bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the Experiences of Physical Activity, Body Image, and Quality of Life in Young Adult Males Living with and beyond Cancer
Authors: Dhruva Tana , Sim Jenna A. P. , Wagoner Chad W. , Kenny Sarah J. , Langelier David M. , Culos-Reed S. Nicole
Published: August 2024

For young adults (YAs), a cancer diagnosis and subsequent treatments may result in physical changes that can negatively impact body image (BI) and health-related quality of life (HRQL). Physical activity (PA) is an evidence-based tool found to impact both BI and HRQL. However, most research has focused on the perspectives of older adults with breast or prostate cancer. No research has explored the experiences of PA, BI, and HRQL in YA males affected by cancer. A qualitative study was designed for YA males diagnosed with cancer between the ages of 20 and 39 years. Eligible participants were recruited through pre-existing exercise oncology studies, support organizations, and social media. Semi-structured interviews were conducted to understand participants’ experiences of PA, BI, and HRQL. All interviews were transcribed verbatim and analyzed using interpretive description. The participants were YA males (n = 7) with a mean age of 32.7 ± 4.0 years. Themes included a loss of identity due to cancer, building autonomy and identity using PA, and the “should” behind BI. PA for YA males living with and beyond cancer may support them in rebuilding their identity and BI. The development of exercise oncology resources for YA males may consider addressing BI through education or exercise prescription programs, with the goal of enhancing HRQL.
Comparison of Population Density Estimation Methods for Roe Deer (Capreolus capreolus)
Authors: Tóth Gergely , Katona Krisztián
Published: August 2024

Roe deer (Capreolus capreolus) populations have been increasing in Europe in the last decades. Without reliable methods, game managers frequently underestimate the population size, leading to underharvesting. The aim of this research was to identify the most suitable method for roe deer density estimation in lowland, sparsely forested, high-visibility flat areas in Hungary. The census data of the total counting in the daytime strip transect and the night spotlight strip transect, as the total counting of the sample areas with a thermal camera from observation points within 0–250 m and 0–500 m ranges, were compared in seven hunting areas. It was revealed that using the thermal camera within 0–250 m and the spotlight method in the same range gave the statistically highest population density values. There was no significant difference between the two methods. The smallest mean was revealed in the case of the daytime strip transect data. The thermal imaging method gave significantly lower values for the greater distance (250–500 m) than for the range of spotlighting (250 m). The night spotlight strip transect method and the counting from observation points with a thermal camera, both to 250 m, provided the highest values; thus, they are recommended to determine the roe deer population density in open flat areas. They require the same amount of human resources and time, but due to the high cost of the thermal camera, the spotlight is also perfectly suited for widespread use by hunting companies. The results supported the underestimation of roe deer populations.
Plant Communities of the Tern Sanctuary on the Matsu Islands as a Breeding Habitat for Seabirds
Authors: Wang Wei , Wang Chun-Min , Ho Yi-Chiao , Tang Kuan-Chen , Liao Min-Chun , Lin Hui-Wen , Tzeng Hsy-Yu
Published: August 2024

The Matsu Islands Tern Refuge comprises eight reefs located at a relay station on the East Asian bird migration route, and it attracts many transiting, wintering, or breeding birds to inhabit and live on the reefs every year. In order to understand the compositions of plant communities as a breeding habitat for seabirds, we investigated the plant communities of the eight reefs. A total of 130 plots of 10 × 10 square meters were established, from which we found 107 species of plants in 102 genera and 51 families. Among this, we found one critically endangered (CR) species, four vulnerable (VU) species, and three near-threatened (NT) species. The result of two-way indicator species analysis (TWINSPAN) and indicator value (IndVal) showed 130 samples were divided into 11 vegetation types; most of the vegetation types had significant indicator species. We also use the two-way to present the plot of detrended correspondence analysis (DCA) by vegetation types and reefs. Moreover, this result reveals that these samples were more clearly cluster divided by islands. Our results reveal that the compositions and characteristics of plant communities were related clearly to the environmental factors for each reef in the Matsu Islands Tern Refuge. Canonical correspondence analysis (CCA) indicated that species composition of vegetation yielded high correlation with soil property, especially with soil pH. In addition, we found that the traces of bird activity is relevant to the characteristics and structures of plant communities. We found that the plant communities comprising low-grass shrubs would provide relatively soft nesting materials and sheltering effects for eggs or hatchlings for terns. Compared to low-grass shrubs, the traits of high-grass shrubs would not be beneficial to nest for breeding of terns on the ground, and no nested trace was found in these plant communities.
Accuracy Evaluation of GPT-Assisted Differential Diagnosis in Emergency Department
Authors: Shah-Mohammadi Fatemeh , Finkelstein Joseph
Published: August 2024

In emergency department (ED) settings, rapid and precise diagnostic evaluations are critical to ensure better patient outcomes and efficient healthcare delivery. This study assesses the accuracy of differential diagnosis lists generated by the third-generation ChatGPT (ChatGPT-3.5) and the fourth-generation ChatGPT (ChatGPT-4) based on electronic health record notes recorded within the first 24 h of ED admission. These models process unstructured text to formulate a ranked list of potential diagnoses. The accuracy of these models was benchmarked against actual discharge diagnoses to evaluate their utility as diagnostic aids. Results indicated that both GPT-3.5 and GPT-4 reasonably accurately predicted diagnoses at the body system level, with GPT-4 slightly outperforming its predecessor. However, their performance at the more granular category level was inconsistent, often showing decreased precision. Notably, GPT-4 demonstrated improved accuracy in several critical categories that underscores its advanced capabilities in managing complex clinical scenarios.
An Optimized Encryption Storage Scheme for Blockchain Data Based on Cold and Hot Blocks and Threshold Secret Sharing
Authors: Yang Dong , Tsai Wei-Tek
Published: August 2024

