bluuebunny/crossref_metadata_2025_split huggingface dataset:
Absolute beam monitor: A novel laboratory device for neutral beam calibration
Authors: Gasser Jonathan , Galli André , Wurz Peter 
Published: September 2022

Instruments recording Energetic Neutral Atoms (ENAs) for space applications require thorough laboratory calibration in a dedicated test facility providing a neutral atom beam. Accurate knowledge of the neutral beam intensity and energy is central for the laboratory calibration procedure. However, until recently, the quantification of the neutral atom beam intensity in the low-energy range below a few 100 eV was based on relative measurements with standard detectors of approximately known detection efficiencies for neutral atoms. We report on the design and development of a novel calibration device dedicated to determining the ENA beam flux in an absolute manner in the energy range from 3 keV down to about 10 eV. This is realized by applying ENA scattering at a surface and coincident detection of scattered particles and created secondary electrons. Moreover, the neutral beam energy is determined by a time-of-flight measurement. The applied measurement principle relies on very low background signals. The observed background count rates are in the range 10−2 s for the individual channels and about 10−5 s for coincidence events. The background is, thus, at least two, typically four, orders of magnitude lower than the signal rate for neutral atom beams in the foreseen energy range. We demonstrate a concrete application using the absolute flux calibration of a laboratory neutralization stage.
A high-power long lifetime beam dump for the Thomson scattering diagnostic system in the XuanLong-50 experiment
Authors: Liu J. H. , Li S. J. , Li H. Y. , Xie Q. F. , Bai R. H. , Bo X. K. , Deng B. H. 
Published: September 2022

The Energy iNNovation’s XuanLong-50 is a spherical torus experiment with up to 10 s plasma operation duration. A 3 J/50 Hz pulsed laser is used in the Thomson scattering diagnostic system that is developed to measure the time evolutions of plasma electron temperature and density profiles. The expected laser pulse number is about 7.5 × 106/year with a power load of 150 W. To meet at least 1-year lifetime requirement, a Chevron type beam dump with polished molybdenum plates is designed and fabricated, which absorbs the laser beam energy in a 3D structure to reduce the laser fluence deposited on the material surface. To prevent the backscattered stray light from interfering with the Thomson scattering measurements, a 7.5 m beam path with folding mirrors is set between the beam dump and the plasma scattering volumes. Details of the beam dump design procedure including the laser beam profile control, multi-pulse laser damage threshold, heat dissipation, Zemax modeling, folding mirror selection, and beam path enclosure are presented together with the testing results.
Hydrogen separation with a graphenylene monolayer: Diffusion Monte Carlo study
Authors: Lee Gwangyoung , Hong Iuegyun , Ahn Jeonghwan , Shin Hyeondeok , Benali Anouar , Kwon Yongkyung 
Published: September 2022

We performed fixed-node diffusion Monte Carlo (DMC) calculations to investigate structural and energetic properties of graphenylene (GPNL), a two-dimensional network of sp2-bonded carbon atoms with large near-circular pores, and its H2 separation performance for gas mixtures. We have found that the energetic stability of a GPNL monolayer is comparable to that of γ-graphyne, as evidenced by its large cohesive energy of 6.755(3) eV/atom. Diffusion barriers of several gas molecules, including hydrogen, through a GPNL membrane were determined from the analysis of their adsorption energies depending on the adsorption distance, which led to our estimation for hydrogen selectivity with respect to other target molecules. DMC hydrogen selectivity of a GPNL monolayer was found to be exceptionally high at 300 K, as high as 1010–1011 against CO and N2 gases. This, along with high hydrogen permeance due to its generic pore structure, leads us to conclude that GPNL is a promising membrane to be used as a high-performance hydrogen separator from gas mixtures. We find that when compared to our DMC results, DFT calculations tend to overestimate H2 selectivity, which is mostly due to their inaccurate description of short-range repulsive interactions.
How useful? How important? How difficult?
Authors: Dorer Brita 
Published: September 2022

