Stochastic grid bundling method for backward stochastic differential equations

ABSTRACT

In this work, we apply the Stochastic Grid Bundling Method (SGBM) to numerically solve backward stochastic differential equations (BSDEs). The SGBM algorithm is based on conditional expectations approximation by means of bundling of Monte Carlo sample paths and a local regress-later regression within each bundle. The basic algorithm for solving the backward stochastic differential equations will be introduced and an upper error bound is established for the local regression. A full error analysis is also conducted for the explicit version of our algorithm and numerical experiments are performed to demonstrate various properties of our algorithm.     

pH-independent dissolution enhancement for multiple poorly water-soluble drugs by nano-sized solid dispersions based on hydrophobic–hydrophilic conjugates

The objective of this study was to achieve an optimal formulation of hydrophilic–hydrophobic conjugates for nano-sized solid dispersions (SDs) with enhanced dissolution of multiple drugs in different gastrointestinal (GI) tract environments. A new conjugate powder with an optimized process was used to fabricate SDs that contained three poorly water-soluble drugs that were also poorly soluble in different dissolution media. The self-assembled nanoparticle formation, drug crystallinity and SD molecular interactions were investigated by measuring the particle size during dissolution testing and physicochemical property analysis (powder X-ray diffraction and Fourier transform infrared spectroscopy). Drug release studies indicated that SD containing conjugated powder significantly improved the dissolution rates of these poorly water-soluble drugs in the GI tract. In addition, particle size analysis showed nano-sized particles in the dissolution media in the early stage with a tendency to reduce smaller particles over time. Physicochemical characterizations demonstrated almost amorphous drug states and hydrogen bonding interactions between the drugs and conjugates in the SD. This study optimized a promising material for SD, and the material was shown to have a promising performance under various pH medium conditions with poorly water-soluble drugs.     

Artificial neural network models for FRP-repaired concrete subjected to pre-damaged effects

Confining damaged concrete columns using fibre-reinforced concrete (FRP) has proven to be effective in restoring strength and ductility. However, extensive experimental tests are generally required to fully understand the behaviour of such columns. This paper proposes the artificial neural networks (ANNs) models to simulate the FRP-repaired concrete subjected to pre-damaged loading. The models were developed based on two databases which contained the experimental results of 102 and 68 specimens for restored strength and strain, respectively. The proposed models agreed well with testing data with a general correlation factor of more than 97%. Subsequently, simplified equations in designing the restored strength and strain of FRP-repaired columns were proposed based on the trained ANN models. The proposed equations are simple but reasonably accurate and could be used directly in the design of such columns. The accuracy of the proposed equations is due to the incorporation of most affecting factors such as pre-damaged level, concrete compressive strength, confining pressure and ultimate confined concrete strength.

     

Two‐Terminal Multibit Optical Memory via van der Waals Heterostructure

2D van der Waals (vdWs) heterostructures exhibit intriguing optoelectronic properties in photodetectors, solar cells, and light‐emitting diodes. In addition, these materials have the potential to be further extended to optical memories with promising broadband applications for image sensing, logic gates, and synaptic devices for neuromorphic computing. In particular, high programming voltage, high off‐power consumption, and circuital complexity in integration are primary concerns in the development of three‐terminal optical memory devices. This study describes a multilevel nonvolatile optical memory device with a two‐terminal floating‐gate field‐effect transistor with a MoS₂/hexagonal boron nitride/graphene heterostructure. The device exhibits an extremely low off‐current of ≈10^?14 A and high optical switching on/off current ratio of over ≈10⁶, allowing 18 distinct current levels corresponding to more than four‐bit information storage. Furthermore, it demonstrates an extended endurance of over ≈10⁴ program–erase cycles and a long retention time exceeding 3.6 × 10⁴ s with a low programming voltage of ?10 V. This device paves the way for miniaturization and high‐density integration of future optical memories with vdWs heterostructures.     

A valences-totaling model for English sentiment classification

Sentiment classification plays an important role in everyday life, in political activities, activities of commodity production and commercial activities. Finding a time-effective and highly accurate solution to the classification of emotions is challenging. Today, there are many models (or methods) to classify the sentiment of documents. Sentiment classification has been studied for many years and is used widely in many different fields. We propose a new model, which is called the valences-totaling model (VTM), by using cosine measure (CM) to classify the sentiment of English documents. VTM is a new model for English sentiment classification. In this study, CM is a measure of similarity between two words and is used to calculate the valence (and polarity) of English semantic lexicons. We prove that CM is able to identify the sentiment valence and the sentiment polarity of the English sentiment lexicons online in combination with the Google search engine with AND operator and OR operator. VTM uses many English semantic lexicons. These English sentiment lexicons are calculated online and are based on the Internet. We present a full range of English sentences; thus, the emotion expressed in the English text is classified with more precision. Our new model is not dependent on a special domain and training data set—it is a domain-independent classifier. We test our new model on the Internet data in English. The calculated valence (and polarity) of English semantic words in this model is based on many documents on millions of English Web sites and English social networks.     