In recent years, with the rapid development of blockchain technology, the issues of storage load and data security have attracted increasing attention. Due to the immutable nature of data on the blockchain, where data can only be added and not deleted, there is a significant increase in storage pressure on blockchain nodes. In order to alleviate this burden, this paper proposes a blockchain data storage strategy based on a hot and cold block mechanism. It employs a block heat evaluation algorithm to assess the historical and correlation-based heat indicators of blocks, enabling the identification of frequently accessed block data for storage within the blockchain nodes. Conversely, less frequently accessed or “cold” block data are offloaded to cloud storage systems. This approach effectively reduces the overall storage pressure on blockchain nodes. Furthermore, in applications such as healthcare and government services that utilize blockchain technology, it is essential to encrypt stored data to safeguard personal privacy and enforce access control measures. To address this need, we introduce a blockchain data encryption storage mechanism based on threshold secret sharing. Leveraging threshold secret sharing technology, the encryption key for blockchain data is fragmented into multiple segments and distributed across network nodes. These encrypted key segments are further secured through additional encryption using public keys before being stored. This method serves to significantly increase attackers’ costs associated with accessing blockchain data. Additionally, our proposed encryption scheme ensures that each block has an associated encryption key that is stored alongside its corresponding block data. This design effectively mitigates vulnerabilities such as weak password attacks. Experimental results demonstrate that our approach achieves efficient encrypted storage of data while concurrently reducing the storage pressure experienced by blockchain nodes.
Transforming Educational Leadership: A Historical Context
Authors: Townsend Tony
Published: August 2024

The purpose of this article is to provide a context for this Special Issue, which considers the transformation of school leadership over time, providing some background to the roots of where we are now [...]
Research on Surface Processing Method of Pulse Transmission Signal of Amplitude-Modulated Drilling Fluid in 10,000-m Deep Wells
Authors: Wang Qing , Ji Guodong , Guo Jianhua , Wu Ke , Mei Chao , Zeng Long , Xue Qilong
Published: August 2024

Conventional Measurement-While-Drilling (MWD) technology is unable to function statically at the predicted temperatures of deep formations exceeding 200 °C in wells reaching depths of 10,000 m. It is limited to measuring downhole engineering parameters through purely mechanical means, such as inclination. However, the accurate long-distance transmission of drilling fluid pulse signals poses a significant bottleneck, restricting the application of these mechanical measurement methods. To address these issues, this paper develops and designs an algorithm to identify and analyze the amplitude characteristics of deep well mud signals. By employing a signal coding algorithm, a signal processing analysis method, and a signal feature recognition algorithm based on grey correlation degree, we construct a signal recognition method capable of decoding mud amplitude encoded signals. Key techniques such as filtering, smoothing, and feature extraction are utilized in the signal processing, and the proposed method’s effectiveness is verified through the analysis of collected signals. Furthermore, long-distance simulation analysis software is developed to evaluate waveform distortion during extended transmission, confirming the feasibility of the recognition algorithm. Laboratory experiments demonstrate that this algorithm can accurately recognize and demodulate signals generated by mechanical inclinometer structures, providing a novel decoding method for signal transmission in deep and ultra-deep wells.
Smart IoT SCADA System for Hybrid Power Monitoring in Remote Natural Gas Pipeline Control Stations
Authors: Waqas Muhammad , Jamil Mohsin
Published: August 2024

A pipeline network is the most efficient and rapid way to transmit natural gas from source to destination. The smooth operation of natural gas pipeline control stations depends on electrical equipment such as data loggers, control systems, surveillance, and communication devices. Besides having a reliable and consistent power source, such control stations must also have cost-effective and intelligent monitoring and control systems. Distributed processes are monitored and controlled using supervisory control and data acquisition (SCADA) technology. This paper presents an Internet of Things (IoT)-based, open-source SCADA architecture designed to monitor a Hybrid Power System (HPS) at a remote natural gas pipeline control station, addressing the limitations of existing proprietary and non-configurable SCADA architectures. The proposed system comprises voltage and current sensors acting as Field Instrumentation Devices for required data collection, an ESP32-WROOM-32E microcontroller that functions as the Remote Terminal Unit (RTU) for processing sensor data, a Blynk IoT-based cloud server functioning as the Master Terminal Unit (MTU) for historical data storage and human–machine interactions (HMI), and a GSM SIM800L module and a local WiFi router for data communication between the RTU and MTU. Considering the remote locations of such control stations and the potential lack of 3G, 4G, or Wi-Fi networks, two configurations that use the GSM SIM800L and a local Wi-Fi router are proposed for hardware integration. The proposed system exhibited a low power consumption of 3.9 W and incurred an overall cost of 40.1 CAD, making it an extremely cost-effective solution for remote natural gas pipeline control stations.
Solving the Vehicle Routing Problem with Stochastic Travel Cost Using Deep Reinforcement Learning
Authors: Cai Hao , Xu Peng , Tang Xifeng , Lin Gan
Published: August 2024

