Search results for: anatolian traditional medicine
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6111

Search results for: anatolian traditional medicine

1161 Arsenic (III) Removal by Zerovalent Iron Nanoparticles Synthesized with the Help of Tea Liquor

Authors: Tulika Malviya, Ritesh Chandra Shukla, Praveen Kumar Tandon

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Traditional methods of synthesis are hazardous for the environment and need nature friendly processes for the treatment of industrial effluents and contaminated water. Use of plant parts for the synthesis provides an efficient alternative method. In this paper, we report an ecofriendly and nonhazardous biobased method to prepare zerovalent iron nanoparticles (ZVINPs) using the liquor of commercially available tea. Tea liquor as the reducing agent has many advantages over other polymers. Unlike other polymers, the polyphenols present in tea extract are nontoxic and water soluble at room temperature. In addition, polyphenols can form complexes with metal ions and thereafter reduce the metals. Third, tea extract contains molecules bearing alcoholic functional groups that can be exploited for reduction as well as stabilization of the nanoparticles. Briefly, iron nanoparticles were prepared by adding 2.0 g of montmorillonite K10 (MMT K10) to 5.0 mL of 0.10 M solution of Fe(NO3)3 to which an equal volume of tea liquor was then added drop wise over 20 min with constant stirring. The color of the mixture changed from whitish yellow to black, indicating the formation of iron nanoparticles. The nanoparticles were adsorbed on montmorillonite K10, which is safe and aids in the separation of hazardous arsenic species simply by filtration. Particle sizes ranging from 59.08±7.81 nm were obtained which is confirmed by using different instrumental analyses like IR, XRD, SEM, and surface area studies. Removal of arsenic was done via batch adsorption method. Solutions of As(III) of different concentrations were prepared by diluting the stock solution of NaAsO2 with doubly distilled water. The required amount of in situ prepared ZVINPs supported on MMT K10 was added to a solution of desired strength of As (III). After the solution had been stirred for the preselected time, the solid mass was filtered. The amount of arsenic [in the form of As (V)] remaining in the filtrate was measured using ion chromatograph. Stirring of contaminated water with zerovalent iron nanoparticles supported on montmorillonite K10 for 30 min resulted in up to 99% removal of arsenic as As (III) from its solution at both high and low pH (2.75 and 11.1). It was also observed that, under similar conditions, montmorillonite K10 alone provided only <10% removal of As(III) from water. Adsorption at low pH with precipitation at higher pH has been proposed for As(III) removal.

Keywords: arsenic removal, montmorillonite K10, tea liquor, zerovalent iron nanoparticles

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1160 Optimizing Weight Loss with AI (GenAISᵀᴹ): A Randomized Trial of Dietary Supplement Prescriptions in Obese Patients

Authors: Evgeny Pokushalov, Andrey Ponomarenko, John Smith, Michael Johnson, Claire Garcia, Inessa Pak, Evgenya Shrainer, Dmitry Kudlay, Sevda Bayramova, Richard Miller

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Background: Obesity is a complex, multifactorial chronic disease that poses significant health risks. Recent advancements in artificial intelligence (AI) offer the potential for more personalized and effective dietary supplement (DS) regimens to promote weight loss. This study aimed to evaluate the efficacy of AI-guided DS prescriptions compared to standard physician-guided DS prescriptions in obese patients. Methods: This randomized, parallel-group pilot study enrolled 60 individuals aged 40 to 60 years with a body mass index (BMI) of 25 or greater. Participants were randomized to receive either AI-guided DS prescriptions (n = 30) or physician-guided DS prescriptions (n = 30) for 180 days. The primary endpoints were the percentage change in body weight and the proportion of participants achieving a ≥5% weight reduction. Secondary endpoints included changes in BMI, fat mass, visceral fat rating, systolic and diastolic blood pressure, lipid profiles, fasting plasma glucose, hsCRP levels, and postprandial appetite ratings. Adverse events were monitored throughout the study. Results: Both groups were well balanced in terms of baseline characteristics. Significant weight loss was observed in the AI-guided group, with a mean reduction of -12.3% (95% CI: -13.1 to -11.5%) compared to -7.2% (95% CI: -8.1 to -6.3%) in the physician-guided group, resulting in a treatment difference of -5.1% (95% CI: -6.4 to -3.8%; p < 0.01). At day 180, 84.7% of the AI-guided group achieved a weight reduction of ≥5%, compared to 54.5% in the physician-guided group (Odds Ratio: 4.3; 95% CI: 3.1 to 5.9; p < 0.01). Significant improvements were also observed in BMI, fat mass, and visceral fat rating in the AI-guided group (p < 0.01 for all). Postprandial appetite suppression was greater in the AI-guided group, with significant reductions in hunger and prospective food consumption, and increases in fullness and satiety (p < 0.01 for all). Adverse events were generally mild-to-moderate, with higher incidences of gastrointestinal symptoms in the AI-guided group, but these were manageable and did not impact adherence. Conclusion: The AI-guided dietary supplement regimen was more effective in promoting weight loss, improving body composition, and suppressing appetite compared to the physician-guided regimen. These findings suggest that AI-guided, personalized supplement prescriptions could offer a more effective approach to managing obesity. Further research with larger sample sizes is warranted to confirm these results and optimize AI-based interventions for weight loss.

Keywords: obesity, AI-guided, dietary supplements, weight loss, personalized medicine, metabolic health, appetite suppression

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1159 Lead Chalcogenide Quantum Dots for Use in Radiation Detectors

Authors: Tom Nakotte, Hongmei Luo

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Lead chalcogenide-based (PbS, PbSe, and PbTe) quantum dots (QDs) were synthesized for the purpose of implementing them in radiation detectors. Pb based materials have long been of interest for gamma and x-ray detection due to its high absorption cross section and Z number. The emphasis of the studies was on exploring how to control charge carrier transport within thin films containing the QDs. The properties of QDs itself can be altered by changing the size, shape, composition, and surface chemistry of the dots, while the properties of carrier transport within QD films are affected by post-deposition treatment of the films. The QDs were synthesized using colloidal synthesis methods and films were grown using multiple film coating techniques, such as spin coating and doctor blading. Current QD radiation detectors are based on the QD acting as fluorophores in a scintillation detector. Here the viability of using QDs in solid-state radiation detectors, for which the incident detectable radiation causes a direct electronic response within the QD film is explored. Achieving high sensitivity and accurate energy quantification in QD radiation detectors requires a large carrier mobility and diffusion lengths in the QD films. Pb chalcogenides-based QDs were synthesized with both traditional oleic acid ligands as well as more weakly binding oleylamine ligands, allowing for in-solution ligand exchange making the deposition of thick films in a single step possible. The PbS and PbSe QDs showed better air stability than PbTe. After precipitation the QDs passivated with the shorter ligand are dispersed in 2,6-difloupyridine resulting in colloidal solutions with concentrations anywhere from 10-100 mg/mL for film processing applications, More concentrated colloidal solutions produce thicker films during spin-coating, while an extremely concentrated solution (100 mg/mL) can be used to produce several micrometer thick films using doctor blading. Film thicknesses of micrometer or even millimeters are needed for radiation detector for high-energy gamma rays, which are of interest for astrophysics or nuclear security, in order to provide sufficient stopping power.

