Search results for: safety of food
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6697

Search results for: safety of food

3427 The Oxidative Damage Marker for Sodium Formate Exposure on Lymphocytes

Authors: Malinee Pongsavee

Abstract:

Sodium formate is the chemical substance used for food additive. Catalase is the important antioxidative enzyme in protecting the cell from oxidative damage by reactive oxygen species (ROS). The resultant level of oxidative stress in sodium formatetreated lymphocytes was investigated. The sodium formate concentrations of 0.05, 0.1, 0.2, 0.4 and 0.6 mg/mL were treated in human lymphocytes for 12 hours. After 12 treated hours, catalase activity change was measured in sodium formate-treated lymphocytes. The results showed that the sodium formate concentrations of 0.4 and 0.6 mg/mL significantly decreased catalase activities in lymphocytes (P < 0.05). The change of catalase activity in sodium formate-treated lymphocytes may be the oxidative damage marker for detect sodium formate exposure in human.

Keywords: sodium formate, catalase activity, oxidative damage marker, toxicity

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3426 Establishment and Evaluation of a Nutrition Therapy Guide and 7-Day Menu for Educating Hemodialysis Patients: A Case Study of Douala General Hospital, Cameroon

Authors: Ngwa Lodence Njwe

Abstract:

This study investigated the response of hemodialysis patients to an established nutrition therapy guide accompanied by a 7-day menu plan administered for a month. End Stage Renal Disease (ESRD), also known as End Stage Kidney Disease (ESKD), is a non-communicable disease primarily caused by hypertension and diabetes, posing significant challenges in both developed and developing nations. Hemodialysis is a key treatment for these patients. In this experimental study, 100 hemodialysis patients from Douala General Hospital in Cameroon participated. A questionnaire was used to collect data on sociodemographic and anthropometric characteristics, health status, and dietary intake, while medical records provided biomedical data. The levels of the biochemical parameters (Phosphorus, calcium and hemoglobin) were determined before and one month after the distribution of the nutrition education guide and the use of a 7-day menu plan. The Phosphorus and Calcium levels were measured using an LTCC03 semi-automatic chemistry analyzer. Blood was collected from each patient into a test tube, allowed to clot and centrifuged. 50µl of the serum was aspirated by the analyzer for Ca and P level analysis, and results were read from the display. The hemoglobin level was measured using the URIT–12 hemoglobin Meter. The blood sample was collected by hand prick and placed in a strip, and the results were read from the screen. The means of the biochemical parameters were then computed. The most prevalent age group was 40-49 years, with males constituting 70% and females 30% of respondents. Among these patients, 80% were hypertensive, 3% had both hypertension and diabetes, 9% were hypertensive, diabetic, and obese, and 1% suffered from hypertension and heart failure. Analysis of anthropometric parameters revealed a high prevalence of underweight, overweight, and obesity, highlighting the urgent need for targeted nutrition interventions to modify cooking methods, enhance food choices, and increase dietary variety for improved quality of life. Before the nutrition therapy guide was implemented, average calcium levels were 73.05 mg/L for males and 89.44 mg/L for females; post-implementation, these values increased to 77.55 mg/L and 91.44 mg/L, respectively. Conversely, average phosphorus levels decreased from 42.05 mg/L for males and 43.55 mg/L for females to 41.05 mg/L and 39.3 mg/L, respectively, after the intervention. Additionally, average hemoglobin levels increased from 8.35 g/dL for males and 8.5 g/dL for females to 9.2 g/dL and 8.95 g/dL, respectively. The findings confirm that the nutrition therapy guide and the 7-day menu significantly impacted the biomedical parameters of hemodialysis patients, underscoring the need for ongoing nutrition education and counseling for this population.

Keywords: end stage kidney disease, nutrition therapy guide, nutritional status, anthropometric parameters, food frequency, biomedical data

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3425 Prevalence of Non-Adherence among Psychiatric Patients in Jordan: A Cross Sectional Study

Authors: Tareq L. Mukattash, Karem H. Alzoubi, Ejlal Abu El-Rub, Anan S. Jarab, Sayyer I. Al-Azzam, Maher Khdour, Mohammed Shara, Yazid N. Alhamarneh

Abstract:

Background: It has been estimated that up to 50% of any patient population is at least partially non-adherent to their prescribed treatment. Identifying barriers to adherence is required to develop effective interventions for psychiatric patients. Objective: To explore the prevalence and factors of non-adherence among psychiatric patients present at four psychiatric clinics. Method: A cross-sectional questionnaire-based study. A sample of psychiatric patients attending outpatient psychiatric clinics was enrolled between March and April 2011. Results: A total of 243 psychiatric patients took part in this study with the majority of patients (92.5%) being prescribed more than one psychiatric disorder. The majority (64.2%) of the patients was classified as non-adherent according to the Morisky adherence questionnaire and forgetfulness was the most prevalent reason for that. Conclusions: Non-adherence is a common and important issue among psychiatric patients. Polypharmacy, safety concerns and lack of insight towards the prescribed treatment were reported as the main reasons of non-adherence.

