Search results for: blue color detection

Authors: Jyun-Guo You, Wei-Lung Tseng

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Herein, this study represents a synthetic route for producing highly luminescent AuNCs based on the integration of two concepts, including thiol-induced luminescence enhancement of ligand-insufficient GSH-AuNCs and Ce3+-induced aggregation of GSH-AuNCs. The synthesis of GSH-AuNCs was conducted by modifying the previously reported procedure. To produce more Au(I)-GSH complexes on the surface of ligand-insufficient GSH-AuNCs, the extra GSH is added to attach onto the AuNC surface. The formed ligand-sufficient GSH-AuNCs (LS-GSH-AuNCs) emit relatively strong luminescence. The luminescence of LS-GSH-AuNCs is further enhanced by the coordination of two carboxylic groups (pKa1 = 2 and pKa2 = 3.5) of GSH and lanthanide ions, which induce the self-assembly of LS-GSH-AuNCs. As a result, the quantum yield of the self-assembled LS-GSH-AuNCs (SA-AuNCs) was improved to be 13%. Interestingly, the SA-AuNCs were dissembled into LS-GSH-AuNCs in the presence of adenosine triphosphate (ATP) because of the formation of the ATP- lanthanide ion complexes. Our assay was employed to detect alkaline phosphatase (ALP) activity over the range of 0.1−10 U/mL with a limit of detection (LOD) of 0.03 U/mL.

Keywords: self-assembly, lanthanide ion, adenosine triphosphate, alkaline phosphatase

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

Procedia PDF Downloads 83

Authors: Pelin Yılmaz Çetiner, Metin Mert İlgün, Nazlı Çetindağ, Emine Birci, Gizemnur Yıldız Uysal, Özcan Hatipoğlu, Ehsan Tuzcuoğlu, Gökhan Sır

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Water scarcity is an inevitable problem affecting more and more people day by day. It is a worldwide crisis and a consequence of rapid population growth, urbanization and overexploitation. Thus, the solutions providing the reclamation of the wastewater are the desired approach. Wastewater contains various substances such as organic, soaps and detergents, solvents, biological substances, and inorganic substances. The physical properties of the wastewater differs regarding to its origin such as commerical, domestic or hospital usage. Thus, the treatment strategy of this type of wastewater is should be comprehensively investigated and properly treated. The advanced oxidation process comes up as a hopeful method associated with the formation of reactive hydroxyl radicals that are highly reactive to oxidize of organic pollutants. This process has a priority on other methods such as coagulation, flocuation, sedimentation and filtration since it was not cause any undesirable by-products. In the present study, it was aimed to investigate the applicability of advanced oxidation process for the treatment of household appliances wastewater. For this purpose, the laboratory studies providing the effectively addressing of the formed radicals to organic pollutants were carried out. Then the effect of process parameters were comprehensively studied by using response surface methodology, Box-Benhken experimental desing. The final chemical oxygen demand (COD) was the main output to evaluate the optimum point providing the expected COD removal. The linear alkyl benzene sulfonate (LAS), total dissolved solids (TDS) and color were measured for the optimum point providing the expected COD removal. Finally, present study pointed out that advanced oxidation process might be efficiently preffered to treat of the household appliances wastewater and the optimum process parameters provided that expected removal of COD.

Keywords: advanced oxidation process, household appliances wastewater, modelling, water reuse

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Authors: L. Bernabeo, T. Loftus

