Time-dependent reliability of corroded mild steel pipes by different failure modes

This study aims to analytically assess the time-dependent failure of corrosion-induced mild steel pipes by employing two fracture failure criteria: the fracture toughness-based criterion and the stress-based criterion. The investigation intends to identify the influential factors that impinge upon the assessment of failure probability within this context. It is found that there is a linear relationship between the ratio of wall thickness to inner radius and the probability of failure and that between the internal pressure and the probability of failure. Notably, the influence on the evaluation of failure probability by the ratio of wall thickness to inner radius is more prominent than the internal pressure. It is also found that a comprehensive criterion is necessary for evaluating the fracture resistance of corroded mild steel pipes, which considers both initial fracture toughness and ultimate stress. These findings can provide theoretical evidence for pipe engineers to develop maintenance or repair strategies in mild steel pipes. The significance of this paper is the development of an analytical framework for predicting the probability of failure of corroded mild steel pipes, considering the complexities of elastic-plastic fracture mechanics.</p

Performance of digital image correction technique for mild steel with different strain hardening effects

This paper investigates the performance of Digital Image Correction (DIC) technique in determining the initial fracture toughness of mild steel with different strain hardening effects. To achieve this goal, the results of DIC technique-based method are compared with those of the commonly used unloading compliance (UC) method. The comparison results reveal that the DIC technique-based method exhibit a good agreement with the UC method in determining initial fracture toughness, with a deviation of less than 3.0 %. Additionally, the DIC technique-based method demonstrates the consistency in determining the initial fracture toughness, independent of the ratio of initial pre-crack length to width. Furthermore, the importance of strain hardening effects on initial fracture toughness follows the order of strain hardening capacity, effective yield stress, and yield offset. The significance of this paper is that it provides a deep understanding of the performance of the DIC technique in determining the initial fracture toughness of mild steel.</p

Influence of Free Consultation Services on Patients’ Willingness to Pay in Online Medical Platforms

Online medical platforms have emerged as a popular means for patients to access high-quality medical services efficiently. These platforms offer a variety of services, including paid consultations and free consultations. Given that doctors can increase their revenue through these platforms, researchers should investigate how to improve patients’ willingness to pay for these services. Drawing upon social exchange theory, stimulus-organism-response theory, and the information systems (IS) success model, this study proposes a model and five hypotheses to examine the influence of free medical consultations on patients’ willingness to buy paid services. To test these hypotheses, a questionnaire survey was conducted, and the collected data were analyzed using the structural equation model. The results indicate that the quality of information and services provided by doctors during free consultations positively affects patients’ willingness to pay. By introducing information quality and service quality into the IS success model in the context of free medical consultations, this study contributes to the literature on online medical platforms and expands our understanding of patients’ behavior. The findings of this study can be useful for online medical platforms and doctors to design effective platform functions and individual behavioral strategies

Binder-Free Nickel Oxide Lamellar Layer Anchored CoOx_{x} Nanoparticles on Nickel Foam for Supercapacitor Electrodes

To enhance the connection of electroactive materials/current collector and accelerate the transport efficiency of the electrons, a binder-free electrode composed of nickel oxide anchored CoO$_{x}$ nanoparticles on modified commercial nickel foam (NF) was developed. The nickel oxide layer with lamellar structure which supplied skeleton to load CoO_{x) electroactive materials directly grew on the NF surface, leading to a tight connection between the current collector and electroactive materials. The fabricated electrode exhibits a specific capacitance of 475 F/g at 1 mA/cm$^{2}$. A high capacitance retention of 96% after 3000 cycles is achieved, attributed to the binding improvement at the current collector/electroactive materials interface. Moreover, an asymmetric supercapacitor with an operating voltage window of 1.4 V was assembled using oxidized NF anchored with cobalt oxide as the cathode and activated stainless steel wire mesh as the anode. The device achieves a maximum energy density of 2.43 Wh/kg and power density of 0.18 kW/kg, respectively. The modified NF substrate conducted by a facile and effective electrolysis process, which also could be applied to deposit other electroactive materials for the energy storage device

Original Article One stage laminoplasty and posterior herniotomy for the treatment of myelopathy caused by cervical stenosis with cervical disc herniation

Abstract: The aim of the study was to introduce a method of one stage laminoplasty and posterior herniotomy for myelopathy caused by cervical stenosis with cervical disc herniation and to evaluate the clinical efficacy of this surgery. From 1999 to 2008, 18 patients with myelopathy caused by cervical stenosis with cervical disc herniation who underwent this procedure were included. The average age was 63 years (range 48-74 years), and the average follow-up period was 46 months (range 3-108 months). Neurologic status was evaluated using the JOA scoring system. Neurological symptoms improvement was seen in all patients after surgery. The average JOA score was 14.22±1.86 by final follow-up, which was higher than preoperative values (P&lt;0.01), and the average improvement in neurological function was 76.63%. Neurologic examination showed that excellent results had been obtained by 10 patients, good results by 8 patients, with no fair or poor results. 2 patients developed cerebrospinal fluid leakage after surgery and recovered during the follow-up period. One patient with cervical disc herniation developed postoperative C5 palsy on the axle side on the third day after surgery. She completely recovered by 1 month after surgery. No other patients experienced postoperative neurologic complications. Complete anterior and posterior decompression of the spinal cord was achieved after surgery. We concluded that one stage laminoplasty and posterior herniotomy is an effective, reliable, and safe procedure for the treatment of myelopathy caused by cervical stenosis with cervical disc herniation

