bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence and Distribution of Dental Anomalies among Arab Orthodontic Patients in Israel: Is There a Correlation to Consanguinity Marriage?
Authors: Kadry Rana , Atalla Rojee , Sella Tunis Tatiana , Finkelstein Tamar , Schonberger Shirley , Kharouba Johnny , Shapira Yehoshua
Published: December 2022

The aim of this study was to determine the prevalence of dental anomalies and whethera significant association exists between dental anomalies and consanguinity marriage among Arabic orthodontic patients in Israel. Pretreatment panoramic radiographs of 513 patients (38% males and 62% females) were examined to detect dental anomalies related to number, size, shape, and eruption. A chi-square test was carried out to determine the associations between dental anomalies, gender, and consanguinity marriage. The results indicated that 29% of the subjects manifested at least one dental anomaly. Impacted tooth was found to be the most frequent dental anomaly, with a prevalence of 13.5%, whereas fusion and transmigration were found to be the least common, with a prevalence of 0.2% each. The prevalence of dental anomalies was significantly greater in males (p < 0.001) than in females. In our sample a significant association was found between dental anomalies and consanguinity marriage, and it was found to be greater in subjects with a family history of consanguinity marriage. This association can be attributed to the negative effects of consanguinity marriage, which was also reported in many studies in other fields. This study suggests that consanguinity marriage can be one of the factors involved in the development of dental anomalies in certain at-risk populations.
Color Structured Light Stripe Edge Detection Method Based on Generative Adversarial Networks
Authors: Pham Dieuthuy , Ha Minhtuan , Xiao Changyan
Published: December 2022

The one-shot structured light method using a color stripe pattern can provide a dense point cloud in a short time. However, the influence of noise and the complex characteristics of scenes still make the task of detecting the color stripe edges in deformed pattern images difficult. To overcome these challenges, a color structured light stripe edge detection method based on generative adversarial networks, which is named horizontal elastomeric attention residual Unet-based GAN (HEAR-GAN), is proposed in this paper. Additionally, a De Bruijn sequence-based color stripe pattern and a multi-slit binary pattern are designed. In our dataset, selecting the multi-slit pattern images as ground-truth images not only reduces the labor of manual annotation but also enhances the quality of the training set. With the proposed network, our method converts the task of detecting edges in color stripe pattern images into detecting centerlines in curved line images. The experimental results show that the proposed method can overcome the above challenges, and thus, most of the edges in the color stripe pattern images are detected. In addition, the comparison results demonstrate that our method can achieve a higher performance of color stripe segmentation with higher pixel location accuracy than other edge detection methods.
Multi-Band Polarization Imaging in a Harsh Sea Fog Environment
Authors: Fu Qiang , Liu Nan , Guo Hongrui , Liu Xuanwei , Yan Yujiaqi , Geng Dong , Zhang Su , Zhan Juntong , Duan Jin
Published: December 2022

Researchers in many nations are focusing more on the growth and usage of the marine field, and it is apparent that study on the marine field will be the future development trend. The present study adopts the idea of polarization imaging based on liquid crystal phase retarder as a solution to the drawbacks of conventional industrial camera imaging clarity. Various optical thicknesses are employed to characterize the sea fog concentration; an outside optical imaging equipment is constructed for sea fog imaging research; and pictures comprising polarization characteristics may be determined through image processing. Using multi-band as factors, the benefit of polarization imaging in a sea fog environment is assessed objectively using contrast, information entropy, degree of polarization, and other evaluation indices. The results demonstrate that the quality of the polarization image is superior to that of the intensity image and that the outline of the target is more pronounced in the polarization image. Additionally, the polarization imaging effect is better in the 670 nm band, and the polarization contrast is increased by 1.9%. The contrast trend of the polarization picture is impacted by the time period, but it is roughly equivalent to that of the intensity image. This gives a solid platform for target surveys and civic operations under conditions of dense marine fog.
Stabilization Time of Running Equivalent Level LAeq for Urban Road Traffic Noise
Authors: Brambilla Giovanni , Benocci Roberto , Potenza Andrea , Zambon Giovanni
Published: December 2022

In urban areas, noise levels can largely vary in space and time due to the great complexity of these environments. The time required for the fluctuations of the running equivalent level LAeq to be limited within a preset variability range is a key issue for determining a statistically representative sample of the urban acoustic environment. The goal of the present study is to evaluate the potential of the stabilization time, defined as the minimum time ST after which the difference between the corresponding continuous equivalent sound pressure level LAeq,ST and the continuous equivalent sound pressure level LAeq,T referred a longer time T, including ST, is never greater than a preset uncertainty interval ε. For this purpose, a dataset of road traffic noise continuously monitored in 97 sites in the city of Milan, Italy, is considered, providing 268 time series of 1 s short LAeq,1s, each lasting 24 h. The stabilization time ST referred the hourly LAeq,1h was determined for three preset uncertainty intervals ε, namely ±0.5, ±1.0 and ±1.5 dB(A). The results are promising and provide useful hints to obtain short-time noise monitoring as a statistically representative sample of the urban acoustic environment and, therefore, can be a tool to increase the low spatial resolution usually achievable by unattended permanent monitoring units.
Analytically Regularized Evaluation of the Coupling of Planar Concentric Conducting Rings
Authors: Schettino Fulvio
Published: December 2022

