bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Dynamic Response of a Slope Reinforced by a Pile-Anchor Structure under Seismic Loading
Authors: Li Yanyan , Chu Zhuqiang , Zhang Le , He Yujie
Published: October 2023

In earthquake-prone areas, pile-anchor structures are widely employed for slope reinforcement due to their reliable performance. Current research has primarily focused on static and quasi-static analyses of slopes reinforced by using pile-anchor structures, with limited investigation into their dynamic response. In this work, the finite element method (FEM) is used to study the dynamic behavior of a pile-anchor slope system, and the extended finite element method (XFEM) is used to simulate the progressive failure processes of piles. Three different reinforcement schemes, which include no support, pile support, and pile-anchor support, are considered to examine the performance of the pile-anchor structure. The simulation results suggest that the pile-anchor structure displays a reduction of 39.6% and 40.6% in the maximum shear force and bending moment of the piles, respectively, compared to the pile structure. The XFEM is utilized to model the progressive failure process of the piles subjected to seismic loading. We find that crack initiation in the pile body near the slip surface, for both the pile supported and the pile-anchor supported conditions, occurs when the peak ground acceleration arrives. Crack growth in the piles completes in a very short period, with two distinct increments of crack area observed. The first increment occurs when the peak ground acceleration arrives and is significantly larger than the second increment. Consequently, for the seismic design of piles, it is necessary to strengthen the pile body around slip surfaces. The novelty of this paper is that we realize the simulation of crack initiation and propagation in piles subjected to seismic loading.
An Analysis of the Isomerism of Tibetan Vernacular Dwellings Based on Space Syntax: A Case Study of the Semi-Agricultural and Semi-Pastoral District in Gannan Prefecture, China
Authors: An Yuyuan , Liu Lu , Guo Yixin , Wu Xiao , Liu Pengquan
Published: October 2023

Vernacular dwellings carry both material and spiritual connotations, playing a significant role in preserving and developing regional culture. While current research on vernacular dwellings has primarily focused on the cultural center, there is a critical knowledge gap regarding the “differentiation” of dwellings in border areas. This knowledge gap poses risks to the sustainable development of vernacular dwellings. Therefore, this study employs a space syntax approach to analyze the spatial configuration of the Tibetan vernacular dwellings of the semi-agricultural and semi-pastoral areas in Gannan prefecture, China, which is situated in the Tibetan border area. The findings reveal the following key insights: (i) disparities exist in the spatial organization of “sacred–secular” node spaces and the structural characteristics of buildings, resulting in a misalignment between physical center spaces and psychological center spaces; (ii) variation in cultural intensity contributes to distinct characteristics, i.e., “prototype”, “transition”, and “mutant”, among dwellings in different counties; and (iii) the continuous development and adaptation of dwellings hinge on the homogeneity and differentiation of regional culture. The crux of achieving sustainable dwelling development lies in preserving the diversity of dwellings. This study offers a more comprehensive understanding of the relationship between the spatial configuration of vernacular dwellings in the Tibetan border area and their sociocultural connotations. Consequently, it provides valuable guidance for promoting the sustainable development of these dwellings.
Lean System-Based Tool for Housing Projects Management in the Pandemic Period
Authors: Sundararajan S. , Madhavi T. Ch.
Published: October 2023

This research describes a detailed analysis of the enactment of a lean Tool, the Last Planner System during pandemic period which helps in optimizing resources for better coordination among all stakeholders in a pandemic period. The LPS, as it is known, focusses on minimizing factors such as uncertainties, barriers, and variability to make construction projects more flexible for better project management. These include variations and deviations, supervision, delays in approvals, change resistance, and subcontractor dedication, which are all related to various stakeholders in the project. Following that, a Design Science Research technique is used to evaluate the effect of applying the LPS in buildings to address and achieve the objective of reducing the impact of setbacks created by the stakeholders such as architects, consultants, clients, project management team, etc., during the implementation of the LPS during any pandemic so as not to reduce the progress of execution. An action strategy is being used to attain this goal, and four case studies are documented which concern the implementation of the LPS in the building of the Boy’s Hostel, Research Scholar Quarters, Faculty Housing, and Girls’ Hostel at Chennai, Tamilnadu, India. Data was gathered by observation of site activities, interviews, documentation analysis, and a questionnaire survey and grouped into various factors. While adopting the LPS tool in research, the factors affecting the implementation in the COVID-19 pandemic period were found. Further, these factors were analysed, measured, ranked, and validated for adopting in projects.
Aesthetic Assessment of Free-Form Space Structures Using Machine Learning Based on the Expert’s Experiences
Authors: Shahbazi Yaser , Ghofrani Mahsa , Pedrammehr Siamak
Published: October 2023

Parametric form findings of free-form space structures and qualitative assessment of their aesthetics are among the concerns of architects. This study aims to evaluate the aesthetic aspect of these structures using ML algorithms based on the expert’s experiences. First, various datasets of forms were produced using a parametric algorithm of free-form space structures written in Grasshopper. Then, three multilayer perceptron ANN models were adjusted in their most optimal modes using the results of the preference test based on the aesthetic criteria including simplicity, complexity, and practicality. The results indicate that the ANN models can quantitatively evaluate the aesthetic value of free-form space structures.
Modern Techniques in Re-Irradiation for Locally Recurrent Rectal Cancer: A Systematic Review
Authors: Mantello Giovanna , Galofaro Elena , Bisello Silvia , Chiloiro Giuditta , Romano Angela , Caravatta Luciana , Gambacorta Maria Antonietta
Published: October 2023

