Search results for: diameter error

Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

Abstract:

Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 167

Authors: Carlos Amnael Orozco-Diaz, Robert David Moorehead, Gwendolen Reilly, Fiona Gilchrist, Cheryl Ann Miller

Abstract:

The current gold-standard for maxillofacial reconstruction surgery (MRS) utilizes auto-grafted cancellous bone as a filler. This study was aimed towards developing a polylactic-acid/hydroxyapatite (PLA-HA) composite suitable for fused-deposition 3D printing. Functionalization of the polymer through the addition of HA was directed to promoting bone-regeneration properties so that the material can rival the performance of cancellous bone grafts in terms of bone-lesion repair. This kind of composite enables the production of MRS implants based off 3D-reconstructions from image studies – namely computed tomography – for anatomically-correct fitting. The present study encompassed in-vitro degradation and in-vitro biocompatibility profiling for 3D-printed PLA and PLA-HA composites. PLA filament (Verbatim Co.) and Captal S hydroxyapatite micro-scale HA powder (Plasma Biotal Ltd) were used to produce PLA-HA composites at 5, 10, and 20%-by-weight HA concentration. These were extruded into 3D-printing filament, and processed in a BFB-3000 3D-Printer (3D Systems Co.) into tensile specimens, and were mechanically challenged as per ASTM D638-03. Furthermore, tensile specimens were subjected to accelerated degradation in phosphate-buffered saline solution at 70°C for 23 days, as per ISO-10993-13-2010. This included monitoring of mass loss (through dry-weighing), crystallinity (through thermogravimetric analysis/differential thermal analysis), molecular weight (through gel-permeation chromatography), and tensile strength. In-vitro biocompatibility analysis included cell-viability and extracellular matrix deposition, which were performed both on flat surfaces and on 3D-constructs – both produced through 3D-printing. Discs of 1 cm in diameter and cubic 3D-meshes of 1 cm3 were 3D printed in PLA and PLA-HA composites (n = 6). The samples were seeded with 5000 MG-63 osteosarcoma-like cells, with cell viability extrapolated throughout 21 days via resazurin reduction assays. As evidence of osteogenicity, collagen and calcium deposition were indirectly estimated through Sirius Red staining and Alizarin Red staining respectively. Results have shown that 3D printed PLA loses structural integrity as early as the first day of accelerated degradation, which was significantly faster than the literature suggests. This was reflected in the loss of tensile strength down to untestable brittleness. During degradation, mass loss, molecular weight, and crystallinity behaved similarly to results found in similar studies for PLA. All composite versions and pure PLA were found to perform equivalent to tissue-culture plastic (TCP) in supporting the seeded-cell population. Significant differences (p = 0.05) were found on collagen deposition for higher HA concentrations, with composite samples performing better than pure PLA and TCP. Additionally, per-cell-calcium deposition on the 3D-meshes was significantly lower when comparing 3D-meshes to discs of the same material (p = 0.05). These results support the idea that 3D-printable PLA-HA composites are a viable resorbable material for artificial grafts for bone-regeneration. Degradation data suggests that 3D-printing of these materials – as opposed to other manufacturing methods – might result in faster resorption than currently-used PLA implants.

Keywords: bone regeneration implants, 3D-printing, in vitro testing, biocompatibility, polymer degradation, polymer-ceramic composites

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Authors: Md Tanvir Rahman, Mahbube Subhani, Mahmud Ashraf, Paul Kremer

Abstract:

Cross-laminated timber (CLT) is made from layers of timber boards orthogonally oriented in the thickness direction, and due to this, CLT can withstand bi-axial bending in contrast with most other engineered wood products such as laminated veneer lumber (LVL) and glued laminated timber (GLT). Wood is cylindrically anisotropic in nature and is characterized by significantly lower elastic modulus and shear modulus in the planes perpendicular to the fibre direction, and is therefore classified as orthotropic material and is thus characterized by 9 elastic constants which are three elastic modulus in longitudinal direction, tangential direction and radial direction, three shear modulus in longitudinal tangential plane, longitudinal radial plane and radial tangential plane and three Poisson’s ratio. For simplification, timber materials are generally assumed to be transversely isotropic, reducing the number of elastic properties characterizing it to 5, where the longitudinal plane and radial planes are assumed to be planes of symmetry. The validity of this assumption was investigated through numerical modelling of CLT with both orthotropic mechanical properties and transversely isotropic material properties for three softwood species, which are Norway spruce, Douglas fir, Radiata pine, and three hardwood species, namely Victorian ash, Beech wood, and Aspen subjected to uniformly distributed loading under simply supported boundary condition. It was concluded that assuming the timber to be transversely isotropic results in a negligible error in the order of 1 percent. It was also observed that along with longitudinal elastic modulus, ratio of longitudinal shear modulus (GL) and rolling shear modulus (GR) has a significant effect on a deflection for CLT panels of lower span to depth ratio. For softwoods such as Norway spruce and Radiata pine, the ratio of longitudinal shear modulus, GL to rolling shear modulus GR is reported to be in the order of 12 to 15 times in literature. This results in shear flexibility in transverse layers leading to increased deflection under out-of-plane loading. The rolling shear modulus of hardwoods has been found to be significantly higher than those of softwoods, where the ratio between longitudinal shear modulus to rolling shear modulus as low as 4. This has resulted in a significant rise in research into the manufacturing of CLT from entirely from hardwood, as well as from a combination of softwood and hardwoods. The commonly used beam theory to analyze the performance of CLT panels under out-of-plane loads are the Shear analogy method, Gamma method, and k-method. The shear analogy method has been found to be the most effective method where shear deformation is significant. The effect of the ratio of longitudinal shear modulus and rolling shear modulus of cross-layer on the deflection of CLT under uniformly distributed load with respect to its length to depth ratio was investigated using shear analogy method. It was observed that shear deflection is reduced significantly as the ratio of the shear modulus of the longitudinal layer and rolling shear modulus of cross-layer decreases. This indicates that there is significant room for improvement of the bending performance of CLT through developing hybrid CLT from a mix of softwood and hardwood.

Keywords: rolling shear modulus, shear deflection, ratio of shear modulus and rolling shear modulus, timber

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Authors: Praveena Sinha

Abstract:

Context: Diabetes is a global public health burden, particularly affecting postmenopausal women. Insulin resistance (IR) is prevalent in this population, and it is associated with an increased risk of developing type 2 diabetes. Yoga therapy is gaining attention as a complementary intervention for diabetes due to its potential to address stress psychophysiology. This study focuses on the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Research Aim: The aim of this research is to investigate the effect of a 3-month long yoga practice on insulin resistance in early postmenopausal women. Methodology: The study conducted a prospective longitudinal design with 67 women within five years of menopause. Participants were divided into two groups based on their willingness to join yoga. The Yoga group (n = 37) received routine gynecological management along with an integrated yoga module, while the Non-Yoga group (n = 30) received only routine management. Insulin resistance was measured using the homeostasis model assessment of insulin resistance (HOMA-IR) method before and after the intervention. Statistical analysis was performed using GraphPad Prism Version 5 software, with statistical significance set at P < 0.05. Findings: The results indicate a significant decrease in serum fasting insulin levels and HOMA-IR measurements in the Yoga group, although the decrease did not reach statistical significance. In contrast, the Non-Yoga group showed a significant rise in serum fasting insulin levels and HOMA-IR measurements after 3 months, suggesting a detrimental effect on insulin resistance in these postmenopausal women. Theoretical Importance: This study provides evidence that a 12-week yoga practice can attenuate the increase in insulin resistance in early postmenopausal women. It highlights the potential of yoga as a preventive measure against the early onset of insulin resistance and the development of type 2 diabetes mellitus. Regular yoga practice can be a valuable tool in addressing hormonal imbalances associated with early postmenopause, leading to a decrease in morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in this population. Data Collection and Analysis Procedures: Data collection involved measuring serum fasting insulin levels and calculating HOMA-IR. Statistical analysis was performed using GraphPad Prism Version 5 software, and mean values with standard error of the mean were reported. The significance level was set at P < 0.05. Question Addressed: The study aimed to address whether a 3-month long yoga practice could attenuate insulin resistance in early postmenopausal women. Conclusion: The research findings support the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Regular yoga practice has the potential to prevent the early onset of insulin resistance and the development of type 2 diabetes mellitus in this population. By addressing the hormonal imbalances associated with early post menopause, yoga could significantly decrease morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in these subjects.

