Purpose Of Application Research Articles

Application of FWM-Based OFC for DWDM Optical Communication System with Embedded FBG Sensor Network

Abstract Four-wave mixing optical frequency comb fibre-based setups (FWM-OFCs) have the potential to improve the combined dense wavelength division multiplexed passive optical network (DWDM-PON) and fibre Bragg grating (FBG) temperature sensors network providing easier application, broader technological opportunities for network development, and energy efficiency by substituting a power-demanding laser array. In this research, OFCs are generated for the purpose of combined network application of DWDM-PON and FBG optical sensors. The paper also investigates compatibility scenarios with OFCs in such systems. The mathematical simulation model has been developed and the performance of FWM-OFC based 8-channel 50 GHz spaced non-return-to-zero on-off keying (NRZ-OOK) modulated DWDM-PON transmission system, operating at 50 km single-mode fibre (SMF) with a bit rate of at least 10 Gbps embedded with 7 FBG optical temperature sensors, has been studied. As it is shown, FWM application results in OFC source that has fluctuations of the individual comb tones of less than 3 dB in power, and with an extinction ratio of about 33 dB for operation range of 192.9–193.25 THz, acting as a unified light source for all the data transmission channels. Embedded FBG optical sensors network causes negligible 0.3 dB power penalty.

Analysis study of the carbon monoxide sensor for vehicle safety system application

Carbon monoxide sensor is used to detect the presence of carbon monoxide. In this study, carbon monoxide detection system was developed for the purpose of vehicle safety system application. Factors that were investigated in the simulation study includes the design of circuit, carbon monoxide detection performance and the output design that will not affect the driver performance. Buzzer and motors were added in the circuit design and the simulations were done using Proteus and Tinkercad software. Both software showed a good performance in the detection of carbon monoxide. In the case of high carbon monoxide environment, buzzer was activated to alert the people inside the car and motor automatically rolled down the windows to let the outside air into the vehicle and reduce the carbon monoxide.

An Embedded Convolutional Neural Network for Maze Classification and Navigation

Traditionally, the maze solving robots employ ultrasonic sensors to detect the maze walls around the robot. The robot is able to transverse along the maze omnidirectionally measured depth. However, this approach only perceives the presence of the objects without recognizing the type of these objects. Therefore, computer vision has become more popular for classification purpose in robot applications. In this study, a maze solving robot is equipped with a camera to recognize the types of obstacles in a maze. The types of obstacles are classified as: intersection, dead end, T junction, finish zone, start zone, straight path, T–junction, left turn, and right turn. Convolutional neural network, consisting of four convolution layers, three pooling layers, and three fully-connected layers, is employed to train the robot using a total of 24,000 images to recognize the obstacles. Jetson Nano development kit is used to implement the trained model and navigate the robot. The results show an average training accuracy of 82% with a training time of 30 minutes 15 seconds. As for the testing, the lowest accuracy is 90% for the T-junction with the computational time being 500 milliseconds for each frame. Therefore, the convolutional neural network is adequate to serve as classifier and navigate a maze solving robot.

STUDY COMPANION

The Study Companion Android Application is a comprehensive mobile platform designed to enhance the study experience for students and individuals preparing for academic and competitive exams. The application provides a user-friendly interface that allows users to easily download and upload notes related to their academic subjects and competitive exams. By centralizing study materials in one convenient location, the application simplifies the process of accessing and organizing study materials. The application offers various modules tailored to the specific needs of users. The Home Page module presents two options: "Academic" and "Competitive," allowing users to navigate between their academic subjects and competitive exam materials effortlessly. The My Info module provides a personalized space for users to manage their profile information and track their progress. To ensure a secure and efficient user experience, the application incorporates a Log-in and Register page module, where users can create accounts and securely access their personal information and uploaded notes. Additionally, an Admin module is connected to Firebase, enabling administrators to manage user accounts and handle backend operations effectively. The About module serves as a comprehensive resource, offering an app description and contact information for user support. Users can gain a clear understanding of the application's purpose and easily reach out for assistance or feedback. The Study Companion Android Application employs a robust system architecture, utilizing Firebase for seamless data storage, retrieval, and synchronization. The application has undergone rigorous testing, including unit testing, integration testing, and acceptance testing, to ensure functionality, performance, security, and usability. With its user-centric design, reliable architecture, and efficient functionalities, the Study Companion Android Application aims to provide a seamless and enriching study experience for users. By offering a centralized platform for downloading and uploading study materials, the application empowers users in their academic and competitive exam preparations, promoting knowledge sharing, collaboration, and effective learning.

