bluuebunny/crossref_metadata_2025 huggingface dataset:
Connected vehicles at single lane roundabouts and its performance evaluation
Authors: Echab H. , Kouli L. , Ez-Zahraouy H.
Published: June 2022

Connected vehicles (CVs) have led to innovative changes in the transportation field. In this wise, an extended CA model was established incorporating the CVs and regular vehicles to investigate a roundabout traffic flow under the open boundary condition. The throughput and the phase diagrams of the system in the ([Formula: see text]) area is constructed in both cases: with and without CVs. The density profile and the capacity are also calculated. The simulation findings show that CVs presentation changes the traffic dynamics, enhancing roundabout capacity in accordance with the CVs penetration rate. Furthermore, it is found that roundabout size plays a dominant role in its performance where it suggests that the midsized roundabouts operate more optimally. Another relevant aspect is the short sized of Splitter Island shows a better performance. Moreover, the traffic dynamics is negatively (resp. positively) correlated to the probability of displaying indicator [Formula: see text] as well as the probability of aggressive driving behavior of regular vehicles (resp. the cooperation probability [Formula: see text]).
A simple application of quantum metrology to isotropic and anisotropic spacetimes
Authors: de Sá Neto Olimpio P. , da Paz Irismar G. , Carvalho Paulo R. S. , Costa Helder A. S.
Published: June 2022

In this work, we study quantum metrology protocol in the context of relativistic quantum fields in curved spacetimes. In particular, we restrict our attention to the isotropic and anisotropic models. We investigate how the oscillatory anisotropy affects a quantum metrology protocol. Here, the oscillatory anisotropy is incorporated as a small gravitational disturbance. We calculate the Fisher information for both cosmological parameters [Formula: see text] (expansion volume) and [Formula: see text] (expansion rate). We find that, unlike the isotropic case, the Fisher information of both the parameters [Formula: see text] and [Formula: see text] are oscillating functions of the momentum [Formula: see text]. The oscillatory spectra of Fisher information can theoretically be understood as results of the dependence of the Bogoliubov coefficients on the anisotropic oscillations. In principle, this framework can be used to infer about the underlying spacetime structure and examine the effects of the universe scale factor oscillations.
Configurational entropy and braneworlds in f(T,B) gravity
Authors: Moreira A. R. P. , Lima F. C. E. , Almeida C. A. S.
Published: June 2022

The thick brane scenario built on the [Formula: see text] teleparallel gravity theory was considered for the study of phase transitions, internal structures and new classes of solutions in a model. In this theory, [Formula: see text] denotes the torsion scalar and [Formula: see text] is a boundary term. An interesting result was observed when brane splitting occurs, i.e. internal structures in the model arise as a consequence of the appearance of new domain walls in the theory. In fact, this preliminary result influences the profile of the matter field (from kink to multikink) so that for appropriate values of the parameters [Formula: see text], multiple phase transitions are identified. To perform this analysis, the Differential Configurational Entropy (DCE) that has the ability to predict the existence of phase transitions through critical points was used. Furthermore, the DCE is able to select the most stable solutions since it gives us details about the informational content to the field settings.
A FRACTIONAL BOREL–POMPEIU-TYPE FORMULA FOR HOLOMORPHIC FUNCTIONS OF TWO COMPLEX VARIABLES
Authors: GONZÁLEZ-CERVANTES JOSÉ OSCAR , BORY-REYES JUAN
Published: June 2022

This paper is a continuation of our work [J. O. González Cervantes and J. Bory Reyes, A quaternionic fractional Borel–Pompeiu type formula, Fractal 30(1) (2022) 2250013], where we introduced a fractional operator calculus related to a fractional [Formula: see text]-Fueter operator in the one-dimensional Riemann–Liouville derivative sense in each direction of the quaternionic structure, that depends on an additional vector of complex parameters with fractional real parts. This allowed us also to study a pair of lower order fractional operators and prove the associated analogues of both Stokes and Borel–Pompieu formulas for holomorphic functions in two complex variables.
OPTIMISM BRINGS ACCURATE PERCEPTION IN ITERATED PRISONER’S DILEMMA
Authors: GORKEM ORHUN , BINGOL HALUK O.
Published: June 2022

We analyze an extended model of the Iterated Prisoner’s Dilemma where agents decide to play based on the data from their limited memory or recommendations. The cooperators can decide whether to play with the matched opponent or not. The agents’ decisions are directly linked to their level of optimism since they decide to play if they believe the opponent has a high probability of cooperating. Optimism is precisely tuned by parameters optimism threshold and tolerance. Our experiment showed that being optimistic isbetter for cooperators as it leads to more accurate exploration in the multi-agent system, which tolerates the vulnerability against defectors.
Sequential electron transfer in a bis(styryl)BODIPY-aluminum(III) porphyrin – naphthalenediimide reaction center mimic
Authors: Zarrabi Niloofar , Holzer Noah , Lim Gary N. , Obondi Christopher O. , van der Est Art , D’Souza Francis , Poddutoori Prashanth K.
Published: June 2022