Abstract
English ‘gradation’ expressions—the interrogative adverb how followed by an adjective or an adverb—are frequent in questionnaires and they are not straightforward to translate into French. A good translation approach is needed, and there are mainly two options: The recommended approach involves the French adverbs à quel point or dans quelle mesure. The second approach uses a direct question, and the gradation occurs by choosing one of several options in the pre-established answer scale. Could there be a link between questionnaire translators’ expertise and the way they handle these translations, both the product and the process? This exploratory project studied six professional questionnaire translators, whose performance was recorded with concurrent think-aloud and keylogging techniques, and then triangulated. Correlations were analysed qualitatively. The results revealed a link between the questionnaire translators’ expertise and their translations. This confirms the importance of relying on expert translators and further briefing and training them to become good questionnaire translators.
Revealing the influence of carbon on shear-coupled grain boundary migrationin α-iron via molecular dynamics simulations
Authors: Wang Chang , Wang Yi , Yu Zheteng , Yin Jian , Lai Wensheng 
Published: September 2022

Abstract
Shear-coupled grain boundary (GB) migration is of importance theoretically on the mechanisms of GB behaviors and application oriented on the development of novel processing methods by plastic deformation. We demonstrate via molecular dynamics simulations that the interstitial species carbon may affect the shear-coupled migration in α-iron strongly. The impact of carbon selectively takes effect depending on the variety of grain boundaries. Specifically, the coupling factor of the Σ9(221) GB is increased in the presence of carbon. While the carbon effect is inactive for the Σ17(223) GB. The influence of carbon is revealed to be connected with the disconnection modes of grain boundaries. The results of the work implicate correlations between the carbon enrichment and the final microstructure after severe plastic deformation.
Spectral estimation for Hamiltonians: a comparison between classical imaginary-time evolution and quantum real-time evolution
Authors: Stroeks M E , Helsen J , Terhal B M 
Published: September 2022

Abstract
We consider the task of spectral estimation of local quantum Hamiltonians. The spectral estimation is performed by estimating the oscillation frequencies or decay rates of signals representing the time evolution of states. We present a classical Monte Carlo (MC) scheme which efficiently estimates an imaginary-time, decaying signal for stoquastic (i.e. sign-problem-free) local Hamiltonians. The decay rates in this signal correspond to Hamiltonian eigenvalues (with associated eigenstates present in an input state) and can be extracted using a classical signal processing method like ESPRIT. We compare the efficiency of this MC scheme to its quantum counterpart in which one extracts eigenvalues of a general local Hamiltonian from a real-time, oscillatory signal obtained through quantum phase estimation circuits, again using the ESPRIT method. We prove that the ESPRIT method can resolve S = poly(n) eigenvalues, assuming a 1/poly(n) gap between them, with poly(n) quantum and classical effort through the quantum phase estimation (QPE) circuits, assuming efficient preparation of the input state. We prove that our MC scheme plus the ESPRIT method can resolve S = O(1) eigenvalues, assuming a 1/poly(n) gap between them, with poly(n) purely classical effort for stoquastic Hamiltonians, requiring some access structure to the input state. However, we also show that under these assumptions, i.e. S = O(1) eigenvalues, assuming a 1/poly(n) gap between them and some access structure to the input state, one can achieve this with poly(n) purely classical effort for general local Hamiltonians. These results thus quantify some opportunities and limitations of MC methods for spectral estimation of Hamiltonians. We numerically compare the MC eigenvalue estimation scheme (for stoquastic Hamiltonians) and the quantum-phase-estimation-based eigenvalue estimation scheme by implementing them for an archetypal stoquastic Hamiltonian system: the transverse field Ising chain.
Human Violence Detection Using Deep Learning Techniques
Authors: Arun Akash S A , Sri Skandha Moorthy R , Esha K , Nathiya N 
Published: September 2022

