bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilization of Low-Rank Coals for Producing Syngas to Meet the Future Energy Needs: Technical and Economic Analysis
Authors: Ahmed Usama , Hussain Muhammad Arsalan , Bilal Muhammad , Zeb Hassan , Zahid Umer , Onaizi Sagheer A. , Jameel Abdul Gani Abdul
Published: September 2021

Increased energy demand in recent decades has resulted in both an energy crisis and carbon emissions. As a result, the development of cleaner fuels has been under the research spotlight. Low-rank coals are geographically dispersed, abundant, and cheap but are not utilized in conventional processes. Syngas can be produced from coal-using gasification which can be used in various chemical engineering applications. In this study, the process model for syngas production from low-rank coal is developed and the effects of various process parameters on syngas composition are evaluated, followed by a technical and economic evaluation. The syngas production rate for the low-rank coal has been evaluated as 25.5 kg/s, and the contribution to H2 and CO production is estimated as 1.59 kg/s and 23.93 kg/s, respectively. The overall syngas production and energy consumed in the process was evaluated as 27.68 kg/GJ, and the CO2 specific emissions were calculated as 0.20 (mol basis) for each unit of syngas production. The results revealed that the syngas production efficiency for low-rank coals can be as high as 50.86%. Furthermore, the economic analysis revealed that the investment and minimum selling prices per tonne of syngas production are EUR 163.92 and EUR 180.31, respectively.
Identification of Factors Affecting Pedestrian Satisfaction toward Land Use and Street Type
Authors: Lee Soongbong , Han Myungjoo , Rhee Kyoungah , Bae Bumjoon
Published: September 2021

Walking is an essential sustainable mode of transportation. Encouraging to increase walking trips can bring various social and economic benefits to our society. Since the policy paradigm has been shifting from car-oriented to pedestrian-oriented, interest in securing pedestrian rights and improving walking environments is increasing significantly. This study aims to examine factors affecting pedestrian satisfaction according to land use and street type. A pedestrian satisfaction survey was conducted in an industrial city with a mid-size population in the city of Changwon, South Korea. Based on the survey data from 500 respondents, factors affecting pedestrian satisfaction were analyzed by land use (commercial or residential areas) and street type (non-separated or separated sidewalks). The analysis results, using binary and ordered logit models, showed that the less illegal parking, the more pedestrian space, pedestrian guidance facility, and green space, the higher the pedestrian satisfaction. Factors positively affecting the satisfaction of pedestrian paths according to land use were physical environmental variables, such as the separated sidewalk variable. In commercial areas, pedestrian guidance facilities and street cleanliness were included as major influencing factors, implying differences in land use influencing factors. A common factor affecting the satisfaction of separated or non-separated sidewalk cases was also identified as the sufficiency of walking space. Therefore, the most urgent policy measure for improving pedestrian satisfaction for the city was to install a sidewalk or expand the pedestrian space. In the pedestrian-vehicle separation models, green space and cleanliness were included as significant variables, and in the non-separated models, variables of pedestrian guidance facilities and sidewalk conditions were included.
Forensic Studies on Spent Catalytic Converters to Examine the Effect of Diesel and B100 Pongamia Biodiesel on Emissions
Authors: Manjunath N. , Rajashekhar C. R. , Venkatesh J. , Khan T. M. Yunus , Tirth Vineet , Badruddin Irfan Anjum
Published: September 2021

The ever-increasing demand for transport is sustained by fossil fuel-based internal combustion (IC) engines fitted with catalytic converters (CCs) while alternative options and fuels are still emerging. Biodiesel seems to be a potential alternate to diesel, but the formation of NOx and smoke are major issues. This study aimed to explore the effect of B100 Pongamia biodiesel on the performance of CCs and to assist the designers of compression ignition engines. This study included a comparison of deposits on the catalytic converter (CC) in the cases of diesel fuel and biodiesel. Forensic examination of the spent CCs after 250 h was performed by characterization using SEM/EDS. The amount and composition of the deposits were compared for the diesel and biodiesel, and the effectiveness of the CC. The study revealed that the efficiency of the CC increased in biodiesel. The amount of soot and deposits was greater at the engine side of the spent CC with diesel, including the atomic percentage (At. %) of C, while the minimum deposits and C At. % in the spent CC were at the exhaust side with biodiesel. Oxygen content in the deposits was greater in biodiesel. The efficiency and effectiveness of the CC increased with the biodiesel.
Climate-Based Analysis for the Potential Use of Coconut Oil as Phase Change Material in Buildings
Authors: Eller Cibele , Rida Mohamad , Boudier Katharina , Otoni Caio , Celani Gabriela , Labaki Lucila , Hoffmann Sabine
Published: September 2021

