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This paper defines a conversion factor included in the European technical specification for the design of fibre–polymer composite structures that considers the effects of moisture on the mechanical properties of fiber-reinforced polymer (FRP) composites exposed to natural weathering. The first part of the paper presents a field investigation about the durability of four pultruded glass fiber–reinforced polymer (GFRP) structures in service for 11–22 years in a Mediterranean climate. Their performance was evaluated by dynamic mechanical analysis and mechanical tests on small-scale coupons. The changes of thermophysical and mechanical properties showed low-to-moderate degradation. The second part of the paper presents the design-oriented methodology to define the moisture conversion factor. The results from the experimental study and those gathered from a literature data survey on the retention of mechanical properties of FRP materials after long-term exposure to natural weathering were analyzed. Based on these data and statistical considerations, a value of 0.85 was adopted for the natural weathering moisture conversion factor. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to the fuzzy newsvendor problem for inventory management applications. The main contributions of the paper are the following: a new credibility estimation is proposed, to explore the neighborhood around the most impactful demand scenarios; a simulation procedure was designed for the different demand scenarios, which allows comparison of the proposed approach with classical and fuzzy multi-item newsvendor problems; a modified genetic algorithm (GA) is introduced to ameliorate previous genetic algorithms in both the generation and evaluation of solutions. The new formulation of the fuzzy newsvendor problem, together with the modified GA, were shown to improve the average profit by up to 55% in problems with low-budget scenarios. [ABSTRACT FROM AUTHOR]

As it becomes increasingly necessary to reduce aviation-related emissions, condensation trails present an additional challenge. These are arguably responsible for the largest contribution to radiative forcing in the sector, but the phenomenon is still not as well understood as those involving other agents. The present study employs a large eddy simulation (LES) parametrization to validate a previously developed contrail model in order to assess the feasibility of a multi-model approach to increase confidence in simulations of contrail cirrus formation. Subsequently, the computational model was used to analyze the impact of e-fuels in contrail dynamics, resulting in reductions of over 7% and 14%, respectively, in average contrail lifetime and optical depth, with such improvements increasing if higher blending limits are utilized. This confirmed the potential for e-fuels as the most viable option for near-future large-scale implementations among all sustainable aviation fuel alternatives. [ABSTRACT FROM AUTHOR]

Robotic systems are increasingly present in dynamic environments. This paper proposes a hierarchical control structure wherein a behavior tree (BT) is used to improve the flexibility and adaptability of an omni-directional mobile robot for point stabilization. Flexibility and adaptability are crucial at each level of the sense–plan–act loop to implement robust and effective robotic solutions in dynamic environments. The proposed BT combines high-level decision making and continuous execution monitoring while applying non-linear model predictive control (NMPC) for the point stabilization of an omni-directional mobile robot. The proposed control architecture can guide the mobile robot to any configuration within the workspace while satisfying state constraints (e.g., obstacle avoidance) and input constraints (e.g., motor limits). The effectiveness of the controller was validated through a set of realistic simulation scenarios and experiments in a real environment, where an industrial omni-directional mobile robot performed a point stabilization task with obstacle avoidance in a workspace. [ABSTRACT FROM AUTHOR]

In order to achieve a more efficient allocation of healthcare resources in the near future, it is crucial to understand the patterns and causes of excess mortality and hospitalizations. Neonatal mortality still poses a significant challenge, particularly in developed nations where the mortality rates are already low and healthcare resources are generally available to most of the population. Furthermore, the low mortality rates mean that the data available for modeling are often very limited, restricting the modeling methods that can be used. It is also important that the chosen methods allow for explainable, non-black-box models that can be interpreted by healthcare professionals. Considering these challenges, the work hereby presented thoroughly analyzed the time series of the neonatal mortality rates in Portugal between 2014 and 2019 in terms of trend and seasonal patterns. The applicability and performance of different data-based methods were also analyzed. Furthermore, the mortality rates were studied in terms of their relation to environmental variables, such as temperature and air pollution indicators, with the goal of establishing causal relations between such variables and excess mortality. The preliminary results show that ARMA, neural and fuzzzy models are able to forecast the studied mortality rates with good performance. In particular, neural models have the best predictive performance, while fuzzy models are well suited to obtain interpretable models with acceptable performance. [ABSTRACT FROM AUTHOR]

