bluuebunny/crossref_metadata_2025 huggingface dataset:
The validity and reliability of the Slovenian version of the health literacy questionnaire short-form (HLS-EU-Q16) among adults and older adults
Authors: Lamot Monika , Kirbiš Andrej
Published: December 2024

Introduction

Health literacy is an important predictor of health behavior and self-rated health, playing a crucial role in shaping public health outcomes. Valid and reliable health literacy assessments are essential for effectively tailoring health interventions, particularly in different cultural contexts. Several questionnaires have been developed to measure health literacy, including the widely used 47-item Health Literacy Questionnaire and its shorter versions. However, the validity of these shorter and more time efficient HLS-EU versions, such as the 16-item HLS-EU-Q16, has been less extensively researched in different age subgroups. Given Slovenia’s aging population and the differences in health literacy between adults and older adults, it is important to assess whether the HLS-EU-Q16 performs reliably across these groups. Therefore, the present study aimed to examine the validity and reliability of the 16-item health literacy questionnaire (HLS-EU-Q16) in Slovenia across two age groups: adults and older adults.

Methods

We analyzed representative Slovenian sample data from the Health Literacy of Adults study. The sample included 2,327 adults aged 23–64 years (53.7% women) and 876 older adults aged 65–99 years (55.7% women).

Results

Construct validity revealed a modified three-factor structure of the HLS-EU-Q16 among adults, reflecting a broader conceptualization of health literacy that encompasses overlapping domains of health promotion, disease prevention, and health care. In contrast, a two-factor structure emerged among older adults, indicating a more consolidated approach where these domains are perceived as part of an integrated health management strategy. This suggests that adults may conceptualize health literacy across multiple, yet interconnected dimensions, while older adults approach it more holistically. Convergent validity, reliability, concurrent-predictive, concurrent, and discriminant validity results were satisfactory for both age groups. Predictive validity, however, provided somewhat inadequate results, as the tool poorly predicted certain health behaviors, such as smoking, alcohol consumption, and physical activity, in both age groups.

Conclusion

Overall, the HLS-EU-Q16 demonstrated adequate validity and reliability among both adults and older adults, indicating that it is an appropriate instrument for assessing health literacy in Slovenia.
A hybrid deep learning-based approach for optimal genotype by environment selection
Authors: Khalilzadeh Zahra , Kashanian Motahareh , Khaki Saeed , Wang Lizhi
Published: December 2024

The ability to accurately predict the yields of different crop genotypes in response to weather variability is crucial for developing climate resilient crop cultivars. Genotype-environment interactions introduce large variations in crop-climate responses, and are hard to factor in to breeding programs. Data-driven approaches, particularly those based on machine learning, can help guide breeding efforts by factoring in genotype-environment interactions when making yield predictions. Using a new yield dataset containing 93,028 records of soybean hybrids across 159 locations, 28 states, and 13 years, with 5,838 distinct genotypes and daily weather data over a 214-day growing season, we developed two convolutional neural network (CNN) models: one that integrates CNN and fully-connected neural networks (CNN model), and another that incorporates a long short-term memory (LSTM) layer after the CNN component (CNN-LSTM model). By applying the Generalized Ensemble Method (GEM), we combined the CNN-based models and optimized their weights to improve overall predictive performance. The dataset provided unique genotype information on seeds, enabling an investigation into the potential of planting different genotypes based on weather variables. We employed the proposed GEM model to identify the best-performing genotypes across various locations and weather conditions, making yield predictions for all potential genotypes in each specific setting. To assess the performance of the GEM model, we evaluated it on unseen genotype-location combinations, simulating real-world scenarios where new genotypes are introduced. By combining the base models, the GEM ensemble approach provided much better prediction accuracy compared to using the CNN-LSTM model alone and slightly better accuracy than the CNN model, as measured by both RMSE and MAE on the validation and test sets. The proposed data-driven approach can be valuable for genotype selection in scenarios with limited testing years. In addition, we explored the impact of incorporating state-level soil data alongside the weather, location, genotype and year variables. Due to data constraints, including the absence of latitude and longitude details, we used uniform soil variables for all locations within the same state. This limitation restricted our spatial information to state-level knowledge. Our findings suggested that integrating state-level soil variables did not substantially enhance the predictive capabilities of the models. We also performed a feature importance analysis using RMSE change to identify crucial predictors. Location showed the highest RMSE change, followed by genotype and year. Among weather variables, maximum direct normal irradiance (MDNI) and average precipitation (AP) displayed higher RMSE changes, indicating their importance.
Relationship between functional independence and community integration of people with spinal cord injury in Bangladesh
Authors: Das Shazal Kumar , Bakhtiar Md , Sabrin Saiba Muhammad , Curtin Michael , Rahman Ehsanur , Nahid Zahid Bin Sultan , Rahman Zakia , Haque Md. Furatul , Patwary Md. Fazlul Karim , Alam Md. Jahangir , Hossain Md. Emran , Rahman Md. Atiar , Islam Shafiqul , Ashfaquzzaman Md. , Parvez Md. Anowar Khasru
Published: December 2024

Design

Prospective, cross-sectional study.