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Many children often experience phases of picky eating, food aversions and/or avoidance. For families with children who have special needs, these experiences are often exacerbated, which can lead to feelings that negatively impact a caregiver’s relationship with their child. Within the scope of speech language pathology practice, knowledge of both emotional and feeding development is key. This paper will explore the significance of “messy play” within typical feeding development, and the challenges that may arise if a child does not have the opportunity to engage in this type of exploratory play. This paper will consider several contributing factors that can result in a “picky eater.” Further, research has shown that individuals with special needs, including autism, possess a neurological makeup that differs from that of a typical individual. Because autism is a disorder of relating and communicating due to differences in the limbic system, an individual with special needs may respond to a typical feeding experience as if it is a traumatic event. As a result, broadening one’s dietary repertoire may seem to be an insurmountable challenge. This paper suggests that introducing new foods through exploratory play can help broaden and strengthen diets, as well as improve the feeding experience, of individuals with autism. The DIRFloortimeⓇ methodology stresses the importance of following a child's lead. Within this developmental model, there is a special focus on a person’s individual differences, including the unique way they process the world around them, as well as the significance of therapy occurring within the context of a strong and motivating relationship. Using this child-centered approach, we can support our children in expanding their diets, while simultaneously building upon their cognitive and creative development through playful and respectful interactions that include exposure to foods that differ in color, texture, and smell. Further, this paper explores the importance of exploration, self-feeding and messy play on brain development, both in the context of typically developing individuals and those with disordered development.

Keywords: development, feeding, floortime, sensory

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Authors: J. Yang, M. Monnot, T. Eljaddi, L. Simonian, L. Ercolei, P. Moulin

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The application of membrane technology to wastewater treatment has expanded rapidly under increasing stringent legislation and environmental protection requirements. At the same time, the water resource is becoming precious, and water reuse has gained popularity. Particularly, ultrafiltration (UF) is a very promising technology for water reuse as it can retain organic matters, suspended solids, colloids, and microorganisms. Nevertheless, few studies dealing with operating optimization of UF as a tertiary treatment for water reuse on a semi-industrial scale appear in the literature. Therefore, this study aims to explore the permeate water quality and to optimize operating parameters (maximizing productivity and minimizing irreversible fouling) through the operation of a UF pilot plant under real conditions. The fully automatic semi-industrial UF pilot plant with periodic classic backwashes (CB) and air backwashes (AB) was set up to filtrate the secondary effluent of an urban wastewater treatment plant (WWTP) in France. In this plant, the secondary treatment consists of a conventional activated sludge process followed by a sedimentation tank. The UF process was thus defined as a tertiary treatment and was operated under constant flux. It is important to note that a combination of CB and chlorinated AB was used for better fouling management. The 200 kDa hollow fiber membrane was used in the UF module, with an initial permeability (for WWTP outlet water) of 600 L·m-2·h⁻¹·bar⁻¹ and a total filtration surface of 9 m². Fifteen filtration conditions with different fluxes, filtration times, and air backwash frequencies were operated for more than 40 hours of each to observe their hydraulic filtration performances. Through comparison, the best sustainable condition was flux at 60 L·h⁻¹·m⁻², filtration time at 60 min, and backwash frequency of 1 AB every 3 CBs. The optimized condition stands out from the others with > 92% water recovery rates, better irreversible fouling control, stable permeability variation, efficient backwash reversibility (80% for CB and 150% for AB), and no chemical washing occurrence in 40h’s filtration. For all tested conditions, the permeate water quality met the water reuse guidelines of the World Health Organization (WHO), French standards, and the regulation of the European Parliament adopted in May 2020, setting minimum requirements for water reuse in agriculture. In permeate: the total suspended solids, biochemical oxygen demand, and turbidity were decreased to < 2 mg·L-1, ≤ 10 mg·L⁻¹, < 0.5 NTU respectively; the Escherichia coli and Enterococci were > 5 log removal reduction, the other required microorganisms’ analysis were below the detection limits. Additionally, because of the COVID-19 pandemic, coronavirus SARS-CoV-2 was measured in raw wastewater of WWTP, UF feed, and UF permeate in November 2020. As a result, the raw wastewater was tested positive above the detection limit but below the quantification limit. Interestingly, the UF feed and UF permeate were tested negative to SARS-CoV-2 by these PCR assays. In summary, this work confirms the great interest in UF as intensified tertiary treatment for water reuse and gives operational indications for future industrial-scale production of reclaimed water.

