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The purpose of this study is to compare the different pesticides management practices and productions in three apple farms in the Northeastern US and Northern China.

Interviews and surveys were conducted in the three farms between the summer of 2010 and spring of 2011. Production, pesticide and fertilizer usage, and labor costs were calculated for comparison.

The conventional US apple grower manages his farm for maximum production and minimum labor costs. As a result, the farm achieved a high yield of 24.68 kg/dollar, but low health value for the highest amount of pesticide expenditure ($2.43 per 100 kg of apples). The organic apple farm aims at minimizing environmental impact and protecting consumers. Its yield was 14.22 kg/dollar with 15-30 percent greater labor costs. The health value of the apples improved with pesticide expenditure of $1.66 per 100 kg of apples. This farm uses only the least toxic pesticide certified by OMRI. The traditional apple farm in Northern China spent 1,365 hours/ha on bagging to protect consumers, comparing to only 252 hours/ha of total labor spent in the conventional apple farm. Annual production of the Chinese farm was 22,727 kg/ha, which was only 50 percent of the conventional apple production and 71 percent of the organic apple production.

The results reveal great potential for a much better economic and environmental effectiveness in the Chinese apple farm if they redirect labor from bagging to an effort for production and efficient management while still providing consumer protection.

The purpose of this paper is to focus on the climatic trends of mean annual temperature and annual precipitation from 1931 to 2000, in four regions of the USA: Northeast, South Atlantic, North Central, and Pacific West.

Five-year moving averages are calculated for each climatic variable of all regions and used for the trend analysis. Regression analysis was performed to evaluate the level of significance for each trend line. A trend with p < 0.0001 is considered statistically significant throughout the study.

The data show a 0.62°C increase in temperature in the Pacific West from 1931 to 2000. Over the same time period, precipitation has increased by 10.4 centimeters in the North Central Region, which is 10 percent higher than the long-term average for the region.

The 0.62°C increase suggests that the Pacific West may be experiencing the effect of global warming because this finding is consistent with the result of the Canadian climatic trend study by Zhang et al. who also found that annual precipitation has increased by 35 percent in southern Canada over the same period, which coincides with the increasing trend of precipitation found in the North Central Region. With the best available data and the findings from other studies, the authors are confident that the warming trend in the western USA is likely linked to the increasing sea surface temperature of the Pacific Ocean.

Student participation has been an important issue for information literacy (IL) teachings. The purpose of this paper is to promote active student participation in IL courses with Rain Classroom, an intelligent teaching tool.

Using mixed method research, the paper presents a practical case study of the author’s experiences with Rain Classroom to improve teaching and learning of IL.

The study shows that Rain Classroom helps implement problem-based learning, promote student participation in class interaction and optimize learning experience, which facilitates a shift of the IL course from passive to active learning.

It is known that university public courses have large class sizes (more than 50 students per class), and, therefore, class interaction is difficult to organize. So this is a big issue for the researchers to study.

The proposed Rain Classroom is a free teaching tool and can be used in other academic libraries to enhance active student participation in IL lessons.

The paper includes implications for improving interaction in large-size conference or trainings using Rain Classroom.

The existing literature has not traced the reports on using the Rain Classroom to enhance student participation in IL courses in academic libraries. This paper intends to fill this gap and share practical methods and experiences, deepening the application research of Rain Classroom.

This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of clean energy in China.

This study contained a sample of 653 households in 8 provinces/regions by stratified, and random sampling in rural China. Descriptive analysis, exploratory factor analysis and confirmatory factor analysis techniques have been used for analytical purposes.

The empirical results indicate that financial incentive and social interaction have positive effects on rural residents’ adoption willingness, while village leaders’ engagement can indirectly influence their adoption willingness through social interaction and residents’ cognition.

This study mainly considers external and internal factors but ignores the effect of technical factors. In addition, the samples are just selected from the residents who have adopted solar PV.

This study is expected to be useful for the government, regulators, village leaders, village leaders and other institutions.

This study conducts a systematic analysis and clarifies the relationship between factors (external and internal) and rural residents’ adoption willingness. The village leaders’ engagement is first added to the conceptual model as an external factor, which is very essential in rural residents’ adoption in China.

With the development of electronic devices, including the desires of integration, miniaturization, high performance and the output power, cooling requirement of chips have been increased gradually. Water-cooled minichannel is an effective cooling technology for cooling of heat sinks. The minichannel flow geometry offers large surface area for heat transfer and a high convective heat transfer coefficient with only a moderate pressure loss. The purpose of this paper is to analyze a minichannel heat sink having the bottom size of 35 mm×35 mm numerically. Two kinds of chip arrangement are investigated: diagonal arrangement and parallel arrangement.