In this paper, an accurate and efficient method for the analysis of coupled perfectly conducting annular rings is presented. The problem is first formulated as a couple of Integral Equation (IEs) in the Vector Hankel Transform (VHT) domain, considered as unknowns in the cylindrical harmonics of the unknown surface current density. As a second step, Galerkin’s method is applied with suitable expansion functions. The selected functions have two main properties: they reconstruct the expected physical behavior of the nth cylindrical harmonic at the edges of the annular rings, and their VHT transform is analytical and can be expressed in closed-form. Consequently, the method is effective and the problem is regularized, as testified by the truncation error. Comparisons with the commercial software CST Microwave Studio have been carried out and are presented to validate the method.
Supply Sequence Modelling Using Hidden Markov Models
Authors: Borucka Anna , Kozłowski Edward , Parczewski Rafał , Antosz Katarzyna , Gil Leszek , Pieniak Daniel
Published: December 2022

Logistics processes, their effective planning as well as proper management and effective implementation are of key importance in an enterprise. This article analyzes the process of supplying raw materials necessary for the implementation of production tasks. The specificity of the examined waste processing company requires the knowledge about the size of potential deliveries because the delivered waste must be properly managed and stored due to its toxicity to the natural environment. In the article, hidden Markov models were used to assess the level of supply. They are a statistical modeling tool used to analyze and predict the phenomena of a sequence of events. It is not always possible to provide sufficiently reliable information with the existing classical methods in this regard. Therefore, the article proposes modeling techniques with the help of stochastic processes. In hidden Markov models, the system is represented as a Markov process with states that are invisible to the observer but with a visible output (observation) that is a random state function. In the article, the distribution of outputs from the hidden states is defined by a polynomial distribution.
Study on the Seismic Effect of the Pebble Soil Site in the Zhongwei Basin
Authors: Yang Shun , Han Xin , Lei Qiyun , Du Peng , Liu Chao , Li Zeshan
Published: December 2022

Based on a large amount of drilling and geophysical exploration work in the Zhongwei Basin, and combined with the collected borehole data of a seismic safety assessment, this paper summarizes and builds 16 typical pebble soil layer calculation models. The effects of the thickness of the pebble layer, the thickness of the overlying silty clay, the top interface of the pebble layer on the peak acceleration and the response spectrum of the site seismic response were analyzed using the equivalent linearization method of the one-dimensional soil layer seismic response. The analysis results showed that the variation in pebble layer thickness had no obvious effect on the peak acceleration of the ground surface under different inputs; the influence of the pebble layer thickness on the ground acceleration response spectrum was primarily concentrated in the middle/high-frequency band of 0.2–0.6 s. Within this range, the acceleration response spectrum of the site with a 30 m pebble layer thickness was small, and the response spectrum curve showed a “trough” shape with a certain “weak isolation” effect. Under the same pebble layer thickness, the upper ground surface peak acceleration with a silty clay layer thickness increased with the increase in the central basin pebble soil field, where a short cycle of the seismic wave amplification effect was more obvious. The response spectrum peak period points were within 0.1–0.2 s and were influenced by the action of rare earthquakes. Moreover, the response spectrum curve showed a more obvious phenomenon of “twin peaks”, and the second peak point appeared in the period of 0.5–0.7 s. With the increase in the input intensity, the PGA amplification ratio of the pebble-top interface was significantly smaller than that of the site surface; under different intensities of input, the acceleration response spectrum of the pebble-top interface showed a “trough” phenomenon that was lower than the bedrock input at approximately 0.1 s. Under the action of rare ground motion, the acceleration response spectrum curve of the pebble-top interface showed a “double peak” phenomenon, and within 0.24–0.4 s, the spectrum value was lower than the bedrock input, showing an obvious shock absorption and isolation effect. Under the action of an earthquake, the energy of the pebble-top interface was concentrated in the low-frequency range of 1.1–2.2 Hz, and the amplification effect was obvious. In the range of 8–10 Hz, the amplitude was lower than the bedrock input, and the seismic isolation effect was obvious.
In-Structure Response Spectra of an Auxiliary Building in a Nuclear Power Plant Considering Equipment–Structure Interaction
Authors: Ahn Sook-Jin , Park Ji-Hun
Published: December 2022

A two-degree-of-freedom (two-DOF) equation of motion was derived in the frequency domain using a substructuring technique for efficiently calculating the in-structure response spectrum (ISRS) considering equipment–structure interaction. The model of the primary structure was condensed into a mechanical impedance function and combined with the equipment represented by a single-degree-of-freedom oscillator in the frequency domain. This condensed two-DOF system is applied to the efficient calculation of the ISRS considering the equipment–structure interaction without repeated analysis of the coupled model with full DOFs. This coupled analysis procedure was applied to a finite element model of an auxiliary building in a nuclear power plant to validate both the accuracy and impact on the equipment response. Finally, the adequacy of three representative decoupling criteria on the necessity of coupled analysis was investigated by applying those criteria to the auxiliary building example.
Knowledge Graph Completion Based on Entity Descriptions in Hyperbolic Space
Authors: Zhang Xiaoming , Tian Dongjie , Wang Huiyong
Published: December 2022

