bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Global Performance of the BDS-2 and BDS-3 Joint Real-Time Undifferenced and Uncombined Precise Point Positioning Using RTS Products from Different Analysis Centers
Authors: Wang Ahao , Zhang Yize , Chen Junping , Wang Hu , Luo Tianning , Gong Mingyou , Liu Quanpeng
Published: February 2024

Compared to the traditional ionospheric-free (IF) precise point positioning (PPP) model, the undifferenced and uncombined (UU) PPP has the advantages of lower observation noise and the ability to obtain ionospheric information. Thanks to the IGS (International GNSS Service), real-time service (RTS) can provide RT vertical total electron content (VTEC) products, and an enhanced RT UU-PPP based on the RT-VTEC constraints can be achieved. The global performance of the BeiDou Navigation Satellite System-2 (BDS-2) and BDS-3 joint RT UU-PPP using different RTS products was investigated. There is not much difference in the RTS orbit accuracy of medium earth orbit (MEO) satellites among all analysis centers (ACs), and the optimal orbit accuracy is better than 5, 9, and 7 cm in the radial, along-track, and cross-track directions, respectively. The orbit accuracy of inclined geosynchronous orbit (IGSO) satellites is worse than that of MEO satellites. Except for CAS of 0.46 ns, the RTS clock accuracy of MEO satellites for other ACs achieves 0.2–0.27 ns, and the corresponding accuracy is about 0.4 ns for IGSO satellites. In static positioning, due to the limited accuracy of RT-VTEC, the convergence time of the enhanced RT UU-PPP is longer than that of RT IF-PPP for most ACs and can be better than 25 and 20 min in the horizontal and vertical components, respectively. After convergence, the 3D positioning accuracy of the static RT UU-PPP is improved by no more than 8.7%, and the optimal horizontal and vertical positioning accuracy reaches 3.5 and 7.0 cm, respectively. As for the kinematic mode with poor convergence performance, with the introduction of RT-VTEC constraints, the convergence time of RT UU-PPP can be slightly shorter and reaches about 55 and 60 min in the horizontal and vertical components, respectively. Both the horizontal and vertical positioning accuracies of the kinematic RT UU-PPP can be improved and achieve around 7.5 and 10 cm, respectively.
Untrained Metamaterial-Based Coded Aperture Imaging Optimization Model Based on Modified U-Net
Authors: Cheng Yunhan , Luo Chenggao , Zhang Heng , Liang Chuanying , Wang Hongqiang , Yang Qi
Published: February 2024

Metamaterial-based coded aperture imaging (MCAI) is a forward-looking radar imaging technique based on wavefront modulation. The scattering coefficients of the target can resolve as an ill-posed inverse problem. Data-based deep-learning methods provide an efficient, but expensive, way for target reconstruction. To address the difficulty in collecting paired training data, an untrained deep radar-echo-prior-based MCAI (DMCAI) optimization model is proposed. DMCAI combines the MCAI model with a modified U-Net for predicting radar echo. A joint loss function based on deep-radar echo prior and total variation is utilized to optimize network weights through back-propagation. A target reconstruction strategy by alternatively using the imaginary and real part of the radar echo signal (STAIR) is proposed to solve the DMCAI. It makes the target reconstruction task turn into an estimation from an input image by the U-Net. Then, the optimized weights serve as a parametrization that bridges the input image and the target. The simulation and experimental results demonstrate the effectiveness of the proposed approach under different SNRs or compression measurements.
HATF: Multi-Modal Feature Learning for Infrared and Visible Image Fusion via Hybrid Attention Transformer
Authors: Liu Xiangzeng , Wang Ziyao , Gao Haojie , Li Xiang , Wang Lei , Miao Qiguang
Published: February 2024

Current CNN-based methods for infrared and visible image fusion are limited by the low discrimination of extracted structural features, the adoption of uniform loss functions, and the lack of inter-modal feature interaction, which make it difficult to obtain optimal fusion results. To alleviate the above problems, a framework for multimodal feature learning fusion using a cross-attention Transformer is proposed. To extract rich structural features at different scales, residual U-Nets with mixed receptive fields are adopted to capture salient object information at various granularities. Then, a hybrid attention fusion strategy is employed to integrate the complementing information from the input images. Finally, adaptive loss functions are designed to achieve optimal fusion results for different modal features. The fusion framework proposed in this study is thoroughly evaluated using the TNO, FLIR, and LLVIP datasets, encompassing diverse scenes and varying illumination conditions. In the comparative experiments, HATF achieved competitive results on three datasets, with EN, SD, MI, and SSIM metrics reaching the best performance on the TNO dataset, surpassing the second-best method by 2.3%, 18.8%, 4.2%, and 2.2%, respectively. These results validate the effectiveness of the proposed method in terms of both robustness and image fusion quality compared to several popular methods.
The Extreme Rainfall Events of the 2020 Typhoon Season in Vietnam as Seen by Seven Different Precipitation Products
Authors: Roversi Giacomo , Pancaldi Marco , Cossich William , Corradini Daniele , Nguyen Thanh Thi Nhat , Nguyen Thu Vinh , Porcu’ Federico
Published: February 2024

