bluuebunny/crossref_metadata_2025 huggingface dataset:
Interpenetration Phenomena via Anion Template Effects in Fe(II) and Co(II) Coordination Networks with a Bis-(1,2,4-triazole) Ligand
Authors: Jordan Dustin N. , Straßburg Patrick G. , Woschko Dennis , Carrella Luca M. , Cuignet Laure P. , Eickmeier Katharina , Dronskowski Richard , Garcia Yann , Rentschler Eva , Janiak Christoph
Published: August 2023

Seven new coordination networks, [Fe(tbbt)3](BF4)2 (1), [Co(tbbt)3](BF4)2 (2), [Fe(tbbt)3](ClO4)2 (3), [Co(tbbt)3](ClO4)2 (4), [Fe(NCS)2(tbbt)2] (5), [Co(NCS)2(tbbt)2] (6), and [Fe(H2O)2(tbbt)2]Br2·2H2O (7), were synthesized with the linker 1,1’-(trans-2-butene-1,4-diyl)bis-1,2,4-triazole (tbbt) and structurally investigated. The structure of complexes 1–4 is composed of three interpenetrating, symmetry-related 3D networks. Each individual 3D network forms a primitive, nearly cubic lattice (pcu) with BF4– or ClO4– anions present in the interstitial spaces. The structure of compounds 5 and 6 is composed of two-dimensional sql layers, which are parallel to each other in the AB stacking type. These layers are interpenetrated by one-dimensional chains, both having the same formula unit, [M(NCS)2(tbbt)2] (M = Fe, Co). The structure of compound 7 consists of parallel, two-dimensional sql layers in the ABCD stacking type. The interpenetration in 1–6 is not controlled by π–π-interactions between the triazole rings or C=C bonds, as could have been expected, but by (triazole)C-H⋯F4B, C-H⋯O4Cl, and C-H⋯SCN anion hydrogen bonds, which suggests a template effect of the respective non-coordinated or coordinated anion for the interpenetration. In 7, the (triazole)C-H⋯Br anion interactions are supplemented by O-H⋯O and O-H⋯Br hydrogen bonds involving the aqua ligand and crystal water molecules. It is evident that the coordinated and non-coordinated anions play an essential role in the formation of the networks and guide the interpenetration. All iron(II) coordination networks are colorless, off-white to yellow-orange, and have the metal ions in the high-spin state down to 77 K. Compound 5 stays in the high spin state even at temperatures down to 10 K.
Mechanical and Thermal Characterization of Annealed Oriented PAN Nanofibers
Authors: Sanchaniya Jaymin Vrajlal , Lasenko Inga , Kanukuntala Sai Pavan , Smogor Hilary , Viluma-Gudmona Arta , Krasnikovs Andrejs , Tipans Igors , Gobins Valters
Published: August 2023

Polyacrylonitrile (PAN) nanofibers have extensive applications as filters in various fields, including air and water filtration, biofluid purification, and the removal of toxic compounds and hazardous pollutants from contaminated water. This research focuses on investigating the impacts of annealing on the mechanical and thermal characteristics of oriented PAN nanofibers produced through the electrospinning of a PAN solution. The nanofiber mats were subjected to annealing temperatures ranging from 70 °C to 350 °C and characterized using a tensile test machine, thermogravimetry, differential scanning calorimetry, and scanning electron microscopy (SEM). The study aimed to examine the tensile strength in the transverse and longitudinal directions, Young’s modulus, and glass transition temperatures of PAN nanofiber mats. The results indicate that, upon annealing, the diameter of the nanofibers decreased by approximately 20%, while the tensile strength increased in the longitudinal and transverse directions by 32% and 23%, respectively. Furthermore, the annealing temperature influenced the glass transition temperature of the nanofiber mats, which exhibited a 6% decrease at 280 °C, while the degradation temperature showed a slight increase of 3.5% at 280 °C. The findings contribute to a better understanding of the effects of annealing on PAN nanofiber mats, facilitating their potential for various filtration applications.
The Thermodynamic Characterizations of Hydrogen Production from Catalyst-Enhanced Steam Reforming of Bio-Oil over Granulated Blast Furnace Slag as Heat Carrier
Authors: Ding Zhijun , Liu Yang , Yao Xin , Xue Yuekai , Li Chenxiao , Li Zhihui , Wang Shuhuan , Wu Jianwei
Published: August 2023