Objectives

To determine the functional outcome and home and social integration of people who had spinal cord injury and completed their inpatient rehabilitation.

Setting

Centre for the Rehabilitation of the Paralysed (CRP), Bangladesh.

Methods

Spinal Cord Independence Measure (SCIM) and Community Integration Questionnaire (CIQ) were used to analyse the relationship between the functional outcome and home and social integration at the end of rehabilitation. Descriptive and inferential statistics were performed to analyse the data.

Results

A total of two hundred participants (181 men and 19 women) were recruited for the study. Among the participants, 92.5% of them reported a history of trauma or accident, including road traffic accidents, falls and other injuries. Approximately 60% of participants presented with paraplegia and 62.5% of participants were categorized on the ASIA Impairment Scale (AIS) as Grade A, complete spinal cord injury. Participants with paraplegia and participants with a Grade B, incomplete injury, on the AIS were functionally more independent (p = 0.011)) compared with participants with tetraplegia and other AIS grades. Participants with paraplegia reported having a more active lifestyle (p = 0.040) in their home and social activities compared to those with tetraplegia. There was no significant association found between functional independence at pre-discharged and community integration one-month post-discharge of the people with SCI.

Conclusion

A month after discharge, there is no statistically significant relationship between community reintegration and functional independence. A measure of functional independence may not be a suitable indicator of community integration. It is proposed that to monitor a person's community integration the CIQ could be used with a measure of quality of life as this would indicate a person's contentment with their level of community integration.
Prevalence and associated factors of non-consensual sexual acts among adolescents in the Democratic Republic of Congo
Authors: Yode Miangotar , Ekofo Felly , Mudekereza Mihigo Blaise
Published: December 2024

Introduction

During adolescence, due to lack of experience, individuals may engage in or tolerate certain non-consensual acts under coercion. There are significant associations between forced sexual intercourse and a range of negative effects on reproductive health, as well as psychological and emotional health. Studies on non-consensual sexual acts among adolescents are rare in the Democratic Republic of Congo (DRC). This study is one of the first to focus on urban adolescents, aiming to assess the prevalence of non-consensual sexual acts and to identify associated factors.

Methods

Data for this study were obtained from the baseline survey of the project “Reducing the Vulnerability of Adolescents and Young Girls to Violence and HIV/AIDS Infection,” conducted in 2018 in the provinces of Kinshasa and Kasaï Oriental among adolescents aged 10-24 years. A total of 2,123 adolescents were surveyed (46.8% in Kinshasa and 53.2% in Kasaï Oriental). A structured survey questionnaire was developed in French to collect data. This questionnaire was pre-tested and corrected before use. Non-consensual sexual acts were assessed using three variables: (i) Have you ever experienced non-consensual touching, (ii) Have you ever experienced an attempted forced sexual intercourse, and (iii) Have you ever been physically forced, injured, or threatened to have sexual intercourse. Bivariate and multivariate analyses were conducted on these three variables separately.

Results

Among all adolescents surveyed, 11.5% reported having experienced non-consensual touching, 15.3% reported having experienced an attempted forced sexual intercourse, and 5.8% reported having been physically forced, injured, or threatened to have sexual intercourse. Among the 575 sexually active adolescents, these proportions were 43.4%, 57.4% and 22.0%, respectively. Prevalences were higher among girls and in the province of Kinshasa. Factors associated with non-consensual sexual acts included gender, cohabitation with biological parents (father and mother), age at first sexual intercourse, communication about sexuality or intimate subjects with a family member, and adolescents' perceptions of the role and place of partners in intimate relationships. A quarter (25.5%) of adolescents who were victims of forced sexual intercourse and were aware of an appropriate institution or person sought help from a professional for the violence they experienced.

Discussion

The results revealed a high prevalence of non-consensual sexual acts, the significance attributed by adolescents to traditional beliefs regarding the dominant role of men in intimate relationships, and the existence of barriers preventing victims of sexual violence from seeking appropriate care. These findings advocate for providing healthcare services tailored to the needs of adolescents and adapted to sociocultural contexts.
“Narrative images” as a learning approach: (transformative) adaptation scenarios for dealing with urban water risks in Hamburg, Germany
Authors: Hanf Franziska S. , Meier Linda , Hawxwell Tom , Oßenbrügge Jürgen , Knieling Jörg , Sillmann Jana
Published: December 2024

