bluuebunny/crossref_metadata_2025 huggingface dataset:
Breast Cancer Classification Using Synthesized Deep Learning Model with Metaheuristic Optimization Algorithm
Authors: Thirumalaisamy Selvakumar , Thangavilou Kamaleshwar , Rajadurai Hariharan , Saidani Oumaima , Alturki Nazik , Mathivanan Sandeep kumar , Jayagopal Prabhu , Gochhait Saikat
Published: September 2023

Breast cancer is the second leading cause of mortality among women. Early and accurate detection plays a crucial role in lowering its mortality rate. Timely detection and classification of breast cancer enable the most effective treatment. Convolutional neural networks (CNNs) have significantly improved the accuracy of tumor detection and classification in medical imaging compared to traditional methods. This study proposes a comprehensive classification technique for identifying breast cancer, utilizing a synthesized CNN, an enhanced optimization algorithm, and transfer learning. The primary goal is to assist radiologists in rapidly identifying anomalies. To overcome inherent limitations, we modified the Ant Colony Optimization (ACO) technique with opposition-based learning (OBL). The Enhanced Ant Colony Optimization (EACO) methodology was then employed to determine the optimal hyperparameter values for the CNN architecture. Our proposed framework combines the Residual Network-101 (ResNet101) CNN architecture with the EACO algorithm, resulting in a new model dubbed EACO–ResNet101. Experimental analysis was conducted on the MIAS and DDSM (CBIS-DDSM) mammographic datasets. Compared to conventional methods, our proposed model achieved an impressive accuracy of 98.63%, sensitivity of 98.76%, and specificity of 98.89% on the CBIS-DDSM dataset. On the MIAS dataset, the proposed model achieved a classification accuracy of 99.15%, a sensitivity of 97.86%, and a specificity of 98.88%. These results demonstrate the superiority of the proposed EACO–ResNet101 over current methodologies.
Diagnostic Value of DAPK Methylation for Nasopharyngeal Carcinoma: Meta-Analysis
Authors: Lao Thuan Duc , Truong Phuong Kim , Le Thuy Ai Huyen
Published: September 2023

Background: Methylation of DAPK has been reported to play a key role in the initiation and progression of nasopharyngeal cancer. However, there are differences between the studies on it. This meta-analysis was performed to evaluate the diagnostic value of DAPK promoter methylation for NPC. Method: The study method involves the systematic research of eligible studies based on criteria. The frequency, odds ratios (OR), sensitivity as well as specificity with the corresponding 95% confidence intervals (CIs) were used to assess the effect sizes. Results: A total of 13 studies, including 1048 NPC samples and 446 non-cancerous samples, were used for the meta-analysis. The overall frequencies of DAPK methylation were 56.94% and 9.28% in NPC samples and non-cancerous samples, respectively. The association between DAPK methylation and risk of NPC was also confirmed by calculating the OR value which was 13.13 (95%CI = 54.24–40.72) based on a random-effect model (Q = 64.74; p < 0.0001; I2 = 81.47% with 95%CI for I2 = 69.39–88.78). Additionally, the study results suggest that testing for DAPK methylation in tissue samples or brushing may provide a promising method for diagnosing NPC. Conclusion: This is the first meta-analysis that provided scientific evidence that methylation of the DAPK gene could serve as a potential biomarker for diagnosis, prognosis, and early screening of NPC patients.
Enhancing X-ray-Based Wrist Fracture Diagnosis Using HyperColumn-Convolutional Block Attention Module
Authors: Oh Joonho , Hwang Sangwon , Lee Joong
Published: September 2023

Fractures affect nearly 9.45% of the South Korean population, with radiography being the primary diagnostic tool. This research employs a machine-learning methodology that integrates HyperColumn techniques with the convolutional block attention module (CBAM) to enhance fracture detection in X-ray radiographs. Utilizing the EfficientNet-B0 and DenseNet169 models bolstered by the HyperColumn and the CBAM, distinct improvements in fracture site prediction emerge. Significantly, when HyperColumn and CBAM integration is applied, both DenseNet169 and EfficientNet-B0 showed noteworthy accuracy improvements, with increases of approximately 0.69% and 0.70%, respectively. The HyperColumn-CBAM-DenseNet169 model particularly stood out, registering an uplift in the AUC score from 0.8778 to 0.9145. The incorporation of Grad-CAM technology refined the heatmap’s focus, achieving alignment with expert-recognized fracture sites and alleviating the deep-learning challenge of heavy reliance on bounding box annotations. This innovative approach signifies potential strides in streamlining training processes and augmenting diagnostic precision in fracture detection.
Correlations between Demographic, Clinical, and Paraclinical Variables and Outcomes in Patients with KRAS-Mutant or KRAS Wild-Type Metastatic Colorectal Cancer—A Retrospective Study from a Tertiary-Level Center in Romania
Authors: Pîrvu Edvina Elena , Severin Emilia , Pătru Raluca Ileana , Niță Irina , Toma Stefania Andreea , Macarie Roxana Rodica , Cocioabă Cristina Elena , Florescu Ioana , Coniac Simona
Published: September 2023

Colorectal cancer (CRC) is a significant global public health concern and its characteristics in Eastern Europe are underexplored. In this retrospective study, data of 225 patients with metastatic colorectal cancer (mCRC) from the Colțea Clinical Hospital’s Oncology Department in Bucharest were analyzed between 2015 and 2023. They were divided into two groups based on the presence of KRAS mutation. The primary objective of the study was to investigate whether the presence of KRAS mutations influenced the prognosis of mCRC and to identify any demographic, clinical, or paraclinical factors associated with KRAS mutations in stage IV CRC. The overall survival for the entire study population was 29 months. There was a trend towards increased survival in the KRAS wild-type group (31 months) compared to the KRAS-mutant group (26 months), but this difference did not reach statistical significance. We found that lower levels of education, advanced T stage, advanced N stage, and M1 stage at diagnosis negatively impacted prognosis. Real-world data are crucial in shaping public policy strategies to better support patients with metastatic CRC. Understanding the correlations between the demographic, clinical, and paraclinical variables and the outcomes in mCRC patients with KRAS-mutant and KRAS wild-type colorectal cancer is essential for improving patient care and treatment strategies in Romania and beyond.
The Role and Motivation of Pre-Service Teacher (PST) Mentors from Pro-Social to Cognitive-Effective Perspectives
Authors: Simon Eitan , Nissim Yonit
Published: September 2023

The purpose of this quantitative descriptive study is to shed light on the driving forces of the mentor’s positions in teacher training processes in Israel. The research is based on an exploratory cross-sectional study which included 170 preservice teacher mentors in the north of Israel. The mentoring position, despite its importance, is often unappreciated, even by the mentors themselves. It is barely rewarded, in money, status, or prestige. The current study focuses on the internal motivation of mentors for choosing to serve in this role in addition to their main role as classroom teachers. In this regard, the theory of cognitive-effective perspective can help us to understand the reasons behind these motivations. Our findings indicate that mentors exhibit internal motivation from the pro-social and cognitive-effective perspectives. The average score for attitudes was M = 2.92 (SD ± 0.42). The total score was higher for the cognitive components than for the effective ones (M = 2.98, SD ± 0.44, and M = 2.85, SD ± 0.52, respectively). The main motivations of the mentors were based on their strong desire to improve the level of teaching in Israel. Contributing to the future of education was a dominant part of their personal educational philosophy. These insights depict the mentor as a pillar of the teacher training community in Israel. Our findings also indicate that, while a supportive school climate and autonomy in the mentor’s role are factors that promote mentoring practices, a lack of theoretical knowledge about teacher training and a lack of clarity about the mentors’ responsibilities are factors that hinder such practices. It is important to address these factors in order to enhance the desirable variables while decreasing the undesirable ones, in order to translate educational philosophy into stable and sustainable improved teacher training processes.
Teaching Biodiversity: Towards a Sustainable and Engaged Education
Authors: Id Babou Asma , Selmaoui Sabah , Alami Anouar , Benjelloun Nadia , Zaki Moncef
Published: September 2023

The preservation of biodiversity has become a major concern in contemporary society. It is essential to understand teachers’ representations of biodiversity to effectively guide educational efforts because of the significant role of education in raising awareness and promoting sustainable behavior. Through a survey of a sample of 118 teachers, we adopted a mixed-method approach combining both a closed questionnaire and interviews. We used these methods to explore teachers’ representations of the concept of biodiversity as an integral part of the school curriculum, as well as to gather their views on certain features of its teaching. The results state that the majority of teachers perceive biodiversity as a whole and in its most complex relationships. During their professional experience, they have developed a biocentric and anthropocentric conception of biodiversity. This study provides valuable information to guide future pedagogical practices and educational policies in sustainable education.
An Effective Approach for Stepping-Stone Intrusion Detection Resistant to Intruders’ Chaff-Perturbation via Packet Crossover
Authors: Wang Lixin , Yang Jianhua , Kim Jae , Wan Peng-Jun
Published: September 2023

Today’s intruders usually send attacking commands to a target system through several stepping-stone hosts, for the purpose of decreasing the probability of being caught. Using stepping-stone intrusion (SSI), the intruder’s identity is very difficult to discover as it is concealed by a long interactive connection chain of hosts. An effective approach for SSI detection (SSID) is to determine how many connections are contained in a connection chain. This type of method is called network-based SSID. Most existing network-based SSID only worked for network traffic without intruders’ session manipulation. These known SSID algorithms are either weak to resist intruders’ chaff-perturbation manipulation or have very limited capability in resisting attacker’s session manipulation. This paper develops a novel network-based SSID algorithm resistant to intruders’ chaff-perturbation by using packet crossover. The SSID approach proposed in this paper is simple and easy to implement as the number of packet crossovers can be easily computed. Our proposed algorithm is verified by rigorous technical proofs as well as well-designed network experiments. Our experimental results show that the proposed SSID algorithm works effectively and perfectly in resisting intruders’ chaff-perturbation up to a chaff rate of 50%.
A Fault-Tolerant Control Method for a PMSM Servo Drive System with a Four-Leg Inverter
Authors: Cui Peijuan , Zheng Zaiping , Fu Jie , Zhang Qianfan , An Linxue
Published: September 2023

In this paper, a fault tolerant control method is proposed for a permeant magnet synchronous motor (PMSM) servo drive system with four leg inverters to cope with the open phase fault. As one of common faults in the motor drive system, the open phase fault will degrade the control performance and efficiency. Even serious damage is caused in some extreme cases. Hence, it is meaningful to realize the fault tolerance of the drive system with open phase fault. The proposed method includes three parts: a torque-producing current calculator, phase voltage determination and voltage distributor. The torque-producing current calculator is designed by taking the third harmonic flux into consideration to calculate the torque-producing current. In the phase voltage determination, it is proved that the third harmonic flux has no influence on the line voltage equation. For healthy operation and fault operation, the voltage requirements in remaining healthy phases are determined based on the line voltages. Finally, two voltage distributors are designed to distributor the phase voltages into remaining inverter leg. The main difference of two voltage distributors is the polarity of two remaining voltage. Compared to the conventional method, the proposed method can reduce the torque ripple under a postfault condition. In addition, the controller structure will not be changed under a pre-fault and postfault condition. The proposed method has been validated by simulated results and experimental results.
Analysis of Function Approximation and Stability of General DNNs in Directed Acyclic Graphs Using Un-Rectifying Analysis
Authors: Hwang Wen-Liang , Tung Shih-Shuo
Published: September 2023

A general lack of understanding pertaining to deep feedforward neural networks (DNNs) can be attributed partly to a lack of tools with which to analyze the composition of non-linear functions, and partly to a lack of mathematical models applicable to the diversity of DNN architectures. In this study, we analyze DNNs using directed acyclic graphs (DAGs) under a number of basic assumptions pertaining to activation functions, non-linear transformations, and DNN architectures. DNNs that satisfy these assumptions are referred to as general DNNs. Our construction of an analytic graph was based on an axiomatic method in which DAGs are built from the bottom–up through the application of atomic operations to basic elements in accordance with regulatory rules. This approach allowed us to derive the properties of general DNNs via mathematical induction. We demonstrate that the proposed analysis method enables the derivation of some properties that hold true for all general DNNs, namely that DNNs “divide up” the input space, “conquer” each partition using a simple approximating function, and “sparsify” the weight coefficients to enhance robustness against input perturbations. This analysis provides a systematic approach with which to gain theoretical insights into a wide range of complex DNN architectures.
A Low RCS and Array-Insensitive FSS Wideband Radome
Authors: Gong Lei , Zhang Ge , Wang Haibin , Zhou Pan , Wang Liguo , Yang Zhiqiang
Published: September 2023

In order to further expand the RCS reduction model of the miniature broadband antenna, a four-notch shaped FSS radome insensitive to the number of array elements is designed based on the multi-layered medium Green’s function and the transflective coefficient of the finite radome is derived. The calculated results are in good agreement with the infinite array, showing broadband transmission performance in both C-band and X-band. The electric field distribution and far-field distribution of a finite FSS array are given and the effects of a 5 × 5 array in a V-shaped structure on the surface of a miniature broadband antenna on its gain coefficient and RCS reduction characteristics are calculated numerically. The results show that the designed radome exhibits good array element insensitivity and far-field scattering reduction characteristics and achieves significant in-band and out-of-band RCS accurate reduction under the premise of constant antenna radiation performance. At normal incidence, the single-station RCS in the passband and stopband are as low as −35 dB and −32.66 dB, respectively. The maximum reduction in the transmission band reaches 20.96 dB under oblique incidence and the projection size of the radome decreases with the increase in the bottom angle of the radome but the RSC reduction performance is basically unaffected and can be adjusted flexibly according to actual needs. The above results provide a theoretical basis and technical support for the application of FSS radome in RCS reduction in micro wideband antennas.
Ship Diesel Engine Fault Diagnosis Using Data Science and Machine Learning
Authors: Pająk Michał , Kluczyk Marcin , Muślewski Łukasz , Lisjak Dragutin , Kolar Davor
Published: September 2023

One of the most important elements of the reliability structure of a motor vessel is its power subsystem, with the most crucial component being the engine. An engine failure excludes the ship from operation or significantly limits its operation. Therefore, accurate fault diagnosis should be a crucial issue for modern maintenance strategies. In mechanical engineering, the vibration and acoustic signals recorded during the operation of the device are the most meaningful data used to identify the reliability state. In this paper, a novel system-oriented method of reliability state identification is proposed. The method consists of the analysis of the vibration and noise signals collected on each of the engine cylinders using supervised machine learning. The main novelty of this method is data augmentation application and SVM classifier implementation. Due to these aspects, the method becomes robust in the case of poor-quality data or a limited and incomplete learning dataset. The quality of the proposed identification method was evaluated by addressing a new industrial issue (Sulzer 6AL20/24 marine engine reliability state identification). During the tests, the efficiency of the method was analyzed in the case of a complete learning data set (all types of inability states were presented in the learning data set) and an incomplete learning data set (in the testing data set, there were new types of inability states). As a result, in both cases, a very high (100%) identification accuracy of the reliability state and the type of inability state was obtained. This is a significant increase in accuracy (4.6% for the complete and 22% for the incomplete learning data set) in comparison to the efficiency of the same method without the use of machine learning and data science.
Development of Temperature Sensor Based on AlN/ScAlN SAW Resonators
Authors: Wei Min , Liu Yan , Qu Yuanhang , Gu Xiyu , Wang Yilin , Liu Wenjuan , Cai Yao , Guo Shishang , Sun Chengliang
Published: September 2023

Temperature monitoring in extreme environments presents new challenges for MEMS sensors. Since aluminum nitride (AlN)/scandium aluminum nitride (ScAlN)-based surface acoustic wave (SAW) devices have a high Q-value, good temperature drift characteristics, and the ability to be compatible with CMOS, they have become some of the preferred devices for wireless passive temperature measurement. This paper presents the development of AlN/ScAlN SAW-based temperature sensors. Three methods were used to characterize the temperature characteristics of a thin-film SAW resonator, including direct measurement by GSG probe station, and indirect measurement by oscillation circuit and antenna. The temperature characteristics of the three methods in the range of 30–100 °C were studied. The experimental results show that the sensitivities obtained with the three schemes were −28.9 ppm/K, −33.6 ppm/K, and −29.3 ppm/K. The temperature sensor using the direct measurement method had the best linearity, with a value of 0.0019%, and highest accuracy at ±0.70 °C. Although there were differences in performance, the characteristics of the three SAW temperature sensors make them suitable for sensing in various complex environments.
High-Efficiency GaN-Based Power Amplifiers for Envelope Nonlinearities’ Mitigation in VHF Wideband Polar-Mode Transmitters
Authors: Patiño-Gómez Moisés , Ortega-González Francisco-Javier
Published: September 2023

Space-based communications at the very high frequency (VHF) band for air traffic management is a new technology application under development that requires energy-efficient architectures to mitigate the power limitations of satellite platforms. The usage of high-efficiency radiofrequency (RF) transmitters can help reduce the power consumption, but nonlinearities concerning the amplified signal in wide fractional bandwidth systems are a problem to solve. This paper proposes a high-efficiency (RF) power amplifier (PA) for satellite communications at the VHF band that aims to reduce the envelope distortion inherent to wide fractional bandwidth multicarrier polar-mode transmitters. Its design is based on a solution called hybrid-coupled switching voltage PA in combination with gallium nitride (GaN) high electron mobility transistor (HEMT) technology. The developed VHF PA prototype delivers up to 95 W from a 28 V power supply, with a drain efficiency about 80% within the 118 MHz to 138 MHz operating band. To test its linearity performance, operating in a polar-mode configuration, a GaN-based wideband envelope amplifier (EA) has been developed to modulate the RF PA supply port. This EA improves its power efficiency by combining it with a slow envelope power supply (SEPS). Some measurements have been taken for a 100 W peak envelope power (PEP) and 10 MHz (maximum carrier spacing) four-tone digitally-modulated test signal, where any distortion product is attenuated 46 dB below the average power of the amplified signal without applying any digital predistortion (DPD) technique.
Sustainable Energy Development and Sustainable Social Development in EU Countries
Authors: Wyrwa Joanna , Jędrzejczak-Gas Janina , Barska Anetta , Wojciechowska-Solis Julia
Published: September 2023

Sustainable development has been the focus of many analyses in economics. Nevertheless, only a few attempts have so far been made to identify the underlying relationship between sustainable energy development and sustainable social development. This article fills this research gap and enables a better understanding of the essence of sustainable development to help draw applicable conclusions. The aim is to assess sustainable energy and social development in EU countries and to examine their shared relationship in this area. To this end, this study uses a taxonomic method and correlation analysis. The analysis period covers the years 2014–2020. The research builds directly on the assumptions of the concept of sustainable development, with particular emphasis on energy and social aspects. The article is composed of two parts. The first, based on a literature review, discusses the essence of sustainable energy development and social sustainability. The second outlines the research methodology, including the underpinnings of synthetic measures and the results of the conducted empirical research.
Influence of Cooling Water Parameters on the Thermal Performance of the Secondary Circuit System of a Modular High-Temperature Gas-Cooled Reactor Nuclear Power Plant
Authors: Wang Xin , Zhao Gang , Qu Xinhe , Yang Xiaoyong , Wang Jie , Wang Peng
Published: September 2023

This study quantitatively analysed the influence of cooling water parameters on the performance of a modular high-temperature gas-cooled reactor (MHTGR) nuclear power plant (NPP). The secondary circuit system and cold-end system were modelled using EBSILON software, version 16.0. The influence of cooling water inlet temperature and mass flow rate on the thermal performance of the secondary circuit system was analysed over the full power range with the goal of optimising net power. Under 100% rated condition, for each 1 °C increase in cooling water inlet temperature between 10 and 33 °C, the net power and cycle efficiency decreased by 0.67 MW and 0.14%, respectively, whereas the heat consumption rate increased by 28.72 kJ/(kW·h). The optimal cooling water mass flow rates corresponding to cooling water inlet temperatures of 16 °C and 33 °C were obtained. The optimal cooling water mass flow rate decreased nonlinearly with decreasing power levels. At a cooling water inlet temperature of 33 °C, an increase in cooling water mass flow rate from the designed value (7697.61 kg/s) to the optimal value (10,922.14 kg/s) resulted in a 1.03 MW increase in net power. These findings provide guidelines for MHTGR NPP operation optimisation and economic improvement, especially under high-temperature weather conditions.
A Multi-Stage Real-Time Fast Search Method for Closed-Loop Paths Based on Grid Hierarchical Partitioning Characteristics
Authors: Zhang Dongying , Yang Kai , Wang Wei , Zhou Yunbin , Hua Xiong , Liang Tianjun , Song Kunhao
Published: September 2023

Prior to switching operations, the dispatch automation system is required to be able to search for closed-loop paths quickly in real time. In order to improve the efficiency of closed-loop path search, this paper proposes a multi-stage real-time fast search method for closed-loop paths based on the characteristics of power grid hierarchical partitioning. First, we divide the closed-loop judgement process into three phases: initialization, acceptance of the closed-loop judgement command, and post-operation. Then, we define three types of nodes, including root nodes, same-layer contact nodes, and common nodes, and construct path data models for each type of node in accordance with the node liaison relationship in grid hierarchical zoning. In the initialization phase, we design a method for the automatic generation of real-time nodal path data models and study a hierarchical partitioned closed-loop path search method based on a nodal path data model for the phase of accepting closed-loop judgement commands. Next, we design a fast local correction method for nodal path models after the switch closure and disconnection operations in the post-operation idle phase are performed. Finally, a real power grid model is used as an example to test the above closed-loop path search method, which improves the search efficiency by eight times compared with the conventional breadth-first search method. The method is applicable to real large and complex power grids.
Effect of Sharing Schemes on the Collective Energy Self-Consumption Feasibility
Authors: Llera-Sastresa Eva , Gimeno José Ángel , Osorio-Tejada José Luis , Portillo-Tarragona Pilar
Published: September 2023

Collective self-consumption is called to be a crucial part of the current energy transition. In addition to the advantages of individual self-consumption, the possibility of improving economic feasibility exists. This paper shows how matching production and consumption loads increase the rate of self-consumption. Still, how the electricity is distributed among a renewable energy community’s prosumers would reduce the total costs of self-consumed energy. Possible criteria for the allocation of the generated electricity among shareholders are analysed. The study also evaluates the use of static and dynamic distribution coefficients, observing their results and applicability and sorting them to maximise self-consumption participants’ savings. The results are questioned against them and a reference scenario without shared self-consumption installation. As the exploitation of renewable energy for self-consumption is closely linked to the energy market and regulations, the analysis is based on a territorial case study. It is shown that the highest savings occur when electricity is allocated following distribution coefficients that consider the customer’s energy consumption better than investment participation or contracted power, even when the compensation of surpluses is added. These criteria can accomplish technical and economic objectives and are introduced in regulations that foster the requested changes in consumers’ behaviour and prosumers for sustainability.
Economic Analysis and Policies for the Environment, Natural Resources, and Energy
Authors: Halkos George
Published: September 2023

Blueprinting sustainable development pathways is by no means plain sailing [...]
Experimental Study on the Dynamic Stability of Circular Saw Blades during the Processing of Bamboo-Based Fiber Composite Panels
Authors: Ding Yucheng , Ma Yaqiang , Liu Tongbin , Zhang Jiawei , Yang Chunmei
Published: September 2023

Bamboo-based fiber composite panel is a new type of composite material with excellent performance. When processing bamboo-based fiber composite panels, the dynamic stability of the circular saw blade affects the surface quality of the product and the life of the machinery and equipment. Sawing heat and vibration characteristics can significantly affect the dynamic stability of circular saw blades. Circular saw blade temperature and vibration characteristics are affected by the processing parameters, and the circular saw blade temperature and vibration characteristics are analyzed by changing the processing parameters. Adopting the thermoset coupling model can be used to analyze the change rule of circular saw blade temperature when sawing bamboo-based fiber composite boards, and at the same time to analyze the change rule of circular saw blade temperature, vibration speed, and vibration acceleration through the use of by CCD experiments. The regression equations for circular saw blade temperature, vibration velocity, and vibration acceleration were derived through the use of ANOVA and significance analysis. The thermoset coupling model predictions agree with the experimental results, and the density of the isotherms is progressively thinner as the temperature is conducted from the serrated region to the body of the saw. Finally, the accuracy of the regression equations for circular saw blade temperature, vibration velocity, and vibration acceleration was checked via error analysis. The temperature change regression equation has the highest fitting accuracy, with an average error of only 1.37%; the vibration velocity and vibration acceleration regression equations have poorer fitting accuracy, with an average error of 9.5% and 11.45%, respectively, but all of them have sufficient accuracy to predict the dynamic stability of circular saw blades. The results of the study can provide some guidance for the innovative design of circular saw blades.
Comparative Transcriptome Analysis Reveals the Molecular Mechanism of Salt Combined with Flooding Tolerance in Hybrid Willow (Salix matsudana × alba)
Authors: Chen Zhenan , Gao Handong , Wu Haoqi , Xue Xiaoming , Ren Jiahui
Published: September 2023

Plants in coastal areas often face the combined stress of salt and flooding, which can cause severe damage. The impact of multiple stresses on plant growth and survival is greater than that of individual stresses. However, the molecular responses of hybrid willow (Salix matsudana × alba) to the combination of salt and flooding have not been well understood. In this study, we conducted a comparative transcriptome analysis to investigate the molecular mechanism underlying the tolerance of hybrid willow to salt-flooding. Seedings were, respectively, treated with 200 mM NaCl and flooded with water or 200 mM NaCl solution for 3 d, 10 d, and 17 d. We identified 1842, 3350, and 2259 differentially expressed genes (DEGs) regulated by hybrid willow under single salt stress, single flooding stress, and combined salt and flooding stress, respectively. Many DEGs detected in single salt- and flooding-treated plants were expressed differentially after the combined salt and flooding. Most of the shared transcripts exhibited similar fold changes in common molecular responses such as detoxification of reactive oxygen species (ROS) and signaling pathways related to calcium, phytohormones, and protein kinases, which were also observed in plants exposed to each stress individually. Additionally, a large number of specific DEGs were identified under salt-flooding stress, primarily associated with cell wall remodeling, osmotic adjustments, stress signaling, primary metabolism, and ROS scavenging. KEGG (Kyoto Encyclopedia of Genes and Genomes) annotation indicated that hybrid willow leaves responded to salt-flooding stress mainly through phytohormone signaling and MAPK signaling pathways. Overall, this study provides new insights into the molecular mechanisms underlying the response of Salix species to multiple stresses and identifies potential candidate genes for enhancing the performance of hybrid willows.
Analysis of Slope Stability with Different Vegetation Types under the Influence of Rainfall
Authors: Chen Bozhou , Shui Wei , Liu Yuanmeng , Deng Ruyue
Published: September 2023

Rainfall-prone shallow landslides account for one-fifth of the global land area, and rainfall is critical to the mechanics and hydrology of shallow slopes. In typical geological disaster-prone areas, the hydrodynamic responses of slopes with different vegetation types under rainfall conditions require further study. The purpose of this study was to analyze the hydraulic stability of soils with different vegetation types under rainfall conditions and their effects on slope stability. Thus, the soil–water characteristic curves and water-stable aggregate characteristics of soils with three vegetation types were analyzed. A two-dimensional finite element model was used to simulate the slope stability of extreme rainfall environments with different rainfall durations. The results showed that the matric suction of soil with trees was less affected by rainfall with a better stability of water-stable aggregates than that of soil with shrubs and grass. The plastic strain cloud map showed that the maximum plastic strain occurred at the toe of the slope. In addition, the potential slip depth of slopes with trees was smaller than that of slopes with shrubs and grass. Under the two rainfall durations, the factor of safety (FoS) of slopes with trees changed by 0.06, whereas that of slopes with shrubs and grass changed by 0.1. The findings of this study provide valuable insights into changes in the stability of slopes with different vegetation types under varying rainfall conditions. It is of great significance to provide a scientific basis for the application of ecological measures in the prevention and control of mountain disasters and guide the implementation of appropriate land management measures.
Transcriptomic Analysis Revealed That Low-Density Aphid Infestation Temporarily Changes Photosynthesis and Disease Resistance but Persistently Promotes Insect Resistance in Poplar Leaves
Authors: Shen Wanna , Fu Yuchen , Wang Li , Yao Yanxia , Zhang Yinan , Li Min , Liu Huixiang , Su Xiaohua , Zhao Jiaping
Published: September 2023

Insect infestations cause substantial changes in the leaves they attack, but the effects of insect infestation on photosynthesis and gene expression in the whole infestation period are rarely reported. In this study, the effects of poplar aphid (Chaitophorus populialbae Boyer de Fonscoloube) on photosynthetic rate and gene expression of Populus alba var. pyramidalis were studied, from 2 to 36 days after low-density aphid inoculation (DAI). The results revealed a dynamic change of photosynthesis in poplar after aphid infestation: compensatory increased at 8 DAI, was inhibited at 17 DAI, but repaired after 21 DAI. Aphid infestation promoted the expression of the majority of differentially expressed genes (DEGs) at 4, 6, 8, and 21 DAI. The DEGs were enriched into a plant–pathogen interaction, plant hormone signal transduction, and MAPK signaling pathway, suggesting a significant but transient resistance to disease or other stresses. Photosynthesis-related DEGs were downregulated at 8 DAI, which might result in photosynthetic inhibition at 17 DAI. The expression of flavonoid biosynthesis-related DEGs dynamic changed from all downregulated at 2 DAI to almost all upregulated at 21 DAI, suggesting a persistent resistance to insect infestation. This study reveals dynamic changes in photosynthesis, resistance to pathogens, and insects in poplar leaves after aphid infestation.
Modelisation of the Biomethane Accumulation in Anaerobic Co-Digestion of Whey and Sugarcane Molasse Mixtures
Authors: Arotingo Guandinango Huaita Pacari , Espín Valladares Rosario del Carmen , Núñez Pérez Jimmy , Lara Fiallos Marco Vinicio , Pereda Reyes Ileana , Pais-Chanfrau José Manuel
Published: September 2023

The biomethane accumulation of several combinations of whey and sugarcane molasses, inoculated with sludge from a treatment facility of one of the dairy enterprises of the Imbabura province in Ecuador, was assessed in the current experiment at a constant COD0/VSin ratio of 0.5. The whey/molasses (W:M) ratios for each treatment were (in % (m/m)) 0:100, 25:75, 50:50, 75:25, and 100:0, with a constant temperature of 37 °C and an initial pH adjustment of 7.5. Half a litre of total mixes was used for each treatment in duplicate. Six kinetic models were evaluated to account biomethane accumulation in anaerobic co-digestion processes in batch of whey and sugarcane molasses. Five of these have been tested by other researchers, and one was developed by modifying a first-order model to consider changes in the biomethane accumulation profile. This proposed model, along with the modified two-phase Gompertz model, resulted in the ones that were best able to adjust the experimental data, obtaining in all cases an R2 ≥ 0.949, indicating the accuracy of both models. In addition, the proposed here model has five parameters, one less than the modified two-phase Gompertz model, making it more straightforward and robust.
On Evaluating IoT Data Trust via Machine Learning
Authors: Tadj Timothy , Arablouei Reza , Dedeoglu Volkan
Published: September 2023

Data trust in IoT is crucial for safeguarding privacy, security, reliable decision-making, user acceptance, and complying with regulations. Various approaches based on supervised or unsupervised machine learning (ML) have recently been proposed for evaluating IoT data trust. However, assessing their real-world efficacy is hard mainly due to the lack of related publicly available datasets that can be used for benchmarking. Since obtaining such datasets is challenging, we propose a data synthesis method, called random walk infilling (RWI), to augment IoT time-series datasets by synthesizing untrustworthy data from existing trustworthy data. Thus, RWI enables us to create labeled datasets that can be used to develop and validate ML models for IoT data trust evaluation. We also extract new features from IoT time-series sensor data that effectively capture its autocorrelation as well as its cross-correlation with the data of the neighboring (peer) sensors. These features can be used to learn ML models for recognizing the trustworthiness of IoT sensor data. Equipped with our synthesized ground-truth-labeled datasets and informative correlation-based features, we conduct extensive experiments to critically examine various approaches to evaluating IoT data trust via ML. The results reveal that commonly used ML-based approaches to IoT data trust evaluation, which rely on unsupervised cluster analysis to assign trust labels to unlabeled data, perform poorly. This poor performance is due to the underlying assumption that clustering provides reliable labels for data trust, which is found to be untenable. The results also indicate that ML models, when trained on datasets augmented via RWI and using the proposed features, generalize well to unseen data and surpass existing related approaches. Moreover, we observe that a semi-supervised ML approach that requires only about 10% of the data labeled offers competitive performance while being practically more appealing compared to the fully supervised approaches. The related Python code and data are available online.
Effect of Schmidt Number on Forced Isotropic Turbulence with Passive Scalars
Authors: Orlandi Paolo , Pirozzoli Sergio
Published: September 2023

Traditionally, Fourier spectra have been employed to gain a deeper understanding of turbulence flow structures. The investigation of isotropic forced turbulence with passive scalars offers a straightforward means to examine the disparities between velocity and passive scalar spectra. This flow configuration has been extensively studied in the past, encompassing a range of Reynolds and Schmidt numbers. In this present study, direct numerical simulations (DNS) of this flow are conducted at sufficiently high Reynolds numbers, enabling the formation of a wide inertial range. The primary focus of this investigation is to quantitatively assess the variations in scalar spectra with the Schmidt number (Sc). The spectra exhibit a transition from a k−5/3 scaling for low Sc to a k−4/3 scaling for high Sc. The emergence of the latter power law becomes evident at Sc = 2, with its width expanding as Sc increases. To gain further insights into the underlying flow structures, a statistical analysis is performed by evaluating quantities aligned with the principal axes of the strain field. The study reveals that enstrophy is primarily influenced by the vorticity aligned with the intermediate principal strain axis, while the scalar gradient variance is predominantly controlled by the compressive strain. To provide a clearer understanding of the differences between enstrophy and scalar gradient variance, joint probability density functions (PDFs) and visualizations of the budget terms for both quantities are presented. These visualizations serve to elucidate the distinctions between the two and offer insights into their respective behaviors.
Flow Rate Augmentation of Valveless Pumping via a Time-Dependent Stenosis: A Novel Device
Authors: Manopoulos Christos , Mathioulakis Dimitrios
Published: September 2023

A novel device of flow rate augmentation is proposed and experimentally examined in a horizontal valveless closed loop pump using a time-dependent stenosis (convergent–divergent channel) in contrast with the commonly used taper tubes of constant opening as flow rectifiers. The stenosis, being a part of the flexible tube of the pump, is formed by a semi-cylindrical surface attached to a compression spring of adjustable pretension compressing the tube against a flat plate. Located at either side of the pump pincher, the shape of the stenosis changes in time, without any external power source, as a function of the fluid pressure and the pretension of the spring. The spring pretension is adjusted by a trial-and-error procedure aiming for net flow rate maximization for each pinching frequency. For the examined pitching frequencies (5 Hz to 11 Hz, for which net flow rate is maximized) and for compression ratios 38% to 75%, the maximum net flow rate was found to be 720% of the non-stenosis case. Important parameters for flow enhancement were found to be the stenosis location along the loop, its opening, the compression ratio at the pincher area and the pinching frequency.
Antioxidant Activities of Konjac Glucomannan Hydrolysates of Different Molecular Weights at Different Values of pH
Authors: Tripetch Phattanit , Lekhavat Supaporn , Devahastin Sakamon , Chiewchan Naphaporn , Borompichaichartkul Chaleeda
Published: September 2023

Konjac glucomannan (KGM) is a high-molecular-weight polysaccharide that was originally extracted from the corms (underground storage organs) of Amorphophallus konjac. KGM and its oligomers have been reported as dietary fibers that exhibit an array of health benefits. The depolymerization of KGM via enzymatic hydrolysis at different conditions gives products of low viscosity and can be used for coating materials in microencapsulation. In the present study, konjac glucomannan hydrolysates (KGMHs) were produced by enzymatic hydrolysis using commercial mannanase at pH 4.5 at 70 °C for 5–120 min, then KGMHs’ molecular weight (Mw), Degree of Polymerization (DP) and their bioactivities were determined. A longer hydrolysis time resulted in KGMH of a lower DP. Oligoglucomannans (Mw < 10,000) could be obtained after hydrolysis for 20 min. The DP of KGMH rapidly decreased during an early stage of the hydrolysis (first 40 min); DP reached around 7 at the end of the hydrolysis. Antioxidant activities were determined by the DPPH radical scavenging and FRAP assays of KGMHs prepared at pH 4.5 and evaluated at pH 2.0–8.0 depending on pH. KGMH having lower Mw exhibited higher antioxidant activities. KGMHs having the smallest molecular weight (Mw = 419) exhibited the highest DPPH radical scavenging activity. Mw and pH have a greater impact on KGMHs’ bioactivities which can be useful information for KGMHs as functional ingredients.
Integrated Transcriptomics and Metabolomics Reveal the Mechanism of Alliin in Improving Hyperlipidemia
Authors: Zhang Min , Zou Xiaoying , Du Yixuan , Pan Zhuangguang , He Fangqing , Sun Yuanming , Li Meiying
Published: September 2023

This research aims to assess the anti-hyperlipidemia effects of alliin in vivo and its potential mechanisms through transcriptomics and metabolomics analysis. A hyperlipidemia mode was established in C57BL/6 mice fed a high-fat diet, and the related physiological parameters of the animals were recorded. Serum TC and MDA in livers significantly decreased by 12.34% and 29.59%, respectively, and SOD and CAT in livers significantly increased by 40.64% and 39.05%, respectively, after high doses of alliin interventions. In total, 148 significantly different genes, particularly Cel, Sqle, Myc, and Ugt1a2, were revealed for their potential roles in HFD-induced alliin, mainly through steroid biosynthesis, triglyceride metabolism, drug metabolism–cytochrome P450, and the PI3K–Akt signaling pathway, according to transcriptomics analysis. Metabolomics results revealed 18 significantly different metabolites between the alliin group and HFD group, which were classified as carboxylic acids, such as N-undecanoylglycine, adipic acid, D-pantothenic acid, cyprodenate, and pivagabine. We found pantothenic acid played a vital role and was effective through pantothenic acid and CoA biosynthesis metabolism. The “steroid biosynthesis pathway” was identified as the most significant metabolic pathway by integrated transcriptomics and metabolomics analysis. This work offered a theoretical framework for the mechanism of alliin lipid lowering in the future. The development and utilization of alliin will be a viable strategy to improve the health status of people with hyperlipidemia, suggesting prospective market opportunities.
A Functional Drink Containing Kaempferia parviflora Extract Increases Cardiorespiratory Fitness and Physical Flexibility in Adult Volunteers
Authors: Wattanathorn Jintanaporn , Tong-Un Terdthai , Thukham-Mee Wipawee , Weerapreeyakul Natthida
Published: September 2023

Owing to the reputation of Kaempferia parviflora and the crucial role of oxidative stress on the disturbance of physical fitness, the effect of a functional drink containing K. parviflora extract (KP) on the physical fitness of healthy adult volunteers was assessed. Healthy male and female volunteers (19–60 years old) were randomly divided into placebo, KP90, and KP180 groups. All the subjects in KP90 and KP180 were directed to consume a functional drink containing K. parviflora extract at doses of 90 and 180 mg per serving per 80 mL, respectively. Parameters of physical fitness, including cardiovascular endurance, muscular strength and endurance, flexibility, and body composition, together with changes in lactate, creatinine kinase, and oxidative stress markers were assessed before the intervention, and at 6 and 12 weeks of intervention. The oxidative stress markers, creatine kinase, and lactate were also measured. Subjects who consumed the developed drink had increased VO2 max and improved performance in a timed shuttle run test and 5 min distance run, and exhibited decreased oxidative stress and lactate; therefore, K. parviflora extract can be successfully used for developing a KP drink to improve cardiorespiratory fitness and physical performance by improving oxidative stress and lactate.