APPLICATION OF LINEAR FREE ENERGY RELATIONSHIPS IN THE PREDICTION OF TRIGLYCERIDE/WATER PARTITION COEFFICIENTS AND LIPID BILAYER PERMEABILITY COEFFICIENTS OF SMALL ORGANIC MOLECULES AND PEPTIDES

Computational methods such as linear free energy relationships (LFERs) offer a useful high-throughput solution to quickly evaluate drug developability, e.g. membrane permeability, organic solvent/water partition coefficients, and solubility. LFERs typically assume the contribution of structural components/functional groups to the overall properties of a given molecule to be constant and independent. This dissertation describes a series of studies in which linear free energy relationships were developed to predict solvation of small organic molecules in lipid formulations, specifically, triglyceride containing solvents and phospholipid-based liposomes. The formation of intermolecular HBs in triglyceride solvents (homogenous with H-bond accepting ability) and intramolecular HBs within the bilayer barrier domain (hydrocarbon-like) proved to be the major factors to consider in developing LFERs to account for the increased oil/water partition coefficients and enhanced bilayer permeability of small organic molecules. The triglyceride solvent/water partition coefficients of a series of model compounds varying in polarity and H-bond donating/accepting capability were used to establish a correlation between the solvent descriptors and the ester concentration in these solvents using the Abraham LFER approach. The LFER analyses showed that the descriptors representing the polarizability and H-bond basicity of the solvents vary systematically with the ester concentration. A fragment-based LFER to predict membrane permeability or 1,9- decadiene/water partition coefficients of small organic molecules including small peptides was systematically constructed using a total of 47 compounds. Significant nonadditivity was observed in peptides in that the contribution of the peptide backbone amide to the apparent transfer free energy from water into the bilayer barrier domain is considerably smaller than that of a “well-isolated” amide and greatly affected by adjacent polar substituents on the C-termini. In order to explain the phenomenon of nonadditivity, the formation of intramolecular HBs and inductive effects of neighboring polar groups on backbone amide, were investigated using FTIR and MD simulations. Both spectroscopic and computational results provided supportive evidence for the hypothesis that the formation of intramolecular HBs in peptides is the main reason for the observed nonadditivity of Δ(ΔG°)-CONH-. The MD simulation results showed that the inductive effect of neighboring groups is not as important as the effect of intramolecular HBs

Verifying Programs with Logic and Extended Proof Rules: Deep Embedding v.s. Shallow Embedding

Many foundational program verification tools have been developed to build machine-checked program correctness proofs, a majority of which are based on Hoare logic. Their program logics, their assertion languages, and their underlying programming languages can be formalized by either a shallow embedding or a deep embedding. Tools like Iris and early versions of Verified Software Toolchain (VST) choose different shallow embeddings to formalize their program logics. But the pros and cons of these different embeddings were not yet well studied. Therefore, we want to study the impact of the program logic's embedding on logic's proof rules in this paper. This paper considers a set of useful extended proof rules, and four different logic embeddings: one deep embedding and three common shallow embeddings. We prove the validity of these extended rules under these embeddings and discuss their main challenges. Furthermore, we propose a method to lift existing shallowly embedded logics to deeply embedded ones to greatly simplify proofs of extended rules in specific proof systems. We evaluate our results on two existing verification tools. We lift the originally shallowly embedded VST to our deeply embedded VST to support extended rules, and we implement Iris-CF and deeply embedded Iris-Imp based on the Iris framework to evaluate our theory in real verification projects

Detector optimization to reduce the cosmogenic neutron backgrounds in the TAO experiment

Short-baseline reactor antineutrino experiments with shallow overburden usually have large cosmogenic neutron backgrounds. The Taishan Antineutrino Observatory (TAO) is a ton-level liquid scintillator detector located at about 30 m from a core of the Taishan Nuclear Power Plant. It will measure the reactor antineutrino spectrum with high precision and high energy resolution to provide a reference spectrum for JUNO and other reactor antineutrino experiments, and provide a benchmark measurement to test nuclear databases. Background is one of the critical concerns of TAO since the overburden is just 10 meter-water-equivalent. The cosmogenic neutron background was estimated to be ~10% of signals. With detailed Monte Carlo simulations, we propose several measures in this work to reduce the neutron backgrounds, including doping Gadolinium in the buffer liquid, adding a polyethylene layer above the bottom lead shield, and optimization of the veto strategy. With these improvements, the neutron background-to-signal ratio can be reduced to ~2%, and might be further suppressed with pulse shape discrimination.Comment: 11 pages, 3 figure

Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty

Knowledge distillation is an effective paradigm for boosting the performance of pocket-size model, especially when multiple teacher models are available, the student would break the upper limit again. However, it is not economical to train diverse teacher models for the disposable distillation. In this paper, we introduce a new concept dubbed Avatars for distillation, which are the inference ensemble models derived from the teacher. Concretely, (1) For each iteration of distillation training, various Avatars are generated by a perturbation transformation. We validate that Avatars own higher upper limit of working capacity and teaching ability, aiding the student model in learning diverse and receptive knowledge perspectives from the teacher model. (2) During the distillation, we propose an uncertainty-aware factor from the variance of statistical differences between the vanilla teacher and Avatars, to adjust Avatars' contribution on knowledge transfer adaptively. Avatar Knowledge Distillation AKD is fundamentally different from existing methods and refines with the innovative view of unequal training. Comprehensive experiments demonstrate the effectiveness of our Avatars mechanism, which polishes up the state-of-the-art distillation methods for dense prediction without more extra computational cost. The AKD brings at most 0.7 AP gains on COCO 2017 for Object Detection and 1.83 mIoU gains on Cityscapes for Semantic Segmentation, respectively.Comment: Accepted by ACM MM 202

Dr.Bokeh: DiffeRentiable Occlusion-aware Bokeh Rendering

Bokeh is widely used in photography to draw attention to the subject while effectively isolating distractions in the background. Computational methods simulate bokeh effects without relying on a physical camera lens. However, in the realm of digital bokeh synthesis, the two main challenges for bokeh synthesis are color bleeding and partial occlusion at object boundaries. Our primary goal is to overcome these two major challenges using physics principles that define bokeh formation. To achieve this, we propose a novel and accurate filtering-based bokeh rendering equation and a physically-based occlusion-aware bokeh renderer, dubbed Dr.Bokeh, which addresses the aforementioned challenges during the rendering stage without the need of post-processing or data-driven approaches. Our rendering algorithm first preprocesses the input RGBD to obtain a layered scene representation. Dr.Bokeh then takes the layered representation and user-defined lens parameters to render photo-realistic lens blur. By softening non-differentiable operations, we make Dr.Bokeh differentiable such that it can be plugged into a machine-learning framework. We perform quantitative and qualitative evaluations on synthetic and real-world images to validate the effectiveness of the rendering quality and the differentiability of our method. We show Dr.Bokeh not only outperforms state-of-the-art bokeh rendering algorithms in terms of photo-realism but also improves the depth quality from depth-from-defocus

SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models

Multimodal large language models (MLLMs) have demonstrated remarkable problem-solving capabilities in various vision fields (e.g., generic object recognition and grounding) based on strong visual semantic representation and language reasoning ability. However, whether MLLMs are sensitive to subtle visual spoof/forged clues and how they perform in the domain of face attack detection (e.g., face spoofing and forgery detection) is still unexplored. In this paper, we introduce a new benchmark, namely SHIELD, to evaluate the ability of MLLMs on face spoofing and forgery detection. Specifically, we design true/false and multiple-choice questions to evaluate multimodal face data in these two face security tasks. For the face anti-spoofing task, we evaluate three different modalities (i.e., RGB, infrared, depth) under four types of presentation attacks (i.e., print attack, replay attack, rigid mask, paper mask). For the face forgery detection task, we evaluate GAN-based and diffusion-based data with both visual and acoustic modalities. Each question is subjected to both zero-shot and few-shot tests under standard and chain of thought (COT) settings. The results indicate that MLLMs hold substantial potential in the face security domain, offering advantages over traditional specific models in terms of interpretability, multimodal flexible reasoning, and joint face spoof and forgery detection. Additionally, we develop a novel Multi-Attribute Chain of Thought (MA-COT) paradigm for describing and judging various task-specific and task-irrelevant attributes of face images, which provides rich task-related knowledge for subtle spoof/forged clue mining. Extensive experiments in separate face anti-spoofing, separate face forgery detection, and joint detection tasks demonstrate the effectiveness of the proposed MA-COT. The project is available at https$:$//github.com/laiyingxin2/SHIEL