One of the most efficient measures to reduce energy consumption in buildings is using passive thermal comfort strategies. This paper shows the potential of coconut oil as a bio-based phase change material (PCM) incorporated into construction components to improve the thermal performance of buildings for several climates, due to its environmental advantages, wide availability, and economic feasibility. The thermophysical properties of coconut oil were determined through differential scanning calorimetry. Numerical simulations were conducted in ESP-r, comparing an office space with a gypsum ceiling to one with coconut oil as PCM for 12 climate types in the Köppen–Geiger classification. The results show that coconut oil is a suitable PCM for construction applications under tropical and subtropical climates. This PCM can provide year-round benefits for these climates, even though a higher melting point is needed for optimum performance during hotter months. The highest demand reduction of 32% and a maximum temperature reduction of 3.7 °C were found in Mansa, Zambia (Cwa climate). The best results occur when average outdoor temperatures are within the temperature range of phase change. The higher the diurnal temperature range, the better the results. Our findings contribute to a better understanding of coconut oil in terms of its properties and potential for application in the building sector as PCM.
Psychological Well-Being Sustainable during Entrepreneurial Process—The Moderating Role of Entrepreneurial Creativity
Authors: Wang Chengchun , Mundorf Norbert , Salzarulo-McGuigan Ann
Published: September 2021

Despite pitfalls during the entrepreneurial journey, entrepreneurship offers the opportunity to illuminate new ventures and preserve psychological well-being to sustain entrepreneurial development. From a dynamic perspective, this study discusses the early stage of the entrepreneurial process affecting student entrepreneurs’ psychological well-being and examines the moderating role of entrepreneurial creativity. By building a framework with the data of 1873 student entrepreneurs across 36 university business incubators in China involved in entrepreneurship activity, we found that entrepreneurial passion, alertness and intention had a positive correlation with entrepreneurs’ psychological well-being, but entrepreneurial action had the opposite effect. Entrepreneurial creativity positively moderated relationships between entrepreneurial action and students’ psychological well-being. This finding contributes to a full understanding of students’ psychological well-being on their entrepreneurial journey in the context of COVID-19 and eases the pressure of entrepreneurship by strengthening entrepreneurial creativity education.
Climate Change, Security, and the Resource Nexus: Case Study of Northern Nigeria and Lake Chad
Authors: Wakdok Samuel Stephen , Bleischwitz Raimund
Published: September 2021

This paper analyses the impacts of climate change and its implications for human security for the regions of Northern Nigeria and Lake Chad. The introduction identifies a gap between evidence on global environmental change and interactions on the ground; it positions the scope for a deeper understanding of the climate–security–resource nexus in Northern Nigeria and Lake Chad and consequences for the implementation of SDGs (Sustainable Development Goals). The section on methods describes the nexus concept and justifies adopting it. As a result of analysing the region, the paper sheds light on the conflict pathways triggered by failures in land grazing policy, which is further evidenced by a short comparison with Northern Kenya. A potentially novel contribution is discussed in terms of scaling up collaboration and green markets for the future of Lake Chad, along with an integrated agricultural nexus policy, both of which are ambitious in the spirit of mission-oriented policies and delivering on the SDGs.
Sustainability Analysis of a ZnO-NaCl-Based Capacitor Using Accelerated Life Testing and an Intelligent Modeling Approach
Authors: Sharma Pardeep Kumar , Bhargava Cherry , Kotecha Ketan
Published: September 2021

From small toys to satellites, capacitors play a vital role as an energy storage element, filtering or controlling other critical tasks. This research paper focuses on estimating the remaining useful life of a nanocomposite-based fabricated capacitor using various experimental and artificial intelligence techniques. Accelerated life testing is used to explore the sustainability and remaining useful life of the fabricated capacitor. The acceleration factors affecting the health of capacitors are investigated, and experiments are designed using Taguchi’s approach. The remaining useful lifetime of the fabricated capacitor is calculated using a statistical technique, i.e., regression analysis using Minitab 18.1 software. An expert model is designed using artificial neural networks (ANN), which warns the user of any upcoming faults and failures. The average remaining useful life of the fabricated capacitor, using accelerated life testing, regression, and artificial neural network, is reported as 13,724.3 h, 14,515.9 h, and 14,247.1 h, respectively. A comparison analysis is conducted, and performance metrics are analyzed to opt for the most efficient technique for the prediction of the remaining useful life of the fabricated capacitor, which confirms 93.83% accuracy using the statistical method and 95.82% accuracy using artificial neural networks. The root mean square error (RMSE) of regression and artificial neural networks is found to be 0.102 and 0.167, respectively, which validates the consistency of the reliability methods.
Optimization of a Combination of Thermal Insulation and Cool Roof for the Refurbishment of Social Housing in Southern Spain
Authors: Domínguez-Torres Carlos-Antonio , Domínguez-Torres Helena , Domínguez-Delgado Antonio
Published: September 2021

