Search results for: evolution mechanism

Authors: Thammanoon Charmjuree, Yuosre F. Badir, Umar Safdar

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There is a consensus among innovation scholars that knowledge is a vital antecedent for firm’s innovation; e.g., process innovation. Recently, there has been an increasing amount of attention to more open approaches to innovation. This open model emphasizes the use of purposive flows of knowledge across the organization boundaries. Firms adopt open innovation strategy to improve their innovation performance by bringing knowledge into the organization (inbound open innovation) to accelerate internal innovation or transferring knowledge outside (outbound open innovation) to expand the markets for external use of innovation. Reviewing open innovation research reveals the following. First, the majority of existing studies have focused on inbound open innovation and less on outbound open innovation. Second, limited research has considered the possible interaction between both and how this interaction may impact the firm’s innovation performance. Third, scholars have focused mainly on the impact of open innovation strategy on product innovation and less on process innovation. Therefore, our knowledge of the relationship between firms’ inbound and outbound open innovation and how these two impact process innovation is still limited. This study focuses on the firm’s external technology acquisition (ETA) and external technology exploitation (ETE) and the firm’s process innovation performance. The ETA represents inbound openness in which firms rely on the acquisition and absorption of external technologies to complement their technology portfolios. The ETE, on the other hand, refers to commercializing technology assets exclusively or in addition to their internal application. This study hypothesized that both ETA and ETE have a positive relationship with process innovation performance and that ETE fully mediates the relationship between ETA and process innovation performance, i.e., ETA has a positive impact on ETE, and turn, ETE has a positive impact on process innovation performance. This study empirically explored these hypotheses in software development firms in Thailand. These firms were randomly selected from a list of Software firms registered with the Department of Business Development, Ministry of Commerce of Thailand. The questionnaires were sent to 1689 firms. After follow-ups and periodic reminders, we obtained 329 (19.48%) completed usable questionnaires. The structure question modeling (SEM) has been used to analyze the data. An analysis of the outcome of 329 firms provides support for our three hypotheses: First, the firm’s ETA has a positive impact on its process innovation performance. Second, the firm’s ETA has a positive impact its ETE. Third, the firm’s ETE fully mediates the relationship between the firm’s ETA and its process innovation performance. This study fills up the gap in open innovation literature by examining the relationship between inbound (ETA) and outbound (ETE) open innovation and suggest that in order to benefits from the promises of openness, firms must engage in both. The study went one step further by explaining the mechanism through which ETA influence process innovation performance.

Keywords: process innovation performance, external technology acquisition, external technology exploitation, open innovation

Procedia PDF Downloads 197

Authors: H. Y. Al-Matubsi, G. A. Oriquat, M. Abu-Samak, O. A. Al Hanbali, M. Salim

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Background: Uncontrolled diabetes mellitus (DM) is an etiological factor for recurrent pregnancy loss and major congenital malformations in the offspring. Antioxidant therapy has been advocated to overcome the oxidant-antioxidant disequilibrium inherent in diabetes. The aims of this study were to evaluate the protective effect of lipoic acid (LA) on fetal outcome and to elucidate changes that may be involved in the mechanism(s) implicit diabetic fetopathy. Methods: Female rats were rendered hyperglycemic using streptozocin and then mated with normal male rat. Pregnant non-diabetic (group1; n=9; and group2; n=7) or pregnant diabetic (group 3; n=10; and group 4; n=8) rats were treated daily with either lipoic acid (LA) (30 mg/kg body weight; groups 2 and 4) or vehicle (groups 1 and 3) between gestational days 0 and 15. On day 15 of gestation, the rats were sacrificed, and the fetuses, placentas and membranes dissected out of the uterine horns. Following morphological examination, the fetuses, placentas and membranes were homogenized, and used to measure cyclooxygenases (COX) activities and metabolisms of prostaglandin (PG) E2 (PGEM) and PGF2 (PGFM) levels. Maternal liver and plasma total glutathione levels were also determined. Results: Supplementation of diabetic rats with LA was found to significantly (P<0.05) reduce resorption rates in diabetic rats and increased mean fetal weight compared to diabetic group. Treatment of diabetic rats with LA leads to a significant (P<0.05) increase in liver and plasma total glutathione, in comparison with diabetic rats. Decreased levels of PGEM and elevated levels of PGFM in the fetuses, placentas and membranes were characteristic of experimental diabetic gestation associated with malformation. LA treatment to diabetic mothers failed to normalize levels of PGEM to the non-diabetic control rats. However, the levels of PGEM in malformed fetuses from LA-treated diabetic mothers was significantly (P < 0.05) higher than those in malformed fetuses from diabetic rats. Conclusions: We conclude that LA can reduce congenital malformations in the offspring of diabetic rats at day 15 of gestation. However, LA treatment did not completely prevent the occurrence of malformations, other factors, such as arachidonic acid deficiency and altered prostaglandin metabolismmay be involved in the pathogenesis of diabetes-induced congenital malformations.

Keywords: diabetes, lipoic acid, pregnancy, prostaglandins

Procedia PDF Downloads 256

Authors: Djamila Chabane, Asma Rouane, Karim Arab

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

Keywords: calluses, Pulicaria incisa, mucilage, Wounds

Procedia PDF Downloads 124

Authors: Fang Liu, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun, JunShuai Xue

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The explosive increasing needs of data processing and information storage strongly drive the advancement of the binary logic system to multiple-valued logic system. Inherent negative differential resistance characteristic, ultra-high-speed switching time, and robust anti-irradiation capability make III-nitride resonant tunneling diode one of the most promising candidates for multi-valued logic devices. Here we report the monolithic integration of GaN resonant tunneling diodes in series to realize multiple negative differential resistance regions, obtaining at least three stable operating states. A multiply-by-three circuit is achieved by this combination, increasing the frequency of the input triangular wave from f0 to 3f0. The resonant tunneling diodes are grown by plasma-assistedmolecular beam epitaxy on free-standing c-plane GaN substrates, comprising double barriers and a single quantum well both at the atomic level. Device with a peak current density of 183kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed, which is the best result reported in nitride-based resonant tunneling diodes. Microwave oscillation event at room temperature was discovered with a fundamental frequency of 0.31GHz and an output power of 5.37μW, verifying the high repeatability and robustness of our device. The switching behavior measurement was successfully carried out, featuring rise and fall times in the order of picoseconds, which can be used in high-speed digital circuits. Limited by the measuring equipment and the layer structure, the switching time can be further improved. In general, this article presents a novel nitride device with multiple negative differential regions driven by the resonant tunneling mechanism, which can be used in high-speed multiple value logic field with reduced circuit complexity, demonstrating a new solution of nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, negative differential resistance, multiple-valued logic system, switching time, peak-to-valley current ratio