Keywords: semi-industrial UF pilot plant, water reuse, fouling management, coronavirus

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Authors: O. Ikpotokin

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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics

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Authors: Elisa K. Schoenell, Cristiano De Oliveira, Luiz R. H. Dos Santos, Alexandre Giacobbo, Andréa M. Bernardes, Marco A. S. Rodrigues

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Water is an indispensable natural resource, which must be preserved to human activities as well the ecosystems. However, the sewage discharge has been contaminating water resources. Conventional treatment, such as physicochemical treatment followed by biological processes, has not been efficient to the complete degradation of persistent organic compounds, such as medicines and hormones. Therefore, the use of advanced technologies to sewage treatment has become urgent and necessary. The aim of this study was to apply Reverse Osmosis (RO) on sewage tertiary treatment from a Waste Water Treatment Plant (WWTP) in south Brazil. It was collected 200 L of sewage pre-treated by wetland with aquatic macrophytes. The sewage was treated in a RO pilot plant, using a polyamide membrane BW30-4040 model (DOW FILMTEC), with 7.2 m² membrane area. In order to avoid damage to the equipment, this system contains a pleated polyester filter with 5 µm pore size. It was applied 8 bar until achieve 5 times of concentration, obtaining 80% of recovery of permeate, with 10 L.min-1 of concentrate flow rate. Samples of sewage pre-treated on WWTP, permeate and concentrate generated on RO was analyzed for physicochemical parameters and by gas chromatography (GC) to qualitative analysis of organic compounds. The results proved that the sewage treated on WWTP does not comply with the limit of phosphorus and nitrogen of Brazilian legislation. Besides this, it was found many organic compounds in this sewage, such as benzene, which is carcinogenic. Analyzing permeate results, it was verified that the RO as sewage tertiary treatment was efficient to remove of physicochemical parameters, achieving 100% of iron, copper, zinc and phosphorus removal, 98% of color removal, 91% of BOD and 62% of ammoniacal nitrogen. RO was capable of removing organic compounds, however, it was verified the presence of some organic compounds on de RO permeate, showing that RO did not have the capacity of removal all organic compounds of sewage. It has to be considered that permeate showed lower intensity of peaks in chromatogram in comparison to the sewage of WWTP. It is important to note that the concentrate generate on RO needs a treatment before its disposal in environment.

Keywords: organic compounds, reverse osmosis, sewage treatment, tertiary treatment

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Authors: Zeid A. Alothman

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Silver nanoparticle (AgNP) has been synthesized using adrenaline. Adrenaline readily undergoes an autoxidation reaction in an alkaline medium with the dissolved oxygen to form adrenochrome, thus behaving as a mild reducing agent for the dissolved oxygen. This reducing behavior of adrenaline when employed to reduce Ag(+) ions yielded a large enhancement in the intensity of absorbance in the visible region. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) studies have been performed to confirm the surface morphology of AgNPs. Further, the metallic nanoparticles with size greater than 2 nm caused a strong and broad absorption band in the UV-visible spectrum called surface plasmon band or Mie resonance. The formation of AgNPs caused the large enhancement in the absorbance values with λmax at 436 nm through the excitation of the surface plasmon band. The formation of AgNPs was adapted to for the quantitative assessment of adrenaline using spectrophotometry with lower detection limit and higher precision values.

Keywords: silver nanoparticle, adrenaline, XRD, TEM, analysis

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Authors: Hyun-Woo Cho

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Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

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Authors: David J. Thomson, Joshua C. J. Chew

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Background: Syndrome of Irreversible Lithium-Effectuated Neurotoxicity (SILENT) is a rare complication of lithium toxicity that typically causes irreversible cerebellar dysfunction. These patients may require hemodialysis and extensive supports in the intensive care. Methods: A review was performed on the available literature of SILENT with a focus on current pathophysiological hypotheses and advances in treatment. Articles were restricted to the English language. Results: Although the exact mechanism is unclear, CNS demyelination, especially in the cerebellum, was seen on the brain biopsies of a proportion of patients. There is no definitive management of SILENT but instead current management is focused on primary and tertiary prevention – detection of those at risk, and rehabilitation post onset of neurological deficits. Conclusions: This review draws conclusions from a limited amount of available literature, most of which are isolated case reports. Greater awareness of SILENT and further investigation into the risk factors and pathogenesis are required so this serious and irreversible syndrome may be avoided.

