bluuebunny/crossref_metadata_2025 huggingface dataset:
Pulse Width Modulation-Controlled Switching Impedance for Wireless Power Transfer
Authors: Ma Bole , Chai Lin , Lu Jianghua , Sun Shixiong
Published: December 2023

The exceptional performance of the wireless power transfer (WPT) system hinges on its resonant state. However, the capacitance drift caused by manufacturing tolerance and temperature will result in a state of detuning. In this manuscript, a PWM-controlled switched impedance (PCSI) topology that can express inductive and capacitive is proposed to eliminate line mismatches resulting from the above factors. Firstly, the PCSI topology is introduced, and its placement is determined based on the characteristics of the inductor–capacitor–capacitor series (LCC-S) network. Secondly, the working principle of the proposed topology is introduced. Finally, the simulation and experimental results show that the system could be restored to its resonant state by adjusting the PCSI topology. Under different values of resonant capacitors, the PCSI topology enhances the output power of the system by 40 W~150 W compared to the previous state, and the efficiency is increased by 9~13%.
Environmental Protection Tax and Energy Efficiency: Evidence from Chinese City-Level Data
Authors: Qi Junmei , Song Yi , Zhang Yijun
Published: December 2023

The aggravated global warming and energy crisis have greatly challenged the healthy and sustainable development of society worldwide. Improving energy efficiency is one of the vital ways to overcome the dilemma. Existing studies explore the impact of environmental regulation on energy efficiency; however, the potential impact of the environmental protection tax (EPT) on urban energy efficiency has received little attention. Using the panel dataset of 278 Chinese cities from 2011 to 2019, the unified efficiency index (UEI) based on a total non-radial directional distance function (TNDDF) is first used to calculate urban energy efficiency. A difference-in-differences (DIDs) model is conducted to explore the impact of the EPT policy on the urban UEI and its potential mechanisms. The findings indicate that: (1) The average UEI in cities experienced an uptrend and a downtrend during 2011–2019. The overall UEI levels were low, especially in Jiaxiaguan, Tianshui, and Huyang cities. (2) The EPT policy significantly increases energy efficiency for the heavily polluting cities by approximately 5.21% more than that of the non-heavily polluting cities. (3) Heterogeneity analysis shows that EPT has a better effect on improving UEI in higher-level economic and non-resource-based cities. (4) Mechanism analysis implies that EPT boosts the urban UEI by stimulating urban green technology innovation, upgrading the industrial structure, and introducing foreign direct investment. This study offers empirical evidence and implications for policymakers using EPT to achieve higher urban energy efficiency and sustainable targets.
Forecasting of Solar Power Using GRU–Temporal Fusion Transformer Model and DILATE Loss Function
Authors: Mazen Fatma Mazen Ali , Shaker Yomna , Abul Seoud Rania Ahmed
Published: December 2023

Solar power is a clean and sustainable energy source that does not emit greenhouse gases or other atmospheric pollutants. The inherent variability in solar energy due to random fluctuations introduces novel attributes to the power generation and load dynamics of the grid. Consequently, there has been growing attention to developing an accurate forecast model using various machine and deep learning techniques. Temporal attention mechanisms enable the model to concentrate on the critical components of the input sequence at each time step, thereby enhancing the accuracy of the prediction. The suggested GRU–temporal fusion transformer (GRU-TFT) model was trained and validated employing the “Daily Power Production of Solar Panels” Kaggle dataset. Furthermore, an innovative loss function termed DILATE is introduced to train the proposed model specifically for multistep and nonstationary time series forecasting. The outcomes have been subjected to a comparative analysis with alternative algorithms, such as neural basis expansion analysis for interpretable time series (N-BEATS), neural hierarchical interpolation for time series (N-HiTS), and extreme gradient boosting (XGBoost), using several evaluation metrics, including the absolute percentage error (MAE), mean square error (MSE), and root mean square error (RMSE). The model presented in this study exhibited significant performance improvements compared with traditional statistical and machine learning techniques. This is evident from the achieved values of MAE, MSE, and RMSE, which were 1.19, 2.08, and 1.44, respectively. In contrast, the machine learning approach utilizing the Holt–Winters method for time series forecasting in additive mode yielded MAE, MSE, and RMSE scores of 4.126, 29.105, and 5.3949, respectively.
Experimental Investigation of the In-Cylinder Flow of a Compression Ignition Optical Engine for Different Tangential Port Opening Areas
Authors: Ichiyanagi Mitsuhisa , Yilmaz Emir , Hamada Kohei , Hara Taiga , Anggono Willyanto , Suzuki Takashi
Published: December 2023

The push for decarbonization of internal combustion engines (ICEs) has spurred interest in alternative fuels, such as hydrogen and ammonia. To optimize combustion efficiency and reduce emissions, a closer look at the intake system and in-cylinder flows is crucial, especially when a hard-to-burn fuel, such as ammonia is utilized. In port fuel injection ICEs, airflow within cylinders profoundly affects combustion and emissions by influencing the air–fuel mixing phenomenon. Adjusting intake port openings is an important factor in controlling the in-cylinder airflow. In previous experiments with a transparent cylinder, tangential and helical ports demonstrated that varying the helical port’s opening significantly impacts flow velocities, swirl ratios, and swirl center positions (SCPs). In this study, we used a particle image velocimetry technique to investigate how the tangential port’s opening affects intake and in-cylinder flows. Flow velocities were assessed at different planes near the cylinder head, evaluating streamline maps, turbulent kinetic energy (TKE), and SCPs. Under the given experimental conditions, swirl flows were successfully generated early in the compression stroke when the tangential port opening exceeded 25%. Our findings emphasize the importance of minimizing TKE and SCP variation for successful swirl flow generation in engine cylinders equipped with both tangential and helical ports.
Smart Decentralized Electric Vehicle Aggregators for Optimal Dispatch Technologies
Authors: Eltamaly Ali M.
Published: December 2023

The number of electric vehicles (EVs) is growing exponentially, which presents the power grid with new challenges to turn their reliance to renewable energy sources (RESs). Coordination between the available generations from RESs and the charging time should be managed to optimally utilize the available generation from RESs. The dispatch scheduling of EVs can significantly reduce the impact of these challenges on power systems. Three different technologies can be used to manage the dispatch of EV batteries which are unregulated charging (UC), unidirectional grid-to-vehicle (G2V), and bidirectional vehicle-to-grid (V2G) technologies. This study aims to address the primary reason for EV owners’ disbelief in the accuracy of battery wear models, which is impeding their involvement in V2G technology. This paper introduces a novel accurate EV battery wear model considering the instantaneous change in the operation of the EV battery. Moreover, an effective musical chairs algorithm (MCA) is used to reduce everyday expenses and increase revenue for V2G technologies in a short convergence time with accurate determination of optimal power dispatch scheduling. The results obtained from these three strategies are compared and discussed. The salient result from this comparison is that V2G technology increases wear and reduces the battery lifespan in comparison with the UC and G2V. The yearly expenses of G2V are reduced by 33% compared to the one associated with the UC. Moreover, the use of V2G technology provides each EV owner with USD 3244.4 net yearly profit after covering the charging and wear costs. The superior results extracted from the proposed model showed the supremacy of V2G usage, which is advantageous for both EV owners and the power grid.
Multi-Objective Capacity Optimization of Grid-Connected Wind–Pumped Hydro Storage Hybrid Systems Considering Variable-Speed Operation
Authors: Li Yang , Li Outing , Wu Feng , Ma Shiyi , Shi Linjun , Hong Feilong
Published: December 2023

The coordination of pumped storage and renewable energy is regarded as a promising avenue for renewable energy accommodation. Considering wind power output uncertainties, a collaborative capacity optimization method for wind–pumped hydro storage hybrid systems is proposed in this work. Firstly, considering the fluctuation of wind power generation caused by the natural seasonal weather and inherent uncertainties of wind power outputs, a combined method based on the generative adversarial network and K-means clustering algorithm is presented to construct wind power output scenarios. Then, a multi-objective wind–pumped storage system capacity optimization model is established with three objectives consisting of minimizing the levelized cost of energy, minimizing the net load peak–valley difference of regional power grids, and minimizing the power output deviation of hybrid systems. An inner and outer nested algorithm is proposed to obtain the Pareto frontiers based on the strength of the Pareto evolutionary algorithm II. Finally, the complementarity of wind power and pumped storage is illustrated through an analysis of numerical examples, and the advantages of variable-speed pumped storage in complementary operation with wind power over fixed-speed units are verified.
Lithofacies Identification from Wire-Line Logs Using an Unsupervised Data Clustering Algorithm
Authors: Hasan Md Monjur Ul , Hasan Tanzeer , Shahidi Reza , James Lesley , Peters Dennis , Gosine Ray
Published: December 2023

Stratigraphic identification from wire-line logs and core samples is a common method for lithology classification. This traditional approach is considered superior, despite its significant financial cost. Artificial neural networks and machine learning offer alternative, cost-effective means for automated data interpretation, allowing geoscientists to extract insights from data. At the same time, supervised and semi-supervised learning techniques are commonly employed, requiring a sufficient amount of labeled data to be generated through manual interpretation. Typically, there are abundant unlabeled geophysical data while labeled data are scarcer. Supervised and semi-supervised techniques partially address the cost issue. An underutilized class of machine-learning-based methods, unsupervised data clustering, can perform consonant classification by grouping similar data without requiring known results, presenting an even more cost-effective solution. In this study, we examine a state-of-the-art unsupervised data clustering algorithm called piecemeal clustering to identify lithofacies from wire-line logs, effectively addressing these challenges. The piecemeal clustering algorithm groups similar wire-log signatures into clusters, determines the number of clusters present in the data, and assigns each signature to one of the clusters, each of which represents a lithofacies. To evaluate the performance, we tested the algorithm on publicly released data from ten wells drilled in the Hugoton and Panoma fields of southwest Kansas and northwest Oklahoma, respectively. The data consist of two major groups: marine and non-marine facies. The study herein is centered around addressing two fundamental research questions regarding the accuracy and practicality of the piecemeal clustering algorithm. The algorithm successfully identified nine distinct clusters in our dataset, aligning with the cluster count observed in previously published works employing the same data. Regarding mapping accuracy, the results were notable, with success rates of 81.90% and 45.20% with and without considering adjacent facies, respectively. Further detailed analysis of the results was conducted for individual types of facies and independently for each well. These findings suggest the algorithm’s precision in characterizing the geological formations. To assess its performance, a comprehensive comparative analysis was conducted, encompassing other data clustering algorithms, as well as supervised and semi-supervised machine learning techniques. Notably, the piecemeal clustering algorithm outperformed alternative data clustering methods. Furthermore, despite its unsupervised nature, the algorithm demonstrated competitiveness by yielding results comparable to, or even surpassing, those obtained through supervised and semi-supervised techniques.
Techno-Economic Analysis of a Highly Renewable and Electrified District Heating Network Operating in the Balancing Markets
Authors: Javanshir Nima , Syri Sanna
Published: December 2023

In pursuit of Finland’s carbon neutrality objective by 2035, integrating renewable energy sources into the power grid is essential. To address the stochastic nature of these resources, additional sources of flexibility are required to maintain grid stability. Meanwhile, district heating network (DHN) operators in Finland are decommissioning fossil fuel-based combined heat and power plants (CHPs) and electrifying heating systems with heat pumps (HPs) and electric boilers. A techno-economic assessment and the optimized operation of DHN-connected HPs and electric boilers in providing ancillary balancing services were explored in this study. The primary goal was to maximize the potential revenue for DHN operators through participation in the day-ahead electricity market and frequency containment reserve (FCR) balancing markets. Three interconnected DHNs in the Helsinki metropolitan area were optimized based on 2019 data and each operator’s decarbonization strategies for 2025. HPs are expected to achieve the highest profit margins in the FCR-D up-regulation market, while electric boilers could generate substantial profits from the FCR-D down-regulation market. In contrast to other balancing markets studied, the FCR-N market exhibited limited profit potential. Sensitivity analysis indicated that spot electricity prices and CO2 emission allowance prices significantly influence the profitability derived from balancing markets.
Ionic Storage Materials for Anodic Discoloration in Electrochromic Devices
Authors: Chen Po-Wen , Chang Chen-Te , Kuo Po-Hsiu
Published: December 2023

The ion storage layer in electrochromic devices (ECDs) stores protons or lithium ions to provide electrochemical stability and extend cycle durability. This paper reports on the performance and stability of ECDs paired with various ion storage layers (NiO, V2O5, and IrO2 films). The complementary ECD using a V2O5 ion storage layer presented the fastest response time, but the lowest optical contrast. In addition, the ECD using an IrO2 ion storage layer proved the most effective as an ion storage layer, due to its high optical modulation ability capability and long-term stability. Chronoamperometry analysis revealed that IrO2-based ECD (glass/IZTO/WO3/liquid electrolyte/IrO2/IZTO/glass) can be highly effective in modulating optical transmittance, as indicated by T = 61.5% (from Tbleaching (69.6%) to Tcoloring (8.1%)) and switching times of 5.3 s for coloring and 7.3 s for bleaching at 633 nm.
Environmental Sustainability Implications and Economic Prosperity of Integrated Renewable Solutions in Urban Development
Authors: Kazancoglu Yigit , Berberoglu Yalcin , Lafci Cisem , Generalov Oleksander , Solohub Denys , Koval Viktor
Published: December 2023

The increasing urbanization and growth of cities worldwide have led to a significant increase in energy demand. As a transition to a low carbon environment occurs, the role of renewable and sustainable energy systems in urban areas is benefiting industry and the environment alike. From this perspective, the Sustainable Development Goals (SDGs) have a lot to offer to the energy industry, particularly the integration of renewable and sustainable energy systems for environmental protection in cities. This study presents a comprehensive view that integrates technological, economic, political, and social challenges confronted with the effective implementation of renewable and sustainable energy in urban cities and proposes a solution agenda to overcome these hurdles with the aid of the SDGs. The weights for the challenges of adopting renewable and sustainable energy systems were determined using the Fuzzy Best-Worst Method. The SDGs were then ranked using the fuzzy TOPSIS technique to overcome predetermined challenges. The originality of this study lies in finding solutions to the determined challenges by adopting SDGs, emphasizing the need for integrated solutions that address energy-related concerns, and highlighting the role and importance of SDGs in environmental protection. The study highlights the importance of SDGs in promoting renewable energy integration in urban areas, with SDG 11 being the most crucial to mitigate harmful environmental occurrences related to energy-related issues in urban areas, followed by SDG 7 and SDG 13.
Reinforcement Learning for Stand Structure Optimization of Pinus yunnanensis Secondary Forests in Southwest China
Authors: Xuan Shuai , Wang Jianming , Chen Yuling
Published: December 2023

Aiming to enhance the efficiency and precision of multi-objective optimization in southwestern secondary growth of Pinus yunnanensis forests, this study integrated spatial and non-spatial structural indicators to establish objective functions and constraints for assessing forest structure. Felling decisions were made using the random selection method (RSM), Q-value method (QVM), and V-map method (VMM). Actions taken to optimize the forest stand structure (FSS) through tree selection were approached as decisions by a reinforcement learning (RL) agent. Leveraging RL’s trial-and-error strategy, we continually refined the agent’s decision-making process, applying it to multi-objective optimization. Simulated felling experiments conducted across circular sample plots (P1–P4) compared RL, Monte Carlo (MC), and particle swarm optimization (PSO) in FSS optimization. Notable enhancements in the values of the objective function (VOFs) were observed across all plots. RL-based strategies exhibited improvements, achieving VOF increases of 17.24%, 44.92%, 34.66%, and 17.10% for P1–P4, respectively, outperforming MC-based (10.73%, 41.54%, 30.39%, and 15.07%, respectively) and PSO-based (14.08%, 37.78%, 26.17%, and 16.23%, respectively) approaches. The hybrid M7 scheme, integrating RL with the RSM, consistently outperformed other schemes across all plots, yielding an average 26.81% increase in VOF compared to the average enhancement of all schemes (17.42%). This study significantly advances the efficacy and precision of multi-objective optimization strategies for Pinus yunnanensis secondary forests, emphasizing RL’s superior optimization performance, particularly when combined with the RSM, highlighting its potential for optimizing sustainable forest management strategies.
Study on the Comprehensive Health Effects of Coastal Green Areas in Qingdao City, China
Authors: Leng Xiushan , Kong Di , Gao Zhiwen , Wang Kai , Zhang Yu , Li Chunyu , Liang Hong
Published: December 2023

The recuperation factors (negative air ion concentration, airborne particulate matter, human comfort index, and acoustic environment index) of coastal green spaces have significant health effects. Most current studies focus on the distribution pattern of single recuperation factors in the forest environment; however, the comprehensive health effects of coastal green spaces are still unknown. To address this, we analyzed the distribution patterns of single and comprehensive health factors in different landscape configurations, landscape compositions, and coastal distances by principal component analysis and systematic clustering. The results show that: (1) coniferous and broadleaf mixed forests exhibit higher integrated health benefits than other landscape compositions; (2) closed and partially closed landscape configurations exhibit enhanced potential for promoting health benefits as opposed to partially open and open spaces; (3) a coastal distance of 150–300 m offers the strongest comprehensive health benefits. These findings collectively suggest that the increased cultivation of closed and partially closed mixed coniferous and broadleaf forest species at a distance of 150–300 m could effectively provide higher comprehensive health effects. Our study complements the ecosystem service of coastal green areas, especially in coastal health ecological services, providing support for coastal rehabilitation landscape planning; and can help to guide tourists in scheduling coastal health activities scientifically.
Decentralized Storage with Access Control and Data Persistence for e-Book Stores
Authors: Ogata Keigo , Fujita Satoshi
Published: December 2023

The e-book services we use today have a serious drawback in that we will no longer be able to read the books we have purchased when the service is terminated. One way to solve this problem is to build a decentralized system that does not depend on a specific company or organization by combining smart contracts running on the Ethereum blockchain and distributed storage such as an IPFS. However, a simple combination of existing technologies does not make the stored e-book data persistent, so the risk of purchased e-books becoming unreadable remains. In this paper, we propose a decentralized distributed storage called d-book-repository, which has both access management function and data durability for purchased e-books. This system uses NFTs as access rights to realize strict access control by preventing clients who do not have NFTs from downloading e-book data. In addition, e-book data stored on storage nodes in the distributed storage is divided into shards using Reed–Solomon codes, and each storage node stores only a single shard, thereby preventing the creation of nodes that can restore the entire content from locally stored data. The storage of each shard is not handled by a single node but by a group of nodes, and the shard is propagated to all nodes in the group using the gossip protocol, where erasure codes are utilized to increase the resilience against node departure. Furthermore, an incentive mechanism to encourage participation as a storage node is implemented using smart contracts. We built a prototype of the proposed system on AWS and evaluated its performance. The results showed that both downloading and uploading 100 MB of e-book data (equivalent to one comic book) were completed within 10 s using an instance type of m5.xlarge. This value is only 1.3 s longer for downloading and 2.2 s longer for uploading than the time required for a simple download/upload without access control, confirming that the overhead associated with the proposed method is sufficiently small.
Collaborative Cost Multi-Agent Decision-Making Algorithm with Factored-Value Monte Carlo Tree Search and Max-Plus
Authors: Alexander-Reindorf Nii-Emil , Cotae Paul
Published: December 2023

In this paper, we describe the Factored Value MCTS Hybrid Cost-Max-Plus algorithm, a collection of decision-making algorithms (centralized, decentralized, and hybrid) for a multi-agent system in a collaborative setting that considers action costs. Our proposed algorithm is made up of two steps. In the first step, each agent searches for the best individual actions with the lowest cost using the Monte Carlo Tree Search (MCTS) algorithm. Each agent’s most promising activities are chosen and presented to the team. The Hybrid Cost Max-Plus method is utilized for joint action selection in the second step. The Hybrid Cost Max-Plus algorithm improves the well-known centralized and distributed Max-Plus algorithm by incorporating the cost of actions in agent interactions. The Max-Plus algorithm employed the Coordination Graph framework, which exploits agent dependencies to decompose the global payoff function as the sum of local terms. In terms of the number of agents and their interactions, the suggested Factored Value MCTS-Hybrid Cost-Max-Plus method is online, anytime, distributed, and scalable. Our contribution competes with state-of-the-art methodologies and algorithms by leveraging the locality of agent interactions for planning and acting utilizing MCTS and Max-Plus algorithms.
Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men
Authors: Hornung Bastian V. H. , Azmani Zakia , den Dekker Alexander T. , Oole Edwin , Ozgur Zeliha , Brouwer Rutger W. W. , van den Hout Mirjam C. G. N. , van IJcken Wilfred F. J.
Published: December 2023

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.
Ranking Opportunities for Autonomous Trucks Using Data Mining and GIS
Authors: Bridgelall Raj , Jones Ryan , Tolliver Denver
Published: December 2023

The inefficiency of transporting goods contributes to reduced economic growth and environmental sustainability in a country. Autonomous trucks (ATs) are emerging as a solution, but the imbalance in the weight moved and ton-miles produced by long-haul and short-haul trucking creates a challenge in targeting initial deployments. This study offers a unique solution by presenting a robust method that combines data mining and geographic information systems (GISs) to identify the optimal routes for ATs based on a top-down approach to maximize business benefits. Demonstrated in a U.S. case study, this method revealed that despite accounting for only 16% of the weight moved, long-haul trucking produced 56% of the ton-miles, implying a high potential for ATs in this segment. The method identified eight key freight zones in five U.S. states that accounted for 27% of the long-haul weight and suggested optimal routes for initial AT deployment. Interstate 45 emerged as a pivotal route in the shortest paths among these freight zones. This suggests that stakeholders should seek to prioritize funding for infrastructure upgrades and maintenance along that route and the other routes identified. The findings will potentially benefit a broad range of stakeholders. Companies can strategically focus resources to achieve maximum market share, regulators can streamline policymaking to facilitate AT adoption while ensuring public safety, and transportation agencies can better plan infrastructure upgrades and maintenance. Users globally can apply the methodological framework as a reliable tool for decision-making about where to initially deploy ATs.
Experimental and Numerical Analysis of Laterally Loaded Single- and Double-Paddled H-Piles in Clay
Authors: Abouziad Abdelrahman , El Naggar M. Hesham
Published: December 2023

An efficient foundation system of single- or double-paddled H-piles (PHPs), which comprises steel H-piles fitted with specially configured steel plates (paddles), is proposed to support sound walls subjected to wind loading. The lateral responses of single-paddled (SPHPs) and double-paddled H-piles (DPHPs) installed in clay is evaluated using a comprehensive assessment of the foundation performance via a full-scale lateral load testing program, alongside extensive three-dimensional (3D) nonlinear finite element (FE) analysis. The comparison between the calculated and measured responses of the PHPs demonstrates that the developed numerical model accurately depicts the response of the PHPs under lateral load. The validated numerical model is then used to evaluate the effect of the soil consistency on the lateral response and capacity of the PHPs. The influence of the paddles’ configuration on the lateral response and capacity of the PHPs is also evaluated. Furthermore, the change in the PHP lateral stiffness due to adding a second paddle is also examined. Finally, the influence of the plates on the surrounding soil is investigated by analyzing the formation of the strain field around the pile and evaluating the extent of the soil influence zone at different plate-width-to-pile-flange-width ratios (Wp/Wf). The result of this study indicates that adding plates contributes significantly to the lateral capacity of PHPs in clay and reduces the maximum bending moment. The parametric study reveals that the top 5–6 Wp of the soil have a significant effect on the lateral response of the proposed H-pile. Based on the outcomes of the field tests and numerical analysis, optimal geometrical parameters for paddles are proposed.
Interaction of Culture Medium and Artificial Light Type on Pigmentation of Micro-Propagated Opuntia Plants
Authors: Silos Espino Hector , Escalera García R. , Moncada González D. , Valera-Montero Luis L. , Flores Benítez S. , Ortiz Morales M. , Guzmán Maldonado H. S. , Escalante-Garcia Nivia , Olvera-Gonzalez Ernesto
Published: December 2023

Opuntia is recognized economically as a significant crop for its nutritional, functional, and therapeutic properties and its potential in the pharmaceutical, cosmetic, and bioenergy industries. Opuntia is conventionally propagated by seed or vegetative propagation via rooted scions or grafting. However, multiplication procedures are insufficient for extensive spreading. One of the alternative techniques is in vitro. For this reason, the objective was to evaluate the growth of different components combined with light conditions to induce callus, embryogenesis, and the possible synthesis of a component in the genus Opuntia. The existence of genes involved in pigment synthesis in genotypes of different fruit colors was complementarily analyzed. In this study, we used different combinations of fructose (2 g/L) with prickly pear juice (2 mL/L), mannitol (4 g/L), silver nitrate (AgNO3: 1 mg/L), 2,4-dichlorophenoxyacetic acid (2,4-D: 2 mg/L), and indole-3-acetic acid (IAA: 1 g/L), with white, blue, and red LEDs (light-emitting diodes) and laser beams. These explants yielded sufficient contents of simple phenols, gallic acid equivalents (GAE: 2283.30 ± 6.29 mg/100 g), and coumaric (2155.0 ± 35.0 mg/100 g) and ferulic (2176 ± 27.9 mg/100 g) acids for the genotype Tapón aguanoso, and chlorogenic acid (CGA: 380.22 ± 22.05 mg/100 g) for the Copena V1 genotype. Upon analyzing the genotypes of different fruit pigmentations, we also observed the following: enzyme 4,5 estradiol dioxygenases can be present in all genotypes (regardless of pigmentation); enzyme 5,3 glucosyltransferases (GTs) could be induced in pigment synthesis in the genotypes of orange to purple fruits. Sequencing primer-amplified fragments for GT showed high similarity to uridine diphospho (UDP)-glucose from other species. This allows us to infer that it is possible to obtain products of high therapeutic value in the near future under controlled conditions.
Arbuscular Mycorrhizal Fungi, Especially Rhizophagus intraradices as a Biostimulant, Improve Plant Growth and Root Columbin Levels in Tinospora sagittata
Authors: Meng Lu-Lu , Xu Fu-Qi , Zhang Ze-Zhi , Alqahtani Mashael Daghash , Tashkandi Manal A. , Wu Qiang-Sheng
Published: December 2023

Tinospora sagittata is a columbin-rich medicinal plant, but its columbin levels are reduced under artificial cultivation conditions. The objective of this study was to analyze the effects of inoculations with Diversispora versiformis (Dv), Funneliformis mosseae (Fm), Rhizophagus intraradices (Ri), and mixed inoculation (Dv + Fm + Ri) (Mix) on growth performance, root morphology, leaf photosynthetic physiology, and root columbin levels in T. sagittata. These arbuscular mycorrhizal fungi (AMF) were able to colonize the roots, as evidenced by a root mycorrhizal colonization rate ranging from 17% to 48% and soil hyphal lengths ranging from 17.51 cm/g to 32.02 cm/g, with the Mix treatment being the greatest. AMF inoculations improved plant height (16–151%), leaf number (119–283%), shoot (37–211%), and root biomass (22–318%) to varying extents, with Ri and Mix treatments being the most prominent. AMF-treated plants presented relatively greater root total length, projected area, surface area, volume, and average diameter, especially those treated with Ri and Mix. AMF inoculations also significantly improved the leaf nitrogen balance index, transpiration rate, and stomatal conductance, while the photosynthesis rate and chlorophyll index varied by AMF species, along with a decrease in intercellular CO2 levels. Root columbin levels ranged from 0.524 mg/g to 5.389 mg/g, and AMF inoculation significantly increased root columbin levels by 228–928%, with Ri being the most significant. Root columbin levels were significantly positively correlated with soil hyphal length, root total length, root projected area, root surface area, root volume, and root average diameter, but not root AMF colonization rate. This study demonstrates for the first time that AMF, especially Ri, can be employed as a biostimulant to promote growth as well as root columbin levels in T. sagittata, where AMF-triggered improvement in root morphology is an important reason for promoting root columbin levels.
Screening and Selection for Herbicide Tolerance among Diverse Tomato Germplasms
Authors: Sharma Gourav , Shrestha Swati , Tseng Te-Ming , Shrestha Sanju
Published: December 2023

Solanum lycopersicum, the domesticated species of tomato, is produced and consumed globally. It is one of the most economically important vegetable crops worldwide. In the commercial production of tomatoes, tomatoes are extremely sensitive to herbicide drifts from row crops in the vicinity. Injury to tomatoes from auxin herbicides and glyphosate can occur at rates as low as 0.01×. This results in a substantial yield reduction, and at high drift rates, plants may not show signs of recovery. With the new herbicide-resistant crop technologies on the market, which include 2,4-D and dicamba-resistant crops, there is an increase in the usage of these herbicides, causing more serious drift problems. There is a diverse germplasm of tomatoes that includes wild relatives which are tolerant to numerous biotic and abiotic stresses. Herbicide/chemical stress is an abiotic stress, and wild tomato accessions may have a natural tolerance to herbicides and other abiotic stresses. In the current study, diverse tomato genotypes consisting of 110 accessions representing numerous species, Solanum habrochaites, S. cheesmaniae, S. pimpinellifolium, S. chilense, S. lycopersicum, S. pimpinellifolium, S. galapagense, S. chimelewskii, S. corneliomulleri, S. neorickii, and S. lycopersicoides, were used for screening drift rate herbicide tolerance. The herbicides tested included simulated drift rates of 2,4-D, dicamba, glyphosate, quinclorac, aminopyralid, aminocyclopyrachlor, and picloram. The visual injury rating of each accession for each herbicide treatment was taken 7, 14, 21, and 28 days after treatment (DAT) on a scale of 0–100%. Numerous accessions were found to have minimal injury (less than 20%) for each of the herbicides tested; nine accessions were found for both 2,4-D and glyphosate, eleven for dicamba, five for quinclorac, eight for aminocyclopyrachlor and two for both aminopyralid and picloram at 28 DAT. The identification of genotypes with a higher herbicide tolerance will provide valuable genetic resources for the development of elite tomato varieties that can resist herbicide injury and produce competitive yields.
Quality and Safety of Proximity Care Centered on the Person and Their Domiciliation: Systematic Literature Review
Authors: Martins Carlos , Escoval Ana , Lopes Manuel , Mendonça Susana , Fonseca César
Published: December 2023

The quality and safety of health care are a priority for health organizations and social institutions to progressively provide people with a higher level of health and well-being. It is in the development of this path that home care currently represents an area of gradual investment and where health care services and the scientific community have shown interest in building circuits and instruments that can respond to needs. The purpose of this article is to identify areas and criteria for quality and safety in home care. The method used was a systematic review registered in PROSPERO (CRD42022380989). The search was systematically carried out in CINAHL Plus with Full Text, MEDLINE with Full Text and Psychology and Behavioral Sciences Collection, using the following criteria: articles published in Portuguese and English, from January 2017 to November 2022. The results of the analysis of the articles showed areas of quality and safety in home care with their respective dimensions and operational criteria. We concluded that there are three areas: the intervention with the patient, with proximity and patient-centered care, which integrates the individual care plan and the proximity of professionals to the patient and family; the intervention of care and service management, with care management and clinical governance that includes the integrated model of health care, goal management, and context management; and the intervention related to training and professional development, where we have the skills and training of professionals.
Prevalence and Covariates of Electronic Cigarette Use among Students Aged 13–15 Years in the Philippines: 2019 Global Youth Tobacco Survey
Authors: Serra Chelsea , Njie Gibril , Jacques Nerline , Pan Liping
Published: December 2023

Electronic cigarette use is growing in popularity and accessibility among youth in the Southeast Asia region. We analyzed data on 6670 students, aged 13–15 years, from the Philippines’ 2019 Global Youth Tobacco Survey. Prevalence estimates and 95% confidence intervals (CI) were estimated for current use (i.e., past 30 days), ever use, and awareness of e-cigarettes. Chi-square tests compared prevalence differences between groups. Multiple logistic regression models assessed factors associated with e-cigarette use while controlling for sociodemographic characteristics, current use of other tobacco products, and secondhand smoke exposure. Prevalence of current e-cigarette use was 14.1% (95% CI = 12.4%, 15.8%), ever use was 24.6% (95% CI = 22.4%, 26.9%), and awareness was 75.5% (95% CI = 73.0%, 78.0%). Current use of any other tobacco products and exposure to secondhand smoke at home, school, or other public places were positively associated with current and ever use of e-cigarettes. Boys and youth living in Luzon or Mindanao had higher odds of current e-cigarette use compared to girls and youth in Visayas. Findings indicated that one in four Philippine students aged 13–15 years ever used e-cigarettes and one in seven currently use e-cigarettes. This study highlights the importance of implementing evidence-based strategies, including relevant tobacco control policies.
A Web-Based Geodesign Tool for Evaluating the Integration of Transport Infrastructure, Public Spaces, and Human Activities
Authors: Yang Liu
Published: December 2023

The need for addressing the adverse impacts of transport infrastructure on public spaces and human activities (TSH) emphasizes the importance of designing integrated TSH system, thereby necessitating tailored planning support systems (PSS). This study begins by assessing the demand for PSS using surveys and interviews to uncover the need for robust analysis and evaluation support, particularly through the use of geographical information systems (GIS). On this basis, a prototype GIS platform is proposed for analyzing and evaluating the integration of the TSH system at the block scale. This user-friendly geodesign tool encompasses a customizable evaluation index (includes seven KPAs and KPIs), allowing for combined quantitative and qualitative assessments. Notably, it introduces a buffer effect index to quantify transport–space interaction. The proposed tool serves as a dedicated platform for evaluating TSH systems, offering 2D/3D visualization capabilities and two analysis units and facilitating cross-platform collaboration. Applied to a case study in Nanjing, China, it effectively assessed the interdependence among different TSH system components and block integration around expressways, railways, and main roads. This tool holds promise in offering invaluable insights into urban planning and (re)development, thereby enhancing the integration of transport infrastructure and public spaces.
Pomegranate (Punica granatum L.) and Its Rich Ellagitannins as Potential Inhibitors in Ulcerative Colitis
Authors: Li Huimin , Ruan Jingya , Huang Jiayan , Yang Dingshan , Yu Haiyang , Wu Yuzheng , Zhang Yi , Wang Tao
Published: December 2023

Ulcerative colitis, an immune-mediated inflammatory disease of the gastrointestinal tract, places a significant financial burden on patients and the healthcare system. Recently, reviews of the pomegranate and the abundant medicinal applications of its ellagitannins, as well as its pharmacological action, phytochemicals, metabolism, and pharmacokinetics, have been completed. However, summaries on their anti-ulcerative colitis effects are lacking. Numerous preclinical animal investigations and clinical human trial reports demonstrated the specific therapeutic effects of pomegranate and the effect of its ellagitannins against ulcerative colitis. According to the literature collected by Sci-finder and PubMed databases over the past 20 years, this is the first review that has compiled references regarding how the rich ellagitannins found in pomegranate have altered the ulcerative colitis. It was suggested that the various parts of pomegranates and their rich ellagitannins (especially their primary components, punicalagin, and ellagic acid) can inhibit oxidant and inflammatory processes, regulate the intestinal barrier and flora, and provide an anti-ulcerative colitis resource through dietary management.
Shake It Up Baby Now: The Changing Focus on TWIST1 and Epithelial to Mesenchymal Transition in Cancer and Other Diseases
Authors: Mirjat Dureali , Kashif Muhammad , Roberts Cai M.
Published: December 2023

TWIST1 is a transcription factor that is necessary for healthy neural crest migration, mesoderm development, and gastrulation. It functions as a key regulator of epithelial-to-mesenchymal transition (EMT), a process by which cells lose their polarity and gain the ability to migrate. EMT is often reactivated in cancers, where it is strongly associated with tumor cell invasion and metastasis. Early work on TWIST1 in adult tissues focused on its transcriptional targets and how EMT gave rise to metastatic cells. In recent years, the roles of TWIST1 and other EMT factors in cancer have expanded greatly as our understanding of tumor progression has advanced. TWIST1 and related factors are frequently tied to cancer cell stemness and changes in therapeutic responses and thus are now being viewed as attractive therapeutic targets. In this review, we highlight non-metastatic roles for TWIST1 and related EMT factors in cancer and other disorders, discuss recent findings in the areas of therapeutic resistance and stemness in cancer, and comment on the potential to target EMT for therapy. Further research into EMT will inform novel treatment combinations and strategies for advanced cancers and other diseases.
Metabolomic Signatures of Treatment Response in Bladder Cancer
Authors: Vieira de Sousa Tiago , Guedes de Pinho Paula , Pinto Joana
Published: December 2023

Bladder cancer (BC) stands as one of the most prevalent urological malignancies, with over 500 thousand newly diagnosed cases annually. Treatment decisions in BC depend on factors like the risk of recurrence, the type of tumor, and the stage of the disease. While standard therapeutic approaches encompass transurethral resection of the bladder tumor, radical cystectomy, and chemo- or immunotherapy, these methods exhibit limited efficacy in mitigating the aggressive and recurrent nature of bladder tumors. To overcome this challenge, it is crucial to develop innovative methods for monitoring and predicting treatment responses among patients with BC. Metabolomics is gaining recognition as a promising approach for discovering biomarkers. It has the potential to reveal metabolic disruptions that precisely reflect how BC patients respond to particular treatments, providing a revolutionary method to improve accuracy in monitoring and predicting outcomes. In this article, we present a comprehensive review of studies employing metabolomics approaches to investigate the metabolic responses associated with different treatment modalities for BC. The review encompasses an exploration of various models, samples, and analytical techniques applied in this context. Special emphasis is placed on the reported changes in metabolite levels derived from these studies, highlighting their potential as biomarkers for personalized medicine in BC.
The Role of NKG2D and Its Ligands in Autoimmune Diseases: New Targets for Immunotherapy
Authors: Wei Leiyan , Xiang Zhiqing , Zou Yizhou
Published: December 2023

Natural killer (NK) cells and CD8+ T cells can clear infected and transformed cells and generate tolerance to themselves, which also prevents autoimmune diseases. Natural killer group 2 member D (NKG2D) is an important activating immune receptor that is expressed on NK cells, CD8+ T cells, γδ T cells, and a very small percentage of CD4+ T cells. In contrast, the NKG2D ligand (NKG2D-L) is generally not expressed on normal cells but is overexpressed under stress. Thus, the inappropriate expression of NKG2D-L leads to the activation of self-reactive effector cells, which can trigger or exacerbate autoimmunity. In this review, we discuss the role of NKG2D and NKG2D-L in systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), multiple sclerosis (MS), type I diabetes (T1DM), inflammatory bowel disease (IBD), and celiac disease (CeD). The data suggest that NKG2D and NKG2D-L play a pathogenic role in some autoimmune diseases. Therefore, the development of strategies to block the interaction of NKG2D and NKG2D-L may have therapeutic effects in some autoimmune diseases.