bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolving Dispatching Rules in Improved BWO Heuristic Algorithm for Job-Shop Scheduling
Authors: Zhang Zhen , Jin Xin , Wang Yue
Published: July 2024

In this paper, an improved Beluga Whale Optimization algorithm based on data mining and scheduling rules with AdaBoost(IBWO-DDR-AdaBoost) rule heuristic scheduling method for solving job-shop scheduling problems (JSP) is proposed, in which data mining-extracted dispatching rules are incorporated into the heuristic algorithm to guide the optimization process. Firstly, an AdaBoost-CART integrated learning algorithm is introduced to evolve dispatching knowledge from historical data and convert it into effective dispatching rules. Secondly, in order to address the issues of local optimality and slow convergence speed faced by the beluga whale optimization algorithm (BWO) when solving JSP, this study presents an improved beluga whale optimization algorithm (IBWO) that incorporates two enhancement mechanisms: a neighborhood search strategy based on greedy thinking and genetic operators. These enhancements aim to improve both the efficiency and quality of reconciliation in scheduling, ultimately leading to better scheduling schemes. Furthermore, the extracted scheduling rules obtained through the AdaBoost-CART integrated learning algorithm are embedded into the improved beluga optimization algorithm, enabling real-time solution updates for optimized schedules. Finally, extensive simulation tests are conducted on JSP benchmark examples of varying scales with minimizing maximum completion time as the objective function for schedule optimization. The simulation results demonstrate the significant advantages of our proposed IBWO-DDR-AdaBoost rule heuristic scheduling method in terms of accuracy, performance optimization, and convergence speed.
RMBCC: A Replica Migration-Based Cooperative Caching Scheme for Information-Centric Networks
Authors: Chao Yichao , Ni Hong , Han Rui
Published: July 2024

How to maximize the advantages of in-network caching under limited cache space has always been a key issue in information-centric networking (ICN). Replica placement strategies aim to fully utilize cache resources by optimizing the location and quantity distribution of replicas in the network, thereby improving the performance of the cache system. However, existing research primarily focuses on optimizing the placement of replicas along the content delivery path, which cannot avoid the inherent drawback of not being able to leverage off-path cache resources. The proposals for off-path caching cannot effectively solve this problem as they introduce excessive complexity and cooperation costs. In this paper, we address the trade-off between cache resource utilization and cooperation costs by introducing a mechanism complementary to replica placement. Instead of redesigning a new caching strategy from scratch, we propose a proactive cooperative caching mechanism (called RMBCC) that involves an independent replica migration process, through which we proactively relocate replicas evicted from the local cache to neighboring nodes with sufficient cache resources. The cooperation costs are effectively controlled through migration replica filtering, migration distance limitation, as well as hop-by-hop migration request propagation. Extensive simulation experiments show that RMBCC can be efficiently integrated with different on-path caching strategies. Compared with representative caching schemes, RMBCC achieves significant improvements in evaluation metrics such as cache hit ratio and content retrieval time, while only introducing negligible cooperation overhead.
On the Asymmetry of Resistive Switching Transitions
Authors: Vinuesa Guillermo , García Héctor , Pérez Eduardo , Wenger Christian , Íñiguez-de-la-Torre Ignacio , González Tomás , Dueñas Salvador , Castán Helena
Published: July 2024

In this study, the resistive switching phenomena in TiN/Ti/HfO2/Ti metal–insulator–metal stacks is investigated, mainly focusing on the analysis of set and reset transitions. The electrical measurements in a wide temperature range reveal that the switching transitions require less voltage (and thus, less energy) as temperature rises, with the reset process being much more temperature sensitive. The main conduction mechanism in both resistance states is Space-charge-limited Conduction, but the high conductivity state also shows Schottky emission, explaining its temperature dependence. Moreover, the temporal evolution of these transitions reveals clear differences between them, as their current transient response is completely different. While the set is sudden, the reset process development is clearly non-linear, closely resembling a sigmoid function. This asymmetry between switching processes is of extreme importance in the manipulation and control of the multi-level characteristics and has clear implications in the possible applications of resistive switching devices in neuromorphic computing.
Automated Conversion of CVE Records into an Expert System, Dedicated to Information Security Risk Analysis, Knowledge-Base Rules
Authors: Benetis Dovydas , Vitkus Donatas , Janulevičius Justinas , Čenys Antanas , Goranin Nikolaj
Published: July 2024

Expert systems (ESs) can be seen as a perspective method for risk analysis process automation, especially in the case of small- and medium-sized enterprises that lack internal security resources. Expert system practical applicability is limited by the fact that the creation of an expert system knowledge base requires a lot of manual work. External knowledge sources, such as attack trees, web pages, and ontologies, are already proven to be valuable sources for the automated creation of knowledge base rules, thus leading to more effective creation of specialized expert systems. This research proposes a new method of automated conversion of CVE data from the National Vulnerability Database (version CVSS 2) into the knowledge base of an expert system and flags CVE records that have higher risk due to already existing exploit tools. This manuscript also contains a description of the method for implementing software and a practical evaluation of conversion results. The uniqueness of the proposed method is incorporation of the records included in the Cybersecurity and Infrastructure Security Agency (CISA) Known Exploited Vulnerabilities Catalog.
Mixed-Criticality Traffic Scheduling in Time-Sensitive Networking Using Multiple Combinatorial Packing Based on Free Time Domain
Authors: Zheng Ling , Zhang Keyao , Wei Guodong , Chu Hongyun
Published: July 2024

