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Painleve-Kuratowski convergence of the solution sets is investigated for the perturbed set-valued weak vector variational inequalities with a sequence of mappings converging continuously. The closedness and Painleve-Kuratowski upper convergence of the solution sets are obtained. We also obtain Painleve-Kuratowski upper convergence when the sequence of mappings converges graphically. By virtue of a sequence of gap functions and a key assumption, Painleve-Kuratowski lower convergence of the solution sets is established. Some examples are given for the illustration of our results.

In this paper, we carry out the empirical numerical study of the [l.sub.[infinity] portfolio selection model where the objective is to minimize the maximum individual risk. We compare the numerical performance of this model with that of the Markowitz's quadratic programming model by using real data from the Stock Exchange of Hong Kong. Our computational results show that the [l.sub.[infinity]]. model has a similar performance to the Markowitz's model and that the [l.sub.[[infinity] model is not sensitive to the data. For the situation with only two assets, we establish that the expected return of the minimum variance model is less than that of the minimum [l.sub.[infinity]]: model when both variance and the return rate of one asset is less than the corresponding values of another asset. Keywords: variance: standard deviation; portfolio selection: risk aversion measures; numerical study.

We present a novel numerical approach for solving nonlinear constrained optimal control problems (NCOCPs). Instead of directly solving the NCOCPs, we start by linearizing the constraints and dynamic system, which results in a sequence of sub-problems. For each sub-problem, we use finite number of Chebyshev polynomials to estimate the control and state vectors. To eliminate the errors at non-collocation points caused by conventional collocation methods, we additionally estimate the coefficient functions involved in the linear constraints and dynamic system by Chebyshev polynomials. By leveraging the characteristics of Chebyshev polynomials, the approximate sub-problem is changed into an equivalent nonlinear optimization problem with linear equality constraints. Consequently, any feasible point of the approximate sub-problem will satisfy the constraints and dynamic system throughout the entire time scale. To validate the efficacy of the new method, we solve three examples and assess the accuracy of the method through the computation of its approximation error. Numerical results obtained show that our approach achieves lower approximation error when compared to the Chebyshev pseudo-spectral method. The proposed method is particularly suitable for scenarios that require high-precision approximation, such as aerospace and precision instrument production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 ISA. Published by Elsevier Ltd. All rights reserved.)

The problem of blood transshipment and allocation in the context of the COVID-19 epidemic has many new characteristics, such as two-stage, trans-regional, and multi-modal transportation. Considering these new characteristics, we propose a novel multi-objective optimization model for the two-stage emergent blood transshipment-allocation. The objectives considered are to optimize the quality of transshipped blood, the satisfaction of blood demand, and the overall cost including shortage penalty. An improved integer encoded hybrid multi-objective whale optimization algorithm (MOWOA) with greedy rules is then designed to solve the model. Numerical experiments demonstrate that our two-stage model is superior to one-stage optimization methods on all objectives. The degree of improvement ranges from 0.69 to 66.26%., (© The Author(s) 2023.)

Background: The aim of the study is to derive deeper insights into the control of the spread of COVID-19 during the second half of 2021, from seven countries that are among the earliest to have accelerated the deployment of COVID-19 vaccines. Methodology . This study used data from the Global COVID-19 Index and Google COVID-19 Community Mobility Reports. Data was extracted on the 5 th of each month from July to December 2021. Seven countries were selected-United Kingdom, United States of America, Israel, Canada, France, Italy, and Austria. The sample comprised number of new cases, hospitalisations, ICU admissions and deaths due to COVID-19, government stringency measures, partial and full vaccination coverage, and changes in human mobility. Principal component analysis was conducted, and the results were interpreted and visualized through 2-dimensional and 3-dimensional plots to reveal the systematic patterns of the data., Results: The first three principal components captured around 77.3% of variance in the data. The first component was driven by the spread of COVID-19 (31.6%), the second by mobility activities (transit, retail, and recreational) (24.3%), whereas the third by vaccination coverage, workplace-related mobility, and government stringency measures (21.4%). Visualizations showed lower or moderate levels of severity in COVID-19 during this period for most countries. By contrast, the surge in the USA was more severe especially in September 2021. Human mobility activities peaked in September for most countries and then receded in the following months as more stringent government measures were imposed, and countries began to grapple with a surge in COVID-19 cases., Conclusion: This study delineated the spread of COVID-19, human mobility patterns, widespread vaccination coverage, and government stringency measures on the overall control of COVID-19. While at least moderate levels of stringency measures are needed, high vaccine coverage is particularly important in curbing the spread of this disease., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Jane K. L. Teh et al.)

