A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Which soft lens power is better for piggyback in keratoconus? Part II

Purpose: To evaluate how soft lens power affects rigid gas-permeable (RGP) lens power and visual acuity (VA) in piggyback fittings for keratoconus. Methods: Sixteen keratoconus subjects (30 eyes) were included in the study. Piggyback contact lens fittings combining Senofilcon-A soft lenses of −6.00, −3.00, +3.00 and +6.00 D with Rose K2 RGP contact lenses were performed. Corneal topography was taken on the naked eye and over each soft contact lens before fitting RGP lenses. Mean central keratometry, over-refraction, RGP back optic zone radius (BOZR) and estimated final power as well as VA were recorded and analyzed. Results: In comparison to the naked eye, the mean central keratometry flattened with both negative lens powers (p < 0.05 in all cases), did not change with the +3.00 soft lens power (p = 1.0); and steepened with the +6.00 soft lens power (p = 0.02). Rigid gas-permeable over-refraction did not change significantly between different soft lens powers (all p > 0.05). RGP’s BOZR decreased significantly with both positive in comparison with both negative soft lens powers (all p < 0.001), but no significant differences were found among negative- or positive-powers separately (both p > 0.05). Estimated RGP’s final power increased significantly with positive in comparison with negative lens powers (all p < 0.001), but no significant differences were found among negative or positive lens powers separately (both p > 0.05). Visual acuity did not change significantly between the different soft lens powers assessed (all p > 0.05). Conclusion: The use of negative-powered soft lenses in piggyback fitting reduces RGP lens power without impacting VA in keratoconus subjects.

Myopia control with a novel peripheral gradient soft lens and orthokeratology: a 2-year clinical trial

Objective. To evaluate the degree of axial elongation with soft radial refractive gradient (SRRG) contact lenses, orthokeratology (OK), and single vision (SV) spectacle lenses (control) during a period of 1 year before treatment and 2 years after treatment. Methods. This was a prospective, longitudinal, nonrandomized study. The study groups consisted of 30, 29, and 41 children, respectively. The axial length (AL) was measured during 2 years after recruitment and lens fitting. Results. The baseline refractive sphere was correlated significantly (r 2 = 0.542; P < 0.0001) with the amount of myopia progression before baseline. After 2 years, the mean myopia progression values for the SRRG, OK, and SV groups were −0.56 ± 0.51, −0.32 ± 0.53, and −0.98 ± 0.58 diopter, respectively. The results represent reductions in myopic progression of 43% and 67% for the SRRG and OK groups, respectively, compared to the SV group. The AL increased more in the SV group compared to the SRRG and OK groups, with 27% and 38% lower axial elongation, respectively, compared to the SV group at the 2-year visit (P < 0.05). SRRG and OK showed no differences (P = 0.430). Conclusion. The SRRG lens significantly decreased AL elongation compared to the SV control group. The SRRG lens was similarly effective to OK in preventing myopia progression in myopic children and adolescent.

Common symptoms of Nepalese soft contact lens wearers: A pilot study

Aim: To determine the common symptoms in current soft contact lens (CL) wearers and theirassociation with other factors among Nepalese population.Methods: All the current CL wearers who started to wear soft CL in Nepal Eye Hospital between July 2007 and June 2012 were invited for the participation. Frequency of the ten most common symptoms, divided into never, occasionally, frequently and consistent were recorded. Association between degree of symptoms with other factors, e.g. age, gender, profession, cigarette smoking, ethnicity, level of education and duration and wearing modality of CL wear were analyzed.Results: Out of 129 subjects participated in this study, 67% were female; the mean age of the subjects was 23.9 ± 4.3 years. Ninety seven percent of them had at least one symptom occasionally or frequently or consistently. Discomfort was found in 88.4% of the total subjects.Other common symptoms were foreign body sensation in 73.6%, redness in 65.9%, reduced wearing time in 63.6% and dryness in 62.8%. Symptoms were found occasionally in the majority of subjects. Degree of symptoms was not associated with age, gender, profession, education status, ethnicity of subjects and duration or modality of lens wear (p > 0.05) but was positively associated with passive cigarette smoking (p < 0.001).Conclusion: Almost all of the Nepalese soft CL wearers had some types of symptoms at least occasionally. Discomfort was the most common symptom. Degree of symptoms was associated with the passive smoking but not with other factors like age, sex, profession and duration of lens wear.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Saloplastic membranes as green devices for soft tissue regeneration