Keywords: medication adherence, psychiatric disorders, clinical pharmacy, polypharmacy

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3424 Implementation of ALD in Product Development: Study of ROPS to Improve Energy Absorption Performance Using Absorption Part

Authors: Zefry Darmawan, Shigeyuki Haruyama, Ken Kaminishi

Abstract:

Product development is a big issue in the industrial competition and takes a serious part in development of technology. Product development process could adapt high changes of market needs and transform into engineering concept in order to produce high-quality product. One of the latest methods in product development is Analysis-Led-Design (ALD). It utilizes digital engineering design tools with finite analysis to perform product robust analysis and valuable for product reliability assurance. Heavy machinery which operates under severe condition should maintain safety to the customer when faced with potential hazard. Cab frame should able to absorb the energy while collision. Through ALD, a series of improvement of cab frame to increase energy absorption was made and analyzed. Improvement was made by modifying shapes of frame and-or install absorption device in certain areas. Simulation result showed that install absorption device could increase absorption energy than modifying shape.

Keywords: ALD, ROPS, energy absorption, cab frame

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3423 Green Synthesis of Red-Fluorescent Gold Nanoclusters: Characterization and Application for Breast Cancer Detection

Authors: Agnė Mikalauskaitė, Renata Karpicz, Vitalijus Karabanovas, Arūnas Jagminas

Abstract:

The use of biocompatible precursors for the synthesis and stabilization of fluorescent gold nanoclusters (NCs) with strong red photoluminescence creates an important link between natural sciences and nanotechnology. Herein, we report the cost-effective synthesis of Au nanoclusters by templating and reduction of chloroauric acid with the cheap amino acid food supplements. This synthesis under the optimized conditions leads to the formation of biocompatible Au NCs having good stability and intense red photoluminescence, peaked at 680 to 705 nm, with a quantum yield (QY) of ≈7% and the average lifetime of up to several µs. The composition and luminescent properties of the obtained NCs were compared with ones formed via well-known bovine serum albumin reduction approach. Our findings implied that synthesized Au NCs tend to accumulate in more tumorigenic breast cancer cells (line MDA-MB-213) and after dialysis can be prospective for bio imagining.

Keywords: gold nanoclusters, proteins, materials chemistry, red-photoluminescence, bioimaging

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3422 Unification of Lactic Acid Bacteria and Aloe Vera for Healthy Gut

Authors: Pavitra Sharma, Anuradha Singh, Nupur Mathur

Abstract:

There exist more than 100 trillion bacteria in the digestive system of human-beings. Such bacteria are referred to as gut microbiota. Gut microbiota comprises around 75% of our immune system. The bacteria that comprise the gut microbiota are unique to every individual and their composition keeps changing with time owing to factors such as the host’s age, diet, genes, environment, and external medication. Of these factors, the variable easiest to control is one’s diet. By modulating one’s diet, one can ensure an optimal composition of the gut microbiota yielding several health benefits. Prebiotics and probiotics are two compounds that have been considered as viable options to modulate the host’s diet. Prebiotics are basically plant products that support the growth of good bacteria in the host’s gut. Examples include garden asparagus, aloe vera etc. Probiotics are living microorganisms that exist in our intestines and play an integral role in promoting digestive health and supporting our immune system in general. Examples include yogurt, kimchi, kombucha etc. In the context of modulating the host’s diet, the key attribute of prebiotics is that they support the growth of probiotics. By developing the right combination of prebiotics and probiotics, food products or supplements can be created to enhance the host’s health. An effective combination of prebiotics and probiotics that yields health benefits to the host is referred to as synbiotics. Synbiotics comprise of an optimal proportion of prebiotics and probiotics, their application benefits the host’s health more than the application of prebiotics and probiotics used in isolation. When applied to food supplements, synbiotics preserve the beneficial probiotic bacteria during storage period and during the bacteria’s passage through the intestinal tract. When applied to the gastrointestinal tract, the composition of the synbiotics assumes paramount importance. Reason being that for synbiotics to be effective in the gastrointestinal tract, the chosen probiotic must be able to survive in the stomach’s acidic environment and manifest tolerance towards bile and pancreatic secretions. Further, not every prebiotic stimulates the growth of a particular probiotic. The prebiotic chosen should be one that not only maintains 2 balance in the host’s digestive system, but also provides the required nutrition to probiotics. Hence in each application of synbiotics, the prebiotic-probiotic combination needs to be carefully selected. Once the combination is finalized, the exact proportion of prebiotics and probiotics to be used needs to be considered. When determining this proportion, only that amount of a prebiotic should be used that activates metabolism of the required number of probiotics. It was observed that while probiotics are active is both the small and large intestine, the effect of prebiotics is observed primarily in the large intestine. Hence in the host’s small intestine, synbiotics are likely to have the maximum efficacy. In small intestine, prebiotics not only assist in the growth of probiotics, but they also enable probiotics to exhibit a higher tolerance to pH levels, oxygenation, and intestinal temperature