Social housing built in the middle of the last century in Spain suffers from poor thermal insulation conditions that cause situations of discomfort and energy poverty. For this reason, the energetic refurbishment of the envelope of this social building stock is necessary to overcome these situations and reduce energy consumption aimed at achieving interior comfort for its occupants. The goal of this work is to optimize a constructive solution that combines cool roof techniques with the use of thermal insulation applied to the refurbishment of the roof of buildings belonging to a quarter of social housing in Seville, Spain. The optimization analysis is based on the computation of the energy performance of the roofs when the energy retrofitting measure is applied, considering a variety of combinations of solar reflective coatings and insulation layer thickness, performing a dynamic analysis that accounts for the aging effect of the cool coats on the monthly roof energy performance and on the economic balance for the whole life cycle (LC) span. Economic and energy optimization analysis show that a suitable combination of cool roof emissivity and insulation layer thickness produces significant savings in the operational energy and in the economic profitability of the proposed retrofitting measure: the optimum combination obtained provides for the entire life cycle timespan an energy savings of 5.71 GJ/m2 and a cost savings equivalent to the 63.1% of the total costs when compared to the non-refurbished roof. The application of a time-dependent pattern for the changes on time produced by the aging effect on the cool roof emissivity, and its effects on the optimization of the combination of cool roof and insulation layer, can be considered novel in literature, both from an energy and an economic point of view.
Planning Tourism in Protected Natural Areas: Safety, Soft Law and Conflict Management between Beach Users. The Case of Surf in Aljezur, Portugal
Authors: Machado Virgílio , Contreiras Joaquim Pinto , Duarte Ana Patrícia
Published: September 2021

The intensification of tourism in coastal areas can increase planning problems, with potential conflicts amongst beach users affecting their safety perceptions and, ultimately, their tourist experience. Therefore, this constitutes an important concern for local authorities. The present study was conducted on an environmentally sensitive tourism destination located in a protected natural area in the Algarve, Portugal, with a quite significant level of surf tourism activities-the Aljezur municipality. In total, 245 surfers and 282 bathers were surveyed as these beach user groups have been observed to have a potential for intergroup conflict. Data were collected regarding their perceptions of personal safety, conflicts between beach users, and conflict management strategies. The respondents were also surveyed regarding how local authorities can provide strategies of soft law for a more sustainable management of surfing tourism. The findings revealed a consensus about the safety of Aljezur beaches and existence of perceived low conflict levels amongst beach users. The strategies more valued by respondents to promote surfing tourism development in the territory include the preservation of the natural resources and the developed of local regulation. Overall, these findings can be useful to the sustainable management of the surfing tourism in the territory.
Spatial and Temporal Variations of Nitrogen and Phosphorus in Surface Water and Groundwater of Mudong River Watershed in Huixian Karst Wetland, Southwest China
Authors: Pan Linyan , Dai Junfeng , Wu Zhiqiang , Huang Liangliang , Wan Zupeng , Han Junlei , Li Zhangnan
Published: September 2021

When considering the factors affecting the spatial and temporal variation of nitrogen and phosphorus in karst watersheds, the unique karst hydrogeology as an internal influencing factor cannot be ignored, as well as natural factors such as meteorological hydrology and external factors such as human activities. A watershed-scale field investigation was completed to statistically analyze spatial and temporal dynamics of nitrogen and phosphorus through the regular monitoring and collection of surface water and shallow groundwater in the agricultural-dominated Mudong River watershed in the Huixian Karst Wetland over one year (May 2020 to April 2021). Our research found that non-point source pollution of nitrogen (84.5% of 239 samples TN > 1.0 mg/L) was more serious than phosphorus (7.5% of 239 samples TP > 0.2 mg/L) in the study area, and shallow groundwater nitrogen pollution (98.3% of 118 samples TN > 1.0 mg/L) was more serious than surface water (68.6% of 121 samples TN > 1.0 mg/L). In the three regions with different hydrodynamic features, the TN concentration was higher and dominated by NO3−-N in the river in the northern recharge area, while the concentrations of TN and TP were the highest in shallow groundwater wells in the central wetland core area and increased along the surface water flow direction in the western discharge area. This research will help improve the knowledge about the influence of karst hydrodynamic features on the spatial patterns of nitrogen and phosphorus in water, paying attention to the quality protection and security of water in karst areas with a fragile water ecological environment.
Real-Time DDoS Attack Detection System Using Big Data Approach
Authors: Awan Mazhar Javed , Farooq Umar , Babar Hafiz Muhammad Aqeel , Yasin Awais , Nobanee Haitham , Hussain Muzammil , Hakeem Owais , Zain Azlan Mohd
Published: September 2021

Currently, the Distributed Denial of Service (DDoS) attack has become rampant, and shows up in various shapes and patterns, therefore it is not easy to detect and solve with previous solutions. Classification algorithms have been used in many studies and have aimed to detect and solve the DDoS attack. DDoS attacks are performed easily by using the weaknesses of networks and by generating requests for services for software. Real-time detection of DDoS attacks is difficult to detect and mitigate, but this solution holds significant value as these attacks can cause big issues. This paper addresses the prediction of application layer DDoS attacks in real-time with different machine learning models. We applied the two machine learning approaches Random Forest (RF) and Multi-Layer Perceptron (MLP) through the Scikit ML library and big data framework Spark ML library for the detection of Denial of Service (DoS) attacks. In addition to the detection of DoS attacks, we optimized the performance of the models by minimizing the prediction time as compared with other existing approaches using big data framework (Spark ML). We achieved a mean accuracy of 99.5% of the models both with and without big data approaches. However, in training and testing time, the big data approach outperforms the non-big data approach due to that the Spark computations in memory are in a distributed manner. The minimum average training and testing time in minutes was 14.08 and 0.04, respectively. Using a big data tool (Apache Spark), the maximum intermediate training and testing time in minutes was 34.11 and 0.46, respectively, using a non-big data approach. We also achieved these results using the big data approach. We can detect an attack in real-time in few milliseconds.
Numerical Study on Effects of Pipeline Geometric Parameters on Release Characteristics of Gas Extinguishing Agent
Authors: Li Quanwei , Li Zongyu , Chen Ruiyu , Zhang Zhaojun , Ge Hui , Zhou Xia , Pan Renming
Published: September 2021

