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Malignant peritoneal effusion is a common complication of advanced malignancies, which has a poor prognosis for patients. Hyperthermic intraperitoneal chemotherapy (HIPEC) has been widely used in the treatment of advanced gynecological tumors, especially ovarian cancer (OC). Relative studies have indicated that HIPEC allows for direct exposure of tumor cells to high peritoneal concentrations of cytotoxic drugs without increasing systemic toxicity compared with intravenous treatment. Recombinant human tumor necrosis factor for injection (rmhTNF-NC) is a safely tolerated immunotherapeutic drug that has becoming a mainstay of treatment for malignant effusions. Currently, a prospective study is required to determining the efficacy of rmhTNF-NC plus cisplatin for the treatment of malignant peritoneal effusion for OC.Design and setting: This is a single-center, open trial will be performed in Zhongshan Affiliated Hospital, Guangzhou University of Chinese Medicine.Eligible patients will be those with advanced gynecologic cancers and who would be suitable for HIPEC.HIPEC with cisplatin and intraperitoneal perfusion with rmhTNF-NC.Further chemotherapy will be offered to patients as per current practice.OutcomesPilot study: Patients and clinicians' acceptability of the trial to assist in optimization of recruitment.Primary outcome: One-year overall survival (OS).Secondary outcomes: Progression-free survival (PFS), adverse events.Follow-up: One-year follow-up for OS.Sample size: Twenty patients to demonstrate therapeutic effect of peritoneal effusion caused by OC.This trial will determine the effectiveness of HIPEC with cisplatin and intraperitoneal perfusion with rmhTNF-NC for advanced gynecologic cancers, and guide the optimal treatment for these patients.

Background Ganoderma lucidum, a double-walled basidiospore produced by porous basidiomycete fungi, has been used as a traditional medicine for thousands of years. It is considered a valuable Chinese medicine for strengthening body resistance, invigorating the spleen, and replenishing Qi. G. lucidum contains a variety of active ingredients, such as polysaccharides, triterpenoids, nucleosides, sterols, alkaloids, polypeptides, fatty acids, steroids, and inorganic elements, and has anticancer, anti-inflammatory, hepatoprotection, hypoglycemic, anti-melanogenesis, anti-aging, and skin barrier-repairing activity. Conclusions The review summarizes the traditional usages, distribution, active constituents, structure, and biological effects of G. lucidum, with an aim to offer directions for further research and better usage of G. lucidum as a medicinal raw material.

We propose a novel fiber Bragg grating (FBG)-optical coherence tomography (OCT) catheter to reconstruct vascular shape by intravascular OCT imaging of the actual curvature as well as the bending direction of the vascular in real-time. Compared with the traditional OCT catheter, the FBG-OCT catheter uses the FBG encapsulated with half- sectioned stainless-steel tube as a flexural sensitive component. With the 360-degree rotation of the catheter, the encapsulated FBG will produce maximum tension and maximum compression at the bend of the blood vessel, and then get the solution of the curvature and direction of the bending catheter as well as the OCT imaging simultaneously. To test the proposed catheter for real-time measurement, a bending calibration system and a vascular prosthesis model to simulate the actual vascular bending morphology are manufactured through three-dimension (3D) printing. Experimental data shows that the new FBG-OCT catheter can acquire the OCT images and FBG bending parameters real-timely and synchronously. Further, the obtained bending parameters and OCT images are used to restore the morphology of the vascular model, which will provide corrective data for accurate measurements of further vascular plaques, blood flow, and intravascular pressure.

This paper proposes a multiplexing method of sensor subnets for the multiparameter heterogeneous fiber sensor network (MHFSN). In each sensor subnet, a continuous laser signal with a different wavelength is designed. This signal is used to identify the access subnet type and to monitor the subnet at all times. The correct recognition rate of this method can reach 100%. This method broadens the access subnet type, increases the number of sensors, and widens the measurement range. At the same time, we propose a robustness analysis model for MHFSN and analyze the light source stability of MHFSN. When the access subnet number increases, the failure rate of the shared mode gradually increases from 0.01 to 0.09, while the failure rate of the dedicated mode remains unchanged. The robustness model provides an effective means for system stability analysis.

Contrast optimization is a key issue in polarimetric imaging for the purpose of target detection. In practice, the noise could induce the intensity fluctuation of the image and thus lead to the decrease of the image contrast. A joint noise reduction method is proposed for contrast enhancement in Stokes polarimetric imaging. The proposed method is based on the relation of the joint polarimetric image set, which includes four images taken to calculate Stokes vector and one image taken at the optimal state of a polarization state analyzer (PSA). By our method, the traditional contrast-enhanced image is modified to decrease the disturbance of noise, and the contrast of the image is further enhanced. Both the theoretical analysis and the real-world experimental results demonstrate that our method can effectively decrease the disturbance by the noise and thus increase the contrast of the image. In particular, it is found that the effect of the proposed method is independent of the optimal PSA state when the regular tetrahedron measurement matrix is implemented.

