bluuebunny/crossref_metadata_2025 huggingface dataset:
Vibration Rather than Microgravity Affects Bone Metabolism in Adult Zebrafish Scale Model
Authors: Carnovali Marta , Zava Stefania , Banfi Giuseppe , Rizzo Angela Maria , Mariotti Massimo
Published: March 2024

Gravity and mechanical forces cause important alterations in the human skeletal system, as demonstrated by space flights. Innovative animal models like zebrafish embryos and medaka have been introduced to study bone response in ground-based microgravity simulators. We used, for the first time, adult zebrafish in simulated microgravity, with a random positioning machine (RPM) to study bone remodeling in the scales. To evaluate the effects of microgravity on bone remodeling in adult bone tissue, we exposed adult zebrafish to microgravity for 14 days using RPM and we evaluated bone remodeling on explanted scales. Our data highlight bone resorption in scales in simulated microgravity fish but also in the fish exposed, in normal gravity, to the vibrations produced by the RPM. The osteoclast activation in both rotating and non-rotating samples suggest that prolonged vibrations exposure leads to bone resorption in the scales tissue. Stress levels in these fish were normal, as demonstrated by blood cortisol quantification. In conclusion, vibrational mechanical stress induced bone resorption in adult fish scales. Moreover, adult fish as an animal model for microgravity studies remains controversial since fish usually live in weightless conditions because of the buoyant force from water and do not constantly need to support their bodies against gravity.
Brain-Derived Neurotrophic Factor (BDNF) Enhances Osteogenesis and May Improve Bone Microarchitecture in an Ovariectomized Rat Model
Authors: Park Eugene J. , Truong Van-Long , Jeong Woo-Sik , Min Woo-Kie
Published: March 2024

Background: Brain-derived neurotrophic factor (BDNF) has gained attention as a therapeutic agent due to its potential biological activities, including osteogenesis. However, the molecular mechanisms involved in the osteogenic activity of BDNF have not been fully understood. This study aimed to investigate the action of BDNF on the osteoblast differentiation in bone marrow stromal cells, and its influence on signaling pathways. In addition, to evaluate the clinical efficacy, an in vivo animal study was performed. Methods: Preosteoblast cells (MC3T3-E1), bone marrow-derived stromal cells (ST2), and a direct 2D co-culture system were treated with BDNF. The effect of BDNF on cell proliferation was determined using the CCK-8 assay. Osteoblast differentiation was assessed based on alkaline phosphatase (ALP) activity and staining and the protein expression of multiple osteoblast markers. Calcium accumulation was examined by Alizarin red S staining. For the animal study, we used ovariectomized Sprague-Dawley rats and divided them into BDNF and normal saline injection groups. MicroCT, hematoxylin and eosin (H&E), and tartrate-resistant acid phosphatase (TRAP) stain were performed for analysis. Results: BDNF significantly increased ALP activity, calcium deposition, and the expression of osteoblast differentiation-related proteins, such as ALP, osteopontin, etc., in both ST-2 and the MC3T3-E1 and ST-2 co-culture systems. Moreover, the effect of BDNF on osteogenic differentiation was diminished by blocking tropomyosin receptor kinase B, as well as inhibiting c-Jun N-terminal kinase and p38 MAPK signals. Although the animal study results including bone density and histology showed increased osteoblastic and decreased osteoclastic activity, only a portion of parameters reached statistical significance. Conclusions: Our study results showed that BDNF affects osteoblast differentiation through TrkB receptor, and JNK and p38 MAPK signal pathways. Although not statistically significant, the trend of such effects was observed in the animal experiment.
Health-Related Quality of Life in Relation to Health Behaviour Patterns among Canadian Children
Authors: Wu Xiuyun , Ohinmaa Arto , Veugelers Paul J. , Maximova Katerina
Published: March 2024

Poor health behaviours in childhood, including sedentary behaviour, low physical activity levels, inadequate sleep, and unhealthy diet, are established risk factors for both chronic diseases and mental illness. Scant studies have examined the importance of such health behaviour patterns for health-related quality of life (HRQoL). This study aimed to examine the association of health behaviour patterns with HRQoL among Canadian children. Data from 2866 grade five students were collected through a provincially representative school-based survey of the 2014 Raising Healthy Eating and Active Living Kids in Alberta study. Latent class analysis was used to identify health behaviour patterns based on 11 lifestyle behaviours: sedentary behaviour (using a computer, playing video games, watching TV), physical activity (with and without a coach), sleep (bedtime on weekdays and weekends), and diet (fruit and vegetables intake, grain products, milk and alternatives, meat and alternatives). Multivariable multilevel logistic regression was applied to examine the associations of health behaviour patterns with HRQoL. Three groupings with distinct health behaviour patterns were identified: the first grouping (55%) is characterized by relatively healthy levels of sedentary behaviour, physical activity, and sleep, but a less healthy diet (“activity-focused” group). The second grouping (24%) is characterized by a relatively healthy diet, but moderately healthy levels of sedentary behaviour, physical activity, and sleep (“diet-focused” group). The third grouping (21%) is characterized by mostly unhealthy behaviours (“not health-focused” group). Students in the third and second groupings (“not health-focused” and “diet-focused”) were more likely to report lower HRQoL relative to students in the first grouping (“activity-focused”). The findings suggest that health promotion strategies may be more effective when considering the patterns of health behaviours as distinct targets in the efforts to improve HRQoL. Future research should include prospective observational and intervention studies to further elucidate the relationship between health behaviour patterns and HRQoL among children.
The Corrosion Resistance of Concrete-Filled Steel Tubes with the Assembly Unit of Na2MoO4 and Benzotriazole
Authors: Wang Di , Xu Zhiqiang , Xu Na , Hu Zengliang , Wang Hui , Shi Feiting
Published: March 2024