Keywords: colloidal synthesis, lead chalcogenide, radiation detectors, quantum dots

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1158 Chemical Synthesis, Characterization and Dose Optimization of Chitosan-Based Nanoparticles of MCPA for Management of Broad-Leaved Weeds (Chenopodium album, Lathyrus aphaca, Angalis arvensis and Melilotus indica) of Wheat

Authors: Muhammad Ather Nadeem, Bilal Ahmad Khan, Tasawer Abbas

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Nanoherbicides utilize nanotechnology to enhance the delivery of biological or chemical herbicides using combinations of nanomaterials. The aim of this research was to examine the efficacy of chitosan nanoparticles containing MCPA herbicide as a potential eco-friendly alternative for weed control in wheat crops. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and ultraviolet absorbance were used to analyze the developed nanoparticles. The SEM analysis indicated that the average size of the particles was 35 nm, forming clusters with a porous structure. Both nanoparticles of fluroxyper + MCPA exhibited maximal absorption peaks at a wavelength of 320 nm. The compound fluroxyper +MCPA has a strong peak at a 2θ value of 30.55°, which correlates to the 78 plane of the anatase phase. The weeds, including Chenopodium album, Lathyrus aphaca, Angalis arvensis, and Melilotus indica, were sprayed with the nanoparticles while they were in the third or fourth leaf stage. There were seven distinct dosages used: doses (D0 (Check weeds), D1 (Recommended dose of traditional herbicide, D2 (Recommended dose of Nano-herbicide (NPs-H)), D3 (NPs-H with 05-fold lower dose), D4 ((NPs-H) with 10-fold lower dose), D5 (NPs-H with 15-fold lower dose), and D6 (NPs-H with 20-fold lower dose)). The chitosan-based nanoparticles of MCPA at the prescribed dosage of conventional herbicide resulted in complete death and visual damage, with a 100% fatality rate. The dosage that was 5-fold lower exhibited the lowest levels of plant height (3.95 cm), chlorophyll content (5.63%), dry biomass (0.10 g), and fresh biomass (0.33 g) in the broad-leaved weed of wheat. The herbicide nanoparticles, when used at a dosage 10-fold lower than that of conventional herbicides, had a comparable impact on the prescribed dosage. Nano-herbicides have the potential to improve the efficiency of standard herbicides by increasing stability and lowering toxicity.

Keywords: mortality, visual injury, chlorophyl contents, chitosan-based nanoparticles

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1157 Adaptive Process Monitoring for Time-Varying Situations Using Statistical Learning Algorithms

Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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1156 Some Considerations about the Theory of Spatial-Motor Thinking Applied to a Traditional Fife Band in Brazil

Authors: Murilo G. Mendes

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This text presents part of the results presented in the Ph.D. thesis that has used John Baily's theory and method as well as its ethnographic application in the context of the fife flutes of the Banda Cabaçal dos Irmãos Aniceto in the state of Ceará, northeast of Brazil. John Baily is a British ethnomusicologist dedicated to studying the relationships between music, musical gesture, and embodied cognition. His methodology became a useful tool to highlight historical-social aspects present in the group's instrumental music. Remaining indigenous and illiterate, these musicians played and transmitted their music from generation to generation, for almost two hundred years, without any nomenclature or systematization of the fingering performed on the flute. In other words, his music, free from any theorization, is learned, felt, perceived, and processed directly through hearing and through the relationship between the instrument's motor skills and its sound result. For this reason, Baily's assumptions became fundamental in the analysis processes. As the author's methodology recommends, classes were held with the natives and provided technical musical learning and some important concepts. Then, transcriptions and analyses of musical aspects were made from patterns of movement on the instrument incorporated by repetitions and/or by the intrinsic facility of the instrument. As a result, it was discovered how the group reconciled its indigenous origins with the demand requested by the public power and the interests of the local financial elite from the mid-twentieth century. The article is structured from the cultural context of the group, where local historical and social aspects influence the social and musical practices of the group. Then, will be present the methodological conceptions of John Baily and, finally, their application in the music of the Irmãos Aniceto. The conclusion points to the good results of identifying, through this methodology and analysis, approximations between discourse, historical-social factors, and musical text. Still, questions are raised about its application in other contexts.

Keywords: Banda Cabaçal dos Irmãos Aniceto, John Baily, pífano, spatial-motor thinking

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1155 A Topology-Based Dynamic Repair Strategy for Enhancing Urban Road Network Resilience under Flooding

Authors: Xuhui Lin, Qiuchen Lu, Yi An, Tao Yang

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As global climate change intensifies, extreme weather events such as floods increasingly threaten urban infrastructure, making the vulnerability of urban road networks a pressing issue. Existing static repair strategies fail to adapt to the rapid changes in road network conditions during flood events, leading to inefficient resource allocation and suboptimal recovery. The main research gap lies in the lack of repair strategies that consider both the dynamic characteristics of networks and the progression of flood propagation. This paper proposes a topology-based dynamic repair strategy that adjusts repair priorities based on real-time changes in flood propagation and traffic demand. Specifically, a novel method is developed to assess and enhance the resilience of urban road networks during flood events. The method combines road network topological analysis, flood propagation modelling, and traffic flow simulation, introducing a local importance metric to dynamically evaluate the significance of road segments across different spatial and temporal scales. Using London's road network and rainfall data as a case study, the effectiveness of this dynamic strategy is compared to traditional and Transport for London (TFL) strategies. The most significant highlight of the research is that the dynamic strategy substantially reduced the number of stranded vehicles across different traffic demand periods, improving efficiency by up to 35.2%. The advantage of this method lies in its ability to adapt in real-time to changes in network conditions, enabling more precise resource allocation and more efficient repair processes. This dynamic strategy offers significant value to urban planners, traffic management departments, and emergency response teams, helping them better respond to extreme weather events like floods, enhance overall urban resilience, and reduce economic losses and social impacts.

