Search results for: recombinant protein processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5928

Search results for: recombinant protein processing

738 Processing and Characterization of Aluminum Matrix Composite Reinforced with Amorphous Zr₃₇.₅Cu₁₈.₆₇Al₄₃.₉₈ Phase

Authors: P. Abachi, S. Karami, K. Purazrang

Abstract:

The amorphous reinforcements (metallic glasses) can be considered as promising options for reinforcing light-weight aluminum and its alloys. By using the proper type of reinforcement, one can overcome to drawbacks such as interfacial de-cohesion and undesirable reactions which can be created at ceramic particle and metallic matrix interface. In this work, the Zr-based amorphous phase was produced via mechanical milling of elemental powders. Based on Miedema semi-empirical Model and diagrams for formation enthalpies and/or Gibbs free energies of Zr-Cu amorphous phase in comparison with the crystalline phase, the glass formability range was predicted. The composite was produced using the powder mixture of the aluminum and metallic glass and spark plasma sintering (SPS) at the temperature slightly above the glass transition Tg of the metallic glass particles. The selected temperature and rapid sintering route were suitable for consolidation of an aluminum matrix without crystallization of amorphous phase. To characterize amorphous phase formation, X-ray diffraction (XRD) phase analyses were performed on powder mixture after specified intervals of milling. The microstructure of the composite was studied by optical and scanning electron microscope (SEM). Uniaxial compression tests were carried out on composite specimens with the dimension of 4 mm long and a cross-section of 2 ˟ 2mm2. The micrographs indicated an appropriate reinforcement distribution in the metallic matrix. The comparison of stress–strain curves of the consolidated composite and the non-reinforced Al matrix alloy in compression showed that the enhancement of yield strength and mechanical strength are combined with an appreciable plastic strain at fracture. It can be concluded that metallic glasses (amorphous phases) are alternative reinforcement material for lightweight metal matrix composites capable of producing high strength and adequate ductility. However, this is in the expense of minor density increase.

Keywords: aluminum matrix composite, amorphous phase, mechanical alloying, spark plasma sintering

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737 Integrated On-Board Diagnostic-II and Direct Controller Area Network Access for Vehicle Monitoring System

Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

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The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

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736 The Strategy for Detection of Catecholamines in Body Fluids: Optical Sensor

Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha, Kamila Drzozga

Abstract:

Catecholamines are the principal neurotransmitters that mediate a variety of the central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, fluorescent techniques for detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid modified biosensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in the manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence sensing strategy for catecholamines detection based on FRET (fluorescence resonance energy transfer) phenomena observed for, i.e., complexes of Fe²⁺ and epinephrine. The biosensor was constructed using low temperature co-fired ceramics technology (LTCC). This sensing system used the catalytical oxidation of catecholamines and quench of the strong luminescence of obtained complexes due to FRET. The detection process was based on the oxidation of substrate in the presence of the enzyme–laccase/tyrosinase.

Keywords: biosensor, conducting polymer, enzyme, FRET, LTCC

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735 Lexical-Semantic Deficits in Sinhala Speaking Persons with Post Stroke Aphasia: Evidence from Single Word Auditory Comprehension Task

Authors: D. W. M. S. Samarathunga, Isuru Dharmarathne

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In aphasia, various levels of symbolic language processing (semantics) are affected. It is shown that Persons with Aphasia (PWA) often experience more problems comprehending some categories of words than others. The study aimed to determine lexical semantic deficits seen in Auditory Comprehension (AC) and to describe lexical-semantic deficits across six selected word categories. Thirteen (n =13) persons diagnosed with post-stroke aphasia (PSA) were recruited to perform an AC task. Foods, objects, clothes, vehicles, body parts and animals were selected as the six categories. As the test stimuli, black and white line drawings were adapted from a picture set developed for semantic studies by Snodgrass and Vanderwart. A pilot study was conducted with five (n=5) healthy nonbrain damaged Sinhala speaking adults to decide familiarity and applicability of the test material. In the main study, participants were scored based on the accuracy and number of errors shown. The results indicate similar trends of lexical semantic deficits identified in the literature confirming ‘animals’ to be the easiest category to comprehend. Mann-Whitney U test was performed to determine the association between the selected variables and the participants’ performance on AC task. No statistical significance was found between the errors and the type of aphasia reflecting similar patterns described in aphasia literature in other languages. The current study indicates the presence of selectivity of lexical semantic deficits in AC and a hierarchy was developed based on the complexity of the categories to comprehend by Sinhala speaking PWA, which might be clinically beneficial when improving language skills of Sinhala speaking persons with post-stroke aphasia. However, further studies on aphasia should be conducted with larger samples for a longer period to study deficits in Sinhala and other Sri Lankan languages (Tamil and Malay).