Background: Radiotherapy (RT) plays an important role in the treatment of patients with previously irradiated locally recurrent rectal cancer (LRRC). Over the years, numerous technologies and different types of RT have emerged. The aim of our systematic literature review was to determine whether the new techniques have led to improvements in both outcomes and toxicities. Methods: A computerized search was performed by MEDLINE and the Cochrane database. The studies reported data from patients treated with carbon ion radiotherapy (CIRT), intensity-modulated photon radiotherapy (IMRT), and stereotactic radiotherapy (SBRT). Results: Seven publications of the 126 titles/abstracts that emerged from our search met the inclusion criteria and presented outcomes of 230 patients. OS was reported with rates of 90.0% and 73.0% at 1 and 2 years, respectively; LC was 89.0% and 71.6% at 1 and 2 years after re-RT, respectively. Toxicity data vary widely, with emphasis on acute and chronic gastrointestinal and urogenital toxicity, even with modern techniques. Conclusion: data on toxicity and outcomes of re-RT for LRRC with new technologies are promising compared with 3D techniques. Comparative studies are needed to define the best technique, also in relation to the site of recurrence.
An Insight into Synergistic Metal-Oxide Interaction in CO2 Hydrogenation to Methanol over Cu/ZnO/ZrO2
Authors: Chang Xiao , Zi Xiaohui , Li Jing , Liu Fengdong , Han Xiaoyu , Chen Jiyi , Hao Ziwen , Zhang Heng , Zhang Zhenmei , Gao Pengju , Li Maoshuai , Lv Jing , Ma Xinbin
Published: October 2023

The metal-oxide interaction is of significance to the construction of active sites for Cu-catalyzed CO2 hydrogenation to methanol. This study examines the effect of ZnO and ZrO2 composition on the Cu/ZnO/ZrO2 catalyst structure and surface properties to further tune the catalytic activity for methanol synthesis. The ZnO/ZrO2 ratio can impact the CuZn alloy formation from strong Cu-ZnO interactions and the surface basic sites for CO2 adsorption at the Cu-ZrO2 interface. The proportional correlation of the CuZn alloy content and CO2 desorption amount with the space-time yield (STY) of methanol reveals a synergistic interaction between Cu and oxides (ZnO and ZrO2) that enhances methanol synthesis. The optimized Cu/ZnO/ZrO2 catalyst exhibits higher STY relative to the traditional Cu/ZnO/Al2O3 catalyst. The obtained results presented herein can provide insight into the catalyst design for methanol synthesis from CO2.
BdCV1-Encoded P3 Silencing Suppressor Identification and Its Roles in Botryosphaeria dothidea, Causing Pear Ring Rot Disease
Authors: Li Shanshan , Zhu Haodong , He Ying , Hong Ni , Wang Guoping , Wang Liping
Published: October 2023

Pear ring rot disease is an important branch disease, caused by Botryosphaeria dothidea. With the discovery of fungal viruses, the use of their attenuated properties for biological control provides a new strategy for the biological control of fungal disease. RNA silencing is a major antiviral defense mechanism in plants, insects, and fungi. Viruses encode and utilize RNA silencing suppressors to suppress host defenses. Previous studies revealed that Botryosphaeria dothidea chrysovirus 1 (BdCV1) exhibited weak pathogenicity and could activate host gene silencing by infecting B. dothidea. The aim of our study was to investigate whether BdCV1 can encode a silencing suppressor and what effect it has on the host. In this study, the capability of silencing inhibitory activity of four BdCV1-encoded proteins was analyzed, and the P3 protein was identified as a BdCV1 RNA silencing suppressor in the exotic host Nicotiana benthamiana line 16c. In addition, we demonstrated that P3 could inhibit local silencing, block systemic RNA silencing, and induce the necrosis reaction of tobacco leaves. Furthermore, overexpression of P3 could slow down the growth rate and reduce the pathogenicity of B. dothidea, and to some extent affect the expression level of RNA silencing components and virus-derived siRNAs (vsiRNAs). Combined with transcriptomic analysis, P3 had an effect on the gene expression and biological process of B. dothidea. The obtained results provide new theoretical information for further study of interaction between BdCV1 P3 as a potential silencing suppressor and B. dothidea.
Aging and Age-Related Epigenetic Drift in the Pathogenesis of Leukemia and Lymphomas: New Therapeutic Targets
Authors: Allegra Alessandro , Caserta Santino , Mirabile Giuseppe , Gangemi Sebastiano
Published: October 2023

