bluuebunny/crossref_metadata_2025 huggingface dataset:
Stable, long-term single-neuronal recording from the rat spinal cord with flexible carbon nanotube fiber electrodes
Authors: Liu Xiaojun , Xu Zheng , Fu Xuefeng , Liu Yang , Jia Huilin , Yang Ziqian , Zhang Jing , Wei Shiyuan , Duan Xiaojie
Published: September 2022

Objective. Flexible implantable electrodes enable months-long stable recording of single-unit signals from rat brains. Despite extensive efforts in the development of flexible probes for brain recording, thus far there are no conclusions on their application in long-term single neuronal recording from the spinal cord which is more mechanically active. To this end, we realized the chronic recording of single-unit signals from the spinal cord of freely-moving rats using flexible carbon nanotube fiber (CNTF) electrodes. Approach. We developed flexible CNTF electrodes for intraspinal recording. Continuous in vivo impedance monitoring and histology studies were conducted to explore the critical factors determining the longevity of the recording, as well as to illustrate the evolution of the electrode–tissue interface. Gait analysis were performed to evaluate the biosafety of the chronic intraspinal implantation of the CNTF electrodes. Main results. By increasing the insulation thickness of the CNTF electrodes, single-unit signals were continuously recorded from the spinal cord of freely-moving rats without electrode repositioning for 3–4 months. Single neuronal and local field potential activities in response to somatic mechanical stimulation were successfully recorded from the spinal dorsal horns. Histological data demonstrated the ability of the CNTF microelectrodes to form an improved intraspinal interfaces with greatly reduced gliosis compared to their stiff metal counterparts. Continuous impedance monitoring suggested that the longevity of the intraspinal recording with CNTF electrodes was determined by the insulation durability. Gait analysis showed that the chronic presence of the CNTF electrodes caused no noticeable locomotor deficits in rats. Significance. It was found that the chronic recording from the spinal cord faces more stringent requirements on the electrode structural durability than recording from the brain. The stable, long-term intraspinal recording provides unique capabilities for studying the physiological functions of the spinal cord relating to motor, sensation, and autonomic control in both health and disease.
Full statistics of nonstationary heat transfer in the Kipnis–Marchioro–Presutti model
Authors: Bettelheim Eldad , Smith Naftali R , Meerson Baruch
Published: September 2022

We investigate non-stationary heat transfer in the Kipnis–Marchioro–Presutti (KMP) lattice gas model at long times in one dimension when starting from a localized heat distribution. At large scales this initial condition can be described as a delta-function, u(x, t = 0) = Wδ(x). We characterize the process by the heat transferred to the right of a specified point x = X by time T,

J
=

∫

X

∞

u

(

x
,
t
=
T

)

d
x
,

and study the full probability distribution

P

(

J
,
X
,
T

)

. The particular case of X = 0 has been recently solved by Bettelheim et al (2022 Phys. Rev. Lett.
128 130602). At fixed J, the distribution

P

as a function of X and T has the same long-time dynamical scaling properties as the position of a tracer in a single-file diffusion. Here we evaluate

P

(

J
,
X
,
T

)

by exploiting the recently uncovered complete integrability of the equations of the macroscopic fluctuation theory (MFT) for the KMP model and using the Zakharov–Shabat inverse scattering method. We also discuss asymptotics of

P

(

J
,
X
,
T

)

which we extract from the exact solution and also obtain by applying two different perturbation methods directly to the MFT equations.
Design and Simulation of Miniaturization of Triangular Shape Dielectric Resonator Antenna Using AMC Surface for 5G Applications
Authors: Raghavendra Ch , Pranav V S N , Umasri R , Siva Nageswara Rao T , Nikhita K
Published: September 2022

A Dielectric Resonator Antenna (DRA) is a radio antenna. It is built up of ceramic material into blocks of various forms and is generally suitable at frequencies larger than 1 GHz (microwave frequencies and higher than microwave frequencies). Using this Dielectric Resonator Antenna, the operating frequency is achieved at 4.8GHz for 5G applications like IOT (Internet of Things), AI (Artificial Intelligence). Here, artificial magnetic conductor (AMC) surface is used to miniaturize a triangular shaped Dielectric Resonator Antenna (DRA). There are nine tiny copper patches forms the Artificial Magnetic Conductor (AMC) surface having gap of 1.5mm between the patches. AMC is installed on FR4 substrate which has dielectric constant as 4.4. On the AMC surface, a Dielectric Resonator (DR) of dielectric constant 2.2 is placed. The surface of the Artificial Magnetic Conductor is shorted with ground metal using tiny metallic vias. Antenna characteristics such as antenna gain, resonant frequency, and efficiency will not be affected due to the usage of Dielectric Resonator. As a result, the overall volume of DRA is significantly diminishing. There are three primary aspects in this design: (a) Impedance matching using a Parasitic Metallic Strip (b) Design miniaturisation with an AMC surface (c) Simple microstrip line Feeding. Overall volume of Dielectric Resonator Antenna size reduced by 85%. In addition, when compared to the original Dielectric Resonator Antenna without the surface of Artificial Magnetic Conductor, the ground surface is lowered by 15.5 percent.
Photonic crystal race track ring resonator design for the detection of cancer cells
Authors: Biswas Uttara , Rakshit Jayanta Kumar
Published: September 2022

