bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developing the Functional Relation of Input parameters in single-point incremental forming through Dimensional Analysis
Authors: oraon manish , sharma vinay 
Published: September 2022

Abstract
The system is designed with the basics of fundamental units termed dimensional analysis (DA). The fundamental units are modeled to figure out some quantitative measures without the knowledge of the system behavior. Subsequently, the dimension analysis-based modeling helps to develop the functional relation of input parameters for the set objectives. The generalized model is validated with the output of experiments with an agreement to adopt the model within a certain range of error. Single Point Incremental Forming (SPIF) is an innovative sheet metal forming technique in which the forming of metal sheets to the desired shape without using dedicated dies. The SPIF investigations and declared results are desperately waiting for its industrial acceptability but yet the optimization of the process is absent. The current study is to develop the functional relation of input parameters of SPIF through dimensional analysis. Multiple input parameters such as step-down size, diameter and area of forming tool, feed rate of the tool, the ultimate tensile strength of the blank (metal sheet) and density of blank, lubricants, rotational and transverse speed of forming tool are taken for experiments as well as model development. The model confirmed the functional relation of step-down size and area of tool end for surface roughness. Similarly, UTS of the blank (σ), thickness of the metal sheet (t), and tool end diameter (d) is observed as the prominent parameters for vertical force (Fz) whereas the step-down size (Δz) are dominate inversely the Fz-value. The acceptable limit of mean error for Ra and Fz is noted as 6.136nm and 2.044N respectively. The modified i.e. best fitted Ra and Fz are lower than the experimental and ANN values.
Imaging the field inside nanophotonic devices
Authors: Fishman Tal , Haeusler Urs , Dahan Raphael , Yannai Michael , Adiv Yuval , Abudi Tom , Shiloh Roy , Eyal Ori , Yousefi Peyman , Eisenstein Gadi , Hommelhoff Peter , Kaminer Ido 
Published: September 2022

Abstract
Controlling optical fields on the subwavelength scale is at the core of any nanophotonic device. Of particular interest are nanophotonic particle accelerators that promise a compact alternative to conventional radiofrequency-based accelerators. Efficient electron acceleration in such compact devices critically depends on achieving nanometer control of electron trajectories by precisely designed optical nearfields inside the device. However, these nearfields have so far been inaccessible due to the complexity of the devices and their geometrical constraints, hampering efforts to design and optimize future nanophotonic particle accelerators. Here we present the first measurement of the field distribution inside a nanophotonic accelerator. We develop a novel microscopy approach based on photon-induced nearfield electron microscopy (PINEM) to achieve frequency-tunable deep-subwavelength imaging of the nearfield inside nanophotonic accelerators. We compare the two leading designs of nanophotonic accelerators, also known as dielectric laser accelerators (DLAs): a dual-pillar structure with distributed Bragg reflector and an inverse-designed resonant structure. Our experiments are complemented by full 3D simulations, unveiling surprising deviations from the expected designs, showing complex field distributions related to intricate 3D features in the device and its fabrication tolerances. We further envision a tomography method to image the 3D field distribution, key for the future development of high-precision and hence high-efficiency DLA devices as well as other nanophotonic devices.
Localised Thermal Levering Events Drive Spontaneous Kinetic Oscillations in Catalysis
Authors: Decarolis Donato , Panchal Monik , Quesne Matthew , Mohammed Khaled , Xu Shaojun , Isaacs Mark , Keenan Luke , Wakisaka Takuo , Kusada Kohei , Kitagawa Hiroshi , Catlow C. Richard , Gibson Emma , Goguet Alexandre , Wells Peter 
Published: September 2022

Abstract

Unravelling kinetic oscillations, that arise spontaneously during catalysis, has been a challenge for decades; not only to understand these complex phenomena but also in an aim to exploit kinetics at the peak maxima. In this study, through temporally and spatially resolved operando analysis, we demonstrate that CO oxidation over Rh/Al2O¬3 involves a series of thermal levering events – CO oxidation, Boudouard reaction, and carbon combustion – which drive oscillatory CO2 formation. This catalytic sequence relies on harnessing localised temperature episodes at the nanoparticle level that provides an efficient means to drive unfavourable reactions, where the macroscopic conditions do not allow. This insight provides a new basis for coupling thermal events at the nanoscale for efficient harvesting of energy, essential for emerging net-zero carbon technologies.
Detection and recognition based on machine learning and deep learning for Morse signal in wide-band wireless spectrum
Authors: Gao Zhenbin , Zhang Yi , Su Shaoying , Liu Jinyuan 
Published: September 2022

