Search results for: deep oxidation

Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

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Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: Song Qingfeng

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This research aims to seek the relationship between social media usage and overtourism from the perspective of tourists based on the theory of Maslow’s hierarchy needs. A questionnaire is formulated to collect data from 400 tourists who have visited the Hangzhou city in China in the last 12 months. Structural Equation Model (SEM) is employed to analysis data. The finding is that social media usage aggravates overtourism. Specifically, social media is used by tourists to information-seeking, entertainment, self-presentation, and socialization for traveling. These roles of social media would evoke the traveling intention to a specific destination at a certain time, which further influences the tourist flow. When the tourist flow concentrate, the overtourism would be aggravated. This study contributes to the destination managers to deep-understand the cause-effect relationship between social media and overtourism in order to address this problem.

Keywords: social media, overtourism, tourist flow, SEM, Maslow’s hierarchy of needs, Hangzhou

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Authors: Lizhi Ma, Chengcheng Hu, Fuxian Wong

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Partial reduce (P-Reduce) has set a state-of-the-art performance on distributed machine learning in the heterogeneous environment over the All-Reduce architecture. The dynamic P-Reduce based on the exponential moving average (EMA) approach predicts all the intermediate model parameters, which raises unreliability. It is noticed that the approximation trick leads the wrong way to obtaining model parameters in all the nodes. In this paper, SAP-Reduce is proposed, which is a variant of the All-Reduce distributed training model with staleness-aware dynamic P-Reduce. SAP-Reduce directly utilizes the EMA-like algorithm to generate the normalized weights. To demonstrate the effectiveness of the algorithm, the experiments are set based on a number of deep learning models, comparing the single-step training acceleration ratio and convergence time. It is found that SAP-Reduce simplifying dynamic P-Reduce outperforms the intermediate approximation one. The empirical results show SAP-Reduce is 1.3× −2.1× faster than existing baselines.

Keywords: collective communication, decentralized distributed training, machine learning, P-Reduce

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Authors: Divyanka Sontakke, Arpit Thakre, D. K Shinde, Sujata Parmeshwaran

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Electrospinning is the most widely utilized method to create nanofibers because of the direct setup, the capacity to mass-deliver consistent nanofibers from different polymers, and the ability to produce ultrathin fibers with controllable diameters. Smooth and much arranged ultrafine Polyacrylonitrile (PAN) nanofibers with diameters going from submicron to nanometer were delivered utilizing Electrospinning technique. PAN powder was used as a precursor to prepare the solution utilized as a part of this process. At the point when the electrostatic repulsion contradicted surface tension, a charged stream of polymer solution was shot out from the head of the spinneret and along these lines ultrathin nonwoven fibers were created. The effect of electrospinning parameter such as applied voltage, feed rate, concentration of polymer solution and tip to collector distance on the morphology of electrospun PAN nanofibers were investigated. The nanofibers were heat treated for carbonization to examine the changes in properties and composition to make for electrical application. Scanning Electron Microscopy (SEM) was performed before and after carbonization to study electrical conductivity and morphological characterization. The SEM images have shown the uniform fiber diameter and no beads formation. The average diameter of the PAN fiber observed 365nm and 280nm for flat plat and rotating drum collector respectively. The four probe strategy was utilized to inspect the electrical conductivity of the nanofibers and the electrical conductivity is significantly improved with increase in oxidation temperature exposed.

Keywords: electrospinning, polyacrylonitrile carbon nanofibres, heat treatment, electrical conductivity

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Authors: Kais Rtibi, Slimen Selmi, Jamel El-Benna, Lamjed Marzouki, Hichem Sebai

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Background: Myeloperoxidase (MPO) is a hemic enzyme found in high concentrations in the primary neutrophils granules. In addition to its peroxidase activity, it has a chlorination activity, using hydrogen peroxide and chloride ions to form hypochlorous acid, a strong oxidant, capable of chlorinating molecules. Bioactive compounds contained in medicinal plants could limit the action of this enzyme to reduce the reactive oxygen species production and its chlorination activity. The purpose of this study is to evaluate the effect of the carob aqueous extract (CAE) on the release of MPO by human neutrophils in vitro and its activity following stimulation of these cells by PMA. Methods: Neutrophils were isolated by simple sedimentation using the Dextran/Ficoll method. After stimulation with phorbol 12-myristate 13-acetate (PMA), neutrophils release the MPO by degranulation. The effect of CAE on the release of MPO was analyzed by the Western blot technique, while, its activity was determined by biochemical method using the method of 3,3', 5,5'- Tetramethylbenzidine (TMB) and hydrogen peroxide. The data were expressed as mean ± SEM. Results: The carob aqueous extract causes a decrease in MPO quantity and activity in a concentration-dependent manner which leads to a reduction of the production of the ROS (reactive oxygen species) and the protection of the molecules against oxidation and chlorination mechanisms. Conclusion: Thanks to its richness in bioactive compounds, the aqueous extract of carob could limit the development of damages related to the uncontrolled activity of MPO.