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Authors: Heikki Ruohomaa, Vesa Salminen

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Regions are facing huge competition to attract companies, businesses, inhabitants, students, etc. This way to improve living and business environment, which is rapidly changing due to digitalization. On the other hand, from the industry's point of view, the availability of a skilled labor force and an innovative environment are crucial factors. In this context, qualified staff has been seen to utilize the opportunities of digitalization and respond to the needs of future skills. World Manufacturing Forum has stated in the year 2019- report that in next five years, 40% of workers have to change their core competencies. Through digital transformation, new technologies like cloud, mobile, big data, 5G- infrastructure, platform- technology, data- analysis, and social networks with increasing intelligence and automation, enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Digitalization will be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, the education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The Fourth Industrial Revolution will bring unprecedented change to societies, education organizations and business environments. This article aims to identify how education, education content, the way education has proceeded, and overall whole the education business is changing. Most important is how we should respond to this inevitable co- evolution. Methodology: The study aims to verify how the learning process is boosted by new digital content, new learning software and tools, and customer-oriented learning environments. The change of education programs and individual education modules can be supported by applied research projects. You can use them in making proof- of- the concept of new technology, new ways to teach and train, and through the experiences gathered change education content, way to educate and finally education business as a whole. Major findings: Applied research projects can prove the concept- phases on real environment field labs to test technology opportunities and new tools for training purposes. Customer-oriented applied research projects are also excellent for students to make assignments and use new knowledge and content and teachers to test new tools and create new ways to educate. New content and problem-based learning are used in future education modules. This article introduces some case study experiences on customer-oriented digital transformation projects and how gathered knowledge on new digital content and a new way to educate has influenced education. The case study is related to experiences of research projects, customer-oriented field labs/learning environments and education programs of Häme University of Applied Sciences.

Keywords: education process, digitalization content, digital tools for education, learning environments, transdisciplinary co-operation

Procedia PDF Downloads 171

Authors: Himani Sharma, Amit Agrawal

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Stability of the Cassie and Wenzel wetting states depends on intrinsic contact angle and geometric features on a surface that was exploited in capturing biofluids in microwells. However, the mechanism of imbibition of biofluids in the microwells is not well implied in terms of wettability of a substrate. In this work, we experimentally demonstrated filling dynamics in hydrophilic and hydrophobic microwells by protein solutions. Towards this, we utilized lotus leaf as a mold to fabricate microwells on a Polydimethylsiloxane (PDMS) surface. Lotus leaf containing micrometer-sized blunt-conical shaped pillars with a height of 8-15 µm and diameter of 3-8 µm were transferred on to PDMS. Furthermore, PDMS surface was treated with oxygen plasma to render the hydrophilic nature. A 10µL droplets containing fluorescein isothiocyanate (FITC) - labelled bovine serum albumin (BSA) were rested on both hydrophobic (θa = 108o, where θa is the apparent contact angle) and hydrophilic (θa = 60o) PDMS surfaces. A time-dependent fluorescence microscopy was conducted on these modified PDMS surfaces by recording the fluorescent intensity over a 5 minute period. It was observed that, initially (at t=1 min) FITC-BSA was accumulated on the periphery of both hydrophilic and hydrophobic microwells due to incomplete penetration of liquid-gas meniscus. This deposition of FITC-BSA on periphery of microwell was not changed with time for hydrophobic surfaces, whereas, a complete filling was occurred in hydrophilic microwells (at t=5 mins). This attributes to a gradual movement of three-phase contact line along the vertical surface of the hydrophilic microwells as compared to stable pinning in the hydrophobic microwells as confirmed by Surface Evolver simulations. In addition, if the cavities are presented on hydrophobic surfaces, air bubbles will be trapped inside the cavities once the aqueous solution is placed over these surfaces, resulting in the Cassie-Baxter wetting state. This condition hinders trapping of proteins inside the microwells. Thus, it is necessary to impart hydrophilicity to the microwell surfaces so as to induce the Wenzel state, such that, an entire solution will be fully in contact with the walls of microwells. Imbibition of microwells by protein solutions was analyzed in terms fluorescent intensity versus time. The present work underlines the importance of geometry of microwells and surface wettability of substrate in wetting and effective capturing of solid sub-phases in biofluids.

Keywords: BSA, microwells, surface evolver, wettability

Procedia PDF Downloads 193

Authors: A. Díaz-Roa, P. I. Silva Junior, F. J. Bello

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Sarconesiopsis magellanica (Diptera: Calliphoridae) is a medically important necrophagous fly which is used for establishing the post-mortem interval. Dipterous maggots release diverse proteins and peptides contained in larval excretion and secretion (ES) products playing a key role in digestion. The most important mechanism for combating infection using larval therapy depends on larval ES. These larvae are protected against infection by a diverse spectrum of antimicrobial peptides (AMPs), one already known like lucifensin. Special interest in these peptides has also been aroused regarding understanding their role in wound healing since they degrade necrotic tissue and kill different bacteria during larval therapy. The action of larvae on wounds occurs through 3 mechanisms of action: removal of necrotic tissue, stimulation of granulation tissue, and antibacterial action of larval ES. Some components of the ES include calcium, urea, allantoin ammonium bicarbonate and reducing the viability of Gram positive and Gram negative bacteria. The Lucilia sericata fly larvae have been the most used, however, we need to evaluate new species that could potentially be similar or more effective than fly above. This study was thus aimed at identifying and characterizing S. magellanica AMPs contained in ES products for the first time and compared them with the common fly used L. sericata. These products were obtained from third-instar larvae taken from a previously established colony. For the first analysis, ES fractions were separate by Sep-Pak C18 disposable columns (first step). The material obtained was fractionated by RP-HPLC by using Júpiter C18 semi-preparative column. The products were then lyophilized and their antimicrobial activity was characterized by incubation with different bacterial strains. The first chromatographic analysis of ES from L. sericata gives 6 fractions with antimicrobial activity against Gram-positive bacteria Micrococus luteus, and 3 fractions with activity against Gram-negative bacteria Pseudomonae aeruginosa while the one from S. magellanica gaves 1 fraction against M. luteus and 4 against P. aeruginosa. Maybe one of these fractions could correspond to the peptide already known from L. sericata. These results show the first work for supporting further experiments aimed at validating S. magellanica use in larval therapy. We still need to search if we find some new molecules, by making mass spectrometry and ‘de novo sequencing’. Further studies are necessary to identify and characterize them to better understand their functioning.

