bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep learning for image reconstruction in thermoacoustic tomography
Authors: Xu Qiwen , Zheng Zhu , Jiang Huabei
Published: June 2021

Microwave-induced thermoacoustic tomography (TAT) is a rapidly-developing noninvasive imaging technique that integrates the advantages of microwave imaging and ultrasound imaging. While an image reconstruction algorithm is critical for the TAT, current reconstruction methods often creates significant artifacts and are computationally costly. In this work, we propose a deep learning-based end-to-end image reconstruction method to achieve the direct reconstruction from the sinogram data to the initial pressure density image. We design a new network architecture TAT-Net to transfer the sinogram domain to the image domain with high accuracy. For the scenarios where realistic training data are scarce or unavailable, we use the finite element method (FEM) to generate synthetic data where the domain gap between the synthetic and realistic data is resolved through the signal processing method. The TAT-Net trained with synthetic data is evaluated through both simulations and phantom experiments and achieves competitive performance in artifact removal and robustness. Compared with other state-of-the-art reconstruction methods, the TAT-Net method can reduce the root mean square error to 0.0143, and increase the structure similarity and peak signal-to-noise ratio to 0.988 and 38.64, respectively. The results obtained indicate that the TAT-Net has great potential applications in improving image reconstruction quality and fast quantitative reconstruction.
High efficiency, small size, and large bandwidth vertical interlayer waveguide coupler
Authors: Li Shao-Yang , Wang Liang-Liang , Wu Dan , You Jin , Wang Yue , Zhang Jia-Shun , Yin Xiao-Jie , An Jun-Ming , Wu Yuan-Da
Published: June 2021

Since the advent of three-dimensional photonic integrated circuits, the realization of efficient and compact optical interconnection between layers has become an important development direction. A vertical interlayer coupler between two silicon layers is presented in this paper. The coupling principle of the directional coupler is analyzed, and the traditional method of using a pair of vertically overlapping inverse taper structures is improved. For the coupling of two rectangular waveguide layers, a pair of nonlinear tapers with offset along the transmission direction is demonstrated. For the coupling of two ridge waveguide layers, a nonlinear taper in each layer is used to achieve high coupling efficiency. The simulation results show that the coupling efficiency of the two structures can reach more than 90% in a wavelength range from 1500 nm to 1650 nm. Moreover, the crosstalk is reduced to less than –50 dB by using multimode waveguides at intersections. The vertical interlayer coupler with a nonlinear taper is expected to realize the miniaturization and dense integration of photonic integrated chips.
Irradiation behavior and recovery effect of ferroelectric properties of PZT thin films*
Authors: Zhao Yu , Zhao Wen-Yue , Ju Dan-Dan , Yao Yue-Yue , Wang Hao , Sun Cheng-Yue , Peng Ya-Zhou , Wu Yi-Yong , Fei Wei-Dong
Published: June 2021

Lead zirconate titanate piezoelectric ceramics have important applications in space and aerospace technology, but the effect and physical mechanism of charged particle radiation on their performance yet to be clarified. In this study, we characterized PbZr0.52Ti0.48O3 (PZT) thin films, and changes in the ferroelectric properties of the films before and after electron and proton irradiation were investigated. The natural and heat treatment recoverability of the ferroelectric properties were studied, and the damages and mechanisms of different types of radiation in PZT films were also investigated. The results show that, in addition to ionization damages, electron irradiation causes certain structural damage on the PZT film, and the large structural damage caused by proton irradiation reduces drastically the ferroelectricity of the PZT film.
Correlation mechanism between force chains and friction mechanism during powder compaction
Authors: Zhang Ning , Zhang Shuai , Tan Jian-Jun , Zhang Wei
Published: June 2021

The relation between friction mechanism and force chains characteristics has not yet been fully studied in the powder metallurgy research area. In this work, a uniaxial compression discrete element model is established based on the compaction process of ferrous powder. Furthermore, the correlation mechanism between force chains and the friction mechanism during powder compaction is investigated. The simulation results reveal a strong correlation between the variation of the friction coefficient and the evolution of force chains. During the powder compaction, the friction coefficient would eventually tend to be stable, a feature which is also closely related to the slip ratio between particles. The side wall friction and the friction between particles would have an important effect on the direction of force chain growth in about one-third of the area near the side wall. The research results provide theoretical guidance for improving the densification process of the powder according to the force chain and friction.
Assessment of cortical bone fatigue using coded nonlinear ultrasound*
Authors: Liu Duwei , Li Boyi , Bi Dongsheng , H. T. Tran Tho N. , Li Yifang , Liu Dan , Li Ying , Ta Dean
Published: June 2021