Some of body’s cells grow in an uncontrolled manner and spreads to the other parts of the body due to cancer. Also in cancer, normal body cells infiltrate and destroy rapidly. Though the advanced treatment process has improved the survival rates of cancer, but still the cancer holds the second highest place as the leading cause of death throughout the world. But diagnosis at the earlier stage may cure the disease and improve the survival rates. In the reported article, photonic crystal based racetrack shaped ring resonator is designed using FDTD simulation to conduct study of cancer cell detection and a very high sensitivity of 900 nm/RIU is obtained from the analysis.
High pass filter based on one-dimensional graded photonic crystal
Authors: Ankita  , Bissa Shivangi , Suthar Bhuvneshwer , Bhargava Anami
Published: September 2022

In this study, a graded thickness photonic crystal is studied containing metamaterial and air multilayers. Transmission spectra are calculated using the transfer matrix method. The transmission values of proposed structure increases with frequency and attain values as unity, which can show an application as optical high pass filter. The frequency corresponding to half transmission value i.e. cut-off frequency of proposed optical high pass filter can be tuned with the graded index parameter.
Design of UWB Antenna for Multimedia and High-Speed Automotive Communication
Authors: Sriram A. , Sangeetha M.
Published: September 2022

This paper reveals a planar ultra-wideband (UWB) antenna with defective ground structure is designed and analyzed. A size of 24 × 24 × 1.6 mm3 circular shaped proposed UWB antenna uses FR-4 substrate covering the impedance bandwidth (S11 ≤ −10 dB) of 11 GHz ranging from 2.9 GHz to 13.9 GHz and also offers a peak gain of 5.1 dBi, more than 65% of efficiency in overall UWB operating band with omnidirectional radiation pattern. The simulated results of proposed UWB planar antenna have good performance, and is well-suited for high-speed and multimedia communications in vehicular environment.
Coverage Optimization in LoRa with Diverse Fading Wireless Channels
Authors: Gnanaselvam R , Vasanthi M S
Published: September 2022

In LoRa (Long Range) network, the Probability of Coverage (PoCov) in the LoRa User Equipment (UEs) is evaluated in diverse fading wireless channels through closed expressions, particularly considering the distribution of Nakagami and Rayleigh wireless fading channels. The PoCov in Nakagami-m fading channel has been calculated approximately, similarly, the PoCov in Rayleigh fading channel was evaluated in an extract manner. Moreover, we see the effect of diverse interference under PoCov performance. In particular, consider interferences such as intra Spreading Factor (SF), inter SF, and both inter and intra SF.
Microstrip feed dual band and triple band frequency reconfigurable antenna for diverse applications
Authors: Jhansi Rani A , Raghunadh K , Siva Sai Srinivas T , Pranathi V , Megha Sree K
Published: September 2022

A compact reconfigurable antenna which can operate at wide range of frequency bands like ITU-band (7.725 GHz– 8.5 GHz), X-band (8-12.5GHz) and Wi-Fi (3.6 GHz, 5 GHz, and 5.9 GHz) very efficiently with gain ranging from 10dB to 12dB which can be useful for commercial applications is designed. A circular shaped antenna with microstrip line feeding is designed with highest switching rate with the abet of two-diodes which provides state of flexibility in terms of frequency reconfigurability, number of operating bands, frequency reconfigurability and stable radiation pattern with easily fabricating opportunities consists of stub loaded circular patch radiator. The novelty of proposed ultramodern antenna in terms of the band-width frequency reconfigurability, and multiple operating modes are achieved due to the collation performance of the suggested antenna operates in commercial applications.
Investigations on Mode Analysis of Distributed Bragg Reflector based Hybrid Plasmonic Terahertz Waveguide
Authors: Mahankali Pallavi , Rama Rao T , Susila M
Published: September 2022

Terahertz (THz) technology is emerging field and is fascinating to the researchers who are working with photonics integrated circuits. With technological advancements and developments for various applications, a novel distributed Bragg reflector (DBR) based hybrid plasmonic terahertz waveguide (HPTW) is proposed and designed to operate at 3 THz with Graphene, Gallium Arsenide (GaAs), High-density Polyethylene (HDPE) and Aluminium Gallium Arsenide (AlGaAs) is discussed in this work. To bring the confinement of the THz wave in a small mode area efficiently, a stripe is introduced between graphene and DBR in HDPE. The normalized mode area is decreased to about 3.733 x 10-3 µm2 by reducing the stripe’s width from 20 to 14 µm with a constant of stripe’s height of 1 µm. The Figure of Merit (FOM) and Propagation Length (PL) increases inversely in correspondence with the stripe’s width from 1.4 to 4.8 and 6 to 16.8 µm respectively.
Pressure Dependent Characteristics of 1D Random Photonic Crystals
Authors: Lakshmi Thara R , Aruna Priya P. , Nayak Chittaranjan
Published: September 2022