Keywords: aphasia, auditory comprehension, selective lexical-semantic deficits, semantic categories

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734 A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses

Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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733 Alternative Seed System for Enhanced Availability of Quality Seeds and Seed/Varietal Replacement Rate - An Experience

Authors: Basave Gowda, Lokesh K., Prasanth S. M., Bellad S. B., Radha J., Lokesh G. Y., Patil S. B., Vijayakumar D. K., Ganigar B. S., Rakesh C. Mathad

Abstract:

Quality seed plays an important role in enhancing the crop productivity. It was reported and confirmed by large scale verification research trials that by use of quality seeds alone, the crop yield can be enhanced by 15 to 20 per cent. At present, the quality seed production and distribution through organised sectors comprising both public and private seed sector was only 20-25% of the requirement and the remaining quantity is met through unorganised sector which include the farmer to farmers saved seeds. With an objective of developing an alternative seed system, the University of Agricultural Sciences, Raichur in Karnataka state has implemented Seed Village Programme in more than 100 villages covering around 5000 farmers every year since 2009-10 and in the selected seed villages, a group of 50-150 farmers were supplied the foundation seeds of new varieties to an extent of 0.4 ha at 50 % subsidy. And two to three training programmes were conducted in the targeted villages for quality seed production and the seed produced in the target group was processed locally in the university seed processing units and arranged for distribution in the local villages by the seed growers themselves. By this new innovative and modified seed system, the university can able to replace old varieties of pigeon pea and green gram by producing 1482, 2978, 2729, 2560, and 4581 tonnes of seeds of new varieties on large scale under farmers and scientists participatory seed village programmes respectively during 2009-10, 2010-11, 2011-12, 2012-13 and 2013-14. From this new alternate model of seed system, there should be large scale promotion of regional seed system involving farmers, NGO and voluntary organisation for quick and effective replacement of old, low yielding, disease susceptible varieties with new high yielding, disease resistant for enhanced food production and food security.

Keywords: seed system, seed village, seed replacement, varietal replacement

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732 Comparison Study of 70% Ethanol Effect on Direct and Retrival Culture of Contaminated Umblical Cord Tissue for Expansion of Mesenchymal Stem Cells

Authors: Ganeshkumar, Ashika, Valavan, Ramesh, Thangam, Chirayu

Abstract:

MSCs are found in much higher concentration in the Wharton’s jelly compared to the umbilical cord blood, which is a rich source of hematopoietic stem cells. Umbilical cord tissue is collected at the time of birth; it is processed and stored in liquid nitrogen for future therapeutical purpose. The source of contamination might be either from vaginal tract of mother or from hospital environment or from personal handling during cord tissue sample collection. If the sample were contaminated, decontamination procedure will be done with 70% ethanol (1 minute) in order to avoid sample rejection. Ethanol is effective against a wide range of bacteria, protozoa and fungi and has low toxicity to humans. Among the 1954 samples taken for the study, 24 samples were found to be contaminated with microorganism. The organisms isolated from the positive samples were found to be E. coli, Stenotrophomonas maltophilia, Pseudomonas aueroginosa, Enterococcus fecalis, Acinetobacter bowmani, Staphylococcus epidermidis, Enterobacter cloacae, and Proteus mirabilis. Among these organisms 70% ethanol successfully eliminated E. coli, Enterococcus fecalis, Acinetobacter bowmani, Staphylococcus epidermidis, and Proteus mirabilis. 70% ethanol was unsuccessful in eliminating Stenotrophomonas maltophilia, Pseudomonas aueroginosa, and Enterobacter cloacae. Stenotrophomonas maltophilia and Pseudomonas aueroginosa have the ability to form biofilm that make them resistant to alcohol. Biofilm act as protective layer for bacteria and which protects them from host defense and antibiotic wash. Finally it was found 70% ethanol wash saved 58.3% cord tissue samples from rejection and it is ineffective against 41% of the samples. The contamination rate can be reduced by maintaining proper aseptic techniques during sample collection and processing.

Keywords: umblical cord tissue, decontamination, 70% ethanol effectiveness, contamination

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731 Application of Hyperspectral Remote Sensing in Sambhar Salt Lake, A Ramsar Site of Rajasthan, India

Authors: Rajashree Naik, Laxmi Kant Sharma

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Sambhar lake is the largest inland Salt Lake of India, declared as a Ramsar site on 23 March 1990. Due to high salinity and alkalinity condition its biodiversity richness is contributed by haloalkaliphilic flora and fauna along with the diverse land cover including waterbody, wetland, salt crust, saline soil, vegetation, scrub land and barren land which welcome large number of flamingos and other migratory birds for winter harboring. But with the gradual increase in the irrational salt extraction activities, the ecological diversity is at stake. There is an urgent need to assess the ecosystem. Advanced technology like remote sensing and GIS has enabled to look into the past, compare with the present for the future planning and management of the natural resources in a judicious way. This paper is a research work intended to present a vegetation in typical inland lake environment of Sambhar wetland using satellite data of NASA’s EO-1 Hyperion sensor launched in November 2000. With the spectral range of 0.4 to 2.5 micrometer at approximately 10nm spectral resolution with 242 bands 30m spatial resolution and 705km orbit was used to produce a vegetation map for a portion of the wetland. The vegetation map was tested for classification accuracy with a pre-existing detailed GIS wetland vegetation database. Though the accuracy varied greatly for different classes the algal communities were successfully identified which are the major sources of food for flamingo. The results from this study have practical implications for uses of spaceborne hyperspectral image data that are now becoming available. Practical limitations of using these satellite data for wetland vegetation mapping include inadequate spatial resolution, complexity of image processing procedures, and lack of stereo viewing.