Abstract
Morse code radio communication is one of the indispensable shortwave communication methods, but the automatic receiving effect is poor. The accuracy and speed of detection and recognition, in the environment of neighborhood interference and low signal-to-noise ratio (SNR), cannot meet the practical requirements, which is a problem that needs to be solved. Combined with machine learning and deep learning, we propose an automatic Morse signal detection and recognition algorithm based on the ED-FE-CCBC structure. First, based on the time-frequency spectrum, the radio audio signal is adaptively energy sorted, and the target signal is detected according to the characteristics of bandwidth, windowed standard deviation, etc., and its frequency points are calculated. Then, narrow-band digital filtering is performed on the original audio signal with this frequency point as the center frequency, the target signal frequency band is re-extracted on the time-frequency spectrum after noise reduction, and the frequency spectrum is enhanced by pseudo-color. Finally, the pseudo-color image is put into the proposed network for identification and to realize end-to-end decoding. To evaluate the algorithm’s effectiveness, we use two parts of the data of simulation signal and professional training terminal audio to conduct experiments. The results show that in a complex channel environment, the ED-FE-CCBC algorithm can effectively detect and recognize Morse signals. While ensuring real-time performance, the recognition accuracy is better than the most advanced methods.
AI Business Models: A Strategic Business Dynamics
Authors: Mishra Shrutika , Mishra Priyanshu 
Published: September 2022

Abstract
A lot of research has been done recently in evolving the artificial intelligence business model framework. However, one issue is still undeveloped, immature to understood, even it has vital for budding and progressive managers, policy decision makers, and academics alike, namely, how businesses transform and develop their AI business models framework to accomplish continuous value formation. Businesses which achieve to make value over prolonged stages of time effectively figure, acclimate and recommence their business models with AI technology to fuel such value formation. Sketch on verdicts from a research program on uninterruptedly buddingbusinesses. This paper categorizes three perilouscompetences, namely an alignment towards investigating with and manipulatinginnovative business openings; a well-adjusted use of properties; as well as attaininglucidity between management, ethos, and member of staff obligations, together decisive key maneuveringschedules. We conclude the paper by signifyingconsequences for AI business model framework research and experts, providing a tool for executives which permits them to reproduce on and classifyperilousproblems relevant for shifting and emerging their business model to sustain value creation. In this paper we are trying to explore the keys of Business Model Framework with revolutionizes business market ecosystem.
Genetic Diversity of the Camellia oleifera Abel. Germplasm and Development of a Core Collection Using Simple Sequence Repeat Markers
Authors: Wang Pengliang , Su Jiexa , Wu Hongying , Chen Yuansong , Xie Yayu , Wang Huayu , He Guizheng , Chen Naiming , Wei Changjiang , Yang Liping , Zhang Zhaoyuan 
Published: September 2022

Abstract
Camellia oleifera is an important oilseed crop. With the increasing attention given to C. oleifera, germplasms have been collected, and banks have recently been established or renewed. The lack of knowledge of genomic SSRs, limited investigation into the genetic diversity of the germplasm bank, and lack of a core collection have hindered the breeding of oil tea. Therefore, genomic libraries were constructed and sequenced, and all clean reads were assembled into 673,863 unigenes. In total, 27,953 SSRs were detected from all the unigenes, and 17,517 SSR primer pairs were successfully designed. Furthermore, we re-evaluated the genetic diversity of the germplasm bank of C. oleifera using 22 SSR markers. The number of alleles (Na) ranged from 4 to 25, with an average of 11.41; the effective number of alleles (Ne) ranged from 2.014 to 9.284, with an average of 4.800; the Shannon index (I) ranged from 0.716 to 2.471, with an average of 1.682; and the polymorphic information index (PIC) ranged from 0.380 to 0.883, with an average of 0.717. Finally, a core collection consisting of 45 samples (15% of the 300 trees in the entire germplasm bank) was developed, the genetic diversity parameters of which showed nonsignificant differences from the entire germplasm bank. Genomic SSR development, the re-evaluation of genetic diversity and the development of a core collection from the germplasm bank in this study provided useful tools, abundant genetic resources and an effective collection for the utilization and deep exploration of C. oleifera.
“Because I Agree With Him”: The Impact Of Middle-School Students’ Prior Attitude On The Evaluation Of Source Credibility When Watching Videos
Authors: Lescarret Colin , Magnier Julien , Floch Valérie Le , Sakdavong Jean-Christophe , Boucheix Jean-Michel , Amadieu Franck 
Published: September 2022

