Search results for: food composition data

Authors: D. P. Rajesh, H. N. Anjanayappa, P. Nayana, S. Benakappa

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The present study deals with length-weight relationship of Atropus atropos for which no information is available on this aspect from Mangalore coast. Therefore the present investigation was undertaken. Fish samples were collected from fish landing center (Mangalore) and fish market. The regression co-efficient of male was found to be lower than female. From this observation it may be opined that female gained more weight with increase in length compared to male. Data on seasonal variation in condition factor (Kn) showed that Kn values were more or less similar in both the sexes, indicating almost identical metabolic activity. Gonadal development and high feeding intensity are the factors which influenced the condition factor. The seasonal fluctuations in the relative condition factor of both the sexes could be attributed to the sexual cycle, food intake and environmental factors. From the present study, it can be inferred that the variation in the condition of Atropus atropos was due to feeding activity and gonadal maturity.

Keywords: Atropus atropos, length-weight relationship, Mangalore coast, relative condition factor, Kn

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Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

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Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: Adenike O. Olatunji-Akioye, Emmanual B Farayola

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In order to improve the animal protein recommended daily intake of Nigerians, there is an upsurge in breeding of hitherto shunned food animals one of which is the rabbit. Radiography and ultrasonography are tools for diagnosing disease and evaluating the anatomical architecture of parts of the body non-invasively. As the rabbit is becoming a more important food animal, to achieve improved breeding of these animals, the best of the species form a breeding stock and will usually depend on breeding soundness which may be evaluated by assessment of the male reproductive organs by these tools. Four male intact rabbits weighing between 1.2 to 1.5 kg were acquired and acclimatized for 2 weeks. Dorsoventral views of the testes were acquired using a digital radiographic machine and a 5 MHz portable ultrasound scanner was used to acquire images of the testes in longitudinal, sagittal and transverse planes. Radiographic images acquired revealed soft tissue images of the testes in all rabbits. The testes lie in individual scrotal sacs sides on both sides of the midline at the level of the caudal vertebrae and thus are superimposed by caudal vertebrae and the caudal limits of the pelvic girdle. The ultrasonographic images revealed mostly homogenously hypoechogenic testes and a hyperechogenic mediastinum testis. The dorsal and ventral poles of the testes were heterogeneously hypoechogenic and correspond to the epididymis and spermatic cord. The rabbit is unique in the ability to retract the testes particularly when stressed and so careful and stressless handling during the procedures is of paramount importance. The imaging of rabbit testes can be safely done using both imaging methods but ultrasonography is a better method of assessment and evaluation of soundness for breeding.

Keywords: breeding soundness, rabbit, radiography, ultrasonography

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Authors: Okpala Charles Chikwendu, Ezeanyim Okechukwu Chiedu, Onukwuli Somto Kenneth

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The demand for lightweight and fuel-efficient automobiles has led to the use of fiber-reinforced polymer composites in place of traditional metal parts. Coir, a natural fiber, offers qualities such as low cost, good tensile strength, and biodegradability, making it a potential filler material for automotive components. However, poor interfacial adhesion between coir and polymeric matrices has been a challenge. To address poor interfacial adhesion with polymeric matrices due to their moisture content and method of preparation, the extracted coir was chemically treated using NaOH. To develop a side view mirror encasement by investigating the mechanical effect of fiber percentage composition, fiber length and percentage composition of Epoxy in a coir fiber reinforced composite, polyester was adopted as the resin for the mold, while that of the product is Epoxy. Coir served as the filler material for the product. Specimens with varied compositions of fiber loading (15, 30 and 45) %, length (10, 15, 20, 30 and 45) mm, and (55, 70, 85) % weight of epoxy resin were fabricated using hand lay-up technique, while those specimens were later subjected to mechanical tests (Tensile, Flexural and Impact test). The results of the mechanical test showed that the optimal solution for the input factors is coir at 45%, epoxy at 54.543%, and 45mm coir length, which was used for the development of a vehicle’s side view mirror encasement. The optimal solutions for the response parameters are 49.333 Mpa for tensile strength, flexural for 57.118 Mpa, impact strength for 34.787 KJ/M2, young modulus for 4.788 GPa, stress for 4.534 KN, and 20.483 mm for strain. The models that were developed using Design Expert software revealed that the input factors can achieve the response parameters in the system with 94% desirability. The study showed that coir is quite durable for filler material in an epoxy composite for automobile applications and that fiber loading and length have a significant effect on the mechanical behavior of coir fiber-reinforced epoxy composites. The coir's low density, considerable tensile strength, and bio-degradability contribute to its eco-friendliness and potential for reducing the environmental hazards of synthetic automotive components.