Keywords: Algal community, NASA’s EO-1 Hyperion, salt-tolerant species, wetland vegetation mapping

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730 Carbon-Encapsulated Iron Nanoparticles for Hydrogen Sulfide Removal

Authors: Meriem Abid, Erika Oliveria-Jardim, Andres Fullana, Joaquin Silvestre-Albero

Abstract:

The rapid industrial development associated with the increase of volatile organic compounds (VOCs) has seriously impacted the environment. Among VOCs, hydrogen sulfide (H₂S) is known as a highly toxic, malodorous, flammable, and corrosive gas, which is emitted from diverse chemical processes, including industrial waste-gas streams, natural gas processing, and biogas purification. The high toxicity, corrosively, and very characteristic odor threshold of H2S call for urgent development of efficient desulfurization processes from the viewpoint of environmental protection and resource regeneration. In order to reduce H₂S emissions, effective technologies for have been performed. The general method of H₂S removal included amine aqueous solution, adsorption process, biological methods, and fixed-bed solid catalytic oxidation processes. Ecologically and economically, low-temperature direct oxidation of H₂S to elemental sulfur using catalytic oxidation is the preferred approach for removing H₂S-containing gas streams. A large number of catalysts made from carbon, metal oxides, clay, and others, have been studied extensively for this application. In this sense, activated carbon (AC) is an attractive catalyst for H₂S removal because it features a high specific surface area, diverse functional groups, low cost, durability, and high efficiency. It is interesting to stand out that AC is modified using metal oxides to promote the efficiency of H₂S removal and to enhance the catalytic performance. Based on these premises, the main goal of the present study is the evaluation of the H₂S adsorption performance in carbon-encapsulated iron nanoparticles obtained from an olive mill, thermally treated at 600, 800 and 1000 ºC temperatures under anaerobic conditions. These results anticipate that carbon-encapsulated iron nanoparticles exhibit a promising performance for the H₂S removal up to 360 mg/g.

Keywords: H₂S removal, catalytic oxidation, carbon encapsulated iron, olive mill wastewater

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729 Immunoliposome-Mediated Drug Delivery to Plasmodium-Infected and Non-Infected Red Blood Cells as a Dual Therapeutic/Prophylactic Antimalarial Strategy

Authors: Ernest Moles, Patricia Urbán, María Belén Jiménez-Díaz, Sara Viera-Morilla, Iñigo Angulo-Barturen, Maria Antònia Busquets, Xavier Fernàndez-Busquets

Abstract:

Bearing in mind the absence of an effective vaccine against malaria and its severe clinical manifestations causing nearly half a million deaths every year, this disease represents nowadays a major threat to life. Besides, the basic rationale followed by currently marketed antimalarial approaches is based on the administration of drugs on their own, promoting the emergence of drug-resistant parasites owing to the limitation in delivering drug payloads into the parasitized erythrocyte high enough to kill the intracellular pathogen while minimizing the risk of causing toxic side effects to the patient. Such dichotomy has been successfully addressed through the specific delivery of immunoliposome (iLP)-encapsulated antimalarials to Plasmodium falciparum-infected red blood cells (pRBCs). Unfortunately, this strategy has not progressed towards clinical applications, whereas in vitro assays rarely reach drug efficacy improvements above 10-fold. Here, we show that encapsulation efficiencies reaching >96% can be achieved for the weakly basic drugs chloroquine (CQ) and primaquine using the pH gradient active loading method in liposomes composed of neutrally charged, saturated phospholipids. Targeting antibodies are best conjugated through their primary amino groups, adjusting chemical crosslinker concentration to retain significant antigen recognition. Antigens from non-parasitized RBCs have also been considered as targets for the intracellular delivery of drugs not affecting the erythrocytic metabolism. Using this strategy, we have obtained unprecedented nanocarrier targeting to early intraerythrocytic stages of the malaria parasite for which there is a lack of specific extracellular molecular tags. Polyethylene glycol-coated liposomes conjugated with monoclonal antibodies specific for the erythrocyte surface protein glycophorin A (anti-GPA iLP) were capable of targeting 100% RBCs and pRBCs at the low concentration of 0.5 μM total lipid in the culture, with >95% of added iLPs retained into the cells. When exposed for only 15 min to P. falciparum in vitro cultures synchronized at early stages, free CQ had no significant effect over parasite viability up to 200 nM drug, whereas iLP-encapsulated 50 nM CQ completely arrested its growth. Furthermore, when assayed in vivo in P. falciparum-infected humanized mice, anti-GPA iLPs cleared the pathogen below detectable levels at a CQ dose of 0.5 mg/kg. In comparison, free CQ administered at 1.75 mg/kg was, at most, 40-fold less efficient. Our data suggest that this significant improvement in drug antimalarial efficacy is in part due to a prophylactic effect of CQ found by the pathogen in its host cell right at the very moment of invasion.

Keywords: immunoliposomal nanoparticles, malaria, prophylactic-therapeutic polyvalent activity, targeted drug delivery

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728 Aerofloral Studies and Allergenicity Potentials of Dominant Atmospheric Pollen Types at Some Locations in Northwestern Nigeria

Authors: Olugbenga S. Alebiosu, Olusola H. Adekanmbi, Oluwatoyin T. Ogundipe

Abstract:

Pollen and spores have been identified as major airborne bio-particles inducing respiratory disorders such as asthma, allergic rhinitis and atopic dermatitis among hypersensitive individuals. An aeropalynological study was conducted within a one year sampling period with a view to investigating the monthly depositional rate of atmospheric pollen and spores; influence of the immediate vegetation on airborne pollen distribution; allergenic potentials of dominant atmospheric pollen types at selected study locations in Bauchi and Taraba states, Northwestern Nigeria. A tauber-like pollen trap was employed in aerosampling with the sampler positioned at a height of 5 feet above the ground, followed by a monthly collection of the recipient solution for the sampling period. The collected samples were subjected to acetolysis treatment, examined microscopically with the identification of pollen grains and spores using reference materials and published photomicrographs. Plants within the surrounding vegetation were enumerated. Crude protein contents extracted from pollen types found to be commonly dominant at both study locations; Senna siamea, Terminalia cattapa, Panicum maximum and Zea mays were used to sensitize Musmusculus. Histopathological studies of bronchi and lung sections from certain dead M.musculus in the test groups was conducted. Blood samples were collected from the pre-orbital vein of M.musculus and processed for serological and haematological (differential and total white blood cell counts) studies. ELISA was used in determining the levels of serological parameters: IgE and cytokines (TNF-, IL-5, and IL-13). Statistical significance was observed in the correlation between the levels of serological and haematological parameters elicited by each test group, differences between the levels of serological and haematological parameters elicited by each test group and those of the control, as well as at varying sensitization periods. The results from this study revealed dominant airborne pollen types across the study locations; Syzygiumguineense, Tridaxprocumbens, Elaeisguineensis, Mimosa sp., Borreria sp., Terminalia sp., Senna sp. and Poaceae. Nephrolepis sp., Pteris sp. and a trilete fern also produced spores. This study also revealed that some of the airborne pollen types were produced by local plants at the study locations. Bronchi sections of M.musculus after first and second sensitizations, as well as lung section after first sensitization with Senna siamea, showed areas of necrosis. Statistical significance was recorded in the correlation between the levels of some serological and haematological parameters produced by each test group and those of the control, as well as at certain sensitization periods. The study revealed some candidate pollen allergens at the study locations allergy sufferers and also established a complexity of interaction between immune cells, IgE and cytokines at varied periods of mice sensitization and forming a paradigm of human immune response to different pollen allergens. However, it is expedient that further studies should be conducted on these candidate pollen allergens for their allergenicity potential in humans within their immediate environment.

Keywords: airborne, hypersensitive, mus musculus, pollen allergens, respiratory, tauber-like

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727 Silicon-Photonic-Sensor System for Botulinum Toxin Detection in Water

Authors: Binh T. T. Nguyen, Zhenyu Li, Eric Yap, Yi Zhang, Ai-Qun Liu

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Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection.

Keywords: biotoxin, photonic, ring resonator, sensor

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726 Motion Planning and Simulation Design of a Redundant Robot for Sheet Metal Bending Processes

Authors: Chih-Jer Lin, Jian-Hong Hou

Abstract:

Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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725 Stability of Total Phenolic Concentration and Antioxidant Capacity of Extracts from Pomegranate Co-Products Subjected to In vitro Digestion

Authors: Olaniyi Fawole, Umezuruike Opara

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Co-products obtained from pomegranate juice processing contain high levels of polyphenols with potential high added values. From value-addition viewpoint, the aim of this study was to evaluate the stability of polyphenolic concentrations in pomegranate fruit co-products in different solvent extracts and assess the effect on the total antioxidant capacity using the FRAP, DPPH˙ and ABTS˙+ assays during simulated in vitro digestion. Pomegranate juice, marc and peel were extracted in water, 50% ethanol (50%EtOH) and absolute ethanol (100%EtOH) and analysed for total phenolic concentration (TPC), total flavonoids concentration (TFC) and total antioxidant capacity in DPPH˙, ABST˙+ and FRAP assays before and after in vitro digestion. Total phenolic concentration (TPC) and total flavonoid concentration (TFC) were in the order of peel > marc > juice throughout the in vitro digestion irrespective of the extraction solvents used. However, 50% ethanol extracted 1.1 to 12-fold more polyphenols than water and ethanol solvents depending on co-products. TPC and TFC increased significantly in gastric digests. In contrast, after the duodenal, polyphenolic concentrations decreased significantly (p < 0.05) compared to those obtained in gastric digests. Undigested samples and gastric digests showed strong and positive relationships between polyphenols and the antioxidant activities measured in DPPH, ABTS and FRAP assays, with correlation coefficients (r2) ranging between 0.930 – 0.990 whereas, the correlation between polyphenols (TPC and TFC) and radical cation scavenging activity (in ABTS) were moderately positive in duodenal digests. Findings from this study also showed that the concentration of pomegranate polyphenols and antioxidant thereof during in vitro gastro-intestinal digestion may not reflect the pre-digested phenolic concentration. Thus, this study highlights the need to provide biologically relevant information on antioxidants by providing data reflecting their stability and activity after in vitro digestion.

Keywords: by-product, DPPH, polyphenols, value addition

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724 A Nutrient Formulation Affects Brain Myelination in Infants: An Investigative Randomized Controlled Trial

Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

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Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

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723 Foamability and Foam Stability of Gelatine-Sodium Dodecyl Sulfate Solutions

Authors: Virginia Martin Torrejon, Song Hang

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Gelatine foams are widely explored materials due to their biodegradability, biocompatibility, and availability. They exhibit outstanding properties and are currently subject to increasing scientific research due to their potential use in different applications, such as biocompatible cellular materials for biomedical products or biofoams as an alternative to fossil-fuel-derived packaging. Gelatine is a highly surface-active polymer, and its concentrated solutions usually do not require surfactants to achieve low surface tension. Still, anionic surfactants like sodium dodecyl sulfate (SDS) strongly interact with gelatine, impacting its viscosity and rheological properties and, in turn, their foaming behaviour. Foaming behaviour is a key parameter for cellular solids produced by mechanical foaming as it has a significant effect on the processing and properties of cellular materials. Foamability mainly impacts the density and the mechanical properties of the foams, while foam stability is crucial to achieving foams with low shrinkage and desirable pore morphology. This work aimed to investigate the influence of SDS on the foaming behaviour of concentrated gelatine foams by using a dynamic foam analyser. The study of maximum foam height created, foam formation behaviour, drainage behaviour, and foam structure with regard to bubble size and distribution were carried out in 10 wt% gelatine solutions prepared at different SDS/gelatine concentration ratios. Comparative rheological and viscometry measurements provided a good correlation with the data from the dynamic foam analyser measurements. SDS incorporation at optimum dosages and gelatine gelation led to highly stable foams at high expansion ratios. The viscosity increase of the hydrogel solution at SDS content increased was a key parameter for foam stabilization. In addition, the impact of SDS content on gelling time and gel strength also considerably impacted the foams' stability and pore structure.

