Multiple Solutions for the Asymptotically Linear Kirchhoff Type Equations on R

The multiplicity of positive solutions for Kirchhoff type equations depending on a nonnegative parameter λ on RN is proved by using variational method. We will show that if the nonlinearities are asymptotically linear at infinity and λ>0 is sufficiently small, the Kirchhoff type equations have at least two positive solutions. For the perturbed problem, we give the result of existence of three positive solutions

Mutual dependency grid for stakeholder mapping: a component-based approach to supply chain participant analysis

Stakeholder analysis plays a critical role in business analysis. However, the majority of the stakeholder identification and analysis methods focus on the activities and processes and ignore the artefacts being processed by human beings. By focusing on the outputs of the organisation, an artefact-centric view helps create a network of artefacts, and a component-based structure of the organisation and its supply chain participants. Since the relationship is based on the components, i.e. after the stakeholders are identified, the interdependency between stakeholders and the focal organisation can be measured. Each stakeholder is associated with two types of dependency, namely the stakeholder’s dependency on the focal organisation and the focal organisation’s dependency on the stakeholder. We identify three factors for each type of dependency and propose the equations that calculate the dependency indexes. Once both types of the dependency indexes are calculated, each stakeholder can be placed and categorised into one of the four groups, namely critical stakeholder, mutual benefits stakeholder, replaceable stakeholder, and easy care stakeholder. The mutual dependency grid and the dependency gap analysis, which further investigates the priority of each stakeholder by calculating the weighted dependency gap between the focal organisation and the stakeholder, subsequently help the focal organisation to better understand its stakeholders and manage its stakeholder relationships

A component-based method for stakeholder analysis

Stakeholders can facilitate or hinder an organisation’s performance significantly. The identification and management of the stakeholder is one of the key business activities for organisations. Although stakeholder identification is the first step of stakeholder analysis, there is little attention paid to the methodologies for stakeholder identification. This paper uses a system view point and proposes a component-based method for stakeholder identification and analysis, which focuses on the artefacts as linkage between different sub-systems of an organisation. Stakeholders, identified through components, include the processors who produce, use, communicate and control the component making process. The identified stakeholders can then be mapped into a stakeholder relationship map according to the components that are being used to identify the stakeholders. This method provides a novel approach to identify stakeholders through artefacts and define stakeholder relationship, through the a rtefacts they are involved in. Hence, it provides a comprehensive and better understanding of stakeholder management

MRI Image Segmentation System of Uterine Fibroids Based on AR-Unet Network

Uterine fibroids are the most common benign tumors in female reproductive organs. The segmentation of uterine fibroids is crucial for accurate treatment. This paper proposes a new uterine fibroids MRI T2W image segmentation network AR-Unet (Attention Resnet101-Unet), which uses the deep neural network ResNet101 as the front end of feature extraction, extracts image semantic information, and combines U-net design ideas to build a network structure. The attention gate module is added before the upsampling and downsampling feature maps are spliced. We tested a total of 123 uterine fibroids MRI T2W images from 13 patients. The segmentation results were verified with expert-defined manual segmentation results. The average Dice coefficient, IOU value, sensitivity and specificity of all segmented images were 0.9044, 0.8443, 88.55% and 94.56%, the performance is better than ResNet101-Unet and Attention-Unet models, and finally the network is encapsulated into an auxiliary diagnostic system

Desiccation and cracking behaviour of clay layer from slurry state under wetting-drying cycles

