bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree
Authors: Wang Wei , Zhang Yi , Ge Genyu , Jiang Qin , Wang Yang , Hu Lihe
Published: October 2021

The spatial index structure is one of the most important research topics for organizing and managing massive 3D Point Cloud. As a point in Point Cloud consists of Cartesian coordinates (x,y,z), the common method to explore geometric information and features is nearest neighbor searching. An efficient spatial indexing structure directly affects the speed of the nearest neighbor search. Octree and kd-tree are the most used for Point Cloud data. However, octree or KD-tree do not perform best in nearest neighbor searching. A highly balanced tree, 3D R*-tree is considered the most effective method so far. So, a hybrid spatial indexing structure is proposed based on octree and 3D R*-tree. In this paper, we discussed how thresholds influence the performance of nearest neighbor searching and constructing the tree. Finally, an adaptive way method adopted to set thresholds. Furthermore, we obtained a better performance in tree construction and nearest neighbor searching than octree and 3D R*-tree.
Comparison of Fracture Strengths of Three Provisional Prosthodontic CAD/CAM Materials: Laboratory Fatigue Tests
Authors: Mendes José Manuel , Botelho Pedro Colaço , Mendes Joana , Barreiros Pedro , Aroso Carlos , Silva António Sérgio
Published: October 2021

Temporary restorations play a fundamental role in oral rehabilitation. They can be used on teeth or implants for a variable period of time during the period prior to rehabilitation with definitive restorations. Temporary or provisional restorations manufactured via CAD/CAM methods are becoming increasingly used in the intermediate phase of the treatment of complex cases. The main objective of this study was to compare the fracture resistance of three materials used in the creation of provisional crowns on implants: polymethyl methacrylate (PMMA), composite resin, and polyether ether ketone (PEEK). Fracture resistance in PMMA (Zirkonzahn Temp Basic® , Gais, South Tyrol, Italy) ranged from 1216.0 N to 1461.2 N, with a mean of 1300.4 N (SD = 97.09). In the composite material (3M Lava Ultimate®, Minnesota, USA), fracture resistance varied between 1343.5 N and 1490.6 N, with a mean of 1425.9 N (SD = 49.03). Lastly, in PEEK (Tecno Med Mineral®, Zirkonzahn®, Gais, South Tyrol, Italy), fracture resistance ranged from 2294.8 N to 2451.7 N, with a mean of 2359.5 (SD = 50.01). The crowns made with the PEEK Tecno Med Mineral® (Zirkonzahn®, Tyrol, Italy) material presented the best fracture resistance, followed by the crowns made with the Lava Ultimate® (3M® ESPE, Minnesota, USA) composite resin material and, finally, those made with the PMMA Temp Basic® (Zirkonzahn®, Tyrol, Italy) material.
Flexural Behavior of Steel Fiber Reinforced Concrete Beams: Probabilistic Numerical Modeling and Sensitivity Analysis
Authors: Blagojević Predrag , Blagojević Nikola , Kukaras Danijel
Published: October 2021

One of the principle issues concerning the practical application of steel fiber reinforced concrete (SFRC) is the uncertainty related to its structural behavior, primarily caused by the partially random distribution and orientation of steel fibers in SFRC structural elements. This paper aims to provide a better understanding of how the variance of material properties of the SFRC affects the flexural behavior of SFRC beams. First, a distributed plasticity fiber finite element model of beam flexural behavior is proposed and validated. Then, probability distributions of selected material properties are defined based on existing probabilistic models and experimental results from the literature. Finally, a variance-based sensitivity analysis is performed using Sobol’ indices to identify uncertainties in material properties that contribute most to the uncertainties related to three characteristic points of a beam’s flexural behavior: first crack, yield, and collapse point. Sensitivity analysis is performed by surrogating the numerical model using polynomial chaos expansion. The variance in residual tensile strength is identified as the main contributor to the variance in the flexural behavior of an SFRC beam used in the case study.
Closed-Loop Modeling to Evaluate the Performance of a Scaled-Up Lithium–Sulfur Battery in Electric Vehicle Applications
Authors: Zeng Qingxin , Zou Zhuo , Chen Jie , Jiang Yali , Zeng Lingzhi , Li Changming
Published: October 2021

A closed-loop modeling method was established here to evaluate the performance of new battery technology from lab research to scaled-up developed electric vehicle (EV) applications. As an emerging energy-storage device, the lithium–sulfur battery (LSB) is a very promising candidate for the next generation of rechargeable batteries. However, it has been difficult to commercialize the LSB up to now. In this work, we designed and built a battery, EV, and driver system loop model to study the key performance parameters of LSB operation in EVs, in which the tested data from the lab were introduced into the model followed by simulating driving cycles and fast charging. A comparison with the lithium-ion batteries used in real vehicles verified the high reliability of the model. Meanwhile, the simulation results showed that the LSB needs more improvements for EV application; in particular, developments are still highly needed to overcome the high power and energy loss and sharp voltage vibration for practical applications. The novelty of this work relies on the created closed-loop modeling method to simulate lab research results for evaluating new battery technology in scaled-up EV applications in order to not only vividly predict EV operation performance and commercialization feasibility, but also thoughtfully guide researchers and developers for further optimization and problem solutions. Therefore, this method holds great promise as a powerful tool for both lab research and the industrial development of new batteries for EV applications.
Using the Local Drought Data and GRACE/GRACE-FO Data to Characterize the Drought Events in Mainland China from 2002 to 2020
Authors: Cui Lilu , Zhang Cheng , Luo Zhicai , Wang Xiaolong , Li Qiong , Liu Lulu
Published: October 2021

