7,412 research outputs found
A biogeographical analysis of the tenebrionid beetles (Coleoptera, Tenebrionidae) of the island of Thasos in the context of the Aegean Islands (Greece)
No full textFattorini, Simone, Fowles, Adrian P. (2005): A biogeographical analysis of the tenebrionid beetles (Coleoptera, Tenebrionidae) of the island of Thasos in the context of the Aegean Islands (Greece). Journal of Natural History 39 (46): 3919-3949, DOI: 10.1080/00222930500533443, URL: http://dx.doi.org/10.1080/0022293050053344
The Treatment of Ties in AP Correlation
No full textThe Kendall tau and AP correlation coefficients are very commonly use to compare two rankings over the same set of items. Even though Kendall tau was originally defined assuming that there are no ties in the rankings, two alternative versions were soon developed to account for ties in two different scenarios: measure the accuracy of an observer with respect to a true and objective ranking, and measure the agreement between two observers in the absence of a true ranking. These two variants prove useful in cases where ties are possible in either ranking, and may indeed result in very different scores. AP correlation was devised to incorporate a top-heaviness component into Kendall tau, penalizing more heavily if differences occur between items at the top of the rankings, making it a very compelling coefficient in Information Retrieval settings. However, the treatment of ties in AP correlation remains an open problem. In this paper we fill this gap, providing closed analytical formulations of AP correlation under the two scenarios of ties contemplated in Kendall tau. In addition,we developed an R package that implements these coefficients.Best Short Paper Accepted author manuscriptMultimedia ComputingWeb Information System
Strategie di Modellazione e Tecniche di Rilevamento dei Pasti in supporto ad un Pancreas Artificiale Individualizzato e Completamente Automatizzato
No full textLa malattia autoimmune conosciuta come diabete di tipo 1 (T1D) è caratterizzata dalla distruzione delle cellule beta pancreatiche, le quali sono responsabili della produzione di insulina. La conseguente incapacità di produrre insulina è associata a livelli anomali di glucosio. Oltre all'infusione di insulina, la terapia del diabete convenzionale mira a mantenere la glicemia nel range di normalità regolando la dieta e l'attività fisica sulla base di 4-5 misurazioni giornaliere della glicemia (SMBG), ottenute mediante sensori pungidito. Fortunatamente, negli ultimi anni sono stati aperti nuovi scenari nel trattamento del diabete. I sensori di monitoraggio continuo del glucosio (CGM) sono in grado di monitorare la concentrazione di glicemia in modo continuo (cioè con una lettura ogni 1-5 min) per diversi giorni (7-10 giorni consecutivi), consentendo di monitorare la dinamica del glucosio in modo più efficace rispetto ai sensori SMBG. Le pompe portatili per l'infusione sottocutanea continua erogano insulina attraverso un catetere e consentono al paziente di modificare il dosaggio durante il giorno. Un altro promettente progresso è il cosiddetto pancreas artificiale (AP), un sistema che utilizza algoritmi di controllo per modulare automaticamente l'infusione di insulina. Si noti che l'uso combinato di dispositivi CGM, pompe per insulina, AP e applicazioni dedicate ha offerto la possibilità di registrare diversi tipi di informazioni, ad esempio dati di glicemia, insulina, pasti, attività fisica ed eventi quotidiani. Tutte queste serie temporali possono essere utilizzate sia in modo retrospettivo, ad esempio per ottimizzare la terapia di controllo, sia attraverso applicazioni in tempo reale: infatti, la gestione del T1D può essere migliorata da predizioni dei livelli futuri di glucosio e dalla progettazione di specifici sistemi di allarme, attraverso i quali è possibile rilevare e prevenire situazioni critiche. Inoltre, diversi algoritmi di controllo per AP sfruttano i modelli predittivi, incluso l'approccio "model predictive control" (MPC). La componente chiave sia dei sistemi di allarme che dell'AP è il modello utilizzato per descrivere la dinamica del glucosio, che deve essere in grado di affrontare la variabilità inter- e intra-soggetto: la risposta del glucosio all'insulina e al pasto è diversa in ogni persona, e nello stesso paziente cambia nel tempo. Questo problema può essere affrontato imparando e aggiornando i modelli della dinamica glucosio-insulina specifici di ogni paziente. Inoltre, questi ultimi possono essere utilizzati per progettare algoritmi di allerta individualizzati o per personalizzare l'algoritmo di controllo di un AP. Nonostante i vantaggi, gli attuali sistemi AP sono lontani dal soddisfare tutte le aspettative. Una delle richieste degli utenti è di eliminare il conteggio dei carboidrati. In