Keywords: post menopause, insulin resistance, HOMA-IR, yoga, type 2 diabetes mellitus

Procedia PDF Downloads 40

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

Procedia PDF Downloads 49

Authors: T. Schilirò, S. Bonetta, S. Bonetta, E. Ceretti, D. Feretti, I. Zerbini, V. Romanazzi, S. Levorato, T. Salvatori, S. Vannini, M. Verani, C. Pignata, F. Bagordo, G. Gilli, S. Bonizzoni, A. Bonetti, E. Carraro, U. Gelatti

Abstract:

Air pollution is one of the most important worldwide health concern. In the last years, in both the US and Europe, new directives and regulations supporting more restrictive pollution limits were published. However, the early effects of air pollution occur, especially for the urban population. Several epidemiological and toxicological studies have documented the remarkable effect of particulate matter (PM) in increasing morbidity and mortality for cardiovascular disease, lung cancer and natural cause mortality. The finest fractions of PM (PM with aerodynamic diameter <2.5 µm and less) play a major role in causing chronic diseases. The International Agency for Research on Cancer (IARC) has recently classified air pollution and fine PM as carcinogenic to human (1 Group). The structure and composition of PM influence the biological properties of particles. The chemical composition varies with season and region of sampling, photochemical-meteorological conditions and sources of emissions. The aim of the MAPEC (Monitoring Air Pollution Effects on Children for supporting public health policy) study is to evaluate the associations between air pollution and biomarkers of early biological effects in oral mucosa cells of 6-8 year old children recruited from first grade schools. The study was performed in five Italian towns (Brescia, Torino, Lecce, Perugia and Pisa) characterized by different levels of airborne PM (PM10 annual average from 44 µg/m3 measured in Torino to 20 µg/m3 measured in Lecce). Two to five schools for each town were chosen to evaluate the variability of pollution within the same town. Child exposure to urban air pollution was evaluated by collecting ultrafine PM (PM0.5) in the school area, on the same day of biological sampling. PM samples were collected for 72h using a high-volume gravimetric air sampler and glass fiber filters in two different seasons (winter and spring). Gravimetric analysis of the collected filters was performed; PM0.5 organic extracts were chemically analyzed (PAH, Nitro-PAH) and tested on A549 by the Comet assay and Micronucleus test and on Salmonella strains (TA100, TA98, TA98NR and YG1021) by Ames test. Results showed that PM0.5 represents a high variable PM10 percentage (range 19.6-63%). PM10 concentration were generally lower than 50µg/m3 (EU daily limit). All PM0.5 extracts showed a mutagenic effect with TA98 strain (net revertant/m3 range 0.3-1.5) and suggested the presence of indirect mutagens, while lower effect was observed with TA100 strain. The results with the TA98NR and YG1021 strains showed the presence of nitroaromatic compounds as confirmed by the chemical analysis. No genotoxic or oxidative effect of PM0.5 extracts was observed using the comet assay (with/without Fpg enzyme) and micronucleus test except for some sporadic samples. The low biological effect observed could be related to the low level of air pollution observed in this winter sampling associated to a high atmospheric instability. For a greater understanding of the relationship between PM size, composition and biological effects the results obtained in this study suggest to investigate the biological effect of the other PM fractions and in particular of the PM0.5-1 fraction.

Keywords: airborne PM, ames test, comet assay, micronucleus test

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Authors: Yetti Marlida, Syukri Arif, Nadirman Haska

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Recently, alcohol fuels have been produced on industrial scales by fermentation of sugars derived from wheat, corn, sugar beets, sugar cane etc. The enzymatic hydrolysis of cellulosic materials to produce fermentable sugars has an enormous potential in meeting global bioenergy demand through the biorefinery concept, since agri-food processes generate millions of tones of waste each year (Xeros and Christakopoulos 2009) such as sugar cane baggase , wheat straw, rice straw, corn cob, and oil palm trunk. In fact oil palm trunk is one of the most abundant lignocellulosic wastes by-products worldwide especially come from Malaysia, Indonesia and Nigeria and provides an alternative substrate to produce useful chemicals such as bioethanol. Usually, from the ages 3 years to 25 years, is the economical life of oil palm and after that, it is cut for replantation. The size of trunk usually is 15-18 meters in length and 46-60 centimeters in diameter. The trunk after cutting is agricultural waste causing problem in elimination but due to the trunk contains about 42% cellulose, 34.4%hemicellulose, 17.1% lignin and 7.3% other compounds,these agricultural wastes could make value added products (Pumiput, 2006).This research was production of bioethanol from oil palm trunk via saccharafication by cocktail carbohydrases enzymes. Enzymatic saccharification of acid treated oil palm trunk was carried out in reaction mixture containing 40 g treated oil palm trunk in 200 ml 0.1 M citrate buffer pH 4.8 with 500 unit/kg amylase for treatment A: Treatment B: Treatment A + 500 unit/kg cellulose; C: treatment B + 500 unit/kgg xylanase: D: treatment D + 500 unit/kg ligninase and E: OPT without treated + 500 unit/kg amylase + 500 unit/kg cellulose + 500 unit/kg xylanase + 500 unit/kg ligninase. The reaction mixture was incubated on a water bath rotary shaker adjusted to 600C and 75 rpm. The samples were withdraw at intervals 12 and 24, 36, 48,60, and 72 hr. For bioethanol production in biofermentor of 5L the hydrolysis product were inoculated a loop of Saccharomyces cerevisiae and then incubated at 34 0C under static conditions. Samples are withdraw after 12, 24, 36, 48 and 72 hr for bioethanol and residual glucose. The results of the enzymatic hidrolysis (Figure1) showed that the treatment B (OPT hydrolyzed with amylase and cellulase) have optimum condition for glucose production, where was both of enzymes can be degraded OPT perfectly. The same results also reported by Primarini et al., (2012) reported the optimum conditions the hydrolysis of OPT was at concentration of 25% (w /v) with 0.3% (w/v) amylase, 0.6% (w /v) glucoamylase and 4% (w/v) cellulase. In the Figure 2 showed that optimum bioethanol produced at 48 hr after incubation,if time increased the biothanol decreased. According Roukas (1996), a decrease in the concentration of ethanol occur at excess glucose as substrate and product inhibition effects. Substrate concentration is too high reduces the amount of dissolved oxygen, although in very small amounts, oxygen is still needed in the fermentation by Saccaromyces cerevisiae to keep life in high cell concentrations (Nowak 2000, Tao et al. 2005). The results of the research can be conluded that the optimum enzymatic hydrolysis occured when the OPT added with amylase and cellulase and optimum bioethanol produced at 48 hr incubation using Saccharomyses cerevicea whereas 18.08 % bioethanol produced from glucose conversion. This work was funded by Directorate General of Higher Education (DGHE), Ministry of Education and Culture, contract no.245/SP2H/DIT.LimtabMas/II/2013