Keywords: antimicrobial peptides, larval therapy, Lucilia sericata, Sarconesiopsis magellanica

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Authors: Ziv Kassner, Gal Ribak

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Members of the Odonata order (dragonflies and damselflies) stand out for their maneuverability and superb flight control, which allow them to catch flying prey in the air. These outstanding aerial abilities were fine-tuned during millions of years of an evolutionary arms race between Odonata and their prey, providing an attractive research model for studying the relationship between sensory input – and aerodynamic output in a flying insect. The ability to catch a maneuvering target in air is interesting not just for insect behavioral ecology and neuroethology but also for designing small and efficient robotic air vehicles. While the aerial prey interception of dragonflies (suborder: Anisoptera) have been studied before, little is known about how damselflies (suborder: Zygoptera) intercept prey. Here, high-speed cameras (filming at 1000 frames per second) were used to explore how damselflies catch unpredictable targets that move through air. Blue-tailed damselflies - Ischnura elegans (family: Coenagrionidae) were introduced to a flight arena and filmed while landing on moving targets that were oscillated harmonically. The insects succeeded in capturing targets that were moved with an amplitude of 6 cm and frequencies of 0-2.5 Hz (fastest mean target speed of 0.3 m s⁻¹) and targets that were moved in 1 Hz (an average speed of 0.3 m s⁻¹) but with an amplitude of 15 cm. To land on stationary or slow targets, damselflies either flew directly to the target, or flew sideways, up to a point in which the target was fixed in the center of the field of view, followed by direct flight path towards the target. As the target moved in increased frequency, damselflies demonstrated an ability to track the targets while flying sideways and minimizing the changes of their body direction on the yaw axis. This was likely an attempt to keep the targets at the center of the visual field while minimizing rotational optic flow of the surrounding visual panorama. Stabilizing rotational optic flow helps in estimation of the velocity and distance of the target. These results illustrate how dynamic visual information is used by damselflies to guide them towards a maneuvering target, enabling the superb aerial hunting abilities of these insects. They also exemplifies the plasticity of the damselfly flight apparatus which enables flight in any direction, irrespective of the direction of the body.

Keywords: bio-mechanics, insect flight, target fixation, tracking and interception

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

Procedia PDF Downloads 121

Authors: Venkata Srikanth Meka, Nur Arthirah Binti Ahmad Tarmizi Tan, Muhammad Syahmi Bin Md Nazir, Adinarayana Gorajana, Senthil Rajan Dharmalingam

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Biphasic drug delivery systems are designed to release drug at two different rates, either fast/prolonged or prolonged/fast. A fast/prolonged release system provides a burst drug release at initial stage followed by a slow release over a prolonged period of time and in case of prolonged/fast release system, the release pattern is vice versa. Terminalia catappa gum (TCG) is a natural polymer and was successfully proven as a novel pharmaceutical excipient. The main objective of the present research is to investigate the applicability of natural polymer, Terminalia catappa gum in the design of oral biphasic drug delivery system in the form of mini tablets by using a model drug, buspirone HCl. This investigation aims to produce a biphasic release drug delivery system of buspirone by combining immediate release and prolonged release mini tablets into a capsule. For immediate release mini tablets, a dose of 4.5 mg buspirone was prepared by varying the concentration of superdisintegrant; crospovidone. On the other hand, prolonged release mini tablets were produced by using different concentrations of the natural polymer; TCG with a buspirone dose of 3mg. All mini tablets were characterized for weight variation, hardness, friability, disintegration, content uniformity and dissolution studies. The optimized formulations of immediate and prolonged release mini tablets were finally combined in a capsule and was evaluated for release studies. FTIR and DSC studies were conducted to study the drug-polymer interaction. All formulations of immediate release and prolonged release mini tablets were passed all the in-process quality control tests according to US Pharmacopoeia. The disintegration time of immediate release mini tablets of different formulations was varied from 2-6 min, and maximum drug release was achieved in lesser than 60 min. Whereas prolonged release mini tablets made with TCG have shown good drug retarding properties. Formulations were controlled for about 4-10 hrs with varying concentration of TCG. As the concentration of TCG increased, the drug release retarding property also increased. The optimised mini tablets were packed in capsules and were evaluated for the release mechanism. The capsule dosage form has clearly exhibited the biphasic release of buspirone, indicating that TCG is a suitable natural polymer for this study. FTIR and DSC studies proved that there was no interaction between the drug and polymer. Based on the above positive results, it can be concluded that TCG is a suitable polymer for the biphasic drug delivery systems.

Keywords: Terminalia catappa gum, biphasic release, mini tablets, tablet in capsule, natural polymers

Procedia PDF Downloads 386

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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

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

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Authors: Bastian Vollrath, Hartwig Hubel

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In case of over-elastic and cyclic loading, strain may accumulate due to a ratcheting mechanism until the state of shakedown is possibly achieved. Load history dependent numerical investigations by a step-by-step analysis are rather costly in terms of engineering time and numerical effort. In the case of multi-parameter loading, where various independent loadings affect the final state of shakedown, the computational effort becomes an additional challenge. Therefore, direct methods like the Simplified Theory of Plastic Zones (STPZ) are developed to solve the problem with a few linear elastic analyses. Post-shakedown quantities such as strain ranges and cyclic accumulated strains are calculated approximately by disregarding the load history. The STPZ is based on estimates of a transformed internal variable, which can be used to perform modified elastic analyses, where the elastic material parameters are modified, and initial strains are applied as modified loading, resulting in residual stresses and strains. The STPZ already turned out to work well with respect to cyclic loading between two states of loading. Usually, few linear elastic analyses are sufficient to obtain a good approximation to the post-shakedown quantities. In a multi-dimensional load domain, the approximation of the transformed internal variable transforms from a plane problem into a hyperspace problem, where time-consuming approximation methods need to be applied. Therefore, a solution restricted to structures with four stress components was developed to estimate the transformed internal variable by means of three-dimensional vector algebra. This paper presents the extension to cyclic multi-parameter loading so that an unlimited number of load cases can be taken into account. The theoretical basis and basic presumptions of the Simplified Theory of Plastic Zones are outlined for the case of elastic shakedown. The extension of the method to many load cases is explained, and a workflow of the procedure is illustrated. An example, adopting the FE-implementation of the method into ANSYS and considering multilinear hardening is given which highlights the advantages of the method compared to incremental, step-by-step analysis.