A high-precision wavelength demodulation method based on optical fiber Fabry-Perot tunable (FPT) filter is proposed for the fiber Bragg grating temperature sensing system. This algorithm uses the original sampling data obtained from the data acquisition card to simultaneously calculate the transmission spectrum of the F-P etalon (FPE) and the reflection spectrum of the fiber Bragg grating (FPG) sensors. In each scanning cycle, the transmission spectrum wavelength of the F-P etalon (FPE) is calibrated dynamically in real time, the reflectance spectrum central wavelength of the FPE sensors is calculated by referring to the transmission spectrum wavelength of the FPE that has been calibrated. It effectively weakens the perturbation effect caused by the nonlinear and non-reproducibility of narrowband light source from the fiber FPT filter, reduces the numerical error and effectively eliminates the pseudo peak of the FPE, and greatly improves the measurement accuracy of the system. Most programming languages can implement this algorithm. A temperature sensing experiment for the proposed method has been carried out. Results showed that the demodulation precision by our method could reach up to ±0.2 °C, wavelength demodulation accuracy 3 pm.

We consider a multi-stage inventory system with stochastic demand and processing capacity constraints at each stage, for both finite-horizon and infinite-horizon, discounted-cost settings. For a class of such systems characterized by having the smallest capacity at the most downstream stage and system utilization above a certain threshold, we identify the structure of the optimal policy, which represents a novel variation of the order-up-to policy. We find the explicit functional form of the optimal order-up-to levels, and show that they depend (only) on upstream echelon inventories. We establish that, above the threshold utilization, this optimal policy achieves the decomposition of the multidimensional objective cost function for the system into a sum of single-dimensional convex optimization subproblems. This decomposition eliminates the curse of dimensionality and allows us to numerically solve the problem. We provide a fast algorithm to determine a (tight) upper bound on this threshold utilization for capacity-constrained inventory problems with an arbitrary number of stages. We make use of the algorithm to quantify upper bounds on the threshold utilization for three-, four-, and five-stage capacitated systems over a range of model parameters, and discuss insights that emerge. This article is protected by copyright. All rights reserved.

To determine in vitro anti-aging activity and identify the active chemical constituents in Ginkgo leaf extracts. The antioxidant properties of Ginkgo biloba leaves extracts were evaluated using 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) scavenging and 2,2’-azino-bis (3-ethylbenzothiazoline)-6 sulfonic acid radical (ABTS) scavenging assays. The inhibitory effects of extracts and chemical constituents on reactive oxygen species, matrix metalloproteinase-1 (MMP-1) and collagen tpye I level were tested using human dermal fibroblasts (HDFs). Reverse-phase liquid chromatography (RPLC) and ultra-performance liquid chromatography tandem mass spectroscopy (UPLC/MS/MS) were used to quantitatively analyze flavonoids and terpene trilactones in the extraction. The established quantitative analysis method was validated according to the regulatory guidelines. The extraction and compounds kaempferol 3-O-β-D-glucopyranoside, isorhamnetin-3-O-glucoside, myricetin, ginkgolide A and bilobalide could have potential anti-aging activities of G. biloba. The results suggest that G. biloba could be used as anti-aging products and as a cosmetic and medicinal raw material.

Document images are ubiquitous, but existing methods mainly focus on the text reading but not information understanding. In this paper, we propose a novel document image information extraction framework with application to domain-specific analysis. Key gains of our system result from the modularized implementation of the document analysis modules needed for different document analysis problems. Further, we provide an efficient text recognition approach that makes a trade-off between performance and running speed for document images and a novel information extraction method with both visual and semantic information. Our framework is scalable and customizable, and only a few annotations of the keyword-content mapping is needed towards domain-specific document analysis.

This paper proposes a heterogeneous structure of multiparameter optical fiber sensor network, which is composed of the quasidistributed temperature and strain sensor networks and the discrete pressure and vibration sensor networks. This network can multiplex different types of optical fiber sensors and can automatically identify the subnet type of the access network. We designed two structures of light source distribution and compared their advantages and disadvantages. The sensor network proposed in this paper provides a deliberate exploration for the construction of a large-capacity, large-scale, multiparameter, high-precision optical fiber sensor network.

Although vendor‐managed inventory (VMI) programs have gained popularity in practice, some empirical studies report that their implementations have not been successful. We conduct experiments to investigate behaviors in a supply chain where a supplier replenishes inventories for a retailer according to a VMI program under a revenue‐sharing contract. The results show that subjects’ decisions deviate significantly from the standard theoretical predictions because the retailer presents equality preference with adjustment, and the supplier exhibits fairness concern. Since the supplier bears not only the production cost, but also the risk of leftover inventory in the VMI program, we propose an approach that provides the retailer with an opportunity to voluntarily compensate the supplier with an additional percentage of revenue after demand realization. Experimental results based on this new operational procedure show that the retailer still presents equality preference with adjustment, but the supplier has a decision bias of ex post inventory error regret. The supply chain can perform better under the proposed approach than under only a revenue‐sharing contract. Interestingly, the proposed approach does not cause the retailer to share a higher percentage of revenue with the supplier, but it induces the supplier to replenish a higher stock quantity, which leads to higher profits for both the retailer and the supplier.

