bluuebunny/crossref_metadata_2025 huggingface dataset:
Quality-of-Life Assessment in Pediatric Advanced Cancer: Development of the Patient-Reported Outcome Measure Advance QoL
Authors: Robichaud Lye-Ann , Felipe Julie , Duval Michel , Michon Bruno , Olivier-D’Avignon Marianne , Perreault Sébastien , Tyo-Gomez Mathias , Marquis Marc-Antoine , Sultan Serge
Published: April 2024

A recent measure was developed to assess the Quality of Life (QoL) of young people with advanced cancer and is available for parents and professionals (Advance QoL). The present study aimed to elaborate self-reported versions for children and adolescents with advanced cancer. We adopted a four-phase research plan: (1) to elaborate the Advance QoL questionnaire for youth (8–12 and 13–18 years old) with a team of young research partners; (2) to evaluate the understandability of these versions in a sample of 12 young patients from the target population using cognitive interviews; (3) to assess social validity in the same group using a questionnaire and the content validity index (CVI); and (4) to refine the questionnaires according to these results. Four major themes were identified: (1) issues affecting the understanding of the tool; (2) issues that did not affect the understanding of the tool; (3) modifications to improve the tool; and (4) positive features of the tool. Advance QoL was well received, and feedback was positive. Adjustments were made according to young people’s comments and two self-reported versions are now available. It is essential to measure the key domains of QoL in advanced cancer. Advance QoL self-report versions will help target the specific needs of young people with this condition and their families.
Impact of Pregnancy on Breast Cancer Features and Prognosis
Authors: Bounous Valentina E. , Minella Carola , Fuso Luca , Actis Silvia , Petroni Greta , Sgrò Luca G. , Borghese Martina , Tomasi Cont Nicoletta , Ponzone Riccardo , Ferrero Annamaria
Published: April 2024

Background: pregnancy-associated breast cancer (PABC) affects one in 3000 pregnancies, often presenting with aggressive features. Methods: We retrospectively evaluated a cohort of 282 young BC patients (≤45 years old) treated between 1995 and 2019, dividing them into three groups: nulliparous women, women with PABC (diagnosed within 2 years since last pregnancy) and women with BC diagnosed > 2 years since last pregnancy. This last group was further stratified according to the time between pregnancy and BC. The analysis encompassed histological factors (tumor size, histotype, grading, nodal involvement, multifocality, lympho-vascular invasion, hormone receptor expression, Ki-67 index, and HER2 expression), type of surgery and recurrence. Results: Age at diagnosis was younger in nulliparous than in parous women (p < 0.001). No significant differences were noticed regarding histological characteristics and recurrences. At univariate analysis, nodal involvement (OR = 2.4; p < 0.0001), high tumor grade (OR = 2.6; p = 0.01), and lympho-vascular invasion (OR = 2.3; p < 0.05), but not pregnancy (OR = 0.8; p = 0.30), influenced DFS negatively. Multivariate analysis confirmed nodal involvement as the only negative independent prognostic factor for a worse DFS (OR = 2.4; p = 0.0001). Conclusions: in our experience, pregnancy is not an independent adverse prognostic factor for BC DFS.
The Impact of the Pandemic on the Quality of Colorectal and Anal Cancer Care, and 2-Year Clinical Outcomes
Authors: Powis Melanie , Sutradhar Rinku , Singh Simron , Alibhai Shabbir , Hack Saidah , Baiad Abed , Chen Kevin , Li Huaqi , Mohmand Zuhal , Krzyzanowska Monika K.
Published: April 2024

We undertook a retrospective study to compare the quality of care delivered to a cohort of newly diagnosed adults with colon, rectal or anal cancer during the early phase of COVID-19 (02/20–12/20) relative to the same period in the year prior (the comparator cohort), and examine the impact of the pandemic on 2-year disease progression and all-cause mortality. We observed poorer performance on a number of quality measures, such as approximately three times as many patients in the COVID-19 cohort experienced 30-day post-surgical readmission (10.5% vs. 3.6%; SD:0.27). Despite these differences, we observed no statistically significant adjusted associations between COVID-19 and time to either all-cause mortality (HR: 0.88, 95% CI: 0.61–1.27, p = 0.50) or disease progression (HR: 1.16, 95% CI: 0.82–1.64, p = 0.41). However, there was a substantial reduction in new patient consults during the early phase of COVID-19 (12.2% decrease), which appeared to disproportionally impact patients who traditionally experience sociodemographic disparities in access to care, given that the COVID-19 cohort skewed younger and there were fewer patients from neighborhoods with the highest Housing and Dwelling, ands Age and Labour Force marginalization quintiles. Future work is needed to understand the more downstream effects of COVID-19 related changes on cancer care to inform planning for future disruptions in care.
Comparative Metagenomic Analysis of Marine eDNA Investigating the Production Crisis of Aquacultured Saccharina japonica
Authors: Choi Soyun , Yang Kwon Mo , Choi Dong Mun , Choi Yang Ho , Wang Xiuliang , Wang Lingxiu , Liu Xiaoyong , Duan Delin , Park Hyun , Kim Jeong Ha
Published: April 2024