A series of typhoons and tropical storms have produced extreme precipitation events in Vietnam during the first part of the 2020 monsoon season: events of this magnitude pose significant challenges to remote sensing Quantitative Precipitation Estimation (QPE) techniques. The weather-monitoring needs of modern human activities require that these challenges be overcome. In order to address this issue, in this work, seven precipitation products were validated with high spatial and temporal detail against over 1200 rain gauges in Vietnam during six case studies tailored around the most intense events of 2020. The data sources included the Vietnamese weather radar network, IMERG Early run and Final run, the South Korean GEO-KOMPSAT-2A and Chinese FengYun-4A geostationary satellites, DPR on board the GPM-Core Observatory, and European ERA5-Land reanalysis. All products were resampled to a standardized 0.02° grid and compared at hourly scale with ground stations measurements. The results indicated that the radars product was the most capable of reproducing the information collected by the rain gauges during the selected extreme events, with a correlation coefficient of 0.70 and a coefficient of variation of 1.38. However, it exhibited some underestimation, approximately 30%, in both occurrence and intensity. Conversely, geostationary products tended to overestimate moderate rain rates (FY-4A) and areas with low precipitation (GK-2A). More complex products such as ERA5-Land and IMERG failed to capture the highest intensities typical of extreme events, while GPM-DPR showed promising results in detecting the highest rain rates, but its capability to observe isolated events was limited by its intermittent coverage.
Charging Process in Dusty Plasma of Large-Size Dust Particles
Authors: Yue Dong , Li Ke , Guo Lixin , Li Jiangting , Zheng Yan
Published: February 2024

During reentry, the high temperatures experienced by near-space hypersonic vehicles result in surface ablation, generating ablative particles. These particles become part of a plasma, commonly referred to as a “dusty plasma sheath” in radar remote sensing. The dusty plasma model, integral in radar studies, involves extensive charge and dynamic interactions among dust particles. Previous derivations assumed that the dust particle radius significantly surpassed the Debye radius, leading to the neglect of dust radius effects. This study, however, explores scenarios where the dust particle radius is not markedly smaller than the Debye radius, thereby deducing the charging process of dusty plasma. The derived equations encompass the Debye radius, charging process, surface potential, and charging frequency, particularly considering larger dust particle radii. Comparative analysis of the dusty plasma model, both before and after modification, reveals improvements when dust particles approach or exceed the Debye length. In essence, our study provides essential equations for understanding dusty plasma under realistic conditions, offering potential advancements in predicting electromagnetic properties and behaviors, especially in scenarios where dust particles closely align with or surpass the Debye radius.
The GM-JMNS-CPHD Filtering Algorithm for Nonlinear Systems Based on a Generalized Covariance Intersection
Authors: Xu Zhixuan , Wei Yu , Qin Xiaobao , Guo Pengfei
Published: February 2024

Some fusion criteria in multisensor and multitarget motion tracking cannot be directly applied to nonlinear motion models, as the fusion accuracy applied in nonlinear systems is relatively low. In response to the above issue, this study proposes a distributed Gaussian mixture cardinality jumping Markov-cardinalized probability hypothesis density (GM-JMNS-CPHD) filter based on a generalized inverse covariance intersection. The state estimation of the JMNS-CPHD filter combines the state evaluation of traditional CPHD filters with the state estimation of jump Markov systems, estimating the target state of multiple motion models without knowing the current motion models. The performances of the generalized covariance intersection (GCI)GCI-GM-JMNS-CPHD and generalized inverse covariance intersection (GICI)GICI-GM-JMNS-CPHD methods are evaluated via simulation results. The simulation results show that, compared with algorithms such as Sensor1, Sensor2, GCI-GM-CPHD, and GICI-GM-CPHD, this algorithm has smaller optimal subpattern assignment (OSPA) errors and a higher fusion accuracy.
Which Technologies Make Australian Farm Machinery Safer? A Decision Support Tool for Agricultural Safety Effectiveness
Authors: Latham Amity , Najdovski Zoran , Bartel Rebecca , Cotton Jacqueline
Published: February 2024

This project combined systems engineers, farm safety researchers, work health and safety inspectorate and policymakers with the aim of designing a way in which to reduce fatal farm injury caused by run-overs and roll-overs by tractors and side-by-side vehicles. The team made comparisons between farm machinery and powered mobile plant that is used in the industrial manufacturing, warehousing and logistics, mining, and construction sectors. Current and emerging safety technologies and engineering solutions were collated. Safety standards, legislated engineering controls, retrofit designs, and known ways in which farmers’ workaround safety features were considered. These elements were used as criteria to propose a way to resolve which safety technologies or engineering controls should be recommended for aftermarket retrofitting or incorporated at the original equipment manufacturer design stage. The concept of measuring safety effectiveness to prevent fatal farm injury emerged. This developed into a score sheet and a corresponding matrix to highlight engineering strength and industry acceptance. The project resulted in the conceptual design of the agricultural safety effectiveness score (ASES). The next phase is a multi-stakeholder validation process and a protocol for the scoring system. It requires a hypothesis to test the theory that when safety technologies and engineering solutions are mature in other industries or if they are associated with agricultural productivity gains, their adoption into the agricultural sector is more likely, which in turn will reduce the incidence of tractor and side-by-side run-overs and roll-overs on farms.
Flexural Performance of Steel-Continuous-Fiber Composite Bar and Fiber-Reinforced Polymer Bar Hybrid-Reinforced Sustainable Sea-Sand Concrete Beams: Numerical and Theoretical Study
Authors: Wang Anlian , Zhang Zhiwen , Liu Yan
Published: February 2024