Airborne wind energy (AWE) has received increasing attention during the last decade, with the goal of achieving electricity generation solutions that may be used as a complement or even an alternative to conventional wind turbines. Despite that several concepts have already been proposed and investigated by several companies and research institutions, no mature technology exists as yet. The mode of energy generation, the type of wing, the take-off and landing approaches, and the control mechanisms, to name a few, may vary among AWE crosswind systems. Given the diversity of possibilities, it is necessary to determine the most relevant factors that drive AWE exploration. This paper presents a review on the characteristics of currently existing AWE technological solutions, focusing on the hardware architecture of crosswind systems, with the purpose of providing the information required to identify and assess key factors to be considered in the choice of such systems. The identified factors are categorized into four distinct classes: technical design factors (aerodynamic performance, mass-to-area ratio, durability, survivability); operational factors (continuity of power production, controllability, take-off and landing feasibility); fabrication and logistical factors (manufacturability, logistics); and social acceptability factors (visual impact, noise impact, ecological impact, safety). [ABSTRACT FROM AUTHOR]

As the push for carbon-neutral transport continues, the aviation sector is facing increasing pressure to reduce its carbon footprint. Furthermore, commercial air traffic is expected to resume the continuous growth experienced until the pandemic, highlighting the need for reduced emissions. The use of alternative fuels plays a key role in achieving future emission goals, while also lowering the dependency on fossil fuels. The so-called sustainable aviation fuels (SAF), which encompass bio and synthetic fuels, are currently the most viable option, but hydrogen is also being considered as a long-term solution. The present paper reviews the production methods, logistical and technological barriers, and potential for future mass implementation of these alternative fuels. In general, biofuels currently present higher technological readiness levels than other alternatives. Sustainable mass production faces critical feedstock-related challenges that synthetic fuels, together with other solutions, can overcome. All conventional fuel replacements, though with different scopes, will be important in meeting long-term goals. Government support will play an important role in accelerating and facilitating the transition towards sustainable aviation. [ABSTRACT FROM AUTHOR]

In the last few decades, there has been a growing necessity for systems that handle market changes and personalized customer needs with near mass production efficiency, defined as the new mass customization paradigm. The Industry 5.0 vision further enhances the human-centricity aspect, in the necessity for manufacturing systems to cooperate with workers, taking advantage of their problem-solving capabilities, creativity, and expertise of the manufacturing process. A solution is to develop a flexible manufacturing system capable of handling different customer requests and real-time decisions from operators. This paper tackles these aspects by proposing a digital twin of a robotic system for solution preparation capable of making real-time scheduling decisions and forecasts using a simulation model while allowing human interventions. A discrete event simulation model was used to forecast possible system improvements. The simulation handles real-time scheduling considering the possibility of adding identical parallel machines. Results show that processing multiple jobs simultaneously with more than one machine on critical processes, increasing the robot speed, and using heuristics that emphasize the shortest transportation time can reduce the overall completion time by 82%. The simulation model has an animated visualization window for a deeper understanding of the system. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study about the effects of hygrothermal and outdoor ageing on a polyurethane (PUR) adhesive used in civil engineering applications. Small-scale adhesive coupons were exposed to different types of ageing environments for up to two years: (i) immersion in demineralised water at 20 and 40 °C, (ii) immersion in salt water at 20 and 40 °C, (iii) continuous condensation environment at 40 °C, and (iv) outdoor ageing in Lisbon, Portugal. At predetermined times, after a desorption period until constant mass, the effects of such exposure on the physical and mechanical responses of the PUR adhesive was investigated using the following techniques: (i) water sorption, (ii) dynamic mechanical analyses (DMA); (iii) flexural; and (iv) in-plane shear tests. The diffusion mechanisms observed were not purely Fickian; a long relaxation period was noticed, with water molecules being continuously incorporated in the adhesive until the end of the experiments; two alternative analytical modelling approaches were successfully used to simulate the diffusion processes. After immersion in water and salt water for two years, the viscoelastic behaviour of the adhesive showed signs of post-curing phenomena, and some of the physical degradation was found to be reversible due to drying, although it was not explicitly quantified; accordingly, the T g showed increasing trends (11-14%). The mechanical properties of the adhesive showed signs of irreversible degradation mechanisms, more relevant on the in-plane shear properties, with reductions up to 26% in strength and 44% in modulus under the harsher conditions. Flexural properties also exhibited irreversible degradation, with maximum reductions up to 30% in strength and 36% in modulus. Increased temperature did not have a significant effect in the flexural and shear strength, but caused higher degradation in the corresponding moduli. The degradation caused by salt water immersion and continuous condensation was comparable to that in demineralized water immersion (at the same temperature). [ABSTRACT FROM AUTHOR]

