaluate the results of treatment, and keep a visual record of the patient’s medical history. Photographs may act as a substitute for lengthy descriptions and imprecise drawings in medical literature, allowing the reader to view objective findings with their own eyes. In the Internet era, the process of submitting images for publication is much easier than it was in the past. Virtually all journals have online submission portals for manuscripts and any relevant additional information, including images.
Imaging Appearance of Ballistic Wounds Predicts Bullet Composition: Implications for MRI Safety

OBJECTIVE. The purpose of this article was to determine whether the radiographic and CT appearance of ballistic projectiles predicts their composition and to characterize the translational, rotational, and temperature effects of a 1.5-T MRI magnetic field on representative bullets. MATERIALS AND METHODS. Commercially available handgun and shotgun ammunition representing projectiles commonly encountered in a clinical setting was fired into ballistic gelatin as a surrogate for human tissue, and radiographs and CT images of these gelatin blocks were obtained. MR images of unfired bullets suspended in gelatin blocks were also obtained using T1- and T2-weighted sequences. Magnetic attractive force, rotational torque, and heating effects of unfired bullets were assessed at 1.5 T. RESULTS. Fired bullets were separated into ferromagnetic and nonferromagnetic groups based on the presence of a debris trail and deformation of the primary projectile in the gelatin blocks. Whereas ferromagnetic bullets showed mild torque forces and marked imaging artifacts at 1.5 T, nonferromagnetic bullets did not have these effects. Heating above the Food and Drug Administration limit of 2°C was not observed in any of the projectiles tested. CONCLUSION. Patients with ballistic embedded fragments are frequently denied MRI because the bullet composition cannot be determined without shell casings. We found that radiography and CT can be used to identify nonferromagnetic projectiles that are safe for MRI. We also present an algorithm for determining the triage of patients with retained bullets.
Transition kernel couplings of the Metropolis-Hastings algorithm

Couplings play a central role in the analysis of Markov chain convergence to stationarity and in the construction of novel Markov chain Monte Carlo diagnostics, estimators, and variance reduction techniques. The quality of the resulting bounds or methods typically depends on how quickly the coupling induces meeting between chains, a property sometimes referred to as its efficiency. The design of efficient Markovian couplings remains a difficult open question, especially for discrete time processes. In pursuit of this goal, in this paper we fully characterize the couplings of the Metropolis--Hastings (MH) transition kernel, providing necessary and sufficient conditions in terms of the underlying proposal and acceptance distributions. We apply these results to characterize the set of maximal couplings of the MH kernel, resolving open questions posed in O'Leary et al. [2020] on the structure and properties of these couplings. These results represent an advance in the understanding of the MH kernel and a step toward the formulation of efficient couplings for this popular family of algorithms.
Machine Learning and Advanced Statistical Modeling Can Identify Key Quality Management Practices That Affect Postpasteurization Contamination of Fluid Milk.

ABSTRACT Spoilage of high-temperature, short-time (HTST)- and vat-pasteurized fluid milk due to the introduction of gram-negative bacteria postpasteurization remains a challenge for the dairy industry. Although processing facility-level practices (e.g., sanitation practices) are known to impact the frequency of postpasteurization contamination (PPC), the relative importance of different practices is not well defined, thereby affecting the ability of facilities to select intervention targets that reduce PPC and provide the greatest return on investment. Thus, the goal of this study was to use an existing longitudinal data set of bacterial spoilage indicators obtained for pasteurized fluid milk samples collected from 23 processing facilities between July 2015 and November 2017 (with three to five samplings per facility) and data from a survey on fluid milk quality management practices, to identify factors associated with PPC and rank their relative importance. This ranking was accomplished using two separate approaches: multimodel inference and conditional random forest. Data preprocessing for multimodel inference analysis showed (i) nearly all factors were significantly associated with PPC when assessed individually using univariable logistic regression and (ii) numerous pairs of factors were strongly associated with each other (Cramer's V ≥ 0.80). Multimodel inference and conditional random forest analyses identified similar drivers associated with PPC; factors identified as most important based on these analyses included cleaning and sanitation practices, activities related to good manufacturing practices, container type (a proxy for different filling equipment), in-house finished product testing, and designation of a quality department, indicating potential targets for reducing PPC. In addition, this study illustrates how machine learning approaches can be used with highly correlated and unbalanced data, as typical for food safety and quality, to facilitate improved data analyses and decision making. HIGHLIGHTS
Does the Meeting Style Matter? The Effects of Exposure to Participatory and Deliberative School Board Meetings