The effects of hydrostatic pressure on the defective random one dimensional photonic crystals (1DPC) were investigated for the two cases of polymeric materials. The polymers, Polystyrene (PS), and Polymethyl methacrylate (PMMA) act as the defect layer. Where the random structure is modeled with a combination of silicon and silica. The transmission spectra of the two multilayer photonic structures under pressure are analyzed using the transfer matrix method. The numerical results reveal a significant shift of localized states towards the shorter wavelength i.e., from 1550 to 1405 nm for the pressure range of 0-6 GPa. The localized states are very narrow which depends on the photoelastic relations between the selected materials. The sensitivity and R2 value obtained in PMMA inserted random structure is 29.5 nm/GPa and 0.959 respectively. When PMMA is replaced by Polystyrene, the sensitivity and the R2 value is improved to 35 nm/GPa and 0.987 respectively. These properties facilitate their applications in designing pressure sensors. The proposed configurations are physically realizable and versatile.
A Machine Learning approach for classification of ovarian tumours
Authors: Heartlin Maria H. , Maria Jossy A. , Malarvizhi S.
Published: September 2022

Ovarian tumours are abnormal growths in the ovaries which can be either cancerous or non-cancerous. Ovarian cancer is reported to cause more deaths than any other female reproductive cancers. In order to reduce the death rate, early diagnosis and treatment is required. In the recent days, Artificial Intelligence (AI) based Computer Aided Diagnosis(CAD) is being used performed in order to reduce human errors. This work is one such CAD based classification system to classify of benign and malignant ovarian tumours. Six popular Machine Learning(ML) algorithms have been applied on clinical ovarian bio-markers with an aim to classify the tumours. Also, a comparative study between the applied ML techniques is given in the result and discussion section.
Vision-Based Obstacle Detection and Collision Prevention in Self-Driving Cars
Authors: Sarada Devi Y , Sathvik S , Ananya P , Tharuni P , Naga Krishna Vamsi N
Published: September 2022

With increasing computational power and a vast amount of data to work with, deep learning has risen to prominence since the 2010s. Numerous applications are being researched and developed using deep learning. One of the applications is computer vision in self-driving cars. Convolutional Neural Networks (CNNs) are being widely used because of their high performance compared to other alternative techniques in several perception and control tasks. The Convolutional Neural Networks (CNNs) allows the automobile to learn from different types of roads, scenarios allowing the car to forecast its route on any particular road with minimum inaccuracy. This paper proposes a working model of the autonomous car, which has a Raspberry Pi 4 Model B as the control unit and processing unit. This working model gets real-time images from the Raspberry Pi camera and these images are used by the CNN model, which predicts the direction the car must turn. The raspberry pi sends the control signals to the L298n motor driver. The trained CNN model achieved an accuracy of 96.39% with the test dataset and 84.77% with the validation dataset.
Brain Cancer Detection by Using Cluster Evaluation Technique
Authors: Suneetha Bobbillapati , Jhansi Rani A.
Published: September 2022

The diagnosis of brain cancer is made by a radiologist using a Magnetic Resonance Imaging scan, which takes a long time. The majority of brain tumour recognition approaches provide detailed information on the tumour and need providing an accurate report on tumour proximity. So a formal consultation with a radiologist is required, that becomes an unnecessary expense if a non-tumor understanding is discovered. The goal of the paper is to provide a supporting system that will assist radiologist in knowing the results ahead of time, reducing the time spent on the core worry of tumour disclosure. The following stages are included in the suggested procedure. The Magnetic Resonance Image of Brain is initially obtained from the Brain MRI Image instructional collection. The selected MRI image is sent to Pre-Processing in the second stage, where the film workmanship markings are erased. The large repeated regions of the MRI image are removed in the third step utilizing separate filtering techniques. Finally, in this suggested study, the proposed approach explores the optimum improved methodology, called as Ant Colony Optimization (ACO). The proposed strategies reduce the time irregularity in the region of brain tumour, resulting in increased precision. The MRI images of brain are used as data in this study. The end users examine the report of MRI on their own, without the assistance of a radiologist.
A Novel Technique For Enhancing Underwater Visibility Using Non-Local Stretch Directional Gradient
Authors: Chrispin Jiji A , Maik Vivek , Gowda Vijay Kumar
Published: September 2022

Owing to the many effects of the underwater medium, underwater images are often captured with a hazy quality. These effects are caused by suspended particles in the image forming phase, which cause light absorption and scattering. On account of these pictures with fluctuating levels of dimness and colour variation, traditional algorithms have several disadvantages. Underwater image enhancement’s main goal is to increase the clarity and contrast of underwater photographs in order to solve these issues. Our paper describes a novel technique by combining several algorithms characteristics for achieving the following goals: i) better scattering, (ii) grey world assumption, (iii) non-Local stretch Directional Gradient process. For example, a better scattering model would be better at modelling hazy scenes and overcoming the image illumination dimming effect. Second, for uniform visibility recovery on the captured picture, an appropriate gray world-assumption is used. Finally, the Non-Local stretch and Directional gradient filter work on the edge details and overall dual tone enhancement required for a high-quality picture. Simulation experiments indicate that the proposed methodology produces improved visual effects and has a greater impact on consistency metrics than other methods.
Skin Cancer Lesions Classification Using Probabilistic Neural Network
Authors: Prasad Kudumu Vara , Susmitha Bollamreddi , Chennu Tulasi , Bhanu Murthy Kambala Mithra Sai , Datta Meda Vishnu
Published: September 2022