The growing environmental concerns and liberalization of energy markets have resulted in an increased competition between utilities and a strong focus on efficiency. To develop new energy efficiency measures and optimize operations, utilities seek new market-related insights and customer engagement strategies. This paper proposes a clustering-based methodology to define the segmentation of residential gas consumers. The segments of gas consumers are obtained through a detailed clustering analysis using smart metering data. Insights are derived from the segmentation, where the segments result from the clustering process and are characterized based on the consumption profiles, as well as according to information regarding consumers' socio-economic and household key features. The study is based on a sample of approximately one thousand households over one year. The representative load profiles of consumers are essentially characterized by two evident consumption peaks, one in the morning and the other in the evening, and an off-peak consumption. Significant insights can be derived from this methodology regarding typical consumption curves of the different segments of consumers in the population. This knowledge can assist energy utilities and policy makers in the development of consumer engagement strategies, demand forecasting tools and in the design of more sophisticated tariff systems. [ABSTRACT FROM AUTHOR]

Left ventricular ejection fraction (LVEF) constitutes an important physiological parameter for the assessment of cardiac function, particularly in the settings of coronary artery disease and heart failure. This study explores the use of routinely and easily acquired variables in the intensive care unit (ICU) to predict severely depressed LVEF following ICU admission. A retrospective study was conducted. We extracted clinical physiological variables derived from ICU monitoring and available within the MIMIC II database and developed a fuzzy model using sequential feature selection and compared it with the conventional logistic regression (LR) model. Maximum predictive performance was observed using easily acquired ICU variables within 6 hours after admission and satisfactory predictive performance was achieved using variables acquired as early as one hour after admission. The fuzzy model is able to predict LVEF ≤ 25% with an AUC of 0.71 ± 0.07, outperforming the LR model, with an AUC of 0.67 ± 0.07. To the best of the authors’ knowledge, this is the first study predicting severely impaired LVEF using multivariate analysis of routinely collected data in the ICU. We recommend inclusion of these findings into triaged management plans that balance urgency with resources and clinical status, particularly for reducing the time of echocardiographic examination. [ABSTRACT FROM AUTHOR]

The article discusses a study that determined the thoracic and heart biometrics of non-anesthetized agouti raised in captivity using radiography. Thirty adult agoutis were physically restrained before radiographies in laterolateral and ventrodorsal recumbence were produced. The researchers found that the radiographic technique without chemical restraint was well-tolerated. They concluded that the values of the variances found for the ratios measured can be used to predict normal heart measurements in agoutis.

Bayesian networks (BNs) are knowledge representation tools capable of representing dependence or independence relationships among random variables. Learning the structure of BNs from datasets has received increasing attention in the last two decades, due to the BNs' capacity of providing good inference models and discovering the structure of complex domains. One approach for BNs' structure learning from data is to define a scoring metric that evaluates the quality of the candidate networks, given a dataset, and then apply an optimization procedure to explore the set of candidate networks. Among the most frequently used optimization methods for BN scorebased learning is greedy hill climbing (GHC) search. This paper proposes a new local discovery ant colony optimization (ACO) algorithm and a hybrid algorithm max-min ant colony optimization (MMACO), based on the local discovery algorithm max-min parents and children (MMPC) and ACO to learn the structure of a BN. In MMACO, MMPC is used to construct the skeleton of the BN and ACO is used to orientate the skeleton edges, thus returning the final structure. The algorithms are applied to several sets of benchmark networks and are shown to outperform the GHC and simulated annealing algorithms. [ABSTRACT FROM AUTHOR]