effetti, i sistemi AP commerciali hanno adottato questo conteggio per superare le sfide del controllo postprandiale. Tuttavia, i ritardi tra la traccia CGM e la glicemia reale, oltre alle dinamiche di assorbimento dell'insulina sottocutanea, limitano l'efficacia dell'AP nella compensazione dell'assorbimento del glucosio postprandiale. Nei sistemi AP che richiedono il questo conteggio, ovvero "AP ibridi", gli utenti devono fornire una stima del contenuto del pasto affinché l'AP possa erogare un bolo di insulina pre-pasto. Questo bolo pre-pasto anticipa la necessità di insulina, migliorando così il controllo postprandiale. Tuttavia, il conteggio potrebbe ridurre le prestazioni dell'AP a causa di annunci mancati o ritardati e stime di carboidrati imprecise. Una possibile soluzione è l'uso di algoritmi di rilevamento dei pasti, un passo cruciale verso un “AP completamente automatizzato”. Lo scopo di questa tesi è esplorare e valutare nuove strategie e metodi di predizione per individualizzare e migliorare la gestione del T1D, verso un AP più efficace, personalizzato e completamente automatizzato.The autoimmune metabolic disease called type 1 diabetes (T1D) is characterized by the destruction of the pancreatic beta-cells, responsible for insulin production. The consequent inability to produce insulin, a crucial hormone in glucose homeostasis, is associated with anomalous blood glucose (BG) levels in the body. Besides insulin infusion, conventional diabetes therapy aims at maintaining glycemia in the normal range by tuning diet and physical activity on the basis of 4-5 daily self-monitoring of blood glucose (SMBG) measurements, obtained by the patient using portable minimally-invasive lancing sensor devices.
Fortunately, new scenarios in diabetes treatment have been opened in the last 20 years. Minimally invasive continuous glucose monitoring (CGM) sensors are able to monitor glucose concentration in the subcutis continuously (i.e., with a reading every 1 to 5 min) over several days (7-10 consecutive days), allowing tracking glucose dynamics much more effectively than SMBG. Portable pumps for continuous subcutaneous insulin infusion (CSII) deliver insulin through an intradermal catheter and allow the user to change the dosage during the day. Another promising advancement in T1D management is the so-called artificial pancreas (AP), a system that uses closed-loop control (CLC) algorithms to automatically modulate insulin infusion.
Note that the combined use of CGM devices, insulin pumps, AP systems, and dedicated mobile applications brought the possibility of recording different types of information, for instance, CGM data, insulin, meal, physical activity, and self-reported life events.
All these glycemia-related time series can be used both retrospectively, e.g., to optimize metabolic control therapy, and in real-time applications: in fact, T1D management can be considerably improved by accurate predictions of future glucose levels and by the design of specific alarm systems through which upcoming critical situations can be detected and prevented. Moreover, several control algorithms for AP leverage predictive models, including the model predictive control (MPC).
The key component of both predictive alert systems and AP is the mathematical model used to describe glucose dynamics, which must be able to deal with inter- and intra-subject variability: the glucose response to insulin and meal is different in every person, and even in the same patient changes over time. This issue can be addressed by learning and updating patient-specific models of the glucose-insulin dynamics and using them to design individualized predictive alert algorithms or to personalize the model-based CLC algorithm of an AP system.
Despite the many advantages, current AP systems are far from fulfilling all users' expectations. One of AP users' demands is to remove carbohydrate counting. In fact, commercial AP systems have adopted carbohydrate (CHO) counting to overcome the challenges of postprandial control. CGM lags and subcutaneous insulin absorption dynamics limit the AP effectiveness in post-meal glucose absorption compensation. In AP systems requiring CHO counting, i.e., "hybrid AP", users must provide an estimation of the meal CHO content for the AP to deliver a pre-meal insulin bolus. This pre-meal bolus advances the insulin needs to compensate for the glucose rise despite absorption delays, improving postprandial control. However, CHO counting might degrade AP performance due to timing delays, announcement omissions, and inaccurate CHO estimations. In addition, the extra burden on the users constitutes a reason for disconformity with the technology. A possible solution is the use of automated meal detection algorithms, a crucial step towards a "fully-automated AP".