Keywords: lithium toxicity, pathogenesis, SILENT, syndrome of irreversible lithium-effectuated neurotoxicity

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Authors: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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Authors: Sarah Pasala, Elizabeth Zacharias

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Vital sign monitoring is crucial for both everyday health and medical diagnosis. A significant factor in assessing a human's health is their vital signs, which include heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings. Vital sign monitoring has been the focus of many system and method innovations recently. Piezoelectrics are materials that convert mechanical energy into electrical energy and can be used for vital sign monitoring. Piezoelectric energy harvesters that are stretchable and flexible can detect very low frequencies like airflow, heartbeat, etc. Current advancements in piezoelectric materials and flexible sensors have made it possible to create wearable and implantable medical devices that can continuously monitor physiological signals in humans. But because of their non-biocompatible nature, they also produce a large amount of e-waste and require another surgery to remove the implant. This paper presents a biocompatible and flexible piezoelectric composite material for wearable and implantable devices that offers a high-performance platform for seamless and continuous monitoring of human physiological signals and tactile stimuli. It also addresses the issue of e-waste and secondary surgery. A Lead-free piezoelectric, SrBi4Ti4O15, is found to be suitable for this application because the properties can be tailored by suitable substitutions and also by varying the synthesis temperature protocols. In the present work, SrBi4Ti4O15 modified by rare-earth has been synthesized and studied. Coupling factors are calculated from resonant (fr) and anti-resonant frequencies (fa). It is observed that Samarium substitution in SBT has increased the Curie temperature, dielectric and piezoelectric properties. From impedance spectroscopy studies, relaxation, and non-Debye type behaviour are observed. The composite of bioresorbable poly(l-lactide) and Lead-free rare earth modified Bismuth Layered Ferroelectrics leads to a flexible piezoelectric device for non-invasive measurement of vital signs, such as heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings and also artery pulse signals in near-surface arteries. These composites are suitable to detect slight movement of the muscles and joints. This Lead-free rare earth modified Bismuth Layered Ferroelectrics – polymer composite is synthesized using a ball mill and the solid-state double sintering method. XRD studies indicated the two phases in the composite. SEM studies revealed the grain size to be uniform and in the range of 100 nm. The electromechanical coupling factor is improved. The elastic constants are calculated and the mechanical flexibility is found to be improved as compared to the single-phase rare earth modified Bismuth Latered piezoelectric. The results indicate that this composite is suitable for the non-invasive detection of multiple vital signs of humans.

Keywords: composites, flexible, non-invasive, piezoelectric

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Authors: Memnun Seven, Aygül Akyüz

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Having a baby, giving birth and being a mother are generally considered happy events, especially for women who have had a history of infertility and may have suffered emotionally, physically and financially. Although the transition from the prenatal period to the postnatal period is usually desired and planned, it is a developmental and cognitive transition period full of complex emotional reactions. During this period, common mood disorders for women include maternity blues, postpartum depression and postpartum psychosis. Postpartum depression is a common and serious mood disorder which can jeopardize the health of the mother, baby and family within the first year of delivery. Knowing the risks factors is an important issue for the early detection and early intervention of postpartum depression. However, knowing that a history of infertility may contribute to the development of postpartum depression, there are few studies assessing the effects of infertility during the diagnosis and treatment of depression. In this review, the effects of infertility on the development of postpartum depression and nurse/midwives’ roles in this issue are discussed in light with the literature.