Abstract-This paper proposes a fuzzy classification system to perform word indexing in ancient printed documents. The indexing system receives a given word selected by an user. The word is preprocessed using an aspect ratio filter, assuring that only interesting word candidates are considered. The image is classified by oriented feature extraction using Gabor filter banks. The oriented features are used to generate membership functions that characterize the selected word. This target word image is then compared to the potential matches, using a similarity matrix. The indexing system is flexible and lightweight when compared to other optimal recognizers, which allows its use in "real-time" applications. A significant test revealed that the indexer achieved very good results in terms of precision and recall in texts from XVIIth century. [ABSTRACT FROM AUTHOR]

Condensation trails and contrail cirrus are currently responsible for the largest contribution to radiative forcing in the aviation sector, yet they have lifetimes of only a few hours. Their much shorter lifetimes when compared to long-lived greenhouse gases makes them ideal for the implementation of short-term mitigation measures. The use of Sustainable Aviation Fuel (SAF) instead of regular jet fuel has been associated to a reduction in soot particle emissions, leading to a decrease in initial ice crystal numbers in contrails, but also to a possible increase in contrail frequency and contrail ice mass due to higher water vapor emissions. A computational model was used to explore the influence of the variations of soot and water vapor emissions when using SAF and SAF blends in the formation of contrails, their ensuing optical depth, and their lifespan. An increase in frequency of contrails was found in cases where regular jet fuel emissions were close to threshold conditions. Reductions in contrail lifetime of up to 76% were found for contrails with lifetimes of over 30 min, while decreases in optical depth of up to 37% were found for contrails formed in air with a relative humidity of 42% or above. This work provides a better understanding of the potential of SAF as a mitigation measure against the impact of contrails on global warming. [ABSTRACT FROM AUTHOR]

Extensive digitization and interconnection through networks have ushered in a number of new paradigms over the last years: Internet of Things, cyber–physical systems, Industry 4.0, etc. These challenging systems rely on an effective information communication between distributed components. Therefore, the heterogeneity of entities, both hardware and software, must be handled to achieve an operative interoperability and a proper behavior. However, there is also a heterogeneous availability of solutions; different technologies, protocols, and architectures aim to achieve a seamless interconnection. Henceforth, the standardization still requires great efforts from industrial and scientific environments. In this sense, the interface of the open platform communications (OPC) has supported connectivity for automation and supervision infrastructures for more than two decades. The OPC comprises the so-called classic OPC, the original protocol, as well as the last specification, unified architecture (UA). The widespread utilization of the classic OPC together with the powerful functionalities of OPC UA, make the latter one of the main candidates to lead the standardization and systems integration. This paper presents a survey of recent OPC-based systems reported in scientific literature for different domains as well as research projects. The goal of this paper is to provide a broad perspective about the OPC' applicability and capabilities in order to support the decision about communication interfaces. The results are analyzed and discussed putting special attention on the aforementioned new paradigms. Finally, the main conclusions and open research directions are highlighted. [ABSTRACT FROM AUTHOR]

Background: MRI does not offer a direct method to obtain attenuation correction maps as its predecessors (stand-alone PET and PET/CT), and bone visualisation is particularly challenging. Recently, zero-echo-time (ZTE) was suggested for MR-based attenuation correction (AC). The aim of this work was to evaluate ZTE- and atlas-AC by comparison to 68Ge-transmission scan-based AC.Nine patients underwent brain PET/MR and stand-alone PET scanning using the dopamine transporter ligand 11C-PE2I. For each of them, two AC maps were obtained from the MR images: an atlas-based, obtained from T1-weighted LAVA-FLEX imaging with cortical bone inserted using a CT-based atlas, and an AC map generated from proton-density-weighted ZTE images. Stand-alone PET 68Ge-transmission AC map was used as gold standard. PET images were reconstructed using the three AC methods and standardised uptake value (SUV) values for the striatal, limbic and cortical regions, as well as the cerebellum (VOIs) were compared. SUV ratio (SUVR) values normalised for the cerebellum were also assessed. Bias, precision and agreement were calculated; statistical significance was evaluated using Wilcoxon matched-pairs signed-rank test.Results: Both ZTE- and atlas-AC showed a similar bias of 6-8% in SUV values across the regions. Correlation coefficients with 68Ge-AC were consistently high for ZTE-AC (r 0.99 for all regions), whereas they were lower for atlas-AC, varying from 0.99 in the striatum to 0.88 in the posterior cortical regions. SUVR showed an overall bias of 2.9 and 0.5% for atlas-AC and ZTE-AC, respectively. Correlations with 68Ge-AC were higher for ZTE-AC, varying from 0.99 in the striatum to 0.96 in the limbic regions, compared to atlas-AC (0.99 striatum to 0.77 posterior cortex).Conclusions: Absolute SUV values showed less variability for ZTE-AC than for atlas-AC when compared to 68Ge-AC, but bias was similar for both methods. This bias is largely caused by higher linear attenuation coefficients in atlas- and ZTE-AC image compared to 68Ge-images. For SUVR, bias was lower when using ZTE-AC than for atlas-AC. ZTE-AC shows to be a more robust technique than atlas-AC in terms of both intra- and inter-patient variability. [ABSTRACT FROM AUTHOR]

