Search results for: tool/tissue interaction

Authors: C. Soffritti, A. Fortini, E. Baroni, M. Merlin, G. L. Garagnani

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Aluminum alloys are widely used in many engineering applications due to their advantages such ashigh electrical and thermal conductivities, low density, high strength to weight ratio, and good corrosion resistance. However, their low hardness and poor tribological properties still limit their use in industrial fields requiring sliding contacts. Hard anodizing is one of the most common solution for overcoming issues concerning the insufficient friction resistance of aluminum alloys. In this work, the tribological behavior ofhard-anodized AW-4006 aluminum alloys in dry and lubricated conditions was evaluated. Three different hard-anodizing treatments were selected: a conventional one (HA) and two innovative golden hard-anodizing treatments (named G and GP, respectively), which involve the sealing of the porosity of anodic aluminum oxides (AAO) with silver ions at different temperatures. Before wear tests, all AAO layers were characterized by scanning electron microscopy (VPSEM/EDS), X-ray diffractometry, roughness (Ra and Rz), microhardness (HV0.01), nanoindentation, and scratch tests. Wear tests were carried out according to the ASTM G99-17 standard using a ball-on-disc tribometer. The tests were performed in triplicate under a 2 Hz constant frequency oscillatory motion, a maximum linear speed of 0.1 m/s, normal loads of 5, 10, and 15 N, and a sliding distance of 200 m. A 100Cr6 steel ball10 mm in diameter was used as counterpart material. All tests were conducted at room temperature, in dry and lubricated conditions. Considering the more recent regulations about the environmental hazard, four bio-lubricants were considered after assessing their chemical composition (in terms of Unsaturation Number, UN) and viscosity: olive, peanut, sunflower, and soybean oils. The friction coefficient was provided by the equipment. The wear rate of anodized surfaces was evaluated by measuring the cross-section area of the wear track with a non-contact 3D profilometer. Each area value, obtained as an average of four measurements of cross-section areas along the track, was used to determine the wear volume. The worn surfaces were analyzed by VPSEM/EDS. Finally, in agreement with DoE methodology, a statistical analysis was carried out to identify the most influencing factors on the friction coefficients and wear rates. In all conditions, results show that the friction coefficient increased with raising the normal load. Considering the wear tests in dry sliding conditions, irrespective of the type of anodizing treatments, metal transfer between the mating materials was observed over the anodic aluminum oxides. During sliding at higher loads, the detachment of the metallic film also caused the delamination of some regions of the wear track. For the wear tests in lubricated conditions, the natural oils with high percentages of oleic acid (i.e., olive and peanut oils) maintained high friction coefficients and low wear rates. Irrespective of the type of oil, smallmicrocraks were visible over the AAO layers. Based on the statistical analysis, the type of anodizing treatment and magnitude of applied load were the main factors of influence on the friction coefficient and wear rate values. Nevertheless, an interaction between bio-lubricants and load magnitude could occur during the tests.

Keywords: hard anodizing treatment, silver ions, bio-lubricants, sliding wear, statistical analysis

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Adam J. Bowen

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Abstract— Should robots have rights or legal protections. Often debates concerning whether robots and AI should be afforded rights focus on conditions of personhood and the possibility of future advanced forms of AI satisfying particular intrinsic cognitive and moral attributes of rights-holding persons. Such discussions raise compelling questions about machine consciousness, autonomy, and value alignment with human interests. Although these are important theoretical concerns, especially from a future design perspective, they provide limited guidance for addressing the moral and legal standing of current and near-term AI that operate well below the cognitive and moral agency of human persons. Robots and AI are already being pressed into service in a wide range of roles, especially in healthcare and biomedical contexts. The design and large-scale implementation of robots in the context of core societal institutions like healthcare systems continues to rapidly develop. For example, we bring them into our homes, hospitals, and other care facilities to assist in care for the sick, disabled, elderly, children, or otherwise vulnerable persons. We enlist surgical robotic systems in precision tasks, albeit still human-in-the-loop technology controlled by surgeons. We also entrust them with social roles involving companionship and even assisting in intimate caregiving tasks (e.g., bathing, feeding, turning, medicine administration, monitoring, transporting). There have been advances to enable severely disabled persons to use robots to feed themselves or pilot robot avatars to work in service industries. As the applications for near-term AI increase and the roles of robots in restructuring our biomedical practices expand, we face pressing questions about the normative implications of human-robot interactions and collaborations in our collective worldmaking, as well as the moral and legal status of robots. This paper argues that robots operating in public and private spaces be afforded some protections as either moral patients or legal agents to establish prohibitions on robot abuse, misuse, and mistreatment. We already implement robots and embed them in our practices and institutions, which generates a host of human-to-machine and machine-to-machine relationships. As we interact with machines, whether in service contexts, medical assistance, or home health companions, these robots are first encountered in relationship to us and our respective roles in the encounter (e.g., surgeon, physical or occupational therapist, recipient of care, patient’s family, healthcare professional, stakeholder). This proposal aims to outline a framework for establishing limiting factors and determining the extent of moral or legal protections for robots. In doing so, it advocates for a relational approach that emphasizes the priority of mapping the complex contextually sensitive roles played and the relations in which humans and robots stand to guide policy determinations by relevant institutions and authorities. The relational approach must also be technically informed by the intended uses of the biomedical technologies in question, Design History Files, extensive risk assessments and hazard analyses, as well as use case social impact assessments.

Keywords: biomedical robots, robot ethics, robot laws, human-robot interaction

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Authors: Sibgha Noreen, Muhammad Salim Akhter, Seema Mahmood

