bluuebunny/crossref_metadata_2025 huggingface dataset:
Binocular Rivalry Impact on Macroblock-Loss Error Concealment for Stereoscopic 3D Video Transmission
Authors: Hasan Md Mehedi , Hossain Md. Azam , Alotaibi Naif , Arnold John F. , Azad AKM
Published: March 2023

Three-dimensional video services delivered through wireless communication channels have to deal with numerous challenges due to the limitations of both the transmission channel’s bandwidth and receiving devices. Adverse channel conditions, delays, or jitters can result in bit errors and packet losses, which can alter the appearance of stereoscopic 3D (S3D) video. Due to the perception of dissimilar patterns by the two human eyes, they can not be fused into a stable composite pattern in the brain and hence try to dominate by suppressing each other. Thus, a psychovisual sensation that is called binocular rivalry occurs. As a result, undetectable changes causing irritating flickering effects are seen, leading to visual discomforts such as eye strain, headache, nausea, and weariness. This study addresses the observer’s quality of experience (QoE) by analyzing the binocular rivalry impact on the macroblock (MB) losses in a frame and its error propagation due to predictive frame encoding in stereoscopic video transmission systems. To simulate the processing of experimental videos, the Joint Test Model (JM) reference software has been used as it is recommended by the International Telecommunication Union (ITU). Existing error concealing techniques were then applied to the contiguous lost MBs for a variety of transmission impairments. In order to validate the authenticity of the simulated packet loss environment, several objective evaluations were carried out. Standard numbers of subjects were then engaged in the subjective testing of common 3D video sequences. The results were then statistically examined using a standard Student’s t-test, allowing the impact of binocular rivalry to be compared to that of a non-rivalry error condition. The major goal is to assure error-free video communication by minimizing the negative impacts of binocular rivalry and boosting the ability to efficiently integrate 3D video material to improve viewers’ overall QoE.
BICM-ID Labeling-Based Recipient Identification in a Heterogeneous Network
Authors: Krasicki Maciej
Published: March 2023

The concept of labeling-based recipient identification (LABRID) for bit-interleaved coded modulation with iterative decoding (BICM-ID) is revisited. LABRID allows addressing a message recipient station in a wireless network by using an individual labeling map without compromising error performance. This eliminates the need to use any byte of the data frame to carry the recipient address explicitly. In addition, the destination of the frame can be determined in parallel with a BICM-ID decoding procedure in the receiver’s physical layer. Therefore, the MAC layer is not involved in processing the vast majority of frames transmitted in a network. Previously, it was shown that LABRID works fine if there are only LABRID-compatible stations within the network, and every receiver can reject frames destined for other receivers. This paper considers a scenario in which LABRID-compatible BICM-ID stations and legacy BICM stations coexist in the same network. A few experiments show that the LABRID receiver can reject an old-fashioned BICM frame by judging the convergence of the iterative decoding process. It also turns out that the legacy BICM receiver can identify and dismiss the LABRID-type frames thanks to the standard cyclic redundancy check (CRC) procedure.
Path Planning and Motion Control of Indoor Mobile Robot under Exploration-Based SLAM (e-SLAM)
Authors: Roy Rohit , Tu You-Peng , Sheu Long-Jye , Chieng Wei-Hua , Tang Li-Chuan , Ismail Hasan
Published: March 2023

Indoor mobile robot (IMR) motion control for e-SLAM techniques with limited sensors, i.e., only LiDAR, is proposed in this research. The path was initially generated from simple floor plans constructed by the IMR exploration. The path planning starts from the vertices which can be traveled through, proceeds to the velocity planning on both cornering and linear motion, and reaches the interpolated discrete points joining the vertices. The IMR recognizes its location and environment gradually from the LiDAR data. The study imposes the upper rings of the LiDAR image to perform localization while the lower rings are for obstacle detection. The IMR must travel through a series of featured vertices and perform the path planning further generating an integrated LiDAR image. A considerable challenge is that the LiDAR data are the only source to be compared with the path planned according to the floor map. Certain changes still need to be adapted into, for example, the distance precision with relevance to the floor map and the IMR deviation in order to avoid obstacles on the path. The LiDAR setting and IMR speed regulation account for a critical issue. The study contributed to integrating a step-by-step procedure of implementing path planning and motion control using solely the LiDAR data along with the integration of various pieces of software. The control strategy is thus improved while experimenting with various proportional control gains for position, orientation, and velocity of the LiDAR in the IMR.
The Impact of Profile Genesis and Land Use of Histosol on Its Organic Substance Stability and Humic Acid Quality at the Molecular Level
Authors: Amaleviciute-Volunge Kristina , Volungevicius Jonas , Ceponkus Justinas , Platakyte Rasa , Mockeviciene Ieva , Slepetiene Alvyra , Lepane Viia
Published: March 2023