To promote the efficiency of waste heat recovery from granulated blast furnace (BF) slag, a novel method of catalyst-enhanced steam reforming of bio-oil to recover heat from slag is proposed. CaO is utilized as a superior catalyst for the process of catalyst-enhanced steam reforming. The thermodynamic production of the catalyst-enhanced steam reforming of bio-oil in granulated BF slag is obtained using HSC 6.0 software. The optimal conditions are mainly assessed according to the hydrogen yield, hydrogen concentration and carbon production. Through the thermodynamic production and industrial application, the temperature of 608 °C, S/C of eight and pressure of 1 bar are found as the optimal conditions. At the optimal conditions, the hydrogen yield, hydrogen concentration and carbon production are 95.25%, 76.89% and 0.28 mol/kg, respectively. Taking the temperature of 625 °C, S/C of eight and pressure of 1 bar as an example, the catalyst could improve the hydrogen yield and hydrogen concentration from 93.99% and 70.31% to 95.15% and 76.49%, respectively. It is implied that utilizing the catalyst could promote the hydrogen yield and hydrogen concentration of steam reforming of bio-oil to recover waste heat from granulated BF slag. The mechanism of catalyst-enhanced steam reforming of bio-oil to recover waste heat from granulated BF slag is obtained to guide the subsequent industry application.
The Seasonal Variations Analysis of Permanent GNSS Station Time Series in the Central-East of Europe
Authors: Savchuk Stepan , Doskich Sofiia , Gołda Paweł , Rurak Adam
Published: August 2023

Observations from permanent GNSS stations are actively used for the research and monitoring of geodynamic processes. Today, with the use of modern scientific programs and IGS products, it is possible to determine GNSS station coordinates and velocities at the level of a few millimeters. However, the scientific community constantly faces the question of increasing the accuracy of coordinate definitions to obtain more reliable data in the study of geodynamic phenomena. One of the main sources of errors is systematic measurement errors. To date, the procedure for their removal is still incomplete and imperfect. Also, during the processing of long-term GNSS measurements, it was found that the coordinate time series, after the removal of trend effects, are also characterized by seasonal variations, mainly of annual and semi-annual periods. We estimated the daily coordinate time series of 10 permanent GNSS stations in the central-eastern part of Europe from 2001 to 2019 and calculated the seasonal variation coefficients for these stations. The average value of the coefficients for the annual cycle for the N, E, and H components is −0.7, −0.2, and −0.7 mm, and for the semi-annual cycle the average value is 0.3, 0.4, and −0.5 mm. The obtained coefficients are less than 1 mm, which is why it can be argued that there is no seasonal component in the coordinate time series or that it is so small that it is a problematic task to calculate it. This practical absence of a seasonal component in long-term time series of GNSS coordinates, in our opinion, is partly compensated by the use of modern models of mapping functions (such as VMF3) for zenith tropospheric delays instead of the empirical GMF. To test the obtained results, we calculated the coefficients of seasonal variations for the sub-network of GNSS stations included in the category of the best EPN stations—C0 and C1. The values of the coefficients for the stations of this network are also less than 1 mm, which confirms the previous statement about the absence of a seasonal component in the long-term time series of coordinates. We also checked the presence of seasonal changes in the time series using the well-known decomposition procedure, which showed that the seasonal component is not observed because the content does not exceed 10% for additive decomposition and 20% for multiplicative decomposition.
High-Throughput Effect-Directed Monitoring Platform for Specific Toxicity Quantification of Unknown Waters: Lead-Caused Cell Damage as a Model Using a DNA Hybrid Chain-Reaction-Induced AuNPs@aptamer Self-Assembly Assay
Authors: Xiao Jiaxuan , Yuan Kuijing , Tao Yu , Wang Yuhan , Yang Xiaofeng , Cui Jian , Wei Dali , Zhang Zhen
Published: August 2023

A high-throughput cell-based monitoring platform was fabricated to rapidly measure the specific toxicity of unknown waters, based on AuNPs@aptamer fluorescence bioassays. The aptamer is employed in the platform for capturing the toxicity indicator, wherein hybrid chain-reaction (HCR)-induced DNA functional gold nanoparticle (AuNPs) self-assembly was carried out for signal amplification, which is essential for sensitively measuring the sub-lethal effects caused by target compounds. Moreover, the excellent stability given by the synthesized DNA nanostructure provides mild conditions for the aptamer thus used to bind the analyte. Herein, ATP was treated as a toxicity indicator and verified using lead-caused cell damage as a model. Under optimized conditions, excellent performance for water sample measurement was observed, yielding satisfactory accuracy (recovery rate: 82.69–114.20%; CV, 2.57%–4.65%) and sensitivity (LOD, 0.26 µM) without sample pretreatment other than filtration, indicating the method’s simplicity, high efficiency, and reliability. Most importantly, this bioassay could be used as a universal platform to encourage its application in the rapid quantification of specific toxicity in varied sources of samples, ranging from drinking water to highly contaminated wastewater.
A Multi-Layer Feature Fusion Method for Few-Shot Image Classification
Authors: Gomes Jacó C. , Borges Lurdineide de A. B. , Borges Díbio L.
Published: August 2023