Hyperbolic space has received extensive attention because it can accurately and concisely represent hierarchical data. Currently, for knowledge graph completion tasks, the introduction of exogenous information of entities can enrich the knowledge representation of entities, but there is a problem that entities have different levels under different relations, and the embeddings of different entities in Euclidean space often requires high dimensional space to distinguish. Therefore, in order to solve the above problem, we propose a method that use entity descriptions to complete the knowledge graph in the Poincaré ball model of hyperbolic space. In this method, the text representation of entity descriptions is in Euclidean space and mapped to hyperbolic space through exponential map. Next, the triple embeddings are initialized in hyperbolic space, and the structured representation of the triple is trained by the hyperbolic model. Finally, the text representation and the structured representation of the entity are cross-fused in hyperbolic space, and then the balance factors are used to adjust the unbalanced energy function. Experimental results show that, compared with baseline models, the proposed method can improve the performance of knowledge graphs completion.
Mechanical Behavior and Excavation Optimization of a Small Clear-Distance Tunnel in an Urban Super Large and Complex Underground Interchange Hub
Authors: Wang Jianxiu , Cao Ansheng , Li Zonghai , Wu Zhao , Lin Lihua , Liu Xiaotian , Li Huboqiang , Sun Yuanwei
Published: December 2022

Close excavation section spacing, the mutual influence and interpenetration of various processes, and the multiple disturbances of the middle rock pillar in a small clear-distance tunnel pose great difficulty to construction. This study adopted the small clear-distance tunnel of Xiamen Haicang Evacuate Channel as the research object. The tunnel belonged to a small clear-distance tunnel in an urban super large and complex underground interchange hub where complex adjacent small clear-distance tunnels were adopted. ABAQUS was used to analyze the influence of different excavation schemes, lithological grades, and footage lengths for tunnel stability. The deformation and stress characteristics of the tunnel’s surrounding rock and lining structure in different excavation schemes (full section method, bench method, center diaphragm (CD) method, and double wall heading method), lithological grades (III, IV and V), and footage lengths (3 m, 4 m and 5 m) were introduced. The results showed that the double wall heading method could effectively control the horizontal displacement of the hance, and the overall stress state of the lining in the CD and double wall heading methods were reasonable. The vertical displacement of the surface and vault was positively correlated with the elastic modulus of the rock mass. When no temporary support was present in the grade V rock mass, the area from the hance to the arch foot was prone to large deformation. Reducing the footage was beneficial to controlling the deformation of the vault and hance. This study can provide a reference for the on-site construction of small clear-distance tunnels.
Microscopic Pair Potentials and the Physical Properties of the Condensed Phases of Parahydrogen
Authors: Hu Jieru , Boninsegni Massimo
Published: December 2022

Equilibrium physical properties of the solid and liquid phases of parahydrogen, computed by first principle computer simulations, are compared for different choices of pair-wise, spherically symmetric intermolecular potentials. The most recent ab initio potential [Patkowski et al., J. Chem. Phys., 2008, 129, 094304], which has a stiffer repulsive core than the commonly used Silvera-Goldman, yields results for structural quantities in better agreement with the most recent experimental measurements, while possibly overestimating the kinetic energy per molecule by as much as 10%. Altogether, the comparison between theory and the available experimental evidence suggests that the potential of Patkowski et al. may be a better choice for simulations of condensed phases of parahydrogen at moderate pressure.
Performance Analysis of a Repairable Production Line Using a Hybrid Dependability Queueing Model Based on Monte Carlo Simulation
Authors: Chiacchio Ferdinando , Oliveri Ludovica , Khodayee Soheyl Moheb , D’Urso Diego
Published: December 2022

Due to the augmented complexity of the factory on the one hand and the increased availability of information on the other hand, nowadays it is possible to design models of production lines able to consider the state of the health of the production system. Such models must combine both the deterministic and the stochastic behaviours of a system, with the former accounting for the mechanics and physics of the industrial process and the latter for randomness, including reliability of the production systems and the unpredictability of the maintenance and of the manufacturing lines. This study proposes the application of a Hybrid Dependability Modelling based on Monte Carlo simulation to estimate the performances of a repairable production line modelled with a queueing G/G/1 system. The model proposed is characterized by random interarrival and service times and by the wearing and dynamic aging phenomena of the machine tools that depend on the working and operating conditions.
Hierarchical Fine Extraction Method of Street Tree Information from Mobile LiDAR Point Cloud Data
Authors: Wang Yanjun , Lin Yunhao , Cai Hengfan , Li Shaochun
Published: December 2022

