Doctor of Philosophy

dissertationWith the spread of internet and mobile devices, transferring information safely and securely has become more important than ever. Finite fields have widespread applications in such domains, such as in cryptography, error correction codes, among many others. In most finite field applications, the field size - and therefore the bit-width of the operands - can be very large. The high complexity of arithmetic operations over such large fields requires circuits to be (semi-) custom designed. This raises the potential for errors/bugs in the implementation, which can be maliciously exploited and can compromise the security of such systems. Formal verification of finite field arithmetic circuits has therefore become an imperative. This dissertation targets the problem of formal verification of hardware implementations of combinational arithmetic circuits over finite fields of the type F2k . Two specific problems are addressed: i) verifying the correctness of a custom-designed arithmetic circuit implementation against a given word-level polynomial specification over F2k ; and ii) gate-level equivalence checking of two different arithmetic circuit implementations. This dissertation proposes polynomial abstractions over finite fields to model and represent the circuit constraints. Subsequently, decision procedures based on modern computer algebra techniques - notably, Gr¨obner bases-related theory and technology - are engineered to solve the verification problem efficiently. The arithmetic circuit is modeled as a polynomial system in the ring F2k [x1, x2, · · · , xd], and computer algebrabased results (Hilbert's Nullstellensatz) over finite fields are exploited for verification. Using our approach, experiments are performed on a variety of custom-designed finite field arithmetic benchmark circuits. The results are also compared against contemporary methods, based on SAT and SMT solvers, BDDs, and AIG-based methods. Our tools can verify the correctness of, and detect bugs in, up to 163-bit circuits in F2163 , whereas contemporary approaches are infeasible beyond 48-bit circuits

Unlocking Insights: Semantic Search in Jupyter Notebooks

Semantic search, a process aimed at delivering highly relevant search results by comprehending the searcher's intent and the contextual meaning of terms within a searchable dataspace, plays a pivotal role in information retrieval. In this paper, we investigate the application of large language models to enhance semantic search capabilities, specifically tailored for the domain of Jupyter Notebooks. Our objective is to retrieve generated outputs, such as figures or tables, associated functions and methods, and other pertinent information. We demonstrate a semantic search framework that achieves a comprehensive semantic understanding of the entire notebook's contents, enabling it to effectively handle various types of user queries. Key components of this framework include: 1). A data preprocessor is designed to handle diverse types of cells within Jupyter Notebooks, encompassing both markdown and code cells. 2). An innovative methodology is devised to address token size limitations that arise with code-type cells. We implement a finer-grained approach to data input, transitioning from the cell level to the function level, effectively resolving these issues

Unlocking Insights: Semantic Search in Jupyter Notebooks

Semantic search, a process aimed at delivering highly relevant search results by comprehending the searcher's intent and the contextual meaning of terms within a searchable dataspace, plays a pivotal role in information retrieval. In this paper, we investigate the application of large language models to enhance semantic search capabilities, specifically tailored for the domain of Jupyter Notebooks. Our objective is to retrieve generated outputs, such as figures or tables, associated functions and methods, and other pertinent information. In this study, we demonstrate a semantic search framework that achieves a comprehensive semantic understanding of the entire notebook's contents, enabling it to effectively handle various types of user queries. Key components of this framework include: 1). A data preprocessor is designed to handle diverse types of cells within Jupyter Notebooks, encompassing both markdown and code cells. 2). An innovative methodology is devised to address token size limitations that arise with code-type cells. We implement a finer-grained approach to data input, transitioning from the cell level to the function level, effectively resolving these issues

Signal Timing Optimization to Improve Air Quality

This study develops an optimization methodology for signal timing at intersections to reduce emissions based on MOVES, the latest emission model released by U.S. Environmental Protection Agency (EPA). The primary objective of this study is to bridge the gap that the research on signal optimization at intersections lags behind the development of emissions models. The methodology development includes four levels: the vehicle level, the movement level, the intersection level, and the arterial level. At the vehicle level, the emission function with respect to delay is derived for a vehicle driving through an intersection. Multiple acceleration models are evaluated, and the best one is selected in terms of emission estimations at an intersection. Piecewise functions are used to describe the relationship between emissions and intersection delay. At the movement level, emissions are modeled if the green time and red time of a movement are given. To account for randomness, the number of vehicle arrivals during a cycle is assumed to follow Poisson distributions. According to the numerical results, the relative difference of emission estimations with and without considering randomness is usually smaller than 5.0% at a typical intersection of two urban arterials. At the intersection level, an optimization problem is formulated to consider emissions at an intersection. The objective function is a linear combination of delay and emissions at an intersection, so that the tradeoff between the two could be examined with the optimization problem. In addition, a convex approximation is proposed to approximate the emission calculation; accordingly, the optimization problem can be solved more efficiently using the interior point algorithm (IPA). The case study proves that the optimization problem with this convex approximation can still find appropriate optimal signal timing plans when considering traffic emissions. At the arterial level, emissions are minimized at multiple intersections along an arterial. First, discrete models are developed to describe the bandwidth, stops, delay, and emissions at a particular intersection. Second, based on these discrete models, an optimization problem is formulated with the intersection offsets as decision variables. The simulation results indicate that the benefit of emission reduction become more and more significant as the number of intersections along the arterial increases