Accurate quantification of drought characteristics helps to achieve an objective and comprehensive analysis of drought events and to achieve early warning of drought and disaster loss assessment. In our study, a drought characterization approach based on drought severity index derived from Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) data was used to quantify drought characteristics. In order to improve drought detection capability, we used the local drought data as calibration criteria to improve the accuracy of the drought characterization approach to determine the onset of drought. Additionally, the local precipitation data was used to test drought severity determined by the calibrated drought characterization approach. Results show that the drought event probability of detection (POD) of this approach in the four study regions increased by 61.29%, 25%, 94.29%, and 66.86%, respectively, after calibration. We used the calibrated approach to detect the drought events in Mainland China (MC) during 2016 and 2019. The results show that CAR of the four study regions is 100.00%, 92.31%, 100.00%, and 100.00%. Additionally, the precipitation anomaly index (PAI) data was used to evaluate the severity of drought from 2002 to 2020 determined by the calibrated approach. The results indicate that both have a strong similar spatial distribution. Our analysis demonstrates that the proposed approach can serve a useful tool for drought monitoring and characterization.
Different Fault Response to Stress during the Seismic Cycle
Authors: Zaccagnino Davide , Telesca Luciano , Doglioni Carlo
Published: October 2021

Seismic prediction was considered impossible, however, there are no reasons in theoretical physics that explicitly prevent this possibility. Therefore, it is quite likely that prediction is made stubbornly complicated by practical difficulties such as the quality of catalogs and data analysis. Earthquakes are sometimes forewarned by precursors, and other times they come unexpectedly; moreover, since no unique mechanism for nucleation was proven to exist, it is unlikely that single classical precursors (e.g., increasing seismicity, geochemical anomalies, geoelectric potentials) may ever be effective in predicting impending earthquakes. For this reason, understanding the physics driving the evolution of fault systems is a crucial task to fine-tune seismic prediction methods and for the mitigation of seismic risk. In this work, an innovative idea is inspected to establish the proximity to the critical breaking point. It is based on the mechanical response of faults to tidal perturbations, which is observed to change during the “seismic cycle”. This technique allows to identify different seismic patterns marking the fingerprints of progressive crustal weakening. Destabilization seems to arise from two different possible mechanisms compatible with the so called preslip patch, cascade models and with seismic quiescence. The first is featured by a decreasing susceptibility to stress perturbation, anomalous geodetic deformation, and seismic activity, while on the other hand, the second shows seismic quiescence and increasing responsiveness. The novelty of this article consists in highlighting not only the variations in responsiveness of faults to stress while reaching the critical point, but also how seismic occurrence changes over time as a function of instability. Temporal swings of correlation between tides and nucleated seismic energy reveal a complex mechanism for modulation of energy dissipation driven by stress variations, above all in the upper brittle crust. Some case studies taken from recent Greek seismicity are investigated.
Crack Propagation Process and Seismogenic Mechanisms of Rock Due to the Influence of Freezing and Thawing
Authors: Si Kai , Cui Zhendong , Peng Ruidong , Zhao Leilei , Zhao Yan
Published: October 2021

A common problem in cold regions is the influence of freeze–thaw damage on the stability of rock engineering. Therefore, a series of uniaxial compression tests of sandstone after freeze–thaw treatment was carried out in this study. The purpose was to express the initial damage of rock after freezing and thawing treatment more quantitatively and to study the influence of freeze–thaw damage on the rock crack growth process to provide some reference for the stability evaluation of rock engineering in cold regions. The results showed that the number of freeze–thaw cycles and the lowest freeze–thaw temperature had a significant effect on the rock damage and characteristic stress value, and the number of cycles had a more obvious effect: with an increase in the number of freeze–thaw cycles and a decrease in the freeze–thaw temperature, the initial damage DNT had an increasing trend. In addition, the intrinsic mechanism of the freeze–thaw effect on the rock characteristic stress was explained from the perspective of a meso-mechanical mechanism. From the inversion results of the acoustic emission (AE) moment tensor, it was found that the proportion of tensile cracks gradually increased with the increase in the initial damage of the rock in the stable and unsteady stages of the rock crack propagation.
Effects and Mechanism of Plasma-Activated Medium on Angiogenesis of Vascular Endothelial Cells
Authors: Hao Yue , Xu Guimin , Wang Xiangni , Cui Yixin , Liu Na , Shi Xingmin , Zhang Guanjun
Published: October 2021