Photoinduced electron transfer properties are reported for a triad composed of a central aluminum(III) porphyrin (AlPorF[Formula: see text] with a secondary electron donor, bis-triphenylaminoborondipyrromethene (TPA2-BDP) attached covalently to AlPorF3, and an electron acceptor, pyridine-appended naphthalenediimide (NDI), attached by coordination of the pyridine group to the AlPor on the opposite face. Excitation of either the AlPorF3 or BDP-TPA2 in the triad results in a two-step electron transfer leading to (TPA2-BDP)[Formula: see text]-AlPorF3-NDI[Formula: see text] as the final charge-separated species. The electron transfer is investigated using the steady-state fluorescence spectroscopy and time-resolved EPR spectroscopy. The behavior of the triad is compared to that of a previously reported triad in which the NDI acceptor was replaced with C[Formula: see text]. The two triads have virtually identical energetics, but the reorganization energies of the acceptors are known to be very different. The spectroscopic data show that the final charge-separated state is formed in both triads despite the large difference in the reorganization energy associated with the acceptors. This suggests that the ability to perform sequential electron transfer does not depend strongly on the properties of the final acceptor, provided that secondary electron transfer can outcompete recombination in the initial charge-separated state.
Technical Perspective - No PANE, No Gain
Authors: Hogan Aidan
Published: June 2022

The machine learning community has traditionally been proactive in developing techniques for diverse types of data, such as text, audio, images, videos, time series, and, of course, matrices, tensors, etc. "But what about graphs?" some of us graph enthusiasts may have asked ourselves, dejectedly, before transforming our beautiful graph into a brutalistic table of numbers that bore little resemblance to its parent, nor the phenomena it represented, but could at least be shovelled into the machine learning frameworks of the time. Thankfully those days are coming to an end.
Technical Perspective
Authors: Mamoulis Nikos
Published: June 2022

The optimal assignment problem is a classic combinatorial optimization problem. Given a set of n agents A, a set T of m tasks, and an n×m cost matrix C, the objective is to find the matching between A and T, which minimizes or maximizes an aggregate cost of the assigned agent-task pairs. In its standard definition, n = m and we are looking for the 1-to-1 matching with the minimum total cost. From a graph theory perspective, this is a weighted bipartite graph matching problem. A classic algorithm for solving the assignment problem is the Hungarian algorithm (a.k.a. Kuhn-Munkres algorithm) [3], which bears a O(n3) computational cost (assuming that n = m); this is the best run-time of any strongly polynomial algorithm for this problem. There are many variants of the assignment problem, which differ in the optimization objective (i.e., minimize/maximize an aggregate cost, achieve a stable matching, maximize the number of agents matched which their top preferences, etc.) and in whether there are constraints on the number of matches for each agent or task.
Technical Perspective
Authors: Howe Bill
Published: June 2022

There is a tension between an imperative style for control flow that has been shown to be easier to use, especially for novices, and a functional style for control flow that better exposes optimization opportunities, thereby making the optimizers more capable. The authors of "Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance" propose Mitos, a program rewriting framework that achieves the best of both worlds by borrowing program analysis concepts from compilers and lifting them to the distributed dataflow regime. Dataflow systems require significant data movement during processing, which can be highly redundant and wasteful in the context of iteration: naive execution plans can reprocess the same massive dataset on each iteration, and iteration i+1 must wait until iteration i is finished. The authors design a mechanism for labeling each intermediate result with its execution path, allowing the system to simultaneously manage complex branching situations while also implementing efficient processing via loop pipelining, all by reasoning about and comparing execution paths.
Relative Error Streaming Quantiles
Authors: Cormode Graham , Karnin Zohar , Liberty Edo , Thaler Justin , Vesely Pavel
Published: June 2022

Estimating ranks, quantiles, and distributions over streaming data is a central task in data analysis and monitoring. Given a stream of n items from a data universe equipped with a total order, the task is to compute a sketch (data structure) of size polylogarithmic in n. Given the sketch and a query item y, one should be able to approximate its rank in the stream, i.e., the number of stream elements smaller than or equal to y.
Investigating Installers of Security Software in 20 Countries: Individual- and Country-Level Differences
Authors: Smahel David , Dedkova Lenka , Kraus Lydia , Matyas Vaclav , Stavova Vlasta
Published: June 2022

This article provides detailed evidence about the installers of online security software on personal computers according to differences among clusters of countries and various other country characteristics. The study presents unique data based on real installations around the world. The data are based on a large-scale quantitative study (