Time-sensitive networking (TSN) is considered an ideal solution to meet the transmission needs of existing industrial production methods. The traffic scheduling problem of TSN is an NP-hard problem. The traditional traffic scheduling algorithms can lead to issues such as significant computational time consumption and traffic congestion, which are not conducive to the rapid and high-quality deployment of TSN. To simplify the complexity of TSN schedule table generation, the paper studies the scheduling problem of mixed critical traffic in TSN. Using a combinatorial packing traffic scheduling algorithm based on unoccupied space (CPTSA-US), a scheduling table for TSN traffic transmission is generated, proving the feasibility of transforming the TSN traffic scheduling problem into a packing problem. In addition, the initial packing algorithm and traditional traffic scheduling algorithm can cause traffic accumulation, seriously affecting network performance. This paper proposes a mixed-critical traffic scheduling algorithm based on free time domain (MCTSA-FTD), which further partitions the packing space transformed by the time domain. And performs multiple packing of traffic based on the partitioned packing space and generates the TSN schedule table according to the reverse transformation of the packing results. The simulation results show that compared to the CPTSA-US and the traditional traffic scheduling solution algorithm SMT (Satisfiability Modulo Theory), the schedule table generated by the MCTSA-FTD significantly improves the delay, jitter, and packet loss of BE flows in the network while ensuring the transmission requirements of TT flows. This can effectively enhance the transmission performance of the network.
Hierarchical Cross-Modal Interaction and Fusion Network Enhanced with Self-Distillation for Emotion Recognition in Conversations
Authors: Wei Puling , Yang Juan , Xiao Yali
Published: July 2024

Emotion recognition in conversations (ERC), which aims to capture the dynamic changes in emotions during conversations, has recently attracted a huge amount of attention due to its importance in providing engaging and empathetic services. Considering that it is difficult for unimodal ERC approaches to capture emotional shifts in conversations, multimodal ERC research is on the rise. However, this still suffers from the following limitations: (1) failing to fully explore richer multimodal interactions and fusion; (2) failing to dynamically model speaker-dependent context in conversations; and (3) failing to employ model-agnostic techniques to eliminate semantic gaps among different modalities. Therefore, we propose a novel hierarchical cross-modal interaction and fusion network enhanced with self-distillation (HCIFN-SD) for ERC. Specifically, HCIFN-SD first proposes three different mask strategies for extracting speaker-dependent cross-modal conversational context based on the enhanced GRU module. Then, the graph-attention-based multimodal fusion (MF-GAT) module constructs three directed graphs for representing different modality spaces, implements in-depth cross-modal interactions for propagating conversational context, and designs a new GNN layer to address over-smoothing. Finally, self-distillation is employed to transfer knowledge from both hard and soft labels to supervise the training process of each student classifier for eliminating semantic gaps between different modalities and improving the representation quality of multimodal fusion. Extensive experimental results on IEMOCAP and MELD demonstrate that HCIFN-SD is superior to the mainstream state-of-the-art baselines by a significant margin.
Mitigating Adversarial Attacks against IoT Profiling
Authors: Neto Euclides Carlos Pinto , Dadkhah Sajjad , Sadeghi Somayeh , Molyneaux Heather
Published: July 2024

Internet of Things (IoT) applications have been helping society in several ways. However, challenges still must be faced to enable efficient and secure IoT operations. In this context, IoT profiling refers to the service of identifying and classifying IoT devices’ behavior based on different features using different approaches (e.g., Deep Learning). Data poisoning and adversarial attacks are challenging to detect and mitigate and can degrade the performance of a trained model. Thereupon, the main goal of this research is to propose the Overlapping Label Recovery (OLR) framework to mitigate the effects of label-flipping attacks in Deep-Learning-based IoT profiling. OLR uses Random Forests (RF) as underlying cleaners to recover labels. After that, the dataset is re-evaluated and new labels are produced to minimize the impact of label flipping. OLR can be configured using different hyperparameters and we investigate how different values can improve the recovery procedure. The results obtained by evaluating Deep Learning (DL) models using a poisoned version of the CIC IoT Dataset 2022 demonstrate that training overlap needs to be controlled to maintain good performance and that the proposed strategy improves the overall profiling performance in all cases investigated.
Virtual Energy Storage System Scheduling for Commercial Buildings with Fixed and Dynamic Energy Storage
Authors: Brhane Grmay Yordanos , Oh Eunsung , Son Sung-Yong
Published: July 2024