Keywords: dynamic foam analyser, gelatine foams stability and foamability, gelatine-surfactant foams, gelatine-SDS rheology, gelatine-SDS viscosity

Procedia PDF Downloads 147
722 AI for Efficient Geothermal Exploration and Utilization

Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

Procedia PDF Downloads 46
721 Pattern of Anisometropia, Management and Outcome of Anisometropic Amblyopia

Authors: Husain Rajib, T. H. Sheikh, D. G. Jewel

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Background: Amblyopia is a frequent cause of monocular blindness in children. It can be unilateral or bilateral reduction of best corrected visual acuity associated with decrement in visual processing, accomodation, motility, spatial perception or spatial projection. Anisometropia is an important risk factor for amblyopia that develops when unequal refractive error causes the image to be blurred in the critical developmental period and central inhibition of the visual signal originating from the affected eye associated with significant visual problems including anisokonia, strabismus, and reduced stereopsis. Methods: It is a prospective hospital based study of newly diagnosed of amblyopia seen at the pediatric clinic of Chittagong Eye Infirmary & Training Complex. There were 50 anisometropic amblyopia subjects were examined & questionnaire was piloted. Included were all patients diagnosed with refractive amblyopia between 3 to 13 years, without previous amblyopia treatment, and whose parents were interested to participate in the study. Patients diagnosed with strabismic amblyopia were excluded. Patients were first corrected with the best correction for a month. When the VA in the amblyopic eye did not improve over month, then occlusion treatment was started. Occlusion was done daily for 6-8 hours (full time) together with vision therapy. The occlusion was carried out for 3 months. Results: In this study about 8% subjects had anisometropia from myopia, 18% from hyperopia, 74% from astigmatism. The initial mean visual acuity was 0.74 ± 0.39 Log MAR and after intervention of amblyopia therapy with active vision therapy mean visual acuity was 0.34 ± 0.26 Log MAR. About 94% of subjects were improving at least two lines. The depth of amblyopia associated with type of anisometropic refractive error and magnitude of Anisometropia (p<0.005). By doing this study 10% mild amblyopia, 64% moderate and 26% severe amblyopia were found. Binocular function also decreases with magnitude of Anisometropia. Conclusion: Anisometropic amblyopia is a most important factor in pediatric age group because it can lead to visual impairment. Occlusion therapy with at least one instructed hour of active visual activity practiced out of school hours was effective in anisometropic amblyopes who were diagnosed at the age of 8 years and older, and the patients complied well with the treatment.

Keywords: refractive error, anisometropia, amblyopia, strabismic amblyopia

Procedia PDF Downloads 275
720 Metal Extraction into Ionic Liquids and Hydrophobic Deep Eutectic Mixtures

Authors: E. E. Tereshatov, M. Yu. Boltoeva, V. Mazan, M. F. Volia, C. M. Folden III

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Room temperature ionic liquids (RTILs) are a class of liquid organic salts with melting points below 20 °C that are considered to be environmentally friendly ‘designers’ solvents. Pure hydrophobic ILs are known to extract metallic species from aqueous solutions. The closest analogues of ionic liquids are deep eutectic solvents (DESs), which are a eutectic mixture of at least two compounds with a melting point lower than that of each individual component. DESs are acknowledged to be attractive for organic synthesis and metal processing. Thus, these non-volatile and less toxic compounds are of interest for critical metal extraction. The US Department of Energy and the European Commission consider indium as a key metal. Its chemical homologue, thallium, is also an important material for some applications and environmental safety. The aim of this work is to systematically investigate In and Tl extraction from aqueous solutions into pure fluorinated ILs and hydrophobic DESs. The dependence of the Tl extraction efficiency on the structure and composition of the ionic liquid ions, metal oxidation state, and initial metal and aqueous acid concentrations have been studied. The extraction efficiency of the TlXz3–z anionic species (where X = Cl– and/or Br–) is greater for ionic liquids with more hydrophobic cations. Unexpectedly high distribution ratios (> 103) of Tl(III) were determined even by applying a pure ionic liquid as receiving phase. An improved mathematical model based on ion exchange and ion pair formation mechanisms has been developed to describe the co-extraction of two different anionic species, and the relative contributions of each mechanism have been determined. The first evidence of indium extraction into new quaternary ammonium- and menthol-based hydrophobic DESs from hydrochloric and oxalic acid solutions with distribution ratios up to 103 will be provided. Data obtained allow us to interpret the mechanism of thallium and indium extraction into ILs and DESs media. The understanding of Tl and In chemical behavior in these new media is imperative for the further improvement of separation and purification of these elements.