One of the traits of cancer cells is abnormal DNA methylation patterns. The idea that age-related epigenetic changes may partially explain the increased risk of cancer in the elderly is based on the observation that aging is also accompanied by comparable changes in epigenetic patterns. Lineage bias and decreased stem cell function are signs of hematopoietic stem cell compartment aging. Additionally, aging in the hematopoietic system and the stem cell niche have a role in hematopoietic stem cell phenotypes linked with age, such as leukemia and lymphoma. Understanding these changes will open up promising pathways for therapies against age-related disorders because epigenetic mechanisms are reversible. Additionally, the development of high-throughput epigenome mapping technologies will make it possible to identify the “epigenomic identity card” of every hematological disease as well as every patient, opening up the possibility of finding novel molecular biomarkers that can be used for diagnosis, prediction, and prognosis.
A CD276-Targeted Antibody-Drug Conjugate to Treat Non-Small Lung Cancer (NSCLC)
Authors: Zhang Jiashuai , Zhou Zhuoxin (Zora) , Chen Kai , Kim Seulhee , Cho Irene Soohyun , Varadkar Tanvi , Baker Hailey , Cho Ju Hwan , Zhou Lufang , Liu Xiaoguang (Margaret)
Published: October 2023

Non-small cell lung cancer (NSCLC) patients, accounting for approximately 85% of lung cancer cases, are usually diagnosed in advanced stages. Traditional surgical resection and radiotherapy have very limited clinical benefits. The objective of this study was to develop and evaluate a targeted therapy, antibody-drug conjugate (ADC), for NSCLC treatment. Specifically, the CD276 receptor was evaluated and confirmed as an ideal surface target of NSCLC in the immunohistochemistry (IHC) staining of seventy-three patient tumor microarrays and western blotting analysis of eight cell lines. Our anti-CD276 monoclonal antibody (mAb) with cross-activity to both human and mouse receptors showed high surface binding, effective drug delivery and tumor-specific targeting in flow cytometry, confocal microscopy, and in vivo imaging system analysis. The ADC constructed with our CD276 mAb and payload monomethyl auristatin F (MMAF) showed high anti-NSCLC cytotoxicity to multiple lines and effective anti-tumor efficacy in both immunocompromised and immunocompetent NSCLC xenograft mouse models. The brief mechanism study revealed the integration of cell proliferation inhibition and immune cell reactivation in tumor microenvironments. The toxicity study did not detect off-target immune toxicity or peripheral toxicity. Altogether, this study suggested that anti-CD276 ADC could be a promising candidate for NSCLC treatment.
Noncoding RNAs and Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes in Cardiac Arrhythmic Brugada Syndrome
Authors: Theisen Benjamin , Holtz Austin , Rajagopalan Viswanathan
Published: October 2023

Hundreds of thousands of people die each year as a result of sudden cardiac death, and many are due to heart rhythm disorders. One of the major causes of these arrhythmic events is Brugada syndrome, a cardiac channelopathy that results in abnormal cardiac conduction, severe life-threatening arrhythmias, and, on many occasions, death. This disorder has been associated with mutations and dysfunction of about two dozen genes; however, the majority of the patients do not have a definite cause for the diagnosis of Brugada Syndrome. The protein-coding genes represent only a very small fraction of the mammalian genome, and the majority of the noncoding regions of the genome are actively transcribed. Studies have shown that most of the loci associated with electrophysiological traits are located in noncoding regulatory regions and are expected to affect gene expression dosage and cardiac ion channel function. Noncoding RNAs serve an expanding number of regulatory and other functional roles within the cells, including but not limited to transcriptional, post-transcriptional, and epigenetic regulation. The major noncoding RNAs found in Brugada Syndrome include microRNAs; however, others such as long noncoding RNAs are also identified. They contribute to pathogenesis by interacting with ion channels and/or are detectable as clinical biomarkers. Stem cells have received significant attention in the recent past, and can be differentiated into many different cell types including those in the heart. In addition to contractile and relaxational properties, BrS-relevant electrophysiological phenotypes are also demonstrated in cardiomyocytes differentiated from stem cells induced from adult human cells. In this review, we discuss the current understanding of noncoding regions of the genome and their RNA biology in Brugada Syndrome. We also delve into the role of stem cells, especially human induced pluripotent stem cell-derived cardiac differentiated cells, in the investigation of Brugada syndrome in preclinical and clinical studies.
Anterior Uveitis and Coats Disease in a 16-Year-Old Girl with Noonan Syndrome—A Case Report
Authors: Świerczyńska Marta , Tronina Agnieszka , Lorenc Anna , Filipek Erita
Published: October 2023

Background: Noonan syndrome (NS) represents a fairly common genetic disorder with a highly variable phenotype. Its features include inherited heart defects, characteristic facial features, short stature, and mild retardation of motor skills. Case presentation: A 16-year-old Caucasian girl with NS reported visual deterioration, photophobia, and pain in the right eye (RE). The initial best-corrected visual acuity (BCVA) was 0.3 in the RE. An examination demonstrated conjunctival and ciliary body hyperemia, keratic precipitates, and flare in the anterior chamber. In addition, post-hemorrhagic floaters, tortuous vessels, and an epiretinal membrane in the RE were present. Diagnosis of unilateral anterior uveitis was made, and this resolved after the use of topical steroids and cycloplegic drops. Due to the presence of retinal telangiectasias and extraocular exudates (consistent with Coats’ disease (CD) stage 2A) in the RE, laser therapy was performed. The patient remains under constant follow-up, and after one year, the BCVA in the RE was 0.7. Conclusions: Here, we report the clinical characteristics, genetic findings, and retinal imaging results of a patient with NS. To our knowledge, this is, to date, the first report of an association of NS with a PTPN11 mutation with anterior uveitis and CD.
A Robust Deep Learning Approach for Accurate Segmentation of Cytoplasm and Nucleus in Noisy Pap Smear Images
Authors: Nazir Nahida , Sarwar Abid , Saini Baljit Singh , Shams Rafeeya
Published: October 2023