This study presents a virtual energy storage system (VESS) scheduling method that strategically integrates fixed and dynamic energy storage (ES) solutions to optimize energy management in commercial buildings. Fixed ES, such as batteries, provides stable flexibility but is expensive and can be inefficiently operated. In contrast, dynamic ES can be utilized as needed but requires validation of their flexibility. By combining fixed ES with dynamic ES utilizing vehicle-to-grid (V2G) capabilities, this approach enhances grid stability and manages energy costs more effectively. Empirical validation using real-world data from Korea demonstrates significant improvements in total net benefits by reducing energy costs, which are crucial for the economic sustainability of commercial energy use. Additionally, the analysis of Pearson’s linear correlation coefficient with demand identifies where benefits occur in the scheduling process. The integrated system reduces the need for costly upgrades to the utility grid, suggesting a strategic advantage for large-scale adoption. This study establishes a framework for the broader implementation of such integrated systems, highlighting the potential for substantial improvements in energy efficiency, reduced carbon emissions, and enhanced grid reliability.
Hydrogeological and Mining Considerations in the Design of a Pumping Station in a Shaft of a Closed Black Coal Mine
Authors: d’Obyrn Kajetan , Kamiński Paweł , Cień Damian , Jendrysik Sebastian , Prostański Dariusz
Published: July 2024

In an overwhelming number of cases, the closure of a coal mine in Poland, for safety reasons, requires the installation of a pumping station and systems for the drainage of inflowing water due to its connection via roadways, goaves, or water-leaking pillars with other adjacent active mines. Due to operational costs, stationary pumping stations are being replaced with submersible pumping stations, wherever the geological/mining conditions allow this. The key factors to be considered when designing a submersible pumping station include the estimated water influx and the storage and emergency reservoir fill-up time. If the water level in the emergency reservoir exceeds the level of the maximum ordinate, there is the risk of water flooding an adjacent active mine, which poses a serious safety risk to this mine. A pumping station design must ensure that water can be pumped out also in emergency situations and must ensure permanent control over the level of the water table. The pumped-out water, after potential treatment, can be utilized as technological water in industrial plants. In the designed pumping station, it is also feasible to establish underground pumped-storage hydropower. This would enable the storage of energy from renewable sources, thereby contributing to CO2 emission reduction.
Assessment of the Use of Carbon Capture and Storage Technology to Reduce CO2 Emissions from a Natural Gas Combined Cycle Power Plant in a Polish Context
Authors: Garcés Lucia F. Pérez , Sztekler Karol , Azevedo Leonardo , Boruta Piotr , Bujok Tomasz , Radomska Ewelina , Mlonka-Mędrala Agata , Mika Łukasz , Chmielniak Tomasz
Published: July 2024

This study investigates the crucial role of Carbon Capture and Storage (CCS) technology in mitigating CO2 emissions from Poland’s power systems, which is essential not only for meeting climate targets but also for maintaining energy security in the country. Acknowledging natural gas as a transitional fuel, the focus is on evaluating the decarbonization potential of the natural gas combined cycle (NGCC) power plant. The NGCC with and without an amine-based carbon capture unit was modeled using IPSEpro (SimTech, version 7.0). It was found that the annual CO2 emission from 435.68 MWe (net) NGCC can be reduced from 1,365,501 tons (357.8 kgCO2/MWh) to 136,556 tons (42.9 kgCO2/MWh). On the other hand, the CCS reduced the net electric power of the NGCC from 435.68 MW to 363.47 MW and the net energy efficiency from 55.60% to 46.39%. Nonetheless, these results demonstrate the potential of using the amine-based CO2 capture technology in NGCC systems. This is especially important in the context of the decarbonization of the Polish power system.
Pelican Optimization Algorithm-Based Proportional–Integral–Derivative Controller for Superior Frequency Regulation in Interconnected Multi-Area Power Generating System
Authors: Sagor Abidur Rahman , Talha Md Abu , Ahmad Shameem , Ahmed Tofael , Alam Mohammad Rafiqul , Hazari Md. Rifat , Shafiullah G. M.
Published: July 2024

The primary goal of enhancing automatic generation control (AGC) in interconnected multi-area power systems is to ensure high-quality power generation and reliable distribution during emergencies. These systems still struggle with consistent stability and effective response under dynamic load conditions despite technological advancements. This research introduces a secondary controller designed for load frequency control (LFC) to maintain stability during unexpected load changes by optimally tuning the parameters of a Proportional–Integral–Derivative (PID) controller using pelican optimization algorithm (POA). An interconnected power system for ith multi-area is modeled in this study; meanwhile, for determining the optimal PID gain settings, a four-area interconnected power system is developed consisting of thermal, reheat thermal, hydroelectric, and gas turbine units based on the ith area model. A sensitivity analysis was conducted to validate the proposed controller’s robustness under different load conditions (1%, 2%, and 10% step load perturbation) and adjusting nominal parameters (R, Tp, and Tij) within a range of ±25% and ±50%. The performance response indicates that the POA-optimized PID controller achieves superior performance in frequency stabilization and oscillation reduction, with the lowest integral time absolute error (ITAE) value showing improvements of 7.01%, 7.31%, 45.97%, and 50.57% over gray wolf optimization (GWO), Moth Flame Optimization Algorithm (MFOA), Particle Swarm Optimization (PSO), and Harris Hawks Optimization (HHO), respectively.
Harvesting Sunlight: The Promise of Agro-Photovoltaic Fusion Systems for Sustainable Agriculture and Renewable Energy Generation
Authors: Bojnec Štefan , Daraz Umar , Khan Younas
Published: July 2024

