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European standards have set stringent particulate number (PN) regulations for gasoline direct injection (GDI) engine, proposing a great challenge for the particulate emission control. The dual-injection mode, which incorporates direct-injection with port-fuel-injection, is considered to be an effective approach to reduce PN emissions. In this study the combustion, gaseous and particulate emission characteristics under different direct-injection ratios in a dual-injection gasoline engine were investigated. The results show that dual-injection increases the peak of in-cylinder pressure curves and makes the heat release curves shift towards an earlier region. The dual-injection mode yields a notable CO reduction while there is a slight increase in NOx emission. Dual-injection can significantly reduce the PN emission compared with GDI engines. As the direct-injection ratio decreases, the PN concentration continuously declines. The peak of size distributions curves for dual-injection tends to shift towards the smaller diameter region, showing the ability to generate particles in smaller size. The soot particles from dual-injection have lower oxidation activation energy than those from direct-injection. According to the results above, it can be inferred that dual-injection can promote the combustion process and has remarkably positive effects on particle emission control owing to its reduced PN emissions and improved particle oxidation reactivity.

As one of the most widely used recommender systems, movie recommendation plays an important role in our life. However, the data sparsity problem severely hinders the effectiveness of personalized movie recommendation, which requires more rich content information to be utilized. Posters and still frames, which directly display the visual contents of movies, have significant influences on movie recommendation. They not only reveal rich knowledge for understanding movies but also useful for understanding user preferences. However, existing recommendation methods rarely consider aesthetic features, which tell how the movie looks and feels, extracted from these pictures for the movie recommendation. To this end, in this paper, we propose an aesthetic-aware unified visual content matrix factorization (called UVMF-AES) to integrate visual feature learning and recommendation into a unified framework. Specifically, we first integrate the convolutional neural network (CNN) features and aesthetic features into probabilistic matrix factorization. Then we establish a unified optimization framework with these features for the movie recommendation. The experimental results on two real-world datasets show that our proposed method UVMF-AES is significantly superior to the state-of-the-art methods on movie recommendation.

Next basket recommendation with consideration of user sequential shopping behaviors plays a significant role in E-commerce to improve the user experience and service quality. Recently, recurrent neural networks (RNNs), especially attention-based RNN, have been widely adopted in the next basket recommendation. However, existing fixed attention mechanisms are not designed to model the dynamic and diverse characteristics of user appetites. In this paper, we propose an inter-basket and intra-basket adaptive attention network (IIAAN) for the next basket recommendation. Specifically, the inter-basket adaptive attention acts on all historical user baskets to model user's diverse long-term preferences, while the intra-basket adaptive attention is designed to act on item-level in the most recent basket to model user's dynamic and different short-term preferences. Then, we further integrate inter-basket and intra-basket adaptive attentions together to improve recommendation effectiveness. Finally, we evaluate the proposed model IIAAN using three real-world datasets from various E-commerce platforms. Our experimental results show that our model IIAAN significantly outperforms the state-of-the-art approaches for the next basket recommendation.

Key-based workload partitioning is now commonly used in parallel stream processing, enabling effective key-value tuple distribution over worker threads in a logical operator. While randomized hashing on the keys is capable of balancing the workload for key-based partitioning when the keys generally follow a static distribution, it is likely to generate poor balancing performance when workload variance occurs on the incoming data stream. This paper presents a new key-based workload partitioning framework, with practical algorithms to support dynamic workload assignment for stateful operators. The framework combines hash-based and explicit key-based routing strategies for workload distribution, which specifies the destination worker threads for a handful of keys and assigns the other keys with the hashing function. We formulate the rebalance operation as an optimization problem, with multiple objectives on minimizing state migration costs, controlling the size of the routing table and breaking workload imbalance among the worker threads. Despite of the NP-hardness nature behind the optimization formulation, we carefully investigate and justify the heuristics behind key (re)routing and state migration, to facilitate fast response to workload variance with ignorable cost to the normal processing in the distributed system. Empirical studies on synthetic data and real-world stream applications validate the usefulness of our proposals and prove the huge advantage of our approaches over state-of-the-art solutions in the literature.

