Probing the Morphology of Bulk Heterojunctions with Phthalocyanine and Naphthalocyanine Small Molecules: A Microwave and Solar Cell Device Study

Organic photovoltaics (OPVs) have the potential to provide clean, renewable energy. In this thesis work, solar devices were constructed by using an inverted architecture. Silicon naphthalocyanine (SiNc) and one of three phthalocyanine molecules (Pc1, Pc2, or Pc3) were separately added to the active layer of OPV solar cells in order to determine their impact on the performance and spectral response. Also, time-resolved microwave conductivity (TRMC) measurements were performed on thin films of P3HT:PC60BM with SiNc or one of three phthalocyanine molecules, neat P3HT with one of the small molecules, and neat PC60BM with a small molecule. The results from the TRMC experiments demonstrate that ternary blends showed characteristics of a three-phase morphology and it was possible to provide insight into the location of the molecules in the bulk heterojunction by analysis of the data. Therefore, TRMC has the potential to probe the morphology of different systems used for solar devices.</p

The polo-like kinase 1 inhibitor volasertib synergistically increases radiation efficacy in glioma stem cells.

Background: Despite the availability of hundreds of cancer drugs, there is insufficient data on the efficacy of these drugs on the extremely heterogeneous tumor cell populations of glioblastoma (GBM). Results: The PKIS of 357 compounds was initially evaluated in 15 different GSC lines which then led to a more focused screening of the 21 most highly active compounds in 11 unique GSC lines using HTS screening for cell viability. We further validated the HTS result with the second-generation PLK1 inhibitor volasertib as a single agent and in combination with ionizing radiation (IR). Conclusions: Our results reinforce the potential therapeutic efficacy of volasertib in combination with radiation for the treatment of GBM. Methods: We used high-throughput screening (HTS) to identify drugs, out of 357 compounds in the published Protein Kinase Inhibitor Set, with the greatest efficacy against a panel of glioma stem cells (GSCs), which are representative of the classic cancer genome atlas (TCGA) molecular subtypes. Oncotarget 2018; 9(8):10497-10509

Metabolism and Toxicity of Thioacetamide and Thioacetamide SOxide in Rat Hepatocytes

“This document is the Accepted Manuscript version of a Published Work that appeared in final form in Chemical Research in Toxicology, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/tx3002719The hepatotoxicity of thioacetamide (TA) has been known since 1948. In rats, single doses cause centrilobular necrosis accompanied by increases in plasma transaminases and bilirubin. To elicit these effects TA requires oxidative bioactivation leading first to its S-oxide (TASO) and then to its chemically reactive S,S-dioxide (TASO2) which ultimately modifies amine-lipids and proteins. To generate a suite of liver proteins adducted by TA metabolites for proteomic analysis, and to reduce the need for both animals and labeled compounds, we treated isolated hepatocytes directly with TA. Surprisingly, TA was not toxic at concentrations up to 50 mM for 40 hr. On the other hand, TASO was highly toxic to isolated hepatocytes as indicated by LDH release, cellular morphology and vital staining with Hoechst 33342/propidium iodide. TASO toxicity was partially blocked by the CYP2E1 inhibitors diallyl sulfide and 4-methylpyrazole, and was strongly inhibited by TA. Significantly, we found that hepatocytes produce TA from TASO relatively efficiently by back-reduction. The covalent binding of [14C]-TASO is inhibited by unlabeled TA which acts as a “cold-trap” for [14C]-TA and prevents its re-oxidation to [14C]-TASO. This in turn increases the net consumption of [14C]-TASO despite the fact that its oxidation to TASO2 is inhibited. The potent inhibition of TASO oxidation by TA, coupled with the back-reduction of TASO and its futile redox cycling with TA may help explain phenomena previously interpreted as “saturation toxicokinetics” in the in vivo metabolism and toxicity of TA and TASO. The improved understanding of the metabolism and covalent binding of TA and TASO facilitates the use of hepatocytes to prepare protein adducts for target protein identification

Influenza vaccination for immunocompromised patients: systematic review and meta-analysis from a public health policy perspective.