After cell culture medium is treated with low temperature plasma (LTP), the liquid is rich in reactive oxygen and nitrogen species (RONS), and becomes plasma-activated medium (PAM). PAM, as the supplier of RONS, can affect the angiogenesis of cells. The purpose of this study is to investigate the effects and related mechanism of PAM on human umbilical vein endothelial cells (HUVECs). Cell viability and cell cycle were evaluated after HUVECs were treated with PAM for 24 h. Changes in cell angiogenesis, migration and adhesion, secretion of cytokines such as VEGF and bFGF, expression of VEGFR-2 and phosphorylation of the key proteins in the MEK/ERK signaling pathway, concentrations of H2O2 and NO2− in PAM and in cells were also investigated. The results showed that PAM obtained by LTP treatment had dual effects on the angiogenesis of HUVECs: PAM obtained by short-term LTP treatment promoted the angiogenesis of HUVECs, while PAM obtained by long-term LTP treatment inhibited the angiogenesis of HUVECs. The mechanism may be that PAM treatment changes the content of RONS, affects the VEGF-VEGFR-2 signaling pathway, and ultimately affects the angiogenesis of HUVECs.
Tunable Mixed-Mode Voltage Differencing Buffered Amplifier-Based Universal Filter with Independently High-Q Factor Controllability
Authors: Roongmuanpha Natchanai , Faseehuddin Mohammad , Herencsar Norbert , Tangsrirat Worapong
Published: October 2021

This paper proposes the design of a mixed-mode universal biquad configuration, which realizes generic filter functions in all four possible modes, namely voltage mode (VM), current mode (CM), transadmittance mode (TAM), and transimpedance mode (TIM). The filter architecture employs two voltage differencing buffered amplifiers (VDBAs), two resistors and two capacitors, and can provide lowpass (LP), bandpass (BP), highpass (HP), bandstop (BS), and allpass (AP) biquadratic filtering responses without any circuit alteration. All passive elements used are grounded, except VM. The circuit not only allows for the electronic tuning of the natural angular frequency (ωo), but also achieves orthogonal tunability of the quality factor (Q). It also provides the feature of availability of output voltage at the low-output impedance terminal in VM and TIM, and does not require inverting-type or double-type input signals to realize all the responses. Moreover, in all modes of operation, the high-Q filter can be easily obtained by adjusting a single resistance value. Influences of the VDBA nonidealities and parasitic elements are also discussed in detail. PSPICE simulations with TSMC 0.18-µm CMOS process parameters and experimental testing results with commercially available IC LT1228s have been used to validate the theoretical predictions.
Eliciting Auxiliary Information for Cold Start User Recommendation: A Survey
Authors: Abdullah Nor Aniza , Rasheed Rasheed Abubakar , Nasir Mohd Hairul Nizam Md. , Rahman Md Mujibur
Published: October 2021

Recommender systems suggest items of interest to users based on their preferences. These preferences are typically generated from user ratings of the items. If there are no ratings for a certain user or item, it is said that there is a cold start problem, which leads to unreliable recommendations. Existing studies that reviewed and examined cold start in recommender systems have not explained the process of deriving and obtaining the auxiliary information needed for cold start recommendation. This study surveys the existing literature in order to explain the various approaches and techniques employed by researchers and the challenges associated with deriving and obtaining the auxiliary information necessary for cold start recommendation. Results show that auxiliary information for cold start recommendation is obtained by adapting traditional filtering and matrix factorization algorithms typically with machine learning algorithms to build learning prediction models. The understanding of similar or connected user profiles can be used as auxiliary information for building cold start user profile to enable similar recommendations in social networks. Similar users are clustered into sub-groups so that a cold start user could be allocated and inferred to a sub-group having similar profiles for recommendations. The key challenges of the process for obtaining the auxiliary information involve: (1) two separate recommendation processes of conversion from pure cold start to warm start before eliciting the auxiliary information; (2) the obtained implicit auxiliary information is usually ranked and sieved in order to select the top rated and reliable auxiliary information for the recommendation. This study also found that cold start user recommendation has frequently been researched in the entertainment domain, typically using music and movie data, while little research has been carried out in educational institutions and academia, or with cold start for mobile applications.
Age Estimates from Name Characters
Authors: Liou Jung-Shiuan , Hsiao Ching-Yen , Chow Lork-Yee , Huang Yen-Hao , Chen Yi-Shin
Published: October 2021

