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We study the binomial option pricing model and the Black-Scholes-Merton pricing model. In the binomial option pricing model, we concentrate on two widely-used call options: (1) European and (2) American. Under the Black-Scholes-Merton model, we investigate pricing American put options. Our contributions are two-fold: First, we transform the option pricing problems into nonlinear stencil computation problems and present efficient algorithms to solve them. Second, using our new FFT-based nonlinear stencil algorithms, we improve the work and span asymptotically for the option pricing problems we consider. In particular, we perform $O(T\log^2 T)$ work for both American call and put option pricing, where $T$ is the number of time steps.

Additional file 5: Table S2.The specific RT primers were listed as below.

Additional file 4: Table S1. Gradient elution condition.

We present two cache-oblivious sorting-based convex hull algorithms in the Binary Forking Model. The first is an algorithm for a presorted set of points which achieves $O(n)$ work, $O(\log n)$ span, and $O(n/B)$ serial cache complexity, where $B$ is the cache line size. These are all optimal worst-case bounds for cache-oblivious algorithms in the Binary Forking Model. The second adapts Cole and Ramachandran's cache-oblivious sorting algorithm, matching its properties including achieving $O(n \log n)$ work, $O(\log n \log \log n)$ span, and $O(n/B \log_M n)$ serial cache complexity. Here $M$ is the size of the private cache., Comment: 15 pages 3 figures

Additional file 5: Table S2.The specific RT primers were listed as below.

Additional file 6: Table S3. Identification of 96 chemical components from SJS by UPLC–Q/TOF–MS.

Additional file 1: Table S1. Self-inspection results of STROBE-MR checklist of recommended items to address in reports of Mendelian randomization studies. Table S2. Self-inspection results of critical appraisal checklist proposed by Davies et al. for evaluating Mendelian randomization studies. Table S3. The MR results of causal links between gut microbiome and smoking phenotypes by using IVW method under two instrumental variable selection thresholds. Figure S1. Overview of the analytical plan and main findings. Figure S2. Scatter plot of associations between genetic variants and Actinobacteria[p] versus between genetic variants and Cigarettes Per Day. The slope of each line represents the causal effect estimate using the corresponding MR analysis model, and the intercept can be interpreted as an estimate of the average horizontal pleiotropic effect across the genetic variants. Figure S3. Forest plot of individual SNP estimates and summary estimates for the causal associations between Actinobacteria[p] abundance and Cigarettes Per Day. Figure S4. Leave-one-out plot to assess if a single SNP drives the causal association between Actinobacteria[p] abundance and Cigarettes Per Day. Figure S5. Funnel plot of MR estimation for the causal association between Actinobacteria[p] abundance and Cigarettes Per Day.

Additional file 7: Table S4. 23 Active Compounds.

Additional file 6: Table S3. Identification of 96 chemical components from SJS by UPLC–Q/TOF–MS.

Additional file 7: Table S4. 23 Active Compounds.

Background: Sepsis is a life-threatening organ dysfunction caused by dysregulated host responses to infection, for which effective therapeutic strategies are still absent. Shengjiang San (SJS), a well-known Traditional Chinese Medicine formula, has been widely used clinically. However, its role in sepsis-induced lung injury remains unclear. Methods: To explore its specific mechanism, we firstly established a sepsis animal model using cecal ligation and puncture (CLP) and treated MH-S cells with LPS plus ATP. Then, UPLC/Q-TOF-MS/MS was utilized to identify its active ingredients. Network pharmacology analysis was performed to uncover the potential mechanism. HE staining and biochemical analysis were conducted to validate its therapeutic effect. ELISA was applied to detect the release of pro-inflammatory and anti-inflammatory cytokines. Western blot was utilized to detect the protein levels of GSDMD, NLRP3, P65, ASC and caspase-1. Results: SJS could dramatically increase the survival rate of sepsis. In addition, it is able to inhibit the pro-inflammatory cytokines release at day 1 post CLP while promote their production at day 7, indicating SJS could attenuate uncontrolled inflammatory response in the early stage and improve immunosuppression in the late phase. Network pharmacology analysis showed that pyroptosis is the crucial action SJS exerted in the protection of sepsis-induced lung injury. Western blot data implicated SJS could attenuate pyroptosis in early sepsis while enhance in the late phase. Conclusions: SJS acted to alleviate sepsis-induced lung injury through its bidirectional regulatory effect.