Mechanical, dielectric, and microwave absorption properties of rGO nanosheets and ZnO filled ZnAl2O4 composites with broad bandwidth and strong absorption

Reduced graphene oxide (rGO) nanosheets and ZnO filled ZnAl2O4 composites (rGO/ZnO/ZnAl2O4 composites) were fabricated by hot-pressing sintering process in-situ reactions for the purpose of microwave absorption applications. The effects of ZnO and rGO content on the mechanical, dielectric and microwave absorption properties were systemically investigated. The results show that the porosity and microhardness increase with increasing the absorbent content, while the flexural strength presents an opposite trend. In addition, the dielectric properties present an overall increase trend with increasing the absorbent content. Because of the favorable impedance matching and the optimal microwave attenuation, the rGO/ZnO/ZnAl2O4 composite with 1 vol% rGO and 8 vol% ZnO demonstrates minimum reflection loss of –44.5 dB at 10.1 GHz and effective absorption bandwidth of 3.8 GHz in 8.2–11.8 GHz and 12.2–12.4 GHz as the thickness is 2.2 mm. The synergistic effects of interfacial polarization, dipole polarization, conductance loss, and multiple scattering result in the outstanding microwave absorption properties for the investigated rGO/ZnO/ZnAl2O4 composite, which indicates their potential candidates for the microwave absorbing materials with broad bandwidth and strong absorption.

Impacts of Clinker Storages Heat Transfer, Its Effect on Vertical Roller Cement Performances: A Case Study of Cement Grinding Operations in Nigeria

Operational data indicates that vertical roller cement mills (VRCM) consumed lesser energy when compared to horizontal/ball mills. A case study of a vertical roller cement mills was carried out in Nigeria which was experiencing a lower production output and a higher energy consumption. This research was to investigate reasons behind the low production output on the VRCM. A thorough analysis was carried out on the clinker storage facilities and the heat transfer across the composite cylindrical clinker silo walls (off – spec and main clinker) both silos having the same design but with different dimensions and with different application purpose. The off-spec clinker silo has a design capacity of 1,800 tons and main clinker silo a design capacity of 60, 000 tons and both silo stores hot clinker that left the kiln clinker cooler at approximate temperature of 95oC. The analytical results shows that the rate of heat transfer across the main clinker composite walls was 728 kW and the rate of heat transfer across the off-spec clinker composite walls was 217.15 kW. Numerical simulation was also carried out using ANSYS simulation package and the results obtained were in good agreement with the results obtained theoretically. The ratio of heat loss on the main clinker composite walls to off-spec clinker composite walls was 3.35:1.

Airborne sound transmission loss of ship bulkheads: A new methodological approach for in-laboratory assessment by including low frequencies

Current standard laboratory measurements of sound transmission loss properties of ship bulkheads at low frequencies, below 100 Hz, are not accurate enough due to the non-diffuse acoustic field of typical laboratory volumes. However, what has been recently observed in non-diffuse field conditions is the transmission of source modes into the receiving room through the partition. On the basis of this, in this paper, a novel procedure to determine the laboratory airborne sound transmission loss properties of ship bulkheads at low frequencies through the airborne modal sound transmission loss is investigated. It is defined as the difference between the average sound pressure levels of source room modes peaks that occur in both source and receiving rooms. A correction method is proposed to suppress the influence of natural receiving room modes. Normalization terms related to receiving room volume and modal damping are introduced, and an envelope method is applied to extend the results in third octave bands. Measurements on five different ship bulkheads show that the standard transmission loss in the low frequency range provides unlikely results, whereas the proposed descriptor follows the expected theoretical curve. This evidence confirms the validity of the proposed method, at least for comparison purposes in marine applications.