Bone fatigue accumulation is a factor leading to bone fracture, which is a progressive process of microdamage deteriorating under long-term and repeated stress. Since the microdamage of the early stage in bone is difficult to be investigated by linear ultrasound, the second harmonic generation method in nonlinear ultrasound technique is employed in this paper, which is proved to be more sensitive to microdamage. To solve the deficiency that the second harmonic component is easily submerged by noise in traditional nonlinear measurement, a weighted chirp coded sinusoidal signal was applied as the ultrasonic excitation, while pulse inversion is implemented at the receiving side. The effectiveness of this combination to improve the signal-to-noise ratio has been demonstrated by in vitro experiment. Progressive fatigue loading experiments were conducted on the cortical bone plate in vitro for microdamage generation. There was a significant increase in the slope of the acoustic nonlinearity parameter with the propagation distance (increased by 8% and 24% respectively) when the bone specimen was at a progressive level of microdamage. These results indicate that the coded nonlinear ultrasonic method might have the potential in diagnosing bone fatigue.
Photonic-plasmonic hybrid microcavities: Physics and applications*
Authors: Zhang Hongyu , Zhao Wen , Liu Yaotian , Chen Jiali , Wang Xinyue , Lu Cuicui
Published: June 2021

Photonic-plasmonic hybrid microcavities, which possess a higher figure of merit Q/V (the ratio of quality factor to mode volume) than that of pure photonic microcavities or pure plasmonic nano-antennas, play key roles in enhancing light–matter interaction. In this review, we summarize the typical photonic-plasmonic hybrid microcavities, such as photonic crystal microcavities combined with plasmonic nano-antenna, whispering gallery mode microcavities combined with plasmonic nano-antenna, and Fabry–Perot microcavities with plasmonic nano-antenna. The physics and applications of each hybrid photonic-plasmonic system are illustrated. The recent developments of topological photonic crystal microcavities and topological hybrid nano-cavities are also introduced, which demonstrates that topological microcavities can provide a robust platform for the realization of nanophotonic devices. This review can bring comprehensive physical insights of the hybrid system, and reveal that the hybrid system is a good platform for realizing strong light–matter interaction.
Effects of anisotropic energetic particles on zonal flow residual level
Authors: Lu Z.X. , Weiland M. , Lauber Ph. , Wang X. , Meng G. , Zonca F.
Published: June 2021

In tokamak plasmas, the interaction among the micro-turbulence, zonal flows (ZFs) and energetic particles (EPs) can affect the turbulence saturation level and the consequent confinement quality and thus, is important for future burning plasmas. In this work, the EP anisotropy effects on the ZF residual level are studied by using anisotropic EP distributions with dependence on pitch. Significant effects on the long wavelength ZFs have been found when small to moderate width around the dominant pitch in the EP distribution function is assumed. In addition, it is found that ZF residual level is enhanced by barely passing/trapped and/or deeply trapped EPs, but it is suppressed by well passing and/or intermediate trapped EPs. Numerical calculation shows that for ASDEX Upgrade plasmas, typical EP distribution functions can bring in −3% to +5.5% mitigation/enhancement in ZF residual level, depending on the EP distribution functions.
Recognition of Hand Movement for Training Motor Skill of Children With Autism Spectrum Disorder (ASD) Using Myo Gestures Control Armband and Artificial Neural Network
Authors: Syahputra M F , Hardi S M , Prasetyo A
Published: June 2021

Autism disorder causes sufferers to tend to lag behind other children in understanding and accepting the stimuli given, due to the patient’s inability to focus attention on the stimulation given. One of the therapies used to train autistic sufferers is the help of technology. One of the technologies used is the Myo Gestures Control Armband which is equipped with several sensors that can recognize hand and arm movements using the Artificial Neural Network method which adopts a thought through a mechanism that affects the human brain, both for processing various signal elements received, tolerance of errors, and also parallel processing. In this study, there are five movements classified as Ok, Fist, Like, Rock, and Spock movements to train motor movements of children with autism. With this system in the future it can become a method of therapy that is carried out at home with the supervision and control of a therapist so that it can improve the development of hand motor skills in children with autism which can be seen through a graph of the development of movements per day displayed on the system.
Bahasa Indonesia pre-trained word vector generation using word2vec for computer and information technology field
Authors: Putri Syarifah K , Amalia A , Nababan E B , Sitompul O S
Published: June 2021

Words embedding or distributed representations is a popular method for representing words. In this method, the resulting vector value is a set of real values with specific dimensions that are more effective than the Bag of Word (BoW) method. Also, the advantages of distributed representations can produce word vectors that contain semantic and syntactic information, so that word vectors with close meanings will have close word vectors. However, distributed representation requires a huge corpus with a long training time. For this reason, many researchers have created trained word vectors that can be used repeatedly. The problem is that the available trained word vectors are usually general domain word vectors. This study aims to form pre-trained word vectors for specific domains, namely computers and information technology. Researchers used a dataset of student scientific papers from the Universitas Sumatera Utara (USU) repository. Researchers used the word2vec model, where the model has two architectures, namely the Continuous Bag-of-Words (CBOW) and Skip-gram. This research’s result is word2vec model with the CBOW method is more effective than the Skip-gram method.
Web-based E-Commerce Products Grouping
Authors: Elveny M , Hardi S M , Jaya I , Gundari P
Published: June 2021