Keywords: Urban resilience, road networks, flood response, dynamic repair strategy, topological analysis

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1154 Increased Energy Efficiency and Improved Product Quality in Processing of Lithium Bearing Ores by Applying Fluidized-Bed Calcination Systems

Authors: Edgar Gasafi, Robert Pardemann, Linus Perander

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For the production of lithium carbonate or hydroxide out of lithium bearing ores, a thermal activation (calcination/decrepitation) is required for the phase transition in the mineral to enable an acid respectively soda leaching in the downstream hydrometallurgical section. In this paper, traditional processing in Lithium industry is reviewed, and opportunities to reduce energy consumption and improve product quality and recovery rate will be discussed. The conventional process approach is still based on rotary kiln calcination, a technology in use since the early days of lithium ore processing, albeit not significantly further developed since. A new technology, at least for the Lithium industry, is fluidized bed calcination. Decrepitation of lithium ore was investigated at Outotec’s Frankfurt Research Centre. Focusing on fluidized bed technology, a study of major process parameters (temperature and residence time) was performed at laboratory and larger bench scale aiming for optimal product quality for subsequent processing. The technical feasibility was confirmed for optimal process conditions on pilot scale (400 kg/h feed input) providing the basis for industrial process design. Based on experimental results, a comprehensive Aspen Plus flow sheet simulation was developed to quantify mass and energy flow for the rotary kiln and fluidized bed system. Results show a significant reduction in energy consumption and improved process performance in terms of temperature profile, product quality and plant footprint. The major conclusion is that a substantial reduction of energy consumption can be achieved in processing Lithium bearing ores by using fluidized bed based systems. At the same time and different from rotary kiln process, an accurate temperature and residence time control is ensured in fluidized-bed systems leading to a homogenous temperature profile in the reactor which prevents overheating and sintering of the solids and results in uniform product quality.

Keywords: calcination, decrepitation, fluidized bed, lithium, spodumene

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1153 Investigation and Comprehensive Benefit Analysis of 11 Typical Polar-Based Agroforestry Models Based on Analytic Hierarchy Process in Anhui Province, Eastern China

Authors: Zhihua Cao, Hongfei Zhao, Zhongneng Wu

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The development of polar-based agroforestry was necessary due to the influence of the timber market environment in China, which can promote the coordinated development of forestry and agriculture, and gain remarkable ecological, economic and social benefits. The main agroforestry models of the main poplar planting area in Huaibei plain and along the Yangtze River plain were carried out. 11 typical management models of poplar were selected to sum up: pure poplar forest, poplar-rape-soybean, poplar-wheat-soybean, poplar-rape-cotton, poplar-wheat, poplar-chicken, poplar-duck, poplar-sheep, poplar-Agaricus blazei, poplar-oil peony, poplar-fish, represented by M0-M10, respectively. 12 indexes related with economic, ecological and social benefits (annual average cost, net income, ratio of output to investment, payback period of investment, land utilization ratio, utilization ratio of light energy, improvement and system stability of ecological and production environment, product richness, labor capacity, cultural quality of labor force, sustainability) were screened out to carry on the comprehensive evaluation and analysis to 11 kinds of typical agroforestry models based on analytic hierarchy process (AHP). The results showed that the economic benefit of each agroforestry model was in the order of: M8 > M6 > M9 > M7 > M5 > M10 > M4 > M1 > M2 > M3 > M0. The economic benefit of poplar-A. blazei model was the highest (332, 800 RMB / hm²), followed by poplar-duck and poplar-oil peony model (109, 820RMB /hm², 5, 7226 RMB /hm²). The order of comprehensive benefit was: M8 > M4 > M9 > M6 > M1 > M2 > M3 > M7 > M5 > M10 > M0. The economic benefit and comprehensive benefit of each agroforestry model were higher than that of pure poplar forest. The comprehensive benefit of poplar-A. blazei model was the highest, and that of poplar-wheat model ranked second, while its economic benefit was not high. Next were poplar-oil peony and poplar-duck models. It was suggested that the model of poplar-wheat should be adopted in the plain along the Yangtze River, and the whole cycle mode of poplar-grain, popalr-A. blazei, or poplar-oil peony should be adopted in Huaibei plain, northern Anhui. Furthermore, wheat, rape, and soybean are the main crops before the stand was closed; the agroforestry model of edible fungus or Chinese herbal medicine can be carried out when the stand was closed in order to maximize the comprehensive benefit. The purpose of this paper is to provide a reference for forest farmers in the selection of poplar agroforestry model in the future and to provide the basic data for the sustainable and efficient study of poplar agroforestry in Anhui province, eastern China.

Keywords: agroforestry, analytic hierarchy process (AHP), comprehensive benefit, model, poplar

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1152 Predictors of Clinical Failure After Endoscopic Lumbar Spine Surgery During the Initial Learning Curve

Authors: Daniel Scherman, Daniel Madani, Shanu Gambhir, Marcus Ling Zhixing, Yingda Li

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Objective: This study aims to identify clinical factors that may predict failed endoscopic lumbar spine surgery to guide surgeons with patient selection during the initial learning curve. Methods: This is an Australasian prospective analysis of the first 105 patients to undergo lumbar endoscopic spine decompression by 3 surgeons. Modified MacNab outcomes, Oswestry Disability Index (ODI) and Visual Analogue Score (VAS) scores were utilized to evaluate clinical outcomes at 6 months postoperatively. Descriptive statistics and Anova t-tests were performed to measure statistically significant (p<0.05) associations between variables using GraphPad Prism v10. Results: Patients undergoing endoscopic lumbar surgery via an interlaminar or transforaminal approach have overall good/excellent modified MacNab outcomes and a significant reduction in post-operative VAS and ODI scores. Regardless of the anatomical location of disc herniations, good/excellent modified MacNab outcomes and significant reductions in VAS and ODI were reported post-operatively; however, not in patients with calcified disc herniations. Patients with central and foraminal stenosis overall reported poor/fair modified MacNab outcomes. However, there were significant reductions in VAS and ODI scores post-operatively. Patients with subarticular stenosis or an associated spondylolisthesis reported good/excellent modified MacNab outcomes and significant reductions in VAS and ODI scores post-operatively. Patients with disc herniation and concurrent degenerative stenosis had generally poor/fair modified MacNab outcomes. Conclusion: The outcomes of endoscopic spine surgery are encouraging, with a low complication and reoperation rate. However, patients with calcified disc herniations, central canal stenosis or a disc herniation with concurrent degenerative stenosis present challenges during the initial learning curve and may benefit from traditional open or other minimally invasive techniques.