From accurate genome sequence to biotechnological application: The thermophile Mycolicibacterium hassiacum as experimental model.

Mycobacteria constitute a large group of microorganisms belonging to the phylum Actinobacteria encompassing some of the most relevant pathogenic bacteria and many saprophytic isolates that share a unique and complex cell envelope. Also unique to this group is the extensive capability to use and synthesize sterols, a class of molecules that include active signalling compounds of pharmaceutical use. However, few mycobacterial species and strains have been established as laboratory models to date, Mycolicibacterium smegmatis mc2 155 being the most common one. In this work, we focus on the use of a thermophilic mycobacterium, Mycolicibacterium hassiacum, which grows optimally above 50°C, as an emerging experimental model valid to extend our general knowledge of mycobacterial biology as well as for application purposes. To that end, accurate genomic sequences are key for gene mining, the study of pathogenicity or lack thereof and the potential for gene transfer. The combination of long- and short-massive sequencing technologies is strictly necessary to remove biases caused by errors specific to long-reads technology. By doing so in M. hassiacum, we obtained from the curated genome clues regarding the genetic manipulation potential of this microorganism from the presence of insertion sequences, CRISPR-Cas, type VII ESX secretion systems, as well as lack of plasmids. Finally, as a proof of concept of the applicability of M. hassiacum as a laboratory and industrial model, we used this high-quality genome of M. hassiacum to successfully knockout a gene involved in the use of phytosterols as source of carbon and energy, using an improved gene cassette for thermostable selection and a transformation protocol at high temperature.

ANALYSIS OF RFID-TAGGING TECHNOLOGY APPLICATION IN THE OIL AND GAS INDUSTRY

In the oil and gas industry, one of the key tasks is to assess the current state of pipelines and equipment. Most of the existing methods used to assess depreciation are narrowly focused and expensive, for example, flaw detection of downhole equipment, tubing, rod and pumping equipment, which can eventually reach the cost of the equipment itself. To date, one of the main methods for assessing the equipment state is the analysis of its operation time, which directly depends on the identification accuracy. Various technological solutions are used as an identifier, for example, barcodes, seals with technical information, however, such controls are unreliable, wear out quickly, and, as a result, it becomes difficult to correctly identify them.
 The paper considers the technology of radio frequency identification (RFID) – «RFID-tags», describes the operation principle and its features. The basic scheme of the tags, conditions and purposes of application in the oil and gas field industry and, in particular, in the pipeline transport. The cases of technology implementation by different foreign and domestic companies are described, and some ways of their potential development are indicated. The analysis of technical solutions is given, the advantages achieved in the implementation of RFID systems are compiled.
 The key and promising factors for the use of this technology in pipeline transport are the possibility of minimizing risks in case of accidents and oil spills, minimizing environmental disasters for both organizations and the environment, since the cost of equipping RFID tags and RFID reading equipment can be insignificant in comparison equivalent.

Biosynthesis and Genome Mining Potentials of Nucleoside Natural Products.

Nucleoside natural products show diverse biological activities and serve as leads for various application purposes, including human and veterinary medicine and agriculture. Studies in the past decade revealed that these nucleosides are biosynthesized through divergent mechanisms, in which early steps of the pathways can be classified into two types (C5' oxidation and C5' radical extension), while the structural diversity is created by downstream tailoring enzymes. Based on this biosynthetic logic, we investigated the genome mining discovery potentials of these nucleosides using the two enzymes representing the two types of C5' modifications: LipL-type α-ketoglutarate (α-KG) and Fe-dependent oxygenases and NikJ-type radical S-adenosyl-L-methionine (SAM) enzymes. The results suggest that this approach allows discovery of putative nucleoside biosynthetic gene clusters (BGCs) and the prediction of the core nucleoside structures. The results also revealed the distribution of these pathways in nature and implied the possibility of future genome mining discovery of novel nucleoside natural products.

