Conditional Preference Networks with User's Genuine Decisions

User's choices involve habitual behavior and genuine decision. Habitual behavior is often expressed using preferences. In a multiattribute case, the Conditional Preference Network (CP-net) is a graphical model to represent user's conditional ceteris paribus (all else being equal) preference statements. Indeed, the CP-net induces a strict partial order over the outcomes. By contrast, we argue that genuine decisions are environmentally influenced and introduce the notion of “comfort” to represent this type of choices. In this article, we propose an extension of the CP-net model that we call the CP-net with Comfort (CPC-net) to represent a user's comfort with preferences. Given that preference and comfort might be two conflicting objectives, we define the Pareto optimality of outcomes when achieving outcome optimization with respect to a given CPC-net. Then, we propose a backtrack search algorithm to find the Pareto optimal outcomes. On the other hand, two outcomes can stand in one of six possible relations with respect to a CPC-net. The exact relation can be obtained by performing dominance testing in the corresponding CP-net and comparing the numeric comforts.     

Protein–Energy Malnutrition: A Risk Factor for Various Ailments

The wheel of industrialization that spun throughout the last century resulted in urbanization coupled with modifications in lifestyles and dietary habits. However, the communities living in developing economies are facing many problems related to their diet and health. Amongst, the prevalence of nutritional problems especially protein–energy malnutrition (PEM) and micronutrients deficiencies are the rising issues. Moreover, the immunity or susceptibility to infect-parasitic diseases is also directly linked with the nutritional status of the host. Likewise, disease-related malnutrition that includes an inflammatory component is commonly observed in clinical practice thus affecting the quality of life. The PEM is treatable but early detection is a key for its appropriate management. However, controlling the menace of PEM requires an aggressive partnership between the physician and the dietitian. This review mainly attempts to describe the pathophysiology, prevalence and consequences of PEM and aims to highlight the importance of this clinical syndrome and the recent growth in our understanding of the processes behind its development. Some management strategies/remedies to overcome PEM are also the limelight of the article. In the nutshell, early recognition, prompt management, and robust follow up are critical for best outcomes in preventing and treating PEM.     

MRMR Based Feature Vector Design for Efficient Citrus Disease Detection

In recent times, the images and videos have emerged as one of the most important information source depicting the real time scenarios. Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane. The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition. One of the application fields pertains to detection of diseases occurring in the plants, which are destroying the widespread fields. Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests. This is a tedious and time consuming process and does not suffice the accuracy levels. This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading. The digital images captured from the field's forms the dataset which trains the machine learning models to predict the nature of the disease. The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images, appropriate segmentation methodology, feature vector development and the choice of machine learning algorithm. To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages. Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection. The training vector thus developed is capable of presenting the relationship between the feature values and the target class. In this article, a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is proposed. The overall improvement in terms of accuracy is measured and depicted.     

Microbial-Catalyzed Biotransformation of Multifunctional Triterpenoids Derived from Phytonutrients

Microbial-catalyzed biotransformations have considerable potential for the generation of an enormous variety of structurally diversified organic compounds, especially natural products with complex structures like triterpenoids. They offer efficient and economical ways to produce semi-synthetic analogues and novel lead molecules. Microorganisms such as bacteria and fungi could catalyze chemo-, regio- and stereospecific hydroxylations of diverse triterpenoid substrates that are extremely difficult to produce by chemical routes. During recent years, considerable research has been performed on the microbial transformation of bioactive triterpenoids, in order to obtain biologically active molecules with diverse structures features. This article reviews the microbial modifications of tetranortriterpenoids, tetracyclic triterpenoids and pentacyclic triterpenoids.     

Effect of atomic layer deposition temperature on the performance of top-down ZnO nanowire transistors

This paper studies the effect of atomic layer deposition (ALD) temperature on the performance of top-down ZnO nanowire transistors. Electrical characteristics are presented for 10-μm ZnO nanowire field-effect transistors (FETs) and for deposition temperatures in the range 120°C to 210°C. Well-behaved transistor output characteristics are obtained for all deposition temperatures. It is shown that the maximum field-effect mobility occurs for an ALD temperature of 190°C. This maximum field-effect mobility corresponds with a maximum Hall effect bulk mobility and with a ZnO film that is stoichiometric. The optimized transistors have a field-effect mobility of 10 cm²/V.s, which is approximately ten times higher than can typically be achieved in thin-film amorphous silicon transistors. Furthermore, simulations indicate that the drain current and field-effect mobility extraction are limited by the contact resistance. When the effects of contact resistance are de-embedded, a field-effect mobility of 129 cm²/V.s is obtained. This excellent result demonstrates the promise of top-down ZnO nanowire technology for a wide variety of applications such as high-performance thin-film electronics, flexible electronics, and biosensing.     

Performance of PAM/PEI gel system for water shut‐off in high temperature reservoirs: Laboratory study

A polymer gel is one of the common remediate methods to either reduce or totally block excessive water production in oilfields. Some systems demonstrated an excellent performance in treating the problem like polyacrylamide tert‐butyl acrylate (PAtBA)/polyethylenimine (PEI). In this study, polyacrylamide (PAM) was introduced as a cheap alternative to PAtBA that can tolerate high salinity reservoirs. The thermal stability of the PAM/PEI polymeric gel in saline water was examined at 150°C (302F). Samples prepared in sea water showed better stability compared with distilled and field water. Dynamic rheology and core‐flooding experiments were used to evaluate the PAM / PEI gel system at high temperatures. NaCl and NH₄Cl were evaluated as a possible retarders for delaying the gelation time in order to achieve a successful placement. NH₄Cl was found to be more effective retarder. Core‐flooding tests were conducted in sandstone and carbonate cores. The subject polymer gel was injected at rates typical of those in field applications. The injectivity of PAM/PEI was tested in Berea sandstone cores with initial permeability of ～45 mD. The post‐treatment of the system showed a permeability reduction of ～94% for a period of two weeks. The injectivity in low permeability carbonate cores required more retardation compared with the injectivity in sandstone cores. The gel reduced the permeability to brine in Indiana limestone core by 99.8% for more than 5 months. Rheology of cured gel samples indicated that the gel strength needs about one day of curing in the core for the strength to stabilize. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41869.     

Use of multisensor and multitemporal geospatial datasets to extract the foundation characteristics of a large building: a case study

Bulletin of Engineering Geology and the Environment - The assessment of the ground conditions for large buildings is important because the results are sensitive to the ground conditions, especially...     

Inorganic thermoelectric materials: A review

Thermoelectric generator, which converts heat into electrical energy, has great potential to power portable devices. Nevertheless, the efficiency of a thermoelectric generator suffers due to inefficient thermoelectric material performance. In the last two decades, the performance of inorganic thermoelectric materials has been significantly advanced through rigorous efforts and novel techniques. In this review, major issues and recent advancements that are associated with the efficiency of inorganic thermoelectric materials are encapsulated. In addition, miscellaneous optimization strategies, such as band engineering, energy filtering, modulation doping, and low dimensional materials to improve the performance of inorganic thermoelectric materials are reported. The methodological reviews and analyses showed that all these techniques have significantly enhanced the Seebeck coefficient, electrical conductivity, and reduced the thermal conductivity, consequently, improved ZT value to 2.42, 2.6, and 1.85 for near-room, medium, and high temperature inorganic thermoelectric material, respectively. Moreover, this review also focuses on the performance of silicon nanowires and their common fabrication techniques, which have the potential for thermoelectric power generation. Finally, the key outcomes along with future directions from this review are discussed at the end of this article.