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Salt stress is an abiotic stress that causes a heavy toll on growth and development and also reduces the productivity of arable and horticultural crops. Globally, a quarter of total arable land has fallen prey to this menace, and more is being encroached because of the usage of brackish water for irrigation purposes. Though barley is categorized as salt-tolerant crop, but cultivars show a wide genetic variability in response to it. In addressing salt stress, silicon nutrition would be a facile tool for enhancing salt tolerant to sustain crop production. A greenhouse study was conducted to evaluate the response of barley (Hordeum vulgare L.) cultivars to silicon nutrition under salt stress. The treatments included [(a) four barley cultivars (Jou-87, B-14002, B-14011, B-10008); (b) two salt levels (0, 200 mM, NaCl); and (c) two silicon levels (0, 200ppm, K2SiO3. nH2O), arranged in a factorial experiment in a completely randomized design with 16 treatments and repeated 4 times. Plants were harvested at 15 days after exposure to different experimental salinity and silicon foliar conditions. Results revealed that various physiological and biochemical attributes differed significantly (p<0.05) in response to different treatments and their interactive effects. Cultivar “B-10008” excelled in biological yield, chlorophyll constituents, antioxidant enzymes, and grain yield compared to other cultivars. The biological yield of shoot and root organs was reduced by 27.3 and 26.5 percent under salt stress, while it was increased by 14.5 and 18.5 percent by exogenous application of silicon over untreated check, respectively. The imposition of salt stress at 200 mM caused a reduction in total chlorophyll content, chl ‘a’ , ‘b’ and ratio a/b by 10.6,16.8,17.1 and 7.1, while spray of 200 ppm silicon improved the quantum of the constituents by 10.4,12.1,10.2,10.3 over untreated check, respectively. The quantum of free amino acids and protein content was enhanced in response to salt stress and the spray of silicon nutrients. The amounts of superoxide dismutase, catalases, peroxidases, hydrogen peroxide, and malondialdehyde contents rose to 18.1, 25.7, 28.1, 29.5, and 17.6 percent over non-saline conditions under salt stress. However, the values of these antioxidants were reduced in proportion to salt stress by 200 ppm silicon applied as rooting medium on barley crops. The salt stress caused a reduction in the number of tillers, number of grains per spike, and 100-grain weight to the amount of 29.4, 8.6, and 15.8 percent; however, these parameters were improved by 7.1, 10.3, and 9.6 percent by foliar spray of silicon over untreated crop, respectively. It is concluded that the barley cultivar “B-10008” showed greater tolerance and adaptability to saline conditions. The yield of barley crops could be potentiated by a foliar spray of 200 ppm silicon at the vegetative growth stage under salt stress.

Keywords: salt stress, silicon nutrition, chlorophyll constituents, antioxidant enzymes, barley crop

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Authors: Djamila Chabane, Asma Rouane, Karim Arab

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Depending of the chemical substances responsible for the pharmacological effects, a future therapeutic drug might be produced by extraction from whole plants or by callus initiated from some parts. The optimized callus culture protocols now offer the possibility to use cell culture techniques for vegetative propagation and open minds for further studies on secondary metabolites and drug establishment. In Algerian traditional medicine, Pulicaria incisa (Asteraceae) is used in the treatment of daily troubles (stomachache, headhache., cold, sore throat and rheumatic arthralgia). Field findings revealed that many healers use some fresh parts (leaves, flowers) of this plant to treat skin wounds. This study aims to evaluate the healing efficiency of artisanal cream prepared from sticky mucilage isolated from calluses on dermal wounds of animal models. Callus cultures were initiated from reproductive explants (young inflorescences) excised from adult plants and transferred to a MS basal medium supplemented with growth regulators and maintained under dark for for months. Many calluses types were obtained with various color and aspect (friable, compact). Several subcultures of calli were performed to enhance the mucilage accumulation. After extraction, the mucilage extracts were tested on animal models as follows. The wound healing potential was studied by causing dermal wounds (1 cm diameter) at the dorsolumbar part of Rattus norvegicus; different samples of the cream were applied after hair removal on three rats each, including two controls (one treated by Vaseline and one without any treatment), two experimental groups (experimental group 1, treated with a reference ointment "Madecassol® and experimental group 2 treated by callus mucilage cream for a period of seventeen days. The evolution of the healing activity was estimated by calculating the percentage reduction of the area wounds treated by all compounds tested compared to the controls by using AutoCAD software. The percentage of healing effect of the cream prepared from callus mucilage was (99.79%) compared to that of Madecassol® (99.76%). For the treatment time, the significant healing activity was observed after 17 days compared to that of the reference pharmaceutical products without any wound infection. The healing effect of Madecassol® is more effective because it stimulates and regulates the production of collagen, a fibrous matrix essential for wound healing. Mucilage extracts also showed a high capacity to heal the skin without any infection. According to this pharmacological activity, we suggest to use calluses produced by in vitro culture to producing new compounds for the skin care and treatment.

Keywords: calluses, Pulicaria incisa, mucilage, Wounds

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Authors: Rosa Amalia Safitri, Ine van der Fels-Klerx, Henk Hogeveen

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Halal is a dietary law observed by people following Islamic faith. It is considered as a type of credence food quality which cannot be easily assured by consumers even upon and after consumption. Therefore, Halal certification takes place as a practical tool for the consumers to make an informed choice particularly in a non-Muslim majority country, including the Netherlands. Discrete choice experiment (DCE) was employed in this study for its ability to assess the importance of attributes attached to Halal beef in the Dutch market and to investigate consumer utilities. Furthermore, willingness to pay (WTP) for the desired Halal certification was estimated. Four most relevant attributes were selected, i.e., the slaughter method, traceability information, place of purchase, and Halal certification. Price was incorporated as an attribute to allow estimation of willingness to pay for Halal certification. There were 242 Muslim respondents who regularly consumed Halal beef completed the survey, from Dutch (53%) and non-Dutch consumers living in the Netherlands (47%). The vast majority of the respondents (95%) were within the age of 18-45 years old, with the largest group being student (43%) followed by employee (30%) and housewife (12%). Majority of the respondents (76%) had disposable monthly income less than € 2,500, while the rest earned more than € 2,500. The respondents assessed themselves of having good knowledge of the studied attributes, except for traceability information with 62% of the respondents considered themselves not knowledgeable. The findings indicated that slaughter method was valued as the most important attribute, followed by Halal certificate, place of purchase, price, and traceability information. This order of importance varied across sociodemographic variables, except for the slaughter method. Both Dutch and non-Dutch subgroups valued Halal certification as the third most important attributes. However, non-Dutch respondents valued it with higher importance (0,20) than their Dutch counterparts (0,16). For non-Dutch, the price was more important than Halal certification. The ideal product preferred by the consumers indicated the product serving the highest utilities for consumers, and characterized by beef obtained without pre-slaughtering stunning, with traceability info, available at Halal store, certified by an official certifier, and sold at 2.75 € per 500 gr. In general, an official Halal certifier was mostly preferred. However, consumers were not willing to pay for premium for any type of Halal certifiers, indicated by negative WTP of -0.73 €, -0.93 €, and -1,03€ for small, official, and international certifiers, respectively. This finding indicated that consumers tend to lose their utility when confronted with price. WTP estimates differ across socio-demographic variables with male and non-Dutch respondents had the lowest WTP. The unfamiliarity to traceability information might cause respondents to perceive it as the least important attribute. In the context of Halal certified meat, adding traceability information into meat packaging can serve two functions, first consumers can justify for themselves whether the processes comply with Halal requirements, for example, the use of pre-slaughtering stunning, and secondly to assure its safety. Therefore, integrating traceability info into meat packaging can help to make informed decision for both Halal status and food safety.