E-Commerce is a group of technologies, applications, and businesses that connect companies or individuals as consumers to conduct electronic transactions, exchange of goods or information through the internet or television, www, or other computer networks. The rapid growth of E-Commerce is caused by the many conveniences for buyers and sellers. This can be seen by the increasing number of E-Commerce sites such as Bukalapak.com, Tokopedia.com, and so on. The buyers want to get products with the lowest prices, the best quality, and from trusted sellers. This encourages them to search for and compare the same products from one store to another, even between different sites. Variables that they compare vary. Some are based on price, number of reviews, and so on. But it is troublesome when they have to look for the same product from another site. This study used the product name as a reference in grouping the same product from 5 different sites. The algorithm used to group online shop products was Jaro-Winkler Distance. The study was to create a system that can group products from 5 different sites with the highest level of similarity product as the output. From the 20 times of the search tests, the accuracy of the online shop product grouping with Jaro-Winkler Distance was 81.27%.
Face Recognition for a Student Violation Point System in Schools Using the Fisherface Algorithm
Authors: Arisandi D , Syahputra M F , Purnamawati S , Hizriadi A , Azra M H
Published: June 2021

The violation point system is one of the policies to increase discipline in schools. If a student commits a violation, then the student will be processed by the teacher and record the violation into the violation note held by each teacher. If a student’s violation record is contained in the notebooks of several teachers, it will be difficult to recapitulate the violations committed by students. This study makes a system approach and development that can centrally record student violations that run on the Android platform. To facilitate student recognition, the system is made using face recognition. Face recognition is implemented into this research because data retrieval can be done in real time with an Android smartphone camera so there is no need for additional devices. Face recognition uses the Fisherface method, which is a facial recognition method that uses Linear Discriminant Analytics for its feature extraction process. The accuracy obtained from the research is 90%.
Experimental study of seawater evaporation using natural convection principles
Authors: Sibarani Divan Apryanto , Siagian Horas , Ambarita H.
Published: June 2021

Evaporation of seawater into the air is a phenomenon that involves heat and mass transfer. The process of evaporation of water can be divided into different categories based on the flow regime, such as natural convection. The rate of evaporation that occurs in seawater without treatment or is called natural convection method only takes into account the density difference between the existing fluids. The method has been tested in natural convection with the result that the highest rate of evaporation of water in the tub is directly proportional to the radiation received. It was found that experimental result have a good agreement.
Design a Potential Analysis using Fingerprint PC Base
Authors: Hermanus Davy Ronald , Sasmoko  , Indrianti Yasinta
Published: June 2021

Fingerprint analysis is a concept that continues to develop to be implemented in various fields. Starting from the forensic needs, nowadays fingerprint analysis can be applied in various fields including education in terms of exploring one’s potential. This study is a series of preliminary research that aims to develop fingerprint analysis in relation to the concept of multiple intelligence. The research method used is the Neuro Research method with the main stage of exploratory research. The result of the research is the successful use of a fingerprint detection tool via PC so that it can produce patterns that can be analysed further. This pattern will be developed in the next stage to identify various important aspects and components in multiple intelligence.
Implementation of hybrid cryptosystem using Rabin-p algorithm and One Time Pad to secure images
Authors: Budiman M A , Zarlis M , Hafrizah
Published: June 2021

Cryptography is a study of mathematical techniques to secure messages by encoding the messages so it cannot be read by a third party. There are two types of algorithms in cryptography, symmetric algorithm and asymmetric algorithm. Asymmetric algorithms, such as Rabin-p cryptosystem, are known to be secure if the key sizes are long enough. However, asymmetric algorithms are ineffective to encrypt large data since the calculations consume CPU time and the resulting ciphertext is multiple times bigger than the original data. In this research, we combine Rabin-p cryptosystem and One Time Pad (OTP) in a hybrid scheme to solve this problem. The OTP is used to encrypt the data (images) and Rabin-p algorithm is used to encrypt the OTP key. In this research, we demonstrate how to secure a *.bmp file with this hybrid scheme.
A neural cryptography approach for digital image security using Vigenère cipher and tree parity machine
Authors: Budiman M A , Handrizal  , William
Published: June 2021