In image classification, few-shot learning deals with recognizing visual categories from a few tagged examples. The degree of expressiveness of the encoded features in this scenario is a crucial question that needs to be addressed in the models being trained. Recent approaches have achieved encouraging results in improving few-shot models in deep learning, but designing a competitive and simple architecture is challenging, especially considering its requirement in many practical applications. This work proposes an improved few-shot model based on a multi-layer feature fusion (FMLF) method. The presented approach includes extended feature extraction and fusion mechanisms in the Convolutional Neural Network (CNN) backbone, as well as an effective metric to compute the divergences in the end. In order to evaluate the proposed method, a challenging visual classification problem, maize crop insect classification with specific pests and beneficial categories, is addressed, serving both as a test of our model and as a means to propose a novel dataset. Experiments were carried out to compare the results with ResNet50, VGG16, and MobileNetv2, used as feature extraction backbones, and the FMLF method demonstrated higher accuracy with fewer parameters. The proposed FMLF method improved accuracy scores by up to 3.62% in one-shot and 2.82% in five-shot classification tasks compared to a traditional backbone, which uses only global image features.
Vehicle Localization Kalman Filtering for Traffic Light Advisor Application in Urban Scenarios
Authors: Vignarca Daniele , Arrigoni Stefano , Sabbioni Edoardo
Published: August 2023

The recent advancements in Intelligent Transportation Systems (ITS) have revealed significant potential for enhancing traffic management through Advanced Driver Assist Systems (ADASs), with benefits for both safety and environment. This research paper proposes a vehicle localization technique based on Kalman filtering, as accurate positioning of the ego-vehicle is essential for the proper functioning of the Traffic Light Advisor (TLA) system. The aim of the TLA is to calculate the most suitable speed to safely reach and pass the first traffic light in front of the vehicle and subsequently keep that velocity constant to overcome the following traffic light, thus allowing safer and more efficient driving practices, thereby reducing safety risks, and minimizing energy consumption. To overcome Global Positioning Systems (GPS) limitations encountered in urban scenarios, a multi-rate sensor fusion approach based on the Kalman filter with map matching and a simple kinematic one-dimensional model is proposed. The experimental results demonstrate an estimation error below 0.5 m on urban roads with GPS signal loss areas, making it suitable for TLA application. The experimental validation of the Traffic Light Advisor system confirmed the expected benefits with a 40% decrease in energy consumption compared to unassisted driving.
Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method
Authors: Lajmi Fatma , Mhamdi Lotfi , Abdelbaki Wiem , Dhouibi Hedi , Younes Khaled
Published: August 2023

The paper focuses on the importance of prompt and efficient process fault detection in contemporary manufacturing industries, where product quality and safety protocols are critical. The study compares the efficiencies of two techniques for process fault detection: Kernel Principal Component Analysis (KPCA) and the observer method. Both techniques are applied to observe water volume variation within a hydraulic system comprising three tanks. PCA is an unsupervised learning technique used for dimensionality reduction and pattern recognition. It is an extension of Principal Component Analysis (PCA) that utilizes kernel functions to transform data into higher-dimensional spaces, where it becomes easier to separate classes or identify patterns. In this paper, KPCA is applied to detect faults in the hydraulic system by analyzing the variation in water volume. The observer method originates from control theory and is utilized to estimate the internal states of a system based on its output measurements. It is commonly used in control systems to estimate the unmeasurable or hidden states of a system, which is crucial for ensuring proper control and fault detection. In this study, the observer method is applied to the hydraulic system to estimate the water volume variations within the three tanks. The paper presents a comparative study of these two techniques applied to the hydraulic system. The results show that both KPCA and the observer method perform similarly in detecting faults within the system. This similarity in performance highlights the efficacy of these techniques and their potential adaptability in various fault diagnosis scenarios within modern manufacturing processes.
Method for Denoising the Vibration Signal of Rotating Machinery through VMD and MODWPT
Authors: Zhou Xiaolong , Wang Xiangkun , Wang Haotian , Xing Zhongyuan , Yang Zhilun , Cao Linlin
Published: August 2023

The vibration signals from rotating machinery are constantly mixed with other noises during the acquisition process, which has a negative impact on the accuracy of signal feature extraction. For vibration signals from rotating machinery, the conventional linear filtering-based denoising method is ineffective. To address this issue, this paper suggests an enhanced signal denoising method based on maximum overlap discrete wavelet packet transform (MODWPT) and variational mode decomposition (VMD). VMD decomposes the vibration signal of rotating machinery to produce a set of intrinsic mode functions (IMFs). By computing the composite weighted entropy (CWE), the phantom IMF component is then removed. In the end, the sensitive component is obtained by computing the value of the degree of difference (DID) after the high-frequency noise component has been decomposed through MODWPT. The denoised signal reconstructs the signal’s intrinsic characteristics as well as the denoised high-frequency IMF component. This technique was used to analyze the simulated and real-world signals of gear faults and it was compared to wavelet threshold denoising (WTD), empirical mode decomposition reconstruction denoising (EMD-RD), and ensemble empirical mode decomposition wavelet threshold denoising (EEMD-WTD). The outcomes demonstrate that this method can accurately extract the signal feature information while filtering out the noise components in the signal.
ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders
Authors: Jayousi Sara , Martinelli Alessio , Lucattini Paolo , Mucchi Lorenzo
Published: August 2023