Traditionally, we have been attempting to extract useful features from the massive amount of data generated daily. However, following the legal constraints regarding personal data protection and the challenges of potential data biases and manipulation, artificial intelligence that relies less on big data and more on reasoning ability has become an emerging trend. This paper demonstrates how to estimate age and gender using names only. The proposed two-layer comparative model was trained on Taiwanese names, and its generalizability was further examined on bilingual and cross-border names. By considering additional features of the contextual environment, the model achieves high accuracy in age and gender prediction on Taiwanese and bilingual names. However, the prediction results for ethnic-Chinese Malaysian names (in English) do not reach the same level. This is due to the linguistic differences among Chinese dialects; the features trained on Taiwanese names cannot be directly applied to English names in Malaysia. This study illustrates a path for accomplishing prediction tasks using minimal data and highlights a future possibility for further research.
A Proposal for a Simple Method for Determining the Concrete Slab Width of Composite Beam-to-Column Joints
Authors: Lu Linfeng , Wang Di , Ding Kai , Yan Hongwei , Hao Hanlin
Published: October 2021

Extensive brittle failures in the weld zone of the beam bottom flange in composite joints of SMRFs were observed during the Northridge earthquake and the Kobe earthquake. One of the main reasons is the large tensile strain demand generated at the beam bottom flange zone under positive bending. The key to accurately understanding the mechanical properties of composite joints is the effective width of the slab. However, researchers have no consensus on the flange slab’s effective width for composite joints, even with the simplest solid concrete slab. Therefore, the best way to design the composite joint specimen is by following the current design specifications. However, each specification implements different ideas and approaches for specifying an effective slab width. This paper presents comparisons of the effective flange width provisions in China, the United States, Australia/New Zealand, and the European Union. The characteristics of each provision are briefly described and summarized. Numerical comparisons for positive and negative moment regions of continuous spans follow. Based on the commonalities and main differences among all these provisions, we propose a recommended equation for calculating the effective width of a solid concrete slab, reflecting the specification differences. The reliability of the recommended equation was verified with ABAQUS software analysis. The recommended equation can meet the fast and secure design requirements for composite joints in tests with concrete slabs.
Application of Artificial Neural Networks in Construction Management: Current Status and Future Directions
Authors: Liu Shicheng , Chang Ruidong , Zuo Jian , Webber Ronald J. , Xiong Feng , Dong Na
Published: October 2021

Artificial neural networks (ANN) exhibit excellent performance in complex problems and have been increasingly applied in the research field of construction management (CM) over the last few decades. However, few papers draw up a systematic review to evaluate the state-of-the-art research on ANN in CM. In this paper, content analysis is performed to comprehensively analyze 112 related bibliographic records retrieved from seven selected top journals published between 2000 and 2020. The results indicate that the applications of ANN of interest in CM research have been significantly increasing since 2015. Back-propagation was the most widely used algorithm in training ANN. Integrated ANN with fuzzy logic/genetic algorithm was the most commonly employed way of addressing the CM problem. In addition, 11 application fields and 31 research topics were identified, with the primary research interests focusing on cost, performance, and safety. Lastly, challenges and future directions for ANN in CM were put forward from four main areas of input data, modeling, application fields, and emerging technologies. This paper provides a comprehensive understanding of the application of ANN in CM research and useful reference for the future.
A Model-Driven Architecture for Automated Deployment of Microservices
Authors: Aksakalli Isil Karabey , Celik Turgay , Can Ahmet Burak , Tekinerdogan Bedir
Published: October 2021

Microservice architecture consists of a collection of loosely coupled, self-contained services that can be deployed independently. Given the limited capacity of the resources for a large number of services, the deployment of the services does not scale well and leads to operational complexity and runtime overhead. This paper proposes a model-driven approach for the automated deployment of microservices to minimize the execution cost and communication costs among the microservices. The identification of the feasible deployment is defined at the architecture design level based on the provided capacity of the resources and the collection of microservices. The corresponding tool support using Eclipse Modeling Environment is described, and a case study on book shopping is used to illustrate the approach.
Experimental Study on the Near-Bed Flow Characteristics of Alluvial Channel with Seepage
Authors: Sharma Anurag , Kumar Bimlesh , Oliveto Giuseppe
Published: October 2021

This paper aims to analyze the turbulent structure of flows over beds undergoing downward seepage under clear-water conditions. Laboratory experiments in this regard were carried out in a straight rectangular channel that was 17.20 m long and 1.00 m wide. A sandy bed with median grain size d50 = 0.50 mm and sediment gradation σg = 1.65 (i.e., slightly non-uniform sediment) was used for the channel bed. The 3D instantaneous velocities of water were measured with an Acoustic Doppler Velocimeter (ADV) at the working test section. In the vicinity of the bed surface with seepage, measurements revealed that the flow longitudinal velocities (i.e., velocities in x direction) were higher than those in the case of a bed without seepage. Moreover, the variations inthe Reynolds shear stresses increased for the bed with seepage, indicating a higher exchange of flow energy towards the boundary and vice versa. Therefore, it was found that seepage processes influence the turbulence intensity, with a prominent magnitude in the streamwise and vertical directions. The paper also focuses on the third-order moment (skewness) and the kurtosis of velocity fluctuations and the governance of sweep events within the near-bed flow in cases where seepage was observed.
LogoNet: A Robust Layer-Aggregated Dual-Attention Anchorfree Logo Detection Framework with an Adversarial Domain Adaptation Approach
Authors: Jain Rahul Kumar , Watasue Taro , Nakagawa Tomohiro , Sato Takahiro , Iwamoto Yutaro , Ruan Xiang , Chen Yen-Wei
Published: October 2021