In recent years, weather-related extreme events have shown the limits of technical approaches to urban water challenges and highlighted the urgent need to rethink the relationship between cities and water and to see water as a partner in shaping transformative, climate-safe and just urban futures. However, existing scientific studies depicting future trajectories of urban water management have struggled to make the intertwined social and ecological dynamics of (transformative) urban adaptation tangible and accessible. This study focuses on the potential of visual communication of scenarios to stimulate both learning among scientists (during the process of creating the scenarios) and social learning (as a next step using the developed “narrative images”) to motivate diverse societal actors to engage with the complexity of sustainable urban water management. Art can overcome barriers of scientific and technical concepts and touch peoples' inner motivation for preserving and sustainably transforming our cities in a way that written texts cannot. As sustainability challenges transcend disciplines, this study draws methodically on an interdisciplinary scenario approach. Three adaptation scenarios were developed in a participatory process and professionally visualized as “narrative images” using the city of Hamburg as a case study. The scenarios take place in 2050 depicting a gradient ranging from coping to incremental adaptation to transformative adaptation for managing the water-adaptation nexus: “Water defensive city,” “Water resilient city,” and “Water aware city.” The scenario study shows innovatively how to bring the humanities, natural and engineering sciences into a deliberative dialog, while at the same time promoting collective learning. It can serve as a model for successful future interdisciplinary research and scenario developing exercises.
Optimal investment strategies for decarbonizing the Indian private road transport sector
Authors: Saraf Nandita , Shastri Yogendra
Published: December 2024

The Indian government's COP26 emission reduction target has led to explore strategies to decarbonize India's private road transport sector. Adoption of novel vehicle options such as E85, electric, and CNG vehicles and strong network of public transportation are expected to reduce the emissions significantly. A system dynamics model for India's private road transport sector has been developed previously. This study expands that model by incorporating the dynamics between public and private road transportation and uses it to identify strategy for optimal incentive allocation for novel vehicle adoption to minimize the GHG emissions. The idea of epsilon-constraint method for multi objective optimization has been used in this work. The results suggested a trade off between investment in incentives and reduction in GHG emissions. Incentivization strategy prioritized electric cars and two-wheelers, as well as charging/CNG stations, to discourage the adoption of petrol vehicles till CNG infrastructure was established. The minimum GHG emissions achieved was 535.5 Mt CO2e by 2050 with an investment of 137.74 trillion Indian Rupee when public transportation was not considered. Upon considering public transportation, the minimum GHG emissions further reduced to 464.5 Mt CO2e by 2050 with reduced investment of 128.25 trillion Indian Rupee, indicating greater emission reduction benefits per unit investment. However, beyond a certain threshold, increase in public transportation resulted in increased incentive investment due to a feedback effect. This necessitates incorporating dynamic analysis into policy strategy. Other strategies such as carbon tax and renewable share in electricity grid proves very effective in reducing GHG emissions as well as incentive investments. However, despite reducing emissions COP26 emission target for 2030 was missed by 34%. Banning the purchase of new petrol and diesel vehicles, along with restrictions on the use of existing petrol and diesel vehicles, could help bridge this gap.
Quantifying the effects of water management decisions on streambank stability
Authors: Wei Q. , Brookfield A. , Layzell A.
Published: December 2024

Both natural processes and human activities alter streamflow conditions, which can significantly affect streambank erosion and stability, leading to consequences such as sedimentation of reservoirs, contamination of streams, loss of productive land, and damage to infrastructure. Hydrological conditions, which are often controlled by water management decisions and infrastructure (e.g., reservoirs and dams), are a major factor affecting streambank erosion and stability. Extensive research has explored the relationships between hydrology, water management, and streambank stability. However, limited studies directly address the impacts of water management decisions, particularly reservoir operations, on the driving mechanisms of streambank stability such as changes in pore water pressure, pressure differentials between the surface and subsurface, and gravitational forces versus shear stress. This study builds upon these existing concepts by integrating them into a model that accounts for both the effects of water management and inherent hydrologic conditions on streambank stability.

The module estimates streambank stability using a factor of safety approach, with hydrologic conditions derived from an established integrated hydrologic model, HydroGeoSphere, coupled with the surface water operations model, OASIS. This module is validated and then demonstrated using simulations from the Lower Republican River Basin in Kansas, United States. Results indicate that several water management decisions, such as groundwater pumping and timing of reservoir releases, may negatively affect streambank stability by changing pore water pressure, the weight of the bank material, and the pressure differential between the surface and the subsurface. Given that most of the rivers and streams of the world are regulated by reservoir operations, this work demonstrates that water management practices need to be considered in simulations of streambank stability.
Estimating willingness-to-pay for adaptations to climate change in water resources projects: demonstration for Lesotho irrigation investment
Authors: Odunola Tolulope , Bryant Benjamin , Rowcroft Petrina , Zhilyaev Samson , Richardson Jeremy , Boehlert Brent , Castillo Diego , Strzepek Kenneth , Myer Ethan , Brown Casey , Ray Patrick
Published: December 2024