Keywords: oil palm trunk, enzymatic hydrolysis, saccharification

Procedia PDF Downloads 492

Authors: Manushi Srivastava

Abstract:

Introduction: Doctor’s role, and relation with respect to patient care is at the core of medical ethics. The rapid pace of medical advances along with increasing consumer awareness about their rights and hike in cost of effective health care demand a robust, transparent and patient-friendly medical care system. However, doctors’ role performance is still in the frame of activity-passivity model of Doctor-Patient Relationship (DPR) where doctors act as parent and use to instruct their patients, without their consensus that is not going to help in the 21st century. Thus the current situation is a new challenge for traditional doctor-patient relationship after the introduction of Consumer Protection Act (CPA) in medical profession and the same is evidenced by increasing cases of medical litigation. To strengthen this system of medical services, the doctor plays a vital role, and the same should be reviewed in the present context. Objective: To understand the opinion of consultants regarding medical negligence and effect of Consumer Protection Act in terms of current practices of patient care. Method: This is a cross-sectional study in which both quantitative and qualitative methods are applied. Total 69 consultants were selected from multi-specialty hospitals of densely populated Varanasi city catering a population of about 1.8 million. Two-stage sampling was used for selection of respondents. At the first stage, selection of major wards (Medicine, Surgery, Ophthalmology, Gynaecology, Orthopaedics, and Paediatrics) was carried out, which are more susceptible to medical negligence. At the second stage, selection of consultants from the respective wards was carried out. In-depth Interviews were conducted with the help of semi-structured schedule. Two case studies of medical negligence were also carried out as part of the qualitative study. Analysis: Data were analyzed with the help of SPSS software (21.0 trial version). Semi-structured research tool was used to know consultant’s opinion about the pattern of medical negligence cases, litigations and claims made by patient community and inclusion of government medical services in CPA. Statistical analysis was done to describe data, and non-parametric test was used to observe the association between the variables. Analysis of Verbatim was used in case-study. Findings and Conclusion: Majority (92.8%) of consultants felt changes in the behaviour of community (patient) after implementation of CPA, as it had increased awareness about their rights. Less than half of the consultants opined that Medical Negligence is an Unintentional act of doctors and generally occurs due to communication gap and behavioural problem between doctor and patients. Experienced consultants ( > 10 years) pointed out that unethical practice by doctors and mal-intention of patient to harass doctors were additional reasons of Medical Negligence. In-depth interview revealed that now patients’ community expects more transparency and hence they demand cafeteria approach in diagnosis and management of cases. Thus as study results, we propose ‘Agreement Model’ of DPR to re-ensure ethical practice in medical profession.

Keywords: doctors, communication, consumer protection act (CPA), medical error

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Authors: Andrew Gray, Zhibing Zhang

Abstract:

The ability for consumer products to deliver a sustained perfume response can be a key driver for a variety of applications. Many compounds in perfume oils are highly volatile, meaning they readily evaporate once the product is applied, and the longevity of the scent is poor. Perfume capsules have been introduced as a means of abating this evaporation once the product has been delivered. The impermeable capsules are aimed to be stable within the formulation, and remain intact during delivery to the desired substrate, only rupturing to release the core perfume oil through application of mechanical force applied by the consumer. This opens up the possibility of obtaining an olfactive response hours, weeks or even months after delivery, depending on the nature of the desired application. Tailoring the properties of the polymeric capsules to better address the needs of the application is not a trivial challenge and currently design of capsules is largely done by trial and error. The aim of this work is to have more predictive methods for capsule design depending on the consumer application. This means refining formulations such that they rupture at the right time for the specific consumer application, not too early, not too late. Finding the right balance between these extremes is essential if a benefit is sought with respect to neat addition of perfume to formulations. It is important to understand the forces that influence capsule rupture, first, by quantifying the magnitude of these different forces, and then by assessing bulk rupture in real-world applications to understand how capsules actually respond. Samples were provided by an industrial partner and the mechanical properties of individual capsules within the samples were characterized via a micromanipulation technique, developed by Professor Zhang at the University of Birmingham. The capsules were synthesized such as to change one particular physicochemical property at a time, such as core: wall material ratio, and the average size of capsules. Analysis of shell thickness via Transmission Electron Microscopy, size distribution via the use of a Mastersizer, as well as a variety of other techniques confirmed that only one particular physicochemical property was altered for each sample. The mechanical analysis was subsequently undertaken, showing the effect that changing certain capsule properties had on the response under compression. It was, however, important to link this fundamental mechanical response to capsule performance in real-world applications. As such, the capsule samples were introduced to a formulation and exposed to full scale stresses. GC-MS headspace analysis of the perfume oil released from broken capsules enabled quantification of what the relative strengths of capsules truly means for product performance. Correlations have been found between the mechanical strength of capsule samples and performance in terms of perfume release in consumer applications. Having a better understanding of the key parameters that drive performance benefits the design of future formulations by offering better guidelines on the parameters that can be adjusted without worrying about the performance effects, and singles out those parameters that are essential in finding the sweet spot for capsule performance.

Keywords: consumer products, mechanical and physicochemical properties, perfume capsules, rupture behaviour

Procedia PDF Downloads 113

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Ali Kazemi

Abstract:

The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

Procedia PDF Downloads 26

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 51

Authors: Loreta Serniene, Dalia Sekmokiene, Justina Tomkeviciute, Lina Lauciene, Vaida Andruleviciute, Ingrida Sinkeviciene, Kristina Kondrotiene, Neringa Kasetiene, Mindaugas Malakauskas

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One of the most important areas of product development and research in the dairy industry is the product enrichment with active ingredients as well as leading to increased product safety and sustainability. The most expanding field of the active ingredients is the various plants' CO₂ extracts with aromatic, antioxidant and antimicrobial properties. In this study, 15 plant extracts were evaluated based on their antioxidant, antimicrobial properties as well as sensory acceptance indicators for the development of new dairy products. In order to increase the total antioxidant capacity of the milk products, it was important to determine the content of phenolic compounds and antioxidant activity of CO₂ extract. The total phenolic content of fifteen different commercial CO₂ extracts was determined by the Folin-Ciocalteu reagent and expressed as milligrams of the Gallic acid equivalents (GAE) in gram of extract. The antioxidant activities were determined by 2.2′-azinobis-(3-ethylbenzthiazoline)-6-sulfonate (ABTS) methods. The study revealed that the antioxidant activities of investigated CO₂ extract vary from 4.478-62.035 µmole Trolox/g, while the total phenolic content was in the range of 2.021-38.906 mg GAE/g of extract. For the example, the estimated antioxidant activity of Chinese cinnamon (Cinammonum aromaticum) CO₂ extract was 62.023 ± 0.15 µmole Trolox/g and the total flavonoid content reached 17.962 ± 0.35 mg GAE/g. These two parameters suggest that cinnamon could be a promising supplement for the development of new cheese. The inhibitory effects of these essential oils were tested by using agar disc diffusion method against pathogenic bacteria, most commonly found in dairy products. The obtained results showed that essential oil of lemon myrtle (Backhousia citriodora) and cinnamon (Cinnamomum cassia) has antimicrobial activity against E. coli, S. aureus, B. cereus, P. florescens, L. monocytogenes, Br. thermosphacta, P. aeruginosa and S. typhimurium with the diameter of inhibition zones variation from 10 to 52 mm. The sensory taste acceptability of plant extracts in combination with a dairy product was evaluated by a group of sensory evaluation experts (31 individuals) by the criteria of overall taste acceptability in the scale of 0 (not acceptable) to 10 (very acceptable). Each of the tested samples included 200g grams of natural unsweetened greek yogurt without additives and 1 drop of single plant extract (essential oil). The highest average of overall taste acceptability was defined for the samples with essential oils of orange (Citrus sinensis) - average score 6.67, lemon myrtle (Backhousia citriodora) – 6.62, elderberry flower (Sambucus nigra flos.) – 6.61, lemon (Citrus limon) – 5.75 and cinnamon (Cinnamomum cassia) – 5.41, respectively. The results of this study indicate plant extracts of Cinnamomum cassia and Backhousia citriodora as a promising additive not only to increase the total antioxidant capacity of the milk products and as alternative antibacterial agent to combat pathogenic bacteria commonly found in dairy products but also as a desirable flavour for the taste pallet of the consumers with expressed need for safe, sustainable and innovative dairy products. Acknowledgment: This research was funded by the European Regional Development Fund according to the supported activity 'Research Projects Implemented by World-class Researcher Groups' under Measure No. 01.2.2-LMT-K-718.