Cervical cancer poses a significant global health burden, affecting women worldwide. Timely and accurate detection is crucial for effective treatment and improved patient outcomes. The Pap smear test has long been a standard cytology screening method, enabling early cancer diagnosis. However, to enhance quantitative analysis and refine diagnostic capabilities, precise segmentation of the cervical cytoplasm and nucleus using deep learning techniques holds immense promise. This research focuses on addressing the primary challenge of achieving accurate segmentation in the presence of noisy data commonly encountered in Pap smear images. Poisson noise, a prevalent type of noise, corrupts these images, impairing the precise delineation of the cytoplasm and nucleus. Consequently, segmentation boundaries become indistinct, leading to compromised overall accuracy. To overcome these limitations, the utilization of U-Net, a deep learning architecture specifically designed for automatic segmentation, has been proposed. This approach aims to mitigate the adverse effects of Poisson noise on the digitized Pap smear slides. The evaluation of the proposed methodology involved a dataset of 110 Pap smear slides. The experimental results demonstrate that the proposed approach successfully achieves precise segmentation of the nucleus and cytoplasm in noise-free images. By preserving the boundaries of both cellular components, the method facilitates accurate feature extraction, thus contributing to improved diagnostic capabilities. Comparative analysis between noisy and noise-free images reveals the superiority of the presented approach in terms of segmentation accuracy, as measured by various metrics, including the Dice coefficient, specificity, sensitivity, and intersection over union (IoU). The findings of this study underline the potential of deep-learning-based segmentation techniques to enhance cervical cancer diagnosis and pave the way for improved quantitative analysis in this critical field of women’s health.
Microscopic Characteristics of Kinking Phenomenon in Vertically Free-Standing Nanowires
Authors: Razaghi Zhina , Zhu Guo-zhen
Published: October 2023

Vertically free-standing nanowires, synthesized through vapor-based growth, can undergo changes in their growth directions known as kinking. These alterations can significantly influence the physical and chemical properties of nanowires, thereby expanding their potential applications. The occurrence of kinks is commonly associated with variations in vapor, temperature, seed, and/or their combinations. However, the interplay among different growth factors complicates the identification of the dominating factor and, consequently, limits precise control over nanowire morphology. Theoretical models, incorporating factors like supersaturation, wetting angle, nanowire size, and surface/interface energies tied to growth conditions, have been developed to describe and predict kinking during nanowire growth. While a few pivotal parameters, such as surface/interface energies and wetting angles, can be subtly adjusted through minor alterations in growth conditions, accurately predicting the occurrence of kinks remains a practical challenge. Conversely, in the present review, we attempted to elucidate connections between microscopic aspects, such as changes in composition and the formation of defects, and the nucleation and progression of kinks. This effort aims to construct a predictive framework that enhances our understanding of the tendencies in nanowire growth.
RDS-DR: An Improved Deep Learning Model for Classifying Severity Levels of Diabetic Retinopathy
Authors: Bashir Ijaz , Sajid Muhammad Zaheer , Kalsoom Rizwana , Ali Khan Nauman , Qureshi Imran , Abbas Fakhar , Abbas Qaisar
Published: October 2023

A well-known eye disorder called diabetic retinopathy (DR) is linked to elevated blood glucose levels. Cotton wool spots, confined veins in the cranial nerve, AV nicking, and hemorrhages in the optic disc are some of its symptoms, which often appear later. Serious side effects of DR might include vision loss, damage to the visual nerves, and obstruction of the retinal arteries. Researchers have devised an automated method utilizing AI and deep learning models to enable the early diagnosis of this illness. This research gathered digital fundus images from renowned Pakistani eye hospitals to generate a new “DR-Insight” dataset and known online sources. A novel methodology named the residual-dense system (RDS-DR) was then devised to assess diabetic retinopathy. To develop this model, we have integrated residual and dense blocks, along with a transition layer, into a deep neural network. The RDS-DR system is trained on the collected dataset of 9860 fundus images. The RDS-DR categorization method demonstrated an impressive accuracy of 97.5% on this dataset. These findings show that the model produces beneficial outcomes and may be used by healthcare practitioners as a diagnostic tool. It is important to emphasize that the system’s goal is to augment optometrists’ expertise rather than replace it. In terms of accuracy, the RDS-DR technique fared better than the cutting-edge models VGG19, VGG16, Inception V-3, and Xception. This emphasizes how successful the suggested method is for classifying diabetic retinopathy (DR).
Non-Hermitian Floquet Topological Matter—A Review
Authors: Zhou Longwen , Zhang Da-Jian
Published: October 2023

The past few years have witnessed a surge of interest in non-Hermitian Floquet topological matter due to its exotic properties resulting from the interplay between driving fields and non-Hermiticity. The present review sums up our studies on non-Hermitian Floquet topological matter in one and two spatial dimensions. We first give a bird’s-eye view of the literature for clarifying the physical significance of non-Hermitian Floquet systems. We then introduce, in a pedagogical manner, a number of useful tools tailored for the study of non-Hermitian Floquet systems and their topological properties. With the aid of these tools, we present typical examples of non-Hermitian Floquet topological insulators, superconductors, and quasicrystals, with a focus on their topological invariants, bulk-edge correspondences, non-Hermitian skin effects, dynamical properties, and localization transitions. We conclude this review by summarizing our main findings and presenting our vision of future directions.
Hierarchical Reinforcement Learning Framework in Geographic Coordination for Air Combat Tactical Pursuit
Authors: Chen Ruihai , Li Hao , Yan Guanwei , Peng Haojie , Zhang Qian
Published: October 2023