Keywords: cyclic loading, direct method, elastic shakedown, multi-parameter loading, STPZ

Procedia PDF Downloads 157

Authors: Chandan Kumar

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Background and Context: Population growth and rapid urbanization resulted nearly 2 Lacs migrants along with families moving to Delhi each year in search of jobs. Most of these poor migrant families end up living in slums and constitute an estimated population of 1.87 lacs every year. Further, more than half (52 per cent) of Delhi’s population resides in places such as unauthorized and resettled colonies. Slum population is fully dependent on public toilet to defecate. In Public toilets, manholes either connected with Sewer line or septic tank. Septic tank connected public toilet faces major challenges to dispose of waste water. They have to dispose of waste water in outside open drain and waste water struck out side of public toilet complex and near to the slum area. As a result, outbreak diseases such as Malaria, Dengue and Chikungunya in slum area due to stagnated waste water. Intervention and Innovation took place by Save the Children in 21 Public Toilet Complexes of South Delhi and North Delhi. These public toilet complexes were facing same waste water disposal problem. They were disposing of minimum 1800 liters waste water every day in open drain. Which caused stagnated water-borne diseases among the nearest community. Construction of Soak Well: Construction of soak well in urban context was an innovative approach to minimizing the problem of waste water management and increased water table of existing borewell in toilet complex. This technique made solution in Ground water recharging system, and additional water was utilized in vegetable gardening within the complex premises. Soak well had constructed with multiple filter media with inlet and safeguarding bed on surrounding surface. After construction, soak well started exhausting 2000 liters of waste water to raise ground water level through different filter media. Finally, we brought a change in the communities by constructing soak well and with zero maintenance system. These Public Toilet Complexes were empowered by safe disposing waste water mechanism and reduced stagnated water-borne diseases.

Keywords: diseases, ground water recharging system, soak well, toilet complex, waste water

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Authors: M. A. Hafiz, P. T. Matevenga

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Micro-level machining of metals is a developing field which has shown to be a prospective approach to produce features on the parts in the range of a few to a few hundred microns with acceptable machining quality. It is known that the mechanics (i.e. the material removal mechanism) of micro-machining and conventional machining have significant differences due to the scaling effects associated with tool-geometry, tool material and work piece material characteristics. Shape memory alloys (SMAs) are those metal alloys which display two exceptional properties, pseudoelasticity and the shape memory effect (SME). Nickel-titanium (NiTi) alloys are one of those unique metal alloys. NiTi alloys are known to be difficult-to-cut materials specifically by using conventional machining techniques due to their explicit properties. Their high ductility, high amount of strain hardening, and unusual stress–strain behaviour are the main properties accountable for their poor machinability in terms of tool wear and work piece quality. The motivation of this research work was to address the challenges and issues of micro-machining combining with those of machining of NiTi alloy which can affect the desired performance level of machining outputs. To explore the significance of range of cutting conditions on surface roughness and tool wear, machining tests were conducted on NiTi. Influence of different cutting conditions and cutting tools on surface and sub-surface deformation in work piece was investigated. Design of experiments strategy (L9 Array) was applied to determine the key process variables. The dominant cutting parameters were determined by analysis of variance. These findings showed that feed rate was the dominant factor on surface roughness whereas depth of cut found to be dominant factor as far as tool wear was concerned. The lowest surface roughness was achieved at the feed rate of equal to the cutting edge radius where as the lowest flank wear was observed at lowest depth of cut. Repeated machining trials have yet to be carried out in order to observe the tool life, sub-surface deformation and strain induced hardening which are also expecting to be amongst the critical issues in micro machining of NiTi. The machining performance using different cutting fluids and strategies have yet to be studied.

Keywords: nickel titanium, micro-machining, surface roughness, machinability

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Authors: Sonia Bautista Carrascosa, Carlos Renedo Sanchez

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The effect of a rapid drawdown is a classical scenario to be considered in slope stability under submerged conditions. This situation arises when totally or partially submerged slopes experience a descent of the external water level and is a typical verification to be done in a dam engineering discipline, as reservoir water levels commonly fluctuate noticeably during seasons and due to operational reasons. Although the scenario is well known and predictable in general, site conditions can increase the complexity of its assessment and external factors are not always expected, can cause a reduction in the stability or even a failure in a slope under a rapid drawdown situation. The present paper describes and discusses the interaction between two different infrastructures, a dam and a highway, and the impact on the stability of a natural rock slope overlaid by the north abutment of a viaduct of the A-44 Highway due to the rapid drawdown of the Rules Dam, in the province of Granada (south of Spain). In the year 2011, with both infrastructures, the A-44 Highway and the Rules Dam already constructed, delivered and under operation, some movements start to be recorded in the approximation embankment and north abutment of the Guadalfeo Viaduct, included in the highway and developed to solve the crossing above the tail of the reservoir. The embankment and abutment were founded in a low-angle natural rock slope formed by grey graphic phyllites, distinctly weathered and intensely fractured, with pre-existing fault and weak planes. After the first filling of the reservoir, to a relative level of 243m, three consecutive drawdowns were recorded in the autumns 2010, 2011 and 2012, to relative levels of 234m, 232m and 225m. To understand the effect of these drawdowns in the weak rock mass strength and in its stability, a new geological model was developed, after reviewing all the available ground investigations, updating the geological mapping of the area and supplemented with an additional geotechnical and geophysical investigations survey. Together with all this information, rainfall and reservoir level evolution data have been reviewed in detail to incorporate into the monitoring interpretation. The analysis of the monitoring data and the new geological and geotechnical interpretation, supported by the use of limit equilibrium software Slide2, concludes that the movement follows the same direction as the schistosity of the phyllitic rock mass, coincident as well with the direction of the natural slope, indicating a deep-seated movement of the whole slope towards the reservoir. As part of these conclusions, the solutions considered to reinstate the highway infrastructure to the required FoS will be described, and the geomechanical characterization of these weak rocks discussed, together with the influence of water level variations, not only in the water pressure regime but in its geotechnical behavior, by the modification of the strength parameters and deformability.