Background: The aim of the study was to visualize the global spread of the COVID-19 pandemic over the first 90 days, through the principal component analysis approach of dimensionality reduction., Methods: This study used data from the Global COVID-19 Index provided by PEMANDU Associates. The sample, representing 161 countries, comprised the number of confirmed cases, deaths, stringency indices, population density and GNI per capita (USD). Correlation matrices were computed to reveal the association between the variables at three time points: day-30, day-60 and day-90. Three separate principal component analyses were computed for similar time points, and several standardized plots were produced., Results: Confirmed cases and deaths due to COVID-19 showed positive but weak correlation with stringency and GNI per capita. Through principal component analysis, the first two principal components captured close to 70% of the variance of the data. The first component can be viewed as the severity of the COVID-19 surge in countries, whereas the second component largely corresponded to population density, followed by GNI per capita of countries. Multivariate visualization of the two dominating principal components provided a standardized comparison of the situation in the161 countries, performed on day-30, day-60 and day-90 since the first confirmed cases in countries worldwide., Conclusion: Visualization of the global spread of COVID-19 showed the unequal severity of the pandemic across continents and over time. Distinct patterns in clusters of countries, which separated many European countries from those in Africa, suggested a contrast in terms of stringency measures and wealth of a country. The African continent appeared to fare better in terms of the COVID-19 pandemic and the burden of mortality in the first 90 days. A noticeable worsening trend was observed in several countries in the same relative time frame of the disease's first 90 days, especially in the United States of America., Competing Interests: The authors have declared that no competing interests exist.

The novelty and the contribution of this paper consists of applying an iterative joint singular spectrum analysis and low-rank decomposition approach for suppressing the spikes in an electroencephalogram. First, an electroencephalogram is filtered by an ideal lowpass filter via removing its discrete Fourier transform coefficients outside the wave band, the wave band, the wave band, the wave band and the wave band. Second, the singular spectrum analysis is performed on the filtered electroencephalogram to obtain the singular spectrum analysis components. The singular spectrum analysis components are sorted according to the magnitudes of their corresponding eigenvalues. The singular spectrum analysis components are sequentially added together starting from the last singular spectrum analysis component. If the variance of the summed singular spectrum analysis component under the unit energy normalization is larger than a threshold value, then the summation is terminated. The summed singular spectrum analysis component forms the first scale of the electroencephalogram. The rest singular spectrum analysis components are also summed up together separately to form the residue of the electroencephalogram. Next, the low-rank decomposition is performed on the residue of the electroencephalogram to obtain both the low-rank component and the sparse component. The low-rank component is added to the previous scale of the electroencephalogram to obtain the next scale of the electroencephalogram. Finally, the above procedures are repeated on the sparse component until the variance of the current scale of the electroencephalogram under the unit energy normalization is larger than another threshold value. The computer numerical simulation results show that the spike suppression performance based on our proposed method outperforms that based on the state-of-the-art methods., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results”.