Keywords: coir, composite, coir fiber, coconut husk, polymer, automobile, mechanical test

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: Rahul Malhotra, Anurag Sharma

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

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Authors: Qianqian He, Naian Liu, Xiaodong Xie, Linhe Zhang, Yang Zhang, Weidong Yan

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In the wild, the vegetation layer with exceptionally complex fuel composition and heterogeneous spatial distribution strongly affects the rate of fire spread (ROS) and fire intensity. Clarifying the influence of fuel bed structure on fire spread behavior is of great significance to wildland fire management and prediction. The packing ratio is one of the key physical parameters describing the property of the fuel bed. There is a threshold value of the packing ratio for ROS, but little is known about the controlling mechanism. In this study, to address this deficiency, a series of fire spread experiments were performed across a discrete fuel bed composed of some regularly arranged laser-cut cardboards, with constant wind speed and different packing ratios (0.0125-0.0375). The experiment aims to explore the relative importance of the internal and surface heat transfer with packing ratio. The dependence of the measured ROS on the packing ratio was almost consistent with the previous researches. The data of the radiative and total heat fluxes show that the internal heat transfer and surface heat transfer are both enhanced with increasing packing ratio (referred to as ‘Stage 1’). The trend agrees well with the variation of the flame length. The results extracted from the video show that the flame length markedly increases with increasing packing ratio in Stage 1. Combustion intensity is suggested to be increased, which, in turn, enhances the heat radiation. The heat flux data shows that the surface heat transfer appears to be more important than the internal heat transfer (fuel preheating inside the fuel bed) in Stage 1. On the contrary, the internal heat transfer dominates the fuel preheating mechanism when the packing ratio further increases (referred to as ‘Stage 2’) because the surface heat flux keeps almost stable with the packing ratio in Stage 2. As for the heat convection, the flow velocity was measured using Pitot tubes both inside and on the upper surface of the fuel bed during the fire spread. Based on the gas velocity distribution ahead of the flame front, it is found that the airflow inside the fuel bed is restricted in Stage 2, which can reduce the internal heat convection in theory. However, the analysis indicates not the influence of inside flow on convection and combustion, but the decreased internal radiation of per unit fuel is responsible for the decrease of ROS.

Keywords: discrete fuel bed, fire spread, packing ratio, wildfire

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Authors: Ali Alhajeri, Tarig Makki, Mosa Almutahhar, Mohammed Ahmed, Usman Ali

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Metal powder is the raw material used for laser powder-bed fusion (LPBF) additive manufacturing (AM). There are many metal materials that can be used in LPBF. The properties of these materials are varied between each other, which can affect the building part. The objective of this paper is to do an overview of the titanium powders available in LBPF. Comparison between different literature works will lead us to study the similarities and differences between the powder properties such as size, shape, and chemical composition. Furthermore, the results of this paper will point out the significant titanium powder properties in order to clearly illustrate their effect on the build parts.