The applied behavior analysis (ABA) model emphasizes observable and measurable behaviors by carrying out decision making using experimental data (behavioral observation assessment strategies). In this framework, information and communication technology (ICT) becomes highly suitable for enhancing the efficiency and effectiveness of the methodology. This paper aims to delve into the potential of ICT in providing innovative solutions to support ABA applications. It focuses on how ICT can contribute to fostering social inclusion with respect to children with neurodevelopmental disorders. ICT offers advanced solutions for continuous and context-aware monitoring, as well as automatic real-time behavior assessments. Wireless sensor systems (wearable perceptual, biomedical, motion, location, and environmental sensors) facilitate real-time behavioral monitoring in various contexts, enabling the collection of behavior-related data that may not be readily evident in traditional observational studies. Moreover, the incorporation of artificial intelligence algorithms that are appropriately trained can further assist therapists throughout the different phases of ABA therapy. These algorithms can provide intervention guidelines and deliver an automatic behavioral analysis that is personalized to the child’s unique profile. By leveraging the power of ICT, ABA practitioners can benefit from cutting-edge technological advancements to optimize their therapeutic interventions and outcomes for children with neurodevelopmental disorders, ultimately contributing to their social inclusion and overall wellbeing.
Underwater Acoustic Signal Acquisition and Sensing Using a Ring Vector Sensor Communication Receiver: Theory and Experiments
Authors: Rashid Rami , Zhang Erjian , Abdi Ali
Published: August 2023

Signal acquisition and sensing in underwater systems and applications is typically a challenging issue due to the small signal strength within the background noise. Here, we present a ring vector sensor communication receiver that can significantly improve signal acquisition, by utilizing the underwater acoustic vector field components, compared to the scalar component. The vector sensor receiver is a multichannel receiver that measures particle velocities, which are vector components of the underwater acoustic field, in addition to the scalar field component. According to the combination of our measured experimental data with our signal acquisition performance analysis, the introduced ring vector sensor receiver exhibits higher signal acquisition probabilities for the vector components compared to the scalar component. This can be attributed to certain characteristics of the vector field components. Another advantage of this multichannel receiver is that combining all of its channels can further increase the signal acquisition and packet detection probability in underwater communication systems compared to a single-channel approach.
Faster Walking Speeds Require Greater Activity from the Primary Motor Cortex in Older Adults Compared to Younger Adults
Authors: Alcock Lisa , Vitório Rodrigo , Stuart Samuel , Rochester Lynn , Pantall Annette
Published: August 2023

Gait speed declines with age and slower walking speeds are associated with poor health outcomes. Understanding why we do not walk faster as we age, despite being able to, has implications for rehabilitation. Changes in regional oxygenated haemoglobin (HbO2) across the frontal lobe were monitored using functional near infrared spectroscopy in 17 young and 18 older adults while they walked on a treadmill for 5 min, alternating between 30 s of walking at a preferred and fast (120% preferred) speed. Gait was quantified using a triaxial accelerometer (lower back). Differences between task (preferred/fast) and group (young/old) and associations between regional HbO2 and gait were evaluated. Paired tests indicated increased HbO2 in the supplementary motor area (right) and primary motor cortex (left and right) in older adults when walking fast (p < 0.006). HbO2 did not significantly change in the young when walking fast, despite both groups modulating gait. When evaluating the effect of age (linear mixed effects model), greater increases in HbO2 were observed for older adults when walking fast (prefrontal cortex, premotor cortex, supplementary motor area and primary motor cortex) compared to young adults. In older adults, increased step length and reduced step length variability were associated with larger increases in HbO2 across multiple regions when walking fast. Walking fast required increased activation of motor regions in older adults, which may serve as a therapeutic target for rehabilitation. Widespread increases in HbO2 across the frontal cortex highlight that walking fast represents a resource-intensive task as we age.
A Variable Photo-Model Method for Object Pose and Size Estimation with Stereo Vision in a Complex Home Scene
Authors: Tian Hongzhi , Wang Jirong
Published: August 2023

Model-based stereo vision methods can estimate the 6D poses of rigid objects. They can help robots to achieve a target grip in complex home environments. This study presents a novel approach, called the variable photo-model method, to estimate the pose and size of an unknown object using a single photo of the same category. By employing a pre-trained You Only Look Once (YOLO) v4 weight for object detection and 2D model generation in the photo, the method converts the segmented 2D photo-model into 3D flat photo-models assuming different sizes and poses. Through perspective projection and model matching, the method finds the best match between the model and the actual object in the captured stereo images. The matching fitness function is optimized using a genetic algorithm (GA). Unlike data-driven approaches, this approach does not require multiple photos or pre-training time for single object pose recognition, making it more versatile. Indoor experiments demonstrate the effectiveness of the variable photo-model method in estimating the pose and size of the target objects within the same class. The findings of this study have practical implications for object detection prior to robotic grasping, particularly due to its ease of application and the limited data required.
A 256 × 256 LiDAR Imaging System Based on a 200 mW SPAD-Based SoC with Microlens Array and Lightweight RGB-Guided Depth Completion Neural Network
Authors: Wang Jier , Li Jie , Wu Yifan , Yu Hengwei , Cui Lebei , Sun Miao , Chiang Patrick Yin
Published: August 2023