Keywords: infertility, postpartum depression, risk factors, mood disorder

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Authors: Sunglim Lee, Susumu Fujii, Koji Okamura

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Smart grid is a new approach for electric power grid that uses information and communications technology to control the electric power grid. Smart grid provides real-time control of the electric power grid, controlling the direction of power flow or time of the flow. Control devices are installed on the power lines of the electric power grid to implement smart grid. The number of the control devices should be determined, in relation with the area one control device covers and the cost associated with the control devices. One approach to determine the number of the control devices is to use the data on the surplus power generated by home solar generators. In current implementations, the surplus power is sent all the way to the power plant, which may cause power loss. To reduce the power loss, the surplus power may be sent to a control device and sent to where the power is needed from the control device. Under assumption that the control devices are installed on a lattice of equal size squares, our goal is to figure out the optimal spacing between the control devices, where the power sharing area (the area covered by one control device) is kept small to avoid power loss, and at the same time the power sharing area is big enough to have no surplus power wasted. To achieve this goal, a simulation using landscape ecology method is conducted on a sample area. First an aerial photograph of the land of interest is turned into a mosaic map where each area is colored according to the ratio of the amount of power production to the amount of power consumption in the area. The amount of power consumption is estimated according to the characteristics of the buildings in the area. The power production is calculated by the sum of the area of the roofs shown in the aerial photograph and assuming that solar panels are installed on all the roofs. The mosaic map is colored in three colors, each color representing producer, consumer, and neither. We started with a mosaic map with 100 m grid size, and the grid size is grown until there is no red grid. One control device is installed on each grid, so that the grid is the area which the control device covers. As the result of this simulation we got 350 m as the optimal spacing between the control devices that makes effective use of the surplus power for the sample area.

Keywords: landscape ecology, IT, smart grid, aerial photograph, simulation

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Authors: O. A. Al-Mashaqbeh, A. M. Ghrair, D. Alsafadi, S. S. Dalahmeh, S. L. Bartelt-Hunt, D. D. Snow

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Grab samples were collected in the summer to characterize selected pharmaceuticals and personal care products (PPCPs) in the influent of two wastewater treatment plants (WWTPs) in Jordan. Liquid chromatography tandem mass spectrometry (LC–MS/MS) was utilized to determine the concentrations of 18 compounds of PPCPs. Among all of the PPCPs analyzed, eight compounds were detected in the influent samples (1,7-dimethylxanthine, acetaminophen, caffeine, carbamazepine, cotinine, morphine, sulfamethoxazole and trimethoprim). However, five compounds (amphetamine, cimetidine, diphenhydramine, methylenedioxyamphetamine (MDA) and sulfachloropyridazine) were not detected in collected samples (below the detection limits <0.005 µg/l). Moreover, the results indicated that the highest concentration levels detected in collected samples were caffeine, acetaminophen, 1,7-dimethylxanthine, cotinine and carbamazepine at concentration of 182.5 µg/L, 28.7 µg/l, 7.47 µg/l, 4.67 µg/l and 1.54 µg/L, respectively. In general, most of compounds concentrations measured in wastewater in Jordan are within the range for wastewater previously reported in India wastewater except caffeine.

Keywords: pharmaceuticals, personal care products, wastewater, Jordan

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Authors: Hebat‑Allah S. Tohamy, Mohamed El‑Sakhawy, Samir Kamel

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Fluorescent carbon quantum dots (CQDs) were prepared by an economical, green, and single-step procedure based on microwave heating of urea with sugarcane bagasse (SCB), cellulose (C), or carboxymethyl cellulose (CMC). The prepared CQDs were characterized using a series of spectroscopic techniques, and they had small size, strong absorption in the UV, and excitation wavelength-dependent fluorescence. The prepared CQDs were used for Pb(II) adsorption from an aqueous solution. The removal efficiency percentages (R %) were 99.16, 96.36, and 98.48 for QCMC, QC, and QSCB. The findings validated the efficiency of CQDs synthesized from CMC, cellulose, and SCB as excellent materials for further utilization in the environmental fields of wastewater pollution detection, adsorption, and chemical sensing applications. The kinetics and isotherms studied found that all CQD isotherms fit well with the Langmuir model than Freundlich and Temkin models. According to R², the pseudo-second-order fits the adsorption of QCMC, while the first-order one fits with QC and QSCB.