This study is designed to evaluate soil organic matter (SOM) quality indicators: molecular indicators of dissolved organic matter (DOM) and hydrophobicity of humic acid (HA), distribution of quantity in humified and labile fractions of histosols during renaturalization. The aim is to determine the differences in the qualitative composition of humic acids at the molecular level, which are decided by the previous tillage and genesis, and to evaluate the impact of anthropogenization on the peat soil according to hydrophobicity, as well as to estimate the impact of soil genesis and removing peat layer. Soil samples were taken from the three Sapric Histosol (according to WRB2022) profiles and the 0–30 cm layer in three field replicates (Lithuania, Radviliskis mun.). Our study suggested that in the differently managed drained Sapric Histosol under renaturalization, the most significant changes occurred in the topsoil layer (0–30 cm), in which an increase in the content of SOM particles 106–2 µm in size. It is expedient to grow perennial grasses and legumes to maintain the soil organic carbon stability mobile humic acids to mobile fulvic acids ratio (MHA:MFA 0.83 to 0.86). An evaluation of the quality of HA (E4:E6) revealed their highest maturity in the unfertilized perennial grasses (3.88) and crop rotation (3.87) with grasses. The highest concentrations of hydrophilic groups (ratio of the C=O to O-H) were found in Sapric Histosol under deciduous hardwood forest (12.33). The lowest hydrophilicity (9.25 and 9.36) was of the crop rotation Sapric Histosol with removed peat layer. The most sustainable use of drained Sapric Histosol in the context of the sustainability and quality of its humus substances should be associated with the formation of perennial grass and clover grassland and the cultivation of deciduous hardwood. Therefore, the horizon forms on the top part of the profile, which protects deeper Histosolic material layers from its mineralization.
Toward Designing a Secure Authentication Protocol for IoT Environments
Authors: Hosseinzadeh Mehdi , Malik Mazhar Hussain , Safkhani Masoumeh , Bagheri Nasour , Le Quynh Hoang , Tightiz Lilia , Mosavi Amir H.
Published: March 2023

Authentication protocol is a critical part of any application to manage the access control in many applications. A former research recently proposed a lightweight authentication scheme to transmit data in an IoT subsystem securely. Although the designers presented the first security analysis of the proposed protocol, that protocol has not been independently analyzed by third-party researchers, to the best of our knowledge. On the other hand, it is generally agreed that no cryptosystem should be used in a practical application unless its security has been verified through security analysis by third parties extensively, which is addressed in this paper. Although it is an efficient protocol by design compared to other related schemes, our security analysis identifies the non-ideal properties of this protocol. More specifically, we show that this protocol does not provide perfect forward secrecy. In addition, we show that it is vulnerable to an insider attacker, and an active insider adversary can successfully recover the shared keys between the protocol’s entities. In addition, such an adversary can impersonate the remote server to the user and vice versa. Next, the adversary can trace the target user using the extracted information. Finally, we redesign the protocol such that the enhanced protocol can withstand all the aforementioned attacks. The overhead of the proposed protocol compared to its predecessor is only 15.5% in terms of computational cost.
Influence of Recycled Plastic Incorporation as Coarse Aggregates on Concrete Properties
Authors: Ali Khawar , Saingam Panumas , Qureshi Muhammad Irshad , Saleem Shahzad , Nawaz Adnan , Mehmood Tahir , Maqsoom Ahsen , Malik Muhammad Waqas , Suparp Suniti
Published: March 2023

Plastic waste has increased significantly in recent years as a result of fast population growth and urbanization. Studies on the incorporation of plastic aggregates as a substitution for natural aggregates in concrete are needed to successfully reduce both adverse environmental impact and the depletion of natural resources. The objective of this research was to investigate the use of plastic as a partial substitution for natural coarse aggregates in concrete. For this purpose, seven concrete mixes were produced using 0, 10, 15, and 20% plastic coarse aggregates to replace natural aggregates with and without silica fume of similar replacement levels with cement. Fresh density, workability, compressive strength, splitting tensile strength, stress–strain response, and Poisson’s ratio were observed to study the fresh as well as hardened properties of concrete mixtures. Indoor and outdoor thermal performance and thermo-gravimetric analysis were also investigated. The results revealed that the plastic aggregates’ incorporation improved the workability of concrete; however, it negatively influenced the fresh density and mechanical properties of concrete. The compressive and tensile strengths of plastic aggregate concrete without silica fume were reduced by 32 and 33%, respectively. The reduction in strength could be associated with the smooth texture of plastic aggregates. The addition of silica fume with plastic aggregates resulted in denser concrete and improved mechanical properties. In general, the performance of plastic aggregates as a partial replacement for natural aggregates was satisfactory, which suggests their possible use to produce eco-friendlier concrete.
Road Car Accident Prediction Using a Machine-Learning-Enabled Data Analysis
Authors: Pourroostaei Ardakani Saeid , Liang Xiangning , Mengistu Kal Tenna , So Richard Sugianto , Wei Xuhui , He Baojie , Cheshmehzangi Ali
Published: March 2023