As with other form of digital media, image can also contain private information that should be kept secret. Commonly, symmetric and asymmetric cryptosystem can be used to secure an image. Symmetric-key cryptography is not a best solution as the secret key has to be transmitted through private channel. Asymmetric-key cryptosystem, however, allows transmission of key through public channel, but requires high computational power and long computational time. This paper proposes a neural cryptography approach to protect image by using tree parity machine and Vigenère cipher. By using this approach, the secret key will never be transmitted. Moreover, the whole process does not require high computational power and long computational time as in public-key cryptosystem. To overcome the weakness of Vigenère cipher, change is made to the algorithm by multiplying the key value with y-axis of image. The effectiveness is validated by the value of pearson correlation that is close to 0. Lastly, the result of experiments show neural synchronization time depends on the size of network, initial weights and randomly generated input vector.
An Automatic Fluid Filling Mechanism Using Delta PLC
Authors: Muralidharan J , Saran S , Tamilkavi G , Thivakar S , Vivin M
Published: June 2021

This project is carried out using Programmable Logic Controller, which is the main component of the proposed system. It is an industrial oriented machine system used to fill water in the empty bottles automatically, which reduce the usage of man power, low power consumption, accuracy. The system is implemented in various soft drink industries, water packaging industries and food industries. The filling process gets efficient, when our filling machine is combined with an automatic conveyor to increase the speed of filling process. The conveyor belt roll-up the empty bottles and an analog timer is used to adjust the timing of the water flow. The empty bottles are sensed by photo electric sensors and it detects the empty bottles present in the conveyor, stops the conveyor, then the valve is opened up to fill the bottles. This sequential process will continue for each and every water bottle filling process. A Programmable Logic Controller machine is preferred due to its and cost efficient high ratings. The proposed method will reduce the cost for small scale industries and help them in setting up and an automated decision for filling water bottles.
Chronological overview and algorithmic analysis of EEG Signal Processing for Brain Response to Stimuli
Authors: Bhat Ravindra , Deshmukh Saurabh
Published: June 2021

The brain is one of the most complicated organs in the human body that controls the entire actions/reactions of the body by getting diverse stimuli via the nervous system. The stimulus that is stronger than the threshold stimulus is decoded by the sensory neurons counts creating information on the frequency and the stimulus of the action potentials. This work intends to plan a detailed survey on brain response to stimuli in EEG signal processing by reviewing about 35 papers selectively to determine the shortcoming of contributed works. The analysis is subjugated in terms of chronological review, and algorithmic analysis. This analysis determines the utilization of diverse models/approaches in the contributed papers. Moreover, the performance parameter analysis along with the best performance values is also stated clearly. Finally, the research gaps and challenges that rely on this topic are clearly described that paves the way for future research contributions.
Digital Thermometers: Its Types, Utilities, and Global Trade Prospects for India
Authors: Anthony Raj S. , Senith S. , Kalpana Sai B.
Published: June 2021

Digital thermometer, a developed product from the mercury based aged Clinical thermometer is an apparent device used to sensitize the body temperature with six different latest types of innovation. These are used not only to detect body temperatures of human but also used in animal medicines and industries to check the boiling points. As the world is inching towards alien era, the infusing these thermometers with mobile apps and clouding the data is not a wonder. Understanding the raise of influenzas across the globe triggered biomedical companies to win early global demands and record their presence in global markets. India is also a great player in international demand and supply of biomedical instruments and devices. Government of India, assigned Indian Trade Clarification Harmonized System for digital thermometer. The 8-digit Code allotted is 90251910. This article focuses on the different types of digital thermometer, its utilities and the Indian trade analysis with select countries data.
IoT Based Smart Bus System using wireless sensor networks
Authors: Jeyakkannan N. , Karthik C. , Lukose Vivek
Published: June 2021

Millions of kids want to travel from their houses to their institution daily. The Safety in the transport of the kid’s plays an important role and it is said that, kids were kept locked in the bus during their boarding till they reach the destination. Another challenge is that they may miss the bus and board the wrong bus in certain cases. This paper provides the solution to overcome these issues and to develop a system that monitors the entry and exit of students in their buses with an excellent IoT based technology. The proposed system will record the data of student’s entry and exit in the bus using RFID (Radio Frequency Identification) and GSM technologies when the travel is successful from their house to their institutions, the system itself generates the SMS to all the parents concerned. Meanwhile it detects the children who are entering the wrong bus and absence and it detects whether the driver is drunken also. If any stuck in the traffic the driver can give the information to the management without any delay.
Optimal design of quadratic support vector machine based end stage renal disease predictor model
Authors: Sathyadeepa S , Sivakumar T.
Published: June 2021

