Comparison of the effects of Tripterygii totorum and sulfasalazine on rheumatoid arthritis: A retrospective cohort study

Purpose: To compare, in a retrospective study, the effects and safety profiles of Tripterygii totorum and sulfasalazine in patients with rheumatoid arthritis (RA) following 24 weeks of treatment. Methods: RA patients (n = 164) who were treated with Tripterygii totorum or sulfasalazine from August 2012 to February 2016 were included in this study. The major end-point was ≥ 20 % improvement as per American College of Rheumatology (ACR) criterion (ACR 20 response) after 24 weeks. Moreover, ACR 50 and ACR 70 responses were studied. The safety parameters investigated comprised of adverse events, vital signs, as well as hematological and biochemical indices (blood counts, electrolyte levels, and kidney and liver function). Results: At 24 weeks, ACR 20 response was 57.32 % in patients on Tripterygii totorum, while the corresponding value in patients on sulfasalazine was 39.02 % (p = 0.02). In the Tripterygii totorum group, ACR 50 response was 41.46 %, while ACR 70 response was 29.27 %. In sulfasalazine group, ACR 50 response was identified in 26.83 % of the patients, while ACR 70 response was seen in 21.95 % of patients. Adverse events were greater in the Tripterygii totorum group than in sulfasalazine group. Conclusion: These results suggest that Tripterygii Totorum significantly mitigates RA, with a tolerable safety profile. However, there is need for long-term or controlled trials to ascertain the therapeutic potential of Tripterygii totorum in RA. Keywords: Traditional Chinese medicine, Tripterygii totorum, Sulfasalazine, Rheumatoid arthriti

Effects of early lumbar cistern drainage of cerebrospinal fluid and combination of edaravone and nimodipine on vasospasm, intracranial pressure, inflammatory factors in traumatic subarachnoid hemorrhage

Purpose: To investigate the effect of early lumbar cistern drainage (LCD) of cerebrospinal fluid (CSF) and combination of edaravone and nimodipine on vasospasm, intracranial pressure (ICP), serum inflammation, S100 and vascular endothelial growth factor (VEGF) levels in traumatic subarachnoid hemorrhage (tSAH). Methods: Treatment was administered to 136 patients divided into control group (n = 68) and study group (n = 68). Serum inflammation was determined by assessing the levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) while nitric oxide (NO), endothelin-1 (ET-1), S100 and VEGF levels were determined by enzyme-linked immunosorbent assay (ELISA). Serum C-reactive protein (CRP) level was measured by immunoturbidimetry. Perfusion weighted imaging was performed and the mean transit time (MTT), cerebral blood flow (CBF), cerebral blood volume (CBV), mean flow velocity (Vm) and pulsatility index (PI) were recorded. Glasgow coma scale (GCS) score and Montreal cognitive assessment (MoCA) score were used to compare the differences in therapeutic effect. Results: Compared with values before treatment, Vm, PI, NO, CBF, CBV, GCS score and MoCA score were significantly increased (p < 0.05), while ICP, serum levels of TNF-α, IL-6, CRP, ET-1, S100 and VEGF and MTT significantly decreased (p < 0.05). Therapeutic response rate of the study group (89.71 %) was higher than that of control group (66.18%) (p < 0.05). Conclusion: Early LCD of CSF and combination of edaravone and nimodipine reduces the degree of cerebral vasospasm and contribute to brain function recovery in the treatment of patients with tSAH. This therapeutic strategy requires further clinical trials before application in clinical practice

Forward and Inverse D-Form Modelling based on Optimisation

D-Form is a special piece-wise developable surface formed by aligning the boundaries of two planar domains. It has been widely used in different design scenarios. In this paper, we study how to computationally and intuitively model D-Forms. We present an optimisation-based framework that can efficiently generate D-Form shapes. Our framework can model D-Forms with two approaches based on two different user inputs, including the forward modelling from two given planar domains and, more importantly, the inverse modelling from a given space curve where the planar domains are no longer needed. Our optimisation is devised based on two critical characteristics of D-Forms. Firstly, the constituent developable surfaces of a D-Form are isometrically deformed from planar domains. Secondly, there is a close relationship between a D-Form and the convex hull of its seam. Through extensive evaluation, we demonstrate that our approach can model plausible D-Forms efficiently from various inputs with different geometric properties.<br/