Traffic accidents have become severe risks as they are one of the causes of enormous deaths worldwide. Reducing the number of incidents is critical to saving lives and achieving sustainable cities and communities. Machine learning and data analysis techniques interpret the reasons for car accidents and propose solutions to minimize them. However, this needs to take the benefits of big data solutions as the size and velocity of traffic accident data are increasingly large and rapid. This paper explores road car accident data patterns and proposes a predictive model by investigating meaningful data features, such as accident severity, the number of casualties, and the number of vehicles. Therefore, a pre-processing model is designed to convert raw data using missing and meaningless feature removal, data attribute generalization, and outlier removal using interquartile. Four classification methods, including decision trees, random forest, multinomial logistic regression, and naïve Bayes, are used and evaluated to study the performance of road accident prediction. The results address acceptable levels of accuracy for car accident prediction except for naïve Bayes. The findings are discussed through a data-driven approach to understand the factors influencing road car accidents and highlight the key ones to propose accident prevention solutions. Finally, some strategies are provided to achieve healthy and community-friendly cities.
Fatigue Life Evaluation of Orthotropic Steel Deck of Steel Bridges Using Experimental and Numerical Methods
Authors: Zeng Yong , Wang Shenxu , Xue Xiaofang , Tan Hongmei , Zhou Jianting
Published: March 2023

Orthotropic steel deck (OSD) structures are widely used in the bridge deck system of rail transit bridges. Reducing the amplitude of the stress intensity factor is the most effective method to improve the fatigue life of OSD structures. In order to explore the fatigue crack propagation of the OSD structure and the factors affecting the amplitude of the structural stress intensity factor, linear elastic fracture mechanics and Paris’ law is used for theoretical support in this paper. Firstly, a cable-stayed bridge of urban rail transit is taken as the research object, a full-scale segment model of the OSD structure is designed and static and fatigue tests are carried out. Based on the test data, the fatigue life of the structure is simulated and predicted. Finally, ABAQUS and Franc3D are used to analyze the influence of parameters, such as U-rib thickness, roof thickness and diaphragm thickness, of the OSD structure on the amplitude of the stress intensity factor. The test and FEM analysis results show that the thickness of diaphragm and the height of the U-rib have little effect on the fatigue life of the OSD structure, appropriately increasing the thickness of the top plate and U-rib has a positive significance for prolonging the fatigue life of the structure. In addition, it is also of reference value to the application of sustainability and the science of sustainable development.
Effects of Incentives and Penalties on Farmers’ Willingness and Behavior to Separate Domestic Waste-Analysis of Farm Household Heterogeneity Based on Chain Multiple Intermediary Effects
Authors: Chen Shi-Wen , Huang Sen-Wei , Chen Jing , Huang Ke-Yang , He You-Xing
Published: March 2023

It is important to investigate the influence of incentives and penalties on farmers’ willingness and behavior towards domestic waste separation and the mechanism of influence. It is helpful for the government to formulate policies to guide farmers to actively participate in domestic waste separation, solve the problem of rural domestic waste pollution, and improve the effectiveness of rural waste separation management. By using the public data of 2020CLES, we analyzed the influence of incentives and penalties on farmers’ willingness and behavior towards domestic waste separation by using the Probit model, based on the technology acceptance model, using a chain of multiple mediating effects. The results are as follows. Firstly, the net effect of incentives and penalties on farmers’ willingness and behavior to separate household waste was 6.86%, and the net effect of separation behavior was 33.37%. Relatively speaking, the strengthening effect of incentives and penalties on farmers’ domestic waste sorting behavior is stronger than the promotion effect on farmers’ domestic waste sorting intention. Secondly, perceived ease of use and perceived usefulness had significant chain mediating effects, with perceived ease of use having the strongest mediating effect. Thirdly, the incentives and penalties have a stronger effect on promoting the willingness of female farmers, elderly farmers, and farmers with low education to separate domestic waste. Finally, the influence of individual and household characteristics of farmers on their willingness and behavior to separate household waste varies. Accordingly, suggestions for improving the willingness and behavior of farmers to separate domestic waste are proposed in the following aspects: improving the reward and punishment system, making good use of market instruments, and increasing farmers’ awareness level and value recognition of domestic waste separation.
PCB-YOLO: An Improved Detection Algorithm of PCB Surface Defects Based on YOLOv5
Authors: Tang Junlong , Liu Shenbo , Zhao Dongxue , Tang Lijun , Zou Wanghui , Zheng Bin
Published: March 2023

To address the problems of low network accuracy, slow speed, and a large number of model parameters in printed circuit board (PCB) defect detection, an improved detection algorithm of PCB surface defects based on YOLOv5 is proposed, named PCB-YOLO, in this paper. Based on the K-means++ algorithm, more suitable anchors for the dataset are obtained, and a small target detection layer is added to make the PCB-YOLO pay attention to more small target information. Swin transformer is embedded into the backbone network, and a united attention mechanism is constructed to reduce the interference between the background and defects in the image, and the analysis ability of the network is improved. Model volume compression is achieved by introducing depth-wise separable convolution. The EIoU loss function is used to optimize the regression process of the prediction frame and detection frame, which enhances the localization ability of small targets. The experimental results show that PCB-YOLO achieves a satisfactory balance between performance and consumption, reaching 95.97% mAP at 92.5 FPS, which is more accurate and faster than many other algorithms for real-time and high-precision detection of product surface defects.
Bearing Characteristics of Composite Foundation Reinforced by Geosynthetic-Encased Stone Column: Field Tests and Numerical Analyses
Authors: Wang Kaifeng , Liu Mengjie , Cao Jie , Niu Jiayong , Zhuang Yunxia
Published: March 2023