Keywords: deep eutectic solvents, indium, ionic liquids, thallium

Procedia PDF Downloads 238
719 Neural Correlates of Attention Bias to Threat during the Emotional Stroop Task in Schizophrenia

Authors: Camellia Al-Ibrahim, Jenny Yiend, Sukhwinder S. Shergill

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Background: Attention bias to threat play a role in the development, maintenance, and exacerbation of delusional beliefs in schizophrenia in which patients emphasize the threatening characteristics of stimuli and prioritise them for processing. Cognitive control deficits arise when task-irrelevant emotional information elicits attentional bias and obstruct optimal performance. This study is investigating neural correlates of interference effect of linguistic threat and whether these effects are independent of delusional severity. Methods: Using an event-related functional magnetic resonance imaging (fMRI), neural correlates of interference effect of linguistic threat during the emotional Stroop task were investigated and compared patients with schizophrenia with high (N=17) and low (N=16) paranoid symptoms and healthy controls (N=20). Participants were instructed to identify the font colour of each word presented on the screen as quickly and accurately as possible. Stimuli types vary between threat-relevant, positive and neutral words. Results: Group differences in whole brain effects indicate decreased amygdala activity in patients with high paranoid symptoms compared with low paranoid patients and healthy controls. Regions of interest analysis (ROI) validated our results within the amygdala and investigated changes within the striatum showing a pattern of reduced activation within the clinical group compared to healthy controls. Delusional severity was associated with significant decreased neural activity in the striatum within the clinical group. Conclusion: Our findings suggest that the emotional interference mediated by the amygdala and striatum may reduce responsiveness to threat-related stimuli in schizophrenia and that attenuation of fMRI Blood-oxygen-level dependent (BOLD) signal within these areas might be influenced by the severity of delusional symptoms.

Keywords: attention bias, fMRI, Schizophrenia, Stroop

Procedia PDF Downloads 196
718 A Single Feature Probability-Object Based Image Analysis for Assessing Urban Landcover Change: A Case Study of Muscat Governorate in Oman

Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

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The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

Procedia PDF Downloads 271
717 Improving the Supply Chain of Vietnamese Coffee in Buon Me Thuot City, Daklak Province, Vietnam to Achieve Sustainability

Authors: Giang Ngo Tinh Nguyen

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Agriculture plays an important role in the economy of Vietnam and coffee is one of most crucial agricultural commodities for exporting but the current farming methods and processing infrastructure could not keep up with the development of the sector. There are many catastrophic impacts on the environment such as deforestation; soil degradation that leads to a decrease in the quality of coffee beans. Therefore, improving supply chain to develop the cultivation of sustainable coffee is one of the most important strategies to boost the coffee industry and create a competitive advantage for Vietnamese coffee in the worldwide market. If all stakeholders in the supply chain network unite together; the sustainable production of coffee will be scaled up and the future of coffee industry will be firmly secured. Buon Ma Thuot city, Dak Lak province is the principal growing region for Vietnamese coffee which accounted for a third of total coffee area in Vietnam. It plays a strategically crucial role in the development of sustainable Vietnamese coffee. Thus, the research is to improve the supply chain of sustainable Vietnamese coffee production in Buon Ma Thuot city, Dak Lak province, Vietnam for the purpose of increasing the yields and export availability as well as helping coffee farmers to be more flexible in an ever-changing market situation. It will help to affirm Vietnamese coffee brand when entering international market; improve the livelihood of farmers and conserve the environment of this area. Besides, after analyzing the data, a logistic regression model is established to explain the relationship between the dependent variable and independent variables to help sustainable coffee organizations forecast the probability of farmer will be having a sustainable certificate with their current situation and help them choose promising candidates to develop sustainable programs. It investigates opinions of local farmers through quantitative surveys. Qualitative interviews are also used to interview local collectors and staff of Trung Nguyen manufacturing company to have an overview of the situation.

Keywords: supply chain management, sustainable agricultural development, sustainable coffee, Vietnamese coffee

Procedia PDF Downloads 443
716 A Study on the Application of Machine Learning and Deep Learning Techniques for Skin Cancer Detection

Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

Procedia PDF Downloads 81
715 The Optimal Order Policy for the Newsvendor Model under Worker Learning

Authors: Sunantha Teyarachakul

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We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems.

Keywords: inventory management, Newsvendor model, order policy, worker learning

Procedia PDF Downloads 412
714 From Biowaste to Biobased Products: Life Cycle Assessment of VALUEWASTE Solution

Authors: Andrés Lara Guillén, José M. Soriano Disla, Gemma Castejón Martínez, David Fernández-Gutiérrez