Driven by the fast development of mobile internet and mobile devices, huge volumes of trajectory data describing the spatial-temporal information of moving objects are currently generated. Trajectory similarity processing is playing a critical role to explore valuable information, such as the patterns of human activities and behaviors. However, most of the existing works optimize this operation in an off-line manner, which is unable to provide timely feedback for time-sensitive applications. In this paper, we present a new real-time processing framework for trajectory similarity measurement, with practical algorithms to reduce the computing resource cost and guarantee the correctness of the result. Our proposal includes a cost-effective framework to ensure the correctness of trajectory similarity processing, a stream partition algorithm to maximize the processing throughput, a lightweight Top-k computing mode to cut off unnecessary network cost. Empirical studies on real-world stream applications validate the usefulness of our proposals and prove the huge advantage of our approaches over state-of-the-art solutions in the literature.

Along with the popularization of big data applications, real-time data analysis is playing an increasingly important role in data analytic applications. The distributed parallel processing framework is a good choice for real-time big data processing, since it provides an effective solution which facilitates processing of massive data stream with low latency. Furthermore, among the real-time applications, location based service is recognized as the most challenging one, especially under expectation on fast response to distribution change and minimal resource consumption. We find that the fundamental reason for this is that the index performance is a stumbling block. Specifically, the original intention of index design is to speed up retrieval speed; in other words, the index is more useful for operations that have more queries than updates. However, in the distributed parallel processing framework, each incoming tuple is both a query request and an update request. In this paper, we propose a new tree index, quad balanced space tree called QBS-tree, to solve this problem, with practical algorithms to support dynamic index items assignment for distributed parallel processing framework. Specifically, make tree index's tolerability to the index items' unbalanced distribution in space be more resilient through a configurable balance factor. In addition, through the lazy update mechanism, let some updates offset each other and the upper node's update covers the underlying node's. Experiments show that QBS-tree responds to a new tuple 1300 times faster than the traditional tree index.

This experimental study demonstrates the potential to apply the thermochemical fuel reforming (TFR) concept to simultaneously reduce emissions and improve brake specific fuel consumption in a spark-ignition natural gas engine. CH 4 , H 2 and CO are the major components of TFR exhaust gas over a range of rich equivalence ratios. A numerical analysis is conducted to illustrate the chemical reaction pathways for H 2 and CO formation, which occurs in the cylinder during the TFR process. The main reaction pathways for H 2 and CO formation under 3 modeling conditions (20%, 50% and 80% fuel consumed) are different from each other. According to the experimental analysis, thermochemical fuel reforming gas improves combustion performance and accelerates the burn rate in every phase of the natural gas engine. Combustion stability, brake thermal efficiency, brake specific fuel consumption (BSFC), brake specific hydrocarbon (BSHC) and brake specific carbon monoxide (BSCO) emissions can also be improved by TFR. The brake specific oxides of nitrogen (BSNO x ) emissions for natural gas engines, combined with a TFR system, are still lower than those of an original natural gas engine in the same operation mode. Thermochemical fuel reforming has been shown to be effective in simultaneously reducing emissions and improving thermal efficiency for a spark-ignition natural gas engine. Furthermore, a 1.2 equivalence ratio for cylinder 4 (TFR cylinder) can be recommended in future research on TFR optimization, based on BSFC and combustion stability.

Considering the characteristics of frequent occurrence and serious losses, a technology for the standpipe in flat roof of green building community was designed to alleviate the urban waterlogging, and a test was carried out to find out the influence of the concrete height, underlying surface and return period on reduction rate of peak discharge and rainwater pipe diameter. Results showed that the reduction rate of peak discharge increased with the increase of concrete height, and the reduction rate kept constant as 36.98% when the concrete height was 5 cm or more. The reduction rate of peak discharge increased with the increase of roof area proportion, while the reduction rate of peak discharge decreased with the increase of return period. At the same time, these results can be used to guide practical engineering.