Anthropogenic activities in tropical rivers favor the eutrophication process, which causes increased concentration of heavy metals. The presence and bioaccumulation of metals are directly related to the presence of genotoxic damage in aquatic organisms. Thus, we evaluated the presence of heavy metals (Fe, Zn, Cr, Cu and Al) and performed toxicogenetic tests in surface (S) and bottom (B) of water samples of the Poti river (Piaui/Brazil). Cytotoxicity and genotoxicity tests were performed in Allium cepa , and micronucleus (MN) and comet assay were performed in Oreochromis niloticus. The chemical analysis showed concentrations above the limit for Cu, Cr, Fe and Al according to Brazilian laws, characterizing anthropogenic disturbance in this aquatic environment. Toxicogenetic analysis presented significant cytotoxic, mutagenic and genotoxic effects in different exposure times and water layers (S and B), especially alterations in mitotic spindle defects, MN formations, nuclear bud and DNA strand breaks. Correlations between Fe and cytotoxicity, and Al and mutagenicity were statistically significant and point out to the participation of heavy metals in genotoxic damage. Therefore, Poti river water samples presented toxicogenetic effects on all bioindicators analyzed, which are most likely related to heavy metals pollution. [ABSTRACT FROM AUTHOR]

The use of ultrasound for pregnancy monitoring is critical for the evaluation of hemodynamic parameters essential to fetal viability. In the present study, using B-mode and Doppler ultrasound, we characterized the placenta, subplacenta, maternal, and fetal vessels during normal gestation of healthy agoutis raised in captivity. In total, 30 agoutis were obtained from the Center for the Study and Preservation of Wild Animals, Center of Agricultural Sciences, Federal University of Piauí (Núcleo de Estudos e Preservação de Animais Silvestres—NEPAS, Centro de Ciências Agrárias—CCA, Universidade Federal do Piauí—UFPI). These animals were subjected to B-mode and Doppler ultrasound examinations to evaluate their maternal and fetal hemodynamic profiles. The placenta was located in the mesometrial region and had a discoid, ellipsoid, or globular aspect. With spectral Doppler, characteristic systolic and diastolic flow was observed in the umbilical artery. This flow increased during pregnancy. A cross-sectional view revealed a goblet-shaped placenta. The uteroplacental blood flow was characterized by a marked increase in systolic peak velocity during pregnancy, the presence of a rapid deceleration ramp, and a relatively high diastolic speed. The fetal aortic vascular flow was predominantly systolic and diastolic. The caudal vena cava blood flow was characterized by a systolic peak followed by a decreased diastolic wave throughout pregnancy. In the present study, we characterized the morphologic and hemodynamic interactions of the placenta/subplacenta with maternal and fetal vessels in agoutis at 30, 45, 60, 75, and 90 days gestation using B-mode and Doppler ultrasound. We determined the approximation and separation of the blood flow values of the umbilical artery, subplacental flow, uteroplacental artery, fetal aorta, and fetal vena cava. We believe these values may contribute to an understanding of the gestational biology and aid delivery prediction in this species. [ABSTRACT FROM AUTHOR]