The aim of this thesis is to explore and assess new prediction strategies and methods to individualize and to improve the management of T1D, towards a more effective, personalized, and fully-automated AP
Lysianassa's skills: Philodemus, Anth. Pal. 5.126 (=Sider 22)
No full textThe analysis of an epigram by the Greek writer Philodemus (AP 5.126) and the explanation of the meaning of the mysterious number "twelve
Delamination Analysis of A Class of AP-PLY Composite Laminates
No full textA recently developed fiber placement architecture, AP-PLY, has been shown to give significantly improved damage tolerance characteristics of composite structures. The behavior of delaminations resulting from low speed impact damage is of particular concern. Major attention has been paid to expand current knowledge on the delamination response of simple AP-PLY composite structure and move towards in-depth understanding of the failure mechanisms behind the damage tolerance. This thesis presents the approaches to predict delamination onset and analyze delamination growth, in support of the search of the optimum woven pattern for AP-PLY composite laminates. The recovered interlaminar stress between layers combined with the maximum stress criterion determined the delamination onset of simple AP-PLY composite laminate under out-of-plane loads. 2D finite element models with cohesive elements inserted in the interfaces of woven layers have been built to evaluate the delamination initiation and propagation in the different woven patterns of simple AP-PLY composite beams. The parameters of the woven pattern, such as the woven angle, the number of woven plies, the number of straight filled plies, and the location of the woven patterns in through the thickness direction, were investigated and shown to have a significant effect on delamination creation and growth. An energy method based on beam theory was proposed to analyze the strain energy release rate (SERR) of an existing crack in an AP-PLY beam structure. The developed analytical method was implemented in isotropic materials and the obtained SERR of a crack was validated by reference results and finite element solutions. The general behavior of crack growth on the left or right crack tip was evaluated and basic trends leading to crack propagation on one side of the crack were established. A correction factor was introduced to improve the accuracy of the SERR of a small crack through the numerical calculation. The singularity of crack tip caused by dissimilar materials was investigated and was found that the inclusion of the singularity effect could increase the accuracy for small cracks. It has been shown that the neutral axis needs to be relocated to decouple the bending and membrane behavior of unsymmetrical composite laminates, thus to meet the requirement of minimizing the strain energy of the delaminated beam to calculate the SERR of a delaminated composite beam. The calculated SERR of a crack in a composite beam has been verified by comparing with a finite element model. The woven plies in AP-PLY composite laminate altered the layup and two conventional laminates with different stacking sequences were identified in an AP-PLY composite laminate based on the assumption that the resin areas were ignored. A step by step approach was developed to obtain the SERR of a crack that goes across different materials. The analytical SERR determined when two materials are used in sequence, sets the stage for optimization of AP-PLY composite laminates without taking account of the effect of the resin area. The procedure of optimization of simple AP-PLY pattern was proposed and industry may benefit for many applications. An equivalent stiffness approach was used to model regions containing resin pockets and straight or inclined composite layers. A series of three point bending tests was carried out where the failure process and loading capacity were evaluated. The methodology, procedure of optimization, philosophy outlined in this thesis might also be applied to the more complicated fully woven AP-PLY composite laminates. The work in this thesis contributes to the understanding of the behavior of AP-PLY composite laminates with delaminations
Racial Inequality in AP and Honors Courses in the U.S. Education System
No full textWith the expansion of the Accelerated Placement (AP) Program as a result of President Bush’s No Child Left Behind Act, an increasing number of Universities and Colleges are using AP scores, either directly or indirectly, as one, among many, important criteria for making decisions on admissions and scholarship awards. However, a cross-section of the literature on educational inequality has found huge demographic (i.e. gender, class, racial, ethnic, etc.) gaps in enrollments and success in AP courses - with high income, white, and female students enrolling in, and performing better in, AP courses than other groups. While there is a wealth of literature examining these disparities at the national level, there is a dearth of information on factors associated with racial inequality in the AP Program at the local level. Using an availability sample of AP/Honors teachers within Spartanburg County, the current study set out to investigate factors associated with racial inequality in AP and Honors courses within Spartanburg County Public Schools. The sample consisted of eight teachers who self-identified as white females and three who self-identified as black females. These eleven teachers were the ones who responded affirmatively to email requests sent out to thirty (30) AP/Honors teachers in three school districts within Spartanburg County. In-depth interviews were conducted either in person or by phone using a semi-structured, open-ended questionnaire. The questionnaire collected information on the teacher’s demographic characteristics, overall student performance in the teacher’s AP/Honors classes, their experiences and interactions with the students, their perceptions about the demographic gaps in enrollment and performance in AP/Honors courses, among others. Data was analyzed using thematic analysis. Consistent with national trends, our study found that a majority of AP/Honors teachers in the Spartanburg County public schools were white females, just as the majority of students enrolled in the AP/Honors courses these teachers taught. There were very few teachers of color, and even fewer minority students, even in schools where the racial minority students were the majority. Racial disparities in enrollment and performance in AP/Honors courses were attributed to a number of factors, including tracking in the educational system, cultural dissonance, peer influence, social stigma, teacher implicit bias/prejudice, and differential support at school and home. The current study discusses the implications of these findings, strategies for mitigating the observed inequalities, and implications for future studies
Structure function analysis of blazars AP Librae and 3c279
No full textHighest Honors in AstronomyBlazars AP Librae and 3c279 are analyzed for microvariability using a technique known as structure function analysis. AP Librae was observed in April
of 2005 and 3c279 was observed in April of 2007. The data for AP Librae was
previously reduced by Andrew Collazzi and the author reduced the data for
3c279. Both sets of data were reduced using Robert Knop's data reduction
program.