Keywords: carbon quantum dots, graphene quantum dots, fluorescence, quantum yield, water treatment, agricultural wastes

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Authors: Eszter J. Tóth, Alexandra Hoffmann, Csaba Vágvölgyi, Tamás Papp

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Members of the genera Curvularia and Bipolaris are closely related melanin producing filamentous fungi; both of them have the teleomorph states in genus Cochliobolus. While Bipolaris species infect only plants and may cause serious agriculture damages, some Curvularia species was recovered from opportunistic human infections. The human pathogenic species typically cause phaeohyphomycoses, i.e. mould infections caused by melanised fungi, which can manifest as invasive mycoses with frequent involvement of the central nervous system in immunocompromised patients or as local infections (e.g. keratitis, sinusitis, and cutaneous lesions) in immunocompetent people. Although their plant-fungal interactions have been intensively studied, there is only little information available about the human pathogenic feature of these fungi. The aim of this study was to investigate the neutrophil granulocytes’ response to hyphal forms of Curvularia and Bipolaris in comparison with the response to Aspergillus. In the present study Curvularia lunata SZMC 23759 and Aspergillus fumigatus SZMC 23245 both isolated from human eye infection, and Bipolaris zeicola BRIP 19582b isolated from plant leaf were examined. Neutrophils were isolated from heparinised venous blood of healthy donors with dextran sedimentation followed by centrifugation over Ficoll and hypotonic lysis of erythrocytes. Viability and purity of the cells were checked with trypan blue and Wright staining, respectively. Infection of neutrophils was carried out with germinated conidia in a ratio of 5:1. Production of hydrogen peroxide, superoxide anion, and nitrogen monoxide was measured both intracellularly and extracellularly in response to the germinated spores with or without the supernatant and after serum treatment. ROS and NOS production of neutrophils in interaction with the three fungi were compared. It is already known that Aspergillus species induce ROS production of neutrophils only after serum treatment. Although, in case of C. lunata, serum opsonisation also induced an intensive production of reactive species, lower level of production was measured in the lack of serum as well. After interaction with the plant pathogenic B. zeicola, amount of reactive species found to be similar with and without serum treatment. The presence of germination supernatant decreased the reactive species production in case of each fungus. Interaction with Curvularia, Bipolaris and Aspergillus species induced different response of neutrophils. It seems that recognition of C. lunata and B. zeicola is independent of serum opsonisation, albeit it increases the level of the produced reactive species in response for C. lunata. The study was supported by the grant LP2016-8/2016.

Keywords: Curvularia, neutrophils, NOS, ROS, serum opsonisation

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Maryam Panahiazar, Andrew M. Bishara, Yorick Chern, Roohallah Alizadehsani, Dexter Hadleye, Ramin E. Beygui

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Early detection plays a crucial role in enhancing the outcome for a patient with coronary artery disease (CAD). We utilized a big data analytics platform on ~23,000 patients with CAD from a total of 960,129 UCSF patients in 8 years. We traced the patients from their first encounter with a physician to diagnose and treat CAD. Characteristics such as demographic information, comorbidities, vital, lab tests, medications, and procedures are included. There are statistically significant gender-based differences in patients younger than 60 years old from the time of the first physician encounter to coronary artery bypass grafting (CABG) with a p-value=0.03. There are no significant differences between the patients between 60 and 80 years old (p-value=0.8) and older than 80 (p-value=0.4) with a 95% confidence interval. This recognition would affect significant changes in the guideline for referral of the patients for diagnostic tests expeditiously to improve the outcome by avoiding the delay in treatment.

