The Feasibility and Method of News Mass Customization (NMC)

Mass Customization (MC) is a new production mode developed from the combination of Mass Production (MP) and single customization. News businesses putting the News Mass Customization (NMC) in force has its inherent advantages and NMC is a new way to get competence. The paper firstly analyzes two problems notation of MC and NewsML which have strong relation with NMC. Secondly, Compared with the MC rules in manufacturing industry, we draw the feasibility of NMC in News Businesses. Finally,according to the usage of Petri nets, we describe the NMC process and provide a detailed implement method

Optimization of a Parallel CFD Code and Its Performance Evaluation on Tianhe-1A

This paper describes performance tuning experiences with a parallel CFD code to enhance its performance and flexibility on large scale parallel computers. The code solves the incompressible Navier-Stokes equations based on the novel Slightly Compressible Model on three-dimensional structure grids. High level loop transformations and argument based code specialization are utilized to optimize its uniprocessor performance. Static arrays are converted into dynamically allocated arrays to improve the flexibility. The grid generator is coupled with the flow solver so that they can exchange grid data in the memory. A detailed performance evaluation is performed. The results show that our uniprocessor optimizations improve the performance of the flow solver for 1.38 times to 3.93 times on Tianhe-1A supercomputer. In memory grid data exchange optimization speeds up the application startup time by nearly two magnitudes. The optimized code exhibits an excellent parallel scalability running realistic test cases. On 4 096 CPU cores, it achieves a strong scaling parallel efficiency of 77.39 % and a maximum performance of 4.01 Tflops

Application of a Spectral Method to Simulate Quasi-Three-Dimensional Underwater Acoustic Fields

The solution and synthesis of quasi-three-dimensional sound fields have always been core issues in computational ocean acoustics. Traditionally, finite difference algorithms have been employed to solve these problems. In this paper, a novel numerical algorithm based on the spectral method is devised. The quasi-three-dimensional problem is transformed into a problem resembling a two-dimensional line source using an integral transformation strategy. Then, a stair-step approximation is adopted to address the range dependence of the two-dimensional problem; because this approximation is essentially a discretization, the range-dependent two-dimensional problem is further simplified into a one-dimensional problem. Finally, we apply the Chebyshev--Tau spectral method to accurately solve the one-dimensional problem. We present the corresponding numerical program for the proposed algorithm and describe some representative numerical examples. The simulation results ultimately verify the reliability and capability of the proposed algorithm.Comment: 43 pages, 20 figures. arXiv admin note: text overlap with arXiv:2112.1360

Electrochemical determination of chemical oxygen demand using Ti/TiO2 electrode.

To overcome the shortcomings of the conventional potassium dichromate method (PDM) for monitoring chemical oxygen demand (COD) of waters, many efforts have been made on developing quick and environment-friendly techniques. Among all alternatives, electrochemical (EC) techniques are very competitive due to their relatively simple devices and quickness. A number of electrodes have been fabricated to investigate electrochemical determination of COD. However, little work has been reported on Ti/TiO2 based electrode for this purpose. In the present work, Ti/Ti/TiO2 electrode was simply prepared by anodic oxidation of pure titanium. Aqueous solutions of potassium hydrogen phthalate and phenol were electrolyzed by chronocoulometry in a three-electrode system with Ti/Ti/TiO2 as working electrode (anode). Organic compounds were electrochemically oxidized on Ti/Ti/TiO2 electrode by hydroxyl radicals and the released electrons were recorded and transferred to currents. The electric currents were proportional to the COD values of the water samples being investigated. Based on data of COD values and corresponding currents, a linear regression equation was obtained for a certain kind of waste water. With the regression equation, current of an unknown water sample was transferred to its COD value. Conditions for the presented EC method were set up as cell voltage 2.0V v.s. SCE and pH 7.0. The linear range of COD was of about 25~530 mg/L. COD values of real waste water samples were measured by Ti/Ti/TiO2 electrode and the relative errors were all in the range of ±8% compared with data determined by conventional PDM. The electrochemicalmethodology was successfully applied to evaluate COD in waste water

Task-Distributionally Robust Data-Free Meta-Learning

Data-Free Meta-Learning (DFML) aims to efficiently learn new tasks by leveraging multiple pre-trained models without requiring their original training data. Existing inversion-based DFML methods construct pseudo tasks from a learnable dataset, which is inversely generated from the pre-trained model pool. For the first time, we reveal two major challenges hindering their practical deployments: Task-Distribution Shift (TDS) and Task-Distribution Corruption (TDC). TDS leads to a biased meta-learner because of the skewed task distribution towards newly generated tasks. TDC occurs when untrusted models characterized by misleading labels or poor quality pollute the task distribution. To tackle these issues, we introduce a robust DFML framework that ensures task distributional robustness. We propose to meta-learn from a pseudo task distribution, diversified through task interpolation within a compact task-memory buffer. This approach reduces the meta-learner's overreliance on newly generated tasks by maintaining consistent performance across a broader range of interpolated memory tasks, thus ensuring its generalization for unseen tasks. Additionally, our framework seamlessly incorporates an automated model selection mechanism into the meta-training phase, parameterizing each model's reliability as a learnable weight. This is optimized with a policy gradient algorithm inspired by reinforcement learning, effectively addressing the non-differentiable challenge posed by model selection. Comprehensive experiments across various datasets demonstrate the framework's effectiveness in mitigating TDS and TDC, underscoring its potential to improve DFML in real-world scenarios