Keywords: consumer utilities, discrete choice experiments, Halal certification, willingness to pay

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

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Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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Authors: Adriana de Paula Lacerda Santos, Bruna Godke, Mauro Lacerda Santos Filho

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Several dams in the world have already collapsed, causing environmental, social and economic damage. The concern to avoid future disasters has stimulated the creation of a great number of laws and rules in many countries. In Brazil, Law 12.334/2010 was created, which establishes the National Policy on Dam Safety. Overall, this policy requires the dam owners to invest in the maintenance of their structures and to improve its monitoring systems in order to provide faster and straightforward responses in the case of an increase of risks. As monitoring tools, visual inspections has provides comprehensive assessment of the structures performance, while auscultation’s instrumentation has added specific information on operational or behavioral changes, providing an alarm when a performance indicator exceeds the acceptable limits. These limits can be set using statistical methods based on the relationship between instruments measures and other variables, such as reservoir level, time of the year or others instruments measuring. Besides the design parameters (uplift of the foundation, displacements, etc.) the dam instrumentation can also be used to monitor the behavior of defects and damage manifestations. Specifically in concrete gravity dams, one of the main causes for the appearance of cracks, are the concrete volumetric changes generated by the thermal origin phenomena, which are associated with the construction process of these structures. Based on this, the goal of this research is to propose a monitoring process of the thermal cracking behavior in concrete gravity dams, through the instrumentation data analysis and the establishment of control values. Therefore, as a case study was selected the Block B-11 of José Richa Governor Dam Power Plant, that presents a cracking process, which was identified even before filling the reservoir in August’ 1998, and where crack meters and surface thermometers were installed for its monitoring. Although these instruments were installed in May 2004, the research was restricted to study the last 4.5 years (June 2010 to November 2014), when all the instruments were calibrated and producing reliable data. The adopted method is based on simple linear correlations procedures to understand the interactions among the instruments time series, verifying the response times between them. The scatter plots were drafted from the best correlations, which supported the definition of the limit control values. Among the conclusions, it is shown that there is a strong or very strong correlation between ambient temperature and the crack meters and flowmeters measurements. Based on the results of the statistical analysis, it was possible to develop a tool for monitoring the behavior of the case study cracks. Thus it was fulfilled the goal of the research to develop a proposal for a monitoring process of the behavior of thermal cracking in concrete gravity dams.

Keywords: concrete gravity dam, dams safety, instrumentation, simple linear correlation

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Authors: Ziyad S. Haidar

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Background: Saliva plays a major role in maintaining oral and dental health (consequently, general health and well-being). Where it normally bathes the oral cavity and acts as a clearing agent. This becomes more apparent when the amount and quality of salivare significantly reduced due to medications, salivary gland neoplasms, disorders such as Sjögren’s syndrome, and especially ionizing radiation therapy for tumors of the head and neck, the fifth most common malignancy worldwide, during which the salivary glands are included within the radiation field or zone. Clinically, patients affected by salivary gland dysfunction often opt to terminate their radiotherapy course prematurely because they become malnourished and experience a significant decrease in their quality of life. Accordingly, the development of an alternative treatment to restore or regenerate damaged salivary gland tissue is eagerly awaited. Likewise, the formulation of a radioprotection modality and early damage prevention strategy is also highly desirable. Objectives: To assess the pre-clinical radio-protective effect as well as the reparative/regenerative potential of layer-by-layer self-assembled lipid-polymer-based core-shell nanocapsules designed and fine-tuned in this experimental work for the sequential (ordered) release of dual cytokines, following a single local administration (direct injection) into a murine sub-mandibular salivary gland model of irradiation. Methods: The formulated core-shell nanocapsules were characterized by physical-chemical-mechanically pre-/post-loading with the drugs (in solution and powder formats), followed by optimizing the pharmaco-kinetic profile. Then, nanosuspensions were administered directly into the salivary glands, 24hrs pre-irradiation (PBS, un-loaded nanocapsules, and individual and combined vehicle-free cytokines were injected into the control glands for an in-depth comparative analysis). External irradiation at an elevated dose of 18Gy (revised from our previous 15Gy model) was exposed to the head-and-neck region of C57BL/6 mice. Salivary flow rate (un-stimulated) and salivary protein content/excretion were regularly assessed using an enzyme-linked immunosorbent assay (3-month period). Histological and histomorphometric evaluation and apoptosis/proliferation analysis followed by local versus systemic bio-distribution and immuno-histochemical assays were then performed on all harvested major organs (at the distinct experimental end-points). Results: Monodisperse, stable, and cytocompatible nanocapsules capable of maintaining the bioactivity of the encapsulant within the different compartments with the core and shell and with controlled/customizable pharmaco-kinetics, resulted, as is illustrated in the graphical abstract (Figure) below. The experimental animals demonstrated a significant increase in salivary flow rates when compared to the controls. Herein, salivary protein content was comparable to the pre-irradiation (baseline) level. Histomorphometry further confirmed the biocompatibility and localization of the nanocapsules, in vivo, into the site of injection. Acinar cells showed fewer vacuoles and nuclear aberration in the experimental group, while the amount of mucin was higher in controls. Overall, fewer apoptotic activities were detected by a Terminal deoxynucleotidyl Transferase (TdT) dUTP Nick-End Labeling (TUNEL) assay and proliferative rates were similar to the controls, suggesting an interesting reparative and regenerative potential of irradiation-damaged/-dysfunctional salivary glands. The Figure below exemplifies some of these findings. Conclusions: Biocompatible, reproducible, and customizable self-assembling layer-by-layer core-shell delivery system is formulated and presented. Our findings suggest that localized sequential bioactive delivery of dual cytokines (in specific dose and order) can prevent irradiation-induced damage via reducing apoptosis and also has the potential to promote in situ proliferation of salivary gland cells; maxSALIVA is scalable (Good Manufacturing Practice or GMP production for human clinical trials) and patent-pending.