Steel pipes are commonly used to strengthen the concrete’s load-bearing capacity. However, they are prone to corrosion in salt erosion environments. In this study, the influence of Na2MoO4 and benzotriazole on concrete-filled steel tubes’ corrosion performance is investigated. The steel pipes’ mass loss rates (MRs), ultrasonic velocity, electrical resistance, and the AC impedance spectrum and Tafel curves of concrete-filled steel tubes were used to characterize the degree of corrosion in the steel pipes. Scanning electron microscopy–energy-dispersive spectrometry and X-ray diffraction were used for studying the composition of steel pipe rust. The research results revealed that the NaCl freeze–thaw cycles (F-C) and NaCl dry–wet alternation (D-A) actions had a reducing effect on the mass and ultrasonic velocity of the concrete-filled steel tubes. After 300 NaCl F-C and 30 NaCl D-A, the MRs were 0%~0.00470% and 0%~0.00666%. The corresponding ultrasonic velocities were 0%~21.1% and 0%~23.6%. When a rust inhibitor was added, the results were the opposite. The MRs decreased by 0%~80.3% and 0%~81.6% with the added Na2MoO4 and benzotriazole. Meanwhile, the corresponding ultrasonic velocities were 0%~8.1% and 0%~8.3%. The steel tubes were corroded after 300 NaCl F-C and 30 NaCl D-A. The addition of rust inhibitors improved the corrosion resistance of the concrete-filled steel tubes by increasing the electrical resistance before NaCl erosion. The corrosion area rate decreased by using the rust inhibitors. The corrosion resistance effect of benzotriazole was higher than that of Na2MoO4. The concrete-filled steel tube with an assembly unit comprising 5 kg/m3 of Na2MoO4 and 15 kg/m3 of benzotriazole had the best corrosion resistance under the erosion induced by NaCl F-C and D-A. Rust inhibitors reduced the content of iron-containing crystals and iron elements. The specimens with 5 kg/m3 Na2MoO4 and 15 kg/m3 benzotriazole had the lowest concentration of iron-containing crystals and iron elements.
Machinability of MoS2 after Oxygen Plasma Treatment under Mechanical Scanning Probe Lithography
Authors: He Yang , Su Xing , Hai Kuo
Published: March 2024

The surface of molybdenum disulfide (MoS2) underwent oxygen plasma treatment to enhance its machinability and mitigate the tearing effects commonly associated with mechanical forces on 2D materials. This treatment led to the oxidation of the atoms on the top 1–3 layers of MoS2, resulting in the formation of MoO3 on the surface. During mechanical scanning probe lithography (m-SPL), only the surface oxide layer was uniformly removed, with material accumulation occurring predominantly on one side of the machined area. The resolution of the machining process was significantly enhanced via dynamic lithography while maintaining atomic-level smoothness in the machined area. Importantly, these techniques only removed the surface oxide layer, preserving the integrity of the underlying MoS2 surface, which was pivotal in avoiding damage to the original material structure. This study provided valuable insights and practical guidance for the nanofabrication of transition metal dichalcogenides (TMDCs) nanodevices, demonstrating a method to finely tune the machining of these materials.
Diet and Lifestyle Intervention-Induced Pattern of Weight Loss Related to Reduction in Low-Attenuation Coronary Plaque Burden
Authors: Henzel Jan , Kruk Mariusz , Kępka Cezary , Makarewicz-Wujec Magdalena , Wardziak Łukasz , Trochimiuk Piotr , Krysztofiak Hubert , Dąbrowski Rafał , Dzielińska Zofia , Maurovich-Horvat Pál , Demkow Marcin
Published: March 2024