Citrinin (CIT) is a polyketide-derived mycotoxin, which is produced by many fungal strains belonging to the gerena Monascus, Aspergillus, and Penicillium. It has been postulated that mycotoxins have several toxic mechanisms and are potentially used as antineoplastic agents. Therefore, the present study carried out a systematic review, including articles from 1978 to 2022, by collecting evidence in experimental studies of CIT antiplorifactive activity in cancer. The Data indicate that CIT intervenes in important mediators and cell signaling pathways, including MAPKs, ERK1/2, JNK, Bcl-2, BAX, caspases 3,6,7 and 9, p53, p21, PARP cleavage, MDA, reactive oxygen species (ROS) and antioxidant defenses (SOD, CAT, GST and GPX). These factors demonstrate the potential antitumor drug CIT in inducing cell death, reducing DNA repair capacity and inducing cytotoxic and genotoxic effects in cancer cells., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Human exposure to the natural environmental contaminant methylmercury (MeHg) has been associated to adverse health effects. Importantly, the mechanisms by which this organomercurial exerts its neurotoxicity have yet to be fully clarified. Therefore, the aim of this study was to evaluate whether exposure to MeHg alters dopamine (DA) and octopamine (OA) levels, acetylcholinesterase (AChE) activity and impacts both motor and non-motor behaviours. We studied the effect of MeHg by feeding 1-2 d old flies (male and females) with 25 and 50 μM MeHg for 4 d and determined effects on survival, motor and non-motor behaviours, oxidative stress, AChE and tyrosine hydroxylase (TH) activities, as well as DA and OA levels. We found that Drosophila melanogaster (D. melanogaster) exposed to MeHg showed a reduction in survival rate, associated with the inhibition of AChE and TH activities in head of flies and decreased DA and OA levels. These changes were accompanied by behavioural alterations, such as locomotor deficit and increased grooming behaviour, in addition to an increase in oxidative stress markers both in head and in body of flies, and an increase in glutathione-S-transferase (GST) activity in head of flies. Collectively, our data support the hypothesis that MeHg neurotoxicity is associated with altered OA and DA levels, AChE inhibition, which may serve, at least in part, as the underpinnings of both motor and non-motor behavioural changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Centilla asiatica L is a medicinal herb that has been widely used in folk medicine to treat various diseases. Asiatic Acid (AA), a triterpene and a known component of this herb, has been shown to display important biological activities, including anti-inflammatory, antibacterial, antidiabetic and antihyperlipidemic, neuroprotective, anxiolytic and antidepressant, hepatoprotective, pancreas protective, and cardio- protective., Objective: This review focuses on AA's anti-cancer effects on the basis of published literature found in a number of databases such as PubMed and Science Direct. Emphasis has been given to the mechanisms of action of its anti-cancer effect., Methods: A literature survey was conducted using known databases such as PubMed and Science Direct using the keywords 'Asiatic acid', pairing with 'cancer', 'tumor', 'anti-cancer effect', 'cytotoxic effect', 'anti-tumor activity', 'cell line', 'animal cancer', and 'human cancer'., Results: Findings suggest that AA exerts anti-cancer effects in several test systems through various pathways, including oxidative/antioxidant, anti-inflammatory, cytotoxicity, apoptotic cell death, necrosis, anti-angiogenesis, inhibition of proliferation and cell migration, and chemoprevention., Conclusion: AA may be an effective plant-based cancer chemotherapeutic agent and a promising lead for the development of potent anticancer drugs., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Motivation: Emergency Departments' (ED) modern triage systems implemented worldwide are solely based upon medical knowledge and experience. This is a limitation of these systems, since there might be hidden patterns that can be explored in big volumes of clinical historical data. Intelligent techniques can be applied to these data to develop clinical decision support systems (CDSS) thereby providing the health professionals with objective criteria. Therefore, it is of foremost importance to identify what has been hampering the application of such systems for ED triage., Objectives: The objective of this paper is to assess how intelligent CDSS for triage have been contributing to the improvement of quality of care in the ED as well as to identify the challenges they have been facing regarding implementation., Methods: We applied a standard scoping review method with the manual search of 6 digital libraries, namely: ScienceDirect, IEEE Xplore, Google Scholar, Springer, MedlinePlus and Web of Knowledge. Search queries were created and customized for each digital library in order to acquire the information. The core search consisted of searching in the papers' title, abstract and key words for the topics "triage", "emergency department"/"emergency room" and concepts within the field of intelligent systems., Results: From the review search, we found that logistic regression was the most frequently used technique for model design and the area under the receiver operating curve (AUC) the most frequently used performance measure. Beside