In order to study the bearing characteristic of the geosynthetic-encased stone column (GESC) on the composite foundation, a series of field tests and numerical simulation were carried out on the composite foundations reinforced by the traditional stone column and the GESC. The pile–soil stress ratio, excess pore water pressure and lateral displacement of two kinds of composite foundations were monitored. The effects of geotextile stiffness, geotextile wrapping length and gravel internal friction angle on the composite foundation with the GESC were analyzed by establishing different numerical models. The results show that the GESC can bear larger loading compared with the traditional stone column. The pile–soil stress ratio of the composite foundation with the traditional stone column gradually increases from 1.1 to 1.5 with the increasing of the embankment height. However, the pile–soil stress ratio of the composite foundation with the GESC reaches 1.5 at the initial filling stage and increases to 1.7 with the filling construction. The drainage effect of the GESC is better than that of the traditional stone column, and the GESC can effectively improve the overall stiffness of stone column, so as to reduce the lateral displacement of soil mass. The increases of geotextile stiffness, geotextile wrapping length and gravel internal friction angle can improve the bearing performance of the composite foundation with the GESC. However, after geotextile stiffness and wrapping length reach a certain value, the influence of its lifting amount on the composite foundation will be reduced.
Impact of Digital Economy on the Upgrading of Energy Consumption Structure: Evidence from Mainland China
Authors: Zeng Yating , Xu Xinyue , Zhao Yuyao , Li Bin
Published: March 2023

The digital economy is fundamentally altering human productivity and lifestyles, gradually becoming a new engine that drives energy technology transformation and optimizes the energy consumption structure. This paper examines the impact of the digital economy on upgrading the energy consumption structure using panel data from 30 Chinese provinces from 2013 to 2019. The empirical findings indicate that the digital economy’s development can help to improve energy consumption structure, and this impact can have a threshold effect. Heterogeneity analysis reveals that upgrading the energy consumption structure affected by the digital economy is more significant in lower digital divide regions, the eastern and central regions, and provinces with high economic development levels. Moreover, the findings of a mechanism analysis demonstrate that the digital economy primarily influences green technology innovation, and government environmental regulation affects the major upgrades of the energy consumption structure.
What Drives Industry 4.0 Technologies Adoption? Evidence from a SEM-Neural Network Approach in the Context of Vietnamese Firms
Authors: Le Vu , Nguyen Tien , Pham Khanh
Published: March 2023

The development of the Industrial Revolution 4.0 has far-reaching effects on all aspects of life, the economy, and society, bringing various growth opportunities for businesses. However, businesses are still hesitant to apply these new technologies. On a research sample from a survey of 396 Vietnamese enterprises, the study uses the SEM-neural network method to determine the relationship and importance of five groups of factors affecting the firms’ Industry 4.0 technologies adoption. The results suggest that five groups of factors, including Perceived characteristics, Technological competencies, CEO characteristics, Environmental characteristics, and Subjective Norms, all positively and significantly impact the Industry 4.0 technologies adoption in Vietnam. In particular, Technological competencies are the most influential factors according to the SEM method, while Subjective norms factors have the most decisive impact according to the neural-network method. Moreover, the research also found that adopting Industry 4.0 technologies depends on different company characteristics, such as age, size, status, and industry.
The Need for a Paradigm Shift toward an Occupant-Centered Environmental Control Model
Authors: Wegertseder-Martínez Paulina
Published: March 2023

Office-based environmental control systems are centralized and designed to control entire spaces, ignoring use dynamics and requirements, and despite being regulated by standardized comfort models, they fail to satisfy real occupants, mainly due to their varied individual characteristics. This research is field-based with a quantitative approach and correlational design. Its objective is to empirically demonstrate that open-plan design, where different users share the same space and generalized environmental conditions, lacks a holistic view of IEQ criteria and the integration of other factors that affect health and well-being. Four buildings are chosen in different Chilean cities, measuring temperatures and CO2 levels at different desks, and applying a survey, which was designed as part of the research to analyze the estimation of relationships between variables and to reveal the factors that cause differences among occupants. The results show that people’s satisfaction is multivariable and depends on other factors that positively or negatively stimulate their sensations and perceptions, such as, for example, the option to personally control their environmental conditions. Likewise, it is evident that to achieve comfort, health is being affected while in the building.
Monitoring of Subsurface Emissions and the Influence of Meteorological Factors on Landfill Gas Emissions: A Case Study of a South African Landfill
Authors: Njoku Prince Obinna , Piketh Stuart , Makungo Rachel , Edokpayi Joshua Nosa
Published: March 2023