Efficient Commitment to Functional CD34+ Progenitor Cells from Human Bone Marrow Mesenchymal Stem-Cell-Derived Induced Pluripotent Stem Cells

The efficient commitment of a specialized cell type from induced pluripotent stem cells (iPSCs) without contamination from unknown substances is crucial to their use in clinical applications. Here, we propose that CD34+ progenitor cells, which retain hematopoietic and endothelial cell potential, could be efficiently obtained from iPSCs derived from human bone marrow mesenchymal stem cells (hBMMSC-iPSCs) with defined factors. By treatment with a cocktail containing mesodermal, hematopoietic, and endothelial inducers (BMP4, SCF, and VEGF, respectively) for 5 days, hBMMSC-iPSCs expressed the mesodermal transcription factors Brachyury and GATA-2 at higher levels than untreated groups (P<0.05). After culturing with another hematopoietic and endothelial inducer cocktail, including SCF, Flt3L, VEGF and IL-3, for an additional 7–9 days, CD34+ progenitor cells, which were undetectable in the initial iPSC cultures, reached nearly 20% of the total culture. This was greater than the relative number of progenitor cells produced from human-skin-fibroblast-derived iPSCs (hFib-iPSCs) or from the spontaneous differentiation groups (P<0.05), as assessed by flow cytometry analysis. These induced cells expressed hematopoietic transcription factors TAL-1 and SCL. They developed into various hematopoietic colonies when exposed to semisolid media with hematopoietic cytokines such as EPO and G-CSF. Hematopoietic cell lineages were identified by phenotype analysis with Wright-Giemsa staining. The endothelial potential of the cells was also verified by the confirmation of the formation of vascular tube-like structures and the expression of endothelial-specific markers CD31 and VE-CADHERIN. Efficient induction of CD34+ progenitor cells, which retain hematopoietic and endothelial cell potential with defined factors, provides an opportunity to obtain patient-specific cells for iPSC therapy and a useful model for the study of the mechanisms of hematopoiesis and drug screening

Incidence, clinical characteristics and prognosis of tumor lysis syndrome following B-cell maturation antigen-targeted chimeric antigen receptor-T cell therapy in relapsed/refractory multiple myeloma

Background aimsB-cell maturation antigen (BCMA)-targeted chimeric antigen receptor-T cell (CAR-T) therapy is used for refractory or relapsed multiple myeloma (r/r MM). However, CAR-T-related tumor lysis syndrome (TLS) has been observed. We aimed to elucidate the incidence, clinical and laboratory characteristics, and prognosis of CAR-T cell-related TLS.MethodsPatients (n=105) with r/r MM treated with BCMA-targeted CAR-T cell therapy were included. Patient characteristics, laboratory parameters, and clinical outcomes were assessed.ResultsEighteen (17.1%) patients developed TLS after BCMA-targeted CAR-T cell therapy. The median time till TLS onset was 8 days. Patients with TLS had steep rise in uric acid (UA), creatinine, and lactate dehydrogenase (LDH) within 6 days following CAR-T cell infusion and presented earlier and persistent escalation of cytokines (C-reactive protein [CRP], interleukin-6 [IL-6], interferon-γ [IFN-γ], and ferritin levels). All 18 patients had cytokine release syndrome (CRS), of which 13 (72.2%) developed grade 3–4 CRS. Three of 18 patients (16.7%) developed immune effector cell-associated neurotoxicity syndrome (ICANS): two patients with grade 1 ICANS and one with grade 2 ICANS. TLS development had a negative effect on the objective response rate (77.8% in the TLS group vs. 95.4% in the non-TLS group, p&lt;0.01). During the median follow-up of 15.1 months, the median PFS was poorer of patients with TLS (median: 3.4 months in the TLS group vs. 14.7 months in the non-TLS group, p&lt;0.001, hazard ratio [HR]=3.5 [95% confidence interval [CI] 1.5–8.5]). Also, TLS development exhibited significant effects on OS (median: 5.0 months in the TLS group vs. 39.8 months in the non-TLS group, p&lt;0.001, hazard ratio [HR]=3.7 [95% CI 1.3–10.3]). TLS was associated with a higher tumor burden, elevated baseline creatinine and UA levels, severe CRS, pronounced CAR-T cell expansion, and corticosteroid use.ConclusionTLS is a frequently observed CAR-T therapy complication and negatively influences clinical response and prognosis. Close monitoring for TLS should be implemented during CAR-T cell therapy, especially for those at high TLS risk