To investigate the flexural performance of steel-continuous-fiber composite bar (SFCB) and fiber-reinforced polymer (FRP) bar hybrid-reinforced sea-sand concrete (SSC) beams, a total of 21 SSC beams were numerically studied. The concrete damaged plasticity model (CDPM) and FRP brittle damage model were adopted, and the bond-slip behavior between the reinforcement and concrete was considered. Parametric studies were conducted to study the effects of the SSC strength, sectional steel ratio of the SFCB, core steel bar yield strength of the SFCB, out-wrapped FRP elastic modulus of the SFCB, and the ultimate tensile strength of the SFCB on the flexural performance of the beams. The results indicate that increasing the SSC strength and out-wrapped FRP modulus enhanced the bearing capacity and stiffness but reduced the ductility, shifting failure from concrete crushing to FRP bar fracture. A higher SFCB sectional steel ratio markedly improved the flexural stiffness, transforming the load–deflection curve. Elevated core steel bar yield strength maintained the cracking load and deflection while increasing the yield and ultimate loads. For SFCB fracture, higher ultimate tensile strength in the out-wrapped FRP enhanced the ultimate load and deflection, but not in concrete crushing failure. In addition, three failure modes were defined based on the proper assumption, with the proposed bearing capacity formulas aligning well with the FE results.
Assessment of Ecotourism Environmental Carrying Capacity in the Qilian Mountains, Northwest China
Authors: Du Qinqin , Guan Qingyu , Sun Yunfan , Wang Qingzheng
Published: February 2024

Ecotourism is the main trend of global tourism development, and evaluating the ecotourism environmental carrying capacity (EECC) of ecologically fragile areas can provide a scientific basis for the sustainable development of regional tourism. This study uses the typical fragile mountain area, the Qilian Mountains (QLMs), as an example and analyzes the spatial and temporal changes in EECC by constructing an evaluation indicator system of EECC, which is based on the framework of “natural ecological environment support—socio-economic pressure—tourism activity pressure”. In the results, it is found that the natural ecological environment support, socio-economic pressure, and tourism activity pressure in the QLMs all present a spatial distribution pattern of higher in the southeast and lower in the northwest. From a temporal perspective, most of the indicators of different subsystems show an increasing trend. The whole area of EECC in the QLMs shows an increasing trend in 85.4% of the region, while the EECC in some areas in the southeastern and northern parts shows a decreasing trend. Comparing different time periods, it is found that the EECC in the whole region shows an increasing trend from 2000 to 2010, while the proportion of areas with a decreasing trend in EECC from 2010 to 2018 reaches 67.1%. The research results can provide a scientific basis for the sustainable development of ecotourism in the QLMs and other similar regions in the world, and they further contribute to the protection of the ecological environment.
Optimizing the Benefits of Invasive Alien Plants Biomass in South Africa
Authors: Rawat Yashwant S. , Singh G. S. , Tekleyohannes Anteneh T.
Published: February 2024

The current political situation in South Africa is seeking opportunities to promote sustainable development and use of renewable resources for energy, poverty alleviation, economic development, and environmental protection (e.g., mitigation of greenhouse gas emissions). The present study is based on a critical literature review and synthesis of policy advice in South Africa. The study comprehensively examined the knowledge base and gathered relevant empirical findings and perspectives so as to identify the gaps, trends, and patterns in the optimal management and utilization of invasive alien plants (IAPs) biomass, thereby supporting evidence-based practice. Additionally, the literature review was supported by the first-hand experience of invasive alien plants management and its biomass utilization. This research proposes long-term options for optimizing the costs and benefits of invasive alien plants biomass and meeting rising energy demand. Biomass from the country’s approximately 300 “Working for Water (WfW) Projects” might be used for bioenergy, firewood, charcoal, and other value-added forest products, both for internal and international use. The extraction and use of biomass from invasive alien plants for green energy and other valuable products would aid in the elimination of hazardous invasive species and reduce the amount of fuel in the fields, as well as fire and flood threats. Biomass from invasive alien plants clearings can be distributed to rural regions and informal settlements as a supply of firewood with the aim of reducing reliance on nearby forests, conserving the environment and biodiversity, minimizing forest degradation, supporting climate change, and enhancing energy efficiency and wood waste management (e.g., recycling and prevention) for green economic development and industrial transformation. The findings of this study imply that for competitive biomass-to-energy conversion and bio-economic applications for the use of invasive alien plant biomass, cost management, particularly for transportation, and significant regulatory incentives are essential. In addition, effective policy instruments that aid in the promotion of innovative systems and knowledge generation are required so that biomass can be optimally used for bioenergy and other competitive bio-economic applications.
A Machine Learning Approach to Predict Relative Residual Strengths of Recycled Aggregate Concrete after Exposure to High Temperatures
Authors: Abed Mohammed , Mehryaar Ehsan
Published: February 2024