Improving the nitrogen removal capacity of stormwater runoff has been the main research direction of bioretention systems in recent years. Heterotrophic denitrification in traditional bioretention systems was often used, but insufficient carbon sources in the runoff limit it. In this study, two bioretention systems using natural pyrite and zeolite as substrates were constructed to explore the feasibility of pyrite-based autotrophic denitrification in bioretention for nitrogen removal. During eight months of operation at natural conditions, the results showed that pyrite had no negative effects on the removal of NH4+—N, but enhanced denitrification in the bioretention system with no or low carbon source in the influent. Pyrite based bioretention system (PBS) can adapt to low temperature and irregular wet and dry alternation. The average NH4+—N, TN, and TP removal efficiency of PBS during eight months were 87.6 %, 89.3 %, and 81.6 %. The average NH4+—N, TN, and TP removal efficiency of zeolite-based bioretention system (ZBS) were 98.7 %, 47.1 %, and 47.5 %. By-products ( S O 4 2 - and Total iron) of PBS were all at an acceptable level. The dominant genera in PBS were Denitratisoma (3.6 %), Ellin6067 (2.7 %), Thiobacillus (2.6 %), Thauera (2.1 %), CL500−29 marine group (1.8 %), Sulfuritalea (1.7 %), Subgroup 10 (1.4 %). Genera Thiobacillus, Thauera, and Sulfuritalea were highly related to autotrophic denitrification. Moreover, genera Denitratisoma was highly related to heterotrophic denitrification. This study shows that pyrite could be a promising eco-friendly substrate in the bioretention system for nutrient removal.

Homogenous charge compression ignition (HCCI) engines feature high thermal efficiency and ultralow emissions compared to gasoline engines. However, unlike SI engines, HCCI combustion does not have a direct way to trigger the in-cylinder combustion. Therefore, gasoline HCCI combustion is facing challenges in the control of ignition and, combustion, and operational range extension. In this paper, an active fuel design concept was proposed to explore a potential pathway to optimize the HCCI engine combustion and broaden its operational range. The active fuel design concept was realized by real time control of dual-fuel (gasoline and n-heptane) port injection, with exhaust gas recirculation (EGR) rate and intake temperature adjusted. It was found that the cylinderto- cylinder variation in HCCI combustion could be effectively reduced by the optimization in fuel injection proportion, and that the rapid transition process from SI to HCCI could be realized. The active fuel design technology could significantly increase the adaptability of HCCI combustion to increased EGR rate and reduced intake temperature. Active fuel design was shown to broaden the operational HCCI load to 9.3 bar indicated mean effective pressure (IMEP). HCCI operation was used by up to 70% of the SI mode load while reducing fuel consumption and nitrogen oxides emissions. Therefore, the active fuel design technology could manage the right fuel for clean engine combustion, and provide a potential pathway for engine fuel diversification and future engine concept.

Ethanol-gasoline blended fuels have been widely applied in markets recently, as ethanol reduces life-cycle greenhouse gas emissions and improves anti-knock performance. However, its effects on particulate matter (PM) emissions from gasoline direct injection (GDI) engine still need further investigation. In this study, the effects of ethanol-gasoline blended fuels on particle size distributions, number concentrations, chemical composition and soot oxidation activity of GDI engine were investigated. It was found that ethanol-gasoline blended fuels increased the particle number concentration in low-load operating conditions. In higher load conditions, the ethanol-gasoline was effective for reducing the particle number concentration, indicating that the chemical benefits of ethanol become dominant, which could reduce soot precursors such as large n-alkanes and aromatics in gasoline. The volatile organic mass fraction in ethanol-gasoline particulates matter was higher than that in gasoline particulate matter because ethanol reduced the amount of soot precursors during combustion and thereby reduced the elemental carbon proportions in PM. Ethanol addition also increased the proportion of small particles, which confirmed the effects of ethanol on organic composition. Ethanol-gasoline reduced the concentrations of most PAH species, except those with small aromatic rings, e.g., naphthalene. Soot from ethanol-gasoline has lower activation energy of oxidation than that from gasoline. The results in this study indicate that ethanol-gasoline has positive effects on PM emissions control, as the soot oxidation activity is improved and the particle number concentrations are reduced at moderate and high engine loads.

This work is to investigate the internal flow pattern and macroscopic spray characteristics of R134a discharged through twin-orifice atomizers. Two inlet orifices with the diameters of 0.6 mm and 3.0 mm were subsequently implemented and connected to the supply line of R134a to find the influence of the inlet orifice geometry on flow and spray characteristics. Transparent atomizers were manufactured to study the effects of different diameters of discharge nozzles on the internal flow and atomization. An injection pressure of 6.0 MPa was operated to produce “stable” flash-boiling sprays vertically, and the ambient condition was atmospheric. Internal flow in the expansion chamber and external liquid atomization were observed simultaneously during the actuation. The relationship between the internal boiling flow in the expansion chamber and external flash-boiling spray were analyzed. A “sudden” gas–liquid transition was observed when the inlet/discharge orifice ratio is one. This work provides a guide and reference for the volatile or liquefied material discharged through a twin-orifice atomizer.

