Search results for: deep hole

Authors: Saba Didarataee, Abbas Ali Khodadadi, Yadollah Mortazavi, Fatemeh Mousavi

Abstract:

Photocatalytic water splitting is one of the most attractive alternative methods for hydrogen evolution. A variety of nanoparticle engineering techniques were introduced to improve the activity of semiconductor photocatalysts. Among these methods, heterojunction formation is an appealing method due to its ability to effectively preventing electron-hole recombination and improving photocatalytic activity. Reaching an optimal ratio of the two target semiconductors for the formation of heterojunctions is still an open question. Considering environmental issues as well as the cost and availability, ZnS and ZnO are frequently studied as potential choices. In this study, first, the ZnS nanoparticle was synthesized in a hydrothermal process; the formation of ZnS nanorods with a diameter of 14-30 nm was confirmed by field emission scanning electron microscope (FESEM). Then two different methods, partial oxidation and chemical precipitation were employed to construct ZnS/ZnO core-shell heterojunction. X-ray diffraction (XRD), BET, and diffuse reflectance spectroscopy (DRS) analysis were carried out to determine crystallite phase, surface area, and bandgap of photocatalysts. Furthermore, the temperature of oxidation was specified by a temperature programmed oxidation (TPO) and was fixed at 510℃, at which mild oxidation occurred. The bandgap was calculated by the Kubelka-Munk method and decreased by increasing oxide content from 3.53 (pure ZnS) to 3.18 (pure ZnO). The optimal samples were determined by testing the photocatalytic activity of hydrogen evolution in a quartz photoreactor with side irradiation of UVC lamps with a wavelength of 254 nm. In both procedures, it was observed that the photocatalytic activity of the ZnS/ZnO composite was sensibly higher than the pure ZnS and ZnO, which is attributed to forming a type-II heterostructure. The best ratio of oxide to sulfide was 0.24 and 0.37 in partial oxidation and chemical precipitation, respectively. The highest hydrogen evolution was 1081 µmol/gr.h, gained from partial oxidizing of ZnS nanoparticles at 510℃ for 30 minutes.

Keywords: heterostructure, hydrogen, partial oxidation, photocatalyst, water splitting, ZnS

Procedia PDF Downloads 128

Authors: Mounir Zekkaoui, Abdelhadi Fennan

Abstract:

The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

Procedia PDF Downloads 445

Authors: Abdulwakeel B. Raji

Abstract:

This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

Procedia PDF Downloads 135

Authors: Risdiana, D. Suhendar, S. Pratiwi, W. A. Somantri, T. Saragi

Abstract:

Superconductor is a promising material for future applications especially for energy saving because of their advantages properties such as zero electrical resistivity when they are cooled down to sufficiently low temperatures. However, the mechanism describing the role of physical properties in superconductor is far from being understood clearly, so that the application of this material for wider benefit in various industries is very limited. Most of superconductors are cuprate compounds, which has CuO2 as a conducting plane in their crystal structures. The study of physical properties through the partially substitution of impurity for Cu in superconducting cuprates has been one of great interests in relation to the mechanism of superconductivity. Different behaviors between the substitution of nonmagnetic impurity and magnetic impurity for Cu are observed. For examples, the superconductivity and Cu-spin fluctuations in the electron-doped system are suppressed through the substitution of magnetic Ni for Cu more markedly than through the substitution of nonmagnetic Zn for Cu, which is contrary to the result in the hole-doped system. Here, we reported the effect of partially substitution of magnetic impurity Fe for Cu to the magnetic and transport properties in electron-doped superconducting cuprates of Eu1.85+yCe0.15-yCu1-yFeyO4+α-δ (ECCFO) with y = 0.01, 0.02, and 0.05, in order to investigate the mechanism of magnetic and transport properties of ECCFO in normal-state. Magnetic properties are investigated by DC magnetic-susceptibility measurements that carried out at low temperatures down to 2 K using a standard SQUID magnetometer in a magnetic field of 5 Oe on field cooling. Transport properties addressed to electron mobility, are extracted from radius of electron localization calculated from temperature dependence of resistivity. For y = 0, temperature dependence of dc magnetic-susceptibility indicated the change of magnetic behavior from paramagnetic to diamagnetic below 15 K. Above 15 K, all samples show paramagnetic behavior with the values of magnetic moment in every volume unit increased with increasing y. Electron mobility decreased with increasing y. Some reasons for these results will be discussed.

Keywords: DC magnetic-susceptibility, electron mobility, Eu1.85+yCe0.15-yCu1-yFeyO4+α-δ, normal state

Procedia PDF Downloads 348

Authors: Nidhal K. Azawi, John M. Gauch

Abstract:

Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 253

Authors: Sanskar, Abhinav Pal, Aryush Gupta, Sushil Kumar Mishra

Abstract:

One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper.