Would public meetings incite more civic engagement if they were structured in ways that are simply more engaging? I addressed this question by conducting an original survey with an oversample of racial and ethnic minorities and individuals from low-income households. The survey featured a randomized experiment in which each study participant was shown a short clip of an actual school board meeting that was (1) a standard meeting with no public participation, (2) a meeting with public participation, or (3) a meeting with deliberation (public participation followed by a reasoned response from the school board). The experience of viewing the more participatory and deliberative school board meetings led to increased trust in local officials and a stronger willingness to attend school board meetings in the future. This study has significant implications for civic engagement, local politics, and public school governance.
Evaluating Digital Instructional Materials for K-12 Online and Blended Learning

With the large increase in online instruction, including remote instruction with online materials during the COVID-19 pandemic, there also was an increase in the use of instructional materials that were made to be displayed online or were digitized for online use. However, teachers have not had access to guidance about how to select and evaluate online instructional materials for classroom use. The lack of guidance has the potential to harm historically excluded populations of students and could frustrate teachers as they learn to teach with digital materials. The purpose of this paper is to share the 4A Framework for evaluating online instructional materials. The framework is organized around the premise that quality online instructional materials are accessible, promote active engagement, advocate for inclusion, and are accountable for their relationships to standards and data privacy. Each feature is discussed and examples of teacher work in applying the framework are shared.
Epigenetics of Personalized Medicine

Interindividual variability in epigenetic processes is often formed through environmental influences that shape the epigenome, and these epigenetic signatures can be translated to assist disease prevention or therapy. Since epigenetic aberrations often span across the genome, analysis of the epigenome through computational epigenetics has gained increasing attention as a means to identify key epigenetic changes that allow diseases to form and progress. Many medical conditions have an epigenetic basis and are therefore amenable to management through personalized epigenetic analyses. Drug development, responses to changes in nutrition, toxicity, and forensics also have high potential for analysis of epigenetic signatures. It is apparent that personalized epigenetics is on the horizon of advances that could significantly improve the management of many disorders and diseases that are currently presenting persistent challenges to more conventional approaches to medicine.
Laboratory validation of a sparse aperture image quality model

The majority of image quality studies in the field of remote sensing have been performed on systems with conventional aperture functions. These systems have well-understood image quality tradeoffs, characterized by the General Image Quality Equation (GIQE). Advanced, next-generation imaging systems present challenges to both post-processing and image quality prediction. Examples include sparse apertures, synthetic apertures, coded apertures and phase elements. As a result of the non-conventional point spread functions of these systems, post-processing becomes a critical step in the imaging process and artifacts arise that are more complicated than simple edge overshoot. Previous research at the Rochester Institute of Technology's Digital Imaging and Remote Sensing Laboratory has resulted in a modeling methodology for sparse and segmented aperture systems, the validation of which will be the focus of this work. This methodology has predicted some unique post-processing artifacts that arise when a sparse aperture system with wavefront error is used over a large (panchromatic) spectral bandpass. Since these artifacts are unique to sparse aperture systems, they have not yet been observed in any real-world data. In this work, a laboratory setup and initial results for a model validation study will be described. Initial results will focus on the validation of spatial frequency response predictions and verification of post-processing artifacts. The goal of this study is to validate the artifact and spatial frequency response predictions of this model. This will allow model predictions to be used in image quality studies, such as aperture design optimization, and the signal-to-noise vs. post-processing artifact tradeoff resulting from choosing a panchromatic vs. multispectral system.
The Limits of Omniscience