A broad set of tools, frameworks, and guidance documents are available for water resources project planning, design, evaluation, and implementation in an ever-evolving world. The principles underlying most of these resources aim to advance the practice of water systems engineering under uncertainty, preserve and enhance project benefits, and achieve investment goals. Approaches to financial and economic evaluation under climate uncertainty in civil infrastructure investments, in particular, are currently being reviewed by academics and practitioners in the field to assess their ability to deliver resilience, sustainability, and equity. In climate-sensitive projects, adaptation measures that help mitigate the adverse effects of climate change and preserve project benefits are required, and stakeholder willingness-to-pay (WTP) for these must be assessed. Typically, stakeholders and decision-makers utilize the outcomes of economic assessment methods such as cost–benefit analysis (CBA) to justify large capital investments. Synthesizing previous advancements in water resources planning and evaluation, this study illustrates how a CBA framework can be augmented by applying a Climate-informed Robustness Index (CRI). The analytics underpinning the CRI, as well as the summary metric itself, help characterize project climate vulnerability, while conducting CBA with and without potential adaptation measures can be used to estimate WTP of investors for adaptation to the identified climate vulnerabilities. The case study of a planned irrigated agriculture project in Lesotho highlights critical climate conditions for which adaptation measures such as integrated catchment management (ICM) plans can be introduced to safeguard project robustness.
An Electrifying View into the Life of Plants: The Plant Electrome
Authors: Reissig Gabriela Niemeyer , Oliveira Thiago Francisco de Carvalho , Parise André Geremia , Posso Douglas Antônio , Souza Gustavo Maia
Published: December 2024

Do living beings need brains to do extraordinary things? The human brain manages many tasks at the same time, from keeping the body working to thinking and dreaming, thanks to the electrical signals it produces. But what about organisms that survive pretty well without brains, like plants? You might be surprised to learn that plants can produce electricity as well, and they use electrical signals for communication, learning, self-preservation, and as a rapid alarm system against potential threats. All this without any brain cells! With scientific equipment, it is possible to study the hidden electrical activity of plants and discover the secrets of their lives in a challenging world. Plant scientists have developed gadgets like those used to study the brain to explore plant electricity. They have made astonishing discoveries about hidden aspects of plant life. Join us in exploring the electrifying world of plants and uncovering their remarkable powers.
Consumer willingness to pay for fair and sustainable foods: who profits in the agri-food chain?
Authors: Mouchtaropoulou Evangelia , Mallidis Ioannis , Giannaki Marianna , Koukaras Konstantinos , Früh Simon , Ettinger Tamara , Benmehaia Amine M. , Kacem Adnen , Achour Lotfi , Detzel Andreas , Gianotti Andrea , Samoggia Antonella , Ayfantopoulou Georgia , Argiriou Anagnostis
Published: December 2024

Going through an era where sustainability and definitions of fairness have been extended and integrated into the agri-food chain, there is a need to understand, on a multi-dimensional and multinational level, the structure of agri-food value chain revenues and consumers’ intentions regarding necessity foods. The study analyzed 1,020 questionnaires from Algeria, Germany, Greece, Italy, and Tunisia revealing that taste prioritizes brand and packaging. Social networks, including family and friends, significantly influence the purchase of fair products. Furthermore, a choice experiment revealed the consumer preferences around attributes of the olive oil case as local, traditional, or organic, from a family or farmer association, in a glass bottle, purchased in small local shops/markets, typical and/or extensive nutritional labeling and health claims, non-relevant branding, and finally a fair price reflecting the reasonable quality of the olive oil product. Regarding the agri-food value chain, the results highlight the revenue distribution among stakeholders as unequal and unfair from consumer perceptions, with an imperative need for transparency. The study investigates in-depth the multifaceted dimensions of the fairness concept in the food market from a consumer’s perception, showing their willingness to pay for necessities based on fair pricing and sustainable practices.
Diagnosis and surgical decision-making of a 46, XX ovotesticular disorders of sex development patient: a case report
Authors: Zhao Hanxing , Chen Zhixing , Wang Baoyun , Zhang Zhenyu , Li Zhengyong
Published: December 2024

Background

Ovotesticular disorder of sex development is a rare form of disorder of sex development that manifests as ovotestis in individuals. The precise diagnosis and the choice of surgical procedures are still in conflict condition due to the rarity of the disease, diverse clinical presentations, and the lack of evidence-based medical studies on postoperative outcomes.

Case presentation

We present a 46, XX ovotesticular disorder of sex development case, aged 19, with Prader stage IV virilization who underwent feminizing genitoplasty surgery. Our surgical strategy prioritized the patient's genitourinary function restoration and cosmetic reconstruction achieved satisfactory results. We attribute the success of the treatment to the systematic diagnostic process and individualized surgical planning.

Conclusion

The purpose of this article is to provide an evaluation protocol for the ovotesticular disorder of sex development, improving the diagnostic rate and providing some fresh ideas for surgical management.
Resveratrol and β-hydroxy-β-methylbutyric acid supplementation promotes ileal development and digestive function by altering microbial community abundance and metabolites in Tibetan sheep
Authors: Gan Jiacheng , Ji Qiurong , Su Quyangangmao , Hou Shengzhen , Gui Linsheng
Published: December 2024

Introduction

The effects of resveratrol (RES) and β-hydroxy-β-methylbutyric acid (HMB) on phenotype, immunity, digestive enzyme activity and short-chain fatty acids (SCFAs) contents in ileum of Tibetan sheep were investigated.