A Hybrid Double Feedforward Neural Network for Suspended Sediment Load Estimation

Estimation of suspended sediment loads (SSL) in rivers is an important issue in water resources management and planning. This study proposes a hybrid double feedforward neural network (HDFNN) model for daily SSL estimation, by combining fuzzy pattern-recognition and continuity equation into a structure of double neural networks. A comparison is performed between HDFNN, multi-layer feedforward neural network (MFNN), double parallel feedforward neural network (DPFNN) and hybrid feedforward neural network (HFNN) models. Based on a case study on the Muddy Creek in Montana of USA, it is found that the HDFNN model is strongly superior to the other three benchmarking models in terms of root mean squared error (RMSE) and Nash-Sutcliffe efficiency coefficient (NSEC). HDFNN model demonstrates the best generalization and estimation ability due to its configuration and capability of physically dealing with different inputs. The peak value of SSL is closely estimated by the HDFNN model as well. The performances of HDFNN model in low and medium loads are satisfactory when investigated by partitioning analysis. Thus, the HDFNN is appropriate for modeling the sediment transport process with nonlinear, fuzzy and time-varying characteristics. It explores a practical alternative for use and can be recommended as an efficient estimation model for SSL.     

Dynamic P‐Δ effects for multistorey steel columns in long‐span tube‐in‐tube tall buildings

An Euler–Bernoulli beam–column model is employed to investigate the dynamic P‐Δ effects of steel columns located at the external tube of a long‐span tube‐in‐tube tall building. A steel column with multistorey lateral open‐web beam supports is modelled as a beam–column element supported by elastic springs, from which a governing partial differential equation is established for the vibration of the column subjected to an axial compression force, lateral beam forces and base excitations. The problem is solved by a modal superposition method for both transient and steady‐state solutions. A numerical example is illustrated and the results indicate that the secondary moment of a steel column induced from dynamic multistorey P‐Δ effects is essential and should not be ignored in a practical design. The influences of the factors including flexural rigidity of the column, axial stiffness of the open‐web beams and the magnitude of the compressive axial force are discussed. Copyright © 2005 John Wiley & Sons, Ltd.     

Is activity-based working impacting health,work performance and perceptions? A systematic review

ABSTRACT

Numerous claims have been made about the benefits of activity-based working (ABW) on workers’ health and work performance. Yet, it is unclear if these claims are proven. This systematic review aims to establish whether there is an evidence base for the effects of ABW on health, work performance and perceptions of the work environment. Eight databases were searched in September 2016. Three reviewers independently screened titles and abstracts and assessed the studies and extracted the data. Seventeen studies involving 36,039 participants were included. The study designs varied in rigorousness from qualitative studies to pre–post-trials and in sample size ranging from 12 to 11,799. This review found that ABW has positive merits in the areas of interaction, communication, control of time and space, and satisfaction with the workspace; however, it is unfavourable for concentration and privacy. For physical and mental health, the evidence is equivocal. ABW seems to be a promising concept that can be implemented and promoted based on some benefits for work performance and perceptions of the work environment when it is coupled with appropriate management support and organization. More high-quality research is needed to strengthen the evidence base further and establish its health effects.     

A Microcomputer Model for Flood Prediction with Applications

Abstract: A generally applicable mathematical model, tailored for use on a Personal Computer, as the design tool to simulate unsteady flood flow in a network of interconnected rivers has been developed and applied to the Sham Chun River along the border between Hong Kong and the People's Republic of China. The effect on the improved Sham Chun River due to the proposed river training in the River Indus, one of its tributaries, is evaluated. The one-dimensional unsteady flow model itself is broadly applicable to a wide range of hydrologic conditions and varying field situations. It incorporates real hydraulic features including branched channels and 'tidal flats' flooding and drying. The time history of water stages and discharges are computed at any desired location throughout the connected essentially one-dimensional channel network subject to initial and boundary conditions. Details are given of techniques adapted in using the computational scheme to quantify the unsteady flow condition and the means to assure an efficient numerical solution as well as to verify the accuracy of the computed outputs by subjection to carefully selected schematic simplified test cases and real prototype cases with numerical solution method is a useful predictive engineering tool in river design.     

Determination of labile and strongly bound metals in lake water

Differential pulse anodic stripping voltammetry is applied to differentiate and determine the labile and strongly bound forms of Zn, Cd, Pb and Cu in lake water without preconcentration of the sample. The sensitivities as established for an oxidation peak current of 0·020 μA are: 0·2 ppb for Zn. 0·4 ppb Cd. 0·7 ppb Pb and 0·5 ppb for Cu. For the analysis of a lake water containing 5·0–24·5 ppb of the four metals, the relative S.D. ranged from 1·6 to 10 per cent. Interferences of cations and anions and the choice of a buffer system have been discussed. The method has been applied to study a number of small lakes in the Sudbury area. Ontario.