Parametric SAR Image Formation - A Promising Approach to Resolution-Unlimited Imaging

Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 201

Mathematical Mechanism on Dynamical System Algorithms of the Ising Model

Various combinatorial optimization NP-hard problems can be reduced to finding the minimizer of an Ising model, which is a discrete mathematical model. It is an intellectual challenge to develop some mathematical tools or algorithms for solving the Ising model. Over the past decades, some continuous approaches or algorithms have been proposed from physical, mathematical or computational views for optimizing the Ising model such as quantum annealing, the coherent Ising machine, simulated annealing, adiabatic Hamiltonian systems, etc.. However, the mathematical principle of these algorithms is far from being understood. In this paper, we reveal the mathematical mechanism of dynamical system algorithms for the Ising model by Morse theory and variational methods. We prove that the dynamical system algorithms can be designed to minimize a continuous function whose local minimum points give all the candidates of the Ising model and the global minimum gives the minimizer of Ising problem. Using this mathematical mechanism, we can easily understand several dynamical system algorithms of the Ising model such as the coherent Ising machine, the Kerr-nonlinear parametric oscillators and the simulated bifurcation algorithm. Furthermore, motivated by the works of C. Conley, we study transit and capture properties of the simulated bifurcation algorithm to explain its convergence by the low energy transit and capture in celestial mechanics. A detailed discussion on $2$-spin and $3$-spin Ising models is presented as application.Comment: 39 pages, 2 figures(including 8 sub-figures

Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Uncertainty decomposition refers to the task of decomposing the total uncertainty of a model into data (aleatoric) uncertainty, resulting from the inherent complexity or ambiguity of the data, and model (epistemic) uncertainty, resulting from the lack of knowledge in the model. Performing uncertainty decomposition for large language models (LLMs) is an important step toward improving the reliability, trustworthiness, and interpretability of LLMs, but this research task is very challenging and remains unresolved. The existing canonical method, Bayesian Neural Network (BNN), cannot be applied to LLMs, because BNN requires training and ensembling multiple variants of models, which is infeasible or prohibitively expensive for LLMs. In this paper, we introduce an uncertainty decomposition framework for LLMs, called input clarifications ensemble, which bypasses the need to train new models. Rather than ensembling models with different parameters, our approach generates a set of clarifications for the input, feeds them into the fixed LLMs, and ensembles the corresponding predictions. We show that our framework shares a symmetric decomposition structure with BNN. Empirical evaluations demonstrate that the proposed framework provides accurate and reliable uncertainty quantification on various tasks. Code will be made publicly available at https://github.com/UCSB-NLP-Chang/llm_uncertainty .Comment: 15 pages, 3 figure

NEIMiner: nanomaterial environmental impact data miner

As more engineered nanomaterials (eNM) are developed for a wide range of applications, it is crucial to minimize any unintended environmental impacts resulting from the application of eNM. To realize this vision, industry and policymakers must base risk management decisions on sound scientific information about the environmental fate of eNM, their availability to receptor organisms (eg, uptake), and any resultant biological effects (eg, toxicity). To address this critical need, we developed a model-driven, data mining system called NEIMiner, to study nanomaterial environmental impact (NEI). NEIMiner consists of four components: NEI modeling framework, data integration, data management and access, and model building. The NEI modeling framework defines the scope of NEI modeling and the strategy of integrating NEI models to form a layered, comprehensive predictability. The data integration layer brings together heterogeneous data sources related to NEI via automatic web services and web scraping technologies. The data management and access layer reuses and extends a popular content management system (CMS), Drupal, and consists of modules that model the complex data structure for NEI-related bibliography and characterization data. The model building layer provides an advanced analysis capability for NEI data. Together, these components provide significant value to the process of aggregating and analyzing large-scale distributed NEI data. A prototype of the NEIMiner system is available at http://neiminer.i-a-i.com/.Keywords: content management system, data management, data mining, modeling, nanomaterial environmental impact, data integration, model compositionThis is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Dove Medical Press Ltd. The published article can be found at: https://www.dovepress.com/international-journal-of-nanomedicine-journal

Predictive modeling of nanomaterial exposure effects in biological systems

BACKGROUND: Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. METHODS: We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric) was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. RESULTS: We found several important attributes that contribute to the 24 hours post-fertilization (hpf) mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of nanomaterials. Sample prediction models can be found at http://neiminer.i-a-i.com/nei_models. CONCLUSION: The EZ Metric-based data mining approach has been shown to have predictive power. The results provide valuable insights into the modeling and understanding of nanomaterial exposure effects.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Dove Medical Press Ltd. The published article can be found at: https://www.dovepress.com/international-journal-of-nanomedicine-journal.Keywords: biological response, embryonic zebrafish, toxicity, numerical prediction, data mining, nanomaterial exposure effect

Dried tea residue can alter the blood metabolism and the composition and functionality of the intestinal microbiota in Hu sheep