In recent years, there has been a heightened focus among researchers and policymakers on assessing the environmental impact and sustainability of human activities. In this context, the reutilization of construction materials, particularly recycled aggregate concrete, has emerged as an environmentally friendly choice in construction projects, gaining significant traction. This study addresses the critical need to investigate the mechanical properties of recycled aggregate concrete under diverse extreme scenarios. Conducting an extensive literature review, key findings were synthesized on the relative residual strength of recycled aggregate concrete following exposure to high temperatures. Leveraging these insights, innovative hybrid machine learning models were developed, offering practical equations and model trees for predicting the relative residual compressive strength, flexural strength, elasticity modulus, and splitting tensile strength of recycled aggregate concrete post high temperature exposure. Uncertainty analysis was performed on each model to assess the reliability, while sensitivity analysis was performed to find out the significance of each input variable for each predictive model. This paper presents interpretable models achieving high levels of performance, with R2 values of 0.91, 0.94, 0.9, and 0.96 for predicting the relative residual compressive strength, flexural strength, modulus of elasticity, and splitting tensile strength of RCA concrete exposed to high temperatures, respectively. The unique contribution of the paper lies in the provision of easily applicable equations and model trees, enhancing accessibility for practitioners seeking to estimate mechanical properties of recycled aggregate concrete. Notably, our hybrid machine learning models stand out for their user-friendly nature compared with conventional ML algorithms, without compromising on accuracy. This paper not only advances our understanding of sustainable construction practices but also equips industry professionals with efficient tools for practical implementation.
Research on Microclimate Performance Simulation Application and Scheme Optimization in Traditional Neighborhood Renewal—A Case Study of Donghuali District, Foshan City
Authors: Zheng Jian , Zhang Haitao , Liu Zhonghui , Zheng Bohong
Published: February 2024

With global warming and rapid urbanization, the microclimate in the Lingnan region is prone to health problems, such as pyrexia and infectious diseases, and the average annual number of heatwave-related deaths is rising rapidly. The large-scale regeneration of traditional neighborhoods in Lingnan under high-quality development is underway, which has implications for the thermal comfort of microclimatic environments. This study focused on the impact of different building unit types and spatial patterns on thermal comfort in the Donghuali traditional neighborhood of Foshan City as an example. We extracted eight basic morphological units and designed a prototype block of 400 m × 400 m. In the Rhinoceros & Grasshopper parametric software 6.7, a variety of plug-ins were integrated to establish a platform with parametric modeling, microclimate simulation and evaluation, and optimal design for thermal comfort. Through experiments, the effects of new single-type and new composite building units on thermal comfort were investigated, and the correlation equations between spatial morphology and microclimate comfort in Lingnan traditional neighborhoods were established. Finally, the multi-objective genetic optimization of thermal comfort was carried out as an example of real block renewal, which provides a practical reference for the planning and design of traditional blocks.
Exploring Sustainability Concerns and Ecosystem Services: The Role of the New Ecological Paradigm Scale in Understanding Public Opinion
Authors: Tonin Stefania , Benedetto Diego
Published: February 2024

This study mainly explores people’s environmental attitudes and perceptions and their motivations for protecting and improving ecosystem services in Italy. The environmental perceptions of people were explored through the New Ecological Paradigm (NEP) scale, a tool for gauging environmental consciousness and perceptions, especially in the context of ecological sustainability. Data were collected from a sample of more than 1500 respondents residing in Italy using computer-assisted web interviewing (CAWI). The results showed that respondents have a high level of environmental concern for most scale issues. The application of principal component analysis (PCA) to the respondents’ responses revealed the multidimensionality of the NEP scale: anti-anthropocentrism (pro-NEP items), human domination (pro-dominant social paradigm (DSP) items), and limits of nature. The results also showed that socio-demographic characteristics and people’s knowledge and beliefs are associated with a strong concern for nature, which can support ecosystem service conservation. Different cultural backgrounds may place varying emphasis on sustainability, conservation, or economic development.
The Cobalt Supply Chain and Environmental Life Cycle Impacts of Lithium-Ion Battery Energy Storage Systems
Authors: Das Jani , Kleiman Andrew , Rehman Atta Ur , Verma Rahul , Young Michael H.
Published: February 2024