Utilizing the power of sunlight through agro-photovoltaic fusion systems (APFSs) seamlessly blends sustainable agriculture with renewable energy generation. This innovative approach not only addresses food security and energy sustainability but also plays a pivotal role in combating climate change. This study assesses the feasibility and impact of APFS implementation in District Dir Lower, Pakistan, a region significant for its agriculture and energy needs. A quasi-experimental design was employed, comparing outcomes between a treatment group (with an APFS) and a control group (without an APFS). Stratified random sampling was used to select 400 participants, including farmers, residents, local authorities, and community leaders. Data were collected using structured questionnaires and analyzed employing paired t-tests, linear regression, analysis of variance (ANOVA), and Chi-square tests. The results show that the treatment group with an APFS exhibited significant improvements in farming practices (mean change = 4.20 vs. 2.80). Linear regression indicated a strong positive effect of APFSs on renewable energy production. The ANOVA results demonstrated significant mitigation of environmental challenges, and the Chi-square test showed a strong association between APFS implementation and community sustainability, resilience, and prosperity. It is concluded that APFS implementation significantly enhances farming practices, renewable energy production, and environmental sustainability, contributing to the resilience and prosperity of agricultural communities in District Dir Lower. These findings advocate for the broader adoption of APFSs in similar contexts to integrate sustainable agriculture with renewable energy generation.
Optimization of Torrefaction Parameters Using Metaheuristic Approach
Authors: Dhaundiyal Alok , Toth Laszlo
Published: July 2024

The probabilistic technique was used to optimize the torrefaction parameters that indirectly influence the yield of end-products obtained through the pyrolysis of biomass. In the same pursuit, pine cones underwent thermal pre-treatment at 210 °C, 220 °C, 230 °C, 240 °C, and 250 °C in the presence of N2 gas with a flowing rate of 0.7 L∙s−1, whereas the duration of the pre-treatment process was 5 min, 10 min, and 15 min at each. To facilitate the processing of pine waste, a muffle furnace was improvised for pilot-scale testing. The thermal process used to carry out torrefaction was quasi-static. The average dynamic head of volatile gases inside the chamber was 1.04 m. The criteria for determining the optimal solution were based on calorific value, solid yield, energy consumption during the pre-treatment process, and ash handling. In absolute terms, time and temperature did not influence the statistical deviation in cellulose and hemicellulose decomposition after thermal pre-treatment. While considering ash content as a primal factor, thermal processing should be conducted for 5 min at 210 °C for the bounded operating conditions, which are similar to the operating conditions obtained experimentally. The optimal solid yield would be obtained if the thermal pre-treatment is performed at 250 °C for 5 min. The solution derived through a simulated annealing technique provided a better convergence with the experimental dataset.
CO2 Corrosion of Downhole Sand Control Screen: Experiments, Model, and Application
Authors: Zhou Bo , Dong Changyin , Li Xiaobo , Bai Haobin , Yin Bin , Li Huaiwen , Shen Kaixiang
Published: July 2024

Under simulated conditions typical of a high-temperature, high-pressure (HTHP) oil and gas reservoir in the South China Sea, dynamic corrosion evaluation experiments were performed on a three-layer screen structure and three types of sand retaining media. The results showed significant variations in corrosion morphology and rates among different screen components and materials. Corrosion products on the base pipe accumulated as cubic crystals, while the protective shroud showed surface needle-like corrosion products. Sand retaining media exhibited “coiled wire” corrosion products with cubic accumulations along seam edges. The 316L media showed a high corrosion risk, especially at temperatures between 140–150 °C. As CO2 partial pressure increased, corrosion rates generally rose. A new predictive method was developed to assess and compare the corrosion resistance and life of screens, achieving a compliance rate of over 90%. This method supports evaluating the corrosion life of screens in HTHP environments. For a typical well in the South China Sea gas field with 4% CO2, there is a high risk of screen corrosion. The screen media was identified as a failure site with a minimum corrosion life of about 5 years, while the protective shroud’s life was estimated at 11–12 years.
A Feasible Region-Based Evaluation Method for the Renewable Energy Hosting Capacity with Frequency Security Constraints
Authors: Zhang Zhi , Zhao Haibo , Ran Qingyue , Wang Yao , Yu Juan , Liu Hongli , Duan Hui
Published: July 2024

As renewable energy becomes more widespread, the uncertainty of its output poses serious challenges for peak and frequency regulation of the power system. Evaluating a grid’s capacity to integrate renewable energy sources can provide an early-warning and decision-making basis for grid operation and scheduling. This paper presents a method for evaluating the hosting capacity of renewable energy, considering frequency security constraints. Introducing the system frequency nadir constraint into a system ensures that the frequency does not drop to a dangerous level in the event of power disturbances. The analytical characterization relation equation for the system frequency nadir constraint is constructed based on polynomial chaos expansion (PCE) theory. Furthermore, with the goal of minimizing the reduction in renewable energy, considering multiple flexible resources, like demand response (DR), Combined Heat and Power (CHP), energy storage, and Power-to-Gas (P2G), a renewable energy hosting capacity evaluation model that considers frequency security and flexibility resources is established. Finally, based on the concept of the feasible region, the maximum hosting capacity of a system’s renewable energy is visualized using the progressive vertex enumeration method. It identifies the safe operating region for renewable energy output that meets the safety constraints of power grid operations. The simulation results were validated using a modified IEEE 39 bus system.
Comparative and Phylogenetic Analysis of Six New Complete Chloroplast Genomes of Rubus (Rosaceae)
Authors: Shi Yujie , Chen Zhen , Jiang Jingyong , Li Xiaobai , Zeng Wei
Published: July 2024