Keywords: microbiota, probiotics, prebiotics, synbiotics

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3421 Qualitative Characterization of Proteins in Common and Quality Protein Maize Corn by Mass Spectrometry

Authors: Benito Minjarez, Jesse Haramati, Yury Rodriguez-Yanez, Florencio Recendiz-Hurtado, Juan-Pedro Luna-Arias, Salvador Mena-Munguia

Abstract:

During the last decades, the world has experienced a rapid industrialization and an expanding economy favoring a demographic boom. As a consequence, countries around the world have focused on developing new strategies related to the production of different farm products in order to meet future demands. Consequently, different strategies have been developed seeking to improve the major food products for both humans and livestock. Corn, after wheat and rice, is the third most important crop globally and is the primary food source for both humans and livestock in many regions around the globe. In addition, maize (Zea mays) is an important source of protein accounting for up to 60% of the daily human protein supply. Generally, many of the cereal grains have proteins with relatively low nutritional value, when they are compared with proteins from meat. In the case of corn, much of the protein is found in the endosperm (75 to 85%) and is deficient in two essential amino acids, lysine, and tryptophan. This deficiency results in an imbalance of amino acids and low protein content; normal maize varieties have less than half of the recommended amino acids for human nutrition. In addition, studies have shown that this deficiency has been associated with symptoms of growth impairment, anemia, hypoproteinemia, and fatty liver. Due to the fact that most of the presently available maize varieties do not contain the quality and quantity of proteins necessary for a balanced diet, different countries have focused on the research of quality protein maize (QPM). Researchers have characterized QPM noting that these varieties may contain between 70 to 100% more residues of the amino acids essential for animal and human nutrition, lysine, and tryptophan, than common corn. Several countries in Africa, Latin America, as well as China, have incorporated QPM in their agricultural development plan. Large parts of these countries have chosen a specific QPM variety based on their local needs and climate. Reviews have described the breeding methods of maize and have revealed the lack of studies on genetic and proteomic diversity of proteins in QPM varieties, and their genetic relationships with normal maize varieties. Therefore, molecular marker identification using tools such as mass spectrometry may accelerate the selection of plants that carry the desired proteins with high lysine and tryptophan concentration. To date, QPM maize lines have played a very important role in alleviating the malnutrition, and better characterization of these lines would provide a valuable nutritional enhancement for use in the resource-poor regions of the world. Thus, the objectives of this study were to identify proteins in QPM maize in comparison with a common maize line as a control.

Keywords: corn, mass spectrometry, QPM, tryptophan

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3420 The Monitor for Neutron Dose in Hadrontherapy Project: Secondary Neutron Measurement in Particle Therapy

Authors: V. Giacometti, R. Mirabelli, V. Patera, D. Pinci, A. Sarti, A. Sciubba, G. Traini, M. Marafini

Abstract:

The particle therapy (PT) is a very modern technique of non invasive radiotherapy mainly devoted to the treatment of tumours untreatable with surgery or conventional radiotherapy, because localised closely to organ at risk (OaR). Nowadays, PT is available in about 55 centres in the word and only the 20\% of them are able to treat with carbon ion beam. However, the efficiency of the ion-beam treatments is so impressive that many new centres are in construction. The interest in this powerful technology lies to the main characteristic of PT: the high irradiation precision and conformity of the dose released to the tumour with the simultaneous preservation of the adjacent healthy tissue. However, the beam interactions with the patient produce a large component of secondary particles whose additional dose has to be taken into account during the definition of the treatment planning. Despite, the largest fraction of the dose is released to the tumour volume, a non-negligible amount is deposed in other body regions, mainly due to the scattering and nuclear interactions of the neutrons within the patient body. One of the main concerns in PT treatments is the possible occurrence of secondary malignant neoplasm (SMN). While SMNs can be developed up to decades after the treatments, their incidence impacts directly life quality of the cancer survivors, in particular in pediatric patients. Dedicated Treatment Planning Systems (TPS) are used to predict the normal tissue toxicity including the risk of late complications induced by the additional dose released by secondary neutrons. However, no precise measurement of secondary neutrons flux is available, as well as their energy and angular distributions: an accurate characterization is needed in order to improve TPS and reduce safety margins. The project MONDO (MOnitor for Neutron Dose in hadrOntherapy) is devoted to the construction of a secondary neutron tracker tailored to the characterization of that secondary neutron component. The detector, based on the tracking of the recoil protons produced in double-elastic scattering interactions, is a matrix of thin scintillating fibres, arranged in layer x-y oriented. The final size of the object is 10 x 10 x 20 cm3 (squared 250µm scint. fibres, double cladding). The readout of the fibres is carried out with a dedicated SPAD Array Sensor (SBAM) realised in CMOS technology by FBK (Fondazione Bruno Kessler). The detector is under development as well as the SBAM sensor and it is expected to be fully constructed for the end of the year. MONDO will make data tacking campaigns at the TIFPA Proton Therapy Center of Trento, at the CNAO (Pavia) and at HIT (Heidelberg) with carbon ion in order to characterize the neutron component and predict the additional dose delivered on the patients with much more precision and to drastically reduce the actual safety margins. Preliminary measurements with charged particles beams and MonteCarlo FLUKA simulation will be presented.