The classification and extraction of street tree geometry information in road scenes is crucial in urban forest biomass statistics and road safety. To address the problem of 3D fine extraction of street trees in complex road scenes, this paper designs and investigates a method for extracting street tree geometry and forest parameters from vehicle-mounted LiDAR point clouds in road scenes based on a Gaussian distributed regional growth algorithm and Voronoi range constraints. Firstly, a large number of non-tree and other noise points, such as ground points, buildings, shrubs and vehicle points, are filtered by applying multi-geometric features; then, the main trunk of the street tree is extracted based on the vertical linear features of the tree and the region growth algorithm based on Gaussian distribution; secondly, a Voronoi polygon constraint is established to segment the single tree canopy region with the main trunk center of mass; finally, based on the extracted locations of the street trees and their 3D points, the tree growth parameters of individual trees are obtained for informative management and biomass estimation by combining geometric statistical methods. In this paper, the experimental data from vehicle-borne LiDAR point clouds of different typical areas were selected to verify that the proposed Gaussian-distributed regional growth algorithm can achieve fine classification and extraction of tree growth parameters for different types of roadside trees, with accuracy, recall and F1 values reaching 96.34%, 97.22% and 96.45%, respectively. This research method can be used for the extraction of 3D fine classification of street trees in complex road environments, which in turn can provide support for the safety management of traffic facilities and forest biomass estimation in urban environments.
Training Autoencoders Using Relative Entropy Constraints
Authors: Li Yanjun , Yan Yongquan
Published: December 2022

Autoencoders are widely used for dimensionality reduction and feature extraction. The backpropagation algorithm for training the parameters of the autoencoder model suffers from problems such as slow convergence. Therefore, researchers propose forward propagation algorithms. However, the existing forward propagation algorithms do not consider the characteristics of the data itself. This paper proposes an autoencoder forward training algorithm based on relative entropy constraints, called relative entropy autoencoder (REAE). When solving the feature map parameters, REAE imposes different constraints on the average activation value of the hidden layer outputs obtained by the feature map for different data sets. In the experimental section, different forward propagation algorithms are compared by applying the features extracted from the autoencoder to an image classification task. The experimental results on three image classification datasets show that the classification performance of the classification model constructed by REAE is better than that of the classification model constructed by other forward propagation algorithms.
Modeling Locations with Enhanced Earth’s Crust Deformation during Earthquake Preparation near the Kamchatka Peninsula
Authors: Gapeev Maksim , Marapulets Yuri
Published: December 2022

In seismically active regions of the Earth, to which the Kamchatka peninsula refers, pre-seismic anomalies are recorded in different geophysical fields. One of such fields is the acoustic emission of rocks, the anomalies of which are recorded 1–3 days before earthquakes at the distance of the first hundreds of kilometers from their epicenters. Results of joint acoustic-deformation measurements showed that growth of geoacoustic radiation intensity occurs during the increase in the level of deformations in rock masses by more than one order compared to the background values. Simulation studies of the areas with increased deformation are realized to understand the causes of anomalous acoustic-deformation disturbance occurrences before strong earthquakes. The model is based on the assumption that the Earth’s crust in the first approximation can be considered as a homogeneous isotropic elastic half-space, and an earthquake source can be considered as a displacements along a rectangular fault plane. Based on these assumptions, deformation regions of Earth’s crust were modeled during the preparations of two earthquakes with local magnitudes ML≈5 occurred on the Kamchatka Peninsula in 2007 and 2009. The simulation results were compared for the first time with the data of a laser strainmeter-interferometer installed at the Karymshina observation site (52.83∘ N, 158.13∘ E). It was shown that, during the preparation of the both earthquakes, the Karymshina observation site was within the region of shear deformations ≈10−7, which exceeded the tidal ones by an order. On the whole, simulation results corresponded to the results of the natural observations. Construction of an adequate model for the generation of acoustic-deformation disturbances before strong earthquakes is topical for the development of an early notification system on the threat of catastrophic natural events.
Classification of Tree Composition in the Forest Using Images from SENTINEL-2: A Case Study of Geomunoreum Forests Using NDVI Images
Authors: Chung Yong Suk , Yoon Seong Uk , Heo Seong , Kim Yoon Seok , Kim Yoon-Ha , Han Gyung Deok , Ahn Jinhyun
Published: December 2022

Climate change may alter tree species’ distribution, which could impact on forest biodiversity. However, frequent and continuous surveys of forests need intense labor and are time-consuming. The current study utilized SENTINEL-2 images of Geomunoreum to solve this problem as a case study. Acquired images were converted into various indices, such as the normalized difference vegetation index (NDVI), which could be an efficient method to examine the diversity in forests over time. In the current study, the images were obtained in March and April from 2017 to 2021. As a result of analysis using NDVI images of the study area taken from the satellite, vegetation groups were classified into evergreen trees and deciduous trees. This implies that NDVI using extracted data from SENTINEL-2 images could be used for surveying large-scale examinations for tree classification in order to observe variations caused by climate change in an efficient and cost-effective manner.
Understanding the Tolerance of Different Strains of Human Pathogenic Bacteria to Acidic Environments
Authors: Porto-Figueira Priscilla , Câmara José S. , Vigário Ana M. , Pereira Jorge A. M.
Published: December 2022