Keywords: electronic medical records, coronary artery disease, data analytics, young women

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Authors: Renjith George Pallivathukal, Preethy Mary Donald

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Asymptomatic oral lesions are often ignored by the patients and usually will be identified only in advanced stages. Early detection of precancerous lesions is important for better prognosis. It is also important for the oral health care person to be aware of the regional prevalence of oral lesions in order to provide early care for the same. We conducted a retrospective study to assess the prevalence of oral lesions based on the information available from patient records in a teaching dental school. Dental records of patients who attended the department of Oral medicine and diagnosis between September 2014 and September 2016 were retrieved and verified for oral lesions. Results: The ages of the patients ranged from 13 to 38 years with a mean age of 21.8 years. The lesions were classified as white (40.5%), red (23%), ulcerated (10.5%), pigmented (15.2%) and soft tissue enlargements (10.8%). 52% of the patients were unaware of the oral lesions before the dental visit. Overall, the prevalence of lesions in dental patients lower to national estimates, but the prevalence of some lesions showed variations.

Keywords: oral mucosal lesion, pre-cancer, prevalence, soft tissue lesion

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Jonida Canaj

Abstract:

A simple method of extraction and determination of fifteen priority polycyclic aromatic hydrocarbons (PAHs) from drinking water using high performance liquid chromatography (HPLC) has been validated with limits of detection (LOD) and limits of quantification (LOQ), method recovery and reproducibility, and other factors. HPLC parameters, such as mobile phase composition and flow standardized for determination of PAHs using fluorescent detector (FLD). PAH was carried out by liquid-liquid extraction using dichloromethane. Linearity of calibration curves was good for all PAH (R², 0.9954-1.0000) in the concentration range 0.1-100 ppb. Analysis of standard spiked water samples resulted in good recoveries between 78.5-150%(0.1ppb) and 93.04-137.47% (10ppb). The estimated LOD and LOQ ranged between 0.0018-0.98 ppb. The method described has been used for determination of the fifteen PAHs contents in drinking water samples.

Keywords: high performance liquid chromatography, HPLC, method validation, polycyclic aromatic hydrocarbons, PAHs, water

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Authors: Mhaned Oubounyt, Jan Baumbach

Abstract:

Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

Abstract:

Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

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Authors: Kaouther Jaouadi, Jihene Bettaieb, Amira Bennour, Ghassen Kharroubi, Sadok Salem, Afif Ben Salah

Abstract:

In Tunisia, chronic cutaneous leishmaniasis due to Leishmania (L) tropica is an important health problem. Its spreading has not been fully elucidated. Information on sandfly vectors, as well as their associated Leishmania species, is of paramount importance since vector dispersion is one of the major factors responsible for pathogen dissemination. In total, 650 sandflies were captured between June and August 2015 using sticky paper traps in the governorate of Sidi Bouzid, a classical focus of L. major in the Central-West of Tunisia. Polymerase chain reaction-restriction fragment length polymorphism analysis of the internal transcribed spacer 1 and sequencing were used for Leishmania detection and identification. Ninety-seven unfed females were tested for the presence of Leishmania parasite DNA. Six Phlebotomus sergenti were found positive for L. tropica. This finding enhances the understanding of the cycle extension of L. tropica outside its original focus of Tataouine in the South-East of the country.

Keywords: cutaneous leishmaniasis, Leishmania tropica, sandflies, Tunisia

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Authors: Ibrahim Aly, Waleed Elawamy, Hanan Taher, Amira Matar

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Schistosomiasis is infection with blood flukes of the genus Schistosoma, which are acquired trans-cutaneously by swimming or wading in contaminated freshwater. The present study was proposed to produce ultra-sensitive, field-friendly high-throughput rapid immunochromatography diagnostic device for accurate detection of asymptomatic parasite carriers in schistosomiasis pre-elimination settings.For assessing diagnostic potential of rapid device, 50 blood samples from patients with schistosomiasis mansoni, 29 other proven parasitic diseases and 25 blood samples as negative control were from healthy individuals were used. The sensitivity of Quantitative antigen-capture nano-ELISAwas 82 %, and specificity was 87.1 %, where the sensitivity of Nano Dot- ELISA was 86 % and specificity was 90.7 %. The sensitivity of diagnostic device was 78 % and specificity was 85.2 %, with PPV and NPV of 86.2 % and 83.1 %, respectively.The Point of care device resulted in a good performance for the diagnosis of low-intensity infections, it was able to identify 19 out of 25 (76 %) individuals with ⩽7 eggs, 10 out of 14 individuals (71.4 %) with 11–99 eggs and 100 % of individuals with 100–399 eggs.