Keywords: complications, lumbar disc herniation, lumbar endoscopic spine surgery, predictors of failed endoscopic spine surgery

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1151 Disentangling the Sources and Context of Daily Work Stress: Study Protocol of a Comprehensive Real-Time Modelling Study Using Portable Devices

Authors: Larissa Bolliger, Junoš Lukan, Mitja Lustrek, Dirk De Bacquer, Els Clays

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Introduction and Aim: Chronic workplace stress and its health-related consequences like mental and cardiovascular diseases have been widely investigated. This project focuses on the sources and context of psychosocial daily workplace stress in a real-world setting. The main objective is to analyze and model real-time relationships between (1) psychosocial stress experiences within the natural work environment, (2) micro-level work activities and events, and (3) physiological signals and behaviors in office workers. Methods: An Ecological Momentary Assessment (EMA) protocol has been developed, partly building on machine learning techniques. Empatica® wristbands will be used for real-life detection of stress from physiological signals; micro-level activities and events at work will be based on smartphone registrations, further processed according to an automated computer algorithm. A field study including 100 office-based workers with high-level problem-solving tasks like managers and researchers will be implemented in Slovenia and Belgium (50 in each country). Data mining and state-of-the-art statistical methods – mainly multilevel statistical modelling for repeated data – will be used. Expected Results and Impact: The project findings will provide novel contributions to the field of occupational health research. While traditional assessments provide information about global perceived state of chronic stress exposure, the EMA approach is expected to bring new insights about daily fluctuating work stress experiences, especially micro-level events and activities at work that induce acute physiological stress responses. The project is therefore likely to generate further evidence on relevant stressors in a real-time working environment and hence make it possible to advise on workplace procedures and policies for reducing stress.

Keywords: ecological momentary assessment, real-time, stress, work

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1150 The Methods of Customer Satisfaction Measurement and Its Statistical Analysis towards Sales and Logistic Activities in Food Sector

Authors: Seher Arslankaya, Bahar Uludağ

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Meeting the needs and demands of customers and pleasing the customers are important requirements for companies in food sectors where the growth of competition is significantly unpredictable. Customer satisfaction is also one of the key concepts which is mainly driven by wide range of customer preference and expectation upon products and services introduced and delivered to them. In order to meet the customer demands, the companies that engage in food sectors are expected to have a well-managed set of Total Quality Management (TQM), which sets out to improve quality of products and services; to reduce costs and to increase customer satisfaction by restructuring traditional management practices. It aims to increase customer satisfaction by meeting (their) customer expectations and requirements. The achievement would be determined with the help of customer satisfaction surveys, which is done to obtain immediate feedback and to provide quick responses. In addition, the surveys would also assist the making of strategic planning which helps to anticipate customer future needs and expectations. Meanwhile, periodic measurement of customer satisfaction would be a must because with the better understanding of customers perceptions from the surveys (done by questioners), the companies would have a clear idea to identify their own strengths and weaknesses that help the companies keep their loyal customers; to stand in comparison toward their competitors and map out their future progress and improvement. In this study, we propose a survey based on customer satisfaction measurement method and its statistical analysis for sales and logistic activities of food firms. Customer satisfaction would be discussed in details. Furthermore, after analysing the data derived from the questionnaire that applied to customers by using the SPSS software, various results obtained from the application would be presented. By also applying ANOVA test, the study would analysis the existence of meaningful differences between customer demographic proportion and their perceptions. The purpose of this study is also to find out requirements which help to remove the effects that decrease customer satisfaction and produce loyal customers in food industry. For this purpose, the customer complaints are collected. Additionally, comments and suggestions are done according to the obtained results of surveys, which would be useful for the making-process of strategic planning in food industry.

Keywords: customer satisfaction measurement and analysis, food industry, SPSS, TQM

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1149 Harnessing Clinical Trial Capacity to Mitigate Zoonotic Diseases: The Role of Expert Scientists in Ethiopia

Authors: Senait Belay Adugna, Mirutse Giday, Tsegahun Manyazewal

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Background: The emergence and resurgence of zoonotic diseases have continued to be a major threat to global health and the economy. Developing countries are particularly vulnerable due to agricultural expansions and the domestication of animals by humans. Scientifically sound clinical trials are important to find better ways to prevent, diagnose, and treat zoonotic diseases, while there is a lack of evidence to inform the clinical trials’ capacity and practice in countries highly affected by the diseases. This study aimed to investigate researchers’ perceptions and experiences in conducting clinical trials on zoonotic diseases in Ethiopia. Methods: This study employed a descriptive, qualitative study design. It included major academic and research institutions in Ethiopia that had active engagements in veterinary and public health research. It included the National Veterinary Institute, the National Animal Health Diagnostic and Investigation Center, the College of Veterinary Medicine at Addis Ababa University, the Ethiopian Public Health Institute, the Armauer Hansen Research Institute, and the College of Health Sciences at Addis Ababa University. In-depth interviews were conducted with 14 senior researcher investigators in the institutions who hold a proven exhibit primarily leading research activities or research units. Data were collected from October 2019 to April 2020. Data analysis was undertaken using open code 4.03 for qualitative data analysis. Results: Five major themes, with 18 sub-themes, emerged from the in-depth interview in connection. These were: challenges in the prevention, control, and treatment of zoonotic diseases; One Health approach to mitigate zoonotic diseases; personal and institutional experiences in conducting clinical trials on zoonotic diseases; barriers in conducting clinical trials towards zoonotic diseases; and strategies that promote conducting clinical trials on zoonotic diseases. Conducting clinical trials on zoonotic diseases in Ethiopia is hampered by a lack of clearly articulated ethics and regulatory frameworks, trial experts, financial resources, and good governance. Conclusions: In Ethiopia, conducting clinical trials on zoonotic diseases deserves due attention. Strengthening institutional and human resources capacity is a precondition to harnessing effective implementation of clinical trials on zoonotic diseases in the country. In Ethiopia, where skilled human resource is scarce, the One Health approach has the potential to form multidisciplinary teams to systematically improve clinical trials capacity and outcomes in the country.