Lithium-ion batteries (LIBs) deployed in battery energy storage systems (BESS) can reduce the carbon intensity of the electricity-generating sector and improve environmental sustainability. The aim of this study is to use life cycle assessment (LCA) modeling, using data from peer-reviewed literature and public and private sources, to quantify environmental impacts along the supply chain for cobalt, a crucial component in many types of LIBs. The study seeks to understand where in the life cycle stage the environmental impacts are highest, thus highlighting actions that can be taken to improve sustainability of the LIB supply chain. The system boundary for this LCA is cradle-to-gate. Impact assessment follows ReCiPe Midpoint (H) 2016. We assume a 30-year modeling period, with augmentation occurring at the end of the 3rd, 7th, and 14th years of operations, before a complete replacement in the 21st year. Three refinery locations (China, Canada, and Finland), a range of ore grades, and five battery chemistries (NMC111, NMC532, NMC622, NMC811, and NCA) are used in scenarios to better estimate their effect on the life cycle impacts. Insights from the study are that impacts along nearly all pathways increase according to an inverse power-law relationship with ore grade; refining outside of China can reduce global warming potential (GWP) by over 12%; and GWP impacts for cobalt used in NCA and other NMC battery chemistries are 63% and 45–74% lower than in NMC111, respectively. When analyzed on a single-score basis, marine and freshwater ecotoxicity are prominent. For an ore grade of 0.3%, the GWP values for the Canada route decrease at a rate of 58% to 65%, and those for Finland route decrease by 71% to 76% from the base case. Statistical analysis shows that cobalt content in the battery is the highest predictor (R2 = 0.988), followed by the ore grade (R2 = 0.966) and refining location (R2 = 0.766), when assessed for correlation individually. The results presented here point to areas where environmental burdens of LIBs can be reduced, and thus they are helpful to policy and investment decision makers.
A Review of the Factors Influencing Surface Roughness in Machining and Their Impact on Sustainability
Authors: Abellán-Nebot José V. , Vila Pastor Carlos , Siller Hector R.
Published: February 2024

Understanding surface roughness generation in machining is critical to estimate the final quality of the part, optimize cutting conditions, reduce costs and improve manufacturing sustainability in industry. This work presents a review of the factors that affect surface roughness generation in machining (turning/milling) processes. Up to twenty-five different factors were identified, which were classified as setup factors (cutting tool, machine tool/fixturing and workpiece factors), operational factors (cutting and process parameters) and processing factors, which are related to the resulting cutting processes, such as built-up edge, chatter or tool wear. The importance of understanding these factors to improve machining sustainability is highlighted through three case studies, ranging from a simple change in the cutting insert to a more complex case where a controlled surface roughness leads to the elimination of a grinding stage. A case study illustrating the potential benefit of MQL in the sustainability of the machining process is also reported from the mold manufacturing industry. In all of the cases, the improvement in sustainability in terms of the reduction in kg of CO2 equivalent is notable, especially when grinding operations are reduced or eliminated from the manufacturing process. This paper can be of interest to practitioners in finishing operations at milling and turning operations that want to increase machining sustainability through a deep understanding of surface roughness generation.
The Remaining Useful Life Forecasting Method of Energy Storage Batteries Using Empirical Mode Decomposition to Correct the Forecasting Error of the Long Short-Term Memory Model
Authors: Yan Tao , Chen Jizhong , Hui Dong , Li Xiangjun , Zhang Delong
Published: February 2024

Energy storage has a flexible regulatory effect, which is important for improving the consumption of new energy and sustainable development. The remaining useful life (RUL) forecasting of energy storage batteries is of significance for improving the economic benefit and safety of energy storage power stations. However, the low accuracy of the current RUL forecasting method remains a problem, especially the limited research on forecasting errors. In this paper, a method for forecasting the RUL of energy storage batteries using empirical mode decomposition (EMD) to correct long short-term memory (LSTM) forecasting errors is proposed. Firstly, the RUL forecasting model of energy storage batteries based on LSTM neural networks is constructed. The forecasting error of the LSTM model is obtained and compared with the real RUL. Secondly, the EMD method is used to decompose the forecasting error into many components. The time series of EMD components are forecasted by different LSTM models. The forecasting values of different time series are added to determine the corrected forecasting error and improve the forecasting accuracy. Finally, a simulation analysis shows that the proposed method can effectively improve the forecasting effect of the RUL of energy storage batteries.
Organic and Conventional Farmers’ Mental Health: A Preliminary Study on the Role of Social Psychological Mediators
Authors: David Lucas , Streith Michel , Michaud Audrey , Dambrun Michaël
Published: February 2024

The study of farmers’ mental health according to their production model (organic vs. conventional) suggests that organic farming was associated with better mental health than conventional farming. However, to our knowledge, no research has been conducted to examine the social psychological factors responsible for these differences. This research aims to investigate the role of job content and values on farmers’ mental health according to their production model. To this end, an online questionnaire study on these dimensions was conducted on a sample of farmers. The results revealed that organic farmers scored significantly lower in anxiety and higher in positive emotions than conventional farmers. Psychological demand and conformity value appeared to be the most important explanatory factors related to the effect of farmers’ production model on mental health. Implications for the response rate and farmers’ mental health were discussed.
Conditional Strong Law of Large Numbers under G-Expectations
Authors: Zhang Jiaqi , Tang Yanyan , Xiong Jie
Published: February 2024

