Stand-alone groundwater desalination system using reverse osmosis combined with a cooled greenhouse for use in arid and semi-arid zones of India

In many areas of northern India, salinity renders groundwater unsuitable for drinking and even for irrigation. Though membrane treatment can be used to remove the salt, there are some drawbacks to this approach e.g. (1) depletion of the groundwater due to over-abstraction, (2) saline contamination of surface water and soil caused by concentrate disposal and (3) high electricity usage. To address these issues, a system is proposed in which a photovoltaic-powered reverse osmosis (RO) system is used to irrigate a greenhouse (GH) in a stand-alone arrangement. The concentrate from the RO is supplied to an evaporative cooling system, thus reducing the volume of the concentrate so that finally it can be evaporated in a pond to solid for safe disposal. Based on typical meteorological data for Delhi, calculations based on mass and energy balance are presented to assess the sizing and cost of the system. It is shown that solar radiation, freshwater output and evapotranspiration demand are readily matched due to the approximately linear relation among these variables. The demand for concentrate varies independently, however, thus favouring the use of a variable recovery arrangement. Though enough water may be harvested from the GH roof to provide year-round irrigation, this would require considerable storage. Some practical options for storage tanks are discussed. An alternative use of rainwater is in misting to reduce peak temperatures in the summer. An example optimised design provides internal temperatures below 30EC (monthly average daily maxima) for 8 months of the year and costs about €36,000 for the whole system with GH floor area of 1000 m2 . Further work is needed to assess technical risks relating to scale-deposition in the membrane and evaporative pads, and to develop a business model that will allow such a project to succeed in the Indian rural context.

Should topical opioid analgesics be regarded as effective and safe when applied to chronic cutaneous lesions?

Objectives: The induction of analgesia for many chronic cutaneous lesions requires treatment with an opioid analgesic. In many patients suffering with these wounds such drugs are either contraindicated or shunned because of their association with death. There are now case reports involving over 100 patients with many different types of chronic superficial wounds, which suggest that the topical application of an opioid in a suitable gel leads to a significant reduction in the level of perceived pain. Key findings: Some work has been undertaken to elucidate the mechanisms by which such a reduction is achieved. To date there have been no proven deleterious effects of such an analgesic system upon wound healing. Although morphine is not absorbed through the intact epidermis, an open wound provides no such barrier and for large wounds drug absorption can be problematic. However, for most chronic cutaneous lesions, where data has been gathered, the blood levels of the drug applied ranges from undetectable to below that required for a systemic effect. Summary If proven, the use of opioids in this way would provide adequate analgesia for a collection of wounds, which are difficult to treat in patients who are often vulnerable. Proof of this concept is now urgently required. © 2011 Royal Pharmaceutical Society.

GENIAL Design: A System for Improving Guest Satisfaction with Hospitality Design

Over the past decades, hospitality design has lost sight of its basic goals of providing the guest with safe, pleasant, convenient accommodations and providing the owner with a facility which can be operated efficiently and profitably over the life of the structure. The author offers the acronym GE- NIAL, Guest, Environment, Needs, Interiors, Accessibility, and Long-term, as a means of keeping owners, developers, managers, and designers aware of the desired goals of the facility throughout its design and development. The author believes that the use of this acronym will promulgate de- signs more attuned to guest and owner/operator needs, resulting in in- creased guest satisfaction and increased profitability.

Using Computational Significance and Resilience in System Software Stacks.:Keynote Talk

This talk explores how the runtime system and operating system can leverage metrics that express the significance and resilience of application components in order to reduce the energy footprint of parallel applications. We will explore in particular how software can tolerate and indeed exploit higher error rates in future processors and memory technologies that may operate outside their safe margins.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Efficacy of entecavir and tenofovir in chronic hepatitis B under treatment in the public health system in southern Brazil

There are about 350 million hepatitis B virus (HBV) carriers worldwide and chronic HBV is considered a major public health problem. The objective of the present study was to assess the effectiveness of the nucleos(t)ide analogues tenofovir (TDF) and entecavir (ETV) in the treatment of chronic HBV. A cross-sectional study was carried out from March-December 2013, including all patients with chronic HBV, over 18 years of age, undergoing therapy through the public health system in southern Brazil. Only the data relating to the first treatments performed with TDF or ETV were considered. Retreatment, co-infection, transplanted or immunosuppressed patients were excluded. Six hundred and forty patients were evaluated, of which 336 (52.5%) received TDF and 165 (25.8%) ETV. The other 139 (21.7%) used various combinations of nucleos(t)ide analogues and were excluded. The negativation of viral load was observed in 87.3% and 78.8% and the negativation of hepatitis B e antigen was achieved in 79% and 72% of those treated with ETV or TDF, respectively. Negativation of hepatitis B surface antigen was not observed. There was no occurrence of adverse effects. This is a real-life study demonstrating that long-term treatment with ETV and TDF is both safe and effective.