The task of logo detection is desirable and important for various fields. However, it is challenging and difficult to identify logos in complex scenarios as a logo can appear in different styles and platforms. Logo images include diverse contexts, sizes, projective transformation, resolution, illumination and fonts, which make it more difficult to detect a logo. To address these issues, we presented a deep learning-based algorithm for logo detection called LogoNet. It includes an hourglass like top-down bottom-up feature extraction network, a spatial attention module and an anchorfree detection head similar to CenterNet. In order to improve performance, in this paper, an extended version of LogoNet is proposed, called—Dual-Attention LogoNet, that exploits different attention mechanisms more efficiently. The incorporated channel-wise and spatial attention modules refine and generate robust and balanced feature maps to predict visual and semantic information more accurately. In addition, we propose a lightweight architecture for both LogoNet and Dual-Attention LogoNet for practical applications. The proposed lightweight architecture significantly reduces the number of network parameters and improves the inference time to address the real-time performance while maintaining accuracy. Furthermore, to address the domain shift problem in practical applications, we also propose an adversarial-learning-based domain adaptation approach, which is easily adaptable to any anchorfree detectors. Our attention-based method shows a 1.8% improvement in accuracy compared to the state-of-the-art detection network on the FlickrLogos-32 dataset. Our proposed domain adaptation approach significantly improves performance by 1.3% mAP compared to direct transfer on the target domain without increasing any labeling cost and network parameters.
Toward a Better Understanding of Academic Programs Educational Objectives: A Data Analytics-Based Approach
Authors: Yahya Anwar Ali , Sulaiman Adel A. , Mashraqi Aisha Mousa , Zaidan Ziad M. , Halawani Hanan Talal
Published: October 2021

In outcome-based academic programs, Program Education Objects (PEOs) are the key pillars on which program components are built. They are articulated linguistically as broad statements of graduates’ professional and career accomplishments within a few years of graduation. Moreover, PEOs are mapped into a set of skills and attributes known as Program Learning Outcomes (PLOs). It goes without saying that a profound understanding of the PEOs is a key factor in the success of an academic program. For this sake, this paper proposes a data analytics-based approach to examine the correlations among PEOs. More specifically, it applies a data similarity-based approach to analyze the correlations among the PEOs of engineering programs. To this end, a dataset of PEOs–PLOs mapping of a set of engineering programs has been extracted from their self-study reports. The collected dataset has undergone preprocessing steps to transform it into a suitable representation. This involves data cleaning, data annotation using a developed set of PEOs labels, and removal of data instances with multiple PEO labels. Each PEO is then represented as a vector space model whose dimensions are the PLOs, and their values are the relative frequencies of PLOs computed from all data instances of that PEO. After that, three data similarity measures, namely Euclidean distance, cosine measure, and Manhattan distance, are applied to measure the similarity between PEOs vector space models. The resultant similarity matrices are then analyzed at the level of a specific measure, an agreement between measures, and average similarity across all measures. The analysis results contribute to a better understanding of the PEOs correlations and provide very useful actionable insights for empowering decision making toward systemization and optimization of academic programs processes.
Understanding the Adsorption Capacity for CO2 in Reduced Graphene Oxide (rGO) and Modified Ones with Different Heteroatoms in Relation to Surface and Textural Characteristics
Authors: Politakos Nikolaos , Cordero-Lanzac Tomás , Tomovska Radmila
Published: October 2021

Reduced graphene oxide is a material that has a variety of applications, especially in CO2 adsorption. The study of this research is the preparation of reduced graphene oxide with different heteroatoms and how the adsorption capacity is changed. The functionalization with other compounds bearing Si, S, N, and O was before reducing graphene oxide. Different monoliths were prepared by changing the ascorbic acid analogy and the temperature of reduction. The different porosity values, percentages of heteroatoms, and synthetic parameters show that the adsorption capacity is a complex procedure that can be affected by multiple parameters. Microporosity, different functionalities from heteroatoms, and high surface/volume of pores are the significant parameters that affect adsorption. All parameters should establish a balance among all parameters to achieve high adsorption of CO2.
Real-Time Circuit Breaker Availability Assessment in the Transmission Network
Authors: Petrović Ivica , Glavaš Hrvoje , Noskov Robert , Blažević Damir
Published: October 2021

