Experimental Study on Dispersion of Unconfined Aquifer in a Site of Jilin City

Dispersion parameter is an important parameter for the establishment of groundwater solute transport model.The dispersion test uses sodium chloride as a tracer,which was conducted in a site in Jilin City.The standard curve comparison method was used to solve the dispersion parameters of the aquifer under the natural flow field.The test results show that under the natural flow field,the longitudinal dispersion of unconfined aquifer in Jilin City is 0.400m,and the lateral dispersion is 1.933×10-5~6.557×10-3m;while the vertical dispersion coefficient is 0.246m2d,the lateral dispersion coefficient is 1.191×10-5~4.039×10-3m2d.The above results can provide an important parameter basis for the establishment of groundwater solute transport model,the accurate prediction of temporal and spatial variation of pollutant concentration in groundwater and the formulation of groundwater pollution prevention and control scheme

Approximate Common Knowledge Based on Uncertain Measure

This paper studies that how an uncertain event can be outlined as an approximate common knowledge. By replacing “know” with “know with certainty α” in standard definitions of common knowledge, approximate common knowledge with some certainty, defined iteratively and mutually, iteratively known and mutually known with some certainty, are explored. Examples are constructed to show that an event which is not common knowledge can be analyzed as an approximate common knowledge with some certainty. An application in the principal-agent model is investigated to show that approximate common knowledge based on uncertain measure can be applied to improve the behavior of an economic model

A Unified Knowledge Graph Service for Developing Domain Language Models in AI Software

Natural Language Processing (NLP) is one of the core techniques in AI software. As AI is being applied to more and more domains, how to efficiently develop high-quality domain-specific language models becomes a critical question in AI software engineering. Existing domain-specific language model development processes mostly focus on learning a domain-specific pre-trained language model (PLM); when training the domain task-specific language model based on PLM, only a direct (and often unsatisfactory) fine-tuning strategy is adopted commonly. By enhancing the task-specific training procedure with domain knowledge graphs, we propose KnowledgeDA, a unified and low-code domain language model development service. Given domain-specific task texts input by a user, KnowledgeDA can automatically generate a domain-specific language model following three steps: (i) localize domain knowledge entities in texts via an embedding-similarity approach; (ii) generate augmented samples by retrieving replaceable domain entity pairs from two views of both knowledge graph and training data; (iii) select high-quality augmented samples for fine-tuning via confidence-based assessment. We implement a prototype of KnowledgeDA to learn language models for two domains, healthcare and software development. Experiments on five domain-specific NLP tasks verify the effectiveness and generalizability of KnowledgeDA. (Code is publicly available at https://github.com/RuiqingDing/KnowledgeDA.)Comment: 12 page

Experimental Study of an Iron-Based Metal-Organic Framework as Flame Retardant for Poly (methyl methacrylate) (PMMA)

PresentationPoly (methyl methacrylate) (PMMA) is a kind of widely used thermoplastic in the family of poly (acrylic ester)s due to its good mechanical properties, like good moldability, high resistance to UV light and weathering, high strength, and excellent dimensional stability. However, PMMA is also characterized by limited heat resistance, poor thermal stability, and high flammability. Metal-organic frameworks (MOFs) are a new class of porous materials, which possess unique physicochemical properties and have attracted considerable interests from different fields, such as energy, gas storage and separation, and catalysis. Additionally, because of their inorganic−organic hybrid nature, MOFs are usually compatible with polymers to form composites. PCN-250 is an iron-based MOF with nitrogen-containing structure and it is chemically stable and physically robust. So far, it can be economically synthesized in large scale. In this study, PCN-250 is used as a potential flame retardant for PMMA. To evaluate the performance of PCN-250 with different concentrations, the thermostability and flame retardancy of the PMMA composites are systematically investigated using thermal gravimetric analysis (TGA) and cone calorimetry. This study will give us some insight about the application of MOFs as a new kind of flame retardant to enhance and improve the fire safety of polymer materials

Developing and Activated T Cell Survival Depends on Differential Signaling Pathways to Regulate Anti-Apoptotic Bcl-xL

Survival of T cells in both the central and peripheral immune system determines its ultimate function in the regulation of immune responses. In the thymus, developing T cells undergo positive and negative selection to generate a T cell repertoire that responds to foreign, but not self, antigens. During T cell development, the T cell receptor α chain is rearranged. However, the first round of rearrangement may fail, which triggers another round of α chain rearrangement until either successful positive selection or cell death occurs. Thus, the lifespan of double positive (CD4+CD8+; DP) thymocytes determines how many rounds of α chain rearrangement can be carried out and influences the likelihood of completing positive selection. The anti-apoptotic protein Bcl-xL is the ultimate effector regulating the survival of CD4+CD8+ thymocytes subject to the selection process, and the deletion of Bcl-xL leads to premature apoptosis of thymocytes prior to the completion of the developmental process. In addition to its critical function in the thymus, Bcl-xL also regulates the survival of peripheral T cells. Upon engagement with antigens, T cells are activated and differentiated into effectors. Activated T cells upregulate Bcl-xL to enhance their own survival. Bcl-xL-mediated survival is required for the generation of effectors that carry out the actual immune responses. In the absence of Bcl-xL, mature T cells undergo apoptosis prior to the completion of the differentiation process to become effector cells. Therefore, Bcl-xL ensures the survival of both developing and peripheral T cells, which is essential for a functional immune system

A Birandom Job Search Problem with Risk Tolerance

This paper considers a novel class of birandom job search problem, in which the job offers are sampled by the job searcher from a finite job set with equivalent probability and their wages are characterized as independent but maybe not identically nonnegative random variables. The job searcher knows the job offer's wage distribution when he samples the job offer. Since the offered wage is a random variable and the reservation wage is a deterministic number, it is meaningless to make comparison directly. In order to rank the random wage and the reservation wage and provide decision support, a risk tolerance criterion is designed, and the job searcher then accepts or rejects the sampled job offer depending on whether the risk tolerance criterion is met or not. Since the offered wages are random variables and the search process is random, it's impossible to obtain the job searcher's real return; in this case, its expected value can be calculated via birandom theory. Simultaneously, some propositions on the expected return as well as the average search times are also studied which may provide some valuable suggestions to the job searcher. Numerical examples are given to illustrate the decision process of the risk tolerance-based birandom job search problem

Zinc-Tiered Synthesis of 3D Graphene for Monolithic Electrodes

A high-surface-area conductive cellular carbon monolith is highly desired as the optimal electrode for achieving high energy, power, and lifetime in electrochemical energy storage. 3D graphene can be regarded as a first-ranking member of cellular carbons with the pore-wall thickness down to mono/few-atomic layers. Current 3D graphenes, derived from either gelation or pyrolysis routes, still suffer from low surface area, conductivity, stability, and/or yield, being subjected to methodological inadequacies including patchy assembly, wet processing, and weak controllability. Herein, a strategy of zinc-assisted solid-state pyrolysis to produce a superior 3D graphene is established. Zinc unprecedentedly impregnates and delaminates a solid ( nonhollow ) char into multiple membranes, which eliminates the morphological impurities ever-present in the previous pyrolyses using solid-state carbon precursors. Zinc also catalyzes the carbonization and graphitization, and its in situ thermal extraction and recycling enables the scaled-up production. The created 3D graphene network consists integrally of morphologically and chemically pure graphene membranes. It possesses unrivaled surface area, outstanding stability, and conductivity both in air and electrolyte, exceeding preexisting 3D graphenes. The advanced 3D graphene thus equips a porous monolithic electrode with unparalleled energy density, power density, and lifetime in electric-double-layer capacitive devices