triage priority, the most frequently used variables for modelling were patients' age, gender, vital signs and chief complaints. The main contributions of the selected papers consisted in the improvement of a patient's prioritization, prediction of need for critical care, hospital or Intensive Care Unit (ICU) admission, ED Length of Stay (LOS) and mortality from information available at the triage., Conclusions: In the papers where CDSS were validated in the ED, the authors found that there was an improvement in the health professionals' decision-making thereby leading to better clinical management and patients' outcomes. However, we found that more than half of the studies lacked this implementation phase. We concluded that for these studies, it is necessary to validate the CDSS and to define key performance measures in order to demonstrate the extent to which incorporation of CDSS at triage can actually improve care., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The aim of this work was to develop computational intelligence models based on neural networks (NN), fuzzy models (FM), and support vector machines (SVM) to predict physicochemical composition of bee pollen mixture given their botanical origin. To obtain the predominant plant genus of pollen (was the output variable), based on physicochemical composition (were the input variables of the predictive model), prediction models were learned from data. For the inverse case study, input/output variables were swapped. The probabilistic NN prediction model obtained 98.4% of correct classification of the predominant plant genus of pollen. To obtain the secondary and tertiary plant genus of pollen, the results present a lower accuracy. To predict the physicochemical characteristic of a mixture of bee pollen, given their botanical origin, fuzzy models proven the best results with small prediction errors, and variability lower than 10%., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Phytol have various pharmacological activities such as antimicrobial, cytotoxic, antitumoral, antimutagenic, anti-atherogenic, antidiabetic, lipid-lowering, antispasmodic, antiepileptic, antinociceptive, antioxidant, anti-inflammatory, anxiolytic, antidepressant and immunoadjuvant. Several studies point to an association of phytol with implications for apoptosis and necrosis at cellular levels in cancer, yet no clear conclusions were drawn., Method: To clarify this, we conducted a meta-analysis of non-clinical studies of phytol and its associations with toxicity and cytotoxicity emphasizing the mechanisms of apoptosis and necrosis induction and its importance in tumor therapy. Relevant studies were systematically searched in PubMed and Web of Science. The association between phytol and cyto-/toxicity was assessed by odds ratio (ORs) and 95% confidence intervals (CI). Twentythree studies were finally included in the meta-analysis. A significant association between phytol and toxicity (OR: 1.47; 95% CI = 0.86-2.48) was found among in vivo studies and cytotoxicity (OR: 1.81; 95% CI = 1.12- 2.65, p<0.05) in in vitro and ex vivo studies. In in vitro studies, 24% of them indicate that phytol at high doses induces apoptosis by several mechanisms; while about 40% of ex vivo studies indicate that phytol induces reactive oxygen species generation. But, Phytol does not act as a direct oxidant, unlike its metabolite phytanic acid. The 24% of in vivo studies also highlighted the mechanisms for apoptosis-like including expression of Bcl2 protein or mutations in pro-apoptotic protein Bax. Of them, 8% studies show necrosis and hepatotoxicity. However, in 24% of the articles, the mechanisms of toxicity and cytotoxicity are still not well elucidated., Conclusion: This study confirms that the association between phytol and cyto-/toxicity depends on the dose/concentration used in the given experimental conditions. Thus, there are still great prospects for new research aimed at the use of phytol and its metabolite as anticancer agents., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Left ventricular ejection fraction (LVEF) constitutes an important physiological parameter for the assessment of cardiac function, particularly in the settings of coronary artery disease and heart failure. This study explores the use of routinely and easily acquired variables in the intensive care unit (ICU) to predict severely depressed LVEF following ICU admission. A retrospective study was conducted. We extracted clinical physiological variables derived from ICU monitoring and available within the MIMIC II database and developed a fuzzy model using sequential feature selection and compared it with the conventional logistic regression (LR) model. Maximum predictive performance was observed using easily acquired ICU variables within 6 hours after admission and satisfactory predictive performance was achieved using variables acquired as early as one hour after admission. The fuzzy model is able to predict LVEF ≤ 25% with an AUC of 0.71 ± 0.07, outperforming the LR model, with an AUC of 0.67 ± 0.07. To the best of the authors' knowledge, this is the first study predicting severely impaired LVEF using multivariate analysis of routinely collected data in the ICU. We recommend inclusion of these findings into triaged management plans that balance urgency with resources and clinical status, particularly for reducing the time of echocardiographic examination.