A DWT based perceptual video coding framework: concepts, issues and techniques

The work in this thesis explore the DWT based video coding by the introduction of a novel DWT (Discrete Wavelet Transform) / MC (Motion Compensation) / DPCM (Differential Pulse Code Modulation) video coding framework, which adopts the EBCOT as the coding engine for both the intra- and the inter-frame coder. The adaptive switching mechanism between the frame/field coding modes is investigated for this coding framework. The Low-Band-Shift (LBS) is employed for the MC in the DWT domain. The LBS based MC is proven to provide consistent improvement on the Peak Signal-to-Noise Ratio (PSNR) of the coded video over the simple Wavelet Tree (WT) based MC. The Adaptive Arithmetic Coding (AAC) is adopted to code the motion information. The context set of the Adaptive Binary Arithmetic Coding (ABAC) for the inter-frame data is redesigned based on the statistical analysis. To further improve the perceived picture quality, a Perceptual Distortion Measure (PDM) based on human vision model is used for the EBCOT of the intra-frame coder. A visibility assessment of the quantization error of various subbands in the DWT domain is performed through subjective tests. In summary, all these findings have solved the issues originated from the proposed perceptual video coding framework. They include: a working DWT/MC/DPCM video coding framework with superior coding efficiency on sequences with translational or head-shoulder motion; an adaptive switching mechanism between frame and field coding mode; an effective LBS based MC scheme in the DWT domain; a methodology of the context design for entropy coding of the inter-frame data; a PDM which replaces the MSE inside the EBCOT coding engine for the intra-frame coder, which provides improvement on the perceived quality of intra-frames; a visibility assessment to the quantization errors in the DWT domain

Towards Computational Efficiency of Next Generation Multimedia Systems

To address throughput demands of complex applications (like Multimedia), a next-generation system designer needs to co-design and co-optimize the hardware and software layers. Hardware/software knobs must be tuned in synergy to increase the throughput efficiency. This thesis provides such algorithmic and architectural solutions, while considering the new technology challenges (power-cap and memory aging). The goal is to maximize the throughput efficiency, under timing- and hardware-constraints

Proceedings, MSVSCC 2014

Proceedings of the 8th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 17, 2014 at VMASC in Suffolk, Virginia

Deep Model for Improved Operator Function State Assessment

A deep learning framework is presented for engagement assessment using EEG signals. Deep learning is a recently developed machine learning technique and has been applied to many applications. In this paper, we proposed a deep learning strategy for operator function state (OFS) assessment. Fifteen pilots participated in a flight simulation from Seattle to Chicago. During the four-hour simulation, EEG signals were recorded for each pilot. We labeled 20- minute data as engaged and disengaged to fine-tune the deep network and utilized the remaining vast amount of unlabeled data to initialize the network. The trained deep network was then used to assess if a pilot was engaged during the four-hour simulation

In vitro and in vivo studies of a DNA repair protein upon DNA alkylation damage

Studio approfondito sulle Agt di tre diversi organismi da tre diversi regni: archea, procarioti ed eucarioti. Ponendo l'attenzione sull'attività, sulla stabilità intrinseca, sull'instabilità post-alchilazione e sul possibile ruolo in vivo nell'organismo modello C. elegans. In fine si propone come un utile tool biotecnologico

52nd Rocky Mountain Conference on Analytical Chemistry

Final program, abstracts, and information about the 52nd annual meeting of the Rocky Mountain Conference on Analytical Chemistry, co-endorsed by the Colorado Section of the American Chemical Society and the Society for Applied Spectroscopy. Held in Snowmass, Colorado, August 1-5, 2010

Analiza porównawcza własności fizycznych miejsc wiązania antybiotyków aminoglikozydowych w RNA i białkach