In order to guide the optimization design of the pipeline network of the aircraft-fixed gas fire extinguishing system and improve its fire extinguishing performance, FLUENT software was used to simulate the influence of pipeline parameters such as diameter, length, and roughness on the release characteristics of the fire extinguishing agent. It can be found that the extinguishing agent can be divided into liquid and vapor extinguishing agents in the fire extinguishing pipeline system during the release. The spatial distribution and proportion of the liquid and vapor extinguishing agents are asymmetric. Results show that the peak value of the pressure drop rate (dPmax) has a good quadratic function relationship with the pipeline diameter (D) and the functional relationship is dPmax=−22.224+2.782D+0.089D2, which means that the peak value increased significantly with the increase in the pipeline diameter. Moreover, when the pipeline diameter is 25 mm, the average pressure drop rate of the vessel is about 35.02 MPa/s, which is 5.97 times the value of the average pressure drop rate when the pipeline diameter is 10 mm. With the increase in the pipeline diameter, the release time decreases significantly, the mass flow rate increases obviously, while the gasification ratio decreases rapidly at first and then increases slightly. The pipeline length also has a significant influence on the release characteristics of the extinguishing agent. With the increase in the pipeline length, the release time and the gasification ratio increase linearly, while the mass flow rate decreases linearly. Compared with the pipeline diameter and pipeline length, the influence of the pipeline roughness on the release characteristics of the extinguishing agent is weak. With the increase in the pipeline roughness, the release time and the gasification ratio of the extinguishing agent increases slowly, while the mass flow rate decreases slowly.
Deep Neural Network Compression for Plant Disease Recognition
Authors: Wang Ruiqing , Zhang Wu , Ding Jiuyang , Xia Meng , Wang Mengjian , Rao Yuan , Jiang Zhaohui
Published: September 2021

Deep neural networks (DNNs) have become the de facto standard for image recognition tasks, and their applications with respect to plant diseases have also obtained remarkable results. However, the large number of parameters and high computational complexities of these network models make them difficult to deploy on farms in remote areas. In this paper, focusing on the problems of resource constraints and plant diseases, we propose a DNN-based compression method. In order to reduce computational burden, this method uses lightweight fully connected layers to accelerate reasoning, pruning to remove redundant parameters and reduce multiply–accumulate operations, knowledge distillation instead of retraining to restore the lost accuracy, and then quantization to compress the size of the model further. After compressing the mainstream VGGNet and AlexNet models, the compressed versions are applied to the Plant Village dataset of plant disease images, and a performance comparison of the models before and after compression is obtained to verify the proposed method. The results show that the model can be compressed to 0.04 Mb with an accuracy of 97.09%. This experiment also proves the effectiveness of knowledge distillation during the pruning process, and compressed models are more efficient than prevalent lightweight models.
From Neural Command to Robotic Use: The Role of Symmetry/Asymmetry in Postural and Locomotor Activities
Authors: Blanchet Mariève , Guertin Pierre , Pilon Francine , Gorce Philippe , Prince François
Published: September 2021

This article deepens a reflection on why and how symmetry/asymmetry affects the motor and postural behavior from the neural source, uterine development, child maturation, and how the notion of symmetry/asymmetry has been applied to walking robot design and control. The concepts of morphology and tensegrity are also presented to illustrate how the biological structures have been used in both sciences and arts. The development of the brain and the neuro-fascia-musculoskeletal system seems to be quite symmetric from the beginning of life through to complete maturity. The neural sources of movements (i.e., central pattern generators) are able to produce both symmetric or asymmetric responses to accommodate to environmental constraints and task requirements. Despite the fact that the human development is mainly symmetric, asymmetries already regulate neurological and physiological development. Laterality and sports training could affect natural musculoskeletal symmetry. The plasticity and flexibility of the nervous system allows the abilities to adapt and compensate for environmental constraints and musculoskeletal asymmetries in order to optimize the postural and movement control. For designing humanoid walking robots, symmetry approaches have been mainly used to reduce the complexity of the online calculation. Applications in neurological retraining and rehabilitation should also be considered.
A SPH-GFDM Coupled Method for Elasticity Analysis
Authors: Tong Zheming , Peng Zezhao , Yue Yuqing , Chen Zhou
Published: September 2021