Rubus includes a group of important plants with medicinal and culinary significance, as well as ornamental value. However, due to its status as one of the largest genera in the Rosaceae family and frequent occurrences of apomixis, hybridization, and polyploidy among its species, the morphological identification of this genus is highly challenging. The plastid genome serves as a valuable tool for studying the evolutionary relationships among plants. Therefore, based on the raw data of the whole genomes from six popular Rubus taxa, the complete Cp genomes were assembled, annotated, and subjected to comparative and phylogenetic analyses. In this research, six newly complete Cp genomes were reported, which all had a representative quadripartite formation, with a similar GC content (37.06%–37.26%), and their size ranged from 155,493 bp to 156,882 bp. They all encode 111 unique genes, containing 79 PCGs, 28 tRNA, and 4 rRNA. The analysis of gene structure of different groups showed that the sequence and content of genes were relatively conservative, and there was no gene rearrangement. Most of their PCGs had a high frequency codon usage bias and all genes were in purifying selection states. A nucleotide variable analysis revealed that the IR areas had less variation than the SC areas, and there was the greatest diversity in the SSC area. Eleven hypervariable areas were identified, containing rpl32-trnL, rpl32, rps16-trnQ, trnT-trnL, trnQ-psbK, trnK-rps16, and rps15-ycf1, which could be used as labels for genetic diversity and taxa identification. The phylogenetic trees of 72 Rosaceae plants were constructed based on ML and BI methods. The results strongly support the theory that the Rubus genus was a monophyletic group and sampled species could be arranged into seven subgenera. Overall, this study sheds its new light into the phylogeny of the Rubus genus, providing valuable insights for future studies of the Cp genomes from the expanded taxa of the Rosaceae family.
Elite Genotype Characterization and Genetic Structure Analysis of the Medicinal Tree Archidendron clypearia (Jack) I. C. Nielsen Using Microsatellite Markers
Authors: Li Dandan , Gan Siming , Weng Qijie , Zhou Mingming , Zhou Changpin , Li Mei
Published: July 2024

Archidendron clypearia (Jack) I. C. Nielsen is an important tree species for traditional medicine purposes such as anti-inflammatory, detoxification, uric acid control and neuro-protection. Here, a set of 15 microsatellite markers were used to fingerprint 248 elite genotypes from six origins of A. clypearia and investigate the genetic structure of these genotypes. A total of 170 alleles were amplified. The elite genotypes showed moderate genetic variability, with mean observed heterozygosity (Ho) and expected heterozygosity (He) being 0.651 and 0.699, respectively. Each of the elite genotypes could be fingerprinted uniquely. The cumulative probability of identity (PI) and the cumulative probability of paternity exclusion (PE) were 2.25 × 10−12 and 0.999992, respectively, demonstrating the extremely high power of the markers for genotype identification. In STRUCTURE and clustering analyses, the same origin of elite genotypes tended to be grouped in a sub-population and clustered closely, but some genotypes from different geographic origins were mixed, suggesting a low level of genetic differentiation between the origins. These results can contribute to the protection and management of the elite genotype resources of A. clypearia and the comprehensive understanding of its genetic structure.
Mechanism of the Effects of Phyllostachys edulis Invasion on the Soil Microbial Community in Quercus acutissima Forests
Authors: Fang Lu , Hu Haibo , Chen Jianyu , Gong Yuyang , Zhu Ziyi
Published: July 2024

In recent years, the invasion of Phyllostachys edulis has intensified. This study selected Phyllostachys edulis, Phyllostachys edulis–Quercus acutissima mixed and Quercus acutissima forest areas and analyzed the changes in soil bulk density, porosity, water-holding capacity, pH, soil organic carbon (SOC), soil readily oxidized organic carbon (ROC), soluble organic carbon (DOC) and microbial biomass carbon (SMBC). Then, we obtained the Chao index, Shannon index and Simpson index and analyzed the relationship between microbial α diversity, β diversity and community composition, abundance and structure and between microbial community changes and environmental factors. The results showed that soil with the invasion of Phyllostachys edulis, soil pH, water content, capillary water capacity and total porosity of surface soil increased significantly by 4.35%, 18.71%, 16.37% and 14.56%, respectively, compared with the Quercus acutissima forest, while soil bulk density, organic carbon, microbial biomass carbon and soluble organic carbon decreased significantly by 7.27%, 18.43%, 61.12% and 61.90%. Soil readily oxidized organic carbon decreased at first and then increased. The soil community richness and diversity of the Phyllostachys edulis forest were significantly greater than those of the other two stands. Soil pH and organic carbon content were the main factors affecting the changes in the soil microbial community. Therefore, the invasion of Phyllostachys edulis improved soil water retention, while soil pH had the greatest effect on the microbial community, followed by soil bulk density and organic carbon, and water content had the smallest effect.
Optimizing the Preparation Process of Bamboo Scrimber with Bamboo Waste Bio-Oil Phenolic Resin Using Response Surface Methodology
Authors: Li Ying , Li Chunmiao , Ren Xueyong , Chen Fuming , Chen Linbi
Published: July 2024