Keywords: schistosomiasis, immunochromatography, naon-dot-ELISa, diagnostis device

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Authors: Adrizal, Irsan Ryanto, Sri Juwita, Adika Sugara, Tino Bapirco

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The objective of the research was to study the influence of the inclusion of the cabbage waste into a buffalo rations made of sugarcane waste on the feed formula and characteristic of complete feed silage. Research carried out a two-stage i.e. the feed formulation and experiment of making complete feed silage. Feed formulation is done by linear programming. Data input is the price of feed stuffs and their nutrient contents as well as requirements for rations, while the output is the use of each feed stuff and the price of complete feed. The experiment of complete feed silage was done by a completely random design 4 x 4. The treatments were 4 inclusion levels of the cabbage waste i.e. 0%,(T1) 5%(T2), 10%(T3) and 15% (T4), with 4 replications. The result of feed formulation for T1 was cabbage (0%), sugarcane top (17.9%), bagasse (33.3%), Molasses (5.0%), cabagge (0%), Thitonia sp (10.0%), rice brand (2.7%), palm kernel cake (20.0%), corn meal (9.1%), bond meal (1.5%) and salt (0.5%). The formula of T2 was cabagge (5%), sugarcane top (1.7%), bagasse (45.2%), Molasses (5.0%), , Thitonia sp (10.0%), rice brand (3.6%), palm kernel cake (20.0%), corn meal (7.5%), bond meal (1.5%) and salt (0.5%). The formula of T3 was cabbage (10%), sugarcane top (0%), bagasse (45.3%), Molasses (5.0%), Thitonia sp (10.0%), rice brand (3.8%), palm kernel cake (20.0%), corn meal (3.9%), bond meal (1.5%) and salt(0.5%). The formula of T4 was cabagge (15.0%), sugarcane top (0%), bagasse (44.1%), Molasses (5.0%), Thitonia sp (10.0%), rice brand (3.9%), palm kernel cake (20.0%), corn meal (0%), bond meal (1.5%) and salt (0.5%). An increase in the level of inclusion of the cabbage waste can decrease the cost of rations. The cost of rations (IDR/kg on DM basis) were 1442, 1367, 1333, and 1300 respectively. The rations formula were not significantly (P > 0.05) influent the on fungal colonies, smell, texture and color of the complete ration silage, but the pH increased significantly (P < 0.05). It concluded that inclusion of cabbage waste can minimize the cost of buffalo ration, without decreasing the silage quality of complete feed.

Keywords: buffalo, cabbage, complete feed, sillage characteristic, sugarcane waste

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Satyendra Mourya, Jyoti Jaiswal, Gaurav Malik, Brijesh Kumar, Ramesh Chandra

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Present work describes the fabrication and sensing characteristics of the Pd-Pt decorated nanostructured silicon carbide (SiC) thin films on anodized porous silicon (PSi) substrate by RF magnetron sputtering. The gas sensing performance of Pd-Pt/SiC/PSi sensing electrode towards H2 gas under low (10–400 ppm) detection limit and high operating temperature regime (25–600 °C) were studied in detail. The chemiresistive sensor exhibited high selectivity, good sensing response, fast response/recovery time with excellent stability towards H2 at high temperature. The selectivity measurement of the sensing electrode was done towards different oxidizing and reducing gases and proposed sensing mechanism discussed in detail. Therefore, the investigated Pd-Pt/SiC/PSi structure may be a highly sensitive and selective hydrogen gas sensing electrode for deployment in extreme environment applications.

Keywords: RF Sputtering, silicon carbide, porous silicon, hydrogen gas sensor

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