Keywords: monitoring, rock slope stability, water drawdown, weak rock

Procedia PDF Downloads 158

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 36

Authors: Komal Khan, Hafsa Zaneb, Saima Masood, Muhammad Younus, Sanan Raza

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Cigarette smoke induces many physiological and pathological changes in respiratory tract like goblet cell hyperplasia and regional distention of airspaces. It is also associated with elevation of inflammatory profiles in different airway compartments. As probiotics are generally known to promote mucosal tolerance, it was postulated that prophylactic use of probiotics can be helpful in reduction of respiratory damage induced by cigarette smoke exposure. Twenty-four adult mice were randomly divided into three groups (cigarette-smoke (CS) group, cigarette-smoke+ Lactobacillus (CS+ P) group, control (Cn) group), each having 8 mice. They were exposed to cigarette smoke for 28 days (6 cigarettes/ day for 6 days/week). Wright-Giemsa staining of bronchoalveolar lavage fluid (BALF) was performed in three mice per group. Tissue samples of trachea and lungs of 7 mice from each group were processed by paraffin embedding technique for haematoxylin & eosin (H & E) and alcian blue- periodic acid-Schiff (AB-PAS) staining. Then trachea (goblet cell number, ratio and loss of cilia) and lungs (airspace distention) were studied. The results showed that the number of goblet cells was increased in CS group as a result of defensive mechanism of the respiratory system against irritating substances. This study also revealed that the cells of CS group having acidic glycoprotein were found to be higher in quantity as compared to those containing neutral glycoprotein. However, CS + P group showed a decrease in goblet cell index due to enhanced immunity by prophylactically used probiotics. Moreover, H & E stained tracheas showed significant loss of cilia in CS group due to propelling of mucous but little loss in CS + P group because of having good protective tracheal epithelium. In lungs, protection of airspaces was also much more evident in CS+ P group as compared to CS group having distended airspaces, especially at 150um distance from terminal bronchiole. In addition, a comprehensive analysis of inflammatory cells population of BALF showed neutrophilia and eosinophilia was significantly reduced in CS+ P group. This study proved that probiotics are found to be useful for reduction of changes in micro-architecture of the respiratory system. Thus, dietary supplementation of probiotic as prophylactic measure can be useful in achieving immunomodulatory effects.

Keywords: cigarette smoke, probiotics, goblet cells, airspace enlargement, BALF

Procedia PDF Downloads 362

Authors: Reuben Mugisha, Stella Bakibinga

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The cervical cancer burden is a global threat, but more so in low income settings where more than 85% of mortality cases occur due to lack of sufficient screening programs. There is consequently a lack of early detection of cancer and precancerous cells among women. Studies show that 3% to 35% of deaths could have been avoided through early screening depending on prognosis, disease progression, environmental and lifestyle factors. In this study, a systematic literature review is undertaken to understand potential barriers and facilitators as documented in previous studies that focus on the application of telehealth in cervical cancer screening programs for early detection of cancer and precancerous cells. The study informs future studies especially those from low income settings about lessons learned from previous studies and how to be best prepared while planning to implement telehealth for cervical cancer screening. It further identifies the knowledge gaps in the research area and makes recommendations. Using a specified selection criterion, 15 different articles are analyzed based on the study’s aim, theory or conceptual framework used, method applied, study findings and conclusion. Results are then tabulated and presented thematically to better inform readers about emerging facts on barriers and facilitators to telehealth implementation as documented in the reviewed articles, and how they consequently lead to evidence informed conclusions that are relevant to telehealth implementation for cervical cancer screening. Preliminary findings of this study underscore that use of low cost mobile colposcope is an appealing option in cervical cancer screening, particularly when coupled with onsite treatment of suspicious lesions. These tools relay cervical images to the online databases for storage and retrieval, they permit integration of connected devices at the point of care to rapidly collect clinical data for further analysis of the prevalence of cervical dysplasia and cervical cancer. Results however reveal the need for population sensitization prior to use of mobile colposcopies among patients, standardization of mobile colposcopy programs across screening partners, sufficient logistics and good connectivity, experienced experts to review image cases at the point-of-care as important facilitators to the implementation of mobile colposcope as a telehealth cervical cancer screening mechanism.

Keywords: cervical cancer screening, digital technology, hand-held colposcopy, knowledge-sharing

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Authors: Aaron Kim, Nydia Hernandez

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Despite the known deficits in sleep duration among adolescents and the increasing prevalence of substance use behaviors among this group, relatively little is known about how insufficient sleep is related to various substance use behaviors and the underlying mechanisms. Informed by the literature suggesting the predictive role of insufficient sleep for substance use and depressive symptoms, we hypothesized that adolescents who lack sufficient sleep during school nights would report a higher level of depressive symptoms and substance use than their counterparts with sufficient sleep. We also hypothesized that depressive symptoms would explain the association of insufficient sleep with substance use, suggesting that mental health plays an important role as a mechanism between insufficient sleep and substance use. This study used the data drawn from the 2019 Youth Risk Behavior Surveillance System Data, which includes a nationally representative sample of U.S. high school students (N=13,677, 49.4% Female, 9th-12th graders). Self-report measures of insufficient sleep (sleeping<7 h on an average school night), depressive symptoms (yes/no), any past 30-day use of cigarette (yes/no), e-cigarette (yes/no), alcohol (yes/no), and marijuana (yes/no). Among the total sample, 47.9% of students reported that they did not have sufficient sleep on school nights, indicating sleeping less than 7 hours. Regarding depressive symptoms, 36.7% of students reported feeling sad or hopeless almost every day for two weeks or more in a row during the past 12 months. Also, the percentages of students who reported one or more times of cigarette use, e-cigarette use, alcohol use, and marijuana use in the past month were 5.32%, 30.11%, 26.83%, and 21.65%, respectively. For bivariate associations among these study variables, insufficient sleep was positively associated with other variables: depressive symptoms (r=.08, p<.001), cigarette use (r=.03, p<.001), e-cigarette use (r=.04, p<.001), alcohol use (r=.07, p<.001), and marijuana use (r=.08, p<.001). After controlling for students’ characteristics (i.e., age, gender, race/ethnicity, grades), sleeping less than 7 hours on school nights (vs. sleeping more than 7 hours) was significantly associated with the past 30-day use of alcohol and marijuana, whereas cigarette and e-cigarette uses were not. That is, the students who reported having an insufficient sleep on school nights had higher odds of alcohol (Odds Ratio [OR]=1.15, 95% Confidence Interval [CI]=1.014-1.301) and marijuana use (OR=1.36, 95% CI=1.132-1.543). In a subsequent analysis including depressive symptoms together with insufficient sleep, the association of insufficient sleep with alcohol use (OR=1.13, 95% CI=1.011-1.297) and marijuana use (OR=1.33, 95% CI=1.130-1.521) were attenuated and explained by depressive symptoms. Depressive symptoms significantly increased the odds of alcohol use by 32.2% (OR=1.32, 95% CI=1.131-1.557) and marijuana use by 202.1% (OR=2.02, 95% CI=1.672-2.502). These findings together suggest that insufficient sleep may contribute to increased risks of substance uses among adolescents. The current study also shows that psychological disorders of adolescents play important roles in understanding the association between insufficient sleep and substance use, suggesting insufficient sleep is related to substance use indirectly through depressive symptoms. This study indicates the importance of sleep deprivation among adolescents and screening for insufficient sleep in preventing/intervening in substance use.