The join operations, including both equi and non-equi joins, are essential to the complex data analytics in the big data era. However, they are not inherently supported by existing DSPEs ( D istributed S tream P rocessing E ngines). The state-of-the-art join solutions on DSPEs rely on either complicated routing strategies or resource-inefficient processing structures, which are susceptible to dynamic workload, especially when the DSPEs face various join predicate operations and skewed data distribution. In this paper, we propose a new cost-effective stream join framework, named A-DSP ( A daptive D imensional S pace P rocessing), which enhances the adaptability of real-time join model and minimizes the resource used over the dynamic workloads. Our proposal includes: 1) a join model generation algorithm devised to adaptively switch between different join schemes so as to minimize the number of processing task required; 2) a load-balancing mechanism which maximizes the processing throughput; and 3) a lightweight algorithm designed for cutting down unnecessary migration cost. Extensive experiments are conducted to compare our proposal against state-of-the-art solutions on both benchmark and real-world workloads. The experimental results verify the effectiveness of our method, especially on reducing the operational cost under pay-as-you-go pricing scheme.

The Lower Silurian Longmaxi Formation (the Palaeozoic) is organic-rich (black) shale in the southern Sichuan Basin (the Yangtze Plate) of China. This study analyses the lateral extent and thickness, burial depth, total organic carbon content and thermal maturity of the Longmaxi Formation black shale as the key features of the shale gas reservoir. The thickness of the black shale ranges from 10 to 170 m. The thickest reservoir is located in Changning-Naxi-Yongchuan region. The TOC of the shale at the bottom of the formation (50-m thickness) is above 2.0%. The lateral distribution of TOC varies with the lateral distribution of thickness, with the maximum TOC in the Gongxian-Luzhou-Yongchuan region. The burial depth ranges from 2000 to 4500 m. The shale is thermally over mature. The evaluation of reservoir characteristics indicates that the Longmaxi Formation has conditions appropriate for shale gas accumulation and thus resource potential in the southern Sichuan Basin of China. The objective of this preliminary evaluation of the reservoir characteristics is to locate potential areas favourable for exploration. The most favourable areas are defined here as those where the thickness of black shale is more than 100 m and the burial depth is less than 3000 m; these cover approximately 12,600 km 2 . The most favourable areas, which cover an area of approximately 5100 km 2 , are located in the northeast Luzhou region.

The Yangshan deepwater port is the only container port built in the islands off the mainland of China. Batter piles with a sheet-pile-supported platform bulkhead structure were first used as a new shore-connecting structure to connect the front main wharf structure and the back land. Large-diameter sand columns were also used to reinforce the soft foundation of the shore-connecting structure in the deep water of the open sea. A 3D nonlinear FEM model based on real geological conditions was built to optimize the large-diameter sand columns’ reinforcing scheme and investigate shore-connecting structures’ mechanical properties under different construction conditions. The replacement ratio of 30%, the bottom elevation of the fourth soil layer, and the soft soil just below and directly adjacent to the shore-connecting structure were determined as optimal replacement ratio, reinforcing depths, and reinforcing area of the large-diameter sand columns reinforcement by assessing the force and deformation of the sho...

Experiments were conducted on a diesel engine operating on Euro V diesel fuel, pure biodiesel and biodiesel blended with ethanol (BE blends) to assess the particulate and unregulated emissions with and without diesel oxidation catalyst (DOC). The results indicate an increase of particle number concentration, formaldehyde emission and acetaldehyde emission while a decrease of particulate mass concentration, when the diesel engine is operated with biodiesel, compared with the diesel fuel. Adding ethanol in biodiesel can help to control particulate emissions, especially particle number concentration. However, the unregulated emissions, such as formaldehyde, acetaldehyde and unburned ethanol are worsened with BE blended fuels. The diesel oxidation catalyst (DOC) can effectively reduce particulate mass concentration, particle number concentration and unregulated emissions for all different fuels, while the conversion efficiency of DOC is different for each fuel. The oxidation catalyst is not equally active for different hydrocarbon species. The oxidation catalyst is most active for unburned ethanol, then formaldehyde and benzene emissions. The effects of DOC on particulate and unregulated emissions are more obvious for BE blends than those for Euro V diesel fuel and biodiesel, indicating that application of biodiesel–ethanol blends together with DOC has the potential to reduce particulate emission and unregulated emissions of diesel engine.