Keywords: saliva, head and neck cancer, nanotechnology, controlled drug delivery, xerostomia, mucositis, biopolymers, innovation

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Yifan Lu, Ying Cui, Ying Zhu, Edward S. Lu, Rebecca Zeng, Rohan Bajaj, Raviv Katz, Rongrong Le, Jay C. Wang, John B. Miller

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Purpose: Retinal artery occlusion (RAO) is an ophthalmic emergency that can lead to poor visual outcome and is associated with an increased risk of cerebral stroke and cardiovascular events. Fluorescein angiography (FA) is the traditional diagnostic tool for RAO; however, wide-field swept-source optical coherence tomography angiography (WF SS-OCTA), as a nascent imaging technology, is able to provide quick and non-invasive angiographic information with a wide field of view. In this study, we looked for associations between OCT-A vascular metrics and visual acuity in patients with prior diagnosis of RAO. Methods: Patients with diagnoses of central retinal artery occlusion (CRAO) or branched retinal artery occlusion (BRAO) were included. A 6mm x 6mm Angio and a 15mm x 15mm AngioPlex Montage OCT-A image were obtained for both eyes in each patient using the Zeiss Plex Elite 9000 WF SS-OCTA device. Each 6mm x 6mm image was divided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. The average measurement of the central foveal subfield, inner ring, and outer ring was calculated for each parameter. Non-perfusion area (NPA) was manually measured using 15mm x 15mm Montage images. A linear regression model was utilized to identify a correlation between the imaging metrics and visual acuity. A P-value less than 0.05 was considered to be statistically significant. Results: Twenty-five subjects were included in the study. For RAO eyes, there was a statistically significant negative correlation between vision and retinal thickness as well as superficial capillary plexus vessel density (SCP VD). A negative correlation was found between vision and deep capillary plexus vessel density (DCP VD) without statistical significance. There was a positive correlation between vision and choroidal thickness as well as choroidal volume without statistical significance. No statistically significant correlation was found between vision and the above metrics in contralateral eyes. For NPA measurements, no significant correlation was found between vision and NPA. Conclusions: This is the first study to our best knowledge to investigate the utility of WF SS-OCTA in RAO and to demonstrate correlations between various retinal vascular imaging metrics and visual outcomes. Further investigations should explore the associations between these imaging findings and cardiovascular risk as RAO patients are at elevated risk for symptomatic stroke. The results of this study provide a basis to understand the structural changes involved in visual outcomes in RAO. Furthermore, they may help guide management of RAO and prevention of cerebral stroke and cardiovascular accidents in patients with RAO.

Keywords: OCTA, swept-source OCT, retinal artery occlusion, Zeiss Plex Elite

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Authors: Kathy Pain, Nalumino Akakandelwa

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The study explores the potential to fill a gap in health and wellbeing evidence for purposeful urban real estate asset management to make investment a powerful force for societal good. Part of a five-year programme investigating the root causes of unhealthy urban development funded by the United Kingdom Prevention Research Partnership (UKPRP), the study pilots the use of a systems mapping approach to identify drivers and barriers to the incorporation of health and wellbeing evidence in urban brownfield asset management decision-making. Urban real estate not only provides space for economic production but also contributes to the quality of life in the local community. Yet market approaches to urban land use have, until recently, insisted that neo-classical technology-driven efficient allocation of economic resources should inform acquisition, operational, and disposal decisions. Buildings in locations with declining economic performance have thus been abandoned, leading to urban decay. Property investors are recognising the inextricable connection between sustainable urban production and quality of life in local communities. The redevelopment and operation of brownfield assets recycle existing buildings, minimising embodied carbon emissions. It also retains established urban spaces with which local communities identify and regenerate places to create a sense of security, economic opportunity, social interaction, and quality of life. Social implications of urban real estate on health and wellbeing and increased adoption of benign sustainability guidance in urban production are driving the need to consider how they affect brownfield real estate asset management decisions. Interviews with real estate upstream decision-makers in the study, find that local social needs and impact analysis is becoming a commercial priority for large-scale urban real estate development projects. Evidence of the social value-added of proposed developments is increasingly considered essential to secure local community support and planning permissions, and to attract sustained inward long-term investment capital flows for urban projects. However, little is known about the contribution of population health and wellbeing to socially sustainable urban projects and the monetary value of the opportunity this presents to improve the urban environment for local communities. We report early findings from collaborations with two leading property companies managing major investments in brownfield urban assets in the UK to consider how the inclusion of health and wellbeing evidence in social valuation can inform perceptions of brownfield development social benefit for asset managers, local communities, public authorities and investors for the benefit of all parties. Using holistic case studies and systems mapping approaches, we explore complex relationships between public health considerations and asset management decisions in urban production. Findings indicate a strong real estate investment industry appetite and potential to include health as a vital component of sustainable real estate social value creation in asset management strategies.

Keywords: brownfield urban assets, health and wellbeing, social needs and impact, social valuation, sustainable real estate, systems mapping

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Authors: Miguel A. Figueroa, José A. Lara-Ramos, Miguel A. Mueses

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Pharmaceutical residues are a section of emerging contaminants of anthropogenic origin that are present in a myriad of waters with which human beings interact daily and are starting to affect the ecosystem directly. Conventional waste-water treatment systems are not capable of degrading these pharmaceutical effluents because their designs cannot handle the intermediate products and biological effects occurring during its treatment. That is why it is necessary to hybridize conventional waste-water systems with non-conventional processes. In the specific case of an ozonation process, its efficiency highly depends on a perfect dispersion of ozone, long times of interaction of the gas-liquid phases and the size of the ozone bubbles formed through-out the reaction system. In order to increase the efficiency of these parameters, the use of a modified flotation cell has been proposed recently as a reactive system, which is used at an industrial level to facilitate the suspension of particles and spreading gas bubbles through the reactor volume at a high rate. The objective of the present work is the development of a mathematical model that can closely predict the kinetic rates of reactions taking place in the flotation cell at an experimental scale by means of identifying proper reaction mechanisms that take into account the modified chemical and hydrodynamic factors in the FeO-catalyzed Ozonation of Diclofenac aqueous solutions in a flotation cell. The methodology is comprised of three steps: an experimental phase where a modified flotation cell reactor is used to analyze the effects of ozone concentration and loading catalyst over the degradation of Diclofenac aqueous solutions. The performance is evaluated through an index of utilized ozone, which relates the amount of ozone supplied to the system per milligram of degraded pollutant. Next, a theoretical phase where the reaction mechanisms taking place during the experiments must be identified and proposed that details the multiple direct and indirect reactions the system goes through. Finally, a kinetic model is obtained that can mathematically represent the reaction mechanisms with adjustable parameters that can be fitted to the experimental results and give the model a proper physical meaning. The expected results are a robust reaction rate law that can simulate the improved results of Diclofenac mineralization on water using the modified flotation cell reactor. By means of this methodology, the following results were obtained: A robust reaction pathways mechanism showcasing the intermediates, free-radicals and products of the reaction, Optimal values of reaction rate constants that simulated Hatta numbers lower than 3 for the system modeled, degradation percentages of 100%, TOC (Total organic carbon) removal percentage of 69.9 only requiring an optimal value of FeO catalyst of 0.3 g/L. These results showed that a flotation cell could be used as a reactor in ozonation, catalytic ozonation and photocatalytic ozonation processes, since it produces high reaction rate constants and reduces mass transfer limitations (Ha > 3) by producing microbubbles and maintaining a good catalyst distribution.