Keywords: Ethiopia, clinical triak, zoonoses, disease

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1148 Response Regimes and Vibration Mitigation in Equivalent Mechanical Model of Strongly Nonlinear Liquid Sloshing

Authors: Maor Farid, Oleg Gendelman

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Equivalent mechanical model of liquid sloshing in partially-filled cylindrical vessel is treated in the cases of free oscillations and of horizontal base excitation. The model is designed to cover both the linear and essentially nonlinear sloshing regimes. The latter fluid behaviour might involve hydraulic impacts interacting with the inner walls of the tank. These impulsive interactions are often modeled by high-power potential and dissipation functions. For the sake of analytical description, we use the traditional approach by modeling the impacts with velocity-dependent restitution coefficient. This modelling is similar to vibro-impact nonlinear energy sink (VI NES) which was recently explored for its vibration mitigation performances and nonlinear response regimes. Steady-state periodic regimes and chaotic strongly modulated responses (CSMR) are detected. Those dynamical regimes were described by the system's slow motion on the slow invariant manifold (SIM). There is a good agreement between the analytical results and numerical simulations. Subsequently, Finite-Element (FE) method is used to determine and verify the model parameters and to identify dominant dynamical regimes, natural modes and frequencies. The tank failure modes are identified and critical locations are identified. Mathematical relation is found between degrees-of-freedom (DOFs) motion and the mechanical stress applied in the tank critical section. This is the prior attempt to take under consideration large-amplitude nonlinear sloshing and tank structure elasticity effects for design, regulation definition and resistance analysis purposes. Both linear (tuned mass damper, TMD) and nonlinear (nonlinear energy sink, NES) passive energy absorbers contribution to the overall system mitigation is firstly examined, in terms of both stress reduction and time for vibration decay.

Keywords: nonlinear energy sink (NES), reduced-order modelling, liquid sloshing, vibration mitigation, vibro-impact dynamics

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1147 Aristotle’s Notion of Prudence as Panacea to the Leadership Crisis in Nigeria

Authors: Wogu Ikedinachi Ayodele Power, Agbude Godwyns, Eniayekon Eugenia, Nchekwube Excellence-Oluye, Abasilim Ugochukwu David

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Contemporary ethicists and writers on leadership, in their quest to address the problem of leadership crisis in Nigeria, have identified the absence of practical prudence -which manifests in variables such as corruption, ethnicity and greed- as one of the major factors which breeds leadership crises. These variables are further fuelled by the lack of a consistent theory of leadership among scholars that could guide the pertinent actions of political leaders, hence the rising cases of leadership crises in the country. The theoretical framework that guides this study emanates from Aristotle’s notion of prudence as contained in the Nicomachean Ethics, which states that prudence is a central moral resource for political leaders. The method of conceptual analysis shall be used to clarify the concepts of virtue, prudence and leadership. The traditional method of critical analysis and the reconstructive method of ideas in philosophy are used to conceptually and contextually analyze all relevant texts and archival materials in the subject areas of this study. The study identifies a high degree of ideological bias and logical inconsistencies inherent in the theories of leadership proposed by the realist and the moralist schools of thought. The conflicting ideologies regarding what political leadership should be among scholars of leadership is identified as one of the major factors militating against ascertaining a practicable theory of leadership, which has the capacity to guide the pertinent actions of political leaders all over the world. This paper therefore identifies the absence of practical prudence, ‘wisdom’, as the major factor associated with leadership crises in Nigeria. We therefore argue that only prudent leaders will have the capacity to identify salient aspects of political situations which leaders have obligations to consider before making political decisions. Seven frameworks were prescribed from Aristotle’s Notion of prudence to strengthen this position, they include: Disciplined reason and openness to experience; Foresight and attention to the long term, among others. We submit that leadership devoid of crisis can be attained through the application of the virtue of prudence. Where this theory is adopted, it should eliminate further leadership crises in Nigeria.

Keywords: Aristotle, leadership crisis, political leadership, prudence

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1146 UV-Enhanced Room-Temperature Gas-Sensing Properties of ZnO-SnO2 Nanocomposites Obtained by Hydrothermal Treatment

Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

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Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

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1145 Building a Blockchain-based Internet of Things

Authors: Rob van den Dam

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Today’s Internet of Things (IoT) comprises more than a billion intelligent devices, connected via wired/wireless communications. The expected proliferation of hundreds of billions more places us at the threshold of a transformation sweeping across the communications industry. Yet, we found that the IoT architecture and solutions that currently work for billions of devices won’t necessarily scale to tomorrow’s hundreds of billions of devices because of high cost, lack of privacy, not future-proof, lack of functional value and broken business models. As the IoT scales exponentially, decentralized networks have the potential to reduce infrastructure and maintenance costs to manufacturers. Decentralization also promises increased robustness by removing single points of failure that could exist in traditional centralized networks. By shifting the power in the network from the center to the edges, devices gain greater autonomy and can become points of transactions and economic value creation for owners and users. To validate the underlying technology vision, IBM jointly developed with Samsung Electronics the autonomous decentralized peer-to- peer proof-of-concept (PoC). The primary objective of this PoC was to establish a foundation on which to demonstrate several capabilities that are fundamental to building a decentralized IoT. Though many commercial systems in the future will exist as hybrid centralized-decentralized models, the PoC demonstrated a fully distributed proof. The PoC (a) validated the future vision for decentralized systems to extensively augment today’s centralized solutions, (b) demonstrated foundational IoT tasks without the use of centralized control, (c) proved that empowered devices can engage autonomously in marketplace transactions. The PoC opens the door for the communications and electronics industry to further explore the challenges and opportunities of potential hybrid models that can address the complexity and variety of requirements posed by the internet that continues to scale. Contents: (a) The new approach for an IoT that will be secure and scalable, (b) The three foundational technologies that are key for the future IoT, (c) The related business models and user experiences, (d) How such an IoT will create an 'Economy of Things', (e) The role of users, devices, and industries in the IoT future, (f) The winners in the IoT economy.