Bamboo scrimber is a new type of biomass fiber-based composite material with broad application. In this study, self-developed bio-oil phenolic resin (BPF) was used to prepare bamboo scrimber. The effects of hot-pressing temperature, hot-pressing time, and BPF resin solid content on the modulus of rupture (MOR) and modulus of elasticity (MOE) were systematically investigated through single-factor experiments and response surface methodology (RSM). According to the Box-Behnken design (BBD) experiment of the RSM, the effects of all three factors on MOR and MOE are significant. The effects of the main factors affecting the MOR and MOE decreased in the order of resin solid content, hot-pressing temperature, and hot-pressing time. Based on BBD, the optimal conditions for the preparation of bamboo scrimber were determined as follows: a hot-pressing temperature of 150 °C, a hot-pressing time of 27.5 min, and a resin solid content of 29%. Under these conditions, the MOR is 150.05 MPa and the MOE is 12,802 MPa, which are close to the theoretical values, indicating that the optimization results are credible. This study helps to promote the full utilization of bamboo components and provides a reference for the development of high-quality bamboo scrimber.
TWIN-ADAPT: Continuous Learning for Digital Twin-Enabled Online Anomaly Classification in IoT-Driven Smart Labs
Authors: Gupta Ragini , Tian Beitong , Wang Yaohui , Nahrstedt Klara
Published: July 2024

In the rapidly evolving landscape of scientific semiconductor laboratories (commonly known as, cleanrooms), integrated with Internet of Things (IoT) technology and Cyber-Physical Systems (CPSs), several factors including operational changes, sensor aging, software updates and the introduction of new processes or equipment can lead to dynamic and non-stationary data distributions in evolving data streams. This phenomenon, known as concept drift, poses a substantial challenge for traditional data-driven digital twin static machine learning (ML) models for anomaly detection and classification. Subsequently, the drift in normal and anomalous data distributions over time causes the model performance to decay, resulting in high false alarm rates and missed anomalies. To address this issue, we present TWIN-ADAPT, a continuous learning model within a digital twin framework designed to dynamically update and optimize its anomaly classification algorithm in response to changing data conditions. This model is evaluated against state-of-the-art concept drift adaptation models and tested under simulated drift scenarios using diverse noise distributions to mimic real-world distribution shift in anomalies. TWIN-ADAPT is applied to three critical CPS datasets of Smart Manufacturing Labs (also known as “Cleanrooms”): Fumehood, Lithography Unit and Vacuum Pump. The evaluation results demonstrate that TWIN-ADAPT’s continual learning model for optimized and adaptive anomaly classification achieves a high accuracy and F1 score of 96.97% and 0.97, respectively, on the Fumehood CPS dataset, showing an average performance improvement of 0.57% over the offline model. For the Lithography and Vacuum Pump datasets, TWIN-ADAPT achieves an average accuracy of 69.26% and 71.92%, respectively, with performance improvements of 75.60% and 10.42% over the offline model. These significant improvements highlight the efficacy of TWIN-ADAPT’s adaptive capabilities. Additionally, TWIN-ADAPT shows a very competitive performance when compared with other benchmark drift adaptation algorithms. This performance demonstrates TWIN-ADAPT’s robustness across different modalities and datasets, confirming its suitability for any IoT-driven CPS framework managing diverse data distributions in real time streams. Its adaptability and effectiveness make it a versatile tool for dynamic industrial settings.
Direct Feedback Regulation of E2, T, and hCG in the Brain–Pituitary–Gonad Axis of Japanese Eel (Anguilla japonica) during Artificial Maturation
Authors: Lai Xiaojian , Peng Shuai , Bai Zhaoren , Cao Le , Huang Huixuan , Jiang Yonghua , Wang Yilei
Published: July 2024

The feedback regulatory effects of estrogen (E2) and androgen (T) on the gonadotropin-releasing hormone (GnRH) and gonadotropin (GtH) within the brain–pituitary–gonad (BPG) axis in eels with undeveloped ovaries were investigated through in vivo studies. However, the regulatory role of the BPG axis only became apparent during ovary development in the migratory stage. To further elucidate the direct feedback regulation of the BPG axis, female Anguilla japonica underwent artificial induction of vitellogenesis, and the regulation of BPG axis tissues by GtH (human chorionic gonadotropin, hCG), E2, and T was explored through in vitro exposure. The mRNA expression levels of GnRH (mGnRH), GtH (fshb and lhb), and steroid biosynthesis enzymes (cyp11a1, hsd3b, cyp17a1, and cyp17a2) in the diencephalon, pituitary, and ovary, respectively, were determined. The results showed that the expression level of mGnRH in the diencephalon was significantly downregulated by 0.1 IU/mL hCG but upregulated by both 1 nM E2 and higher concentrations of T, suggesting a direct positive feedback regulation of E2 on mGnRH. In the pituitary, the expression levels of fshb and lhb were upregulated by E2, while fshb was suppressed by T. In the ovaries, the expression of cyp11a1 and hsd3b was upregulated by 1 nM E2, whereas T exposure resulted in an opposite effect. Cyp17a1 mRNA levels did not differ significantly with E2 treatment but were upregulated by 1 nM T. These findings suggest that low concentrations of E2 exhibited positive feedback regulation on all three levels (diencephalon, pituitary, and ovary) of the BPG axis, while T showed weaker and differential feedback regulation in BPG axis tissues. Overall, this study’s results revealed the direct feedback regulation of hCG, E2, and T on the BPG axis in eels, a phylogenetic base of teleosts.
A Microbiological and Sensory Evaluation of Modified Atmosphere-Packed (MAP) Chicken at Use-By Date and Beyond
Authors: Söderqvist Karin , Peterson Max , Johansson Marcus , Olsson Viktoria , Boqvist Sofia
Published: July 2024