Characterization and in-depth genome analysis of a halotolerant probiotic bacterium Paenibacillus sp. S-12, a multifarious bacterium isolated from Rauvolfia serpentina

BackgroundMembers of Paenibacillus genus from diverse habitats have attracted great attention due to their multifarious properties. Considering that members of this genus are mostly free-living in soil, we characterized the genome of a halotolerant environmental isolate belonging to the genus Paenibacillus. The genome mining unravelled the presence of CAZymes, probiotic, and stress-protected genes that suggested strain S-12 for industrial and agricultural purposes.ResultsMolecular identification by 16 S rRNA gene sequencing showed its closest match to other Paenibacillus species. The complete genome size of S-12 was 5.69 Mb, with a GC-content 46.5%. The genome analysis of S-12 unravelled the presence of an open reading frame (ORF) encoding the functions related to environmental stress tolerance, adhesion processes, multidrug efflux systems, and heavy metal resistance. Genome annotation identified the various genes for chemotaxis, flagellar motility, and biofilm production, illustrating its strong colonization ability.ConclusionThe current findings provides the in-depth investigation of a probiotic Paenibacillus bacterium that possessed various genome features that enable the bacterium to survive under diverse conditions. The strain shows the strong ability for probiotic application purposes.

Applying Appreciative Education to Undergraduate Music Therapy Supervision

Abstract Music therapy is by nature an interdisciplinary profession, focusing on the triangulation of the client, the therapist, and the music. This complex relationship creates the necessity for specialized supervision practices. As part of the training for this profession, it is required that students are supervised by board-certified music therapists during practicum placements. Music therapy supervision has incorporated theories grounded in the field of psychology to inform supervision practices. However, recent work in the field suggests Appreciative Education theory may be a more useful approach for supervision. Appreciative education is “a framework that provides an intentional and positive approach to bettering educational enterprises by focusing on the strengths and potential of individuals and organizations to accomplish co-created goals” (Bloom, J., Hutson, B., He, Y., & Konkle, E. 2013). Appreciative education. New Directions for Student Services, 143, 5–6). This paper discusses examples of the appreciative education approach and how to best integrate these practices within the context of undergraduate music therapy supervision. For this article, the primary approach discussed will be the 6D framework developed (Bloom, J. L., Hutson, B. L., & He, Y. (2008). The appreciative advising revolution. Stipes Publishing). The purpose of this practical application is for music therapy supervisors to integrate this framework into their supervisory practices.

Automated Detection and Scoring of Tumor-Infiltrating Lymphocytes in Breast Cancer Histopathology Slides.

Detection of tumor-infiltrating lymphocytes (TILs) in cancer images has gained significant importance as these lymphocytes can be used as a biomarker in cancer detection and treatment procedures. Our goal was to develop and apply a TILs detection tool that utilizes deep learning models, following two sequential steps. First, based on the guidelines from the International Immuno-Oncology Biomarker Working Group (IIOBWG) on Breast Cancer, we labeled 63 large pathology imaging slides and annotated the TILs in the stroma area to create the dataset required for model development. In the second step, various machine learning models were employed and trained to detect the stroma where U-Net deep learning structure was able to achieve 98% accuracy. After detecting the stroma area, a Mask R-CNN model was employed for the TILs detection task. The R-CNN model detected the TILs in various images and was used as the backbone analysis network for the GUI development of the TILs detection tool. This is the first study to combine two deep learning models for TILs detection at the cellular level in breast tumor histopathology slides. Our novel approach can be applied to scoring TILs in large cancer slides. Statistical analysis showed that the output of the implemented approach had 95% concordance with the scores assigned by the pathologists, with a p-value of 0.045 (n = 63). This demonstrated that the results from the developed software were statistically meaningful and highly accurate. The implemented approach in analyzing whole tumor histology slides and the newly developed TILs detection tool can be used for research purposes in biomedical and pathology applications and it can provide researchers and clinicians with the TIL score for various input images. Future research using additional breast cancer slides from various sources for further training and validation of the developed models is necessary for more inclusive, rigorous, and robust clinical applications.