It is a challenge for investors to decide optimal configurations and operations of a concentrating solar power plant because of the new market trends, namely that the governments no longer offer secured and fixed tariff schemes regulated by Power Purchase Agreements, nor do they continue to provide subsidy over the power plant’s entire life. The concentrating solar power plant must adjust configurations and operations to address market price variation and subsidy decrease. This study presents a non-linear optimization model that captures the critical component investment costs and operational flexibility in the plant configuration. We use it to analyze economies of scale, thermal energy storage, economic curtailment, and hybrid systems with wind plant, and to evaluate their impact on plant configuration decisions under the new market trends. First, we find that the economic performance of the concentrating solar power plant, despite market price variation and subsidy decrease, can be enhanced substantially by optimal configurations and operations flexibility, which improve the overall plant utilization. Second, compared to the traditional fixed tariff scheme, the market-price-based tariff scheme can yield substantially higher net present value for the plant investment, due to the optimal configurations and flexible operations. Finally, our sensitivity analyses show that the optimal plant configurations are significantly affected by market price variations and the constraints of transmission line capacity.

This paper analyses several wavelength demodulation methods based on optical fiber Fabry-Perot tunable filter. In view of the shortcomings of these methods, we proposed a real-time data acquisition method and a simple and effective demodulation algorithm based on optical fiber Fabry-Perot tunable filter and set up a temperature sensing system. The sensing system consists of an FBG sensor part, a data acquisition part, a data demodulation part and a data display part, we introduce the operation of the data acquisition part by explaining how the hardware and software work. Then we introduce the method of data demodulation we proposed, and demonstrated the steps of data demodulation in detail. We test the performance of this data acquisition part by carrying out a temperature sensor experiment, and prove the effectiveness of the demodulation algorithm at the same time. In addition, most programming languages can implement this simple and effective algorithm.

We propose a real-time monitoring method for shield tunnel boring machine cutter wear based on chirped fiber Bragg grating (CFBG). We use the chirped fiber Bragg grating as the wear detection sensor. When the wear occurs at the end face of the wear detection sensor (the end face of chirped fiber Bragg grating), the grating area of the chirped fiber Bragg grating will shorten with the occurrence of wear, which causes the bandwidth of the grating reflection spectrum to be narrowed, and the correlation theory of the fiber Bragg grating is used to calculate the wear rate. Experimental data shows that the sensor can survive in the actual operating conditions of the shield tunnel boring machine. After calibration, measurement accuracy can less than 1mm, and it can be used for real time wear detection of large machinery, such as shield tunnel boring machine.

This paper presents the implementation of a real-time control algorithm based on model predictive control and neural network load forecasting for microgrid optimization. At each stage, the algorithm updates the optimal trajectory for system state in order to minimize operations costs while ensuring instantaneous power balance and physical constraints respect. The proposed framework is implemented on a semi-physical demonstrator including residential load, electric vehicles, solar panels and battery storage to assess viability and optimality of control policies. In order to assess control efficiency and influence of economic parameters, several scenarios are run in parallel on the semi-physical platform. The robustness against forecast error of the proposed control architecture is confirmed through sensitivity analysis with various error distributions.

An optical fiber Fabry-Perot (F-P) flow measurement technology is presented, which is based on partial bend structure. A 90° partial bend structure is designed to achieve the non-probe flow measurement with a pressure difference. The fluid simulation results of partial bend structure show that the error of the pressure difference is below 0.05 kPa during steady flow. The optical fiber F-P sensor mounted on the elbow with pressure test accuracy of 1% full scale is used to measure the fluid flow. Flow test results show that when the flow varies from 1 m(3)/h to 6.5 m(3)/h at ambient temperature of 25 °C, the response time is 1 s and the flow test accuracy is 4.5% of the F-P flow test system, proving that the F-P flow test method based on partial bend structure can be used in fluid flow measurement.

We propose a real-time parallel data acquisition and big data processing method. This method can multiplex different types of fiber sensors and quickly complete the simultaneous sampling of thousands of sensors on hundreds of channels in four-parameter heterogeneous fiber sensor network, its sampling frequency is up to 6.4MHz, and the data throughput is up to 13.8MB/s. This method is three times faster than the usual method.

A two-stage serial supply chain in which a retailer and his supplier are operating in make-to-stock environments and the retailer faces uncertain demands from the end-customers is studied. When this supply chain is centrally managed, the optimal policy is an extension of the Clark–Scarf echelon base stock policy. Since these supply chains are usually operated in a decentralized manner, an operational change is proposed that reduces the inefficiency associated with decentralization. The policy, which is called Periodic Flexibility (PF), provides the retailer with structural flexibility to order any amount in one period of a cycle, while requiring that the retailer receives a fixed-quantity shipment in the other periods. Optimal policies and their associated costs for the non-stationary inventory control problems faced by the retailer and the supplier under PF are characterized. A detailed computational study shows that PF improves the supply chain performance by about 11% on average. This improvement is a ...