The emerging chimeric antigen receptor (CAR) T cell revolutionized the clinic treatment of hematological cancers, but meet its Waterloo in solid tumor therapy. Although there exist many reasons for this limitation, one of the largest challenges is the scarcity of recognition for tumor cells, resulting in the undesirable side effects and the subsequent ineffectiveness. To overcome it, a lung-cancer-cell-targeting peptide termed A1 was used in this work to reform the scFv domain of CAR by genetic manipulation. As a result, this modified A1CAR T exhibited the optimized cancer-cell targeting and cytotoxicity in vitro and in vivo. More importantly, by tuning the sensitivity of CAR to antigen, peptide-based A1CAR T cells could distinguish tumors from normal tissue, thereby eliminating the off-tumor toxicity in healthy organs. Collectively, we herein constructed a genetic peptide-engineered CAR T cells by inserting A1 peptide into the scFv domain. Profitted from the optimized recognition pattern and sensitivity, A1CAR T cells showed the ascendancy in solid tumor treatment. Our findings demonstrate that peptide-based CAR T holds great potential in solid tumor therapy due to an excellent targeting ability towards tumor cells.

ObjectiveTo investigate the effectiveness and limitations of multifetal pregnancy reduction (MFPR) on the improvement of pregnancy outcomes of triplet or twin pregnancies conceived by in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI).MethodsWe performed a cohort study of women undergoing IVF or ICSI from 2002–2016 in reproductive center, women’s hospital, Zhejiang University School of Medicine. The cohort included 502 women who underwent MFPR and 9641 non-reduced women. Pregnancy outcomes were gestational age (GA) at delivery, pregnancy loss, preterm delivery, low birth weight (LBW), very low birth weight (VLBW), and small for gestational age (SGA). Multiple linear regression and logistic regression models were used to compare pregnancy outcomes between groups.ResultsTriplets reduced to singletons had a longer median GA (39.07 vs 37.00, PConclusionsThis study suggests that the pregnancy loss rate is similar between reduction and non-reduction groups. MFPR improves pregnancy outcomes, including the risk of preterm delivery, LBW, and SGA, but still could not completely reverse the adverse pregnancy outcomes of multiple pregnancies.

Additional file 1.

Additional file 1. Supplementary Tables.

Additional file 4: Table S3. Associations of the three aging metrics incorporating cognitive and physical function with all-cause mortality when additionally adjusting for comorbidities. Figure S2. Kaplan-Meier survival curves of the groups defined by the three aging metrics in NHANES.

Additional file 5: Sensitivity Analyses Results. Table S4. Associations of the three aging metrics incorporating cognitive and physical function with all-cause mortality among older adults aged 60 years and over in NHANES (N = 2751). Figure S3. Association of the three aging metrics with all-cause mortality among older adults aged 60 years and over in NHANES (N = 2751).

Additional file 1: Figure S1. Roadmap for the comprehensive analyses of the three aging metrics incorporating cognitive and physical function.

Additional file 2. Detailed description of the Methods.

Additional file 3: Table S1A. Summary characteristics of the cognition status among different age groups, CHARLS 2011/2012 and NHANES 1999–2002. Table S1B. Characteristics of the included and excluded population. Table S1C. Distribution of the participants with CI-PF and MCR across the FI groups, CHARLS 2011/2012 and NHANES 1999–2002.