Keywords: LPBF, titanium, Ti-6Al-4V, Ti-5553, metal powder, AM

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

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Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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Authors: Margaret S. Wright

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Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

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Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

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Authors: Nani Mchedlishvili, Nino Omiadze, Marine Abutidze, Jose Neptuno Rodriguez-Lopez, Tinatin Sadunishvili, Nikoloz Pruidze, Giorgi Kvesitadze

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Recently, there is an increased interest in the development of food natural colorants as alternatives to synthetic dyes because of both legislative action and consumer concern. Betalains are widely used in the food industry as an alternative of synthetic colorants. The interest of betalains are caused not only by their coloring effect but also by their beneficial properties. The aim of the work was to study of stability of crude and purified red pigments of pokeberry (Phytolacca america L.). The pokeberry fruit juice was filtrated and concentrated by rotary vacuum evaporator up to 25% and the concentrated juice was passed through the Sepadex-25(fine) column (20×1.1 cm). From the column the pigment elution rate was 18 ml/hr. 1.5ml fractions of pigment were collected. In the fractions the coloring substances were determined using CuS04 x 7 H2O as a standard. From the Sephadex G-25 column only one fraction of the betalain red pigment was eluted with the absorption maximum at 538 nm. The degree of pigment purification was 1.6 and pigment yield from the column was 15 %. It was shown that thermostability of pokeberry fruit red pigment was significantly decreased after the purification. For example, during incubation at 100C for 10 min crude pigment retained 98 % of its color while under the same conditions only 72% of the color of purified pigment was retained. The purified pigment was found to be characterized by less storage stability too. The storage of the initial crude juice and the pigment fraction obtained after the gelfiltration for 10 days at 4°C showed the lost of color by 29 and 74 % respectively. From the results obtained, it can be concluded that during the gelfiltration the pokeberry fruit red pigment gets separated from such substances that cause its stabilization in the crude juice.

Keywords: betalains, gelfiltration, pokeberry fruit, stability

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Authors: Rasoul Eslami, Reza Gharakhanlou

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NT-4/5 and TrkB have been proposed to be involved in the coordinated adaptations of the neuromuscular system to elevated level of activity. Despite the persistence of this neurotrophin and its receptor expression in adult skeletal muscle, little attention has been paid to the functional significance of this complex in the mature neuromuscular system. Therefore, the purpose of this research was to study the effect of one session of resistance exercise on mRNA expression of NT4/5 and TrkB proteins in slow and fast muscles of Wistar Rats. Male Wistar rats (10 mo of age, preparation of Pasteur Institute) were housed under similar living conditions in cages (in groups of four) at room temperature under a controlled light/dark (12-h) cycle with ad libitum access to food and water. A number of sixteen rats were randomly divided to two groups (resistance exercise (T) and control (C); n=8 for each group). The resistance training protocol consisted of climbing a 1-meter–long ladder, with a weight attached to a tail sleeve. Twenty-four hours following the main training session, rats of T and C groups were anaesthetized and the right soleus and flexor hallucis longus (FHL) muscles were removed under sterile conditions via an incision on the dorsolateral aspect of the hind limb. For NT-4/5 and TrkB expression, quantitative real time RT-PCR was used. SPSS software and independent-samples t-test were used for data analysis. The level of significance was set at P < 0.05. Data indicate that resistance training significantly (P<0.05) decreased mRNA expression of NT4/5 in soleus muscle. However, no significant alteration was detected in FHL muscle (P>0.05). Our results also indicate that no significant alterations were detected for TrkB mRNA expression in soleus and FHL muscles (P>0.05). Decrease in mRNA expression of NT4/5 in soleus muscle may be as result of post-translation regulation following resistance training. Also, non-alteration in TrkB mRNA expression was indicated in probable roll of P75 receptor.

Keywords: neurotrophin-4/5 (NT-4/5), TrkB receptor, resistance training, slow and fast muscles

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Authors: Coppa Federica, Iannello Giulia, Pennisi Stefania, Giuffrida Graziella, Lo Faro Riccardo, Cartelli Simone, Ferruggia Greta, Brundo Maria Violetta