Background: Despite extensive research on body weight and cardiovascular risk, the mechanistic relationship between weight loss and coronary plaque modification has not been adequately addressed. This study aimed to determine the association between body composition dynamics and low-attenuation coronary plaque (LAP) burden. Methods: Eighty-nine participants (40% women, 60 ± 7.7 years) of the Dietary Intervention to Stop Coronary Atherosclerosis in Computed Tomography (DISCO-CT) study with non-obstructive atherosclerosis with nonobstructive atherosclerosis confirmed in computed tomography angiography (CCTA), a randomized (1:1), prospective, single-center study were included into the analysis. Patients were randomly assigned to either experimental arm (intensive diet and lifestyle intervention atop optimal medical therapy, n = 45) or control arm (optimal medical therapy alone, n = 44) over 66.8 ± 13.7 weeks. Changes (∆) in body mass (BM) and body composition parameters, including total body fat (TBF), skeletal muscle mass (SMM), and fat-to-muscle ratio (FMR), measured with bioimpedance analyzer were compared with CCTA-measured ∆LAP. Coronary plaque analysis was performed using the 2 × 192 dual-energy scanner (Somatom Force, Siemens, Germany), while quantitative coronary plaque measurements were performed using a semi-automated plaque analysis software system (QAngioCT v3.1.3.13, Medis Medical Imaging Systems, Leiden, The Netherlands). Results: Significant intergroup differences were found for ∆BM (−3.6 ± 4.9 kg in the experimental vs. −1.4 ± 2.9 kg in the control group, p = 0.015), ∆TBF (−3.4 ± 4.8% in the experimental vs. 1.1 ± 5.5% in the control arm, p < 0.001), ∆SMM (1.9 ± 2.8% in the experimental vs. −0.7 ± 3.2% in the control arm, p < 0.001), and FMR [−12.9 (−21.2; −4.3)% in the experimental vs. 3.1 (−5.3; 10.7)% in the control arm, p < 0.001]. ∆LAP did not differ significantly between the study arms; however, in the whole study population, ∆LAP was positively correlated with ∆BM, ∆TBF, and ∆FMR (r = 0.45, p < 0.001; r = 0.300, p = 0.004; r = 0.233, p = 0.028, respectively), and negatively with ∆SMM (r = −0.285, p = 0.007). Multivariate linear regression analysis revealed the association of ∆LAP with ∆BM, ∆TBF, and ∆FMR. Conclusions: The study intervention resulted in BM reduction characterized by fat loss, skeletal muscle gain, and increased FMR. This weight loss pattern may lead to a reduction in high-risk coronary plaque. Compared to a simple weight control, tracking body composition changes over time can provide valuable information on adverse coronary plaque modification.
Tumor-like Lesions in Primary Angiitis of the Central Nervous System: The Role of Magnetic Resonance Imaging in Differential Diagnosis
Authors: Zedde Marialuisa , Napoli Manuela , Moratti Claudio , Pavone Claudio , Bonacini Lara , Di Cecco Giovanna , D’Aniello Serena , Grisendi Ilaria , Assenza Federica , Boulouis Grégoire , Nguyen Thanh N. , Valzania Franco , Pascarella Rosario
Published: March 2024

Primary Angiitis of the Central Nervous System (PACNS) is a rare disease and its diagnosis is a challenge for several reasons, including the lack of specificity of the main findings highlighted in the current diagnostic criteria. Among the neuroimaging pattern of PACNS, a tumefactive form (t-PACNS) is a rare subtype and its differential diagnosis mainly relies on neuroimaging. Tumor-like mass lesions in the brain are a heterogeneous category including tumors (in particular, primary brain tumors such as glial tumors and lymphoma), inflammatory (e.g., t-PACNS, tumefactive demyelinating lesions, and neurosarcoidosis), and infectious diseases (e.g., neurotoxoplasmosis). In this review, the main features of t-PACNS are addressed and the main differential diagnoses from a neuroimaging perspective (mainly Magnetic Resonance Imaging—MRI—techniques) are described, including conventional and advanced MRI.
Machine Learning-Based Algorithms for Enhanced Prediction of Local Recurrence and Metastasis in Low Rectal Adenocarcinoma Using Imaging, Surgical, and Pathological Data
Authors: Volovat Cristian-Constantin , Scripcariu Dragos-Viorel , Boboc Diana , Volovat Simona-Ruxandra , Vasilache Ingrid-Andrada , Ursulescu-Lupascu Corina , Gheorghe Liliana , Baean Luiza-Maria , Volovat Constantin , Scripcariu Viorel
Published: March 2024

(1) Background: Numerous variables could influence the risk of rectal cancer recurrence or metastasis, and machine learning (ML)-based algorithms can help us refine the risk stratification process of these patients and choose the best therapeutic approach. The aim of this study was to assess the predictive performance of 4 ML-based models for the prediction of local recurrence or distant metastasis in patients with locally advanced low rectal adenocarcinomas who underwent neoadjuvant chemoradiotherapy and surgical treatment; (2) Methods: Patients who were admitted at the first Oncologic Surgical Clinic from the Regional Institute of Oncology, Iasi, Romania were retrospectively included in this study between November 2019 and July 2023. Decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF) were used to analyze imagistic, surgical, and pathological data retrieved from the medical files, and their predictive performance was assessed; (3) Results: The best predictive performance was achieved by RF when used to predict disease recurrence (accuracy: 90.85%) or distant metastasis (accuracy: 89.63%). RF was closely followed by SVM (accuracy for recurrence 87.8%; accuracy for metastasis: 87.2%) in terms of predictive performance. NB and DT achieved moderate predictive power for the evaluated outcomes; (4) Conclusions: Complex algorithms such as RF and SVM could be useful for improving the prediction of adverse oncological outcomes in patients with low rectal adenocarcinoma.
Differential Entropy-Based Fault-Detection Mechanism for Power-Constrained Networked Control Systems
Authors: Rojas Alejandro J.
Published: March 2024