Aquaculture farms cultivating Saccharina japonica are highly active in Wando, Korea, and Rongcheng, China. However, the yield of S. japonica significantly declined in the Rongcheng region in 2022 compared to previous records, whereas that in Wando remained at a normal level, presumably due to the presence of a pathogenic microbiome. We used environmental DNA (eDNA) metagenomic analysis to compare the microbial compositions of seawater from aquaculture farms in Wando and Rongcheng. Seawater samples were collected from one Korean site in Wando (WA) and two Chinese sites in Ailian Bay (AB) and Lidao Bay (LB). Metagenomic analysis focusing on the microbial 16S rRNA identified 38 phyla and 58 families of microbiomes in all regions. Potentially pathogenic bacterial groups associated with S. japonica in AB and LB were more abundant than in WA, suggesting their potential influence on mortality and the decline in the harvest yield of S. japonica. The microbial composition of WA was distinguished from those of the other two sites, which clustered together with higher similarity. Since the S. japonica aquaculture industry is important for both countries, this comparative eDNA monitoring is a valuable initiation towards the next step of problem-solving practices in coastal management in these two aquaculture systems.
Comprehensive Investigation of Angiogenesis, PASS Score and Immunohistochemical Factors in Risk Assessment of Malignancy for Paraganglioma and Pheochromocytoma
Authors: Milinkovic Marija , Soldatovic Ivan , Zivaljevic Vladan , Bozic Vesna , Zivotic Maja , Tatic Svetislav , Dundjerovic Dusko
Published: April 2024

A challenging task in routine practice is finding the distinction between benign and malignant paragangliomas and pheochromocytomas. The aim of this study is to conduct a comparative analysis of angiogenesis by assessing intratumoral microvascular density (MVD) with immunohistochemical (IHC) markers (CD31, CD34, CD105, ERG), and S100 immunoreactivity, Ki67 proliferative index, succinate dehydrogenase B (SDHB) expressiveness, tumor size with one the most utilized score Pheochromocytoma of Adrenal Gland Scales Score (PASS), using tissue microarray (TMA) with 115 tumor samples, 61 benign (PASS < 4) and 54 potentially malignant (PASS ≥ 4). We found no notable difference between intratumoral MVD and potentially malignant behavior. The group of potentially malignant tumors is significantly larger in size, has lower intratumoral MVD, and a decreased number of S100 labeled sustentacular cells. Both groups have low proliferative activity (mean Ki67 is 1.02 and 1.22, respectively). Most tumors maintain SDHB expression, only 6 cases (5.2%) showed a loss of expression (4 of them in PASS < 4 group and 2 in PASS ≥ 4). PASS score is easily available for assessment and complemented with markers of biological behavior to complete the risk stratification algorithm. Size is directly related to PASS score and malignancy. Intratumoral MVD is extensively developed but it is not crucial in evaluating the malignant potential.
Empowering Potential of the My Assistive Technology Guide: Exploring Experiences and User Perspectives
Authors: Orellano-Colon Elsa M. , Fernández-Torres Angelis , Figueroa-Alvira Nixmarie , Ortiz-Vélez Bernice , Rivera-Rivera Nina L. , Torres-Ferrer Gabriela A. , Martín-Payo Rubén
Published: April 2024

The use of assistive technology (AT) devices enhances older adults’ function in daily activities. However, the lack of awareness of AT among potential AT users has been identified as a major barrier to its adoption. This study aimed to assess the quality of the Mi Guía de Asistencia Tecnológica (MGAT) web app, which provides information on AT, from the perspective of older Latinos with physical disabilities, and to explore their experience using the MGAT. We employed a convergent parallel mixed-method design involving 12 older Latinos living in Puerto Rico. In Phase I, the researchers trained the participants in the use of the MGAT. In Phase II, participants were encouraged to use it for 30 days. In Phase III, the participants completed the User Mobile Application Rating Scale (uMARS) and individual interviews, analyzed with descriptive statistics and a directed thematic content analysis. The quality of the MGAT was rated high in both the objective (uMARS mean = 3.99; SD = 0.68) and subjective (uMARS mean = 4.13; SD = 1.10) domains. Qualitative data revealed the MGAT was accessible, usable, desirable, credible, useful, and valuable to increasing older Latinos’ AT knowledge, function, and autonomy. The MGAT has the potential to increase AT awareness and adoption among older adults.
Generalized Category Discovery in Aerial Image Classification via Slot Attention
Authors: Zhou Yifan , Zhu Haoran , Zhang Yan , Liang Shuo , Wang Yujing , Yang Wen
Published: April 2024