Keywords: advanced oxidation technologies, iron oxide, emergent contaminants, AOTS intensification

Procedia PDF Downloads 87

Authors: Rupak Kumar Sarma, Ratul Saikia

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Macrophytes encompass major functional group in eutrophic wetland ecosystems. As a key functional element of freshwater lakes, they play a crucial role in regulating various wetland biogeochemical cycles, as well as maintain the biodiversity at the ecosystem level. The high carbon-rich underground biomass of macrophyte populations may harbour diverse microbial community having significant potential in maintaining different biogeochemical cycles. The present investigation was designed to study the macrophyte-microbe interaction in coupled nitrification and denitrification, considering Deepor Beel Lake (a Ramsar conservation site) of North East India as a model eutrophic system. Highly eutrophic sites of Deepor Beel were selected based on sediment oxygen demand and inorganic phosphorus and nitrogen (P&N) concentration. Sediment redox potential and depth of the lake was chosen as the benchmark for collecting the plant and sediment samples. The average highest depth in winter (January 2016) and summer (July 2016) were recorded as 20ft (6.096m) and 35ft (10.668m) respectively. Both sampling depth and sampling seasons had the distinct effect on variation in macrophyte community composition. Overall, the dominant macrophytic populations in the lake were Nymphaea alba, Hydrilla verticillata, Utricularia flexuosa, Vallisneria spiralis, Najas indica, Monochoria hastaefolia, Trapa bispinosa, Ipomea fistulosa, Hygrorhiza aristata, Polygonum hydropiper, Eichhornia crassipes and Euryale ferox. There was a distinct correlation in the variation of major sediment physicochemical parameters with change in macrophyte community compositions. Quantitative estimation revealed an almost even accumulation of nitrate and nitrite in the sediment samples dominated by the plant species Eichhornia crassipes, Nymphaea alba, Hydrilla verticillata, Vallisneria spiralis, Euryale ferox and Monochoria hastaefolia, which might have signified a stable nitrification and denitrification process in the sites dominated by the selected aquatic plants. This was further examined by a systematic analysis of microbial populations through culture dependent and independent approach. Culture-dependent bacterial community study revealed the higher population of nitrifiers and denitrifiers in the sediment samples dominated by the six macrophyte species. However, culture-independent study with bacterial 16S rDNA V3-V4 metagenome sequencing revealed the overall similar type of bacterial phylum in all the sediment samples collected during the study. Thus, there might be the possibility of uneven distribution of nitrifying and denitrifying molecular markers among the sediment samples collected during the investigation. The diversity and abundance of the nitrifying and denitrifying molecular markers in the sediment samples are under investigation. Thus, the role of different aquatic plant functional types in microorganism mediated nitrogen cycle coupling could be screened out further from the present initial investigation.

Keywords: denitrification, macrophyte, metagenome, microorganism, nitrification

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Authors: Angelis P. Barlampas

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Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

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Authors: M. Trousselard, D. Steiler, C. Drogou, P. van-Beers, G. Lamour, S. N. Crosnier, O. Bouilland, P. Dubost, M. Chennaoui, D. Léger

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According to published data, undersea navigation for long periods (nuclear-powered ballistic missile submarine, SSBN) constitutes an extreme environment in which crews are subjected to multiple stresses, including the absence of natural light, illuminance below 1,000 lux, and watch schedules that do not respect natural chronobiological rhythms, for a period of 60-80 days. These stresses seem clearly detrimental to the submariners’ sleep, with consequences for their affective (seasonal affective disorder-like) and cognitive functioning. In the long term, there are abundant publications regarding the consequences of sleep disruption for the occurrence of organic cardiovascular, metabolic, immunological or malignant diseases. It seems essential to propose countermeasures for the duration of the patrol in order to reduce the negative physiological effects on the sleep and mood of submariners. Light therapy, the preferred treatment for dysfunctions of the internal biological clock and the resulting seasonal depression, cannot be used without data to assist knowledge of submariners’ chronobiology (melatonin secretion curve) during patrols, given the unusual characteristics of their working environment. These data are not available in the literature. The aim of this project was to assess, in the course of two studies, the benefits of two environmental techniques for managing chronobiological stress: techniques for optimizing potential (TOP; study 1)3, an existing programme to help in the psychophysiological regulation of stress and sleep in the armed forces, and dawn and dusk simulators (DDS, study 2). For each experiment, psychological, physiological (sleep) or biological (melatonin secretion) data were collected on D20 and D50 of patrol. In the first experiment, we studied sleep and depressive distress in 19 submariners in an operational setting on board an SSBM during a first patrol, and assessed the impact of TOP on the quality of sleep and depressive distress in these same submariners over the course of a second patrol. The submariners were trained in TOP between the two patrols for a 2-month period, at a rate of 1 h of training per week, and assigned daily informal exercises. Results show moderate disruptions in sleep pattern and duration associated with the intensity of depressive distress. The use of TOP during the following patrol improved sleep and depressive mood only in submariners who regularly practiced the techniques. In light of these limited benefits, we assessed, in a second experiment, the benefits of DDS on chronobiology (daily secretion of melatonin) and depressive distress. Ninety submariners were randomly allocated to two groups, group 1 using DDS daily, and group 2 constituting the control group. Although the placebo effect was not controlled, results showed a beneficial effect on chronobiology and depressive mood for submariners with a morning chronotype. Conclusions: These findings demonstrate the difficulty of practicing the tools of psychophysiological management in real life. They raise the question of the subjects’ autonomy with respect to using aids that involve regular practice. It seems important to study autonomy in future studies, as a cognitive resource resulting from the interaction between internal positive resources and “coping” resources, to gain a better understanding of compliance problems.

Keywords: chronobiology, light therapy, seasonal affective disorder, sleep, stress, stress management, submarine