Implantable devices must exhibit mechanical properties similar to native tissues to promote appropriate cellular behavior and regeneration. Herein, we report a new membrane manufacture method based on the synthesis of polyelectrolyte complexes (PECs) that exhibit saloplasticity, i.e. variable physical-chemistry using salt as a plasticizer. This is a Green Chemistry approach, as PECs generate structures that are stabilized solely by reversible electrostatic interactions, avoiding the use of harmful crosslinkers completely. Furthermore, natural polyelectrolytes - chitosan and alginate - were used. Upon mixing them, membranes were obtained by drying the PECs at 37ºC, yielding compact PECs without resorting to organicsolvents. The plasticizing effect of salt after synthesis was shown by measuring tensile mechanical properties, which were lower when samples were immersed in high ionic strength solutions.Salt was also used during membrane synthesis in different quan- tities (0 M, 0.15 M and 0.5 M in NaCl) yielding structures with no significant differences in morphology and degradation (around 15% after 3 months in lysozyme). However, swelling was higher (about 10x) when synthesized in the presence of salt. In vitro cell studies using L929 fibroblasts showed that cells adhered and proliferated preferentially in membranes fabricated in the presence of salt (i.e. the membranes with lower tensile strength). Structures with physical-chemical properties controlled with precision open a path to tissue engineering strategies depending on fine tuning mechanical properties and cellular adhesion simply by changing ionic strength during membrane manufacture

Compact saloplastic membranes of natural polysaccharides for soft tissue engineering

The regeneration of soft biological tissues requires new substitutes that exhibit mechanical properties similar to the native tissue. Herein, thin saloplastic membranes with tunable physical properties are prepared by complexation of chitosan and alginate solutions containing different concentrations of sodium chloride. Polyelectrolyte complexes (PECs) are transferred to flat Petri dishes for compaction into membrane shapes by sedimentation and solvent evaporation. All membranes are resistant to degradation by lysozyme and are stable in solutions with pH values between 1 and 13. Immersing the different membranes in new doping solutions of increasing salt concentrations triggers the typical saloplastic behavior, with a high water absorption and decrease of the rigidity and ultimate tensile strength. The range of such variations is tuned by the sodium chloride amount used in the synthesis: high salt concentrations increase water uptake and tensile moduli, while decreasing the ultimate strength. Cellular assays demonstrate high proliferation rates and viability of L929 fibroblasts seeded onto the most rigid membranes. The results validate the use of saloplastic membranes as soft tissue substitutes for future biomedical applications.

Development of benchmarks for operating costs and resources consumption to be used in healthcare building sustainability assessment methods

Since the last decade of the twentieth century, the healthcare industry is paying attention to the environmental impact of their buildings and therefore new regulations, policy goals and Buildings Sustainability Assessment (HBSA) methods are being developed and implemented. At the present, healthcare is one of the most regulated industries and it is also one of the largest consumers of energy per net floor area. To assess the sustainability of healthcare buildings it is necessary to establish a set of benchmarks related with their life-cycle performance. They are both essential to rate the sustainability of a project and to support designers and other stakeholders in the process of designing and operating a sustainable building, by allowing the comparison to be made between a project and the conventional and best market practices. This research is focused on the methodology to set the benchmarks for resources consumption, waste production, operation costs and potential environmental impacts related to the operational phase of healthcare buildings. It aims at contributing to the reduction of the subjectivity found in the definition of the benchmarks used in Building Sustainability Assessment (BSA) methods, and it is applied in the Portuguese context. These benchmarks will be used in the development of a Portuguese HBSA method.

Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal

As a renewable energy source, the use of forest biomass for electricity generation is advantageous in comparison with fossil fuels, however the activity of forest biomass power plants causes adverse impacts, affecting particularly neighbouring communities. The main objective of this study is to estimate the effects of the activity of forest biomass power plants on the welfare of two groups of stakeholders, namely local residents and the general population and we apply two stated preference methods: contingent valuation and discrete choice experiments, respectively. The former method was applied to estimate the minimum compensation residents of neighbouring communities of two forest biomass power plants in Portugal would be willing to accept. The latter method was applied among the general population to estimate their willingness to pay to avoid specific environmental impacts. The results show that the presence of the selected facilities affects individuals’ well-being. On the other hand, in the discrete choice experiments conducted among the general population all impacts considered were significant determinants of respondents’ welfare levels. The results of this study stress the importance of performing an equity analysis of the welfare effects on different groups of stakeholders from the installation of forest biomass power plants, as their effects on welfare are location and impact specific. Policy makers should take into account the views of all stakeholders either directly or indirectly involved when deciding crucial issues regarding the sitting of new forest biomass power plants, in order to achieve an efficient and equitable outcome.