Light detection and ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation in mobile devices. To surmount these obstacles, this paper proposes a low-power, low-cost, single-photon avalanche detector (SPAD)-based system-on-chip (SoC) which packages the microlens arrays (MLAs) and a lightweight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8 × 8 SPAD macropixel array with time-to-digital converters (TDCs) and a charge pump, fabricated using a 180 nm bipolar-CMOS-DMOS (BCD) process. Initially, the primary function of this SoC was limited to serving as a ranging sensor. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8 × 8 to quarter video graphics array level (QVGA; 256 × 256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. The state-of-the-art SoC-neural network solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications on mobile devices.
BoxStacker: Deep Reinforcement Learning for 3D Bin Packing Problem in Virtual Environment of Logistics Systems
Authors: Murdivien Shokhikha Amalana , Um Jumyung
Published: August 2023

Manufacturing systems need to be resilient and self-organizing to adapt to unexpected disruptions, such as product changes or rapid order, in supply chain changes while increasing the automation level of robotized logistics processes to cope with the lack of human experts. Deep Reinforcement Learning is a potential solution to solve more complex problems by introducing artificial neural networks in Reinforcement Learning. In this paper, a game engine was used for Deep Reinforcement Learning training, which allows visualization of view learning and result processes more intuitively than other tools, as well as a physical engine for a more realistic problem-solving environment. The present research demonstrates that a Deep Reinforcement Learning model can effectively address the real-time sequential 3D bin packing problem by utilizing a game engine to visualize the environment. The results indicate that this approach holds promise for tackling complex logistical challenges in dynamic settings.
Gibberellin (GA3) and Copper Sulfate Pentahydrate (CuSO4·5H2O) Reduce Seeds per Fruit and Increase Fruit Quality in Bac Son Mandarin Fruit
Authors: Hung Nguyen Quoc , My Ha Le Thi , Hieu Nguyen Quoc , Tu Pham Thi Thanh , Lam Vu Phong
Published: August 2023

The aim of this study was to find the optimal gibberellic acid (GA3) and copper sulfate (CuSO4·5H2O) concentrations to reduce the number of seeds and increase the quality of Bac Son mandarin fruit. In experiment 1, the control plants (without GA3) were sprayed with water, and the remaining plants were sprayed with different concentrations of GA3 (50, 75, 100, or 125 ppm). In experiment 2, the control plants (without CuSO4·5H2O) were sprayed with water, and the remaining plants were sprayed with different concentrations of CuSO4·5H2O (50, 75, 100, or 125 ppm). Spraying GA3 at 100 ppm in 2018 produced the lowest seed number and the highest theoretical yield. In 2019, spraying GA3 led to a lower seed number and a higher actual yield compared with the control. Similarly, spraying CuSO4·5H2O significantly reduced the number of seeds/fruit and significantly increased the theoretical yield in 2018. In 2019, the total number of seeds/fruit was significantly lower in the CuSO4·5H2O treatments than in the control. Importantly, both GA3 and CuSO4·5H2O treatments did not adversely affect the fruit’s biochemical parameters or yield. These findings demonstrate that spraying GA3 or CuSO4·5H2O at a certain concentration can effectively reduce the number of seeds per fruit in Bac Son mandarin without compromising fruit quality or yield.
Central Coast Regional Equity Initiative: Co-Creating and Actionizing a New Community-Led Equity Framework
Authors: Knight Kathleen , Love Morgan , Williams Jonnie , Vargas Marcos
Published: August 2023

We present a community-led equity framework as a foundation for promoting equity on the Central Coast of California. We discuss the key elements of a participatory, community-led evaluation and planning approach for the Central Coast Regional Equity Initiative, which aims to advocate for social, health, environmental, and economic equity through region-wide cross-sector collaboration, community and research-informed action, and an indigenized and decolonized approach. Through a systematic mixed-methods evaluation and planning approach, including Community Consultations and Strategic Action Planning, we found that our community’s lived experience contributes to a deeper understanding of inequities, and that engagement in cross-sector collaboration empowers our community to bridge data with action organizing. The findings demonstrate that engagement in community-led evaluation and planning contributes to a greater readiness for cross-sector collaborative action and a sense of community ownership of solutions to equity issues, and sets the stage for deeper-rooted, long-term success built on genuine reciprocity and trust. We present our community-led equity framework inviting others to adopt systematic community knowledge-base-building that values community wisdom, identifies power imbalance, promotes trust-building through healthy discomfort, and encourages reflective action.
“I’m an Academic, Now What?”: Exploring Later-Career Women’s Academic Identities in Australian Higher Education Using Foucauldian Discourse Analysis
Authors: Phillips Matthew James , Dzidic Peta Louise
Published: August 2023