Abstract
The world’s average annual fatality rate from human violence is 7.9 per 10,000 people. Most of this human violence takes place in an isolated area or of sudden. The information delay here is a major impediment in stopping these acts. To thrive on this issue, the detection technique is used in this study. Detecting moving objects from CCTV is one of the most effective computer vision algorithms. CCTV cameras are now in every streets which are extremely helpful in solving cases. Some techniques of deep learning are used as computer vision to predict and detect the action, properties from video. In real-time police reach violent destinations and start checking CCTV cameras, and investigate to proceed further. This study is deliberately designed to detect violent acts from CCTV cameras. The Inception – v3 and Yolo – v5 models detect the violent act, the number of persons involved, and also the weapons used in the situation. The study consists of these deep learning models, which are used to form a video detection system. This model can be used in real-time as an application programming interface (API) or software. The study results showed the proposed model achieves an accuracy of 74%.
Exoskeleton Device For Left Hemiplegia Patients With Electromyograph
Authors: Nithyaa A N , Premkumar R , Gokul M , Iswarya C , Lakshmi Priya S 
Published: September 2022

Abstract
Loss of motion is a condition in which muscle activity in a part of the body is lost; it is also known as paralysis. Loss of motion is most commonly caused by a severe stroke, in which the blood supply to a portion of the cerebrum is cut off. Hemiplegia is a sort of loss of motion which influences half of the body, i.e., one arm and one leg of same side of the body will not be functioning. Normally, left hemiplegia is a severe disease caused by a lack of blood supply to the cerebrum’s right hemisphere. Fixed frameworks, such as Lokomat, are used in rehabilitation centres to assist patients in resuming their normal activities. However, the results provided by those frameworks are extremely time-consuming and will only benefit patients who can walk on a treadmill. However, these frameworks are not portable and cannot be used for home or day-to-day exercises. To overcome these disadvantages, this paper presents the ergonomic framework, which includes an exoskeleton that guides and assists in the development process of the left upper arm. The entire framework is powered by a compatible and miniaturized motor via a microcontroller, which aids in the development of patient flexion and augmentation. Meanwhile, EMG acquisition would be done by putting flexible pre-gelled electrodes to know the recuperation of physiological neuro-muscular activities of the subject.
GPU based epileptic seizure detection using deep autoencoder with particle swarm optimization
Authors: Sinha Dipali , Sasirekha K. , Thangavel K. 
Published: September 2022

Abstract
Epilepsy is a long-term neurodegenerative disorder that impacts the brain and causes at least two gratuitous convulsions. It is frequently diagnosed using electroencephalograms (EEG). Existing models were unable to accurately predict the seizure due to the signal’s non-stationary nature. Deep learning techniques have recently gotten a lot of attention from researchers working on a variety of signal processing problems. A deep learning approach was used in this analysis to retrieve relevant features from a raw form EEG signal. Furthermore, the metaheuristic swarm-based algorithm to optimize the deep autoencoder’s hyperparameters. Experiments are carried out on Bonn dataset with the CUDA-enabled GPU version P100. To assess the efficacy of the constructed model, the computational results are compared to other benchmark classifiers and obtained the accuracy of 93.6%.
Voice controlled home automation, security system and virtual joystick-controlled robot for patients in home quarantines
Authors: Vighnesh M , John Andrew , Shibu Merin , Jagannath M 
Published: September 2022

Abstract
The threat of COVID-19 is increasing by the day, while those who are infected must quarantine immediately. Since the disease is lethal and spreads by direct or indirect human contact, it is critical to disinfect all contact surfaces on a regular basis. Since continual direct exposure to chemicals promotes antibiotic resistance, it is less likely to be considered as a long-term solution. As COVID-19 had such a negative impact on people’s health, even regular commuting inside the house became a difficult and time-consuming activity for a variety of reasons, including the fact that the person is isolated alone and has a strong inclination to leave things neglected. This paper consists of a quarantine home automation system that allows the user to remotely turn on and off the appliances in the room as well as monitor the temperature in the rooms. The proposed system has incorporated an intruder alarm system, which sends notifications to the user’s mobile phone whenever some unexpected movement is detected near the entrance. The entire system is voice-enabled, which means that instead of completing the work manually, the user may give Alexa the directions. The quarantine home automation system also includes a robot that can be operated by the user virtually using the joystick present in the common user interface.
Design of an automated oxygen flow control system for hypoxemic patients
Authors: Krishnakumar S , Sabarivani A , Grace Kanmani Prince P , Robinson Sheryl , Kumar Aishwarya Mohan , Janney JB , Lumen Christy V 
Published: September 2022