One of the most frequent types of cancer is skin cancer. Skin cancer is one of a deadly disease caused due to the abnormal skin cell proliferation in the epidermis resulting in the formation of mass called as Tumor. The formed tumor can be cancerous known as Malignant, that is it can raise and can open out to the rest of the body and the other is non-cancerous tumor known as benign which can raise but it does not open out to the rest of the parts. Skin cancer is mainly caused because of exposure of skin to the harmful UV(Ultraviolet) radiation. If skin cancer is detected in early stage then there are high chances for successful skin cancer treatment. In this paper we are describing a model which uses deep learning technique and some Image processing techniques for distinguishing of skin cancer as benign tumor or malignant tumor. The proposed model gives results in less time and eliminates the cost compared to the formal strategy that is Biopsy which is used for skin cancer recognition. The proposed model uses image processing techniques like Pre-processing, different Segmentation techniques, Feature Extraction and deep learning technique PNN (Probabilistic Neural Network) is used for classification of the skin image.
Comparison of various CNN encoders for image captioning
Authors: Veena S , Ashwin K S , Gupta Prateek
Published: September 2022

Image captioning is the ability of machines to study the features of an image and then give a textual description of that image. It uses computer vision to extract the features from the image and natural language processing for generating the caption. Image captioning requires both Image analysis and natural language processing. It is a very important task for further research on visual intelligence in line with human perception. In this project we will compare the different CNN pretrained models that are available like VGG16, RESNET50, Xception and INCEPTION and find out which performs better for image captioning.
Analysis of various Pre-processing filtering methods for MRI brain tumour detection in a noisy environment
Authors: Jain Priyanka , Parmar Priyasha
Published: September 2022

Magnetic Resonance Imaging (MRI) is playing a very important role in the detection of various abnormalities in the human body. Biomedical image processing is helping us in the proper identification of various abnormalities such as a malignant tumour in various parts of the body. In this paper different types of filtering methods applied in the pre-processing stage have been compared. When MRI images have been corrupted by Gaussian noise then various filters are applied to obtain recovered MRI images. After performing filtering operation segmentation has been applied on MRI images to obtain tumour region. The processes have been implemented with the help of MatLab 2018.
Wave Active Low Pass Filter Employing Modern Active Block VDDIBA
Authors: Rana Prerna , Ranjan Ashish
Published: September 2022

This paper presents a second and third-order wave active low pass filter (WALPF) using modern active block Voltage Differencing Differential Input Buffered Amplifier (VDDIBA) with a lower supply voltage of 1V. The wave-active approach is chosen for the filter designing to get a higher order, lower sensitivity, modular and stable filter structure. The design procedure of WALPF involves the implementation of wave-active equivalent for series inductor and shunt capacitor. And it needs to realize the subtractor block physically, and the lossy subtractor integrator block using VDDIBA gives a flavor of differencing voltage property. So, the physical implementation of the subtractor block and the lossy subtractor integrator block goes very smoothly using this block. It is considered a possible reason for reducing active blocks and passive components. Theoretical justification of the proposed WALPF is achieved by using the wave-equivalent concept of the wave-active approach. This method of WAF design consists of only one resistor and capacitor, making the filter structure less complex easy to use with a cut-off frequency of 10MHz. Finally, the workability test is examined with the PSPICE simulation that results in the WALPF frequency response using 180 nm TSMC CMOS technology parameter for VDDIBA.
High Gain CMOS Transimpedance Amplifier For Near Infrared Spectroscopy Applications
Authors: Muthukumaran B. , Ramachandran B.
Published: September 2022

In this paper, design and analysis of High Gain CMOS Transimpedance Amplifier (HGCTIA) is presented which is greatly necessitated for frequency domain functional Near Infrared Spectroscopy (FD-f NIRS). Generally, feedback resistor and drain resistor play a major role in deciding TIA gain and bandwidth. Most of the research work have utilized only feedback resistor and drain resistor. Here, the gain improvement is greatly achieved by replacing the drain resistor by an active inductor which is designed using CMOS transistor. The active inductor loaded based TIA exhibits only 0.01mW power dissipation which is comparatively lesser than previous research works. Also the proposed design achieves maximum value of transimpedance gain 140dB, bandwidth of 10 MHz, where average noise over the bandwidth is 4.6pA/√Hz with 0.68nArms. Input referred noise is 3.38pA/√Hz. These results are obtained by simulating the proposed approach using cadence 45nm technology. The simulated results shows that the proposed HGCTIA is superior in terms of power, gain and bandwidth.
Design and Performance Analysis of Partially Depleted and Fully Depleted Silicon on Insulator MOSFET
Authors: Shashwat  , Singh Adarsh Kumar , Misra Rishabh , Wadhwa Girish , Nirosha R , Agarwal Rajesh
Published: September 2022