The government-accredited GA 2000 landfill gas analyzer was used to monitor the landfill gas (methane (CH4) and carbon dioxide (CO2)) generated from the subsurface of a landfill. Eighteen gas sample probes were constructed and placed approximately 100 m apart on the boundaries of the landfill site. The monitoring of the gases was conducted over a period of two years, taking into consideration the different seasons of the year. Results from the study show that as the LFG migrates toward the boundaries of the landfill in the subsurface, higher CO2 levels are recorded when compared to CH4. This could be a result of the oxidation process and some other factors present in the landfill. CH4 emissions ranged from 0.54 to 2.22% v/v in 2020. For the year 2021, the CH4 concentration ranged from 0.24% v/v to 2.33% v/v. In addition, the CO2 concentration for the year 2020 ranged from 4.66 to 6.37% v/v. In the year 2021, the CO2 concentration ranged from 3.5 to 6.56% v/v. Furthermore, higher gaseous concentrations were found in the surrounding active cells, where there is currently deposition of municipal solid waste (MSW). However, the monitoring probes situated in areas far away from the landfill recorded lower gaseous levels. This study recommends that there should be continuous monitoring of the LFG emission from the Thohoyandou landfill due to the different results obtained over the temporal variation. Frequent monitoring will help prevent the potential risk of fire hazards and pollution in the future.
An Introductory Overview of Bessel Polynomials, the Generalized Bessel Polynomials and the q-Bessel Polynomials
Authors: Srivastava Hari Mohan
Published: March 2023

Named essentially after their close relationship with the modified Bessel function Kν(z) of the second kind, which is known also as the Macdonald function (or, with a slightly different definition, the Basset function), the so-called Bessel polynomials yn(x) and the generalized Bessel polynomials yn(x;α,β) stemmed naturally in some systematic investigations of the classical wave equation in spherical polar coordinates. Our main purpose in this invited survey-cum-expository review article is to present an introductory overview of the Bessel polynomials yn(x) and the generalized Bessel polynomials yn(x;α,β) involving the asymmetric parameters α and β. Each of these polynomial systems, as well as their reversed forms θn(x) and θn(x;α,β), has been widely and extensively investigated and applied in the existing literature on the subject. We also briefly consider some recent developments based upon the basic (or quantum or q-) extensions of the Bessel polynomials. Several general families of hypergeometric polynomials, which are actually the truncated or terminating forms of the series representing the generalized hypergeometric function rFs with r symmetric numerator parameters and s symmetric denominator parameters, are also investigated, together with the corresponding basic (or quantum or q-) hypergeometric functions and the basic (or quantum or q-) hypergeometric polynomials associated with rΦs which also involves r symmetric numerator parameters and s symmetric denominator parameters.
A Novel Problem for Solving Permuted Cordial Labeling of Graphs
Authors: ELrokh Ashraf , Al-Shamiri Mohammed M. Ali , Almazah Mohammed M. A. , El-hay Atef Abd
Published: March 2023

In this paper, we used the permutation group together with the concept of cordiality in graph theory to introduce a new method of labeling. This construed permuted cordial labeling can be applied to all paths, cycles, fans and wheel graphs. Moreover, some other properties are investigated and show that the union of any two paths and the union of any two cycles are permuted cordial graphs. In addition, we investigated the permuted cordiality for the union of any path with cycle.
Geometric Aggregation Operators for Solving Multicriteria Group Decision-Making Problems Based on Complex Pythagorean Fuzzy Sets
Authors: Hezam Ibrahim M. , Rahman Khaista , Alshamrani Ahmad , Božanić Darko
Published: March 2023

The Complex Pythagorean fuzzy set (CPyFS) is an efficient tool to handle two-dimensional periodic uncertain information, which has various applications in fuzzy modeling and decision making. It is known that the aggregation operators influence decision-making processes. Algebraic aggregation operators are the important and widely used operators in decision making techniques that deal with uncertain problems. This paper investigates some complex Pythagorean fuzzy geometric aggregation operators, such as complex Pythagorean fuzzy weighted geometric (CPyFWG), complex Pythagorean fuzzy ordered weighted geometric (CPyFOWG), complex Pythagorean fuzzy hybrid geometric (CPyFHG), induced complex Pythagorean fuzzy ordered weighted geometric (I-CPyFOWG), and induced complex Pythagorean fuzzy hybrid geometric (I-CPyFHG), and their structure properties, such as idempotency, boundedness, and monotonicity. In addition, we compare the proposed model with their existing models, such as complex fuzzy set and complex intuitionistic fuzzy set. We analyze an example involving the selection of an acceptable location for hospitals in order to demonstrate the effectiveness, appropriateness, and efficiency of the novel aggregation operators.
A Novel Second-OrderSine-Cost-Function-Derived Kernel Adaptive Algorithm for Non-Linear System Identification
Authors: Sun Liping , Zhou Hongju , Zhou Hongwei
Published: March 2023

A novel kernel recursive second-order sine adaptive (KRSOSA) algorithm was devised for identifying non-linear systems, which was constructed using a symmetry squared sine function to develop a novel kernel loss function and recursive scheme. In the proposed KRSOSA algorithm, the squared sine function provides resistance to impulsive noise due to the sine operation, which was well-derived and investigated in the framework of kernel adaptive filtering (KAF). The behavior of the proposed KRSOSA algorithm was investigated and analyzed using computer simulations, which provided good performance for identifying non-linear systems under impulsive noises.
Polarization of Gravitational Waves in Modified Gravity
Authors: Khlopov Maxim , Chowdhury Sourav Roy
Published: March 2023