N
=
18,727

) which was prepared in cooperation with an international security company. The cluster analyses revealed four distinct clusters of software installers: those who install the software for a different user, those who are IT technicians and mostly install the software for other users, those who install the software for themselves and others on a shared computer, and those who install the software only for themselves. A second cluster analysis revealed four different country clusters. Within these clusters, countries handle online security software installation similarly; however, there are differences for the clusters according to industrialized, English-speaking countries and the cluster of developing countries. This study presents unique cluster analyses of the countries to shed light on the cross-culture differences in security software adoption and installation. The results implicate that software companies should consider providing different versions of the security software to match the country characteristics.
Current Control of Permanent Magnet Synchronous Motors Using Improved Model Predictive Control
Authors: Kashif Nawaz Muhammad , Dou Manfeng , Riaz Saleem , Usman Sardar Muhammad
Published: June 2022

Model predictive control (MPC) is a powerful tool for the control of permanent magnet synchronous motors. However, conventional MPC permits using a single voltage vector during one control interval. This results in higher current distortions and large torque ripples. Sensitivity to control parameters is another issue associated with conventional MPC. The duty cycle suggests using an active vector and a null vector during one sampling interval. The method needs excessive computational and prediction effort. Furthermore, a necessary zero vector as the second vector might not give the optimal results. To overcome the problems of computational burden, this paper proposes that a reference voltage vector can be calculated and used to determine the voltage vector to be used for the next interval. This reduces the computational effort to a minimum. Furthermore, it is proposed that the second vector can either be active or null. To overcome the problem of parameter dependence, an electromotive force is calculated on basis of previous values. Simulations have been carried out to verify the efficacy of the proposed method.
Multi-Band mm-Wave Wearable Antenna Synthesized with a Genetic Algorithm
Authors: Dejen Arebu , Ridwan Murad , Jayasinghe Jeevani , Anguera Jaume
Published: June 2022

This paper presents the design of a novel fabric-based multi-band microstrip antenna in mm-wave frequencies for wearable applications. The reference patch antenna was etched on a flexible polytetrafluoroethylene (PTFE) fabric substrate with an overall dimension of 18 mm × 18 mm × 0.6 mm and optimized the patch geometry using a binary-coded genetic algorithm. The algorithm iteratively creates a new shape of the path surface, evaluates the cost function, and returns the best-fitted geometry based on the formulated fitness function. The free space and on-body simulation of the best-fitted antenna performance parameter was investigated and analyzed. In free space, the proposed antenna is resonant at five distinct frequencies: 27.8 GHz, 30.3 GHz, 40.1 GHz, 47.2 GHz, and 56.7 GHz. The antenna achieves a wide bandwidth of 0.69, 2.32, 2.22, 1.76, and 8.11 GHz and an improved broadside directivity of 10.3, 8.5, 7.8, 9.6, and 8.9 dB in free space, respectively. For on-body analysis, the antenna was simulated using a three-layer human body phantom model at three distinct distances. The gain and radiation efficiency were significantly reduced when the antenna was close to the phantom model and gradually enhanced as the gap increased. Moreover, the antenna performances were evaluated and compared by using four additional fabric substrates. Because of its excellent on-body performance with flexible textile-based substrates, the optimized antenna is a suitable candidate for multi-band body-centric communications.
Parametric Optimal Design System of Construction System Based on Distributed Optimal Algorithm
Authors: Zhang Wei
Published: June 2022

With the rapid development of science and technology and the continuous expansion of network scale, traditional centralized control and optimization techniques have been difficult to solve large-scale complex network problems, and distributed optimization algorithms with more robustness and flexibility have attracted more and more attention. In view of the irreplaceable advantages of multi-intelligent systems in distributed computing, many researchers have used them as carriers of distributed optimization for theoretical research and application promotion. For the distributed optimization problem in the undirected network environment, this article outlines and summarizes the existing gradient-based distributed simultaneous optimization algorithms, based on which a novel distributed simultaneous momentum acceleration optimization algorithm is proposed. Under the premise that the local objective function is strongly convex and Lipschitz continuous, the algorithm uses heterogeneous steps to precisely drive each node to converge asymptotically to the global optimal solution, and we reduce or compensate the effect of the original error on the pairwise error by introducing an adjustable symmetric matrix. The distributed resource allocation problem under undirected graphs is studied, in which the local cost function of the intelligences is unknown. Using sinusoidal signal excitation, the input and output of the cost function are utilized, and the first-order and second-order polar search algorithms are designed, respectively. In addition, the algorithm innovatively introduces the dual acceleration mechanism combining the Nesterov gradient method and the Heavy-Ball method to greatly improve the convergence speed of the algorithm. Based on the interrelationship of the agreement error, the optimal distance, the state difference, and the tracking error, the step size and the range of the momentum parameters for the linear convergence of the algorithm to the optimal solution are analyzed using the linear matrix inequality technique.
Ultrasonic Image Feature Analysis under Deep Learning Algorithm to Evaluate the Efficacy of Drug-Coated Balloon for Treatment of Arteriosclerotic Occlusion
Authors: Zhang Yuchao , Xu Gang , Chen Maozhen , Chen Ziliang , Shen Mingyang , Wang Ping
Published: June 2022