Decision methods applied to solve a safety problem on a waste treatment facility

To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

Qualitative risk assessment during polymer mortar test specimens preparation - methods comparison

Polymer binder modification with inorganic nanomaterials (NM) could be a potential and efficient solution to control matrix flammability of polymer concrete (PC) materials without sacrificing other important properties. Occupational exposures can occur all along the life cycle of a NM and “nanoproducts” from research through scale-up, product development, manufacturing, and end of life. The main objective of the present study is to analyse and compare different qualitative risk assessment methods during the production of polymer mortars (PM) with NM. The laboratory scale production process was divided in 3 main phases (pre-production, production and post-production), which allow testing the assessment methods in different situations. The risk assessment involved in the manufacturing process of PM was made by using the qualitative analyses based on: French Agency for Food, Environmental and Occupational Health & Safety method (ANSES); Control Banding Nanotool (CB Nanotool); Ecole Polytechnique Fédérale de Lausanne method (EPFL); Guidance working safely with nanomaterials and nanoproducts (GWSNN); Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro, Italy method (ISPESL); Precautionary Matrix for Synthetic Nanomaterials (PMSN); and Stoffenmanager Nano. It was verified that the different methods applied also produce different final results. In phases 1 and 3 the risk assessment tends to be classified as medium-high risk, while for phase 2 the more common result is medium level. It is necessary to improve the use of qualitative methods by defining narrow criteria for the methods selection for each assessed situation, bearing in mind that the uncertainties are also a relevant factor when dealing with the risk related to nanotechnologies field.

Evaluating ubiquitous computing environments using 3D simulation

Human activity is very dynamic and subtle, and most physical environments are also highly dynamic and support a vast range of social practices that do not map directly into any immediate ubiquitous computing functionally. Identifying what is valuable to people is very hard and obviously leads to great uncertainty regarding the type of support needed and the type of resources needed to create such support. We have addressed the issues of system development through the adoption of a Crowdsourced software development model [13]. We have designed and developed Anywhere places, an open and flexible system support infrastructure for Ubiquitous Computing that is based on a balanced combination between global services and applications and situated devices. Evaluation, however, is still an open problem. The characteristics of ubiquitous computing environments make their evaluation very complex: there are no globally accepted metrics and it is very difficult to evaluate large-scale and long-term environments in real contexts. In this paper, we describe a first proposal of an hybrid 3D simulated prototype of Anywhere places that combines simulated and real components to generate a mixed reality which can be used to assess the envisaged ubiquitous computing environments [17].

A trust model for cloud computing environment

This paper presents a proposal for a management model based on reliability requirements concerning Cloud Computing (CC). The proposal was based on a literature review focused on the problems, challenges and underway studies related to the safety and reliability of Information Systems (IS) in this technological environment. This literature review examined the existing obstacles and challenges from the point of view of respected authors on the subject. The main issues are addressed and structured as a model, called "Trust Model for Cloud Computing environment". This is a proactive proposal that purposes to organize and discuss management solutions for the CC environment, aiming improved reliability of the IS applications operation, for both providers and their customers. On the other hand and central to trust, one of the CC challenges is the development of models for mutual audit management agreements, so that a formal relationship can be established involving the relevant legal responsibilities. To establish and control the appropriate contractual requirements, it is necessary to adopt technologies that can collect the data needed to inform risk decisions, such as access usage, security controls, location and other references related to the use of the service. In this process, the cloud service providers and consumers themselves must have metrics and controls to support cloud-use management in compliance with the SLAs agreed between the parties. The organization of these studies and its dissemination in the market as a conceptual model that is able to establish parameters to regulate a reliable relation between provider and user of IT services in CC environment is an interesting instrument to guide providers, developers and users in order to provide services and secure and reliable applications.

HEP-Frame: A software engineered framework to aid the development and efficient multicore execution of scientific code

This work was supported by FCT (Fundação para a Ciência e Tecnologia) within Project Scope (UID/CEC/00319/2013), by LIP (Laboratório de Instrumentação e Física Experimental de Partículas) and by Project Search-ON2 (NORTE-07-0162- FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework, through the European Regional Development Fund.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.