Keywords: adolescents, depressive symptoms, sleep, substance use

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

Procedia PDF Downloads 78

Authors: Sara Camino, Fernando Vega, Mercedes Cano, Benito Navarrete, José A. Camino

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Carbon capture and storage (CCS) technologies should play a relevant role towards low-carbon systems in the European Union by 2030. Partial oxy-combustion emerges as a promising CCS approach to mitigate anthropogenic CO₂ emissions. Its advantages respect to other CCS technologies rely on the production of a higher CO₂ concentrated flue gas than these provided by conventional air-firing processes. The presence of more CO₂ in the flue gas increases the driving force in the separation process and hence it might lead to further reductions of the energy requirements of the overall CO₂ capture process. A higher CO₂ concentrated flue gas should enhance the CO₂ capture by chemical absorption in solvent kinetic and CO₂ cyclic capacity. They have impact on the performance of the overall CO₂ absorption process by reducing the solvent flow-rate required for a specific CO₂ removal efficiency. Lower solvent flow-rates decreases the reboiler duty during the regeneration stage and also reduces the equipment size and pumping costs. Moreover, R&D activities in this field are focused on novel solvents and blends that provide lower CO₂ absorption enthalpies and therefore lower energy penalties associated to the solvent regeneration. In this respect, sterically hindered amines are considered potential solvents for CO₂ capture. They provide a low energy requirement during the regeneration process due to its molecular structure. However, its absorption kinetics are slow and they must be promoted by blending with faster solvents such as monoethanolamine (MEA) and piperazine (PZ). In this work, the kinetic behavior of two sterically hindered amines were studied under partial oxy-combustion conditions and compared with MEA. A lab-scale semi-batch reactor was used. The CO₂ composition of the synthetic flue gas varied from 15%v/v – conventional coal combustion – to 60%v/v – maximum CO₂ concentration allowable for an optimal partial oxy-combustion operation. Firstly, 2-amino-2-methyl-1-propanol (AMP) showed a hybrid behavior with fast kinetics and a low enthalpy of CO₂ absorption. The second solvent was Isophrondiamine (IF), which has a steric hindrance in one of the amino groups. Its free amino group increases its cyclic capacity. In general, the presence of higher CO₂ concentration in the flue gas accelerated the CO₂ absorption phenomena, producing higher CO₂ absorption rates. In addition, the evolution of the CO2 loading also exhibited higher values in the experiments using higher CO₂ concentrated flue gas. The steric hindrance causes a hybrid behavior in this solvent, between both fast and slow kinetic solvents. The kinetics rates observed in all the experiments carried out using AMP were higher than MEA, but lower than the IF. The kinetic enhancement experienced by AMP at a high CO2 concentration is slightly over 60%, instead of 70% – 80% for IF. AMP also improved its CO₂ absorption capacity by 24.7%, from 15%v/v to 60%v/v, almost double the improvements achieved by MEA. In IF experiments, the CO₂ loading increased around 10% from 15%v/v to 60%v/v CO₂ and it changed from 1.10 to 1.34 mole CO₂ per mole solvent, more than 20% of increase. This hybrid kinetic behavior makes AMP and IF promising solvents for partial oxy–combustion applications.

Keywords: absorption, carbon capture, partial oxy-combustion, solvent

Procedia PDF Downloads 183

Authors: Samuel E. Okere, Anthony E. Ataga

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Introduction: This paper evaluated the mineral compositions, disease resistance elicitors in Pleurotus ostratus (POWESMS), and Pleurotus tuber-regium water extract spent mushroom substrate (PTWESMS) on the growth, yield, and management of cassava mosaic disease. Materials and Methods: The cassava plantlet (tms 98/0505) were generated through meristem tip culture at the Tissue Culture Laboratory, National Root Crop Research Institute, Umudike before they were transferred to the screen house, University of Port Harcourt Research Farm. The minerals and elicitors contained in the two spent mushroom substrates were evaluated using standard procedures. The treatments for this investigation comprised cassava plants treated with POWESMS, PTWESMS, and untreated cassava as control, which were inoculated with viral inoculum seven days after treatment application. The experiment was laid out in a completely randomized block design with 3 replicates. The data generated were subjected to analysis of variance (ANOVA). Means were separated using Fishers Least Significant Difference at p=0.05. Results: The results obtained revealed that POWESMS contained 19.3, 0.52, and 0.1g/200g substrate of carbohydrate polymers, glycoproteins, and lipid molecules elicitors respectively while it also contained 3.17, 212.1, 17.9,21.8, 58.8 and 111.0 mg/100g substrate for N, P, K, Na, Mg and Ca respectively. Further, PTWESMS contain 1.6, 0.04, and 0.2g/200g of the substrate as carbohydrate polymers, glycoprotein, and lipid respectively; the minerals contained in this substrate were 3.4, 204.8, 8.9, 24.2, 32.2 and 105.5 mg respectively for N, P, K, Na, and Ca. There were also significant differences in the mean values of the number of storage roots, root length, fresh root weight, fresh weight plant biomass, root girth, and whole plant dry biomass, but no significant difference was recorded for harvest index. The result also revealed significant differences in mean values of disease severity index evaluated at 4, 8, 12, 16, 20, 24, and 28 weeks after inoculation (WAI). Conclusion: The aqueous extract of these spent mushrooms substrate have shown outstanding prospect in managing cassava mosaic disease and also improvement in growth and yield of cassava due to the high level of the minerals and elicitors they contain when compared with the control. However, more work is recommended, especially in understanding the mechanism of this induced resistance.

Keywords: characterization, elicitors, mosaic, mushroom

Procedia PDF Downloads 123

Authors: Choon Seong Ng, P. Petrick, C. L. Lau

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Background: Carbapenem-resistant isolates have been increasingly reported recently. Carbapenem stewardship is designed to optimize its usage particularly among medical wards with high prevalence of carbapenem prescriptions to combat such emerging resistance. Carbapenem stewardship programmes (CSP) can reduce antibiotic use but clinical outcome of such measures needs further evaluation. We examined this in a prospective manner using feedback mechanism. Methods: Our single-center prospective cohort study involved all carbapenem prescriptions across the medical wards (including medical patients admitted to intensive care unit) in a tertiary university hospital setting. The impact of such stewardship was analysed according to the accepted and the rejected groups. The primary endpoint was safety. Safety measure applied in this study was the death at 1 month. Secondary endpoints included length of hospitalisation and readmission. Results: Over the 19 months’ period, input from 144 carbapenem prescriptions was analysed on the basis of acceptance of our CSP recommendations on the use of carbapenems. Recommendations made were as follows : de-escalation of carbapenem; stopping the carbapenem; use for a short duration of 5-7 days; required prolonged duration in the case of carbapenem-sensitive Extended Spectrum Beta-Lactamases bacteremia; dose adjustment; and surgical intervention for removal of septic foci. De-escalation, shorten duration of carbapenem and carbapenem cessation comprised 79% of the recommendations. Acceptance rate was 57%. Those who accepted CSP recommendations had no increase in mortality (p = 0.92), had a shorter length of hospital stay (LOS) and had cost-saving. Infection-related deaths were found to be higher among those in the rejected group. Moreover, three rejected cases (6%) among all non-indicated cases (n = 50) were found to have developed carbapenem-resistant isolates. Lastly, Pitt’s bacteremia score appeared to be a key element affecting the carbapenem prescription’s behaviour in this trial. Conclusions: Carbapenem stewardship program in the medical wards not only saves money, but most importantly it is safe and does not harm the patients with added benefits of reducing the length of hospital stay. However, more time is needed to engage the primary clinical teams by formal clinical presentation and immediate personal feedback by senior Infectious Disease (ID) personnel to increase its acceptance.

