CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering

Visual Question Answering (VQA) is a multi-discipline research task. To produce the right answer, it requires an understanding of the visual content of images, the natural language questions, as well as commonsense reasoning over the information contained in the image and world knowledge. Recently, large-scale Vision-and-Language Pre-trained Models (VLPMs) have been the mainstream approach to VQA tasks due to their superior performance. The standard practice is to fine-tune large-scale VLPMs pre-trained on huge general-domain datasets using the domain-specific VQA datasets. However, in reality, the application domain can change over time, necessitating VLPMs to continually learn and adapt to new domains without forgetting previously acquired knowledge. Most existing continual learning (CL) research concentrates on unimodal tasks, whereas a more practical application scenario, i.e, CL on cross-domain VQA, has not been studied. Motivated by this, we introduce CL-CrossVQA, a rigorous Continual Learning benchmark for Cross-domain Visual Question Answering, through which we conduct extensive experiments on 4 VLPMs, 4 CL approaches, and 5 VQA datasets from different domains. In addition, by probing the forgetting phenomenon of the intermediate layers, we provide insights into how model architecture affects CL performance, why CL approaches can help mitigate forgetting in VLPMs to some extent, and how to design CL approaches suitable for VLPMs in this challenging continual learning environment. To facilitate future work on CL for cross-domain VQA, we will release our datasets and code.Comment: 10 pages, 6 figure

Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance

Phenotypic plasticity is associated with non-genetic drug tolerance in several cancers. Such plasticity can arise from chromatin remodeling, transcriptomic reprogramming, and/or protein signaling rewiring, and is characterized as a cell state transition in response to molecular or physical perturbations. This, in turn, can confound interpretations of drug responses and resistance development. Using BRAF-mutant melanoma cell lines as the prototype, we report on a joint theoretical and experimental investigation of the cell-state transition dynamics associated with BRAF inhibitor drug tolerance. Thermodynamically motivated surprisal analysis of transcriptome data was used to treat the cell population as an entropy maximizing system under the influence of time-dependent constraints. This permits the extraction of an epigenetic potential landscape for drug-induced phenotypic evolution. Single-cell flow cytometry data of the same system were modeled with a modified Fokker-Planck-type kinetic model. The two approaches yield a consistent picture that accounts for the phenotypic heterogeneity observed over the course of drug tolerance development. The results reveal that, in certain plastic cancers, the population heterogeneity and evolution of cell phenotypes may be understood by accounting for the competing interactions of the epigenetic potential landscape and state-dependent cell proliferation. Accounting for such competition permits accurate, experimentally verifiable predictions that can potentially guide the design of effective treatment strategies

Evaluating the Accuracy of Approximate Power and Sample Size Calculations for Logistic Regression

Thesis (Master's)--University of Washington, 2019This master’s thesis evaluates and implements power, sample size and effect size calculations for logistic regression. The earlier sections set up an ordinary logistic regression model, review the current approaches including those of Whittemore, Hsieh and Schoenfeld & Borenstein, and illustrate comparisons of the existing approaches. Schoenfeld & Borenstein’s method exhibits general superiority and, with slight modifications, is implemented in a Shiny web application and an R package. We give examples to demonstrate its use, and make recommendations about when its results can be considered accurate enough for applications

The common and intrinsic skin electric-double-layer (EDL) and its bonding characteristics of nanostructures

We show that nanocrystals share a common and intrinsic skin electric-double-layer (EDL). The EDL is determined to be 2.14 regular-bond-length thick using differential phonon spectroscopy that distills phonon abundance transiting from the core region to the EDL of the sized crystals. Theoretical reproduction of the size-resolved Raman shift for Si, CeO₂, and SnO₂ nanocrystals, elasticity of ZnO, and the XPS 2p energy shift, band gap expansion and melting point shift of Si crystals confirmed the universality of the EDL of which bonds are shorter and stronger than those inside the bulk or the particle core interior. The EDL bond contraction and the associated electron entrapment and polarization originate, and the EDL volume quantifies the size dependency of nanostructures while the electron entrapment or polarization entitles the undercoordinated single or edge atoms with properties that a bulk does never show.Financial support received from the National Natural Science Foundation (No 21273191) of China, is gratefully acknowledged