At present kidney failure has become one such important paradigm for higher mortality rate. Chronic kidney disease (CKD) is a severe kidney infection, and it has different stage of infection with final condition is being called as End Stage Renal Disease (ESRD). At this juncture patient are supported with dialysis or kidney transplant. The process requires time to analyze, diagnose the different parameters in determining CKD. The study involves using machine learning techniques for predicting the stages involved in infection and prevent the disease progression. There are four different stages of kidney disease, patient above 12 years of age are analyzed with 24 different input parameters. Around 160 subject’s parameters were taken into the database. Important feature includes serum creatinine, blood pressure, bacterial infection, pedal edema, urine sugar and sodium level in the blood are included. Machine learning algorithm was developed using MATLAB 2018 to predict the early end stage of CKD. Algorithms like Fine Decision Tree (FDT), Quadratic Support Vector Machine (Quad-SVM) and Linear Discriminant Analysis (LDA) are the three main algorithms used for designing the predictor model. Classification Learner Toolkit helps is determining the accurate model and Curve Fitting Toolbox helps in curve fitting over the given data set. After analyzing the system with different predictor model, the model with high accuracy and less training time is chosen. The proposed work also incorporates an e-message alert system linking the nephrologists in case of any emergency wirelessly. It enables high speed prediction and diagnosis process for treatment of subject under high risk factor. The threshold value is continuously monitored and in case if the value exceeds the safer limit, a notification is sent to the physician in proper time.
Prognostication of Acute Lymphocytic Leukemia (ALL) using Capsule Network Algorithm
Authors: Melfi Rose S. , Merlin Sheeba J. , Vijay Prabaharan R. , Bhuvaneshwari M. , Subha Hency Jose P.
Published: June 2021

A type of cancer that affects the blood-forming tissues in the body including lymphatic system and bone marrow is Leukemia. The second most commonly occurring acute leukemia is the acute lymphoblastic leukemia or acute lymphocytic leukemia (ALL). Around 25% of the cases are observed to be due to malignant T-cell precursors while the remaining 75% of cases is due to precursors of B-cell lineage. In general, response to chemotherapy, white blood cell count and age are the clinical factors that contribute towards risk stratification. However, in recent years it has been identified that genetic alterations have enabled between individual prognosis and recovery. Despite advancement in technology, chemotherapy using anthracycline, corticosteroids and vincristine serves to be the backbone therapy to treat this disease. In this proposed work, we have used a deep convolutional neural network to detect the presence of ALL accurately and based on the image screened, it is further categorized into one of the 4 subclasses. Using Capsule network algorithm (CapsNet), we have established 100% average sensitivity for ALL detection with a highest specificity of 99.56%, precision of 99.82% and accuracy of 99.36%. When compared with other similar methodologies, we have been able to accomplish higher accuracy without microscopic image segmentation using capsule network algorithm.
Detection of Acute Lymphoblastic Leukemia in Microscopic images using Image Processing Techniques
Authors: Philip Arun Tom , Shifaana S. , Sunny Stelin , Manimegalai P.
Published: June 2021

Leukemia is a form of blood cancer that affects the body’s ability to fight against infection. Every year, about 1 million cases of leukemia are reported with an increased mortality rate that can cause a delay in diagnosis and treatment of leukemia. Conventionally, Acute Lymphoblastic Leukemia is identified by manual counting of cells from a peripheral blood smear or by bone marrow aspiration. However, this method is time consuming and prone to human errors. To prevail over this, various automated techniques were introduced which are faster, reliable and cheaper than the manual methods. This paper focuses on how image processing techniques can be used to identify Acute Lymphoblastic Leukemia (ALL) from the peripheral blood smear images.
Prevalence of musculoskeletal disorders and occupational risk factors among building painters in South India
Authors: Shanmugam M , Gnanavel B K , Vijaya Rajan V , Santhanam V
Published: June 2021

The main objective of this study is to find out the prevalence of musculoskeletal disorders (MSDs) and risks among building painters in South India. Cross-sectional data were collected from 120 male building painters in South India using a modified Nordic Musculoskeletal Questionnaire (NMQ) survey. The question includes demographic information, psychological factors, medical history, work-related information, MSDs symptoms and severity of MSDs. The statistical analyses reported the highest prevalence of MSDs among building painters was reported as 70.8%. The highest prevalence rate has been found in the shoulder region (69.5%) and neck region (65.4%). It is also evident that the chief painters experienced the highest discomfort (72.0%) than assistant painters (68.4%). The repetitive task, awkward postures, forceful exertions and work height above shoulder level were reported as highly contributing factors of MSDs among building painters. The building painters who participated in this research were found to exhibit both MSDs and ergonomic hazards. Results suggest that further studies are needed to establish different preventive measures and ergonomics interventions to reduce the risks of MSDs among building painters.
Simulation And Modelling of BCI Based Multi Purpose Wheel Chair For Paralysed People
Authors: Sindhuja R , Samson Isaac J , Vijayakumar Poornima , Joseph Jeffin , Samuel A.E.Adrian
Published: June 2021

