Morita homotopy theory of C*-categories

In this article we establish the foundations of the Morita homotopy theory of C*-categories. Concretely, we construct a cofibrantly generated simplicial symmetric monoidal Quillen model structure M_Mor on the category C*cat1 of small unital C*-categories. The weak equivalences are the Morita equivalences and the cofibrations are the *-functors which are injective on objects. As an application, we obtain an elegant description of the Brown-Green-Rieffel Picard group in the associated Morita homotopy category Ho(M_Mor). We then prove that the Morita homotopy category is semi-additive. By group completing the induced abelian monoid structure at each Hom-set we obtain an additive category Ho(M_Mor)^{-1} and a canonical functor C*cat1 {\to} Ho(M_Mor)^{-1} which is characterized by two simple properties: inversion of Morita equivalences and preservation of all finite products. Finally, we prove that the classical Grothendieck group functor becomes co-represented in Ho(M_Mor)^{-1} by the tensor unit object.Comment: 35 page

Analysis of Incident DKA in the Indiana New Onset T1D Patient Population

Background/Objective: Diabetic ketoacidosis (DKA) is a life-threatening complication of type 1 diabetes (T1D) resulting from ketone body production and metabolic acidosis occurring due to insulin deficiency. We sought to define the occurrence of DKA amongst pediatric patients presenting with new-onset T1D in Indiana and to determine whether patterns of DKA were affected by the COVID-19 pandemic. Methods: This was a retrospective chart review for patients <18 years admitted to Riley Children’s Hospital with a clinical diagnosis of new onset T1D who had available chemistry values. Patients diagnosed from March 23- June 30, 2020 and over the same period in 2019 were included. DKA was classified as mild (bicarbonate 10-15 mmol/L) or severe (bicarbonate <10 mmol/L). Results: Ninety-four patients met inclusion criteria. The total number of incident T1D cases in 2019 and 2020 were similar (48 vs. 46, respectively). Similarly, there was no significant difference in rates of DKA (21 in 2019 vs. 25 in 2020; p>0.05). Of the 94 patients, 49% met criteria for DKA; 79% of cases were classified as severe and 21% as mild. More males were diagnosed with DKA in both 2019 and 2020 (61% of DKA cases). Non-Hispanic whites comprised 75% of all new onset T1D patients and no differences in race or ethnicity were present amongst those presenting in DKA. Conclusion: DKA was present in nearly half of all new onset pediatric T1D cases in Indiana in 2019 and 2020. There was no observed impact of the COVID-19 pandemic on T1D or DKA. Impact and Implications: DKA is common amongst pediatric patients with new onset T1D in Indiana. Prompt recognition of symptoms is needed to prevent this life-threatening complication of T1D

Integer Quantum Hall Effect in Graphite

We present Hall effect measurements on highly oriented pyrolytic graphite that indicate the occurrence of the integer quantum-Hall-effect. The evidence is given by the observation of regular plateau-like structures in the field dependence of the transverse conductivity obtained in van der Pauw configuration. Measurements with the Corbino-disk configuration support this result and indicate that the quasi-linear and non-saturating longitudinal magnetoresistance in graphite is governed by the Hall effect in agreement with a recent theoretical model for disordered semiconductors.Comment: 3 figures, to be published in Solid State Communication (2006

A novel transflectance near infrared spectroscopy technique for monitoring hot melt extrusion

yesA transflectance near infra red (NIR) spectroscopy approach has been used to simultaneously measure drug and plasticiser content of polymer melts with varying opacity during hot melt extrusion. A high temperature reflectance NIR probe was mounted in the extruder die directly opposed to a highly reflective surface. Carbamazepine (CBZ) was used as a model drug, with polyvinyl pyrollidone-vinyl acetate co-polymer (PVP-VA) as a matrix and polyethylene glycol (PEG) as a plasticiser. The opacity of the molten extrudate varied from transparent at low CBZ loading to opaque at high CBZ loading. Particulate amorphous API and voids formed around these particles were found to cause the opacity. The extrusion process was monitored in real time using transflectance NIR; calibration and validation runs were performed using a wide range of drug and plasticiser loadings. Once calibrated, the technique was used to simultaneously track drug and plasticiser content during applied step changes in feedstock material. Rheological and thermal characterisations were used to help understand the morphology of extruded material. The study has shown that it is possible to use a single NIR spectroscopy technique to monitor opaque and transparent melts during HME, and to simultaneously monitor two distinct components within a formulation

Negotiation in strategy making teams : group support systems and the process of cognitive change

This paper reports on the use of a Group Support System (GSS) to explore at a micro level some of the processes manifested when a group is negotiating strategy-processes of social and psychological negotiation. It is based on data from a series of interventions with senior management teams of three operating companies comprising a multi-national organization, and with a joint meeting subsequently involving all of the previous participants. The meetings were concerned with negotiating a new strategy for the global organization. The research involved the analysis of detailed time series data logs that exist as a result of using a GSS that is a reflection of cognitive theory

Near infra red spectroscopy as a multivariate process analytical tool for predicting pharmaceutical co-crystal concentration