Methotrexate nanoparticle delivery system for treatment of inflammatory bowel disease in pediatric patients

Purpose: To evaluate the efficacy and safety of methotrexate (MTX) nanoparticles in pediatric patients with inflammatory bowel disease (IBD). Methods: In this randomized, open-label clinical study, 28 pediatric patients with moderate to severe IBD were randomly assigned to treatment (MTX nanoparticles,15 mg/week) or control (azathioprine, AZA, 2 mg/kg/day) group. Nanoparticles were synthesized by adding calcium chloride to sodium alginate solution containing MTX, and was further treated with poly-L-lysine aqueous solution. The nanoparticles were evaluated for particle size, zeta potential and drug encapsulation efficacy. Erythrocyte sedimentation rate, C-reactive protein, aspartate aminotransferase, alanine transaminase, and disease activity scores were used to assess IBD remission. Results: Nanoparticle size, zeta potential and encapsulation efficacy were 164.4 ± 6.9 nm, -32.6 ± 3.7 mV, and 97.8 ± 4.2 %, respectively. After 12 weeks of therapy, the mean Pediatric Crohn\'s Disease Activity Index (PCDAI) scores for control and treatment groups were 22.3 ± 2.14 and 16.8 ± 1.87, respectively, while mean Pediatric Ulcerative Colitis Activity (PUCAI) Index scores were 24.3 ± 1.47 and 18.7 ± 1.92, respectively. Eight patients in the treatment and five patients in the control group achieved remission. Biochemical parameters varied significantly between the groups. Conclusion: MTX nanoparticles are safe and more effective than standard first-line IBD therapy. However, further studies are required to determine the suitability of the formulation for therapeutic use.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Engineering design of an integrated sustainable process system for cassava biobased materials

Cassava contributes significantly to biobased material development. Conventional approaches for its bio-derivative-production and application cause significant wastes, tailored material development challenges, with negative environmental impact and application limitations. Transforming cassava into sustainable value-added resources requires redesigning new approaches. Harnessing unexplored material source, and downstream process innovations can mitigate challenges. The ultimate goal proposed an integrated sustainable process system for cassava biomaterial development and potential application. An improved simultaneous release recovery cyanogenesis (SRRC) methodology, incorporating intact bitter cassava, was developed and standardized. Films were formulated, characterised, their mass transport behaviour, simulating real-distribution-chain conditions quantified, and optimised for desirable properties. Integrated process design system, for sustainable waste-elimination and biomaterial development, was developed. Films and bioderivatives for desired MAP, fast-delivery nutraceutical excipients and antifungal active coating applications were demonstrated. SRRC-processed intact bitter cassava produced significantly higher yield safe bio-derivatives than peeled, guaranteeing 16% waste-elimination. Process standardization transformed entire root into higher yield and clarified colour bio-derivatives and efficient material balance at optimal global desirability. Solvent mass through temperature-humidity-stressed films induced structural changes, and influenced water vapour and oxygen permeability. Sevenunit integrated-process design led to cost-effectiveness, energy-efficient and green cassava processing and biomaterials with zero-environment footprints. Desirable optimised bio-derivatives and films demonstrated application in desirable in-package O2/CO2, mouldgrowth inhibition, faster tablet excipient nutraceutical dissolutions and releases, and thymolencapsulated smooth antifungal coatings. Novel material resources, non-root peeling, zero-waste-elimination, and desirable standardised methodology present promising process integration tools for sustainable cassava biobased system development. Emerging design outcomes have potential applications to mitigate cyanide challenges and provide bio-derivative development pathways. Process system leads to zero-waste, with potential to reshape current style one-way processes into circular designs modelled on nature's effective approaches. Indigenous cassava components as natural material reinforcements, and SRRC processing approach has initiated a process with potential wider deployment in broad product research development. This research contributes to scientific knowledge in material science and engineering process design.

Safe and Collaborative Navigation & Interaction With Mobile Manipulators in Domestic Appliance Test Labs

Safe collaboration between a robot and human operator forms a critical requirement for deploying a robotic system into a manufacturing and testing environment. In this dissertation, the safety requirement for is developed and implemented for the navigation system of the mobile manipulators. A methodology for human-robot co-existence through a 3d scene analysis is also investigated. The proposed approach exploits the advance in computing capability by relying on graphic processing units (GPU’s) for volumetric predictive human-robot contact checking. Apart from guaranteeing safety of operators, human-robot collaboration is also fundamental when cooperative activities are required, as in appliance test automation floor. To achieve this, a generalized hierarchical task controller scheme for collision avoidance is developed. This allows the robotic arm to safely approach and inspect the interior of the appliance without collision during the testing procedure. The unpredictable presence of the operators also forms dynamic obstacle that changes very fast, thereby requiring a quick reaction from the robot side. In this aspect, a GPU-accelarated distance field is computed to speed up reaction time to avoid collision between human operator and the robot. An automated appliance testing also involves robotized laundry loading and unloading during life cycle testing. This task involves Laundry detection, grasp pose estimation and manipulation in a container, inside the drum and during recovery grasping. A wrinkle and blob detection algorithms for grasp pose estimation are developed and grasp poses are calculated along the wrinkle and blobs to efficiently perform grasping task. By ranking the estimated laundry grasp poses according to a predefined cost function, the robotic arm attempt to grasp poses that are more comfortable from the robot kinematic side as well as collision free on the appliance side. This is achieved through appliance detection and full-model registration and collision free trajectory execution using online collision avoidance.

