bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of substrate formulation for Hericium erinaceus by replacing wood by straw and their effect on enzyme activities
Authors: Lu Zhu , Liu Lingyun , Ren Ziming , Hu Shuang , Wang Yue , Ji Shujuan , Wang Xu , Du Zhongwei , Liu Yanni , Yang Yang , Yu Yanshen
Published: December 2024

Introduction

China is rich in straw resources. The utilization of straw in the cultivation of edible fungi partially resolves the resource conflicts between mushroom cultivation and forest industry and also contributes to environmental protection.

Methods

In this study, based on the technology of replacing wood by grass, the straw formula for mycelial culture of Hericium erinaceus was optimized with Simplex-lattice method commonly used in mixture design. By measuring the growth rate and the activity of lignocellulose degrading enzymes of mycelia in different formulations, and further combining with model optimization, the optimal formulation was screened and validated for mushroom cultivation.

Results

In the experiments, different kinds of straw used as the main material showed interaction effects, further affecting the growth rate of mycelia and the activities of laccase, cellulase, and neutral xylanase. The screened optimal formula was composed of 16.3% rice straw, 59.7% cob, 20.0% wheat bran, 2.0% gypsum, 1.0% sucrose, and 1.0% calcium superphosphate. In the mushroom cultivation, 445.69 g of fresh mushroom were obtained and the biological efficiency reached 89.14%. The growth period of the first mushroom was shortened by 7-9 days. Some nutritional components of fruiting bodies, such as crude fats (6.10%), crude proteins (152.02 g/kg), K (19.71 g/kg), P (2.48 g/kg), and Se (6.06 g/kg), were significantly higher than those of the control formula.

Discussion

These above indicators indicated that the screened formula could be applied in the high-yield and high-quality cultivation of H. erinaceus. Our study lays the foundation for expanding cultivation and strains improvement of H. erinaceus, and is conducive in promoting the rapid development of H. erinaceus industry.
Unveiling the molecular mechanism of sepal curvature in Dendrobium Section Spatulata through full-length transcriptome and RNA-seq analysis
Authors: Qu Xuefeng , Li Na , Xu Cong , Huang Zifeng , Li Chunyan , Jiang Yang , Zheng Guizhao , Fu Haiping , Zhang Guangyan , Liu Chuan
Published: December 2024

Introduction

Orchids are renowned for their intricate floral structures, where sepals and petals contribute significantly to ornamental value and pollinator attraction. In Dendrobium Section Spatulata, the distinctive curvature of these floral organs enhances both aesthetic appeal and pollination efficiency. However, the molecular and cellular mechanisms underlying this trait remain poorly understood.

Methods

Morphological characteristics of five hybrids were analyzed, with a particular focus on hybrid H5, which exhibits pronounced sepal curling. Full-length transcriptomic sequencing was employed to assemble a reference transcriptome, while RNA-seq identified differentially expressed genes (DEGs) between sepals and petals. Gene ontology and pathway enrichment analyses were conducted to uncover biological processes associated with sepal curvature. Cytological microscopy was used to examine cell size and number, and quantitative real-time PCR (qRT-PCR) was performed to validate transcriptomic findings.

Results

The reference transcriptome contained 94,258 non-redundant transcripts, and RNA-seq identified 821 DEGs between sepals and petals, with 72.8% of these upregulated in sepals. Enrichment analysis revealed the significant involvement of DEGs in cytokinesis, cytoskeletal organization, and energy metabolism. Notably, myosin II filament organization was implicated in generating the mechanical forces responsible for curling, while metabolic pathways provided the energy necessary for these developmental processes. Cytological observations showed that the upper cell layers of the sepal were smaller and more numerous than the lower layers, indicating that differential cell growth contributes to sepal curvature. qRT-PCR analysis validated the differential expression of selected genes, supporting the transcriptomic findings.

Discussion

The interplay of cellular mechanics, cytoskeletal dynamics, and metabolic regulation is crucial in shaping sepal morphology. Future studies involving gene knockdown or overexpression experiments are recommended to validate the roles of specific genes in processes such as actin organization and myosin activity. Such work would provide deeper insights into the contributions of cytoskeletal dynamics and mechanical force generation to sepal morphogenesis.
Broad-spectrum resistance to fungal foliar diseases in wheat: recent efforts and achievements
Authors: Mourad Amira M. I. , Ahmed Asmaa A. M. , Baenziger P. Stephen , Börner Andreas , Sallam Ahmed
Published: December 2024

Wheat (Triticum spp.) is one of the most important cereal crops in the world. Several diseases affect wheat production and can cause 20-80% yield loss annually. Out of these diseases, stripe rust, also known as yellow rust (Puccinia striiformis f. sp. tritici), stem rust (Puccinia graminis f. sp. tritici), leaf rust (Puccinia recondita), and powdery mildew (Blumeria graminis f. sp. tritici) are the most important fungal diseases that infect the foliar part of the plant. Many efforts were made to improve wheat resistance to these diseases. Due to the continuous advancement in sequencing methods and genomic tools, genome-wide association study has become available worldwide. This analysis enabled wheat breeders to detect genomic regions controlling the resistance in specific countries. In this review, molecular markers significantly associated with the resistance of the mentioned foliar diseases in the last five years were reviewed. Common markers that control broad-spectrum resistance in different countries were identified. Furthermore, common genes controlling the resistance of more than one of these foliar diseases were identified. The importance of these genes, their functional annotation, and the potential for gene enrichment are discussed. This review will be valuable to wheat breeders in producing genotypes with broad-spectrum resistance by applying genomic selection for the target common markers and associated genes.
Fostering children’s creativity through LLM-driven storytelling with a social robot
Authors: Elgarf Maha , Salam Hanan , Peters Christopher
Published: December 2024