Scientific experiments significantly enhance the understanding of human-building interactions in building and engineering research. Recently, conducting virtual reality (VR) experiments has gained acceptance and popularity as an approach to studying human-building interactions. However, little attention has been given to the standardization of the experimentations. Proper standardization can promote the reusability, replicability, and repeatability of VR experiments and accelerate the maturity of this emerging experimentation method. Responding to such needs, the authors proposed a virtual human-building interaction experimentation ontology (VHBIEO). It is an ontology at the domain level, extending the ontology of scientific experiments (EXPO) to standardize virtual human-building interaction experimentation. It was developed based on state-of-the-art ontology development approaches. Competency questions (CQs) were used to derive requirements and regulate the development. Semantic Web technologies were applied to make VHBIEO machine-readable, accessible, and processable. VHBIEO incorporates an application view (APV) to support the inclusion of unique information for particular applications. The authors performed taxonomy evaluations to assess the consistency, completeness, and redundancy, affirming no occurrence of errors in its structure. Application evaluations were applied for investigating its ability to standardize and support generating of machine-readable, accessible, and processable information. Application evaluations also verified the capability of APV to support the inclusion of unique information.

This paper proposes a visual analytics framework that addresses the complex user interactions required through a command-line interface to run analyses in distributed data analysis systems. The visual analytics framework facilitates the user to manage access to the distributed servers, incorporate data from the source, run data-driven analysis, monitor the progress, and explore the result using interactive visualizations. We provide a user interface embedded with generalized functionalities and access protocols and integrate it with a distributed analysis system. To demonstrate our proof of concept, we present two use cases from the earth science and Sustainable Human Building Ecosystem research domain.

As a crucial biophysical property, red blood cell (RBC) deformability is pathologically altered in numerous disease states, and biochemical and structural changes occur over time in stored samples of otherwise normal RBCs. However, there is still a gap in applying it further to point-of-care blood devices due to the large external equipment (high-resolution microscope and microfluidic pump), associated operational difficulties, and professional analysis. Herein, we revolutionarily propose a smart optofluidic system to provide a differential diagnosis for blood testing via precise cell biophysics property recognition both mechanically and morphologically. Deformation of the RBC population is caused by pressing the hydrogel via an integrated mechanical transfer device. The biophysical properties of the cell population are obtained by the designed smartphone algorithm. Artificial intelligence-based modeling of cell biophysics properties related to blood diseases and quality was developed for online testing. We currently achieve 100% diagnostic accuracy for five typical clinical blood diseases (90 megaloblastic anemia, 78 myelofibrosis, 84 iron deficiency anemia, 48 thrombotic thrombocytopenic purpura, and 48 thalassemias) via real-world prospective implementation; furthermore, personalized blood quality (for transfusion in cardiac surgery) monitoring is achieved with an accuracy of 96.9%. This work suggests a potential basis for next-generation blood smart health care devices.

This paper investigates the problem of control synthesis for a class of discrete-time semi-Markov jump linear systems, in which the sojourn time of each mode is bi-boundary (with upper and lower bounds). The system is subject to modal asynchrony, which means that the switchings of the mode-dependent controller to be designed lag behind the ones of the controlled plant, and the lag is mode-dependent. In contrast with the traditional mode-independent lag commonly assumed in the existing studies, not only is the modal lag more practical and general, but also it yields less conservatism of the controller design. By virtue of the semi-Markov kernel approach, the conditions on the existence of the anticipated stabilizing controllers capable of overcoming the modal asynchrony are derived. Illustrative examples including a class of vertical take-off and landing (VTOL) helicopter models are presented to demonstrate the necessity and the validity of the designed anti-modal-asynchrony controllers.

Additional file 1: Table S1. Associations of continuous laboratory markers with the severity of COVID-19 in the training set. Table S2. Remaining frequency of the 16 markers in 1000 LASSO regression models. Table S3. Associations of the selected eight markers with the severity of COVID-19 in the external validation set.