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In recent years, a new field of basic research has emerged: the biology and physiology of extracellular vesicles and their application in diagnostics and therapy. In particular, exosomes attract the scientific community as nanovesicles of endosomal origin, which can be secreted by a variety of cells and are found in all biological fluids. Exosomes have recently gained attention also in the cosmetic field: in fact, they are used in creams, serums and masks for topical use, proving to have a series of therapeutic and anti-aging benefits. To date, the oral administration of exosomes is the subject of attention because it represents a non-invasive and efficient method for delivering bioactive molecules into the intestine. We decided to focus our research on the creation of a food supplement that contains various bioactive factors, vitamins, and a new technology called AMPLEX PLUS, containing a mixture of 20 different biologically active factors (GF20) and exosomes isolated and purified from bovine colostrum. We have demonstrated in vitro that this new supplement acts on telomerase, slowing down cell aging. Amplex plus increased the proliferation rate of cells and the addition of it reduced the rate of telomere shortening. Under oxidative stress conditions (H2O2 – induced), the TSR increased; however, treatment with colostrum appeared to attenuate this increase. In particular, after 2 weeks of treatment, AMPLEX plus increased the proliferation rate of cells and exerted a protective effect on telomere length erosion, reducing the rate of its shortening.

Keywords: AMPLEX PLUS, colostrum, exosomes, telomerase

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

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Authors: Luisa Müting, Wisnu Harto Adiwijoyo

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Agroforestry systems transform the agricultural landscapes in the Sahel region of Africa, providing food and farming products consumed for subsistence or sold for income. In the incrementally dry climate of the Sahel region, the spreading of agroforestry practices is integral for policymaker efforts to counteract land degradation and provide soil restoration in the region. Several measures on agroforestry practices have been implemented in the region by governmental and non-governmental institutions in recent years. However, despite the efforts, past research shows that awareness of how policies and interventions are being consumed and perceived by the public remains low. Therefore, interpreting public policy dilemmas by analyzing the public perception regarding agroforestry concepts and practices is necessary. Public perceptions and discourses can be an essential driver or constraint for the adoption of agroforestry practices in the region. Thus, understanding the public discourse behavior of crucial stakeholders could assist policymakers in developing inclusive and contextual policies that are relevant to the context of agroforestry adoption in Sahel region. To answer how information about agroforestry spreads and is perceived by the public. As internet usage increased drastically over the past decade, reaching a share of 33 percent of the population being connected to the internet, this research is based on online conversation data. Social media data from Facebook are gathered daily between April 2021 and April 2022 in Djibouti, Senegal, Mali, and Nigeria based on their share of active internet users compared to other countries in the Sahel region. A systematic methodology was applied to the extracted social media using discourse network analysis (DNA). This study then clustered the data by the types of agroforestry practices, sentiments, and country. Additionally, this research extracted the text data from online news media during the same period to pinpoint events related to the topic of agroforestry. The preliminary result indicates that tree management, crops, and livestock integration, diversifying species and genetic resources, and focusing on interactions and productivity across the agricultural system; are the most notable keywords in agroforestry-related conversations within the four countries in the Sahel region. Additionally, approximately 84 percent of the discussions were still dominated by big actors, such as NGO or government actors. Furthermore, as a subject of communication within agroforestry discourse, the Great Green Wall initiative generates almost 60 percent positive sentiment within the captured social media data, effectively having a more significant outreach than general agroforestry topics. This study provides an understanding for scholars and policymakers with a springboard for further research or policy design on agroforestry in the four countries of the Sahel region with systematically uncaptured novel data from the internet.

Keywords: sahel, djibouti, senegal, mali, nigeria, social networks analysis, public discourse analysis, sentiment analysis, content analysis, social media, online news, agroforestry, land restoration

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Authors: El Kolli Meriem, Laouer Hocine, Sahli Farida, Akkal Salah, El Kolli Hayet

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The aerial parts of Daucus gracilis (Apiaceae) were subjected to hydrodistillation by a Clevenger apparatus to obtain the essential oil (EO) which has been analyzed by Gas Chromatography (GC) and GC coupled with mass spectrometry. The antioxidant properties of this EO and D. gracilis methanolic extract were studied by both of the free diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and the reducing power techniques. The dominant constituents of the EO were the elemicin (35.3 %) and the geranyl acetate (26.8 %). Both of EO and methanolic extract showed important antioxidant properties with respectively IC50 of 0,002 mg/ml and 0.06 mg/ml. They showed also a reducing power dose-dependent.