Creativity is an important skill that is known to plummet in children when they start school education that limits their freedom of expression and their imagination. On the other hand, research has shown that integrating social robots into educational settings has the potential to maximize children’s learning outcomes. Therefore, our aim in this work was to investigate stimulating children’s creativity through child-robot interactions. We fine-tuned a Large Language Model (LLM) to exhibit creative behavior and non-creative behavior in a robot and conducted two studies with children to evaluate the viability of our methods in fostering children’s creativity skills. We evaluated creativity in terms of four metrics: fluency, flexibility, elaboration, and originality. We first conducted a study as a storytelling interaction between a child and a wizard-ed social robot in one of two conditions: creative versus non-creative with 38 children. We investigated whether interacting with a creative social robot will elicit more creativity from children. However, we did not find a significant effect of the robot’s creativity on children’s creative abilities. Second, in an attempt to increase the possibility for the robot to have an impact on children’s creativity and to increase the fluidity of the interaction, we produced two models that allow a social agent to autonomously engage with a human in a storytelling context in a creative manner and a non-creative manner respectively. Finally, we conducted another study to evaluate our models by deploying them on a social robot and evaluating them with 103 children. Our results show that children who interacted with the creative autonomous robot were more creative than children who interacted with the non-creative autonomous robot in terms of the fluency, the flexibility, and the elaboration aspects of creativity. The results highlight the difference in children’s learning performance when inetracting with a robot operated at different autonomy levels (Wizard of Oz versus autonoumous). Furthermore, they emphasize on the impact of designing adequate robot’s behaviors on children’s corresponding learning gains in child-robot interactions.
Knowledge, perceptions, and management of symptoms of hormonal imbalance among adolescent girls in selected schools in Ghana: a qualitative exploratory study
Authors: Zakariah-Akoto Sawudatu , Abuaku Benjamin , Egbi Godfred , Klu Bismark Edem Kofi , Kyei-Baafour Eric , Ofori Michael Fokuo , Ahorlu Collins Stephen , Yeboah-Manu Dorothy
Published: December 2024

Introduction

Adolescent girls are more sensitive to hormonal imbalance with major impact on their nutritional, reproductive, physical, psychosocial, and academic wellbeing. This study explored adolescent girls’ knowledge and perceptions of causes and management of symptoms of hormonal imbalance.

Materials and methods

Using a qualitative approach, focus group discussions were conducted with 116 assented in-school adolescent girls aged 10–19 years between 3rd and 19th October 2022. Two urban and two rural communities in two regions were purposively selected for the study. Using a convenient sampling approach, participants were recruited from Upper Primary, Junior, and Senior High schools. Data was analyzed thematically using both inductive and deductive approaches.

Results

Senior High School participants had a fair understanding of hormonal imbalance in both regions. Symptoms were perceived to include headaches, heavy and painful periods, and pimples, most of which participants alluded to experiencing. Perceived causes included natural process of adolescent growth, consumption of unhealthy diets, use of cosmetics and medications. Perceived reproductive effects included infertility, pregnancy disorders, breastfeeding challenges, and low sexual drive. Physiological effects included extreme fatigue, loss of appetite and impaired growth. Psychosocial and academic effects included mood swings/irritability, low self-esteem, poor inter-personal relationship, poor concentration in class and irregular school attendance. Female relatives and friends were mostly consulted for advice. Self-medication, dietary modification, physical activities, and personal hygiene were adopted to manage perceived symptoms. Self-medication was common, but physical activities and dietary modification were also adopted by most participants to manage symptoms.

Conclusion

It is recommended that Ghana Education Service should formally incorporate hormonal-related issues into its School Health Education Programmes to enhance knowledge, attitudes, and management among adolescent girls at all levels of education.
Performance of the Verily Study Watch for measuring sleep compared to polysomnography
Authors: Saeb Sohrab , Nelson Benjamin W. , Barman Poulami , Verma Nishant , Allen Hannah , de Zambotti Massimiliano , Baker Fiona C. , Arra Nicole , Sridhar Niranjan , Sullivan Shannon S. , Plowman Scooter , Rainaldi Erin , Kapur Ritu , Shin Sooyoon
Published: December 2024

Introduction

This study evaluated the performance of a wrist-worn wearable, Verily Study Watch (VSW), in detecting key sleep measures against polysomnography (PSG).

Methods

We collected data from 41 adults without obstructive sleep apnea or insomnia during a single overnight laboratory visit. We evaluated epoch-by-epoch performance for sleep vs. wake classification, sleep stage classification and duration, total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), sleep efficiency (SE), and number of awakenings (NAWK). Performance metrics included sensitivity, specificity, Cohen's kappa, and Bland-Altman analyses.