According to the survey of Reeve foundation and WHO says, there are nearly 1 in 50 people living with paralysis, every year 5.4 million people affected. Paralysis is caused by spinal injury, stroke, multiple sclerosis, cerebral palsy and other causes like motor accidents and victim of violence. It is also called loss of muscle function in some part of the body. In this paper, we systematically survey a different techniques used for brain computer interface and also review the research on non-invasive, electroencephalography (EEG)-based BCI systems for communication and rehabilitation. Main research focus on previous techniques like deep learning or deep neural network, machine learning, Neuro plasticity, support vector machine, artifact suppression and so on. In this Differing from traditional machine learning algorithms, online sequential machine learning algorithm is empowered to learn distinct high-level representations from raw brain signals without manual feature selection. A certain MATLAB program is designed to use these motions. Our results are to exploit the accuracy rate and to generate the assistive devices for restoration of movement and communication strength for physically disabled patients in order to rehabilitate their lost motor abilities.
IOT Based Infant Healthcare Monitoring System
Authors: Dhana Sony Ms. , Samson Isaac J , Ezhilarasi N. , Jayanth V.
Published: June 2021

Newborn child needs appropriate consideration for great wellbeing and mental health. These days, families comprise of just guardians and kids. Managing infant youngsters is ambling for grandparents so the chances of giving extra thought and love are diminished. In a family, necessities to really focus on the child’s clinical issue are inevitable. To deal with such issues a system is proposed for the device health watch framework. This will assist a mother or a dad to screen the baby with different boundaries. The framework began getting more altered. These days numerous baby checking frameworks came into the market with different alternatives. This framework keeps newborn children to be in a protected condition by avoiding wet condition utilizing sensors and continue to check the vital health parameters.. IoT is helpful in this angle as it replaces the customary checking frameworks with a more proficient plan, by giving basic data in regards to the state of the patient. This framework utilizes the heartbeat sensor, Temperature sensor, wetness senor and conductivity sensor with Node MCU. The beat sensor is put on the finger and it estimates the pulse and afterward sends the heart rate to android versatile application by means of Bluetooth. A microcontroller is interfaced with the Wi-Fi system to make a straightforward TCP/IP correspondence. The parameters will be checked and downloaded very easily using the android application. The other advantage of the programmability is parents can be aware of their infant’s health status continuously.
Treatment of Sleep Apnea using CPAP
Authors: Jayachitra S. , Abinaya S. , Mohan Raj D. , Shobika R.
Published: June 2021

Worldwide, they are more than one in ten children are born prematurely. Eleven countries, have higher preterm birth rates Premature maturation (born before 37 weeks of pregnancy) is strongly associated with difficulty breathing diseases, that is, the leading cause of death for children under five. Because their lungs well developed, enemies in particular exposure to respiratory problems. One such the leading cause of child mortality worldwide Respiratory Distress Syndrome (RDS). Currently \ technology (recommended by WHO) by CPAP (Continuous Positive Airway Pressure), i.e. helps keep the alveoli open by giving continuous distribution of air / oxygen. This ensures that the children stay healthy residual air in the lungs, so it does not they strive to breathe and are continually saved problems such as hypoxia and even death CPAP standalone devices cost more than INR 150,000 ($ 2300) more expensive many developing hospitals. For the most part hospitals in restricted services, Oxygen treatment in the nose is often the solution available, on the basis of respiratory depression.
Magnetic induction device for nanoparticles heating at frequency > 500 kHz
Authors: Plascencia-Cruz L.E. , Hernández-Rayas A. , Villaseñor-Mora C. , Torres-Osorio J. , Córdova-Fraga T.
Published: June 2021

Treatment with magnetic induction hyperthermia can be complementary by raising the temperature in cell clusters above 42 ∘C, this procedure increasing the effectiveness of treatments for the elimination of cancer cells based on drugs. A magnetic induction device working in selectable modules of frequencies > 500 kHz is presented, it was developed and constructed for transfer heat in a selected biological tissue. An LC parallel resonant circuit configuration was used with an inverter coupled to a power supply as an auto-resonator and the oscillation frequency depends on the capacitor bank to generate a phased sine signal in the oscillating signal in the LC tank circuit. It works with switchable modules that operate in different frequencies, among 85 kHz and 900 kHz which makes it completely autonomous and portable, this selection of work frequencies is the main contribution of this equipment. This device generating a magnetic field from 0.44 mT to 5.11 mT. So, the use of a self-resonator inverter allows operating without requiring an external signal generator for tuning the different frequencies, coupled with the incorporation of a cooling system embedded in the same device, which makes no external complimentary devices required. Finally, it is highlighted that the frequency range presented in this work is higher than those reported by other authors, which is below 500 kHz.
Compensation scheme for non-linear beam defocusing inside planar undulator
Authors: Karmakar J. , Tischer M. , Ghosh S. , Vagin P. , Aggarwal M. , Sahu S.
Published: June 2021