Aerial images record the dynamic Earth terrain, reflecting changes in land cover patterns caused by natural processes and human activities. Nonetheless, prevailing aerial image classification methodologies predominantly function within a closed-set framework, thereby encountering challenges when confronted with the identification of newly emerging scenes. To address this, this paper explores an aerial image recognition scenario in which a dataset comprises both labeled and unlabeled aerial images, intending to classify all images within the unlabeled subset, termed Generalized Category Discovery (GCD). It is noteworthy that the unlabeled images may pertain to labeled classes or represent novel classes. Specifically, we first develop a contrastive learning framework drawing upon the cutting-edge algorithms in GCD. Based on the multi-object characteristics of aerial images, we then propose a slot attention-based GCD training process (Slot-GCD) that contrasts learning at both the object and image levels. It decouples multiple local object features from feature maps using slots and then reconstructs the overall semantic feature of the image based on slot confidence scores and the feature map. Finally, these object-level and image-level features are input into the contrastive learning module to enable the model to learn more precise image semantic features. Comprehensive evaluations across three public aerial image datasets highlight the superiority of our approach over state-of-the-art methods. Particularly, Slot-GCD achieves a recognition accuracy of 91.5% for known old classes and 81.9% for unknown novel class data on the AID dataset.
Multi-Sensor 3D Survey: Aerial and Terrestrial Data Fusion and 3D Modeling Applied to a Complex Historic Architecture at Risk
Authors: Roggero Marco , Diara Filippo
Published: April 2024

This work is inscribed into a more comprehensive project related to the architectural requalification and restoration of Frinco Castle, one of the most significant fortified medieval structures in the Monferrato area (province of Asti, Italy), that experienced a structural collapse. In particular, this manuscript focuses on data fusion of multi-sensor acquisitions of metric surveys for 3D documenting this structural-risky building. The structural collapse made the entire south front fragile. The metric survey was performed by using terrestrial and aerial sensors to reach every area of the building. Topographically oriented Terrestrial Laser Scans (TLS) data were collected for the exterior and interior of the building, along with the DJI Zenmuse L1 Airborne Laser Scans (ALS) and Zenmuse P1 Photogrammetric Point Cloud (APC). First, the internal alignment in the TLS data set was verified, followed by the intra-technique alignments, choosing TLS as the reference data set. The point clouds from each sensor were analyzed by computing voxel-based point density and roughness, then segmented, aligned, and fused. 3D acquisitions and segmentation processes were fundamental for having a complete and structured dataset of almost every outdoor and indoor area of the castle. The collected metrics data was the starting point for the modeling phase to prepare 2D and 3D outputs fundamental for the restoration process.
Simulation of Natural Convection with Sinusoidal Temperature Distribution of Heat Source at the Bottom of an Enclosed Square Cavity
Authors: Zeng Min , Wang Zhiqiang , Xu Ying , Ma Qiang
Published: April 2024

The lattice Boltzmann method is employed in the current study to simulate the heat transfer characteristics of sinusoidal-temperature-distributed heat sources at the bottom of a square cavity under various conditions, including different amplitudes, phase angles, initial positions, and angular velocities. Additionally, a machine learning-based model is developed to accurately predict the Nusselt number in such a sinusoidal temperature distribution of heat source at the bottom of a square cavity. The results indicate that (1) in the phase angle range from 0 to π, Nu basically shows a decreasing trend with an increase in phase angle. The decline in Nu at an accelerated rate is consistently observed when the phase angle reaches 4π/16. The corresponding Nu decreases as the amplitude increases at the same phase angle. (2) The initial position of the sinusoidal-temperature-distributed heat source Lc significantly impacts the convective heat transfer in the cavity. Moreover, the decline in Nu was further exacerbated when Lc reached 7/16. (3) The optimal overall heat transfer effect was achieved when the angular velocity of the non-uniform heat source reached π. As the angular velocity increases, the local Nu in the square cavity exhibits a gradual and oscillatory decline. Notably, it is observed that Nu at odd multiples of π surpasses that at even multiples of π. Furthermore, the current work integrates LBM with machine learning, enabling the development of a precise and efficient prediction model for simulating Nu under specific operational conditions. This research provides valuable insights into the application of machine learning in the field of heat transfer.
“Don’t Touch Race”: Nice White Leadership and Calls for Racial Equity in Salt Lake City Schools, 1969–Present
Authors: Wall Maeve K.
Published: April 2024

This paper examines school leaders’ evasive attitudes towards race in Salt Lake City (SLC), Utah, between 1969 and 1975. Salt Lake’s unique demographic status as predominantly white and Mormon underscored elements of white anti-Black racism under the guise of innocence. Utilizing critical whiteness theory and historical inquiry to analyze archival documents and interviews, I highlight one white superintendent, Arthur Wiscombe, and his failed attempts to confront anti-Blackness in schools as he navigated his conflicting values of racial justice, good intentions, and white Niceness. Framing the past as prologue, I uncover the historical legacy of white supremacy’s influence on local school policies and leaders’ actions, and make explicit connections to the repetition of these patterns today. Contemporary iterations of white supremacy rely on the same tools of whiteness used during intense periods of integration and racial awareness in Salt Lake City in the 1960s and 1970s. I conclude that white educational leaders must look more closely at the ‘nice’, color-evasive discourse that enables them to maintain power and privilege in their communities.
Advanced Analytics and Data Management in the Procurement Function: An Aviation Industry Case Study
Authors: Altundag Andrea , Wynn Martin
Published: April 2024