Surrogate-assisted high-accuracy observation modeling in building digital twins: In situ nonintrusive modeling without sensor observation (Y)

Observation and prediction models play important roles in intelligent building systems in terms of holistic monitoring and optimal control. These models overcome the limitations of physical sensors and contribute to organizing the building sensing environment into a more informative arrangement. However, developing an in-situ prediction model for real systems is challenging, as the target sensor observation (Y) is absent. Although physics-based white-box modeling is possible, the model observations have operational uncertainties in a real system. Therefore, this study proposes a novel and integrated framework for a nonintrusive high-accuracy observation modeling method including (1) white-box modeling, (2) indirect-nonintrusive calibration, and (3) surrogate-based uncertainty reduction. In contrast to the conventional application purpose of a surrogate model, the proposed method adopts surrogate modeling to reduce the model uncertainty and provide high accuracy. The proposed method is applied to a real building system to evaluate the accuracy of each modeling step in the proposed framework. The initial white-box model shows an error of 0.81 °C, indirect-nonintrusive calibration improves the accuracy with an error of 0.55 °C, and the surrogate-assisted model reaches an error of 0.27 °C. Notably, 51% of sensor errors are decreased through surrogate modeling.

Exact κ–μ Sum Statistics

Sums of random variables are the statistical core in several performance analyses of communications systems. In this paper, we provide a fundamental contribution to this field, deriving original, exact, handy expressions for the probability density function and the cumulative distribution function for the sum of independent and identically distributed κ-μ variates. Our formulations can be quickly computed in all cases, even in those for which Brennan’s integral—the only available exact approach—may take several hours or not compute at all. For application purposes, we use our formulations to investigate the outage probability and the mean bit error rate in equal-gain diversity systems. Further contribution includes asymptotic analyses. Numerical simulations validate our findings.

USING THE KIR OF THE KARASYAZ-TASPAS DEPOSIT AS A COMPONENT OF HOT ASPHALT CONCRETE

Natural bitumen has long been used in road paving, but in recent years, the demand for it has decreased. However, the use of natural bitumen in the road surface is gaining popularity again. Natural bitumen has a high content of asphaltenes and a higher molecular weight compared to petroleum bitumen. For the purpose of promising application of natural bitumen as road construction materials, studies were conducted on the selection of compositions based on oil-bitumen rocks of the Karasyaz-Taspas deposit.

On the identification of radon areas as defined in art. 103 of Council Directive 2013/59/EURATOM.

Radon maps are one of the key tools for implementing a graded approach to reduce exposure due to radon. The Council Directive 2013/59/Euratom indicated how to identify the geographical areas of the country most exposed to indoor radon. Using annual average radon concentrations in 5000 dwellings in the Lazio region, located in central Italy, the expected number of dwellings with annual average radon concentrations above the reference level of 300Bq per m3 within the 6km grid squares was estimated. For the purpose of application, radon areas were identified by arbitrarily selecting grid squares with at least 10 expected dwellings per square kilometer above 300Bq per m3. Since comprehensive measurements surveys must be conducted within the radon areas to identify all dwellings exceeding the reference level for the purpose of reducing radon concentration, quantitative economic considerations are reported.