The Delhi Light Source (DLS), is a compact THz facility based on the principle of pre-bunched FEL, which is at the commissioning stage at Inter University Accelerator Centre (IUAC), New Delhi. The facility will produce relativistic electron beam in the energy range 4 to 8 MeV to generate THz radiation in the range 0.18–3.0 THz. To study the effect of the undulator U48 on this low energy range of the electron beam, a 3D field map of U48 was generated with the help of measured magnetic field data. Beam tracking simulations were performed with the generated field map at the minimum gap of U48. Simulations showed that the quadrupole component of the transverse field roll-off, which is the dominant component within the width of the vacuum chamber can introduce a substantial growth of the beam size in the wiggling plane and result in severe beam loss while propagating through the vacuum chamber inside the undulator. To compensate the dynamic quadrupolar field, an extended quadrupole field correction coil was implemented in the simulation by superimposing its field on the magnetic field of U48. Such a correction scheme showed a remarkable improvement to contain the beam transverse growth.
A resource-based phosphorus footprint for urban diets
Authors: Papangelou Anastasia , Towa Edgar , Achten Wouter M J , Mathijs Erik
Published: June 2021

Large amounts of phosphorus resources, such as mineral fertilizers and manure, are mobilized globally to produce the food consumed in cities. Accounting for the use of these resources can allow cities to plan for interventions that reduce related pressures in their hinterlands, conserve resources, and lead to more circular food systems. In this study we calculate a resource-based phosphorus footprint for the food consumption in Brussels Capital Region and use it to compare different strategies towards increased circularity: waste reuse, waste reduction, dietary changes and shifts to locally produced food. The P footprint of an average inhabitant in Brussels is 7.7 kgP cap yr−1, 10 times higher than the physical P consumption of 0.7 kgP cap yr−1. About 60% of the total P inputs into food production are through manure, and the rest through mineral fertilizers; almost 80% of the inputs occur outside Belgium. Most of these inputs are related to the cultivation of feed for livestock, which is why a shift to vegetarian and vegan diets can reduce the footprint down to 4.8 kgP cap yr−1 and 0.9 kgP cap yr−1. To the contrary, consuming only food produced in Belgium would increase the footprint to 12 kgP cap yr−1, mostly as a result of the high manure use in the north of the country. A reduction in the P footprint signifies an absolute reduce in total resource use that can alleviate pressures in the hinterland and promote a city’s transition towards circularity.
Cropland heterogeneity drives frequency and intensity of pesticide use
Authors: Nicholson Charlie C , Williams Neal M
Published: June 2021

Agricultural landscapes across the planet have replaced natural habitat with crop production that is less diverse at field and landscape scales. Loss of cropland heterogeneity can increase pest colonization rates and decrease predation rates, thereby exacerbating pest pressure and leading to increased use of pesticides. Linking landscape pattern, crop pest pressure, and pesticide use is emerging as critical step for understanding the benefits, and potential trade-offs, of diversified agriculture. We advance this work by exploring how cropland heterogeneity drives pesticide use, and whether this effect is modified by pesticide class (i.e. fungicide, herbicide or insecticide). We focus on a diverse growing region, California’s Central Valley, and use spatial auto-regressive models to test for consistent class-based differences in the relationship between pesticide use and cropland heterogeneity (i.e. mean field size and landscape-level crop diversity). We find reduced pesticide use, in terms of both frequency and intensity of application, in diversified, spatially-heterogenous landscapes. Additionally, we see (a) more consistent responses of fungicides and insecticides to landscape pattern, (b) pesticide use increases as cropland becomes more homogenous with respect to crop identity, and (c) this effect is more consistent for perennial crops than annual crops. The modifying influence of pesticide class is largely consistent with expectations from ecological theory. Our results support increasing focus on whether enhancing the heterogeneity of the crop mosaic itself can benefit biodiversity, ecosystem services, and human well-being.
Changes in the frequency of global high mountain rain-on-snow events due to climate warming
Authors: López-Moreno J I , Pomeroy J W , Morán-Tejeda E , Revuelto J , Navarro-Serrano F M , Vidaller I , Alonso-González E
Published: June 2021

Rain-on-snow (ROS) events can trigger severe floods in mountain regions. There is high uncertainty about how the frequency of ROS events (ROS) and associated floods will change as climate warms. Previous research has found considerable spatial variability in ROS responses to climate change. Detailed global assessments have not been conducted. Here, atmospheric reanalysis data was used to drive a physically based snow hydrology model to simulate the snowpack and the streamflow response to climate warming of a 5.25 km2 virtual basin (VB) applied to different high mountain climates around the world. Results confirm that the sensitivity of ROS to climate warming is highly variable among sites, and also with different elevations, aspects and slopes in each basin. The hydrological model predicts a decrease in the frequency of ROS with warming in 30 out 40 of the VBs analyzed; the rest have increasing ROS. The dominant phase of precipitation, duration of snow cover and average temperature of each basin are the main factors that explain this variation in the sensitivity of ROS to climate warming. Within each basin, the largest decreases in ROS were predicted to be at lower elevations and on slopes with sunward aspects. Although the overall frequency of ROS drops, the hydrological importance of ROS is not expected to decline. Peak streamflows due to ROS are predicted to increase due to more rapid melting from enhanced energy inputs, and warmer snowpacks during future ROS.
An enhanced phase field model for micron-scale droplet impact with solidification microstructure formation
Authors: Shen Mingguang , Li Ben Q , Yang Qingzhen
Published: June 2021