In this study, the effect of ethanol on combustion and emissions in premixed low temperature combustion (LTC) was investigated in a four cylinders heavy-duty diesel engine. The biodiesel was used as an additive to prevent the stratification of ethanol and diesel blends. The premixed LTC is achieved by the medium level of EGR and the prolonged ignition delay. Compared with diesel fuel, ethanol–diesel–biodiesel blends have lower NO x emissions due to lower combustion temperature, resulting from the higher latent heat of vaporization. Unfortunately, the lower combustion temperature also leads to the higher HC and CO emissions. Smoke emissions for ethanol blends decrease obviously because of higher oxygen content and longer ignition delay. The oxygen in ethanol also has a favorable impact on the reduction of smoke emissions, which is obvious in high loads. Thus, the upper load limit of LTC mode is extended. Compared with diesel fuel, 20 vol.% ethanol in diesel and biodiesel blends (BDE20) has lower NO x and smoke emissions and higher brake thermal efficiency in LTC.

Background The sensitivities and specificities of biomarkers for gastric cancer are insufficient for clinical detection, and new diagnostics are therefore urgently required. Methods A discovery set of gastric cancer tissues was labeled with iTRAQ reagents, separated using SCX chromatography, and identified using LC-ESI-MS/MS. A validation set of gastric cancer tissues was used to confirm the expression levels of potential markers. Results The present study detected metastasis-associated protein 2 (MTA2) and Histone deacetylases 1 (HDAC1) proteins that were overexpressed in gastric cancer tissues compared with that in adjacent gastric tissue. The sensitivity and specificity of MTA2 in detecting 76 cases gastric cancers were 57.9% (95% CI: 46.5%–69.3%) and 55.3% (95% CI: 43.8%–66.7%), respectively. The sensitivity and specificity of HDAC1 were 61.8% (95% CI: 50.7%–73%) and 63.2% (95% CI: 52.1%–74.3%), respectively. The co-expression of MTA2 and HDAC1 in gastric cancer achieved 65.3% sensitivity (95% CI: 51.5%–79.1%) and 65.2% specificity (95% CI: 50.9%–79.5%), which was strongly associated with lymph node metastasis and TNM staging. Conclusion The present findings indicated a tight correlation between the MTA2 and HDAC1 expression level and lymph node metastasis and TNM staging in gastric cancers. Therefore, MTA2 and HDAC1 might be predictors of lymph node metastasis phenotype and possible target molecule for anticancer drug design in human gastric cancer.

Key-based workload partitioning is a common strategy used in parallel stream processing engines, enabling effective key-value tuple distribution over worker threads in a logical operator. While randomized hashing on the keys is capable of balancing the workload for key-based partitioning when the keys generally follow a static distribution, it is likely to generate poor balancing performance when workload variance occurs on the incoming data stream. This paper presents a new key-based workload partitioning framework, with practical algorithms to support dynamic workload assignment for stateful operators. The framework combines hash-based and explicit key-based routing strategies for workload distribution, which specifies the destination worker threads for a handful of keys and assigns the other keys with the hashing function. When short-term distribution fluctuations occur to the incoming data stream, the system adaptively updates the routing table containing the chosen keys, in order to rebalance the workload with minimal migration overhead within the stateful operator. We formulate the rebalance operation as an optimization problem, with multiple objectives on minimizing state migration costs, controlling the size of the routing table and breaking workload imbalance among worker threads. Despite of the NP-hardness nature behind the optimization formulation, we carefully investigate and justify the heuristics behind key (re)routing and state migration, to facilitate fast response to workload variance with ignorable cost to the normal processing in the distributed system. Empirical studies on synthetic data and real-world stream applications validate the usefulness of our proposals and prove the huge advantage of our approaches over state-of-the-art solutions in the literature.