Results

Sensitivity and specificity (95% CIs) of sleep vs. wake classification were 0.97 (0.96, 0.98) and 0.70 (0.66, 0.74), respectively. Cohen's kappa (95% CI) for 4-class stage detection was 0.64 (0.18, 0.82). Most VSW sleep measures had proportional bias. The mean bias values (95% CI) were 14.0 min (5.55, 23.20) for TST, −13.1 min (−21.33, −6.21) for WASO, 2.97% (1.25, 4.84) for SE, −1.34 min (−7.29, 4.81) for SOL, 1.91 min (−8.28, 11.98) for light sleep duration, 5.24 min (−3.35, 14.13) for deep sleep duration, and 6.39 min (−0.68, 13.18) for REM sleep duration. Mean and median NAWK count differences (95% CI) were 0.05 (−0.42, 0.53) and 0.0 (0.0, 0.0), respectively.

Discussion

Results support applying the VSW to track overnight sleep measures in free-living settings. Registered at clinicaltrials.gov (NCT05276362).
Imaging and clinical outcomes of COVID-19- vs. non-COVID-19-related cerebral venous thrombosis
Authors: Maxhuni Toska , Doeppner Thorsten R. , Braun Tobias , Emde Julia , Struffert Tobias , Dembek Thomas , Huttner Hagen B. , Juenemann Martin B. , Gerner Stefan T.
Published: December 2024

Background

Cerebral venous thrombosis (CVT) is a rare but serious subtype of stroke. Several studies have reported an increased incidence of CVT after either COVID-19 (CoV19) infection or vaccination; however, data on clinical characteristics, the radiological profiles, and the outcomes of these patients with CVT as the only severe symptom of a CoV19 infection or vaccination compared to patients with non-CoV19-related CVT are still scarce.

Methods

We performed a retrospective monocentric study over 10 years (January 2013–December 2022) that included consecutive patients with a confirmed diagnosis of CVT based on imaging of the cerebral venous system. Patients were categorized as CoV19 CVT (either due to infection or post-vaccination) or non-CoV19 CVT and compared regarding demographics, risk factors, clinical characteristics, and imaging findings as well as outcome (at discharge, at 6 months, and last follow-up). Furthermore, sub-analyses were performed to compare CoV19-infection-related-CVT and CoV19-vaccination-related-CVT patients.

Results

Overall, 122 patients with suspected CVT were identified. After excluding patients with missing data (n = 20) or missing imaging of the cerebral venous system (n = 31), 71 patients with confirmed CVT remained for the final analyses. Of those, 11 patients had CoV19 CVT (infection n = 3, vaccination n = 8), and 60 patients had non-CoV19-CVT. There were no differences regarding median age (CoV19: 40 [IQR: 22–70] vs. non-CoV19: 41 [IQR:27–64]) or percentage of female sex among both groups. A lower rate of CVT risk factors was observed in the CoV19 group but without significant differences. No patient with CoV19 CVT displayed impaired consciousness on presentation, and only 30% had focal neurological deficits compared to 51.7% in the control group. The rate of CVT-related intracranial hemorrhage and venous infarcts were 27.3% and 9.1%, respectively, in the CoV19 group and 30% and 16.7%, respectively, in the non-CoV19 group. The mortality rate at discharge was 9.1% in the CoV19-CVT group vs. 3.3% in the non-CoV19-CVT group, without differences in functional outcomes during the follow-up period. Sub-analyses comparing CoV19-infection-related CVT vs. CoV19-vaccination-related CVT patients revealed no significant differences in clinical, imaging, or treatment characteristics.

Conclusion

In this monocentric study, there was no signal for a worse severity of CoV19 CVT compared to non-CoV19 CVT regarding clinical characteristics, imaging profile, or outcomes in patients with CVT only. Larger observational data with sophisticated workups of CVT patients are needed to confirm our results.
Automatic Filtering of Sugarcane Yield Data
Authors: da Silva Eudocio Rafael Otavio , Molin José Paulo , Wei Marcelo Chan Fu , Canal Filho Ricardo
Published: December 2024

Sugarcane mechanized harvesting generates large volumes of data that are used to monitor harvesters’ functionalities. The dynamic interaction of the machine-onboard instrumentation–crop system introduces discrepant and noisy values into the data, requiring outlier detectors to support this complex and empirical decision. This study proposes an automatic filtering technique for sugarcane harvesting data to automate the process. A three-step automated filtering algorithm based on a sliding window was developed and further evaluated with four configurations of the maximum variation factor f and six SW sizes. The performance of the proposed method was assessed by using artificial outliers in the datasets with an outlier magnitude (OM) of ±0.01 to ±1.00. Three case studies with real crop data were presented to demonstrate the effectiveness of the proposed filter in detecting outliers of different magnitudes, compared to filtering by another method in the literature. In each dataset, the proposed filter detected nearly 100% of larger (OM = ±1.00 and ±0.80) and medium (OM = ±0.50) magnitudes’ outliers, and approximately 26% of smaller outliers (OM = ±0.10, ±0.05, and ±0.01). The proposed algorithm preserved wider ranges of data compared to the comparative method and presented equivalent results in the identification of regions with different productive potentials of sugarcane in the field. Therefore, the proposed method retained data that reflect sugarcane yield variability at the row level and it can be used in practical application scenarios to deal with large datasets obtained from sugarcane harvesters.
Predictive Models for Correlation of Compaction Characteristics of Weakly Cohesive Soils
Authors: Debeleac Carmen Nicoleta , Buraga Andrei , Miron Daniel Sorin
Published: December 2024