Keywords: IoT, internet, wired, wireless

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1144 Next Generation Radiation Risk Assessment and Prediction Tools Generation Applying AI-Machine (Deep) Learning Algorithms

Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

Procedia PDF Downloads 95
1143 A Literature Review of Precision Agriculture: Applications of Diagnostic Diseases in Corn, Potato, and Rice Based on Artificial Intelligence

Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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1142 Atypical Retinoid ST1926 Nanoparticle Formulation Development and Therapeutic Potential in Colorectal Cancer

Authors: Sara Assi, Berthe Hayar, Claudio Pisano, Nadine Darwiche, Walid Saad

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Nanomedicine, the application of nanotechnology to medicine, is an emerging discipline that has gained significant attention in recent years. Current breakthroughs in nanomedicine have paved the way to develop effective drug delivery systems that can be used to target cancer. The use of nanotechnology provides effective drug delivery, enhanced stability, bioavailability, and permeability, thereby minimizing drug dosage and toxicity. As such, the use of nanoparticle (NP) formulations in drug delivery has been applied in various cancer models and have shown to improve the ability of drugs to reach specific targeted sites in a controlled manner. Cancer is one of the major causes of death worldwide; in particular, colorectal cancer (CRC) is the third most common type of cancer diagnosed amongst men and women and the second leading cause of cancer related deaths, highlighting the need for novel therapies. Retinoids, consisting of natural and synthetic derivatives, are a class of chemical compounds that have shown promise in preclinical and clinical cancer settings. However, retinoids are limited by their toxicity and resistance to treatment. To overcome this resistance, various synthetic retinoids have been developed, including the adamantyl retinoid ST1926, which is a potent anti-cancer agent. However, due to its limited bioavailability, the development of ST1926 has been restricted in phase I clinical trials. We have previously investigated the preclinical efficacy of ST1926 in CRC models. ST1926 displayed potent inhibitory and apoptotic effects in CRC cell lines by inducing early DNA damage and apoptosis. ST1926 significantly reduced the tumor doubling time and tumor burden in a xenograft CRC model. Therefore, we developed ST1926-NPs and assessed their efficacy in CRC models. ST1926-NPs were produced using Flash NanoPrecipitation with the amphiphilic diblock copolymer polystyrene-b-ethylene oxide and cholesterol as a co-stabilizer. ST1926 was formulated into NPs with a drug to polymer mass ratio of 1:2, providing a stable formulation for one week. The contin ST1926-NP diameter was 100 nm, with a polydispersity index of 0.245. Using the MTT cell viability assay, ST1926-NP exhibited potent anti-growth activities as naked ST1926 in HCT116 cells, at pharmacologically achievable concentrations. Future studies will be performed to study the anti-tumor activities and mechanism of action of ST1926-NPs in a xenograft mouse model and to detect the compound and its glucuroconjugated form in the plasma of mice. Ultimately, our studies will support the use of ST1926-NP formulations in enhancing the stability and bioavailability of ST1926 in CRC.

Keywords: nanoparticles, drug delivery, colorectal cancer, retinoids

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1141 Metagenomic Analysis and Pharmacokinetics of Phage Therapy in the Treatment of Bovine Subclinical Mastitis

Authors: Vaibhav D. Bhatt, Anju P. Kunjadia, D. S. Nauriyal, Bhumika J. Joshi, Chaitanya G. Joshi

Abstract:

Metagenomic analysis of milk samples collected from local cattle breed, kankrej (Bos indicus), Gir (Bos indicus) and Crossbred (Bos indicus X Bos taurus) cattle harbouring subclinical mastitis was carried out by next-generation sequencing (NGS) 454 GS-FLX technology. Around 56 different species including members of Enterobacteriales, Pseudomonadales, Bacillales and Lactobacillales with varying abundance were detected in infected milk. The interesting presence of bacteriophages against Staphylococcus aureus, Escherichia coli, Enterobacter and Yersinia species were observed, especially Enterobacteria and E. coli phages (0∙32%) in Kankrej, Enterobacteria and Staphylococcus phages (1∙05%) in Gir and Staphylococcus phages (2∙32%) in crossbred cattle. NGS findings suggest that phages may be involved in imparting natural resistance of the cattle against pathogens. Further infected milk samples were subjected for bacterial isolation. Fourteen different isolates were identified, and DNA was extracted. Genes (Tet-K, Msr-A, and Mec-A) providing antibiotic resistance to the bacteria were screened by Polymerase Chain Reaction and results were validated with traditional antibiotic assay. Total 3 bacteriophages were isolated from nearby environment of the cattle farm. The efficacy of phages was checked against multi-drug resistant bacteria, identified by PCR. In-vivo study was carried out for phage therapy in mammary glands of female rats “Wister albino”. Mammary glands were infused with MDR isolates for 3 consecutive days. Recovery was observed in infected rats after intramammary infusion of sterile phage suspension. From day 4th onwards, level of C-reactive protein was significant increases up to day 12th . However, significant reduction was observed between days 12th to 18th post treatment. Bacteriophages have significant potential as antibacterial agents and their ability to replicate exponentially within their hosts and their specificity, make them ideal candidates for more sustainable mastitis control.

Keywords: bacteriophages, c-reactive protein, mastitis, metagenomic analysis

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1140 Speckle-Based Phase Contrast Micro-Computed Tomography with Neural Network Reconstruction

Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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1139 Enabling Socio Cultural Sustainability of the "Thousand and One Churches" Archaeological Site

Authors: E. Erdogan, M. Ulusoy

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In terms of tourism, the concept of sustainability can be defined as preserving and developing natural, historical, cultural, social, and aesthetic values and enabling their permanency. Sustainable tourism aims to preserve natural, historical, cultural, and social resources, also by supporting economic progress protecting economic development and environmental values that emerge as a consequence of tourism activities. Cultural tourism feeds on sustainable cultural treasures inherently and is the most effective touristic activity. Traditional configurations and structural characteristics play an important role in generating cultural tourism in a region. Sustainable cultural tourism is related to trips upon people who embark with the aim of visiting culturally rich regions, learning about and observing fast-disappearing lifestyles and collecting cultural values as memories. With its huge tourism potential, Karadağ is the most significant cultural asset of the Karaman province, possessing unique riches in terms of cultural world history. Host to one of the most important Byzantine cities in Anatolia, Karadağ is like an open-air museum with its unparalleled architectural structures. There is a village named Madenşehir in the plain at the outskirts of Karadağ, near to which are located the “Thousand and One Churches” ruins. The 80-household house is located near the ruins in an area that been declared a 1st degree historic preservation district. stones gathered from local churches were used in the construction of these households. A ministry has assigned a new residential site near the boundaries of the 2nd degree preservation district, and the decision has been made to move the occupants to this area. The most important issue here is to enable locals’ sociocultural and socioeconomic sustainability. It is also important to build these structures in a manner compatible with the historical visual look, ecological system and environmental awareness. Therefore this new site will be planned as touristic area in terms of sustainable cultural tourism and in these new plans, shall fulfill functions oriented toward both tourists and locals. It is very important that this change be sustainable and also support cultural tourism.