Immunocompromised patients are vulnerable to severe or complicated influenza infection. Vaccination is widely recommended for this group. This systematic review and meta-analysis assesses influenza vaccination for immunocompromised patients in terms of preventing influenza-like illness and laboratory confirmed influenza, serological response and adverse events

Kostnadsberäknings- och dimensioneringsprogram för BinStacker®, helautomatiskt höglager

Syftet med detta examensarbete var att utveckla en programvara för kostnadsberäkning och dimensionering av Mesmecs nya helautomatiska lagerlösning, BinStacker®. Företagets tidigare system för att prissätta och dimensionera lagret var mycket krävande både när det gäller tid och pengar. Då BinStacker® har en standardiserad design oavsett storlek eller kapacitet, ansågs det möjligt att utveckla en automatiserad programvara som skulle förenkla både prissättning och dimensionering. Programvaran utvecklades i Microsoft Excel för att öka användarvänligheten och tillgängligheten. Genom att använda data från befintliga materiallistor och samarbeta med företaget byggdes programvaran gradvis upp med hjälp av kostnadsberäkningens principer. Resultatet av detta examensarbete är en programvara som förenklar prissättningen av lagerlösningen genom att ge användaren pris- och dimensioneringsinformation efter att de viktigaste parametrarna har matats in i programmet. Programvaran innehåller även en offertmall som kan användas direkt för att ge kunden en detaljerad och korrekt kostnadsuppskattning. Programvaran är utformad på ett sätt som gör den enkel att uppdatera till aktuella priser. Programmets baksida som består av materiallistor som krävs för lagrets uppbyggnad fungerar även som reservdelslistor.Tämän opinnäytetyön tarkoituksena oli kehittää ohjelmisto Mesmecin uudelle automaattiselle varastoratkaisulle, jota kutsutaan nimellä BinStacker®️. Aiempi järjestelmä varaston hinnan laskemiseen ja mitoittamiseen oli sekä aikaa että rahaa vievä. BinStacker®️ standardoitu suunnittelu mahdollisti automatisoidun ohjelmiston kehittämisen, joka helpottaisi sekä hinnoittelua että mitoitusta. Ohjelmisto kehitettiin Microsoft Excelissä käyttäjäystävällisyyden ja saavutettavuuden parantamiseksi. Olemassa olevista materiaaliluetteloista saatavan datan avulla ja yhteistyössä yrityksen kanssa rakennettiin ohjelmisto kustannuslaskennan periaatteiden mukaan. Tämän opinnäytetyön tuloksena syntyi ohjelmisto, joka helpottaa varastoratkaisun hinnoittelua antamalla käyttäjälle hinta- ja mitoitustiedot tärkeimpien parametrien syöttämisen jälkeen. Ohjelmisto sisältää myös tarjousmallin, jota voidaan käyttää kun annetaan asiakkaalle suoraan yksityiskohtaisen ja tarkan kustannusarvion. Ohjelmisto on suunniteltu siten, että se on helppo päivittää ajantasaisilla hinnoilla. Ohjelmiston taustalla olevat materiaaliluettelot, jotka tarvitaan varaston rakentamiseen, toimivat myös varaosaluetteloina.The purpose of this thesis was to develop software for cost estimation and dimensioning of Mesmec's new fully automated warehouse solution, BinStacker®. The company's previous system for pricing and dimensioning the warehouse was both time and cost consuming. Since BinStacker® has a standardized design regardless of size or capacity, it was deemed possible to develop an automated software solution that would simplify both pricing and dimensioning. The software was developed in Microsoft Excel to increase user-friendliness and accessibility. Using data from existing material lists and collaborating with the company, the software was gradually built-up using cost estimation principles. The result of this thesis is a software that simplifies the pricing of the warehouse solution by providing the user with price and dimensioning information after the most important parameters have been entered into the program. The software also includes a quote template that can be used directly to provide the customer with a detailed and accurate cost estimate. The software is designed in a way that makes it easy to update to current prices. The software's backside, which consists of material lists required for the construction of the warehouse, also functions as spare parts lists

Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity

Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. The goal of this master project is to develop an artificial neural network-based model for food waste analysis, an area in which large quantities of data is not yet readily available. Given two images an algorithm is expected to identify what has changed in the image, ignore the uncharged areas even though they might contain objects which can be classified and finally classify the change. The approach chosen in this project was to attempt to reduce the problem the machine learning algorithm has to solve by subtracting the images before they are handled by the neural network. In theory this should resolve both object localisation and filtering of uninteresting objects, which only leaves classification to the neural network. Such a procedure significantly simplifies the task to be resolved by the neural network, which results in reduced need for training data as well as keeping the process of gathering data relatively simple and fast. Several models were assessed and theories of adaptation of the neural network to this particular task were evaluated. Test accuracy of at best 78.9% was achieved with a limited dataset of about 1000 images with 10 different classes. This performance was accomplished by a siamese neural network based on VGG19 utilising triplet loss and training data using subtraction as a basis for ground truth mask creation, which was multiplied with the image containing the changed object.Maskininlärning kräver generellt mycket data, men stora mängder data står inte alltid till förfogande. Generellt ökar behovet av data med problemets komplexitet. Med hjälp av överföringsinlärning, dataaugumentation och problemreduktion kan dock acceptabel prestanda erhållas på begränsad datamängd för flera uppgifter.  Målet med denna masteruppsats är att ta fram en modell baserad på artificiella neurala nätverk för matavfallsanalys, ett område inom vilket stora mängder data ännu inte finns tillgängligt. Givet två bilder väntas en algoritm identifiera vad som ändrats i bilden, ignorera de oförändrade områdena även om dessa innehåller objekt som kan klassificeras och slutligen klassificera ändringen. Tillvägagångssättet som valdes var att försöka reducera problemet som maskininlärningsalgoritmen, i detta fall ett artificiellt neuralt nätverk, behöver hantera genom att subtrahera bilderna innan de hanterades av det neurala nätverket. I teorin bör detta ta hand om både objektslokaliseringen och filtreringen av ointressanta objekt, vilket endast lämnar klassificeringen till det neurala nätverket. Ett sådant tillvägagångssätt förenklar problemet som det neurala nätverket behöver lösa avsevärt och resulterar i minskat behov av träningsdata, samtidigt som datainsamling hålls relativt snabbt och simpelt.  Flera olika modeller utvärderades och teorier om specialanpassningar av neurala nätverk för denna uppgift evaluerades. En testnoggrannhet på som bäst 78.9% uppnåddes med begränsad datamängd om ca 1000 bilder med 10 klasser. Denna prestation erhölls med ett siamesiskt neuralt nätverk baserat på VGG19 med tripletförlust och träningsdata som använde subtraktion av bilder som grund för framställning av grundsanningsmasker (eng. Ground truth masks) multiplicerade med bilden innehållande förändringen.

Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity

Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. The goal of this master project is to develop an artificial neural network-based model for food waste analysis, an area in which large quantities of data is not yet readily available. Given two images an algorithm is expected to identify what has changed in the image, ignore the uncharged areas even though they might contain objects which can be classified and finally classify the change. The approach chosen in this project was to attempt to reduce the problem the machine learning algorithm has to solve by subtracting the images before they are handled by the neural network. In theory this should resolve both object localisation and filtering of uninteresting objects, which only leaves classification to the neural network. Such a procedure significantly simplifies the task to be resolved by the neural network, which results in reduced need for training data as well as keeping the process of gathering data relatively simple and fast. Several models were assessed and theories of adaptation of the neural network to this particular task were evaluated. Test accuracy of at best 78.9% was achieved with a limited dataset of about 1000 images with 10 different classes. This performance was accomplished by a siamese neural network based on VGG19 utilising triplet loss and training data using subtraction as a basis for ground truth mask creation, which was multiplied with the image containing the changed object.Maskininlärning kräver generellt mycket data, men stora mängder data står inte alltid till förfogande. Generellt ökar behovet av data med problemets komplexitet. Med hjälp av överföringsinlärning, dataaugumentation och problemreduktion kan dock acceptabel prestanda erhållas på begränsad datamängd för flera uppgifter.  Målet med denna masteruppsats är att ta fram en modell baserad på artificiella neurala nätverk för matavfallsanalys, ett område inom vilket stora mängder data ännu inte finns tillgängligt. Givet två bilder väntas en algoritm identifiera vad som ändrats i bilden, ignorera de oförändrade områdena även om dessa innehåller objekt som kan klassificeras och slutligen klassificera ändringen. Tillvägagångssättet som valdes var att försöka reducera problemet som maskininlärningsalgoritmen, i detta fall ett artificiellt neuralt nätverk, behöver hantera genom att subtrahera bilderna innan de hanterades av det neurala nätverket. I teorin bör detta ta hand om både objektslokaliseringen och filtreringen av ointressanta objekt, vilket endast lämnar klassificeringen till det neurala nätverket. Ett sådant tillvägagångssätt förenklar problemet som det neurala nätverket behöver lösa avsevärt och resulterar i minskat behov av träningsdata, samtidigt som datainsamling hålls relativt snabbt och simpelt.  Flera olika modeller utvärderades och teorier om specialanpassningar av neurala nätverk för denna uppgift evaluerades. En testnoggrannhet på som bäst 78.9% uppnåddes med begränsad datamängd om ca 1000 bilder med 10 klasser. Denna prestation erhölls med ett siamesiskt neuralt nätverk baserat på VGG19 med tripletförlust och träningsdata som använde subtraktion av bilder som grund för framställning av grundsanningsmasker (eng. Ground truth masks) multiplicerade med bilden innehållande förändringen.

