Differentiations of 5-HT and GAS cells in the digestive canals of Rana chensinensis tadpoles

In the current study, 5-nydroxytryptamine （5-HT） and gastrin （GAS） cells in the digestive canals of Rana chensinensis tadpoles at different developmental stages were investigated by immunohistochemistry. Results showed that the 5-HT cells were only detected in the duodenum before metamorphosis began, and were extensively distributed in the stomach, duodenum, small intestine, and rectum thereafter, with the highest counts found in the duodenum and rectum when metamorphosis was completed. The GAS cells were only distributed in the stomach and duodenum, and only rarely detected in the duodenum before metamorphosis began, but increased in the stomach during metamorphosis and showed zonal distribution in the gastric mucosa when metamorphosis was completed. Metamorphosis is a critical period for amphibians, during which structural and functional physiological adaptations are required to transition from aquatic to terrestrial environments. During metamorphosis, the differentiations of 5-HT cells in the gastrointestinal canals of tadpoles could facilitate mucus secretion regulation, improve digestive canal lubrication, and help water- shortage food digestion in terrestrial environments. Conversely, GAS cell differentiations during metamorphosis might contribute to the digestive and absorptive function transition from herbivore to omnivore.

GTL or LNG:Which is the best way to monetize "stranded" natural gas?

A large portion of world＇s natural gas reserves are ＂stranded＂ resources, the drive to monetize these resources leads to the development of gas-to-liquids （GTL） and liquefied natural gas （LNG） technologies. LNG has the advantage of having been developed for the past 40 years and having an excellent safety record. GTL on the other hand is another option with substantial benefits, but its development stage and commercial viability are far behind LNG. This paper presents a techno-economic comparison of GTL with LNG, including technical development, plant efficiency, market potential for the products, and capital cost for the infrastructure. The aim is to give an overall view on both LNG and GTL and provide a perspective on the profitability of these two technologies.

Numerical analysis of gas emission rule from a goaf of tailing roadway

Targeting the problem of large amounts of gas emission from the goaf of the No.14201 working face in the Shaqu coal mine of Huajin Coking Coal Co. Ltd., we used a negative exponential function to describe the attenuation process of gas emission in goaf (the stable source) based on the principle of field flow. Equations of two-component flow (gas and air) and seep- age-diffusion in a heterogeneous goaf flow field are solved by means of numerical simulation and fluid mechanics principles of air movement and gas distribution during gas emission from goaf. The results indicate that the air diversion volume has a negative, exponential relation with the volume of gas emitted from goaf to the working face and is clearly inversely related to gas concentra- tion. We calculated the minimum amount of air diversion and distributed air volume in the tailing roadway required for safe pro- duction.

Biology and treatment of cervical adenocarcinoma

Uterine cervical adenocarcinoma （ADC） has been increasing in its prevalence world widely despite the decrease of squamous cell carcinoma （SCC）. It comprises nearly 20-25% of the all cervical malignancy in developed countries. The worse biological behavior had been reported in patients with intermediateand high risk factors after surgery, and in advanced stage over III, radiotherapy （RT） alone and concurrent chemo-radiotherapy （CCRT） with cisplatin was not always effective. As for chemotherapy （CT）, the iaduction CT has not established, as well. Further molecular targeted therapy （MTT） has been studied. The targets of oncogenic driver mutations were vascular endothelial growth factor （VEGF） in SCC, or tyrosine kinase （TK） of endothelial growth factor receptor 2 （EGFR2, Her2/neu）-Ras-MAPK-ERK pathway. Bevacizumab （Bey, anti-VEGF monoclonal antibody） is considered as one of key agent with paclitaxel and carboplatin in SCC, but not for ADC. This article focuses on up-to-date knowledge of biology and possible specific therapeutic directions to explore in the management of cervical ADC.