It is known that many bacteria are susceptible to low pH, but it is less clear how the acid nature influences this susceptibility. The objective of this work was to evaluate the susceptibility of selected bacteria to different low pH conditions and to understand if their tolerance is affected by the type of acid (organic vs inorganic) in the media acidification. Strains of different species of human pathogenic bacteria were cultivated at different acidic conditions, using organic or inorganic acids. Overall, we verified that tolerance to acidic conditions is dependent on the type of acid used to acidify the growing medium, organic or inorganic. The strains analysed, although having different tolerance to low pH, were shown to be more susceptible to organic than inorganic acids. This result shows that beyond the pH of the media, the nature of the acid affects bacterial growth. Such a result has consequences in the evaluation of the efficiency of an antibacterial extract, which should take into consideration the differential susceptibility of bacteria to low pHs obtained using organic or inorganic acids.
The Use of Artificial Intelligence for Assessing the Pro-Environmental Practices of Companies
Authors: Dostatni Ewa , Mikołajewski Dariusz , Rojek Izabela
Published: December 2022

In the present study, the authors analyze, supported by the use of artificial intelligence, the environmental solutions implemented in selected manufacturing companies using the example of the Great Poland Voivodship. The companies analyzed were selected from different industry sectors and were of different sizes, divided into two groups: small- and medium-sized enterprises (SMEs) and large enterprises (LEs). The authors observed the environmental activities of these two groups of companies, paying particular attention to the differences that were evident. The study is based on a questionnaire survey. All survey questions referred to the life cycle of a product, ranging from design, production, and use to recycling processes. We discuss the environmental solutions proposed by enterprises of different sizes and at different stages of the product’s life cycle. The goal of this study is three-fold: (1) To investigate the differences in the introduction of environmental issues in SMEs and LEs in the Greater Poland Voivodship, Poland; (2) to examine whether companies in this Voivodship are equally aware of the impact of their business activities and their products on the environment; and (3) to discover novel, more rapid, and simpler methods to analyze the environmental sustainability of companies, including efficient models based on artificial intelligence. An analysis based on ANNs (artificial neural networks) was performed. The novelty of the proposed approach lies in the use of a combination of research data and methods using artificial intelligent tools to develop and scalable conclusions. This approach is unique and has no equivalent in the literature. An analysis was conducted via two perspectives: (1) The level of environmental solutions implemented at successive stages of the product’s life cycle and (2) the size of the company. The results show significant differences between the environmental practices of small, medium, and large Polish enterprises, and reveal the emerging trends in enterprise operations, which will be subject to an AI-based analysis.
Stress and Disease Resistance in Crayfish (Procambarus clarkii) Breed “Huachizhen-1”
Authors: Ren Xin , Xiong Lijing , Tan Yunfei , Liu Xiaoyu , Zhu Xi , Bai Xufeng
Published: December 2022

Stress and disease are critical factors hindering the industrial development of red swamp crayfish (Procambarus clarkii). Breeding crayfish with stress- and disease-resistant characteristics can overcome these limitations and promote their industrial development. In this study, the crayfish breed F3, which exhibits rapid growth and a favoured haplotype combination of the immune genes R, ALF, and crustin2, encoding the Toll-like receptor, anti-lipopolysaccharide factor, and antimicrobial peptide, respectively, were selected as parents to breed offspring (the selected group (SG)). The genotype, stress resistance, and disease resistance of crayfish in the SG and unselected group (USG) were compared. The results showed that the ratio of the favoured haplotype was higher in the SG crayfish than in the USG crayfish, leading to stronger stress and disease resistance. Compared to that of the USG crayfish, the mortality of the SG crayfish subjected to stress during eight days of transport and challenged with bacteria (Aeromonas hydrophila or Vibrio parahaemolyticus) or white spot syndrome virus were significantly reduced by 60% and 20%, respectively (p < 0.05). Based on these results, the stress- and disease-resistant SG crayfish were named the “Huachizhen-1” breed. Additionally, the ratio of the unfavoured homozygous genotypes of R, ALF, and crustin2 sharply decreased, whereas those of the heterozygous genotypes increased together with stress and disease resistance during crayfish maturation under natural conditions, indicating that the heterozygotes of these genes also exhibit strong stress and disease resistance. All of this taken together, the crayfish breed “Huachizhen-1” may be applicable for improving stress and disease resistance and the production of crayfish.
HONO Formation from the Oxidation Reactions of ClO, NO, and Water in the Gas-Phase and at the Air-Water Interface
Authors: Zhang Qi , Hadizadeh Mohammad Hassan , Wang Xiaotong , Zhao Xianwei , Bai Xurong , Xu Fei , Sun Yanhui
Published: December 2022