This paper proposes an air combat training framework based on hierarchical reinforcement learning to address the problem of non-convergence in training due to the curse of dimensionality caused by the large state space during air combat tactical pursuit. Using hierarchical reinforcement learning, three-dimensional problems can be transformed into two-dimensional problems, improving training performance compared to other baselines. To further improve the overall learning performance, a meta-learning-based algorithm is established, and the corresponding reward function is designed to further improve the performance of the agent in the air combat tactical chase scenario. The results show that the proposed framework can achieve better performance than the baseline approach.
On Complexity of Deterministic and Nondeterministic Decision Trees for Conventional Decision Tables from Closed Classes
Authors: Ostonov Azimkhon , Moshkov Mikhail
Published: October 2023

In this paper, we consider classes of conventional decision tables closed relative to the removal of attributes (columns) and changing decisions assigned to rows. For tables from an arbitrary closed class, we study the dependence of the minimum complexity of deterministic and nondeterministic decision trees on the complexity of the set of attributes attached to columns. We also study the dependence of the minimum complexity of deterministic decision trees on the minimum complexity of nondeterministic decision trees. Note that a nondeterministic decision tree can be interpreted as a set of true decision rules that covers all rows of the table.
Picture Fuzzy Soft Matrices and Application of Their Distance Measures to Supervised Learning: Picture Fuzzy Soft k-Nearest Neighbor (PFS-kNN)
Authors: Memiş Samet
Published: October 2023

This paper redefines picture fuzzy soft matrices (pfs-matrices) because of some of their inconsistencies resulting from Cuong’s definition of picture fuzzy sets. Then, it introduces several distance measures of pfs-matrices. Afterward, this paper proposes a new kNN-based classifier, namely the Picture Fuzzy Soft k-Nearest Neighbor (PFS-kNN) classifier. The proposed classifier utilizes the Minkowski’s metric of pfs-matrices to find the k-nearest neighbor. Thereafter, it performs an experimental study utilizing four UCI medical datasets and compares to the suggested approach using the state-of-the-art kNN-based classifiers. To evaluate the performance of the classification, it conducts ten iterations of five-fold cross-validation on all the classifiers. The findings indicate that PFS-kNN surpasses the state-of-the-art kNN-based algorithms in 72 out of 128 performance results based on accuracy, precision, recall, and F1-score. More specifically, the proposed method achieves higher accuracy and F1-score results compared to the other classifiers. Simulation results show that pfs-matrices and PFS-kNN are capable of modeling uncertainty and real-world problems. Finally, the applications of pfs-matrices to supervised learning are discussed for further research.
Pyrolysis and Combustion Behavior of Flax Straw as Biomass: Evaluation of Kinetic, Thermodynamic Parameters, and Qualitative Analysis of Degradation Products
Authors: Vafakish Bahareh , Babaei-Ghazvini Amin , Ebadian Mahmood , Acharya Bishnu
Published: October 2023

This study describes an investigation of the pyrolysis and combustion of flax straw as biofuel, focusing on the physicochemical properties and kinetic and thermodynamic parameters, and evaluates the type of degradation products using the thermogravimetry analysis–Fourier transform infrared spectroscopy (TGA-FTIR) technique. Pyrolysis and combustion processes were studied via thermogravimetric analysis at different heating rates of 5-10-15 and 20 °C min, one using three isoconversional methods and one using a model-fitting method. The activation energies, frequency factors, and thermodynamic parameters of flax straw biomass were investigated using different models. The obtained activation energy values for pyrolysis varied between 101.0 and 109.6 kJ mol−1 and for combustion were between 203.3 and 239.2 kJ mol−1. The frequency factors were determined to be 1.7 × 109 for pyrolysis and 1.5 × 1017 s−1 for combustion. The change in Gibbs free energy (ΔG) for the pyrolysis of flax straw was calculated to be 162.6 kJ mol−1, whereas for combustion it increased to 203.9 kJ mol−1. A notable contrast between the volatiles produced by pyrolysis and combustion is evident from the real-time analysis of the degradation products. Specifically, carboxylic acids, aromatics, alkanes, and alcohols are the principal degradation products during pyrolysis, while carbon dioxide is the primary component produced during combustion. These encouraging research outcomes regarding flax straw pyrolysis and combustion can broaden its application in bioenergy and biofuel, thus contributing significantly to it for resource recovery.
Enhanced Economic Load Dispatch by Teaching–Learning-Based Optimization (TLBO) on Thermal Units: A Comparative Study with Different Plug-in Electric Vehicle (PEV) Charging Strategies
Authors: Khobaragade Tejaswita , Chaturvedi K. T.
Published: October 2023