In the current emerging trend of using human mesenchymal stromal cell (MSCs) for cell therapy, large quantities of cells are needed for clinical testing. Current methods of culturing cells, using tissue culture flasks or cell multilayer vessels, are proving to be ineffective in terms of cost, space and manpower. Therefore, alternatives such as large-scale industrialized production of MSCs in stirred tank bioreactors using microcarriers (MCs) are needed. Moreover, the development of biodegradable MCs for MSC expansion can streamline the bioprocess by eliminating the need for enzymatic cell harvesting and scaffold seeding for bone-healing therapies. Our previous studies described a process of making regulated density (1.06 g/cm 3 ) porous polycaprolactone biodegradable MCs Light Polycarprolactone (LPCL) (MCs), which were used for expanding MSCs from various sources in stirred suspension culture. Here, we use human early MSCs (heMSCs) expanded on LPCL MCs for evaluation of their osteogenic differentiation potential in vitro as well as their use in vivo calvarial defect treatment in a rat model. In summary, (i) in vitro data show that LPCL MCs can be used to efficiently expand heMSCs in stirred cultures while maintaining surface marker expression; (ii) LPCL MCs can be used as scaffolds for cell transfer for transplantation in vivo; (iii) 50% sub-confluency, mid-logarithmic phase, on LPCL MCs (50% confluent) exhibited higher secretion levels of six cytokines (interleukin [IL]-6, IL-8, Vascular endothelial growth factor (VEGF), Monocyte Chemoattractant Protein-1 (MCP-1), growth-regulated oncogene-α (GRO-α) and stromal cell-derived factor-1α (SDF-1α)) as compared with 100% confluent, stationary phase cultures (100% confluent); (iv) these 50% confluent cultures demonstrated better in vitro osteogenic differentiation capacity as compared with 100% confluent cultures (higher levels of calcium deposition and at earlier stage); the improved bone differentiation capacity of these 50% confluent cultures was also demonstrated at the molecular level by higher expression of early osteoblast genes Runt-related transcription factor 2 (RUNX2), Alkaline phosphatase (ALP), collagen type I, osterix and osteocalcin); and (v) in vivo implantation of biodegradable LPCL MCs covered with 50% heMSCs into rats with calvarial defect demonstrated significantly better bone formation as compared with heMSCs obtained from monolayer cultures (5.1 ± 1.6 mm 3 versus 1.3 ± 0.7 mm 3 ). Moreover, the LPCL MCs covered with 50% heMSCs supported better in vivo bone formation compared with 100% confluent culture (2.1 ± 1.3 mm 3 ). Taken together, our study highlights the potential of implanting 50% confluent MSCs propagated on LPCL MCs as optimal for bone regeneration. This methodology allows for the production of large numbers of MSCs in a three-dimensional (3D) stirred reactor, while supporting improved bone healing and eliminating the need for a 3D matrix support scaffold, as traditionally used in bone-healing treatments., (Copyright © 2019 International Society for Cell and Gene Therapy. Published by Elsevier Inc. All rights reserved.)

Rapidly evolving cell-based therapies towards clinical trials demand alternative approaches for efficient expansion of adherent cell types such as human mesenchymal stem cells (hMSCs). Using microcarriers (100-300 µm) in a stirred tank bioreactor offers considerably enhanced surface to volume ratio of culture environment. However, downstream purification of the harvested cell product needs to be addressed carefully due to distinctive features and fragility of these cell products. This work demonstrates a novel alternative approach which utilizes inertial focusing to separate microcarriers (MCs) from the final cell suspension. First, we systematically investigated MC focusing dynamics inside scaled-up curved channels with trapezoidal and rectangular cross-sections. A trapezoidal spiral channel with ultra-low-slope (Tan(α) = 0.0375) was found to contribute to strong MC focusing (~300 < Re < ~400) while managing high MC volume fractions up to ~1.68%. Accordingly, the high-throughput trapezoidal spiral channel successfully separated MCs from hMSC suspension with total cell yield~94% (after two passes) at a high volumetric flow rate of ~30 mL/min (Re~326.5).