Plasma CO2 splitting to CO over oxygen-deficient Mo-doped CeO2 under mild conditions was investigated for the first time, showing ∼20 times higher CO2 conversion compared to pure CeO2, which can be attributed to the increased oxygen vacancies (VO) and the formation of Ce3+-VO-Mo on the catalyst surface. Importantly, VO sites showed excellent catalytic stability.

\The development of effective delivery system for peptides targeting to the tumor microenvironment has always been a hot topic in the field of cancer diagnosis and therapy. A multifunctional delivery system by encapsulating superparamagnetic iron oxide nanoparticles (SPIO NPs) with tumor cell membrane obtained by hypotonic lysis followed by mechanical fragmentation was constructed to effectively deliver therapeutic peptides. SPIO nanoparticles were encapsulated with H460 lung cancer cell membranes (SPIO NP@M) and peptides consisted of PD-L1 inhibitory peptide (TPP-1) and MMP2 substrate peptide (PLGLLG) was conjugated to H460 membrane (SPIO NP@M-P). The abilities of homologous targeting, cytotoxicity, pharmacokinetics, and tumor targeting ability of SPIO NP@M-P were evaluated. TPP-1 peptide was delivered and released to the tumor microenvironment through the homotypic effect of tumor cell membrane and specific digestion by the tumor specific enzyme, MMP2. The newly developed delivery system (SPIO NP@M-P) for PD-L1 inhibitory peptide could effectively extend the half-life of the peptides (60 times longer) and meanwhile maintain the ability to re-activate T cell and inhibit the tumor growth in vitro and in vivo. Furthermore, SPIO NPs in the system could be used as a tumor imaging agent and thus indicate the effect of peptide treatment. The SPIO NP@M might provide a promising theranostic platform for therapeutic peptide application in cancer therapy.

Traffic management models that include route choice form the basis of traffic management systems. High-fidelity models that are based on rapidly evolving contextual conditions can have significant impact on smart and energy efficient transportation. Existing traffic/route choice models are generic and are calibrated on static contextual conditions. These models do not consider dynamic contextual conditions such as the location, failure of certain portions of the road network, the social network structure of population inhabiting the region, route choices made by other drivers, extreme conditions, etc. As a result, the model’s predictions are made at an aggregate level and for a fixed set of contextual factors. There is a clear need to develop traffic models that take into account local contexts and are closer to ground reality to provide government agencies the ability to make well-informed model-based decisions/policies. In this project: (1) used Immersive Virtual Environment (IVE) tools for generating context-aware and high-fidelity data related to drivers’ route choice behavior, (2) developed a novel approach for developing high-fidelity route choice models with increased predictive power by augmenting existing aggregate level baseline models with information on drivers' responses to contextual factors obtained from stated choice experiments carried out in an IVE through the use of knowledge distillation. To this end, the study used a virtual driving environment designed based on I-10 in Baton Rouge, LA. Five alternate routes were introduced to the participant. Ten experimental scenarios were conducted to produce initial data about drivers’ dynamic route choice behavior, given emerging contextual factors. Experimental results have demonstrated that the predictions of the augmented models produced by our approach are much closer to reality than that of the baseline. Our study demonstrates that existing route choice models based on econometric theories cannot accurately predict behavior in real world scenarios. For high-fidelity route choice models, one needs to combine existing route choice models with information about contextual factors gleaned from SCEs., Tran-SET Project No. 18ITSLSU09

Pilot scale experiments were conducted to prepare magnesium hydroxide by magnesia hydration under gas-liquid-solid (three-phase) reaction system. The effect of reaction pressure, reactivity and particle size of magnesia and the concentration of the pulp on the degree of hydration was investigated. The results indicated that the hydration reaction occurred at the first 30min mainly. During the set reaction condition, degree of hydration of 68% could be obtained at the reaction pressure of 0.2MPa, concentration of pulp of 5%w/w with high reactivity and fine powder. The promotion effect on the degree of hydration caused by the three-phase reaction system was mostly attributed to the exfoliation of steam.