This research paper presents an enhanced economic load dispatch (ELD) approach using the Teaching–Learning-Based Optimization (TLBO) algorithm for 10 thermal units, examining the impact of Plug-in Electric Vehicles (PEVs) in different charging scenarios. The TLBO algorithm was utilized to optimize the ELD problem, considering the complexities associated with thermal units. The integration of PEVs in the load dispatch optimization was investigated, and different charging profiles and probability distributions were defined for PEVs in various scenarios, including overall charging profile, off-peak charging, peak charging, and stochastic charging. These tables allow for the modeling and analysis of PEV charging behavior and power requirements within the power system. By incorporating PEVs, additional controllable resources were introduced, enabling more effective load management and grid stability. The comparative analysis showcases the advantages of the TLBO-based ELD model with PEVs, demonstrating the potential of coordinated dispatch strategies leveraging PEV storage and controllability. This paper emphasizes the importance of integrating PEVs into the load dispatch optimization process, utilizing the TLBO algorithm, to achieve economic and reliable power system operation while considering different PEV charging scenarios.
A Quantitatively Divided Approach for the Vertical Belt of Vegetation Based on NDVI and DEM—An Analysis of Taibai Mountain
Authors: Zhao Ting , Bai Hongying , Han Hongzhu , Ta Zhijie , Li Peilin , Wang Pengtao
Published: October 2023

Vertical vegetation differentiation is the most important form of spatial pattern in mountainous areas. It is of great significance to accurately divide vegetation into vertical zones for the study of mountain ecosystems and ecological protection. In order to accurately divide the vertical zone of mountain vegetation and determine the spatial distribution of mountain vegetation, the relationship between the vegetation index of various vegetation types and altitude was examined using remote sensing and geographic information technology. Taking Taibai Mountain, the main peak of the Qinling Mountains in China, as the study area, based on the difference in NDVI between summer and autumn (DNSA), this work constructed a DEM-NDVI scatter plot and quantified the boundary of the vertical zone by the half-peak width calculation method. The findings showed that: (1) the vertical distribution pattern of mountain vegetation may very well be reflected in the scatterplot that NDSA and DEM created; (2) Six vertical belts could be accurately identified to the meter level on Taibai Mountain’s south slope. Up to the altitude, the oak forest zone from the bottom of the mountain to the elevation of 1919 m, the pine-oak mixed forest zone is distributed in 1919–2331 m, the birch forest is distributed in 2115–2585 m, the fir forest is distributed in 2516–3150 m, the redwood forest is distributed in 3109–3551 m, and the alpine scrub meadow is distributed in 3551 m to the peak. On the north slope, 1053–2087 m above sea level is oak forest, 2087–2693 is birch forest, 2562–3006 is fir forest, 2987–3513 m is redwood forest, and 3513 to the top of the mountain is alpine scrub meadow; and (3) the distribution pattern of the vegetation vertical belt on the DEM-NDVI scatter plot was essentially compatible with the vegetation classification results derived from remote sensing images. The DEM-NDVI scatter plot can reflect the average distribution of vegetation population and can more accurately express the characteristics of vegetation vertical zone changes with altitude.
Pocket Parks: A New Approach to Improving the Psychological and Physical Health of Recreationists
Authors: Huang Yabing , Lin Xiaoqian , Lin Shumeng , Chen Ziyi , Fu Weicong , Wang Minghua , Dong Jianwen
Published: October 2023

The increasing density of cities poses a huge threat to public health, so pocket parks with high accessibility and flexibility have become potential resources to promote public health. In this context, the ways in which pocket parks can improve public health have become the focus and challenge of current research. This study selected 10 different types of pocket parks in Fuzhou, China, as the research subjects and collected real-time psychological and physiological data of participants by watching videos of the sample plots. The aim was to explore the impact of the environmental characteristics of pocket parks on the psychological and physiological responses of recreational users. The results of the study showed that: (1) the environmental characteristics of pocket parks significantly affect the psychological and physiological responses of recreationists. Different environmental characteristics can affect recreationists’ emotional state, attention recovery, environmental preferences, and the indicators of IBI, HR, SDNN, RMSSD, pNN50, SCL, and EMG to varying degrees. (2) The environment of pocket parks may encourage recreationists to generate positive psychological benefits when the site is larger and has a higher degree of scenic beauty, and when the space is not effectively confined. A pocket park environment with a low paving ratio, open view, cultural elements, topographic changes, special vegetation and distributing space can also have a positive effect on the psychological benefits of recreationists to a certain extent. Low canopy density and high green visibility can also play a role in suppressing negative emotions. (3) Pocket parks with high levels of depression and off-site disturbance are not conducive to positive physiological responses from recreationists, while pocket parks with high levels of green visibility and beauty and specialized vegetation are more likely to provide health benefits to them.
The Diversity of Wood and Non-Wood Forest Products: Anatomical, Physical, and Chemical Properties, and Potential Applications
Authors: Sousa Vicelina , Miranda Isabel , Quilhó Teresa , Pereira Helena
Published: October 2023

Forests are continuously changing, as is the related gap in our understanding [...]
Immune-Boosting Potentiating Properties of Brassica nigra Hydroalcoholic Extract in Cyclophosphamide-Induced Immunosuppression in Rats
Authors: Barakat Hassan , Alkhurayji Raghad I. , Aljutaily Thamer
Published: October 2023

