Search results for: flavonoid fluorescence sensor

Authors: Zhaoxu Lu, Yufeng Ma, Linying Gao, Li Wang, Mei Qiang

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Mercury (Hg) is a well-recognized environmental pollutant known by its toxicity of development and neurotoxicity, which may result in adverse health outcomes. However, the mechanisms underlying the teratogenic effects of Hg are not well understood. Imprinting genes are emerging regulators for fetal development subject to environmental pollutants impacts. In this study, we examined the association between paternal preconception Hg exposures and the alteration of DNA methylation of imprinting genes in human sperm DNA. A total of 618 men aged from 22 to 59 was recruited from the Reproductive Medicine Clinic of Maternal and Child Care Service Center and the Urologic Surgery Clinic of Shanxi Academy of Medical Sciences during April 2015 and March 2016. Demographic information was collected using questionnaires. Urinary Hg concentrations were measured using a fully-automatic double-channel hydride generation atomic fluorescence spectrometer. And methylation status in the DMRs of imprinting genes H19, Meg3 and Peg3 of sperm DNA were examined by bisulfite pyrosequencing in 243 participants. Spearman’s rank and multivariate regression analysis were used for correlation analysis between sperm DNA methylation status of imprinting genes and urinary Hg levels. The median concentration of Hg for participants overall was 9.09μg/l (IQR: 5.54 - 12.52μg/l; range = 0 - 71.35μg/l); no significant difference was found in median concentrations of Hg among various demographic groups (p > 0.05). The proportion of samples that a beyond intoxication criterion (10μg/l) for urinary Hg was 42.6%. Spearman’s rank correlation analysis indicates a negative correlation between urinary Hg concentrations and average DNA methylation levels in the DMRs of imprinted genes H19 (rs=﹣0.330, p = 0.000). However, there was no such a correlation found in genes of Peg3 and Meg3. Further, we analyzed of correlation between methylation level at each CpG site of H19 and Hg level, the results showed that three out of 7 CpG sites on H19 DMR, namely CpG2 (rs =﹣0.138, p = 0.031), CpG4 (rs =﹣0.369, p = 0.000) and CpG6 (rs=﹣0.228, p = 0.000), demonstrated a significant negative correlation between methylation levels and the levels of urinary Hg. After adjusting age, smoking, drinking, intake of aquatic products and education by multivariate regression analysis, the results have shown a similar correlation. In summary, mercury nonoccupational environmental exposure in reproductive-aged men associated with altered DNA methylation outcomes at DMR of imprinting gene H19 in sperm, implicating the susceptibility of the developing sperm for environmental insults.

Keywords: epigenetics, genomic imprinting gene, DNA methylation, mercury, transgenerational effects, sperm

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Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles

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The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.

Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite

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Authors: Wann-Yun Shieh, Hsin-Yi Kathy Cheng, Yan-Ying Ju, Yu-Chun Yu, Ya-Cheng Shieh

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Adolescents who have intellectual disabilities often demonstrate maladaptive behaviors in their daily activities due to either physical abnormalities or neurological disorders. These adolescents commonly struggle with their cognition and movement coordination when it comes to executing tasks such as throwing or catching objects smoothly, quickly, and gracefully, in contrast to their typically developing peers. Simply measuring movement time and distance doesn't provide a comprehensive view of their performance challenges. In this study, a ball-playing approach was proposed to assess the cognition and movement coordination of adolescents with intellectual disabilities using a smart ball equipped with an embedded inertial sensor. Four distinct ball games were specifically designed for this smart ball: two focusing on lower limb activities (dribbling along a straight line and navigating a zigzag path) and two centered around upper limb tasks (picking up and throwing and catching the ball). The cognition and movement coordination of 25 adolescents with intellectual disabilities (average age 18.36 ± 2.46 years) with that of 25 typically developing adolescents (average age 18.36 ± 0.49 years) were compared in these four tests. The results clearly revealed significant differences in the cognition and movement coordination between the adolescents with intellectual disabilities and the typically developing adolescents. These differences encompassed aspects such as movement speed, hand-eye coordination, and control over objects across all the tests conducted.