Consumers are responsible for a large proportion of food waste, and food that has reached its use-by or best-before date is often discarded, even if edible. In this study on fresh chicken, the suitability of use-by dates currently used in the EU was evaluated by using microbial and sensory analyses. This was carried out by analyzing bacterial populations of chicken breast fillets (M. pectoralis major) at three different time points (use-by date, 2 days past use-by date, 4 days past use-by date) and two different storage temperatures (4 °C, 8 °C). A discrimination triangle test was performed to check for sensory differences between chicken breast fillets cooked at the three selected time points for both storage temperatures. A consumer preference test was also performed for chicken breast fillets that had been stored at the highest recommended temperature (4 °C) and after being cooked at the three time points. Changes in populations of total aerobic count (TAC), Enterobacteriaceae (EB), and lactic acid bacteria (LAB) were recorded over time. Despite large differences in bacterial counts at the selected time points, with TAC populations of approximately 6.5 and 8.0 log CFU/g at use-by date and four days after use-by date, respectively, storage for two or four extra days had no significant effect on the sensory parameters of cooked chicken compared with chicken consumed at its use-by date. Since the TAC populations were close to or above levels that are associated with spoilage, more work is needed to explore if shelf life can be extended.
Visual Loop-Mediated Isothermal Amplification (LAMP) Assay for Rapid On-Site Detection of Escherichia coli O157: H7 in Milk Products
Authors: Cui Shuangshuang , Wei Yong , Li Can , Zhang Jian , Zhao Yunfeng , Peng Xiayu , Sun Fengxia
Published: July 2024

(1) Background: Rapid on-site testing is an effective method for the detection of Escherichia coli O157: H7(E. coli O157: H7) in food ingredients and the environment. (2) Methods: In this study, we developed colorimetric loop-mediated isothermal amplification (LAMP) and immunochromatographic test strips (ICTs) for the rapid and visual detection of E. coli O157: H7. This study designed new specific LAMP primers for E. coli O157: H7 virulence island genes. After the LAMP amplification, the double-stranded DNA target sequence labeled with digoxin and fluorescein isothiocyanate (FITC) at both ends was bound to the anti-digoxin antibody on the gold nanoparticles. Subsequently, it was further bound to the anti-FITC antibody at the T line of the ICTs, forming a positive test result. Hydroxynaphthyl blue dye was directly added to the LAMP amplification product. A blue color indicated positive results, while a purple color indicated negative results. (3) Results: Two visualization methods showed high specificity for the target strains. The visualization tests had sensitivities of 5.7 CFU mL−1, and the detection limit of the Escherichia coli O157: H7 in artificially contaminated milk samples was 5.7 × 102 CFU mL−1, which was consistent with the results of the standard method (LAMP-electrophoresis method) used in commercial inspection. (4) Conclusions: Both methods could be useful in remote and under-resourced areas.
Degradable Gel for Temporary Plugging in High Temperature Reservoir and Its Properties
Authors: Yang Fan , Liu Jinhua , Ji Renjing , Yu Xiaorong , Yang Huan , Su Gaoshen
Published: July 2024

Although various degradable gel materials have been developed for temporary plugging in oil fields, they often degrade too quickly in high-temperature environments. To address this issue, an unstable crosslinker was synthesized to prepare a high-temperature degradable gel. This gel does not degrade excessively fast at high temperatures. Temperature and crosslinker concentration are the primary factors influencing gel degradation time, followed by monomer and initiator concentrations. Increased temperature and decreased crosslinker concentration both reduce degradation time, which can be adjusted within the range of 90–130 °C by varying the crosslinker concentration. The molecular structure and thermal stability of the degradable gel were analyzed using FTIR, 13C NMR, and TG. Furthermore, the viscoelastic properties, compressive performance, plugging performance, and core damage performance of the gel were evaluated. Within the test range of 0.1–1000 Pa, the storage modulus is higher than the loss modulus. The gel prepared at 130 °C exhibited a compressive stress of 0.25 MPa at 50% strain. The plugging pressure of the gel in sand-filled tubes with varying permeabilities (538.2–2794.1 mD) exceeded 15 MPa while maintaining a core damage rate below 5%. SEM analysis indicated that the degradation mechanism of the gel may involve the collapse of its three-dimensional network structure due to the hydrolysis of amide groups in the crosslinker. The viscosity of the degradation liquid was below 11 mPa·s, enabling it to be brought back to the surface with the formation fluid without the need for further breaking operations.
Predicting Outcomes in Frail Older Community-Dwellers in Western Australia: Results from the Community Assessment of Risk Screening and Treatment Strategies (CARTS) Programme
Authors: Clarnette Roger M. , Kostov Ivan , Ryan Jill P. , Svendrovski Anton , Molloy D. William , O’Caoimh Rónán
Published: July 2024