In this paper, we investigate two types of the conditional strong law of large numbers with a new notion of conditionally independent random variables under G-expectation which are related to the symmetry G-function. Our limit theorem demonstrates that the cluster points of empirical averages fall within the bounds of the lower and upper conditional expectations with lower probability one. Moreover, for conditionally independent random variables with identical conditional distributions, we show the existence of two cluster points of empirical averages that correspond to the essential minimum and essential maximum expectations, respectively, with G-capacity one.
Overcoming Uncertainty in Novel Technologies: The Role of Venture Capital Syndication Networks in Artificial Intelligence (AI) Startup Investments in Korea and Japan
Authors: Hyun Eun-jung , Kim Brian Tae-Seok
Published: February 2024

This paper investigates how historical inter-firm syndication networks influence venture capitalists’ (VCs) propensity to invest in startups pursuing novel, uncertain technologies, with a focus on artificial intelligence (AI). We theorize that VCs’ positional attributes within cumulative syndication networks determine their access to external expertise and intelligence that aid AI investment decisions amidst informational opacity. Specifically, reachability to prior AI investors provides referrals and insights transmitted across short network paths to reduce ambiguity. Additionally, VC brokerage between disconnected industry clusters furnishes expansive, non-redundant information that is pivotal for discovering and assessing AI opportunities. Through hypotheses grounded in social network theory, we posit network-based mechanisms that equip VCs to navigate uncertainty when engaging with ambiguous innovations like AI. We test our framework, utilizing comprehensive historical records of global venture capital investments. Analyzing the location information of VC firms in this database, we uncovered a history of 14,751 investments made by Korean and Japanese firms. Using these data, we assembled an imbalanced panel dataset from 1984 to 2022 spanning 230 Korean and 413 Japanese VCs, with 4508 firm-year observations. Negative binomial regression analysis of this dataset reveals how historical relational patterns among venture capital firms foster readiness to evaluate unfamiliar innovations.
Mapping Acoustic Frictional Properties of Self-Lubricating Epoxy-Coated Bearing Steel with Acoustic Emissions during Friction Test
Authors: Krishnamoorthy Venkatasubramanian , Anitha John Ashvita , Bhaumik Shubrajit , Paleu Viorel
Published: February 2024

This work investigates the stick–slip phenomenon during sliding motion between solid lubricant-impregnated epoxy polymer-coated steel bars and AISI 52,100 steel balls. An acoustic sensor detected the stick–slip phenomenon during the tribo-pair interaction. The wear characteristics of the workpiece coated with different epoxy coatings were observed and scrutinized. The RMS values of the acoustic sensor were correlated with the frictional coefficient to develop a standard based on the acoustic sensor, leading to the detection of the stick–slip phenomenon. As per the findings, the acoustic waveform remained relatively similar to the friction coefficient observed during the study and can be used effectively in detecting the stick–slip phenomenon between steel and polymer interaction. This work will be highly beneficial in industrial and automotive applications with a significant interaction of polymer and steel surfaces.
Integrated Strategies for Aedes aegypti Control Applied to Individual Houses: An Approach to Mitigate Vectorial Arbovirus Transmission
Authors: Melo Danielle Cristina Tenório Varjal de , Santos Eloína Maria de Mendonça , Xavier Morgana Nascimento , Nascimento Josimara do , Barbosa Victor Araújo , Oliveira André Luiz de Sá , Meiado Marcos Vinícius , Melo-Santos Maria Alice Varjal de , Paiva Marcelo Henrique Santos , Wallau Gabriel da Luz , Oliveira Cláudia Maria Fontes de
Published: February 2024

Aedes aegypti and Culex quinquefasciatus mosquitoes are vectors of different arboviruses that cause a large burden of disease in humans worldwide. A key step towards reducing the impact of arboviruses on humans can be achieved through integrated mosquito surveillance and control approaches. We carried out an integrated approach of mosquito surveillance and control actions to reduce populations of these insects along with a viral surveillance in a neighborhood of Recife (Northeastern Brazil) with high mosquito densities and arbovirus transmission. The actions were carried out in 40 different houses in the Nova Descoberta neighborhood. The area was divided into two groups, the control group using tools to monitor the mosquito density (1 OVT; 1 Double BR-ovt; monthly capture of alates) and the experimental group with control actions using surveillance tools in an intensified way (2 OVTs; 2 Double BR-ovts; fortnightly capture of alates; toxic baits). We evaluated the study’s impact on the mosquito density via the Egg Density (ED) and Adult Density (AD) over a period of 12 cycles of 28 days each. The collected adult mosquitoes were processed via RT-qPCR for DENV, CHIKV and ZIKV and, subsequently, the Minimum Infection Rate (MIR) was calculated. After 12 cycles, we observed a 91% and 99% reduction in Aedes ED and AD in the monitored properties, as well as a 76% reduction in the AD of Cx. quinquefasciatus in the same properties. Moreover, we detected circulating arboviruses (DENV and ZIKV) in 19.52% of captured adult mosquitoes. We show that enhancing entomological surveillance tools can aid in the early detection of possible risk areas based on vector mosquito population numbers. Additionally, the detection of important arboviruses such as ZIKV and DENV raises awareness and allows for a better selection of risk areas and silent virus spread. It offers supplementary information for guiding emergency mosquito control measures in the target area. The goal is to minimize human–vector interactions and, subsequently, to lower the risk of transmitting circulating arboviruses.
Characterizing Timing Noise in Normal Pulsars with the Nanshan Radio Telescope
Authors: Yuan Jianping , Wang Na , Dang Shijun , Li Lin , Kou Feifei , Yan Wenming , Wen Zhigang , Liu Zhiyong , Yuen Rai , Wang Jingbo , Zhou Zurong , Liu Peng , He Dalin
Published: February 2024