Keywords: cognition, intellectual disabilities, movement coordination, smart ball

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Authors: Temesgen Geremew

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ZnS/glass and CdS/glass single layers and ZnS/CdS and CdS/ZnS heterojunction thin films were deposited by the chemical bath deposition method using zinc acetate and cadmium acetate as the metal ion sources and thioacetamide as a nonmetallic ion source in acidic medium. Na2EDTA was used as a complexing agent to control the free cation concentration. +e single layer and heterojunction thin films were characterized with X-ray diffraction (XRD), a scanning electron microscope (SEM), energy dispersive X-ray (EDX), and a UV-VIS spectrometer. +e XRD patterns of the CdS/glass thin film deposited on the soda lime glass substrate crystalized in the cubic structure with a single peak along the (111) plane. +e ZnS/CdS heterojunction and ZnS/glass single layer thin films were crystalized in the hexagonal ZnS structure. +e CdS/ZnS heterojunction thin film is nearly amorphous.The optical analysis results confirmed single band gap values of 2.75 eV and 2.5 eV for ZnS/CdS and CdS/ZnS heterojunction thin films, respectively. +e CdS/glass and CdS/ZnS thin films have more imaginary dielectric components than the real part. The optical conductivity of the single layer and heterojunction films is in the order of 1015 1/s. +e optical study also confirmed refractive index values between 2 and 2.7 for ZnS/glass, ZnS/CdS, and CdS/ZnS thin films for incident photon energies between 1.2 eV and 3.8 eV. +e surface morphology studies revealed compacted spherical grains covering the substrate surfaces with few cracks on ZnS/glass, ZnS/CdS, and CdS/glass and voids on CdS/ZnS thin films. +e EDX result confirmed nearly 1 :1 metallic to nonmetallic ion ratio in the single-layered thin films and the dominance of Zn ion over Cd ion in both ZnS/CdS and CdS/ZnS heterojunction thin films.

Keywords: SERS, sensor, Hg2+, water detection, polythiophene

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Astrid Tannert, Anuradha Ramoji, Christina Ebert, Frederike Gladigau, Lorena Tuchscherr, Jürgen Popp, Ute Neugebauer

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Staphylococcus aureus is a facultative intracellular pathogen, which by entering host cells may evade immunologic host response as well as antimicrobial treatment. In that way, S. aureus can cause persistent intracellular infections which are difficult to treat. Depending on the strain, S. aureus may persist at different intracellular locations like the phagolysosome. The first barrier invading pathogens from the blood stream that they have to cross are the endothelial cells lining the inner surface of blood and lymphatic vessels. Upon proceeding from an acute to a chronic infection, intracellular pathogens undergo certain biochemical and structural changes including a deceleration of metabolic processes to adopt for long-term intracellular survival and the development of a special phenotype designated as small colony variant. In this study, the endothelial cell line Ea.hy 926 was used as a model for acute and chronic S. aureus infection. To this end, Ea.hy 926 cells were cultured on QIAscout™ Microraft Arrays, a special graded cell culture substrate that contains around 12,000 microrafts of 200 µm edge length. After attachment to the substrate, the endothelial cells were infected with GFP-expressing S. aureus for 3 weeks. The acute infection and the development of persistent bacteria was followed by confocal laser scanning microscopy, scanning the whole Microraft Array for the presence and for detailed determination of the intracellular location of fluorescent intracellular bacteria every second day. After three weeks of infection representative microrafts containing infected cells, cells with protruded infections and cells that did never show any infection were isolated and fixed for Raman micro-spectroscopic investigation. For comparison, also microrafts with acute infection were isolated. The acquired Raman spectra are correlated with the fluorescence microscopic images to give hints about a) the molecular alterations in endothelial cells during acute and chronic infection compared to non-infected cells, and b) metabolic and structural changes within the pathogen when entering a mode of persistence within host cells. We thank Dr. Ruth Kläver from QIAGEN GmbH for her support regarding QIAscout technology. Financial support by the BMBF via the CSCC (FKZ 01EO1502) and from the DFG via the Jena Biophotonic and Imaging Laboratory (JBIL, FKZ PO 633/29-1, BA 1601/10-1) is highly acknowledged.