The becoming of, and being, a later-career woman academic is marked by being positioned to play a key role in the operation of the academic institution. Tensions emerge when later-career women academics are expected to balance these expectations, while simultaneously contemplating how they choose to remain, work, and identify within academia. We qualitatively explored how Australian later-career women academics conceptualise their academic identities, and the subject positions made available through their discourse. Aged between 43 and 72 years, 17 participants were interviewed. Data was analysed using Foucauldian Discourse Analysis. Four subject positions were identified—The Insecure Woman, who experienced tensions between the academic that the system required them to be, compared to the academic that they wanted to be; The Expert Academic, viewed by other individuals as the voice of reason within academia; The Reflective Academic, who reflects on, and summarises, their academic career; and The Disengaging Academic, who begins to transition out of their academic roles and responsibilities. Overall, the identified discourses created subjectivities questioning how much one has contributed to the academic setting, what it means to have been a part of academia, as well as evaluating what it means to identify beyond it.
Material Aspect of Sustainable Nuclear Waste Management
Authors: Petrov Vladislav A. , Ojovan Michael I. , Yudintsev Sergey V.
Published: August 2023

Effectively managing nuclear waste is crucial to ensure the safe sustainable usage of nuclear energy, which ranges from large-scale applications in power generation to numerous smaller-scale applications in medicine, industry, and agriculture, and scientific research is needed at the current state of development [...]
Impact Investing: Determinants of External Financing of Social Enterprises in Brazil
Authors: Fernandes Eduardo da Silva , Grochau Inês Hexsel , Ten Caten Carla Schwengber
Published: August 2023

Social impact investing and social entrepreneurship have great potential for solving global problems. However, practitioners and researchers know little about the entrepreneurial process and the investors’ criteria. Therefore, we identify the determinants of access to external finance for social enterprises in an emerging economy using a quantitative approach in a large sample (N = 601). We found that impact sector, business model, entrepreneurial support, development stage, and the adoption of technologies impact access to finance by social enterprises. We also show that green technologies have greater funding access than other enterprises and that social impact investors are more aware of environmental issues and less concerned with financial returns. To raise more funding, we suggest that social entrepreneurs include environmental issues in their business, quickly validate their idea, add an intermediary company between the enterprise and the consumer, seek the support of incubators or accelerators, and adopt emerging technologies in the product or service offered.
Collaborative Integrated Sustainable Tourism Management Model Using System Dynamics: A Case of Labuan Bajo, Indonesia
Authors: Fatina Shana , Soesilo Tri Edhi Budhi , Tambunan Rudy Parluhutan
Published: August 2023

Tourism is one of a region’s most prominent development vehicles. However, quality tourism is only achieved when supported by multi-sectors. This study aims to create a model of sustainable tourism management using a system dynamics approach. The model is based on the tourism development case in Labuan Bajo, a newly growing destination in Indonesia and a UNESCO Komodo biosphere reserve area. The research results in a model of sustainable tourism relevant to similar destinations with characteristics of high biodiversity but vulnerable to social inequality. This research finds it is critical to balance tourism growth and impact through the environment, economy, and social aspects and how destination management shall ensure multi-sector participation to create a conducive tourism ecosystem in the long run.
Spatiotemporal Evolution Characteristics and Driving Factors of Water Conservation Service in Jiangxi Province from 2001 to 2020
Authors: Gu Kangkang , Ma Luyao , Xu Jian , Yu Haoran , Zhang Xinmu
Published: August 2023

Water conservation services are key indicators of ecological services. Against the backdrop of frequent extreme weather events and water scarcity caused by global climate change and intensified human activities, assessing these services and their drivers are crucial tasks for regional ecological security and sustainable development. Jiangxi Province is one of the first national ecological civilization pilot zones in China, representing an important ecological barrier in southern China. Exploring the characteristics of spatial and temporal changes in water conservation and their driving factors can facilitate the rational development and utilization of regional water resources and the construction of ecological civilizations. Therefore, based on long time series data, the InVEST model was used to explore the spatiotemporal evolution characteristics of water conservation services, and to elucidate the trend of their change through the Theil–Sen median trend analysis and the Mann–Kendall test; then, the geographic detector and geographically weighted regression model were used to further analyze the drivers of spatial variability of water conservation services. The results showed the following: (1) The average depth of water conservation was 103.18 mm, showing a spatial pattern of “low in the middle, high in the surroundings, high in the north and low in the south”. (2) Slight improvements were primarily observed (77.49%), with only 1.60% of the area showing significant improvements. (3) Land use was the main driver of the spatial differentiation, and the interaction between precipitation and forestland had a significantly greater effect on spatial heterogeneity than any single factor. (4) Obvious spatial heterogeneity occurred in the driving factor impacts, with natural factors (precipitation, evapotranspiration, forestland, and grassland) having a positive impact on water conservation services, and land-use factors (construction land and cropland) and socioeconomic factors (population density and land area) having a negative effect. This study provides a reference for water-conservation-based ecosystem construction and policy formulation in Jiangxi Province.
Evaluation of Valorisation Strategies to Improve Grape Stems’ Nutritional Value as an Ingredient for Ruminants’ Diets
Authors: San Martin David , Ibarruri Jone , Luengo Nagore , Ferrer Jorge , García-Rodríguez Aser , Goiri Idoia , Atxaerandio Raquel , Zufía Jaime , Sáez de Cámara Estíbaliz , Iñarra Bruno
Published: August 2023