Aminoglycoside antibiotics have been in use for more than 60 years, helping combat severe bacterial infections. Due to this long time of usage, more and more bacteria become resistant to one or several drugs from this group. This spread of resistant species is alarming and additionally, there is little knowledge about the mechanisms of bacterial resistance. In order to broaden our understanding of how bacteria combat aminoglycosides, we performed computer simulations of various molecules that bind aminoglycosides in a bacterial cell: (i) the primary binding site, called the A-site and located in ribosomal RNA, wild type and with mutations that decrease the aminoglycoside binding affinity; and (ii) the aminoglycoside modifying enzymes (AMEs), which are produced by bacteria to inactivate these drugs. The mutations of the RNA A-site were chosen based on previous experimental studies on whole bacteria. These studies showed that even single base substitutions were sufficient to make bacteria resistant, but did not explain how this resistance was gained on an atomic level. There are many AMEs and they vary a lot among themselves, yet they all have a narrow specificity towards aminoglycosides, which are quite homogeneous group. The two main questions we have posed in our research are: (i) what are the physical grounds of bacteria becoming less susceptible to aminoglycosides due to RNA A-site mutations; and (ii) how different AMEs attract aminoglycosides and interact with them? We performed all-atom molecular dynamics (MD) simulations of the A-site model with selected mutations and of AME representatives. In addition, the complexes of these biomolecules with aminoglycosides were simulated. For comparison, we also performed simulations of the wild type A-site model and of the aminoglycosides in water. We used various biophysical methods to analyze these simulations and to study: internal dynamics of the biomolecules; electrostatic potential, shape, and volume of the binding pockets; types of interactions with aminoglycosides; and changes in conformations of aminoglycosides. In addition, we developed and implemented an algorithm that helps describe molecular motions. We found that different A-site mutations affect different features of the RNA binding site. Some of them changed the mobility of the nucleic bases, and therefore the shape of the A-site was altered. Other mutations changed the electrostatic potential inside the binding site, thus making it almost unrecognizable to aminoglycosides. The study of AMEs showed that apart from their structural and sequence-related diversity, they differ in the internal movement patterns. However, these enzymes interact with aminoglycosides very similarly, using mainly electrostatic interactions. Interestingly, we noticed that these interactions were copied from the RNA:aminoglycoside complex. Our findings were in agreement with experimental studies and also helped to explain some of their outcomes. The results presented in this dissertation may help design new antibiotics that would overcome the bacterial resistance.Od ponad 60 lat antybiotyki aminoglikozydowe są z powodzeniem stosowane w szpitalach przeciwko ciężkim infekcjom bakteryjnym. Jednak pojawianie się coraz większej liczby przypadków bakterii opornych na stosowane aminoglikozydy sprawia, że badania mechanizmów oporności u bakterii stają kluczowe w dalszej skutecznej walce z infekcjami tego typu. Przeprowadziłam komputerowe symulacje biomolekuł, które oddziałują z antybiotykami aminoglikozydowymi we wnętrzu komórek bakteryjnych. Badanymi obiektami są: (i) główne miejsce wiązania aminoglikozydów, zwane miejscem A, w rybosomalnym RNA; natywne oraz z mutacjami powodującymi wzrost oporności u bakterii; a także (ii) enzymy modyfikujące aminoglikozydy (ang. aminoglycoside modifying enzymes, AME}), produkowane przez bakterie w celu chemicznej dezaktywacji tych leków. Motywacją do badań nad zmutowanym miejscem A był brak informacji o zmianach jakie zachodzą w fizycznych własnościach miejsca A po różnych zamianach nukleotydów. Wiadomo jakie mutacje prowadzą do oporności oraz że nawet pojedyncze zamiany nukleotydu mogą mieć bardzo wymierne skutki, ale nie wyjaśniono jakie są tego podstawy. Natomiast, w przypadku AME, celem prowadzenia symulacji było wyjaśnienie w jaki sposób ta grupa białek jest w stanie być jednocześnie bardzo zróżnicowana i wysoce specyficzna względem aminoglikozydów. Przeprowadziłam symulacje dynamiki molekularnej (MD) modelu miejsca A z wybranymi mutacjami oraz reprezentatywnych enzymów z trzech największych rodzin AME. Aby uzyskać opis oddziaływań między tymi miejscami wiążącymi a aminoglikozydami, przeprowadziłam również symulacje MD tych biomolekuł w kompleksach z wybranymi antybiotykami. W celu analizy symulacji użyłam metodologii z zakresu biofizyki teoretycznej. Badałam wiele własności fizykochemicznych wybranych biomolekuł i ich kompleksów, m.in.: dynamikę wewnętrzną, własności elektrostatyczne, kształt i objętość miejsc wiązania aminoglikozydów, a także rodzaje oddziaływań z aminoglikozydami. Ponadto, stworzyłam nową metodę analizy zmian konformacyjnych w molekułach, która dokonuje podziału biomolekuł na tzw. dynamiczne domeny, na podstawie danych pochodzących z symulacji lub eksperymentów. Z analizy symulacji rybosomalnego miejsca A wynika, że mutacje różnych zasad wpływają na różne własności fizyczne tego fragmentu RNA. W zależności od położenia mutowanej zasady, zmieniał się rozkład ładunków cząstkowych w miejscu wiążącym lub kształt tego miejsca. Mutacje wpływały również na dynamikę ruchów wewnętrznych miejsca A. Analiza symulacji cząsteczek AME wskazała, że oprócz różnorodności struktur trzeciorzędowych i sekwencji, występuje w tej grupie również różnorodność w ruchach wewnętrznych. Pomimo tych różnic, wszystkie enzymy oddziaływały z aminoglikozydami w bardzo podobny sposób, głównie elektrostatycznie. Ponadto, te oddziaływania wydają się być kopiowane z kompleksów, jakie aminoglikozydy tworzą z miejscem A. Rezultaty moich badań są zgodne z poprzednimi doniesieniami eksperymentalnymi, a także pomagają wyjaśnić niektóre z nich. Wyniki opisane w tej pracy mogą być podstawą do zaprojektowania zmodyfikowanych aminoglikozydów, które mogłyby być aktywne nawet wobec opornych bakterii