Procedia PDF Downloads 423

Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

Procedia PDF Downloads 87

Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Danjuma Bawa

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This paper aimed at exploring the capabilities of Location-Allocation model in complementing the strides of the existing physical planning models in the location and distribution of facilities for regional consumption. The paper was designed to provide a blueprint to the Nigerian government and other donor agencies especially the Fertilizer Distribution Initiative (FDI) by the federal government for the revitalization of the terrorism ravaged regions. Theoretical underpinnings of central place theory related to spatial distribution, interrelationships, and threshold prerequisites were reviewed. The study showcased how Location-Allocation Model (L-AM) alongside Central Place Theory (CPT) was applied in Geographic Information System (GIS) environment to; map and analyze the spatial distribution of settlements; exploit their physical and economic interrelationships, and to explore their hierarchical and opportunistic influences. The study was purely spatial qualitative research which largely used secondary data such as; spatial location and distribution of settlements, population figures of settlements, network of roads linking them and other landform features. These were sourced from government ministries and open source consortium. GIS was used as a tool for processing and analyzing such spatial features within the dictum of CPT and L-AM to produce a comprehensive spatial digital plan for equitable and judicious location and distribution of fertilizer deports in the study area in an optimal way. Population threshold was used as yardstick for selecting suitable settlements that could stand as service centers to other hinterlands; this was accomplished using the query syntax in ArcMapTM. ArcGISTM’ network analyst was used in conducting location-allocation analysis for apportioning of groups of settlements around such service centers within a given threshold distance. Most of the techniques and models ever used by utility planners have been centered on straight distance to settlements using Euclidean distances. Such models neglect impedance cutoffs and the routing capabilities of networks. CPT and L-AM take into consideration both the influential characteristics of settlements and their routing connectivity. The study was undertaken in two terrorism ravaged Local Government Areas of Adamawa state. Four (4) existing depots in the study area were identified. 20 more depots in 20 villages were proposed using suitability analysis. Out of the 300 settlements mapped in the study area about 280 of such settlements where optimally grouped and allocated to the selected service centers respectfully within 2km impedance cutoff. This study complements the giant strides by the federal government of Nigeria by providing a blueprint for ensuring proper distribution of these public goods in the spirit of bringing succor to these terrorism ravaged populace. This will ardently at the same time help in boosting agricultural activities thereby lowering food shortage and raising per capita income as espoused by the government.

Keywords: central place theory, GIS, location-allocation, network analysis, urban and regional planning, welfare economics

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Authors: Valerie Porr, Sydney A. DeCaro

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TARA for borderline personality disorder (BPD), an education and advocacy organization, helps families to compassionately and effectively deal with troubling BPD behaviors. Our psychoeducational programs focus on understanding underlying neurobiological features of BPD and evidence-based methodology integrating dialectical behavior therapy (DBT) and mentalization based therapy (MBT,) clarifying the inherent misunderstanding of BPD behaviors and improving family communication. TARA4BPD conducts online surveys, workshops, and topical webinars. For over 25 years, we have collected data from BPD helpline callers. This data drew our attention to particular childhood idiosyncrasies that seem to characterize many of the children who later met the criteria for BPD. The idiosyncrasies we observed, heightened sensory sensitivity and hypervigilance, were included in Adolf Stern’s 1938 definition of “Borderline.” This aspect of BPD has not been prioritized by personality disorder researchers, presently focused on emotion processing and social cognition in BPD. Parents described sleep reversal problems in infants who, early on, seem to exhibit dysregulation in circadian rhythm. Families describe children as supersensitive to sensory sensations, such as specific sounds, heightened sense of smell, taste, textures of foods, and an inability to tolerate various fabrics textures (i.e., seams in socks). They also exhibit high sensitivity to particular words and voice tones. Many have alexithymia and dyslexia. These children are either hypo- or hypersensitive to sensory sensations, including pain. Many suffer from fibromyalgia. BPD reactions to pain have been studied (C. Schmahl) and confirm the existence of hyper and hypo-reactions to pain stimuli in people with BPD. To date, there is little or no data regarding what comprises a normative range of sensitivity in infants and children. Many parents reported that their children were tested or treated for sensory processing disorder (SPD), learning disorders, and ADHD. SPD is not included in the DSM and is treated by occupational therapists. The overwhelming anecdotal data from thousands of parents of children who later met criteria for BPD led TARA4BPD to develop a sensitivity survey to develop evidence of the possible role of early sensory perception problems as a pre-cursor to BPD, hopefully initiating new directions in BPD research. At present, the research community seems unaware of the role supersensory sensitivity might play as an early indicator of BPD. Parents' observations of childhood sensitivity obtained through family interviews and results of an extensive online survey on sensory responses across various ages of development will be presented. People with BPD suffer from a sense of isolation and otherness that often results in later interpersonal difficulties. Early identification of supersensitive children while brain circuits are developing might decrease the development of social interaction deficits such as rejection sensitivity, self-referential processes, and negative bias, hallmarks of BPD, ultimately minimizing the maladaptive methods of coping with distress that characterizes BPD. Family experiences are an untapped resource for BPD research. It is hoped that this data will give family observations the critical credibility to inform future treatment and research directions.

Keywords: alexithymia, dyslexia, hypersensitivity, sensory processing disorder

Procedia PDF Downloads 176

Authors: Kylie Mueller, Nijole Bernaitis, Shailendra Anoopkumar-Dukie

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Background: Vitamin K antagonists particularly warfarin is the most frequently used oral medication for deep vein thrombosis (DVT) treatment and prophylaxis. Time in therapeutic range (TITR) of the international normalised ratio (INR) is widely accepted as a measure to assess the quality of warfarin therapy. Multiple factors can affect warfarin control and the subsequent adverse outcomes including thromboembolic and bleeding events. Predictor models have been developed to assess potential contributing factors and measure the individual risk of these adverse events. These predictive models have been validated in atrial fibrillation (AF) patients, however, there is a lack of literature on whether these can be successfully applied to other warfarin users including DVT patients. Therefore, the aim of the study was to assess the ability of these risk models (HAS BLED and CHADS2) to predict haemorrhagic and ischaemic incidences in DVT patients treated with warfarin. Methods: A retrospective analysis of DVT patients receiving warfarin management by a private pathology clinic was conducted. Data was collected from November 2007 to September 2014 and included demographics, medical and drug history, INR targets and test results. Patients receiving continuous warfarin therapy with an INR reference range between 2.0 and 3.0 were included in the study with mean TITR calculated using the Rosendaal method. Bleeding and thromboembolic events were recorded and reported as incidences per patient. The haemorrhagic risk model HAS BLED and ischaemic risk model CHADS2 were applied to the data. Patients were then stratified into either the low, moderate, or high-risk categories. The analysis was conducted to determine if a correlation existed between risk assessment tool and patient outcomes. Data was analysed using GraphPad Instat Version 3 with a p value of <0.05 considered to be statistically significant. Patient characteristics were reported as mean and standard deviation for continuous data and categorical data reported as number and percentage. Results: Of the 533 patients included in the study, there were 268 (50.2%) female and 265 (49.8%) male patients with a mean age of 62.5 years (±16.4). The overall mean TITR was 78.3% (±12.7) with an overall haemorrhagic incidence of 0.41 events per patient. For the HAS BLED model, there was a haemorrhagic incidence of 0.08, 0.53, and 0.54 per patient in the low, moderate and high-risk categories respectively showing a statistically significant increase in incidence with increasing risk category. The CHADS2 model showed an increase in ischaemic events according to risk category with no ischaemic events in the low category, and an ischaemic incidence of 0.03 in the moderate category and 0.47 high-risk categories. Conclusion: An increasing haemorrhagic incidence correlated to an increase in the HAS BLED risk score in DVT patients treated with warfarin. Furthermore, a greater incidence of ischaemic events occurred in patients with an increase in CHADS2 category. In an Australian population of DVT patients, the HAS BLED and CHADS2 accurately predicts incidences of haemorrhage and ischaemic events respectively.