An investigation has been carried out on a reconfigured form of the Einstein-Hilbert action, denoted by f(R,Tϕ), where Tϕ represents the energy-momentum tensor trace of the scalar field under consideration. The study has focused on how the structural behavior of the scalar field changes based on the potential’s shape, which has led to the development of a new set of Friedmann equations. In the context of modified theories, researchers have extensively explored the range of gravitational wave polarization modes associated with relevant fields. In addition to the two transverse-traceless tensor modes that are typically observed in general relativity, two additional scalar modes have been identified: a massive longitudinal mode and a massless transverse mode, also known as the breathing mode.
Joint Optimization of Order Allocation and Rack Selection in the “Parts-to-Picker” Picking System Considering Multiple Stations Workload Balance
Authors: Wang Fang , Wang Yu , Chang Daofang
Published: March 2023

E-commerce companies generate massive orders daily, and efficiently fulfilling them is a critical challenge. In the “parts-to-picker” order fulfillment system, the joint optimization of order allocation and rack selection is a crucial problem. Previous research has primarily focused on these two aspects separately and has yet to consider the issue of workload balancing across multiple picking stations, which can significantly impact picking efficiency. Therefore, this paper studies a joint optimization problem of order allocation and rack selection for a “parts-to-picker” order picking system with multiple picking stations to improve order picking efficiency and avoid uneven workload distribution. An integer programming model of order allocation and rack selection joint optimization is formulated to minimize the racks’ total moving distance and to balance the orders allocated to each picking station. The problem is decomposed into three sub-problems: order batching, batch allocation, and rack selection, and an improved simulated annealing (SA) algorithm is designed to solve the problem. Two workload comparing operators and two random operators are developed and introduced to the SA iterations. Random instances of different scales are generated for experiments. The algorithm solutions are compared with those generated by solving the IP model directly in a commercial solver, CPLEX, and applying the first-come-first-serve strategy (FCFS), respectively. The numerical results show that the proposed algorithm can generate order allocation and rack selection solutions much more efficiently, where the moving distances of the racks are effectively reduced and the workloads are balanced among the picking stations simultaneously. The model and algorithm proposed in this paper can provide a scientific decision-making basis for e-commerce companies to improve their picking efficiency.
Image-Based Quantification of Color and Its Machine Vision and Offline Applications
Authors: Yoo Woo Sik , Kang Kitaek , Kim Jung Gon , Yoo Yeongsik
Published: March 2023

Image-based colorimetry has been gaining relevance due to the wide availability of smart phones with image sensors and increasing computational power. The low cost and portable designs with user-friendly interfaces, and their compatibility with data acquisition and processing, are very attractive for interdisciplinary applications from art, the fashion industry, food science, medical science, oriental medicine, agriculture, geology, chemistry, biology, material science, environmental engineering, and many other applications. This work describes the image-based quantification of color and its machine vision and offline applications in interdisciplinary fields using specifically developed image analysis software. Examples of color information extraction from a single pixel to predetermined sizes/shapes of areas, including customized regions of interest (ROIs) from various digital images of dyed T-shirts, tongues, and assays, are demonstrated. Corresponding RGB, HSV, CIELAB, Munsell color, and hexadecimal color codes, from a single pixel to ROIs, are extracted for machine vision and offline applications in various fields. Histograms and statistical analyses of colors from a single pixel to ROIs are successfully demonstrated. Reliable image-based quantification of color, in a wide range of potential applications, is proposed and the validity is verified using color quantification examples in various fields of applications. The objectivity of color-based diagnosis, judgment and control can be significantly improved by the image-based quantification of color proposed in this study.
Decoupled Anisotropic Solutions Using Karmarkar Condition in f(G, T) Gravity
Authors: Hassan Komal , Sharif Muhammad
Published: March 2023

In this paper, we compute two anisotropic static spherical solutions for two compact stellar candidates in the background of f(G,T) gravity using the minimal geometric decoupling technique. The internal structure becomes anisotropic when an additional sector is added to the isotropic system. With this method, the radial component is distorted to establish two sets of the field equations that represent perfect and anisotropic sources. We use the Karmarkar condition to formulate the metric potentials that help to find the solution of the first set. For the second set, two extra constraints are applied on theanisotropic sector to find its solution. Both of the solutions are then combined to yield the ultimate anisotropic solution. We then examine the physical feasibility and stability of the resulting anisotropic solutions through energy conditions and stability criteria, respectively. It is found that the compact star Her X-1 is viable but not stable corresponding to the first solution while satisfying all the physical acceptability conditions for the second solution. On the other hand, the star 4U 1820-30 indicates viable and stable behavior for both anisotropic solutions.
Discovery of Potential Inhibitors of SARS-CoV-2 Main Protease by a Transfer Learning Method
Authors: Zhang Huijun , Liang Boqiang , Sang Xiaohong , An Jing , Huang Ziwei
Published: March 2023