Abstract
Hypoxemia is a condition for which there is a lack of sufficient oxygen in the blood. Which might range from minor issues like dizziness and shortness of breath to more severe problems like interfering with heart and brain functions. The amount of oxygen in a person’s blood indicates how efficiently the body transports oxygen from the lungs to the cells. The present research aims to design continuously monitor the blood oxygen level and to regulate the opening and closing of the oxygen flow meter valve using a servo motor. If the blood oxygen level is normal, the valve remains closed. If the blood oxygen level falls below the normal range, the valve is opened. The system employs a SpO2 sensor for monitoring the heart rate and oxygen saturation. The output of the sensor is sent to the microcontroller that comes up with an in-built analog to digital converter. Servo motor is utilized to control the flow meter valve to deliver the required oxygen to the patient during abnormal detection of blood oxygen saturation level. When the blood oxygen level falls below 94%, the oxygen valve is opened to allowing for oxygen flow. The blood oxygen level detected as normal that is 97% and hence the oxygen flow is at off state. The output is sent to an LCD unit, which keeps track of the SpO2 level. This microcontroller-based oxygen supply control device can prevent the adverse effects of hypoxemia. The present research reduces the time and a caretaker requirement to oxygenate the patient by providing controlled delivery system.
Prosthetic Arm with Functional Fingers and Wireless Recharge on Walk Function
Authors: Bharathan Abhijeet , Premkumar J. , Sudhakar T , Bethanney Janney J , Sindu  
Published: September 2022

Abstract
The efficiency, tactile features, and weight of prosthetic limbs have all improved over time, but the long charging period that comes with these benefits reduces their overall appeal. The purpose of this study is to incorporate a portable power source into the prosthetic arm in order to decrease downtime and increase reliability. The use of special footwear that serves as a regenerative power source for the prosthetic arm’s battery, a piezoelectric generator that generates energy while walking, and a charging station that transfers power directly to the prosthetic arm while on the move. The complete device allows the user to comfortably use the prosthetic arm for longer periods of time.
Design of transfemoral prosthesis for above the knee amputees
Authors: Kesavapuram Sreya Reddy , Dhanalakshmi M 
Published: September 2022

Abstract
Transfemoral amputation is a condition where the person above the knee area is amputated due to some infection, cancer or trauma. Due to this their mobility is eminently compromised, their lifestyle gets affected and also the individual’s self-confidence is distraught. The only way to aid this condition is to provide a prosthetic to provide support and mitigate easy movement. Usually, prosthetics are not selected due to high cost. In India there are around two lakh thirty thousand amputees in need of prosthetic care but are hesitant to opt for one, for the reason that they are expensive. Most of them go for cosmesis due to this demographic. In this work, we focus on developing a mechanical knee joint prosthesis where the pylon or the shank is replaced by a shock absorber in order to reduce the transient mechanical force acting on the artificial leg. By replacing the basic design with the shock absorber, it also enables the subject to perform other activities such as jumping and jogging with ease as the force is dispersed evenly on the prosthesis. In this we also perform von mises analysis, strain analysis and displacement analysis and carry through a comparative analysis between two commonly used materials in making the prosthetic against carbon fibre and prove the efficacy of carbon fibre.
Detection of Anaemia using Image Processing Techniques from microscopy blood smear images
Authors: Nithya R , Nirmala K 
Published: September 2022