SPH (smoothed particle hydrodynamics) is one of the oldest meshless methods used to simulate mechanics of continuum media. Despite its great advantage over the traditional grid-based method, implementing boundary conditions in SPH is not easy and the accuracy near the boundary is low. When SPH is applied to problems for elasticity, the displacement or stress boundary conditions should be suitably handled in order to achieve fast convergence and acceptable numerical accuracy. The GFDM (generalized finite difference method) can derive explicit formulae for required partial derivatives of field variables. Hence, a SPH–GFDM coupled method is developed to overcome the disadvantage in SPH. This coupled method is applied to 2-D elastic analysis in both symmetric and asymmetric computational domains. The accuracy of this method is demonstrated by the excellent agreement with the results obtained from FEM (finite element method) regardless of the symmetry of the computational domain. When the computational domain is multiply connected, this method needs to be further improved.
Gain-Loss Evaluation-Based Generic Selection for Steganalysis Feature
Authors: Jin Ruixia , Wang Yihao , Ma Yuanyuan , Li Tao , Duan Xintao
Published: September 2021

Fewer contribution feature components in the image high-dimensional steganalysis feature are able to increase the spatio-temporal complexity of detecting the stego images, and even reduce the detection accuracy. In order to maintain or even improve the detection accuracy while effectively reducing the dimension of the DCTR steganalysis feature, this paper proposes a new selection approach for DCTR feature. First, the asymmetric distortion factor and information gain ratio of each feature component are improved to measure the difference between the symmetric cover and stego features, which provides the theoretical basis for selecting the feature components that contribute to a great degree to detecting the stego images. Additionally, the feature components are arranged in descending order rely on the two measurement criteria, which provides the basis for deleting the components. Based on the above, removing feature components that are ranked larger differently according to two criteria. Ultimately, the preserved feature components are used as the final selected feature for training and detection. Comparison experiments with existing classical approaches indicate that this approach can effectively reduce the feature dimension while maintaining or even improving the detection accuracy. At the same time, it can reduce the detection spatio-temporal complexity of the stego images.
Hand Preference in Adults’ Referential Gestures during Storytelling: Testing for Effects of Bilingualism, Language Ability, Sex and Age
Authors: Nicoladis Elena , Shirazi Safi
Published: September 2021

Previous studies have shown that gestures are mediated by the left hemisphere. The primary purpose of this study was to test whether most gestures are also asymmetrical, i.e., produced with the right hand. We also tested four predictors of the degree of right-hand gesture use: bilingualism, language ability, sex, and age. These factors have been related to differences in the degree of language lateralization. English monolinguals, French–English bilinguals, and French monolinguals watched a cartoon and told the story back. For the gestures they produced while speaking, we calculated the percentage produced with the right hand. As predicted, the majority of gestures were right-handed (60%). Bilingualism, language ability, and age were not significantly related to hand choice in either English or French. In English, males tended to produce more right-handed gestures than females. These results raise doubts as to whether hand preference in gestures reflects speech lateralization. We discuss possible alternative explanations for a right-hand preference.
Spin Quantization in Heavy Ion Collision
Authors: Zheng Hua , Bonasera Aldo
Published: September 2021

We analyzed recent experimental data on the disassembly of 28Si into 7α in terms of a hybrid α-cluster model. We calculated the probability of breaking into several α-like fragments for high l-spin values for identical and non-identical spin zero nuclei. Resonant energies were found for each l-value and compared to the data and other theoretical models. Toroidal-like structures were revealed in coordinate and momentum space when averaging over many events at high l. The transition from quantum to classical mechanics is highlighted.
Some Trapezoid Intuitionistic Fuzzy Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple-Attribute Decision Making
Authors: Dong Zheng , Geng Yushui
Published: September 2021

In order to solve multiple-attribute group decision-making (MAGDM) problems under a trapezoid intuitionistic fuzzy linguistic (TIFL) environment and the relationships between multiple input parameters needed, in this paper, we extend the Maclaurin symmetric mean (MSM) operators to TIFL numbers (TIFLNs). Some new aggregation operators are proposed, including the trapezoid intuitionistic fuzzy linguistic Maclaurin symmetric mean (TIFLMSM) operator, trapezoid intuitionistic fuzzy linguistic generalized Maclaurin symmetric mean (TIFLGMSM) operator, trapezoid intuitionistic fuzzy linguistic weighted Maclaurin symmetric mean (TIFLWMSM) operator and trapezoid intuitionistic fuzzy linguistic weighted generalized Maclaurin symmetric mean (TIFLWGMSM) operator. Next, based on the TIFLWMSM and TIFLWGMSM operators, two methods are presented to deal with MAGDM problems. Finally, there is a numerical example to verify the effectiveness and feasibility of the proposed approaches.
Optimizing the Tolerance for the Products with Multi-Dimensional Chains via Simulated Annealing
Authors: Tsung Chen-Kun
Published: September 2021