The antioxidative and immune-boosting properties of the hydroalcoholic extract of Brassica nigra sprouts in cyclophosphamide-induced immunosuppression in rats were investigated in this study. B. nigra sprouts were prepared in the lab to monitor the bio-changes in bioactive compounds during the sprouting period up to 7 days at 17 ± 1 °C and 90% relative humidity. The total phenolic content (TPC), antioxidant activity (AOA), total flavonoids (TFs), total flavonols (TFLs), and total carotenoids (TCs) were evaluated. Consequently, the identification and quantification of phenolic acids, their derivatives, and flavonoids were carried out using HPLC. Subsequently, the selected BN sprout (6-day-old sprout) was biologically examined, and oxidative stress biomarkers, hematological parameters, immunoglobulins (Igs), and pro-inflammatory and anti-inflammatory cytokines were investigated. An increase in TPC, AOA, TFs, TFLs, and TCs was observed by increasing the sprouting time. The HPLC analysis indicated that the B. nigra seeds contained 10 phenolic acids and 4 flavonoids, predominantly syringic acid and quercetin, respectively. After 3 days, the number of phenolic acids increased to 16, predominantly syringic acid, and the number of flavonoids increased to 7, predominantly quercetin. On the 6th day, 13 phenolic acids were estimated, with the highest being benzoic acid, and 6 flavonoids were estimated, with the highest being quercetin. The greatest rise in phenols was seen on the sixth day of sprouting. These included caffeic acid, chlorogenic acid, cinnamic acid, ferulic acid, coumaric acid, benzoic acid, and rosmarinic acid. Flavonoids such as kaempferol and myricetin increased. The sprouts on day 6 were recorded as having the highest bioactive compounds and AOA content. The selected B. nigra sprouts were examined for antioxidative and immunomodulatory properties in a rat model. Dosing 250 and 500 mg kg−1, the rats exhibited significant improvements in terms of antioxidative stress and the number of white blood cells (WBCs), lymphocytes, and neutrophils in the blood, indicating stimulation of the immune response in a dose-dependent manner. In addition, the production of immune proteins, such as IgG, IgM, and IgA, was enhanced in the blood. Moreover, the 500 mg kg−1 concentration of BN extract stimulated cytokine production in a stronger manner than the 250 mg kg−1 concentration, indicating that the extract significantly increased immune activity. In conclusion, the results indicate that mustard seed extracts have immunosuppressive properties against cyclophosphamide-induced immunosuppression in rats.
Spin Equilibrium of Rapidly Spinning Neutron Stars via Transient Accretion
Authors: Bhattacharyya Sudip
Published: October 2023

The concept of spin equilibrium due to an interaction between the stellar magnetosphere and a thin, Keplerian accretion disk, and a well-known formula of the corresponding equilibrium spin frequency, provide a key understanding of spin evolution and the distribution of rapidly spinning neutron stars, viz., millisecond pulsars. However, this concept and formula are for stable accretion, but the mass transfer to most accreting millisecond pulsars is transient and the accretion rate evolves by orders of magnitude during an outburst. In this short and focussed review, we briefly discuss a relatively new concept of the spin equilibrium condition and a new formula for the equilibrium spin frequency for transiently accreting millisecond pulsars. We also review a new method to estimate this equilibrium spin frequency for observed transiently accreting millisecond pulsars, even when a pulsar has not yet attained the spin equilibrium. These will be crucial to probe the spin evolution and distribution of millisecond pulsars, and should also be applicable to all magnetic stars transiently accreting via a thin, Keplerian accretion disk.
The Genome of the Korean Island-Originated Perilla citriodora ‘Jeju17’ Sheds Light on Its Environmental Adaptation and Fatty Acid and Lipid Production Pathways
Authors: Bae Seon-Hwa , Lee Myoung Hee , Lee Jeong-Hee , Yu Yeisoo , Lee Jundae , Kim Tae-Ho
Published: October 2023

Perilla is a key component of Korean food. It contains several plant-specialized metabolites that provide medical benefits. In response to an increased interest in healthy supplement food from the public, people are focusing on the properties of Perilla. Nevertheless, unlike rice and soybeans, there are few studies based on molecular genetics on Perilla, so it is difficult to systematically study the molecular breed. The wild Perilla, Perilla citriodora ‘Jeju17’, was identified a decade ago on the Korean island of Jeju. Using short-reads, long-reads, and Hi-C, a chromosome-scale genome spanning 676 Mbp, with high contiguity, was assembled. Aligning the ‘Jeju17’ genome to the ‘PC002’ Chinese species revealed significant collinearity with respect to the total length. A total of 31,769 coding sequences were predicted, among which 3331 were ‘Jeju17’-specific. Gene enrichment of the species-specific gene repertoire highlighted environment adaptation, fatty acid metabolism, and plant-specialized metabolite biosynthesis. Using a homology-based approach, genes involved in fatty acid and lipid triacylglycerol biosynthesis were identified. A total of 22 fatty acid desaturases were found and comprehensively characterized. Expression of the FAD genes in ‘Jeju17’ was examined at the seed level, and hormone signaling factors were identified. The results showed that the expression of FAD genes in ‘Jeju17’ at the seed level was high 25 days after flowering, and their responses of hormones and stress were mainly associated with hormone signal transduction and abiotic stress via cis-elements patterns. This study presents a chromosome-level genome assembly of P. citriodora ‘Jeju17’, the first wild Perilla to be sequenced from the Korean island of Jeju. The analyses provided can be useful in designing ALA-enhanced Perilla genotypes in the future.
The Role of lncRNAs in Pig Muscle in Response to Cold Exposure
Authors: Zhang Dongjie , Wang Liang , Wang Wentao , Liu Di
Published: October 2023

Cold exposure is an essential factor affecting breeding efforts in cold regions. Muscle, as an important tissue for homeothermic animals, can produce heat through shivering thermogenesis (ST) and non-shivering thermogenesis (NST) under cold exposure. Long non-coding RNAs (lncRNAs) play important roles in regulating gene expression. However, the regulatory mechanisms of lncRNAs and their role in the thermogenesis of pigs are unclear. We examined lncRNAs in the skeletal muscle of an indigenous pig breed, the Enshi black pig, when the pigs were exposed to acute or chronic cold. Three pigs were maintained inside a pig house (control group), three pigs were maintained outside the pig house for 55 d (chronic cold group), and three pigs were suddenly exposed to the conditions outside the pig house for 3 days (acute cold group). After the experiment, the longissimus dorsi of each pig were collected, and their lncRNA profiles were sequenced and analyzed. Each sample obtained nearly 12.56 Gb of clean data. A total of 11,605 non-coding RNAs were obtained, including 10,802 novel lncRNAs. The number of differentially expressed lncRNAs (DElncRNAs) was identified under acute cold (427) and cold acclimation (376), with 215 and 192 upregulated lncRNAs, respectively. However, only 113 lncRNAs were commonly upregulated by acute cold and cold acclimation. In addition, 65% of the target genes were trans-regulated by DElncRNAs. The target genes were enriched in signal transduction, immune system, cell growth and death pathways, and amino acid and carbohydrate metabolism. Compared to cold acclimation, acute cold stress-induced more DElncRNAs and response pathways. In conclusion, low temperatures altered the expression levels of lncRNAs and their target genes in muscle tissue. Some potential mechanisms were revealed, including ion migration and the metabolism of amino acids and carbohydrates.
Community Champions: The Crucial Contribution of an Independent Pharmacy in COVID-19 Vaccination Efforts in an Underserved Community
Authors: Whitner Chardaé , Curtis Stacey D. , Allen John M. , Duane Kevin J.
Published: October 2023

Historically, pharmacists in independent community pharmacies have been pivotal in promoting community health. During the COVID-19 pandemic, they demonstrated their commitment by advocating for vaccination and providing accessible care, particularly in underserved communities. By addressing disparities, implementing strategies like mobile clinics and community outreach, and fostering trust and engagement, independent community pharmacists played a crucial role in bridging gaps in healthcare access for vulnerable populations and mitigating the impact of the COVID-19 pandemic.
Knowledge Graph Construction to Facilitate Indoor Fire Emergency Evacuation
Authors: Da Mingkang , Zhong Teng , Huang Jiaqi
Published: October 2023

Indoor fire is a sudden and frequent disaster that severely threatens the safety of indoor people worldwide. Indoor fire emergency evacuation is crucial to reducing losses involving various objects and complex relations. However, traditional studies only rely on numerical simulation, which cannot provide adequate support for decision-making in indoor fire scenarios. The knowledge graph is a knowledge base that can fully utilize massive heterogeneous data to form a sound knowledge system; however, it has not been effectively applied in the fire emergency domain. This study is a preliminary attempt to construct a knowledge graph for indoor fire emergency evacuation. We constructed the indoor fire domain ontology and proposed a four-tuple knowledge representation model. A knowledge graph was constructed with 1852 nodes and 2364 relations from 25 indoor fire events. The proposed method was tested for the case study of Henan Pingdingshan ‘5.25’ Fire Accident in China. Results show that the proposed knowledge representation model and the corresponding knowledge graph can represent complicated indoor fire events and support indoor fire emergency evacuation.
Interactions between Quantum Dots and G-Actin
Authors: Le Nhi , Chand Abhishu , Braun Emma , Keyes Chloe , Wu Qihua , Kim Kyoungtae
Published: October 2023

Quantum dots (QDs) are a type of nanoparticle with excellent optical properties, suitable for many optical-based biomedical applications. However, the potential of quantum dots to be used in clinical settings is limited by their toxicity. As such, much effort has been invested to examine the mechanism of QDs’ toxicity. Yet, the current literature mainly focuses on ROS- and apoptosis-mediated cell death induced by QDs, which overlooks other aspects of QDs’ toxicity. Thus, our study aimed to provide another way by which QDs negatively impact cellular processes by investigating the possibility of protein structure and function modification upon direct interaction. Through shotgun proteomics, we identified a number of QD-binding proteins, which are functionally associated with essential cellular processes and components, such as transcription, translation, vesicular trafficking, and the actin cytoskeleton. Among these proteins, we chose to closely examine the interaction between quantum dots and actin, as actin is one of the most abundant proteins in cells and plays crucial roles in cellular processes and structural maintenance. We found that CdSe/ZnS QDs spontaneously bind to G-actin in vitro, causing a static quenching of G-actin’s intrinsic fluorescence. Furthermore, we found that this interaction favors the formation of a QD–actin complex with a binding ratio of 1:2.5. Finally, we also found that CdSe/ZnS QDs alter the secondary structure of G-actin, which may affect G-actin’s function and properties. Overall, our study provides an in-depth mechanistic examination of the impact of CdSe/ZnS QDs on G-actin, proposing that direct interaction is another aspect of QDs’ toxicity.