Abstract
The purpose of this study was to assess the impact of young students' prior attitude on source consideration when watching videos on controversial topics. 271 seventh graders watched a series of videos in which two interviewees (one expert in the field, one layperson) expressed divergent positions on a socioscientific issue ("Will organic farming be able to feed the entire world population by 2050?"). After watching the videos, students were asked to recall the identity and arguments of the interviewees and indicate how far they had perceived them to be credible and convincing. If no effect of students' prior attitude was found on source recall, students were prompt to judge the interviewee who provided arguments that were congruent with their prior attitude as more credible and convincing that the interviewee that provided incongruent arguments. These results suggest that young students' beliefs contribute to their assessment of the credibility of an information source when watching videos.
The effect of an abdominal drawing-in maneuver with real-time visual biofeedback on muscle activity in young adults
Authors: Kantha Phunsuk , Sakulsriprasert Prasert , Wattananon Peemongkon 
Published: September 2022

Abstract
Background
The abdominal drawing-in maneuver (ADIM) is a core stability exercise through the activation of the transversus abdominis and internal abdominal oblique (TrA/IO). However, controlling muscle activity of TrA/IO is difficult, especially when combined with other exercises. It has been proposed that real-time visual biofeedback (RVBF) can increase muscle activation but it has not been investigated in standing and lunge positions.
Objectives
This study aimed to investigate the effect of ADIM with RVBF on muscle activity during standing and lunge positions.
Methods
Twelve young adults (21.5 ± 2.1 years) were recruited for this study. Surface electromyography (EMG) was attached to 1) TrA/IO; 2) lumbar multifidus (LM); 3) lumbar erector spinae (LES); 4) gluteus medius (GMed); and 5) gluteus maximus (GMax) during ADIM and without ADIM (no-ADIM). Those data were processed and reported as a percentage of maximal voluntary isometric contraction (%MVIC). The RVBF was used to provide feedback to participants during ADIM in both standing and lunge positions.
Results
During standing position, the ADIM of about 24.92%MVIC of TrA/IO can increase the muscle activity of LM (p < 0.01), LES (p < 0.01), and GMed (p = 0.02) when compared to no-ADIM. During lunge position, the ADIM of about 25.48%MVIC of TrA/IO can increase the muscle activity of GMax (p < 0.01) when compared to no-ADIM.
Conclusions
ADIM of about 25%MVIC of TrA/IO is sufficient to improve back and hip muscle activity. Therefore, we recommended ADIM with RVBF when exercising in the standing and lunge positions.
Designing breathing air-electrode and enhancing the oxygen electrocatalysis by thermoelectric effect for efficient Zn-air batteries
Authors: Zheng Xuerong , Cao Yanhui , Han Xiaopeng , Wang Haozhi , Zhang Zhao , Zhao Menghan , Li Jihong , Wang Yang , Wang Jiajun , Wang Yuesheng , Zhang Li , Zaghib Karim , Deng Yida , Hu Wenbin 
Published: September 2022