Circuit breakers (CBs) in the transmission network are the basic elements for energy flow control. CB diagnosis represents a decisive action for increasing power system reliability and safety. Their actual availability status and ability to perform major functions can sometimes be difficult to determine. This paper presents a general state estimation model based on fuzzy logic (FL), membership function (MF), and expert knowledge for diagnosis schemes to handle unclear information in the diagnosis procedure. The proposed model uses inputs from the Supervisory Control and Data Acquisition (SCADA) system, data on the position and state of the switch, changes in current in the network element CB (NECB), start or trip action of a protection relay on the NECB, and alarm status of the CB. For the diagnostic system input variables, data from the SCADA system, along with transformer and line protection devices, are used to allow the proper formation of rules and ultimately to determine the diagnostic status of the CB. The proposed method is tested on an authentic test power system, and the outcome results are compared with a previously reported technique. The obtained test results and the comparison prove the efficiency, authenticity, and fast operation feature of the suggested strategy.
Coupled Flexural-Electrical Evaluation of Additively Manufactured Multifunctional Composites at Ambient Temperature
Authors: Ghimire Ritesh , Liou Frank
Published: October 2021

Multifunctional composites offer a higher strength to weight ratio, electrical properties, etc., thereby providing possible solutions for replacing the physical electrical wirings in aircraft. The lack of research on the coupled multifunctional characterization of 3D printed composites flexural-electrical properties is the main reason for its unsuitability in aerospace applications. The proposed method evaluates multifunctional flexural-electrical properties of 3D printed multifunctional carbon fiber composites. Traditional methods for conducting structural and electrical analyses for aircraft certification do not accommodate new technologies that are not yet proven. Such technologies are additive manufacturing (AM) techniques, multifunctional composite structures, and the certification requirements for 3D printed multifunctional carbon fiber composites for use in aircraft. In this study, the multifunctional 3D printed specimens were concurrently evaluated for flexural-electrical properties using three-point bending and electrical conductivity tests. The results showed that the multifunctional properties included the maximum flexural strength of 271 MPa and the maximum electrical resistance of 55.1 G Ohms, with the failure modes and mechanisms found to be consistent with the traditional composites. Due to its infancy, the existing AM techniques, and the use of the multifunctional carbon fiber composites manufactured using those AM technologies, are not implemented on a large commercial scale.
Epidemic Location Intelligence System as Response to the COVID-19 Outbreak in Bosnia and Herzegovina
Authors: Karabegovic Almir , Ponjavic Mirza , Hukic Mirsada
Published: October 2021

The outbreak of COVID-19 is a public health emergency that caused disastrous results in many countries. The global aim is to stop transmission and prevent the spread of the disease. To achieve it, every country needs to scale up emergency response mechanisms, educate and actively communicate with the public, intensify infected case finding, contact tracing, monitoring, quarantine of contacts, and isolation of cases. Responding to an emergency requires efficient collaboration and a multi-skilled approach (medical, information, statistical, political, social, and other expertise), which makes it hard to define one interface for all. As actors from different perspectives and domain backgrounds need to address diverse functions, the possibility to exchange available information quickly would be desirable. In Bosnia and Herzegovina, a joint state-level public health institution has not been established, but is covered by entity competencies. In this sense, a geoportal has been developed as an epidemiological location-intelligence system (ELIS) that supports the exchange of such information between the entities and the cantons. For its development, open source software components in the cloud were used as a working platform with all the necessary functionalities. The geoportal provides an entry point for access to geospatial, epidemiological, environmental and statistical data used for analysis, geocoding of confirmed COVID-19 cases, identification of disease dynamics, identification of vulnerable groups, mapping of health capacities, and general modeling of infection spread with application support for communication and collaboration between all institutions and the public. The paper describes the challenges and ways to overcome them in the development and use of ELIS.
Quantitative Precipitation Forecasting Using an Improved Probability-Matching Method and Its Application to a Typhoon Event
Authors: Liu Jin-Qing , Li Zi-Liang , Wang Qiong-Qun
Published: October 2021

This present study aims to explore how forecasters can quickly make accurate predictions by using various high-resolution model forecasts. Based on three high temporal-spatial resolution (3 km, hourly) numerical weather prediction models (CMA-MESO, CMA-GD, CMA-SH3) from the China Meteorological Administration (CMA), the hourly precipitation characteristics of three model within 24 h from March to September 2020 are discussed and integrated into a single, hourly, deterministic quantitative precipitation forecast (QPF) by making use of an improved weighted moving average probability-matching method (WPM). The results are as follows: (1) In non-rainstorm forecasts, CMA-MESO and CMA-GD have similar forecast abilities. However, in rainstorm forecasts, CMA-MESO has a notable advantage over the other two models. Thus, CMA-MESO is selected as a critical factor when participating in sensitivity experiments. (2) Compared with the traditional equal-weight probability-matching method (PM), the WPM improves the different grade QPF because it can effectively reduce rainfall pattern bias by making use of the weighted moving average (WMA). Additionally, the WPM threat score in rainstorm forecast similarly improved from 0.051 to 0.056, with a 9.8% increase relative to the PM. (3) The sensitivity experiments show that an optimal rainfall intensity score (WPM-best) can further improve the QPF and overcome all single models in both rainstorm and non-rainstorm forecasts, and the WPM-best has a rainstorm threat score skill of 0.062, with an increase of 21.6% compared with the PM. The performance of the WPM-best will be better if the precipitation intensity is stronger and the valid forecast periods is longer. It should be noted that there is no need to select models before using the WPM-best method, because WPM-best can give a very low weight to the less-skillful model in a more objective way. (4) The improved WPM method is also applied to investigate the heavy-rainfall case induced by typhoon Mekkhala (2020), where the improved WPM technique significantly improves rainstorm forecasting ability compared with a single model.
Forecasting Economic Growth of the Group of Seven via Fractional-Order Gradient Descent Approach
Authors: Wang Xiaoling , Fečkan Michal , Wang JinRong
Published: October 2021