Keywords: carob, MPO, myeloperoxidase, neutrophils, PMA, phorbol 12-myristate 13-acetate

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Authors: Shumaila Shakoor

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C. tubulosa is a rare parasitic plant. It is found to be endangered and it acquires nutrition by penetrating roots deep in host roots. It has momentous potential to fulfill local and national health needs. This specie became endangered due to its parasitic mode of life and lack of awareness. Investigation of distribution and habitat conditions of C. tubulosa from District Pakpattan is the objective of this study. To explore its habitat conditions and community ecology phytosociological survey of C. tubulosa in different habitats i.e roadsides and graveyards was carried out. It was found that C. tubulosa occurs successfully in different habitats like graveyards and roadsides with specific neighboring species. Soil analysis was carried out by taking soil samples from seven sites. Soil was analyzed for pH, EC, soil texture, OM, N %age, Ca, Mg, P and K, which shows that soil of C. tubulosa is rich in all these nutrients.

Keywords: organic matter, potassium, phosphorus, magnesium

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Taylor Harris

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Gustilo-anderson grade III tibial fractures are exquisitely difficult injuries to manage as they require extensive soft tissue repair in addition to fracture fixation. These injuries are best managed collaboratively by Orthopedic and Plastic surgeons. While utilizing an Orthoplastics approach has decreased the rates of adverse outcomes in these injuries, there is a large amount of variation in exactly how an Orthoplastics team approaches complex cases such as these. It is sometimes recommended that definitive bone fixation and soft tissue coverage be completed simultaneously in a single-stage manner, but there is a paucity of large scale studies to provide evidence to support this recommendation. It is the aim of this study to report the outcomes of a single-stage "fix-and-flap" approach through a systematic review of the available literature. Hopefully, this better informs an evidence-based Orthoplastics approach to managing open tibial fractures. Systematic review of the literature was performed. Medline and Google Scholar were used and all studies published since 2000, in English were included. 103 studies were initially evaluated for inclusion. Reference lists of all included studies were also examined for potentially eligible studies. Gustilo grade III tibial shaft fractures in adults that were managed with a single-stage Orthoplastics approach were identified and evaluated with regard to outcomes of interest. Exclusion criteria included studies with patients <16 years old, case studies, systemic reviews, meta-analyses. Primary outcomes of interest were the rates of deep infections and rates of limb salvage. Secondary outcomes of interest included time to bone union, rates of non-union, and rates of re-operation. 15 studies were eligible. 11 of these studies reported rates of deep infection as an outcome, with rates ranging from 0.98%-20%. The pooled rate between studies was 7.34%. 7 studies reported rates of limb salvage with a range of 96.25%-100%. The pooled rate of the associated studies was 97.8%. 6 reported rates of non-union with a range of 0%-14%, a pooled rate of 6.6%. 6 reported time to bone union with a range of 24 to 40.3 weeks and a pooled average time of 34.2 weeks, and 4 reported rates of reoperation ranging from 7%-55%, with a pooled rate of 31.1%. A few studies that compared a single stage to a multi stage approach side-by-side unanimously favored the single stage approach. Outcomes of Gustilo grade III open tibial fractures utilizing an Orthoplastics approach that is specifically done in a single-stage produce low rates of adverse outcomes. Large scale studies of Orthoplastic collaboration that were not completed in strictly a single stage, or were completed in multiple stages, have not reported as favorable outcomes. We recommend that not only should Orthopedic surgeons and Plastic surgeons collaborate in the management of severe open tibial fracture, but they should plan to undergo definitive fixation and coverage in a single-stage for improved outcomes.