The author ran structure function analysis on both sets of data. Structure function analysis is a statistical analysis run on data that is suppose to
nd timescales of variability, periodicity, and the noise type of data. Previous analysis of AP Librae confirmed mircrovariability, which also shows up in
the structure function of AP Librae. Blazar 3c279 was much quieter than AP
Librae and showed no microvariability durning any of the nights.College of Arts and ScienceDepartment of Physics and Astronom
AP-based wireless intrusion detection systems
No full textThis thesis was scanned from the print manuscript for digital preservation and is copyright the author.
Researchers can access this thesis by asking their local university, institution or public library to
make a request on their behalf. Monash staff and postgraduate students can use the link in the References field
Recommended from our members
The HIV-1 Protein Nef Utilizes AP Complexes and other Sorting Proteins to Downregulate CD4 and MHC-I
No full textHIV-1 (human immunodeficiency virus-1) is a retrovirus that has affected millions of people. Effective therapies allow patients to live for decades by suppressing viral replication, yet there is no vaccine or cure. The HIV-1 protein Nef increases replication fitness by downregulating the receptors, CD4 and MHC-I, on the cell surface of infected CD4+ T cells to evade the immune system. It also enhances viral replication competence by a multifaceted mechanism. Nef utilizes host adaptor protein (AP) complexes, mostly AP-1 and AP-2, to modulate and form membrane vesicles within the cell, reducing CD4 and MHC-I at the cell surface. CD4 would be reduced by endocytosis and MHC-I would be reduced by decreasing transport to the cell surface. Nef also causes the degradation of these proteins in lysosomes through more vesicle-mediated lysosomal trafficking, but it is unclear whether Nef utilizes AP-3 and other sorting proteins, such as the ESCRT-related (Endosomal Sorting Complexes Required for Transport) proteins PTPN23 and ALIX, which support vesicular transport to lysosomes and with which Nef reportedly interacts. In this thesis work, the roles of AP-1, AP-2, AP-3, PTPN23, and ALIX in Nef-mediated downregulation and degradation of CD4 and MHC-I were determined by knocking down these proteins in both non-Nef expressing (CEM) and Nef-expressing (CEM4B) CD4+ T cells and observing how MHC-I and CD4 levels were affected. The CEM knockdown cells were also infected with HIV-1 to assess surface downregulation of MHC-I and CD4 during viral replication and to determine if these proteins have roles in supporting viral replication, taking care to assess the growth rate of the cells themselves. The findings confirmed that AP-1 is utilized for Nef-mediated MHC-I downregulation, while AP-2 utilized for Nef-mediated CD4 downregulation. However, AP-3, ALIX and PTPN23 did not appear to play a substantial role in Nef-mediated downregulation of MHC-I or CD4. Infection of the CEM knockdown cells with HIV-1 showed that AP-2 and PTPN23 are needed for efficient viral replication. Knockdown of AP-2 reproducibly affected cell growth, whereas the effect of PTPN23 knockdown on cell growth was less certain. These results support AP-1, AP-2, and PTPN23 as possible targets for therapeutic interventions
Environmental toxicity, redox signaling and lung inflammation:the role of glutathione
No full textGlutathione (gamma-glutamyl-cysteinyl-glycine, GSH) is the most abundant intracellular antioxidant thiol and is central to redox defense during oxidative stress. GSH metabolism is tightly regulated and has been implicated in redox signaling and also in protection against environmental oxidant-mediated injury. Changes in the ratio of the reduced and disulfide form (GSH/GSSG) can affect signaling pathways that participate in a broad array of physiological responses from cell proliferation, autophagy and apoptosis to gene expression that involve H(2)O(2) as a second messenger. Oxidative stress due to oxidant/antioxidant imbalance and also due to environmental oxidants is an important component during inflammation and respiratory diseases such as chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, acute respiratory distress syndrome, and asthma. It is known to activate multiple stress kinase pathways and redox-sensitive transcription factors such as Nrf2, NF-kappaB and AP-1, which differentially regulate the genes for pro-inflammatory cytokines as well as the protective antioxidant genes. Understanding the regulatory mechanisms for the induction of antioxidants, such as GSH, versus pro-inflammatory mediators at sites of oxidant-directed injuries may allow for the development of novel therapies which will allow pharmacological manipulation of GSH synthesis during inflammation and oxidative injury. This article features the current knowledge about the role of GSH in redox signaling, GSH biosynthesis and particularly the regulation of transcription factor Nrf2 by GSH and downstream signaling during oxidative stress and inflammation in various pulmonary diseases. We also discussed the current therapeutic clinical trials using GSH and other thiol compounds, such as N-acetyl-l-cysteine, fudosteine, carbocysteine, erdosteine in environment-induced airways disease
- …