Methods

A total of 120 two-month-old Tibetan sheep (15.5 ± 0.14 kg) were randomly allocated to 4 treatments: control group (basal diet), RES group (basal diet +1.5 g RES/d), HMB group (basal diet +1.25 g HMB/d), RES-HMB group (basal diet +1.5 g RES/d + 1.25 g HMB/d).

Results

Results indicated that dietary RES and (or) HMB supplementation significantly improved the phenotype (mucosal thickness and villus width), SCFAs concentrations, and digestive enzymes (lipase, cellulase, and α-amylase) (p < 0.05). The relative abundance of Brevibacillus, Clostridium sensu stricto 3, and Eubacterium hallii group were increased, while the abundance of Ruminococcus and Mogibacterium were decreased (p < 0.05) in the RES-HMB group. The metabolic profiling indicated an increase in the differential metabolites (DMs) including L-arginine, butanoic acid, D-mannose, and retinol were increased in the RES-HMB group (p < 0.05).

Discussion

In summary, our results suggested that RES and (or) HMB supplementation improved SCFAs concentration by up-regulating the microbial community abundance (Brevibacillus, Clostridium sensu stricto 3, and Eubacterium hallii group) and metabolism (L-arginine, butanoic acid, D-mannose, and retinol), thus contributing to ileal morphology and digestive enzyme activity. These findings may provides a novel reference for the nutritional regulation to improve the production of Tibetan sheep.
A Data-Driven Method for Predicting and Optimizing Industrial Robot Energy Consumption Under Unknown Load Conditions
Authors: Chang Qing , Yuan Tiantian , Li Haifeng , Chen Yuxiang , Wang Xuehao , Gao Sen , Ren Hongsheng , Zhao Xiangyun , Wang Lingyu
Published: December 2024

The growing diversity and number of industrial robots make energy consumption prediction and optimization increasingly essential. Current data-driven approaches, particularly those based on multi-layer perception (MLP), have shown feasibility but typically overlook the variability or unknown nature of load-related parameters in real-world applications. This paper presents a KAN-LSTM model designed to accurately predict energy consumption under unknown load conditions, alongside a particle swarm optimization (PSO) algorithm for minimizing energy use. First, an industrial robot dynamics and energy consumption model is established. Then, the KAN-LSTM model is trained on datasets from the AUBO-E5 robot, with its predictions compared to alternative network models. Finally, PSO is applied to optimize energy consumption. Experimental results indicate that the KAN-LSTM model achieves high prediction accuracy (95.7–97.1%) and offers substantial energy optimization potential (53.1–64.7%). Optimized industrial robots are particularly suitable for tasks such as picking and palletizing in the courier industry, saving operational costs and increasing the sustainability of automated systems in logistics environments.
The Inversion of Rice Leaf Pigment Content: Using the Absorption Spectrum to Optimize the Vegetation Index
Authors: Ma Longfei , Li Yuanjin , Yuan Ningge , Liu Xiaojuan , Yan Yuyan , Zhang Chaoran , Fang Shenghui , Gong Yan
Published: December 2024

The pigment content of rice leaves plays an important role in the growth and development of rice. The accurate and rapid assessment of the pigment content of leaves is of great significance for monitoring the growth status of rice. This study used the Analytical Spectra Device (ASD) FieldSpec 4 spectrometer to measure the leaf reflectance spectra of 4 rice varieties during the entire growth period under 4 nitrogen application rates and simultaneously measured the leaf pigment content. The leaf’s absorption spectra were calculated based on the physical process of spectral transmission. An examination was conducted on the variations in pigment composition among distinct rice cultivars, alongside a thorough dissection of the interrelations and distinctions between leaf reflectance spectra and absorption spectra. Based on the vegetation index proposed by previous researchers in order to invert pigment content, the absorption spectrum was used to replace the original reflectance data to optimize the vegetation index. The results showed that the chlorophyll and carotenoid contents of different rice varieties showed regular changes during the whole growth period, and that the leaf absorption spectra of different rice varieties showed more obvious differences than reflectance spectra. After replacing the reflectance of pigment absorptivity-sensitive bands (400 nm, 550 nm, 680 nm, and red-edge bands) with absorptivities that would optimize the vegetation index, the correlation between the vegetation index, which combines absorptivity and reflectivity, and the chlorophyll and carotenoid contents of 4 rice varieties during the whole growth period was significantly improved. The model’s validation results indicate that the pigment inversion model, based on the improved vegetation index using absorption spectra, outperforms the traditional vegetation index-based pigment inversion model. The results of this study demonstrate the potential application of absorption spectroscopy in the quantitative inversion of crop phenotypes.
Towards an Effective Risk Management in Durum Wheat Production: A Systematic Review and Bibliometric Analysis of Factors Influencing Quality and Yield
Authors: Chab Lamiaa , Biagini Luigi , Severini Simone
Published: December 2024