The assembly is the last process of controlling the product quality during manufacturing. The installation guidance should provide the appropriate assembly information, e.g., to specify the components in each product. The installation guidance with low quality results in rework or the resource waste from the failure products. This article extends the dimensional chain assembly problem proposed by Tsung et al. to consider the multiple dimensional chains in the product. Since there are multiple dimensional chains in a product, the installation guidance should consider inseparability and acceptability as computing the installation guidance. The inseparability means that the qualities of all dimensional chains in the part should be evaluated together without separation, while the acceptability stands for that the size of each product should be satisfied with the specification. The simulated annealing (SA) algorithm is applied to design the assembly guidance optimizer named as AGOMDC to compute the assembly guidance in the dimensional chain assembly problem with multiple dimensional chains. Since SA has high performance in searching neighbor solutions, the proposed approach could converge rapidly. Thus, proposed AGOMDC could be applied in real-world application for the implementation consideration. The simulations consist of two parts: the feasibility evaluation and the algorithm configuration discussion. The first part is to verify the inseparability and acceptability that are the hard constraints of the assembly problem for the proposed AGOMDC, and the second one is to analyze the algorithm configurations to calculate the assembly guidance with 80% quality. The simulation results show that the inseparability and acceptability are achieved, while the proposed AGOMDC only requires more than two seconds to derive the results. Moreover, the recommended algorithm configurations are derived for evaluate the required running time and product quality. The configurations with product quality 80% are that the temperature descent rate is 0.9, the initial temperature is larger than 1000, and the iteration recommended function is derived based on the problem scale. The proposed AGOMDC not only helps the company to save the time of rework and prevent the resource waste of the failure products, but is also valuable for the automatic assembly in scheduling the assembly processes.
On Eigenfunctions and Eigenvalues of a Nonlocal Laplace Operator with Multiple Involution
Authors: Turmetov Batirkhan , Karachik Valery
Published: September 2021

We study the eigenfunctions and eigenvalues of the boundary value problem for the nonlocal Laplace equation with multiple involution. An explicit form of the eigenfunctions and eigenvalues for the unit ball are obtained. A theorem on the completeness of the eigenfunctions of the problem under consideration is proved.
The Inequalities of Merris and Foregger for Permanents
Authors: Udayan Divya K. , Somasundaram Kanagasabapathi
Published: September 2021

Conjectures on permanents are well-known unsettled conjectures in linear algebra. Let A be an n×n matrix and Sn be the symmetric group on n element set. The permanent of A is defined as perA=∑σ∈Sn∏i=1naiσ(i). The Merris conjectured that for all n×n doubly stochastic matrices (denoted by Ωn), nperA≥min1≤i≤n∑j=1nperA(j|i), where A(j|i) denotes the matrix obtained from A by deleting the jth row and ith column. Foregger raised a question whether per(tJn+(1−t)A)≤perA for 0≤t≤nn−1 and for all A∈Ωn, where Jn is a doubly stochastic matrix with each entry 1n. The Merris conjecture is one of the well-known conjectures on permanents. This conjecture is still open for n≥4. In this paper, we prove the Merris inequality for some classes of matrices. We use the sub permanent inequalities to prove our results. Foregger’s inequality is also one of the well-known inequalities on permanents, and it is not yet proved for n≥5. Using the concepts of elementary symmetric function and subpermanents, we prove the Foregger’s inequality for n=5 in [0.25, 0.6248]. Let σk(A) be the sum of all subpermanents of order k. Holens and Dokovic proposed a conjecture (Holen–Dokovic conjecture), which states that if A∈Ωn,A≠Jn and k is an integer, 1≤k≤n, then σk(A)≥(n−k+1)2nkσk−1(A). In this paper, we disprove the conjecture for n=k=4.
Closed-Form Solution of Adiabatic Particle Trajectories in Axis-Symmetric Magnetic Fields
Authors: Sattin Fabio , Escande Dominique Franck
Published: September 2021

The dynamics of a low-energy charged particle in an axis-symmetric magnetic field is known to be a regular superposition of periodic—although possibly incommensurate—motions. The projection of the particle orbit along the two non-ignorable coordinates (x,y) may be expressed in terms of each other: y=y(x), yet—to our knowledge—such a functional relation has never been directly produced in literature, but only by way of a detour: first, equations of motion are solved, yielding x=x(t),y=y(t), and then one of the two relations is inverted, x(t)→t(x). In this paper, we present a closed-form functional relation which allows us to express coordinates of the particle’s orbit without the need to pass through the hourly law of motion.
On the Total Neighbor Sum Distinguishing Index of IC-Planar Graphs
Authors: Zhang Donghan , Li Chao , Chao Fugang
Published: September 2021

A proper total k-coloring ϕ of G with ∑z∈EG(u)∪{u}ϕ(z)≠∑z∈EG(v)∪{v}ϕ(z) for each uv∈E(G) is called a total neighbor sum distinguishing k-coloring, where EG(u)={uv|uv∈E(G)}. Pilśniak and Woźniak conjectured that every graph with maximum degree Δ exists a total neighbor sum distinguishing (Δ+3)-coloring. In this paper, we proved that any IC-planar graph with Δ≥12 satisfies this conjecture, which improves the result of Song and Xu.
Multirobot Formation with Sensor Fusion-Based Localization in Unknown Environment
Authors: Le Anh Vu , Apuroop Koppaka Ganesh Sai , Konduri Sriniketh , Do Huy , Elara Mohan Rajesh , Xi Ray Cheng Chern , Wen Raymond Yeong Wei , Vu Minh Bui , Duc Phan Van , Tran Minh
Published: September 2021