Evaluation of the effect and profitability of gene-assisted selection in pig breeding system

Objective:To evaluate the effect and profitability of using the quantitative trait loci (QTL)-linked direct marker (DR marker) in gene-assisted selection (GAS). Methods: Three populations (100, 200, or 300 sows plus 10 boars within each group) with segregating QTL were simulated stochastically. Five economic traits were investigated, including number of born alive (NBA), average daily gain to 100 kg body weight (ADG), feed conversion ratio (FCR), back fat at 100 kg body weight (BF) and intramuscular fat (IMF). Selection was based on the estimated breeding value (EBV) of each trait. The starting frequencies of the QTL's favorable allele were 0.1, 0.3 and 0.5, respectively. The economic return was calculated by gene flow method. Results: The selection efficiency was higher than 100% when DR markers were used in GAS for 5 traits. The selection efficiency for NBA was the highest, and the lowest was for ADG whose QTL had the lowest variance. The mixed model applied DR markers and obtained higher extra genetic gain and extra economic returns. We also found that the lower the frequency of the favorable allele of the QTL, the higher the extra return obtained. Conclusion: GAS is an effective selection scheme to increase the genetic gain and the eco- nomic returns in pig breeding.

Employing Computational Intelligence to Generate More Intelligent and Energy Efficient Living Spaces

Our living environments are being gradually occupied with an abundant number of digital objects that have networking and computing capabilities. After these devices are plugged into a network, they initially advertise their presence and capabilities in the form of services so that they can be discovered and, if desired, exploited by the user or other networked devices. With the increasing number of these devices attached to the network, the complexity to configure and control them increases, which may lead to major processing and communication overhead. Hence, the devices are no longer expected to just act as primitive stand-alone appliances that only provide the facilities and services to the user they are designed for, but also offer complex services that emerge from unique combinations of devices. This creates the necessity for these devices to be equipped with some sort of intelligence and self-awareness to enable them to be self-configuring and self-programming. However, with this ＂smart evolution＂, the cognitive load to configure and control such spaces becomes immense. One way to relieve this load is by employing artificial intelligence （AI） techniques to create an intelligent ＂presence＂ where the system will be able to recognize the users and autonomously program the environment to be energy efficient and responsive to the user＇s needs and behaviours. These AI mechanisms should be embedded in the user＇s environments and should operate in a non-intrusive manner. This paper will show how computational intelligence （CI）, which is an emerging domain of AI, could be employed and embedded in our living spaces to help such environments to be more energy efficient, intelligent, adaptive and convenient to the users.

The efficacy of the inhalation of an aerosolized Group A streptococcal preparation in the treatment of lung cancer

Objective： To observe the efficacy of the inhalation of an aerosonzeo group ~ sueloto^u v / preparation in treating orthotopic lung cancer in mouse models and assess the feasibility, safety, and effectiveness of this administration mode for lung cancer. Methods： Lewis lung carcinoma （LLC） cell strains were administered via intrathoracic injection to establish orthotopic lung cancer mouse models. After the tumor-bearing models were successfully established, as confirmed by computed tomography, the mice were administered by inhalation with an aerosolized GAS preparation （GAS group） or aerosolized normal saline （control group）. The anti-tumor effect of the aerosolized GAS preparation was evaluated histologically; meanwhile, the survival and quality of life were compared between these two groups. Results： The aerosolized GAS preparation showed remarkably anti-tumor effect, causing the necrosis of the orthotopic lung cancer cells in tumor-bearing mice. Furthermore, mice in the GAS group had significantly better qualitT of life and longer survival than those in control group. Conclusions： The inhalation of aerosolized GAS preparation may be a feasible, safe and effective solution for lung cancer

WHR （Waste Heat Technology） Method in Tri-generation Model

This paper is focused on description of cool production in using WHR （Waste Heat Technology） Technology-a new method of centralized production of heat by using the waste heat from generated exhaust gas, which has been in 2009 developed and operated by companies HELORO s.r.o, and COMTHERM s.r.o.

Chemical Composition and Antibacterial Activity of Artemisia herba-alba and Mentha pulegium Essential Oils

The chemical composition of essential oils obtained from Artemisia herba-alba and Mentha pulegium were determined. The essential oils were analyzed by gas chromatography coupled with mass spectrometry （GC/MS）. Their antibacterial activity was studied in vitro against three standard strains： E. coli ATCC 25922, Staphylococcus aureus ATCC 29213, Pseudomonas aeruginosa ATCC 27853, and five clinical strains： Enterobacter cloacae, Staphylococcus aureus, Pseudomonas pyocyanique, Enterococcus faecium, and E. coli. Nineteen constituents were identified in A. herba-alba essential oil representing 99.57% of the total composition The major component was α-thujone （59.07%）. The bacterial strains were inhibited at concentrations ranging from 1.25 μL/mL to 5μL/mL and killed at concentrations ranging from 1.25 μL/mL to 10 μL/mL. M. pulegium resulted in the identification of eighteen constituents representing 99.48% of the total composition. The main component was pulegone （78.07%）. The minimal inhibitory （MIC） and bactericidal （MBC） concentrations were ranging from 1.25 μL/mL to 2.5 μL/mL.