We present a decade of observations of pulse arrival times for 85 pulsars using the Nanshan radio telescope from July 2002 to March 2014. The Cholesky method can accurately estimate the covariance function of the timing residuals, significantly improving the parameter’s estimation accuracy when red noise is prominent. We utilize the Cholesky method to determine positions and basic timing parameters of these pulsars, as well as to obtain timing residuals. Most of these sources showed evidence of significant timing irregularities, which are described. The spectral analyses of timing residuals are presented for pulsars showing obvious red noise. Our results show that timing residuals in half of these pulsars are attributed to rotational irregularities. The red noise in normal pulsars may originate from a random walk in spin frequency or spin-down rate.
Properties of the Top Quark
Authors: Jung Andreas
Published: February 2024

Recent measurements of the properties of the top quark at the CERN Large Hadron Collider are discussed. The results were measured for single and top quark pair production in their final states, including jets with either one or two leptons or only in hadronic final states. Top quark properties include angular correlations, top quark spin correlations, mass, and width. When looking towards the future, top quark properties open new and even interdisciplinary avenues for probing quantum information science.
Promoting Vaccinations in Pregnancy: Results of a Systematic Literature Review of Italian Initiatives
Authors: Properzi Sara , Sepioni Maria Stella , Carestia Roberta , Cervelli Giulia , de Waure Chiara
Published: February 2024

Pregnant women and infants inherently face heightened susceptibility to complications resulting from infectious diseases. Within these populations, vaccinations offer numerous advantages. This systematic review endeavors to comprehensively analyze the existing literature concerning interventions designed to promote vaccinations among pregnant women and newborns in Italy. We searched PubMed, Scopus, and Web of Science for primary studies published until 3 August 2023 which assessed the impact of vaccination education interventions targeting pregnant Italian women. Data extraction, pooling, and a quality appraisal of the included studies were conducted according to PRISMA guidelines. Among the 528 articles identified, 3 met the inclusion criteria and focused on pregnant women aged 25 to 40 attending pre-delivery courses. In these studies, the effectiveness of the interventions was assessed using pre- and post-intervention questionnaires that investigated knowledge, attitudes, and behaviors regarding recommended vaccinations. The results reveal significant increases in intention and adherence to vaccination among participants after these interventions. The results underscore the positive influence of health professionals’ educational initiatives on pregnant Italian women’s vaccination knowledge and attitudes. However, longitudinal studies with larger representative samples are needed to validate these findings and identify potential avenues for improving maternal educational interventions.
Safety Monitoring of COVID-19 Vaccines in Persons with Prior SARS-CoV-2 Infection: A European Multi-Country Study
Authors: Ciccimarra Francesco , Luxi Nicoletta , Bellitto Chiara , L’Abbate Luca , Raethke Monika , van Hunsel Florence , Lieber Thomas , Mulder Erik , Riefolo Fabio , Dureau-Pournin Caroline , Farcas Andreea , Batel Marques Francisco , Morton Kathryn , Roy Debabrata , Sonderlichová Simona , Thurin Nicolas H. , Villalobos Felipe , Sturkenboom Miriam C. , Trifirò Gianluca
Published: February 2024

In all pivotal trials of COVID-19 vaccines, the history of previous SARS-CoV-2 infection was mentioned as one of the main exclusion criteria. In the absence of clinical trials, observational studies are the primary source for evidence generation. This study aims to describe the patient-reported adverse drug reactions (ADRs) following the first COVID-19 vaccination cycle, as well as the administration of booster doses of different vaccine brands, in people with prior SARS-CoV-2 infection, as compared to prior infection-free matched cohorts of vaccinees. A web-based prospective study was conducted collecting vaccinee-reported outcomes through electronic questionnaires from eleven European countries in the period February 2021–February 2023. A baseline questionnaire and up to six follow-up questionnaires collected data on the vaccinee’s characteristics, as well as solicited and unsolicited adverse reactions. Overall, 3886 and 902 vaccinees with prior SARS-CoV-2 infection and having received the first dose or a booster dose, respectively, were included in the analysis. After the first dose or booster dose, vaccinees with prior SARS-CoV-2 infection reported at least one ADR at a higher frequency than those matched without prior infection (3470 [89.6%] vs. 2916 [75.3%], and 614 [68.2%] vs. 546 [60.6%], respectively). On the contrary side, after the second dose, vaccinees with a history of SARS-CoV-2 infection reported at least one ADR at a lower frequency, compared to matched controls (1443 [85.0%] vs. 1543 [90.9%]). The median time to onset and the median time to recovery were similar across all doses and cohorts. The frequency of adverse reactions was higher in individuals with prior SARS-CoV-2 infection who received Vaxzevria as the first dose and Spikevax as the second and booster doses. The frequency of serious ADRs was low for all doses and cohorts. Data from this large-scale prospective study of COVID-19 vaccinees could be used to inform people as to the likelihood of adverse effects based on their history of SARS-CoV-2 infection, age, sex, and the type of vaccine administered. In line with pivotal trials, the safety profile of COVID-19 vaccines was also confirmed in people with prior SARS-CoV-2 infection.
An Overview of the Efficiency of Roundabouts: Design Aspects and Contribution toward Safer Vehicle Movement
Authors: Gkyrtis Konstantinos , Kokkalis Alexandros
Published: February 2024