Topological insulators with spin-momentum-locked topological surface states are expected to exhibit a giant spin-orbit torque in the topological insulator/ferromagnet systems. To date, the topological insulator spin-orbit torque-driven magnetization switching is solely reported in a Cr-doped topological insulator at 1.9 K. Here we directly show giant spin-orbit torque-driven magnetization switching in a Bi 2 Se 3 /NiFe heterostructure at room temperature captured using a magneto-optic Kerr effect microscope. We identify a large charge-to-spin conversion efficiency of ~1-1.75 in the thin Bi 2 Se 3 films, where the topological surface states are dominant. In addition, we find the current density required for the magnetization switching is extremely low, ~6 × 10 5  A cm -2 , which is one to two orders of magnitude smaller than that with heavy metals. Our demonstration of room temperature magnetization switching of a conventional 3d ferromagnet using Bi 2 Se 3 may lead to potential innovations in topological insulator-based spintronic applications.

This paper addresses the problem of robust fuzzy L2-L∞ filtering for a class of uncertain nonlinear discrete-time Markov jump systems (MJSs) with nonhomogeneous jump processes. The Takagi-Sugeno fuzzy model is employed to represent such nonlinear nonhomogeneous MJS with norm-bounded parameter uncertainties. In order to decrease conservation, a polytope Lyapunov function which evolves as a convex function is employed, and then, under the designed mode-dependent and variation-dependent fuzzy filter which includes the membership functions, a sufficient condition is presented to ensure that the filtering error dynamic system is stochastically stable and that it has a prescribed L2-L∞ performance index. Two simulated examples are given to demonstrate the effectiveness and advantages of the proposed techniques.

Background Aims: Mesenchymal stromal cells (MSCs) are being investigated as potential cell therapies for many different indications. Current methods of production rely on traditional monolayer culture on tissue-culture plastic, usually with the use of serum-supplemented growth media. However, the monolayer culturing system has scale-up limitations and may not meet the projected hundreds of billions to trillions batches of cells needed for therapy. Furthermore, serum-free medium offers several advantages over serum-supplemented medium, which may have supply and contaminant issues, leading to many serum-free medium formulations being developed., Methods: We cultured seven MSC lines in six different serum-free media and compared their growth between monolayer and microcarrier culture., Results: We show that (i) expansion levels of MSCs in serum-free monolayer cultures may not correlate with expansion in serum-containing media; (ii) optimal culture conditions (serum-free media for monolayer or microcarrier culture) differ for each cell line; (iii) growth in static microcarrier culture does not correlate with growth in stirred spinner culture; (iv) and that early cell attachment and spreading onto microcarriers does not necessarily predict efficiency of cell expansion in agitated microcarrier culture., Conclusions: Current serum-free media developed for monolayer cultures of MSCs may not support MSC proliferation in microcarrier cultures. Further optimization in medium composition will be required for microcarrier suspension culture for each cell line., (Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.)

We report the strong experimental evidence of the existence of topological surface states with large electric field tunability and mobility in β-Ag2Te. Pronounced 2D Shubnikov-de Haas oscillations have been observed in β-Ag2Te nanoplates. A Berry phase is determined to be near π using the Landau level fan diagram for a relatively wide nanoplate while the largest electric field ambipolar effect in topological insulator so far (~2500%) is observed in a narrow nanoplate. The π Berry phase and the evolution of quantum oscillations with gate voltage (Vg) in the nanoplates strongly indicate the presence of topological surface states in β-Ag2Te. Moreover, the mobility of the narrow Ag2Te nanoplate is about several thousand cm(2)s(-1)V(-1). Our results suggest that β-Ag2Te has the potential to become an important material in the investigation of topological insulators.

