Sufficient condition for existence of solutions for higher-order resonance boundary value problem with one-dimensional p-Laplacian

By using coincidence degree theory of Mawhin, existence results for some higher order resonance multipoint boundary value problems with one dimensional p-Laplacian operator are obtained

Understanding the Spatial Structure of Urban Commuting Using Mobile Phone Location Data: A Case Study of Shenzhen, China

Understanding commuting patterns has been a classic research topic in the fields of geography, transportation and urban planning, and it is significant for handling the increasingly serious urban traffic congestion and air pollution and their impacts on the quality of life. Traditional studies have used travel survey data to investigate commuting from the aspects of commuting mode, efficiency and influence factors. Due to the limited sample size of these data, it is difficult to examine the large-scale commuting patterns of urban citizens, especially when exploring the spatial structure of commuting. This study attempts to understand the spatial structure characteristics generated by human commutes to work by using massive mobile phone datasets. A three-step workflow was proposed to accomplish this goal, which includes extracting the home and work locations of phone users, detecting the communities from the commuting network, and identifying the commuting convergence and divergence areas for each community. A case study of Shenzhen, China was implemented to determine the commuting structure. We found that there are thirteen communities detected from the commuting network and that some of the communities are in accordance with urban planning; moreover, spatial polycentric polygons exist in each community. These findings can be referenced by urban planners or policy-makers to optimize the spatial layout of the urban functional zones. Document type: Articl

Self-consistent Reasoning For Solving Math Word Problems

Math word problems (MWPs) is a task that automatically derives solution expression from a giving math problems in text. The previous studies suffer from spurious correlations between input text and output expression. To mitigate this issue, we propose a self-consistent reasoning framework called SCR, which attempts to adopt a pruning strategy to correct the output distribution shift so as to implicitly fix those spurious correlative samples. Specifically, we firstly obtain a sub-network by pruning a roberta2tree model, for the sake to use the gap on output distribution between the original roberta2tree model and the pruned sub-network to expose spurious correlative samples. Then, we calibrate the output distribution shift by applying symmetric Kullback-Leibler divergence to alleviate spurious correlations. In addition, SCR generates equivalent expressions, thereby, capturing the original text's logic rather than relying on hints from original text. Extensive experiments on two large-scale benchmarks demonstrate that our model substantially outperforms the strong baseline methods.Comment: Submitted to IEEE ICASSP 202

Expression Syntax Information Bottleneck for Math Word Problems

Math Word Problems (MWP) aims to automatically solve mathematical questions given in texts. Previous studies tend to design complex models to capture additional information in the original text so as to enable the model to gain more comprehensive features. In this paper, we turn our attention in the opposite direction, and work on how to discard redundant features containing spurious correlations for MWP. To this end, we design an Expression Syntax Information Bottleneck method for MWP (called ESIB) based on variational information bottleneck, which extracts essential features of expression syntax tree while filtering latent-specific redundancy containing syntax-irrelevant features. The key idea of ESIB is to encourage multiple models to predict the same expression syntax tree for different problem representations of the same problem by mutual learning so as to capture consistent information of expression syntax tree and discard latent-specific redundancy. To improve the generalization ability of the model and generate more diverse expressions, we design a self-distillation loss to encourage the model to rely more on the expression syntax information in the latent space. Experimental results on two large-scale benchmarks show that our model not only achieves state-of-the-art results but also generates more diverse solutions. The code is available.Comment: This paper has been accepted by SIGIR 2022. The code can be found at https://github.com/menik1126/math_ESI

Comparison of Nondestructive Testing Methods for Evaluating No. 2 Southern Pine Lumber: Part B, Modulus of Rupture

The identification of strength-reducing characteristics that impact modulus of rupture (MOR) is a key differentiation between lumber grades. Because global design values for MOR are at the fifth percentile level and in-grade lumber can be highly variable, it is important that nondestructive evaluation technology be used to better discern the potential wood strength. In that manner, higher-performance pieces could potentially be identified and their value captured accordingly. In this study, laboratory tests of three nondestructive testing (NDT) technologies and destructive four-point static bending were applied to 343 pieces of visually graded No. 2 southern pine lumber in the 38140 mm2 (n . 86), 38186 mm2 (n . 112), 38236 mm2 (n . 91), and 38 287 mm2 (n . 54) sizes collected across the southeast region of the United States. The NDT tests included continuous lumber test in continuous proof bending (MetriguardModel 7200 High Capacity Lumber Tester), transverse vibration (Metriguard E-Computer), and two longitudinal stress wave tools (Falcon A-Grader and Fiber-gen Director HM200). Following nondestructive tests, the specimens were destructively tested in four-point static bending. Single-predictor linear correlations were observed between static bending MOE and MOR value; and NDT outputs and bending MOR value. The regression results showed that the average NDT outputs (r2 . 0.23-0.28) had lower performance than static bending MOE (r2 . 0.39), for predicting the bending MOR of sawn lumber.