A histologic evaluation of the human dental pulp following treatment by the Caridex caries removal system

PLEASE NOTE: This work is protected by copyright. Downloading is restricted to the BU community: please click Download and log in with a valid BU account to access. If you are the author of this work and would like to make it publicly available, please contact [email protected] photographs included.Caridex is a trademark.Thesis (M.Sc.D.)--Boston University, Henry M. Goldman School of Graduate Dentistry, 1987 (Endodontics)Bibliography : leaves 127-136.A histological study to evaluate human pulpal responses following caries removal treatment by the Caridex caries removal system was conducted utilizing fifteen human teeth. The teeth employed in this investigation were previously scheduled to be extracted and possessed a carious lesion involving only enamel and dentin. Vitality of the dental pulp was confirmed through a series of diagnostic tests. Following caries removal by the Caridex system, a temporary zinc oxide-eugenol (ZOE) restoration was placed in the cavity preparation. The teeth were extracted either seven days post-operatively or thirty days post-operatively,　and then histologically prepared and examined. Histological evaluation of the specimens in the seven day post-operative group revealed three specimens which demonstrated a possible hyperemic response; two specimens displayed a generalized inflammatory response indicative of a carious pulp exposure,　although no exposures were observed; one specimen revealed a localized inflammatory response; and two specimens displayed normal pulp tissue. Examination of specimens in the thirty day post-operative group found three specimens which demonstrated a possible hyperemic response, and four specimens which displayed normal pulp tissue. No generalized or localized inflammatory response was noted. Analysis of the histologic sections also revealed that six of the fifteen specimens showed evidence of dental caries remaining on the surface of the cavity preparation and extending into dentinal tubules. Additionally, caries removal by the Caridex system was noted to be a slow and lengthy process. Actual caries removal time ranged from nine minutes to　22　minutes, with an average caries removal treatment phase of 15.5　minutes. Based on the evaluation of the teeth utilized in this study, the following conclusions may be drawn: 1. No significant inflammatory response was observed in carious teeth following treatment by the Caridex caries removal system in either the seven day or thirty day post-operative groups which could be attributable to the Caridex system. 2. Dental caries were found to remain on the cavity preparation surface following diligent caries removal treatment utilizing the Caridex system in　40%　of the teeth studied. 3. Exceptionally long caries removal treatment times were necessary in order to obtain clinically caries-free cavity preparations.　However, histologically, caries were demonstrated to still be evident in six of the fifteen specimens studied. 4. The Caridex caries removal system seems to be a good marketing tool for dentists however, with incomplete caries removal, protracted treatment times, the relatively high cost of the system, and the need for rotary instruments after caries removal in order to refine the cavity preparation and place retention, the Caridex system does not appear to be a practical addition to the dental armamentarium of caries removal techniques as it currently exists

Power analysis for detecting trends in the presence of concomitant variables

In some situations, survey counts must be adjusted for the effects of concomitant variables using analysis of covariance in order to detect a trend in abundance over time. A power analysis in these cases allows the calculation of the probability of detecting a trend after adjustments. The methods will be applicable to samples taken at regular or irregular intervals in time or space, and in which the effects of the concomitant variables do not change over time. Furthermore, the detection of linear and intrinsically linear change can be determined. The methods are applied to the monitoring of American alligator (Alligator mississippiensis) populations in Florida