Durum wheat is essential for global food security. Nevertheless, its cultivation is susceptible to hazards, including unpredictability in yield and grain quality. This systematic review and bibliometric analysis identify factors influencing durum wheat yield and quality, assessing the degree of control farmers have over these factors. The goal is to understand their impact on production risks. Peer-reviewed studies in English from 1990 to April 2024 that focused on the yield or quality of durum wheat were included, while those lacking specific data or not peer-reviewed were excluded. Data were acquired via the Web of Science (WoS), with the concluding search conducted in April 2024. Results were synthesized from 2131 studies selected from an initial pool of 5159, using a bibliometric approach to categorize findings into standard, biotic, abiotic, and other factors. Analysis revealed that practices like irrigation and nitrogen fertilization improve yields, while genetic advancements boost stress resilience. These insights support targeted agronomic strategies. Despite potential biases and inconsistencies, the review underscores key strategies to enhance durum wheat risk management and bolster food security. This study was funded by the Italian Ministry of University and Research (CURSA, D.I.Ver.So.) and PRIN—2020 Call.
Morphological, Physiological, and Molecular Bases of Salt Tolerance in Crape Myrtle (Lagerstroemia indica)
Authors: Yu Chunmei , Ding Zuorong , Yuan Tianyi , Yu Cannan , Qin Jin , Lu Di , Wei Hui , Zhong Fei , Liu Guoyuan , Chen Yanhong , Zhang Jian
Published: December 2024

Crape myrtle (Lagerstroemia indica and its relatives) is an important summer-flowering plant in numerous countries worldwide. However, there are few reports on salt-tolerant (ST) crape myrtle germplasm resources and their morphological and molecular biological foundations for adaptation to salinized soil, one of the main abiotic stresses in plants. This study identified the salt tolerance characteristics of 19 crape myrtle varieties and created four salt-tolerant germplasms through hybridization. Morphological anatomy and transcriptome analyses clarified that the xylem of the ST variety possessed a high number of vessels with a small lumen. Transcriptome research has indicated that under salt stress conditions, Ca2+, abscisic acid (ABA), and reactive oxygen species (ROS) pathways are involved in salt stress responses. One of the candidate genes LiTIP1;1 (encoding a tonoplast intrinsic protein) was overexpressed in Arabidopsis and the resultant overexpression (OE) lines performed better under CK and 100 mmol∙L−1 NaCl salt stress, but not under 200 mmol∙L−1 NaCl salt stress. Corresponding to physiological traits, genes encoding tubulin and fasciclin-like arabinogalactan proteins (FLAs), which are related to the plasma membrane localization of the cellulose synthase complex, are maintained at higher levels and are induced more by salt. In summary, this research has revealed the morphological, physiological, and molecular bases of ST crape myrtle to a certain extent and has provided a theoretical basis for further screening and breeding of salt-tolerant crape myrtle varieties.
A Lightweight Method for Peanut Kernel Quality Detection Based on SEA-YOLOv5
Authors: Liu Zhixia , Wang Chunyu , Zhong Xilin , Shi Genhua , Zhang He , Yang Dexu , Wang Jing
Published: December 2024

Peanuts are susceptible to defects such as insect damage, breakage, germinant, and mildew, leading to varying qualities of peanuts. The disparity in peanut kernel quality results in significant differences in their prices and economic value. Conducting real-time, accurate, and non-destructive quality inspections of peanut kernels can effectively increase the utilization rate and commercial value of peanuts. Manual inspections are inefficient and subjective, while photoelectric sorting is costly and less precise. Therefore, this study proposes a peanut kernel quality detection algorithm based on an enhanced YOLO v5 model. Compared to other models, this model is practical, highly accurate, lightweight, and easy to integrate. Initially, YOLO v5s was chosen as the foundational training model through comparison. Subsequently, the original backbone network was replaced with a lightweight ShuffleNet v2 network to improve the model’s ability to differentiate features among various types of peanut kernels and reduce the parameters. The ECA (Efficient Channel Attention) mechanism was introduced into the C3 module to enhance feature extraction capabilities, thereby improving average accuracy. The CIoU loss function was replaced with the alpha-IoU loss function to boost detection accuracy. The experimental results indicated that the improved model, SEA-YOLOv5, achieved an accuracy of 98.8% with a parameter count of 0.47 M and an average detection time of 11.2 ms per image. When compared to other detection models, there was an improvement in accuracy, demonstrating the effectiveness of the proposed peanut kernel quality detection model. Furthermore, this model is suitable for deployment on resource-limited embedded devices such as mobile terminals, enabling real-time and precise detection of peanut kernel quality.
Optimizing Sampling Points and Path Planning for Soil Monitoring in Agricultural Land
Authors: Wang Jing , Zhai Zhiqiang , Xu Guangdong , Zhang Ruoyu , Zhang Xin , Hu Rong
Published: December 2024