Nitrous acid (HONO) plays a key role in atmospheric chemistry. Nevertheless, the HONO formation mechanism in the atmosphere, especially in the marine boundary layer, remains to be fully understood. Here, Born–Oppenheimer molecular dynamic and metadynamics simulations were performed to study the formation mechanism of HONO from the oxidation reactions of ClO radical and NO with the addition of (H2O)1–2, considering a monohydrated system ((ClO)(NO)(H2O)1) and dihydrated system ((ClO)(NO)(H2O)2), as well as at the air-water interface. This study shows that HONO formation follows a single-water mechanism in gas-phase and air-water interface systems. The free-energy barrier of the (ClO)(NO)(H2O)1 system was 9.66 kJ mol−1, whereas the (ClO)(NO)(H2O)2 system was a barrierless reaction. HONO formation at the air-water interface was faster than that in monohydrated and dihydrated systems. Although the concentration of ClO radical in the marine boundary layer is two orders higher than that of Cl radical, the production rates of HONO from the (ClO)(NO)(H2O)1 system are six orders lower than that from the (Cl)(NO)(H2O)1 system, which means that Cl radical dominates HONO formation rather than ClO radical in the marine boundary layer. These results can deepen our understanding of the HONO formation mechanism and be used to reduce HONO emissions and establish HONO-control strategies.
Planting Rice at Monsoon Onset Could Mitigate the Impact of Temperature Stress on Rice–Wheat Systems of Bihar, India
Authors: Montes Carlo , Urfels Anton , Han Eunjin , Balwinder-Singh
Published: December 2022

The rice–wheat rotation is the dominant cropping system in Bihar, where food security of the rural population depends heavily on the production of rice and wheat. In Bihar, farmers plant rice after the first significant rains, and climatic shocks induced by low temperatures and terminal heat stress at the end of the corresponding season can significantly affect rice and wheat yields. The present work evaluates the benefit of using an earlier date for planting rice, following the monsoon onset, in reducing thermal stress on rice–wheat systems. High-resolution gridded crop simulations using the APSIM model were performed to simulate potential yields using the monsoon onset and the farmers’ practice as planting dates. The monsoon onset was calculated using an agronomic definition, and farmers’ practice dates were estimated using satellite data. The results were analyzed in terms of planting dates, yields, and the incidence of temperature stress on rice and wheat by means of the APSIM yields limiting factors. The results show that the rice planting and harvest dates using the monsoon onset are, in general, 20–30 days earlier, which translates into higher and more stable potential yields, which can be up to 50% higher in wheat and 29% in rice. The incidence of thermal stress can be, on average, 12% lower in rice and 25% in wheat. These results can help design mitigation strategies for the impacts of temperature-induced shock events in the context of the advances in sub-seasonal and seasonal forecasting, targeting climate services for farmers in Bihar.
An Improved Strategy for Real-Time Troposphere Estimation and Its Application in the Severe Weather Event Monitoring
Authors: Zhao Lewen , Cui Mingxuan , Song Jia
Published: December 2022

The water vapor content in the atmosphere is highly correlated with rainfall events, which can be used as a data source for rainfall prediction or drought monitoring. The GNSS PPP (Precise Point Positioning) technique can be used to estimate the troposphere ZWD (Zenith Wet Delay) parameter which can be converted into precipitable water vapor (PWV). In this study, we first investigate the impacts of the weighting strategies, observation noise settings, and gradient estimation on the accuracy of ZWD and positions. A refined strategy is proposed for the troposphere estimation with uncombined raw PPP model, down-weighting of Galileo/GLONASS/BDS code observation by a factor of 3, using a sine2-type elevation-dependent weighting function and estimating the horizontal gradients. Based on the strategy, the correlation of the estimated tropospheric parameters with the rainfall is analyzed based on the data from the “7.20” rainstorm in Henan Province, China. The PWV is first calculated based on the hourly global pressure and temperature (HGPT) model and compared with the results from ERA5 products. Results show their good consistency during the rainfall period or the normal period with a standard deviation of 3 mm. Then, the high correlation between the PWV and the heavy rain rainfall event is validated. Results show that the accumulated PWV maintains a high level before the rainstorm if a sustainable water supply is available, while it decreased rapidly after the rainfall. In comparison, the horizontal gradients and the satellite residuals are less correlated with the water vapor content. However, the gradients can be used to indicate the horizontal asymmetry of the water vapor in the atmosphere.
Comparison of Tinnitus Handicap Inventory and Tinnitus Functional Index as Treatment Outcomes
Authors: Fernández Marta , Cuesta María , Sanz Ricardo , Cobo Pedro
Published: December 2022