In this paper, an investigation was conducted to characterize the behavior of weakly cohesive soil subjected to vibratory compaction. Thus, the authors developed a model for weakly cohesive soils, defined by inter-parametric laws that consider their initial state and predict the evolution of state parameters resulting from static and vibratory compaction processes, depending on the number of equipment passes. Four types of soil were proposed for testing, with different initial characteristics such as dry density, longitudinal modulus, and moisture content. Some correlations between main parameters involved in the compaction process were established, considering soil mechanical properties, compaction equipment, and in situ technology applied. The results obtained in the computational environment were implemented to predict the performance compaction process for an overall assessment. This research contributes to database development by offering valuable insights for specialists aiming to apply Industry 4.0 digitalization practices, which stipulate the use of predictability laws in pre-assessing the degree of soil compaction (or settlement) to estimate and maximize the efficiency of road construction or foundation works. These insights help optimize design processes, enhance functional performance, improve resource utilization, and ensure long-term sustainability in large infrastructure projects built on these soils.
Innovative Ultrasonic Spray Methods for Indoor Disinfection
Authors: Shalunov Andrey , Kudryashova Olga , Khmelev Vladimir , Genne Dmitry , Terentiev Sergey , Nesterov Viktor
Published: December 2024

This study explores the challenges associated with dispersing disinfectant liquids for sanitizing individuals, indoor spaces, vehicles, and outdoor areas. Among the various approaches, fine aerosol sprays with a high particle surface area emerge as a particularly promising solution. Ultrasonic spraying, which leverages diverse mechanisms of ultrasound interaction with liquids, offers several distinct advantages. Notably, it enables the production of fine aerosols from liquids with a broad range of physical and chemical properties, including variations in purity, viscosity, and surface tension. This capability is especially critical for disinfectant liquids and suspensions, which often exhibit low surface tension and/or high viscosity. The article provides a comprehensive review of ultrasonic spraying methods and technologies developed by the authors’ team in recent years. It highlights innovative ultrasonic sprayers, including the latest designs, which are capable of generating aerosols with precise dispersion characteristics and high productivity from disinfectant liquids.
A Comprehensive Review of Multiple Physical and Data-Driven Model Fusion Methods for Accurate Lithium-Ion Battery Inner State Factor Estimation
Authors: Tao Junjie , Wang Shunli , Cao Wen , Fernandez Carlos , Blaabjerg Frede
Published: December 2024

With the rapid global growth in demand for renewable energy, the traditional energy structure is accelerating its transition to low-carbon, clean energy. Lithium-ion batteries, due to their high energy density, long cycle life, and high efficiency, have become a core technology driving this transformation. In lithium-ion battery energy storage systems, precise state estimation, such as state of charge, state of health, and state of power, is crucial for ensuring system safety, extending battery lifespan, and improving energy efficiency. Although physics-based state estimation techniques have matured, challenges remain regarding accuracy and robustness in complex environments. With the advancement of hardware computational capabilities, data-driven algorithms are increasingly applied in battery management, and multi-model fusion approaches have emerged as a research hotspot. This paper reviews the fusion application between physics-based and data-driven models in lithium-ion battery management, critically analyzes the advantages, limitations, and applicability of fusion models, and evaluates their effectiveness in improving state estimation accuracy and robustness. Furthermore, the paper discusses future directions for improvement in computational efficiency, model adaptability, and performance under complex operating conditions, aiming to provide theoretical support and practical guidance for developing lithium-ion battery management technologies.
Microfluidic Technology for Measuring Mechanical Properties of Single Cells and Its Application
Authors: Yin Yixin , Liu Ziyuan
Published: December 2024

Cellular mechanical properties are critical for tissue and organ homeostasis, which are associated with many diseases and are very promising non-labeled biomarkers. Over the past two decades, many research tools based on microfluidic methods have been developed to measure the biophysical properties of single cells; however, it has still not been possible to develop a technique that allows for high-throughput, easy-to-operate and precise measurements of single-cell biophysical properties. In this paper, we review the emerging technologies implemented based on microfluidic approaches for characterizing the mechanical properties of single cells and discuss the methodological principles, advantages, limitations, and applications of various technologies.
Growth Differentiation Factor 15 as a Biomarker for Risk Stratification in the Cardiothoracic Surgery Intensive Care Unit
Authors: Ferreira Ricardo , Velho Tiago R. , Pereira Rafael Maniés , Pedroso Dora , Draiblate Beatriz , Constantino Susana , Nobre Ângelo , Almeida Ana G. , Moita Luís F. , Pinto Fausto
Published: December 2024