Multirobot cooperation enhancing the efficiency of numerous applications such as maintenance, rescue, inspection in cluttered unknown environments is the interesting topic recently. However, designing a formation strategy for multiple robots which enables the agents to follow the predefined master robot during navigation actions without a prebuilt map is challenging due to the uncertainties of self-localization and motion control. In this paper, we present a multirobot system to form the symmetrical patterns effectively within the unknown environment deployed randomly. To enable self-localization during group formatting, we propose the sensor fusion system leveraging sensor fusion from the ultrawideband-based positioning system, Inertial Measurement Unit orientation system, and wheel encoder to estimate robot locations precisely. Moreover, we propose a global path planning algorithm considering the kinematic of the robot’s action inside the workspace as a metric space. Experiments are conducted on a set of robots called Falcon with a conventional four-wheel skid steering schematic as a case study to validate our proposed path planning technique. The outcome of our trials shows that the proposed approach produces exact robot locations after sensor fusion with the feasible formation tracking of multiple robots system on the simulated and real-world experiments.
Research and Application of Improved Clustering Algorithm in Retail Customer Classification
Authors: Fang Chu , Liu Haiming
Published: September 2021

Clustering is a major field in data mining, which is also an important method of data partition or grouping. Clustering has now been applied in various ways to commerce, market analysis, biology, web classification, and so on. Clustering algorithms include the partitioning method, hierarchical clustering as well as density-based, grid-based, model-based, and fuzzy clustering. The K-means algorithm is one of the essential clustering algorithms. It is a kind of clustering algorithm based on the partitioning method. This study’s aim was to improve the algorithm based on research, while with regard to its application, the aim was to use the algorithm for customer segmentation. Customer segmentation is an essential element in the enterprise’s utilization of CRM. The first part of the paper presents an elaboration of the object of study, its background as well as the goal this article would like to achieve; it also discusses the research the mentality and the overall content. The second part mainly introduces the basic knowledge on clustering and methods for clustering analysis based on the assessment of different algorithms, while identifying its advantages and disadvantages through the comparison of those algorithms. The third part introduces the application of the algorithm, as the study applies clustering technology to customer segmentation. First, the customer value system is built through AHP; customer value is then quantified, and customers are divided into different classifications using clustering technology. The efficient CRM can thus be used according to the different customer classifications. Currently, there are some systems used to evaluate customer value, but none of them can be put into practice efficiently. In order to solve this problem, the concept of continuous symmetry is introduced. It is very important to detect the continuous symmetry of a given problem. It allows for the detection of an observable state whose components are nonlinear functions of the original unobservable state. Thus, we built an evaluating system for customer value, which is in line with the development of the enterprise, using the method of data mining, based on the practical situation of the enterprise and through a series of practical evaluating indexes for customer value. The evaluating system can be used to quantify customer value, to segment the customers, and to build a decision-supporting system for customer value management. The fourth part presents the cure, mainly an analysis of the typical k-means algorithm; this paper proposes two algorithms to improve the k-means algorithm. Improved algorithm A can get the K automatically and can ensure the achievement of the global optimum value to some degree. Improved Algorithm B, which combines the sample technology and the arrangement agglomeration algorithm, is much more efficient than the k-means algorithm. In conclusion, the main findings of the study and further research directions are presented.
Recent Advances in Handedness Genetics
Authors: Paracchini Silvia
Published: September 2021

Around the world, about 10% people prefer using their left-hand. What leads to this fixed proportion across populations and what determines left versus right preference at an individual level is far from being established. Genetic studies are a tool to answer these questions. Analysis in twins and family show that about 25% of handedness variance is due to genetics. In spite of very large cohorts, only a small fraction of this genetic component can be pinpoint to specific genes. Some of the genetic associations identified so far provide evidence for shared biology contributing to both handedness and cerebral asymmetries. In addition, they demonstrate that handedness is a highly polygenic trait. Typically, handedness is measured as the preferred hand for writing. This is a very convenient measure, especially to reach large sample sizes, but quantitative measures might capture different handedness dimensions and be better suited for genetic analyses. This paper reviews the latest findings from molecular genetic studies as well as the implications of using different ways of assessing handedness.
Mirror and Circular Symmetry of Autofocusing Beams
Authors: Khonina Svetlana N.
Published: September 2021

This article demonstrates the crucial importance of the symmetrization method for the formation of autofocusing beams. It is possible to impart autofocusing properties to rather arbitrary distributions, for example, truncated and inverted classical modes (such as Hermite–Gaussian, Laguerre–Gaussian, and Bessel modes) or shift the fundamental Gaussian beam by inserting mirror or circular symmetry. The most convenient for controlling autofocusing characteristics is the truncated sinus function with a power-law argument dependence. In this case, superlinear chirp beams (with power q > 2) exhibit sudden and more abrupt autofocusing than sublinear chirp beams (with power 1 < q < 2). Comparison of the different beams’ propagation is performed using fractional Fourier transform, which allows obtaining the field distribution in any paraxial region (both in the Fresnel and Fraunhofer diffraction regions). The obtained results expand the capabilities of structured beams in various applications in optics and photonics.
Grounding Fault Model of Low Voltage Direct Current Supply and Utilization System for Analyzing the System Grounding Fault Characteristics
Authors: Liu Jie , Sun Kaiqi , Ma Zhao , Liu Zhijie , Li Kejun
Published: September 2021