Keywords: orthoplastic, gustilo grade iii, single-stage, trauma, systematic review

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Authors: David Guillermo Piedrahita Marquez, Hector Suarez Mahecha, Jairo Humberto Lopez

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There is a need to preserve aquaculture matrices due to their high nutritional value, and its broad consumption, one of those species is the white cachama (Piaractus brachypomus), this fish is located in the rivers of eastern Colombia, and the previously mentioned species needs more study. Therefore, in a paper the effects of an alternative method of preservation of shell life were investigated, the method used is the application of an edible coating made from chitosan and ethanolic extract of propolis (EEP) encapsulated in maltodextrin. The coating was applied by immersion, and after that, we investigated the post mortem quality changes of the fish performing physicochemical and microbiological analysis. pH, volatile bases, test thiobarbituric acid and peroxide value were tested; finally, we studied the effect of the coating on mesophilic strains, coliforms and other microorganisms such as Staphylococcus, and Salmonella. Finally, we concluded that the coating prolongs the shelf life because it acts as a barrier to oxygen and moisture, the bioactive compounds trap free radicals and the coatings changes the metabolism and cause the cell lysis of the microorganisms. It was determined that the concentration of malonaldehyde, the volatile basic nitrogen content and pH are the variables that distinguish more clearly between the samples with the treatment and the control samples.

Keywords: antimicrobial activity, lipid oxidation, texture profile analysis (TPA), sensorial analysis, peroxide value, thiobarbituric acid assay (TBA), total volatile basic nitrogen (TVB-N)

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Authors: K. Krishna Milan Rao, Nelvin Joseph, Praveen Dwarakanath

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Augmented and Virtual Realties is quickly becoming a hotbed of activity with millions of dollars being spent on R & D and companies such as Google and Microsoft rushing to stake their claim. Augmented reality (AR) is however marching ahead due to the spread of the ideal AR device – the smartphone. Despite its potential, there remains a deep digital divide between the Developed and Developing Countries. The Technological Acceptance Model (TAM) and Hofstede cultural dimensions also predict the behaviour intention to uptake AR in India will be large. This paper takes a quantified approach by collecting 340 survey responses to AR scenarios and analyzing them through statistics. The Survey responses show that the Intention to Use, Perceived Usefulness and Perceived Enjoyment dimensions are high among the urban population in India. This along with the exponential smartphone indicates that India is on the cusp of a boom in the AR sector.

Keywords: mobile augmented reality, technology acceptance model, Hofstede, cultural dimensions, India

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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

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

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Sadhana Agrawal, Tarkeshwari Verma, Shmbhavi Katyayan

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The magnificently accentuating phenomenon of luminescence has gathered a lot of attentions from last few decades. Probably defined as the one involving emission of light from certain kinds of substances on absorbing various energies in the form of external stimulus, the phenomenon claims a versatile pertinence. First observed and reported in an extract of Ligrium Nephriticum by Monards, the phenomenon involves turning of crystal clear water into colorful fluid when comes in contact with the special wood. In words of Sir G.G. Stokes, the phenomenon actually involves three different techniques – absorption, excitation and emission. With variance in external stimulus, the corresponding luminescence phenomenon is obtained. Here, this paper gives a concise discussion of thermoluminescence which is one of the types of luminescence obtained when the external stimulus is given in form of heat energy. A deep insight of thermoluminescence put forward a qualitative analysis of various parameters such as glow curves peaks, trap depth, frequency factors and order of kinetics.

Keywords: frequency factor, glow curve peaks, thermoluminescence, trap depth

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Authors: Zohreh Fallah, Edward P. L. Roberts

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One of the big challenges for produced water treatment is removing oil from water in the form of emulsified droplets which are not easily separated. An attractive approach is adsorption, as it is a simple and effective process. However, adsorbents must be regenerated in order to make the process cost effective. Several sorbents have been tested for treating oily wastewater. However, some issues such as high energy consumption for activated carbon thermal regeneration have been reported. Due to their significant electrical conductivity, Graphite Intercalation Compounds (GIC) were found to be suitable to be regenerated electrochemically. They are non-porous materials with low surface area and fast adsorptive capacity which are useful for removal of low concentration of organics. An innovative adsorption/regeneration process has been developed at the University of Manchester in which adsorption of organics are done by using a patented GIC adsorbent coupled with subsequent electrochemical regeneration. The oxidation of adsorbed organics enables 100% regeneration so that the adsorbent can be reused over multiple adsorption cycles. GIC adsorbents are capable of removing a wide range of organics and pollutants; however, no comparable report is available for removal of emulsified oil in produced water using abovementioned process. In this study the performance of this technology for the removal of emulsified oil in wastewater was evaluated. Batch experiments were carried out to determine the adsorption kinetics and equilibrium isotherm for both real produced water and model emulsions. The amount of oil in wastewater was measured by using the toluene extraction/fluorescence analysis before and after adsorption and electrochemical regeneration cycles. It was found that oil in water emulsion could be successfully treated by the treatment process and More than 70% of oil was removed.