DialoGPS: Dialogue Path Sampling in Continuous Semantic Space for Data Augmentation in Multi-Turn Conversations

In open-domain dialogue generation tasks, contexts and responses in most datasets are one-to-one mapped, violating an important many-to-many characteristic: a context leads to various responses, and a response answers multiple contexts. Without such patterns, models poorly generalize and prefer responding safely. Many attempts have been made in either multi-turn settings from a one-to-many perspective or in a many-to-many perspective but limited to single-turn settings. The major challenge to many-to-many augment multi-turn dialogues is that discretely replacing each turn with semantic similarity breaks fragile context coherence. In this paper, we propose DialoGue Path Sampling (DialoGPS) method in continuous semantic space, the first many-to-many augmentation method for multi-turn dialogues. Specifically, we map a dialogue to our extended Brownian Bridge, a special Gaussian process. We sample latent variables to form coherent dialogue paths in the continuous space. A dialogue path corresponds to a new multi-turn dialogue and is used as augmented training data. We show the effect of DialoGPS with both automatic and human evaluation.Comment: ACL 2023 mai

The construction of a prognostic model of cervical cancer based on four immune-related LncRNAs and an exploration of the correlations between the model and oxidative stress

Introduction: The immune-related lncRNAs (IRLs) are critical for the development of cervical cancer (CC), but it is still unclear how exactly ILRs contribute to CC. In this study, we aimed to examine the relationship between IRL and CC in detail.Methods: First, the RNAseq data and clinical data of CC patients were collected from The Cancer Genome Atlas (TCGA) database, along with the immune genes from the Import database. We used univariate cox and least absolute shrinkage and selection operator (lasso) to obtain IRLs for prediction after screening the variables. According to the expression levels and risk coefficients of IRLs, the riskscore were calculated. We analyzed the relationship between the model and oxidative stress. We stratified the risk model into two as the high and low-risk groups. We also evaluated the survival differences, immune cell differences, immunotherapeutic response differences, and drug sensitivity differences between the risk groups. Finally, the genes in the model were experimentally validated.Results: Based on the above analyses, we further selected four IRLs (TFAP2A.AS1, AP000911.1, AL133215.2, and LINC02078) to construct the risk model. The model was associated with oxidative-stress-related genes, especially SOD2 and OGG1. Patients in the high-risk group had a lower overall survival than those in the low-risk group. Riskscore was positively correlated with resting mast cells, neutrophils, and CD8+ T-cells. Patients in the low-risk group showed a greater sensitivity to immunosuppression therapy. In addition, we found that patients with the PIK3CA mutation were more sensitive to chemotherapeutic agents such as dasatinib, afatinib, dinaciclib and pelitinib. The function of AL133215.2 was verified, which was consistent with previous findings, and AL133215.2 exerted a pro-tumorigenic effect. We also found that AL133215.2 was closely associated with oxidative-stress-related pathways.Discussion: The results suggested that risk modeling might be useful for prognosticating patients with CC and opening up new routes for immunotherapy

A New Digital to Analog Converter Based on Low-Offset Bandgap Reference

This paper presents a new 12-bit digital to analog converter (DAC) circuit based on a low-offset bandgap reference (BGR) circuit with two cascade transistor structure and two self-contained feedback low-offset operational amplifiers to reduce the effects of offset operational amplifier voltage effect on the reference voltage, PMOS current-mirror mismatch, and its channel modulation. A Start-Up circuit with self-bias current architecture and multipoint voltage monitoring is employed to keep the BGR circuit working properly. Finally, a dual-resistor ladder DAC-Core circuit is used to generate an accuracy DAC output signal to the buffer operational amplifier. The proposed circuit was fabricated in CSMC 0.5 μm 5 V 1P4M process. The measured differential nonlinearity (DNL) of the output voltages is less than 0.45 LSB and integral nonlinearity (INL) less than 1.5 LSB at room temperature, consuming only 3.5 mW from a 5 V supply voltage. The DNL and INL at −55°C and 125°C are presented as well together with the discussion of possibility of improving the DNL and INL accuracy in future design