Current soil mixing sampling surveys face several challenges. These challenges include significant variations in the size and shape of farmland plots, which complicate the sampling process. Additionally, the procedures for establishing mixing points are often cumbersome and non-standardized. Furthermore, when the number of mixing points is large and the plot area is extensive, sampling efficiency is significantly reduced. In this study, an automated method for establishing the layout of sampling points and a threshold-based mixed path planning algorithm are proposed. These approaches are designed to automatically arrange sampling points within delineated sampling units according to various sampling methods. Additionally, real-time path planning is conducted on the basis of the initial position of the sampling vehicle. The experimental results indicate that the maximum relative error in estimating farmland area is 0.22%, which is less than 666.67 m2. The average deviation between the locations of the sampling points generated by the sampling point layout algorithm and those established via related software is 0.0336 m. Furthermore, the threshold-based hybrid algorithm consistently yields optimal or near-optimal paths while reducing the path planning time, with an average duration of 1.0783 s for path planning. This study provides reliable technical support for standardizing the sampling point layout and enhancing the soil sampling efficiency.
Nutritional Value of Nannochloropsis oceanica for Weaner Piglets
Authors: Chaves Andreia A. M. , Ribeiro David M. , Martins Cátia F. , Fernandes Tatiane , Maia Margarida R. G. , Fonseca António J. M. , Cabrita Ana R. J. , Alves Susana P. , Pinho Mário , Bessa Rui J. B. , de Almeida André M. , Freire João P. B.
Published: December 2024

This study evaluates the nutritional value of spray-dried Nannochloropsis oceanica biomass to infer its applicability for weaner piglet feeding. Twenty-four piglets were randomly allocated to four dietary treatments (n = 6) with increasing N. oceanica inclusion (0, 5, 10, and 15%) levels. After a 4-day adaptation period, the digestibility experiment lasted two weeks, with daily excreta collection. Total tract apparent digestibility (TTAD), N balance, intestinal pH, histomorphology, and volatile fatty acid (VFA) concentrations were measured. No significant differences were observed in feed intake, growth, or intestinal morphology (p > 0.05). N intake increased linearly (p = 0.005) with N. oceanica inclusion, while N retention efficiency remained unchanged (p = 0.058). VFA concentrations decreased linearly (p < 0.001). The TTAD of dry matter (DM), organic matter, ether extract, and gross energy decreased (p < 0.05) with higher N. oceanica levels, while the ash TTAD increased (p < 0.001). The estimated TTAD values for N. oceanica biomass were 72.5% for DM, 82.9% for N, and 64.4% for gross energy. The digestible energy, metabolisable energy, and digestible crude protein values estimated for N. oceanica were 12.74 MJ/kg DM, 12.40 MJ/kg DM, and 20.4% DM, respectively. This information enabled the first nutritional characterisation of N. oceanica for weaner piglets, ultimately leveraging its use in piglet diet formulation.
Comparative Analysis of Muscle Fibers in Selected Muscles of Working and Companion Dog Breeds
Authors: Osiak-Wicha Cezary , Kras Katarzyna , Arciszewski Marcin B.
Published: December 2024

The structural and functional characteristics of skeletal muscle fibers play a crucial role in understanding the physical capabilities of dogs, particularly in relation to their breed-specific roles. This study aimed to compare the muscle fiber composition of working and companion dog breeds by analyzing the triceps brachii and biceps femoris muscles, focusing on fiber morphology, myosin heavy chain (MYH) isoform distribution, and nuclei per fiber. A total of 12 dogs, divided equally into working and companion breed groups, were used in this study. Muscle samples were collected post-mortem and prepared for histological analysis using cryosectioning. Immunohistochemical staining was employed to identify the expression of MYH isoforms, including MYH2, MYH4, and MYH7, which correspond to type IIa, IIb, and type I fibers, respectively. The results demonstrated significant differences between the two breed groups. Working dogs exhibited larger muscle fibers, a higher proportion of type IIa (MYH2) and type I (MYH7) fibers, and a greater number of nuclei per fiber, suggesting adaptations for endurance and strength. In contrast, companion dogs showed a higher proportion of type IIb (MYH4) fibers, indicative of their capacity for short bursts of activity rather than sustained exertion. Companion breeds also displayed a higher fiber density but fewer nuclei per fiber, which may contribute to slower muscle regeneration. These findings may provide insights into the muscle adaptations of dogs based on their breed-specific functional demands and highlight the importance of considering these differences in veterinary care and rehabilitation. The study underscores the influence of selective breeding on muscle structure and function in dogs and suggests further research into breed-specific muscle recovery mechanisms.
Effects of Dietary Medium-Chain Triglyceride Supplementation on the Serum Metabolome of Young Adult and Senior Canines
Authors: Pan Yuanlong , Sindelar Miriam , Stancliffe Ethan , Shriver Leah P. , Middleton Rondo P. , Patti Gary J.
Published: December 2024

In dogs, brain aging may lead to cognitive decline and cognitive dysfunction syndrome (CDS) [...]
Active Vibration Control of a Cantilever Beam Structure Using Pure Deep Learning and PID with Deep Learning-Based Tuning
Authors: Saif Abdul-Wahid A. , Mohammed Ahmed Abdulrahman , AlSunni Fouad , El Ferik Sami
Published: December 2024