Background: Tinnitus is an audiological disorder for which there are no objective measuring tools. Thus, many self-report questionnaires have been proposed to assess its severity. These questionnaires have been judged for their capacity to assess the tinnitus severity at baseline, their sensitivity to treatment-related changes (responsiveness), and their resolution. Methods: The most widely used questionnaires for clinical and research studies are the Tinnitus Handicap Inventory (THI) and the Tinnitus Functional Index (TFI). While both questionnaires have been recognized as good evaluators of the baseline tinnitus severity, the latter is considered to be more responsive to changes following treatments. Objectives: The aim of this work is to provide a preliminary comparison of the performance of both questionnaires in the initial and final tinnitus severity assessment of a cohort of patients undergoing a four-month Enriched Acoustic Environment (EAE) therapy. Results: The EAE therapy provided a 30 and 26 point reduction in THI and TFI, respectively. A good correlation is obtained between the THI and TFI questionnaires at baseline and after the treatment. Conclusion: At baseline, the THI provided a higher score than the TFI for a higher degree of tinnitus but a lower score for lower tinnitus severity. Both THI and TFI were good questionnaires for baseline assessment and for treatment-related changes. The THI provided a slightly higher score drop than the TFI following the treatment, although the TFI had better resolution.
Dynamic Correlation between the Chinese and the US Financial Markets: From Global Financial Crisis to COVID-19 Pandemic
Authors: Liu Jianxu , Wan Yang , Qu Songze , Qing Ruihan , Sriboonchitta Songsak
Published: December 2022

As China’s economy and the U.S. economy have shown a definite interaction, there is considerable interest in studying the correlation between the Chinese stock market and the US financial markets. This paper uses an Asymmetric Dynamic Conditional Correlation (ADCC)-GARCH to investigate the correlation between the Shanghai Composite Index (SHCI) and the U.S. financial markets, including SP500, NASDAQ, and US dollar indexes. The empirical results show that the time-varying daily and the lag-one correlation between China and the US stock markets have different performances during global events and national events. Compared with the complicated effect of negative events on the correlation of the stock market, SHCI and USD are negatively correlated with higher negative correlation during the global negative events. In addition, we found Chinese investors are more contagious to the news than American investors, indicating that the Chinese government’s policy are more indicated to Chinese investors. Finally, some policy suggestions are provided, and are beneficial to risk prevention and control, and investment.
Fejér-Type Midpoint and Trapezoidal Inequalities for the Operator ω1,ω2-Preinvex Functions
Authors: Mehmood Sikander , Srivastava Hari Mohan , Mohammed Pshtiwan Othman , Al-Sarairah Eman , Zafar Fiza , Nonlaopon Kamsing
Published: December 2022

In this work, we obtain some new integral inequalities of the Hermite–Hadamard–Fejér type for operator ω1,ω2-preinvex functions. The bounds for both left-hand and right-hand sides of the integral inequality are established for operator ω1,ω2-preinvex functions of the positive self-adjoint operator in the complex Hilbert spaces. We give the special cases to our results; thus, the established results are generalizations of earlier work. In the last section, we give applications for synchronous (asynchronous) functions.
Improved Method for Oriented Waste Detection
Authors: Yang Weizhi , Xie Yi , Gao Peng
Published: December 2022

Waste detection is one of the main problems preventing the realization of automated waste classification, which is a basic function for robotic arms. In addition to object identification in general image analysis, a waste-sorting robotic arm not only needs to identify a target object but also needs to accurately judge its placement angle so that it can determine an appropriate angle for grasping. In order to solve the problem of low-accuracy image detection caused by irregular placement angles, in this work, we propose an improved oriented waste detection method based on YOLOv5. By optimizing the detection head of the YOLOv5 model, this method can generate an oriented detection box for a waste object that is placed at any angle. Based on the proposed scheme, we further improved three aspects of the performance of YOLOv5 in the detection of waste objects: the angular loss function was derived based on dynamic smoothing to enhance the model’s angular prediction ability, the backbone network was optimized with enhanced shallow features and attention mechanisms, and the feature aggregation network was improved to enhance the effects of feature multi-scale fusion. The experimental results showed that the detection performance of the proposed method for waste targets was better than other deep learning methods. Its average accuracy and recall were 93.9% and 94.8%, respectively, which were 11.6% and 7.6% higher than those of the original network, respectively.
Multidimensional Markovian BSDEs with Jumps and Continuous Generators
Authors: Eddahbi Mhamed , Almualim Anwar , Khelfallah Nabil , Madoui Imène
Published: December 2022

We deal with a multidimensional Markovian backward stochastic differential equation driven by a Poisson random measure and independent Brownian motion (BSDEJ for short). As a first result, we prove, under the Lipschitz condition, that the BSDEJ’s adapted solution can be represented in terms of a given Markov process and some deterministic functions. Then, by means of this representation, we show existence results for such equations assuming that their generators are totally or partially continuous with respect to their variables and satisfy the usual linear growth conditions. The ideas of the proofs are to approximate the generator by a suitable sequence of Lipschitz functions via convolutions with mollifiers and make use of the L2–domination condition, on the law of the underlying Markov process, for which several examples are given.
Digital Coupon Promotion and Inventory Strategies of Omnichannel Brands
Authors: Zhang Yue , Hu Xiaojian
Published: December 2022