Keywords: correlative image analysis, intracellular infection, pathogen-host adaption, Raman micro-spectroscopy

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Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

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This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

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The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

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Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

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Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

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Authors: Nishanth Venugopal Menon, Chuah Yon Jin, Samantha Phey, Wu Yingnan, Zhang Ying, Vincent Chan, Kang Yuejun

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Cell Migration is a vital phenomenon that the cells undergo in various physiological processes like wound healing, disease progression, embryogenesis, etc. Cell migration depends primarily on the chemical and physical cues available in the cellular environment. The chemical cue involves the chemokines secreted and gradients generated in the environment while physical cues indicate the impact of matrix properties like nanotopography and stiffness on the cells. Mesenchymal Stem Cells (MSCs) have been shown to have a role wound healing in vivo and its migration to the site of the wound has been shown to have a therapeutic effect. In the field of stem cell based tissue regeneration of bones and cartilage, one approach has been to introduce scaffold laden with MSCs into the site of injury to enable tissue regeneration. In this work, we have studied the combinatorial impact of the substrate physical properties on MSC migration. A microfluidic in vitro model was created to perform the migration studies. The microfluidic model used is a three compartment device consisting of two cell seeding compartments and one migration compartment. Four different PDMS substrates with varying substrate roughness, stiffness and hydrophobicity were created. Its surface roughness and stiffness was measured using Atomic Force Microscopy (AFM) while its hydrphobicity was measured from the water contact angle using an optical tensiometer. These PDMS substrates are sealed to the microfluidic chip following which the MSCs are seeded and the cell migration is studied over the period of a week. Cell migration was quantified using fluorescence imaging of the cytoskeleton (F-actin) to find out the area covered by the cells inside the migration compartment. The impact of adhesion proteins on cell migration was also quantified using a real-time polymerase chain reaction (qRT PCR). These results suggested that the optimal substrate for cell migration would be one with an intermediate level of roughness, stiffness and hydrophobicity. A higher or lower value of these properties affected cell migration negatively. These observations have helped us in understanding that different substrate properties need to be considered in tandem, especially while designing scaffolds for tissue regeneration as cell migration is normally impacted by the combinatorial impact of the matrix. These observations may lead us to scaffold optimization in future tissue regeneration applications.

Keywords: cell migration, microfluidics, in vitro model, stem cell migration, scaffold, substrate properties

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Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

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Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

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Authors: Gurjeet Singh, Rabindra K. Panda

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Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

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Authors: Elenice Maria Schons Silva, Andre Carlos Silva