In this paper, Partially Depleted Silicon on Insulator (PDSOI) MOSFET and Fully Depleted Silicon on Insulator (FDSOI) MOSFET are designed, and the impact of n-type doping concentration, work function variation, gate oxide, and silicon layer thickness on the performance of the device is studied and analyzed. The floating body and associated kink effects present in a PDSOI device are also investigated in detail. In addition to this, comparisons are made between PDSOI and FDSOI MOSFET to analyze their performance for various device parameters. The threshold voltage rises with increasing Si surface thickness and source doping, according to the data found. The drain current increases as the N-type doping concentration develops in both PD and FDSOI MOSFETs, and conduction begins after a concentration of 3x1017 cm−3 for PD and 2x1017 cm−3 for FDSOI, before which conduction is not effective. For the same n-type doping concentration and gate work function, FDSOI has a higher drain current than PDSOI. FDSOI is better than PDSOI since it eliminates PDSOI’s defects and enhances its performance. The Silvaco Atlas-2D TCAD simulator is used to simulate the device using conventional architecture and models.
Design and Analysis of Partial shading of the PV System Integrated with High-Frequency Inverter and Rectifier Operation for the Electric Vehicle
Authors: Geetha P , Usha S
Published: September 2022

Solar photovoltaic cells are in high demand for sustainable energy generation because of their capacity to provide direct power. As a result, DC-DC converters that can enhance the output voltage and do so reliably while eliminating changes in solar panel outputs are required. Inconsistencies in sun-light availability, ambient temperature, and shadows, among many other considerations, cause the fluctuations. Compared to the typical DC-DC Boost converter, the suggested converter architecture has a higher efficiency of over 95%. In a resonant inductive coupled power transmission system for an electric vehicle, this research demonstrates partial shading of a 250-W PV solar-powered interfaced with a high-frequency resonant full-bridge inverter. The suggested system’s DC input is provided by a PV panel. The ratio of DC Input sources supplied to the high-frequency inverter is 1:3. For a fixed modulation of 0.7, the step modulated for a high-frequency inverter uses a pre-calculated switching angle. Due to a very high-frequency AC connection, the suggested system is more efficient than a traditional system of 50 Hz inverter operation and multiple-output transformer architecture. Zero Voltage Switching (ZVS) is ensured in this study, which decreases switching losses. In the MATLAB/ SIMULINK environment, the suggested approach has been validated. The research aims to investigate and illustrate the effect of partial shading with and without a bypass diode on the I (V) and P (V) properties of solar panels. Hence, the suggested approach’s performance is compared to the present method in terms of parameters, and 95 percent efficiency may be attained. When compared to shaded and unshaded situations, this paper displays greater feature modifications.
Adaptive Central Control Scheme and Investigation of Fault Current Contribution for Protection of Microgrid
Authors: Balasubramanian Sujatha , Preetha Roselyn J. , Srividya K.S.
Published: September 2022

Microgrids suffer from issues namely protection blinding, sympathetic tripping. Microgrids operate in which differs from the conventional power system. Micro-grids operate in grid-connected mode or islanded mode of operation. In islanded mode microgrids utilize distributed energy resources that are renewable such as solar, wind, along with energy storage systems. In both, the modes of the system undergo various challenges such as protection blinding, sympathetic tripping, or short circuit current in power electronic interfaced generation. This work focuses on the analysis of fault in both modes of operation as well as the issues that are specific to a microgrid. Hence adaptive settings of the relay are required to switch over under the different modes of operation. This work utilizes an adaptive central controller for MG protection. Hence the sensed data from the system is fed to the controller and managing the relay operation which is the IDMT relay. This work focuses on the relay setting and plug set for the relays under modes of operation. The detailed analysis is carried out in IEEE 13 bus system and adaptive relay setting calculation for adaptive centralized MG protection is carried out.
Modelling of Vehicle Dynamics and Determination of Energy Demand for Electric Vehicle
Authors: Kubendran V , Mohamed Shuaib Y , Preetha Roselyn J
Published: September 2022

The WLTP Class 3 driving cycle is used in this article for the design of a battery and super-capacitor for electric vehicles. The energy demand for electric vehicle is calculated using WLTP drive cycle and the total power required for electric vehicle is calculated by calculating tractive force. A hybrid energy storage system (HESS) overcomes numerous shortcomings of a battery energy storage system (BESS), including reduced battery life, limited power density, etc. In a proposed system, a Li-Ion battery is coupled with a super-capacitor/Ultra-capacitor as a bidirectional converter, where the Li-Ion battery is the primary energy source, while the Super Capacitor/Ultra-capacitor is an auxiliary energy source. The range of battery and Super Capacitor/ultra-capacitor sizes for Tata Nixon 2020 are calculated and simulated using the MATLAB/SIMULINK environment to verify the efficiency and effectiveness of the proposed model.
Implementation of Quantum Key Distribution network simulation in Quantum Channel
Authors: Praveen Kumar S. , Jaya T. , Rajalingam Prithiviraj
Published: September 2022