Grounding fault analysis is of vital importance for low voltage direct current (LVDC) supply and utilization systems. However, the existing DC grounding fault model is inappropriate for LVDC supply and utilization system. In order to provide an appropriate assessment model for the DC grounding fault impact on the LVDC supply and utilization system, an LVDC supply and utilization system grounding fault model is proposed in this paper. Firstly, the model is derived by utilizing capacitor current and voltage as the system state variable, which considers the impact of the converter switch state on the topology of the fault circuit. The variation of system state parameters under various fault conditions can be easily obtained by inputting system state data in normal conditions as the initial value. Then, a model solution algorithm for the proposed model is utilized to calculated the maximum fault current, the system maximum fault current with different grounding resistance is simple to acquired based on the solution algorithm. The calculation results demonstrate that grounding resistance and structure of LVDC supply and utilization system have remarkable impacts on the transient current. The effectiveness of the proposed model is verified in PSCAD/EMTDC. The simulation results indicate that the proposed method is appropriate for the system fault analysis under various fault conditions with different grounding resistance and the proposed model can offer theoretical guidance for system fault protection.
Probing Many-Body Systems near Spectral Degeneracies
Authors: Ziegler Klaus
Published: September 2021

The diagonal elements of the time correlation matrix are used to probe closed quantum systems that are measured at random times. This enables us to extract two distinct parts of the quantum evolution, a recurrent part and an exponentially decaying part. This separation is strongly affected when spectral degeneracies occur, for instance, in the presence of spontaneous symmetry breaking. Moreover, the slowest decay rate is determined by the smallest energy level spacing, and this decay rate diverges at the spectral degeneracies. Probing the quantum evolution with the diagonal elements of the time correlation matrix is discussed as a general concept and tested in the case of a bosonic Josephson junction. It reveals for the latter characteristic properties at the transition to Hilbert-space localization.
Two Isospectral-Nonisospectral Super-Integrable Hierarchies and Related Invariant Solutions
Authors: Lu Huanhuan , Zhang Yufeng
Published: September 2021

In this article, we adopt two kinds of loop algebras corresponding to the Lie algebra B(0,1) to introduce two line spectral problems with different numbers of even and odd superfunctions. Through generalizing the time evolution λt to a polynomial of λ, two isospectral-nonisospectral super integrable hierarchies are derived in terms of Tu scheme and zero-curvature equation. Among them, the first super integrable hierarchy is further reduced to generalized Fokker–Plank equation and special bond pricing equation, as well as an explicit super integrable system under the choice of specific parameters. More specifically, a super integrable coupled equation is derived and the corresponding integrable properties are discussed, including the Lie point symmetries and one-parameter Lie symmetry groups as well as group-invariant solutions associated with characteristic equation.
Deformations of Subway Tunnels Induced by the Overcrossing Jacked Box Tunnels
Authors: Liu Wei , Wu Yinlong , Zhao Huajing , Xu Xiangyang , Miao Lingyi
Published: September 2021

The rectangular utility tunnels have been increasingly built in urban areas in recent decades. In this paper, a case of jacked box tunnels built closely over-crossing the existing subway tunnels in Suzhou, China, is presented. The tunneling-induced deformation of the subway tunnels is measured and analyzed. The measurement indicates that the subway tunnels are uplifted and subjected to the overcrossing box tunneling. As compared, the longitudinal deformation of the range that locates under the box tunnels is more significant than that outside the range. The tunneling-induced deformation of the left subway tunnel is relatively higher than that of the right one. The numerical simulation is performed for validation. The numerical result is agreed with the in-situ measurements. Moreover, the simulation reveals that the presence of friction in jacked tunnels causes the extra uplift deformation of subway tunnels. The higher the friction, the is the deformation. It is affirmed that using the effective lubrication not only facilitates the tunnel jacking but also inabilities the tunneling-induced deformation of underlying tunnels
SLAC and SNAC Wrist: The Top Five Things That General Radiologists Need to Know
Authors: Kompoliti Eliza , Prodromou Mikaella , Karantanas Apostolos H.
Published: September 2021

Wrist osteoarthritis (OA) is a common painful condition that affects the patient’s quality of life by limiting the range of wrist motion and grip strength. Wrist OA often results from scapholunate advanced collapse (SLAC) or scaphoid nonunion advanced collapse (SNAC). Early diagnosis of SLAC and SNAC is crucial because it affects treatment planning. Thus, radiologists should be able to interpret the early imaging findings. This pictorial review discusses the pathophysiology and the clinical symptoms of SLAC and SNAC and presents the imaging findings with emphasis on the proper imaging algorithm. Finally, it focuses on the treatment according to the degenerative status of each of these patterns.