Genetic information, such as single nucleotide polymorphism (SNP) data, has been widely recognized as useful in prediction of disease risk. However, how to model the genetic data that is often categorical in disease class prediction is complex and challenging. In this paper, we propose a novel class of nonlinear threshold index logistic models to deal with the complex, nonlinear effects of categorical/discrete SNP covariates for Schizophrenia class prediction. A maximum likelihood methodology is suggested to estimate the unknown parameters in the models. Simulation studies demonstrate that the proposed methodology works viably well for moderate-size samples. The suggested approach is therefore applied to the analysis of the Schizophrenia classification by using a real set of SNP data from Western Australian Family Study of Schizophrenia (WAFSS). Our empirical findings provide evidence that the proposed nonlinear models well outperform the widely used linear and tree based logistic regression models in class prediction of schizophrenia risk with SNP data in terms of both Types I/II error rates and ROC curves.

We report on the high mobility wide electron slabs with enhanced correlation effects by tailoring the polarization effects in a functionally graded ZnMgO/ZnO heterostructures. The characteristics of three-dimensional (3D) spreading electrons are evidenced by the capacitance-voltage profiling and the quantization of 3D Fermi surface in magneto-transport measurements. Despite the weak spin-orbit interaction, such electron slabs are spin-polarized with a large zero-field spin splitting energy, which is induced by the carrier-mediated ferromagnetism. Our results suggest that the vast majority of electrons are localized at the surface magnetic moment which does not allow spin manipulations, and only in the region visited by the itinerant carriers that the ferromagnetic exchange interactions via coupling to the surface local moments contribute to the spin transport. The host ferromagnetism is likely due to the formation of Zn cation vacancies on the surface regime induced by the stabilization mechanism and strain-relaxation in ZnMgO polar ionic surface.

This correspondence is concerned with the robust stability for a class of impulsive switched systems under the LQ guaranteed cost control. Some results on robust stability for this class of impulsive switched systems are obtained. Sufficient conditions for the existence of a guaranteed cost control law are also given. Subject to these sufficient conditions, the closed-loop uncertain impulsive switched system under the guaranteed cost control law is robustly stable with a guaranteed cost value.

This paper considers the problems of global exponential stability and exponential convergence rate for impulsive high-order Hopfield-type neural networks with time-varying delays. By using the method of Lyapunov functions, some sufficient conditions for ensuring global exponential stability of these networks are derived, and the estimated exponential convergence rate is also obtained. As an illustration, an numerical example is worked out using the results obtained.

In using the B-spline network for nonlinear system modeling, owing to a lack of suitable theoretical results, it is quite difficult to choose an appropriate set of knot points to achieve a good network structure for minimizing, say, a minimum error criterion. In this paper, a novel knot-optimizing B-spline network is proposed to approximate the general nonlinear system behavior. The knot points are considered to be independent variables in the B-spline network and are optimized together with the B-spline expansion coefficients. The simulated annealing algorithm with an appropriate search strategy is used as an optimization algorithm for the training process in order to avoid any possible local minima. Examples involving dynamic systems up to six dimensions in the input space to the network are solved by the proposed method to illustrate the effectiveness of this approach.

An optimal parameter selection model of cancer chemotherapy in which two system parameters are unknown is formulated as a worst-case optimal parameter selection model. The model assumes that the unknown parameters lie within a known set. The system constraints must be satisfied over this entire set, and the objective function minimized in the worst case. The continuous dependence of the objective function and the system constraints upon the unknown parameters can be removed, making a numerical solution tractable. For the data considered it is proven that a cure is impossible no matter what the values of the unknown parameters in the parameter set. The optimal policy is shown to be relatively low dose intensity for the majority of the treatment, with the remaining drug delivered towards the end of the treatment interval.

Mathematical optimization techniques are applied to a simplified mathematical model of blood glucose dynamics to derive insulin infusion programs for the control of blood glucose levels in diabetic individuals. Two particular cases are discussed. First, the insulin infusion program which results in an initially high blood glucose level being reduced to acceptable levels. Second, the control of blood glucose levels following a meal, prior to which blood glucose and net blood-glycemic hormone were at their fasting levels.