This paper establishes a model of economic growth for all the G7 countries from 1973 to 2016, in which the gross domestic product (GDP) is related to land area, arable land, population, school attendance, gross capital formation, exports of goods and services, general government, final consumer spending and broad money. The fractional-order gradient descent and integer-order gradient descent are used to estimate the model parameters to fit the GDP and forecast GDP from 2017 to 2019. The results show that the convergence rate of the fractional-order gradient descent is faster and has a better fitting accuracy and prediction effect.
Regulation of Milk Protein Synthesis by Free and Peptide-Bound Amino Acids in Dairy Cows
Authors: Zhou Miaomiao , Xu Lianbin , Zhao Fengqi , Liu Hongyun
Published: October 2021

Milk protein (MP) synthesis in the mammary gland of dairy cows is a complex biological process. As the substrates for protein synthesis, amino acids (AAs) are the most important nutrients for milk synthesis. Free AAs (FAAs) are the main precursors of MP synthesis, and their supplies are supplemented by peptide-bound AAs (PBAAs) in the blood. Utilization of AAs in the mammary gland of dairy cows has attracted the great interest of researchers because of the goal of increasing MP yield. Supplying sufficient and balanced AAs is critical to improve MP concentration and yield in dairy cows. Great progress has been made in understanding limiting AAs and their requirements for MP synthesis in dairy cows. This review focuses on the effects of FAA and PBAA supply on MP synthesis and their underlying mechanisms. Advances in our knowledge in the field can help us to develop more accurate models to predict dietary protein requirements for dairy cows MP synthesis, which will ultimately improve the nitrogen utilization efficiency and lactation performance of dairy cows.
Antiviral Function of NKEF against VHSV in Rainbow Trout
Authors: Chico Veronica , Salvador-Mira Maria Elizabhet , Nombela Ivan , Puente-Marin Sara , Perez Luis , Mercado Luis , Ortega-Villaizan Maria del Mar
Published: October 2021

Natural killer enhancing factor (NKEF) belongs to the peroxiredoxin family of proteins, a group of antioxidants that has been extensively studied in mammals. Recently, we identified NKEF in the immunoprecipitated proteome of rainbow trout red blood cells (RBCs) exposed to viral hemorrhagic septicemia virus (VHSV). In the present study, we evaluated the role of NKEF in the antiviral response of rainbow trout against VHSV by examining the expression profile of NKEF in VHSV-exposed RBCs and rainbow trout gonad-2 (RTG-2) cell line. We found an in vitro correlation between decreased VHSV replication and increased NKEF expression after RBCs were exposed to VHSV, however this was not found in RTG-2 cells where the infection highly increased and nkef transcripts remained almost unchanged. In addition, siRNA silencing of the nkef gene in rainbow trout RBCs and RTG-2 cells resulted in increased VHSV replication. We also found a correlation between nkef gene silencing and a decrease in the expression of genes related to type 1 interferon (IFN1) pathway. These findings indicated that NKEF is involved in the antiviral mechanisms of rainbow trout RBCs against VHSV and thus support its antiviral role and implication in the modulation of their immune response. Finally, overexpression of NKEF in an EPC cell line significantly reduced VHSV infectivity and was coupled to an increment in IFN1-related genes. In conclusion, NKEF may be a potential target for new therapeutic strategies against viral infections.
Cyclic Dipeptides: The Biological and Structural Landscape with Special Focus on the Anti-Cancer Proline-Based Scaffold
Authors: Bojarska Joanna , Mieczkowski Adam , Ziora Zyta M. , Skwarczynski Mariusz , Toth Istvan , Shalash Ahmed O. , Parang Keykavous , El-Mowafi Shaima A. , Mohammed Eman H. M. , Elnagdy Sherif , AlKhazindar Maha , Wolf Wojciech M.
Published: October 2021

Cyclic dipeptides, also know as diketopiperazines (DKP), the simplest cyclic forms of peptides widespread in nature, are unsurpassed in their structural and bio-functional diversity. DKPs, especially those containing proline, due to their unique features such as, inter alia, extra-rigid conformation, high resistance to enzyme degradation, increased cell permeability, and expandable ability to bind a diverse of targets with better affinity, have emerged in the last years as biologically pre-validated platforms for the drug discovery. Recent advances have revealed their enormous potential in the development of next-generation theranostics, smart delivery systems, and biomaterials. Here, we present an updated review on the biological and structural profile of these appealing biomolecules, with a particular emphasis on those with anticancer properties, since cancers are the main cause of death all over the world. Additionally, we provide a consideration on supramolecular structuring and synthons, based on the proline-based DKP privileged scaffold, for inspiration in the design of compound libraries in search of ideal ligands, innovative self-assembled nanomaterials, and bio-functional architectures.
Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed
Authors: Khan Shahid Ullah , Saeed Sumbul , Khan Muhammad Hafeez Ullah , Fan Chuchuan , Ahmar Sunny , Arriagada Osvin , Shahzad Raheel , Branca Ferdinando , Mora-Poblete Freddy
Published: October 2021

