Near-Infrared Spectroscopy Combined with Absorbance Upper Optimization Partial Least Squares Applied to Rapid Analysis of Polysaccharide for Proprietary Chinese Medicine Oral Solution

Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance upper optimization partial least squares (AUO-PLS), was proposed and successfully applied to the wavelength selection. Based on varied partitioning of the calibration and prediction sample sets, the parameter optimization was performed to achieve stability. On the basis of the AUO-PLS method, the selected upper bound of appropriate absorbance was 1.53 and the corresponding wavebands combination was 400 - 1880 & 2088 - 2346 nm. With the use of random validation samples excluded from the modeling process, the root-mean-square error and correlation coefficient of prediction for polysaccharide were 27.09 mg·L-1 and 0.888, respectively. The results indicate that the NIR prediction values are close to those of the measured values. NIR spectroscopy combined with AUO-PLS method provided a promising tool for quantification of the polysaccharide for PCM oral solution and this technique is rapid and simple when compared with conventional methods.

OPTIMAL INTERIOR PARTIAL REGULARITY FOR NONLINEAR ELLIPTIC SYSTEMS WITH DINI CONTINUOUS COEFFICIENTS

In this article, we consider nonlinear elliptic systems of divergence type with Dini continuous coefficients. The authors use a new method introduced by Duzaar and Grotowski, to prove partial regularity for weak solutions, based on a generalization of the technique of harmonic approximation and directly establish the optimal HSlder exponent for the derivative of a weak solution on its regular set.

AO-MW-PLS method applied to rapid quantification of teicoplanin with near-infrared spectroscopy

Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reagent-free and rapid quantification method for TCP in the TCP-Tris-HCl mixture samples was developed using near infrared(NIR)spectroscopy by focusing our attention on the fermentation process for TCP.The absorbance optimization(AO)partial least squares(PLS)was proposed and integrated with the moving window(MW)PLS,which is called AO-MW-PLS method,to select appropriate wavebands.Amodel set that includes various wavebands that were equivalent to the optimal AO-MW-PLS waveband was,proposed based on statistical considerations.The public region of all equivalent wavebands was just one of the equivalent wavebands.The obtained public regions were 1540-1868 nm for TCP and 1114-1310 nm for Tris.The root-mean-square error and correlation coeficient for leave-one-out cross validation were 0.046 mg mL^(-1)and 0.9998 mg mL^(-1)for TCP,and 0.235 mg mL^(-1)and 0.9986 mg mL^(-1)for Tris,respectively.All the models achieved highly accurate prediction effects,and the selected wavebands provided valuable references for designing specialized spectrometers.This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields.

A PARTIAL ROBUST OPTIMIZATION APPROACH TO INVENTORY MANAGEMENT FOR THE OFFLINE-TO-ONLINE PROBLEM UNDER DIFFERENT SELLING PRICES

This study examines an optimal inventory strategy when a retailer markets a product at different selling prices through a dual-channel supply chain, comprising an online channel and an offiine channel. Using the operating pattern of the offiine-to-online （020） business model, we develop a partial robust optimization （PRO） model. Then, we provide a closed-form solution when only the mean and standard deviation of the online channel demand distribution is known and the offiine channel demand follows a uniform distribution （partial robust）. Specifically, owing to the good structural properties of the solution, we obtain a heuristic ordering formula for the general distribution case （i.e., the offiine channel demand follows a general distribution）. In addition, a series of numerical experiments prove the rationality of our conjecture. Moreover, after comparing our solution with other possible policies, we conclude that the PRO approach improves the performance of incorporating the internet into an existing supply chain and, thus, is able to adjust the level of conservativeness of the solution. Finally, in a degenerated situation, we compare our PRO approach with a combination of information approach. The results show that the PRO approach has more ＂robust＂ performance. As a result, a reasonable trade-off between robustness and performance is achieved.

The LP-rounding plus greed approach for partial optimization revisited

There are many optimization problems having the following common property:Given a total task consisting of many subtasks,the problem asks to find a solution to complete only part of these subtasks.Examples include the k-Forest problem and the k-Multicut problem,etc.These problems are called partial optimization problems,which are often NP-hard.In this paper,we systematically study the LP-rounding plus greed approach,a method to design approximation algorithms for partial optimization problems.The approach is simple,powerful and versatile.We show how to use this approach to design approximation algorithms for the k-Forest problem,the k-Multicut problem,the k-Generalized connectivity problem,etc.

Method for Fault Diagnosis and Speed Control of PMSM

In the field of fault tolerance estimation,the increasing attention in electrical motors is the fault detection and diagnosis.The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis.It has now turned out to be essential to diagnose faults at their very inception;as unscheduled machine downtime can upset deadlines and cause heavy financial burden.In this paper,fault diagnosis and speed control of permanent magnet synchronous motor(PMSM)is proposed.Elman Neural Network(ENN)is used to diagnose the fault of permanent magnet synchronous motor.Both the fault location and fault severity are considered.In this,eccentricity fault may occur in the motor.To control the speed of the permanent magnet synchronous motor,Dolphin Swarm Optimization(DSO)algorithm is used.The proposed work is simulated by using MATLAB in terms of amplitude,speed and torque.The comparison graph of speed vs.torque obtained by the proposed method gives better result compared to the other existing techniques.The proposed work is also compared with Particle Swarm Optimization(PSO)and Elephant Herding Optimization(EHO)algorithm.The proposed usage of Elman Neural Network to detect the fault and the usage of Dolphin Swarm Optimization algorithm to control the speed of the permanent magnet synchronous motor gives better outcome.

MAC Layer Resource Allocation for Wireless Body Area Networks

Wireless body area networks （WBANs） can provide low-cost, timely healthcare services and are expected to be widely used for e-healthcare in hospitals. In a hospital, space is often limited and multiple WBANs have to coexist in an area and share the same channel in order to provide healthcare services to different patients. This causes severe interference between WBANs that could significantly reduce the network throughput and increase the amount of power consumed by sensors placed on the body. There-fore, an efficient channel-resource allocation scheme in the medium access control （MAC） layer is crucial. In this paper, we devel-op a centralized MAC layer resource allocation scheme for a WBAN. We focus on mitigating the interference between WBANs and reducing the power consumed by sensors. Channel and buffer state are reported by smartphones deployed in each WBAN, and channel access allocation is performed by a central controller to maximize network throughput. Sensors have strict limitations in terms of energy consumption and computing capability and cannot provide all the necessary information for channel allocation in a timely manner. This deteriorates network performance. We exploit the temporal correlation of the body area channel in order to minimize the number of channel state reports necessary. We view the network design as a partly observable optimization prob-lem and develop a myopic policy, which we then simulate in Matlab.

THE MAXIMUM PRINCIPLE FOR PARTIALLY OBSERVED OPTIMAL CONTROL OF FORWARD-BACKWARD STOCHASTIC SYSTEMS WITH RANDOM JUMPS

This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.

PARTIAL REGULARITY RESULT OF SUPERQUADRATIC ELLIPTIC SYSTEMS WITH DINI CONTINUOUS COEFFICIENTS

We consider the partial regularity for weak solutions to superquadratic elliptic systems with controllable growth condition, under the assumption of Dini continuous coefficients. The proof relies upon an iteration scheme of a decay estimate for a new type of excess functional. To establish the decay estimate, we use the technique of A-harmonic approximation and obtain a general criterion for a weak solution to be regular in the neighborhood of a given point. In particular, the proof yields directly the optimal H¨older exponent for the derivative of the weak solutions on the regular set.