Keywords: secondary neutrons, particle therapy, tracking detector, elastic scattering

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3419 Challenges of Blockchain Applications in the Supply Chain Industry: A Regulatory Perspective

Authors: Pardis Moslemzadeh Tehrani

Abstract:

Due to the emergence of blockchain technology and the benefits of cryptocurrencies, intelligent or smart contracts are gaining traction. Artificial intelligence (AI) is transforming our lives, and it is being embraced by a wide range of sectors. Smart contracts, which are at the heart of blockchains, incorporate AI characteristics. Such contracts are referred to as "smart" contracts because of the underlying technology that allows contracting parties to agree on terms expressed in computer code that defines machine-readable instructions for computers to follow under specific situations. The transmission happens automatically if the conditions are met. Initially utilised for financial transactions, blockchain applications have since expanded to include the financial, insurance, and medical sectors, as well as supply networks. Raw material acquisition by suppliers, design, and fabrication by manufacturers, delivery of final products to consumers, and even post-sales logistics assistance are all part of supply chains. Many issues are linked with managing supply chains from the planning and coordination stages, which can be implemented in a smart contract in a blockchain due to their complexity. Manufacturing delays and limited third-party amounts of product components have raised concerns about the integrity and accountability of supply chains for food and pharmaceutical items. Other concerns include regulatory compliance in multiple jurisdictions and transportation circumstances (for instance, many products must be kept in temperature-controlled environments to ensure their effectiveness). Products are handled by several providers before reaching customers in modern economic systems. Information is sent between suppliers, shippers, distributors, and retailers at every stage of the production and distribution process. Information travels more effectively when individuals are eliminated from the equation. The usage of blockchain technology could be a viable solution to these coordination issues. In blockchains, smart contracts allow for the rapid transmission of production data, logistical data, inventory levels, and sales data. This research investigates the legal and technical advantages and disadvantages of AI-blockchain technology in the supply chain business. It aims to uncover the applicable legal problems and barriers to the use of AI-blockchain technology to supply chains, particularly in the food industry. It also discusses the essential legal and technological issues and impediments to supply chain implementation for stakeholders, as well as methods for overcoming them before releasing the technology to clients. Because there has been little research done on this topic, it is difficult for industrial stakeholders to grasp how blockchain technology could be used in their respective operations. As a result, the focus of this research will be on building advanced and complex contractual terms in supply chain smart contracts on blockchains to cover all unforeseen supply chain challenges.

Keywords: blockchain, supply chain, IoT, smart contract

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3418 Working Effectively with Muslim Communities in the West

Authors: Lisa Tribuzio

Abstract:

This paper explores the complexity of working with Muslim communities in Australia. It will draw upon the notions of belonging, social inclusion and effective community programming to engage Muslim communities in Western environments given the current global political climate. Factors taken into consideration for effective engagement include: family engagement, considering key practices such as Ramadan, fasting and prayer and food requirements, gender relations, core values around faith and spirituality, considering attitudes towards self disclosure in a counseling setting and the notion of Us and Them in the media and systems and its effect on minority communities. It will explore recent research in the field from Australian researchers as well as recommendations from United Nations in working with Muslim communities. It will also explore current practice models applied in Australia in engaging effectively with diverse communities and addressing racism and discrimination in innovative ways.

Keywords: Muslim, cultural diversity, social inclusion, racism

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3417 Standardization Of Miniature Neutron Research Reactor And Occupational Safety Analysis

Authors: Raymond Limen Njinga

Abstract:

The comparator factors (Fc) for miniature research reactors are of great importance in the field of nuclear physics as it provide accurate bases for the evaluation of elements in all form of samples via ko-NAA techniques. The Fc was initially simulated theoretically thereafter, series of experiments were performed to validate the results. In this situation, the experimental values were obtained using the alloy of Au(0.1%) - Al monitor foil and a neutron flux setting of 5.00E+11 cm-2.s-1. As was observed in the inner irradiation position, the average experimental value of 7.120E+05 was reported against the theoretical value of 7.330E+05. In comparison, a percentage deviation of 2.86 (from theoretical value) was observed. In the large case of the outer irradiation position, the experimental value of 1.170E+06 was recorded against the theoretical value of 1.210E+06 with a percentage deviation of 3.310 (from the theoretical value). The estimation of equivalent dose rate at 5m from neutron flux of 5.00E+11 cm-2.s-1 within the neutron energies of 1KeV, 10KeV, 100KeV, 500KeV, 1MeV, 5MeV and 10MeV were calculated to be 0.01 Sv/h, 0.01 Sv/h, 0.03 Sv/h, 0.15 Sv/h, 0.21Sv/h and 0.25 Sv/h respectively with a total dose within a period of an hour was obtained to be 0.66 Sv.