In their discussion of the phrase 1in077rn M7 "t-l in Amos 4:13, F. I. Andersen and David Noel Freedman explain that the verse means not that God can tell what a human being is thinking' but that God sometimes tells his own innermost thoughts to certain individuals.2 Thus, the verse is not meant to indicate that God can "read" one's mind. After all, say Andersen and Freedman, that is obvious in any case. But is it? What I wish to suggest here is that, as in so many other instances, on this question the Hebrew Bible is of two minds. It includes texts which presuppose the notion that God has direct access to what human beings are thinking and other texts which presuppose that God does not know directly what goes on in the human mind.3 As Andersen and Freedman's comment demonstrates, the notion that the biblical God can read minds is one with which most scholars today would automatically agree.4 Let me begin, then, by discussing
Report of an additional case of puerperal septicemia due to infection by clostridium welchii

F OUR years ago, in conjunction with Dr. I. D. Michelson, I reported a case of puerperal gas bacillus infection, with an extended review of previous publications on the same subject. I wish now to present another case occurring in my service, and to examine the literature which has appeared since my earlier paper was published. As the ground was quite thoroughly covered in the earlier paper, it will be nec’essary at this time only to summarize very briefly the history of this complication of the puerperium, as those interested can refer to that paper and the authors listed in the bibliography attached to’ it.
A Missile Control Strategy for Maneuvering Targets

This paper first analyzes and discusses some missile target tracking algorithms. A general formulation of the optimal guidance law using linear state models is then presented for a bank-to-turn missile.
How should we measure chunks? a continuing issue in chunking research and a way forward.

Generally defined, chunking is a process through which one reorganizes or groups presented information to compress information; it is one of the best-known methods of increasing the amount of information stored in memory. Chunking can occur by two different means: either through strategic reorganization based on familiarity or prior knowledge, or through grouping based on perceptual characteristics. An example of the former is using knowledge of acronyms to break a string of letters (e.g., AWOLNASAMIA) into smaller, separate groups (i.e., AWOL, NASA, MIA). In the case of the latter, more common with visual stimuli, one can form groups on the basis of similarity or proximity. Although both methods are considered part of the general phenomenon of chunking, it is the goal-directed, strategic chunking that is the focus of this piece. Although the process of chunking has been discussed as a mnemonic strategy in William James's Principles of Psychology (1890), it is most widely known through George Miller's paper, “The Magical Number Seven, Plus or Minus Two.” Miller (1956) primarily reviewed several studies that examined capacity limits in immediate recall; across various types of stimuli, a consistent recall limit of between five and nine items was observed. As a secondary emphasis, Miller also discussed recoding and subsequent implications on estimates of immediate memory capacity. Miller observed that if information was recoded into meaningful units (called chunks), this increased the amount of information that could be recalled, and thereby increased immediate memory span. This occurs because increased meaning through chunking or recoding increases the size of each respective chunk (e.g., Tulving and Patkau, 1962; Chase and Simon, 1973; Simon, 1974), but the number of chunks that can be stored in short-term memory remains constant, typically limited to four or fewer items (e.g., Cowan, 2001; Gobet and Clarkson, 2004; Mathy and Feldman, 2012). Despite the fact that Miller published his paper nearly 60 years prior, our understanding of chunking remains incomplete. In particular, though many chunking papers use a variety of methods to measure how chunks are formed and retrieved, it is unclear whether the majority of these methods of measuring chunks accurately reflect the internal cognitive processes that are involved in chunk formation. Before discussing this problem in further detail, I will briefly review well-known methods of measuring chunks and how these methods have been used in previous research (see Gilchrist and Cowan, 2012, for a detailed discussion of chunking and these measurement methods). For present purposes, I will be restricting these measurement methods to those involved in deliberate and goal-directed chunking of verbal materials, as these typically require more effortful processing.
The MICROBE Benchmarking Toolkit for Java: A Component-Based Approach

Java technology has recently been receiving increasing attention as a platform for high performance and large scale scientific computing. The MICROBE benchmarking toolkit is being developed to assist in the accurate evaluation of Java platforms. MICROBE is based on the tenet that benchmarking suites, in addition to furnishing benchmark codes, should provide flexibility in customizing algorithms, instruments, and data interpretation to facilitate more thorough evaluation of virtual environments' performance. The MICROBE architecture, projected usage scenarios, and preliminary experiences are presented in this paper.