The HCCI-DI combustion mode was achieved in a heavy-duty diesel engine using the early pilot injection in the intake stroke and the main injection around compression top dead center (TDC). The effects of pilot injection quantity and EGR rate on HCCI-DI combustion and emissions were investigated. NOx emission has a dramatically decrease as the pilot injection quantity increases, but it is still in a high level that needs to be reduced. The smoke emission has a slight increase with the rise of pilot quantity, but it is always in a low level. The increasing HC and CO emissions can be easily removed by the diesel oxidation catalyst (DOC). The HCCI-DI combustion with low level of EGR is an effective method to reduce NOx emission further, and smoke emission increases as EGR rate increases, but it is in an acceptable level. The HCCI-DI combustion mode operating range is limited by the peak of cylinder pressure, the pressure rise rate and the cycle-to-cycle variations. There are optimal EGR rates and pilot quantities to achieve low NOx and low smoke emissions.

The Lower Silurian Longmaxi Formation is an organic-rich (black) mudrock that is widely considered to be a potential shale gas reservoir in the southern Sichuan Basin (the Yangtze plate) in Southwest China. A case study is presented to characterise the shale gas reservoir using a workflow to evaluate its characteristics. A typical characterisation of a gas shale reservoir was determined using basset sample analysis (geochemical, petrographical, mineralogical, and petrophysical) through a series of tests. The results show that the Lower Silurian Longmaxi Formation shale reservoir is characterised by organic geochemistry and mineralogical, petrophysical and gas adsorption. Analysis of the data demonstrates that the reservoir properties of the rock in this region are rich and that the bottom group of the Longmaxi Formation has the greatest potential for gas production due to higher thermal maturity, total organic carbon (TOC) enrichment, better porosity and improved fracture potential. These results will provide a basis for further evaluation of the hydrocarbon potential of the Longmaxi Formation shale in the Sichuan Basin and for identifying areas with exploration potential.

The Dongpu (东濮) depression is a Mesozoic subsidence and Cenozoic fault basin developed within the North China craton. Since the deposition of Permo-Carboniferous hydrocarbon source rock, the depression has undergone many tectonic disturbances and uplifts. The source rocks have undergone nonuniform uplift, deformation, deep burying, and magmatism, and those led to an interrupted or stepwise evolution of the hydrocarbon source rocks in Qinggu (庆古)-2 well. We have investigated the history of burying, heating, and hydrocarbon generation of the Permo-Carboniferous hydrocarbon source rocks not just on the basis of tectonic disturbance and deep burying, but also with new studies in apatite fission track analysis, fluid inclusion measurements, and the application of the numerical simulation of EASY%R o. The heating temperature of the source rocks pulsated upward from Indosinian to Himalayan stages and reached a maximum during early Himalayan. This led to the stepwise increases of organic maturation and multiple stages of hydrocarbon generation. This study delineated the tectonic stages, maturity evolved ranges, and the intensity of hydrocarbon generation of Permo-Carboniferous source rocks in Qinggu-2 well. The hydrocarbon generation mainly occurred during Indosinian and early Himalayan. The early Himalayan stage hydrocarbon generation is the larger one, but the Dongying (东营) movement, which happened at the end of early Himalayan, may destroy the trapped oil and gas. Thereby, future exploration will need to pay more attention to the Dongying movement effect in Qinggu-2 well area, and it may get new breakthrough in Permo-Carboniferous oil and gas.

Though, as a renewable energy resource, alcohol fuel has many advantages in China, it is difficult for diesel engines to operate on alcohol due to its low cetane number and high latent heat of vaporization. This paper proposes an approach to its ignition problem by combining internal exhaust gas recirculation (EGR) with injection of small diesel fuel. Based on this approach, a two-stroke single-cylinder diesel engine was developed. Preliminary studies demonstrated that the engine can run on alcohol with almost zero level of smoke and low exhaust gas temperature, and that the engine operating on alcohol has lower nitrogen oxide (NOx) emissions and 2–3% higher effective thermal efficiency than that operating on diesel fuel in moderate and high load zones.