Keywords: neutron flux, comparator factor, NAA techniques, neutron energy, equivalent dose

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3416 UPPAAL-based Design and Analysis of Intelligent Parking System

Authors: Abobaker Mohammed Qasem Farhan, Olof M. A. Saif

Abstract:

The demand for parking spaces in urban areas, particularly in developing countries, has led to a significant issue in the absence of sufficient parking spaces in crowded areas, which results in daily traffic congestion as drivers search for parking. This not only affects the appearance of the city but also has indirect impacts on the economy, society, and environment. In response to these challenges, researchers from various countries have sought technical and intelligent solutions to mitigate the problem through the development of smart parking systems. This paper aims to analyze and design three models of parking lots, with a focus on parking time and security. The study used computer software and Uppaal tools to simulate the models and determine the best among them. The results and suggestions provided in the paper aim to reduce the parking problems and improve the overall efficiency and safety of the parking process. The conclusion of the study highlights the importance of utilizing advanced technology to address the pressing issue of insufficient parking spaces in urban areas.

Keywords: preliminaries, system requirements, timed Au- tomata, Uppaal

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3415 Development of Ceramic Spheres Buoyancy Modules for Deep-Sea Oil Exploration

Authors: G. Blugan, B. Jiang, J. Thornberry, P. Sturzenegger, U. Gonzenbach, M. Misson, D. Cartlidge, R. Stenerud, J. Kuebler

Abstract:

Low-cost ceramic spheres were developed and manufactured from the engineering ceramic aluminium oxide. Hollow spheres of 50 mm diameter with a wall thickness of 0.5-1.0 mm were produced via an adapted slip casting technique. It was possible to produce the spheres with good repeatability and with no defects or failures in the spheres due to the manufacturing process. The spheres were developed specifically for use in buoyancy devices for deep-sea exploration conditions at depths of 3000 m below sea level. The spheres with a 1.0 mm wall thickness exhibit a buoyancy of over 54% while the spheres with a 0.5 mm wall thickness exhibit a buoyancy of over 73%. The mechanical performance of the spheres was confirmed by performing a hydraulic burst pressure test on individual spheres. With a safety factor of 3, all spheres with 1.0 mm wall thickness survived a hydraulic pressure of greater than 150 MPa which is equivalent to a depth of more than 5000 m below sea level. The spheres were then incorporated into a buoyancy module. These hollow aluminium oxide ceramic spheres offer an excellent possibility of deep-sea exploration to depths greater than the currently used technology.

Keywords: buoyancy, ceramic spheres, deep-sea, oil exploration

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3414 Modal Analysis for Study of Minor Historical Architecture

Authors: Milorad Pavlovic, Anna Manzato, Antonella Cecchi

Abstract:

Cultural heritage conservation is a challenge for contemporary society. In recent decades, significant resources have been allocated for the conservation and restoration of architectural heritage. Historical buildings were restored, protected and reinforced with the intent to limit the risks of degradation or loss, due to phenomena of structural damage and to external factors such as differential settlements, earthquake effects, etc. The wide diffusion of historic masonry constructions in Italy, Europe and the Mediterranean area requires reliable tools for the evaluation of their structural safety. In this paper is presented a free modal analysis performed on a minor historical architecture located in the village of Bagno Grande, near the city of L’Aquila in Italy. The location is characterized by a complex urban context, seriously damaged by the earthquake of 2009. The aim of this work is to check the structural behavior of a masonry building characterized by several boundary conditions imposed by adjacent buildings and infrastructural facilities.

Keywords: FEM, masonry, minor historical architecture, modal analysis

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3413 Drying Modeling of Banana Using Cellular Automata

Authors: M. Fathi, Z. Farhaninejad, M. Shahedi, M. Sadeghi

Abstract:

Drying is one of the oldest preservation methods for food and agriculture products. Appropriate control of operation can be obtained by modeling. Limitation of continues models for complex boundary condition and non-regular geometries leading to appearance of discrete novel methods such as cellular automata, which provides a platform for obtaining fast predictions by rule-based mathematics. In this research a one D dimensional CA was used for simulating thin layer drying of banana. Banana slices were dried with a convectional air dryer and experimental data were recorded for validating of final model. The model was programmed by MATLAB, run for 70000 iterations and von-Neumann neighborhood. The validation results showed a good accordance between experimental and predicted data (R=0.99). Cellular automata are capable to reproduce the expected pattern of drying and have a powerful potential for solving physical problems with reasonable accuracy and low calculating resources.