The COVID-19 pandemic caused by SARS-CoV-2 remains a global public health threat and has prompted the development of antiviral therapies. Artificial intelligence may be one of the strategies to facilitate drug development for emerging and re-emerging diseases. The main protease (Mpro) of SARS-CoV-2 is an attractive drug target due to its essential role in the virus life cycle and high conservation among SARS-CoVs. In this study, we used a data augmentation method to boost transfer learning model performance in screening for potential inhibitors of SARS-CoV-2 Mpro. This method appeared to outperform graph convolution neural network, random forest and Chemprop on an external test set. The fine-tuned model was used to screen for a natural compound library and a de novo generated compound library. By combination with other in silico analysis methods, a total of 27 compounds were selected for experimental validation of anti-Mpro activities. Among all the selected hits, two compounds (gyssypol acetic acid and hyperoside) displayed inhibitory effects against Mpro with IC50 values of 67.6 μM and 235.8 μM, respectively. The results obtained in this study may suggest an effective strategy of discovering potential therapeutic leads for SARS-CoV-2 and other coronaviruses.
Cross-Protection of an Inactivated and a Live-Attenuated Lumpy Skin Disease Virus Vaccine against Sheeppox Virus Infections in Sheep
Authors: Wolff Janika , Beer Martin , Hoffmann Bernd
Published: March 2023

Sheeppox virus (SPPV) (genus Capripoxvirus, family Poxviridae) infections are a highly virulent and contagious disease of sheep with a high morbidity and mortality, especially in naïve populations and young animals. For the control of SPPV, homologous and heterologous live-attenuated vaccines are commercially available. In our study, we compared a commercially available live-attenuated lumpy skin disease virus (LSDV) vaccine strain (Lumpyvax) with our recently developed inactivated LSDV vaccine candidate regarding their protective efficacy against SPPV in sheep. Both vaccines were proven to be safe in sheep, and neither clinical signs nor viremia could be detected after vaccination and challenge infection. However, the local replication of the challenge virus in the nasal mucosa of previously vaccinated animals was observed. Because of the advantages of an inactivated vaccine and its heterologous protection efficacy against SPPV in sheep, our inactivated LSDV vaccine candidate is a promising additional tool for the prevention and control of SPPV outbreaks in the future.
Evaluation of Corpus Luteum and Plasma Progesterone the Day before Embryo Transfer as an Index for Recipient Selection in Dairy Cows
Authors: Choi Woojae , Ro Younghye , Choe Eunhui , Hong Leegon , Lee Wonyou , Kim Danil
Published: March 2023

The aim of the present study was to evaluate the effects of synchronization method, season, parity, corpus luteum (CL) size, and progesterone (P4) levels on the pregnancy rate after bovine embryo transfer (ET). Among 165 recipient candidates who received 1 of 2s estrus synchronization treatments, 96 heifers and 43 cows were selected through rectal examination and used as recipients. The day before ET, the CL size and plasma P4 concentration were evaluated. The CL sizes and plasma P4 levels were not different between the selected and unselected candidates, and the pregnancy rates with the two synchronization methods were not different. However, the pregnancy rates were higher in heifers than in lactating cows, and also higher after ET performed from September to February than from March to August (p < 0.05). The recipients with a CL larger than 1.5 cm showed statistically higher pregnancy rates, and although there was no statistical significance, the pregnancy rate was higher when the plasma P4 levels were between 2.0 and 4.0 ng/mL. Exposure to a stressful environment and repeated manipulations can reduce the success rate of ET, and recipient selection with an optimal CL size and P4 level can increase the success rate of ET.
Development of a Nomogram to Predict the Outcome for Patients with Soft Tissue Sarcoma
Authors: Bray Jonathan P. , Munday John S.
Published: March 2023

Soft tissue sarcomas (STSs) are common cutaneous or subcutaneous neoplasms in dogs. Most STSs are initially treated by surgical excision, and local recurrence may develop in almost 20% of patients. Currently, it is difficult to predict which STS will recur after excision, but this ability would greatly assist patient management. In recent years, the nomogram has emerged as a tool to allow oncologists to predict an outcome from a combination of risk factors. The aim of this study was to develop a nomogram for canine STSs and determine if the nomogram could predict patient outcomes better than individual tumour characteristics. The current study provides the first evidence in veterinary oncology to support a role for the nomogram to assist with predicting the outcome for patients after surgery for STSs. The nomogram developed in this study accurately predicted tumour-free survival in 25 patients but failed to predict recurrence in 1 patient. Overall, the sensitivity, specificity, positive predictive, and negative predictive values for the nomogram were 96%, 45%, 45%, and 96%, respectively (area under the curve: AUC = 0.84). This study suggests a nomogram could play an important role in helping to identify patients who could benefit from revision surgery or adjuvant therapy for an STS.
Integrating Remote Sensing, Proximal Sensing, and Probabilistic Modeling to Support Agricultural Project Planning and Decision-Making for Waterlogged Fields
Authors: Bukombe Benjamin , Csenki Sándor , Szlatenyi Dora , Czako Ivan , Láng Vince
Published: March 2023