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The crescent demand for raw material has increased mining activities. Mineral industry faces the challenge of process more complexes ores, with very small particles and low grade, together with constant pressure to reduce production costs and environment impacts. Froth flotation deserves special attention among the concentration methods for mineral processing. Besides its great selectivity for different minerals, flotation is a high efficient method to process fine particles. The process is based on the minerals surficial physicochemical properties and the separation is only possible with the aid of chemicals such as collectors, frothers, modifiers, and depressants. In order to use sustainable and eco-friendly reagents, oils extracted from three different vegetable species (pequi’s pulp, macauba’s nut and pulp, and Jatropha curcas) were studied and tested as apatite collectors. Since the oils are not soluble in water, an alkaline hydrolysis (or saponification), was necessary before their contact with the minerals. The saponification was performed at room temperature. The tests with the new collectors were carried out at pH 9 and Flotigam 5806, a synthetic mix of fatty acids industrially adopted as apatite collector manufactured by Clariant, was used as benchmark. In order to find a feasible replacement for cornstarch the flour and starch of a graniferous variety of sorghum was tested as depressant. Apatite samples were used in the flotation tests. XRF (X-ray fluorescence), XRD (X-ray diffraction), and SEM/EDS (Scanning Electron Microscopy with Energy Dispersive Spectroscopy) were used to characterize the apatite samples. Zeta potential measurements were performed in the pH range from 3.5 to 12.5. A commercial cornstarch was used as depressant benchmark. Four depressants dosages and pH values were tested. A statistical test was used to verify the pH, dosage, and starch type influence on the minerals recoveries. For dosages equal or higher than 7.5 mg/L, pequi oil recovered almost all apatite particles. In one hand, macauba’s pulp oil showed excellent results for all dosages, with more than 90% of apatite recovery, but in the other hand, with the nut oil, the higher recovery found was around 84%. Jatropha curcas oil was the second best oil tested and more than 90% of the apatite particles were recovered for the dosage of 7.5 mg/L. Regarding the depressant, the lower apatite recovery with sorghum starch were found for a dosage of 1,200 g/t and pH 11, resulting in a recovery of 1.99%. The apatite recovery for the same conditions as 1.40% for sorghum flour (approximately 30% lower). When comparing with cornstarch at the same conditions sorghum flour produced an apatite recovery 91% lower.

Keywords: collectors, depressants, flotation, mineral processing

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Authors: Andrei Bejan, Luminita Marin, Dalila Belei

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Phenothiazine with electron-rich nitrogen and sulfur heteroatoms has a high electron-donating ability which promotes a good conjugation and therefore low band-gap with consequences upon charge carrier mobility improving and shifting of light emission in visible domain. Moreover, its non-planar butterfly conformation inhibits molecular aggregation and thus preserves quite well the fluorescence quantum yield in solid state compared to solution. Therefore phenothiazine and its derivatives are promising hole transport materials for use in organic electronic and optoelectronic devices as light emitting diodes, photovoltaic cells, integrated circuit sensors or driving circuits for large area display devices. The objective of this paper was to obtain a series of new phenothiazine derivatives by introduction of different electron withdrawing substituents as formyl, carboxyl and cyanoacryl units in order to create a push pull system which has potential to improve the electronic and optical properties. Bromine atom was used as electrono-donor moiety to extend furthermore the existing conjugation. The understudy compounds were structural characterized by FTIR and 1H-NMR spectroscopy and single crystal X-ray diffraction. Besides, the single crystal X-ray diffraction brought information regarding the supramolecular architecture of the compounds. Photophysical properties were monitored by UV-vis and photoluminescence spectroscopy, while the electrochemical behavior was established by cyclic voltammetry. The absorption maxima of the studied compounds vary in a large range (322-455 nm), reflecting the different electronic delocalization degree, depending by the substituent nature. In a similar manner, the emission spectra reveal different color of emitted light, a red shift being evident for the groups with higher electron withdrawing ability. The emitted light is pure and saturated for the compounds containing strong withdrawing formyl or cyanoacryl units and reach the highest quantum yield of 71% for the compound containing bromine and cyanoacrilic units. Electrochemical study show reversible oxidative and reduction processes for all the compounds and a close correlation of the HOMO-LUMO band gap with substituent nature. All these findings suggest the obtained compounds as promising materials for optoelectronic devices.

Keywords: electrochemical properties, phenothiazine derivatives, photoluminescence, quantum yield

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Authors: Yan-Shiang Chiou, Yi-Huang Hsueh