Advanced Computational Methods for Oncological Image Analysis

[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.

Proteomics of bacteroides fragilis and enterobacter cancerogenus

Bacteroides fragilis NCTC 9343 is a Gram-negative anaerobic bacterium with genomic DNA of 5205 Kb and a GC ratio of 43%. It is a commensal organism that can act as an opportunistic pathogen and is commonly present on the mucous membranes. It causes a variety of infections including intra abdominal infections, perirectal abscesses and decubitus ulcers. Enterotoxigenic forms are capable of causing diarrhoea in children and animals. Enterobacter cancerogenus ATCC 35316 is also a Gram-negative facultatively anaerobic bacterium with genomic DNA of 4602 Kb and a GC ratio of 55%. It is a naturally occurring human gut symbiont known to exhibit resistance to antibiotics like aminopenicillins. It has also been reported in cases of severe osteomyelitis and infections of bones and joints. This study aims to analyse the differential expression of proteins in the presence of mucin since it serves as the first site of adherence for the bacteria. The E. cancerogenus and B. fra gilis proteins were extracted and separated by two dimensional electrophoresis from logarithmic phase cultures grown in semi-defined media enriched with or without porcine gastric mucin Types II and III. The gel images were analysed using Bio-Rad PDQuest, Ludesi Redfin and Nonlinear Dynamics SameSpots softwares. It was observed that the presence of mucin in the media affected the expression of a number of proteins in E. cancerogenus and B. fragilis cells. The protein spots of interest were excised, hydrolysed using trypsin and subjected to electrospray ionisation based LC-MS analysis in order to determine the identity of the digested proteins and obtain a better understanding of the interactions of B. fra gilis and E. cancero genus with mucin. The outer membrane protein surface antigen X was found to be up-regulated in both mucin Type II and III enriched media in E. cancerogenus. Some of the other proteins that were differentially regulated in both E. cancerogenus and B. fra gilis included the elongation factor Ts, malate dehydrogenase, triose phosphate isomerase and thiol peroxidase proteins indicating that these proteins may be associated with the ability of bacteria to grow in mucin and may be potential virulence factors. Genes encoding the proteins CAH06598 and CAH09443 from the glycoside hydrolase families 95 and 97 in B. fra gilis strain NCTC9343 were cloned, overexpressed and purified using nickel affinity and gel filtration chromatography. The enzymes were found to be active by performing fluorimetric assays using methyl-umbelliferyl sugar substrates. Diffracting crystals of CAH09443 were obtained from the PACT ANION screens containing polyethylene glycol and sodium malonate as a precipitant. Structure determination was achieved via molecular replacement using the glycoside hydrolase Family 97 α-galactosidase, BtGH97b, from Bacteroides thetaiotaomicron as a starting model. The structure of CAH09443 was shown to be composed of a N-terminal β-super-sandwich domain and a canonical (β/α)₈ barrel, similar to the two other glycoside hydrolase family 97 enzyme structures reported