Waterlogging in agriculture poses severe threats to soil properties, crop yields, and farm profitability. Remote sensing data coupled with drainage systems offer solutions to monitor and manage waterlogging in agricultural systems. However, implementing agricultural projects such as drainage is associated with high uncertainty and risk, with substantial negative impacts on farm profitability if not well planned. Cost–benefit analyses can help allocate resources more effectively; however, data scarcity, high uncertainty, and risks in the agricultural sector make it difficult to use traditional approaches. Here, we combined a wide range of field and remote sensing data, unsupervised machine learning, and Bayesian probabilistic models to: (1) identify potential sites susceptible to waterlogging at the farm scale, and (2) test whether the installation of drainage systems would yield a positive benefit for the farmer. Using the K-means clustering algorithm on water and vegetation indices derived from Sentinel-2 multispectral imagery, we were able to detect potential waterlogging sites in the investigated field (elbow point = 2, silhouette coefficient = 0.46). Using a combination of the Bayesian statistical model and the A/B test, we show that the installation of a drainage system can increase farm profitability by 1.7 times per year compared to the existing farm management. The posterior effect size associated with yield, cropping area, and time (year) was 0.5, 1.5, and 1.9, respectively. Altogether, our results emphasize the importance of data-driven decision-making for agriculture project planning and resource management in the wake of smart agriculture for food security and adaptation to climate change.
Un poème passé inaperçu : contribution au dossier hagiographique de saint Maieul, quatrième abbé de Cluny
Authors: Dolveck Franz
Published: March 2023

Catherine Magne a découvert en 1994 un poème rythmique sur la mort de Maieul de Cluny jusqu’alors inconnu ; malheureusement, un défaut d’édition l’avait fait passer inaperçu. Il est ici réédité d’après l’unique témoin conservé (Paris, BnF, lat. 5611). Tout porte à croire qu’il faut l’attribuer à Odilon de Cluny, mais il n’est pas impossible que l’auteur soit Jotsald de Saint-Claude.
La entrada Dentium proprietates et infirmitates del Armarium scripturarum de Juan Gil de Zamora (OFM) († ca. 1318) : editio princeps acompañada de un comentario gramatical
Authors: Martín Iglesias José Carlos
Published: March 2023

Cet article offre l’editio princeps du petit traité sur les dents et leurs maladies issu de l’encyclopédie Armarium scripturarum de Juan Gil (OFM) de Zamora († ca. 1318). Le seul manuscrit connu est Salamanca, Biblioteca General Histórica de la Universidad, 2691, fol. 109r-115v. Les sources utilisées sont le De proprietatibus rerum de Barthélemy l’Anglais et le Viaticum de Constantin l’Africain. Mots-clés : Franciscains, encyclopédisme, Moyen Âge, Espagne.
Vocabulario técnico del agua en el Glossarium Mediae Latinitatis Cataloniae
Authors: Gómez Rabal Ana , Segarrés Gisbert Marta
Published: March 2023

La documentation du Glossarium Mediae Latinitatis Cataloniae, composée de textes écrits entre le IXe et le XIIe siècle, nous donne l’occasion de concevoir et recréer l’aménagement du territoire rural et urbain. L’étude de ces textes nous permet d’affirmer que l’un des facteurs qui déterminent cette organisation est justement l’eau et, en particulier, l’usage des sources et des artères fluviales naturelles, le détournement
Gutta als Krankheitsbezeichnung
Authors: Mandrin Isabelle
Published: March 2023

Ein «Tropfen» (gutta) kann unterschiedliche Krankheiten bezeichnen, entweder für sich allein stehend oder mit einem Attribut versehen, wie zum Beispiel in gutta cadiva, gutta serena, gutta coralis und gutta rosacea. Wörtlich übersetzt wären das die «fallende Tropfkrankheit» , die «klare Tropfkrankheit» , die «Herz-Tropfkrankheit» und die «rosige Tropfkrankheit» . Welche Krankheitsbilder stecken hinter diesen Bezeichnungen ? Auf welche Ursachen werden sie nach mittelalterlichen Vorstellungen zurückgeführt ? Diesen Fragen wird im vorliegenden Beitrag an Hand von Parallelbelegen, insbesondere aus dem Zettelmaterial des Mittellateinischen Wörterbuchs, nachgegangen.
Technical Vocabulary and its Identification in Medieval Celtic Latinity
Authors: Harvey Anthony
Published: March 2023

Originating as it did in the context of a conference of dictionarymakers, this paper surveys some problems that arise in the attempt to identify a subcorpus of vocabulary as technical, before going on to discuss specific items of the subcorpus so identified within the medieval Latin writings of the Celts.
Language Change in the Dictionary of Polish Medieval Latin
Authors: Nowak Andrzej Krzysztof
Published: March 2023

The paper presents an analysis of lexicographic features which have been employed in the Lexicon Mediae et Infimae Latinitatis Polonorum (Dictionary of Polish Medieval latin) to account for linguistic change. It starts with an outline of the history of Medieval Latin in Poland. Nest, the author focuses on word formation and semantic change as reflected in the dictionary''s macro-and microstructure. Finally, some possible improvements in diachronic data presentation are suggested.
Un neologismo in Rodolfo Tortario ?
Authors: Sivo Francesca
Published: March 2023

À deux endroits de ses oeuvres en vers (De memorabilibus VII, 3, 94 e epist. V, 73), Raoul Tortaire emploie le mot vafria, qui n’est attesté dans aucune autre oeuvre latine. Ce n’est cependant pas un néologisme créé par le poète, mais un mot corrompu présent dans la tradition manuscrite des Facta et dicta memorabilia de Valère Maxime (VII, 3, ext. 2) au lieu du mot correct vafritia et considéré par Raoul comme un mot latin authentique. L’article a aussi pour objet de traiter des relations intertextuelles qui émergent de l’analyse des textes examinés.