Growth Differentiation Factor 15 (GDF15) is an emerging biomarker that significantly increases during acute stress responses, such as infections, and is moderately elevated in chronic and inflammation-driven conditions. While evidence suggests that high levels of GDF15 in cardiac surgery are associated with worse outcomes, its utility as an evaluator of early postoperative complications remains unclear. This study aims to characterize the postoperative profile of GDF15 in patients undergoing isolated surgical aortic valve replacement, evaluating its association with short-term outcomes. Serum samples from patients undergoing cardiac surgery were collected preoperatively and at defined postoperative time points (1 h, 6 h, 12 h, 24 h, and 48 h) to measure GDF15 levels. GDF15 levels significantly increased after surgery, peaking at 6 h. A positive correlation was observed between GDF15 levels and both cardiopulmonary bypass and aortic cross-clamp times. Notably, patients who developed postoperative acute kidney injury (AKI) or required prolonged hemodynamic support had significantly higher GDF15 levels, with increased mechanical ventilation time and extended intensive care unit length of stay. Furthermore, GDF15 levels correlated with postoperative SOFA scores at 24 h after surgery. GDF15 may be a valuable biomarker for risk stratification and guiding therapeutic decisions in cardiac surgery patients. Higher GDF15 levels were significantly associated with prolonged hemodynamic support, postoperative AKI, and measures of illness severity.
Rapid Detection of PML::RARA Fusions in Acute Promyelocytic Leukemia: CRISPR/Cas9 Nanopore Sequencing with Adaptive Sampling
Authors: Middlezong William , Stinnett Victoria , Phan Michael , Phan Brian , Morsberger Laura , Klausner Melanie , Ghabrial Jen , DeMetrick Natalie , Zhu Jing , James Trisha , Pallavajjala Aparna , Gocke Christopher D. , Baer Maria R. , Zou Ying S.
Published: December 2024

Acute promyelocytic leukemia (APL) accounts for approximately 10–15% of newly diagnosed acute myeloid leukemia cases and presents with coagulopathy and bleeding. Prompt diagnosis and treatment are required to minimize early mortality in APL as initiation of all-trans retinoic acid therapy rapidly reverses coagulopathy. The PML::RARA fusion is a hallmark of APL and its rapid identification is essential for rapid initiation of specific treatment to prevent early deaths from coagulopathy and bleeding and optimize patient outcomes. Given limitations and long turnaround time of current gene fusion diagnostic strategies, we have developed a novel amplification-free nanopore sequencing-based approach with low cost, easy setup, and fast turnaround time. We termed the approach CRISPR/Cas9-enriched nanopore sequencing with adaptive sampling (CENAS). Using CENAS, we successfully sequenced breakpoints of typical and atypical PML::RARA fusions in APL patients. Compared with the standard-of-care genetic diagnostic tests, CENAS achieved good concordance in detecting PML::RARA fusions in this study. CENAS allowed for the identification of sequence information of fusion breakpoints involved in typical and atypical PML::RARA fusions and identified additional genes (ANKFN1 and JOSD1) and genomic regions (13q14.13) involving the atypical fusions. To the best of our knowledge, involvements of the ANKFN1 gene, the JOSD1 gene, and the 13q14.13 genomic region flanking with the SIAH3 and ZC3H13 genes have not been reported in the atypical PML::RARA fusions. CENAS has great potential to develop as a point-of-care test enabling immediate, low-cost bedside diagnosis of APL patients with a PML::RARA fusion. Given the early death rate in APL patients still reaches 15%, and ~10% of APL patients are resistant to initial therapy or prone to relapse, further sequencing studies of typical and atypical PML::RARA fusion might shed light on the pathophysiology of the disease and its responsiveness to treatment. Understanding the involvement of additional genes and positional effects related to the PML and RARA genes could shed light on their role in APL and may aid in the development of novel targeted therapies.
The Protection of RC Columns by Bio-Inspired Honeycomb Column Thin-Walled Structure (BHTS) Under Impact Load
Authors: Wang Shijie , Xia Hongxiang , Zong Yuncui , Liang Jianjun , Zhu Ripeng
Published: December 2024

The bio-inspired honeycomb column thin-walled structure (BHTS) is inspired by the biological structure of beetle elytra and designed as a lightweight buffer interlayer to prevent damage to the reinforced concrete bridge pier (RCBP) under the overload impact from vehicle impact. According to the prototype structure of the pier, a batch of scale models with a scaling factor of 1:10 was produced. The BHTS buffer interlayer was installed on the reinforced concrete (RC) column specimen to carry out the steel ball impact test. Then, the modified numerical model was subjected to the low-energy input impact test of the steel ball without energy loss during the falling process at the equivalent height of 1.0–3.5 m, and the dynamic response characteristics of the RC column were analyzed. By comparing the impact force and impact duration, maximum displacement, and residual displacement in the impact model, the BHTS buffer interlayer’s protective effect on RC columns under lower energy lateral impact was evaluated. Later, a high-energy input lateral impact test of a steel ball falling at an equivalent height of 20.0 m was carried out. According to the material damage, dynamic response, and energy absorption characteristics in the impact model, the failure process of the RC columns was analyzed. The results showed that BHTS absorbed 82.33% of the impact kinetic energy and reduced 77.27% of the impact force, 86.51% of the inertia force, and 64.86% of the base shear force under the failure mode of a 20 m impact condition. It can transform the shear failure of the RC column into bending failure and play an effective protective role for the RC column. This study can provide useful references for collision prevention design in practical engineering.
Experimental Study on Axial Compression of Bamboo Scrimber Cold-Formed Thin-Walled Steel Composite Special-Shaped Columns
Authors: Lei Chao , Wu Yuhao , Yang Bingyang , Wang Bingbing , Han Jianqiang , Fu Xiuyan
Published: December 2024