Obesity And Inflammation And The Effect On The Hematopoietic System.

Bone marrow is organized in specialized microenvironments known as 'marrow niches'. These are important for the maintenance of stem cells and their hematopoietic progenitors whose homeostasis also depends on other cell types present in the tissue. Extrinsic factors, such as infection and inflammatory states, may affect this system by causing cytokine dysregulation (imbalance in cytokine production) and changes in cell proliferation and self-renewal rates, and may also induce changes in the metabolism and cell cycle. Known to relate to chronic inflammation, obesity is responsible for systemic changes that are best studied in the cardiovascular system. Little is known regarding the changes in the hematopoietic system induced by the inflammatory state carried by obesity or the cell and molecular mechanisms involved. The understanding of the biological behavior of hematopoietic stem cells under obesity-induced chronic inflammation could help elucidate the pathophysiological mechanisms involved in other inflammatory processes, such as neoplastic diseases and bone marrow failure syndromes.

The Value Of The 2005 International Society Of Urological Pathology (isup) Modified Gleason Grading System As A Predictor Of Biochemical Recurrence After Radical Prostatectomy.

To compare time and risk to biochemical recurrence (BR) after radical prostatectomy of two chronologically different groups of patients using the standard and the modified Gleason system (MGS). Cohort 1 comprised biopsies of 197 patients graded according to the standard Gleason system (SGS) in the period 1997/2004, and cohort 2, 176 biopsies graded according to the modified system in the period 2005/2011. Time to BR was analyzed with the Kaplan-Meier product-limit analysis and prediction of shorter time to recurrence using univariate and multivariate Cox proportional hazards model. Patients in cohort 2 reflected time-related changes: striking increase in clinical stage T1c, systematic use of extended biopsies, and lower percentage of total length of cancer in millimeter in all cores. The MGS used in cohort 2 showed fewer biopsies with Gleason score ≤ 6 and more biopsies of the intermediate Gleason score 7. Time to BR using the Kaplan-Meier curves showed statistical significance using the MGS in cohort 2, but not the SGS in cohort 1. Only the MGS predicted shorter time to BR on univariate analysis and on multivariate analysis was an independent predictor. The results favor that the 2005 International Society of Urological Pathology modified system is a refinement of the Gleason grading and valuable for contemporary clinical practice.

The Applicability Of Ordered Mesoporous Sba-15 And Its Hydrophobic Glutaraldehyde-bridge Derivative To Improve Ibuprofen-loading In Releasing System.

The mesoporous SBA-15 silica with uniform hexagonal pore, narrow pore size distribution and tuneable pore diameter was organofunctionalized with glutaraldehyde-bridged silylating agent. The precursor and its derivative silicas were ibuprofen-loaded for controlled delivery in simulated biological fluids. The synthesized silicas were characterized by elemental analysis, infrared spectroscopy, (13)C and (29)Si solid state NMR spectroscopy, nitrogen adsorption, X-ray diffractometry, thermogravimetry and scanning electron microscopy. Surface functionalization with amine containing bridged hydrophobic structure resulted in significantly decreased surface area from 802.4 to 63.0 m(2) g(-1) and pore diameter 8.0-6.0 nm, which ultimately increased the drug-loading capacity from 18.0% up to 28.3% and a very slow release rate of ibuprofen over the period of 72.5h. The in vitro drug release demonstrated that SBA-15 presented the fastest release from 25% to 27% and SBA-15GA gave near 10% of drug release in all fluids during 72.5 h. The Korsmeyer-Peppas model better fits the release data with the Fickian diffusion mechanism and zero order kinetics for synthesized mesoporous silicas. Both pore sizes and hydrophobicity influenced the rate of the release process, indicating that the chemically modified silica can be suggested to design formulation of slow and constant release over a defined period, to avoid repeated administration.

Electronic And Structural Study Of Pt-modified Au Vicinal Surfaces: A Model System For Pt-au Catalysts.

Two single crystalline surfaces of Au vicinal to the (111) plane were modified with Pt and studied using scanning tunneling microscopy (STM) and X-ray photoemission spectroscopy (XPS) in ultra-high vacuum environment. The vicinal surfaces studied are Au(332) and Au(887) and different Pt coverage (θPt) were deposited on each surface. From STM images we determine that Pt deposits on both surfaces as nanoislands with heights ranging from 1 ML to 3 ML depending on θPt. On both surfaces the early growth of Pt ad-islands occurs at the lower part of the step edge, with Pt ad-atoms being incorporated into the steps in some cases. XPS results indicate that partial alloying of Pt occurs at the interface at room temperature and at all coverage, as suggested by the negative chemical shift of Pt 4f core line, indicating an upward shift of the d-band center of the alloyed Pt. Also, the existence of a segregated Pt phase especially at higher coverage is detected by XPS. Sample annealing indicates that the temperature rise promotes a further incorporation of Pt atoms into the Au substrate as supported by STM and XPS results. Additionally, the catalytic activity of different PtAu systems reported in the literature for some electrochemical reactions is discussed considering our findings.