Keywords: cultural tourism, new village settlement, socio cultural sustainability, “thousand and one churches” site

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1138 Tool Development for Assessing Antineoplastic Drugs Surface Contamination in Healthcare Services and Other Workplaces

Authors: Benoit Atge, Alice Dhersin, Oscar Da Silva Cacao, Beatrice Martinez, Dominique Ducint, Catherine Verdun-Esquer, Isabelle Baldi, Mathieu Molimard, Antoine Villa, Mireille Canal-Raffin

Abstract:

Introduction: Healthcare workers' exposure to antineoplastic drugs (AD) is a burning issue for occupational medicine practitioners. Biological monitoring of occupational exposure (BMOE) is an essential tool for assessing AD contamination of healthcare workers. In addition to BMOE, surface sampling is a useful tool in order to understand how workers get contaminated, to identify sources of environmental contamination, to verify the effectiveness of surface decontamination way and to ensure monitoring of these surfaces. The objective of this work was to develop a complete tool including a kit for surface sampling and a quantification analytical method for AD traces detection. The development was realized with the three following criteria: the kit capacity to sample in every professional environment (healthcare services, veterinaries, etc.), the detection of very low AD traces with a validated analytical method and the easiness of the sampling kit use regardless of the person in charge of sampling. Material and method: AD mostly used in term of quantity and frequency have been identified by an analysis of the literature and consumptions of different hospitals, veterinary services, and home care settings. The kind of adsorbent device, surface moistening solution and mix of solvents for the extraction of AD from the adsorbent device have been tested for a maximal yield. The AD quantification was achieved by an ultra high-performance liquid chromatography method coupled with tandem mass spectrometry (UHPLC-MS/MS). Results: With their high frequencies of use and their good reflect of the diverse activities through healthcare, 15 AD (cyclophosphamide, ifosfamide, doxorubicin, daunorubicin, epirubicin, 5-FU, dacarbazin, etoposide, pemetrexed, vincristine, cytarabine, methothrexate, paclitaxel, gemcitabine, mitomycin C) were selected. The analytical method was optimized and adapted to obtain high sensitivity with very low limits of quantification (25 to 5000ng/mL), equivalent or lowest that those previously published (for 13/15 AD). The sampling kit is easy to use, provided with a didactic support (online video and protocol paper). It showed its effectiveness without inter-individual variation (n=5/person; n= 5 persons; p=0,85; ANOVA) regardless of the person in charge of sampling. Conclusion: This validated tool (sampling kit + analytical method) is very sensitive, easy to use and very didactic in order to control the chemical risk brought by AD. Moreover, BMOE permits a focal prevention. Used in routine, this tool is available for every intervention of occupational health.

Keywords: surface contamination, sampling kit, analytical method, sensitivity

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1137 Breast Cancer Metastasis Detection and Localization through Transfer-Learning Convolutional Neural Network Classification Based on Convolutional Denoising Autoencoder Stack

Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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1136 In vivo Wound Healing Activity and Phytochemical Screening of the Crude Extract and Various Fractions of Kalanchoe petitiana A. Rich (Crassulaceae) Leaves in Mice

Authors: Awol Mekonnen, Temesgen Sidamo, Epherm Engdawork, Kaleab Asresb

Abstract:

Ethnopharmacological Relevance: The leaves of Kalanchoe petitiana A. Rich (Crassulaceae) are used in Ethiopian folk medicine for treatment of evil eye, fractured surface for bone setting and several skin disorders including for the treatment of sores, boils, and malignant wounds. Aim of the Study: In order to scientifically prove the claimed utilization of the plant, the effects of the extracts and the fractions were investigated using in vivo excision, incision and dead space wound models. Materials and Method: Mice were used for wound healing study, while rats and rabbit were used for skin irritation test. For studying healing activity, 80% methanolic extract and the fractions were formulated in strength of 5% and 10%, either as ointment (hydroalcoholic extract, aqueous and methanol fractions) or gel (chloroform fraction). Oral administration of the crude extract was used for dead space model. Negative controls were treated either with simple ointment or sodium carboxyl methyl cellulose xerogel, while positive controls were treated with nitrofurazone (0.2 w/v) skin ointment. Negative controls for dead space model were treated with 1% carboxy methyl cellulose. Parameters, including rate of wound contraction, period of complete epithelializtion, hydroxyproline contents and skin breaking strength were evaluated. Results: Significant wound healing activity was observed with ointment formulated from the crude extract at both 5% and 10% concentration (p<0.01) compared to controls in both excision and incision models. In dead space model, 600 mg/kg (p<0.01), but not 300 mg/kg, significantly increased hydroxyproline content. Fractions showed variable effect, with the chloroform fraction lacking any significant effect. Both 5% and 10% formulations of the aqueous and methanolic fractions significantly increased wound contraction, decreased epithelializtion time and increased hydroxyproline content in excision wound model (p<0.05) as compared to controls. These fractions were also endowed with higher skin breaking strength in incision wound model (p<0.01). Conclusions: The present study provided evidence that the leaves of Kalanchoe petitiana A. Rich possess remarkable wound healing activities supporting the folkloric assertion of the plant. Fractionation revealed that polar or semi-polar compound may play vital role, as both aqueous and methanolic fractions were endowed with wound healing activity.

Keywords: wound healing, Kalanchoae petitiana, excision wound, incision wound, dead space model

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1135 Research on Energy Field Intervening in Lost Space Renewal Strategy

Authors: Tianyue Wan

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Lost space is the space that has not been used for a long time and is in decline, proposed by Roger Trancik. And in his book Finding Lost Space: Theories of Urban Design, the concept of lost space is defined as those anti-traditional spaces that are unpleasant, need to be redesigned, and have no benefit to the environment and users. They have no defined boundaries and do not connect the various landscape elements in a coherent way. With the rapid development of urbanization in China, the blind areas of urban renewal have become a chaotic lost space that is incompatible with the rapid development of urbanization. Therefore, lost space needs to be reconstructed urgently under the background of infill development and reduction planning in China. The formation of lost space is also an invisible division of social hierarchy. This paper tries to break down the social class division and the estrangement between people through the regeneration of lost space. Ultimately, it will enhance vitality, rebuild a sense of belonging, and create a continuous open public space for local people. Based on the concept of lost space and energy field, this paper clarifies the significance of the energy field in the lost space renovation. Then it introduces the energy field into lost space by using the magnetic field in physics as a prototype. The construction of the energy field is support by space theory, spatial morphology analysis theory, public communication theory, urban diversity theory and city image theory. Taking Wuhan’s Lingjiao Park of China as an example, this paper chooses the lost space on the west side of the park as the research object. According to the current situation of this site, the energy intervention strategies are proposed from four aspects: natural ecology, space rights, intangible cultural heritage and infrastructure configuration. And six specific lost space renewal methods are used in this work, including “riveting”, “breakthrough”, “radiation”, “inheritance”, “connection” and “intersection”. After the renovation, space will be re-introduced into the active crow. The integration of activities and space creates a sense of place, improve the walking experience, restores the vitality of the space, and provides a reference for the reconstruction of lost space in the city.