Keywords: antioxidant properties, antimicrobial properties, cinnamon, CO₂ plant extracts, dairy products, essential oils, lemon myrtle

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Authors: Raja Umer Sajjad, Chang Hee Lee

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Stormwater runoff is the leading contributor to pollution of receiving waters. In response, an efficient stormwater monitoring program is required to quantify and eventually reduce stormwater pollution. The overall goals of stormwater monitoring programs primarily include the identification of high-risk dischargers and the development of total maximum daily loads (TMDLs). The challenge in developing better monitoring program is to reduce the variability in flux estimates due to sampling errors; however, the success of monitoring program mainly depends on the accuracy of the estimates. Apart from sampling errors, manpower and budgetary constraints also influence the quality of the estimates. This study attempted to develop optimum stormwater monitoring design considering both cost and the quality of the estimated pollutants flux. Three years stormwater monitoring data (2012 – 2014) from a mix land use located within Geumhak watershed South Korea was evaluated. The regional climate is humid and precipitation is usually well distributed through the year. The investigation of a large number of water quality parameters is time-consuming and resource intensive. In order to identify a suite of easy-to-measure parameters to act as a surrogate, Principal Component Analysis (PCA) was applied. Means, standard deviations, coefficient of variation (CV) and other simple statistics were performed using multivariate statistical analysis software SPSS 22.0. The implication of sampling time on monitoring results, number of samples required during the storm event and impact of seasonal first flush were also identified. Based on the observations derived from the PCA biplot and the correlation matrix, total suspended solids (TSS) was identified as a potential surrogate for turbidity, total phosphorus and for heavy metals like lead, chromium, and copper whereas, Chemical Oxygen Demand (COD) was identified as surrogate for organic matter. The CV among different monitored water quality parameters were found higher (ranged from 3.8 to 15.5). It suggests that use of grab sampling design to estimate the mass emission rates in the study area can lead to errors due to large variability. TSS discharge load calculation error was found only 2 % with two different sample size approaches; i.e. 17 samples per storm event and equally distributed 6 samples per storm event. Both seasonal first flush and event first flush phenomena for most water quality parameters were observed in the study area. Samples taken at the initial stage of storm event generally overestimate the mass emissions; however, it was found that collecting a grab sample after initial hour of storm event more closely approximates the mean concentration of the event. It was concluded that site and regional climate specific interventions can be made to optimize the stormwater monitoring program in order to make it more effective and economical.

Keywords: first flush, pollutant load, stormwater monitoring, surrogate parameters

Procedia PDF Downloads 214

Authors: A.H.Y. Lai, C. Teyra

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In Taiwan, there are 16 official indigenous groups, accounting for 2.3% of the total population. Like other indigenous populations worldwide, indigenous peoples in Taiwan have poorer mental health because of their history of oppression and colonisation. Amid the negative narratives, the ethnic identity of cultural minorities is their unique psychological and cultural asset. Moreover, positive socialisation is found to be related to strong ethnic identity. Based on Phinney’s theory on ethnic identity development and social support theory, this study adopted a strength-based approach conceptualising ethnic identity as the central organising principle that linked perceived social support and mental health among indigenous adults in Taiwan. Aims. Overall aim is to examine the effect of ethnic identity and social support on mental health. Specific aims were to examine : (1) the association between ethnic identity and mental health; (2) the association between perceived social support and mental health ; (3) the indirect effect of ethnic identity linking perceived social support and mental health. Methods. Participants were indigenous adults in Taiwan (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Respondent-driven sampling was used. Standardised measurements were: Ethnic Identity Scale(6-item); Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender and economic satisfaction. A four-stage structural equation modelling (SEM) with robust maximin likelihood estimation was employed using Mplus8.0. Step 1: A measurement model was built and tested using confirmatory factor analysis (CFA). Step 2: Factor covariates were re-specified as direct effects in the SEM. Covariates were added. The direct effects of (1) ethnic identity and social support on depression and anxiety and (2) social support on ethnic identity were tested. The indirect effect of ethnic identity was examined with the bootstrapping technique. Results. The CFA model showed satisfactory fit statistics: x^2(df)=869.69(608), p<.05; Comparative ft index (CFI)/ Tucker-Lewis fit index (TLI)=0.95/0.94; root mean square error of approximation (RMSEA)=0.05; Standardized Root Mean Squared Residual (SRMR)=0.05. Ethnic identity is represented by two latent factors: ethnic identity-commitment and ethnic identity-exploration. Depression, anxiety and social support are single-factor latent variables. For the SEM, model fit statistics were: x^2(df)=779.26(527), p<.05; CFI/TLI=0.94/0.93; RMSEA=0.05; SRMR=0.05. Ethnic identity-commitment (b=-0.30) and social support (b=-0.33) had direct negative effects on depression, but ethnic identity-exploration did not. Ethnic identity-commitment (b=-0.43) and social support (b=-0.31) had direct negative effects on anxiety, while identity-exploration (b=0.24) demonstrated a positive effect. Social support had direct positive effects on ethnic identity-exploration (b=0.26) and ethnic identity-commitment (b=0.31). Mediation analysis demonstrated the indirect effect of ethnic identity-commitment linking social support and depression (b=0.22). Implications: Results underscore the role of social support in preventing depression via ethnic identity commitment among indigenous adults in Taiwan. Adopting the strength-based approach, mental health practitioners can mobilise indigenous peoples’ commitment to their group to promote their well-being.

