Design and Analysis of an Improved Tubular Permanent Magnet Linear Machine with a T-type Magnet Array

The surface-mounted tubular permanent magnet linear machine (SM-TPMLM) is widely used in many industrial applications. However, the PMs are fragile and easily fall off when linear machines are operated at reciprocating oscillation speed over long periods or encounter harsh environments, the exposed PMs are susceptible to corrosion, which reduces the service life of linear machines. To solve this problem, an improved tubular permanent magnet linear machine with a T-type magnet array (T-TPMLM) is proposed. The axial and radial magnets are combined in a magnetic pole array to increase the thrust force, power and protect the PMs. First, an equivalent analytical model of T-TPMLM is established to predict the magnetic field, the subdomain method with Schwarz-Christoffel mapping method is introduced to consider slotting effect and end effect. Then, to verify the merit of the proposed T-TPMLM, a quantitative electromagnetic performance comparison with two traditional SM-TPMLM including radial magnetization and Halbach magnetization is performed through the finite element analysis method (FEM). Besides, the mechanical strength of three linear machines is discussed briefly. Finally, a prototype of proposed T-TPMLM is manufactured and tested to validate the effectiveness of the analytical model and the FEA predicted results. The results show that the proposed machine offers high electromagnetic performance

Analysis of temporal and spatial evolution characteristics and influencing factors of land use transformation in Hebei Province from the perspective of supply and demand

This study focuses on the counties and districts of Hebei Province as the research unit. It adopts a supply-demand perspective to analyze the spatial-temporal evolution characteristics of farmland utilization transformation in the province, investigate the coordination of this transformation, and explore the influencing factors. The weight of indicators is calculated using the entropy weighting method and Analytic Hierarchy Process The comprehensive evaluation model is then applied to calculate the supply-demand transformation index of farmland utilization in Hebei Province for the years 2005, 2010, 2015, and 2020. Furthermore, the spatial-temporal evolution characteristics are analyzed using the kernel density estimation method. The coupling coordination degree model is selected to explain the relationship between the supply-demand transformation of farmland utilization. Finally, the influencing factors are analyzed using the geographical detector model. The research findings are as follows: 1) The supply-demand transformation index of farmland utilization in Hebei Province has shown an increasing trend during the study period. The standard deviation of the supply transformation index has increased over time, while the demand transformation index has increased at a faster rate. High-density supply transformation is concentrated in the southeast, particularly in the eastern part of Shijiazhuang. Conversely, the northwest exhibits a low-density supply transformation. High-density demand transformation is observed in urban areas across the province, with a significant expansion from 2010 to 2015. 2) There is a strong correlation between the supply and demand transformation of farmland utilization. The coupling coordination degree has gradually improved from 2005 to 2015, transitioning from rapid to stable growth. The level of coupling coordination has shifted from imbalance to coordination. The mountainous areas in the northwest of Hebei Province exhibit relatively lower coupling coordination degrees, while the plains in the southeast demonstrate higher levels. 3) The supply transformation of farmland utilization is closely correlated with the natural environment, particularly elevation and topography. On the other hand, the demand transformation is closely associated with socio-economic development, with a scarcity of supply driving an increase in the demand transformation index. Industrial developed areas show a higher intensity of demand for farmland utilization. 4) To ensure the sustainable utilization of farmland while meeting food production needs, it is crucial to enhance contiguous farmland and mechanization levels, promote the integration of agriculture and tourism, establish an ecological barrier around Beijing-Tianjin, and optimize the ecological compensation mechanism for farmland. The above findings provide valuable insights into farmland utilization transformation and suggest important strategies for its sustainable development

Noninvasive prenatal diagnosis of 21-Hydroxylase deficiency using target capture sequencing of maternal plasma DNA.

Here, we aimed to validate a noninvasive method using capture sequencing for prenatal diagnosis of congenital adrenal hyperplasia due to 21-Hydroxylase deficiency (21-OHD). Noninvasive prenatal diagnosis (NIPD) of 21-OHD was based on 14 plasma samples collected from 12 families, including four plasma sample collected during the first trimester. Targeted capture sequencing was performed using genomic DNA from the parents and child trios to determine the pathogenic and wild-type alleles associated with the haplotypes. Maternal plasma DNA was also sequenced to determine the fetal inheritance of the allele using hidden Markov model-based haplotype linkage analysis. The effect of fetal DNA fraction and sequencing depth on the accuracy of NIPD was investigated. The lower limit of fetal DNA fraction was 2% and the threshold mean sequence depth was 38, suggesting potential advantage if used in early gestation. The CYP21A2 genotype of the fetus was accurately determined in all the 14 plasma samples as early as day 1 and 8 weeks of gestation. Results suggest the accuracy and feasibility of NIPD of 21-OHD using a small target capture region with a low threshold for fetal DNA fraction and sequence depth. Our method is cost-effective and suggests diagnostic applications in clinical practice

Magnetic and Cryogenic Design of the MICE Coupling Solenoid Magnet System

The Muon Ionization Cooling Experiment (MICE) will demonstrate ionization cooling in a short section of a realistic cooling channel using a muon beam at Rutherford Appleton Laboratory in the UK. The coupling magnet is a superconducting solenoid mounted around four 201MHz RF cavities, which produces magnetic field up to 2.6 T on the magnet centerline to keep muons within the iris of RF cavities windows. The coupling coil with inner radius of 750mm, length of 285mm and thickness of 102.5mm will be cooled by a pair of 1.5 W at 4.2 K small coolers. This paper will introduce the updated engineering design of the coupling magnet made by ICST in China. The detailed analyses on magnetic fields, stresses induced during the processes of winding, cool down and charging, and cold mass support assembly are presented as well