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The worldwide population is exponentially increasing, which causes a rising demand for food, energy and non-renewable resources. These demands must be attended to from a circular economy point of view. Under this approach, the obtention of strategic products from biowaste is crucial for the society to keep the current lifestyle reducing the environmental and social issues linked to the lineal economy. This is the main objective of the VALUEWASTE project. VALUEWASTE is about valorizing urban biowaste into proteins for food and feed and biofertilizers, closing the loop of this waste stream. In order to achieve this objective, the project validates three value chains, which begin with the anaerobic digestion of the biowaste. From the anaerobic digestion, three by-products are obtained: i) methane that is used by microorganisms, which will be transformed into microbial proteins; ii) digestate that is used by black soldier fly, producing insect proteins; and iii) a nutrient-rich effluent, which will be transformed into biofertilizers. VALUEWASTE is an innovative solution, which combines different technologies to valorize entirely the biowaste. However, it is also required to demonstrate that the solution is greener than other traditional technologies (baseline systems). On one hand, the proteins from microorganisms and insects will be compared with other reference protein production systems (gluten, whey and soybean). On the other hand, the biofertilizers will be compared to the production of mineral fertilizers (ammonium sulphate and synthetic struvite). Therefore, the aim of this study is to provide that biowaste valorization can reduce the environmental impacts linked to both traditional proteins manufacturing processes and mineral fertilizers, not only at a pilot-scale but also at an industrial one. In the present study, both baseline system and VALUEWASTE solution are evaluated through the Environmental Life Cycle Assessment (E-LCA). The E-LCA is based on the standards ISO 14040 and 14044. The Environmental Footprint methodology was the one used in this study to evaluate the environmental impacts. The results for the baseline cases show that the food proteins coming from whey have the highest environmental impact on ecosystems compared to the other proteins sources: 7.5 and 15.9 folds higher than soybean and gluten, respectively. Comparing feed soybean and gluten, soybean has an environmental impact on human health 195.1 folds higher. In the case of biofertilizers, synthetic struvite has higher impacts than ammonium sulfate: 15.3 (ecosystems) and 11.8 (human health) fold, respectively. The results shown in the present study will be used as a reference to demonstrate the better environmental performance of the bio-based products obtained through the VALUEWASTE solution. Other originalities that the E-LCA performed in the VALUEWASTE project provides are the diverse direct implications on investment and policies. On one hand, better environmental performance will serve to remove the barriers linked to these kinds of technologies, boosting the investment that is backed by the E-LCA. On the other hand, it will be a germ to design new policies fostering these types of solutions to achieve two of the key targets of the European Community: being self-sustainable and carbon neutral.

Keywords: anaerobic digestion, biofertilizers, circular economy, nutrients recovery

Procedia PDF Downloads 87
713 Progress in Replacing Antibiotics in Farm Animal Production

Authors: Debabrata Biswas

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The current trend in the development of antibiotic resistance by multiple bacterial pathogens has resulted in a troubling loss of effective antibiotic options for human. The emergence of multi-drug-resistant pathogens has necessitated higher dosages and combinations of multiple antibiotics, further exacerbating the problem of antibiotic resistance. Zoonotic bacterial pathogens, such as Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli (such as enterohaemorrhagic E. coli or EHEC), and Listeria are the most common and predominant foodborne enteric infectious agents. It was observed that these pathogens gained/developed their ability to survive in the presence of antibiotics either in farm animal gut or farm environment and researchers believe that therapeutic and sub-therapeutic antibiotic use in farm animal production might play an important role in it. The mechanism of action of antimicrobial components used in farm animal production in genomic interplay in the gut and farm environment, has not been fully characterized. Even the risk of promoting the exchange of mobile genetic elements between microbes specifically pathogens needs to be evaluated in depth, to ensure sustainable farm animal production, safety of our food and to mitigate/limit the enteric infection with multiple antibiotic resistant bacterial pathogens. Due to the consumer’s demand and considering the current emerging situation, many countries are in process to withdraw antibiotic use in farm animal production. Before withdrawing use of the sub-therapeutic antibiotic or restricting the use of therapeutic antibiotics in farm animal production, it is essential to find alternative natural antimicrobials for promoting the growth of farm animal and/or treating animal diseases. Further, it is also necessary to consider whether that compound(s) has the potential to trigger the acquisition or loss of genetic materials in zoonotic and any other bacterial pathogens. Development of alternative therapeutic and sub-therapeutic antimicrobials for farm animal production and food processing and preservation and their effective implementation for sustainable strategies for farm animal production as well as the possible risk for horizontal gene transfer in major enteric pathogens will be focus in the study.

Keywords: food safety, natural antimicrobial, sustainable farming, antibiotic resistance

Procedia PDF Downloads 264
712 Performance Enrichment of Deep Feed Forward Neural Network and Deep Belief Neural Networks for Fault Detection of Automobile Gearbox Using Vibration Signal

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 108
711 Morphology Analysis of Apple-Carrot Juice Treated by Manothermosonication (MTS) and High Temperature Short Time (HTST) Processes

Authors: Ozan Kahraman, Hao Feng

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Manothermosonication (MTS), which consists of the simultaneous application of heat and ultrasound under moderate pressure (100-700 kPa), is one of the technologies which destroy microorganisms and inactivates enzymes. Transmission electron microscopy (TEM) is a microscopy technique in which a beam of electrons is transmitted through an ultra-thin specimen, interacting with the specimen as it passes through it. The environmental scanning electron microscope or ESEM is a scanning electron microscope (SEM) that allows for the option of collecting electron micrographs of specimens that are "wet," uncoated. These microscopy techniques allow us to observe the processing effects on the samples. This study was conducted to investigate the effects of MTS and HTST treatments on the morphology of apple-carrot juices by using TEM and ESEM microscopy. Apple-carrot juices treated with HTST (72 0C, 15 s), MTS 50 °C (60 s, 200 kPa), and MTS 60 °C (30 s, 200 kPa) were observed in both ESEM and TEM microscopy. For TEM analysis, a drop of the solution dispersed in fixative solution was put onto a Parafilm ® sheet. The copper coated side of the TEM sample holder grid was gently laid on top of the droplet and incubated for 15 min. A drop of a 7% uranyl acetate solution was added and held for 2 min. The grid was then removed from the droplet and allowed to dry at room temperature and presented into the TEM. For ESEM analysis, a critical point drying of the filters was performed using a critical point dryer (CPD) (Samdri PVT- 3D, Tousimis Research Corp., Rockville, MD, USA). After the CPD, each filter was mounted onto a stub and coated with gold/palladium with a sputter coater (Desk II TSC Denton Vacuum, Moorestown, NJ, USA). E.Coli O157:H7 cells on the filters were observed with an ESEM (Philips XL30 ESEM-FEG, FEI Co., Eindhoven, The Netherland). ESEM (Environmental Scanning Electron Microscopy) and TEM (Transmission Electron Microscopy) images showed extensive damage for the samples treated with MTS at 50 and 60 °C such as ruptured cells and breakage on cell membranes. The damage was increasing with increasing exposure time.