Keywords: banana, cellular automata, drying, modeling

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3412 Transparency in Politics: Evaluation Rules and Principles

Authors: Stylianos Galoukas

Abstract:

since the eve of human societies, the need for survival and covering even the most basic needs such as hunting for food, led to the realization of the need for regulation between the personal and common interest. This led to the establishment of initially unwritten and later on, written rules which then became the Law. Transparency as a word has been used for more than 2.500 years. Born in ancient Greece around the 5th BC century and although it was not originally correlated to political or public administration acts, its enclosed principles and rules, were given even then, great attention. In today’s times of fake news and meta-politics, transparency has greatly correlated with the fight against corruption especially in the financially related matters. It is believed however that transparency, being a much wider than corruption meaning, has an even greater role to play than the corruption counterpart. It can be further used to unveil or examine the genuineness of the will towards the public interest, behind every public policy or political act. Therefore, herein the timeless and fundamental principles of institutional and public administration transparency are made clear as well as their application rules that can and ought to be used as evaluation criteria.

Keywords: evaluation citeria, policies, politics, principles, rules, transparency

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3411 Predicting Bridge Pier Scour Depth with SVM

Authors: Arun Goel

Abstract:

Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper, attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly and Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly and Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicates the improvement in the performance of SVM (Poly and Rbf) in comparison to dimensional form of scour.

Keywords: modeling, pier scour, regression, prediction, SVM (Poly and Rbf kernels)

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3410 Design of an Automated Deep Learning Recurrent Neural Networks System Integrated with IoT for Anomaly Detection in Residential Electric Vehicle Charging in Smart Cities

Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

Abstract:

The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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3409 Effect on Nutritional and Antioxidant Properties of Yellow Alkaline Noodles Substituted with Different Levels of Mangosteen (Garcinia Mangostana) Pericarp Powder

Authors: Mardiana Ahamad Zabidi, Nurain Abdul Karim, Nur Shazrinna Sazali

Abstract:

Mangosteen (Garcinia mangostana) pericarp is considered as agricultural waste and not fully utilized in food products. It is widely reported that mangosteen pericarp contains high antioxidant properties. The objective of this study is to develop novel yellow alkaline noodle (YAN) substituted with different levels of mangosteen pericarp powder (MPP). YAN formulation was substituted with different levels of MPP (0%, 5%, 10% and 15%). The effect on nutritional and antioxidant properties were evaluated. Higher substitution levels of MPP resulted in significant increase (p < 0.05) of ash, fibre, specific mineral elements, and antioxidant properties (total phenolic, total flavonoid, anthocyanin and DPPH) than control sample.

Keywords: antioxidant properties, Mangosteen pericarp, proximate composition, yellow alkaline noodle

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3408 Exploring the Relationship Between Past and Present Reviews: The Influence of User Generated Content on Future Hotel Guest Experience Perceptions

Authors: Sacha Joseph-Mathews, Leili Javadpour

Abstract:

In the tourism industry, hoteliers spend millions annually on marketing and positioning efforts for their respective hotels, all in an effort to create a specific image in the minds of the consumer. Yet despite extensive efforts to seduce potential hotel guests with sophisticated advertising messages generated by hotel entities, consumers continue to mistrust corporate branding, preferring instead to place their trust in the reviews of their consumer peers. In today’s complex and cluttered marketplace, online reviews can serve as a mediator for consumers who do not have actual knowledge and experiences with the brand, but are in the process of deciding whether or not to engage in a consumption exercise. Traditionally, consumers have used online reviews as a source of comfort and confirmation of a product/service’s positioning. But today, very few customers make any purchase decisions without first researching existing user reviews, making reviews more of a necessity, rather than a luxury in the purchase decision process. The influence of user generated content (UGC) is amplified in the tourism industry; as more than a third of potential hotel guests will not book a room without first reading a review. As corporate branding becomes less relevant and online reviews become more important, how much of the consumer’s stay expectations are being dictated by existing UGC? Moreover, as hotel guest experience a hotel through the lens of an existing review, how much of their stay and in turn their review, would have been influenced by those reviews that they read? Ultimately, there is the potential for UGC to dictate what potential guests will be most critical about, and or most focused on during their stay. If UGC is a stronger influencer in the purchase decision process than corporate branding, doesn’t it have the potential to dictate, the entire stay experience by influencing the expectations of the guest prior to them arriving on the property? For example, if a hotel is an eco-destination and they focus their branding on their website around sustainability and the retreat nature of the hotel. Yet, guest reviews constantly discuss how dissatisfactory the service and food was with no mention of nature or sustainability, will future reviews then focus primarily on the food? Using text analysis software to examine over 25,000 online reviews, we explore the extent to which new reviews are influenced by wording used in previous reviews for a hotel property, versus content generated by corporate positioning. Additionally, we investigate how distinct hotel related UGC is across different types of tourism destinations. Our findings suggest that UGC can have a greater impact on future reviews, than corporate branding and there is more cohesiveness across UGC of different types of hotel properties than anticipated. A model of User Generated Content Influence is presented and the managerial impact of the power of online reviews to trump corporate branding and shape future user experiences is discussed.