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System

Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to take humans out of the loop when building artificial intelligence (AI) applications, scant literature has focused on how AutoML works well in open-environment scenarios such as the process of training and updating large models, industrial supply chains or the industrial metaverse, where people often face open-loop problems during the search process: they must continuously collect data, update data and models, satisfy the requirements of the development and deployment environment, support massive devices, modify evaluation metrics, etc. Addressing the open-environment issue with pure data-driven approaches requires considerable data, computing resources, and effort from dedicated data engineers, making current AutoML systems and platforms inefficient and computationally intractable. Human-computer interaction is a practical and feasible way to tackle the problem of open-environment AI. In this paper, we introduce OmniForce, a human-centered AutoML (HAML) system that yields both human-assisted ML and ML-assisted human techniques, to put an AutoML system into practice and build adaptive AI in open-environment scenarios. Specifically, we present OmniForce in terms of ML version management; pipeline-driven development and deployment collaborations; a flexible search strategy framework; and widely provisioned and crowdsourced application algorithms, including large models. Furthermore, the (large) models constructed by OmniForce can be automatically turned into remote services in a few minutes; this process is dubbed model as a service (MaaS). Experimental results obtained in multiple search spaces and real-world use cases demonstrate the efficacy and efficiency of OmniForce

Effects of high-intensity interval training, moderate-intensity continuous training, and guideline-based physical activity on cardiovascular metabolic markers, cognitive and motor function in elderly sedentary patients with type 2 diabetes (HIIT-DM): a protocol for a randomized controlled trial

Background and objectiveSedentary behavior is of increasing concern in older patients with type 2 diabetes mellitus (T2DM) due to its potential adverse effects on cardiovascular health, cognitive function, and motor function. While regular exercise has been shown to improve the health of individuals with T2DM, the most effective exercise program for elderly sedentary patients with T2DM remains unclear. Therefore, the objective of this study was to assess the impact of high-intensity interval training (HIIT), moderate-intensity continuous training (MICT), and guideline-based physical activity programs on the cardiovascular health, cognitive function, and motor function of this specific population.MethodsThis study will be a randomized, assessor-blind, three-arm controlled trial. A total of 330 (1:1:1) elderly sedentary patients diagnosed with T2DM will be randomly assigned the HIIT group (10 × 1-min at 85–95% peak HR, intersperse with 1-min active recovery at 60–70% peak HR), MICT (35 min at 65–75% peak HR), and guideline-based group (guideline group) for 12 weeks training. Participants in the guideline group will receive 1-time advice and weekly remote supervision through smartphones. The primary outcomes will be the change in glycosylated hemoglobin (HbA1c) and brain-derived neurotrophic factor (BDNF) after 12-weeks. Secondary outcomes will includes physical activity levels, anthropometric parameters (weight, waist circumference, hip circumference, and body mass index), physical measurements (fat percentage, muscle percentage, and fitness rate), cardiorespiratory fitness indicators (blood pressure, heart rate, vital capacity, and maximum oxygen), biochemical markers (high-density lipoprotein, low-density lipoprotein, triglycerides, total cholesterol, and HbA1c), inflammation level (C-reactive protein), cognitive function (reaction time and dual-task gait test performance), and motor function (static balance, dynamic balance, single-task gait test performance, and grip strength) after 12 weeks.DiscussionThe objective of this study is to evaluate the effect of 12 weeks of HIIT, MICT, and a guideline-based physical activity program on elderly sedentary patients diagnosed with T2DM. Our hypothesis is that both HIIT and MICT will yield improvements in glucose control, cognitive function, cardiopulmonary function, metabolite levels, motor function, and physical fitness compared to the guideline group. Additionally, we anticipate that HIIT will lead to greater benefits in these areas. The findings from this study will provide valuable insights into the selection of appropriate exercise regimens for elderly sedentary individuals with T2DM.Ethics and disseminationThis study has been approved by the Ethics Review Committee of the Reproductive Hospital Affiliated with China Medical University (approval number: 202203). Informed consent will be obtained from all participants or their guardians. Upon completion, the authors will submit their findings to a peer-reviewed journal or academic conference for publication.Clinical trial registrationChinese Clinical Trial Registry, identifier ChiCTR2200061573

Privacy Protection Scheme for Data Aggregation in Wireless Sensor Networks Based on PRDA+ Protocol

To improve the data aggregation privacy protection scheme in wireless sensor network (WSN), a new scheme is put forward based on the privacy protection of polynomial regression and the privacy protection method based on the homomorphic encryption. The polynomial data aggregation (PRDA+) protocol is also proposed. In this scheme, the node and the base station will pre-deploy a secret key, and the random number generator encrypts the random number for the seed through the private key, which protects the privacy of the data. Then, by comparing the decrypted aggregate data through the correlation between the two metadata, the integrity protection of the data is realized. A weighted average aggregation scheme that can be verified is proposed. In view of the different importance of user information, the corresponding weights are set for each sensor node. EL Gamal digital signature is used to authenticate sensor nodes. The results show that the signature verification algorithm enables the scheme to resist data tampering and data denial, and to trace the source of erroneous data.</p

Privacy Protection Scheme for Data Aggregation in Wireless Sensor Networks Based on PRDA+ Protocol

To improve the data aggregation privacy protection scheme in wireless sensor network (WSN), a new scheme is put forward based on the privacy protection of polynomial regression and the privacy protection method based on the homomorphic encryption. The polynomial data aggregation (PRDA+) protocol is also proposed. In this scheme, the node and the base station will pre-deploy a secret key, and the random number generator encrypts the random number for the seed through the private key, which protects the privacy of the data. Then, by comparing the decrypted aggregate data through the correlation between the two metadata, the integrity protection of the data is realized. A weighted average aggregation scheme that can be verified is proposed. In view of the different importance of user information, the corresponding weights are set for each sensor node. EL Gamal digital signature is used to authenticate sensor nodes. The results show that the signature verification algorithm enables the scheme to resist data tampering and data denial, and to trace the source of erroneous data