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Bacillus cereus is a foodborne pathogen that causes two types of foodborne illness, the emetic and diarrheal syndromes. B. cereus consistently ranks among the top three among bacterial foodborne outbreaks in the ten years of 2001 to 2010 in Taiwan. Foodborne outbreak caused by B. cereus has been increased, and recently it ranks second foodborne pathogen after Vibrio parahaemolyticus. This pathogen is difficult to control due to its ubiquitousness in the environment, the psychrotrophic nature of many strains, and the heat resistance of their spores. Because complete elimination of biofilms is difficult, a better understanding of the molecular mechanisms of biofilm formation by B. cereus will help to develop better strategies to control this pathogen. Surface translocation can be an important factor in biofilm formation. In B. cereus, NprR is a quorum sensor, and its apo NprR is a dimer and changes to a tetramer in the presence of NprX. The small peptide NprX may induce conformational change allowing the apo dimer to switch to an active tetramer specifically recognizing target DNA sequences. Our result showed that mutation of nprRX causes surface spreading deficiency. Mutation of flagella, pili and surfactant genes (flgAB, bcpAB, krsABC), did not abolish spreading motility. Under nprRX mutant, mutation of spo0A restored the spreading deficiency. This suggests that spreading motility is not related surfactant, pili and flagella but other unknown mechanism and Spo0A, a sporulation initiation protein, inhibits spreading motility.

Keywords: Bacillus cereus, nprRX, spo0A, spreading motility

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Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

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Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Daniel R. McDougall, Martin D. de Jonge, Gordon M. Miskelly, Duncan J. McGillivray, Andrew G. Jeffs

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The chelating agent ethylenediaminetetraacetic acid (EDTA) is commonly added as a cure-all to seawater in aquaculture hatcheries around the world to reduce heavy metal toxicity, significantly improve the survival of larval shellfish, and to therefore improve the overall production efficiency of the aquaculture industry. However, EDTA is not a biodegradable chemical and is considered to be a persistent organic pollutant, which will accumulate in the environment over time. This makes the use of EDTA unsustainable environmentally, and therefore alternatives should be considered. Ethylenediaminedisuccinic acid (EDDS) is a biodegradable alternative to EDTA with very similar metal chelation properties. This study investigates the effect of EDTA and EDDS at two different concentrations, on metal concentrations found within developing New Zealand green-lipped mussel (Perna canaliculus) larvae. P. canaliculus is New Zealand’s main shellfish aquaculture species, providing a major export for New Zealand’s economy, with excellent potential for increased production in the near future. It is well known that the early stages of bivalve development are the most vulnerable to metal toxicity and P. canaliculus is no exception. The commercially used concentration (12 µmol L⁻¹) of EDTA added to P. canaliculus larval rearing tanks often increases the yield of D-larvae by over 80%. This concentration of EDTA and EDDS will be tested in this study, along with a lower concentration (3 µmol L⁻¹). After 48 hours of larval development, the D-larvae will be analyzed for heavy metal content with Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and heavy metal distribution with synchrotron X-ray Fluorescence Microscopy (XFM). In this study, we found that EDDS also improves the yield of P. canaliculus larvae and could be a viable alternative to EDTA in aquaculture. Furthermore, results suggest a higher concentration of chelating agent is more effective for improving the yield of developing P. canaliculus larvae. Metals with significant differences in concentration with the addition of EDTA were Cr, Cu, Zn, Cd and Pb (P < 0.05). We observed for the first time to the author’s best knowledge, metal distribution within 100 µm P. canaliculus D-larvae using synchrotron XFM and found changes in the distribution of metals with the addition of EDTA. XFM also has the potential to provide information about the chemical state of the metals within mussel larvae. This research provides greater insight into the reasons for the effectiveness of adding the chelating agent to aquaculture culture water, and a more environmentally conscious alternative to the currently used EDTA, which could be extremely valuable for the aquaculture industry.

Keywords: EDDS, EDTA, heavy metals, P. canaliculus, toxicity, water treatment

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Authors: Zohreh Derikvand

Abstract:

One new 2D metal-organic coordination polymer of Ni(II) namely [Ni2(ndc)2(DMSO)4(H2O)]n, where ndc = naphthalene-1,4-dicarboxylic acid and DMSO= dimethyl sulfoxide has been synthesized and characterized by elemental analysis, spectral (IR, UV-Vis), thermal (TG/DTG) analysis and single crystal X-ray diffraction. Compound 1 possesses a 2D layer structure constructed from dinuclear nickel(II) building blocks in which two crystallographically independent Ni2+ ions are bridged by ndc2– ligands and water molecule. The ndc2– ligands adopt μ3 bridging modes, linking the metal centers into a two-dimensional coordination framework. The two independent NiII cations are surrounded by dimethyl sulfoxide and naphthalene-1,4-dicarboxylate molecules in distorted octahedron geometry. In the crystal structures of 1 there are non-classical hydrogen bonding arrangements and C-H–π stacking interactions. Electrochemical behavior of [Ni2(ndc)2(DMSO)4(H2O)]n, (Ni-NDA) on the surface of carbon nanotube (CNTs) glassy carbon electrode (GCE) was described. The surface structure and composition of the sensor were characterized by scanning electron microscopy (SEM). Oxidation of fructose on the surface of modified electrode was investigated with cyclic voltammetry and electrochemical impedance spectroscopy (EIS) and the results showed that the Ni-NDA/CNTs film displays excellent electrochemical catalytic activities towards fructose oxidation.

Keywords: naphthalene-1, 4-dicarboxylic acid, crystal structure, coordination polymer, electrocatalysis, impedance spectroscopy

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Authors: Zeyu Zhou, Xiaojun Bi

Abstract:

Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Auday Al-Mayyahi, Phil Birch, William Wang

Abstract:

A vision system-based navigation for autonomous ground vehicle (AGV) equipped with a single camera in an indoor environment is presented. A proposed navigation algorithm has been utilized to detect obstacles represented by coloured mini- cones placed in different positions inside a corridor. For the recognition of the relative position and orientation of the AGV to the coloured mini cones, the features of the corridor structure are extracted using a single camera vision system. The relative position, the offset distance and steering angle of the AGV from the coloured mini-cones are derived from the simple corridor geometry to obtain a mapped environment in real world coordinates. The corridor is first captured as an image using the single camera. Hence, image processing functions are then performed to identify the existence of the cones within the environment. Using a bounding box surrounding each cone allows to identify the locations of cones in a pixel coordinate system. Thus, by matching the mapped and pixel coordinates using a projection transformation matrix, the real offset distances between the camera and obstacles are obtained. Real time experiments in an indoor environment are carried out with a wheeled AGV in order to demonstrate the validity and the effectiveness of the proposed algorithm.

Keywords: autonomous ground vehicle, navigation, obstacle avoidance, vision system, single camera, image processing, ultrasonic sensor

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Authors: Huixia Shi, Can Hu, Jun Zhu, Hongling Guo, Haiyan Li, Hongyan Du

Abstract:

The identification of human body fluids during forensic investigations is a critical step to determine key details, and present strong evidence to testify criminal in a case. With the popularity of DNA and improved detection technology, the potential question must be revolved that whether the suspect’s DNA derived from saliva or semen, menstrual or peripheral blood, how to identify the red substance or aged blood traces on the spot is blood; How to determine who contribute the right one in mixed stains. In recent years, molecular approaches have been developing increasingly on mRNA, miRNA, DNA methylation and microbial markers, but appear expensive, time-consuming, and destructive disadvantages. Physicochemical methods are utilized frequently such us scanning electron microscopy/energy spectroscopy and X-ray fluorescence and so on, but results only showing one or two characteristics of body fluid itself and that out of working in unknown or mixed body fluid stains. This paper focuses on using chemistry methods Raman spectroscopy and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to discriminate species of peripheral blood, menstrual blood, semen, saliva, vaginal secretions, urine or sweat. Firstly, non-destructive, confirmatory, convenient and fast Raman spectroscopy method combined with more accurate matrix-assisted laser desorption/ionization time-of-flight mass spectrometry method can totally distinguish one from other body fluids. Secondly, 11 spectral signatures and specific metabolic molecules have been obtained by analysis results after 70 samples detected. Thirdly, Raman results showed peripheral and menstrual blood, saliva and vaginal have highly similar spectroscopic features. Advanced statistical analysis of the multiple Raman spectra must be requested to classify one to another. On the other hand, it seems that the lactic acid can differentiate peripheral and menstrual blood detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, but that is not a specific metabolic molecule, more sensitivity ones will be analyzed in a forward study. These results demonstrate the great potential of the developed chemistry methods for forensic applications, although more work is needed for method validation.