A possible pathway for rapid growth of sulfate during haze days in China

Rapid industrialization and urbanization have caused frequent occurrence of haze in China during wintertime in recent years. The sulfate aerosol is one of the most important components of fine particles (PM[subscript 2. 5]) in the atmosphere, contributing significantly to the haze formation. However, the heterogeneous formation mechanism of sulfate remains poorly characterized. The relationships of the observed sulfate with PM[subscript 2. 5], iron, and relative humidity in Xi'an, China have been employed to evaluate the mechanism and to develop a parameterization of the sulfate heterogeneous formation involving aerosol water for incorporation into atmospheric chemical transport models. Model simulations with the proposed parameterization can successfully reproduce the observed sulfate rapid growth and diurnal variations in Xi'an and Beijing, China. Reasonable representation of sulfate heterogeneous formation in chemical transport models considerably improves the PM2. 5 simulations, providing the underlying basis for better understanding the haze formation and supporting the design and implementation of emission control strategies

Protective Effect of Tartaty Buckwheat Extract Fermented with Pleurotus eryngii on Alcoholic Liver and Stomach Injury in Mice

Objective: To investigate the antioxidant activity of fermented tartaty buckwheat extract of Pleurotus eryngii in vitro as well as its protective effect on alcohol-induced liver and gastric mucosa injury in vivo. Methods: The study involved determining the contents of functional components in fermented tartary buckwheat extract and observing its antioxidant capacity. Mice models of chronic alcoholic liver and gastric mucosa injury were established using Lieber-DeCarli liquid feed. The protective effects of fermented tartary buckwheat extract at low and high doses (1.5 g/kg B.W., 3.0 g/kg B.W.) were investigated for both liver and gastric mucosa injury. Results: The extract of fermented buckwheat with Pleurotus eryngii contained more antioxidant components, the contents of polyphenols, flavonoids and triterpenes were 11.40±0.32 mgGAE/g DW, 17.19±0.30 mg RE/g DW and 7.59±0.24 mg/g, respectively. The contents of rutin and quercetin were as follows: 13.55±0.05 and 0.665±0.01 mg/g. The iron reducing antioxidant capacity and DPPH and ABTS+ free radical scavenging efficiency of Tartary buckwheat extract were 16.66±0.65, 33.49±1.26 and 15.68±1.17 μmol Trolox/g DW, respectively. Compared with the model group, both high-dose and low-dose groups significantly reduced malondialdehyde (P<0.05), aspartate aminotransferase (P<0.01), alanine aminotransferase (P<0.01), lactate dehydrogenase (P<0.05), and interleukin-1β (P<0.05) levels and significantly increased levels of superoxide dismutase (P<0.01) and glutathione peroxidase (P<0.01), downregulated protein expression levels of reactive oxygen species (P<0.01), rat sarcoma (P<0.01), rapidly accelerated fibrosarcoma (P<0.01), extracellular signal-regulated kinases (P<0.05), and mitogen activated protein kinase kinase (P<0.05). Conclusion: Fermented tartaty buckwheat extract of Pleurotus eryngii has good antioxidant activity, and has obvious protective effect on chronic alcoholic liver and gastric mucosa injury in mice

Male Patients With Dilated Cardiomyopathy Exhibiting a Higher Heart Rate Acceleration Capacity or a Lower Deceleration Capacity Are at Higher Risk of Cardiac Death

The effects of dilated cardiomyopathy (DCM) on cardiac autonomic regulation and electrophysiology, and the consequences of such changes, remain unclear. We evaluated the associations between heart rate acceleration capacity (AC) and deceleration capacity (DC), heart structural and functional changes, and cardiac death in 202 healthy controls and 100 DCM patients. The DC was lower and the AC was higher in DCM patients (both males and females). Multivariable, linear, logistic regression analyses revealed that in males, age was positively associated with AC in healthy controls (N = 85); the left atrial diameter (LAD) was positively and the left ventricular ejection fraction (LVEF) was negatively associated with AC in DCM patients (N = 65); age was negatively associated with DC in healthy controls (N = 85); and the LAD was negatively and the LVEF was positively associated with DC in DCM patients (N = 65). In females, only age was associated with either AC or DC in healthy controls (N = 117). Kaplan–Meier analysis revealed that male DCM patients with greater LADs (≥46.5 mm) (long-rank chi-squared value = 11.1, P = 0.001), an elevated AC (≥-4.75 ms) (log-rank chi-squared value = 6.8, P = 0.009), and a lower DC (≤4.72 ms) (log-rank chi-squared value = 9.1, P = 0.003) were at higher risk of cardiac death within 60 months of follow-up. In conclusion, in males, DCM significantly affected both the AC and DC; a higher AC or a lower DC increased the risk of cardiac death