Linear time algorithm for quantum 2SAT

A canonical result about satisfiability theory is that the 2-SAT problem can be solved in linear time, despite the NP-hardness of the 3-SAT problem. In the quantum 2-SAT problem, we are given a family of 2-qubit projectors $\Pi_{ij}$ on a system of $n$ qubits, and the task is to decide whether the Hamiltonian $H=\sum \Pi_{ij}$ has a 0-eigenvalue, or it is larger than $1/n^\alpha$ for some $\alpha=O(1)$. The problem is not only a natural extension of the classical 2-SAT problem to the quantum case, but is also equivalent to the problem of finding the ground state of 2-local frustration-free Hamiltonians of spin $\frac{1}{2}$, a well-studied model believed to capture certain key properties in modern condensed matter physics. While Bravyi has shown that the quantum 2-SAT problem has a classical polynomial-time algorithm, the running time of his algorithm is $O(n^4)$. In this paper we give a classical algorithm with linear running time in the number of local projectors, therefore achieving the best possible complexity.Comment: 20 page

Utilizing Genetically Engineered Mouse Models of Pancreatic Cancer: Evaluating the Role of Cathepsin B and the Efficacy of Farnesyl Thiosalicylic Acid

I have utilized genetically engineered mouse models of pancreatic cancer to identify a potential new therapeutic target, and to test the efficacy of a putative ras inhibitor. In the first part, I show that cathepsin B is upregulated during disease progression in the mouse pancreas, as is overall cathepsin activity. Loss of cathepsin B decreases preinvasive disease burden and imparts a significant survival benefit, with a consistent decrease in proliferation. In addition, lack of cathepsin B also decreases the burden of liver metastasis. Phospho-Erk localization appears to be affected by cathepsin B loss, which may account for the defect in proliferation. Cathepsin B null tumours also have increased active cathepsin L, which may compensate for cathepsin B in tumour progression and metastasis. Finally, a cysteine protease inhibitor in combination with gemcitabine confers a significant increase in survival in tumour-bearing mice. In the second part of this work, I have investigated the effect of farnesylthiosalicylic acid (FTS) in pancreatic tumour-bearing mice. In combination with gemcitabine, FTS significantly increases survival and decreases tumour kinetics and proliferation, and inhibits liver metastasis. Although FTS has previously been reported as a ras inhibitor, there is no evidence of modulation of ras activity or signaling in primary tumours after long-term or short-term intervention, or in liver metastases. In short, the therapeutic effects of FTS in this mouse model of pancreatic cancer do not appear to be ras-related, and the target of FTS remains to be elucidated

Hypoplastic amelogenesis imperfecta with multiple impacted teeth: report of two cases

Amelogenesis Imperfecta (AI) represents a group of developmental conditions, genomic in origin, which affect the structure and clinical appearance of enamel of all or nearly all the teeth in a more or less equal manner. It is usually inherited either as an X-linked, autosomal dominant or autosomal recessive trait. The enamel may be hypoplastic, hypomineralised or both and affected teeth may be discolored, sensitive or prone to disintegration. Diagnosis is based on the family history, pedigree plotting and meticulous clinical observation. The treatment of patients with AI should start with early diagnosis and intervention to prevent latter restorative problems. Herein, we present two case reports of hypoplastic amelogenesis imperfecta with oligodontia, multiple unerupted teeth, pulpal calcification, taurodontism and anterior deep bite who were provided with functional and esthetic rehabilitation