Keywords: plant diseases, machine learning, image processing, deep learning

Procedia PDF Downloads 7

Authors: Lina Jassim, Robiah Yunus, , Amran Salleh

Abstract:

Since nano particles have been assessed as thermo stabilizer, rheology enhancer, and ecology safer, nano drilling fluid can be utilized to overcome the complexity of hole cleaning in highly deviated interval of an extended reach wells. The eccentric annular flow is a flow with special considerations; it forms a vital part of drilling fluid flow analysis in an extended reach wells. In this work eccentric, dual phase flow (different types of rock cuttings with different size were blended with nano fluid) through horizontal well (an extended reach well) are simulated with the help of CFD, Fluent package. In horizontal wells flow occurs in an adverse pressure gradient condition, that makes the particle inside it susceptible to reversed flow. Thus the flow has to be analyzed in a three dimensional manner. Moreover the non-Newtonian behavior of the nano fluid makes the problem really challenging in numerical and physical aspects. The primary objective of the work is to establish a relationship between different flow characteristics with the speed of inner wall rotation. The nano fluid flow characteristics include swirl of flow and its effect on wellbore cleaning ability , wall shear stress and its effect on fluid viscosity to suspend and carry the rock cuttings, axial velocity and its effect on transportation of rock cuttings to the wellbore surface, finally pressure drop and its effect on managed of drilling pressure. The importance of eccentricity of the inner cylinder has to be analyzed as a part of it. Practical horizontal well flows contain a good amount of particles (rock cuttings) with moderate axial velocity, which verified nano drilling fluid ability of carrying and transferring cuttings particles in the highly deviated eccentric annular flow is also of utmost importance.

Keywords: Non-Newtonian, dual phase, eccentric annular, CFD

Procedia PDF Downloads 434

Authors: Razieh Niazmand, Dina Sadat Mousavian, Parvin Sharayei

Abstract:

This study investigated the effect of carboxymethyl cellulose (CMC), tragacanth, and saalab hydrocolloids in two concentrations (0.3%, 0.7%) and different frying media, refined canola oil (RCO), RCO + 1% bene kernel oil (BKO), and RCO + 1 mg/l unsaponifiable matter (USM) of BKO on acrylamide formation in fried potato slices. The hydrocolloid coatings significantly reduced acrylamide formation in potatoes fried in all oils. Increasing the hydrocolloid concentration from 0.3% to 0.7% produced no effective inhibition of acrylamide. The 0.7 % CMC solution was identified as the most promising inhibitor of acrylamide formation in RCO oil, with a 62.9% reduction in acrylamide content. The addition of BKO or USM to RCO led to a noticeable reduction in the acrylamide level in fried potato slices. The findings suggest that a 0.7% CMC solution and RCO+USM are promising inhibitors of acrylamide formation in fried potato products.

Keywords: CMC, frying, potato, saalab, tracaganth

Procedia PDF Downloads 288

Authors: Ulrike Dowie, Ralph Grothmann

Abstract:

Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

Procedia PDF Downloads 189

Authors: Rebecca Pryce, Nijole Bernaitis, Andrew K. Davey, Shailendra Anoopkumar-Dukie

Abstract:

Background: Warfarin is an oral anticoagulant widely used in the prevention of strokes in patients with atrial fibrillation (AF) and in the treatment and prevention of deep vein thrombosis (DVT). Regular monitoring of Internationalised Normalised Ratio (INR) is required to ensure therapeutic benefit with time in therapeutic range (TTR) used to measure warfarin control. A number of factors influence TTR including diet, concurrent illness, and drug interactions. Extensive literature exists regarding the effect of conventional medicines on warfarin control, but documented interactions relating to complementary medicines are limited. It has been postulated that fish oil and krill oil supplementation may affect warfarin due to their association with bleeding events. However, to date little is known as to whether fish and krill oil significantly alter the incidence of bleeding with warfarin or impact on warfarin control. Aim:To assess the influence of fish oil and krill oil supplementation on warfarin control in AF and DVT patients by determining the influence of these supplements on TTR and bleeding events. Methods:A retrospective cohort analysis was conducted utilising patient information from a large private pathology practice in Queensland. AF and DVT patients receiving warfarin management by the pathology practice were identified and their TTR calculated using the Rosendaal method. Concurrent medications were analysed and patients taking no other interacting medicines were identified and divided according to users of fish oil and krill oil supplements and those taking no supplements. Study variables included TTR and the incidence of bleeding with exclusion criteria being less than 30 days of treatment with warfarin. Subject characteristics were reported as the mean and standard deviation for continuous data and number and percentages for nominal or categorical data. Data was analysed using GraphPad InStat Version 3 with a p value of <0.05 considered to be statistically significant. Results:Of the 2081 patients assessed for inclusion into this study, a total of 573 warfarin users met the inclusion criteria. Of these, 416 (72.6%) patients were AF patients and 157 (27.4%) DVT patients and overall there were 316 (55.1%) male and 257 (44.9%) female patients. 145 patients were included in the fish oil/krill oil group (supplement) and 428 were included in the control group. The mean TTR of supplement users was 86.9% and for the control group 84.7% with no significant difference between these groups. Control patients experienced 1.6 times the number of minor bleeds per person compared to supplement patients and 1.2 times the number of major bleeds per person. However, this was not statistically significant nor was the comparison between thrombotic events. Conclusion: No significant difference was found between supplement and control patients in terms of mean TTR, the number of bleeds and thrombotic events. Fish oil and krill oil supplements when used concurrently with warfarin do not significantly affect warfarin control as measured by TTR and bleeding incidence.