Keywords: daucus gracilis, apiaceae, essential oil, antioxidant activity

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Authors: Haci Halil Baser, Nurullah Ekmekci, Muammer Zerenler

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In the age of environmental concerns increasingly becoming more important, consumer attitudes towards environmentally sensitive products attract attention. Threats to the health and the environment are important factors for consumers to tend to eco-friendly practices and products. In this regard, it is seen positive increases in the tendency to consume organic food and recyclable products. Choosing products, selecting manufacturers and sellers have gained more importance because of increasing consumers' environmental concerns. In this case, it is very important for businesses to act eco-friendly approach in marketing. Green marketing has gained importance and became a concept that manufacturers' agenda by environmental understanding. Although the green marketing activities are common worldwide, studies on consumer perceptions and preferences are unsatisfactory in the literature. In this regard, this study aims to investigate the tendency of consumers to prefer eco-friendly products under the green marketing activities. In the frame of this information and the purpose of the study described above, the survey method has been used in the study. The obtained data have been analyzed through SPSS 20.0 software package, hypothesizes have been tested and suggestions have been made.

Keywords: eco-friendly product, environmental concerns, green consumption, green marketing

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Authors: Betelhem M. Negede, Maarten Voors, Hugo De Groote, Bart Minten

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Farmers in Ethiopia produce most of their own food during one agricultural season per year. Therefore, they need to use on-farm storage technologies to bridge the lean season and benefit from price arbitrage. Maize stored using traditional storage bags offer no protection from insects and molds, leading to high storage losses. In Ethiopia access to and use of modern storage technologies are still limited, restraining farmers to benefit from local maize price fluctuations. We used a randomized controlled trial among 871 maize farmers to evaluate the impacts of Purdue Improved Crop Storage (PICS) bags, also known as hermetic bags, on storage losses, and especially on behavioral changes with respect to consumption, marketing, and income among maize farmers in Ethiopia. This study builds upon the limited previous experimental research that has tried to understand farmers’ grain storage and post-harvest losses and identify mechanisms behind the persistence of these challenges. Our main hypothesis is that access to PICS bags allows farmers to increase production, storage and maize income. Also delay the length of maize storage, reduce maize post-harvest losses and improve their food security. Our results show that even though farmers received only three PICS bags that represent 10percent of their total maize stored, they delay their length of maize storage for sales by two weeks. However, we find no treatment effect on maize income, suggesting that the arbitrage of two weeks is too small. Also, we do not find any reduction in storage losses due to farmers’ reaction by selling early and by using cheap and readily available but potentially harmful storage chemicals. Looking at the heterogeneity treatment effects between the treatment variable and highland and lowland villages, we find a decrease in the percentage of maize stored by 4 percent in the highland villages. This confirms that location specific factors, such as agro-ecology and proximity to markets are important factors that influence whether and how much of the harvest a farmer stores. These findings highlight the benefits of hermetic storage bags, by allowing farmers to make inter-temporal arbitrage and by reducing potential health risks from storage chemicals. The main policy recommendation that emanates from our study is that postharvest losses reduction throughout the whole value chain is an important pathway to food and income security in Sub-Saharan Africa (SSA). However, future storage loss interventions with hermetic storage technologies should take into account the agro-ecology of the study area and quantify storage losses beyond farmers self-reported losses, such as the count and weigh method. Finally, studies on hermetic storage technologies indicate positive impacts on post-harvest losses and in improving food security, but the adoption and use of these technologies is currently still low in SSA. Therefore, future works on the scaling up of hermetic bags, should consider reasons why farmers only use PICS bags to store grains for consumption, which is usually related to a safety-first approach or due to lack of incentives (higher price from maize not treated with chemicals), and no grain quality check.