Non-local Consciousness Influence to Physical Sensors： Experimental Data

Experimental approach to investigation of NLCI （Non-local Consciousness Influence） effects is based on sensors of different design, and most of it based on transitional effects in gas-discharge plasma with several quasi-stable states is also presented. Computerized device for detecting NLCI is based on commercially available Gas Discharge Camera （www.ktispb.ru） and allows following time dynamics of several sensors in NLCI conditions. The typical sensors are： water, air, earth, and wood, this instrument was named ＂The 5th Element＂. Readings are taken continuously by special software every five or ten seconds in automatic mode. Sensitivity of the device was tested by detecting the influence of total sun eclipse in Siberia in 2008 and by detecting sunrise and sunset. Several experimental modalities have been developed： （1） directed NLCI of a person; （2） directed NLCI of a group of people; and （3） non-directed NLCI of a group of people. Experiments during many years demonstrated efficiency of the developed approach.

Balancing multiple criteria in formulation of weighted, single-objective genetic algorithm optimization for CNC machining problems

This paper presents results obtained from the implementation of a genetic algorithm （GA） to a simplified multi-objective machining optimization problem. The major goal is to examine the effect of crucial machining parameters imparted to computer numerical control machining operations when properly balanced conflicting criteria referring to part quality and process productivity are treated as a single optimization objective. Thus the different combinations of weight coefficient values were examined in terms of their significance to the problem＇s response. Under this concept, a genetic algorithm was applied to optimize the process parameters exist in typical; commercially available CAM systems with significantly low computation cost. The algorithm handles the simplified linear weighted criteria expression as its objective function. It was found that optimization results vary noticeably under the influence of different weighing coefficients. Thus, the obtained optima differentiate, since balancing values strongly affect optimization objective functions.

A comparative study of differential evolution and genetic algorithms for optimizing the design of water distribution systems

The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performarice comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm （GA）. A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies, indicating that the DE exhibits comparable performance with other algorithms. It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs.

Neuro-heuristic computational intelligence for solving nonlinear pantograph systems

We present a neuro-heuristic computing platform for finding the solution for initial value problems （IVPs） of non- linear pantograph systems based on functional differential equations （P-FDEs） of different orders. In this scheme, the strengths of feed-forward artificial neural networks （ANNs）, the evolutionary computing technique mainly based on genetic algorithms （GAs）, and the interior-point technique （IPT） are exploited. Two types of mathematical models of the systems are constructed with the help of ANNs by defining an unsupervised error with and without exactly satisfying the initial conditions. The design parameters of ANN models are optimized with a hybrid approach GA-IPT, where GA is used as a tool for effective global search, and IPT is incorporated for rapid local convergence. The proposed scheme is tested on three different types oflVPs of P-FDE with orders 1-3 The correctness of the scheme is established by comparison with the existing exact solutions. The accuracy and convergence ofthc proposed scheme are further validated through a large number of numerical experiments by taking different numbers of neurons in ANN models.

Measure oriented training： a targeted approach to imbalanced classification problems

Since the overall prediction error of a classifier on imbalanced problems can be potentially misleading and bi- ased, alternative performance measures such as G-mean and F-measure have been widely adopted. Various techniques in- cluding sampling and cost sensitive learning are often em- ployed to improve the performance of classifiers in such sit- uations. However, the training process of classifiers is still largely driven by traditional error based objective functions. As a result, there is clearly a gap between the measure accord- ing to which the classifier is evaluated and how the classifier is trained. This paper investigates the prospect of explicitly using the appropriate measure itself to search the hypothesis space to bridge this gap. In the case studies, a standard three- layer neural network is used as the classifier, which is evolved by genetic algorithms （GAs） with G-mean as the objective function. Experimental results on eight benchmark problems show that the proposed method can achieve consistently fa- vorable outcomes in comparison with a commonly used sam- pling technique. The effectiveness of multi-objective opti- mization in handling imbalanced problems is also demon- strated.