Understanding risk factors for frailty, functional decline and incidence of adverse healthcare outcomes amongst community-dwelling older adults is important to plan population-level health and social care services. We examined variables associated with one-year risk of institutionalisation, hospitalisation and death among patients assessed in their own home by a community-based Aged Care Assessment Team (ACAT) in Western Australia. Frailty and risk were measured using the Clinical Frailty Scale (CFS) and Risk Instrument for Screening in the Community (RISC), respectively. Predictive accuracy was measured from the area under the curve (AUC). Data from 417 patients, median 82 ± 10 years, were included. At 12-month follow-up, 22.5% (n = 94) were institutionalised, 44.6% (n = 186) were hospitalised at least once and 9.8% (n = 41) had died. Frailty was common, median CFS score 6/9 ± 1, and significantly associated with institutionalisation (p = 0.001), hospitalisation (p = 0.007) and death (p < 0.001). Impaired activities of daily living (ADL) measured on the RISC had moderate correlation with admission to long-term care (r = 0.51) and significantly predicted institutionalisation (p < 0.001) and death (p = 0.01). The RISC had the highest accuracy for institutionalisation (AUC 0.76). The CFS and RISC had fair to good accuracy for mortality (AUC of 0.69 and 0.74, respectively), but neither accurately predicted hospitalisation. Home assessment of community-dwelling older patients by an ACAT in Western Australia revealed high levels of frailty, ADL impairment and incident adverse outcomes, suggesting that anticipatory care planning is imperative for these patients.
Layout Optimization of Logistics and Warehouse Land Based on a Multi-Objective Genetic Algorithm—Taking Wuhan City as an Example
Authors: Li Haijun , Zhou Jie , Niu Qiang , Feng Mingxiang , Zhou Dongming
Published: July 2024

With the rapid development of the logistics industry, the demand for logistics activities is increasing significantly. Concurrently, growing urbanization is causing the space for logistics and warehousing to become limited. Thus, more and more attention is being paid to the planning and construction of logistics facilities. However, due to spatiotemporal trajectory data (such as truck GPS data) being used less often in planning, the method of quantitative analysis for freight spatiotemporal activity is limited. Thus, the spatial layout of logistics and warehousing land does not match the current demand very well. In addition, it is necessary to consider the interactive relationship with the urban built environment in the process of optimizing layout, in order to comprehensively balance the spatial coupling with the functions of housing, transportation, industry, and so on. Therefore, the layout of logistics and warehouse land could be treated as a multi-objective optimization problem. This study aims to establish a model for logistics and warehouse land layout optimization to achieve a supply–demand matching. The proposed model comprehensively considers economic benefits, time benefits, cost benefits, environmental benefits, and other factors with freight GPS data, land-use data, transportation network data, and other multi-source data. A genetic algorithm is built to solve the model. Finally, this study takes the Wuhan urban development area as an example to practice the proposed method in three scenarios in order to verify its effectiveness. The results show that the optimization model solves the problem of mismatch between the supply and demand of logistics spaces to a certain extent, demonstrating the efficiency and scientificity of the optimization solutions. Based on the results of the three scenarios, it is proven that freight activities could effectively enhance the scientific validity of the optimization solution and the proposed model could optimize layouts under different scenario requirements. In summary, this study provides a practical and effective tool for logistics- and warehouse-land layout evaluation and optimization for urban planners and administrators.
Counting Conditions on Newborn Bloodspot Screening Panels in Australia and New Zealand
Authors: Heather Natasha , Greaves Ronda F. , Bhattacharya Kaustuv , Greed Lawrence , Pitt James , Siu Carol Wai-Kwan , de Hora Mark , Price Ricky , Ranieri Enzo , Wotton Tiffany , Webster Dianne
Published: July 2024

A greater number of screened conditions is often considered to equate to better screening, whereas it may be due to conditions being counted differently. This manuscript describes a harmonised Australasian approach to listing target conditions found on bloodspot screening panels. Operational definitions for target disorders and incidental findings were developed and applied to disorder lists. A gap analysis was performed between five, state-based Australian newborn screening programme disorder lists and the single national New Zealand and state-level Californian versions. Screening panels were found to be broadly similar. Gap analysis with Californian data reflected differences in jurisdictional approval (for example, haemoglobinopathies and lysosomal disorders not being recommended in Australasia). Differences amongst Australasian panels reflected varied the timeframes recommended in order to implement newly approved disorders, as well as decisions to remove previously screened disorders. A harmonised approach to disorder counting is essential to performing valid comparisons of newborn bloodspot screening panels.