In order to explore the adoption of ultrasonic images under deep learning (DL) algorithm to evaluate the efficacy of drug-coated balloon (DCB) for treatment of arteriosclerotic occlusion, 56 patients who underwent DCB surgery of lower limb artery were selected and all the patients received the examinations of algorithmic ultrasound and digital subtraction angiography (DSA) before surgery. According to the examination methods, they were classified into algorithmic ultrasound group and DSA group. One to two months after DCB surgery, ultrasound examination was performed with the region-based faster convolutional neural network (faster R-CNN) target detection algorithm to check the therapeutic effect. The results showed that the image effect processed by the target detection algorithm based on DL was signally better than that of traditional ultrasonic processing algorithm in Dice, precision (Pre), and sensitivity, with significant difference (

P
<
0.05

). Compared with DSA, algorithmic ultrasound showed better consistency between the two groups in the diagnosis of common femoral artery, superficial femoral artery, and popliteal artery stenosis, with statistical significance (

P
<
0.05

). However, for the diagnosis of anterior tibial artery stenosis, the consistency between algorithmic ultrasound and DSA was general. The residual stenosis of each artery segment decreased obviously in postoperative review compared with that before surgery, and the difference was statistically significant (

P
<
0.05

). Besides, both the pulsatility index (PI) and the blood flow velocity of the dorsalis pedis artery increased after surgery, compared with those before surgery, with significant differences (

P
<
0.05

). To sum up, ultrasound based on DL target detection algorithm had good imaging effect and good consistency with DSA, which was of the clinical reference value. Additionally, DCB surgery was helpful to treat arteriosclerosis occlusion and improve limb blood supply, which had clinical adoption value.
Application of Digital Image Processing Technology in Automatic Recognition Algorithm of Rock Microseismic Events in Mining Area under the Background of Mobile Communication
Authors: Wang Shuai , Liu Penghe , Lu Shasha
Published: June 2022

In all kinds of production, the changes of the times and scientific and technological progress make us have higher requirements for monitoring data. In order to improve the accuracy of mine rock microseismic monitoring and the sensitivity and specificity of mine disaster early warning, it is very important to use the change of light and material vibration to monitor environmental changes. This paper is the design of an optical hardware system, which improves the traditional system, uses the change of light wave to detect the spatial change, and forms a nano digital imaging photography (ndip) system to collect more detailed data. The three-year field experiment under the guidance of a simulation experiment shows that the system has higher monitoring sensitivity, early warning sensitivity, and specificity than the laser gyroscope system, but its antidust interference ability is low, so it cannot replace the laser gyroscope system in a short time, but it can supplement and realize data fusion analysis.
Dedifferentiated Leiomyosarcoma of the Auricle with Heterologous Osteosarcoma Component: Case Report and Literature Review
Authors: Dekanić Andrea , Jonjić Nives , Savić Vuković Anita
Published: June 2022

Leiomyosarcomas are rare malignant tumors of smooth muscles. Head and neck involvement by this disease is very rare, and cutaneous leiomoysarcomas of the ear are even rarer. This is way clinically they are usually mistaken for either squamous or basal cell carcinomas, as was the case in an 85-year-old male patient presented in this report. However, the final diagnosis was even more interesting considering that it was a dedifferentiated leiomyosarcoma of the auricle with a heterologous component of osteosarcoma. The auricular cutaneous malignancies have a much higher rate of recurrence than the corresponding malignancy in other regions of the head and neck, even when resected with negative surgical margins, and dedifferentiated leiomyosarcoma is clinically even more aggressive. Thus, the treatment of choice is a total auriculectomy and great attention should be paid to appropriate margins.
A B/S-Based Computer-Aided Translation Teaching Method
Authors: Liu Yan
Published: June 2022

English and Chinese are fundamentally different in many ways, due to which miscommunications are common in both languages. For this purpose, there are several English-Chinese translation systems available these days, but most of them provide a sluggish interactive experience, primarily due to erroneous language, grammatical problems, imprecise pronunciation of the system, and slow translation feedback speed. Therefore, there is a need to develop an efficient and collaborative system. Due to these factors, this paper proposes an interactive machine translation system for English-Chinese based on the B/S architecture to aid communication between English and Chinese speakers in both directions. This system is designed based on the B/S three-layer architecture. To achieve the desired results, this paper explains the machine translations mode and then implements the overall system design based on the process of system operation, algorithm for translation enhancement, network structure, and application, respectively. Lastly, an investigational platform is created using the WINCC6.0 operating system to evaluate the overall system performance. Results of the system testing demonstrate that the comprehensive score of manual evaluation is 3.769 points, which is higher than the limit value of 3.5, which shows that the system’s translation quality is high and that it can fulfill the expectations of users.
Exposure to Sex Education and Its Effects on Adolescent Sexual Behavior in Nigeria
Authors: Osadolor Uyi E. , Amoo Emmanuel O. , Azuh Dominic E. , Mfonido-Abasi Ikono , Washington Christian Philip , Ugbenu Oke
Published: June 2022