Keywords: dynamic vitality intervention, lost space, space vitality, sense of place

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1134 Agriculture and Forests: A Perception of Farmers on Sustainable Agro-Ecological Practices

Authors: Kever Gomes, Rosana Martins

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The use of environmental indicators is today an important strategy for analyzing the sustainability of agricultural systems. Despite of the considerable importance of family agriculture for Brazilian economy, sustainable agricultural practices are still weakly known, and the known ones, underused. Currently, economic aspects of the relationship between man and nature lead to the destruction of natural ecosystems, which justifies the urgent need for dissemination and usage of new sustainable production techniques. The study shows the agro-social and social-cultural trajectory of the farmers and hypothesis are advanced on what would imply the adoption of agroforestry systems in family agriculture. This study aimed to investigate aspects related to the perception of sustainable agriculture, especially on agroforestry systems in farms of farmers from Distrito Federal-Brazil. Agro-social characteristics of farmers were systematized considering their perceptions about agroforestry systems for the preparation of proposal for a program of Environmental Services Payment, intended for families who are involved in the various activities of home gardens. This study used qualitative methodological approaches of quantitative research, using descriptive exploratory research. To get the necessary elements for the intended analysis, interviews were conducted at 40 heads of households of which 15 were men and 25 women. The results were analyzed using descriptive statistics, having been considered in the analysis the frequency, consistency, coherence and originality of responses. It was found that the lack of financial resources and lack of technical assistance are limiting factors for the dissemination and use of sustainable agricultural practices. Considering the great number of species found for the main categories of use, it can be inferred that the home gardens play important functions for the interviewed families, contributing for the food and medicine production destined for the consumption by the families themselves, and also playing an important esthetic function thanks to the variety of their ornamental plants. The wealth of these home gardens may be related to the rural origin and to the culture of the owners, who still keep a cultivation tradition. It was found that the products obtained from the home gardens contributed for the diet’s variety of the informants, representing a promising potential for the improvement of the population alimentation. The study reached the conclusion over the need to motivate the interest of these farmers to seek information and resources to enable the implementation of Agroforestry projects, including the recovery of areas in their properties, even those distinct from their backyards. The study shows the agro-social and social-cultural trajectory of the farmers and hypothesis are advanced on what would imply the adoption of agroforestry systems in family agriculture.

Keywords: agro-biodiversity, natural conservation, silviculture, urban agriculture

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1133 Crime Prevention with Artificial Intelligence

Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Today, with the increase in quantity and quality and variety of crimes, the discussion of crime prevention has faced a serious challenge that human resources alone and with traditional methods will not be effective. One of the developments in the modern world is the presence of artificial intelligence in various fields, including criminal law. In fact, the use of artificial intelligence in criminal investigations and fighting crime is a necessity in today's world. The use of artificial intelligence is far beyond and even separate from other technologies in the struggle against crime. Second, its application in criminal science is different from the discussion of prevention and it comes to the prediction of crime. Crime prevention in terms of the three factors of the offender, the offender and the victim, following a change in the conditions of the three factors, based on the perception of the criminal being wise, and therefore increasing the cost and risk of crime for him in order to desist from delinquency or to make the victim aware of self-care and possibility of exposing him to danger or making it difficult to commit crimes. While the presence of artificial intelligence in the field of combating crime and social damage and dangers, like an all-seeing eye, regardless of time and place, it sees the future and predicts the occurrence of a possible crime, thus prevent the occurrence of crimes. The purpose of this article is to collect and analyze the studies conducted on the use of artificial intelligence in predicting and preventing crime. How capable is this technology in predicting crime and preventing it? The results have shown that the artificial intelligence technologies in use are capable of predicting and preventing crime and can find patterns in the data set. find large ones in a much more efficient way than humans. In crime prediction and prevention, the term artificial intelligence can be used to refer to the increasing use of technologies that apply algorithms to large sets of data to assist or replace police. The use of artificial intelligence in our debate is in predicting and preventing crime, including predicting the time and place of future criminal activities, effective identification of patterns and accurate prediction of future behavior through data mining, machine learning and deep learning, and data analysis, and also the use of neural networks. Because the knowledge of criminologists can provide insight into risk factors for criminal behavior, among other issues, computer scientists can match this knowledge with the datasets that artificial intelligence uses to inform them.

Keywords: artificial intelligence, criminology, crime, prevention, prediction

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1132 Remote Sensing Reversion of Water Depths and Water Management for Waterbird Habitats: A Case Study on the Stopover Site of Siberian Cranes at Momoge, China

Authors: Chunyue Liu, Hongxing Jiang

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Traditional water depth survey of wetland habitats used by waterbirds needs intensive labor, time and money. The optical remote sensing image relies on passive multispectral scanner data has been widely employed to study estimate water depth. This paper presents an innovative method for developing the water depth model based on the characteristics of visible and thermal infrared spectra of Landsat ETM+ image, combing with 441 field water depth data at Etoupao shallow wetland. The wetland is located at Momoge National Nature Reserve of Northeast China, where the largest stopover habitat along the eastern flyway of globally, critically-endangered Siberian Cranes are. The cranes mainly feed on the tubers of emergent aquatic plants such as Scirpus planiculmis and S. nipponicus. The effective water control is a critical step for maintaining the production of tubers and food availability for this crane. The model employing multi-band approach can effectively simulate water depth for this shallow wetland. The model parameters of NDVI and GREEN indicated the vegetation growth and coverage affecting the reflectance from water column change are uneven. Combining with the field-observed water level at the same date of image acquisition, the digital elevation model (DEM) for the underwater terrain was generated. The wetland area and water volume of different water levels were then calculated from the DEM using the function of Area and Volume Statistics under the 3D Analyst of ArcGIS 10.0. The findings provide good references to effectively monitor changes in water level and water demand, develop practical plan for water level regulation and water management, and to create best foraging habitats for the cranes. The methods here can be adopted for the bottom topography simulation and water management in waterbirds’ habitats, especially in the shallow wetlands.

Keywords: remote sensing, water depth reversion, shallow wetland habitat management, siberian crane

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