The company’s strategic procurement function makes a significant contribution to overall corporate success, and yet remains under-researched in terms of digitalisation and digital maturity. This research adopts an inductive case study approach, using qualitative data from in-depth interviews with industry practitioners to develop and apply a digital maturity model for the deployment of strategic procurement analytics. The case study company is a multinational aerospace corporation with almost 150,000 employees worldwide. The research presents a snapshot of the digital maturity of the strategic procurement function of this global aircraft manufacturer and finds that the current exploitation of analytics remains constrained by a range of factors, including the need for close compliance with regulatory norms. Thematic analysis of the interview material provides the basis for the development of the maturity model, which—although geared to a specific industry context—is nevertheless of relevance in other business environments. The research thus contributes to the existing literature in this field, and will also be of interest to procurement professionals. However, the research clearly has its limitations, not least in that it is based on just one industry case, and cross-industry generalisations from the findings must therefore be treated with caution.
A Power-Efficient High-Drive Current Mirror Combining a Regulated Cascode Topology with a Non-Linear CCII-Based Feedback
Authors: Julien Mohan , Bernard Serge , Soulier Fabien , Kerzérho Vincent , Cathébras Guy
Published: April 2024

This brief presents a continuously regulated current mirror topology capable of providing a wide range of currents with high-precision and speed control features. The circuit combines a non-linear current-mode feedback solution for fast and energy-efficient operation with an input-referred regulated-cascode configuration for precise current mirroring. The proposed implementation has an output current ranging from 100 μA to 2 mA, exhibits a fast response time of ≈100 ns for the full range steps, while ensuring a high power efficiency (>90%) and low current copy errors (<0.5%).
Scalable Multi-Robot Task Allocation Using Graph Deep Reinforcement Learning with Graph Normalization
Authors: Zhang Zhenqiang , Jiang Xiangyuan , Yang Zhenfa , Ma Sile , Chen Jiyang , Sun Wenxu
Published: April 2024

Task allocation plays an important role in multi-robot systems regarding team efficiency. Conventional heuristic or meta-heuristic methods face difficulties in generating satisfactory solutions in a reasonable computational time, particularly for large-scale multi-robot task allocation problems. This paper proposes a novel graph deep-reinforcement-learning-based approach, which solves the problem through learning. The framework leverages the graph sample and aggregate concept as the encoder to extract the node features in the context of the graph, followed by a cross-attention decoder to output the probability that each task is allocated to each robot. A graph normalization technique is also proposed prior to the input, enabling an easy adaption to real-world applications, and a deterministic solution can be guaranteed. The most important advantage of this architecture is the scalability and quick feed-forward character; regardless of whether cases have a varying number of robots or tasks, single depots, multiple depots, or even mixed single and multiple depots, solutions can be output with little computational effort. The high efficiency and robustness of the proposed method are confirmed by extensive experiments in this paper, and various multi-robot task allocation scenarios demonstrate its advantage.
High-Speed CNN Accelerator SoC Design Based on a Flexible Diagonal Cyclic Array
Authors: Lee Dong-Yeong , Aliev Hayotjon , Junaid Muhammad , Park Sang-Bo , Kim Hyung-Won , Lee Keon-Myung , Sim Sang-Hoon
Published: April 2024

The latest convolutional neural network (CNN) models for object detection include complex layered connections to process inference data. Each layer utilizes different types of kernel modes, so the hardware needs to support all kernel modes at an optimized speed. In this paper, we propose a high-speed and optimized CNN accelerator with flexible diagonal cyclic arrays (FDCA) that supports the acceleration of CNN networks with various kernel sizes and significantly reduces the time required for inference processing. The accelerator uses four FDCAs to simultaneously calculate 16 input channels and 8 output channels. Each FDCA features a 4 × 8 systolic array that contains a 3 × 3 processing element (PE) array and is designed to handle the most commonly used kernel sizes. To evaluate the proposed CNN accelerator, we mapped the widely used YOLOv5 CNN model and evaluated the performance of its implementation on the Zynq UltraScale+ MPSoC ZCU102 FPGA. The design consumes 249,357 logic cells, 2304 DSP blocks, and only 567 KB BRAM. In our evaluation, the YOLOv5n model achieves an accuracy of 43.1% (mAP@0.5). A prototype accelerator has been implemented using Samsung’s 14 nm CMOS technology. It achieves 1.075 TOPS, a peak performance with a 400 MHz clock frequency.
ML-Enhanced Live Video Streaming in Offline Mobile Ad Hoc Networks: An Applied Approach
Authors: Jesús-Azabal Manuel , Soares Vasco N. G. J. , Galán-Jiménez Jaime
Published: April 2024

Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions is challenging due to the stringent requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts in which an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal is implemented and assessed in a laboratory context, in which the model performance and QoS metrics are analyzed. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% accuracy. Also, the obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.
Advanced Algorithmic Approaches for Scam Profile Detection on Instagram
Authors: Bokolo Biodoumoye George , Liu Qingzhong
Published: April 2024

Social media platforms like Instagram have become a haven for online scams, employing various deceptive tactics to exploit unsuspecting users. This paper investigates advanced algorithmic approaches to combat this growing threat. We explore various machine learning models for scam profile detection on Instagram. Our methodology involves collecting a comprehensive dataset from a trusted source and meticulously preprocessing the data for analysis. We then evaluate the effectiveness of a suite of machine learning algorithms, including decision trees, logistic regression, SVMs, and other ensemble methods. Each model’s performance is measured using established metrics like accuracy, precision, recall, and F1-scores. Our findings indicate that ensemble methods, particularly random forest, XGBoost, and gradient boosting, outperform other models, achieving accuracy of 90%. The insights garnered from this study contribute significantly to the body of knowledge in social media forensics, offering practical implications for the development of automated tools to combat online deception.
Application and Analysis of Liquid Organic Hydrogen Carrier (LOHC) Technology in Practical Projects
Authors: Li Hanqi , Zhang Xi , Zhang Chenjun , Ding Zhenfeng , Jin Xu
Published: April 2024