Keywords: anticoagulant agent, deep vein thrombosis, risk assessment, warfarin

Procedia PDF Downloads 244

Authors: Nebojsa Stefanovic, Sasa Milijic, Natasa Danilovic Hristic

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Spatial plan of the special purpose area constitutes a basic tool in the planning of infrastructure corridor of a highway. The aim of the plan is to define the planning basis and provision of spatial conditions for the construction and operation of the highway, as well as for developing other infrastructure systems in the corridor. This paper presents a methodology and approach to the preparation of the Spatial Plan for the special purpose area for the infrastructure corridor of the highway E-80, Section Niš-Merdare in Serbia. The applied methodological approach is based on the combined application of the integrative and participatory method in the decision-making process on the sustainable development of the highway corridor. It was found that, for the planning and management of the infrastructure corridor, a key problem is coordination of spatial and urban planning, strategic environmental assessment and sectoral traffic planning and designing. Through the development of the plan, special attention is focused on increasing the accessibility of the local and regional surrounding, reducing the adverse impacts on the development of settlements and the economy, protection of natural resources, natural and cultural heritage, and the development of other infrastructure systems in the corridor of the highway. As a result of the applied methodology, this paper analyzes the basic features such as coverage, the concept, protected zones, service facilities and objects, the rules of development and construction, etc. Special emphasis is placed to methodology and results of the Strategic Environmental Assessment of the Spatial Plan, and to the importance of protection measures, with the special significance of air and noise protection measures. For evaluation in the Strategic Environmental Assessment, a multicriteria expert evaluation (semi-quantitative method) of planned solutions was used in relation to the set of goals and relevant indicators, based on the basic set of indicators of sustainable development. Evaluation of planned solutions encompassed the significance and size, spatial conditions and probability of the impact of planned solutions on the environment, and the defined goals of strategic assessment. The framework of the implementation of the Spatial Plan is presented, which is determined for the simultaneous elaboration of planning solutions at two levels: the strategic level of the spatial plan and detailed urban plan level. It is also analyzed the relationship of the Spatial Plan to other applicable planning documents for the planning area. The effects of this methodological approach relate to enabling integrated planning of the sustainable development of the infrastructure corridor of the highway and its surrounding area, through coordination of spatial, urban and sectoral traffic planning and design, as well as the participation of all key actors in the adoption and implementation of planned decisions. By the conclusions of the paper, it is pointed to the direction for further research, particularly in terms of harmonizing methodology of planning documentation and preparation of technical-design documentation.

Keywords: corridor, environment, highway, impact, methodology, spatial plan, urban

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Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

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Authors: M. B. Atui, A. M. Silva, M. A. M. Marciano, M. I. Fioravanti, V. A. Franco, L. B. Chasin, A. R. Ferreira, M. D. Nogueira

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Fungi attack large amount of fruits and those who have suffered an injury on the surface are more susceptible to the growth, as they have pectinolytic enzymes that destroy the edible portion forming an amorphous and soft dough. The spores can reach the plant by the wind, rain and insects and fruit may have on its surface, besides the contaminants from the fruit trees, land and water, forming a flora composed mainly of yeasts and molds. Other contamination can occur for the equipment used to harvest, for the use of boxes and contaminated water to the fruit washing, for storage in dirty places. The hyphae in tomato products indicate the use of raw materials contaminated or unsuitable hygiene conditions during processing. Although fungi are inactivated in heat processing step, its hyphae remain in the final product and search for detection and quantification is an indicator of the quality of raw material. Howard Method count of fungi mycelia in industrialized pulps evaluates the amount of decayed fruits existing in raw material. The Brazilian legislation governing processed and packaged products set the limit of 40% of positive fields in tomato pulps. The aim of this study was to evaluate the quality of the tomato pulp sold in greater São Paulo, through a monitoring during the four seasons of the year. All over 2010, 110 samples have been examined; 21 were taking in spring, 31 in summer, 31 in fall and 27 in winter, all from different lots and trademarks. Samples have been picked up in several stores located in the city of São Paulo. Howard method was used, recommended by the AOAC, 19th ed, 2011 16:19:02 technique - method 965.41. Hundred percent of the samples contained fungi mycelia. The count average of fungi mycelia per season was 23%, 28%, 8,2% and 9,9% in spring, summer, fall and winter, respectively. Regarding the spring samples of the 21 samples analyzed, 14.3% were off-limits proposed by the legislation. As for the samples of the fall and winter, all were in accordance with the legislation and the average of mycelial filament count has not exceeded 20%, which can be explained by the low temperatures during this time of the year. The acquired samples in the summer and spring showed high percentage of fungal mycelium in the final product, related to the high temperatures in these seasons. Considering that the limit of 40% of positive fields is accepted for the Brazilian Legislation (RDC nº 14/2014), 3 spring samples (14%) and 6 summer samples (19%) will be over this limit and subject to law penalties. According to gathered data, 82% of manufacturers of this product manage to keep acceptable levels of fungi mycelia in their product. In conclusion, only 9.2% samples were for the limits established by Resolution RDC. 14/2014, showing that the limit of 40% is feasible and can be used by these segment industries. The result of the filament count mycelial by Howard method is an important tool in the microscopic analysis since it measures the quality of raw material used in the production of tomato products.