Design and Construction of a Prototype Solenoid Coil for MICE Coupling Magnets

A superconducting coupling solenoid mounted around four conventional RF cavities, which produces up to 2.6 T central magnetic field to keep the muons within the cavities, is to be used for the Muon Ionization Cooling Experiment (MICE). The coupling coil made from copper matrix NbTi conductors is the largest of three types of magnets in MICE both in terms of 1.5 m inner diameter and about 13MJ stored magnetic energy at full operation current of 210A. The stress induced inside the coil assembly during cool down and magnet charging is relatively high. In order to validate the design method and develop the coil winding technique with inside-wound SC splices required for the coupling coil, a prototype coil made from the same conductor and with the same diameter and thickness but only one-fourth long as the coupling coil was designed and fabricated by ICST. The prototype coil was designed to be charged to strain conditions that are equivalent or greater than would be encountered in the coupling coil. This paper presents detailed design of the prototype coil as well as developed coil winding skills. The analyses on stress in the coil assembly and quench process were carried out

Voxel- and tensor-based morphometry with machine learning techniques identifying characteristic brain impairment in patients with cervical spondylotic myelopathy

AimThe diagnosis of cervical spondylotic myelopathy (CSM) relies on several methods, including x-rays, computed tomography, and magnetic resonance imaging (MRI). Although MRI is the most useful diagnostic tool, strategies to improve the precise and independent diagnosis of CSM using novel MRI imaging techniques are urgently needed. This study aimed to explore potential brain biomarkers to improve the precise diagnosis of CSM through the combination of voxel-based morphometry (VBM) and tensor-based morphometry (TBM) with machine learning techniques.MethodsIn this retrospective study, 57 patients with CSM and 57 healthy controls (HCs) were enrolled. The structural changes in the gray matter volume and white matter volume were determined by VBM. Gray and white matter deformations were measured by TBM. The support vector machine (SVM) was used for the classification of CSM patients from HCs based on the structural features of VBM and TBM.ResultsCSM patients exhibited characteristic structural abnormalities in the sensorimotor, visual, cognitive, and subcortical regions, as well as in the anterior corona radiata and the corpus callosum [P < 0.05, false discovery rate (FDR) corrected]. A multivariate pattern classification analysis revealed that VBM and TBM could successfully identify CSM patients and HCs [classification accuracy: 81.58%, area under the curve (AUC): 0.85; P < 0.005, Bonferroni corrected] through characteristic gray matter and white matter impairments.ConclusionCSM may cause widespread and remote impairments in brain structures. This study provided a valuable reference for developing novel diagnostic strategies to identify CSM

Electroacupuncture stimulation modulates functional brain connectivity in the treatment of pediatric cerebral palsy: a case report

BackgroundPediatric cerebral palsy (CP) is a non-progressive brain injury syndrome characterized by central motor dysfunction and insufficient brain coordination ability. The etiology of CP is complex and often accompanied by diverse complications such as intellectual disability and language disorders, making clinical treatment difficult. Despite the availability of pharmacological interventions, rehabilitation programs, and spasticity relief surgery as treatment options for CP, their effectiveness is still constrained. Electroacupuncture (EA) stimulation has demonstrated great improvements in motor function, but its comprehensive, objective therapeutic effects on pediatric CP remain to be clarified.MethodsWe present a case of a 5-year-old Chinese female child who was diagnosed with CP at the age of 4. The patient exhibited severe impairments in motor, language, social, and cognitive functions. We performed a 3-month period of EA rehabilitation, obtaining resting state functional magnetic resonance imaging (rs-fMRI) of the patient at 0 month, 3 months and 5 months since treatment started, then characterized brain functional connectivity patterns in each phase for comparison.ResultsAfter a 12-month follow-up, notable advancements were observed in the patient’s language and social symptoms. Changes of functional connectivity patterns confirmed this therapeutic effect and showed specific benefits for different recovery phase: starting from language functions then modulating social participation and other developmental behaviors.ConclusionThis is a pioneering report demonstrating the longitudinal effect of EA stimulation on functional brain connectivity in CP patients, suggesting EA an effective intervention for developmental disabilities (especially language and social dysfunctions) associated with pediatric CP

A niche-based evolutionary algorithm with dual cooperative archive for solving constrained multi-objective optimization problems

Constrained multi-objective optimization problems (CMOPs) are commonly encountered in engineering practice. The key to effectively solving these problems lies in achieving a timely balance between convergence, diversity, and feasibility during iterations. Furthermore, the appropriate utilization of infeasible solutions is crucial for identifying potential feasible regions. In order to accomplish this comprehensive objective, we propose a novel dual-stage constrained multi-objective evolutionary algorithm (CMOEA) called NACMOEA in this paper. It can be characterized by the following features: 1) Introducing a novel niche-based individual selection and infeasible solution utilization strategy to enhance convergence, diversity, and feasibility. 2) Presenting a cooperative search strategy assisted by dual archives to approximate the constrained Pareto front (CPF) from both feasible and infeasible perspectives, thereby improving the efficiency of obtaining the complete CPF. 3) Designing a new stage switch method based on non-dominant coverage rate to ensure proper completion of search stage switching. Extensive experiments demonstrate that NACMOEA exhibits competitive comprehensive performance when compared with other advanced CMOEAs