Keywords: body fluids, identification, Raman spectroscopy, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

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Authors: Xinwen Zhu, Xingguang Li, Sun Yi

Abstract:

Crack is one of the most common damages in buildings, bridges, roads and so on, which may pose safety hazards. However, cracks frequently happen in structures of various materials. Traditional methods of manual detection and measurement, which are known as subjective, time-consuming, and labor-intensive, are gradually unable to meet the needs of modern development. In addition, crack detection and measurement need be safe considering space limitations and danger. Intelligent crack detection has become necessary research. In this paper, an efficient method for crack detection and quantification using a 3D sensor, LiDAR, and depth camera is proposed. This method works even in a dark environment, which is usual in real-world applications. The LiDAR rapidly spins to scan the surrounding environment and discover cracks through lasers thousands of times per second, providing a rich, 3D point cloud in real-time. The LiDAR provides quite accurate depth information. The precision of the distance of each point can be determined within around  ±3 cm accuracy, and not only it is good for getting a precise distance, but it also allows us to see far of over 100m going with the top range models. But the accuracy is still large for some high precision structures of material. To make the depth of crack is much more accurate, the depth camera is in need. The cracks are scanned by the depth camera at the same time. Finally, all data from LiDAR and Depth cameras are analyzed, and the size of the cracks can be quantified successfully. The comparison shows that the minimum and mean absolute percentage error between measured and calculated width are about 2.22% and 6.27%, respectively. The experiments and results are presented in this paper.

Keywords: LiDAR, depth camera, real-time, detection and measurement

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

Abstract:

Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

Abstract:

In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

Procedia PDF Downloads 275

Authors: Itti Bist, Snehasis Bhakta, Di Jiang, Tia E. Keyes, Aaron Martin, Robert J. Forster, James F. Rusling

Abstract:

DNA damage from metabolites of lipophilic drugs and pollutants, generated by enzymes, represents a major toxicity pathway in humans. These metabolites can react with DNA to form either 8-oxo-7,8-dihydro-2-deoxyguanosine (8-oxodG), which is the oxidative product of DNA or covalent DNA adducts, both of which are genotoxic and hence considered important biomarkers to detect cancer in humans. Therefore, detecting reactions of metabolites with DNA is an effective approach for the safety assessment of new chemicals and drugs. Here we describe a novel electrochemiluminescent (ECL) sensor array which can detect DNA oxidation and chemical DNA damage in a single array, facilitating a more accurate diagnostic tool for genotoxicity screening. Layer-by-layer assembly of DNA and enzyme are assembled on the pyrolytic graphite array which is housed in a microfluidic device for sequential detection of two type of the DNA damages. Multiple enzyme reactions are run on test compounds using the array, generating toxic metabolites in situ. These metabolites react with DNA in the films to cause DNA oxidation and chemical DNA damage which are detected by ECL generating osmium compound and ruthenium polymer, respectively. The method is further validated by the formation of 8-oxodG and DNA adduct using similar films of DNA/enzyme on magnetic bead biocolloid reactors, hydrolyzing the DNA, and analyzing by liquid chromatography-mass spectrometry (LC-MS). Hence, this combined DNA/enzyme array/LC-MS approach can efficiently explore metabolic genotoxic pathways for drugs and environmental chemicals.