YesThe use of near infra red spectroscopy to predict the concentration of two pharmaceutical co-crystals; 1:1 ibuprofen – nicotinamide (IBU-NIC) and 1:1 carbamazepine – nicotinamide (CBZ-NIC) has been evaluated. A Partial Least Squares (PLS) regression model was developed for both co-crystal pairs using sets of standard samples to create calibration and validation data sets with which to build and validate the models. Parameters such as the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and correlation coefficient were used to assess the accuracy and linearity of the models. Accurate PLS regression models were created for both co-crystal pairs which can be used to predict the co-crystal concentration in a powder mixture of the co-crystal and the active pharmaceutical ingredient (API). The IBU-NIC model had smaller errors than the CBZ-NIC model, possibly due to the complex CBZ-NIC spectra which could reflect the different arrangement of hydrogen bonding associated with the co-crystal compared to the IBU-NIC co-crystal. These results suggest that NIR spectroscopy can be used as a PAT tool during a variety of pharmaceutical co-crystal manufacturing methods and the presented data will facilitate future offline and in-line NIR studies involving pharmaceutical co-crystals

Hybrid Multicore/vectorisation technique applied to the elastic wave equation on a staggered grid

In modern physics it has become common to find the solution of a problem by solving numerically a set of PDEs. Whether solving them on a finite difference grid or by a finite element approach, the main calculations are often applied to a stencil structure. In the last decade it has become usual to work with so called big data problems where calculations are very heavy and accelerators and modern architectures are widely used. Although CPU and GPU clusters are often used to solve such problems, parallelisation of any calculation ideally starts from a single processor optimisation. Unfortunately, it is impossible to vectorise a stencil structured loop with high level instructions. In this paper we suggest a new approach to rearranging the data structure which makes it possible to apply high level vectorisation instructions to a stencil loop and which results in significant acceleration. The suggested method allows further acceleration if shared memory APIs are used. We show the effectiveness of the method by applying it to an elastic wave propagation problem on a finite difference grid. We have chosen Intel architecture for the test problem and OpenMP (Open Multi-Processing) since they are extensively used in many applications

Current Treatment Strategies for Castration-Resistant Prostate Cancer

Prostate cancer is the most common cancer in men in United States and the fifth most common cancer in men in Korea. Although the majority of patients with metastatic prostate cancer initially respond to androgen deprivation therapy, almost all patients will eventually progress to develop castration-resistant prostate cancer (CRPC). Treatment options for CRPC remain limited. Prostate cancer was considered unresponsive to chemotherapy until the mid-1990s, when mitoxantrone combined with prednisone was shown to play a role in the palliative treatment of patients with CRPC. In 2004, two large randomized clinical trials demonstrated for the first time a small but significant survival advantage of docetaxel-based chemotherapy compared with mitoxantrone in patients with metastatic CRPC. Recently, cabazitaxel was shown to improve survival in patients with metastatic CRPC who progressed after docetaxel-based chemotherapy. Sipuleucel-T was also demonstrated to improve overall survival in patients with asymptomatic or minimally symptomatic metastatic CRPC. Along with mitoxantrone and docetaxel, cabazitaxel and sipuleucel-T are now approved for use in metastatic CRPC by the US Food and Drug Administration. There have been multiple early-phase clinical trials of various agents for the treatment of CRPC, and some are in phase III development. This review focuses on the key clinical trials of various treatment options of CRPC currently in use and under investigation

Can a “state of the art” chemistry transport model simulate Amazonian tropospheric chemistry?

We present an evaluation of a nested high-resolution Goddard Earth Observing System (GEOS)-Chem chemistry transport model simulation of tropospheric chemistry over tropical South America. The model has been constrained with two isoprene emission inventories: (1) the canopy-scale Model of Emissions of Gases and Aerosols from Nature (MEGAN) and (2) a leaf-scale algorithm coupled to the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model, and the model has been run using two different chemical mechanisms that contain alternative treatments of isoprene photo-oxidation. Large differences of up to 100 Tg C yr^(−1) exist between the isoprene emissions predicted by each inventory, with MEGAN emissions generally higher. Based on our simulations we estimate that tropical South America (30–85°W, 14°N–25°S) contributes about 15–35% of total global isoprene emissions. We have quantified the model sensitivity to changes in isoprene emissions, chemistry, boundary layer mixing, and soil NO_x emissions using ground-based and airborne observations. We find GEOS-Chem has difficulty reproducing several observed chemical species; typically hydroxyl concentrations are underestimated, whilst mixing ratios of isoprene and its oxidation products are overestimated. The magnitude of model formaldehyde (HCHO) columns are most sensitive to the choice of chemical mechanism and isoprene emission inventory. We find GEOS-Chem exhibits a significant positive bias (10–100%) when compared with HCHO columns from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI) for the study year 2006. Simulations that use the more detailed chemical mechanism and/or lowest isoprene emissions provide the best agreement to the satellite data, since they result in lower-HCHO columns

Introducing systems approaches

Systems Approaches to Managing Change brings together five systems approaches to managing complex issues, each having a proven track record of over 25 years. The five approaches are: System Dynamics (SD) developed originally in the late 1950s by Jay Forrester Viable Systems Model (VSM) developed originally in the late 1960s by Stafford Beer Strategic Options Development and Analysis (SODA: with cognitive mapping) developed originally in the 1970s by Colin Eden Soft Systems Methodology (SSM) developed originally in the 1970s by Peter Checkland Critical Systems Heuristics (CSH) developed originally in the late 1970s by Werner Ulrich