International audienceLaboratory tests were conducted to investigate the effect of wetting-drying (W-D) cycles on the initiation and evolution of cracks in clay layer. Four identical slurry specimens were prepared and subjected to five subsequent W-D cycles. The water evaporation, surface cracks evolution and structure evolution during the W-D cycles were monitored. The effect of W-D cycles on the geometric characteristics of crack patterns was analyzed by image processing. The results show that the desiccation and cracking behaviour was significantly affected by the applied W-D cycles: the measured cracking water content c, surface crack ratio Rsc and final thickness hf of the specimen increased significantly in the first three W-D cycles and then tended to reach equilibrium; the formed crack patterns after the second W-D cycle were more irregular than that after the first W-D cycle; the increase of surface cracks was accompanied by the decrease of pore volume shrinkage during drying. In addition, it was found that the applied W-D cycles resulted in significant rearrangement of specimen structure: the initially homogeneous and non-aggregated structure was converted to a clear aggregated-structure with obvious inter-aggregate pores after the second W-D cycle; the specimen volume generally increased with increasing cycles due to the aggregation and increased porosity. The image analysis results show that the geometric characteristics of crack pattern were significantly influenced by the W-D cycles, but this influence was reduced after the third cycle. This is consistent with the observations over the experiment, and indicates that the image processing can be used for quantitatively analyzing the W-D cycle dependence of clay desiccation cracking behaviour

Water transport properties of boron nitride nanosheets incorporated thin film nanocomposite membrane for salt removal

This work has focused on the fabrication of thin film composite (TFC) and thin film nanocomposite (TFN) membranes for reverse osmosis (RO) application. Raw boron nitride (BN) and chemically activated boron nitride (A-BN) were used as nanofillers in polysulfone support layer and trimesoyl chloride (TMC) to improve the membrane performance. Different concentrations of BN and A-BN (ranging from 0 to 1 wt %) were added to the polysulfone (PSf) microporous support and polyamide layer was formed on top of PSf support through interfacial polymerization of 1,3-Phenylendiamine and trimesoyl chloride. The fabricated TFN membranes were characterized in terms of membranes structure, contact angle, separation properties, as well as RO performance. According to AFM and SEM images, TFN membranes showed larger average pore size and higher surface roughness as compared with TFC membrane. Thus, TFN membrane showed higher pure water flux but lower NaCl rejection. The addition of BN led to increase in pore size of membrane without increase the selectivity of membrane. The addition of both BN and A-BN into polyamide layer does not aid to improve the properties of membrane. In conclusion, BN nanoparticles showed the potential to be used as nanofillers that aid in formation of larger pore size

A Comparative Study on Improved Arrhenius-Type and Artificial Neural Network Models to Predict High-Temperature Flow Behaviors in 20MnNiMo Alloy

The stress-strain data of 20MnNiMo alloy were collected from a series of hot compressions on Gleeble-1500 thermal-mechanical simulator in the temperature range of 1173∼1473 K and strain rate range of 0.01∼10 s−1. Based on the experimental data, the improved Arrhenius-type constitutive model and the artificial neural network (ANN) model were established to predict the high temperature flow stress of as-cast 20MnNiMo alloy. The accuracy and reliability of the improved Arrhenius-type model and the trained ANN model were further evaluated in terms of the correlation coefficient (R), the average absolute relative error (AARE), and the relative error (η). For the former, R and AARE were found to be 0.9954 and 5.26%, respectively, while, for the latter, 0.9997 and 1.02%, respectively. The relative errors (η) of the improved Arrhenius-type model and the ANN model were, respectively, in the range of −39.99%∼35.05% and −3.77%∼16.74%. As for the former, only 16.3% of the test data set possesses η-values within ±1%, while, as for the latter, more than 79% possesses. The results indicate that the ANN model presents a higher predictable ability than the improved Arrhenius-type constitutive model

Intra-abdominal abscess caused by toothpick injury

SummaryWe present the case of a 42-year-old female who presented to our emergency department (ED) complaining of epigastric pain for four days. She had been seen in the outpatient department and ED previously for evaluation, but continued to experience epigastric pain with fever. Emergency panendoscopy was performed and a toothpick was discovered impacted in the duodenal bulb. The gastroenterologist was unable to remove the toothpick endoscopically. Computed tomography of the abdomen revealed a long and straight hyperdense foreign body, and intra-abdominal abscess formation. An emergency laparotomy was performed. The patient recovered gradually and was discharged 11 days later. She could not remember when she swallowed the wooden toothpick, but guessed that it was while out drinking. There is an old wives’ tale in Taiwan that putting a toothpick in the cup while drinking beer reduces the likelihood of abdominal distention from the carbonation of the beer