Keywords: arbitrage, PICS hermetic bags, post-harvest storage loss, RCT

Procedia PDF Downloads 136

Authors: Thomas Arink, Isam Janajreh

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The petroleum industry generates significant amounts of waste in the form of drill cuttings, contaminated soil and oily sludge. Drill cuttings are a product of the off-shore drilling rigs, containing wet soil and total petroleum hydrocarbons (TPH). Contaminated soil comes from different on-shore sites and also contains TPH. The oily sludge is mainly residue or tank bottom sludge from storage tanks. The two main treatment methods currently used are incineration and thermal desorption (TD). Thermal desorption is a method where the waste material is heated to 450ºC in an anaerobic environment to release volatiles, the condensed volatiles can be used as a liquid fuel. For the thermal desorption unit dry contaminated soil is mixed with moist drill cuttings to generate a suitable mixture. By thermo gravimetric analysis (TGA) of the TD feedstock it was found that less than 50% of the TPH are released, the discharged material is stored in landfill. This study proposes co-gasification of petroleum waste with waste tires as an alternative to thermal desorption. Co-gasification with a high-calorific material is necessary since the petroleum waste consists of more than 60 wt% ash (soil/sand), causing its calorific value to be too low for gasification. Since the gasification process occurs at 900ºC and higher, close to 100% of the TPH can be released, according to the TGA. This work consists of three parts: 1. a mathematical gasification model, 2. a reactive flow CFD model and 3. experimental work on a drop tube reactor. Extensive material characterization was done by means of proximate analysis (TGA), ultimate analysis (CHNOS flash analysis) and calorific value measurements (Bomb calorimeter) for the input parameters of the mathematical and CFD model. The mathematical model is a zero dimensional model based on Gibbs energy minimization together with Lagrange multiplier; it is used to find the product species composition (molar fractions of CO, H2, CH4 etc.) for different tire/petroleum feedstock mixtures and equivalence ratios. The results of the mathematical model act as a reference for the CFD model of the drop-tube reactor. With the CFD model the efficiency and product species composition can be predicted for different mixtures and particle sizes. Finally both models are verified by experiments on a drop tube reactor (1540 mm long, 66 mm inner diameter, 1400 K maximum temperature).

Keywords: computational fluid dynamics (CFD), drop tube reactor, gasification, Gibbs energy minimization, petroleum waste, waste tires

Procedia PDF Downloads 520

Authors: J. Plocek, P. Holec, S. Kubickova, B. Pacakova, I. Matulkova, A. Mantlikova, I. Němec, D. Niznansky, J. Vejpravova

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This article presents summary on preparation and characterization of zinc, copper, cadmium and cobalt chromite nano crystals, embedded in an amorphous silica matrix. The ZnCr2O4/SiO2, CuCr2O4/SiO2, CdCr2O4/SiO2 and CoCr2O4/SiO2 nano composites were prepared by a conventional sol-gel method under acid catalysis. Final heat treatment of the samples was carried out at temperatures in the range of 900–1200 °C to adjust the phase composition and the crystallite size, respectively. The resulting samples were characterized by Powder X-ray diffraction (PXRD), High Resolution Transmission Electron Microscopy (HRTEM), Raman/FTIR spectroscopy and magnetic measurements. Formation of the spinel phase was confirmed in all samples. The average size of the nano crystals was determined from the PXRD data and by direct particle size observation on HRTEM; both results were correlated. The mean particle size (reviewed by HRTEM) was in the range from ~ 4 to 46 nm. The results showed that the sol-gel method can be effectively used for preparation of the spinel chromite nano particles embedded in the silica matrix and the particle size is driven by the type of the cation A2+ in the spinel structure and the temperature of the final heat treatment. Magnetic properties of the nano crystals were found to be just moderately modified in comparison to the bulk phases.

Keywords: sol-gel method, nanocomposites, Rietveld refinement, Raman spectroscopy, Fourier transform infrared spectroscopy, magnetic properties, spinel, chromite

Procedia PDF Downloads 216

Authors: Claudio Lamilla, Andrés Santos, Vicente Llanquinao, Jocelyn Hermosilla, Leticia Barrientos