Keywords: audit and feedback, carbapenem stewardship, medical wards, university hospital

Procedia PDF Downloads 200

Authors: Bastien Sanglard, Simon Cayez, Guillaume Viau, Thomas Blon, Julian Carrey, Sébastien Lachaize

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The need to develop clean production processes is a key challenge of any industry. Steel and iron industries are particularly concerned since they emit 6.8% of global anthropogenic greenhouse gas emissions. One key step of the process is the high-temperature reduction of iron ore using coke, leading to large amounts of CO2 emissions. One route to decrease impacts is to get rid of fossil fuels by changing both the heat source and the reducer. The present work aims at investigating experimentally the possibility to use concentrated solar energy and carbon-free reducing agents. Two sets of experimentations were realized. First, in situ X-ray diffraction on pure and industrial powder of hematite was realized to study the phase evolution as a function of temperature during reduction under hydrogen and ammonia. Secondly, experiments were performed on industrial iron ore pellets, which were reduced by NH3 or H2 into a “solar furnace” composed of a controllable 1600W Xenon lamp to simulate and control the solar concentrated irradiation of a glass reactor and of a diaphragm to control light flux. Temperature and pressure were recorded during each experiment via thermocouples and pressure sensors. The percentage of iron oxide converted to iron (called thereafter “reduction ratio”) was found through Rietveld refinement. The power of the light source and the reduction time were varied. Results obtained in the diffractometer reaction chamber show that iron begins to form at 300°C with pure Fe2O3 powder and 400°C with industrial iron ore when maintained at this temperature for 60 minutes and 80 minutes, respectively. Magnetite and wuestite are detected on both powders during the reduction under hydrogen; under ammonia, iron nitride is also detected for temperatures between400°C and 600°C. All the iron oxide was converted to iron for a reaction of 60 min at 500°C, whereas a conversion ratio of 96% was reached with industrial powder for a reaction of 240 min at 600°C under hydrogen. Under ammonia, full conversion was also reached after 240 min of reduction at 600 °C. For experimentations into the solar furnace with iron ore pellets, the lamp power and the shutter opening were varied. An 83.2% conversion ratio was obtained with a light power of 67 W/cm2 without turning over the pellets. Nevertheless, under the same conditions, turning over the pellets in the middle of the experiment permits to reach a conversion ratio of 86.4%. A reduction ratio of 95% was reached with an exposure of 16 min by turning over pellets at half time with a flux of 169W/cm2. Similar or slightly better results were obtained under an ammonia reducing atmosphere. Under the same flux, the highest reduction yield of 97.3% was obtained under ammonia after 28 minutes of exposure. The chemical reaction itself, including the solar heat source, does not produce any greenhouse gases, so solar metallurgy represents a serious way to reduce greenhouse gas emission of metallurgy industry. Nevertheless, the ecological impact of the reducers must be investigated, which will be done in future work.

Keywords: solar concentration, metallurgy, ammonia, hydrogen, sustainability

Procedia PDF Downloads 134

Authors: Mamunur Rashid, Jialin Yan

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The current years have witnessed a rapid evolution and integration of artificial intelligence (AI) in various fields, prominently influencing the education industry. Acknowledging this transformative wave, AI tools like ChatGPT and Grammarly have undeniably introduced perspectives and skills, enriching the educational experiences of higher education students. The prevalence of AI utilization in higher education also drives an increasing number of researchers' attention in various dimensions. Departments, offices, and professors in universities also designed and released a set of policies and guidelines on using AI effectively. In regard to this, the study targets exploring and analyzing graduate students' perspectives regarding AI guidelines set by teachers. A mixed-methods study will be mainly conducted in this study, employing in-depth interviews and focus groups to investigate and collect students' perspectives. Relevant materials, such as syllabi and course instructions, will also be analyzed through the documentary analysis to facilitate understanding of the study. Surveys will also be used for data collection and students' background statistics. The integration of both interviews and surveys will provide a comprehensive array of student perspectives across various academic disciplines. The study is anchored in the theoretical framework of self-determination theory (SDT), which emphasizes and explains the students' perspective under the AI guidelines through three core needs: autonomy, competence, and relatedness. This framework is instrumental in understanding how AI guidelines influence students' intrinsic motivation and sense of empowerment in their learning environments. Through qualitative analysis, the study reveals a sense of confusion and uncertainty among students regarding the appropriate application and ethical considerations of AI tools, indicating potential challenges in meeting their needs for competence and autonomy. The quantitative data further elucidates these findings, highlighting a significant communication gap between students and educators in the formulation and implementation of AI guidelines. The critical findings of this study mainly come from two aspects: First, the majority of graduate students are uncertain and confused about relevant AI guidelines given by teachers. Second, this study also demonstrates that the design and effectiveness of course materials, such as the syllabi and instructions, also need to adapt in regard to AI policies. It indicates that certain of the existing guidelines provided by teachers lack consideration of students' perspectives, leading to a misalignment with students' needs for autonomy, competence, and relatedness. More emphasize and efforts need to be dedicated to both teacher and student training on AI policies and ethical considerations. To conclude, in this study, graduate students' perspectives on teacher-provided AI guidelines are explored and reflected upon, calling for additional training and strategies to improve how these guidelines can be better disseminated for their effective integration and adoption. Although AI guidelines provided by teachers may be helpful and provide new insights for students, educational institutions should take a more anchoring role to foster a motivating, empowering, and student-centered learning environment. The study also provides some relevant recommendations, including guidance for students on the ethical use of AI and AI policy training for teachers in higher education.