Keywords: atrial fibrillation, deep vein thormbosis, fish oil, krill oil, warfarin

Procedia PDF Downloads 304

Authors: Rasha F. Sharaf

Abstract:

Administration of local anesthesia for a child is considered a painful procedure, which affects his vital signs, physiological parameters, and his further attitude in the dental clinic. During the extraction of mandibular molars, the nerve block technique is the most commonly used for the administration of local anesthesia; however, this technique requires deep penetration of the needle, which causes pain and discomfort for the child. Therefore, the inferior alveolar nerve block technique can be substituted with an infiltration technique which is not painful if a potent anesthetic solutions will be used. In the current study, the effect of Articaine 4% will be compared to Mepivacaine 2%, and their influence on the vital signs of the child, as well as their ability to control pain during extraction, will be assessed.

Keywords: anesthesia, articaine, pain control, extraction

Procedia PDF Downloads 122

Authors: Sara Sharifi Yazdi

Abstract:

The main purpose of this study is to find out about the reasons and the ways of middle-class married women betrayal via their living world. This is qualitative research, so deep semi-structured, episodic interview techniques and observation techniques were used to collect data; meanwhile, the basic theory method was used to analyze the data. The sample in this research includes 34 women with emotional and sexual relationships out of marriage. The results indicate that some set of conditions created the first spark of change in their opinions. These changes are empowered through both experiences of tolerance and exclusion, so strategies such as distance, compulsive tolerance, counteract, etc. have been used for reacting by the people in this study; besides some of the other consequences of betrayal which can be named are lack of comfort, feeling of deprivation, violence, labeling, guilty feelings of grief, and so on.

Keywords: living world, rejection, admission, betrayal, sexual relationship, marriage

Procedia PDF Downloads 144

Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

Abstract:

Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

Procedia PDF Downloads 76

Authors: Tamer Shehata

Abstract:

Recently, nanotechnology acquired a great interest in the field of pharmaceutical production. Several pharmaceutical equipment were introduced into the research field for production of nanoparticles, among them, BÜCHI’ fourth generation nano-spray dryer B-90. B-90 is specialized with single step of production and drying of nano and microparticles. Currently, our research group is investigating several pharmaceutical formulations utilizing BÜCHI Nano-Spray Dryer B-90 technology. One of our projects is the formulation and evaluation of metformin hydrochloride mucoadhesive microparticles for treatment of type 2-diabetis. Several polymers were investigated, among them, gelatin and sodium alginate. The previous polymers are natural polymers with mucoadhesive properties. Preformulation studies such as atomization head mesh size, flow rate, head temperature, polymer solution viscosity and surface tension were performed. Postformulation characters such as particle size, flowability, surface scan and dissolution profile were evaluated. Finally, the pharmacological activity of certain selected formula was evaluated in streptozotocin-induced diabetic rats. B-90’spray head was 7 µm hole heated to 120 with air flow rate 3.5 mL/min. The viscosity of the solution was less than 11.5 cP with surface tension less than 70.1 dyne/cm. Successfully, discrete, non-aggregated particles and free flowing powders with particle size was less than 2000 nm were obtained. Gelatin and Sodium alginate combination in ratio 1:3 were successfully sustained the in vitro release profile of the drug. Hypoglycemic evaluation of the previous formula showed a significant reduction of blood glucose level over 24 h. In conclusion, mucoadhesive metformin hydrochloride microparticles obtained from B-90 could offer a convenient dosage form with enhanced hypoglycemic activity.

Keywords: mucoadhesive, microparticles, metformin hydrochloride, nano-spray dryer

Procedia PDF Downloads 311

Authors: Maurice A. Duka, Leobel Von Q. Tamayo, Niño Carlo I. Casim

Abstract:

The paucity of long-term measurements and monitoring of accurate water quality parameter profiles is evident for small and deep tropical lakes in Southeast Asia. This leads to a poor understanding of the stratification and mixing dynamics of these lakes in the region. The water quality dynamics of Sampaloc Lake, a tropical crater lake (104 ha, 27 m deep) in the Philippines, were investigated to understand how monsoon-driven conditions impact water quality and ecological health. Located in an urban area with approximately 10% of its surface area allocated to aquaculture, the lake is subject to distinct seasonal changes associated with the Northeast (NE) and Southwest (SW) monsoons. NE Monsoon typically occurs from October to April, while SW monsoon from May to September. These monsoons influence the lake’s water temperature, dissolved oxygen (DO), chlorophyll-α (chl-α), phycocyanin (PC), and turbidity, leading to significant seasonal variability. Monthly field observations of water quality parameters were made from October 2022 to September 2023 using a multi-parameter probe, YSI ProDSS, together with the collection of meteorological data during the same period. During the NE monsoon, cooler air temperatures and winds with sustained speeds caused surface water temperatures to drop from 30.9 ºC in October to 25.5 ºC in January, resulting in the weakening of stratification and eventually in lake turnover. This turnover redistributed nutrients from hypolimnetic layers to surface layers, increasing chl-α and PC levels (14-41 and 0-2 µg/L) throughout the water column. The fish kill was also observed during the lake’s turnover event as a result of the mixing of hypoxic hypolimnetic waters. Turbidity levels (0-3 NTU) were generally low but showed mid-column peaks in October, which was linked to thermocline-related effects, while low values in November followed heavy rainfall dilution and mixing effects. Conversely, the SW monsoon showed increased surface temperatures (28-30 ºC), shallow thermocline formations (3-11 m), and lower surface chl-α and PC levels (2-8 and 0-0.5 µg/L, respectively), likely due to limited nutrient mixing and more stable stratification. Turbidity was notably higher also in July (11-15 NTU) due to intense rainfall and reduced light penetration, which minimized photosynthetic activity. The SW monsoon also coincided with the typhoon season in the study area, resulting in partial upwelling of nutrients during strong storm events. These findings emphasize the need for continued monitoring of Sampaloc Lake’s seasonal water quality patterns, as monsoon-driven changes are crucial to maintaining its ecological balance and sustainability.

Keywords: seasonal water quality dynamics, Philippine tropical lake, monsoon-driven conditions, stratification and mixing

Procedia PDF Downloads 10

Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

Abstract:

Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

Procedia PDF Downloads 141

Authors: Andreas Aceranti, Riccardo Dossena, Marco Colorato, Simonetta Vernocchi

Abstract:

By the term “limbic resonance,” we usually refer to a state of deep connection, both emotional and physiological, between people who, when in resonance, find their limbic systems in tune with one another. Limbic resonance is not only about sharing emotions but also physiological states. In fact, people in such resonance can influence each other’s heart rate, blood pressure, and breathing. Limbic resonance is fundamental for human beings to connect and create deep bonds among a certain group. It is fundamental for our social skills. A relationship between gifted and resonant subjects is perceived as feeling safe, living the relation like an isle of serenity where it is possible to recharge, to communicate without words, to understand each others without giving explanations, to strengthen the balance of each member of the group. Within the circle, self-esteem is consolidated and makes it stronger to face what is outside, others, and reality. The idea that gifted people who are together may be unfit for the world does not correspond to the truth. The circle made up of people with high cognitive potential characterized by a limbic resonance is, in general, experienced as a solid platform from which you can safely move away and where you can return to recover strength. We studied 8 adults (between 21 and 47 years old). All of them with IQ higher than 130. We monitored their brain waves frequency (alpha, beta, theta, gamma, delta) by means of biosensing tracker along with their physiological states (heart beat frequency, blood pressure, breathing frequency, pO2, pCO2) and some blood works only (5-HT, dopamine, catecholamines, cortisol). The subjects of the study were asked to adhere to a protocol involving bonding activities (such as team building activities), role plays, meditation sessions, and group therapy. All these activities were carried out together. We observed that after about 4 months of activities, their brain waves frequencies tended to tune quicker and quicker. After 9 months, the bond among them was so important that they could “sense” each other inner states and sometimes also guess each others’ thoughts. According to our findings, it may be hypothesized that large synchronized outbursts of cortex neurons produces not only brain waves but also electromagnetic fields that may be able to influence the cortical neurons’ activity of other people’s brain by inducing action potentials in large groups of neurons and this is reasonably conceivable to be able to transmit information such as different emotions and cognition cues to the other’s brain. We also believe that upcoming research should focus on clarifying the role of brain magnetic particles in brain-to-brain communication. We also believe that further investigations should be carried out on the presence and role of cryptochromes to evaluate their potential roles in direct brain-to-brain communication.