Previous studies reveal that combining non-thermal plasma with cheap metal catalysts achieved a significant synergy of enhancing performance of NH3 decomposition, and this synergy strongly depended on the properties of the catalyst used. In this study, techniques of vacuum-freeze drying and plasma calcination were employed to improve the conventional preparation method of catalyst, aiming to enhance the activity of plasma-catalytic NH3 decomposition. Compared with the activity of the catalyst prepared by a conventional method, the conversion of NH3 significantly increased by 47% when Co/fumed SiO2 was prepared by the improved method, and the energy efficiency of H2 production increased from 2.3 to 5.7 mol(kW·h)−1 as well. So far, the highest energy efficiency of H2 formation of 15.9 mol(kW·h)−1 was achieved on improved prepared Co/fumed SiO2 with 98.0% ammonia conversion at the optimal conditions. The improved preparation method enables cobalt species to be highly dispersed on fumed SiO2 support, which creates more active sites. Besides, interaction of Co with fumed SiO2 and acidity of the catalyst were strengthened according to results of H2-TPR and NH3-probe experiments, respectively. These results demonstrate that employing vacuum-freeze drying and plasma calcination during catalyst preparation is an effective approach to manipulate the properties of catalyst, and enables the catalyst to display high activity towards plasma-catalytic NH3 decomposition to produce H2.

By taking the imperfect channel state information(CSI) into account, the optimal precoding matrix is deduced with the proposition that the full CSI of the source-relay link and the estimation errors and antennas correlation information of the relay-destination link are known by the relay node. Considering the maximum power constraint at the relay node, the precoding matrix is optimized based on the minimum mean-squared error (MMSE) criterion, then the closed-form of the optimal decoding matrix is derived. Numerical results demostrate that the proposed design scheme achieves better performance than other approaches.

To investigate the predictive value of pediatrics end-stage liver disease (PELD) or the model for end-stage liver disease (MELD) in the prognosis of pediatric acute liver failure (PALF) treated with artificial liver support system (ALSS).The clinical data of 47 children with acute liver failure seen from August 2008 to July 2013 treated in Children's Hospital, Fudan University were analyzed. Thirty children were treated with ALSS in addition to conventional comprehensive medical treatment (ALSS group). Seventeen children were treated with only conventional comprehensive medical treatment (control group). The main biochemical parameters and coagulation function parameters before and after treatment were compared in the ALSS group and the mortality rates were compared between the two groups. The patients were graded by PELD or MELD when they were hospitalized and the relationship of PELD or MELD scores and mortalities of child patients with the receiver operating characteristic curve (ROC) were analyzed.There were significant differences in total bilirubin (TB) ((302 ± 208) vs. (161 ± 129) µmol/L); alanine aminotransferase (ALT) ((161 ± 225) vs. (761 ± 834) U/L); aspartate aminotransferase ( AST) (66 (35, 123 ) vs. 447 (184, 1,129 ) U/L) ; international normalized ratio (INR) ((2.6 ± 1.6) vs. (5.1 ± 4.0)); prothrombin time activity percentage (PTA) ((42 ± 25)% vs. (22 ± 13)%); albumin( ALB) ((35 ± 5) vs. (33 ± 6) g/L) in the ALSS group after treatment. Through the ROC curve analysis, the best PELD/MELD threshold was 25 to predict the patients survival after ALSS therapy, with a sensitivity of 92. 3% , and a specificity of 94.1% at the cutoff point. The area under the ROC curve was 0. 912. The mortality of patients with PELD or MELD score below 25 in the ALSS group (1/13) was lower than the control group (3/4) (P = 0.022), and the mortality of patients with PELD or MELD score over 25 (16/17) was higher than that of the control group (10/13) (P = 0.290).PELD or MELD score is a valid index in prognostic evaluation of ALSS therapy, which may provide an evidence for the therapeutic strategies of PALF. Patients with PELD or MELD score below 25 treated with ALSS obtained more benefit.