Keywords: biosensor, electrochemiluminescence, DNA damage, microfluidic array

Procedia PDF Downloads 368

Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

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In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

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Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

Abstract:

Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: Chandra Shekhar Majumder, Orin Sultana Jamie

Abstract:

Background: Dacryocystorhinostomy (DCR) has been a widely accepted surgical intervention for nasolacrimal duct obstructions. Some previous studies demonstrated the potential benefits of the peroperative application of agents like Mitomycin-C (MMC) with DCR to improve surgical outcomes. Relevant studies are rare in Bangladesh, and there are controversies about the dose, duration of MMC, and outcome. Therefore, the present study aimed to investigate the comparative efficacy of DCR with and without MMC in a tertiary hospital in Bangladesh. Objective: The study aims to determine the outcome of a dacryocystorhinostomy with preoperative local use of mitomycin–C. Methods: An analytical study was conducted in the Department of Ophthalmology, Sir Salimullah Medical College & Mitford Hospital, Dhaka, from January 2023 to September 2023. Seventy patients who were admitted for DCR operation were included according to the inclusion and exclusion criteria. Patients were divided into two groups: those who underwent DCR with peroperative administration of 0.2 mg/ml Mitomycin-C for 5 minutes (Group I) and those who underwent DCR alone (Group II). All patients were subjected to detailed history taking, clinical examination, and relevant investigations. All patients underwent DCR according to standard guidelines and ensured the highest peroperative and postoperative care. Then, patients were followed up at 7th POD, 1-month POD, 3 months POD, and 6 months POD to observe the success rate between the two groups by assessing tearing condition, irrigation, height of tear meniscus, and FDDT- test. Data was recorded using a pre-structured questionnaire, and collected data were analyzed using SPSS 23. Results: The mean age of the study patients was 42.17±6.7 (SD) years and 42.29±7.1 (SD) years in Groups I and II, respectively, with no significant difference (p=0.945). At the 6th month’s follow-up, group I patients were observed with 94.3% frequency of symptom-free, 85.6% patency of lacrimal drainage system, 68.6% had tear meniscus <0.1mm and 88.6% had positive Fluorescence Dye Disappearance Test (FDDT test). In group II, 91.4% were symptom-free, 68.6% showed patency, 57.1% had a height of tear meniscus < 0.1 mm, and 85.6% had FDDT test positive. But no statistically significant difference was observed (p<.05). Conclusion: The use of Mitomycin-C preoperatively during DCR offers better postoperative outcomes, particularly in maintaining patency and achieving symptom resolution with more FDDT test positive and improvement of tear meniscus in the MMC group than the control group. However, this study didn’t demonstrate a statistically significant difference between the two groups. Further research with larger sample sizes and longer follow-up periods would be beneficial to corroborate these findings.

Keywords: dacryocystorhinostomy, mitomycin-c, dacryocystitis, nasolacrimal duct obstruction

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Authors: Samhani Ismail, Tahamina Begum, Faruque Reza, Zamzuri Idris, Hafizan Juahir, Jafri Malin Abdullah

Abstract:

Holy Quran, a rhymed prosed scripture has a complete literary structure that exemplifies the peak of literary beauty. Memorizing of its verses could enhance one’s memory capacity and cognition while those who are listening to its recitation it is also believed that the Holy Quran alter brainwave producing neuronal excitation engaging with cognitive processes. 28 normal healthy subjects (male =14 & female = 14) were recruited and EEG recording was done using 128-electrode sensor net (Electrical Geosics, Inc.) with the impedance of ≤ 50kΩ. They listened to Sura Fatiha recited by Sheikh Qari Abdul Basit bin Abdus Samad. Arabic news and no sound were chosen as positive and negative control, respectively. The waveform was analysed by Fast Fourier Transform (FFT) to get the power in frequency bands. Bilateral frontal (F7, F8) and temporal region (T7, T8) showed decreased power significantly in alpha wave band in respondent stimulated by Sura Fatihah recitation reflects acoustic attention processing. However, decreased in alpha power in selective attention to memorized, and in familial but not memorized language, reveals the memorial processing in long-term memory. As a conclusion, Quranic recitation relates both cognitive element of memory and language in its listeners and memorizers.

Keywords: auditory stimulation, cognition, EEG, linguistic, memory, Quranic recitation

Procedia PDF Downloads 342