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The industry in general is very interested in improving and optimizing industrial processes in order to reduce the costs involved in obtaining raw materials and production. Thus, an interesting and cost-effective alternative is the incorporation of bioactive metabolites in such processes, being an example of this enzymes which catalyze efficiently a large number of enzymatic reactions of industrial and biotechnological interest. In the search for new sources of these active metabolites, Antarctica is one of the least explored places on our planet where the most drastic cold conditions, salinity, UVA-UVB and liquid water available are present, features that have shaped all life in this very harsh environment, especially bacteria that live in different Antarctic ecosystems, which have had to develop different strategies to adapt to these conditions, producing unique biochemical strategies. In this work the production of cellulolytic enzymes of seven bacterial strains isolated from marine sediments at different sites in the Antarctic was evaluated. Isolation of the strains was performed using serial dilutions in the culture medium at M115°C. The identification of the strains was performed using universal primers (27F and 1492R). The enzyme activity assays were performed on R2A medium, carboxy methyl cellulose (CMC)was added as substrate. Degradation of the substrate was revealed by adding Lugol. The results show that four of the tested strains produce enzymes which degrade CMC substrate. The molecular identifications, showed that these bacteria belong to the genus Streptomyces and Pseudoalteromonas, being Streptomyces strain who showed the highest activity. Only some bacteria in marine sediments have the ability to produce these enzymes, perhaps due to their greater adaptability to degrade at temperatures bordering zero degrees Celsius, some algae that are abundant in this environment and have cellulose as the main structure. The discovery of new enzymes adapted to cold is of great industrial interest, especially for paper, textiles, detergents, biofuels, food and agriculture. These enzymes represent 8% of industrial demand worldwide and is expected to increase their demand in the coming years. Mainly in the paper and food industry are required in extraction processes starch, protein and juices, as well as the animal feed industry where treating vegetables and grains helps improve the nutritional value of the food, all this clearly puts Antarctic microorganisms and their enzymes specifically as a potential contribution to industry and the novel biotechnological applications.

Keywords: antarctic, bacteria, biotechnological, cellulolytic enzymes

Procedia PDF Downloads 297

Authors: Walid Fantazi

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The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 254

Authors: Shao-Hsuan Chien, Ju-Hui Fu

Abstract:

Parkinson’s disease (PD) is a degenerative disorder of the central nervous system that is characterized by progressive loss of dopaminergic neurons in the substantia nigra pars compacta and motor impairment. Aggregation of α-synuclein in neuronal cells plays a key role in this disease. At present, therapeutics for PD provides moderate symptomatic benefit but is not able to delay the development of this disease. Current efforts for the treatment of PD are to identify new drugs that show slow or arrest progressive course of PD by interfering with a disease-specific pathogenetic process in PD patients. Maackiain is a bioactive compound isolated from the roots of the Chinese herb Sophora flavescens. The purpose of the present study was to assess the potential for maackiain to ameliorate PD in Caenorhabditis elegans models. Our data reveal that maackiain prevents α-synuclein accumulation in the transgenic Caenorhabditis elegans model and also improves dopaminergic neuron degeneration, food-sensing behavior, and life-span in 6-hydroxydopamine-induced Caenorhabditis elegans model, thus indicating its potential as a candidate antiparkinsonian drug.

Keywords: maackiain, Parkinson’s disease, dopaminergic neurons, α-Synuclein

Procedia PDF Downloads 199

Authors: Fauzia Dianawati, Riska W. Purnomo

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Food and agricultural sector become the biggest sector contributing to inflation in Indonesia. Especially in Wonogiri district, red cayenne pepper was the biggest sector contributing to inflation on 2016. A national statistic proved that in recent five years red cayenne pepper has the highest average level of fluctuation among all commodities. Some factors, like supply chain, price disparity, production quantity, crop failure, and oil price become the possible factor causes high volatility level in red cayenne pepper price. Therefore, this research tries to find the key factor causing fluctuation on red cayenne pepper by using ARCH/GARCH method. The method could accommodate the presence of heteroscedasticity in time series data. At the end of the research, it is statistically found that the second level of supply chain becomes the biggest part contributing to inflation with 3,35 of coefficient in fluctuation forecasting model of red cayenne pepper price. This model could become a reference to the government to determine the appropriate policy in maintaining the price stability of red cayenne pepper.

Keywords: ARCH/GARCH, forecasting, red cayenne pepper, volatility, supply chain

Procedia PDF Downloads 186