The aim is to analyze the efficiency of a communication method, Quantum key distribution. This newly popularized method of communication uses the principles of quantum mechanics. The simulation environment allows researchers to create complex network topologies and a high degree of control and repeatable experiments, allowing them to conduct studies and verify their outcomes. It would be costly to implement QKD in reality, which would need optical and Internet connections between network nodes and the verification of a certain network method or protocol. Thus, the performance analysis here is done in open-source software called NS-3 or Network Simulator- 3, which has an in-built module called QKD netsim for creating the quantum channel.
Campus Routing Using QR Code
Authors: Padmaja M , Geethasri K , Sai Kousik J , Vaishnavi M , Kranthi Sai B , Lokesh Nayak D
Published: September 2022

In today’s modernized world, proficiency is at a step forward expecting the man kind to be in advance. This elevation can be seen in various aspects of diversification which majorly include raising number of Smart cities around us. A smart city explains itself as the one, which consists of complex infrastructures, that takes help of communication technologies to increase operational efficiency. Increasing complexity in the infrastructure of institutions, organizations and even malls, make user more reliant on the navigation services. But these navigational services that are in use today are constrained to open areas. So, this Campus Routing using QR code is proposed, to provide better indoor navigation. It describes development of a web-based application that is designed for providing both outdoor and indoor routing to meet the user’s requirement and the same is extended to implement in exam halls for providing route pictures to students of different rooms. There are various solutions exist in the market for indoor navigation using NFC, Bluetooth, Wi-Fi, GPS, but their reliability at every situation is not ideal. Unlike previously proposed solutions this paper chose a different implementation technique by developing a full stack web application that helps in both indoor and outdoor navigation i.e., it involves creating a client interface at frontend and a server at backend. Maps used here are predefined using Auto-Cad tool, stored in database and are retrieved upon user’s request. These route pictures (Maps) can be accessed by the user through the mobile phone using QR code.
Smart Trolley Application with an Approximate Multiplier Approach Using Embedded Platform
Authors: Maria Dominic Savio M. , Deepa T.
Published: September 2022

Shopping malls, these days, are crowded and many people find it time-consuming and hard to shop. Locating a commodity coupled with standing in long queues for billing looks cumbersome. To overcome these difficulties, the authors of this paper, present the design of the product, smart trolley. When the customer enters the market, he has to log-in to the product and the map of the supermarket is displayed on the LCD screen. Later, once he starts shopping, upon entering each aisle, the details of the products in the aisle are displayed. For billing, the user has to scan the bar code for packed goods and based on the scanned code corresponding to the product, the price is displayed. For unpacked items such as fruits, vegetables etc, a picture of the commodity is taken which is classified with neural networks, the weight of the commodity is measured and the price is calculated with this information. Later, the customer has to click the finish button upon finishing shopping and pay via online transactions. This system design is validated with a prototype that has a camera, transducers, LCD screens RFID readers and raspberry Pi embedded in it. RFID technology is used for location tracking, cameras are used for scanning bar codes (packed goods) and taking snaps of commodities (unpacked) and a force transducer is used for measuring weight. Finally, the database images are multiplied with different level of approximate multipliers and various error level database has been created. The accuracy of all databases is tested with the VGG-16 network.
Using natural language processing to find research topics in Living Machines conferences and their intersections with Bioinspiration & Biomimetics publications
Authors: Carniel Théophile , Cazenille Leo , Dalle Jean-Michel , Halloy José
Published: September 2022

The number of published scientific articles is increasing dramatically and makes it difficult to keep track of research topics. This is particularly difficult in interdisciplinary research areas where different communities from different disciplines are working together. It would be useful to develop methods to automate the detection of research topics in a research domain. Here we propose a natural language processing (NLP) based method to automatically detect topics in defined corpora. We start by automatically generating a global state of the art of Living Machines conferences. Our NLP-based method classifies all published papers into different clusters corresponding to the research topic published in these conferences. We perform the same study on all papers published in the journals Bioinspiration & Biomimetics and Soft Robotics. In total this analysis concerns 2099 articles. Next, we analyze the intersection between the research themes published in the conferences and the corpora of these two journals. We also examine the evolution of the number of papers per research theme which determines the research trends. Together, these analyses provide a snapshot of the current state of the field, help to highlight open questions, and provide insights into the future.
Development of cannabidiol nanoemulsion for direct nose to brain delivery: statistical optimization, in vitro and in vivo evaluation
Authors: Ahmed Bakr , Rizwanullah Md , Mir Showkat Rasool , Akhtar M Shaheer , Amin Saima
Published: September 2022