In this work, a novel diffuse interface model combining droplet impact with solidification microstructure formation was developed. A number of numerical models simulating droplet impact with solidification have been invented, but few are capable of unveiling the nucleation and growth of polycrystalline crystals on a micro scale. This paper thus aims to propose a diffuse interface model to simulate droplet impact, and moreover, solidification microstructure formation. To implicitly track the evolving liquid-gas interface, the Cahn-Hilliard equation is coupled with the Navier-Stokes equation. A phase field model involving polycrystalline growth is responsible for the capturing of solid-liquid interface and grain-grain boundaries. The current model is discretized explicitly such that it lends itself to shared-memory parallelism like OpenMP. A parallel SOR scheme based on Red/Black ordering is used to solve the pressure velocity coupling. The model was applied to various impact conditions in plasma spraying, including both single and multiple droplet impact, to show its robustness. Besides, with the model being modified slightly, non-equilibrium effect induced by rapid solidification was investigated as well.
Methods for synthesizing β-Ga2O3 thin films beyond epitaxy
Authors: Cooke Jacqueline , Sensale-Rodriguez Berardi , Ghadbeigi Leila
Published: June 2021

Gallium oxide is an exceptional ultra-wide bandgap material. Its most stable phase, β-Ga2O3, has been extensively studied and recently attracted much attention for various applications in electronics and optoelectronics. Recent research interest has also arisen in the study of two-dimensional β-Ga2O3, which might promise superior electrical, optical, thermal, and mechanical properties due to quantum confinement, high surface to volume ratio, and ease of integration with other materials. This work reviews and discusses facile, versatile, and economic methods such as exfoliation, spray pyrolysis, and oxide printing to produce few-nanometer thin β-Ga2O3 films. Optical properties and applications in optoelectronic devices are particularly highlighted, along with possible directions for future research.
Second order monotone finite differences discretization of linear anisotropic differential operators
Authors: Bonnans J. Frédéric , Bonnet Guillaume , Mirebeau Jean-Marie
Published: June 2021

We design adaptive finite differences discretizations, which are degenerate elliptic and second order consistent, of linear and quasi-linear partial differential operators featuring both a first order term and ananisotropicsecond order term. Our approach requires the domain to be discretized on a Cartesian grid, and takes advantage of techniques from the field of low-dimensional lattice geometry. We prove that the stencil of our numerical scheme is optimally compact, in dimension two, and that our approach is quasi-optimal in terms of the compatibility condition required of the first and second order operators, in dimensions two and three. Numerical experiments illustrate the efficiency of our method in several contexts.
Relativizing computable categoricity
Authors: Downey Rodney , Harrison-Trainor Matthew , Melnikov Alexander
Published: June 2021

A recent thread in computable structure theory has been the investigation of computable structures after relativizing, the key idea being that facts which are true for algebraic/structural reasons tend to relativize. On the other hand, there are pathological examples such as a structure which is computably categorical but not relatively computably categorical; but such behaviour must eventually stabilize, as for example a structure is either computably categorical relative to all degrees above

0

\mathbf {0}

or not computably categorical relative to all degrees above

0

\mathbf {0}

. But what can happen in between? We show a surprising result: there is a structure which alternates between being computably categorical and not computably categorical relative to an infinite increasing sequence of c.e. degrees.
Learning from a successful process evaluation in care homes
Authors: Allen Frances , Darby Janet , Cook Marie , Evley Rachel , Godfrey Maureen , Horne Jane , Leighton Paul , Logan Pip , Robinson Katie
Published: June 2021

Introduction

process evaluations (PE) are increasingly used in parallel with randomised controlled trials (RCT) to inform the implementation of complex health interventions. This paper explores the learning accrued from conducting a PE within the Falls in Care Homes Study (FinCH), a large UK RCT.

Methods

in the FinCH study, six purposively sampled care homes provided data for the PE, which followed a realist approach. In this study researchers kept written diaries of their experiences in completing the interviews, focus groups and observations. We have reflected on these and present the main themes for discussion.

Findings

care home staff were enthusiastic to participate in the PE but researchers found it difficult to collect data due to staff not having time to take part, environmental factors such as no space for focus groups and low levels of research understanding. Researchers found that the expectations of the PE protocol were often unrealistic due to these limitations. Flexible and pragmatic approaches such as interviews in place of focus groups enabled data collection but required a reduced sample size and length of data collection to be accepted by researchers.

Conclusion

to enable care home staff to participate in successful PEs, researchers should build flexibility into research schedules, spend time building trust, collaborate with all levels of care home staff prior to data collection, increase research capacity in care home staff and co-design research projects.