In contemporary times, the utilization of liquid organic hydrogen carriers (LOHCs) has gained prominence due to their high volumetric storage density and material properties closely resembling conventional fuels. Numerous countries are incorporating LOHCs in hydrogen demonstration initiatives, encompassing applications such as hydrogen refueling stations, hydrogen-powered ships, and trains. This paper conducts a comprehensive review of seventeen LOHC projects, spanning Germany, Europe, and other nations, presenting detailed project specifications. This review includes information on project consortiums, funding sources, covered supply chains, transport modalities, and employed technologies. Through a global evaluation of LOHC projects, this review underscores the promising and competitive nature of LOHCs as a viable option for the large-scale and long-distance storage and transportation of hydrogen. The future development of this field is discussed at in the last section.
Research on the Monitoring of Overlying Aquifer Water Richness in Coal Mining by the Time-Lapse Electrical Method
Authors: Zhu Chenyang , Zhu Guowei , Gong Yufei , Zhang Lei
Published: April 2024

To study the influence of coal mining on the water richness overlying strata in the mining area using time-lapse electrical monitoring technology, four dataset acquisitions were completed with the same acquisition method, equipment, parameters, and processing flow. According to the characteristics of the data, major problems such as topographic correction, high-precision denoising, spatial and temporal normalization, and resistivity data inversion have been solved. Precise tomographic imaging was achieved through high-precision data processing and difference inversion. The results show that the electrical stratification characteristics of the overlying soil and rock layers are clear, the resistivity from the surface down gradually increases, and the electrical layers are not uniform locally. During mining, the overlying strata are affected by mining, the electrical resistivity of the underlying aquifers increased to varying degrees, and the fluctuation of electrical resistivity increased while the aquifer’s water content decreased. After mining, the overlying aquifer has the phenomenon of ‘reduced resistivity and water recovery’. After a period of time, the overlying soil disturbance and overlying rock failure zone will gradually tend to be stable. Meanwhile, the aquifer structure and water content will also gradually recover. Our results could provide guidance for water resources protection in this region.
Collaborative Optimization Scheduling of Multi-Microgrids Incorporating Hydrogen-Doped Natural Gas and P2G–CCS Coupling under Carbon Trading and Carbon Emission Constraints
Authors: Zhao Yuzhe , Chen Jingwen
Published: April 2024

In the context of “dual carbon”, restrictions on carbon emissions have attracted widespread attention from researchers. In order to solve the issue of the insufficient exploration of the synergistic emission reduction effects of various low-carbon policies and technologies applied to multiple microgrids, we propose a multi-microgrid electricity cooperation optimization scheduling strategy based on stepped carbon trading, a hydrogen-doped natural gas system and P2G–CCS coupled operation. Firstly, a multi-energy microgrid model is developed, coupled with hydrogen-doped natural gas system and P2G–CCS, and then carbon trading and a carbon emission restriction mechanism are introduced. Based on this, a model for multi-microgrid electricity cooperation is established. Secondly, design optimization strategies for solving the model are divided into the day-ahead stage and the intraday stage. In the day-ahead stage, an improved alternating direction multiplier method is used to distribute the model to minimize the cooperative costs of multiple microgrids. In the intraday stage, based on the day-ahead scheduling results, an intraday scheduling model is established and a rolling optimization strategy to adjust the output of microgrid equipment and energy purchases is adopted, which reduces the impact of uncertainties in new energy output and load forecasting and improves the economic and low-carbon operation of multiple microgrids. Setting up different scenarios for experimental validation demonstrates the effectiveness of the introduced low-carbon policies and technologies as well as the effectiveness of their synergistic interaction.
Integrated Study on Carbon Dioxide Geological Sequestration and Gas Injection Huff-n-Puff to Enhance Shale Oil Recovery
Authors: Wang Lei , Cai Shengyao , Chen Wenli , Lei Gang
Published: April 2024