Keywords: adsorption, electrochemical regeneration, emulsified oil, produced water

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Authors: Abhinav Sirvaiya, Karan Gupta, Pankaj Garg

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The global warming due to the increased atmospheric carbon dioxide (CO2) concentration is the most prominent issue of environment that the world is facing today. To solve this problem at global level, sequestration of CO2 in deep and unmineable coal seams has come out as one of the attractive alternatives to reduce concentration in atmosphere. This sequestration technology is not only going to help in storage of CO2 beneath the sub-surface but is also playing a major role in enhancing the coal bed methane recovery (ECBM) by displacing the adsorbed methane. This paper provides the answers for the need of CO2 injection in coal seams and how recovery is enhanced. We have discussed the recent development in enhancing the coal bed methane recovery and the economic scenario of the same. The effect of injection on the coal reservoir has also been discussed. Coal is a good absorber of CO2. That is why the sequestration of CO2 is emerged out to be a great approach, not only for storage purpose but also for enhancing coal bed methane recovery.

Keywords: global warming, carbon dioxide (CO2), CO2 sequestration, enhance coal bed methane (ECBM)

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Authors: Zhang Lei, Zhao Qingrong, Wang Chen, Zhang Sufang, Zhang Hanguo

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Larch is the main afforestation and timber tree species in Northeast China, and drought is one of the main factors limiting the growth of Larch and other organisms in Northeast China. In order to further explore the mechanism of Larch drought resistance, PEG was used to simulate drought stress. The full-length sequencing of Larch embryogenic callus under PEG simulated drought stress was carried out by combining Illumina-Hiseq and SMRT-seq. A total of 20.3Gb clean reads and 786492 CCS reads were obtained from the second and third generation sequencing. The de-redundant transcript sequences were predicted by lncRNA, 2083 lncRNAs were obtained, and the target genes were predicted, and a total of 2712 target genes were obtained. The de-redundant transcripts were further screened, and 1654 differentially expressed genes (DEGs )were obtained. Among them, different DEGs respond to drought stress in different ways, such as oxidation-reduction process, starch and sucrose metabolism, plant hormone pathway, carbon metabolism, lignin catabolic/biosynthetic process and so on. This study provides basic full-length sequencing data for the study of Larch drought resistance, and excavates a large number of DEGs in response to drought stress, which helps us to further understand the function of Larch drought resistance genes and provides a reference for in-depth analysis of the molecular mechanism of Larch drought resistance.

Keywords: larch, drought stress, full-length transcriptome sequencing, differentially expressed genes

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Authors: Alex Soares Castro, Matheus Manoel Teles de Menezes, Larissa Silva de Azevedo, Ana Carolina Caleffi Patelli, Osmair Vital de Oliveira, Aline Thais Bruni, Marcelo Firmino de Oliveira

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Considering the problem of the seizure of illicit drugs, as well as the development of electrochemical sensors using chemically modified electrodes, this work shows the study of the electrochemical activity of cocaine in carbon paste electrode chemically modified with Cu (II) trans 3-MeO salcn complex. In this context, cyclic voltammetry was performed on 0.1 mol.L⁻¹ KCl supporting electrolyte at a scan speed of 100 mV s⁻¹, using an electrochemical cell composed of three electrodes: Ag /AgCl electrode (filled KCl 3 mol.L⁻¹) from Metrohm® (reference electrode); a platinum spiral electrode, as an auxiliary electrode, and a carbon paste electrode chemically modified with Cu (II) trans 3-MeO complex (as working electrode). Two forms of cocaine were analyzed: cocaine hydrochloride (pH 3) and cocaine free base form (pH 8). The PM7 computational method predicted that the hydrochloride form is more stable than the free base form of cocaine, so with cyclic voltammetry, we found electrochemical signal only for cocaine in the form of hydrochloride, with an anodic peak at 1.10 V, with a linearity range between 2 and 20 μmol L⁻¹ had LD and LQ of 2.39 and 7.26x10-5 mol L⁻¹, respectively. The study also proved that cocaine is adsorbed on the surface of the working electrode, where through an irreversible process, where only anode peaks are observed, we have the oxidation of cocaine, which occurs in the hydrophilic region due to the loss of two electrons. The mechanism of this reaction was confirmed by the ab-inito quantum method.