Ruminant animals face multiple challenges during the rearing process, including immune disorders and oxidative stress. Green tea by-products have gained widespread attention for their significant immunomodulatory and antioxidant effects, leading to their application in livestock production. In this study, we investigated the effects of Dried Tea Residue (DTR) as a feed additive on the growth performance, blood biochemical indicators, and hindgut microbial structure and function of Hu sheep. Sixteen Hu sheep were randomly divided into two groups and fed with 0 and 100 g/d of DTR, respectively. Data were recorded over a 56-day feeding period. Compared to the control group, there were no significant changes in the production performance of Hu sheep fed with DTR. However, the sheep fed with DTR showed a significant increase in IgA (p < 0.001), IgG (p = 0.005), IgM (p = 0.003), T-SOD (p = 0.013), GSH-Px (p = 0.005), and CAT (p < 0.001) in the blood, along with a significant decrease in albumin (p = 0.019), high density lipoprotein (p = 0.050), and triglyceride (p = 0.021). DTR supplementation enhanced the fiber digestion ability of hindgut microbiota, optimized the microbial community structure, and increased the abundance of carbohydrate-digesting enzymes. Therefore, DTR can be used as a natural feed additive in ruminant animal production to enhance their immune and antioxidant capabilities, thereby improving the health status of ruminant animals

Street vendors in Chinese cities since economic reform : a case study of Guangzhou

The growth of informal employment characterizes the urbanization process in the developing countries in the previous decades. China is in the fast lane of urbanization and there are signs of casual employment in Chinese cities in the recent decade. This study chooses a prevalent phenomenon, i.e., street vending, in Chinese cities to investigate the emergence and growth mechanisms of informal employment in Chinese cities since the economic reform. The city of Guangzhou is chosen for case study. There are two theoretical frameworks in explaining the growth of street vendors in other developing countries. First, they could be interpreted as the mismatch of job opportunities against the capacity in generating employment under specific development strategy (the dualist framework and ISI strategy); or street vending, along with other informal employment opportunities, is the efficient way of doing business (the neoliberal framework). The Chinese case is unique as the country is on the course of marketization while the state remains strong. What is the role of the strong state played in contributing to or refraining from the growth of street vendors; and how the lives of street vendors are in this particular context; are the two questions to be investigated. Empirical finding shows that the revival of street vendors in Chinese cities (the first generation of street vendors since economic reform) is facilitated by a series of reform policies initiated by the state, particularly the introduction and promotion of individual business. Street vendors relieved employment pressure, met the commodity shortages in the cities, and rejuvenated urban economy in China. The returnees and the peasants in the city suburb are two major groups practicing street vending, who made fortune out of it. The current wave of street vendors is resulted from the unexpected consequences of the state’s policies, including the state’s promotion on labor dispatching regulations to lower the labor price, the land centered urbanization pushing up the rent, the persistent rural urban disparity in generating urban-bound migration, the hukou system in inferiorizing the rural migrants to the locals, and the changing labor market as more young rural migrants emerge. Street vendors in the current wave could be differentiated into developmental street vendors, who drop the low-wage income to practice street vending; and survival street vendors, who are rejected by regular job markets but have to turn to street vending. The street vendors in the recent years tend to have higher income than some regular paid jobs. Survey on their operation, commuting and accommodation shows that they could maintain they live in the city and their vibrancy is due to the abundant cheap products, as the country is the world factory; and a large number of low and lower-middle income wage workers being their clients. This study concludes that the state contributes to the growth of street vendors in Chinese cities. The strong growth momentum on the growth of street vendors suggests the current antagonistic policies against street vendors need to be reviewed.published_or_final_versionUrban Planning and DesignDoctoralDoctor of Philosoph

Damage Mechanism and Stress Distribution of Gypsum Rock Pillar Subjected to Blasting Disturbance

The room-pillar mining technology of underground gypsum resources results in numerous gypsum rock pillars for controlling and supporting mined gobs, which forms a large area of roof hanging gobs. Owing to weathering and mining activities, gypsum rock pillar damage and failure will occur, thereby inducing a large area of gypsum mined-gob collapse accidents and disasters. Blasting is vital to the stability of gypsum rock pillars and is indispensable in mining engineering. Based on field blasting tests and using wave velocity as the basic parameter to characterise the integrity of gypsum rock, the damage mechanism of gypsum rock pillars subjected to blasting disturbance is investigated. With ten blasting tests, the maximum damage rate is 7.82% along the horizontal direction of pillar, and 3.52% along the vertical direction. The FLAC numerical simulation calculation software is used to analyse the stress distribution law of gypsum rock pillars with disturbances of different strengths from different distances. As the disturbance strength increased, the stress increased with no clear linear relationship; as the disturbance distance increased, the stress decreased gradually with a linear relationship. All stress after disturbance is greater than the original static stress, and lower than the ultimate compressive strength. However, the correlation between blasting tests results and numerical simulation results is poor and is discussed for many factors. The results can provide important guidance and reference for clarifying the damage mechanism of gypsum rock pillars subjected to blasting disturbance, as well as reveal the collapse mechanism of gypsum mined gobs