Keywords: ethnic identity, indigenous population, mental health, perceived social support

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Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

Procedia PDF Downloads 253

Authors: Ivan Maguire, Alan Barrett, Alex Forte, Sandra Kwiatkowska, Rohit Mishra, Jens Ducrèe, Fiona Regan

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Biofouling is defined as the gradual accumulation of Biomimetics refers to the use and imitation of principles copied from nature. Biomimetics has found interest across many commercial disciplines. Among many biological objects and their functions, aquatic animals deserve a special attention due to their antimicrobial capabilities resulting from chemical composition, surface topography or other behavioural defences, which can be used as an inspiration for antifouling technology. Marine biofouling has detrimental effects on seagoing vessels, both commercial and leisure, as well as on oceanographic sensors, offshore drilling rigs, and aquaculture installations. Sensor optics, membranes, housings and platforms can become fouled leading to problems with sensor performance and data integrity. While many anti-fouling solutions are currently being investigated as a cost-cutting measure, biofouling settlement may also be prevented by creating a surface that does not satisfy the settlement conditions. Brill (Scophthalmus rhombus) is a small flatfish occurring in marine waters of Mediterranean as well as Norway and Iceland. It inhabits sandy and muddy coastal waters from 5 to 80 meters. Its skin colour changes depending on environment, but generally is brownish with light and dark freckles, with creamy underside. Brill is oval in shape and its flesh is white. The aim of this study is to translate the unique micro-topography of the brill scale, to design marine inspired biomimetic surface coating and test it against a typical fouling organism. Following extensive study of scale topography of the brill fish (Scophthalmus rhombus) and the settlement behaviour of the diatom species Psammodictyon sp. via SEM, two state-of-the-art antifouling surface solutions were designed and investigated; A brill fish scale bioinspired surface pattern platform (BFD), and generic and uniformly-arrayed, circular micropillar platform (MPD), with offsets based on diatom species settlement behaviour. The BFD approach consists of different ~5 μm by ~90 μm Brill-replica patterns, grown to a 5 μm height, in a linear array pattern. The MPD approach utilises hexagonal-packed cylindrical pillars 10.6 μm in diameter, grown to a height of 5 μm, with vertical offset of 15 μm and horizontal offset of 26.6 μm. Photolithography was employed for microstructure growth, with a polydimethylsiloxane (PDMS) chip-based used as a testbed for diatom adhesion on both platforms. Settlement and adhesion tests were performed using this PDMS microfluidic chip through subjugation to centrifugal force via an in-house developed ‘spin-stand’ which features a motor, in combination with a high-resolution camera, for real-time observing diatom release from PDMS material. Diatom adhesion strength can therefore be determined based on the centrifugal force generated at varying rotational speeds. It is hoped that both the replica and bio-inspired solutions will give comparable anti-fouling results to these synthetic surfaces, whilst also assisting in determining whether anti-fouling solutions should predominantly be investigating either fully bioreplica-based, or a bioinspired, synthetically-based design.

Keywords: anti-fouling applications, bio-inspired microstructures, centrifugal microfluidics, surface modification

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Authors: Farideh Namvar, Rosfarizan Mohamed

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In the field of nanotechnology, the use of various biological units instead of toxic chemicals for the reduction and stabilization of nanoparticles, has received extensive attention. This use of biological entities to create nanoparticles has designated as “Green” synthesis and it is considered to be far more beneficial due to being economical, eco-friendly and applicable for large-scale synthesis as it operates on low pressure, less input of energy and low temperatures. The lack of toxic byproducts and consequent decrease in degradation of the product renders this technique more preferable over physical and classical chemical methods. The variety of biomass having reduction properties to produce nanoparticles makes them an ideal candidate for fabrication. Metal oxide nanoparticles have been said to represent a "fundamental cornerstone of nanoscience and nanotechnology" due to their variety of properties and potential applications. However, this also provides evidence of the fact that metal oxides include many diverse types of nanoparticles with large differences in chemical composition and behaviour. In this study, iron oxide nanoparticles (Fe3O4-NPs) were synthesized using a rapid, single step and completely green biosynthetic method by reduction of ferric chloride solution with brown seaweed (Sargassum muticum) water extract containing polysaccharides as a main factor which acts as reducing agent and efficient stabilizer. Antimicrobial activity against six microorganisms was tested using well diffusion method. The resulting S-IONPs are crystalline in nature, with a cubic shape. The average particle diameter, as determined by TEM, was found to be 18.01 nm. The S-IONPs were efficiently inhibited the growth of Listeria monocytogenes, Escherichia coli and Candida species. Our favorable results suggest that S-IONPs could be a promising candidate for development of future antimicrobial therapies. The nature of biosynthesis and the therapeutic potential by S-IONPs could pave the way for further research on design of green synthesis therapeutic agents, particularly nanomedicine, to deal with treatment of infections. Further studies are needed to fully characterize the toxicity and the mechanisms involved with the antimicrobial activity of these particles. Antioxidant activity of S-IONPs synthesized by green method was measured by ABTS (2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (IC50= 1000µg) radical scavenging activity. Also, with the increasing concentration of S-IONPs, catalase gene expression compared to control gene GAPDH increased. For anti-angiogenesis study the Ross fertilized eggs were divided into four groups; the control and three experimental groups. The gelatin sponges containing albumin were placed on the chorioalantoic membrane and soaked with different concentrations of S-IONPs. All the cases were photographed using a photo stereomicroscope. The number and the lengths of the vessels were measured using Image J software. The crown rump (CR) and weight of the embryo were also recorded. According to the data analysis, the number and length of the blood vessels, as well as the CR and weight of the embryos reduced significantly compared to the control (p < 0.05), dose dependently. The total hemoglobin was quantified as an indicator of the blood vessel formation, and in the treated samples decreased, which showed its inhibitory effect on angiogenesis.

Keywords: anti-angiogenesis, antimicrobial, antioxidant, biosynthesis, iron oxide (fe3o4) nanoparticles, sargassum muticum, seaweed

Procedia PDF Downloads 295

Authors: Shyam Sunder Gupta

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For creation of Universe, theory of Big Bang , from Singularity is most acceptable theory, but has limitations as it does not answer ; how Singularity gets created and what causes Big Bang ?Further , Universe is composed of 95% Dark Energy and Dark Matter and balance 5% is visible part of Universe , but no explanation . Recently, it has been reported that there could be very large number of Universes, but only , a stipulation. This research which is based on Bhagvat Puran, a Vedic Scripture answers all questions. There is a Unique Energy Field which is eternal and infinite. The carrier Particles of Unique Energy are Paramanus; God Particles. Paramanus are Fundamental Particles and combination of these particles create bigger particles from which Universe gets created. For creation to initiate, Unique Energy gets represented in three phases; Positive Male Energy, Neutral Energy(creates Eternal Time)and Negative Female Energy. Positive Male Energy further expands in three forms of Creative Energies (CE1,CE2andCE3)and 16 principles get created, namely, Energy of Activation , Energy of Action, Energy of Darkness, Pradhan ( Equilibrium state of three energies ) , Prakriti(Non-equilibrium state of three energies, creating modes of Activation, Action and Darkness),Mahat-tattva ( consists of three modes , dominant in Mode of Darkness), Time, Energy of Consciousness, Ego Energy(consists of three modes , very strongly dominated by Mode of Darkness),Energy of Intellect, Mind Energy , Sky( creates Space and Sound Energy),Air(creates gaseous substances), Fire( creates different forms of energies like thermal, light, electrical etc.), Water( creates liquid substances)and Earth(creates solid substances). CE1 Energy creates Infinite number of Singularities from seven principles, Pradhan , Mahat-tattva, Sky , Air, Fire, Water and Earth . CE1 Energy gets divided as CE2 and enters along with other 9 principles , in each of Singularity and Primary Big Bang takes and infinite number of Universes get created. Each Universe has seven coverings of 7 principles and each layer is 10 times thicker than previous layer. By Energy CE2 , space in Universe under the coverings is divided in two parts , upper part and lower part. Upper part is occupied by Dark Energy which is created from Mode of Darkness in Ego Energy which keeps getting converted in Dark Matter and forms Invisible part of Universe. In the lower part , process of evolution gets initiated and seeds of 24 elements , Consciousness , Ego, Intellect, Mind, 5 Fundamental Elements( space, Air, Fire, Water Earth, which create non-living matter ),5 senses which receive inputs( eyes, nose, ears, tongue , skin), 5 Working Senses (Smell, Taste, Sight, Touch and Hearing);5 elements of Action( Organs of procreation , excretion, locomotion , speech and acquisition ), get created . In EC2 Energy, Singularity gets created which gets exploded by force of Energy of Action ,and Secondary Big Bang takes place and Visible Universe gets created in the shape of Bud of Flower Lotus . Within the Visible part of Universe, a small part gets created , Phenomenal Universe. Diameter of Sun and planetary system ,at the time of formation ,is 6.4 billion km, which is close to reported value . There are 5 different orbits , with reference to our Solar System. Moon around earth takes one month,, earth around sun one year, sun around Milk way one cosmic year(322.58 million years), Milky way around Universe 4.32 billion years and universe around center of universe 311.04 trillion years. Universe creation is a cyclic process with cycle time of 622.08 trillion years.In summary, Universe consists of 4 parts; covering of 7 layers, Dark Energy and Dark Matter, Visible and Phenomenal universe.