Improved Anti-Collision Algorithm for the Application on Intelligent Warehouse

As an important part of economic development, warehousing logistics also needs to be transformed and upgraded in order to adapt to the development of the new situation. The RFID reader records the related information of the goods to improve the efficiency of warehouse operation by identifying the RFID tags attached to the goods in batches. This paper also proposes an improved group-based anti-collision algorithm (GMQT) to solve the problem of tag collision in the process of Radio Frequency Identification (RFID) identification. The simulation results show that the GMQT algorithm improves the recognition efficiency of the system. The algorithm has the advantages of small data transmission and stable performance; in particular, the recognition efficiency is not affected by the number of tags

Phonon abundance-stiffness-lifetime transition from the mode of heavy water to its confinement and hydration

A combination of the spatially- and temporally-resolved phonon spectroscopies has enabled calibration of hydrogen bond transition from the vibration mode of heavy water to the core-shell structured nanodroplets and to the ionic hydration shells of salt solutions in terms of phonon abundance-lifetime-stiffness. It is uncovered that charge injection by salt solvation and skin formation by molecular undercoordination (often called confinement) share the same supersolidity characterized by H–O (D–O as a probe) bond contraction, O:H nonbond elongation, and polarization. Such a process of bond transition stems the solution viscosity, surface stress, and slowing down of the molecular dynamics and diffusivity. The nanodroplet skin reflection further hinders phonon energy dissipation associated with longer D–O phonon lifetime.Financial support received from National Natural Science Foundation of China (Nos. 11872052(YL); 21875024(CQ)), the Science Challenge Project (No. TZ2016001) of China is acknowledged

Coordination-resolved local bond relaxation, electron binding-energy shift, and Debye temperature of Ir solid skins

Numerical reproduction of the measured 4f7/2 energy shift of Ir(100), (111), and (210) solid skins turns out the following: (i) the 4f7/2 level of an isolated Ir atom shifts from 56.367eV to 60.332 eV by 3.965 eV upon bulk formation; (ii) the local energy density increases by up to 130% and the atomic cohesive energy decreases by 70% in the skin region compared with the bulk values. Numerical match to observation of the temperature dependent energy shift derives the Debye temperature that varies from 285.2 K (Surface) to 315.2 K (Bulk). We clarified that the shorter and stronger bonds between under-coordinated atoms cause local densification and quantum entrapment of electron binding energy, which perturbs the Hamiltonian and the core shifts in the skin region.Accepted versio

Improving the Solubility of Aripiprazole by Multicomponent Crystallization

Aripiprazole (ARI) is a third-generation antipsychotic with few side effects but a poor solubility. Salt formation, as one common form of multicomponent crystals, is an effective strategy to improve pharmacokinetic profiles. In this work, a new ARI salt with adipic acid (ADI) and its acetone hemisolvate were obtained successfully, along with a known ARI salt with salicylic acid (SAL). Their comprehensive characterizations were conducted using X-ray diffraction and differential scanning calorimetry. The crystal structures of the ARI-ADI salt acetone hemisolvate and ARI-SAL salt were elucidated by single-crystal X-ray diffraction for the first time, demonstrating the proton transfer from a carboxyl group of acid to ARI piperazine. Theoretical calculations were also performed on weak interactions. Moreover, comparative studies on pharmaceutical properties, including powder hygroscopicity, stability, solubility, and the intrinsic dissolution rate, were carried out. The results indicated that the solubility and intrinsic dissolution rate of the ARI-ADI salt and its acetone hemisolvate significantly improved, clearly outperforming that of the ARI-SAL salt and the untreated ARI. The study presented one potential alternative salt of aripiprazole and provided a potential strategy to increase the solubility of poorly water-soluble drugs

Stress-mediated dysregulation of the Rap1 small GTPase impairs hippocampal structure and function

Summary: The effects of repeated stress on cognitive impairment are thought to be mediated, at least in part, by reductions in the stability of dendritic spines in brain regions critical for proper learning and memory, including the hippocampus. Small GTPases are particularly potent regulators of dendritic spine formation, stability, and morphology in hippocampal neurons. Through the use of small GTPase protein profiling in mice, we identify increased levels of synaptic Rap1 in the hippocampal CA3 region in response to escalating, intermittent stress. We then demonstrate that increased Rap1 in the CA3 is sufficient in and of itself to produce stress-relevant dendritic spine and cognitive phenotypes. Further, using super-resolution imaging, we investigate how the pattern of Rap1 trafficking to synapses likely underlies its effects on the stability of select dendritic spine subtypes. These findings illuminate the involvement of aberrant Rap1 regulation in the hippocampus in contributing to the psychobiological effects of stress