As one of the four key sectors for energy saving and emissions reduction, the construction industry faces ongoing high energy consumption and emissions. To support China’s sustainable development, urgent promotion of green construction and energy-saving measures is necessary. This led to the proposal of nine specimens of L-shaped, T-shaped, and cross-shaped engineered bamboo, cold-formed thin-walled steel, and their combinations for axial compression tests to study the effect of bamboo–steel structures on axial compression performance. The results showed that the load-bearing capacity of the three bamboo–steel composite columns increased by 19.5–21.4% compared to the sum of steel composite and L-shaped bamboo composite columns, significantly enhancing overall stability and deformation capacity. The synergy between steel and engineered bamboo effectively addressed the instability issues of steel structures with large width-to-thickness ratios. Using Abaqus finite element software for simulation, the stress distribution at failure and load-displacement curves were closely aligned with experimental outcomes. The study presents a formula for calculating the axial compression capacity of cold-formed thin-walled steel-engineered bamboo composite columns, with theoretical and experimental discrepancies within 13.28%, offering a theoretical basis for the design of engineered bamboo–steel composite columns.
Analysis of Kinship and Population Genetic Structure of 53 Apricot Resources Based on Whole Genome Resequencing
Authors: Xin Qirui , Qing Jun , He Yanhong
Published: December 2024

Based on the single nucleotide polymorphism (SNP) markers developed by whole genome resequencing (WGRS), the relationship and population genetic structure of 53 common apricot (P. armeniaca) varieties were analyzed to provide a theoretical basis for revealing the phylogenetic relationship and classification of the common apricot. WGRS was performed on 53 common apricot varieties, and high-quality SNP sites were obtained after alignment with the “Yinxiangbai” apricot genome as a reference. Phylogenetic analysis, G matrix analysis, principal component analysis, and population structure analysis were performed using Genome-wide Complex Trait Analysis (GCTA), FastTree, Admixture, and other software. The average comparison ratio between the sequencing results and the reference genome was 97.66%. After strict screening, 88,332,238 high-quality SNP sites were finally obtained. Based on the statistical SNP variation type, it was found that LNLJX had the largest number of variations (3,951,322) and the lowest base transition/base transversion ratio (ts/tv = 1.77), indicating that its gene exchange events occurred less frequently. Based on the SNP point estimation of the relationship and genetic distance between samples, the relationship between species was 1.41–0.01, among which PLDJX and BK1 had the closest relationship of 1.41, and YZH and LGWSX had the farthest relationship of 0.01. The genetic distance between species was 0.00367–0.264344, the genetic distance between HMX and JM was the closest, and the genetic distance between WYX and YX was the farthest, which was the largest. Phylogenetic tree, PCA, and genetic structure analysis results all divided 53 common apricot varieties into four groups, and the classification results were consistent. The SNP markers mined using WGRS technology are useful not only to analyze the variation of common apricots, but also to effectively identify their kinship and genetic structure, which plays a critical role in the classification and utilization of common apricot germplasm resources.
Enhancing Environmental Performance: A Method for Identifying and Prioritizing Key Environmental Issues in Industry
Authors: Marie Dellise , Villot Jonathan , Gaucher Rodolphe , Amardeil Anne , Laforest Valérie
Published: December 2024

BAT-based regulations necessitate defining key environmental issues (KEIs) to focus data collection and discussions on the main topics when establishing best available techniques (BATs) at the sector level. However, Article 14 of the Industrial Emissions Directive (IED) suggests that some significant environmental issues may not be covered by BAT conclusions but still require the implementation of BATs at the local level, even in the absence of defined sectoral BAT references. The IED, along with the associated Commission Implementing Decisions and guides, does not offer guidelines for selecting KEIs at the local level, whether by the competent authority or the operator. To ensure full compliance with the IED by installations under its scope, this paper proposes a methodology for determining KEIs locally. Based on the environmental aspects of the installation, the sensitivity of the environment, and the levels of emissions or consumption, this methodology has been tested on a case study at the plant level to demonstrate its effectiveness. The paper then discusses the contributions and limitations of the methodology and suggests areas for future research. The proposed methodology was tested at the factory level, where it effectively identified and prioritized key environmental issues (KEIs) by focusing on site-specific environmental aspects not covered by sectoral BAT conclusions. The results suggested improved alignment with local environmental challenges, indicating the methodology’s effectiveness in capturing key issues that may require immediate action under Article 14 of the IED. This approach provides a practical framework for prioritizing environmental impacts based on local context and regulatory requirements.
Unlocking New Opportunities for Spatial Analysis of Farms’ Income and Business Activities in Italy: The Agricultural Regions in Shapefile Format
Authors: Quaresima Sara , Nino Pasquale , Cardillo Concetta , Di Paola Arianna
Published: December 2024