Grape stems are a by-product of wine production which is managed as a waste. Animal feeding arises as a potential alternative. However, its practical use may be compromised by its high lignin content. In this sense, hydrolysis emerges as a strategy to increase fibre digestibility. In addition, due to its high and variable moisture content, it should be dried to prevent microbial deterioration and a washing pre-treatment to reduce sugar content becomes necessary to minimize drying problems due to sugar melting at high temperatures. Within this framework, this study assessed the effect of washing and three different hydrolysis on the nutritive value of grape stems. A factorial design was carried out, with washing (with or without) and hydrolysis (without, enzymatic, alkali, and alkali-enzymatic) as factors. When the washing pre-treatment was not applied, only the alkali hydrolysis process maintained in vitro digestibility, but at the expense of a lower fermentation efficiency. When the washing pre-treatment was applied, fibre contents were similar among hydrolysis processes, but the alkali hydrolysis improved in vitro digestibility with similar fermentation efficiency. In conclusion, the alkali hydrolysis maintained or improved the grape stem nutritive value depending on whether the washing pre-treatment was applied or not.
Performance Evaluation of Open-Graded Bituminous Concrete Modified with Natural Fibers
Authors: Balreddy Muttana S. , Nethra Pamisetty , Naganna Sujay Raghavendra
Published: August 2023

Open-graded bituminous concrete (OGBC), also known as open-graded friction course or permeable asphalt layer, is a skid-resistant surface applied to pavements with high bitumen content. This mixture contains more coarse aggregates than fine aggregates, which improves subsurface drainage and indirectly reduces hydroplaning potential during wet weather conditions. The objective of the present study was to enhance the properties of the OGBC mix with fibers. Hence, four distinct natural biofibers, namely, sisal fiber, jute fiber, coir fiber, and bamboo fiber, were considered during experimental investigation at different dosages like 0.15%, 0.3% & 0.45% by weight of mix. Binder content levels ranged from 5 to 6% with an increment of 0.25% between the values in the range. Fiber-reinforced OGBC mixes were tested for air voids (%), draindown, resistance to moisture susceptibility, Cantabro loss, and indirect tensile strength of the compacted mixtures. The experimental findings demonstrate that fibers enhance the performance of OGBC mixes. Fiber incorporation reduced binder draindown and the percentage of air voids in OGBC mixes while maintaining the desired characteristics. The optimal fiber content was determined to be 0.30% for sisal, bamboo, and coir fibers and 0.45% for jute fibers. With the addition of sisal fibers at a dosage rate of 0.30%, the tensile strength of the OGBC mixture increased along with resistance to susceptibility to moisture.
Mushroom Biomass Waste Is a Source of the Antioxidants Ergothioneine and Glutathione
Authors: Sivakumar Dhanya , Bozzo Gale
Published: August 2023

Low-grade foodstuffs and unharvested materials from farms contribute a sizable amount of the waste that is disposed to landfills. Mushroom farms also contribute to this problem, as unmarketable fruiting bodies or parts of them are discarded in the waste stream. To limit the proportion of mushroom biomass waste that is deposited to landfills, we assessed whether culls of oyster and shiitake mushrooms and white button mushroom stem waste contain the antioxidants ergothioneine and glutathione. Enzyme-coupled spectrophotometric assays were used to assess the concentrations of glutathione (GSH) and its oxidized form glutathione disulfide in mushroom biomass waste. Ergothioneine analysis was performed with a high-performance liquid chromatography analysis. Most of the biomass waste contained ergothioneine and GSH concentrations that were on par with each one of the fresh mushrooms. Conversely, white button mushroom stem waste contained 77% less GSH than market-ready mushrooms. Finally, as a proof-of-concept cation exchange column chromatography was used to capture ergothioneine from oyster mushroom culls. This strategy has the potential to produce gram quantities of high value ergothioneine per tonne of mushroom biomass waste. These findings provide a strategy for the valorization of mushroom biomass waste and its diversion from landfills.
Scenarios to Improve E-Commerce SMEs Activity Based on Their Classification: A Case Study on Romania
Authors: Iordache Ana Maria Mihaela , Ionescu Alexandru , Cârstea Vlad Gabriel , Chung Hanna , Dumitru Nicoleta Rossela , Glăvan Bogdan
Published: August 2023

With the onset of the COVID-19 pandemic, society has increasingly relied on alternative ways to procure goods, leading to an e-commerce boom. This study analyzes the performance of small and medium-sized enterprises (SMEs) that are active in e-commerce in Romania and provides recommendations for entrepreneurs to improve their efficiency. Through unsupervised learning techniques, three classes are identified according to company performance: (1) a class of high-performing companies whose entrepreneurs took the risk of investing in the business, (2) a class of medium-performing companies that maintained their position in the market and (3) a class of financially weak companies whose managers adopted risk-averse, defensive policies. Furthermore, we present scenarios for moving companies from a lower-performing class to a higher-performing class. The research identifies the strategies that managers need to adopt in order to stimulate the activity of e-commerce companies, provides foreign investors a rubric for making investment decisions, and offers a starting point for an entrepreneurship course in academia.
A Comprehensive Review of Recent Research Trends on Unmanned Aerial Vehicles (UAVs)
Authors: Telli Khaled , Kraa Okba , Himeur Yassine , Ouamane Abdelmalik , Boumehraz Mohamed , Atalla Shadi , Mansoor Wathiq
Published: August 2023