Vibration is a major problem that can cause structures to wear out prematurely and even fail. Smart structures are a promising solution to this problem because they can be equipped with actuators, sensors, and controllers to reduce or eliminate vibration. The primary objective of this paper is to explore and compare two deep learning-based approaches for vibration control in cantilever beams. The first approach involves the direct application of deep learning techniques, specifically multi-layer neural networks and RNNs, to control the beam’s dynamic behavior. The second approach integrates deep learning into the tuning process of a PID controller, optimizing its parameters for improved control performance. To activate the structure, two different input signals are used, an impulse signal at time zero and a random one. Through this comparative analysis, the paper aims to evaluate the effectiveness, strengths, and limitations of each method, offering insights into their potential applications in the field of smart structure control.
The Use of Some Natural Extracts as Environmentally Friendly Carbon Steel Corrosion Inhibitors
Authors: Ciobotaru Ioana-Alina , Mic Oana Camelia , Vaireanu Danut-Ionel
Published: December 2024

This paper presents the influence of natural extracts obtained from Levisticum officinale and Citrus x clementine on the corrosion of carbon steel in a 3.5% NaCl solution. We started from dried leaves of Levisticum officinale and Citrus x clementine peel in order to prepare several extracts in a 50%:50% (v:v) water/ethanol solution and in analytical-grade ethanol. Several electrochemical techniques, such as open circuit potential monitoring, electrochemical impedance spectroscopy and potentiodynamic polarization, were employed in order to investigate the influence of the synthetized extracts on the corrosion of carbon steel. The aggressive solution that the corrosion tests were performed in was a 3.5% NaCl solution modified with different amounts of the extracts. The electrochemical tests performed in order to determine the influence of the Levisticum officinale leaf and Citrus x clementine peel extracts showed that these extracts may be employed as natural corrosion inhibitors for carbon steel in a 3.5% NaCl solution, achieving inhibiting efficiencies up to 87.8%, in the case of the Levisticum officinale extracts.
An Enhanced Retrieval Scheme for a Large Language Model with a Joint Strategy of Probabilistic Relevance and Semantic Association in the Vertical Domain
Authors: Chen Qi , Zhou Weifeng , Cheng Jian , Yang Ji
Published: December 2024

Large language model (LLM) processing, with natural language as its core, carries out information retrieval through intelligent Q&A. It has a wide range of application scenarios and is commonly considered a kind of generative AI. However, when LLMs handle generation tasks, the results generated by fundamental LLMs with an insufficient comprehensive performance, specifically in the vertical domain, are often inaccurate due to a poor generalization ability, resulting in the so-called “hallucination” phenomenon. To solve these problems, in this study, an enhanced retrieval scheme for LLM processing was developed, named the BM-RAGAM (BM25 retrieval-augmented generation attention mechanism), by constructing a vectorized knowledge base, utilizing a hybrid joint retrieval strategy of keyword matching through searching and a semantic-enhanced association with an attention mechanism and taking ocean-front- and eddy-related knowledge in oceanography as an example. This scheme realized accurate word-based matching with the BM25 algorithm and text generation through a semantic-enhanced association using RAG, and it was used to construct a vector database of the text knowledge on ocean fronts and eddies. The output was compared and analyzed with the fundamental LLM of Qwen2-72B using the proposed scheme, and an ablation experiment was conducted. The results show that the proposed scheme greatly reduced hallucination generation in the process of text generation, making its outputs more interpretable.
Comparative Study on Fire Resistance of Different Thermal Insulation Materials for Electric Vehicle Tunnel Fire
Authors: Li Xiaojun , Cheng Yuanwei
Published: December 2024

With the growing prevalence of lithium battery electric vehicles, the incidence of fires resulting from thermal runaway in lithium batteries is also on the rise. In contrast to conventional fuel vehicle fires, fires involving lithium battery electric vehicles exhibit distinct differences in fire dynamics, fire loads, and smoke characteristics. These variations impose more stringent requirements on the design of passive fire protection systems within tunnels. To evaluate the fire resistance performance of existing passive fire protection systems under electric vehicle fire conditions, this study first used PyroSim software 2022 (integrating FDS 6.7.9) to establish fire models for combustion engine trucks and electric trucks, comparing the combustion characteristics of both types of fires without insulation lining materials. Based on the electric truck fire model, different insulation lining materials were added. The analysis of the simulation results focused on the impact of the thermal conductivity and emissivity of each lining material on peak tunnel temperatures, aiming to identify the insulation lining material with the best fire resistance performance. The results indicate that the heat release rate, temperature distribution, toxic gas concentration, and smoke propagation of lithium battery combustion engine truck fires are all higher than those of combustion engine truck fires. Among the five insulation lining materials studied, SiO2 gel material demonstrated superior fire resistance compared to the others. This research provides a scientific and rational basis for tunnel fire protection design and fire response strategies, aiming to mitigate the damage caused by lithium battery electric vehicle fires to tunnel lining structures.