Cannabidiol (CBD) is a prescribed drug for epilepsy but has low oral bioavailability and gastric instability. Because of the direct link between the nasal cavity and the central nervous system, intranasal administration of CBD as nanoemulsions which are the small sized lipid carriers seem to improve the bioavailability. CBD-nanoemulsions (NEs) were made using Capryol 90, Tween 80, and Transcutol P as oil, surfactant, and co-surfactant, respectively, following aqueous titration approach. Then, using the Box–Behnken design, CBD-NE was statistically optimised for the selection of desirable excipient concentrations in order to create the optimal CBD-NE formulation. As independent variables in the statistical design, Capryol 90 (oil; coded as A), Tween 80 (surfactant; coded as B), and Transcutol P (co-surfactant; coded as C) were used. The dependent variables were droplet size (DS; coded as R
1) and polydispersity index (PDI; coded as R
2). The average DS, PDI, and the zeta potential of the optimized CBD-NEs were observed to be 88.73 ± 2.67 nm, 0.311 ± 0.015, and −2.71 ± 0.52 mV respectively. Pure CBD and lyophilized CBD-NE Fourier-transform infrared spectra demonstrated no physicochemical interaction between excipients and the drug. Furthermore, differential scanning calorimetry and x-ray diffraction measurements revealed the amorphous CBD in the NE. As compared to pure CBD, the optimised CBD-NE showed considerably better in vitro drug release as well as ex vivo nasal permeability. The drug targeting efficiency and direct transport percentage of the optimised CBD-NEs were found to be 419.64% and 76.17%, respectively, in this research. Additionally, pharmacokinetic investigations after intranasal administration of CBD-NE revealed considerably higher drug concentrations in the brain with better brain targeting efficiency. As a result, the development of CBD-NE may be an excellent alternative for better intranasal delivery.
Design, synthesis, and characterization of a novel dual cross-linked gelatin-based bioadhesive for hard and soft tissues adhesion capability
Authors: Pirmoradian Maryam , Hooshmand Tabassom , Najafi Farhood , Haghbin Nazarpak Masoumeh , Davaie Sotoudeh
Published: September 2022

Many surgical treatments require a suitable tissue adhesive that maintains its performance in wet conditions and can be applied simultaneously for hard and soft tissues. In the present study, a dual cross-linked tissue adhesive was synthesized by mixing the gelatin methacryloyl (Gel-MA) and gelatin-dopamine conjugate (Gel-Dopa). The setting reaction was based on a photopolymerization process in the presence of a combination of riboflavin and triethanolamine and a chemical cross-linking process attributed to the genipin as a natural cross-linker. Modified gelatin macromolecules were characterized and the best wavelength for free radical generation in the presence of riboflavin was obtained. Tissue adhesives were prepared with 30% hydrogels of Gel-MA and Gel-Dopa with different ratios in distilled water. The gelation occurred in a short time after light irradiation. The chemical, mechanical, physical, and cytotoxicity properties of the tissue adhesives were evaluated. The results showed that despite photopolymerization, chemical crosslinking with genipin played a more critical role in the setting process. Water uptake, degradation behavior, cytotoxicity, and adhesion properties of the adhesives were correlated with the ratio of the components. The SEM images showed a porous structure that could ensure the entry of cells and nutrients into the surgical area. While acceptable properties in most experiments were observed, all features were improved as the Gel-Dopa ratio increased. Also, the obtained hydrogels revealed excellent adhesive properties, particularly with bone even after wet incubation, and it was attributed to the amount of gelatin-dopamine conjugate. From the obtained results, it was concluded that a dual adhesive hydrogel based on gelatin macromolecules could be a good candidate as a tissue adhesive in wet condition.
Potential benefits of climate change for potatoes in the United States
Authors: Zhao Chuang , Stockle Claudio O , Karimi Tina , Nelson Roger Leroy , van Evert Frits K , Pronk Annette A , Riddle Anne A , Marshall Elizabeth , Raymundo Rubí , Li Yan , Guan Kaiyu , Gustafson Dave , Hoogenboom Gerrit , Wang Xi , Cong Jiahui , Asseng Senthold
Published: September 2022

Potatoes are a mainstay of human diets and 4 million metric tons are produced annually in the United States. Simulations of future crop production show that climate change is likely to reduce the yields of the major grain crops around the world, but the impacts on potato production have yet to be determined. A model ensemble consisting of five process-based and one statistical model was used to estimate the impact of climate change on fully irrigated, well-fertilized potato crop across the USA under the RCP 8.5 scenario of high emissions. Results indicate that increasing temperature will reduce potato yields, but this will be mostly compensated by elevated atmospheric CO2. Yields are predicted to decline with climate change in the current highest-yielding areas, which might experience the highest rises in growing season temperature during short hot summers. Simulated yields increase slightly elsewhere in the southern regions of the USA. Planting potatoes earlier as adaptation to avoid hot summers might improve yields in most regions. Water use by the potato crop is predicted to decline despite higher temperatures, due to a shorter growing season and increased water use efficiency under elevated atmospheric CO2. With higher yields in many regions, crop uptake for (nitrogen + phosphorus + potassium) NPK fertilizer will increase, despite the reduced concentration of nutrients in potatoes due to a growth stimulus from elevated atmospheric CO2. With earlier planting, by 2050 water use will decline by 11.7%, NPK fertilizer uptake will increase by 10.4%, and yields of slightly less nutritious potatoes will increase by 14.9% nationally.
The strong role of external forcing in seasonal forecasts of European summer temperature
Authors: Patterson Matthew , Weisheimer Antje , Befort Daniel J , O’Reilly Christopher H
Published: September 2022