Wavelet analyses are applied to the Pacific Decadal Oscillation index and North Pacific index for the period 1900–2000, which identifies two dominant interdecadal components, the bidecadal (15–25-yr) and pentadecadal (50–70-yr) modes. Joint propagating patterns of sea surface temperature (SST) and sea level pressure (SLP) anomalies in the North Pacific for the two modes are revealed by using the techniques of multi-channel singular spectrum analysis (MSSA) and linear regression analysis with the global sea surface temperature (GISST) data and the northern hemispheric SLP data for the common period 1903–1998. Significant differences in spatio-temporal structures are found between the two modes. For the bidecadal mode, SST anomalies originating from the Gulf of Alaska appear to slowly spread southwestward, inducing a reversal of early SST anomalies in the central North Pacific. Due to further westward spreading, the SST variation of the central North Pacific leads that of the Kuroshio-Oyashio Extension (KOE) region by approximately 4 to 5 years. Concomitantly, SLP anomalies spread over most parts of the North Pacific during the mature phase and then change into an NPO(North Pacific Oscillation)-like pattern during the transition phase. For the pentadecadal mode, SST anomalies develop in the southeast tropical Pacific and propagate along the North American coast to the mid-latitudes; meanwhile, SST anomalies with the same polarity in the western tropical Pacific expand northward to Kuroshio and its extension region; both merge into the central North Pacific reversing the sign of early SST anomalies there. Accompanying SLP anomalies are characterized by an NPO-like pattern during the mature phase while they are dominant over the North Pacific during the transitional phase. The bidecadal and pentadecadal modes have different propagating patterns, suggesting that the two interdecadal modes may arise from different physical mechanisms.

In the study of SO2 removal using pulsed corona discharge, there exists a serious confusion, that is, which kind of reactions, the thermal chemical reactions or the radical chemical reactions, plays a dominant role in SO2 removal? In this work, through some experiments together with qualitative analyses, this confusion has been clarified. Pulsed corona discharge induces the radical reactions that mainly contribute to oxidizing SO2. High relative humidity in flue gas is a basis of the heterogeneous radical reactions. Ammonia not only is an additive but also accelerates the oxidization of SO2. Only by synergistic effects of pulsed corona discharge, relative humidity and ammonia, can it be effective to oxidize SO2 via the heterogeneous radical reactions. In the SO2 removal, the essence of heterogeneous reactions is the radical reactions both in gas phase and at aerosol surface, which is the reason of the oxidization of SO2. It has also been evaluated that in an optimum process the oxidization of SO2 in gas phase is responsible for about 30%, and at the aerosol surface is about 50%, while the thermal chemical reactions result in about 20%, of all the removed SO2.

The matching between generator and reactor is a crucial aspect in optimizing the pulsed corona discharge. Several methods can be adopted to reach the matching, reducing inductance in discharge circuit, regulating relative humidity of flue gas, and paralleling a suitable condenser with the reactor. The detail of the matching discussed in this paper is based on experimental results and the theories of streamer formation as well. The matching not only makes the injection of pulsed energy effective, but also promotes the formation of pulsed streamer in the reactor.

This paper gives the main parameters of the generator and reactor system for SO 2 removal with gas flow rates of 1,000–3,000 Nm 3 /h using pulsed corona discharge. During the design, establishment and operation, the system has been improved in many aspects, i.e. the insulation treatment of the system, the realization of the high energy pulse formation and transmission, and the optimization of the pulsed corona characteristics etc.. Finally, the preliminary results show that: with a gas flow rate of 1,400 Nm 3 /h, initial concentrations of 2000–2400 ppm of SO 2 , gas temperature of 60–70 °C, resident time of 7s, and stoichiometric ratios of NH 3 to SO 2 among 1–1.1, 75–80% of SO 2 is removed at power consumption of 5–6 KW.