Keywords: big bang, creation, dark energy, dark matter, singularity, universe

Procedia PDF Downloads 55

Authors: Ntandazo Dlatu, Benjamin Longo-Mbenza, Andre Renzaho, Ruffin Appalata, Yolande Yvonne Valeria Matoumona Mavoungou, Mbenza Ben Longo, Kenneth Ekoru, Blaise Makoso, Gedeon Longo Longo

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Background: The gap between complexities related to the integration of Tuberculosis /HIV control and evidence-based knowledge motivated the initiation of the study. Therefore, the objective of this study was to explore correlations between national TB management guidelines, multiple deprivation indexes, quantiles, components and levels of Tuberculosis control programme using mathematical modeling in rural O.R. Tambo District Health Facilities, South Africa. Methods: The study design used mixed secondary data analysis and cross-sectional analysis between 2009 and 2013 across O.R Tambo District, Eastern Cape, South Africa using univariate/ bivariate analysis, linear multiple regression models, and multivariate discriminant analysis. Health inequalities indicators and component of an impediment to the tuberculosis control programme were evaluated. Results: In total, 62 400 records for TB notification were analyzed for the period 2009-2013. There was a significant but negative between Financial Year Expenditure (r= -0.894; P= 0.041) Seropositive HIV status(r= -0.979; P= 0.004), Population Density (r = -0.881; P= 0.048) and the number of TB defaulter in all TB cases. It was shown unsuccessful control of TB management program through correlations between numbers of new PTB smear positive, TB defaulter new smear-positive, TB failure all TB, Pulmonary Tuberculosis case finding index and deprivation-concentration-dispersion index. It was shown successful TB program control through significant and negative associations between declining numbers of death in co-infection of HIV and TB, TB deaths all TB and SMIAD gradient/ deprivation-concentration-dispersion index. The multivariate linear model was summarized by unadjusted r of 96%, adjusted R2 of 95 %, Standard Error of estimate of 0.110, R2 changed of 0.959 and significance for variance change for P=0.004 to explain the prediction of TB defaulter in all TB with equation y= 8.558-0.979 x number of HIV seropositive. After adjusting for confounding factors (PTB case finding the index, TB defaulter new smear-positive, TB death in all TB, TB defaulter all TB, and TB failure in all TB). The HIV and TB death, as well as new PTB smear positive, were identified as the most important, significant, and independent indicator to discriminate most deprived deprivation index far from other deprivation quintiles 2-5 using discriminant analysis. Conclusion: Elimination of poverty such as overcrowding, lack of sanitation and environment of highest burden of HIV might end the TB threat in O.R Tambo District, Eastern Cape, South Africa. Furthermore, ongoing adequate budget comprehensive, holistic and collaborative initiative towards Sustainable Developmental Goals (SDGs) is necessary for complete elimination of TB in poor O.R Tambo District.

Keywords: tuberculosis, HIV/AIDS, success, failure, control program, health inequalities, South Africa

Procedia PDF Downloads 138

Authors: Riadh Zorgati, Thomas Triboulet

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In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Jatziri Y. Moreno-Martínez, Arturo Galván, Israel Enrique Herrera Díaz, José Ramón Gasca Tirado

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In recent years, for the elevated viaducts in Mexico City, a construction system based on precast/pre-stressed concrete elements has been used, in which the bridge girders are divided in two parts by imposing a hinged support in sections where the bending moments that are originated by the gravity loads in a continuous beam are minimal. Precast concrete girders with dapped ends are a representative sample of a behavior that has complex configurations of stresses that make them more vulnerable to cracking due to flexure–shear interaction. The design procedures for ends of the dapped girders are well established and are based primarily on experimental tests performed for different configurations of reinforcement. The critical failure modes that can govern the design have been identified, and for each of them, the methods for computing the reinforcing steel that is needed to achieve adequate safety against failure have been proposed. Nevertheless, the design recommendations do not include procedures for controlling diagonal cracking at the entrant corner under service loading. These cracks could cause water penetration and degradation because of the corrosion of the steel reinforcement. The lack of visual access to the area makes it difficult to detect this damage and take timely corrective actions. Three-dimensional non-linear numerical models based on Finite Element Method to study the cracking at the entrant corner of dapped-end beams were performed using the software package ANSYS v. 11.0. The cracking was numerically simulated by using the smeared crack approach. The concrete structure was modeled using three-dimensional solid elements SOLID65 capable of cracking in tension and crushing in compression. Drucker-Prager yield surface was used to include the plastic deformations. The longitudinal post-tension was modeled using LINK8 elements with multilinear isotropic hardening behavior using von Misses plasticity. The reinforcement was introduced with smeared approach. The numerical models were calibrated using experimental tests carried out in “Instituto de Ingeniería, Universidad Nacional Autónoma de México”. In these numerical models the characteristics of the specimens were considered: typical solution based on vertical stirrups (hangers) and on vertical and horizontal hoops with a post-tensioned steel which contributed to a 74% of the flexural resistance. The post-tension is given by four steel wires with a 5/8’’ (16 mm) diameter. Each wire was tensioned to 147 kN and induced an average compressive stress of 4.90 MPa on the concrete section of the dapped end. The loading protocol consisted on applying symmetrical loading to reach the service load (180 kN). Due to the good correlation between experimental and numerical models some additional numerical models were proposed by considering different percentages of post-tension in order to find out how much it influences in the appearance of the cracking in the reentrant corner of the dapped-end beams. It was concluded that the increasing of percentage of post-tension decreases the displacements and the cracking in the reentrant corner takes longer to appear. The authors acknowledge at “Universidad de Guanajuato, Campus Celaya-Salvatierra” and the financial support of PRODEP-SEP (UGTO-PTC-460) of the Mexican government. The first author acknowledges at “Instituto de Ingeniería, Universidad Nacional Autónoma de México”.