Sexual behavior during adolescence fundamentally steers the future life of both girls and boys, and it should be guided with appropriate education, especially as it also represents a key factor to be considered in attainment of sustainable developmental goals. The study assessed the effect of exposure to sex education on adolescents’ sexual behavior. The primary and cross‐sectional survey data used for this study were analyzed using basic descriptive statistics and binary logistic regression analytical technique. The results, among others, highlighted that the most common sources of first sex education among the respondents are school (54.6%), family (21.6%), social media (9.5%), and others like television (7.6%) and books or magazines (4.9%). Frequency of discussion on sexual matters is positively associated with the use of protection such as condom (β = 0.261; p ≤ 0.01). The study gave support to the increasing pursuit of sexuality education. However, since adolescents’ needs could vary by demographics, streamlining sex education need by age and sex characteristics could enhance its effectiveness.
Surgical Treatment of Single Pontomedullary Junction Metastasis from Lung Cancer
Authors: Missori Paolo , Peschillo Simone , Ambrosone Angela , Currà Antonio , Paolini Sergio
Published: June 2022

Background. When lung cancer develops a solitary metastasis at the pontomedullary junction, due to surgical risk, the current oncologic treatment is radiosurgery and chemotherapy. Case Description. We describe a patient with a single intrinsic metastasis at the pons and medulla. Removal was successful, without complication. Conclusion. Surgery can provide excellent results, and in selected patients, it should be considered a first-line treatment in experienced hands.
Privacy-Preserving Cross-Zone Ride-Matching for Online Ride-Hailing Service
Authors: Ma Hui , Ping Yuan , Zhang Yong
Published: June 2022

Although online ride-hailing supplies the nearest taxi matching for riders, the potential leakage of riders’ hobbies and physical condition raises privacy concerns. Since most of the privacy-preserving schemes do limited matching of riders and drivers in the same zone, in this paper, we propose a novel privacy-preserving cross-zone ride-matching scheme, namely, Cride, which extends one zone into multiple neighboring zones. Based on the zone division of a city, CRide allows distance computation between rider and driver across adjacent zones in the encrypted domain. Furthermore, towards efficiency improvement, a ciphertext packing technique is introduced. Theoretical analysis and experimental results suggest that CRide achieves a high ride-matching accuracy and acceptable efficiency without leaking privacy.
Analysis of Load Transfer Law of Short Pile-Net Composite Foundation for High-Speed Railway
Authors: Li Shiyou , Ye Liming , Jiang Hong , Chen Zhaofeng
Published: June 2022

Although pile-net composite foundation has been widely used in the construction of high-speed railway, load transfer characteristics of its structural system during the filling of roadbed are seldom studied, so field studies are conducted in the Gan-Long (Ganzhou-Longyan) high-speed railway DK86 + 998.0–DK87 + 191.2 test section, aiming to explore the bearing characteristics of a short pile-net composite foundation over low to medium compressible soil. The study encompasses a field measurement of Earth pressure and pore water pressure which lasted almost two years, and a systematic analysis of variation law of soil pressure between piles and their tops and that of pore pressure in reinforcement zone and retaining layer in medium and low compressibility soil area. The results suggest that the soil in the test section bears the characteristic of a low water content, low porosity ratio, and high liquid limit, with compression factor being approximately 0.25, and test values of the natural soil pressure and the lateral distribution are close to the theoretical values. Soil pressure at the top of the piles is higher than that between the piles by approximately 2.4 times because of the differences in pile-net rigidity. Besides, the soil pressure of the pile-net composite foundation follows the pattern of “jagged” in the transverse direction of the roadbed. The filling load of the composite foundation soil arch is 80 kPa and the composite foundation reaction coefficient is 6.4 kN/m3 when the filling is stable. The pile-soil stress ratio at the shoulder and the center of the line is 3.2 and 2.8, respectively. The change of the hole pressure at the pile end point is larger than that at the reinforcement area, and the side verification short pile can effectively transmit the additional stress of the upper part to the pile end soil layer.
Research on Folk Handicraft Image Recognition Based on Neural Networks and Visual Saliency
Authors: Yu Xinyong , Dai Yanli
Published: June 2022

How to identify quickly the images of folk arts and crafts works has become a difficult problem of cultural heritage value mining. Therefore, combined with the image recognition technology can improve the accuracy of the identification of folk arts and crafts works. This paper improves the ITTI significant model based on the method of linear addition of significant maps with the same proportion. Firstly, Bayesian model and Gaussian model are used to extract the probability distribution of image feature vector; secondly, the k-means algorithm is used to identify image accuracy extraction work, and finally ALOI database is used to test judgment image recognition accuracy; experimental results found that the improved technology does help to improve the folk arts and handicraft image recognition accuracy.
Analysis and Correction of Wrong Technical Actions in Juvenile Sports Training Based on Deep Learning
Authors: Zhao Xuefeng
Published: June 2022