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.
The Interplay between Histamine H4 Receptor and the Kidney Function: The Lesson from H4 Receptor Knockout Mice
Authors: Verta Roberta , Gurrieri Maura , Borga Sara , Benetti Elisa , Pollicino Paolo , Cavalli Roberta , Thurmond Robin L. , Chazot Paul L. , Pini Alessandro , Rosa Arianna Carolina , Grange Cristina
Published: October 2021

Previous studies implicated the histamine H4 receptor in renal pathophysiology. The aim here is to elucidate the role of this receptor on renal function using H4 receptor knockout mice (H4R−/−). Healthy and diabetic H4R−/− mice compared to their C57BL/6J wild-type counterpart for renal function and the expression of crucial tubular proteins. H4R−/− and wild-type mice, matched for ages, showed comparable weight gain curves reaching similar median weight at the end of the study. However, H4R−/− mice displayed a higher basal glycemia. H4R−/− mice showed a lower urine 24 h outflow, and albumin-to-creatinine ratio (ACR) compared to wild-type mice. Consistently, H4R−/− mice presented a higher expression of megalin and a lower basal expression of the sodium-hydrogen exchanger (NHE)3 and aquaporin (AQP)2. According to these basal differences, diabetic H4R−/− mice developed more severe hyperglycemia and a higher 24 h urine volume, but a lower increase in ACR and decrease in urine pH were observed. These events were paralleled by a reduced NHE3 over-expression and megalin loss in diabetic H4R−/− mice. The AQP1 and AQP7 patterns were also different between H4R−/− and wild-type diabetic mice. The collected results highlight the role of the histamine H4 receptor in the control of renal reabsorption processes, particularly albumin uptake.
Hyaluronic Acid: A Key Ingredient in the Therapy of Inflammation
Authors: Marinho Andreia , Nunes Cláudia , Reis Salette
Published: October 2021

Hyaluronic acid (HA) is a natural polymer, produced endogenously by the human body, which has unique physicochemical and biological properties, exhibiting desirable biocompatibility and biodegradability. Therefore, it has been widely studied for possible applications in the area of inflammatory diseases. Although exogenous HA has been described as unable to restore or replace the properties and activities of endogenous HA, it can still provide satisfactory pain relief. This review aims to discuss the advances that have been achieved in the treatment of inflammatory diseases using hyaluronic acid as a key ingredient, essentially focusing on studies carried out between the years 2017 and 2021.
The Role of Indoleamine 2,3-Dioxygenase in Renal Tubular Epithelial Cells Senescence under Anoxia or Reoxygenation
Authors: Eleftheriadis Theodoros , Pissas Georgios , Filippidis Georgios , Liakopoulos Vassilios , Stefanidis Ioannis
Published: October 2021

Ischemia-reperfusion injury is the commonest form of acute kidney injury (AKI). Tubular epithelial cell senescence contributes to incomplete recovery from AKI and predisposes to subsequent chronic kidney disease. In cultures of primary proximal renal tubular epithelial cells (RPTECs) subjected to anoxia or reoxygenation, we evaluated the role of indoleamine 2,3-dioxygenase 1 (IDO) in cellular senescence. Proteins of interest were assessed with Western blotting or enzyme-linked immunosorbent assay or histochemically. Under anoxia or reoxygenation, IDO expression and activity were increased. Moreover, the two IDO-derived pathways, the general control nonderepressible 2 kinase (GCN2K) pathway and the aryl-hydrocarbon receptor (AhR) pathway, were also activated. A DNA damage response (DDR) took place and led to increased levels of the cell-cycle inhibitors p21 and p16, and senescence-associated β-galactosidase (SA-β-Gal) activity. Cell proliferation was inhibited, and more IL-6 was produced. The IDO inhibitor 1-DL-methyl-tryptophan ameliorated the DDR; decreased p21, p16, and SA-β-Gal activity; restored cell proliferation; and decreased IL-6 production. The AhR inhibitor CH223191 did not affect the above parameters. In conclusion, anoxia and the subsequent reoxygenation upregulate IDO. IDO depletes tryptophan and activates GCN2K. The latter enhances the anoxia- or reoxygenation-induced DDR, resulting in increased p21 and p16 expression and eventually leading to RPTEC senescence. Since cellular senescence affects AKI outcome, the role of IDO in cellular senescence and the possible therapeutic role of IDO inhibitors deserve further investigation.