Deep Learning-Based Modeling of 5G Core Control Plane for 5G Network Digital Twin

Digital twin is a key enabler to facilitate the development and implementation of new technologies in 5G and beyond networks. However, the complex structure and diverse functions of the current 5G core network, especially the control plane, lead to difficulties in building the core network of the digital twin. In this paper, we propose two novel data-driven architectures for modeling the 5G control plane and implement corresponding deep learning models, namely 5GC-Seq2Seq and 5GC-former, based on the Vanilla Seq2Seq model and Transformer decoder respectively. To train and test models, we also present a solution that allows the signaling messages to be interconverted with vectors, which can be utilized in dataset construction. The experiments are based on 5G core network signaling data collected by the Spirent C50 network tester, including various procedures related to registration, handover, PDU sessions, etc. Our results show that 5GC-Seq2Seq achieves over 99.98% F1-score (A metric to measure the accuracy of positive samples) with a relatively simple structure, while 5GC-former attains higher than 99.998% F1-score by establishing a more complex and highly parallel model, indicating that the method proposed in this paper reproduces the major functions of the core network control plane in 5G digital twin with high accuracy

The noise control of minicar body in white based on acoustic panel participation method

It is very important to predict the acoustic radiation of vehicle body for the control of interior noise. Firstly, the kinetic equations of coupled acoustic-structural finite element method are explained and the numerical analytical methods of noise transfer function and acoustic panel participation are further obtained. Then the coupled acoustic-structural finite element model of body in white and passenger compartment cavity of a minicar is established and verified by modal test. The passive side of engine mounting points are chosen as the excitation points, and driver’s right ear is the output point of sound pressure response. The noise transfer function is calculated and the critical frequency of vehicle interior noise is obtained. The acoustic panel participation analysis of vehicle roof and floor are conducted, and the key acoustic panels are identified. In order to reduce the noise of critical frequency, the measures, pasting damping material and welding beam, are adopted. The results indicate that, compared with the results of structure improvement of modal method, the vehicle interior noise is controlled more effectively by using the acoustic panel participation analytical method

Engineering microencapsulated PCM slurry with improved performance for cold storage

Cold is essential in many aspects of everyday life ranging from food, drugs and chemicals processing, storage and distribution to control of thermal comfort and superconductors in power electronics. The demand for cooling in all its forms is accelerating with the growing global urban population1. However, existing cooling technologies consume large amounts of energy and can be highly polluting in terms of carbon and other emissions2. One way of reducing the energy required for cooling and increasing cooling technologies efficiency whilst minimising their environmental impact involves the storage of energy efficiently as cold and to deliver cooling whenever needed without worsening peak demand. To this end we have developed a range of microencapsulated low freezing point phase change materials in slurries (MPCMSs) where the PCM core and the carrier fluid are both liquid coolants. Our strategy was to encapsulate LPCM and structured LPCM with thermal conductivity enhancer materials using inorganic-organic composite shell material to achieve improved cold storage performance from -35˚C to -110˚C. Figure 1 shows microencapsulated diethyl benzene based coolant and structured methanol-water dispersed in ethylene glycol-water and silicone based fluid, respectively. Initial results are promising and these MPCMSs now offer new horizon for cold storage and energy management. Please click Additional Files below to see the full abstract

3D LiDAR Aided GNSS NLOS Mitigation for Reliable GNSS-RTK Positioning in Urban Canyons