Scientific analysis of students’ incorrect actions in class, as well as timely and effective correction, is frequently an important link in the PE process. At the same time, it is an important symbol for assessing a teacher’s teaching level and quality. In this paper, the analysis and correction model of sports wrong technical movements is built using DCNN to address shortcomings in the process of detecting wrong movements in PE and training. This article is based on CNN and has been enhanced by DL. The model learns both manual and DL features; the manual features use an improved dense trajectory, the DL features use CNN based on motion information, and the generalization ability of the kernel support vector machine is used to fuse the two. The simulation results show that the accuracy of the wrong action judgment of this method can reach 92.16 percent, which is 4.6 percent higher than the method of combining NN with region prediction and 5.7 percent higher than the method of detecting image matching score. This method can accurately describe the characteristics of human motion and identify incorrect movements, improve the ability of judging and correcting incorrect movements in sports training, and help athletes improve their sports level.
A Necessary and Sufficient Condition for
k
=
ℚ

4
n

2

+
1

to Have Class Number
ω

n

+
c
Authors: Issa Ahmad , Sankari Hasan
Published: June 2022

In this paper, we give a necessary and sufficient condition for real quadratic field

k
=
ℚ

4
n

 

2

+
1

to have class number

ω

n

+
c

where

c
∈

1
,
 
2

and

ω

n

is the number of odd prime divisors of

n

.
Effects of COVID-19 on Coffee Market Participation of Smallholder Coffee Producers’ in Godere District, Southwestern Ethiopia
Authors: Kabeta Temesgen , Dangia Mabiratu
Published: June 2022

In sub-Saharan countries like Ethiopia, COVID-19 affected not only the health sector, but also the agricultural productivity and marketing, especially affecting coffee producers’ probability of market participation. The study was conducted on the effects of COVID-19 on smallholder coffee producers’ coffee market participation in Godere district, southwestern Ethiopia. This study aimed to identify the effects of COVID-19 on coffee producers, its effect on the decisions of market participation mechanisms, and the prevention mechanisms employed during the pandemic. For this study, qualitative and quantitative data were collected from primary and secondary sources by using a semi-structured interview schedule with well-trained data collectors. The data was analyzed, and a simple random sampling technique was used to select 384 coffee producers at 95% confidence level. The study result shows that the level of coffee producers’ market participation was reduced from 100% to 81.25% because of COVID-19’s effect on smallholder farmers, with 18.75% failing to participate in the coffee market. COVID-19 prevention mechanism provided by the government for social movement was strongly affecting farmer levels of market participation. Most of the coffee producers agreed that COVID-19 affected their probability of coffee market participation because concerned stakeholders in the sector were not well subsidized to recover from the depression. Most of the farmers were not effectively getting financial services from aid organizations and government to mitigate the impact on their livelihood. Generally, COVID-19 strongly affected the levels of coffee producers’ market participation, and it is advisable for concerned bodies to support producers by providing subsidies and creating market linkages.
Distributed Compressed Hyperspectral Sensing Imaging Incorporated Spectral Unmixing and Learning
Authors: Xiao Hua , Wang Zhongliang , Cui Xueying , Wang Liping , Yang Hongsheng , Jia Yingbiao
Published: June 2022

Compressed hyperspectral imaging is a powerful technique for satellite-borne and airborne sensors that can effectively shift the complex computational burden from the resource-constrained encoding side to a presumably more capable base-station decoder. Reconstruction algorithms play a pivotal role in compressive imaging systems. Traditional model-based reconstruction approaches are computationally burdensome and achieve limited success. Deep learning-based approaches, while improving in reconstruction accuracy and speed, depend heavily on data, which is a major challenge for satellite-borne hyperspectral compressed imaging. In this article, we combine the respective advantages of model-based and learning-based approaches in a distributed compressed hyperspectral sensing framework, employing linear mixed model assumptions and spectral library learning to simultaneously improve the reconstruction speed and accuracy without using a large amount of additional hyperspectral data. First, the relationship between the CS band and the key band is learned from the spectral library to ensure that the key band endmembers can be accurately predicted. Then, the joint horizontal and vertical difference operators are proposed to enhance the estimation of the initial values of abundance. Finally, the CS band endmembers and residuals are updated in the reconstruction module to deal with the endmember and abundance mismatch. Extensive experimental results on five real hyperspectral datasets demonstrate that the proposed spectral library learning, abundance initialization, and reconstruction strategy can effectively improve the compressed sensing reconstruction accuracy, outperforming the existing state-of-the-art methods.
System Resource Allocation and Rural Industry Revitalization Based on Max-Min Algorithm
Authors: Dai Qiongyao
Published: June 2022

