Oxidation of cellulose in pressurized carbon dioxide

This work presents first results upon oxidation of type II cellulose by nitrogen dioxide dissolved in carbon dioxide at high pressure. This reaction leads to oxidized cellulose, a natural-based bioresorbable fabric used for biomedical applications. The oxidation reaction takes place in a heterogeneous fluid–solid system. Kinetics of oxidation is presented here and effects of operating conditions such as pressure, temperature and initial moisture content of cellulose are investigated. Results are presented in terms of degree of oxidation of cellulose and quality of the final oxidized cellulose, which has been characterized using liquid-state and solid-state 13C NMR. The experimental results show the existence of possible secondary reactions which may lead to oxidized cellulose with insufficient mechanical strength. An attempt is made to evidence and understand the role of CO2 as a solvent in this system. Indeed, although supercritical CO2 appears to be a suitable candidate as a solvent for oxidation reactions, some inhibiting effect on nitrogen dioxide activity are observed in this case

The Impact of Emotional Intelligence on Conditions of Trust among Leaders at the Kentucky Department for Public Health

There has been limited leadership research on emotional intelligence and trust in governmental public health settings. The purpose of this study was to identify and seek to understand the relationship between trust and elements of emotional intelligence, including stress management, at the Kentucky Department for Public Health (KDPH). The KDPH serves as Kentucky’s state governmental health department. KDPH is led by a Commissioner and composed of seven primary divisions and 25 branches within those divisions. The study was a non-randomized cross-sectional study utilizing electronic surveys that evaluated conditions of trust among staff members and emotional intelligence among supervisors. Pearson correlation coefficients and corresponding p-values are presented to provide the association between emotional intelligence scales and the conditions of trust. Significant positive correlations were observed between supervisors’ stress management and the staff members’ trust or perception of supervisors’ loyalty (r = 0.6, p = 0.01), integrity (r = 0.5, p = 0.03), receptivity (r = 0.6, p = 0.02), promise fulfillment (r = 0.6, p = 0.02), and availability (r= 0.5, p = 0.07). This research lays the foundation for emotional intelligence and trust research and leadership training in other governmental public health settings, such as local, other state, national, or international organizations. This original research provides metrics to assess the public health workforce with attention to organizational management and leadership constructs. The survey tools could be used in other governmental public health settings in order to develop tailored training opportunities related to emotional intelligence and trust organizations

The Impact of Emotional Intelligence on Conditions of Trust among Leaders at the Kentucky Department for Public Health

There has been limited leadership research on emotional intelligence and trust in governmental public health settings. The purpose of this study was to identify and seek to understand the relationship between trust and elements of emotional intelligence, including stress management, at the Kentucky Department for Public Health (KDPH). The KDPH serves as Kentucky’s state governmental health department. KDPH is led by a Commissioner and composed of seven primary divisions and 25 branches within those divisions. The study was a non-randomized cross-sectional study utilizing electronic surveys that evaluated conditions of trust among staff members and emotional intelligence among supervisors. Pearson correlation coefficients and corresponding p-values are presented to provide the association between emotional intelligence scales and the conditions of trust. Significant positive correlations were observed between supervisors’ stress management and the staff members’ trust or perception of supervisors’ loyalty (r = 0.6, p = 0.01), integrity (r = 0.5, p = 0.03), receptivity (r = 0.6, p = 0.02), promise fulfillment (r = 0.6, p = 0.02), and availability (r = 0.5, p = 0.07). This research lays the foundation for emotional intelligence and trust research and leadership training in other governmental public health settings, such as local, other state, national, or international organizations. This original research provides metrics to assess the public health workforce with attention to organizational management and leadership constructs. The survey tools could be used in other governmental public health settings in order to develop tailored training opportunities related to emotional intelligence and trust organizations

The Ursinus Weekly, May 11, 1972

Travelin\u27 5 talent ready • Campus Chest presents: You can\u27t take it with you • U.C. students offered esoteric subject matter • Warren Robinson named St. Andrews scholar • U.C. receives grant • U.C. graduate presents piano concert • Executives discuss gift solicitation on campus • Editorial: Reflections; Need for a counselor • Focus: Barbara Dando • Fidler on the wax: Humble Pie • Faculty portrait: Dr. Louis DeCatur • Strike • College scholars • Letters to the editor: U.S. government defended; Collegeville\u27s smut store; Apathy habit • Final examination schedule • Spring Parents\u27 Day • Ursinus pounds Penn • U.C. baseball loses to Haverford in top of 9th • The Ersinus Weaklyhttps://digitalcommons.ursinus.edu/weekly/1124/thumbnail.jp

Active sensors for health monitoring of aging aerospace structures

A project to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage (fatigue cracks and corrosion) is presented. The state of the art in active sensors structural health monitoring and damage detection is reviewed. Methods based on (a) elastic wave propagation and (b) electro-mechanical (NM) impedance technique are sighted and briefly discussed. The instrumentation of these specimens with piezoelectric active sensors is illustrated. The main detection strategies (E/M impedance for local area detection and wave propagation for wide area interrogation) are discussed. The signal processing and damage interpretation algorithms are tuned to the specific structural interrogation method used. In the high-frequency EIM impedance approach, pattern recognition methods are used to compare impedance signatures taken at various time intervals and to identify damage presence and progression from the change in these signatures. In the wave propagation approach, the acoustic-ultrasonic methods identifying additional reflection generated from the damage site and changes in transmission velocity and phase are used. Both approaches benefit from the use of artificial intelligence neural networks algorithms that can extract damage features based on a learning process. Design and fabrication of a set of structural specimens representative of aging aerospace structures is presented. Three built-up specimens, (pristine, with cracks, and with corrosion damage) are used. The specimen instrumentation with active sensors fabricated at the University of South Carolina is illustrated. Preliminary results obtained with the E/M impedance method on pristine and cracked specimens are presented