In this work, we consider the design of power-constrained networked control systems (NCSs) and a differential entropy-based fault-detection mechanism. For the NCS design of the control loop, we consider faults in the plant gain and unstable plant pole locations, either due to natural causes or malicious intent. Since the power-constrained approach utilized in the NCS design is a stationary approach, we then discuss the finite-time approximation of the power constraints for the relevant control loop signals. The network under study is formed by two additive white Gaussian noise (AWGN) channels located on the direct and feedback paths of the closed control loop. The finite-time approximation of the controller output signal allows us to estimate its differential entropy, which is used in our proposed fault-detection mechanism. After fault detection, we propose a fault-identification mechanism that is capable of correctly discriminating faults. Finally, we discuss the extension of the contributions developed here to future research directions, such as fault recovery and control resilience.
The Fabric of Transition: Unraveling the Weave of Labor Dynamics, Economic Structures, and Innovation on Income Disparities in Central and Eastern Europe Nations
Authors: Davidescu Adriana AnaMaria , Lobonţ Oana-Ramona , Nae Tamara Maria
Published: March 2024

In recent years, the issue of income inequality has ascended to the forefront of national and international agendas, underscored by the urgency to navigate the complexities of market-driven economies without exacerbating social disparities. These challenges are particularly pronounced in the post-communist nations of Central and Eastern Europe, where the transition legacy and the marketization forces present unique dynamics in the evolution of income disparities. This research investigates the intricate mechanisms through which marketization impacts income inequality within the Central and Eastern European countries context, aiming to uncover how economic transformations influenced by global sustainability goals can contribute to narrowing the income gap. By employing panel data estimation techniques and Generalized Method of Moments (GMM) analysis, this study highlights the enduring nature of income disparities and the critical roles played by economic growth, education investment, labor market reforms, globalization, and governance quality in shaping equitable income distributions. Findings reveal that, despite the competitive nature of market economies potentially creating disparities, strategic policy interventions in education, economic policy, and labor market regulations can mitigate the adverse effects of marketization on income inequality. Additionally, this research emphasizes the importance of strong institutional frameworks and the nuanced role of the informal economy in influencing income distribution dynamics.
Exploring the Dynamic Nexus between Cross-Border Dollar Claims and Global Economic Growth
Authors: Alexiou Constantinos , Vogiazas Sofoklis , Benbow Alex
Published: March 2024

This paper addresses the role of the U.S. dollar in fostering global economic growth during the post-war period. The existing literature lacks a comprehensive understanding of the true implications of the U.S. dollar’s status as a reserve currency and a dearth of studies examining its impact. In this study, we explore the dynamic long-run and short-run relationships between cross-border U.S. dollar claims, global GDP, and global trade while gauging the impact of the Global Financial Crisis (GFC) and the COVID-19 pandemic. In doing so, we use ARDL methodology for a data set that spans the period of 1980 to 2022. The estimation results reveal a robust long-run relationship between U.S. dollar claims, global GDP and global trade and no clear evidence of asymmetric effects. Our findings are of great significance for monetary authorities, emphasising the need for a nuanced understanding of the implications of the U.S. dollar’s conducive role in shaping global economic dynamics and fostering growth.
When Video Improves Learning in Higher Education
Authors: Trenholm Sven , Marmolejo-Ramos Fernando
Published: March 2024

The use of video in education has become ubiquitous as technological developments have markedly improved the ability and facility to create, deliver, and view videos. The concomitant pedagogical transformation has created a sense of urgency regarding how video may be used to advance learning. Initial reviews have suggested only limited potential for the use of video in higher education. More recently, a systematic review of studies on the effect of video use on learning in higher education, published in the journal Review of Educational Research, found, overall, effects to be positive. In the present paper, we critique this study. We reveal significant gaps in the study methodology and write-up and use a cognitive processing lens to critically assess and re-analyse study data. We found the results of this study to be only applicable to learning requiring lower-level cognitive processing and conclude, consistent with prior research, that claims of a universal benefit are not yet warranted.
A 0.49–4.34 μW LC-SAR Hybrid ADC with a 10.85-Bit ENOB and 20 KS/s Bandwidth
Authors: Tang Hai , Xu Weilin , Li Haiou , Wei Baolin , Wei Xueming
Published: March 2024

This paper presents a level-crossing successive-approximation-register (LC-SAR) hybrid analog-to-digital converter (ADC) that combines an LC ADC with an SAR ADC, which may be used for Internet of Things (IoT) random sparse event scenarios. The sampling frequency of a traditional LC ADC is usually proportional to the maximum instantaneous rate of change of the input signal; therefore, a higher input signal frequency inevitably leads to higher system power consumption. However, the proposed hybrid ADC uses the input level difference between the two moments before and after level-crossing detection, thereby ensuring a higher conversion precision and lower power consumption, even at higher input signal frequencies. Compared with traditional LC ADC or SAR ADC, the proposed hybrid ADC combines the ultralow-power advantage of LC ADC with the high-precision advantage of SAR ADC in converting IoT data with sparse characteristics such as ECG, EEG, and brain potential. The LC-SAR hybrid ADC is designed with a 0.18 μm CMOS process and consumes 4.34 μW at a 1.8 V supply voltage, achieving an SNDR of 67.41 dB and a bandwidth of 20 kHz. The spectrum analysis result was 10.85 ENOB when the input sinusoidal signal was 14.975 kHz. When inputted with an ECG signal, the system power consumption was as low as 0.49 μW. Furthermore, the proposed hybrid ADC obtained a good figure of merit, with FoMw and FoMs reaching 58.8 fJ/conv.steps and 164 dB, respectively. Compared to a conventional uniform sampling ADC, approximately 80% of the power savings and an 8x compression ratio can be achieved in physiological signal acquisition applications.
Effects of Battery Energy Storage Systems on the Frequency Stability of Weak Grids with a High-Share of Grid-Connected Converters
Authors: Paiva Pedro , Castro Rui
Published: March 2024

To achieve an energy sector independent from fossil fuels, a significant increase in the penetration of variable renewable energy sources, such as solar and wind power, is imperative. However, these sources lack the inertia provided by conventional thermo-electric power stations, which is essential for maintaining grid frequency stability. In this study, a grid resembling Madeira Island’s power generation mix was modeled using the Matlab/Simulink platform. The model included solar, wind, hydro, and thermo-electric generation to accurately represent the energy landscape of Madeira Island. Three scenarios were examined: one reflecting the current power generation on Madeira Island, a future scenario with a substantial rise in the percentage of photovoltaic (PV) generation, and the same future scenario but incorporating a battery energy storage system (BESS). Various analyses were conducted to assess the impact on frequency stability during a ground fault and rapid load/generation changes. In the future scenario without a BESS, the thermoelectric power plant generator desynchronized, leading to system collapse in several simulations. However, with the addition of a BESS, a significant improvement in frequency stability was observed. The thermoelectric power plant generator could return to a steady state after each disturbance. Furthermore, both the maximum frequency deviation and the absolute value of the Rate of Change of Frequency (ROCOF) were reduced, indicating enhanced system performance and stability.
A Malicious Program Behavior Detection Model Based on API Call Sequences
Authors: Li Nige , Lu Ziang , Ma Yuanyuan , Chen Yanjiao , Dong Jiahan
Published: March 2024

To address the issue of low accuracy in detecting malicious program behaviors in new power system edge-side applications, we present a detection model based on API call sequences that combines rule matching and deep learning techniques in this paper. We first use the PrefixSpan algorithm to mine frequent API call sequences in different threads of the same program within a malicious program dataset to create a rule base for malicious behavior sequences. The API call sequences to be examined are then matched using the malicious behavior sequence matching model, and those that do not match are fed into the TextCNN deep learning detection model for additional detection. The two models collaborate to accomplish program behavior detection. Experimental results demonstrate that the proposed detection model can effectively identify malicious samples and discern malicious program behaviors.
Numerical Analysis of Three Vertical Axis Turbine Designs for Improved Water Energy Efficiency
Authors: Karakaya Derya , Bor Aslı , Elçi Sebnem
Published: March 2024

A hydrokinetic turbine with a vertical axis is specifically designed to harvest the kinetic energy from moving water. In this study, three vertical axis water turbines, namely Gorlov, Darrieus, and Savonius turbines, were compared for their efficiency via numerical modeling for steady-state conditions via the ANSYS 2022 R2 Fluent model. The Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) was implemented with an SST k-ω turbulence model. The dynamic mesh technique, which allows modeling according to changes in angular velocity at each time step, was used to simulate flow around the turbines for six different velocities (from 0.5 to 3 m/s). The efficiency of the turbines was compared and the results were analyzed. The pressure, velocity, and turbulence kinetic energy distributions around the rotor were measured at different rotational angles and results indicated a wider operating range for the Darrieus and Gorlov turbines compared to the Savonius turbine. The highest power coefficient of 0.293 was achieved in the model featuring a Darrieus turbine, corresponding to a TSR value of 1.34, compared to 0.208 for the Gorlov and 0.257 for the Savonius turbine, at TSR values of 1.3 and 1.06, respectively. Numerical modeling results pointed to a significantly higher self-starting capacity for the Savonius turbine compared to the others.
A Compound Control Strategy for an Ultralight Power Generation System
Authors: Wen Pingping , Yuan Zhibao , Yuan Zengquan , Xu Haiping
Published: March 2024

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density and substantial stability control in the power unit design. In order to meet the power density requirements of ultralight power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite compound control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralight generator set and improve the stability of the system, where response recovery can be achieved within 0.9 s under the conditions of a total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.
The Use of Hydrodynamic Cavitation to Improve the Anaerobic Digestion of Waste from Dairy Cattle Farming—From Laboratory Tests to Large-Scale Agricultural Biogas Plants
Authors: Dębowski Marcin , Kazimierowicz Joanna , Nowicka Anna , Dudek Magda , Zieliński Marcin
Published: March 2024

There is a need to find methods to intensify the anaerobic digestion process. One possibility is the use of pretreatment techniques. Many laboratory tests confirm their effectiveness, but in most cases, there is no verification work carried out on industrial plants. A reliable and complete evaluation of new solutions can only be carried out in plants that reflect operating conditions at a higher readiness technological level. This has a direct impact on the scientific value and, above all, on the high application value of innovative technologies. The aim of our research carried out under laboratory conditions and on a large scale was to determine the technological and energy efficiency of the use of hydrodynamic cavitation in the pretreatment of a waste mixture from dairy farms. It has been shown that hydrodynamic cavitation significantly increases the concentration of organic compounds in the dissolved phase. In the most effective variants, the increase in the content of these indicators was over 90% for both COD and TOC. The degree of solubilisation achieved was 49 ± 2.6% for COD and almost 52 ± 4.4% for TOC. Under laboratory conditions, the highest effects of anaerobic digestion were achieved after 10 min of pretreatment. The amount of biogas was, on average, 367 ± 18 mL/gCOD, and the amount of methane was 233 ± 13 mL/gCOD. Further large-scale optimisation trials showed that after 8 min of hydrodynamic cavitation, the biogas yield was 327 ± 8 L/kgCOD with a CH4 content of 62.9 ± 1.9%. With this variant, the net energy yield was 66.4 ± 2.6 kWh/day, a value that was 13.9% higher than the original variant with 10 min of disintegration and 3.1% higher than the variant without pretreatment.
Vehicular Fuel Consumption and CO2 Emission Estimation Model Integrating Novel Driving Behavior Data Using Machine Learning
Authors: Wang Ziyang , Mae Masahiro , Nishimura Shoma , Matsuhashi Ryuji
Published: March 2024

Fossil fuel vehicles significantly contribute to CO2 emissions due to their high consumption of fossil fuels. Accurate estimation of vehicular fuel consumption and the associated CO2 emissions is crucial for mitigating these emissions. Although driving behavior is a vital factor influencing fuel consumption and CO2 emissions, it remains largely unaddressed in current CO2 emission estimation models. This study incorporates novel driving behavior data, specifically counts of occurrences of dangerous driving behaviors, including speeding, sudden accelerating, and sudden braking, as well as driving time and driving distances on expressways, national highways, and local roads, respectively, into monthly fuel consumption estimation models for individual gasoline and hybrid vehicles. The CO2 emissions are then calculated as a secondary parameter based on the estimated fuel consumption, assuming a linear relationship between the two. Using regression algorithms, it has been demonstrated that all the proposed driving behavior data are relevant for monthly CO2 emission estimation. By integrating the driving behavior data of various vehicle categories, a generalizable CO2 estimation model is proposed. When utilizing all the proposed driving behavior data collectively, our random forest regression model achieves the highest prediction accuracy, with R2, RMSE, and MAE values of 0.975, 13.293 kg, and 8.329 kg, respectively, for monthly CO2 emission estimation of individual vehicles. This research offers insights into CO2 emission reduction and energy conservation in the road transportation sector.
Topological Structure and Control Strategy of E-UPFC
Authors: Yang Weiping , Liu Cong , Yin Limin
Published: March 2024

This article proposes a unified power flow controller with energy (E-UPFC) installed at the renewable energy grid connection node of the transmission network. Compared with other unified power flow controllers (UPFCs), the proposed E-UPFC can not only regulate the power flow on its connected transmission lines, but also suppress the power fluctuations of grid-connected nodes injected with large-scale renewable energy. At the same time, with the installation position of E-UPFC transferred from the transmission line to the node, the original stiff node can be transformed into a flexible node that can regulate the injected power flexibly. First, the PV grid-connected system with E-UPFC is introduced, and its principle of power flow regulation is detailed. In addition, the topology, mathematical modeling, and control strategies of E-UPFC are discussed. Finally, the E-UPFC is applied to the IEEE 3-generator 9-bus system with large-scale renewable energy integration in Matlab/Simulink in order to verify the correctness and feasibility of E-UPFC and its control strategies.
Thermographic Analysis of Exhaust Gas and Emissions by Varying Catalyst Behaviour and Injection Parameters
Authors: Farinango-Herrera Christian , Zambrano-Ramón Joshebet , Rojas-Reinoso Edgar Vicente
Published: March 2024

This study focuses on the detailed analysis of exhaust emissions from multi-point fuel injection (MPFI) engines by manipulating the injection parameters through a programmable electronic control unit. In addition, tests are carried out using different generations of catalytic converters and checking that their working temperature is correct using a thermographic camera, verifying operation, to evaluate their effect on emission reduction. Detailed comparisons of the results between these configurations will allow the identification of the combination that reduces emissions the most without compromising engine efficiency and performance. This research aims to promote a more sustainable approach in the automotive sector by properly configuring systems, but also by demonstrating the technical robustness of their application in vehicles. It has also helped to verify that varying injection and ignition parameters help to fine-tune fuel injection, resulting in efficient combustion. Combining this variation with catalytic converters has further reduced exhaust pollutants.
Optimal Operation of Residential Battery Energy Storage Systems under COVID-19 Load Changes
Authors: Hijazi Zahraa , Hong Junho
Published: March 2024

Over the past few years as COVID-19 was declared a worldwide pandemic that resulted in load changes and an increase in residential loads, utilities have faced increasing challenges in maintaining load balance. Because out-of-home activities were limited, daily residential electricity consumption increased by about 12–30% with variable peak hours. In addition, battery energy storage systems (BESSs) became more affordable, and thus higher storage system adoption rates were witnessed. This variation created uncertainties for electric grid operators. The objective of this research is to study the optimal operation of residential battery storage systems to maximize utility benefits. This is accomplished by formulating an objective function to minimize distribution and generation losses, generation fuel prices, market fuel prices, generation at peak time, and battery operation cost and to maximize battery capacity. A mixed-integer linear programming (MILP) method has been developed and implemented for these purposes. A residential utility circuit has been selected for a case study. The circuit includes 315 buses and 100 battery energy storage systems without the connection of other distributed energy resources (DERs), e.g., photovoltaic and wind. Assuming that the batteries are charging overnight, the results show that energy costs can be reduced by 10% and losses can decrease by 17% by optimally operating batteries to support increased load demand.
Study on Multivariable Dynamic Matrix Control for a Novel Solar Hybrid STIGT System
Authors: Zheng Shupeng , Luo Zecheng , Wu Jiwu , Zhang Lunyuan , He Yijian
Published: March 2024

To construct a clean and efficient energy system, advanced solar thermal power generation technology is developed, i.e., a solar hybrid STIGT (Steam Injected Gas Turbine) system with near zero water supply. Such a system is conducive to the efficient use of solar energy and water resources, and to improvement of the performance of the overall system. Given that the strong correlation between multiple-input and multiple-output of the new system, the MDMC (Multivariable Dynamic Matrix Control) method is proposed as an alternative to a PID (Proportional-Integral-Derivative) controller to meet requirements in achieving better control characteristics for a complex power system. First, based on MATLAB/Simulink, a dynamic model of the novel system is established. Then it is validated by both experimental and literature data, yielding an error no more than 5%. Subsequently, simulation results demonstrate that the overshoot of output power on MDMC is 1.2%, lower than the 3.4% observed with the PID controller. This improvement in stability, along with a reduction in settling time and peak time by over 50%, highlights the excellent potential of the MDMC in controlling overshoot and settling time in the novel system, while providing enhanced stability, rapidity, and accuracy in the regulation and control of distribution networks.
ML- and LSTM-Based Radiator Predictive Maintenance for Energy Saving in Compressed Air Systems
Authors: Jeon Seung Hyun , Yoo Sarang , Yoo Yoon-Sik , Lee Il-Woo
Published: March 2024

Air compressors are widely used in industrial fields. Compressed air systems aggregate air flows and then supply them to places of demand. These huge systems consume a significant amount of energy and generate heat internally. Machine components in compressed air systems are vulnerable to heat, and, in particular, a radiator to cool the heat of the overall air compressor is the core component. Dirty radiators increase energy consumption due to anomalous cooling. To reduce the energy consumption of air compressors, this mechanism emphasizes a machine learning-based radiator fault detection, using features such as RPM, motor power, outlet pressure, air flow, water pump power, and outlet temperature with slight true fault labels. Moreover, the proposed system adds an LSTM-based motor power prediction model to point out the initial judgment of radiator fault possibility. Via the rigorous analysis and the comparison among machine learning models, this meticulous approach improves the performance of radiator fault prediction up to 93.0%, and decreases the mean power consumption of the air compressor around 2.24%.
Effect of Irrigation Regime and Soil Nutrients on the Growth of the Paddy Weed Heteranthera reniformis and Rice Grain Yield
Authors: Magar Srijana Thapa , Fujino Takeshi , Han Thant Ko Ko
Published: March 2024

The growth of Heteranthera reniformis, an invasive alien paddy weed, can be affected by cultivation practices. The experiments were conducted using herbicide-free soil to understand the effects of irrigation regimes and nutrient treatments on the growth of H. reniformis, as well as yield parameters while competing with a pre-existing seedbank. The pot experiments were conducted in a randomized complete block design (RBCD) with three replicates and twelve treatments. The four irrigation regimes (IRs): continuous irrigation (CI), soil condition at near saturation (non-puddled) (S), alternate wetting and drying (AWD) irrigation under two conditions [rewatered when the soil water potential reached −25 kPa (25P) and −35 kPa (35P)], and three nutrient treatments (NTs) of 0–0–0 NPK (NT0), 40–25–30 NPK (NT1), 80–50–60 NPK (NT2), kg ha−1 were established. The IRs had a significant effect on the growth of H. reniformis and other paddy field weeds, and the growth of H. reniformis was suppressed in the AWD regimes. NT2 resulted in more rice panicles, higher grain yield, and increased irrigation water use efficiency (IWUE). The highest grain yield and protein content were observed in S–NT2 and 25P–NT2 treatments. The IR and NT can be maintained to prevent yield penalties and reduce the invasiveness of weeds.
Thinning vs. Pruning: Impacts on Sap Flow Density and Water Use Efficiency in Young Populus tomentosa Plantations in Northern China
Authors: Liu Yan , Liu Yadong , Qi Shuanglei , Fan Ziying , Xue Yadan , Tang Qingxuan , Liu Zhengyuan , Zheng Xiaomin , Wu Chuangye , Xi Benye , Duan Jie
Published: March 2024

Water is a vital resource for tree growth, and changes in plantation and canopy structure can affect stand transpiration (Ec), consequently influencing water use efficiency (WUE). Populus tomentosa is a fast-growing and productive timber species in China. In recent years, thinning combined with pruning has become a widely used silvicultural practice for timber management. However, its effect on water utilization has been less well studied. To address this gap, we designed experiments with two thinning intensities and three pruning treatments. Thermal dissipation probes were employed to monitor tree sap flow density (Js), and estimated Ec and canopy conductance (gc). We established a relationship between the canopy transpiration per unit leaf area (EL) and gc and climatic factors. Finally, we compared basal area increment (BAI) and WUE among treatments under different rainfall conditions. The results indicated that: (1) The pattern of transpiration changes was consistent at both the individual tree and stand level. (2) The combined effect of T1 (thinning intensity of 833 trees per hectare) and pruning reduced Ec, decreasing the sensitivity of tree transpiration to the climate, with no discernible impact on EL and gc. Conversely, T2 (thinning intensity of 416 trees per hectare) and pruning increased EL and gc but had no effect on Ec, enhancing the sensitivity of tree transpiration to the climate. The sensitivity of gc to VPD suggested a flexible stomatal regulation of transpiration under different combined thinning and pruning treatments. (3) Under T1, only P2 (4 m pruning from ground) promoted WUE, while pruning effects significantly reduced WUE under T2. Overall, the WUE of T2P0 (thinning intensity of 416 trees per hectare combined with no pruning) was significantly higher than that of the other treatments, and that of T1P0 (thinning intensity of 833 trees per hectare combined with no pruning) was significantly lower than that of the other treatments. Additionally, significant differences in Ec and BAI were observed among treatments under different rainfall conditions, with the promotion effect of Ec on BAI being more pronounced in the dry season.
Changing Relationship between Specific Leaf Area and Leaf Matter Dry Content of Moso Bamboo Phyllostachys pubescens syn. edulis (Poales: Poaceae) under the Stress of Pantana phyllostachysae (Lepidoptera: Lymantriidae)
Authors: Shen Wanling , Xu Zhanghua , Qin Na , Chen Lingyan , Yang Yuanyao , Zhang Huafeng , Yu Xier , He Anqi , Sun Lei , Li Xia
Published: March 2024

The objective of this study was to deeply understand the adaptation mechanism of the functional traits of Moso bamboo Phyllostachys pubescens syn. edulis (Poales: Poaceae) leaves to the environment under different Pantana phyllostachysae Chao damage levels, analyzing the changes in the relationship between specific leaf area (SLA) and leaf dry matter content (LDMC). We combined different machine learning models (decision tree, RF, XGBoost, and CatBoost regression models), and used different canopy heights and different levels of infestation, to analyze the changes in the relationship between the two under different levels of infestation based on the results of the best estimation model. The results showed the following: (1) The SLA of Ph. pubescens showed a decreasing trend with the increase om insect pest degree, and LDMC showed an inverse trend. (2) The SLA of bamboo leaves was negatively correlated with the LDMC under different insect pest degrees; the correlation of the data under the healthy class was higher than that of other insect pest levels, and at the same time better than that of the full sample, which laterally confirmed the effect of insect pest stress on the functional traits of Ph. pubescens leaves. (3) When modeling under different infestation levels, the CatBoost model was used for heavy damage and the RF model was used for the rest of the cases; the decision tree regression model was used when modeling different canopy heights. The findings contribute certain insights into the nuanced responses and adaptive mechanisms of Ph. pubescens forests to environmental fluctuations. Moreover, these results furnish a robust scientific foundation, essential for ensuring the enduring sustainability of Ph. pubescens forest ecosystems.
Public Attitudes towards Forest Pest Damage Cost and Future Control Extent: A Case Study from Two Cities of Pakistan
Authors: Hayat Umer , Abbas Aqsa , Shi Juan
Published: March 2024

Infestations of pests are perhaps an anthropogenic catastrophe for trees. Aeolesthes sarta (Sart longhorned beetle—SLB) is one of the most severe pests that cause serious damage to a number of hardwood tree species, i.e., Populus, Salix, Acer, Juglans, and Malus. To investigate people’s attitudes towards pest damage cost and future control extent of SLB, a door-to-door method was adopted to survey two major cities (Quetta—QU and Peshawar—PE) of the northwestern region of Pakistan where this pest has caused severe damage. Respondents were asked about SLB pest knowledge, pest damage costs, preferences for control choices, and program extent. According to respondents, more trees (181 ± 1.20 trees/ha/annum) were damaged in QU compared to PE. Populus spp. was the dominant tree genre that attacked and damaged the most. Around 85% of respondents from both cities stated the pest damage cost was calculated as high for QU (480,840.80 ± 4716.94$/annum) compared to PE. Respondents in both locations strongly supported (more than 82%) biological control of future SLB outbreaks. They all agreed that protecting ecologically vulnerable places and wildlife habitats should be the primary priority in a future SLB outbreak. Respondents from both cities who preferred to protect more land area in future SLB outbreaks were calculated to be high for QU (61%) compared to PE (58%). However, city variations in opinions regarding forest-type priority that should be protected and control options were observed. Socio-demographic characteristics were discovered to impact pest damage cost positively, as well as preferred SLB control extent. The findings of this study can help policymakers and forest managers develop publicly permissible pest control plans and make more accurate predictions about future pest outbreaks.