Evaluation of Renal Ischemia–Reperfusion Injury Using Optical Coherence Tomography Based on Fractal Dimension

Renal ischemia–reperfusion (IR) is inevitable in partial nephrectomy and kidney transplantation. Acute tubular necrosis (ATN) induced by renal IR causes the loss of functional units in the kidney, pathologically presenting as the nonhomogeneous distribution of normal uriniferous tubules and usually used to characterize kidney activity. Optical coherence tomography (OCT) has been proven to have the ability to image the kidney microstructure in vivo and in real time. However, a fast image analysis method is needed for clinical application purpose. In this work, a new method for assessing renal IR injury was developed using a fractal-dimension-based texture of the OCT kidney image. Thirty-five Wistar rats were divided into seven groups for renal ischemia–reperfusion: control and various ischemia-time groups. A time series of 3D OCT kidney images was obtained. We calculated the fractal dimension (FD) of OCT en face images and found that the value increased gradually and finally became stable after 90 min of reperfusion. The stable value in the long-ischemia-time group was smaller than that in the short-ischemia-time group. The FD value of the OCT kidney image was highly responsive to renal IR injury. The proposed method is promising for a fast diagnostic application.

Effect of Organic Powders on Surface Quality in Abrasive Blasting Process

Abrasive blasting, sometimes known as sandblasting, is a method used to change the surface condition of materials, clean surfaces, and prepare surfaces for applications such as paint, bonding, coating, etc. The abrasive materials used in abrasive blasting are applied to the surface with compressed air or water and vary according to the purpose of application. The abrasive materials used have negative effects on the environment and human health. So far, organic materials have been used in limited applications in abrasive blasting. However, these materials have a high potential of usage since they are environmentally friendly, safe for human health, and have non-toxic and sustainable properties. In this study, the usability of three different organic wastes (walnut shell, olive pomace and mussel shell) recovered by recycling in abrasive blasting was investigated. In addition, the effect of blasting distance (5, 10 and 15 mm), blasting time (10, 20 and 30 s), powder type (mussel shell, olive pomace and walnut shell) and grain size (38, 45 and 63 µm) on surface roughness have been investigated using the Taguchi L9 experimental design. Regression models were built using ANOVA (Analysis of Variance). Moreover, the surface condition after abrasive blasting was examined using an Al2O3 abrasive and compared with other samples. As a result, 5 mm, 30 s, mussel shell and 45 µm test sets were recommended for “larger is better” and it was determined that the blasting time had the greatest effect on the surface roughness by 50.19%. On the other hand, 10 mm, 20 s, walnut shell and 63 µm test sets were recommended for “smaller is better”, and it was determined that blasting time had the greatest effect on the surface roughness by 39.02%. While there was an increase compared to the surface roughness values before abrasive blasting in the first set of experiments, it was determined that the organic material had a polishing rather than an abrasion effect in the second set of experiments.

Dynamic Footprints of the Specific Artificial Spin Ice Microstate on Its Spin Waves

We present a micromagnetic investigation of the spin dynamics at remanence (zero applied field) in a periodic square artificial spin ice (ASI) prepared four different microstates (i.e., with zero, two or four magnetic charges at the vertex). The ASI elements consist of permalloy elliptical dots with a fixed long axis, and a variable width and interdot separation. For each vertex configuration, we compute the equilibrium ground state at zero applied field by relaxing a previously set magnetic configuration (microstate). After the excitation of such ground state, we perform a Fourier analysis obtaining frequency spectra and space phase profiles. We discuss the behavior of the spectra in changing the system’s microstate and geometry, with reference to the spin mode space profiles, magnetization configuration, and effective internal field. Our results draw a correlation between ASI macrospin orientation at vertex and a few important dynamic properties like a phase-shift in the mode profiles or the frequency gap between the edge and fundamental modes. We suggest a few specific experiments to validate of our predictions, as well as applications in the field of interferometric magnonic devices. We believe that our results can help, from the fabrication stage, in tailoring the appropriate ASI geometry for specific application purposes.