Abstract
The sluggish kinetics and mutual interference of oxygen evolution and reduction reactions (OER and ORR) in the air electrode resulted in large charge/discharge overpotential and low energy efficiency of Zn-air batteries. In this work, we designed a breathing air-electrode configuration in Zn-air batteries using P-type Ca3Co4O9 and N-type CaMnO3 as charge and discharge thermoelectrocatalysts, respectively. The Seebeck voltages generated from thermoelectric effect of Ca3Co4O9 and CaMnO3 synergistically compensated the OER and ORR overpotentials. The carrier migration and accumulation on the cold surface of Ca3Co4O9 and CaMnO3 optimized the electronic structure of metallic sites and thus enhanced their intrinsic catalytic activity. The OER and ORR overpotentials were enhanced by 101 and 90 mV, respectively, at temperature gradient of 200 ℃. The breathing Zn-air battery displayed a remarkable energy efficiency of 68.1%. This work provides an efficient avenue towards utilizing waste heat for improving the energy efficiency of Zn-air batteries.
Correlation between Harris Hip Score and gait analysis through Artificial Intelligence pose estimation in patients after Total Hip Arthroplasty
Authors: Lee Sang Yeob , Park Seong Jin , Gim Jeong-An , Kang Yang Jae , Choi Sung Hoon , Seo Sung Hyo , Kim Shin June , Kim Seung Chan , Kim Hyeon Su , Yoo Jun-Il 
Published: September 2022

Abstract
Background: Recently, open pose estimation using artificial intelligence (AI) has enabled the analysis of time series of human movements through digital video inputs. Analyzing a person's actual movement as a digitized image would give objectivity in evaluating a person's physical function. In the present study, we investigated the relationship of AI camera-based open pose estimation with Harris Hip Score (HHS) developed for patient-reported outcome (PRO) of hip joint function.
Method: HHS evaluation and pose estimation using AI camera were performed for a total of 56 patients after total hip arthroplasty in Gyeongsang National University Hospital. Joint angles and gait parameters were analyzed by extracting joint points from time-series data of the patient's movements. A total of 65 parameters were from raw data of the lower extremity. Principal component analysis (PCA) was used to find main parameters. K-means cluster, X-squared test, Random forest, and mean decrease Gini (MDG) graph were also applied.
Results: The train model showed 75% prediction accuracy and the test model showed 81.8% reality prediction accuracy in Random forest. “Anklerang_max”, “kneeankle_diff”, and “anklerang_rl” showed the top 3 Gini importance score in the Mean Decrease Gini (MDG) graph. Conclusion: The present study shows that pose estimation data using AI camera is related to HHS by presenting associated gait parameters. In addition, our results suggest that ankle angle associated parameters could be key factors of gait analysis in patients who undergo total hip arthroplasty.
Channel Bed and Bank Stability Assessment Case Study Mersa River, Ethiopia
Authors: Sewnetu Getanew , Sintayehu Gashaw , Kifle Teshome , Belay Alemu 
Published: September 2022

Abstract
The objective of this study is evaluating channel stability investigation and recommend appropriate mitigation measure of Mersa river, Awash basin Ethiopia. HEC-RAS5.0.7 model with BSTEM (its extension) was used for assessing Mersa riverbed and bank stability and identifying flood prone area. To achieve the objective both filed investigation such as river cross section data collected, soil sample taken and experimental tasks such as sieve analysis, triaxial compression test are carried out. HEC-RAS model simulation with Yang sediment transport formula is best representative for study reach as compared to Meyer Peter and Muller sediment transport method. For entire simulation period an average aggradation was 1.24m and 0.98m at upstream and downstream reach respectively, whereas average degradation on both upstream and downstream reach was 1.25m. The average erosion generated from Mersa river was 22.47kt/yr. Both aggradation and degradation were observed on the study reach but Mersa river reach more affected in erosion than deposition. Mersa riverbank stability and toe erosion assessed by BSTEM of HEC-RAS was safe and again bank toe neither aggrade nor degrade in response to the flow. Additionally, Water surface of Mersa river was computed using steady flow analysis shows that flood over top above the bank, adjacent area (Mersa town) was severed by flood and the reality also true. The reality also true especially due to flood loss their farmland and different property. Finally, this investigation presented that channel bed was unstable while bank was stable. Different stabilization measures like Gabion bank, Check dam and drop structure were recommended to prevent flood prone area from flood and to control channel bed instability.
Disease-related cytokine markers in persistent apical periodontitis – associated with comorbidities?
Authors: Agger Anne Eriksson , Reseland Janne Elin , Hjelkrem Erik , Lian Aina-Mari , Hals Else K. Breivik , Zandi Homan , Sunde Pia Titterud 
Published: September 2022