Keywords: fungi, howard, method, tomato, pulps

Procedia PDF Downloads 356

Authors: Hisham Arab Alkabeya, A. M. Hughes, J. Adams

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Background: People with Rheumatoid Arthritis (RA) continue to experience problems with hand function despite new drug advances and targeted medical treatment. Consequently, it is important to identify the factors that influence the impact of RA disease on hand function. This systematic review identified observational studies that reported factors that influenced the impact of RA on hand function. Methods: MEDLINE, EMBASE, CINAL, AMED, PsychINFO, and Web of Science database were searched from January 1990 up to March 2017. Full-text articles published in English that described factors related to hand functional disability in people with RA were selected following predetermined inclusion and exclusion criteria. Pertinent data were thoroughly extracted and documented using a pre-designed data extraction form by the lead author, and cross-checked by the review team for completion and accuracy. Factors related to hand function were classified under the domains of the International Classification of Functioning, Disability, and Health (ICF) framework and health-related factors. Three reviewers independently assessed the methodological quality of the included articles using the quality of cross-sectional studies (AXIS) tool. Factors related to hand function that was investigated in two or more studies were explored using a best-evidence synthesis. Results: Twenty articles form 19 studies met the inclusion criteria from 1,271 citations; all presented cross-sectional data (five high quality and 15 low quality studies), resulting in at best limited evidence in the best-evidence synthesis. For the factors classified under the ICF domains, the best-evidence synthesis indicates that there was a range of body structure and function factors that were related with hand functional disability. However, key factors were hand strength, disease activity, and pain intensity. Low functional status (physical, emotional and social) level was found to be related with limited hand function. For personal factors, there is limited evidence that gender is not related with hand function; whereas, conflicting evidence was found regarding the relationship between age and hand function. In the domain of environmental factors, there was limited evidence that work activity was not related with hand function. Regarding health-related factors, there was limited evidence that the level of the rheumatoid factor (RF) was not related to hand function. Finally, conflicting evidence was found regarding the relationship between hand function and disease duration and general health status. Conclusion: Studies focused on body structure and function factors, highlighting a lack of investigation into personal and environmental factors when considering the impact of RA on hand function. The level of evidence which exists was limited, but identified that modifiable factors such as grip or pinch strength, disease activity and pain are the most influential factors on hand function in people with RA. The review findings suggest that important personal and environmental factors that impact on hand function in people with RA are not yet considered or reported in clinical research. Well-designed longitudinal, preferably cohort, studies are now needed to better understand the causality between personal and environmental factors and hand functional disability in people with RA.

Keywords: factors, hand function, rheumatoid arthritis, systematic review

Procedia PDF Downloads 124

Authors: Aya Al Masri, Kamel Guerchouche, Youssef Laynaoui, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: Mobile C-arms move throughout operating rooms of the operating theater. Being designed to move between rooms, they are not equipped with relays to retrieve the exposition information and export it outside the room. Therefore, no light signaling is available outside the room to warn the X-ray emission for staff. Inadvertent exposition of staff outside the operating theater is a real problem for radiation protection. The French standard NFC 15-160 require that: (1) access to any room containing an X-ray emitting device must be controlled by a light signage so that it cannot be inadvertently crossed, and (2) setting up an emergency button to stop the X-ray emission. This study presents a system that we developed to meet these requirements and the results of its clinical test. Materials and methods: The system is composed of two communicating boxes: o The "DetectBox" is to be installed inside the operating theater. It identifies the various operation states of the C-arm by analyzing its power supply signal. The DetectBox communicates (in wireless mode) with the second box (AlertBox). o The "AlertBox" can operate in socket or battery mode and is to be installed outside the operating theater. It detects and reports the state of the C-arm by emitting a real time light signal. This latter can have three different colors: red when the C-arm is emitting X-rays, orange when it is powered on but does not emit X-rays, and green when it is powered off. The two boxes communicate on a radiofrequency link exclusively carried out in the ‘Industrial, Scientific and Medical (ISM)’ frequency bands and allows the coexistence of several on-site warning systems without communication conflicts (interference). Taking into account the complexity of performing electrical works in the operating theater (for reasons of hygiene and continuity of medical care), this system (having a size <10 cm²) works in complete safety without any intrusion in the mobile C-arm and does not require specific electrical installation work. The system is equipped with emergency button that stops X-ray emission. The system has been clinically tested. Results: The clinical test of the system shows that: it detects X-rays having both high and low energy (50 – 150 kVp), high and low photon flow (0.5 – 200 mA: even when emitted for a very short time (<1 ms)), Probability of false detection < 10-5, it operates under all acquisition modes (continuous, pulsed, fluoroscopy mode, image mode, subtraction and movie mode), it is compatible with all C-arm models and brands. We have also tested the communication between the two boxes (DetectBox and AlertBox) in several conditions: (1) Unleaded room, (2) leaded room, and (3) rooms with particular configuration (sas, great distances, concrete walls, 3 mm of lead). The result of these last tests was positive. Conclusion: This system is a reliable tool to alert the staff present outside the operating room for X-ray emission and insure their radiation protection.

Keywords: Clinical test, Inadvertent staff exposition, Light signage, Operating theater

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

Procedia PDF Downloads 93

Authors: Karim Hrratha, Khaled Essalahb, Christophe Morellc, Henry Chermettec, Salima Boughdiria

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Among the carbon-carbon bond formation types, allylation of active methylene compounds with cyclic Baylis-Hillman (BH) alcohols is a reliable and widely used method. This reaction is a very attractive tool in organic synthesis of biological and biodiesel compounds. Thus, in view of an insistent and peremptory request for an efficient and straightly method for synthesizing the desired product, a thorough analysis of various aspects of the reaction processes is an important task. The product afforded by the reaction of active methylene with BH alcohols depends largely on the experimental conditions, notably on the catalyst properties. All experiments reported that catalysis is needed for this reaction type because of the poor ability of alcohol hydroxyl group to be as a suitable leaving group. Within the catalysts, several transition- metal based have been used such as palladium in the presence of acid or base and have been considered as reliable methods. Furthemore, acid catalysts such as BF3.OEt2, BiX3 (X= Cl, Br, I, (OTf)3), InCl3, Yb(OTf)3, FeCl3, p-TsOH and H-montmorillonite have been employed to activate the C-C bond formation through the alkylation of active methylene compounds. Interestingly a report of a smoothly process for the ability of 4-imethyaminopyridine(DMAP) to catalyze the allylation reaction of active methylene compounds with cyclic Baylis-Hillman (BH) alcohol appeared recently. However, the reaction mechanism remains ambiguous, since the C- allylation process leads to an unexpected product (noted P1), corresponding to a direct allylation instead of conjugate allylation, which involves the most electrophilic center according to the electron withdrawing group CO effect. The main objective of the present theoretical study is to better understand the role of the DMAP catalytic activity as well as the process leading to the end- product (P1) for the catalytic reaction of a cyclic BH alcohol with active methylene compounds. For that purpose, we have carried out computations of a set of active methylene compounds varying by R1 and R2 toward the same alcohol, and we have attempted to rationalize the mechanisms thanks to the acid–base approach, and conceptual DFT tools such as chemical potential, hardness, Fukui functions, electrophilicity index and dual descriptor, as these approaches have shown a good prediction of reactions products.The present work is then organized as follows: In a first part some computational details will be given, introducing the reactivity indexes used in the present work, then Section 3 is dedicated to the discussion of the prediction of the selectivity and regioselectivity. The paper ends with some concluding remarks. In this work, we have shown, through DFT method at the B3LYP/6-311++G(d,p) level of theory that: The allylation of active methylene compounds with cyclic BH alcohol is governed by orbital control character. Hence the end- product denoted P1 is generated by direct allylation.

Keywords: DFT calculation, gas phase pKa, theoretical mechanism, orbital control, charge control, Fukui function, transition state

Procedia PDF Downloads 270