Keywords: higher education policy, graduate students’ perspectives, higher education teacher, AI guidelines, AI in education

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Authors: Arnesh Vijay

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Ever since its early introduction in the late 1980s, the mobile industry has been rapidly evolving with each passing year. The development witnessed is not just in its ability to support diverse applications, but also its extension into diverse technological means to access and offer various services to users. Amongst the various technologies present, radio systems have clearly emerged as a strong contender, due to its fine attributes of accessibility, reachability, interactiveness, and cost efficiency. These advancements have no doubt guaranteed unprecedented ease, utility and sophistication to the cell phone users, but caused uncertainty due to the interdependence of various systems, making it extremely complicated to exactly map concepts on to 3GPP (3rd Generation Partnership Project) standards. Although the close interrelation and interdependence of intellectual property rights and mobile standard specifications have been widely acknowledged by the technical and legal community; there, however, is a requirement for clear distinction between the scope and future-proof of inventions to influence standards and its market place adoptability. For this, collaborative work is required between intellectual property professionals, researchers, standardization specialists and country specific legal experts. With the evolution into next generation mobile technology, i.e., to 5G systems, there is a need for further work to be done in this field, which has been felt now more than ever before. Based on these lines, this poster will briefly describe the importance of intellectual property rights in the European market. More specifically, will analyse the role played by intellectual property in various standardization institutes, such as 3GPP (3rd generation partnership project) and ITU (International Telecommunications Union). The main intention: to ensure the scope and purpose is well defined, and concerned parties on all four sides are well informed on the clear significance of good proposals which not only bring economic revenue to the company but those that are capable of improving the technology and offer better services to mankind. The poster will comprise different sections. The first segment begins with a background on the rapidly evolving mobile technology, with a brief insight on the industrial impact of standards and its relation to intellectual property rights. Next, section two will succinctly outline the interplay between patents and standards; explicitly discussing the ever changing and rapidly evolving relationship between the two sectors. Then the remaining sections will examine ITU and its role played in international standards development, touching upon the various standardization process and the common patent policies and related guidelines. Finally, it proposes ways to improve the collaboration amongst various sectors for a more evolved and sophisticated next generation mobile telecommunication system. The sole purpose here is to discuss methods to reduce the gap and enhance the exchange of information between the two sectors to offer advanced technologies and services to mankind.

Keywords: mobile technology, mobile standards, intellectual property rights, 3GPP

Procedia PDF Downloads 123

Authors: K. K. Balavenkatraman, B. Bertschi, K. Bigot, A. Grevot, A. Doelemeyer, S. D. Chibout, A. Wolf, F. Pognan, N. Manevski, O. Kretz, P. Swart, K. Litherland, J. Ashton-Chess, B. Ling, R. Wettstein, D. J. Schaefer

Abstract:

Skin toxicity is poorly detected during preclinical studies, and drug-induced side effects in humans such as rashes, hyperplasia or more serious events like bullous pemphigus or toxic epidermal necrolysis represent an important hurdle for clinical development. In vitro keratinocyte-based epidermal skin models are suitable for the detection of chemical-induced irritancy, but do not recapitulate the biological complexity of full skin and fail to detect potential serious side-effects. Normal healthy skin explants may represent a valuable complementary tool, having the advantage of retaining the full skin architecture and the resident immune cell diversity. This study investigated several conditions for the maintenance of good morphological structure after several days of culture and the retention of phase II metabolism for 24 hours in skin explants in vitro. Human skin samples were collected with informed consent from patients undergoing plastic surgery and immediately transferred and processed in our laboratory by removing the underlying dermal fat. Punch biopsies of 4 mm diameter were cultured in an air-liquid interface using transwell filters. Different cultural conditions such as the effect of calcium, temperature and cultivation media were tested for a period of 14 days and explants were histologically examined after Hematoxylin and Eosin staining. Our results demonstrated that the use of Williams E Medium at 32°C maintained the physiological integrity of the skin for approximately one week. Upon prolonged incubation, the upper layers of the epidermis become thickened and some dead cells are present. Interestingly, these effects were prevented by addition of EGFR inhibitors such as Afatinib or Erlotinib. Phase II metabolism of the skin such as glucuronidation (4-methyl umbeliferone), sulfation (minoxidil), N-acetyltransferase (p-toluidene), catechol methylation (2,3-dehydroxy naphthalene), and glutathione conjugation (chlorodinitro benzene) were analyzed by using LCMS. Our results demonstrated that the human skin explants possess metabolic activity for a period of at least 24 hours for all the substrates tested. A time course for glucuronidation with 4-methyl umbeliferone was performed and a linear correlation was obtained over a period of 24 hours. Longer-term culture studies will indicate the possible evolution of such metabolic activities. In summary, these results demonstrate that human skin explants maintain a normal structure for several days in vitro and are metabolically active for at least the first 24 hours. Hence, with further characterisation, this model may be suitable for the study of drug-induced toxicity.

Keywords: human skin explant, phase II metabolism, epidermal growth factor receptor, toxicity

Procedia PDF Downloads 276

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: R. L. Shirole, N. L. Shirole, R. B. Patil, M. N. Saraf

Abstract:

The present investigation aimed to elucidate the probable mechanism of antiasthmatic action of essential oil of Pistacia integerrima J.L. Stewart ex Brandis galls (EOPI). EOPI was investigated for its potential antiasthmatic action using in vitro antiallergic assays mast cell degranulation and soyabean lipoxidase enzyme activit, and spasmolytic action using isolated guinea pig ileum preparation. In vivo studies included lipopolysaccharide-induced bronchial inflammation in rats and airway hyperresponsiveness in ovalbumin in sensitized guinea pigs using spirometry. Data was analysed by GraphPad Prism 5.01 and results were expressed as means ± SEM. P < 0.05 was considered to be significant. EOPI inhibits 5-lipoxidase enzyme activity, DPPH scavenging activity and erythropoietin- induced angiogenesis. It showed dose dependent anti-allergic activity by inhibiting compound 48/80 induced mast cell degranulation. The finding that essential oil induced inhibition of transient contraction of acetylcholine in calcium free medium, and relaxation of S-(-)-Bay 8644-precontracted isolated guinea pig ileum jointly suggest that suggesting that the L-subtype Cav channel is involved in spasmolytic action of EOPI. Treatment with EOPI dose dependently (7.5, 15 and 30 mg/kg i.p.) inhibited lipopolysaccharide- induced increased in total cell count, neutrophil count, nitrate-nitrite, total protein, albumin levels in bronchoalveolar fluid and myeloperoxidase levels in lung homogenates. Mild diffused lesions involving focal interalveolar septal, intraluminal infiltration of neutrophils were observed in EOPI (7.5 &15 mg/kg) pretreated while no abnormality was detected in EOPI (30 mg/kg) and roflumilast (1mg/kg) pretreated rats. Roflumilast was used as standard. EOPI reduced the respiratory flow due to gasping in ovalbumin sensitized guinea pigs. The study demonstrates the effectiveness of EOPI in bronchial asthma possibly related to its ability to inhibit L-subtype Cav channel, mast cell stabilization, antioxidant, angiostatic and through inhibition of 5-lipoxygenase enzyme.

Keywords: asthma, lipopolysaccharide, spirometry, Pistacia integerrima J.L. Stewart ex Brandis, essential oil

Procedia PDF Downloads 279