Keywords: ab-initio computational method, analytical method, cocaine, Schiff base complex, voltammetry

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

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Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

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Authors: Jasna M. Čanadanović-Brunet, Gordana S. Ćetković, Jelena J. Vulić, Sonja M. Djilas, Vesna T. Tumbas Šaponjac, Sladjana M. Stajčić

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Honey serves as a source of natural antioxidants, which are effective in reducing the risk of heart disease, cancer, immune-system decline, cataracts, different inflammatory processes, and also prevent deteriorative oxidation reactions in foods such as enzymatic browning of fruit and vegetables. Honey is a natural saturated sugar solution, but it also contains certain minor constituents, proteins, enzymes, amino and organic acids, lipids, vitamins, phenolic acids, flavonoids and carotenoids. It is consumed in its natural form alone, but also in combination with nuts and various kinds of dried fruits. The aim of this research was to investigate the contribution of dried cherry on phenols (TPh) and flavonoids (Fl) contents and antioxidant activities of honey. Phenolic compounds in Serbian polyfloral (PH), linden (LH) and acacia (AH) honey and also in their mixtures with dried cherry, in 40% mass concentrations (PH40; LH40, AH40), were determined. In comparison to honey, TPh increased 2.25 times for LH40, 2.16 times for AH40 and 1.45 times for PH40, while Fl increased 2.81-fold for PH40, 1.21-fold for LH40 and 1.44-fold for AH40. Antioxidant activity was investigated with two assays, DPPH test and reducing power (RP), and expressed as EC50DPPH and RP0.5 values. The EC50DPPH values were: EC50PH40 = 1.16 mg/ml; EC50LH40= 1.42 mg/ml and EC50AH40= 1.69 mg/ml, while RP0.5 were: RP0.5PH40 = 15.05 mg/ml; RP0.5LH40 = 16.09 mg/ml and P0.5AH40 = 17.60 mg/ml. Our results indicate that supplementation of polyfloral, linden and acacia honey with 40% dried cherry improves antioxidant activity of honey by enriching the phenolic composition.

Keywords: antioxidant activity, dried cherry, honey, phenolics

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Authors: S. Divya, M. Jose

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Over the past years, industrial dyes have emerged as a significant threat to aquatic life, extensively detected in drinking water and groundwater, thus contributing to water pollution due to their improper and excessive use. To address this issue, the utilization of core-shell structures has been prioritized as it demonstrates remarkable efficiency in utilizing light energy for catalytic reactions and exhibiting excellent photocatalytic activity despite the availability of various photocatalysts. This work focuses on the photocatalytic degradation of Nd₂O₃@SiO₂ CSNs under UV light irradiation against MB and RhB dyes. Different characterization techniques, including XRD, FTIR, and TEM analyses, were employed to reveal the material's structure, functional groups, and morphological features. VSM and XPS analyses confirmed the soft, paramagnetic nature and chemical states with respective atomic percentages, respectively. Optical band gaps, determined using the Tauc plot model, indicated 4.24 eV and 4.13 eV for Nd₂O₃ NPs and Nd₂O₃@SiO₂ CSNs, respectively. The reduced bandgap energy of Nd₂O₃@SiO₂ CSNs enhances light absorption in the UV range, potentially leading to improved photocatalytic efficiency. The Nd₂O₃@SiO₂ CSNs exhibited greater degradation efficiency, reaching 95% and 96% against MB and RhB dyes, while Nd₂O₃ NPs showed 90% and 92%, respectively. The enhanced efficiency of Nd₂O₃@SiO₂ CSNs can be attributed to the larger specific surface area provided by the SiO₂ shell, as confirmed by surface area analysis using the BET surface area analyzer through N₂ adsorption-desorption.

Keywords: core shell nanocomposites, rare earth oxides, photocatalysis, advanced oxidation process

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Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Djarot B. Darmadi

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The wider growing Finite Element Method (FEM) application is caused by its benefits of cost saving and environment friendly. Also, by using FEM a deep understanding of certain phenomenon can be achieved. This paper observed the role of material properties and volumetric change when Solid State Phase Transformation (SSPT) takes place in residual stress formation due to a welding process of ferritic steels through coupled Thermo-Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by experiment. From parametric study of the FEM model, it can be concluded that the material properties change tend to over-predicts residual stress in the weld center whilst volumetric change tend to underestimates it. The best final result is the compromise of both by incorporates them in the model which has a better result compared to a model without SSPT.