Italy is divided into 773 Agricultural Regions (ARs) based on shared physical and agronomic characteristics. These regions offer a valuable tool for analyzing various geographical, socio-economic, and environmental aspects of agriculture, including the climate. However, the ARs have lacked geospatial data, limiting their analytical potential. This study introduces the “Italian ARs Dataset”, a georeferenced shapefile defining the boundaries of each AR. This dataset facilitates geographical assessments of Italy’s complex agricultural sector. It also unlocks the potential for integrating AR data with other datasets like the Farm Accounting Data Network (FADN) dataset, in Italy represented by the Rete di Informazione Contabile Agricola (RICA), which samples hundreds of thousands of farms annually. To demonstrate the dataset’s utility, a large sample of RICA data encompassing 179 irrigated crops from 2011 to 2021, covering all of Italy, was retrieved. Validation confirmed successful assignment of all ARs present in the RICA sample to the corresponding shapefile. Additionally, to encourage the use of the ARs Dataset with gridded data, different spatial-scale resolutions are tested to identify a suitable threshold. The minimal spatial scale identified is 0.11 degrees, a commonly adopted scale by several climate datasets within the EURO-CORDEX and COPERNICUS programs.
Ten Questions on Using Lung Ultrasonography to Diagnose and Manage Pneumonia in the Hospital-at-Home Model: Part I—Techniques and Patterns
Authors: Hsu Nin-Chieh , Lin Yu-Feng , Tsai Hung-Bin , Huang Tung-Yun , Hsu Chia-Hao
Published: December 2024

The hospital-at-home (HaH) model delivers hospital-level acute care, including diagnostics, monitoring, and treatments, in a patient’s home. It is particularly effective for managing conditions such as pneumonia. Point-of-care ultrasonography (PoCUS) is a key diagnostic tool in the HaH model, and it often serves as a substitute for imaging-based diagnosis in the HaH setting. Both standard and handheld ultrasound equipment are suitable for lung ultrasound (LUS) evaluation. Curvelinear and linear probes are typically used. Patient positioning depends on their clinical condition and specific diagnostic protocols. To enhance sensitivity, we recommend using at least 10-point protocols supported by studies for pneumonia. Five essential LUS patterns should be identified, including A-line, multiple B-lines (alveolar-interstitial syndrome), confluent B-lines, subpleural consolidation, and consolidation with air bronchogram. Pleural effusion is common, and its internal echogenicity can indicate severity and the need for invasive procedures. The current evidence on various etiologies and types of pneumonia is limited, but LUS demonstrates good sensitivity in detecting abnormal sonographic patterns in atypical pneumonia, tuberculosis, and ventilator-associated pneumonia. Further LUS studies in the HaH setting are required to validate and generalize the findings.
Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review
Authors: Surdu Amelia , Budala Dana Gabriela , Luchian Ionut , Foia Liliana Georgeta , Botnariu Gina Eosefina , Scutariu Monica Mihaela
Published: December 2024

Artificial intelligence (AI) is revolutionizing the field of oral and dental healthcare by offering innovative tools and techniques for optimizing diagnosis, treatment planning, and patient management. This narrative review explores the current applications of AI in dentistry, focusing on its role in enhancing diagnostic accuracy and efficiency. AI technologies, such as machine learning, deep learning, and computer vision, are increasingly being integrated into dental practice to analyze clinical images, identify pathological conditions, and predict disease progression. By utilizing AI algorithms, dental professionals can detect issues like caries, periodontal disease and oral cancer at an earlier stage, thus improving patient outcomes.
Charactering Neural Spiking Activity Evoked by Acupuncture Through Coupling Generalized Linear Model
Authors: Qin Qing , Zhang Kaiyue , Che Yanqiu , Han Chunxiao , Qin Yingmei , Li Shanshan
Published: December 2024

Acupuncturing the ST36 acupoint can evoke a responding activity in the spinal dorsal root ganglia and generate spikes. In order to identify the responding mechanism of different acupuncture manipulations, in this paper the spike history of neurons is taken as the starting point and the coupling generalized linear model is adopted to encode the neuronal spiking activity evoked by different acupuncture manipulations. Then, maximum likelihood estimation is used to fit the model parameters and estimate the coupling parameters of stimulus, the self-coupling parameters of the neuron’s own spike history and the cross-coupling parameters of other neurons’ spike history. We use simulation data to test the estimation algorithm’s effectiveness and analyze the main factors that evoke neuronal responding activity. Finally, we use the coupling generalized linear model to encode neuronal spiking activity evoked by two acupuncture manipulations, and estimate the coupling parameters of stimulus, the self-coupling parameters and the cross-coupling parameters. The results show that in acupuncture experiments, acupuncture stimulus is the inducing factor of neuronal spiking activity, and the cross-coupling of other neurons’ spike history is the main factor of neuronal spiking activity. Additionally, the higher the amplitude of the neuronal spiking waveform, the greater the cross-coupling parameter. This lays a theoretical foundation for the scientific application of acupuncture therapy.
Internal Energy, Fundamental Thermodynamic Relation, and Gibbs’ Ensemble Theory as Emergent Laws of Statistical Counting
Authors: Qian Hong
Published: December 2024