Keywords: user generated content, UGC, corporate branding, online reviews, hotels and tourism

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3407 Agriculture in the Dominican Republic: Competitiveness in a New Trade Regime and Lessons for Cuba

Authors: Sarita D. Jackson

Abstract:

Agriculture remains a sensitive issue during multilateral trade negotiations within the World Trade Organization (WTO). Similar problems arise at the bilateral level, as in the case of trade talks between the United States and the Dominican Republic. The study explores the determinant of agricultural industry competitiveness in the 21st century, particularly in the case of U.S. and Dominican agriculture in each other’s market. Complementing existing scholarship on industry competitiveness, the study argues that trade rules that are established under preferential access programs and trade agreements play a significant role in shaping an industry’s ability to compete. The final analysis is used to offer recommendations to the same sector in Cuba. Cuba currently relies heavily on U.S. food imports and is experiencing the gradual opening of trade with the United States.

Keywords: agriculture, bargaining, competitiveness, Dominican Republic, DR-CAFTA, free trade agreement, institutions

Procedia PDF Downloads 283
3406 Geospatial Information for Smart City Development

Authors: Simangele Dlamini

Abstract:

Smart city development is seen as a way of facing the challenges brought about by the growing urban population the world over. Research indicates that cities have a role to play in combating urban challenges like crime, waste disposal, greenhouse gas emissions, and resource efficiency. These solutions should be such that they do not make city management less sustainable but should be solutions-driven, cost and resource-efficient, and smart. This study explores opportunities on how the City of Johannesburg, South Africa, can use Geographic Information Systems, Big Data and the Internet of Things (IoT) in identifying opportune areas to initiate smart city initiatives such as smart safety, smart utilities, smart mobility, and smart infrastructure in an integrated manner. The study will combine Big Data, using real-time data sources to identify hotspot areas that will benefit from ICT interventions. The GIS intervention will assist the city in avoiding a silo approach in its smart city development initiatives, an approach that has led to the failure of smart city development in other countries.

Keywords: smart cities, internet of things, geographic information systems, johannesburg

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3405 Counterfeit Drugs Prevention in Pharmaceutical Industry with RFID: A Framework Based On Literature Review

Authors: Zeeshan Hamid, Asher Ramish

Abstract:

The purpose of this paper is to focus on security and safety issues facing by pharmaceutical industry globally when counterfeit drugs are in question. Hence, there is an intense need to secure and authenticate pharmaceutical products in the emerging counterfeit product market. This paper will elaborate the application of radio frequency identification (RFID) in pharmaceutical industry and to identify its key benefits for patient’s care. The benefits are: help to co-ordinate the stream of supplies, accuracy in chains of supplies, maintaining trustworthy information, to manage the operations in appropriate and timely manners and finally deliver the genuine drug to patient. It is discussed that how RFID supported supply chain information sharing (SCIS) helps to combat against counterfeit drugs. And a solution how to tag pharmaceutical products; since, some products prevent RFID implementation in this industry. In this paper, a proposed model for pharma industry distribution suggested to combat against the counterfeit drugs when they are in supply chain.

Keywords: supply chain, RFID, pharmaceutical industry, counterfeit drugs, patients care

Procedia PDF Downloads 314
3404 Uncertainty Estimation in Neural Networks through Transfer Learning

Authors: Ashish James, Anusha James

Abstract:

The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

Procedia PDF Downloads 138
3403 Carbon Dioxide Capture, Utilization, and Storage: Sequestration

Authors: Ankur Sachan

Abstract:

Carbon dioxide being the most anthropogenic greenhouse gas,it needs to be isolated from entering into atmosphere. Carbon capture and storage is process that captures CO2 emitted from various sources, separates it from other gases and stores it in a safe place preferably in underground geological formations for large period of time. It is then purified and monitored so that can be made to reuse. Monoethanolamine, zeolitic imidazolate framework, microalgae, membranes etc are utilized to capture CO2. Post-combustion, pre-combustion and oxyfuel combustion along with chemical looping combustion are technologies for scrubbing CO2. The properties of CO2 being easily miscible and readily dissolving in oil with impurities makes it capable for numerous applications such as in producing oil by enhanced oil recovery (EOR), Bio CCS Algal Synthesis etc. CO2-EOR operation is capable to produce million barrels of oil and extend the field's lifetime as in case of Weyburn Oil Field in Canada. The physical storage of CO2 is technically the most feasible direction provided that the associated safety and sustainability issues can be met and new materials for CCUS process at low cost are urgently found so that so that fossil based systems with carbon capture are cost competitive.

Keywords: carbon capture, CCUS, sustainability, oil

Procedia PDF Downloads 520
3402 Identifying Key Factors for Accidents’ Severity at Rail-Road Level Crossings Using Ordered Probit Models

Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri

Abstract:

The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.

Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors

Procedia PDF Downloads 152
3401 Psychosocial Risk Factors among Women: A Case-Study of the Nigerian Female Worker

Authors: Bassey Odiong Akan

Abstract:

In recent decades potentially significant changes have taken place in the world of work and these have led to the emergence of new challenges in occupational safety and health. The working environment is now not only wroth with concerns about physical, biological and chemical risks but also emerging risks which are completely new risks that have never been seen before or previously known risks that are evolving in unexpected ways with unanticipated consequences. Psychosocial risk factors and its attendant hazards happen to be one of them and can impact health directly or indirectly, mediated by work-related stress. These risks are related to the way work is designed, organised and managed, as well as the economic and social contexts of work. It has become necessary to identify, explore and anticipate the dynamics of these risks factors and hazards with regards to how it affects women. This presentation is a review of information gathered from books of distinguished authors, research work and scientific/professional journals on the psychosocial work environment intended as a guide to stimulate discussion, raise awareness and encourage research and action at different levels.

Keywords: emerging risks, psychosocial hazards, psychosocial risk factors, work related stress

Procedia PDF Downloads 279
3400 Bioflavonoids Derived from Mandarin Processing Wastes: Functional Hydrogels as a Sustainable Food Systems

Authors: Niharika Kaushal, Minni Singh

Abstract:

Fruit crops are widely cultivated throughout the World, with citrus being one of the most common. Mandarins, oranges, grapefruits, lemons, and limes are among the most frequently grown varieties. Citrus cultivars are industrially processed into juice, resulting in approx. 25-40% by wt. of biomass in the form of peels and seeds, generally considered as waste. In consequence, a significant amount of this nutraceutical-enriched biomass goes to waste, which, if utilized wisely, could revolutionize the functional food industry, as this biomass possesses a wide range of bioactive compounds, mainly within the class of polyphenols and terpenoids, making them an abundant source of functional bioactive. Mandarin is a potential source of bioflavonoids with putative antioxidative properties, and its potential application for developing value-added products is obvious. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was studied for its flavonoid profile. For this, dried and pulverized peels were subjected to green and sustainable extraction techniques, namely, supercritical fluid extraction carried out under conditions pressure: 330 bar, temperature: 40 ̊ C and co-solvent: 10% ethanol. The obtained extract was observed to contain 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the prevalence of polymethoxyflavones (PMFs), chiefly tangeretin and nobiletin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which was estimated to be at an IC₅₀ of 0.55μg/ml. The pre-systemic metabolism of flavonoids limits their functionality, as was observed in this study through in vitro gastrointestinal studies where nearly 50.0% of the flavonoids were degraded within 2 hours of gastric exposure. We proposed nanoencapsulation as a means to overcome this problem, and flavonoids-laden polylactic-co-glycolic acid (PLGA) nano encapsulates were bioengineered using solvent evaporation method, and these were furnished to a particle size between 200-250nm, which exhibited protection of flavonoids in the gastric environment, allowing only 20% to be released in 2h. A further step involved impregnating the nano encapsulates within alginate hydrogels which were fabricated by ionic cross-linking, which would act as delivery vehicles within the gastrointestinal (GI) tract. As a result, 100% protection was achieved from the pre-systemic release of bioflavonoids. These alginate hydrogels had key significant features, i.e., less porosity of nearly 20.0%, and Cryo-SEM (Cryo-scanning electron microscopy) images of the composite corroborate the packing ability of the alginate hydrogel. As a result of this work, it is concluded that the waste can be used to develop functional biomaterials while retaining the functionality of the bioactive itself.

Keywords: bioflavonoids, gastrointestinal, hydrogels, mandarins

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3399 The Effect of Gross Vehicle Weight on the Stability of Heavy Vehicle during Cornering

Authors: Nurzaki Ikhsan, Ahmad Saifizul Abdullah, Rahizar Ramli

Abstract:

One of the functions of the commercial heavy vehicle is to safely and efficiently transport goods and people. Due to its size and carrying capacity, it is important to study the vehicle dynamic stability during cornering. Study has shown that there are a number of overloaded heavy vehicles or permissible gross vehicle weight (GVW) violations recorded at selected areas in Malaysia assigned by its type and category. Thus, the objective of this study is to investigate the correlation and effect of the GVW on heavy vehicle stability during cornering event using simulation. Various selected heavy vehicle types and category are simulated using IPG/Truck Maker® with different GVW and road condition (coefficient of friction of road surface), while the speed, driver characteristic, center of gravity of load and road geometry are constant. Based on the analysis, the relationship between GVW and lateral acceleration were established. As expected, on the same value of coefficient of friction, the maximum lateral acceleration would be increased as the GVW increases.

Keywords: heavy vehicle, road safety, vehicle stability, lateral acceleration, gross vehicle weight

Procedia PDF Downloads 532
3398 Evaluation of Diagnosis Performance Based on Pairwise Model Construction and Filtered Data

Authors: Hyun-Woo Cho

Abstract:

It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

Procedia PDF Downloads 245