The Vehicle Routing Problem (VRP) is a classic combinatorial optimization problem commonly encountered in the fields of transportation and logistics. This paper focuses on a variant of the VRP, namely the Vehicle Routing Problem with Stochastic Travel Cost (VRP-STC). In VRP-STC, the introduction of stochastic travel costs increases the complexity of the problem, rendering traditional algorithms unsuitable for solving it. In this paper, the GAT-AM model combining Graph Attention Networks (GAT) and multi-head Attention Mechanism (AM) is employed. The GAT-AM model uses an encoder–decoder architecture and employs a deep reinforcement learning algorithm. The GAT in the encoder learns feature representations of nodes in different subspaces, while the decoder uses multi-head AM to construct policies through both greedy and sampling decoding methods. This increases solution diversity, thereby finding high-quality solutions. The REINFORCE with Rollout Baseline algorithm is used to train the learnable parameters within the neural network. Test results show that the advantages of GAT-AM become greater as problem complexity increases, with the optimal solution generally unattainable through traditional algorithms within an acceptable timeframe.
Thermodynamic and Economic Analysis of a Phosphoric Acid Fuel Cell Combined Heating Cooling and Power System
Authors: Chen Zhao , Mohd Ripin Zaidi , Wang Jie
Published: August 2024

This study proposes an innovative hybrid system that integrates a phosphoric acid fuel cell (PAFC) with an absorption refrigeration system (ARS) to enhance overall exergy efficiency. Waste heat from the PAFC is used in ARS generation. An evaluation is made of the energy efficiency, economic aspects, and the influence of the operating pressures of the two working fluid pairs, LiBr/H2O and R134a/DMF. In the combined PAFC-ARS, the absorption refrigeration unit incurs the highest exergy loss: 157 kW (R134a/DMF) and 146 kW (LiBr/H2O). The second-largest loss is experienced by the pure electrical generation PAFC unit at 117 kW. From an economic perspective, PAFC-ARS (LiBr/H2O) systems incur costs of USD 2.4/t for both hot water and cooling water, and USD 0.13 kW/h for electricity, with an 8 year payback period. In comparison, the R134a/DMF system entails costs of USD 2.1/t for hot water and cooling water and USD 0.16 kW/h for electricity. The PAFC exhibits a net output power of 434 kW, considering both energy and exergy perspectives. The corresponding maximum net electric energy efficiency (ηI) of the PAFC is 52%, while the overall exergy efficiency of the cooling model (ηII,dc) of the PAFC-ARS peaks at 56%, and the overall exergy efficiency of the heating model (ηII,dh) reaches its maximum at 61%. In conclusion, the PAFC-ARS (LiBr/H2O) demonstrates superior economic viability.
An Up-to-Date Review of Passive Building Envelope Technologies for Sustainable Design
Authors: Kitsopoulou Angeliki , Bellos Evangelos , Tzivanidis Christos
Published: August 2024

A primary driving force of today’s urban environment is the development or enhancement of building stock with a focus on minimizing its environmental footprint, eliminating its dependence on fossil fuels, enforcing its energy efficiency and self-sufficiency, and helping alleviate climate change. Therefore, in the present study, an up-to-date review regarding the passive building retrofitting techniques for sustainable and energy efficiency design is conducted. Numerous passive building solutions and design concepts are thoroughly examined in terms of innovation and energy-saving potential. The examined techniques include novel thermal insulation materials, innovative windows systems, high thermal mass technologies, optically advanced coatings appropriate for cooling abatement, and various energy-efficient bioclimatic designs, for instance, shading techniques, mechanical ventilation in combination with heat recovery, and green roofs and façades. The scope of the present review is to thoroughly and comparatively investigate passive building energy retrofit solutions as presented in the recent scientific literature mainly within the last five or up to ten years. The passive, energy-mitigating solutions are examined in terms of energy savings primarily in residential buildings, but also in tertiary buildings, as well as of specific investment costs. Lastly, an extensive discussion evaluating the comparative advantages and disadvantages of the examined passive envelope technologies is conducted, allowing a comprehensive and multilevel comparison.
Factors Influencing the Energy Consumption in a Building: Comparative Study between Two Different Climates
Authors: Ali-Tagba Abdoul-Razak , Baneto Mazabalo , Lucache Dumitru Dorin
Published: August 2024

The design of a high energy performance building requires an assessment of the various design options. Energy simulation offers interesting possibilities for clarifying the architect’s decisions at this level, especially in the initial design phases where the greatest opportunities for optimization lie. The aim of this work is to develop an approach for the evaluation and optimal use of energy simulation in the building design phases. To do this, EnergyPlus building simulation software was used to simulate the energy consumption of the Faculty of Electrical Engineering building at “Gheorghe Asachi” Technical University in Iasi, in order to identify the factors influencing energy consumption in buildings. The results of this study show that an increase in the cooling setpoint temperature from 22 °C to 28 °C in the roof construction can reduce operating temperatures by 14.2% and 20.0%, respectively. This optimization could significantly reduce the hours of thermal discomfort, in a ratio of 6.0 and 3.25, respectively. Consequently, optimizing parameters linked to design and the heating and cooling systems within the building makes it possible to achieve energy savings and ensure thermal comfort in buildings.
Performance Enhancement of H-Type Darrieus VAWT Using a Hybrid Method of Blade Pitch Angle Regulation
Authors: Hammad Mahmood Abduljabbar , Mahmoud Abdelgadir Mohamed , Abdelrhman Ahmed M. , Sarip Shamsul
Published: August 2024

Blade pitch angle regulation is an effective approach to enhance the performance of H-type Darrieus Vertical Axis Wind Turbines (VAWTs). Improving the blade interaction with the wind for this type of rotor is a challenging task, especially in unsteady wind conditions. This paper presents a novel hybrid approach that integrates fixed and variable blade pitch angle regulation techniques, aiming to enhance the wind turbine efficiency across various operational stages and wind speeds. The proposed blade pitch angle regulation method targets a less complicated, mechanically feasible, and cost-effective pitching technique. This study uses the Double Multiple Streamtube (DMST) model to analyze the aerodynamic performance and calculate the power output generated at different pitch angles. MATLAB Simulink was utilized to implement the DMST model, and experimental validation was conducted to confirm the results. The findings indicate that the blade pitch angle regulation has significantly enhanced the self-starting ability of H-type Darrieus VAWT by 80%. Additionally, the maximum rotational speed and power coefficient are achieved at a zero pitch angle. Furthermore, regulating the blade pitch angle allows for the effective control of excessive rotational speeds during high wind conditions.
Research on an Intelligent Fault Diagnosis Method for Small Modular Reactors
Authors: Ren Changan , Lei Jichong , Liu Jie , Hong Jun , Hu Hong , Fang Xiaoyong , Yi Cannan , Peng Zhiqiang , Yang Xiaohua , Yu Tao
Published: August 2024

Small modular reactors (SMRs) are currently advancing towards increased degrees of automation and intelligence, with intelligent control emerging as a prominent trend in SMR development. SMRs exhibit significant variations in design specifications and safety auxiliary system design as compared to conventional commercial nuclear power reactors. Consequently, defect diagnostic techniques that rely on commercial nuclear power plants are not appropriate for SMRs. This study designed a defect detection system for the System-integrated Modular Advanced ReacTor SMR by utilizing the PCTRAN/SMR V1.0 software and a deep learning neural network structure. Through the comparison of several neural network designs, it was discovered that the CNN-BiLSTM model, which utilizes bidirectional data processing, obtained a fault diagnostic accuracy of 97.33%. This result confirms the accuracy and effectiveness of the fault diagnosis system. This strongly supports the eventual implementation of autonomous control for SMRs.
Motor Fault Diagnosis Using Attention-Based Multisensor Feature Fusion
Authors: Miao Zhuoyao , Feng Wenshan , Long Zhuo , Wu Gongping , Deng Le , Zhou Xuan , Xie Liwei
Published: August 2024

In order to reduce the influence of environmental noise and different operating conditions on the accuracy of motor fault diagnosis, this paper proposes a capsule network method combining multi-channel signals and the efficient channel attention (ECA) mechanism, sampling the data from multiple sensors and visualizing the one-dimensional time-frequency domain as a two-dimensional symmetric dot pattern (SDP) image, then fusing the multi-channel image data and extracting the image using a capsule network combining the ECA attention mechanism features to match eight different fault types for fault classification. In order to guarantee the universality of the suggested model, data from Case Western Reserve University (CWRU) is used for validation. The suggested multi-channel signal fusion ECA attention capsule network (MSF-ECA-CapsNet) model fault identification accuracy may reach 99.21%, according to the experimental findings, which is higher than the traditional method. Meanwhile, the method of multi-sensor data fusion and the use of the ECA attention mechanism make the diagnosis accuracy much higher.
Numerical Simulation to Investigate the Effect of Adding a Fixed Blade to a Magnus Wind Turbine
Authors: Dyusembaeva Ainura , Tanasheva Nazgul , Tussypbayeva Ardak , Bakhtybekova Asem , Kutumova Zhibek , Kyzdarbekova Sholpan , Mukhamedrakhim Almat
Published: August 2024

The investigation of aerodynamics and the establishment of flow patterns around finite-length cylinders with various end shapes in a free, boundless air flow with longitudinal and transverse flow over a wide range of geometric and regime parameters is sketchy and does not have a wide range of geometric and regime parameters. This, in turn, affects the entire aerodynamics of the streamlined body. This paper considers the numerical simulation of a wind turbine made of combined blades. CFD (computational fluid dynamics) methods based on the realisable k-ε turbulence model were used in the study. The results on the influence of the position of the fixed blade on the angle of inclination are obtained (0°, 15°, 30°, 45°, and 60°). The authors found that the pressure of a fixed blade at an optimal angle increases the power coefficient Cp by 35–40%. The dependence of the Cp power coefficient on the rotational speed (speed coefficient) for a three-bladed wind turbine was also established, and it was determined that the maximum value of Cp = 0.28 at Z = 4.9. Based on the results obtained, it was determined that the wind turbine has a maximum power coefficient at an angle of inclination of 0 degrees.
Response of Thinning to C:N:P Stoichiometric Characteristics and Seasonal Dynamics of Leaf-Litter-Soil System in Cupressus funebris Endl. Artificial Forests in Southwest, China
Authors: Jiang Xue , Yang Jingtian , Yang Yulian , Yang Jiaping , Dong Qing , Zeng Houyuan , Zhang Kaiyou , Xu Ning , Yuan Jiayi , Liu Mei , Li Dehui , Wu Qinggui
Published: August 2024

Ecological stoichiometry is essential for investigating biogeochemical cycling in an ecosystem. Thinning, a management practice that closely mimics natural processes, significantly influences stand structure and microclimate, thereby affecting nutrient cycling. Nonetheless, seasonal variations in ecological stoichiometry across the leaf-litter-soil continuum under different thinning regimes remain inadequately understood. In this study, we evaluated three thinning methods (strip filling (SF), ecological thinning (ET), and forest gap (FG)) to investigate the stoichiometric characteristics of Cupressus funebris Endl (C. funebris). within the leaf-litter-soil system in Southwest China. The samples were collected during four distinct seasonal periods: early dry season (January–March, EDS), late dry season (April–June, LDS), early wet season (July–September, EWS), and late wet season (October–December, LWS). The results indicated that the (1) carbon (C), nitrogen (N), and phosphorus (P) contents and C:N:P ratio in leaves, litter, and soils varied widely and were strongly influenced by thinning method and season. (2) In the EDS, the soil TP content significantly decreased by 36.9% (p < 0.05), 41.67% (p < 0.05), and 17.9% (p < 0.05) under ET, FG, and SF treatments compared to the pure C. funebris forest (PC). (3) Compared to the PC, the leaf organic C content under ET significantly increased by 6.6% (EDS, p < 0.05), 8.4% (EWS, p < 0.05), 24.8% (LDS, p < 0.05), and 11.5% (EWS, p < 0.05). (4) Under identical thinning methods, the contents of litter C, litter N, litter P, leaf N, and leaf P (excluding litter C in SF) were found to be highest in the LWS. Conversely, the ratios of litter C:N, litter C:P, litter N:P, leaf C:N, leaf C:P, leaf N:P, soil N:P, and soil C:P (except for the ratios of litter N:P in ET and FG) were observed to be lowest in the LWS. (5) Season and thinning method significantly affected the internal stability of P stoichiometric homeostasis, and litter P under ET (EWS) was categorized as “plastic” (p < 0.1, 0.75 < H). (6) The results of the structural equation model show that the thinning method has a direct positive impact on leaf C, N, and P contents and a direct negative impact on the chemical stoichiometry of leaves and soil. Season has a direct positive impact on soil C, N, and P contents, as well as on the chemical stoichiometry of litter and leaves; however, they have a direct negative impact on leaf C, N, and P contents. This study contributes to C. funebris plantation management and provides basic information for global stoichiometric analysis.
Improved Branch Volume Prediction of Multi-Stemmed Shrubs: Implications in Shrub Volume Inventory and Fuel Characterization
Authors: Yuan Chuan , Zhou Jiayu , Xiang Wenhua , Lu Nan , Hu Yanting , Guo Li , Wang Yi , Chen Weiliang , Gao Guangyao , Tang Qiang , Wang Sheng , Cheng Xian , Gao Jie , Wei Xiaohua
Published: August 2024

Accurately estimating the volume of woody vegetation is critical for assessing fuel characteristics and associated wildfire risks in shrublands. However, few studies have investigated the branch volume of multi-stemmed shrubs, a dominant life form in wildfire-prone drylands. This study predicts branch volume using the inflection point of branch diameter. This inflection point, identified using the “Segmented” package in R, marks the transition from a gradual decrease to a significant reduction in diameter along the stem. The volume of branch segment above this point is calculated as a cone, and below it, a cylinder. We validated this method on various species such as Caragana korshinskii, Salix psammophila, and Vitex negundo. Good estimations were achieved with an average 19.2% bias relative to reference branch volumes, outperforming conventional methods that subjectively treated the whole branch as either a cylinder (96.9% bias) or a cone (−34.4% bias). We tallied branches by basal diameter and provided inventories for easily locating the inflection point, as well as using two-way branch volume tables for rapid volume predictions in shrubland. In general, we developed an effective method for estimating branch volumes of multi-stemmed shrubs, enabling its application to larger-scale shrubland volumetric prediction. This advancement supports wildfire hazard assessment and informs decision-making in fuel treatments.
Differences in Leaf Functional Traits of Quercus rehderiana Hand.-Mazz. in Forests with Rocky and Non-Rocky Desertification in Southwest China
Authors: Bai Xiao-Long , Feng Tu , Zou Shun , He Bin , Chen Yang , Li Wang-Jun
Published: August 2024

Quercus rehderiana Hand.-Mazz. belongs to Quercus sect. Heteroallenes’ of the Fagaceae family. It is widely distributed in forests with rocky and non-rocky desertification in Guizhou Province of Southwest China. However, our knowledge of the adaptation strategies of Quercus in forests with rocky desertification is surprisingly lacking. In this study, 16 leaf traits (morphological, anatomical, and chemical) of Quercus rehderiana were investigated in 15 individuals in five 20 × 20 m quadrants of forests with rocky and non-rocky desertification. The aim was to analyze their strategies of adaptation to arid and poor-soil environments in forests with rocky desertification. The results showed that Quercus rehderiana leaves in forests with rocky desertification had a greater leaf thickness, specific leaf area, abaxial epidermis thickness, and sponge mesophyll thickness but a lower leaf area than in forests with non-rocky desertification. Quercus rehderiana leaves in forests with rocky desertification had higher calcium and magnesium concentrations and a higher N:P ratio but lower potassium and phosphorus concentrations than in forests with non-rocky desertification. The results of principal component analysis showed that forests with rocky desertification tended to show resource-conserving strategies with thicker leaf tissue and a lower nutrient concentration, while forests with non-rocky desertification tended to show resource acquisition strategies with a greater leaf area and potassium concentration. In resource-poor environments, species that adopt conservative resource strategies are more likely to survive; therefore, we forecasted that more conservative, slow-growing Quercus rehderiana will be more stable over time.
Dynamic Graph Representation Learning for Passenger Behavior Prediction
Authors: Xie Mingxuan , Zou Tao , Ye Junchen , Du Bowen , Huang Runhe
Published: August 2024

Passenger behavior prediction aims to track passenger travel patterns through historical boarding and alighting data, enabling the analysis of urban station passenger flow and timely risk management. This is crucial for smart city development and public transportation planning. Existing research primarily relies on statistical methods and sequential models to learn from individual historical interactions, which ignores the correlations between passengers and stations. To address these issues, this paper proposes DyGPP, which leverages dynamic graphs to capture the intricate evolution of passenger behavior. First, we formalize passengers and stations as heterogeneous vertices in a dynamic graph, with connections between vertices representing interactions between passengers and stations. Then, we sample the historical interaction sequences for passengers and stations separately. We capture the temporal patterns from individual sequences and correlate the temporal behavior between the two sequences. Finally, we use an MLP-based encoder to learn the temporal patterns in the interactions and generate real-time representations of passengers and stations. Experiments on real-world datasets confirmed that DyGPP outperformed current models in the behavior prediction task, demonstrating the superiority of our model.
Enhancing Gluten-Free Muffins with Milk Thistle Seed Proteins: Evaluation of Physicochemical, Rheological, Textural, and Sensory Characteristics
Authors: Ozgolet Muhammed , Kasapoglu Muhammed Zahid , Avcı Esra , Karasu Salih
Published: August 2024

This study investigated the potential utilization of milk thistle seed protein (MTP) isolates in gluten-free muffins to enhance the protein quantity and technological attributes. MTP was employed to partially substitute a blend including equal amounts of rice flour and corn starch (RCS) at 3%, 6%, 9%, and 12%. The study encompassed a rheological assessment of muffin batters and physicochemical, textural, and sensory analyses of the muffins. The consistency coefficient (K) of muffin batters exhibited an increase with the incorporation of MTP, with all batters demonstrating shear-thinning behavior (n < 1). The dough samples exhibited solid-like characteristics attributed to G′ > G″, indicative of their viscoelastic nature. The storage modulus (G′) and loss modulus (G″) escalated with higher levels of MTP, suggesting an overall enhancement in dough viscoelasticity. The muffin containing wheat flour displayed the lowest hardness value, followed by MTP-added muffins at ratios of 12% and 9%. Additionally, MTP-added muffins exhibited greater springiness values than control samples without MTP (C2). However, the oxidative stability of MTP-added muffins was lower than the wheat control muffin (C1) and gluten-free control muffin. The protein content in muffins increased with MTP addition, reaching parity with wheat flour muffins at 6% MTP replacement. Sensory analysis revealed that substituting RCS with up to 6% MTP did not significantly alter the overall quality (p > 0.05), whereas higher MTP levels (9% and 12%) led to a decline in sensory attributes. Incorporating MTP at up to 6% yielded protein-enriched muffins with sensory characteristics comparable to the wheat flour muffin (C1). Furthermore, higher MTP additions (9% and 12%) conferred more favorable textural properties than the C2 muffin. However, the oxidative stability of the control muffins was found to be higher than that of MTP-added muffins. This study suggested that MTP could be a potential ingredient to increase the protein amount and specific volume of gluten-free muffins and to improve textural attributes such as springiness and hardness.
Effect of Carbohydrase Treatment on the Dietary Fibers and Bioactive Compounds of Cocoa Bean Shells (CBSs)
Authors: Disca Vincenzo , Jaouhari Yassine , Carrà Francesca , Martoccia Manuel , Travaglia Fabiano , Locatelli Monica , Bordiga Matteo , Arlorio Marco
Published: August 2024

Cocoa bean shells (CBSs) are a byproduct of the chocolate production process, representing the external layer of the cocoa bean. CBSs exhibit many interesting chemical and nutritional characteristics resulting in a very rich content of dietary fiber (DF) and antioxidant compounds such as phenolic acids and flavan-3-ols. The DF fraction of CBSs is notably rich in soluble dietary fibers (SDFs), which may be associated with fermentability and prebiotic properties. The objective of this study was the valorization of CBSs through enzymatic treatments, thereby increasing the solubility of DF and potentially augmenting fermentability. CBSs were treated both raw and defatted. Three sets of carbohydrases were used in order to impact the dietary fiber profile. Cellulase, xylanase, pectinase and their combinations were used to perform enzymatic treatments. The application of cellulase, xylanase and a combination of both enzymes proved effective in achieving a high SDF destructuring of the insoluble dietary fiber (IDF) fraction in both defatted and raw CBSs. Notably, the SDF/IDF ratio was significantly elevated in the enzymatically hydrolyzed samples (1.13–1.33) compared to the untreated CBSs (0.33). Furthermore, the various treatments did not affect the antioxidant activity or the content of the main bioactive compounds. These results provide a foundation for new opportunities in the biovalorization of CBSs through green techniques for a range of potential industrial applications in the food and nutraceutical sectors.
Burden of Disease Due to Respiratory Syncytial Virus in Adults in Five Middle-Income Countries
Authors: Gómez Jorge A. , Cintra Otavio , Berzanskis Arnas , Pacheco Salma , Jaswantlal Henny , Hasnaoui Abdelkader El , van Oorschot Desirée A. M. , Guzman-Holst Adriana
Published: August 2024

Respiratory syncytial virus (RSV) is an important cause of severe respiratory disease in older adults. Understanding the disease burden is crucial for guiding vaccination policy and raising disease awareness. We estimated the burden of RSV hospitalizations and deaths in adults in five middle-income countries: Argentina, Brazil, Chile, Mexico, and Malaysia. Hospital discharge and death statistics due to any respiratory disease (ICD-10 codes: J00–99) from 2010 to 2022 were obtained. The RSV attributable burden on hospitalizations and deaths by age group was determined for 2019 using previously published estimates. Latin American countries showed distinct annual peaks in respiratory-related hospitalizations and deaths during winter months that were absent in Malaysia. Among ≥20-year-olds in 2019, there were 14,604 RSV-attributable hospitalizations nationally in Argentina, 44,323 in Brazil, 4529 in Chile, 7416 in Malaysia, and 8651 in Mexico, and 60–74% in ≥65-year-olds. There were also 3518 RSV-attributable deaths in Argentina, 9115 in Brazil, 801 in Chile, 704 in Malaysia, and 3806 in Mexico 79–88% in ≥65-year-olds. Incidences of RSV-attributable hospitalizations in ≥75-year-olds ranged between 256.3 and 294.3 per 100,000 population, and deaths between 33.6 and 112.9 per 100,000 population. RSV is associated with a substantial disease burden beyond pediatric age groups, and preventive vaccines could have a major impact on this burden, especially in older adults.
Automatic Functional Classification of Buildings Supported by a POI Semantic Characterization Knowledge Graph
Authors: Su Youneng , Xu Qing , Zhu Xinming , Zhang Fubing , Liu Yi
Published: August 2024

The division of urban functional zones is crucial for understanding urban characteristics and aiding in urban management and planning. Traditional methods, like dividing based on blocks and grids, are insufficient for modern demands. To address this, a knowledge-graph-supported method for building functional category division is proposed. Firstly, the associations between points of interest (POI) and buildings are established using triangulation and buffer zones. Then, a knowledge graph of buildings is constructed through entity and relationship extraction. A functional category classification model supported by the Z-score is designed using the semantic characterizations of surrounding POIs for inference rules. The results demonstrate high accuracy in building functional category division, supporting the refinement and intelligent expression of urban functional zones for urban construction, planning, and management.
Structural and Mechanistic Insights into a Novel Monooxygenase for Poly(acrylic acid) Biodegradation
Authors: Feng Rui , Zhao Juyi , Li Xiaochen , Dong Sijun , Ma Dan
Published: August 2024

Polyacrylamide (PAM) is a high-molecular-weight polymer with extensive applications. However, the inefficient natural degradation of PAM results in environmental accumulation of the polymer. Biodegradation is an environmentally friendly approach in the field of PAM treatment. The first phase of PAM biodegradation is the deamination of PAM, forming the product poly(acrylic acid) (PAA). The second phase of PAM biodegradation involves the cleavage of PAA into small molecules, which is a crucial step in the degradation pathway of PAM. However, the enzyme that catalyzes the degradation of PAA and the molecular mechanism remain unclear. Here, a novel monooxygenase PCX02514 is identified as the key enzyme for PAA degradation. Through biochemical experiments, the monooxygenase PCX02514 oxidizes PAA with the participation of NADPH, causing the cleavage of carbon chains and a decrease in the molecular weight of PAA. In addition, the crystal structure of the monooxygenase PCX02514 is solved at a resolution of 1.97 Å. The active pocket is in a long cavity that extends from the C-terminus of the TIM barrel to the protein surface and exhibits positive electrostatic potential, thereby causing the migration of oxygen-negative ions into the active pocket and facilitating the reaction between the substrates and monooxygenase PCX02514. Moreover, Arg10-Arg125-Ser186-Arg187-His253 are proposed as potential active sites in monooxygenase PCX02514. Our research characterizes the molecular mechanism of this monooxygenase, providing a theoretical basis and valuable tools for PAM bioremediation.
The Key Targets of NO-Mediated Post-Translation Modification (PTM) Highlighting the Dynamic Metabolism of ROS and RNS in Peroxisomes
Authors: Ergashev Ulugbek , Yu Mei , Luo Long , Tang Jie , Han Yi
Published: August 2024

Nitric oxide (NO) has been firmly established as a key signaling molecule in plants, playing a significant role in regulating growth, development and stress responses. Given the imperative of sustainable agriculture and the urgent need to meet the escalating global demand for food, it is imperative to safeguard crop plants from the effects of climate fluctuations. Plants respond to environmental challenges by producing redox molecules, including reactive oxygen species (ROS) and reactive nitrogen species (RNS), which regulate cellular, physiological, and molecular processes. Nitric oxide (NO) plays a crucial role in plant stress tolerance, acting as a signaling molecule or free radical. NO is involved in various developmental processes in plants through diverse mechanisms. Exogenous NO supplementation can alleviate the toxicity of abiotic stresses and enhance plant resistance. In this review we summarize the studies regarding the production of NO in peroxisomes, and how its molecule and its derived products, (ONOO−) and S-nitrosoglutathione (GSNO) affect ROS metabolism in peroxisomes. Peroxisomal antioxidant enzymes including catalase (CAT), are key targets of NO-mediated post-translational modification (PTM) highlighting the dynamic metabolism of ROS and RNS in peroxisomes.
Hyperthermia Intensifies α-Mangostin and Synthetic Xanthones’ Antimalignancy Properties
Authors: Rech Jakub , Żelaszczyk Dorota , Marona Henryk , Gunia-Krzyżak Agnieszka , Żmudzki Paweł , Bednarek Ilona Anna
Published: August 2024

In order to improve naturally occurring xanthones’ anticancer properties, chemical synthesis is proposed. In this study, from eight novel xanthone derivatives coupled to morpholine or aminoalkyl morpholine, only the two most active ones were chosen. For additional enhancement of the anticancer activity of our tested compounds, we combined chemotherapy with hyperthermia in the range of 39–41 °C, from which the mild conditions of 39 °C were the most influencing. This approach had a profound impact on the anticancer properties of the tested compounds. TOV-21G and SC-OV-3 ovarian cell line motility and metastasis behavior were tested in native and hyperthermia conditions, indicating decreased wound healing properties and clonogenic activity. Similarly, the expression of genes involved in metastasis was hampered. The expression of heat shock proteins involved in cancer progression (Hsc70, HSP90A, and HSP90B) was significantly influenced by xanthone derivatives. Chemotherapy in mild hyperthermia conditions had also an impact on decreasing mitochondria potential, visualized with JC-1. Synthetic xanthone ring modifications may increase the anticancer activity of the obtained substances. Additional improvement of their activity can be achieved by applying mild hyperthermia conditions. Further development of a combined anticancer therapy approach may result in increasing currently known chemotherapeutics, resulting in a greater recovery rate and diminishment of the cytotoxicity of drugs.
2,3-Diphosphoglyceric Acid Alleviating Hypoxic-Ischemic Brain Damage through p38 MAPK Modulation
Authors: Ni Jiawei , Zhao Jing , Chen Haocong , Liu Wenjuan , Le Meini , Guo Xirong , Dong Xiaohua
Published: August 2024

Neonatal hypoxic-ischemic encephalopathy (HIE) is a critical condition characterized by significant brain damage due to insufficient blood flow and oxygen delivery at birth, leading to high rates of neonatal mortality and long-term neurological deficits worldwide. 2,3-Diphosphoglyceric acid (2,3-DPG), a small molecule metabolite prevalent in erythrocytes, plays an important role in regulating oxygen delivery, but its potential neuroprotective role in hypoxic-ischemic brain damage (HIBD) has yet to be fully elucidated. Our research reveals that the administration of 2,3-DPG effectively reduces neuron damage caused by hypoxia-ischemia (HI) both in vitro and in vivo. We observed a notable decrease in HI-induced neuronal cell apoptosis, attributed to the downregulation of Bax and cleaved-caspase 3, alongside an upregulation of Bcl-2 expression. Furthermore, 2,3-DPG significantly alleviates oxidative stress and mitochondrial damage induced by oxygen-glucose deprivation/reperfusion (OGD/R). The administration of 2,3-DPG in rats subjected to HIBD resulted in a marked reduction in brain edema and infarct volume, achieved through the suppression of neuronal apoptosis and neuroinflammation. Using RNA-seq analysis, we validated that 2,3-DPG offers protection against neuronal apoptosis under HI conditions by modulating the p38 MAPK pathway. These insights indicated that 2,3-DPG might act as a promising novel therapeutic candidate for HIE.
Genetic Dissection of ToLCNDV Resistance in Resistant Sources of Cucumis melo
Authors: Pérez-Moro Clara , Sáez Cristina , Sifres Alicia , López Carmelo , Dhillon Narinder P. S. , Picó Belén , Pérez-de-Castro Ana
Published: August 2024

Tomato leaf curl New Delhi virus (ToLCNDV) is a begomovirus causing significant melon (Cucumis melo) crop losses globally. This study aims to map the ToLCNDV resistance in the PI 414723 melon accession, previously identified and characterized through phenotypic studies, thereby exploring shared genomic regions with the established resistant source WM-7. In the present study, WM-7 and PI 414723 were crossed with the susceptible accessions ‘Rochet’ and ‘Blanco’ respectively, to generate F1 hybrids. These hybrids were self-pollinated to generate the populations for mapping the ToLCNDV resistance region and designing markers for marker-assisted selection. Disease evaluation included visual symptom scoring, viral-load quantification and tissue printing. Genotyping-by-sequencing and SNP markers were used for quantitative trait loci (QTL) mapping. For genetic analysis, qPCR and bulked segregant RNA-seq (BSR-seq) were performed. Gene expression was assessed using RNA-seq, and qRT-PCR was used for confirmation. The research narrows the candidate region for resistance in WM-7 and identifies overlapping QTLs on chromosome 11 in PI 414723, found in the region of the DNA primase large subunit. BSR-seq and expression analyses highlight potential regulatory roles of chromosome 2 in conferring resistance. Differential expression was confirmed for six genes in the candidate region on chromosome 2. This study confirms the existence of common resistance genes in PI 414723 and WM-7.