Statistical counting ad infinitum is the holographic observable to a statistical dynamics with finite states under independent and identically distributed N sampling. Entropy provides the infinitesimal probability for an observed empirical frequency ν^ with respect to a probability prior p, when ν^≠p as N→∞. Following Callen’s postulate and through Legendre–Fenchel transform, without help from mechanics, we show that an internal energy u emerges; it provides a linear representation of real-valued observables with full or partial information. Gibbs’ fundamental thermodynamic relation and theory of ensembles follow mathematically. u is to ν^ what chemical potential μ is to particle number N in Gibbs’ chemical thermodynamics, what β=T−1 is to internal energy U in classical thermodynamics, and what ω is to t in Fourier analysis.
Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities
Authors: Takata Ryosuke , Masumori Atsushi , Ikegami Takashi
Published: December 2024

We study the emergence of agency from scratch by using Large Language Model (LLM)-based agents. In previous studies of LLM-based agents, each agent’s characteristics, including personality and memory, have traditionally been predefined. We focused on how individuality, such as behavior, personality, and memory, can be differentiated from an undifferentiated state. The present LLM agents engage in cooperative communication within a group simulation, exchanging context-based messages in natural language. By analyzing this multi-agent simulation, we report valuable new insights into how social norms, cooperation, and personality traits can emerge spontaneously. This paper demonstrates that autonomously interacting LLM-powered agents generate hallucinations and hashtags to sustain communication, which, in turn, increases the diversity of words within their interactions. Each agent’s emotions shift through communication, and as they form communities, the personalities of the agents emerge and evolve accordingly. This computational modeling approach and its findings will provide a new method for analyzing collective artificial intelligence.
Novel Current-Fed Bidirectional DC-DC Converter for Battery Charging in Electric Vehicle Applications with Reduced Spikes
Authors: Sharma Piyush , Palwalia Dheeraj Kumar , Sharma Ashok Kumar , Gopal Yatindra , Rosas-Caro Julio C.
Published: December 2024

Electric vehicles (EVs) have emerged as the best alternative to conventional fossil fuel-based vehicles due to their lower emission rate and operating cost. The escalating growth of EVs has increased the necessity for distributed charging stations. On the other hand, the fast charging of EVs can be improved by the use of efficient converters. Hence, the fractional order proportional resonant (FOPR) controller-based current-fed bidirectional DC-DC converter is proposed in this work for EV charging applications. The output capacitance of the switches is utilized to achieve the resonance condition for zero voltage switching (ZVS) and zero current switching (ZCS). The proposed converter topology is implemented using the MATLAB Simulink tool. The result analysis verified that the proposed converter topology provides better switching characteristics for different operating modes, which is necessary for a high-voltage EV charger. Hence, it is proved that the proposed converter is more efficient for battery charging in EVs.
A Unified Semiconductor-Device-Physics-Based Ballistic Model for the Threshold Voltage of Modern Multiple-Gate Metal-Oxide-Semiconductor Field-Effect-Transistors
Authors: Chiang Te-Kuang
Published: December 2024

Based on the minimum conduction band edge caused by the minimum channel potential resulting from the quasi-3D scaling theory and the 3D density of state (DOS) accompanied by the Fermi–Dirac distribution function on the source and drain sides, a unified semiconductor-device-physics-based ballistic model is developed for the threshold voltage of modern multiple-gate (MG) transistors, including FinFET, Ω-gate MOSFET, and nanosheet (NS) MOSFET. It is shown that the thin silicon, thin gate oxide, and high work function will alleviate ballistic effects and resist threshold voltage degradation. In addition, as the device dimension is further reduced to give rise to the 2D/1D DOS, the lowest conduction band edge is increased to resist threshold voltage degradation. The nanosheet MOSFET exhibits the largest threshold voltage among the three transistors due to the smallest minimum conduction band edge caused by the quasi-3D minimum channel potential. When the n-type MOSFET (N-FET) is compared to the P-type MOSFET (P-FET), the P-FET shows more threshold voltage because the hole has a more effective mass than the electron.
Characteristics and Protection Methods for Double-Circuit HVDC Transmission Lines on the Same Tower Considering DC Line-Touching Faults
Authors: Tao Yan , Zheng Junchao , Kong Xiangping , Gao Lei , Lin Jinjiao , Wang Chenqing
Published: December 2024

In heavily loaded regional power grids, some AC transmission lines are confronting escalating pressures due to excessive short-circuit currents. To optimize AC channels, most research advocates for retrofitting existing AC lines into multi-line-commutated converter-based high-voltage direct current (LCC-HVDC) lines. However, there is a contradiction between limited land area for AC stations and the relatively large footprint of passive filters in LCC-HVDC; this paper introduces self-adapted LCC (SLCC) by replacing passive filter groups with a static var generator (SVG). Secondly, the reactive power compensation, harmonic filtering control methods of SVGs, and operation characteristics of the SLCC system are explored, and the harmonics of the grid-side current are reduced by nearly 14.6%. Then, to fill the gap of previous studies on solely AC or AC-DC line touching, inspired by emerging DC line-touching risks in double-circuit (LCC and SLCC) lines on the same tower, the equivalent models are formulated to elucidate the evolution mechanisms of voltage/current and extract fault features in various line-touching faults; it finds that the longitudinal differential current during line-touching faults can be capitalized. Based on the current feature, an effective protection algorithm tailored for the identification of DC line-touching faults is proposed. Finally, simulations are conducted to validate the efficacy of proposed control and protect methods, demonstrating the potential to enhance the reliability of AC to DC conversion projects.