Abstract
Objectives: This study aimed to identify disease-related markers in persistent apical periodontitis (PAP) biopsies and examine whether these were associated with comorbidities.
Materials and method: The levels of the cytokines GM-CSF, IFN-γ, IL-2, IL-6, IL-9, IL-10, IL-13, IL-15, IL-17E/IL-25, IL-21, IL-23, IL-27, IL-28A/IFN -λ2, IL-33, MIP-3α/CCL20 and TNF-α were determined in lesions from patients with persistent apical periodontitis (n = 20) and compared to healthy bone samples (n = 20).
Results: We identified eleven cytokines to be differently expressed, and among them, IL-2, IL-6, IL-17E, IL-21, and IL-27 appeared to drive the discrepancy between the disease and healthy groups. The levels of T follicular helper (Tfh) cell promoting cytokines (IL-21, IL-6, IL-27) were enhanced while T helper (Th) 1 cell promoting cytokine (IL-2), Th2 cell promoting cytokine (IL-13), and Th17 cell promoting cytokine (IL-17E) were reduced in the PAP group. The data also indicate that Tfh cell differentiation (IL-21), along with Th1 (GM-CSF, IFNγ), Th2 (IL-13), and Th17 (GM-CSF) cell differentiation, might be increased in the subpopulation of patients suffering from rheumatoid arthritis, whereas no differences were found in patients with cardiovascular diseases.
Conclusions: A cluster of potential cellular markers for PAP was identified. The lesions contained additional factors that might be associated with differentiation of various T cell populations.
Clinical Relevance: Molecular analyses of PAP may result in identification of prognostic markers.
Public Health Supply chain Performance of Tracer Drugs across Primary Health Care Units, Gamo Zone, Southern Nations Nationalities and People’s Region, Ethiopia
Authors: Alemu Aynoshe Adio , Fenta Teferi Gedif , Gebregeorgise Dawit Teshome 
Published: September 2022

Abstract
Background: Health supply chain performance is a key to strengthening the health system. Thus, the current study aimed to assess the public health supply chain performance of tracer drugs across primary health care units in the Gamo zone, SNNPR, Ethiopia.
Method: A convergent parallel mixed-method was adopted. Quantitative data were collected from 46 primary health care units between April 01 and May 30, 2021. A stratified simple random sampling method was employed. Logistics records and reports, service registers, physical observation, and interviews of key informants were sources of data. The data was analyzed using SPSS version 20. Descriptive statistics such as mean, frequency, and percentages were used to present a result. Qualitative data concerning public health supply chain challenges were collected from key informants by using a semi-structured interview guide. It was analyzed manually using an inductive thematic approach and the result was narrated.
Results: The study revealed that the public health supply chain performance of tracer drugs across primary health care units in the Gamo zone was low. Inventory management KPIs, LMIS report KPIs, and storage condition KPIs were below the national standard. Means of availability (64.8 %±14.8%), stocked according to plan (16.5%±9.5%), inventory accuracy rate (65%±17.2%), and stock out rate (64.9%±9.8%) of tracer drugs deviate from ideal. Likewise, the means of LMIS report accuracy rate (64%± 13.6%) and LMIS report completeness (80%±15) are below the standard. Only 81% of assessed primary health care units adhere to good pharmaceutical storage practices. In general, public health supply chain performance of tracer drugs decreases down the levels of primary healthcare units. LMIS reported quality; pharmaceutical distribution; storage condition; low access to public transportation; lack of supply chain workforce training and motivation; low dedicated budgeting and finance for logistics activity; and low support from management were reported as prevailing challenges.
Conclusion:Inventory management, LMIS reporting, and storage practices are areas where gaps in public health program supply chain performance are identified. It leads to wastage and interruption of essential medicines, which affects the quality of healthcare delivery at each level of the primary healthcare units.