Multi-stage fractured horizontal well technology is an effective development method for unconventional reservoirs; however, shale oil reservoirs with ultra-low permeability and micro/nanopore sizes are still not ideal for production and development. Injecting CO2 into the reservoir, after hydraulic fracturing, gas injection flooding often produces a gas channeling phenomenon, which affects the production of shale oil. In comparison, CO2 huff-n-puff development has become a superior method in the development of multi-stage fractured horizontal wells in shale reservoirs. CO2 huff and injection can not only improve shale oil recovery but also store the CO2 generated in industrial production in shale reservoirs, which can reduce greenhouse gas emissions to a certain extent and achieve carbon capture, utilization, and storage (CCUS). In this paper, the critical temperature and critical parameters of fluid in shale reservoirs are corrected by the critical point correction method in this paper, and the influence of reservoir pore radius on fluid phase behavior and shale oil production is analyzed. According to the shale reservoir applied in isolation to the actual state of the reservoir and under the condition of a complex network structure, we described the seepage characteristics of shale oil and gas and CO2 in the reservoir by embedding a discrete fracture technology structure and fracture network, and we established the numerical model of the CO2 huff-n-huff development of multi-stage fractured horizontal wells for shale oil. We used the actual production data of the field for historical fitting to verify the validity of the model. On this basis, CO2 huff-n-puff development under different gas injection rates, huff-n-puff cycles, soaking times, and other factors was simulated; cumulative oil production and CO2 storage were compared; and the influence of each factor on development and storage was analyzed, which provided theoretical basis and specific ideas for the optimization of oilfield development modes and the study of CO2 storage.
Towards a Net Zero-Emission Electricity Generation System by Optimizing Renewable Energy Sources and Nuclear Power Plant
Authors: Rahmanta Mujammil Asdhiyoga , Hasibi Rahmat Adiprasetya Al , Tambunan Handrea Bernando , Ruly  , Syamsuddin Agussalim , Aditya Indra Ardhanayudha , Susanto Benny
Published: April 2024

Greenhouse gas emissions, including CO2 emissions, are an issue in the energy sector that must be addressed urgently. The energy sector, including electricity, has been given a global aim of net zero emissions (NZE). This article examines three scenarios for reaching net-zero emissions in power supply. These scenarios are baseline, NZE1, and NZE2. The baseline scenario represents power plant capacity planning based on existing regulations in the base year. The net zero emissions consisting of the NZE1 and NZE2 scenarios aim to achieve net zero emissions by 2060. The NZE1 and NZE2 scenarios differ in the usage of nuclear power plant technology. The NZE1 scenario employs advanced costs for small modular reactors and large reactors technology, whilst the NZE2 scenario employs the low cost of small modular reactors and large reactors. The three scenarios were implemented and examined using the low emissions analysis platform software. The analytical results demonstrate that the NZE1 and NZE2 scenarios can meet the net zero emission objective by 2058. The baseline scenario results in power plant capacity planning with an average annual CO2 emission growth rate of 3.58%. On the other hand, the baseline scenario has the lowest investment expenses, at only 44 billion USD.
A Comprehensive Review of Machine Learning Approaches for Anomaly Detection in Smart Homes: Experimental Analysis and Future Directions
Authors: Rahman Md Motiur , Gupta Deepti , Bhatt Smriti , Shokouhmand Shiva , Faezipour Miad
Published: April 2024

Detecting anomalies in human activities is increasingly crucial today, particularly in nuclear family settings, where there may not be constant monitoring of individuals’ health, especially the elderly, during critical periods. Early anomaly detection can prevent from attack scenarios and life-threatening situations. This task becomes notably more complex when multiple ambient sensors are deployed in homes with multiple residents, as opposed to single-resident environments. Additionally, the availability of datasets containing anomalies representing the full spectrum of abnormalities is limited. In our experimental study, we employed eight widely used machine learning and two deep learning classifiers to identify anomalies in human activities. We meticulously generated anomalies, considering all conceivable scenarios. Our findings reveal that the Gated Recurrent Unit (GRU) excels in accurately classifying normal and anomalous activities, while the naïve Bayes classifier demonstrates relatively poor performance among the ten classifiers considered. We conducted various experiments to assess the impact of different training–test splitting ratios, along with a five-fold cross-validation technique, on the performance. Notably, the GRU model consistently outperformed all other classifiers under both conditions. Furthermore, we offer insights into the computational costs associated with these classifiers, encompassing training and prediction phases. Extensive ablation experiments conducted in this study underscore that all these classifiers can effectively be deployed for anomaly detection in two-resident homes.
Using qPCR to Identify Potential Effects of Thermal Conditions during Embryogenesis on Mitochondrial DNA Copy Number in Juvenile Brown Trout Salmo trutta
Authors: Erlandsson Ann , Ašmonaitė Giedrė , Jonsson Bror , Greenberg Larry
Published: April 2024

Changes in the number, structure, and function of mitochondria during the early life stages of animals can play an important role for an organism’s metabolic rate, growth, and health. Previous studies have shown that juvenile brown trout (Salmo trutta) subjected to elevated temperatures during the embryonic stage respond phenotypically with a reduced metabolic rate. The aim of this study was to explore if embryonic temperature affects the mitochondria content of young brown trout and as such explains the previously found differences in metabolic rates. Here, we optimize a quantitative PCR (qPCR) method for the mitochondria cytochrome c oxidase subunit I gene, and then use the method as a proxy for mitochondrial DNA content. We hypothesize that young trout subjected to elevated temperatures during the embryonic stage respond phenotypically with a reduced mitochondrial DNA content. To test this hypothesis, we subjected brown trout to either control ambient (4.4 ± 1.5 °C) or elevated temperatures (7.1 ± 0.6 °C) during embryogenesis. Subsequently, we extracted DNA from liver and white muscle tissue of juvenile brown trout from the two different incubation temperature treatments and successively optimized qPCR for mitochondrial DNA. We found that the amount of mitochondria DNA in liver tissue was 18 times higher than in white muscle tissue, but there was no significant difference in mitochondria content in liver or muscle tissue between brown trout exposed to elevated and ambient control temperatures during embryogenesis. We conclude that reduced metabolic rate is not likely associated with mitochondria DNA content. We also suggest that qPCR is a simple and cost-effective method to quantify mitochondria DNA in frozen and partly degraded tissue from different treatment groups and a useful proxy for identification of differences in mitochondria number.
Analysis of MAV Rotors Optimized for Low Noise and Aerodynamic Efficiency with Operational Constraints
Authors: Li Volsi Pietro , Brogna Gianluigi , Gojon Romain , Jardin Thierry , Parisot-Dupuis Hélène , Moschetta Jean-Marc
Published: April 2024