GNSS and LiDAR odometry are complementary as they provide absolute and relative positioning, respectively. Their integration in a loosely-coupled manner is straightforward but is challenged in urban canyons due to the GNSS signal reflections. Recent proposed 3D LiDAR-aided (3DLA) GNSS methods employ the point cloud map to identify the non-line-of-sight (NLOS) reception of GNSS signals. This facilitates the GNSS receiver to obtain improved urban positioning but not achieve a sub-meter level. GNSS real-time kinematics (RTK) uses carrier phase measurements to obtain decimeter-level positioning. In urban areas, the GNSS RTK is not only challenged by multipath and NLOS-affected measurement but also suffers from signal blockage by the building. The latter will impose a challenge in solving the ambiguity within the carrier phase measurements. In the other words, the model observability of the ambiguity resolution (AR) is greatly decreased. This paper proposes to generate virtual satellite (VS) measurements using the selected LiDAR landmarks from the accumulated 3D point cloud maps (PCM). These LiDAR-PCM-made VS measurements are tightly-coupled with GNSS pseudorange and carrier phase measurements. Thus, the VS measurements can provide complementary constraints, meaning providing low-elevation-angle measurements in the across-street directions. The implementation is done using factor graph optimization to solve an accurate float solution of the ambiguity before it is fed into LAMBDA. The effectiveness of the proposed method has been validated by the evaluation conducted on our recently open-sourced challenging dataset, UrbanNav. The result shows the fix rate of the proposed 3DLA GNSS RTK is about 30% while the conventional GNSS-RTK only achieves about 14%. In addition, the proposed method achieves sub-meter positioning accuracy in most of the data collected in challenging urban areas

Role of Self-Efficacy and Resistance to Innovation on the Demotivation and Insufficient Learning Capabilities of Preservice English Normal Students in China

Learning capabilities among students are the crucial element for the student’s success in learning a particular language, and this phenomenon needs recent studies. The current study examines the impact of self-efficacy and resistance to innovation on the demotivation and insufficient learning capabilities of preservice English normal students in China. The current research also investigates the mediating impact of demotivation among self-efficacy, resistance to innovation, and insufficient learning capabilities. The questionnaires were employed by the researchers to gather the data from chosen respondents. The preservice English students are the respondents of the study. These are selected using purposive sampling. These questionnaires were forwarded to them by personal visits. The researchers have sent 690 surveys but only received 360 surveys and used them for analysis. These surveys represented a 52.17% response rate. The SPSS-AMOS was applied to test the relationships among variables and also test the hypotheses of the study. The results revealed that self-efficacy and resistance to innovation have a significant and a positive linkage with demotivation and insufficient learning capabilities. The findings also indicated that demotivation significantly mediates self-efficacy, resistance to innovation, and insufficient learning capabilities. The article helps the policymakers to establish the regulations related to the improvement of learning capabilities using innovation adoption and motivation of the students

Generation of Human Epidermis-Derived Mesenchymal Stem Cell-like Pluripotent Cells and their reprogramming in mouse chimeras

Stem cells can be derived from the embryo (embryonic stem cells, ESCs), from adult tissues (adult stem cells, ASCs), and by induction of fibroblasts (induced pluripotent stem cells, iPSs). Ethical problems, immunological rejection, and difficulties in obtaining human tissues limit the use of ESCs in clinical medicine. Induced pluripotent stem cells are difficult to maintain in vitro and carry a greater risk of tumor formation. Furthermore, the complexity of maintenance and propagation is especially difficult in the clinic. Adult stem cells can be isolated from several adult tissues and present the possibility of self-transplantation for the clinical treatment of a variety of human diseases. Recently, several ASCs have been successfully isolated and cultured in vitro, including hematopoietic stem cells (HSCs) , mesenchymal stem cells (MSCs), epidermis stem cells, neural stem cells (NSCs), adipose-derived stem cells (ADSCs), islet stem cells, and germ line stem cells. Human mesenchymal stem cells originate mainly from bone marrow, cord blood, and placenta, but epidermis-derived MSCs have not yet been isolated. We isolated small spindle-shaped cells with strong proliferative potential during the culture of human epidermis cells and designed a medium to isolate and propagate these cells. They resembled MSCs morphologically and demonstrated pluripotency in vivo; thus, we defined these cells as human epidermis-derived mesenchymal stem cell-like pluripotent cells (hEMSCPCs). These hEMSCPCs present a possible new cell resource for tissue engineering and regenerative medicine