Computational fluid dynamics (CFD) technique is used to investigate the flow and thermal fields in forced convection in a three-dimensional minichannels heat sink with different chip arrangements. The standard k-e turbulence model is applied for the turbulence simulations on the minichannel heat sink.

The results show that the bottom surface of the heat sink with various chip arrangements will have different temperature distribution and thermal resistance. A suitable chip arrangement will achieve a good cooling performance for electronic devices.

The fluid is incompressible and the thermophysical properties are constant.

New and additional data will be helpful as guidelines in the design of heat sinks to achieve a good thermal performance and a long lifetime in operation.

In real engineering situations, chips are always placed in various manners according to design conditions and constraints. In this case the assumption of uniform heat flux is acceptable for the surfaces of the chips rather than for the entire bottom surface of the heat sink.

The research on leaching behaviors of heavy metals in municipal solid waste incineration (MSWI) fly ash is of great significance. Because of the limitations like experimental condition, experiment data volume of heavy metals is difficult to achieve the prediction of requirements. In order to solve the problem of uncertainty and fuzziness caused by small sample, a new method based on fuzzy theory is proposed in this paper. By comparing fitting results from measured data and Visual MINTEQ simulation results, the method in this paper is considered to be more reliable and has a better interpretation for the leaching behaviors of heavy metals. The simulation results show the feasibility and superiority of the proposed method.

In general, cloud computing is a model of on-demand business computing that grants a convenient access to shared configurable resources on the internet. With the increment of workload and difficulty of tasks that are submitted by cloud consumers; “how to complete these tasks effectively and rapidly with limited cloud resources?” is becoming a challenging question. The major point of a task scheduling approach is to identify a trade-off among user needs and resource utilization. However, tasks that are submitted by varied users might have diverse needs of computing time, memory space, data traffic, response time, etc. This paper aims to proposes a new way of task scheduling.

To make the workflow completion in an efficient way and to reduce the cost and flow time, this paper proposes a new way of task scheduling. Here, a self-adaptive fruit fly optimization algorithm (SA-FFOA) is used for scheduling the workflow. The proposed multiple workflow scheduling model compares its efficiency over conventional methods in terms of analysis such as performance analysis, convergence analysis and statistical analysis. From the outcome of the analysis, the betterment of the proposed approach is proven with effective workflow scheduling.

The proposed algorithm is more superior regarding flow time with the minimum value, and the proposed model is enhanced over FFOA by 0.23%, differential evolution by 2.48%, artificial bee colony (ABC) by 2.85%, particle swarm optimization (PSO) by 2.46%, genetic algorithm (GA) by 2.33% and expected time to compute (ETC) by 2.56%. While analyzing the make span case, the proposed algorithm is 0.28%, 0.15%, 0.38%, 0.20%, 0.21% and 0.29% better than the conventional methods such as FFOA, DE, ABC, PSO, GA and ETC, respectively. Moreover, the proposed model has attained less cost, which is 2.14% better than FFOA, 2.32% better than DE, 3.53% better than ABC, 2.43% better than PSO, 2.07% better than GA and 2.90% better than ETC, respectively.

This paper presents a new way of task scheduling for making the workflow completion in an efficient way and for reducing the cost and flow time. This is the first paper uses SA-FFOA for scheduling the workflow.

The purpose of this paper is to investigate the relationship between board characteristics and real performance among state-owned enterprises (SOEs) in Malaysia in a longitudinal period following the introduction of transformation policy.

The study deviates from prior research in utilising a real performance measure rather than traditional measures of performance. The authors adopt the quantile regression approach to examine the impact of board characteristics on real performance in a comparison using ordinary least squares.

The results of quantile regression reveal that the impact of board mechanisms on real performance was not as expected. Specifically, board size and duality had a bearing on real performance. Board independence also is considered as influential factor through the time. However, such effects were not homogenous across different quantiles. The dummy year variable to compare the period pre- and post-transformation policy reveals that the dummy year is not significant, indicating that performance post-transformation is indifferent compared to the pre-transformation policy period.

It is important for government to reconsider the policies embedded in the transformation policy. This study provides insights on the enhancement of board effectiveness and new developments regarding GLCs.

This is an early to attempt to measure real performance and its link to board characteristics in SOEs post-transformation policy.