Influence of high-definition transcranial direct current stimulation to the parietal cortex on postural control: a single-blind randomized crossover study

BackgroundThe parietal lobe is an important cerebral cortex area for sensory information processing to maintain postural control. High-definition transcranial direct current stimulation (HD-tDCS) can improve the excitability of the target brain region. The purpose of this study was to investigate whether HD-tDCS applied to either unilateral or bilateral parietal lobes would improve postural control.MethodA single-blind randomized crossover experimental design was used. 18 healthy right-handed adults were recruited for unilateral and bilateral HD-tDCS, as well as sham stimulation. All participants completed the sensory organization test (SOT) and motor control test (MCT) under eyes open and eyes closed conditions before and immediately after each intervention. The equilibrium score (ES), composite score (CS), and sensory score (VIS, SOM, VEST, PREF) from SOT, along with latency and response strength from the MCT, were calculated. Two-way repeated measures analyses of variance (ANOVAs) were used for the dependent variables. Bonferroni’s post hoc tests were used in case of significant ANOVA results.ResultsThe composite latency increased significantly after right (p = 0.025) and bilateral (p = 0.004) stimulation under eyes open condition. When the balance plate moved large forward, the latency increased significantly after left (p = 0.003) and bilateral (p = 0.04) stimulation under eyes closed condition. For response strength, when the balance plate moved forward at different magnitude under eyes closed condition, they all decreased significantly after bilateral stimulation (p < 0.05).ConclusionThe parietal lobe participates in the modulation of automatic postural response. The primary function of the right parietal lobe in postural response is to process visual information, while the left is responsible for processing somatosensory information

Immunotherapy rechallenge after ICI-related pneumonitis in lung cancer patients: a retrospective cohort study

BackgroundImmune checkpoint inhibitors (ICIs) have significant advantages in treating lung cancer due to their low toxicity and high efficacy. However, adverse events, especially ICI-related pneumonitis (CIP), may restrict their applicability. CIP not only impairs patients’ lung function but also carries a 35% mortality rate, thereby restricting ICIs rechallenge. As information is limited on the efficacy and safety of ICIs rechallenge, these issues were assessed in the present study.MethodsThe data on 2673 patients who underwent ICI therapy at the First Affiliated Hospital of Zhejiang University between 2019 and 2023 were reviewed, identifying 106 patients with CIP who were allocated to rechallenge, non-discontinuation, and permanent discontinuation groups. Baseline information was collected, including sex, age, staging, pathological type, medication details, and underlying diseases, along with treatment status post-CIP occurrence, re-challenge of ICIs, and data on disease progression and mortality. The clinical studies examined the efficacy of treatments by assessing progression-free survival (PFS) and overall survival (OS) as key indicators.ResultsNo significant difference in CIP onset time was observed between grades 1–2 and 3–4 (P = 0.99), CIP was found to occur most frequently 5.17 months after treatment initiation (95%CI 4.61-5.72). The likelihood of CIP recurrence or progression while continuing ICI treatment was 50% (15/30). Patients who resumed ICI treatment and did not cease taking the medication showed markedly improved outcomes relative to those who permanently discontinued treatment, with a 6-month longer mPFS (13.67 vs. 7.90 months, P<0.001) and a twofold increase in mOS (33.77 vs. 13.23 months, P=0.002).ConclusionsThe outcomes of patients with CIP were found to be contingent upon rechallenge or continuation of ICIs. Contrary to the belief that an earlier restart is always better, decisions to reinitiate ICIs should be based on the improvement of symptoms and radiographic findings

Large-scale statistical mapping of T-cell receptor β sequences to human leukocyte antigens

IntroductionT-cell receptors (TCRs) interacting with peptides presented by human leukocyte antigens (HLAs) are the foundation of the adaptive immune system, but population-level analysis of TCR–HLA interactions is lacking.MethodsWe statistically associated approximately 106 public TCRβs to specific HLAs using TCRβ repertoires sampled from 4,144 HLA-genotyped subjects. The TCRβs we associated were specific to unique HLA allotypes, not allelic groups, and to the paired α–β heterodimer of class II HLAs, though exceptions were observed.ResultsThis specificity permitted highly accurate imputation of 248 class I and II HLAs from the TCRβ repertoire. Notably, 45 HLA-DP and -DQ heterodimers lacked associated TCRs because they likely arise from non-functional trans-complementation. The public class I and II HLA-associated TCRβs we identified were primarily expressed on CD8+ and CD4+ memory T cells, respectively, which were responding to various common antigens.DiscussionOur results recapitulate fundamental biology, provide insights into the functionality of HLAs, and demonstrate the power and potential of population-level TCRβ repertoire sequencing