Regulation of B cell response to respiratory viruses

Viruses replicating in the respiratory tract (RT) triggers a wide- range of cytokines and chemokines that have antiviral and pro-inflammatory features, instigating an efficient virus- specific B and T cell response that aids in virus- clearance. The majority of antibody secreting cells (ASCs) localizing in the upper RT secrete IgA that can effectively neutralize viruses. In addition, elements of B cell memory are generated that can provide protection from re-infection. Studies examining these aspects, following murine gammaherpesvirus 68 (MHV-68) infection comprise chapter 2 of the dissertation work. Our studies demonstrate that following MHV-68 infection, unlike influenza infection, resulted in a generalized deficiency of virus-specific IgA induction and deficient B cell memory establishment in the respiratory tract. The studies indicate that these aspects of B cell response are regulated by features of virus- replication in the RT. These studies lead to the speculation that these features of B cell response may represent an evolutionary adaptation of viruses that establish long-term latency and are transmitted periodically after reactivation and shedding in secretions. Following cognate interactions with CD4+ T cells, the B cells undergo proliferation, isotype-switching and differentiate towards extrafollicular (low affinity, rapid) or germinal center pathway (high affinity). It is not clear what factors regulate these pathways of B cell differentiation, especially in the context of virus infection in the RT. Studies examining these aspects following influenza infection comprise chapter 3 of the dissertation work. Our studies establish a model for the investigation of host and viral factors that modulate the quality and effectiveness of the B cell response to influenza infection. The findings indicate that the strength of the extrafollicular B cell response depends on the nature of the infecting virus. We present evidence that this pathway of rapid antiviral antibody production relates to the production of non-specifically acting factors in the lung and also dependent of the cytokine profile of virus-specific CD4+T cells. In summary, the current dissertation findings point out to an influence of virus and host associated factors in regulating features of B cell response in the RT

Real-Time Deep Learning-Based Face Recognition System

This research proposes Real-time Deep Learning-based Face recognition algorithms using MATLAB and Python. Generally, Face recognition is defined as the process through which people are identified using facial images. This technology is applied broadly in biometrics, security information, accessing controlled areas, etc. The facial recognition system can be built by following two steps. In the first step, the facial features are picked up or extracted, then the second step involves pattern classification. Deep learning, specifically the convolutional neural network (CNN), has recently made more progress in face recognition technology. Convolution Neural Network is one among the Deep Learning approaches and has shown excellent performance in many fields, such as image recognition of a large amount of training data (such as ImageNet). However, due to hardware limitations and insufficient training datasets, high performance is not achieved. Therefore, in this work, the Transfer Learning method is used to improve the performance of the face-recognition system even for a smaller number of images. For this, two pre-trained models, namely, GoogLeNet CNN (in MATLAB) and FaceNet (in Python) are used. Transfer learning is used to perform fine-tuning on the last layer of CNN model for new classification tasks. FaceNet presents a unified system for face verification (is this the same person?), recognition (who is this person?) and clustering (finds common people among these faces) using the method based on learning a Euclidean embedding per image using a deep convolutional network

The Eco Office: Dynamic and Homeostatic Facades inspired by BIOMORPHIM, BIOMIMICRY, and BIOPHILIA

"Come forth into the light of things, Let Nature be your teacher.” ~ William Wordsworth The focus of this dissertation research is to extend and increase an understanding of sustainable building envelope design strategies, with specific focus on transfer of light, air, and heat, within a tropical site setting/context. Biomimetic architecture is a process that is primarily driven by inspiration from natural systems and organisms. Designs and patterns found in nature are often resolved at the “macro” as well as at the “micro/nano” molecular levels, which prompts further investigation into present-day advancements in material science and nanotechnological concepts. Nanotechnology is a way of looking closer at systems and material structures and properties; the translation from biomimetic architecture to the nano-molecular scale of materials thus promotes sustainability in buildings, by providing ways and means to incorporate new technologies and novel material systems into the architectural design of building facades, that will further aid with the successful implementation of passive design strategies, in order to establish comfortable interior lighting, ventilation, and thermal conditions. Extensive literature reviews and material research are utilized for the bio-tonano design process and analyses. Performance of design modules created has been tested using design simulations and reiterative analysis processes. “Taking cues from Nature – creation of responsive (environment and human responsive) architecture” – is the idea that is the primary motivation behind the research focus. The key goal of this research is to propose alternative futures in building envelope design, for a site in Honolulu, which would serve as a digital prototype for similar such investigations into integrating nature-inspired macro and nanotechnology structures and materials into building systems design. Psychophysiology (the mind-body-interaction) and experimental testing is used as part of the final testing and analysis, to assess people’s responses to nature-inspired design and emerging building technologies