A combustion control strategy is proposed for diesel engine to reduce PM and NOx emissions significantly, which adopts some technologies including internal exhaust gas recirculation (EGR), split spray, adjustable fuel delivery advance angle and the application of alternative fuels. Based on this strategy, a flexible fuel engine has been developed. The experimental results show that this engine can be fueled with diesel fuel, alcohol, dimethyl carbonate (DMC), etc. It works with extremely low levels of particulate matter (PM) and NOx, 2–3% higher effective thermal efficiency on moderate and high loads when alternative fuels are used. This engine not only has lower exhaust emissions, but also can be fueled with those alternative fuels, which are difficult to be ignited by compression.

A new concept of the controllable premixed combustion (CPC) system was proposed for dimethyl ether (DME) to explore a new approach to achieving ultra-low NOX emissions with the zero level of particulate matter exhaust emissions. The DME fuel was injected into the premix chamber by means of the electronically controlled low pressure injection system, then the mixture formation and combustion process were controlled with a control-valve set between the main chamber and the premix chamber. The test bench was constructed based on a single diesel engine. Preliminary studies demonstrated that ultra-low NOX emissions had been realized with zero particulate matter emissions under the optimum specifications of the DME engine, NOX emissions were less than 65 × 10−6. According to the engine combustion analysis, it was found that the control-valve played an important role in the pre-mixture formation and ignition timing.

Dual-fuel reactivity-controlled compression ignition (RCCI) combustion using port injection of a less reactive fuel and early-cycle direct injection of a more reactive fuel has been shown to yield both high thermal efficiency and low NOX and soot emissions over a wide engine operating range. Conventional and alternative fuels such as gasoline, natural gas and E85 as the lower reactivity fuel in RCCI have been studied by many researchers; however, published experimental investigations of hydrous ethanol use in RCCI are scarce. Making greater use of hydrous ethanol in internal combustion engines has the potential to dramatically improve the economics and life cycle carbon dioxide emissions of using bio-ethanol. In this work, an experimental investigation was conducted using 150 proof hydrous ethanol as the low reactivity fuel and commercially-available diesel as the high reactivity fuel in an RCCI combustion mode at various load conditions. A modified single-cylinder diesel engine was used for the experiments. Based on previous studies on RCCI combustion by other researchers, early-cycle split-injection strategy of diesel fuel was used to create an in-cylinder fuel reactivity distribution to maintain high thermal efficiency and low NOX and soot emissions. At each load condition, timing and mass fraction of the first diesel injection was held constant, while timing of the second diesel injection was swept over a range where stable combustion could be maintained. Since hydrous ethanol is highly resistant to auto-ignition and has large heat of vaporization, intake air heating was needed to obtain stable operations of the engine. The study shows that 150 proof hydrous ethanol can be used as the low reactivity fuel in RCCI through 8.6 bar IMEP and with ethanol energy fraction up to 75% while achieving simultaneously low levels of NOX and soot emissions. With increasing engine load, less intake heating is needed and EGR is required to maintain low NOX emissions. Future work will look at stability of hydrous ethanol RCCI at higher engine load.Copyright © 2013 by ASME

As a pure electronic device the flash memory has many outstanding features, such as higher read-write speed, lower noise and better shock-resistance. Flash-based DBMS soon becomes the area that attracts the most attention. A Flash-based DBMS FDBMS1.0 is implemented by us. The index is very important to improve the efficiency of flash-based DBMS, and researchers have put forward many index algorithm about it, among them, μ-Tree is a higher efficiency index. The μ-Tree is improvement of B+-tree for flash memory. One of great strengths of μ-Tree is the ability to remove the phenomenon of “wandering trees” that bring by traditional B+ Tree in flash memory. There is a scent of trouble to deal with update of index and the maintenance of tree's structure for intensive update or small record update operations. This paper proposes an improved μ-Tree structure to reduce cost in update index and the maintenance of tree's structure. The update-area and self-adaptive mechanism is utilized in the improved μ-Tree structure. The experimental results show that our method is effective.

Using genetic algorithm to resolve dynamic production scheduling problem of flexible job shop is presented. A math model and objective function for dynamic scheduling of flexible job shop is set up by analysis problem of flexible job shop scheduling and restrictive condition is research. A genetic operator that can meet the need of production scheduling of flexible job shop is designed based on working procedure coding. Coding, crossover, mutation, fitness calculation, controls parameter selection and stop condition is studied. Based on those simulation is carry out and the result of it show correctness and validity of arithmetic.