Keywords: residual stress, ferritic steels, SSPT, coupled-TMM

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Authors: J. Sánchez-Beaskoetxea

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The analysis of accidents, such as marine accidents, is one of the most useful instruments to avoid future accidents. In the case of marine accidents, from a simple collision of a small boat in a port to the wreck of a gigantic tanker ship, the study of the causes of the accidents is the basis of a great part of the marine international legislation. Some countries have official institutions who investigate all the accidents in which a ship with their flag is involved. In the case of the USA, the National Transportation Safety Board (NTSB) is responsible for these researches. The NTSB, after a deep investigation into each accident, publishes a Marine Accident Report with the possible cause of the accident. This paper analyses all the Marine Accident Reports published by the NTBS and focuses its attention especially in the Human Errors that led to reported accidents. In this research, the different Human Errors made by crew members are cataloged in 10 different groups. After a complete analysis of all the reports, the statistical analysis on the Human Errors typology in marine accidents is presented in order to use it as a tool to avoid the same errors in the future.

Keywords: human error, marine accidents, ship crew, USA

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Authors: Shamini Dhana, G. Subrahmanya VRK Rao

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The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

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Authors: Praveen Kumar, R. Uma, R. P. Sharma

Abstract:

This study investigates the generation of turbulence in a deep-fluid environment using a damped 1D-modified nonlinear Schrödinger equation model. The well-known damped modified nonlinear Schrödinger equation (d-MNLS) is solved using numerical methods. Artificial damping is added to the MNLS equation, and turbulence generation is investigated through a numerical simulation. The numerical simulation employs a finite difference method for temporal evolution and a pseudo-spectral approach to characterize spatial patterns. The results reveal a recurring periodic pattern in both space and time when the nonlinear Schrödinger equation is considered. Additionally, the study shows that the modified nonlinear Schrödinger equation disrupts the localization of structure and the recurrence of the Fermi-Pasta-Ulam (FPU) phenomenon. The energy spectrum exhibits a power-law behavior, closely following Kolmogorov's spectra steeper than k⁻⁵/³ in the inertial sub-range.

Keywords: water waves, modulation instability, hydrodynamics, nonlinear Schrödinger's equation

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Authors: Zhengrong Wu, Haibo Yang

Abstract:

In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

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Authors: Ezra Yehuwalashet, Alireza Malehmir

Abstract:

Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Brahim El Fadil

Abstract:

The nature of science as a solution (NOS) to life problems is well established in school activities the world over. However, this study reveals the lack of representation of the NOS in science textbooks used in Quebec Province. A content analysis method was adopted to analyze the NOS in relation to optics knowledge and teaching-learning activities in Grade 9 science and technology textbooks and Grade 11 physics textbooks. The selected textbooks were approved and authorized by the Provincial Ministry of Education. Our analysis points out that most of these editions provided a poor representation of NOS. None of them indicates that scientific knowledge is subject to change, even though the history of optics reveals evolutionary and revolutionary changes. Moreover, the analysis shows that textbooks place little emphasis on the discussion of scientific laws and theories. Few of them argue that scientific inquiries are required to gain a deep understanding of scientific concepts. Moreover, they rarely present empirical evidence to support their arguments.

Keywords: nature of science, history of optics, geometrical theory of optics, wave theory of optics

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Authors: Shyhrete Morina

Abstract:

This paper deals with morphological features in Mjeda's works. To make such a distinction, these features will be compared to standard Albanian language, considering the linguistic structure in the morphological field, which represent an all-important segment of Albanian language. Therefore, the study will focus mainly on the description and construction of these paradigms, which will give a linguistic insight into the entire work of Mjeda as the author who wrote in the dialect of northwestern Geg. Therefore, we have tried to distinguish different parts of the author's language, as well as the distinctive features or even the similarities of these paradigms that arise in the literary work of Mjeda. By constructing the corpus of this phonetic and grammar segment from the whole of Mjeda's work, we have seen that in these fields has built a variety of grammar structures, which for the history of Albanian are of special importance, that in the full variant of the work, as far as we can investigate, we will point out in all the distinctive features. Therefore, our study aims to highlight the linguistic features, namely the author's deep knowledge toward the language, the authenticity of its use, and its mutual relationship with it.

Keywords: distinctive morpholgy, nouns, adjetives, pronouns, Albanian standard language

Procedia PDF Downloads 153