Keywords: concrete dapped-end beams, cracking control, finite element analysis, postension

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Authors: Do-Won Kim, Andy Eu Jin Lim, Raja Muthusamy Kumarasamy, Vishal Vinayak, Jacky Wang Yu-Shun, Jason Liow Tsung Yang, Patrick Lo Guo Qiang

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In this study, we demonstrate 4-channel coarse wavelength division multiplexing (CWDM) optical transceiver based on silicon photonics integrated circuits (PIC) of waveguide Ge-photodiode (Ge-PD) and Mach Zehnder (MZ)-modulator. 4-channel arrayed PICs of Ge-PD and MZ-modulator are verified to operate at 25 Gbps/ch achieving 4x25 Gbps of total data rate. 4 bare dies of single-channel commercial electronics ICs (EICs) of trans-impedance amplifier (TIA) for Ge-PD and driver IC for MZ-modulator are packaged with PIC on printed circuit board (PCB) in a chip-on-board (COB) manner. Each single-channel EIC is electrically connected to the one channel of 4-channel PICs by wire bonds to trace. The PICs have 4-channel multiplexer for MZ-modulator and 4-channel demultiplexer for Ge-PD. The 4-channel multiplexer/demultiplexer have echelle gratings for4 CWDM optic signals of which center wavelengths are 1511, 1531, 1553, and 1573 nm. Its insertion loss is around 4dB with over 15dB of extinction ratio.The dimension of 4-channel Ge-PD is 3.6x1.4x0.3mm, and its responsivity is 1A/W with dark current of less than 20 nA.Its measured 3dB bandwidth is around 20GHz. The dimension of the 4-channel MZ-modulator is 3.6x4.8x0.3mm, and its 3dB bandwidth is around 11Ghz at -2V of reverse biasing voltage. It has 2.4V•cmbyVπVL of 6V for π shift to 4 mm length modulator.5x5um of Inversed tapered mode size converter with less than 2dB of coupling loss is used for the coupling of the lensed fiber which has 5um of mode field diameter.The PCB for COB packaging and signal transmission is designed to have 6 layers in the hybrid layer structure. 0.25 mm-thick Rogers Duroid RT5880 is used as the first core dielectric layer for high-speed performance over 25 Gbps. It has 0.017 mm-thick of copper layers and its dielectric constant is 2.2and dissipation factor is 0.0009 at 10 GHz. The dimension of both single ended and differential microstrip transmission lines are calculated using full-wave electromagnetic (EM) field simulator HFSS which RF industry is using most. It showed 3dB bandwidth at around 15GHz in S-parameter measurement using network analyzer. The wire bond length for transmission line and ground connection from EIC is done to have less than 300 µm to minimize the parasitic effect to the system.Single layered capacitors (SLC) of 100pF and 1000pF are connected as close as possible to the EICs for stabilizing the DC biasing voltage by decoupling. Its signal transmission performance is under measurement at 25Gbps achieving 100Gbps by 4chx25Gbps. This work can be applied for the active optical cable (AOC) and quad small form-factor pluggable (QSFP) for high-speed optical interconnections. Its demands are quite large in data centers targeting 100 Gbps, 400 Gbps, and 1 Tbps. As the demands of high-speed AOC and QSFP for the application to intra/inter data centers increase, this silicon photonics based high-speed 4 channel CWDM scheme can have advantages not only in data throughput but also cost effectiveness since it reduces fiber cost dramatically through WDM.

Keywords: active optical cable(AOC), 4-channel coarse wavelength division multiplexing (CWDM), communication system, data center, ge-photodiode, Mach Zehnder (MZ) modulator, optical interconnections, optical transceiver, photonics integrated circuits (PIC), quad small form-factor pluggable (QSFP), silicon photonics

Procedia PDF Downloads 389

Authors: Quan Wen, Tianxiao Chang, Shaolu Shi, Yushi Wang, Guangyu Wang

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As a kind of working environment of the fuze, the spin rate decaying law of projectile in exterior trajectory is of great value in the design of the rotation count fixed distance fuze. In addition, it is significant in the field of devices for simulation tests of fuze exterior ballistic environment, flight stability, and dispersion accuracy of gun projectile and opening and scattering design of submunition and illuminating cartridges. Besides, the self-destroying mechanism of the fuze in small-caliber projectile often works by utilizing the attenuation of centrifugal force. In the theory of projectile aerodynamics and fuze design, there are many formulas describing the change law of projectile angular velocity in external ballistic such as Roggla formula, exponential function formula, and power function formula. However, these formulas are mostly semi-empirical due to the poor test conditions and insufficient test data at that time. These formulas are difficult to meet the design requirements of modern fuze because they are not accurate enough and have a narrow range of applications now. In order to provide more accurate ballistic environment parameters for the design of a hemispherical head projectile fuze, the projectile’s spin rate decaying law in exterior trajectory under the effect of air resistance was studied. In the analysis, the projectile shape was simplified as hemisphere head, cylindrical part, rotating band part, and anti-truncated conical tail. The main assumptions are as follows: a) The shape and mass are symmetrical about the longitudinal axis, b) There is a smooth transition between the ball hea, c) The air flow on the outer surface is set as a flat plate flow with the same area as the expanded outer surface of the projectile, and the boundary layer is turbulent, d) The polar damping moment attributed to the wrench hole and rifling mark on the projectile is not considered, e) The groove of the rifle on the rotating band is uniform, smooth and regular. The impacts of the four parts on aerodynamic moment of the projectile rotation were obtained by aerodynamic theory. The surface friction stress of the projectile, the polar damping moment formed by the head of the projectile, the surface friction moment formed by the cylindrical part, the rotating band, and the anti-truncated conical tail were obtained by mathematical derivation. After that, the mathematical model of angular spin rate attenuation was established. In the whole trajectory with the maximum range angle (38°), the absolute error of the polar damping torque coefficient obtained by simulation and the coefficient calculated by the mathematical model established in this paper is not more than 7%. Therefore, the credibility of the mathematical model was verified. The mathematical model can be described as a first-order nonlinear differential equation, which has no analytical solution. The solution can be only gained as a numerical solution by connecting the model with projectile mass motion equations in exterior ballistics.

Keywords: ammunition engineering, fuze technology, spin rate, numerical simulation

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Authors: Kenneth A. Rostowsky, Alexander S. Maher, Nahian F. Chowdhury, Andrei Irimia