The growing interest in unmanned aerial vehicles (UAVs) from both the scientific and industrial sectors has attracted a wave of new researchers and substantial investments in this expansive field. However, due to the wide range of topics and subdomains within UAV research, newcomers may find themselves overwhelmed by the numerous options available. It is therefore crucial for those involved in UAV research to recognize its interdisciplinary nature and its connections with other disciplines. This paper presents a comprehensive overview of the UAV field, highlighting recent trends and advancements. Drawing on recent literature reviews and surveys, the review begins by classifying UAVs based on their flight characteristics. It then provides an overview of current research trends in UAVs, utilizing data from the Scopus database to quantify the number of scientific documents associated with each research direction and their interconnections. This paper also explores potential areas for further development in UAVs, including communication, artificial intelligence, remote sensing, miniaturization, swarming and cooperative control, and transformability. Additionally, it discusses the development of aircraft control, commonly used control techniques, and appropriate control algorithms in UAV research. Furthermore, this paper addresses the general hardware and software architecture of UAVs, their applications, and the key issues associated with them. It also provides an overview of current open source software and hardware projects in the UAV field. By presenting a comprehensive view of the UAV field, this paper aims to enhance our understanding of this rapidly evolving and highly interdisciplinary area of research.
Association between Heavy Metals, Metalloids and Metabolic Syndrome: New Insights and Approaches
Authors: Martins Airton C. , Ferrer Beatriz , Tinkov Alexey A. , Caito Samuel , Deza-Ponzio Romina , Skalny Anatoly V. , Bowman Aaron B. , Aschner Michael
Published: August 2023

Metabolic syndrome (MetS) is an important public health issue that affects millions of people around the world and is growing to pandemic-like proportions. This syndrome is defined by the World Health Organization (WHO) as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Moreover, the etiology of MetS is multifactorial, involving many environmental factors, including toxicant exposures. Several studies have associated MetS with heavy metals exposure, which is the focus of this review. Environmental and/or occupational exposure to heavy metals are a major risk, contributing to the development of chronic diseases. Of particular note, toxic metals such as mercury, lead, and cadmium may contribute to the development of MetS by altering oxidative stress, IL-6 signaling, apoptosis, altered lipoprotein metabolism, fluid shear stress and atherosclerosis, and other mechanisms. In this review, we discuss the known and potential roles of heavy metals in MetS etiology as well as potential targeted pathways that are associated with MetS. Furthermore, we describe how new approaches involving proteomic and transcriptome analysis, as well as bioinformatic tools, may help bring about an understanding of the involvement of heavy metals and metalloids in MetS.
Host Derivation of Sindbis Virus Influences Mammalian Type I Interferon Response to Infection
Authors: Crawford John M. , Buechlein Aaron M. , Moline Davis A. , Rusch Douglas B. , Hardy Richard W.
Published: August 2023

Arboviruses are defined by their ability to replicate in both mosquito vectors and mammalian hosts. There is good evidence that arboviruses “prime” their progeny for infection of the next host, such as via differential glycosylation of their outer glycoproteins or packaging of host ribosomal subunits. We and others have previously shown that mosquito-derived viruses more efficiently infect mammalian cells than mammalian-derived viruses. These observations are consistent with arboviruses acquiring host-specific adaptations, and we hypothesized that a virus derived from either the mammalian host or mosquito vector elicits different responses when infecting the mammalian host. Here, we perform an RNA-sequencing analysis of the transcriptional response of Human Embryonic Kidney 293 (HEK-293) cells to infection with either mosquito (Aedes albopictus, C7/10)- or mammalian (Baby Hamster Kidney, BHK-21)-derived Sindbis virus (SINV). We show that the C7/10-derived virus infection leads to a more robust transcriptional response in HEK-293s compared to infection with the BHK-derived virus. Surprisingly, despite more efficient infection, we found an increase in interferon-β (IFN-β) and interferon-stimulated gene (ISG) transcripts in response to the C7/10-derived virus infection versus the BHK-derived virus infection. However, translation of interferon-stimulated genes was lower in HEK-293s infected with the C7/10-derived virus, starkly contrasting with the transcriptional response. This inhibition of ISG translation is reflective of a more rapid overall shut-off of host cell translation following infection with the C7/10-derived virus. Finally, we show that the C7/10-derived virus infection of HEK-293 cells leads to elevated levels of phosphorylated eukaryotic translation elongation factor-2 (eEF2), identifying a potential mechanism leading to the more rapid shut-off of host translation. We postulate that the rapid shut-off of host translation in mammalian cells infected with the mosquito-derived virus acts to counter the IFN-β-stimulated transcriptional response.