Speciation control during Suzuki-Miyaura cross-coupling of haloaryl and haloalkenyl MIDA boronic esters

Boronic acid solution speciation can be controlled during the Suzuki-Miyaura cross-coupling of haloaryl MIDA boronic esters to enable the formal homologation of boronic acid derivatives. The reaction is contingent upon control of the basic biphase and is thermodynamically driven: temperature control provides highly chemoselective access to either BMIDA adducts at room temperature or BPin products at elevated temperature. Control experiments and solubility analyses have provided some insight into the mechanistic operation of the formal homologation process

Miniaturization optimized weapon killing power during the social stress of late pre-contact North America (AD 600-1600)

Before Europeans arrived to Eastern North America, prehistoric, indigenous peoples experienced a number of changes that culminated in the development of sedentary, maize agricultural lifeways of varying complexity. Inherent to these lifeways were several triggers of social stress including population nucleation and increase, intergroup conflict (warfare), and increased territoriality. Here, we examine whether this period of social stress co-varied with deadlier weaponry, specifically, the design of the most commonly found prehistoric archery component in late pre-contact North America: triangular stone arrow tips (TSAT). The examination of modern metal or carbon projectiles, arrows, and arrowheads has demonstrated that smaller arrow tips penetrate deeper into a target than do larger ones. We first experimentally confirm that this relationship applies to arrow tips made from stone hafted onto shafts made from wood. We then statistically assess a large sample (n = 742) of late pre-contact TSAT and show that these specimens are extraordinarily small. Thus, by miniaturizing their arrow tips, prehistoric people in Eastern North America optimized their projectile weaponry for maximum penetration and killing power in warfare and hunting. Finally, we verify that these functional advantages were selected across environmental and cultural boundaries. Thus, while we cannot and should not rule out stochastic, production economizing, or non-adaptive cultural processes as an explanation for TSAT, overall our results are consistent with the hypothesis that broad, socially stressful demographic changes in late pre-contact Eastern North America resulted in the miniaturization–and augmented lethality–of stone tools across the region

High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities.

T-cell specificity is determined by the T-cell receptor, a heterodimeric protein coded for by an extremely diverse set of genes produced by imprecise somatic gene recombination. Massively parallel high-throughput sequencing allows millions of different T-cell receptor genes to be characterized from a single sample of blood or tissue. However, the extraordinary heterogeneity of the immune repertoire poses significant challenges for subsequent analysis of the data. We outline the major steps in processing of repertoire data, considering low-level processing of raw sequence files and high-level algorithms, which seek to extract biological or pathological information. The latest generation of bioinformatics tools allows millions of DNA sequences to be accurately and rapidly assigned to their respective variable V and J gene segments, and to reconstruct an almost error-free representation of the non-templated additions and deletions that occur. High-level processing can measure the diversity of the repertoire in different samples, quantify V and J usage and identify private and public T-cell receptors. Finally, we discuss the major challenge of linking T-cell receptor sequence to function, and specifically to antigen recognition. Sophisticated machine learning algorithms are being developed that can combine the paradoxical degeneracy and cross-reactivity of individual T-cell receptors with the specificity of the overall T-cell immune response. Computational analysis will provide the key to unlock the potential of the T-cell receptor repertoire to give insight into the fundamental biology of the adaptive immune system and to provide powerful biomarkers of disease

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data

PURPOSE Precise mechanism-based gene expression signatures (GES) have been developed in appropriate in vitro and in vivo model systems, to identify important cancer-related signaling processes. However, some GESs originally developed to represent specific disease processes, primarily with an epithelial cell focus, are being applied to heterogeneous tumor samples where the expression of the genes in the signature may no longer be epithelial-specific. Therefore, unknowingly, even small changes in tumor stroma percentage can directly influence GESs, undermining the intended mechanistic signaling. EXPERIMENTAL DESIGN Using colorectal cancer as an exemplar, we deployed numerous orthogonal profiling methodologies, including laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single-cell RNA sequencing and finally spatial transcriptomics, to perform a comprehensive assessment of the potential for the most widely used GESs to be influenced, or confounded, by stromal content in tumor tissue. To complement this work, we generated a freely-available resource, ConfoundR; https://confoundr.qub.ac.uk/, that enables users to test the extent of stromal influence on an unlimited number of the genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian and prostate cancer datasets. RESULTS Findings presented here demonstrate the clear potential for misinterpretation of the meaning of GESs, due to widespread stromal influences, which in-turn can undermine faithful alignment between clinical samples and preclinical data/models, particularly cell lines and organoids, or tumor models not fully recapitulating the stromal and immune microenvironment. CONCLUSIONS Efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples