bluuebunny/crossref_metadata_2025 huggingface dataset:
Protective Effect of Galantamine against Doxorubicin-Induced Neurotoxicity
Authors: Alsikhan Rawan S. , Aldubayan Maha A. , Almami Ibtesam S. , Alhowail Ahmad H.
Published: June 2023

Background and aims: Doxorubicin (DOX) causes cognitive impairment (chemobrain) in patients with cancer. While DOX damages the cholinergic system, few studies have focused on the protective effects of cholinergic function on chemobrain. The acetylcholinesterase inhibitor galantamine (GAL) demonstrates neuroprotective properties. We investigated the mechanisms associated with DOX-induced cognitive impairments and the potential protective role of GAL in preventing chemobrain. Main methods: Female Wistar rats were divided into control, DOX, GAL, and DOX + GAL groups. The rats in the DOX group were administered DOX (5 mg/kg intraperitoneally twice weekly for two weeks), while those in the GAL group were orally administered GAL (2.5 mg/kg) via oral gavage once daily for 15 days. The combination group (DOX + GAL) received GAL (once daily) and DOX (two times per week) concurrently. The body weights and survival rates were monitored daily. The animals were subjected to behavioral tests to assess the memory function followed by the biochemical estimation of inflammatory markers, including tumor necrosis factor-α (TNF-α), interleukine-1β (IL-1β), and interleukine-6 (IL-6) in rat brain tissue and RT-qPCR. Key findings: DOX caused a reduction in the body weight and survival rate, which was alleviated by GAL concomitant treatment with DOX (DOX + GAL). These groups had reduced body weights and survival rates. DOX-treated animals exhibited an impairment of short-term spatial working memory, manifested as a behavioral alteration in the Y-maze test, the novel object recognition (NOR) test, and the elevated plus-maze (EPM) test. Concurrent treatment with GAL (DOX + GAL) showed improved memory function, as evidenced by an increase in the number of entries and time spent in the novel arm, the time spent exploring the novel object, and the transfer latency in the Y-maze, NOR test, and EPM test, respectively. These findings were also supported by biochemical observations showing the reversal of DOX-induced changes in IL-1β, IL-6, and TNF-α, as well as their relative expression of mRNA in brain tissue following concurrent GAL treatment. Conclusion: GAL appeared to be a neuroprotective agent against neuroinflammation caused by DOX by reducing inflammatory markers in the brain.
Perceptions of Stakeholders Regarding China’s Special Education and Inclusive Education Legislation, Law, and Policy: Implications for Student Wellbeing and Mental Health
Authors: Alduais Ahmed , Deng Meng , Alfadda Hind
Published: June 2023

Laws and policies, no matter how well designed, can fail if they are not implemented correctly. This can occur when there is no interaction between policymakers and those who are working on the ground. The purpose of this study was to determine the understanding of Chinese stakeholders regarding legislation, policy, and law associated with the provision of special education and explore its implications for student wellbeing and mental health. Two questions were posed: (1) Does a stakeholder’s attitude towards legislation, policy, and law regarding special education impact their role or responsibilities? (2) In what ways do stakeholders interact with legislation, laws, and policies regarding special education and their work experience in the field? Using in-depth interviews as the basis for the study, researchers gained valuable insight into how administrators, practitioners, and academics perceive laws and policies. Participants exhibited exaggerated attitudes and over-interpretations of some of these items, which we attribute to partly real factors, as well as nationalistic or patriotic feelings. The evidence included calls for specific laws and policies as well as a switch from a top-down to a bottom-up approach to reform to bridge the disparity between different regions in the country. As the participants agreed, there have also been remarkable achievements in building a more comprehensive and inclusive system over the last decade. However, the gaps between rural and urban areas, primary and middle schools, high schools and vocational schools need to be addressed urgently in specific laws and policies. Addressing these disparities will not only improve the overall quality of special education but also have significant implications for student wellbeing and mental health. By ensuring that all students have access to tailored support and resources, policymakers can foster a more inclusive and supportive environment that promotes positive mental health outcomes for all learners.
Exposure to Terrorism, Post-Traumatic Stress Disorder and University Teachers’ Performance: Underpinning the Role of Social Support
Authors: Saleem Farida , Malik Muhammad Imran
Published: June 2023

This study aims to investigate the impact of exposure to terrorism on post-traumatic stress disorder and employee performance, and to determine whether social support acts as a boundary condition that can attenuate the adverse effects of PTSD on employee performance. The study used a cross-sectional sample of 178 university teachers who had experienced a terrorist attack. Data was collected using closed-ended questionnaires and analyzed using PROCESS Macro). The results found a negative and significant relationship between exposure to terrorism, post-traumatic disorder, and employees’ performance. Moreover, it was also found that social support helps attenuate the negative impact of PTSD on performance levels. This study adds to the existing body of knowledge by exploring the relationship between terrorism exposure, PTSD, employee performance, and the potential mitigating effects of social support.
Research on the Conservation Methods of Qu Street’s Living Heritage from the Perspective of Life Continuity
Authors: Wang Shaojie , Guo Qian , Yuan Jingjing , Li Huaqi , Fu Bohuai
Published: June 2023

In the current context of urban development transformation and the gradual decline of historic and cultural districts, new demands have been raised for the preservation of such districts. The question of how to effectively safeguard historically and culturally significant districts, imbued with the vibrant essence of indigenous life, has become a topic worthy of contemplation. This paper takes the historical and cultural district of Leizhou Qu Street as a case study, using the concept of continuity of life as its focal point. Employing methods such as on-site observation, questionnaire surveys, and case studies, this paper investigates and evaluates the core community through identification and collaboration, and proposes corresponding preservation strategies and subsequent maintenance approaches. In doing so, the paper aims to achieve community identity, cultural heritage transmission, and the continuity of life. The findings reveal that the method of protecting the living heritage through continuity of life is applicable to historically and culturally significant districts that still thrive with the vibrancy of daily life, and this method can be effectively implemented. This research deepens our understanding of the concept of living heritage preservation in historic and cultural districts, further substantiating and implementing the principle of continuity of life in their preservation. The study also aims to provide valuable insights and references for the preservation of similar heritage sites.
A Study on the Applicability and Accuracy of the Discrete Element Method for Plates Based on Parameter Sensitivity Analysis
Authors: Guo Fei , Ye Jihong
Published: June 2023

In order to verify the accuracy and applicability of the discrete element method (DEM) in dealing with geometrically large deformations of continuous plate structures, both a single-parameter analysis and an orthogonal design method were adopted to analyze the displacement responses of the plate structures and were compared with those calculated using the finite element method (FEM). The single-parameter change condition involved the thickness-to-width ratio, elastic modulus, or Poisson’s ratio, while the multi-parameter change included boundary conditions, dimensions, load forms, thickness-to-width ratio, elastic modulus, and Poisson’s ratio. The results showed that displacements of the target locations were basically identical to those obtained according to FEM, with a maximum error of less than 5% under the single-parameter change condition. The maximum displacement error of the plate structures calculated using the DEM and FEM, respectively, was 4.212%, and the mean error and extreme difference of error parameters were 2.633% and 2.184%, respectively. These results indicate that the displacements of the plate structures calculated using the DEM were highly consistent with those obtained according to the FEM. Additionally, single-parameter changes and multi-parameter changes barely influenced the accuracy and suitability of the DEM in solving displacement response problems of plate structures. Therefore, the DEM is applicable in terms of dealing with displacement response problems of plate structures.
Electrolessly Deposited Carbon-Supported CuNiSn Electrocatalysts for the Electrochemical Reduction of CO2
Authors: Chaitree Wasu , Hongmeuan Atikom , Pinthong Piriya , Panpranot Joongjai
Published: June 2023

Aiming at developing low-cost, high-performance catalysts for the electrochemical reduction of CO2 (CO2-ERR) to valuable multicarbon (C2–C3) chemicals to alleviate global warming, trimetallic alloy electrocatalysts containing Cu, Ni, and Sn supported on a Pd-activated carbon fabric substrate (CS) were prepared via an electroless deposition method. The as-deposited CuNiSn/CS electrocatalysts were employed in CO2-ERR in an H-cell type reactor at an applied potential of −1.6 V vs. Ag/AgCl. The effect of the electroless deposition time (15, 30, and 45 min) was investigated, finding no significant structural differences according to the X-ray diffraction patterns. The evaluation of the reaction performance via linear sweep voltammetry revealed that CO2 was more effectively reduced to adsorbed species on the catalytic surface sites of the electrocatalyst prepared with a 30 min deposition time. The analysis of the gas and liquid products via gas chromatography and nuclear magnetic resonance, respectively, revealed that the Faradaic efficiency and H2 production over CuNiSn/CS was lower than those over related bimetallic and monometallic electrocatalysts, indicating the inhibition of the competitive H2 evolution reaction. Liquid products including formate, ethylene glycol, acetone, ethanol, acetate, and 1-buthanol were detected.
Rabconnectin-3α/DMXL2 Is Locally Enriched at the Synaptic Ribbon of Rod Photoreceptor Synapses
Authors: Dittrich Alina , Ramesh Girish , Jung Martin , Schmitz Frank
Published: June 2023

Ribbon synapses reliably transmit synaptic signals over a broad signalling range. Rod photoreceptor ribbon synapses are capable of transmitting signals generated by the absorption of single photons. The high precision of ribbon synapses emphasizes the need for particularly efficient signalling mechanisms. Synaptic ribbons are presynaptic specializations of ribbon synapses and are anchored to the active zone. Synaptic ribbons bind many synaptic vesicles that are delivered to the active zone for continuous and faithful signalling. In the present study we demonstrate with independent antibodies at the light- and electron microscopic level that rabconnectin-3α (RC3α)—alternative name Dmx-like 2 (DMXL2)—is localized to the synaptic ribbons of rod photoreceptor synapses in the mouse retina. In the brain, RC3α-containing complexes are known to interact with important components of synaptic vesicles, including Rab3-activating/inactivating enzymes, priming proteins and the vesicular H+-ATPase that acidifies the synaptic vesicle lumen to promote full neurotransmitter loading. The association of RC3α/DMXL2 with rod synaptic ribbons of the mouse retina could enable these structures to deliver only fully signalling-competent synaptic vesicles to the active zone thus contributing to reliable synaptic communication.
Silencing of circCacna1c Inhibits ISO-Induced Cardiac Hypertrophy through miR-29b-2-5p/NFATc1 Axis
Authors: Lu Peilei , Zhang Danyu , Ding Fan , Ma Jialu , Xiang Yang K. , Zhao Meimi
Published: June 2023

Pathological cardiac hypertrophy is one of the notable causes of heart failure. Circular RNAs (circRNAs) have been studied in association with cardiac hypertrophy; however, the mechanisms by which circRNAs regulate cardiac hypertrophy remain unclear. In this study, we identified a new circRNA, named circCacna1c, in cardiac hypertrophy. Adult male C57BL/6 mice and H9c2 cells were treated with isoprenaline hydrochloride (ISO) to establish a hypertrophy model. We found that circCacna1c was upregulated in ISO-induced hypertrophic heart tissue and H9c2 cells. Western blot and quantitative real-time polymerase chain reaction showed that silencing circCacna1c inhibited hypertrophic gene expression in ISO-induced H9c2 cells. Mechanistically, circCacna1c competitively bound to miR-29b-2-5p in a dual-luciferase reporter assay, which was downregulated in ISO-induced hypertrophic heart tissue and H9c2 cells. MiR-29b-2-5p inhibited the nuclear factor of activated T cells, cytoplasmic, calcineurin-dependent 1 (NFATc1) to control hypertrophic gene expression. After silencing circCacna1c, the expression of miR-29b-2-5p increased, which reduced hypertrophic gene expression by inhibiting NFATc1 expression. Together, these experiments indicate that circCacna1c promotes ISO-induced pathological hypertrophy through the miR-29b-2-5p/NFATc1 axis.
Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning
Authors: Elhassan Nasrin , Varone Giuseppe , Ahmed Rami , Gogate Mandar , Dashtipour Kia , Almoamari Hani , El-Affendi Mohammed A. , Al-Tamimi Bassam Naji , Albalwy Faisal , Hussain Amir
Published: June 2023

Social media networks have grown exponentially over the last two decades, providing the opportunity for users of the internet to communicate and exchange ideas on a variety of topics. The outcome is that opinion mining plays a crucial role in analyzing user opinions and applying these to guide choices, making it one of the most popular areas of research in the field of natural language processing. Despite the fact that several languages, including English, have been the subjects of several studies, not much has been conducted in the area of the Arabic language. The morphological complexities and various dialects of the language make semantic analysis particularly challenging. Moreover, the lack of accurate pre-processing tools and limited resources are constraining factors. This novel study was motivated by the accomplishments of deep learning algorithms and word embeddings in the field of English sentiment analysis. Extensive experiments were conducted based on supervised machine learning in which word embeddings were exploited to determine the sentiment of Arabic reviews. Three deep learning algorithms, convolutional neural networks (CNNs), long short-term memory (LSTM), and a hybrid CNN-LSTM, were introduced. The models used features learned by word embeddings such as Word2Vec and fastText rather than hand-crafted features. The models were tested using two benchmark Arabic datasets: Hotel Arabic Reviews Dataset (HARD) for hotel reviews and Large-Scale Arabic Book Reviews (LARB) for book reviews, with different setups. Comparative experiments utilized the three models with two-word embeddings and different setups of the datasets. The main novelty of this study is to explore the effectiveness of using various word embeddings and different setups of benchmark datasets relating to balance, imbalance, and binary and multi-classification aspects. Findings showed that the best results were obtained in most cases when applying the fastText word embedding using the HARD 2-imbalance dataset for all three proposed models: CNN, LSTM, and CNN-LSTM. Further, the proposed CNN model outperformed the LSTM and CNN-LSTM models for the benchmark HARD dataset by achieving 94.69%, 94.63%, and 94.54% accuracy with fastText, respectively. Although the worst results were obtained for the LABR 3-imbalance dataset using both Word2Vec and FastText, they still outperformed other researchers’ state-of-the-art outcomes applying the same dataset.
Developing CeO2-CoAl2O4 Semiconductor Ionic Based Heterostructure Composite Electrolyte for Low-Temperature Solid Oxide Fuel Cells (SOFCs)
Authors: Dong Yiwang , Yousaf Muhammad , Shah Muhammad Ali Kamran Yousaf , Akbar Muhammad , Lu Yuzheng , Zhang Lei , Sial Qadeer Akbar , Cao Peng , Deng Changhong
Published: June 2023

Semiconductor ionic electrolytes, especially heterostructure composites, have a significant role in enhancing oxide ion conductivity and peak power density (PPD) because of their interfacial contact. In this work, the fluorite structure CeO2 and spinel-based CoAl2O4 samples, as a heterostructure composite electrolyte, are successfully fabricated. The p-type CoAl2O4 and n-type CeO2 heterostructure (CeO2-CoAl2O4) used as an electrolyte exhibits a cell performance of 758 mW/cm2 under fuel cell H2/air conditions at 550 °C, which is quite higher than the pure CoAl2O4 and CeO2 fuel cell devices. Scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HR-TEM) verified the heterostructure formation including the morphological analysis of the prepared heterostructure composite. The heterostructure-based CeO2-CoAl2O4 composite achieved a higher ionic conductivity of 0.13 S/cm at 550 °C temperature, which means that the constructed device successfully works as an electrolyte by suppressing electronic conductivity. Meanwhile, the obtained results demonstrate the semiconductor ionic heterostructure effect by adjusting the appropriate composition to build heterostructure of the n-type (CeO2) and p-type (CoAl2O4) components and built-in electric field. So, this work exhibits that the constructed device can be effective for energy conversion and storage devices.
Recent Advances in Polydopamine for Surface Modification and Enhancement of Energetic Materials: A Mini-Review
Authors: Qin Ziquan , Li Dapeng , Ou Yapeng , Du Sijia , Jiao Qingjie , Peng Jiwu , Liu Ping
Published: June 2023

Polydopamine (PDA), inspired by the adhesive mussel foot proteins, is widely applied in chemical, biological, medical, and material science due to its unique surface coating capability and abundant active sites. Energetic materials (EMs) play an essential role in both military and civilian fields as a chemical energy source. Recently, PDA was introduced into EMs for the modification of crystal phase stability and the interfacial bonding effect, and, as a result, to enhance the mechanical, thermal, and safety performances. This mini-review summarizes the representative works in PDA modified EMs from three perspectives. Before that, the self-polymerization mechanisms of dopamine and the methods accelerating this process are briefly presented for consideration of researchers in this field. The future directions and remaining issues of PDA in this field are also discussed at last in this mini-review.
An Experimental Investigation of the Solid State Sintering of Cemented Carbides Aiming for Mechanical Constitutive Modelling
Authors: Rosenblad Louise , Staf Hjalmar , Larsson Henrik , Larsson Per-Lennart
Published: June 2023

The densification of cemented carbides during sintering was studied using an existing constitutive model based on powder particle size and material composition. In the present analysis, we study how well the constitutive model can capture the experimental results of a dilatometer test. Three experiments were performed, where the only difference was the transition between the debinding and sintering process. From magnetic measurements, it is concluded that the carbon level in the specimen is affected by changes to the experimental setup. It is shown, using parameter adjustments, that the constitutive model is more suited for a certain experimental setup and carbon level, which is a limitation of the model. In order to capture the mechanical behaviour under different experimental conditions, further constitutive modelling relevant to the carbon level is recommended.
Robotic Lobectomy without Complete Fissure for Non-Small Cell Lung Cancer: Technical Aspects and Perioperative Outcomes of the Tunnel Technique
Authors: Gallina Filippo Tommaso , Forcella Daniele , Melis Enrico , Facciolo Francesco
Published: June 2023

Even though the use of the “fissure-last” technique in mini-invasive lobectomy with the fissureless condition is well accepted, in terms of perioperative outcomes, controversies still surround the hilar lymph node dissection. In this article, we reported a description of the robotic “tunnel technique” approach in the right upper lobectomy in the absence of a defined fissure. We then compared the short terms outcomes of 30 consecutive cases treated using this technique, with 30 patients treated using the “fissure last” VATS approach in the same institution, before the start of the robotic surgery program.
Inflammatory Bowel Diseases: Does One Histological Score Fit All?
Authors: Villanacci Vincenzo , Del Sordo Rachele , Parigi Tommaso Lorenzo , Leoncini Giuseppe , Bassotti Gabrio
Published: June 2023

Mucosal healing (MH) is the main treatment target in ulcerative colitis (UC) and Crohn’s disease, and it is defined by the combination of complete endoscopic and histologic remission. The complete resolution of mucosal inflammation should be confirmed by histology but its assessment is not always univocal. Neutrophil infiltration represents the unique histological marker in discriminating the active vs. quiescent phases of the disease, together with crypt injuries (cryptitis and crypt abscesses), erosions, and ulcerations. On the contrary, basal plasmacytosis is not indicative of activity or the remission of inflammatory bowel diseases (IBDs) but instead represents a diagnostic clue, mostly at the onset. Several histological scoring systems have been developed to assess grade severity, particularly for UC. However, most are complex and/or subjective. The aim of this review was to summarize available scores, their characteristics and limitations, and to present the advantages of a simplified mucosa healing scheme (SHMHS) based on neutrophils and their distribution in the gut mucosa. Finally, we overview future developments including artificial intelligence models for standardization of disease assessments and novel molecular markers of inflammation with potential application in diagnostic practice.
Prognostic Models in Growth-Hormone- and Prolactin-Secreting Pituitary Neuroendocrine Tumors: A Systematic Review
Authors: Dumitriu-Stan Roxana-Ioana , Burcea Iulia-Florentina , Salmen Teodor , Poiana Catalina
Published: June 2023

Growth-hormone (GH)- and prolactin (PRL)-secreting PitNETs (pituitary neuroendocrine tumors) are divided into multiple histological subtypes, which determine their clinical and biological variable behavior. Proliferation markers alone have a questionable degree of prediction, so we try to identify validated prognostic models as accurately as possible. (1) Background: The data available so far show that the use of staging and clinical–pathological classification of PitNETs, along with imaging, are useful in predicting the evolution of these tumors. So far, there is no consensus for certain markers that could predict tumor evolution. The application of the WHO (World Health Organisation) classification in practice needs to be further evaluated and validated. (2) Methods: We performed the CRD42023401959 protocol in Prospero with a systematic literature search in PubMed and Web of Science databases and included original full-text articles (randomized control trials and clinical trials) from the last 10 years, published in English, and the search used the following keywords: (i) pituitary adenoma AND (prognosis OR outcome OR prediction), (ii) growth hormone pituitary adenoma AND (prognosis OR outcome OR prediction), (iii) prolactin pituitary adenoma AND (prognosis OR outcome OR prediction); (iv) mammosomatotroph adenoma AND (prognosis OR outcome OR prediction). (3) Results: Two researchers extracted the articles of interest and if any disagreements occurred in the selection process, these were settled by a third reviewer. The articles were then assessed using the ROBIS bias assessment and 75 articles were included. (4) Conclusions: the clinical–pathological classification along with factors such as GH, IGF-1, prolactin levels both preoperatively and postoperatively offer valuable information.
Selection of an Insurance Company in Agriculture through Hybrid Multi-Criteria Decision-Making
Authors: Puška Adis , Lukić Marija , Božanić Darko , Nedeljković Miroslav , Hezam Ibrahim M.
Published: June 2023

Crop insurance is used to reduce risk in agriculture. This research is focused on selecting an insurance company that provides the best policy conditions for crop insurance. A total of five insurance companies that provide crop insurance services in the Republic of Serbia were selected. To choose the insurance company that provides the best policy conditions for farmers, expert opinions were solicited. In addition, fuzzy methods were used to assess the weights of the various criteria and to evaluate insurance companies. The weight of each criterion was determined using a combined approach based on fuzzy LMAW (the logarithm methodology of additive weights) and entropy methods. Fuzzy LMAW was used to determine the weights subjectively through expert ratings, while fuzzy entropy was used to determine the weights objectively. The results of these methods showed that the price criterion received the highest weight. The selection of the insurance company was made using the fuzzy CRADIS (compromise ranking of alternatives, from distance to ideal solution) method. The results of this method showed that the insurance company DDOR offers the best conditions for crop insurance for farmers. These results were confirmed by a validation of the results and sensitivity analysis. Based on all of this, it was shown that fuzzy methods can be used in the selection of insurance companies.
An Automatic Generation and Verification Method of Software Requirements Specification
Authors: Wei Xiaoyang , Wang Zhengdi , Yang Shuangyuan
Published: June 2023

The generation of standardized requirements specification documents plays a crucial role in software processes. However, the manual composition of software requirements specifications is a laborious and time-consuming task, often leading to errors that deviate from the actual requirements. To address this issue, this paper proposes an automated method for generating requirements specifications utilizing a knowledge graph and graphviz. Furthermore, in order to overcome the limitations of the existing automated requirement generation process, such as inadequate emphasis on data information and evaluation, we enhance the traditional U/C matrix by introducing an S/U/C matrix. This novel matrix represents the outcomes of data/function systematic analysis, and verification is facilitated through the design of inspection rules. Experimental results demonstrate that the requirements specifications generated using this method achieve standardization and adherence to regulations, while the devised S/U/C inspection rules facilitate the updating and iteration of the requirements specifications.
An FPGA Architecture for the RRT Algorithm Based on Membrane Computing
Authors: Shang Zeyi , Wei Zhe , Verlan Sergey , Li Jianming , He Zhige
Published: June 2023

This paper investigates an FPGA architecture whose primary function is to accelerate parallel computations involved in the rapid-exploring random tree (RRT) algorithm. The RRT algorithm is inherently serial, while in each computing step there are many computations that can be executed simultaneously. Nevertheless, how to carry out these parallel computations on an FPGA so that a high degree of acceleration can be realized is the key issue. Membrane computing is a parallel computing paradigm inspired from the structures and functions of eukaryotic cells. As a newly proposed membrane computing model, the generalized numerical P system (GNPS) is intrinsically parallel; so, it is a good candidate for modeling parallel computations in the RRT algorithm. Open problems for the FPGA implementation of the RRT algorithm and GNPS include: (1) whether it possible to model the RRT with GNPS; (2) if yes, how to design such an FPGA architecture to achieve a better speedup; and (3) instead of implementing GNPSs with a fixed-point-number format, how to devise a GNPS FPGA architecture working with a floating-point-number format. In this paper, we modeled the RRT with a GNPS at first, showing that it is feasible to model the RRT with a GNPS. An FPGA architecture was fabricated according to the GNPS-modeled RRT. In this architecture, computations, which can be executed in parallel, are accommodated in different inner membranes of the GNPS. These membranes are designed as Verilog modules in the register transfer level model. All the computations within a membrane are triggered by the same clock impulse to implement parallel computing. The proposed architecture is validated by implementing it on the Xilinx VC707 FPGA evaluation board. Compared with the software simulation of the GNPS-modeled RRT, the FPGA architecture achieves a speedup of a 104 order of magnitude. Although this speedup is obtained on a small map, it reveals that this architecture promises to accelerate the RRT algorithm to a higher level compared with the previously reported architectures.
BiGA-YOLO: A Lightweight Object Detection Network Based on YOLOv5 for Autonomous Driving
Authors: Liu Jun , Cai Qiqin , Zou Fumin , Zhu Yintian , Liao Lyuchao , Guo Feng
Published: June 2023

Object detection in autonomous driving scenarios has become a popular task in recent years. Due to the high-speed movement of vehicles and the complex changes in the surrounding environment, objects of different scales need to be detected, which places high demands on the performance of the network model. Additionally, different driving devices have varying performance capabilities, and a lightweight model is needed to ensure the stable operation of devices with limited computing power. To address these challenges, we propose a lightweight network called BiGA-YOLO based on YOLOv5. We design the Ghost-Hardswish Conv module to simplify the convolution operations and incorporate spatial coordinate information into feature maps using Coordinate Attention. We also replace the PANet structure with the BiFPN structure to enhance the expression ability of features through different weights during the process of fusing multi-scale feature maps. Finally, we conducted extensive experiments on the KITTI dataset, and our BiGA-YOLO achieved a mAP@0.5 of 92.2% and a mAP@0.5:0.95 of 68.3%. Compared to the baseline model YOLOv5, our proposed model achieved improvements of 1.9% and 4.7% in mAP@0.5 and mAP@0.5:0.95, respectively, while reducing the model size by 15.7% and the computational cost by 16%. The detection speed was also increased by 6.3 FPS. Through analysis and discussion of the experimental results, we demonstrate that our proposed model is superior, achieving a balance between detection accuracy, model size, and detection speed.
Smart Contract Design in Distributed Energy Systems: A Systematic Review
Authors: Honari Kimia , Rouhani Sara , Falak Nida E. , Liu Yuan , Li Yunwei , Liang Hao , Dick Scott , Miller James
Published: June 2023

Blockchain technology and, in particular, smart contracts based on it, offers a new, decentralized mechanism for entering into and fulfilling contracts in diverse markets. Energy markets are no exception, and indeed, the decentralized nature of the blockchain may be particularly important for them as the penetration of residential prosumers offering microgeneration to the grid grows. At this time, however, the literature on smart contracts in energy markets—and particularly their interaction with the technical infrastructure of the smart grid—is limited and scattered. There is a need to consolidate these studies into a comprehensive understanding of the state-of-the-art in smart contract design for the smart grid. However, no existing reviews focus on smart contracts in energy systems. The scope of our study is the role of smart contracts in energy systems and what limitations they encounter. We conduct a systematic review of this topic, focusing on systems that have been implemented as prototypes. These studies provide key evidence on the scalability of smart contracts for energy systems and their interaction with the technical elements of the smart grid. We selected a pool of 76 papers meeting our criteria, with three others excluded for misinterpreting fundamental aspects of blockchains and smart contracts. After reviewing each paper, we found that this literature falls into four categories: market operations, ancillary services, auditing and monitoring, and cybersecurity. We then identify and examine the cross-cutting concerns of data storage in and interoperability between blockchains. We finally discuss the implications of our findings for future research. In particular, there is likely to be a complex interplay between the data generated and stored via the blockchain versus the data required to meet energy system reliability targets and market obligations for participants.
Frequency Fluctuation Mitigation in a Single-Area Power System Using LQR-Based Proportional Damping Compensator
Authors: Das Pranta , Biswas Shuvra Prokash , Mondal Sudipto , Islam Md Rabiul
Published: June 2023

To maintain the stability of the power system, frequency fluctuations must be reduced in the shortest possible timeframe. Load frequency control (LFC) plays a critical role in achieving this objective by regulating the system frequency and the desired demand or output power in an interconnected network, thereby enabling the system to adapt the load disturbances. In order to effectively mitigate the frequency fluctuation caused by load variation in a single-area power system, a new control strategy integrating a linear quadratic regulator (LQR), a proportional controller, and a damping compensator is proposed in this paper. The proposed controller is named as the LQR-based proportional damping compensator which mitigates the frequency fluctuation of a single-area power system. MATLAB/Simulink simulation is conducted on a single-area power system to demonstrate the efficacy of the proposed control technique. The simulation results demonstrate that the proposed method successfully reduces frequency variations, maintains system frequency within reasonable limits, and substantially reduces the settling time as compared to other existing control techniques. Apart from the simulation analysis, to experimentally validate the performance of the proposed controller, a hybrid multiprocessor-based processor-in-loop (PIL) technique is also introduced in the paper. Both the simulation and experimental results prove the promising performance of the proposed controller for mitigating the frequency fluctuation of a single-area power system.
Protein Extraction, Precipitation, and Recovery from Chlorella sorokiniana Using Mechanochemical Methods
Authors: Cutshaw Ashley , Frost Henry , Uludag-Demirer Sibel , Liu Yan , Liao Wei
Published: June 2023

Protein extraction, precipitation, and recovery methods were evaluated by this study using a green alga—Chlorella sorokiniana. A mechanochemical cell disruption process was applied to facilitate protein extraction from microalgal biomass. Optimization of the mechanochemical process resulted in milling conditions that achieved a protein extraction of 52.7 ± 6.45%. The consequent acid precipitation method was optimized to recover 98.7% of proteins from the microalgal slurry. The measured protein content of the protein isolate was 41.4% w/w. These results indicate that the precipitation method is successful at recovering the extracted proteins in the algal slurry; however, the removal of non-protein solids during centrifugation and pH adjustment is not complete. The energy balance analysis elucidated that the energy demand of the protein extraction and recovery operation, at 0.83 MJ/kg dry algal biomass, is much lower than previous studies using high-pressure homogenization and membrane filtration. This study concludes that mechanochemical protein extraction and recovery is an effective, low-energy processing method, which could be used by algal biorefineries to prepare algal proteins for value-added chemical production as well as to make algal carbohydrates and lipids in the residual biomass more accessible for biofuel production.
A Review of the Metallogenic Mechanisms of Sandstone-Type Uranium Deposits in Hydrocarbon-Bearing Basins in China
Authors: Li Guihe , Yao Jia , Song Yiming , Tang Jieyun , Han Hongdou , Cui Xiangdong
Published: June 2023

As a valuable mineral resource, uranium is extensively utilized in nuclear power generation, radiation therapy, isotope labeling, and tracing. In order to achieve energy structure diversification, reduce dependence on traditional fossil fuels, and promote the sustainable development of energy production and consumption, research on the metallogenic mechanisms and related development technologies of uranium resources has been one of the focuses of China’s energy development. Sandstone-type uranium deposits make up approximately 43% of all deposits in China, making them the most prevalent form of uranium deposit there. Sandstone-type uranium deposits and hydrocarbon resources frequently coexist in the same basin in China. Therefore, this study summarizes the spatial and chronological distribution, as well as the geological characteristics, of typical sandstone-type uranium deposits in China’s hydrocarbon-bearing basins. From the perspectives of fluid action, geological structure, and sedimentary environment, the metallogenic mechanisms of sandstone-type uranium deposits in hydrocarbon-bearing basins are explored. According to the research, the rapid reduction effect of oil and gas in the same basin is a major factor in the generation of relatively large uranium deposits. Additionally, ions such as CO32− and HCO3− in hydrothermal fluids of hydrocarbon-bearing basins, which typically originate from dispersed oil and gas, are more conducive to uranium enrichment and sedimentation. This study provides guidance for efficient sandstone-type uranium deposit exploration and production in hydrocarbon-bearing basins and helps to achieve significant improvements in uranium resource exploitation efficiency.
Nitrogen Addition Alleviates Cadmium Toxicity in Eleocarpus glabripetalus Seedlings
Authors: Liu Meihua , Shi Mengjiao , Gao Haili , Zheng Yu , Yi Lita
Published: June 2023

Cadmium (Cd) accumulation in soil is a serious form of heavy metal pollution affecting environmental safety and human health. In order to clarify the tolerance mechanisms to Cd-contaminated soils under N deposition, changes in plant growth, root architecture and physiological characteristics of Eleocarpus glabripetalus seedlings under combined nitrogen (N) and cadmium (Cd) treatments were determined in this study. The results indicated that Cd-induced negative effects inhibited the growth of E. glabripetalus seedlings through increased underground biomass allocation, and affected transpiration and respiratory processes, resulting in a decreased soluble sugars concentration in leaves and non-structural carbohydrates (NSC) in the roots. Root systems might play a major role in Cd absorption. Cd stress restricted the growth of fine roots (<0.5 mm), and affected the uptake of N and P. N addition alleviated the Cd-induced negative effect on plant growth through improving the root system, increasing starch and NSC contents in the roots and increasing total biomass. These findings have important implications for understanding the underlying tolerance mechanisms of Cd pollution under N deposition in arbor species.
Tree Species Classification Using Optimized Features Derived from Light Detection and Ranging Point Clouds Based on Fractal Geometry and Quantitative Structure Model
Authors: Hui Zhenyang , Cai Zhaochen , Xu Peng , Xia Yuanping , Cheng Penggen
Published: June 2023

Tree species classification is a ubiquitous task in the forest inventory field. Only directly measured feature vectors have been applied to most existing methods that use LiDAR technology for tree species classification. As a result, it is difficult to obtain a satisfactory tree species classification performance. To solve this challenge, the authors of this paper developed two new kinds of feature vectors, including fractal geometry-based feature vectors and quantitative structural model (QSM)-based feature vectors. In terms of fractal geometry, both two fractal parameters were extracted as feature vectors for reflecting how tree architecture is distributed in three-dimensional space. In terms of QSM, the ratio of length change and the ratio of radius change of different branches were extracted as feature vectors. To reduce the feature vector dimensionality and explore valuable feature vectors, feature vector dimension reduction was conducted using the classification and regression tree (CART). Five hundred and sixty-eight individual trees with five tree species were selected for evaluating the performance of the developed feature vectors. The experimental results indicate that the tree species of Fagus sylvatica achieved the highest overall accuracy, which is 98.06%, while Quercus petraea obtained the lowest overall accuracy, which is 96.65%. Four other classical supervised learning methods were adopted for comparison. The comparison result indicates that the proposed method outperformed the other four supervised learning methods no matter which accuracy indicator was adopted. In comparison with the relevant method, the eight feature vectors developed in this paper also performed much better. This indicates that the fractal geometry-based feature vectors and QSM-based feature vectors developed in this paper can effectively improve the performance of tree species classification.
Constructing Coupling Model of Generalized B-Spline Curve and Crown (CMGBCC) to Explore the 3D Modeling of Chinese Fir Polymorphism
Authors: Cui Zeyu , Zhang Huaiqing , Liu Yang , Zhang Jing , Yang Tingdong , Zuo Yuanqing , Lei Kexin
Published: June 2023

Crown simulation based on basis spline (b-spline) interpolation is a compatible method to simulate tree polymorphism at present. However, there are two problems when it simulates the crown: the first problem is that the derivative value at the top point needs to be given manually, and the second is that the type of value point needs to be collected equidistantly. To solve the above problems and realize convenient and accurate tree polymorphism simulation, this study took Chinese fir as the study object, set the crown morphological feature as the model value point, and constructed a coupling model of generalized B-spline curve and crown (CMGBCC) as the constraint condition of the crown shape to simulate the polymorphism in the process of a tree three-dimensional (3D) model. The position and size of the distribution on the 3D model of the branches were constrained by the curve, and the 3D modeling of a Chinese fir polymorphism was constructed. According to the collection of Chinese fir-type value points in the sample plot, the study realized the detailed types of value points’ precise simulation for three polymorphisms of the Chinese fir crown, including natural pruning, crown displacement, and crown shape difference. At the same time, the different withered existence states of the branches were considered preliminarily. Compared to the 3D model with the field survey data, indicating that constructed models could simulate the difference in tree crown morphology precisely, the branch models were separated by convenience to simulate the process of Chinese fir growth. In the process of construction, CMGBCC did not need to add the derivative value in a manual way and could collect the type of value points according to the characteristics of the crown morphological changes completely. Compared to the results of the crown curve constructed, which were based on generalized B-spline (GB-spline) interpolation and b-spline interpolation, it showed that the number of crown value points collected by the GB-spline interpolation method decreased by 18% on average. The precision of the crown shape constraint was improved by 7.63% compared to b-spline interpolation. The 3D modeling of tree polymorphism was combined with the relationship between tree morphology and environment. At the same time, it was convenient to simulate the behavior of forest management measures, such as pruning.
Quality Improvement and Shelf-Life Extension of Iced Nile Tilapia Fillets Using Natural Garlic Extract
Authors: Jiménez-Ruíz Edgar Iván , Ocaño-Higuera Víctor Manuel , Valdez-Hurtado Santiago , Cruz-Guzmán José Alberto , Otero-León Cesar Benjamín , Ruíz-Cruz Saúl , Garzón-García Alba Mery , Barrales-Cureño Hebert Jair , Canizales-Rodríguez Dalila Fernanda , Pérez-Martínez Cinthia Jhovanna , Sumaya-Martínez María Teresa
Published: June 2023

Fish represent one of the most perishable food groups. Therefore, it is important to find viable alternatives that contribute to the preservation of quality and increase the shelf life of fishery products, and one alternative is to use natural extracts with antimicrobial activity. The objective of this study was to determine the effect of a natural extract prepared with garlic (NGE) on the quality and shelf life of tilapia fillets stored on ice for 18 days. For this purpose, NGE was prepared by homogenizing peeled garlic cloves with distilled water, which were then centrifuged to obtain the extract (NGE); then, the fish fillets were immersed in the extract and were coated in NGE. The fillets with NGE were packed in high-density polyethylene bags and stored in crushed ice for 18 days. The adenosine 5′-triphosphate (ATP) and degradation products, K-value, color, texture, water holding capacity, pH, total mesophilic count, and total volatile bases (TVB-N) were monitored during storage. The ATP content, K-value, pH, total microbial count, and TVB-N changed with respect to ice storage time, and the results between fillets with NGE and control fillets differed. In conclusion, the application of NGE increased the shelf life of fillets stored on ice by 6 days, obtaining a shelf life of 18 days on ice, which shows its potential to improve the utilization of the species.
Spatial Ecology of the Population of Reef Manta Rays, Mobula alfredi (Krefft, 1868), in New Caledonia Using Satellite Telemetry 1–Horizontal Behaviour
Authors: Lassauce Hugo , Chateau Olivier , Wantiez Laurent
Published: June 2023

The reef manta ray, Mobula alfredi (Krefft, 1868), is a highly mobile and plankton-feeding species, classified vulnerable to extinction on the IUCN Red List for Threatened Species. Knowledge on their spatial ecology and the extent of their dispersal remain incomplete, especially within island-fragmented habitats as found in New Caledonia. Satellite telemetry was used to investigate the horizontal movement ecology of reef manta rays in New Caledonia. A total of 21 reef manta rays were tagged with pop-up satellite archival transmitting tags (21 Fastloc and 2 MiniPAT) that remained deployed for a duration ranging from 3 to 180 days (mean ± SE = 76.7 ± 50.3). Rays presented a strong site fidelity and an important affinity for coastal waters. Long-distance migrations (>300 km) were also observed, mainly through coastal and shallow water paths. Horizontal movements were compared to a home range area and classified into four distinct patterns: Fidelity, Excursion, Fidelity + Relocation and Relocation. The most dominant pattern was Fidelity, where manta rays remained within their home range for the whole duration of the tag deployment. Our findings may assist in the design of more appropriate management strategies for the species in New Caledonia and other regions worldwide.