The rapid growth of drone use in urban areas has prompted authorities to review airspace regulations, forcing drone manufacturers to anticipate and reduce the noise emissions during the design stage. Additionally, micro air vehicles (MAVs) are designed to be aerodynamically efficient, allowing them to fly farther, longer and safer. In this study, a steady aerodynamic code and an acoustic propagator based on the non-linear vortex lattice method (NVLM) and Farassat’s formulation-1A of the Ffowcs Williams and Hawkings (FW-H) acoustic analogy, respectively, are coupled with pymoo, a python-based optimization framework. This tool is used to perform a multi-objective (noise and aerodynamic efficiency) optimization of a 20 cm diameter two-bladed rotor under hovering conditions. From the set of optimized results, (i.e., the Pareto front), three different rotors are 3D-printed using a stereolithography (SLA) technique and tested in an anechoic room. Here, an array of far-field microphones captures the acoustic radiation and directivity of the rotor, while a balance measures the aerodynamic performance. Both the aerodynamic and aeroacoustic performance of the three different rotors, in line with what has been predicted by the numerical codes, are compared and guidelines for the design of aerodynamically and aeroacoustically efficient MAV rotors are extracted.
Enhancing Stability and Antioxidant Activity of Resveratrol-Loaded Emulsions by Ovalbumin–Dextran Conjugates
Authors: Zhang Wen , Meng Lingli , Lv Xinyi , Wang Limin , Zhao Pei , Wang Jinrong , Zhang Xinping , Chen Jinyu , Wu Zijian
Published: April 2024

A reliable strategy for improving the stability and shelf life of protein-stabilized systems is by covalently attaching the protein onto a polysaccharide. In this study, ovalbumin (OVA) was modified with dextran (DEX) of different molecular weights by the Maillard reaction, and was used to enhance the stability of emulsions loaded with resveratrol. The surface hydrophobicity, thermal stability, and FT-IR spectroscopy of the OVA–DEX conjugates were evaluated. The results showed that the surface hydrophobicity of OVA decreased, while the thermal stability of OVA was significantly improved after DEX covalent modification. The OVA–DEX1k-stabilized emulsion exhibited high encapsulation efficiency of resveratrol, with the value of 89.0%. In addition, OVA–DEX was considerably more effective in droplet stabilization against different environmental stresses (heat, pH, and ionic strength). After 28 days of storage at 25 °C, the OVA-stabilized emulsion showed faster decomposition of resveratrol, whereas the OVA–DEX-conjugate-stabilized emulsion had approximately 73% retention of resveratrol. Moreover, the antioxidant activity of resveratrol-loaded emulsions stabilized by OVA–DEX was higher during storage under different temperatures. These results proved that the OVA–DEX conjugates had the potential to form stable, food-grade emulsion-based delivery systems against environmental stresses, which strongly supports their potential in the field of food and biomedical applications.
Development, Validation, and Application of High-Performance Liquid Chromatography with Diode-Array Detection Method for Simultaneous Determination of Ginkgolic Acids and Ginkgols in Ginkgo biloba
Authors: Boateng Isaac Duah , Li Fengnan , Yang Xiao-Ming
Published: April 2024

Ginkgo biloba leaves (GBLs), which comprise many phytoconstituents, also contain a toxic substance named ginkgolic acid (GA). Our previous research showed that heating could decarboxylate and degrade GA into ginkgols with high levels of bioactivity. Several methods are available to measure GA in GBLs, but no analytical method has been developed to measure ginkgols and GA simultaneously. Hence, for the first time, an HPLC-DAD method was established to simultaneously determine GA and ginkgols using acetonitrile (0.01% trifluoroacetic acid, v/v) as mobile phase A and water (0.01% trifluoroacetic acid, v/v) as mobile phase B. The gradient elution conditions were: 0–30 min, 75–90% phase A; 30–35 min, 90–90% phase A; 35–36 min, 90–75% phase A; 36–46 min, 75–75% phase A. The detection wavelength of GA and ginkgol were 210 and 270 nm, respectively. The flow rate and injection volume were 1.0 mL/min and 50 μL, respectively. The linearity was excellent (R2 > 0.999), and the RSD of the precision, stability, and repeatability of the total ginkgols was 0.20%, 2.21%, and 2.45%, respectively, in six parallel determinations. The recoveries for the low, medium, and high groups were 96.58%, 97.67%, and 101.52%, respectively. The limit of detection of ginkgol C13:0, C15:1, and C17:1 was 0.61 ppm, 0.50 ppm, and 0.06 ppm, respectively. The limit of quantification of ginkgol C13:0, C15:1, and C17:1 was 2.01 ppm, 1.65 ppm, and 0.20 ppm, respectively. Finally, this method accurately measured the GA and ginkgol content in ginkgo leaves and ginkgo tea products (ginkgo black tea, ginkgo dark tea, ginkgo white tea, and ginkgo green tea), whereas principal component analysis (PCA) was performed to help visualize the association between GA and ginkgols and five different processing methods for GBLs. Thus, this research provides an efficient and accurate quantitative method for the subsequent detection of GA and ginkgols in ginkgo tea.
Characterization of Key Odorants in Lushan Yunwu Tea in Response to Intercropping with Flowering Cherry
Authors: Gao Yinxiang , Lei Zhiyong , Huang Jigang , Sun Yongming , Liu Shuang , Yao Liping , Liu Jiaxin , Liu Wenxin , Liu Yanan , Chen Yan
Published: April 2024