Forgetting before Learning: Utilizing Parametric Arithmetic for Knowledge Updating in Large Language Models

Recently Large Language Models (LLMs) have demonstrated their amazing text understanding and generation capabilities. However, even stronger LLMs may still learn incorrect knowledge from the training corpus, as well as some knowledge that is outdated over time. Direct secondary fine-tuning with data containing new knowledge may be ineffective in updating knowledge due to the conflict between old and new knowledge. In this paper, we propose a new paradigm for fine-tuning called F-Learning (Forgetting before Learning), which is based on parametric arithmetic to achieve forgetting of old knowledge and learning of new knowledge. Experimental results on two publicly available datasets demonstrate that our proposed F-Learning can obviously improve the knowledge updating performance of both full fine-tuning and LoRA fine-tuning. Moreover, we have also discovered that forgetting old knowledge by subtracting the parameters of LoRA can achieve a similar effect to subtracting the parameters of full fine-tuning, and sometimes even surpass it significantly.Comment: 8 pages, 2 figures, 2 table

Experimental study of chemotherapy related leukocytopenia treated by various peroal leucocyte increasing drugs

Background: Clinically, the patients with significant WBC decrease are mostly administered G-CSF, this kind of drugs is expensive and adverse reactions are often seen. In contrast, oral leucocyte increasing drug has small adverse reactions, can be used for longer time and can improve the continuity and stability of treatment. The experimental study based on study of mouse was to evaluate the effects of treatment and chemotherapy of related leukocytopenia by five kinds of commonly used peroal leucocyte increasing drugs.Materials and Methods: We prepared mice chemotherapy related leukocytopenia model by cyclophosphamide intraperitoneal injection, the positive control drug is G-CSF, respectively fill five kinds of peroal Leucocyte increasing drugs (Qijiao Shengbai Capsule, Weixuening Granule, Compound Zaofan Pill, Berbamine and Leucogen Tablets) in the stomach, the experimental group was divided into normal control group (group A), model group (group B), positive control group (Group rhG-CSF, group C) and treatment groups (group D-H), and treatment groups were divided into Qijiao Shengbai Capsule group (group D), Weixuening Granule group (group E), Compound Zaofan Pill group (group F), Berbamine Tablet group (group G) and Leucogen Tablet group (group H). Calculate the death rate, blood routine and important visceral organ index in each group..Results: The death rate of mice in each group has no significant difference (P>0.05). WBC of B, D, E and F groups was significantly lower than that of group A (P<0.05 or P<0.01). WBC of C, G and H groups was significantly higher than those of group B (P<0.01). WBC of D, E and F groups was significantly lower than that of group C (P<0.01). WBC of G and H groups was significantly higher than that of D and F groups (P<0.01), WBC of group H is significantly higher than that of group E (P<0.05). RBC of group F, G and H groups was significantly higher than that of group D (P<0.05 or P<0.01). HB of group H is significantly higher than that of group A (P<0.01). HB of C, G and H groups was significantly higher than that of group B (P average <0.01). HB of D, E and F groups was significantly lower than that of group C (P<0.05 or P<0.01). HB of G and H groups was significantly higher than that of D, E and F groups (P average <0.01). PLT of group H was significantly higher than that of group B (P average <0.05). PLT of F, G and H groups was significantly higher than that of group D (P<0.01). Lung index of group G was significantly higher than that of D, E, F and H groups (P<0.01). Liver index of group H is significantly higher than that of group D (P<0.05). Thymus index of G and H groups is significantly higher than that of group F (P<0.05 or P<0.01).Conclusions: Among all drugs of rising WBC, G-CSF owns strongest effect. In oral drug groups, WBC rising effect of Leucogen Tablets is best, RBC, HB and PLT improvement effect of Berbamine and Leucogen Tablets is best. In addition, Berbamine and Leucogen Tablets respectively caused significant increase of lung and liver index, what indicates that, the two drugs may be accompanied by relevant viscera damage. At the same time, the two drugs also  increased thymus index, which indirectly indicates that, the immunity and regulation abilities of Berbamine and Leucogen Tablets are stronger. The spleen index of Qijiao Shengbai Capsule group was significantly higher than that of Berbamine Tablet and Leucogen Tablet groups, what indicates that, the immunity and regulation abilities of Qijiao Shengbai Capsule may be stronger in oral drug group.Keywords: leucocyte increasing drugs; chemotherapy; leukocytopenia; mous

Effect of Baicalin on inflammatory mediator levels and microcirculation disturbance in rats with severe acute pancreatitis

Objective: To investigate the effect of Bacailin on inflammatory mediator levels and microcirculation disturbance in severe acute pancreatitis (SAP) rats and explore its therapeutic mechanism on this disease. Methods: SAP model rats were randomly divided into model control group and Baicalin treated group, 45 rats in each group. The same number of normal rats were included in sham-operated group. These groups were further subdivided into 3 h, 6 h and 12 h subgroups, respectively (15 rats in each subgroup). At 3, 6 and 12 hours after operation, rats were killed to conduct the following experiments: (1) to examine the mortality rates of rats, the ascites volume and pancreatic pathological changes in each group; (2) to determine the contents of amylase, PLA~2~, TXB~2~, PGE~2~, PAF and IL-1[beta]; in blood as well as the changes in blood viscosity.Results: (1) Compared to model control group, treatment with Baicalin is able to improve the pathological damage of the pancreas, lower the contents of amylase and multiple inflammatory mediators in blood, decrease the amount of ascitic fluid and reduce the mortality rates of SAP rats; (2) at 3 hours after operation, the low-shear whole blood viscosity in Baicalin treated group was significantly lower than that in model control group;at 12 hours after operation, both the high-shear and low-shear whole blood viscosity in Baicalin treated group were also significantly lower than those in model control group.Conclusion: Baicalin, as a new drug, has good prospects in the treatment of SAP since it can exert therapeutic effects on this disease through inhibiting the production of inflammatory mediators, lowering blood viscosity, improving microcirculation and mitigating the pathological damage of the pancreas