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The clinical significance of cerebral microbleeds (CMBs) due to mild traumatic brain injury (mTBI) remains unclear. Here we use magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and connectomic analysis to investigate the statistical association between mTBI-related CMBs, post-TBI changes to the human connectome and neurological/cognitive deficits. This study was undertaken in agreement with US federal law (45 CFR 46) and was approved by the Institutional Review Board (IRB) of the University of Southern California (USC). Two groups, one consisting of 26 (13 females) mTBI victims and another comprising 26 (13 females) healthy control (HC) volunteers were recruited through IRB-approved procedures. The acute Glasgow Coma Scale (GCS) score was available for each mTBI victim (mean µ = 13.2; standard deviation σ = 0.4). Each HC volunteer was assigned a GCS of 15 to indicate the absence of head trauma at the time of enrollment in our study. Volunteers in the HC and mTBI groups were matched according to their sex and age (HC: µ = 67.2 years, σ = 5.62 years; mTBI: µ = 66.8 years, σ = 5.93 years). MRI [including T1- and T2-weighted volumes, gradient recalled echo (GRE)/susceptibility weighted imaging (SWI)] and gradient echo (GE) DWI volumes were acquired using the same MRI scanner type (Trio TIM, Siemens Corp.). Skull-stripping and eddy current correction were implemented. DWI volumes were processed in TrackVis (http://trackvis.org) and 3D Slicer (http://www.slicer.org). Tensors were fit to DWI data to perform DTI, and tractography streamlines were then reconstructed using deterministic tractography. A voxel classifier was used to identify image features as CMB candidates using Microbleed Anatomic Rating Scale (MARS) guidelines. For each peri-lesional DTI streamline bundle, the null hypothesis was formulated as the statement that there was no neurological or cognitive deficit associated with between-scan differences in the mean FA of DTI streamlines within each bundle. The statistical significance of each hypothesis test was calculated at the α = 0.05 level, subject to the family-wise error rate (FWER) correction for multiple comparisons. Results: In HC volunteers, the along-track analysis failed to identify statistically significant differences in the mean FA of DTI streamline bundles. In the mTBI group, significant differences in the mean FA of peri-lesional streamline bundles were found in 21 out of 26 volunteers. In those volunteers where significant differences had been found, these differences were associated with an average of ~47% of all identified CMBs (σ = 21%). In 12 out of the 21 volunteers exhibiting significant FA changes, cognitive functions (memory acquisition and retrieval, top-down control of attention, planning, judgment, cognitive aspects of decision-making) were found to have deteriorated over the six months following injury (r = -0.32, p < 0.001). Our preliminary results suggest that acute post-TBI CMBs may be associated with cognitive decline in some mTBI patients. Future research should attempt to identify mTBI patients at high risk for cognitive sequelae.

Keywords: traumatic brain injury, magnetic resonance imaging, diffusion tensor imaging, connectomics

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Authors: Nkechi V. Enwuru, Bullum Nkeki, Elizabeth A. Adekoya, Olumide A. Adebesin, Rebecca F. Peters, Victoria A. Aikhomu, Mendie E. U.

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Background: Probiotics are live microbial feed supplement beneficial for host. Probiotics and their postbiotic products have been used to prevent or treat various health conditions. However, the products cell viability is often low due to harsh conditions subjected during processing, handling, storage, and gastrointestinal transit. These strongly influence probiotics’ benefits; thus, viability is essential for probiotics to produce health benefits for the host. Microencapsulation is a promising technique with considerable effects on probiotic survival. The study is aimed to formulate a microencapsulated probiotic and evaluate its viability, antimicrobial efficacy, and cytotoxic activity of its postbiotic on the MCF-7 breast cancer cell line. Method: Human and animal raw milk were sampled for lactic acid bacteria. The isolated bacteria were identified using conventional and VITEK 2 systems. The identified lactic acid bacterium was encapsulated using spray-dried and extrusion methods. The free, encapsulated, and chitosan-coated encapsulated probiotics were tested for viability in simulated-gastric intestinal (SGI) fluid and different storage conditions at refrigerated (4oC) and room (25oC) temperatures. The disintegration time and weight uniformity of the spray-dried hard gelatin capsules were tested. The antimicrobial property of free and encapsulated probiotics was tested against enteric pathogenic isolates from antiretroviral therapy (ART) treated HIV-positive patients. The postbiotic of the free cells was extracted, and its cytotoxic effect on the MCF-7 breast cancer cell line was tested through an MTT assay. Result: The Lactobacillus plantarum was isolated from animal raw milk. Zero-size hard gelatin L. plantarum capsules with granules within a size range of 0.71–1.00 mm diameter was formulated. The disintegration time ranges from 2.14±0.045 to 2.91±0.293 minutes, while the average weight is 502.1mg. Simulated gastric solution significantly affected viability of both free and microcapsules. However, the encapsulated cells were more protected and viable due to impermeability in the microcapsules. Furthermore, the viability of free cells stored at 4oC and 25oC were less than 4 log CFU/g and 6 log CFU/g respectively after 12 weeks. However, the microcapsules stored at 4oC achieved the highest viability among the free and microcapsules stored at 25oC and the free cells stored at 4oC. Encapsulated cells were released in the simulated gastric fluid, viable and effective against the enteric pathogens tested. However, chitosan-coated calcium alginate encapsulated probiotics significantly inhibited Shigella flexneri, Candida albicans, and Escherichia coli. The Postbiotic Metabolites (PM) of L. plantarum produced a cytotoxic effect on the MCF-7 breast cancer cell line. The postbiotic showed significant cytotoxic activity similar to 5FU, a standard antineoplastic agent. The inhibition concentration of 50% growth (IC50) of postbiotic metabolite K3 is low and consistent with the IC50 of the positive control (Cisplatin). Conclusions: Lactobacillus plantarum postbiotic exhibited a cytotoxic effect on the MCF-7 breast cancer cell line and could be used as combined adjuvant therapy in breast cancer management. The microencapsulation technique protects the probiotics, improving their viability and delivery to the gastrointestinal tract. Chitosan enhances antibacterial efficacy; thus, chitosan-coated microencapsulated L. plantarum probiotics could be more effective and used as a combined therapy in HIV management of opportunistic enteric infection.

Keywords: probiotics, encapsulation, gastrointestinal conditions, antimicrobial effect, postbiotic, cytotoxicity effect

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

Procedia PDF Downloads 104

Authors: Yuna Lee

Abstract:

In the current policy process, there has been a growing interest in more open approaches that incorporate creativity and innovation based on the forecasting groups composed by the public and experts together into scientific data-driven foresight methods to implement more effective policymaking. Especially, citizen participation as collective intelligence in policymaking with design and deep scale of innovation at the global level has been developed and human-centred design thinking is considered as one of the most promising methods for strategic foresight. Yet, there is a lack of a common theoretical foundation for a comprehensive approach for the current situation of and post-COVID-19 era, and substantial changes in policymaking practice are insignificant and ongoing with trial and error. This project hypothesized that rigorously developed policy systems and tools that support strategic foresight by considering the public understanding could maximize ways to create new possibilities for a preferable future, however, it must involve a better understating of Behavioural Insights, including individual and cultural values, profit motives and needs, and psychological motivations, for implementing holistic and multilateral foresight and creating more positive possibilities. To what extent is the policymaking system theoretically possible that incorporates the holistic and comprehensive foresight and policy process implementation, assuming that theory and practice, in reality, are different and not connected? What components and environmental conditions should be included in the strategic foresight system to enhance the capacity of decision from policymakers to predict alternative futures, or detect uncertainties of the future more accurately? And, compared to the required environmental condition, what are the environmental vulnerabilities of the current policymaking system? In this light, this research contemplates the question of how effectively policymaking practices have been implemented through the synthesis of scientific, technology-oriented innovation with the strategic design for tackling complex societal challenges and devising more significant insights to make society greener and more liveable. Here, this study conceptualizes the notions of a new collaborative way of strategic foresight that aims to maximize mutual benefits between policy actors and citizens through the cooperation stemming from evolutionary game theory. This study applies mixed methodology, including interviews of policy experts, with the case in which digital transformation and strategic design provided future-oriented solutions or directions to cities’ sustainable development goals and society-wide urgent challenges such as COVID-19. As a result, artistic and sensual interpreting capabilities through strategic design promote a concrete form of ideas toward a stable connection from the present to the future and enhance the understanding and active cooperation among decision-makers, stakeholders, and citizens. Ultimately, an improved theoretical foundation proposed in this study is expected to help strategically respond to the highly interconnected future changes of the post-COVID-19 world.

Keywords: policymaking, strategic design, sustainable innovation, evolution of cooperation

Procedia PDF Downloads 166

Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

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Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

Procedia PDF Downloads 280

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

Procedia PDF Downloads 369