Transforming intersections into roundabouts has shown that a sufficient degree of road safety and traffic capacity can be achieved. Because of the lower speeds at the area of a roundabout, drivers tend to become more easily adaptive to any kind of conflict with the surrounding environment. Despite the contribution to safety, the design elements of roundabouts are not uniformly fixed on a worldwide scale because of different traffic volumes, vehicle dimensions, drivers’ attitude, etc. The present study provides a brief overview of the contribution of roundabouts to road safety and the interactions between safety and the design elements of roundabouts. In addition, discussion points about current challenges and prospects are elaborated, including findings from the environmental assessment of roundabouts; their use and performance on the era of autonomous vehicles that will dominate in the near future; as well as the role and importance of simulation studies towards the improvement of the design and operation of roundabouts in favor of safer vehicle movement. The criticality of roundabouts, in terms of their geometric design as well as the provided road safety, lies upon the fact that roundabouts are currently used for the conventional vehicle fleet, which will be gradually replaced by new vehicle technologies. Such an action will directly impact the criteria for road network design and/or redesign, thereby continuously fostering new research initiatives.
Extreme Flood Flow Routing for Panchet and Maithan Reservoirs of India Using Modified Puls Technique
Authors: Dasgupta Mayuree , Das Subhasish
Published: February 2024

An important aspect of economic considerations is the routing and safety of hydraulic storage facilities such as dams for extreme probable water flooding. The routing of dam reservoirs requires more attention for determining the magnitude of extreme probable flooding. Apparently, the type of structure, importance, and economic development of the surrounding area guide the routing criteria for choosing the extreme flood magnitude. The Maithan and Panchet Dams in India have faced several major floods with diversified magnitudes since 1978. The present study aims to estimate the storage and routing of extreme probable floodings for these two dams based on real-time flood data like inflow, outflow, and elevation for the extreme flood years of 1978, 2009, and 2014. Reservoir storages at different elevations are calculated from the initial storage volumes. For both reservoirs, discharge equations are derived and calculated at given elevations during extreme floods. The Modified Puls technique is used for routing extreme floods. At the end of each extreme flood in 1978, 2009, and 2014, the variation in outflow discharges at different elevations and flood hydrographs is predicted. Finally, estimated outflow discharges are compared with the actual outflow discharges for the given inflows during extreme floods. Using this approach, extreme floods that occurred in 1978 are predicted with less than 10% error. Outcomes from this study may help in the future planning and routing of flood-control detention facilities and in predicting the variation in outflow discharges at different elevations. Based on this work, alternative studies and regional drainage planning can also be carried out.
Effect of LULC Changes on Annual Water Yield in the Urban Section of the Chili River, Arequipa, Using the InVEST Model
Authors: Carrasco-Valencia Lorenzo , Vilca-Campana Karla , Iruri-Ramos Carla , Cárdenas-Pillco Berly , Ollero Alfredo , Chanove-Manrique Andrea
Published: February 2024

Arequipa is a semi-desert city located in southern Peru which depends on the Chili River as its only water source. During recent years, this city has increased its number of inhabitants significantly as a result of internal migratory flows and population growth. Because of this, the city has undergone a rapid urbanization process which has increased the urban areas near the river and caused the destruction of agricultural areas, as well as their native vegetation. This change in land use can be quantified through satellite image analysis across many years, but as noted, there are no studies on its impact on water yield (WY) in the urban section of the river. Now, by using the Integrated Valuation of Ecosystem Services and Compensation (InVEST) model, which allows the WY of the study area to be evaluated in millimeters and cubic meters by introducing a series of variables, such as precipitation, reference evapotranspiration and types of land use classes, among others, it is possible to determine that the WY from the study area was 1,743,414 m3 in 1984 and 1,323,792 m3 in 2022; the urban area is the type of land use with the highest increase with respect to its percentage contribution to the WY, going from 30.43% to 49.62% between 1984 and 2022, respectively. The increase in urban area mitigated the loss of total WY, explained by a higher percentage runoff rate, surface flow and drainage problems in the study area.