Keywords: limbic resonance, psychotherapy, brain waves, emotion regulation, giftedness

Procedia PDF Downloads 92

Authors: Farzaneh Shayeganfar, Ali Ramazani

Abstract:

Exciton (strong electronic interaction of electron-hole) and hot carriers created by surface plasmon polaritons has been demonstrated in nanoscale optoelectronic devices, enhancing the photoresponse of the system. Herein, we employ a quantum framework to consider coupled exciton- hot carriers effects on photovoltaiv energy distribution, scattering process, polarizability and light emission of 2D-semicnductor. We use density functional theory (DFT) to design computationally a semi-functionalized 2D honeycomb silicon boride (SiB) monolayer with H atoms, suitable for photovoltaics. The dynamical stability, electronic and optical properties of SiB and semi-hydrogenated SiB structures were investigated utilizing the Tran-Blaha modified Becke-Johnson (TB-mBJ) potential. The calculated phonon dispersion shows that while an unhydrogenated SiB monolayer is dynamically unstable, surface semi-hydrogenation improves the stability of the structure and leads to a transition from metallic to semiconducting conductivity with a direct band gap of about 1.57 eV, appropriate for photovoltaic applications. The optical conductivity of this H-SiB structure, determined using the random phase approximation (RPA), shows that light adsorption should begin at the boundary of the visible range of light. Additionally, due to hydrogenation, the reflectivity spectrum declines sharply with respect to the unhydrogenated reflectivity spectrum in the IR and visible ranges of light. The energy band gap remains direct, increasing from 0.9 to 1.8 eV, upon increasing the strain from -6% (compressive) to +6% (tensile). Additionally, compressive and tensile strains lead, respectively, to red and blue shifts of optical the conductivity threshold around the visible range of light. Overall, this study suggests that H-SiB monolayers are suitable as two-dimensional solar cell materials.

Keywords: surface plasmon, hot carrier, strain engineering, valley polariton

Procedia PDF Downloads 109

Authors: A. Nabi, S. Panahi

Abstract:

In the recent years, due to the countless changes in the world and various sciences, architecture has faced a new approach and different concepts more than any other times. The direct influence of philosophy on architecture is one of the features of contemporary architecture. Linking these two learnings directly together needs deep reflection. Gilles Deleuze and Félix Guattari are among the people who greatly influenced the thinking of future architects and artists by bringing up new concepts. If we focus on the works of these architects and artists whose works resemble anti-Platonism and who subvert the western philosophy, we can extract concepts which we can see their influence on art and architecture. Using content analysis, this study has come to this conclusion that the ideas of Deleuze and Guattari could influence the contemporary architecture.

Keywords: Gilles Deleuze, Felix Guattari, anti-platonism, post-modern architecture, folding

Procedia PDF Downloads 199

Authors: Dimitrios Tzilopoulos, Panagiotis Symeonidis, Michael Loufakis, Dimosthenis Ioannidis, Dimitrios Tzovaras

Abstract:

The domestic film industry in Greece has traditionally relied heavily on state support. While film productions are crucial for the country's economy, it has not fully capitalized on attracting and promoting foreign productions. The lack of motivation, organized state support for attraction and licensing, and the absence of location scouting have hindered its potential. Although recent legislative changes have addressed the first two of these issues, the development of a comprehensive location database and a search engine that would effectively support location scouting at the pre-production location scouting is still in its early stages. In addition to the expected benefits of the film, television, marketing, and multimedia industries, a location-scouting service platform has the potential to yield significant financial gains locally and nationally. By promoting featured places like cultural and archaeological sites, natural monuments, and attraction points for visitors, it plays a vital role in both cultural promotion and facilitating tourism development. This study introduces LOCATION3, an internet platform revolutionizing film production location management. It interconnects location providers, film crews, and multimedia stakeholders, offering a comprehensive environment for seamless collaboration. The platform's central geodatabase (PostgreSQL) stores each location’s attributes, while web technologies like HTML, JavaScript, CSS, React.js, and Redux power the user-friendly interface. Advanced functionalities, utilizing deep learning models, developed in Python, are integrated via Node.js. Visual data presentation is achieved using the JS Leaflet library, delivering an interactive map experience. LOCATION3 sets a new standard, offering a range of essential features to enhance the management of film production locations. Firstly, it empowers users to effortlessly upload audiovisual material enriched with geospatial and temporal data, such as location coordinates, photographs, videos, 360-degree panoramas, and 3D location models. With the help of cutting-edge deep learning algorithms, the application automatically tags these materials, while users can also manually tag them. Moreover, the application allows users to record locations directly through its user-friendly mobile application. Users can then embark on seamless location searches, employing spatial or descriptive criteria. This intelligent search functionality considers a combination of relevant tags, dominant colors, architectural characteristics, emotional associations, and unique location traits. One of the application's standout features is the ability to explore locations by their visual similarity to other materials, facilitated by a reverse image search. Also, the interactive map serves as both a dynamic display for locations and a versatile filter, adapting to the user's preferences and effortlessly enhancing location searches. To further streamline the process, the application facilitates the creation of location lightboxes, enabling users to efficiently organize and share their content via email. Going above and beyond location management, the platform also provides invaluable liaison, matchmaking, and online marketplace services. This powerful functionality bridges the gap between visual and three-dimensional geospatial material providers, local agencies, film companies, production companies, etc. so that those interested in a specific location can access additional material beyond what is stored on the platform, as well as access production services supporting the functioning and completion of productions in a location (equipment provision, transportation, catering, accommodation, etc.).