AbstractThe human blood includes Red blood Corpuscles (RBC), White Blood Corpuscles (WBC), platelets and plasma. The status of one’s health is determined by a complete blood count, therefore segmentation and identification of blood cells are critical. A Complete Blood Count (CBC) is a test that counts all of the cells in the body to assess a person’s health. The RBC and WBC count are vital in diagnosing disorders such as anaemia, leukaemia, tissue damage, and so forth. This paper focuses mainly on RBC counting and the detection of abnormality, anaemia based on the count of RBCs from a peripheral blood smear using digital image processing techniques. Anemia is an indicator, and the most important one at that, for many other diseases. Therefore, basic screening of anemia is very important, especially in regions prone to poverty. Malnutrition due to poverty is the major cause for anemia. The paper presents an algorithm to automatically count the RBCs present in the blood of a person. The count of RBC, in 1 microlitre if blood is considered and it is observed how the count varies in normal blood smears and the anemic blood smears. In remote places, where a lot of people are to be screened, using cell counters and hemocytometer is not feasible. A faster method of counting is one of major demand. Therefore, to reduce the computation time, an algorithm in digital image processing is developed to compute the number of red blood cells. Although anemia is a vast subject and there are various different characteristics to consider, this is a humble approach to automate the counting of the RBCs which would be useful for future research purposes.
Fully printed ZnO-based valency-change memories for flexible and transparent applications
Authors: Delfag Mohamed , Rachovitis Georgios , González Yoandris , Jehn Johannes , Youssef Azza Hadj , Schindler Christina , Ruediger Andreas 
Published: September 2022

Abstract
Printable and flexible memory devices have attracted a great deal of attention in several emerging technological applications for the development of flexible electronics, such as interconnections/wearables/smart devices for the internet of things (IoT). In this work, we report on the fabrication of flexible, transparent, and fully inkjet-printed resistive random access memory (ReRAM) cells using poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS)/ZnO/PEDOT:PSS structures. The electrical characteristics were studied, including the determination of space charge limited conduction (SCLC) as the dominant charge transport mechanism. In addition, the bending performance and the transparency of the devices was tested in order to confirm the reliable operation and reproducibility of the cells. The switching for the printed structures of PEDOT:PSS/ZnO/PEDOT:PSS was led through the formation and dissolution of a stable oxygen vacancy filament, as confirmed by conductive atomic force microscopy. While the conduction mechanism for the high resistance state (HRS) was attributed to the SCLC mechanism. The switching of the memory cells, their endurance and retention properties were analysed and indicated the stability of the HRS and low resistance state for more than 104 cycles and 105 s comparable to ZnO-based ReRAM produced by clean-room techniques. The study of the mechanical flexibility of the cells shows that up to 700 bending cycles can be reached without significantly changing the switching characteristics.
P-type conductivity in Sn-doped Sb2Se3
Authors: Hobson Theodore D C , Shiel Huw , Savory Christopher N , Swallow Jack E N , Jones Leanne A H , Featherstone Thomas J , Smiles Matthew J , Thakur Pardeep K , Lee Tien-Lin , Das Bhaskar , Leighton Chris , Zoppi Guillaume , Dhanak Vin R , Scanlon David O , Veal Tim D , Durose Ken , Major Jonathan D 
Published: September 2022

Abstract
Antimony selenide (Sb2Se3) is a promising absorber material for thin-film photovoltaics. However, certain areas of fundamental understanding of this material remain incomplete and this presents a barrier to further efficiency gains. In particular, recent studies have highlighted the role of majority carrier type and extrinsic doping in drastically changing the performance of high efficiency devices (Hobson et al 2020 Chem. Mater.
32 2621–30). Herein, Sn-doped Sb2Se3 bulk crystals are shown to exhibit p-type conductivity using Hall effect and hot-probe measurements. The measured conductivities are higher than those achieved through native defects alone, but with a carrier density (up to 7.4 × 1014 cm−3) several orders of magnitude smaller than the quantity of Sn included in the source material. Additionally, a combination of ultraviolet, x-ray and hard x-ray photoemission spectroscopies are employed to obtain a non-destructive depth profile of the valence band maximum, confirming p-type conductivity and indicating a majority carrier type inversion layer at the surface. Finally, these results are supported by density functional theory calculations of the defect formation energies in Sn-doped Sb2Se3, showing a possible limit on the carrier concentration achievable with Sn as a dopant. This study sheds light on the effectiveness of Sn as a p-type dopant in Sb2Se3 and highlights avenues for further optimisation of doped Sb2Se3 for solar energy devices.