Keywords: MTS, HTST, ESEM, TEM, E.COLI O157:H7

Procedia PDF Downloads 280
710 Rheological and Crystallization Properties of Dark Chocolate Formulated with Essential Oil of Orange and Carotene Extracted from Pineapple Peels

Authors: Mayra Pilamunga, Edwin Vera

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The consumption of dark chocolate is beneficial due to its high content of flavonoids, catechins, and procyanidins. To improve its properties, fortification of chocolate with polyphenols, anthocyanins, soy milk powder and other compounds has been evaluated in several studies. However, to our best knowledge, the addition of carotenes to chocolate has not been tested. Carotenoids, especially ß-carotene and lutein, are widely distributed in fruits and vegetables so that they could be extracted from agro-industrial waste, such as fruit processing. On the other hand, limonene produces crystalline changes of cocoa butter and improves its consistency and viscosity. This study aimed to evaluate the production of dark chocolate with the addition of carotenes extracted from an agro industrial waste and to improve its rheological properties and crystallization, with orange essential oil. The dried and fermented cocoa beans were purchased in Puerto Quito, Ecuador, and had a fat content of 51%. Six types of chocolates were formulated, and two formulations were chosen, one at 65% cocoa and other at 70% cocoa, both with a solid: fat ratio of 1.4:1. With the formulations selected, the influence of the addition of 0.75% and 1.5% orange essential oil was evaluated, and analysis to measure the viscosity, crystallization and sensory analysis were done. It was found that essential oil does not generate significant changes in the properties of chocolate, but has an important effect on aroma and coloration, which changed from auburn to brown. The best scores on sensory analysis were obtained for the samples formulated with 0.75% essential oil. Prior to the formulation with carotenes, the extraction of these compounds from pineapple peels were performed. The process was done with and without a previous enzymatic treatment, with three solid-solvent ratios. The best treatment was using enzymes in a solids-solvent ratio of 1:12.5; the extract obtained under these conditions had 4.503 ± 0.214 μg Eq. β-carotene/mL. This extract was encapsulated with gum arabic and maltodextrin, and the solution was dried using a freeze dryer. The encapsulated carotenes were added to the chocolate in an amount of 1.7% however 60,8 % of them were lost in the final product.

Keywords: cocoa, fat crystallization, limonene, carotenoids, pineapple peels

Procedia PDF Downloads 158
709 Characterization of the Ignitability and Flame Regression Behaviour of Flame Retarded Natural Fibre Composite Panel

Authors: Timine Suoware, Sylvester Edelugo, Charles Amgbari

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Natural fibre composites (NFC) are becoming very attractive especially for automotive interior and non-structural building applications because they are biodegradable, low cost, lightweight and environmentally friendly. NFC are known to release high combustible products during exposure to heat atmosphere and this behaviour has raised concerns to end users. To improve on their fire response, flame retardants (FR) such as aluminium tri-hydroxide (ATH) and ammonium polyphosphate (APP) are incorporated during processing to delay the start and spread of fire. In this paper, APP was modified with Gum Arabic powder (GAP) and synergized with carbon black (CB) to form new FR species. Four FR species at 0, 12, 15 and 18% loading ratio were added to oil palm fibre polyester composite (OPFC) panels as follows; OPFC12%APP-GAP, OPFC15%APP-GAP/CB, OPFC18%ATH/APP-GAP and OPFC18%ATH/APPGAP/CB. The panels were produced using hand lay-up compression moulding and cured at room temperature. Specimens were cut from the panels and these were tested for ignition time (Tig), peak heat released rate (HRRp), average heat release rate (HRRavg), peak mass loss rate (MLRp), residual mass (Rm) and average smoke production rate (SPRavg) using cone calorimeter apparatus as well as the available flame energy (ɸ) in driving the flame using radiant panel flame spread apparatus. From the ignitability data obtained at 50 kW/m2 heat flux (HF), it shows that the hybrid FR modified with APP that is OPFC18%ATH/APP-GAP exhibited superior flame retardancy and the improvement was based on comparison with those without FR which stood at Tig = 20 s, HRRp = 86.6 kW/m2, HRRavg = 55.8 kW/m2, MLRp =0.131 g/s, Rm = 54.6% and SPRavg = 0.05 m2/s representing respectively 17.6%, 67.4%, 62.8%, 50.9%, 565% and 62.5% improvements less than those without FR (OPFC0%). In terms of flame spread, the least flame energy (ɸ) of 0.49 kW2/s3 for OPFC18%ATH/APP-GAP caused early flame regression. This was less than 39.6 kW2/s3 compared to those without FR (OPFC0%). It can be concluded that hybrid FR modified with APP could be useful in the automotive and building industries to delay the start and spread of fire.

Keywords: flame retardant, flame regression, oil palm fibre, composite panel

Procedia PDF Downloads 126