At this stage, the research hotspots on wireless multimedia sensor networks mainly include MAC protocol, network security, and node positioning. Research on resource allocation is scarce. Due to the lack of an effective wireless resource allocation strategy, even the most advanced transmission technology will not be able to fully utilize its unique advantages due to unreasonable resource allocation. Therefore, in-depth research on wireless resource allocation strategies is of great significance for the better application of wireless transmission technology. The entire network uses OFDMA mechanism to divide time slots. According to this method, resource allocation can be divided into intercluster and intracluster, and then the Max-Min subcarrier allocation algorithm is innovated and perfected to ensure maximum information transmission speed and throughput and promote information data efficient transmission. Based on the research of wireless sensor system resource allocation technology, China has emphasized industrial prosperity as the key point in its rural revitalization strategy, and doing a good job in technological innovation and industrial innovation is of great significance to economic development. At this stage, the capacity of rural industrial economic development is poor, and the economic level of most rural areas is not high. This situation is inseparable from problems such as limited industrial development and insufficient technological innovation capabilities. In order to promote the prosperity of rural industries and achieve the goal of rural revitalization, we must proceed from the fundamentals and give priority to solving the outstanding problems encountered in the process of rural industrial revitalization. Promoting the revitalization of rural industries can effectively solve the current plight of agricultural development and is an inherent requirement for rural prosperity and the country's prosperity. Aiming at the problems in the process of restricting the revitalization of rural industries, this article adheres to the principle of integrating theory with practice and puts forward practical and feasible measures to solve the problem in a targeted manner.
Deep Learning-Based Surface Nerve Electromyography Data of E-Health Electroacupuncture in Treatment of Peripheral Facial Paralysis
Authors: Zhu Pengdong , Wang Hui , Zhang Lumin , Jiang Xuan
Published: June 2022

This study was aimed at exploring the application value of electroacupuncture in the treatment of peripheral facial palsy using surface nerve electromyogram (EMG) image data based on deep learning. The surface nerve EMG recognition model was constructed based on multiview convolutional neural network, and the differences between it and the traditional single-view convolutional neural network were analyzed. Meanwhile, the influence of the multiview aggregation method based on pooling of view and decision fusion on facial recognition accuracy was compared and analyzed. 150 patients with peripheral facial paralysis were randomly divided into the control group (

n
=
70

, basic treatment) and treatment group (

n
=
80

, basic treatment + electroacupuncture). After 4 weeks of treatment, the therapeutic effect was evaluated by surface EMG parameters based on Horsfall-Barratt (

H

-

B

) scale and multiview convolutional neural network. The results showed that the face recognition accuracy of multiview convolutional neural networks was significantly higher than that of all single-view convolutional neural networks. The multiview aggregation network proposed in this research had a higher accuracy in facial recognition than the pooling of the view method and decision fusion-based multiview aggregation method. According to the evaluation results of H-B scale, the number of patients who recovered, significantly effective, effective, and ineffective in the control group was 39, 17, 3, and 11, respectively. The number of patients in the treatment group who recovered, significantly effective, effective, and ineffective was 51, 15, 9, and 5, respectively. Total effective rate of patients in the control group was 84.29%, and that of the treatment group was 93.75%, which was significantly higher than the control group (

P
<
0.05

). According to surface EMG assessment results, compared with the control group, the mean root mean square (RMS), median frequency (MF), and mean power frequency (MPF) of the buccal and frontalis muscles in the treatment group increased significantly (

P
<
0.05

). Compared with that before treatment, the mean buccal and frontalis RMS of patients in the control and treatment groups increased significantly after treatment (

P
<
0.05

). In conclusion, electroacupuncture treatment could significantly improve the muscle strength of patients with peripheral facial paralysis.
Projeto e implementação de assistente pessoal para agendamento de compromissos
Authors: Vendramini Mateus Ramos , Imagure Ricardo Ciriaco Camargo , Barretto Marcos Ribeiro Pereira
Published: June 2022

O processo de agendamento de compromissos envolve a condução de uma negociação entre duas ou mais pessoas e pode ser um processo tedioso para muitos, que leva a resultados não ótimos no agendamento devido à falta de comprometimento das pessoas à tarefa  de negociação (tanto em ambientes profissionais como pessoais de cada um). Para resolver esse problema, foi proposta a implementação de um assistente com uma arquitetura dividida em dois grandes módulos: Semantizador, responsável por fazer o processamento  de linguagem natural e criar um objeto com uma semântica que é utilizada pelo segundo módulo; Gerenciadores de Diálogo, responsáveis por conduzir o diálogo, processando as entradas dos usuários e gerando saídas. Essa solução permitiu que metade dos usuários que testaram o assistente conseguissem atingir seus objetivos e que a coleta das informações básicas do compromisso fosse feita com uma média de 3 turnos. Permitiu também uma taxa de 84% de acerto na identificação de entidades relevantes e  de 53% de acerto na identificação das intenções relevantes expressas pelo usuário.
Tracing Karma in Meiji Japan
Authors: Kameyama Mitsuhiro
Published: June 2022