Lushan Yunwu tea (LSYWT) is a famous green tea in China. However, the effects of intercropping tea with flowering cherry on the overall aroma of tea have not been well understood. In this study, headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC–MS) was used for analysis. A total of 54 volatile compounds from eight chemical classes were identified in tea samples from both the intercropping and pure-tea-plantation groups. Principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and odor activity value (OAV) methods combined with sensory evaluation identified cis-jasmone, nonanal, and linalool as the key aroma compounds in the intercropping group. Benzaldehyde, α-farnesene, and methyl benzene were identified as the main volatile compounds in the flowering cherry using headspace solid-phase microextraction/gas chromatography–mass spectrometry (HS-SPME/GC–MS). These findings will enrich the research on tea aroma chemistry and offer new insights into the product development and quality improvement of LSYWT.
The Bioaccessibility and Bioavailability of Pentachlorophenol in Five Animal-Derived Foods Measured by Simulated Gastrointestinal Digestion
Authors: Zhou Quan , Chen Huiming , Li Liangliang , Wu Yongning , Yang Xingfen , Jiang Aimin , Wu Weiliang
Published: April 2024

Pentachlorophenol (PCP) is a ubiquitous emerging persistent organic pollutant detected in the environment and foodstuffs. Despite the dietary intake of PCP being performed using surveillance data, the assessment does not consider the bioaccessibility and bioavailability of PCP. Pork, beef, pork liver, chicken and freshwater fish Ctenopharyngodon Idella-fortified by three levels of PCP were processed by RIVM and the Caco-2 cell model after steaming, boiling and pan-frying, and PCP in foods and digestive juices were detected using isotope dilution–UPLC-MS/MS. The culinary treatment and food matrix were significantly influenced (p < 0.05) in terms of the bioaccessibility and bioavailability of PCP. Pan-frying was a significant factor (p < 0.05) influencing the digestion and absorption of PCP in foods, with the following bioaccessibility: pork (81.37–90.36%), beef (72.09–83.63%), pork liver (69.11–78.07%), chicken (63.43–75.52%) and freshwater fish (60.27–72.14%). The bioavailability was as follows: pork (49.39–63.41%), beef (40.32–53.43%), pork liver (33.63–47.11%), chicken (30.63–40.83%) and freshwater fish (17.14–27.09%). Pork and beef with higher fat content were a key factor in facilitating the notable PCP bioaccessibility and bioavailability (p < 0.05). Further, the exposure of PCP to the population was significantly reduced by 42.70–98.46% after the consideration of bioaccessibility and bioavailability, with no potential health risk. It can improve the accuracy of risk assessment for PCP.
Changes in the Quality and Microbial Communities of Precooked Seasoned Crayfish Tail Treated with Microwave and Biological Preservatives during Room Temperature Storage
Authors: Wei Banghong , Gao Yan , Zheng Yao , Yu Jinxiang , Fu Xuejun , Bao Hairong , Guo Quanyou , Hu Huogen
Published: April 2024

The qualities of precooked foods can be significantly changed by the microorganisms produced during room temperature storage. This work assessed the effects of different antibacterial treatments (CK, without any treatment; microwave treatment, MS; microwave treatment and biological preservatives, MSBP) on the physicochemical properties and microbial communities of precooked crayfish tails during room temperature storage. Only the combination of microwave sterilization and biological preservatives significantly inhibited spoilage, as evidenced by the total viable count (4.15 log CFU/g) after 3 days of room temperature storage, which satisfied the transit time of most logistics companies in China. Changes in pH and TVB-N were also significantly inhibited in the MSBP group compared with those in the CK and MS groups. More than 30 new volatile compounds were produced in the CK groups during room temperature storage. However, in the MSBP groups, the volatile compounds were almost unchanged. The correlations between the microbial composition and volatile compounds suggested that specific bacterial species with metabolic activities related to amino acid, energy, cofactor, and vitamin metabolism, as well as xenobiotics biodegradation and metabolism, were responsible for the changes in volatile compounds. These bacteria included Psychrobacter, Arthrobacter, Facklamia, Leucobacter, Corynebacterium, Erysipelothrix, Devosia, Dietzia, and Acidovorax. Overall, our findings provide a foundation for the development of strategies to inhibit spoilage in precooked crayfish tails stored at room temperature.