This paper investigates when an omnichannel brand should offer digital coupons in the online and buy-online-and-pick-up-in-store (BOPS) channels and, if so, the joint decision of coupon face value and store inventory. The impact of a digital coupon promotion on store inventory is also explored. Two scenarios are considered, one where consumers’ costs in the online and store channels are homogeneous and another in which they are heterogeneous, and two newsvendor models, with and without a coupon promotion, are constructed under each scenario. The results show that the issuance of coupons improves the omnichannel brand’s profit when the price is high and the coefficient of the difference in valuation between two types of consumers is low in the homogeneous scenario. In the heterogeneous scenario, the brand prefers the coupon promotion when the price is high or moderate and the coefficient of the difference in valuation between two types of consumers is high. In addition, offering a coupon promotion yields a higher store inventory in most cases. However, store inventory is decreased in some special cases in the homogeneous scenario. Moreover, an increased hassle cost in the BOPS channel significantly lowers the offline demand and profit increase from a digital coupon promotion. Furthermore, a coupon promotion is more likely to benefit both the brand and consumers as the cross-selling revenue increases. These results provide guidance for omnichannel brands to implement coupon promotions and adjust store inventory with stochastic demand.
The Assessment of Electric Vehicle Storage Lifetime Using Battery Thermal Management System
Authors: Pires Rodrigo A. , Carvalho Samuel A. , Cardoso Filho Braz J. , Pires Igor A. , Huebner Rudolf , Maia Thales A. C.
Published: December 2022

Degradation and heat generation are among the major concerns when treating Lithium-ion batteries’ health and performance parameters. Due to the high correlation between the battery’s degradation, autonomy and heat generation to the cell’s operational temperature, the Battery Thermal Management System plays a key role in maximizing the battery’s health. Given the fact that the ideal temperature for degradation minimization usually does not match the ideal temperature for heat generation minimization, the BTMS must manage these phenomena in order to maximize the battery’s lifespan. This work presents a new definition of the discharge operation point of a lithium-ion battery based on degradation, autonomy and heat generation. Two cells of different electrodes formulation were modeled and evaluated in a case study. The results demonstrated a 50% improvement on total useful battery cycles in best-case scenarios.
Ultrasonication Effects on Quality of Tea-Based Beverages
Authors: Uzuner Sibel
Published: December 2022

Tea is the most popular consumed drink after water. Teas and tea-based beverages have grown in popularity due to bioactive compounds. Tea-based beverages have started to take their place in the market. Extraction is a crucial step for the production of functional tea-based beverages. Compared to conventional methods, ultrasound is attractive due to its lower energy requirements, and shorter extraction time. This review aimed to discuss recent marketing aspects of tea-based beverages as well as the potential and challenges of a novel infusion technique. This review describes the health benefits and technological aspects of tea-based beverages in relation to how to best solve nutritional and microbial concerns. Current and future challenges and opportunities of the novel infusion technique and its scaling-up for the extraction of bioactive compounds are also covered in the present review.
Metallic Microneedles for Transdermal Drug Delivery: Applications, Fabrication Techniques and the Effect of Geometrical Characteristics
Authors: Sargioti Nikoletta , Levingstone Tanya J. , O’Cearbhaill Eoin D. , McCarthy Helen O. , Dunne Nicholas J.
Published: December 2022

Current procedures for transdermal drug delivery (TDD) have associated limitations including poor administration of nucleic acid, small or large drug molecules, pain and stress for needle phobic people. A painless micro-sized device capable of delivering drugs easily and efficiently, eliminating the disadvantages of traditional systems, has yet to be developed. While polymeric-based microneedle (MN) arrays have been used successfully and clinically as TDD systems, these devices lack mechanical integrity, piercing capacity and the ability to achieve tailored drug release into the systemic circulation. Recent advances in micro/nano fabrication techniques using Additive Manufacturing (AM), also known as 3D printing, have enabled the fabrication of metallic MN arrays, which offer the potential to overcome the limitations of existing systems. This review summarizes the different types of MNs used in TDD and their mode of drug delivery. The application of MNs in the treatment of a range of diseases including diabetes and cancer is discussed. The potential role of solid metallic MNs in TDD, the various techniques used for their fabrication, and the influence of their geometrical characteristics (e.g., shape, size, base diameter, thickness, and tip sharpness) on effective TDD are explored. Finally, the potential and the future directions relating to the optimization of metallic MN arrays for TDD are highlighted.
Distinction of Different Colony Types by a Smart-Data-Driven Tool
Authors: Rodrigues Pedro Miguel , Ribeiro Pedro , Tavaria Freni Kekhasharú
Published: December 2022

Background: Colony morphology (size, color, edge, elevation, and texture), as observed on culture media, can be used to visually discriminate different microorganisms. Methods: This work introduces a hybrid method that combines standard pre-trained CNN keras models and classical machine-learning models for supporting colonies discrimination, developed in Petri-plates. In order to test and validate the system, images of three bacterial species (Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus) cultured in Petri plates were used. Results: The system demonstrated the following Accuracy discrimination rates between pairs of study groups: 92% for Pseudomonas aeruginosa vs. Staphylococcus aureus, 91% for Escherichia coli vs. Staphylococcus aureus and 84% Escherichia coli vs. Pseudomonas aeruginosa. Conclusions: These results show that combining deep-learning models with classical machine-learning models can help to discriminate bacteria colonies with good accuracy ratios.