Since the 1980s, external forcings from increasing greenhouse gases and declining aerosols have had a large effect on European summer temperatures. These forcings may therefore provide an important source of forecast skill, even for timescales as short as a season ahead. However, the relative importance of external forcings for seasonal forecasts has thus far received little attention, particularly on a regional scale. In this study, we investigate forcing-induced skill by comparing the near-surface temperature skill of a multi-model ensemble of seasonal predictions from the Copernicus Climate Change Service archive to that of an uninitialised ensemble of Coupled Model Intercomparison Project phase 6 projections for European summers (June–July–August) spanning the years 1993–2016. As expected, predictive skill over southern Europe is larger for initialised seasonal predictions compared to uninitialised climate projections. However, for northern Europe, we find that predictive skill is generally small in current seasonal models and surprisingly even smaller compared to uninitialised climate projections. These results imply that further research is necessary to understand the role of external forcing on seasonal temperature variations over Europe.
Deep learning technique for examining the mechanism, transport, and behavior of oil-related hazardous material caused by wave breaking and turbulence
Authors: Fang Shibiao , Lin Mu , Jia Sen , Liu Kuan , Liu Darong
Published: September 2022

A marine oil spill produces oil-related hazardous material (OHM) which can cause damage to the marine ecological environment, and seriously affect coastal economic development such as tourism and aquaculture. The turbulent momentum and energy generated by the wave breaking process have a significant effect on accelerating the mixing of OHM and seawater, which is one of the main factors in oil becoming sunken or submerged. In order to explore the influence of offshore wave breaking on the formation and transportation of OHM, the wave breaking process was simulated in a 2D laboratory flume, and the behavior process of OHM was identified and tracked in this paper. Five groups of breaking waves of different significant wave height (SWH) were set up in the experiment, and then OHM with the same density and mass was added, respectively, in order to observe the sinking process under the action of wave-induced turbulence. The results show that the turbulence intensity is closely related to the phase of the wave, the turbulence activity is violent at the wave crest, and the vertical distribution of the turbulent energy dissipation rate in the turbulent mixing zone remains basically unchanged. Under the actions of wave breaking and turbulence, the OHM’s submergence depth shows a good binomial growth trend. For SWH = 12.45 cm, the OHM stays under the water for nearly 2.32 s, and it reaches the deepest position of 0.165 m. Compared with SWH = 12.45 cm, the submergence depths for waves with SWHs of 20.61 cm, 26.81 cm, 32.32 cm, and 36.54 cm are increased by 8%, 37%, 80%, and 159%, respectively. Then, the submergence depths due to the other four waves are increased progressively, and the growth rates are 8%, 26%, 31%, 44%, respectively (compared with the same period of the previous wave).
Resetting photons
Authors: Freire Oliveira Guilherme Eduardo , Maes Christian , Meerts Kasper
Published: September 2022

Starting from a frequency diffusion process for a tagged photon which simulates relaxation to the Planck law, we introduce a resetting where photons lower their frequency at random times. We consider two versions, one where the resetting to low frequency is independent of the existing frequency and a second case where the reduction in frequency scales with the original frequency. The result is a nonlinear Markov process where the stationary distribution modifies the Planck law by abundance of low-frequency occupation. The physical relevance of such photon resetting processes can be found in explorations of nonequilibrium effects, e.g., via random expansions of a confined plasma or photon gas or via strongly inelastic scattering with matter.
The SAGEX review on scattering amplitudes Chapter 10: Selected topics on modular covariance of type IIB string amplitudes and their

N=4

supersymmetric Yang–Mills duals
Authors: Dorigoni Daniele , Green Michael B , Wen Congkao
Published: September 2022

This article reviews some results of the SAGEX programme that have developed in the understanding of the interplay of supersymmetry and modular covariance of scattering amplitudes in type IIB superstring theory and its holographic image in

N
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4

supersymmetric Yang–Mills theory (SYM). The first section includes the determination of exact expressions for BPS interactions in the low-energy expansion of type IIB superstring amplitudes. The second section concerns properties of a certain class of integrated correlators in

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4

SYM with arbitrary classical gauge group that are exactly determined by supersymmetric localisation. Not only do these reproduce known features of perturbative and non-perturbative

N
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SYM for any classical gauge group, but they have large-N expansions that are in accord with expectations based on the holographic correspondence with superstring theory. The final section focusses on modular graph functions. These are modular functions that are closely associated with coefficients in the low-energy expansion of superstring perturbation theory and have recently received quite a lot of interest in both the physics and mathematics literature.