Keywords: deep learning models, film industry, geospatial data management, location scouting

Procedia PDF Downloads 71

Authors: Kok Hong Tan, Hing Wah Lee, Jhih-Wei Chen, Chang Fu Dee, Chung-Lin Wu, Siang-Piao Chai, Wei Sea Chang

Abstract:

Semiconductor photocatalyst is known as one of the key roles in developing clean and sustainable energy. However, most of the semiconductor only possesses photoactivity within the UV light region, and hence, decreases the overall photocatalyst efficiency. Generally, the overall effectiveness of the photocatalyst activity is determined by three critical steps: (i) light absorption efficiency and photoexcitation electron-hole pair generation, (ii) separation and migration of charge carriers to the surface of the photocatalyst, and (iii) surface reaction of the carriers with its environment. Much effort has been invested on optimizing hierarchical nanostructures of semiconductors for efficient photoactivity due to the fact that the visible light absorption capability and occurrence of the chemical reactions mostly depend on the dimension of photocatalysts. In this work, we incorporated zero-dimensional (0D) gold nanoparticles (AuNPs) and one dimensional (1D) Zinc Oxide (ZnO) nanorods (NRs) onto strontium titanate (STO) for efficient visible light absorption, charge transfer, and separation. We demonstrate that the electrical and optical properties of the photocatalyst can be tuned by controlling the dimensional structures of AuNPs and ZnO NRs. We found that smaller AuNPs sizes exhibited higher photoactivity because of Fermi level shifting toward the conductive band of STO, STO band gap narrowing and broadening of absorption spectrum to the visible light region. For ZnO NRs, it was found that the average ZnO NRs c-axis length must achieve of certain length to induce multiphoton absorption as a result of light reflection and trapping behavior in the free space between adjacent ZnO NRs hence broadening the absorption spectrum of ZnO from UV to visible light region. This work opens up a new way of broadening the absorption spectrum by incorporating controllable nanostructures of semiconductors, which is important in optimizing the solar water splitting process.

Keywords: gold nanoparticles, photoelectrochemical, PEC, semiconductor photocatalyst, zinc oxide nanorods

Procedia PDF Downloads 161

Authors: Husam Mohammed Saleh Alziyadi

Abstract:

The drilling fluid has a significant impact on drilling efficiency. Drilling fluids have several functions which make them most important within the drilling process, such as lubricating and cooling the drill bit, removing cuttings from down of hole, preventing formation damage, suspending drill bit cuttings, , and also removing permeable formation as a result, the flow of fluid into the formation process is delayed. In the oil and gas sector, unconventional shale reserves have been a central player in meeting world energy demands. Oil-based drilling fluids (OBM) are generally favored for drilling shale plays due to negligible chemical interactions. Nevertheless, the industry has been inspired by strict environmental regulations to design water-based drilling fluids (WBM) capable of regulating shale-water interactions to boost their efficiency. However, traditional additives are too large to plug the micro-fractures and nanopores of the shale. Recently, nanotechnology in the oil and gas industries has shown a lot of promise, especially with drilling fluids based on nanoparticles. Nanotechnology has already made a huge contribution to technical developments in the energy sector. In the drilling industry, nanotechnology can make revolutionary changes. Nanotechnology creates nanomaterials with many attractive properties that can play an important role in improving the consistency of mud cake, reducing friction, preventing differential pipe sticking, preserving the stability of the borehole, protecting reservoirs, and improving the recovery of oil and gas. The selection of suitable nanomaterials should be based on the shale formation characteristics intended for drilling. The size, concentration, and stability of the NPs are three more important considerations. The effects of the environment are highly sensitive to these materials, such as changes in ionic strength, temperature, or pH, all of which occur under downhole conditions. This review paper focused on the previous research and recent development of environmentally friendly drilling fluids according to the regulatory environment and cost challenges.

Keywords: nanotechnology, WBM, Drilling Fluid, nanofluids

Procedia PDF Downloads 125

Authors: Ahmad S. Darwish, Tarek Lemaoui, Hanifa Taher, Inas M. AlNashef, Fawzi Banat

Abstract:

This research reports a systematic top-down approach for designing neoteric hydrophobic solvents –particularly, deep eutectic solvents (DES) and ionic liquids (IL)– as furfural extractants from aqueous media for the application of sustainable biomass conversion. The first stage of the framework entailed screening 32 neoteric solvents to determine their efficacy against toluene as the application’s conventional benchmark for comparison. The selection criteria for the best solvents encompassed not only their efficiency in extracting furfural but also low viscosity and minimal toxicity levels. Additionally, for the DESs, their natural origins, availability, and biodegradability were also taken into account. From the screening pool, two neoteric solvents were selected: thymol:decanoic acid 1:1 (Thy:DecA) and trihexyltetradecyl phosphonium bis(trifluoromethylsulfonyl) imide [P₁₄,₆,₆,₆][NTf₂]. These solvents outperformed the toluene benchmark, achieving efficiencies of 94.1% and 97.1% respectively, compared to toluene’s 81.2%, while also possessing the desired properties. These solvents were then characterized thoroughly in terms of their physical properties, thermal properties, critical properties, and cross-contamination solubilities. The selected neoteric solvents were then extensively tested under various operating conditions, and an exceptional stable performance was exhibited, maintaining high efficiency across a broad range of temperatures (15–100 °C), pH levels (1–13), and furfural concentrations (0.1–2.0 wt%) with a remarkable equilibrium time of only 2 minutes, and most notably, demonstrated high efficiencies even at low solvent-to-feed ratios. The durability of the neoteric solvents was also validated to be stable over multiple extraction-regeneration cycles, with limited leachability to the aqueous phase (≈0.1%). Moreover, the extraction performance of the solvents was then modeled through machine learning, specifically multiple non-linear regression (MNLR) and artificial neural networks (ANN). The models demonstrated high accuracy, indicated by their low absolute average relative deviations with values of 2.74% and 2.28% for Thy:DecA and [P₁₄,₆,₆,₆][NTf₂], respectively, using MNLR, and 0.10% for Thy:DecA and 0.41% for [P₁₄,₆,₆,₆][NTf₂] using ANN, highlighting the significantly enhanced predictive accuracy of the ANN. The neoteric solvents presented herein offer noteworthy advantages over traditional organic solvents, including their high efficiency in both extraction and regeneration processes, their stability and minimal leachability, making them particularly suitable for applications involving aqueous media. Moreover, these solvents are more environmentally friendly, incorporating renewable and sustainable components like thymol and decanoic acid. This exceptional efficacy of the newly developed neoteric solvents signifies a significant advancement, providing a green and sustainable alternative for furfural production from biowaste.

Keywords: sustainable biomass conversion, furfural extraction, ionic liquids, deep eutectic solvents

Procedia PDF Downloads 70

Authors: Chao Yang, Jinchuan Zhang, Yongqiang Xiong

Abstract:

The Lower Cambrian Niutitang Formation shale (NFS) deposited in the marine deep-shelf environment in Southeast Upper Yangtze (SUY), possess excellent source rock basis for shale gas generation, however, it is currently challenged by being over-mature with strong tectonic deformations, leading to much uncertainty of gas-bearing potential. With emphasis on the shale gas enrichment of the NFS, analyses were made based on the regional gas-bearing differences obtained from field gas-desorption testing of 18 geological survey wells across the study area. Results show that the NFS bears low gas content of 0.2-2.5 m³/t, and the eastern region of SUY is higher than the western region in gas content. Moreover, the methane fraction also presents the similar regional differentiation with the western region less than 10 vol.% while the eastern region generally more than 70 vol.%. Through the analysis of geological theory, the following conclusions are drawn: Depositional environment determines the gas-enriching zones. In the western region, the Dengying Formation underlying the NFS in unconformity contact was mainly plateau facies dolomite with caves and thereby bears poor gas-sealing ability. Whereas the Laobao Formation underling the NFS in eastern region was a set of siliceous rocks of shelf-slope facies, which can effectively prevent the shale gas from escaping away from the NFS. The tectonic conditions control the gas-enriching bands in the SUY, which is located in the fold zones formed by the thrust of the Southern China plate towards to the Sichuan Basin. Compared with the western region located in the trough-like folds, the eastern region at the fold-thrust belts was uplifted early and deformed weakly, resulting in the relatively less mature level and relatively slight tectonic deformation of the NFS. Faults determine whether shale gas can be accumulated in large scale. Four deep and large normal faults in the study area cut through the Niutitang Formation to the Sinian strata, directly causing a large spillover of natural gas in the adjacent areas. For the secondary faults developed within the shale formation, the reverse faults generally have a positive influence on the shale accumulation while the normal faults perform the opposite influence. Overall, shale gas enrichment targets of the NFS, are the areas with certain thickness of siliceous rocks at the basement of the Niutitang Formation, and near the margin of the paleouplift with less developed faults. These findings provide direction for shale gas exploration in South China, and also provide references for the areas with similar geological conditions all over the world.

Keywords: over-mature marine shale, shale gas accumulation, structure-complicated area, Southeast Upper Yangtze

Procedia PDF Downloads 147

Authors: Jurijs Salijevs, Katrina Bolocko

Abstract:

The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

Procedia PDF Downloads 103

Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

Abstract:

Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

Procedia PDF Downloads 732

Authors: Ben Levenger

Abstract:

Social life revolves around a central meeting place or gathering space. It is where the community integrates, earns social skills, and ultimately becomes part of the community. Following this premise, public spaces are one of the most important spaces that downtowns offer, providing locations for people to be witnessed, heard, and most importantly, seamlessly integrate into the downtown as part of the community. To facilitate this, these local spaces must be envisioned and designed to meet the changing needs of a downtown, offering a space and purpose for everyone. This paper will dive deep into analyzing, designing, and implementing public space design for small plazas or gathering spaces. These spaces often require a detailed level of study, followed by a broad stroke of design implementation, allowing for adaptability. This paper will highlight how to assess needs, define needed types of spaces, outline a program for spaces, detail elements of design to meet the needs, assess your new space, and plan for change. This study will provide participants with the necessary framework for conducting a grass-roots-level assessment of public space and programming, including short-term and long-term improvements. Participants will also receive assessment tools, sheets, and visual representation diagrams. Urbanism, for the sake of urbanism, is an exercise in aesthetic beauty. An economic improvement or benefit must be attained to solidify these efforts' purpose further and justify the infrastructure or construction costs. We will deep dive into case studies highlighting economic impacts to ground this work in quantitative impacts. These case studies will highlight the financial impact on an area, measuring the following metrics: rental rates (per sq meter), tax revenue generation (sales and property), foot traffic generation, increased property valuations, currency expenditure by tenure, clustered development improvements, cost/valuation benefits of increased density in housing. The economic impact results will be targeted by community size, measuring in three tiers: Sub 10,000 in population, 10,001 to 75,000 in population, and 75,000+ in population. Through this classification breakdown, the participants can gauge the impact in communities similar to their work or for which they are responsible. Finally, a detailed analysis of specific urbanism enhancements, such as plazas, on-street dining, pedestrian malls, etc., will be discussed. Metrics that document the economic impact of each enhancement will be presented, aiding in the prioritization of improvements for each community. All materials, documents, and information will be available to participants via Google Drive. They are welcome to download the data and use it for their purposes.

Keywords: downtown, economic development, planning, strategic

Procedia PDF Downloads 81

Authors: Jaiden X. Schraut

Abstract:

Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

Procedia PDF Downloads 144

Authors: Meilisha Putri Pertiwi, Mufti Petala Patria

Abstract:

Mangrove forest often categorized as a productive ecosystem in trophic water and the highest carbon storage among all the forest types. Mangrove-derived organic matter determines the food web of fish and invertebrates. In Indonesia trophic water ecosystem, 80% commersial fish caught in coastal area are high related to food web in mangrove forest ecosystem. Based on the previous research in Panjang Island, Bojonegara, Banten, Indonesia, removed mangrove litterfall to the sea water were 9,023 g/m³/s for two stations (west station–5,169 g/m³/s and north station-3,854 g/m³/s). The vegetation were dominated from Rhizophora apiculata and Rhizopora stylosa. C element is the highest content (27,303% and 30,373%) than N element (0,427% and 0,35%) and P element (0,19% and 0,143%). The aim of research also to know the diversity of fish inhabit in mangrove forest. Fish sampling is by push net. Fish caught are collected into plastics, total length measured, weigh measured, and individual and total counted. Meanwhile, the 3 modified pipes (1 m long, 5 inches diameter, and a closed one hole part facing the river by using a nylon cloth) set in the water channel connecting mangrove forest and sea water for each stasiun. They placed for 1 hour at low tide. Then calculate the speed of water flow and volume of modified pipes. The fish and mangrove litter will be weigh for wet weight, dry weight, and analyze the C, N, and P element content. The sampling data will be conduct 3 times of month in full moon. The salinity, temperature, turbidity, pH, DO, and the sediment of mangrove forest will be measure too. This research will give information about the fish diversity in mangrove forest, the removed mangrove litterfall to the sea water, the composition of sediment, the total element content (C, N, P) of fish and mangrove litter, and the correlation of element content absorption between fish and mangrove litter. The data will be use for the fish and mangrove ecosystem conservation.

Keywords: fish diversity, mangrove forest, mangrove litter, carbon element, nitrogen element, P element, conservation

Procedia PDF Downloads 485

Authors: Indra Gonzalez Ojeda, Tatiana Quinones, Manuel Rosario, Igor Lednev, Juan Lopez Garriga

Abstract:

Amyloid fibrils are stable aggregates of misfolded protein associated with many neurodegenerative disorders. It has been shown that hydrogen sulfide (H2S), inhibits the fibrillation of lysozyme through the formation of trisulfide (S-S-S) bonds. However, the overall mechanism remains elusive. Here, the concentration dependence of H2S effect was investigated using Atomic force microscopy (AFM), non-resonance Raman spectroscopy, Deep-UV Raman spectroscopy and circular dichroism (CD). It was found that small spherical aggregates with trisulfide bonds and a unique secondary structure were formed instead of amyloid fibrils when adding concentrations of 25 mM and 50 mM of H2S. This could indicate that H2S might serve as a protecting agent for the protein. However, further characterization of these aggregates and their trisulfide bonds is needed to fully unravel the function H2S has on protein fibrillation.

Keywords: amyloid fibrils, hydrogen sulfide, protein folding, raman spectroscopy

Procedia PDF Downloads 216