Despite its doctrinal importance, the concept of karma or karmic causality has come to occupy a complicated place in contemporary Japanese Buddhism, due to its historical connection with discrimination against outcast groups and disabled people. Furthermore, among post-war Japanese intellectuals, the idea of karma has often invoked criticism in the context of modern values such as free will and human potential. Against this conventional framework, this paper demonstrates how the concept of karma was the focus of intense interest among Meiji Japanese intellectuals and a center concern in the developing global network of modern Buddhists. At the intersection of the multifaceted problems facing the Buddhist world at that time—namely, the Buddhist search for scientific religion, civil morality in the nation-building process, reformulating Buddhism for non-Japanese audiences, and the confrontation with competing forms of Western thought—lies the relatively unexamined story of karma in Meiji Japan (1868–1912).
Catalogue of Vietnamese springtails (Hexapoda, Collembola)
Authors: NGUYEN ANH T. T. , THUY KIM N. , ARBEA JAVIER I.
Published: June 2022

Based on what we believe is a complete survey of the previous literature, the citations of the collembola found in Vietnam are recorded. In total, the catalogue includes 350 species in 118 genera from 21families (69 dubious records). For each species the current name is indicated, as well as the basionym and main synonyms with the complete bibliographic reference, the records for different provinces and regions with the authorships, and the general distribution data. When necessary, taxonomic notes are added. The catalog includes 120 bibliographic references (up to December 2021). The main goal of this paper is to promote future studies on the collembolan fauna of Vietnam.
Effect of Some Growth Stimulants and Different Levels of Potassium and Biofertilizer on Growth Aspects, Bulb Yield and Quality Attributes of Onion (Allium cepa L.)
Authors: Mohamed Mostafa H. M. , Eid Rania S. M. , Ali Maha M. E. , Mohamed Ibrahim , Sami Rokayya , Alyamani Amal , Aloufi Salman , Aljahani Amani H. , Metwally Amr A. , Abdellatif Yasmin M. R. , Elsayed Nesma , Zewail Reda M. Y. , Eldesouky Heba S.
Published: June 2022

Onion (Allium cepa L.) is the most widely cultivated species of the Allium genus. Onion is rich in many vital nutrients and sulfur (S)-containing several compounds important for human health. Recently, Allium species requirements have gained special attention in this special
time due to its export importance. The aim of this study is to compare the effects of the recommended dose of potassium (100% KRD) against three lower levels of potassium mixed with Bacillus circulans, potassium solubilizing bacteria (80% KRD+biofertilizer, 60% KRD+biofertilizer or
40% KRD+ biofertilizer, as well as foliar applications of copper (Cu), boron (B) or putrescine (Put) that have great impacts on yield, quality and onion attributes.The highest level of potassium (100% KRD) resulted in the highest growth parameters and the richest leaves content in N, P, K,
S, B, Cu, and carbohydrates, yield, as well as the best quality parameters of bulbs. All growth and yield parameters decreased gradually with reducing the levels of K fertilization. Foliar spraying of Cu, B, and Put combined with all different levels of K fertilizer improved all plant parameters.
The highest impact on plant growth was due to Put followed by B at all levels of soil fertilization. Plants that were exogenously sprayed with Put and B exhibited an increase in N, P, K, B, and carbohydrates under different levels of fertilizers, while foliar application with Cu highly increased
S and Cu in onion leaves with all levels of K fertilization. The combined treatment of B and all different levels of K fertilizer considerably improved all yield measurements, except with allyl propyl disulfide, which estimated a highly significant increase with Put foliar application coupled
with 40% KRD+Bio. In a nutshell, exogenous Put, B, and Cu foliar applications on onion plants increased bulb yield and its quality attributes with the recommended level of potassium or lower recommended levels of K mixed with biofertilizer.
Rolling Stock Allocation and Timetabling for Urban Rail Transit Network with Multiple Depots
Authors: Pu Fan , Yin Jiateng , Wang Yihui , Su Shuai , Yang Lixing , Tang Tao
Published: June 2022

Rolling stock management and train timetabling are two challenging but very related issues in urban rail systems. The former is to allocate a certain fleet of trains to each depot, and the latter determines the arrival and departure times of train services according to the available rolling stock at each depot. While most existing studies consider these two tasks for a single line, this study focuses on the integrated optimization of rolling stock allocation, train timetabling, and rolling stock circulation for a whole network, where each depot can serve multiple connected lines and the trains can change lines in one operational cycle (i.e., one day). A time-space network is constructed to model the rolling stock circulation among multiple lines and depots, and a novel integer linear programming model is proposed to jointly optimize the allocation of rolling stock and train timetables for the involved lines. The objective function maximizes the service quality provided to passengers with minimized rolling stock investment cost. Numerical experiments based on the real-world data of the Beijing rail transit network are conducted to validate the effectiveness of this approach. The results demonstrate that the proposed approach can reduce the fleet size of rolling stock by 5% while providing the same service quality to passengers.