Since the 1980s, along with the deepening of China's reform and open policy, education, like the economy, has shown pluralistic, developmental characteristics in the area of school systems. Nongovernmental schools established by the people began to grow. Since entering the 1990s, in particular, the development of such schools has broken through the 1980s mode which focused on nonregular education such as vocational and technical education. Along with the formation of the socialist market economic system and society's multilevel needs in education, the field has responded with multilevel development. Currently, nongovernmental schools have expanded to the preschool, secondary, and higher educational levels.

To solve oceanic environment problem caused by alien species invasion of ballast water, a novel approach of micro-pore ceramic filtration and UV radiation (MPCF&UV) was prompted. This work has studied on the MPCF&UV performance on small alga removal at the flow rate of 1~9m3/h. In the experiment, Chlorella Vulgaris, Nitzschia closterium, Platymonas subcordiformis were chosen as indicator organisms to mix with clean seawater as simulated ballast water. Microscope and SEM was used to analyze alga removal rates and to observe the changes in shape and structure of alga cells. The results show that higher removal percentages were obtained on all the three types of alga, and Platymonas subcordiformis was observed the highest removal rates of up to 100%. By SEM observation, it can be found that micro-pore ceramic filter (MPCF) can only ruin cell walls of the algae, and UV radiation can damage both cell walls and nucleus of the algae.

In this work, chemical oxygen demand (COD) removal and decolorization of polyester scouring effluent by coagulation-acidation have been studied experimentally. Acidulated bentonite was used as coagulant. The effects of bentonite dosage, PAM dosage, stirring time, and pH after acidation on the efficiency of COD and color reduction were studied by orthogonal methodology. Finally the optimum conditions have been obtained. The products of coagulation and acidation were test by Fourier transform infrared spectra. It has been concluded that the most of residual color and suspended solid are removed during the coagulation process and the acidation product is terephthalic acid. Under the optimum condition, the removal efficiencies of COD and color are 79.7% and 90%, respectively.

Currently applied filtration methods on ballast water treatment may have problems of low efficiency, low flow rate or short lifespan. So a novel micro-pore ceramic filter (MPCF) is used to combine with UV. To evaluate the performance of the new approach, alga removal percentages and oceanic bacteria inactivation rates were studied on simulated ballast water mixing with indicator algae. They were compared with single MPCF treatment and UV treatment at different flow rates and alga concentration. Up to 96.2% on Chlorella Vulgari, and up to 100% on both Nitzschia Closterium and bacteria were observed in the experiment, by combination of micro-pore ceramic filtration and UV radiation (MPCF&UV). MPCF&UV approach obviously superior than either MPCF or UV treatment on both alga removal and bacteria inactivation.

Significant literature has been dedicated to research on partnering in construction, and a plethora of underlying theories and industrial practices on partnering application have been reported. The aim is to analyze and summarize the research trend of partnering research from leading construction-related journals. Keywords identified on the subject based on prior experience were constructed into search strings. Articles found utilizing this search string were reviewed according to their relevant subject theme as identified in the narrative coding sections and synthesized into relevant themes. The review shows that research on development and application of partnering is becoming moderately mature as exemplified by a decreasing amount of published papers after 2007, on the other hand, research on trust; feasibility; advantages; inducements of implementation and barriers to implementation is emerging. This critical overview establishes a solid reference platform for researchers to seek further research opportunities in non-mature areas.

The production of sustainable housing requires the cooperation of a variety of participants with different goals, needs, levels of commitment and cultures. To achieve mainstream net zero energy housing objectives, there is arguably a need for a non-linear network of collaboration between all the stakeholders. In order to create and improve such collaborative networks between stakeholders, we first need to map stakeholders’ relationships, processes, and practices. This paper discusses compares and contrasts maps of the sustainable housing production life-cycle in Australia, developed from different perspectives. The paper highlights the strengths and weaknesses of each visualization, clarifying where gaps in connectivity exist within existing industry networks. Understanding these gaps will help researchers and practitioners identify how to improve the collaboration between participants in the housing industry. This in turn may improve decision making across all stakeholder groups, leading to mainstream implementation of sustainability into the housing industry.